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https://f1000research.com/articles/5-775/v1
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28 Apr 16
|
{
"type": "Review",
"title": "Current techniques for visualizing RNA in cells",
"authors": [
"Lilith V.J.C. Mannack",
"Sebastian Eising",
"Andrea Rentmeister",
"Lilith V.J.C. Mannack",
"Sebastian Eising"
],
"abstract": "Labeling RNA is of utmost interest, particularly in living cells, and thus RNA imaging is an emerging field. There are numerous methods relying on different concepts ranging from hybridization-based probes, over RNA-binding proteins to chemo-enzymatic modification of RNA. These methods have different benefits and limitations. This review aims to outline the current state-of-the-art techniques and point out their benefits and limitations.",
"keywords": [
"RNA",
"visualization",
"imaging",
"proteins"
],
"content": "Introduction\n\nThe localization of mRNA in the cell has been a topic of interest since the 1980s, when protein localization was linked to localized mRNA translation1. At that time, the only method by which RNA could be visualized was in situ hybridization (ISH)2. Since then, the options for RNA detection have expanded greatly. Labeling RNA—particularly mRNA—is of utmost interest, as mRNA localization has been shown to be important in a range of situations. For example, in a developing Drosophila oocyte, asymmetrically localized mRNA produces a bicoid protein gradient through localized translation, which specifies the anterior-posterior polarity of the developing larva3. In neurons, localization of mRNA is also particularly important, and localized mRNA leads to multiple rounds of translation at the synapse and activity-dependent changes4. Additionally, since the number of genes transcribed was found to surpass the amount of protein-coding genes, interest in non-coding RNAs has increased5. Thus, imaging microRNAs or small interfering RNAs (siRNAs) is also of interest6. Furthermore, defects in mRNA localization play an important role in some diseases such as fragile X syndrome7, and non-coding RNAs have been shown to be important in diseases such as cancers8.\n\n\nHybridization methods\n\nISH is used to visualize RNA containing a known sequence. A DNA or RNA strand of complementary sequence hybridizes to the RNA strand of interest via Watson-Crick base pairing. The probe bears features that enable its visualization (e.g., a fluorophore; Figure 1A). Fluorescence in situ hybridization (FISH) can distinguish between RNA molecules that differ in only a single base9. FISH is highly sequence-specific, and individual RNA strands may be detected when combined with various amplification procedures in fixed cells9,10. A variety of derivatives of ISH that reduce background signal have been developed, most notably molecular beacons (Figure 1B). Molecular beacons consist of a DNA probe that is linked to a fluorophore at one end and a quencher at the opposite end. When unbound, the probe folds into a hairpin structure, bringing the fluorophore and quencher together, thereby inhibiting fluorescence. Upon target recognition, the probe anneals and stretches out, separating the quencher from the fluorophore and enabling fluorescence11. Molecular beacons have been advanced further since the 1990s. For example, the types of quencher used have been expanded to include nanoparticles12. Microinjected molecular beacons can mislocalize to the nucleus in live cells; however, incorporating a tRNA sequence was shown to abrogate this problem13.\n\n(A) Standard fluorescence in situ hybridization (FISH): a fluorophore-linked RNA probe binds the target RNA sequence. (B) Molecular beacon: signal to noise is improved relative to a standard FISH probe because the fluorescence signal of the reporter probe is quenched when unbound. (C) Forced intercalation (FIT) probes: binding enforces intercalation of the dye molecule into the probe-target duplex, resulting in a strong turn-on effect of the fluorophore.\n\nAn alternative approach to increase the specific fluorescent signal upon binding is to use forced intercalation (FIT) probes (Figure 1C). FIT probes are peptide nucleic acid (PNA) or DNA single strands containing a base surrogate (typically, thiazole orange) that intercalates between the Watson-Crick base pairs and fluoresces only upon exact hybridization14,15. Their strong turn-on effect (~30-fold) makes FIT probes an attractive improvement of ISH. FIT probes have been expanded to contain dyes that emit in the blue and green ranges16,17 and have been successfully used for mRNA visualization in cells and Drosophila embryos14,18.\n\nHybridization-based RNA detection is an excellent tool for use in fixed samples and can be used in living cells and organisms when strong turn-on effects are achieved (e.g., molecular beacons and FIT probes). However, probes based on modified nucleic acids or derivatives thereof are neither cell-permeable nor can they be produced by the cell itself. Furthermore, hybridization has to occur in regions of the target RNA free of secondary structure, and hybridization conditions are typically not optimized for the cellular milieu. Recently, probes and conditions have started to be developed for use in live cells; this approach is termed fluorescence in vivo hybridization (FIVH)19–21. In particular, 2′-O-methylated oligonucleotides exhibit faster hybridization kinetics, increased melting temperatures, enhanced binding specificity, improved nuclease stability, and the ability to bind structured molecules—properties beneficial for FIVH probes20. They were used to detect a variety of RNA types, such as snRNAs, rRNA, and poly(A) RNA20. Nevertheless, these probes need to be introduced into the cells and thus FIVH requires transient permeabilization of cells.\n\n\nAptamers\n\nRNA aptamers are another form of nucleotide-based probe but work on a different principle to the above mentioned hybridization probes. Aptamers are short, single-stranded oligonucleotides capable of binding specific target molecules based on their shape and can be obtained by in vitro selection22. Recently, an aptamer termed “Spinach” was selected that folds to allow binding of a small-molecule fluorophore that fluoresces only upon binding the RNA aptamer (Figure 2C)23. Herein, the reporter and probe are contained within the same oligonucleotide. The aptamer sequence can be appended to the RNA of interest to enable visualization of that RNA upon binding of the fluorophore23. RNA aptamers in conjunction with said small fluorophore are available in a range of colors from blue to red23 and have been improved to further enhance binding efficiency and fluorescence strength24. Additionally, the folding properties have been optimized for the cellular milieu25,26. A downside of RNA aptamers is the potential impediment in localization or function of some RNAs by the “Spinach” RNA tag.\n\n(A) A green fluorescent protein-fused-MS2 coat protein (GFP-MCP) binds a consensus sequence (MS2) appended to the RNA of interest. (B) Two pumilio variants fused to different halves of split-GFP recognize a target sequence within an RNA molecule of interest. (C) The aptamer “Spinach” folds to bind a turn-on fluorophore and can be appended to an RNA of interest.\n\n\nParticle-associated hybridization-based imaging probes\n\nThe group of Mirkin describe a nanoparticle conjugated spherical nucleic acid that recognizes specific RNA targets and is capable of entering the cell without the need for transfection27,28. However, there is considerable controversy surrounding this study, mainly concerning whether these sticky- or nano-flares mark specific RNAs or merely remain in endosomes after uptake by the cell29. Gold nanoparticles bound to quantum dots via hybridizing DNA strands have been developed to detect specific microRNA30. The microRNA triggers the dissociation of the quantum dots from the gold particle, resulting in the abrogation of quenching and thus a signal. These gold nanoparticle-quantum dot-probes bind target RNA quantitatively in vitro, and cell lines expressing a certain microRNA can be distinguished from cell lines that do not.\n\n\nCovalent modification of RNA in cells\n\nAn alternative method to mark RNA is to incorporate visualizable moieties directly into the RNA. A convenient way to achieve marking RNA without introducing a large moiety that may interfere with RNA function is to incorporate a small chemical group that may be further reacted by using click chemistry to attach to a fluorophore. There are a number of different click reactions, the most prominent being the copper(I)-catalyzed azide alkyne cycloaddition (CuAAC). Here, an azide reacts with an alkyne in the presence of Cu(I) as a catalyst. CuAAC is rapid and extremely selective; however, Cu(I) at millimolar concentrations is toxic to cells and thus this approach is limited to fixed cell samples. Jao and Salic succeeded in incorporating ethynyl groups into total RNA by feeding cells with the uridine analog 5-ethynyluridine (EU), which is converted to the respective triphosphate inside the cell (Figure 3A)31. Using a similar approach—feeding cells with N6-propargyl adenosine—the poly(A) dynamics of mRNA could be monitored32.\n\nThere are also a number of copper-free click reactions, which are more suitable for live-cell imaging, termed bioorthogonal click reactions (reviewed in 33). Sawant et al. synthesized an azido-modified UTP analog that can be used in the bioorthogonal strain-promoted azide-alkyne cycloaddition (SPAAC)34. This allowed the click reaction to proceed in live cells; however, this UTP analog had to be transfected into the cells as its uridine precursor was no longer cell-permeable or was not a good substrate for the ribonucleoside salvage pathway (Figure 3A).\n\n(A) Incorporation of modified nucleotides into nascent RNA by endogenous RNA polymerases. Ethynyluridine is cell-permeable, and the respective triphosphate is made inside the cell; hence, feeding the cell with the nucleoside precursor is possible. In other examples (azido-U), the cells have to be transfected with the respective triphosphates. (B) Hallmarks of RNA subtypes, such as the 5′ cap, can be selectively modified. A methyltransferase (MTase) variant can be used to modify the mRNA cap with the clickable group if the respective S-adenosylmethionine (AdoMet) analog is provided. (C) Transcript-specific installation of a click reactive moiety can be achieved by appending a tRNA-mimicking sequence to the RNA of interest. The enzyme tRNAIle2-agmatidine synthetase (Tias) modifies the tag with a clickable group if appropriate agmatine analogs are provided.\n\nA downside of incorporating modified nucleotides during transcription or poly(A) tail addition is that different subtypes of RNA cannot be distinguished. A possible method by which to obtain specific labeling of different subtypes is to attach chemical groups used for click reactions post-synthetically by using RNA-modifying enzymes. Subtypes of RNA may also be labeled by taking advantage of certain structures or modifications in an RNA type. For example, the 5′ cap of mRNA may be specifically labeled by using an engineered methyltransferase that is only active on the mRNA cap (Figure 3B)35–37. This approach should be suitable in live cells because the S-adenosylmethionine (AdoMet) analog can be made from cell-permeable and stable methionine analogs by a variant of the methionine adenosyltransferase (MAT), which is responsible for AdoMet synthesis37.\n\nSequence-specific RNA-modification with a propargyl group and subsequent labeling with a fluorophore have been achieved in vitro by using a box C/D methyltransferase-guide RNA complex and the respective propargyl-bearing analog of the cosubstrate AdoMet38. Li et al. developed an RNA labeling system in which an RNA of interest was extended by a tRNA-derived sequence and an enzyme that specifically modifies this sequence (tRNAIle2-agmatidine synthetase, or Tias) was introduced into a cell (Figure 3C)39. This RNA-Tias combination can also accept agmatine analogs that are click-reactive and thus can be used to label RNA in cells39. Similarly, a tRNA-derived recognition motif may be specifically marked by using an engineered transglycosylase that is able to transfer large visualizable groups40.\n\n\nRNA-binding proteins\n\nA number of bacteriophage-derived RNA-binding proteins have been used to mark RNA in cells. The most notable of these is the MS2-MS2 coat protein (MS2-MCP) system (Figure 2A). This comprises a green fluorescent protein (GFP)-fused version of the bacteriophage MCP (an RNA-binding protein that recognizes a specific RNA sequence-determined hairpin) and the RNA of interest extended by multiple MS2-binding sites (MBS)41. Recently, the MS2 system has been used to image single mRNA molecules in living mouse cells42. This study displays both the power and drawback of this method. On the one hand, the MS2 system allows tracking and resolution of single mRNA molecules; on the other, producing a transgenic organism is very time-consuming. Another drawback is that the size of the MS2-fusion tag and the appendages to the RNA might interfere with normal mRNA function or localization43,44. Furthermore, the quantity of MS2 used must be sufficient to saturate the target RNA without raising background fluorescence, which may be difficult to achieve45.\n\nAnother RNA-binding protein worth mentioning is pumilio. Pumilio is a member of the RNA-binding protein family PUF46. Like many RNA-binding proteins, pumilio is modularly composed of domains that can be engineered to alter the specific RNA sequence bound47–49. Pumilio is of particular interest as it can target RNA directly without the need to introduce an RNA tag into the target RNA.\n\nAn advantage of using RNA-binding proteins to visualize RNA is that two individual RNA sequences may be targeted by separate RNA-binding proteins, thus allowing the imaging of the association of two RNA molecules of interest50,51. The potential drawback of high background fluorescence due to unbound protein may be countered by using a split GFP, which fluoresces only upon dimerization (Figure 2B)52,53.\n\n\nReporter protein expression by trans-splicing to visualize RNA\n\nTwo approaches have been developed by which a pre-mRNA may be spliced into a functional form, which allows the expression of a reporter protein. This enables tissue-specific localization of an mRNA of interest, although the resolution at a subcellular level is lost. Bhaumik et al. described a method based on trans-splicing that results in the expression of luciferase in cells of a living organism microinjected with an exogenous RNA that was processed to pre-mRNA54. So et al., employing a similar approach, developed an engineered ribozyme, which fuses a reporter gene to a specific gene of interest55. The authors were able to detect p53 in a whole organism and on a cellular level. Despite theoretical expansion potential56, the approach taken by the Gambhir lab has not been significantly developed since the publication of the original study, leaving it with the limitation that only exogenous RNA can be visualized. Similarly, the work of So et al. has not been further developed.\n\n\nConclusions: current applications and outlook\n\nImaging of RNA is of interest at the level of both single cells and the whole organism. Labeling RNA in a single cell can show the localization of a specific transcript, which may have important biological consequences57. RNA imaging at the whole organism level is important to determine the tissue expression pattern of a specific transcript. RNA labeling has seen extensive use in imaging of infection by RNA viruses (e.g., 58). Another interesting application of RNA imaging has been to monitor transcription and this has been used, for example, to determine the toxicity of certain substances that inhibit transcription59.\n\nIn summary, RNA may be visualized by a variety of methods. RNA may be seen via hybridization of a reporter molecule, most commonly through FISH or variations thereof. Alternatively, RNA-binding proteins that bind specific sequences may mark an RNA molecule of interest, or an RNA aptamer that fluoresces upon binding of a fluorophore may be incorporated into the target molecule. RNA may be sequence- or subtype-specifically labeled by using click chemistry. Challenges facing the field of RNA imaging are the cell permeability of dyes used and the low abundance of target RNA. Furthermore, no method of RNA labeling is yet able to yield quantitative data on its target RNA. However, with continued development, RNA imaging will continue to provide important biological insights.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nOur work is supported by the Deutsche Forschungsgemeinschaft (RE 2796/2-1 and EXC 1003 Cells in Motion – Cluster of Excellence, Münster, Germany). Andrea Rentmeister gratefully acknowledges the Fonds der Chemischen Industrie for a “Dozentenstipendium”.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nLehmann R, Nüsslein-Volhard C: Abdominal segmentation, pole cell formation, and embryonic polarity require the localized activity of oskar, a maternal gene in Drosophila. Cell. 1986; 47(1): 141–52. PubMed Abstract | Publisher Full Text\n\nWeil TT, Parton RM, Davis I: Making the message clear: visualizing mRNA localization. Trends Cell Biol. 2010; 20(7): 380–90. 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}
|
[
{
"id": "13638",
"date": "28 Apr 2016",
"name": "Seergazhi G. Srivatsan",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13639",
"date": "28 Apr 2016",
"name": "Jiangyun Wang",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-775
|
https://f1000research.com/articles/5-591/v1
|
06 Apr 16
|
{
"type": "Research Article",
"title": "Activity-relevant similarity values for fingerprints and implications for similarity searching",
"authors": [
"Swarit Jasial",
"Ye Hu",
"Martin Vogt",
"Jürgen Bajorath",
"Swarit Jasial",
"Ye Hu",
"Martin Vogt"
],
"abstract": "A largely unsolved problem in chemoinformatics is the issue of how calculated compound similarity relates to activity similarity, which is central to many applications. In general, activity relationships are predicted from calculated similarity values. However, there is no solid scientific foundation to bridge between calculated molecular and observed activity similarity. Accordingly, the success rate of identifying new active compounds by similarity searching is limited. Although various attempts have been made to establish relationships between calculated fingerprint similarity values and biological activities, none of these has yielded generally applicable rules for similarity searching. In this study, we have addressed the question of molecular versus activity similarity in a more fundamental way. First, we have evaluated if activity-relevant similarity value ranges could in principle be identified for standard fingerprints and distinguished from similarity resulting from random compound comparisons. Then, we have analyzed if activity-relevant similarity values could be used to guide typical similarity search calculations aiming to identify active compounds in databases. It was found that activity-relevant similarity values can be identified as a characteristic feature of fingerprints. However, it was also shown that such values cannot be reliably used as thresholds for practical similarity search calculations. In addition, the analysis presented herein helped to rationalize differences in fingerprint search performance.",
"keywords": [
"Bioactive compounds",
"molecular similarity",
"similarity-property principle",
"similarity searching",
"fingerprints",
"Tanimoto coefficient",
"activity similarity"
],
"content": "Introduction\n\nCalculation of molecular similarity is a central task in chemoinformatics1–4 for which a variety of methods, chemical descriptors, and similarity measures have been introduced1–7. A key aspect of the molecular similarity concept is that one often attempts to extrapolate from calculated similarity to activity similarity. In other words, it is assumed that increasing chemical similarity correlates with an increasing likelihood that two compounds share the same activity, in accord with the similarity-property principle (“similar compounds should have similar properties”)1; a major foundation of chemoinformatics. A methodological consequence of the molecular similarity concept and similarity-property principle was the introduction of similarity searching for active compounds2,6. Here, similarity values are calculated for known active reference and database compounds, which are then ranked in the order of decreasing similarity to the reference(s). Classical molecular descriptors for these search calculations include 2D-fingerprints, i.e. bit string representations of chemical structures and/or properties derived from molecular graphs2,8,9. The overlap between fingerprints is quantified as a measure of molecular similarity using metrics such as the Tanimoto coefficient (Tc)2,7; the gold standard in the chemoinformatics field. For a pair of compounds represented by fingerprints, its Tc value is calculated as the ratio between the number of features conserved in both fingerprints and the number of features present in either fingerprint. Accordingly, the Tc is a numerical measure of similarity ranging from zero (no fingerprint overlap) to one (fingerprint identity).\n\nSimilarity search calculations exemplify the similarity conundrum in chemoinformatics: the ultimate goal is the identification of new active compounds on the basis of similarity, but activity information is not used as a search parameter. It has been shown that generally applicable Tc threshold values as an indicator of activity similarity do not exist9. This is the case because similarity value distributions are compound class- and fingerprint-dependent. To further complicate matters, it has also been shown that 2D-fingerprints successfully detect structurally diverse active compounds at varying similarity levels9,10. In general, a continuum of similarity values is produced that may or may not indicate activity similarity, depending on the characteristics of active compounds.\n\nA limited number of attempts have been made to associate calculated similarity with observed activity similarity. For example, early investigations of compound clustering, molecular diversity, and chemical neighborhood behavior using fingerprints have indicated that, on average, 85% of compounds that yielded a Tc value of 0.85 compared to a known active molecule were also active11–13. These findings were based on MACCS keys14, a classical fingerprint in chemoinformatics consisting of a dictionary of 166 structural fragments, as well as UNITY fingerprints13 that assemble atom pathways of pre-defined lengths. However, using connectivity pathway fingerprints of different design and biological screening data to analyze the relationship between calculated similarity and observed activity similarity, it was concluded that there was only a likelihood of 30% that compounds yielding a Tc value of at least 0.85 shared the same activity15. In addition, Kullback-Leibler divergence analysis from information theory and Bayesian modeling were combined16 to predict the recall of active compounds from fingerprint similarity searching and a conditional correlated Bernoulli model of similarity value distributions was developed17 to predict database rankings. Furthermore, belief theory was applied to empirically derive probabilistic relationships between calculated similarity and activity on the basis of similarity search benchmark calculations18. In this study, MACCS keys and extended connectivity fingerprints (ECFPs)19 were used, among others. ECFPs capture layered atom environments in compounds up to a pre-determined bond diameter. When different fingerprints were compared in benchmark calculations ECFPs often yielded highest similarity search performance8,9. On the basis of probability assignment curves that related activity and similarity values for pairs of compounds to each other, it was shown, for example, that at a Tc value of 0.85 calculated with atom pathway fingerprints, ~30% of detected compound pairs shared the same activity18, consistent with earlier observations15. For an ECFP with bond diameter 6 (ECFP6), a Tc threshold of 0.42 yielded comparable results18.\n\nOther types of fingerprints were generated exclusively on the basis of experimental activity observations, e.g. activities measured in panels of screening assays20, or by combining chemical and biological criteria21. These studies departed from the conceptual framework of the similarity-property principle by using activity data as descriptors and -completely or partly- circumventing similarity calculations on the basis of molecular structures.\n\nHerein, we report an analysis designed to rationalize similarity searching on the basis of different molecular comparisons, carried out on a large scale, and determine similarity values across different compound activity classes. It is shown that similarity value ranges indicative of activity can be identified for different fingerprints. However, it is also shown that such similarity values cannot be reliably used as thresholds for similarity searching, given the ratio of different molecular comparisons that are involved.\n\n\nMaterials and methods\n\nIn a previous large-scale similarity search analysis of the ChEMBL database22, a variety of activity classes were identified for benchmarking that were “easy” (i.e. yielded generally high compound recall using different fingerprints), “preferred/intermediate” (moderate compound recall), or “difficult” (low compound recall)23. For our analysis, we have made use of this classification scheme and extracted these activity classes from ChEMBL version 20 if they contained at least 50 compounds with high-confidence assay data for human targets24 and a potency of at least 10 µM. In addition, a random sample of 10,000 compounds was drawn from ZINC25 representing assumed inactive database compounds. All randomly selected (“random”) compounds had a molecular weight of less than 550 Da. Accordingly, all compounds with a molecular weight exceeding 550 Da were also removed from activity classes, thus balancing the potential of molecular size effects in similarity searching26.\n\nOn the basis of these criteria, 22 easy, 50 intermediate, and 30 difficult activity classes were obtained covering a wide range of targets. Easy activity classes contained a total of 2967 compounds with, on average, 135 compounds per target; intermediate activity classes contained 25,175 compounds with a mean of 504 per target, and difficult activity classes 47,109 compounds with a mean of 1570 per target. The molecular weight distributions of compounds from all categories are reported in Figure 1. Compounds from ZINC had overall slightly lower weight than active compounds but the distributions of molecular weights of from different activity class categories were very similar.\n\nDensity plots report the molecular weight (Da) distributions of compounds in all categories.\n\nTwo standard fingerprints of different design were used including MACCS and ECFP with bond diameter 4 (ECFP4). As a similarity metric, the Tc was calculated.\n\nSystematic pairwise similarity calculations were carried out for all individual activity classes (active vs. active), the random category (random vs. random), and active vs. random compounds.\n\n\nResults and discussion\n\nDuring similarity searching, active reference compounds are compared to inactive database compounds or desired compounds having the same activity (“hits”). Thus, similarity searching can be mimicked by systematically comparing active compounds having the same activity with each other and active compounds to random database compounds. Comparison of random database compounds with each other is not carried out during traditional similarity searching, but the similarity value distribution resulting from this comparison can be monitored as an additional reference.\n\nFigure 2 shows the distribution of Tc values from active vs. active, random vs. active, and random vs. random compound comparisons using MACCS and ECFP4. For this comparison, Tc values obtained for all activity classes were combined. Thus, the resulting distribution represented ~55 million Tc values for compounds active against 102 targets. Comparison of ZINC compounds yielded 50 million Tc values. Their distribution was regarded to represent global chemical similarity (although many ZINC compounds are considered “drug-like”) and thus termed “chemical similarity distribution”.\n\nDensity plots of Tc values are shown for similarity comparison using (a) MACCS and (b) ECFP4. Compared were active compounds in each activity class (Act vs Act, purple), 10,000 random ZINC compounds with each activity class (Rand vs Act, maroon), and 10,000 random compounds (Rand vs Rand, green). Similarity values of all 102 activity classes were combined. Dashed vertical lines indicate the means of the distributions.\n\nFigure 2a shows that global similarity values calculated using MACCS yielded a normal distribution, given its very large sample size, which was centered on a MACCS Tc value of 0.4. The comparison of random vs. active compounds using MACCS, resulting in a total of ~753 million Tc values, 50 million of which were randomly sampled for the generation of density plots, produced a nearly identical normal distribution, also reflecting randomness. By contrast, the distribution of Tc values from active compounds, albeit significantly overlapping with the reference distributions, was shifted to the right, centered on a MACCS Tc value of 0.47. This distribution was regarded to represent activity-relevant similarity, given that it originated from more than 100 qualifying activity classes.\n\nFigure 2b shows that calculations using ECFP4 produced very different Tc value distributions. Compared to MACCS, ECFP4 Tc value distributions were shifted towards much lower Tc values and confined to small value ranges mostly falling within the interval [0.0, 0.2] (which should be known to similarity search practitioners). The chemical similarity distribution and random vs. active distribution were centered on an ECFP4 Tc value of 0.11. Also in this case, a slight shift of the activity-relevant distribution towards higher values was observed, centered on an ECFP4 Tc of 0.15. Hence, for both ZINC and ChEMBL compounds, ECFP4 calculations mostly covered only small Tc value ranges.\n\nFigure 3 shows corresponding Tc value distributions that were separately generated for easy, intermediate, and difficult activity classes. Comparison of these value distributions nicely correlated with the different similarity search performance observed for these activity classes.\n\nDensity plots of Tc values are shown for similarity comparison using (a) MACCS and (b) ECFP4 according to Figure 2. In this case, Tc value distributions were separately recorded for each activity class category (easy, intermediate, and difficult). In addition, easy activity classes were compared to a reduced random set of 1000 ZINC compounds (reported in the upper right panels).\n\nIn Figure 3a, the chemical similarity and random vs. active distributions were again essentially identical and centered on a MACCS Tc value of 0.4, although the sample sizes of active compounds were smaller in this case. The random vs. active distribution did not change when the random sample was reduced in size from 10,000 to 1000 ZINC compounds, indicating that the distribution was stable. Equivalent observations were made for the distributions of ECFP4 values shown in Figure 3b.\n\nHowever, for both MACCS and ECFP4, gradual shifts in the distributions of Tc values for different activity class categories were observed. From difficult over intermediate to easy activity classes, the activity-relevant distributions shifted towards higher Tc values. Thus, corresponding to increasing similarity search performance, the comparison of active compounds produced higher Tc values than random vs. active comparisons, leading to an enrichment of active compounds at higher positions in similarity-based rankings. For easy activity classes, the shape of the distributions departed from normal distributions and became multi-modal, probably reflecting activity class-dependent differences in Tc values. These distributions displayed a significant shift towards higher Tc values with a mean of 0.6 and 0.28 for MACCS and ECFP4, respectively.\n\nComparison of the distributions in Figure 3 made it possible to delineate activity-relevant similarity value ranges. In Figure 3a, the chemical similarity and random vs. active distributions for MACCS matched the baseline at a value of ~0.8, whereas a significant proportion of Tc values of 0.8 or greater were observed for comparisons of active compounds, especially for easy activity classes. Equivalent observations were made for an ECFP4 Tc value of ~0.3 shown in Figure 3b. Thus, for MACCS and ECFP4, there was a much higher probability that comparison of active compounds yielded a Tc value of at least 0.8 and 0.3, respectively, than comparison of active vs. random (or random vs. random) compounds. Figure 4 reports for all activity class categories the percentages of Tc values of at least 0.8 (MACCS, Figure 4a) and 0.3 (ECFP4, Figure 4b). These percentages significantly increased for difficult over intermediate to easy activity classes, (again mirroring similarity search performance), reaching medians of 17.7% (MACCS) and 37.5% (ECFP4), with a significant spread of percentages among easy activity classes, as revealed by the box plot representations in Figure 4.\n\nBox plots report the distribution of the percentage of Tc values falling into activity-relevant ranges for each category of activity classes using (a) MACCS and (b) ECFP4. A box plot gives the minimum percentage of Tc values in the activity-relevant range per category (bottom line), first quartile (lower boundary of the box), median value (thick line), third quartile (upper boundary of the box), and highest percentage of Tc values (top line).\n\nTaken together, these findings show that it was possible to detect activity-relevant Tc value ranges for different fingerprints by systematically comparing Tc value distributions for active and randomly selected compounds.\n\nA key question was whether activity-relevant similarity values might also serve as threshold values for similarity searching, contrary to the conclusions drawn from earlier studies analyzing compound recall rates and rankings. In this context, the ratio of different compound comparisons involved in similarity search calculations must be considered, as discussed below. The activity-relevant Tc value ranges of ≥ 0.8 (MACCS) and ≥ 0.3 (ECFP4) derived from comparison of similarity value distributions are plausible likelihood estimates, as further supported by the data in Table 1. For example, for easy activity classes, 16% of MACCS Tc values for comparison of active compounds reached or exceeded 0.8, whereas this was only the case for 0.005% of random vs. active comparisons. For ECFP4, the corresponding percentages were 38.2% and 0.03%, respectively. However, in a typical similarity search trial, many more active vs. random compound comparisons are carried out than active vs. active comparisons, given that only small numbers of compounds with a specific activity are usually available in databases. For example, let us consider the most favorable case of easy activity classes, a search with MACCS using a single active reference compound, and a similarity threshold value of 0.8. If a database of 100,000 inactive and 50 active compounds were to be screened, eight active compounds would be detected together with five false-positives on the basis of the ratios given in Table 1. If 500,000 database compounds were to be screened, the number of false-positives would increase to 25 (given that the active vs. random distribution was normal). For ECFP4, applying a similarity threshold value of 0.3 under the same search conditions, screening a database with 50 active and 500,000 inactive compounds would result in 19 true- and 150 false-positives. Hence, even for easy activity classes, activity-relevant similarity values could not be reliably applied as thresholds in a typical similarity search scenario because of the large discrepancy in the number of different comparisons. Furthermore, for difficult search tasks, the number of true-positive detections would be reduced significantly and the number of false-positives would further increase (Table 1).\n\nReported are the total number of pairwise compound comparisons and percentages of Tc values (bold) falling into activity-relevant ranges of similarity values identified for the MACCS and ECFP4 fingerprints. “Act” stands for active and “Rand” for random.\n\nThe percentages of compounds from different categories falling into activity-relevant similarity ranges reported in Table 1 also helped to rationalize the relative performance of fingerprints in benchmark calculations. Such retrospective calculations typically focus on easy or intermediate activity classes (otherwise, mostly “negative” results would be obtained). In benchmark settings, ECFPs are often superior to MACCS and other standard fingerprints. If compound recall rates are determined, which is usually the case, but only possible in retrospective applications, ECFP4 is clearly favored over MACCS, given the much larger percentage of true-positive detections according to Table 1. However, it should also be noted that even for easy activity classes, ECFP4 only detected less than 40% of active compounds at activity-relevant similarity values. Thus, the false-negative rate was high, even more so for MACCS, indicating that the sensitivity of these fingerprints to active compounds in a similarity search scenario is low. This again reflects the fact that structure-activity information is not explicitly used in a fingerprint search.\n\nIn a prospective similarity search application, when active compounds are sparse and unknown and source databases are large, it would be more difficult to draw a line between ECFP4 and MACCS, as discussed above. Then, the ability to identify novel hits will much depend on the specific features of active compounds and the capacity of different fingerprints to capture them.\n\nA plus of activity-relevant similarity values, as determined herein, is that they have been derived over many different activity classes and are thus general in nature. As such, they become a characteristic feature of a given fingerprint, although their utility for practical similarity searching is limited.\n\n\nConclusion\n\nIn conclusion, in this study, we have addressed the issue of how, from a fundamental point of view, activity similarity might be related to molecular similarity calculated using fingerprints by focusing on systematic compound comparisons involved in similarity searching. The analysis has led to the introduction of activity-relevant similarity values as a characteristic feature of fingerprints of different design, which we consider useful as likelihood estimates. For example, given our ensemble of activity classes, the likelihood that a compound comparison yielded a Tc value of at least 0.8 for MACCS or 0.3 for ECFP4 was hundreds of times higher for compounds sharing the same activity than randomly selected or active vs. random compounds.\n\n\nData availability\n\nZENODO: Activity classes from different categories, doi: http://dx.doi.org/10.5281/zenodo.4731527",
"appendix": "Author contributions\n\n\n\nJB conceived the study; SJ and YH carried out the computational analysis; SJ, YH, MV, and JB analyzed the data and planned follow-up experiments; JB wrote the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nJohnson M, Maggiora GM: Concepts and applications of molecular similarity. Wiley, 1990. Reference Source\n\nWillett P, Barnard JM, Downs GM: Chemical similarity searching. J Chem Inf Comput Sci. 1998; 38(6): 983–996. Publisher Full Text\n\nBender A, Glen RC: Molecular similarity: a key technique in molecular informatics. Org Biomol Chem. 2004; 2(22): 3204–3218. PubMed Abstract | Publisher Full Text\n\nMaggiora G, Vogt M, Stumpfe D, et al.: Molecular similarity in medicinal chemistry. J Med Chem. 2014; 57(8): 3186–3204. PubMed Abstract | Publisher Full Text\n\nEckert H, Bajorath J: Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches. Drug Discov Today. 2007; 12(5–6): 225–233. PubMed Abstract | Publisher Full Text\n\nStumpfe D, Bajorath J: Similarity searching. Wiley Interdiscip Rev Comput Mol Sci. 2011; 1(2): 260–282. Publisher Full Text\n\nMaggiora GM, Shanmugasundaram V: Molecular similarity measures. Methods Mol Biol. 2004; 275: 1–50. PubMed Abstract | Publisher Full Text\n\nWillett P: Similarity-based virtual screening using 2D fingerprints. Drug Discov Today. 2006; 11(23–24): 1046–1053. PubMed Abstract | Publisher Full Text\n\nVogt M, Stumpfe D, Geppert H, et al.: Scaffold hopping using two-dimensional fingerprints: true potential, black magic, or a hopeless endeavor? Guidelines for virtual screening. J Med Chem. 2010; 53(15): 5707–5715. PubMed Abstract | Publisher Full Text\n\nGardiner EJ, Holliday JD, O'Dowd C, et al.: Effectiveness of 2D fingerprints for scaffold hopping. Future Med Chem. 2011; 3(4): 405–414. PubMed Abstract | Publisher Full Text\n\nWillett P: Similarity and clustering in chemical information systems. Research Studies Press, Letchworth, Hertfordshire, England, 1987.\n\nBrown RD, Martin YC: The Information Content of 2D and 3D Structural Descriptors Relevant to Ligand-Receptor Binding. J Chem Inf Comput Sci. 1997; 37(1): 1–9. Publisher Full Text\n\nPatterson DE, Cramer RD, Ferguson AM, et al.: Neighborhood behavior: a useful concept for validation of “molecular diversity” descriptors. J Med Chem. 1996; 39(16): 3049–3059. PubMed Abstract | Publisher Full Text\n\nDurant JL, Leland BA, Henry DR: Reoptimization of MDL keys for use in drug discovery. J Chem Inf Comput Sci. 2002; 42(6): 1273–1280. PubMed Abstract | Publisher Full Text\n\nMartin YC, Kofron JL, Traphagen LM: Do structurally similar molecules have similar biological activity? J Med Chem. 2002; 45(19): 4350–4358. PubMed Abstract | Publisher Full Text\n\nVogt M, Bajorath J: Introduction of a generally applicable method to estimate retrieval of active molecules for similarity searching using fingerprints. ChemMedChem. 2007; 2(9): 1311–1320. PubMed Abstract | Publisher Full Text\n\nVogt M, Bajorath J: Introduction of the conditional correlated Bernoulli model of similarity value distributions and its application to the prospective prediction of fingerprint search performance. J Chem Inf Model. 2011; 51(10): 2496–2506. PubMed Abstract | Publisher Full Text\n\nMuchmore SW, Debe DA, Metz JT, et al.: Application of belief theory to similarity data fusion for use in analog searching and lead hopping. J Chem Inf Model. 2008; 48(5): 941–948. PubMed Abstract | Publisher Full Text\n\nRogers D, Hahn M: Extended-connectivity fingerprints. J Chem Inf Model. 2010; 50(5): 742–754. PubMed Abstract | Publisher Full Text\n\nPetrone PM, Simms B, Nigsch F, et al.: Rethinking molecular similarity: comparing compounds on the basis of biological activity. ACS Chem Biol. 2012; 7(8): 1399–1409. PubMed Abstract | Publisher Full Text\n\nWassermann AM, Lounkine E, Glick M: Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules. J Chem Inf Model. 2013; 53(3): 692–703. PubMed Abstract | Publisher Full Text\n\nBento AP, Gaulton A, Hersey A, et al.: The ChEMBL bioactivity database: an update. Nucleic Acids Res. 2014; 42(Database issue): D1083–D1090. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHeikamp K, Bajorath J: Large-scale similarity search profiling of ChEMBL compound data sets. J Chem Inf Model. 2011; 51(8): 1831–1839. PubMed Abstract | Publisher Full Text\n\nHu Y, Bajorath J: Influence of search parameters and criteria on compound selection, promiscuity, and pan assay interference characteristics. J Chem Inf Model. 2014; 54(11): 3056–3066. PubMed Abstract | Publisher Full Text\n\nSterling T, Irwin JJ: ZINC 15--ligand discovery for everyone. J Chem Inf Model. 2015; 55(11): 2324–2337. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWang Y, Eckert H, Bajorath J: Apparent asymmetry in fingerprint similarity searching is a direct consequence of differences in bit densities and molecular size. ChemMedChem. 2007; 2(7): 1037–1042. PubMed Abstract | Publisher Full Text\n\nJasial S, Hu Y, Vogt M, et al.: Activity classes from different categories. ZENODO. 2016. Data Source"
}
|
[
{
"id": "13263",
"date": "07 Apr 2016",
"name": "Georgia B. McGaughey",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors summarize in detail the threshold between actives and inactives using 2D fingerprints for the MACCS and ECFP4 fingerprint methods using data derived from ChEMBL. The paper is well written and should be indexed. A few suggestions are made, however: Given that this is a chemistry paper, perhaps a few examples of chemical compounds showing the threshold for an active in Tc and ECFP4 space. How “low” can one go and still have an active? This would bolster the need for chemoinformatic approaches over the medchemists’ view of “eyeing” similarity. You have numerous references and mention belief theory in passing. I couldn’t help but think of Muchmore’s paper 1 and think you might want to include this paper as well especially given that he uses MACCS and ECFP4. You make no mention of 3D similarity methods, which even in passing, I recommend you include (ie a reference). I have one in JCIM from 2006 comparing 2D to 3D (but it’s not pairwise). What about the overlap between the methods in terms of actives? The result begs the question to the reader – do I now compute both and take an average (if I can only screen X%)? The threshold of 10uM for an active seems extremely generous. In practice, I would typically consider this an inactive compound especially if the screen was an enzymatic screen. How would the results differ if you used a different active threshold? Besides molecular weight, was there any consideration given to the number of PAINS or REOS flags? By this question I’m trying to understand if “actives” were easier to discriminate if compounds were merely promiscuous and if that mattered based on the easy-intermediate-hard ACs (have to agree with Wendy Warr on this – if you could spell out AC – I kept thinking activity cliffs).",
"responses": [
{
"c_id": "1919",
"date": "14 Apr 2016",
"name": "Jürgen Bajorath",
"role": "Author Response F1000Research Advisory Board Member",
"response": "It is noted that the Muchmore et al. reference was already cited. In addition, 3D similarity measures were not considered herein. By design, the study did neither focus on compound overlap for alternative fingerprint representations nor on general compound liabilities."
}
]
},
{
"id": "13265",
"date": "12 Apr 2016",
"name": "Peter Ertl",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAn interesting manuscript focusing on a relationship between molecule similarity and biological activity, one of the most important (and still not fully solved) problems of applied cheminformatics. The topic is therefore relevant to drug design.The question the authors are trying to answer is the significance of similarity thresholds when using MACCS and ECFP4 fingerprints and its implications in virtual screening, when one tries to identify small number of active molecules in the large number of inactives.There have been several studies focusing on the same question (an influence of a similarity thresholds on discriminating active and inactive molecules). Although such studies are mentioned in the literature overview it would be interesting to directly compare their conclusions with the conclusions of the present paper in the “Implications for similarity searching” section.The information content of the MACCS keys and the ECFP fingerprints are vastly different. The MACCS keys are, to my knowledge, no more used in a productive set-up as molecule descriptors in discriminating between actives and inactives. It would be interesting to focus on additional, more relevant structure descriptors, for example Daylight-like linear fingerprints or topological torsions. I suggest this as a topic for a follow-up study.The authors should mention which software they used for the calculation of fingerprints. Did they used PipelinePilot, open source tools or their own software? Results generated by different software tools may differ in some cases considerably, based on different molecule normalization, treatment of aromaticity, tautomers etc..I recommend to mention also a classical paper from this area by Brown and Martin1.",
"responses": [
{
"c_id": "1918",
"date": "14 Apr 2016",
"name": "Jürgen Bajorath",
"role": "Author Response F1000Research Advisory Board Member",
"response": "Thank you for suggesting the follow-up investigation. We note that the results of the two most relevant investigations were discussed in the introduction."
}
]
},
{
"id": "13264",
"date": "12 Apr 2016",
"name": "Wendy Warr",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a short but interesting paper and is extremely well written. I use the adjective “short” because the novel results occupy fewer than eight pages, if the figures and tables are ignored. Nevertheless, the results are interesting and well worth publishing because they do address a significant problem. The issue in question is well explained on pages 3-5. The literature background appears to cover all relevant research, but I suggest that two of the references be changed. I would replace the ACS meeting abstract cited at 12 with Brown and Martin, 19971. That paper does not mention “85%” specifically, but it does discuss the cutoff threshold in detail. Reference 14 is useless: a researcher novel to the field of similarity could not locate MACCS keys by seeking a non-existent company which had an office in San Leandro in 2005. I would prefer to see “activity classes” written out in full: it is not a long-winded term, and ACs looks a bit like a typo for ACS.On page 8 the sentence “Thus, similarity searching can be mimicked by systematically comparing compounds having the same activity and active compounds to random database compounds” is not clear enough. Further down the page it is made clear exactly what is compared with what, but that is too late. I also did not fully understand the statement “Comparison of random database compounds is not carried out during similarity searching. However, the similarity value distribution resulting from the latter comparison can be monitored as an additional reference.” Maybe: “Comparison of random database compounds to random database compounds is not carried out during traditional similarity searching, but the similarity value distribution resulting from this comparison can be monitored as an additional reference in mimicked similarity searching”? (Note also that it is better not to start a sentence with “However”.)On page 13 there should be a heading saying “Conclusion” before the sentence that begins “In conclusion”.The sentence beginning “In conclusion, in this study, we have addressed the issue how molecular similarity calculated using fingerprints and activity similarity might be related to each other from a fundamental point of view…” is ambiguous, e.g., “…molecular similarity calculated using both fingerprints and activity similarity, might be related to what?” Admittedly there is no comma, but it would be clearer to say “In conclusion, in this study, we have addressed the issue of how, from a fundamental point of view, activity similarity might be related to molecular similarity calculated using fingerprints…” At the very end the phrase “…was hundreds of times higher for compounds sharing the same activity than randomly selected or active vs. random compounds.” is not clear enough.In short, I like the science, and I think it should be indexed, but I would like to see a few minor improvements to the text as detailed above.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-591
|
https://f1000research.com/articles/5-770/v1
|
28 Apr 16
|
{
"type": "Review",
"title": "Recent advances in understanding psoriasis",
"authors": [
"Franziska C. Eberle",
"Jürgen Brück",
"Julia Holstein",
"Kiyoshi Hirahara",
"Kamran Ghoreschi",
"Franziska C. Eberle",
"Jürgen Brück",
"Julia Holstein"
],
"abstract": "T helper (Th) cells producing interleukin (IL)-17, IL-22, and tumor necrosis factor (TNF) form the key T cell population driving psoriasis pathogenesis. They orchestrate the inflammation in the skin that results in the proliferation of keratinocytes and endothelial cells. Besides Th17 cells, other immune cells that are capable of producing IL-17-associated cytokines participate in psoriatic inflammation. Recent advances in psoriasis research improved our understanding of the cellular and molecular players that are involved in Th17 pathology and inflammatory pathways in the skin. The inflammation-driving actions of TNF in psoriasis are already well known and antibodies against TNF are successful in the treatment of Th17-mediated psoriatic skin inflammation. A further key cytokine with potent IL-17-/IL-22-promoting properties is IL-23. Therapeutics directly neutralizing IL-23 or IL-17 itself are now extending the therapeutic spectrum of antipsoriatic agents and further developments are on the way. The enormous progress in psoriasis research allows us to control this Th17-mediated inflammatory skin disease in many patients.",
"keywords": [
"psoriasis",
"T helper cells",
"skin inflammation",
"keratinocyte"
],
"content": "Introduction\n\nPsoriasis is one of the most common chronic diseases, affecting 2–3% of the adult population and 0.5–1% of children. Due to the frequency of the disease worldwide and its clinical characteristics, psoriasis has gained the interest of many scientists in academia as well as industrial research. The easy accessibility of the skin allows scientists to study cells and mediators in inflamed skin and their relevance in disease pathogenesis in detail. Recent advances in psoriasis pathogenesis improved our understanding of disease mechanisms and resulted in the development of new immunobiologics and small molecules that help to control the chronic inflammation1. Here we summarize the recent findings on the cellular and molecular players that presumably contribute to psoriasis development. In general, psoriasis is considered to be an autoimmune disease and most scientists agree on the central importance of T cells in disease pathogenesis2–4, yet the psoriatic inflammation may originate from epidermal epithelial cells and innate immune cells. Clearly, a close interaction between mediators and cells of the innate and adaptive immune systems and keratinocytes and endothelial cells is present in psoriasis5,6.\n\n\nAberrant keratinocyte biology as a pathogenic driver in psoriasis\n\nDecades ago, psoriasis was primarily thought to be caused by aberrant keratinocytes resulting in uncontrolled proliferation of the epidermal cell layers. Early studies on the cellular ‘turnover’ of epidermal cells supported this hypothesis7. The keratinocytes in psoriasis are characterized not only by strong proliferation but also by an altered expression of certain keratins like keratin 16. The concept of altered keratinocytes as pathogenic cells causing psoriasis has gained new attention since different reports published in the beginning of this millennium showed that genetic alterations in epidermal transcription factors can cause skin disorders that resemble human psoriasis clinically and histologically. Mice with altered expression of JunB/c-Jun or phosphorylation of STAT3 in keratinocytes develop skin inflammation with histological and molecular characteristics of psoriasis8,9. Interestingly, in both models, the psoriatic skin inflammation seems to depend on the presence of immune cells including T cells and their cytokines. In fact, there is a close interaction between cytokines and keratinocytes. A number of cytokines present in psoriatic inflammation promotes keratinocyte proliferation. Intradermal injections of T helper 17 (Th17)-associated cytokines like interleukin (IL)-23 or IL-21 into mouse skin induce epidermal hyperplasia with morphological characteristics of human psoriasis associated with the infiltration of inflammatory T cells. On the other hand, keratinocytes themselves are a cellular source of cytokines. The most famous member is IL-8, a cytokine originally discovered in psoriatic scales10. Another example is the cytokine IL-15, which is expressed in psoriatic epidermis and protects keratinocytes from apoptosis. Interestingly, soluble IL-15Rα has been shown to dampen the psoriatic inflammation by suppressing cytokine secretion from keratinocytes and the expansion of IL-17-producing T cells11. Moreover, keratinocytes are a major source of IL-1 production12. Factors such as cytosolic DNA can trigger inflammasome activation and IL-1 secretion by keratinocytes, which contribute to the psoriatic inflammation13. Other mediators that are linked to psoriasis pathogenesis and that are produced by keratinocytes include antimicrobial peptides like S100A8/9, β-defensins, and cathelicidin (LL-37)3. Taken together, genetic alterations in transcription factors and environmental triggering factors affecting keratinocytes presumably facilitate the manifestation of psoriasis, yet psoriasis pathogenesis seems to be dominated by the activation of immune cells rather than alterations in keratinocytes.\n\n\nCentral role of immune cells\n\nSeveral observations support the importance of immune cells in the pathogenesis of psoriasis. One is the transfer of the disease by bone marrow cells. Case reports from individuals undergoing bone marrow transplantation for hematological disorders have linked the disappearance of psoriasis as well as the development of psoriasis in the recipient to the skin status of the donor14,15. The other observation is that immunosuppressive agents originally introduced for the prevention of organ transplant rejection showed unexpected benefits on the clinical course of psoriasis16,17. Subsequently, immunosuppressive agents like cyclosporine or methotrexate have been established in the treatment of psoriasis. Genetic data on human leukocyte antigen (HLA) associations as well as data on the presence of oligoclonal T cells in lesional skin and their reactivity towards cutaneous antigens further underline the importance of immune cells in psoriasis pathogenesis. Putative autoantigens in psoriasis include keratins, heat shock proteins, the antimicrobial peptide LL37, and the melanocytic antigen ADAMTS-like protein 5 (ADAMTSL5)18–20. The recent discovery of ADAMTSL5 as a potential autoantigen in psoriasis is a key finding. The recognition of this protein is restricted to epidermal CD8+ T cells of patients with psoriasis and a HLA-C*06:02 genotype. Stimulation of ADAMTSL5-specific CD8+ T cells results in IL-17A production20. Of note, HLA-C*06:02 is known as the HLA locus with the strongest genetic association with psoriasis. In addition to the linkage to certain HLA genotypes, recent investigations revealed that psoriasis is also linked to polymorphisms in genes encoding certain cytokines, cytokine receptors, and transcription factors. Today, there is a widely accepted consensus that psoriasis is an immune cell-mediated disease.\n\n\nA prototypic Th17 disease\n\nAmong the gene polymorphisms that have been linked to psoriasis are genes encoding IL23A, IL23R, STAT3, RUNX3, and TYK2. All of these genes are associated with the Th17 immune response1. Th17 cells are characterized by the expression of their lineage-defining cytokine IL-17A. In addition, Th17 cells can produce other cytokines like IL-17F, IL-21, IL-22, tumor necrosis factor (TNF), and granulocyte-macrophage colony-stimulating factor (GM-CSF). Some Th17 populations also secrete IL-9 or IL-10, depending on the signals they receive during initial activation. The differentiation and activation of the Th17 population from naïve T cells depend on cytokines like IL-6, IL-21, IL-1, TGF-β, and IL-2321. Strikingly, IL-23, its receptor, and its downstream signaling molecule STAT3 are all linked to the genetic susceptibility for developing psoriasis. Of note, the transcription factor STAT3 is also activated by IL-6 and IL-21 and, together with the other Th17-characterizing transcription factor RORγ, STAT3 is responsible for IL-17A and IL-17F expression22. Skin-infiltrating Th17 cells seem to be the central players orchestrating psoriasis pathogenesis (Figure 1). They interact with tissue cells like keratinocytes and endothelial cells and with various immune cells including dendritic cells (DCs) and neutrophilic granulocytes. The reactivation of memory Th17 cells is presumably responsible for the chronic course of the disease.\n\nCharacteristic markers and cytokines related to the interleukin (IL)-17/IL-23 immune signature of T cells, dendritic cells (DCs), and associated immune cells in psoriatic skin inflammation.\n\n\nContribution of skin-resident immune cells\n\nIt has become obvious that there is a critical population of memory T cells that resides in the tissue and is involved in the local immune response23. Those specific memory T cells were named “resident-memory T” (TRM) cells. TRM cells preferentially reside in epithelial barrier tissues such as the respiratory tract, reproductive tract, and skin24–26. TRM cells can respond rapidly to pathogenic invaders in the epithelial barrier site, so TRM cells are crucial for the protection of the host from harmful microorganisms. The pathogenic role of TRM cells in immune-mediated diseases including skin diseases like psoriasis is gaining more evidence. A recent study revealed the augmentation of TRM cells in the local inflamed skin of patients with psoriasis27. Moreover, TRM cells in psoriatic skin express higher levels of both IL17A and IL22 compared to those in the skin of healthy individuals. The majority of TRM cells in the epidermis express CD103. TRM cells residing in the dermis show lower expression of this marker27. IL-9-producing TRM cells have also been reported to be present in conditions of skin inflammation like in psoriasis28. Besides T cells, DCs can reside in the skin. DCs are a key population of the immune system, bridging the breaks between innate and adaptive immunity. Among the heterogeneous DC population, CD1c-CD11c+ DCs represent a population of inflammatory dermal DCs. Ultraviolet exposure reduces the number of inflammatory CD1c-CD11c+ dermal DCs in patients with psoriasis29, while the number of CD1c+CD11c+ so-called resident DCs remains unaffected30. A potent marker that allows the discrimination of inflammatory CD1c-CD11c+ DCs from resident CD1c+CD11c+ DCs in patients with psoriasis is TNF-related apoptosis-inducing ligand (TRAIL)31. More intensive studies are needed to identify the environmental signals that induce specific features of TRM cells and resident DCs in the skin under steady state and inflammatory conditions.\n\n\nPhenotype of dendritic cells in psoriasis\n\nIn general, DCs are a heterogeneous population. In the skin, different types of DCs have been described. The distinct populations are characterized by the expression of certain surface markers and mediators. In psoriasis, certain DC populations like plasmacytoid DCs (pDCs) and dermal myeloid DCs (mDCs) dominate the inflammatory skin, while the number of epidermal Langerhans cells seems to stay stable as compared to non-lesional skin. During initial inflammation, an increased number of pDCs is activated, which results in the release of type I interferon (IFN-α)32. Interestingly, complexes formed by self-DNA or self-RNA and the antimicrobial peptide LL37 have been shown to activate pDCs through Toll-like receptor 9 (TLR9) or TLR7/8, respectively33,34. Recently, a novel mechanism of pDC activation has been described. As shown for antimicrobial peptides, the Th17-associated cytokine IL-26 can also form complexes with DNA from dying bacterial or host tissue cells and these complexes also promote IFN-α production by pDCs through TLR9 stimulation35. These innate mechanisms seem to be relevant for pDC activation in psoriasis pathogenesis. The activation of pDCs is followed by an increase of CD11c+ mDCs, which express TNF, inducible nitric oxide synthase (iNOS), and IL-23. As mentioned above, inflammatory CD11c+ mDCs do not express CD1c in contrast to skin-resident CD1c+ mDCs. Another DC population that is capable of producing IL-23 is the so-called 6-sulfo LacNAc-expressing population (slanDCs)36,37. Moreover, CD163+ macrophages can produce IL-23 (Figure 1). Taken together, the major function of DCs and macrophages in psoriasis pathogenesis is to provide the signals that promote the Th17 inflammation.\n\n\nNon-T cell sources of IL-17A and IL-22 in psoriasis\n\nAs we discussed before, the IL-23/IL-17A and IL-23/IL-22 axes play a pivotal role in the pathogenesis of psoriasis38. Besides Th17 cells, IL-17A and/or IL-22 are produced by other types of immune cells including innate lymphoid cells (ILCs) 3, and gamma delta (γδ) T cells39–41. ILCs have recently been identified as a unique population of innate immune cells that lack antigen-specific receptors. They can be stimulated by cytokines and they produce a series of effector cytokines40. ILCs are now recognized to be divided into three main groups based on the feature of producing lineage-defining cytokines and specific transcription factors40,42,43. Among these groups of ILCs, ILC3 including lymphoid tissue inducer (LTi) cells are characterized by the production of IL-17A and/or IL-22 accompanied with high expression of Rorγt40,44,45. In the case of humans, ILC3 can be distinguished into several subpopulations based on expression patterns of natural killer (NK) cell markers like NKp44 and NKp4646. Among these subpopulations, NKp44+ ILC3 were reported to contribute to the pathogenesis of psoriasis, since IL-17A- and IL-22-producing NKp44+ ILC3 were increased in both the peripheral blood and the skin of patients with psoriasis47. The crucial role of ILC3 subpopulations in psoriasis pathogenesis is supported by the finding that Rorγt+CD56+ ILC3, which are capable of producing IL-22, are highly accumulated in the skin of patients with psoriasis48. Another cellular source of IL-17A in the skin is the γδ T cell population49. The majority of dermal γδ T cells express a T cell receptor (TCR) containing Vγ4 together with the chemokine receptor CCR650. In an experimental model of psoriasis-like inflammation in mice using the TLR7-agonist imiquimod, dermal Vγ4+ γδ T cells persist in the skin and contribute to skin inflammation by producing IL-17A and IL-17F51,52. Consistent with these findings, the increased number of γδ T cells, which produce large amounts of IL-17A, was detected in the affected skin of patients with psoriasis53. More recently, mast cells have also been reported as producers of IL-17A and IL-22 in psoriasis54. Similarly, neutrophils have been suggested as a further cellular source of IL-17A and IL-22. Of note, all immune cells mentioned also produce TNF, a factor well established in psoriasis pathogenesis and treatment. Taken together, various types of immune cells produce the psoriasis-driving cytokines TNF, IL-17A, and IL-22 (Figure 1).\n\n\nImmunotherapies supporting the role of TNF and IL-17A in psoriasis\n\nBased on the immunopathogenesis, antipsoriatic therapies target antigen-presenting cells (APCs), T cells, or their cytokines (Table 1). Modern small molecules like dimethyl fumarate and the PDE4 inhibitor apremilast both primarily act on APCs. By interfering with intracellular signaling pathways like NRF2 or second messengers like cAMP, they impair the production of pro-inflammatory DC cytokines like IL-23 and in contrast induce the release of anti-inflammatory IL-10. Since they also inhibit IL-12 and TNF production by APCs, dimethyl fumarate and apremilast treatment both result in the suppression of Th17 and Th1 responses55,56. Thus, silencing IL-23 expression by DCs by small molecules or by RNA interference (RNAi) technology, as recently tested in preclinical settings of autoimmune disease, is an attractive approach57,58. A new class of modern immunosuppressants is the class of JAK inhibitors59. These compounds interfere with the signaling pathways of numerous cytokines and hormones. Selective JAK inhibitors inhibit the activation and differentiation of multiple Th cell subsets, but they also inhibit the effects of cytokines on non-T cells and non-immune cells60. Thus, the mode of action of all of these compounds is not restricted to APCs and T cells. Although they may also affect other immune cells and tissue cells, they underline the importance of cytokine signaling in psoriasis61. To improve our understanding of psoriasis pathogenesis, it is more helpful to focus on therapeutics targeting single cytokines.\n\nThe table summarizes approved therapeutics and compounds that are in advanced stage development (according to www.clinicaltrials.gov) and some of their effects on the Th17 response. cAMP, cyclic adenosine monophosphate; DC, dendritic cell; HO-1, heme oxygenase-1; IL, interleukin; NRF2, nuclear factor (erythroid-derived 2)-like 2; PKC, protein kinase C; Th1, T helper type 1; Th2, T helper type 2; Th17, T helper type 17; TNF, tumor necrosis factor.\n\nThe first generation of antipsoriatic biologics targeting cytokines focused on TNF. These immunotherapeutics are highly effective in the treatment of psoriasis of skin and joints since they neutralize the effects of TNF on multiple cell types. In psoriatic skin, where TNF is mainly produced by DCs and macrophages, the neutralization of this cytokine rapidly decreases the expression of the Th17-promoting IL-23p40 and some other mediators62,63. This initial action of TNF neutralization on IL-23 in the skin is followed by the reduction of IL-17A, IL-22, IFN-γ, and TNF. The second generation of anti-psoriatic biologics targeting cytokines focuses directly on the Th17 cytokines IL-23 and IL-17A. The neutralization of p40, a cytokine unit shared by IL-23 and IL-12, is also effective in the treatment of psoriasis and psoriatic arthritis and directly interferes with the activation of Th17 as well as Th1 cells. Importantly, selective inhibition of the IL-23 unit p19 also improves psoriasis. Currently, three antibodies targeting p19 are in phase 3 development for the treatment of psoriasis. Neutralization of IL-23 results in decreased numbers of skin-infiltrating T cells, mDCs, pDCs, and neutrophils, while epidermal Langerhans cells remain unaffected64. Finally, IL-17A itself became a therapeutic target in psoriasis. The first monoclonal antibody directed against IL-17A is already approved for the treatment of psoriasis and psoriatic arthritis65. A second anti-IL-17A antibody recently received a positive opinion by the European Medicines Agency66. Systemic neutralization of IL-17A lowers the expression of IL-17A, IL-17F, IL-22, TNF, IL-6, IL-8, and p40 in the skin65. Of note, an antibody blocking the IL-17 receptor A (IL-17RA) is also effective in psoriasis and is in phase 3 development. These new approaches emphasize the significance of the Th17 pathway in psoriasis.\n\n\nRemaining questions\n\nRecent findings have helped us to improve our understanding of psoriasis pathogenesis. We now allocate the mechanisms of previously established antipsoriatic treatments to their effects on the Th17 pathway. This is best illustrated for the use of recombinant IL-4 or the small molecule dimethyl fumarate, which both suppress Th17 cell development55,67,68. The new generation of antipsoriatic biologics directly targeting IL-23 or IL-17A underlines the central role of these cytokines in psoriasis pathogenesis. Although we have a battery of systemic treatments for our patients, we do not know which patient will respond adequately to a certain drug. There is still a significant number of primary and secondary non-responders. The lack and the loss of response are mainly observed in patients treated with oral therapeutics and TNF antagonists. Possibly, this will be similar in patients receiving modern drugs directly interfering with the Th17 axis. One of the most important future developments is the establishment of testing methods to predict the clinical response to certain targeted therapies using immunobiologics or small molecules. Definition of useful biomarkers may help to identify responders in an early stage. Some markers like IL-8, IL-19, NOS2, or S100 proteins are typically expressed in psoriatic skin10,67,69–71, but ideal biomarkers are still not established. Furthermore, we have to understand why the same body sites can develop psoriatic plaques, even after long periods of remission. One study demonstrates that epidermal CD8+ TRM and also CD4+ T cells reside in the skin even after successful treatment and retain their capability of responding rapidly with the production of IL-17A and IL-22, respectively, upon ex vivo stimulation27. Another issue to be studied is the exact mechanism that causes the development of paradoxical psoriasis in patients without prior history of psoriasis who receive TNF antagonists for the treatment of inflammatory colitis or rheumatoid arthritis. Unraveling these immunological mechanisms may also help us to understand the different phenotypes of psoriasis. One example is given by recent findings on pustular psoriasis. Genetic studies could link IL-36RN deficiency and CARD14 mutations to the susceptibility for generalized pustular psoriasis72,73. Thus, interfering with inflammasome activation or IL-1 family cytokines may be of benefit in such patients74. Similarly, it is of interest to understand why certain environmental factors like infections and drugs but also acquired immunodeficiency result in treatment-resistant cases of psoriasis. To complete our understanding of this chronic inflammatory disease affecting a large proportion of our global population, further research in immunology, genetics, epigenetics, microbiology, and molecular biology is needed.\n\n\nAbbreviations\n\nDC, dendritic cells; HLA, human leukocyte antigen; IL, interleukin; ILC, innate lymphoid cell; mDC, myeloid dendritic cell; NK cell, natural killer cell; pDC, plasmacytoid dendritic cell; Th cell, T helper cell; TLR, Toll-like receptor; TRM cell, resident-memory T cell.",
"appendix": "Competing interests\n\n\n\nKamran Ghoreschi has been a consultant, lecturer, or investigator for AbbVie, Almirall, Boehringer, Biogen, Celgene, Eli Lilly and Company, Janssen-Cilag, MSD Sharp & Dohme, Novartis Pharmaceuticals, and Pfizer.\n\n\nGrant information\n\nThis work was supported by the Deutsche Forschungsgemeinschaft (DFG) Sonderforschungsbereich (SFB) 685 (to Kamran Ghoreschi) and SFB TR-156 (to Franziska C. Eberle and Kamran Ghoreschi).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nBelge K, Brück J, Ghoreschi K: Advances in treating psoriasis. F1000Prime Rep. 2014; 6: 4. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNestle FO, Kaplan DH, Barker J: Psoriasis. N Engl J Med. 2009; 361(5): 496–509. PubMed Abstract | Publisher Full Text\n\nLowes MA, Suárez-Fariñas M, Krueger JG: Immunology of psoriasis. Annu Rev Immunol. 2014; 32: 227–55. 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J Immunol. 2011; 186(11): 6091–5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPantelyushin S, Haak S, Ingold B, et al.: Rorγt+ innate lymphocytes and γδ T cells initiate psoriasiform plaque formation in mice. J Clin Invest. 2012; 122(6): 2252–6. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nRamírez-Valle F, Gray EE, Cyster JG: Inflammation induces dermal Vγ 4+ γδT17 memory-like cells that travel to distant skin and accelerate secondary IL-17-driven responses. Proc Natl Acad Sci U S A. 2015; 112(26): 8046–51. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHartwig T, Pantelyushin S, Croxford AL, et al.: Dermal IL-17-producing γδ T cells establish long-lived memory in the skin. Eur J Immunol. 2015; 45(11): 3022–33. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCai Y, Shen X, Ding C, et al.: Pivotal role of dermal IL-17-producing γδ T cells in skin inflammation. Immunity. 2011; 35(4): 596–610. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMashiko S, Bouguermouh S, Rubio M, et al.: Human mast cells are major IL-22 producers in patients with psoriasis and atopic dermatitis. J Allergy Clin Immunol. 2015; 136(2): 351–9.e1. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGhoreschi K, Brück J, Kellerer C, et al.: Fumarates improve psoriasis and multiple sclerosis by inducing type II dendritic cells. J Exp Med. 2011; 208(11): 2291–303. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSchafer PH, Parton A, Gandhi AK, et al.: Apremilast, a cAMP phosphodiesterase-4 inhibitor, demonstrates anti-inflammatory activity in vitro and in a model of psoriasis. Br J Pharmacol. 2010; 159(4): 842–55. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGeisel J, Brück J, Glocova I, et al.: Sulforaphane protects from T cell-mediated autoimmune disease by inhibition of IL-23 and IL-12 in dendritic cells. J Immunol. 2014; 192(8): 3530–9. PubMed Abstract | Publisher Full Text\n\nBrück J, Pascolo S, Fuchs K, et al.: Cholesterol Modification of p40-Specific Small Interfering RNA Enables Therapeutic Targeting of Dendritic Cells. J Immunol. 2015; 195(5): 2216–23. PubMed Abstract | Publisher Full Text\n\nGhoreschi K, Laurence A, O'Shea JJ: Selectivity and therapeutic inhibition of kinases: to be or not to be? Nat Immunol. 2009; 10(4): 356–60. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGhoreschi K, Jesson MI, Li X, et al.: Modulation of innate and adaptive immune responses by tofacitinib (CP-690,550). J Immunol. 2011; 186(7): 4234–43. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGhoreschi K, Gadina M: Jakpot! New small molecules in autoimmune and inflammatory diseases. Exp Dermatol. 2014; 23(1): 7–11. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBrunner PM, Koszik F, Reininger B, et al.: Infliximab induces downregulation of the IL-12/IL-23 axis in 6-sulfo-LacNac (slan)+ dendritic cells and macrophages. J Allergy Clin Immunol. 2013; 132(5): 1184–1193.e8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nTsianakas A, Brunner PM, Ghoreschi K, et al.: The single-chain anti-TNF-α antibody DLX105 induces clinical and biomarker responses upon local administration in patients with chronic plaque-type psoriasis. Exp Dermatol. 2016. PubMed Abstract | Publisher Full Text\n\nKopp T, Riedl E, Bangert C, et al.: Clinical improvement in psoriasis with specific targeting of interleukin-23. Nature. 2015; 521(7551): 222–6. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nHueber W, Patel DD, Dryja T, et al.: Effects of AIN457, a fully human antibody to interleukin-17A, on psoriasis, rheumatoid arthritis, and uveitis. Sci Transl Med. 2010; 2(52): 52ra72. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGriffiths CE, Reich K, Lebwohl M, et al.: Comparison of ixekizumab with etanercept or placebo in moderate-to-severe psoriasis (UNCOVER-2 and UNCOVER-3): results from two phase 3 randomised trials. Lancet. 2015; 386(9993): 541–51. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGhoreschi K, Thomas P, Breit S, et al.: Interleukin-4 therapy of psoriasis induces Th2 responses and improves human autoimmune disease. Nat Med. 2003; 9(1): 40–6. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGuenova E, Skabytska Y, Hoetzenecker W, et al.: IL-4 abrogates TH17 cell-mediated inflammation by selective silencing of IL-23 in antigen-presenting cells. Proc Natl Acad Sci U S A. 2015; 112(7): 2163–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWitte E, Kokolakis G, Witte K, et al.: IL-19 is a component of the pathogenetic IL-23/IL-17 cascade in psoriasis. J Invest Dermatol. 2014; 134(11): 2757–67. PubMed Abstract | Publisher Full Text\n\nQuaranta M, Knapp B, Garzorz N, et al.: Intraindividual genome expression analysis reveals a specific molecular signature of psoriasis and eczema. Sci Transl Med. 2014; 6(244): 244ra90. PubMed Abstract | Publisher Full Text\n\nSchonthaler HB, Guinea-Viniegra J, Wculek SK, et al.: S100A8-S100A9 protein complex mediates psoriasis by regulating the expression of complement factor C3. Immunity. 2013; 39(6): 1171–81. PubMed Abstract | Publisher Full Text\n\nMarrakchi S, Guigue P, Renshaw BR, et al.: Interleukin-36-receptor antagonist deficiency and generalized pustular psoriasis. N Engl J Med. 2011; 365(7): 620–8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBerki DM, Liu L, Choon SE, et al.: Activating CARD14 Mutations Are Associated with Generalized Pustular Psoriasis but Rarely Account for Familial Recurrence in Psoriasis Vulgaris. J Invest Dermatol. 2015; 135(12): 2964–70. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nHüffmeier U, Wätzold M, Mohr J, et al.: Successful therapy with anakinra in a patient with generalized pustular psoriasis carrying IL36RN mutations. Br J Dermatol. 2014; 170(1): 202–4. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13626",
"date": "28 Apr 2016",
"name": "Thomas Herzinger",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13627",
"date": "28 Apr 2016",
"name": "Mario Fabri",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-770
|
https://f1000research.com/articles/5-768/v1
|
27 Apr 16
|
{
"type": "Review",
"title": "Recent advances in the management of Hodgkin lymphoma",
"authors": [
"Jose C. Villasboas",
"Stephen M. Ansell",
"Stephen M. Ansell"
],
"abstract": "Hodgkin lymphoma (HL) is a rare cancer of the immune system that typically affects lymph nodes and sometimes other organs. Although the majority of patients can be potentially cured with the use of multi-agent chemotherapy and radiotherapy, a proportion of them will relapse or develop resistant disease for which treatment options are limited. In recent years, new agents have been developed and tested in HL with encouraging results. Two classes of drugs stand out as highly active in advanced HL based on recent study results: antibody-drug conjugates and programmed death 1 inhibitors. Clinical trials in HL with these agents have been completed in the past several years and the results have recently become available. In this review, we discuss the recent advances in the management of HL with a focus on strategies to decrease toxicity and a review of the two drug classes that have the potential to change the landscape of treatment of this disease.",
"keywords": [
"Hodgkin lymphoma",
"cancer",
"lymph nodes",
"b lymphocytes"
],
"content": "Introduction\n\nHodgkin lymphoma (HL) is a rare cancer that arises from immune cells known as B lymphocytes (B cells) and typically affects the lymph nodes and sometimes other organs1. HL accounts for 10% of all lymphomas and less than 1% of all cancers diagnosed in the United States (US) yearly2. It is a cancer of young adults, primarily occurring during the first four decades of life with a secondary peak between the sixth and seventh decades3. Approximately 8500 new patients will be diagnosed with HL and 1120 will die of the disease in the US in 2016 according to projections2.\n\nHL is a curable cancer and current treatments can eradicate the disease in up to 80% of cases4. Multi-agent chemotherapy, often in combination with radiation therapy, is the mainstay of management of HL, and treatment intensity is tailored to the risk of relapse. Despite the use of best available therapies, some patients will develop relapsed or refractory HL for which effective treatment options are limited. To meet the needs of these patients, new therapies are being tested in patients with HL and results are encouraging. These include agents that deliver cytotoxic chemotherapy to the interior of cancer cells using specific targets on the cell surface (antibody-drug conjugates [ADCs]) and strategies that enhance the ability of the patient’s immune system to eliminate HL cells (checkpoint inhibitors).\n\nHere we provide an overview of the latest advances in the management of HL with a focus on the two classes of drugs that have gained the most visibility in recent years: ADCs and programmed death 1 (PD-1) receptor inhibitors.\n\n\nAntibody-drug conjugates\n\nThe term ADC describes a therapeutic agent designed to selectively deliver toxic compounds to the interior of cancer cells using a monoclonal antibody that recognizes a specific target. These agents aim to selectively target the malignant cells using the specificity of antibodies while minimizing collateral damage to normal tissue. This technology has now been tested in different cancers and there are currently two ADCs on the market in the US: trastuzumab emtansine and brentuximab vedotin (BV).\n\nBV consists of a chimeric monoclonal antibody against human CD30 (cAC10) coupled to monomethyl auristatin E (MMAE) using a peptide linker. BV recognizes CD30 on the surface of the malignant HL cells and is internalized, releasing MMAE in its interior. Once inside the HL cell, MMAE prevents the polymerization of tubulin, a protein that is essential for cell division. Since CD30 is highly expressed on the surface of HL cells but not on most normal human tissue, BV can selectively target malignant cells to achieve its therapeutic effect.\n\nEarly studies of BV demonstrated encouraging activity in pre-clinical models5–7 and the drug was taken forward into initial clinical trials in patients with HL and anaplastic large cell lymphoma.\n\nAn initial phase I dose-escalation study investigated the safety and clinical activity of BV in 45 patients with relapsed CD30-positive lymphomas, 42 of them with HL8. A total of 15 patients (36%) with HL achieved an objective response to treatment with BV, nine (21%) of whom had a complete response. Overall, the drug was well tolerated and safe at the dose level of 1.8 mg/kg given every 3 weeks, which moved forward into clinical development.\n\nA multinational phase II study was then designed to evaluate the efficacy of BV in patients with advanced HL who had failed autologous stem cell transplantation (auto-SCT). A total of 105 patients with HL were treated with 1.8 mg/kg of BV every 3 weeks for a maximum of 16 cycles and assessed primarily for objective response. An objective response was observed in 76 patients (75%), including 35 (34%) complete remissions (CRs). The median duration of response was 6.7 months for all responders and 20.5 months for those achieving CR. The drug was well tolerated and the most common adverse effects were peripheral neuropathy, fatigue, gastrointestinal symptoms, and neutropenia. There were no cases of febrile neutropenia or deaths attributed to BV.\n\nBased on the results of this trial, BV received accelerated approval from the US Food and Drug Administration (FDA) on 19 August 2011 for the treatment of patients with HL after failure of auto-SCT or after failure of at least two prior multi-agent chemotherapy regimens in patients who are not candidates for auto-SCT. Updated results from that trial after a median follow-up of 3 years confirmed that responses were durable, especially for the group achieving CR9.\n\nAdditional studies were designed to evaluate the role of BV in other settings. A large phase III trial demonstrated increased progression-free survival (PFS) when BV was used as consolidative treatment following auto-SCT10. A phase I dose-escalation trial studied the use of BV + ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) or BV + AVD (ABVD without bleomycin) in treatment-naïve patients with HL13. Fifty-one patients were treated and CR was achieved in 95% of BV + ABVD and 96% of BV + AVD patients. Aside from excessive pulmonary toxicity in the BV + ABVD group, treatment was generally well tolerated. A large multicenter phase III trial of BV + AVD versus ABVD (NCT01712490) for newly diagnosed advanced HL has recently completed accrual.\n\nBV has been approved for use as a single agent at the dose of 1.8 mg/kg (up to 180 mg) administered intravenously every 3 weeks until a maximum of 16 cycles, disease progression, or unacceptable toxicity. At this dose level, BV is generally well tolerated. The most clinically relevant side effect of BV is peripheral neuropathy. Sensory neuropathy is more commonly seen (42%) than motor neuropathy (11%). Cases of BV-induced neuropathy may be severe (up to 31% at least grade 2) and constituted the leading cause of drug discontinuation in some of the clinical trials12,13. Median time to onset of neuropathy was about 12 weeks and severity was cumulative. The majority of patients (80%) experienced some improvement of symptoms (of at least one grade) with drug discontinuation but complete resolution was observed in only half of the cases. It is important to mention that the incidence of febrile neutropenia was extremely low, making BV an attractive drug for combination with multi-agent chemotherapy regimens.\n\nThe combination of BV with bleomycin in a phase I trial investigating the use of BV in combination with standard therapy (ABVD) led to unacceptable pulmonary toxicity11. On the basis of these findings, the label of BV was modified to include a contraindication to its use in conjunction with bleomycin. Consequently, the trials currently evaluating the use of BV in combination with chemotherapy have modified the regimens to exclude bleomycin.\n\nAlthough BV is generally safe and well tolerated, two other uncommon but serious adverse events potentially associated with the use of BV are worth mentioning: progressive multifocal leukoencephalopathy (PML)14,15 and pancreatitis16. Post-marketing reports linked BV to these serious and potentially life-threatening conditions. These resulted in the addition of a black-box warning for the risk of PML and raised awareness for the occurrence of acute pancreatitis in patients treated with BV.\n\nThe success of BV – the first ADC approved for the treatment of lymphomas – has spurred interest in developing new agents using the same platform. ADCT-301 is an ADC that combines a monoclonal antibody against CD25 to an antibiotic with anti-tumoral properties (pyrrolobenzodiazepine or PBD). This compound has demonstrated pre-clinical activity17 and is now accruing patients with HL for a phase I study (NCT02432235). Another compound targeting CD25 combines the specificity of a monoclonal antibody (daclizumab) to the anti-tumoral activity of radiotherapy (RT) by linkage to a beta-emitter particle (90Y). 90Y-daclizumab has now been tested in patients with advanced HL in a recently published phase II study with encouraging results18.\n\n\nCheckpoint inhibitors\n\nThe normal immune system is constantly monitoring the body for infections and cancer cells. Once activated, immune cells are subject to regulatory checkpoints designed to extinguish the immunological response once the offender has been eliminated. These natural regulatory mechanisms are meant to prevent uncontrolled immune activation, which could lead to untoward damage to normal tissue. These pathways are collectively known as immune checkpoints, and our knowledge of these mechanisms is rapidly increasing. Cancer cells, however, can highjack immune checkpoint pathways to actively evade immune surveillance.\n\nOne such example is the overexpression of ligands for the PD-1 receptor on the surface of cancer cells. Once these ligands (PD-L1 or PD-L2) engage the PD-1 receptor expressed on the surface of activated T cells, they lead to a cascade of events that culminate in decreased function and survival of immune cells. The ultimate effect is dampening of the immune response, which allows the tumor to progress unopposed. The use of this evasion mechanism by HL cells has been clearly described19–22. Drugs that interfere with the interaction between PD-1 and its ligands (PD-L1 or PD-L2) have been developed and tested in different cancer types.\n\nTwo of these PD-1 inhibitors – nivolumab and pembrolizumab – have now been tested in patients with advanced HL with remarkable results, which will be discussed here.\n\nNivolumab is a monoclonal antibody that binds to the PD-1 receptor and prevents it from interacting with its ligands (PD-L1 and PD-L2). By disrupting the PD-1:PD-L1/2 axis, nivolumab seeks to overcome immune tolerance induced by cancer cells, thereby releasing the immune system for an effective anti-cancer response. Nivolumab has now been tested in several malignancies and received FDA approval for use in melanoma, non-small cell lung cancer, and renal cell carcinoma23.\n\nA phase I dose-escalation trial tested the safety and efficacy of nivolumab in patients with heavily pre-treated advanced HL. The original manuscript reported on the experience with the first 23 patients treated at the 3 mg/kg dose level after a median follow-up of 40 weeks24. An objective response was observed in 20 (87%) patients, including four (17%) with a complete response. The additional three patients had stable disease, indicating that all 23 patients derived some degree of clinical benefit from the treatment. Nivolumab was well tolerated and the safety profile was consistent with previous experience documented for other tumor types. No serious adverse events or deaths attributed to the drug were observed.\n\nUpdated long-term results on these patients after a median follow-up of 86 weeks were presented at the most recent American Society of Hematology (ASH) annual meeting25. Of the 20 initial responders, 10 demonstrated responses lasting over 41 weeks (range 41.7 to 90.7 weeks), including one who was retreated at progression after treatment was discontinued. Of the remaining 10 responders, four developed progressive disease, one discontinued due to adverse effects (without progression), and five discontinued nivolumab to undergo allogeneic SCT. These results provide early evidence that responses obtained with nivolumab in HL may be durable.\n\nBased on these encouraging early results, nivolumab received breakthrough therapy designation for HL from the FDA. A registrational phase II trial utilizing nivolumab for the treatment of HL is currently underway (NCT02181738).\n\nPembrolizumab is another monoclonal antibody that belongs to the class of PD-1 inhibitors. Similar to nivolumab, this agent works by targeting the PD-1 receptor and is approved by the FDA for the treatment of melanoma and non-small cell lung cancer26.\n\nThe safety and clinical activity of pembrolizumab is being tested in a phase Ib multicenter clinical trial for patients with relapsed/refractory HL after failure of auto-SCT and BV. Patients who were deemed ineligible for or refused auto-SCT were also included. Patients were treated with 10 mg/kg of pembrolizumab every 2 weeks. An updated report on the first 31 patients was presented at the most recent ASH annual meeting27. At a median follow-up of 9.7 months, an objective response was observed in 20 (65%) patients including five (16%) achieving CR. An additional seven (23%) patients had stable disease as best response, indicating that 87% of patients derived clinical benefit. Pembrolizumab was well tolerated and toxicity was consistent with previous experience in other cancers. Fourteen of the 20 responses were ongoing at the time of data cut-off. No serious adverse events or deaths were attributed to the treatment.\n\nThese results reinforced the notion that PD-1 inhibition is a safe strategy with a strong signal of clinical activity in heavily pre-treated HL patients. These and other studies are currently open and accruing patients with HL.\n\nPD-1 inhibitors are usually well-tolerated drugs, even for patients who are heavily pre-treated with standard cytotoxic agents. The most common adverse effects of this class are dermatologic (rash and pruritus), metabolic (lipid changes, hyperglycemia, hypoalbuminemia, and electrolyte imbalances), hematologic (anemia and lymphopenia), gastrointestinal (changes in bowel habits and nausea/vomiting), and respiratory (cough and dyspnea)26,28 in nature and also include fatigue, abnormal liver enzymes, and arthralgia.\n\nA distinct class of adverse effects – collectively known as immune-related adverse effects (IrAEs) – deserves special mention, since they are uniquely associated with these immunotherapeutic agents29. These are the result of the immune-stimulatory effects of these drugs and can affect different organs with pleomorphic presentations. Despite being uncommon, early recognition and management is crucial, as these events can progress rapidly to cause significant morbidity or even death. Potentially affected organs are the lungs (pneumonitis), the endocrine system (hypophysitis, thyroiditis, and adrenal insufficiency), the skin (toxic epidermal necrolysis), and the gastrointestinal tract (colitis and pancreatitis). These occurrences should trigger immediate evaluation and providers should have a low threshold to hold therapy (for mild cases) and treat with systemic steroids (for moderate to severe cases). Expert consultation with organ-specific specialties is highly advised, as these patients often need invasive testing (i.e. bronchoscopies and colonoscopies) to rule out alternative diagnoses (i.e. infection or tumor progression). Standardized guidelines on the management of these patients are not yet available and treatment must be individualized.\n\nCaution is advised when utilizing checkpoint inhibitors in patients with a documented history of autoimmune disorders, especially if poorly controlled. The same applies for the use of checkpoint inhibitor therapy in patients who have failed allogeneic SCT and have active graft-versus-host disease (GVHD). Evidence is starting to surface supporting the safety of the use of these agents in patients with pre-existing autoimmune conditions30 (as long as they are adequately controlled) or after allogeneic transplant (as long as GVHD is minimal)31–34. These are mostly retrospective studies or small case series; therefore, therapy in these special situations must be individualized and include a thorough discussion of the risks, benefits, and uncertainties.\n\n\nOther immunotherapeutic strategies in development for Hodgkin lymphoma\n\nThe exciting responses observed with the use of PD-1 inhibitors in HL resulted in the development of a number of strategies combining these drugs with other agents in an attempt to increase efficacy. Clinical trials combining PD-1 inhibitors to Bruton tyrosine kinase inhibitors (NCT02362035), bispecific NK-cell engager antibodies (NCT02665650), BV (NCT01896999 and NCT02572167), other immune checkpoint inhibitors (NCT01896999, NCT02304458, and NCT01592370) or standard cytotoxic chemotherapy (NCT02181738) are under active development.\n\nAnother strategy to manipulate the immune system against the cancer cell is the use of chimeric antigen receptor-modified T cell (CAR-T) therapy. This involves genetically re-engineering the patient’s effector immune cells (T cells) to directly recognize and eliminate tumor cells via modifications to the T cell receptor35. Exciting results were observed when this technology was tested in a pivotal study of patients with relapsed acute lymphoblastic leukemia36. The principle has now been applied to target CD30 – expressed on the surface of HL cells – and preclinical models demonstrate encouraging activity37. At least seven studies evaluating the use of CAR-T therapy in HL are currently open.\n\n\nResponse-adapted strategies for early stage Hodgkin lymphoma\n\nPatients with stages I/II HL have a chance of cure above 90% when treated with a combination of multi-agent chemotherapy and RT. Unfortunately, long-term side effects of treatment are still a reality that may negatively impact the quality of life and morbidity of long-term survivors. Recent strategies have focused on de-escalating treatment in lower risk patients based on an interim assessment using positron-emission tomography (PET) scans. These response-adapted strategies aim to identify patients in whom therapy may be safely de-escalated to minimize long-term toxicity without compromising efficacy.\n\nTwo studies have recently reported the use of interim PET scans in response-adapted therapy for early stage HL. The Randomised Phase III Trial to Determine the Role of FDG–PET Imaging in Clinical Stages IA/IIA Hodgkin’s Disease (RAPID) randomized 426 patients with a negative PET after three cycles of ABVD to receive either RT or no further treatment using a non-inferiority design38. The PFS at 3 years was 94.6% in the RT group and 90.8% in the observation group. Although the trial failed to demonstrate that this strategy was non-inferior to RT, the results highlighted the low incidence of recurrence in early stage patients who are able to achieve a negative PET scan following initial chemotherapy.\n\nA second study from the US Intergroup had interim results presented at the most recent ASH annual meeting39. In this phase II study, patients with stages I/II HL were assessed with a PET scan after two cycles of ABVD. Patients with a positive PET went on to receive escalated therapy with two cycles of dose-intense bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone (escalated BEACOPP) + RT. Patients with a negative PET received only two additional cycles of ABVD. At a median follow-up of 2 years, PFS was 92% in PET-negative patients compared to 66% in the PET-positive group. These results again suggested excellent outcomes with an abbreviated chemotherapy-only approach.\n\nTogether, these results indicate that an interim PET scan is a powerful biomarker with predictive value in patients with early stage HL. Its use has now been incorporated into clinical practice guidelines for a select group of patients40.\n\n\nFuture perspectives in the management of Hodgkin lymphoma\n\nIn an era when immunotherapy has emerged as the next frontier in cancer management, HL consistently stands out as a successful platform for the development of these strategies. One must not forget, however, the tremendous success that has been achieved up to this point by virtue of treatment with standard cytotoxic agents and RT. Unfortunately, negative long-term consequences of these therapies can be significant for HL survivors. This constitutes both the challenge and the opportunity that will need to be addressed by the next generation of clinical trials. The challenge consists of incorporating these highly active agents into well-established standard-of-care treatment paradigms without compromising efficacy for this highly curable disease. The opportunity that unfolds involves a potential for de-escalation of treatment intensity by incorporating these newer agents and metabolic biomarkers such as PET scans. Similarly, these new agents provide our elderly and frail patients with treatment opportunities that were not previously available. As long as this can be achieved safely while retaining efficacy, the potential to increase the cure rate and reduce long-term toxicity is significant.\n\n\nAbbreviations\n\nABVD, doxorubicin, bleomycin, vinblastine, and dacarbazine; ADC, antibody-drug conjugate; ASH, American Society of Hematology; auto-SCT, autologous stem cell transplantation; BV, brentuximab vedotin; CAR-T, chimeric antigen receptor-modified T cell; CR, complete remission; escalated BEACOPP, dose-intense bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine and prednisone; FDA, US Food and Drug Administration; GVHD, graft-versus-host disease; HL, Hodgkin lymphoma; IrAEs, immune-related adverse effects; MMAE, monomethyl auristatin E; PBD, pyrrolobenzodiazepine; PD-1, programmed death 1; PD-L1, programmed death receptor ligand 1; PD-L2, programmed death receptor ligand 2; PET, positron-emission tomography; PFS, progression-free survival; PML, progressive multifocal leukoencephalopathy; RT, radiotherapy; SCT, stem cell transplantation.",
"appendix": "Competing interests\n\n\n\nJose C. Villasboas declares that he has no competing interests.\n\n\nGrant information\n\nStephen M. Ansell receives research funding from Seattle Genetics, Bristol-Myers Squibb, and Celldex, Inc.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nSwerdlow SH: WHO classification of tumours of haematopoietic and lymphoid tissues. (International Agency for Research on Cancer, 2008). Reference Source\n\nSiegel RL, Miller KD, Jemal A: Cancer statistics, 2016. CA Cancer J Clin. 2016; 66(1): 7–30. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSmith A, Crouch S, Lax S, et al.: Lymphoma incidence, survival and prevalence 2004-2014: sub-type analyses from the UK's Haematological Malignancy Research Network. Br J Cancer. 2015; 112(9): 1575–84. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nConnors JM: State-of-the-art therapeutics: Hodgkin's lymphoma. J Clin Oncol. 2005; 23(26): 6400–8. PubMed Abstract | Publisher Full Text\n\nOkeley NM, Miyamoto JB, Zhang X, et al.: Intracellular activation of SGN-35, a potent anti-CD30 antibody-drug conjugate. Clin Cancer Res. 2010; 16(3): 888–97. PubMed Abstract | Publisher Full Text\n\nOflazoglu E, Kissler KM, Sievers EL, et al.: Combination of the anti-CD30-auristatin-E antibody-drug conjugate (SGN-35) with chemotherapy improves antitumour activity in Hodgkin lymphoma. Br J Haematol. 2008; 142(1): 69–73. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFrancisco JA, Cerveny CG, Meyer DL, et al.: cAC10-vcMMAE, an anti-CD30-monomethyl auristatin E conjugate with potent and selective antitumor activity. Blood. 2003; 102(4): 1458–65. PubMed Abstract | Publisher Full Text\n\nYounes A, Bartlett NL, Leonard JP, et al.: Brentuximab vedotin (SGN-35) for relapsed CD30-positive lymphomas. N Engl J Med. 2010; 363(19): 1812–21. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nGopal AK, Chen R, Smith SE, et al.: Durable remissions in a pivotal phase 2 study of brentuximab vedotin in relapsed or refractory Hodgkin lymphoma. Blood. 2015; 125(8): 1236–43. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMoskowitz CH, Nademanee A, Masszi T, et al.: Brentuximab vedotin as consolidation therapy after autologous stem-cell transplantation in patients with Hodgkin's lymphoma at risk of relapse or progression (AETHERA): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2015; 385(9980): 1853–62. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nYounes A, Gopal AK, Smith SE, et al.: Results of a pivotal phase II study of brentuximab vedotin for patients with relapsed or refractory Hodgkin's lymphoma. J Clin Oncol. 2012; 30(18): 2183–9. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nForero-Torres A, Holkova B, Goldschmidt J, et al.: Phase 2 study of frontline brentuximab vedotin monotherapy in Hodgkin lymphoma patients aged 60 years and older. Blood. 2015; 126(26): 2798–804. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nYounes A, Connors JM, Park SI, et al.: Brentuximab vedotin combined with ABVD or AVD for patients with newly diagnosed Hodgkin's lymphoma: a phase 1, open-label, dose-escalation study. Lancet Oncol. 2013; 14(13): 1348–56. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nvon Geldern G, Pardo CA, Calabresi PA, et al.: PML-IRIS in a patient treated with brentuximab. Neurology. 2012; 79(20): 2075–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCarson KR, Newsome SD, Kim EJ, et al.: Progressive multifocal leukoencephalopathy associated with brentuximab vedotin therapy: a report of 5 cases from the Southern Network on Adverse Reactions (SONAR) project. Cancer. 2014; 120(16): 2464–71. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nGandhi MD, Evens AM, Fenske TS, et al.: Pancreatitis in patients treated with brentuximab vedotin: a previously unrecognized serious adverse event. Blood. 2014; 123(18): 2895–7. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFlynn MJ, van Berkel P, Zammarchi F, et al.: Pre-Clinical Activity of Adct-301, a Novel Pyrrolobenzodiazepine (PBD) Dimer-Containing Antibody Drug Conjugate (ADC) Targeting CD25-Expressing Hematological Malignancies. Blood. 2014; 124(21): 4491 [Oral and Poster Abstracts]. Reference Source\n\nJanik JE, Morris JC, O'Mahony D, et al.: 90Y-daclizumab, an anti-CD25 monoclonal antibody, provided responses in 50% of patients with relapsed Hodgkin's lymphoma. Proc Natl Acad Sci U S A. 2015; 112(42): 13045–50. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSteidl C, Shah SP, Woolcock BW, et al.: MHC class II transactivator CIITA is a recurrent gene fusion partner in lymphoid cancers. Nature. 2011; 471(7338): 377–81. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGreen MR, Rodig S, Juszczynski P, et al.: Constitutive AP-1 activity and EBV infection induce PD-L1 in Hodgkin lymphomas and posttransplant lymphoproliferative disorders: implications for targeted therapy. Clin Cancer Res. 2012; 18(6): 1611–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMuenst S, Hoeller S, Dirnhofer S, et al.: Increased programmed death-1+ tumor-infiltrating lymphocytes in classical Hodgkin lymphoma substantiate reduced overall survival. Hum Pathol. 2009; 40(12): 1715–22. PubMed Abstract | Publisher Full Text\n\nYamamoto R, Nishikori M, Kitawaki T, et al.: PD-1-PD-1 ligand interaction contributes to immunosuppressive microenvironment of Hodgkin lymphoma. Blood. 2008; 111(6): 3220–4. PubMed Abstract | Publisher Full Text\n\nProduct Information: OPDIVO(R) intravenous injection solution, nivolumab intravenous injection solution. Bristol-Myers Squibb Company (per FDA), Princeton, NJ. 2016.\n\nAnsell SM, Lesokhin AM, Borrello I, et al.: PD-1 blockade with nivolumab in relapsed or refractory Hodgkin's lymphoma. N Engl J Med. 2015; 372(4): 311–9. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAnsell S, Armand P, Timmerman JM, et al.: Nivolumab in Patients (Pts) with Relapsed or Refractory Classical Hodgkin Lymphoma (R/R cHL): Clinical Outcomes from Extended Follow-up of a Phase 1 Study (CA209-039). Blood. 2015; 126(23): 583. [Oral and Poster Abstracts] Reference Source\n\nMerck. Keytruda (pembrolizumab) package insert.2015; 1–22. Reference Source\n\nArmand P, Shipp MA, Ribrag V, et al.: PD-1 Blockade with Pembrolizumab in Patients with Classical Hodgkin Lymphoma after Brentuximab Vedotin Failure: Safety, Efficacy, and Biomarker Assessment. Blood. 2015; 126(23): 584. [Oral and Poster Abstracts] Reference Source\n\nSquibb BM: Opdivo (nivolumab) package insert. 2014. Reference Source\n\nGangadhar TC, Vonderheide RH: Mitigating the toxic effects of anticancer immunotherapy. Nat Rev Clin Oncol. 2014; 11(2): 91–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJohnson DB, Sullivan RJ, Ott PA, et al.: Ipilimumab Therapy in Patients With Advanced Melanoma and Preexisting Autoimmune Disorders. JAMA Oncol. 2016; 2(2): 234–40. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCecchini M, Sznol M, Seropian S: Immune therapy of metastatic melanoma developing after allogeneic bone marrow transplant. J Immunother Cancer. 2015; 3: 10. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAngenendt L, Schliemann C, Lutz M, et al.: Nivolumab in a patient with refractory Hodgkin's lymphoma after allogeneic stem cell transplantation. Bone Marrow Transplant. 2016; 51(3): 443–5. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nYared JA, Hardy N, Singh Z, et al.: Major clinical response to nivolumab in relapsed/refractory Hodgkin lymphoma after allogeneic stem cell transplantation. Bone Marrow Transplant. 2016. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nVillasboas JC, Ansell SM, Witzig TE: Targeting the PD-1 pathway in patients with relapsed classic Hodgkin lymphoma following allogeneic stem cell transplant is safe and effective. Oncotarget. 2016. PubMed Abstract | Publisher Full Text\n\nPark JH, Brentjens RJ: Adoptive immunotherapy for B-cell malignancies with autologous chimeric antigen receptor modified tumor targeted T cells. Discov Med. 2010; 9(47): 277–88. PubMed Abstract | Free Full Text\n\nMaude SL, Frey N, Shaw PA, et al.: Chimeric antigen receptor T cells for sustained remissions in leukemia. N Engl J Med. 2014; 371(16): 1507–17. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSavoldo B, Rooney CM, Di Stasi A, et al.: Epstein Barr virus specific cytotoxic T lymphocytes expressing the anti-CD30zeta artificial chimeric T-cell receptor for immunotherapy of Hodgkin disease. Blood. 2007; 110(7): 2620–30. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRadford J, Illidge T, Counsell N, et al.: Results of a trial of PET-directed therapy for early-stage Hodgkin's lymphoma. N Engl J Med. 2015; 372(17): 1598–607. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nStraus DJ, Pitcher B, Kostakoglu L, et al.: Initial Results of US Intergroup Trial of Response-Adapted Chemotherapy or Chemotherapy/Radiation Therapy Based on PET for Non-Bulky Stage I and II Hodgkin Lymphoma (HL) (CALGB/Alliance 50604). Blood. 2015; 126(23): 578. [Oral and Poster Abstracts] Reference Source\n\nHoppe RT, Advani RH, Ai WZ, et al.: Hodgkin lymphoma (version 2.2015). National Comprehensive Cancer Network. J Natl Compr Canc Netw. 2015; 13(5): 554–86. PubMed Abstract"
}
|
[
{
"id": "13610",
"date": "27 Apr 2016",
"name": "Nancy Bartlett",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13611",
"date": "27 Apr 2016",
"name": "David Straus",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13612",
"date": "27 Apr 2016",
"name": "Catherine Diefenbach",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-768
|
https://f1000research.com/articles/5-767/v1
|
27 Apr 16
|
{
"type": "Research Article",
"title": "Socioeconomic gradients in general and oral health of primary school children in Shiraz, Iran",
"authors": [
"Ali Golkari",
"Aira Sabokseir",
"Aubrey Sheiham",
"Richard G. Watt",
"Aira Sabokseir",
"Aubrey Sheiham",
"Richard G. Watt"
],
"abstract": "Background: Health status is largely determined by socio-economic status. The general health of individuals at higher social hierarchy is better than people in lower levels. Likewise, people with higher socio-economic status have better oral health than lower socio-economic groups. There has not been much work regarding the influence of socio-economic status on the health conditions of children in developing countries, particularly in Iran. The aim of this study was to compare the oral and general health conditions of primary school children of three different socio-economic areas in the city of Shiraz, Iran.Methods: This cross-sectional study was conducted on 335, 8- to 11-year-old primary schoolchildren in Shiraz. The children were selected by a three-stage cluster sampling method from three socio-economically different areas. Tools and methods used by the United Kingdom’s Medical Research Council were used to obtain anthropometric variables as indicators of general health. The Decay, Missing, Filled Teeth (DMFT) Index for permanent teeth, dmft Index for primary teeth, the Modified Developmental Defects of Enamel (DDE) Index, the Gingival Index (GI) and the Debris Index-Simplified (DI-S) were used for oral health assessment. Results: Height (P<0.001), weight (P<0.001), and BMI (P=0.001) significantly increased as the socio-economic status of area increased. GI score (P<0.001), DI-S score (P<0.001), number of permanent teeth with DDE (P=0.008), and number of DDE lesions in permanent teeth (P=0.008) significantly decreased as the socio-economic status of area increased.Discussion: Findings of this study generally confirmed that social gradients exist in both general and oral health status of the primary schoolchildren of Shiraz. The influence of socio-economic status on health condition means children have different life chances based on their socio-economic conditions. These findings emphasize the significance of interventions for tackling socio-economic inequalities in order to improve the health status of children in lower socio-economic areas.",
"keywords": [
"Health status disparities",
"Inequalities",
"Oral health",
"Socio-economic factors"
],
"content": "Introduction\n\nHealth status is largely determined by social class and socio-economic status. Understanding the association between socio-economic status and health outcomes is of great importance for planning health promotion strategies. It is generally accepted that “there is a social gradient in health”1–4. In the national trend, the gradient is the status of an individual in socio-economic hierarchy and shows that people at the top of social hierarchy have better health than those in lower levels5. In the international trend, the gradient indicates more affluent countries have better health outcomes compared to poorer countries6.\n\nThe effect of socio-economic status is shown on a wide range of health outcomes from drug misuse related diseases7 to age-specific mortality8. A study on 6 to 11 year-old children of the United States found that social class had positive association with minor and major physical disorders such as colds, infections, allergies, diabetes, and even epilepsy9. The relationship between household income and a range of health outcomes in children and adolescents has been shown in Britain10. A study in France has found a significant positive correlation between family income and some of the most important child health indicators such as anthropometric measurements11.\n\nIn consistence with general health, social gradients are shown in oral health indicators. It seems that despite the remarkable improvements in the averages of oral health indices among communities in the last decades, inequities in oral health - mostly related to social inequalities - continue to exist12,13.\n\nA study on the relationship between work conditions and health inequalities in Switzerland has found clear social gradients for almost all adverse working status and the outcomes of oral health14. In a case-control study in Mexico, lower socioeconomic status was identified as a risk factor for non-syndromic orofacial clefts15. Another study on Chinese 5-year-old children found that there were notable gradients in carious primary teeth related to their household income16. A study on young children of Salem, Tamil Nadu, India, showed that those from lower socio-economic groups, especially whose parents' had lower education were more likely to suffer from Early Childhood Caries17. It was also shown that poor socio-economic background can be a strong predictor for poor oral hygiene18.\n\nThere has been limited evidence in Iran regarding the association between socio-economic status and general and oral health gradients, particularly among children. Therefore, this study was designed to assess the existence of social gradients in oral and general health of 8- to 11-year-old primary school children in three different socio-economic areas of Shiraz, a city in Southern Iran.\n\n\nMaterial and methods\n\nThis cross-sectional study was conducted on 8- to 11-year-old children (third to fifth grade primary school children) of the city of Shiraz, Iran, in 2009. Approval and ethical permission were obtained from the National Ethical Committee in Medical Research of Iran (# 85/p/3/1095). Permission to enter the selected schools was then obtained from the Educational Head Office of the Province of Fars (# 17568/55). Based on the prevalence of Developmental Defects of Enamel (DDE) and a confidence level of 95%, a sample size of 335 was estimated appropriate for this study.\n\nA three-stage cluster sampling approach was used to select the children. The main Educational Affairs Office of Shiraz had a category which divided the city into three areas based on socio-economic status: upper, middle, and lower social class areas. This kind of division seemed more appropriate for this study than any other division, such as geographically separated zones. One boys' and one girls' school (primary schools are segregated in Iran) were selected from each of the three socio-economically different areas. This was done by simple randomization using the list of primary schools in each area. Then, two classes were randomly selected in each school from the third, forth, and fifth grades. All children present in each selected class were included in the study, only if their parents provided written consent.\n\nAlthough socio-economic differences between the three areas were well recognized by officials (Educational Head Office 2006), the number of parents having an occupation (any job), and the number of parents having a permanent occupation (as a job security indicator) were used as socio-economic related variables to compare the three areas and confirm the socio-economic difference between children chosen from these areas19,20. Related information was obtained from schools' administration offices.\n\nHeight and weight are valuable indicators of present and past health status. Dividing the body height into trunk and leg length provides more precise information particularly on nutrition status of the early years of life21,22. Standing height, leg length, weight, and BMI (Body Mass Index) were used in this study as indicators of general health.\n\nTo obtain children's height and weight, the tools and methods used by United Kingdom’s Medical Research Council were adopted22. For weight, a digital scale (Beurer Electronic Weight Scale PS 07, Germany) with accuracy of 100 grams was used. It was calibrated in each school. A wall mounted height meter with accuracy of millimetres was used for measuring children's standing height. A similar metre adjusted to the seat of a chair was used to measure the length of the upper trunk, from head to the chair’s seat (sitting height). The leg length was calculated by deduction of the sitting height from the standing height. BMI was calculated by dividing the weight by the square of the standing height. Identically calibrated tools were used for all cases in all schools.\n\nAssessment of dental caries, DDE and gingival health determined the oral health status of children. Clinical intra-oral examinations were carried out using WHO screening criteria to record data on Decay, Missing, and Filled Teeth (dmft) for the primary dentition and DMFT for the permanent dentition23. Permanent teeth were assessed from first molar to first molar in each arch. Therefore, second permanent molars, if present, were not assessed. DDEs of permanent teeth were recorded based on the Modified DDE Index24. Gingival health and oral hygiene were assessed using the Gingival Index (GI)25,26 and the Debris Index – Simplified (DI-S)27. All examinations were carried out in classrooms using natural light, disposable mirrors and tongue blades.\n\nNormality of distribution of each outcome variable was assessed by a histogram. All continuous variables had a distribution close to normal. The difference between sexes was analysed by a t-test. Two socio-economic variables of number of parents with any occupation and with a permanent occupation were compared among the three areas using one-way ANOVA. Anthropometric measurements, gingival health, and oral hygiene status were also assessed among the three areas by one-way ANOVA. Anthropometric measurements (linear regression), gingival health status, and oral hygiene status (quantile regression) were also compared among the three areas after adjusting for sex and age. DMFT, dmft, number of teeth needed treatment, number of permanent teeth with DDE and total number of DDEs in children’s permanent dentition were compared between areas using Poisson regression model after adjusting for sex and age, and number of permanent teeth present in the mouth. SPSS statistical package (version 14) and STATA statistical package (version 10 Intercooled) were used. The significance level was set at α=0.05.\n\n\nResults\n\nConsent forms were sent for 376 parents, out of which 335 accepted to participate (response rate = 89.1%). Table 1 shows the number of cases examined in each area by sex.\n\nThe number of parents with an occupation (P < 0.001) and with a permanent occupation (P < 0.001) significantly increased from the lower socioeconomic to the higher socioeconomic area (Table 1). These results confirm that the three areas were socio-economically different.\n\nGirls were slightly heavier and taller, but had shorter leg length than boys. All anthropometric variables had distributions close to normal. Children in lower socio-economic neighbourhoods were shorter and lighter, and had shorter legs. Even after adjustments were made for sex and age, still all anthropometric variables: height (P < 0.001), weight (P < 0.001), BMI (P = 0.001) and leg length (P < 0.001) of children significantly increased as the socio-economic status of area increased. These findings demonstrated clear social gradient in the general health status among Shiraz primary school children.\n\nThe average number (± standard deviation) of present deciduous teeth was 6.2 (± 4.3). Number of permanent teeth present in the mouth ranged from four to 24 with an average of 16 fully erupted permanent teeth per child (Table 2). Number of present permanent teeth was significantly higher in girls (mean = 18.1) than in boys (mean = 13.6). The difference remained statistically significant after adjustment for age (P < 0.001).\n\n(1) Adjustments made only for number of permanent teeth.\n\n(2) Adjustments made for number of permanent teeth, sex, and age.\n\nForty nine percent (164) of children had a DDE. There was no difference between the percentages of boys and girls having a DDE in permanent teeth. Table 2 shows the number of permanent teeth with DDE and the total number of DDEs in permanent teeth. Both variables increased as socio-economic status of area decreased. The trends were statistically significant for number of permanent teeth with DDE (P = 0.018) and the total number of DDEs in permanent teeth (P = 0.025) after adjusting for number of present permanent teeth in the mouth. The significance levels increased (P = 0.008 for both variables) after adjusting for age and sex in the regression model.\n\nThe average dmft (of the primary dentition) was 2.8 ± 2.5. Three quarters of the cases (75.2%) had a dmft of 1 or more. The average DMFT (of the permanent dentition) was 1.22 ± 1.5. Almost half of the sample (47.5%) had caries experience in their permanent teeth. DMFT increased from 0.7 in 8-year-olds to 1.4 in 11-year-olds. Although the mean DMFT was higher in girls (1.3) than in boys (1.0) (P = 0.02), the difference was not significant after adjustments for age and number of permanent teeth (P = 0.42).\n\nThere was no statistically significant trend in DMFT or dmft among areas. Children in the middle class area had the highest caries prevalence and highest need for treatment among all three areas. Although a clear path of social gradients was not observed, total number of teeth with treatment need was significantly lower in children in high socio-economic area compared with other children (P = 0.006). There was also a significant difference in mean number of deciduous teeth with treatment need between the high socio-economic area and the two other areas (P = 0.005) (Table 3).\n\nA considerable number of children had gingival inflammation. Average GI score was 0.18 with only 82% of children being scored 0. The average DI-S was 0.52. The difference between the sexes was not statistically significant (P = 0.43 for GI and P = 0.44 for DI-S).\n\nThe gingival health significantly improved as the socio-economic status of area increased (P < 0.001). The significance did not change after adjustments for sex and age. There was also significant trend in oral hygiene status (P < 0.001). The number of children with dental plaque (P < 0.001), and also the average level of dental plaque in children (P < 0.001) decreased as the socio-economic status of area increased (Table 4).\n\n\nDiscussion\n\nFindings of this study generally confirmed that social gradients exist in both general and oral health status of the primary school children of Shiraz. Children in lower socio-economic areas were shorter and lighter, and had shorter legs. In terms of oral health, socio-economic status had more effects on gingival inflammation, levels of plaque, and specially occurrence of DDEs, but was less related to dental caries experience and caries treatment need.\n\nMost findings of this study were consistent with those of similar studies in other parts of the world. As an example, the social gradients seen in the anthropometric measurements were similar to those presented among French children11. One of the strong relationships found in this study was between the area of living and the state of oral hygiene determined by DI-S. This finding was in accordance with the findings of a recent study by Mathur et al. in India18. They had also divided a city, Delhi, into three socio-economically different areas and found that children in poorer areas were more susceptible for poorer oral hygiene.\n\nIn the current study, social gradient could not been shown in DMFT or dmft of studied children. Further research revealed that similar conditions had been reported by others. As an example, Sagheri et al. (2009) reported a social gradient in using preventive dental services among children of Ireland, but no such trend in DMFT of the same children28. To justify such findings, one could blame the nature and shortcomings of the DMF Index or complexity of the risk factors for dental caries.\n\nDDE is probably the most important oral health indicator assessed in this study. Presence of DDE on teeth can be an index of both general and oral health. Many early childhood adverse health conditions and diseases can increase the risk of developing a DDE on permanent dentition29. Despite the importance of DDE as a health indicator, few studies have tried to assess the relationship of the prevalence of DDE, especially on permanent teeth, with socio-economic factors. One of such studies has been conducted by Basha et al. that reports a significant negative association between the presence of DDE and socio-economic status of children30, a finding that is very similar to what is shown in the current study.\n\nThe influence of socio-economic status on health condition means children have different life chances based on their birthplace, or area of living, even inside one city. If they live in a higher socio-economic zone, they would have a higher chance for better oral and general health in comparison to their peers in neighboring lower socio-economic zones. These findings could help policymakers to make intervention decisions that might help to improve the health status of children in lower socio-economic areas.\n\nBearing in mind that no clear social class determinant or assessment tool exists in Iran, the authors decided to use the school area as the best available indicator of subjects' social class. Assessing the job status of parents acted as a proof that the selected groups of children were really from different backgrounds. Therefore, it seems fair to say that this study has been able to illustrate that oral health follows the other aspects of health in having gradients according to socio-economic status.\n\nAs oral health and general health follow the social gradients, tackling health inequalities would need identifying and understanding the underlying causes of problems31. Upstream measures would be needed to build a society that could reinforce good oral and general health. Future assessment of the relationship between social gradients in oral health and general health is recommended.\n\n\nConclusion\n\nThere are social gradients in general and oral health among primary school children of Shiraz, Iran. The gradient in oral health seems to follow the same pattern in general health.\n\n\nConsent\n\nWritten informed consent for participation in the study was obtained from the parents of the children.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data, 10.5256/f1000research.8641.d12061232.",
"appendix": "Author contributions\n\n\n\nThe study was conceived and designed by AG, Ash, and RGW. AG and ASa carried out the research. AG analyzed the data. All authors were involved in preparation of the first draft. AG and ASa finalized the manuscript. The data for this study were extracted from a PhD thesis by AG under supervision of RGW and ASh. ASa was involved in data collection and preparation of the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nMacintyre S: Understanding the social patterning of health: the role of the social sciences. J Public Health Med. 1994; 16(1): 53–9. PubMed Abstract\n\nMarmot MG, Smith GD, Stansfeld S, et al.: Health inequalities among British civil servants: the Whitehall II study. Lancet. 1991; 337(8754): 1387–93. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nStarfield B, Robertson J, Riley AW: Social class gradients and health in childhood. Ambul Pediatr. 2002; 2(4): 238–46. PubMed Abstract\n\nEmerson E, Graham H, Hatton C: Household income and health status in children and adolescents in Britain. Eur J Public Health. 2006; 16(4): 354–60. PubMed Abstract | Publisher Full Text\n\nApouey BH, Geoffard PY: Child health and access to health care in France: Evidence on the role of family income. Rev Epidemiol Sante Publique. 2014; 62(3): 179–90. PubMed Abstract | Publisher Full Text\n\nLocker D: Deprivation and oral health: a review. Community Dent Oral Epidemiol. 2000; 28(3): 161–9. PubMed Abstract | Publisher Full Text\n\nKumar S, Kroon J, Lalloo R: A systematic review of the impact of parental socio-economic status and home environment characteristics on children's oral health related quality of life. Health Qual Life Outcomes. 2014; 12: 41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHämmig O, Bauer GF: The social gradient in work and health: a cross-sectional study exploring the relationship between working conditions and health inequalities. BMC Public Health. 2013; 13: 1170. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAcuña-González G, Medina-Solís CE, Maupomé G, et al.: Family history and socioeconomic risk factors for non-syndromic cleft lip and palate: a matched case-control study in a less developed country. Biomedica. 2011; 31(3): 381–91. PubMed Abstract\n\nGuan Y, Zeng X, Tai B, et al.: Socioeconomic inequalities in dental caries among 5-year-olds in four Chinese provinces. Community Dent Health. 2015; 32(3): 185–9. PubMed Abstract | Publisher Full Text\n\nStephen A, Krishnan R, Ramesh M, et al.: Prevalence of early childhood caries and its risk factors in 18–72 month old children in Salem, Tamil Nadu. J Int Soc Prev Community Dent. 2015; 5(2): 95–102. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMathur MR, Tsakos G, Parmar P, et al.: Socioeconomic inequalities and determinants of oral hygiene status among Urban Indian adolescents. Community Dent Oral Epidemiol. 2016; 44(3): 248–54. PubMed Abstract | Publisher Full Text\n\nSiegrist J, Theorell T: Socioeconomic position and health: the role of work and employment. In: Siegrist J, Marmot M, editors. Social inequalities in health: new evidence and policy implication. Oxford: Oxford University Press; 2006; 73–100.\n\nWilkinson R, Marmot M: Social determinants of health: the solid facts. 2nd ed. Copenhagen: World Health Organization, Regional Office for Europe; 2003. Reference Source\n\nLangenberg C, Hardy R, Kuh D, et al.: Influence of height, leg and trunk length on pulse pressure, systolic and diastolic blood pressure. J Hypertens. 2003; 21(3): 537–43. PubMed Abstract\n\nWadsworth ME, Hardy RJ, Paul AA, et al.: Leg and trunk length at 43 years in relation to childhood health, diet and family circumstances; evidence from the 1946 national birth cohort. Int J Epidemiol. 2002; 31(2): 383–90. PubMed Abstract | Publisher Full Text\n\nWorld Health Organization: Oral health surveys: basic methods. 4th Edition, Geneva: World Health Organization Publication; 1997. Reference Source\n\nClarkson J, O'Mullane D: A modified DDE Index for use in epidemiological studies of enamel defects. J Dent Res. 1989; 68(3): 445–50. PubMed Abstract | Publisher Full Text\n\nLöe H: The Gingival Index, the Plaque Index and the Retention Index Systems. J Periodontol. 1967; 38(6 Suppl): 610–6. PubMed Abstract | Publisher Full Text\n\nLoe H, Silness J: Periodontal disease in pregnancy. I. Prevalence and severity. Acta Odontol Scand. 1963; 21(6): 533–51. PubMed Abstract | Publisher Full Text\n\nGreene JG, Vermillion JR: The simplified oral hygiene index. J Am Dent Assoc. 1964; 68(1): 7–13. PubMed Abstract | Publisher Full Text\n\nSagheri D, McLoughlin J, Clarkson JJ: The prevalence of dental caries and fissure sealants in 12 year old children by disadvantaged status in Dublin (Ireland). Community Dent Health. 2009; 26(1): 32–7. PubMed Abstract\n\nMemarpour M, Golkari A, Ahmadian R: Association of characteristics of delivery and medical conditions during the first month of life with developmental defects of enamel. BMC Oral Health. 2014; 14: 122. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBasha S, Mohamed RN, Swamy HS: Prevalence and associated factors to developmental defects of enamel in primary and permanent dentition. Oral Health Dent Manag. 2014; 13(3): 588–94. PubMed Abstract\n\nWatt RG: From victim blaming to upstream action: tackling the social determinants of oral health inequalities. Community Dent Oral Epidemiol. 2007; 35(1): 1–11. PubMed Abstract | Publisher Full Text\n\nGolkari A, Sabokseir A, Sheiham A, et al.: Dataset 1 in: Socioeconomic gradients in general and oral health of primary school children in Shiraz, Iran. F1000Research. 2016. Data Source"
}
|
[
{
"id": "13621",
"date": "16 May 2016",
"name": "Tayebeh Malek Mohammadi",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript reported very important subject in oral health' field, seems sound and very well written. It is acceptable for indexation. I suggest the authors should address some studies regarding oral health and general health and also oral health and socio-economic factors which have been reported in Iran.",
"responses": []
},
{
"id": "13930",
"date": "24 May 2016",
"name": "Myung Ki",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe theme of this paper is, to my mind, very interesting (socioeconomic inequalities in general and dental health) and various general and dental measures with trustable definition are plus. The design and data analysis seem acceptable to support the conclusion. Thus, I believe that this paper merits indexation, but there is a few points to be addressed / discussed more.\n\nFor anthropometric variables, authors describe: “Even after adjustments were made for sex and age, still all anthropometric variables: height (P < 0.001), weight (P < 0.001), BMI (P = 0.001) and leg length (P < 0.001) of children significantly increased as the socioeconomic status of area increased.”\nHowever, no actual results on this appear in the table and please check in which table the result is shown. If this finding is less important and authors decided not to present the data, please indicate that “data is not presented”.\n\nIt is not clear why two p values are presented in the table 1 and I think it would be four p-values per each column. Similarly, only two p-values were presented in the table 2, instead of four as to four measures. I am sorry, if misunderstanding is mine.\n\nFor presentation of table 1, I wonder whether the use of Odds Ratio is proper approach. I think instead of OR, presenting different proportions for three area groups and statistical test with Chi-square would be relevant and complementary to other results in table 1, for example, Chi-square test for “having at least one jobless parent” for three area levels.\n\nUse of area level SEP could be more justifiable, if the parents are actual residents of the areas to which their siblings attend, if additional information of this kind is available.",
"responses": []
},
{
"id": "13623",
"date": "25 May 2016",
"name": "Ali Kazemian",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI found this article worth indexing. Well organized, well written.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-767
|
https://f1000research.com/articles/5-764/v1
|
27 Apr 16
|
{
"type": "Review",
"title": "Regulation of Microtubule Dynamics in Axon Regeneration: Insights from C. elegans",
"authors": [
"Ngang Heok Tang",
"Andrew D. Chisholm",
"Ngang Heok Tang"
],
"abstract": "The capacity of an axon to regenerate is regulated by its external environment and by cell-intrinsic factors. Studies in a variety of organisms suggest that alterations in axonal microtubule (MT) dynamics have potent effects on axon regeneration. We review recent findings on the regulation of MT dynamics during axon regeneration, focusing on the nematode Caenorhabditis elegans. In C. elegans the dual leucine zipper kinase (DLK) promotes axon regeneration, whereas the exchange factor for Arf6 (EFA-6) inhibits axon regeneration. Both DLK and EFA-6 respond to injury and control axon regeneration in part via MT dynamics. How the DLK and EFA-6 pathways are related is a topic of active investigation, as is the mechanism by which EFA-6 responds to axonal injury. We evaluate potential candidates, such as the MT affinity-regulating kinase PAR-1/MARK, in regulation of EFA-6 and axonal MT dynamics in regeneration.",
"keywords": [
"DLK-1",
"EFA-6",
"PAR-1/MARK"
],
"content": "Introduction\n\nMore than a hundred years ago, Ramon y Cajal was the first to describe how individual axons respond to injury1. Many types of axons regenerate, including neurons in the peripheral nervous system (PNS), re-forming growth cones similar to those that Ramon y Cajal had characterized during development. In contrast, neurons of the mammalian central nervous system (CNS) often fail to regenerate, and their damaged ends form swollen, non-motile structures later termed retraction bulbs. These fundamental observations set the stage for subsequent exploration of why regenerative capacity varies drastically between the CNS and PNS. Many studies have focused on the inhibitory environment of the adult mammalian CNS2–4. However, it is becoming evident that cell-intrinsic processes are also key determinants of axon regeneration5. Among these intrinsic factors, regulation of axonal microtubule (MT) dynamics has emerged as a major influence on the capacity of an axon to regrow effectively6–10. Most strikingly, pharmacological stabilization of MTs by paclitaxel or related molecules enhances axon regeneration in vitro and in vivo, suggesting a potentially therapeutically significant role for MT dynamics in axon regeneration11–13.\n\nThe nematode C. elegans has long been used for studies in neuronal development and behavior, owing to its short life cycle, genetic tractability, and ease of in vivo imaging. The nervous system of an adult C. elegans hermaphrodite consists of 302 neurons of nearly invariant lineage14. A decade ago, a pioneering study showed that axons of mature C. elegans neurons can regenerate after precise laser axotomy15. Several kinds of neuron display robust axon regeneration; most work has focused on the mechanosensory and motor axons (Figure 1A)16,17. The genetic tractability and ease of imaging in vivo have made C. elegans a rising star in axon regeneration studies. Several laboratories have used large-scale genetic18, chemical19, and RNA interference (RNAi)20 screens to identify genes or molecules that regulate axon regeneration. These studies have identified several new players in axon regeneration, including the dual leucine zipper kinase (DLK) and mixed lineage kinase (MLK) mitogen-activated protein kinase (MAPK) pathways21,22, Notch signaling pathway23, insulin signaling pathway24, and microRNA25. Some pathways, such as DLK signaling, have been shown to function in axon regeneration in vertebrates26–29, suggesting that axon regeneration factors identified in C. elegans may be suitable for translational studies. Here, we review the role of MT dynamics in axon regeneration, primarily focusing on C. elegans.\n\n(A) Illustration of the positions of the mechanosensory neurons anterior lateral microtubule (ALM) and posterior lateral microtubule (PLM) cells (top) and the GABAergic motor neurons dorsal D (DD) and ventral D (VD) (bottom). (B) Examples of PLM axon regeneration in wild-type, dlk-1(lf), and efa-6(lf) at 24 hours post-axotomy. dlk-1(lf) mutant (middle) shows decreased axon regeneration, whereas efa-6(lf) mutant (bottom) shows increased axon regeneration upon axotomy, compared with wild-type (top). Scale bar, 20 µm. DLK, dual leucine zipper kinase.\n\n\nAxonal microtubule organization before and after injury\n\nMTs are among the major cytoskeletal structures in cells. MTs are cylindrical and polarized polymers formed by αβ-tubulin heterodimers arranged in a head-to-tail configuration30. In vitro and in vivo MTs undergo rapid growth (i.e. polymerization) and shrinkage (i.e. depolymerization) at their plus ends, a behavior known as dynamic instability31. Minus ends of MTs are relatively stable but can also undergo polymerization and depolymerization. MT dynamics in vivo are influenced by many factors, including concentration of free tubulin monomers and tubulin post-translational modifications, and by MT-binding proteins. MT plus-end dynamics are regulated by a large cohort of plus end-tracking proteins (+TIPs)32; relatively few minus end-targeting proteins (−TIPs) have been identified that regulate MT minus ends33. Together, these proteins affect the frequency of catastrophe (switching from growth to shrinkage) and rescue (switching from shrinkage to growth) events.\n\nIn contrast to the highly dynamic behavior of MTs in dividing or migrating cells, axonal MTs of mature neurons are relatively stable, forming a consistent architecture that maintains neuronal polarity and allows directed axonal transport34. Axonal MTs in C. elegans were first characterized in the MT-rich mechanosensory neurons35,36. More recent imaging of the dynamics of plus end-binding proteins indicates that, as in other organisms, C. elegans axonal MTs are consistently arranged with plus ends away from the soma (‘plus end out’) but that dendritic MTs either are oriented with minus ends out or have mixed orientation37,38.\n\nAfter axon injury, the stable axonal MTs become highly dynamic to allow axonal regrowth and establishment of a new growth cone6,7. In cultured Aplysia californica neurons, injury triggers rapid MT depolymerization followed by repolymerization with aberrant MT orientation39,40. Reversal of MT polarity after injury has been observed in Drosophila dendrites41,42. In addition, axotomy triggers an acute change of MT dynamics in Drosophila41,43,44. In C. elegans, axotomy of the mechanosensory posterior lateral microtubule (PLM) neuron triggers an increase in growing MTs locally at the injury site, followed by persistent growth of MTs that leads to formation of functional growth cones37. A mutation in mec-7/β-tubulin that hyperstabilizes MTs in touch neurons inhibits anterior lateral microtubule (ALM) axon regeneration, suggesting that precise regulation of MT dynamics is essential for axon regeneration45. Regenerating axon tips in severed mouse neurons display an acute increase in MT dynamics, followed by a sustained increase over several days46. Collectively, these findings suggest that axonal injury initiates an intricate series of changes in axonal MT organization.\n\n\nThe DLK-1 MAPK cascade promotes axon regeneration, in part via microtubule dynamics\n\nThe DLK MAPK pathway was identified several years ago as essential for axon regeneration in C. elegans motor neurons and in mechanosensory neurons21,22. Mutants lacking DLK-1 [dlk-1(lf)] display normal developmental axon growth but are unable to regenerate after injury, being blocked at the initial phase of growth cone reformation (Figure 1B). Conversely, overexpression of dlk-1 [dlk-1(gf)] enhances axon regeneration21,22. A mammalian DLK-1 homolog MAP3K13/LZK can functionally substitute for dlk-147, suggesting a high degree of conservation of the DLK pathway in axon regeneration. Indeed, in mammals, DLK is also required for axon regeneration after axonal injury26–29.\n\nDLK-1 activity is required cell-autonomously at the time of regrowth, and DLK-1 itself is likely activated by injury signals. An axotomy-triggered Ca2+ transient has been implicated in DLK-1 activation47–49. In addition, the DLK pathway is sensitive to MT depolymerization. Mutations disrupting MTs trigger a DLK-dependent reduction of protein levels in touch neurons50. In Drosophila, loss of Short stop (shot), a member of the spectraplakin family that crosslinks actin and MT51,52, activates the DLK signaling pathway to promote axon regeneration53. Moreover, disruption of MTs by nocodazole in mammalian sensory neurons activates the DLK signaling pathway54. As yet, it remains unclear how MT polymerization is sensed by DLK.\n\nActivation of the DLK pathway leads to two major outputs in C. elegans: a transcriptional response involving the CEBP-1 bZip transcription factor and CEBP-1-independent effects on axonal MT dynamics. The dlk-1(lf) mutant fails to increase persistent MT growth after axotomy, whereas dlk-1(gf) shows increased number of growing axonal MTs, both before and after axotomy37. Following laser injury, the DLK pathway promotes MT dynamics and growth, through downregulation of the kinesin-13 KLP-7 and upregulation of the cytosolic carboxypeptidase CCPP-637. Thus, the DLK cascade is closely interconnected with MTs, both as a sensor of MT integrity and as a regulator of MT dynamics, making it well placed to mediate regenerative reorganization of the axonal MT cytoskeleton after injury.\n\n\nEFA-6, an inhibitor of axon regeneration acting via microtubule dynamics\n\nThe above studies of DLK-1 have helped spur efforts to identify additional factors that control MT dynamics during axon regeneration. Using a large-scale genetic screen, we identified the evolutionarily conserved protein EFA-6 (exchange factor for Arf-6) as a cell-intrinsic suppressor of axon regeneration18. Loss-of-function mutations of efa-6 [efa-6(lf)] enhance axonal regeneration, whereas efa-6 overexpression [efa-6(gf)] blocks regeneration (Figure 1B). Uniquely, efa-6(lf) partially bypasses the requirement for DLK-1 in axonal regeneration18, suggesting that EFA-6 and DLK-1 have antagonistic effects on a common process. Multiple lines of evidence suggest that EFA-6 inhibits axon regeneration through modulation of MT dynamics18,55.\n\nThe EFA-6/EFA6 protein family is conserved from yeast to mammals. EFA-6 contains a Sec7 domain that confers guanine exchange activity (GEF) for Arf6 GTPases56. Four EFA6 members (EFA6A–EFA6D) have been identified in mammals and three of them (except EFA6B) are expressed in neurons57,58. EFA6 localizes to the plasma membrane through its pleckstrin homology (PH) domain56. Furthermore, EFA6 can interact with filamentous actin in vitro through its PH domain and plays important roles in regulation of cortical actin cytoskeleton in vertebrate cells56,57,59–61. In C. elegans, efa-6 suppresses the embryonic lethality caused by mutations in dynein, a MT motor62, suggesting a functional linkage between actin and MT cytoskeletons at the cell cortex. In the one-cell C. elegans embryo, EFA-6 localizes to the plasma membrane, with enrichment in the anterior cortex in late one-cell embryo, to limit MT growth throughout the cell cortex62,63. The plasma membrane localization of EFA-6 is dependent upon the presence of its PH domain, whereas the intrinsically disordered N-terminal domain confers the enrichment at the anterior cell cortex63. The N-terminal region of EFA-6 contains a conserved 18-amino acid (18-aa) motif (Figure 2), which is essential for the MT growth-inhibiting activity.\n\n(A) EFA-6 protein domain organization in different organisms. Red boxes in the EFA-6 N-terminus highlight a conserved 18-aa motif, found in both Caenorhabditis elegans and Drosophila63. (B) Plot of intrinsic protein disorder score for C. elegans EFA-6. Different domains of EFA-6 are color-coded as in (A). Note that EFA-6 N-terminus has an overall high disorder probability, apart from the 18-aa motif. Figure adapted from 55.\n\nIn mature uninjured neurons, EFA-6 also localizes to the cell cortex via its C-terminal PH domain55. Upon axotomy, EFA-6 rapidly (within minutes) relocalizes to puncta close to sites containing MT minus ends, as marked by the minus end-binding protein PTRN-1/Patronin55,64. Relocalization of EFA-6 is dependent on the intrinsically disordered N-terminal domain and plays important roles in inhibition of axon regeneration (Figure 3A). In addition, the N-terminal domain of EFA-6 binds to the MT-associated proteins TAC-1/TACC (transforming acidic coiled-coil) and ZYG-8/DCLK (double-cortin-like kinase). Both TAC-1 and ZYG-8 are required for regenerative growth cone formation after axonal injury55. Although the roles of mammalian EFA6 family members in axon regeneration remain to be examined, Xenopus TACC3 promotes axon outgrowth in embryonic cultured neural crest cells65, and DCLK is required in mammalian axon regrowth66, suggesting potential functional conservation from C. elegans to mammals.\n\n(A) Model for the regulation of EFA-6. In steady-state axons, EFA-6 localizes to the plasma membrane through its pleckstrin homology (PH) domain. Upon axon injury, EFA-6 and TAC-1/TACC (transforming acidic coiled-coil) relocalize close to the microtubule (MT) minus ends as defined by PTRN-1/Patronin puncta. The N-terminal intrinsically disordered region of EFA-6 is necessary and sufficient for relocalization and binding to TAC-1. (B) In one-cell embryos, PAR-1 and PAR-2 localize to the posterior cortex. This localization restricts the PAR-3/PAR-6/aPKC polarity complex to the anterior cortex. EFA-6 is enriched at the anterior cortex, dependent on the intrinsically disordered N-terminal domain. Such polarity complexes could regulate EFA-6 localization.\n\n\nEFA-6, cell polarity proteins, and microtubule dynamics\n\nCurrent evidence suggests that EFA-6 has bifunctional roles, as an MT destabilizing factor at the cell cortex in the steady state and relocalizing to the vicinity of MT minus ends after injury55. The molecular mechanisms involved in the transitions between these putative EFA-6 activity/localization states remain unknown. However, the intrinsically disordered N-terminal domain appears to be key to understanding the functions of EFA-6 with respect to MT dynamics. All EFA6 family members contain large N-terminal domains that are predicted to be intrinsically disordered (Figure 2A). Within the N-terminal domain, the sole region of primary sequence conservation is the 18-aa motif conserved in C. elegans and other invertebrate EFA6 family members and partly recognizable in some vertebrate EFA6 members. This motif contains potential phosphorylation sites, mutation of which abolishes the relocalization and regeneration-inhibiting activities of EFA-655. However, the identity of upstream kinases or phosphatases remains unknown; DLK-1 does not appear to be required for injury-triggered relocalization of EFA-6.\n\nAs the phosphorylation status of EFA-6 is tightly correlated to its MT dynamics-regulating activity55, the kinase or kinases responsible for EFA-6 phosphorylation may also have MT dynamics-regulating activity, directly or indirectly. Furthermore, like EFA-6, such kinases may also regulate MT dynamics in early embryo. Many candidates, including PAR-1/MARK (MT affinity-regulating kinase) and polo-like kinase, have been implicated in MT dynamics in embryos and neurons67,68, although none of these kinases has yet been associated with EFA-6 phosphorylation. Here, we focus on PAR-1/MARK and summarize the known functions of PAR-1/MARK in neurons and embryos that may be relevant to axon regeneration.\n\nPAR-1/MARK is one of the PAR (partitioning defective) proteins, first identified in C. elegans for their roles in polarization of the early embryo69. PAR-1 encodes a serine/threonine kinase related to the MARKs70. Misregulation of PAR-1 and its phosphorylation targets has long been implicated in neuronal diseases such as Alzheimer’s disease and autism71,72. In mammalian neurons, MARK phosphorylates the MT-associated proteins (MAPs) tau, MAP2, and MAP4, causing these MAPs to dissociate from MTs and thereby destabilizing the MT network and increasing MT dynamics70. Furthermore, expression of MARK in cultured neurons promotes neurite outgrowth73. Neurite outgrowth involves a pioneer population of dynamic MTs that invades growth cones, followed by MT stabilization in axon extension74. These studies suggest that PAR-1/MARK plays key roles in MT plasticity during neurite outgrowth; less is known of its roles in axon regeneration.\n\nPAR-1/MARK can regulate MT dynamics in many cell types75–79. In C. elegans one-cell embryos, PAR-1, together with its partner PAR-2, accumulates at the posterior cortex80. This localization prevents the anterior polarity complex, PAR-3/PAR-6/aPKC, from concentrating at the posterior cortex81,82 (Figure 3B). Intriguingly, MTs are more dynamic at the posterior end of an embryo, dependent on the asymmetric distribution of PAR proteins, including PAR-175. It is possible that PAR-1 regulates localization of EFA-6, causing an enrichment of EFA-6 at the anterior cortex (Figure 3B). Interactions between PAR network proteins and EFA-6 in the early embryo have not yet been tested but could affect regulation of cortical MT dynamics.\n\n\nConcluding remarks\n\nRecent studies have highlighted the importance of MT dynamics in regulation of axon regeneration. Several players, including DLK-1 and EFA-6, have been identified to regulate MT dynamics upon axon injury. However, many questions remain unexamined (see “Outstanding issues”). Importantly, pharmacological stabilization of MTs enhances axon regeneration both in vitro and in vivo, highlighting the therapeutic potential of MT dynamics regulation in axon regeneration. We anticipate that future studies should elucidate these mechanisms, which are potentially relevant to therapeutic interventions aimed at promoting regenerative axon growth.\n\n\nOutstanding issues\n\nEFA-6 rapidly relocalizes close to the MT minus ends to inhibit MT dynamics upon axon injury. This relocalization may be controlled by phosphorylation of the intrinsically disordered N-terminus of EFA-6. However, the signals (kinases/phosphatases) that might trigger EFA-6 relocalization or function remain to be discovered. Identification of these signals will bring crucial insights into how the activity of EFA-6 is regulated, possibly allowing precise manipulation of EFA-6 activity in a regrowing axon.\n\nUpon axotomy, DLK-1 promotes MT dynamics and growth, whereas EFA-6 relocalizes close to the MT minus ends to inhibit MT dynamics. Both proteins seem to affect axon regeneration by regulating MT dynamics. Intriguingly, efa-6(lf) can partially bypass the requirement of DLK-1 in axon regeneration. However, how EFA-6 interacts with the DLK-1 pathway remains unclear. It is of great interest to investigate these issues further to provide a better understanding of how MT dynamics control axon regeneration.\n\nIdentification of EFA-6 as a cell-intrinsic inhibitor of axon regeneration in C. elegans raises the question of whether any of the four mammalian EFA6 family members are involved in mammalian axon regeneration or axonal MT dynamics or both. Like C. elegans EFA-6, mammalian EFA6 family members all contain large N-terminal domains that are predicted to be intrinsically disordered. EFA6A, EFA6C, and EFA6D are expressed in the nervous system, but their roles in axon regeneration have yet to be assessed. Given evidence that partial stabilization of MT dynamics can improve axon regeneration in vertebrates, manipulation of specific MT destabilizing factors such as EFA-6 might allow a more targeted approach to enhancing regrowth in a therapeutic context.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nWork in the Andrew D. Chisholm and Yishi Jin lab on axon regeneration is supported by NIH R01 NS093588 (to Andrew D. Chisholm and Yishi Jin).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe thank Fumio Motegi and members of the Andrew D. Chisholm and Yishi Jin labs for comments.\n\n\nReferences\n\nRamon y Cajal S, Defelipe J, Jones EG: Cajal's degeneration and regeneration of the nervous system. New York, Oxford University Press. 1991. Publisher Full Text\n\nGeoffroy CG, Zheng B: Myelin-associated inhibitors in axonal growth after CNS injury. Curr Opin Neurobiol. 2014; 27: 31–8. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFilbin MT: Myelin-associated inhibitors of axonal regeneration in the adult mammalian CNS. Nat Rev Neurosci. 2003; 4(9): 703–13. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nYiu G, He Z: Glial inhibition of CNS axon regeneration. Nat Rev Neurosci. 2006; 7(8): 617–27. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJin Y: Unraveling the mechanisms of synapse formation and axon regeneration: the awesome power of C. elegans genetics. Sci China Life Sci. 2015; 58(11): 1084–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChisholm AD: Cytoskeletal dynamics in Caenorhabditis elegans axon regeneration. Annu Rev Cell Dev Biol. 2013; 29: 271–97. PubMed Abstract | Publisher Full Text\n\nBradke F, Fawcett JW, Spira ME: Assembly of a new growth cone after axotomy: the precursor to axon regeneration. Nat Rev Neurosci. 2012; 13(3): 183–93. 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PubMed Abstract | Publisher Full Text\n\nStone MC, Nguyen MM, Tao J, et al.: Global up-regulation of microtubule dynamics and polarity reversal during regeneration of an axon from a dendrite. Mol Biol Cell. 2010; 21(5): 767–77. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSong Y, Ori-McKenney KM, Zheng Y, et al.: Regeneration of Drosophila sensory neuron axons and dendrites is regulated by the Akt pathway involving Pten and microRNA bantam. Genes Dev. 2012; 26(14): 1612–25. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nChen L, Stone MC, Tao J, et al.: Axon injury and stress trigger a microtubule-based neuroprotective pathway. Proc Natl Acad Sci U S A. 2012; 109(29): 11842–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLu W, Lakonishok M, Gelfand VI: Kinesin-1-powered microtubule sliding initiates axonal regeneration in Drosophila cultured neurons. Mol Biol Cell. 2015; 26(7): 1296–307. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKirszenblat L, Neumann B, Coakley S, et al.: A dominant mutation in mec-7/β-tubulin affects axon development and regeneration in Caenorhabditis elegans neurons. Mol Biol Cell. 2013; 24(3): 285–96. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKleele T, Marinković P, Williams PR, et al.: An assay to image neuronal microtubule dynamics in mice. Nat Commun. 2014; 5: 4827. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nYan D, Jin Y: Regulation of DLK-1 kinase activity by calcium-mediated dissociation from an inhibitory isoform. Neuron. 2012; 76(3): 534–48. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGhosh-Roy A, Wu Z, Goncharov A, et al.: Calcium and cyclic AMP promote axonal regeneration in Caenorhabditis elegans and require DLK-1 kinase. J Neurosci. 2010; 30(9): 3175–83. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPinan-Lucarre B, Gabel CV, Reina CP, et al.: The core apoptotic executioner proteins CED-3 and CED-4 promote initiation of neuronal regeneration in Caenorhabditis elegans. PLoS Biol. 2012; 10(5): e1001331. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBounoutas A, Kratz J, Emtage L, et al.: Microtubule depolymerization in Caenorhabditis elegans touch receptor neurons reduces gene expression through a p38 MAPK pathway. Proc Natl Acad Sci U S A. 2011; 108(10): 3982–7. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nApplewhite DA, Grode KD, Duncan MC, et al.: The actin-microtubule cross-linking activity of Drosophila Short stop is regulated by intramolecular inhibition. Mol Biol Cell. 2013; 24(18): 2885–93. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAlves-Silva J, Sánchez-Soriano N, Beaven R, et al.: Spectraplakins promote microtubule-mediated axonal growth by functioning as structural microtubule-associated proteins and EB1-dependent +TIPs (tip interacting proteins). J Neurosci. 2012; 32(27): 9143–58. PubMed Abstract | Publisher Full Text | Free Full Text\n\nValakh V, Walker LJ, Skeath JB, et al.: Loss of the spectraplakin short stop activates the DLK injury response pathway in Drosophila. J Neurosci. 2013; 33(45): 17863–73. PubMed Abstract | Publisher Full Text | Free Full Text\n\nValakh V, Frey E, Babetto E, et al.: Cytoskeletal disruption activates the DLK/JNK pathway, which promotes axonal regeneration and mimics a preconditioning injury. Neurobiol Dis. 2015; 77: 13–25. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChen L, Chuang M, Koorman T, et al.: Axon injury triggers EFA-6 mediated destabilization of axonal microtubules via TACC and doublecortin like kinase. eLife. 2015; 4: e08695. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFranco M, Peters PJ, Boretto J, et al.: EFA6, a sec7 domain-containing exchange factor for ARF6, coordinates membrane recycling and actin cytoskeleton organization. EMBO J. 1999; 18(6): 1480–91. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDerrien V, Couillault C, Franco M, et al.: A conserved C-terminal domain of EFA6-family ARF6-guanine nucleotide exchange factors induces lengthening of microvilli-like membrane protrusions. J Cell Sci. 2002; 115(Pt 14): 2867–79. PubMed Abstract\n\nSakagami H, Suzuki H, Kamata A, et al.: Distinct spatiotemporal expression of EFA6D, a guanine nucleotide exchange factor for ARF6, among the EFA6 family in mouse brain. Brain Res. 2006; 1093(1): 1–11. 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PLoS Genet. 2007; 3(8): e128. PubMed Abstract | Publisher Full Text | Free Full Text\n\nO'Rourke SM, Christensen SN, Bowerman B: Caenorhabditis elegans EFA-6 limits microtubule growth at the cell cortex. Nat Cell Biol. 2010; 12(12): 1235–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChuang M, Goncharov A, Wang S, et al.: The microtubule minus-end-binding protein patronin/PTRN-1 is required for axon regeneration in C. elegans. Cell Rep. 2014; 9(3): 874–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNwagbara BU, Faris AE, Bearce EA, et al.: TACC3 is a microtubule plus end-tracking protein that promotes axon elongation and also regulates microtubule plus end dynamics in multiple embryonic cell types. Mol Biol Cell. 2014; 25(21): 3350–62. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nNawabi H, Belin S, Cartoni R, et al.: Doublecortin-Like Kinases Promote Neuronal Survival and Induce Growth Cone Reformation via Distinct Mechanisms. Neuron. 2015; 88(4): 704–19. PubMed Abstract | Publisher Full Text\n\nZitouni S, Nabais C, Jana SC, et al.: Polo-like kinases: structural variations lead to multiple functions. Nat Rev Mol Cell Biol. 2014; 15(7): 433–52. PubMed Abstract | Publisher Full Text\n\nGoldstein B, Macara IG: The PAR proteins: fundamental players in animal cell polarization. Dev Cell. 2007; 13(5): 609–22. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKemphues KJ, Priess JR, Morton DG, et al.: Identification of genes required for cytoplasmic localization in early C. elegans embryos. Cell. 1988; 52(3): 311–20. PubMed Abstract | Publisher Full Text\n\nDrewes G, Ebneth A, Preuss U, et al.: MARK, a novel family of protein kinases that phosphorylate microtubule-associated proteins and trigger microtubule disruption. Cell. 1997; 89(2): 297–308. PubMed Abstract | Publisher Full Text\n\nDelacourte A, Buée L: Tau pathology: a marker of neurodegenerative disorders. Curr Opin Neurol. 2000; 13(4): 371–6. PubMed Abstract\n\nDrewes G, Trinczek B, Illenberger S, et al.: Microtubule-associated protein/microtubule affinity-regulating kinase (p110mark). A novel protein kinase that regulates tau-microtubule interactions and dynamic instability by phosphorylation at the Alzheimer-specific site serine 262. J Biol Chem. 1995; 270(13): 7679–88. PubMed Abstract | Publisher Full Text\n\nBiernat J, Wu YZ, Timm T, et al.: Protein kinase MARK/PAR-1 is required for neurite outgrowth and establishment of neuronal polarity. Mol Biol Cell. 2002; 13(11): 4013–28. PubMed Abstract | Publisher Full Text | Free Full Text\n\nConde C, Cáceres A: Microtubule assembly, organization and dynamics in axons and dendrites. Nat Rev Neurosci. 2009; 10(5): 319–32. PubMed Abstract | Publisher Full Text\n\nLabbé JC, Maddox PS, Salmon ED, et al.: PAR proteins regulate microtubule dynamics at the cell cortex in C. elegans. Curr Biol. 2003; 13(9): 707–14. PubMed Abstract | Publisher Full Text\n\nDoerflinger H, Benton R, Shulman JM, et al.: The role of PAR-1 in regulating the polarised microtubule cytoskeleton in the Drosophila follicular epithelium. Development. 2003; 130(17): 3965–75. PubMed Abstract | Publisher Full Text\n\nSapir T, Sapoznik S, Levy T, et al.: Accurate balance of the polarity kinase MARK2/Par-1 is required for proper cortical neuronal migration. J Neurosci. 2008; 28(22): 5710–20. PubMed Abstract | Publisher Full Text\n\nMandelkow EM, Thies E, Trinczek B, et al.: MARK/PAR1 kinase is a regulator of microtubule-dependent transport in axons. J Cell Biol. 2004; 167(1): 99–110. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSapir T, Shmueli A, Levy T, et al.: Antagonistic effects of doublecortin and MARK2/Par-1 in the developing cerebral cortex. J Neurosci. 2008; 28(48): 13008–13. PubMed Abstract | Publisher Full Text\n\nGuo S, Kemphues KJ: par-1, a gene required for establishing polarity in C. elegans embryos, encodes a putative Ser/Thr kinase that is asymmetrically distributed. Cell. 1995; 81(4): 611–20. PubMed Abstract | Publisher Full Text\n\nMunro E, Nance J, Priess JR: Cortical flows powered by asymmetrical contraction transport PAR proteins to establish and maintain anterior-posterior polarity in the early C. elegans embryo. Dev Cell. 2004; 7: 413–24. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCuenca AA, Schetter A, Aceto D, et al.: Polarization of the C. elegans zygote proceeds via distinct establishment and maintenance phases. Development. 2003; 130(7): 1255–65. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "13597",
"date": "27 Apr 2016",
"name": "Martin Oudega",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13598",
"date": "27 Apr 2016",
"name": "Zhigang He",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13599",
"date": "27 Apr 2016",
"name": "Laura Ann Lowery",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-764
|
https://f1000research.com/articles/5-763/v1
|
27 Apr 16
|
{
"type": "Review",
"title": "Is there still a role for thyroid scintigraphy in the workup of a thyroid nodule in the era of fine needle aspiration cytology and molecular testing?",
"authors": [
"Rodrigo Moreno-Reyes",
"Aglaia Kyrilli",
"Maria Lytrivi",
"Carole Bourmorck",
"Rayan Chami",
"Bernard Corvilain",
"Rodrigo Moreno-Reyes",
"Aglaia Kyrilli",
"Maria Lytrivi",
"Carole Bourmorck",
"Rayan Chami"
],
"abstract": "Thyroid scintigraphy is now rarely used in the work-up of a thyroid nodule except in the presence of a low TSH value. Therefore, autonomously functioning thyroid nodules (AFTNs) with a normal TSH value are diagnosed only in the rare medical centers that continue to use thyroid scan systematically in the presence of a thyroid nodule. In this review, we discuss the prevalence of AFTN with a normal TSH level and the possible consequences of performing fine needle aspiration cytology (FNAC) in an undiagnosed AFTN. We also discuss the risk of malignant AFTN which may be higher than previously stated.",
"keywords": [
"Thyroid",
"scintigraphy",
"AFTN"
],
"content": "Introduction\n\nThyroid nodules are a very common problem in adults. Their prevalence increases with age and may reach 50% by the age of 65 years1–2. Thyroid scintigraphy is the only technique that permits evaluation of the functional characteristics of a nodule. Two radionuclides are mainly used for the evaluation of patients with thyroid nodules: 99mTcO4- and 123I. 123I is both concentrated and organified within the gland, whereas 99mTcO4- is only concentrated. According to the 2015 American Thyroid Association (ATA) guidelines, if a thyroid scan is performed, 123I should be preferred over 99mTcO4-3, but this preference is not justified for the European Association for Nuclear Medicine4. Thyroid nodules are classified according to their ability to take up the isotope compared to that of the extranodular tissue. A cold nodule (hypofunctional) has reduced tracer uptake, a warm nodule (isofunctional) has tracer uptake roughly equivalent to the non-nodular tissue, and a hot nodule (hyperfunctional) has increased tracer uptake. The term autonomously functioning thyroid nodules (AFTNs) is frequently used as synonymous for hot nodules because they are characterized by their capacity to grow and produce thyroid hormones in the absence of thyroid-stimulating hormone (TSH)5. In the presence of a hot nodule and a normal level of TSH, the autonomous function can be formally demonstrated by administration of a suppressive dose of thyroid hormone and showing that it does not affect the function of the nodule (persistence of increased radionuclide uptake). This test is rarely used in clinical practice. The vast majority of nodules are hypofunctioning (cold nodules), whilst a minority is hyperfunctioning. The thyroid scan should always be compared to thyroid ultrasound images to be sure that the abnormality observed on the scan corresponds to a thyroid lesion. AFTNs account for 5–10% of palpable nodules and up to 20% in regions with iodine deficiency6–9. Gain-of-function mutations of the TSH receptor (TSHR) or of the α subunit of the stimulating G-protein (Gsα) are the main causes of AFTNs. The frequencies of Gsα and TSHR mutation in AFTNs reach 5% and 60%, respectively. The mutations responsible for the remaining cases remain unknown but are also probably involved in constitutive activity of cAMP cascade (e.g. other G-protein subunits, adenylyl cyclase, phosphodiesterase, and protein kinase A). Other pathways may also play a role in the pathogenesis of AFTNs like vascular growth factors10, AMPK signaling pathway11, and miRNA cascades12. Thus far, more than 40 TSHR mutations have been reported13–15. It is generally accepted that the risk of cancer is around 5% in a cold nodule and extremely low in AFTNs, which therefore do not require further investigation16. Driven by studies from areas with normal iodine intake, mainly North America, thyroid scintigraphy is now rarely used in the management of thyroid nodules in the presence of a normal TSH value. This strategy is based on the assumption that AFTNs are uncommon and that TSH levels are always subnormal in the presence of an AFTN and therefore that a normal TSH value rules out the presence of an AFTN. Consequently, the ATA and the European Thyroid Association (ETA) guidelines recommend considering radionuclide scanning in patients with thyroid nodules only if their TSH is low3,17. For the ETA, a thyroid scan may also be considered in the presence of a multinodular goiter in areas with insufficient iodine supply. Despite case reports of hot nodules that have turned out to be malignant, most groups agree that AFTNs do not necessitate fine needle aspiration cytology (FNAC) based on their very low risk of cancer. An additional reason to avoid FNAC of AFTNs is the risk of obtaining equivocal results (follicular lesion of unknown significance or FLUS), which tends to prompt surgery18. However, the risk of malignancy in an AFTN has not been clearly quantified in the literature. Independent of a better estimation of the risk of cancer, diagnosis of AFTN by a thyroid scan will change the follow up that will mainly consist of prevention, detection, and adequate treatment of thyroid dysfunction. The rate of development of thyrotoxicosis in patients with hyperfunctioning adenomas who are euthyroid initially is about 4% per year19–21. It is important to point out that in patients with an AFTN, even a small increase in iodide supply leads to increased thyroid hormone synthesis and will accelerate the development of thyrotoxicosis22,23.\n\nIn this review, we discuss whether there remains a place for thyroid scintigraphy in the workup of a thyroid nodule in the era of FNAC and molecular testing. To answer this question, we address the following points:\n\n\n1. Does normal TSH exclude a hyperfunctioning thyroid nodule?\n\nThe ATA and the ETA guidelines recommend considering radionuclide scanning in patients with thyroid nodules only if the TSH level is low3,17. However, this assertion comes from small clinical studies24 or expert opinions25. In the absence of thyroid scintigraphy in the workup of a patient with a thyroid nodule and a normal TSH level, there is a risk of performing FNAC in an unsuspected AFTN. Until recently, the proportion of patients with an AFTN and a normal TSH level was unknown. In 2014, we published a study of 368 patients, which demonstrated that more than 70% of patients with an AFTN referred to our hospital for the workup of a thyroid nodule had a normal TSH level26. The proportion of patients with subclinical hyperthyroidism increased with the size of the nodule and reached 50% or more only for patients with a nodule size above 3 cm (Figure 1). A recent meta-analysis confirmed that TSH is not an effective tool to detect or exclude an AFTN27. However, the majority of these studies came from European countries with a history of past or present iodine deficiency28–30. Therefore, we cannot claim that this observation is also valid for patients from areas with sufficient iodine intake. Another limitation of these studies is the fact that thyroid scans were generally performed using 99mTcO4- rather than 123I and that some nodules may appear “hot” on 99mTcO4- but are actually cold on 123I. This discordance is observed in 5-10% of nodules and up to 30% of them may be malignant31. The absence of hyperthyroidism in a large proportion of patients with an AFTN is not surprising, as the majority of the described TSHR mutations only activate the cyclic AMP cascade that is involved in the stimulation of iodide transport but not in its organification13–15,32. Iodide organification and thyroid hormone synthesis are stimulated by the Ca2+−IP3 cascade32. This cascade is constitutively activated only by a minority of TSHR mutations. This explains why an organification defect is observed in the majority of AFTN cases33. In this latter study, the iodide perchlorate discharge test was used to diagnose impaired iodide organification. Perchlorate is a competitive inhibitor of iodide trapping. In cases of normal organification, perchlorate does not cause significant changes in the iodide content of the thyroid, since most iodide is organified and cannot be released. In cases of organification defect, administration of perchlorate causes a decrease in thyroid iodide content. Examples of AFTN with or without iodide organification defect are shown in Figure 2.\n\nPanel a: Proportion of patients with an autonomously functioning thyroid nodule (AFTN) and a normal thyroid-stimulating hormone (TSH) level (Black bars: global population; white bars: subpopulation in which the AFTN was discovered in the workup of a thyroid nodule). Panels b and c: Proportion of patients with a normal TSH level according to the size of the nodule; main diameter (panel b) or volume (panel c). (Black bars: global population; white bars: subpopulation in which the AFTN was discovered in the workup of a thyroid nodule).\n\nIodide perchlorate test was used to evaluate organification defect in patients with an autonomously functioning thyroid nodule (AFTN). A time 0, 26MBq 123I was administered orally with 500 µg stable iodide. Three hours later, a first scintigraphy was acquired, followed immediately by the oral administration of perchlorate. One hour later, a second scintigraphy was obtained. After correction for radioisotope decay, discharge can be evaluated by comparing the counts before and after perchlorate. Thyroid scan in a patient with a positive discharge test before (A) and after (B) perchlorate. Thyroid scan in a patient with a negative perchlorate test before (C) and after (D) perchlorate.\n\nIn our study, 60% of patients with an AFTN had an organification defect as revealed by the perchlorate discharge test33. Some differences in thyroid hormone level were observed between the two groups, but our population was too small to make a definitive conclusion. No genetic data were obtained, but our hypothesis was that AFTNs harboring a TSHR mutation that activates only the cAMP cascade had an organification defect, while AFTNs harboring a TSHR mutation that activates both the cAMP and the Ca2+−IP3 cascade had a more severe phenotype owing to more efficient thyroid hormone synthesis. Not only is the diversity in clinical behavior of AFTN probably caused by differences in causal TSHR mutations but it may also reflect the differences in cellular density from one nodule to another owing to various decreases in colloid space and the difficulty of estimating the actual weight of the active nodule13. Whatever the reason for the persistence of a normal TSH level, on the basis of a “TSH only” screening, as recommended by the vast majority of international guidelines, more than 50% of patients with AFTN may undergo unjustified FNAC in the workup of a thyroid nodule.\n\n\n2. What is the ultrasound appearance of an AFTN?\n\nIf thyroid scan is not used in the workup of a thyroid nodule, ultrasound malignancy criteria are now current practice to establish the necessity of FNAC34. These criteria include the presence of microcalcifications, nodule hypoechogenicity, irregular margins, intranodular vascularity, and a nodule with a shape taller than it is wide. As thyroid scintigraphy is no longer systematically performed in the workup of a thyroid nodule, the literature is inconclusive on the ultrasound appearance of an AFTN. One uncontrolled retrospective study reported that more than 30% of AFTNs may have a suspicious feature on ultrasound (mainly a hypoechoic aspect and intranodular vascularization)35. Another study reported the presence of microcalcifications in more than 50% of AFTN cases36. Perinodular and intranodular signals evaluated by color flow Doppler sonography are significantly higher in AFTNs than in cold nodules37,38. These findings in the absence of a thyroid scan always lead to the performance of FNAC. The exact percentage of patients with an unsuspected AFTN who deserve FNAC according to the ultrasonographic appearance of the nodule needs to be evaluated in a prospective study.\n\n\n3. What is the risk of obtaining a cytological report of an indeterminate follicular lesion that may lead to unnecessary surgery when a FNAC is performed on an unsuspected AFTN?\n\nOnce again, as thyroid scintigraphy is no longer systematically performed and as an AFTN does not warrant FNAC, data in the literature on the cytological aspect of an AFTN are rare. When FNAC is performed on a known AFTN, it is generally accepted that the risk of obtaining a cytological report of a FLUS is not negligible, but until now only small uncontrolled studies have been published18,36,39. No data exist for assessing the risk of malignancy in an AFTN when an FNAC is read as an indeterminate follicular lesion. The fact that a thyroid scan is no longer used in the workup of a thyroid nodule in euthyroid patients increases the likelihood of performing FNAC on an unsuspected AFTN and the risk of performing thyroid surgery for benign lesions, although removal of a hot nodule may eliminate a long-term risk of developing hyperthyroidism. A prospective study of the results of FNAC when performed in an AFTN is needed to quantify more precisely the risk of surgery in such patients.\n\n\n4. Can molecular testing improve the diagnosis of thyroid FNA specimens from AFTN?\n\nMolecular testing for miRNA, mRNA, and DNA on FNA specimens improves the diagnosis of thyroid nodules with indeterminate cytology40–44. The most advanced multigene molecular panels provide both high positive predictive value and high negative predictive value for cancer detection in thyroid nodules, and in the near future they will probably eliminate indeterminate cytologic diagnosis of thyroid nodules. These techniques have never been studied for suspicious cytology obtained in an AFTN. If they prove to be reliable in an AFTN, molecular testing will also decrease the risk of unnecessary surgery in cases of indeterminate cytology in an AFTN. The cost effectiveness of performing a thyroid scan to avoid an unnecessary FNAC in an AFTN or to skip the thyroid scan and perform molecular testing in case of FNAC with indeterminate cytology in an AFTN is not known. This will depend on the cost of molecular testing (which will probably decrease in the next few years), the prevalence of AFTN (higher in areas where dietary iodine is or was insufficient), and the as yet unknown risks of obtaining indeterminate cytology in an AFTN.\n\n\n5. What is the risk of cancer in an AFTN?\n\nIt is generally accepted that the risk of cancer in an AFTN is very low. However, the risk may be higher than generally believed, and in a recent review based on retrospective surgical series, the risk was estimated at 3%, i.e. nearly the same as for a cold nodule (5%)38. The risk of thyroid microcarcinoma may reach 30% in autopsy studies45. Therefore, there is a risk of overestimation of thyroid cancer in patients with AFTN owing to the high prevalence of incidentally found thyroid microcarcinoma at surgery. The possibility that high incidences of cancer in some series may result from misdiagnosis of malignancy was also suggested46. There are no studies specifically designed to assess the risk of malignity of AFTNs as a primary outcome. There are many published case reports but with the obvious bias that only rare cases are reported. In some studies, tumor size is not reported and it is not clear if the observed cancer is an incidental microcarcinoma outside or within the AFTN, or within another nodule in the case of a multinodular goiter47–55. The risk of thyroid cancer within an AFTN seems independent of the level of TSH. The huge variation of the risk of malignancy within AFTNs between the different studies reported in Mirfakhraee et al.’s review (between 0% and 12.5%) raises the question of potential bias and underlines the need for prospective studies38.\n\n\nConclusion\n\nThyroid scan is now used in the workup of thyroid nodules only in the presence of a low serum TSH. This strategy is not appropriate, at least in areas with a present or past iodine deficiency. In these areas, several studies have demonstrated that up to 70% of patients with an AFTN may have a normal TSH value. This does not mean that thyroid scan must be performed in every patient with a thyroid nodule but only in those with an indication of FNAC, i.e. nodule above 10–15 mm of diameter. We believe that before giving up the use of thyroid scan, prospective studies must be done on the reliability of FNAC and molecular testing in an AFTN and on the risk of thyroid cancer in an AFTN.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nHegedüs L: Clinical practice. The thyroid nodule. N Engl J Med. 2004; 351(17): 1764–71. PubMed Abstract | Publisher Full Text\n\nMazzaferri EL: Management of a solitary thyroid nodule. N Engl J Med. 1993; 328(8): 553–9. PubMed Abstract | Publisher Full Text\n\nHaugen BR, Alexander EK, Bible KC, et al.: 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid. 2016; 26(1): 1–133. 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Surgery. 1998; 124(4): 656–61; discussion 661–2. PubMed Abstract | Publisher Full Text\n\nMeier DA, Kaplan MM: Radioiodine uptake and thyroid scintiscanning. Endocrinol Metab Clin North Am. 2001; 30(2): 291–313, viii. PubMed Abstract | Publisher Full Text\n\nChami R, Moreno-Reyes R, Corvilain B: TSH measurement is not an appropriate screening test for autonomous functioning thyroid nodules: a retrospective study of 368 patients. Eur J Endocrinol. 2014; 170(4): 593–9. PubMed Abstract | Publisher Full Text\n\nTreglia G, Trimboli P, Verburg FA, et al.: Prevalence of normal TSH value among patients with autonomously functioning thyroid nodule. Eur J Clin Invest. 2015; 45(7): 739–44. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGörges R, Kandror T, Kuschnerus S, et al.: [Scintigraphically \"hot\" thyroid nodules mainly go hand in hand with a normal TSH]. Nuklearmedizin. 2011; 50(5): 179–88. PubMed Abstract | Publisher Full Text\n\nMoreno-Reyes R, Carpentier YA, Macours P, et al.: Seasons but not ethnicity influence urinary iodine concentrations in Belgian adults. Eur J Nutr. 2011; 50(4): 285–90. PubMed Abstract | Publisher Full Text\n\nPearce EN, Andersson M, Zimmermann MB: Global iodine nutrition: Where do we stand in 2013? Thyroid. 2013; 23(5): 523–8. PubMed Abstract | Publisher Full Text\n\nReschini E, Ferrari C, Castellani M, et al.: The trapping-only nodules of the thyroid gland: prevalence study. Thyroid. 2006; 16(8): 757–62. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCorvilain B, Laurent E, Lecomte M, et al.: Role of the cyclic adenosine 3',5'-monophosphate and the phosphatidylinositol-Ca2+ cascades in mediating the effects of thyrotropin and iodide on hormone synthesis and secretion in human thyroid slices. J Clin Endocrinol Metab. 1994; 79(1): 152–9. PubMed Abstract | Publisher Full Text\n\nMoreno-Reyes R, Tang BN, Seret A, et al.: Impaired iodide organification in autonomous thyroid nodules. J Clin Endocrinol Metab. 2007; 92(12): 4719–24. PubMed Abstract | Publisher Full Text\n\nRuss G, Royer B, Bigorgne C, et al.: Prospective evaluation of thyroid imaging reporting and data system on 4550 nodules with and without elastography. Eur J Endocrinol. 2013; 168(5): 649–55. PubMed Abstract | Publisher Full Text\n\nErdoğan MF, Anil C, Cesur M, et al.: Color flow Doppler sonography for the etiologic diagnosis of hyperthyroidism. Thyroid. 2007; 17(3): 223–8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nDirikoc A, Polat SB, Kandemir Z, et al.: Comparison of ultrasonography features and malignancy rate of toxic and nontoxic autonomous nodules: a preliminary study. Ann Nucl Med. 2015; 29(10): 883–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nIanni F, Perotti G, Prete A, et al.: Thyroid scintigraphy: an old tool is still the gold standard for an effective diagnosis of autonomously functioning thyroid nodules. J Endocrinol Invest. 2013; 36(4): 233–6. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMirfakhraee S, Mathews D, Peng L, et al.: A solitary hyperfunctioning thyroid nodule harboring thyroid carcinoma: review of the literature. Thyroid Res. 2013; 6(1): 7. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLiel Y, Zirkin HJ, Sobel RJ: Fine needle aspiration of the hot thyroid nodule. Acta Cytol. 1988; 32(6): 866–7. PubMed Abstract\n\nHadd AG, Houghton J, Choudhary A, et al.: Targeted, high-depth, next-generation sequencing of cancer genes in formalin-fixed, paraffin-embedded and fine-needle aspiration tumor specimens. J Mol Diagn. 2013; 15(2): 234–47. PubMed Abstract | Publisher Full Text\n\nNikiforova MN, Wald AI, Roy S, et al.: Targeted next-generation sequencing panel (ThyroSeq) for detection of mutations in thyroid cancer. J Clin Endocrinol Metab. 2013; 98(11): E1852–60. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nNikiforov YE, Carty SE, Chiosea SI, et al.: Highly accurate diagnosis of cancer in thyroid nodules with follicular neoplasm/suspicious for a follicular neoplasm cytology by ThyroSeq v2 next-generation sequencing assay. Cancer. 2014; 120(23): 3627–34. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLabourier E, Shifrin A, Busseniers AE, et al.: Molecular Testing for miRNA, mRNA, and DNA on Fine-Needle Aspiration Improves the Preoperative Diagnosis of Thyroid Nodules With Indeterminate Cytology. J Clin Endocrinol Metab. 2015; 100(7): 2743–50. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLe Mercier M, D'Haene N, De Nève N, et al.: Next-generation sequencing improves the diagnosis of thyroid FNA specimens with indeterminate cytology. Histopathology. 2015; 66(2): 215–24. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nHarach HR, Franssila KO, Wasenius VM: Occult papillary carcinoma of the thyroid. A \"normal\" finding in Finland. A systematic autopsy study. Cancer. 1985; 56(3): 531–8. PubMed Abstract | Publisher Full Text\n\nHarach HR, Sánchez SS, Williams ED: Pathology of the autonomously functioning (hot) thyroid nodule. Ann Diagn Pathol. 2002; 6(1): 10–9. PubMed Abstract | Publisher Full Text\n\nRuggeri RM, Campennì A, Giovinazzo S, et al.: Follicular variant of papillary thyroid carcinoma presenting as toxic nodule in an adolescent: coexistent polymorphism of the TSHR and Gsα genes. Thyroid. 2013; 23(2): 239–42. PubMed Abstract | Publisher Full Text\n\nYalla NM, Reynolds LR: Hürthle cell thyroid carcinoma presenting as a \"hot\" nodule. Endocr Pract. 2011; 17(3): e68–72. PubMed Abstract | Publisher Full Text\n\nTfayli HM, Teot LA, Indyk JA, et al.: Papillary thyroid carcinoma in an autonomous hyperfunctioning thyroid nodule: case report and review of the literature. Thyroid. 2010; 20(9): 1029–32. PubMed Abstract | Publisher Full Text | Free Full Text\n\nUludag M, Yetkin G, Citgez B, et al.: Autonomously functioning thyroid nodule treated with radioactive iodine and later diagnosed as papillary thyroid cancer. Hormones (Athens). 2008; 7(2): 175–9. PubMed Abstract\n\nNiepomniszcze H, Suárez H, Pitoia F, et al.: Follicular carcinoma presenting as autonomous functioning thyroid nodule and containing an activating mutation of the TSH receptor (T620I) and a mutation of the Ki-RAS (G12C) genes. Thyroid. 2006; 16(5): 497–503. PubMed Abstract | Publisher Full Text\n\nEszlinger M, Niedziela M, Typlt E, et al.: Somatic mutations in 33 benign and malignant hot thyroid nodules in children and adolescents. Mol Cell Endocrinol. 2014; 393(1–2): 39–45. PubMed Abstract | Publisher Full Text\n\nKuan YC, Tan FH: Thyroid papillary carcinoma in a 'hot' thyroid nodule. QJM. 2014; 107(6): 475–6. PubMed Abstract | Publisher Full Text\n\nLee ES, Kim JH, Na DG, et al.: Hyperfunction thyroid nodules: their risk for becoming or being associated with thyroid cancers. Korean J Radiol. 2013; 14(4): 643–52. PubMed Abstract | Publisher Full Text | Free Full Text\n\nErdoğan MF, Anil C, Ozer D, et al.: Is it useful to routinely biopsy hot nodules in iodine deficient areas? J Endocrinol Invest. 2003; 26(2): 128–31. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13488",
"date": "27 Apr 2016",
"name": "Markus Luster",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13595",
"date": "27 Apr 2016",
"name": "Stephen W. Spaulding",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13596",
"date": "27 Apr 2016",
"name": "Jacques Dumont",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-763
|
https://f1000research.com/articles/5-756/v1
|
26 Apr 16
|
{
"type": "Review",
"title": "The expanding regulatory universe of p53 in gastrointestinal cancer",
"authors": [
"Andrew Fesler",
"Ning Zhang",
"Jingfang Ju",
"Andrew Fesler",
"Ning Zhang"
],
"abstract": "Tumor suppresser gene TP53 is one of the most frequently deleted or mutated genes in gastrointestinal cancers. As a transcription factor, p53 regulates a number of important protein coding genes to control cell cycle, cell death, DNA damage/repair, stemness, differentiation and other key cellular functions. In addition, p53 is also able to activate the expression of a number of small non-coding microRNAs (miRNAs) through direct binding to the promoter region of these miRNAs. Many miRNAs have been identified to be potential tumor suppressors by regulating key effecter target mRNAs. Our understanding of the regulatory network of p53 has recently expanded to include long non-coding RNAs (lncRNAs). Like miRNA, lncRNAs have been found to play important roles in cancer biology. With our increased understanding of the important functions of these non-coding RNAs and their relationship with p53, we are gaining exciting new insights into the biology and function of cells in response to various growth environment changes. In this review we summarize the current understanding of the ever expanding involvement of non-coding RNAs in the p53 regulatory network and its implications for our understanding of gastrointestinal cancer.",
"keywords": [
"p53",
"non-coding RNA",
"gastrointestinal cancer"
],
"content": "Introduction\n\nThe discovery of p53 is one of the most exciting events in biological research over the past 30 years1–3. The field of p53 research represents a large growing body of exciting studies with over 75000 citations in PubMed. p53 is one of the most frequently mutated or deleted tumor suppressor genes in gastrointestinal (GI) cancers which represent nearly 30% of tumor incidences. It is well established that the classical function of tumor suppressor gene p53 is to act as a transcription factor to regulate its downstream protein coding genes in response to various growth conditions and cellular stresses4,5. Most of the research effort in the past has been devoted to the regulatory mechanism of transcriptional regulation of protein coding genes by p53. Independent of its transcriptional function, p53 is also able to regulate cell death by migrating directly to the mitochondria and interacting with B-cell lymphoma 2 (BCL-2) family member proteins to induce mitochondrial outer membrane permeability6. Limited attention has been devoted to other p53 functions such as RNA binding and post-transcriptional control7. With the discovery of non-coding RNA such as microRNA (miRNA), we and others have recognized the importance of post-transcriptional control mediated by non-coding RNAs in cancer8,9. Post-transcriptional and translational controls mediated by RNA binding proteins and non-coding RNAs provide cells with a great advantage in response to acute growth environment changes such as genotoxic stress caused by chemo- and/or radiation- therapy10–12. Non-coding RNAs comprise nearly 97% of transcribed RNA molecules13. Much of the research efforts in the past decade concerning non-coding RNAs have been focused on short non-coding RNAs such as miRNAs and piRNAs. However, with advances in sequencing technology, now there is a growing body of evidence showing that lncRNAs also contribute to gene regulation at multiple levels14,15. Perhaps not surprisingly, important interactions have been discovered between the functions and regulation of these non-coding RNAs and p53. The relationship between non-coding RNA and p53 has been revealed to be quite dynamic, with p53 regulating the expression of some non-coding RNAs while other non-coding RNAs can function to regulate p53. While our appreciation of the important functions of non-coding RNA has grown, we have achieved a much better understanding of non-coding RNAs in the p53 regulated mechanisms in cancer.\n\n\np53 and miRNAs\n\np53 is one of the most well studied tumor suppressor genes. Disruptions of p53 functions, via deletions or mutations are found in many different types of cancers, including over 50% of colorectal cancers16–18. The importance of p53 in cancers, is associated with its role as a transcriptional activator or suppressor, by which it regulates the expression of many essential genes. p53 function is crucial to maintain genome integrity and stability. p53 has been called the ‘guardian of the genome’19. It can also act as an RNA-binding protein to modulate gene expression at the post-transcriptional level. p53 binds to the 5'-UTR region of cyclin-dependent kinase 4 (CDK4) to suppress translation and it has been shown to auto-regulate its own translation by directly interacting with its own mRNA20,21.\n\nmiRNA are short non-coding RNA that are transcribed as primary miRNAs (pri-miRNA)22. The pri-miRNA is cleaved by Drosha to a 70 nucleotide stem-loop pre-miRNA. Pre-miRNA is transported to the cytoplasm by Exportin 5 and further cleaved by RNAse Dicer to a 20 to 25 base pair double stranded miRNA. miRNAs modulate expression of target mRNAs by either perfect or imperfect base pairing mainly at the 3'-UTR regions of mRNA transcripts to inhibit translation and/or promote mRNA degradation. One particular miRNA can regulate multiple mRNA transcripts providing the possibility for the regulation of multiple different cellular networks and pathways by an individual miRNA23. There are also multiple miRNAs that can directly interact with one particular mRNA. With the discovery of miRNAs and the fact that they can have important roles in cancer biology, as well as the well-established function of p53 in cancer, we reasoned that there may be some interplay between the two and some of these miRNAs may be involved in the p53 regulatory network. We first reported a systematic analysis of miRNA profiles in colon cancer cell lines, HCT 116, containing either wild type p53 or null p538. In this study, we also profiled actively translated mRNAs impacted by p53 loss, and bioinformatically identified putative p53-binding sites in nearly 40% of miRNA promoter regions (e.g. miR-34s, miR-192, miR-215, miR-194, miR-502, miR-200c, miR-26a, miR-15)8. Many of these miRNAs were found to be directly regulated by p53 by us and other groups, thus establishing the interplay between p53 and miRNA networks in cancer24–30.\n\n\nmiRNA regulation by p53\n\nResearch by us and other groups has clearly demonstrated that regulation of miRNA is among the many important functions of p53 in the cell. The miRNAs that have been shown to be regulated by p53 have important roles in regulating cellular pathways and functions such as cell cycle, apoptosis and chemoresistance. Working with the miRNAs we identified as having putative p53 binding sites in their promoter region we validated that miR-26a was directly regulated by p53 in colon cancer8. miR-26a has been found to act as a tumor suppressor in mouse intestine31. In gastric cancer, miR-26a also seems to act as a tumor suppressor, by targeting fibroblast growth factor 9 (FGF9) and inhibiting cell proliferation and metastasis32. miR-34s are the most extensively investigated miRNAs shown to be directly regulated by p53 in a number of different tumor types28. miR-34a regulation by p53 is important in p53 mediated apoptosis, with inhibition of miR-34a reducing p53-induced apoptosis9. miR-34a suppresses the E2F transcription factor pathway, reducing cell cycle progression. miR-34a contributes to apoptosis regulation in colon cancer through targeting silent information regulator 1 (SIRT1). miR-34a also contributes to the activation of both p53 and p21. These functions contribute to the tumor suppressor role of miR-34a9,28,33–35. miR-34 is directly regulated by p53 and is reduced in 36% of human colorectal cancer tumor specimens33. p53 dependent expression of miR-34 also inhibits tumor progression by disrupting an IL-6R/Stat3/miR-34a feedback loop36. miR-34s have also been demonstrated to be important in other GI tumor types37. In gastric cancer, miR-34 expression can activate tumor suppressor pathways in cells that lack functional p53 as well as being able to inhibit tumorsphere formation38. miR-34 is one of the best characterized miRNAs that is regulated by p53 and has important functions in cancer, and thus not surprisingly, miR-34 based anti-cancer therapy also represents one of the first miRNAs to enter into clinical trials39.\n\nBeyond miR-34 as the poster child of p53 regulated miRNA, there are other important p53 regulated miRNAs. miR-192 and miR-215 have been shown by multiple groups to be regulated by p53 and their expression levels were reduced in colorectal cancer25,29,40,41. miR-192 and miR-215 can induce cell cycle arrest and enhance p53 mediated p21 expression when overexpressed in colon cancer cell lines. Our group has focused our efforts on investigating the roles of miR-192 and miR-215 in colorectal cancer with the interest of understanding chemoresistance mechanisms to 5-fluorouracil (5-FU) and methotrexate (MTX). We discovered that p53 and miR-192 form a positive feedback loop to regulate cell cycle and proliferation25. In addition, we discovered a key protein target of miR-192 is dihydrofolate reductase (DHFR). DHFR is a protein therapeutic target of MTX. miR-192 also suppresses the expression of 5-FU protein target thymidylate synthase (TYMS, TS). These results have also been reported by another research group42. However, the function of miR-215 and miR-192 seems to be different in gastric cancer. It has been reported that the expression of miR-215 is up-regulated in gastric cancer and one of the key targets is tumor suppressor retinoblastoma gene Rb143. Consistent with this, another report shows that miR-192 and miR-215 are associated with gastric tumor invasion and lymph node metastasis44. It appears that depending on the cellular and disease context, miRNAs can target different sets of mRNAs, as a result, they can function as either tumor suppressors or oncogenes. The regulatory mechanism and function of miR-192/215 will be quite unique in colorectal cancer vs. gastric cancer. One recent study demonstrated the potential of miR-192, miR-215 and miR-194 as promising detection biomarkers for Barrett's esophagus45, further supporting the importance of the p53 mediated miRNAs. miR-194 has also been identified as a p53 regulated miRNA. In colon cancer, miR-194 targets thrombospondin 1 (TSP-1) and is involved in promoting angiogenesis46. In gastric cancer, miR-194 has been shown to target E3 ubiquitin-protein ligase RBX1 and decrease proliferation and migration47. In contrast to these miRNAs, we have identified a negative correlation between miR-502 expression and p53, suggesting that rather than inducing the expression of miR-502, p53 inhibits its expression in colon cancer. miR-502 plays a role in regulating autophagy and proliferation in colon cancer cells24. miR-145 is also transcriptionally regulated by p53. miR-145 in turn suppresses the expression of cMyc and cyclin-dependent kinase 6 (CDK6), to inhibit cell proliferation and induce apoptosis48,49. miR-1204 is transcriptionally activated by p53 and also inhibits cellular proliferation50.\n\nIn addition to wild type p53, mutant p53 also plays key roles in GI cancer. Studies have demonstrated that the gain-of-function of mutant p53 is an important mechanism for tumors to develop resistance and impacts tumor progression51,52. In fact, mutant p53 can directly influence miRNA expression by interacting with miRNA promoters53,54. Mutant p53 exerts oncogenic functions and promotes epithelial-mesenchymal transition (EMT) in endometrial cancer (EC) by directly binding to the promoter of miR-130b, a negative regulator of zinc finger E-box-binding homeobox 1 (ZEB-1), and inhibiting its transcription. miR-223 was recently found to be down-regulated directly by mutant p53 proteins in breast and colon cancer cell lines55. Mutant p53 binds the miR-223 promoter and reduces its transcriptional activity. Such regulation requires the transcriptional repressor ZEB-1. In addition, miR-223 exogenous expression sensitizes breast and colon cancer cell lines expressing mutant p53 to treatment with DNA-damaging drugs55. Let-7i has also been found to be regulated by mutant p53, inhibiting invasion and migration54. These results suggest that it will be important to identify additional miRNAs that are regulated by various mutant p53 proteins. Table 1 summarizes some p53 regulated miRNAs in GI cancer.\n\n*--Role not clear, or conflicting reports in different cancer types\n\n\np53 regulation by miRNA\n\nThe relationship between p53 and miRNAs is more complex than just transcription regulation by p53. In fact, the interaction between the two is a two way street, with several miRNAs being able to regulate p53 expression either through direct targeting, or through regulation of other proteins that in turn modulate p53 expression and function. Some of the miRNAs regulated by p53 are actually able to act in feedback loops to regulate p53 as well. We investigated the regulation mechanism of p53 by miR-215 in colorectal cancer and discovered that a key target of miR-215 is denticleless protein homolog (DTL). The suppression of DTL by miR-215 triggered an up-regulation of p53 and p2126. DTL (RAMP, CDT2) is thought to play an essential role in DNA synthesis, cell cycle progression, proliferation and differentiation56. DTL controls cell cycle progression through several different mechanisms, and has an important role in the early radiation induced G2/M checkpoint57,58. The Proliferating cell nuclear antigen (PCNA)-coupled CUL4/DDB1/DTL complex can ubiquitinate and degrade key cell cycle proteins such as p53, mouse double minute 2 homolog (MDM2), p21, and E2F159–61. miR-502, also regulated by p53, acts in a feedback loop to repress expression of p53 indirectly24. miR-34 also acts in a feedback loop with p53 in colon cancer cells. Transfection of miR-34 into colon cancer cells leads to an increase in p53 and p21 expression as a result of down regulation of the E2F pathway33. Several other miRNAs including miR-339-5p and miR-542-3p positively regulate p53 through their targeting of p53 inhibitor MDM262,63. In addition to these miRNAs that regulate p53 through indirect mechanisms, others have been found to directly target p53. Among the first miRNAs found to target p53 directly, were miR-125b and miR-50464,65. miR-504 was demonstrated to target p53 in several cancer types, and reduce in vivo tumor growth of colon cancer cells65. In metastatic gastric cancer, miR-300 is up-regulated and acts as a tumor promoter. miR-300 was found to directly target p53 by interacting with the 3'-UTR of p53. Overexpression of miR-300 led to decreased p53 expression in gastric cancer cells, and inhibition of miR-300 led to an increase in p53 expression. Overexpression of p53 also reduced tumor promotion by miR-300, highlighting the importance of p53 targeting in miR-300 cellular function66. Additionally, miR-25 and miR-30d directly targeted p53 to regulate apoptosis in colon cancer cells67. These results suggest that not only can the functions of miRNAs be modulated by the p53 status in colorectal cancer, the tumor suppressive function of p53 can also be modulated by the post-transcriptional controls of various miRNAs under different stress and/or physiological conditions, providing p53 with a greater flexibility to control cell cycle and cell death.\n\nClearly miRNAs play important roles in the p53 regulatory network in GI cancer. p53 can regulate the transcription of several miRNAs that have important cellular functions in GI cancer. In addition, several miRNAs can regulate p53 expression to influence cellular pathways in cancer. The importance of the role of miRNAs in the p53 network is reflected in several other reviews that highlight this interaction68–72. Our understanding of these networks will likely continue to increase as we expand our understanding of the important functions of miRNAs as well as the roles of other non-coding RNAs in p53 regulation and function. Table 2 summarizes some miRNAs that regulate p53 in GI cancers. Figure 1 depicts the involvement of miRNAs in the p53 regulatory network.\n\nmiRNAs regulate p53 through direct targeting as well through indirect mechanisms such as targeting p53 regulators. p53 also regulates several miRNAs, through transcriptional activation as well as other mechanisms. The miRNAs involved in the p53 network carry out important functions regulating several cellular pathways such as proliferation, apoptosis, invasion and migration. In this figure, solid lines represent direct regulation, while dashed lines represent indirect, or poorly characterized regulation.\n\n\np53 and lncRNAs\n\nInteraction between p53 and non-coding RNA is certainly not limited to miRNA. Recent evidence has demonstrated that lncRNAs also have important functions in the p53 regulatory network. LncRNAs (200 nucleotides or more in length), thanks to improvements in sequencing technology, have begun to emerge recently as critical regulatory RNAs73–75. The understanding of the roles of lncRNAs in diseases, such as cancer, is still very limited but recent work has shown that these molecules can have some important functions in cancer biology and like miRNA are tied into the p53 regulatory network.\n\n\nLncRNAs regulated by p53\n\nThe field of lncRNA research remains in its early stages, and we are still identifying more lncRNAs and discovering the important functions they have in the cell. The progress that has been made thus far is quite interesting and encourages increased investigation. A systematic ChIP-Seq analysis has identified 23 lncRNAs that are up-regulated by p5376. Among the over six thousand lncRNAs that have been identified, lincRNA-p21 is one of the better characterized lncRNAs and importantly, is regulated by p5377,78. LincRNA-p21 locates next to the p21 gene on mouse chromosome 17 and is activated upon DNA damaging signals in mouse cells. It has been reported that lincRNA-p21 is a direct transcriptional target of p53 and is involved in p53-dependent transcriptional responses. There is a significant overlap among the genes regulated by lincRNA-p21 expression and genes that are repressed by p53. Heterogeneous nuclear ribonucleoprotein K (hnRNP-K) plays an important role in the ability of lincRNA-p21 to regulate these genes. Expression of lincRNA-p21 in mouse embryonic fibroblasts (MEFs) also has shown the ability to induce apoptosis77. Subsequent studies further revealed that lincRNA-p21 activates p21 in cis to promote polycomb target gene expression and to enforce the G1/S checkpoint79. Recent studies also demonstrated that in human cervical carcinoma HeLa cells, a RNA binding protein, human antigen R (HuR), modulates the expression level of lincRNA-p21, which in turn regulates its target protein translation, such as transcription factor jun-B (JUNB) and β-catenin78. Intriguingly for this review, lincRNA-p21 can be regulated by some miRNAs including let-780. Our group has recently show that lincRNA-p21 is associated with colorectal cancer progression81. Such association may be due to the unique function of lincRNA-p21 under hypoxia. LincRNA-p21 is a hypoxia-responsive lncRNA and is essential for hypoxia-enhanced glycolysis82. There is a positive feedback loop between hypoxia-inducible factor 1-alpha (HIF-1α) and lincRNA-p21 to promote tumor growth and the regulation of the Warburg effect. lincRNA-p21 has also been found to regulate the Wnt/β-catenin signaling pathway, and be associated with susceptibility to radiation therapy in colon cancer83. LincRNA-p21 is a powerful example of a long non-coding RNA, regulated by p53 that carries out important functions in the response pathway of p53. Another p53 regulated lncRNA named, p53 induced noncoding transcript (Pint), is a direct transcriptional target of p53. Pint is a nuclear RNA, that directly interacts with polycomb repressive complex 2 (PRC2), and is required for PRC2 targeting of specific genes for H3K27 tri-methylation and repression84. Pint is down-regulated in primary colon tumors and overexpression of Pint inhibits tumor cell proliferation, suggesting a potential tumor suppressor role84. Tumor suppressor candidate 7 (Tusc7) (LncRNA loc285194) has also been shown to be a p53 mediated tumor suppressor in colon cancer85. Tusc7 is transcriptionally activated by p53 to inhibit cell growth and exerts its function by suppressing miR-21185. In patient samples, Tusc7 was shown to be reduced in cancer compared to normal colon tissue. Reduced Tusc7 expression is associated with increased tumor size, stage and distant metastasis as well as decreased survival86. Similar results were found in esophageal cancer as well as pancreatic cancer, suggesting Tusc7 might be a good biomarker candidate87,88. In gastric cancer, Tusc7 expression is reduced in patient samples, and in cell lines decreases tumor cell growth. Tusc7 expression is also induced by wild type p53 but not mutant p5389. While Tusc7 seems to act as a tumor suppressor and is reduced in several types of cancer, the picture for taurine up-regulated 1 (Tug1), another p53 regulated lncRNA, is not as clear. Tug1 was first discovered to be important in retinal development and was then shown to be a direct transcriptional target of p53 in the context of non-small cell lung cancer90,91. The role of Tug1 in cancer however, seems to be different in different cellular contexts. In lung cancer, Tug1 expression was found to be decreased in cancer tissue compared to normal. Lower expression of Tug1 correlates with higher tumor stage, increased tumor size and decreased overall survival91. In esophageal cancer however, the role of Tug1 seems to be quite different. Tug1 is found to be over expressed in cancer tissue with expression being correlated with tumor stage. Knockdown of Tug1 also seems to inhibit cancer cell proliferation as well as migration92. This oncogenic type function for Tug1 has also been found in bladder cancer where it appears to be up-regulated in cancer and promote cancer invasion as well as resistance to radiotherapy93. There is clearly a need to perform more research on Tug1 to get a more in-depth understanding of its functions, and confirm what has been found in these different types of cancer. The disparity seen thus far however, may be due to differences in functions of this lncRNA in different cellular contexts, something that may be expected based on what we have already discovered about the functions of miRNA in cancer. LncRNA activator of enhancer domains (LED) has recently been identified via genome-wide profiling as a p53 induced lncRNAs that acts as an enhancer to regulate p2194. LED knockdown reduces p21 enhancer induction, activity, and cell cycle arrest following p53 activation. LED was identified and its function assessed in MCF-7 cells, however it has also been identified in a genome wide profile of colon cancer cells, though its specific function in this cellular context will need to be investigated95. Also identified in genome wide screening in colon cancer cells, PR-lncRNA-1 and PR-lncRNA-10 were identified as transcriptional targets of p53, that then act to regulate the transcription of target genes. These lncRNAs, may have potential tumor suppressor like function, and seem to play a role in regulating p53 anti-apoptotic and cell cycle regulatory functions. They may be important lncRNAs to investigate further96. Perhaps one of the more interesting p53 regulated lncRNAs is PVT1, which is transcriptionally induced by p53. Evidence suggests that PVT1 has an anti-apoptotic effect in colon cancer cells, and promotes proliferation and invasion50,97. PVT1 expression is also increased in colon cancer patients and increased expression predicts poor prognosis. At the same time, miR-1204 is also encoded from the PVT1 locus and seems to increase apoptosis and inhibit cell cycle progression50. This demonstrates the complex and dynamic nature of the relationship between p53 and non-coding RNAs. Linc-Regulator Of Reprogramming (Linc-ROR) is a transcriptional target of p53, and inhibits p53 related apoptosis and cell cycle arrest98. Beyond GI cancers, PANDA has been identified as a lncRNA that is a direct transcriptional target of p53. However, its function in GI cancers has not been investigated. This is something that needs to be further investigated as PANDA may have some roles in regulating apoptosis and cell cycle arrest in the p53 pathway99. Table 3 summarizes the p53 regulated lncRNAs based on their critical molecular and cellular functions in GI cancers.\n\n*--Role not clear, or conflicting reports in different cancer types\n\n\np53 regulation by lncRNA\n\nClearly there are quite a few lncRNA that are regulated by p53 that are already known to play important roles in cancer, and undoubtedly more will be discovered in the near future. Like miRNAs however, the relationship between p53 and lncRNAs works both ways, and there have been several lncRNAs discovered to regulate p53 as well. LncRNAs can function as modulators by preventing p53 degradation. One example is human maternally expressed gene 3 (MEG3). MEG3 is a non-coding RNA that functions as a tumor suppressor in colon cancer cell lines. MEG3 down-regulates MDM2, which in turn up-regulates p53 expression level100. MEG3 can inhibit cell proliferation in the absence of p53, suggesting a possible p53 independent tumor suppressor role. LncRNAs can also inactivate p53 function and H19 is an example. The H19 lncRNA has been demonstrated to be associated with p53 in gastric cancer101. Such interaction resulted in partial inactivation of p53. Metastasis associated lung adenocarcinoma transcript 1 (MALAT-1) is another lncRNA that seems to regulate p53. In the case of MALAT-1, it seems to be a negative regulator of p53, and depletion of MALAT-1 leads to an increase in p53 expression102. In colon cancer, MALAT-1 has increased expression in cancer tissue vs. normal. Increased MALAT-1 is associated with poor patient prognosis103. In colon cancer cell lines, overexpression of MALAT-1 promotes proliferation, migration and invasion. These functions are associated with regulation of A-kinase anchor protein 9 (AKAP-9) by MALAT-1104. LincRNA-ROR acting in a feedback loop, is also able to regulate p53, and knockdown of lincRNA-ROR leads to an increase in genes in the p53 pathway response98,105. There is also recent evidence that lincRNA-ROR expression is reduced in colon cancer, however more needs to be done to investigate this role106. Table 4 summarizes lncRNAs that regulate p53 in GI cancers. Through their regulation by p53 or their ability to regulate p53, lncRNAs clearly have important functions in the p53 network, and our appreciation of these roles will continue to grow as we discover additional lncRNAs and elucidate their functions in cancer. Figure 2 depicts lncRNAs’ roles in the p53 regulatory network.\n\n*--Role not clear, or conflicting reports in different cancer types\n\nlncRNAs, have a function in regulating p53. p53 in turn regulates the expression of several different lncRNAs. The lncRNAs involved in the p53 network regulate cellular functions such as proliferation, apoptosis, invasion and migration. In this figure, solid lines represent direct regulation, while dashed lines represent indirect, or poorly characterized regulation.\n\n\nSummary\n\nThe research community continues to push the boundaries of the p53 regulatory networks beyond protein coding genes to non-coding RNAs and other novel entities. There are many circular RNAs that have been discovered recently107,108. The impact of p53 on circular RNAs in GI cancer will potentially be an important field to explore going forward. As protein coding genes only represent a small percentage of our genome, we can expect more exciting discoveries in the non-coding RNA field impacted by p53. We hope that with the advancement of high throughput genomics technology and computational biology approaches, we can fully access the complete spectrum and scope of the p53 regulatory network. Such insight will provide a foundation to study other key proteins in cancer and other diseases. It will also help us to develop novel therapeutic strategies to combat cancer109.",
"appendix": "Author contributions\n\n\n\nAndrew Fesler, Ning Zhang and Jingfang Ju wrote the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis study was supported by National Institute of Health/National Cancer Institute R01CA155019 (J. Ju), R33CA147966 (J. Ju).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nWe apologize to our colleagues whose research was not cited in this review due to space limitations and timing.\n\n\nReferences\n\nKress M, May E, Cassingena R, et al.: Simian virus 40-transformed cells express new species of proteins precipitable by anti-simian virus 40 tumor serum. J Virol. 1979; 31(2): 472–483. PubMed Abstract | Free Full Text\n\nLane DP, Crawford LV: T antigen is bound to a host protein in SV40-transformed cells. Nature. 1979; 278(5701): 261–263. 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FEBS Lett. 2014; 588(16): 2610–2615. PubMed Abstract | Publisher Full Text\n\nMercer TR, Dinger ME, Mattick JS: Long non-coding RNAs: insights into functions. Nat Rev Genet. 2009; 10(3): 155–159. PubMed Abstract | Publisher Full Text\n\nPonting CP, Oliver PL, Reik W: Evolution and functions of long noncoding RNAs. Cell. 2009; 136(4): 629–641. PubMed Abstract | Publisher Full Text\n\nPonjavic J, Ponting CP, Lunter G: Functionality or transcriptional noise? Evidence for selection within long noncoding RNAs. Genome Res. 2007; 17(5): 556–565. PubMed Abstract | Publisher Full Text | Free Full Text\n\nIdogawa M, Ohashi T, Sasaki Y, et al.: Identification and analysis of large intergenic non-coding RNAs regulated by p53 family members through a genome-wide analysis of p53-binding sites. Hum Mol Genet. 2014; 23(11): 2847–2857. PubMed Abstract | Publisher Full Text\n\nHuarte M, Guttman M, Feldser D, et al.: A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response. Cell. 2010; 142(3): 409–419. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYoon JH, Abdelmohsen K, Srikantan S, et al.: LincRNA-p21 suppresses target mRNA translation. Mol Cell. 2012; 47(4): 648–655. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDimitrova N, Zamudio JR, Jong RM, et al.: LincRNA-p21 activates p21 in cis to promote Polycomb target gene expression and to enforce the G1/S checkpoint. Mol Cell. 2014; 54(5): 777–790. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYoon JH, Srikantan S, Gorospe M: MS2-TRAP (MS2-tagged RNA affinity purification): tagging RNA to identify associated miRNAs. Methods. 2012; 58(2): 81–87. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhai H, Fesler A, Schee K, et al.: Clinical significance of long intergenic noncoding RNA-p21 in colorectal cancer. Clin Colorectal Cancer. 2013; 12(4): 261–266. PubMed Abstract | Publisher Full Text\n\nYang F, Zhang H, Mei Y, et al.: Reciprocal regulation of HIF-1α and lincRNA-p21 modulates the Warburg effect. Mol Cell. 2014; 53(1): 88–100. PubMed Abstract | Publisher Full Text\n\nWang G, Li Z, Zhao Q, et al.: LincRNA-p21 enhances the sensitivity of radiotherapy for human colorectal cancer by targeting the Wnt/β-catenin signaling pathway. Oncol Rep. 2014; 31(4): 1839–1845. PubMed Abstract | Publisher Full Text\n\nMarín-Béjar O, Marchese FP, Athie A, et al.: Pint lincRNA connects the p53 pathway with epigenetic silencing by the Polycomb repressive complex 2. Genome Biol. 2013; 14(9): R104. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu Q, Huang J, Zhou N, et al.: LncRNA loc285194 is a p53-regulated tumor suppressor. Nucleic Acids Res. 2013; 41(9): 4976–4987. PubMed Abstract | Publisher Full Text | Free Full Text\n\nQi P, Xu MD, Ni SJ, et al.: Low expression of LOC285194 is associated with poor prognosis in colorectal cancer. J Transl Med. 2013; 11: 122. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTong YS, Zhou XL, Wang XW, et al.: Association of decreased expression of long non-coding RNA LOC285194 with chemoradiotherapy resistance and poor prognosis in esophageal squamous cell carcinoma. J Transl Med. 2014; 12: 233. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDing YC, Yu W, Ma C, et al.: Expression of long non-coding RNA LOC285194 and its prognostic significance in human pancreatic ductal adenocarcinoma. Int J Clin Exp Pathol. 2014; 7(11): 8065–8070. PubMed Abstract | Free Full Text\n\nQi P, Xu MD, Shen XH, et al.: Reciprocal repression between TUSC7 and miR-23b in gastric cancer. Int J Cancer. 2015; 137(6): 1269–1278. PubMed Abstract | Publisher Full Text\n\nYoung TL, Matsuda T, Cepko CL: The noncoding RNA taurine upregulated gene 1 is required for differentiation of the murine retina. Curr Biol. 2005; 15(6): 501–512. PubMed Abstract | Publisher Full Text\n\nZhang EB, Yin DD, Sun M, et al.: P53-regulated long non-coding RNA TUG1 affects cell proliferation in human non-small cell lung cancer, partly through epigenetically regulating HOXB7 expression. Cell Death Dis. 2014; 5(5): e1243. PubMed Abstract | Publisher Full Text | Free Full Text\n\nXu Y, Wang J, Qiu M, et al.: Upregulation of the long noncoding RNA TUG1 promotes proliferation and migration of esophageal squamous cell carcinoma. Tumour Biol. 2015; 36(3): 1643–1651. PubMed Abstract | Publisher Full Text\n\nTan J, Qiu K, Li M, et al.: Double-negative feedback loop between long non-coding RNA TUG1 and miR-145 promotes epithelial to mesenchymal transition and radioresistance in human bladder cancer cells. FEBS Lett. 2015; 589(20 Pt B): 3175–81. PubMed Abstract | Publisher Full Text\n\nLéveillé N, Melo CA, Rooijers K, et al.: Genome-wide profiling of p53-regulated enhancer RNAs uncovers a subset of enhancers controlled by a lncRNA. Nat Commun. 2015; 6: 6520. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAllen MA, Andrysik Z, Dengler VL, et al.: Global analysis of p53-regulated transcription identifies its direct targets and unexpected regulatory mechanisms. eLife. 2014; 3: e02200. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSánchez Y, Segura V, Marín-Béjar O, et al.: Genome-wide analysis of the human p53 transcriptional network unveils a lncRNA tumour suppressor signature. Nat Commun. 2014; 5: 5812. 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FEBS J. 2012; 279(17): 3159–3165. PubMed Abstract | Publisher Full Text\n\nTripathi V, Shen Z, Chakraborty A, et al.: Long noncoding RNA MALAT1 controls cell cycle progression by regulating the expression of oncogenic transcription factor B-MYB. PLoS Genet. 2013; 9(3): e1003368. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZheng HT, Shi DB, Wang YW, et al.: High expression of lncRNA MALAT1 suggests a biomarker of poor prognosis in colorectal cancer. Int J Clin Exp Pathol. 2014; 7(6): 3174–3181. PubMed Abstract | Free Full Text\n\nYang MH, Hu ZY, Xu C, et al.: MALAT1 promotes colorectal cancer cell proliferation/migration/invasion via PRKA kinase anchor protein 9. Biochim Biophys Acta. 2015; 1852(1): 166–174. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLoewer S, Cabili MN, Guttman M, et al.: Large intergenic non-coding RNA-RoR modulates reprogramming of human induced pluripotent stem cells. Nat Genet. 2010; 42(12): 1113–1117. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRezaei M, Emadi-Baygi M, Hoffmann MJ, et al.: Altered expression of LINC-ROR in cancer cell lines and tissues. Tumour Biol. 2015; 1–7. PubMed Abstract | Publisher Full Text\n\nGuo JU, Agarwal V, Guo H, et al.: Expanded identification and characterization of mammalian circular RNAs. Genome Biol. 2014; 15(7): 409. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJeck WR, Sharpless NE: Detecting and characterizing circular RNAs. Nat Biotechnol. 2014; 32(5): 453–461. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJu J, Jiang J, Fesler A: miRNA: the new frontier in cancer medicine. Future Med Chem. 2013; 5(9): 983–985. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTarasov V, Jung P, Verdoodt B, et al.: Differential regulation of microRNAs by p53 revealed by massively parallel sequencing: miR-34a is a p53 target that induces apoptosis and G1-arrest. Cell cycle. 2007; 6(13): 1586–1593. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13581",
"date": "20 May 2016",
"name": "Yuichiro Tanaka",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this review, the authors systematically summarize the interplay between non-coding RNAs and the P53 pathway, with emphasis on how this affects gastrointestinal cancer. The non-coding RNAs are focused on miRNA and lncRNA, and how these both regulate and get regulated by P53.\n\nThe review is solid. The authors highlight each of the major miRNA or lncRNA involved with p53 in gastrointestinal cancer in a concise way. Mutant p53 and its effects on these noncoding RNA’s are also discussed. They go into regulation of noncoding RNA or P53, not only by direct but indirect mechanisms and include genes involved in this regulation. They also touch up on noncoding RNA that have opposite effects depending on cancer type and thus, not biased. References are appropriate. The use of tables and figures highlight the key points made for each of the miRNA’s and lncRNA’s and thus, make it easier for the reader to follow.\n\nComment: The summary section is not really a summary of what was discussed. It is more of forthcoming ideas. Recommend adding a few sentences or a paragraph summarizing what was actually discussed since this is a summary section. This can then be followed by what is currently stated such as circular RNA, genomics technology and computational approaches, and the rest, as future approaches. Alternatively, the heading could be changed to “Future approaches” or something similar, if permissible.",
"responses": []
},
{
"id": "14211",
"date": "07 Jun 2016",
"name": "Rajeev S Samant",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article by Fesler et al. is a timely summary of the state of the art of P53 related regulatory mechanisms with specific emphasis on colon cancer. P53 is certainly the most critical node of oncogenesis and progression. With the rapidly advancing information about the importance of non-coding RNA in the field of cancer biology it is critical to establish an integrated picture that allows us to make working models for regulation. The review has done a perfect job towards this by providing two well designed figures. Overall it is a very timely review of this ever evolving field. It is really appreciated that the authors have provided a bit of introduction on what are miRNAs and what are Lnc RNAs. It will make it easy for readers that are new to this field to appreciate the review.\nIt is intriguing that the authors have provided a glimpse of future directions for the field. Overall I do not have any major or necessary suggestions. However I do have a curious request. Authors may wish to provide insight on if there is any way to integrate the miRNA based pathways to mRNA based pathways and if that has been done for P53 field.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-756
|
https://f1000research.com/articles/5-752/v1
|
26 Apr 16
|
{
"type": "Review",
"title": "The myofibroblast in wound healing and fibrosis: answered and unanswered questions",
"authors": [
"Marie-Luce Bochaton-Piallat",
"Giulio Gabbiani",
"Boris Hinz",
"Giulio Gabbiani",
"Boris Hinz"
],
"abstract": "The discovery of the myofibroblast has allowed definition of the cell responsible for wound contraction and for the development of fibrotic changes. This review summarizes the main features of the myofibroblast and the mechanisms of myofibroblast generation. Myofibroblasts originate from a variety of cells according to the organ and the type of lesion. The mechanisms of myofibroblast contraction, which appear clearly different to those of smooth muscle cell contraction, are described. Finally, we summarize the possible strategies in order to reduce myofibroblast activities and thus influence several pathologies, such as hypertrophic scars and organ fibrosis.",
"keywords": [
"Myofibroblast",
"mechanotransduction",
"myofibroblast generation",
"myofibroblast contraction",
"hypertrophic scars",
"organ fibroses"
],
"content": "Introduction\n\nWound healing has interested the medical praxis since the beginning of human history, but for many centuries the effort of physicians has concentrated more on empirical therapeutic strategies rather than on the understanding of its biological mechanisms. During the last few centuries, however, a gradual progress has been achieved in defining and understanding several physiological aspects of wound healing. In particular, the formation and evolution of granulation tissue has been described in the second half of the 18th century, mainly thanks to the British surgeon John Hunter, and in the last century it has been shown that wound contraction is due to an active contraction of granulation tissue, mainly thanks to the work of the French surgeon Alexis Carrel1. The discovery of the myofibroblast more than forty years ago allowed the identification of the cell responsible for this phenomenon2. This coincided with the early establishment of the cytoskeleton concept3. The myofibroblast was then considered to be a contractile non-muscle cell4. Since the first description, our knowledge of myofibroblast structure and activity has progressed enormously. The purpose of this article is to briefly summarize the biological features of the myofibroblast and to discuss some of the promising strategies to suppress this cell’s activity in order to achieve the possibility of influencing important pathological situations, such as fibrotic lesions, that presently cannot be cured successfully.\n\n\nEvolution of the myofibroblast concept\n\nInitially, the myofibroblast was described by means of electron microscopy revealing the presence of prominent cytoplasmic microfilament bundles and peripheral focal adhesions in the fibroblastic cells of granulation tissue2. Electron microscopy further showed the existence of gap junctions connecting myofibroblasts, thus reinforcing the suggestion of similarity between myofibroblasts and smooth muscle (SM) cells5. The production of a specific antibody against α-SM actin, the actin isoform typical of vascular SM cells, allowed the demonstration that myofibroblasts express α-SM actin and are hence equipped with a typical SM protein6.\n\nIn the early phases of granulation tissue formation after the production of a wound, local fibroblasts begin moving from the unaffected dermis and subcutaneous tissue toward the wound center and acquire bundles of microfilaments, similar to in vitro stress fibers, containing only β- and γ-cytoplasmic actins; these cells have been named proto-myofibroblasts and evolve generally into α-SM actin containing differentiated myofibroblasts that are responsible for wound contraction7. When the wound closes, myofibroblasts disappear through apoptosis8, and a scar persists in the affected area. When myofibroblasts persist in a closed wound, they indicate the development of a hypertrophic scar, an important pathological evolution of wound healing, particularly frequent after burn injury7,9. Myofibroblasts are also present in all fibrotic diseases, such as scleroderma, as well as liver, kidney, and lung fibrosis and are prominent in heart failure and repair after myocardial infarction. Finally, myofibroblasts are the main components of the stromal reaction to several epithelial tumors7,10. It should be noted that both proto-myofibroblasts and differentiated myofibroblasts can be found in normal tissues, for example in lung alveolar septa and at the periphery of intestinal crypts, respectively7, where they probably exert physiological mechanical functions.\n\nMuch work has been performed in order to find specific markers of the myofibroblastic phenotype. As stated above, α-SM actin discriminates myofibroblasts from fibroblasts and has become the most used marker for this cell. Several other markers have been proposed, but no specific marker has been identified until now. However, several SM cell markers are not expressed in myofibroblasts, such as SM myosin heavy chains, h-caldesmon, and smoothelin11; this underlines the functional differences between the two cells, as we shall discuss below.\n\n\nMechanisms of myofibroblast formation and evolution\n\nAfter a wounding insult, blood extravasation and clot formation occur followed by an inflammatory phase that allows an accumulation of blood-borne cells, liberating many cytokines and growth factors essential for the onset of the following phase of granulation tissue formation12. In early granulation tissue, motile proto-myofibroblasts appear and start to synthesize extracellular matrix (ECM) components, such as collagen type I and III7. Another relevant new component of ECM is cellular fibronectin, which contains the alternatively spliced segments EDA (or EIIIA) and EDB (or EIIIB) and is present in connective tissue during development but reappears in pathological situations such as granulation tissue and fibrotic lesions13,14. EDA fibronectin has been shown to be essential for the differentiation of myofibroblasts15. The early transformation of fibroblasts into proto-myofibroblasts appears to depend on the mechanical changes taking place in the wound compared to the normal skin, in particular increased stiffness7,16; moreover, platelet-derived growth factor has been shown to stimulate proto-myofibroblast motility17. The development of α-SM actin synthesizing differentiated myofibroblasts is essentially due to the action of transforming growth factor (TGF)-β1 in the presence of EDA fibronectin15,18. TGF-β1 is present in the ECM as a large latent complex including latency-associated peptide and latent TGF-β1-binding protein9. It can be liberated by proteolytic enzymes as well as by integrin-dependent mechanically induced mechanisms9. The force exerted by stress fibers through transmembrane integrins is enough to free TGF-β1 from the large latent complex, and the strained ECM is capable of maintaining a feedback mechanism, assuring a persistent fibrotic activity by the myofibroblast19,20; moreover, straining and/or stiffening of the ECM can increase the availability of TGF-β121,22 (Figure 1). Straining and stiffening are consequences of fibroblast and myofibroblast remodeling activities. Matrix stiffening is additionally promoted by fibroblast and inflammatory cell-derived collagen crosslinking enzymes including lysyl oxidases and lysyl oxidase-like enzymes, as reviewed in 20,23. The incorporation of α-SM actin into stress fibers has been shown to significantly increase the contractile activity of fibroblasts24; the force generated by myofibroblast stress fibers is transmitted to the ECM through focal adhesions that contain specialized transmembrane integrins25. As stated above, myofibroblasts disappear when a wound closes, mainly through apoptosis8. The mechanisms of apoptosis induction, or conversely of myofibroblast persistence, in hypertrophic scars are not clarified; however, the importance of a focal adhesion complex component, Hic-5, a paxillin homologue, in maintaining the myofibroblast phenotype has been demonstrated26. Moreover, myofibroblasts can disappear by means of accelerated senescence27 and even, at least in some instances, revert to the normal phenotype28.\n\nIn normal connective tissue, loosely arranged collagen protects resident fibroblasts and latent transforming growth factor (TGF)-β1 complexes from being strained with the extracellular matrix (ECM). Fibroblasts in normal tissue do not express or present the integrin receptors that bind and activate latent TGF-β1. During tissue repair and in organ fibrosis, activated myofibroblasts express αv integrins that connect the contractile actin/myosin cytoskeleton to latent TGF-β1. The accumulation of collagen and its excessive remodeling (crosslinking) by these myofibroblasts result in denser and straighter ECM fibers, which leads to overall higher tissue stiffness. Because ECM fibers are straighter, even smaller strains applied to the fibrotic ECM externally, or by residing myofibroblasts, will be sufficient for the release of active TGF-β1 (modified from Hinz B and Suki B [2016] Does breathing amplify fibrosis? Editorial on 21).\n\n\nMechanism of myofibroblast contraction and mechanotransduction\n\nThe initial studies suggesting a similarity between myofibroblast and SM cell contractile activities4 were gradually reconsidered in light of the consideration of the different functional activities of the two cells: SM cell contraction is rapid and short in duration, whereas myofibroblast contraction is rather long lasting and results in a permanent tissue retraction, probably stabilized by ECM deposition7. Evidence has gradually accumulated suggesting that, in addition to the classical calcium-calmodulin-myosin light chain kinase-dependent SM cell contraction mechanism11, myofibroblast contractile activity can be regulated by the activation of the Rho/ROCK/myosin light chain phosphatase pathway7,29–31. This long-duration type of contraction underlines an essential difference between the SM cell and the myofibroblast and could explain the characteristic tissue remodeling activity of this cell.\n\nThe forces generated by the contractile activity of myofibroblasts are transmitted to the surrounding ECM through specialized focal adhesions containing transmembrane integrins. As a result, strained and more compacted ECM develops. Interestingly, the mechanical conditions generated by the myofibroblast feedback leads to their sustained pro-fibrotic activity10,19. More recently, it has been shown that megakaryoblastic leukemia factor 1 (MKL1), also named myocardin-related transcription factor (MRTF), is crucial for myofibroblast differentiation and mechanotransduction. In various myofibroblast precursor cells, it links mechanical stress to the transcriptional activity of muscle-cell genes via the polymerization state of actin32–36. Inhibition of MRTF reduces experimentally induced skin fibrosis in rodents37, as well as differentiation of human colonic myofibroblasts38. Similarly, YAP/TAZ transcription factors, known to mediate mechano-responses39, positively regulate myofibroblast activation40–44.\n\n\nMyofibroblast origin\n\nOne of the intriguing features of the myofibroblast is that it can derive from a large variety of cell types. As stated above, mesenchymal cells with myofibroblastic features are present in normal tissues, including the uterine submucosa, follicles of lymph nodes and spleen, intestinal villous cores and crypts, theca externa of the ovary, periodontal ligament, adrenal capsule, lung septa, and bone marrow stroma7. It appears more and more evident that the term fibroblast comprises a heterogeneous cell population10,45, thus it is possible that only some specialized fibroblastic cells generate myofibroblasts in normal and pathological situations, as recently supported by studies on skin and heart fibrosis46–48. During pathological situations, local fibroblasts allegedly represent the major source of myofibroblastic cells10; however, in particular cases, other local cells become the main precursors, such as SM cells in coronary atheromatous plaque49, keratocytes in the eye50,51, perisinusoidal cells in the liver52, and pericytes in many organs53–55. In addition, myofibroblasts may develop through the process of epithelial-mesenchymal transition56,57 or endothelial-mesenchymal transition58. Finally, myofibroblasts may derive from circulating bone marrow-derived specialized inflammatory cells called fibrocytes and participate in fibrotic lesions in several organs59,60. Circulating and/or resident mesenchymal stromal/stem cells (MSCs) are prominent precursors of myofibroblasts in a variety of organs and injury situations61,62. Because delivery of MSCs is an attractive approach to regenerate organs that are beyond repair within the body’s own capacity63,64, understanding MSC-to-myofibroblast activation (fibrogenesis) will be of particular importance for the success of MSC therapies40,65.\n\nThere is considerable variability and dispute in the literature concerning the proportions of different precursor cells contributing to the myofibroblast pool. However, different research groups seem to generally agree that myofibroblast sources can differ between different individuals, organs, animals, or particular injury models. For example, in the corneal fibrosis model, 30 to 70% of myofibroblasts are derived from bone marrow-derived precursors depending on the type of wound and the individual that is wounded (reviewed in 51). Thus, using drugs that modulate myofibroblast activation from specific precursor cells can be an effective strategy to inhibit fibrosis in an organ-specific manner.\n\n\nPerspectives\n\nAs we have seen, the myofibroblast represents an eclectic cell whose major function appears to be the remodeling of connective tissue. If we consider the variety of its possible origins, the myofibroblast could be defined as a phenotypic variant of many cell types, developing upon the appearance of appropriate stimuli. Myofibroblast activity can be physiological, e.g., regulation of ventilation/perfusion ratio in pulmonary alveoli, and useful for wound healing but noxious in many pathological situations, e.g., fibrotic lesions7.\n\nDespite many attempts and despite the clinical importance of fibrotic lesions9,12, there is not at present any clinically accepted pharmacological tool capable of influencing myofibroblast activity and thus the evolution of these diseases. We shall discuss some strategies that could possibly lead to the development of efficient tools. Despite the heterogeneity of origin, all differentiated myofibroblasts perform the same functions, i.e. tissue remodeling and synthesis of ECM. Hence, the processes regulating these functions appear to represent promising targets of therapeutic strategies. TGF-β1 would appear as an ideal target in order to control myofibroblast activity. Unfortunately, until now no relevant results have been obtained by using direct inhibitors; however, several pathways of TGF-β1 action remain to be explored and a number of clinical trials that target TGF-β1 are pending66. EDA fibronectin is necessary for myofibroblast differentiation15 and its absence results in wound healing or pulmonary fibrosis reduction67, suggesting that EDA fibronectin could be addressed as a therapeutic target. The observation that α-SM actin is essential for the remodeling activity of the myofibroblast and the finding that its N-terminal peptide Ac-EEED is essential for α-SM actin incorporation into stress fibers68 have suggested that this peptide could represent a tool for decreasing myofibroblast activity. This possibility has been demonstrated in vitro and in rat wound healing69, suggesting that this peptide or, possibly more efficiently, a mimetic compound could be used therapeutically. The recent observation that tropomyosin 1.6/7 isoforms play an essential role in the stable incorporation of α-SM actin into fibroblast stress fibers70 points to a new target for the reduction of α-SM actin expression in myofibroblasts with the consequent reduction of their remodeling activity71. Another way to regulate myofibroblast remodeling activity could be the control of the Rho/ROCK/myosin light chain phosphatase pathway. In this respect, it has been shown that the ROCK inhibitor Y-27632 decreases granulation tissue contraction31. Closely related to reducing cell contraction is the idea of blocking myofibroblast adhesion to the ECM via integrins. This will have two potential beneficial outcomes: reduced force transmission to the ECM and, provided the correct integrins are targeted, reduction of TGF-β1 activation72,73.\n\nFurther work is needed in order to develop an efficient therapeutic approach to excessive wound healing and fibrotic diseases. Importantly, myofibroblast research will need to cross organ boundaries to exploit the full potential of drugs that are effective in one system but not studied in others. For instance, mitomycin C was shown to block fibrosis development after eye surgery74, but its action in other organs is unknown. We feel confident that during the next few years the above-discussed strategies will allow the discovery of new, efficient tools to control these devastating diseases.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe research of BH is supported by Canadian Institutes of Health Research (CIHR) (grants #210820, #286920, #286720, and #497202), the Collaborative Health Research Programme (CIHR/NSERC) (grants #1004005 and #413783), and the Canada Foundation for Innovation and Ontario Research Fund (CFI/ORF) (grant #26653). The research of MLBP is supported by the Swiss National Science Foundation (grant #146790/1).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nWhipple AO: The story of wound healing and wound repair. Springfield, 1963. Reference Source\n\nGabbiani G, Ryan GB, Majno G: Presence of modified fibroblasts in granulation tissue and their possible role in wound contraction. Experientia. 1971; 27(5): 549–50. PubMed Abstract | Publisher Full Text\n\nZampieri F, Coen M, Gabbiani G: The prehistory of the cytoskeleton concept. Cytoskeleton (Hoboken). 2014; 71(8): 464–71. PubMed Abstract | Publisher Full Text\n\nGabbiani G, Hirschel BJ, Ryan GB, et al.: Granulation tissue as a contractile organ. A study of structure and function. J Exp Med. 1972; 135(4): 719–34. PubMed Abstract | Free Full Text\n\nGabbiani G, Chaponnier C, Hüttner I: Cytoplasmic filaments and gap junctions in epithelial cells and myofibroblasts during wound healing. J Cell Biol. 1978; 76(3): 561–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSkalli O, Ropraz P, Trzeciak A, et al.: A monoclonal antibody against alpha-smooth muscle actin: a new probe for smooth muscle differentiation. J Cell Biol. 1986; 103(6 Pt 2): 2787–96. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTomasek JJ, Gabbiani G, Hinz B, et al.: Myofibroblasts and mechano-regulation of connective tissue remodelling. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nHinz B: The extracellular matrix and transforming growth factor-β1: Tale of a strained relationship. Matrix Biol. 2015; 47: 54–65. PubMed Abstract | Publisher Full Text\n\nFroese AR, Shimbori C, Bellaye PS, et al.: Stretch Induced Activation of TGF-β1 in Pulmonary Fibrosis. Am J Respir Crit Care Med. 2016. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKlingberg F, Chow ML, Koehler A, et al.: Prestress in the extracellular matrix sensitizes latent TGF-β1 for activation. J Cell Biol. 2014; 207(2): 283–97. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKlingberg F, Hinz B, White ES: The myofibroblast matrix: implications for tissue repair and fibrosis. J Pathol. 2013; 229(2): 298–309. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHinz B, Celetta G, Tomasek JJ, et al.: Alpha-smooth muscle actin expression upregulates fibroblast contractile activity. Mol Biol Cell. 2001; 12(9): 2730–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDugina V, Fontao L, Chaponnier C, et al.: Focal adhesion features during myofibroblastic differentiation are controlled by intracellular and extracellular factors. J Cell Sci. 2001; 114(Pt 18): 3285–96. PubMed Abstract\n\nVarney SD, Betts CB, Zheng R, et al.: Hic-5 is required for myofibroblast differentiation by regulating mechanically dependent MRTF-A nuclear accumulation. J Cell Sci. 2016; 129(4): 774–87. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJun JI, Lau LF: The matricellular protein CCN1 induces fibroblast senescence and restricts fibrosis in cutaneous wound healing. Nat Cell Biol. 2010; 12(7): 676–85. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKisseleva T, Cong M, Paik Y, et al.: Myofibroblasts revert to an inactive phenotype during regression of liver fibrosis. Proc Natl Acad Sci U S A. 2012; 109(24): 9448–53. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nParizi M, Howard EW, Tomasek JJ: Regulation of LPA-promoted myofibroblast contraction: role of Rho, myosin light chain kinase, and myosin light chain phosphatase. Exp Cell Res. 2000; 254(2): 210–20. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nAnderson S, DiCesare L, Tan I, et al.: Rho-mediated assembly of stress fibers is differentially regulated in corneal fibroblasts and myofibroblasts. Exp Cell Res. 2004; 298(2): 574–83. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nTomasek JJ, Vaughan MB, Kropp BP, et al.: Contraction of myofibroblasts in granulation tissue is dependent on Rho/Rho kinase/myosin light chain phosphatase activity. Wound Repair Regen. 2006; 14(3): 313–20. PubMed Abstract | Publisher Full Text\n\nCrider BJ, Risinger GM Jr, Haaksma CJ, et al.: Myocardin-related transcription factors A and B are key regulators of TGF-β1-induced fibroblast to myofibroblast differentiation. J Invest Dermatol. 2011; 131(12): 2378–85. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nScharenberg MA, Pippenger BE, Sack R, et al.: TGF-β-induced differentiation into myofibroblasts involves specific regulation of two MKL1 isoforms. J Cell Sci. 2014; 127(Pt 5): 1079–91. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nZhou Y, Huang X, Hecker L, et al.: Inhibition of mechanosensitive signaling in myofibroblasts ameliorates experimental pulmonary fibrosis. J Clin Invest. 2013; 123(3): 1096–108. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSmall EM, Thatcher JE, Sutherland LB, et al.: Myocardin-related transcription factor-a controls myofibroblast activation and fibrosis in response to myocardial infarction. Circ Res. 2010; 107(2): 294–304. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLuchsinger LL, Patenaude CA, Smith BD, et al.: Myocardin-related transcription factor-A complexes activate type I collagen expression in lung fibroblasts. J Biol Chem. 2011; 286(51): 44116–25. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHaak AJ, Tsou PS, Amin MA, et al.: Targeting the myofibroblast genetic switch: inhibitors of myocardin-related transcription factor/serum response factor-regulated gene transcription prevent fibrosis in a murine model of skin injury. J Pharmacol Exp Ther. 2014; 349(3): 480–6. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nJohnson LA, Rodansky ES, Haak AJ, et al.: Novel Rho/MRTF/SRF inhibitors block matrix-stiffness and TGF-β-induced fibrogenesis in human colonic myofibroblasts. Inflamm Bowel Dis. 2014; 20(1): 154–65. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nHalder G, Dupont S, Piccolo S: Transduction of mechanical and cytoskeletal cues by YAP and TAZ. Nat Rev Mol Cell Biol. 2012; 13(9): 591–600. PubMed Abstract | Publisher Full Text\n\nTalele NP, Fradette J, Davies JE, et al.: Expression of α-Smooth Muscle Actin Determines the Fate of Mesenchymal Stromal Cells. Stem Cell Reports. 2015; 4(6): 1016–30. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCalvo F, Ege N, Grande-Garcia A, et al.: Mechanotransduction and YAP-dependent matrix remodelling is required for the generation and maintenance of cancer-associated fibroblasts. Nat Cell Biol. 2013; 15(6): 637–46. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLiu F, Lagares D, Choi KM, et al.: Mechanosignaling through YAP and TAZ drives fibroblast activation and fibrosis. Am J Physiol Lung Cell Mol Physiol. 2015; 308(4): L344–57. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSpeight P, Nakano H, Kelley TJ, et al.: Differential topical susceptibility to TGFβ in intact and injured regions of the epithelium: key role in myofibroblast transition. Mol Biol Cell. 2013; 24(21): 3326–36. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPiersma B, de Rond S, Werker PM, et al.: YAP1 Is a Driver of Myofibroblast Differentiation in Normal and Diseased Fibroblasts. Am J Pathol. 2015; 185(12): 3326–37. PubMed Abstract | Publisher Full Text\n\nDriskell RR, Lichtenberger BM, Hoste E, et al.: Distinct fibroblast lineages determine dermal architecture in skin development and repair. Nature. 2013; 504(7479): 277–81. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nRinkevich Y, Walmsley GG, Hu MS, et al.: Skin fibrosis. Identification and isolation of a dermal lineage with intrinsic fibrogenic potential. Science. 2015; 348(6232): aaa2151. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMoore-Morris T, Guimarães-Camboa N, Banerjee I, et al.: Resident fibroblast lineages mediate pressure overload-induced cardiac fibrosis. J Clin Invest. 2014; 124(7): 2921–34. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMarangoni RG, Korman BD, Wei J, et al.: Myofibroblasts in murine cutaneous fibrosis originate from adiponectin-positive intradermal progenitors. Arthritis Rheumatol. 2015; 67(4): 1062–73. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHao H, Gabbiani G, Camenzind E, et al.: Phenotypic modulation of intima and media smooth muscle cells in fatal cases of coronary artery lesion. Arterioscler Thromb Vasc Biol. 2006; 26(2): 326–32. PubMed Abstract | Publisher Full Text\n\nHinz B: Myofibroblasts. Exp Eye Res. 2016; 142: 56–70. PubMed Abstract | Publisher Full Text\n\nTorricelli AA, Santhanam A, Wu J, et al.: The corneal fibrosis response to epithelial-stromal injury. Exp Eye Res. 2016; 142: 110–8. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFriedman SL: Evolving challenges in hepatic fibrosis. Nat Rev Gastroenterol Hepatol. 2010; 7(8): 425–36. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKramann R, Schneider RK, DiRocco DP, et al.: Perivascular Gli1+ progenitors are key contributors to injury-induced organ fibrosis. Cell Stem Cell. 2015; 16(1): 51–66. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGreenhalgh SN, Iredale JP, Henderson NC: Origins of fibrosis: pericytes take centre stage. F1000Prime Rep. 2013; 5: 37. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nDuffield JS: Cellular and molecular mechanisms in kidney fibrosis. J Clin Invest. 2014; 124(6): 2299–306. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nZeisberg M, Kalluri R: The role of epithelial-to-mesenchymal transition in renal fibrosis. J Mol Med (Berl). 2004; 82(3): 175–81. PubMed Abstract | Publisher Full Text\n\nKim KK, Kugler MC, Wolters PJ, et al.: Alveolar epithelial cell mesenchymal transition develops in vivo during pulmonary fibrosis and is regulated by the extracellular matrix. Proc Natl Acad Sci U S A. 2006; 103(35): 13180–5. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHo WT, Chang JS, Su CC, et al.: Inhibition of matrix metalloproteinase activity reverses corneal endothelial-mesenchymal transition. Am J Pathol. 2015; 185(8): 2158–67. PubMed Abstract | Publisher Full Text\n\nGalligan CL, Fish EN: The role of circulating fibrocytes in inflammation and autoimmunity. J Leukoc Biol. 2013; 93(1): 45–50. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nReilkoff RA, Bucala R, Herzog EL: Fibrocytes: emerging effector cells in chronic inflammation. Nat Rev Immunol. 2011; 11(6): 427–35. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBarbosa FL, Chaurasia SS, Cutler A, et al.: Corneal myofibroblast generation from bone marrow-derived cells. Exp Eye Res. 2010; 91(1): 92–6. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nDirekze NC, Hodivala-Dilke K, Jeffery R, et al.: Bone marrow contribution to tumor-associated myofibroblasts and fibroblasts. Cancer Res. 2004; 64(23): 8492–5. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBehfar A, Crespo-Diaz R, Terzic A, et al.: Cell therapy for cardiac repair--lessons from clinical trials. Nat Rev Cardiol. 2014; 11(4): 232–46. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBianco P, Cao X, Frenette PS, et al.: The meaning, the sense and the significance: translating the science of mesenchymal stem cells into medicine. Nat Med. 2013; 19(1): 35–42. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHinz B: The myofibroblast in connective tissue repair and regeneration. In: Regenerative Medicine and Biomaterials for the Repair of Connective Tissues: Elsevier; 2010; 39–80. Publisher Full Text\n\nFriedman SL, Sheppard D, Duffield JS, et al.: Therapy for fibrotic diseases: nearing the starting line. Sci Transl Med. 2013; 5(167): 167sr1. PubMed Abstract | Publisher Full Text\n\nMuro AF, Moretti FA, Moore BB, et al.: An essential role for fibronectin extra type III domain A in pulmonary fibrosis. Am J Respir Crit Care Med. 2008; 177(6): 638–45. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nChaponnier C, Goethals M, Janmey PA, et al.: The specific NH2-terminal sequence Ac-EEED of alpha-smooth muscle actin plays a role in polymerization in vitro and in vivo. J Cell Biol. 1995; 130(4): 887–95. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHinz B, Gabbiani G, Chaponnier C: The NH2-terminal peptide of alpha-smooth muscle actin inhibits force generation by the myofibroblast in vitro and in vivo. J Cell Biol. 2002; 157(4): 657–63. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPrunotto M, Bruschi M, Gunning P, et al.: Stable incorporation of α-smooth muscle actin into stress fibers is dependent on specific tropomyosin isoforms. Cytoskeleton (Hoboken). 2015; 72(6): 257–67. PubMed Abstract | Publisher Full Text\n\nGunning PW, Hardeman EC, Lappalainen P, et al.: Tropomyosin - master regulator of actin filament function in the cytoskeleton. J Cell Sci. 2015; 128(16): 2965–74. PubMed Abstract | Publisher Full Text\n\nReed NI, Jo H, Chen C, et al.: The αvβ1 integrin plays a critical in vivo role in tissue fibrosis. Sci Transl Med. 2015; 7(288): 288ra79. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHenderson NC, Arnold TD, Katamura Y, et al.: Targeting of αv integrin identifies a core molecular pathway that regulates fibrosis in several organs. Nat Med. 2013; 19(12): 1617–24. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSanthiago MR, Netto MV, Wilson SE: Mitomycin C: biological effects and use in refractive surgery. Cornea. 2012; 31(3): 311–21. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "13414",
"date": "26 Apr 2016",
"name": "Jack Gauldie",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13415",
"date": "26 Apr 2016",
"name": "Steven E Wilson",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-752
|
https://f1000research.com/articles/5-750/v1
|
26 Apr 16
|
{
"type": "Review",
"title": "Extracorporeal membrane oxygenation 2016: an update",
"authors": [
"Warwick Butt",
"Graeme MacLaren",
"Warwick Butt"
],
"abstract": "The use of extracorporeal membrane oxygenation (ECMO) is an important issue for intensivists, critical care nurses, surgeons, cardiologists, and many others. There has been a continued increase in the number of centres performing ECMO. This review examines novel applications and recent trends in the use of ECMO over the last 2 years. These include ECMO to facilitate the safe use of other treatments, changing the timing of initiation, newer equipment and better biocompatibility, and the ability of ECMO programs to essentially choose which cluster of potential complications they are prepared to accept. ECMO continues to evolve, diversify in its applications, and improve in safety.",
"keywords": [
"fulminant respiratory failure",
"neonatal respiratory failure",
"severe pulmonary hypertension",
"cardiac failure",
"mechanical circulatory support",
"Extra Corporeal Life Support"
],
"content": "Introduction\n\nExtracorporeal membrane oxygenation (ECMO) was developed as a treatment for fulminant respiratory failure (hence its name) in adults in the early 1970s by removing venous blood from the body, adding oxygen, removing carbon dioxide, and returning it to the patient. This therapy was limited to 5 days, and vascular access was obtained by cannulation of the femoral artery and vein. Subsequently, in the early 1980s, this veno-arterial mode was changed to veno-venous, but only a few centres persisted with the technology because bleeding and poor outcomes were common. Similarly, in children, ECMO was first used for neonatal respiratory failure, but, in newborns and young children, severe pulmonary hypertension and poor cardiac function often accompanied respiratory failure. Hence, its use for mechanical circulatory support when isolated cardiac failure occurred was a logical extension. In adults, after cardiac surgery, intra-aortic balloon pumps were commonly used as mechanical circulatory support, but these were very difficult to use successfully in small children (because of the child’s high heart rate and smaller blood vessels). Therefore, veno-arterial ECMO was used in children with cardiac failure, and ECMO became extra-corporeal life support. In the 2000s, a better understanding of the pathophysiology of ECMO and diseases for which it was used led to a rapid re-emergence of this as a therapy for all patients with cardio-respiratory failure; various modifications allowed single or biventricular support, oxygenation or carbon dioxide removal, for short or longer periods of time. This was extensively reviewed in F1000Prime Reports 2013; the concluding paragraph in that review stated that “ECMO is a standard therapy in critical care. It is used as a treatment for acute severe cardiorespiratory failure and as a resuscitation strategy in many clinical scenarios. It is also used as a ‘bridge’ to other treatments and transplantation. It continues to be applied to more complex and chronic situations. It is being integrated into multiple-organ support therapies. Substantial improvements in biotechnology and clinical practices over the last 40 years have allowed ECMO to provide a vital role in acute organ support in patients of all ages. It is likely that further such advances will diminish complication rates, facilitate more widespread adoption of the technology in middle- and high-income countries, and improve outcomes from refractory heart, lung, and multiorgan failure”1.\n\nOver the last 2 years, the use of ECMO continues to be an important issue for clinicians: a literature search with ECMO as a key word and including only English language articles and publication dates from 2014 to 2015 yielded 932 articles, 123 reviews, and 16 editorials. During this period, there have also been continued increases in the number of centres performing ECMO (Figure 1) and in the amount of paediatric and neonatal use in children with cardiac disease as well as a large increase in the use of ECMO for adult respiratory and cardiac disease (Table 1). The latest cumulative survival reported by the Extracorporeal Life Support Organization is shown in Table 2. The last 2 years have revealed many new uses and issues involving ECMO. These are summarised in the sections below.\n\nECPR, extracorporeal cardiopulmonary resuscitation.\n\n\nCentres experimenting with new applications of extracorporeal membrane oxygenation\n\nThe most important issues in the last few years for clinicians involved in ECMO depend on the type and experience of the ECMO program and the hospital in which ECMO is performed. New programs are focusing on standard uses of ECMO, systems for safe use and deployment of ECMO, management of patients on ECMO, understanding indications and contraindications, education, and simulation. Long-standing programs, on the other hand, are focusing on improving outcomes by considering alternative ECMO strategies (such as normal or high flow for septic shock, different types of peripheral or trans-thoracic cannulation, and initiating ECMO earlier) or different patient groups that hitherto were not considered (such as patients with immune suppression or cancer, pregnant women2, or the elderly3). Perhaps more controversially, some centres have begun research in using it as a bridge to solid organ transplantation4, referred to as extracorporeal support-assisted organ donation. Once a patient has died in a controlled environment as part of a donation-after-cardiac death (DCD) strategy, an aortic balloon is inserted into the proximal descending aorta to prevent re-establishing cerebral blood flow and the patient is cannulated onto femoral-femoral ECMO. This improves abdominal organ metabolic support and has been associated with improved graft survival in the recipient5.\n\n\nThe use of extracorporeal membrane oxygenation to facilitate the safe use of other treatments\n\nThe safety and capacity to transport patients on ECMO now allow the consideration of the use of ECMO as a haemodynamically stable platform in order to facilitate complex surgery6 or interventional cardiology procedures7. Moreover, ECMO stabilises deranged cardiopulmonary physiology in unstable patients such that therapies deemed unsafe—haemodialysis in newborn infants or support of vital organ function during rewarming from accidental hypothermia, such as in avalanche victims8–10, for example—can be undertaken safely. Comparable to cardiopulmonary bypass facilitating safe cardiac surgery, ECMO provides a haemodynamically stable platform to facilitate these other therapies that otherwise might not be tolerated by the patient. Patients can have complex chemotherapy11 or immunotherapy regimens that cause a severe systemic inflammatory response and are supported with ECMO. ECMO is increasingly being used as a long-term bridge to facilitate lung transplantation12,13. The use of ECMO in adult cardiorespiratory failure to resuscitate from cardiogenic shock and transport to local cardiac surgical centres for long-term support with ventricular assist devices and transplant programs is also increasingly available14,15.\n\n\nWhen to initiate extracorporeal membrane oxygenation\n\nThe implementation of ECMO is changing as the technology continues to improve. Rather than being used as a last resort or rescue therapy, it has become a standard therapy and increasingly is being implemented earlier in the course of disease in attempts to minimise multi-organ failure. The timing of initiation varies between centres and is a balance of risk for each particular program; it is not a case of better or worse but of the appropriate use of the therapy given each program’s system of use. The realisation that increased survival occurred with earlier use of veno-venous ECMO is now being applied to veno-arterial ECMO in many centres. The role of ECMO in resuscitation and stabilisation of cardiac arrest or cardiogenic shock also varies.\n\n\nNew equipment for extracorporeal membrane oxygenation: cannulas and biocompatible circuits\n\nNewer cannulas with improved flow characteristics or more biocompatible plastics are being developed that will further improve the safety of ECMO. The ultimate goal is to have a circuit that is fully biocompatible with no need for anticoagulation and no risk of thromboembolism or haemorrhage. Excellent circuit flow characteristics and self-regulated flow-demand loops are only a generation away16–18.\n\n\nChoose your complication\n\nCurrently, after weighing the benefits and risks to determine an approach that suits their needs, each program can essentially choose which cluster of potential complications they are prepared to accept. For instance, the type and extent of anticoagulation contribute to the likelihood of promoting either surgical bleeding or thromboembolism. A transthoracic cannulation approach leads to a higher incidence of bleeding and mediastinitis but also allows larger cannulas with increased flow. Jugular-carotid cannulation is more likely to cause cerebral thromboembolic and haemorrhagic complications than central cannulation19. Femoro-femoral cannulation is more likely to have differential hypoxemia or limb ischaemia than other types of cannulation. These are very important issues, as each program has a different cannulation strategy influenced by the skill set of the cannulating doctor; intensivists are different from general surgeons, who are different from cardiac surgeons. Comparison of results clearly requires knowledge of similarities and differences between programs.\n\n\nConclusions\n\nECMO continues to evolve, diversify in its applications, and improve in safety. Patient outcome is centre specific and very dependent on local factors, local indications, and contraindications. Evaluation of each centre’s results should be done with these factors in mind; the ECMO community continues to share results and knowledge in an attempt to improve patient outcomes.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nButt W, Maclaren G: Extracorporeal membrane oxygenation. F1000Prime Rep. 2013; 5: 55. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSharma NS, Wille KM, Bellot SC, et al.: Modern use of extracorporeal life support in pregnancy and postpartum. ASAIO J. 2015; 61(1): 110–4. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMendiratta P, Tang X, Collins RT 2nd, et al.: Extracorporeal membrane oxygenation for respiratory failure in the elderly: a review of the Extracorporeal Life Support Organization registry. ASAIO J. 2014; 60(4): 385–90. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nOniscu GC, Randle LV, Muiesan P, et al.: In situ normothermic regional perfusion for controlled donation after circulatory death--the United Kingdom experience. Am J Transplant. 2014; 14(12): 2846–54. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCarter T, Bodzin AS, Hirose H, et al.: Outcome of organs procured from donors on extracorporeal membrane oxygenation support: an analysis of kidney and liver allograft data. Clin Transplant. 2014; 28(7): 816–20. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLang G, Ghanim B, Hötzenecker K, et al.: Extracorporeal membrane oxygenation support for complex tracheo-bronchial procedures†. Eur J Cardiothorac Surg. 2015; 47(2): 250–5; discussion 256. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nShebani SO, Ng GA, Stafford P, et al.: Radiofrequency ablation on veno-arterial extracorporeal life support in treatment of very sick infants with incessant tachymyopathy. Europace. 2015; 17(4): 622–7. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nDunne B, Christou E, Duff O, et al.: Extracorporeal-assisted rewarming in the management of accidental deep hypothermic cardiac arrest: a systematic review of the literature. Heart Lung Circ. 2014; 23(11): 1029–35. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nRuttmann E, Weissenbacher A, Ulmer H, et al.: Prolonged extracorporeal membrane oxygenation-assisted support provides improved survival in hypothermic patients with cardiocirculatory arrest. J Thorac Cardiovasc Surg. 2007; 134(3): 594–600. PubMed Abstract | Publisher Full Text\n\nSawamoto K, Bird SB, Katayama Y, et al.: Outcome from severe accidental hypothermia with cardiac arrest resuscitated with extracorporeal cardiopulmonary resuscitation. Am J Emerg Med. 2014; 32(4): 320–4. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWorku B, DeBois W, Sobol I, et al.: Extracorporeal Membrane Oxygenation as a Bridge through Chemotherapy in B-Cell Lymphoma. J Extra Corpor Technol. 2015; 47(1): 52–4. PubMed Abstract | Free Full Text | Faculty Opinions Recommendation\n\nInci I, Klinzing S, Schneiter D, et al.: Outcome of Extracorporeal Membrane Oxygenation as a Bridge To Lung Transplantation: An Institutional Experience and Literature Review. Transplantation. 2015; 99(8): 1667–71. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nChiumello D, Coppola S, Froio S, et al.: Extracorporeal life support as bridge to lung transplantation: a systematic review. Crit Care. 2015; 19(1): 19. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPellegrino V, Hockings LE, Davies A: Veno-arterial extracorporeal membrane oxygenation for adult cardiovascular failure. Curr Opin Crit Care. 2014; 20(5): 484–92. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nAbrams D, Combes A, Brodie D: Extracorporeal membrane oxygenation in cardiopulmonary disease in adults. J Am Coll Cardiol. 2014; 63(25 Pt A): 2769–78. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMajor TC, Brisbois EJ, Jones AM, et al.: The effect of a polyurethane coating incorporating both a thrombin inhibitor and nitric oxide on hemocompatibility in extracorporeal circulation. Biomaterials. 2014; 35(26): 7271–85. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nStang K, Borchardt R, Neumann B, et al.: First In Vivo Results of a Novel Pediatric Oxygenator with an Integrated Pulsatile Pump. ASAIO J. 2015; 61(5): 574–82. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nTeman NR, Demos DS, Bryner BS, et al.: In vivo testing of a novel blood pump for short-term extracorporeal life support. Ann Thorac Surg. 2014; 98(1): 97–102. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nTeele SA, Salvin JW, Barrett CS, et al.: The association of carotid artery cannulation and neurologic injury in pediatric patients supported with venoarterial extracorporeal membrane oxygenation*. Pediatr Crit Care Med. 2014; 15(4): 355–61. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nExtracorporeal Life Support Organization: ECLS Registry Report. International Summary, Ann Arbor. 2016. Reference Source"
}
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[
{
"id": "13452",
"date": "26 Apr 2016",
"name": "Gail Mary Annich",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13453",
"date": "26 Apr 2016",
"name": "Margaret Parker",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13451",
"date": "26 Apr 2016",
"name": "Niranjan Kissoon",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-750
|
https://f1000research.com/articles/5-749/v1
|
26 Apr 16
|
{
"type": "Review",
"title": "The dynamics of spatio-temporal Rho GTPase signaling: formation of signaling patterns",
"authors": [
"Rafael Dominik Fritz",
"Olivier Pertz",
"Rafael Dominik Fritz"
],
"abstract": "Rho GTPases are crucial signaling molecules that regulate a plethora of biological functions. Traditional biochemical, cell biological, and genetic approaches have founded the basis of Rho GTPase biology. The development of biosensors then allowed measuring Rho GTPase activity with unprecedented spatio-temporal resolution. This revealed that Rho GTPase activity fluctuates on time and length scales of tens of seconds and micrometers, respectively. In this review, we describe Rho GTPase activity patterns observed in different cell systems. We then discuss the growing body of evidence that upstream regulators such as guanine nucleotide exchange factors and GTPase-activating proteins shape these patterns by precisely controlling the spatio-temporal flux of Rho GTPase activity. Finally, we comment on additional mechanisms that might feed into the regulation of these signaling patterns and on novel technologies required to dissect this spatio-temporal complexity.",
"keywords": [
"Rho GTPase",
"Guanine nucleotide exchange factors",
"GTPase-activating proteins",
"spatio-temporal control",
"signalling patterns"
],
"content": "Introduction\n\nSince the seminal articles from Allan Hall’s lab back in the early 1990s1–3, we have learned much about the biology of Rho GTPases4–9. The combination of experimental approaches, including genetics in model organisms, cell biology, and biochemistry, was key to establish the basics of Rho GTPase signaling. These techniques revealed the principles of GTPase regulation by guanine nucleotide exchange factors (GEFs), GTPase-activating proteins (GAPs), and Rho guanine nucleotide dissociation inhibitors (RhoGDIs), and identified effectors that exert specific biological functions downstream of Rho GTPases. This uncovered a surprisingly intertwined network of mutual regulatory protein complexes in which Rho GTPases are vastly outnumbered by GEFs, GAPs, and effectors10.\n\nIn the last 15 years, an additional layer of complexity was superimposed on Rho GTPase biology. Fluorescence resonance energy transfer (FRET)-based and other biosensors enabled investigators to capture the spatio-temporal dimensions of Rho GTPase signaling in living cells with unprecedented resolution10,11. Visualizing Rho GTPase activity drastically changed our perception of Rho GTPase signaling and implies a higher degree of complexity than the classic ON-OFF schemes typically depicted in feed-forward, linear signaling networks. This fresh view emphasizes the importance of analyzing Rho GTPase activity dynamics by microscopy instead of analyzing steady states of limited information content by biochemistry.\n\nUnderstanding that Rho GTPase signaling is organized in spatio-temporal patterns poses important novel questions: How are these signaling activity patterns generated? What forms their structural basis? And which technologies do we need to dissect the mechanisms of pattern formation in the future? In this review, we will survey the spatio-temporal activity patterns that have been documented to date and highlight possible answers to these intriguing questions. Then we discuss important players that might feed into this spatio-temporal regulation, and we comment on novel technologies to analyze the latter.\n\n\nBiosensors visualize Rho GTPase activity domains in time and space\n\nThe traditional model of Rho GTPase signaling during cell migration states that Rac and Cdc42, respectively, regulate membrane protrusion and filopodia formation at the leading edge, whereas RhoA controls contractility at the trailing edge12. However, the use of FRET biosensors proved this view to be too simplistic. Accordingly, Rac1, Cdc42, RhoA, and RhoC activity has been found at the leading edge in randomly migrating fibroblasts (Figure 1A). While Rac1 forms a broad activity gradient that spans several micrometers into the cell interior13–18, Cdc4214,16,19,20, RhoA16,21–24, and RhoC24 activity zones are somewhat narrower. Despite overlapping activity zones, the dynamics of all four Rho GTPases precisely correlate with cell edge protrusion/retraction dynamics16,24,25. RhoA is also activated at the trailing edge during retraction and this suggests that RhoA is regulated by different GEFs, GAPs, and couples to distinct effectors to regulate edge dynamics or tail retraction10.\n\n(A) Rho GTPase activity gradients in randomly migrating fibroblasts. The activity is highest at the cell edge and declines toward the cell center. Color code is displayed to the right. (B, C) Reshaping of Rho GTPase activity zones in response to growth factor treatment in fibroblasts (B) or MTLN3 epithelial cells (C). (D) Rac1 activity in colliding fibroblasts. Rac1 is activated in a broad gradient in the contact-free protrusion (bottom) but restricted to a sharp band at the tip of the contact protrusion (top). (E) RhoA activity at the tip of filopodia during growth cone protrusion and in the entire growth cone during collapse. (F) Concentric Rho GTPase signaling zones during wound closure in Xenopus oocytes. (G) Distinct Rho GTPase signaling domains in macropinocytosis. (H) Rho GTPase activity domains during invadopodia assembly and disassembly. EGF, epidermal growth factor; PDGF, platelet-derived growth factor.\n\nThe RhoA activity pattern considerably changes if fibroblasts are stimulated with platelet-derived growth factor (PDGF). On timescales of 10 to 20 minutes, PDGF stimulation leads to increased edge protrusion that correlates with immediate decrease of RhoA activity23,25. On a timescale of hours, homogeneous application of PDGF locks fibroblasts in a permanent state of persistent migration in one direction26. This depends on the formation of podosome-like structures (PLSs), which broadly inhibits RhoA at the leading edge and simultaneously restricts RhoA activity to a sharp zone at the lamellipodium tip (Figure 1B). Here, the PLSs function as a spatially organizing cytoskeletal module that defines the zones of high and low RhoA activity. This spatial organization of RhoA signaling uncouples myosin-based, actin retrograde flow from the leading edge, which is essential to maintain a polarized state required for persistent migration. Importantly, RhoA activity remains present at the back of PDGF-treated cells during tail retraction, further underpinning the local nature of spatio-temporal Rho GTPase regulation in different subcellular regions. Similarly, in epithelial cancer cells, epidermal growth factor (EGF) confines RhoA activity to the very edge of the cell and additionally shifts the diffuse RhoC activity pattern some micrometers back behind the edge in motile cells27 (Figure 1C). This is thought to position distinct effector pathways to coordinate leading-edge dynamics. These examples illustrate that activity patterns of particular Rho GTPases are highly dependent on the cellular context (that is, presence or absence of a growth factor, morphodynamic behavior such as edge protrusion and tail retraction, and cell type).\n\nThe plasticity of such spatio-temporal activity patterns was further demonstrated in fibroblasts undergoing cell-cell collisions18. Colliding cells have two types of protrusions: contact protrusions, which touch the neighbor cell, and contact-free protrusions. The two protrusion types fundamentally differ in edge dynamics, which correlate with distinct Rac1 activity patterns. As observed earlier13–17, Rac1 activity forms a broad gradient in contact-free protrusions. In marked contrast, Rac1 activity is constrained to a narrow band at the tip of contact protrusions (Figure 1D). This activity pattern correlates with formation of a robust F-actin band that allows contact protrusions to efficiently squeeze below adjacent cells. Again, the precise cellular context (presence or absence of cell-cell contact) dictates the shape of the Rho GTPase activity zone.\n\nRho GTPase activity zones have also been reported in cellular processes different from cell migration. In growth cones of neuroblastoma cells, RhoA is activated either locally or globally depending on the morphodynamic process21. During growth cone protrusion, RhoA activity is detectable at the tip of F-actin bundles forming filopodia, where it most likely couples to the effector formin mDia to drive actin polymerization (Figure 1E). In contrast, the collapsing growth cone displays bulk RhoA activity all over the retracting structure. Here, RhoA might interact with its effector Rho kinase to stimulate global actomyosin contractility.\n\nThe Xenopus oocyte wound repair process is another intriguing example of Rho GTPase activity patterning as it features two adjacent activity zones (Figure 1F). Wounding rapidly activates both RhoA and Cdc42 that form local mutual exclusive activity rings that encircle the wound. The RhoA and Cdc42 zones colocalize with ring-like arrays of myosin-2 and F-actin, respectively, and coordinate the spatial regulation of both cytoskeletal structures to close the actomyosin ring inward and to seal the wound28,29.\n\nFurther concentric Rho GTPase activity zones were also found during macropinocytosis and the formation of invadopodia. In both cases, active RhoC surrounds macropinosomes24 and invadopodia30, and additional Rho GTPases are active in the core of these structures (Figure 1G, H). RhoC is active during the entire macropinocytotic process24, whereas Rac131 and RhoA23 activities peak before and after vesicle closure, respectively (Figure 1G). Similar activity separation can be observed in invadopodia. Here, concentric RhoC activity drives invadopodia assembly30, whereas Rac1 activity in the invadopodium’s core promotes its disassembly17 (Figure 1H).\n\nIn summary, multiple Rho GTPase activities can either overlap in time and space or form distinct zones, which are subject to modulation by growth factors and cell-cell interactions. Thus, rather than the classic dogma in which one Rho GTPase regulates one specific cytoskeletal structure, multiple Rho GTPases collaborate to fine-tune cytoskeletal dynamics at a specific subcellular location. The Rho GTPase activity zones then precisely position and coordinate multiple cytoskeletal regulating activities in time and space.\n\n\nGEF/GAP-mediated Rho GTPase fluxes underlie spatio-temporal signaling patterns\n\nAn important question that immediately comes up is how these sharp or diffuse Rho GTPase activity zones are created. A possible answer to this fundamental question comes from the Rho GTPase life cycle (Figure 2A). Rho GTPases are molecular switches that alternate between the active, GTP-loaded and inactive, GDP-loaded states. GEFs exchange GDP to GTP, whereas GAPs stimulate the hydrolysis of GTP to GDP. Additionally, active GTP-loaded GTPases reside in the membrane compartment where they interact with effector proteins. Conversely, inactive, GDP-loaded Rho GTPases are sequestered in the cytoplasm by RhoGDI. It has been proposed that this Rho GTPase cycling enables the dynamic signaling fluxes that are required to build spatially restricted signaling patterns. This has been mostly explored in the Xenopus egg wounding model system32. As described above, oocyte wounding induces RhoA and Cdc42 activation within 20 seconds. At first, RhoA and Cdc42 activities form shallow and overlapping gradients that become steeper and eventually establish distinct concentric zones 90 seconds after wounding28. Interestingly, both Rho GTPases cycle more rapidly between GTP- and GDP-loaded states inside activity zones than outside33. Moreover, RhoA becomes preferentially inactivated at the trailing edge of the zone (that is, more distal with respect to the wound center), showing that a signaling treadmill generates a GTPase activity flux by proximal RhoA activation and distal RhoA inactivation within the zone (Figure 2B). Experimental work and mathematical modeling further showed that the RhoA and Cdc42 concentric zones are partially shaped by the dual GEF-GAP Abr34,35. Abr is a GEF for RhoA, Rac, and Cdc42 and concomitantly a GAP for Rac and Cdc4236. Abr docks on active RhoA to generate a positive feedback loop that impinges on RhoA itself and simultaneously inhibits Cdc42 in the RhoA zone34,35. These data indicate that GEFs and GAPs regulate reaction-diffusion-based signaling fluxes that shape Rho GTPase activity zones during oocyte wound closure.\n\n(A) Rho GTPases are kept in the cytoplasm by RhoGDIs. Activation occurs through GEF-mediated GTP loading and insertion of the GTPase into the membrane, where it interacts with downstream effectors. GAPs stimulate GTP hydrolysis to inactivate the Rho GTPase, which is sequestered in the cytoplasm by RhoGDI. (B) RhoA signaling treadmill during oocyte wound closure. RhoA activation and inactivation occurs at opposite boundaries of the activity zone. RhoGDI is omitted for clarity. (C) Possible view of the Rho GTPase lifecycle as a reaction-diffusion system. Spatial subcellular separation of GEFs and GAPs may determine distinct activation/deactivation zones, which maintain the Rho GTPase activity flux. GAP, GTPase-activating protein; GDP, guanosine diphosphate; GEF, guanosine nucleotide exchange factor; GTP, guanosine triphosphate.\n\nSimilar mechanisms have been documented in mammalian cells. In the case of invadopodia formation, RhoC activity is spatially restricted in a concentric zone surrounding the invadopodium core through the interplay of p190RhoGEF and p190RhoGAP30. Outside the core, p190RhoGEF activates RhoC, while p190RhoGAP localizes to the inner of the core where it inhibits RhoC. Another example is the regulation of the exquisitely focused RhoA activity pattern at the tip of F-actin bundles that form neuronal growth cone filopodia (Figure 1D). A recent study identified the RhoA-specific GAP DLC1 (deleted in liver cancer 1) to spatially regulate the filopodial RhoA activity pattern37. RNA interference (RNAi)-mediated DLC1 knockdown leads to widening of the RhoA activity domain, suggesting that DLC1 acts by shaping the focused RhoA activity zone at filopodial tips. Together, these data clearly suggest that fine spatial regulation of Rho GTPase activation/deactivation cycles enables the formation of a signaling pattern.\n\nTaking into consideration the aforementioned examples, we propose a general mechanism of Rho GTPase pattern formation based on reaction-diffusion systems. Such a Rho GTPase activity pattern would be dynamically maintained by successive cycles of (1) local activation by a GEF, (2) slow plasma membrane (PM) diffusion (0.02 to 1.36 µm2 s−1)38,39 from a zone preferentially occupied by a GEF to a zone preferentially occupied by a GAP, (3) local inactivation by the GAP, and (4) membrane extraction by RhoGDI. Once in the cytoplasm, the Rho GTPase-RhoGDI complex can quickly diffuse (10 to 100 µm2 s−1)40 and reach an equilibrium within the cytosol before being used for subsequent activation cycles (Figure 2C). Such a constant reaction-diffusion system requires spatially regulated GEFs and GAPs. Additionally, regulation of membrane/cytosol partitioning by RhoGDI will most likely also feed into the shaping of spatio-temporal Rho GTPase activity patterns. Membrane/cytosol partitioning is subject to modulation by multiple protein kinases, which determine the release of specific Rho GTPases from the cytosolic RhoGDI-bound pool or the affinity of Rho GTPases for membranes (reviewed in 5). The impact of RhoGDI on Rho GTPase activity pattern formation is underpinned by the comparison of RhoGDI-responsive and non-responsive FRET sensors21. In the case of RhoA, a biosensor version that does not bind to RhoGDI and thus is constitutively targeted to the PM shows global activation in the neuronal growth cone. In contrast, a biosensor that retains the ability to bind to RhoGDI displays the highly focused filopodial RhoA activity pattern described above (Figure 1E). It is therefore important to consider that constitutively membrane-bound Rho GTPase FRET biosensors might miss some aspects of spatio-temporal Rho GTPase signaling.\n\nOnly a few examples of spatio-temporal Rho GTPase regulation mechanisms by GEFs and GAPs have been studied up to now. An important question that emerges from the initial data we have discussed above is how GEFs and GAPs are themselves spatially regulated. Below, we review a large number of possible GEF/GAP interactions that might feed into this spatio-temporal regulation. This provides an idea of the players and mechanisms that will have to be studied to understand spatio-temporal Rho GTPase regulation.\n\n\nSpatio-temporal regulation of GEFs and GAPs\n\nAlmost all GEFs bear a lipid-interaction domain37,39,40: a pleckstrin homology (PH), a DOCK homology region 1 (DHR-1), or a Bin-Amphiphysin-Rvs (BAR) domain41–43. Many GAPs also contain a variety of lipid-binding domains44. Since PH and DHR-1 domains vary in their binding specificity and affinity for phospholipids such as phosphatidylinositol 4,5-bisphosphate (PIP2) and phosphatidylinositol (3-5)-triphosphate42,45,46, GEFs and GAPs might be directed to specific PM subdomains (Figure 3A). Indeed, distinct lipid distributions were found in the RhoA and Cdc42 zones during oocyte wound closure47. Furthermore, specific sorting has been shown for the Rac GAP β2-chimaerin that localizes and inhibits Rac in the non-lipid raft zone48 and p190 RhoGAP, which translocates to lipid rafts to cease RhoA activity in response to growth factor treatment49. BAR domains recognize membrane curvature and thus target proteins to specific PM topologies50. One GEF and seven GAPs with different BAR domains have been identified to date51,52. The F-BAR domain of srGAP2 was recently shown to tether the Rac GAP exclusively to convex, protruding membranes where it limits the duration of Rac1 activity during cell-cell collision without affecting the shape of the Rac1 activity pattern per se18. Since srGAP2 integrates both membrane topology and Slit-Robo repulsive signals, this mechanism ensures that srGAP2 inactivates Rac1 at the right subcellular region and in a specific morphodynamic phase.\n\n(A) Membrane composition and topology influence the recruitment of GEFs and GAPs to the PM. Lipid rafts and phospholipid-enriched zones attract GEFs and facilitate Rho GTPase activation. Certain GAPs can localize to protruding convex cell edges (white arrowheads), while concave cell edges can recruit both GEFs and GAPs (black arrowheads). The key to the left indicates the various symbols. RhoGDI is omitted for clarity. (B) Receptor tyrosine kinases (RTKs) and PDZ-domain scaffold proteins cluster GEFs and might create local Rho GTPase activation zones. (C) Focal adhesions (FAs) serve as GEF enrichment structures and locally activate Rho GTPase signaling. F-actin and microtubules sequester and inactivate GEFs and GAPs that become active upon release into the cytosol. GAP, GTPase-activating protein; GEF, guanosine nucleotide exchange factor; PDZ, PSD95-Dlg1-ZO1; PM, plasma membrane.\n\nBesides mere targeting of GAPs, lipids also influence both GAP activity and the specificity toward particular Rho GTPases in vitro. The Rac- and Cdc42-specifc GAP n-Chimaerin is inhibited by phosphatidylserine and phosphatidic acid but activated by PIP2 and arachidonic acid53. Some phospholipids have also been reported to switch the specificity of p190RhoGAP by inhibiting its GAP activity for Rho and stimulating its activity for Rac154. Since lipid distribution can be highly ordered in the PM, these results strongly suggest that both lipid species and membrane topology can create Rho GTPase signaling microdomains.\n\nReceptor tyrosine kinases (RTKs) play a paramount role in Rho GTPase activation55 and are very likely to determine their spatio-temporal activity in two ways. First, RTKs alter the lipid composition of the PM through activation of phosphatidylinositol-3 kinase and phospholipase Cγ56 to influence GEF and GAP targeting as described above. Second, RTKs recruit GEFs directly and activate them by phosphorylation (Figure 3B). For instance, Tiam157, LARG58, Vav1-359–62, Vsm63, Dbs64, RasGfr165, and Kalirin66 are found in complexes with various RTKs and some of them also become activated by phosphorylation59,60,62–65,67,68. Since RTKs themselves are capable of generating spatial signaling patterns at the level of their phosphorylation69, this might serve as an additional way to spatio-temporally regulate Rho GTPases. G protein-coupled receptors have also been shown to feed into the regulation of Rho GTPase signaling70, but their contribution to spatio-temporal regulation has not yet been explored.\n\nA striking feature in approximately 40% of GEFs is the presence of a PSD95-Dlg1-ZO1 (PDZ) domain-binding motif at the C-terminus. These GEFs interact with various scaffold proteins such as Shank and Scribble71. Shank positions β-Pix in the postsynaptic density region to locally control Rac1-dependent dendritic spine formation72,73, whereas Scribble recruits β-Pix to the PM to regulate thyrotropin receptor trafficking74,75. Interestingly, the Scribble/β-Pix interaction is modulated by TIP-1, which competes for β-Pix binding and affects its subcellular localization76.\n\nAdhesion complexes are further important hubs for spatial regulation of GEFs and GAPs (Figure 3C). β-Pix is directly recruited from the cytosol to focal adhesions (FAs) at the leading edge of migrating cells through the interaction with the Paxillin-GIT-PAK complex39,77. At adhesions, focal adhesion kinase (FAK) phosphorylates β-Pix to strengthen the β-Pix-Rac1 interaction and thus enhance Rac1 recruitment to adhesions78,79. Notably, the balance of β-Pix distribution between FAs and endosomes is regulated by the PDZ domain-containing sorting nexin 2780. Another GEF that activates Rac at FAs is DOCK180. Its polarized localization to the leading edge is mediated through interaction with the Paxillin-p130Cas-CrkII complex following integrin engagement81–83. Furthermore, the Rac GEF Tiam1 was found to bind to talin in FAs and to activate Rac1 in a PAR complex-dependent manner84. There are also several Rho-specific GEFs enriched at FAs in a FAK-dependent manner. Net1 is present in FA complexes at the leading and the trailing edge85, whereas PDZ-RhoGEF localizes to the trailing edge only86,87. LARG and p115RhoGEF also interact with FAK at adhesions86,88. These four Rho-specific GEFs seem to regulate similar processes, although it is not fully understood yet whether their functions are redundant or whether they depend on different upstream signals.\n\nThe cytoskeleton also tethers GEFs and GAPs. Active myosin II (MII), which generates actomyosin-based contractility, sequesters and inactivates β-Pix at actin fibers and thus confers an MII- and β-Pix-dependent front-back polarity in migrating cells89,90. Thus, MII orchestrates adhesion formation and maturation by adsorption and release of β-Pix. Notably, MII sequesters and inhibits GEFs containing a Dbl homology domain such as FGD1, Kalirin, LARG, DOCK180, Tiam1, Trio, GEF-H1, and Dbl89. F-actin also traps GAPs as FilGAP, which binds to the F-actin cross-linker filamin A. After mechanical deformation of F-actin branches, FilGAP is released and translocates to the PM to inhibit Rac at the leading edge91. Finally, microtubules tie and inactivate GEF-H1, which is released after the depolymerization of microtubules to stimulate RhoA activity and contractility at the leading edge92,93.\n\nIn summary, growth factors, mechanosensation, membrane topology/composition, and the actomyosin and tubulin cytoskeletons regulate the spatio-temporal aspects of Rho GTPase activity patterns, which in turn feedback on these different organizational and signaling levels. It is now time to explore how this plethora of different GEF/GAP regulatory mechanisms impact on spatio-temporal Rho GTPase activation.\n\n\nConclusions\n\nThe technological progress in the last 15 years has empowered us with the ability to monitor Rho GTPase signaling with high spatio-temporal resolution. With respect to initial models, this has revealed an unexpected spatio-temporal signaling complexity, which now needs to be systematically analyzed by perturbation of the different players we have discussed in this review. Because spatio-temporal Rho GTPase signaling patterns are constantly regulated on timescales of tens of seconds, novel technologies are required to perturb cell systems at that exact timescale. This can take advantage of existing techniques such as optogenetics or small-molecule dimerizers to control GEF/GAP targeting and activity94–98. Dissection of the complexity of spatio-temporal Rho GTPase signaling patterns will also require obtaining biophysical parameters with subcellular resolution, which can for example be inferred from fluorescence correlation spectroscopy99. Ultimately, such multidisciplinary approaches will inform mathematical models that can describe the network properties required to generate robust spatial signaling patterns100. In addition to in vitro experiments, analyzing Rho GTPase activity by FRET reporters in vivo101 will guarantee new insights, provided that RhoGDI-responsive sensors are used. Beyond the goal of understanding how Rho GTPase signaling is spatio-temporally regulated, these approaches will also unveil how Rho GTPase coordinately regulate different cytoskeletal polymers to fine-tune the highly complex and dynamic processes required for cell morphogenesis. We foresee that a limited number of conserved spatio-temporal Rho GTPase networks will emerge from systematic perturbation approaches. Tuning of a limited number of parameters might then allow the cell to repurpose such networks to regulate edge protrusion, growth cone motility, macropinocytosis, sealing of a cell wound, or other morphodynamic processes.\n\n\nAbbreviations\n\nBAR, Bin-Amphiphysin-Rvs; DHR-1, DOCK homology region 1; FA, focal adhesion; F-actin, filamentous actin; FAK, focal adhesion kinase; FRET, fluorescence resonance energy transfer; GAP, GTPase-activating protein; GEF, guanosine triphosphate exchange factor; GTP, guanosine triphosphate; PAK, p21-activated kinase; PDGF, platelet-derived growth factor; PDZ, PSD95-Dlg1-ZO1; PH, pleckstrin homology; PIP2, phosphatidylinositol 4,5-bisphosphate; PLS, podosome-like structure; PM, plasma membrane; RhoGDI, Rho guanine nucleotide dissociation inhibitor; RTK, receptor tyrosine kinase.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThis work is supported by a grant from the Swiss National Science Foundation.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nNobes CD, Hall A: Rho, rac, and cdc42 GTPases regulate the assembly of multimolecular focal complexes associated with actin stress fibers, lamellipodia, and filopodia. Cell. 1995; 81(1): 53–62. PubMed Abstract | Publisher Full Text\n\nRidley AJ, Hall A: The small GTP-binding protein rho regulates the assembly of focal adhesions and actin stress fibers in response to growth factors. Cell. 1992; 70(3): 389–99. PubMed Abstract | Publisher Full Text\n\nRidley AJ, Paterson HF, Johnston CL, et al.: The small GTP-binding protein rac regulates growth factor-induced membrane ruffling. Cell. 1992; 70(3): 401–10. 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}
|
[
{
"id": "13567",
"date": "26 Apr 2016",
"name": "Anne Debant",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13568",
"date": "26 Apr 2016",
"name": "Louis Hodgson",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-749
|
https://f1000research.com/articles/5-137/v1
|
04 Feb 16
|
{
"type": "Research Note",
"title": "Does inactivation of USP14 enhance degradation of proteasomal substrates that are associated with neurodegenerative diseases?",
"authors": [
"Daniel Ortuno",
"Holly J. Carlisle",
"Silke Miller",
"Daniel Ortuno",
"Holly J. Carlisle"
],
"abstract": "A common pathological hallmark of age-related neurodegenerative diseases is the intracellular accumulation of protein aggregates such as α-synuclein in Parkinson’s disease, TDP-43 in ALS, and tau in Alzheimer’s disease. Enhancing intracellular clearance of aggregation-prone proteins is a plausible strategy for slowing progression of neurodegenerative diseases and there is great interest in identifying molecular targets that control protein turnover. One of the main routes for protein degradation is through the proteasome, a multisubunit protease that degrades proteins that have been tagged with a polyubiquitin chain by ubiquitin activating and conjugating enzymes. Published data from cellular models indicate that Ubiquitin-specific protease 14 (USP14), a deubiquitinating enzyme (DUB), slows the degradation of tau and TDP-43 by the proteasome and that an inhibitor of USP14 increases the degradation of these substrates. We conducted similar experiments designed to evaluate tau, TDP-43, or α-synuclein levels in cells after overexpressing USP14 or knocking down endogenous expression by siRNA.",
"keywords": [
"Neurodegeneration",
"ubiquitin",
"proteasome",
"deubiquitinating enzyme",
"tau",
"TDP-43",
"ubiquitin-specific peptidase 14",
"protein clearance"
],
"content": "Introduction\n\nResearch on the ubiquitin-proteasome system has far reaching implications for the development of drugs to treat illnesses associated with the accumulation of misfolded proteins, including Alzheimer’s and Parkinson’s disease (Ciechanover & Kwon, 2015). Ubiquitin-specific protease 14 (USP14), like its yeast ortholog Ubp6, is a proteasome-associated deubiquitinating enzyme (DUB) that is activated upon binding to the proteasome and catalyzes the cleavage of ubiquitin subunits from substrates before degradation by the proteasome (Borodovsky et al., 2001; Hanna et al., 2006; Hu et al., 2005). By releasing ubiquitin molecules from the substrate, USP14/Ubp6 helps to prevent the rapid degradation of ubiquitin molecules together with the substrate protein (Hanna et al., 2007). A critical role of USP14 in stabilizing cellular ubiquitin levels was demonstrated in vivo in USP14 deficient axJ mice which display decreased ubiquitin levels in all tissues with the greatest loss observed at synaptic terminals (Anderson et al., 2005; Wilson et al., 2002).\n\nIn addition to maintaining cellular ubiquitin pools, USP14/Ubp6 has been shown to modulate substrate degradation. Goldberg and colleagues showed that upon binding to a substrate’s polyubiquitin chain, activated USP14/Ubp6 facilitates gate-opening of the proteasome (Peth et al., 2009). This mutual interaction of USP14/Ubp6 with the proteasome is thought to enhance selectivity of the proteasome for ubiquitinated proteins and couple deubiquitination to degradation. In contrast, Finley and colleagues found that USP14/Ubp6, and in some instances a catalytically inactive mutant (C114A in mammals), could cause an inhibition of the degradation of substrates (Hanna et al., 2006; Lee et al., 2010). For model substrates and ataxin3, this effect was shown to require USP14/Ubp6 protein but not its catalytic activity. For two proteins involved in neurodegenerative diseases, tau and TDP-43, inhibition of proteasomal degradation by USP14 was dependent on its deubiquitinating activity, since the catalytically inactive mutant had no effect (Lee et al., 2010). This led to the hypothesis that deubiquitination of substrates by USP14 at a faster rate than the proteasome initiates degradation could cause rejection of otherwise competent substrates from the proteasome. Supporting this hypothesis, inhibition of USP14 by a small molecule inhibitor (IU1) enhanced proteasomal substrate degradation in cells overexpressing tau or TDP-43 (Lee et al., 2010). Thus, inhibition of USP14 was proposed as a therapeutic strategy to enhance proteasomal function in neurodegenerative diseases in which these proteins accumulate.\n\n\nMethods\n\nConstructs. Human USP14 (hUSP14wt), V5-tagged hUSP14wt (V5-hUSP14wt), catalytically inactive mutant USP14-C114A (hUSP14CA), V5-tagged hUSP14CA (V5-hUSP14CA), human tau, and Flag-tagged human TDP- 43 (Flag-TDP-43) were cloned into the pTT5d expression vector by Amgen’s Protein Sciences department and confirmed by sequencing. Human α-synuclein-Flag CMV6 expression vector was purchased from Origene (#RC221446) and confirmed by sequencing.\n\nCell lines. All cell lines were obtained from ATCC. HEK293 cells were grown in DMEM/10% fetal bovine serum/1% penicillin, streptomycin, glutamine. U2OS cells stably expressing Flag-tagged human α-synuclein (U2OS/synuclein) were generated by Amgen Neuroscience in San Francisco and grown in McCoy’s 5A/10% fetal bovine serum/1% penicillin, streptomycin/2% glutamine and 0.5mg/mL G418. SH-SY5Y cells were grown DMEM/10% fetal bovine serum/1% penicillin, streptomycin, glutamine and 0.5mg/mL G418. All cells were grown in incubators at 5%CO2/37°C. All cell culture reagents were purchased from Gibco.\n\nTransfections. HEK293 cells were plated at a density of 10-6 cells/well in 6-well plates and transfected with plasmids using Lipofectamine™ 2000 (Thermofisher) for 4 hours, and analyzed 48 hours after transfection. U2OS/synuclein cells were plated at 5×10-4 cells/well in 24-well plates and SH-SY5Y cells were plated at 2×10-5 cells/well in 6-well plates. Cells were transfected with Opti-MEM™ (Thermofisher) containing 100nM siRNA, and analyzed 60, 72 or 96 hours after transfection. USP14 siRNAs were obtained from Ambion.\n\nWestern blot. Cells were lysed with Lysis Reagent (Roche) containing 1% SDS/1X Complete™ protease inhibitors cocktail tablets (Roche). Samples were boiled and Benzonase Nuclease (Sigma) was added following the manufacturer’s instructions. 10ug of lysate was loaded on a 12% Bis-Tris gel (Life-Sciences) and proteins were separated by electrophoresis (100mA, 200V) and transferred onto 0.2µm nitrocellulose membrane (Life Sciences) for a minimum of 4hrs (100mA, 25V). Membranes were blocked with Odyssey Blocking Buffer (Li-Cor), incubated with primary antibodies diluted in Li-Cor buffer with 0.2% Tween-20 at 4°C shaking overnight, and washed 3× with phosphate-buffered saline/0.1% Tween-20 (PBST). Membranes were then incubated with secondary antibodies for 1 hour at room temperature in the dark, washed 3× with PBST, and analyzed with the Odyssey imaging system at a relative intensity setting of 2–2.5 for the 800 channel and 1–2 for the 700 channel. Beta-actin or GAPDH served as a loading control.\n\nAntibodies. Mouse monoclonal anti-tau5 (1µg/ml; Invitrogen AHB0042), mouse monoclonal beta-actin (1:1000; Cell Signaling 3700S), mouse monoclonal anti-flag (1:500; Sigma-Aldrich F1804), mouse monoclonal anti-V5 (1µg/ml, Sigma-Aldrich V8012), mouse monoclonal anti-GAPDH (1µg/ml; Invitrogen 39-8600), chicken polyclonal anti-USP14 (5µg/ml; Lifesensors AB505), IRDye 680 or 800 anti-mouse or anti-chicken infrared secondary antibodies (1:10000; Li-Cor).\n\nData analysis. Ratios of the intensity readings for the protein of interest and the loading control were calculated in Microsoft Excel 2010 and plotted using GraphPad Prism 6.05.\n\n\nResults\n\nA key experiment from Lee et al., 2010, (Figure 1g) showed that recombinantly expressed tau or TDP-43 levels in HEK293 cells were higher when coexpressed with wild type as compared to catalytically inactive (C114A) USP14. We cotransfected V5-pTT5d-USP14 or V5-pTT5d-USP14 (C114A) plasmids (ranging from 0.5 to 2µg) and 2µg pTT5d-Tau or pTT5d-Flag-TDP-43 plasmids in HEK293 cells. Note that we used a pTT5d vector to express proteins, while Finley and colleagues used a pcDNA3.1 vector (Invitrogen). Despite robust expression of USP14 or the catalytically inactive mutant as detected by anti-V5 antibody (Figure 1A, C), no decrease was observed in the levels of tau (Figure 1A, B) or TDP-43 (Figure 1C, D) in cells transfected with the catalytically inactive mutant compared to wild type USP14. These experiments were repeated twice with similar results.\n\n1, 1.5 or 2ug of V5-hUSP14wt (wt = wild type) or V5-hUSP14(CA) (CA = C114A, catalytically inactive) were cotransfected with 2ug Tau or Flag-TDP-43 plasmid in HEK293 cells. Cells were lysed after 48 hours and analyzed by western blot using a standard protocol. Actin served as loading control. Despite robust expression of USP14 or its catalytically inactive mutant as detected by the V5-tag (A, C), no differences were observed in Tau (A, B) or Flag-TDP-43 (C, D) protein levels. Note that we did not observe differences in the expression levels of USP14 versus USP14(CA). Control = empty vector control.\n\nTo exclude the possibility that the V5-tag rendered the USP14 constructs non-functional, we validated an anti-USP14 antibody (Supplementary material) and tested untagged USP14 constructs in TDP-43 overexpressing cells. HEK293 cells were transfected with USP14 or USP14(C114A) plasmids at concentrations ranging from 31ng to 4µg and tau and Flag-TDP-43 at concentrations of 2 or 4µg (3 independent experiments were run for tau and Flag-TDP-43 each); representative blots are shown in Figure 2. Despite robust expression of USP14 or its catalytically inactive mutant as detected by the USP14 antibody, no decrease was observed in tau or Flag-TDP-43 protein levels in cells transfected with the catalytically inactive mutant compared to wild type USP14 (Figure 2A, B).\n\n31 to 500ng of hUSP14wt or hUSP14(CA) plasmids were cotransfected with 2ug tau or TDP-43 plasmid in HEK293 cells. Cells were lysed after 48 hours and analyzed by western blot using a standard protocol. Actin served as loading control. Despite robust expression of USP14 or the catalytically inactive mutant as detected by anti-USP14 antibody (A, C), no decreases were observed in tau (A, B) or TDP-43 (C, D) protein levels in the cells transfected with hUSP14CA. Note that we did not observe differences in the expression levels of USP14 versus USP14(CA). Mock = empty vector control, GOI = gene of interest and refers to either tau or TDP-43 in the absence of USP14 cotransfection.\n\nBecause there was a possibility that even the untagged-USP14 constructs were not functional, we tested whether siRNA knock down of endogenous USP14 would increase turnover of substrate. Lee et al. (2010) showed that Usp14-/- mouse embryonic fibroblasts had lower levels of tau or TDP-43 than those overexpressing wild-type USP14. Therefore, we reasoned that USP14 knockdown should result in lower levels of substrate. To avoid variability resulting from transient transfections, we tested USP14 knockdown in a stable Flag-tagged α-synuclein U2OS cell line. As shown in Figure 3, four different siRNAs (A58, A59, A60 and A90; 100nM) caused a 50–75% decrease in endogenous USP14 protein levels at 60 or 96 hours post-transfection (Figure 3A, B). No changes in Flag-α-synuclein were detected (Figure 3A, C).\n\nU2OS cells stably expressing Flag-α-synuclein were treated with 100nM USP14 siRNA from Ambion (A58, A59, A60 or A90) for 60 or 96 hours (A). Scrambled siRNA (AS) served as control for the specificity of the siRNA knockdown. Despite 50–75% knockdown of basal USP14 protein levels (B), no changes in Flag-α-synuclein expression were detected (C).\n\nFinally, to eliminate the concern that the artificial levels of the transiently or stably overexpressed substrates caused the lack of effect, we repeated the siRNA knockdown experiment in SH-SY5Y cells that endogenously express tau using siRNAs from Ambion (A58, A59, A60 and A90; 100nM) in two independent experiments. As shown in a representative western blot in Figure 4, no changes in endogenous tau levels were observed despite a 50–75% knockdown of endogenous USP14 protein levels.\n\nSH-SY5Y cells endogenously expressing tau were transfected with 100nM USP14 siRNAs from Ambion (A58, A59, A60 or A90) or scrambled siRNA (AS) for 72 hours. Cells were lysed and analyzed by western blot using a standard protocol. A 50–75% decrease in USP14 protein levels was achieved compared to scrambled control, but no change in basal tau protein levels (A, B).\n\n\nConclusions\n\nThough we took several different approaches to assay the effects of USP14 on substrate levels, we were unable to confirm a robust role for USP14 in tau or TDP-43 degradation in our experimental systems. The possibility remains that differences in our methods (such as using a different expression vector) caused the discrepancies between our data and those in Lee et al. (2010). After these data in immortalized cell lines were generated, Wilson and colleagues published in vivo data from USP14-deficient axJ mice. They found no changes in endogenous tau or ataxin-3 protein levels, but did observe a difference in phosphorylated tau (Jin et al., 2012). They also generated mice expressing catalytically inactive USP14 and could not detect altered proteasomal function in these mice, although tau levels were not analyzed (Vaden et al., 2015). However, whether pharmacological or genetic inhibition of USP14 could improve degradation of aggregate-prone proteins in a disease state is still unknown. We hope our findings serve as a starting point for further discussion, collaboration, and research in this field.\n\n\nData availability\n\nOpen Science Framework: Dataset: Does inactivation of USP14 enhance degradation of proteasomal substrates that are associated with neurodegenerative diseases?, doi 10.17605/OSF.IO/8HWUB (Ortuno et al., 2016).",
"appendix": "Author contributions\n\n\n\nDO conducted all experiments. DO, HC and SM conceived of the experimental design. HC and SM wrote the article.\n\n\nCompeting interests\n\n\n\nAll authors were full-time employees at Amgen Inc. at the time the experiments were conducted.\n\n\nGrant information\n\nThis research was funded by Amgen Inc.\n\n\nAcknowledgements\n\nThe authors like to thank Amgen’s Protein Sciences department for providing the constructs for transfections and Amgen’s Neuroscience group in San Francisco for providing the stable U2OS/synuclein cell line.\n\n\nSupplementary material\n\n1µg V5-tagged USP14, V5-tagged USP14(CA) or empty vector control constructs were transfected in HEK293 cells and probed with V5 or chicken polyclonal anti-USP14 antibodies. Beta-actin served as loading control.\n\n\nReferences\n\nAnderson C, Crimmins S, Wilson JA, et al.: Loss of Usp14 results in reduced levels of ubiquitin in ataxia mice. J Neurochem. 2005; 95(3): 724–731. PubMed Abstract | Publisher Full Text\n\nBorodovsky A, Kessler BM, Casagrande R, et al.: A novel active site-directed probe specific for deubiquitylating enzymes reveals proteasome association of USP14. EMBO J. 2001; 20(18): 5187–5196. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCiechanover A, Kwon YT: Degradation of misfolded proteins in neurodegenerative diseases: therapeutic targets and strategies. Exp Mol Med. 2015; 47(3): e147. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHanna J, Hathaway NA, Tone Y, et al.: Deubiquitinating enzyme Ubp6 functions noncatalytically to delay proteasomal degradation. Cell. 2006; 127(1): 99–111. PubMed Abstract | Publisher Full Text\n\nHanna J, Meides A, Zhang DP, et al.: A ubiquitin stress response induces altered proteasome composition. Cell. 2007; 129(4): 747–759. PubMed Abstract | Publisher Full Text\n\nHu M, Li P, Song L, et al.: Structure and mechanisms of the proteasome-associated deubiquitinating enzyme USP14. EMBO J. 2005; 24(21): 3747–3756. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJin YN, Chen PC, Watson JA, et al.: Usp14 deficiency increases tau phosphorylation without altering tau degradation or causing tau-dependent deficits. PLoS One. 2012; 7(10): e47884. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLee BH, Lee MJ, Park S, et al.: Enhancement of proteasome activity by a small-molecule inhibitor of USP14. Nature. 2010; 467(7312): 179–184. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOrtuno D, Carlisle H, Miller S: Dataset: Does inactivation of USP14 enhance degradation of proteasomal substrates that are associated with neurodegenerative diseases? Open Science Framework. 2016. Data Source\n\nPeth A, Besche HC, Goldberg AL: Ubiquitinated proteins activate the proteasome by binding to Usp14/Ubp6, which causes 20S gate opening. Mol Cell. 2009; 36(5): 794–804. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVaden JH, Watson JA, Howard AD, et al.: Distinct effects of ubiquitin overexpression on NMJ structure and motor performance in mice expressing catalytically inactive USP14. Front Mol Neurosci. 2015; 8: 11. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWilson SM, Bhattacharyya B, Rachel RA, et al.: Synaptic defects in ataxia mice result from a mutation in Usp14, encoding a ubiquitin-specific protease. Nat Genet. 2002; 32(3): 420–425. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "12772",
"date": "07 Mar 2016",
"name": "Scott T Brady",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nMany adult-onset neurodegenerative diseases are associated with aggregates of misfolded proteins or peptides. A number of groups have proposed that those aggregates that are intracellular, such as tau, synuclein and TDP-43, may result from defects in the protein-degradation pathways like the proteasome which slows normal protein turnover. Such proposals lead naturally to the idea that enhancing endogenous protein degradation pathways is a potential therapeutic strategy to reduce aggregate levels, thereby slowing or blocking disease progression. This manuscript focuses on USP14, a deubiquinating enzyme associated with the proteasome that catalyzes the release of ubiquitin for proteins targeted for degradation and allow the ubiquitin to be recycled for targeting other proteins to the proteasome. Recycling of ubiquitin is particularly important in domains far removed from sites where newly synthesized ubiquitin is available. The need to transport ubiquitin to synaptic terminals is an obvious example. Studies in a mouse model deficient in USP14 found reduced tissue ubiquitin levels in all tissues with a particularly significant loss in synaptic terminals and there is evidence of altered synaptic transmission in these mice. Curiously, there were no obvious accumulations of specific proteins or increased aggregates in brains noted in descriptions of this USP14-deficient mouse, despite its putative role in proteasome function. Subsequent studies failed to show a difference in endogenous levels of tau in the USP14-deficient mouse and a second mouse line expressing a catalytically dead USP14 did not find altered proteasomal activity.Understanding the role of USP14 in clearance of pathogenic proteins is complicated by the fact that different proteins may involve different actions of USP14. For example, degradation of some proteins is normal in the presence of catalytically dead USP14, while others require catalytic activity. Tau and TDP-43 were both reported to be in the latter category as recombinant proteins accumulated to a higher level when expressed with wild type, but not with catalytically inactive USP14. This finding was the basis for suggestions that inhibition of USP14 might enhance clearance of these proteins.Experiments described in this report sought to further characterize the ability of USP14 to modulate the clearance of tau, TDP-43 and α-synuclein. Unfortunately, increased levels of either wild type or catalytically inactive USP14 had no effect on levels of tau or TDP-43 and siRNA knockdown of endogenous USP14 failed to affect cellular levels of α-synuclein or alter endogenous expression of tau protein in a differentiated neuroblastoma cell line. A variety of different approaches to alter levels of USP14 failed to confirm the previous reports of altered clearance. The experiments are carefully documented and well controlled, suggesting that USP14 does not play a role in modulating the clearance of these proteins, consistent with the mouse studies. The conclusion is that inhibition of USP14 is not a promising therapeutic target for enhancing clearance of pathogenic proteins in adult-onset neurodegeneration. Although these cell-based assays make a strong case for this conclusion, data from the mouse models were never consistent with this proposal, since they showed no obvious evidence of proteasomal dysfunction or reduced tau levels. Indeed, given the fact that loss of USP14 catalytic activity in the mouse led to defects in synaptic transmission, it is hard to see how inhibition of USP14 was a plausible therapeutic strategy. Minor Points.The quantitative data in figures 1 and 2 are expressed as being normalized to beta actin levels. No indication is given as to the number of replicates or whether any statistical analysis was done. The raw data is shown as immunoblots with epitope tags, so the conclusions appear justifiable. Nevertheless, the number of experimental replicates must be given and the case would be more compelling with statistics. Technically, the bar graphs show ratios, which are dimensionless, not arbitrary units.",
"responses": []
},
{
"id": "12829",
"date": "09 Mar 2016",
"name": "Thomas Kodadek",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis study tests the previously published assertion that reducing the activity of USP14, a proteasome-associated deubiqtuitylase, results in decreased levels of neurotoxic proteins such as TDP43 and Tau. The bottom line of the study is that manipulation of USP14 level and activity in a cell model system has no discernable effect of the levels of these proteins, contrary to expectations based on a previously published 2010 study1. While this is obviously a model system with unknown relevance to bona fide neurons in vivo, the experiments appear to be well done and the data support the conclusions. The authors are careful to point out that there are minor differences between some of their protocols and those used in the 2010 study and call for increased communication and collaboration between interested laboratories to determine if USP14 is truly a good drug target for neurodegenerative diseases. This is entirely appropriate.",
"responses": [
{
"c_id": "1861",
"date": "14 Mar 2016",
"name": "Thomas Kodadek",
"role": "Reviewer Response",
"response": "Since posting my review of this F1000Research article, a colleague made me aware of two manuscripts that are highly relevant to this topic, but were not cited by Ortuno et al. They are: Homma T, Ishibashi D, Nakagaki T, et al.: Ubiquitin-specific protease 14 modulates degradation of cellular prion protein. Sci Rep. 2015; 5:11028. McKinnon C, Goold R, Andre R, et al.: Prion-mediated neurodegeneration is associated with early impairment of the ubiquitin-proteasome system. Acta Neuropathol. 2016; 131(3): 411-425. Both of these papers report that levels of prion proteins in neurons are strongly influenced by USP14 activity. Thus, while the experiments conducted by Ortuno et al. reported in this communication do not seem to indicate that manipulation of USP14 has a major effect on TDP-43 and α-synuclein levels under their conditions, the major findings of the 2010 Nature paper by Lee et al. are strongly supported by these two studies. Thus, these papers should have been cited by Ortuno et al. in their F1000Research article. I apologize for not being aware of these two studies when I reviewed this work."
},
{
"c_id": "1879",
"date": "22 Mar 2016",
"name": "Takujiro Homma",
"role": "Reader Comment",
"response": "Thank you for introducing our work. It supports Lee's findings. Inhibition of USP14 has a major effect on prion aggregation. McKinnon et al. reproduced our result."
}
]
},
{
"id": "12882",
"date": "14 Mar 2016",
"name": "Scott Wilson",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nUbiquitin-dependent protein degradation involves the assembly of ubiquitin chains on specific proteins followed by their recognition and subsequent degradation by the proteasome. Since ubiquitination is a reversible reaction, there has been great interest in understanding the role of protein deubiquitination as a mechanism to regulate protein degradation. This is particularly true in post-mitotic neurons where lowering the burden of ubiquitinated aggregates of tau, Htt, alpha-synuclein and TDP-43 observed in Alzheimer’s Disease, Huntington’s Disease, Parkinson’s Disease and Amyotropic lateral sclerosis, respectively, is an attractive therapeutic intervention for the treatment of these diseases. Ubiquitinated proteins stably associate with the proteasome through their interaction with proteasomal ubiquitin binding proteins. Following binding, and prior to degradation by the proteasome, ubiquitinated proteins are stripped of their ubiquitin tag. The disassembly of ubiquitin chains by proteasomal deubiquitinating enzymes serves multiple functions, including maintaining ubiquitin pools and determining whether a substrate will be released or degraded by the proteasome. The ubiquitin-specific protease 14 (USP14) is a proteasome-associated deubiquitinating enzyme that is required to maintain ubiquitin levels by preventing conjugated ubiquitin from entering the proteasome. Previous studies have also indicated that either a pharmacological block or genetic inactivation of USP14’s ubiquitin-hydrolase activity can reduce the steady-state levels of overexpressed aggregate-prone proteins tau, TDP-43 and ataxin-3 in immortalized cell lines. These findings suggested that blocking USP14’s deubiquitinating activity would lead to enhanced degradation of ubiquitinated substrates by preventing the substrates from being released by the proteasome prior to their commitment to degradation. Studies in mice provide support for an essential role for USP14 in controlling ubiquitin pools. Analysis of USP14-deficient mice revealed a significant loss of ubiquitin in multiple tissues, including the brain, and even greater loss of ubiquitin at synaptic terminals. Restoration of ubiquitin pools in these mice restored some of the synaptic transmission deficits caused by the loss of USP14, indicating a requirement for USP14 in ubiquitin homeostasis. Contrary to what was observed in immortalized cell lines, there was no detectable change in the steady state levels of the aggregate-prone proteins tau and ataxin-3 in the USP14-deficient mice. However, increased levels of phosphorylated tau were observed in the USP14-deficient mice and correlated with elevated levels of activated JNK, ERK and AKT. While USP14 still remains an interesting target for therapeutic intervention in protein-aggregate diseases, its role in controlling the degradation of specific proteins is not clear.\n\nThis study by Ortuno et. al. aims to further investigate a role for USP14 in controlling proteasomal degradation of aggregate-prone proteins. To do this, the authors first investigated if either overexpression of wild type USP14 or ubiquitin-hydrolase inactive USP14 would alter the levels of transfected tau or alpha-synuclein in an HEK293 cell line. If USP14 acts as an inhibitor of protein degradation, then overexpression of wild type USP14 should lead to increased levels of these aggregate-prone proteins while overexpression of ubiquitin-hydrolase inactive USP14 should reduce their levels. However, increasing either wild type or ubiquitin hydrolase inactive USP14 did not result in a detectable change in the steady-state levels of tau or alpha-synuclein.The authors then investigated if lowering the levels of USP14 in the neuronal SHSY5Y cell line, which expresses endogenous tau, would result in decreased tau levels. Although the authors were able to significantly decrease the expression of USP14, they did not observe any significant change in the level of endogenous tau. The authors were therefore unable to confirm a role for USP14 in controlling the degradation of aggregate-prone proteins. The title is appropriate and the abstract provides a suitable summary. The experiments conducted in this study all generated high quality data and included appropriate controls. The authors provided a reasonable conclusion and potential reasons for differences between their results and those previously reported on USP14. Concerns:The entire premise of this paper is based on the manipulation of proteasome-bound USP14. Unfortunately, the authors did not determine the level of proteasome-bound USP14. This is particularly important for the transfection of USP14(CA) and the Usp14 siRNA knockdown experiments. If proteasome-bound USP14 has a long half-life, then these manipulations may not have significantly displaced endogenous USP14 from the proteasome. The steady state level of any protein depends on the rates of synthesis and degradation. However, the measurements in this report did not take into account either of these variables. While highly unlikely, changes in protein turnover due to manipulation of USP14 may have caused increased turnover of tau, alpha-synuclein or TDP-43 with a corresponding increase in synthesis, resulting in no change in protein abundance. There are no error bars in figures 1, 2 and 4. It is not clear if the quantitations represent averages from replicate immunoblots or if a single blot was performed for each experiment.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-137
|
https://f1000research.com/articles/5-385/v1
|
22 Mar 16
|
{
"type": "Method Article",
"title": "A divide-and-conquer strategy in tumor sampling enhances detection of intratumor heterogeneity in routine pathology: A modeling approach in clear cell renal cell carcinoma",
"authors": [
"José I. Lopez",
"Jesús M. Cortes",
"Jesús M. Cortes"
],
"abstract": "Intratumor heterogeneity (ITH) is an inherent process in cancer development which follows for most of the cases a branched pattern of evolution, with different cell clones evolving independently in space and time across different areas of the same tumor. The determination of ITH (in both spatial and temporal domains) is nowadays critical to enhance patient treatment and prognosis. Clear cell renal cell carcinoma (CCRCC) provides a good example of ITH. Sometimes the tumor is too big to be totally analyzed for ITH detection and pathologists decide which parts must be sampled for the analysis. For such a purpose, pathologists follow internationally accepted protocols. In light of the latest findings, however, current sampling protocols seem to be insufficient for detecting ITH with significant reliability. The arrival of new targeted therapies, some of them providing promising alternatives to improve patient survival, pushes the pathologist to obtain a truly representative sampling of tumor diversity in routine practice. How large this sampling must be and how this must be performed are unanswered questions so far. Here we present a very simple method for tumor sampling that enhances ITH detection without increasing costs. This method follows a divide-and-conquer (DAC) strategy, that is, rather than sampling a small number of large-size tumor-pieces as the routine protocol (RP) advises, we suggest sampling many small-size pieces along the tumor. We performed a computational modeling approach to show that the usefulness of the DAC strategy is twofold: first, we show that DAC outperforms RP with similar laboratory costs, and second, DAC is capable of performing similar to total tumor sampling (TTS) but, very remarkably, at a much lower cost. We thus provide new light to push forward a shift in the paradigm about how pathologists should sample tumors for achieving efficient ITH detection.",
"keywords": [
"Intratumor heterogeneity",
"clear cell renal cell carcinoma",
"pathologist",
"tumor sampling",
"divide-and-conquer strategy",
"computational modelling",
"laboratory costs"
],
"content": "Introduction\n\nNeoplasia is the result of multiple and complex disturbances of the cellular metabolism1,2. Although the arrival of sophisticated technological devices like massive sequencing has improved the knowledge on the molecular mechanisms underlying carcinogenesis, intratumor heterogeneity (ITH) still remains poorly understood3. ITH, the fact that a given tumor is intrinsically diverse across different regions, is of crucial importance for both basic and clinical researchers. Whilst basic researchers focus on ITH because it reflects the complexity of tumor development, clinical researchers do it because ITH is a major obstacle for the success of new patient therapies. ITH develops stochastically in both time and space domains, in a manner that the resulting ITH patterns are unique and utterly unpredictable. Modern pathologists have the challenge to determine ITH efficiently, helping basic researchers in the detection of mutational signatures and oncologists in the selection of better personalized therapies. This paper shows an affordable, very simple but efficient method to improve ITH detection in clear cell renal cell carcinoma (CCRCC) in the routine practice without increasing costs. The approach, however, can be applied to any other tumor type. This simple method is supported by a computational modeling approach.\n\n\nThe context\n\nRenal cancer, a common neoplasm in Western Countries with more than 62,000 expected deaths in the USA in 20164, is a complex disease with several distinct tumor subtypes5,6. CCRCC is by far the most common renal cancer histological variant, accounting for 75 to 80% of renal neoplasms in adults7. CCRCC is a clinically aggressive neoplasm, where radical surgery is the only treatment with significant impact on patient survival8. Chemo- and radiotherapy are inefficient so far and modern targeted therapies obtain only partial results9. This context makes CCRCC one of the most attractive challenges in cancer research for the coming years. As a result, many investment efforts are being made worldwide to improve CCRCC response to new therapies.\n\nCCRCC is a paradigm of a heterogeneous tumor from several viewpoints10–17, where not only different CCRCCs are distinct from each other, but the ITH within the same CCRCC is also high. CCRCC presents ITH patterns which vary from obvious to subtle depending on very different approaches. In some cases, for instance, ITH is evident to the naked eye, while in others it is not (Figures 1a & 1b). Although some CCRCCs might seem apparently homogeneous at first sight, they can actually be heterogeneous under the microscope. It is also possible that other CCRCCs that appear homogeneous at the microscope are in fact heterogeneous at the molecular level, where different gene mutations (each one pursuing a different clinical outcome) can be present at different regions, i.e., gene mutations located at the BAP-1 gene are associated to high-risk of aggressive clinical outcome; mutations at the mTOR pathway make the tumor sensitive to targeted therapies; mutations at the PBRM1 gene are linked to low-risk clinical aggressiveness14,18. In contrast, some mutations like those located at the VHL gene seem to be truncal (early) and generalized for all CCRCC regions14, which makes the VHL mutations potential targets for modern therapies; but unfortunately, all the assays performed to date to target this pathway have obtained disappointing results19. Importantly, this therapeutic failure has been associated to ITH; and in particular, to the branching evolution patterns that malignant cells follow across different regions10,13–15. This unpredictable regional variability makes impossible to date to design efficient therapeutic strategies for these neoplasms. This fact explains the high 5-year cancer-related mortality of CCRCC, currently reaching up to 40%20.\n\nITH in CCRCCs may be hidden (a) or evident (b) to the naked eye during the management of surgical specimens, an issue that is critical for subsequent tumor sampling. The RP strategy selects for the analysis 1 sample per cm of tumor diameter, as reflected at the left side of panels c–d (c, diagram; d, histological slide) and at the top row of blocks in panel e. In contrast, the DAC strategy (the alternative we are suggesting here) selects more small-pieces for tumor sampling (for instance, panels c–e show how while RP selects big blocks, DAC selects 8 small-pieces per each large block, but the pieces are randomly chosen along the tumor. Importantly, both methods RP and DAC demand the same laboratory costs.\n\nThe expected effect of modern targeted therapies is tumor necrosis, which is achieved by acting against either specific gene mutations or abnormal protein products generated by neoplasia21. Depending on the response to these drugs, CCRCCs are divided into responders to therapy and non-responders, and this makes the difference between having success or failure in the clinical setting. After the CCRCC has been surgically removed, responders show generalized tumor necrosis and are associated with longer survival rates, whilst non-responders typically display a mixture of tumor necrosis and a viable tumor, and are associated with shorter survivals.\n\n\nThe problem\n\nPathologists are the clinicians who handle surgical specimens and decide which parts of the tumor will be studied and which others won’t. If tumor size is small (≤3 cm in diameter), pathologists can analyse the entire tumor. However, CCRCCs are usually much larger than that, reaching up to 10–15 cm in tumor-diameter or even more, and this fact makes the sampling of the entire tumor not cost-effective. For this reason, pathologists perform tumor sampling following internationally accepted protocols22–24, a selection made with the intention to achieve obtained samples which are good representatives of the entire tumor. In particular, the accepted consensus is to obtain 1-centimetre-in-length sample per 1-centimetre-of-tumor-size plus additional similar samples from every suspicious region detected by the naked eye. ITH, however, is frequently hidden in apparently identical areas, as we have previously mentioned, and this is what makes ITH an important limitation to the performance of these protocols. A second limitation is related to the percentage of total tumor sampled, in cases where tumor size is larger than 3 cm in diameter the current practice leaves out the analysis of a very significant portion of the tumor (for instance, more than 95% of a 10 cm-in-diameter CCRCC is not included for analysis).\n\nOnce the sampling for diagnosis is performed, the remainder of the tumor is first stored and then destroyed, so that, the amount of crucial information forever lost remains largely unknown. Previous studies on total samplings assays performed in two short series have shown very concerning data11,12 that are not acceptable in modern clinical practice. Being aware of the limitations provided by current protocols in unveiling ITH, both clinicians involved in patient treatment and basic researchers are appealing for urgent solutions25. However, pathologists have not provided a well sustained solution to this problem so far, and the latest updates on sampling protocols23,24 apparently are not taking this problem into consideration. To overcome these limitations, several authors have recently developed algorithms to quantify ITH when very limited tissue is available for analysis26–29.\n\nThe appropriate selection of tumor samples falls absolutely into the pathologist’s responsibility. Importantly, a deficient or incomplete tumor sampling will give rise to a deficient or incomplete histological and/or molecular study, and this deficiency may have important consequences for patient treatment. It is indeed a paradox that such crucial information affecting the patient and obtained by using such sophisticated and expensive high-tech devices do drastically depend on the tumor samples that were selected based on dogmatic rules.\n\nDespite these limitations, the classical pathologic routine morphology under the microscope still remains a decisive source of information for ITH discovery. Indeed, Andor et al.30 showed very recently that the nuclear and cellular features associated with tumor aggressiveness observed in histological sections correlate with genetic ITH in several tumor types, renal cancer included.\n\n\nA solution\n\nThe solution for ITH detection must be affordable and workable at the same time, balancing scientific accuracy and cost. A total tumor sampling (TTS), although an ideal solution, is utterly unaffordable for most of the CCRCCs, as the huge number of samples generated would collapse the laboratory workflow. But at the other extreme, the current routine protocol has proven to be insufficient. Once arrived at this point, the key question is as follows: How can pathologists overcome this deficiency? An increase in the number of random samples would obviously increase the probability of finding the hidden ITH, as it has been empirically proposed recently14,17,25, but, how large must such an increase should be? Although (as far as we know) there is no answer to these questions at this time, it is possible to increase the number of samples to some degree while keeping the same cost fixed. For instance, if we assume that the tumor has a regular shape (e.g., a circle in Figure 1c), straightforward reasoning says that 56 small samples placed in 7 blocks might have a higher chance for detection of ITH as compared to 7 large samples placed in the same number of blocks (Figures 1c–1e). These figures show that more regions can be assessed without increasing laboratory costs (pathology laboratory costs are mostly based on the number of paraffin blocks used for the analysis, where the higher the number of blocks, the higher the cost).\n\n\nModeling approach\n\nFor simplicity reasons, tumor shape was modeled using a 2D square of side L. ITH was represented by the γ matrix, defined by the elements:\n\n\n\nwith i, j = 1, ..., L and where i indicates row and j column. The zero value models homogeneity, rather non-zero values model the presence of ITH at the tumor position given by (i, j). The matrix γ can account for C (in principle, an arbitrary number) different ITH types.\n\nTwo classes of ITH were simulated, random ITH (ranITH) and regional ITH (regITH), the latter being the situation more realistic with regard to how ITH typically is found in tumors10. For both ranITH and regITH situations, ITH was simulated using an iterative method with h = 1, ..., H steps and where the initial condition was for all the cases γ = 0. At each step h, a 2D position (i, j) is chosen at random and a value of (γ)ij = 1 or 2 or 3 or... or C is assigned with probability 1C. After the H steps, the γ matrix was fixed and defined the tumor ITH configuration to be detected by tumor sampling. The percentage of ITH density associated to a given tumor was defined as ρ≡HL×L×100 (c.f., x-axis in Figure 2 and Figure 3).\n\nResults from the computational modeling approach show that, for tumors with ITH types=1, DAC (red) performs similar to RP (blue) for random ITH (a–c) but the former outperforms the latter for regional ITH (d–f). a,c: Percentage of ITH detection (mean ± SD) as a function of the percentage of ITH density defining for each tumor. SD was calculated across N different repetitions of the same strategy and across M different tumors. b,e: similar to a,c but we only represented the mean. c,f: similar to a,c, but we only represented SD. Notice that, not only the mean of ITH detection was drastically enhanced by DAC, but SD was substantially smaller, meaning that DAC in comparison to RP is more efficient and more reliable (less variable). Exact values for all simulated parameters are given in the text.\n\nSimilar to Figure 2 for C = 1, DAC performed equally as RP for random ITH (not visualised). a: regional ITH, DAC plotted as solid lines, RP as dashed ones. Different colors correspond to different ITH types. The mean of ITH detection (measured in %) is represented as function of the ITH density (also in %). Notice that, for the simulations we have performed here, DAC performed better in detecting all the C = 4 ITH types in comparison to the performance that RP achieved when only 1 ITH type existed. b: P-values after t-test (as implemented in Matlab, function ttest) showing significant differences in performance between DAC (blue) and RP (red) for different values of ITH density.\n\nFor the RanITH situation, the matrix elements of γ were randomly generated at position (i, j), with no constraints for i and j, and this occurred for all the H steps. In contrast, for RegITH, only at the first iteration (h = 1) the value of γ was assigned at position (i, j) with no constraints for i and j (using the same procedure as for ranITH), but for the following iterations (h ≥ 2), either the new chosen i or the new j was constrained to be necessarily a neighbor index of any of all the previously chosen i or j.\n\nFor a given tumor, and after introducing an ITH configuration defined by γ (Equation 1), we repeated N times (and separately) two different strategies: routine protocol (RP, the one accepted in routine pathology) and our alternative, the divide-and-conquer strategy (DAC). For each repetition and strategy, we calculated the number of successfully detected ITH sites for each of the C ITH types, i.e., detecting the value of (γ)ij = 1 for ITH subtype = 1, the value of (γ)ij = 2 for ITH subtype = 2, …, and the value of (γ)ij = C for ITH subtype = C . Results were averaged across the N repetitions and also across M different tumors (each one with a different ITH configuration).\n\nFor the two strategies, RP and DAC, the total number of blocks for each repetition was equal to Q (as explained above, this number is modeling the laboratory costs). For DAC, all the Q sites were chosen at random with no constraints for i and j. For RP, the first site, defined as (i, j) ≡ (I, J), was chosen at random with the constraint of d + 1 ≤ I, J ≤ L − d, where d is an index controlling the block size used for tumor sampling. For the following sites to be inspected (up to the number Q), we chose i = {I ± 1, I ± 2, I ± 3, ..., I ± d} and j = {J ± 1, J ± 2, J ± 3, ..., J ± d}, that is, d sites up to I, d sites down to I, d sites right to J and d sites left to J.\n\nA generalization to 3D tumors is straightforward; notating tumor sites with triplets (i, j, k) and defining for RP also the d sites backwards to K and the d sites forwards to K.\n\nThe code for the modeling approach was implemented in Matlab (The Mathworks, Inc, version 2012a) and is available at Script 1, which internally calls to other functions, Script 2–Script 5.\n\nResults from the modeling approach are shown in Figure 2 (ITH types=1) and Figure 3 (ITH types=4). RP and DAC performed similar for ranITH (Figure 2) and this happened independently on C (the number of ITH types). However, for regITH, DAC significantly outperformed RP for any C number (Figure 2 and Figure 3). Other parameters for the simulations were: L = 27 (side of 2D square), C = 4 (ITH types), H (number of sites with ITH) varying from 1 to 500 (or equivalently the ITH density ρ varying from approx. zero to 68%), N = 500 (repetitions number for the two RP and DAC strategies), M = 15 (number of simulated tumors), d = 4 (block size), which is equivalently to Q = 17 (total number of blocks for ITH detection by applying both RP and DAC strategies).\n\n\nEstimation of laboratory costs for the DAC strategy\n\nWe have shown based on a modeling approach that DAC strategy outperforms RP at the same cost as both strategies make use of the same number of blocks to search for ITH. But, what is the cost of the DAC strategy in relation to the cost of the TTS strategy? The answer to this question can be also estimated using a similar modeling approach as explained in the previous section. Before starting, it is interesting to remark that the TTS strategy is an ideal scenario for two reasons; first, TTS performance in detecting ITH is by definition 100% and second, TTS cost is the maximum possible, because the entire tumor is sampled, and laboratory costs can be measured as the number of paraffin blocks. What we can address by modeling is increasing systematically the number of blocks used by the DAC strategy (ie., its cost) and computing, for different values of tumor ITH density, the mean performance of ITH detection. The results are shown in Table 1, where the parameters for the simulations are now L=27, C=1, N=50 and M=5. The DAC cost is normalized to the TTS cost (which in this case coincides with the tumor size, ie., for a 2D square, L2 = 729). One can see from Table 1 that DAC strategy performed very well in detecting ITH, as compared to TTS but, with a much smaller cost; for instance, even for the most difficult situation of detecting a very low ITH density equal to 5% of the tumor (second row in Table 1) the mean DAC performance is equal to 94% (8th column, 2nd row in Table 1) but only demanding 3.5% of the TTS cost (8th column, 1st row). Other situations are given in Table 1. This finding is of extraordinary importance for laboratory work, and adds further advantages for DAC in comparison to RP, balancing a higher reliability to a lower cost.\n\n\nConclusions, take-home message\n\nITH is ubiquitous in CCRCCs, and current protocols for tumor sampling do not guarantee its detection, which is crucial for modern medicine as ITH affects patient prognosis and treatment. This new clinical need cannot be fully assessed using old pathological approaches as any solution to this problem must be cost-effective. This paper, resulting from the interaction between a practical pathologist and a basic researcher, suggests that a simple DAC strategy for tumor sampling is a very efficient approach for ITH detection, outperforming RP sampling at the same cost, and performing similar to the idealized strategy of TTS but with a (much) smaller cost (eg., for tumors with ITH densities of a 5%, DAC performs 94% equally well than TTS but with a 3.5% its cost). This issue is really critical when sampling large-sized tumors and makes it relevant for economical sustainability of health systems. We expect that the DAC strategy (validated here with synthetic data) might provide new light for a shift in the paradigm about how pathologists should sample tumors to achieve efficient ITH detection.\n\n\nSoftware availability\n\nScript 1: Main Matlab function to start simulation. To run it in Matlab, simply run “simula2D.m”. Some comments within.\n\nScript 2: A small function “creates_random_ITH_cube2D.m” called from “simula2D.m”.\n\nScript 3: A small function “creates_regional_ITH_cube2D.m” called from “simula2D.m”.\n\nScript 4: A small function “RP2D.m” called from “simula2D.m”.\n\nScript 5: A small function “DAC2D.m” called from “simula2D.m”.",
"appendix": "Author contributions\n\n\n\nJIL exposed the problem and provided an affordable solution; JMC implemented the modelling approach; JIL and JMC wrote the final version of the manuscript and agreed with this submission.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nJMC acknowledges financial support from Ikerbasque: The Basque Foundation for Science. This work was partially funded by grant SAF2013-48812-R from Ministerio de Economía y Competitividad (Spain).\n\n\nReferences\n\nCancer Genome Atlas Research Network: Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature. 2013; 499(7456): 43–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDe la Fuente IM: Elements of the cellular metabolic structure. Front Mol Biosci. 2015; 2: 16. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGay L, Baker AM, Graham TA: Tumour Cell Heterogeneity [version 1; referees: 5 approved]. F1000Research. 2016; 5(F1000 Faculty Rev): 238. Publisher Full Text | Free Full Text\n\nSiegel RL, Miller KD, Jemal A: Cancer statistics, 2016. CA Cancer J Clin. 2016; 66(1): 7–30. PubMed Abstract | Publisher Full Text\n\nLopez-Beltran A, Scarpelli M, Montironi R, et al.: 2004 WHO classification of the renal tumors of the adults. Eur Urol. 2006; 49(5): 798–805. PubMed Abstract | Publisher Full Text\n\nLópez JI: Renal tumors with clear cells. A review. Pathol Res Pract. 2013; 209(3): 137–46. PubMed Abstract | Publisher Full Text\n\nMacLennan GT, Cheng L: Neoplasms of the kidney. In: Bostwick DG and Cheng L, eds., Urologic Surgical Pathology, 3rd edition. Philadelphia, PA, Elsevier Saunders, 2014; 76–156. Reference Source\n\nPalsdottir HB, Hardarson S, Petursdottir V, et al.: Incidental detection of renal cell carcinoma is an independent prognostic marker: results of a long-term, whole population study. J Urol. 2012; 187(1): 48–53. PubMed Abstract | Publisher Full Text\n\nHiley C, de Bruin EC, McGranahan N, et al.: Deciphering intratumor heterogeneity and temporal acquisition of driver events to refine precision medicine. Genome Biol. 2014; 15(8): 453. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGerlinger M, Rowan AJ, Horswell S, et al.: Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med. 2012; 366(10): 883–92. PubMed Abstract | Publisher Full Text\n\nLópez JI, Guarch R, Camarasa N, et al.: Grade heterogeneity in clear cell renal cell carcinoma. BJU Int. 2013. Publisher Full Text\n\nLopez JI, Guarch R, Larrinaga G, et al.: Cell heterogeneity in clear cell renal cell carcinoma. APMIS. 2013; 121(12): 1187–91. PubMed Abstract | Publisher Full Text\n\nBurrell RA, McGranahan N, Bartek J, et al.: The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013; 501(7467): 338–45. PubMed Abstract | Publisher Full Text\n\nGerlinger M, Horswell S, Larkin J, et al.: Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat Genet. 2014; 46(3): 225–33. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRenovanz M, Kim EL: Intratumoral heterogeneity, its contribution to therapy resistance and methodological caveats to assessment. Front Oncol. 2014; 4: 142. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZaldumbide L, Erramuzpe A, Guarch R, et al.: Large (>3.8 cm) clear cell renal cell carcinomas are morphologically and immunohistochemically heterogeneous. Virchows Arch. 2015; 466(1): 61–6. PubMed Abstract | Publisher Full Text\n\nLópez JI: Intratumor heterogeneity in clear cell renal cell carcinoma: a review for the practicing pathologist. APMIS. 2016; 124(3): 153–159. PubMed Abstract | Publisher Full Text\n\nJoseph RW, Kapur P, Serie DJ, et al.: Clear Cell Renal Cell Carcinoma Subtypes Identified by BAP1 and PBRM1 Expression. J Urol. 2016; 195(1): 180–7. PubMed Abstract | Publisher Full Text\n\nRicketts CJ, Linehan WM: Intratumoral heterogeneity in kidney cancer. Nat Genet. 2014; 46(3): 214–5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAudenet F, Yates DR, Cancel-Tassin G, et al.: Genetic pathways involved in carcinogenesis of clear cell renal cell carcinoma: genomics towards personalized medicine. BJU Int. 2012; 109(12): 1864–70. PubMed Abstract | Publisher Full Text\n\nTsuzuki T, Sassa N, Shimoyama Y, et al.: Tyrosine kinase inhibitor-induced vasculopathy in clear cell renal cell carcinoma: an unrecognized antitumour mechanism. Histopathology. 2014; 64(4): 484–93. PubMed Abstract | Publisher Full Text\n\nHiggins JP, McKenney JK, Brooks JD, et al.: Recommendations for the reporting of surgically resected specimens of renal cell carcinoma: the Association of Directors of Anatomic and Surgical Pathology. Hum Pathol. 2009; 40(4): 456–63. PubMed Abstract | Publisher Full Text\n\nAlgaba F, Delahunt B, Berney DM, et al.: Handling and reporting of nephrectomy specimens for adult renal tumours: a survey by the European Network of Uropathology. J Clin Pathol. 2012; 65(2): 106–13. PubMed Abstract | Publisher Full Text\n\nTrpkov K, Grignon DJ, Bonsib SM, et al.: Handling and staging of renal cell carcinoma: the International Society of Urological Pathology Consensus (ISUP) conference recommendations. Am J Surg Pathol. 2013; 37(10): 1505–17. PubMed Abstract | Publisher Full Text\n\nSoultati A, Stares M, Swanton C, et al.: How should clinicians address intratumour heterogeneity in clear cell renal cell carcinoma? Curr Opin Urol. 2015; 25(5): 358–66. PubMed Abstract | Publisher Full Text\n\nOesper L, Satas G, Raphael BJ: Quantifying tumor heterogeneity in whole-genome and whole-exome sequencing data. Bioinformatics. 2014; 30(24): 3532–40. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRoth A, Khattra J, Yap D, et al.: PyClone: statistical inference of clonal population structure in cancer. Nat Methods. 2014; 11(4): 396–8. PubMed Abstract | Publisher Full Text\n\nAndor N, Harness JV, Müller S, et al.: EXPANDS: expanding ploidy and allele frequency on nested subpopulations. Bioinformatics. 2014; 30(1): 50–60. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHa G, Roth A, Khattra J, et al.: TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. Genome Res. 2014; 24(11): 1881–93. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAndor N, Graham TA, Jansen M, et al.: Pan-cancer analysis of the extent and consequences of intratumor heterogeneity. Nat Med. 2016; 22(1): 105–13. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13018",
"date": "05 Apr 2016",
"name": "Nicola Ancona",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors address the challenging problem of detecting of intratumor heterogeneity (ITH), an important question in routine pathology with relevant impact on patient treatment and prognosis. Nowadays, pathologists follow standard protocols although current practice seem to be insufficient for detecting intratumor heterogeneity with high reliability. To assess ITH with high precision, the authors proposed a divide and conquer strategy, a very simple approach consisting in sampling many small-size pieces along the tumor. The proposed strategy has two advantages: a) increases the performances of standard protocols for detecting ITH and b) reducing the laboratory costs. To assess the performances of the proposed strategy, the authors designed an interesting statistical model and performed an accurate simulation. The paper is well written and fit well the spirit of the journal. I have only one minor remark. The procedure adopted for detecting ITH sites in the simulation is not clear. Is this a random selection? Please add one sentence to make clearer this aspect. Finally, I found the paper extremely interesting, with high impact and relevance on current patient prognosis and treatment.",
"responses": [
{
"c_id": "1915",
"date": "25 Apr 2016",
"name": "Jesus Cortes",
"role": "Author Response",
"response": "We thank the reviewer for making us clarify this. Yes, we use a random sampling as a first stage solution to this problem. We added a paragraph at the end of the section \"Modeling approach\" clarifying this.We also added two new sentences for making the manuscript more clear; a new sentence in the \"Introduction\" briefly explaining what a divide and conquer strategy means and another sentence in the section \"The problem\" indicating why references (Lopez JI et al. BJU Int 2012) and (Lopez et al. APMIS 2013) show very concerning data."
}
]
},
{
"id": "13020",
"date": "06 Apr 2016",
"name": "Francisco Nogales",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the field of Gynaecological Pathology, tumours are known for their heterogeneous histology which often bear a prognostic significance, either by unmasking areas of malignant histology in an otherwise benign tumour of by evaluating multiple areas in tumour grading. To illustrate this, I would choose two particular tumours where multiple small tissue blocks, as proposed in the article, would be of help. An example involving the first situation would be mucinous tumours of the ovary, while the second one will be immature ovarian teratoma, where the semiquantitave evaluatiom of the number of developmentally immature neural and endodermal areas provides the histological grade necessary for managing the neoplasm.This simple technique may be helpful with a lower cost in both working hours and laboratory material",
"responses": []
},
{
"id": "13021",
"date": "11 Apr 2016",
"name": "Samuel Johnson",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper provides a very elegant solution to the problem of detecting intratumour heterogeneity. The authors show quite convincingly that, at least in their modelling framework, the proposed divide-and-conquer method can outperform the routing protocol, and even yield results close to the ideal, total sampling method at a small fraction of the cost. I hope this idea will be taken up by researchers who can test the divide-and-conquer strategy in the lab, and eventually provide a significant improvement in tumour diagnosis.",
"responses": []
},
{
"id": "13017",
"date": "29 Apr 2016",
"name": "Mattia Barbareschi",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nResearch and diagnosis of human tumours is based upon the analysis of small samples of the neoplasms, which are collected by surgical pathologist during macroscopic examination of surgically resected tumours. The study of Lopez and Cortes proposes a new method for tumour sampling for histological and molecular analysis, which could be particularly useful for large tumours (diameter > than 3 cm) with high intratumour heterogeneity (ITH). Detecting ITH is indeed challenging especially for large tumours which cannot be examined in toto and this issue may be a limitation for research and therapy. The method suggested by Lopez and Cortes is essentially based upon a new multiple sampling strategy that could overcome some of the limitations of current sampling protocols. Their assumption is that usual sampling protocols (examining sampling roughly 1 large tissue fragment every centimeter of tumour size), do not allow a reliable evaluation of ITH, which could be ideally achieved with a total tumour sampling strategy (TTS) which is however not sustainable by routine diagnostic laboratories. Lopez and Cortes suggest that performing multiple smaller samples for each tumour collected from randomly selected multiple tumour areas would more effectively detect ITH. Lopez and Cortes defined this strategy as “divide-and-conquer” (DAC) and used a sophisticated mathematical modelling approach to demonstrate that it largely outperforms standard protocols with similar laboratory costs. The data of Lopez and Cortes are based on synthetic data and suggest for that DAC performs 94% in detecting ITH as compared with an idealized TTS strategy, but at a much lower cost.The paper of Lopez and Cortes is very interesting and it is an incentive to consider new sampling strategies of human tumours and should prompt additional studies using real tumour samples to verify whether these synthetic data reflect real life and if this approach will allow a more accurate and relevant histopathological and molecular analysis.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-385
|
https://f1000research.com/articles/5-740/v1
|
25 Apr 16
|
{
"type": "Review",
"title": "Recent advances in understanding Kaposi’s sarcoma-associated herpesvirus",
"authors": [
"Nathan J. Dissinger",
"Blossom Damania",
"Nathan J. Dissinger"
],
"abstract": "Kaposi’s sarcoma (KS)-associated herpesvirus (KSHV) is an oncogenic human herpesvirus. KSHV is associated with three cancers in the human population: KS, primary effusion lymphoma (PEL), and multicentric Castleman’s disease (MCD). KS is the leading cause of cancer in HIV-infected individuals. In this review, we discuss the most recent discoveries behind the mechanisms of KSHV latency maintenance and lytic replication. We also review current therapies for KSHV-associated cancers.",
"keywords": [
"Kaposi’s sarcoma-associated herpesvirus",
"KSHV",
"primary effusion lymphoma",
"multicentric Castleman’s disease"
],
"content": "Introduction\n\nKaposi’s sarcoma (KS)-associated herpesvirus (KSHV), also known as human herpesvirus 8 (HHV-8), is a linear double-stranded DNA virus and a member of the gammaherpesvirus subfamily. The virus was first isolated by Chang et al. in KS biopsy samples from AIDS patients1. Subsequent studies further identified KSHV as the etiologic agent of primary effusion lymphoma (PEL)2 and the B-cell hyperplasia known as multicentric Castleman’s disease (MCD)3. KSHV is also linked to two under-studied inflammatory syndromes. One KSHV inflammatory disease recognized, immune reconstitution inflammatory syndrome-KS (IRIS-KS), is the paradoxical rapid development of KS after the start of highly active antiretroviral therapy (HAART) for HIV and during the rebound of CD4+ T-cells4,5. Uldrick et al. discovered another inflammatory disease, termed KSHV inflammatory cytokine syndrome (KICS), in patients infected with both HIV and KSHV with high levels of viral interleukin-6 (vIL-6), human IL-6 (hIL-6), and KSHV viral loads6. Subsequent to this initial report, KICS has also been found to affect non-HIV-infected KSHV-positive individuals7.\n\nKSHV, like other herpesviruses, has a latent and lytic phase to its lifecycle8,9. Following primary infection, both latent and lytic genes are expressed, but after several rounds of replication, lytic gene expression decreases and latency is established. Latency is the default program of the virus10. During latency establishment, the linear KSHV genome circularizes to become an episome. This latent form of KSHV expresses only a few proteins, including latency-associated nuclear antigen (LANA), viral FADD-like interleukin-1-β-converting enzyme (FLICE/caspase 8)-inhibitory protein (vFLIP), vCyclin, and multiple microRNAs8,11. Additional genes that are expressed at low levels during latency include K1, vIL-612, and K1513. The expression of LANA is sufficient and necessary to establish latency, as it plays a pivotal role in episome maintenance and latent replication. Two LANA proteins form a dimer and the N-termini bind to the host chromosomes while the C-termini interact with LANA-binding sites (LBSs) in the KSHV episome14. Recently, three labs have crystalized the C-terminus of LANA and found that the LANA dimers oligomerize, forming a higher order of organization that facilitates the binding of DNA15–18. It was also discovered that LANA contains positively charged patches opposite to the DNA-binding face. Mutations of these residues did not alter LANA’s DNA binding capabilities but diminished the interaction with cellular chromatin bromodomain (BRD) proteins, which play a role in latent replication and maintenance16,17,19.\n\nLytic replication is divided into three phases of gene expression: immediate early (IE), delayed early (DE), and late8,20. As the transcription of IE genes does not require prior viral protein synthesis, IE genes are experimentally defined by their transcription in the presence of inhibitors of protein synthesis such as cycloheximide. DE gene expression can be inhibited by cycloheximide because they require proteins encoded by IE genes to transactivate their promoters but are also not dependent on DNA replication. Late genes are expressed subsequent to the start of viral DNA replication and encode for structural proteins required for assembling new virions as well as envelope glycoproteins. Viral replication inhibitors (e.g. the viral polymerase inhibitor ganciclovir) can prevent the production of infectious progeny virions.\n\nLatent KSHV can be induced into lytic replication with the addition of chemicals such as 12-O-tetradecanoylphorbol-13-acetate (TPA), valproic acid (VPA), and sodium butyrate. These chemicals activate the expression of the IE gene replication and transcription activator (RTA), encoded by ORF50, which is the key regulator of KSHV lytic replication as its ectopic expression is sufficient to start the lytic cascade8. However, it has recently been proposed that KSHV can be reactivated and enter lytic replication in a RTA-independent manner21,22. In this pathway, KSHV reactivation is induced by cellular apoptosis and is dependent on the activation of caspase 3. It is interesting to note that the virions produced though this RTA-independent lytic pathway appear to be less infectious than virions produced through RTA-dependent lytic replication21. This observation needs to be furthered expanded upon in the future.\n\nKSHV is a pathogenic virus whose mechanism of disease is not fully understood. It is clear that both the latent and lytic phases of the KSHV lifecycle play a role in virus-related disease and a better understanding of these phases can help guide the development of treatments. This review covers recent advances in understanding the latent/lytic switch and discusses current and potential future therapeutic treatments for KSHV-related malignancies.\n\n\nMaintenance of KSHV latency\n\nHow latent KSHV reactivates and efficiently makes new progeny virus is a complex process that requires not only viral but also cellular proteins. To maintain latency, it is important that latent genes are expressed while lytic gene transcription is repressed23. The KSHV episome is packaged in chromatin and several labs have shown that in actively transcribed latency regions, the chromatin is in an open configuration, lacks nucleosomes, and exhibits active histone marks while lytic genes are packaged in closed chromatin (Figure 1)24–30. Recently, LANA has been found to bind to both viral and cellular transcriptional start sites that contain histones with the active H3K4me3 mark, allowing the packaged DNA to be more accessible and actively transcribed31. Interestingly, LANA was also found to interact with the H3K4 methyltransferase hSET1, indicating LANA’s potential to play an active role in altering epigenetic changes31. Indeed, histone modifiers play an important role in the maintenance of latency31. Class I and class II histone deacetylases (HDACs) have been shown to repress TPA-induced reactivation through epigenetic changes32. Li et al. examined the effect of class III HDACs, known as sirtuins (SIRTs), and found that they also repress reactivation through epigenetic changes33. SIRT1 is able to inhibit lytic replication through its ability to bind to RTA and inhibit its transactivation activity33. In fact, inhibition of SIRT1 was sufficient to induce lytic replication33. Dillon et al. reported that the knockdown of another family of histone-modifying enzymes, the tousled-like kinases (TLKs), resulted in loss of latency and reactivation of the virus34. This was due to a decrease in inhibitory phospho-histone H3 associated with the RTA promoter.\n\nDuring latency, only a few viral proteins and microRNAs are expressed. The KSHV latent protein latency-associated nuclear antigen (LANA) establishes latency and tethers the KSHV episome to host chromosomes. During this phase of the KSHV lifecycle, lytic genes are suppressed. This suppression occurs due to chromatin modifications that put the replication and transcription activator (RTA) gene and other lytic genes in a closed chromatin conformation with histones that contain inhibitory marks (histones shown in red). These inhibitory modifications are likely regulated by histone deacetylases (HDACs) and tousled-like kinases (TLKs). LANA (lime green semi-circle) also suppresses RTA expression through a complex with poly-SUMO-2-ylated KAP1 (pink tear-drop with yellow circle) and nuclear factor E2-related factor 2 (Nrf2) (tan L) that binds to the RTA gene promoter, further inhibiting transcription (indicated by the red arrow). Upon addition of inducers of the latent/lytic switch, e.g. cellular stress or 12-O-tetradecanoylphorbol-13-acetate (TPA), the chromatin around lytic genes is opened. The histones associated with lytic genes lack inhibitory marks and contain activation marks (histones shown in green). This results in gene transcription from the RTA promoter being activated (green arrow), allowing for RTA expression and transactivation of downstream lytic genes.\n\nBesides epigenetic changes, cellular proteins play a role in the maintenance of latency through direct interactions with viral proteins. Krüppel-associated box domain-associated protein 1 (KAP1) is a chromatin remodeler, and several groups have shown that it also interacts with LANA35–37. Cai et al. reported that this interaction is strengthened by poly-SUMO-2-ylation of KAP1 so it can bind to a LANA SUMO-2 interacting motif37. LANA and KAP1 form a complex with another cellular protein named nuclear factor E2-related factor 2 (Nrf2)38, which targets the RTA promoter and allows for LANA-KAP1 to inhibit RTA expression, thereby repressing lytic replication (Figure 1)35,36.\n\nHeat shock protein 90 (HSP90) is a cellular chaperone protein that interacts with the N-terminus of LANA39. Using the HSP90 inhibitors 17-dimethylaminoethylamino-17-demethoxygeldana-mycin (17-DMAG) and AUY922, Chen et al. disrupted this interaction and found it led to degradation of LANA39. It was also observed that these inhibitors along with a third HSP90 inhibitor (PU-H71) caused apoptosis of PEL cell lines. Another group also reported an increase in apoptosis of PEL cell lines treated with PU-H7140. K1 is another viral protein involved in preventing apoptosis that was found to interact with HSP9041. When cells expressing K1 were treated with HSP90 inhibitors, it was discovered that K1 expression was decreased and K1’s anti-apoptotic effect was diminished. These studies show the important role of HSP90 in maintaining latency through stability of LANA39 and inhibition of apoptosis39–41.\n\n\nEfficient lytic replication of KSHV\n\nOnce KSHV is reactivated, it is important for efficient completion of the lytic cycle to make infectious viral progeny. Though RTA is the driver of reactivation, completion of the lytic cycle requires cellular proteins. The KSHV IE/DE protein ORF45 has been shown to activate cellular kinases in the ERK-RSK pathway, and inhibition of this leads to reduced lytic replication42. Recently, it has been found that sustained activation of ERK-RSK leads to the phosphorylation and accumulation of c-Fos, which binds to KSHV promoters43. This accumulation of active c-Fos allows for efficient late lytic gene expression, as shown by a knockdown of c-Fos resulting in a decrease of ORF64 lytic gene expression and the fact that a non-functional form of c-Fos resulted in decreased virion production. Fu et al. also examined ORF45 activation of ERK-RSK signaling and discovered that amino acids 56–70 of ORF45 are critical for its interaction with RSK44. In fact, a single amino acid mutation of ORF45 at F66 can disrupt its ability to activate RSK, which leads to decreased late lytic gene expression and reduction of new virus. It was also shown that reactive oxygen species (ROS) can induce KSHV reactivation from latency45 and that induction of the KSHV lytic cycle further upregulates ROS, which can be targeted with N-acetyl-L-cysteine (NAC) to inhibit the development of KS46.\n\nAnother pathway shown to be important for late lytic replication is the DNA damage response (DDR) pathway. Hollingworth et al. have demonstrated that upon reactivation, early lytic gene expression activates DDR kinases47, as does primary infection48. When inhibitors of ATM and ATR were added to cell culture, it was found that the virus could reactivate and enter lytic replication, but late gene expression was diminished, resulting in fewer infectious viral progeny being made47.\n\n\nCurrent therapies\n\nMost KSHV-infected cells harbor the latent form of the virus. In the case of KS and PEL, most tumor cells are latent with only a few cells exhibiting lytic gene expression. In MCD, a larger proportion of the tumor mass displays lytic gene expression. Lytic replication is thought to be required to promote the growth of KSHV-associated cancers and help spread the virus. In most cases, the high proportion of cells undergoing abortive lytic replication express lytic proteins involved in the activation of angiogenesis and signal transduction, and complete viral replication does not occur9. Some researchers have hypothesized that the induction of lytic replication would be a good therapy for KSHV cancers if used in combination with a lytic inhibitor such as ganciclovir. By initiating reactivation but not allowing full lytic replication, more immunodominant targets could be produced that would be recognized by the immune system and provide more druggable targets to kill infected cells49,50.\n\nIn 2011, a pilot study was published in support of induction therapy in the treatment of KSHV-related MCD51. In this study, patients were treated with high-dose zidovudine along with valganciclovir. The KSHV kinases ORF36 and ORF21 phosphorylated these compounds, making them toxic to the cell. Overall, 86% of treated patients obtained a major clinical response and 50% obtained a major biochemical response as determined by improvements in clinical parameters such as hemoglobin, albumin, and C-reactive protein levels. The 5-year survival rate reported in this study was 86%51. Another report showed that in vitro treatment of KSHV-infected cells with the HIV protease drug nelfinavir resulted in less infectious KSHV virus being produced52.\n\nIn a search for effective inducers of lytic replication, Kang et al. screened 650 US Food and Drug Administration (FDA)-approved drugs in an in vitro assay53. This screen identified three topoisomerase II inhibitors (doxorubicin, daunorubicin, and epirubicin) as strong inducers of viral reactivation and that daunorubicin was even more powerful than the classic inducer, sodium butyrate. These three drugs were able to cause apoptosis through DNA intercalation, but the virus produced was capable of infecting new cells. Hence, if these inducers were to be used in patients, it would require their use in combination with a viral replication inhibitor.\n\nSeveral groups have shown that latency is linked to a dysregulated metabolic state of the cell with increased fatty acid synthesis54–56. SIRT1 function is also linked to promoting increased fatty acid synthesis, and, as previously stated, inhibition of SIRT1 leads to increased lytic replication33. Bhatt et al. showed that inhibition of fatty acid synthase (FASN) with a drug, C75, led to cellular apoptosis by activation of caspase 3 (another inducer of lytic replication, as discussed above)54. Moreover, KSHV-latent endothelial cells go through caspase 3/7-induced apoptosis when glutaminolysis is inhibited57. Dai et al. have also demonstrated that by inhibiting sphingosine kinase 2 and sphingolipid metabolism, PEL cells build up ceramides in the cell that result in lytic replication and apoptosis58. Furthermore, Leung et al. also demonstrated that clinically achievable amounts of the glucose metabolic analog 2-Deoxy-D-glucose (2-DG) induce endoplasmic reticulum stress and inhibit KSHV replication and reactivation from latency59. These data suggest that new therapeutics targeting metabolic pathways in KSHV cancer cells should also be explored.\n\nOther modes of therapies for KSHV-associated cancers have also been reported. Valiya Veettil et al. recently reported that latent KSHV cells have increased glutamate secretion and metabotropic glutamate receptor 1 expression60. Inhibitors of glutamate secretion and receptor expression in KS and PEL cells were found to decrease cellular proliferation. Another study has demonstrated the ability of the drug celecoxib to suppress RTA expression and viral production by blocking the activation of the p38 MAPK pathway61. Another key pathway that has been targeted is the PI3K/Akt/mTOR pathway. Sin et al. demonstrated that the use of the mTOR inhibitor rapamycin was capable of inhibiting PEL tumor growth by reducing cytokine secretion and autocrine signaling62. Since then, more reports have come out showing other inhibitors of this pathway have similar effects63–65. It is interesting to note that not only does rapamycin inhibit tumor growth but it is also capable of inhibiting viral reactivation by repressing RTA expression through transcriptional and post-transcriptional mechanisms66.\n\nAnother pathway, the Notch signaling pathway, which is activated by KSHV, has recently been reported to cause endothelial-to-mesenchymal transition (EndMT)67,68 through the upregulation of membrane-type 1 matrix metalloproteinase (MT1-MMP)67 and the transcription factors Snail, Slug, Twist, ZEB1, and ZEB268. This EndMT event allows for the KSHV-infected cell to invade other tissue, an important aspect for the development of KS, and this knowledge of Notch signaling and KSHV provides new molecular targets for therapy.\n\n\nConcluding thoughts\n\nKSHV is a double-stranded DNA oncogenic herpesvirus. After infection, the virus goes latent and expresses only a few proteins and microRNAs. This latent virus can be reactivated and enter the lytic cycle through either cellular stress or chemical induction that alters the epigenetics of the cell. During the complete lytic cycle, the virus expresses its genes in a temporal fashion and produces new, infectious virus particles that ultimately kill the cell.\n\nEven though the lytic cycle is important for pathogenesis, the vast majority of cells in KSHV malignancies harbor latent virus. Viral induction therapy is a promising method to treat KSHV-related diseases. It is important, however, to create a balance between efficient reactivation of latent cells and controlling the spread of infection through the use of combination therapies involving lytic replication inhibitors. This method of treatment has the potential to induce immunodominant viral proteins, cause apoptosis of the cell, and inhibit the production of structural proteins so new virions cannot be made. Future experiments should explore new combinations of KSHV-reactivating drugs and late lytic cycle inhibitors. Some potential inducers to be used in these experiments include the anthracyclines and HSP90 inhibitors described above as well as the growing number of SIRT1 inhibitors69. To inhibit late lytic replication, classical drugs such as valganciclovir can be used. Other possibilities include inducing RTA-independent lytic replication, possibly by targeting metabolic processes, where a significant decrease in viral progeny is observed. Continued advances in this field will provide additional insights into the biology and pathogenesis of KSHV infection as well as better treatments and cures for KSHV-related cancers.\n\n\nAbbreviations\n\nDDR, DNA damage response; DE, delayed early; EndMT, endothelial-to-mesenchymal transition; HDAC, histone deacetylase; HSP90, Heat shock protein 90; IE, immediate early; KAP1, Krüppel-associated box domain-associated protein 1; KICS, KSHV inflammatory cytokine syndrome; KSHV, Kaposi’s sarcoma-associated herpesvirus; LANA, latency-associated nuclear antigen; MCD, multicentric Castleman’s disease; PEL, primary effusion lymphoma; RTA, replication and transcription activator; ROS, reactive oxygen species; SIRT, sirtuin; TLK, tousled-like kinase; TPA, 12-O-tetradecanoylphorbol-13-acetate; vIL-6, viral interleukin-6.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nBlossom Damania is supported by NIH grants CA096500, CA163217, CA019014, and DE018281. Nathan J. Dissinger is supported by T90-DE021986. Blossom Damania is a Leukemia & Lymphoma Society Scholar and a Burroughs Wellcome Fund Investigator in the Pathogenesis of Infectious Disease.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nDue to limitations on the total word count for this article, we sincerely apologize for not being able to cite all papers related to this topic.\n\n\nReferences\n\nChang Y, Cesarman E, Pessin MS, et al.: Identification of herpesvirus-like DNA sequences in AIDS-associated Kaposi's sarcoma. Science. 1994; 266(5192): 1865–1869. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFu B, Kuang E, Li W, et al.: Activation of p90 ribosomal S6 kinases by ORF45 of Kaposi's sarcoma-associated herpesvirus is critical for optimal production of infectious viruses. J Virol. 2015; 89(1): 195–207. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nYe F, Zhou F, Bedolla RG, et al.: Reactive oxygen species hydrogen peroxide mediates Kaposi's sarcoma-associated herpesvirus reactivation from latency. PLoS Pathog. 2011; 7(5): e1002054. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMa Q, Cavallin LE, Leung HJ, et al.: A role for virally induced reactive oxygen species in Kaposi's sarcoma herpesvirus tumorigenesis. Antioxid Redox Signal. 2013; 18(1): 80–90. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHollingworth R, Skalka GL, Stewart GS, et al.: Activation of DNA Damage Response Pathways during Lytic Replication of KSHV. Viruses. 2015; 7(6): 2908–2927. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSingh VV, Dutta D, Ansari MA, et al.: Kaposi's sarcoma-associated herpesvirus induces the ATM and H2AX DNA damage response early during de novo infection of primary endothelial cells, which play roles in latency establishment. J Virol. 2014; 88(5): 2821–2834. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKlass CM, Krug LT, Pozharskaya VP, et al.: The targeting of primary effusion lymphoma cells for apoptosis by inducing lytic replication of human herpesvirus 8 while blocking virus production. Blood. 2005; 105(10): 4028–4034. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBhatt S, Ashlock BM, Toomey NL, et al.: Efficacious proteasome/HDAC inhibitor combination therapy for primary effusion lymphoma. J Clin Invest. 2013; 123(6): 2616–2628. PubMed Abstract | Publisher Full Text | Free Full Text\n\nUldrick TS, Polizzotto MN, Aleman K, et al.: High-dose zidovudine plus valganciclovir for Kaposi sarcoma herpesvirus-associated multicentric Castleman disease: a pilot study of virus-activated cytotoxic therapy. Blood. 2011; 117(26): 6977–6986. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGantt S, Carlsson J, Ikoma M, et al.: The HIV protease inhibitor nelfinavir inhibits Kaposi's sarcoma-associated herpesvirus replication in vitro. Antimicrob Agents Chemother. 2011; 55(6): 2696–2703. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKang H, Song J, Choi K, et al.: Efficient lytic induction of Kaposi's sarcoma-associated herpesvirus (KSHV) by the anthracyclines. Oncotarget. 2014; 5(18): 8515–8527. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBhatt AP, Jacobs SR, Freemerman AJ, et al.: Dysregulation of fatty acid synthesis and glycolysis in non-Hodgkin lymphoma. Proc Natl Acad Sci U S A. 2012; 109(29): 11818–11823. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSharma-Walia N, Chandran K, Patel K, et al.: The Kaposi's sarcoma-associated herpesvirus (KSHV)-induced 5-lipoxygenase-leukotriene B4 cascade plays key roles in KSHV latency, monocyte recruitment, and lipogenesis. J Virol. 2014; 88(4): 2131–2156. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDelgado T, Sanchez EL, Camarda R, et al.: Global metabolic profiling of infection by an oncogenic virus: KSHV induces and requires lipogenesis for survival of latent infection. PLoS Pathog. 2012; 8(8): e1002866. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSanchez EL, Carroll PA, Thalhofer AB, et al.: Latent KSHV Infected Endothelial Cells Are Glutamine Addicted and Require Glutaminolysis for Survival. PLoS Pathog. 2015; 11(7): e1005052. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDai L, Trillo-Tinoco J, Bai A, et al.: Ceramides promote apoptosis for virus-infected lymphoma cells through induction of ceramide synthases and viral lytic gene expression. Oncotarget. 2015; 6(27): 24246–24260. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLeung HJ, Duran EM, Kurtoglu M, et al.: Activation of the unfolded protein response by 2-deoxy-D-glucose inhibits Kaposi's sarcoma-associated herpesvirus replication and gene expression. Antimicrob Agents Chemother. 2012; 56(11): 5794–5803. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nValiya Veettil M, Dutta D, Bottero V, et al.: Glutamate secretion and metabotropic glutamate receptor 1 expression during Kaposi's sarcoma-associated herpesvirus infection promotes cell proliferation. PLoS Pathog. 2014; 10(10): e1004389. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nChen J, Jiang L, Lan K, et al.: Celecoxib Inhibits the Lytic Activation of Kaposi's Sarcoma-Associated Herpesvirus through Down-Regulation of RTA Expression by Inhibiting the Activation of p38 MAPK. Viruses. 2015; 7(5): 2268–2287. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSin SH, Roy D, Wang L, et al.: Rapamycin is efficacious against primary effusion lymphoma (PEL) cell lines in vivo by inhibiting autocrine signaling. Blood. 2007; 109(5): 2165–2173. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBhatt AP, Bhende PM, Sin SH, et al.: Dual inhibition of PI3K and mTOR inhibits autocrine and paracrine proliferative loops in PI3K/Akt/mTOR-addicted lymphomas. Blood. 2010; 115(22): 4455–4463. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRoy D, Sin SH, Lucas A, et al.: mTOR inhibitors block Kaposi sarcoma growth by inhibiting essential autocrine growth factors and tumor angiogenesis. Cancer Res. 2013; 73(7): 2235–2246. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAnders P, Bhende PM, Foote M, et al.: Dual inhibition of phosphatidylinositol 3-kinase/mammalian target of rapamycin and mitogen activated protein kinase pathways in non-Hodgkin lymphoma. Leuk Lymphoma. 2015; 56(1): 263–266. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNichols LA, Adang LA, Kedes DH: Rapamycin blocks production of KSHV/HHV8: insights into the anti-tumor activity of an immunosuppressant drug. PLoS One. 2011; 6(1): e14535. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nCheng F, Pekkonen P, Laurinavicius S, et al.: KSHV-initiated notch activation leads to membrane-type-1 matrix metalloproteinase-dependent lymphatic endothelial-to-mesenchymal transition. Cell Host Microbe. 2011; 10(6): 577–590. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGasperini P, Espigol-Frigole G, McCormick PJ, et al.: Kaposi sarcoma herpesvirus promotes endothelial-to-mesenchymal transition through Notch-dependent signaling. Cancer Res. 2012; 72(5): 1157–1169. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHu J, Jing H, Lin H: Sirtuin inhibitors as anticancer agents. Future Med Chem. 2014; 6(8): 945–966. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "13556",
"date": "25 Apr 2016",
"name": "Melanie M Brinkmann",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13557",
"date": "25 Apr 2016",
"name": "Thomas F Schulz",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-740
|
https://f1000research.com/articles/5-739/v1
|
25 Apr 16
|
{
"type": "Review",
"title": "Early detection of lung cancer",
"authors": [
"David E. Midthun"
],
"abstract": "Most patients with lung cancer are diagnosed when they present with symptoms, they have advanced stage disease, and curative treatment is no longer an option. An effective screening test has long been desired for early detection with the goal of reducing mortality from lung cancer. Sputum cytology, chest radiography, and computed tomography (CT) scan have been studied as potential screening tests. The National Lung Screening Trial (NLST) demonstrated a 20% reduction in mortality with low-dose CT (LDCT) screening, and guidelines now endorse annual LDCT for those at high risk. Implementation of screening is underway with the desire that the benefits be seen in clinical practice outside of a research study format. Concerns include management of false positives, cost, incidental findings, radiation exposure, and overdiagnosis. Studies continue to evaluate LDCT screening and use of biomarkers in risk assessment and diagnosis in attempt to further improve outcomes for patients with lung cancer.",
"keywords": [
"lung cancer",
"lung cancer screening",
"lung Screening"
],
"content": "Introduction\n\nThe American Cancer Society estimates that there will be approximately 224,000 new cases and 158,000 deaths from lung cancer in 2016; the current 5-year survival is about 18%1. Those are sobering statistics, yet in cancers where widespread screening is employed (breast, colon, and prostate), the 5-year survival rates are significantly better: 91%, 66%, and 99%, respectively1. We now know that screening for lung cancer saves lives. There is considerable relief in that statement given it has been over 30 years since the results of the Mayo Lung Project along with studies from Johns Hopkins University and Memorial Sloan Kettering Cancer Center showed lack of mortality reduction from screening with chest X-ray and sputum cytology2. Advances in computed tomography (CT) technology with spiral low-dose CTs (LDCTs) allow for scanning of the entire chest in less than 15 seconds and in a single breath-hold, which is convenient and eliminates respiratory motion artefact3. Early studies of screening for lung cancer with CT showed promise in detecting more cancers and more early stage cancers, and with improved survival, yet benefit in mortality reduction needed to be shown4–6. The National Lung Screening Trial (NLST) was a trial of over 53,000 high-risk individuals (defined as current smokers aged 55–74 years with 30 pack-years or if quit had done so within 15 years) randomized between screening with LDCT versus chest X-ray7. The three scans (baseline and annually for 2 years) in the LDCT arm resulted in a 20% lower mortality from lung cancer8. Screening may result in detection at a time when treatment is more effective and so improves outcomes and functional abilities and enhances quality of life. Implementation of LDCT screening into daily practice needs to be done with care to maximize the benefit and minimize the harms. Further studies will help better determine who to screen, how often, and how best to handle results. The potential role for biomarkers to assist or substantially redirect the lung cancer screening process is being explored.\n\n\nScreening for lung cancer: the story so far\n\nSmoking avoidance or cessation is the primary means to prevent lung cancer9. The goal for those who remain at high risk would be to detect lung cancer at an early stage, when treatment is more likely curative. In the NLST, 649 cancers were detected by CT and 367 diagnosed during follow-up post screening in the CT arm8. In the chest X-ray arm, there were 279 cancers detected by chest X-ray and 525 diagnosed during follow-up post screening. Within the CT arm, 63% of lung cancers diagnosed from a positive screening test were stage I; only 29.8% were stage III or IV. Among cancers detected by chest X-ray, 47.6% were stage I, and 43.2% were stage III or IV. The reduction in advanced cancers detected with CT in the NLST demonstrated a shift in stage at diagnosis from advanced disease to early stage. After a median follow-up of 6.5 years, there were 356 lung cancer deaths among those in the CT arm versus 443 deaths among those in the chest X-ray arm, or a 20% reduction8. In the NLST, the number of high-risk participants needed to screen with CT to save one life from lung cancer was 320 with three scans and 6 years of follow-up. This compares quite favorably to breast cancer, where the estimate is 781 women need to be screened for 8 years to save one life, and colon cancer where 1250 need to be screened over 8 years with fecal occult blood testing to save one life10. These data indicate that CT screening is more efficient than other accepted forms of screening for cancer.\n\nSince the publication of the findings from the NLST, screening with LDCT has been endorsed in guidelines and recommendations from various organizations including the American Cancer Society11, American Lung Association12, American Association of Thoracic Surgeons13, American Society for Clinical Oncology14, American College of Chest Physicians14,15, American Thoracic Society16, National Comprehensive Cancer Network17, and the US Preventive Services Task Force (USPSTF)18. In 2013, the USPSTF gave LDCT screening a B recommendation (same as mammography) for screening high-risk individuals18.\n\nTo date, the NLST is the only study that has shown a reduction in death from lung cancer with LDCT (Table 1). Several other randomized CT screening trials in Europe have not shown benefit in mortality reduction, though these trials were small, underpowered, included participants at lower risk, and may have had inadequate follow-up. The Danish Lung Cancer Screening Trial (DLCST) randomized 4104 participants to CT versus no screening with lower inclusion limits of age of 50 years and 20 pack-years of smoking19. After five rounds of screening, investigators reported 100 lung cancers and 39 deaths in the CT screen group versus 53 cancers and 38 deaths in the no screening group19. In other words, despite CT detecting more cancers and more early stage cancers, there were comparable numbers of advanced cancers in both groups and there was no mortality reduction with CT screening. Similarly, the MILD and DANTE studies showed no reduction in mortality with CT screening compared to no screening20,21. The ITALUNG study randomized 3206 participants to LDCT versus no screening, and the Depiscan study randomized 621 participants between CT and chest X-ray and no information has been published regarding mortality in these studies22,23. The largest remaining study is the NELSON trial with 7557 participants randomized to receive CT screening, and 71% of the cancers identified were stage I and only 5% were in stage IV; information on mortality has not been published24,25. Results from the pilot of the UK Lung Cancer Screening trial are promising, showing that 35 of 42 participants (83%) found to have lung cancer on the baseline or 12-month scan underwent surgical resection26. European countries have not endorsed LDCT screening at this time27.\n\nNR: not reported\n\n* reported as positive if a nodule ≥5 mm was detected\n\n** reported as positive if a nodule ≥4 mm was detected\n\nHow is the medical community in the US supposed to implement screening? At this point, it may be easier to come up with questions rather than the answers. Additional appropriately powered randomized studies to guide the process appear unlikely. Programs will have similar elements yet will have features that reflect local needs and resources. Policy statements and implementation reviews are available to help identify the key components of a CT screening program16,28,29. Much of this process is being dictated by the Center for Medicare and Medicaid Services (CMS) and the American College of Radiology (ACR), which will maintain the registry through which reimbursement by CMS has been approved30,31. CMS has activated two new G codes for use for the shared decision making visit (G0296) and for the LDCT scan (G0297) and began reimbursement in January 201632. A multidisciplinary committee consisting of pulmonology, radiology, primary care, thoracic surgery, interventional radiology, and medical and radiation oncology is important to facilitate LDCT screening, evaluate those with significantly abnormal results, and treat those with cancer. The inclusion of each of these disciplines within the process helps to assure the patient has a complete complement of options regarding diagnosis and treatment and also should limit the implementation of screening to systems with needed expertise available. Having dedicated secretarial and administrative support is important to a program’s success.\n\nWho should be screened? A study based on the findings of the NLST found that if the screening regimen adopted in the NLST was fully implemented among screening-eligible US populations, a total of 12,250 (95% confidence interval [CI] 10,170–15,671) lung cancer deaths (8990 deaths in men and 3260 deaths in women) would be averted each year33. Unfortunately, that would be fewer than 10% of the annual deaths from lung cancer. Why so few? The NLST was designed to make a small pond with big fish in it to see if fishing for lung cancer with LDCT was effective. The simplest answer of who to screen is to simply follow the NLST criteria: age 55–74 with a 30 pack-year history of smoking and either current smokers or those who have quit within 15 years7. In doing so, many individuals at equivalent or higher risk than included in the NLST would be excluded from screening. There are several guidelines published recommending screening and they differ. USPSTF recommends ages 55–80 (and is so mandated within the Affordable Care Act)18; CMS is reimbursing for those aged 55–77 and so defines the coverage for those in Medicare and Medicaid30. The National Comprehensive Care Network (NCCN) additionally recommends screening for those aged ≥50 with a 20 pack-year history and one additional risk factor such as chronic obstructive pulmonary disease (COPD), family history of lung cancer, occupational exposure to carcinogens, and significant radon exposure17. Similarly, the American Association of Thoracic Surgery recommends screening for those aged 55–79 within the NLST smoking criteria as well as those aged ≥50 with a ≥20 pack-year history and a cumulative risk of ≥5% over 5 years13. At present, the American Academy of Family Physicians recommends against LDCT screening34.\n\nAge and pack-years alone do not utilize other factors know to be indicators of increased risk such as presence of COPD and a family history of lung cancer. Our program is recommending screening based on risk rather than reimbursement and, as a consequence, in addition to those who meet USPSTF criteria, recommends screening to those who have equivalent or higher risk using the PLCO2012 model35. The primary group that this adds comprises those who smoked 30 pack-years but have quit 15 or more years ago and remain at high risk for lung cancer. In a retrospective cohort of patients who were diagnosed with lung cancer, Yang et al. suggest that expanding the criteria of screening to include those who quit smoking 15–30 years ago would have the potential to include 16% more of those who got cancer with acceptable cost and minimal harm36.\n\nBenefit from screening has been demonstrated in only high-risk individuals as defined by the NLST; there are no data to support screening in individuals at lower risk. There is good evidence that likelihood of benefit drops off sharply at lower risk and, as the likelihood of benefit from screening diminishes, the probability of harm increases. Within the NLST, the 60% of participants with the highest risk accounted for 88% of the prevented lung cancer deaths, while in contrast the 20% at lowest risk were the source for only 1% of the prevented lung cancer deaths37. Stated another way, among those at highest risk in the NLST, only 161 participants needed to be screened for the study period to avoid one lung cancer death, while among those at lowest risk screening more than 5000 was required to save a life37. Screening in lower risk individuals is to be avoided. One of the top five recommendations identified as medically appropriate and cost saving within the Choosing Wisely campaign was to avoid screening low-risk individuals for lung cancer38.\n\nExclusion criteria should be similar between programs and include a history of lung cancer within the past 5 years, poor lung function or other serious comorbidities that would not allow one to be a candidate for surgery if needed or would greatly limit life expectancy, need for continuous oxygen supplementation, an unexplained weight loss of more than 15 lbs in the 12 months prior, recent hemoptysis, a chest CT examination in the prior 12 months, and current symptoms of an acute or resolving respiratory tract infection7.\n\nThe USPSTF recommendation includes a shared decision making process (not required for breast cancer screening)17; this is mandated by CMS as an identifiable visit with specific components: eligibility, absence of signs or symptoms of lung cancer, discussion of benefits and harms of screening, follow-up diagnostic testing, overdiagnosis, false positive rate, radiation exposure, importance of adherence to annual screening, impact of comorbidities, willingness to undergo treatment, and the importance of cigarette smoking abstinence or cessation30. In the NLST, there were 16 deaths within 60 days of an invasive procedure and only 10 of those had cancer; patients need to know that the process of screening can be fatal8. Our program mandates tobacco cessation counseling for current smokers prior to screening in an attempt to make clear that cessation is more lifesaving than screening.\n\nThe ACR and Society of Thoracic Radiology have identified specifications for LDCT and the registry requires that those technical parameters be met31. A structured reporting system is desired; the ACR registry is the only approved registry and requires that the Lung Imaging Reporting and Data System (Lung-RADS) be used. Lung-RADS is only partially consistent with evidence-based guidelines, is ambiguous, and is not aimed at patient communication. Mandating a result be reported by one algorithm adds consistency and benefit if correct but stands to delay innovation to determine the best response to abnormal results. Endorsing screening in programs able to demonstrate a multidisciplinary approach may have been a better means to reduce the harms of screening rather than to focus on the radiology performance as CMS has chosen to do. Doing the CT scan is the easy part; what happens afterward is where there is opportunity to do this badly. Screening with LDCT has now shown the ability to reduce deaths from lung cancer. However, harmful effects of screening can include unnecessary testing from false positive results and incidental findings, radiation exposure, cost, biopsy and surgery for benign disease, and overdiagnosis. Other concerns include the potential for anxiety, distress, or impact on quality of life. Despite these concerns, reports have shown no significant short-term effects on quality of life in patients with LDCT screening39.\n\n\nNodule evaluation\n\nAn optimal nodule evaluation algorithm is yet to be determined and, since patient preference is to be weighed, no one fit will size all. Guidelines and nodule risk tools can assist in the decision making17,40–42. Data show that patients nearly always assumed that their lung nodule was malignant43. Given that as many as 50% of those having a screening CT will have one or more nodules detected, educating the patient about nodules and the low likelihood of malignancy is important5,24. In a survey of participants in the NELSON trial, those with a nodule detected had a short-term increase in lung cancer-specific distress, whereas those with a negative scan experienced relief39. Follow-up of the CT results is imperative – a dedicated program registry is mandatory in this regard.\n\nMany raise concerns about the false positives of CT screening; within the NLST (positive defined as ≥4 mm), false positives were 96%8. The 4 mm nodule has a likelihood of lung cancer of well less than 1%8,42. Should we call it a positive with that probability? The reality is that the vast majority of nodules found by CT screening need no additional evaluation other than CT follow-up – most with the next annual scan. An analysis of data from the NLST showed the percentages of lung cancer diagnoses that would have been missed or delayed and false positives that would have been avoided increased from 1.0% and 15.8% at a 5 mm threshold to 10.5% and 65.8% at an 8 mm threshold, respectively (Figure 1)44.\n\nA 62-year-old woman, former smoker with a 40-pack year history, had a low-dose computed tomography (CT) screen showing a 3 mm nodule (A) in the left lung (lingula). At 1-year follow-up, the nodule had grown (B) and at surgical resection was a 6 mm adenocarcinoma. She remains without evidence of disease 9 years after removal.\n\nIn a 5-year study of LDCT screening with 5203 asymptomatic high-risk individuals, primary lung cancers were detected with 77.7% being early stage and only 14.2% benign lesions diagnosed surgically45. In the Mayo Clinic study, 10 (18%) of 55 participants underwent resection for benign disease46. Similarly, in a German study, benign nodules represented 20% of resections47. Despite narrowing what was considered a positive study, 24% and 27% of the surgical interventions in the NLST and NELSON trials, respectively, were for benign disease8,24.\n\nOur program is recommending positron emission tomography (PET)-CT or biopsy (depending on the circumstances) only for nodules 1 cm or greater, and that eliminates immediate evaluation for over 95% of the participants. At the same time, we don’t consider a 6 mm nodule negative; it exists and needs follow-up – the key is to provide accurate information to the patient and their provider as to the likelihood of malignancy. The program is responsible for the evaluation and follow-up of findings in a desire to favorably tip the balance of benefit versus harm. People don’t die from false positives, but they can die from their evaluation. Nodule evaluation should be done by those who do it every day; this is not appropriate for the primary provider and perhaps why the American Academy of Family Practice rejects LDCT screening34. Having the primary care provider evaluate the CT results would be similar to having the colonoscopist call at the time of a colonoscopy, describe the presence of an 8 mm polyp, and ask the provider, “what should I do?”\n\n\nIncidental findings\n\nIn addition to the concerns raised from abnormal opacities in the lungs, LDCT scans of the chest may find other abnormalities in the lung such as emphysema and fibrosis as well as disorders of other organs. Examples include coronary calcifications, aneurysms, nodules in the thyroid adrenals, adenopathy, and liver and kidney disease. Prevalence of incidental findings have been reported to be as high as 59–73% of those scanned48,49; clinically significant findings, defined as those requiring additional evaluation, were present on an average of 14% of those scanned50. Such abnormalities may be the source of significant anxiety and uncertainty of what to do and may lead to additional testing and intervention, for which benefit has not been demonstrated.\n\n\nRadiation\n\nCT imaging involves radiation; thus, with the chance to find lung cancer is the chance to actually induce it. Estimates of the risk of LDCT are low, even if it were performed annually over several decades. The effective dose of radiation absorption is expressed in millisieverts (mSv). The average effective dose for a standard CT of the chest is approximately 7 mSv. A low-dose scan is approximately 1.5 mSv, and this is approximately one-half of the natural ambient radiation exposure of approximately 3 mSv per year51,52. The American Association of Physicists in Medicine cites that the threshold radiation dose potentially associated with carcinogenesis is 50 mSv29. The authors of the NLST estimated that the radiation risk from screening smokers aged 55 years results in one to three lung cancer deaths per 10,000 people screened and 0.3 new breast cancers per 10,000 females8. This potential harm from screening highlights the importance of having proven mortality reduction through a randomized controlled trial. Whether every high-risk patient who initiates screening should continue screening annually is unclear. The NELSON trial is investigating screening at intervals of 2 and 2.5 years, and risk modeling that takes into account the findings on the baseline scan may be useful in determining for whom other than annual screening frequency is appropriate.\n\n\nCost\n\nWith the CMS coverage determination established, it is likely that insurance companies will endorse reimbursement of annual lung cancer screenings for the appropriate populations. Cost-effectiveness analysis using data from the NLST showed that screening for lung cancer with LDCT costs $81,000 per quality-adjusted life year (QALY) gained53. An actuarial modeling of LDCT using 2012 dollars estimated the cost per life year saved at $19,00054. Comparatively, annual mammography for breast cancer screening in women aged 40–80 is approximately $58,000 per QALY gained55, and screening for colon cancer with colonoscopy every 10 years starting at age 50 has a cost of $56,800 per QALY gained56. A projected analysis predicts that US implementation will result in 10.7 million more LDCT scans and 52,000 lung cancers detected with a total cost of $6.8 billion over a 5-year expenditure57.\n\n\nOverdiagnosis\n\nOverdiagnosis is recognized as a problem within lung cancer screening as it is within breast cancer and particularly prostate cancer screening. Most eventually lethal lung cancers have doubling times of 50 to 150 days, yet CT screening studies identify a subset of tumors with long tumor-doubling times of 400 days or more. These slow-growing cancers tend to appear as non-solid – either pure ground glass opacities (GGOs) or part solid nodules on CT (Figure 2). One screening study from Japan reported tumor doubling times ranging from 662 to 1486 days with a mean of 880 days among malignancies presenting as pure GGOs58. In the Mayo CT screening study, 13 of 48 (27%) screen-detected cancers exhibited doubling times that were over 400 days, suggesting these may have been overdiagnosis cancers59. Knowing that mortality is reduced with screening reduces the concern for overdiagnosis, even if non-lethal cancers are detected; lives saved through screening indicate that enough fast-growing cancers were found to be of benefit. Within the CT arm of the NLST, the estimate of overdiagnosis among all cancers was 18.5%60. The concept of overdiagnosis can be confusing to patients and providers, yet it is important to understand that some lung cancers can be less bio-aggressive and delay or avoidance of diagnosis and treatment may be appropriate where other clinical factors are more likely to affect life expectancy.\n\nThe nodule has changed minimally over 3 years and is currently being followed with annual computed tomography (CT). If this is a cancer, it is likely to be an adenocarcinoma in situ and may represent an overdiagnosis cancer.\n\n\nBiomarkers\n\nGiven concerns over the high cost, cumulative radiation exposure, and high rate of false positives from LDCT screening, researchers are investigating the value of non-invasive biomarkers. Biomarkers may be used to evaluate risk for lung cancer, to evaluate the likelihood a nodule is a cancer, and as the primary screening test prior to the CT. Investigations have evaluated different source material such as blood, sputum, exhaled breath, and airway epithelium and with various assays such as microRNA (miRNA), methylation, antitumor antibodies, plasma proteins, airway cell, and complement fragments. Establishing utility requires validation of the biomarker in the clinical setting in which it is intended (i.e. as a predictor of the presence of malignancy in a patient with a screen-detected nodule) and should be prospectively shown to outperform other methods of evaluation.\n\nSeveral trials have shown promise for using biomarkers for screening or evaluation of suspected cancer. For example, miRNAs are short single-stranded RNAs that direct the post-transcriptional repression of protein-coding genes and many are involved in oncogenesis61. Investigators retrospectively evaluated plasma miRNA signatures in samples from 939 participants, including 69 patients with lung cancer and 870 disease-free individuals in the MILD screening trial62. The diagnostic performance of miRNA for lung cancer detection was 87% for sensitivity and 81% for specificity; a negative predictive value (NPV) of 99% and the combination of both miRNA and LDCT resulted in a fivefold reduction of the LDCT false positive rate. Similarly, another group of investigators used a 13 miRNA signature on 1113 participants in the COSMOS lung cancer screening trial and reported sensitivity and specificity of 77.8% and 74.8%, respectively, with an NPV of 99%63. A negative result was found in 810 out of the 1067 individuals without lung cancer and in 10 of the 48 individuals with lung cancer, and the authors suggest that the miRNA test could be used as a first-line screening tool.\n\nA blood test that measures autoantibodies to lung cancer-associated antigens was tested in 1613 patients felt to be at high risk for lung cancer64; 61 patients (4%) were identified as having lung cancer and 25 tested positive by autoantibodies (sensitivity = 41%). A positive autoantibody test was associated with a 5.4-fold increase in lung cancer incidence versus a negative, suggesting it may be a complementary tool to LDCT for the detection of early lung cancer. The autoantibody test is now prospectively being tested in the primary screen setting.\n\nA validation study of a mass spectrometry, plasma-protein assay assessed the presence of malignancy in 141 CT-detected indeterminate pulmonary nodules and showed a 90% NPV and 26% positive predictive value65. The results were independent of patient age, tobacco use, nodule size, and presence of COPD, suggesting proteomic classifier provides a probability estimate for the likelihood of a benign etiology in clinical assessments of pulmonary nodules.\n\nAn alternative means of predicting the likelihood that a nodule is malignant uses a gene-expression classifier measured in airway lining cells collected from the mainstem bronchus at the time of bronchoscopy. Investigators reported on 341 patients, 63 of whom had non-diagnostic bronchoscopic investigations of a peripheral nodule66. The classifier had an area under the receiver-operating-characteristic curve (AUC) of 0.74, a sensitivity of 89%, and a specificity of 47%; the combination of the classifier plus bronchoscopy had a sensitivity of 98% independent of lesion size and location. The diagnostic performance of bronchoscopy was improved with the addition of the gene-expression classifier.\n\n\nConclusion\n\nThe debate regarding the appropriate onset, interval, and benefits of screening flames on in regard to breast cancer and mammography decades after studies showed mortality reduction. Given that, we should not expect to have all the answers regarding LDCT screening at the onset of clinical implementation. LDCT screening has been shown to save lives and implementation of screening is appropriate. The goal of a CT screening program is to detect early lung cancer and facilitate curative treatment; however, primary prevention through smoking cessation or never starting is the best means to reduce the risk of dying of lung cancer. We need to get the word out to those at high risk who stand to benefit most from mortality reduction. That being said, the current USPSTF recommendations are subject to change, as many at high risk for lung cancer are excluded by the blunt assessment of age and pack-years of smoking. We want and need people to quit smoking to reduce their risk for lung cancer. The incredulity of the current recommendation is that the 55 year old, with a 30 pack-year history of smoking who does what is desired and quits smoking at onset of screening, will be told in 15 years to quit screening – when the risk of lung cancer is approximately one and a half times the risk it was when screening began35. Fewer and fewer patients who actually get lung cancer are candidates for screening under the current criteria, predominantly because of the issue of stopping screening (or not starting) when beyond 15 years of having quit smoking36,67. Modifications to current screening guidelines will likely incorporate an individual’s additional factors beyond age and pack-years that increase their risk for lung cancer35,68. Risk modeling may also be used to indicate the interval for subsequent screenings based on the initial results69.\n\nDespite the focus on the radiologic performance, harm limitation centers on the appropriate evaluation of screen-detected nodules and calls for careful evaluation by pulmonologists and thoracic surgeons who do this every day and not simply passing the burden back to the primary care providers. Better methods need to be developed to separate the benign from the malignant abnormality on CT. Implementation of screening with regard to reducing harm is critical. We must implement screening in centers capable of multidisciplinary evaluation and with the expertise in dealing with lung cancer with options for video thoracic resections and reduced morbidity and options for stereotactic radiotherapy for those who may choose not to pursue surgery70.\n\nThe future will likely hold use of biomarkers as an initial screening test in those at high risk and as a means of evaluating those who have had LDCT screening and have an abnormal result. No guideline presently recommends the use of biomarkers in clinical practice, but there are now biomarkers commercially available; they need to be shown to prospectively improve upon the current methods of risk assessment and diagnostic evaluation in the context of screening to be part of daily practice.",
"appendix": "Competing interests\n\n\n\nThe author’s institution received funding for clinical research from Integrated Diagnostics in the evaluation of a protein classifier in patients with an indeterminate pulmonary nodule. The author served on an advisory committee for Oncimmune with no financial relationship.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nSiegel RL, Miller KD, Jemal A: Cancer statistics, 2016. CA Cancer J Clin. 2016; 66(1): 7–30. PubMed Abstract | Publisher Full Text\n\nFontana RS, Sanderson DR, Woolner LB, et al.: Screening for lung cancer. A critique of the Mayo Lung Project. Cancer. 1991; 67(4 Suppl): 1155–1164. PubMed Abstract | Publisher Full Text\n\nBrawley OW, Flenaugh EL: Low-dose spiral CT screening and evaluation of the solitary pulmonary nodule. Oncology (Williston Park). 2014; 28(5): 441–446. 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Lancet Oncol. 2014; 15(12): 1332–1341. PubMed Abstract | Publisher Full Text\n\nField JK, Duffy SW, Baldwin DR, et al.: UK Lung Cancer RCT Pilot Screening Trial: baseline findings from the screening arm provide evidence for the potential implementation of lung cancer screening. Thorax. 2016; 71(2): 161–170. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nVeronesi G: Lung cancer screening: the European perspective. Thorac Surg Clin. 2015; 25(2): 161–174. PubMed Abstract | Publisher Full Text\n\nMazzone P, Powell CA, Arenberg D, et al.: Components necessary for high-quality lung cancer screening: American College of Chest Physicians and American Thoracic Society Policy Statement. Chest. 2015; 147(2): 295–303. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMulshine JL, D'Amico TA: Issues with implementing a high-quality lung cancer screening program. CA Cancer J Clin. 2014; 64(5): 352–363. PubMed Abstract | Publisher Full Text\n\nCenters for Medicare & Medicaid Services: Decision memo for screening for lung cancer with low dose computed tomography (ldct) (cag-00439n).2015. Reference Source\n\nKazerooni EA, Austin JH, Black WC, et al.: ACR-STR practice parameter for the performance and reporting of lung cancer screening thoracic computed tomography (CT): 2014 (Resolution 4). J Thorac Imaging. 2014; 29(5): 310–316. PubMed Abstract | Publisher Full Text\n\nhttp://www.acr.org/News-Publications/News/News-Articles/2015/Economics/2015110315-Billing-Instructions-Lung-Cancer-Screening\n\nMa J, Ward EM, Smith R, et al.: Annual number of lung cancer deaths potentially avertable by screening in the United States. Cancer. 2013; 119(7): 1381–1385. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nAmerican Academy of Family Physicians Policy Statement. Reference Source\n\nTammemägi MC, Katki HA, Hocking WG, et al.: Selection criteria for lung-cancer screening. N Engl J Med. 2013; 368(8): 728–736. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYang P, Wang Y, Wampfler JA, et al.: Trends in Subpopulations at High Risk for Lung Cancer. J Thorac Oncol. 2016; 11(2): 194–202. PubMed Abstract | Publisher Full Text\n\nKovalchik SA, Tammemagi M, Berg CD, et al.: Targeting of low-dose CT screening according to the risk of lung-cancer death. N Engl J Med. 2013; 369(3): 245–254. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWiener RS, Ouellette DR, Diamond E, et al.: An official American Thoracic Society/American College of Chest Physicians policy statement: the Choosing Wisely top five list in adult pulmonary medicine. Chest. 2014; 145(6): 1383–1391. PubMed Abstract | Publisher Full Text | Free Full Text\n\nvan den Bergh KA, Essink-Bot ML, Borsboom GJ, et al.: Short-term health-related quality of life consequences in a lung cancer CT screening trial (NELSON). Br J Cancer. 2010; 102(1): 27–34. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGould MK, Donington J, Lynch WR, et al.: Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013; 143(5 Suppl): e93S–120S. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNaidich DP, Bankier AA, MacMahon H, et al.: Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society. Radiology. 2013; 266(1): 304–317. PubMed Abstract | Publisher Full Text\n\nMcWilliams A, Tammemagi MC, Mayo JR, et al.: Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med. 2013; 369(10): 910–919. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWiener RS, Gould MK, Woloshin S, et al.: What do you mean, a spot?: A qualitative analysis of patients' reactions to discussions with their physicians about pulmonary nodules. Chest. 2013; 143(3): 672–677. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGierada DS, Pinsky P, Nath H, et al.: Projected outcomes using different nodule sizes to define a positive CT lung cancer screening examination. J Natl Cancer Inst. 2014; 106(11): pii: dju284. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nVeronesi G, Maisonneuve P, Spaggiari L, et al.: Diagnostic performance of low-dose computed tomography screening for lung cancer over five years. J Thorac Oncol. 2014; 9(7): 935–939. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCrestanello JA, Allen MS, Jett JR, et al.: Thoracic surgical operations in patients enrolled in a computed tomographic screening trial. J Thorac Cardiovasc Surg. 2004; 128(2): 254–259. PubMed Abstract | Publisher Full Text\n\nDiederich S, Thomas M, Semik M, et al.: Screening for early lung cancer with low-dose spiral computed tomography: results of annual follow-up examinations in asymptomatic smokers. Eur Radiol. 2004; 14(4): 691–702. PubMed Abstract | Publisher Full Text\n\nJacobs PC, Mali WP, Grobbee DE, et al.: Prevalence of incidental findings in computed tomographic screening of the chest: a systematic review. J Comput Assist Tomogr. 2008; 32(2): 214–221. PubMed Abstract | Publisher Full Text\n\nPriola AM, Priola SM, Giaj-Levra M, et al.: Clinical implications and added costs of incidental findings in an early detection study of lung cancer by using low-dose spiral computed tomography. Clin Lung Cancer. 2013; 14(2): 139–148. PubMed Abstract | Publisher Full Text\n\nvan de Wiel JC, Wang Y, Xu DM, et al.: Neglectable benefit of searching for incidental findings in the Dutch-Belgian lung cancer screening trial (NELSON) using low-dose multidetector CT. Eur Radiol. 2007; 17(6): 1474–1482. PubMed Abstract | Publisher Full Text\n\nBrenner DJ, Hall EJ: Computed tomography--an increasing source of radiation exposure. N Engl J Med. 2007; 357(22): 2277–2284. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMcCollough CH, Primak AN, Braun N, et al.: Strategies for reducing radiation dose in CT. Radiol Clin North Am. 2009; 47(1): 27–40. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBlack WC, Gareen IF, Soneji SS, et al.: Cost-effectiveness of CT screening in the National Lung Screening Trial. N Engl J Med. 2014; 371(19): 1793–1802. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPyenson BS, Sander MS, Jiang Y, et al.: An actuarial analysis shows that offering lung cancer screening as an insurance benefit would save lives at relatively low cost. Health Aff (Millwood). 2012; 31(4): 770–779. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nStout NK, Rosenberg MA, Trentham-Dietz A, et al.: Retrospective cost-effectiveness analysis of screening mammography. J Natl Cancer Inst. 2006; 98(11): 774–782. PubMed Abstract | Publisher Full Text\n\nSharaf RN, Ladabaum U: Comparative effectiveness and cost-effectiveness of screening colonoscopy vs. sigmoidoscopy and alternative strategies. Am J Gastroenterol. 2013; 108(1): 120–132. PubMed Abstract | Publisher Full Text\n\nRoth JA, Sullivan SD, Goulart BH, et al.: Projected Clinical, Resource Use, and Fiscal Impacts of Implementing Low-Dose Computed Tomography Lung Cancer Screening in Medicare. J Oncol Pract. 2015; 11(4): 267–272. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nAoki T, Nakata H, Watanabe H, et al.: Evolution of peripheral lung adenocarcinomas: CT findings correlated with histology and tumor doubling time. AJR Am J Roentgenol. 2000; 174(3): 763–768. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLindell RM, Hartman TE, Swensen SJ, et al.: Five-year lung cancer screening experience: CT appearance, growth rate, location, and histologic features of 61 lung cancers. Radiology. 2007; 242(2): 555–562. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nPatz EF Jr, Pinsky P, Gatsonis C, et al.: Overdiagnosis in low-dose computed tomography screening for lung cancer. JAMA Intern Med. 2014; 174(2): 269–274. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nJoshi P, Middleton J, Jeon YJ, et al.: MicroRNAs in lung cancer. World J Methodol. 2014; 4(2): 59–72. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSozzi G, Boeri M, Rossi M, et al.: Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study. J Clin Oncol. 2014; 32(8): 768–773. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMontani F, Marzi MJ, Dezi F, et al.: miR-Test: a blood test for lung cancer early detection. J Natl Cancer Inst. 2015; 107(6): djv063. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nJett JR, Peek LJ, Fredericks L, et al.: Audit of the autoantibody test, EarlyCDT®-lung, in 1600 patients: an evaluation of its performance in routine clinical practice. Lung Cancer. 2014; 83(1): 51–55. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nVachani A, Pass HI, Rom WN, et al.: Validation of a multiprotein plasma classifier to identify benign lung nodules. J Thorac Oncol. 2015; 10(4): 629–637. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSilvestri GA, Vachani A, Whitney D, et al.: A Bronchial Genomic Classifier for the Diagnostic Evaluation of Lung Cancer. N Engl J Med. 2015; 373(3): 243–251. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWang Y, Midthun DE, Wampfler JA, et al.: Trends in the proportion of patients with lung cancer meeting screening criteria. JAMA. 2015; 313(8): 853–855. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVeronesi G, Maisonneuve P, Rampinelli C, et al.: Computed tomography screening for lung cancer: results of ten years of annual screening and validation of cosmos prediction model. Lung Cancer. 2013; 82(3): 426–430. PubMed Abstract | Publisher Full Text\n\nMaisonneuve P, Bagnardi V, Bellomi M, et al.: Lung cancer risk prediction to select smokers for screening CT--a model based on the Italian COSMOS trial. Cancer Prev Res (Phila). 2011; 4(11): 1778–1789. PubMed Abstract | Publisher Full Text\n\nChang JY, Senan S, Paul MA, et al.: Stereotactic ablative radiotherapy versus lobectomy for operable stage I non-small-cell lung cancer: a pooled analysis of two randomised trials. Lancet Oncol. 2015; 16(6): 630–637. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "13552",
"date": "25 Apr 2016",
"name": "Frank C Detterbeck",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13553",
"date": "25 Apr 2016",
"name": "Giulia Veronesi",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13555",
"date": "25 Apr 2016",
"name": "James L Mulshine",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-739
|
https://f1000research.com/articles/5-738/v1
|
25 Apr 16
|
{
"type": "Review",
"title": "Updates in diabetic peripheral neuropathy",
"authors": [
"Kelsey Juster-Switlyk",
"A. Gordon Smith",
"A. Gordon Smith"
],
"abstract": "Diabetes has become one of the largest global health-care problems of the 21st century. According to the Centers for Disease Control and Prevention, the population prevalence of diabetes in the US is approaching 10% and is increasing by 5% each year. Diabetic neuropathy is the most common complication associated with diabetes mellitus. Diabetes causes a broad spectrum of neuropathic complications, including acute and chronic forms affecting each level of the peripheral nerve, from the root to the distal axon. This review will focus on the most common form, distal symmetric diabetic polyneuropathy. There has been an evolution in our understanding of the pathophysiology and the management of diabetic polyneuropathy over the past decade. We highlight these new perspectives and provide updates from the past decade of research.",
"keywords": [
"diabetic peripheral neuropathy",
"Diabetes mellitus",
"polyneuropathy"
],
"content": "Introduction\n\nDiabetes has become one of the largest global health-care problems of the 21st century. The number of people with diabetes worldwide is predicted to double between 2000 and 2030, reaching a pandemic level of 366 million people1. Diabetic polyneuropathy (DPN), which has a lifetime prevalence of approximately 50%, is the most common diabetic complication2–6. DPN is a leading cause for disability due to foot ulceration and amputation, gait disturbance, and fall-related injury. Approximately 20 to 30% of patients with DPN suffer from neuropathic pain5–8. DPN significantly lowers quality of life and substantially increases health costs associated with diabetes9. The total annual medical costs for diabetes is $6,632 per patient10. Those with DPN experience a twofold increase in health-care costs ($12,492), and those with severe painful peripheral neuropathy experience a fourfold increase ($30,755)10. On a larger scale, the annual cost of diabetes in the US in 2012 was $245 billion, and it has been estimated that about 27% of health-care costs of diabetes can be attributed to DPN11,12. Despite a long history of research in this area, we are only starting to understand the pathophysiology of the disease. The past decade of research is marked by many surprises, the most pertinent being the major differences in pathogenesis and treatment of DPN in type 1 and type 2 diabetes.\n\n\nClinical features\n\nDiabetes causes a wide variety of acute, chronic, focal, and diffuse neuropathy syndromes. By far the most common is DPN, which accounts for 75% of diabetic neuropathy and thus is the focus of our review4,13. The other patterns of nerve injury include diabetic autonomic neuropathy, cranial neuropathy, mononeuritis multiplex, mononeuropathy, radiculoplexus neuropathies, diabetic neuropathic cachexia, and treatment-induced neuropathy in diabetes14. The last of these is an important recent advance and will be discussed separately. A patient may have multiple forms of neuropathy.\n\nDPN has been defined by the Toronto Consensus Panel on Diabetic Neuropathy as a “symmetrical, length-dependent sensorimotor polyneuropathy attributable to metabolic and microvessel alterations as a result of chronic hyperglycemia exposure and cardiovascular risk covariates”4. Sensory symptoms start in the toes and over time affect the upper limbs in a distribution classically described as a “stocking and glove” pattern. Motor involvement is not typically seen in the early stages of DPN. Patients describe a range of sensory symptoms, which may include loss of pain sensation or “Novocain-like” insensitivity, tingling, “pins and needles” sensation, burning, “electric shocks”, allodynia (painful sensation to an inoffensive stimuli), or hyperalgesia (increased sensitivity to painful stimuli). Interestingly, symptoms are not a predictable indicator of the severity of axonal loss. Often those with the most severe painful symptoms have minimal or no sensory deficit on exam or electrodiagnostic studies4. Neuropathic pain affects up to 20 to 30% of patients with DPN and is one of the main reasons this group seeks medical care5–8.\n\n\nTreatment-induced neuropathy in diabetes\n\nIn a seemingly paradoxical relationship, both poor glucose control and rapid treatment of hyperglycemia can be associated with an increased risk of neuropathy. A clinically distinct form of neuropathy that deserves mention is treatment-induced neuropathy in diabetes (TIND). This underdiagnosed iatrogenic small-fiber neuropathy is defined as the “acute onset of neuropathic pain and/or autonomic dysfunction within 8 weeks of a large improvement in glycemic control specified as a decrease in glycosylated HbA1c of more than 2% points over 3 months”15. TIND was first recognized soon after the introduction of insulin and named “insulin neuritis”16. For many decades, “insulin neuritis” was considered a rare cause for acute neuropathy. However, recently published data suggest that it is much more common and clinically relevant. It is most common in type 1 diabetes mellitus (DM) treated with insulin, although rapid glucose correction can occur in both types of diabetes as a result of either insulin, or less frequently, oral agents. In a study by Gibbons and Freeman, a surprising 10.9% of 954 subjects with diabetes met criteria for TIND, and the risk of developing TIND was associated with the magnitude and rate of HbA1c change15. Similar to DPN, the neuropathy of TIND generally follows a length-dependent pattern, but, in contrast, the pain and autonomic symptoms are more extensive and less responsive to opioids. The underlying pathophysiology is poorly understood, although it has been suggested that rapid glycemic control both with and without insulin leads to hemodynamic changes (arteriovenous shunting) resulting in endoneurial hypoxia of small fibers17,18.\n\n\nDiagnosis\n\nThe diagnosis of a DPN is most often made on clinical grounds with a suggestive clinical history and neurologic exam. The Toronto consensus criteria define probable neuropathy as the presence of two or more of the following: neuropathic symptoms, decreased distal sensation, or decreased or absent ankle reflexes. Confirmed neuropathy requires abnormality of nerve conduction study (NCS) or a validated measure of small-fiber function19. However, the diagnostic value of NCS in routine clinical practice has been called into question. Whereas patients with warning signs for an atypical neuropathy (e.g., acute onset, asymmetry, proximal involvement, and unexpected severity) clearly need electrodiagnostic testing, those with typical DPN likely do not need NCS to confirm diagnosis20–22. Early diabetic neuropathy often preferentially involves small-diameter axons; thus, skin biopsy with assessment of intraepidermal nerve fiber density (IENFD) may be useful in confirming the diagnosis when clinically warranted. In our practice, we use skin biopsies when we suspect a predominately small-fiber neuropathy in patients with an atypical course or a paucity of risk factors. Corneal confocal microscopy provides a non-invasive quantitative method of detecting neuropathy, and has been found to be more sensitive in assessing nerve repair than other standard measures such as IENFD and NCS23. Patients with suspected DPN should have a basic workup, including a blood glucose or hemoglobin A1c to confirm diabetes (fasting plasma glucose of more than 126 mg/dL or A1c of more than 6.5%) or pre-diabetes (fasting plasma glucose of more than 100 mg/dLor A1c of 5.7 to 6.4%), vitamin B12 deficiency, paraproteinemia (serum protein electrophoresis and immunofixation), and (when appropriate) evaluation for alcohol use24,25. When routine blood glucose testing is normal, the glucose tolerance test should be considered24. An important cause of vitamin B12 deficiency is iatrogenic, linked to cumulative doses of metformin26.\n\n\nPathogenesis of diabetic polyneuropathy\n\nDespite the different pathophysiology underlying type 1 and type 2 diabetes, there has been a longstanding assumption that the mechanism leading to DPN is shared. This assumption has recently been called into question8. Type 2 DM is much more common (90 to 95%) but has a slightly lower lifetime incidence of neuropathy (45%) compared with the 54 to 59% associated with type 1 DM27. Whereas treating hyperglycemia in type 1 DM can significantly reduce the incidence of neuropathy by up to 60 to 70%28,29, glucose control in type 2 DM has only a marginal 5 to 7% reduction in the development of neuropathy30,31. Over 40% of patients with diabetes develop neuropathy despite good glucose control, suggesting that other factors are driving nerve injury32. Type 2 DM is inseparably linked to the obesity epidemic; about 90% of diabetic risk is attributable to excess weight1. The longstanding notion that DPN occurs only after longstanding hyperglycemia has been replaced by the observation that even those with good glycemic control (HbA1c of less than 5.4%) are at risk33. Many recent studies have implicated cardiovascular risk factors, including obesity34, hypertriglyceridemia, hypercholesterolemia, hypertension, and cigarette smoking, in the pathogenesis of DPN35.\n\nThe pathogenesis of diabetic peripheral neuropathy is complex and is marked by both metabolic and vascular factors36. Hyperglycemia is only one of the many key metabolic events known to cause axonal and microvascular injury. A comprehensive, but by no means exhaustive, list of key players include hyperglycemia, toxic adiposity, oxidative stress, mitochondrial dysfunction, activation of the polyol pathway, accumulation of advanced glycation end products (AGEs), and elevation of inflammatory markers2,35. Although nerve fiber loss is accepted as the genesis of insensitivity in DPN4, the pathophysiological explanation behind neuropathic pain in diabetes is poorly understood. Sural nerve biopsies from patients with DPN revealed microvascular defects, including endoneurial basement membrane thickening as well as endothelial cell proliferation and hypertrophy, findings which were absent in diabetics without DPN37.\n\n\nManagement\n\nManagement of DPN includes attempts to alter the natural history and symptomatic treatments. The Diabetes Controls and Complications Trial clearly demonstrated that aggressive glycemic control reduced the risk of DPN and rate of progression of DPN in patients with type 1 diabetes28. Although for many years it was assumed that the same was true for DPN associated with type 2 diabetes, multiple studies now show no meaningful impact on DPN risk with aggressive versus standard glycemic control38. Owing to a growing understanding of the association between metabolic syndrome and DPN, more emphasis has been placed on obesity (particularly, visceral adiposity), dyslipidemia, and hypertension8. Several small studies suggest that lifestyle changes, including diet and exercise, may slow the progression of neuropathy by promoting small nerve fiber regeneration in neuropathy patients with diabetes and prediabetes39. One year of exercise has been shown to result in increased IENFD in diabetic patients without neuropathy, suggesting that this approach may be a useful preventative therapy39. This is supported by the observation, based on NCSs, that long-term exercise training can help prevent the development of DPN40. Data from a study using a capsaicin axotomy regeneration experiment before and after exercise suggest that the beneficial effects of exercise are mediated by enhanced nerve regeneration41. A common feature of these studies is individualized counseling or supervised exercise with clear goals and accountability. Integral to management of DPN is prevention of diabetic complications such as ulcers and falls. The lifetime risk of developing foot ulcers in patients with diabetes is high at 15%2. In addition to modifying metabolic factors contributing to the underlying diabetes, effective interventions to prevent ulceration include educating patients about prescription footwear, periodic foot examinations, and intensive podiatric care. Falls are an under-reported cause of injury, emergency room visits, and loss of independence. Primary prevention should start with primary care providers and involve a fall risk assessment, education, and referral to physical therapy or a community exercise program when appropriate42.\n\nMany potential disease-modifying drugs have been designed to target multiple metabolic pathways, including reactive oxygen species inhibitors, aldose reductase inhibitors, protein kinase C-beta inhibitors, agents acting on the AGE pathway, and agents acting on the hexosamine pathway2,43. Despite very promising preclinical and early-phase clinical data, none of these has proven effective. Given the known importance of oxidative stress in the underlying endothelial dysfunction and microvascular complications in diabetic neuropathy, one would expect antioxidants to be a viable therapeutic option. Alpha lipoic acid (ALA) is considered the most successful antioxidant in clinical trials and has been approved for the treatment of DPN in Europe but not in the US6,44. In the NATHAN 1 (Neurological Assessment of Thioctic Acid in Diabetic Neuropathy 1) trial, a multicenter randomized double-blind trial, 600 mg ALA daily for 4 years did not influence the primary composite end point (exam findings, a symptoms score, and NCSs) but did show a benefit in the examination score, but not NCSs43. In our practice, we have found some benefit in using ALA 600 mg daily for mild painful neuropathies or as an adjunct in more moderate or severe cases. Aldose reductase treatment showed initial promise in the treatment of DPN in several studies45,46; however, in a Cochrane review of 32 randomized controlled trials, no statistically significant difference between aldose reductase inhibitors and placebo was found47. Many other disease-modifying therapies have been studied, although the vast majority, including the antioxidant benfotiamine, have failed to show efficacy48.\n\nThe most common disabling symptom of DPN is pain, which occurs in 20 to 30% of patients5–8. The most popular analgesic treatments include tricyclic antidepressants (amitriptyline and nortriptyline), anticonvulsants (gabapentin and pregabalin), and serotonin-norepinephrine reuptake inhibitors (SNRIs) (duloxetine and venlafaxine)2. The European Federation of Neurological Societies (EFNS) and the American Academy of Neurology (AAN) have each published evidence-based guidelines regarding treatment of painful DPN. However, given the relative paucity of head-to-head trials on comparative efficacy and the short duration of most clinical trials, clinicians rely heavily on clinical judgment based on a patient comorbidities, potential adverse effects, medication interactions, and cost49,50. Despite evidence suggesting that the effectiveness of these first-line agents does not differ substantially, only duloxetine and pregabalin are approved by the US Food and Drug Administration to treat neuropathic pain in diabetes5,50. These two agents are significantly more expensive than other first-line agents. A recent cost comparison found that the costs for 1 month at the typical starting dose were $189.98 for pregabalin and $170.99 for duloxetine compared with $18.99 for gabapentin and $12.99 for amitriptyline50. The EFNS and AAN provide conflicting evidence for topical agents and in clinical practice they are rarely sufficient as monotherapy. Both controlled-release oxycodone and tramadol with acetaminophen were recommended with level A evidence by the EFNS and with level B evidence by the AAN8. A recent survey showed that DPN was treated with anticonvulsants in 27%, SNRIs in 18%, and opioids in 43%51. Despite many effective agents, poor access to specialists leads to inadequate and often inappropriate treatment.\n\nBeyond pain, falls and foot ulcers are two very costly and debilitating symptoms, which are important patient-oriented outcomes. Patients with DPN are two to three times more likely to fall than diabetics without neuropathy. This is not a late-stage complication; the increased risk of falls has been noted 3 to 5 years prior to their diagnosis8,52. In addition, those with neuropathy have a 15% increased risk of developing ulcers during their disease course and 6 to 43% of those with ulcers will eventually have an amputation8.\n\n\nConclusions\n\nDPN is a common and costly disease. Over the past decade, there have been great strides in understanding the underlying pathophysiology and the interplay of metabolic risk factors. Aggressive glycemic control is an effective disease-altering strategy in type 1 diabetes but not in type 2 diabetes. The many metabolic and inflammatory consequences of toxic adiposity are likely major contributors to neuropathy risk, particularly in type 2 diabetes. Evolving data suggest that weight loss and exercise are helpful strategies for patients with neuropathy in the setting of both diabetes and prediabetes. Implementing strategies that target these modifiable risk factors will require fundamental social changes and may necessitate major public health initiatives.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nHossain P, Kawar B, El Nahas M: Obesity and diabetes in the developing world--a growing challenge. N Engl J Med. 2007; 356(3): 213–5. PubMed Abstract | Publisher Full Text\n\nSingh R, Kishore L, Kaur N: Diabetic peripheral neuropathy: current perspective and future directions. Pharmacol Res. 2014; 80: 21–35. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBoulton AJ: Management of Diabetic Peripheral Neuropathy. Clin Diabetes. 2005; 23(1): 9–15. Publisher Full Text\n\nTesfaye S, Selvarajah D: Advances in the epidemiology, pathogenesis and management of diabetic peripheral neuropathy. Diabetes Metab Res Rev. 2012; 28(Suppl 1): 8–14. PubMed Abstract | Publisher Full Text\n\nTesfaye S, Vileikyte L, Rayman G, et al.: Painful diabetic peripheral neuropathy: consensus recommendations on diagnosis, assessment and management. Diabetes Metab Res Rev. 2011; 27(7): 629–38. PubMed Abstract | Publisher Full Text\n\nTesfaye S, Boulton AJ, Dyck PJ, et al.: Diabetic neuropathies: update on definitions, diagnostic criteria, estimation of severity, and treatments. Diabetes Care. 2010; 33(10): 2285–93. PubMed Abstract | Publisher Full Text | Free Full Text\n\nQuattrini C, Tesfaye S: Understanding the impact of painful diabetic neuropathy. Diabetes Metab Res Rev. 2003; 19(Suppl 1): S2–8. PubMed Abstract | Publisher Full Text\n\nCallaghan BC, Cheng HT, Stables CL, et al.: Diabetic neuropathy: clinical manifestations and current treatments. Lancet Neurol. 2012; 11(6): 521–34. PubMed Abstract | Publisher Full Text | Free Full Text\n\nArgoff CE, Cole BE, Fishbain DA, et al.: Diabetic peripheral neuropathic pain: clinical and quality-of-life issues. Mayo Clin Proc. 2006; 81(4 Suppl): S3–11. PubMed Abstract | Publisher Full Text\n\nSadosky A, Mardekian J, Parsons B, et al.: Healthcare utilization and costs in diabetes relative to the clinical spectrum of painful diabetic peripheral neuropathy. J Diabetes Complications. 2015; 29(2): 212–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAmerican Diabetes Association: Economic costs of diabetes in the U.S. in 2012. Diabetes Care. 2013; 36(4): 1033–46. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nGordois A, Scuffham P, Shearer A, et al.: The health care costs of diabetic peripheral neuropathy in the US. Diabetes Care. 2003; 26(6): 1790–5. PubMed Abstract | Publisher Full Text\n\nBansal V, Kalita J, Misra UK: Diabetic neuropathy. Postgrad Med J. 2006; 82(964): 95–100. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTracy JA, Dyck PJ: The spectrum of diabetic neuropathies. Phys Med Rehabil Clin N Am. 2008; 19(1): 1–26, v. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGibbons CH, Freeman R: Treatment-induced diabetic neuropathy: a reversible painful autonomic neuropathy. Ann Neurol. 2010; 67(4): 534–41. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nEllenberg M: Diabetic neuropathic cachexia. Diabetes. 1974; 23(5): 418–23. PubMed Abstract | Publisher Full Text\n\nTran C, Philippe J, Ochsner F, et al.: Acute painful diabetic neuropathy: an uncommon, remittent type of acute distal small fibre neuropathy. Swiss Med Wkly. 2015; 145: w14131. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTesfaye S, Malik R, Harris N, et al.: Arterio-venous shunting and proliferating new vessels in acute painful neuropathy of rapid glycaemic control (insulin neuritis). Diabetologia. 1996; 39(3): 329–35. PubMed Abstract | Publisher Full Text\n\nBril V, Tomioka S, Buchanan RA, et al.: Reliability and validity of the modified Toronto Clinical Neuropathy Score in diabetic sensorimotor polyneuropathy. Diabet Med. 2009; 26(3): 240–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRosenberg NR, Portegies P, de Visser M, et al.: Diagnostic investigation of patients with chronic polyneuropathy: evaluation of a clinical guideline. J Neurol Neurosurg Psychiatry. 2001; 71(2): 205–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDyck PJ, Overland CJ, Low PA, et al.: Signs and symptoms versus nerve conduction studies to diagnose diabetic sensorimotor polyneuropathy: Cl vs. NPhys trial. Muscle Nerve. 2010; 42(2): 157–64. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSmith AG, Singleton JR: The diagnostic yield of a standardized approach to idiopathic sensory-predominant neuropathy. Arch Intern Med. 2004; 164(9): 1021–5. PubMed Abstract | Publisher Full Text\n\nShtein RM, Callaghan BC: Corneal confocal microscopy as a measure of diabetic neuropathy. Diabetes. 2013; 62(1): 25–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nEngland JD, Gronseth GS, Franklin G, et al.: Practice Parameter: evaluation of distal symmetric polyneuropathy: role of laboratory and genetic testing (an evidence-based review). Report of the American Academy of Neurology, American Association of Neuromuscular and Electrodiagnostic Medicine, and American Academy of Physical Medicine and Rehabilitation. Neurology. 2009; 72(2): 185–92. PubMed Abstract | Publisher Full Text\n\nEngland JD, Gronseth GS, Franklin G, et al.: Practice parameter: the evaluation of distal symmetric polyneuropathy: the role of autonomic testing, nerve biopsy, and skin biopsy (an evidence-based review). Report of the American Academy of Neurology, the American Association of Neuromuscular and Electrodiagnostic Medicine, and the American Academy of Physical Medicine and Rehabilitation. PM R. 2009; 1(1): 14–22. PubMed Abstract | Publisher Full Text\n\nBeulens JW, Hart HE, Kuijs R, et al.: Influence of duration and dose of metformin on cobalamin deficiency in type 2 diabetes patients using metformin. Acta Diabetol. 2015; 52(1): 47–53. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZilliox L, Russell JW: Treatment of diabetic sensory polyneuropathy. Curr Treat Options Neurol. 2011; 13(2): 143–59. PubMed Abstract | Publisher Full Text | Free Full Text\n\nThe effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993; 329(14): 977–86. PubMed Abstract | Publisher Full Text\n\nLinn T, Ortac K, Laube H, et al.: Intensive therapy in adult insulin-dependent diabetes mellitus is associated with improved insulin sensitivity and reserve: a randomized, controlled, prospective study over 5 years in newly diagnosed patients. Metabolism. 1996; 45(12): 1508–13. PubMed Abstract | Publisher Full Text\n\nDuckworth W, Abraira C, Moritz T, et al.: Glucose control and vascular complications in veterans with type 2 diabetes. N Engl J Med. 2009; 360(2): 129–39. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nIsmail-Beigi F, Craven T, Banerji MA, et al.: Effect of intensive treatment of hyperglycaemia on microvascular outcomes in type 2 diabetes: an analysis of the ACCORD randomised trial. Lancet. 2010; 376(9739): 419–30. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCallaghan BC: The Impact of the Metabolic Syndrome on Neuropathy. Reference Source\n\nTesfaye S, Stevens LK, Stephenson JM, et al.: Prevalence of diabetic peripheral neuropathy and its relation to glycaemic control and potential risk factors: the EURODIAB IDDM Complications Study. Diabetologia. 1996; 39(11): 1377–84. PubMed Abstract | Publisher Full Text\n\nTesfaye S, Chaturvedi N, Eaton SE, et al.: Vascular risk factors and diabetic neuropathy. N Engl J Med. 2005; 352(4): 341–50. PubMed Abstract | Publisher Full Text\n\nCallaghan B, Feldman E: The metabolic syndrome and neuropathy: therapeutic challenges and opportunities. Ann Neurol. 2013; 74(3): 397–403. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCameron NE, Eaton SE, Cotter MA, et al.: Vascular factors and metabolic interactions in the pathogenesis of diabetic neuropathy. Diabetologia. 2001; 44(11): 1973–88. PubMed Abstract | Publisher Full Text\n\nMalik RA, Tesfaye S, Thompson SD, et al.: Endoneurial localisation of microvascular damage in human diabetic neuropathy. Diabetologia. 1993; 36(5): 454–9. PubMed Abstract | Publisher Full Text\n\nCallaghan BC, Hur J, Feldman EL: Diabetic neuropathy: one disease or two? Curr Opin Neurol. 2012; 25(5): 536–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSmith AG, Russell J, Feldman EL, et al.: Lifestyle intervention for pre-diabetic neuropathy. Diabetes Care. 2006; 29(6): 1294–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBalducci S, Iacobellis G, Parisi L, et al.: Exercise training can modify the natural history of diabetic peripheral neuropathy. J Diabetes Complications. 2006; 20(4): 216–23. PubMed Abstract | Publisher Full Text\n\nSingleton JR, Marcus RL, Jackson JE, et al.: Exercise increases cutaneous nerve density in diabetic patients without neuropathy. Ann Clin Transl Neurol. 2014; 1(10): 844–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nStevens JA, Phelan EA: Development of STEADI: a fall prevention resource for health care providers. Health Promot Pract. 2013; 14(5): 706–14. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZiegler D, Low PA, Litchy WJ, et al.: Efficacy and safety of antioxidant treatment with α-lipoic acid over 4 years in diabetic polyneuropathy: the NATHAN 1 trial. Diabetes Care. 2011; 34(9): 2054–60. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOyenihi AB, Ayeleso AO, Mukwevho E, et al.: Antioxidant strategies in the management of diabetic neuropathy. Biomed Res Int. 2015; 2015: 515042. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nHotta N, Akanuma Y, Kawamori R, et al.: Long-term clinical effects of epalrestat, an aldose reductase inhibitor, on diabetic peripheral neuropathy: the 3-year, multicenter, comparative Aldose Reductase Inhibitor-Diabetes Complications Trial. Diabetes Care. 2006; 29(7): 1538–44. PubMed Abstract | Publisher Full Text\n\nBril V, Buchanan RA: Long-term effects of ranirestat (AS-3201) on peripheral nerve function in patients with diabetic sensorimotor polyneuropathy. Diabetes Care. 2006; 29(1): 68–72. PubMed Abstract | Publisher Full Text\n\nChalk C, Benstead TJ, Moore F: Aldose reductase inhibitors for the treatment of diabetic polyneuropathy. Cochrane Database Syst Rev. 2007; (4): CD004572. PubMed Abstract | Publisher Full Text\n\nFraser DA, Diep LM, Hovden IA, et al.: The effects of long-term oral benfotiamine supplementation on peripheral nerve function and inflammatory markers in patients with type 1 diabetes: a 24-month, double-blind, randomized, placebo-controlled trial. Diabetes Care. 2012; 35(5): 1095–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGriebeler ML, Morey-Vargas OL, Brito JP, et al.: Pharmacologic interventions for painful diabetic neuropathy: An umbrella systematic review and comparative effectiveness network meta-analysis. Ann Intern Med. 2014; 161(9): 639–49. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCallaghan BC, Feldman EL: Painful diabetic neuropathy: many similarly effective therapies with widely dissimilar costs. Ann Intern Med. 2014; 161(9): 674–5. PubMed Abstract | Publisher Full Text\n\nIyer S, Tanenberg RJ: Pharmacologic management of diabetic peripheral neuropathic pain. Expert Opin Pharmacother. 2013; 14(13): 1765–75. PubMed Abstract | Publisher Full Text\n\nCallaghan B, Kerber K, Langa KM, et al.: Longitudinal patient-oriented outcomes in neuropathy: Importance of early detection and falls. Neurology. 2015; 85(1): 71–9. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation"
}
|
[
{
"id": "13558",
"date": "25 Apr 2016",
"name": "James Russell",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13559",
"date": "25 Apr 2016",
"name": "Amanda Peltier",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13560",
"date": "25 Apr 2016",
"name": "John Kissel",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-738
|
https://f1000research.com/articles/5-291/v1
|
07 Mar 16
|
{
"type": "Data Note",
"title": "A compendium of monocyte transcriptome datasets to foster biomedical knowledge discovery",
"authors": [
"Darawan Rinchai",
"Sabri Boughorbel",
"Scott Presnell",
"Charlie Quinn",
"Damien Chaussabel",
"Sabri Boughorbel",
"Scott Presnell",
"Charlie Quinn",
"Damien Chaussabel"
],
"abstract": "Systems-scale profiling approaches have become widely used in translational research settings. The resulting accumulation of large-scale datasets in public repositories represents a critical opportunity to promote insight and foster knowledge discovery. However, resources that can serve as an interface between biomedical researchers and such vast and heterogeneous dataset collections are needed in order to fulfill this potential. Recently, we have developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). This tool can be used to overlay deep molecular phenotyping data with rich contextual information about analytes, samples and studies along with ancillary clinical or immunological profiling data. In this note, we describe a curated compendium of 93 public datasets generated in the context of human monocyte immunological studies, representing a total of 4,516 transcriptome profiles. Datasets were uploaded to an instance of GXB along with study description and sample annotations. Study samples were arranged in different groups. Ranked gene lists were generated based on relevant group comparisons. This resource is publicly available online at http://monocyte.gxbsidra.org/dm3/landing.gsp.",
"keywords": [
"Monocyte",
"Transcriptomics",
"Gene Expression Browser",
"Immunology",
"Bioinformatics"
],
"content": "Introduction\n\nPlatforms such as microarrays and, more recently, next generation sequencing have been leveraged to generate molecular profiles at the scale of entire systems. The global perspective gained using such approaches is potentially transformative. Transcriptome profiling enabled for instance the characterization of molecular perturbations that occur in the context of a wide range disease processes1–10. This in turn has provided opportunities for the discovery of biomarkers and for the development of novel therapeutic modalities3,11–13. More recently such systems-scale profiling of the blood transcriptome has also been used to monitor response to vaccines or therapeutic drugs14–19. The democratization of these approaches has led to proliferation of data in public repositories: over 1.7 million individual transcriptome profiles from more than 65,000 studies have been deposited to date in the NCBI Gene Expression Omnibus (GEO), a public repository of transcriptome profiles.\n\nTaken together this vast body of “collective data” holds the promise of accelerating the pace of biomedical discovery by creating countless opportunities for identifying and filling critical knowledge gaps. Building tools that provide biomedical researchers with the ability to seamlessly interact with collections of datasets along with rich contextual information is essential in promoting insight and enabling knowledge discovery. To address this need we have developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB).\n\nGXB was described in a recent publication and is available as open source software on GitHub20. This tool constitutes a simple interface for the browsing and interactive visualization of large volumes of heterogeneous data. Users can easily customize data plots by adding multiple layers of information, modifying the order of samples, and generating links that capture these settings which can be inserted in email communications or in publications. Accessing the tool via these links also provides access to rich contextual information that is essential for data interpretation. This includes access to gene information and relevant literature, study design information, detailed sample information as well as ancillary data20.\n\nIn recent years, a large number of transcriptional studies have been conducted aiming at the characterization and functional classification of monocytes in health and disease. Monocytes are a population of immune cells found in the blood, bone marrow, and spleen. They constitute ~10% of the total circulating blood leukocytes in humans. They can remain in the blood circulation for up to 1–2 days, after which time, if they have not been recruited to a tissue, they die and are removed. They are considered the systemic reservoir of myeloid precursors for renewal of tissue macrophages and dendritic cells. Monocytes play a key role during immune response as professional phagocytes21,22, and producers of immune mediators23,24. Indeed, reports show that monocytes are recruited at the site of infections as innate effectors of the inflammatory response to microbes, killing pathogens via phagocytosis, production of reactive oxygen intermediate (ROIs)25, reactive nitrogen intermediate (RNIs)26,27, myeloperoxidase (MPO)28,29, and producing inflammatory cytokines30 that contribute to further amplifying the antimicrobial response31.\n\nHuman monocytes are derived from hematopoietic stem cells in the bone marrow and are released into peripheral blood circulation upon maturation. They are divided into three major subsets based on the expression of cell surface markers CD14 and CD16. The most prevalent subset in the blood circulation, accounting for 90% of all monocytes, are the classical monocytes that express high levels of CD14 but low levels of CD16. The remaining 10% is divided into two subsets: intermediate monocyte with high expression of CD14 and CD16 (CD14+CD16+) and non-classical monocytes that express low levels of CD14 but high levels of CD16 (CD14dimCD16++ or CD14+CD16++)32–34.\n\nIn this data note we are making available via GXB a curated compendium of 93 public datasets relevant to human monocyte immunobiology, representing a total of 4,516 transcriptome profiles.\n\n\nMaterials and methods\n\nPotentially relevant datasets deposited in GEO were identified using an advanced query based on the Bioconductor package GEOmetadb and the SQLite database that captures detailed information on the GEO data structure; https://www.bioconductor.org/packages/release/bioc/html/GEOmetadb.html35. The search query was designed to retrieve entries where the title and description contained the word Monocyte OR Monocytes, were generated from human samples, using Illumina or Affymetrix commercial platforms. The query result is appended with rich metadata from GEOmetadb that allows for manual filtering of the retrieved collection.\n\nThe relevance of each entry returned by this query was assessed individually. This process involved reading through the descriptions and examining the list of available samples and their annotations. Sometimes it was also necessary to review the original published report in which the design of the study and generation of the dataset is described in more detail. The datasets cover a broad range of human immunology studies investigating monocyte immunobiology in the context of diseases and through comparison with diverse cell populations and study types as illustrated by a graphical representation of relative occurrences of terms in the list of diseases loaded into our tool (Figure 1). A wide range of cell types and diseases are represented. Ultimately, the collection was comprised of 93 curated datasets. It includes datasets generated from studies profiling primary human CD14+ cells isolated from patients with autoimmune diseases (7), bacterial, virus and parasite infections (7), cancer (4), cardiovascular diseases (4), kidney diseases (4), as well as monocytes isolated from healthy subjects (58) (Figure 2). The 58 datasets in which monocytes were isolated from healthy subjects were classified based on whether profiling was conducted ex vivo or following in vitro experiments. In total 38 datasets were identified in which primary human CD14+ cells were stimulated or infected in in vitro experiments (Figure 2). Among the many noteworthy datasets, there are 8 datasets investigating differences between monocytes subsets; classical (CD14++CD16-), intermediate (CD14+CD16+) and non-classical monocytes (CD14-CD16++)32–34 [GXB: GSE16836, GSE18565, GSE25913, GSE34515, GSE35457, GSE51997, GSE60601, GSE66936]. Another dataset from Banchereau and colleagues investigated responses of monocyte and dendritic cells to 13 different vaccines in vitro36 [GXB: GSE44721]. The datasets that comprise our collection are listed in Table 1 and can be browsed interactively in GXB.\n\nWord frequencies extracted from text descriptions of the studies loaded into the GXB tool are depicted as a word cloud. The size of the words is proportional to their frequency.\n\nThe pie chart on the left panel indicates dataset frequencies by disease status. The chart on the right panel indicates the type of studies carried out for the 58 datasets consisting of monocyte obtained exclusively from healthy donors.\n\nOnce a final selection had been made each dataset was downloaded from GEO in the SOFT file format. It was in turn uploaded on an instance of the Gene Expression Browser (GXB) hosted on the Amazon Web Services cloud. Available sample and study information were also uploaded. Samples were grouped according to possible interpretations of study results and ranking based on the different group comparisons that were computed (e.g. comparing monocyte isolated from case vs controls in studies where profiling was performed ex-vivo; or stimulated vs medium control in in vitro experiments).\n\nThe GXB software has been described in detail in a recent publication20. This custom software interface provides users with a means to easily navigate and filter the dataset collection available at http://monocyte.gxbsidra.org/dm3/landing.gsp. A web tutorial is also available online: http://monocyte.gxbsidra.org/dm3/tutorials.gsp#gxbtut. Briefly, datasets of interest can be quickly identified either by filtering using criteria from pre-defined lists on the left or by entering a query term in the search box at the top of the dataset navigation page. Clicking on one of the studies listed in the dataset navigation page opens a viewer designed to provide interactive browsing and graphic representations of large-scale data in an interpretable format. This interface is designed to present ranked gene lists and display expression results graphically in a context-rich environment. Selecting a gene from the rank ordered list on the left of the data-viewing interface will display its expression values graphically in the screen’s central panel. Directly above the graphical display drop down menus give users the ability: a) To change how the gene list is ranked; this allows the user to change the method used to rank the genes, or to include only genes that are selected for specific biological interest; b) To change sample grouping (Group Set button), in some datasets a user can switch between groups based on cell type to groups based on disease type, for example; c) To sort individual samples within a group based on associated categorical or continuous variables (e.g. gender or age); d) To toggle between the bar chart view and a box plot view, with expression values represented as a single point for each sample. Samples are split into the same groups whether displayed as a bar chart or box plot; e) To provide a color legend for the sample groups; f) To select categorical information that is to be overlaid at the bottom of the graph. For example, the user can display gender or smoking status in this manner; g) To provide a color legend for the categorical information overlaid at the bottom of the graph; and h) To download the graph as a png image or csv file for performing a separate analysis. Measurements have no intrinsic utility in absence of contextual information. It is this contextual information that makes the results of a study or experiment interpretable. It is therefore important to capture, integrate and display information that will give users the ability to interpret data and gain new insights from it. We have organized this information under different tabs directly above the graphical display. The tabs can be hidden to make more room for displaying the data plots, or revealed by clicking on the blue “show info panel” button on the top right corner of the display. Information about the gene selected from the list on the left side of the display is available under the “Gene” tab. Information about the study is available under the “Study” tab. Information available about individual samples is provided under the “Sample” tab. Rolling the mouse cursor over a bar chart's element while displaying the “Sample” tab lists any clinical, demographic, or laboratory information available for the selected sample. Finally, the “Downloads” tab allows advanced users to retrieve the original dataset for analysis outside this tool. It also provides all available sample annotation data for use alongside the expression data in third party analysis software. Other functionalities are provided under the “Tools” drop-down menu located in the top right corner of the user interface. Some of the notable functionalities available through this menu include: a) Annotations, which provides access to all the ancillary information about the study, samples and dataset organized across different tabs; b) Cross-project view, which provides the ability for a given gene to browse through all available studies; c) Copy link, which generates a mini-URL encapsulating information about the display settings in use and that can be saved and shared with others (clicking on the envelope icon on the toolbar inserts the url in an email message via the local email client); and d) Chart options, which gives user the option to customize chart labels.\n\nQuality control checks were performed with the examination of profiles of relevant biological indicators. Known leukocyte markers were used, such as CD14, which is expressed by monocytes and macrophages; as well as markers that would indicate significant contamination of the sample by other leukocyte populations: such as CD3, a T-cells marker; CD19, a B-cell marker; CD56, an NK cell marker (Figure 3; The expression of the CD14 marker across all studies can be checked using the cross project functionality of GXB: http://monocyte.gxbsidra.org/dm3/geneBrowser/crossProject?probeID=201743_at&geneSymbol=CD14&geneID=929). In addition, expression of the XIST transcripts, in which expression is gender-specific, was also examined to determine its concordance with demographic information provided with the GEO submission.\n\nThe expression of this gene is indicative of the purity of primary human monocyte preparation; this marker is expected to be high in monocyte preparations and low in other leukocyte populations. In this view of the GXB expression of CD14 can be visualized across projects listed on the left.\n\n\nData availability\n\nAll datasets included in our curated collection are also available publically via the NCBI GEO website: http://www.ncbi.nlm.nih.gov/geo/; and are referenced throughout the manuscript by their GEO accession numbers (e.g. GSE25913). Signal files and sample description files can also be downloaded from the GXB tool under the “downloads” tab.",
"appendix": "Author contributions\n\n\n\nDR: curated, uploaded and annotated datasets, and drafted the manuscript. SB: installed the software, uploaded datasets, programmed portions of the web application, and tested the software, and assisted in drafting the manuscript. SP: participated in the design of the software, programmed portions of the original web application, installed the software, and tested the software, and assisted in drafting the manuscript. CQ: participated in designed and programmed portions of the original web application, tested the software, and assisted in drafting the manuscript. DC: participated in software design, tested the software, and drafted the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nDR, SB and DC received support from the Qatar Foundation.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgement\n\nThe authors would like to acknowledge all the investigators who decided to make their datasets publically available by sharing them in GEO.\n\n\nReferences\n\nBennett L, Palucka AK, Arce E, et al.: Interferon and granulopoiesis signatures in systemic lupus erythematosus blood. J Exp Med. 2003; 197(6): 711–23. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGriffiths MJ, Shafi MJ, Popper SJ, et al.: Genomewide analysis of the host response to malaria in Kenyan children. J Infect Dis. 2005; 191(10): 1599–611. 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}
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[
{
"id": "12768",
"date": "16 Mar 2016",
"name": "Marc Pellegrini",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this short descriptive report the authors put their published Gene Expression Browser tool to work in arranging several thousand transcriptome profiles obtained from public datasets that looked at monocyte immunology. They were able to compare groups of monocytes based on phenotypic attributes and rank gene expression. The authors provide a nice summary of the technique and validation.",
"responses": []
},
{
"id": "12769",
"date": "21 Mar 2016",
"name": "Ping Chen",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nGeneral Comments Modern genomics, especially with the emergence of high-throughput next-generation sequencing, is generating data at such a rapid rate that new tools for organizing, visualizing, sharing, and integrating heterogeneous data in the context of scientific information are needed for scientists to efficiently use these published data. The Chaussabel group has recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB), to address this problem. In this data note, Dr. Rinchai et al. report a compendium of ninety-six curated human monocyte transcriptome datasets from GEO spanning a broad range of diseases, cell types, and experiments. These datasets were then uploaded to the Gene Expression Browser for exploratory data analysis and dataset validation. The Gene Expression Browser should prove very useful for investigating large datasets; however, I have several questions and comments regarding the curated data itself: Title: The novel aspect and apparent emphasis of this data note is using the Gene Expression Browser to more easily explore the curated ninety-six datasets. But the current title emphasizes the key information on fostering the knowledge discovery. Please consider rephrasing it by focusing on the monocyte datasets and web application. Introduction: As the Gene Expression Browser has been described in detail previously, the emphasis of this data note should be on the curated data. It would be helpful to discuss the motivation for creating this particular compendium of monocyte transcriptome datasets as well as the intended use of the curated data given the breadth and heterogeneity of diseases, cell types, and experiments that it includes. Methods:1. Please elaborate more specifically on how the datasets were curated. What were the eligibility criteria for inclusion into the compendium? 2. The table summarizing the published data can difficult to read due to its landscape orientation. Consider rotating the table from a landscape orientation to a portrait orientation. 3. In the right pie chart of Figure 2, there are twelve datasets studying primary monocytes; however, datasets classified as in vitro stimulation, infection, and monocyte subsets may also contain primary monocytes. Better categorization is needed. 4. Data validation is critical for verifying that a dataset is acceptable for use. The authors mention performing dataset validation but do not report the related results or summary of their validation. On page 9, the process of assessing contamination by other leukocyte populations using surface markers should be done carefully as CD14+ monocytes do share surface marker CD4. 5. In Fig. 3, it is unclear whether the orange bar plot is referring to CD4+ T cells or CD4+ cells in general. They are different cell types.",
"responses": [
{
"c_id": "1892",
"date": "25 Apr 2016",
"name": "Darawan Rinchai",
"role": "Author Response",
"response": "We thank the reviewers for their valuable feedback and suggestions to improve our manuscript.Title: Following the suggestion of the reviewers we changed the title of the manuscript to “A curated compendium of of transcriptome datasets of relevance to human monocyte immunobiology research”.Introduction: Thanks for raising this point. We added a long paragraph and new references in the introduction to emphasize the role of monocyte across different diseases and the motivation for creating this compendium of monocyte transcriptome datasets. Methods:1. We have added information about how datasest were selected for inclusion in the collections in the methods section under the title “Identification of monocyte datasets”…“Using the search query, the results also returned a number of datasets that did not include profiles of monocytes but instead of “monocyte-derived dendritic cells” or “monocyte-derived macrophages”. During our manual screen these were excluded as were studies employing monocytic cell lines. Only studies including primary human monocyte profiles were retained.”…2. We agree with the reviewer that presenting the table using landscape orientation makes it difficult to read. We therefore changed table format from landscape to portrait orientation. 3. Thank you for pointing this out. We changed the label on this figure to read “ex-vivo, no treatment”. These include studies where monocytes were isolated from healthy subjects for comparison with other cell types, or evaluation of variation among healthy individuals.4. Assessing contamination can indeed be difficult, especially using this type of data where cell-level information is lacking. We plan to explore with our bioinformatics collaborators the development of a \"scoring\" approach to better quantify potential contamination but this is not a simple matter to address. At this point we have simply verified for each dataset that expression of markers was consistent with grouping labels provided by depositors. We have added language in the manuscript to clarify this point. 5. Thank you for pointing out this typo on this label. This dataset focuses on genomic profile of human blood both CD4+ and CD8+ T cells, B cells, NK cells monocytes and neutrophil. Figure 3 was corrected accordingly as shown in the new Figure 3."
}
]
}
] | 1
|
https://f1000research.com/articles/5-291
|
https://f1000research.com/articles/5-728/v1
|
22 Apr 16
|
{
"type": "Review",
"title": "Beta cell antigens in type 1 diabetes: triggers in pathogenesis and therapeutic targets",
"authors": [
"François-Xavier Mauvais",
"Julien Diana",
"Peter van Endert",
"François-Xavier Mauvais",
"Julien Diana"
],
"abstract": "Research focusing on type 1 diabetes (T1D) autoantigens aims to explore our understanding of these beta cell proteins in order to design assays for monitoring the pathogenic autoimmune response, as well as safe and efficient therapies preventing or stopping it. In this review, we will discuss progress made in the last 5 years with respect to mechanistic understanding, diagnostic monitoring, and therapeutic modulation of the autoantigen-specific cellular immune response in T1D. Some technical progress in monitoring tools has been made; however, the potential of recent technologies for highly multiplexed exploration of human cellular immune responses remains to be exploited in T1D research, as it may be the key to the identification of surrogate markers of disease progression that are still wanting. Detailed analysis of autoantigen recognition by T cells suggests an important role of non-conventional antigen presentation and processing in beta cell-directed autoimmunity, but the impact of this in human T1D has been little explored. Finally, therapeutic administration of autoantigens to T1D patients has produced disappointing results. The application of novel modes of autoantigen administration, careful translation of mechanistic understanding obtained in preclinical studies and in vitro with human cells, and combination therapies including CD3 antibodies may help to make autoantigen-based immunotherapy for T1D a success story in the future.",
"keywords": [
"Type 1 Diabetes",
"Beta Cell Antigen",
"insulin recognition",
"Antigen-based immunotherapy",
"autoreactive T cells"
],
"content": "Introduction and context\n\nThe key role in type 1 diabetes (T1D) of T lymphocytes recognizing self-antigens expressed by insulin-producing beta cells in pancreatic islets is amply documented and beyond reasonable doubt. As discussed in detail in many excellent reviews (see, for example, 1–4), a large number of such autoantigens, generally also recognized by autoantibodies, have been identified and are targeted by CD8+ and CD4+ T cells that may contribute to beta cell destruction but can also have a regulatory, protective role. (Pre-)proinsulin ([P]PI), glutamic acid decarboxylase (GAD), the tyrosine phosphatase IA-2, and the zinc transporter ZnT8 play a particularly prominent role and are recognized by autoantibodies detected in routine clinical laboratory assays (see 5,6 for a discussion of the role of B lymphocytes and autoantibodies in T1D). Given that autoantigens provide specificity to the autoimmune pathology in T1D, major efforts in the scientific field have been devoted, on the one hand, to developing assays for monitoring pathogenic T cell responses against them and, on the other hand, to designing therapeutic strategies specifically silencing such responses.\n\nThis short review will take a look at the progress towards the development of diagnostic and therapeutic approaches focusing on T cell autoantigens in the last 5 years. Reviewing the pertinent literature, we will propose three general conclusions. With regard to diagnostic tools, we believe that the number of beta cell proteins and major histocompatibility complex (MHC)-restricted epitopes thereof, as well as the performance of tetramers for the detection of cognate T cells, now provides an increasingly promising basis for monitoring autoreactive T cells. However, as recently argued by Odegard et al., assays for antigen-specific cells are still not robust enough for routine use in clinical trials, particularly multicenter trials7. In this context, we will argue that, first, the information obtained in current analyses of such cells is insufficient so that the methods are in need of complementation and, second, that T cell analysis in human T1D should not be limited to self-reactive cells. Concerning autoantigen-based immunotherapy, we agree with Greenbaum and colleagues8 and believe that the general failure of published recent trials calls for more research in preclinical models and in vitro with human cells, which should precede small proof-of-concept trials. This being said, occasional discordance between results in the nonobese diabetic (NOD) model and human T1D (e.g. concerning the effect of interleukin [IL]-2 in combination with rapamycin9), and poor reproducibility of some other results in the NOD model10, calls for caution when translating preclinical results to human T1D. Finally, we will argue that important gaps in our understanding of processing, presentation, and T cell recognition of beta cell antigens may have to be addressed to design efficient autoantigen-based immunotherapies.\n\n\nT cell epitopes and tetramers\n\nNext to the simple and efficient enzyme-linked immunosorbent spot (ELISpot) assays, tetramers have become standard and increasingly sophisticated tools for detecting both CD8+ and CD4+ autoreactive T cells. Production of these reagents requires identification of MHC-restricted epitopes, the number of which is still increasing. Thus, using mass spectrometric analysis of human leukocyte antigen (HLA) class I eluates11, or prediction algorithm-assisted analysis of PI degradation products produced by the proteasome12, new epitopes presented by four HLA class I alleles, including the disease-associated A*24 and recognized preferentially by patient CD8+ T cells, could be identified. Using the technology of combinatorial labeling of identical tetramers with different sets of multiple fluorochromes, Roep and colleagues developed a tetramer “kit” able to detect T cells specific for multiple dominant autoreactive epitopes simultaneously13. Such kits will be useful where small blood volumes must be analyzed, especially when studying pediatric samples, although even with recent approaches it will be difficult to obtain satisfactory results with blood volumes of significantly less than 20 mL, which realistically can be obtained in trials involving young children. Interestingly, investigators led by von Herrath succeeded in using HLA class I tetramers to analyze pancreatic islets from T1D patients14. Somewhat astonishingly, on average no more than two to nine CD8+ T cells, the dominant lymphocyte type in islet infiltrates, were present per islet; tetramer staining revealed recognition of one or multiple antigens by these cells.\n\nTetramers have also provided interesting insight into insulin B9–23-specific CD4+ T cell responses restricted by the strongly T1D-associated allele HLA-DQ8 (DQB1*03:02). T cells with this specificity were found in six out of 16 patients and recognized denatured but not native antigen. The authors speculate that the disulfide bridges in native insulin might inhibit processing by myeloid cells, perhaps suggesting special processing pathways overcoming this inhibition in pancreatic islets (see also below)15. DQ8-restricted CD4+ T cells recognizing PI (C peptide in this case) were also found in islet infiltrates of a T1D patient and among blood lymphocytes of several T1D patients16. Interestingly, in both studies, autoreactive DQ8-restricted T cells were exclusively found in patients, an unusual feature given that autoimmunity generally leads to amplification and activation but not de novo appearance of autoreactive cells, which are also present in healthy individuals. As recently reviewed by Ehlers and Rigby17, it is well documented that self-reactive T cells tend to have a naïve phenotype in healthy individuals but a memory phenotype in subjects with T1D.\n\nZnT8 has also joined the ranks of CD4+ T cell-recognized autoantigens in human T1D. T1D patients responded to a larger number of ZnT8 epitopes with greater proliferative responses18; moreover, ZnT8-specific CD4+ T cells were skewed towards T helper 1 (Th1) cells in T1D patients, while Th2 and IL-10-producing cells were prevalent in healthy adults19. We have found that ZnT8 is a major autoantigen for CD8+ T cells in pediatric diabetes20; as transfer of ZnT8-specific human CD8+ T cells can induce diabetes in HLA-humanized mice, such cells may play an important role in the human pathology21.\n\nBecause tetramer detection of human CD4+ T cells recognizing islet cell antigens generally requires their prior expansion, methods for quantitative assessment of such cells in untouched lymphocytes could be of substantial interest. Eugster and colleagues analyzed sequences of 1650 T cell receptors (TCRs), obtained from six patients, recognizing the dominant DR4-restricted epitope GAD 557I and then used next-generation sequencing to determine the frequency of individual TCR sequences among patient CD4+ cells, which was found to rank from <0.00001 to 1.6%22. Disappointingly, there were almost as many different TCR sequences as T cell clones, suggesting that specific TCR-targeted therapies have little chance of success.\n\n\nNovel insights on frequency and expression signatures of self-reactive T cells\n\nWhile the vast majority of research efforts concerning autoreactive T cells has focused on detecting and enumerating such cells, possibly combined with limited functional analyses, recent studies suggest that exploration of adaptive autoimmunity should go beyond this step and aim to perform in-depth characterization of phenotypic and functional properties. One critical finding is the abundance of the self-reactive T cell repertoire in healthy individuals and the surprisingly limited purging of it during thymic education. Yu and colleagues found that T cells recognizing male antigens were only threefold more abundant in females than in males, with full cytotoxic potential and equivalent tetramer staining intensity for cells from male and female donors. Moreover, the frequency range of self-reactive cells was similar to that of cells recognizing foreign antigens23. As an example, the frequency of T cells recognizing a dominant insulin epitope (B10–18) was 1 in 104, with only a 2.66-fold increase in T1D patients. Similar findings were reported by Maeda et al. for T cells recognizing Melan-A24. However, in both studies, self-reactive CD8+ T cells were anergic when challenged with antigen, reflected in distinct gene expression profiles including low Bcl-2 expression and up-regulation of CTLA-4. Interestingly, anergic self-reactive CD8+ T cells may not only indicate the absence of auto-aggressive responses in healthy individuals but also play a beneficial role in patients with ongoing autoimmunity, since such cells increase in frequency upon treatment with CD3 antibodies25.\n\nAnother study suggested that not only is looking at gene expression profiles of self-reactive cells more informative than counting cells but also screening for self-reactivity can sometimes be omitted when searching for gene expression profiles with prognostic value in organ-specific autoimmune diseases. McKinney and associates compared gene expression by single CD8+ T cells from patients with chronic infections and patients with autoimmune diseases and found a profile indicative of T cell exhaustion with good clinical outcome in the latter but poor outcome and response to therapy in the former setting26. A single surrogate marker, the anti-apoptotic transcription factor KAT2B, correlated with progression to disease in children at risk of T1D and with triggering of autoimmunity in the NOD model. Thus, one might say that one of the most interesting surrogate markers of progression to T1D described so far was identified while ignoring the antigenic specificity of the CD8+ T cells examined. Why a surprisingly large number of peripheral blood T cells would express a signature indicating progressive disease is unclear; however, this may be related to systemic immune and metabolic alterations in pre-diabetic children, such as a type 1 interferon (IFN) transcription signature27 and altered lipid and amino acid metabolism28. Whatever the reason for the findings of McKinney et al., they indicate that the search for surrogate markers of disease progression or immunotherapeutic effects in T1D should not be limited to self-reactive T cells or, to be more precise, should not be limited to cells detectable with tetramers. This is not only because systemic effects of a type 1 IFN signature and of metabolic perturbation might produce surrogate markers in non-autoreactive cells but also because many autoreactive cells are likely to escape detection due to the frequently low affinity of self-reactive T cells. This was impressively demonstrated by Sabatino and colleagues, who used a novel method (micropipette adhesion frequency assay) to show that low-affinity, tetramer-undetectable but fully functionally competent T cells outnumbered tetramer-detectable cells in both an anti-viral and an autoimmune response29. In conclusion, recent technological advances, in particular single cell technology, have opened up new avenues for the identification of surrogate markers of T1D risk, rate of progression, and response to immunotherapy. These technologies should now be applied to the analysis of different immune cell populations from T1D patients including, but not limited to, self-reactive T lymphocytes.\n\n\nAre self-reactive T cell responses unique?\n\nResults obtained in the last 5 years have provided more evidence for some unique features preferentially found in self-reactive T cell responses. One of them is the unusual interaction among TCR, peptide, and MHC molecule resulting in weak avidity. Lamont and colleagues identified a self-peptide (an epitope in the insulin A chain) lacking the C-terminal anchor residue and thus extending the list of self-epitopes filling MHC peptide-binding sites only partially, a feature thought to facilitate escape from thymic negative selection30. Bulek and colleagues found another mechanism resulting in “ultra-weak” TCR-pMHC interaction (studying presentation of PPI15-24 by HLA-A2), in which an extremely peptide-centric TCR-pMHC interaction limited TCR-MHC interactions to a “light touch” unlikely to be sufficient for negative selection31. Post-translational epitope modification in the periphery (in this case by transglutaminase) is another mechanism allowing epitopes to escape negative selection and has recently been suggested to be implicated in the autoantigenicity of a chromogranin A epitope (one of the epitopes filling the peptide binding site partially) recognized by the popular BDC2.5 CD4+ T cells32. Similarly, citrullination of the GRP78 protein specifically in the NOD beta cells induces the translocation of this chaperone from the endoplasmic reticulum to the plasma membrane and generates a novel autoantigen recognized by effector T cells33.\n\nAn additional mechanism contributing to escape from thymic deletion is the phenomenon of type B CD4+ T cells. This type of T cell, identified first and studied in depth by Unanue’s group, recognizes cognate peptides exogenously added to antigen-presenting cells (APCs), but not peptides produced within APCs from native antigen (at least when peptide loading occurs in standard H-2M-equipped intracellular compartments)34. In the NOD model, Mohan and colleagues found that the majority of islet-infiltrating CD4+ T cells recognizing insulin B9–23 were of type B. Having previously shown that type B clones transferred diabetes, the group demonstrated that a mouse expressing the transgenic type B TCR 8F10 on a RAG knockout background developed T1D with faster kinetics than an analogous mouse expressing a standard type A TCR (recognizing both exogenous and APC-processed peptide)35. Interestingly, diabetes was also triggered by 8F10 cells in mice lacking pancreatic lymph nodes, suggesting that stimulation of type B T cells can occur directly in islets, bypassing for unknown reasons the requirement for priming by APCs migrating to lymph nodes documented for other T cells recognizing islet antigens. Presumably, dendritic cells (DCs) reaching into islet vessels attract such cells36; whether direct expression of MHC class II by beta cells, recently confirmed to occur in the NOD model, plays a role in recruiting type B T cells, or any autoreactive CD4+ T cells, into islets remains to be determined37.\n\n\nInsulin recognition by CD4+ T cells\n\nInsulin is arguably the “number one” autoantigen in the NOD model of T1D, not only because of its expression restricted to beta cells, the association of its genetic polymorphism with disease risk, and the role of its recognition in initial triggering of the autoimmune response38 but also because the structural basis of its recognition by CD4+ T cells is well understood and provides more evidence for the key role of unusual TCR-pMHC interactions in T1D. The insulin B chain fragment 9–23 has long been known as the key self-epitope recognized by murine and human CD4+ T cells. Examining the interaction of this peptide with the murine MHC class II molecule I-Ag7, Stadinski and colleagues identified four possible “binding registers” of which number 1 and 2 were most efficient39. Surprisingly, four different T cell clones examined recognized register 3, the least efficient register due to a conflict between the p9 peptide residue and the p9 binding site pocket. The authors proposed that particularly poor autoantigen presentation underlies the predisposing effect of some MHC class II alleles in T1D and postulated that only the very high insulin concentrations in islets allow for the formation of MHC complexes with poor ligands, consistent with a model proposed by Unanue and colleagues40. Given that activation of many T cells recognizing register 3 can be ameliorated by removing a glutamic acid in p8 (residue B21), the authors speculated that an islet-specific processing (i.e. proteolytic) event might remove this residue, thus creating a “cryptic” epitope absent during thymic T cell selection41.\n\nA similar study by Unanue’s group agreed that I-Ag7 can bind B9–23 in multiple registers; however, the authors did not find any T cells recognizing register 342. Standard type A T cells recognized the efficient register 1, but type B cells dominating responses upon immunization with B9–23 reacted with register 2 presented poorly by I-Ag7.\n\nBecause I-Ag7–restricted CD4+ T cell responses to B10–23 trigger islet cell autoimmunity, studying specific responses in non-autoimmune mice expressing I-Ag7 might reveal insight into the regulatory mechanisms that protect against T1D. Pauken and colleagues found specific T cells both in NOD mice and in C57BL/6 mice expressing I-Ag743. Interestingly, in the pancreatic lymph nodes of young NOD mice, i.e. in early pre-diabetes, the majority of these cells were anergic or expressed Foxp3 and IFN-γ expression was limited to intra-islet cells. However, in non-autoimmune B6/I-Ag7 mice, B10–23 reactive cells remained naïve, suggesting that they did not encounter antigen. Therefore, islet insults or inflammation in the NOD mouse are likely to precede priming of key autoreactive CD4+ T cells.\n\nCollectively, the molecular and functional characterization of autoreactive T cells from patients and in the NOD model raises a number of intriguing questions. How common is “ultra-weak” TCR/pHLA interaction in human T1D, and what are the mechanisms underlying low-avidity interactions? Can the micropipette adhesion assay reveal an additional autoreactive repertoire in human T1D? Are type B CD4+ T cells as critical in humans as they are in the NOD model? Finally, are there specific processing/proteolytic events producing “cryptic” epitopes in pancreatic islets?\n\n\nAntigen-based immunotherapy trials in patients\n\nGiven encouraging results of prior preclinical or human pilot studies, hopes had been raised that antigen-based immunotherapy might provide a safe and efficient strategy to prevent or even cure human T1D. Unfortunately, the trials concluded in recent years have almost completely failed to provide any evidence of clinical efficacy. Treatment starting with nasally applied insulin at T1D onset of 52 adult patients not requiring exogenous insulin had no effect on C peptide levels or progression to dependence on exogenous insulin44, thereby repeating a previous failure of a trial of oral insulin. Immunization of 12 patients with newly diagnosed T1D with insulin B chain in incomplete Freund’s adjuvant induced robust insulin-specific adaptive responses, but a clinical effect was not noted45. Two independent and relatively large trials in which patients were injected within 3 months of disease onset with GAD and alum adjuvant also showed no effect on C peptide levels or insulin requirement46,47. However, as has been commented on by others48, the regimens used in the GAD trials differed in numerous parameters (dose, route of injection, timing relative to disease onset, and use of alum adjuvant) from those tested in preclinical experiments, making trial failure appear less surprising. The single glimpse of hope published derives from a trial in which a PI-encoding plasmid was injected for 12 weeks after disease onset49. One of the regimens resulted in a transient increase of C peptide levels by 15% (vs. -10% for placebo) at 15 weeks after start of treatment. The authors also noted a decrease in CD8+ T cells specific for one peptide/HLA combination, although it was not clear whether this decrease was related to the transient clinical response.\n\nGlobally, it is safe to say that antigen-based therapy is far from having met expectations and that new avenues must be explored to produce more encouraging results. Presently, immunomodulatory approaches, particularly CD3 antibodies, remain the “gold standard” with respect to efficacy50,51, although transient EBV reactivation by anti-CD3 dosing schemes with the best clinical efficacy has been a source of concern52. Only short-term treatment with CD3 antibodies has been able to suppress the rise in insulin requirement over a period of 48 months53. Others better placed than we are have made recommendations on how to make progress, which we wish to reiterate here8,48,54. The need for better biomarkers has been formulated repeatedly but remains as urgent as ever. More research on the natural history of T1D, including the issues formulated above, is required to design more efficient therapies. In vitro studies with human samples, and large-scale in-depth characterization of the autoimmune response as outlined above, should be performed. The focus should be on preventing T1D onset. Small pilot studies based on rigorous hypothesis testing in the preclinical model and including mechanistic outcome studies should be preferred to large studies as performed in the past. Novel therapeutic strategies developed in the NOD model may also point the way to more efficient antigen-based immune intervention.\n\n\nNovel strategies for antigen-based immune therapy of T1D\n\nThe last few years have seen a wealth of novel ideas on how to treat or prevent T1D, most of them developed and tested in the NOD model. One of these uses targeting of complete autoantigens to specific APC receptors to induce regulatory responses. Targeting of self or non-self proteins to the DC asialoglycoprotein receptor induces suppressive T regulatory type 1 (Tr1) cells secreting large amounts of IL-10 but little tumor necrosis factor-α, IFN-γ, and IL-2, which are all produced upon targeting of the same proteins to Dectin-1, DC-SIGN, or Lox155. Interestingly, the approach also works in cynomolgus macaques; however, its efficacy in a pre-existing autoimmune setting has not been tested. Another approach uses Lactococcus lactis engineered to secrete PI and IL-10; in combination with low-dose parenteral anti-CD3, oral administration of these bacteria to freshly diabetic mice can induce lasting remission of T1D, possibly due to the induction of PI-specific regulatory T cells found in the intestinal mucosa and in islets56.\n\nVarious other recent strategies use self-epitopes to attenuate the autoimmune response. Injection of 10-week-old mice with a lentivirus, driving exclusive expression of B9–23 in hepatocytes due to a microRNA sequence, induces peptide-specific CD8+ T cells and regulatory T cells and halts the progression of T1D; combining the virus with low-dose anti-CD3 may induce remission of T1D57. Administration of a super-agonist variant of B9–23 with strongly enhanced stimulatory capacity provides complete protection from T1D if this peptide is delivered in subimmunogenic doses via an osmotic pump, starting at a young age, or via a DEC205-targeted fusion antibody. The protective effect was reflected in an increase of Foxp3+ T cells and a decrease in IFN-γ and IL-17 production. However, the necessity of administration during very early pre-diabetes and of determining the precise subimmunogenic dose will complicate the practical application of this strategy58. Others have proposed using TCR-like antibodies blocking or deleting specific autoreactive T cell populations59,60, or to produce tetramers targeting presumably pathogenic T cells and eliminating them by inducing apoptosis or by directly killing them through tetramer conjugation with saponin61,62. Some of these approaches can reduce the number of the targeted T cells significantly in vivo and delay or reduce onset of T1D. Determining biomarker profiles of patients prior to antigen-based immunotherapy may be key for the success of such treatments.\n\nProbably the most exciting novel approach was reported during the drafting of this article by the group of Santamaria63. This group had previously demonstrated protection from spontaneous diabetes in the NOD model upon stimulation and expansion of autoantigen-experienced CD8+ T cells by nanoparticles coated with cognate MHC-class I/peptide complexes64. Applying this approach to stimulating CD4+ T cells by nanoparticles coated with MHC class II/peptide complexes, the group could now show that the novel strategy can not only prevent and revert T1D in the NOD model but also attenuate autoimmune inflammation in rodent models of collagen-induced autoimmune arthritis and in experimental autoimmune encephalomyelitis. Remarkably, the approach even works when T cells recognizing subdominant epitopes are targeted. Applied to patients, this would obviate the need for identifying dominant or triggering epitopes and T cell populations, thereby removing one of the major obstacles to epitope-based immunotherapy in the outbred human population. The strategy seems to work by converting Th1 memory cells to Tr1 cells producing IL-10 and transforming growth factor-β, which in turn induce the differentiation of cognate regulatory B lymphocytes producing IL-10. Expanded Tr1 and regulatory B lymphocytes then suppress autoimmunity in a synergistic manner, presumably both by direct effects on effector T cells and by suppressing the pro-inflammatory action of cognate APCs63. A limitation of the strategy is the need to maintain bi-weekly treatment, since about half of NOD mice relapse with disease upon interruption of treatment.\n\n\nConcluding remarks\n\nThe period reviewed in this article has witnessed significant progress in the mechanistic understanding of autoantigen recognition and the development of some novel tools for monitoring the cellular autoimmune response in T1D. However, much remains to be learned with respect to the phenotype and function of pathogenic and protective human T cells, and surrogate markers of disease progression and response to therapy are still urgently needed. Moreover, the initial events activating autoreactive T cells and subsequent factors, both genetic and environmental, resulting in expansion rather than silencing of such cells remain poorly understood. The very recent finding that islet-infiltrating CD4+ T cells both in the NOD model and in T1D patients can recognize covalently linked hybrids of PI peptides with other beta cell peptides highlights the need to better understand the peculiar antigen processing environment in the islet organ65. This important finding may also suggest that the antigens used in previous trials of antigen-specific immunotherapy may not have been optimal. We anticipate that the application of recent technologies to highly multiplexed analysis of gene and protein expression by single human cells will make an important contribution to identifying surrogate markers and advancing our mechanistic understanding of human T1D. Recent results also suggest that simple oral or parenteral administration of autoantigens may stand little chance in achieving remission of human T1D. Given that CD3 antibodies so far have produced the most promising results, combining antigen administration with anti-CD3 has become a preferred option for many in the field. The future will show whether novel approaches such as those cited above can obviate the need for broadly immunomodulatory components in combination therapies or enhance their therapeutic efficacy.\n\n\nAbbreviations\n\nAPC, antigen-presenting cell; DC, dendritic cell; ELISpot, enzyme-linked immunosorbent spot; GAD, glutamic acid decarboxylase; HLA, human leukocyte antigen; IFN, interferon; IL, interleukin; MHC, major histocompatibility complex; NOD, nonobese diabetic; (P)PI, (pre-)proinsulin; T1D, type 1 diabetes; TCR, T cell receptor; Tr1, T regulatory type 1.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nWork in the authors’ laboratory is supported by grants from Fondation pour la Recherche Médicale (DEQ20130326539) and Idex Sorbonne Paris Cité to PvE, by a grant from Aide aux Jeunes Diabétiques to FXM and PvE, and by grants from EFSD-Lilly and from the Juvenile Diabetes Research Foundation (47-2013-524 and 2-SRA-2015-73) to JD.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nStadinski B, Kappler J, Eisenbarth GS: Molecular targeting of islet autoantigens. Immunity. 2010; 32(4): 446–456. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBabad J, Geliebter A, DiLorenzo TP: T-cell autoantigens in the non-obese diabetic mouse model of autoimmune diabetes. Immunology. 2010; 131(4): 459–465. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nKronenberg D, Knight RR, Estorninho M, et al.: Circulating preproinsulin signal peptide-specific CD8 T cells restricted by the susceptibility molecule HLA-A24 are expanded at onset of type 1 diabetes and kill β-cells. Diabetes. 2012; 61(7): 1752–1759. PubMed Abstract | Publisher Full Text | Free Full Text\n\nUnger WW, Velthuis J, Abreu JR, et al.: Discovery of low-affinity preproinsulin epitopes and detection of autoreactive CD8 T-cells using combinatorial MHC multimers. J Autoimmun. 2011; 37(3): 151–159. PubMed Abstract | Publisher Full Text\n\nVelthuis JH, Unger WW, Abreu JR, et al.: Simultaneous detection of circulating autoreactive CD8+ T-cells specific for different islet cell-associated epitopes using combinatorial MHC multimers. Diabetes. 2010; 59(7): 1721–1730. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCoppieters KT, Dotta F, Amirian N, et al.: Demonstration of islet-autoreactive CD8 T cells in insulitic lesions from recent onset and long-term type 1 diabetes patients. J Exp Med. 2012; 209(1): 51–60. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nYang J, Chow IT, Sosinowski T, et al.: Autoreactive T cells specific for insulin B:11-23 recognize a low-affinity peptide register in human subjects with autoimmune diabetes. Proc Natl Acad Sci U S A. 2014; 111(41): 14840–14845. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nPathiraja V, Kuehlich JP, Campbell PD, et al.: Proinsulin-specific, HLA-DQ8, and HLA-DQ8-transdimer-restricted CD4+ T cells infiltrate islets in type 1 diabetes. Diabetes. 2015; 64(1): 172–182. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nEhlers MR, Rigby MR: Targeting memory T cells in type 1 diabetes. Curr Diab Rep. 2015; 15(11): 84. PubMed Abstract | Publisher Full Text\n\nDang M, Rockell J, Wagner R, et al.: Human type 1 diabetes is associated with T cell autoimmunity to zinc transporter 8. J Immunol. 2011; 186(10): 6056–6063. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChujo D, Foucat E, Nguyen TS, et al.: ZnT8-Specific CD4+ T cells display distinct cytokine expression profiles between type 1 diabetes patients and healthy adults. PLoS One. 2013; 8(2): e55595. PubMed Abstract | Publisher Full Text | Free Full Text\n\nÉnée É, Kratzer R, Arnoux JB, et al.: ZnT8 is a major CD8+ T cell-recognized autoantigen in pediatric type 1 diabetes. Diabetes. 2012; 61(7): 1779–1784. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLi S, Li H, Chen B, et al.: Identification of novel HLA-A 0201-restricted cytotoxic T lymphocyte epitopes from Zinc Transporter 8. Vaccine. 2013; 31(12): 1610–1615. PubMed Abstract | Publisher Full Text\n\nEugster A, Lindner A, Catani M, et al.: High diversity in the TCR repertoire of GAD65 autoantigen-specific human CD4+ T cells. J Immunol. 2015; 194(6): 2531–2538. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nYu W, Jiang N, Ebert PJ, et al.: Clonal Deletion Prunes but Does Not Eliminate Self-Specific αβ CD8+ T Lymphocytes. Immunity. 2015; 42(5): 929–941. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMaeda Y, Nishikawa H, Sugiyama D, et al.: Detection of self-reactive CD8⁺ T cells with an anergic phenotype in healthy individuals. Science. 2014; 346(6216): 1536–1540. PubMed Abstract | Publisher Full Text\n\nTooley JE, Vudattu N, Choi J, et al.: Changes in T-cell subsets identify responders to FcR-nonbinding anti-CD3 mAb (teplizumab) in patients with type 1 diabetes. Eur J Immunol. 2016; 46(1): 230–241. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMcKinney EF, Lee JC, Jayne DR, et al.: T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection. Nature. 2015; 523(7562): 612–616. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFerreira RC, Guo H, Coulson RM, et al.: A type I interferon transcriptional signature precedes autoimmunity in children genetically at risk for type 1 diabetes. Diabetes. 2014; 63(7): 2538–2550. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nOresic M, Simell S, Sysi-Aho M, et al.: Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes. J Exp Med. 2008; 205(13): 2975–2984. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSabatino JJ Jr, Huang J, Zhu C, et al.: High prevalence of low affinity peptide-MHC II tetramer-negative effectors during polyclonal CD4+ T cell responses. J Exp Med. 2011; 208(1): 81–90. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nLamont D, Mukherjee G, Kumar PR, et al.: Compensatory mechanisms allow undersized anchor-deficient class I MHC ligands to mediate pathogenic autoreactive T cell responses. J Immunol. 2014; 193(5): 2135–2146. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nBulek AM, Cole DK, Skowera A, et al.: Structural basis for the killing of human beta cells by CD8+ T cells in type 1 diabetes. Nat Immunol. 2012; 13(3): 283–289. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nDelong T, Baker RL, He J, et al.: Diabetogenic T-cell clones recognize an altered peptide of chromogranin A. Diabetes. 2012; 61(12): 3239–3246. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRondas D, Crèvecoeur I, D'Hertog W, et al.: Citrullinated glucose-regulated protein 78 is an autoantigen in type 1 diabetes. Diabetes. 2015; 64(2): 573–586. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMohan JF, Unanue ER: Unconventional recognition of peptides by T cells and the implications for autoimmunity. Nat Rev Immunol. 2012; 12(10): 721–728. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMohan JF, Calderon B, Anderson MS, et al.: Pathogenic CD4+ T cells recognizing an unstable peptide of insulin are directly recruited into islets bypassing local lymph nodes. J Exp Med. 2013; 210(11): 2403–2414. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCalderon B, Carrero JA, Miller MJ, et al.: Cellular and molecular events in the localization of diabetogenic T cells to islets of Langerhans. Proc Natl Acad Sci U S A. 2011; 108(4): 1561–1566. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nZhao Y, Scott NA, Quah HS, et al.: Mouse pancreatic beta cells express MHC class II and stimulate CD4+ T cells to proliferate. Eur J Immunol. 2015; 45(9): 2494–2503. PubMed Abstract | Publisher Full Text\n\nNakayama M, Abiru N, Moriyama H, et al.: Prime role for an insulin epitope in the development of type 1 diabetes in NOD mice. Nature. 2005; 435(7039): 220–223. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nStadinski BD, Zhang L, Crawford F, et al.: Diabetogenic T cells recognize insulin bound to IAg7 in an unexpected, weakly binding register. Proc Natl Acad Sci U S A. 2010; 107(24): 10978–10983. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSuri A, Levisetti MG, Unanue ER: Do the peptide-binding properties of diabetogenic class II molecules explain autoreactivity? Curr Opin Immunol. 2008; 20(1): 105–110. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCrawford F, Stadinski B, Jin N, et al.: Specificity and detection of insulin-reactive CD4+ T cells in type 1 diabetes in the nonobese diabetic (NOD) mouse. Proc Natl Acad Sci U S A. 2011; 108(40): 16729–16734. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMohan JF, Petzold SJ, Unanue ER: Register shifting of an insulin peptide-MHC complex allows diabetogenic T cells to escape thymic deletion. J Exp Med. 2011; 208(12): 2375–2383. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nPauken KE, Linehan JL, Spanier JA, et al.: Cutting edge: type 1 diabetes occurs despite robust anergy among endogenous insulin-specific CD4 T cells in NOD mice. J Immunol. 2013; 191(10): 4913–4917. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFourlanos S, Perry C, Gellert SA, et al.: Evidence that nasal insulin induces immune tolerance to insulin in adults with autoimmune diabetes. Diabetes. 2011; 60(4): 1237–1245. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nOrban T, Farkas K, Jalahej H, et al.: Autoantigen-specific regulatory T cells induced in patients with type 1 diabetes mellitus by insulin B-chain immunotherapy. J Autoimmun. 2010; 34(4): 408–415. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nLudvigsson J, Krisky D, Casas R, et al.: GAD65 antigen therapy in recently diagnosed type 1 diabetes mellitus. N Engl J Med. 2012; 366(5): 433–442. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nWherrett DK, Bundy B, Becker DJ, et al.: Antigen-based therapy with glutamic acid decarboxylase (GAD) vaccine in patients with recent-onset type 1 diabetes: a randomised double-blind trial. Lancet. 2011; 378(9788): 319–327. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nTooley JE, Waldron-Lynch F, Herold KC: New and future immunomodulatory therapy in type 1 diabetes. Trends Mol Med. 2012; 18(3): 173–181. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRoep BO, Solvason N, Gottlieb PA, et al.: Plasmid-encoded proinsulin preserves C-peptide while specifically reducing proinsulin-specific CD8⁺ T cells in type 1 diabetes. Sci Transl Med. 2013; 5(191): 191ra82. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nHagopian W, Ferry RJ Jr, Sherry N, et al.: Teplizumab preserves C-peptide in recent-onset type 1 diabetes: two-year results from the randomized, placebo-controlled Protégé trial. Diabetes. 2013; 62(11): 3901–3908. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nHerold KC, Gitelman SE, Ehlers MR, et al.: Teplizumab (anti-CD3 mAb) treatment preserves C-peptide responses in patients with new-onset type 1 diabetes in a randomized controlled trial: metabolic and immunologic features at baseline identify a subgroup of responders. Diabetes. 2013; 62(11): 3766–3774. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKeymeulen B, Candon S, Fafi-Kremer S, et al.: Transient Epstein-Barr virus reactivation in CD3 monoclonal antibody-treated patients. Blood. 2010; 115(6): 1145–1155. PubMed Abstract | Publisher Full Text\n\nKeymeulen B, Walter M, Mathieu C, et al.: Four-year metabolic outcome of a randomised controlled CD3-antibody trial in recent-onset type 1 diabetic patients depends on their age and baseline residual beta cell mass. Diabetologia. 2010; 53(4): 614–623. PubMed Abstract | Publisher Full Text\n\nMatthews JB, Staeva TP, Bernstein PL, et al.: Developing combination immunotherapies for type 1 diabetes: recommendations from the ITN-JDRF Type 1 Diabetes Combination Therapy Assessment Group. Clin Exp Immunol. 2010; 160(2): 176–184. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLi D, Romain G, Flamar AL, et al.: Targeting self- and foreign antigens to dendritic cells via DC-ASGPR generates IL-10-producing suppressive CD4+ T cells. J Exp Med. 2012; 209(1): 109–121. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nTakiishi T, Korf H, van Belle TL, et al.: Reversal of autoimmune diabetes by restoration of antigen-specific tolerance using genetically modified Lactococcus lactis in mice. J Clin Invest. 2012; 122(5): 1717–1725. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAkbarpour M, Goudy KS, Cantore A, et al.: Insulin B chain 9-23 gene transfer to hepatocytes protects from type 1 diabetes by inducing Ag-specific FoxP3+ Tregs. Sci Transl Med. 2015; 7(289): 289ra81. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nDaniel C, Weigmann B, Bronson R, et al.: Prevention of type 1 diabetes in mice by tolerogenic vaccination with a strong agonist insulin mimetope. J Exp Med. 2011; 208(7): 1501–1510. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nDahan R, Gebe JA, Preisinger A, et al.: Antigen-specific immunomodulation for type 1 diabetes by novel recombinant antibodies directed against diabetes-associates auto-reactive T cell epitope. J Autoimmun. 2013; 47: 83–93. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZhang L, Crawford F, Yu L, et al.: Monoclonal antibody blocking the recognition of an insulin peptide-MHC complex modulates type 1 diabetes. Proc Natl Acad Sci U S A. 2014; 111(7): 2656–2661. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSamanta D, Mukherjee G, Ramagopal UA, et al.: Structural and functional characterization of a single-chain peptide-MHC molecule that modulates both naive and activated CD8+ T cells. Proc Natl Acad Sci U S A. 2011; 108(33): 13682–13687. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nVincent BG, Young EF, Buntzman AS, et al.: Toxin-coupled MHC class I tetramers can specifically ablate autoreactive CD8+ T cells and delay diabetes in nonobese diabetic mice. J Immunol. 2010; 184(8): 4196–4204. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nClemente-Casares X, Blanco J, Ambalavanan P, et al.: Expanding antigen-specific regulatory networks to treat autoimmunity. Nature. 2016; 530(7591): 434–440. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTsai S, Shameli A, Yamanouchi J, et al.: Reversal of autoimmunity by boosting memory-like autoregulatory T cells. Immunity. 2010; 32(4): 568–580. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nDelong T, Wiles TA, Baker RL, et al.: Pathogenic CD4 T cells in type 1 diabetes recognize epitopes formed by peptide fusion. Science. 2016; 351(6274): 711–714. PubMed Abstract | Publisher Full Text | F1000 Recommendation"
}
|
[
{
"id": "13336",
"date": "22 Apr 2016",
"name": "Mario Ehlers",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13334",
"date": "22 Apr 2016",
"name": "Massimo Pietropaolo",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13335",
"date": "22 Apr 2016",
"name": "Kathryn M. Haskins",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-728
|
https://f1000research.com/articles/5-727/v1
|
22 Apr 16
|
{
"type": "Research Article",
"title": "Normative data for Lezak’s Tinkertoy test in healthy Italian adults",
"authors": [
"Franca Crippa",
"Luca Cesana",
"Roberta Daini",
"Luca Cesana",
"Roberta Daini"
],
"abstract": "The Tinkertoy test is a tool for the neuropsychological assessment of executive functions and a predictor of employability. Originally a children’s toy comprising pieces to assemble freely, the TinkerToy Test examines organizational abilities, planning, and response flexibility. It allows subjects to use their own initiative and does not force them to choose from a series of predetermined alternatives. Tinkertoy test normative values were collected from 256 neurologically healthy Italian subjects. Multivariable analysis showed sex and education to have significant confounding effects. Adjusted and inferential cut-off points were determined and converted into equivalent scores, applying a distribution-free technique.",
"keywords": [
"executive functions",
"brain lesions",
"neuropsychological assessment",
"confounding effects"
],
"content": "Introduction\n\nExecutive functions are the cognitive capacities that control lower-level functions and are essential to future-oriented thought and behaviour. They are affected by head injuries24 or arise because of a focal frontal lesion, either cortical5,24,25 or subcortical13. In particular, the term executive functions refers to cognitive, emotional and behavioural aspects of conduct involved in achieving a specific purpose. Executive functions include processes that are complex, mixed together and in constant interaction. They facilitate the optimum adaptation of the individual to the environment1,16,23,24. Lezak16 suggested the division of competencies into four specific components: volition, planning, goal-oriented behaviour and effective performance. Several psychometric instruments are available for evaluating executive functions during neuropsychological examinations. However, most of them are generally highly structured (the task and the stimuli set the goal and the processes required to achieve that goal)15,16. Moreover, none of the tools currently in use for evaluating the performance in the domain of executive functions is able to assess how the patients are able to formulate a goal and to plan how to pursue it, which are prerequisites for a return to work as well as for social life.\n\nThe Tinkertoy was created originally as a toy for kids made of various wooden and plastic pieces (wooden dowels, knobs, wheels, connectors, caps, points), to be assembled freely in order to make constructions. Based on this toy, Lezak created a test for the neuropsychological assessment of executive functions, which gives subjects the opportunity to use their own initiative and does not force them to choose from a series of predetermined alternatives. In fact, one of the most relevant characteristics of frontal lobe syndrome is an environment-dependent behaviour, which makes it difficult to cope with the requirements of everyday life. In this respect, Lezak’s Tinkertoy test (TTT) stands out, because it was specifically conceived to examine the ability to generate the most achievable goal, to organize, to plan and act, and to respond in a flexible way in a given context15. At the outset, studies of the TTT showed that it could be considered a useful predictor of employability3,15. Particularly, some researchers found the TTT complexity score correlated more positively with the employability of traumatic brain-damaged patients, than other tests for executive functions, such as trail making test -B, maze tracking, and several WAIS-R subtests9,10. Ownsworth and Shum20 showed that the difference in TTT scores between employed and unemployed patients after strokes was highly significant (p < 0.005 in a group of 27 subjects.) According to the authors, the TTT seems to describe productivity outcomes better than other tests of executive functioning (i.e. the FAS test and the five -point test), independent of the presence of hemiplegia and the elapsed time since the stroke. Furthermore, the TTT has been shown to be useful both for differentiating between types of dementia and for evaluating the severity of dementia12,17. In addition, subjects generally find the TTT interesting or amusing, so that it is easy to carry out this test, even in the cases of patients who are not very cooperative. Despite the fact that the TTT is commonly used in a clinical context, the only normative data refers to a very small sample of non-Italians16. Given both the potential relevance of this instrument for neuropsychological practice, and the lack of any validation so far, the present study aimed at setting TTT normative values in Italian adults, in order to determine firstly inferential cut-off points and their tolerance limits, and then equivalent scores, applying a statistical technique developed for neuropsychological tests7,8,22.\n\n\nMaterials and methods\n\nTwo hundred and fifty six neurologically unimpaired Italian subjects (mean age: 44.6; sd 20.85, range: 15–86 years) enrolled in this study on a voluntary basis, with verbal consent. The Research Ethics Committee of the University of Milano-Bicocca approved this (permit number: RM-2016-40) as a minimal risk study, whereby a signed consent document was not required. The subjects were nearly equally distributed according to sex (126 women and 130 men) and age class (range: 15 to 86 years). The level of education (from primary school to university) was recorded in years. Nobody showed a history or evidence of psychiatric disorders or dementia. The demographic distribution of the sample is shown in Table 1.\n\nValues represent the number of subjects.\n\nTest items, administration procedure and scoring criteria in this study followed the ones described by Lezak in the fourth edition of the Neuropsychological Assessment Handbook16. The test items were selected from the classic version of the Tinkertoy set. Namely, 50 items were used: 24 wooden dowels (4 red, 4 green, 4 orange, 6 blue, 6 yellow), 10 wooden knobs, 4 wooden wheels, 4 wooden caps, 4 wooden connectors, and 4 plastic yellow connectors (Figure 1).\n\nEach subject was individually presented with the aforementioned 50 pieces in different colours and forms, placed at random on a clean surface, and were told to build up whatever construction they wanted with a 5-minute minimum time limit, but no maximum time limit. On completion, the subjects were asked to say what the construction represented. Assessment took into account 7 performance variables: 1. Made construction(s) - whether the subject made any combination of pieces; 2. Number of pieces - total number of pieces used; 3. Name - whether and when the subject gave a name appropriate to the construction’s appearance; 4. Mobility (wheels working) and moving parts; 5. Three-dimensionality - whether the subject’s construction had three dimensions; 6. Free-standing - whether the subject’s construction stayed standing; 7. Errors - pieces forced together (misfit), connections not properly made (incomplete fit), and dropped and not picked up pieces (see Table 2). At the end a complexity score was given, determined by the sum of the points earned in each of the performance variables, with a maximum of 12 points (for two examples, see Figure 2).\n\nThe first is a male, 46 years old, with 13 years of education; his performance has been evaluated as 11.64 (corrected score) and 4 as equivalent score, according to Table 2. The TBI patient is a female, 36 years old, with 13 years of education; her performance has been evaluated as 4.33 (corrected score) and 0 as equivalent score.\n\nThe choice of the equivalent scores procedure was prompted by the need to obtain norms that could be directly compared to the already available norms of a wide set of other neuropsychological tests. In the first place, the influence of age, education and gender, the latter dichotomised, was evaluated through a linear multiple regression model, with least square estimation method. Several monotonic transformations of independent variables were analysed and the most effective in reducing the residual variance was adopted. The effect of each variable was studied partialling out the effect held in common with the other variables, after discarding age, as non significant as a covariate. In this way, it was possible to estimate the effects of confounding factors on the raw scores and, based on these estimates, adjusted scores were computed, adding or subtracting the contribution of the significant confounding effect. After ranking adjusted scores, Wilks’ nonparametric procedure was applied to set tolerance limits26,27 for pathological TTT result 0 (the lower 5% of all population). The maximum equivalent score, 4, was set with the analogous procedure for the upper 5% of population, whereas equivalent scores 1,2,3 were determined based on the ranking. Spss 21 package for the Social Science led to linear model estimation and to the ranking, Wilks’ tolerance intervals by mean of the R package ‘tolerance’27.\n\n\nResults\n\nNormality criteria are generally appraised by comparing one subject’s performance to that of all the other subjects. This implies homogeneity across the subjects in the comparison, and hence imposes the requirement that all possible factors influencing performance have been taken into account and removed from the raw scores. From a statistical point of view, this aim can be accomplished using stratification, which nonetheless, in some cases, raises problems concerning the sample size in each stratum. Alternatively, the effect of confounding factors can be removed from raw scores in a multiple regression model4,8,22. In order to set correction grids for the raw values of participants’ complexity scores, a linear model for the simultaneous effect of sex, age and educational level in years was fitted. Apart from sex, coded as a dummy variable, all dependent and independent variables were centred, where centring each variable on its mean corrected for any overlap with the effect of other terms of the model. The multiple regression proved significant (F2;242) = 9.08; p <0.001, adjusted Rsquare = 0.45). With regard to regression coefficients, sex and education proved significant (p = 0.002 and p = 0.008 respectively), whereas age did not, due to multicollinearity with education (rp = 0.422; p < .001) and it was therefore discarded. On average, females obtained lower scores than males (8.71 versus 9.40, sd 1.743 and 1.645 respectively). Education played a positive but modest role, an increase in the score from one education class to the adjacent one accounting approximately half a point (Table 3).\n\nLet yf,, ym indicate the score of a female and a male respectively and x the number of years of education. Then, the estimated impact of confounding variables on the TTT Complexity Centred raw scores can be expres e (males coded as 0, females as 1) and centred years of education.\n\n(y−y¯)=β1x1+.β1(x1−x¯1)(1\n\nThe estimation of the linear regression for the raw scores gives:\n\n(ym−9.06)=−.06×(x−11.35)(yf−9.06)=.645−.06×(x−11.35)(2\n\nAccordingly, adjustment was performed subtracting the estimated contribution of the confounding variables from each raw score, distinctly for females, with x = 1, and for males, with x = 0 in (2). In order to produce the adjustment to be applied to patients raw scores evaluated in rehabilitation practice, Table 4 shows the correction grid with the points to be added to raw Complexity Scores in order to calculate adjusted scores. Once the adjusted distribution had been computed, the identification of a cut-off point that assessed normality or impairment was a crucial step19. The appropriate criteria were represented by the interval underlying the lowest 5% tail of the adjusted scores in the cumulative distribution.\n\nHowever, misclassification of performance may arise and needs to be taken into account. In using the widely accepted value of the lower 5% of the normal population (regarded as a reasonable criterion for classifying subjects that are probably not normal) there is an inherent risk of incorrect categorization. The estimation of inferential tolerance limits enable one to obtain the thresholds above (or below) which there is at least (or at most) a desired percentage of the population, and the estimation of these limits keeps errors in performance assessment under control7,18. With the thirteenth observation, corresponding to the value of 6.25, representing the fifth percentile of the cumulative distribution function, the tenth and the sixteenth observation were identified as the outer and the inner limits, yielding the values of 5.86 and 6.44 respectively. Values equal to, or lower than, the outer tolerance limit indicate a pathological performance, with a controlled error risk. In order to compare the performance in this test to those in other tests, the standardization issue needs to be faced. The commonly used z-scores raise various difficulties, such as an alteration of the statistical dispersion of adjusted scores and problems with floor and ceiling values7. Distribution-free techniques are required here, since the best standpoint seems to be that of regarding adjusted scores as raw estimates of performance and hence converting them into an ordinal scale with just a few ordinal values, by means of the cumulative function of adjusted scores. A 5-point scale from (0 to 4), termed equivalent scores, is widely used, where 0 indicates the score that lies below the outer non-parametric tolerance limit of adjusted scores, Equivalent scores 1, 2 and 3 are intermediate between 0 and 4, id est they are obtained in the cumulative adjusted scores distribution. The equivalent score 4 indicates a performance equal to or superior to the median, thus no longer distinguishing between scores found in the upper half of the distribution. Equivalent scores 1, 2 and 3 are intermediate between 0 and 4 on a quasi-interval scale. An equivalent score equal to 0 is considered below the normal range, with a controlled error risk. This contracted scale of equivalent scores is then measured on a quasi-interval scale8 and may be viewed as a standardisation of adjusted scores. Table 5 shows the equivalent score limits, the density (i.e. the number of subjects within each equivalent score), and the cumulative frequency of subjects from 0 to 4 equivalent scores.\n\n\nDiscussion\n\nThe TTT has proved to be a highly sensitive instrument for the assessment of organization, planning abilities and response flexibility in a less structured context, compared with other neuropsychological tests generally used to evaluate executive functions16. Previously, the TTT could not be administered during psychometric neuropsychological examinations, owing to the absence of normative values, apt to compare the performance of frontal brain-damaged patients with the mean performance of unimpaired subjects with similar demographic features. The present study has filled this gap, establishing TTT normative data for a wide, healthy population sample, representative of the Italian population (n=256). Statistical analyses were adopted according to the methodology that is most widely used in Italy for the computation of normative values2,6–8,14,21,22. Our findings showed how TTT performance was affected by sex and education. In particular, males performed better than females and the higher the education the higher the TTT scores. Both effects have already been found in other tests for executive functions, such as the Wisconsin card sorting and Weigl tests14 and show an effect of culture and learning in structuring high-level functions. The relationship with education was also found by Apollonio and collaborators with the FAB2. Adjusted scores and inferential cut-off scores were calculated. Moreover, adjusted scores were transformed into equivalent scores, since the availability of equivalent scores makes it possible to evaluate whether a patient presents a homogeneous cognitive profile, or if he/she presents selective deficits in one or more cognitive areas. Therefore, it is now possible to compare the performance of brain-damaged patients directly with the TTT and other neuropsychological tests, using normative data with equivalent scores.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for ‘Normative data for Lezak’s Tinkertoy test in healthy Italian adults’, Crippa et al. 2016., 10.5256/f1000research.8409.d11868428\n\n\nConsent\n\nWritten informed consent was obtained from each patient in the normative study and from a pathological patient whose construction is depicted.",
"appendix": "Author contributions\n\n\n\nLC provided expertise in the clinical practice and the administration of the test. RD designed the study and supervised data collection. FC performed the statistical analysis. FC and RD prepared the first draft of the manuscript, LC contributed to the preparation of the manuscript. All authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nAlvarez JA, Emory E: Executive function and the frontal lobes: a meta-analytic review. Neuropsychol Rev. 2006; 16(1): 17–42. PubMed Abstract | Publisher Full Text\n\nApollonio I, Leone M, Isella V, et al.: The Frontal Assessment Battery (FAB): normative values in an Italian population sample. Neurol Sci. 2005; 26(2): 108–116. PubMed Abstract | Publisher Full Text\n\nBayless JD, Varney NR, Roberts RJ: Tinkertoy test performance and vocational outcome in patients with closed head injuries. J Clin Exp Neuropsychol. 1989; 11(6): 913–917. PubMed Abstract | Publisher Full Text\n\nBenton AL, Hamsher KdeH, Varney N, et al.: Contributions to Neurophychological Assessment. New York, Oxford University Press. 1983.\n\nBianchi L: The functions of the frontal lobes. Brain. 1985; 18(4).\n\nCaffarra P, Vezzadini F, Dieci F, et al.: Rey-Osterrieth complex figure: normative values in an Italian population sample. Neurol Sci. 2002; 22(6): 443–447. PubMed Abstract | Publisher Full Text\n\nCapitani E: Normative data and neuropsychological assessment. Common problems in clinical practice and research. Neuropsychol Rehabil. 1997; 7(4): 295–310. Publisher Full Text\n\nCapitani E, Laiacona M: Composite neuropsychological batteries and demographic correction: standardization based on equivalent scores, with a review of published data. The Italian Group for the Neuropsychological Study of Ageing. J Clin Exp Neuropsychol. 1997; 19(6): 795–809. PubMed Abstract | Publisher Full Text\n\nCicerone KD, De Luca J: Neurpsychological predictors of head injury rehabilitation outcome [abstract]. J Clin Exp Neuropsychol. 1990; 12: 92.\n\nCicerone KD, Wood JC: Planning disorder after closed head injury: a case study. Arch Phys Med Rehabil. 1987; 68(2): 111–115. PubMed Abstract\n\nGazzaniga MS, Ivry RB, Mangun GR: Cognitive Neuroscience. New York: Norton & Company, Inc. 2002.\n\nKoss E, Patterson MB, Mack JL, et al.: Reliability and validity of the Tinkertoy Test in evaluating individuals with Alzheimer’s disease. Clin Neuropsychol. 1998; 12(3): 325–329. Publisher Full Text\n\nKrause M, Mahant N, Kotschet K, et al.: Dysexecutive behaviour following deep brain lesions--a different type of disconnection syndrome? Cortex. 2012; 48(1): 97–119. PubMed Abstract | Publisher Full Text\n\nLaiacona M, Inzaghi MG, De Tanti A, et al.: Wisconsin Card Sorting Test: a new global score, with Italian norms, and its relationship with the Weigl sorting Test. Neurol Sci. 2000; 21(5): 279–291. PubMed Abstract | Publisher Full Text\n\nLezak MD: The problem of assessing executive functions. Int J Psychol. 1982; 17(1–4): 281–297. Publisher Full Text\n\nLezak MD, Howieson DB, Loring DV: Neuropsychological Assessment (4th ed). Oxford: Oxford University Press, 2004.\n\nMendez MF, Ashla-Mendez M: Differences between multi-infarct dementia and Alzheimer’s disease on unstructured neuropsychological tasks. J Clin Exp Neuropsychol. 1991; 13(6): 923–932. PubMed Abstract | Publisher Full Text\n\nMeyer JS: Outer and Inner Confidence Intervals for Finite Population Quantile Intervals. J Am Stat Assoc. 1987; 82(397): 201–204. Publisher Full Text\n\nMitrushina MN, Boone KB, Razani LJ, et al.: Handbook of Normative Data for Neuropsychological Assessment (2nd ed). Oxford: Oxford University Press, 2005. Reference Source\n\nOwnsworth T, Shum D: Relationship between executive functions and productivity outcomes following stroke. Disabil Rehabil. 2008; 30(7): 531–540. PubMed Abstract | Publisher Full Text\n\nRizzo S, Venneri A, Papagno C: Famous face recognition and naming test: a normative study. Neurol Sci. 2002; 23(4): 153–159. PubMed Abstract | Publisher Full Text\n\nSpinnler H, Tognoni G (eds): Standardizzazione e Taratura Italiana di Test Neuropsicologici. Ital J Neurol Sci. 1987. Reference Source\n\nStuss DT, Alexander MP: Executive functions and the frontal lobes: a conceptual view. Psychol Res. 2000; 63(3–4): 289–298. PubMed Abstract | Publisher Full Text\n\nStuss DT, Levine B: Adult clinical neuropsychology: lessons from studies of the frontal lobes. Annu Rev Psychol. 2002; 53: 401–433. PubMed Abstract | Publisher Full Text\n\nStuss DT: Traumatic brain injury: relation to executive dysfunction and the frontal lobes. Curr Opin Neurol. 2011; 24(6): 584–9. PubMed Abstract | Publisher Full Text\n\nWilks SS: Determination of sample sizes for setting tolerance limits. Ann Math Statist. 1941; 12(1): 91–96. Publisher Full Text\n\nYoung DS: Tolerance: an R package for estimating tolerance intervals. J Stat Softw. 2010; 36(5): 1–39. Publisher Full Text\n\nCrippa F, Cesana L, Daini R: Dataset 1 in: Normative data for Lezak’s Tinkertoy test in healthy Italian adults. F1000Research. 2016. Data Source"
}
|
[
{
"id": "14328",
"date": "13 Jun 2016",
"name": "Luigi Trojano",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors present a normative study for an unstructured test aimed at assessing cognitive flexibility and planning abilities. The methods adopted to obtain normative values are often used in Italy and allow comparing individuals’ performance on neuropsychological tests tapping different cognitive domains. The study sample is similar to that enrolled in other normative studies.\nHowever, the authors also enrolled 29 late adolescents (15-18 year-old) in their sample, and this is not usual in normative studies on neuropsychological tests. I suggest deleting these individuals from the sample, as development and maturation of executive processes across adolescence is quite variable and should be addressed by dedicated normative studies.\nThe authors should also consider several limitations of their study, and acknowledge them in their final remarks. For instance, the authors stated in their discussion that they enrolled a “wide” sample, “representative of the Italian population”. I believe that the authors should provide more details about procedures and methods adopted for recruitment of participants, and likely tone down claims about the extension of the sample and its representativeness of the “Italian population”. Moreover, the study did not provide data about psychometric properties of the test such as convergent or divergent validity, test-retest reliability, or inter-rater agreement. I understand that to address some of these properties is outside the authors’ scope, but I believe that at least inter-rater agreement is important to reassure the reader about clinical applicability of the present test.\nMinor points: the authors should provide more details about the exact instructions for examinees, about time limits, and about the pieces to be used, also to make clear for the reader which types of errors are considered as “misfit” or “incomplete fit”. Info about availability of test material might be useful.",
"responses": []
},
{
"id": "16486",
"date": "03 Oct 2016",
"name": "Andrea Peru",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis study provides normative data on the Lezak’s Tinkertoy test for Italian population ranging in age from adolescence to older adulthood (range: 15-86 years).\nIn this vein, the word “adults” in the title seems to be not completely appropriate. Even more importantly, I don’t see any reason why ethnicity should impact performance on this test. To sum up, I strongly suggest a shorter and more appealing title: Normative data for Lezak’s Tinkertoy test.\nActually, so far normative data for this test are limited and based on a relatively small sample. Thus, I commend the authors for their intent to address this lack of evidence. There are, however, some shortcomings that should be addressed in a new version of the manuscript.\nIf my understanding is correct, the authors treated age as a continuous rather than discrete variable. If so, Table 1 is not necessary since it leaves the reader the idea that the age effect is spurious, due to the fact that the different age groups are not the same size. Alternatively, the authors could consider the opportunity to use statistical analysis like ANOVA – quite robust against different group sizes - rather than linear regression.\nThe main problem with the present paper, however, has to do with the fact that the authors missed a great opportunity to demonstrate that the Tinkertoy test has good construct validity. Previous studies reported that among elderly, demented, and traumatic brain injury patients the Tinkertoy test score has a significant, positive correlation with performances on the Trail Making and Wisconsin Card Sorting Test. In particular, the Tinkertoy complexity score turned out to be very sensitive to disorders of executive functions. In no way, however, can this be taken as convincing evidence that the Tinkertoy test is a reliable and valid instrument to assess executive functions in healthy people. I encourage the authors to provide further data on this topic.\nFinally, I want to focus authors’ attention on some grammatical and lexical issues. As to grammar: Methods section, second paragraph: subject and verb are not in agreement as to number “Each subject…… were told…”. As to lexicon: For more than 100 years, in the field of experimental psychology, the term “subjects” has been used to describe people who take part in research and its use is still widely accepted. In the last decades, however, several psychological societies argued that the term “subject” is disrespectful, and recommended to replace it by “participants”. Authors could consider this possibility. Analogously, notwithstanding the taxonomic label “frontal lobe syndrome” is still very popular among clinicians, it has really had its day and should be replaced by \"dysexecutive syndrome\" or “prefrontal lobe dysfunction” according to whether the emphasis is put on the function or the localization.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-727
|
https://f1000research.com/articles/5-725/v1
|
22 Apr 16
|
{
"type": "Review",
"title": "Recent advances in understanding and treating ARDS",
"authors": [
"Rebecca M. Baron",
"Bruce D. Levy",
"Rebecca M. Baron"
],
"abstract": "Acute respiratory distress syndrome represents a complex syndrome with considerable morbidity and mortality, for which there exist no targeted treatment strategies. However, recent advances in clinical care have improved outcomes, and we will review a number of these approaches here, as well as explore the mechanisms underlying the benefit of intervention that might point us in the direction toward future treatment and preventive strategies for this devastating syndrome.",
"keywords": [
"Adjunctive therapy",
"Berlin criteria",
"Low Tidal Volume Ventilation",
"Prone Positioning",
"Neuromuscular Blockade"
],
"content": "Introduction\n\nThe acute respiratory distress syndrome (ARDS), first described in 1967, remains difficult to treat and has significant morbidity and mortality. Risk factors for ARDS include factors resulting from direct injury to the lung (e.g., pneumonia and gastric aspiration) or indirect injury (e.g., sepsis and pancreatitis). These conditions result in inflammatory lung injury and hypoxemia that arise from disruption of the alveolar-capillary membrane and influx of protein-rich edema fluid, producing physiologic lung dysfunction. Remarkably, despite intense investigation and numerous large-scale clinical trials, no targeted medical therapies have yet been developed nor proven effective, and there exist no universally agreed-upon biomarkers that might predict severity of illness, or clinical outcomes, or both. These challenges in characterization and treatment likely result from the heterogeneity of ARDS as well as the difficulty of treating a “syndrome” rather than a molecularly confirmed disease; however, a number of management strategies have proven beneficial and have resulted in reductions in mortality1. It is unlikely, as is the case for many serious ailments, that there is a “one size fits all” treatment for ARDS, and thus improved understanding of the disease process and appropriately characterizing severity of illness will be critical for making advances in treatment strategy. Furthermore, the National Institutes of Health (NIH) has recognized the importance of addressing strategies to prevent ARDS development, thus forming the new version of the ARDS Network under the heading of “PETAL”: Prevention and Early Treatment of Acute Lung Injury. Therefore, in this brief review, we set out to discuss some of the recent advances in understanding and treating ARDS, as well as to address the possible biological mechanisms underlying these mechanisms, to attempt to shed light on potential areas for future scientific investigation. We focus our discussion on significant articles that have modified mortality from ARDS, and we summarize a proposed overall approach to ARDS.\n\n\nAdvances in defining acute respiratory distress syndrome and improving mortality prediction: the Berlin Criteria\n\nFrom 1994 to 2012, ARDS was defined on the basis of the American-European Consensus Conference (AECC) criteria: (a) acute onset of hypoxemia defined by partial pressure of arterial oxygen/fraction of inspired oxygen (PaO2/FiO2, or P/F) ratio of >200 with (b) new bilateral infiltrates (c) not attributable to heart failure as defined by pulmonary capillary wedge pressure (PCWP) (as measured by a Swan-Ganz catheter) of not more than 18 mmHg (or absence of suspected left atrial hypertension/cardiogenic pulmonary edema if PCWP was not available)2. These criteria were adopted with the goal of more uniformly defining the syndrome and identifying appropriate patients for ARDS therapies and enrollment in clinical trials. Although these criteria facilitated these goals, it was felt that certain improvements in the definition might improve the clinical phenotyping and risk stratification of ARDS subjects, including a more explicit definition of “acute” onset of hypoxemia, further definition of the dependence of the P/F ratio on ventilator settings (in particular, the positive end-expiratory pressure (PEEP) setting), improved criteria for chest radiograph interpretation of “bilateral infiltrates”, and more explicit guidance with defining the contribution of cardiogenic pulmonary edema to the clinical picture.\n\nIn 2012, the European Society of Intensive Care Medicine convened an expert panel to improve the reliability and validity of the ARDS definition, termed the Berlin Criteria3. These newer criteria improve upon the old, in part through the following: (a) defining three categories of ARDS severity on the basis of P/F ratio: P/F ratio ≤300 and >200 (“mild” ARDS, which was previously categorized as acute lung injury under AECC criteria), P/F ratio of between 100 and 200 (“moderate” ARDS), and P/F ratio of <100 (“severe” ARDS); (b) defining “acute” onset of bilateral infiltrates as within 7 days of exposure to an ARDS risk factor or worsening respiratory symptoms; (c) more definitive chest radiograph criteria were provided (with retention of the description of bilateral infiltrates consistent with pulmonary edema and not fully explained by effusions, lobar/lung collapse, or nodules), and use of chest computed tomography was allowed for fulfilling the radiographic definition as well; (d) use of the PCWP for defining cardiogenic pulmonary edema was removed (given the declining use of Swan-Ganz catheters), and it was acknowledged that cardiogenic and non-cardiogenic pulmonary edema can coexist. However, determination of whether the bilateral infiltrates are attributable to a cardiogenic cause cannot be based solely upon clinical decision making. If a risk factor for ARDS is not identified, then some objective criteria of cardiac function, such as echocardiography, are required to exclude a sole cardiogenic cause for pulmonary edema; and (e) minimum use of PEEP of at least 5 cm H2O on the mechanical ventilator (or delivered by non-invasive ventilation only in the mild ARDS category) in assessing the severity of oxygenation impairment using the P/F ratio.\n\nThe Berlin Criteria were derived and validated, and additional variables that were considered in the definition (lung compliance, radiographic severity, levels of PEEP, and exhaled minute ventilation) did not improve severity prediction and therefore were not incorporated into the final criteria (although the authors acknowledged that analysis of these factors plays an important role in bedside clinical care). Of note, defining the “severe ARDS” category called attention to the most afflicted group (with a P/F ratio of <100), which has the highest mortality irrespective of ventilator strategy and therefore might benefit from applications of more advanced ARDS rescue strategies (see discussions below). Specifically, mortality rates in the mild, moderate, and severe groups were 27%, 32%, and 45%, respectively, and the Berlin Criteria improved mortality prediction beyond that of AECC; however, as acknowledged by the authors, there are clearly limitations to clinical criteria in defining a syndrome1,3,4. Ideally, the use of additional biologic predictors might have the capacity to improve prediction of outcome and risk stratification. Although the hunt for predictive biomarkers for ARDS development and outcome is still under way, existing studies suggest the promise of using plasma biomarkers—e.g., interleukin-8 (IL-8), tumor necrosis factor alpha (TNFα), surfactant protein-D (SPD), and mitochondrial DNA—to improve prediction of outcomes beyond clinical classification algorithms (e.g., Acute Physiology and Chronic Health Evaluation scoring systems)5,6. Recent studies suggest that ARDS might be better predicted by specific biomarkers, such as plasma levels of the soluble form of the receptor for advanced glycation end products (sRAGE) as a marker of lung epithelial injury7,8 and plasma levels of tumor necrosis factor receptor-1 (TNFR1), IL-6, IL-8, and plasminogen activator inhibitor-1 (PAI1) as markers of a hyperinflammatory ARDS subphenotype8,9. Although the Berlin Criteria have enhanced our clinical phenotyping systems, ongoing work in clinical/biological phenotyping of critically ill subjects will ideally facilitate additional prevention trials, allowing investigators to target specific risk groups with modifiable risk factors for ARDS development.\n\n\nAdvances in mechanical ventilation support of patients with acute respiratory distress syndrome: low tidal volume ventilation\n\nIn a seminal study performed by the ARDS Network in 2000, mechanical ventilatory support of ARDS patients with 12 ml/kg (ideal body weight) tidal volume was compared with low tidal volume ventilation at 6 ml/kg, and there was a significant reduction in mortality with low tidal volume ventilation (38% to 31%)10. This study prompted the widespread use of low tidal volume ventilation in supporting patients with ARDS and has led to ongoing studies to investigate the mechanisms underlying this profound benefit (see below). In addition, this important trial has prompted additional recent trials investigating whether low tidal volume ventilation might also benefit other populations of patients, such as those undergoing mechanical ventilation for an operative procedure (i.e. whether patients without significant pre-existing lung injury might be similarly injured with potentially injurious mechanical ventilator settings, thereby being placed at risk for the development of ARDS).This question remains a point of clinical debate in setting mechanical ventilation parameters for critically ill patients without the presence of ARDS. Although it is known that normal laboratory mice exposed to high tidal volume ventilation develop lung injury11, it is not clear whether this is the case for humans without pre-existing lung injury. Interestingly, a recent article reported that the use of a “prophylactic” protective ventilation strategy improved clinical outcomes (relative to higher tidal volumes usually used during anesthesia in patients without pre-existing lung injury with the goal of preventing atelectasis) in intermediate- and high-risk patients undergoing abdominal surgery12.\n\nThe findings of improved mortality with low tidal volume ventilation prompted widespread investigation into the mechanisms underlying this protection, resulting in a vast expansion in our understanding of factors driving mechanotransduction-related lung injury. Physiologic lung improvements as a result of low tidal volume ventilation have been attributed to a number of factors, including most grossly, reduced incidence of barotrauma (application of high pressures to the lung resulting in injury), volutrauma (application of high tidal volumes—i.e. lung stretching—resulting in injury), and perhaps improved hemodynamics (blood pressure and organ perfusion) as a result of less overdistention of the lung and improved venous return to the heart; however, ventilation at low tidal volumes can result in collapse of the lung parenchyma, and trials of high-frequency oscillatory ventilation that allowed for very small tidal volumes did not prove beneficial13,14, supporting the complexity of ARDS pathophysiology and management. Mechanical ventilation without maintenance of open lung units has the potential to exacerbate lung injury as a result of opening and closing of lung units, termed “atelectrauma”15,16, which has led to widespread studies of optimal application of PEEP to maintain open lung units, and a recent meta-analysis suggested that higher levels of applied PEEP might be beneficial in patients with moderate ARDS17. Beyond physiologic benefits of low tidal volume ventilation, numerous studies have called attention to the concept of “biotrauma” as a result of injurious mechanical ventilation, in which stretching of lung units might activate cellular signaling cascades resulting in lung inflammation, increased release of pro-inflammatory mediators (e.g., IL-6), and effects on non-pulmonary tissues resulting in multi-system organ failure. Potential physiologic benefits of low tidal volume ventilation have recently been reviewed in detail19.\n\n\nAdvances in adjunctive therapy for severe acute respiratory distress syndrome: neuromuscular blockade\n\nNeuromuscular blockers (NMBs) have been used for a long period of time in the intensive care unit, largely to facilitate mechanical ventilation of ARDS subjects when sedation alone was insufficient, usually in the setting of severe gas exchange impairment, or to facilitate other advanced therapies for ARDS, such as prone positioning (see below), or to do both; however, protocolized care for use of NMBs in ARDS has not been uniformly applied, and concerns regarding adverse effects of NMBs (e.g., prolonged neuromuscular weakness) without clear data showing benefit of NMBs limited widespread use until recently. Papazian et al. examined 340 intubated patients in a multi-center trial with severe ARDS (P/F ratio of <150), who were randomly assigned to receive NMB (cisatracurium besylate) versus placebo for 48 hours. All patients received low tidal volume ventilation and were on at least 5 cm H2O PEEP. The adjusted 90-day in-hospital mortality rate was lower with NMB versus placebo, and no increased neuromuscular weakness was observed in the NMB group20. Additionally, an increased number of ventilator-free days was observed in the NMB group. Of note, both groups received deep sedation. This study has raised important questions about the utility of NMB in ARDS, and there is sufficient uncertainty about its widespread use that the NIH PETAL Network is addressing this issue in one of its first network trials. Thus, further data will be available in the future to help guide clinical practice. Residual questions that remain include whether patients solely with severe ARDS might benefit from NMB, what the optimal NMB infusion duration might be, whether similar benefits might be observed with NMB agents other than cisatracurium besylate, and what the independent effects of heavy sedation apart from NMB might be21,22.\n\nAlthough much of the mechanism remains to be learned regarding protective effects underlying NMB (and additional significant information is likely to be gained from the upcoming PETAL Network NMB trial and planned associated ancillary studies), there exist data to support a number of possible pathways of benefit: (a) NMBs counteract patients bucking the ventilator, thereby limiting lung injury arising from ventilator dyssynchrony—of note, an increased rate of pneumothoraces (consistent with barotrauma) was observed in the placebo group20; (b) NMBs might result in less biotrauma as evidenced by less end-organ failure associated with their use20, as well as reduction in lung (IL-1β, IL-6, and IL-8) and serum (IL-1β and IL-8) cytokines in patients on NMB23; (c) NMBs limit expiratory muscle function and therefore reduced respiratory system collapse and derecruitment that might result in improved respiratory system compliance and improved ventilation-perfusion matching21,22. Interestingly, a recent preclinical study suggests that the mechanism of protection of NMBs might relate to direct anti-inflammatory effects of blocking the nicotinic acetylcholine receptor-α1, independent of effects on improving ventilator dyssynchrony24.\n\n\nAdvances in adjunctive therapy for severe acute respiratory distress syndrome: prone positioning\n\nAlthough it was realized in the 1970s that prone positioning improved oxygenation in ARDS, numerous studies over ensuing decades demonstrated improvement in oxygenation but failed to show improved mortality from prone positioning. This lack of mortality benefit, coupled with concerns regarding possible adverse events from proning patients (e.g., facial edema, skin breakdown at areas of pressure necrosis, transient desaturation as well as less commonly dislodgement of lines, endotracheal tubes, and hemodynamic instability), led to limited/sporadic use across clinical ARDS centers25. In 2013, Guérin et al. examined prone positioning (at least 16 hours per day) versus standard positioning in 466 subjects with severe ARDS (within 36 hours of intubation and after a stabilization period of 12 to 24 hours; P/F ratio of < 150), FiO2 of at least 0.6, low tidal volume ventilation, and PEEP of at least 5 cm H2O and found a striking 28-day mortality benefit of prone positioning (32.8% supine versus 16% prone), and a mortality benefit persisted until day 9026. Of note, there was no significant difference in complications between the prone and supine groups (except for an increased rate of cardiac arrests in the supine group); however, the authors acknowledge that this study was carried out in centers with substantial experience and expertise in prone positioning. This lack of expertise in prone positioning, the potential complications that might arise from proning, and the potential difficulty in selecting optimal patients who might benefit from proning (a highly selected group of patients was included in the most recent trial) have led to variability in uniform adoption of prone positioning in ARDS clinical centers.\n\nAlthough a number of studies over many years examined potential benefits of proning, a mortality benefit to the degree described above was only recently observed. Some of the earlier studies were small studies and in addition studied patients in later ARDS phases when prone positioning might be less likely to reverse the disease process. It is possible that more routine use of low tidal volume ventilation in this most recent study is a factor, as well as the more prolonged period of proning that was employed in this study compared with other trials27. Of note, differential use of neuromuscular blockade (increased NMB was used in the prone position group) has been cited as an important factor to consider in interpreting this trial (see Advances in adjunctive therapy for severe acute respiratory distress syndrome: neuromuscular blockade section above). Some earlier studies suggested that the most afflicted patients (i.e. those with the lowest P/F ratios) might benefit from proning, prompting the selection of the patient population in the most recent study26. In general, potential benefits of proning might include (a) improved lung ventilation perfusion matching, (b) improved right ventricular dysfunction28,29, and (c) recruitment of lower-lobe atelectatic lung units (perhaps related to reduced compression of lung units in the prone position) and decreased intrapulmonary shunting, as well as potentially improved maintenance of open lung units, thus limiting ventilator-induced lung injury (through mitigating repeated opening and closing of lung units that generates lung injury). It is believed that some patients also experience improved secretion clearance gravitationally in the prone position25.\n\n\nConclusions\n\nAlthough ARDS represents a complex syndrome with considerable morbidity and mortality, recent advances in clinical care have improved outcomes, as described in this review. Support of ARDS patients with low tidal volume ventilation has become the standard of care, and this approach has revealed important underlying mechanisms that have led to new areas of investigation in lung injury. Use of the Berlin Criteria has aided in the identification of the most afflicted ARDS patients who might benefit from rescue therapies, and targeting of neuromuscular blockade and prone positioning in severe ARDS has recently proven beneficial in terms of improved ARDS mortality. Ongoing studies will be important for providing additional information for helping us target these modalities to the patients most likely to benefit from them as well as to gain further understanding of the mechanisms underlying benefit of these modalities. An additional area of clinical care and investigation not reviewed here in detail is the use of conservative fluid strategy to decrease ventilator time in patients with ARDS30,31, although more recent data have called attention to the possibility that a more restrictive fluid management strategy is associated with cognitive dysfunction32. Fluid management in critical illness is currently under review33, and the information that is gleaned may help guide clinical practice in the future.\n\nAlthough targeted medical therapies have not yet proven beneficial in clinical trials, promising targets16,34, including those in an ongoing NIH-funded trial in mesenchymal stromal cells35,36, are under investigation; however, it is widely appreciated that the heterogeneity of the syndrome might require a more targeted/personalized approach toward ameliorating complex biologic pathways that might be differentially activated with different host responses and at different time points in each illness. Increasingly, it is appreciated that efforts targeted at prevention of ARDS represent a growing opportunity for investigation and treatment37, both in optimally identifying at-risk subjects and in selecting those most likely to benefit from early interventions. Of note, prevention studies will be a major focus of the NIH PETAL Network. In conclusion, although ARDS represents a challenging syndrome to characterize, manage, and treat, recent advances have improved clinical outcomes, and exciting approaches on the horizon hold promise for allowing us to gain insights into novel treatment strategies.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nHager DN: Recent Advances in the Management of the Acute Respiratory Distress Syndrome. Clin Chest Med. 2015; 36(3): 481–496. PubMed Abstract | Publisher Full Text\n\nBernard GR, Artigas A, Brigham KL, et al.: The American-European Consensus Conference on ARDS. Definitions, mechanisms, relevant outcomes, and clinical trial coordination. Am J Respir Crit Care Med. 1994; 149(3 Pt 1): 818–824. PubMed Abstract | Publisher Full Text\n\nARDS Definition Task Force, Ranieri VM, Rubenfeld GD, et al.: Acute respiratory distress syndrome: the Berlin Definition. JAMA. 2012; 307(23): 2526–2533. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSweatt AJ, Levitt JE: Evolving epidemiology and definitions of the acute respiratory distress syndrome and early acute lung injury. Clin Chest Med. 2014; 35(4): 609–624. PubMed Abstract | Publisher Full Text\n\nCalfee CS, Ware LB, Glidden DV, et al.: Use of risk reclassification with multiple biomarkers improves mortality prediction in acute lung injury. Crit Care Med. 2011; 39(4): 711–717. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nNakahira K, Kyung SY, Rogers AJ, et al.: Circulating mitochondrial DNA in patients in the ICU as a marker of mortality: derivation and validation. PLoS Med. 2013; 10(12): e1001577; discussion e1001577. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJabaudon M, Blondonnet R, Roszyk L, et al.: Soluble Receptor for Advanced Glycation End-Products Predicts Impaired Alveolar Fluid Clearance in Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med. 2015; 192(2): 191–199. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nWare LB, Calfee CS: Biomarkers of ARDS: what's new? Intensive Care Med. 2016; 42(5): 797–799. PubMed Abstract | Publisher Full Text\n\nCalfee CS, Delucchi K, Parsons PE, et al.: Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014; 2(8): 611–620. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nVentilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. The Acute Respiratory Distress Syndrome Network. N Engl J Med. 2000; 342(18): 1301–1308. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMatute-Bello G, Frevert CW, Martin TR: Animal models of acute lung injury. Am J Physiol Lung Cell Mol Physiol. 2008; 295(3): L379–99. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFutier E, Constantin JM, Paugam-Burtz C, et al.: A trial of intraoperative low-tidal-volume ventilation in abdominal surgery. N Engl J Med. 2013; 369(5): 428–437. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nFerguson ND, Cook DJ, Guyatt GH, et al.: High-frequency oscillation in early acute respiratory distress syndrome. N Engl J Med. 2013; 368(9): 795–805. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nYoung D, Lamb SE, Shah S, et al.: High-frequency oscillation for acute respiratory distress syndrome. N Engl J Med. 2013; 368(9): 806–813. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMuscedere JG, Mullen JB, Gan K, et al.: Tidal ventilation at low airway pressures can augment lung injury. Am J Respir Crit Care Med. 1994; 149(5): 1327–1334. PubMed Abstract | Publisher Full Text\n\nStandiford TJ, Ward PA: Therapeutic targeting of acute lung injury and acute respiratory distress syndrome. Transl Res. 2016; 167(1): 183–191. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBriel M, Meade M, Mercat A, et al.: Higher vs lower positive end-expiratory pressure in patients with acute lung injury and acute respiratory distress syndrome: systematic review and meta-analysis. JAMA. 2010; 303(9): 865–873. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHan S, Mallampalli RK: The acute respiratory distress syndrome: from mechanism to translation. J Immunol. 2015; 194(3): 855–860. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSlutsky AS, Ranieri VM: Ventilator-induced lung injury. N Engl J Med. 2014; 370(10): 979–980. PubMed Abstract | Publisher Full Text\n\nPapazian L, Forel JM, Gacouin A, et al.: Neuromuscular blockers in early acute respiratory distress syndrome. N Engl J Med. 2010; 363(12): 1107–1116. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHraiech S, Dizier S, Papazian L: The use of paralytics in patients with acute respiratory distress syndrome. Clin Chest Med. 2014; 35(4): 753–763. PubMed Abstract | Publisher Full Text\n\nSlutsky AS: Neuromuscular blocking agents in ARDS. N Engl J Med. 2010; 363(12): 1176–1180. PubMed Abstract | Publisher Full Text\n\nForel JM, Roch A, Marin V, et al.: Neuromuscular blocking agents decrease inflammatory response in patients presenting with acute respiratory distress syndrome. Crit Care Med. 2006; 34(11): 2749–2757. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nFanelli V, Morita Y, Cappello P, et al.: Neuromuscular Blocking Agent Cisatracurium Attenuates Lung Injury by Inhibition of Nicotinic Acetylcholine Receptor-α1. Anesthesiology. 2016; 124(1): 132–140. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBenson AB, Albert RK: Prone positioning for acute respiratory distress syndrome. Clin Chest Med. 2014; 35(4): 743–752. PubMed Abstract | Publisher Full Text\n\nGuérin C, Reignier J, Richard JC, et al.: Prone positioning in severe acute respiratory distress syndrome. N Engl J Med. 2013; 368(23): 2159–2168. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSoo Hoo GW: In prone ventilation, one good turn deserves another. N Engl J Med. 2013; 368(23): 2227–2228. PubMed Abstract | Publisher Full Text\n\nRepessé X, Charron C, Vieillard-Baron A: Acute respiratory distress syndrome: the heart side of the moon. Curr Opin Crit Care. 2016; 22(1): 38–44. PubMed Abstract | Publisher Full Text\n\nVieillard-Baron A, Charron C, Caille V, et al.: Prone positioning unloads the right ventricle in severe ARDS. Chest. 2007; 132(5): 1440–1446. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNational Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Wiedemann HP, Wheeler AP, et al.: Comparison of two fluid-management strategies in acute lung injury. N Engl J Med. 2006; 354(24): 2564–2575. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nGrissom CK, Hirshberg EL, Dickerson JB, et al.: Fluid management with a simplified conservative protocol for the acute respiratory distress syndrome*. Crit Care Med. 2015; 43(2): 288–295. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMikkelsen ME, Christie JD, Lanken PN, et al.: The adult respiratory distress syndrome cognitive outcomes study: long-term neuropsychological function in survivors of acute lung injury. Am J Respir Crit Care Med. 2012; 185(12): 1307–1315. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSilversides JA, Ferguson AJ, McAuley DF, et al.: Fluid strategies and outcomes in patients with acute respiratory distress syndrome, systemic inflammatory response syndrome and sepsis: a protocol for a systematic review and meta-analysis. Syst Rev. 2015; 4: 162. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChen ZL, Song YL, Hu ZY, et al.: An estimation of mechanical stress on alveolar walls during repetitive alveolar reopening and closure. J Appl Physiol (1985). 2015; 119(3): 190–201. PubMed Abstract | Publisher Full Text\n\nWalter J, Ware LB, Matthay MA: Mesenchymal stem cells: mechanisms of potential therapeutic benefit in ARDS and sepsis. Lancet Respir Med. 2014; 2(12): 1016–1026. PubMed Abstract | Publisher Full Text\n\nWilson JG, Liu KD, Zhuo H, et al.: Mesenchymal stem (stromal) cells for treatment of ARDS: a phase 1 clinical trial. Lancet Respir Med. 2015; 3(1): 24–32. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFestic E, Kor DJ, Gajic O: Prevention of acute respiratory distress syndrome. Curr Opin Crit Care. 2015; 21(1): 82–90. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "13242",
"date": "22 Apr 2016",
"name": "Gregory Downey",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13243",
"date": "22 Apr 2016",
"name": "Jason Bates",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-725
|
https://f1000research.com/articles/5-723/v1
|
22 Apr 16
|
{
"type": "Review",
"title": "Update on the pathogenesis of Scleroderma: focus on circulating progenitor cells",
"authors": [
"Alexandra Maria Giovanna Brunasso",
"Cesare Massone",
"Cesare Massone"
],
"abstract": "In systemic sclerosis (SSc), the development of fibrosis seems to be a consequence of the initial ischemic process related to an endothelial injury. The initial trigger event in SSc is still unknown, but circulating progenitor cells (CPCs) might play a key role. Such cells have the ability to traffic into injury sites, exhibiting inflammatory features of macrophages, tissue remodeling properties of fibroblasts, and vasculogenesis functions of endothelial cells. The different subsets of CPCs described thus far in SSc arise from a pool of circulating monocyte precursors (CD14+ cells) and probably correspond to a different degree of differentiation of a single cell of origin. Several subsets of CPCs have been described in patients with SSc, all have a monocytic origin but may or may not express CD14, and all of these cells have the ability to give origin to endothelial cells, or collagen (Col)-producing cells, or both. We were able to identify six subsets of CPCs: pluripotent stem cells (CD14+, CD45+, and CD34+), monocyte-derived multipotential cells (MOMCs) or monocyte-derived mesenchymal progenitors (CD14+, CD45+, CD34+, Col I+, CD11b+, CD68+, CD105+, and VEGFR1+), early endothelial progenitor cells (EPCs) or monocytic pro-angiogenic hematopoietic cells or circulating hematopoietic cells (CD14+, CD45+, CD34low/−, VEGFR2+/−, CXCR4+, c-kit+, and DC117+), late EPCs (CD14−, CD133+, VEGFR2+, CD144+ [VE-cadherin+], and CD146+), fibroblast-like cells (FLCs)/circulating Col-producing monocytes (CD14+, CD45+, CD34+/−, and Col I+), and fibrocytes (CD14−, CD45+, CD34+, Col I+, and CXCR4+). It has been demonstrated that circulating CD14+ monocytes with an activated phenotype are increased in patients with SSc when compared with normal subjects. CD14+, CD34+, and Col I+ spindle-shaped cells have been found in increased numbers in lungs of SSc patients with interstitial lung disease. Elevated blood amounts of early EPCs have been found in patients with SSc by different groups of researchers and such levels correlate directly with the interstitial lung involvement. The prevalence of hematopoietic markers expressed by CPCs that migrate from blood into injury sites in SSc differs and changes according to the degree of differentiation. CXCR4 is the most commonly expressed marker, followed by CD34 and CD45 at an end stage of differentiation. Such difference also indicates a continuous process of cell differentiation that might relate to the SSc clinical phenotype (degree of fibrosis and vascular involvement). A deeper understanding of the role of each subtype of CPCs in the development of the disease will help us to better classify patients in order to offer them targeted approaches in the future.",
"keywords": [
"fibrosis",
"CD14+ cells",
"pluripotent stem cells",
"monocyte-derived multipotential cells",
"early endothelial progenitor cells",
"monocytic pro-angiogenic hematopoietic cells",
"fibroblast-like cells",
"fibrocytes"
],
"content": "Introduction\n\nSystemic sclerosis (SSc) is a chronic, complex, and not yet completely understood autoimmune disease characterized by the presence of immunological events, the onset of fibrosis, and the development of vascular alterations1. The development of fibrosis seems to be a consequence of the initial ischemic process related to an endothelial injury2. In the early disease phase (first year from diagnosis), there is an increase of pro-angiogenic factors—vascular endothelial growth factor (VEGF), platelet-derived growth factor, and stromal-derived growth factor-1—in response to the vascular damage that correlates to the nailfold capillaroscopy changes observed by clinicians (giant capillaries and new vessel formation)3. But in the late phase of SSc, the anti-angiogenic response and the fibrosis seem to dominate over the initial pro-angiogenic phase4. The initial trigger event in SSc is still unknown, but circulating progenitor cells (CPCs) might play a key role4.\n\nSince 1994, when Bucala et al. first described these fibrocytes as circulating leukocytes able to produce collagen (Col), different types of progenitor cells have been described as key players in different entities, such as pulmonary artery hypertension (PAH), asthma, interstitial lung disease (ILD), idiopathic pulmonary fibrosis, and sclerosing diseases (cirrhosis, atherosclerosis, SSc, chronic kidney disease, and so on), and as initially described in wound healing. Such cells have the ability to traffic into injury sites, exhibiting both inflammatory features of macrophages and tissue remodeling properties of fibroblasts5. Interestingly, some of the CPCs are also able to differentiate into endothelial cells playing a role in the vasculogenesis process5. In this review, we will summarize the existing evidence regarding the role of CPCs in SSc.\n\n\nAnalysis of the recent literature\n\nSince 1994, different subtypes of CPCs have been described as quantitatively or functionally altered in patients with SSc (Table 1)6–19. The different subtypes of CPCs described thus far in SSc arise from a pool of circulating monocyte precursors (CD14+ cells) and probably correspond to a different degree of differentiation from a single cell of origin. The pluripotent stem cells (PSCs) seem to correspond to a very early degree of differentiation. The monocyte-derived mesenchymal progenitors (MOMCs), also known as monocyte-derived mesenchymal progenitors, are multipotent cells with a spindle-shaped morphology and a unique phenotype (CD14+, CD45+, CD34+, and type I Col+) that might correspond to the PSCs described by Zhao et al.6, but with the ability to produce Col (a further degree of differentiation). MOMCs show mixed morphologic and phenotypic features of phagocytes, mesenchymal cells, and endothelial cells2,4,8. It has been demonstrated that circulating CD14+ monocytes with an activated phenotype (CD68+, CD204+, and Singlec-1+) are increased in patients with SSc when compared with normal subjects12–14,16. CD14+, CD34+, and Col I+ spindle-shaped cells (compatible with MOMCs) have been found in increased numbers in the lungs of SSc patients with ILD15,16. In 2004, Postlethwaite et al. reported an elevated number of spindle-shaped cells with a new phenotype (CD14+, CD45+, CD34−, and Col I+) in patients with SSc after culturing peripheral blood monocyte cells (PBMCs) with type I Col. They called these particular cells fibroblast-like cells (FLCs). They differ from the already-known PSCs and MOMCs by the absence of CD34 expression and from fibrocytes by the presence of CD14 and the absence of CD34 as surface markers11. They also suggested that the increased outgrowth of FLCs from patients with SSc may be a marker of diffuse disease and pulmonary fibrosis11.\n\nOther subtypes of CPCs have been related to the vascular alterations seen in patients with SSc, as the circulating endothelial precursor cells (EPCs) that seem to contribute to the initial phase of SSc. In 2009, the European League Against Rheumatism (EULAR) Scleroderma Trials and Research group provided recommendations for standardization for future research in EPCs10. The consensus panel agreed to classify EPCs in two groups:\n\n1. Early EPCs, characterized by the positive expression of CD14, CD45, the low expression of CD34, and the variable expression of VEGFR2 (+/−), have also been described as monocytic pro-angiogenic hematopoietic cells by Yamaguchi et al.2 and as circulating hemotopoietic progenitor cells (CD45+, CXCR4+, c-kit+, and CD117+) by Campioni et al.9. Early EPCs have the ability to differentiate into endothelial cells, fibroblasts, smooth muscle cells, and pericytes2. Elevated blood levels of early EPCs have been found in patients with SSc by different groups of researchers and such levels correlate directly with interstitial lung involvement2,9. In a pro-fibrotic environment—elevated levels of both endothelin-1 (ET-1) and transforming growth factor-beta (TGF-β)—early EPCs differentiate mainly into fibroblasts and promote fibrosis2.\n\n2. Late EPCs are a population of bone marrow-derived cells that are characterized by the phenotype CD14−, CD34+, CD133+, and VEGFR2+, and that are able to differentiate into mature endothelial cells and participate in vasculogenesis. In patients affected by SSc, late EPCs are able to differentiate into myofibroblasts and play a role in the development of fibrosis20. The number of circulating late EPCs is inversely proportional to the SSc disease duration: in the early phase such cells are increased and at late stages they are decreased, as confirmed by different authors4,9,10,20. Lower levels of late EPCs particularly are found in patients with past or current digital ulcers and PAH20. Such cells not only decrease in a late phase of SSc but are also functionally impaired and resistant to in vitro maturation treatments, suggesting a defect in the vasculogenesis process (the failure of new blood vessel formation because of a failure in recruitment and in situ differentiation of late EPCs)4. A plausible explanation for the decrease of late EPCs during the late phase of SSc regards the recruitment into injured tissues of such cells, decreasing the circulating numbers20.\n\nThe importance of CPCs relies on the capacity of such cells to migrate into SSc injury tissues (mediated by CXCR4 /CXCL12 interaction), to differentiate into both endothelial cells and fibroblasts, to cause defective vasculogenesis or fibrosis (or both), and to have immunomodulatory effects19. The prevalence of hematopoietic markers expressed by CPCs that migrate from blood into injury sites in SSc differs and changes according to the degree of differentiation. CXCR4 is the most commonly expressed marker, followed by CD34 and CD45 at the end stage of differentiation15. Such difference also indicates a continuous process of cell differentiation that might relate to the SSc clinical phenotype (degree of fibrosis and vascular involvement).\n\nIn patients with SSc, the fraction of CD14+ monocytes in circulation is higher than the CD14− monocytes and a greater portion of circulating monocytes express Col I, suggesting that SSc monocyte preparations may contain a significant number of Col-producing cells that are partially differentiated into different subtypes of CPCs (MOMCs, FLCs, EPCs, and fibrocytes)14. Such circulating Col-producing cells have an increased migration capacity into injury sites because of the overexpression of CXCR4 and the deficiency in caveolin-1. CPCs that have finished their differentiation process generate fibrocytes that produce Col, extracellular matrix and cause fibrosis at injury sites (skin, lung, kidneys, and so on)15. Interestingly, it has been described that African-Americans may be predisposed to lung fibrosis and SSc because of low baseline caveolin-1 levels in their monocytes, potentially affecting signaling, migration, and fibrocyte differentiation21. The finding that CD14+/Col I+ monocytes are present in the lung tissue of patients with SSc-ILD and not in healthy donors supports this hypothesis15. It is interesting that, in a pro-fibrotic environment (elevated levels of ET-1 and TGF-β), early EPCs that normally give rise to endothelial cells can also differentiate into FLCs and promote fibrosis2. Fibrosis occurs after the activation of tissue-resident fibroblasts and their transdifferentiation into myofibroblasts, but is also due to differentiation of bone marrow-derived CPCs and transition of endothelial epithelial cells, pericytes, and adipocytes into activated mesenchymal cells1,22,23. Fibrocytes (CD14−, CD34+, CD45+, CXCR4+, CCR3, and Col I+), defined as FLCs that differentiate from a different pool of bone marrow-derived monocytic CD14+ progenitor cells, are involved in both ischemic and fibrotic processes in SSc8,19,22,23. It is worth noting that CD14+ circulating monocytes in the presence of T cells give rise to fibrocytes (CD14− cells)22. Fibrocytes cultured with TGF-β or ET-1 downregulate CD34 and upregulate alpha-smooth muscle actin (α-SMA) expression and differentiate into myofibroblasts17. Fibrocytes are considered to be mesenchymal cells that arise from a pool of circulating monocyte precursors24. The number of circulating fibrocytes in patients with idiopathic pulmonary fibrosis directly correlates with exacerbations of the disease, and patients with fibrocytes more than 5% of total circulating blood leukocytes had a worse prognosis than patients with levels under this cut-off19.\n\nBoth late EPCs and FLCs have been found to be significantly increased not only in blood of patients with SSc but also at injury sites (lungs with ILD-SSc)20. Late EPCs contribute to new vessel formation and vascular repair via secretion angiogenic factors under normal conditions, a mechanism that is disrupted in patients with SSc20. FLCs are key effectors of fibrosis11. The number of circulating late EPCs is inversely proportional to the disease duration10,21. Lower levels of late EPCs are found in the late phase of SSc, in patients with diffuse fibrosis, and particularly in patients with past or current digital ulcers and PAH21. Late EPCs not only decrease in a late phase of SSc but also are functionally impaired and resistant to in vitro maturation treatment, suggesting a defective vasculogenesis (the failure in new blood vessel formation because of a failure in recruitment and in situ differentiation of late EPCs)4. The total number of circulating CD45+/pro-Col-1α cells (that might correspond to FLCs and fibrocytes) has been reported to be 0.34 ± 0.12 × 106 cells/ml, and the percentage of such cells between PBMCs to be between 1.34 ± 0.25 (ILD-SSc) and 2.5% (SSc)10,15. CD14+, CD11b+, and Col I+ cells have been reported to be 1.5% of PBMCs in patients with SSc, versus 0.95% in healthy donors (P <0.05)14. EPC frequency in peripheral blood is quite low: 0.01% to 0.0001% of PBMCs20.\n\n\nConclusions and future perspective of circulating progenitor cells in systemic sclerosis\n\nIn the past 15 years, a pool of circulating monocyte precursors has been found to be altered both quantitatively and qualitatively in different sclerosing conditions, including SSc. Such alterations have been partially related to the subtype of SSc (diffuse versus limited forms), the duration of the SSc, and the prominent clinical manifestations (vascular involvement versus fibrosis). The exact role of each subtype of CPCs needs to be further defined. A deeper understanding of the role of each subtype of CPCs in the development of the disease will help us to better classify patients in order to offer them personalized therapeutic approaches in the future25–28. It might also open a door regarding the modulation/regulation of the differentiation of CPCs in order to avoid a pro-fibrotic phenotype and to reverse the altered vascular phenotype of such cells. Autologous hematopoietic stem cell transplantation (HSTC) seems to reintroduce immunological tolerance in patients with SSc, and we hypothesize that such tolerance might be due to the regulation of CPC differentiation. It has been demonstrated that after HSTC there is an improvement of vasculopathy, modified Rodnan skin score, and lung function in patients with SSc26.\n\nThis review had the intention to summarize the available data regarding CPCs in SSc; considering the fact that several studies have been conducted with single CPC subsets, we herein intended to describe the whole spectrum of CPCs in SSc described thus far and their roles in the pathogenesis of SSc. During this review process, we faced several difficulties: the same cell has been studied by different research groups and named differently, several subsets of CPCs that might correspond to the same cell have been described, there are no studies available that compare different subsets of CPCs in the same patients, and there is no direct correlation in the literature between different CPC subsets and clinical manifestations of SSc.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests and received no funding support.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nWei J, Bhattacharyya S, Tourtellotte WG, et al.: Fibrosis in systemic sclerosis: emerging concepts and implications for targeted therapy. Autoimmun Rev. 2011; 10(5): 267–275. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYamaguchi Y, Kuwana M: Proangiogenic hematopoietic cells of monocytic origin: roles in vascular regeneration and pathogenic processes of systemic sclerosis. Histol Histopathol. 2013; 28(2): 175–183. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCutolo M, Sulli A, Smith V: Assessing microvascular changes in systemic sclerosis diagnosis and management. Nat Rev Rheumatol. 2010; 6(10): 578–587. PubMed Abstract | Publisher Full Text\n\nKuwana M, Okazaki Y, Yasuoka H, et al.: Defective vasculogenesis in systemic sclerosis. Lancet. 2004; 364(9434): 603–610. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBucala R, Spiegel LA, Chesney J, et al.: Circulating fibrocytes define a new leukocyte subpopulation that mediates tissue repair. Mol Med. 1994; 1(1): 71–81. PubMed Abstract | Free Full Text\n\nZhao Y, Glesne D, Huberman E: A human peripheral blood monocyte-derived subset acts as pluripotent stem cells. Proc Natl Acad Sci U S A. 2003; 100(5): 2426–2431. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nKuwana M, Okazaki Y, Kodama H, et al.: Human circulating CD14+ monocytes as a source of progenitors that exhibit mesenchymal cell differentiation. J Leukoc Biol. 2003; 74(5): 833–845. PubMed Abstract | Publisher Full Text\n\nSeta N, Kuwana M: Derivation of multipotent progenitors from human circulating CD14+ monocytes. Exp Hematol. 2010; 38(7): 557–563. PubMed Abstract | Publisher Full Text\n\nCampioni D, Lo Monaco A, Lanza F, et al.: CXCR4pos circulating progenitor cells coexpressing monocytic and endothelial markers correlating with fibrotic clinical features are present in the peripheral blood of patients affected by systemic sclerosis. Haematologica. 2008; 93(8): 1233–1237. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nDistler JHW, Allanore Y, Avouac J, et al.: EULAR Scleroderma Trials and Research group statement and recommendations on endothelial precursor cells. Ann Rheum Dis. 2009; 68(2): 163–168. PubMed Abstract | Publisher Full Text\n\nPostlethwaite AE, Shigemitsu H, Kanangat S: Cellular origins of fibroblasts: possible implications for organ fibrosis in systemic sclerosis. Curr Opin Rheumatol. 2004; 16(6): 733–738. PubMed Abstract | Publisher Full Text\n\nYork MR, Nagai T, Mangini AJ, et al.: A macrophage marker, Siglec-1, is increased on circulating monocytes in patients with systemic sclerosis and induced by type I interferons and toll-like receptor agonists. Arthritis Rheum. 2007; 56(3): 1010–1020. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHigashi-Kuwata N, Jinnin M, Makino T, et al.: Characterization of monocyte/macrophage subsets in the skin and peripheral blood derived from patients with systemic sclerosis. Arthritis Res Ther. 2010; 12(4): R128. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nMathai SK, Gulati M, Peng X, et al.: Circulating monocytes from systemic sclerosis patients with interstitial lung disease show an enhanced profibrotic phenotype. Lab Invest. 2010; 90(6): 812–823. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nTourkina E, Bonner M, Oates J, et al.: Altered monocyte and fibrocyte phenotype and function in scleroderma interstitial lung disease: reversal by caveolin-1 scaffolding domain peptide. Fibrogenesis Tissue Repair. 2011; 4(1): 15. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nBinai N, O'Reilly S, Griffiths B, et al.: Differentiation potential of CD14+ monocytes into myofibroblasts in patients with systemic sclerosis. PloS One. 2012; 7(3): e33508. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSchmidt M, Sun G, Stacey MA, et al.: Identification of circulating fibrocytes as precursors of bronchial myofibroblasts in asthma. J Immunol. 2003; 171(1): 380–389. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nQuan TE, Cowper S, Wu S, et al.: Circulating fibrocytes: collagen-secreting cells of the peripheral blood. Int J Biochem Cell Biol. 2004; 36(4): 598–606. PubMed Abstract | Publisher Full Text\n\nStrieter RM, Keeley EC, Hughes MA, et al.: The role of circulating mesenchymal progenitor cells (fibrocytes) in the pathogenesis of pulmonary fibrosis. J Leukoc Biol. 2009; 86(5): 1111–1118. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAvouac J, Juin F, Wipff J, et al.: Circulating endothelial progenitor cells in systemic sclerosis: association with disease severity. Ann Rheum Dis. 2008; 67(10): 1455–1460. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nReese C, Perry B, Heywood J, et al.: Caveolin-1 deficiency may predispose African Americans to systemic sclerosis-related interstitial lung disease. Arthritis Rheumatol. 2014; 66(7): 1909–1919. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nStruyf S, Burdick MD, Proost P, et al.: Platelets release CXCL4L1, a nonallelic variant of the chemokine platelet factor-4/CXCL4 and potent inhibitor of angiogenesis. Circ Res. 2004; 95(9): 855–857. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZaldivar MM, Pauels K, von Hundelshausen P, et al.: CXC chemokine ligand 4 (Cxcl4) is a platelet-derived mediator of experimental liver fibrosis. Hepatology. 2010; 51(4): 1345–1353. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBucala R: Fibrocytes at 20 Years. Mol Med. 2015; 21(Suppl 1): S3–5. PubMed Abstract | Free Full Text\n\nStruyf S, Salogni L, Burdick MD, et al.: Angiostatic and chemotactic activities of the CXC chemokine CXCL4L1 (platelet factor-4 variant) are mediated by CXCR3. Blood. 2011; 117(2): 480–488. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCutolo M, Sulli A, Pizzorni C, et al.: Systemic sclerosis: markers and targeted treatments. Acta Reumatol Port. 2016. PubMed Abstract\n\nvan Bon L, Affandi AJ, Broen J, et al.: Proteome-wide analysis and CXCL4 as a biomarker in systemic sclerosis. N Engl J Med. 2014; 370(5): 433–443. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nVandercappellen J, van Damme J, Struyf S: The role of the CXC chemokines platelet factor-4 (CXCL4/PF-4) and its variant (CXCL4L1/PF-4var) in inflammation, angiogenesis and cancer. Cytokine Growth Factor Rev. 2011; 22(1): 1–18. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13522",
"date": "22 Apr 2016",
"name": "Adriana Georgescu",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13523",
"date": "22 Apr 2016",
"name": "Christopher Denton",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-723
|
https://f1000research.com/articles/5-722/v1
|
22 Apr 16
|
{
"type": "Research Article",
"title": "Report on noninvasive prenatal testing: classical and alternative approaches",
"authors": [
"Kateryna S. Pantiukh",
"Nikolay N. Chekanov",
"Igor V. Zaigrin",
"Alexei M. Zotov",
"Alexander M. Mazur",
"Egor B. Prokhortchouk",
"Nikolay N. Chekanov",
"Igor V. Zaigrin",
"Alexei M. Zotov",
"Alexander M. Mazur",
"Egor B. Prokhortchouk"
],
"abstract": "Concerns of traditional prenatal aneuploidy testing methods, such as low accuracy of noninvasive and health risks associated with invasive procedures, were overcome with the introduction of novel noninvasive methods based on genetics (NIPT). These were rapidly adopted into clinical practice in many countries after a series of successful trials of various independent submethods. Here we present results of own NIPT trial carried out in Moscow, Russia. 1012 samples were subjected to the method aimed at measuring chromosome coverage by massive parallel sequencing. Two alternative approaches are ascertained: one based on maternal/fetal differential methylation and another based on allelic difference. While the former failed to provide stable results, the latter was found to be promising and worthy of conducting a large-scale trial. One critical point in any NIPT approach is the determination of fetal cell-free DNA fraction, which dictates the reliability of obtained results for a given sample. We show that two different chromosome Y representation measures—by real-time PCR and by whole-genome massive parallel sequencing—are practically interchangeable (r=0.94). We also propose a novel method based on maternal/fetal allelic difference which is applicable in pregnancies with fetuses of either sex. Even in its pilot form it correlates well with chromosome Y coverage estimates (r=0.74) and can be further improved by increasing the number of polymorphisms.",
"keywords": [
"noninvasive prenatal testing (NIPT)",
"trisomy",
"aneuploidy",
"cell-free DNA",
"fetal cell-free DNA concentration",
"Down syndrome",
"Edwards syndrome",
"Patau syndrome"
],
"content": "Introduction\n\nAneuploidies can be attributed to cause 30% of miscarriage cases, and affect up to 1 in 300 live births1. Most common autosomal aneuploidies are the trisomies of 21st, 18th and 13th chromosomes1. While still causing various health defects and intellectual disabilities, normally they are not lethal to fetus, in contrast to many other chromosomal abnormalities.\n\nRecently a new noninvasive prenatal testing technology based on sequencing of cell-free DNA from maternal blood was widely implemented in the industry. Blood plasma of a pregnant woman contains cell-free DNA fragments of both maternal and fetal origin. The latter permeates through the placental barrier into the main blood flow. Fetal cfDNA (cffDNA) emerges during the apoptosis of cytotrophoblast cells2. Fetal fraction makes up 10–20% of all blood plasma cfDNA on average, rising through the whole pregnancy duration. After labor it disappears from the blood flow in several hours3. It was shown that fragments of cffDNA uniformly represent the whole genome of the fetus4. Trisomy of a certain chromosome in the fetus may be detected through sequencing of total cfDNA from maternal blood plasma and subsequent counting of reads mapped on each chromosome. Such chromosome would show statistically significant increase in coverage5–7. In 2% of cases at 10th through 21st weeks of gestation, cffDNA fraction comprises less than 4%8. Underrepresentation of fetal genetic material might lead to false negative outcomes, so such cases must be diagnosed by other means.\n\nSequencing of cell-free DNA from maternal blood proved to be a technique which is completely safe, highly accurate, and shows high potential for extendability. Since its introduction into clinical practice in 2011, it has spread quickly and now is available in most developed countries. Its precision was confirmed in a number of studies on hundreds of thousands of samples combined, showing accuracy rates of more than 99%, which is especially intriguing given a wide variety of statistical methods employed by different providers. Here we describe our experience with introduction of NIPT in Russia. The test was developed at the Genoanalytica private laboratory.\n\nWe chose whole-genome low coverage sequencing with GC correction9 as our main method. It doesn't rely on prior knowledge of population and yields stable and reproducible results. 1012 samples were analyzed with the main method to assess its performance. Two additional methods for aneuploidy detection were evaluated: one based on differential DNA methylation between mother and fetus, and another based on difference in allele content.\n\nDetermination of the cffDNA fraction is a crucial part of the NIPT pipeline, as samples with low concentration must be treated with caution. We addressed this issue in the second part of this article. Several techniques for calculation of cffDNA percentage were employed: 1) a method based on RT-PCR detection of sequences coming from Y-chromosome in samples with male fetus; 2) a method based on counting sequenced reads mapped on Y-chromosome in samples with male fetus; 3) a method based on deep sequencing of several highly polymorphic regions to assess differences in allele content between mother and fetus; and 4) a method based on sequencing of polymorphisms with an additional stage for eliminating PCR duplicates. It's worth mentioning that the two latter methods are self-reliant and do not require prior genotyping of either parent.\n\n\nMethods\n\nPatients and sample collection. The study design was approved by the Institutional Review Board of Genoanalytica, CJSC, approval no. 103/2015.\n\nA total of 1012 women participated in the study. All participants gave informed consent for providing their blood samples for scientific purposes. The cohort included cases with both high and low risk of aneuploidies as typical screening procedures suggested. Biochemical or ultrasonographic markers, as well as advanced age (35 years and older) were considered as high risk factors. A karyotyping report for the fetus, or postnatal diagnosis were obtained in all studied pregnancies.\n\nBlood samples were transported to the laboratory in tubes with EDTA at 4°C no longer than 4 hours after drawing. Whole blood was centrifuged for 10 minutes at 1600g twice sequentially. After that plasma was separated and placed in new tubes, which were again centrifuged for 10 minutes at 1600g and then stored at 4°C. Cell-free DNA was extracted from stored blood plasma using QIAamp DNA Circulating Nucleic Acid Kit (Qiagen) according to the manufacturer’s instructions. The amount of DNA was determined on Qubit 2.0 (Invitrogen) using Qubit dsDNA HS Assay Kit (Invitrogen) according to the manufacturer’s instructions.\n\n\nSequencing, bioinformatics analysis and confirmation of results\n\nWhole-genome libraries were prepared according to standard Illumina protocol. Their quality was assessed with Bioanalyzer using High Sensitivity DNA Analysis Kits (Agilent Technologies). 5 to 10 million reads of 50bp length were obtained on HiSeq 1500 (Illumina) for every sample. Sequencing data were processed as in 9, and cffDNA concentration calculated according to 10.\n\nAfter the test every participant was consulted according to her results. Invasive diagnostic procedure (karyotyping via amniocentesis or similar measure) was suggested to women with positive test results; those denying to do so were monitored until the birth to obtain the medical outcome data. For participants with negative test results outcome data was obtained through telephone interview a month after the expected date of birth.\n\n6 blood samples from pregnant women were selected from the main cohort to test the alternative method employing differential DNA methylation. All of them were at gestational age of 12 weeks; 3 were known to be chromosome 21 trisomic (cytogenetically confirmed) and 3 were known to be normal (confirmed after the birth). One additional sample was obtained from a non-pregnant woman.\n\n16 genomic regions known to be differentially methylated between fetal tissues and maternal blood cells11 were assessed: 12 from chromosome 21 and 4 from other chromosomes. Extracted cfDNA underwent bisulphite conversion using Zymo Research EZ DNA Methylation Kit according to its protocol. Genomic libraries were sequenced on Ion Torrent PGM (Thermo Fisher Scientific) using the 316 chip type.\n\nAcquired reads were subjected to filtering by quality (at least having average of Q20) and length (at least having length of 100bp) and mapped to DMRs. Bisulphite conversion percentage and methylation status at the first two CpG positions were then calculated for every DMR.\n\n4 blood samples from pregnant women were selected from the main cohort to test the alternative method based on differences in genotypes of mother and fetus. 2 were known to be chromosome 21 trisomic (cytogenetically confirmed) and 2 were known to be normal (confirmed after the birth). Genome libraries were prepared according to the Ovation Custom Target Enrichment System protocol (NuGen)12. One distinguishing feature of this method is a ligation of random adapter sequence to cfDNA fragments before the amplification. It then can be used to precisely remove PCR duplicates, which otherwise are capable of introducing unwanted allele bias. Sequencing was carried out on a HiSeq 1500 (Illumina). Reads were mapped on reference genome hg19 with bowtie2 and then PCR-duplicates were filtered out using NuGen Ovation Target Enrichment System Data Processing Application ver.1.0.0 (NuGen). SNP-calling was performed with samtools ver.1.1 mpileup. Polymorphisms were classified into either of two groups: homozygous in mother (prevalent maternal allele and minor fetal allele) and heterozygous in mother (no prevalence of either maternal allele with possible slight bias towards one of fetal alleles). Dividing coefficient a was calculated with formula (1):\n\na = Rmin/Rmaj (1)\n\nConcentration of cffDNA was predicted for every SNP. One of the formulas (2,3) was applied depending on the type of polymorphism.\n\nif a > 0.25, C = (Rmaj – Rmin)/Rsum (2)\n\nif а < 0.25, C = 2 * Rmin/Rsum (3)\n\nAll such predictions were combined in two distributions: one based on polymorphisms of chromosome 21 only, and another for all other autosomess (except for 13 and 18 chromosomes). These two distributions were then compared using t-test. Samples with p-value < 0.05 were considered to possess a high risk of aneuploidy. These analyses were performed in R version 3.2.\n\n\nDetermination of cffDNA concentration\n\nAll samples from the main cohort were subjected to a sex determination procedure which also included determination of cffDNA concentration for samples with male fetus. These steps were performed using the method of Jiang et al.13 which employs calculation of chromosome Y coverage with correction of GC-content bias. To evaluate accuracy of this approach cffDNA concentration was also determined using an alternative method based on real-time PCR14 in 10 samples.\n\n15 samples in which cffDNA concentration was determined were selected from the main cohort. They underwent target amplification of highly polymorphic genome regions and then proceeded to standard preparation of sequencing libraries. These regions were defined to maximize the number of SNPs with high MAF (0.3–0.5) in a 200bp span. The target panel included 36 such regions with 220 SNPs in total. SNP coordinates and MAF values were obtained from dbSNP v141 and ExAC databases15. Sequencing was carried out on HiSeq 1500 (Illumina). Each sample yielded 1 to 3 mln reads of 150bp length.\n\nAnother 10 samples from the main cohort were subjected to similar procedures, with a sonication step added before the preparation of genomic libraries. These were sequenced on the same machine, yielding 3 to 5 mln reads of 50bp length per sample. Reads were mapped to reference sequences of regions (which were extracted from human reference genome UCSC hg19) using the bowtie2 ver.2.2.2 software. SNP calling was performed with the samtools ver.1.1 program (mpileup).\n\nAll found polymorphisms were annotated with the following metrics: overall number of reads mapped at the position (raw coverage), number of reads supporting non-reference allele at the position (minor allele coverage), and percentage of reads supporting non-reference allele (minor allele coverage/raw coverage). These percentages were split into two groups (high-MAF with percentages ranging from 35% to 65%, and low-MAF for others). A set of theoretical distributions was prepared to compare with the distribution of high-MAF percentages. It included a normal distribution with a peak at 50% (representing the case with zero percentage of cffDNA), and a sum of two normal distributions with peaks at 50% and 50±1/2x% (x representing the concentration of cffDNA) for every x in range from 1 to 25. The one theoretical distribution which correlates best with the observed distribution would yield the percentage of cffDNA.\n\nSample selection, experimental procedures and calculation details are described in the respective section of methods for aneuploidy detection. Contrary to the aneuploidy detection method, here percentage of cffDNA was calculated not for every chromosome separately, but for all autosomes combined (save for 13, 18 and 21, as these are susceptible to trisomies). Resulting cffDNA percentage was calculated as average of cffDNA concentration values in all polymorphisms. These analyses were performed in R version 3.2.\n\n\nResults\n\n\n\n\nAneuploidy detection (whole genome low-coverage)\n\n1012 blood samples of pregnant women were collected in a period from April 2014 through April 2015. Patients came from 47 medical institutions, as well as independently, across 16 federal subjects of Russia. The average age of participants was 35 years; the youngest was 20, and the oldest 51. Gestation ages were in the range of 10 to 24 weeks, with a median of 14. The average concentration of cffDNA was 11%.\n\nFor 30 out of 1012 samples (2.9%) a high risk of either aneuploidy was predicted: 25 were T21, 4 T18 and 1 T13. Of these, 24 cases were confirmed via karyotyping (22 T21 and 3 T18), and 3 failed such confirmation (1 T21, 1 T18, 1 T13). 1 other case of predicted T21 was confirmed after childbirth via standard medical examination of the newborn. 2 cases of predicted T21 could not be confirmed due to loss of contact with the participant. Figure 1 describes different indications and outcomes in 30 cases of detected aneuploidies.\n\nA negative result (low risk of either aneuploidy) was returned in 982 cases. Of these, in 813 cases (82.8%) pregnancy ended with labor and thus confirmation was obtained. One case was a false-negative.\n\nMethod accuracy metrics are presented in the Table 1. Some of the metrics there are affected by small sample sizes, and will be reevaluated later as the number of participants grows.\n\nWith regards to trisomies of chromosome 13, only one case of elevated risk was encountered. This particular result failed to replicate through karyotyping though. The precision of T13 detection with the method was not calculated due to the small sample size.\n\nHere we will define DMRs as regions of genome highly methylated in DNA of fetal origin, but with low methylation in maternal DNA. Concentration of cffDNA thus could be assessed as the percentage of methylated reads obtained by cell-free DNA sequencing targeted at these particular DMRs. Levels of methylation were determined separately for DMRs on chromosome 21 and for control DMRs coming from all other autosomes save for chromosomes 13 and 18. Three groups of samples were considered: pregnant women (fetus with normal karyotype), pregnant women (fetus with T21) and one non-pregnant woman. Both chromosome 21 and control DMRs showed high within-group variance of methylation (Figure 2). Methylation of control DMRs was unexpectedly high and did not differ significantly when compared between pregnant and non-pregnant women. Only the 2nd and 9th DMRs of chromosome 21 clearly indicated such difference. We expected methylation levels to rise in chromosome 21-trisomic samples compared to normal ones when considering DMRs of chromosome 21, while DMRs of control chromosomes would show no such change. However, in most cases there was no significant change, except for DMR7. DMR3 also exhibited it, but variation of methylation levels in normal samples made it insignificant.\n\nA: DMRs of control chromosomes. B: DMRs of chromosome 21.\n\nHigh within-group variation may be explained either by individual differences or by heterogeneity of sources of cffDNA. CffDNA mainly originates from the cells of placenta and chorionic cilia, so the observed pattern of DNA methylation might be biased by interference of different epigenetic profiles.\n\nNegative factors such as individual differences and nonsignificant maternal-fetal methylation ratios prevent this method from immediate application in clinical NIPT. These may be alleviated through introduction of more suitable DMRs.\n\nThis method is based on estimating cffDNA fractions for SNPs in every autosome separately and measuring shift of their distribution in the chromosome of interest. In this study we tested the method on 10 samples (5 normal and 5 with trisomy of chromosome 21). Figure 3 provides examples of these distributions.\n\nA and B: samples with chromosome 21 trisomic fetus. C and D: samples with normal fetus.\n\nShift of cffDNA fractions' distribution was assessed with t-test; p-value of 0.05 was enough to correctly discern normal samples from problematic ones. However it is worth mentioning that p-values between these series were only one order of magnitude apart, which may point at the risk of low confidence and beg for further inquiry.\n\n\nCalculation of cffDNA fraction\n\nWe have discovered a very high correlation between cffDNA concentration predictions (r=0.94) obtained from real-time PCR and NGS-based chromosome Y presence detection (Figure 4). We thus conclude that results of both methods closely reflect the real fraction.\n\nAs NGS-based method doesn't require any additional experimental procedures we selected it as the reference to compare proposed alternative methods to.\n\nWe have determined allele frequencies of polymorphisms and displayed them in the form of distributions. Figure 5.A shows an example of such distribution in comparison with theoretically expected distribution for a sample with a given cffDNA fraction. 3 peaks can be seen near MAF of 50%. These are SNPs in following maternal-fetal genotype configurations: ABmABf, ABmAAf and ABmBBf. Peaks near both extremes of 0% MAF exhibit a higher level of background noise and slightly differ from theoretically expected values. There are also some SNPs with MAF of 15–40% which are quite unlikely in theory. Existence of these polymorphisms may be explained by structural variations of genomic region or by uneven amplification favoring certain alleles over their counterparts, which may be very pronounced in highly polymorphic regions with tens of SNPs per amplicon. The latter hypothesis was confirmed after closer examination of unlikely polymorphisms: whereas in every sample they came typically from the same region, these regions did not replicate between different samples.\n\nA and B: distribution of allele frequencies of polymorphisms. Theoretical distribution for 12% cffDNA fraction shown in purple. C: Results of cffDNA fraction estimation based on allele frequencies of polymorphisms and NGS method.\n\nLarge numbers of SNPs tend to have MAF near 0% and may be explained by sequencing errors. Those with an alternative allele percentage of 100% are probably sites where both the mother and fetus have the same genotype.\n\nSome samples did not exhibit peaks at all (Figure 5.C), probably because of absence of SNPs in required genotype configurations, which is expected from the fact that method doesn't require prior knowledge of parents' genotypes and instead relies on SNPs with high penetrance in the population. Introduction of additional regions and polymorphisms in them will overcome this issue.\n\nHigh levels of background noise near 0% MAF prompted exclusion of these peaks, and further analysis was performed only on central ones. Concentration of cffDNA was calculated for 15 samples. Resulting values did not show correlation with the reference results (r=0.11, Figure 5.B). This fact suggests the need for method enhancement, primarily via a) using larger numbers of examined polymorphisms and regions, and b) elimination of PCR-introduced allele bias. Further we describe one approach to achieve this.\n\nAnother batch of samples was subjected to the modified approach. We employed an additional experimental technique to mark sequences originating from the same molecule during PCR, and changed the algorithm to calculate the cffDNA fraction separately for every found polymorphism; overall sample fraction would be the average of these. Per-SNP cffDNA fractions formed a gamma distribution, examples are presented in Figure 6. With these modifications in action, correlation with reference results reached 0.74. This marks the discussed method as a viable choice for further study in a sufficiently big sample cohort to allow it later for a commercial application.\n\n\nConclusion\n\nOne of the aims of the current study was to assess the precision of our specific method in comparison to other NIPT techniques16–18. Sensitivity and specificity values obtained with the method regarding trisomy of chromosome 21 (95.6% and 99.8%, respectively) are in a good concordance with those of other reported NIPT practices. Determination of sensitivity and specificity for the 18th and 13th chromosomes will require bigger sample size due to small numbers of detected trisomies (4 and 1, respectively) and their lower incidence in general.\n\nAs expected, aneuploidies occurred more often in pregnancies of older women: 21 cases in a group of 35 years and older compared to 9 cases in those younger than 35 years. In the latter group 4 cases already had biochemical and/or ultrasonographic indications, and the other 5 had results of primary screening unknown. A group of younger women without any biochemical indications of elevated risk did not yield NIPT risk as well. On the contrary, in a group of women older than 35 years aneuploidies were detected in all subgroups, even in samples without biochemical or ultrasonographic risk indications.\n\nWe have shown that introducing an additional experimental step to eliminate PCR duplicates greatly enhances the precision of determining cffDNA concentration. Here it was implemented using the commercially available general purpose panel, yet further focusing only on relatively small number of polymorphisms with high MAF would be preferential due to lower coverage requirements and therefore lower sequencing costs.\n\nDetection of aneuploidies through the estimation of cffDNA fraction shift between the chromosome in question and control autosomes shows some potential, but the statistical power of its current implementation might raise concerns enough to delay its in-field deployment. We propose further inquiry into the underlying mathematical models and expansion of sample sizes.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details and/or clinical images was obtained from the patient/parent/guardian/relative of the patient. The study design was approved by the Institutional Review Board of Genoanalytica, CJSC, approval no. 103/2015.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for 'Report on noninvasive prenatal testing: classical and alternative approaches’, Pantiukh et al. 2015, 10.5256/f1000research.8243.d11868619\n\nThe raw sequencing data are available at the NCBI Sequence Read Archive (http://www.ncbi.nlm.nih.gov/sra), accession number SRP072416.",
"appendix": "Author contributions\n\n\n\nPKS, MAM and PEB conceived the study. PKS, CNN, MAM and PEB designed the experiments. CNN implemented the whole-genome low-coverage aneuploidy detection method. PKS, ZIV and ZAM implemented polymorphism-based methods. PKS and MAM carried out experimental work. PKS and CNN drafted the manuscript. All authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nGenoanalytica, CJSC is a commercial provider of the product which is based on methods described in current paper. All affiliated authors are the employees of said company.\n\nOther authors declare no competing interests.\n\n\nGrant information\n\nThis study was supported by Ministry of Education and Science of the Russian Federation via agreement on subsidy allocation No. 14.576.21.0069 (unique identifier of applied scientific project RFMEFI57614X0069). Subsidy was granted to Genoanalytica, CJSC.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nGriffiths AJF, Miller JH, Suzuki DT, et al.: An Introduction to Genetic Analysis. 7th edition. New York: W. H. Freeman; 2000. Reference Source\n\nDondorp W, de Wert G, Bombard Y, et al.: Non-invasive prenatal testing for aneuploidy and beyond: challenges of responsible innovation in prenatal screening. Eur J Hum Genet. Nature Publishing Group; 2015; 23(11): 1438–50. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHochstenbach R, Nikkels PG, Elferink MG, et al.: Cell-free fetal DNA in the maternal circulation originates from the cytotrophoblast: proof from an unique case. Clin Case Rep. 2015; 3(6): 489–91. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWong FC, Lo YM: Prenatal Diagnosis Innovation: Genome Sequencing of Maternal Plasma. Annu Rev Med. 2016; 67(1): 419–32. PubMed Abstract | Publisher Full Text\n\nLi PQ, Zhang J, Fan JH, et al.: Development of noninvasive prenatal diagnosis of trisomy 21 by RT-MLPA with a new set of SNP markers. Arch Gynecol Obstet. 2014; 289(1): 67–73. PubMed Abstract | Publisher Full Text\n\nFan HC, Blumenfeld YJ, Chitkara U, et al.: Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci U S A. National Acad Sciences, 2008; 105(42): 16266–71. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChiu RW, Chan KC, Gao Y, et al.: Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma. Proc Natl Acad Sci U S A. National Acad Sciences, 2008; 105(51): 20458–63. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhang H, Gao Y, Jiang F, et al.: Non-invasive prenatal testing for trisomies 21, 18 and 13: clinical experience from 146,958 pregnancies. Ultrasound Obstet Gynecol. 2015; 45(5): 530–8. PubMed Abstract | Publisher Full Text\n\nWang E, Batey A, Struble C, et al.: Gestational age and maternal weight effects on fetal cell-free DNA in maternal plasma. Prenat Diagn. 2013; 33(7): 662–6. PubMed Abstract | Publisher Full Text\n\nJiang P, Chan KC, Liao GJ, et al.: FetalQuant: deducing fractional fetal DNA concentration from massively parallel sequencing of DNA in maternal plasma. Bioinformatics. 2012; 28(22): 2883–90. PubMed Abstract | Publisher Full Text\n\nLim JH, Lee da E, Park SY, et al.: Disease specific characteristics of fetal epigenetic markers for non-invasive prenatal testing of trisomy 21. BMC Med Genomics. 2014; 7(1): 1–11. PubMed Abstract | Publisher Full Text | Free Full Text\n\nA single workflow for targeted analysis of CNVs, SNPs and mutations - the Ovation®. Target Enrichment System Luke Sherlin, Doug Amorese, Stephanie Huelga, Ashesh Saraiya, I-Ching Wang, Joe Don Heath NuGEN Technologies, Inc., 201 Industrial Road, Suite 310, San Carlos, CA 94070. Reference Source\n\nJiang F, Ren J, Chen F, et al.: Noninvasive Fetal Trisomy (NIFTY) test: an advanced noninvasive prenatal diagnosis methodology for fetal autosomal and sex chromosomal aneuploidies. BMC Med Genomics. BioMed Central Ltd; 2012; 5(1): 57. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJohnson KL, Dukes KA, Vidaver J, et al.: Interlaboratory comparison of fetal male DNA detection from common maternal plasma samples by real-time PCR. Clin Chem. 2004; 50(3): 516–21. PubMed Abstract | Publisher Full Text\n\nExome Aggregation Consortium, Monkol Lek, Karczewski K, et al.: Analysis of protein-coding genetic variation in 60,706 humans. BioRxiv. 2015. Publisher Full Text\n\nDar P, Curnow KJ, Gross SJ, et al.: Clinical experience and follow-up with large scale single-nucleotide polymorphism-based noninvasive prenatal aneuploidy testing. Am J Obstet Gynecol. Elsevier Inc; 2014; 211(5): 527.e1–527.e17. PubMed Abstract | Publisher Full Text\n\nMcCullough RM, Almasri EA, Guan X, et al.: Non-invasive prenatal chromosomal aneuploidy testing--clinical experience: 100,000 clinical samples. Zwick ME, editor. PLoS One. 2014; 9(10): e109173–9. PubMed Abstract | Publisher Full Text\n\nFutch T, Spinosa J, Bhatt S, et al.: Initial clinical laboratory experience in noninvasive prenatal testing for fetal aneuploidy from maternal plasma DNA samples. Prenat Diagn. 2013; 33(6): 569–574. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPantiukh K, Chekanov N, Zaigrin I, et al.: Dataset 1 in: Report on noninvasive prenatal testing: classical and alternative approaches. F1000Research. 2016. Data Source"
}
|
[
{
"id": "13521",
"date": "13 Jun 2016",
"name": "Fyodor D Urnov",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe well-established positive correlation between maternal age and the incidence of newborns bearing chromosomal trisomies, combined with the decision that many women make to bear children later in life, makes prenatal genetic diagnostics both a field of major public health impact, and of relevance to individual women making reproductive choices. This places a significant burden of responsibility on the molecular geneticists developing such diagnostic methods to ensure their ease, scalability, sensitivity (ability to detect an aneuploidy), and specificity (not raising a false alarm). In this field, therefore, the excellent truly is the enemy of the good. Prenatal genetic testing, traditionally performed by invasive techniques, has in the past decade been replaced -- as a first-pass diagnostic -- with non-invasive genetic testing (NIPT), which is based on (1) the presence in maternal circulation of DNA of fetal origin and (2) the ability to use deep sequencing to karyotype the fetus at the molecular level. This approach has been reduced to routine clinical practice but, as is always the case, there is room for improvement. Pantiukh and colleagues present their findings on over 1,000 pregnancies in which both prenatal molecular analysis and newborn karyotype status are available, thus allowing an evaluation of novel methods for fetal karyotyping. The application of whole-genome low-coverage deep sequencing yielded data with clinical-grade sensitivity and specificity. Several additional approaches were evaluated, with variable, but in all cases informative, levels of success. In particular, an attempt to use epigenome profiling based on measuring DNA methylation levels, failed to provide robustly predictive results because of both experimental noise and variability in methylation itself. In contrast, an approach that uses SNP-based \"counting\" of alleles, while in need of further development, clearly shows potential. Overall the data in the paper give one confidence that building on existing approaches, in combination with novel ways to analyze fetal DNA, will continue to provide women with an ever-improving array of ways to make informed decisions about their reproductive choices.",
"responses": []
},
{
"id": "16320",
"date": "04 Oct 2016",
"name": "Sergey Nikolaev",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper by Pantiukh et al. reports the results of the two novel NIPT approaches for the detection of aneuploidies.\nThe work is performed on a large cohort of 1012 patients, all using appropriate controls. One of the methods under evaluation employs differential methylation status between cell free DNA in maternal blood of maternal and fetal origin. It is a very interesting idea to use this phenomenon for NIPT, which may have led to cost effective and fast diagnosis but unfortunately did not render promising results.\nHowever the other method, which is based on the assessment of VAFs of 220 common polymorphisms, is probably more promising. The presented results reached the correlation of 0.74 with the reference, which is still quite modest for the standards of diagnostics, but has potential for improvement with the increase of the number of tested SNPs. Among the disadvantages of this technique, which may potentially preclude it from wide use, is the utilization of sequence capture step which is time and labor consuming. Moreover, precap-PCR may bias the VAF distribution.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-722
|
https://f1000research.com/articles/5-721/v1
|
22 Apr 16
|
{
"type": "Research Article",
"title": "Uptake of dietary milk miRNAs by adult humans: a validation study",
"authors": [
"Amanda Auerbach",
"Gopi Vyas",
"Anne Li",
"Marc Halushka",
"Kenneth W. Witwer",
"Amanda Auerbach",
"Gopi Vyas",
"Anne Li",
"Marc Halushka"
],
"abstract": "Breast milk is replete with nutritional content as well as nucleic acids including microRNAs (miRNAs). In a recent report, adult humans who drank bovine milk appeared to have increased circulating levels of miRNAs miR-29b-3p and miR-200c-3p. Since these miRNAs are homologous between human and cow, these results could be explained by xeno-miRNA influx, endogenous miRNA regulation, or both. More data were needed to validate the results and explore for additional milk-related alterations in circulating miRNAs. Samples from the published study were obtained, and 223 small RNA features were profiled with a custom OpenArray, followed by individual quantitative PCR assays for selected miRNAs. Additionally, small RNA sequencing (RNA-seq) data obtained from plasma samples of the same project were analyzed to find human and uniquely bovine miRNAs. OpenArray revealed no significantly altered miRNA signals after milk ingestion, and this was confirmed by qPCR. Plasma sequencing data contained no miR-29b or miR-200c reads and no intake-consistent mapping of uniquely bovine miRNAs. In conclusion, the results do not support transfer of dietary xenomiRs into the circulation of adult humans.",
"keywords": [
"Milk",
"miRNA",
"xenomiR",
"plasma",
"PBMC",
"diet",
"extracellular vesicles"
],
"content": "Introduction\n\nConfirmation that microRNAs (miRNAs) from the diet, or dietary xenomiRs1, could be taken up into mammalian circulation and influence gene expression in the ingesting organism would be a paradigm-shifting development in our understanding of nutrition and cross-organism communication. In animals, mature miRNAs are short oligonucleotides that bind with imperfect complementarity to target sequences in longer RNA molecules including messenger RNAs (mRNAs)2. Loaded into proteins known as Argonautes (AGOs) that recruit additional protein constituents of RNA-induced silencing complexes (RISCs)3–5, miRNAs may achieve cleavage, translational repression, or sequestration of target molecules, usually resulting in minor post-transcriptional adjustments that fall within the range of normal physiologic variation6, although larger effects have also been described.\n\nMilk is a reported potential source of small RNA molecules in the diet7. The nutritional content of milk includes extracellular vesicles, fat globules, and other structures8, some of which contain miRNAs9. In contrast with plant sources, in which foreign AGO-inferred protection of miRNAs could also preclude uptake and function in mammalian cells, mammalian miRNAs in the diet could be protected by proteins that might function in recipient cells. Baier et al. reported transient increases of two miRNAs, miR-29b-3p and miR-200c-3p, in circulating plasma and peripheral blood mononuclear cells (PBMCs) of human donors who drank bovine milk10. In this study of five subjects, blood was drawn at baseline (T0) and at several intervals after milk intake (including T3, T6, T9 and T24). Peak levels of miR-29b and miR-200c were observed at T3 in plasma and at T6 in PBMC. The authors hypothesized that these additional miRNA copies were xenomiRs, supplied by the cow milk as these bovine and human miRNAs are 100% identical. An alternative hypothesis11 suggests that glucose-sensitive endogenous miRNAs, including these two miRNAs12–15, could respond to dietary intake.\n\nConsidering the tremendous implications of these findings for the xenomiR delivery hypothesis, we approached Baier et al. and offered to profile additional miRNAs. We hypothesized that more data would help to assess the not necessarily mutually exclusive explanations of the original results: xenomiR delivery or endogenous regulation. The authors generously provided a selection of the original samples. We jointly decided to profile miRNAs at baseline and at the reported peak miRNA concentration for each sample type to look for additional alterations in miRNAs. Accordingly, 10 plasma-derived RNA samples (5 subjects at T0 and T3) and 10 PBMC-derived RNA samples (5 subjects at T0 and T6) were assessed with TaqMan medium-density OpenArray technology arrays and individual miRNA qPCR assays. Finally, these data were compared with small RNA sequencing (RNA-seq) results collected from the same study materials by an independent facility.\n\n\nMaterials and methods\n\nPlasma samples and PBMC total RNA samples, prepared as previously described during an institutional review board-approved study10, were sent to the authors’ laboratory by overnight delivery from the University of Nebraska, Lincoln. No identifying information about the donors was provided. Samples included 10 aliquots of T0 and T3 plasma and 10 T0 and T6 PBMC RNA aliquots from the five participants of the initial study10. Although the package arrived on time via overnight delivery, the dry ice within had largely sublimated. Plasma RNA was isolated using the Exiqon \"miRCURY RNA Isolation Kits - Biofluids\" (Product # 300112) with modifications as previously described16. PBMC RNA quantity and quality was checked by NanoDrop spectrophotometer (Thermo Scientific). Selected miRNAs were assessed by individual qPCR assays (see below under “qPCR assays”).\n\nA custom miRNA OpenArray chip (Thermo Fisher) was designed to detect miRNAs that are consistently found at relatively high abundance in cell-free body fluids such as blood plasma. Features included 220 miRNAs and three non-miRNA small RNAs, RNU44, RNU48, and snRNA U6 (although these are not necessarily suitable references for extracellular RNA). The highly conserved and abundant plant miRNA MIR159a served as a negative control. MIR159a is not expected to be found in mammalian samples, and, if detected, is likely a sign of environmental contaminants17,18. As expected, MIR159a did not amplify in any sample.\n\nSample processing. RNA (3 ul plasma RNA or 100 ng PBMC RNA) was reverse-transcribed with the MegaPlex ‘A’ pool of reverse transcription primers (Thermo Fisher). cDNA was pre-amplified using MegaPlex ‘A’ primer pools for a cycle number of 14 (plasma) or 12 (PBMC). Pre-amplified material was diluted per manufacturer’s protocol and as previously described19 and loaded onto the custom TaqMan OpenArray slides by liquid handling robot in the Johns Hopkins DNA Analysis Facility. Quantitative PCR was run for 40 cycles on a QuantStudio instrument.\n\nData retrieval and analysis. Data including amplification score and relative threshold cycle (Crt) were retrieved using ExpressionSuite software (Thermo Fisher, v1.0.3). Data were analyzed and visualized using Microsoft Excel for Mac 2011, Version 14.5.4, R version 3.2.1, and the Multiple Experiment Viewer (MeV, Version 10.2, part of the TM4 Microarray Software Suite)20.\n\nData have been deposited with the Gene Expression Omnibus [GEO21,22, RRID:SCR_004584] under accession numbers GSE79922 (PBMC) and GSE79960 (plasma).\n\nRaw Crt values were normalized by several methods. For plasma, correction factors were calculated based on the geometric mean of the Crts of 22 relatively invariant features (“GM22”) or on Crt of miR-16, a biofluids reference commonly employed in the literature that, while not appropriate in every case, was relatively invariant in these plasma RNA samples. For PBMC, a correction factor was calculated based on the geometric mean of Crt values of 26 features (including the average of U6 readings) that were selected for relatively low variability (“GM26”). A larger number of reference features were selected for the PBMC dataset because of the proportionally larger total number of apparently detected features. A second correction factor was based on the geometric mean of Crt values for the three non-miRNAs on the array, RNU44, RNU48, and the average of U6, which have been used in previous studies as reference RNAs for intracellular RNA expression (“RN3”). Separately, for both plasma and PBMC RNA, quantile normalization was performed, using all RNAs that were detected in at least 9 of 10 samples. Three different adjustments were thus performed for both the plasma and PBMC datasets.\n\nBecause of the small number of samples, we performed paired sample t-tests in Microsoft Excel for Mac 2011 v14.5.4 for those miRNAs with complete pre-to-peak sample pairs and considered results potentially significant at p < 0.01.\n\nHierarchical clustering of plasma or PBMC data, filtered by amplification score and for detection in 9 of 10 samples, then adjusted or not via the normalization strategies outlined above, was performed with the Multiple Experiment Viewer v10.2. Data were mean-centered across features. Hierarchical clustering was performed for all samples and features using Pearson correlation and average linkage.\n\nIsolated RNA (different plasma source from the above) was aliquoted, frozen at -80 C, and then thawed and left at 22 C for 24, 8, 4, or 0 hours. Quantitative PCR assays (see below) were then used to assess levels of hsa-miR-16-5p and spiked-in cel-miR-39.\n\nStem-loop reverse transcription quantitative PCR assays23 were performed as previously described16. Input was normalized by volume (3 ul for plasma RNA) or mass (33 ng/reaction for PBMC RNA). Assays were ordered from Applied Biosystems/Thermo Fisher, under Inventoried Cat. # 4427975: hsa-miR-1-3p (002222), hsa-miR-16-5p (000391), hsa-miR-125b-5p (000449), hsa-miR-223-3p (002295), hsa-miR-29b-3p (000413), ath-MIR156a (000333), ath-MIR166a (000347), and cel-miR-39 (000200); and ath-MIR167a (000348) under \"Made to Order\" Cat. # 4440886.\n\nRNA sequencing data (BioProject ID PRJNA307561) were downloaded from the Sequence Read Archive and processed on a local server. Analysis was done with miRge [24, output: raw and rpm counts for human mapping], Chimira release 1 [25, output: raw and normalized by DESeq2 v3.226 for human and bovine], and Bowtie v1.1.2 [27, RRID:SCR_005476, mapping to human sequences in miRBase v2128. Sequences were obtained from miRBase v21 for human and bovine comparisons, and milk miRNA profiling data were sought from several previous publications9,29.\n\n\nResults\n\nThe packaging of the shipped samples demonstrated marked sublimation of the dry ice. To assess the stability of the samples, PBMC RNA was measured by spectrophotometer and assessed with stem-loop reverse transcription miRNA qPCR assays for miRs-16, -125b, and -223. This showed limited evidence of degradation, since the signal from each miRNA was consistent across samples (Table 1) with two exceptions: the zero time point PBMC samples of subjects 4 and 5 amplified 1.9 and 5.8 cycles later, respectively, than the average. There was no indication of general degradation, and it remains unclear whether the two later-amplifying samples were different prior to transport or only after. Plasma stability is less of a concern, since biofluid miRNAs are protected by close association with AGO proteins, whether inside or outside of extracellular vesicles (EVs). Nevertheless, we used qPCR to assess miR-16 stability and that of a spiked-in RNA, cel-miR-39, finding good agreement across samples (Table 1). Furthermore, RNA samples that were placed at room temperature (22 C) for 0 to 24 hours showed no evidence of degradation of an endogenous or a spiked-in RNA (Figure 1). We elected to proceed with profiling of all samples, including the two later-amplifying PBMC samples.\n\nIndicated miRNAs from plasma and PBMC were measured by stem-loop qPCR assays to discover any indications of sample degradation during transport. Shown are average Cq (cycle of quantitation) values across samples as well as standard deviation. For the PBMC samples, removing the two T0 outliers from donors 4 and 5 substantially reduced the variability.\n\nRNA was isolated by the Exiqon Biofluids method from an archived sample of plasma and aliquoted and frozen. Aliquots were thawed and allowed to sit at room temperature (22 C) for 0, 4, 8, or 24 hours. qPCR was used to assess miR-16 and spiked-in cel-miR-39 levels. Shown are +/- 1 standard deviation for triplicate measurements.\n\nResults overview. A total of 223 microRNAs and small RNA controls were assayed by custom qPCR OpenArray, with 134 plasma miRNAs showing amplification in at least 9 of 10 samples. 118 miRNAs were detected in all samples. In RNA from PBMCs, 167 miRNAs amplified in at least 9 of 10 samples, while 135 miRNAs amplified in all samples.\n\nAnalysis criteria. We employed an inclusive approach toward identifying miRNAs that differed between baseline (T0) and peak (either T3 or T6) due to the relatively small number of subjects. No p value or false discovery rate corrections were performed. Instead, we flagged as potentially interesting those features that: 1) were detected in at least 9 of 10 samples (and thus supplied at least four of a possible five complete T0-to-peak sample pairs); and 2) had an uncorrected p value by paired t-test of < 0.01. The same criteria were applied to both plasma and PBMC data.\n\nPlasma miRNA results. As shown in Table 2, no plasma miRNAs fulfilled the above inclusion criteria as being altered by milk intake in the raw dataset. Several miRNAs had a nominally significant p value in the normalized datasets. However, there was no overlap between the miRNAs identified in the variously normalized data, indicating a lack of robustness of the findings. These arbitrary findings likely represent type 1 error due to the uncorrected p value cutoff. Furthermore, the average fold change for each feature was less than two fold, with a maximum average upregulation of 92% and a maximum downregulation of 36%.\n\nShown are miRNAs that satisfied an arbitrary uncorrected p value (“uncorr. p”) of 0.01 by two-tailed paired t-test, in data normalized variously for plasma: none, GM22 (geometric mean of 22 invariant features), 16 (miR-16), and QN (quantile normalization); and for PBMC: none, GM26 (geometric mean of 26 invariant features), RN3 (geometric mean of U6, RNU44, and RNU48), and QN (quantile normalization). Average fold change (avg FC) across donors is also shown.\n\nPBMC miRNA results. In the PBMC dataset, miR-142-3p was identified in the quantile-normalized dataset, but was not identified under any other normalization strategy (Table 2). Again, this likely represented type I error. No other miRNAs that differed between time points were identified including those previously evaluated (miR-200c, miR-29b, miR-1)1. Our lack of finding any additionally variant miRNAs due to milk feeding and our inability to replicate the prior study led us to further examine miR-29b and miR-200c.\n\nIt is possible that expression changes would not reach statistical significance but could still provide some support for the uptake hypothesis, for example, if small increases occurred consistently in all sample pairs or if large but variable fold changes were observed. Therefore, we examined the data for miR-29b and miR-200c for any trends.\n\nPlasma miR-29b. In plasma samples, miR-29b did not amplify consistently and did not satisfy our inclusion criteria above (Crt for only 7 of 10 samples and three complete sample pairs). When we examined these values individually, there was no evidence for intake-related increases. miR-29b appeared to increase slightly for donor 1, but to decrease for donors 2 and 3 (raw values). Following normalization by GM22 or miR-16, there was a decrease in all three complete sample pairs. As for other miRNAs examined, these differences were not statistically significant (Table 3).\n\nResults are shown for normalization techniques for plasma: none, GM22 (geometric mean of 22 invariant features), 16 (miR-16), and QN (quantile normalization); and for PBMC: none, GM26 (geometric mean of 26 invariant features), RN3 (geometric mean of U6, RNU44, and RNU48), and QN (quantile normalization). “NA” = not applicable (miRNA data did not satisfy inclusion criteria), “p” = p value (two-tailed paired t-test with no corrections), “FC” = fold change.\n\nPlasma miR-200c. miR-200c-associated signal was detected in all plasma samples. This miRNA experienced a slight average downregulation from 0 to 3 hours by 15 to 40% depending on normalization. Although downregulation was observed in four sample pairs (normalized data) or three (raw data), no changes were significant by paired t-test (Table 3).\n\nPBMC miR-29b and miR-200c. For PBMC samples, the raw miR-29b and miR-200c signals were upregulated by 67% and 93%, respectively, on average (Table 3). These changes were driven by the donor 4 and 5 T0 samples, which quality control had already identified as having abnormally high Cq values. Following normalization, miR-29b and miR-200c became slightly downregulated.\n\nHierarchical clustering was performed to find possible milk-intake-related patterns that were potentially consistent with relationships between samples obtained at the same time points (baseline versus peak) for the entire miRNA dataset. For raw, unadjusted plasma data, samples clustered by donor, not by time point (Figure 2A). After normalization, no consistent pattern (time point or individual) remained (Figure 2B; shown is analysis of quantile-normalized data; similar results were obtained from otherwise normalized data, not shown). Similar results were also seen for PBMC data (Figure 3; as above, results from only raw and quantile-normalized data are shown).\n\nHierarchical clustering was performed by Pearson correlation and average linkage and conducted for all features from T0 and T3 (previously reported peak of milk-derived RNA expression) using raw data (A) or quantile-normalized data (B) from OpenArray profiling of miRNA. Sample notation “P_1_0” indicates plasma, donor 1, at the 0 hr time point. Each color represents one donor.\n\nSample notation “C_1_0” means cellular (PBMC) RNA, donor 1, at the 0 hr time point. Hierarchical clustering of raw (A) and quantile-normalized data (B) are shown.\n\nIt is possible that some array-based assays may be less sensitive than standard, higher-volume qPCR assays (10–25 microliters) because of input RNA volume differences. In particular, miR-29b was not detected in all samples, so trends may have been missed. To gather more data on miR-29b if possible, we used individual qPCR assays to probe miR-29b expression and that of known high- and low-expressed miRNAs (miRs-16 and -1). As negative controls, we measured several foreign RNAs (plant miRNAs MIR156a, 166a, and 167a) that are expected to be present negligibly if at all in human plasma. (Also, plant miRNAs are probably not found in milk30.)\n\nControl miRNAs. Cq values for miR-16, often used as a control in circulating miRNA studies, were fairly stable across samples, with no obvious pattern of alteration following milk intake (Figure 4A and Table 1). Only one group of technical triplicates (subject 2, T3) displayed standard deviation of > 0.4 Cq (CqSD). A miRNA normally found at low levels in circulation is miR-1. This largely cardiac and skeletal muscle-specific miRNA may serve as a reliable biomarker of muscle injury precisely because of its normally low abundance in blood31. The low abundance and late detection (all Cq > 32) of miR-1 contributed to large variation in readings even between technical replicates (Figure 4A, most CqSD > 0.4).\n\n(A) miR-16 is detected reliably in plasma with Cq in the low 20s, while miR-1 is detected only in the 30s, with high variability. (B) miR-29b-associated signal is detected only late, with no obvious pattern between pre (0) and post (3) milk intake, and is in the same range as spuriously detected plant miRNA-associated signals (C) for ath-MIR156a, -166a, and 167a. * = Cq standard deviation (CqSD) > 0.4. Throughout, the data points are labeled in the format “miRNA_donor_time point”, and replicate measurements are indicated by differently shaded symbols.\n\nLow miR-29b signal. miR-29b was associated with amplification at even higher Cq values than miR-1, with most replicates amplifying after Cq of 37 and with CqSD > 0.4 (Figure 4B). miR-29b appears to be present at only very low levels in circulation of these subjects, and its measurement may be subject to the Poisson effect. miR-29b did not appear to change in response to milk intake. Indeed, miR-29b levels are in the same range associated with nonspecific amplification, as shown by non-specific signals from plant miRNA assays. In these samples, three widely conserved plant miRNAs, MIR156a, MIR167a, and MIR166a, had Cq values almost universally later than 37 and with high variability (Figure 4C).\n\nAnalysis of small RNA-seq data. It remains formally possible that real responses to milk intake were masked in our studies. Varying degrees of partial degradation of samples that we received could have contributed to the lack of significant differences in our OpenArray results. Compromised samples might also explain the failure to detect substantial amounts of miR-29b by individual qPCR. To determine whether sample integrity or technical problems might have biased our results, we found another data source to analyze. We examined a high-throughput small RNA-seq dataset in the Sequence Read Archive (BioProject ID PRJNA307561)32,33. In this project, pooled RNA from the same plasma samples we examined was sequenced by an independent facility. The dataset consisted of four pooled samples, representing the five donors at time points 0, 3, 6 and 9 hours post-milk intake. Each sample had between 17.9 and 21 million total reads (Table 4). We analyzed the sample by three methods: miRge24, Chimira release 1.025, and direct mapping via Bowtie v1.1.2 to mature miRNAs. The percent miRNAs were between 96.6 and 99.1% for samples at T0, T6, and T9. However, at T3, the % aligned miRNAs was only 44.9–47%. The dominant miRNA by any measure, representing 43–98% of all miRNAs in these specimens, was miR-486-5p, a miRNA known to be robustly expressed in red blood cells34. Its high level of expression greatly suppressed the RPM counts of all other miRNAs. Despite that, we mapped up to 302 miRNAs, depending on analysis tool and mapping of paralogs. No reads corresponding to miR-29b or miR-200c were detected in any of the samples.\n\nTotal reads in the RNA-seq datasets for plasma at T0, T3, T6, and T9 are shown, along with the number and percentage of reads mapped using miRge, Chimira, or Bowtie.\n\nWe additionally evaluated the datasets against bovine miRNAs using Chimira. There are 794 known bovine (bta) miRNAs (miRBase v21), some of which do not appear to have homology to human miRNAs. A total of 205 miRNAs matched to this database, including 165, 131, 138, and 150 miRNAs at 0, 3, 6, and 9 hours. 17 sequences mapped to bta miRNAs without known homologs in humans (Table 5). Of these, only six had ten raw counts in at least one sample, and only one, bta-miR-1839, was mapped in all samples. However, bta-miR-1839 was most abundant at T0, inconsistent with derivation from milk. The remaining unique bovine miRNA sequences were distributed in a seemingly random fashion amongst the time points.\n\nChimira was used to map known bovine miRNAs in RNA-seq data. The miRNAs in this table do not appear to have human homologs. Shown are raw counts at the indicated time points.\n\nMilk abundance versus apparent changes at T3. Since all samples at 0, 3, 6, and 9 hours were pooled, expression comparisons cannot strictly be made. Even so, we compared the miRNAs with the greatest apparent fold increase at T3 with previously reported abundance in milk9. The top ten increased miRNAs were not found in milk or were not among the most abundant in milk (Table 6). One has no known homolog in cow (hsa-miR-4732-3p). Similarly, the ten miRNAs with the highest reported abundance in milk9 experienced apparent decline or increase with no obvious pattern (Table 7). This includes let-7b, the most abundant milk miRNA (40% of reads) and also among the most enriched in milk exosomes29, which appeared to decline >100-fold from T0 to T3 (miRge rpm).\n\nPlasma miRNAs with the greatest apparent increase from T0 to T3 by RNA-seq were compared with their reported abundance in milk. The top two increasing miRNAs were not detected (ND) in the initial milk sequencing study9 while another is not found in bovine. The other increasing miRNAs were not among the most abundant in milk.\n\nOf the most highly expressed miRNAs in milk9, some appeared to decline after milk intake, while others increased (“FC” = fold change). let-7d was not detected (ND) in human plasma at the T3 time point.\n\nWe attempted to replicate and expand on the report of Baier et al., that milk intake increases presence of bovine miRNAs in human plasma and PBMCs. Instead, we found no evidence to support this position. Based on OpenArray analysis and qPCR, we found no evidence of a spike of miR-29b or miR-200c levels at time points 3 and 6 hours for plasma and PBMC, respectively. Additionally, in a screen of 220 miRNAs with multiple normalization methods, we found no consistent evidence of any other miRNA alterations at these time points. We further evaluated pooled small RNA-seq data from these same samples. There was no evidence of any miR-29b or miR-200c in any of these sequencing libraries at any time points based on analysis by three methods of miRNA quantification, despite very low levels of amplification by OpenArray or qPCR in most of these samples. Finally, we found no evidence of unique bovine miRNAs or consistently elevated levels of human/bovine homologs from 3 to 9 hours that would be consistent with dietary uptake.\n\nAlthough our findings are at odds with Baier et al., they are in agreement with other recent publications. When mouse pups were fed by wild-type dams or transgenic mice engineered to overexpress miR-30b by approximately an order of magnitude in milk35, there were no significant differences in detected miR-30b levels in various organs and blood of nine mice in each group. miR-375 and miR-200c knockout pups experience no significant uptake of these miRNAs from wild-type nursing dams36. As the only experiment to date that can easily distinguish endogenous regulation from exogenous uptake, this study must be given great weight.\n\nNormalization. Baier et al. used a spiked-in RNA as a reference for the plasma miRNA qPCR results. This method does not control for biological variation. Since the spike-in appears to have been used to assign concentrations, the different concentrations in Figure 1 of Baier et al.10, could be the result of technical batch effects (see also below) at different time points. Indeed, using this method, the authors have reported miR-29b concentration estimates for bovine milk that appear to range over almost four orders of magnitude, from 20 fmol/L in skim milk (0.2% fat)37 to 50 fmol/L in raw milk, to 150 pmol/L in 1% fat milk10. For PBMC, an endogenous RNA, U6, was used, but this is not a miRNA, and its suitability as a reference was not established in these samples. We would also caution that normalizing late-amplifying (high Cq) features can be misleading.\n\nRNA purification. To obtain RNA from plasma, Baier et al. used the NucleoSpin miRNA plasma kit (Machery-Nagel), whereas we used the Exiqon Biofluids kit. We previously reported that the Biofluids protocol outperformed several other methods16, but we have not tested the Machery-Nagel kit. Although the methods might have different recovery efficiencies, it is not clear how this would influence robust findings. Hypothetical RNA purification differences would not affect the PBMC results, since we used the PBMC RNA isolated by Baier et al.\n\nqPCR assay design. The qPCR system used in the original study depends on enzymatic addition of sequences to the target miRNA followed by amplification and detection with a sequence-non-specific intercalating dye. The assays we used have sequence-specific RT and qPCR forward primers, as well as a partially sequence-specific hydrolysis probe. It is possible that assays for individual miRNAs might have differing abilities to discriminate between closely-related miRNAs such as members of the miR-29 and miR-200 families.\n\nVariation. In Baier et al., the apparent dose- and time-dependence of the results could be within the range of measurement error as no error bars were given. Indeed, establishing less than two-fold expression differences is technically challenging, especially for a small number of samples.\n\nSample quality. As noted, samples arrived at our laboratory with dry ice largely sublimated. However, as a batch, the data do not indicate poor quality, with the exception of two T0 samples from the PBMC group. Differential degradation of specific samples in transit seems unlikely to have occurred by chance. Thus, these two problematic T0 samples may have been in the same condition in the original study and thereby explain the PBMC miRNA results of Baier et al.\n\nDifferential stability of specific molecules in specific samples. One might conjecture that the miRNAs detected in plasma at higher concentrations by Baier et al. after milk intake were in a particularly labile form that may have been more likely to degrade over time in plasma. However, it is unclear how such degradation could have occurred disproportionately in post-intake plasma.\n\nReproduction. An experimental reproduction of the original study might be informative. However, it may be difficult to justify the expense of new studies given that neither our results nor the RNA sequencing echo the original findings. Rigorous transgenic studies have also yielded negative findings35,36. From the standpoint of stoichiometry, it is also unclear that sufficient miRNA, e.g., miR-29b, is present in milk to achieve the originally reported levels in blood. Based on reported miRNA concentrations, one can calculate the quantity of milk and efficiency of uptake required to achieve hypothetical human plasma alterations. As noted above, the authors’ milk miR-29b estimates have ranged over almost four orders of magnitude10,37. The lower concentration (20 fmol/L) would necessitate 100% uptake efficiency and stability and at least 75 liters of bolused milk intake to achieve an increase of 300 fmol/L in blood of an ingesting human. At the highest reported concentration of miR-29b, 150 pmol/L, > 1% uptake would be needed. This percentage may be unlikely, as other groups have detected no or negligible dietary miRNA content in an in vitro digestion model36 or in intestinal material after gavage of massively non-physiologic quantities of synthetic, modification-stabilized RNA38. Even a purportedly positive study of dietary xenomiRs reported a median uptake of just 0.14% [39, not counting a clearly spurious detection40]. While further experimentation would provide additional, welcomed data, it may not be justified by current results or theory.\n\nOther studies: delivery mechanisms. In general, there is a need to learn more about packaging and potential transfer of miRNAs and other cargoes in endogenous EVs or protein complexes. Despite interesting in vitro data suggesting transfer of lipophilic dyes from highly concentrated milk EVs to epithelial models41, it is not clear that such experiments are relevant to in vivo transfer. In the absence of consistent evidence of xenomiR delivery in vivo, studies of delivery mechanisms specific to xenomiRs and their carriers are not strongly indicated.\n\nOverall conclusion: miRNA profiling by qPCR array and RNA sequencing of plasma and/or PBMC samples from subjects who ingested milk failed to provide support for uptake of bovine miRNAs. Growing evidence casts doubt on the hypothesis of dietary xenomiR transfer to mammals, whether from different kingdoms10,18,42,43 or related organisms35,36. Although several related and interesting research questions remain, their exigency is low, and further research in this area should be justified in terms of deliverables for more pressing health questions. In mammals, dietary miRNAs, along with other ingested molecules, are likely to serve as nutrition, not post-transcriptional regulators.\n\nArray data can be accessed in the NCBI’s GEO public repository (RRID:SCR_004584) under accession numbers GSE79922 (PBMC) and GSE79960 (plasma).\n\nOpen Science Framework: Dataset: Uptake of dietary milk miRNAs by adult humans: a validation study, doi 10.17605/OSF.IO/M9RQ244",
"appendix": "Author contributions\n\n\n\nKWW conceived of and directed the study. Experiments were performed by ARA and Witwer lab staff, with assistance from the Johns Hopkins University DNA Analysis Facility. Analyses were performed by GV, AL, and KWW. MKH provided direction on analysis of RNA sequencing data. The first draft of the paper was written by KWW, and the manuscript was revised by KWW and MKH. All authors reviewed and consented to the final manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work was supported by start-up funds from the Department of Molecular and Comparative Pathobiology (to KWW).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nThe authors would like to thank Scott Baier and Janos Zempleni for providing samples from the original study and for helpful discussions. The expert technical assistance of Lauren Ostrenga and members of the Johns Hopkins University Genetic Resources Core Facility/DNA Analysis Facility is gratefully acknowledged. Zezhou Zhao and Dillon C Muth are acknowledged for contributing miRNA stability data.\n\n\nReferences\n\nWitwer KW: XenomiRs and miRNA homeostasis in health and disease: Evidence that diet and dietary miRNAs directly and indirectly influence circulating miRNA profiles. RNA Biol. 2012; 9(9): 1147–54. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBartel DP: MicroRNAs: target recognition and regulatory functions. Cell. 2009; 136(2): 215–33. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHutvágner G, Zamore PD: A microRNA in a multiple-turnover RNAi enzyme complex. Science. 2002; 297(5589): 2056–60. PubMed Abstract | Publisher Full Text\n\nMeister G, Landthaler M, Patkaniowska A, et al.: Human Argonaute2 mediates RNA cleavage targeted by miRNAs and siRNAs. Mol Cell. 2004; 15(2): 185–97. PubMed Abstract | Publisher Full Text\n\nFarazi TA, Juranek SA, Tuschl T: The growing catalog of small RNAs and their association with distinct Argonaute/Piwi family members. Development. 2008; 135(7): 1201–14. PubMed Abstract | Publisher Full Text\n\nSeitz H: Redefining microRNA targets. Curr Biol. 2009; 19(10): 870–3. PubMed Abstract | Publisher Full Text\n\nKosaka N, Izumi H, Sekine K, et al.: microRNA as a new immune-regulatory agent in breast milk. Silence. 2010; 1(1): 7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZonneveld MI, Brisson AR, van Herwijnen MJ, et al.: Recovery of extracellular vesicles from human breast milk is influenced by sample collection and vesicle isolation procedures. J Extracell Vesicles. 2014; 3: 24215. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChen X, Gao C, Li H, et al.: Identification and characterization of microRNAs in raw milk during different periods of lactation, commercial fluid, and powdered milk products. Cell Res. 2010; 20(10): 1128–37. PubMed Abstract | Publisher Full Text\n\nBaier SR, Nguyen C, Xie F, et al.: MicroRNAs are absorbed in biologically meaningful amounts from nutritionally relevant doses of cow milk and affect gene expression in peripheral blood mononuclear cells, HEK-293 kidney cell cultures, and mouse livers. J Nutr. 2014; 144(10): 1495–500. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWitwer KW: Diet-responsive mammalian miRNAs are likely endogenous. J Nutr. 2014; 144(11): 1880–1. PubMed Abstract | Publisher Full Text\n\nHe A, Zhu L, Gupta N, et al.: Overexpression of micro ribonucleic acid 29, highly up-regulated in diabetic rats, leads to insulin resistance in 3T3-L1 adipocytes. Mol Endocrinol. 2007; 21(11): 2785–94. PubMed Abstract | Publisher Full Text\n\nBagge A, Clausen TR, Larsen S, et al.: MicroRNA-29a is up-regulated in beta-cells by glucose and decreases glucose-stimulated insulin secretion. Biochem Biophys Res Commun. 2012; 426(2): 266–72. PubMed Abstract | Publisher Full Text\n\nPandey AK, Verma G, Vig S, et al.: miR-29a levels are elevated in the db/db mice liver and its overexpression leads to attenuation of insulin action on PEPCK gene expression in HepG2 cells. Mol Cell Endocrinol. 2011; 332(1–2): 125–33. PubMed Abstract | Publisher Full Text\n\nHennessy E, Clynes M, Jeppesen PB, et al.: Identification of microRNAs with a role in glucose stimulated insulin secretion by expression profiling of MIN6 cells. Biochem Biophys Res Commun. 2010; 396(2): 457–62. PubMed Abstract | Publisher Full Text\n\nMcAlexander MA, Phillips MJ, Witwer KW: Comparison of Methods for miRNA Extraction from Plasma and Quantitative Recovery of RNA from Cerebrospinal Fluid. Front Genet. 2013; 4: 83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTosar JP, Rovira C, Naya H, et al.: Mining of public sequencing databases supports a non-dietary origin for putative foreign miRNAs: underestimated effects of contamination in NGS. RNA. 2014; 20(6): 754–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWitwer KW, Hirschi KD: Transfer and functional consequences of dietary microRNAs in vertebrates: concepts in search of corroboration: negative results challenge the hypothesis that dietary xenomiRs cross the gut and regulate genes in ingesting vertebrates, but important questions persist. Bioessays 2014; 36(4): 394–406. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMcCall MN, Baras AS, Crits-Christoph A, et al.: A benchmark for microRNA quantification algorithms using the OpenArray platform. BMC Bioinformatics. 2016; 17(1): 138. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChu VT, Gottardo R, Raftery AE, et al.: MeV+R: using MeV as a graphical user interface for Bioconductor applications in microarray analysis. Genome Biol. 2008; 9(7): R118. PubMed Abstract | Publisher Full Text | Free Full Text\n\nEdgar R, Domrachev M, Lash AE: Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002; 30(1): 207–10. PubMed Abstract | Publisher Full Text | Free Full Text\n\nClough E, Barrett T: The Gene Expression Omnibus Database. Methods Mol Biol. 2016; 1418: 93–110. PubMed Abstract | Publisher Full Text\n\nChen C, Ridzon DA, Broomer AJ, et al.: Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res. 2005; 33(20): e179. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBaras AS, Mitchell CJ, Myers JR, et al.: miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy. PLoS One. 2015; 10(11): e0143066. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVitsios DM, Enright AJ: Chimira: analysis of small RNA sequencing data and microRNA modifications. Bioinformatics. 2015; 31(20): 3365–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLove MI, Huber W, Anders S: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12): 550. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLangmead B, Trapnell C, Pop M, et al.: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. BioMed Central; 2009; 10(3): R25. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKozomara A, Griffiths-Jones S: miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014; 42(Database issue): D68–73. PubMed Abstract | Publisher Full Text | Free Full Text\n\nIzumi H, Tsuda M, Sato Y, et al.: Bovine milk exosomes contain microRNA and mRNA and are taken up by human macrophages. J Dairy Sci. 2015; 98(5): 2920–33. PubMed Abstract | Publisher Full Text\n\nBağcı C, Allmer J: One Step Forward, Two Steps Back; Xeno-MicroRNAs Reported in Breast Milk Are Artifacts. PLoS One. 2016; 11(1): e0145065. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAi J, Zhang R, Li Y, et al.: Circulating microRNA-1 as a potential novel biomarker for acute myocardial infarction. Biochem Biophys Res Commun. 2010; 391(1): 73–7. PubMed Abstract | Publisher Full Text\n\nShu J, Chiang K, Zempleni J, et al.: Computational Characterization of Exogenous MicroRNAs that Can Be Transferred into Human Circulation. PLoS One. 2015; 10(11): e0140587. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHomo sapiens (ID 307561) - BioProject - NCBI. Reference Source\n\nKent OA, McCall MN, Cornish TC, et al.: Lessons from miR-143/145: the importance of cell-type localization of miRNAs. Nucleic Acids Res. 2014; 42(12): 7528–38. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLaubier J, Castille J, Le Guillou S, et al.: No effect of an elevated miR-30b level in mouse milk on its level in pup tissues. RNA Biol. 2015; 12(1): 26–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTitle AC, Denzler R, Stoffel M: Uptake and Function Studies of Maternal Milk-derived MicroRNAs. J Biol Chem. 2015; 290(39): 23680–91. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHoward KM, Jati Kusuma R, Baier SR, et al.: Loss of miRNAs during processing and storage of cow’s (Bos taurus) milk. J Agric Food Chem. 2015; 63(2): 588–92. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMlotshwa S, Pruss GJ, MacArthur JL, et al.: A novel chemopreventive strategy based on therapeutic microRNAs produced in plants. Cell Res. 2015; 25(4): 521–4. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiang H, Zhang S, Fu Z, et al.: Effective detection and quantification of dietetically absorbed plant microRNAs in human plasma. J Nutr Biochem. 2015; 26(5): 505–12. PubMed Abstract | Publisher Full Text\n\nWitwer KW: Contamination or artifacts may explain reports of plant miRNAs in humans. J Nutr Biochem. 2015; 26(12): 1685. PubMed Abstract | Publisher Full Text\n\nWolf T, Baier SR, Zempleni J: The Intestinal Transport of Bovine Milk Exosomes Is Mediated by Endocytosis in Human Colon Carcinoma Caco-2 Cells and Rat Small Intestinal IEC-6 Cells. J Nutr. 2015; 145(10): 2201–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCottrill KA, Chan SY: Diet-Derived MicroRNAs: Separating the Dream from Reality. microRNA Diagnostics Ther. 2014; 1(1): 46–57. Publisher Full Text\n\nPetrick JS, Brower-Toland B, Jackson AL, et al.: Safety assessment of food and feed from biotechnology-derived crops employing RNA-mediated gene regulation to achieve desired traits: a scientific review. Regul Toxicol Pharmacol. 2013; 66(2): 167–76. PubMed Abstract | Publisher Full Text\n\nAuerbach AR, Vyas G, Li A, et al.: Dataset: Uptake of dietary milk miRNAs by adult humans: a validation study. Open Science Framework. 2016. Data Source"
}
|
[
{
"id": "13516",
"date": "29 Apr 2016",
"name": "Cherie Blenkiron",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nHere Auerbach et al report their attempts to validate the data of Baier et al that showed the presence of bovine miRNAs in human plasma samples after ingestion of milk. Baier et al kindly provided the original samples for this study but Auerbach et al were unable to replicate their findings.This study is presented in a very thorough and logical manner and the techniques used are appropriate. Multiple analyses are performed in their attempts to validate the findings; they do not rely on a single detection technique or normalisation protocol. The discussion points are also well considered.Clarity could be provided on the following:The content of the OpenArray. I presume that this was biased towards Human miRNAs. Clarification on the number of miRNAs that are conserved in bovine would be valuable for the reader. In the methods, the OpenArray used a preamplification step but the single probes did not. This was not obvious unless the referenced article was accessed and read. This is a point of difference that affects sensitivity between these assays. With preamplification for the single assays, the Ct values would improve for the low abundance miRNAs and the SD lower for replicates also. The discussion comment on use of differing RNA purification methods might be improved by commenting on why the kits cause differences (e.g. ability to dissociate protein aggregates, lyse EVs etc). A couple of typos- ul used instead of µL pages 2 and 3. Also a degree symbol is missing on pg 3 for 22oC. In all the authors have presented a well considered and technically robust study that adds further fuel to the debate of cross-species microRNA signaling.",
"responses": []
},
{
"id": "13515",
"date": "04 May 2016",
"name": "Jens Allmer",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn essence, Auerbach et al. tried to replicate findings by Baier et al. 1 and were unable to come to the same conclusions.Starting from the alleged (tbk unreproduced) finding of rice miRNAs in human plasma 2, a field advocating dietary uptake of xenomiRs and proposing potential regulatory effects has arisen. While the number of studies contesting such findings is rising, it is important that more scrutiny is applied in this context and the study by Auerbach et al. is very important in this context.One clever analysis in this study is the application of clustering to investigate if there is a patient or time point related effect, or none at all. And as it turns out there rather is a patient than a time point effect.I fully support their conclusion that no more studies in this area are indicated before some additional fundamentals have been established. E.g.: the uptake efficiencies of naked and packed (pre-)miRNAs. Then downstream process like uptake of (pre-)miRNAs by cells and finally the regulatory effect of these need to be established before any further effort in the area of dietary xenomiRs should be exerted.Minor Revisions:The introduction mentions that ‘essential’ miRNAs would lead to a paradigm shift, but many co-factors and other metabolites like amino acids and vitamins are essential and can only be acquired via food sources. I suggest the statement should be slightly revised and refer more clearly to cross-kingdom communication and less to nutrition.In Figure 3 the bars marking samples may have a problem in respect to samples 2 and 3 for both panels.The study by Bagci and Allmer3 does not conclude that there are no plant miRNAs in milk, but rather claims that for the particular samples investigated the plant miRNAs that were found are due to contamination.However far-fetched this may sound, the Cq values above some threshold are, as pointed out, likely spurious, but I believe that this has to become clear from Figure 4, as well; because some may judge the results as incidence for plant miRNAs in human plasma while they were intended to be negative controls. The figure legend could clearly state that results above Cq X are unreliable.The methodology describing RNA sequencing data analysis is not reproducible in its current form and could be expanded upon.Baier et al. 1 provide error bars for most graphs and present the average +/- SEM (=SD/sqrt(n)) for Figure 1 in Table 1. The section variation in the discussion should be revised accordingly.xeno-miRNA and xenomiR is used in the text, but xeno-microRNA is not and the abbreviation xenomiR was not introduced as such. Questions:Why was no spiking applied to the PBMC samples?Would it be possible to provide the quality assessment of SRA samples to see whether the sample SRR3083758 with the most reads has a much lower sequencing quality than the other samples? Perhaps there is some problem with the file which prevents its proper processing by some of the tools and, therefore, not the complete data was mapped. This needs some clarification.",
"responses": []
},
{
"id": "13517",
"date": "10 May 2016",
"name": "Hervé Seitz",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this article, A. Auerbach and colleagues revisit the published claim that dietary miRNAs can be detected in human blood. Using carefully designed analytical procedures, they show that the original claim was most likely erroneous. Using RNA samples provided by the authors of the initial paper, with various detection techniques and sensitive statistical testing, Auerbach et al. could not find any indication of food-derived miRNAs in human plasma or peripheral blood mononuclear cells. They also provide a simple mathematical demonstration that the proposed miRNA dietary intake would require unrealistic volumes of ingested milk. This is a solid manuscript, which addresses an important issue. I only have minor comments: this manuscript is almost already suitable for indexing.Minor comment #1:End of the first paragraph of page 2 (\"[...] although larger effects have also been described\"): bibliographical references are needed here (to my knowledge, large effects were only measured after experimental miRNA over-expression - not with endogenous miRNA levels).Minor comment #2:In paragraph \"Sample delivery, preparation, and quality control\" (page 2): dry ice was \"largely sublimated\" (that observation is also reported at various other places in the manuscript). Do the authors mean that dry ice was completely gone? Or were there still some pellets? If the styrofoam box is well insulated, just one solid pellet in the box ensures that the atmosphere inside the box is still at -80°C. The authors should at least tell whether RNA solutions were still solid on arrival.Minor comment #3:In paragraph \"OpenArray data normalization and analysis\" (page 2): 26 features were selected for \"relatively low variability\". How was this done?Minor comment #4:In paragraph \"RNA stability test\" (page 3): was cel-miR-39 spiked-in before or after shipping on dry ice?Minor comment #5:The only reliably detected bovine miRNA in human blood is bta-miR-1839, but its accumulation dynamics are not compatible with dietary uptake (first sentence of page 10). The authors may wish to be aware that this \"miRNA\" is most likely a degradation product from an abundant nuclear RNA, SCARNA15. Full-length bovine and human SCARNA15 are not absolutely identical, but that subsequence (AAGGUAGAUAGAACAGGUCUUGUU) is common to the bovine and human sequences.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-721
|
https://f1000research.com/articles/5-716/v1
|
21 Apr 16
|
{
"type": "Review",
"title": "Advances in laparoscopic urologic surgery techniques",
"authors": [
"Haidar M. Abdul-Muhsin",
"Mitchell R. Humphreys",
"Haidar M. Abdul-Muhsin"
],
"abstract": "The last two decades witnessed the inception and exponential implementation of key technological advancements in laparoscopic urology. While some of these technologies thrived and became part of daily practice, others are still hindered by major challenges. This review was conducted through a comprehensive literature search in order to highlight some of the most promising technologies in laparoscopic visualization, augmented reality, and insufflation. Additionally, this review will provide an update regarding the current status of single-site and natural orifice surgery in urology.",
"keywords": [
"laparoscopic urology",
"Augmented reality",
"Laparoendoscopic single site surgery",
"natural orifice transluminal surgery",
"Laparoendoscopic",
"insufflation devices"
],
"content": "Introduction\n\nUrology has long been recognized as an avid adopter of new technologies and innovations in surgical practice. In concert with the exponential and rapid improvements in laparoscopic techniques and instrumentations over the last two decades, urologists’ enthusiasm to implement minimally invasive approaches has led to the near extinction of open surgical approaches in several different urological diseases. This captivation was driven mainly by the morbidity associated with classic open approaches and the real benefits of less invasive approaches.\n\nSince the description of the first laparoscopic nephrectomy by Clayman et al.1 in 1991, there has been a continual effort to enhance outcomes and introduce newer, less invasive approaches. This has been accomplished through laparoendoscopic approaches which encompass a wide array of surgical interventions, including robotic surgery, laparoendoscopic single-site surgery (LESS), and natural orifice transluminal surgery (NOTES). The aim of this review is to highlight the major conceptual advancements in this field regardless of both the specific surgical approaches, whether pure laparoscopic or robotic, and the specific organ or pathology treated.\n\nThis review was conducted through a comprehensive literature search in order to describe the major advances that impacted daily practice or had the potential to do so. No specific search period was applied. All relevant articles that represented a key addition to existing knowledge were selected on the basis of the discretion of the authors. For descriptive purposes, these advances will be classified into the following categories: enhanced laparoscopic visualization, augmented reality in laparoscopy, overview of access, and new advances in insufflation devices.\n\n\nEnhanced visualization\n\nOne of the main advantages of laparoscopy is the enhanced appreciation of intraoperative anatomy through the use of magnifying optics with high-definition properties. Although this greatly facilitates certain parts of each procedure, this comes at the cost of losing some or all of the haptic feedback because of the presence of an instrument interface between the surgeon’s hands and the surgical field. Haptics generally describes touch feedback, which is a combination of kinesthetic (force applied to muscle and joints) and cutaneous (tactile; applied to sensory receptor on the skin) feedback1. In laparoscopic surgery, the surgeon feels the interaction of the instrument and the tissue via the shaft of the instrument. Thus, the force feedback is partially maintained while there is no tactile feedback as he is not touching the tissue directly with his fingers as in open surgery. On the other hand, lack of haptic feedback is profound in robot-assisted surgery because of the lack of both force and tactile feedback. Recently, the TELELAP ALF-X robotic surgical platform (Sofar SpA, Milan, Italy) was introduced; this platform provides force feedback but no tactile feedback and was used in gynecological procedures such as ovarian cystectomies and hysterectomy2,3. To the best of our knowledge, this system was not used in urology other than in preclinical trials4,5. Of note, the newest generation of the commercially available robot, the da Vinci Xi (Intuitive Surgical, Inc., Sunnyvale, CA, USA), provides visual feedback relative to the degree of pressure applied between the jaws of some of the available instruments, such as the Vessel Sealer™ and the Endowrist stapler™ (Intuitive Surgical, Inc., Sunnyvale, CA, USA).\n\nIt is a well-established observation that minimally invasive surgeons gradually develop alternative visual cues in order to compensate for the lack of tactile feedback6. However, the mere utilization of high-definition cameras does not help completely overcome this limitation. Recently, several three-dimensional (3D) cameras and monitors have been introduced and used in conventional laparoscopy and were shown to demonstrate a high degree of accuracy and precision in conducting the surgical procedure in a more efficient manner7–10. With regard to robotics, the 3D visualization was a feature that accompanied robotic surgical platforms since its inception and to the best of our knowledge there were no data to compare between the 2D and 3D visualization in robotics.\n\nIn robotic surgery, real-time ultrasound (US) visualization with simultaneous display at the console can be performed by using the TilePro technology (Intuitive Surgical, Inc.). This can be used with a variety of ultrasound probes that are used at the bedside by the assistant or the surgeon (through a robotic instrument). Several examples exist for the use of this technology and one of the earliest uses was when a transrectal US was used during radical prostatectomy to visualize the neurovascular bundle, shape of the prostate, and surgical instruments to help guide various surgical steps of the procedure in both laparoscopic and robotic prostatectomy11. In one report that used this technology in robotic prostatectomy, the transrectal probe was manipulated with a remote controller without the need of a bedside assistant12. Although the use of this system demonstrated less positive surgical margin rates in T3 prostate cancer, it did not gain widespread usage during robot-assisted radical prostatectomy since most surgeons are currently familiar with laparoscopic prostate anatomy and can use alternative visual cues to guide them during these surgical steps. On the other hand, the use of robotically held, small linear probes with 13.3 Hz is of clinical value, especially during robot-assisted partial nephrectomies. The images can still be displayed on the console and help identify endophytic tumors and plan accurate surgical resection. In our opinion, the use of intraoperative US in partial nephrectomy offers a great technical advantage in accurate tumor localization and subsequently may decrease operative time. However, its impact on surgical margins and oncological outcomes is not clear. Although certain reports demonstrated less positive surgical margins in partial nephrectomies when intraoperative US was used13, this could be attributed to surgical skills and experience.\n\nOne of the limitations of intraoperative US is that the surgeon has to correlate the US imaging with the real images of the anatomy through cognitive fusion. For example, the depth of a tumor can be only mentally estimated, with the potential for error, resulting in cutting through a tumor or much deeper, leading to unnecessary loss of healthy parenchymal tissue. Interestingly, certain reports described the benefit of combined in vivo and ex vivo US examination of surgical margins and found that this correlated with final histopathological margins14. Veeratterapillay et al. recently demonstrated an interesting concept of overlaying the intraoperative US images on the surgical field, resulting in direct fusion of the US and the 3D images seen in the console15. However, the authors reported some delay resulting from processing of these high-definition images.\n\n\nAugmented reality and surgical navigation\n\nAugmented reality (AR) has been an active area of research and development in laparoscopic urology in recent years. It is an advanced form of image-guided surgery and implies the use of enhanced visual information to the normal surgical field to supplement the lack of tactile feedback. This information is typically extrapolated from preoperative or, less commonly, intraoperative 3D imaging from US, computerized tomography, or magnetic resonance imaging16–19. The images are superimposed on the real-time surgical field to guide precise surgical resection. This was first reported by Marescaux et al. in a laparoscopic adrenalectomy in 200416.\n\nThe most common operation in which AR is used in urology is partial nephrectomy, where understanding of hilar anatomy and 3D location of the tumor is of paramount importance. This is specifically used to avoid vascular injuries, collecting system violation, and incomplete tumor resection in partial or complete endophytic tumors. AR starts with “registration”, where multiple points from both the images and the real anatomic physical objects are aligned in a single coordinate system20. There are various methods of registration and this can be done manually or with computer-assisted surface-based methodologies, fiducial based registration, stereotactic image registration, or a combination of these methods19,21–24. The details of these techniques are beyond the scope of this review.\n\nOne of the main challenges of AR is organ movement and tissue deformation during respiration or surgical manipulation. The real-time changes in organ size and shape during surgery may significantly impair the accuracy of image fusion. So far, no real practical solution exists for this problem and this precludes the use of AR in clinical practice. However, in an attempt to do so, Teber et al. used an intraoperative mobile C-arm computed tomography scan and custom-designed navigation aids to enhance surgical decision making immediately prior to surgical resection of kidney tumors18. The model was tested in 10 porcine renal units and 10 laparoscopic partial nephrectomies. They demonstrated a small margin of error of 0.5 mm, and all specimens had negative surgical margins. Although this is encouraging, the impact of this technique on the perioperative and oncological outcomes remains to be proven.\n\nSurgical navigation in laparoscopy can be aided with the use of various injectable substances that can be visualized intraoperatively. The most commonly used material so far is indocyanine green (ICG) dye, which is a fluorescent dye that was first used in the 1950s at the Mayo Clinic for medical diagnostic purposes in hepatology and cardiology. It is a fluorescent substance that is administered intravenously and binds to plasma proteins (globulin and plasma protein); thus, it is confined to the intravascular compartment with a half-life of 4 minutes and complete hepatic excretion. ICG dye has no major adverse effects and has a peak spectral absorption of 800 nm25–31. It can be visualized with a special near-infrared camera (700–1000 nm) that is currently available in both laparoscopic and robotic platforms: the Storz D-light (Storz GmbH, Tuttlingen, Germany) and Firefly fluorescence, the latter of which is incorporated directly into the da Vinci Si and Xi system (Intuitive Surgical, Inc.). The vessels and vascular organs can be seen as bright florescent structures, and renal cortical tumors (except oncocytomas, which will appear as isofluorescent) will be less bright as they have reduced expression of ICG dye carrier protein. The main application of ICG dye in urology is in partial nephrectomy for selective clamping and localization of the tumor, and in order to decrease warm ischemia time. The ability of this technique to differentiate tumor from parenchyma is reported to range from 65 to 10% with a positive surgical margin rate of 0 to 6.4% and warm ischemia time of 12.5 to 26.6 minutes32. Although the aim of this technique is to aid in selective clamping, the impact of selective clamping on long-term renal function and epidermal growth factor receptor (eGFR) reduction needs further evaluation.\n\nAlthough this article focuses on what we see to be the main advances in laparoscopic urology, it is worth noting the major expected role of 3D printing in surgery in general and its impact on laparoscopy. 3D printing is part of a process called additive manufacturing in which an object is created by adding materials layer by layer. This involves scanning an existing object using sophisticated software (or occasionally creating the image of an object), and then converting these images into multiple successive 2D layers that can be deposited by the printer and added together to form a 3D object again33,34. Materials of different physical properties can be used in 3D printing to serve different purposes. One of the uses of this technology is preoperative planning for complex surgical operations. Silberstein et al.35 and Zhang et al.36 reported the use of 3D printed kidney units with cancer to educate patients and trainees prior to partial nephrectomies. Interestingly, the authors used the cross-sectional images to build these models.\n\nAn additional use of 3D printing is to reproduce surgical instruments where several studies reported the use of 3D-printed surgical instruments in animal and cadaveric models such as laparoscopic ports or ureteral stents37,38. Among the various advantages of these instruments, the benefits of cost and potential individualization are very promising.\n\nLastly, the ultimate goal of 3D printing is to use biological material to produce biological grafts or transplant artificial organs (bioprinting). This will revolutionize the treatment of many urological disorders. However, this is currently facing many challenges that are beyond the scope of this review.\n\n\nInsufflation devices\n\nThe creation of a large and stable working space between the abdominal wall and viscera is essential for successful conduction of any laparoscopic procedure. The most commonly used method is the insufflation of carbon dioxide (CO2) to establish pneumoperitoneum. CO2 is used to achieve the intra-abdominal pressure and space that can be tolerated by the patient without adverse physiological effects. CO2 is commonly used because it is inexpensive, colorless, odorless, nonflammable, and rapidly eliminated from the systemic circulation39. Effective and stable pneumoperitoneum can result in shorter and safer operation. With conventional insufflators, laparoscopic ports are supplied with mechanical valves that help maintain pressure and prevent leakage while the insufflator is set to automatically maintain pressure at a certain level. A relatively recent innovative insufflator was introduced as the AirSeal system (Surgi-Quest, Inc., Milford, CT, USA). This system has the potential advantages of smoke evacuation, gas circulation, and maintenance of a more stable high-flow pressure that rapidly replaces the sudden decrements in pressure in case of leak. The system achieves these aims through a valveless trocar and tri-lumen filter tube set. The gas leakage is prevented through tiny circumferential CO2 nozzles within the proximal part of the trocar that creates an invisible gas “curtain” that has higher pressures than the abdominal wall. The tubing is composed of three lumens for inflow, outflow, and constant pressure monitoring; all are connected to a built-in filter that helps eliminate smoke and microbial contamination and potentially decrease CO2 consumption. The circulation of gas takes place at a rate of 3 L/min and reactively increases in case of pressure drop.\n\nThe use of this insufflation system was found to be associated with shorter operative times and lower CO2 consumption and, more importantly, reduced patient systemic CO2 absorption. Horstmann et al. prospectively compared the conventional insufflation system with the AirSeal and found that the latter resulted in more stable pneumoperitoneal pressures and easier specimen and needle extraction because of valveless ports40. In our experience, we found that the majority of pelvic urological procedures can be performed safely in the hands of experienced surgeons without the added cost of this device to the operating room. Moreover, the benefit of this insufflation system is evident mainly in cases of partial nephrectomy where continuous suction is needed during renorrhaphy. Of note, this insufflation system mandates the use of large-size trocars and results in noise from the high flow of insufflation that may make direct verbal communication between the assistant and the console surgeon somewhat difficult in robotic cases.\n\n\nAccess\n\nThe evolution of surgical intervention from classic open surgery to minimally invasive laparoscopic surgery resulted in the development of less invasive techniques. This was manifest in the description of LESS, minilaparoscopy, and NOTES. In LESS, surgery is performed through a single port of entry to the abdominal cavity in an attempt to minimize pain, enhance recovery, and improve cosmesis. In contrast, natural orifice surgery (NOTES) is where surgery is performed in a scar-less fashion through transoral, transvaginal, transrectal, or transurethral routes. Although these techniques of access represent an attractive option to perform some of the most commonly performed procedures in urology, its widespread adoption is limited by the technical difficulty encountered and the need for the development of more sophisticated flexible instruments that can facilitate these surgical tasks. Moreover, the measurable improvement of patient outcomes needs to be objectively validated to demonstrate superiority over standard laparoscopic and robotic procedures.\n\nSince the first NOTES nephrectomy in a porcine model by Gettman et al. was described in 2002, there have been several other reports of pure and hybrid NOTES urological procedures in the literature41. Most of these efforts were preclinical and were performed on either animals or cadavers and focused on NOTES nephrectomy with the less commonly described NOTES prostatectomy42–59. The first clinical NOTES procedure was performed by Branco et al., who successfully performed a hybrid transvaginal nephrectomy60. Kaouk et al. performed the first pure NOTES nephrectomy in 2010 through a 3 cm colpotomy incision followed by the first robot-assisted hybrid NOTES donor nephrectomy in 201261,62.\n\nAlthough a transurethral prostate resection for benign disease is the current standard of care, performing a radical prostatectomy through a transurethral approach is challenging. This was first reported by Humphreys et al. in both a cadaveric and a clinical setting63,64. The latter was performed in two patients without perioperative complications and with negative surgical margins. Further development of the procedure was hindered by the lack of an appropriate transurethral anastomotic device.\n\nDespite the great promise of pure NOTES, the surgical instrumentation has been criticized because of lack of flexibility, difficult retraction of large and heavy intra-abdominal organs, and difficult use of relatively large hemostatic devices. These limitations may make surgery extremely difficult, especially when a complication such as bleeding occurs. Additionally, closure of site of entry is of extreme importance, especially in transgastric, transvesical, and transcolonic approaches where poor closure carries a great risk of infectious complication.\n\nEach natural orifice route is associated with its own advantages and disadvantages. The transvaginal route is most commonly used because of the advantage of easy closure and low contamination risk but is associated with gender confinement to 50%. Digestive tract access is associated with easier access to kidney (in transgastric access) and pelvis (in transcolonic and transrectal access) but carries a significant risk of contamination and wound closure and specimen extraction difficulty.\n\nOwing to the aforementioned difficulties associated with pure NOTES, many groups use a hybrid NOTES technique in which a number of laparoscopic instruments (usually one or two 5 mm ports) are added to the instruments inserted through the natural orifice. The prevailing thought was that by avoiding the extraction incision the morbidity would be reduced. Thus, using the natural orifice for specimen extraction (most commonly, the vagina) provides a potential cosmetic and recovery advantage65.\n\n\nConclusions\n\nLaparoscopic and robot-assisted approaches in urology have fostered significant advances in minimally invasive surgery and in some instances completely replaced previously performed standard open procedures such as robotic prostatectomy and laparoscopic live-donor nephrectomies. Although efforts continue to explore newer, less invasive technologies and procedures, their widespread implementation will depend on the introduction of newer instrumentations that facilitate these surgeries. In order to prove the clinical utility of these newly described technologies and their equivalent therapeutic benefits compared with conventional laparoscopy, there is a strong need to have an objective and stringent evaluation of its clinical outcome.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nClayman RV, Kavoussi LR, Soper NJ, et al.: Laparoscopic nephrectomy: initial case report. J Urol. 1991; 146(2): 278–282. PubMed Abstract\n\nFanfani F, Restaino S, Gueli Alletti S, et al.: TELELAP ALF-X Robotic-assisted Laparoscopic Hysterectomy: Feasibility and Perioperative Outcomes. J Minim Invasive Gynecol. 2015; 22(6): 1011–1017. PubMed Abstract | Publisher Full Text\n\nGueli Alletti S, Rossitto C, Fanfani F, et al.: Telelap Alf-X-Assisted Laparoscopy for Ovarian Cyst Enucleation: Report of the First 10 Cases. J Minim Invasive Gynecol. 2015; 22(6): 1079–1083. PubMed Abstract | Publisher Full Text\n\nBozzini G, Gidaro S, Taverna G: Robot-Assisted Laparoscopic Partial Nephrectomy with the ALF-X Robot on Pig Models. Eur Urol. 2016; 69(2): 376–377. 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J Cell Sci. 1996; 109(Pt 10): 2509–2520. PubMed Abstract\n\nDesmettre T, Devoisselle JM, Mordon S: Fluorescence properties and metabolic features of indocyanine green (ICG) as related to angiography. Surv Ophthalmol. 2000; 45(1): 15–27. PubMed Abstract | Publisher Full Text\n\nTobis S, Knopf JK, Silvers CR, et al.: Near infrared fluorescence imaging after intravenous indocyanine green: initial clinical experience with open partial nephrectomy for renal cortical tumors. Urology. 2012; 79(4): 958–964. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHope-Ross M, Yannuzzi LA, Gragoudas ES, et al.: Adverse reactions due to indocyanine green. Ophthalmology. 1994; 101(3): 529–533. PubMed Abstract | Publisher Full Text\n\nEbert B, Riefke B, Sukowski U, et al.: Cyanine dyes as contrast agents for near-infrared imaging in vivo: acute tolerance, pharmacokinetics, and fluorescence imaging. J Biomed Opt. 2011; 16(6): 066003. PubMed Abstract | Publisher Full Text\n\nOtt P, Bass L, Keiding S: The kinetics of continuously infused indocyanine green in the pig. J Pharmacokinet Biopharm. 1996; 24(1): 19–44. PubMed Abstract | Publisher Full Text\n\nShinohara H, Tanaka A, Kitai T, et al.: Direct measurement of hepatic indocyanine green clearance with near-infrared spectroscopy: separate evaluation of uptake and removal. Hepatology. 1996; 23(1): 137–144. PubMed Abstract | Publisher Full Text\n\nBjurlin MA, McClintock TR, Stifelman MD: Near-infrared fluorescence imaging with intraoperative administration of indocyanine green for robotic partial nephrectomy. Curr Urol Rep. 2015; 16(4): 20. PubMed Abstract | Publisher Full Text\n\nMichalski MH, Ross JS: The shape of things to come: 3D printing in medicine. JAMA. 2014; 312(21): 2213–2214. PubMed Abstract | Publisher Full Text\n\nMurphy SV, Atala A: 3D bioprinting of tissues and organs. Nat Biotechnol. 2014; 32(8): 773–785. PubMed Abstract | Publisher Full Text\n\nSilberstein JL, Maddox MM, Dorsey P, et al.: Physical models of renal malignancies using standard cross-sectional imaging and 3-dimensional printers: a pilot study. Urology. 2014; 84(2): 268–272. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZhang Y, Ge HW, Li NC, et al.: Evaluation of three-dimensional printing for laparoscopic partial nephrectomy of renal tumors: a preliminary report. World J Urol. 2016; 34(4): 533–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\ndel Junco M, Okhunov Z, Yoon R, et al.: Development and initial porcine and cadaver experience with three-dimensional printing of endoscopic and laparoscopic equipment. J Endourol. 2015; 29(1): 58–62. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nPark CJ, Kim HW, Jeong S, et al.: Anti-Reflux Ureteral Stent with Polymeric Flap Valve Using Three-Dimensional Printing: An In Vitro Study. J Endourol. 2015; 29(8): 933–938. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJunghans T, Böhm B, Gründel K, et al.: Effects of pneumoperitoneum with carbon dioxide, argon, or helium on hemodynamic and respiratory function. Arch Surg. 1997; 132(3): 272–278. PubMed Abstract | Publisher Full Text\n\nHorstmann M, Horton K, Kurz M, et al.: Prospective comparison between the AirSeal® System valve-less Trocar and a standard Versaport™ Plus V2 Trocar in robotic-assisted radical prostatectomy. J Endourol. 2013; 27(5): 579–582. PubMed Abstract | Publisher Full Text\n\nTyson MD, Humphreys MR: Laparoendoscopic single-site surgery, minilaparoscopy and natural orifice transluminal endoscopic surgery in urology. Minerva Urol Nefrol. 2014; 66(1): 25–35. PubMed Abstract\n\nGettman MT, Lotan Y, Napper CA, et al.: Transvaginal laparoscopic nephrectomy: development and feasibility in the porcine model. Urology. 2002; 59(3): 446–450. PubMed Abstract | Publisher Full Text\n\nClayman RV, Box GN, Abraham JB, et al.: Rapid communication: transvaginal single-port NOTES nephrectomy: initial laboratory experience. J Endourol. 2007; 21(6): 640–644. PubMed Abstract | Publisher Full Text\n\nBox G, Averch T, Cadeddu J, et al.: Nomenclature of natural orifice translumenal endoscopic surgery (NOTES) and laparoendoscopic single-site surgery (LESS) procedures in urology. J Endourol. 2008; 22(11): 2575–2581. PubMed Abstract | Publisher Full Text\n\nHaber G, Crouzet S, Kamoi K, et al.: Robotic NOTES (Natural Orifice Translumenal Endoscopic Surgery) in reconstructive urology: initial laboratory experience. Urology. 2008; 71(6): 996–1000. PubMed Abstract | Publisher Full Text\n\nIsariyawongse JP, McGee MF, Rosen MJ, et al.: Pure natural orifice transluminal endoscopic surgery (NOTES) nephrectomy using standard laparoscopic instruments in the porcine model. J Endourol. 2008; 22(5): 1087–1091. PubMed Abstract | Publisher Full Text\n\nCrouzet S, Haber GP, Kamoi K, et al.: Natural orifice translumenal endoscopic surgery (NOTES) renal cryoablation in a porcine model. BJU Int. 2008; 102(11): 1715–1718. PubMed Abstract | Publisher Full Text\n\nHaber GP, Brethauer S, Crouzet S, et al.: Pure 'natural orifice transluminal endoscopic surgery' for transvaginal nephrectomy in the porcine model. BJU Int. 2009; 104(9): 1260–1264. PubMed Abstract | Publisher Full Text\n\nRaman JD, Bergs RA, Fernandez R, et al.: Complete transvaginal NOTES nephrectomy using magnetically anchored instrumentation. J Endourol. 2009; 23(3): 367–371. PubMed Abstract | Publisher Full Text\n\nPerretta S, Allemann P, Asakuma M, et al.: Feasibility of right and left transvaginal retroperitoneal nephrectomy: from the porcine to the cadaver model. J Endourol. 2009; 23(11): 1887–1892. PubMed Abstract | Publisher Full Text\n\nAron M, Berger AK, Stein RJ, et al.: Transvaginal nephrectomy with a multichannel laparoscopic port: a cadaver study. BJU Int. 2009; 103(11): 1537–1541. PubMed Abstract | Publisher Full Text\n\nBoylu U, Oommen M, Joshi V, et al.: Natural orifice translumenal endoscopic surgery (NOTES) partial nephrectomy in a porcine model. Surg Endosc. 2010; 24(2): 485–489. PubMed Abstract | Publisher Full Text\n\nBazzi WM, Wagner O, Stroup SP, et al.: Transrectal hybrid natural orifice transluminal endoscopic surgery (NOTES) nephrectomy in a porcine model. Urology. 2011; 77(3): 518–523. PubMed Abstract | Publisher Full Text\n\nBaldwin DD, Tenggardjaja C, Bowman R, et al.: Hybrid transureteral natural orifice translumenal endoscopic nephrectomy: a feasibility study in the porcine model. J Endourol. 2011; 25(2): 245–250. PubMed Abstract | Publisher Full Text\n\nSánchez-Margallo FM, Pérez FJ, Sánchez MA, et al.: Transvaginal NOTES-assisted laparoscopic nephrectomy: a survival study in a sheep model. Surg Endosc. 2012; 26(4): 926–932. PubMed Abstract | Publisher Full Text\n\nLima E, Rolanda C, Correia-Pinto J: Transvesical route for NOTES urological applications: advances & controversies. Arch Esp Urol. 2012; 65(3): 385–392. PubMed Abstract\n\nBazzi WM, Stroup SP, Cohen SA, et al.: Feasibility of transrectal hybrid natural orifice transluminal endoscopic surgery (NOTES) nephrectomy in the cadaveric model. Urology. 2012; 80(3): 590–595. PubMed Abstract | Publisher Full Text\n\nBazzi WM, Stroup SP, Cohen SA, et al.: Comparison of transrectal and transvaginal hybrid natural orifice transluminal endoscopic surgery partial nephrectomy in the porcine model. Urology. 2013; 82(1): 84–89. PubMed Abstract | Publisher Full Text\n\nEyraud R, Laydner H, Autorino R, et al.: Robot-assisted transrectal hybrid natural orifice translumenal endoscopic surgery nephrectomy and adrenalectomy: initial investigation in a cadaver model. Urology. 2013; 81(5): 1090–1094. PubMed Abstract | Publisher Full Text\n\nBranco AW, Branco Filho AJ, Kondo W, et al.: Hybrid transvaginal nephrectomy. Eur Urol. 2008; 53(6): 1290–1294. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKaouk JH, Haber GP, Goel RK, et al.: Pure natural orifice translumenal endoscopic surgery (NOTES) transvaginal nephrectomy. Eur Urol. 2010; 57(4): 723–726. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKaouk JH, Khalifeh A, Laydner H, et al.: Transvaginal hybrid natural orifice transluminal surgery robotic donor nephrectomy: first clinical application. Urology. 2012; 80(6): 1171–1175. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHumphreys MR, Krambeck AE, Andrews PE, et al.: Natural orifice translumenal endoscopic surgical radical prostatectomy: proof of concept. J Endourol. 2009; 23(4): 669–675. PubMed Abstract | Publisher Full Text\n\nHumphreys MR, Sauer JS, Ryan AR, et al.: Natural orifice transluminal endoscopic radical prostatectomy: initial perioperative and pathologic results. Urology. 2011; 78(6): 1211–1217. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKallidonis P, Kontogiannis S, Kyriazis I, et al.: Laparoendoscopic single-site surgery in kidney surgery: clinical experience and future perspectives. Curr Urol Rep. 2013; 14(5): 496–505. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13331",
"date": "21 Apr 2016",
"name": "Prokar Dasgupta",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13332",
"date": "21 Apr 2016",
"name": "Maria Ribal",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13333",
"date": "21 Apr 2016",
"name": "Jens Rassweiler",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-716
|
https://f1000research.com/articles/4-135/v1
|
29 May 15
|
{
"type": "Antibody Validation Article",
"title": "Purification and characterization of GAD65-specific monoclonal autoantibodies",
"authors": [
"Wei Jiang",
"Henriette Macmillan",
"Anne-Marie Madec",
"Elizabeth D. Mellins",
"Henriette Macmillan",
"Anne-Marie Madec"
],
"abstract": "Autoantibodies against antigens expressed by insulin-producing β cells are circulating in both healthy individuals and patients at risk of developing Type 1 diabetes. Recent studies suggest that another set of antibodies (anti-idiotypic antibodies) exists in this antibody/antigen interacting network to regulate auto-reactive responses. Anti-idiotypic antibodies may block the antigen-binding site of autoantibodies or inhibit autoantibody expression and secretion. The equilibrium between autoantibodies and anti-idiotypic antibodies plays a critical role in mediating or preventing autoimmunity. Herein, using GAD65/anti-GAD65 autoantibodies as a model system, we aimed at establishing reliable approaches for purification of highly pure autoantibodies for the downstream investigation of molecular mechanisms underlying such a network.",
"keywords": [
"GAD65-specific",
"monoclonal autoantibody",
"affinity purification",
"autoantibody production"
],
"content": "Introduction\n\nType 1 diabetes (T1D) is an autoimmune disorder characterized by the immune-mediated destruction of the insulin-producing β cells in the pancreas. Human islet cells express the 65-kDa isoform of glutamic acid decarboxylase (GAD65), which is one of the most common autoantigens associated with the development of T1D. Anti-GAD65 autoantibodies (GAD65Abs) are detectable several years before diabetes and present in over 70% of patients at the time of diagnosis1. It has been suggested that healthy individuals also generate GAD65Abs, which are sufficiently neutralized by anti-idiotypic antibodies (anti-Id Abs), resulting in protection from GAD65-specific islet destruction2,3. Probably because the antigen-binding region of GAD65Abs is blocked by anti-Id Abs, circulating GAD65Abs in sera of healthy individuals are not detectable using GAD65-specific methods. The decline of anti-Id Abs in patients developing T1D, on the contrary, unmasks GAD65Abs, which then serve as critical serum markers in prediction and diagnostics of diabetes4. Studies of the interaction between GAD65 and recombinant GAD65Abs have suggested immunodominant epitopes on GAD655–9. However, how the recognition of these epitopes by GAD65Abs drives islet destruction, and how anti-Id Abs block GAD65Ab-mediated auto-reactivity are largely unknown. In order to generate anti-Id Abs aimed at understanding of pathophysiologic mechanism(s), and more importantly, preventing GAD65 autoreactivity, it is necessary to isolate and utilize native GAD65Abs rather than synthesizing recombinant proteins. However, no published data have ever reported on the quality of purified GAD65Abs for such aims, even though two of these human Abs (b96.11 and b78)10–13 are commercialized.\n\nCertain limitations stem from technical issues in the purification and characterization of native GAD65Abs originated from T1D patients. The most efficient way to produce monoclonal autoantibodies in vitro is to generate monoclonal B cell lines, culture them in batches, and purify the Abs from the culture supernatant. Although many established methods have been standardized for Ab purification14, the polymorphic nature of Abs and the diverse culture conditions of Ab-secreting cell lines may impede the achievement of native autoantibody products with satisfactory quality and purity. Utilization of impure GAD65Abs in the generation of anti-Id Abs and determination of their protective role in T1D pathogenesis may lead to unconvincing or inconclusive results.\n\nIn this report, we evaluated multiple strategies for the purification of two human monoclonal GAD65Abs: DPA and DPD10. Our goal was to isolate a pure population of Abs with minimal contaminants. We also determined GAD65-binding affinity of these two autoantibodies as the initial step of molecular characterization.\n\n\nMaterials and methods\n\nDetailed information on reagents used in this study is listed in Table 1.\n\nThe monoclonal B cell lines secreting either DPA or DPD were immortalized by Epstein-Barr virus (EBV) transformation as described10. These cell lines were maintained in complete Iscove’s modified Dulbecco’s medium (IMDM); or adapted to serum-free medium by diluting at a ratio of 1:2–1:3 every three days followed by a complete replacement after 10 days. Five million live cells were pelleted and reverse transcriptase polymerase chain reaction (RT-PCR) performed with the SuperScript III First-Strand Synthesis System (Life Technology) and antibody-specific primers (Table 2).\n\n* SN: sense primer. All SN primer sequences were described previously10.\n\n** ASN: antisense primer.\n\n*** CTdomain: the oligonucleotide primes the 3’-end of the cytoplasmic tail of membrane Ig.\n\nThe supernatants of cell cultures containing Abs were filtered through a 0.22 μm membrane to remove cell debris. Abs were purified from the supernatant by affinity chromatography (as per manufacturer’s instructions (Table 1)), followed by size exclusion chromatography (SEC) using a Superdex 200 gel filtration column (GE Healthcare). Fractions containing monomeric forms of each protein were pooled and analyzed by Coomassie stain or western blot.\n\nPurified immunoglobulin G (IgG) products were reduced in sodium-dodecyl-sulphate (SDS) -containing Laemmli sample buffer with freshly added β-mercaptoethanol (βME) and denatured by boiling at 100°C for 10 min before separation by gel electrophoresis using Mini-PROTEAN TGX precast polyacrylamide gels (Bio-Rad). The gels were stained with SimplyBlue SafeStain (Life Technology) and destained with Milli-Q water for at least 1 h before imaging of IgG heavy and light chains. To differentiate the heavy and light chains of human IgG from non-specific contaminants co-purified from cell culture supernatant, proteins on the gel were transferred to Immobilon-P membrane (EMD Millipore) for human IgG detection. Goat F(ab’)2 anti-human Ig (2.5 mg/ml, Life Technology, Inc; used at 1:3000 dilution) followed by HRP-donkey anti-goat IgG (0.4 mg/ml, Santa Cruz Biotechnology, Inc; used at 1:10000 dilution) (see Table 3 for full Ab information) were used to detect human Ig.\n\nRecombinant GAD65 (a gift from Peter van Endert, Institut National de la Santé et de la Recherche Médicale, France) in 20 mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES)+1 mM pyridoxal phosphate (PLP)+50% Glycerol, pH 7.4, was stored in aliquots at -80°C; and the reactivity was verified by ELISA using commercially available mouse anti-GAD65 IgG1 and horseradish peroxidase (HRP) labeled goat anti-mouse IgG1 (Table 3). The ELISA protocol for GAD65/autoantibody interaction has been described (see Table 4).\n\n\nResults\n\nBoth GAD65Abs purified in this study belong to the human IgG1 (γ1) subclass; DPA uses a λ light chain and DPD uses a κ light chain10. Prior to the purification of soluble DPA or DPD IgG from cell culture supernatant, we first validated Ig cDNA expression in each cell line using standard RT-PCR (Figure 1). Note that we used an anti-sense oligonucleotide to prime the 3'-end of membrane IgG heavy chain cytoplasmic domain instead of one priming the 3'-end of the IgG heavy chain constant region used elsewhere, in order to generate the entire sequence of the heavy chain (Supplementary file S1).\n\nThe RT-PCR amplified heavy chain cDNA using the indicated 5' primer and the 3' cytoplasmic-tail-specific primer, or the amplified light chain cDNA using the indicated 5' primer and the 3' constant-region-specific primer, are shown. Note that the PCR product amplified by Vλ1 from DPA-secreting cell line provided the same sequence as the one amplified by Vλ3, indicating that Vλ1 may result in non-specific primer annealing and PCR amplification.\n\nAlthough both anti-GAD65 Ab-secreting cell lines are derived from peripheral blood mononuclear cells (PBMCs) of a T1D patient10, their culture conditions are significantly different. The DPA cell line expanded well in both serum-supplemented and serum-free medium, while the DPD cell line survived only in serum-supplemented medium. Fetal bovine serum (FBS) is widely used in tissue-culture medium to provide essential proteins, nutrients and other uncharacterized factors for optimum cell growth; however, the presence of bovine IgG (bIgG) in the serum (up to 50 mg/L) is the main source of contamination in human IgG (hIgG) purification. Bovine serum albumin (BSA) is also commonly used at a high concentration in culture medium (can be over 1 mg/ml), and binds non-specifically during the protein purification process.\n\nAffinity purification using antigens or IgG-binding proteins (e.g., Protein A, G and L) is very effective for Ab production, with antigen affinity purification being the most specific technique and providing the purest batches of antibody. However, GAD65Ab purification using recombinant GAD65 (rGAD65) for antigen-specific affinity purification is difficult because rGAD65 is unstable and requires pyridoxal phosphate (PLP) for stabilization. Considering the inevitable exposure of rGAD65 pre-coupled to resin to the extreme pH (<4 or >10) in elution and regeneration steps, this would not be a viable option. We therefore chose IgG-binding proteins in our attempt to affinity purify GAD65Abs without potential protein contaminants. Both Protein A and G recognize the Fc domain of IgG from human and bovine sera, while protein L binds to κ light chain. Gammabind sepharose beads (GE healthcare) use a recombinant form of Protein G (rProtein G), which significantly reduces the non-specific binding of BSA to the resin. Purification of IgG from the supernatant of DPA cell culture (grown in FBS-containing medium) on rProtein G resin resulted in purer IgG (Figure 2A), than using native Protein A resin (nProtein A) (Figure 2B). However, the purified IgG products from both rProtein G and nProtein A still contained a high molecular-weight (MW; MW>100 kDa) component besides the anticipated heavy chain (~50 kDa) and light chain (25 kDa) on coomassie-stained protein gels. Western blotting analysis suggested that this component did not belong to human Ig (Figure 2C). The relative percentage of contamination with the high MW protein in IgG purified using nProtein A was significantly lower than when purified with rProtein G (Figure 2A, Figure 2B). This component may reflect bIgG-associated contaminants, as bIgG has lower binding affinity for nProtein A than rProtein G. To test this, we gradually adapted DPA cells from FBS-containing medium to FBS-free medium and were able to affinity-purify hIgG from the culture supernatant without bIgG using rProtein G (Figure 2D). We further separated DPA hIgG from any BSA contamination by SEC. The comparison between DPA purified using different methods and bIgG purified from pure FBS confirmed that the high MW contaminate is associated with bIgG (Figure 2D and Figure 3). Importantly, we demonstrated that serum-free culture is key to isolating highly pure DPA hIgG.\n\n(A, B) GAD65Ab-secreting cell lines were cultured with or without FBS, as indicated in parentheses, and the culture supernatant was applied to a pre-packed column containing one of the IgG-binding resins (right-pointing arrows) for affinity purification. Shown are Coomassie-stained gel images. S: supernatant; FT: flow through; W: wash; E: eluate. (C) Western blotting analysis of eluted proteins from (A) using anti-human Ig antibodies. (D, E) Eluate from (A) and (B) was applied to a second column containing another IgG-binding resin or applied to a gel filtration column for size exclusion chromatography (SEC). Fractions (F) eluted from the gel filtration column were pooled before analysis by gel electrophoresis and Coomassie staining. Pure FBS was also applied to the gammabind resin-containing column for purification of bovine IgG. DPD (FBS)* indicates DPD culture supernatant pre-depleted with gammabind sepharose (Original gel images in Supplementary materials S2).\n\n(A) DPA with bovine IgG eluted in more fractions (10–13 ml, 1ml per fraction), likely containing bIgG, unidentified bIgG-associated proteins, and BSA. (B) Pure DPA without bIgG mainly eluted at two fractions (11 and 12 ml), which can be easily separated from BSA (~66.5 kDa, fraction 13) based on the difference in their sizes.\n\nIn contrast, DPD did not grow well in the serum-free medium we tested, and thus we opted to use Protein L as an alternative method to obtain more pure hIgG from this line. Protein L binds the light chain of IgG and DPD has a κ light chain. Notably, no previous evidence suggested that Protein L distinguishes κ chain of hIgG from bIgG; however, we found that Protein L affinity purification followed by SEC separation generated DPD hIgG with satisfactory purity and no detectable bIgG or bIgG-associated high MW proteins even though DPD cell culture contains 10% FBS (Figure 2E). We also demonstrated that ion-exchange chromatography is not appropriate to separate hIgG from bIgG, as the high MW bIgG-associated protein(s) were present in all fractions eluted from anion or cation exchange columns (Figure 4).\n\nNeither cation nor anion exchange separated hIgG from bIgG, as the non-specific bIgG associated band on the protein gel was present in all eluted fractions that contained IgG.\n\nWe then determined the binding affinity of the purified DPA and DPD to rGAD65 by ELISA (Figure 5). Given the instability of rGAD65, the measurement of its concentration was inaccurate. To overcome this problem, we coated the ELISA plate with two concentrations of rGAD65 (10–100 nM) differing by 3-fold and incubated immobilized rGAD65 with titrated amounts of purified DPA or DPD monoclonal Abs at 37°C for 2 h. The concentration of immobilized rGAD65 did not influence the calculation of the dissociation constant (KD). We assumed that the duration of incubation was sufficient for the interaction between rGAD65 and GAD65Ab to reach equilibrium and fitted the data to a single site binding equation:\n\ny=Bmax*x/(KD+x)\n\nto estimate KD (Table 5). Purified DPA has over 100-fold higher rGAD65-binding affinity (the inverse of KD) than purified DPD.\n\n96-well plates were coated with two different concentrations of rGAD65 before incubation with different concentrations of (A) DPA and (B) DPD autoantibodies. The amount of GAD65Ab/rGAD65 complexes at equilibrium were measured by ELISA and plotted against the concentration of GAD65Abs. Data were fit to a single site binding equation for calculation of the dissociation constant.\n\n\nConclusions\n\nTo the best of our knowledge, purification and characterization of native GAD65Ab, free from culture medium-derived contaminants such as bIgG and BSA, have not been reported previously, in spite of the availability of monoclonal cell lines secreting these Abs10,11. Our goal was to obtain a very pure preparation of GAD65-specific hIgG. Here, we demonstrate several strategies to overcome limitations associated with affinity purification that would be applicable to the purification of many other antibodies: (1) antigen-specific affinity purification is always superior, if the autoantigen itself can be easily produced and can tolerate exposure to pH extremes; (2) when dealing with an unstable autoantigen (most often), the attempt to adapt cells to serum-free medium is worthwhile to avoid bIgG contamination; (3) Protein L recognizes the light chains of Ig from different species, however, as we have shown here Protein L may preferentially bind human rather than bovine κ chain and provide an alternative approach to purification of autoreactive hIgG(κ).\n\nIt is of interest that there is over 100-fold difference in the rGAD65-binding affinity between DPA and DPD. Without understanding the mechanism, it is hard to predict the relationship between autoantigen binding affinity and the severity of disease. However, this finding reminds us that low affinity autoantibodies indeed exist, but are less likely to be detected in diagnostic tests, considering the binding of GAD65Abs by anti-Id Abs. Therefore, the detection threshold in diagnostic tests for measuring GAD65Abs or other autoantibodies in patient sera may need further optimization for a more thorough monitoring of low affinity autoantibodies and prediction of T1D.",
"appendix": "Author contributions\n\n\n\nWJ and EDM conceived the study. WJ designed the experiment, carried out the research and prepared the first draft of the manuscript. HM contributed to the design of experiments and provided expertise in cell culture. AM provided the DPA and DPD cell lines. All authors were involved in the preparation and revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work was supported by National Institutes of Health Grants AI095813 and AI075253 (both to E.D.M.), the Stanford NIH/NCRR CTSA award UL1 RR025744 (to W.J.), National Institutes of Health/National Center for Research Resources Clinical and Translational Science Award UL1 RR025744 (to H.M.), and the Lucile Packard Foundation for Children’s Health. H.M. was also supported by National Institutes of Health Training Grant T32 AI07290 to the Stanford Interdisciplinary Program in Immunology.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe thank Peter van Endert (Institut National de la Santé et de la Recherche Médicale, France) for providing the recombinant GAD65 protein and Taejin Yoon (former member of the Mellins laboratory) for providing advice and expertise in protein purification.\n\n\nSupplementary Materials\n\nSequences for human IgG DPA and DPD\n\nClick here to access the data\n\nOriginal gel images for Figure 2\n\nClick here to access the data\n\n\nReferences\n\nTaplin CE, Barker JM: Autoantibodies in type 1 diabetes. Autoimmunity. 2008; 41(1): 11–18. PubMed Abstract | Publisher Full Text\n\nOak S, Gilliam LK, Landin-Olsson M, et al.: The lack of anti-idiotypic antibodies, not the presence of the corresponding autoantibodies to glutamate decarboxylase, defines type 1 diabetes. Proc Natl Acad Sci U S A. 2008; 105(14): 5471–5476. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWang X, Zhang A, Liu Y, et al.: Anti-idiotypic antibody specific to GAD65 autoantibody prevents type 1 diabetes in the NOD mouse. PLoS One. 2012; 7(2): e32515. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLarsson HE, Jönsson I, Lernmark A, et al.: Decline in titers of anti-idiotypic antibodies specific to autoantibodies to GAD65 (GAD65Ab) precedes development of GAD65Ab and type 1 diabetes. PLoS One. 2013; 8(6): e65173. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRichter W, Shi Y, Baekkeskov S: Autoreactive epitopes defined by diabetes-associated human monoclonal antibodies are localized in the middle and C-terminal domains of the smaller form of glutamate decarboxylase. Proc Natl Acad Sci U S A. 1993; 90(7): 2832–2836. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPowers AC, Bavik K, Tremble J, et al.: Comparative analysis of epitope recognition of glutamic acid decarboxylase (GAD) by autoantibodies from different autoimmune disorders. Clin Exp Immunol. 1999; 118(3): 349–356. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSchwartz HL, Chandonia JM, Kash SF, et al.: High-resolution autoreactive epitope mapping and structural modeling of the 65 kDa form of human glutamic acid decarboxylase. J Mol Biol. 1999; 287(5): 983–999. PubMed Abstract | Publisher Full Text\n\nFenalti G, Hampe CS, O’connor K, et al.: Molecular characterization of a disease associated conformational epitope on GAD65 recognised by a human monoclonal antibody b96.11. Mol Immunol. 2007; 44(6): 1178–1189. PubMed Abstract | Publisher Full Text\n\nFenalti G, Hampe CS, Arafat Y, et al.: COOH-terminal clustering of autoantibody and T-cell determinants on the structure of GAD65 provide insights into the molecular basis of autoreactivity. Diabetes. 2008; 57(5): 1293–1301. PubMed Abstract | Publisher Full Text\n\nMadec AM, Rousset F, Ho S, et al.: Four IgG anti-islet human monoclonal antibodies isolated from a type 1 diabetes patient recognize distinct epitopes of glutamic acid decarboxylase 65 and are somatically mutated. J Immunol. 1996; 156(9): 3541–3549. PubMed Abstract\n\nTremble J, Morgenthaler NG, Vlug A, et al.: Human B cells secreting immunoglobulin G to glutamic acid decarboxylase-65 from a nondiabetic patient with multiple autoantibodies and Graves’ disease: a comparison with those present in type 1 diabetes. J Clin Endocrinol Metab. 1997; 82(8): 2664–2670. PubMed Abstract | Publisher Full Text\n\nJury K, Sohnlein P, Vogel M, et al.: Isolation and functional characterization of recombinant GAD65 autoantibodies derived by IgG repertoire cloning from patients with type 1 diabetes. Diabetes. 2001; 50(9): 1976–1982. PubMed Abstract | Publisher Full Text\n\nPadoa CJ, Banga JP, Madec AM, et al.: Recombinant Fabs of human monoclonal antibodies specific to the middle epitope of GAD65 inhibit type 1 diabetes-specific GAD65Abs. Diabetes. 2003; 52(11): 2689–2695. PubMed Abstract | Publisher Full Text\n\nCommittee on Methods of Producing Monoclonal Antibodies, I. f. L. A. R., National Research Council. Monoclonal Antibody Production. National Academy Press. 1999. Reference Source"
}
|
[
{
"id": "11219",
"date": "01 Dec 2015",
"name": "David Soll",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article describes simple purification methods of highly pure antibodies from supernatant of human monoclonal B-cell cultures. However, all of the methods are already known. They are not new. One good thing that this article is showing is an example for the purification grades depending on the purification methods and culturing condition of the cells with and without FCS to avoid contamination with bovine antibodies. In my opinion, the abstract is not appropriated and overemphasized with points that are not directly related to this article.Characterization of the antibodies is weak.For the sentence on page 2 at the end of second paragraph “Utilization of impure GAD65Abs in the generation of anti-Id Abs and determination of their protective role in T1D pathogenesis may lead to unconvincing or inconclusive results.”, the authors have to explain with citations, why the purity of the antibody is important, and how the impure antibodies lead to unconvincing or inconclusive results.",
"responses": [
{
"c_id": "1940",
"date": "22 Apr 2016",
"name": "Wei Jiang",
"role": "Author Response",
"response": "Per Dr. Soll’s comment we have edited the title to “Optimized purification strategies for the elimination of non-specific products in the isolation of GAD65-specific monoclonal autoantibodies” to show that we have utilized known methods but we very specifically optimized the purification of the GAD65-specific antibodies. The abstract and introduction was updated to focus on our goal of optimization and validation of approaches for the purification of highly pure autoantibodies. These approaches are not novel, but the specific application to purification of anti-GAD65 antibodies were never evaluated. We agree that the characterization is weak and have updated the abstract and introduction to focus on purification. Highly purified autoantigen-specific antibodies could be suitable for the downstream study of mechanisms underlying the interaction between autoantigen and antibody or autoantibody and anti-idiotypic antibody which is beyond the scope of this current report. We have removed the sentence on page 2 that read “Utilization of impure GAD65Abs in the generation of anti-Id Abs and determination of their protective role in T1D pathogenesis may lead to unconvincing or inconclusive results.” The purity of autoantibody might be important, for example, in the generation of anti-Id Abs; otherwise, there might be anti-byproduct Abs in the final mixture, which can be problematic. Since there are currently no publications reporting an issue caused by non-specific by-products in the production of anti-GAD65 autoantibodies we have removed the sentence."
}
]
},
{
"id": "9336",
"date": "10 Mar 2016",
"name": "Xiao He",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a good Ab validation study, where the authors testified multiple established Ab purification strategies in an autoimmune disease model. Non-specific proteins present in an autoantibody product could potentially affect its usage in many aspects. For example, the authors pointed out that pure autoantibodies can be more efficient in the study of both autoantigens and anti-idiotypic antibodies, although neither were further characterized. As this article mainly validated and discussed purification strategies, it will be more straightforward to emphasize only on Ab production, but not characterization, which was not the focus as I can tell.",
"responses": [
{
"c_id": "1939",
"date": "22 Apr 2016",
"name": "Wei Jiang",
"role": "Author Response",
"response": "In light of Dr. He’s comment we have edited the title to “Optimized purification strategies for the elimination of non-specific products in the isolation of GAD65-specific monoclonal autoantibodies” in order to emphasize purification rather than characterization of the GAD65-specific antibodies. The abstract and introduction was also updated to reflect the focus on purification."
}
]
}
] | 1
|
https://f1000research.com/articles/4-135
|
https://f1000research.com/articles/5-715/v1
|
21 Apr 16
|
{
"type": "Review",
"title": "Recent advances in the understanding of male lower urinary tract symptoms (LUTS)",
"authors": [
"Arman A. Kahokehr",
"Peter J. Gilling",
"Arman A. Kahokehr"
],
"abstract": "In this review, we have looked at three important areas in understanding male lower urinary tract symptoms. These are improvement in terminology, detrusor underactivity, and nocturia. Benign prostatic hyperplasia leading to bladder outlet obstruction has been covered in a previous review.",
"keywords": [
"male lower urinary tract symptoms",
"LUTS",
"detrusor underactivity",
"nocturia"
],
"content": "Introduction\n\nLower urinary tract symptoms (LUTS) are a progressive and age-related, but not sex- or organ-specific, group of ‘complaints’ and comprise a combination of storage, voiding, and post-micturition symptoms1. LUTS are highly prevalent in the population2. They cause bother and impair quality of life2,3. They are strongly associated with ageing and represent a major health burden3.\n\nThe natural history of LUTS is dynamic. In some individuals, LUTS will persist and worsen over time and for others will wax, wane, and remit. In this review, we look at three important areas in the understanding of LUTS often not covered in the traditional descriptions. These are improvements in the terminology and diagnostics of LUTS, detrusor underactivity (DU), and nocturia.\n\nThe management of benign prostatic hyperplasia (BPH) leading to benign prostatic enlargement (BPE) and subsequent bladder outlet obstruction (BOO) has been covered in a previous F1000 review4.\n\nAlthough LUTS in men are traditionally thought to relate to BOO secondary to BPH, studies have shown that LUTS are often unrelated to prostate disease1. Bladder dysfunction may also cause LUTS, including detrusor overactivity and DU, as well as other structural or functional abnormalities of the urinary tract5. In addition, many non-urological conditions contribute to LUTS, especially nocturia1.\n\n\nImprovements in terminology\n\nClinical symptoms of BPH have been described as ‘prostatism’. This terminology was sufficient, but perhaps oversimplified, for another era6. However, not all men with histological BPH would develop clinical sequelae. Prostatism (incorrectly) implies an organ-specific source of symptoms. Recent advances in the understanding of these symptoms have concentrated on getting the terminology internationally accepted and standardised. The term LUTS describes the patients’ symptoms without implying a cause and has replaced older terms such as ‘prostatism’7.\n\nMale LUTS have traditionally been ascribed to BOO, which often is caused by BPE resulting from BPH. The transition in terminology with an emphasis on symptoms-based terminology greatly aids the clinical mindset and the understanding of the differences between clinical and laboratory-based diagnostics and helps dispel the misconceptions that all LUTS in men are caused by BPE.\n\n\nDetrusor underactivity\n\nDU is defined by the International Continence Society (ICS) as a voiding contraction of reduced strength or duration (or both), which prolongs urination or prevents complete emptying of the bladder within a ‘normal’ period of time (or both)8. DU is associated with voiding LUTS and a high post-void residual, which may predispose to urinary tract infection and acute urinary retention. The true prevalence is likely under-recognised, and the aetiology is not well understood. Several factors are likely to play a part, and there are several current pathophysiological models affecting myogenic function and neural control mechanisms as well as the efferent and afferent innervation.\n\nIt is currently unknown whether ageing is the primary cause or a condition necessary for the development of DU. The association between DU and ageing is well established, but there are conflicting data on bladder function and morphology in ageing animals. Afferent nerve density declines in ageing animals9; however, the age-related increase in urothelial transmitter release within the human bladder10 has not been reproduced in animal preparations. In both rats and mice, contractility either is diminished or increases with age11,12. Detrusor muscle loss usually12, but not always, increases with age.\n\nImpaired bladder contractility has been traditionally regarded as a major aetiological factor behind DU. However, over time, the bladder has decreased bladder afferent innervation, which is associated with DU and hence suggests complex pathology13. The urothelium, detrusor muscle, interstitial cells, and ganglia form a mechanical sensor and transducer system which activates afferent nerve fibres13. Each of these components could have an impact on lower urinary tract function by altering the release of neurotransmitters, thereby altering the excitability of sensory fibres and the contractility of the detrusor muscle in the urinary bladder. These afferent inputs monitor bladder volume and determine detrusor contraction during the voiding phase. By ending prematurely, these afferent signals may prematurely terminate the voiding reflex (as seen in diabetic cystopathy). Detrusor contraction force and duration are a result of efferent nerve activity, which in turn is dependent on sensory input, hence the potential for impaired afferent function to cause DU.\n\nIn vitro as well as in vivo animal studies show a correlation between oxidative stress and impaired contractility. Atherosclerosis-induced chronic bladder ischaemia significantly reduces detrusor contractility in animals14–16. It is still unknown whether these models will lead to therapeutic targets in humans.\n\nBOO has traditionally been seen as a prerequisite to LUTS in the ageing male population. However, whether a patient develops a higher post-void residual or eventual urinary retention is not dependent only on the grade of BOO. Animal studies have shown the relationship between bladder tissue mass and altered contractile responses to BOO17,18. Initially, there is muscle hypertrophy and hyperplasia leading to a thick-walled bladder, resulting in decreased tissue oxygen tension and chronic ischaemia. Contractility increases to compensate; however, after a variable period, detrusor function is impaired and results in a decompensating phase.\n\nDeterioration of bladder function proceeds slowly, and the reversibility of function after removal of the obstruction is often not seen once a patient is in the decompensated state. This may mean that reversing obstruction may not reverse the detrusor contractility that is lost.\n\nIncomplete emptying is common in patients with bladder dysfunction caused by neurological disease such as multiple sclerosis, Parkinson’s disease, and multiple system atrophy19,20. Dysfunction of the central control mechanism and voiding reflex may lead to DU by affecting the perception, integration, and outflow. In these models, DU can span a spectrum from a slightly decreased ability to generate pressure to a bladder that cannot generate any pressure. Though useful for understanding specific scenarios, these models are unlikely to be applied to a wider non-neurological model for patients with DU.\n\nUrodynamic tests are used to diagnose DU, either by assessing the relationship between bladder pressure and urinary flow or by interrupting voiding to measure detrusor pressure changes in isovolumetric conditions. Diagnostic criteria are based on urodynamic measurements relating to bladder contractility such as maximum flow rate and detrusor pressure at maximum flow (Table 1). Other estimates rely on mathematical formulas to calculate isovolumetric contractility indices or urodynamic ‘stop tests’. Most methods have practical disadvantages or are poorly validated. Contraction strength is only one aspect of bladder voiding function, however. The others are the speed and persistence of the contraction, which have not yet been incorporated in a widely accepted international diagnostic regime.\n\naPercentage with an acontractile detrusor. Pdet@Qmax, detrusor pressure at the time of maximum flow; Qmax, maximum flow.\n\nTreatments for DU have poor efficacy and tolerability and often fail to improve quality of life; muscarinic receptor agonists, in particular, have limited efficacy and frequent adverse effects. Bladder emptying might be achieved through Valsalva straining and intermittent or indwelling catheterization. Novel stem cell-based therapies have been attempted; however, new drugs that increase contractility are currently largely conceptual, and the complex pathophysiology of DU, the difficulty of achieving organ specificity of treatment, the limited availability of animal models, and the subjective nature of current outcome measures must be addressed as part of the development of such agents.\n\n\nNocturia\n\nIn normal adult physiology, the amount of urine produced at night is less than the functional bladder capacity, hence the ability to sleep at night without having to wake to void. This is based on adequate anti-diuretic hormone (ADH) production. Our knowledge of the pathophysiology of nocturia has not dramatically changed recently; however, it is recognised that nocturia is increasingly complex and multifactorial in aetiology. These factors can be divided into (a) bladder storage problem, (b) nocturnal polyuria, (c) global polyuria, and (d) mixed disorder or sleep disorder or both. In addition to the known causes of LUTS, several recent advances may help shed light on this very common and bothersome symptom. Nocturia is increasingly important and independently associated with sleep-disordered breathing21.\n\nCompared with normal controls, patients with nocturia have little or no diurnal variation in urine output and have greater nocturnal urine production. This is associated with the lack of a nocturnal increase in ADH level22. The exact physiological reasons underlying this defect in ADH secretion have not been fully elucidated. When used carefully, intranasal desmopressin may improve nocturnal polyuria and can extend the time to first void (an important aspect concerning sleep quality)23.\n\nOveractive bladder (OAB) syndrome is defined by the ICS as symptoms of urinary urgency, with or without urge incontinence, usually with increased daytime frequency and nocturia. Urgency is thought to be the primary driver of the syndrome of OAB. Nocturnal cystometrograms show the relationship with nocturnal detrusor overactivity and nocturia24. Urgency also increases the risk of having nocturia by 5- to 7-fold25; however, most patients with nocturia do not report urgency. These data point to a mixed and complex pathophysiology, which is not fully understood.\n\nObesity is associated with a two to threefold increased risk for nocturia26,27, and patients with nocturia have a higher risk of diabetes25. The association between diabetes/obesity and sleep apnoea is well established, but the association between nocturia and hypertension and coronary artery disease is less well elucidated. However, the increase in the prevalence of metabolic syndrome is likely to lead to further interest in the association between nocturia and this global problem.\n\n\nSummary\n\nThe understanding of LUTS is evolving and becoming increasingly complex. Consensus group reports point out that LUTS increase with age and are prevalent in both male and female patients1. LUTS are neither gender nor organ specific and are sometimes age related and sometimes progressive. There is a need to further investigate and understand LUTS, its causes, the resulting morbidity, and the therapeutic strategies necessary for this very common problem.\n\n\nAbbreviations\n\nADH, anti-diuretic hormone; BOO, bladder outlet obstruction; BPE, benign prostatic enlargement; BPH, benign prostatic hyperplasia; DU, detrusor underactivity; ICS, International Continence Society; LUTS, lower urinary tract symptoms; OAB, overactive bladder.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nChapple CR, Wein AJ, Abrams P, et al.: Lower urinary tract symptoms revisited: a broader clinical perspective. Eur Urol. 2008; 54(3): 563–9. PubMed Abstract | Publisher Full Text\n\nAgarwal A, Eryuzlu LN, Cartwright R, et al.: What is the most bothersome lower urinary tract symptom? Individual- and population-level perspectives for both men and women. Eur Urol. 2014; 65(6): 1211–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMartin SA, Haren MT, Marshall VR, et al.: Prevalence and factors associated with uncomplicated storage and voiding lower urinary tract symptoms in community-dwelling Australian men. World J Urol. 2011; 29(2): 179–84. PubMed Abstract | Publisher Full Text\n\nvan Rij S, Gilling P: Recent advances in treatment for Benign Prostatic Hyperplasia [version 1; referees: 2 approved]. F1000Res. 2015; 4: pii: F1000 Faculty Rev-1482. PubMed Abstract | Publisher Full Text | Free Full Text\n\nvan Koeveringe GA, Rademakers KL, Birder LA, et al.: Detrusor underactivity: Pathophysiological considerations, models and proposals for future research. ICI-RS 2013. Neurourol Urodyn. 2014; 33(5): 591–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKahokehr A, Gilling PJ: Landmarks in BPH--from aetiology to medical and surgical management. Nat Rev Urol. 2014; 11(2): 118–22. PubMed Abstract | Publisher Full Text\n\nAbrams P, Cardozo L, Fall M, et al.: The standardisation of terminology in lower urinary tract function: report from the standardisation sub-committee of the International Continence Society. Urology. 2003; 61(1): 37–49. PubMed Abstract | Publisher Full Text\n\nChapple CR, Osman NI, Birder L, et al.: The underactive bladder: a new clinical concept? Eur Urol. 2015; 68(3): 351–3. PubMed Abstract | Publisher Full Text\n\nMohammed HA, Santer RM: Distribution and changes with age of calcitonin gene-related peptide- and substance P-immunoreactive nerves of the rat urinary bladder and lumbosacral sensory neurons. Eur J Morphol. 2002; 40(5): 293–301. PubMed Abstract | F1000 Recommendation\n\nYoshida M, Inadome A, Maeda Y, et al.: Non-neuronal cholinergic system in human bladder urothelium. Urology. 2006; 67(2): 425–30. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZhao W, Aboushwareb T, Turner C, et al.: Impaired bladder function in aging male rats. J Urol. 2010; 184(1): 378–85. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nLai HH, Boone TB, Thompson TC, et al.: Using caveolin-1 knockout mouse to study impaired detrusor contractility and disrupted muscarinic activity in the aging bladder. Urology. 2007; 69(2): 407–11. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSmith PP: Aging and the underactive detrusor: a failure of activity or activation? Neurourol Urodyn. 2010; 29(3): 408–12. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAzadzoi KM, Tarcan T, Siroky MB, et al.: Atherosclerosis-induced chronic ischemia causes bladder fibrosis and non-compliance in the rabbit. J Urol. 1999; 161(5): 1626–35. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNomiya M, Yamaguchi O, Andersson KE, et al.: The effect of atherosclerosis-induced chronic bladder ischemia on bladder function in the rat. Neurourol Urodyn. 2012; 31(1): 195–200. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nWitthaus MW, Nipa F, Yang JH, et al.: Bladder oxidative stress in sleep apnea contributes to detrusor instability and nocturia. J Urol. 2015; 193(5): 1692–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSchröder A, Chichester P, Kogan BA, et al.: Effect of chronic bladder outlet obstruction on blood flow of the rabbit bladder. J Urol. 2001; 165(2): 640–6. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLevin RM, Schuler C, Leggett RE, et al.: Partial outlet obstruction in rabbits: duration versus severity. Int J Urol. 2013; 20(1): 107–14. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAraki I, Kitahara M, Oida T, et al.: Voiding dysfunction and Parkinson's disease: urodynamic abnormalities and urinary symptoms. J Urol. 2000; 164(5): 1640–3. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKhalaf KM, Coyne KS, Globe DR, et al.: Lower urinary tract symptom prevalence and management among patients with multiple sclerosis. Int J MS Care. 2015; 17(1): 14–25. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nParthasarathy S, Fitzgerald M, Goodwin JL, et al.: Nocturia, sleep-disordered breathing, and cardiovascular morbidity in a community-based cohort. PLoS One. 2012; 7(2): e30969. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nMoon DG, Jin MH, Lee JG, et al.: Antidiuretic hormone in elderly male patients with severe nocturia: a circadian study. BJU Int. 2004; 94(4): 571–5. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZong H, Yang C, Peng X, et al.: Efficacy and safety of desmopressin for treatment of nocturia: a systematic review and meta-analysis of double-blinded trials. Int Urol Nephrol. 2012; 44(2): 377–84. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKrystal AD, Preud'homme XA, Amundsen CL, et al.: Detrusor overactivity persisting at night and preceding nocturia in patients with overactive bladder syndrome: a nocturnal cystometrogram and polysomnogram study. J Urol. 2010; 184(2): 623–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTikkinen KA, Auvinen A, Johnson TM 2nd, et al.: A systematic evaluation of factors associated with nocturia--the population-based FINNO study. Am J Epidemiol. 2009; 170(3): 361–8. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nVaughan CP, Auvinen A, Cartwright R, et al.: Impact of obesity on urinary storage symptoms: results from the FINNO study. J Urol. 2013; 189(4): 1377–82. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAsplund R, Aberg HE: Nocturia in relation to body mass index, smoking and some other life-style factors in women. Climacteric. 2004; 7(3): 267–73. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNitti VW, Lefkowitz G, Ficazzola M, et al.: Lower urinary tract symptoms in young men: videourodynamic findings and correlation with noninvasive measures. J Urol. 2002; 168(1): 135–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKaplan SA, Ikeguchi EF, Santarosa RP, et al.: Etiology of voiding dysfunction in men less than 50 years of age. Urology. 1996; 47(6): 836–9. PubMed Abstract | Publisher Full Text\n\nAbarbanel J, Marcus EL: Impaired detrusor contractility in community-dwelling elderly presenting with lower urinary tract symptoms. Urology. 2007; 69(3): 436–40. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJeong SJ, Kim HJ, Lee YJ, et al.: Prevalence and Clinical Features of Detrusor Underactivity among Elderly with Lower Urinary Tract Symptoms: A Comparison between Men and Women. Korean J Urol. 2012; 53(5): 342–8. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFusco F, Groutz A, Blaivas JG, et al.: Videourodynamic studies in men with lower urinary tract symptoms: a comparison of community based versus referral urological practices. J Urol. 2001; 166(3): 910–3. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13503",
"date": "21 Apr 2016",
"name": "Lori Lerner",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13504",
"date": "21 Apr 2016",
"name": "Andreas Gross",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-715
|
https://f1000research.com/articles/5-714/v1
|
21 Apr 16
|
{
"type": "Review",
"title": "Statin non-adherence: clinical consequences and proposed solutions",
"authors": [
"Robert S. Rosenson"
],
"abstract": "Large controlled clinical trials have demonstrated reductions with statin therapy in cardiovascular events in patients presenting with acute coronary syndromes and stable coronary heart disease and individuals at high risk of a cardiovascular event. In trials of acute coronary syndromes and stable coronary heart disease, high-intensity statin therapy is more effective in the prevention of recurrent cardiovascular events than low-intensity statin therapy. Thus, evidence-based guidelines recommend in-hospital initiation of high-intensity statin therapy for all acute coronary syndrome patients. Clinical trials report high adherence to and low discontinuation of high-intensity statin therapy; however, in clinical practice, high-intensity statins are prescribed to far fewer patients, who often discontinue their statin after the first refill. A coordinated effort among the patient, provider, pharmacist, health system, and insurer is necessary to improve utilization and persistence of prescribed medications. The major cause for statin discontinuations reported by patients is perceived adverse events. Evaluation of potential adverse events requires validated tools to distinguish between statin-associated adverse events versus non-specific complaints. Treatment options for statin-intolerant patients include the use of a different statin, often at a lower dose or frequency. In order to lower LDL cholesterol, lower doses of statins may be combined with ezetimibe or bile acid sequestrants. Newer treatment options for patients with statin-associated muscle symptoms may include proprotein convertase subtilisin kexin 9 (PCSK9) inhibitors.",
"keywords": [
"statin therapy",
"cardiovascular events",
"coronary heart disease",
"acute coronary syndromes",
"statin therapy adherence"
],
"content": "Introduction\n\nAmong patients hospitalized for an acute coronary syndrome (ACS) and stable coronary heart disease (CHD), randomized controlled trials have demonstrated that high-dose/high-intensity atorvastatin therapy is more effective than placebo, low-intensity therapy with pravastatin, moderate-intensity therapy with simvastatin, or low-dose atorvastatin therapy in the reduction of recurrent cardiovascular disease (CVD) events1. In a meta-analysis, high-intensity statin therapy was more effective than control or low-moderate intensity for reducing the risk of vascular death (1.3% versus 1.5%, [0.88 {0.84–0.91}]) and all-cause mortality (2.3% versus 2.5%, [0.91{0.88–0.93}])2. Thus, the American College of Cardiology/American Heart Association (ACC/AHA) guidelines for the treatment of ACS and secondary prevention of CHD recommend the initiation of high-intensity statin therapy in patients with clinical atherosclerotic CVD (ASCVD) regardless of baseline low-density lipoprotein (LDL) cholesterol levels2. In contrast, European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) guidelines recommend reductions in LDL cholesterol to less than 1.8 mmol/L or by 50% or more3. The National Lipid Association (NLA) and International Atherosclerosis Society adopted a similar LDL cholesterol-centric perspective and recommend LDL cholesterol levels less than 1.8 mmol/L regardless of the statin dosage needed to achieve this target4,5. From the perspective of randomized clinical trials, the mandate for empiric high-intensity statins is particularly relevant for ACS patients in whom initiation of this therapy is recommended before hospital discharge6.\n\nData from ACS registries suggest that over 80% of patients are prescribed statins following a myocardial infarction (MI) or coronary revascularization7. However, few prior studies have reported the percentage of patients who filled prescriptions for high-intensity statins following CHD events. In ACS registries conducted from 2003 to 2008, utilization of statins ranged from 80 to 91%, while only 23–38% were prescribed high-intensity statins. In a real-world analysis of Medicare beneficiaries, which included hospitalizations for CHD between 2007 and 2011, only 27% with insurance coverage for medications were prescribed high-intensity statins after hospitalization for a coronary event8. The principal factor associated with being discharged and remaining on high-intensity statin therapy for 365 days was prior use of a high-intensity statin. These data suggest that clinicians focus on the LDL cholesterol rather than the clinical trial evidence supporting high-intensity statins that encompasses other atherothrombotic properties9. Utilization of high-intensity statins in Medicare beneficiaries diminished progressively during the ensuing year, such that an additional 24% of participants reduced their statin dosage or discontinued high-intensity statins8. Among patients hospitalized for a non-cardiovascular illness, who then have an in-hospital myocardial infarction, the use of high-intensity statins is lower10. At the time of this survey, simvastatin 80 mg was the only generic statin. Due to the safety concerns with this dosage of simvastatin, particularly in the elderly and in those patients taking multiple medications, simvastatin 40 mg daily was the more commonly prescribed dosage.\n\nUtilization and persistence of high-intensity statins represents an important performance measure6; however, the clinical consequences of non-adherence to high-intensity statin therapy have been less well studied. In preliminary data from a 5% sample Medicare population, poor adherence and discontinuation of high-intensity statin therapy after the first prescription fill was accompanied by higher rates of hospitalization for cardiovascular and non-cardiovascular causes and more deaths during the ensuing 5 years11.\n\nSince hospitalizations for recurrent cardiovascular events increase more rapidly in patients hospitalized for a MI than age- and sex-matched controls hospitalized for other causes, short-term and long-term secondary preventive measures are crucial to minimize the risk of recurrent events12. Thus, discontinuation of statins and other evidence-based secondary preventive therapies has implications for the patient’s future health as well as economic costs to the patient, their family, and society.\n\nSeveral reasons contribute to statin down-titration or discontinuation. In clinical trials, statin-associated adverse events (statin-associated muscle symptoms [SAMS]) are no different between participants assigned to statins or placebo13. However, clinical trials select individuals with lower risk for muscle events based on age, prior musculoskeletal complaints, renal function, and concomitant non-drug and drug therapies that interact with drug elimination pathways. Discontinuation of statins is more common among patients with side effects, which were reported by 60% of former users and 25% of current users14. Since statin intolerance is often symptom based, it is important to develop and administer validated measures of statin intolerance. The NLA proposed a clinical tool for the assessment of SAMS15 that was based on a retrospective analysis of the STOMP trial, which investigated the effects of statin medication on muscle performance16. In order to improve the accuracy of diagnosis of an adverse event, this index incorporates the fundamental process of de-challenge and re-challenge with either the same statin at a lower dosage or an alternate statin that has different drug elimination pathways that may be genetically based.\n\nNon-statin LDL cholesterol-lowering therapies have been evaluated in patients who report SAMS. These studies have randomized individuals who experienced SAMS with two statins that included one agent at the lowest approved dosages. Second-line LDL cholesterol-lowering agents often used in patients who experience SAMS include ezetimibe, bile acid sequestrants, and niacin. However, these agents have modest LDL cholesterol-lowering efficacy. In trials with fully human monoclonal antibodies to proprotein convertase subtilisin kexin 9 (PCSK9) inhibitors (alirocumab and evolocumab), SAMS were reported in fewer individuals and no more often than when treated with ezetimibe17–19. The mean LDL cholesterol reduction was 53–56% with evolocumab compared with 15–18% with ezetimibe17,18. Alirocumab reduced LDL cholesterol by 45% compared to 15% with ezetimibe19. Bempedoic acid (ETC-1002) inhibits ATP citrate lyase (ACL), a key enzyme that supplies substrate for cholesterol and fatty acid synthesis in the liver. Since bempedoic acid inhibits an enzyme earlier in the cholesterol synthetic pathway than statins, it is possible that adverse muscle symptoms caused by HMG-CoA reductase inhibition would also occur with drugs that inhibit metabolites such as mevalonate even earlier in the synthetic pathway. This agent was evaluated in a subgroup of 56 SAMS participants (37 ETC-1002 group and 19 placebo group) enrolled in a larger randomized, placebo-controlled trial; the mean difference in LDL cholesterol was 28.7% versus placebo20. Adverse muscle complaints were similar in the placebo and ETC-1002 treatment groups.\n\nThese trials have not incorporated a placebo-controlled challenge and re-challenge phase with statin therapy to ensure appropriate identification of SAMS individuals. The ODYSSEY ALTERNATIVE included a single-blind placebo run-in and excluded participants who reported SAMS with placebo19. In the second phase, continuing participants were randomized to double-blind treatment (2:2:1) with alirocumab, ezetimibe 10 mg daily, or atorvastatin 20 mg daily. On re-exposure to statin therapy, nearly 50% tolerated atorvastatin. SAMS were 39% less frequent with alirocumab versus atorvastatin. The GAUSS III trial design incorporated the fundamental concept for evaluation of adverse drug reactions through a randomized challenge and de-challenge treatment with placebo and atorvastatin 20 mg daily21. Thus, this trial design may serve as a state-of-the-art model for future such trials in SAMS patients. GAUSS III enrolled 511 patients with uncontrolled LDL cholesterol and history of intolerance to two or more statins22.\n\nCurrently, the phase III clinical outcome trials with PCSK9 inhibitors have not been reported23. The first large cardiovascular outcome trial with a PCSK9 inhibitor is expected to announce results in the second half of 201624. These trials have enrolled patients with cardiovascular disease who have elevated LDL cholesterol levels on moderate- to high-intensity statins and therefore do not address clinical outcomes in patients treated with PCSK9 monotherapy.\n\n\nConclusions\n\nNon-adherence to evidence-based secondary preventive LDL cholesterol-lowering statin therapies increases the risk for recurrent cardiovascular and non-cardiovascular events, and all-cause mortality. Coordinated efforts to improve adherence involve patient factors, provider behavior, and health system factors. Many patients who discontinue their medications perceive that non-specific complaints are drug related and then decide to terminate treatment on their own initiative without the input of healthcare professionals. Thus, it is important to engage in a dialogue concerning major adverse reactions with any medication and evaluate reported side effects with an objective clinical tool, such as the statin muscle index. Non-statin approaches are second-line therapies to LDL cholesterol, but they are ineffective in either lowering LDL cholesterol levels by more than 50% or achieving LDL cholesterol levels that meet established targets proposed by several consensus documents. Anti-PCSK9 antibodies are more effective LDL cholesterol-lowering agents than ezetimibe in multiple short-term studies. The efficacy, safety, tolerability, and long-term persistence of PCSK9 inhibitors await completion of large ongoing clinical trials. These trials have enrolled patients with cardiovascular disease, including ACS, who have LDL cholesterol levels ≥70 mg/dL on maximally tolerated moderate- to high-intensity statins. These trials did not specifically include patients with SAMS. Future trials with PCSK9 inhibitor monotherapy will be required to address the unmet need in high-risk patients who refuse or cannot tolerate statin treatment.",
"appendix": "Competing interests\n\n\n\nRobert S. Rosenson has acted on consulting/advisory boards for Akcea, Amgen, Astra Zeneca, GSK, Regeneron, and Sanofi; he has received an honorarium from Kowa; and he has received royalties from UpToDate, Inc.\n\n\nGrant information\n\nRobert S. Rosenson has received grant support to his institution from Amgen, Astra Zeneca, Catabasis, and Sanofi.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nCholesterol Treatment Trialists’ (CTT) Collaboration, Baigent C, Blackwell L, et al.: Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet. 2010; 376(9753): 1670–81. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nStone NJ, Robinson JG, Lichtenstein AH, et al.: 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014; 63(25 Pt B): 2889–934. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nEuropean Association for Cardiovascular Prevention & Rehabilitation, Reiner Z, Catapano AL, et al.: ESC/EAS Guidelines for the management of dyslipidaemias: the Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS). Eur Heart J. 2011; 32(14): 1769–818. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJacobson TA, Ito MK, Maki KC, et al.: National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1 - executive summary. J Clin Lipidol. 2014; 8(5): 473–88. PubMed Abstract | Publisher Full Text\n\nExpert Dyslipidemia Panel of the International Atherosclerosis Society Panel members: An International Atherosclerosis Society Position Paper: global recommendations for the management of dyslipidemia--full report. J Clin Lipidol. 2014; 8(1): 29–60. PubMed Abstract | Publisher Full Text\n\nBrilakis ES, Hernandez AF, Dai D, et al.: Quality of care for acute coronary syndrome patients with known atherosclerotic disease: results from the Get With the Guidelines Program. Circulation. 2009; 120(7): 560–7. PubMed Abstract | Publisher Full Text\n\nHirsh BJ, Smilowitz NR, Rosenson RS, et al.: Utilization of and Adherence to Guideline-Recommended Lipid-Lowering Therapy After Acute Coronary Syndrome: Opportunities for Improvement. J Am Coll Cardiol. 2015; 66(2): 184–92. PubMed Abstract | Publisher Full Text\n\nRosenson RS, Kent ST, Brown TM, et al.: Underutilization of high-intensity statin therapy after hospitalization for coronary heart disease. J Am Coll Cardiol. 2015; 65(3): 270–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nRosenson RS, Tangney CC: Antiatherothrombotic properties of statins: implications for cardiovascular event reduction. JAMA. 1998; 279(20): 1643–50. PubMed Abstract | Publisher Full Text\n\nYun H, Safford MM, Brown TM, et al.: Statin use following hospitalization among Medicare beneficiaries with a secondary discharge diagnosis of acute myocardial infarction. J Am Heart Assoc. 2015; 4(2): pii: e001208. PubMed Abstract | Publisher Full Text | Free Full Text\n\nColantonio LD, Monda KL, Huang L, et al.: Patterns of statin use and outcomes following myocardial infarction among Medicare beneficiaries. Presented at ESC, London UK. 2015. Reference Source\n\nLevitan EB, Muntner P, Chen L, et al.: Burden of Coronary Heart Disease Rehospitalizations Following Acute Myocardial Infarction in Older Adults. Cardiovasc Drugs Ther. 2016; 1–9. PubMed Abstract | Publisher Full Text\n\nGanga HV, Slim HB, Thompson PD: A systematic review of statin-induced muscle problems in clinical trials. Am Heart J. 2014; 168(1): 6–15. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCohen JD, Brinton EA, Ito MK, et al.: Understanding Statin Use in America and Gaps in Patient Education (USAGE): an internet-based survey of 10,138 current and former statin users. J Clin Lipidol. 2012; 6(3): 208–15. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nRosenson RS, Baker SK, Jacobson TA, et al.: The National Lipid Association's Muscle Safety Expert Panel. An assessment by the Statin Muscle Safety Task Force: 2014 update. J Clin Lipidol. 2014; 8(3 Suppl): S58–71. PubMed Abstract | Publisher Full Text\n\nParker BA, Capizzi JA, Grimaldi AS, et al.: Effect of statins on skeletal muscle function. Circulation. 2013; 127(1): 96–103. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSullivan D, Olsson AG, Scott R, et al.: Effect of a monoclonal antibody to PCSK9 on low-density lipoprotein cholesterol levels in statin-intolerant patients: the GAUSS randomized trial. JAMA. 2012; 308(23): 2497–506. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nStroes E, Colquhoun D, Sullivan D, et al.: Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol. 2014; 63(23): 2541–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMoriarty PM, Thompson PD, Cannon CP, et al.: Efficacy and safety of alirocumab vs ezetimibe in statin-intolerant patients, with a statin rechallenge arm: The ODYSSEY ALTERNATIVE randomized trial. J Clin Lipidol. 2015; 9(6): 758–69. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nThompson PD, Rubino J, Janik MJ, et al.: Use of ETC-1002 to treat hypercholesterolemia in patients with statin intolerance. J Clin Lipidol. 2015; 9(3): 295–304. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNissen SE, Dent-Acosta RE, Rosenson RS, et al.: Comparison of PCSK9 Inhibitor Evolocumab vs Ezetimibe in Statin-Intolerant Patients: Design of the Goal Achievement After Utilizing an Anti-PCSK9 Antibody in Statin-Intolerant Subjects 3 (GAUSS-3) Trial. Clin Cardiol. 2016; 39(3): 137–44. PubMed Abstract | Publisher Full Text\n\nNissen SE, Stroes E, Dent-Acosta RE, et al. GAUSS-3 Investigators.: Efficacy and tolerability of evolocumab vs ezetimibe in patients with muscle-related statin intolerance: The GAUSS-3 randomized clinical trial. JAMA. 2016. PubMed Abstract | Publisher Full Text\n\nGiugliano RP, Sabatine MS: Are PCSK9 Inhibitors the Next Breakthrough in the Cardiovascular Field? J Am Coll Cardiol. 2015; 65(24): 2638–51. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHusten L: CardioBrief: First PCSK9 drug outcomes trial due in 2016 - FOURIER set to finish ahead of schedule. Medpage Today. 2015. [Accessed 19 March 2016]. Reference Source"
}
|
[
{
"id": "13501",
"date": "21 Apr 2016",
"name": "Patrick Moriarty",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13502",
"date": "21 Apr 2016",
"name": "Evan Stein",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-714
|
https://f1000research.com/articles/5-713/v1
|
21 Apr 16
|
{
"type": "Method Article",
"title": "Comparing efficacy of a sweep net and a dip method for collection of mosquito larvae in large bodies of water in South Africa",
"authors": [
"Katherine K. Brisco",
"Anthony J. Cornel",
"Yoosook Lee",
"Joel Mouatcho",
"Leo Braack",
"Anthony J. Cornel",
"Yoosook Lee",
"Joel Mouatcho",
"Leo Braack"
],
"abstract": "In this study we tested an alternative method for collecting mosquito larvae called the sweep net catch method and compared its efficiency to that of the traditional dip method. The two methods were compared in various water bodies within Kruger National Park and Lapalala Wilderness area, South Africa. The sweep net catch method performed 5 times better in the collection of Anopheles larvae and equally as well as the dip method in the collection of Culex larvae (p =8.58 x 10-5). Based on 15 replicates the collector’s experience level did not play a significant role in the relative numbers of larvae collected using either method. This simple and effective sweep net catch method will greatly improve the mosquito larval sampling capacity in the field setting.",
"keywords": [
"larval sampling",
"Anopheles",
"Culex",
"sweep net",
"dipping"
],
"content": "Introduction\n\nTraditionally, the larval dip method, as described in detail below, has been the standard method for the collection and sampling of mosquito larvae (O’Malley, 1995). However, this method of collection has proven unsatisfactory for the collection of large numbers of Anopheles mosquito larvae from large water bodies needed for our mosquito genetics studies. Many species of Anopheles, such as An. funestus (Tuno et al., 2007) and An. coluzzii (Gimonneau et al., 2015), readily dive making them difficult to collect from large bodies of water. Collecting Anopheles larvae therefore often means spending considerable time in the field. Also, the larval dip method requires significant experience in dipping techniques and source analysis skills in order to successfully collect the desired genus of larvae (O’Malley, 1995), presenting challenges for a novice.\n\nThis limitation of the dipping method motivated us to evaluate a sweep net system similar to methods used by Trapido & Aitken (1953) and Robert et al. (2002) as an alternative approach for collecting larvae to increase catch numbers, especially of Anopheles, and reduce time spent collecting in the field. The method also had to be simple enough for a novice to successfully use. We named our modified sweep net approach the “sweep net catch (SNC)” method and tested it as described below.\n\n\nMethods\n\nA tray 5.7 cm deep × 45.7 cm in length × 31.8 cm in width (BioQuip®Products, Rancho Dominguez, CA- catalogue number 1426c) or a tray similar in size was pre-filled halfway with the cleanest water available from the collecting site and set aside. The sweep net was essentially designed as a sieve consisting of a 25 cm diameter metal ring mounted to the end of a 1.2 meter pole. White nylon or cotton fabric of fine mesh (177.8 × 177.8 mesh per cm or less) was sewn onto the metal ring so water could be sieved through the net. The net was held at a 45° angle and pushed through the water ahead or next to the collector to avoid casting a shadow on the water surface. The top half of the net was above the water surface and the bottom half below and we walked at a slow pace. A visual representation of this process can be seen in the first half of the accompanying Video (time point 0:04 – 1:20 minutes). This process was continued for ten minutes per trial. During the ten minute period, the net was periodically inverted and its contents transferred to the tray containing pre-filled water. After completing ten minutes of sweeping, any mosquito larvae present in the plastic tray were picked out of the tray using a pipette (BioQuip®Products, Rancho Dominguez, CA- catalogue number 4776) and set aside for further cleaning and storage.\n\nA 350 mL dipper (BioQuip®Products, Rancho Dominguez, CA- catalogue number 1132) attached to the end of an approximately 1.2 meter-long pole was used to scoop samples from the water. The collector then inspected the cup for the presence of mosquito larvae. If no larvae were present, the cup was emptied and the collector would try again in another nearby spot. If larvae were present, they were removed using a small pipette (BioQuip®Products, Rancho Dominguez, CA- catalogue number 4776) and transferred to another holding cup prior to taking another dip sample. The collector would continue this process for ten minutes. A visual representation of this process can be seen in the second half of the accompanying Video (time point 1:21 – 2:23 minutes).\n\nLarval collections took place in pools along the Shingwedzi River (23.11604°S; 31.37524°E) and at Lake Panic in Skukuza (24.98472°S; 31.5797°E) in the Kruger National Park, South Africa, and along the shores of a lake in the Lapalala Wilderness area (23.90125°S; 28.29387°E) in the Limpopo Province, South Africa. Five replicate trials were performed along the Shingwedzi River, four trials in Skukuza, and six trials in Lapalala. For each trial the dip method was performed by one collector and the SNC method was performed by another, resulting in fifteen replicates of each method. Collectors, ranging in experience level, alternated collection methods they performed between sites.\n\nAll larvae collected were separated by genus and counted. The method used for collection (dip method or SNC method) as well as the collector’s name and experience level (experienced – having dipped for larvae before or novice – having never dipped for larvae before) were also recorded. Cornel and Braack were considered experienced collectors and all others were novices who had never dipped for larvae before. The raw data used for data analysis is available (see Data availability).\n\nA relative abundance of mosquito specimens grouped by genus per collection was calculated. The Wilcoxon-Rank-Sum test implemented in the R statistical package version 3.0.0 was used to compare the efficacy of the two collection methods (Figure 1) and to see if experience level of collectors was a contributing factor in the relative proportions of each genus collected using each collection method (Figure 2).\n\nEach collection constitutes a ten minute long sweep net and a ten minute long dip.\n\n\nResults\n\nAs shown in Table 1, a total of 99 Anopheles larvae were collected using the dip method, of which 77 were from Shingwedzi, 4 from Skukuza, and 18 from Lapalala. A total of 605 Anopheles larvae were collected using the SNC method, of which 530 were from Shingwedzi, 20 from Skukuza, and 55 from Lapalala. A total of 61 Culex larvae were collected using the dip method, 22 being from Shingwedzi, 8 from Skukuza, and 31 from Lapalala. A total of 176 Culex larvae were collected using the SNC method, 63 of these from Shingwedzi, 85 from Skukuza, and 28 from Lapalala.\n\nThe number of collected larvae were highly variable between trials, reflecting the general larval density variation between sites. To control for this site variation and compare the relative performance of each collection method, a relative proportion of each genus collected per trial was calculated. The Wilcoxon-Rank-Sum tests on the relative abundance data showed (Figure 1) the SNC method (mean relative abundance = 0.51 ± 0.28) performed significantly better than the dip method (mean relative abundance = 0.12 ± 0.13) in the collection of Anopheles larvae (Wilcoxon-Rank-Sum test P = 8.58 × 10-5). There was no significant difference in the collection of Culex larvae between the SNC method (mean relative abundance = 0.25 ± 0.29) and the dip method (mean relative abundance = 0.12 ± 0.20) (Wilcoxon-Rank-Sum test P = 0.050).\n\nThe collector’s experience was not a contributing factor in the relative proportions of each genus collected using either the SNC method or the dip method (Wilcoxon-Rank-Sum test P ≥ 0.21) (Figure 2).\n\n\n\n\nDiscussion\n\nMany of the Anopheles larvae collected were reared to adults and identified using a morphological key (Gillies & Coetzee, 1987) and molecular assays (Koekemoer et al., 2002; Lee et al., 2014; Scott et al., 1993) (see Supplementary material for methods). The species collected included An. arabiensis, An. quadriannulatus, An. coustani, An. pretoriensis and An. funestus group (An. parensis, An. rivulorum, An. leesoni and an as yet undetermined species).\n\nThe SNC method performed on average five times better than the dip method in the collection of Anopheles larvae. The SNC samples a larger volume of water than the dip method which likely contributes to the higher catches of Anopheles larvae. Many species, such as An. funestus, An. arabiensis (Tuno et al., 2007) and An. coluzzii (Gimonneau et al., 2015), are known to dive and remain in the substrate for long periods of time when there has been a disturbance on the surface or for feeding purposes. The larger net diameter allows the increased capture of these larvae as they begin to submerge. In shallow parts of the water body the SNC also scoops along the substrate and may collect larvae that have dived and rested there. From our observations the SNC method disturbs the surface of the water less than dipping, which possibly reduces diving behavior.\n\nMore Anopheles may also have been captured using the SNC because collectors spent more time sieving through the water in the 10 minute period, thus covering a larger area, whereas during the 10 minutes of collecting, the dip method required spending time actively separating out the larvae after each dip. Depending on the water quality and larval density, the final larval separation for the SNC can be a time-consuming task as mud and debris can make it difficult to see the larvae in the tray. However, the overall processing time (collection and sample separation) per specimen for the SNC (1.09 ± 0.97 minutes) was 75% less than the dip method (4.17 ± 3.95 minutes) (Figure 3). To calculate the average time spent collecting larvae with the SNC we added 12 seconds of processing time for each larva collected to the 10 minutes of sweeping for each trial. This time was then divided by the total number of larvae collected in that trial (Data availability). The average time collecting larvae with the dip method was calculated by dividing the 10 minute dipping period by the total number of larvae collected for each trial (Data availability).\n\nMost of the Culex larvae collected were successfully reared to adults and identified using the key in Jupp (1996). The collections consisted of Cx. poicilipes, Cx. simpsoni and Cx. neavei. It has been shown that many species of Culex larvae exhibit significant diving behavior (Workman & Walton, 2003), which suggests the SNC would also have increased efficiency in collecting these larvae as long as the surface was not too disturbed and the collector’s shadow was cast behind them. However, due to the relatively low numbers of Culex larvae collected throughout our study, we suspect there wasn’t a high enough population density of these larvae at any of our trial sites to accurately determine if either method was more efficient for the collection of Culex larvae. We recommend further research be conducted in areas where Culex larvae occur at higher densities to further evaluate whether the SNC performs better than the dip method.\n\nEven though our current data does not show a significant difference in the relative proportion of larvae collected due to the collector’s experience, our personal observations suggest the SNC is a good method for novices to use. The SNC allows the inexperienced handler to easily collect high numbers of mosquito larvae without analyzing their technique or source characteristics as is required to be successful using the dip method (O’Malley, 1995). A larger trial size may illuminate more conclusively if experience level does affect collection performance.\n\n\nConclusion\n\nWe endorse and encourage the sweep net method as a preferred technique for larval collection that can be easily used in the field setting regardless of experience level. Our SNC method is particularly effective in capturing Anopheles mosquito larvae. The increased sensitivity of SNC towards Anopheles larvae may be due to (1) the sampling of a larger volume of water than the dipping cup, and/or (2) reducing disturbance of the water surface resulting in fewer larval dives. This increased sensitivity of the SNC method makes it an appropriate larval collection tool for studies when more accurate assessments of larval densities are required and when there is less time available to sample for larvae. In addition, the simplicity of the SNC method makes it a recommended choice for novice collectors. Further research is suggested to more rigorously test if a significant correlation between the collector’s experience level and the relative proportion of larvae collected by either method exists.\n\n\nData availability\n\nFigshare: Visual representation of both the sweep net catch and dip larval collection methods as performed by Braack and Cornel. 10.6084/m9.figshare.3123274 (Brisco et al., 2016a).\n\nFigshare: Raw larval collection data for all 15 replicates, including the relative abundance of Anopheles and Culex collected and the estimated time taken to collect one larva for each replicate. 10.6084/m9.figshare.3123463 (Brisco et al., 2016b).",
"appendix": "Author contributions\n\n\n\nAC and LB conceived the study, designed the experiments, conducted the field work, and filmed the accompanying video. YL performed An. gambiae complex identification assays and data analysis and made figures for the manuscript. KB compiled and edited the accompanying video and made the table for the manuscript. JM performed the An. funestus group molecular assays. All authors were involved in the writing of the manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nBoth Cornel and Braack were beneficiaries of a Carnegie African Diaspora Fellowship Program grant (IIE Grantee ID: 15410201) which partly enabled this study.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nThe authors would like to thank Takalani Nelufule (TN) of the Zoonoses Research Unit of the University of Pretoria, as well as the following students of the Lapalala Wilderness School Phumzie Mbonani (PM) and Thoko Jiyane (TJ), and Kruger National Park staff Danny Govender and Purvance Shikwambana for their assistance with the larval collections within Lapalala. Danny Govender also coordinated the field trips in Kruger National Park.\n\n\nSupplementary material\n\nLarval rearing methods.\n\nClick here to access the data\n\n\nReferences\n\nBrisco KK, Cornel AJ, Lee Y, et al.: Visual representation of both the sweep net catch and dip larval collection methods as performed by Braack and Cornel. Figshare. 2016a. Data Source\n\nBrisco KK, Cornel AJ, Lee Y, et al.: Raw larval collection data for all 15 replicates, including the relative abundance of Anopheles and Culex collected and the estimated time taken to collect one larva for each replicate. Figshare. 2016b. Data Source\n\nGillies MT, Coetzee M: A supplement to the Anophelinae of Africa south of the Sahara. The South African Institute for Medical Research Publishers, Johannesburg. 1987; ISBN 0620 10321 3. Reference Source\n\nGimonneau G, Bayibeki AN, Baldet T, et al.: Life history consequences of larval foraging depth differ between two competing Anopheles mosquitoes. Ecol Entomol. 2015; 40(2): 143–149. Publisher Full Text\n\nJupp PG: Mosquitoes of Southern Africa. Ekogilde Publishers, Hartebeespoort, 1996. ISBN 0.9583889-4-6. Reference Source\n\nKoekemoer LL, Kamau L, Hunt RH, et al.: A cocktail polymerase chain reaction assay to identify members of the Anopheles funestus (Diptera: Culicidae) group. Am J Trop Med Hyg. 2002; 66(6): 804–11. PubMed Abstract\n\nLee Y, Marsden CD, Nieman C, et al.: A new multiplex SNP genotyping assay for detecting hybridization and introgression between the M and S molecular forms of Anopheles gambiae. Mol Ecol Resour. 2014; 14(2): 297–305. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLee Y, Olson N, Yamasaki Y, et al.: Absence of kdr resistance alleles in the Union of the Comoros, East Africa [version 1; referees: 2 approved, 1 approved with reservations]. F1000 Res. 2015; 4: 146. PubMed Abstract | Publisher Full Text | Free Full Text\n\nO’Malley C: Seven Ways to a Successful Dipping Career. Wing Beats. 1995; 6(4): 23–24.\n\nRobert V, Le Goff G, Ariey F, et al.: A possible alternative method for collecting mosquito larvae in rice fields. Malar J. 2002; 1: 4. PubMed Abstract | Publisher Full Text | Free Full Text\n\nScott JA, Brogdon WG, Collins FH: Identification of single specimens of the Anopheles gambiae complex by the polymerase chain reaction. Am J Trop Med Hyg. 1993; 49(4): 520–529. PubMed Abstract\n\nTrapido H, Aitken TH: Study of a residual population of Anopheles L. labranchiae Falleroni in the Geremeas Valley, Sardinia. Am J Trop Med Hyg. 1953; 2(4): 658–676. PubMed Abstract\n\nTuno N, Githeko A, Yan G, et al.: Interspecific variation in diving activity among Anopheles gambiae Giles, An. arabiensis Patton, and An. funestus Giles (Diptera: Culicidae) larvae. J Vector Ecol. 2007; 32(1): 112–117. PubMed Abstract | Publisher Full Text\n\nWorkman PD, Walton WE: Larval behavior of four Culex (Diptera: Culicidae) associated with treatment wetlands in the southwestern United States. J Vector Ecol. 2003; 28(2): 213–228. PubMed Abstract"
}
|
[
{
"id": "13506",
"date": "20 May 2016",
"name": "Wolfgang R Mukabana",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe 'method article' by Brisco et al is well written, easy to read/understand and to the point. I have read the article keenly and with deep interest and on this basis declare that I have no reservations whatsoever against this article - its a simple but great piece of work.\nThe Sweep Net Catch (SNC) method for collecting mosquito larvae described is long overdue for inclusion in tool kits for field entomologists.\nThe video showing how larvae were sampled are clear. I note that the SNC method is carried out continuously for 10 minutes and gives it undue advantage over the dip method, which involves sampling with interruptions. However, the authors have discussed this issue adequately and in fact adjusted the length of sampling time for the dip method to legitimatize comparisons.\nTable 1 shows raw data of numbers of mosquito larvae collected by genus and sampling method. I suggest that the data presented be 'digested' a little further to show such important elements like number of sampling trials (N), mean mosquito catches, standard errors etc.\nThe authors conclude that 'Our SNC method is particularly effective in capturing Anopheles mosquito larvae'. This statement is true given the numbers of larvae collected but looking at the video I'm inclined to think that the mosquito breeding sites selected for the studies were not typical habitats for culicine mosquito larvae, thus the use of the word 'particularly' is not due. In fact the authors state in their discussion section that \"However, due to the relatively low numbers of Culex larvae collected throughout our study, we suspect there wasn’t a high enough population density of these larvae at any of our trial sites to accurately determine if either method was more efficient for the collection of Culex larvae.\"",
"responses": []
},
{
"id": "15220",
"date": "26 Jul 2016",
"name": "Norbert Becker",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe study design is appropriate and the article is well written. The use of a sweep net (SN) represents a significant improvement for the surveillance of developmental stages of anophelines. I know by experience how difficult and time consuming it is to assess the abundance of anopheles larvae especially in muddy water with a dipper. The use of a SN will allow a more precise and quick assessment of the larval density e.g. before and after larvicide treatments to calculate the mortality rates or to document the presence of larvae at all.\nI agree with the statements of the authors that the use of a sweep net is more efficient than the dip method when larvae of anophelines have to be counted. I agree also that the data concerning culicine larval counts are not sufficient to draw a conclusion of the efficiency of the SNC for the assessment of culicine larvae. You have also to take into consideration that in some programmes the standardized dip method is used to assess a threshold of larvae (e.g. 10 dips per breeding site) to start the control operation. I confirm that this research work fulfils all prerequisites for indexation and scientific standards.",
"responses": []
}
] | 1
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https://f1000research.com/articles/5-713
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https://f1000research.com/articles/5-711/v1
|
21 Apr 16
|
{
"type": "Review",
"title": "Molecular biology of breast tumors and prognosis",
"authors": [
"Gustavo Baldassarre",
"Barbara Belletti",
"Barbara Belletti"
],
"abstract": "Breast cancer is the most common cancer among women worldwide. Great scientific, economical, and organizational efforts are in place to understand the causes of onset, identify the critical molecular players of progression, and define new lines of intervention providing more benefits and less toxicity. These efforts have certainly not been vain, since overall survival, especially in specific subsets of breast cancer, has greatly improved during the last decades. At present, breast cancer patients’ treatment and care have reached a high standard of quality, and currently one of the most urgent needs resides in the necessity to better distinguish the tumors that need to be more aggressively treated and identify the best therapeutic option tailored to each patient. This objective will be achievable only if the information clarifying the biology of breast cancer can be successfully transferred to the clinic. A common effort by scientists and clinicians toward this integration and toward the use of multidisciplinary approaches will be necessary to reach this important goal.",
"keywords": [
"breast cancer",
"breast cancer treatment and care",
"breast cancer prognosis"
],
"content": "Introduction\n\nBreast cancer (BC) is the most common cancer among women worldwide, accounting for approximately one-quarter of all cancers in females worldwide and 27% of cancers in developed countries with a Western lifestyle, thus representing a real health emergency1. Here, we briefly focus on some specific biological and clinical aspects of BC that are still matter of controversy and in which there is urgent need for competent integration to implement diagnostic and therapeutic options.\n\n\nGene expression profiles define different breast cancer subtypes\n\nLarge-scale gene expression profile (GEP) studies demonstrated that BCs are not a single entity but can be divided into at least four major subtypes: luminal A (LBC-A), luminal B (LBC-B), HER2-positive, and triple negative/basal-like2. This classification has been recently confirmed and integrated with genomic data demonstrating that the diverse subtypes are indeed associated with different recurrent genomic alterations3. LBC in the Western world represents the most common subtype, accounting for more than 60% of all diagnosed BC. In clinical practice, a few characteristics, such as estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 expression, are currently used to distinguish LBC-A (ER+ and/or PR+, HER2-, low Ki67) from LBC-B (ER+ and/or PR+, HER2- or HER2+, high Ki67)4. This classification has therapeutic implications, since based on the relative expression of the above markers, LBC patients will or will not receive hormone-, chemo-, or targeted-therapies4. When compared with LBC-A, LBC-B displays a higher rate of early recurrence and worse prognosis, representing a subgroup for which the choice of the optimal therapy still represents a difficult task for the clinician4. In fact, clear biomarkers to select the most appropriate (hormone- with or without chemo-) therapy in LBC-B still have to be validated and introduced into the clinic4.\n\nThe above-mentioned molecular classification also has prognostic relevance, with triple-negative and HER2+ BC having a more aggressive progression. Moreover, since the same molecular characteristics are already present in the first stages of BC and in in situ lesions, it is expected that early diagnosis could help in the identification (and removal) of potentially malignant tumors that need to be aggressively treated.\n\n\nSignificance of identifying in situ breast cancer and the risk of overtreatment\n\nBased on this idea, several BC screening programs have been introduced worldwide in women aged >50 years. The introduction of screening programs has substantially increased the number of early stage in situ lesions, mainly ductal carcinoma in situ (DCIS). It is debated whether low-grade DCIS would result in an invasive stage5. The general view was that the increase in DCIS diagnoses would result in decreased incidence of invasive BC and, eventually, decreased mortality for BC. However, this has not always been the case, as demonstrated by epidemiological analyses, raising some concern over the possibility of “over-diagnosis” linked to the wide spread of BC screening programs6.\n\nThe importance of early diagnosis in BC was recently addressed by a large observational study estimating the mortality for BC following a diagnosis of DCIS7. This important study, enrolling more than 100,000 women, provided the interesting observation that women diagnosed with DCIS display a BC-related death risk at 20 years comparable to that estimated for the general population and that using aggressive treatments for all DCIS does not reduce the mortality for BC7. Yet a diagnosis of DCIS in black women or in women under the age of 40 and the presence of high risk factors such as HER2 expression are associated with an increased risk of BC-related death7. This clinical evidence reinforces the concept that, even when in situ, different molecular alterations in BC strongly impact on the outcome of the disease and on patients’ survival.\n\n\nBreast cancer: age matters\n\nThis concept introduces the relevance of molecular studies to precisely identify the cancer that needs to be aggressively treated and to discover the most appropriate treatment for each patient. Addressing these two unmet clinical needs is the only way to further improve BC cure while limiting the risk of overtreatment.\n\nThe recent study by Narod and colleagues suggests that the group of BC patients that receives a diagnosis of BC before the age of 40 is the one that more urgently needs to be accurately classified at molecular level7. Young age at diagnosis has emerged as an independent factor associated with higher risk of relapse and death in several large studies on BC8,9. Several factors have been linked to this poor prognosis, including large tumor size at diagnosis, higher tumor grade, mitotic index, lymphovascular invasion, increased expression of HER2, and lower ER and PR expression10. More recently, it has been proposed that for these patients it is also worth testing the presence of mutation in the BC susceptibility genes BRCA1 and BRCA2, independently of their family history11. A general consensus in the scientific community has been reached to define BC in Young Women (BCYW), although fairly rare (~7% of all diagnosed BC), as a distinct entity that merits being studied and treated using specific guidelines and following specific research priorities12.\n\nMore aggressive subtypes are more common in BCYW. In particular, when compared with older patients, BCYW more frequently displays the triple-negative and HER2+ BC subtypes. However, in the Western world, LBC-B still accounts for more than 60% of all BCYW, remaining the most common histotype and displaying a particularly bad prognosis8,9. These observations raised the question of whether BCYW has a unique biology or whether this just represents a surrogate of the higher incidence of aggressive molecular subtypes. But, even after correction for stage and tumor characteristics, young age at diagnosis remains an independent risk factor for relapse and BC-related death13.\n\nUnraveling the biological uniqueness of BCYW is fundamental, as it not only increases our understanding of the disease process but also underlies the decision of whether or not to offer the same therapeutic options reserved to the high-risk older patients or to choose therapeutic approaches based on a specific biology14.\n\nAccumulating evidence suggests that differences in the mammary stroma composition and changes that occur with pregnancy and breastfeeding likely contribute to the different biology of BCYW. Moreover, these tumors are enriched with processes related to immune-related gene signatures and immature mammary cell populations (RANKL, c-kit, BRCA1-mutated phenotype, mammary stem cells, and luminal progenitors)15.\n\nThe comprehensive analysis of BC with respect to age on a large compendium of publicly available gene expression datasets (more than 3500 BCYW)15 has demonstrated that specific pathways are altered in BCYW with respect to older patients. However, the identification of altered signaling pathways is not sufficient to identify the driver alterations responsible for tumor onset and/or progression.\n\nA recent conference centered on the management of BCYW confirmed that, although some progress has been made in the understanding of the clinical and biological behaviors of BC in patients younger than 40, we still need to clarify many aspects to properly treat this particular subgroup of patients16. In particular, there is a consensus on the fact that biology appears to be different in BCYW and that this is particularly true for the endocrine-sensitive tumors. Based on this consideration, it is necessary to study the tumor genetic profile in larger cohorts to further understand if a common and unique pattern of gene expression exists in BCYW. Then, it becomes clear that the study of primary tumors will not be sufficient and that characterizing the recurrent tumors will be mandatory. Finally, it could be of special relevance to understand the interaction of the endocrine and immune systems in these young patients and to cleverly look at response patterns to the current treatments. Only in this way will we have the possibility to improve the treatment, quality of life, and survival of BCYW patients16.\n\n\nIs it the time, in the post-genomic era, to return to functional studies?\n\nIt is now clear that sequencing and gene expression profile studies must be associated with high-throughput functional analyses to precisely identify the genes and/or the pathway each tumor type is addicted to. A recent resource has proposed that it is possible to identify the vulnerability of each type of BC using functional assays, even using a panel of cell lines, if these well recapitulate the original disease17.\n\nWe are convinced, however, that these types of assays should be integrated by the generation of more reliable models of validation. We recently explored this possibility focusing on the onset of local recurrences in BC by setting up a mouse model closely resembling the course of the human pathology18. Our work highlighted that targeting specific signaling pathways at the time of surgery has great potential to prevent the re-appearance of BC in mice18–21. In particular, we observed that the specific inhibition of p70S6K1 had little effect on blocking the growth of established breast tumors but prevented the onset of BC recurrences when therapy was administered with a perisurgical treatment schedule. p70S6K1 activity was necessary for the survival of isolated BC cells residually present in the post-surgery setting, making it an ideal target to improve the efficacy of surgery18,19. Similar results were also shown for the PAR-4 protein using different models of recurrence formation22. In these models, PAR-4 acted as an inhibitor of recurrence formation by inducing multinucleation in oncogene-addicted cells22.\n\nIn accord with the importance of timely delivery of the therapy, it has been recently demonstrated that the application of intraoperative radiotherapy (IORT) in BC patients has different effects if used immediately after tumor removal or as a second procedure after pathological examination23. At the molecular level, this clinical observation could be explained by the recently demonstrated direct effect of IORT in the tumor microenvironment, where it modulates the EGF-EGFR-p70S6K1 signaling axis, via the induction of miR-223 expression in the local peri-tumoral microenvironment21.\n\nIt would be interesting to evaluate whether in high-risk BC patients, such as BCYW, similar mechanisms of cell survival exist and are at least partially responsible for their aggressive phenotype and whether targeting these specific pathways at the right time could significantly impact on the patient’s disease-free and overall survival. To this aim, better models recapitulating the biology of BCYW and more integration between clinicians and preclinical researchers are primarily and urgently needed.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe authors’ work is supported by AIRC (Associazione Italiana Ricerca sul Cancro) IG 15902 (Barbara Belletti) and IG 16865 (Gustavo Baldassarre).\n\n\nAcknowledgements\n\nWe thank all the members of the Breast Unit and of the SCICC lab at CRO and all our external collaborators for their support, dedicated work, and interesting and stimulating discussions.\n\n\nReferences\n\nFerlay J, Shin HR, Bray F, et al.: Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010; 127(12): 2893–917. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nPerou CM, Sørlie T, Eisen MB, et al.: Molecular portraits of human breast tumours. Nature. 2000; 406(6797): 747–52. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCancer Genome Atlas Network: Comprehensive molecular portraits of human breast tumours. Nature. 2012; 490(7418): 61–70. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAdes F, Zardavas D, Bozovic-Spasojevic I, et al.: Luminal B breast cancer: molecular characterization, clinical management, and future perspectives. J Clin Oncol. 2014; 32(25): 2794–803. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nErnster VL, Ballard-Barbash R, Barlow WE, et al.: Detection of ductal carcinoma in situ in women undergoing screening mammography. J Natl Cancer Inst. 2002; 94(20): 1546–54. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBleyer A, Welch HG: Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med. 2012; 367(21): 1998–2005. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNarod SA, Iqbal J, Giannakeas V, et al.: Breast Cancer Mortality After a Diagnosis of Ductal Carcinoma In Situ. JAMA Oncol. 2015; 1(7): 888–96. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nEl Saghir NS, Seoud M, Khalil MK, et al.: Effects of young age at presentation on survival in breast cancer. BMC Cancer. 2006; 6: 194. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCancello G, Maisonneuve P, Mazza M, et al.: Pathological features and survival outcomes of very young patients with early breast cancer: how much is \"very young\"? Breast. 2013; 22(6): 1046–51. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCopson E, Eccles B, Maishman T, et al.: Prospective observational study of breast cancer treatment outcomes for UK women aged 18–40 years at diagnosis: the POSH study. J Natl Cancer Inst. 2013; 105(13): 978–88. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nRosenberg SM, Ruddy KJ, Tamimi RM, et al.: BRCA1 and BRCA2 Mutation Testing in Young Women With Breast Cancer. JAMA Oncol. 2016. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nPartridge AH, Pagani O, Abulkhair O, et al.: First international consensus guidelines for breast cancer in young women (BCY1). Breast. 2014; 23(3): 209–20. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAnders CK, Fan C, Parker JS, et al.: Breast carcinomas arising at a young age: unique biology or a surrogate for aggressive intrinsic subtypes? J Clin Oncol. 2011; 29(1): e18–20. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFredholm H, Eaker S, Frisell J, et al.: Breast cancer in young women: poor survival despite intensive treatment. PLoS One. 2009; 4(11): e7695. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAzim HA Jr, Michiels S, Bedard PL, et al.: Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling. Clin Cancer Res. 2012; 18(5): 1341–51. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBCY 2 - Second Breast Cancer in Young Women Conference 4th–5th November 2014 Dublin, Ireland. Breast Care (Basel). 2015; 10(1): 55–9. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nMarcotte R, Sayad A, Brown KR, et al.: Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance. Cell. 2016; 164(1–2): 293–309. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nSegatto I, Berton S, Sonego M, et al.: Inhibition of breast cancer local relapse by targeting p70S6 kinase activity. J Mol Cell Biol. 2013; 5(6): 428–31. PubMed Abstract | Publisher Full Text\n\nSegatto I, Berton S, Sonego M, et al.: p70S6 kinase mediates breast cancer cell survival in response to surgical wound fluid stimulation. Mol Oncol. 2014; 8(3): 766–80. PubMed Abstract | Publisher Full Text\n\nSegatto I, Berton S, Sonego M, et al.: Surgery-induced wound response promotes stem-like and tumor-initiating features of breast cancer cells, via STAT3 signaling. Oncotarget. 2014; 5(15): 6267–79. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFabris L, Berton S, Citron F, et al.: Radiotherapy-induced miR-223 prevents relapse of breast cancer by targeting the EGF pathway. Oncogene. 2016. PubMed Abstract | Publisher Full Text\n\nAlvarez JV, Pan TC, Ruth J, et al.: Par-4 downregulation promotes breast cancer recurrence by preventing multinucleation following targeted therapy. Cancer Cell. 2013; 24(1): 30–44. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nVaidya JS, Wenz F, Bulsara M, et al.: Risk-adapted targeted intraoperative radiotherapy versus whole-breast radiotherapy for breast cancer: 5-year results for local control and overall survival from the TARGIT-A randomised trial. Lancet. 2014; 383(9917): 603–13. PubMed Abstract | Publisher Full Text | F1000 Recommendation"
}
|
[
{
"id": "13497",
"date": "21 Apr 2016",
"name": "Andrea Morrione",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13498",
"date": "21 Apr 2016",
"name": "Michael Retsky",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13499",
"date": "21 Apr 2016",
"name": "Alfredo Budillon",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-711
|
https://f1000research.com/articles/5-138/v1
|
04 Feb 16
|
{
"type": "Research Note",
"title": "Effect of LXR/RXR agonism on brain and CSF Aβ40 levels in rats",
"authors": [
"Songli Wang",
"Paul Wen",
"Stephen Wood",
"Songli Wang",
"Paul Wen"
],
"abstract": "Alzheimer's disease (AD) is characterized pathologically by the presence of amyloid plaques and neurofibrillary tangles. The amyloid hypothesis contends that the abnormal accumulation of Aβ, the principal component of amyloid plaques, plays an essential role in initiating the disease. Impaired clearance of soluble Aβ from the brain, a process facilitated by apolipoprotein E (APOE), is believed to be a contributing factor in plaque formation. APOE expression is transcriptionally regulated through the action of a family of nuclear receptors including the peroxisome proliferator-activated receptor gamma and liver X receptors (LXRs) in coordination with retinoid X receptors (RXRs). It has been previously reported that various agonists of this receptor family can influence brain Aβ levels in rodents. In this study we investigated the effects of LXR/RXR agonism on brain and cerebrospinal fluid (CSF) levels of Aβ40 in naïve rats. Treatment of rats for 3 days or 7 days with the LXR agonist, TO901317 or the RXR agonist, Bexarotene did not result in significant changes in brain or CSF Aβ40 levels.",
"keywords": [
"Alzheimer’s",
"Apolipoprotein E",
"Aβ",
"liver X receptor",
"retinoid X receptor",
"Bexarotene"
],
"content": "Introduction\n\nAlzheimer’s disease (AD) is a debilitating neurodegenerative disease and the leading cause of dementia in the elderly. It is currently estimated that 5 million people in the US and 30 million worldwide are afflicted with this disease. The pathological hallmarks of AD are the presence of extracellular amyloid plaques and intracellular neurofibrillary tangles in the hippocampus and cortical areas of the brain1. The core constituent of the amyloid plaques is a 4 kDa peptide known as amyloid-β peptide (Aβ). Aggregation of Aβ into soluble, multimeric assemblies and insoluble amyloid fibrils is hypothesized to contribute directly to the pathogenesis of AD; therefore therapeutic strategies aimed at lowering soluble Aβ levels in the brain would be predicted to have a disease-modifying effect2.\n\nThe E4 allele of apolipoprotein E (APOE) is the largest genetic risk factor for sporadic, late-onset AD. The presence of a single copy of E4 increases the risk for Alzheimer’s disease 3-fold and individuals with 2 copies are 15 times more likely to develop AD3. Data showing that APOE4 carriers begin to accumulate amyloid deposits earlier in life relative to non-carriers4 has led to the hypothesis that increased risk associated with an E4 genotype may be the result of the effects of APOE on Aβ production, turnover and/or clearance from the central nervous system (CNS).\n\nThe expression of genes encoding lipid-transport proteins, including APOE is transcriptionally regulated by the ligand-activated nuclear receptors, peroxisome proliferator-activated receptor gamma (PPARγ) and liver X receptors (LXRs) which form obligate heterodimers with retinoid X receptors (RXRs)5. Additionally, activation of these receptors has been shown to affect the activation state of macrophage and microglia6. Based on the processes influenced by this nuclear receptor family it is a reasonable hypothesis that agonism of one or more members of the family could have beneficial effects on Aβ homeostasis in the CNS. In fact, several groups have demonstrated that agonism of the LXR receptor resulted in reduced amyloid plaque burden and/or soluble Aβ levels in amyloid precursor protein (APP) transgenic mouse models7–9. More recently it was reported that a highly selective, blood-brain barrier–permeant, RXR agonist, Bexarotene (Targretin), resulted in enhanced clearance of soluble Aβ in an APP transgenic mouse model in an APOE-dependent manner. In addition, Aβ plaque burden was reduced more than 50% within 72 hours. Further, Bexarotene treatment also resulted in a similar reduction (~25%) in brain interstitial fluid (ISF) levels of Aβ in non-transgenic, C57Bl/6 mice 7–12 hours following a single administration10.\n\nIn the following study, we sought to examine the effects of LXR/RXR agonism on Aβ homeostasis in the CNS of non-transgenic rats using the RXR agonist, Bexarotene and the LXR agonist, TO901317.\n\n\nMaterials and methods\n\nIn vivo pharmacodynamic studies: All procedures were approved by the Amgen Institutional Animal Care and Use Committee. Young male Sprague-Dawley rats (175–200 g) were purchased from Harlan (Indianapolis, IN) and were maintained on a 12h light/dark cycle with unrestricted access to food and water until use. Rats were dosed orally for 3 and 7 consecutive days with AMG8155, a proprietary small molecule BACE1 inhibitor, at 3 mg/kg in 2% HPMC and 1% Tween 80, pH 2, Bexarotene (Alfa Aesar, Ward Hill, MA) at 100 mg/kg in 30% Labrasol, 1% Tween 20, 2% Providone and 0.05% BHA, pH7.0 (Vehicle 3), and TO901317, a LXR agonist (Fisher Scientific, Pittsburgh, PA), at 30 mg/kg in 0.5% NaCl, 2% Tween 80 (Vehicle 4). 4 hours post dose on the last day of study, rats were euthanized with CO2 inhalation for 2 minutes and the cisterna magna was quickly exposed by removing the skin and muscle above it. Cerebrospinal fluid (CSF) was collected with a 30 gauge needle inserted through the dura membrane covering the cisterna magna. CSF samples with visible blood contamination were discarded. Blood was withdrawn by cardiac puncture and plasma was obtained by centrifugation at 15,000 rpm for 10 min at 4°C for drug exposure. Brains were removed and, along with the CSF, immediately frozen on dry ice and stored at -80°C until use. The frozen brains were subsequently homogenized in 10 volumes (w/v) of 0.5% Triton X-100 in TBS with protease inhibitors cocktails. The homogenates were centrifuged at 355,000 rpm for 30 min at 4°C.\n\nQuantification of Aβ40 and APOE in brain and CSF: Samples are analyzed for Aβ levels by immunoassay with a MSD imager. Briefly, 96-well avidin plates (MesoScale Discovery, Inc., Gaithersburg, MD) were coated with biotinylated-anti-Aβ antibody 4G8 (mouse monoclonal, Cat# Sig 39240-1000, Covance Research Products, Princeton, NJ) at 10 μg/ml in PBS. Samples were co-incubated in the plate overnight at 4°C along with a ruthenium-labeled anti-Aβ antibody specific for the C-terminal region of Aβ40 (ConFab40; Amgen, Thousand Oaks, CA). Plates were then washed, 150 μl/well read buffer T (MesoScale Discovery, Inc.) was added, and plates were read immediately on a Sector 6000 imager according to the manufacturer’s recommended protocol (MesoScale Discovery, Inc.). All samples were assayed in triplicate and analyzed by using Prism version 5.04 (GraphPad Software Inc., San Diego, CA). Data was analyzed by one-way analysis of variance and Dunnett’s multiple comparison test.\n\nAPOE levels in brain (50 μg homogenates) and CSF (10 μl) were analyzed by Western blot following PAGE using 4–12% Bis-Tris gels (Invitrogen, Carlsbad, CA). Blots were probed with primary antibodies to APOE (goat polyclonal, EMD Millipore; 1:1000) and the loading control, actin (ThermoFisher Scientific; 1:200) for 60 min at 4°C and then washed with TBST (Tris-buffered saline, 0.1% Tween 20) three times at room temperature, followed by (Goat-anti-mouse) secondary antibody (ThermoFisher Scientific; 1:1000) for 30 min at 4°C. Densitometric analysis of ApoE was performed (exposure time of 4 minutes with a relative intensity of 2.0, Odyssey imaging system, with application software Version 3.0) followed by an unpaired t-test using GraphPad Prism 5.04 software.\n\nMeasurement of Plasma, CSF, and Brain Drug Concentration: Aliquots of plasma (50 μl) were combined with 300 μl of acetonitrile containing 125 μl structurally related internal standard (IS), vortexed, and centrifuged. Supernatant was transferred into a plain polypropylene 96-well plate for sample analysis. Brain tissue samples were homogenized by using a Covaris (Woburn, MA) acoustic homogenizer. Aliquots of 50 μl homogenate were combined with acetonitrile containing a structurally related IS, vortexed, and centrifuged at 1,900 g for 5 minutes. Supernatant was transferred into a 96-well plate for sample analysis. Analytical standards and tissues were measured by liquid chromatography mass spectrometry (Shimadzu Pumps Autosampler Prominence for HPLC and PE Sciex API 4000 for MS, with Analyst 1.6.1 software) using atmospheric-pressure chemical ionization and multiple reaction monitoring in the positive ion mode.\n\n\nResults\n\nOur aim in this study was to investigate the effects of RXR/LXR agonism on Aβ homeostasis in the CNS of non-transgenic rats using the RXR agonist, Bexarotene and the LXR agonist, TO901317. As a positive control, we included a β-secretase inhibitor (AMG8155). Compounds and appropriate vehicle controls were administered to naïve Sprague Dawley rats at doses indicated in Table 1 for either 3 or 7 consecutive days.\n\nTable 1 lists the 3 compounds tested in this study along with the respective doses (mg/kg).\n\nFollowing 3 and 7 days of dosing, animals were evaluated for both compound levels and pharmacodynamic endpoints. APOE levels were quantitated in brain homogenate and CSF by Western blot. Aβ40 levels were quantitated in the same compartments using immunoassay as described in the Materials and methods section. Following 3 and 7 days of dosing, APOE levels were increased in brain and CSF in the TO901317 treated animals compared to vehicle treated animals (Figure 1). Changes in CSF were statistically significant at both 3 (p = 0.0002) and 7 days (p = 0,0007) whereas changes in brain were statistically significant at day 3 (p = 0.030) but did not reach significance at day 7 (p = 0.056). Bexarotene treatment also resulted in a statistically significant increase in CSF APOE levels compared to vehicle treated animals following both 3 (p = 0.019) and 7 days (p = 0.002) of dosing (Figure 2). APOE levels in brain following Bexarotene treatment trended towards an increase however these changes were not statistically significant. Soluble Aβ40 levels were unchanged in brain and CSF following 3-day (Figure 3) and 7-day (Figure 4) treatment with either Bexarotene or TO901317. The positive control BACE inhibitor, AMG8155 effectively reduced Aβ40 levels by 70% and 71% in CSF and by 67% and 69% in brain in the 3-day and 7-day studies respectively (Figure 3 and Figure 4).\n\nAPOE was also increased in brain however the changes only reached statistical significance at day 3. A) Western blot analysis of APOE in brain and CSF. B) Densitometric analysis of the bands was performed as described in the Materials and Methods section; data are presented as the mean plus standard deviation; Vehicle 4 (black bars) and TO901317 (gray bars).\n\nAPOE changes in brain were not statistically significant. A) Western blot analysis of APOE in brain and CSF. B) Densitometric analysis of the bands was performed as described in the Materials and Methods section; data are presented as the mean plus standard deviation; Vehicle 4 (black bars) and Bexarotene (gray bars).\n\nAβ40 levels in (A) CSF and (B) brain were unchanged following 3 days of treatment with Bexarotene (triangles) or TO901317 (diamonds). Positive control BACE inhibitor AMG8155 (squares) reduced Aβ40 levels 70 and 67% in CSF and brain respectively following a single administration.\n\nAβ40 levels in (A) CSF and (B) brain were unchanged following 7 days of treatment with Bexarotene (triangles) or TO901317 (diamonds). Positive control BACE inhibitor AMG8155 (squares) reduced Aβ40 levels 71 and 69% in CSF and brain respectively following a single administration.\n\nDrug levels of Bexarotene and TO901317 were measured in plasma and brain homogenate following 3 and 7 days of dosing (Table 2). Total levels of both compounds achieved single-digit to low double-digit μM levels in brain and showed good uptake in brain relative to plasma in both dosing paradigms.\n\nFollowing 3 and 7 days of dosing, compound levels were measure in brain homogenate and plasma. Total (t) compound concentrations (μM) are reported in each case. The brain to plasma ratio is also shown (far right-hand column).\n\n\nConclusion\n\nIn this study we demonstrate that 3-day or 7-day treatment of naïve rats with the LXR agonist, TO901317 or RXR agonist, Bexarotene treatment resulted in an increase in APOE levels in CSF. No changes were observed in CSF or brain Aβ40 levels with either compound after 3 or 7 days of dosing. We hope that these findings will stimulate further discussion in the Alzheimer’s research community on the impact of LXR/RXR agonism on central Aβ homeostasis.\n\n\nData availability\n\nOpen Science Framework: Dataset: Effect of LXR/RXR agonism on brain and CSF Aβ40 levels in rats, doi: 10.17605/OSF.IO/3NS6411",
"appendix": "Author contributions\n\n\n\nS. Wang: Participated in research design; wrote or contributed to the writing of the manuscript.\n\nP. Wen: Participated in research design; conducted experiments; performed data analysis; wrote or contributed to the writing of the manuscript.\n\nS. Wood: Participated in research design; performed data analysis; wrote or contributed to the writing of the manuscript.\n\n\nCompeting interests\n\n\n\nAll authors are employees and stockholders of Amgen, Inc.\n\n\nGrant information\n\nAll work was funded by Amgen Inc.\n\n\nReferences\n\nCitron M: Alzheimer’s disease: strategies for disease modification. Nat Rev Drug Discov. 2010; 9(5): 387–98. PubMed Abstract | Publisher Full Text\n\nHardy J, Selkoe DJ: The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science. 2002; 297(5580): 353–6. PubMed Abstract | Publisher Full Text\n\nYu JT, Tan L, Hardy J: Apolipoprotein E in Alzheimer’s disease: an update. Annu Rev Neurosci. 2014; 37: 79–100. PubMed Abstract | Publisher Full Text\n\nMorris JC, Roe CM, Xiong C, et al.: APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Ann Neurol. 2010; 67(1): 122–31. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChawla A, Boisvert WA, Lee CH, et al.: A PPAR gamma-LXR-ABCA1 pathway in macrophages is involved in cholesterol efflux and atherogenesis. Mol Cell. 2001; 7(1): 161–71. PubMed Abstract | Publisher Full Text\n\nHong C, Tontonoz P: Coordination of inflammation and metabolism by PPAR and LXR nuclear receptors. Curr Opin Genet Dev. 2008; 18(5): 461–7. PubMed Abstract | Publisher Full Text\n\nJiang Q, Lee CY, Mandrekar S, et al.: ApoE promotes the proteolytic degradation of Abeta. Neuron. 2008; 58(5): 681–93. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKoldamova RP, Lefterov IM, Staufenbiel M, et al.: The liver X receptor ligand T0901317 decreases amyloid beta production in vitro and in a mouse model of Alzheimer’s disease. J Biol Chem. 2005; 280(6): 4079–88. PubMed Abstract | Publisher Full Text\n\nFitz NF, Cronican A, Pham T, et al.: Liver X receptor agonist treatment ameliorates amyloid pathology and memory deficits caused by high-fat diet in APP23 mice. J Neurosci. 2010; 30(20): 6862–72. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCramer PE, Cirrito JR, Wesson DW, et al.: ApoE-directed therapeutics rapidly clear β-amyloid and reverse deficits in AD mouse models. Science. 2012; 335(6075): 1503–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWang S, Wen PH, Wood S: Dataset: Effect of LXR/RXR Agonism on Brain and CSF Aβ40 Levels in Rats. Open Science Framework. 2016. Data Source"
}
|
[
{
"id": "12274",
"date": "29 Feb 2016",
"name": "Sam Gandy",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSome controversy has surrounded the report in Science from Landreth and colleagues showing that bexarotene reduces the brain amyloid plaque burden from APP transgenic mice by 50% or more in a matter of days. Several groups of experts attempted to replicate the dramatic Landreth results but the dramatic results were not replicatable. The current F1000Research paper extends that replication attempt story by treating rats with bexarotene and then measuring APP metabolites and apoE in CSF. In agreement with the \"second wave\" of bexarotene studies, there was no effect of bexarotene on CSF levels of Aβ40 or Aβ42. The one point of agreement of all studies was that bexarotene does indeed modulation CSF levels of apoE. This argues against the development of bexarotene mimetics as Aβ lowering agents for the treatment or prevention of Alzheimer's disease. However, inasmuch as elevating apoE may be beneficial in clinical situations via a non-Aβ-dependent pathway (see http://www.alzforum.org/news/research-news/bexarotene-revisited-improves-mouse-memory-no-effect-plaques), bexarotene does reproducibly modulate CSF levels of apoE. The discovery of the entity of SNAP (for review, see Jack et al., 20161) indicates that about one-third of clinically diagnosed Alzheimer's patients undergo cognitive decline via some as yet unknown non-Aβ-dependent pathway.",
"responses": []
},
{
"id": "12696",
"date": "02 Mar 2016",
"name": "Mary Jo LaDu",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this manuscript, Wang and colleagues report that treatment for 3 and 7 d bexarotene (Bex, an RXR agonist) or T0901317 (TO, an LXR agonist) induce an increase in apoE levels and but have no effect on Aβ40 in the CSF and brain of rats. While the subject matter is timely, the conclusions must be taken with reservations because of three major concerns: Limited readouts and regions analyzed. It has been previously demonstrated that changes in the levels of Aβ40 and apoE in CSF and brain do not always correlate with efficacy in FAD-Tg mice1,2. Furthermore, it has been shown that an increase of apoE levels by Bex can be beneficial or detrimental depending on the isoform of apoE3 or the brain region analyzed3. The exclusion of Aβ42. It has been reported that CSF Aβ42 levels, and not Aβ40, are increased in AD patients compared to controls4. Comparison to previous reports. Suon and colleagues (2010)5 treated rats with LXR agonists TO (at the same dose) or GW3965 and reported an increase in apoE that correlated with an increase in Ab40/42 levels in CSF and a reduction of Aβ40 in brain5. Wang and colleagues should reconcile their results with this work specifically and interpret their work in the context of the filed in general. A minor observation is that in Figure 1A the vehicle is mislabeled as Vehicle 3 (should be Vehicle 4 for TO901317) Within the AD field, there is an ongoing discussion of the effects of Bex on soluble and deposited Aβ levels in the brain and cognition, with contradictory findings. This is likely due to several confounding factors, including: variance within and across models and inconsistencies in the methods used to characterize and quantify the proteins of interest, particularly soluble Aβ. It is imperative to take these parameters into account when considering the efficacy of RXR or LXR agonists for AD therapeutics. As well, a phase I trial of Bex in AD patients recently concluded6. While these results may be of limited significance and were not available for the submission of this manuscript, inclusion of their results in a revision of the Discussion would be helpful.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-138
|
https://f1000research.com/articles/5-705/v1
|
19 Apr 16
|
{
"type": "Review",
"title": "Recent advances in understanding and managing cholestasis",
"authors": [
"Martin Wagner",
"Michael Trauner",
"Martin Wagner"
],
"abstract": "Cholestatic liver diseases are hereditary or acquired disorders with impaired hepatic excretion and enterohepatic circulation of bile acids and other cholephiles. The distinct pathological mechanisms, particularly for the acquired forms of cholestasis, are not fully revealed, but advances in the understanding of the molecular mechanisms and identification of key regulatory mechanisms of the enterohepatic circulation of bile acids have unraveled common and central mechanisms, which can be pharmacologically targeted. This overview focuses on the central roles of farnesoid X receptor, fibroblast growth factor 19, and apical sodium-dependent bile acid transporter for the enterohepatic circulation of bile acids and their potential as new drug targets for the treatment of cholestatic liver disease.",
"keywords": [
"cholestasis",
"liver",
"hepatic",
"bile acid"
],
"content": "Introduction\n\nCholestasis is a hereditary or acquired impairment of bile formation and flow on either a hepatocellular or a cholangiocellular level, resulting in interruption of the enterohepatic circulation of bile acids. Classical hereditary defects comprise mainly mutations of transporter genes involved in hepatocellular bile formation such as ATP8B1, BSEP, and multidrug resistance protein 3 (MDR3) underlying the classical progressive familial intrahepatic cholestasis type I-III, respectively1, and rarely mutations of bile acid synthesis enzymes2 or mutations in the bile acid receptor farnesoid X receptor (FXR)3. In addition, mutations in the Notch signaling pathway frequently cause infant cholestasis in Alagille syndrome1 and mutations/polymorphisms in MDR3, multidrug resistance-associated protein 2 (MRP2), and FXR have been associated with intrahepatic cholestasis of pregnancy or drug-induced liver injury1. Notably, mutations of sodium taurocholate cotransporting polypeptide (NTCP) result in pronounced hypercholanemia without classical clinical features of cholestasis or impaired enterohepatic circulation4. At the cholangiocyte level, hereditary defects of cystic fibrosis transmembrane conductance regulator (CFTR) are the most common genetic contributors to cholestasis1 and polymorphisms in anion exchanger 2 (AE2) have been found as disease modifiers in primary biliary cholangitis (PBC)5. In addition, mutations in tight junction proteins along the canalicular membrane of hepatocytes and cholangiocytes result in hereditary forms of cholestasis6. Acquired forms of cholestasis originate from the hepatocellular level (e.g. estrogen-induced bland cholestasis, sepsis-induced cholestasis, and drug-induced cholestasis) or cholangiocyte or bile duct levels (e.g. PBC, primary sclerosing cholangitis [PSC], secondary sclerosing cholangitis, and intraluminal/extraluminal bile duct obstructions) or represent a mixture of hepatocellular/cholangiocellular origins7. The common hallmark of various forms of cholestasis is impaired proper circulation of bile acids along the enterohepatic circulation resulting in the accumulation of potential toxic bile acids in the systemic circulation and intracellularly. A general goal in treating cholestasis, therefore, is to reduce hepatic and systemic bile acid accumulation and to decrease bile acid pool size (Figure 1).\n\nCholestasis results in the accumulation of bile acids in the enterohepatic bile acid circulation. Novel promising anticholestatic strategies aim to eliminate bile acids and reduce bile acid pool size predominately by either reducing de novo bile acid production or eliminating bile acids by interrupting enterohepatic bile acid circulation. Intrahepatic bile acid levels decrease. Left panel: FGF19 analogues mimic the action of endogenous FGF19, which is synthesized in the terminal ileum. FGF19 robustly represses hepatic de novo bile acid synthesis by blocking the rate-limiting enzyme of bile acid generation, cholesterol 7-alpha hydroxylase (CYP7A1). This reduces bile acid pool size and the amount of bile acids by suppression of the biliary loop of enterohepatic circulation. Middle panel: ASBT inhibitors selectively block bile acid re-uptake in the terminal ileum by blocking the bile acid transporter ASBT. Bile acids spill over into the colon and are lost via feces. This reduces bile acid pool size and the amount of bile acids by initially (1) suppression of the portal loop of enterohepatic circulation. Right panel: FXR agonists are not tissue specific but predominately activate FXR in the ileum and liver. FXR agonists suppress (-) bile acid synthesis via induction of FGF19-mediated CYP7A1 suppression from the ileum and via FXR- short heterodimer partner 1 (SHP)-mediated CYP7A1 repression from the liver. This reduces bile acid pool size. In addition, FXR agonists limit cellular bile acid accumulation by blocking ileal (via ASBT) and hepatic (via sodium taurocholate cotransporting polypeptide [NTCP]) bile acid uptake and by enforcing (+) ileal and hepatic (both via organic solute transporter α/β [OSTα/β]) bile acid export, leading to bile acid spill over into feces and systemic circulation.\n\n\nEnterohepatic circulation of bile acids\n\nBile acids are formed in hepatocytes from hydroxylation of cholesterol by cholesterol 7-alpha hydroxylase (CYP7A1) or alternatively by CYP27A18. The resulting primary bile acid chenodeoxycholic acid (CDCA) can be further hydroxylated to cholic acid (CA) by CYP8B1. Bile acids are exported across the canalicular membrane of hepatocytes into the bile duct lumen via distinct bile acid transporters, of which BSEP (ABCB11) transports the bulk of bile acids, accompanied by MRP2, the latter one transporting conjugated bilirubin and other xenobiotics. In addition, formation of primary bile requires active transport of phospholipids (via MDR3), cholesterol (via ABCG5/8), glutathione (also via MRP2), bicarbonate (via CFTR), and passive dilution by water9,10. Along the bile ducts, bile is further modified by bicarbonate-enriching mechanisms11,12 and further bile acid uptake mechanisms within the liver9,11. In the terminal ileum, bile acids are efficiently shuttled across enterocytes back into the portal circulation by active uptake into enterocytes via apical sodium-dependent bile acid transporter (ASBT) (SLC10A2) and exported via organic solute transporter α/β (OSTα/β) (SLC51)9,10. Only a few bile acids escape this high-capacity re-uptake and conservation mechanism by ASBT and spill over into the colon, where they are secondarily transformed by bacteria into deoxycholic acid (DCA) and lithocholic acid (LCA), taken back up by colonic diffusion, or excreted via the feces9,10. From the portal circulation, bile acids are selectively imported into hepatocytes by an active transporting mechanism, mainly consisting of NTCP (SLC10A1) and to a lesser extent organic anion-transporting polypeptide (OATP1B1). Bile acids that escape the hepatocellular import are spilled over into the systemic circulation and may eventually be eliminated via the kidney and urine9.\n\nBile acid concentrations (and indirectly also composition via different sensitivities of bile acid sensors to various bile acid species) along the enterohepatic circulation are sensed at “checkpoints” in hepatocytes and enterocytes. Depending on the actual bile acid load in the enterohepatic circulation, further bile acids can be produced and more efficiently conserved or production can be repressed and bile acid excretion favored. In cholestasis, when bile acids accumulate, (hepato)cellular export and re-routing bile acids to renal excretion comprises an important adaptive system to reduce further potential toxic bile acid accumulation and cell damage9,13. The alternative export of bile acids is canalized by active bile acid transporter systems such as OSTα/β, MRP3, and MRP4 at basolateral membranes, which transport bile acids out of hepatocytes. In line with enforcing cellular export, import of bile acids into hepatocytes (via NTCP) and enterocytes (via ASBT) is being reduced9,13. Accumulating bile acids in hepatocytes also limit further bile acid production via repressing CYP7A1 at the transcriptional level. However, this very efficient mechanism to reduce bile acid generation in the enterohepatic circulation may be compromised in settings when bile flow is significantly impaired and fewer bile acids are sensed in enterocytes14,15. Fibroblast growth factor 19 (FGF19) is an ileum-specific enteric hormone released in proportion to bile acid concentrations in enterocytes and the most efficient repressor of CYP7A1 and hepatocellular bile acid synthesis14. Bile acids induce FGF19 in the terminal ileum, which is released in the portal circulation and reduces bile acid synthesis in hepatocytes in a negative feedback fashion. In obstructive cholestasis, when bile flow is reduced and fewer bile acids reach the ileum, FGF19 levels decrease and hepatocellular bile acid production is augmented. This results in a paradoxical metabolic situation with further increase of bile acid synthesis despite hepatic accumulation of bile acids.\n\n\nBile acid receptor FXR\n\nThe main sensor of bile acids in the enterohepatic circulation is the bile acid receptor FXR (NR1H4), which is ligand activated in the order of potency by CDCA > DCA > LCA > CA16. FXR is a nuclear hormone receptor and transcription factor that heterodimerizes with the retinoid X receptor α (RXRα, NR2B1) and regulates the expression of genes involved in bile acid metabolism but also genes regulating glucose and lipid metabolism and inflammation17. FXR can either directly induce or reduce gene transcription or indirectly repress genes via the common repressor short heterodimer partner 1 (SHP) (NR0B2), which is a direct positive target of FXR18. FXR is highly expressed along the gastrointestinal system, liver, kidney, and to minor extents the adrenal glands19. Generally, FXR activation reduces intracellular bile acid load in target tissues by repressing bile acid import transporters (i.e. NTCP and ASBT) and inducing bile acid export pumps (i.e. BSEP, MRP2, and OSTα/β) along with suppression of bile acid synthesis (i.e. CYP7A1)10,17. FXR regulates bile acid synthesis from the intestine via induction of FGF19 and in hepatocytes via SHP-induced repression of CYP7A114. For proper CYP7A1 repression by intestinal FGF19, sufficient hepatic SHP expression is required14. In addition, FXR activation favors bile acid detoxification via induction of cytochrome p450 3A4 (CYP3A4), sulfotransferase 2A1 (SULT2A1), and UDP glucuronosyltransferase 2 family, polypeptide B4 (UGT2B4)17 and stimulates biliary phospholipid excretion via MDR3 (ABCB4), thereby also counteracting cholesterol gallstone formation20. Besides its role for bile acid metabolism, FXR activation also shows anti-inflammatory properties by blocking NFκB-mediated inflammatory gene expression and immunomodulatory effects by facilitating homing and function of myeloid-derived suppressor cells, which function as a critical negative feedback loop in immune-mediated liver injury21–23.\n\n\nNew concepts in treating cholestasis\n\nCurrently, the only approved drug for treating chronic cholestatic disorders is the hydrophilic bile acid ursodeoxycholic acid (UDCA)24. UDCA’s anti-cholestatic properties are mainly attributed to its choleretic effects by stimulating hepatocellular secretion of bile acids and organic anions post-translationally and by inducing/stabilizing a bicarbonate-rich protection “umbrella” along the biliary tree12. Anti-apoptotic and anti-inflammatory actions may additionally support UDCA’s beneficial anticholestatic action. Its clinical efficacy is limited because only approximately two-thirds of patients with PBC respond to UDCA therapy25 and in PSC patients UDCA has no effect on transplant-free survival26.\n\nNorUDCA is a side chain shortened UDCA derivative, which induces bicarbonate-rich hypercholeresis as a result of cholehepatic shunting of conjugation-resistant NorUDCA and shows additional anti-inflammatory and anti-fibrotic qualities27–30. In contrast to UDCA, NorUDCA improved sclerosing cholangitis in Mdr2 knockout mice as a model system for PSC while UDCA even aggravates cholestatic liver injury in these animal models28,29,31. Recently, a phase II clinical trial with NorUDCA for PSC has been completed and the full data are eagerly awaited32. Both UDCA and NorUDCA, to a large extent, counteract cholestasis by their choleretic effects targeting impaired bile flow.\n\nWhile UDCA and NorUDCA counteract cholestasis and impaired bile flow by primarily inducing bile-acid independent choleresis and modifying bile acid pool toxicity, another line of currently developed anticholestatic strategies targets enterohepatic circulation to primarily reduce bile acid pools. FXR agonists, FGF19 mimetics, and ASBT inhibitors with clearly defined modes of action are the most promising representatives and are currently being tested in phase II and phase III clinical trials.\n\nFXR agonists. FXR represents the central integrator of bile acid homeostasis and, once activated, results in the reduction of cellular bile acid levels. Although FXR activation by endogenous bile acid accumulation is intended to counteract potential toxic bile acid levels, its endogenous activation in chronic cholestatic liver diseases is apparently too weak for disease self-limitation. Synthetic and semi-synthetic FXR agonists, with higher affinity and potency to activate FXR, have therefore been successfully tested in animal models of cholestasis. In LCA- and ethinyl estradiol-induced cholestatic rats, the semi-synthetic steroidal FXR ligand obeticholic acid (OCA, formerly also referred to as 6-ethylchenodeoxycholic acid [6-ECDCA]), which is currently being tested in several clinical phase II and III studies for PBC and PSC, was able to restore reduced bile flow and improve cholestasis in several preclinical animal models of cholestasis33,34. Interestingly, in a mouse model of cholestasis resembling PSC (i.e. Mdr2 knockout mice), OCA did not show beneficial anticholestatic effects in this model, although ileal FGF15 was induced and hepatic Cyp7a1 repressed. Only the even more potent FXR-activating capacity of the steroidal dual FXR/G-protein-coupled bile acid receptor 1 (TGR5) agonist INT-767 improved cholestasis along with robustly induced bicarbonate-rich choleresis and reduction of biliary bile acid output35. It is likely that species differences and differences in the cholestatic models (i.e. complete absence of biliary phospholipids in the Mdr2 model) may explain these discrepancies. Non-steroidal FXR agonists (i.e. GW4064), which are also being investigated in clinical settings, improved markers of cholestasis as well as reduced hepatic bile acid accumulation in bile duct-ligated and α-naphthyl isothiocyanate-treated rats too36. It is important to note that steroidal FXR agonists (e.g. OCA, CDCA, and INT-767) activate FXR in hepatocytes and enterocytes as well and therefore beneficial effects of FXR agonism may be explained by concerted action of both hepatic and enteric FXR stimulation. Thus, beneficial effects of steroidal FXR agonism likely result from reduction of bile acid pool size along with stimulation of (bile acid-independent) bile flow. Non-steroidal FXR agonists, such as fexaramine, GW4064, PX-102, or various derivatives, are currently being developed and tested by different companies and may have different tissue selectivity and metabolic effects. Interestingly, when FXR was selectively overexpressed in the intestine of various mouse models of intrahepatic and extrahepatic cholestasis (i.e. bile duct ligation, α-naphthyl isothiocyanate treatment, and Mdr2 knockout mice), bile acid pool size was substantially reduced and cholestasis improved in these models37. Similarly, the gut-restricted non-steroidal FXR agonist fexaramine robustly induces intestinal FGF15 without any hepatic FXR agonistic effects and significantly reduces serum bile acid levels, at least in a model of diet-induced obesity38. This suggests that potentially ileal FXR stimulation alone may be sufficient to counteract cholestasis. However, comparable experiments, where only hepatic FXR is activated, have not been performed to further dissect ileal and hepatic requirements of anticholestatic effects. Therefore, from animal experiments, it is not entirely conclusive which FXR, ileal or hepatocyte or both, is required to target and if the effects of FXR activation are more dependent on stimulation/restoration of (bile acid-independent) bile flow or repression of bile acid synthesis and pool size or both.\n\nIn a human clinical phase II trial with PBC patients, OCA treatment showed significant improvement of alkaline phosphatase (AP) as the main readout marker of cholestasis39. Clinically, the major side effect was dose-dependent pruritus, and biochemically an unfavorable trend in the cholesterol profile with decreased high-density lipoprotein (HDL) cholesterol was observed39. The impact of OCA on cholesterol metabolism was even more pronounced in another clinical phase II trial in obese patients with non-alcoholic fatty liver disease (NAFLD) as the disease target, where not only HDL cholesterol decreased but also LDL cholesterol increased40. Generally, the atherogenic lipid profile of OCA is less a concern in PBC patients, while it requires further evaluation in NAFLD patients with increased cardiovascular risk. It is important to note that in the PBC study, participants comprised only patients who did not respond adequately to their standard of care treatment with UDCA and thus were expected to progress with cholestatic liver disease over time. OCA improved laboratory-based clinical scoring parameters in a significant portion of patients to levels associated with normalization of prognosis39. However, in total only 7% of patients completely normalized their AP levels, which might alternatively be explained by direct FXR-induced AP transcription rather than disease-related AP origin40,41. Also, the study’s duration was only 3 months and biopsies for histological correlation were not taken. From a mechanistic point of view, OCA treatment increased FGF19 serum levels and decreased 4-cholesten-3-one (C4) bile acid precursors and endogenous BA plasma levels39, underscoring the ability of FXR agonists to reduce bile acid pool size. Apparently, data on bile flow, choleresis, and bicarbonate-rich flow were not determinable in human clinical trials. The beneficial effects of OCA in PBC patients are confirmed in larger long-term studies over 12 months, including a long-term extension study42,43. Currently, further trials in PBC and PSC are underway to study the long-term effects of OCA and more clearly evaluate OCA’s effects on lipid profiles.\n\nFGF19 mimetics. FGF19 is an endocrine hormone predominantly produced in the ileum, which very efficiently suppresses hepatic bile acid synthesis14. In contrast to rodents, human FGF19 is also expressed in liver tissue and gallbladder epithelium under cholestatic conditions and positively correlates with disease severity44,45. It is assumed that hepatic and biliary FGF19 supports endogenous bile acid suppression in cholestasis via autocrine and paracrine mechanisms45. Part of the beneficial effects of FXR agonists in cholestasis may be attributed to FXR-dependent induction of FGF19, and selective activation of FXR in the intestine even suggests that induction of ileal FGF19 may sufficiently treat cholestasis37. This has led to trials explicitly testing FGF19 in cholestatic models. The potential tumorigenic effects of endogenous FGF19 have been overcome by novel engineered FGF19 mimetics which lack the proliferative potency of their endogenous mother compounds46–48. In bile duct-ligated and α-naphthyl isothiocyanate-treated mouse models of cholestasis, endogenous as well as non-tumorigenic FGF19 mimetics significantly suppress Cyp7a1 and total bile acid pools, resulting in markedly reduced liver injury46. Similar effects were achieved in the Mdr2 knockout mouse model where FGF19 mimetics reversed fully developed liver injury, biliary fibrosis, and even cholecystolithiasis49. In a phase I trial in human volunteers, FGF19 mimetics resulted in a 95% reduction of C4 bile acid precursor levels indicative of robust suppression of endogenous bile acid synthesis without showing apparent side effects46. In a very recent phase II clinical trial in PBC patients unresponsive to UDCA treatment, FGF19 mimetics also robustly decreased C4 and slightly decreased total bile acid levels along with showing a significant reduction of AP levels. Main side effects, which overall were mild, included diarrhea, headache, and nausea50. Besides its effects on bile acid metabolism, FGF19 has major metabolic effects on carbohydrate and lipid metabolism51 and is therefore also regarded as a pharmacological approach to treat the metabolic syndrome and primary bile acid diarrhea52–55.\n\nASBT inhibitors. ASBT maintains the enterohepatic circulation of bile acids by efficiently taking up 95% of bile acids from the intestine and preventing their fecal loss. ASBT knockout mice have a 20- to 30-fold increased fecal bile acid loss, which cannot be compensated by increased bile acid synthesis. These mice, therefore, have robustly reduced bile acid pool sizes by 80% despite significantly repressed FGF19 and increased Cyp7a1 activity56,57. Spillover of bile acids into the colon may cause bile acid-induced diarrhea, an effect which can be utilized in treating constipation but may also have malignant potential for colorectal cancer development58,59. Since ASBT knockout mice exhibit an increased cholesterol turnover, blocking ASBT also has a major impact on lipid metabolism and metabolic disorders57. In the cholestatic Mdr2 knockout mouse model, ASBT inhibitors effectively decrease bile acid pool size, biliary bile acid concentrations, and bile flow, which results in significant improvement of liver injury and biliary fibrosis60,61. In a human phase I trial with healthy volunteers, ASBT inhibitors reduced total serum bile acids by almost 50% along with increased fecal bile acid excretion. FGF19 was decreased and C4 bile acid precursor levels increased but could not compensate for fecal bile acid loss62. Conceptually, comparable effects on bile acid metabolism would be expected by treatment with (unspecific) bile acid sequestrants such as cholestyramine or colesevelam. However, side effects such as bloating, constipation, and sequestering of lipophilic vitamins limit their application63. Interestingly, resin-bound bile acids appear to activate colonic TGR564, while unbound colonic bile acids spilled over by ASBT inhibitors did not induce TGR5 signaling61. Besides direct effects on bile acid metabolism, ASBT-induced spillover of bile acids into the colon may significantly affect the gut microbiome65,66 with potential secondary effects on cholestatic liver disease. These effects would be expected to be less apparent with resin-bound bile acids. Future clinical trials with ASBT inhibitors in patients with cholestasis are currently underway.\n\nWhat else is in the pipeline? Several other molecular targets with more or less well-defined modes of action and anticholestatic properties are currently being investigated. Among the most promising pharmacological options are PPARα ligands, which have shown clinical improvements in PBC patients in small clinical trials and await confirmation in larger multicenter trials24. Mechanistically, PPARα ligands (i.e. fibrates) increase MDR3 expression and insertion into the canalicular membrane of hepatocytes and thereby stimulate biliary phospholipid secretion, rendering bile less aggressive67–69. This bile duct protective effect is further supported by reduction of bile acid synthesis (via CYP7A1 and CYP27A1), induction of bile acid detoxification (via CYP3A4)67, and anti-inflammatory properties70. Also, the glucocorticoid receptor is a putative target in the treatment of cholestasis, since budesonide in combination with UDCA stimulates activity of the Cl-/HCO3- exchanger AE2, thereby promoting bicarbonate-rich choleresis71. Other interesting molecular targets comprise the membrane-located bile acid receptor TGR5, the xenobiotic receptor pregnane X receptor, or the vitamin D receptor. The reader is referred to recent reviews for a detailed overview on these pharmacological anticholestatic drug targets24. Some of the hereditary cholestatic disorders are caused by mutations resulting in mistargeting of misfolded bile acid transporters to their intended subcellular location. Chemical chaperones have been shown to improve targeting of misfolded ATP8B1, MDR3, and BSEP transporters in vitro but also in vivo and may provide a pharmacological treatment option for specific hereditary mutations72–75.\n\n\nSummary and outlook\n\nRecent understandings of the molecular mechanisms of bile formation and the enterohepatic circulation have revealed new molecular targets for treating cholestasis. Conceptually, the most promising drugs either stimulate bile flow as their main principle of action or decrease bile acid pool size. Both strategies decrease cholestatic injury in animal models and also appear to translate their observed effects into human clinical trials. However, from what we have learned from the clinical trials so far, there will still remain a substantial percentage of patients who will not completely respond to novel treatment regimes. From a teleological point of view, it therefore would make sense to combine drugs which are choleretic and target impaired bile flow with drugs that reduce bile acid accumulation and decrease bile acid pool size to maximize overall anticholestatic effects. Perhaps the prototypical compounds are the new FXR ligands, which appear to combine both effects, substantial suppression of bile acid synthesis and increasing bile acid-independent bile flow. Future strategies which combine the effects of the most powerful drugs to induce bicarbonate-rich choleresis, such as NorUDCA, with the most powerful drugs to suppress bile acid pool size, such as FGF19 mimetics or ASBT inhibitors, may therefore have real potential to heal cholestasis. Notably, several of these approaches also have profound anti-inflammatory and immunomodulatory actions, which may be instrumental in treating immune-mediated cholangiopathies. Surgical treatment strategies in severely cholestatic children with hereditary cholestatic defects also suggest that total biliary diversion might be a treatment option to avoid liver transplantation76. However, surgery is complex and post-surgical complications can occur. Notably, some of these pharmacological approaches can be combined. As such, combination of ASBT inhibitors with FGF19 agonists may be a therapeutic way to pharmacologically mimic total biliary diversion and thus provide another rationale to combine new anticholestatic drugs to eventually heal cholestasis.\n\n\nAbbreviations\n\nAE2, anion exchanger 2; AP, alkaline phosphatase; ASBT, apical sodium-dependent bile acid transporter; C4, 4-cholesten-3-one; CA, cholic acid; CDCA, chenodeoxycholic acid; CFTR, cystic fibrosis transmembrane conductance regulator; CYP3A4, cytochrome p450 3A4; CYP7A1, cholesterol 7-alpha hydroxylase; DCA, deoxycholic acid; FGF19, fibroblast growth factor 19; FXR, farnesoid X receptor; LCA, lithocholic acid; MDR3, multidrug resistance protein 3, MRP2-4, multidrug resistance-associated protein 2–4; NAFLD, non-alcoholic fatty liver disease; NTCP, sodium taurocholate cotransporting polypeptide; OCA, obeticholic acid; OSTα/β, organic solute transporter α/β; PBC, primary biliary cholangitis; PSC, primary sclerosing cholangitis; SHP, short heterodimer partner 1; TGR5, G-protein-coupled bile acid receptor 1; UDCA, ursodeoxycholic acid.",
"appendix": "Competing interests\n\n\n\nMichael Trauner has received research support by Albireo, Intercept, and Falk and is listed as co-inventor on a patent on the medical use of NorUDCA. He has received advisory board fees from Abbvie, Albireo, Intercept, Falk, Gilead, MSD, Novartis, and Phenex and lecture fees from Abbvie, BMS, Falk, and Gilead. Martin Wagner has received advisory board fees from Intercept.\n\n\nGrant information\n\nThis work was supported by grants F3008-B19 and F3517-B20 (to Michael Trauner) from the Austrian Science Foundation.\n\n\nReferences\n\nHirschfield GM: Genetic determinants of cholestasis. Clin Liver Dis. 2013; 17(2): 147–59. PubMed Abstract | Publisher Full Text\n\nMonte MJ, Marin JJ, Antelo A, et al.: Bile acids: chemistry, physiology, and pathophysiology. World J Gastroenterol. 2009; 15(7): 804–16. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu Y, Binz J, Numerick MJ, et al.: Hepatoprotection by the farnesoid X receptor agonist GW4064 in rat models of intra- and extrahepatic cholestasis. J Clin Invest. 2003; 112(11): 1678–87. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nModica S, Petruzzelli M, Bellafante E, et al.: Selective activation of nuclear bile acid receptor FXR in the intestine protects mice against cholestasis. Gastroenterology. 2012; 142(2): 355–65.e1–4. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nFang S, Suh JM, Reilly SM, et al.: Intestinal FXR agonism promotes adipose tissue browning and reduces obesity and insulin resistance. Nat Med. 2015; 21(2): 159–65. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHirschfield GM, Mason A, Luketic V, et al.: Efficacy of obeticholic acid in patients with primary biliary cirrhosis and inadequate response to ursodeoxycholic acid. Gastroenterology. 2015; 148(4): 751–61.e8. PubMed Abstract | Publisher Full Text\n\nNeuschwander-Tetri BA, Loomba R, Sanyal AJ, et al.: Farnesoid X nuclear receptor ligand obeticholic acid for non-cirrhotic, non-alcoholic steatohepatitis (FLINT): a multicentre, randomised, placebo-controlled trial. Lancet. 2015; 385(9972): 956–65. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nNeuschwander-Tetri BA: Targeting the FXR nuclear receptor to treat liver disease. Gastroenterology. 2015; 148(4): 704–6. PubMed Abstract | Publisher Full Text\n\nNevens F, Andreone P, Mazzella G, et al.: O168 the first primary biliary cirrhosis (PBC) phase 3 trial in two decades – an international study of the FXR agonist obeticholic acid in PBC patients. J Hepatol. 2014; 60(1): S525–S526. Publisher Full Text\n\nTrauner M, Nevens F, Andreone P, et al.: Sustained improvement in the markers of cholestasis in an open label long term safety extension study of obeticholic acid in primary biliary cirrhosis patients. Hepatology. 2015; 62: 511A (Abstract). Reference Source\n\nWunsch E, Milkiewicz M, Wasik U, et al.: Expression of hepatic Fibroblast Growth Factor 19 is enhanced in Primary Biliary Cirrhosis and correlates with severity of the disease. Sci Rep. 2015; 5: 13462. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nZweers SJ, Booij KA, Komuta M, et al.: The human gallbladder secretes fibroblast growth factor 19 into bile: towards defining the role of fibroblast growth factor 19 in the enterobiliary tract. Hepatology. 2012; 55(2): 575–83. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLuo J, Ko B, Elliott M, et al.: A nontumorigenic variant of FGF19 treats cholestatic liver diseases. Sci Transl Med. 2014; 6(247): 247ra100. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nNicholes K, Guillet S, Tomlinson E, et al.: A mouse model of hepatocellular carcinoma: ectopic expression of fibroblast growth factor 19 in skeletal muscle of transgenic mice. Am J Pathol. 2002; 160(6): 2295–307. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSawey ET, Chanrion M, Cai C, et al.: Identification of a therapeutic strategy targeting amplified FGF19 in liver cancer by Oncogenomic screening. Cancer Cell. 2011; 19(3): 347–58. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhou M, Learned RM, Rossi SJ, et al.: Engineered fibroblast growth factor 19 reduces liver injury and resolves sclerosing cholangitis in Mdr2-deficient mice. Hepatology. 2016; 63(3): 914–29. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMayo MJ, Roberts SK, Arnold H, et al.: NGM282, A Novel Variant of FGF-19, Demonstrates Biologic Activity in Primary Biliary Cirrhosis Patients with an Incomplete Response to Ursodeoxycholic Acid: Results of a Phase 2 Multicenter, Randomized, Double Blinded, Placebo Controlled Trial. Hepatology. 2015; 62(Suppl. 1): 263A (Abstract). Reference Source\n\nKir S, Beddow SA, Samuel VT, et al.: FGF19 as a postprandial, insulin-independent activator of hepatic protein and glycogen synthesis. Science. 2011; 331(6024): 1621–4. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWalters JR, Tasleem AM, Omer OS, et al.: A new mechanism for bile acid diarrhea: defective feedback inhibition of bile acid biosynthesis. Clin Gastroenterol Hepatol. 2009; 7(11): 1189–94. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWalters JR: Bile acid diarrhoea and FGF19: new views on diagnosis, pathogenesis and therapy. Nat Rev Gastroenterol Hepatol. 2014; 11(7): 426–34. PubMed Abstract | Publisher Full Text\n\nOwen BM, Mangelsdorf DJ, Kliewer SA: Tissue-specific actions of the metabolic hormones FGF15/19 and FGF21. Trends Endocrinol Metab. 2015; 26(1): 22–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRysz J, Gluba-Brzózka A, Mikhailidis DP, et al.: Fibroblast growth factor 19-targeted therapies for the treatment of metabolic disease. Expert Opin Investig Drugs. 2015; 24(5): 603–10. PubMed Abstract | Publisher Full Text\n\nDawson PA, Haywood J, Craddock AL, et al.: Targeted deletion of the ileal bile acid transporter eliminates enterohepatic cycling of bile acids in mice. J Biol Chem. 2003; 278(36): 33920–7. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLundåsen T, Andersson EM, Snaith M, et al.: Inhibition of intestinal bile acid transporter Slc10a2 improves triglyceride metabolism and normalizes elevated plasma glucose levels in mice. PLoS One. 2012; 7(5): e37787. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nTrivedi PJ, Ward S: Altered bile acid pool using IBAT inhibitors for constipation: a potentially increased risk of malignancy. Am J Gastroenterol. 2012; 107(1): 140; author reply 140–1. PubMed Abstract | Publisher Full Text\n\nRaufman JP, Dawson PA, Rao A, et al.: Slc10a2-null mice uncover colon cancer-promoting actions of endogenous fecal bile acids. Carcinogenesis. 2015; 36(10): 1193–200. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMiethke AG, Zhang W, Simmons J, et al.: Pharmacological inhibition of apical sodium-dependent bile acid transporter changes bile composition and blocks progression of sclerosing cholangitis in multidrug resistance 2 knockout mice. Hepatology. 2016; 63(2): 512–23. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBaghdasaryan A, Fuchs CD, Österreicher CH, et al.: Inhibition of intestinal bile acid absorption improves cholestatic liver and bile duct injury in a mouse model of sclerosing cholangitis. J Hepatol. 2016; 64(3): 674–81. PubMed Abstract | Publisher Full Text\n\nMarschall HU, Gillberg P, Graffner H, et al.: The ileal bile acid transporter inhibitor A4250 modulates bile acid synthesis and decreases serum bile acids. Hepatology. 2015; 62: 612A (Abstract).\n\nJacobson TA, Armani A, McKenney JM, et al.: Safety considerations with gastrointestinally active lipid-lowering drugs. Am J Cardiol. 2007; 99(6A): 47C–55C. PubMed Abstract | Publisher Full Text\n\nHarach T, Pols TW, Nomura M, et al.: TGR5 potentiates GLP-1 secretion in response to anionic exchange resins. Sci Rep. 2012; 2: 430. PubMed Abstract | Publisher Full Text | Free Full Text\n\nInagaki T, Moschetta A, Lee Y, et al.: Regulation of antibacterial defense in the small intestine by the nuclear bile acid receptor. Proc Natl Acad Sci U S A. 2006; 103(10): 3920–5. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFouts DE, Torralba M, Nelson KE, et al.: Bacterial translocation and changes in the intestinal microbiome in mouse models of liver disease. J Hepatol. 2012; 56(6): 1283–92. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHonda A, Ikegami T, Nakamuta M, et al.: Anticholestatic effects of bezafibrate in patients with primary biliary cirrhosis treated with ursodeoxycholic acid. Hepatology. 2013; 57(5): 1931–41. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKok T, Bloks VW, Wolters H, et al.: Peroxisome proliferator-activated receptor alpha (PPARalpha)-mediated regulation of multidrug resistance 2 (Mdr2) expression and function in mice. Biochem J. 2003; 369(Pt 3): 539–47. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nShoda J, Inada Y, Tsuji A, et al.: Bezafibrate stimulates canalicular localization of NBD-labeled PC in HepG2 cells by PPARalpha-mediated redistribution of ABCB4. J Lipid Res. 2004; 45(10): 1813–25. PubMed Abstract | Publisher Full Text\n\nWagner M, Zollner G, Trauner M: Nuclear receptors in liver disease. Hepatology. 2011; 53(3): 1023–34. PubMed Abstract | Publisher Full Text\n\nArenas F, Hervias I, Uriz M, et al.: Combination of ursodeoxycholic acid and glucocorticoids upregulates the AE2 alternate promoter in human liver cells. J Clin Invest. 2008; 118(2): 695–709. PubMed Abstract | Free Full Text | Faculty Opinions Recommendation\n\nGonzales E, Grosse B, Schuller B, et al.: Targeted pharmacotherapy in progressive familial intrahepatic cholestasis type 2: Evidence for improvement of cholestasis with 4-phenylbutyrate. Hepatology. 2015; 62(2): 558–66. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGonzales E, Grosse B, Cassio D, et al.: Successful mutation-specific chaperone therapy with 4-phenylbutyrate in a child with progressive familial intrahepatic cholestasis type 2. J Hepatol. 2012; 57(3): 695–8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGautherot J, Durand-Schneider A, Delautier D, et al.: Effects of cellular, chemical, and pharmacological chaperones on the rescue of a trafficking-defective mutant of the ATP-binding cassette transporter proteins ABCB1/ABCB4. J Biol Chem. 2012; 287(7): 5070–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nvan der Velden LM, Lieke JM, Stapelbroek JM, et al.: Folding defects in P-type ATP 8B1 associated with hereditary cholestasis are ameliorated by 4-phenylbutyrate. Hepatology. 2010; 51(1): 286–96. PubMed Abstract | Publisher Full Text\n\nvan der Woerd WL, Kokke FT, van der Zee DC, et al.: Total biliary diversion as a treatment option for patients with progressive familial intrahepatic cholestasis and Alagille syndrome. J Pediatr Surg. 2015; 50(11): 1846–9. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13474",
"date": "19 Apr 2016",
"name": "Keith Lindor",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13473",
"date": "19 Apr 2016",
"name": "Saul J. Karpen",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-705
|
https://f1000research.com/articles/5-702/v1
|
19 Apr 16
|
{
"type": "Review",
"title": "Recent advances in psychological therapies for eating disorders",
"authors": [
"Glenn Waller"
],
"abstract": "Recent years have seen substantial consolidation and development of the evidence base for psychological therapies for eating disorders. This review summarises the key changes over that time period. Specific forms of cognitive behavioural therapy and family-based treatment have consolidated and extended their positions as treatments of choice despite the development of novel approaches. However, there is still a significant need for further development and testing to improve recovery rates, particularly in anorexia nervosa.",
"keywords": [
"eating disorders",
"anorexia nervosa",
"anorexia",
"bulimia nervosa",
"bulimia"
],
"content": "Recent advances in psychological therapies for eating disorders\n\nHow far have we progressed in the treatment of eating disorders during the current decade? In a previous review1, it was suggested that developments were necessary. There has been little advance in some areas that were identified as targets for further research, such as treatment matching and the role of pharmaceutical interventions2. However, there have been substantial developments in psychotherapies and their outcomes since 2009. This review will summarise the evidence relating to these advances.\n\nThe psychotherapies considered here are designed to treat the eating disorder in and of themselves. However, there are also symptom-based and adjunctive approaches that are designed to address specific elements of the eating disorder (e.g., cognitive flexibility) without the expectation that they will bring about remission on their own. Recent evidence regarding some of those approaches will be considered separately below.\n\n\nPsychotherapy outcomes: some consolidation, some change\n\nThe setting in which psychological therapies is carried out is an important issue and is at least partly determined by local health practices. For example, in some countries, individuals with bulimia nervosa are routinely treated in a combination of in- and out-patient settings, whereas in others it is very rare for them to be treated as in-patients at all. Thus, findings need to be understood in their context. A particular issue in interpreting treatment outcomes is the need to understand the degree of in-patient work that has been involved in the treatment of patients with anorexia nervosa. In-patient care for anorexia nervosa is not a predictor of better outcomes than treatment in less intensive settings and is substantially more expensive3,4, suggesting that its use should be confined to medical need (e.g., preliminary weight gain, medical stabilisation). Similarly, there is little to suggest that any specific psychotherapy is more effective in an in-patient setting.\n\nAnother issue is whether the delivery modality makes a difference in terms of outcomes. In short, there has been little change here. Different forms of self-help and group treatments are less effective than face-to-face individual therapy, as has been the case since the different modalities were developed. More recent work has examined the potential of electronic media (e.g., smartphone apps) for delivering therapy. However, to date, there is little robust evidence that this is an effective approach5,6. Therefore, unless otherwise specified, it should be noted that the following conclusions usually are developed from, and are more applicable to, out-patient treatment settings.\n\nAmong children and adolescents who have had anorexia nervosa for a relatively short period of time, specific types of family-based treatment (FBT) have a good recovery rate, particularly by the time of follow-up7. However, among younger anorexia nervosa cases, there is some evidence that this superiority over individual therapy is not maintained by the time of follow-up8. Regardless, it remains possible to conclude that FBT is superior to individual approaches in terms of either speed or level of recovery. There are suggestions that this approach can be delivered in fairly diverse ways (e.g., fewer sessions, in multi-family settings) as long as the core therapeutic elements remain in place (e.g., the family taking charge of the patient’s eating).\n\nOther individual-based approaches have been tested with this age group in recent years—particularly, cognitive-behavioural therapy (CBT). There is now evidence that CBT can be a useful approach for adolescents with either underweight or non-underweight eating disorders9–11. However, it should be noted that FBT has the more immediate benefit when compared directly with CBT for adolescents with bulimia nervosa, although it was not statistically superior to CBT at follow-up12. Therefore, in this age group, CBT should be considered as an alternative that can be used only where FBT is not possible or indicated or where FBT has failed to be effective. There is also a need for further exploration of methods suited to childhood cases.\n\nThe role of cognitive-behavioural therapy. The most powerful additional evidence that has emerged in the past five years is a series of articles that reinforce and extend the place of CBT as the leading approach in the treatment of eating disorders in adults. CBT in different forms was already established as the front-line treatment for bulimia nervosa and binge eating disorder13. Since then, a series of studies14–19 using Fairburn’s enhanced form of CBT (CBT-E) have demonstrated the following:\n\nCBT-E is effective for normal-weight bulimia nervosa and atypical eating disorders; approximately half of patients remit and remain well.\n\nPatients with anorexia do moderately well with CBT-E (approximately 30% entering treatment recover by the end of out-patient therapy, and a somewhat higher rate by the end of in-patient treatment).\n\nCBT-E is more effective than interpersonal psychotherapy (IPT) and psychodynamic therapy for normal-weight cases. One study20 has suggested that a focal psychodynamic therapy for anorexia nervosa is as effective as CBT-E by the point of follow-up, but so was the “treatment-as-usual” condition, perhaps because the effects of all the therapies were obscured by a relatively high level of in-patient treatment.\n\nCaveats. These conclusions about CBT need to be considered in the light of certain caveats. First, there is no direct comparison of CBT-E with existing versions of CBT, so it is not clear that CBT-E represents an improvement over existing CBT approaches or simply a wider application of core CBT methods across eating disorders.\n\nSecond, CBT-E has changed over time; in its early incarnation, it had two forms (“broad” and “focused”). However, the lack of difference in outcomes across these forms was followed by the more recent adoption of a hybrid version, based on the original ‘focused’ form but incorporating the “mood intolerance” module from the “broad” version21. Therefore, understanding the impact of CBT-E requires clarity about which form is under consideration.\n\nThird, other structured therapies that are based on a cognitive model but include other elements (e.g., affective) can be as effective as CBT-E in non-underweight patients22. There remains the possibility that the level of structure in a therapy is key to good outcomes, perhaps as much as the content.\n\nFinally, the nature of the CBT that is being delivered needs to be considered. For example, one study23 concluded that out-patient CBT was not effective for delivering remission in long-standing anorexia nervosa cases (although the chronicity of the individuals’ disorders was not greater than that of some patients in other studies). However, although the chronicity of eating disorders is related to the likelihood of spontaneous recovery24,25, the impact of chronicity on treatment outcome has not yet been proven26. Possibly more importantly, the comparability of this variant of CBT with others is limited by the fact that the researchers de-emphasised weight gain as a target of treatment, making it secondary and dependent on the patient’s enthusiasm to engage in it. Thus, the conclusion that CBT is not effective in longer-standing cases is not yet proven, as the key outcome variable of weight gain27 was replaced with a primary outcome of improved quality of life.\n\nOther therapy developments for adults with anorexia nervosa. Though better than they were five years ago, CBT’s outcomes for anorexia nervosa remain disappointing. However, that disappointment needs to be understood in the context of the even poorer outcomes of other therapies for anorexia nervosa that have been reported in recent years. These include the following:\n\nSpecialist supportive clinical management (SSCM). Early SSCM findings were promising, suggesting better outcomes than CBT or IPT for anorexia nervosa28. However, those differences disappeared or reversed at long-term follow-up29, suggesting that SSCM might be a therapy that needs to be delivered long-term to maintain its effects. Subsequent studies have suggested a lower recovery rate than for CBT-E17; the out-patient recovery rate was about 15%30.\n\nThe Maudsley model of anorexia nervosa treatment for adults (MANTRA). MANTRA is based on a relatively elaborate theory compared with CBT, on the assumption that CBT is too simplistic to deal with the multiplicity of different pathological factors in anorexia nervosa cases. However, initial findings suggest that it is notably less effective than CBT-E; the recovery rate is similar to that of SSCM30.\n\nDialectical behaviour therapy (DBT). A version of this therapy (termed radically open-DBT) has been developed for anorexia nervosa, focusing on the compulsive pathology of such cases. To date, it has been tested only in a clinical case series of in-patients, with a large number of missing data31. According to the method of selecting patients for the final analysis, approximately 15-20% of those entering treatment remitted by the end.\n\nThus, although the 30% recovery rate for anorexia nervosa when using CBT-E is undoubtedly weaker than for non-underweight cases, it is noticeably stronger than the recovery rates for other therapies, even where pre-treatment characteristics such as age, duration of disorder, and body mass index are comparable. However, most of the therapies outlined above have a reasonable “partial recovery/improvement” rate for anorexia nervosa17,29–31, suggesting that each has potential to be developed to be more powerful. Efforts to improve all psychological therapies for anorexia nervosa are as important now as they were a decade ago.\n\n\nAdjunctive and symptom-based therapies\n\nIt is important to note that there are treatments that are effective at addressing elements of eating pathology, even though they are not expected to produce remission or recovery. Recent key developments in this domain are considered briefly here.\n\nObviously, re-nourishment is not a psychological therapy in itself but is a treatment element that appears to be crucial in facilitating the impact of psychotherapies. Starvation/semi-starvation is a powerful maintaining factor in the eating disorders; it has an impact on biology, cognitions, emotions and social function. Those effects can be seen among normal-weight patients as well as those who are underweight. There is little doubt that restoring nutritional balance is important for recovery, but it has recently been shown that nutritional improvements are important in terms of both positive changes in core cognitions32 and psychosocial functioning, such as quality of life33. Therefore, nutritional changes appear to be necessary for psychotherapies to be effective for eating disorders.\n\nCognitive remediation therapy (CRT) is increasingly used to address the cognitive inflexibility that is associated with eating disorders, particularly anorexia nervosa. The evidence to date34 suggests that CRT is associated with greater cognitive flexibility in case series. There is also some evidence from randomised controlled trials that CRT is effective in relieving some aspects of eating pathology and in enhancing retention in other therapies35–37, although the benefits do not always appear to operate via the expected route of enhanced cognitive flexibility34. The evidence to date is promising, but conclusions will need to await further studies. Two key questions remain to be addressed. First, are the effects of adjunctive CRT associated with positive outcomes from other therapies? Second, is CRT valuable over and above the impact of re-nourishment of the starved patient?\n\nIt is important to remember that those with the eating disorder are not the only people to suffer from its effects. Carers for such patients also experience high levels of stress and distress. Acknowledging carers’ needs has resulted in a range of individual and group support programmes, intended to relieve those experiences. Those interventions are well received38 and are effective in reducing carers’ distress39, although it remains to be determined whether they have any clear benefit in terms of patients’ symptoms.\n\n\nConclusions\n\nThere have been substantial developments in the field of psychological therapies for eating disorders since this decade began. To summarise, there has been:\n\nconsolidation of the position of CBT for bulimia nervosa and binge eating disorder16,18,19,\n\nsome evidence that other therapies for normal-weight cases can be as effective as CBT22,\n\nenhanced evidence that FBT is the treatment of choice for younger cases7,8,12,\n\nimprovement of the reach of CBT to other eating disorders, including among adolescents11,14–18,\n\nclearer evidence for some adjunctive approaches, even if their target is not recovery32–39, and\n\ndisappointment that treatment outcomes for adults with anorexia nervosa are still weaker than for non-underweight cases, even though there are differential effects for different therapies17,23,29–31.\n\nBetween them, these developments offer both possibilities and challenges. Clinicians have clearer guidance as to what is likely to be effective for their patients, and should be encouraged to work with that information (in the absence of any clear heuristics for treatment matching, apart from age). There remain substantial deficits in our treatment of eating disorders, particularly for cases of anorexia nervosa. Although the development of therapies such as MANTRA and radically open-DBT has been important, at present their benefits are not yet comparable to those of FBT and CBT. CBT and FBT themselves will need further development (e.g., recent evidence that a planful response to a lack of early change is beneficial in FBT for adolescents with anorexia nervosa40). Additionally, other therapies will need to be developed and tested further over the next decade, particularly where they show some promise already in terms of symptom reduction and partial or complete recovery22,28,30,31,34.",
"appendix": "Competing interests\n\n\n\nThe author declares that he has no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nWaller G: Recent advances in therapies for the eating disorders. F1000 Med Rep. 2009; 1: pii: 38. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCrow SJ, Mitchell JE, Roerig JD, et al.: What potential role is there for medication treatment in anorexia nervosa? Int J Eat Disord. 2009; 42(1): 1–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nGowers SG, Clark A, Roberts C, et al.: Clinical effectiveness of treatments for anorexia nervosa in adolescents: randomised controlled trial. Br J Psychiatry. 2007; 191(5): 427–435. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMadden S, Hay P, Touyz S: Systematic review of evidence for different treatment settings in anorexia nervosa. World J Psychiatry. 2015; 5(1): 147–153. 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J Am Acad Child Adolesc Psychiatry. 2014; 53(11): 1162–1167. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCalugi S, Dalle Grave R, Sartirana M, et al.: Time to restore body weight in adults and adolescents receiving cognitive behaviour therapy for anorexia nervosa. J Eat Disord. 2015; 3: 21. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nDalle Grave R, Calugi S, Sartirana M, et al.: Transdiagnostic cognitive behaviour therapy for adolescents with an eating disorder who are not underweight. Behav Res Ther. 2015; 73: 79–82. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nPretorius N, Arcelus J, Beecham J, et al.: Cognitive-behavioural therapy for adolescents with bulimic symptomatology: the acceptability and effectiveness of internet-based delivery. Behav Res Ther. 2009; 47(9): 729–736. PubMed Abstract | Publisher Full Text\n\nLe Grange D, Lock J, Agras WS, et al.: Randomized Clinical Trial of Family-Based Treatment and Cognitive-Behavioral Therapy for Adolescent Bulimia Nervosa. J Am Acad Child Adolesc Psychiatry. 2015; 54(11): 886–94.e2. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nNational Collaborating Centre for Mental Health National Institute for Clinical Excellence: Eating Disorders: Core Interventions in the Treatment and Management of Anorexia Nervosa, Bulimia Nervosa and Related Eating Disorders. (Clinical Guideline 9). London, UK: 2004. PubMed Abstract\n\nByrne S: Principal outcomes of the Strong Without Anorexia Nervosa (SWAN) study: A multicentre randomised controlled trial of three psychological treatments for anorexia nervosa. Paper presented at the Eating Disorders Research Society Meeting, Taormina. 2015.\n\nDalle Grave R, Calugi S, Conti M, et al.: Inpatient cognitive behaviour therapy for anorexia nervosa: a randomized controlled trial. Psychother Psychosom. 2013; 82(6): 390–398. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFairburn CG, Cooper Z, Doll HA, et al.: Transdiagnostic cognitive-behavioral therapy for patients with eating disorders: a two-site trial with 60-week follow-up. Am J Psychiatry. 2009; 166(3): 311–319. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFairburn CG, Cooper Z, Doll HA, et al.: Enhanced cognitive behaviour therapy for adults with anorexia nervosa: a UK-Italy study. Behav Res Ther. 2013; 51(1): R2–8. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFairburn CG, Bailey-Straebler S, Basden S, et al.: A transdiagnostic comparison of enhanced cognitive behaviour therapy (CBT-E) and interpersonal psychotherapy in the treatment of eating disorders. Behav Res Ther. 2015; 70: 64–71. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nPoulsen S, Lunn S, Daniel SI, et al.: A randomized controlled trial of psychoanalytic psychotherapy or cognitive-behavioral therapy for bulimia nervosa. Am J Psychiatry. 2014; 171(1): 109–116. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZipfel S, Wild B, Groß G, et al.: Focal psychodynamic therapy, cognitive behaviour therapy, and optimised treatment as usual in outpatients with anorexia nervosa (ANTOP study): randomised controlled trial. Lancet. 2014; 383(9912): 127–137. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMurphy R, Straebler S, Cooper Z, et al.: Cognitive behavioral therapy for eating disorders. Psychiatr Clin North Am. 2010; 33(3): 611–627. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWonderlich SA, Peterson CB, Crosby RD, et al.: A randomized controlled comparison of integrative cognitive-affective therapy (ICAT) and enhanced cognitive-behavioral therapy (CBT-E) for bulimia nervosa. Psychol Med. 2014; 44(3): 543–553. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTouyz S, Le Grange D, Lacey H, et al.: Treating severe and enduring anorexia nervosa: a randomized controlled trial. Psychol Med. 2013; 43(12): 2501–2511. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTreasure J, Russell G: The case for early intervention in anorexia nervosa: theoretical exploration of maintaining factors. Br J Psychiatry. 2011; 199(1): 5–7. PubMed Abstract | Publisher Full Text\n\nVon Holle A, Pinheiro AP, Thornton LM, et al.: Temporal patterns of recovery across eating disorder subtypes. Aust N Z J Psychiatry. 2008; 42(2): 108–117. PubMed Abstract | Publisher Full Text\n\nWonderlich S, Mitchell JE, Crosby RD, et al.: Minimizing and treating chronicity in the eating disorders: a clinical overview. Int J Eat Disord. 2012; 45(4): 467–475. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBulik CM, Berkman ND, Brownley KA, et al.: Anorexia nervosa treatment: a systematic review of randomized controlled trials. Int J Eat Disord. 2007; 40(4): 310–320. PubMed Abstract | Publisher Full Text\n\nMcIntosh VV, Jordan J, Carter FA, et al.: Three psychotherapies for anorexia nervosa: a randomized, controlled trial. Am J Psychiatry. 2005; 162(4): 741–747. PubMed Abstract | Publisher Full Text\n\nMcIntosh VV, Carter FA, Bulik CM, et al.: Five-year outcome of cognitive behavioral therapy and exposure with response prevention for bulimia nervosa. Psychol Med. 2011; 41(5): 1061–1071. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSchmidt U, Magill N, Renwick B, et al.: The Maudsley Outpatient Study of Treatments for Anorexia Nervosa and Related Conditions (MOSAIC): Comparison of the Maudsley Model of Anorexia Nervosa Treatment for Adults (MANTRA) with specialist supportive clinical management (SSCM) in outpatients with broadly defined anorexia nervosa: A randomized controlled trial. J Consult Clin Psychol. 2015; 83(4): 796–807. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLynch TR, Gray KL, Hempel RJ, et al.: Radically open-dialectical behavior therapy for adult anorexia nervosa: feasibility and outcomes from an inpatient program. BMC Psychiatry. 2013; 13: 293. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nAccurso EC, Ciao AC, Fitzsimmons-Craft EE, et al.: Is weight gain really a catalyst for broader recovery?: The impact of weight gain on psychological symptoms in the treatment of adolescent anorexia nervosa. Behav Res Ther. 2014; 56: 1–6. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nBamford B, Barras C, Sly R, et al.: Eating disorder symptoms and quality of life: where should clinicians place their focus in severe and enduring anorexia nervosa? Int J Eat Disord. 2015; 48(1): 133–138. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTchanturia K, Lounes N, Holttum S: Cognitive remediation in anorexia nervosa and related conditions: a systematic review. Eur Eat Disord Rev. 2014; 22(6): 454–462. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBrockmeyer T, Ingenerf K, Walther S, et al.: Training cognitive flexibility in patients with anorexia nervosa: a pilot randomized controlled trial of cognitive remediation therapy. Int J Eat Disord. 2014; 47(1): 24–31. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nDingemans AE, Danner UN, Donker JM, et al.: The effectiveness of cognitive remediation therapy in patients with a severe or enduring eating disorder: a randomized controlled trial. Psychother Psychosom. 2014; 83(1): 29–36. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLock J, Agras WS, Fitzpatrick KK, et al.: Is outpatient cognitive remediation therapy feasible to use in randomized clinical trials for anorexia nervosa? Int J Eat Disord. 2013; 46(6): 567–575. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nGoddard E, Raenker S, Macdonald P, et al.: Carers' assessment, skills and information sharing: theoretical framework and trial protocol for a randomised controlled trial evaluating the efficacy of a complex intervention for carers of inpatients with anorexia nervosa. Eur Eat Disord Rev. 2013; 21(1): 60–71. PubMed Abstract | Publisher Full Text\n\nHibbs R, Rhind C, Leppanen J, et al.: Interventions for caregivers of someone with an eating disorder: a meta-analysis. Int J Eat Disord. 2015; 48(4): 349–361. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLock J, Le Grange D, Agras WS, et al.: Can adaptive treatment improve outcomes in family-based therapy for adolescents with anorexia nervosa? Feasibility and treatment effects of a multi-site treatment study. Behav Res Ther. 2015; 73: 90–95. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation"
}
|
[
{
"id": "13462",
"date": "19 Apr 2016",
"name": "James Lock",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13463",
"date": "19 Apr 2016",
"name": "Howard Steiger",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-702
|
https://f1000research.com/articles/5-700/v1
|
19 Apr 16
|
{
"type": "Review",
"title": "Recent advances in understanding myelofibrosis and essential thrombocythemia",
"authors": [
"William Vainchenker",
"Stefan N. Constantinescu",
"Isabelle Plo",
"Stefan N. Constantinescu",
"Isabelle Plo"
],
"abstract": "The classic BCR-ABL-negative myeloproliferative neoplasms (MPNs), a form of chronic malignant hemopathies, have been classified into polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). ET and PMF are two similar disorders in their pathogenesis, which is marked by a key role of the megakaryocyte (MK) lineage. Whereas ET is characterized by MK proliferation, PMF is also associated with aberrant MK differentiation (myelodysplasia), leading to the release of cytokines in the marrow environment, which causes the development of myelofibrosis. Thus, PMF is associated with both myeloproliferation and different levels of myelodysplastic features. MPNs are mostly driven by mutated genes called MPN drivers, which abnormally activate the cytokine receptor/JAK2 pathway and their downstream effectors. The recent discovery of CALR mutations has closed a gap in our knowledge and has shown that this mutated endoplasmic reticulum chaperone activates the thrombopoietin receptor MPL and JAK2. These genetic studies have shown that there are two main types of MPNs: JAK2V617F-MPNs, including ET, PV, and PMF, and the MPL-/CALR-MPNs, which include only ET and PMF. These MPN driver mutations are associated with additional mutations in genes involved in epigenetics, splicing, and signaling, which can precede or follow the acquisition of MPN driver mutations. They are involved in clonal expansion or phenotypic changes or both, leading to myelofibrosis or leukemic transformation or both. Only a few patients with ET exhibit mutations in non-MPN drivers, whereas the great majority of patients with PMF harbor one or several mutations in these genes. However, the entire pathogenesis of ET and PMF may also depend on other factors, such as the patient’s constitutional genetics, the bone marrow microenvironment, the inflammatory response, and age. Recent advances allowed a better stratification of these diseases and new therapeutic approaches with the development of JAK2 inhibitors.",
"keywords": [
"myelofibrosis",
"thrombocythemia",
"Myeloprolifarative neoplasms"
],
"content": "Introduction\n\nMyeloproliferative disorders are characterized by excess proliferation of progenitors belonging to the myeloid lineages (myeloproliferation), leading to an excess of mature functional blood cells1. They are all clonal disorders of the hematopoietic system deriving from the transformation of a hematopoietic stem cell (HSC). Among the spectrum of myeloid malignancies they lie at one extreme, characterized only in principle by myeloproliferation (without differentiation defects), in contrast to myelodysplastic syndrome (MDS) (predominant differentiation defects) and acute myeloid leukemia (AML) (blockage in differentiation). The classic BCR-ABL-negative myeloproliferative neoplasms (MPNs) have been classified into three entities: polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). These diseases have common complications: thrombosis or, more rarely, hemorrhages and leukemic transformation. ET is essentially a disorder of the megakaryocyte (MK) lineage with an excess platelet production2. PMF is defined by the presence of bone marrow fibrosis (excess of collagen fibers)3. This is also mainly a disorder of the MK/platelet lineage but is also associated with granulocytic proliferation. The typical forms of PV, ET, and PMF are quite different clinically and have different prognosis. ET and PV can progress to secondary myelofibrosis. Certain ET cases are associated with an erythroid hyperplasia and can progress to a true PV or may remain a form “fruste” of PV. Furthermore, boundaries between ET and PMF are not well standardized. A fourth entity has been described, pre-PMF (or early PMF or prefibrotic myelofibrosis), which corresponds to an ET with a high probability of progression to myelofibrosis and a worse prognosis than classic ET4.\n\nThe molecular pathogenesis of BCR-ABL-negative MPNs is now in large part understood because of recent advances in sequencing techniques, particularly with results derived from next-generation sequencing (NGS) techniques. Recently, the discovery of mutations in the calreticulin (CALR) genes has closed a gap in the knowledge of the physiopathogenesis of these disorders, particularly for ET and myelofibrosis.\n\nIn this review, we will focus on the molecular pathogenesis of MPNs, particularly of ET and PMF. However, somatic acquired mutations cannot summarize the entire pathogenesis of these disorders and other factors such as the constitutional genetics, the bone marrow niche environment, the cytokine release, and the inflammatory response, as well as aging, play important roles in the heterogeneity of these disorders.\n\n\nDiscovery of the mutations in exon 9 of the CALR gene in ET and PMF reinforces the hypothesis that BCR-ABL-negative MPNs are driven by an abnormal activation of JAK2\n\nIn 2005, a major advance in the understanding of the pathogenesis was the discovery of the somatic acquired recurrent mutation JAK2V617F, which is associated with more than 70% of MPNs; namely 95% of PV, 50% of ET, and 60% of PMF5–8. The V617F mutation is located in the pseudokinase domain of JAK2. The V617F mutation appears to prevent the physiologic inhibition and also to directly activate the kinase domain of JAK29. JAK2V617F gain-of-function and the constitutive signaling at sufficient expression levels require cytokine receptors, particularly homodimeric type I receptors. The identification of the JAK2V617F mutation has been a cutting-edge discovery in the pathogenesis of MPNs. This has led to the implication of the cytokine receptor/JAK2/STAT5 signaling pathway in their pathologies and the subsequent discovery of other recurrent mutations in this pathway, such as JAK2 exon 12 in 2% of PV10, and activating mutations in the thrombopoietin receptor MPL. These mutations located in exon 10 of MPL target the W515 residue, which plays a central role in preventing spontaneous activation of the receptor11. When W515 is substituted by 17 other amino acids—most frequently, Leu and Lys—TpoR/MPL becomes constitutively active and oncogenic12. These mutations are found only in ET and PMF, with frequencies of approximately 3% and 5–8% in ET and PMF, respectively13. The somatic MPLS505N is a rare recurrent sporadic mutation in ET and PMF that in certain familial thrombocytosis cases is found in the germline14. Finally, very rare somatic mutations in LNK, a negative regulator of JAK2 kinase activity, have been described in ET and PMF15. JAK2V617F and MPL mutations are only very rarely found in the same patient sample and when both are present they are most of the time in different cells, suggesting that they belong to different clones or subclones.\n\nIn 2013, it was evident that 55% of ET and 65–70% of PMF cases were linked to JAK2V617F and MPL exon 10 mutations. Activation of the cytokine receptor/JAK2 pathway was a common feature. In approximately 40% of ET and PMF, there were no recurrent mutations in genes involved in signaling. At the end of 2013, the teams of Kralovics16 and Green17 discovered mutations (indel) in the CALR gene in 25–30% of ET and PMF that were negative for JAK2 and MPL mutations. More than 50 mutations have been described, but all are in exon 9 and induce a +1 (−1+2) frameshift, leading to a new C-terminal peptide and the absence of the KDEL sequence, a retention sequence for the endoplasmic reticulum (ER) (Figure 1). The C-terminus is almost identical among mutations with about 30 common amino acids. These new sequences completely change the charge of the molecule. The most frequent mutation, del52 (55% of the mutations), also called type 1, eliminates almost all the negative charges, whereas the ins5 (30%)—also called type 2—eliminates about half of these charges. According to these changes, the other mutations have been classified as type 1- or type 2-like. Physiologically, CALR is not a signaling molecule but an ER chaperone involved in the quality control of N-glycosylated protein and in calcium storage in the ER18. However, the fact that the CALR mutations were also mutually exclusive with JAK2V617F and MPL mutations in ET and PMF, together with preliminary results showing that del52 mutations could activate STAT5, suggested that the CALR mutants were involved in signaling16. Recent studies have largely reinforced this hypothesis by showing that CALR mutants activate the MPL receptor after binding to its N-glycosylated residues in the ER19,20. This activation required the positive charge of the C-terminus peptide, the lectin binding domain, and the extracellular N-linked sugars of MPL. There is evidence that the CALR mutant associated with MPL traffics to the cell surface in an immature N-glycosylated form19. In this case, MPL activation can occur anywhere from the ER to the cell surface. Moreover, CALR mutants are secreted proteins, which may be able to activate other cells, especially monocytes, to secrete inflammatory cytokines21. CALR mutants are not able to activate other cytokine receptors different from MPL—except granulocyte colony-stimulating factor receptor (G-CSF-R). However, this activation is weak and does not allow the autonomous growth of factor-dependent cell lines.\n\n(a) CALR protein structure. CALR includes different domains responsible for the two major activities (chaperone and calcium buffering). The mutations lead to altered C-terminal part with loss of KDEL (retrieval and retention domain in endoplasmic reticulum) and generation of a new tail with low calcium-buffering activity. (b) Progression from ET to MF with CALR mutants. CALRdel52 induces ET always progressing to MF in mice in contrast to CALRins5. Thus, in vivo modeling of CALRdel52-induced pathologic effects induces a disorder characterized by a continuum between ET and MF. (c) Pie chart of the different CALR mutations in patients with ET and MF.\n\nThus, it appears that there are two main types of BCR-ABL-negative MPNs. The first one is the JAK2V617F MPNs (∼70% of MPNs), which includes three disorders: ET, PV, and PMF; the second one consists of the CALR and MPL mutated MPNs (20% of MPNs), which usually includes only ET and PMF although CALR mutations have been described in very rare cases of PV associated with a thrombocytosis. The remaining MPNs are called triple-negative (10%). These appear to be heterogeneous disorders, but a large fraction are associated with increased JAK/STAT signaling22. Certain triple-negative MPNs are related to atypical MPL or JAK2 mutations23,24. A fraction of the so-called triple-negative ET might not be MPNs, but polyclonal disorders, such as hereditary thrombocytosis with germline mutations. Furthermore, the triple-negative PMF, which is of poor prognosis, may not be bona fide MPNs, but more a myelodysplastic syndrome associated with myelofibrosis25. This underscores the difficulties for classifying myeloid hematological malignancies, which might represent a spectrum of diseases with proliferation and differentiation defects at different levels.\n\nOne way to demonstrate that these mutations are really the MPN drivers is to create mouse models. Mutations in JAK2V617F, MPL, and CALR are capable of reproducing the MPN phenotype(s) in mice. JAK2V617F induces a myeloproliferative disorder—usually PV but also ET in some models26–29—which may progress to myelofibrosis. The unique models that have been presently described so far for MPLW515 and CALR mutations are bone marrow transplantations after retroviral transfer. In both cases the mice develop thrombocytosis, which progresses to myelofibrosis—quickly in the case of MPLW515L/A and more slowly for CALRdel5211,20.\n\nImportantly, in all these models, mice do not develop true PMF, but a secondary myelofibrosis (post-PV or post-ET). Thus, myelofibrosis can be the natural evolution of ET, without requiring other additional genetic abnormalities. Similarly high TPO levels in mice can induce a very severe myelofibrosis30,31. Overall, an exaggerated stimulation of the MK lineage can lead to myelofibrosis. These results could suggest that PMF may require other events (genetic/environmental).\n\nOne major limitation of the present mouse models is that the disease originates from several hematopoietic stem cells, while human MPNs exhibit a clonal hematopoiesis originating from a single hematopoietic stem cell32. Therefore, the first part of the human disease (how a single mutated HSC becomes predominant) is not studied in these models32. Other factors, including oncogenic cooperation, may be necessary for clonal dominance (see below).\n\nAlthough the different mutations induce the activation of JAK2, they do not lead to the same phenotype. For example, JAK2V617F can be associated with ET and PV, inducing hyperplasia of either MK or erythroid cells, depending on the conditions. One determining factor is clearly the number of JAK2V617F gene copies (heterozygous versus homozygous mutation)28,33. However, this is just one factor in determining MPN heterogeneity.\n\nAnother example is the CALR-mutated and JAK2V617F ET, which display different clinical and biological features, although in both cases the disease is related to the activation of the MPL/JAK2 pathway20,34. One obvious difference is related to the fact that JAK2V617F—in contrast to CALR—activates not only the MK cell line but also the erythroid and granulocytic lineages, explaining differences in the hematocrit and polymorphonuclear count. However, among the most marked differences are the higher level of thrombocytosis and the decreased frequency of thrombotic events in the CALR mutated ET35,36. The most striking difference concerns the allele frequency of the mutation: in ET, the JAK2V617F variant allele frequency is approximately 15% in granulocytes (30% of mutated cells) but is approximately 40% or more for mutated CALR (80% of the cells)37. Therefore, a greater clonal advantage at the level of HSCs is conferred by mutated CALR versus JAK2V617F, even if both diseases are dependent on MPL. Subtle differences in signaling pathways downstream of MPL/JAK2 might also be involved. For example, CALR mutants moderately activate the PI3K/AKT pathway, and PI3K inhibitors are not able to synergize with JAK2 inhibitors, contrasting what was observed for JAK2V617F19,38,39. The type of activated STAT could also play a role since MPL/JAK2 can activate STAT1, 2, 3, and 5, which may have markedly different effects on HSC and MK biology40–43.\n\nFurthermore, among CALR mutated ET, CALRdel52 and CALRins5 may define two different subtypes of diseases characterized by different levels of thrombocytosis and evolution. CALRdel52 ET can progress to secondary myelofibrosis much more frequently than CALRins5 ET44, with an important predominance of CALRdel52 in PMF (Figure 1). In the mouse models, CALRdel52-induced thrombocytosis progresses to myelofibrosis, but this progression is rarely observed for CALRins5.\n\nAgain, such differences might reflect subtle differences in the activation of the MPL/JAK2 pathway or activation of new signaling pathways. Indeed, the CALRdel52 has nearly lost all its capacity to bind calcium in its C-terminal domain (low affinity, high capacity) in contrast to CALRins5. This may lead to a leak of calcium from the ER to the cytoplasm and a different signaling in MKs and in HSCs44.\n\n\nThe somatic landscape of acquired mutations demonstrates that additional somatic mutations are present in MPNs but predominantly in PMF\n\nEarly studies on JAK2V617F MPNs have suggested that, in certain cases, JAK2V617F is not the initiating event but that it could be preceded by other mutations. With genome-wide approaches, it could be shown that some patients have TET2 mutations (∼15%)45. Subsequently, mutations in ASXL1 mutations (10–15%) were found in PMF46.\n\nWith the development of whole exome sequencing, it could be demonstrated that mutations in epigenetic regulators (such as TET2, DNMT3A, ASXL1, EZH2, and IDH1/IDH2) and in spliceosome components (such as SRSF2, U2AF1, and SF3B1) were present in BCR-ABL-negative MPNs harboring JAK2/MPL/CALR mutations17,47,48. Other mutations were also directly associated with leukemic progression, such as p53, RUNX1, CBL, and deletion in IKAROS49–51. These mutations can be associated, and the most frequent co-mutations concern SRSF2 associated with TET2 or ASXL1 or IDH52.\n\nIn contrast to mutations in signaling genes (MPN driver genes), which are rare in other myeloid malignancies, the additional mutations are not specific to MPNs and are found with a higher frequency in MDS and in mixed MDS/MPN disorders, such as chronic myelomonocytic leukemia53,54.\n\nBiological studies and mouse models showed that they may cooperate with MPN drivers to favor clonal dominance (TET2 or DNMT3A), to modify disease phenotype, or to promote either progression to myelofibrosis or leukemic transformation (ASXL1, IDH1/2, EZH2, and TP53).\n\nClonal dominance genes, such as TET2 or DNMT3A, are associated with all types of MPNs with low difference in frequency (∼12% in ET and 18% in PMF). However, all the other mutations are almost exclusively found in PMF17,55. In more than 80% of PMF, mutations of epigenetic regulators or spliceosome components are found, but they are identified in less than 25% of ET. Furthermore, in approximately 50% of PMF, two or more of these non-‘MPN driver’ genes are co-mutated. Moreover, CALR is the first mutation in nearly all cases and additional mutations are secondary in disease evolution16,17,47. In contrast, JAK2V617F can be preceded by mutations such as in TET2, DNMT3A, and ASXL1, whereas the inverse can be also observed.\n\nTwo non-mutually exclusive explanations can be invoked: (1) CALR mutations have a much higher capacity to provide clonal dominance than JAK2V617F and may not require other associated genetic events for disease initiation. (2) JAK2V617F gives rise to MPNs, which occur approximately 10 years later than CALR mutated MPNs. The genes, which precede JAK2V617F occurrence, are associated with age-related clonal hematopoiesis56,57, JAK2V617F MPNs being secondary to aging. Indeed, the order of acquisition of mutations is important in the phenotype of the disease, particularly for TET2 and DNMT3A58,59. Moreover, when the JAK2V617F mutation is acquired on an age-related hematopoiesis, leukemia or myelodysplastic syndrome transformation may occur on the initial JAK2V617F-negative clone60,61. The fact that the number of acquired mutations allows a good discrimination between ET (one mutation in the MPN driver gene plus eventually another driver mutation) and PMF (one mutation in the MPN driver gene and mutations in one or several other driver genes) is in agreement with the physiopathology of myelofibrosis itself (Figure 2). Indeed, there is evidence that myelofibrosis mainly results from a stromal reaction to the clonal hematopoiesis62 as a consequence of the release of profibrotic cytokines63,64. MKs are the key cells involved in the myelofibrosis because they can release, in the bone marrow, large amounts of profibrotic (transforming growth factor β1 [TGF-β1], basic fibroblast growth factor, and platelet-derived growth factor), angiogenic (vascular endothelial growth factor) and pro-inflammatory (interleukin-1 [IL-1]) cytokines62,65. The role of MKs in myelofibrosis development explains the link between MK hyperplasia and myelofibrosis. Cytokines such as TGF-β1 are stored in specific MK granules called α-granules. However, in PMF, the most important phenomenon is the MK differentiation defect, which may result in defective α-granule storage and in the release of fibrotic cytokines. It explains why morphological features of MK dysplasia are criteria to distinguish ET from early PMF66. Interestingly, most of the mutations in epigenetic regulators and spliceosome components lead to myeloid differentiation defects, especially in MKs67,68. Thus, PMF is not a pure MPN, exhibiting myeloproliferative and myelodysplastic features. The heterogeneity of the disease and its prognosis are dependent on the respective levels of each component, and the prognosis is poor when myelodysplastic features are predominant (Figure 3). This explains why ultimately the prognosis of PMF is mainly dependent on the type and number of mutations in epigenetic regulators and spliceosome genes55. Thus, it is expected that the new entity called pre-PMF or prefibrotic myelofibrosis will have a different pattern of acquired mutations from the classic ET, particularly with the presence of mutations in non-MPN driver genes. Otherwise, factors that regulate MPN phenotype and progression (other than acquired somatic mutations) should be identified.\n\nMutated dysplastic megakaryocytes (MKs) are responsible for the myelofibrosis and osteoclerosis by inducing the release of (i) non-activated transforming growth factor β1 (TGFβ1), which is activated in the bone marrow environment by a so far uncharacterized mechanism, possibly via integrins and matrix such as fibronectin and thrombospondin (TSP). Fibrosis begins around MKs associated with the proliferation of fibroblasts and eventually osteoblasts, (ii) interleukin-1α (IL-1α) is released and induces osteoprotegerin (OPG) by t stromal cells, a decoy receptor that blocks osteoclast production. Mutated hematopoietic stem cells (HSCs) induce the increase in IL-1α and the subsequent degradation of Schwann cells and mesenchymal stem cells, leading to fibrosis and osteosclerosis through cytokine storm and providing a favorable environment for the hematopoietic clone.\n\nBoundaries between diseases are not easy to determine and could be dependent on the types or the number of mutations. Proliferation is driven mainly by signaling mutations (JAK2, CALR, and MPL) while most of the mutations in epigenetic regulators and spliceosome components lead to differentiation defects. Thus, it can be considered that primary myelofibrosis (PMF) is not a pure myeloproliferative neoplasm (MPN) but a disorder with both myeloproliferative and myelodysplastic components. The heterogeneity of the disease and its prognosis are dependent on the respective levels of each component, and prognosis is poor if myelodysplastic features are predominant.\n\n\nFactors other than acquired somatic mutations are involved in the pathogenesis of MPNs\n\nIt is clear that factors other than somatic mutations are involved in the pathogenesis of MPNs, particularly in clinical features. They include different factors.\n\nSex-related differences are observed in the distribution of MPNs. ET is predominant in females and PMF in males. There are also differences in the sex ratio between CALR mutated and JAK2V617F ET. The former are slightly more prevalent in men and the latter in women35. There is no clear explanation for these differences. Hormones could be one explanation. Estrogens can inhibit the JAK2V617F cancer stem cells69. Iron metabolism could be another determinant, as it plays an important role in red blood cell and platelet production, with inverse effects.\n\nOther genetic determinants predispose to MPNs. The first characterized was the 46/1 haplotype, which involves the JAK2 locus70–72. This JAK2 haplotype induces a 3- to 5-fold increase in JAK2 V617F MPNs but not in CALR mutated MPNs73. Other genetic determinants have recently been found, such as TERT, MECOM, and HBS1L/MYB. The SNPs in TERT, MECOM, and JAK2 (other than 46/1) appear to predispose to JAK2V617F-negative MPNs, whereas the HBS1L/MYB SNPs predispose only to JAK2V617F ET74. An SNP located in the CALR gene could favor CALR mutations75, but this result remains controversial76. It is unknown whether other genetic determinants that regulate blood cell levels regulate the phenotype of MPNs.\n\nThe importance of these genetic determinants in the initiation and the progression of MPNs has recently been underscored in four families of the same geographical origin that develop hereditary forms of myeloid malignancies. The transmission is autosomal dominant and leads mainly to ET characterized by the same acquired driver mutations as sporadic cases, but with a very poor prognosis due to a rapid evolution to myelofibrosis and leukemia in more than one third of patients77. A duplication of six genes, two of which are GSKIP and ATG2B, appears to play a key role in this predisposition, implying that the Wnt pathway and autophagy may play important roles in the pathogenesis of MPNs.\n\nThe JAK-STAT pathway is central for signaling by the majority of the inflammatory cytokines, which were linked to MPN progression. In a study of 30 cytokine levels in 127 patients with PMF, it was found that circulating IL-8, IL-2R, IL-12, and IL-15 levels independently hold prognostic value in PMF78. Overall, many cytokines, including the above markers, G-CSF, and type I interferon (IFN), were increased, whereas IFN-γ was decreased78. Examination of patient-reported outcome and cytokine profiling demonstrated clear associations between MPN symptoms, such as fatigue, abdominal complaints, and microvascular and constitutional symptoms, and high levels of cytokines, particularly IL-1, IL-6, IL-8, and tumor necrosis factor-α (TNF-α)79.\n\nFrom the pathophysiology standpoint, some pro-inflammatory cytokines or chemokines may be important by directly promoting an extramedullary hematopoiesis. In addition, by increasing reactive oxygen species (ROS) production, they may contribute to the dominance of the JAK2V617F clone and disease progression by inducing secondary mutations. A special case is represented by TNF-α. Clonal dominance in JAK2V617F-positive MPNs has been associated with TNF-α secretion and signaling80. TNF-α was also suggested to impair the inhibitory effects of type I IFN on mutated MPN HSCs81. On the other hand, TNF-α inhibition signaling in one patient with myelofibrosis was associated with leukemia progression82. TNF-α also deregulates erythropoietin signaling, leading to anemia in AML and MDS83,84.\n\nAnemia is also associated with PMF and influences treatment and iron metabolism. Increased levels of both hepcidin and ferritin predicted inferior survival in an independent manner from inflammatory cytokines85.\n\nCo-morbidities can also be coincident with or induced by MPNs. One could ask whether JAK2 inhibitors would impact co-morbidities, which could act on the MPN clone or on the other cells that participate in production and effects of inflammation86. An example is STAT3 activation, which plays an important role in the inflammatory state associated with MPNs. However, when STAT3 is activated in hematopoietic cells from the clone, but not in the other hematopoietic and non-hematopoietic cells, it dampens the MPN phenotype, especially the thrombocytosis42. Chronic inflammation is a driving force for premature atherosclerosis and development of secondary cancer in MPNs81.\n\nThe anatomical location in which the HSCs reside, the hematopoietic niche, is key for HSC regulation and has been divided into two main compartments: (i) the endosteal niche near the endosteum; and (ii) the perivascular niche near the sinusoids. Many different types of cells compose the niche, mainly derived from mesenchymal stem cells (adipocytes, osteoblasts, and smooth muscle cells) of other origins such as Schwann cells, reticular cells, endothelial cells, and hematopoietic cells such as macrophages, osteoclasts, and MKs. MPN development can be potentially controlled by this bone marrow environment either directly through integrin interactions or indirectly via the production of various chemokines, cytokines, and signaling molecules. Alternatively, mutated HSCs can modify the niche to favor their development and to inhibit normal HSCs to induce clonal expansion. It has been shown that JAK2V617F HSCs secrete IL-1β, which induces the apoptotic death of mesenchymal and Schwann cells, suggesting that the normal but not JAK2V617F HSC is dependent of the niche resulting in a clonal expansion or that JAK2V617F HSCs need to damage the microenvironment to overcome its control. Thus, MPN has been considered a neuropathy that could be controlled by neuroprotective agents87.\n\nIn myelofibrosis, the excessive release of fibrotic factors by the mutated MKs could activate mesenchymal cells, leading to myelofibrosis, but also could modify the properties of mesenchymal stromal cells88 and their gene expression89. Some other components of the niche may also belong to the malignant clone. Recently, it has been described that some endothelial cells may also belong to the clone, particularly in the Budd-Chiari syndrome in the liver and the spleen90. Such mutated endothelial cells could potentially be deregulated to exacerbate cytokine or ROS production and to promote platelet adhesion and thrombosis.\n\nCertain cytokines were shown to contribute to MPN development. FLT3L was found to be increased in samples from patients with PMF. It is produced both by HSCs and stromal cells and was shown to participate through the p38 pathway to the dysmegakaryopoiesis and the migration of CD34+ progenitors91. IL-33 is overproduced in patients with MPN. It contributes to MPN development through stromal cells by promoting cytokine (granulocyte-macrophage colony-stimulating factor and IL-6) secretion via its receptor ST-2 and by amplifying hematopoietic progenitors92.\n\nNevertheless, the role of the niche in the development of the disease remains incompletely understood. The question of whether an initial abnormality in the bone marrow niche can be the initial event in MPNs remains entirely open. Experimentally, engineered mesenchymal cells could induce hematological malignancies. Deletion of Dicer1 in mouse osteoprogenitors led to MDS and leukemia through the acquisition of genetic abnormalities93. One of the best ways to study this “niche-induced disease” hypothesis will be to evaluate the role of identified genetic predisposing factors responsible for familial forms of MPNs on the microenvironment and HSCs, respectively, by using engineered mouse models.\n\nMPNs are age-related diseases. Both stromal cells and HSCs are modified during aging. With age, HSCs become myeloid-biased with increased cycling/ROS levels and loss of functional capacities that could be important for disease development94. Furthermore, these alterations can eventually favor clonal hematopoiesis with selection of mutated HSCs that acquired independence from stromal regulation. It is noteworthy that the most frequently involved somatic mutations (DNMT3A, TET2, ASXL1, and JAK2) linked to aging are also implicated in myeloid malignant hematological malignancies, including MPNs.\n\n\nConclusion\n\nThe understanding of the MPN pathogenesis, including ET and PMF, has greatly progressed these 10 last years because of the discovery of the main MPN driver mutations. More than 90% of non-BCR-ABL MPNs are clearly driven by an abnormal JAK2 activation, especially the cytokine receptor/JAK2 pathways and their downstream effectors. Genomic studies demonstrated that PMF is a more advanced form of MPN, but with a molecular redundancy with ET. However, in contrast to classic ET and PV, PMF constantly includes one or several mutations in non-MPN driver genes, which are present also in MDS. This and the cytological features of the disease strongly suggest that PMF is a heterogeneous disorder associating phenotype/genotype features of MPN and MDS, with the latter being crucial for prognosis.\n\nSeveral important questions remain to be solved:\n\n- What are the mechanisms of disease initiation? Indeed, JAK2V617F can be frequently acquired but rarely gives rise to a disease.\n\n- Why in ET and PMF do JAK2V617F and mutant CALR pathways give rise to close but different diseases, while they both activate MPL/JAK2? A similar question may arise for type 1 and type 2 CALR mutations.\n\n- Why can a mutation like JAK2V617F give rise to several diseases?\n\n- What are the molecular mechanisms of oncogenic cooperation between MPN driver mutations and other acquired somatic mutations? How does this oncogenic cooperation lead to leukemia?\n\nIn all cases, one major question remains to be solved: what are the respective roles of the genetic abnormalities, either germline or acquired (intrinsic factors), and of the environment (extrinsic factors) in disease initiation, phenotype, and progression?\n\nFinally, from the therapeutic point of view, new approaches which will preferentially target an oncogenic JAK2 activation versus the physiological JAK2 role in cytokine signaling remain to be identified. In PMF with a high level of myelodysplastic features, this type of approach might not be sufficient and will require novel combined approaches.\n\n\nAbbreviations\n\nAML, acute myeloid leukemia; CALR, calreticulin; ER, endoplasmic reticulum; ET, essential thrombocythemia; G-CSF, granulocyte colony-stimulating factor; HSC, hematopoietic stem cell; IFN, interferon; IL, interleukin; MDS, myelodysplastic syndrome; MK, megakaryocyte; MPN, myeloproliferative neoplasm; NGS, next-generation sequencing; PMF, primary myelofibrosis; PV, polycythemia vera; ROS, reactive oxygen species; TGF-β1, transforming growth factor β1; TNF-α, tumor necrosis factor-α.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThis work was supported by grants from Ligue Nationale Contre le Cancer (“Equipe labellisée 2016”); Association pour la Recherche sur le Cancer (projet libre 2012 to IP); Agence Nationale de la Recherche, programme Jeunes Chercheuses et Jeunes Chercheurs (ANR-13-JVSV1-GERMPN-01 to IP); Institut National du Cancer (PLBIO2015 to IP); MPN research foundation; and Institut National de la Santé et de la Recherche Médicale (Inserm). The Laboratory of Excellence Globule Rouge-Excellence (IP and WV) is funded by the program “Investissements d’avenir”. SNC has received funding from the Ludwig Institute for Cancer Research, FRS-FNRS, Salus Sanguinis, Fondation contre le cancer, Project Action de Recherche Concertée of the Université catholique de Louvain ARC10/15-027, and the PAI program Belgian Medical Genetics Initiative.\n\n\nReferences\n\nSpivak JL: The chronic myeloproliferative disorders: clonality and clinical heterogeneity. Semin Hematol. 2004; 41(2 Suppl 3): 1–5. PubMed Abstract | Publisher Full Text\n\nTefferi A, Vardiman JW: Classification and diagnosis of myeloproliferative neoplasms: the 2008 World Health Organization criteria and point-of-care diagnostic algorithms. Leukemia. 2008; 22(1): 14–22. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBarosi G, Ambrosetti A, Finelli C, et al.: The Italian Consensus Conference on Diagnostic Criteria for Myelofibrosis with Myeloid Metaplasia. Br J Haematol. 1999; 104(4): 730–7. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nEder-Azanza L, Evans P, Wickham C, et al.: Constitutional genetic association with CALR mutations? Leukemia. 2015; 29(12): 2410–1. PubMed Abstract | Publisher Full Text\n\nSaliba J, Saint-Martin C, Di Stefano A, et al.: Germline duplication of ATG2B and GSKIP predisposes to familial myeloid malignancies. Nat Genet. 2015; 47(10): 1131–40. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nTefferi A, Vaidya R, Caramazza D, et al.: Circulating interleukin (IL)-8, IL-2R, IL-12, and IL-15 levels are independently prognostic in primary myelofibrosis: a comprehensive cytokine profiling study. J Clin Oncol. 2011; 29(10): 1356–63. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGeyer HL, Dueck AC, Scherber RM, et al.: Impact of Inflammation on Myeloproliferative Neoplasm Symptom Development. Mediators Inflamm. 2015; 2015: 284706. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFleischman AG, Aichberger KJ, Luty SB, et al.: TNFα facilitates clonal expansion of JAK2V617F positive cells in myeloproliferative neoplasms. Blood. 2011; 118(24): 6392–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHasselbalch HC: Perspectives on the impact of JAK-inhibitor therapy upon inflammation-mediated comorbidities in myelofibrosis and related neoplasms. Expert Rev Hematol. 2014; 7(2): 203–16. PubMed Abstract | Publisher Full Text\n\nFerrer-Marín F, Amigo ML, Vicente V: Leukaemic transformation in patients with haematological disease receiving tumour necrosis factor inhibitors. Clin Drug Investig. 2012; 32(6): 423–6. PubMed Abstract | Publisher Full Text\n\nKurzrock R: The role of cytokines in cancer-related fatigue. Cancer. 2001; 92(6 Suppl): 1684–8. PubMed Abstract | Publisher Full Text\n\nMeyers CA, Albitar M, Estey E: Cognitive impairment, fatigue, and cytokine levels in patients with acute myelogenous leukemia or myelodysplastic syndrome. Cancer. 2005; 104(4): 788–93. PubMed Abstract | Publisher Full Text\n\nPardanani A, Finke C, Abdelrahman RA, et al.: Associations and prognostic interactions between circulating levels of hepcidin, ferritin and inflammatory cytokines in primary myelofibrosis. Am J Hematol. 2013; 88(4): 312–6. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKleppe M, Kwak M, Koppikar P, et al.: JAK-STAT pathway activation in malignant and nonmalignant cells contributes to MPN pathogenesis and therapeutic response. Cancer Discov. 2015; 5(3): 316–31. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nArranz L, Sánchez-Aguilera A, Martín-Pérez D, et al.: Neuropathy of haematopoietic stem cell niche is essential for myeloproliferative neoplasms. Nature. 2014; 512(7512): 78–81. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMartinaud C, Desterke C, Konopacki J, et al.: Osteogenic Potential of Mesenchymal Stromal Cells Contributes to Primary Myelofibrosis. Cancer Res. 2015; 75(22): 4753–65. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMartinaud C, Desterke C, Konopacki J, et al.: Transcriptome analysis of bone marrow mesenchymal stromal cells from patients with primary myelofibrosis. Genom Data. 2015; 5: 1–2. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSozer S, Fiel MI, Schiano T, et al.: The presence of JAK2V617F mutation in the liver endothelial cells of patients with Budd-Chiari syndrome. Blood. 2009; 113(21): 5246–9. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nDesterke C, Bilhou-Nabéra C, Guerton B, et al.: FLT3-mediated p38-MAPK activation participates in the control of megakaryopoiesis in primary myelofibrosis. Cancer Res. 2011; 71(8): 2901–15. PubMed Abstract | Publisher Full Text\n\nMager LF, Riether C, Schürch CM, et al.: IL-33 signaling contributes to the pathogenesis of myeloproliferative neoplasms. J Clin Invest. 2015; 125(7): 2579–91. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nRaaijmakers MH, Mukherjee S, Guo S, et al.: Bone progenitor dysfunction induces myelodysplasia and secondary leukaemia. Nature. 2010; 464(7290): 852–7. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMarty C, Lacout C, Droin N, et al.: A role for reactive oxygen species in JAK2V617F myeloproliferative neoplasm progression. Leukemia. 2013; 27(11): 2187–95. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13456",
"date": "19 Apr 2016",
"name": "Simon Mendez-Ferrer",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13457",
"date": "19 Apr 2016",
"name": "Alessandro M. Vannucchi",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-700
|
https://f1000research.com/articles/5-699/v1
|
19 Apr 16
|
{
"type": "Review",
"title": "Wnt signaling in cancer stem cells and colon cancer metastasis",
"authors": [
"Sayon Basu",
"Gal Haase",
"Avri Ben-Ze'ev",
"Sayon Basu",
"Gal Haase"
],
"abstract": "Overactivation of Wnt signaling is a hallmark of colorectal cancer (CRC). The Wnt pathway is a key regulator of both the early and the later, more invasive, stages of CRC development. In the normal intestine and colon, Wnt signaling controls the homeostasis of intestinal stem cells (ISCs) that fuel, via proliferation, upward movement of progeny cells from the crypt bottom toward the villus and differentiation into all cell types that constitute the intestine. Studies in recent years suggested that cancer stem cells (CSCs), similar to ISCs of the crypts, consist of a small subpopulation of the tumor and are responsible for the initiation and progression of the disease. Although various ISC signature genes were also identified as CRC markers and some of these genes were even demonstrated to have a direct functional role in CRC development, the origin of CSCs and their contribution to cancer progression is still debated. Here, we describe studies supporting a relationship between Wnt-regulated CSCs and the progression of CRC.",
"keywords": [
"Wnt",
"colorectal cancer",
"intestinal stem cells",
"cancer stem cells",
"β-catenin",
"Lgr5"
],
"content": "Introduction\n\nWnt signaling has emerged during evolution as a highly conserved signaling pathway that regulates tissue morphogenesis and regeneration (via stem cells) in various tissues of multicellular organisms1. Hyperactivation of β-catenin-T cell factor (TCF)/lymphoid enhancer factor (LEF)-regulated gene transcription (the end point of Wnt signaling) is a hallmark of colorectal cancer (CRC) development. β-catenin is also a key regulator of cell-cell adhesion, by linking the E-cadherin transmembrane adhesion receptor that binds neighboring epithelial cells to each other, to the actin-cytoskeleton2. Therefore, activation of the Wnt pathway in CRC provides an attractive model for studying the links between tissue morphogenesis and cell adhesion and the disregulation of these processes during cancer progression.\n\nThe canonical Wnt pathway is also known as the Wnt-β-catenin pathway since β-catenin is a key transducer of the Wnt signal from the cytoplasm to the nucleus. In unstimulated cells, the free pool of β-catenin (the one not engaged in cadherin-mediated cell-cell adhesion) is phosphorylated by a complex of proteins that includes the scaffold molecule Axin and adenomatous polyposis coli (APC) and the kinases glycogen synthase kinase 3β (GSK3β) and casein kinase 1 (CK1)1,2. After phosphorylation, β-catenin is targeted for proteolytic degradation by the proteasome. Wnt is secreted from cells as a lipid-modified molecule that acts in short-range signaling3,4 and stimulates signaling by binding of the Wnt ligands to the Frizzled transmembrane receptors and to the Lrp5/6 co-receptors. The cytoplasmic tail of Lrp becomes phosphorylated, inhibits GSK3β, and associates with Axin. Wnt signaling is positively regulated by the secreted R-spondins that act to stabilize the Frizzled receptors against degradation by the Rnf43/Znrf3 ubiquitin ligases5,6. Activation of the Wnt pathway results in the disruption of the CK1-GSK3β-Axin-APC-β-catenin complex, inhibition of GSK3β activity, and the stabilization of β-catenin against degradation in the cytoplasm by the ubiquitin-proteasome pathway. The accumulation of β-catenin in the cytoplasm results in its nuclear translocation. In the nucleus, β-catenin binds to members of the TCF/LEF family of transcription factors and plays a role as a co-activator of target gene transcription7. In CRC, aberrant activation of the Wnt signaling pathway is a central oncogenic driver in 90% of patients, mostly resulting from mutations in the APC gene8. Expression of genes by the aberrant transcriptional activity of the β-catenin-TCF complex contributes to both the initial stages of the disease and the later stages involving invasion and metastasis9. Here, we describe recent findings on the involvement of Wnt signaling in CRC progression and its relationship to the emerging role of cancer stem cells (CSCs) in CRC.\n\n\nWnt signaling in intestinal stem cell homeostasis\n\nIntestinal epithelial cells display the highest turnover rate, and the entire intestinal epithelial lining in humans is replaced every 5 to 7 days10. This rapid regeneration is fueled by the proliferation of stem cells at the base of the intestinal crypts of Lieberkühn and the upward migration and differentiation of stem cells that enables normal tissue homeostasis. The morphological separation of the stem cell compartment (the crypt where the cells proliferate) and the differentiated compartment (villus in the intestine, and the surface epithelium in the colon, where the cells interact with the gut environment) depends on a gradient of Wnt signaling. The strongest Wnt signaling is detected at the crypt base (where some cells display nuclear β-catenin localization) and gradually weakens toward the luminal side of the vertical crypt-villus axis11. Wnt signaling is necessary for the initial potentiation of intestinal stem cells (ISCs) as evident from studies in neonatal transgenic mice that lost TCF4 and thus fail to develop normal proliferative crypts12. Both crypt homeostasis and stem cell maintenance require active Wnt signaling since conditional activation of Wnt antagonists in transgenic mice leads to the progressive loss of intestinal crypts13–15. Similarly, conditional abrogation of Wnt signaling in cells at the crypt base, by deletion of either β-catenin16 or TCF417, leads to the loss of proliferative crypts.\n\nThe intestinal crypt has long been recognized as the niche for proliferative, multipotent precursor cells of the intestine and colon, and the Wnt target gene Lgr5, a receptor for the Wnt agonist R-spondin that enhances Wnt signaling, was identified as a marker for columnar crypt base stem cells18. Lineage-tracing experiments in transgenic mice revealed that Lgr5+ cells found in the crypt base are multipotent and capable of clonally repopulating the entire epithelial lining of the intestine and colon18. Gene expression and proteomic signature studies of Lgr5+ cells revealed several additional ISC markers, including Ascl2 and Sox919. The basic helix-loop-helix (bHLH) transcription factor Ascl2 is a major transcriptional regulator of genes associated with stemness in crypt cells and is a key ISC marker20. Similarly, the transcription factor Sox9 is also expressed by stem cells in the intestinal and colonic crypt base and is necessary for the maintenance of ISCs21,22. Like Lgr5, Ascl2 and Sox9 are also Wnt target genes in ISCs. This points to the requirement for high Wnt signaling in the maintenance of the stem cell niche23.\n\nExperiments tracking cell proliferation and migration in the intestine identified as putative stem cells, cells at position +4 (4 cells up from the crypt base) in the intestine. These cells display proliferative regeneration in intestinal epithelia upon cytotoxic damage and are highly sensitive to radiation-induced apoptosis24,25. The cells at position +4 within the intestinal crypt undergo continuous proliferation while retaining 3H-labeled DNA (hence, the cells are named label-retaining cells, or LRCs) and support the notion that “+4” LRCs function as stem cells26. Bmi1, a chromatin silencing component, was identified as a marker for LRCs, and lineage-tracing experiments revealed that Bmi1+ LRCs are undifferentiated stem-like cells. Bmi1+ LRCs may either self-renew or clonally expand and differentiate into all cell types of the intestinal mucosa, including Lgr5+ columnar crypt base cells27,28. Unlike the turnover rate of Lgr5+ crypt base stem cells, that of Bmi1+ LRCs (situated just above the crypt base) is much slower, indicating that they are probably not the major stem cell type that functions in intestinal homeostasis27 and are proposed to function as reserve stem cells in response to tissue damage29. In addition to Bmi1, Hopx, Tert and Lrig1 are also markers of LRCs30–32. Although Lgr5 and Bmi1 are apparently markers of two distinct subpopulations of stem cells, there is an overlap between these markers with Bmi1 being strongly expressed by a subset of Lgr5+ ISCs19. Apart from LRCs, committed Dll1+ secretory progenitor cells located even further upwards from the crypt bottom also retain the ability to re-acquire stem cell functions and regenerate the stem cell compartment in response to tissue damage33. Although strong Wnt signaling and the paracrine context at the crypt base are essential components that regulate the maintenance of the ISC pool, more differentiated cells retain sufficient plasticity that allows them to revert to a stem cell-like behavior under stressful conditions29,30,34. Since genotoxic stress and other carcinogenic perturbations may affect the stem cell pool, they may also play a key role in the development of CRC34.\n\n\nCancer stem cells and Wnt signaling in colorectal cancer\n\nCSCs are hypothesized to constitute a small fraction of the tumor tissue. In a role similar to that of ISCs in normal tissue, CSCs are suggested to give rise to progenitors that populate the majority of the tumor35. Two models describing the histogenesis of CRC have been proposed: the ‘‘top-down’’ and the “bottom-up” morphogenesis. The “top-down” model suggests that the more differentiated (luminal) cells re-acquire stem cell-like properties and produce aberrant crypt foci where tumors develop36. The ‘‘bottom-up’’ histogenesis suggests that stem cells residing at the crypt base expand and migrate upwards and constitute the tumor-initiating cells37. In both models, Wnt signaling is considered an important regulator. According to the “top-down” theory, hyperactivation of β-catenin-TCF signaling drives differentiated epithelial cells into regaining pluripotency, thereby forming new, disregulated crypt-like structures that later turn into adenomas38. The increased frequency at which very early adenomatous polyps are observed at the top of colonic crypts (far removed from the stem cell compartment) has led researchers to suggest that neoplastic transformation in CRC is initiated from differentiated cells39. Other studies in transgenic mouse models for intestinal cancer have shown that differentiated epithelial cells can re-acquire stem cell-like properties upon the combined activation of Wnt and nuclear factor-κB (NF-κB) signaling, conferring tumor-initiating cell properties38. On the other hand, immunohistochemical studies of early sporadic colorectal adenomas have shown adenomatous lesions near the crypt base37. These lesions have increased proliferative activity with nuclear β-catenin localization while their corresponding surface epithelial cells maintain β-catenin in sub-membrane adherens junctions (not in the nucleus)37. Moreover, the conditional loss of APC in Lgr5+ colonic crypt base stem cells induced their rapid transformation into micro-adenomas, indicating that increased Wnt activity in the Lgr5+ stem cell compartment may trigger a tumor-initiating process40. Similarly, conditional activation of β-catenin in Bmi1+ LRCs led to an immediate generation of adenomas in the duodenum27. These studies support the “bottom up” histogenesis of CRC suggesting that excessive Wnt activation in the stem cell compartment is an essential step in neoplastic transformation. Chronic inflammation and other conditions that increase NF-κB signaling support the notion that a dedifferentiation step can occur in intestinal epithelia, supporting CRC development by a “top down” histogenesis. Conversely, if stem cells at the crypt bottom acquire mutations that lead to activation of Wnt signaling, CRC may arise by the “bottom up” model.\n\nOne way or the other, the overriding importance of Wnt signaling in CRC development, as compared with other driving oncogenes in CRC, such as Kras and p53, was recently demonstrated by an effective, conditional suppression of APC by using small hairpin RNA (shRNA) in transgenic mice41. The suppression of APC by this method resulted in intestinal and colon cancer development in mice. Restoration of APC expression in these tumors resulted in the reversal of tumorigenic lesions and the complete reconstitution of a normal stem cell compartment, even in mice harboring oncogenic Kras and p5341.\n\nIn CRC tissue, Wnt signaling (as gauged by nuclear β-catenin localization) is not homogenous, even though all CRC cells harbor an activating mutation in the Wnt pathway42. This observation, called “the β-catenin paradox”, was first observed by immunohistochemical analyses of CRC tissue. Well-differentiated cells, located in the more central areas of the tumor, display mostly β-catenin associated with E-cadherin under the membrane, as in the normal intestinal epithelium, whereas tumor cells localized at the invasive front of the same tumor exhibit strong nuclear β-catenin staining43. These invasive edge-localized cells were shown to preferentially express Wnt target genes that confer invasive-metastatic capacity when expressed in human CRC cells44–46. Vermeulen et al.47 investigated the role of Wnt signaling in the homeostasis of CSCs in human CRC: CSCs isolated from patients and cultured as spheroids displayed a heterogeneous level of Wnt signaling over a 100-fold change. The Wnthigh cells formed more tumors in mice with fewer injected cells compared with Wntlow cells. This heterogeneity in Wnt signaling was maintained in the tumors formed in mice that also expressed several ISC markers, including Lgr5 and Ascl247. The importance of Wnt signaling in the maintenance of the CSC pool and in driving CRC progression is also highlighted in a study in which conditional activation of the Wnt antagonist HoxA5 suppressed tumor growth and metastatic progression by repressing stemness properties15.\n\n\nLgr5 as a Wnt-induced cancer stem cell marker\n\nLgr5, a target gene of Wnt signaling, is a well-established ISC marker18. Studies involving mouse models of intestinal cancer have provided the initial evidence that Lgr5+ cells act as tumor-initiating cells, since activation of Wnt signaling (by conditional deletions of APC) in the Lgr5+ subpopulation of intestinal cells led to adenoma formation40,48. Recent studies attempting to define an ISC gene signature in CRC tissue repeatedly detected Lgr5 as a key component in such signatures49–52. The presence of Lgr5 on the surface of cells is sufficient for successful isolation of the CSC fraction from CRC tissue, and similar to its role in the normal intestine, Lgr5 defines the undifferentiated stem cell state in CSCs. CRC cells with high Lgr5 expression had enhanced ability to clonally expand and give rise to colonies in vitro, whereas suppression of Lgr5 expression results in the loss of their ability to form colonies51. An ISC gene signature derived from EphB2high columnar crypt base cells was suggested as a powerful predicting tool of human CRC progression and disease relapse50. The EphB2high ISC signature had a significant overlap with a previously described Lgr5-ISC signature19. Tumors with high levels of Lgr5-ISC signature genes were more aggressive and metastatic and also displayed an increased tendency to relapse in patients with CRC50. In an evaluation of 19 putative stem cell markers, Lgr5 was prevalently expressed in 74% of human CRC samples. Lgr5 and Ascl2 were significantly co-expressed with each other and with other genes from the list, supporting the hypothesis that adenocarcinomas are derived from Lgr5+/Ascl2+ crypt stem cells53. However, other studies have defined a non-Wnt-induced CSC gene list that does not include Lgr5 or other well-established Wnt-target genes. In a study on disease recurrence in CRC patients who went through curative surgery, a reverse correlation between Wnt-target genes (Lgr5, Ascl2, Axin2, Dkk1, and Apcdd1) levels and disease recurrence was found, suggesting that elevated expression of Wnt-target genes is associated with good prognosis54. Based on studies with CRC cell lines, these Wnt-target genes were silenced by CpG island methylation, and once methylation was inhibited, these cells lost their ability to generate colonies in vitro. These studies suggest that methylation of Wnt-target genes in CSCs is a strong predictor of CRC recurrence54.\n\n\nThe involvement of Wnt-induced cancer stem cells in colorectal cancer metastasis\n\nAccording to the “β-catenin paradox”, only cells at the invasive front of the tumor tissue display strong nuclear β-catenin localization. These cells apparently go through an epithelial-to-mesenchymal transition (EMT), thus making them more motile and invasive, implying a role for the Wnt-induced CSCs in the propagation of metastasis. EMT has been suggested for some time as a key mechanism governing the generation of CSCs, especially as revealed by studies using breast cancer cell lines55. In CRC, the EMT program influences a variety of malignant phenotypes associated with metastasis, including the generation of CSCs, tumor budding, circulating tumor cells, and drug resistance56. The role of EMT in epithelial cancer, however, is still incompletely understood. Recent reports on lung and pancreatic cancer found that although EMT affects chemoresistance, it is not required for metastasis57,58. Since CSCs can both self-renew and differentiate, such cells can better adjust to the changes involved in the various stages of cancer metastasis59. The involvement of CSCs derived by activation of Wnt signaling in the later stages of cancer progression was suggested in a study showing that Lgr5 expression correlated with the malignant potential of CRC tumors and cell lines49. Tumors displaying increased levels of Lgr5 were of higher stage and were more invasive and formed more lymph node metastases49. With the increasing number of studies suggesting the involvement of CSCs in the propagation of metastasis, the hypothesis of “migrating cancer stem cells” (MCSCs) was put forward as the driving force leading to metastasis59,60. According to this model, the inherent plasticity of CSCs is employed during the advanced stages of cancer progression that require the acquisition of invasive properties and migration through the blood and lymph vessels to distant organs. Newly formed metastatic tumors were shown to have a high genomic and proteomic similarity to the primary tumors from which they were derived, suggesting that after colonization MCSCs revert to their initial phenotype61. A study comparing gene expression from primary CRC tissue and liver metastatic foci of the same patients found that the expression of Ascl2 (an ISC marker and Wnt target gene) is upregulated in the metastatic tumors together with several other Wnt-induced ISC markers, including Lgr5, EphB3, Ets2, and Sox961. Other ISC signature markers, such as Smoc219, were also found to play a role in the promotion of metastasis in human CRC cells62. Smoc2 expression was preferentially increased at the invasive edge of CRC tumors, and Smoc2 exclusively localized at the bottom of colonic crypts in the normal colonic epithelium63. Moreover, L1-induced metastatic CRC cell lines lost their metastatic potential when Smoc2 was silenced62.\n\n\nCrosstalk between Wnt signaling and other pathways in “stemness” and colorectal cancer metastasis\n\nAlthough Wnt/β-catenin-TCF activation can directly influence the expression of “stemness” signature genes in CRC cells, such as Lgr5 and Ascl2, Wnt signaling often interacts with other pathways in triggering the acquisition of a stem cell-like behavior in CRC cells. Inflammation-related signaling has long been implied as a key regulator in Wnt-β-catenin-driven cancers, including CRC63. NF-κB signaling that regulates the pro-inflammatory cytokine response emerged as a key pathway in regulating the development of various cancers by being a potent driver of oncogenic signaling64. In view of the important role of Wnt signaling in the maintenance of the stem niche in intestinal tissue and its deregulation in CRC, it was of interest to determine whether Wnt and NF-κB signaling interact in promoting CRC progression. This was recently addressed in the context of the cell adhesion receptor L1 (or L1CAM), a β-catenin-TCF target gene in CRC cells45. L1 that is exclusively expressed in cells at the invasive edge of CRC tissue displaying nuclear β-catenin was found to activate NF-κB signaling by a mechanism involving the cytoskeletal protein ezrin65. L1 and ezrin, together with IκB, form a complex that induces a more rapid degradation of IκB, followed by nuclear translocation and activation of NF-κB target genes66. By blocking this L1-ezrin-NF-κB signaling, the acquisition of increased motility and liver metastasis by CRC cells was inhibited65. L1-induced NF-κB activation leads to the expression of several ISC markers, including IGFBP266 and Smoc262. In another study, the loss of APC in CRC was shown to trigger the expression of a Rac1 GTPase, a member of the RACGEF family, via β-catenin-TCF-induced expression of the oncogenic transcription factor c-Myc67,68. As in the case of L166, the activation of Rac1 leads to enhanced NF-κB signaling, resulting in the expansion of the Lgr5+ CRC stem cell compartment in an APC-deficient milieu68. Thus, activation of NF-κB signaling in a Wnthigh context may potentiate tumor cells to acquire a stem cell-like phenotype68. In addition, a constitutive activation of β-catenin signaling in differentiated intestinal epithelial cells of transgenic mice was shown to trigger the expansion of intestinal crypt cells and requires the activation of NF-κB signaling38. NF-κB was shown to directly bind to β-catenin and modulate its transcriptional activity, thereby affecting the expression of ISC signature genes38. Lastly, the inflammatory microenvironment displaying highly active NF-κB signaling was shown to lead to the acquisition of a stem cell-like behavior and neoplastic transformation69,70.\n\nBone morphogenetic protein (BMP) signaling, through the transcriptional co-activator SMAD4, also plays an important role in CRC tumorigenesis71. Mutations in the BMP receptor BMPR1A, or in SMAD4, underlie the juvenile polyposis syndrome, a rare autosomal dominant trait with increased risk for CRC71. SMAD4 mutations were shown to account for the shift in CRC tumor phenotype from the large adenoma to the adenocarcinoma stage72,73. Wnt-β-catenin signaling was reported to be required for BMP4 expression in CRC tumors74,75, and the transcription factor GATA6 affects both BMP and Wnt signaling in CRC stem cells76. This is achieved by abrogating Wnt-triggered BMP4 expression in stem cells derived from colorectal adenoma that is apparently required for stem cell self-renewal in colon adenoma76. Thus, the modulation (by the Wnt pathway) of the strength of NF-κB signaling, or of BMP and additional signaling pathways, is an important determinant of CRC progression. The strength of BMP signaling and its downstream messengers, including SMAD4, and additional driver mutations of CRC, such as p53, may affect the outcome of Wnt signaling in CRC development77.\n\nIn addition to interacting with NF-κB and BMP signaling, the Wnt pathway affects other signaling molecules that are required for the acquisition and maintenance of the stem-like state in CRC cells. The β-catenin-TCF complex was shown to regulate the energy metabolism in CRC stem cells and to fuel the growth of CRC tumors by inducing the expression of the transcription factor PROX178,79. The cell adhesion receptor L1 (see above) induces the expression of the ISC marker Clusterin in CRC cells via STAT1 activation that is known to be stimulated by pro-inflammatory cytokines80. The increased expression of the ISC marker Msi181, an RNA-binding protein and a β-catenin-TCF target gene, was linked to the elevated metastatic potential and poorer prognosis of CRC82,83. Msi1 can trigger the activation of Wnt and Notch signaling by a positive feedback regulation in ISCs, a regulatory loop recapitulated during CRC development84. The Msi1 homolog, Msi2 (also a β-catenin-TCF target gene), displays an increased expression in intestinal cancer and drives the proliferation of stem-like cells through inhibition of PTEN and by inducing the mTORC1 pathway85. Thus, together, these results suggest that the increase in Wnt signaling, even in more differentiated CRC cells, promotes the acquisition of a phenotype resembling that of ISCs by reconstituting a signaling environment that supports dedifferentiation.\n\n\nConclusions\n\nA microenvironment enabling high Wnt signaling supports stem cell renewal at the base of the intestinal crypts of Lieberkühn and apparently leads to the acquisition of stem cell-like properties in cells at the invasive edge of CRC tissue. Although a link between “stemness” properties and metastasis was suggested by numerous studies, the existence of CSCs has been difficult to identify in clinical tumor samples35,86. A common concept in cancer development suggests that tumors arise from proliferation and survival of a clonal subpopulation of stem cells within the tumor. However, studies with CRC indicate that tumors may arise from several different parent cells, each contributing a distinct lesion and thus generating polyclonal tumors87. A polyclonal adenoma was described in an XO/XY individual with familial adenomatous polyposis (FAP)88. Polyclonal adenomas were also observed in mice with a chimeric loss in APC in the intestinal epithelium89. Conditional deletion of APC in stem cells labeled with a fluorescence reporter for Lgr5 triggered the development of adenomas from different cell clones within the intestinal tract48. Given the high plasticity of the intestinal and colonic crypt cells and their ability to readily revert to “stemness” upon stress, it is possible that the CSCs in CRC tissue originate from different lineages of parent cells. Although a stem cell hierarchy is supposed to exist in the CRC tissue, the high plasticity also means that the expression of ISC signature genes may be heterogeneous and thus cancer cells not originating from ISCs may also express ISC signature genes to some extent. Thus, CRC cells may express various stem cell markers without re-acquiring a full “stemness” potential. The contradictory reports regarding the association of Lgr5 with various stages of CRC progression49,50,53,54,90–92 could be explained by the heterogeneity among the cells of the CRC tissue, as related to the expression of stem cell markers. Our current understanding of stem markers comes from studies on Wnt target genes or of markers of the Bmi1+ LRCs that were identified as putative cells of the stem cell compartment. Given that some stem cell markers are not dependent on Wnt signaling, further studies are required to determine the functional relevance of the many genes identified as stem cell signature genes in both normal and CRC tissue. Determining their roles in CRC not only will provide a better understanding of their function in intestinal homeostasis but will provide novel markers for targeting CRC. Using expression profiles for multiple stem cell markers in tandem increases the successful prediction of prognosis and outcome in CRC50. Further studies of the stem cell niche and the molecules controlling self-renewal will provide a better definition of markers for the stem cell compartment. Current paradigms propose that treatments against cancer that fail to eradicate the CSC population will have little success in preventing future relapses of the disease. If correct, this hypothesis calls for additional research aiming to identify and understand the role of the subpopulations of CSCs in cancer development and for their more effective targeting.\n\n\nAbbreviations\n\nAPC, adenomatous polyposis coli; BMP, bone morphogenetic protein; CK1, casein kinase 1; CRC, colorectal cancer; CSC, cancer stem cell; EMT, epithelial-to-mesenchymal transition; GSK3β, glycogen synthase kinase 3β; ISC, intestinal stem cell; LEF, lymphoid enhancer factor; LRC, label-retaining cell; MCSC, migrating cancer stem cell; NF-κB, nuclear factor kappa light chain enhancer of B cells; TCF, T-cell factor.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nStudies from the authors’ laboratory were supported by grants from the Israel Science Foundation (ISF) and the Israel Cancer Research Fund (ICRF).\n\n\nReferences\n\nClevers H, Loh KM, Nusse R: Stem cell signaling. An integral program for tissue renewal and regeneration: Wnt signaling and stem cell control. Science. 2014; 346(6205): 1248012. PubMed Abstract | Publisher Full Text\n\nConacci-Sorrell M, Zhurinsky J, Ben-Ze'ev A: The cadherin-catenin adhesion system in signaling and cancer. J Clin Invest. 2002; 109(8): 987–91. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGross JC, Chaudhary V, Bartscherer K, et al.: Active Wnt proteins are secreted on exosomes. Nat Cell Biol. 2012; 14(10): 1036–45. 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}
|
[
{
"id": "13450",
"date": "19 Apr 2016",
"name": "Jan Paul Medema",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13454",
"date": "19 Apr 2016",
"name": "Takeshi Sakurai",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13455",
"date": "19 Apr 2016",
"name": "Hans Clevers",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-699
|
https://f1000research.com/articles/5-696/v1
|
18 Apr 16
|
{
"type": "Review",
"title": "Provisional Tic Disorder: What to tell parents when their child first starts ticcing",
"authors": [
"Kevin J Black",
"Elizabeth Rose Black",
"Deanna J. Greene",
"Bradley L. Schlaggar",
"Elizabeth Rose Black",
"Deanna J. Greene",
"Bradley L. Schlaggar"
],
"abstract": "The child with recent onset of tics is a common patient in a pediatrics or child neurology practice. If the child’s first tic was less than a year in the past, the diagnosis is usually Provisional Tic Disorder (PTD). Published reviews by experts reveal substantial consensus on prognosis in this situation: the tics will almost always disappear in a few months, having remained mild while they lasted. Surprisingly, however, the sparse existing data may not support these opinions.PTD may have just as much importance for science as for clinical care. It provides an opportunity to prospectively observe the spontaneous remission of tics. Such prospective studies may aid identification of genes or biomarkers specifically associated with remission rather than onset of tics. A better understanding of tic remission may also suggest novel treatment strategies for Tourette syndrome, or may lead to secondary prevention of tic disorders.This review summarizes the limited existing data on the epidemiology, phenomenology, and outcome of PTD, highlights areas in which prospective study is sorely needed, and proposes that tic disorders may completely remit much less often than is generally believed.",
"keywords": [
"Provisional Tic Disorder",
"Tourette syndrome",
"tic remission",
"tics"
],
"content": "Introduction\n\nMost parents want predictions of the future for their child. This, however, is one of the more challenging aspects of caring for the child with [tics]1.\n\nPediatricians, child neurologists and child psychiatrists commonly encounter children with recent-onset tics. Many experts conclude that Provisional Tic Disorder (PTD)—tics in someone whose first tic was less than a year ago—is probably a different disease than chronic tic disorders including Gilles de la Tourette syndrome1–7. Others conclude that all tic disorders lie on a continuum, with no appropriate arbitrary duration boundary, and may share the same causes8–11. However, most experts agree that current PTD is usually mild and will likely go away in a few months1–5,12–16 (p. 171). Surprisingly, the sparse existing prospective data may not support this prognosis. This article reviews the current state of knowledge about PTD, focusing on clinical relevance.\n\n\nDefinitions\n\nTics are abnormal, unwanted movements or vocalizations. They are distinguished from other movement disorders by several characteristics: they are repeated, stereotyped, discrete and nonrhythmic, most frequently involve the head and upper body, and (although sometimes described as involuntary) are perceived by most patients as an inevitable capitulation to an almost irresistible urge17. Typical examples of tics include raising the eyebrows, turning the eyes, shaking the head, sniffing, snorting, and more complex phenomena such as repetitive touching or saying words or phrases18. Tics almost always begin in childhood, about ages 3 to 9 years19–21, and on average tics are most severe around ages 9 to 1122. Recent-onset tics caused by a systemic or other neurological illness are not considered further in this review, since most tic disorders are primary23.\n\nA brief digression into nosology is necessary to understand the primary literature. Differences between diagnostic criteria contribute to confusion about the patient with recent-onset tics, since various criteria sets differ on defining features, such as whether a minimum duration of ticcing is needed for diagnosis, or whether brief reappearance of tics after a remission of months to years confirm a single chronic disorder or constitute a second episode of transient tics. Similarly, several diagnostic schemata defined “transient tic disorder” (TTD), but construed the term “transient” in quite different senses. These points complicate interpretation of the literature, because many published reports used different rules than those they claimed to use. Appendix 1 discusses these points in more detail. The simplest definition in current use comes from DSM-5, which specifies that a child with primary tics that began less than a year ago is always diagnosed with Provisional Tic Disorder12,24. We will follow that nomenclature when referring generally to the child with recent-onset tics, but when reviewing the primary literature we attempt to specify the rules the various reports actually used for definition.\n\nThe common, idiopathic DSM-5 chronic tic disorders are Tourette’s Disorder (also called Tourette Syndrome) and Persistent (also called chronic) Motor (or Vocal) Tic Disorder. Hereinafter the terms Tourette Syndrome or Chronic Tic Disorders (TS/CTD) are used.\n\n\nSearch strategy and selection criteria\n\nReferences for this review were identified by searches of PubMed through February, 2016, and references from relevant articles and books. Search terms included “tic disorder”, “transient tic disorder”, “Tourette NOT Tourette [AU]”, and “tic disorder [MAJR] AND (transient [TW] OR persistent [TW])”. The final reference list was generated based on relevance to the topic of this review.\n\n\nEpidemiology of Provisional Tic Disorder\n\nTics are thought to be the most common movement disorder diagnosed in children25.\n\nEstimates of the prevalence of PTD span a wide range25–30. For example, at least one motor tic was observed in 47% of first graders over the course of one school year31, while a study using questionnaires and interviews reported a 5% lifetime prevalence of PTD (the authors reported 2.6% as DSM-IV TTD, plus 2.5% in a separate category for children with current tics that had begun < 12 months prior)32. Obviously at least one of these estimates must be wrong. Below we discuss the key issues in epidemiological studies of PTD before returning to a summary of the evidence.\n\nA number of factors complicate estimation of PTD prevalence, and some of these deserve special attention. A more complete list and additional references appear in Appendix 2.\n\nPoint prevalence vs. lifetime prevalence. Cross-sectional studies are much easier to conduct than longitudinal studies, but provide very different information. Nevertheless, all prevalence studies of chronic tic disorders are relevant to the lifetime prevalence of PTD, because all old tics were once new. In other words, all children with TS or CTD started ticcing at least a year ago, and in the first few months after tic onset would have met criteria for PTD. So the total number of children with a lifetime diagnosis of any tic disorder constitutes a lower bound for the lifetime prevalence of PTD.\n\nFurthermore, since by definition PTD has not lasted for a year, resampling even a short time later can substantially change the prevalence estimate. The most illustrative data come from Snider and colleagues31, who visited an elementary school eight times over the course of a single school year. A trained rater observed the classroom for 1 hour on each visit, attending to each child individually for at least 3 minutes. A motor tic was observed at some point during the year in 47% of first graders [Table 1 in ref. 31]. However, the children in first grade in one year will be in second or third grade in subsequent years, and observers saw tics in children in all grades. One can calculate from their data that by sixth grade, at least 70% of students must have met the DSM-5 criteria for PTD at some point (for details, see Appendix 3).\n\nPopulation. Prevalence of tic disorders depends heavily on the age of the population studied. A prospective, community-based study found that “the percentage of children with tic behaviors varied with age: preschool children (22.3%), elementary school children (7.8%), and adolescents (3.4%)”33. Similarly, the 1-year period prevalence of tics with impairment or distress was 9% in children age 7–9, 6% age 10–12, and 5% age 13–1534. In another grade school study, the prevalence of directly observed motor tics peaked in first grade (~age 6)31. By contrast, a large study identified TS in only 12 of 28,037 teenagers screened at age 16–1735.\n\nTics are much more common in children with intellectual disability compared to healthy children without developmental delay, and in special education classrooms than in regular classrooms33,36–39. In Khalifa and von Knorring’s study, for instance, the 1-year prevalence of any DSM-IV tic disorder was 6.3% in children in regular classrooms but 46.3% in special school settings34. Tics are also common in children with an autism spectrum diagnosis40. Consequently, studies will underestimate prevalence if they do not take care to include children outside mainstream classrooms.\n\nSampling method\n\nGenerally speaking, few patients with tics seek medical advice, since tics are thought to remit spontaneously41.\n\nThe classroom setting is a special case; more generally, any convenience sample is likely not to fairly represent the entire population. Specifically, children evaluated in any health care setting are more likely to have experienced severe tics and to have symptoms other than tics42. In studies that use a staged approach to sample a population, an important concern is the false negative rate of the screening procedure. If, for example, 5% of the original population screen positive, then even if the true negative rate of the screening procedure is 90%, the study will underestimate the true prevalence by about two thirds. In perhaps the most telling example, eight screen-negative children—no tics reported by parent, teacher or self, and no tics observed by an expert visiting the classroom—came in for a 20-minute interview, and tics were observed in three of the eight42a.\n\nSources of information. Several studies show that direct examination of children identifies tics that children, parents and teachers were all unaware of. This result is apparently due to true differences between sources rather than poor within-source reliability: even though “rates of motor tic frequency were found to be moderately stable across both days and school settings,” clinician ratings of tics correlated only moderately with tics observed by researchers or by teachers43. Historical information is also crucial, because tics can be absent during an examination due to spontaneous fluctuations in severity, tic suppression, or effective treatment. In general, studies that employ a more comprehensive approach to identifying cases find a higher prevalence of tics25,44–46.\n\nPrevalence: conclusion. In summary, many factors complicate accurate estimation of tic prevalence, and most of these lead to underestimation (Appendix 2). At a given moment in time, the fraction of children with either chronic or recent-onset tics constitutes a lower bound on the lifetime prevalence of PTD. Point prevalence depends strongly on age, with the highest rate probably about 20% at age 5–10. Lifetime prevalence is much higher; though longitudinal studies have been sparse, the available evidence supports the view that tics occur at some time or another in a large fraction of all children, probably over half. In most cases these tics never come to medical attention, and those that do are disproportionately more severe. Tics are even more common in children with attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD) or intellectual disability.\n\nIt is almost impossible to conduct a prospective study of the onset of tics, as the majority of patients do not seek help for the tics but rather for other problems47.\n\nIncidence means the rate of new (first-episode) cases in a given period of time. Some of the prevalence studies cited above provide limited information on incidence. Spencer and colleagues48 provide some of the most direct data, prospectively observing boys for 4 years. The rate of new-onset tic disorders over the 4-year follow-up period was 3% in boys without ADHD.\n\nSpencer et al. also provide incidence data in boys with ADHD, many of whom had tics at baseline (17%, vs. 4% in boys without ADHD). Boys with ADHD were more likely than those without ADHD to develop new tic disorders over the 4-year follow-up period (20%, including 33% in the 6- to 8-year-old group). Law and Schachar49 performed a large, 1-year-long randomized controlled trial of methylphenidate for ADHD, and monitored carefully for tics. Children who met the criteria for TS at baseline were excluded from participation, but (other) tics were common at baseline (30%). During the year of follow-up, “clinically significant tics for the first time (i.e., moderate or worse)” occurred in 19.0% (12/63) of the children who had no tics at baseline. The relevant part of this study for this section is the high rate of new tic disorder in the placebo group: one sixth (16.7%, 2/12) of children with ADHD but no tics at baseline developed PTD of at least moderate severity in one year (see also Table 2 in ref. 49).\n\nCarter and colleagues50 prospectively followed first-degree relatives of TS probands for 2 to 4 years. Nine of 21 children free of tics initially but at least 4 years old at final assessment had developed tics: five were diagnosed with TS, two with chronic motor or vocal tic disorder, and two with DSM-III-R TTD (one of whom developed tics just before the last assessment). In other words, at least one third of children in this high-risk sample developed a chronic tic disorder over an average of only 3 years. In a similar study, nine of 29 children of a parent with TS had a tic disorder at baseline, and 10 more developed a new tic disorder over the next 2–5 years51.\n\n\nClinical features of Provisional Tic Disorder\n\nGiven its prevalence, the knowledge base on PTD is surprisingly limited and scattered9,47. Some authors report that PTD that remits within the first year has a similar initial presentation as do chronic tic disorders2,52,53. Certainly any clinical feature of TS can present first chronologically (when the diagnosis is still PTD). However, some features of TS are less typical in PTD: not all children with PTD progress to TS, and some features of TS are more common in older children. Many of the conclusions below should be taken as tentative, since cross-sectional studies not focused on recent tics supply most of the data.\n\nBoys are more likely to have PTD than girls, with reported sex ratios of 1.2–4.031,41,54–56. The sex ratio in TS is generally reported as closer to 4. In this regard it may be relevant that children with tics spanning at least 3 months had a significantly higher ratio of boys to girls (7.5:1) than did the children with tics observed in only 1 month or 2 consecutive months (1.6:1)31; perhaps tics persist more often in boys.\n\nIn a large epidemiological study, children with DSM-IV TTD had a later age of onset than children with TS/CTD47. This finding is plausible, but a longitudinal study is required since chronicity is probably easier to recall in children with more severe or less socially acceptable tics34.\n\nChildren with DSM-IV TTD had lower severity and a lower rate of vocal tics than children with TS or CTD47. Similarly, in a school observation study, children with tics spanning at least 3 months had a significantly higher mean tic severity than children with tics observed in only 1 month or 2 consecutive months31. In a report on over 300 children with ADHD, tic disorders (chronic and recent-onset together) were two to three times as common in combined type ADHD than in hyperactive-impulsive or inattentive ADHD57. Case-control and family studies of OCD find an excess of tic disorders in OCD relatives, and suggest that tics are more common and more severe in relatives of boys with OCD beginning earlier in childhood58,59.\n\nTreatment response in PTD has not been carefully studied, in part because treatment is often unnecessary. Clinical experience suggests that symptoms in PTD respond to treatment at least as well as in TS/CTD.\n\n\nEtiology\n\nIn 1987, Zausmer and Dewey opined that “Further research is needed to confirm that there is a connection between childhood tics and Gilles de la Tourette's syndrome, to establish that the predisposition to tics is familial, and, if so, whether there is a complex genetic mechanism involved, or some other environmental ætiology so far undisclosed”60. However, the following year Kurlan et al. reported on two individuals with remitted PTD in TS families whom they concluded were “very likely obligate carriers of the TS gene”61, and in fact most family studies of probands with TS find relatives with other tic disorders including PTD. Of 16 monozygotic twin probands with TS, 56% of co-twins also had TS, but 94% of co-twins had some tic disorder, suggesting strongly that TS and other tic disorders share a genetic predisposition62. High rates of tic disorders including PTD in probands and family members of patients with ADHD and OCD have suggested that these clinical features may be “alternative manifestations of the same underlying illness”7,51,59,63.\n\nIn the monozygotic twin study of TS cited in the previous paragraph, the lower birth-weight twin had more severe tics in 12 of 13 pairs, and “the magnitude of the intrapair birth-weight difference … strongly predicted the magnitude of the intrapair tic score difference”62. These results suggest that environmental factors in utero may predict severity and outcome of tic disorders. Maternal smoking or other drug use during pregnancy may also be risk factors for TS64–67 and thus perhaps also for PTD. Although external contingencies do transiently modify ticcing in PTD68, life events seem to have little to do with the onset of TS/CTD69. Life events have not been evaluated systematically in PTD.\n\n\nOutcome of PTD\n\nStudies of prognosis are infrequent and difficult to conduct, and the conclusions are severely limited by diverse methodological shortcomings [16, p. 188].\n\nOne of the most important questions about PTD remains that of prognosis. Since prospective studies of PTD are so few, we examine cross-sectional and retrospective studies as well.\n\nChild epidemiological studies not focused primarily on tic disorders often identify too few cases to be useful for this context70,71.\n\nAge and sex. Subjects with DSM-IV TTD later recalled their age of onset as 8.5 ± 3.0 years, vs. 4.6 ± 2.9 for TS, though onset for chronic motor or vocal tics also averaged 7–8 years, and a prospective study would be needed to rule out recall bias47. In Snider et al.’s grade school observational study, the boy:girl ratio was higher in “the persistent group,” i.e. tics observed on at least three consecutive monthly visits or two nonconsecutive visits (7.5:1), than in the isolated group, i.e. tics observed only on one visit or two consecutive visits (1.6:1)31.\n\nTics and other symptoms. In the Snider et al. “persistent group,” non-facial tics were twice as common as in the isolated group, and problem behaviors were also more associated with tics in the persistent group31. In a large epidemiological study, TTD subjects had lower tic severity than children with TS/CTD, and were less likely to have vocal tics47. In the same study, people with vocal tics (at least chronic vocal tics) had higher rates of comorbidity (58% vs. 12%), including ADHD (33% vs. 12%) and OCD (8% vs. 0%).\n\nDuration at initial presentation. Editions of the Diagnostic and Statistical Manual previous to DSM-5 had required a 4-week threshold for diagnosing TTD, but a recent expert consensus statement noted no basis for this threshold in data, concluding that “it is unknown whether tics of less than one month’s duration predicts a transient course or not”24. In the Snider et al. “persistent group,” tics were significantly more severe than in the isolated group (mean 1.08, t = 2.7; P < .01)”31.\n\nRemschmidt and Remschmidt located 54 families of children who had been seen for tic disorders72. After an average of 3 years, 11 (38%) of the 29 untreated children had completely remitted according to the family. Abe and Oda73 obtained questionnaire data from the parents of 32 of 57 children of a parent with tics, and 94 of 178 control children, chosen from children seen at a well-child clinic when they were 3. Of the children in the former, high-risk group, 25% were reported to have tics at age 8, compared to 10% of the control children. Stárková reported the duration of clinical treatment in 131 tic patients hospitalized in a Czech child psychiatry department over a 20-year period74. Duration of tics at onset is not provided, so many of these patients may have had TS/CTD at initial presentation, but 38% of the 63 patients aged 15–29 years at last follow-up had completely remitted.\n\nAge and sex. At a one-day clinic in New York in 1977, members of 21 families with a GTS proband were examined. Many family members had current or past tics, and “among those with spontaneous clearing, females predominated”75.\n\nTics and other symptoms. Wang and Kuo concluded that: “Cases in 4–6 years old children with multiple motor and vocal tics have poor prognosis”76. Consistent with that opinion, six of 11 spontaneously remitting tic disorders in another study had only a winking tic at presentation, and only one had a vocal tic72. By contrast, Chouinard and Ford concluded that “the appearance of the tic disorder, the course and prognosis, the family history of tic disorder, and the prevalence of OCD were found to be similar” in nine adult patients in whom a previous history of transient tics in childhood was eventually elicited, whereas a specific cause for the tic disorder (infection, trauma, cocaine use, or neuroleptic exposure) was more often found in 13 adult patients who apparently were truly presenting de novo53. In a large study of adults, “a significantly greater proportion of adults with ADHD (12%) than those without ADHD (4%) had tic disorders. Tic disorders followed a mostly remitting course and had little impact on functional capacities”77.\n\nRemission at presentation. In the epidemiological study of Wang and Kuo, all subjects diagnosed with TTD in childhood had remained in remission76. However, this conclusion, like so many discussed in the preceding sections, may depend on the thoroughness of the assessment. “Detailed questioning disclosed a history of previous childhood transient tic disorder” in nine of 22 patients presenting for medical care of a tic disorder for the first time after the age of 2153. Similarly, children with tic disorders that had remitted before age 20 often experienced a recurrence later in life78. Still, the remission rate for PTD is likely more favorable than that of TS; tics persisted into adulthood in 90%79 or 100%80 of patients with childhood-onset TS.\n\nStatistics on the rate of permanent spontaneous remission are difficult to obtain since these patients, characteristically, do not return for follow-up contacts81.\n\nThe ideal design to address prognosis of PTD is a prospective study, lasting at least through the 1-year anniversary of the first tic. Unfortunately, few such studies are available. Shin and colleagues followed eight children (seven boys) with DSM-III or DSM-III-R TTD82 identified by hospital records. Their age at symptom onset was 8.38 ± 3.60 years (mean ± SD), and symptom duration at presentation was 0.38 ± 0.37 years. At follow-up 3 to 18 years later, using a semi-structured interview by telephone or face to face, four had recovered completely and four had not improved at all. By comparison, of the 22 children in the same study who were initially diagnosed with TS or CTD, seven had remitted by follow-up, 11 had improved somewhat, and four had not improved.\n\nBruun and Budman reported follow-up by telephone (62%) or direct interview (38%) on 58 children who had tics lasting less than a year at presentation (DSM-III and ICD9 TTD)9. After 2–14 years, tics had remained absent throughout the follow-up period in only 17%; 40% now met criteria for chronic motor or vocal tics and the remaining 43% “continued to have tics that were chronic and episodic (either TS or tic disorder ‘not otherwise specified’ by DSM-IV criteria)”9.\n\nPeterson et al.83 followed for up to 15 years a large sample of children with chronic or recent-onset tics, diagnosed initially by parental report only. The follow-ups used direct examination for diagnosis. The number of children with motor tics declined substantially over time (Time 1, 17.7%; Time 2, 2.2%; Time 3, 2.1%; Time 4, 0.6%), but as only Times 2 and 3 used identical ascertainment methods, generalization about remission of PTD is difficult. From 43% to 84% of 32 children with a tic at presentation to an ophthalmology practice still had tics after an average follow-up of 6.1 ± 3.9 years84 (diagnosis at presentation was not reported, but many of these children probably had PTD). A few other studies report limited prospective data52,85,86.\n\nAge and sex. Corbett et al.56 found prospective follow-up data after a mean of 5.4 years on 73 of 89 children who had first seen the doctor specifically because of tics. These 89 were part of a larger sample of 180 children with tics. Of the 122 subjects with adequate information recorded about the date of tic onset, at least 44 had experienced tics for more than a year at the initial assessment. Thus many of the 73 children with prospective follow-up data probably had PTD at the baseline visit, but many already had chronic tics. With this caveat, one interesting point is that outcome depended on age of onset; remission was more likely (16 of 26, 62%) in children whose tics had started at age 6–8 years than in children whose tics began at age 2–5 (7 of 29, 24%) or at age 9–15 (6 of 17, 35%; p<.02; Table VIII in 56). In the same study, full remission was significantly more likely the longer the follow-up, so that only 32% of those followed for 2 years or less were tic-free, vs. 65% of those followed for at least 8 years. In other words, many children who do remit completely will do so only after meeting criteria for TS or CTD.\n\nSpontaneous remission was more likely in girls than boys in one follow-up study of mixed tic disorders87, but a similar study found no relationship of remission to sex88. The latter study also suggested better prognosis for children whose parents had tics that remitted vs. persisted in adulthood.\n\nTics and other clinical features. In a clinical sample of 26 children initially diagnosed with TTD, coprolalia during the first year did not differentiate those later diagnosed with Tourette’s disorder from those still diagnosed with TTD at follow-up 1–11 years later [16, pp. 373–374]. In the same study, none of the three children who presented with a complex tic remitted, though the group difference was not significant. However, “children were more likely to develop Tourette's disorder if they had three or more vocal symptoms during the first year (8 [of] 17 children); all of the children with less than three vocal symptoms had a final diagnosis of TTD (p = 0.02)” [16, p. 374]. Bruun and Budman also reported significantly better prognosis in children who presented without vocal tics9.\n\nNone of the children who remained in remission had a tic below the neck at their first visit, compared with at least 19% of those later diagnosed with TS [16, pp. 373–374]. In fact, all four children who had a lower extremity tic at any point in the first year were diagnosed with TS at follow-up. Neither of these results was statistically significant, but the mixed tic disorder follow-up of Corbett et al. similarly found a trend (p<0.10) for fewer remissions in patients with a lower extremity tic at presentation56.\n\nIn the prospective study by Peterson et al., ADHD at baseline was associated with later tic persistence89. Spencer et al. prospectively monitored the appearance and disappearance of tic disorders over the course of 4 years in boys with or without ADHD who did not have TS at study entry48. Almost all (~90%) of the boys with tics had a chronic tic disorder, so the data are only partially relevant. Still, over the course of 4 years, the age-adjusted rate of remission was 65% for tic disorders (vs. 20% for ADHD).\n\nOne study located 54 children with OCD who had enrolled in OCD treatment studies for which Tourette’s disorder had been an exclusionary criterion, and re-examined them “2–7 years later with a neurological examination and a structured interview to establish the presence or absence of tics and Tourette's disorder”59. At baseline, 16 of the 54 children had a current tic disorder, and 15 other children had a past history of tics. Twelve of the 31 had a diagnosis of DSM-III-R TTD at baseline. At follow-up, 17 of the 31 had current tics, three others had a past diagnosis of TS/CTD, and for 12 the only lifetime tic diagnosis was TTD. One additional person with no tics at baseline had developed a tic disorder (Tourette’s). Thus in this study of childhood OCD, most children had current (30%) or past (28%) tics at baseline, though none were thought to have TS. At follow-up, 31% had a current, chronic tic disorder, but those with a previous diagnosis of TTD had remained remitted. The study was focused on tics only at follow-up, but bearing that caveat in mind, the results suggest the possibility that OCD at baseline may protect children whose tics have already disappeared from tic recurrence over the next few years.\n\nUnpublished data suggest that among children with tics for less than 6 months at study entry, those who could suppress tics better when asked to do so had more improvement in tic severity at the 12-month anniversary of tic onset90.\n\nA few indisputable facts are evident from the existing data on outcome of PTD. Some children who start ticcing will go on to have chronic tics, often associated with impaired quality of life. (Still, prognosis even for TS is primarily hopeful: in a group of children with TS, 11.4 ± 1.6 years old, one third had a YGTSS score of 0 when followed up a mean of 7.5 years later; i.e., no evidence of tics over the past week.) At the other extreme, tics will remit completely in many children with recent-onset tics—or, more likely, will cease to be noticed or to affect quality of life.\n\nHowever, the existing data provide little certainty about outcome even collectively, much less for individuals. The best-quality information we have comes from the few studies limited to patients identified during the first year of ticcing that either followed the patients prospectively or achieved good follow-up rates retrospectively (see Table 1). Overall, these studies suggest that a child with tics who had no tics prior to 1 year ago has a favorable prognosis overall, but has only about a one in three chance of remaining completely tic-free over the next 5–10 years. Many of those who do remit probably remit only after meeting criteria for TS/CTD at some point.\n\n\nDiscussion\n\nOverall, the existing data on PTD are relatively limited. Some of the reasons for this state of affairs are inherent in the problem, and others can be attributed to changing knowledge about tic disorders, diagnostic criteria that have changed several times over the past few decades, and an understandable preference for research to focus on patients with severe and persistent symptoms. Nearly every section above included important unanswered questions, but some of the most important include the following. Do most children, or only a minority, experience tics at some time during childhood? Are the causes of tic disappearance different from the causes of tic appearance? Why do tics usually go away—or at least cease to be a clinical problem? And not least, the question we started with: Will my child’s tics go away, or get worse?\n\nThe conclusion that complete and permanent remission of recent-onset tics may be relatively uncommon is consistent with a number of observations. First, some studies provide direct support for intermittent tics31,46,91. In discussing the DSM-IV-TR criteria, Singer wrote: “Since children are permitted to have recurrent episodes of ‘transient tics’ and recognizing that tics may go unnoticed, this author would suggest that some individuals in this category actually have a CTD”92. Second, the more comprehensive the assessment strategy, the higher are the rates of tics observed in epidemiological studies. To give one example, in a random population sample with very thorough clinical ascertainment, tics were observed in one sixth of children in mainstream schools38 (see also Appendix 2). Cubo provides even more direct evidence for this effect [Table 2 in ref. 25]. Therefore, apparent remission of tics is likely to be much more common than complete remission. Third, many adults with tics are unaware of their tics9,79,80, a fact acknowledged explicitly by the working group for DSM-5 as a reason for changing the diagnostic criteria so that any tics more than a year apart could be diagnosed as a chronic tic disorder.\n\nBruun and Budman suggest that a fluctuating course commonly follows TS: “It is the impression of these authors, rather [than complete, lifelong remission] that the more common course is one of occasional recurrences of mild tics throughout adult life”9. Shapiro et al. provide prospective data on this point: “27.1% of our [TS] patients had one or more periods of spontaneous remission lasting from less than 1 month to 19 years” [16, p. 188]. Similarly, 62% of tic patients hospitalized as children, when followed up between the ages of 15 and 29, reported only occasional short-term tic relapses lasting several days and requiring no treatment; only 14% were considered to have a poor outcome74. In discussing prognosis of TS/CTD, Singer concluded that “whether tics actually disappear completely is unclear, and results appear to be dependent on the methods used to document the presence of tics.”93. The data reviewed above suggest that the same conclusion may apply to tics that began only recently.\n\nThe conclusion that the most common outcome of PTD is improvement without remission is true only if by remission one means zero tics ever again, consistent with DSM-5. However, this threshold brings with it some uncomfortable conclusions. Consider a patient who first developed winking and sniffing tics 13 months ago. He and his mother report that his tics have been gone for the past 6 months, and he shows no tics during a 45-minute office visit, but some of his old tics are observed when he sits alone for a few minutes. His DSM-5 diagnosis is Tourette syndrome even though for all practical clinical purposes he has remitted. This child is a substantial departure from the iconic (if unrepresentative) Marquess of Dampierre94. Martino and colleagues address this problem using an idiosyncratic but understandable nomenclature, diagnosing “physiological tics” if the severity does not warrant diagnosing a “disorder.” They conclude that “‘physiological tics’ commonly occur during normal childhood development and reflect a stage of the physiological synaptogenesis within connections between basal ganglia and frontal lobes” [15 (pp. 105–107)].\n\nA different solution is to reconsider the DSM-IV-TR choice to remove the “impairment or marked distress” criterion. The experience of Coffey and colleagues supports this view: “Although tics followed a persistent course in the majority of youth with TD [Tourette’s Disorder], they were infrequently associated with impairment. There was a significant reduction in the proportion of youth with TD impairment from baseline to follow-up. These results support the view that TD is a persistent disorder, but suggest a dissociation between tic persistence and tic-associated dysfunction”95. However, for both biological and societal reasons, psychosocial consequences of illness, like “distress or impairment,” seem unsatisfactory in defining a highly heritable syndrome. Objective measures focused only on tic severity would sidestep these concerns, but valid, objective tic severity measures encompassing a period longer than a single office visit have been difficult to implement. In either case—whether one prefers to measure tics’ severity or their impact—a zero threshold inevitably produces the nosological frustration discussed in the previous paragraph.\n\nPrognosis\n\nWe do not know the cause of or have the ability to predict spontaneous waxing, waning, fluctuation, and temporary or permanent remission of symptoms [16, p. 175].\n\nResearch to clarify the expected course of PTD would be greatly appreciated by the children and families who seek consultation for recent-onset tics. Firmer group estimates of improvement and remission rates from prospective studies would be welcome, but even more useful would be identification of additional features at presentation that help predict outcome on an individual level.\n\nTreatment\n\nTransient tic disorder “is a self-limiting disorder, and active treatment typically is not indicated.” However, given limited follow-up data, “a child with a diagnosis of TTD should be periodically monitored and the diagnosis and treatment revised as necessary.”2\n\nAt the present time, experts generally agree that treatment for PTD is warranted only when symptoms are severe and persistent enough to substantially distress the child or interfere with his or her school experience or social development. However, better prognostic ability would allow the possibility of early intervention to improve the long-term outcome.\n\nPrevention\n\nIf we can … detect the brain changes years before the behavior starts, then there’s the opportunity to intervene early. And that’s where we do best in medicine. Early intervention, preempting the later stages, is where we’ve had our greatest successes. … At that point, we’ll start to see … the really big public health impact.96\n\nAn ounce of prevention is worth a pound of cure. (Benjamin Franklin)\n\nSince Tourette syndrome and persistent (chronic) motor/vocal tic disorder (TS/CTD) are defined as having lasted at least a year from onset to most recent symptoms, one can envision that an effective intervention, supplied within months of the initial onset of tics, could conceivably prevent TS/CTD. No such intervention has been proven, but it is now clear that a behavior therapy approach (Comprehensive Behavioral Interventions for Tics, or CBIT) is reasonably effective and definitely safe for TS/CTD. If CBIT can be shown to improve the outcome of recent-onset tic disorders, it can become an approach to primary prevention of TS/CTD (secondary prevention of tic disorders). At present, factors such as cost and limited availability mean that treating all children with recent-onset tics is impractical, not to mention unnecessarily intrusive for the majority of children whose tics will disappear (or become mild or rare). However, those limitations could be overcome with better prognostic accuracy.\n\nTics that go away can tell us something important about tics that don’t\n\nFrancis Bacon … pronounced that it must be of the greatest interest for the physician to study healed cases of incurable diseases97.\n\nAs reviewed above, very little is known about predicting outcome from studies of PTD itself. However, more follow-up data are available after tics have become chronic22,79,80,95,98–106. These follow-up studies of chronic tic disorders suggest hypotheses that can be tested in prospective follow-up studies of PTD. Leckman107 lists the following potential prognostic features for TS: visual-motor integration108, decreased TMS motor inhibition,109,110, MRI volumetry89, and white matter integrity111. Singer92 adds: “Proposed predictors of severity and longevity include tic severity, fine motor control, … size of caudate and subgenual volumes99,100, but all are controversial22,93.” Here, “fine motor control” may refer to Purdue Pegboard performance112. Additional potential markers for outcome of PTD include baseline ability to suppress tics68,113, resting state functional connectivity114, probabilistic learning115, ADHD at diagnosis116, vocal tics9 or tics below the neck at presentation, or more than two vocal tics in the first year [16, pp. 373–374], socioeconomic status (ref.16, p. 175) and family history of TS/CTD, perhaps especially family history of tics persisting into adulthood88 or tics in both parents51.\n\nA careful, prospective study that includes some of the most promising of these potential markers may allow discovery of the cause and pathophysiology of tic improvement, with the potential consequences for clinical care noted in the preceding section. This hope provides one of the key motivations for attempting to identify clinical, neuropsychological, or brain imaging variables that correspond to improvement vs. worsening of recent-onset tic disorders. As we tell parents who enroll their children in our ongoing study of recent-onset tics, “We’d love to find out what happens in the brains of kids whose tics improve spontaneously, and put it in a bottle or find out how to teach it to patients with chronic tics.”",
"appendix": "Author contributions\n\n\n\nKJB conceived the study and wrote the first draft. KJB and ERB found and tabulated data from primary sources. DJG gave feedback on early drafts. All authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nResearch reported in this publication was supported by the Eunice Kennedy Shriver National Institute Of Child Health & Human Development of the National Institutes of Health (NIH) under Award Number U54 HD087011 to the Intellectual and Developmental Disabilities Research Center at Washington University, by NIH grants K24 MH087913, R21 NS091635, K01 MH104592, K12 NS001690, by the McDonnell Center for Systems Neuroscience at Washington University, by a NARSAD Young Investigator Award to DJG from the Brain & Behavior Research Foundation, and by the Tourette Association of America. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or any of the other funders.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe thank the children and parents who have participated in the NewTics study (www.NewTics.info).\n\n\nAppendices\n\nThe literature is complicated by substantial confusion about the meaning of the phrase “transient tic disorder” (the nomenclature used most often in the existing literature). The word “transient” is taken to mean two different things. The Tourette Syndrome Study Group (TSSG) criteria117 represent a usage in which “transient” means something that was present but has disappeared. The TSSG criteria for Transient Tic Disorder (TTD) require that tics began over a year ago, but lasted no more than 12 consecutive months; i.e., the tics are now gone. Using the TSSG criteria, patients who are ticcing but whose tics started less than a year ago have “diagnosis deferred.” The ICD-10 criteria similarly require that “tics do not persist for longer than 12 months,” so that in the first year since onset one diagnoses “tic disorder, unspecified”118.\n\nContrary to a common assumption24,27,119,120, DSM-IV-TR specified a different meaning of “transient”121. The DSM-IV-TR criteria for TTD do not require disappearance of the tics, and the accompanying text clearly specifies: “Often, the diagnosis may change over time during the natural history of a Tic Disorder. For example, during the first months, a child may be diagnosed as having a Transient Tic Disorder. After a year, with further tics and longer duration, the diagnosis may become Tourette’s Disorder”121. This usage—tics are transient until they prove themselves to be chronic—seems natural in the context of other DSM-IV-TR diagnoses such as Major Depressive Disorder that are based on current data but may need to be revised (e.g., if the patient later develops a manic episode, in which case the preceding depression is revealed to have been part of bipolar disorder, or if Alzheimer’s disease is diagnosed in life but autopsy reveals a different dementing illness). To deal with the patients left undiagnosed by this misunderstanding, some epidemiology studies claimed to use DSM-IV-TR criteria, but used “provisional” or “not otherwise specified” to describe patients with tics for less than a year, even though these patients in fact met DSM-IV-TR criteria for TTD.\n\nDue to widespread dissatisfaction with the term Transient Tic Disorder, DSM-5 adopted the term “provisional tic disorder” (PTD)12,24. This diagnosis differs from DSM-IV-TR TTD not only in name and in the clarification that the diagnosis is intended for all children whose tics began less than a year ago, but also in two other substantive ways. First, PTD can be diagnosed within the first 4 weeks after tic onset. Second, and more consequentially, DSM-5 requires that any tic present more than 1 year after the first tic be diagnosed as TS or CTD (assuming the tics are not secondary to another illness or to a known toxin), disallowing the diagnosis of PTD for someone with current tics who had tics more than a year ago, regardless of any intervening asymptomatic period.\n\nThe interested reader is also referred to insightful discussions of this topic by Cubo25 and by Robertson and colleagues26.\n\nExcluding the relatively rare tic caused by drugs or a systemic illness, any child with a definite tic on even one examination can be diagnosed with DSM-5 PTD. If the tics continue beyond the 1-year anniversary of the first tic, the child still had PTD for the first year12.\n\nIn one careful study, the highest cross-sectional prevalence of motor tics at any one observation was 9.6%, but since a number of children were seen to tic on one visit to the school but not another, 47% of first graders were observed to have a motor tic at some point during the year [Table 1 in ref. 31]. Admittedly, this rate may include some false positives, for instance nose wrinkling or sniffing that could better be explained by allergic rhinitis, since observers did not talk with the children or their parents. On the other hand, false negatives must also have occurred, as observers did not identify tics in several children with a clinical diagnosis of motor tics, and did not record vocal tics at all. A pediatric neurologist had trained the raters and performed reliability testing, and motor tics were counted only if they occurred three or more times in the same visit.\n\nThe relevant point for the present discussion comes from the fact that tics were observed in classrooms ranging from kindergarten to sixth grade, and collectively the results lead to an interesting conclusion about lifetime prevalence. For instance, 21% of third graders were also observed to tic. If the year the study was done was typical, then about 47% of the current third grade class would have shown tics if observed two years earlier, when they were in first grade. Even assuming a high true rate of chronic tic disorders (say, 8%), tics must have been new in at least 13% (= 21% − 8%) of the third graders in addition to the 47% who had tics in first grade. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nAltman G, Staley JD, Wener P: Children with Tourette disorder: a follow-up study in adulthood. J Nerv Ment Dis. 2009; 197(5): 305–310. PubMed Abstract | Publisher Full Text\n\nBruun RD, Shapiro AK, Shapiro E, et al.: A follow-up of 78 patients with Gilles de la Tourette's syndrome. Am J Psychiatry. 1976; 133(8): 944–947. PubMed Abstract | Publisher Full Text\n\nBruun RD, Shapiro AK, Shapiro E: A followup of eighty patients with Tourette's syndrome. Psychopharmacol Bull. 1976; 12(2): 15–17. PubMed Abstract\n\nByler DL, Chan L, Lehman E, et al.: Tourette Syndrome: a general pediatrician's 35-year experience at a single center with follow-up in adulthood. Clin Pediatr (Phila). 2015; 54(2): 138–144. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLeckman JF: Phenomenology of tics and natural history of tic disorders. Brain Dev. 2003; 25(Suppl 1): S24–S28. PubMed Abstract | Publisher Full Text\n\nSchultz RT, Carter AS, Gladstone M, et al.: Visual-motor integration functioning in children with Tourette syndrome. Neuropsychology. 1998; 12(1): 134–145. PubMed Abstract | Publisher Full Text\n\nZiemann U, Paulus W, Rothenberger A: Decreased motor inhibition in Tourette's disorder: evidence from transcranial magnetic stimulation. Am J Psychiatry. 1997; 154(9): 1277–1284. PubMed Abstract | Publisher Full Text\n\nMoll GH, Wischer S, Heinrich H, et al.: Deficient motor control in children with tic disorder: evidence from transcranial magnetic stimulation. Neurosci Lett. 1999; 272(1): 37–40. PubMed Abstract | Publisher Full Text\n\nFredericksen KA, Cutting LE, Kates WR, et al.: Disproportionate increases of white matter in right frontal lobe in Tourette syndrome. Neurology. 2002; 58(1): 85–89. PubMed Abstract | Publisher Full Text\n\nBloch MH, Sukhodolsky DG, Leckman JF, et al.: Fine-motor skill deficits in childhood predict adulthood tic severity and global psychosocial functioning in Tourette's syndrome. J Child Psychol Psychiatry. 2006; 47(6): 551–559. PubMed Abstract | Publisher Full Text\n\nWoods DW, Himle MB: Creating tic suppression: comparing the effects of verbal instruction to differential reinforcement. J Appl Behav Anal. 2004; 37(3): 417–420. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGreene DJ, Church JA, Dosenbach NU, et al.: Multivariate pattern classification of pediatric Tourette syndrome using functional connectivity MRI. Dev Sci. 2016. PubMed Abstract | Publisher Full Text\n\nMarsh R, Alexander GM, Packard MG, et al.: Habit learning in Tourette syndrome: a translational neuroscience approach to a developmental psychopathology. Arch Gen Psychiatry. 2004; 61(12): 1259–1268. PubMed Abstract | Publisher Full Text\n\nWoods DW, Himle MB, Miltenberger RG, et al.: Durability, negative impact, and neuropsychological predictors of tic suppression in children with chronic tic disorder. J Abnorm Child Psychol. 2008; 36(2): 237–45. PubMed Abstract | Publisher Full Text\n\nThe Tourette Syndrome Classification Study Group: Definitions and classification of tic disorders. Archives of Neurology. 1993; 50(10): 1013–1016. PubMed Abstract | Publisher Full Text\n\nWorld Health Organization: The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organization. 1992. Reference Source\n\nLeckman JF, Peterson BS, Pauls DL, et al.: Tic disorders. Psychiatr Clin North Am. 1997; 20(4): 839–861. PubMed Abstract\n\nSinger HS, Jankovic J, Mink JW, et al.: Movement Disorders in Childhood. Philadelphia, PA: Saunders Elsevier, 2010. Reference Source\n\nAmerican Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Text Revision. Washington, DC, American Psychiatric Association. 2000. Reference Source\n\nKraft JT, Dalsgaard S, Obel C, et al.: Prevalence and clinical correlates of tic disorders in a community sample of school-age children. Eur Child Adolesc Psychiatry. 2012; 21(1): 5–13. PubMed Abstract | Publisher Full Text\n\nPauls DL, Kruger SD, Leckman JF, et al.: The risk of Tourette's syndrome and chronic multiple tics among relatives of Tourette's syndrome patients obtained by direct interview. J Am Acad Child Psychiatry. 1984; 23(2): 134–137. PubMed Abstract | Publisher Full Text\n\nKadesjo B, Gillberg C: Tourette's disorder: epidemiology and comorbidity in primary school children. J Am Acad Child Adolesc Psychiatry. 2000; 39(5): 548–555. PubMed Abstract | Publisher Full Text\n\nWoods DW, Walther MR, Bauer CC, et al.: The development of stimulus control over tics: a potential explanation for contextually-based variability in the symptoms of Tourette syndrome. Behav Res Ther. 2009; 47(1): 41–47. PubMed Abstract | Publisher Full Text\n\nGoetz CG, Leurgans S, Chmura TA: Home alone: methods to maximize tic expression for objective videotape assessments in Gilles de la Tourette syndrome. Mov Disord. 2001; 16(4): 693–697. PubMed Abstract | Publisher Full Text\n\nRobertson MM, Banerjee S, Kurlan R, et al.: The Tourette Syndrome Diagnostic Confidence Index: development and clinical associations. Neurology. 1999; 53(9): 2108–2112. PubMed Abstract | Publisher Full Text\n\nMol Debes NM, Hjalgrim H, Skov L: Limited knowledge of Tourette syndrome causes delay in diagnosis. Neuropediatrics. 2008; 39(2): 101–105. PubMed Abstract | Publisher Full Text\n\nThe Tourette Syndrome Association: DSM-5 Diagnostic Criteria and Classification of Tourette’s Disorder [online]. 2015. http://tsa-usa.org/news/DSM-5.htm, Archived by WebCite® at, accessed 21 Oct 2015. Reference Source\n\nRoessner V, Hoekstra PJ, Rothenberger A: Tourette's disorder and other tic disorders in DSM-5: a comment. Eur Child Adolesc Psychiatry. 2011; 20(2): 71–74. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRobertson MM, Eapen V: Tourette's: syndrome, disorder or spectrum? Classificatory challenges and an appraisal of the DSM criteria. Asian J Psychiatr. 2014; 11: 106–113. PubMed Abstract | Publisher Full Text\n\nWoods DW, Thomsen PH: Tourette and tic disorders in ICD-11: standing at the diagnostic crossroads. Rev Bras Psiquiatr. 2014; 36(Suppl 1): 51–58. PubMed Abstract | Publisher Full Text\n\nFreeman RD: Diagnosis and management of Tourette syndrome: Practical aspects. Medscape Psychiatry & Mental Health eJournal. 1997; 2(4): 431108. Reference Source\n\nDebray-Ritzen P, Dubois H: [Simple tic disease in children. A report on 93 cases (author's transl)]. Rev Neurol (Paris). 1980; 136(1): 15–18. PubMed Abstract\n\nKurlan R, McDermott MP, Deeley C, et al.: Prevalence of tics in schoolchildren and association with placement in special education. Neurology. 2001; 57(8): 1383–1388. PubMed Abstract | Publisher Full Text\n\nGoodman WK, Price LH, Rasmussen SA, et al.: The Yale-Brown Obsessive Compulsive Scale. I. development, use, and reliability. Arch Gen Psychiatry. 1989; 46(11): 1006–1011. PubMed Abstract | Publisher Full Text\n\nGoodman WK, Price LH, Rasmussen SA, et al.: The Yale-Brown Obsessive Compulsive Scale. II. validity. Arch Gen Psychiatry. 1989; 46(11): 1012–1016. PubMed Abstract | Publisher Full Text\n\nLeckman JF, Riddle MA, Hardin MT, et al.: The Yale Global Tic Severity Scale: Initial testing of a clinician-rated scale of tic severity. J Am Acad Child Adolesc Psychiatry. 1989; 28(4): 566–573. PubMed Abstract | Publisher Full Text\n\nBlack KJ: Chewing, rocking, pacing, echoing: Differential diagnosis and importance of stereotyped movements [v1; not peer reviewed]. F1000Res. 2016; 5: 387(slides). Publisher Full Text\n\nMacfarlane JW, Allen L, Honzik MP: A Developmental Study of the Behavior Problems of Normal Children Between 21 Months and 14 Years. Berkeley, CA: University of California Press, 1954. Reference Source\n\nMerriam-Webster Incorporated. s.v. \"tic\". In: Merriam-Webster Online Dictionary: [Internet]. 2015. http://www.merriam-webster.com/dictionary/tic, Archived by WebCite® at, Accessed: 2016-04-12. Reference Source"
}
|
[
{
"id": "13477",
"date": "20 Apr 2016",
"name": "Andreas Hartmann",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors must be congratulated for this thoughtful and exhaustive review on a difficult topic. I hope that their ongoing initiative (www.NewTics.info) will provide answers to many of the questions raised in the manuscript. My comments are few and as follows :The definition of tics varies but a reasonable argument has been made that they are not « abnormal » movements of vocalisations but rather normal or physiologic but occuring in an inappropriate context and/or in an inappropriate fashion. As a net result, one can of course speak of abnormal motor or vocal manifestations but as a movement disorder neurologist, I think it is important to stress that the semiology of tics does not give us clear diagnostic clues , as opposed to dystonia of parkinsonina tremor, for instance. Also, it is worth mentioning that tics can be (temporarily) suppressed, which is not the case in the vast majority of movement disorders. Finally, like it or not, « stereotyped » has been removed from DSM-5. I sympathize with the idea that early intervention, especially using behavioral therapies such as CBIT, may alter disease course, maybe through cerebral plasticity. However, there are no data to support this at present, even in confirmed TS cases. Moreover, CBIT (as opposed to ERP) depends on sensing premonitory urges, which are rarely present before the age of 10, and most PTD cases are likely to fall into this category. Finally, I believe that for patients with PTD, motivation and thus adherence for these kind of treatments will be low, except for severe cases. Thus, the therapeutic angle appears slightly artificial to me. Rather, and this is the main question raised in the manuscript and by parents of children with PTD, is the issue of individual prognosis, and especially conversion of of PTD into TS. The problem, at least in France, is that tics are considered benign, and TS almost malignant. In other words, the terminology we use is paramount. My personal concern is not so much whether one or several tics will persist for more than a year but how damaging they are. This brings us to the talmudic discussion on the utility of DSM criteria and even more on what Tourette syndrome means or not (the authors point out quite rightly that in current clinical pratice, we are usually light years away from the Marquise de Dampierre). If I had a wish, I would get rid of the term « Tourette syndrome » and switch to tic spectrum disorder (or something like that), although I concede this may be a mushy term. However, I don’t expect to see this happen in my lifetime.",
"responses": [
{
"c_id": "1949",
"date": "03 May 2016",
"name": "Kevin J Black",
"role": "Author Response F1000Research Advisory Board Member",
"response": "We appreciate Prof. Hartmann's thoughtful comments."
}
]
},
{
"id": "13533",
"date": "28 Apr 2016",
"name": "Andrea Cavanna",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an interesting article on the nosographic category of provisional tic disorder. The authors provided a useful overview on the development of diagnostic categories for tic disorders which improve over time. The implications for clinical practice are particularly relevant.",
"responses": [
{
"c_id": "1950",
"date": "03 May 2016",
"name": "Kevin J Black",
"role": "Author Response F1000Research Advisory Board Member",
"response": "Thank you."
}
]
},
{
"id": "13530",
"date": "03 May 2016",
"name": "Jeremy S. Stern",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper is a cogent and very useful exploration of an under-considered topic by critical review which challenges certain established clinical assumptions. The difficulties of estimating the prevalence of PTD and the risk of a newly ascertained case of tics progressing to a chronic disorder are discussed in detail, based on the literature. The inevitable conclusion of a need for (expensive) further prospective study is reached, and is an aspiration shared around the world. The appendices are particularly helpful, explaining problems of terminology, ascertainment of tics and the expected lifetime prevalence of PTD in the case of various prevalences of the other tic disorders.I very much agree with my fellow reviewer (http://f1000research.com/articles/5-696/v1#referee-response-13477) that the clinical term \"Tourette\" may have outlived its usefulness, can be unhelpful to patients and clinicians and could be improved by now being subsumed into a concept of \"tic spectrum disorder\", notwithstanding our reverence for its birthplace or, more practically, the freshness of DSM V.",
"responses": [
{
"c_id": "1955",
"date": "04 May 2016",
"name": "Kevin J Black",
"role": "Author Response F1000Research Advisory Board Member",
"response": "Thank you for your thoughtful comments. I agree with you and Prof. Hartmann that the science supports unifying Tourette's disorder / Gilles de la Tourette syndrome and Chronic / Persistent Motor [or Phonic] Tic Disorder. \"Chronic tic disorder\" would be my vote for nomenclature. Family and follow-up studies provide the most important evidence for this viewpoint, but phenomenology is another important clue.1 Walkup et al provide a thoughtful dissent.2 I would argue that whether Provisional Tic Disorder differs meaningfully from the chronic tic disorders remains an important and inadequately studied question.1. Robins E, Guze SB: Establishment of diagnostic validity in psychiatric illness: Its application to schizophrenia. Am J Psychiatry 126(7):983-987, 1970. doi: 10.1176/ajp.126.7.9832. Walkup JT, Ferrão Y, Leckman JF, Stein DJ, Singer H: Tic disorders: some key issues for DSM-V. Depress Anxiety 27(6):600–610, 2010, at p. 603. doi: 10.1002/da.20711"
}
]
}
] | 1
|
https://f1000research.com/articles/5-696
|
https://f1000research.com/articles/5-695/v1
|
18 Apr 16
|
{
"type": "Review",
"title": "Recent advances in managing and understanding nephrolithiasis/nephrocalcinosis",
"authors": [
"Giovanni Gambaro",
"Alberto Trinchieri",
"Giovanni Gambaro"
],
"abstract": "Urinary stone disease is a very common disease whose prevalence is still increasing. Stone formation is frequently associated with other diseases of affluence such as hypertension, osteoporosis, cardiovascular disease, metabolic syndrome, and insulin resistance. The increasing concentration of lithogenic solutes along the different segments of the nephron involves supersaturation conditions leading to the formation, growth, and aggregation of crystals. Crystalline aggregates can grow free in the tubular lumen or coated on the wall of the renal tubule. Plugs of crystalline material have been highlighted in the tubular lumen in some patients, but crystalline growth starting from plaques of calcium phosphate within the renal papillae has been demonstrated in others. Urinary supersaturation is the result of a complex interaction between predisposing genetic features and environmental factors. Dietary intake is certainly the most important environmental risk factor. In particular, an insufficient intake of dietary calcium (<600 mg/day) can increase the intestinal absorption of oxalate and the risk of calcium oxalate stone formation. Other possible risk factors that have been identified include excessive intake of salt and proteins. The potential role of dietary acid load seems to play an important role in causing a state of subclinical chronic acidosis; therefore, the intake of vegetables is encouraged in stone-forming patients. Consumption of sugar-sweetened soda and punch is associated with a higher risk of stone formation, whereas consumption of coffee, tea, beer, wine, and orange juice is associated with a lower risk. A high fluid intake is widely recognized as the cornerstone of prevention of all forms of stones. The effectiveness of protein and salt restriction has been evaluated in some studies that still do not allow definitive conclusions to be made. Calcium stone formation can be prevented by the use of different drugs with different mechanisms of action (thiazide diuretics, allopurinol, and potassium citrate), but there is no ideal drug that is both risk free and well tolerated.",
"keywords": [
"nephrolithiasis",
"nephrocalcinosis",
"Urinary stone disease",
"renal stone",
"nephron"
],
"content": "Introduction\n\nUrinary stone disease is the formation or the presence of concretions in the urinary tract. Stones have different compositions (mainly calcium) and tend to recur, requiring iterative treatments. Urinary stone disease is very common, and its prevalence is still increasing. At least one in ten of the potential readers of this article has already experienced a stone episode or could experience it during their lives. This global epidemic of the disease is even more relevant because it is associated with the increasing prevalence of other non-communicable diseases as the result of the epochal changes in the lifestyle of the world's population.\n\nUrolithiasis is the result of a complex interaction between genetic and environmental factors, and current research is oriented in these two directions, which should enable us to study genetic aspects in combination with environmental exposures. Another unique aspect of this fascinating field of research is the convergence of interests of various specialists in a single subject. Researchers from different backgrounds (chemists, epidemiologists, dieticians, geneticists, pathologists, radiologists, nephrologists, and urologists) come together at the same conferences, they publish in the same magazines and write books together, and they form what we jokingly call \"the stone family\".\n\nThe most important aspects of this research are the epidemiology of the disease, the association with other diseases, the genetics behind the disease, the influence of diet and other environmental factors, and the different ways of preventing the disease.\n\n\nEpidemiology\n\nOver the past 20 years, the world epidemiology of urolithiasis has undergone major changes1–4 related to several factors, such as aging of the population and changes in the lifestyle of the female youth population (low intake of fruits and vegetables and higher consumption of simple sugars and foods with high protein and salt content)5 in Western countries and the westernization of dietary habits and lifestyle in developing countries. In the countries of northern Europe and America, the prevalence values reached a plateau in the late 1980s up to values of 15–20%. Subsequently, no further increases were recorded, although changes were observed in the distribution between males and females and the age of onset of the disease. The prevalence of the disease in women tends to rise and to equal that in men as a result of the more frequent onset of the disease among women aged <30 years. Calcium oxalate is still by far the most frequent composition of urinary calculi, but also uric acid calculi tend to increase as a result of aging of the population and increasing penetration of the metabolic syndrome. On the contrary, infection stones tend to be less frequent as a result of improving health in the population and better methods of treatment of kidney stones. In non-Western countries, particularly in North Africa, the Middle East, India, and China, the prevalence of urolithiasis is increasing with the change of lifestyle due to the improvement of socio-economic conditions and globalization. The warmer climate in the so-called \"stone belt\" contributes to the rapid increase in prevalence in these regions. Global warming could pose a global climate change that could further increase the prevalence of urolithiasis, even in areas with a more temperate climate.\n\n\nRelated diseases\n\nRenal stone formation is frequently associated with other diseases of affluence. Calcium stone formation characterized by alterations in the metabolic regulation of calcium and sodium is frequently associated with hypertension, osteoporosis, and cardiovascular disease, whereas uric acid stones (but to some extent calcium stones too) are often linked to the metabolic syndrome and insulin resistance. In a large cohort of >50,000 men, the risk of hypertension was increased in renal stone formers (odds ratio [OR] 1.31)6, and in another cohort of 90,000 women the risk of a new diagnosis of hypertension was higher in subjects with a history of nephrolithiasis (relative risk [RR] 1.36)7. The link between the two diseases has been identified in common alterations of calcium metabolism8. A history of renal stones was associated with lower bone mineral density in a cross-sectional study of 5995 men >65 years old9, and in another national cross-sectional study in the US, bone mineral density of the femoral neck was found to be lower in men with renal stone history after adjusting for age, body mass index, race, and other potential confounders10. In large cohorts of renal stone formers, the risk of myocardial infarction (+31-78%), angina (+61%), and carotid artery atherosclerosis (+60%) was increased, even after adjustment for other known risk factors11–14. Renal stone formers have increased arterial stiffness, higher arterial calcification score, and reduced bone density15,16, a complex of findings which has been observed in other conditions—hypertension, osteoporosis, and chronic kidney disease (CKD)—and which may suggest that the vessel wall acts as a buffer for the excessive quantity of calcium coming from high bone turnover. The increased arterial calcification and stiffness may explain the higher cardiovascular risk observed in stone formers. Renal stone formers are often overweight or obese. In three large prospective cohorts of nearly 250,000 individuals in the US, the RR for incident stone formation in subjects >100 kg was 1.44 in men, 1.89 in older women, and 1.92 in younger women17. In subjects with metabolic syndrome (impaired fasting glucose, elevated blood pressure, dyslipidemia, and central obesity), the prevalence of nephrolithiasis is high with an increased risk of stone formation in men (OR 2.1) and in women (OR 4.9)18. Idiopathic uric acid nephrolithiasis has been regarded as a renal manifestation of the metabolic syndrome because of the impaired renal production and transport of ammonia that could be related to insulin resistance19,20. Also, the risk of calcium stone formation increases with the number of features of the metabolic syndrome, although further studies are necessary to establish a clear relationship between calcium nephrolithiasis and metabolic syndrome/cardiovascular risk and to disclose the potential mechanisms21,22.\n\n\nPathogenesis\n\nThe formation of kidney stones has been explained by different pathophysiological mechanisms23. Urinary calculi originate from the formation of crystals in the urine, which is a complex solution of various solutes. When the urine becomes supersaturated due to a low urine volume or excessive excretion of solutes, crystalline formation begins. The crystals may grow gradually or aggregate. Formation, growth, and aggregation of crystals may be influenced by substances present in the urine which act as promoters or inhibitors of crystallization. A lack of crystallization inhibitors (magnesium, citrate, and macromolecules) can be the origin of kidney stone formation. Crystallization starts in the renal parenchyma in ways that are not completely known.\n\nThe increasing concentration of lithogenic solutes along the different segments of the nephron involves supersaturation conditions leading to the formation, growth, and aggregation of crystals that might get trapped in the tubular lumen and begin the process of stone formation. The phenomenon could start with crystalline aggregates free in the tubular lumen (free particle theory) or coated on the wall of the tubule (fixed particle theory). The speed of growth of the crystalline aggregates, the diameter of the different segments of the nephron, and the transit time in the nephron are crucial elements in justifying one theory or the other24. Plugs of crystalline material were highlighted with histopathological examinations in the tubular lumen of patients with brushite stones or stones associated with hyperparathyroidism, renal tubular acidosis, hyperoxaluria secondary to intestinal surgery (bypass for obesity, ileal resection, or ileostomy), or cystinuria.\n\nAn alternative mechanism to the crystalline growth within the tubules is crystalline growth starting from plaques of calcium phosphate in the interstitium within the renal papillae. The presence of small plaques of crystalline material in the papillae of the renal calyces, which has been identified as a pre-lithiasic condition (Randall’s plaques), was described in the 1930s25. In more recent years, this observation has been re-evaluated and the nature of these changes has been better investigated by endoscopic observations of the renal cavities in vivo or by micro-computed tomography (CT) analysis of the structure of stones. The origin of the plaques is still under discussion because they may be derived from the basement membrane of the loop of Henle26 or from deeper structures such as the basal membrane of the collecting tubules and vasa recta27. An intervention in the pathogenesis of Randall's plaque of interstitial cells with the capacity to transdifferentiate along the bone lineage has also been suggested28–30.\n\n\nUrinary risk factors for urolithiasis\n\nIn the 1960s and 1970s, many studies identified several possible risk factors for stone formation in the composition of the urine of renal stone formers31,32. For calcium stones (oxalate and calcium phosphate), the main risk factors were identified in high concentrations of calcium and oxalate, which are the main components of these stones, and a lower excretion of magnesium and citrate, which act as inhibitors of crystallization. In calcium oxalate stone formation, increases in urinary oxalate are more relevant than increases of urinary calcium because calcium is present in 10−20-fold higher concentrations in urine and calcium oxalate crystallization occurs in a 1:1 molar ratio. This implies that isolated increases in urinary calcium will not produce more particles33, whereas increases of oxalate produced by a dietary load of oxalate may produce microliths within 24 hours, even in non-stone former subjects34. On the other hand, due to the excess of urinary concentrations of phosphate (from bone and protein metabolism), an increase of urinary calcium will tend to produce calcium phosphate microliths. Inadequate urinary output is another major risk factor, whereas pH values of >7 tend to increase the crystallization of calcium phosphate. For calculi of uric acid, an excessive excretion of uric acid and undue acidic urinary pH are the most important risk factors. In fact, low urinary pH increases the concentration of the insoluble undissociated uric acid.\n\nIn some cases, these changes in urinary composition are caused by well-identifiable diseases. Excessive calcium excretion is a characteristic feature of primary hyperparathyroidism, sarcoidosis, prolonged immobilization, and other bone diseases. Hyperoxaluria can be observed in some congenital abnormalities of metabolism (primary hyperoxaluria) and some acquired forms (inflammatory bowel disease and results of bariatric surgery). Finally, some drugs cause high concentrations of calcium (loop diuretics), oxalate (orlistat), or urate (losartan); others cause increased concentrations of urinary calcium in association with increased urinary pH and lower urinary citrate (acetazolamide, topiramate, and zonisamide) or reduce the concentration of inhibitors such as citrate (thiazide diuretics and angiotensin-converting enzyme [ACE] inhibitors).\n\nThe pathogenic mechanisms for unduly urinary pH in uric acid stone formers are increased net acid excretion (NAE) and reduced renal ammonium (NH4+). The production and transport of ammonia could be impaired by insulin resistance, whereas the underlying mechanism of increased acid production has still to be fully elucidated.\n\nInfection stones are caused by definite urinary abnormalities secondary to infection by urease-producing bacteria. Proteus species and to a lesser extent Klebsiella and Enterobacter species present with an enzymatic activity which cleaves the urea present in the urine into ammonium and bicarbonate. The alkalinity and the high urinary concentrations of ammonium cause the crystallization of magnesium ammonium phosphate (struvite) with formation of large stones that may fill the renal cavities (staghorn stones). The infection by urease producers is often favored by congenital or acquired alterations of the urinary tract, causing stasis of the urine and leading to the appearance and maintenance of infection.\n\nOther types of stones (cystine, xanthine, and dihydroxyadenine) are caused by specific congenital metabolic defects that cause excessive excretion of these poorly soluble substances that tend to precipitate. Finally, some stones are caused by the precipitation of medications themselves (indinavir and other antiretroviral drugs) under conditions of reduced urinary output. However, in the great majority of cases, the alterations in the composition of the urine are not associated with specific diseases and are defined as idiopathic nephrolithiasis. In these cases, the causes of the disease are related to exposure to environmental factors in genetically predisposed subjects.\n\n\nGenetics\n\nSpecific types of nephrolithiasis are clearly linked to some monogenic hereditary alterations, which account for nearly 2% of renal stone cases in adults and 10% in children35. Cystinuria is a defect in tubular reabsorption of cystine and dibasic amino acids, which results in the frequent recurrent formation of stones composed of cystine. Inborn errors of the metabolism of oxalate (primary hyperoxalurias) result in the recurrent formation of calcium oxalate stones and crystal deposition in the renal parenchyma with associated progressive renal failure. Monogenic alterations of purine metabolism can also cause stones of uric acid or other purines (2,8-dihydroxyadenine or xanthine), crystal renal deposition, and progressive renal failure. A group of congenital tubulopathies affecting the convoluted proximal tubule (such as Dent's disease, Lowe syndrome, or hypophosphatemic rickets), the thick ascending limb of the loop of Henle (such as familial hypomagnesemia and Bartter's syndrome), or the distal part of the nephron (congenital distal tubular acidosis with or without hearing loss) are associated with calcium phosphate stone formation, nephrocalcinosis, extensive tubulointerstitial fibrosis, and a significant risk of progressing toward end-stage renal disease. Recurrent calcium stones associated with medullary sponge kidney (MSK) may be associated with an autosomal dominant mutation of a still unknown gene36. One of the most interesting candidate genes is GDNF, a gene involved in renal morphogenesis37. For all these diseases, it is now possible to make a precise genetic diagnosis with the identification of specific mutations; however, they are sometimes misdiagnosed or diagnosed late because the clinical presentation is not recognized38. Also, in the most common idiopathic calcium stone disease, a genetic basis is very likely because only a proportion of those exposed to the same environmental risk factors present with the disease.\n\nThe familial association of idiopathic calcium stone disease has been demonstrated by numerous studies, although the specific genetic and epigenetic factors have remained less clear. Calcium stone disease seems to be a genetically heterogeneous disease related to multiple genetic factors that regulate the excretion of the different urinary risk factors. Family-based or case-control studies of single-candidate genes showed gene polymorphisms related to stone formation for calcium-sensing receptor, vitamin D receptor, Na+/dicarboxylate cotransporter-1, and osteopontin39,40. A recent genome-wide association study in a large cohort of hypercalciuric stone formers from Iceland and the Netherlands identified the claudin 14 (CLDN14) gene as a possible major gene of nephrolithiasis41.\n\n\nEnvironmental factors\n\nDietary intake is certainly the most important environmental risk factor. Several studies of large cohorts of prospectively studied subjects showed some possible associations between the levels of intake of some nutrients and the risk of forming kidney stones. In particular, an insufficient intake of dietary calcium (<600 mg/day) can increase the intestinal absorption of oxalate with increased saturation values for urinary calcium oxalate and the risk of calcium oxalate stone formation42. Other possible risk factors that have been identified include excessive intake of salt and proteins43. The potential role of the acid load of the diet, related to the content in animal protein and the relationship between intake of calcium, magnesium, and potassium and that of chlorine and phosphates, seems to play an important role in causing a state of subclinical chronic acidosis and the consequent excessive mobilization of calcium from bone and its excretion in the urine44–47. For this reason, the intake of vegetables in association with the reduction in salt is encouraged in stone-forming patients. Consumption of sugar-sweetened soda and punch is associated with a higher risk of stone formation, whereas consumption of coffee, tea, beer, wine, and orange juice is associated with a lower risk48,49.\n\nPeople living in hot climates or who are exposed to high temperatures at work are at increased stone risk due to reduced urinary diuresis. Physical inactivity appears to be a risk factor for urinary stones, while moderate and constant physical activity seems sufficient to reduce the risk of forming kidney stones. However, the link between physical activity and risk of kidney stones is still uncertain and needs to be further investigated50.\n\n\nTreatment of kidney stones\n\nOver the last 40 years, the methods of stone removal from the urinary tract have benefited from technological innovations that have revolutionized the treatment of the disease and reduced its morbidity. Extracorporeal shock wave lithotripsy and endoscopic techniques of intracorporeal lithotripsy (percutaneous and retrograde) have made the treatment of kidney stones minimally invasive and easily repeatable. Conversely, medical treatment was not substantially improved. Despite increased knowledge about the pathogenesis and predisposing diseases and risk factors, the current modality of dietary and pharmacological treatment and their results are still unsatisfactory.\n\nA high fluid intake is widely recognized as the cornerstone of prevention of all forms of stones, although only one randomized trial has confirmed the effectiveness of this preventive measure (RR = 0.45)51. A reduction in the consumption of soft drinks significantly reduces the risk of lithiasis (RR = 0.83)52.\n\nNumerous studies have shown the effects of different types of nutritional intervention on urinary risk factors for the formation of kidney stones, but the evidence from randomized trials is still low and of uncertain meaning53. The effectiveness of protein restriction has been evaluated in several studies that still do not allow definitive conclusions to be made owing to the heterogeneity of experimental designs. Protein restriction alone was compared with that of a diet with high fiber content without demonstrating significant differences54. Conversely, protein restriction in combination with salt restriction and a calcium intake normalized according to the levels of intake recommended for the general population was more effective than a low-calcium diet55. However, in this last study, the effect of the reduction in protein intake cannot be distinguished from that of salt restriction and, in turn, the overall effect of this diet cannot be well estimated because the control group was on a diet potentially favoring the formation of stones. Other controlled studies have used multiple variables and dietary interventions that make interpretation difficult. Randomized trials evaluating more specific and targeted interventions are required to obtain more robust information on the effectiveness of dietary treatment of kidney stones. However, the unpredictable nature of nephrolithiasis, its complexity and heterogeneity, and, last but not least, lack of interest from pharmaceutical companies make these studies very difficult to perform.\n\nThe treatment and prophylaxis of kidney stones find their foundations in numerous studies dating back to over 30 years ago. The mechanisms of action and effects of several pharmacological measures on several urinary risk factors have been well studied, but unfortunately clinical evidence from randomized controlled studies is still scarce53. Uric acid stones can be dissolved with an oral alkalinizing therapy by means of potassium bicarbonate or potassium/sodium citrate56. The prevention of this type of stone is based on the long-term taking of citrate. Calcium stone formation can be prevented by the use of different drugs with different mechanisms of action, such as thiazide diuretics, allopurinol, phosphates, and potassium citrate. A meta-analysis of randomized controlled trials53 showed that thiazide diuretics (five studies) may reduce the risk of stone formation by 48% (RR = 0.52) and that the association with allopurinol (RR = 0.79) or with citrates (RR = 0.94) does not significantly increase the effectiveness of these drugs. The use of thiazides is, however, limited by the fear of side effects in the long term. The major concerns about their use arise from their tendency to cause hypokalemia, impaired glucose tolerance, and increases in serum cholesterol and serum uric acid57. Citrates (four studies) may reduce the risk of recurrence by 75% (RR = 0.25) and allopurinol (two studies) of 41% (RR = 0.59)53. Citrates are devoid of potentially serious side effects and may have a favorable impact on low bone density, which is frequently observed in the calcium stone patient, but are poorly tolerated for their digestive effects. On the other hand, although in rare cases, allopurinol may cause severe hypersensitive reactions58. Finally, the results of the use of magnesium (one study) were not significant. In conclusion, although there are several options for the pharmacological prevention of nephrolithiasis, there is no ideal drug that is both risk free and well tolerated. Finally, compliance to a prolonged pharmacological treatment remains a serious limitation of all forms of long-term treatment for a chronic disease, for which treatment effectiveness is conditioned by an efficient follow-up organization.\n\n\nConclusions\n\nThe most important future objectives of renal stone research are epidemiological studies that investigate simultaneously the genetic aspects and the diets of stone patients, studies aimed at correlating the morphological endoscopic and histological aspects of renal papillae with stone composition and chemical composition of urine from the same stone-forming patients, and large-scale randomized studies that evaluate the long-term effects of dietary modifications and pharmacological treatments for the prevention of recurrent stones.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nTrinchieri A: Epidemiology of urolithiasis: an update. Clin Cases Miner Bone Metab. 2008; 5(2): 101–6. PubMed Abstract | Free Full Text\n\nCurhan GC: Epidemiology of stone disease. Urol Clin North Am. 2007; 34(3): 287–93. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTrinchieri A: Epidemiological trends in urolithiasis: impact on our health care systems. Urol Res. 2006; 34(2): 151–6. PubMed Abstract | Publisher Full Text\n\nSakhaee K, Maalouf NM, Sinnott B: Clinical review. Kidney stones 2012: pathogenesis, diagnosis, and management. J Clin Endocrinol Metab. 2012; 97(6): 1847–60. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMeschi T, Nouvenne A, Ticinesi A, et al.: Dietary habits in women with recurrent idiopathic calcium nephrolithiasis. 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PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nWest B, Luke A, Durazo-Arvizu RA, et al.: Metabolic syndrome and self-reported history of kidney stones: the National Health and Nutrition Examination Survey (NHANES III) 1988-1994. Am J Kidney Dis. 2008; 51(5): 741–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMaalouf NM, Cameron MA, Moe OW, et al.: Low urine pH: a novel feature of the metabolic syndrome. Clin J Am Soc Nephrol. 2007; 2(5): 883–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAbate N, Chandalia M, Cabo-Chan AV Jr, et al.: The metabolic syndrome and uric acid nephrolithiasis: novel features of renal manifestation of insulin resistance. Kidney Int. 2004; 65(2): 386–92. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nShavit L, Ferraro PM, Johri N, et al.: Effect of being overweight on urinary metabolic risk factors for kidney stone formation. Nephrol Dial Transplant. 2015; 30(4): 607–13. PubMed Abstract | Publisher Full Text\n\nGambaro G, Ferraro PM, Capasso G: Calcium nephrolithiasis, metabolic syndrome and the cardiovascular risk. Nephrol Dial Transplant. 2012; 27(8): 3008–10. PubMed Abstract | Publisher Full Text\n\nFerraro PM, D'Addessi A, Gambaro G: Randall's plaques, plugs and the clinical workup of the renal stone patient. Urolithiasis. 2015; 43(Suppl 1): 59–61. PubMed Abstract | Publisher Full Text\n\nKok DJ, Khan SR: Calcium oxalate nephrolithiasis, a free or fixed particle disease. Kidney Int. 1994; 46(3): 847–54. PubMed Abstract | Publisher Full Text\n\nRandall A: The origin and growth of renal calculi. Ann Surg. 1937; 105(6): 1009–27. PubMed Abstract | Free Full Text\n\nEvan AP, Lingeman JE, Coe FL, et al.: Randall's plaque of patients with nephrolithiasis begins in basement membranes of thin loops of Henle. J Clin Invest. 2003; 111(5): 607–16. PubMed Abstract | Publisher Full Text | Free Full Text\n\nStoller ML, Low RK, Shami GS, et al.: High resolution radiography of cadaveric kidneys: unraveling the mystery of Randall's plaque formation. J Urol. 1996; 156(4): 1263–6. PubMed Abstract | Publisher Full Text\n\nGambaro G, Abaterusso C, Fabris A, et al.: The origin of nephrocalcinosis, Randall's plaque and renal stones: a cell biology viewpoint. Arch Ital Urol Androl. 2009; 81(3): 166–70. PubMed Abstract\n\nMezzabotta F, Cristofaro R, Ceol M, et al.: Spontaneous calcification process in primary renal cells from a medullary sponge kidney patient harbouring a GDNF mutation. J Cell Mol Med. 2015; 19(4): 889–902. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKhan SR, Gambaro G: Role of Osteogenesis in the Formation of Randall's Plaques. Anat Rec (Hoboken). 2016; 299(1): 5–7. PubMed Abstract | Publisher Full Text\n\nRobertson WG, Peacock M, Heyburn PJ, et al.: Risk factors in calcium stone disease of the urinary tract. Br J Urol. 1978; 50(7): 449–54. PubMed Abstract | Publisher Full Text\n\nTiselius HG: Metabolic evaluation of patients with stone disease. Urol Int. 1997; 59(3): 131–41. PubMed Abstract\n\nRobertson WG, Scurr DS, Bridge CM: Factors influencing the crystallisation of calcium oxalate in urine - critique. J Cryst Growth. 1981; 53(1): 182–94. Publisher Full Text\n\nHess B, Jost C, Zipperle L, et al.: High-calcium intake abolishes hyperoxaluria and reduces urinary crystallization during a 20-fold normal oxalate load in humans. Nephrol Dial Transplant. 1998; 13(9): 2241–7. PubMed Abstract | Publisher Full Text\n\nEdvardsson VO, Goldfarb DS, Lieske JC, et al.: Hereditary causes of kidney stones and chronic kidney disease. Pediatr Nephrol. 2013; 28(10): 1923–42. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFabris A, Lupo A, Ferraro PM, et al.: Familial clustering of medullary sponge kidney is autosomal dominant with reduced penetrance and variable expressivity. Kidney Int. 2013; 83(2): 272–7. PubMed Abstract | Publisher Full Text\n\nTorregrossa R, Anglani F, Fabris A, et al.: Identification of GDNF gene sequence variations in patients with medullary sponge kidney disease. Clin J Am Soc Nephrol. 2010; 5(7): 1205–10. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFerraro PM, D'Addessi A, Gambaro G: When to suspect a genetic disorder in a patient with renal stones, and why. Nephrol Dial Transplant. 2013; 28(4): 811–20. PubMed Abstract | Publisher Full Text\n\nVezzoli G, Terranegra A, Arcidiacono T, et al.: Genetics and calcium nephrolithiasis. Kidney Int. 2011; 80(6): 587–93. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nVezzoli G, Terranegra A, Aloia A, et al.: Decreased transcriptional activity of calcium-sensing receptor gene promoter 1 is associated with calcium nephrolithiasis. J Clin Endocrinol Metab. 2013; 98(9): 3839–47. PubMed Abstract | Publisher Full Text\n\nThorleifsson G, Holm H, Edvardsson V, et al.: Sequence variants in the CLDN14 gene associate with kidney stones and bone mineral density. Nat Genet. 2009; 41(8): 926–30. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCurhan GC, Willett WC, Rimm EB, et al.: A prospective study of dietary calcium and other nutrients and the risk of symptomatic kidney stones. N Engl J Med. 1993; 328(12): 833–8. PubMed Abstract | Publisher Full Text\n\nTaylor EN, Stampfer MJ, Curhan GC: Dietary factors and the risk of incident kidney stones in men: new insights after 14 years of follow-up. J Am Soc Nephrol. 2004; 15(12): 3225–32. PubMed Abstract | Publisher Full Text\n\nTrinchieri A, Maletta A, Lizzano R, et al.: Potential renal acid load and the risk of renal stone formation in a case-control study. Eur J Clin Nutr. 2013; 67(10): 1077–80. PubMed Abstract | Publisher Full Text\n\nTrinchieri A: Development of a rapid food screener to assess the potential renal acid load of diet in renal stone formers (LAKE score). Arch Ital Urol Androl. 2012; 84(1): 36–8. PubMed Abstract\n\nTrinchieri A, Lizzano R, Marchesotti F, et al.: Effect of potential renal acid load of foods on urinary citrate excretion in calcium renal stone formers. Urol Res. 2006; 34(1): 1–7. PubMed Abstract | Publisher Full Text\n\nTrinchieri A, Zanetti G, Currò A, et al.: Effect of potential renal acid load of foods on calcium metabolism of renal calcium stone formers. Eur Urol. 2001; 39(Suppl 2): 33–6; discussion 36-7. PubMed Abstract | Publisher Full Text\n\nFerraro PM, Taylor EN, Gambaro G, et al.: Soda and other beverages and the risk of kidney stones. Clin J Am Soc Nephrol. 2013; 8(8): 1389–95. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFerraro PM, Taylor EN, Gambaro G, et al.: Caffeine intake and the risk of kidney stones. Am J Clin Nutr. 2014; 100(6): 1596–603. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFerraro PM, Curhan GC, Sorensen MD, et al.: Physical activity, energy intake and the risk of incident kidney stones. J Urol. 2015; 193(3): 864–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBorghi L, Meschi T, Amato F, et al.: Urinary volume, water and recurrences in idiopathic calcium nephrolithiasis: a 5-year randomized prospective study. J Urol. 1996; 155(3): 839–43. PubMed Abstract | Publisher Full Text\n\nShuster J, Jenkins A, Logan C, et al.: Soft drink consumption and urinary stone recurrence: a randomized prevention trial. J Clin Epidemiol. 1992; 45(8): 911–6. PubMed Abstract | Publisher Full Text\n\nFink HA, Wilt TJ, Eidman KE, et al.: Medical management to prevent recurrent nephrolithiasis in adults: a systematic review for an American College of Physicians Clinical Guideline. Ann Intern Med. 2013; 158(7): 535–43. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHiatt RA, Ettinger B, Caan B, et al.: Randomized controlled trial of a low animal protein, high fiber diet in the prevention of recurrent calcium oxalate kidney stones. Am J Epidemiol. 1996; 144(1): 25–33. PubMed Abstract | Publisher Full Text\n\nBorghi L, Schianchi T, Meschi T, et al.: Comparison of two diets for the prevention of recurrent stones in idiopathic hypercalciuria. N Engl J Med. 2002; 346(2): 77–84. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTrinchieri A, Esposito N, Castelnuovo C: Dissolution of radiolucent renal stones by oral alkalinization with potassium citrate/potassium bicarbonate. Arch Ital Urol Androl. 2009; 81(3): 188–91. PubMed Abstract\n\nEllison DH, Loffing J: Thiazide effects and adverse effects: insights from molecular genetics. Hypertension. 2009; 54(2): 196–202. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCameron JS, Simmonds HA: Use and abuse of allopurinol. Br Med J (Clin Res Ed). 1987; 294(6586): 1504–5. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "13436",
"date": "18 Apr 2016",
"name": "Allen L. Rodgers",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13437",
"date": "18 Apr 2016",
"name": "Bernhard Hess",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-695
|
https://f1000research.com/articles/5-694/v1
|
18 Apr 16
|
{
"type": "Review",
"title": "Plant Heat Adaptation: priming in response to heat stress",
"authors": [
"Isabel Bäurle"
],
"abstract": "Abiotic stress is a major threat to crop yield stability. Plants can be primed by heat stress, which enables them to subsequently survive temperatures that are lethal to a plant in the naïve state. This is a rapid response that has been known for many years and that is highly conserved across kingdoms. Interestingly, recent studies in Arabidopsis and rice show that this thermo-priming lasts for several days at normal growth temperatures and that it is an active process that is genetically separable from the priming itself. This is referred to as maintenance of acquired thermotolerance or heat stress memory. Such a memory conceivably has adaptive advantages under natural conditions, where heat stress often is chronic or recurring. In this review, I will focus on recent advances in the mechanistic understanding of heat stress memory.",
"keywords": [
"Abiotic stress",
"heat stress",
"thermo-priming",
"heat stress priming",
"heat stress memory",
"plant heat adaptation"
],
"content": "Introduction\n\nPlants are sessile organisms that gauge and adapt to stressful environmental conditions in order to ensure survival and reproductive success. Such stressful conditions include extreme temperatures, drought, salinity, and pathogen and herbivore attacks. In nature, these are often chronic or recurring. Thus, plants have evolved strategies to cope with recurring stress. One such strategy is priming, where a past stress exposure modifies responses to a later stress event1–5. The term priming was coined in the context of pathogen defense, where a transient assault primes a plant to respond more efficiently in response to a future pathogen attack6. In the last few years, the term priming has been increasingly used to describe analogous phenomena that occur in response to other stresses5. Priming involves a lag/memory phase that separates the priming event and the second stress event. Research into different priming phenomena and their respective molecular bases has recently received increasing attention7–9. However, the molecular mechanisms underlying plant stress priming and memory are still largely unknown. In this context, the term memory is defined operationally as a phenomenon where information is perceived, stored, and later retrieved, as shown by a modified response to a second stimulus10. Mechanistically, stress memory may take place at different levels, ranging from metabolites and protein stability to chromatin complexes. In this review, recent progress in the field of priming by and memory of heat stress (HS) will be discussed. HS is a severe threat to global agriculture, and its significance will likely increase with climate change11. HS is detrimental, especially in combination with the lack of a water supply12 and during specific developmental stages such as pollen development11,13,14. It is therefore of the utmost importance to increase our understanding of the molecular basis of plant responses to HS in order to develop strategies to improve stress resistance in crop plants15.\n\n\nHeat stress priming and heat stress memory\n\nModerate HS primes a plant to subsequently withstand high temperatures that are lethal to an unadapted plant16. This is also referred to as acquisition of thermotolerance. After returning to non-stress temperatures, the primed state is maintained over several days (referred to as maintenance of acquired thermotolerance or HS memory), and this maintenance is genetically separable from HS priming17–19. The responses to acute HS have been studied intensively over the last few decades and are covered in several recent reviews20–22. In brief, HS priming involves the activation of heat shock transcription factors (HSFs) that induce the expression of heat shock proteins (HSPs), which in turn assist protein homeostasis through their chaperone activities22,23. This HS response is conserved in plants, animals, and fungi20. Whereas yeast and animals have only one or a few copies of HSF genes, plants typically contain more than 20 members of this protein family21. In Arabidopsis thaliana, at least eight HSFs are involved in the responses to HS17,24–27. HS priming is thought to be mediated primarily through HSFA1 isoforms27.\n\nWhereas the molecular events that lead to HS priming are relatively well understood, little is known about the mechanism of HS memory (i.e. the maintenance of the primed state after HS). HSFA2 is the most strongly heat-induced HSF24,28. Interestingly, HSFA2 is required not for HS priming but specifically for HS memory17. Microarray analyses have identified a number of HS memory-related genes that were classified on the basis of their sustained induction after HS, which lasts for at least 3 days19. They comprise many genes encoding small HSPs (such as HSP21, HSP22.0, and HSP18.2) but also ASCORBATE PEROXIDASE 2. Their expression pattern is in strong contrast to that of HS-inducible non-memory genes such as HSP70 and HSP101, whose expression peaks soon after HS and declines relatively quickly19,29. HSFA2 was reported to be required for the maintenance of high expression levels of several HS memory-related genes but not for their induction, suggesting that they could be direct targets of HSFA217,28. Indeed, HSFA2 associates with the promoter of several of these genes in vivo, as demonstrated by chromatin immunoprecipitation29. Interestingly, binding of HSFA2 to its target loci was detected only transiently, whereas active transcription was detected for much longer29. Among the HS memory-associated genes is HSA32, which was the first gene that was specifically implicated in HS memory18. Although HSA32 has no homology to chaperones, it was reported to be required for HSP101 protein stability and thus may have a similar function30. The peptidyl-prolyl-isomerase (and member of the FK506-binding protein family) ROF1 is also specifically required for HS memory31. ROF1 was shown to directly interact with HSP90.1 and through HSP90.1 with HSFA231. In rof1 mutants, sustained induction of several target genes of HSFA2 was compromised, suggesting that ROF1 (together with HSP90.1) may maintain HSFA2 in an active state during the memory phase31.\n\n\nTranscriptional memory of heat stress\n\nAs described above, both memory genes and non-memory heat-inducible genes are induced by HS, but only the former maintain very high expression levels for several days. To start to address the question of how these genes maintain such high and sustained expression levels, Lämke et al. investigated histone modification patterns at these loci during the memory phase29. Using chromatin immunoprecipitation with histone modification-specific antibodies, the authors found that sustained induction of these memory genes was associated with sustained accumulation of histone H3 lysine 4 trimethylation and dimethylation (H3K4me3 and H3K4me2) that persisted even after active transcription from the loci had subsided. This raises the intriguing possibility that H3K4 methylation marks a locus as recently active and mediates a modified re-induction profile upon a second HS. Indeed, the memory gene with the highest accumulation of H3K4me3 and H3K4me2 showed a pronounced hyper-induction upon recurring HS29. Notably, this H3K4 methylation is dependent on functional HSFA2 and is independent of the initial HS-mediated induction of the locus (which is also found in hsfa2 mutants). As mentioned above, HSFA2 associates only transiently with HS memory loci during the early hours after HS, suggesting that it recruits other factors that mediate lasting chromatin modifications29. Interestingly, HSFA2 itself appears not to be required for the maintenance of those chromatin changes29. Thus, it will be revealing to learn more about the mode of action of HSFA2 in the future. Notably, H3K4 methylation has also been implicated in the memory of other abiotic stresses such as drought and salinity8,9. How H3K4 methylation is recruited in those cases and whether there is a common mechanism remain challenges for future studies.\n\n\nHeat stress memory at the protein level\n\nAlthough regulation at the transcriptional level plays an important role in HS memory as described above, regulation at other levels may contribute to the memory. One such level may be regulated protein stability. For HSP101, transcript levels decline strongly within 24 hours after a priming HS; however, protein levels remain high for at least 48 hours29,30. During HS memory, HSP101 acts in a positive feedback loop together with HSA32, in which both proteins stabilize each other30. This suggests that HSA32, whose function is still poorly understood, acts to prevent denaturation and degradation of proteins. This specific function of HSP101 during HS memory could be uncovered through the isolation of a specific missense mutation in the protein (T599I) from a genetic screen30. The mutant HSP101 (T599I) protein was able to complement a yeast HSP104 deletion mutant, suggesting that its chaperone activity is not affected. In A. thaliana, this mutation specifically disrupts the function of HSP101 during HS memory but not during basal thermotolerance or during acquisition of thermotolerance. This suggests that the conserved chaperone activity of HSP101 is dispensable during HS memory. In rice, HSP101 and HSA32 stabilize each other in a similar manner32. It is tempting to speculate that genes whose transcription depends on HSFA2 will be regulated at the level of transcription but that genes whose transcription is independent of HSFA2 will display high protein stability.\n\n\nIntegrating stress exposure and development\n\nAs described above, an immediate effect of HS priming is to protect the plant during a recurring stress event. A more indirect effect may be the re-adjustment of growth and development after stress exposure. How this may be achieved molecularly became apparent through the finding that a microRNA (miRNA) family, which is important for plant development, is also required for HS memory19. MiRNAs are short RNAs that associate with effector proteins to promote cleavage of complementary mRNAs or to inhibit their translation33. The authors identified miRNAs whose expression is upregulated after HS and identified among them several MIR156 isoforms. Overexpression of MIR156 boosted HS memory, and depletion of miR156 compromised it. In addition, ARGONAUTE1 (AGO1) was specifically required for HS memory but not HS priming. Several target genes of miR156 whose transcript levels are reduced after HS were identified. SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) genes are well-studied target genes of miR15634, and SPL2, SPL9, and SPL11 were identified as relevant in the context of HS memory19. They are downregulated after HS and this was dependent on a functional AGO1 protein and on the miRNA-binding site19. Expression of a miR156-resistant form of SPL2 and SPL11 compromised HS memory, indicating that the repression of SPL2 and SPL11 by HS is required for HS memory. SPL genes regulate several aspects of development such as leaf initiation rate and flowering time34. To separate the two functions, miR156 levels were manipulated specifically after HS by using a heat-inducible promoter, and it was shown that the developmental effects are independent of the function during HS memory. Taken together, the AGO1-miR156-SPL module is important for plant development and also for HS memory. Although direct proof is yet elusive, it is tempting to speculate that employing the same miRNA/transcription factor module in stress acclimation and development may be used to integrate development with stressful environmental conditions10.\n\n\nThe evolution of heat stress memory\n\nGiven that plants acquire thermotolerance within minutes to hours after the onset of HS, the question remains as to why HS memory provides an adaptive advantage over de novo acclimation. To address this question, experiments with wild-type and memory-deficient genotypes under natural conditions will be required. Alternatively, natural and breeding-induced variation could be exploited to address this topic. A first step in this direction was undertaken by Charng and colleagues, who compared heat responses in two rice subspecies: the Oryza sativa ssp. japonica variety Nipponbare and the O. sativa ssp. indica variety N2232. Indica cultivars are thought to be more adapted to subtropical climates, whereas japonica cultivars grow in temperate climates32. Interestingly, Nipponbare has a lower basal thermotolerance but higher HS memory capacity, whereas the indica variety N22 had a higher basal thermotolerance and a lower HS memory. It is tempting to speculate that a memory of past HS may be beneficial especially in temperate climates, where HS is a relatively rare event, compared with subtropical climates, where HS is frequent. Further studies will be needed to test this idea.\n\n\nConclusions\n\nTemperature stress is highly fluctuating in nature. Consequently, the priming and memory of HS may be beneficial for plant survival and fitness under natural environments. HS priming and HS memory in A. thaliana and rice have been established as model systems in which to study the molecular basis and evolution of priming and memory in response to abiotic stress. Although exciting progress has been made in recent years, we are still far from a mechanistic understanding. However, the emerging picture is that HS memory is regulated at different levels ranging from protein stability to miRNA-controlled mRNA stability to transcriptional memory. A challenge for the future will be to unravel how these different levels of control are integrated to achieve a robust physiological response. The ultimate goal of these studies is to mine the mechanistic knowledge gained in model organisms to unlock new approaches for breeding more heat-tolerant crop plants.\n\n\nAbbreviations\n\nAGO1, ARGONAUTE1; HS, heat stress; HSF, heat shock transcription factor; HSP, heat shock protein; H3K4me, histone H3 lysine 4 methylation; miRNA, microRNA; SPL, SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL)",
"appendix": "Competing interests\n\n\n\nThe author declares that she has no competing interests.\n\n\nGrant information\n\nWork in the author’s laboratory is supported by the Alexander von Humboldt Foundation through a Sofja Kovalevskaja Award and by the Deutsche Forschungsgemeinschaft (DFG, CRC973, Project A2).\n\n\nReferences\n\nBruce TJA, Matthes MC, Napier JA, et al.: Stressful \"memories\" of plants: Evidence and possible mechanisms. Plant Sci. 2007; 173(6): 603–608. Publisher Full Text\n\nConrath U: Molecular aspects of defence priming. Trends Plant Sci. 2011; 16(10): 524–531. PubMed Abstract | Publisher Full Text\n\nVriet C, Hennig L, Laloi C: Stress-induced chromatin changes in plants: of memories, metabolites and crop improvement. Cell Mol Life Sci. 2015; 72(7): 1261–1273. PubMed Abstract | Publisher Full Text\n\nAvramova Z: Transcriptional 'memory' of a stress: transient chromatin and memory (epigenetic) marks at stress-response genes. Plant J. 2015; 83(1): 149–159. PubMed Abstract | Publisher Full Text\n\nHilker M, Schwachtje J, Baier M, et al.: Priming and memory of stress responses in organisms lacking a nervous system. Biol Rev Camb Philos Soc. 2015. PubMed Abstract | Publisher Full Text\n\nConrath U, Pieterse CM, Mauch-Mani B: Priming in plant-pathogen interactions. Trends Plant Sci. 2002; 7(5): 210–216. PubMed Abstract | Publisher Full Text\n\nJaskiewicz M, Conrath U, Peterhänsel C: Chromatin modification acts as a memory for systemic acquired resistance in the plant stress response. EMBO Rep. 2011; 12(1): 50–55. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nDing Y, Fromm M, Avramova Z: Multiple exposures to drought 'train' transcriptional responses in Arabidopsis. Nat Commun. 2012; 3: 740. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSani E, Herzyk P, Perrella G, et al.: Hyperosmotic priming of Arabidopsis seedlings establishes a long-term somatic memory accompanied by specific changes of the epigenome. Genome Biol. 2013; 14(6): R59. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nStief A, Brzezinka K, Lämke J, et al.: Epigenetic responses to heat stress at different time scales and the involvement of small RNAs. Plant Signal Behav. 2014; 9(10): e970430. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLobell DB, Schlenker W, Costa-Roberts J: Climate trends and global crop production since 1980. Science. 2011; 333(6042): 616–620. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSuzuki N, Rivero RM, Shulaev V, et al.: Abiotic and biotic stress combinations. New Phytol. 2014; 203(1): 32–43. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nGonzález-Schain N, Dreni L, Lawas LM, et al.: Genome-Wide Transcriptome Analysis During Anthesis Reveals New Insights into the Molecular Basis of Heat Stress Responses in Tolerant and Sensitive Rice Varieties. Plant Cell Physiol. 2016; 57(1): 57–68. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZinn KE, Tunc-Ozdemir M, Harper JF: Temperature stress and plant sexual reproduction: uncovering the weakest links. J Exp Bot. 2010; 61(7): 1959–1968. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nBita CE, Gerats T: Plant tolerance to high temperature in a changing environment: scientific fundamentals and production of heat stress-tolerant crops. Front Plant Sci. 2013; 4: 273. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMittler R, Finka A, Goloubinoff P: How do plants feel the heat? Trends Biochem Sci. 2012; 37(3): 118–125. PubMed Abstract | Publisher Full Text\n\nCharng YY, Liu HC, Liu NY, et al.: A heat-inducible transcription factor, HsfA2, is required for extension of acquired thermotolerance in Arabidopsis. Plant Physiol. 2007; 143(1): 251–262. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCharng YY, Liu HC, Liu NY, et al.: Arabidopsis Hsa32, a novel heat shock protein, is essential for acquired thermotolerance during long recovery after acclimation. Plant Physiol. 2006; 140(4): 1297–1305. PubMed Abstract | Publisher Full Text | Free Full Text\n\nStief A, Altmann S, Hoffmann K, et al.: Arabidopsis miR156 Regulates Tolerance to Recurring Environmental Stress through SPL Transcription Factors. Plant Cell. 2014; 26(4): 1792–1807. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRichter K, Haslbeck M, Buchner J: The heat shock response: life on the verge of death. Mol Cell. 2010; 40(2): 253–266. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nScharf KD, Berberich T, Ebersberger I, et al.: The plant heat stress transcription factor (Hsf) family: structure, function and evolution. Biochim Biophys Acta. 2012; 1819(2): 104–119. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHaslbeck M, Vierling E: A first line of stress defense: small heat shock proteins and their function in protein homeostasis. J Mol Biol. 2015; 427(7): 1537–1548. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFinka A, Sharma SK, Goloubinoff P: Multi-layered molecular mechanisms of polypeptide holding, unfolding and disaggregation by HSP70/HSP110 chaperones. Front Mol Biosci. 2015; 2: 29. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSchramm F, Ganguli A, Kiehlmann E, et al.: The heat stress transcription factor HsfA2 serves as a regulatory amplifier of a subset of genes in the heat stress response in Arabidopsis. Plant Mol Biol. 2006; 60(5): 759–772. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSchramm F, Larkindale J, Kiehlmann E, et al.: A cascade of transcription factor DREB2A and heat stress transcription factor HsfA3 regulates the heat stress response of Arabidopsis. Plant J. 2008; 53(2): 264–274. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nIkeda M, Mitsuda N, Ohme-Takagi M: Arabidopsis HsfB1 and HsfB2b act as repressors of the expression of heat-inducible Hsfs but positively regulate the acquired thermotolerance. Plant physiology. 2011; 157(3): 1243–1254. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nLiu HC, Liao HT, Charng YY: The role of class A1 heat shock factors (HSFA1s) in response to heat and other stresses in Arabidopsis. Plant Cell Environ. 2011; 34(5): 738–751. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNishizawa A, Yabuta Y, Yoshida E, et al.: Arabidopsis heat shock transcription factor A2 as a key regulator in response to several types of environmental stress. Plant J. 2006; 48(4): 535–547. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLämke J, Brzezinka K, Altmann S, et al.: A hit-and-run heat shock factor governs sustained histone methylation and transcriptional stress memory. EMBO J. 2016; 35(2): 162–175. PubMed Abstract | Publisher Full Text\n\nWu TY, Juan YT, Hsu YH, et al.: Interplay between heat shock proteins HSP101 and HSA32 prolongs heat acclimation memory posttranscriptionally in Arabidopsis. Plant Physiol. 2013; 161(4): 2075–2084. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nMeiri D, Breiman A: Arabidopsis ROF1 (FKBP62) modulates thermotolerance by interacting with HSP90.1 and affecting the accumulation of HsfA2-regulated sHSPs. Plant J. 2009; 59(3): 387–399. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLin MY, Chai KH, Ko SS, et al.: A positive feedback loop between HEAT SHOCK PROTEIN101 and HEAT STRESS-ASSOCIATED 32-KD PROTEIN modulates long-term acquired thermotolerance illustrating diverse heat stress responses in rice varieties. Plant Physiol. 2014; 164(4): 2045–2053. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nRogers K, Chen X: Biogenesis, turnover, and mode of action of plant microRNAs. Plant Cell. 2013; 25(7): 2383–2399. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHuijser P, Schmid M: The control of developmental phase transitions in plants. Development. 2011; 138(19): 4117–4129. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13271",
"date": "18 Apr 2016",
"name": "Yee-yung Charng",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13272",
"date": "18 Apr 2016",
"name": "Martin Haslbeck",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-694
|
https://f1000research.com/articles/5-693/v1
|
18 Apr 16
|
{
"type": "Opinion Article",
"title": "Better Outcomes through Learning, Data, Engagement, and Research (BOLDER) – a system for improving evidence and clinical practice in low and middle income countries",
"authors": [
"BOLDER Research Group"
],
"abstract": "Despite the many thousands of research studies published every year, evidence for making clinical decisions is often lacking. The main problem is that the evidence available is generated in conditions very different from those that prevail in routine clinical practice and with patients who are different. This is particularly a problem for low and middle income countries as most evidence is generated in high income countries.A group of clinicians, researchers, and policy makers met at Bellagio in Italy to consider how more relevant evidence might be generated. One answer is to conduct more pragmatic trials—those undertaken in routine clinical practice. The group thought that this might best be achieved by developing “learning health systems” in low and middle income countries.Learning health systems develop in communities that include clinicians, patients, researchers, improvement specialists, information technology specialists, managers, and policy makers and have a governance system that gives a voice to all those in the community. The systems focus on improving outcomes for patients, use a common dataset, and promote quality improvement and pragmatic research. Plans have been developed to create at least two learning systems in Africa.",
"keywords": [
"BOLDER",
"clinical decision making",
"learning health systems",
"low income countries",
"middle income countries",
"Africa"
],
"content": "\n\nBetween 2% and 53% (median 19%) of treatments offered to patients lack substantial research to support them1. A study of 16 guidelines from the American College of Cardiology and the American Heart Association found that only 314 (11%) recommendations of 2711 were supported by the highest level of evidence2; and cardiovascular medicine is probably the best researched part of clinical practice.\n\nThis deficiency is even more serious in low and middle income countries because most research is conducted in high income countries and may not be applicable in low and middle income countries. Those countries have rapidly rising rates of non-communicable disease (NCD), but an analysis of the 633 systematic reviews related to NCD found that almost 90% of 8850 trials included in the reviews were from high income countries, 5% from low-middle income countries, and only 13 (0.15%) from low income countries3.\n\nAt the same time as we have inadequate evidence to support many clinical decisions, clinicians are wary when we do have evidence, doubting its relevance to their local situations. In combination, these two kinds of evidence deficiency are depriving patients of access to the best treatments. How might more useful evidence be produced more efficiently? A group of clinicians, researchers, and policy makers, mostly from Africa, met in 2015 at the Bellagio Centre and developed some tentative answers.\n\n\nWhat is useful evidence?\n\nUseful evidence has two components. It must be internally valid in that users of the research can be confident that its conclusions are supported by its methods and results. But it must also be externally valid, meaning that it is applicable in a wide range of circumstances, in the \"real world\" as opposed to the ideal world common in most clinical trials. This problem of the \"applicability\" of research is particularly acute for those in low and middle income countries as most research has been conducted in high income countries3. Lower income countries need evidence on their own health care challenges, and they need it to be generated within their populations by their patients, clinicians, and researchers.\n\nStudies, particularly clinical trials, may lack internal validity because they are too small, too short term, fail to remove bias, too poorly done, use surrogate outcome measures irrelevant to patients and unconvincing to clinicians, or too poorly reported. A study of 2000 randomised trials in schizophrenia found that most were not useful for making clinical decisions: studies were short (54% lasted less than six weeks), small (mean number of patients 65), and poorly reported (64% had a quality score of less than or equal to two when the maximum score was five)4. Furthermore, the studies tested over 600 different interventions and used 640 different rating scales to measure outcomes, making interpretation for clinical use almost impossible4.\n\nExternal validity may be lacking because the patients are highly selected, excluding, for example, the old and those with multiple conditions, the research setting is not like those in which the treatment will be applied, the conditions of the research protocol are highly controlled, and patients monitored in a way that is not possible in everyday practice. Most drug trials fall into this category because they are what is required by regulators to allow drugs into the market. Furthermore, the drugs may be tested against placebo, when the question that matters to clinicians and policy makers is whether they are better than other currently used existing treatments, not only other drugs. Applicability is a particular problem in paediatrics as most studies are conducted in adults.\n\n\nMore relevant research\n\nSo why not make research more relevant and - at the same time - more effective? At Bellagio our working group developed a concept called BOLDER (Better Outcomes through Learning Data and Engaging in Research: www.bolderresearch.org). One key element of BOLDER is pragmatic research. Pragmatic studies are those conducted in routine clinical practice settings, and patients are enrolled with few selection criteria in order to maintain the representativeness of the true population5. In addition, the organisation of the studies should be simple, as few extra data as possible should need to be collected, and the outcome measures used should matter to those who take part in the trial, both patients and clinicians6,7. The hope is that the clinicians or policy makers will accept the results of the trial and act on them. Ideally these studies should be conducted rapidly and cheaply, avoiding the long delays and substantial costs of many trials, and be largely done by the clinicians who are the main consumers of clinical research.\n\n\nLearning health systems\n\nBefore the meeting it wasn't clear how this more useful research might be achieved, particularly in Subsaharan Africa, but during the meeting a possible answer emerged--the creation of “learning health systems.” A learning health system is one in which patients and providers work together to coproduce new knowledge and share decisions regarding best evidence8. It drives discovery but is a natural outgrowth of patient care. It increases innovation, quality, and safety, and does this in real time.\n\nQuality improvement science identifies barriers to improving health outcomes, finds ways to try and overcome them, evaluates the impact of interventions, and - if services and patients’ outcomes improve - keeps the cycle of improvement going. But the worlds of quality improvement and formal “research” rarely collide. Systems that bring these two worlds together do now exist, however, in a few places in the US and Europe. At the meeting we heard about ImproveCareNow9, which began in 2007 when eight paediatric gastroenterology practices came together to improve the care of children with inflammatory bowel disease. Agreeing on an outcome measure of remission, the system established a common dataset, standardised care, and engaged patients and families. Using cycles of improvement it increased remission rates over seven years from an average of 50% to 80%. During that time it grew from eight practices to over 809. The system then began to conduct research studies, thus becoming a true learning health system.\n\nImproveCareNow served as the prototype for a national, multispecialty learning health system called PEDSnet, which is now expanding to include many more hospitals and children and is conducting several pragmatic trials10. It is part of a wider network, PCORnet, that includes 12 other networks like PEDSnet. PCORnet provides care to 75 million Americans and is an unsung benefit of Obamacare.\n\n\nThe six components of a learning system\n\nA successful learning system has six components.\n\n\n\nA community, which ideally will include clinicians, patients, researchers, improvement specialists, information technology specialists, managers, and policy makers.\n\nA focus on outcomes. The learning health system must produce better outcomes for patients. If it doesn't it will --and should--fold.\n\nA common dataset that is as simple as possible with data being entered only once. Extra data might be collected for particular studies.\n\nQuality improvement, which reliably applies evidence generated from research when and where patients can benefit.\n\nPragmatic research\n\nGovernance, which should ensure a voice for all those in the system, particularly patients.\n\n\nA learning system for Africa?\n\nBut could a learning health system work in Africa? The conviction of those at the meeting was that it could. Nascent platforms were identified in Kenya, Malawi, Zambia, and South Africa, and interrogation of leaders from the Kenyan and South African platforms made those at the meeting think that learning health systems could be developed in those two countries at least11.\n\nIn Kenya the Wellcome KEMRI network of hospital paediatricians has developed a core dataset that is collected on every single patient who is admitted and is able to conduct research using these data. Several important randomised controlled trials have already been completed using this platform12,13.\n\nIn South Africa there is a well developed national system to incorporate current evidence based clinical guidelines into daily clinical practice in primary care. The guidelines reach tens of thousands of nurses and doctors and have improved the care of millions of patients across the entire country14.\n\nIn BOLDER we are working to build on these capacities. The aim in Kenya is to develop a learning health system that can rapidly implement into daily practice across the country the evidence it gathers from pragmatic research. In South Africa we hope to build a basic electronic data platform that can be used in routine care in even the most remote facilities but can also be used to conduct research in these real world practice settings.\n\n\nConclusion\n\nA potential answer to the problem of inadequate evidence for clinical practice, particularly in Africa, has become clear. A learning health system will be built on networks that have already been scaled up in two countries in Africa. The systems will concentrate on improving outcomes and include all stakeholders, including patients, clinicians, and researchers. The research will happen in a context that allows it to be quickly implemented, and the aim is for the research to be pragmatic and be done quickly and cheaply. Plans are launched to make it happen.\n\n\nNote\n\nThe first draft of this article was written by RS, and there is some overlap with a blog he posted immediately after the meeting: http://blogs.bmj.com/bmj/2015/08/11/richard-smith-how-to-fill-the-void-of-evidence-for-everyday-practice/",
"appendix": "Author contributions\n\n\n\n* The participants who contributed to authorship of this paper include: Mark Blecher (South Africa), Samuel Akech (Kenya), Elizabeth Bukusi (Kenya), Kalipso Chalkidou (UK), Roma Chilengi (Zambia), Susie Colville (UK), Mike English (Kenya), Chris Forrest (USA), Trish Groves (UK), Metin Gulmezoglu (Switzerland), Archna Gupta (Canada), Damson Kathyola (Malawi), Michael Makanga (South Africa), Jacquie Oliwa (Kenya), Nelson Sewankambo (Uganda), Richard Smith (UK), Sean Tunis (USA), Jimmy Volmink (South Africa), Merrick Zwarenstein (Canada).\n\nAll of the authors participated in the discussions that led to the ideas expressed in the manuscript. RS wrote the first draft, and all authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe stay at Bellagio was funded by the Rockefeller Foundation.\n\n\nReferences\n\nJamtvedt G, Klemp M, Mørland B, et al.: Responsibility and accountability for well informed health-care decisions: a global challenge. Lancet. 2015; 386(9995): 826–828. PubMed Abstract | Publisher Full Text\n\nTricoci P, Allen JM, Kramer JM, et al.: Scientific evidence underlying the ACC/AHA clinical practice guidelines. JAMA. 2009; 301(8): 831–841. PubMed Abstract | Publisher Full Text\n\nHeneghan C, Blacklock C, Perera R, et al.: Evidence for non-communicable diseases: analysis of Cochrane reviews and randomised trials by World Bank classification. BMJ Open. 2013; 3(7): pii: e003298. PubMed Abstract | Publisher Full Text | Free Full Text\n\nThornley B, Adams C: Content and quality of 2000 controlled trials in schizophrenia over 50 years. BMJ. 1998; 317(7167): 1181–4. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRaymond J, Darsaut TE, Altman DG: Pragmatic trials can be designed as optimal medical care: principles and methods of care trials. J Clin Epidemiol. 2014; 67(10): 1150–6. PubMed Abstract | Publisher Full Text\n\nTosh G, Soares-Weiser K, Adams CE: Pragmatic vs explanatory trials: the pragmascope tool to help measure differences in protocols of mental health randomized controlled trials. Dialogues Clin Neurosci. 2011; 13(2): 209–15. PubMed Abstract | Free Full Text\n\nLoudon K, Treweek S, Sullivan F, et al.: The PRECIS-2 tool: designing trials that are fit for purpose. BMJ. 2015; 350: h2147. PubMed Abstract | Publisher Full Text\n\nInstitute of Medicine (US) Roundtable on Evidence-Based Medicine; Olsen LA, Aisner D, et al.: The Learning Healthcare System: Workshop Summary. Washington (DC): National Academies Press; 2007. PubMed Abstract | Publisher Full Text\n\nGreene SM, Reid RJ, Larson EB: Implementing the learning health system: from concept to action. Ann Intern Med. 2012; 157(3): 207–10. PubMed Abstract | Publisher Full Text\n\nForrest CB, Margolis P, Seid M, et al.: PEDSnet: how a prototype pediatric learning health system is being expanded into a national network. Health Aff (Millwood). 2014; 33(7): 1171–7. PubMed Abstract | Publisher Full Text\n\nEnglish M, et al.: Building Learning Networks to accelerate research and uptake of evidence to improve quality and outcomes of clinical care in low-income settings. Submitted for Publication.\n\nEnglish M, Mohammed S, Ross A, et al.: A randomised, controlled trial of once daily and multi-dose daily gentamicin in young Kenyan infants. Arch Dis Child. 2004; 89(7): 665–669. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAgweyu A, Gathara D, Oliwa J, et al.: Oral amoxicillin versus benzyl penicillin for severe pneumonia among Kenyan children: a pragmatic randomized controlled noninferiority trial. Clin Infect Dis. 2015; 60(8): 1216–24. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFairall L, Bateman E, Cornick R, et al.: Innovating to improve primary care in less developed countries: towards a global model. BMJ Innov. 2015; 1(4): 196–203. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "14218",
"date": "27 Jul 2016",
"name": "Gillian Mann",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nPlease note that I am writing in my personal capacity; this is not an official response from the Department for International Development\n\nThis is a helpful contribution to the health research agenda. For some time researchers have been asking how to have research taken into policy - this goes some way to answer questions of why that does not often happen.\n\nIt would help if more examples outside the specific areas of clinical practice were given. For example research may not only be on one narrow interest topic (though this clearly has validity), but may be on broader approaches to patient care - e.g. improving outreach services in community based care, reaching neglected patient groups with services that already work for others, changing broad clinical protocols to improve patient pathways to care.\nIt would also help to highlight some of the contextual reasons why research has failed to be taken up in the past - e.g. cost of new technologies (not just cost effectiveness), a lack of understanding of what is needed to make new technologies work (e.g. staffing skills, numbers, distribution; consistent availability of water or electricity etc). Previous work relating to the types of evidence required has previously been undertaken1.\nTwo phrases are used rather interchangeably throughout: \"Learning Health Systems\" and \"Learning Systems\". I would argue that the latter is more applicable in this context. A \"learning health system\" implies that the broad health system is learning, whereas this article refers to establishing systems to learn to improve clinical practice in particular, which may only relate to parts of the health system, circumscribed by geography, field or research, or some other criteria. While this may evolve into a broader learning health system, the term is rather grander than the scope at this time.",
"responses": []
},
{
"id": "17309",
"date": "31 Oct 2016",
"name": "Lilian Dudley",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nOverview This opinion paper addresses important concerns about the gap between clinical evidence generation, particularly clinical trials in high income countries (HIC), their appropriateness for low and middle income country (LMIC) health systems, and the challenges of translating research evidence into practice in different settings.\nThe authors propose the use of pragmatic research (trials) methods in LMIC’s within the framework of ‘learning health systems’ (LHS) as a potential solution to the current problems. The proposed approach suggests ways of conducting clinical research within ‘real world’ settings, and mechanisms by which the research evidence can be more appropriate, and facilitate implementation by practitioners and patients particularly in LMIC’s. The opinion paper generates helpful ideas and discussion on ways of reducing the disconnect between knowledge of what works in selected or ideal settings, and producing more appropriate local knowledge with the involvement of practitioners as the primary users of the knowledge.\nFrameworks of LHS, HSR and QI\nThe authors have applied components of LHS’s to the use of clinical research evidence in LMIC’s. The interpretation of LHS has not fully explained the overall concept and framework for LHS, and its application has only used a limited perspective of LHS’s in providing a framework for clinical research methods in LMIC’s.\nLHS’s seek to address concerns re external validity and use of evidence collected through trials, and is therefore an appropriate model to consider for ‘knowledge translation’. However, what the authors do not elaborate is that it does so largely through using ‘evidence’ from electronic patient information systems, and by promoting access to, interoperability and use of electronic patient records (Big Data) to provide more patient centered evidence. This ensures that evidence is linked to real patients in practice, and can be used by real health providers and patients. It benefits from the growth of ICT’s in health in HIC’s, and the extensive access to and improved quality of routine patient information in such settings. This is underpinned by financial and human resources, and infrastructure which is able to support such ICT’s for health in HIC’s.\nThe authors appropriately discuss the re-conceptualisation of ways of doing research i.e. shifting from a pre-occupation with internal validity to ensuring external validity; moving from the ‘ideal’ to ‘pragmatic’ approaches; and collaborations across ‘institutions’, between researchers and practitioners and patients. A component of LHS which could further enhance this reconceptualization is the focus on ‘harvesting’ existing data on real patients from RHIS, rather than ‘hunting’ data on ideal selected group of patients through the expensive and time consuming collection of new data with limited external validity. One of the challenges of such an approach however is that ‘Big data’ and electronic patient record systems do not exist in many LMIC’s. Many have very basic routine health information systems (RHIS), in which the quality of the data is often poor; and very few have electronic patient record systems to generate the kind of evidence needed for clinical decision making and to support a new way of doing research.\nAlthough the opinion piece speaks to LHS, by focusing narrowly on the potential of ‘pragmatic’ trials as a research approach it does not address fully how LHS can be used to promote the generation of evidence from different sources and its translation into practice. It would be useful to explore further the opportunities which LHS present to review the nature of evidence, and the kind of research which can be conducted i.e. sources of data, greater patient centredness, and the role of clinicians/practitioners as researchers and users of evidence in LMIC settings.\nBy limiting the definition and understanding of LHS to one which simply conducts pragmatic trials rather than RCT’s, it misses the opportunity for researchers to rethink the model of research in LMIC’s, and the links between research, RHIS, and the opportunities it can create for ‘co-creation’ and use of knowledge between researchers, practitioners, patients and families to inform and transform practice. It would be useful if the authors could comment on these issues related to LHS and its application in LMIC’s, and whether any consideration was given to it in the Bellagio meeting.\nThe proposal also draws on different approaches to research already practiced as part of ‘health services’ or ‘health systems’ research. The authors propose more collaborative and participative research practices, without referring to the broad and well established field of participatory action research (PAR), which facilitates ‘transformative’ research. PAR specifically aims to include users of knowledge in the research process in order to empower and build capacity of users of research (and researchers) to ensure implementation and sustainability of interventions. LHS and its application in this opinion paper, is therefore not new in identifying processes for greater involvement of users, and it would be helpful to reflect on how lessons from PAR for supporting ‘action learning’ can support such a process.\nThe proposal also draws on Quality Improvement, through which evidence is implemented in collaborative and iterative processes to improve practice, and through which both researchers and practitioners learn. The artificial divide between QI and research has diminished substantially in recent years and QI is increasingly underpinned and supported by QI research on a continuum between research and practice. The HIC projects which the authors identify are useful examples of QI supported by research. It would have been helpful if the authors could identify similar QI projects in LMIC where research is a core component of the project to illustrate that this is indeed feasible in such settings.\nPragmatic Trials as an approach\nIn resource constrained environments such as in LMIC’s, barriers to doing RCT’s include limited financial resources, research and institutional capacity to support any form of trials. The paper does not indicate how pragmatic trials will overcome these constraints to make the kinds of evidence more easily producible and accessible in LMIC’s.\nPage 2, para 5: Although the emphasis of LHS is not on improving internal validity, the authors do raise some concerns about internal validity of clinical trials. However, the article then does not adequately address how pragmatic trials as part of LHS’s can overcome these internal validity shortcomings of RCT’s. If LHS and pragmatic trials are not addressing internal validity, perhaps this section should not receive the level of emphasis – or it needs to be addressed in the context of LHS and pragmatic trials.\nPage 2, para 7: ‘as few extra data as possible should need to be collected’ – If the LHS approach to pragmatic trials includes increased use of routine data, it is important to discuss whether suitable data is available, and indicate how pragmatic trials will overcome the limitations of routine data in many LMIC’s, as well as the lack of trust in the data by clinicians.\n\nPage 2, para 7: The emphasis on clinicians doing the studies may not fully take the reality of LMICs into account. Clinicians are a scarce resource in most LMIC’s and tend to be overburdened with clinical work with little time to undertake additional research activities. Many also do not have the necessary training and research skills to participate in such studies. It would therefore be useful for the opinion piece to indicate how and why it will be easier under these circumstances for clinicians to do pragmatic trials as opposed to other forms of trials or research; and how LHS will contribute to facilitating this and building capacity to undertake these trials.\nPage 2, para 8, proposes a more collaborative and participative research process, but does not reference the extensive experience and lessons of PAR – which precisely aims to not only undertake research under real world conditions, and involve participants and stakeholders and create a learning process for both. Much could be learnt by pragmatic triallists by considering PAR approaches which already describe ways of engaging and joint learning, but also highlight some of the limitations.\nPage 2, para 9: There is a continuum from QI practice to QI research which is increasingly recognised and practiced. Unfortunately the only examples provided of QI research are from HIC projects, and it would have been useful to identify examples of QI research in LMIC’s. It does not help the authors’ argument that LHS need to be local in LMIC, if there is little evidence of that happening.\nPage 3, para 2: Patient centredness is a key element of LHS which receives little focus in the paper. In HICs’ an important component of using electronic patient data is that the data is linked directly to real patients, and can include their experiences and assessments of outcomes. It would be useful for the opinion paper to indicate how this aspect can be used and applied in LMIC’s as part of pragmatic research. Page 3, para 4 – the database of clinical guidelines in SA, although a step in the right direction, does not really encompass the scope of activities proposed in the paper or typical of a LHS. It would be helpful if the authors could indicate how this links to the earlier suggestions of pragmatic trials, and the involvement of clinicians in research.\nPage 3, para 5: The suggestion that new electronic data collection systems for research be established is also contrary to earlier suggestions of limiting the requirement to collect new data. There have been several initiatives to establish electronic patient records in South Africa and the authors should rather investigate what has already been developed and implemented. LMIC’s are littered with projects which have set up independent data collection systems instead of strengthening the routine information systems, and this needs to be approached with caution.\nPage 3, para 6: Before proposing this as a ‘clear’ solution, it would be useful to have more engagement with clinicians, policy makers, patients, ICT personnel and to look at current practices in LMIC’s in order to develop a clearer framework for how LHS’s and pragmatic research can support the use of evidence in LMIC’s.",
"responses": []
}
] | 1
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https://f1000research.com/articles/5-693
|
https://f1000research.com/articles/5-692/v1
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18 Apr 16
|
{
"type": "Data Note",
"title": "Innovations in scholarly communication - global survey on research tool usage",
"authors": [
"Bianca Kramer",
"Jeroen Bosman",
"Jeroen Bosman"
],
"abstract": "Many new websites and online tools have come into existence to support scholarly communication in all phases of the research workflow. To what extent researchers are using these and more traditional tools has been largely unknown. This 2015-2016 survey aimed to fill that gap. Its results may help decision making by stakeholders supporting researchers and may also help researchers wishing to reflect on their own online workflows. In addition, information on tools usage can inform studies of changing research workflows.The online survey employed an open, non-probability sample. A largely self-selected group of 20663 researchers, librarians, editors, publishers and other groups involved in research took the survey, which was available in seven languages. The survey was open from May 10, 2015 to February 10, 2016. It captured information on tool usage for 17 research activities, stance towards open access and open science, and expectations of the most important development in scholarly communication. Respondents’ demographics included research roles, country of affiliation, research discipline and year of first publication.",
"keywords": [
"scholarly communication",
"research workflow",
"survey",
"innovation",
"tools"
],
"content": "Introduction\n\nMany websites and tools exist to support researchers in handling information in all phases of the research cycle. For the first time a multidisciplinary and multilingual survey, carried out in 2015–2016, details the usage of such tools. Insights from these data may help researchers and those that support them in their decisions to improve the efficiency, openness and reliability of research workflows. Anonymized data from the survey is available in both raw (multilingual) and cleaned (all-English) versions (Data availability; 1). Details on data collection and full description of the data is provided in this Data Note.\n\n\nSetup of the survey\n\nThe survey includes four questions on demographics, 17 on tool usage (with pre-selected answer options and free-text answer), two on support of Open Access and Open Science (yes/no/don’t know), one open question on the expected most important development in scholarly communication (free-text answer), one (optional) question asking for an email address and one question asking whether participants would be willing to be contacted for follow-up research. See the Supplementary material for the full list of survey questions in all languages.\n\nQuestions on demographics asked about country of current or last affiliation, research discipline, research role and career stage. Country of affiliation and research discipline were included because there is indication of strong variation in tool usage and publication cultures across these parameters. Our classification of research discipline (seven categories) was based on the broad classification from Scopus, with some modifications:\n\n\n\nPhysical sciences (which in Scopus includes mathematics) - from which we made Engineering & Technology (including computer science) into a separate category\n\nLife sciences\n\nHealth sciences - which we renamed Medicine\n\nSocial sciences - from which we made Arts & Humanities and Law into separate categories.\n\nResearch role (which included various academic roles, but also supporting roles such as publisher, librarian and funder) and career stage (proxied by using the year of first publication in six date ranges) were included to allow testing hypotheses on e.g. the innovation of workflows being dependent on the degree to which people are conditioned by traditions in research practices. In addition, data on demographics can serve to assess and correct for bias.\n\nThe bulk of the survey consisted of questions on tool usage for 17 activities in the research workflow (see Supplementary material and Table 4). These activities were selected from our database of research tools [http://bit.ly/innoscholcomm-list], that distinguishes 30 research activities in seven phases of the research workflow and lists over 600 tools for these activities. The activities included in the survey were chosen for their overall importance (for example we included a question on writing tools but not on translation tools) and for their spread across the research workflow, covering discovery, analysis and writing as well as publication, outreach and assessment. For each of the 17 activities, the survey offered seven tools as preset answers and an eighth answer option to indicate use of any other tools (Figure 1), followed by a question to specify those. The seven preset tools were chosen from the database of tools mentioned. In most cases we included 4–5 of the most well-known tools but also included 2–3 newer and smaller and in some cases even still experimental tools to stimulate respondents to also mention any less well-known tools they might use. Only in exceptional cases tools were offered as preset answer options in more than one question. Participants could skip any question (except demographic questions on research role, country of affiliation and research discipline) they felt did not apply to them, or were otherwise not willing to answer. Finally, people with a role supporting research were explicitly asked to base their answers to the questions on tools on what they would advise researchers to use.\n\nA) Question on sharing notebooks/protocols/workflows. B) Question on measuring impact.\n\nAll questions were entered into the cloud-based survey form software Typeform (http://www.typeform.com). Typeform allows for ample use of graphics. These were used for all preset answers to tool usage questions. For these we used existing logos of tools and some self-made text logos. This made it very easy for respondents to recognize tools they used and enter most of their answers by simply clicking images.\n\n\nDistribution of the survey; sampling\n\nThe survey was live on the Typeform website for a 9-month period between May 10, 2015 and February 10, 2016. Responses submitted were stored by Typeform; a backup in csv format was made at regular intervals and stored on a university server.\n\nThe sample used was a fully open, self-selected, non-probability sample, meaning that the survey was open for anyone to take, with no systematic control on who took it. We used a hybrid of sampling methods, including snowball sampling and quota sampling. Distribution was targeted to researchers and people supporting research, both through direct and indirect distribution. Direct distribution included messages with the link to the survey on Twitter (e.g. in answer to people mentioning their paper/abstract/poster/manuscript got accepted), mailing lists, our own survey website, blog posts, including one on the widely read LSE Impact blog, a podcast interview on the Scholarly Kitchen website and during meetings the authors attended. Indirect distribution included that by 108 partners who distributed the survey among their constituency (either through a direct email message, inclusion in a newsletter or a message on the organisation’s website or intranet), in exchange for the anonymized data from that population. Of these, 65 organizations agreed to have their role disclosed. The 108 partners consisted of 76 universities (often through their libraries), 10 hospitals, 11 publishers and 11 other organizations. Some of these organizations also distributed our translations of the survey (see below). In addition, many individuals and organizations publicized the survey through various channels, e.g. through Twitter and other social media, in blogs and by inclusion in conference presentations. We did not specifically target students and know that many partners also did not do so.\n\nWe offered respondents no financial incentives or presents to stimulate take up. However, all respondents were offered the option to receive automatic feedback (Figure 2) on how their choices of tools compared to those of their peer group (based on research roles entered). For this we used a dataflow from Typeform via Google Drive (http://drive.google.com, for calculations and creating the graphs) to WordPress (http://www.wordpress.com to publish the graphs). To transfer data between these tools we used Zapier (http://www.zapier.com).\n\nClassification: Traditional tools (Trad) - Add no functionality compared to print era, except online accessibility; Modern tools (Mod) - Use scale and linking possibilities of the internet to increase speed and efficiency; Innovative tools (Inn) - Actually change ‘the way it’s always been done’ – e.g. user-driven, different business models, changes in the sequence of research activities, shifting stakeholder roles; Experimental tools (Exp) - Represent radical change, with sometimes uncertain technologies and outcomes; still under development. Tools were scored on a scale of 1 (traditional) to 4 (experimental); the chart shows average scores per workflow phase. Tools mentioned as ‘others’ are not included at this stage.\n\n\nTranslation of the survey\n\nTo address cultural and language bias and simply to increase uptake in non-English language areas we had the survey translated into six world languages: Spanish, French, Chinese, Russian, Japanese and Arabic. These languages were selected based on observed underrepresentation of these language areas after four months of having the survey available only in English. However, this was done only after attaining initial success with attracting respondents to the survey and after getting requests for translation. Translations became available in the 6th month (Spanish and French), the 7th month (Chinese and Russian), the 8th month (Japanese) and 9th month (Arabic) of the survey period.\n\nThe survey was professionally translated, and reviewed by at least two native speakers (one researcher and one librarian). All questions and preselected answer options were kept identical across different language versions. However, in five of the six foreign language versions (the exception being Arabic) we included one additional question at the end of the survey on the use of tools targeting that specific language area. This was done to increase commitment, to stimulate respondents to also mention language-specific tools and to be able to check answers given here against tools mentioned as ‘others’ in the regular survey questions.\n\n\nDistribution of responses\n\nIn total, 20663 valid survey responses were received. Obvious spam responses (n=6) were removed from the data.\n\nDistribution channels - Responses received could be traced back to distribution channels by way of a suffix attached to the survey URL (Table 1). Although in absolute numbers the foreign language versions contributed only modestly to the overall response numbers (Table 2), they were quite important to stimulate response from the respective language areas (Figure 4).\n\nCountry of current or last affiliation - Partly helped by the translations we got a very broad response from across the globe with at least 1 response from 151 countries and at least 20 responses each from 64 countries (Figure 4).\n\nResearch discipline - The largest group of respondents was from social science and economics. Other disciplines were also well represented, with only law lagging (Table 3, Figure 3A).\n\nA) Mentions of research discipline(s) (multiple answers possible, 25820 answers given, N=20663). B) Responses by research role (n=20663). C) Responses by year of first publication (n=20663).\n\nNumber of survey responses per 100 billion US$ GDP for all countries; weighted mean of all countries with at least 1 response: 27.3, median: 27.0.\n\nResearch role - The vast majority of respondents are from inside academia (from students to professors) (Table 4, Figure 3C). Relatively few students responded, probably because many considered themselves not active researchers yet. Other groups are also much smaller, allowing for less detailed analysis.\n\nCareer stage - Table 5 shows career stage of respondents carrying out research as measured by year of first publication (Figure 3C). Interestingly there is a fairly even distribution, indicating interest in the topic of the survey across various ages and career stages. Please note that the answer ‘not published (yet)’ may indicate that the respondent is in the beginning of a researcher’s career, but also that someone has a role in which publishing is not a primary task. To identify these separate populations, demographic data for career stage can be combined with those on research role.\n\n\nPopulation, sample size & response rate estimation\n\nWith an open self-selected survey like this there is no fixed sample size and thus reporting response rates is not straightforward. However we have made estimations of the total number of people that has been targeted in our distribution efforts (1.4 million, Table 6). This number represents an upper limit as it does not account for overlap in populations reached through various modes of distribution. Based on this estimation, the overall response rate is 1.5%. We can also relate the number of responses to officially reported numbers of researchers (i.e. response compared with total target population) and look at response rates from specific partners that distributed the survey to a defined number of researchers (i.e. response of a subset of the population). This latter approach also allows for comparison of response rates across different modes of distribution. For instance, in cases where the survey was distributed via a mass mailing response varied between 1 and 10 percent, reached within less than a week. In cases where partners used an indirect message to an undefined set of people (e.g. through a message on intranet or on social media) very few responses were generated (typically a few dozen, even when the stated target group contained many thousands of people), and it often took months to reach that number.\n\n\nCompleteness of the responses\n\nNot all questions received answers from all respondents and not all answers were valid. Table 7 shows the number of answers per question and the number of valid answers (where applicable). Also shown are the number of respondents that indicated they used (also) other tools (or had another research role) than the ones mentioned as preset answer, and how many of those specified these other tools or research roles.\n\n# answers = total number of answers per survey question; # answers valid (*) = number of valid answers per survey question (where applicable); # answers yes (**) = number of respondents answering ‘yes’ per survey question (where applicable); # others = number of respondents that checked the ‘other’ option per survey question (where applicable); # others specified = number of respondents that specified ‘others’ as free text answers.\n\n\nAnonymization of the data\n\nOn our website and in the survey itself, we guaranteed participants only anonymized data would be shared. We anonymized the data by:\n\n\n\nRemoving email addresses where given;\n\nRemoving information on the specific custom URL through which the response was received;\n\nGeneralizing research role specifications where traceable to specific persons (either directly or through combining with other information);\n\nGeneralizing information given about the country of affiliation (sometimes much more detailed affiliations were given);\n\nRemoving identifiable information from free text answers.\n\nWe had to be extra careful because we do not only share the full data, but also shared subsets containing just the data of respondents invited by the respective partners through the custom survey URLs. In cases where those partners were academic institutions or hospitals, they know the institutional affiliation of respondents in that subset, making possible identification from free text answers potentially more likely.\n\n\nCleaning and harmonization of the data\n\nFor the cleaned dataset we harmonized free-text answers by correcting spelling (of e.g. country names and tool names), unifying acronyms and full names, and grouping similar answers that used different phrasing (e.g. “library databases” and “bibliographic databases”). For country of affiliation, we also replaced names of areas that constitute part of a country with the name of the country as a whole. For this we used the UN list of member and observer states. For instance, responses attributed to people from overseas areas of France and Britain simply got assigned the main country as country of affiliation. In the answers given as specification of other tools used for a certain activity, responses that contained identifying information and could not be generalized to a more generic tool name were categorized as “other”. Cases where respondents indicated they either use no specific tool for an activity or do not engage in the activity were removed as answers. As we chose not to let respondents specify reasons for not answering questions, these answers are conceptually no different from cases where respondents skipped a question altogether.\n\nBoth raw answers and cleaned/harmonized answers are available as separate datafiles, but identifying information is removed from raw answers to guarantee anonymity (see above).\n\n\nReverse translation of foreign language answers\n\nReverse translation of answers given in languages other than English was initially done by using Google Translate. The use of automated translation was justified as most answers contained just simple text, e.g. names or descriptions of tools used. For the answers on the open question on expectations of the most important development in scholarly communication, translations provided by Google Translate were manually checked by the authors for French and Spanish, and in cases of doubt help from a native speaker with domain knowledge was requested. Free text answers to this question given in Chinese, Arabic, Russian and Japanese were also translated by a professional translation service. These translations were compared with the Google Translate texts and in cases of major discrepancies the translations were put before a native speaker with domain knowledge. In all cases, both the original answers and the most suitable translation are provided in the dataset, except where identifying information was removed from raw answers to guarantee anonymity (see above).\n\n\nObserved and expected biases in the data\n\nGiven the nature of the data collection we expect biases to be present in the data. The demographic data we collected can be used to both assess for biases (by comparing against known distributions within the target population) and overcome them, e.g. by zooming in during analyses. For instance, if the distribution over research roles seems not proportional, one could focus analysis on one group only. Where that is not viable raking is a statistical method that can be used to correct distributions, if the distribution in the overall population is known. Of course this only needs to be done if one suspects the variable at hand to be correlated with that distribution.\n\nTo check for regional bias we compared numbers of responses per country to the size of that country’s GDP4, which we took as a crude proxy for the number of researchers. Figure 4 depicts that bias. Measured thus, the Netherlands and some other small European countries are represented far above average and many West-African and Central and Southeast Asian countries way below average or not at all. Given their large absolute sizes, the low levels of response in countries such as China and Korea are noteworthy.\n\nBiases not directly related to the demographic parameters included in the survey will be harder to assess. For instance, we were unable to confirm whether there is bias along the degree to which people are interested in or concerned about scholarly communication issues.\n\n\nData description, data storage and sharing\n\nThe total size of both the raw and cleaned versions of the data is 20663 records and 178 variables, of which 162 for the tools questions and 16 for demographics and other general questions. File format is csv. These files with supplementary material are bundled into one zipped citable data set with DOI identifier.\n\nThe measurement level of the majority of the data is nominal (tools used, affiliation, role, discipline), in a few cases ordinal (indication of support for Open Access and Open Science) and only once interval (year ranges for year of first publication).\n\nFor permanent storage, the anonymized data are deposited in Zenodo under a CC-0 license. In addition, raw data will be stored for up to five years on secure Utrecht University servers for further analysis, with email information in files separate from the rest of the data.\n\nIn addition, we have made the data available through an interactive dashboard on Silk (http://dashboard101innovations.silk.co/) to enable quick visual exploration of the data.\n\n\nConsent\n\nThe research is subject to the code of conduct of the Dutch Association of Universities (VSNU)3.\n\n\nData availability\n\nZenodo: Global survey on research tool usage, doi: https://dx.doi.org/10.5281/zenodo.495831",
"appendix": "Author contributions\n\n\n\nBK and JB equally contributed to setting up, carrying out and reporting on the survey.\n\n\nCompeting interests\n\n\n\nDuring the runtime of the survey Jeroen Bosman accepted an invitation from the RIO Journal to become a subject editor. Bianca Kramer and Jeroen Bosman are both members of the steering committee of the Force11 Scholarly Communication Working Group. F1000Research was one of the partners that distributed the survey using a custom-URL.\n\n\nGrant information\n\nThe survey was supported by a €600 grant from the VOGIN-fonds for subscription to pro-versions of web tools used to distribute the survey and support the flow of data. Utrecht University Library provided the resources to have the survey and parts of the survey website translated into six languages and part of the foreign language answers translated back into English.\n\nWe confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe gratefully acknowledge support of 108 partners that agreed to distribute the survey among their constituency, as well as the people who generously spent time and effort in reviewing the translations and testing the survey implementation in their native language.\n\n\nSupplementary material\n\nSurvey questionnaire text and graphics, in English, Spanish, French, Chinese, Japanese, Russian and Arabic.\n\n\nReferences\n\nBosman J, Kramer B: Global survey on research tool usage. Zenodo. 2016. Data Source\n\nUNESCO: UNESCO science report - towards 2030. Paris: UNESCO, 2015. Reference Source\n\nVSNU: The Netherlands Code of conduct for academic practice. (revised edition 2014). Amsterdam: VSNU, 2014. Reference Source\n\nWorld Bank: GDP at market prices (current US$). Washington: World Bank, 2016. Reference Source"
}
|
[
{
"id": "14542",
"date": "28 Jun 2016",
"name": "Samuel Illingworth",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is an exceptionally well-designed survey, which was carried out professionally and effectively. The results of this survey will be incredibly useful for future researchers who want to gain an insight into current practices relating to innovations in scholarly communications.\n\nThe transparency of this data set, both upon completion and also throughout the collection period is commendable and is something that I would like to hold up as an example of best practice. The authors have worked tirelessly to ensure that this data set is of the greatest possible value to the wider research community. In particular, the use of the WordPress blog and the presentation of the final data set on Silk are processes that I would like to see repeated by others.\nI have only a couple of queries relating to the survey's design and implementation:\nWhat quota sampling strategy was used? In the Distribution of the survey; sampling\nsection the authors mention that quota sampling was used, but how was this done, which quotas were selected, and why were they chosen?\n\nIn the Translation of the survey section the authors mention that the Arabic survey did not include \"one additional question at the end of the survey on the use of tools targeting that specific language area,\" why was this the case?\nApart from these two small details, I would like to commend the authors on such an excellent dataset, which sets a very high standard from research design right through to dissemination of results. I am also very much looking forward to what future analysis of the data will reveal about current practices relating to innovations in scholarly communications.",
"responses": []
},
{
"id": "14417",
"date": "01 Jul 2016",
"name": "Isabella Peters",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors present a data note which aims at describing a data set by giving details on how data was collected and processed and which software or protocols were used, but which will not provide an analysis of the data, results, or conclusions.\nThe authors met these F1000Research requirements and, accordingly, describe the setup of the survey, give details on the sampling methods and ways of disseminating the survey request, and briefly introduce the distribution of responses. They also discuss the population, sample size and response rate as well as the completeness of responses and observed and biases in the data. Information on the post-hoc data processing (i.e., anonymization, cleaning, and harmonization of data) is also given. The data note finishes with a quantitative description of the data, how it is stored (i.e. openly on zenodo, as required by F1000Research), and how it can be accessed.\nOverall, the description of the data and the data processing is sound, seems to be reasonable, and as far as I can assess meet the standards of studies of that kind. The data generation is also suitable for investigations of usage of tools and the data set will serve the understanding of scholarly communication in the digital era in general and on social media in particular. Moreover, the data set cannot only answer if researchers use particular tools but also for what purposes or in what steps of the research cycle respectively.\nHowever, to get a more complete view on how the data has exactly been processed and collected, as well as to enhance repeatability of the study and to aid interpretation of results in later research making use of this data set I recommend adding information to following questions (which mostly refer to initial premises set by the authors of the survey and which have to been known in order to comprehend the processing steps that have been taken):\nActivities were selected from a database developed by the authors. How did you create the database – how did you find the entries? Could tool providers register themselves? How complete is it? Described activities in the survey were chosen for their overall importance/ the most well-known tools were selected as answers: How do you define “overall importance” and “most well-known”? How did you determine this selection? Can you provide evidence (even if this is a data note)? Have you taken into account disciplinary peculiarities? Was it possible to choose more than one tool as answer in the survey (adding up to answer numbers >100%)? Was it possible for participants to answer the survey more than once? Have you detected any bot-like behavior? Six obvious spam answers have been removed from the data set: can you give examples on what was considered spam?",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-692
|
https://f1000research.com/articles/5-682/v1
|
14 Apr 16
|
{
"type": "Research Article",
"title": "Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication?",
"authors": [
"Simon Imhof",
"Cristina Fragoso",
"Andrew Hemphill",
"Conrad von Schubert",
"Dong Li",
"Wesley Legant",
"Eric Betzig",
"Isabel Roditi",
"Simon Imhof",
"Cristina Fragoso",
"Andrew Hemphill",
"Conrad von Schubert",
"Dong Li",
"Wesley Legant",
"Eric Betzig"
],
"abstract": "Diverse structures facilitate direct exchange of proteins between cells, including plasmadesmata in plants and tunnelling nanotubes in bacteria and higher eukaryotes. Here we describe a new mechanism of protein transfer, flagellar membrane fusion, in the unicellular parasite Trypanosoma brucei. When fluorescently tagged trypanosomes were co-cultured, a small proportion of double-positive cells were observed. The formation of double-positive cells was dependent on the presence of extracellular calcium and was enhanced by placing cells in medium supplemented with fresh bovine serum. Time-lapse microscopy revealed that double-positive cells arose by bidirectional protein exchange in the absence of nuclear transfer. Furthermore, super-resolution microscopy showed that this process occurred in ≤1 minute, the limit of temporal resolution in these experiments. Both cytoplasmic and membrane proteins could be transferred provided they gained access to the flagellum. Intriguingly, a component of the RNAi machinery (Argonaute) was able to move between cells, raising the possibility that small interfering RNAs are transported as cargo. Transmission electron microscopy showed that shared flagella contained two axonemes and two paraflagellar rods bounded by a single membrane. In some cases flagellar fusion was partial and interactions between cells were transient. In other cases fusion occurred along the entire length of the flagellum, was stable for several hours and might be irreversible. Fusion did not appear to be deleterious for cell function: paired cells were motile and could give rise to progeny while fused. The motile flagella of unicellular organisms are related to the sensory cilia of higher eukaryotes, raising the possibility that protein transfer between cells via cilia or flagella occurs more widely in nature.",
"keywords": [
"protein transfer",
"membrane fusion",
"cell-cell communication",
"flagellum",
"cilium",
"Trypanosoma",
"lattice light sheet microscopy",
"structured illumination microscopy"
],
"content": "Introduction\n\nIntercellular bridges enabling the direct exchange of macromolecules between cells have been described in a diverse set of multicellular and unicellular organisms. These include plasmodesmata in plants, septal pores in fungi and gap junctions and tunnelling nanotubes in animal cells1–5. Plasmodesmata permit the transfer of transcription factors and mRNAs, triggering developmental programs in neighbouring cells6. In contrast, only small molecules up to 1 kDa can pass through gap junctions. Tunnelling nanotubes (TNT) are dynamic, ultrathin membranous structures that have been observed to form de novo when mammalian cells were mixed in culture5. They have been implicated in tissue repair, development and electrical coupling of cells and permit the transfer of whole organelles such as lysosomes or mitochondria, over distances up to several cell diameters7–11.\n\nRecently it was shown that green fluorescent protein (GFP) can be transferred from cancer cells to epithelial cells and it was postulated that this happens through a transient membrane fusion between the cells12. Intercellular bridges can also be hijacked by pathogens to infect new host cells. TNTs can be involved in the spread of HIV and prions, and plasmodesmata are used by several viruses to spread through the host plant13–15. Prokaryotes are also capable of direct exchange of macromolecules via intercellular bridges. Bacillus subtilis has been reported to exchange proteins and non-conjugative plasmids through TNT-like structures16. In addition, the social bacterium Myxococcus xanthus can exchange outer membrane proteins by transient outer membrane fusion17,18. In summary, targeted exchange of macromolecules by direct cell-cell contact seems to be a widespread in nature. To date, however, no intercellular bridges have been described in protozoa.\n\nTrypanosoma brucei is a unicellular eukaryote that causes human sleeping sickness and nagana in domestic animals. The parasite depends on tsetse flies for its transmission. Tsetse flies feed exclusively on mammalian blood and, in the process, can acquire parasites from infected hosts and transmit their progeny to new hosts. In the course of transmission, trypanosomes progress through several distinct life-cycle stages in the bloodstream of their mammalian host and in the alimentary tract of the fly (reviewed in 19). All life-cycle stages are extracellular and all are equipped with a single flagellum containing a canonical 9+2 axoneme and an extra-axonemal structure called the paraflagellar rod20. In addition to its function in motility, the trypanosome flagellum appears to serve as a sensory organelle21–23.\n\nTrypanosomes can interact with each other as well as with their hosts. In the mammalian bloodstream they extrude extracellular vesicles originating from the flagellar membrane; these can transfer virulence factors from one trypanosome strain to the other and contribute to trypanosome pathogenesis24. Bloodstream form trypanosomes also communicate with each other by a quorum-sensing mechanism that favours chronic infection and host survival25,26. Proliferative slender bloodstream forms release a soluble factor that promotes their differentiation to non-proliferative stumpy forms. The chemical identity of this factor is unknown, but it can be mimicked by cell-permeable cyclic AMP or AMP analogues25,27. Stumpy forms are pre-adapted to survive transmission to the tsetse fly and to differentiate to the next stage of the life cycle, the procyclic form, in the insect midgut28,29. Several years ago it was shown that procyclic trypanosomes exhibit social motility when cultured on a semi-solid surface, in a manner reminiscent of social swarming by bacteria30. This unexpected behaviour shows that procyclic trypanosomes also have the ability to communicate with each other, but the basis of this is largely unknown23. In order to complete transmission via the tsetse, parasites must migrate from the midgut to the salivary glands. This constitutes a population bottleneck and only very small numbers of trypanosomes make this transition31. Once in the glands the parasites attach to the salivary gland epithelium and proliferate as epimastigote forms32. Attachment is mediated by extensive outgrowths of the trypanosome flagellar membrane, which interdigitates between outgrowths of host epithelial cell membranes. The life cycle is completed by an asymmetric division in which one of the progeny is a metacyclic form that can be transmitted to a new mammalian host33.\n\nTrypanosoma brucei can undergo genetic exchange in the tsetse fly as a non-essential part of its life cycle34,35. Both interclonal and intraclonal mating have been reported34,36. Meiotic markers are expressed by trypanosomes in the salivary glands37 and flies co-infected with trypanosomes expressing either red or green fluorescent proteins can give rise to double-positive “yellow” cells in this compartment35. The current model of mating is that cells in the salivary glands undergo meiosis and produce haploid gametes that first interact via their flagella, then fuse together completely38, but the actual fusion event has not been visualised so far. We report here that procyclic form trypanosomes are able to fuse their flagellar membranes, resulting in the exchange of flagellar and cytoplasmic proteins. No transfer of nuclei or DNA was observed. Flagellar membrane fusion is a transient event and the cells lose the transferred fluorescent protein over time. We postulate that the direct protein transfer reported here is a new form of cell-cell communication and that the detection of double-positive trypanosomes in the fly may not always be related to genetic exchange. Furthermore, the relatedness of the trypanosome flagellum to cilia of higher eukaryotes raises the possibility that intercellular protein transfer by this mechanism might be more widespread in eukaryotic organisms.\n\n\nResults\n\nWe initially tagged trypanosomes with different colours in order to study genetic exchange in tsetse flies. For this purpose plasmids encoding different fluorescent proteins (GFP and DsRED) were integrated into defined loci on chromosomes 6 and 10 (see Materials and methods). When flies were co-infected with these tagged procyclic forms, we observed that the growth rates of individual clones differed and one clone/colour overgrew the other. To identify pairs with similar growth rates in culture, pairs of red and green procyclic forms were mixed and their relative numbers monitored by fluorescence microscopy. Unexpectedly, we observed that approximately 1% of the cells were positive for both fluorescent proteins and appeared yellow in merged images. After repeating this experiment several times we discovered that the transfer of cells to fresh medium with fresh FBS led to robust and reproducible production of yellow cells. While most yellow cells observed after 24 hours were single cells with no interacting partner, some were in intimate contact, forming characteristic pairs (Figures 1A & B). This is in contrast to dividing cells, which have two clearly separate flagella and joined posterior ends20. Yellow cells apparently connected by their anterior ends could also be observed (Figure 1C).\n\nA: Double-positive trypanosome after 24 hours co-culture (WT). B: Interacting double-positive trypanosome pair found after 24 hours co-culture (Δproc). C: Double-positive trypanosomes connected at their anterior ends (Δproc). The scale bar indicates 10μm. DsRed tends to accumulate in the nuclei of cells that synthesise it, probably because of its propensity to form tetramers.\n\nProcyclic form trypanosomes are covered by several million copies of glycophosphatidylinositol (GPI)-anchored surface glycoproteins known as EP and GPEET procyclins39. To see if these proteins were required for the formation of yellow cells we used a procyclin null mutant (Δproc;40) tagged with either GFP or DsRED. Mixed cultures of the mutant gave rise to double-positive cells at even higher frequencies than wild-type trypanosomes, reaching 5–7% of the population after 24 hours (Figure S1). No morphological differences could be observed between the procyclin knockout and wild-type parasites or the pairs that they formed. Because of the increased frequency of double-positive cells we used this mutant for some of the experiments reported here. Addition of the chelating agents EDTA or EGTA abolished the formation of yellow cells, indicating a requirement for extracellular calcium (Figure S1).\n\nSince yellow cells are used as a read-out for mating36,41, we initially thought that trypanosomes had undergone some form of genetic exchange, although this has never been documented for procyclic forms. The parasites were tagged with different selectable markers (rendering them resistant to blasticidin and G418, respectively), either at the same locus on the diploid copies of a chromosome or at different chromosomal loci. However, despite repeated attempts, we were never able to isolate genetic hybrids that were resistant to both drugs.\n\nTo better investigate how double-positive cells arose we performed time-lapse microscopy using wild-type trypanosomes expressing cytoplasmic DsRED or GFP, together with a GFP-tagged version of Histone 2B to visualize the nucleus. In order to track cells for extended periods we cultured them for 4 hours in medium without FBS, which causes them to adhere to the surface of the culture flask (see Materials and methods). These experiments revealed that the trypanosomes exchanged cytoplasmic proteins in both directions. The interacting cells became double positive within 10 minutes (the interval between images) and they could separate again (Figure 2, Video 1 and Video 2). Some cells stayed connected for more than 7 hours (Video 1), while others separated within 20 minutes (Video 2). Neither cell-cell fusion nor nuclear exchange was observed, arguing against this phenomenon being mating.\n\nStill images from time-lapse fluorescent microscopy of a mixed culture of wild type trypanosomes expressing Histone2B-GFP/cytosolic DsRED or Histone2B-GFP/cytosolic GFP. The time interval between images is indicated at the right corner of the image; the scale bar indicates 10μm; arrows indicate interacting cells. A: First image taken after one hour, the cells are clearly separate and only positive for one fluorescent protein in the cytoplasm. Second image 20 minutes later (1:20), cells are in contact and have become positive for DsRED and GFP. Third image, 7 hours and 20 minutes later (8:40), the cells have separated again. (Video 1) B: First image taken after 8 hours 50 minutes, cells are only positive for one fluorescent protein in the cytoplasm. Second image, cells have become double-positive (09:10). Third image, 20 minutes later the cells have separated again (09:30). (Video 2).\n\nIf proteins, but not DNA are exchanged between two cells, it would be expected that they lose one fluorescent protein once they separate. To test this we enriched for double-positive cells and monitored how long they retained both colours. After one round of FACS 26% of trypanosomes in the culture were double-positive (Figure 3). Cells expressing GFP only were sorted as a control. Cell numbers and the percentage of yellow cells were determined every day. While the cell number more then doubled within the first 24 hours, the percentage of yellow cells decreased only slightly, indicating that the yellow cells still proliferated and were not simply overgrown by single positive cells (Figure 3). After 3 days, however, the percentage of yellow trypanosomes returned to background level, consistent with turnover of the transferred proteins.\n\nA: Growth curve of Δproc yellow cells after FACS and Δproc GFP cells after FACS. B: Double-positive Δproc cells were enriched by FACS and the percentage of yellow cells was measured by flow cytometry at daily intervals.\n\nThe experiments described above show that procyclic form trypanosomes are capable of exchanging soluble proteins that are mainly present in the cytoplasm. To test whether surface proteins could also be exchanged we first used cells tagged with a GFP-procyclin fusion protein. In trypanosomes, newly synthesised GPI-anchored proteins gain access to the cell surface via the flagellar pocket. This is an invagination of the plasma membrane where the flagellum emerges from the cell body, and is the only known site of endo- and exocytosis. On exiting the pocket GPI-anchored proteins are distributed along the flagellum to the cell surface42. In cells expressing GFP-procyclin the flagellar pocket is seen as an intensely fluorescent signal (Figure 4A). When trypanosomes expressing cytoplasmic DsRED and GFP-procyclin were mixed together, we observed that DsRED was equally distributed between two interacting cells, but GFP-procyclin was only transferred to the flagellum of the recipient and not the rest of the cell surface (Figure 4A). These results indicate that proteins on the outer leaflet of the plasma membrane can be transferred between cells, but transfer appears to be restricted to the flagellum.\n\nA: Interacting pair of trypanosomes expressing either DsRED (Δproc) or the GPI anchored surface protein EP-GFP (WT). B: Interacting pair of trypanosomes expressing the flagellar protein calflagin44-GFP (WT) or calflagin44-Cherry (WT). C: Interacting pair of trypanosomes expressing either cytoplasmic DsRED (Δproc) or the nucleoside transporter NT10-GFP (WT), which localises to the surface of the cell body, but not to the flagellum. The scale bar indicates 10μm.\n\nCalflagin-44 is an acylated protein that is anchored to the flagellar membrane43. To obtain more information on the involvement of the flagellum we generated stable transformants expressing calflagin-GFP and calflagin-mCherry fusion proteins. These were correctly localised to the flagellum, but the protein was sometimes also detected in the cell body, possibly due to its overexpression. When trypanosomes expressing calflagin-GFP and calflagin–mCherry were co-cultured, interacting pairs had both proteins in their flagella, but calflagins in the cell bodies were not exchanged (Figure 4B). Based on these results we hypothesised that surface proteins that were excluded from the flagellum would not be exchanged. To test this we mixed cells expressing DsRED with trypanosomes expressing a GFP-tagged version of the nucleoside transporter NT10, which is restricted to the cell body44. Interacting pairs from this mixture had DsRED distributed equally between the two cells while NT10-GFP remained only on one cell (Figure 4C and Figure S2). Taken together, these data suggest that the flagellum is the primary site of interaction and protein exchange. In this context it is important to note that soluble GFP and DsRED are able to cross the diffusion barrier of the flagellar transition zone and are therefore present in the flagellar matrix as well as in the cytoplasm.\n\nRNA-binding proteins play a major role in regulating gene expression in trypanosomes. They can alter the stability or translational efficiency of individual mRNAs or mRNA cohorts45, or they can silence them by RNA interference46. To test if RNA-binding proteins could be exchanged between cells we used a tagged form of Argonaute (Ago) with GFP fused to its N-terminus (GFP-Ago). Cytoplasmic proteins >75kDa are normally excluded from flagella and cilia unless they contain targeting signals47–49. One rationale for choosing the GFP-Ago fusion was that the protein is 130 kDa and should therefore require active transport; the second rationale was that it is a catalytic component of the RNA-induced silencing complex. When cells expressed GFP-Ago, the protein was detected in the flagellum as well as in the cytoplasm (Figure 5A). Moreover, when these cells were mixed with cells expressing DsRED, bidirectional exchange of both proteins was observed (Figure 5B). In summary, trypanosomes have the capacity to transport Ago into the flagellum and to transfer it to another cell. This transfer could potentially reprogram gene expression in the recipient cell by transferring small interfering RNAs.\n\nA: Fluorescence microscopy of wild-type cells expressing GFP-Ago. B: Fluorescence microscopy of co-cultured wild-type cells expressing DsRED or GFP-Ago. Scale bars indicate 10μm.\n\nTo investigate protein exchange with higher temporal resolution, we performed time-lapse imaging with a lattice light sheet microscope50 using an image acquisition interval of one minute. Again we mixed trypanosomes expressing cytoplasmic GFP or calflagin-mCherry. The exchange of calflagin-mCherry occurred in less than a minute (Figure 6), while it took approximately 2–3 minutes until GFP was equally distributed between two cells (Figure 6 and Video 3). These experiments further demonstrated that interacting pairs were still moving, indicating that the motility function of the flagellum was not impaired (Video 3). Furthermore, complete divisions of interacting cells could be observed (Video 4). While some interacting trypanosomes stayed together for an extended period of time, other interactions were very transient. The shortest interaction we observed was for 1–2 minutes (Video 5).\n\nStill images from lattice light sheet fluorescence microscopy time-lapse video (Video 3) of trypanosomes expressing either GFP (Δproc) or calflagin44-mCherry (WT). The time interval is indicated at the left upper corner of the image. The scale bar is 10μm. First image (00:10): cells are only positive for one fluorescent protein. Second image one minute later (00:11), calflagin44-mCherry is present on both cells, but GFP is detected only weakly in the second cell. Third image: two minutes later (00:13), GFP is equally distributed in both interacting cells.\n\nThe fact that trypanosomes exchange proteins anchored to the outer surface of the flagellar membrane (EP procyclin) or the inner surface (calflagin), suggested either fusion of these membranes or a short-range exchange of vesicles had taken place. To distinguish between these possibilities we performed electron microscopy (EM). Since only a few percent of a mixed population is double-positive, and only some of the cells interact at a given time-point, we again enriched for yellow cells by FACS. Using scanning EM we observed the same characteristic pairs of trypanosomes seen by fluorescence microscopy (Figure 7A). The flagella of these pairs appeared thicker than the flagella of single cells, which could be compatible with fusion along their entire length. From these images alone, however, we could not conclude unambiguously that the membranes were fused; it remained possible that they were merely in very close contact. To better characterise the interaction between flagellar membranes we performed transmission EM (Figure 7B and Figure S3). These images demonstrated unequivocally that pairs of cells shared a flagellum with two axonemes and two paraflagellar rods bounded by a single membrane (Figure 7B and Figure S3A). This differs from what happens during cell division, in which the trypanosomes produce a separate new flagellum posterior to the old one. Thus, the most plausible explanation is that the two flagella have fused. We also documented examples of triple and quadruple fusions (Figures S3B & S3C), albeit at a much lower frequency.\n\nA: Scanning electron microscopy of interacting trypanosomes (Δproc). The scale bar indicates 10μm. B: Transmission electron microscopy of fused flagella (Δproc). The scale bar indicates 0.5μm for the upper image and 1.5μm for the lower image; arrows indicate the cell-body (CB) and the flagellum (F). C: Structured illumination microscopy (SIM) of interacting trypanosomes with fused flagella. Trypanosomes were tagged with either DsRED (Δproc) or calflagin44-GFP (WT). The scale bar indicates 10μm.\n\nStructured Illumination Microscopy (SIM) provides a resolution doubling when compared to diffraction limited imaging and complements scanning EM data by delivering information on protein exchange. We therefore applied this method to co-cultures of trypanosomes expressing cytoplasmic DsRED or calfalgin-GFP. This confirmed that large parts of the flagella fuse into a single structure in double-positive cells (Figure 7C). Once again, fusion of multiple cells could be observed (Figure S4A). Pairs with a second flagellum forming on one cell, double-positive cells undergoing cytokinesis and fused cells giving rise to daughter cells were also seen (Figures S4B & C). Taken together, these data suggest that flagellar fusion is a guided process that is part of normal cell functions.\n\n\nDiscussion\n\nOur results demonstrate that procyclic culture form trypanosomes can use their flagella as conduits for exchanging proteins with other individuals in a population. Cells that become double-positive for GFP and DsRED revert to being single-positive over a period of 72 hours, in agreement with the observation that no DNA is transferred and that these cells are not genetic hybrids. Protein exchange entails fusion of the flagellar membrane, which can be partial or along the entire length. In common with the fusion of plasma membranes between myoblasts51 or of synaptic vesicles with the plasma membrane of neurons in multicellular organisms52, flagellar fusion in trypanosomes is calcium-dependent.\n\nProtein exchange between trypanosomes is bidirectional and can occur in under a minute. This limit of temporal resolution in our experiments was dictated by the need to capture many fields of view in order to observe rare fusion events in a population across time. There are several indications that flagellar fusion does not impair cell function and that it can be reversed. Live imaging revealed that paired cells are motile; pairs can remain together for hours, and even give rise to progeny while in this state, or they can separate within a minute. Thus, the double-positive cells observed 24 hours after mixing could be the result of a transient fusion or they could be daughter cells of previously fused trypanosomes.\n\nWild-type cells that are double-positive usually occur at extremely low frequencies in co-cultures (≈1%), implying that only a small proportion of the population is fusion competent at any one time. These numbers might be an under-estimate, however, if interactions are more fleeting and less protein is transferred between cells. Furthermore, protein exchange between two green cells or two red cells would not be detected. The percentage of double-positive cells increased when cells were washed and supplied with fresh serum, suggesting that factors that inhibit fusion accumulate in the medium. It is not clear whether both cells need to be in a fusion-competent state or if one cell suffices. In the course of live imaging we noted that paired cells seemed to attract additional cells to fuse (Video 1) and examples of 3 or more fused flagella were observed by transmission EM and SIM (Figure S3 and Figure S4). Many proteins, including several potential signal transducers, are localized to different flagellar domains22,53. The Δproc mutant fused more readily than the wild type, which might reflect increased accessibility of components on the flagellar surface. Extracellular vesicles produced by bloodstream form trypanosomes have a sparser variant surface glycoprotein coat than the cell surface, and it was hypothesised that this might influence their fusogenic properties24.\n\nThe trypanosome flagellum has a different lipid and protein composition than the cell body, providing a certain selectivity of exchanged proteins21,53,54. Both soluble and membrane-associated proteins can be translocated between cells provided that they gain access to the flagellum. In contrast, a polytopic membrane protein that is restricted to the surface of the cell body is not transferred between trypanosomes. Although we do not know why trypanosomes exchange cell contents, several possibilities spring to mind. Direct transfer would prevent proteins being diluted or destroyed in the extracellular milieu and might also prevent activation of an antimicrobial response by the host. Sampling each other's proteins and metabolites might enable cells within a population to synchronise. Alternatively, healthy cells might rescue damaged or stressed cells by providing missing components. In this context, two recent publications have shown that tight cell-cell interactions55 or nanotubes56 can enable two bacterial species to exchange missing nutrients. Although double-positive cells seem to proliferate normally after protein exchange, implying that the interaction is relatively benign, we cannot exclude that this mechanism is used by one trypanosome to exploit resources of the other or even to deliver harmful cargo to a competing cell. A further possibility is that exchange might deliver signals for differentiation. Even if protein exchange is transient, it might be sufficient to reprogram the recipient cell. For example, it was shown that inducing expression of a single RNA-binding protein, RBP6, in procyclic (midgut) forms is enough to drive their differentiation to the life-cycle stages normally found in the salivary glands57.\n\nThe flagellar proteome of procyclic forms of T. brucei contains a variety of metabolic enzymes, peptidases, heat shock proteins and RNA-binding proteins, all of which have the potential to be exchanged upon fusion53. It has not been established whether mRNA is present in the flagellum, but poly(A)-binding protein 1 has been detected in the flagellar proteome53. Furthermore, when Ago is exchanged between cells, small interfering RNAs (siRNAs) might be carried over as cargo. At present, however, siRNAs cannot be visualised directly by in situ hybridisation, because of issues with sensitivity and specificity.\n\nTo date, we have not detected double-positive procyclic (midgut) forms in tsetse flies. GFP and its derivatives appear to be mildly toxic for procyclic forms in vivo and trypanosomes expressing it are often overgrown during co-infections40. This could potentially bias the outcome. It is also possible that we observe an extreme form of flagellar fusion in culture and that many interactions between procyclic forms might be too brief and the amount of exchanged protein too low to be detected unequivocally in vivo. Double-positive trypanosomes definitely occur in the salivary glands of tsetse, and have been construed as evidence of mating35,36,41. The expression of meiotic markers by trypanosomes in the glands37 makes it highly likely that this is indeed the site where genetic hybrids form. Nevertheless, several factors make it challenging to distinguish between mating and protein exchange. Since salivary gland forms of T. brucei cannot be cultured, it is impossible to follow double-positive cells over a longer period of time to monitor loss or retention of fluorescent proteins. The low frequency of mixed salivary gland infections and low abundance of yellow cells also make these studies extremely labour intensive. Several previous observations could indicate that a proportion of double-positive cells in the fly are not genetic hybrids. The current model of genetic exchange in trypanosomes involves meiosis and the formation of haploid gametes, which subsequently fuse together38. When flies were co-infected with cells coding for the meiotic marker HOP1 fused to YFP and cells expressing mRFP, trypanosomes positive for both proteins could be detected, indicating that protein exchange occurred before the formation and fusion of gametes (as also mentioned by the authors of the study;37). Double-positive Leishmania major cells have also been detected during co-infections of sand flies, which again has been taken as evidence of genetic exchange58. It was not possible to isolate their progeny, however, and an alternative explanation might be that these cells had only exchanged proteins, but not DNA.\n\nThe list of functions attributed to flagella, in addition to motility, is constantly expanding. Nanotubular structures budding from the flagellar membrane of bloodstream form trypanosomes give rise to extracellular vesicles that are able to transfer proteins between cells24. Protein transfer by extracellular vesicles might reflect a broader form of communication within the trypanosome population, while the protein exchange by flagellar fusion described here could be used for direct, contact-dependent communication between two cells. In addition ectosomes released from the flagella of Chlamydomonas rheinhardtii enable daughter cells to hatch from their mother cell59. The flagella of T. brucei, Leishmania spp, and Chlamydomonas are related to the cilia of higher eukaryotic cells and many proteins involved in intraflagellar transport (IFT) are conserved60. IFT seems to have additional functions that extend to cells without cilia; it has been linked to exocytosis61, and IFT proteins have been localised to the synapse between T cells and antigen-presenting cells62. Very recently a new type of microtubule-based nanotube was described63; this is dependent on IFT proteins for its function in the Drosophila germline. It was proposed that this structure provides selectivity for receptor-ligand interactions, but it was not reported whether membrane fusion occurred or if proteins were transferred from one cell to the other. In this context it is worth noting that attachment of trypanosomes in the salivary glands involves remodeling of both the host epithelial membranes and the parasite flagellar membrane, indicating that the flagellum may be capable of transmitting and receiving signals to and from the host cells. We consider it worth exploring if other flagellated parasites, as well as the sensory cilia of higher eukaryotes also possess the ability to mediate protein exchange between cells.\n\n\nMaterials & methods\n\nUnless otherwise specified, chemicals were obtained from Sigma-Aldrich, Switzerland. Oligonucleotide primers were synthesised by Microsynth AG (Balgach, Switzerland). Enzymes were purchased from New England Biolabs.\n\nProcyclic forms of T. b. brucei AnTat 1.164 and genetically manipulated derivatives were used in this study. The deletion mutant Δproc40 was described previously. Trypanosomes were cultured at 27°C in SDM-79 (Amimed, Cat. No. 9-04V01M) supplemented with 10% heat inactivated foetal bovine serum65.\n\nConditions for double-positive cells: 5 × 106 cells expressing DsRED were mixed with 5 × 106 cells expressing GFP and centrifuged at 1300g for 6 minutes in a 15ml Falcon tube. The cells were resuspended in 10ml phosphate-buffered saline and centrifuged again. The washed trypanosomes were resuspended in 2.5ml SDM-79 with 10% fresh FBS and cultured overnight at 27°C in one well of a six-well plate. The cells tend to adhere weakly to the bottom of the well, so before analysis they were gently flushed loose with a 1ml pipette.\n\nStable transformation of procyclic form trypanosomes was performed as described66. To clone the plasmids pG-EGFP-Blast-ΔLII and pG-DsRED-Blast-ΔLII, pG-EGFP-ΔLII67 and pG-DsRED-ΔLII68 were digested with the restriction enzymes NheI and ClaI to cut out the neomycin resistance gene. The blasticidin resistance gene was amplified by PCR using the primers NheIBlast (GCTAGCTAGCATGGCCAAGCCT) and ClaBlast (CCATCGATACTCACAGCGACTA) and pC-EP2-ΔLII-Blast as template40 the product was digested with NheI and ClaI and ligated into pG-EGFP-ΔLII and pG-DsRED-ΔLII.\n\nThe mCherry coding region was amplified by PCR using the plasmid CWP1:mCherry (a gift from Adrian Hehl, Zürich University) as a template and the primers mCherryfor (TTACCGGTCATGGTGAGCAAGGGCG) and mCherryrev (TTGGATCCCGGGCTTGTACAGCTCGTCCATG). The PCR product was digested with BamHI and AgeI and ligated into BamHI/AgeI digested pG-EGFP-ΔLII, replacing EGFP by mCherry. To change the selectable marker of pG-mCherry-ΔLII from neomycin-resistance to phleomycin-resistance the plasmid G-BIL4-phleo was digested with XbaI and NotI to excise the phleomycin resistance gene. The phleomycin resistance gene was then ligated into the XbaI/NotI-digested pG-mCherry-ΔLII.\n\nTo tag Calflagin44 at its C-terminus with EGFP or mCherry, the coding region of Cal44 was amplified by PCR using the primers Cal44for (ATAAGCTTATGGGTTGCTCTGCATCG) and Cal44rev (ATGTCGACGATTACCTTCATTTGCTCC) and genomic DNA as the template. The PCR product was cloned into the pGEM-T Easy Vector System (Promega), subsequently excised with HindIII and SalI, then ligated into HindIII/SalI digested pG-EGFP-Blast-ΔLII and pG-mCherry-Phleo-ΔLII. To tag Ago1 at its N-terminus the Ago1 coding region was amplified by PCR using the primers Ago1SmaFor (CCCGGGATGTCTGACTGGGAAC) and Ago1SmaRev (CCCGGGTTATAGATAATGCATTGTTG) and the product was cloned into the pGEM-T Easy Vector System (Promega). The plasmids pGEM-Ago1 and pG-EGFP-ΔLIIγ69 were digested with the restriction enzyme SmaI and the coding region of Ago1 was ligated into pG-EGFP-ΔLIIγ, correct integration was confirmed by sequencing.\n\nThe constructs pG-H2B-GFP-ΔLII and pG-NT10-GFP-ΔLII were described previously44,69.\n\nCells were washed in phosphate buffered saline (PBS), spread on a microscope slide and mounted with Moviol. Images were taken with a Leica DFC360FX monochrome CCD (charge-coupled-device) camera mounted on a Leica DM5500 B microscope with a 100x oil immersion objective and analysed using LAS AF 1.0 software (Leica).\n\nStructured illumination microscopy (SIM) was performed as described in 70. Cells were fixed for 20 minutes at room temperature with 4% paraformaldehyde and 0.5% glutaraldehyde. For each axial plane of a 3D stack, raw SIM images were acquired at five phase steps spaced by 2π/5 of the illumination pattern period, and this process was repeated with the excitation pattern rotated by ±120° with respect to the first orientation. The axial stepping size was set to 160 nm. The raw data was reconstructed into the 3D super-resolution image based on the algorithm described in 71. In our study, when the result was Fourier transformed back to real space, we applied a gamma apodization function A(k)=1–(k/kmax)γ, with γ = 0.4, rather than the traditional triangle apodization A(k)=1–k/kmax71, where kmax is the maximum support of the expanded optical transfer function (OTF). Therefore, the higher spatial frequencies were not suppressed more than necessary. Furthermore, we strictly follow the azimuthally dependent maximum support kmax(θ) to define the endpoint of the apodization function. All of these provided a better suppression of the ringing artifacts associated with Fourier transformation. After reconstruction, SIM images achieve 110 nm lateral, 350 nm axial resolution.\n\nTrypanosomes (Δproc) expressing either DsRED or GFP were washed in PBS and co-cultured in SDM-79 with 10% fresh FBS for 8 hours at a density of 107 cells/ml. Then the cells were transferred into PBS containing 2% FBS at a density of 1.5×107 cells/ml for sorting. Sorting was performed with a BD FACS ARIA III (BD Biosciences) equipped with a 130μm nozzle running with 10 psi pressure, flow liquid was PBS. The software used was BD FACS DIVA 6.0 (BD Biosciences). To detect GFP a 488nm blue laser with a 530/30nm bandpass filter was used, to detect DsRED a 561 yellow-green laser with a 610/20 bandpass filter was used. Double-positive cells were sorted into SDM-79 10% FBS.\n\nFlow cytometry was performed with living cells in PBS, 104 cells were analysed using a FACSCalibur (BD Biosciences) and analysed with CellQuest Pro (version 5.1.1).\n\nTransmission electron microscopy. Trypanosomes were washed briefly in PBS, then fixed in 2.5% glutaraldehyde in 100 mM sodium cacodylate buffer (pH7.3) for 2 hours at room temperature, followed by post-fixation in 2% OsO4 in cacodylate buffer, pH 7.3. After three washes in distilled water, samples were pre-stained in saturated uranyl acetate solution in distilled water for 30 min at room temperature, extensively washed in distilled water, and dehydrated by stepwise incubation in ethanol (30%-50%-70%-90%-100%). Parasites were then embedded in EPON812 resin as described previously72. Following polymerisation of the resin at 60°C for 24 h, sections of 80 mm thickness were cut on a ultramicrotome (Reichert & Jung, Vienna, Austria), placed onto 300 mesh formvar-carbon-coated nickel grids (Plano, Wetzlar, Germany), and sections were stained with uranyl acetate and lead citrate40. Specimens were viewed on a Phillips 400 TEM operating at 60 kV.\n\nScanning electron microscopy. Trypanosomes were washed briefly in PBS, then fixed in 2.5% glutaraldehyde in 100 mM sodium cacodylate buffer, pH 7.3, for 2 hours at room temperature, followed by post-fixation in 2% OsO4 in cacodylate buffer, pH 7.3. They were then extensively washed in water, dehydrated by stepwise incubation in ethanol (30%-50%-70%-90%-100%), and two short washes in 50µl hexamethyl-disilazane. Trypanosomes were then taken up in a small volume of hexamethyl-disilazane, and were allowed to settle down on glass coverslips and were air-dried under a fume hood. They were then sputter-coated with gold73 and inspected on a JEOL 840 scanning electron microscope operating at 25 kV.\n\nTo immobilise the trypanosomes approximately 3×106 cells of each clone were mixed and centrifuged for 6 minutes at 1300g. The cell pellet was washed with 10 ml PBS and centrifuged again using the same parameters as above. The cells were resuspended in 1 ml SDM-79 without FBS and incubated for 4 hours at 27°C in a glass bottom culture dish (Willco Wells, the Netherlands). During this time the trypanosomes adhered to the bottom of the dish and were immobilised. After 4h 100μl FBS was added to the cells and the time-lapse imaging was started immediately using a Nikon TE2000E-PFS microscope with a 60x objective. DIC and fluorescent images were taken every 10 minutes for 24 hours.\n\nThe 4D lattice light sheet measurements were performed using a microscope described previously50. This system illuminates the sample with a massively parallel array of coherently interfering beams comprising a non-diffracting 2D optical lattice. This creates a coherent, spatially structured light sheet that is then dithered to create uniform excitation in a ~600 nm thick plane across the entire field of view. In order to capture the statistically rare fusion events in trypanosome samples, 3D images were acquired from 15 fields of view every 60 seconds for a total duration of 9h12min. Raw data were deconvolved via a 3D iterative Lucy-Richardson algorithm in Matlab version 2013b (The Mathworks, Natick, MA) utilizing an experimentally measured point spread function using 100 nm fluorescent beads (Fluospheres, ThermoFisher Cat #: F8803). Movies were generated using ImageJ (Version 1.49m).\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for Figure 1, 10.5256/f1000research.8249.s12006774\n\nClick here to access the data.\n\nF1000Research: Dataset 2. Raw data for Figure 4, 10.5256/f1000research.8249.s12006875\n\nClick here to access the data.\n\nF1000Research: Dataset 3. Raw data for Figure 5, 10.5256/f1000research.8249.s12006976\n\nClick here to access the data.\n\nF1000Research: Dataset 4. Raw data for Figure 7C, 10.5256/f1000research.8249.s12007077\n\nClick here to access the data.\n\nF1000Research: Dataset 5. Raw data for Figure S2, 10.5256/f1000research.8249.s12007178\n\nClick here to access the data.\n\nF1000Research: Dataset 6. Raw data for Figure S4, 10.5256/f1000research.8249.s12007279\n\nClick here to access the data.\n\nF1000Research: Dataset 7. Raw data for Video 1, 10.5256/f1000research.8249.s12007580\n\nClick here to access the data.\n\nF1000Research: Dataset 8. Raw data for Video 2, 10.5256/f1000research.8249.s12007781\n\nClick here to access the data.\n\nAccess to additional time-lapse imaging data may be arranged by contacting the corresponding author.\n\nFigshare: Time-lapse imaging of wild-type trypanosomes expressing histone 2B-GFP together with cytosolic GFP or DsRED. doi: 10.6084/m9.figshare.3126292.v182\n\nFigshare: Time-lapse imaging of wild-type trypanosomes expressing histone 2B-GFP together with cytosolic GFP or DsRED. doi: 10.6084/m9.figshare.3126352.v183\n\nFigshare: Time-lapse imaging of trypanosomes expressing cytoplasmic GFP (Δproc) or calflagin-mCherry (WT). doi: 10.6084/m9.figshare.3126355.v184\n\nFigshare: Time-lapse imaging of trypanosomes expressing cytoplasmic GFP (Δproc) or calflagin-mCherry (WT). doi: 10.6084/m9.figshare.3126412.v185\n\nFigshare: Time-lapse imaging of trypanosomes expressing cytoplasmic GFP (Δproc) or calflagin-mCherry (WT). doi: 10.6084/m9.figshare.3126415.v186",
"appendix": "Author contributions\n\n\n\nConceived and designed the experiments: SI CF IR EB\n\nPerformed the experiments: SI, CF, CvS, AH, LD WL\n\nAnalysed the data: SI, CF, IR\n\nWrote the paper: IR, SI\n\n\nCompeting interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nWork in IR’s laboratory was funded by the HHMI Senior International Scholars Program (grant no. 55007650), the Swiss National Science Foundation (grant no. 31003A-144142) and the Canton of Bern. WRL, DL and EB are funded by the Howard Hughes Medical Institute. We also gratefully acknowledge the Janelia Research Campus visitor program.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nArunasalam Naguleswaran, Gaby Schumann and Kent Hill are thanked for reading the manuscript and for providing insightful comments.\n\n\nSupplementary material\n\nhttps://f1000researchdata.s3.amazonaws.com/supplementary/8249/c7baea27-e89b-4015-8f61-7e2053237bb7.docx.\n\nFigures S1, S2, S3 and S4.\n\n\nReferences\n\nLucas WJ, Ham LK, Kim JY: Plasmodesmata - bridging the gap between neighboring plant cells. Trends Cell Biol. 2009; 19(10): 495–503. PubMed Abstract | Publisher Full Text\n\nGoodenough DA, Paul DL: Gap junctions. Cold Spring Harb Perspect Biol. 2009; 1(1): a002576. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJedd G, Pieuchot L: Multiple modes for gatekeeping at fungal cell-to-cell channels. Mol Microbiol. 2012; 86(6): 1291–1294. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nUrwyler S, Studer E, Renggli CK, et al.: A family of stage-specific alanine-rich proteins on the surface of epimastigote forms of Trypanosoma brucei. Mol Microbiol. 2007; 63(1): 218–228. PubMed Abstract | Publisher Full Text\n\nHaenni S, Renggli CK, Fragoso CM, et al.: The procyclin-associated genes of Trypanosoma brucei are not essential for cyclical transmission by tsetse. Mol Biochem Parasitol. 2006; 150(2): 144–56. PubMed Abstract | Publisher Full Text\n\nBurkard G, Fragoso CM, Roditi I: Highly efficient stable transformation of bloodstream forms of Trypanosoma brucei. Mol Biochem Parasitol. 2007; 153(2): 220–223. PubMed Abstract | Publisher Full Text\n\nFiolka R, Shao L, Rego EH, et al.: Time-lapse two-color 3D imaging of live cells with doubled resolution using structured illumination. Proc Natl Acad Sci U S A. 2012; 109(14): 5311–5315. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGustafsson MG, Shao L, Carlton PM, et al.: Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination. Biophys J. 2008; 94(12): 4957–4970. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRuepp S, Furger A, Kurath U, et al.: Survival of Trypanosoma brucei in the tsetse fly is enhanced by the expression of specific forms of procyclin. J Cell Biol. 1997; 137(6): 1369–1379. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHemphill A, Croft SL: Electron Microscopy in Parasitology. In Analytical Parasitology, M.T. Rogan, ed. (Springer Berlin Heidelberg), 1997; 227–268. Publisher Full Text\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 1 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 2 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 3 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 4 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 5 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 6 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 7 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Dataset 8 in: Flagellar membrane fusion and protein exchange in trypanosomes; a new form of cell-cell communication? F1000Research. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Time-lapse imaging of wild-type trypanosomes expressing histone 2B-GFP together with cytosolic GFP or DsRED. Figshare. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Time-lapse imaging of wild-type trypanosomes expressing histone 2B-GFP together with cytosolic GFP or DsRED. Figshare. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Time-lapse imaging of trypanosomes expressing cytoplasmic GFP (Δproc) or calflagin-mCherry (WT). Figshare. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Time-lapse imaging of trypanosomes expressing cytoplasmic GFP (Δproc) or calflagin-mCherry (WT). Figshare. 2016. Data Source\n\nImhof S, Fragoso C, Hemphill A, et al.: Time-lapse imaging of trypanosomes expressing cytoplasmic GFP (Δproc) or calflagin-mCherry (WT). Figshare. 2016. Data Source"
}
|
[
{
"id": "13386",
"date": "26 Apr 2016",
"name": "Scott M. Landfear",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article by Imhof et al. describes the unanticipated and intriguing observation that flagella of procyclic form African trypanosomes are capable of fusing and exchanging both membrane bound and cytosolic proteins between the interacting cells. Flagellar fusion occurs in ~1% of cells under normal culture conditions, but fusion can be increased up to ~5% of the population with appropriate manipulations. For proteins to be transferred from one cell to the next, they must have access to the flagella. A nucleoside transporter that is localized to the cell body but not flagellar membrane is not transferred, whereas proteins bound to the inner our outer face of the flagellar membrane, or non-membrane proteins, can be transferred. Striking transmission electron micrographs are shown in which two or more flagella are fused, and the corresponding axonemes and paraflagellar rods are encompassed within a single flagellar membrane. Fusion of trypanosomes expressing two different fluorescently labeled proteins can occur within 1 minute of mixing and can persist for minutes or for hours. Parasites fused by their flagella remain motile and are able to undergo cell division, producing two daughter cells that are both dually labeled. This phenomenon is clearly distinct from mating-associated fusion that has been observed in tsetse fly salivary gland stage trypanosomes, because the cell bodies and nuclei do not merge during flagellar fusion, but they do fuse during mating. As the authors discuss, the major mystery is what purpose this behavior serves for parasites. While the phenomenon has been observed only in culture, it seems likely that the process will also occur in trypanosomes within tsetse flies. Furthermore, recent reports in both trypanosomes and other eukaryotes have underscored the role of the flagellum in transfer of proteins and membranes between cells. Recently, blood stream trypanosomes have been shown to secrete tubules and vesicles that can fuse with host red blood cells, and Chlamydomonas reinhardtii release from their flagellar tips vesicles that carry protein cargo. Thus flagella play a variety of biological roles, many involving the flagellar membranes, that were not anticipated even a few years ago. This paper raises the prospect that flagella and cilia in various organisms may be involved in directed exchange of proteins and should alert the scientific community to another possible broader function of these organelles. Minor Points. In Video 2, one of the cells that has undergone exchange of the two fluorescently labeled proteins acquires 4 nuclei without undergoing division. Do the authors see other examples of this phenomenon, and do they have any comments about this behavior?",
"responses": []
},
{
"id": "13625",
"date": "28 Apr 2016",
"name": "Peter Satir",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article describes an interesting, transient interaction between flagella (cilia) of procyclic Trypanosomes, involving exchange of flagellar membrane and cytosolic molecules that can enter the flagellum, that can form quickly and last for some time, sometimes resulting in fusion of the two flagella. Experimental evidence for this phenomenon is shown by mixing populations of cells containing plasmids that produce different fluorescently labelled molecules (GFP and Ds RED) of interest. Originally a few yellow fluorescing cells were seen – indicative of interaction. The system was then refined for study by time lapse and electron microscopy. The data are well presented. The demonstration that molecules that cannot enter the flagellum are not transferred (Figure 4) is particularly nice. There is a suggestion that small RNAs could be transferred which might give the phenomenon added significance. The authors also suggest that this could be a new, more general, means of cell communication involving cilia. It is different from usual ciliary pairing well studied during mating reactions, for example in Tetrahymena or Euplotes. Mating of course eventually involves intercellular bridges in protozoa, so the sentence in the introduction that states that no intercellular bridges are known in protozoa is not correct. In broadening their discussion to mammalian and other cilia, the authors might note the work of Ott et al. (2012) (see also Jackson’s gloss) on MDCK and other cells, which also describes cilia pairing, possibly for communication, but without fusion. It would be useful to know how the cells here separate after flagellar fusion.The videos of the experiments are mostly useful in dynamically emphasizing the points made in the Figs, although some (i.e. Video 3) can be hard to follow. The previous reviewer commented on Video 2 where a cell ends up 4 nuclei – actually nuclei of both interacting cells divide (one begins with two nuclei) although the cells themselves do not. Could this be important?These few discussion points should add to the interest of this article.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-682
|
https://f1000research.com/articles/5-675/v1
|
13 Apr 16
|
{
"type": "Review",
"title": "The big challenges in modeling human and environmental well-being",
"authors": [
"Shripad Tuljapurkar"
],
"abstract": "This article is a selective review of quantitative research, historical and prospective, that is needed to inform sustainable development policy. I start with a simple framework to highlight how demography and productivity shape human well-being. I use that to discuss three sets of issues and corresponding challenges to modeling: first, population prehistory and early human development and their implications for the future; second, the multiple distinct dimensions of human and environmental well-being and the meaning of sustainability; and, third, inequality as a phenomenon triggered by development and models to examine changing inequality and its consequences. I conclude with a few words about other important factors: political, institutional, and cultural.",
"keywords": [
"sustainable development",
"modeling",
"human and environmental well-being",
"population",
"inequality"
],
"content": "Introduction\n\nThe latest United Nations (UN) forecast says that the world population will likely increase from about 7 billion today to about 10.5 billion in 21001. A UN-supported analysis of global well-being2 highlights the costs of development “to ecosystem health, biodiversity, air quality, and climate resiliency”. These trends have motivated a vigorous and growing body of research, policy, opinion, and discussion, much of it polarized, emphasizing either the environment or people. But there is growing acknowledgment that “environmental health and human health are fundamentally linked” (3, an example from the ecological literature). That linkage goes beyond ‘health’ to encompass many dimensions that constitute the ‘well-being’ of humans and the environment. Many of these dimensions are evident in the UN’s new sustainable development goals, or SDGs4, illustrated in Figure 1.\n\nAdopted by the United Nations in 2015. Available with much other material at https://sustainabledevelopment.un.org/.\n\nThe concepts of development, sustainability, human well-being, and environmental well-being are complex. The term ‘development’ is usually defined in economic terms but (as explained later) has been extended to include some environmental attributes. ‘Sustainability’ is a widely used but vague term that can be operationalized in different and not always consistent ways (as indicated later).\n\nHuman well-being (Figure 2) includes obvious factors such as individual and population health but also other conditions of life (e.g. the freedoms discussed by Sen5). Environmental well-being (Figure 2) includes well-known aspects (e.g. viable and diverse ecosystems) but also less obvious factors (e.g. the regional effects of technology transfer). An important but often neglected aspect of both kinds of well-being is their distribution within and between countries. As Pope Francis6 put it, the improvement of human well-being requires that we “protect the vulnerable in our world and … stimulate integral and inclusive models of development”. Much the same can be said of ecosystems. Human and environmental well-being feed back on each other (as in Figure 2) via many pathways (demographic, economic, biological, individual, and institutional). These feedbacks (some illustrated in Figure 2) span a range of scales in space (local, regional, country, and global) and time (short: years to decades; medium: several human generations; long: millennia). These feedbacks are also complex enough that substantive research usually focuses on just a few.\n\nThe central box lists key elements of the two, many of which interact. Most of these dimensions affect both humans and environment. GDP, gross domestic product.\n\nThis invited article uses demographic perspectives as a natural way of linking the human and environmental dimensions. In the space available, I discuss primarily research that informs development (as highlighted in the UN SDGs4). My first aim is to highlight important (but often neglected) areas of quantitative research, historical and prospective, that can contribute significantly to research and policy analyses. Secondly, I want to encourage discussion of the realities and complexities of such central factors as population change or values and culture.\n\nI start with a simple general framework to highlight how demography and productivity shape human well-being. I use that framework to discuss three sets of issues and the corresponding challenges to modeling: first, population prehistory and early human development and their implications for the future; second, the challenges of a framework that incorporates multiple distinct dimensions of human and environmental well-being and the use of such a framework to explore the meanings of sustainability; and, third, inequality as a phenomenon triggered by development in the short run, and perhaps even in the long run, and models that examine changing inequality and its consequences. I conclude with a few words about other important (sometimes all-important) factors—political, institutional, and cultural—that affect human and environmental well-being. Throughout, I draw on perspectives from many disciplines, including demography, sociology, and economics as well as ecology, evolution, and environmental science.\n\nI emphasize that my use of the term ‘models’ is not restricted to mathematical models but includes other types of models, such as computer-based games for one or many players, or visually rich interactive displays.\n\n\nGrowth, demography, consumption: the big questions\n\nEarly agricultural populations7,8 were (mainly) dependent on food and demography. In the simplest case, a single population has W workers each producing a quantity Y food calories per year. These calories have to feed N people (including children and old people who do not work), so human well-being depends on\n\nAverage energy per capita J = (Y W)/N.\n\nHere, age structure determines the ratio W/N of workers to total population. This ratio is low when fertility is low (and/or survival is high, implying more old people), peaks at intermediate fertility, and falls again when fertility is high (and/or survival is low, implying more young people); thus, we have a dependency frontier (Figure 3a). Fertility and survival depend on available energy but saturate when energy available exceeds what can be physiologically used; thus, we have a growth frontier (Figure 3b). For much of human history before about 1800, productivity Y changed slowly whereas fertility and survival could change fairly quickly; populations fluctuated around a stable, essentially Malthusian equilibrium (as shown in Figure 3c). But even in early history, this equilibrium was relevant only in some places and times; climate, migration, disease, and war often kept populations far from equilibrium, and a simplistic Malthusian picture rarely applies anywhere in the world today.\n\n(a) The rate at which children are born increases with survival-weighted fertility. The proportion of workers rises with fertility but eventually falls as the proportion of children increases, forming a dependency frontier. (b) Human fertility increases with available food energy but eventually saturates at some upper limit, forming a growth frontier. (c) The intersection of the dependency and growth frontiers determines the prehistoric (Malthusian) equilibrium.\n\nThe Industrial Revolution led to a post-Malthusian world9 in which average per-capita food energy ceased to be a major determinant of human well-being and fertility. Human well-being now depends on\n\nAverage consumption per capita J = (Y W)/N,\n\nof an increasingly diverse set of consumables. The proportional growth rate of J is\n\nrJ = (1/J)(dJ/dt) and\n\n\n\nOver much of the 20th century, growth, measured by the rate of increase rJ of average per-capita consumption, became a principal measure of development. The relationship (Equation 1) describes the historical experience of the rich countries over many decades: population structure (W/N) changed slowly and development (rJ > 0) was largely due to growth in productivity Y (driven by technology). In recent decades, in the rich countries, populations are not growing, so rN is near zero or may even be negative. The labor supply is static or shrinking as more people age out of the labor force than enter it, so rW is also near zero or slightly negative. Thus, in the 21st century, we expect rich countries to grow at or below the rate of growth rY of productivity.\n\nEquation 1 also describes the more recent experience of emerging economies such as China and India. In those countries, in the past two decades, population growth slowed (so rN was small) but the labor force grew rapidly (so rW >> rN and was large, so rJ was large) and these economies grew rapidly. But India and China have diverged. Over the next two decades, India’s demographics will be much as before, but China’s labor force is shrinking (so for China, rW < 0). It is not surprising that, in recent years, China’s net economic growth rate (the rW in Equation 1) is falling and no longer benefits from demographic change.\n\nThis simple post-Malthusian view, of course, ignores (a) positive effects of population N on technology and thus on productivity Y, (b) negative effects of growth on local or global environment, (c) changes in the dimensions and measures of human well-being, (d) increases in the nature and level of consumption needed to maintain human well-being, and (e) the re-emergence of demographic constraints via the dependency ratio (W/N) as fertility declined and survival rates increased. These are the questions that models and policy aim to confront.\n\n\nSynthetic models of historical change\n\nAn essential aspect of a post-Malthusian world is the positive effect of population N on technological change, first established by Ester Boserup10. Lee11 formulated the first dynamic model that incorporates population growth, technological change, and their negative (Malthusian) and positive (Boserupian) feedbacks. An important feature of this model (and of the real world) is that changes in the level of technology determine multiple equilibria. Such changes in technology may be continuous or discontinuous. This model stimulated more sophisticated models of early agriculture8,12 and has been developed in the context of early human development and evolution13,14.\n\nThe structure of these demographically rich models can and should be extended to study historical population change, both in prehistory and in the past few centuries. Such models are also worth exploring in abstract and general ways to develop insights into the dynamics of human evolution, sustainability, persistence, and similar (slippery and complex) concepts. Particular examples of this are the following:\n\n(a) Extending the models of Lee et al.12 and Kirch et al.8 to study the stability and sustainability of hunter-gatherer populations, the hunting-agriculture transition, and speeds of human migrations in pre-history and their effects on natural resources.\n\n(b) Mapping Lee’s11 multiple equilibria onto developmental paths past and present and the analysis of evolutionary versions of the model that capture the long-run transitions between equilibrium states.\n\n(c) Exploring the relationship between Lee’s11 model and Cohen’s (see Appendix 6 in15) toy models of population-resource dynamics with time-dependent rates of renewal and exploitation. I note in passing that Cohen’s book has useful critiques of popular arguments (e.g. variants of Liebig’s rule and the notion of carrying capacity) that should be required reading for all environmentalists.\n\n(d) The models discussed above and later in this article are built on the relationship between demography, resources, and technology. How do these models compare with simpler aggregate models (e.g. the model used by Turchin et al.16)?\n\n\nThe meaning of sustainable development\n\nSustainability is a term encompassing complex dimensions and processes and is hard to define operationally; see the discussion around the SDGs4. Sustainable development is viewed by economists (at least those who have worked on human-environment linkages) as an equilibrium growth path (i.e. rJ > 0 in Equation 1) that includes human and environmental well-being2,17,18.\n\nA central challenge is valuation: how to measure development in ways that incorporate multiple dimensions of both human well-being (see the indexes and reports accessible at http://hdr.undp.org/en) and environmental well-being. On the human side, data and models must at least describe human capital, socioeconomic condition, human health, the use of ecosystems and other natural resources, and local and global effects on the environment. On the environmental side, we must value a wider range of ecosystem services and describe ecosystem dynamics. And these human and ecosystem models have to be coupled.\n\nThe incorporation of such diverse elements of well-being is essential. The UN effort at measuring development in an integrated way2 makes notable and important progress on combining human and ecosystem valuation but leaves out the value of human longevity. This is probably a fatal omission, given the priorities of people, especially the rich (e.g. the US National Institutes of Health spend over 4.5 times as much on health as the US National Science Foundation does on all other science). The development of measures of ecosystem services has greatly strengthened the assessment of environmental well-being (see, for example, the Natural Capital project, http://www.naturalcapitalproject.org/what-is-natural-capital/), but many problems remain19.\n\nHere is a short list of important open problems:\n\n(a) Quantitative models that incorporate the direct and indirect consumption of renewable and non-renewable resources—one approach is to extend bioeconomic models for fisheries20.\n\n(b) Quantitative models that confront difficult trade-offs. For example, in India, there are about 2200 tigers and there are also about 700 million people who live on less than $2 US per day; how do we value investments in tiger conservation versus industrial development? We should explore models and methods that have been developed to assess multiple and poorly defined objectives such as fuzzy logic21 or grade-of-membership22.\n\n(c) Models to quantify intergenerational effects for both humans and the environment. Intergenerational accounting was developed by economists23 but has been applied only to pensions and taxation, as far as I know. Intergenerational effects clearly matter for the environment, but there has been only limited effort24 to extend economic analysis to environmental well-being.\n\n(d) Human aging worldwide is producing rapid change in the W/N ratio and has drawn enormous interest and analysis by demographers and economists (for just a taste, see Auerbach and Lee25). Aging has been studied in the context of energy and carbon dioxide26–28 but not (as far as I know) in the broader context of effects on environments and sustainability.\n\n(e) Life cycle transfers (from old to young and vice versa, both direct and mediated by taxation) are being studied globally in economic terms in the National Transfer Accounts project (see http://www.ntaccounts.org/web/nta/show/), and data are being collected and analyzed to study how “population growth and changing age structure influence economic growth, gender and generational equity, public finances …”. Extensions of this study are needed to incorporate the life cycle transmission of values/attitudes/ownership of ecosystems/services. These subjects appear to be little studied, and data from different countries can be usefully integrated into better models and better decisions.\n\n\nInequality: an unexplored frontier\n\nA temporary increase in economic inequality has long been expected to accompany development29; in the longer term, inequality was supposed to shrink as economies became developed (i.e. rich). But a surprising and important corollary of rapid economic development is a large rise in spatial inequality in many aspects of human and environmental well-being.\n\nThus, in human health, Ram et al.30 document large spatial differences in adult mortality by district in India, whereas Kumar et al.31 find similar variation in mortality in children under age 5. These spatial differences within India are easily as large as average differences between India and, say, the US. Similar spatial inequality has been documented in China and other developing economies. Rapid development also generates growing economic inequality: Xie and Zhou32 show, for example, that wage income inequality has been and is still rising rapidly in China. Similar trends have been found in India and other developing economies. There is also a rise in social inequality (e.g. in sex bias and the resulting imbalance in the marriage market). Thus, for China in recent years, Jin et al.33 document a dramatic imbalance in the sex ratio of rural youth (what has become known as the problem of ‘Bare Branches’). In regard to environmental well-being, it is well known that there is spatial variation at many spatial scales in ecosystem services34 (e.g. between rural and urban landscapes and ecosystems).\n\nKuznets notwithstanding, inequalities may persist and even widen in the long run. Piketty35 has documented a recent and large rise in within-rich-country economic inequality; this is a surprise (unwelcome to many but perhaps not to everyone). Inequalities are likely to affect peoples’ preferences and willingness to pay for such things as environmental well-being.\n\nWe need analyses of the rise and consequences of spatial inequality that accompanies development. In particular, we need to examine (a) correlations between economic activity, migration, and human well-being; (b) path dependence as a driver of inequality in economics, demands on ecosystems, and environmental vulnerability (see Henning et al.36 for an economic perspective); and (c) probabilistic methods to explore the performance of portfolios of ecosystems distributed in multiple ways: in physical space, in biological space (species, food webs, biomes, and so on), and in patterns of human resource use.\n\n\nOther models, agency, and institutions\n\nMany elements of human-environment interactions are qualitative and may not be quantified easily or at all. Among these are the following: (a) cultural, ethical, moral, and religious differences in world views and individual decisions; (b) the uneven distribution of human agency and democracy (see Sen5 for what I mean by the term ‘agency’); (c) stability or instability of governance and institutions; and (d) the potentially catastrophic effects of war, disease, or famine (these rarely follow a Malthusian script: see Sen5, cited above, or accounts of the 2016 displacement of people from Syria).\n\nSuch qualitative factors mean that the study of human-environment interactions is ripe for exploration using new kinds of models, such as games and virtual reality simulations. I am not talking here about educational tools or about models that reinforce a particular (say, national) perspective; rather, we need tools that engage users from, and expose users to, diverse viewpoints and interests (economic, political, cultural, and institutional). The interactive and educational presentation of human-environment well-being can also exploit new tools to integrate and visualize databases (e.g. Google’s Fusion Tables, https://sites.google.com/site/fusiontableslab/home).\n\nScientists working on human-environment issues and development need to strengthen their engagement with institutions, especially those that shape key changes and attitudes (such as newspapers, media, and multinational institutions and corporations) across the world. For modelers (and others), a central aspect of this recognition is more, better, and targeted communication. But I stress that a goal of such communication is to engage, not preach.",
"appendix": "Competing interests\n\n\n\nThe author declares that he has no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nAcknowledgments\n\nI am most grateful to Mark Boyce, Conrad Istock, Charlotte Lee, Ronald Lee, Diana Rypkema, Cedric Puleston, and Shubha Tuljapurkar for comments that have greatly improved this article. I fear that none of them will be entirely happy with this version.\n\n\nReferences\n\nGerland P, Raftery AE, Sevčíková H, et al.: World population stabilization unlikely this century. Science. 2014; 346(6206): 234–7. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nUNU-IHDP and UNEP: Inclusive Wealth Report 2014. Measuring progress towards sustainability. Cambridge: Cambridge University Press, 2014. Reference Source\n\nWood SLR, DeClerck F: Ecosystems and human well-being in the Sustainable Development Goals. Front Ecol Environ. 2015; 13(3): 123. Publisher Full Text | Faculty Opinions Recommendation\n\nUnited Nations Transforming our world: the 2030 agenda for sustainable development. General assembly Resolution A/RES/70/1, 2015. Reference Source\n\nSen A: Development as Freedom. New York: Knopf. 1999. Reference Source\n\nFrancis P: Address Of The Holy Father. South Lawn of the White House, Washington, D.C., 2015. Reference Source\n\nLee CT, Tuljapurkar S: Population and prehistory I: Food-dependent population growth in constant environments. Theor Popul Biol. 2008; 73(4): 473–82. PubMed Abstract | Publisher Full Text\n\nKirch PV, Asner G, Chadwick OA, et al.: Building and testing models of long-term agricultural intensification and population dynamics: A case study from the Leeward Kohala Field System, Hawai’i. Ecol Model. 2012; 241: 54–64. Publisher Full Text\n\nWeil D: Economic Growth. Prentice Hall, 2nd edition. 2008. Reference Source\n\nBoserup E: The condition of agricultural growth. The Economics of Agrarian Change under Population Pressure. Allan and Urwin, London, 1965. Reference Source\n\nLee R: Malthus and Boserup: A dynamic synthesis. In David Coleman and Roger Schofield (Eds.), The State of Population Theory: Forward from Malthus. Oxford: Blackwell, 1986; 96–130.\n\nLee CT, Puleston CO, Tuljapurkar S: Population and prehistory III: food-dependent demography in variable environments. Theor Popul Biol. 2009; 76(3): 179–88. PubMed Abstract | Publisher Full Text\n\nRicherson PJ, Boyd R: Homage to Malthus, Ricardo, and Boserup: Toward a general theory of population, economic growth, environmental deterioration, wealth, and poverty. Human Ecology Review. 1998; 4: 85–90. Reference Source | Faculty Opinions Recommendation\n\nWood JW: A Theory of Preindustrial Population Dynamics Demography, Economy, and Well‐Being in Malthusian Systems1. Curr Anthropol. 1998; 39(1): 99–135. Publisher Full Text | Faculty Opinions Recommendation\n\nCohen JE: How Many people Can the Earth Support. Norton, New York, 1995. Reference Source\n\nTurchin P, Currie TE, Turner EA, et al.: War, space, and the evolution of Old World complex societies. Proc Natl Acad Sci U S A. 2013; 110(41): 16384–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDasgupta P: Nature in Economics. Environ Resource Econ. 2008; 39(1): 1–7. Publisher Full Text | Faculty Opinions Recommendation\n\nParks S, Gowdy J: What have economists learned about valuing nature?: A review essay. Ecosystem Services. 2013; 3: e1–e10. Publisher Full Text | Faculty Opinions Recommendation\n\nGuerry AD, Polasky S, Lubchenco J, et al.: Natural capital and ecosystem services informing decisions: From promise to practice. Proc Natl Acad Sci U S A. 2015; 112(24): 7348–55. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKroetz K, Sanchirico JN: The Bioeconomics of Spatial-Dynamic Systems in Natural Resource Management. Annu Rev Resour Econ. 2015; 7: 189–207. Publisher Full Text | Faculty Opinions Recommendation\n\nHerrera-Viedma E: Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Zadeh's theory: Introduction. Technological and Economic Development of Economy. 2015; 21(5): 677–83. Publisher Full Text | Faculty Opinions Recommendation\n\nAiroldi EM, Blei D, Erosheva EA, et al.: Handbook of Mixed Membership Models and Their Applications. Boca Raton: CRC Press, 2014. Reference Source\n\nAuerbach AJ, Gokhale J, Kotlikoff LJ: Generational Accounts - A Meaningful Alternative to Deficit Accounting. Cambridge, MA: National Bureau of Economic Research, 1991. Publisher Full Text\n\nRangel A: Forward and Backward Intergenerational Goods: Why Is Social Security Good for the Environment? Am Econ Rev. 2003; 93(3): 813–34. Publisher Full Text | Faculty Opinions Recommendation\n\nAuerbach AJ, Lee RD, editors: Demographic Change and Fiscal Policy. Cambridge University Press, Cambridge, 2008. Reference Source\n\nLiu J, Daily GC, Ehrlich PR, et al.: Effects of household dynamics on resource consumption and biodiversity. Nature. 2003; 421(6922): 530–3. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nO'Neill BC, Dalton M, Fuchs R, et al.: Global demographic trends and future carbon emissions. Proc Natl Acad Sci U S A. 2010; 107(41): 17521–6. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nZagheni E: The leverage of demographic dynamics on carbon dioxide emissions: does age structure matter? Demography. 2011; 48(1): 371–99. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKuznets S: Economic Growth and Income Inequality. American Economic Review. 1955; 45; 1–28. Reference Source\n\nRam U, Jha P, Gerland P, et al.: Age-specific and sex-specific adult mortality risk in India in 2014: Analysis of 0·27 million nationally surveyed deaths and demographic estimates from 597 districts. Lancet Glob Health. 2015; 3(12): e767–e775. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKumar C, Singh PK, Rai RK: Under-five mortality in high focus states in India: a district level geospatial analysis. PLoS One. 2012; 7(5): e37515. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nXie Y, Zhou X: Income inequality in today's China. Proc Natl Acad Sci U S A. 2014; 111(19): 6928–33. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nJin X, Liu L, Li Y, et al.: \"Bare Branches\" and the Marriage Market in Rural China: Preliminary Evidence from a village-level survey. Chin Sociol Rev. 2013; 46(1): 83–104. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nArkema KK, Verutes GM, Wood SA, et al.: Embedding ecosystem services in coastal planning leads to better outcomes for people and nature. Proc Natl Acad Sci U S A. 2015; 112(24): 7390–5. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPiketty T: Capital in the 21st century. Harvard University Press, Cambridge. 2014. Reference Source\n\nHenning M, Stam E, Wenting R: Path Dependence Research in Regional Economic Development: Cacophony or Knowledge Accumulation? Regional Studies. 2013; 47(8): 1348–62. Publisher Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "13352",
"date": "13 Apr 2016",
"name": "Ronald Lee",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13357",
"date": "13 Apr 2016",
"name": "Conrad Istock",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13358",
"date": "13 Apr 2016",
"name": "Mark Boyce",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-675
|
https://f1000research.com/articles/5-674/v1
|
13 Apr 16
|
{
"type": "Software Tool Article",
"title": "MetaNetVar: Pipeline for applying network analysis tools for genomic variants analysis",
"authors": [
"Eric Moyer",
"Megan Hagenauer",
"Matthew Lesko",
"Felix Francis",
"Oscar Rodriguez",
"Vijayaraj Nagarajan",
"Vojtech Huser",
"Ben Busby",
"Eric Moyer",
"Megan Hagenauer",
"Matthew Lesko",
"Felix Francis",
"Oscar Rodriguez",
"Vijayaraj Nagarajan",
"Vojtech Huser"
],
"abstract": "Network analysis can make variant analysis better. There are existing tools like HotNet2 and dmGWAS that can provide various analytical methods. We developed a prototype of a pipeline called MetaNetVar that allows execution of multiple tools. The code is published at https://github.com/NCBI-Hackathons/Network_SNPs. A working prototype is published as an Amazon Machine Image - ami-4510312f .",
"keywords": [
"network analysis",
"genetic variant",
"pipeline",
"next generation sequencing"
],
"content": "Introduction\n\nTraditionally, the goal of genome-wide association studies (GWAS) has been to associate single nucleotide polymorphisms (SNPs) and their respective haplotype blocks with disease status, allowing the eventual identification of particular genes responsible for disease phenotype. Unfortunately, only a small subset of diseases arise from variants within a single gene. For most complex diseases, it is likely that the disease arises due to the interactive effects of multiple genetic variants, and different collections of these variants may be present in different patients. Within a GWAS study, these variants individually will exhibit low predictive power making it difficult for researchers to obtain a sufficient sample size to identify them with high confidence. Therefore, tools that can help detect groups of interacting genetic variants are needed1–3.\n\nOne set of tools that has great potential for aiding in this problem is network analyses. Within these tools, the results from GWAS studies are overlaid on networks constructed from curated molecular interaction data, such as databases documenting protein-protein interactions (PPIs), protein-DNA interactions, metabolite interactions, and gene-gene co-expression1,2. Many of these tools are powerful, but somewhat inaccessible to users with weaker computational backgrounds. For example, installing, configuring, running, and comparing the output of multiple network analysis tools could require a working knowledge of command-line scripting, Python, R, and Perl. Therefore, the goal of our hackathon team was to create a single command-line pipeline within which a user could input the results of a GWAS study, execute existing network analysis tools, and then access results from multiple network analyses. This work was conducted as part of the NCBI January 2016 Hackathon.\n\n\nMethods\n\nThe context of the hackathon event allowed only three development days to create the pipeline which impacted the scope and design of the tool. The focus was on allowing one input file to be directed towards multiple tools; consolidation of results from individual tools was out of scope. Similarly, each tool output was not post-processed for unified output. We envision that future improvement to the pipeline may offer advanced visualisation options; however, this was not part of this pilot implementation. A working instance of the pipeline is also published as an Amazon Machine Image ami-4510312f.\n\nAs much as possible, the MetaNetVar pipeline uses existing tools for network analysis. We only considered tools that are freely available, with no license restrictions. We describe briefly each tool that is integrated into the MetaNetVar pipeline. Tools vary in scope, and some include additional functions that include network analysis.\n\nFunSeq2 is an existing tool for prioritizing variants using several different approaches, including network-based analysis4,5. FunSeq2 identifies hub genes and provides the measure of centrality for those hub genes. Inference of the network analysis results requires further processing of the program’s output. We chose to include FunSeq2 in our pipeline because of its capability to identify functionally important, non-coding variants in the context of biological networks.\n\nNetworkX is a network analysis framework available in a Python language software package. It allows for “the creation, manipulation, and study of the structure, dynamics, and functions of complex networks”6. It contains many standard graph algorithms and accepts and outputs 13 file formats, where nodes can be anything and edges can hold any type of data. NetworkX was used to calculate the degrees and betweenness centrality of nodes (genes) and to create XML format and static PNG figures of subnetworks containing the input genes. The degrees and the betweenness centrality gives you a measurement of how important the gene is in the network. A network analysis framework similar to NetworkX is CytoscapeJS7. We chose to include NetworkX in our pipeline because of our experience with Python.\n\nHotNet2 is an algorithm for detecting “significantly altered subnetworks in a large gene interaction network”8–10. The algorithm uses heat diffusion kernel to capture the local topology of the interaction network. The subnetworks in genome scale interactions that have non-random mutations are identified using this approach. The limitation of HotNet2 are the challenges in getting the scripts running straight out of the box, along with the long computational time involved in the preliminary influence matrix creation process. We chose to include HotNet2 in our pipeline because of our experience with Python.\n\ndmGWAS_3.0 is an existing tool for overlaying gene-level summaries of case-control association p-values onto an existing network (in this case, we use the network extracted from GeneMania detailed below) and then identifying subnetworks that are particularly enriched for strong associations using a greedy algorithm11,12. Unlike the previous version of dmGWAS (2.0), dmGWAS_3.0 also has the ability to incorporate differential gene coexpression data (in other words, the difference in gene co-expression between cases and controls) as weights for the edges in the network, but for the sake of simplicity we did not make use of this new functionality in our pipeline. Due to this choice, we discovered that the dense-module search output (ResList.RData) took the format of the previous version dmGWAS_2.013 and could not be manipulated using the tools referenced in the current documentation. Therefore, we created our own short script to extract out the basic statistics and subnetwork nodes associated with each input gene present in the network (see below: ModuleStrengthSummaryByGene.txt and Top1000ModuleScores.txt). We later discovered that some of the old tools capable of manipulating dmGWAS_2.0 output (ResList.RData) were preserved in the current code package and could be used for further data exploration by a motivated user by loading the output file (ResList.RData) into R and installing the requisite packages (dmGWAS, igraph), although some of the tools did not appear to be fully functional anymore (such as the subnetwork plotting capability in simpleChoose()).\n\nOverall, the primary limitation that we observed for dmGWAS was computing time, so we adapted the existing code to make use of parallel computing using the BiocParallel package in R14.\n\nTo utilize dmGWAS_3.0, it is first necessary to convert the input file containing the case-control association p-values for each SNP to a gene-level summary. Within our pipeline, we complete this conversion using VEGAS, an existing command line (Linux/Unix) based tool recommended within the dmGWAS documentation15,16. It should be noted that by default, VEGAS uses the HapMap2 CEU (Central Europeans, Utah) population to estimate patterns of linkage disequilibrium for each gene.\n\nVEGAS is written in Perl but also makes use of two R packages (corpcor and mvtnorm) and depends on functions provided by PLINK, a commonly-used whole genome analysis toolset17,18. The output of VEGAS requires further processing before input into dmGWAS. We found that several of the VEGAS gene-level p-values were rounded to either 0 or 1, which was incompatible with dmGWAS, so we substituted the minimum p-value present in our test file (1e-06) for 0 and 0.999 for 1.\n\nTable 1 provides a summary of the tools used in this pipeline, including notes about their advantages and disadvantages.\n\n\nNetworks used\n\nNetwork construction based on a user-provided list of variants required accessing molecular interaction network data from external databases. We describe the network databases utilized by each tool. Some networks (such as Multinet) are used by multiple tools (FunSeq2 and HotNet2).\n\nFunSeq2 utilizes multinet19, which is an integrated network consisting of regulatory interactions from the ENCODE regulatory network20,21, phosphorylation interactions from the SignaLink database22–24, protein-protein interactions from BioGRID (release 3.1.83)25, and metabolic interactions from KEGG26. While there are options for users to bring in their own network for use with FunSeq2 analysis, this pipeline prototype uses the pre-packaged multinet.\n\nThe NetworkX and dmGWAS are libraries and do not include particular network data.\n\nWe paired GeneMania with NetworkX and dmGWAS. The GeneMania network is a protein-protein interaction network27,28. Two genes are connected if they are found to interact in a protein-protein interaction study. The network was created from various protein-protein interaction databases, including BioGRID and Pathway Commons29,30. We used version 2014-10-15 of Homo_sapiens.COMBINED network.\n\nHotNet2 uses mutation data to prioritize subnetworks by identifying significantly mutated subnetworks in genome scale interaction networks. In our pipeline, we have used the 2012 version of HINT (High-quality INTeractomes) a database of high-quality protein-protein interactions31.\n\nAs a sample input for our pilot, we searched NCBI dbGaP for a sample study that provided a real world list of variants. We used data from a clinical study of age-related macular degeneration32 with dbGAP identifier phs000182.v3.p1.\n\nAs an additional input example, we used data from ClinVar33. ClinVar is a database of interpretations of clinical significance of variants for reported conditions, hosted by the National Center for Biotechnology Information (NCBI). It includes germline and somatic variants of any size, type, or genomic location with interpretations from several sources (such as clinical testing laboratories, research laboratories, or locus-specific databases). It includes a link of variants to phenotypes. For this example, we identified variations submitted by LabCorp and extracted disease-variant pairs, for diseases with 30+ variants. The example dataset is provided on the MetaNetVar GitHub page.\n\n\nResults\n\nWe implemented four network analysis programs or platforms into our pipeline (FunSeq2, NetworkX, HotNet2, dmGWAS), utilizing molecular interaction data from several external knowledge databases (listed above). Figure 1 provides an overview of the pipeline.\n\nTo lower the adoption threshold for potential users, we offer the snapshot of our working instance as an Amazon Machine Image. The collection of tools and the pipeline script can be executed using an instance of our publicly available Amazon Machine Image: ami-4510312f. The accompanying supplementary file describes the step-by-step procedure for running our pipeline using the published Amazon Machine Image.\n\nWe discuss below the results from individual tools integrated into our pipeline. Results of all of these tools, using the example dataset, is also provided on the MetaNetVar GitHub page.\n\nThe parsed input file required for the FunSeq2 analysis, the PHP script that generates this parsed input file from the original dbGaP association data, and the output files (using default parameters) are provided in the GitHub project page. An example file generated from a filtered list of SNPs from the ClinVar database, for the Cardiomyopathy phenotype is also provided for testing purposes and can be found at http://github.com/NCBI-Hackathons/Network_SNPs/blob/master/test/sample_output/funseq2/cardiomyopathyfunseqoutput.\n\nWe took the NetworkX library and created a script that we refer to as SNPsNet. This script generates one output file containing the degrees and betweenness centrality measure of genes that are input into the pipeline, as well as creating two directories (see Figure 2). The two directories contain figures of subnetworks with the input genes and the XML format of the subnetworks. With these results, the user can prioritize the input variants or genes by sorting how important each gene is based on degreeness or centrality, as well as visualizing the subnetwork. Since NetworkX is not primarily a visualization tool, the XML file can be input into several other tools to better visualize the graph.\n\nThe influence matrix for HINT was pre-computed and then used in the current version of our pipeline. Influence matrix creation is a one-time process for a given network and, if required, advanced users may use custom influence matrices with MetaNetVar by modifying the path to the input influence matrix file and corresponding gene index file. For evaluation of MetaNetVar, we generated heat scores from a test mutation file. The .json file containing heat scores on each gene, which was used in subsequent steps, may be accessed at https://github.com/NCBI-Hackathons/Network_SNPs/blob/master/heat_score.json.\n\nThe final step of weighted graph generation uses the influence matrix for HINT, the HINT index file, and the heat score .json file, to remove edges with weight less than the delta value, and extract the resulting connected components. Two output files were generated: components.txt (available at https://github.com/NCBI-Hackathons/Network_SNPs/blob/master/components.txt) and results.json (available at https://github.com/NCBI-Hackathons/Network_SNPs/blob/master/results.json)\n\nThe sample association file from the age-related macular degeneration dataset (phs000182) was parsed down to a two-column text file containing only SNP identifiers (“rs numbers”) and case-control association p-values. This file was fed into VEGAS and a gene-level summary file was created, which was further parsed into a simple two-column text file containing gene identifiers (gene symbol) and “weight” (an integrated p-value for the gene). Within dmGWAS, this input was overlaid onto a network provided by GeneMania to produce a network of weighted nodes from which particularly “dense” subnetworks are identified (full output: ResList.RData). Finally, our program summarizes the data into two easily navigable tab-delimited .txt files which can be viewed within accessible programs such as Microsoft Excel (ModuleStrengthSummaryByGene.txt, Top1000ModuleScores.txt). Figure 3 and Figure 4 demonstrate example output files.\n\nThis file provides the Normalized Module Score for each gene included in the network (“Zn”, where a larger value indicates the gene is more enriched for significant case-control associations), and the gene-level summary case-control association p-value provided by VEGAS. It is ordered by percentile rank to allow comparison across different network analysis programs.\n\nThis second output provides similar information as the first output file, but expands it to include the list of genes (nodes) present in each gene of interest subnetwork. Only subnetwork output for the top 1000 seed genes is provided (as determined by percentile rank).\n\nThe current version of the pipeline is set to use data from dbGaP and ClinVar out-of-the-box. However, advanced users could tweak the provided scripts to make it run using other input formats. Some of the components of the pipeline use processes that are parallel and compute-intensive in nature. Using the provided working implementation of the pipeline through Amazon Web Services requires some computing skills.\n\n\nConclusions\n\nOur tool, MetaNetVar, allows researchers with limited computational experience to access a host of powerful network analysis tools for application to genomic datasets. This platform is intended for use in a variety of future hackathons, including work on cancer and evolutionary biology, but will most likely also be used by participants from the current hackathon, as well as other interested individuals. Since this work was a pilot project, we expect further modification of the pipeline as new users provide feedback. Ideally, the future pipeline would include a unified output summary, better network visualization tools, and the ability to integrate known disease-related variants into the analysis, such as from ClinVar33, from PheGeni34, or from the output of epistasis analyses35.\n\n\nData and software availability\n\nLatest source code: https://github.com/NCBI-Hackathons/Network_SNPs\n\nArchived source code as at time of publication: http://dx.doi.org/10.5281/zenodo.4820236\n\nAmazon instance ID: ami-4510312f\n\nAmazon instance name: NCBI-Hackathon-20160122-Network-SNPs\n\nLicense: CC0 1.0 Universal",
"appendix": "Author contributions\n\n\n\nAll of the authors participated in designing the study, carrying out the research, and preparing the manuscript. All authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe work on this project by Vojtech Huser, Eric Moyer and Ben Busby was supported by the Intramural Research Program of the National Institutes of Health (NIH)/National Library of Medicine (NLM)/Lister Hill Center (VH) and NCBI (EM and BB). Megan Hagenauer’s work on this project was supported by the Pritzker Neuropsychiatric Disorders Research Consortium.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nThe authors thank Lisa Federer, NIH Library Writing Center, for manuscript editing assistance.\n\n\nSupplementary material\n\nSoftware manual. This document provides instructions on how to start and run the NCBI-Hackathon-20160122-Network-SNPs instance in AWS using a Mac computer.\n\n\nReferences\n\nLeiserson MD, Eldridge JV, Ramachandran S, et al.: Network analysis of GWAS data. Curr Opin Genet Dev. 2013; 23(6): 602–10. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBolouri H: Modeling genomic regulatory networks with big data. Trends Genet. 2014; 30(5): 182–91. PubMed Abstract | Publisher Full Text\n\nHalldórsson BV, Sharan R: Network-based interpretation of genomic variation data. J Mol Biol. 2013; 425(21): 3964–9. PubMed Abstract | Publisher Full Text\n\nKhurana E, Fu Y, Colonna V, et al.: Integrative annotation of variants from 1092 humans: application to cancer genomics. Science. 2013; 342(6154): 1235587. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGersteinLab@Yale: Funseq2 [Internet]. [cited 2016 Feb 24]. Reference Source\n\nNetworkX developer team: Overview — NetworkX [Internet]. [cited 2016 Feb 24]. Reference Source\n\nFranz M, Lopes CT, Huck G, et al.: Cytoscape.js: a graph theory library for visualisation and analysis. Bioinformatics. 2016; 32(2): 309–11. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRaphael Lab: HotNet [Internet]. [cited 2016 Feb 24]. Reference Source\n\nRaphael Group: GitHub - hotnet2 [Internet]. [cited 2016 Feb 24]. Reference Source\n\nVandin F, Upfal E, Raphael BJ: Algorithms for detecting significantly mutated pathways in cancer. J Comput Biol. 2011; 18(3): 507–22. PubMed Abstract | Publisher Full Text\n\nVanderbilt University Bioinformatics, Systems Medicine Laboratory: dmGWAS 3.0 [Internet]. [cited 2016 Feb 24]. Reference Source\n\nJia P, Zheng S, Long J, et al.: dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks. Bioinformatics. 2011; 27(1): 95–102. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJia P, Zheng S, Zhao Z: dmGWAS 2.0: dense module searching for genome-wide association studies in protein-protein interaction network [Internet]. [cited 2016 Feb 24]. Reference Source\n\nCarey V, Lawrence M, Morgan M: Introduction to BiocParallel [Internet]. [cited 2016 Feb 24]. Reference Source\n\nLiu JZ, McRae AF, Nyholt DR, et al.: A versatile gene-based test for genome-wide association studies. Am J Hum Genet. 2010; 87(1): 139–45. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu J, MacGregor S: VEGAS: Versatile Gene-based Association Study [Internet]. [cited 2016 Feb 24]. Reference Source\n\nPurcell S: PLINK: Whole genome data analysis toolset [Internet]. [cited 2016 Feb 24]. Reference Source\n\nPurcell S, Neale B, Todd-Brown K, et al.: PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007; 81(3): 559–75. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKellis M, Wold B, Snyder MP, et al.: Defining functional DNA elements in the human genome. Proc Natl Acad Sci U S A. 2014; 111(17): 6131–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNational Human Genome Research Institute: The ENCODE Project: ENCyclopedia Of DNA Elements [Internet]. [cited 2016 Feb 24]. Reference Source\n\nKhurana E, Fu Y, Chen J, et al.: Interpretation of genomic variants using a unified biological network approach. PLoS Comput Biol. 2013; 9(3): e1002886. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSignaLink: SignaLink 2.0 [Internet]. [cited 2016 Feb 24]. Reference Source\n\nFazekas D, Koltai M, Türei D, et al.: SignaLink 2 - a signaling pathway resource with multi-layered regulatory networks. BMC Syst Biol. 2013; 7: 7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKorcsmáros T, Farkas IJ, Szalay MS, et al.: Uniformly curated signaling pathways reveal tissue-specific cross-talks and support drug target discovery. Bioinformatics. 2010; 26(16): 2042–50. PubMed Abstract | Publisher Full Text\n\nTyersLab.com: BioGrid [Internet]. [cited 2016 Feb 24]. Reference Source\n\nOgata H, Goto S, Sato K, et al.: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 1999; 27(1): 29–34. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWarde-Farley D, Donaldson SL, Comes O, et al.: The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010; 38(Web Server issue): W214–W220. PubMed Abstract | Publisher Full Text | Free Full Text\n\nUniversity of Toronto: GeneMANIA [Internet]. [cited 2016 Feb 25]. Reference Source\n\nCerami EG, Gross BE, Demir E, et al.: Pathway Commons, a web resource for biological pathway data. Nucleic Acids Res. 2011; 39(Database issue): D685–D690. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMemorial Sloan-Kettering Cancer Center, University of Toronto: Pathway Commons [Internet]. [cited 2016 Feb 25]. Reference Source\n\nLeiserson MD, Vandin F, Wu HT, et al.: Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes. Nat Genet. 2015; 47(2): 106–14. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAbecasis GR, Yashar BM, Zhao Y, et al.: Age-related macular degeneration: a high-resolution genome scan for susceptibility loci in a population enriched for late-stage disease. Am J Hum Genet. 2004; 74(3): 482–94. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLandrum MJ, Lee JM, Benson M, et al.: ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016; 44(D1): D862–D868. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNational Center for Biotechnology Information: PheGenI: Phenotype-Genotype Integrator [Internet]. [cited 2016 Feb 25]. Reference Source\n\nUpton A, Trelles O, Cornejo-García JA, et al.: Review: High-performance computing to detect epistasis in genome scale data sets. Brief Bioinform. 2015; pii: bbv058. PubMed Abstract | Publisher Full Text\n\nJohn G, TriLe965, Hsu J, et al.: Structural_Variant_Comparison: Initial Post-Hackathon Release. Zenodo. 2016. Data Source"
}
|
[
{
"id": "13367",
"date": "21 Apr 2016",
"name": "John Didion",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nMinor points:\"...somewhat inaccessible to users with weaker computational backgrounds\" - I have a strong computational background, and dealing with poor build processes and user interfaces is frustrating to me also. Maybe rephrase this to say that different tools have different levels of usability, which can be ameliorated by providing a single, well-designed interface to multiple tools. In Figure 1, \"Network-based variant analysis tools\" is represented as a single box, but there are multiple steps encapsulated there. It would be more informative to show the steps involved for each of the four tools and the output of each tool.",
"responses": []
},
{
"id": "13368",
"date": "26 Apr 2016",
"name": "Sahar Al Seesi",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors describe a pilot version of an integrated pipeline of network analysis tools for genomic variants. It includes four existing tools. The pipeline analyzes the input files and run the tools applicable to the input files. The value of this contribution would greatly increase if the pipeline consolidated the output of the different tools. The authors acknowledge this fact and plan to include that in future versions of the pipelineThe manuscript is well written, and the functionality of tools included is clearly described.",
"responses": []
},
{
"id": "13366",
"date": "29 Apr 2016",
"name": "Tomasz Adamusiak",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nExcellent work given the limited hackathon time frame. I commend the authors for providing an AMI image and source code for the project.Minor comments:aiding in this problem is network analyses.Should be analysisWould change AWS deployment manual format to pdf and provide instructions how to stop the EC2 instance so that the user doesn't not incur unnecessary costs.",
"responses": []
}
] | 1
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https://f1000research.com/articles/5-674
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https://f1000research.com/articles/5-671/v1
|
13 Apr 16
|
{
"type": "Research Article",
"title": "Antimicrobial susceptibility and clarithromycin resistance patterns of Helicobacter pylori clinical isolates in Vietnam",
"authors": [
"Camelia Quek",
"Son T. Pham",
"Kieu T. Tran",
"Binh T. Pham",
"Loc V. Huynh",
"Ngan B.L. Luu",
"Thao K.T. Le",
"Kelly Quek",
"Van H. Pham",
"Camelia Quek",
"Son T. Pham",
"Kieu T. Tran",
"Binh T. Pham",
"Loc V. Huynh",
"Ngan B.L. Luu",
"Thao K.T. Le",
"Kelly Quek"
],
"abstract": "Helicobacter pylori is a gastric pathogen that causes several gastroduodenal disorders such as peptic ulcer disease and gastric cancer. Eradication efforts of H. pylori are often hampered by antimicrobial resistance in many countries, including Vietnam. Here, the study aimed to investigate the occurrence of antimicrobial resistance among H. pylori clinical isolates across 13 hospitals in Vietnam. The study further evaluated the clarithromycin resistance patterns of H. pylori strains. In order to address the study interests, antimicrobial susceptibility testing, epsilometer test and PCR-based sequencing were performed on a total of 193 strains isolated from patients, including 136 children (3–15 years of age) and 57 adults (19–69 years of age). Antimicrobial susceptibility testing showed that the overall resistance to amoxicillin, clarithromycin, levofloxacin, metronidazole, and tetracycline was 10.4%, 85.5%, 24.4%, 37.8%, and 23.8% respectively. The distribution of minimum inhibitory concentrations (MICs) of clarithromycin-resistant strains was 85.5% with MIC >0.5 μg/mL. The majority of the clarithromycin resistant isolates (135 of 165 subjects) have MICs ranging from 2 μg/mL to 16 μg/mL. Furthermore, sequencing detection of mutations in 23S rRNA gene revealed that strains resistant and susceptible to clarithromycin contained both A2143G and T2182C mutations. Of all isolates, eight clarithromycin-resistant isolates (MIC >0.5 μg/mL) had no mutations in the 23S rRNA gene. Collectively, these results demonstrated that a proportion of clarithromycin-resistant H. pylori strains, which are not related to the 23S rRNA gene mutations, could be potentially related to other mechanisms such as the presence of an efflux pump or polymorphisms in the CYP2C19 gene. Therefore, the present study suggests that providing susceptibility testing prior to treatment or alternative screening strategies for antimicrobial resistance is important for future clinical practice. Further studies on clinical guidelines and treatment efficacy are pivotal for successful eradication of H. pylori infection.",
"keywords": [
"Helicobacter pylori",
"antimicrobial resistance",
"23S rRNA",
"mutation",
"gastric ulcer"
],
"content": "Introduction\n\nHelicobacter pylori is a Gram-negative bacterium that plays a causative role in the development of gastric adenocarcinoma, peptic ulcer disease and chronic gastritis1,2. The prevalence of H. pylori infection is more than half of the world’s population, comprising of >80% in developing countries and approximately 40% in the United States3,4. In Vietnam, the prevalence of H. pylori is approximately 80% in adults and 26%–71.4% in children5–7.\n\nEradication therapy of symptomatic H. pylori infection substantially prevents the recurrence and reduces the risk of developing gastroduodenal-associated diseases8–11. Recommended therapy, triple-therapy regimen, composed of two antimicrobial agents (e.g. amoxicillin, metronidazole, tetracycline, levofloxacin, and clarithromycin) in combination with a proton pump inhibitor (PPI), has been widely used to eliminate the bacteria12–14. However, H. pylori antimicrobial resistance is increasing worldwide, contributing to the main factor that affects the efficacy of current therapeutic regimens15,16. Resistance to clarithromycin is believed to be the main factor in treatment failure16,17. In Vietnam, many studies showed that H. pylori is highly resistant to clarithromycin; 33%–34% primary and 74% secondary resistance18–20. The majority of clarithromycin-resistant strains are identified based on point mutations in the peptidyltransferase region of domain V of 23S rRNA, which affects the binding of macrolides to the bacterial ribosome21–23.\n\nThe common 23S rRNA point mutations (e.g. A2143G, A2142C/G and T2182C) are recommended for rapid routine diagnostic procedures, as compared to the time-consuming bacterial culture. A plethora of studies have evidently reported the association of minimum inhibitory concentrations (MICs) of clarithromycin-resistance strains to the respective point mutation24–27. For example, A2142C/G mutations are associated with MIC >256 μg/mL, and mutations such as A2143G and T2182C are associated with MIC >0.5 μg/mL27,28. However, it is unclear whether such association between point mutation and MIC can be utilised as predictors for strains resistant to clarithromycin23,29–31. Here, the present study evaluated the antimicrobial resistance of H. pylori strains isolated from patients in Vietnam with the following antimicrobial agents: amoxicillin, metronidazole, tetracycline, levofloxacin and clarithromycin. The strains resistant to clarithromycin were further investigated to assess the point mutations in the 23S rRNA gene and MIC values as predictors for screening H. pylori strains. The overall findings addressed the issues of using 23S rRNA mutations in clinical diagnosis.\n\n\nMaterials and methods\n\nThe present work was designed as a prospective randomised clinical study across 13 hospitals (Children's Hospital 2, Children's Hospital 1, Trieu An Hospital, Tam Nhat Clinic, Dai Phuoc Clinic, Hoan My Hospital, DH Y Duoc Hospital, Phap Viet Hospital, Yersin International Clinic, Dong Nai International Hospital, Nguyen Tri Phuong Hospital, Van Hanh General Hospital, Gia Dinh People's Hospital) in Ho Chi Minh City, Vietnam, from July 2015 to January 2016 (Data availability). The study was approved by Nam Khoa Biotek Diagnostic Ethics Committee (ID: NCKH 04/02-15/NK). Written informed consent was obtained from each patient or the patient’s parents for the use of this study. Biopsy specimens of the gastric mucosa were obtained from 193 patients, including 136 children (3–15 years of age) and 57 adults (19–69 years of age). These patients showed indication of endoscopy for the examination of dyspeptic symptoms (i.e. gastric ulcer).\n\nThe H. pylori culture and susceptibility testing were performed as described in previous studies32,33. Briefly, biopsy specimens were homogenised in 500 µL transport medium (20% glycerol; 0.9% NaCl in Milli-Q water), and were subsequently inoculated onto H. pylori selective agar plates at 37°C in a microaerophilic atmosphere. Biochemical identification of H. pylori was performed using Gram stain (Gram negative), oxidase test (oxidase positive), catalase test (catalase positive) and urease test (urease positive). Susceptibility testing was performed on Muller-Hinton agar plates supplemented with 10% lysed horse blood for the following antibiotics: amoxicillin (0.25 μg/mL), clarithromycin (0.75 μg/mL), levofloxacin (1 μg/mL), metronidazole (8 μg/ml), and tetracycline (2 μg/mL). The MIC values were obtained by the epsilometer test (E-test; bioMerieux, Marcy I’Etoile, France) for clarithromycin in accordance with the manufacturer’s protocol using 10% lysed horse blood supplemented in Mueller-Hinton Z agar (bioMerieux). Bacterial suspensions were prepared in Mueller-Hinton broth and adjusted to a McFarland turbidity of three. Resistance criteria for clarithromycin was defined according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST); susceptible (MIC ≤0.25 μg/mL) and resistance (MIC >0.5 μg/mL)34.\n\nThe PCR mixture (20-µL final volume) contained HotStar Taq master mix (Qiagen, Hilden, Germany) and 10 pmol of forward DP1 (5’-GTAAAACGACGGCCAGTACGGCGGCCGTAACTATA-3’) and reverse ZGE23 (5’-TATTTAGGTGACACTATAGACAGGCCAGTTAGCTA-3’) primers. These primers contain sequences (written in bold-faced type) that are specific for SP6 (DP1) and M13 (ZGE23), and underlined sequences indicate 23S rRNA amplicon of 308 bp comprising of 2142, 2143 and 2182 positions. H. pylori colonies on selective medium was added to 1× TE buffer (10 mM Tris-HCL, 1 mM EDTA, pH 7.6) and heated up to 100°C for 5 min, followed by centrifugation at 8000 rpm. 1 µL of supernatant was added to the PCR mix to amplify 23S rRNA gene. The PCR cycling conditions were 95°C for 15 min to activate HotStart Taq DNA polymerase, followed by 40 cycles of 94°C for 15 sec, 57°C for 30 sec, 72°C for 30 sec, and final extension at 72°C for 5 min. The PCR products were purified prior to sequencing by Illustra ExoStar 1-Step (GE Healthcare Life Sciences, Buckinghamshire, United Kingdom) according to manufacturer’s instructions, and followed by Big-Dye (Perkin-Elmer Applied Biosystems, Foster City, USA) amplification using SP6 and M13 primers. Sequencing was then performed using ABI 3130XL sequencer. In total, 193 sequences were obtained and analysed using MEGA version 5.035 against wild-type 23S rRNA gene available in the GenBank36 database (Accession number: U27270). Sequence data can be downloaded from GenBank database (Accession numbers: KU904824-KU905015).\n\nMann-Whitney t-test, unpaired two-tailed was used to compare resistance rate between different patient groups. All analyses were performed using SPSS Statistics version 20 (SPSS, Chicago, USA) and Prism version 5.0 (GraphPad, San Diego, USA).\n\n\nResults\n\nTo assess the antimicrobial resistance of H. pylori in Vietnam, susceptibility testing was performed and the resistance rate of each antimicrobial is listed in Table 1. The prevalence of antimicrobial resistance was detected in the following order, from highest to lowest: clarithromycin, metronidazole, levofloxacin, tetracycline and amoxicillin. Of all the antimicrobial agents, the majority of isolates were resistant to clarithromycin as shown in 85.5% of all patients (84.6% in children and 87.7% in adults). The occurrence of metronidazole resistance was lower than clarithromycin (overall 37.8% vs. 85.5%) in this study, as compared to the other published reports18–20. Antimicrobial resistance in adults is predominately higher than children, except for amoxicillin resistance which occurred in 12.5% of children and 5.3% of adults without statistical significance. A statistically significant difference was observed in the resistance rate of levofloxacin (p = 0.0103) between children and adults in Figure 1.\n\nThe graph displays the resistance rate of amoxicillin, clarithromycin, levofloxacin, metronidazole, and tetracycline in both children and adults. Among the antimicrobial agents, clinical isolates resistant to levofloxacin is significantly higher (p = 0.0103) in adults than in children.\n\nTo validate the clarithromycin resistant isolates, MIC values were obtained from a total of 193 clinical isolates using an E-test. Based on EUCAST proposed breakpoints, the respective occurrence of clarithromycin susceptible and resistant isolates was 24 (12.4%) and 165 (85.5%) of the total number of isolates used in this study. The distribution of MICs showed that the majority of clinical isolates resistant to clarithromycin (135 of 165 isolates, 81.8%, including 97 children and 38 adults) ranged from 2 μg/mL to 16 μg/mL (Figure 2). Of all isolates, only five subjects (including four children and one adult) showed a MIC of 24 μg/mL, and one adult subject had a MIC >256 μg/mL (Figure 2).\n\nThe graph shows the number of isolates across a range of minimum inhibitory concentration values of clarithromycin. The total number of clarithromycin susceptible and resistant isolates is 24 and 165, respectively. Majority of clinical isolates resistant to clarithromycin have MIC values ranging from 2 μg/mL to 16 μg/mL.\n\nTo investigate the point mutations in the 23S rRNA gene of clarithromycin-resistant isolates, mutations at position 2142 (A2142G or A2142C), 2143 (A2143G), and 2182 (T2182C) were analysed in this study. Sequence analyses showed the point mutations in the 23S rRNA gene were detected not only in clarithromycin-resistant isolates, but also in clarithromycin-susceptible isolates. In Table 2, both A2143G and T2182C mutations were predominantly detected in 91.7% (n = 177) of the clarithromycin-susceptible and –resistant isolates. Only two clarithromycin-resistant isolates in adults had the A2142G and T2182C mutations with a respective MIC value of 8 µg/mL and >256 µg/mL. In addition, a total of 10 clarithromycin-resistant and –susceptible isolates had no mutations in the 23S rRNA gene. The present study also identified four isolates with both A2143G and T2182C mutations at MIC values ranging from 0.38 to 0.5 μg/mL, which are considered to be intermediate resistance strains34.\n\n‘*’ indicates H. pylori isolates with A2143G and T2182C mutation at MIC values, which are considered to be intermediate resistance strains.\n\nAbbreviations: ‘N.A.’ – not applicable; ‘S’ – susceptible; ‘R’ – resistance.\n\n\nDiscussion\n\nAntimicrobial resistance in H. pylori has become a global health problem because the prevalence of infection and incidence is increasing worldwide37–39. The increasing H. pylori resistance to antimicrobial agents, such as clarithromycin, is considered the main factor for reduced treatment success in several countries, including Vietnam and Japan17,18,40–42. Therefore, the understanding of geographical region specific prevalence is crucial for treatment of H. pylori infection.\n\nVietnam is categorised as a region with a high prevalence of H. pylori infection and an intermediate risk of gastric cancer43,44. In Vietnam (Ho Chi Minh City and Hanoi), clarithromycin and metronidazole are recommended as a first-line therapy regimen13. Our present study showed that the overall resistance rate for clarithromycin and metronidazole was 85.5% and 37.8%, respectively. The high incidence of H. pylori strains resistant to clarithromycin and metronidazole in Vietnam might be attributed to the following: (i) unregulated or widespread over-the-counter use of antibiotics, (ii) clarithromycin is prescribed frequently for treatment due to its high bactericidal effect, and (iii) antibiotics are often used to treat H. pylori infection and other infections including respiratory tract infections (clarithromycin) and intestinal parasites (metronidazole)18,45,46. Of note, this study highlighted that clarithromycin resistance was the highest among the 193 H. pylori clinical isolates collected in 2015−2016, as compared to the other studies in which metronidazole has the highest resistance rate (69.9%−76.1%) in Vietnam18–20. The observation of high clarithromycin resistance rate from our data suggested the increasing occurrence of resistant strains among other antimicrobial agents. Therefore, constant surveillance for antimicrobial resistance rates is necessary to gain insights into effective eradication therapy of H. pylori infection.\n\nAnother interest of this study was to assess the variations of MIC values obtained from the clarithromycin-resistant strains. Our representative clinical isolates obtained from the gastric mucosa revealed that the majority of strains resistant to clarithromycin conferred MIC values ranging from 2 μg/mL to 16 μg/mL. There is also a degree of variation on the MIC range between studies19,32,47–49. The variability of MIC values for resistant isolates might be attributed to different gastric sites. The evidence is supported by Borody et al. who demonstrated that the bimodal distribution of clarithromycin resistance of isolates cultured from 4 gastric sites (i.e. antrum, distal body, proximal body and fundus) ranged from <0.016 μg/mL to 256 μg/mL50. The recent studies also demonstrated that MIC values for clarithromycin resistance vary at different gastric sites47–49. Therefore, the present results confirm previous studies that multiple gastric biopsies from different sites of the stomach are crucial for accurate diagnosis of H. pylori infection.\n\nFurthermore, antimicrobial susceptibility testing using MIC values is often used to determine the appropriate dosage of antimicrobial for a patient’s prescription. However, the respective antimicrobial resistance rate is based on the defined MIC breakpoints, which are much lower than the achievable tissue concentrations of antimicrobial agents such as clarithromycin (ranging from 5.2 μg/mL to 22.2 μg/mL)51. Only a few studies have reported the eradication rate of H. pylori infection with high MIC values (e.g. >24 μg/mL), highlighting that the significant eradication rate of 50%−80% on MIC-defined resistant strains can be achieved by administering PPI with precise antibiotic dosage and appropriate treatment duration20,32,52,53. Hence, further longitudinal studies on treatment efficacy and treatment guidelines are necessary for successful treatment.\n\nPoint mutations at positions 2142, 2143 and 2182 on the 23S rRNA gene were commonly reported25–27. Yet it remains unclear whether or not these point mutations could be a strong predictor of clarithromycin resistance23,29–31. In some studies, only the A2142G mutation was found to be associated with high MIC values54,55. While other studies showed that mutations at positions 2142 and/or 2143 were associated with clarithromycin resistance53,54,56,57. In addition, mutation T2182C was only reported in one study25. Here, we reported that H. pylori strains with mutations in A2143G and T2182C exhibited not only in clarithromycin-resistant strains, but also in susceptible strains as observed in Table 2. Similar to Phan et al.’s study19, none of the clarithromycin-resistant strains portrayed A2142C mutation in our study. It is important to note that the association of MIC values and point mutations was not identified in our work. Additionally, a proportion of all isolates had no point mutations in the 23S rRNA gene (Table 2). Further investigation on other nucleotide positions of the 23S rRNA region should be performed on these resistant strains58,59. Additionally, we suggested that a proportion of these resistant strains, which are not related to the 23S rRNA gene sequence, could be potentially related to other mechanisms such as the presence of an efflux pump (e.g. outer membrane protein hefA) or polymorphisms in the CYP2C19 gene60–62.\n\n\nConclusions\n\nIn conclusion, our present results confirm that MIC values are critical for accurate identification of antimicrobial resistant strains. Susceptibility tests prior to treatment are necessary to select the optimal H. pylori therapy regimens in Vietnam. Further studies on other resistance mechanisms, particularly the mutations of the host genes, will provide additional insights into the development of diagnostic biomarkers and therapeutic drugs.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details was obtained from the parents of the patients.\n\n\nData availability\n\nF1000Research: Dataset 1. A summary of patient information, antimicrobial susceptibility and clarithromycin resistance patterns, 10.5256/f1000research.8239.d11824963",
"appendix": "Author contributions\n\n\n\nC.Q. performed data analysis, interpreted the data, constructed and drafted the manuscript, and coordinated the analysis aspect of the study. S.T.P. participated in data interpretation, drafted the manuscript and provided critical revision of the manuscript. K.T.T. performed the experiments and responsible for data collection. B.T.P designed and coordinated the microbiological experiments. L.V.H supervised and assisted the design of clinical study. N.B.L.L and T.K.T. assisted the microbiological experiments. K.Q. participated in result discussion and provided critical revision of the manuscript. V.H.P. supervised the clinical study, interpreted the data and provided critical revision of the manuscript.\n\n\nCompeting interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThis work was supported by the Nam Khoa-Biotek and Nguyen Tri Phuong hospital.\n\n\nReferences\n\nSuerbaum S, Michetti P: Helicobacter pylori infection. N Engl J Med. 2002; 347(15): 1175–1186. PubMed Abstract | Publisher Full Text\n\nPeek RM Jr, Blaser MJ: Helicobacter pylori and gastrointestinal tract adenocarcinomas. Nat Rev Cancer. 2002; 2(1): 28–37. PubMed Abstract | Publisher Full Text\n\nLacy BE, Rosemore J: Helicobacter pylori: ulcers and more: the beginning of an era. J Nutr. 2001; 131(10): 2789S–2793S. PubMed Abstract\n\nEusebi LH, Zagari RM, Bazzoli F: Epidemiology of Helicobacter pylori infection. Helicobacter. 2014; 19(Suppl 1): 1–5. 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PubMed Abstract | Publisher Full Text\n\nNguyen TL, Uchida T, Tsukamoto Y, et al.: Helicobacter pylori infection and gastroduodenal diseases in Vietnam: a cross-sectional, hospital-based study. BMC Gastroenterol. 2010; 10: 114. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKatelaris PH: Helicobacter pylori: antibiotic resistance and treatment options. J Gastroenterol Hepatol. 2009; 24(7): 1155–1157. PubMed Abstract | Publisher Full Text\n\nGonzales R, Bartlett JG, Besser RE, et al.: Principles of appropriate antibiotic use for treatment of acute respiratory tract infections in adults: background, specific aims, and methods. Ann Intern Med. 2001; 134(6): 479–486. PubMed Abstract | Publisher Full Text\n\nSelgrad M, Tammer I, Langner C, et al.: Different antibiotic susceptibility between antrum and corpus of the stomach, a possible reason for treatment failure of Helicobacter pylori infection. World J Gastroenterol. 2014; 20(43): 16245–16251. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAyala G, Galvan-Portillo M, Chihu L, et al.: Resistance to antibiotics and characterization of Helicobacter pylori strains isolated from antrum and body from adults in Mexico. Microb Drug Resist. 2011; 17(2): 149–155. PubMed Abstract | Publisher Full Text\n\nRimbara E, Noguchi N, Tanabe M, et al.: Susceptibilities to clarithromycin, amoxycillin and metronidazole of Helicobacter pylori isolates from the antrum and corpus in Tokyo, Japan, 1995-2001. Clin Microbiol Infect. 2005; 11(4): 307–311. PubMed Abstract | Publisher Full Text\n\nBorody TJ, Clancy R, Warren EF, et al.: Antibiotic sensitivities of Helicobacter pylori vary at different gastric mucosal sites. Dordrecht, London, Kluwer Academic. 2003; 373–381. Publisher Full Text\n\nGustavson LE, Kaiser JF, Edmonds AL, et al.: Effect of omeprazole on concentrations of clarithromycin in plasma and gastric tissue at steady state. Antimicrob Agents Chemother. 1995; 39(9): 2078–2083. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKim JM, Kim JS, Jung HC, et al.: Distribution of antibiotic MICs for Helicobacter pylori strains over a 16-year period in patients from Seoul, South Korea. Antimicrob Agents Chemother. 2004; 48(12): 4843–4847. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDe Francesco V, Margiotta M, Zullo A, et al.: Clarithromycin-resistant genotypes and eradication of Helicobacter pylori. Ann Intern Med. 2006; 144(2): 94–100. PubMed Abstract | Publisher Full Text\n\nvan Doorn LJ, Glupczynski Y, Kusters JG, et al.: Accurate prediction of macrolide resistance in Helicobacter pylori by a PCR line probe assay for detection of mutations in the 23S rRNA gene: multicenter validation study. Antimicrob Agents Chemother. 2001; 45(5): 1500–1504. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOwen RJ: Molecular testing for antibiotic resistance in Helicobacter pylori. Gut. 2002; 50(3): 285–289. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHulten K, Gibreel A, Skold O, et al.: Macrolide resistance in Helicobacter pylori: mechanism and stability in strains from clarithromycin-treated patients. Antimicrob Agents Chemother. 1997; 41(11): 2550–2553. PubMed Abstract | Free Full Text\n\nOcchialini A, Urdaci M, Doucet-Populaire F, et al.: Macrolide resistance in Helicobacter pylori: rapid detection of point mutations and assays of macrolide binding to ribosomes. Antimicrob Agents Chemother. 1997; 41(12): 2724–2728. PubMed Abstract | Free Full Text\n\nBinh TT, Shiota S, Suzuki R, et al.: Discovery of novel mutations for clarithromycin resistance in Helicobacter pylori by using next-generation sequencing. J Antimicrob Chemother. 2014; 69(7): 1796–1803. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRimbara E, Noguchi N, Kawai T, et al.: Novel mutation in 23S rRNA that confers low-level resistance to clarithromycin in Helicobacter pylori. Antimicrob Agents Chemother. 2008; 52(9): 3465–3466. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu ZQ, Zheng PY, Yang PC: Efflux pump gene hefA of Helicobacter pylori plays an important role in multidrug resistance. World J Gastroenterol. 2008; 14(33): 5217–5222. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHirata K, Suzuki H, Nishizawa T, et al.: Contribution of efflux pumps to clarithromycin resistance in Helicobacter pylori. J Gastroenterol Hepatol. 2010; 25(Suppl 1): S75–79. PubMed Abstract | Publisher Full Text\n\nZhang M: High antibiotic resistance rate: A difficult issue for Helicobacter pylori eradication treatment. World J Gastroenterol. 2015; 21(48): 13432–13437. PubMed Abstract | Publisher Full Text | Free Full Text\n\nQuek C, Pham ST, Tran KT, et al.: Dataset 1 in: Antimicrobial susceptibility and clarithromycin resistance patterns of Helicobacter pylori clinical isolates in Vietnam. F1000Research. 2016. Data Source"
}
|
[
{
"id": "14071",
"date": "31 May 2016",
"name": "Duc Trong Quach",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is one among the informative studies about the antimicrobial susceptibility and clarithromycin resistance patterns of Helicobacter pylori clinical isolates in Vietnam. The title is appropriate for the content. The methods and analysis of the results are well-described and appropriate.\nHowever, there are several minor revisions that the authors should be considered to make results of the paper more clinically meaningful:\nThe design of this study is not prospective randomized one. It is a cross-sectional study.\n\nThe clinical information of the patients recruited in the study should be clarified: are they naïve patients or not. This information is essential to understand the true situation of antimicrobial susceptibility in Vietnam. As a result, the conclusion “Susceptibility tests prior to treatment are necessary to select the optimal H. pylori therapy regimens in Vietnam” may be not appropriate without this information.\n\nThe authors should also addressed the weak points of the studies. Although this is a multi-center study, all of the medical centers locates in southern Vietnam. The picture of antimicrobial susceptibility and clarithromycin resistance patterns of Helicobacter pylori has been shown to be somewhat different in Central and Northern Vietnam. Therefore, the author should change the title from “in Vietnam” to “in southern Vietnam”, or they can keep the title as it was but add a sentence which mentions this weak point of the study.",
"responses": []
},
{
"id": "13392",
"date": "02 Aug 2016",
"name": "Simon Cutting",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn general this is an interesting paper reporting on resistance ot the antibiotic clarithromycin in Vietnam and the relevance of this resistance to Helicobacter pylori infection. The main outcome of this work is that it demonstrates the need for susceptibility testing prior to treatment. It is encouraging that this work is led by Vietnamese scientists and the work appears of a high standard.\n\nIt would have been useful to have a figure showing the mutational hotspots within the 23S rRNA gene.\n\nGeneral\n\nBacterial species names should be written in italics\n\nThe MICs stated on page 3 (3rd para) show considerable variation with a large range, i.e., >256 mg/ml and >0.5 mg/ml. What is considered significant?\n\nMIC should be used as an abbreviation in Figures and Tables as well as text, e.g. Fig 2 and Table 2",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-671
|
https://f1000research.com/articles/4-913/v1
|
28 Sep 15
|
{
"type": "Research Article",
"title": "Measurement of a 5-gene panel in whole blood in kidney transplant recipients with acute rejection and stable controls",
"authors": [
"Gareth Betts",
"Jeroen Van Der Net",
"Sushma Shankar",
"Peter Friend",
"Paul Harden",
"Kathryn Wood",
"Jeroen Van Der Net",
"Sushma Shankar",
"Peter Friend",
"Paul Harden",
"Kathryn Wood"
],
"abstract": "New biomarkers are required to detect acute rejection (AR) in kidney transplant recipients (KTRs) to avoid invasive kidney biopsies. We assess whether a 5-gene panel (DUSP1; NKTR; PBEF1; MAPK9; and PSEN1) in whole blood samples that has previously been shown to identify AR in a paedriatric KTR population is able to distinguish AR in a UK population of adult Caucasian KTR patients.",
"keywords": [
"Renal",
"allograft",
"rejection",
"biomarker",
"acute",
"whole blood",
"kidney",
"gene expression"
],
"content": "Introduction\n\nFurther improvements are required to monitor rejection of kidney allografts post-transplant. Current methodology to detect rejection by kidney biopsy is invasive and presents a risk to the patient, whilst an inadequate biopsy sample may prevent an accurate diagnosis. The patient risk associated with biopsy deters some transplant centers from performing protocol biopsies, instead using clinical signs of allograft damage to inform a decision to perform an indication biopsy. Significant immune mediated damage to the allograft may occur before rejection is clinically visible. Therefore new biomarkers that can be repeatedly measured by minimally invasive sampling that identifies damaging alloreactivity prior to significant pathology and assesses the whole organ are required1.\n\nA 5-gene panel (DUSP1; NKTR; PBEF1; MAPK9; and PSEN1) in whole blood has been shown to distinguish stable allografts from those with acute rejection (AR) in paediatric kidney transplant recipients (KTRs) with mixed ethnicity. Expression of each gene was significantly different between kidneys with AR vs stable function in a separate paediatric validation population (of which 60% had received a deceased-donor allograft)2. Interestingly, expression of these genes appeared to identify borderline rejection as AR and may therefore predict AR before it has become clinically evident.\n\nThe same panel was recently validated in a Korean adult KTR population, although only PSEN1 and MAPK9 were significantly different between AR and control groups3. The lack of differential expression between stable and AR groups for genes DUSP1, NKTR and PBEF1 might demonstrate a variability in gene expression between KTR populations; however these three genes did contribute to the ability of the 5-gene panel to distinguish AR from non-AR using multivariate logistic regression analysis.\n\nThe expression data presented in our study suggests that these 5 genes, measured in whole blood of KTRs, do not distinguish between stable function and AR in Caucasian KTRs in the UK. Our data, provided with complete clinical and raw gene expression data, will be available to be incorporated into larger studies in the future, providing an important resource.\n\n\nMethods\n\n7 KTRs with clinical evidence of AR confirmed by allograft biopsy (5 AR, 2 borderline changes suspicious for AR) and 5 control KTRs with stable graft function closely matched for Human Leukocyte Antigen mismatch, race, initial graft function, induction and maintenance therapy were studied (Supplementary material Table 1; REC number 07/H0603/26, following informed consent). KTRs were adult Caucasians of which 20% had received a deceased-donor allograft. All patients were negative for donor specific antibodies pre-transplantation and therefore did not receive desensitization. There was no difference in panel reactive antibodies between control and AR groups. Blood samples were collected during AR episodes occurring on days 4, 6, 6, 41, 48, 210 and 393 in individual KTRs post transplant.\n\ncDNA was produced from whole blood RNA collected in BD tempus tubes and isolated using the Tempus Spin RNA Isolation kit (BD). Expression of a 5-gene panel comprising DUSP1, PBEF1, PSEN1, MAPK9, NKTR (normalized with HPRT expression; Supplementary material Table 2) was accessed by qPCR using TaqMan Gene Expression Assays (Life Technologies) and measured using a Stratagene Mx3000P qPCR machine (Agilent Technologies). Kits were used according to manufacturers instructions.\n\nEach AR episode was treated successfully with three i.v. daily doses of 500-mg methylprednisolone, as measured by restored eGFR to baseline. Two patients with AR additionally received 30mg i.v alemtuzumab. All patients with AR episodes were re-bled at 1 year post-transplantation, and maintained stable graft function and eGFR, except 1 KTR with AR at day 393 and a second patient that declined follow-up at 1 year.\n\nUnivariate logistic regression analysis was performed using IBM SPSS version 22. All other statistics were performed in GraphPad Prism version 5.0c.\n\n\nResults\n\nUnivariate logistic regression analysis was performed on 2-ΔΔCt values calculated using either the pre-operative time point ΔCt of each KTR4 (Figure 1; DUSP1: p=0.772; MAPK9: p=0.733; PBEF1: p=0.525; NKTR: p=0.698; PSEN1: p=0.935) or an average of all stable KTR ΔCt values as a calibrator for each gene. With both methods of 2-ΔΔCt calculation, univariate logistic regression analysis showed that no single gene was a significant predictor of AR. The size of our cohort was insufficient to allow for multivariate analysis. Expression of each gene showed no significant difference when AR and one year samples (DUSP1: p=0.44; MAPK9: p=0.44; PBEF1: p=0.44; NKTR: p=0.31; PSEN1: p=0.44) or AR and stable KTR (DUSP1: p=0.88; MAPK9: p=0.76; PBEF1: p=0.76; NKTR: p=0.52; PSEN1: p=1.0) samples were compared using Wilcoxon matched-pairs signed rank test and Mann-Whitney test respectively.\n\n\nConclusion\n\nThis study indicates that the expression of this 5-gene panel is unable to distinguish AR from stable allograft function in this adult Caucasian population, which might be explained by differences in expression of these genes between different populations. Importantly, the raw data provided in supplemental tables here are available to supplement future studies involving larger cohorts of patients.",
"appendix": "Author contributions\n\n\n\nGareth Betts: performed experiments, analysed data, wrote manuscript; Jeroen Van Der Net: identified and analysed clinical details of patients; Sushma Shankar: identified and analysed clinical details of patients; Peter Friend: designed research, intellectual input; Paul Harden: intellectual input, analysis of clinical details of patients; Kathryn Wood: designed research, wrote grants that provided funds to perform work, intellectual input.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nWellcome Trust grant 082519/Z/07/Z awarded to Professor Kathryn Wood funded this work.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgement\n\nThe authors thank Sally Ruse for phlebotomy and organizing patient logistics.\n\n\nSupplementary material\n\nTable 1. Full clinical details of KTRs with an acute rejection episode and stable controls is shown. Columns A–F represent patient demographics; columns G–K initial immunosuppression; column L initial graft function; columns M–Q biopsy data; column R long-term outcomes.\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6941.s103109\n\nTable 2. Gene expression Ct values for DUSP1, MAPK9, PBEF1 (NAMPT), NKTR, PSEN1 and the endogenous control HPRT. Data was collected in duplicate tubes and the average gene expression was determined. The average of HPRT expression was subtracted from the average gene expression of the target gene, to create ΔCt values for target genes. ΔΔCt values were subsequently derived by subtracting ΔCt of the preoperative time point from the ΔCt of the time point of interest: e.g. (AR time point ΔCt DUSP1) – (preoperative time point ΔCt DUSP1) = ΔΔCtDUSP1. ΔΔCt values were expressed as 2-ΔΔCt values.\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6941.s103110\n\n\nReferences\n\nHeidt S, San Segundo D, Shankar S, et al.: Peripheral blood sampling for the detection of allograft rejection: biomarker identification and validation. Transplantation. 2011; 92(1): 1–9. PubMed Abstract | Publisher Full Text\n\nLi L, Khatri P, Sigdel TK, et al.: A peripheral blood diagnostic test for acute rejection in renal transplantation. Am J Transplant. 2012; 12(10): 2710–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLee A, Jeong JC, Choi YW, et al.: Validation study of peripheral blood diagnostic test for acute rejection in kidney transplantation. Transplantation. 2014; 98(7): 760–5. PubMed Abstract | Publisher Full Text\n\nBetts G, Shankar S, Sherston S, et al.: Examination of serum miRNA levels in kidney transplant recipients with acute rejection. Transplantation. 2014; 97(4): e28–30. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "10625",
"date": "14 Oct 2015",
"name": "Anita S Chong",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nOverall, an important preliminary study assessing the 5 gene panel in whole blood to distinguish acute rejection from stable kidney allografts. The study is very small of only 7 AR (and 2 are borderline AR), and 5 controls, so it is unclear whether there is statistical power to generate the significant differences observed in previous studies referenced as #2 and #3. Inclusion of a discussion on the limitation of this study would be useful. There is a discrepancy with the study by Li et al 2012, however Li et al. indicated \"all 5 genes had significant change in expression only with the presence of donor specific antibody\" and since the 7 patients did not have DSA, this difference should be highlighted.With regards to the Lee et al. 2014 study, the overall discriminatory effectiveness of the 5 gene set was observed to be much reduced compared to the Li et al study. Only MAPK9 and PSEN1 were significantly different in AR, even then there was wide overlap in the values between the CMR and Healthy control groups. Notably there was no difference in the gene expression between the AMR and healthy control groups, a note of concern since the Li et al. demonstrated an association between DSA and the 5 gene panel. Furthermore it is unclear how the raw data could be used to supplement future studies; clarification is therefore needed. Without such a road map for the potential use of the data set, the study may be too preliminary for firm conclusions.",
"responses": []
},
{
"id": "12321",
"date": "08 Mar 2016",
"name": "Titte Srinivas",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is valuable work that has the caveat that it is applicable to Caucasian recipients. That findings were easily translatable from a pediatric population to adults implies some robustness. This needs to be validated in further study.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/4-913
|
https://f1000research.com/articles/5-647/v1
|
12 Apr 16
|
{
"type": "Research Article",
"title": "A computer model simulating human glucose absorption and metabolism in health and metabolic disease states",
"authors": [
"Richard J. Naftalin"
],
"abstract": "A computer model designed to simulate integrated glucose-dependent changes in splanchnic blood flow with small intestinal glucose absorption, hormonal and incretin circulation and hepatic and systemic metabolism in health and metabolic diseases e.g. non-alcoholic fatty liver disease, (NAFLD), non-alcoholic steatohepatitis, (NASH) and type 2 diabetes mellitus, (T2DM) demonstrates how when glucagon-like peptide-1, (GLP-1) is synchronously released into the splanchnic blood during intestinal glucose absorption, it stimulates superior mesenteric arterial (SMA) blood flow and by increasing passive intestinal glucose absorption, harmonizes absorption with its distribution and metabolism. GLP-1 also synergises insulin-dependent net hepatic glucose uptake (NHGU). When GLP-1 secretion is deficient post-prandial SMA blood flow is not increased and as NHGU is also reduced, hyperglycaemia follows. Portal venous glucose concentration is also raised, thereby retarding the passive component of intestinal glucose absorption. Increased pre-hepatic sinusoidal resistance combined with portal hypertension leading to opening of intrahepatic portosystemic collateral vessels are NASH-related mechanical defects that alter the balance between splanchnic and systemic distributions of glucose, hormones and incretins.The model reveals the latent contribution of portosystemic shunting in development of metabolic disease. This diverts splanchnic blood content away from the hepatic sinuses to the systemic circulation, particularly during the glucose absorptive phase of digestion, resulting in inappropriate increases in insulin-dependent systemic glucose metabolism. This hastens onset of hypoglycaemia and thence hyperglucagonaemia. The model reveals that low rates of GLP-1 secretion, frequently associated with T2DM and NASH, may be also be caused by splanchnic hypoglycaemia, rather than to intrinsic loss of incretin secretory capacity. These findings may have therapeutic implications on GLP-1 agonist or glucagon antagonist usage.",
"keywords": [
"Simulation of human intestinal glucose absorption",
"GLP-1",
"Insulin",
"Glucagon",
"Superior mesenteric arterial blood flow",
"Non-alcoholic steatohepatitis",
"Type 2 diabetes",
"Portosystemic shunting",
"Hyperinsulinaemia",
"Hyperglucagonaemia."
],
"content": "Abbreviations\n\nAMP, adenosine monophosphate; AMPK, adenosine monophosphate–activated kinase; Blood vessel resistance, Hg.s ml-1; C, compartmental volume compliance; GLP-1, glucagon-like peptide-1; GLUT2, low affinity passive glucose transporter type 2 expressed in intestine, liver and pancreatic beta cells; HA, hepatic artery; HOMA, homeostasis model assessment; HV, hepatic vein; Intestinal paracellular glucose permeability, Pgl; half maximal concentration, K½; KO, genetically mutated knock out; L-M method, Levenberg-Marquardt of non-linear least square regression; NASH, non-alcoholic steatohepatitis; Net hepatic glucose uptake, NHGU; OGTT, Oral glucose tolerance test; PV, Portal vein; PSS R, portosystemic shunt resistance; ΔP, Pressure gradients, mm Hg; SGLT1, sodium dependent glucose transporter; SMA, superior mesenteric artery; superior mesenteric capillary, SM cap; Type 2 diabetes mellitus, T2DM; Vmax maximal velocity.\n\n\nIntroduction\n\nThe sodium dependent glucose transporter SGLT1 is the only active component of intestinal transport sugar absorption. When SGLT1 is deficient, as in glucose-galactose malabsorption syndrome1–3, or inactivated by specific inhibitors, such as phloridzin, or similarly acting high efficacy inhibitors e.g. GSK16142354, small intestinal sugar absorption is blocked and the ingested sugar load is relegated to the large intestine where it becomes subject to fermentation processes.\n\nIt has been argued that exposure to high intestinal luminal glucose concentrations ≥ 15mM, or more modest glucose loads, supplemented with artificial sweeteners, induces small intestinal apical membrane passive glucose transport via GLUT25,6. This process is stimulated by enterocyte AMP kinase(AMPK), triggered by opening of Cav 1.3 Ca2+ channels following SGLT1-dependent depolarization of the apical membrane potential7. However, whether apical GLUT2 has any functional role in net glucose absorption has been questioned. No discernible effect on net intestinal glucose absorption in vivo is observed in GLUT2 knock out, (KO) mice,8.\n\nGlucose absorption can only be enhanced by apical GLUT2, when the enterocyte and submucosal glucose concentrations are lower than in the intestinal lumen. The time required to reach steady state glucose accumulation within the enterocytes in vitro following exposure is ≤ 2 min9,10 and within 5 to 10 minutes in vascularly perfused frog11. As net glucose transport across the basolateral membranes is entirely due to passive processes, it follows that this can only occur when intracellular glucose exceeds the submucosal concentrations. Estimates of enterocyte glucose concentrations that are lower than that within the submucosa have been reported12, but as glucose accumulation only occurs in a small proportion of the enterocytes within the intestinal villus, are ascribable to overestimates of the compartmental volume into which glucose is actively accumulated;13. When the intestinal luminal glucose is lower than the enterocyte concentration, any apical component for passive glucose absorption, such as GLUT2, will hinder, rather than assist, net absorption14.\n\nThe experimental evidence supporting the accelerant role of apical GLUT2 in glucose uptake is based on data obtained with pharmacological concentrations of inhibitors, such as phloretin and cytochalasin B. These agents have multiple inhibitory effects, on glucose, Cl-, urea and water permeability. When phloridzin is already present, additional high phloretin concentrations may further inhibit any residual SGLT1 glucose transport activity1 and also prevent paracellular sugar absorption by blocking solvent drag effects14,15. Additionally, any of the pro-absorptive roles of apical GLUTs seen with phloridzin present will be artificially enhanced by the depressed cytosolic glucose concentration14.\n\nWhen the intestinal luminal glucose concentration is higher than mesenteric capillary glucose concentration transcellular glucose transport may be supplemented, by passive flow via paracellular routes from the intestinal lumen16–19. With luminal glucose concentration > 15 mM the passive transport mode becomes predominant. A variable paracellular sugar permeability explains the non-saturable nature of intestinal glucose transport over a concentration range from 15mM to 100mM20,21 and how ingested ligands that are not transported via either SGLT1 or GLUT2, e.g. rhamnose, L-glucose, or mannitol, rapidly appear in human urine. Paracellular shunts also explain why molecules show size selectivity of transepithelial flows,22–24 and how inflammatory intestinal diseases, known to loosen intercellular junctions25,26 induce large increases probe entry into both plasma and urine27.\n\nThe highest rates of glucose transport obtained in exercising dogs are more than an order of magnitude higher than those obtained in vitro20,28. In vitro experimentation on isolated intestine or intestinal tissue or cells, which has become the normal mode of investigation of intestinal absorption, necessarily removes the intestinal capillary network. This capillary plexus provides the essential bridging component between the proximal sugar absorptive process and its distribution to the splanchnic and systemic circulations. So when it is removed, the major part of the sugar absorption control system is destroyed20,29–31. It is evident that lack of capillary perfusion of in vitro intestine heavily masks optimal absorptive performance21,32.\n\n\nIntegration of intestinal glucose absorption with splanchnic circulation\n\nThe discovery that oral glucose generates a more rapid and larger metabolic response to insulin than equivalent amounts of intravenous glucose suggested that substances secreted by the gut wall during glucose absorption augment insulin release from pancreatic islets and its activity on liver and muscle33–36. It was inferred that a portal venous signal raises hepatic glucose uptake and stimulates hepatic glycogen synthesis, independent of a rise in insulin.\n\nThe superior mesenteric artery (SMA) supplies 600–1800 ml min-1 blood to the glucose absorptive portion of the proximal small intestine (Figure 2A and 2B). When ingested glucose is present in the intestinal lumen, splanchnic capillaries channel the absorbate via the portal vein to the liver. Splanchnic blood has approximately double the concentrations of absorbed materials and also of pancreatic hormones and incretins that are present in the systemic circulation (37,38; Figure 3E–G).\n\n\nAn integrated model of glucose transport and metabolism\n\nIt is evident that the incretin response to luminal, submucosal and splanchnic venular glucose; the pancreatic islet secretory response to systemic glucose; the hepatic response to incretins; the intrahepatic circulatory responses to portal blood pressure and the systemic metabolic responses to systemic blood concentrations of glucose, insulin and incretins are interrelated and interdependent39–41.\n\nA quantitative model of the integrated response to glucose ingestion is both lacking and needed to assimilate the extent to which the incretin response to intestinal glucose load affects the balance between splanchnic–systemic blood flow and hepatic and peripheral glucose metabolism. Although there are several compartmental models that simulate intestinal glucose absorption and its subsequent metabolism by liver, none take account of the altered splanchnic blood flows that accompany and accommodate glucose absorption. These models assume that the splanchnic blood compartment imposes no impediment to flows into the liver42–44. As will be seen from the simulations here, the GLP-1 controlled flows of SMA are an important component in glucose absorption.\n\nOther models, based mainly on the work of Cherrington’s and Bergman’s laboratories,45,46 give predictive indices of glucose metabolism and insulin-sensitivity in humans with normal and diabetic metabolism. The HOMA model of whole body glucose metabolism in relation to insulin secretion47,48 accounts for the hepatic contribution to homeostatic control of plasma glucose, but lacks an account of the incretin response, or splanchnic flow response to glucose ingestion, or how hepatic steatosis and/or portal-systemic venous shunting affect these responses. These issues are addressed by the current model.\n\n\nMethods\n\nReplication of the human response to oral glucose ingestion necessitates simulation of the circulatory response to glucose, integrated with hormonal (insulin and glucagon) and incretin (GLP-1) secretion and their effects on the liver and pancreas, also both the peripheral insulin-sensitive (muscle and adipose) tissues and insulin-insensitive (brain, skin and bone) glucose uptakes and metabolism (Figure 1).\n\nThis model of glucose absorption and metabolism was created with several aims. The first was to provide a quantitative simulation of the effects of changes of capillary perfusion rates on intestinal glucose absorption in health and disease. The second was to provide a broader understanding of how incretins affect the whole body response to glucose. The third aim was to demonstrate how metabolic diseases such as NAFLD, NASH and T2DM alter glucose and uptake and metabolism.\n\nThe model of whole body glucose absorption builds on those of Granger and Pappenheimer,29,49. The salient features of the current model are simulation of resting human systemic and splanchnic blood flows and pressures before, during and after glucose absorption. Sets of sub-models simulating the time course of changes in flows and concentrations of glucose, insulin, glucagon and the incretin GLP-1 following intra-duodenal glucose gavage, are embedded within this circulation model (Figure 1; for specific details of the model parameters given in parameter Table 2, see also Table 1). Intestinal glucose absorption is simulated here following initiation of a standard glucose tolerance test by duodenal gavage. By-passing the stomach avoids the extra complexities resulting from control of gastric emptying rates. Although these factors are important, they are inessential to the intestinal absorptive and subsequent vascular and metabolic processes50.\n\nNumber prefixes refer to position in Figure 1.\n\nAll the simulations were generated using Berkeley Madonna version 9.0. (http://www.berkeleymadonna.com), a modelling and analysis program that solves simultaneous non-linear differential equations. It runs on Microsoft Windows 7–10, Macintosh and Linux platforms. The computer simulations are done using the option solving stiff non-linear simultaneous differential equations using the Rosenbrock simulation method51 with a step time of 100 µs and error tolerance of 1×10-8. Simulations usually extend for 1500 virtual seconds, normally outputted at 5 second intervals. The numerical data output tables were subsequently processed in Microsoft Excel 2013 for Windows 2013 and graphed using the build-in Chart facility. Further analysis was done using self-generated Excel Solver macros, and the Levenberg-Marquardt, L-M, least squares minimizing routines available with Synergy Software Kaleidagraph version 3.52, (www.synergy.com). This conveniently includes error estimations of the derived parameters.\n\nCardiac output at rest is set at approximately 5.5 L/min and mean aortic blood pressure at ≈ 105 mm Hg. The core model blood vessel resistances and compliances are adjusted to obtain appropriate normal human steady state flows and pressures. The compartmental volumes are determined by their compliances, C and the transluminal pressure. Their initial and steady state values are adjusted to match known human values. The most pertinent compartmental compliances are the superior mesenteric capillary (SM cap) and hepatic sinusoidal beds. The circulating blood volume is assumed to be a third of the extracellular volume into which glucose, insulin and glucagon are distributed rapidly.\n\nThe main components of the model of glucose circulation and metabolism. Intestinal absorption, is modelled as active and passive parallel transmission elements connecting the intestinal lumen with the submucosal capillary bed. Passive glucose flows depend on the glucose concentration gradient existing between the intestinal lumen and modal sub-mucosal glucose concentration and linked via the passive intestinal paracellular glucose permeability. The active component to intestinal uptake is assumed to be a saturable function of luminal concentration with constant Na+ concentration = 140 mM (Figure 1 (1), Table 1B equation 1).\n\nNet hepatic glucose uptake NHGU and hepatic glucose metabolism. Glucose flows via the portal circulation into the liver, where it is absorbed via sinusoidal GLUT2 and metabolized by insulin and GLP-1-dependent processes, the non-absorbed glucose flows via to the hepatic vein to the systemic circulation. The rate of hepatic glucose uptake and metabolism is controlled by the synergistic incretin and insulin dependent Vmax of hepatic GLUT2 and are tightly coupled to glucokinase activity, Glucose can also be regenerated by glucagon-dependent gluconeogenesis and glycogenolysis (Figure 1 (4), Table 1B equation 4).\n\nGlucose enters into the systemic circulation via the hepatic vein (Figure 1 (2), Table 1B equation 2). It is metabolized by either insulin-dependent processes in muscle and adipose tissue, to which is entry is controlled by the insulin- and GLP-1-dependent Vmax of GLUT4 (Km 2.5 mM glucose), Figure 1 (5), Table 1B equation 5. Additionally, insulin-independent glucose uptake processes in brain, bone and skin consume glucose, entry to these tissues is controlled via GLUT1 parameters (Vmax and Km) Figure 1 (6), Table 1B equation 6.\n\nInsulin is released by pancreatic islet β cells into the superior mesenteric blood compartment, partially in response to a Michaelis-Menten function of systemic arterial glucose concentration. GLUT2 is a rate determining step of this process (Figure 1, Table 1C equation 1).\n\nGlucagon, like insulin, is released from the pancreatic islets (α-cells) into the superior mesenteric blood compartment and circulates in the splanchnic and systemic circulations its release is suppressed by raised systemic glucose as a hyperbolic function of glucose concentrations Ki controlled by GLUT2 (Figure 1, Table 1E equation 1).\n\nIn contrast with glucagon and insulin, which are sensitive to systemic arterial glucose, incretin secretion rates are controlled by the splanchnic capillary glucose concentration. Incretins (GLP-1 and GLP-1-2) are released from proximal intestinal enteroendocrine L cells and flow directly into the portal blood compartment, the stimulus for their release is assumed to be the glucose concentration within this superior mesenteric capillary compartment, determined by GLUT2 Km (Table 1E equation 2).\n\nEstimation of the sensitivities of the flow and concentration variables. Altering single parameters e.g. intestinal paracellular glucose permeability, Pgl, or the glucose sensitivity of enteroendocrine cell GLP-1secretion have many important quantitative and qualitative effects on the flows of blood glucose hormones and incretins. These responses may be linear, where it is simple to estimate the sensitivity by linear regression, or hyperbolic. In this latter case the function is normally fitted to a hyperbolic curve, defined by two parameters, the maximal rate, Vmax, or the concentration of e.g. GLP-1, or the resistance to blood flow giving half maximal concentration, K½ or flow rates. These parameters are estimated by non-linear least squares fits of the hyperbolic function to the observed data. The standard error of these fits is < 5% and as it does not represent an experimental error is omitted. As there is significant interaction between several key effectors, e.g. GLP-1secretion rate and paracellular glucose permeability, Pgl, a measure of this interaction is required. All of the 3D surface plots of the dependent variable, z with respect to alterations in the independent variables x and y can be fitted using least square regression or minimal Chi2 fits either to the second order surface equation, where z = a.x2 + b.y2 + c.x.y + d.x + e.y + f or the equivalent third order equation.\n\nThe key coefficient required to estimate the degree of second order interaction between the two variables x and y is c. For positive x*y interactions c > 0 for negative x*y interactions c < 0. Examples of positive interaction are seen in Figure 5A, where SM arterial flow varies as an increasing function of both GLP-1secretion and paracellular glucose permeability, Pgl. However, with Pgl = 0 or GLP-1≅ 0, SM flow is small 200 ml min-1. SMA flow after feeding increases as a linear function of GLP-1 and as a hyperbolic function of Pgl; K½ = 0.02 μm s-1 and the interaction coefficient c for Figure 5D = 4.1, indicating a strong positive interaction between Pgl and GLP-1secretion, as can be seen from the upward elevation of the surface towards higher values of both independent variables. In contrast, during fasting, when intestinal glucose absorption is absent, although SMA increases with GLP-1secretion, there is no effect of altering Pgl, so coefficient c = 0. Where the independent variables both independently x and y cause a reduction in response, i.e. negative response, as is the effect of increasing GLP-1secretion on SM capillary glucose during feeding, then when both are increased, c = -4.58 during feeding, but during fasting the response c = 0.\n\nBlood flow. The simulations are simplified by assuming that superior mesenteric artery supplying blood to the small intestine is the only flow resistance directly responsive to glucose (Table 1A equation 7, Figure 1 (7)).\n\nAll other blood flow changes are indirect reactions to this primary response. Blood flows are determined directly by the pressure gradients ΔP between the neighbouring nodal points in the circulation model (Table 1A equation 7, Figure 1 (7)).\n\nAs blood flows and pressures within the network obey Kirchoff’s laws, flow changes in other parts of network result from passive reactivity. The initial and steady state compartment volumes are adjusted to match known human values. For typical compartmental pressure change generated by change in volume see Figure 2D and 2E and Table 2. Changes in compartmental volumes (ml) following perturbations in blood flow are determined by their compliances, C and changes in transluminal pressure, generated by the blood flows.\n\nAll other compartments in Figure 1 depend on their assigned initial volumes and compliances and the integrated inflows and outflows. The most relevant compartmental compliances are those determining the splanchnic blood volumes, i.e. the superior mesenteric capillary bed and the hepatic sinusoidal bed resulting from glucose-dependent alteration of SMA flow.\n\nThe total circulating blood volume is assumed to be a third of the extracellular volume into which glucose, insulin and glucagon are rapidly distributed in all accessible compartments52. It is assumed that all the circulating glucose, hormones and incretin concentrations rapidly equilibrate between the circulating blood and their neighbouring extracellular fluid compartments. Thus the total circulating blood volume is 5 L and the fluid volume is initially and remains at approximately 15 L.\n\nGlucose flow sub-model. Both splanchnic and systemic glucose circulations are incorporated within the core blood circulatory model. Ingested fluid entry and exit from the stomach, intestine and colon are programmed in order to fully replicate oral glucose tolerance tests. However, only a standard glucose dose via duodenal gavage delivery is shown in this present study. The key equations determining glucose flows are outlined in Figure 1. The parameters determining the rates of glucose flow and metabolism are shown in the Table 2.\n\nExplanation of the model components of glucose circulation and metabolism. Intestinal absorption, is modelled by parallel active and passive transmission elements connecting the intestinal lumen with the submucosal capillary bed (Table 1B Glucose equation 1).\n\nPassive glucose flows depend on the glucose concentration gradient existing between the intestinal lumen and sub-mucosal capillary glucose concentration and the passive intestinal paracellular glucose permeability, Pgl. The active component to intestinal uptake is assumed to be a saturable function of luminal concentration with constant Na+ concentration = 140 mM. In addition to glucose entry via the superior mesenteric capillary bed, glucose also enters the splanchnic circulation via the superior and inferior mesenteric arteries, splenic and coeliac arteries (Table 1B Glucose equations 2–7). Glucose concentrations, mM within each body compartment are obtained from the amounts of glucose (mmoles)/volumes (L) within each compartment.\n\nNet hepatic glucose uptake, NHGU and hepatic glucose metabolism (Glucose equation 4B). Glucose flows via the portal vein, PV into the liver, where it is absorbed via sinusoidal GLUT2 and metabolized by insulin and GLP-1-dependent processes starting with the enzyme glucokinase, the remaining non-absorbed glucose flows onwards via the hepatic vein, HV to the systemic circulation (Table 1B Glucose equation 4A). The rates of hepatic glucose uptake and metabolism are controlled by the synergistic incretin and insulin-dependent Vmax of hepatic GLUT2/glucokinase complex (Table 1B Glucose equation 4A). It is assumed that GLUT2 and glucokinase activities are tightly coupled, so hepatic glucose metabolism is synergistically controlled by activation of coupled insulin and GLP-1 receptor53,54 that modulates the combined GLUT2- glucokinase Vmax. Glucose can also be added to the hepatic sinusoidal circulation by glucagon-dependent gluconeogenesis and glycogenolysis, ultimately rate-limited by hepatic glucose 6 phosphatase activity55.\n\nSystemic glucose metabolism. Glucose enters the systemic circulation via the hepatic vein (HV). It is consumed by insulin-dependent processes in muscle and adipose tissue, entry to which is controlled by the insulin- and GLP-1-dependent Vmax of the glucose transporter GLUT4 (Table 1B Glucose equation 5B).\n\nAdditionally, insulin-independent glucose uptake processes in brain, bone and skin consume glucose, entry to these tissues is controlled via GLUT1 parameters (Vmax and Km)56,57 (Table 1B Glucose equation 5A).\n\nRenal glucose excretion. When the renal artery glucose concentration exceeds the ceiling for renal glucose reabsorption, glucose is excreted in urine at a rate proportional to the difference between renal glucose filtration rate (approximately 10% of renal artery flow and renal glucose re-absorptive capacity (Table 1B Glucose equation 6). Urinary glucose loss does not significantly affect glucose metabolism in any of the simulations.\n\nInsulin flow sub-model. Insulin is released from pancreatic islet β cells into the superior mesenteric blood compartment, partially in response to a GLUT2 Michaelis-Menten function of systemic arterial glucose concentration (Table 1C Insulin equation 2, Figure 10A). Glucose uptake via GLUT2 is the rate determining step of this process. However this rate is modulated by a glucose sensitivity coefficient, which is a function of systemic GLP-1 concentration,58,59. Like glucose, insulin circulates to the liver via the splanchnic circulation, but is partially inactivated within liver before passing to the systemic circulation, where it is also partially degraded60 (Table 1C Insulin equations 4A and 5A).\n\nInsulin secretion rates are adjusted to give concentrations within the systemic circulation, similar to known concentrations in normal and T2DM states (Table 2). The rates of insulin inactivation/degradation correspond with the reported inactivation rates t½ ≈ 2–3 min33,48) and adjusted to give a ratio of SMA insulin/peripheral venous insulin ≈ 2.061.\n\nGlucagon flow sub-model. Glucagon, like insulin, is released from the pancreatic islets (α-cells) into the superior mesenteric blood compartment and circulates in the splanchnic and systemic circulations. Glucagon release responds as an inverse hyperbolic function of the systemic glucose concentration and is regulated only with a glucose-sensitive coefficient (Figure 1C, Table 1E Glucagon equation 2, Figure 10C).\n\nOn contact with hepatocytes glucagon stimulates hepatic glucose production by gluconeogenesis and glycogenolysis (Table 1B Glucose equation 4B). These processes result in net glucose release, into the systemic circulation. Glucagon, like insulin, decays within the circulation with a similar degradation half-time of 2–3 min, but is more slowly degraded by liver than insulin, so that the portal to arterial glucagon ratio is reported to 1.2–1.461. For present purposes the liver is assumed to be a limitless source, of gluconeogenesis from either glycogen or from fat and protein stores. This condition obviously applies only to the short term (1–2 days).\n\nIncretin sub-model. Incretin secretion rates are controlled by the splanchnic capillary glucose concentration and like insulin and glucagon, incretins flow directly into the portal blood compartment (Table 1D GLP-1 equation 1). The stimulus for GLP-1 release is dependent on glucose concentration within this superior mesenteric capillary SM cap compartment, determined by GLUT2 Km35,62–64. Thus incretin release from enteroendocrine L cells differs from glucagon and insulin release from pancreatic islets; these are sensitive to systemic arterial glucose; whereas GLP-1 release is activated by splanchnic glucose concentrations. Like insulin and glucagon, GLP-1 has a half-time of degradation of 2–3 min; this is modelled by Table 1D GLP-1 equation 2, and Figure 10C.\n\nIn Figure 2–Figure 4 the effects of altering the glucose sensitivity over a range from (0.1–100) of GLP-1 release are shown on the key pressure, volume, flow and concentration variables affecting glucose distribution and metabolism, as functions of time after initiation of duodenal glucose gavage at 100min. Increasing glucose sensitivity over the range (0.1–100) increases the GLP-1 concentration in both splanchnic and systemic circulation by around 20 fold, (Figure 3D and 3H) (The linear regression coefficient of splanchnic capillary GLP-1 concentration with GLP-1-glucose sensitivity coefficient is 0.58 ± 0.01 and for systemic arterial GLP-1, the coefficient is 0.5 ± 0.007).\n\nThe effects of a standard oral glucose tolerance test, OGTT of 50 G glucose delivered by duodenal gavage over a period of twenty minutes are used in all simulations to demonstrate the comparative effects of these altered conditions on glucose flows and metabolism.\n\nThe effects of two major physiological variables, the GLP-1 sensitivity to glucose and the paracellular glucose permeability, Pgl on glucose absorption and its distribution and metabolism are displayed in the first part of this paper. Glucose sensitivity of GLP-1 release is the main regulator of superior mesenteric arterial response to glucose and the second variable Pgl affects the passive paracellular rate of glucose flow and hence its sensitivity to splanchnic capillary flow rates. The other major effects of altered GLP-1 secretion rates will be described in the first part of the Results section.\n\nIn the second part of this paper variations of two parameters, hepatic pre-sinus resistance and portosystemic shunt resistance, PSS R associated with NAFLD and NASH on hormonal and incretin changes affecting glucose absorption and metabolism will be examined.\n\nNo other parameters, or coefficients are altered during these simulations. All the other parameters used are the same as in Table 2.\n\nMost of the graphs shown are 3D representations in which the arrays of dependent variable z are plotted versus array vectors of x (time) and y {independent variables, (resistances, permeabilities, etc.)}. This method of variable mapping using 3D surface graphs with Excel Chart facilities demonstrates the non-linear interactions between variables, however, only the time axis and the dependent variable are an exact linear or logarithmic maps of the independent variable The K½ and “c” estimates of x, y interactions are all obtained with exact fits.\n\n\nResults\n\nAll the graphs are contoured surface plots in which the x axis is the time coordinate, the y axis is the GLP-1 sensitivity to glucose – this generates GLP-1at a rate proportional to the sensitivity and splanchnic blood glucose concentration, (Figure 1B GLP-1equations 1). With low GLP-1secretion the changes in glucose sensitive blood flow are reduced.\n\nPanel A The effects of GLP-1sensitivity and time on SMA flow. There GLP-1dependent increase in SMA flow response to glucose gavage peaks 3–6 min after glucose gavage and is sustained for 15–20min (K½GLP-1 sens. = 12; maximal flow rate 1500 ml min-1; maximal flow rate 1500 ml min-1).\n\nPanel B Portal venous flow ml min-1 versus GLP-1sensitivity and time. The graph has a similar GLP-1sensitivity and time course to SMA in (Panel A). PV flow rises hyperbolically with GLP-1sensitivity K½GLP-1 sens. = 12; maximal flow rate 1100 ml min-1.\n\nPanel C, the effects of GLP-1sensitivity and time after gavage on hepatic artery HA flow. The high GLP-1sensitivity is shown at front of the y scale. HA flows fall simultaneously with the rise in PV flow. This is due to the decreased aortic pressure and volume (Panel D) resulting from the enlargement of the splanchnic volume (Panel E).\n\nPanel F Effects of glucose sensitivity GLP-1secretion on portal venous PV pressure changes after glucose gavage. The rise in pressure mirrors the changes in PV flow (Panel B) and SMA flow (Panel A), (peak PV pressure is approximately 8mm Hg; K½GLP-1 sens. = 15).\n\nPanel A The rise and fall of PV glucose flow following gavage, (peak flow rate 18 mmole min-1 at 2–5 min after gavage, K½GLP-1 sens. = 12).\n\nPanel B, HA glucose flow does not fully reciprocate PV glucose flow since raised GLP-1only reduces HA glucose to a small extent (14.3 to 7–8 mmole min-1 between 4–6 min after gavage).\n\nPanel C, HV glucose flow is the sum of PV and HA flows shown in (Panels A and B).\n\nPanel D The rise off unidirectional intestinal glucose permeability following gavage. Intestinal glucose permeability varies transiently with the transluminal glucose concentration gradient. This rises with the increase in luminal glucose concentration and falls from the peak when glucose gavage ceases and luminal glucose concentration falls and splanchnic capillary glucose concentration rises due to glucose absorption (see Figure 4 Panel G) Raising GLP-1glucose sensitivity increases the peak glucose permeability by 20%. GLP-1increases peak flow glucose permeability from the baseline at the start of gavage compared with maximal glucose gradients by five-fold.\n\nPanels Ei, Eii Mirror views of the effects of GLP-1on hepatic glucose metabolism following gavage. Negative values signify negative net glucose uptake NHGU i.e. positive glucose outflow resulting from glucagon stimulation and suppression of GLP-1and insulin signalling to liver. High GLP-11 sensitivities increase NHGU during times of peak PV glucose flow, however later times, high GLP-1sensitivities leads indirectly to very high rates of glucagon-dependent gluconeogenesis K½GLP-1 sens. = 18.\n\nPanel F Peripheral glucose metabolism increases only slightly with raised systemic glucose concentration following glucose absorption and falls when high rates of glucose sensitive GLP-1secretion drive metabolism to induce hypoglycaemia.\n\nPanel G Insulin-dependent glucose metabolism is extremely sensitive to glucose sensitive GLP-1secretion. The maximal rate is > 100-fold higher than fasting rates. With low GLP-1 net hepatic glucose output is reduced and hepatic uptake reduced during the absorption phase 100–145 min. Low GLP-11 secretion reduces peripheral insulin sensitive glucose uptake.\n\nPanel A–D systemic concentrations of glucagon, insulin, glucose and GLP-1. Panels E–H splanchnic concentrations of glucagon, insulin, glucose and GLP-1respectively. Note that the splanchnic concentrations are generally nearly twice those in the systemic circulation. Peak SM capillary glucose concentration decreases as GLP-1 secretion rate increases, (GLP-1glucose sensitivity range 0–50 K½GLP-1=7.2 required to give half maximal splanchnic glucose concentration maximum splanchnic glucose ranging from 45 to 22 mM as GLP-1is increased).\n\nAfter the glucose absorptive phase glucagon levels rapidly recover with high rates of GLP-1secretion in both splanchnic blood (K½ GLP-1sec = 10) and in systemic blood (K½ GLP-1sec = 5). With high rates of GLP-1-1 secretion glucagon remains high in both splanchnic and systemic blood until fasting is relieved.\n\nPanel B and F Insulin concentration in SM-cap is 2.5-fold higher than in systemic blood. Splanchnic insulin is nearly 10x higher with low GLP-1 than with high rates of GLP-1secretion.\n\nPanels C and G Splanchnic glucose exceeds systemic glucose by 1-5-2 fold during glucose absorption but falls below that of systemic glucose particularly with high rates of GLP-1secretion during fasting and in the later post absorptive phases of digestion. Fasting glucose in systemic blood with high GLP-1 glucose 5.6 mM; with low GLP-1, glucose 9.6mM; splanchnic blood glucose with high GLP-14.4 mM and with low GLP-1 -1 glucose 3.6 mM. In contrast during the absorptive phage splanchnic glucose with low rates of GLP-1secretion glucose 47.5 mM exceeds systemic glucose 19.5 mM this is caused by the lower rates of SMA flow than with higher rates of GLP-1secretion.\n\nPanels D and H Splanchnic GLP-1always exceeds systemic glucose however with high rates of GLP-1secretion due to high glucose sensitivity, the peak splanchnic GLP-126 pM observed during glucose absorption is similar to systemic 19.7 pm whereas during fasting systemic GLP-12–3pm and splanchnic GLP-1 20–22 pM.\n\nAll the panels show 3D surface plots of the effects of two variables GLP-1glucose sensitivity (2–50) that controls GLP-1secretion rate with changes in splanchnic glucose concentration (GLP-1equations 1) and intestinal paracellular glucose permeability, Pgl (0–0.15 μm s-1). The interaction between these variables is shown as the coefficient c. All the panels show paired effects contrasting the interactions at peak splanchnic glucose flow (feed) with those during when splanchnic glucose is at a minimal value (fast panels D and E, the feeding and fasting values are determined at maximal and minimal systemic glucose concentrations.\n\nPanel 5A SMA flow after feeding increases as a linear function of GLP-1and as a hyperbolic function of Pgl; K½max = 0.02 μm s-1 and the interaction coefficient c for = 4.1, indicating a strong positive interaction between Pgl and GLP-1secretion, as can be seen from the upward elevation of the surface towards higher values of both independent variables.\n\nPanel 5B During fasting, in contrast to effects seen with feeding in panel 5A there is no effect of altering Pgl although SMA increases with GLP-1secretion, (coefficient c = 0) when intestinal glucose absorption is absent.\n\nPanel 5C There is a synergistic response of portal blood flow and glucose flow as a result of the interaction between Pgl and GLP-1secretion which leads to both increased splanchnic blood flow and glucose concentrations c= 2.74. With Pgl intestinal paracellular permeability = zero, increased SMA in response to raised GLP-1is almost without effect on portal glucose flow rates. Increasing Pgl from 0 to 0.16 μm s-1 with a constant rate of GLP-1secretion (= 50) and low pre-sinusoidal resistance (0.005 mm Hg.s ml-1), results in a hyperbolic increase in portal venous glucose flow from a base of 2.45 mmole min-1 to a maximal flow of 22.3 ± 1.37 mmole min-1, the Pgl giving half maximal increase in glucose flow is 0.024 ± 0.007 µm s-1.\n\nPanels F and G As with SMA flow see Panels A and B portal vein flows increase synergistically with increases in GLP-1and Pgl during when glucose is present in the splanchnic circulation c= 4.15, but during fasting Pgl effects are absent c= 0.\n\nFigure 5H There is a relatively high degree of negative interaction between the rate of GLP-1secretion and Pgl on splanchnic capillary glucose concentration, c= -4.58 due to both dilution of the intestinal glucose absorbate by the higher capillary blood flow rate, however as already shown glucose flow rate there is a positive interaction between Pgl with GLP-1-1 on PV glucose flow rates c = 1.21. When glucose paracellular permeability is high there the glucose uptake from intestine to the splanchnic blood is increased by high rates of capillary flow induced by GLP-1secretion. This due to the raised glucose gradient between the intestinal lumen and the submucosal capillaries.\n\nPanel A, Unidirectional intestinal permeability decreases as SM capillary glucose concentrations increase (Figure 3D). Unidirectional glucose permeability increases as a hyperbolic function of increasing paracellular permeability Pgl (K½ = 0.045 μm s-1 and GLP-1glucose sensitivity K½ = 5.5, c = 1.69). The positive interaction between paracellular permeability and glucose sensitive SMA flow indicates that raising capillary flow increases unidirectional permeability only when the paracellular leakage is fast enough to increase splanchnic capillary glucose concentration enough to retard permeability substantially if not cleared by splanchnic blood flow.\n\n(Panels 6B, 6C and 6D). During feeding increased rates of GLP-1secretion and intestinal glucose permeability Pgl synergistically increase NHGU (c = 6.08), and peripheral glucose metabolism (c =14.6).\n\n(Figure 6D), Insulin-independent metabolism (c= -13.55) decreases from the more intense competition for systemic glucose from insulin dependent tissues.\n\n(Panel 6E) Systemic insulin and (Panel 6H) GLP-1concentrations also increase with increasing Pgl (K½ ≈ 0.03 µm s-1).\n\nPanel 7A Hepatic shunt blood flow increases as PSS resistance diminishes giving half maximal portal venous glucose flow, (coefficients V = 600 ml min-1; K½= 0.025 mm Hg.s ml-1 is maximum 3–4 min after gavage). A slower but more prolonged rise occurs 20–30 min after gavage.\n\nPanel 7B Portosystemic glucose flow 3–4 min after glucose gavage. Glucose flow increases with decreasing PSS resistance (K½ = 0.05 mm Hg.s ml-1).\n\nPanel 7C PV flow decreases from its peak at a slower rate t½ ≈ 7.5 min to reach a plateau phase. During this plateau phase PV flow also decreases as a hyperbolic function of PSS resistance (K½ = 0.028 Hg.s ml-1)\n\nPanel 7D With zero PSS flow PV glucose flow has peak of approximately 20 mmole min-1 PV glucose flow decreases (t½ = 1.2 min, with zero shunt flow and t½ = 0.45 min with high shunt flows).\n\nPanels 7E and 7F PSS resistance change has negligible effects on either SM arterial blood flow or HA blood flow.\n\nPanel 7G Increasing PSS decreases peak portal venous pressure (K½ = 0.05 Hg.s ml-1 occurs at 5-5 min after the beginning of gavage, the t½ = 5–6 min of peak portal pressure decline).\n\nPanel 7H HV flow is maximal during peak glucose absorption 1500–1800 ml min-1 5 min after the start of gavage. HV flow decreases as a hyperbolic function of PSS resistance (K½ = 0.03 Hg.s ml-1).\n\nPanel 7I There is a strong interaction between PSS and presinusoidal resistance on hepatic shunt flow (c = 2425); when GLP-1secretion rates are high reducing the PSS resistance below 0.027 Hg.s ml-1 reduces peak PV pressure by 50%.\n\nPanel 8A GLP-1flow increase as hyperbolic function of PSS (the shunt resistance giving half maximal GLP-1flow is 0.027 Hg. s ml-1, Peak flow 3 mins after the start of duodenal glucose gavage and decreases very rapidly (t½ ≈ 3 min).\n\nPanel 8B Insulin flow via the PSS peaks 2.5–3 min following the start of glucose gavage. The shunt resistance giving half maximal peak insulin flow (K½ = 0.063 Hg.s ml-1). A second wave of insulin flow via the shunt is seen with low shunt resistance (K½ = 0.03 Hg.s ml-1).\n\nPanel 8C When shunt resistance is ≤ 0.015 Hg.s ml-1 glucagon flows via the PSS in two waves, The first wave peaks (1–2 min after gavage, flow rate of 20 fmoles min-1 and t½ = 1.5 min decrease). The second glucagon wave (peaks at 38 fmoles min-1, 8–10 min after gavage shunt resistance is K½ ≈ 0.055 Hg.s ml-1 (decay t½ = 10–15min).\n\nPanel 8D Opening the PSS resistance < 0.05 Hg.s ml-1 curtails the effect of GLP-1on hepatic glucose metabolism. With high shunt flows of glucose gavage net hepatic glucose uptake, NHGU, switches 6 minutes after the start glucagon-activated gluconeogenesis.\n\nPanel 8E Both hepatic (panel 8D) and peripheral insulin-dependent (Panel 8F) glucose consumption peaks are reduced at high rates of GLP-1secretion and a large PSS (K½ = 0.02 Hg.s.ml-1). The peaks occur earlier and end sooner.\n\nPanel 8F Insulin independent metabolic rate is stable over a wide range of PSS but is decreased with open PSS resistance < 0.02 Hg.s ml-1 simultaneously with the decrease in peripheral glucose concentration.\n\nPanel 8G Unidirectional intestinal glucose permeability increase after gavage as the glucose gradient between intestinal lumen and splanchnic capillaries increases with luminal glucose concentration, it also increases slightly 19% with increased PSS due to decreased splanchnic glucose concentration, (Figure 10A).\n\nPanel 9A. Insulin secretion rates are increased during the glucose absorptive phase of metabolism. This increase is stimulated directly be systemic glucose concentration and by the glucose sensitivity of GLP-1secretion. During fasting insulin secretion rates are directly proportional to GLP-1glucose sensitivity however during peak glucose absorption insulin secretion rates vary to a much lesser extent as with low rates of GLP-1systemic glucose is raised and therefore compensates for lack of glucose sensitivity of GLP-1secretion. 1 (K½GLP-1gluc sens = 0.80, Vmax= 0.41 nmol s-1)\n\nPanel 9B Insulin secretion rates with PSS (K½GLP-1gluc sens = 0.72, Vmax0.375 nmol s-1)\n\nPanel 9C GLP-1secretion is very similar to insulin, GLP-1secretion increases rapidly during the glucose absorptive phase of metabolism and tails of splanchnic glucose is diminishes during the course of metabolism. During fasting GLP-1secretion is hyperbolically dependent on glucose as glucose sensitivity of GLP-1K½ = 4.4 Vmax 12.3 12 pmol s-1) secreting cells in splanchnic blood is concentrations are lower with high rates of GLP-1secretion (Figure 4G).\n\nPanel 9D GLP-1secretion with PSS glucose sensitivity of GLP-1K½ = 4.6 Vmax10.3 pmol s-1 Shunting reduces insulin secretion by approximately 20%.\n\nPanel 9F Shunting increases glucagon secretion rates. The increase is a hyperbolic function of GLP-1 glucose sensitivity (K½ = 6.7 Vmax = 0.12 nmol s-1). During glucose absorption glucagon secretion rates decrease as systemic glucose increases. The decrease is negligible with low rates of GLP-1secretion due to the slow rise in systemic glucose.\n\nPanels 10A and 10E Portosystemic shunting has a relatively small effect on systemic and splanchnic GLP-1concentrations.\n\nFigure 10 Panels 10A and 10E Portosystemic shunting has a relatively small effect on systemic and splanchnic GLP-1concentrations.\n\nPanel 10B and 10F Peak systemic glucose decreases as PSS increases (PSS resistance K½= 0.05 Hg.s.ml-1).\n\nPanels 10C and 10G, Splanchnic insulin is decreased by shunting 2–7 min after duodenal gavage (PSS resistance K½= 0.145 Hg.s.ml-1). The decrease in splanchnic insulin coincides with a shunting-dependent increase in systemic and splanchnic glucagon (Panels 10D, 10H). Portosystemic shunts increase fasting systemic insulin concentrations PSS resistance K½= 0.06 Hg.s.ml-1).\n\nPanels 10D and 10H. Systemic and splanchnic glucagon concentrations have the relatively the largest responses to portosystemic shunt opening. As well as an early peak at 10 min after gavage (PSS resistance K½= 0.06 Hg.s.ml-1), a second later sustained rise in both systemic and splanchnic glucagon (PSS resistance K½= 0.075 Hg.s.ml-1).\n\nPanel 10F Fasting glucagon secretion rates with shunting increase hyperbolically with GLP-1glucose sensitivity K½ = 9.5 Vmax 0.19 nmol s-1).\n\nPanel 11A Opening the PSS resistance from 40 to 0.005 mm Hg.s ml-1, increases the normalized systemic insulin: glucose ratio to 2.1 in the fasting state (K½ = 0.03 mm Hg.s ml-1) The normalized systemic insulin: glucose ratio increases as a hyperbolic function to maximum of 5.4 as shunt resistance falls (K½ = 0.03–0.04 mm Hg.s ml-1). Two peaks in the systemic insulin: glucose ratio (Figure 11A) The second smaller, longer lasting rise in the insulin/glucose ratio coincides with the second wave in hepatic gluconeogenesis/glucose ratio (Figure 12E) (K½ = 0.06 mm Hg.s ml-1) and peripheral insulin-dependent metabolism (K½ = 0.015 mm Hg.s ml-1) (Figure 11D).\n\nPanel 11B Opening the PSS increases GLP-1/glucose ratio as a hyperbolic function of shunt opening (K½ = 0.015 mm Hg.s ml-1) the ratio peaks 5 min after gavage, and thereafter decreases (t½ = 2.5–3 min from the peak maximum).\n\nPanel 11C Opening the PSS increases glucagon/glucose ratio as a hyperbolic function of shunt opening (K½ = 0.015 mm Hg.s ml-1) the ratio peaks 5.5 min after gavage, and thereafter decreases (t½ = 3 min after the peak maximum). With a wide open shunt the glucagon/glucose ratio increases continuously during fasting owing to glucagon stimulated gluconeogenesis.\n\nPanel 11D, GLP-1 and insulin interactively stimulate systemic glucose metabolism in insulin-sensitive tissues. Plots of the product of the normalized GLP-1. Insulin product/glucose peak 4.5 min after gavage. Shunting raises the GLP-1.insulin product 30-fold increase above that without shunting. The enhancement remains during the later digestive periods.\n\nPanel 11E The normalized product of GLP-1*insulin in systemic blood increases as a hyperbolic function of PSS resistance. (K½ = 0.01 mm Hg.s ml-1to a maximum 30-fold above the level with without shunting 7 min after gavage; t½ = 2.5–3 min from the peak maximum a residual increase remains throughout the later digestive phase. (K½= 0.08 mm Hg.s ml-1).\n\nPanel 12A Opening the PSS resistance from 40 to 0.005 mm Hg.s ml-1, increases the normalized splanchnic insulin: glucose ratio in the fasting state to 2.1 (K½ = 0.03 mm Hg.s ml-1) Two peaks in the splanchnic insulin/glucose ratio (Figure 12 panel A). The second smaller, longer lasting rise in the insulin/glucose ratio coincides with the second wave in hepatic gluconeogenesis/glucose ratio (Figure 12 panel E) (K½ = 0.06 mm Hg.s ml-1) and peripheral insulin-dependent metabolism (K½ = 0.015 mm Hg.s ml-1) (Figure 11 panel D).\n\nPanel 12B Opening the PSS increases splanchnic glucagon/glucose ratio as a steep hyperbolic function of shunt opening (K½ = 0.01 mm Hg.s ml-1) the ratio peaks 8 min after gavage, and thereafter decreases (t½ = 2.5 min after the peak maximum).\n\nPanel 12C Opening the PSS increases splanchnic GLP-1/glucose ratio as a hyperbolic function of shunt opening (K½ = 0.015 mm Hg.s ml-1) the ratio peaks 6 min after gavage, and thereafter decreases (t½ = 2.5–3 min from the peak maximum).\n\nPanel 12D The normalized product of GLP-1*insulin in splanchnic blood increases as a hyperbolic function of PSS resistance. (K½ = 0.05 mm Hg.s ml-1, peak maximum is 7 min after gavage; t½ = 2.5–3 min from the peak maximum) The shunting dependent increase in splanchnic blood peaks approximately 5× higher and a residual increase remains throughout the later digestive phase. (K½= 0.08 mm Hg.s ml-1).\n\nPanel 12E The ratio of hepatic metabolism/splanchnic glucose decreases falls dramatically during the early phase of glucose absorption when the PSS is opened (K½ = 0.015 mm Hg.s ml-1) peaking 10 min after starting gavage.\n\nPanels 1–D The time courses of normalized shunt flow of glucose, insulin, glucagon, GLP-1 and peripheral insulin sensitive metabolism, hepatic metabolism.\n\nPanel C normalized shunt/control insulin, GLP-1 and glucagon secretion rates.\n\nPanel E Shunt/control ratio of glucose, insulin, GLP-1 and glucagon in splanchnic blood and hepatic gluconeogenesis rates (positive).\n\nPanel A Normalized ratios of systemic insulin/glucose; glucagon/glucose and GLP-1/glucose in patients with NAFLD.\n\nPanel B Normalized ratios insulin/glucose, glucagon/glucose and GLP-1/glucose in patients with T2DM having no liver disease/control data.\n\n\nIntegration of intestinal glucose absorption with glucose metabolism\n\nThe initial aim was to model the interaction between incretin-induced reduction in SMA blood flow resistance and glucose absorption. Simulations of glucose-induced blood flow changes are shown in Figure 2. SMA (Figure 2A) and portal blood flow (Figure 2B) rise from a fasting rate of approximately 500 ml min-1 to 1500 ml min-1 during peak glucose absorption rates, similar to changes reported by 50. Hepatic arterial flow decreases simultaneously from 700-560 ml min-1 (Figure 2C). This mirrors the hepatic arterial buffer response65, ascribed to a reflex action activated by intrahepatic release of adenosine by portal blood flow66. However, here no humoral or nerve responses are programmed, so the reciprocal changes in HA flow with PV flow are due entirely to the direct mechanical compensatory changes resulting from application of Kirchhoff’s current law within the series-parallel circulatory network of blood vessels. Flow and volume changes resulting from the increases in portal venous flow and splanchnic blood volume, increase splanchnic volume (Figure 2E), with consequential decreases in systemic arterial volume (Figure 2D), blood pressure: aortic BP decreases from mean level of 110 mm Hg to around 90 mm Hg. Similar phenomena may account for the post-prandial hypotension frequently observed in elderly humans67. The increase in SMA blood flow following release of incretins GLP-1 increases portal blood pressure from 1.5–7.5 mm Hg (Figure 2F). The extent of this increase depends on a number of factors, as will be discussed. Raised portal venous pressure lasts as long as the splanchnic blood vessels are exposed to hyperglycaemia and SMA blood flow is raised (Figure 2A).\n\nGlucose flows. As both PV flow (Figure 2B) and superior mesenteric capillary (SM cap) glucose concentrations increase (Figure 4C) during the glucose absorptive phase, PV glucose flow rises by about ten-fold from 2.4–24 mmoles min-1 (Figure 3A). HA glucose flow increases only by threefold from 2 to 6 mmoles min-1 (Figure 3B). Consequently, during the intestinal absorptive phase, PV supplies 80% and HA 20% of hepatic glucose, whereas during fasting periods, hepatic glucose inflows from the PV and HA are nearly equal. During the early glucose absorptive phase HV glucose outflow only slightly exceeds PV glucose inflow, but in the later digestive phases HV glucose outflow greatly exceeds PV glucose inflow (Figure 3C).\n\nWith normal high rates of GLP-1 secretion (systemic arterial GLP-110-20nM; Figure 4D), splanchnic glucose concentration (Figure 4G) rises transiently to 20mM, then subsides to 5 mM as the SMA blood flow and insulin, glucagon and GLP-1 regulate the systemic capillary glucose. Systemic arterial glucose concentrations rises initially to 7 mM and returns to 5 mM in approximately 40–60 min (Figure 4C).\n\nGlucose metabolism. During the glucose absorptive phase, liver glucose metabolism switches from fasting glucagon-controlled net glucose output, ≈ 0.25 mmoles min-1 (N.B. this has a negative value as glucose exits the liver) to feeding net glucose uptake (a positive value, stimulated by insulin and high GLP-1, where NHGU transiently rises to 1.8 mmoles min-1 (Figure 3Ei and 3Eii). These simulations match previously observed hepatic glucose metabolic rates in humans, obtained using the splanchnic/hepatic balance technique68.\n\nThe time dependent changes in peripheral insulin-dependent metabolic rates (muscle and adipose tissue are also shown (Figure 3G). On switching from fasting to feeding with high rates of GLP-1 secretion, there is a large increase in peripheral insulin-dependent metabolism; rising from 0.2 mmoles min-1 during fasting, to a peak rate of 5–6 mmoles min-1 during glucose absorption.\n\nInsulin-independent glucose metabolic rates (brain), change relatively little (from 0.5 to 0.6 mmoles min-1; Figure 3F). As the systemic arterial glucose concentration does not exceed the renal threshold for glucose reabsorption there is no significant glycosuria. These simulations were designed to mirror well-established in vivo findings in humans and dogs38,46,69.\n\nSplanchnic and systemic concentration changes in insulin, glucagon and GLP-1. Because pancreatic hormones and incretins are directly secreted into the splanchnic circulation and then subject to serial degradation, firstly within the liver sinusoids and then within the peripheral circulation, splanchnic concentrations are normally double those in the systemic circulation, (Figures 4A–H, Table 1C Insulin equation 4A)63.\n\nFollowing its glucose-dependent release from enteroendocrine L cells, GLP-1 concentration increases rapidly in splanchnic and systemic circulation (Figure 4D, H). Release rate depends on the glucose sensitivity coefficient, which is varied from 0.1 to 40 in a geometric progression, (Table 1D GLP-1 equation 1). GLP-1 sensitizes the hepatic insulin response by AMPK-dependent increases in glucokinase and GLUT2 activity (Figure 3Ei and 3Eii, Table 1B Glucose equation 5B) and sensitises glucose metabolism to insulin in adipocytes and muscle (Figure 3G, Table 1B Glucose equation 5A).\n\nThe model replicates the observed changes occurring when GLP-1 is released into the splanchnic circulation of normal adults and in GLP-1deficiency when blood GLP-1secretion and concentrations are 0–5% of the controls (Figure 2–Figure 4)70. With attenuated GLP-1 secretion, the glucose-dependent SMA and PV blood flow rises are decreased (Figure 2A and 2B); also blood volume redistribution (Figure 2D and 2E) and portal blood pressure (Figure 2F). Decreased GLP-1secretion prolongs the splanchnic vascular and metabolic responses to ingested glucose.\n\nDecreased SMA flow in response to glucose absorption, increases splanchnic and systemic glycaemia (Figure 4G). Peak SM capillary glucose concentration decreases as GLP-1 secretion rate increases, the GLP-1 glucose sensitivity is (K½GLP-1=7.2 ± 1.2 range 0–50) giving half maximal reduction in SM capillary glucose from 45 to 22 mM.\n\nIn GLP-1 deficient states, although PV glucose concentration is double that with high GLP-1secretion (Figure 4C and 4G), PV glucose flow (8.4 mmoles min-1) is less than half that found in controls (23 mmoles min-1; Figure 3A). The compensatory rise in HA flow with elevated systemic glucose concentration is double HA glucose flow (14.0 mmoles min-1) found with high rates of GLP-1 secretion (6–8.0 mmoles min-1) and partially compensates for the lower PV glucose flow (Figure 3C). Thus, peak net hepatic glucose HV outflow (30 mmole min-1) with low rates of GLP-1 secretion is similar to that with high GLP-1 secretion rates (35 mmoles min-1).\n\nIn the absorptive phase, hepatic sinusoids avidly accumulate glucose, with high GLP-1 secretion rates the (NHGU is 1.7 mmole min-1; Figures 3Ei and 3Eii). Because of rapid rates of insulin-dependent hepatic and peripheral metabolism, blood glucose concentrations in both systemic and splanchnic circulations decline rapidly, (Figure 4C and 4G). With low GLP-1 secretion rates, slower rates of hepatic and peripheral insulin dependent metabolism (Figures 3Ei and 3Eii), lead to the high concentrations, more prolonged, systemic and splanchnic glucose concentrations. Thus, in low GLP-1 secreting states, liver is exposed to higher glucose concentrations for a longer and NHGU remains positive for longer than with high rates of GLP-1 secretion.\n\nInsulin. Insulin and glucagon secretion rates are controlled by systemic glucose, unlike GLP-1 and other incretin secretions which are regulated by splanchnic glucose concentrations (Figure 1, Table 1C Insulin equation 2, Table 1E Glucagon equation 2). The insulin concentration in splanchnic-capillaries is 2-3-fold higher than systemic blood, (Figure 4F and 4B). In low GLP-1secretory states, owing to reduced glucose-sensitivity, splanchnic insulin and glucose concentrations are raised. This is mainly due to reduced hepatic, pancreatic and peripheral tissue metabolic sensitivity to insulin,71. In low GLP-1secreting states even with higher blood glucose (Figure 4C and 4G) and insulin concentrations (Figure 4B and 4F), both the peak hepatic glucose metabolic rate and peripheral insulin-sensitive glucose metabolism are depressed, (Figure 3E and 3G).\n\nSystemic insulin concentration (45 pM) during fasting, with low GLP-1secretion rates, is raised by more than 55% above that seen with high GLP-1 (29 pM) secretion rates. In low GLP-1 secreting states in the later prandial period >1–2h after glucose feeding, systemic insulin concentration is > 100% above that seen with high rates of GLP-1, (Figure 4B and 4F). Splanchnic insulin concentration also is approximately three-fold higher in low GLP-1 than with high rates of GLP-1 secretion at this time. These effects are due to GLP-1-enhanced insulin-dependent metabolic rates that result in decreased blood glucose.\n\nGlucagon. Splanchnic glucagon is approximately double the concentration in systemic blood61. The model simulates this condition in fasting conditions, but shows that during the glucose absorptive phase, when glucagon is at its minimum concentration, the splanchnic/systemic glucagon ratio falls to approximately 1. With low rates of GLP-1secretion, owing to raised systemic glucose concentrations, particularly in the post-prandial phase of digestion > 10min after gavage, systemic and splanchnic glucagon concentrations are decreased (Figure 4A and 4E).\n\nIntestinal glucose permeability. Intestinal glucose permeability (Table 1B Glucose equation 1A) is defined as the rate of glucose flow intestinal wall area per unit glucose concentration difference (mM) (mmole s-1 cm-2), between the luminal source and splanchnic capillary sink. Because of the many uncertainties relating to uncontrolled variables, intestinal glucose permeability is not readily determined in vivo. The very high rate of glucose uptake from the in vivo intestine requires that a known length of intestine be rapidly perfused with high glucose loads to prevent the luminal glucose concentration falling to levels where net flux becomes unmeasurable15,19. Using a high flow via a triple lumen tube, single pass perfusion over a known length of jejunum, with a “physiological” concentration of isotonic glucose ≅ 350 mM, human glucose “permeability” in vivo was estimated at 1×10-3 cm s-172,73. Absorption was complete in 25–30 min, estimated t½= 6.3 min,73.\n\nThe Lennernäs protocol does not actually measure the effect of the transmural glucose gradient on net intestinal glucose uptake. This method measures “unidirectional” intestinal permeability, as it ignores any effects of glucose concentration within the mesenteric capillaries, or effects of capillary perfusion on glucose permeability. Because hyperglycaemia induced by intravenous infusion was without measurable effect on human intestinal glucose absorption. It has been assumed there is no significant reflux component to glucose uptake74.\n\nHowever, during the absorptive phase of digestion, the very high rate of glucose uptake from the intestinal lumen significantly raises the splanchnic vessel glucose concentration to at least twice that of systemic glucose75. Raising the splanchnic capillary glucose reduces the glucose concentration gradient between the intestinal lumen and capillaries. This reduced gradient will reduce intestinal net glucose uptake and hence the unidirectional permeability. It was observed that following intragastric feeding with 1.5g glucose/kg, canine splanchnic glucose balance, i.e. net glucose uptake, was raised to a maximum of 6 mg/min/kg within 30 min and declined after 60 min, reaching a minimum after 120 min. With a higher glucose load (2.5 g/kg), the maximal splanchnic glucose balance still attained 6 mg/min/kg after 30 min, and reached a minimum after 180 min,75. Since the maximal rate of intestinal glucose absorption is the same with both 1.5 and 2.5 g/kg, this indicates that contrary to earlier assumptions, following intraluminal feeding intestinal glucose permeability is slowed by raised splanchnic glucose concentrations.\n\nAs previously stated, there are two components to intestinal glucose permeation; Na-dependent glucose cotransport, which because it is very asymmetric76,77 is insensitive to cytosolic and sub-mucosal glucose concentrations and paracellular glucose permeation, which depends on the glucose concentration gradient existing between the intestinal lumen and the interstitial glucose concentration (Table 1B Glucose equation 1A). During glucose absorption, intestinal capillary glucose concentration is a function of the following variables: the rates of Na-dependent glucose cotransport and the paracellular glucose permeability coefficient; superior mesenteric arterial flow; the superior mesenteric capillary glucose concentration and the concentration difference between intestinal luminal glucose. Superior mesenteric blood flow is regulated by the GLP-1 concentration, which is in turn regulated by the intestinal luminal glucose concentration. Thus glucose-dependent GLP-1 release generates a feedback control loop which controls SMA flow and the SM capillary glucose concentration.\n\nThe effects of variation of the paracellular glucose permeability (0–0.16 μm s-1) and with variable rates of GLP-1 sensitivity glucose sensitivity coefficient (0–100) following a constant initial glucose load = 50 G and constant Na-dependent cotransport rate on the key major model variables are shown in Figure 5–Figure 8 during fasting and a peak rates of glucose absorption. Glucose circulation and its metabolism alter with GLP-1 secretion rates. The controlling coefficient affected GLP-1 secretion is its glucose sensitivity detected by the glucose transporters within enteroendocrine cells.\n\nIn Figures 5A–I and Figure 6A–J, the effects of increasing paracellular glucose permeability from 0–0.16 µm s-1 with a range of glucose sensitivities of GLP-1 secretion (2–50) are illustrated using 3D surface contour plots. GLP-1 glucose sensitivity and intestinal glucose permeability Pgl are plotted as x and y coordinates and the dependent variable in the vertical z plane. Figure 5A–I shows the dependent variable values during fasting and at peak height during glucose absorption. The peak after feeding occurs within 3–10 minutes after absorption. Increasing Pgl from 0 to 0.16 μm s-1 with a constant rate of GLP-1 secretion (= 50) and low pre-sinusoidal (PV) resistance (0.005 mm Hg.s ml-1), results in a hyperbolic increase in portal venous glucose flow from a base of 2.45 mmol min-1 to a maximal flow of 22.3 mmol min-1, the Pgl = 0.024 µm s-1 (Figure 5D).\n\nA synergistic response of portal blood flow and glucose flow results from interactions between Pgl and GLP-1 secretion. Relatively large changes in superior mesenteric artery, (SMA) flow (Figure 5A) and portal venous (PV) flow rates (Figure 5F) occur when both Pgl and GLP-1 sensitivity are varied.\n\nIncreasing Pgl from 0 to 0.16 µm s-1 with low glucose sensitivity to GLP-1 secretion increases the SMA flow from 200 to 315 ml min-1; whereas when GLP-1 sensitivity secretion to glucose is high (= 50), increasing Pgl from 0 to 0.16 µm s-1 increases SMA flow from 450 to 1150. The Pgl giving half maximal activation of SMA flow remains unchanged at 0.02 µm s-1.\n\nPV glucose flows also increase hyperbolically on increasing Pgl (Figure 5C). Glucose flow is substantially higher (21 mmole min-1) when both Pgl and GLP-1 are high, than with high GLP-1 and Pgl = zero (PV glucose flow increases from 1.9–2.5 mmole min-1. When GLP-1 secretion rates are low GLP-1gl.sens = 2, increasing Pgl from 0 to 0.16 µm s-1 PV glucose flow increases only 11.7 mmole min-1).\n\nIncreasing Pgl from 0–0.016 µm s-1 increases glucose flow rates from the intestinal lumen resulting in a hyperbolic rise in splanchnic and systemic circulation glucose concentrations (Figure 5H and 5D).\n\nAs already shown in Figure 4C and 4G, when GLP-1 glucose sensitivity is increased (2–50) maximal splanchnic glucose concentration decreases linearly from 37 to 19 mM; systemic glucose remains at approximately 15 mM (Figure 5D).\n\nThe relative insensitivity of systemic compared with splanchnic glucose concentration to changes in GLP-1 secretion, can be ascribed to the relative constancy of HV glucose outflow into the systemic circulation.\n\nWith low rates of GLP-1 secretion and high Pgl SM capillary glucose concentration is raised during the absorptive phase to 37 mM (Figure 5H). With increasing rates of GLP-1 secretion SM capillary glucose falls to 9.0 mM; (K½ = 0.018 µm s-1 falling to 0.013 µm s-1 when GLP-1 secretin = 50). During fasting periods (Figure 5I) altering Pgl is without any effect on either splanchnic or systemic glucose concentration.\n\nThe observed unidirectional glucose permeability rises during the absorptive phase of glucose digestion and reaches a maximum about 2–4.0 min after initial exposure to luminal glucose feeding (Figure 3D). In Figure 6A with low rates of GLP-1 secretion, the peak intestinal glucose permeability increases as a hyperbolic function of Pgl (K½ = 0.02 µm s-1). On increasing GLP-1from 2 to 50, the maximal observed permeability Pgl increases from 0.041 to 0.056 µm s-1; (K½= 0.03 µm s-1). Thus owing decreased SM capillary glucose resulting from higher rates of SM capillary perfusion the concentration gradient between the intestinal lumen and the submucosal capillaries thereby increasing paracellular glucose diffusion. Consequently there is a positive interaction between GLP-1 secretion and intestinal paracellular permeability (Figure 6A).\n\nThese simulations explain why apparently contradictory results on intestinal glucose permeability have been reported. In T2DM subjects compared with controls, no change in intestinal glucose uptake is observed when intravenous glucose and insulin are clamped,78. Whereas in critically ill patients with a lower SMA response to glucose infusion, irrespective of their GLP-1 secretory status, the intestinal absorption rate is decreased79.\n\nWhen splanchnic blood glucose is abundant during the absorption, increasing both GLP-1 secretion and intestinal glucose permeability Pgl, synergistically increase NHGU (c = 6.08), and insulin dependent peripheral glucose metabolism (c = 14.6) (Figures 6B–D). NGHU increases as a hyperbolic function of increasing Pgl, (Figure 6B). Systemic insulin (Figure 6E) and GLP-1 concentration (Figure 6H) also increase with increasing Pgl, (K½ ≈ 0.03 µm s-1). The reciprocal changes in insulin-dependent and insulin-independent metabolism (c = -13.55) (Figure 6D), result from the more intense competition for systemic glucose from insulin dependent tissues.\n\nDuring fasting, increasing Pgl and/or rates of GLP-1 secretion do not synergise blood flows or glucose flows (Figures 5B, 5G and Figure 6H). When the intestinal lumen is empty, increasing Pgl has no effect on systemic or splanchnic glucose (Figure 5E and 5I), whilst increasing glucose sensitivity of GLP-1 secretion only results in small increases in GLP-1 release or SMA flow; thus interaction between Pgl and GLP-1 in zero i.e. (c ≅ 0).\n\nDuring the intestinal glucose absorptive phase, positive interactions occur between Pgl and glucose sensitive GLP-1 secretion on GLP-1 and insulin concentrations within splanchnic and peripheral blood Figure 6E, J, H and I). Because glucagon secretion decreases as systemic glucose increases, negative interactions occur between GLP-1 and intestinal Pgl on glucagon secretion and concentrations. The interaction coefficients are for splanchnic (Figure 6F; c = 0.06) and systemic glucagon (c = -0.99; (Figure 6F, G). In the absence of intestinal glucose absorption zero interaction takes place between GLP-1 secretion and Pgl on splanchnic glucose concentrations.\n\n\nPart 2 Simulations of NAFLD, NASH and T2DM\n\nNormally, direct blood flow between the portal vein and hepatic vein is prevented by a high intrahepatic portosystemic resistance. Trans-hepatic blood flow resistance is normally very low and portosystemic shunt (PSS) resistance is very high, so 99.0% of portal venous glucose during peak absorption flows via the sinusoids. However, in conditions such as hepatic cirrhosis and/or hepatosteatosis, increased tortuosity of hepatic sinuses and narrowing of the hepatic vessels results in development of low resistance intrahepatic collateral vessels enabling portosystemic shunt PSS flows80. Two important effects of hepatic and portal endothelial dysfunction are increased hepatic vascular resistance resulting in reduced hepatic sinus blood flow and raised portal blood pressure81–83. Additionally, reduction in hepatic glucokinase activity, associated with NASH and T2DM, reduces hepatic insulin-and GLP-1-dependent glucose uptake and metabolism84,85.\n\nGlucose passing through the sinusoids is processed initially by hepatocyte GLUT2 and glucokinase activities. Both these activities are regulated by insulin and GLP-186,87. Although intrahepatic PSS formation alleviates portal hypertension88,89, it also circumvents metabolic processing in liver sinusoids, with adverse consequences on glucose, insulin, glucagon and incretin circulation and metabolism. Splanchnic blood contents enter the systemic circulation directly via the PSS, particularly during the absorptive phase of digestion and thereby raise systemic concentrations of glucose, insulin, glucagon and GLP-1inappropriately, (see below).\n\nProlonged hyperglycaemic exposure of splanchnic endothelia could result in mitochondrial starvation of ascorbate90,91 which could be either an initiating or exacerbating cause of NASH.\n\nThe model of glucose absorption is used here to test a range of portosystemic shunt resistances from 40 to 0.005 mm Hg.s ml-1. With a presinus resistance = 0.005 mm Hg.s ml-1 the change in shunt flow varies as a hyperbolic function, from zero with high shunt resistance to 560 ml min-1 with low resistance, (Vmax = 1160 ml min-1; K½= 0.11 mm Hg.s ml-1 with high presinusoidal resistance = 0.025 mm Hg.s ml-1, the estimate of maximal shunt flow increases to 2034 ml min-1; (K½= 0.43 mm Hg.s ml-1). Portal hypertension as seen in hepatic cirrhosis and NAFLD/NASH is associated with increased hepatic vascular resistance. The model simulates “portal vein resistance” by raising pre-sinusoidal hepatic resistance from 0.005 to 0.025 mm Hg.s ml-1. The higher pre-sinusoidal PV resistances give comparable changes in portal vein pressure to those observed in animal models of NAFLD92.\n\nAlthough others have modelled metabolic syndrome in relation to glucose metabolism to date no other simulation model incorporates portosystemic shunt flows into models of NASH and T2DM,93,94.\n\nIt has been suggested that incretin secretion and/or responses to incretins are defective in obesity, NAFLD, or T2DM,70,95–97. The improvements in patient glycaemic responses elicited by GLP-1 agonists, or dipeptidyl peptidase inhibitors that retard GLP-1 degradation, within the circulation, or AMPK activators, e.g. metformin or other biguanides40,64,98 and reversal of the pathological effects of NAFLD and NASH by GLP-1 agonists85,99 tend to corroborate the view that GLP-1 deficiency is a cause of metabolic disease. GLP-1 agonists, such as exenatide, used in treatment of 2TDM, have been shown to be effective in reducing hyperglycaemia and hyperinsulinaemia namely100. Several reports indicate that incretin deficiency in T2DM and in morbid obesity may be partially reversed by bariatric surgery with subsequent weight loss87,96–98.\n\nNevertheless, other reports show an absence of correlation between GLP-1 secretion and obesity64, and it is evident that T2DM may occur without any marked deficit in GLP-1 secretion99. Thus it seems that low GLP-1 secretion rates observed in NASH, or in T2DM may be a consequence of the changes in glucose metabolism, rather than a cause. Thus modelling the mechanical effects of portosystemic shunting and increased presinusoidal resistance on blood, glucose, hormone and incretin circulation and metabolism may be useful in elucidating the role of GLP-1secretion in metabolic disease syndrome, with or without PSS.\n\nThe effects of varying PSS resistance from high resistance (10 mm Hg.s ml-1), where virtually zero shunt blood flow occurs, to low resistance (0.005 Hg.s ml-1), where approximately 50% of portal blood flow is shunted, on the time courses of change in insulin, glucagon and GLP-1 concentrations in splanchnic and systemic blood following glucose gavage is described in (Figure 7 and Figure 8). The fraction of splanchnic blood flow diverted via the PSS is similar to that when PSS has been surgically initiated by transjugular intrahepatic portosystemic shunting, TIPS80,82,101. The hepatic presinus resistance i.e. trans-hepatic blood flow resistance is maintained at a high level 0.020 Hg.s ml-1 (4× higher than the control value = 0.005 Hg.s ml-1 used in Part 1). These simulations are consistent with those found in NASH83,102.\n\nPSS blood flow decreases as a hyperbolic function of increasing shunt resistance. The PSS resistance giving half maximal flows, (K½ = 0.025 Hg.s ml-1) where Vmax of shunt flow, is 600 ml-1 (Figure 7A). PSS blood flow peaks when SMA flow and PV pressure are maximal (Figure 7E and 7C) and returns to fasting rates once intestinal glucose absorption is completed. PSS flow falls rapidly from its peak to fasting level (t½ ≈ 5 min). Peak PV flow falls reciprocally as PSS rises (K½ = 0.028 Hg.s ml -1; maximal PV flow 725 ml-1). PV flow decreases from its peak at a slightly slower rate, (t½ ≈ 7.5 min to reach a plateau phase) (Figure 7C). During this plateau phase PV flow also decreases as a hyperbolic function of PSS resistance (K½ = 0.028 Hg.s ml-1; Figure 7C).\n\nThe primary effect of reducing the PSS resistance clearly is to increase PSS flow. However this flow is also modulated by the presinusoidal resistance. When shunt flow is negligible (PSS resistance ≥ 0.4 Hg.s ml-1) increasing presinusoidal resistance from the normal low resistance = 0.005 Hg.s ml-1 to the high resistance, as found in NASH, portosystemic shunt blood flow increases by only a small amount, from 13 ml min-1 to 90 ml min-1. But with low PSS resistance = 0.005 Hg.s ml-1(shunt open); raising presinusoidal resistance from 0.005–0.025 Hg.s ml-1 raises shunt flow from 557–1600 ml min-1. There is evidently a strong interaction between PSS and presinusoidal resistance on hepatic shunt flow. When GLP-1 secretion rates are high, reducing the PSS resistance below 0.027 Hg.s ml-1 reduces peak PV pressure by 50% (Figure 7I). Thus with high presinusoidal resistance and high rates of GLP-1 secretion portosystemic shunting diverts ≈ 80% of the portal blood flow away from the sinusoids. Reduction in either PV resistance, or PSS resistance reduces peak shunt flow and reduces portal venous pressure (Figure 7G).\n\nFollowing duodenal glucose gavage, glucose flow via the PSS rapidly reaches a peak (2–3min), (maximal flow 14.5 mmole min-1; t½ ≈ 1.5 min, K½ = 0.028 Hg ml s-1; Figure 7B). PV glucose flow has peak of approximately 20 mmole min-1 and decreases hyperbolically with PSS resistance (Figure 7D). Hepatic arterial blood flow and HA glucose flow decrease during the initial stages of glucose absorption from 720–650 ml min-1 (Figure 7F). Hepatic shunt flow has no significant effect on HA flow.\n\nGLP-1 secretion causes a large increase in insulin-dependent metabolism in liver and muscle and adipose tissues (Figure 3D–F). Opening the PSS resistance <0.05 Hg.s ml-1 reduces the effect of GLP-1 on hepatic glucose metabolism (Figure 8D). With high PSS flows, net hepatic glucose uptake, NHGU, switches more quickly to glucagon-activated gluconeogenesis as the negative values in NHGU (8–14 minutes after the start of glucose gavage, synchronously with the second peak in shunt glucagon flow (Figure 8C).\n\nIn control subjects after duodenal glucose gavage, insulin release stimulates hepatic glucose consumption, (peaking 4–6 min after gavage) (Figure 3E). With a large PSS, even with high rates of GLP-1 secretion, both hepatic and peripheral insulin-dependent glucose consumption peaks are much reduced (PSS K½ = 0.02 Hg.s.ml-1), and occur sooner after glucose gavage, (3–5 minutes) (Figure 8D and 8E). With high PSS flows, when systemic and splanchnic glucose concentrations fall to lower levels ≈ 2 mM and insulin-independent glucose metabolic rates are reduced, (Figure 8F, Figure 10B and Figure 10F).\n\nGLP-1, insulin and glucagon flows after duodenal glucose gavage with varying PSS resistance are shown in Figures 8A–C. GLP-1 flow via the PSS rises swiftly when glucose is absorbed from the intestine into the splanchnic circulation; (PSS R giving half maximal GLP-1 flow is 0.027 Hg.s ml -1) (Figure 8A). Peak flow occurs approximately 3 mins after the start of duodenal glucose gavage and decreases very rapidly thereafter (t½ ≈ 3 min). PSS resistance change has only a small effect on GLP-1 flows and on systemic blood concentrations after the initial surge in GLP-1flow; (with zero PSS shunting, systemic blood GLP-1= 1.9 nM, and with maximal shunting, splanchnic GLP-1= 1 pM; Figure 10A and 10E); (with open shunting during fasting splanchnic GLP-1= 3.5 pM and with zero shunting, GLP-1= 6.6 pM). During fasting and in the late post-absorptive phase, with an open PSS, systemic GLP-1 concentration is approximately 30% of that with zero PSS shunting (Figure 10E). This reduced GLP-1 resulting from PSS, could explain the low plasma GLP-1 levels reported in metabolic disease syndrome64,96,97.\n\nInsulin. Insulin flow via the PSS peaks 2.5–3min after the start of glucose gavage (Figure 8B). The shunt resistance giving half maximal peak insulin flow (K½ = 0.063 Hg. s ml-1) is twice as high as that required to give half maximal shunt flows of GLP-1, or glucagon. Insulin flow via the shunt decreases rapidly from its peak value (t½ ≈ 3 min, but is sustained for longer t½ ≈ 15 min as the shunt resistance is reduced. A second wave of insulin peaks 16–20 min after the start of glucose gavage.\n\nShunting has complex effects on both systemic and splanchnic blood insulin concentrations. The most striking effect being the sustained increase in systemic plasma insulin during fasting and in the absorptive phase (Figure 10Gi and 10Gii) and the large decrease splanchnic insulin concentration observed shortly (2–7 min) after glucose gavage (Figure 10C).\n\nGlucagon. Following glucose gavage, two waves of glucagon flow via the PSS are evident when shunt resistance is ≤ 0.015 Hg. s ml-1. The first wave peaks at 1–2 min, at a flow rate of 20 fmoles min-1 and rapidly decreases; (t½ = 1.5 min) (Figure 8C). The second larger glucagon flow wave peaks at 38 fmoles min-1, 8–10 min after gavage. This flow is half maximal when shunt resistance is ≈ 0.055 Hg. s ml-1 but is sustained at (10–20 fmoles min-1) at least 20 min after gavage (t½ = 10–15min).\n\nHyperglucagonaemia is often linked with 2TDM70,96,103,104 and importantly has been observed with normal GLP-1 secretion rates when portosystemic shunting is present, due to hepatic cirrhosis,104.\n\nA consequence of PSS-dependent stimulation of insulin-dependent glucose metabolism is reduced systemic and splanchnic capillary glucose concentration (Figure 10A and 10B). This steepens the glucose concentration between intestinal lumen and SM capillaries and thereby increases the unidirectional glucose permeability (Figure 8G). A similar increased rate of intestinal glucose uptake in diabetic patients is observed following metformin treatment105.\n\nThese increases in unidirectional rates do not signify real change of intestinal permeability. Nevertheless, real increases in intestinal permeability may occur as a result of splanchnic oedema following portal hypertension106–108.\n\nThe time course of insulin, glucagon and GLP-1 secretion rates are demonstrated as functions the GLP-1 glucose sensitivity as controls, without shunting and normal low presinusoidal resistance (Figure 9A, 9C and 9E), and with portosystemic shunting and high presinusoidal resistance, as obtains in NASH (Figure 9B, 9D and 9F). Insulin secretion rates increase during the glucose absorptive phase of metabolism. This increase is stimulated directly by systemic glucose concentration affecting pancreatic beta cells insulin production (Figure 1, Insulin equation 1) and by the glucose sensitivity of GLP-1 secretion (Table 1E GLP-1 equation 1; Figure 9A).\n\nDuring fasting, insulin secretion rates are directly proportional to GLP-1 glucose sensitivity, however during peak glucose absorption, insulin secretion rates are less GLP sensitive. With low rates of GLP-1 secretion, systemic glucose is raised and compensates in part for reduced GLP-1 glucose sensitivity of insulin release.\n\nGLP-1 secretion has a similar time course to that of insulin, Figure 9C. GLP-1 secretion has a hyperbolic dependence on glucose sensitivity of GLP-1 secretion cells during fasting. During fasting glucose generated by glucagon-stimulated gluconeogenesis (Figure 8D and Figure 9E) raises GLP-1 secretion. Shunting causes a rapid decay in the initial peak of GLP-1 secretion due to the sharp decrease in splanchnic glucose that occurs almost immediately following glucose gavage. Low GLP-1 secretion rates diminish the effects of shunting on metabolism and excessive glucagon release.\n\nIt is evident that glucose, insulin, GLP-1 and glucagon leakages via the PSS alter the normal balance between glucose supply and its disposal in the splanchnic and systemic circulations. The changes in systemic and splanchnic glucose, insulin, glucagon and GLP-1 are shown in Figure 10. The most obvious effects of shunting are displayed in Figure 10C, 10D and Figure 10F, 10G and Figure 10H.\n\nPeak systemic glucose (Figure 10F; PSS resistance K½= 0.05 Hg.s.ml-1) and splanchnic insulin (PSS resistance K½= 0.145 Hg.s.ml-1; Figure 10C) are decreased by shunting 5 min after duodenal gavage. The decrease in splanchnic insulin coincides with a shunt-dependent increase in systemic and splanchnic glucagon (Figures 10D, 10H). Portosystemic shunts increase fasting systemic insulin concentrations (Figure 10G) (PSS resistance K½= 0.06 Hg.s.ml-1).\n\nSystemic and splanchnic glucagon concentrations have very large responses to opening the portosystemic shunt (Figure 10D and 10H). In addition to a peak 10 min after gavage (PSS resistance K½= 0.06 Hg.s.ml-1) a second sustained rise in both systemic and splanchnic glucagon is evident (PSS resistance K½= 0.075 Hg.s.ml-1).\n\nThe extent to which the shunt leakages affect metabolism is reflected in altered rates of insulin-dependent peripheral glucose metabolism. This is evident from the change in peripheral insulin dependent metabolic rate relative to systemic glucose concentration. Figure 11D and of hepatic glucose metabolic rate relative to splanchnic glucose concentration Figure 12D.\n\nNormalizing the systemic and splanchnic hormone and incretin concentrations relative to glucose concentrations in the appropriate compartments illustrate more precisely the specific effects of shunting.\n\nThe simulated data obtained with PSS are normalized relative to the ratios in the absence of PSS (i.e. with a portosystemic resistance = 40 mm Hg.s ml-1). The normalized ratios obtained show the excess or deficit in hormone or incretin response relative to glucose as function of portosystemic shunt opening. In the fasting state opening the shunt (from 40 to 0.005 mm Hg.s ml-1) increases the normalized insulin: glucose ratio to 2.1 above control (without shunting) (K½ = 0.03 mm Hg.s ml-1) (Figure 11A and Figure 12A).\n\nThe normalized systemic insulin: glucose ratio increases as shunt resistance falls to a maximum of 5.4 (PSS R K½ = 0.03–0.04 mm Hg.s ml-1). Two peaks in the systemic insulin: glucose ratio (Figure 11A) and in splanchnic insulin/glucose ratio (Figure 12A). The second smaller, but longer lasting increase in the insulin/glucose ratio, coincides with the second wave in hepatic gluconeogenesis/glucose ratio (Figure 12E; PSS R K½ = 0.06 mm Hg.s ml-1) and peripheral insulin-dependent metabolism (PSS R K½ = 0.015 mm Hg.s ml-1; Figure 11D). The ratio of systemic GLP-1/glucose also increases during the early phase of glucose absorption when the PSS is opened (PSS R K½ = 0.028 mm Hg.s ml-1; Figures 11B and Figure 12E).\n\nGLP-1 and insulin synergistically stimulate systemic glucose metabolism in insulin-sensitive tissues. Plots of the product of the normalized (GLP-1xinsulin product)/Glucose ratios (Figure 11E and Figure 12D) show large and inappropriate stimulation of peripheral insulin-dependent glucose metabolism (Figure 11E) and also stimulus to hepatic metabolism when the PSS is open (Figure 12D). Similar findings have been observed in the adipose tissues of patients with NASH109. PSS–dependent stimulus to insulin metabolism also causes a very large increase in hepatic metabolism relative to splanchnic glucose, particularly during the glucose absorptive phase. However this stimulus continues at a lesser level during the later digestive periods (Figure 12E).\n\n\nDiscussion\n\nThe chronology of events resulting from PSS following glucose gavage assists understanding of the complex interactions induced by hepatic shunting and are outlined in Figure 13:\n\n• Figure 13A. Shunt flows of GLP-1 and glucose and to a lesser extent insulin, are the earliest expression of PSS-dependent alterations in flow and metabolism (0–10min).\n\n• Figure 13A and 13B. A very large (tenfold) increase in the insulin-sensitive glucose metabolism in muscle and adipose tissue follow. This is accompanied by fall in systemic glucose concentration (red continuous line) relative to that observed in controls without shunting.\n\n• Figure 13C. The shunt condition decreases systemic and splanchnic glucose, raises glucagon secretion and inhibits GLP-1 secretion. Insulin secretion is also raised.\n\n• Figure 13D and 13E. The early onset of hypoglycaemia with high PSS increases splanchnic glucagon, thereby increasing hepatic gluconeogenesis. This promotes partial recovery of systemic glucose and insulin concentrations.\n\n• The oscillations of peripheral insulin dependent metabolism and splanchnic gluconeogenesis induced by PSS insulin flow are the cause of hyperglucagonaemia, frequently observed in NASH and T2DM70,96,104.\n\nUnanticipated findings of the model simulation of PSS are explanations for the suppression of post-prandial GLP-1 and raised blood glucagon concentrations (Figure 13C). Reduced GLP-1 concentration in the systemic circulation has been frequently reported, but generally ascribed to intrinsic failure of the secretory process96, rather than as a consequence of splanchnic hypoglycaemia brought about by overstimulation of peripheral insulin-dependent metabolism as demonstrated here.\n\nThe model simulation showing that portosystemic shunting in NASH and NAFLD generates imbalances between splanchnic and systemic distributions of insulin, glucagon and GLP-1 relative to glucose that stimulate insulin-sensitive metabolism in both liver that leads to hyperglucagonaemia and low GLP-1 is novel. A recently published clinical paper70 contains results that enable testing of these model predictions.\n\nThe hormone/glucose ratios in NAFLD patients (Figure 14A) and T2DM patients (Figure 14B) have been obtained from published data of plasma insulin, glucagon, GLP-1 and glucose concentrations70. The time series of insulin/glucose, glucagon/glucose and GLP-1/glucose concentration ratios after OGTT are normalized to those of control subjects. Insulin/glucose ratios exceed those in controls, initially by eightfold and remain higher throughout the test. This finding closely resembles the simulations with moderate portosystemic shunt and raised portal vein resistance shown in Figure 11A and 11C. Glucagon/glucose ratios exceed controls (by 2–3 fold) during the first 100 min of the test meal in both NAFLD and T2DM. As the authors suggest the absence of raised insulin/ratio indicates that insulin secretion may be suppressed in T2DM although not in NAFLD70.\n\n\nSummary of model findings\n\nThe computer model of human glucose absorption and metabolism demonstrates that increased superior mesenteric arterial (SMA) blood flow following intestinal glucose gavage, synchronous with glucose absorption, and insulin and GLP-1 secretion into the splanchnic circulation, is crucial to a harmonious balance between intestinal glucose absorption and its distribution and metabolism. Raised GLP-1 dependent splanchnic capillary flow, raises the passive component glucose absorption. GLP-1 and insulin synergise net hepatic glucose uptake (NHGU). When GLP-1 secretion is low, retarded SMA flow raises portal venous glucose concentration. Splanchnic hyperglycaemia slows passive glucose diffusion from intestine to capillaries.\n\nA second key factor causing hyperglycaemia is reduced NHGU due to decreased GLP-1-dependent hepatic glucokinase activity. Hyperglycaemia is sustained by reduced synergy of GLP-1 with insulin-sensitive muscle and adipocyte glucose metabolism.\n\nNASH initiates intrahepatic portosystemic shunting. Since splanchnic glucose, insulin and glucagon bypass hepatic sinusoids, this leads to inappropriate stimulation of peripheral insulin-dependent metabolism. This in turn accelerates the decrease in both systemic and splanchnic glycaemia. Splanchnic and systemic hyperglucagonaemia and suppression of GLP-1 secretion follow. Prolonged hyperglucagonaemia results in excess gluconeogenesis resulting in fasting hyperglycaemia and hyperinsulinaemia.\n\nLow rates of GLP-1 secretion could have a protective role in reducing post-prandial portal hypertension. This will also reduce portosystemic shunting of insulin and glucose lower splanchnic hypoglycaemia. Splanchnic hypoglycaemia by stimulating ghrelin release may be a contributory factor in the hyperphagia commonly associated with 2TDM inducing behaviour110,111.\n\nProlonged exposure of splanchnic endothelia to hyperglycaemia as occurs with low rates of GLP-1 secretion, could result in mitochondrial starvation of ascorbate due to competition inhibition of dehydroascorbate transport90,91 and initiate or exacerbate NASH.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for ‘A computer model simulating human glucose absorption and metabolism in health and metabolic disease states’, 10.5256/f1000research.8299.d117393112\n\n\nSoftware availability\n\nJmadonna sims of glucose metabolism-RJN March 2016. A working copy of the program, with a choice of graphical outputs available for all of the variables displayed in this paper and many others in addition. A trial copy of Berkeley Madonna is available which will permit the program to be run http://www.berkeleymadonna.com/jmadonna/jmadrelease.html without saving the data.",
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PubMed Abstract | Publisher Full Text\n\nBorgstrom B, Dahlqvist A, Lundh G, et al.: Studies of intestinal digestion and absorption in the human. J Clin invest. 1957; 36(10): 1521–1536. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCummins AJ: Absorption of glucose and methionine from the human intestine; the influence of the glucose concentration in the blood and in the intestinal lumen. J Clin Invest. 1952; 31(10): 928–37. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBarrett EJ, Ferrannini E, Gusberg R, et al.: Hepatic and extrahepatic splanchnic glucose metabolism in the postabsorptive and glucose fed dog. Metabolism. 1985; 34(5): 410–420. PubMed Abstract | Publisher Full Text\n\nHolman GD, Naftalin RJ: Transport of 3-O-methyl d-glucose and beta-methyl d-glucoside by rabbit ileum. Biochim Biophys Acta. 1976; 433(3): 597–614. PubMed Abstract | Publisher Full Text\n\nEskandari S, Wright EM, Loo DD: Kinetics of the reverse mode of the Na+/glucose cotransporter. J Membr Biol. 2005; 204(1): 23–32. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBasu A, Basu R, Shah P, et al.: Type 2 diabetes impairs splanchnic uptake of glucose but does not alter intestinal glucose absorption during enteral glucose feeding: additional evidence for a defect in hepatic glucokinase activity. Diabetes. 2001; 50(6): 1351–1362. PubMed Abstract | Publisher Full Text\n\nSim JA, Horowitz M, Summers MJ, et al.: Mesenteric blood flow, glucose absorption and blood pressure responses to small intestinal glucose in critically ill patients older than 65 years. Intensive Care Med. 2013; 39(2): 258–66. PubMed Abstract | Publisher Full Text\n\nIshikawa T, Shiratsuki S, Matsuda T, et al.: Occlusion of portosystemic shunts improves hyperinsulinemia due to insulin resistance in cirrhotic patients with portal hypertension. J Gastroenterol. 2014; 49(9): 1333–1341. PubMed Abstract | Publisher Full Text\n\nFarrell GC, Teoh NC, McCuskey RS: Hepatic microcirculation in fatty liver disease. Anat Rec (Hoboken). 2008; 291(6): 684–692. PubMed Abstract | Publisher Full Text\n\nMendes FD, Suzuki A, Sanderson SO, et al.: Prevalence and indicators of portal hypertension in patients with nonalcoholic fatty liver disease. Clin Gastroenterol Hepatol. 2012; 10(9): 1028–1033.e2. PubMed Abstract | Publisher Full Text | Free Full Text\n\nShigefuku R, Takahashi H, Kato M, et al.: Evaluation of hepatic tissue blood flow using xenon computed tomography with fibrosis progression in nonalcoholic fatty liver disease: comparison with chronic hepatitis C. Int J Mol Sci. 2014; 15(1): 1026–1039. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBasu A, Basu R, Shah P, et al.: Effects of type 2 diabetes on the ability of insulin and glucose to regulate splanchnic and muscle glucose metabolism: evidence for a defect in hepatic glucokinase activity. Diabetes. 2000; 49(2): 272–283. PubMed Abstract | Publisher Full Text\n\nEdgerton DS, An Z, Johnson KM, et al.: Effects of intraportal exenatide on hepatic glucose metabolism in the conscious dog. Am J Physiol Endocrinol Metab. 2013; 305(1): E132–E139. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBurcelin R, Da Costa A, Drucker D, et al.: Glucose competence of the hepatoportal vein sensor requires the presence of an activated glucagon-like peptide-1 receptor. Diabetes. 2001; 50(8): 1720–1728. PubMed Abstract | Publisher Full Text\n\nThorens B: GLUT2, glucose sensing and glucose homeostasis. Diabetologia. 2015; 58(2): 221–232. PubMed Abstract | Publisher Full Text\n\nBenoit JN, Barrowman JA, Harper SL, et al.: Role of humoral factors in the intestinal hyperemia associated with chronic portal hypertension. Am J Physiol. 1984; 247(5 Pt 1): G486–G493. PubMed Abstract\n\nAlexander B, Cottam H, Naftalin R: Hepatic arterial perfusion regulates portal venous flow between hepatic sinusoids and intrahepatic shunts in the normal rat liver in vitro. Pflugers Arch. 2001; 443(2): 257–64. PubMed Abstract | Publisher Full Text\n\nTu H, Li H, Wang Y, et al.: Low Red Blood Cell Vitamin C Concentrations Induce Red Blood Cell Fragility: A Link to Diabetes Via Glucose, Glucose Transporters, and Dehydroascorbic Acid. EBioMedicine. 2015; 2(11): 1735–50. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLee YC, Huang HY, Chang CJ, et al.: Mitochondrial GLUT10 facilitates dehydroascorbic acid import and protects cells against oxidative stress: mechanistic insight into arterial tortuosity syndrome. Hum Mol Genet. 2010; 19(19): 3721–33. PubMed Abstract | Publisher Full Text\n\nPasarín M, La Mura V, Gracia-Sancho J, et al.: Sinusoidal endothelial dysfunction precedes inflammation and fibrosis in a model of NAFLD. PLoS One. 2012; 7(4): e32785. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVahidi O, Kwok KE, Gopaluni RB, et al.: A comprehensive compartmental model of blood glucose regulation for healthy and type 2 diabetic subjects. Med Biol Eng Comput. 2015; 1–16. PubMed Abstract | Publisher Full Text\n\nSchaller S, Willmann S, Lippert J, et al.: A Generic Integrated Physiologically based Whole-body Model of the Glucose-Insulin-Glucagon Regulatory System. CPT pharmacometrics Syst Pharmacol. 2013; 2(8): e65. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHonka H, Mäkinen J, Hannukainen JC, et al.: Validation of [18F]fluorodeoxyglucose and positron emission tomography (PET) for the measurement of intestinal metabolism in pigs, and evidence of intestinal insulin resistance in patients with morbid obesity. Diabetologia. 2013; 56(4): 893–900. PubMed Abstract | Publisher Full Text\n\nBernsmeier C, Meyer-Gerspach AC, Blaser LS, et al.: Glucose-induced glucagon-like Peptide 1 secretion is deficient in patients with non-alcoholic fatty liver disease. PLoS One. 2014; 9(1): e87488. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMäkinen J, Hannukainen JC, Karmi A, et al.: Obesity-associated intestinal insulin resistance is ameliorated after bariatric surgery. Diabetologia. 2015; 58(5): 1055–62. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu Y, Wei R, Hong TP: Potential roles of glucagon-like peptide-1-based therapies in treating non-alcoholic fatty liver disease. World J Gastroenterol. 2014; 20(27): 9090–9097. PubMed Abstract | Free Full Text\n\nØstoft SH, Bagger JI, Hansen T, et al.: Incretin effect and glucagon responses to oral and intravenous glucose in patients with maturity-onset diabetes of the young--type 2 and type 3. Diabetes. 2014; 63(8): 2838–44. PubMed Abstract | Publisher Full Text\n\nCuthbertson DJ, Irwin A, Gardner CJ, et al.: Improved glycaemia correlates with liver fat reduction in obese, type 2 diabetes, patients given glucagon-like peptide-1 (GLP-1) receptor agonists. PLoS One. 2012; 7(12): e50117. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSu AP, Cao SS, Le Tian B, et al.: Effect of transjugular intrahepatic portosystemic shunt on glycometabolism in cirrhosis patients. Clin Res Hepatol Gastroenterol. 2012; 36(1): 53–59. PubMed Abstract | Publisher Full Text\n\nShigefuku R, Takahashi H, Kobayashi M, et al.: Pathophysiological analysis of nonalcoholic fatty liver disease by evaluation of fatty liver changes and blood flow using xenon computed tomography: can early-stage nonalcoholic steatohepatitis be distinguished from simple steatosis? J Gastroenterol. 2012; 47(11): 1238–1247. PubMed Abstract | Publisher Full Text\n\nRizza RA: Pathogenesis of fasting and postprandial hyperglycemia in type 2 diabetes: implications for therapy. Diabetes. 2010; 59(11): 2697–707. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJunker AE, Gluud LL, Holst JJ, et al.: Influence of gastrointestinal factors on glucose metabolism in patients with cirrhosis. J Gastroenterol Hepatol. 2015; 30(10): 1522–8. PubMed Abstract | Publisher Full Text\n\nOh da Y, Kim JW, Koh SJ, et al.: Does diabetes mellitus influence standardized uptake values of fluorodeoxyglucose positron emission tomography in colorectal cancer? Intest Res. 2014; 12(2): 146–152. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSun Z, Wang X, Deng X, et al.: The influence of intestinal ischemia and reperfusion on bidirectional intestinal barrier permeability, cellular membrane integrity, proteinase inhibitors and cell death in rats. Shock. 1998; 10(3): 203–212. PubMed Abstract | Publisher Full Text\n\nGranger DN, Mortillaro NA, Taylor AE: Interactions of intestinal lymph flow and secretion. Am J Physiol. 1977; 232(1): E13–8. PubMed Abstract\n\nAller MA, Heras N, Blanco-Rivero J, et al.: Portal hypertensive cardiovascular pathology: the rescue of ancestral survival mechanisms? Clin Res Hepatol Gastroenterol. 2012; 36(1): 35–46. PubMed Abstract | Publisher Full Text\n\nKim YO, Schuppan D: When GLP-1 hits the liver: a novel approach for insulin resistance and NASH. Am J Physiol Gastrointest Liver Physiol. 2012; 302(8): G759–G761. PubMed Abstract | Publisher Full Text\n\nDelhanty PJ, van der Lely AJ: Ghrelin and glucose homeostasis. Peptides. 2011; 32(11): 2309–2318. PubMed Abstract | Publisher Full Text\n\nKola B, Wittman G, Bodnár I, et al.: The CB1 receptor mediates the peripheral effects of ghrelin on AMPK activity but not on growth hormone release. FASEB J. 2013; 27(12): 5112–5121. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNaftalin RJ: Dataset 1 in: A computer model simulating human glucose absorption and metabolism in health and metabolic disease states. F1000Research. 2016. Data Source"
}
|
[
{
"id": "13996",
"date": "26 May 2016",
"name": "Martin Diener",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a nice piece of work in which the author simulates elegantly the effect of an incretin, GLP-1, on glucose absorption, metabolism and blood circulation as well as the level of hormones relevant for the regulation of sugar metabolism such as insulin and glucagon. Overall the paper is well written; title, abstract and conclusions are sound.\n\nI have only some minor comments for improvement of the manuscript:\nList of abbreviations: The list is incomplete, e.g. Fig. 9E can only be understood when reading the result text in which it is explained that here glucagon secretion is described. I suggest to control the complete text for further missing abbreviations (such as e.g.sys art V or Ce V in Table 1A). Perhaps this part would be easier to read when presented as a table (if this should be allowed by the journal). Some symbols are used in a double sense, e.g. P for pressure and for permeability. Perhaps it would be easier for the reader to use ‘p’ for pressure (in physics ‘P’ stands for power).\n\nP.9, paragraph about renal glucose excretion: 10 % filtration rate is only a meaningful estimate for glomerular filtration rate if referred to renal artery blood flow (and not renal artery plasma flow, which is the usual reference value for GFR in text books). So perhaps adding the word ‘blood’ might make this estimation more clear.\n\nLegend of Fig. 2, panel D: should be ‘… decreased aortic pressure and arterial volume’. Several figures: please add the units (e.g. mM to Sys glucose in Fig. 4D and so on) to all subheadings of all figures.\n\nP.26, 3 paragraph: I miss any explanation/discussion for the biphasic insulin response presented in Fig. 10C.\n\nTypographical errors:\np.8. last paragraph (right): Kirchhoff (not Kirchoff).",
"responses": []
},
{
"id": "14254",
"date": "09 Jun 2016",
"name": "Ian David Lockhart Bogle",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a comprehensive piece of modelling work. A complex model has been developed and tested and seems to support the evidence, particularly the effects of porto-systemic shunting which I don’t believe has been included in other modelling studies. In this sort of work it is difficult to provide unequivocal confirmation of model validity because of the complexity, the fact that some phenomena are inevitably not included although key ones have been, and any clinical data tends to be partial and there may be other things happening that have not been recorded. However as far as I can see the model supports expected behaviour and reported studies.\n\nThe equations are logical and solution methods seem appropriate. I have a few comments about parameter sensitivity and equation and parameter presentation below.\nThe Conclusions are supported by the predictions.\n\nI did find it difficult to relate the discussion with the model because of the way that nomenclature was used. For example on page 15 para 2 it refers to Table 1D GLP-1 equation 1 but I am not clear exactly which parameter it is referring to (similarly four lines later). What would really help would be for Table 2 to also give the variable name and equation number where it appears for each parameter.\nThis table does not give sources for the data and whether they are either taken from literature or fitted. I think this would also help.\nA few sensitivity studies have been done. I think they have been done because they are thought by the author to be important for clinical reasons. But it may be that model outputs are very sensitive to some parameters and it would be useful to know which ones these are. For example I would have thought that ‘GLUT2 Km’ (presumably ‘KM_GLUT2’ in the model = 20mM) was important given the key role of GLUT2 but sensitivity to this one isn’t tested. Are there others that are critical to model performance? If so the quality of the data supporting this would be critical. On page 17 ‘portosystemic shunt resistances’ were varied but what is the variable name and equation number where it appears?\nSome of the verification is vague. For example on p20 it says ‘these simulations are consistent with those found in NASH’ but does this mean qualitatively, in which what particular features, or quantitatively, in which case this could be quantified? Similarly in the following column ‘Hepatic shunt flow gas no significant effect on HA model’ but this isn’t shown. Is this to be expected?\nOn page 28 does the tenfold increase in insulin-sensitive metabolism apply to the whole metabolism? If so what is the effect on measurable metabolites and is there evidence that this might be the true?\nSome of the syntax of the models isn’t correct: Renal urine glucose flow (eqn 6 and repeated at the bottom of the page) is missing a bracket and Hepatic glucose metabolic rate has a spare one. These were the only two I spotted but it is worth checking all.",
"responses": []
},
{
"id": "14320",
"date": "10 Jun 2016",
"name": "C Charles Michel",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nFor much of the second half of the twentieth century, the absorption of nutrients from the small intestine was regarded as largely a question of understanding the detailed mechanisms of epithelial transport. That other factors might be involved was suggested by the high rates of glucose absorption from the small intestine of unanaesthetised mammals (including humans) that greatly exceeded those estimated or predicted from in vitro studies An analysis of the transport processes between the epithelial brush border and the blood flowing through the villus capillaries drew attention to the importance of the increased blood flow which accompanied glucose absorption1. This maintained gradients of glucose concentration through the mucosa sufficient to sustain the high rates of glucose uptake. At the time, the connection between intestinal glucose absorption and villus blood flow was unknown but the discovery and isolation of the glucagon like peptide, GLP-1, has led Professor Naftalin to suggest that this signalling molecule is the missing link, in addition to its other roles in glucose metabolism. From this starting point in the present paper, he develops a model of glucose absorption which is co-ordinated with changes in blood flow to both the jejunum and the liver and also the insulin dependent uptake of glucose in the liver, adipose tissue and skeletal muscle.\nFrom this simulation of the regulation of glucose absorption and metabolism in the healthy human, he uses his model to explore changes in occurring in patients suffering from non-alcoholic steatohepatitis, non-alcoholic liver disease and type 2 diabetes mellitus.\nWhile there are well known models of glucose metabolism2, to my knowledge, this is the first to incorporate intestinal glucose absorption. The way in which the different steps are coordinated here indicates a substantial advance in our understanding for which Professor Naftalin is to be applauded. I believe others will follow his lead and develop his model. It is interesting to see that it accounts successfully for the interactions between the portal and systemic circulations of the liver by simply assigning them with different compliances and different flows. I was a little surprised, however, that the model ascribed so much of the vascular regulation to GLP-1 when GLP-2 is both released concomitantly with GLP-1 and, in some mammalian species including humans, is known to act as a vasodilator in duodenum and ileum, the sites of glucose absorption. There is also evidence that GLP-1 and GLP-2 act synergistically in promoting glucose absorption3. Also, the governing equations of the present model involve many simplifications. For example, the equation for glucose absorption assumes the passive component is entirely accounted for by diffusion and lies in parallel with the active component when there is evidence for passive transport by solvent drag4 and interaction between active and passive components1. These, however, are relatively minor criticisms when the real achievement of the model is its demonstration of the importance of integrative physiology.\nI should say that I did not find this an easy paper to read. This is probably because I believe that the most important part of a paper describing a mathematical (or computer) model of a physiological process lies in the model's governing equations. When the governing equations are set out and justified in a “methods” or “theory” section, the reader can appreciate the simplifying assumptions and the extent to which they might compromise the model's predictions more quickly. Also, I believe, the values used for the model's parameters should be justified by references to the literature, wherever possible. In the present paper, the governing equations are listed in a table with little justification for their general form. The values taken for the constants and parameters are also presented in a table. I appreciate that the modern trend of many journals to relegate mathematical argument to appendices, may increase the readership of a paper and its number of citations but by doing so, it makes the true evaluation of the work more difficult. For this particular paper, however, I believe the additional effort is well worthwhile.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-647
|
https://f1000research.com/articles/3-164/v1
|
21 Jul 14
|
{
"type": "Research Article",
"title": "Shark fisheries in the Southeast Pacific: A 61-year analysis from Peru",
"authors": [
"Adriana Gonzalez-Pestana",
"Carlos Kouri J.",
"Ximena Velez-Zuazo",
"Adriana Gonzalez-Pestana",
"Carlos Kouri J."
],
"abstract": "Peruvian waters exhibit high conservation value for sharks. This contrasts with a lag in initiatives for their management and a lack of studies about their biology, ecology and fishery. We investigated the dynamics of Peruvian shark fishery and its legal framework identifying information gaps for recommending actions to improve management. Further, we investigated the importance of the Peruvian shark fishery from a regional perspective. From 1950 to 2010, 372,015 tons of sharks were landed in Peru. From 1950 to 1969, we detected a significant increase in landings; but from 2000 to 2011 there was a significant decrease in landings, estimated at 3.5% per year. Six species represented 94% of landings: blue shark (Prionace glauca), shortfin mako (Isurus oxyrinchus), smooth hammerhead (Sphyrna zygaena), common thresher (Alopias vulpinus), smooth-hound (Mustelus whitneyi) and angel shark (Squatina californica). Of these, the angel shark exhibits a strong and significant decrease in landings: 18.9% per year from 2000 to 2010. Peru reports the highest accumulated historical landings in the Pacific Ocean; but its contribution to annual landings has decreased since 1968. Still, Peru is among the top 12 countries exporting shark fins to the Hong Kong market. Although the government collects total weight by species, the number of specimens landed as well as population parameters (e.g. sex, size and weight) are not reported. Further, for some genera, species-level identification is deficient and so overestimates the biomass landed by species and underestimates the species diversity. Recently, regional efforts to regulate shark fishery have been implemented to support the conservation of sharks but in Peru work remains to be done",
"keywords": [
"endangered species",
"fish",
"elasmobranchs",
"fishing",
"landing reports",
"ocean",
"coastal",
"sustainable management",
"Peru",
"southeast Pacific"
],
"content": "Introduction\n\nOverexploitation and bycatch imperils sharks (Baum et al., 2003; Ward & Myers, 2005; Camhi et al., 2008; Ferretti et al., 2008). Sharks have been commercially fished for 200 years (Kroese & Sauer, 1998), but since the 1980’s its fishery has rocketed. The major driver has been a growing demand for shark fins, which can cost up to 1000 Euros per fin (Oceana, 2010). However, sharks are vulnerable to overfishing due to their life-history characteristics including slow growth, late maturity and small litter size (Musick, 1999). Their jeopardized situation is worsened by major gaps of knowledge that hinder the design and implementation of conservation and management actions. These gaps include a limited understanding of shark fishery characteristics (e.g. captures, gear, fishing areas, seasons; Bonfil, 1994; Rose, 1996), species diversity and the dynamics of their populations (Camhi et al., 2008; Smale, 2008).\n\nWithin the Pacific Ocean more than half of the reported landings are from the western and central Pacific (e.g. Japan, Hawaii, Camhi et al., 2008). Fishing vessels in the eastern Pacific also target sharks, but their contribution to the total Pacific catch and their impact on sharks is poorly known due to a lack of detailed landing reports. Three countries in the eastern Pacific; Costa Rica, Ecuador, and Peru, are important suppliers of shark fins for the Asian market, the major consumer of shark fins in the world (Oceana, 2010). Shark fishery information is available for Costa Rica and Ecuador either through published papers (i.e. Jacquet et al., 2008; Carr et al., 2013; Schiller et al., 2014) or by mass-media coverage (e.g. the movie Sharkwater), but for Peru the information is scarce. Yet, the coast of Peru exhibits a high degree of shark species richness and functional richness while the high seas (i.e. international waters) off Peru have a high value for shark conservation (Lucifora et al., 2011). In light of this, an understanding of the dimension and dynamics of shark fishery in Peru and its relative contribution to total landings from the Pacific is crucial to establish both local and regional management actions.\n\nIn this study, the past dynamics and current status of Peruvian shark fishery were investigated. Unpublished data, governmental reports and published literature were compiled to establish a baseline of information about sharks in Peru. This study aimed to (1) describe and analyze the Peruvian shark fishery, (2) identify and analyze the Peruvian shark fishery contribution in the Pacific basin, (3) analyze the international commerce of shark fins and meat in Peru (4) describe and analyze the conservation status of sharks in Peru and its legal framework (national and international), and (5) identify the current gaps in information and regulation hindering management actions in order to offer recommendations for improving management and conservation. This information would enhance local and regional management actions and would promote research in shark fisheries management. This study represents, so far, the first comprehensive investigation of Peruvian shark fishery research.\n\n\nMethods\n\nFor describing and analyzing Peruvian shark fishery, we combined total landing information (tons of sharks - t) from FAO (Food and Agriculture Organization of the United Nations, 1950–1963) and IMARPE (Instituto del Mar del Perú, 1964–2010). FAO reports landing by country using different alternatives for classification. For this study, we used reports using the ASFIS system. IMARPE, until 1996, reported landings of sharks without making any distinction regarding species but dividing them in three main groups which we pooled together: \"tiburon\" (sharks), “toyos” (smoothhounds Mustelus sp.), and “angelotes” (angel sharks, Squatina sp.). From 1996, landing reports are presented at the species level. To determine the six most landed shark species in Peru, we gathered species-specific landing information, from 1996 to 2010, published in the annual fishing reports of IMARPE (Estrella-Arellano & Guevara-Carrasco, 1998; Estrella et al., 1998; Estrella-Arellano et al., 1999a; Estrella-Arellano et al., 1999b; Estrella-Arellano et al., 2000a; Estrella-Arellano et al., 2000b; Estrella-Arellano et al., 2001; Flores et al., 1994; Flores et al., 1997; Flores et al., 1998a; Flores et al., 1998b; Flores et al., 2001).\n\nTo determine the locations with the highest shark landings, we used information from IMARPE between 1996 and 2010; to determine the fishing method used to catch sharks, we used information from IMARPE between 1996 and 2000. To create a map of Peru with landing points along the coast, we used Maptool a resource available from SEATURTLE.ORG.\n\nTo investigate the trend and change in shark landings in Peru between 1950 and 2010, we used a generalized least squares (GLS) to fit a linear model, maximizing the restricted log-likelihood (REML), with unequal variances to account for measurement uncertainty. For this, we used the package nlme (Pinheiro et al., 2014) implemented in R 2.13.2. To estimate the confidence intervals (CI) of the GLS model parameters we used a nonparametric bootstrapping with replacement (R=1000) of the resulting coefficients using the package boot (Davison & Hinkley, 1997; Canty & Ripley, 2013) in R 2.13.2. We established a time-scale length of 10 years to maximize detection of any significant trend in landings over this period of time. The decision for using this length was guided by results from preliminary tests, where we observed significance (p-value <0.05) over this time-scale compared to larger or smaller scales that were mostly non-significant. We partitioned the data every ten years, except for the last segment, from 2000–2010, where we included 11 years to use all the data. We used this same time-scale segment (2000 to 2010) to investigate the trend in landings by species.\n\nTo investigate the correspondence between the six most landed shark species and El Nino Southern Oscillation (ENSO), we used a linear regression analysis, which combined monthly landings by species with monthly values of the Multivariate ENSO Index (MEI). MEI is the value of the first unrotated Principal Component of the integrated analysis of six variables: sea surface temperature, sea-level pressure, surface wind, surface air temperature, and total cloudiness fraction of the sky (http://www.esrl.noaa.gov/psd/enso/mei/). For this analysis, we implemented the linear regression function (lm) in R 3.02 in RStudio 0.98.501 (www.rstudio.org).\n\nWe identified and analyzed the contribution of the Peruvian shark fishery to the Pacific basin by comparing total landings of chondrichthyans (sharks, batoids and chimaeras) followed by sharks only (i.e. using ASFIS system, www.fao.org) with landings reported by other countries fishing in the Pacific Ocean. When this information was filtered for sharks only, we were left with 24 countries reporting at this level. For the analysis, we compiled the statistics reported by country to FAO, between 1950 and 2010, using the software FishStatJ v.2.0.0 (http://www.fao.org/fishery/statistics/software/en).\n\nFor estimating and analyzing the annual and spatial dynamics of shark fin and meat international commerce, we obtained the tons imported and exported, by year and by country, and the free-on-board amount in American dollars ($ FOB) from 1997 to 2012, reported by commodity code by the Superintendencia Nacional de Aduanas y Administracion Tributarias (SUNAT, www.aduanet.gob.pe). Here, we used the same analytical approach used to investigate the trend and change in shark landings over a period of time to test for significant changes in the export and import of shark fins. For this analysis, the difference was that the time-scale length investigated was of five years, except for the period from 2007 to 2012 that was of six years.\n\nFinally, we described and analyzed the conservation status of landed sharks in Peru using the information from Red List of the International Union of the Conservation of Nature (IUCN, www.redlist.org, accessed in March 2012). To determine shark resilience, we used the global online database FishBase (www.fishbase.org, accessed in May, 2012). For describing and analyzing legal framework at the national level, we used information from Ministerial Resolution (RM) Nº 209-2001-PE, which regulates Peruvian shark fishery. At the international level, we used information from The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES, www.cites.org, accessed in March 2013); Convention on Migratory Species (CMS, www.cms.int, April 2012); and United Nations Convention on the Law of the Sea (UNCLOS). For all the analyses and graphic representation of data, we used R 2.13.2 (R Development Core Team, 2011).\n\n\nResults\n\nBetween 1950 and 2010, Peruvian fishery landed 372,015 t of sharks with a landing average of 6,099 t per year (SD ± 4251.3), a minimum of 700 t in 1951 and a maximum landing of 19,718 t in 1973 (Figure 1). Landings fluctuated over time exhibiting an increase between 1950 and 1973 with significant increases from 1950 to 1959 (slope=0.136, 95% CI: 0.057, 0.242, Table 2), which corresponds to an increase of 14.6% per year, and from 1960 to 1969 (slope=0.133, 95% CI: 0.041, 0.228), which corresponds to an increase of 14.2% per year. From 1973, landings decreased to a minimum of 1961 t in 1993. During the last 11 years of landings, from 2000 to 2010, a significant decrease in landings was detected (slope=-0.035, 95% CI: -0.0515, -0.0039), which corresponds to a decline of 3.45% per year.\n\nShark landings in Peru from 1950 to 2010 (solid line), its relative contribution to landings reported for the Pacific Ocean (dotted line), and shark fin exports from 1997 to 2010 (blue dotted line).\n\nIn Peruvian waters, 60 species of sharks are reported (Chirichigno, 1978; Nakaya et al., 2009; Cornejo & Chirichigno, 2012). Of these, 32 species interact with the Peruvian small-scale fishery (Romero & Bustamante, 2007), but landing statistics were limited to 18 species (Table 1). Six species comprise the majority of the shark fishery: blue shark (Prionace glauca), shortfin mako shark (Isurus oxyrinchus), smooth hammerhead (Sphyrna zygaena), smooth-hound shark (Mustelus whitneyi), common thresher (Alopias vulpinus), and the angel shark (Squatina californica). From 1996 to 2010, they represented 98% of total shark landings. Blue shark is the most common species landed in Peru (42% of shark landings), followed by shortfin mako (20%), smooth hammerhead (15%), smooth-hound shark (7%), common thresher (6%), and angel shark (4%). Since the shark fishery is dominated by these six species, their temporal and spatial patterns were analyzed. The other 12 shark species landed represented altogether 2% of the total landings from 1996 to 2010 (see recorded landing species in Table 1).\n\nIUCN: International Union for the Conservation of Nature, CITES: Convention on International Trade in Endangered Species, CMS: Convention on Migratory Specie, UNCLOS: United Nations Convention on the Law of the Sea.\n\n(a) Species status: EN-Endangered, VU-Vulnerable, NT-Near Threatened, LC-Least Concern and DD-Data Deficient; Population trend: DC-Decreasing, ST-Stable, UNK-Unknown, after IUCN Red List (www.redlist.org).\n\n(b) Resilience: Very low: Population doubling only about every 14 years, Low: minimum population doubling 4.5–14 years, from FishBase (www.fishbase.org).\n\nLandings by species varied between 1996 and 2010 exhibiting contrasting patterns for some species and a steady decline for others (Figure 2). Between 2000 and 2010, the landing of smooth hammerheads exhibited a significant increase (slope=0.069, 95% CI: -0.0075, 0.1516), corresponding to an increase of 7.14% per year, while significant declines in landings were detected for the shortfin mako (slope=-0.032, 95% CI: -0.0621, -0.0142) and angel shark (slope=-0.209, 95% CI: -0.3285, -0.1407). The declines of these two species were estimated at 3.16% and 18.88% per year, respectively (Table 2). Landings of blue sharks were particularly high in 1997 and 2001, while landings of the smooth hammerhead shark were the highest in 1998 and 2003. Similar to the blue shark, landings of the mako shark exhibited an increase, albeit not as strong, in 2000. For the angel shark, an increase in landings in 2001 (3,75.3 t) was observed, followed by a steady and significant decline only interrupted by a small peak of landings in 2007 (1,51.3 t). A weak, albeit significant relationship, between monthly shark landings and MEI values for four of the six most landed species was found (blue shark, correlation coefficient-r=0.28, slope=20462, ±SEM=5443.27, p-value<0.001; shortfin mako, r=0.29, slope=11579, ±SEM=2897.78, p-value<0.001; smooth hammerhead, r=0.29, slope= 12834, ±SEM=3241.57, p-value<0.001; smooth-hound, r=0.21, slope=-4317, ±SEM=1540.74, p-value<0.05).\n\nFifteen years of annual landings for the six most important commercial shark species: blue shark-Prionace glauca (green solid line-open circle), mako shark-Isurus oxyrinchus (orange dashed line-closed circle), angel shark-Squatina californica (light purple dashed line-open circle), smooth-hound-Mustelus whitneyi (fucsia solid line-closed square), common thresher shark-Alopias vulpinus (light green solid line-closed triangle), and smooth hammerhead shark-Sphyrna zygaena (yellow solid line-open square).\n\nSlope: parameter estimate for year; SE: standard error of predicted estimate; n.s.: not significant p-value (>=0.05); RSE: model residual standard error; upper and lower limits of the 95% confidence interval. Mean annual change in landings was calculated as = [(eslope - 1) x 100]. The upper and lower limits of change in landings was calculated as =[(eslope±1.96SE -1) x 100].\n\nShark landings were not homogeneously distributed along the coast; we observed a tendency to land certain species at specific points (Figure 3). The analysis was limited to the main ports in the north (i.e. Talara, Paita, San Jose), central (i.e. Chimbote and Pucusana) and south (i.e. Matarani and Ilo) for which information at species level was available from 1996 to 2010. The data suggests that the port of Ilo is the principal landing point for sharks (by biomass). An approximate of 9910 t of sharks was landed, accounting for 32% of the total biomass landed in these seven ports. The second most important port was Pucusana (21%), followed by Paita (20%), San Jose (14%), and Chimbote (9%). Talara and Matarani, together, accounted for less than 4% of the total landings. All ports landed the six species, but landings were biased towards certain shark species: blue sharks were mostly caught in southern (45%) and central (38% of total blue shark landings) landing points; shortfin mako were mostly caught in south (54%) and central (40%); smooth hammerheads were mostly caught in central (43%) and north (57%); and smooth-hound sharks, common thresher and angel sharks were mostly caught in the north with 99%, 83% and 95% landings, respectively.\n\nLanding points reporting shark landings (open circles), including the seven points with highest landings (black squares) along the coastline of Peru with the landing composition by the six most important shark species 1996 to 2010. The horizontal bar represents total landings by species in percent. Dark green: Prionace glauca, orange: Isurus oxyrinchus, purple: Squatina californica, fucsia: Mustelus whitneyi, light green: Alopias vulpinus, and yellow: Sphyrna zygaena.\n\nFrom 1996 to 2000, longline accounted for the highest percentage of landed sharks by biomass (60%), followed by gillnets (32%), purse seine (6%), and beach seine and others that together accounted for the remaining 8%. In general, the gillnet shark fishery catches the highest diversity of sharks (up to 20 species) including both pelagic and benthic species. A marked difference in the composition of the most landed shark species by each fishing method was observed: vessels used longline to capture blue shark (79% of its total landing), shortfin mako (94%) and common thresher shark (39%). In contrast, gillnets were used to capture smooth hammerhead (83%), smooth-hound shark (85%), common thresher shark (58%), and angel shark (86%).\n\nThroughout the Pacific, between 1950 and 2010, Peru had the sixth highest accumulated landings of chondrichthyans (sharks, batoids and chimaeras). The first five countries were (in order): Japan, Taiwan Province, Indonesia, Mexico and Republic of Korea. Along the eastern Pacific, Peru had the second highest number of landings, after Mexico. Other important countries were the USA, Chile, Canada and Costa Rica. In the southeast Pacific, Peru reported the highest landing of chondrichthyans, which was four-fold higher compared with Chile, which had the second highest number of landings in the region.\n\nAccording to FAO, between 1950 and 2010 (for the 24 countries that report its landings at shark level) Peru exhibited the highest accumulated historical landings of sharks in the Pacific basin (431,534 t) followed by New Zealand, Mexico and Indonesia. In the east Pacific, Mexico’s landings were approximately half of Peru’s landings (230,986 t). However, the annual contribution of Peru to total shark landings in the Pacific has changed (Figure 1). It increased from ~7% in 1950 to an all-time high of 88% in 1968, decreasing to a minimum of 2.95% in 2006. In the last five years assessed (2005–2010), the mean contribution was 5.88% (± 2.15), slightly higher than the contribution of Ecuador (5.50% ± 2.96) and Costa Rica (1.56 ± 0.04). In the same period, Indonesia’s mean contribution to Pacific shark landings was 47.27% (± 4.76) and New Zealand contributed 16.14% (± 2.12) of total shark landings.\n\nSix different commodity codes used by SUNAT were used to identify shark-based products (0305591000, 0305710000, 0303750000, 0303810000, 0302810000, 0305791000); half of them corresponded to shark fin while the other half identified shark meat. All of them contained reports of international commerce that, when pooled together, provided all import and export movements from 1997 to 2012 by country of origin/destination.\n\nA significant positive trend was detected for the export and import of shark fins and meat between 1997 and 2012 (shark fin import: r=0.75, p-value<0.001, export: r=0.56, p-value=0.02; shark meat import: r=0.90, p-value<0.001, export: r=0.64, p-value=0.008, see Figure 1). From 1997 to 2012, Peru imported 268.66 t of shark fin worth 2,279,003.67 US dollars and exported 2,353.70 t of shark fin worth 101,480,171.30 US dollars. The main origin for shark fin supply to Peru in this period of time was Ecuador (~87%), followed by the high seas (i.e. international waters, 8%), and Spain (3%). The main destination of shark fin export was Hong Kong (87%), followed by Japan (7.2%), China (~1.3%), United States (1%); minor exports (<1%) were shipped to another 22 other countries around the globe. In the same period of time, Peru imported 16113.85 t of shark meat worth 9,817,805.73 US dollars, mainly from high seas (29%), Japan (~28%), Ecuador (22%), and Spain (9%), and exported 8,177.96 t worth 12,496,756.72 US dollars mainly to Brazil (69%), Venezuela (9%), Colombia (7%), and Spain (6%).\n\nOf the 32 species that interact with fisheries in Peru, two are listed as Endangered, 11 as Vulnerable, 10 as Near-Threatened, one as Least Concern, and eight are classified as Data Deficient by the Red List of the International Union of the Conservation of Nature (IUCN, www.redlist.org, accessed in March 2012) (Table 1).\n\nThe life history traits exhibited by these species indicate that 22 out of the 32 species interacting with fishery in Peru have a very low resilience, and will need a minimum of 14 years to double their population, and 10 species have low resilience, needing a minimum of 4.5–14 years to duplicate their population (FishBase, www.fishbase.org) (Table 1). The Peruvian anchovy (Engraulis ringens) - the most heavily exploited fish in world history - only needs 15 months to double its population.\n\nThe whale shark (Rhincodon typus), oceanic whitetip shark (Carcharhinus longimanus), porbeagle shark (Lamna nasus), scalloped hammerhead (Sphyrna lewini), smooth hammerhead (Sphyrna zygaena) and great hammerhead (Sphyrna mokarran) are listed in Appendix II of The Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES, www.cites.org, accessed in March 2013). The mako shark, the porbeagle shark and the whale shark are listed in the Convention on Migratory Species (CMS, www.cms.int, April 2012), and the United Nations Convention on the Law of the Sea includes the whale shark, members of the Family Sphyrnidae (hammerhead sharks), Isuridae (mackerel sharks), and Carcharhinidae (whaler sharks) in its list of highly migratory species. Peru has been landing whale sharks since 2006; 2,813 t of whale sharks were landed as reported by IMARPE, but isolated events of unreported landings have been observed in northern Peru (B. Alcorta pers. comm.).\n\nThe shark fishery in Peru is regulated by the Ministerial Resolution (RM) Nº 209-2001-PE from the Ministry of Fisheries (now Ministry of Production, Vice-Ministry of Fisheries). There are additional regulations for other fisheries (e.g. sea bass, migratory species, and tuna; RM 236-2001-PE, RM 058-2002-PE, and Decreto Supremo-DS 032-2003-PRODUCE) that indirectly regulate the capture of sharks by considering them accompanying fauna (i.e. bycatch). The RM 209-2001-PE is the most comprehensive regulation for the shark fishery in Peru. It establishes the shark minimum length that can be landed, the maximum tolerance of captured individuals under the minimum length and the minimum mesh size for gillnets targeting sharks. The minimum length at capture applies to five species and one genus: blue shark, shortfin mako, smooth-hounds (Mustelus whitneyi, M. mento), spotted hound shark (Triakis maculata) and species of the genus Carcharhinus (Table 1).\n\n\nDiscussion\n\nThis study represents the first analysis of Peruvian shark fishery, provides a historical perspective of its dynamics over a 61-year period and sets up a baseline of information for further research. The results are discussed within a national and regional framework in the light of shark conservation status, the current legal framework in which the shark fishery operates, and the gaps of information and regulation.\n\nA temporal and spatial variation in shark landings was observed. During the 61 years assessed, shark landings significantly increased by nearly 15% per year during the first two decades; but during the last 11 years it has experienced a constant annual decline of more than 3%. Peruvian vessels related to shark fishery have doubled from 2061 in 1996 to 4013 in 2002 (IMARPE, 2003). Between 1995 and 2010, the number of vessels using longline has increased by 357%; while the total length of gillnets in Peru was estimated at >100,000 km of net per year: 14 times the length used by the Taiwanese high seas driftnet fleet in the Pacific before it was banned (Alfaro-Shigueto et al., 2010). It is noteworthy that the Peruvian fleet using longline and gillnet has increased but the landings have not. This decoupling between fleet size and shark landings might be caused by the following factors or combination of factors: illegal, unreported and unregulated (IUU) fishing in Peru, oceanographic and biological conditions (e.g. El Nino Southern Oscillation, prey availability), changes in fishing target and the decline of the populations of targeted species.\n\nThe extent of IUU fishing in Peru has been determined as critical in Peruvian waters and suggested to be around 30% of total biomass landed (Pramod et al., 2008), but has not been explicitly assessed for sharks. The incidental capture (or bycatch) of sharks occurs but it is unreported. A bycatch rate of 0.99 sharks every 1000 hooks was estimated from the mahi-mahi longline fishery in four ports in Peru between 2004 and 2006, while at the port of Ilo, between 2005 and 2006, shark bycatch represented 1% of the total landings (Gilman et al., 2008). The hake and shrimp fisheries have high shark interactions and discard rates (Kelleher, 2005; Pitcher et al., 2006). In Peru, six species of sharks are incidentally captured and discarded at sea (Mustelus whitneyi, Mustelus sp., Notorynchus cepedianus, Echinorhinus cookie, Galeorhinus galeus, Squatina sp.; Cespedes, 2013). Moreover, small scale trawlers, the numbers of which are unknown but likely considerable, illegally target hake in northern Peru. To the best of our knowledge, no more data on shark bycatch is available; however, reports from fishing gears, specifically trawlers and purse seiners, could be considered as preliminary information since these fisheries do not target sharks: 1130 t of sharks were caught using purse seine (96%) and trawlers (4%) (data from IMARPE, between 1996 and 2000).\n\nThe El Nino Southern Oscillation (ENSO) could also be influencing shark landings. A correlation between species range expansions and contractions and ENSO has been observed and likely to be caused by habitat alterations and changes in food availability (reviewed in Fiedler, 2002). Indeed, prey availability (Vas, 1990) and sea surface temperature (Walsh & Kleiber, 2001; Nakano & Seki, 2003) have been shown to correlate with blue sharks catches. Sharks have been reported in greater abundance as well as moving southward and closer to the coast in the southeast and northeast Pacific during ENSO events (reviewed by Alvial, 1987; Sielfeld et al., 2010). Similarly, the jumbo squid (Dosidiscus gigas) a species preyed by top-predators, including sharks (Vetter et al., 2008; Lopez et al., 2010), exhibited changes in its biomass and distribution range as a response to the environmental changes observed during an ENSO (Field et al., 2007; Zeidberg & Robison, 2007). In this study, a weak but significant correlation between the ENSO and the biomass of four species of sharks landed along the coast of Peru was detected.\n\nAn important gap in data that we were not able to obtain for this study was the fishing effort. Catch rates and fishing effort could provide a more accurate insight into the dynamics of shark fishery in Peru, an explanation for the changes in historical landings and, a better understanding of the status of shark populations (Clarke et al., 2013). Finally, a steady decline of the population can also explain the decrease in landings. An interesting example is the angel shark whose landings have exhibited a steady decrease of nearly 19% per year. The angel shark is a species of low resilience to high fishing pressure (Richards, 1987), and in part of their range of distribution the fishery has been banned. The Red List now considers this species overfished and as Near Threatened (Cailliet, 2005).\n\nPeru reports an approximate 11% of the total diversity of sharks, exhibiting high values of shark species richness and functional richness (Lucifora et al., 2011). According to this study, more than half of the sharks reported in Peru are considered of commercial importance; however, this could be an underestimate. Some commercial species are grouped with a single common name (i.e. “toyo”) that can represent many species in at least two genera (e.g. Mustelus spp., Triakis spp.) and that include species considered as Endangered (i.e. T. acutipinna, IUCN Red List). For other species, such as thresher sharks (Alopias sp.), species identification based on morphology can be difficult to assess when only parts of individuals are landed, which usually occurs. Here, molecular analyses using genetic barcodes (reviewed in Bucklin et al., 2011) or a barcoding approach (Naylor et al., 2012) stand as a powerful tool to identify species landed. Indeed, a study using this approach suggests a misidentification of the species actually landed (Velez-Zuazo et al., in press).\n\nShark landings, at the species level, were not equally distributed by port, along the coast. This might be due to the presence of two main marine currents, the Peruvian Current (or Humboldt Current) and the Equatorial Current, and the regions identified under their influence: temperate cold upwelling region in the south, tropical warm region in the south, and an intermediate area where the two currents converge in the north of Peru (Spalding et al., 2007). Shark landings, particularly species occupying coastal habitats, and mostly caught with gillnets, might be influenced by local oceanographic characteristics and species behaviour (e.g. Espinoza et al., 2011). Pelagic species (e.g. blue shark), on the other hand, might be influenced by other factors. Pellon & Cardenas, 1993 reported that in the exploratory fishery of tuna using longline, high concentrations of blue shark, shortfin mako and common thresher were found in the north off Peru. Another factor influencing landings at ports is that the use of fishing gear is skewed by zone: the central and south of Peru uses mainly longline; while gillnets are the dominant fishing gear in northern Peru. Further research is needed to understand fishing gear selectivity on shark species capture (Pope et al., 1975).\n\nThe Peruvian fishery of elasmobranchs is the third largest in the Americas (Bonfil, 1994) and Peru is among the top 26 shark fishing countries in the world (Fischer et al., 2012). This analysis suggests that Peru has landed more sharks than any other country in the entire Pacific. It is worth noting that neither Costa Rica nor Ecuador, important countries in the eastern Pacific that export shark fins to the Asian market, were at the top of the list. In both countries, until recently, shark finning was legal and common practice, likely contributing to an underestimation of the biomass of sharks captured but discarded at sea (Clarke et al., 2006). In Ecuador, underestimation of shark landings were highlighted by Jacquet et al., 2008 and their study provided new estimates from 1979 to 2004. This was compared with Peruvian estimates and similar landings were found for both countries during that period, with Ecuador having a slightly higher overall landing (178,569 t in Ecuador and 175,571 t in Peru).\n\nRegional initiatives for management and conservation followed after the 1999 FAO International Plan of Action for the Conservation and Management of Sharks (IPOA-sharks). The Regional Action Plan for the Protection and Management of the elasmobranchs of the Southeast Pacific Ocean (PAR-Tiburon) was approved in 2010 by the “Comision Permanente del Pacifico Sudeste” (CPPS 2010) attended by Colombia, Ecuador, Peru, and Chile. At the country level, Peru has adopted the regional plan and just approved its national plan of action (NPOA, Decreto Supremo No 002-2014-PRODUCE) for the conservation and management of elasmobranchs. national plan of action (NPOA) for the conservation and management of elasmobranchs.\n\nBoth shark fin and meat imports and exports exhibited a positive and significant trend during the time evaluated (1997 to 2012). There were differences, however, in the volumes. While import is much lower than export in shark fin, shark meat import is higher that export. Peru exported almost ten times the quantity of shark fins it imported (export=2,353.7 t versus import=268.66 t) and almost double the amount of shark meat (16,113.84 t) was imported compared to the amount exported (8,177.95 t). This suggests that shark fins are a commodity that Peru mostly exports while there is a local demand for shark meat. Indeed, a recent report indicates that Peru is among the top 20 importers of shark meat and is the most important in the southeast Pacific (Mundy-Taylor & Crook, 2013). There is no doubt, however, of the profit made exporting shark fins. During the period of time analyzed, Peru exported shark fins for a FOB value of more than 101 million US dollars. During the same period, the FOB value of shark meat was only around 12.5 million US dollars, even though its export volume was four times higher than shark fins.\n\nA recent study addressing the global shark business estimated that Peru was among the twelve major countries in the world supplying shark fins to the market of Hong Kong between 2002 and 2008 (Cheung & Chang, 2011). CITES determined that a total of 2,768 t of sharks and an average of 146 t of shark fins per year were exported from Peru between 2003 and 2008 (CITES, 2011). The estimates of shark fins exported in our current study are very similar although slightly higher. During that same period of time, Peru exported 156 t of shark fins per year.\n\nThe dynamics of shark fin import indicates that Ecuador is the major country of origin of fins entering Peru, starting in 2008. This is very likely explained by the change in shark fin export regulations in Ecuador (Jacquet et al., 2008). In 2004, a decree from the Ecuadorian government banned all shark fin exports, but in 2008 it was overturned. Before 2008, the average import was 1.52 t originating from several different countries with no obvious dominance over these years. In 2008, however, shark fin imports increased by almost 30-fold. Between 2008 and 2012, Peru imported an average of 51 t of shark fins, almost exclusively from Ecuador. The second most significant source of shark fins was from the high seas, with a total of 22.8 t of fins imported. Since Peru stills lacks regulation for shark finning in general, there is no control over the origin of the fins obtained from vessels fishing in the high seas and how the fins were obtained, although shark finning is banned in the eastern Pacific ocean (IATTC, 2005). While Ecuador is the main source of shark fin imports, Hong Kong is the main destination for shark fin export. Nearly 87% of shark fins exported between 1997 and 2012 went to Hong Kong. Five other countries in Asia made up a further 10% (i.e. China, Japan, Singapore, Republic of Korea, and Vietnam).\n\nThe import and export of shark meat has experienced steady growth. In 1997 Peru imported 16 t and in 2012 imported 5959 t. An important source is the high seas, which provided nearly 36% of all shark meat imported by Peru. Other important sources were Japan, Ecuador and Spain. While Asia was the most important destination area for shark fins, it was Latin America that was the most important area for shark meat exports. Nine countries, headed by Brazil (70%), accounted for 90% of all exports shipped from Peru between 1997 and 2012.\n\nPeruvian shark fishery is regulated; however, this regulation has three fundamental flaws. First, only 13 of the 32 commercially fished species and merely four of the 13 species that are threatened are included, leaving the fishery of species such as the smooth hammerhead unregulated. Neonates and juvenile hammerheads (i.e. those under 90 cm in length) are targeted heavily in the north of Peru (Gonzalez-Pestana, unpublished data). Between 1991 and 2000, 97% of smooth hammerheads landed in the port of San Jose had not reached sexual maturity (Castañeda, 2001). The listing of S. zygaena in CITES Appendix II in March 2013 represents a new challenge and task for Peru for regulating and controlling the international trade of this species, which is currently fished without any kind of regulation. To reinforce the scale of this fishery, between 2002 and 2011, Peru landed a higher biomass of smooth hammerheads than the sum of all other countries reporting landings for this specie (i.e. Spain, Ecuador, Portugal, and New Zealand; Mundy-Taylor & Crook, 2013). Second, it sets the minimum capture length only for a handful of species, which does not include three out of the six most landed sharks (i.e. smooth hammerhead, common thresher, and angel sharks) and groups other species by genus, setting the minimum size for the whole group. This is the case of the genus Carcharhinus, where the minimum capture length is 150 cm; however, of the eight species of Carcharhinus reported interacting with fisheries in Peru, two species mature at smaller sizes, therefore, catches are only allowed for mature individuals, which potentially has a negative impact on their populations. Overfishing of adults of the tope shark Galeorhinus galeus in Australia affected the recruitment on nursery grounds and consequently later adult recruitment (reviewed in Kinney & Simpfendorfer, 2009). Third, the regulation is not biologically meaningful. The minimum capture length for the mako shark is set at 170 cm but IMARPE reports that 60.1% (year 2009) and 88.5% (2010) of mako landings in the port of Pucusana were under minimum legal size (Anuario CientíficoTecnológico Vol. 5–10, 2005–2010).\n\nPeru has no regulation against shark finning (i.e. the practice of removing and retaining the fins of live sharks and returning the shark back to the sea where it eventually dies), but finning at sea seems not to occur in Peru. Gilman et al., (2008) and field observations agree that sharks are commonly landed with fins attached and later removed and sold at the port. Shark fins in Peru have a price by kilogram that is higher compared to the rest of the carcass due to their international demand to prepare shark fin soup. In 2011, the minimum price of shark fin in the local market was 64.2 US$ per kilogram while the maximum price was 98.58 US$. Shark fins, as estimated in this study, are one of most important products exported.\n\nResearch is urgently needed to improve the conservation of sharks and should include taxonomy (production of identification guides), life history (e.g. reproductive biology), spatial ecology (e.g. movement and migration), effect of climate variability (e.g. ENSO), ecosystem role (e.g. diet and trophic structure), fishing (e.g. catch and effort), population status (e.g. stock assessment), commerce (e.g. commercial routes of shark fins), and human values, attitudes, beliefs and behaviors toward sharks (Simpfendorfer et al., 2011). This information is essential to design and implement shark management (e.g. fishery and marine protected areas). For example, combining fishery with biological and ecological information is crucial to estimate the number of individuals that could be safely removed without affecting the integrity and functionality of populations (Botsford et al. 1997; Köster et al., 2003; Dankel et al., 2008). Understanding the trophic ecology of marine environments where sharks interact is critical for implementing ecosystem based fishery management (FAO, 1996) that is being applied by IMARPE. Also, it is equally important to understand the values, attitudes, beliefs and behaviors of the people, industries and communities that depend on sharks (Simpfendorfer et al., 2011) because managing resources is also about the people who exploit it (Hilborn, 2007).\n\nWith so many species interacting with fishery at different spatial and temporal scales Peru must prioritize its conservation management on the most fished and imperiled species. First, management should be applied to the six most fished species in Peru at the most important landing points. Legal regulation is a critical element in achieving effective conservation and management of sharks (Techera & Klein, 2011). Thus, shark finning must be banned and NPOA must be implemented in the short term. One of the major challenges for the conservation of sharks is that the most caught species in Peru are also highly migratory (i.e. blue shark, mako shark, smooth hammerhead and common thresher). So, they are constantly crossing nation borders; if one country within the migratory range has weaker laws, it may undermine conservation and management efforts in another (Techera & Klein, 2011). As such, regional actions are necessary.\n\n\nConclusions\n\nThe Peruvian fishery interacts with 32 shark species of which the six most frequently landed are the blue shark, shortfin mako shark, smooth hammerhead, smooth-hound shark, common thresher, and the angel shark. The highest landings occur at Talara, Paita, San Jose, Chimbote, Pucusana, Matarani and Ilo; and the fishery gear most used are longline and gillnets. Peru is one of the most important countries in the whole Pacific Ocean with regards to shark fishery and the data suggests that, historically, it has landed more sharks than any other country in the Pacific. The international commerce of Peruvian shark fin and meat has increased between 1997 and 2012 with higher profits reported for exporting shark fins, mainly to Hong Kong. Peru also imports shark fin, mostly from Ecuador, although imports from the high seas represent an important source of fins and meat and this needs attention to reduce the entrance of IUU fishery products. The Peruvian shark fishery is under-monitored and under-regulated; even though 41% of shark species landed are threatened and seven species that interact in Peruvian fishery are included in CITES and CMS. The most comprehensive shark regulation in Peru, Ministerial Resolution Nº 209-2001-PE, has fundamental flaws that need to be addressed. Great gaps in information exist that hampers its management including in basic taxonomy, life history and spatial ecology, among others, but this could be addressed by promoting research, education and awareness and involving stakeholders at all levels. Peru has made the first steps towards the recovery and sustainable conservation of sharks by approving the NPOA, but works remains to be done.\n\n\nData availability\n\nAccess to the landing statistics collected by the Instituto del Mar del Peru is possible by presenting, in person, at the administrative office, providing a filled form (downloadable from here: http://www.imarpe.pe/imarpe/index.php?id_seccion=I0116010601000000000000) and corresponding fee, following the instructions described here: http://www.imarpe.pe/imarpe/archivos/informes/imarpe/tup_mod_rd_de_125_2010.xls, also accessible here: http://www.imarpe.pe/imarpe/index.php?id_seccion=I0116010601000000000000 All documents are in Spanish.\n\nAccess to landing statistics published by FAO are available in their webpage (www.fao.org) using the software FishStatJ v.2.0.0 (http://www.fao.org/fishery/statistics/software/en).",
"appendix": "Author contributions\n\n\n\nAGP, CKJ and XVZ conceived and designed the experiments, AGP and CKJ collected the data, AGP and XVZ analyzed the data, AGP and XVZ wrote the paper. All authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis research was supported by a merit and exceptional performance scholarship scholarship from the University of Puerto Rico, Department of Graduate Studies and Research, to XVZ.\n\n\nAcknowledgments\n\nWe would like to acknowledge the division of small-scale fisheries of IMARPE for kindly facilitating access to their public database of landing statistics, to PROMPERU (Ministerio de Comercio Exterior y Turismo) for providing import and export data for our study, and to Aaron Canepa (Ministerio de la Produccion) for providing landing information. 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"id": "5526",
"date": "18 Aug 2014",
"name": "Shelley C. Clarke",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper presents a comprehensive and very useful introduction to the shark fisheries of Peru, a topic about which very little has been published until now. The authors have expended considerable effort to compile historical data and I agree with them that this paper \"sets up a baseline for future research\". However, some of the conclusions in the paper lack sufficient justification to be reliable and should be presented as hypotheses for further study rather than findings from this paper.The main shortcoming of the datasets used in the paper is the over-reliance on landings data to represent the state of the shark stocks. Landings data are a function of fishing effort and the recording system (coverage, consistency and species-specificity). These topics are mentioned but not given the depth of discussion that they deserve. Lack of effort data is a common problem in historical fisheries datasets and the authors may have extracted all the useful information they could from available records, but the paper does provide some information on trends in vessel numbers over time. It would have been useful to provide such numbers in a table or figure, or further to make some assumptions about the number of fishing days based on trip length for certain vessel classes and the number of landings recorded. Even a rudimentary estimate of effort would have assisted in converting catch data to catch rate and thus provide a potential index of abundance. Furthermore, it seems there could have been more discussion on how the coverage and consistency of the landings data changed over the 61 years of the study period, and when species-specific recording practices were implemented for each of the main shark species examined. Given that only landings data were used, and as explained above biases are largely unknown, the complexity of the analysis is probably unwarranted. It is not made clear why trends were analyzed as 10-year intervals and why this is considered appropriate. Fitting a linear model to a noisy time series is not an appropriate means of determining a trend. Even if the fit is statistically significant, the slopes and correlation coefficients are often very small and this does not support a conclusion that a meaningful trend is present. It is noted that only half of the twelve species/time intervals analyzed had statistically significant slopes, though all are presented and discussed.The findings regarding the proportion of Peru's landings of chondrichthyans in the Pacific from 1950-2010 should be checked. Using the FAO FISHSTAT database, my calculations show that Peru's highest proportion (17%, not 80% as suggested by Figure 1) occurred in 1984 and over the 60-year time period it averaged 6%. Of course, the figures from other countries are also subject to the time-dependent biases in fishing effort and reporting systems as mentioned for Peru above. Therefore, this comparison should be heavily caveated. With regard to the discussion of trade, it would have been better to present annual values (perhaps in a table) rather than aggregated amounts for 1997-2012. The important point about Peru having picked up the trade in shark fins when Ecuador banned this trade in 2008 should have been illustrated in a table or figure. I wonder if the authors were able to explore how much of the Peruvian imports during this period were from fishing vessels choosing to land shark products in Peru versus from traders re-routing their consignments through Peru. What role do foreign fishing vessels play in Peruvian shark landings and has this changed over time? It would also have been interesting to hear about the trade in skate and ray wings, and whether this follows similar patterns as shark fins or is primarily for the domestic market. In terms of management, the authors should be clear in recommending whether a maximum size or a minimum size is a better strategy--the discussion seems to make points on both sides of this argument. Also, what is the status of implementation and enforcement in Peruvian fisheries? Finally, since the authors claim that shark finning is not practiced because sharks are utilized for their meat, it is not clear why a shark finning ban is recommended as a management priority. It seems under current circumstances in Peru that recommending catch limits might be a more effective way of controlling shark mortality within sustainable limits.",
"responses": [
{
"c_id": "1846",
"date": "12 Apr 2016",
"name": "Ximena Velez-Zuazo",
"role": "Author Response",
"response": "The main shortcoming of the datasets used in the paper is the over-reliance on landings data to represent the state of the shark stocks. Landings data are a function of fishing effort and the recording system (coverage, consistency and species-specificity). These topics are mentioned but not given the depth of discussion that they deserve. Lack of effort data is a common problem in historical fisheries datasets and the authors may have extracted all the useful information they could from available records, but the paper does provide some information on trends in vessel numbers over time. It would have been useful to provide such numbers in a table or figure, or further to make some assumptions about the number of fishing days based on trip length for certain vessel classes and the number of landings recorded. Even a rudimentary estimate of effort would have assisted in converting catch data to catch rate and thus provide a potential index of abundance. We agree with the reviewer that estimates of fishing effort would provide a more accurate picture of the dynamics of the shark fishery in Peru. These estimates are collected by the government but are not available to the public and are very difficult to obtain. We have made, however, an effort to get a rudimentary estimate using data from published articles. We used data from Alfaro-Shigueto et al. (2010) and extrapolated it. The details and results are now included in the Methods and Results section.In the Methods section we included:\"We estimated the average catch per unit effort (CPUE) for the most landed shark species between 2002 and 2007. According to Alfaro-Shigueto et al. (2010), the fishing effort of the small scale fishery that uses gillnets is 100 000 km of nets per annum and for the longline the effort is 80 million hooks set per annum. We extrapolated these numbers to the Peruvian small-scale shark fishery so we can obtain an estimated CPUE. First for each of the most landed species, we calculated the landings per year using a particular fishing gear (gillnet or hooks). Second, we calculated the CPUE (per species, year and fishing gear): shark species biomass per 100 m per year and shark species biomass per 100 hooks per year. Finally, we obtain an average CPUE for the years between 2002 and 2007.\"In the result section we included:“The average CPUE (2002-2007) for the blue shark, shortfin mako and common thresher shark caught with longline were: 1.18 (SD±0.57), 0.69 (SD±0.07) and 0.07 (SD±0.04) kg of sharks, respectively, per 100 hooks per year. Furthermore, for the smooth hammerhead, smooth-hound shark, common thresher shark, and angel shark caught with gillnets were: 0.37 (SD±0.38), 0.11 (SD±0.04), 0.08 (SD±0.05) and 0.006 (SD±0.004) kg of sharks, respectively, per 100 m per year.”In the Discussion section we included:“We were able to find some values of fishing effort; but there were mainly scarce. According to Elliot et al. (1995, 1996, 1997a, 1997b), the CPUE in the longline shark fishery (number of individuals) in northern and central (120-250 miles off shore) Peru were: 7, 6.6, 4.5, 2.5 sharks per 100 hooks for the years 1995, 1996 and 1997a and 1997b, respectively. The CPUE (number of individuals/ biomass per 100 hooks) by species were: the blue shark (5, 4.7, 2 and 1.8 individuals/ 123.4, 40.4, 131.6, 58.2 kg), shortfin mako shark (1.8 and 0.4 individuals/ 61.6 and 7.6 kg), smooth hammerhead shark (1.06 and 0.16 individuals/ 8.9 and 17.7 kg), thresher shark (0.13 and 0.02 individuals / 8.5 and 1 kg) and copper shark (0.04, 0.4 and 1.1 individuals/ 48.3, 15.1 and 1.1 kg) for the years 1995, 1996 and 1997a and 1997b, respectively. Another study determine the CPUE for the Peruvian small-scale longline fishery in southern Peru. The CPUE mean and standard deviation was 33.6 (SD± 10.9) sharks per 1000 (for the shark season) and 1.9 ± 3.1 sharks per 1000 hooks (for the dolphinfish season). Of these, 70.6% were blue sharks, 28.4% shortfin mako sharks, and 1% were other species (including thresher, hammerhead, porbeagle, and other Carcharhinidae species (Doherty et al. 2014). If we compared the values of Elliot et al. (1995, 1996, 1997a, 1997b) with the values obtained in this study (for the species caught in longline: blue shark, shortfin mako shark, and thresher shark), the CPUE has declined that might suggest a reduction in Peruvian shark population. Nevertheless, our estimates are an extrapolation that uses Peruvian shark total landings which might be underestimated or incorrectly assumed; therefore further studies should calculate a more accurate and reliable CPUE.\"Furthermore, it seems there could have been more discussion on how the coverage and consistency of the landings data changed over the 61 years of the study period, and when species-specific recording practices were implemented for each of the main shark species examined. We have included a short paragraph in the Discussion section (subsection: Gaps of information and recommendations) discussing how the coverage, consistency of the landing data has change and how is currently reported by the government (i.e. Instituto del Mar del Peru and Vice-Ministry of Fisheries). Given that only landings data were used, and as explained above biases are largely unknown, the complexity of the analysis is probably unwarranted. It is not made clear why trends were analyzed as 10-year intervals and why this is considered appropriate. Fitting a linear model to a noisy time series is not an appropriate means of determining a trend. Even if the fit is statistically significant, the slopes and correlation coefficients are often very small and this does not support a conclusion that a meaningful trend is present. It is noted that only half of the twelve species/time intervals analyzed had statistically significant slopes, though all are presented and discussed.We agree with the Reviewer that the data is noisy and biases are largely unknown. However, in order to discuss the behavior of shark landings over 61 years, we needed it an analytical approach that could be applied to all the time series equally. For this, we established a 10-year interval as fixed window to analyze the trend of shark landings to reduce the noise signal as much as possible. Larger intervals did not provide any insight, but it is clear by looking at Figure 1 that landings exhibited a trend over time period of time analyzed. Having said so, we are open to suggestions of better analytical approaches considered the data we have.The low values for the slope and correlation coefficients were observed when investigating the influence of El Nino Southern Oscillation on shark landings. For this, we used monthly landings and compared it to Multivariate ENSO Index (MEI). The findings regarding the proportion of Peru's landings of chondrichthyans in the Pacific from 1950-2010 should be checked. Using the FAO FISHSTAT database, my calculations show that Peru's highest proportion (17%, not 80% as suggested by Figure 1) occurred in 1984 and over the 60-year time period it averaged 6%. Of course, the figures from other countries are also subject to the time-dependent biases in fishing effort and reporting systems as mentioned for Peru above. Therefore, this comparison should be heavily caveated. We have doubled checked our numbers and are correct. It seems we were not clear enough. The 80% record contribution of Peru to Pacific landings in 1984 is limited to sharks and not all chondrichthyans. The Figure 1 mentions this. The numbers estimated by the Reviewer are correct as well if all chondrichthyans (sharks, rays and skates) are included.With regard to the discussion of trade, it would have been better to present annual values (perhaps in a table) rather than aggregated amounts for 1997-2012. The important point about Peru having picked up the trade in shark fins when Ecuador banned this trade in 2008 should have been illustrated in a table or figure. I wonder if the authors were able to explore how much of the Peruvian imports during this period were from fishing vessels choosing to land shark products in Peru versus from traders re-routing their consignments through Peru. We have presented in a table (per year) the import and export of Peruvian shark products. What role do foreign fishing vessels play in Peruvian shark landings and has this changed over time? Hard to tell on how the data is reported.It would also have been interesting to hear about the trade in skate and ray wings, and whether this follows similar patterns as shark fins or is primarily for the domestic market. We don’t have that data as is not reported as such.In terms of management, the authors should be clear in recommending whether a maximum size or a minimum size is a better strategy--the discussion seems to make points on both sides of this argument. Also, what is the status of implementation and enforcement in Peruvian fisheries? Finally, since the authors claim that shark finning is not practiced because sharks are utilized for their meat, it is not clear why a shark finning ban is recommended as a management priority. It seems under current circumstances in Peru that recommending catch limits might be a more effective way of controlling shark mortality within sustainable limits. In the discussion section we included:\"The regulation of the minimum capture length leaves open and unregulated the fishery for the adults which is detrimental for the population. The protection and management of a shark breeding area does not guarantee that the population is healthy in the absence of a lack of management for other size classes (Kinney et al., 2009). Demographic models and experiences in the shark fishery management indicate that focusing the management on adult would be more beneficial for the total population (Musick et al., 1999; Brewster-Geisz et al., 2000; Cortés et al., 2002; Gallucci et al., 2006). For example, over 30 years the management of Galeorhinus galeus fishery in South Australia was oriented toward protecting their breeding areas. However, populations declined until the fishery collapse. This was because the adults were fish unsustainably during those 30 years (Kinney et al., 2009). Taking this as experience, the Mustelus antarcticus fishery in southeast of Australia focused their effort on a single class, youth, resulting in a sustainable fishery (Prince et al., 1992). This way, the minimum capture length regulation should be reevaluated.Third, the regulation is not implemented and enforced; foremost many of the fishermen are unaware of it. The minimum capture length for the mako shark is set at 170 cm but IMARPE reports that 60.1% (year 2009) and 88.5% (2010) of mako landings in the port of Pucusana were under minimum legal size (Anuario CientíficoTecnológico Vol. 5–10, 2005–2010). Of the 41 fishermen interviewed (in the landing points of Paita, Salaverry and Ilo), 93% do not discard any shark once it is hooked, only 34% reported that they discard sharks below 40-60 cm, and only 4.8% were aware of the regulations (Mangel et al., 2007).\""
}
]
},
{
"id": "6465",
"date": "11 Dec 2014",
"name": "Alastair Harry",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis manuscript synthesises, reviews and analyses information on shark landings, fishery characteristics, fisheries management and trade in Peru. Production by shark fisheries in Peru has evidently been and continues to be substantial, and there is clearly a need for work such as this that brings together information and identifies knowledge gaps. The manuscript is interesting, well-researched and includes broad-scale and species-specific data from a range of sources including unpublished and government reports. It is a useful addition to the literature provides a good starting point for further research.Although generally well-organised and structured, in parts the manuscript itself reads more like a report. More critical interpretation of the data is required and careful consideration should be given to the information that is presented. Quantitative analyses are carried out to identify statistically significant trends in the landings data and these seem fairly arbitrary and uninformative. A more useful approach would be to spend more time researching what the historical factors causing these trends are (e.g. economic, market, policy, reporting) and explaining them qualitatively. The correlation of catch with ENSO interesting but quite exploratory and I didn’t really see how it fits in with the aims of the manuscript.A major limitation of the manuscript is a lack of any measure of fishing effort. In the discussion there is some mention of the total lengths of gillnets used and number of fishing vessels suggesting some information may be available. Even gross statistics such as these could be instructive for understanding trends in the landings data and may be worth presenting.Also, perhaps I didn’t read carefully enough, but one thing that still wasn’t clear to me after reading is exactly what the ‘Peruvian shark fishery’ is in the context of the manuscript. Are pelagic species such as blue shark and mako taken as bycatch in pelagic fisheries for tuna/swordfish etc, or are they specifically targeted? Likewise, are Mustelus and Squatina species bycatch in groundfish fisheries, or are they targeted? My interpretation was that the manuscript was describing all records of shark landings from any ‘fishery’ in Peruvian waters, but maybe I have misinterpreted this completely.I feel there could be more detailed discussion of the legal framework. In addition to the ‘RM’ fisheries legislation, are there any other higher-level pieces of environmental legislation that provide any legal protection for sharks? References are made to a spatial closure for angel sharks. Is this in Peru, and are there any other marine parks in Peruvian waters? Are there other management measures (e.g. limited entry) that may have direct/indirect effects on shark landings?",
"responses": [
{
"c_id": "1845",
"date": "12 Apr 2016",
"name": "Ximena Velez-Zuazo",
"role": "Author Response",
"response": "Although generally well-organized and structured, in parts the manuscript itself reads more like a report. More critical interpretation of the data is required and careful consideration should be given to the information that is presented. Quantitative analyses are carried out to identify statistically significant trends in the landings data and these seem fairly arbitrary and uninformative. A more useful approach would be to spend more time researching what the historical factors causing these trends are (e.g. economic, market, policy, reporting) and explaining them qualitatively. In the Discussion section we included:“The increase in shark landings between 1950 and 1975 might have several historical factors. Since 1940 the Peruvian population has mainly migrated to the coast. By 1940, 28.3% of the Peruvian population lived in the coast; while by 1972, 46.1% of the population lived near the coast (OIM, 2015). Therefore, the economically active population of the fishery sector have grown from 1435 in 1940 to 66062 in 1994 (INEI). This coastal migration might have motivated an increase in the consumption and demand of sea food which might have triggered the fishery. Another factor might have been the industrialization of the Peruvian fishery which begun in 1950. This was driven by the fishery of anchovy (Engraulis ringens). Therefore, these factors might have motivated the expansion in size, capacity and power of Peruvian small-scale shark fishery: 32.6m3 GRT, up to 15m, motorized and voyage trips for up to 2 weeks.” The correlation of catch with ENSO interesting but quite exploratory and I didn’t really see how it fits in with the aims of the manuscript.We explain that the ENSO might have influenced the fishery trends.A major limitation of the manuscript is a lack of any measure of fishing effort. In the discussion there is some mention of the total lengths of gillnets used and number of fishing vessels suggesting some information may be available. Even gross statistics such as these could be instructive for understanding trends in the landings data and may be worth presenting.In the Methods section we included:“We estimated the average catch per unit effort (CPUE) for the most landed shark species between 2002 and 2007. According to Alfaro-Shigueto et al. (2010), the fishing effort of the small scale fishery that uses gillnets is 100 000 km of nets per annum and for the longline the effort is 80 million hooks set per annum. We extrapolated these numbers to the Peruvian small-scale shark fishery so we can obtain an estimated CPUE. First for each of the most landed species, we calculated the landings per year using a particular fishing gear (gillnet or hooks). Second, we calculated the CPUE (per species, year and fishing gear): shark species biomass per 100 m per year and shark species biomass per 100 hooks per year. Finally, we obtain an average CPUE for the years between 2002 and 2007.\"In the result section we included:“The average CPUE (2002-2007) for the blue shark, shortfin mako and common thresher shark caught with longline were: 1.18 (SD±0.57), 0.69 (SD±0.07) and 0.07 (SD±0.04) kg of sharks, respectively, per 100 hooks per year. Furthermore, for the smooth hammerhead, smooth-hound shark, common thresher shark, and angel shark caught with gillnets were: 0.37 (SD±0.38), 0.11 (SD±0.04), 0.08 (SD±0.05) and 0.006 (SD±0.004) kg of sharks, respectively, per 100 m per year.”In the Discussion section we included:“We were able to find some values of fishing effort; but there were mainly scarce. According to Elliot et al. (1995, 1996, 1997a, 1997b), the CPUE in the longline shark fishery (number of individuals) in northern and central (120-250 miles off shore) Peru were: 7, 6.6, 4.5, 2.5 sharks per 100 hooks for the years 1995, 1996 and 1997a and 1997b, respectively. The CPUE (number of individuals/ biomass per 100 hooks) by species were: the blue shark (5, 4.7, 2 and 1.8 individuals/ 123.4, 40.4, 131.6, 58.2 kg), shortfin mako shark (1.8 and 0.4 individuals/ 61.6 and 7.6 kg), smooth hammerhead shark (1.06 and 0.16 individuals/ 8.9 and 17.7 kg), thresher shark (0.13 and 0.02 individuals / 8.5 and 1 kg) and copper shark (0.04, 0.4 and 1.1 individuals/ 48.3, 15.1 and 1.1 kg) for the years 1995, 1996 and 1997a and 1997b, respectively. Another study determine the CPUE for the Peruvian small-scale longline fishery in southern Peru. The CPUE mean and standard deviation was 33.6 (SD± 10.9) sharks per 1000 (for the shark season) and 1.9 ± 3.1 sharks per 1000 hooks (for the dolphinfish season). Of these, 70.6% were blue sharks, 28.4% shortfin mako sharks, and 1% were other species (including thresher, hammerhead, porbeagle, and other Carcharhinidae species. If we compared the values of Elliot et al. (1995, 1996, 1997a, 1997b) with the values obtained in this study (for the species caught in longline: blue shark, shortfin mako shark, and thresher shark), the CPUE has declined that might suggest a reduction in Peruvian shark population. Nevertheless, our estimates are an extrapolation that uses Peruvian shark total landings which might be underestimated or incorrectly assumed; therefore further studies should calculate a more accurate and reliable CPUE.” If we compared these values with the values obtained on this study (for the species caught in longline: blue shark, shortfin mako shark, and thresher shark), the CPUE has declined that might suggest a reduction in Peruvian shark population. Nevertheless, more detailed and precise studies are needed in order to corroborate these estimates.” Extrapolated, over assumptions. Currently the fleet has changed. Also, perhaps I didn’t read carefully enough, but one thing that still wasn’t clear to me after reading is exactly what the ‘Peruvian shark fishery’ is in the context of the manuscript. Are pelagic species such as blue shark and mako taken as bycatch in pelagic fisheries for tuna/swordfish etc, or are they specifically targeted? Likewise, are Mustelus and Squatina species bycatch in groundfish fisheries, or are they targeted? My interpretation was that the manuscript was describing all records of shark landings from any ‘fishery’ in Peruvian waters, but maybe I have misinterpreted this completely.In the Introduction section we specified that the “Peruvian shark fishery” is Peruvian small-scale shark fishery (PSSSF). In the Methods section we defined small-scale fishery:\"According to the Peruvian fisheries regulations, the small-scale fisheries (SSF) are defined as containing boats with a maximum of 32.6m3 Gross Registered Tonnage (GRT), up to 15m of length and operating predominantly using manual work (El Peruano, 2001). The PSSSF includes not only target and bycatch species but also oceanic and coastal species. Nevertheless, most species caught by the PSSF are landed and commercialized. The reports of the Peruvian small-scale shark fishery is composed of target shark species but in some cases sharks are not the main target. For example, in Tumbes- northern Peru- the pelagic coastal fishery mainly targets Pacific harvestfish (Peprilus medius) but neonates and juvenile hammerhead sharks are frequently caught; and for the benthic coastal fishery the main target is hake (Merluccius gayi peruanus) but humpback smoothhounds (Mustelus whitneyi) are caught. Nevertheless, sharks are not discarded; they are landed, commercialized and consumed.The only PSSSF that reports shark bycatch is the Peruvian fishery of Patagonian toothfish (Dissostichus eleginoides) where the Pacific sleeper shark (Somniosus pacificus) is a bycatch (Bustamante, 1997 ).”I feel there could be more detailed discussion of the legal framework. In addition to the ‘RM’ fisheries legislation, are there any other higher-level pieces of environmental legislation that provide any legal protection for sharks? References are made to a spatial closure for angel sharks. Is this in Peru, and are there any other marine parks in Peruvian waters? Are there other management measures (e.g. limited entry) that may have direct/indirect effects on shark landings? In the results section (Conservation status and legal framework) we included:\"According to the Peruvian government, none of the shark species in Peruvian waters are categorized as threatened; therefore they are not legally protected and its capture, transport and exportation is authorized (El Peruano, 2014). According to RM 236-2001-PE, the Peruvian government regulates the integrated management and rational exploitation of highly migratory species. IMARPE establishes that the following shark species are categorized as highly migratory: silky shark (Carcharhinus falciformis), Galapagos shark (Carcharhinus galapagensis), blacktip shark (Carcharhinus limbatus), oceanic whitetip shark (Carcharhinus longimanus), shortfin mako (Isurus oxyrinchus), blue shark (Prionace glauca), smooth hammerhead shark (Sphyrna zygaena), Galapagos bullhead shark (Heterodontus quoyi), thresher shark (Alopias vulpinus) and tope shark (Galeorhinus galeus) (DE-100-034-2002-IMP/PE). According to the DS 032-2003-PRODUCE, the fishery of tunas and related species (highly migratory shark species, DE-100-034-2002-IMP/PE) should be sustainable through the implementation of measures for their management and conservation. Moreover, Peru is a member of the Inter-American Tropical Tuna Commission (IATTC). The IATTC urges its member states to cooperate through regional fisheries management organizations, in order to ensure the sustainability of shark populations and to adopt a National Plan of Action for the conservation and management of sharks. Also, the IATTC disallows the retention, landing and sell of the oceanic whitetip shark (Carcharhinus longimanus). According to the RM 236-2001-PE, the Peruvian government promotes the integral development of the Patagonian toothfish (Dissostichus eleginoides) fishery and its accompanying fauna (Pacific sleeper shark, Somniosus pacificus) which enables a sustainable fishery. Moreover, the accompanying fauna should be retained and not discarded. In Peru there are two marine protected areas: Paracas and Sistem of Islands, Islets and Capes. Sustainable fishery is permitted in these areas; nevertheless, it is not frequently enforced. Currently, the presence and distribution of sharks in these areas is unknown.\""
}
]
}
] | 1
|
https://f1000research.com/articles/3-164
|
https://f1000research.com/articles/5-641/v1
|
11 Apr 16
|
{
"type": "Research Article",
"title": "Fasting blood glucose and newborn birth weight of non- diabetic Sudanese women",
"authors": [
"Abdelmageed Elmugabil",
"Duria A. Rayis",
"Ishag Adam",
"Mohamed F. Lutfi",
"Abdelmageed Elmugabil",
"Duria A. Rayis",
"Mohamed F. Lutfi"
],
"abstract": "Background Although risk factors for abnormal birth weight has been extensively investigated, whether the physiological range of glucose tolerance affects birth weight in non-diabetic mothers needs to be verified by further research. Objectives To assess the effect of maternal sociodemographic characteristics, obstetric and anthropometric measurements, fasting and 2-hour blood glucose levels on birth weight. Methods\nOne hundred and thirty four women were followed from early pregnancy until delivery at Saad Abualila Hospital, Khartoum, Sudan. Fasting and 2-hour glucose levels following administration of 75 g oral glucose was performed in the third trimester. Association between birth weight and maternal sociodemographic characteristics, obstetric and anthropometric measurements, haemoglobin, fasting and 2-hour blood glucose levels were assessed by linear regression analysis. Results The mean (SD) birth weight was 3127.7 (480.0) g, while the 10th and 90th centile were 2500 and 3800 g, respectively. There was no significant difference in the birth weight between male (n=73) and female (n=61) newborns [3167.8 (545.0) vs 3068.9 (384.0) g, P= 0.196]. Likewise there was no significant difference in the birth weight of newborns born to primipara and multipara mothers [3101.7 (529.0) g vs 3151.4 (432.0) g, P= 0.551]. Linear regression analysis demonstrated significant association between fasting blood glucose and birth weight (20 g, P = 0.028). None of the other maternal/fetal characteristics was associated with birth weight, including maternal age, body mass index, gravidity, weight gain during pregnancy, interpregnancy interval, history of miscarriage, haemoglobin level, blood pressure, fetal gender and gestational age. Conclusion In this study fasting blood glucose was found to be predictor of birth weight among neonates of non-diabetic Sudanese mothers.",
"keywords": [
"birth weight",
"fasting blood glucose",
"non- diabetic",
"Sudan"
],
"content": "Introduction\n\nAbnormal birth weight constitutes a major risk factor for a wide spectrum of childhood morbidities1. Low birth weight is more prevalent in developing compared with developed countries2,3. It is commonly associated with several maternal sociodemographic, nutritive, medical and obstetrical risk factors4 including poor socioeconomic status5, inadequate antenatal care6, short interpregnancy interval7, history of miscarriage8, preterm labour9, low pre-pregnancy weight10,11 or weight gain during pregnancy12, anaemia13, hypoglycaemia14, hypertension15 and certain infectious diseases during pregnancy16,17. Alternatively, gestational diabetes and past history of fetal macrosomia are the major predictors of high birth weight18.\n\nPrevious reports showed accumulating evidence for chronic maternal hypoglycaemia14 and hyperglycaemia18 as important risk factors for low and high birth weight respectively. Accordingly, the effect of glycaemic control on birth weight seems to extend into the physiological range of glucose tolerance. However, the scientific evidence for this hypothesis remains to be verified by further research. For further exploration of this hypothesis we designed this study to assess the association between glycaemic control and birth weight in non-diabetic Sudanese women. In addition, the influences of maternal sociodemographic characteristics, obstetric history and anthropometric measurements on birth weight were assessed. Scarcity of Sudanese studies on the scope of the present objectives gives this study exceptional importance, especially if we consider the extensive research exploring risk factors of abnormal birth weight worldwide.\n\n\nMethods\n\nA longitudinal study was conducted at Saad Abualila Hospital (Khartoum, Sudan) during the period of January–October 2014. Saad Abualila Hospital is a tertiary semi-private hospital governed by the Faculty of Medicine, University of Khartoum. After giving informed consent, eligible women were enrolled in the study in their first trimester or during the first antenatal visit. Inclusion criteria were: early, singleton pregnancy and willingness to participate in the study. Women with diabetes mellitus, hypertension or any other chronic disease were excluded from the study. A questionnaire was used to gather data from each pregnant women on her age, parity, educational level (illiterate, primary school education or secondary school and above education), occupation (housewife or working mother), gestational age calculated in weeks. Weight and height were determined, and body mass index (BMI) was calculated and expressed as weight in kilograms divided by the square of height in meters. The gestational age was calculated from the last menstrual period and confirmed by early ultrasound. The participants were followed up in the antenatal clinic until delivery; on every visit their weight was recorded and the weight gained during pregnancy was calculated from maximum weight gained and the weight during the first visit. Iron plus folic acid (60 mg iron + 400 μg folic) were prescribed to the women. In the third trimester a 75 gm glucose tolerance test was performed and haemoglobin A1C was evaluated for all the participants.\n\nFasting and 2-hour glucose were measured from venous blood with a colorimetric method. The World Health Organization (WHO) 1999 criteria (fasting plasma glucose ≥ 7.0 mmol/L or 2-hour postprandial glucose ≥ 7.8 mmol/L) was used to diagnose diabetes19.\n\nThe newborns were weighed immediately following birth to the nearest 10 g on a Salter scale, which was checked for accuracy on a weekly basis. The gender of each newborn was recorded.\n\nA total sample size of 130 participants was calculated to investigate the factors influencing normal birth weight (2500–4000g). In order to investigate low birth weight and macrosomia, a much larger sample size is needed. A formula was used to calculate the mean of the proposed variables (birth weight) that would provide 80% power to detect a 5% difference at α = 0.05, with an assumption that complete data might not be available for 12% of participants.\n\n\nStatistics\n\nSPSS for Windows (version 16.0) was used for data analyses. Studied variables were described with means (M) and standard deviations (SD). Proportions of the studied groups were expressed in percentages (%). The difference of mean (SD) of the birth weight was compared between two groups using a T-test. Linear regression analyses were performed where birth weight was the dependent variable and socio-demographic parameters (age, parity, job, and residence), hemoglobin, blood glucose and hemoglobin A1C levels, interpregnancy interval, gestational age, birth weight, maternal BMI and weight gain were the independent variables. P < 0.05 was considered statistically significant.\n\n\nEthics\n\nThe study received ethical clearance from the Research Board at the Department of Obstetrics and Gynaecology, Faculty of Medicine, University of Khartoum, Sudan.\n\n\nResults\n\nOut of 178 pregnant women who were enrolled initially, 7 and 5 had diabetes and hypertension, respectively and were excluded. There were 32 (18.0%) participants lost during follow-up due to address change. The remaining 134 (75.2%) women completed the follow-up till the delivery and their data were included during statistical analysis.\n\nAround half of these women were primipara (64.0, 47.8%), the majority were housewives (101, 75.4%) and few of them of rural residence (14, 10.4%). Thirty three (24.6%) and four (3.0 %) of the studied women (n = 134) had history of miscarriage and stillbirth, respectively. The basic characteristics of the participants are shown in Table 1.\n\nThe birth weight range was 1650–4500 g and the mean (SD) was 3127.7(480.0) g, while the 10th and 90th centile was 2500 and 3800 g, respectively. Six (4.5%) and five (3.7%) newborns were small for gestational (SGA) age and larger for gestational age (LGA), respectively.\n\nThere was no significant difference in the birth weight between male (n=73, 3167.8 (545.0) g) and female (n=61, 3068.9 (384.0) g, P= 0.196] newborns. Likewise there was no significant difference in the birth weight of newborns born to primipara and multipara mothers [3101.7 (529.0) g vs 3151.4 (432.0) g, P= 0.551].\n\nIn linear regression, only the fasting blood glucose was significantly associated with birth weight (20 g, P = 0.028; Table 2).\n\n• corrected for fasting blood glucose\n\n\nDiscussion\n\nIt is evident from the present results that maternal fasting blood glucose level was associated with birth weight among newborns of non-diabetic mothers we studied. According to the current data, maternal fasting blood glucose level had the highest influence on birth weight compared with maternal sociodemographic characteristics, obstetric history and anthropometric measurements. Previous reports exploring the influences of glucose homeostasis on birth weight were mostly based on newborns of diabetic mothers18,20. However, there is evidence that the association of chronic hyperglycemia and macrosomia extends into the physiological range of glucose tolerance21–24. There is considerable debate on the ideal approach for biochemical diagnosis of gestational diabetes25. Likewise, the studies that documented the association between hyperglycemia and high birth weight were unable to provide a clear cutoff for the glucose level above which the risk of macrosomia increased26. In a prospective study, the results of 75 g oral glucose tolerance tests at the 17th and 32nd week of gestation were compared in non-diabetic women attending one antenatal out-patient care unit21. Although the studied women did not fulfil the diagnostic criteria of gestational diabetes mellitus, the mean + 2 standard deviations of glucose level after 2 hour of 75 g oral glucose was 8.0 mmol/l (144 mg/dl) at 32nd week. The significantly impaired glucose level at the 32nd week compared with the 17th week of gestation led the authors to recommend revision of the cut-off values used for diagnosis of gestational diabetes mellitus. The study also demonstrated association between maternal glucose level and weight gain > 18 kg during pregnancy, macrosomia, prematurity and other maternal/fetal complications. Another study assessing the relationship between birth weight and maternal glycemic control during normal pregnancy was able to confirm maternal weight (before pregnancy and at term), gestational age, parity, and newborn gender as significant independent predictors of birth weight22. According to the same study, fasting blood glucose level was positively associated with birth weight independent of the other sociodemographic and obstetric characteristics of the studied mothers. This implication was further supported by Langhoff-Roos et al. who attribute 27% of the variation in newborn birth weight to maternal fasting blood glucose and lean body mass23. Other reports also demonstrated that even within normal range variations of maternal glucose homeostasis can affect growth and development of the fetus24.\n\nHoegsberg et al. found no difference in glucose tolerance between mothers of macrosomic and normal infants, though macrosomic infants had significantly higher insulin levels than the control infants27. A possible explanation for macrosomia in such conditions may be fetal pancreatic beta-cell hypersensitivity to subtle hyperglycemia and subsequent fetal hyperinsulinemia28. Alternatively, an inverse relationship between birth weight and maternal insulin level was demonstrated when 134 normotensive, non-obese, non-diabetic mothers were studied at the 27th week of gestation22. The same study confirmed an inverse relationship between insulin/glucose ratio and birth weight; however, glucose levels were comparable in all quintiles of insulin/glucose ratio. In addition, birth weight was significantly decreased in the upper insulin/glucose quintile when compared to the other quintiles. The study concluded that maternal insulin level was associated with birth weight independently of the state of the maternal glycemic control.\n\nIt is worth mentioning that previous studies reported significant influences of maternal age29, gravidity30, work31, interpregnancy interval7, history of miscarriage32, hemoglobin level13, blood pressure15, BMI10,11, weight gain during pregnancy12, fetal gender33 and gestational age34 on fetal growth; however, none of these parameters were associated with birth weight in the present study.\n\nLimitations of this study include lack of insulin measurements among the pregnant women we studied. Combined evaluation of fasting insulin and glucose concentrations is likely to offer better background on insulin resistance among the studied mothers35. Moreover, it will enable more clarification whether hyperinsulinemia or hyperglycemia has more influence on newborn birth weight22.\n\n\nConclusion\n\nThe present results add a strong evidence for the important role of fasting blood glucose as an indicator of glycemic control in prediction of birth weight among neonates of non-diabetic mothers. According to the current data, maternal fasting blood glucose level had the highest influence on birth weight compared with maternal obstetric history, anthropometric measurements and sociodemographic characteristics.\n\n\nConsent\n\nWritten informed consent for publication of their clinical details was obtained from the patients.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw dataset for Elmugabil et al., 2016 ‘Fasting blood glucose and birth weight in non-diabetic Sudanese women', 10.5256/f1000research.8416.d11822535",
"appendix": "Author contributions\n\n\n\nAE and IA coordinated and carried out the study. DAR and MFL participated in the statistical analysis. AE and DAR participated in the clinical work. All the authors have read and approved the final version of this manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no funding was involved in supporting this work.\n\n\nReferences\n\nFeresu SA, Harlow SD, Woelk GB: Risk Factors for Low Birthweight in Zimbabwean Women: A Secondary Data Analysis. Thorne C, ed. PLoS One. 2015; 10(6): e0129705. PubMed Abstract | Publisher Full Text | Free Full Text\n\nIslam MM: Increasing Incidence of Infants with Low Birth Weight in Oman. Sultan Qaboos Univ Med J. 2015; 15(2): e177–e183. PubMed Abstract | Free Full Text\n\nChen Y, Li G, Ruan Y, et al.: An epidemiological survey on low birth weight infants in China and analysis of outcomes of full-term low birth weight infants. BMC Pregnancy Childbirth. 2013; 13: 242. PubMed Abstract | Publisher Full Text | Free Full Text\n\nValero De Bernabé J, Soriano T, Albaladejo R, et al.: Risk factors for low birth weight: a review. Eur J Obstet Gynecol Reprod Biol. 2004; 116(1): 3–15. PubMed Abstract | Publisher Full Text\n\nKader M, Perera NK: Socio-economic and nutritional determinants of low birth weight in India. N Am J Med Sci. 2014; 6(7): 302–308. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMumbare SS, Maindarkar G, Darade R, et al.: Maternal risk factors associated with term low birth weight neonates: a matched-pair case control study. Indian Pediatr. 2012; 49(1): 25–8. PubMed Abstract | Publisher Full Text\n\nZhu BP: Effect of interpregnancy interval on birth outcomes: findings from three recent US studies. Int J Gynaecol Obstet. 2005; 89(Suppl 1): S25–33. PubMed Abstract | Publisher Full Text\n\nPoorolajal J, Cheraghi P, Cheraghi Z, et al.: Predictors of miscarriage: a matched case-control study. Epidemiol Health. 2014; 36: e2014031. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGulati S, Andrews CA, Apkarian AO, et al.: Effect of gestational age and birth weight on the risk of strabismus among premature infants. JAMA Pediatr. 2014; 168(9): 850–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAdam I, Babiker S, Mohmmed AA, et al.: Low body mass index, anaemia and poor perinatal outcome in a rural hospital in eastern Sudan. J Trop Pediatr. 2008; 54(3): 202–4. PubMed Abstract | Publisher Full Text\n\nElhassan EM, Abbaker AO, Haggaz AD, et al.: Anaemia and low birth weight in Medani, Hospital Sudan. BMC Res Notes. 2010; 3: 181. PubMed Abstract | Publisher Full Text | Free Full Text\n\nShrestha I, Sunuwar L, Bhandary S, et al.: Correlation between gestational weight gain and birth weight of the infants. Nepal Med Coll J. 2010; 12(2): 106–9. PubMed Abstract\n\nHaggaz AD, Radi EA, Adam I: Anaemia and low birthweight in western Sudan. Trans R Soc Trop Med Hyg. 2010; 104(3): 234–6. PubMed Abstract | Publisher Full Text\n\nVadakekut ES, McCoy SJ, Payton ME: Association of maternal hypoglycemia with low birth weight and low placental weight: a retrospective investigation. J Am Osteopath Assoc. 2011; 111(3): 148–52. PubMed Abstract\n\nAli AA, Rayis DA, Abdallah TM, et al.: Severe anaemia is associated with a higher risk for preeclampsia and poor perinatal outcomes in Kassala hospital, eastern Sudan. BMC Res Notes. 2011; 4: 311. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBatran SE, Salih MM, Elhassan EM, et al.: CD20, CD3, placental malaria infections and low birth weight in an area of unstable malaria transmission in Central Sudan. Diagn Pathol. 2013; 8: 189. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMohammed AH, Salih MM, Elhassan EM, et al.: Submicroscopic Plasmodium falciparum malaria and low birth weight in an area of unstable malaria transmission in Central Sudan. Malar J. 2013; 12: 172. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMohammadbeigi A, Farhadifar F, Soufi zadeh N, et al.: Fetal macrosomia: risk factors, maternal, and perinatal outcome. Ann Med Health Sci Res. 2013; 3(4): 546–550. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGabir MM, Hanson RL, Dabelea D, et al.: The 1997 American Diabetes Association and 1999 World Health Organization criteria for hyperglycemia in the diagnosis and prediction of diabetes. Diabetes Care. 2000; 23(8): 1108–1112. PubMed Abstract | Publisher Full Text\n\nYang YD, Zhai GR, Yang HX: [Factors relevant to newborn birth weight in pregnancy complicated with abnormal glucose metabolism]. Zhonghua Fu Chan Ke Za Zhi. 2010; 45(9): 646–51. PubMed Abstract\n\nAgardh CD, Aberg A, Nordén NE: Glucose levels and insulin secretion during a 75 g glucose challenge test in normal pregnancy. J Intern Med. 1996; 240(5): 303–9. PubMed Abstract | Publisher Full Text\n\nBreschi MC, Seghieri G, Bartolomei G, et al.: Relation of birthweight to maternal plasma glucose and insulin concentrations during normal pregnancy. Diabetologia. 1993; 36(12): 1315–21. PubMed Abstract | Publisher Full Text\n\nLanghoff-Roos J, Wibell L, Gebre-Medhin M, et al.: Maternal glucose metabolism and infant birth weight: a study in healthy pregnant women. Diabetes Res. 1988; 8(4): 165–70. PubMed Abstract\n\nFarmer G, Russell G, Hamilton-Nicol DR, et al.: The influence of maternal glucose metabolism on fetal growth, development and morbidity in 917 singleton pregnancies in nondiabetic women. Diabetologia. 1988; 31(3): 134–41. PubMed Abstract | Publisher Full Text\n\nAgarwal MM: Gestational diabetes mellitus: An update on the current international diagnostic criteria. World J Diabetes. 2015; 6(6): 782–791. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHartling L, Dryden DM, Guthrie A, et al.: Screening and diagnosing gestational diabetes mellitus. Evid Rep Technol Assess (Full Rep). 2012; (210): 1–327. PubMed Abstract | Free Full Text\n\nHoegsberg B, Gruppuso PA, Coustan DR: Hyperinsulinemia in macrosomic infants of nondiabetic mothers. Diabetes Care. 1993; 16(1): 32–6. PubMed Abstract | Publisher Full Text\n\nPinar H, Pinar T, Singer DB: Beta-cell hyperplasia in macrosomic infants and fetuses of nondiabetic mothers. Pediatr Dev Pathol. 2000; 3(1): 48–52. PubMed Abstract\n\nShmueli A, Cullen MR: Birth weight, maternal age and education: new observations from Connecticut and Virginia. Yale J Biol Med. 1999; 72(4): 245–258. PubMed Abstract | Free Full Text\n\nMuula AS, Siziya S, Rudatsikira E: Parity and maternal education are associated with low birth weight in Malawi. Afr Health Sci. 2011; 11(1): 65–71. PubMed Abstract | Free Full Text\n\nZhu JL, Hjollund NH, Olsen J, et al.: Shift work, duration of pregnancy, and birth weight: the National Birth Cohort in Denmark. Am J Obstet Gynecol. 2004; 191(1): 285–91. PubMed Abstract | Publisher Full Text\n\nPoorolajal J, Cheraghi P, Cheraghi Z, et al.: Predictors of miscarriage: a matched case-control study. Epidemiol Health. 2014; 36: e2014031. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVeiga-Lopez A, Kannan K, Liao C, et al.: Gender-Specific Effects on Gestational Length and Birth Weight by Early Pregnancy BPA Exposure. J Clin Endocrinol Metab. 2015; 100(11): E1394–403. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPreethi BL, Jaisri G, Kumar KM, et al.: Assessment of insulin resistance in normoglycemic young adults. Fiziol Cheloveka. 2011; 37(1): 118–25. PubMed Abstract\n\nElmugabil A, Rayis D, Adam I, et al.: Dataset 1 in: Fasting blood glucose and newborn birth weight of non-diabetic Sudanese women. F1000Research. 2016. Data Source"
}
|
[
{
"id": "14106",
"date": "27 Jun 2016",
"name": "Angela E Vinturache",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn the study “Fasting blood glucose and newborn birth weight of non- diabetic Sudanese women\" A. Elmugabil et al aimed to assess the relationship between maternal sociodemographic and obstetrics characteristics and blood glucose and birth weight. The authors report an association between fasting blood glucose and birth weight (BW) and no association between other variables and BW. There are several concerns with this study:\nThe title does not accurately reflect the objectives of the study\n\nThe objective of the study does not match the methodology; the study was designed to study an association and not causality/effects\n\nMethodology:\ni) Study designed: there are no information provided on survey data collection; not clear if the sample included both preterm and term pregnancies; what test was used for OGTT, if the test is validated, at what gestational age was the test done; how the correction for 2h blood glucose was done and what was the rationale behind this correction; the term “early” pregnancy and US should be defined;\nii) Statistical analysis is not sound as the authors used both continuous and categorical variables as independent variables in the linear regression analyses; GA is a confounder for the relationship between BMI, GWG and BW and should be controlled for.\n\nResults section do not report on how many women had normal or abnormal OGTT tests; it is not clear what GA was included in Table 1\n\nMost part of the comments from the Discussion section are tangential to the topic; the authors do not provide any explanation for their findings and the differences between their results and the data from literature.\n\nPart of the Conclusions of the study are incorrect.",
"responses": []
},
{
"id": "19645",
"date": "25 Jan 2017",
"name": "Tsi Njim",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nCongratulations to the authors for their efforts in pushing this through. Despite the small sample size, the work provides an insight into the complexities surrounding glycaemia and birth weight and hopefully provides the base for more research. It is context-specific to Sudan where much research on the issue is yet to be done.",
"responses": []
}
] | 1
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https://f1000research.com/articles/5-641
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https://f1000research.com/articles/5-155/v1
|
10 Feb 16
|
{
"type": "Research Article",
"title": "Alanylated lipoteichoic acid primer in Bacillus subtilis",
"authors": [
"Yu Luo"
],
"abstract": "Lipoteichoic acid is a major lipid-anchored polymer in Gram-positive bacteria such as Bacillus subtilis. This polymer typically consists of repeating phosphoglycerol or phosphoribitol units and therefore has a predominant negative charge. The repeating units are attached to a glycolipid anchor which has a diacylglycerol (DAG) moiety attached to a dihexopyranose head group. D-alanylation is known as the major modification of lipoteichoic acid, which partially neutralizes the polymer and plays important roles in bacterial survival and resistance to the host immune system. The biosynthesis pathways of the glycolipid anchor and lipoteichoic acid have been fully characterized. However, the exact mechanism of D-alanyl transfer from the cytosol to cell surface lipoteichoic acid remains unclear. Here I report the use of mass spectrometry in the identification of intermediate species in the biosynthesis and D-alanylation of lipoteichoic acid: the glycolipid anchor, nascent lipoteichoic acid primer with one phosphoglycerol unit, as well as mono- and di-alanylated forms of the lipoteichoic acid primer. Monitoring these species as well as the recently reported D-alanyl-phosphatidyl glycerol would aid in shedding light on the mechanism of the D-alanylation pathway of lipoteichoic acid.",
"keywords": [
"Host immune response",
"Gram-positive",
"Lipoteichoic acid",
"D-alanylation",
"Glycolipid D-alanyl-phosphatidylglycerol",
"Surface charge",
"Lipoteichoic acid primer",
"Mass spectrometry",
"Lipidomics"
],
"content": "Introduction\n\nPhospholipids are the dominant cell membrane component in most bacteria1 which render bacterial cell surface negatively charged. This feature makes bacterial membrane the easy target of host immune molecules such as cationic antibiotic peptides2–4. Bacteria have been known to constantly modulate membrane components1,5. There are at least three pathways which may contribute to surface charge modulation: biosynthesis of phosphatidylethanolamine (PE), L-lysyl-phosphatidylglycerol (lysyl-PG), and D-alanylation of lipo- and wall-teichoic acids. In comparison with Gram-negative bacteria, Gram-positive bacteria typically have noticeably less PE1, but have an abundance of lysyl-PG or other aminoacylated PGs which most Gram-negative bacteria lack5,6. Besides, lipo- and wall-teichoic acids are only found in Gram-positive bacteria.\n\nPeptidoglycan-attached wall-teichoic acids and glycolipid-anchored lipoteichoic acids were discovered six decades ago7. The biosynthesis pathways of the two types of teichoic acids have been characterized8–11. The most common modification of these two types of teichoic acids is D-alanine esterification7,9,12, which is known to be carried out by the four dlt operon-coded proteins DltABCD13. This surface charge modulation has been observed to significantly affect the antigenicity of the bacteria2. In the cytosol, DltA (~500 amino acid residues) catalyzes with the consumption of ATP first the adenylation of D-alanine and then the thioester formation with D-alanyl-carrier protein DltC (~80 amino acids)13–15. Crystal structures of DltA16,17 have proven that DltA is homologous to adenylation domains (also called AMP-forming domains) found in modular nonribosomal peptide synthetases18 as well as fatty acyl-coenzyme A synthetases19 and firefly luciferases20. The functionally uncharacterized DltB (~400 amino acid residues) appears to be an integral membrane protein with multiple putative transmembrane helices with a low level of similarity to a putative group of membrane-bound o-acyltransferases21. DltD (~400 amino acid residues), with a single putative N-terminal transmembrane helix and a large globular domain, has been reported to bind DltC and possibly catalyzes the final D-alanyl transfer from DltC to teichoic acid22. We have recently characterized the presence of D- but not L-alanine in lipid lysate from Bacillus subtilis, implying the presence of D-alanyl-PG in the bacterial membrane23. Observation of other D-alanylated species in the bacterial membrane would help sketching a transfer route for the D-alanyl group from inside the cytosol to teichoic acids on the outer surface. Here I report profiling of B. subtilis lipids and identification of mono- and di-alanylated derivatives of nascent lipoteichoic acid primer with a single phosphoglycerol unit attached to the glycolipid anchor (chemical structures shown in Figure 1).\n\nScissile bonds are labeled alphabetically in D. DAG – diacylglycerol; Pho – phosphate; Gro – glycerol; Glc – glucose; Ala – alanine. A. The glycolipid anchor of lipoteichoic acid: DAG-Glc-Glc. B. The lipoteichoic acid primer: DAG-Glc-Glc-Pho-Gro. C. Mono-alanylated lipoteichoic acid primer: DAG-Glc-Glc-Pho-Gro-Ala. D. Bis-alanylated lipoteichoic acid primer: DAG-Glc-Glc-Pho-Gro-(Ala)2.\n\n\nMaterials and methods\n\nBacterial strain and cell culture. The BL21 (DE3) strain of E. coli (Novagen) and B. subtilis strain 168 (Bacillus Genetic Stock Center) were first plated from freezer stock onto LB-agar media. A single colony was transferred into 100 ml of LB media. After incubation overnight at 37°C and 220 rpm in an environmental shaker, it was transferred to 1 liter of LB media. When the cell density reached ~1.0 at 600 nm, 200 ml cell culture supplemented with 2.0 ml of 1.0 M NaAc buffer at pH 4.6 was centrifuged at 5,500 rpm in a Beckman JLA-8.1 rotor for 16 minutes at 4°C. The wet cell pellet was used for lipid extraction.\n\nLipid extraction. HPLC-grade organic solvents (Fisher Scientific) and distilled and deionized water were used throughout the experiment. The lipid extraction procedure was following that of Bligh and Dyer24. Briefly, the wet cell pellet was re-suspended in a glass tube in 0.5 ml ice-chilled water and 2.0 ml of ice-chilled methanol. Then 1.0 ml of cold chloroform was added. The suspension was vortexed for 3 seconds every 5 minutes and incubated on ice for a duration of 10 minutes. After that, 2.0 ml cold chloroform was added followed by 1.5 ml of cold water. The tube was vortexed for 3 seconds and placed on a rocking platform at a room temperature of 21°C for 3 minutes. Phase separation was assisted by centrifugation at 1,300 rpm for 5 minutes with a Beckman Allegro X-22R centrifuge. The heavier chloroform-rich phase was transferred by a glass syringe to a second glass centrifuge tube. Another 2.0 ml cold chloroform was added to the first tube and vortexed for 3 seconds. Then the first tube was put back on the rocking platform at room temperature for 10 minutes. Centrifugation at 1,300 rpm for 5 minutes and transfer of the heavier chloroform-rich phase to the second glass tube followed. The combined chloroform-rich phase was mixed with 0.5 ml 0.5 M NaCl, vortexed for 3 seconds and gentle shaking by hand for 1 minute. After centrifugation at 1,300 rpm for 5 minutes, the chloroform-rich phase, 4.0–4.5 ml in volume, was collected in a third glass tube for storage at -80°C. Typically, the total lipid concentration was estimated as 0.5 mg/ml.\n\nLipid profiling by mass spectroscopy. The lipid samples were diluted by adding 2-fold volume of methanol to a concentration of ~0.15 mg/ml (or 150 ppm) for direct infusion at a rate of 0.6 ml/hour to a SCIEX 4000 QTRAP mass spectrometer. Electrospray ionization was achieved at a temperature of 500°C and a pressure of 20 psi for curtain gas as well as ion source gas 1 and 2. The collision energy in the ion trap was tested between 30 and 100 electronvolts for most efficient detection of target substructures in the lipids. The SCIEX Analyst 1.6 software was used to acquire and export averaged mass spectra with the 4000 QTRAP system. Agilent MassHunter B.06.00 was used to process mass spectra with an Agilent Q-TOF 6500 system. MS spectra in the figures were also analyzed with Mass++ 2.7.4 software25 and presented with Microsoft Excel.\n\nTandem mass spectroscopy. The targeted MS/MS spectra were first acquired using the SCIEX 4000 QTRAP system with multiple collision energy settings between 50 and 90 electronvolts. High-accuracy MS/MS spectra were acquired using the Agilent Q-TOF 6550 system with collision energy ranging from 30 to 80 electronvolts. Direct infusion was also employed but at a faster flow rate of 2.0 ml/hour for the Q-TOF 6550 system.\n\n\nResults\n\nPolar lipid extraction on ice produced more species in the sample - Ice-chilled solvents instead of room-temperature ones were used during the well-established polar lipid extraction procedure devised by Bligh and Dyer24. The new lipid preparations did not show marked differences on thin-layer chromatograms. However, their mass spectra showed noticeable difference with the cold extraction producing more species than room-temperature extraction. The alanylated derivatives of lipoteichoic acid primer were not observed in lipids extracted at room temperature.\n\nProfiling and tandem mass spectroscopy of polar lipids with dihexose head group - The sodiated form of the lipid anchor of lipoteichoic acid in B. subtilis has been identified by mass spectrometry previously26. Several mass spectrometric scans with the 4000 QTRAP system in search for the lipid anchor were experimented. The anchor has a common structure of DAG-dihexose, with the hexose being either glucose or galactose depending on the identity of the microbial organism27. The unbranched and typically glycerolphosphate polymer is attached to C-6 of the non-reducing hexopyranosyl end of the glycolipid anchor by a phosphodiester bond27. In B. subtilis, the head group is diglucose27 (Figure 1A). The sodiated dehydrated diglucose (342 – 18 + 23 = 347 amu) at a collision energy of +80 electronvolts revealed the two most intense peaks (887 and 915 amu) matching expected sizes of the lipid anchor with the two dominant fatty acyl compositions of (30:0) and (32:0), respectively26 (Figure 2A). Tandem mass spectra of the most abundant 915 amu species was then acquired with the SCIEX 4000 QTRAP system (Figure 2B) and the Agilent Q-TOF 6550 system (Table 1). The QTRAP system produced less noisy spectra which are shown in Figure 2–Figure 4. The m/z values obtained from the Q-TOF system were more accurate and are listed in Table 1–Table 4. The observed molecular mass 915.601 closely matched the calculated value of 915.603 for (32:0) [DAG-Glc-Glc + Na]+. All the observed fragment ions also had their m/z values within 0.002 amu of calculated monoisotopic masses. The molecular ion dissociated to form two most abundant fragments at 645 and 673 amu, corresponding to neutral loss of (17:0) fatty acid (270 amu) and (15:0) fatty acid (242 amu), respectively. The two fatty acids have been known as the dominant ones in B. subtilis lipids23. The 753 amu fragment ion corresponding to a neutral loss of a dehydrated glucose residue (162 amu) was less abundant than the twin peaks. Another set of twin peaks at 483 and 511 amu corresponded to neutral losses of the terminal glucose residue (162 amu) and either of the two fatty acids (270 and 242 amu respectively). The peak at 405 amu corresponded to the sodiated diglucose head group covalently linked with the didehydroxyl residue of glycerol CH2=CH-CH2-Glc-Glc (Table 1). The twin peaks at 365 and 347 amu corresponded to the sodiated diglucose head group and its dehydrated form, respectively. It is worth noting that the signature [DAG – OH]+ ion (551 amu) for glycerolphospholipids was missing. However, the two [MAG – OH]+ ions at 299 and 327 amu were observed at lower intensity. Even though the 405 amu ion was more intense than the 347 ion, lipid profiling by searching for precursors of the 405 amu cation was inferior to the precursor scan for the 347 amu cation.\n\nHorizontal axis denotes m/z values. Vertical axis denotes ion counts. DAG – diacylglycerol; Glc – glucose. A. Precursor scan for 347 amu sodiated diglucose dehydrate. B. MS/MS spectrum of sodiated (32:0) DAG-Glc-Glc (915 amu).\n\nHorizontal axis denotes m/z values. Vertical axis denotes ion counts. DAG – diacylglycerol; PG – phosphatidylglycerol; Pho – phosphate; Gro – glycerol; Glc – glucose; LTA – lipoteichoic aicd primer; CL – cardiolipin. A. Precursor scan for 153 amu cyclo-glycerolphosphate anion. B. MS/MS spectrum of lipoteichoic acid primer (30:0) DAG-Glc-Glc-Pho-Gro (1017 amu).\n\nHorizontal axis denotes m/z values. Vertical axis denotes ion counts. DAG – diacylglycerol; PG – phosphatidylglycerol; Pho – phosphate; Gro – glycerol; Glc – glucose; Ala – alanine; LTA – lipoteichoic aicd primer. A. Precursor scan for 88 amu [Ala-H]-. B. MS/MS spectrum of mono-alanylated (30:0) lipoteichoic acid primer DAG-Glc-Glc-Pho-Gro-Ala (1088 amu). C. MS/MS spectrum of dialanylated (30:0) lipoteichoic acid primer DAG-Glc-Glc-Pho-Gro-(Ala)2 (1159 amu).\n\nNote: The alphabetically labeled scissile bonds are shown in Figure 1D. Pho – phosphate; Gro – glycerol; MAG – monoacylglycerol; DAG – diacylglycerol; Glc – glucose. There are equivalent choices such as between a1 and a2, as well as between b1 and b2.\n\nNote: The alphabetically labeled scissile bonds are shown in Figure 1D. Pho – phosphate; Gro – glycerol; MAG – monoacylglycerol; DAG – diacylglycerol; Glc – glucose; LTA – lipoteichoic acid primer DAG-Glc2-Pho-Gro. Cleavage at a1 and a2, as well as at b1 and b2 produces fragments of identical sizes.\n\nNote: Pho – phosphate; Gro – glycerol; MAG – monoacylglycerol; DAG – diacylglycerol; Glc – glucose; Ala – alanine; LTA - LTA primer DAG-Glc2-Pho-Gro. Values in parentheses were observed only with the low-accuracy 4000 QTRAP system.\n\nNote: The alphabetically labeled scissile bonds are shown in Figure 1. Pho – phosphate; Gro – glycerol; MAG – monoacylglycerol; DAG – diacylglycerol; Glc – glucose; Ala – alanine; LTA – LTA primer DAG-Glc2-Pho-Gro. Values in parentheses were observed only with the low-accuracy 4000 QTRAP system.\n\nProfiling and tandem mass spectrometry of lipids with phosphoglycerol terminus – The phosphoglycerol head group has a molecular mass of 172 and produced a cyclic, equivalent to dehydrated, residual anion at 153 amu. The 153 amu fragment peak is most intense for phospholipids with a terminal phosphoglycerol, and weak for phospholipids - such as cardiolipin (CL) and aminoacylated PGs - with such an embedded group. This scan between 400 and 1700 amu at a collision energy of -95 electronvolts was most effective in hitting larger precursor ions (part of the mass range is shown in Figure 3A). The spectrum revealed a cluster of cardiolipin (CL) double anions in the 650–680 amu range and a more intense cluster centered around two major anions at 693 and 721 amu, corresponding to the dominant lipids of (30:0) and (32:0) PGs, respectively. There was an 887 amu unknown species as well as mostly dehydrated lyso-cardiolipins (lyso-CL) close to 1100 amu and cardiolipins close to 1300 amu. There were no noticeable hits below 600 amu or between 1400 and 1700 amu. Besides, the 1017 amu and 1045 amu anions matched expected masses of lipoteichoic acid primer (Figure 1B) with dominant fatty acyl compositions of (30:0) and (32:0), respectively.\n\nThe smaller 1017 amu anion had two identical (15:0) fatty acyl chains and therefore made assignment of fragments less difficult. The MS/MS spectra of the 1017 ion acquired with the QTRAP system at a collision energy of -90 electronvolts is shown in Figure 3B, and m/z values of fragments are listed in Table 2. In addition to the 79 amu phosphate residue, the pair of 153 amu and 171 amu ions which corresponded to glycerolphosphate residue, the dominant fatty acid ion at 241 amu matched the expected (15:0) composition. Fragmentation at the two glycosyl bonds likely produced the 315 amu and 477 amu ions. At the other end of the spectrum, the 943 amu ion was likely due to the neutral loss of cycloglycerol (74 amu). A further loss of (15:0) fatty acid (242 amu) or ketene (224 amu) likely produced the pair of 701 and 719 amu ions, respectively. Another pair at 775 and 793 amu were produced similarly but from the molecular ion. The 1017 amu molecular ion matched structural characteristics of a lipoteichoic acid primer with a single glycerolphosphate unit attached to the lipid anchor of diglucosyldiacyglycerol.\n\nProfiling of lipids with ester-linked alanine – In negative mode, ester-linked fatty acids are known to form intense fragment [FA-H]- ions. This is also true for ester-linked amino acids23. A precursor scan between 400 and 1700 amu at an optimized collision energy of -95 electronvolts for 88 amu [Alanine-H]- (part of the mass range is shown in Figure 4A) revealed as expected a cluster of alanyl-PGs with two dominant peaks at 764 and 792 amu corresponding to (30:0) and (32:0) alanyl-PG, respectively. The precursor scan also revealed two adjacent clusters of alanylated lipids separated by 71 amu which corresponded to the molecular mass of a dehydrated alanine. The first cluster with dominant 1088 and 1116 amu anions matched expected m/z values of mono-alanylated lipoteichoic acid primers (Figure 1C), while the second cluster centered around the 1159 and 1187 amu anions matched those of di-alanylated lipoteichoic acid primers (Figure 1D). There were no noticeable hits below 700 amu or between 1200 and 1700 amu.\n\nThe overall mass of the 1088 amu anion matched that of (30:0) alanyl-lipoteichoic acid primer. The MS/MS spectra of the 1088 ion acquired with the QTRAP system at a collision energy of -90 electronvolts is shown in Figure 4B, and m/z values of fragments are listed in Table 3. The 79, 153 and 171 amu ions corresponded to the putative glycerolphosphate backbone of this lipid. The dominant fatty acid ion at 241 amu matched the expected (15:0) composition and its putative ester linkage to the lipid. The 88 amu ion implied a terminal ester-linked alanine. The 224 amu ion corresponded to the dehydrated or cyclic form of the putative head group of alanylated glycerolphosphate. At the other end of the spectrum, the 999 amu ion was likely due to the neutral loss of alanine (89 amu) from the 1088 molecular anion. The pair of ions at 925 and 943 amu corresponded to the neutral loss of linear (163 amu) or cyclic (145 amu) alanyl-glycerol. In the mid-section of the spectrum, the 459 amu species corresponded to neutral losses of both DAG (540 amu) and alanine (89 amu), while the 533 amu ion corresponded to neutral losses of both fatty acids (2 × 242 = 484 amu) and a dehydrated alanine (71 amu). Fragments at 757 and 775 amu corresponded to the loss of one (15:0) fatty acid or ketene (242 or 224 amu) as well as alanine (89 amu). The smaller 701 and 719 amu fragments corresponded to loss of one (15:0) fatty acid or ketene as well as cyclo-alanyl-glycerol (145 amu). Except for the absence of 701 amu anion and the low-abundance 757 amu anion in the Q-TOF-acquired spectrum, all fragments matched expected m/z values within 0.004 amu. This 1088 amu is most likely mono-alanylated lipoteichoic acid primer.\n\nThe m/z value of the 1159 amu anion matched that of (30:0) di-alanyl-lipoteichoic acid primer. The MS/MS spectra of the 1159 ion acquired with the QTRAP system at a collision energy of -80 electronvolts is shown in Figure 4C, and m/z values of fragments are listed in Table 4. Due to the lower abundance of the 1159 anion, its MS/MS spectrum was noisier than those of the 1017 and 1088 anions. The spectrum shared 79, 88, 153, 171 and 241 amu ions with that of the 1088 amu anion. Unexpectedly, a 159 amu species corresponding precisely to deprotonated alanylalanine dipeptide was also observed. The mid-section of the spectrum did not reveal reoccurring ions in spectra collected at collision energies 10 electronvolts apart and therefore were likely noise due to the low abundance of this molecular ion. The whole head group of dialanylated glycerolphosphate was not observed. At the high end of the spectrum, an 846 amu fragment was probably generated by neutral losses of both (15:0) fatty acid (242 amu) and a cyclo-alanine (71 amu). The 925, 943 and 999 amu ions were in common with the fragments from the 1088 amu anion of mono-alanylated lipoteichoic acid primer. A further dehydrated 981 amu ion was observed, which corresponded to neutral losses of two alanine molecules (2 × 89 = 178 amu). A larger 1017 amu ion precisely matched that of (30:0) lipoteichoic acid primer. Another even larger 1070 amu ion corresponded to the 89 amu neutral loss of one alanine from the 1159 amu molecular anion. Surprisingly, a 1115 amu ion corresponding to a neutral loss of 44 amu was observed. As shown in Figure 5A, a two-step reaction may account for the formation of alanylalanyl-LTA primer and subsequent fragmentation into the 159 amu alanylalanine anion. An alternate reaction shown in Figure 5B may rearrange the putative bis-alanyl-LTA primer to expose a terminal carboxyl group in one of the two alanine residues, which could subsequently release the 44 amu CO2 and produce the 1115 amu fragment anion. Due to the lack of any fragment ion corresponding to linear (313 amu) or cyclic (295 amu) bis-alanyl-glycerolphosphate, the result was not definitive on the location of two ester-linked alanine residues. Based on its similar fragmentation pattern to that of mono-alanylated LTA primer, this 1159 amu species is tentatively assigned as bis-alanyl-LTA primer (Figure 1D).\n\nThe DAG-Glc-Glc part is shown as R. A. Rearrangement and fragmentation to produce the 159 amu dialanyl anion. B. Rearrangement and decarboxylation reactions which resulted in the neutral loss of the 44 amu CO2 and the 1115 amu fragment anion.\n\n\nDiscussion\n\nAminoacylated lipids play an apparent role in surface charge modulation of Gram-positive bacteria5. The least known part of charge modulation is arguably the D-alanylation pathway of lipoteichoic acids. The Bligh and Dyer method24 carried out at an icy temperature appeared to be essential for successful extraction of species that are almost certainly lipoteichoic acid primer and its mono- and di-alanylated derivatives. The possible existence of the putative bis-alanylated lipoteichoic acid primer indicates that these species are unlikely to be hydrolyzed fragments of lipoteichoic acids since hydrolysis could only produce mono-alanylated derivative. Hydrolysis of lipoteichoic acid should also produce detectable amount of residue with more than one phosphoglycerol units attached to the lipid anchor, which was apparently lacking in the lipid extract. It also implies that lipoteichoic acid is unlikely to be transferred as D-alanyl-glycerolphosphate unit directly from D-alanyl-PG to the growing lipoteichoic acid chain by the LtaS polymerase as that would only produce mono-alanylated derivative. The observable abundance of lipoteichoic acid primer also appear to suggest that one of the four LtaS paralogs in B. subtilis28 may indeed act like LtaP primase in Listeria monocytogenes for the biosynthesis of lipoteichoic acid primer29.\n\nMy lab has recently hypothesized that D-alanyl-PG may serve as the lipid intermediate for subsequent D-alanylation of teichoic acids. Taken together, a putative pathway is shown in Figure 6. It is known that DltA catalyzes the activation of D-alanine with the consumption of ATP and thioester formation with the D-alanyl carrier protein DltC. It is possible either DltD or DltB - with the former being more likely based on the best available evidences that DltD binds DltC and has thioesterase activity22 – catalyzes the transfer of thioester-bound D-alanyl group to PG in the bacterial membrane by a thermodynamically spontaneous esterification reaction. The other one of the pair of Dlt proteins, most likely DltB, then catalyzes the transfer of D-alanyl group from the PG carrier to lipoteichoic acid by a transesterification reaction that can only reach equilibrium. This thermodynamic nature of this final transesterification reaction would enable the accumulation of a significant amount of the D-alanyl-PG intermediate, which is consistent with my lab’s recent observation that alanyl-PG is somewhat abundant in lipids extracted from B. subtilis. Importantly, the diglucosyl-diacylglycerol anchor, lipoteichoic acid primer, D-alanylated lipoteichoic acid primer as well as D-alanylated phosphatidylglycerol can be monitored in lipids extracted from wild-type and mutant cells of B. subtilis and aid in the full elucidation of the D-alanylation pathway of lipoteichoic acids.\n\nDltA catalyzes the loading of thioester-linked D-alanine to the carrier protein DltC. DltC-carried D-alanyl group is further transferred to PG in the membrane by forming an ester bond. The putative enzyme for this process is DltD. PG-attached D-alanyl group is further transferred to LTA by transesterification. The putative enzyme for this latter process is DltB.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for ‘Alanylated lipoteichoic acid primer in Bacillus subtilis’, Luo 2016. README.txt contains a description of the files, 10.5256/f1000research.8007.d11343430",
"appendix": "Author contributions\n\n\n\nYL conceived and carried out this study.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work is supported by Saskatchewan Health Research Foundation Group Grant (2008-2010) and Phase 3 Team Grant (2010-2013) to the Molecular Design Research Group at University of Saskatchewan, a Natural Sciences and Engineering Research Council Discovery Grant (2010-2015) 261981-2010 to YL.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgement\n\nI thank Ms. Deborah Michel for training and maintenance of SCIEX 4000 QTRAP system at the Core Mass Spectrometry Facility at the University of Saskatchewan. I also thank Mr. Paulos Chumala and Dr. George Katselis for tuning and operating the Agilent Q-TOF 6550 system.\n\n\nReferences\n\nSohlenkamp C, Geiger O: Bacterial membrane lipids: diversity in structures and pathways. FEMS Microbiol Rev. 2016; 40(1): 133–59. PubMed Abstract | Publisher Full Text\n\nWeidenmaier C, Kristian SA, Peschel A: Bacterial resistance to antimicrobial host defenses--an emerging target for novel antiinfective strategies? Curr Drug Targets. 2003; 4(8): 643–9. PubMed Abstract | Publisher Full Text\n\nPeschel A, Otto M, Jack RW, et al.: Inactivation of the dlt operon in Staphylococcus aureus confers sensitivity to defensins, protegrins, and other antimicrobial peptides. J Biol Chem. 1999; 274(13): 8405–10. PubMed Abstract | Publisher Full Text\n\nKristian SA, Lauth X, Nizet V, et al.: Alanylation of teichoic acids protects Staphylococcus aureus against Toll-like receptor 2-dependent host defense in a mouse tissue cage infection model. J Infect Dis. 2003; 188(3): 414–23. PubMed Abstract | Publisher Full Text\n\nRoy H: Tuning the properties of the bacterial membrane with aminoacylated phosphatidylglycerol. IUBMB Life. 2009; 61(10): 940–53. PubMed Abstract | Publisher Full Text | Free Full Text\n\nden Kamp JA, Redai I, van Deenen LL: Phospholipid composition of Bacillus subtilis. J Bacteriol. 1969; 99(1): 298–303. PubMed Abstract | Free Full Text\n\nArmstrong JJ, Baddiley J, Buchanan JG, et al.: Composition of teichoic acids from a number of bacterial walls. Nature. 1959; 184: 247–8. PubMed Abstract | Publisher Full Text\n\nNeuhaus FC, Baddiley J: A continuum of anionic charge: structures and functions of D-alanyl-teichoic acids in gram-positive bacteria. Microbiol Mol Biol Rev. 2003; 67(4): 686–723. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFischer W: Physiology of lipoteichoic acids in bacteria. Adv Microb Physiol. 1988; 29: 233–302. PubMed Abstract | Publisher Full Text\n\nPercy MG, Gründling A: Lipoteichoic acid synthesis and function in gram-positive bacteria. Annu Rev Microbiol. 2014; 68: 81–100. PubMed Abstract | Publisher Full Text\n\nBrown S, Santa Maria JP Jr, Walker S: Wall teichoic acids of gram-positive bacteria. Annu Rev Microbiol. 2013; 67: 313–36. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHyyrylainen HL, Vitikainen M, Thwaite J, et al.: D-Alanine substitution of teichoic acids as a modulator of protein folding and stability at the cytoplasmic membrane/cell wall interface of Bacillus subtilis. J Biol Chem. 2000; 275(35): 26696–703. PubMed Abstract | Publisher Full Text\n\nPerego M, Glaser P, Minutello A, et al.: Incorporation of D-alanine into lipoteichoic acid and wall teichoic acid in Bacillus subtilis. Identification of genes and regulation. J Biol Chem. 1995; 270(26): 15598–606. PubMed Abstract | Publisher Full Text\n\nKiriukhin MY, Neuhaus FC: D-alanylation of lipoteichoic acid: role of the D-alanyl carrier protein in acylation. J Bacteriol. 2001; 183(6): 2051–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZimmermann S, Pfennig S, Neumann P, et al.: High-resolution structures of the D-alanyl carrier protein (Dcp) DltC from Bacillus subtilis reveal equivalent conformations of apo- and holo-forms. FEBS Lett. 2015; 589(18): 2283–9. PubMed Abstract | Publisher Full Text\n\nDu L, He Y, Luo Y: Crystal structure and enantiomer selection by D-alanyl carrier protein ligase DltA from Bacillus cereus. Biochemistry. 2008; 47(44): 11473–80. PubMed Abstract | Publisher Full Text\n\nYonus H, Neumann P, Zimmermann S, et al.: Crystal structure of DltA. Implications for the reaction mechanism of non-ribosomal peptide synthetase adenylation domains. J Biol Chem. 2008; 283(47): 32484–91. PubMed Abstract | Publisher Full Text\n\nStachelhaus T, Mootz HD, Marahiel MA: The specificity-conferring code of adenylation domains in nonribosomal peptide synthetases. Chem Biol. 1999; 6(8): 493–505. PubMed Abstract | Publisher Full Text\n\nHisanaga Y, Ago H, Nakagawa N, et al.: Structural basis of the substrate-specific two-step catalysis of long chain fatty acyl-CoA synthetase dimer. J Biol Chem. 2004; 279(30): 31717–26. PubMed Abstract | Publisher Full Text\n\nConti E, Franks NP, Brick P: Crystal structure of firefly luciferase throws light on a superfamily of adenylate-forming enzymes. Structure. 1996; 4(3): 287–98. PubMed Abstract | Publisher Full Text\n\nHofmann K: A superfamily of membrane-bound O-acyltransferases with implications for Wnt signaling. Trends Biochem Sci. 2000; 25(3): 111–2. PubMed Abstract | Publisher Full Text\n\nDebabov DV, Kiriukhin MY, Neuhaus FC: Biosynthesis of lipoteichoic acid in Lactobacillus rhamnosus: role of DltD in D-alanylation. J Bacteriol. 2000; 182(10): 2855–64. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAtila M, Luo Y: Profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis [version 1; referees: awaiting peer review]. F1000Res. 2016; 5: 121. Publisher Full Text\n\nBligh EG, Dyer WJ: A rapid method of total lipid extraction and purification. Can J Biochem Physiol. 1959; 37(8): 911–917. PubMed Abstract | Publisher Full Text\n\nTanaka S, Fujita Y, Parry HE, et al.: Mass++: A Visualization and Analysis Tool for Mass Spectrometry. J Proteome Res. 2014; 13(8): 3846–3853. PubMed Abstract | Publisher Full Text\n\nGidden J, Denson J, Liyanage R, et al.: Lipid Compositions in Escherichia coli and Bacillus subtilis During Growth as Determined by MALDI-TOF and TOF/TOF Mass Spectrometry. Int J Mass Spectrom. 2009; 283(1–3): 178–184. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFischer W, Mannsfeld T, Hagen G: On the basic structure of poly(glycerophosphate) lipoteichoic acids. Biochem Cell Biol. 1990; 68(1): 33–43. PubMed Abstract | Publisher Full Text\n\nGründling A, Schneewind O: Synthesis of glycerol phosphate lipoteichoic acid in Staphylococcus aureus. Proc Natl Acad Sci U S A. 2007; 104(20): 8478–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWebb AJ, Karatsa-Dodgson M, Gründling A: Two-enzyme systems for glycolipid and polyglycerolphosphate lipoteichoic acid synthesis in Listeria monocytogenes. Mol Microbiol. 2009; 74(2): 299–314. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLuo Y: Dataset 1 in: Alanylated lipoteichoic acid primer in Bacillus subtilis. F1000Research. 2016. Data Source"
}
|
[
{
"id": "12352",
"date": "25 Feb 2016",
"name": "Katarzyna Duda",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe work of Luo Y. describes an identification of the biosynthetic intermediates of the lipoteichoic acid utilizing mass spectrometrical approach.Generally, the conclusions are based on the solid raw data, the title is appropriate, and the abstract provides subsequent summary of the article.I have a few comments, which addressing can help to improve the manuscript:In the abstract and introduction given description of LTA refers mainly to Type 1 of LTA. I would specify it, and in the introduction mention other types of LTA, that are structurally different (reviewed: Schneewind O., Missiakas D. J. Bacteriol. 2014, 196(6):1133.) D-Alanylation of LTA 1 and 4 is indeed very common, for the reader of the paper would it be also of interest, to mention other LTA modifications. The use of the sentence with the characterization of D- but not L-Alanine, is confusing, as to date all bacterial Ala is D-configured. Fig. 1 - I suggest to draw sugars in chair conformation, and the double bonds of P- or COO- groups should be equally thick. The given formula of glycerol is wrong - no double bond is present, better to use standard abreviation Gro, e.g. Gro-Glc-Glc (concerns also Table 1). Phosphate groups are commonly abbreviated as P, not Pho. Table 1 - I would write LTA primer, not only LTA, otherwise confusing. Page 4 . when describing peaks at 887 and 915 instead of using 30:0 and 32:0, please use 15:0+15:0, and 15:0+17:0, otherwise confusing. Peak at 887 corresponds to 2x Hex, Gro, 2x15:0, Na, so corresponds to sodiated (but not dehydrated - this word should be removed) linker (Figure 2A). The confusion with dehydrated or not was present a few times in the text (e.g. 753 amu represents loss of glucose and not dehydrated glucose). On page 4 - the QTRAP spectra are shown in Fig 3 - Fig 4, not as in text Fig 2 - Fig 4",
"responses": [
{
"c_id": "1847",
"date": "04 Mar 2016",
"name": "Yu Luo",
"role": "Author Response",
"response": "I appreciate Dr. Duda’s time and comments. I will incorporate changes as described below in my response to Dr. Katarzyna Duda’s suggestions.1. In the abstract and introduction given description of LTA refers mainly to Type 1 of LTA. I would specify it, and in the introduction mention other types of LTA, that are structurally different (reviewed: Schneewind O., Missiakas D. J. Bacteriol. 2014, 196(6):1133.)YL: I will mention the review and specify that B. subtilis produces Type 1 lipoteichoic acid. 2. D-Alanylation of LTA 1 and 4 is indeed very common, for the reader of the paper would it be also of interest, to mention other LTA modifications.YL: I will mention other types of lipoteichoic acid and that Type 1 and 4 lipoteichoic acids are commonly modified by D-alanine. 3. The use of the sentence with the characterization of D- but not L-Alanine, is confusing, as to date all bacterial Ala is D-configured.YL: It is actually necessary to specify D-alanine. MprF in B. subtilis is known to catalyze the synthesis of L-alanyl-phosphatidylglycerol form L-alanyl-tRNA and phosphatisylglycerol. 4. Fig. 1 - I suggest to draw sugars in chair conformation, and the double bonds of P- or COO- groups should be equally thick.YL: I will re-draw the structures with sugars in chair conformation, and revert to normal thickness in ChemDraw to make the double bonds equally thick. 5. The given formula of glycerol is wrong - no double bond is present, better to use standard abbreviation Gro, e.g. Gro-Glc-Glc (concerns also Table 1).YL: The 405 amu species likely represents the structure shown with a double bond in Table-1. It was a common fragment for this group of sodiated cations of DAG-Glc-Glc, indicating both fatty acyl tails are lost. The 405 amu fragment corresponds to the neutral loss of both fatty acyl free radicals, or equivalently a ketene and a peroxyfatty acid. The double bond formation in the glycerol residue is a consequence of such neutral losses.6. Phosphate groups are commonly abbreviated as P, not Pho. Table 1 - I would write LTA primer, not only LTA, otherwise confusing.YL: I will rename Pho as P, and abbreviate LTA primer as LTAp. 7. Page 4 . when describing peaks at 887 and 915 instead of using 30:0 and 32:0, please use 15:0+15:0, and 15:0+17:0, otherwise confusing.YL: The (30:0) species was a mixture of (15:0-15:0), (14:0-16:0) and other diglucosyl-diacylglycerol. I will state that (15:0-15:0) is the most abundant form in the mixture. 8. Peak at 887 corresponds to 2x Hex, Gro, 2x15:0, Na, so corresponds to sodiated (but not dehydrated - this word should be removed) linker (Figure 2A). The confusion with dehydrated or not was present a few times in the text (e.g. 753 amu represents loss of glucose and not dehydrated glucose).YL: Ester and glycosidic bonds, as well as peptide bonds, are synthesized with the net effect of dehydration. Dissociation of the molecular ion is not equivalent to the hydrolysis process in solution where a water molecule is added back to the broken parts. One or the other fragment of the molecular ion has to bare the consequence of dehydration incurred during the biosynthesis process. For instance, the 753 amu fragment indeed represents the loss of a dehydrated glucose (162 amu) from the molecular ion of 915 amu. A neutral loss of 180 amu glucose would produce a fragment of 735 amu. It is true that the head group is not dehydrated in the lipid. However, the scan was indeed for precursor ions of the 347 amu dehydrated (-18 amu) and sodiated (+23 amu) diglucose (342 amu) fragment ion (342 – 18 + 23 = 347).9. On page 4 - the QTRAP spectra are shown in Fig 3 - Fig 4, not as in text Fig 2 - Fig 4YL: They are indeed shown in Figures 2, 3 and 4."
}
]
},
{
"id": "12358",
"date": "24 Mar 2016",
"name": "Christian Sohlenkamp",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe present manuscript describes a mass spectrometric study of Bacillus subtilis lipids in which possible intermediates in the biosynthesis and D-alanylation of type I lipoteichoic acid are detected.In general, the title is appropriate, and the abstract provides an adequate summary of the article. The conclusions are based on the raw data presented. My major critique is that the author actually does not show the presence of the pathway, he only detects molecular ions my MS that might be pathway intermediates. The other comments should be addressed to improve the manuscript.Comments:Abstract: I think the word “possible” should be added, “Here I report the use of mass spectrometry in the identification of possible intermediate species…”, because although that it is very probable that this is case, strictly speaking, it has not been shown. Abstract: In the same sense, I think it is preferable to write “…D-alanyl-phosphatidyl glycerol should aid in…” Introduction: It should be specified that the author refers to type I LTA. Introduction: The first part of the introduction is very simplified, for example no lipid A is mentioned, nor the modification it can suffer to make it less anionic. I suggest rewriting and improving this paragraph. Figure 1 and 5: Double bonds should look identical in the figures. Strictly speaking the authors don’t show that it is D-alanine in the detected structures. Results/Discussion: What does the author think is the explanation that the new species only can be detected after a cold extraction? Methods: Why do the authors add sodium acetate to the growth medium before centrifugation of the culture? Page 2, left column, middle paragraph: I think it should say “adenylylation” not “adenylation”, because it is an AMP-transfer. Page 2, left column, middle paragraph: Instead of “The functionally uncharacterized DltB appears to be an integral membrane protein…”, it would be better to write “is predicted to be…”. Page 2, left column, middle paragraph: It should say “O-acyltransferase”, not “o-acyltransferase” In the legends to figures 3 and 4, it should say “acid” not “aicd”. Methods/Results: Why are the electronvolts sometimes “+” and sometimes “-“ Tables 2 and 4: The abbreviation FA for fatty acid should be explained. Page 8, left column, middle paragraph: The word “smaller” should be deleted. I agree with reviewer one that P is probably a better abbreviation of the phosphate group.",
"responses": [
{
"c_id": "1888",
"date": "29 Mar 2016",
"name": "Yu Luo",
"role": "Author Response",
"response": "Christian Sohlenkamp, Center for Genomic Sciences, National Autonomous University of Mexico (UNAM), Mexico The present manuscript describes a mass spectrometric study of Bacillus subtilis lipids in which possible intermediates in the biosynthesis and D-alanylation of type I lipoteichoic acid are detected.In general, the title is appropriate, and the abstract provides an adequate summary of the article. The conclusions are based on the raw data presented. My major critique is that the author actually does not show the presence of the pathway, he only detects molecular ions my MS that might be pathway intermediates. The other comments should be addressed to improve the manuscript. YL: I appreciate Dr. Sohlenkamp’s comments. I will incorporate changes as described below in the revised version.Comments:1. Abstract: I think the word “possible” should be added, “Here I report the use of mass spectrometry in the identification of possible intermediate species…”, because although that it is very probable that this is case, strictly speaking, it has not been shown.YL: I agree that its status as an intermediate has not been demonstrated so that “possible” should be added. 2. Abstract: In the same sense, I think it is preferable to write “…D-alanyl-phosphatidyl glycerol should aid in…”.YL: I agree. 3. Introduction: It should be specified that the author refers to type I LTA.YL: I agree with both reviewers that type of LTA in B. subtilis should be specified. 4. Introduction: The first part of the introduction is very simplified, for example no lipid A is mentioned, nor the modification it can suffer to make it less anionic. I suggest rewriting and improving this paragraph.YL: I will expand the introductory part. For instance, lipid A and lipopolysaccharide will be mentioned. 5. Figure 1 and 5: Double bonds should look identical in the figures.YL: I will redraw the molecular figures to make the two lines in double bonds in the same thickness and redraw the glucosyl rings in chair conformation. 6. Strictly speaking the authors don’t show that it is D-alanine in the detected structures.YL: I will revise the statements concerning D-alanylation. I will briefly report that the lipid lysate has much more D-alanine than L-alanine. 7. Results/Discussion: What does the author think is the explanation that the new species only can be detected after a cold extraction?YL: It is possible that it is not stable at room temperature. I think the readers can explain this. 8. Methods: Why do the authors add sodium acetate to the growth medium before centrifugation of the culture?YL: It is out of respect to previous publications that teichoic acid-linked D-alanine tend to be most stable under mildly acidic condition. It is also part of my effort to standardize protocols. As the B. subtilis grow dense, pH typically gradually raises from neutrality to ~8.5. Unlike lipid extraction under low temperature, adding sodium acetate before centrifugation was not a required procedure as unbuffered cells also produced similar amount of the reported lipid species. 9. Page 2, left column, middle paragraph: I think it should say “adenylylation” not “adenylation”, because it is an AMP-transfer.YL: Strictly speaking “adenylylation” is correct. It will be corrected. 10. Page 2, left column, middle paragraph: Instead of “The functionally uncharacterized DltB appears to be an integral membrane protein…”, it would be better to write “is predicted to be…”.YL: I agree. 11. Page 2, left column, middle paragraph: It should say “O-acyltransferase”, not “o-acyltransferase”.YL: Thanks for pointing out. 12. In the legends to figures 3 and 4, it should say “acid” not “aicd”.YL: I was typing too fast. 13. Methods/Results: Why are the electronvolts sometimes “+” and sometimes “-“.YL: The sign of voltage values appears to follow the positive/negative mode of ionization. I had to specify the sign during the experiment. 14. Tables 2 and 4: The abbreviation FA for fatty acid should be explained.YL: I will add this abbreviation. 15. Page 8, left column, middle paragraph: The word “smaller” should be deleted.YL: I was emphasizing the relative ease of analyzing the smaller 1017 amu species than the larger 1045 amu species. As the sentence starts a paragraph, I agree it is better to remove “smaller”. 16. I agree with reviewer one that P is probably a better abbreviation of the phosphate group. YL: I was trying to use 3-letter codes consistently. I will simplify it as “P”."
}
]
}
] | 1
|
https://f1000research.com/articles/5-155
|
https://f1000research.com/articles/5-635/v1
|
11 Apr 16
|
{
"type": "Software Tool Article",
"title": "CyLineUp: A Cytoscape app for visualizing data in network small multiples",
"authors": [
"Maria Cecília D. Costa",
"Thijs Slijkhuis",
"Wilco Ligterink",
"Henk W.M. Hilhorst",
"Dick de Ridder",
"Harm Nijveen",
"Maria Cecília D. Costa",
"Thijs Slijkhuis",
"Wilco Ligterink",
"Henk W.M. Hilhorst",
"Dick de Ridder"
],
"abstract": "CyLineUp is a Cytoscape 3 app for the projection of high-throughput measurement data from multiple experiments/samples on a network or pathway map using “small multiples”. This visualization method allows for easy comparison of different experiments in the context of the network or pathway. The user can import various kinds of measurement data and select any appropriate Cytoscape network or WikiPathways pathway map. CyLineUp creates small multiples by replicating the loaded network as many times as there are experiments/samples (e.g. time points, stress conditions, tissues, etc.). The measurement data for each experiment are then mapped onto the nodes (genes, proteins etc.) of the corresponding network using a color gradient. Each step of creating the visualization can be customized to the user’s needs. The results can be exported as a high quality vector image.",
"keywords": [
"Data display",
"Expression profiling",
"Graphical user interfaces",
"Metabolite profiling",
"Small multiples"
],
"content": "Introduction\n\nDevelopments in high-throughput -omics measurement techniques have allowed researchers to routinely obtain presence/absence, levels or interactions of molecules at a genome-wide scale, often addressing important questions that could not be answered before. Consequently, the demand for more and better tools for data analysis is growing, especially visualization tools to project data of multiple samples (e.g. different time points or tissues) on network or pathway maps. Visualization plays an important role in data analysis as a way to obtain insights, select details and present findings1.\n\nSeveral software tools enable visualization of expression data on pathways2–4 and the functionality to plot charts on nodes has become a standard feature of Cytoscape 35. While these visualizations often work well for analyzing measurement patterns of individual genes in a network, they do not easily show changes at a more global level in the network. Often, these global effects are the most interesting to the biologist.\n\nHere, we present a different approach that uses “small multiples”. This approach is a visualization technique that shows multiple copies of a graph with the same combination of variables, but with different changes in each variable6. Small multiples facilitate comparison, presentation, storytelling and search for patterns, trends and outliers1.\n\nThere is currently no visualization tool enabling projection of data from different experiments/samples on small multiples. Therefore, we developed the Cytoscape app CyLineUp, that takes advantage of the tools for importing and displaying maps integrated into Cytoscape to create small multiples. We applied CyLineUp to visualize changes in the glycolysis/tricarboxylic acid (TCA) cycle induced by the phytohormone abscisic acid (ABA) in germinated Arabidopsis thaliana seeds.\n\n\nMethods and implementation\n\nCyLineUp was written in Java 7 as an OSGi (Open Services Gateway Initiative) bundle. It adds a “CyLineUp” tab to the Cytoscape “Control Panel” offering functionality to import the data, configure the views and visual styles, and export an SVG rendering of the visualization. The data import functionality is implemented as a Cytoscape Task, using Tunable annotations for user input dialogs. The small multiples visualization is implemented as a set of views on the same underlying network. Each view has its own visual style for coloring the nodes according to the input data. The FreeHEP Graphics 2D Library is used for exporting an SVG image with the small multiples.\n\nVisualizing -omics data with CyLineUp consists of four main steps. (I) Creating the map or network that will be the basis for data visualization. A large collection of pathways from the WikiPathways platform (http://wikipathways.org) can be easily imported using the WikiPathways Cytoscape app7. Optionally, pathways created and imported directly from Pathvisio8 and networks created in Cytoscape can be used. The users should take care that the names of the identifiers are the same in the data file and in the pathway/network. (II) Importing data and linking it to the map using the graphical user interface provided by CyLineUp (Figure 1). CyLineUp accepts text files with comma, semicolon, tab or arbitrary whitespaces separated values. CyLineUp provides auto-import functionality, but manual selection of data is also possible. The auto-import functionality is based on the order of the columns in the data file. Therefore, it is advisable to have the identifiers in the first column and the values (e.g. fold change) and the p-values for each treatment/sample in subsequent columns. (III) Customizing the visualization to the user’s needs by changing the Visual styles in the CyLineUp user interface (Figure 2). Nodes that have no data associated can be shown (default), greyed out or hidden. In case the nodes are hidden, the edges associated to them will also be hidden. The default colors are green (HEX #00FF00) for up-regulated genes and red (HEX #FF0000) for down-regulated genes. The user can chose different colors by pressing the Pick color buttons. After each change, the user can update the view of the small multiples by pressing the button Update network views. (IV) Exporting the visualization to an SVG image file. A real-time image preview is available, but can be disabled in case it takes too much computer resources.\n\n(A) After selecting the text file with the input data, the user should select the field/column separator character (comma, semicolon, tab or whitespace). (B) On the data binding panel, the user should select the column that contains the identifier (“shared name” in our example) and configure the small multiples either by using the auto-detect functionality or manually (add small multiple views).\n\nThe user can customize several visualization settings by changing the Visual styles. Nodes that have no data associated can be shown (default), greyed out or hidden. For hidden nodes, the associated edges will also be hidden. The node color can be set to reflect the p-value cut-off (0.001, 0.01, 0.05 and 0.1) or fold change. The default colors are green (HEX #00FF00) for “up-regulated genes” and red (HEX #FF0000) for “down-regulated genes”. The user can choose different colors by pressing the Pick color buttons. After customization, the user can export the visualization to an SVG image file.\n\nA general activation of the cycle can be observed and may be a mechanism by which the plant cell prepares for the energy demands of recovery from drought. Red nodes indicate genes with significantly declining transcript abundance. Green nodes indicate genes with significantly accumulating transcripts. White nodes indicate genes without significant changes in transcript abundance. Grey nodes indicate components that are not genes or do not have data associated.\n\nWe used available gene expression data from a time series of microarrays9 to validate the use of CyLineUp. The data were generated to explore the temporal changes induced by ABA in germinated A. thaliana seeds9. Seeds at the stage of radicle protrusion (0 h) and after four periods (2, 12, 24 and 72 h) of incubation in ABA were used. Details about data acquisition and processing can be found in Costa et al.9. Here, we used CyLineUp to explore the main changes in the glycolysis/TCA cycle during ABA incubation (Figure 3).\n\nThe map of the cycle was created using Pathvisio 3.2.08 and imported into Cytoscape 3.2.1 (Supplementary file S1.gpml). Then, the expression data and Bonferroni-corrected p-values (comma-separated values (CSV) file: Supplementary file S2.csv) were imported using the CyLineUp user interface. The visual style was set to “grey out” nodes that have no data associated, use a “p-value cut-off” of 0.1 and “use fill color to visualize p-value”.\n\nThe glycolysis/TCA cycle provides most of the energy for processes in the seed. A general activation of the cycle could be observed as one of the immediate cellular responses induced by ABA10.\n\n\nConclusion\n\nCyLineUp allows easy visual analysis of data from multiple samples on a biological network to study changes at the (sub-)network level. It is a useful and timely addition to the Cytoscape network analysis platform.\n\n\nSoftware availability\n\nSoftware available from: http://apps.cytoscape.org/apps/cylineup\n\nLatest source code: https://github.com/Slijkhuis/CyLineUp\n\nArchived source code as at time of publication: http://dx.doi.org/10.5281/zenodo.4813511\n\nLicense: Lesser GNU Public License 2.1",
"appendix": "Author contributions\n\n\n\nMCDC wrote the manuscript and provided experimental data to validate the use of the app. TS developed initial version of the app. WL, HWMH and DDR provided input on the manuscript. HN supervised app development, improved the app and provided input on the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work has been supported by the ‘Conselho Nacional de Desenvolvimento Científico e Tecnológico’ (CNPq, Brazil) (MCDC).\n\n\nSupplementary material\n\nSupplementary file S1.gpml Map of the glycolysis/TCA cycle.\n\nSupplementary file S2.csv Expression values and Bonferroni-corrected p-values.\n\n\nReferences\n\nvan den Elzen S, van Wijk JJ: Small multiples, large singles: a new approach for visual data exploration. Comput Graph Forum. 2013; 32(3pt2): 191–200. Publisher Full Text\n\nWestenberg MA, Roerdink JB, Kuipers OP, et al.: SpotXplore: a Cytoscape plugin for visual exploration of hotspot expression in gene regulatory networks. Bioinformatics. 2010; 26(22): 2922–3. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYamada T, Letunic I, Okuda S, et al.: iPath2.0: interactive pathway explorer. Nucleic Acids Res. 2011; 39(Web Server issue): W412–5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nThimm O, Bläsing O, Gibon Y, et al.: MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J. 2004; 37(6): 914–39. [cited 2011 Aug 4]. PubMed Abstract | Publisher Full Text\n\nShannon P, Markiel A, Ozier O, et al.: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003; 13(11): 2498–504. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTufte ER: The visual display of quantitative information. In: Tufte ER, editor. The visual display of quantitative information. 2nd ed. Cheshre, Connecticut, Connecticut: Graphics Press, 2001; 197. Reference Source\n\nKutmon M, Riutta A, Nunes N, et al.: WikiPathways: capturing the full diversity of pathway knowledge. Nucleic Acids Res. 2016; 44(D1): D488–94. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKutmon M, van Iersel MP, Bohler A, et al.: PathVisio 3: an extendable pathway analysis toolbox. PLOS Comput Biol. 2015; 11(2): e1004085. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCosta MC, Nijveen H, Ligterink W, et al.: Time-series analysis of the transcriptome of the re-establishment of desiccation tolerance by ABA in germinated Arabidopsis thaliana seeds. Genom Data. 2015; 5: 154–6. Elsevier B.V. PubMed Abstract | Publisher Full Text | Free Full Text\n\nToldi O, Tuba Z, Scott P: Vegetative desiccation tolerance: Is it a goldmine for bioengineering crops? Plant Sci. 2009; 176(2): 187–99. [cited 2011 Aug 7]. Publisher Full Text\n\nCosta MC, Slijkhuis T, Nijveen H: CyLineUp. Zenodo. 2016. Data Source"
}
|
[
{
"id": "13301",
"date": "19 Apr 2016",
"name": "Alexander R Pico",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIt is a common use case for Cytoscape, to have data for multiple conditions or time points. There are a few other apps to address this in various ways, including cyAnimator, enhancedGraphics and DynNetwork, which utilize either animation or custom chart graphics for nodes. The \"small multiples\" approach has always been an option for users who were sufficiently skilled with using Cytoscape, which allows one to make multiple networks and apply a unique, data-mapped style to each. This is a tedious and error-prone task, however. So, the CyLineUp app is a welcome tool to make this task easy, consistent and reliable.The app is easy to install and use, and the paper is clear and well-written. It is nice to see a fundamental visualization technique like \"small multiples\" applied here. However, it is disappointing to see the red-green color gradient offered by default, which should be shunned by data visualization tool developers. Perhaps something to consider changing in the next release of the app? Since the app is open source, maybe I'll contribute this code patch myself as a pull request! The CyLineUp app offers its own table importer, visual style editor and image exporter customized for visualizing data for multiple conditions or time points. Looking forward, it would be interesting to see what would be involved in adapting the core of Cytoscape to be able to annotate columns of table data already imported and then support the small multiple view generator, leveraging the native importer, style editor and image exporters. I could picture this functionality becoming a part of the Cytoscape distribution, in the same way the enhancedGraphics app was eventually merged with the core as an out-of-the-box feature. This would make the useful facility of small multiple views available to all users, without having to learn these new, single-purpose interfaces.",
"responses": []
},
{
"id": "14169",
"date": "14 Jun 2016",
"name": "Oren Tzfadia",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nCyLineUp is a new Cytoscape app which allow users to visualize 'changing' networks by enabling users to match dynamic features to networks.\nIn my humble opinion, I find the title a bit confusing - and would modify it to something like: \"CyLineUp: A Cytoscape app for vizualization of data-matched style in multiple networks\".\n\nThe abstract does a fair job in describing the main features of the app presented in the article. The article include suffice explanations, and usage examples, of the app with real biological data. The app itself is very easy to install and use - and thus is very user friendly, which is always an advantage as Cytoscape is heavily used by no-computer-expert biologists. From my own experience, by following the screenshots and explanations provided in the article, it is easy to plot your own data with CyLineUp.\n\nI see the CyLineUp app as a potentially great app for analyzing multiple 'omics' data sets, as often we wish to plot small multiples based on different omics data sets.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-635
|
https://f1000research.com/articles/5-634/v1
|
11 Apr 16
|
{
"type": "Research Article",
"title": "In search of the mechanisms of ketamine’s antidepressant effects: How robust is the evidence behind the mTor activation hypothesis",
"authors": [
"Susanna Popp",
"Berthold Behl",
"Jaya Julie Joshi",
"Thomas A. Lanz",
"Michael Spedding",
"Esther Schenker",
"Therese M Jay",
"Per Svenningsson",
"Dorian Caudal",
"Jacob I. Cunningham",
"Daniel Deaver",
"Anton Bespalov",
"Berthold Behl",
"Jaya Julie Joshi",
"Thomas A. Lanz",
"Michael Spedding",
"Esther Schenker",
"Therese M Jay",
"Per Svenningsson",
"Dorian Caudal",
"Jacob I. Cunningham",
"Daniel Deaver",
"Anton Bespalov"
],
"abstract": "Extensive evidence on rapid and long-lasting antidepressant effects of intravenous ketamine motivated efforts to identify underlying mechanisms that would enable development of novel drugs with similar efficacy, but improved safety and pharmacokinetic profiles. It has been suggested that the antidepressant-like action of ketamine may be mediated by the activation of mTOR-dependent intracellular cascades. Therefore, without any coordination or pre-existing agreement, research labs at AbbVie, Servier, Pfizer and Alkermes started independent experiments aiming to reproduce and extend published evidence. More than a dozen experiments conducted by these four independent teams failed to detect robust effects of ketamine on markers reported to be affected in the original study by Li et al. (2010). Thus, detection of the effects of ketamine on mTOR seem to require special conditions that are difficult to identify and establish, at least in some labs. Present results emphasize the importance of publishing detailed methods either within the paper or as supplementary material. This information is essential for follow-up studies that any significant research is likely to trigger. Further, our efforts to identify individual labs that tried to establish ketamine’s effects on mTOR highlight the need for a peer-to-peer mechanism of information exchange such as the one being developed by the ECNP Preclinical Data Forum.",
"keywords": [
"ketamine",
"depression",
"mTOR",
"data robustness",
"data sharing"
],
"content": "Introduction\n\nIntravenous ketamine has been shown to induce a rapid and long-lasting antidepressant effect in treatment-resistant patients (Zarate et al., 2006a) and the results have been replicated by several groups (Aan Het Rot et al., 2012). Intravenous route of administration as well as concerns due to psychotomimetic potential of ketamine have triggered a search for alternative medications with improved safety and pharmacokinetic profiles. Ketamine is usually described in the literature as an antagonist acting at N-methyl-d-aspartate (NMDA) subtype of glutamate receptors, and pilot clinical data indicated that its antidepressant effects may be shared at least to some extent by other drugs from this class (e.g. CP 101,606; Preskorn et al., 2008). However, other non-competitive NMDA receptor antagonists appear to lack ketamine’s efficacy at least at the doses free from psychotomimetic effects (memantine: Zarate et al., 2006b; AZD-6765: Sanacora et al., 2014). These controversial findings have called for a deeper understanding of specific biological mechanisms of ketamine’s action.\n\nLi et al. (2010) presented a set of data indicating that, in rats, antidepressant-like action of ketamine may be mediated by the activation of mTOR-dependent intracellular cascades. The phosphatidylinositol 3-kinase (PI3K)–Akt–mTOR pathway responds to a variety of growth factors and mitogenic signals and, when activated, mTOR has multiple functions including facilitated translation of proteins involved in synaptic plasticity and memory. In the study by Li et al. (2010), acute injection of ketamine activated the mTOR pathway, leading to increased synaptic signaling proteins and increased number and function of new spine synapses in the prefrontal cortex of rats. Therefore, assuming that something similar can occur in humans, these data may indeed explain why acute infusion of ketamine produces such long-lasting effects in patients with major depression.\n\nAs these results were reproduced by the same group (Liu et al., 2013) as well as by other academic groups (Yang et al., 2013), ketamine-induced mTOR activation seemed to be a robust finding worth further exploration. These effects were observed under a variety of experimental conditions (e.g. using fresh and frozen tissue; Li et al., 2010; Paul et al., 2014) and appeared to be quite robust (note low sample sizes in some of the studies: n=3 in Paul et al., 2014; n=4 in Li et al., 2010).\n\nTherefore, without any coordination or pre-existing agreement, research labs at AbbVie, Servier, Pfizer and Alkermes started independent experiments aiming to reproduce and extend published evidence.\n\n\nMaterials and methods\n\nAnimals. Male Sprague-Dawley rats (150–250 g, Charles River, Germany) were pair-housed, had access to food and water ad libitum and were maintained on a 12-h light/dark cycle in standard cages. Experimental procedures were approved by AbbVie’s Animal Welfare Office (Ludwigshafen, Germany) and were performed in accordance with the European and German national guidelines as well as the recommendations and policies of the U.S. National Institutes of Health “Principles of Laboratory Animal Care”. Animal housing and experiments were conducted in facilities fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC).\n\nDrug administration and harvesting of tissue. Ketamine was purchased either as a 10% solution (WDT, Garbsen, Germany) or as a powder from Sigma-Aldrich (Cat. No.: K2753) and prepared according to the Ketaset® solution (100 mg/mL ketamine and 0.1 mg/mL benzethonium chloride as a preservative in AMPUWA water [Fresenius Cat.No.: 1080153] at a slightly acid solution [pH=3.5 to 5.5]). The animals were given different ketamine concentrations intraperitoneal (i.p.) either one hour or three hours before being killed or different ketamine concentrations intravenous three hours before being killed. Thirty minutes after ketamine administration some animals underwent a forced swim test. Animals were either killed with an overdose of isoflurane or with a guillotine without anesthesia. The prefrontal cortex, cerebral cortex and/or the hippocampus were dissected from the brain on ice. The brain samples were immediately frozen and stored at -80°C for further analysis.\n\nPreparation of synaptosomal fraction and Western blotting. The brain samples were kept on ice during all stages of the preparation. The tissue was homogenized in 8µl preparation buffer per mg tissue. The preparation buffer contained 10 mM Tris-HCl, 0.32 M sucrose, protease inhibitor complete tablets mini with EDTA (Roche Cat. No.: 04693124001) and phosphatase inhibitor cocktail III (according to the Calbiochem mixture: 10 mM NaF, 0.2 mM Sodium Orthovanadate, 2 mM Sodium Pyrophosphate decahydrate, 2 mM Glycerophosphate). The brain samples were homogenized with a Teflon-glass tissue grinder (pre-cooled, clearance 0.25 mm) with 10 even strokes (one stroke equals one up and one down action; the first stroke was about 5 s and subsequent strokes around 3–4 s) using a motor-driven pestle at 650 rpm. The homogenate was centrifuged 5 min at 1000 × g and contained a pellet (P1), which was discarded and the supernatant (S1).\n\nFor the crude synaptosomes the supernatant (S1) was centrifuged for 30 minutes at 15,000 × g. The resulting pellet was resuspended in ~20µl preparation buffer. The protein concentration was determined by the BCA protein assay according to the manufacturer’s instructions (Thermo Scientific Cat. No.: 23227).\n\nFor the synaptosomal fraction of the Percoll method the supernatant (S1) was transferred to a discontinuous Percoll-Gradient containing layers (2%, 6% and 23% Percoll [Sigma-Aldrich Cat.No.: 77237-500ml] in preparation buffer) and centrifuged for 5 min at 33000 × g. The layer between 6% and 23% Percoll (synaptosomal fraction) was collected and diluted with preparation buffer at least 4 times the collected volume and centrifuged for 10 min at 33000 × g. The resulting pellet (P2) contained the synaptosomal fraction and was resuspended in preparation buffer. The protein concentration was determined by the BCA protein assay according to the manufacturer’s instructions (Thermo Scientific Cat.No.: 23227).\n\nFor Western blotting, equal amounts of protein (24 µg) for each sample were boiled in an E-PAGETM loading buffer (Invitrogen Cat.No.: EPBUF-01)/NuPAGE sample reducing agent (Invitrogen Cat.No.: NP0009) for 5 minutes, cooled down and applied on the E-PAGETM 48 8% gel (Invitrogen Cat.No.: EP048-08). The electrophoresis was run on an Invitrogen electrophoresis device either a Mother E-BaseTM device connected to a power source or a Daughter E-BaseTM connected to a Mother E-BaseTM. Two standard samples (MagicMarkTM XP Western Protein Standard [Invitrogen Cat.No.: LC5602] [marker] and SeeBlue® Plus2 Pre-stained Protein Standard [Invitrogen Cat.No.: LC5925] [marker]) were run in parallel to the samples for 24 minutes. After completion of the run the gel was removed and subjected to the Invitrogen semi-dry blotting procedure. Proteins were transferred to a nitrocellulose blotting membrane with a pore size of 0.2 microns (Invitrogen Cat.No.: IB3010-01). The membrane was dried and stored at 4°C for further analysis.\n\nFor the following steps the Invitrogen WesternBreeze Chemiluminescent Western Blot Immunodetection Kit for primary antibodies made in mouse (Invitrogen Cat. No.: WB7104) or for primary antibodies made in rabbit (Invitrogen Cat. No.: WB7106) was used. The membrane was allowed to come to room temperature, incubated 30 minutes in a blocking solution from the kit on a shaker, washed twice with deionized water and incubated with a Primary Antibody Solution for at least 1 hour at room temperature on a shaker. The membrane was washed four times for 5 minutes with a prepared Antibody Wash (included in the kit) and incubated in a Secondary Antibody Solution for 30 minutes. After washing the blots four times with Antibody Wash and rinsing it twice with deionized water the bands were detected using the Chemiluminescent Substrate Solution (included in the kit). The chemiluminescense intensity of the bands was quantified by a CHEMI DOC XRS imaging system (Bio-Rad Laboratories GmbH, Munich, Germany) utilizing an Universal Hood II enclosure.\n\nThe following proteins were analyzed for samples taken 1 hour after ketamine injection: phospho-p70S6 Kinase, phospho-Akt (Ser 473), Arc (C-7), phospho-mTor (Ser2448), phospho-S6 Ribosomal Protein (Ser 235/236) and phospho-p44/42 MAP Kinase (Erk1/2) (Thr 202/Tyr 204). The following markers were analyzed for samples taken 3 hours after ketamine application: Arc(C-7), Synapsin I, GluR-1 (E-6), phospho-S6 Ribosomal Protein (Ser 235/236) and PSD-95 (7E3). For details see Table 1 and Table 2.\n\nWB: Western blot analysis; CE: Capillary electrophoresis; *Antibody dilution optimized for ProteinSimple WES capillary electrophoresis system\n\n* conditions and markers reported by Li et al. (2010)\n\nAnimals. Male Sprague-Dawley rats (150–200 g, Charles River, Wilmington, MA, USA) were pair-housed and allowed to acclimate for three days before handling. Animals had access to food and water ad libitum and were maintained on a 12-h light/dark cycle in standard cages. All procedures related to animal care and treatment were conducted under an Institutional Animal Care and Use Committee-approved protocol, according to the guidelines of the National Research Council Institute for Laboratory Animal Research Guide for the Care and Use of Laboratory Animals and the US Department of Agriculture Animal Welfare Act and Animal Welfare Regulations.\n\nDrug administration and tissue collection. Ketamine HCl (Ketaset® 100 mg/mL; Fort Dodge Animal Health, IA, USA) was used to prepare a 10 mg/mL solution in sterile 0.9% saline for injection. Rats received a single acute i.p. dose of either ketamine solution or saline appropriate for their body weight. Animals were sacrificed by live decapitation at 0.5, 1, 2, 6, or 24 hours post dose (n=5). Brains were removed and placed on wet ice for immediate dissection and homogenization, while trunk blood was collected in EDTA tubes to measure drug concentrations.\n\nPreparation of synaptosomal fraction and Western blotting. The brains were removed and prefrontal cortex was hand dissected on wet ice. The tissues were placed directly into tubes containing 1 mL of cold Buffer A (Li et al., 2010) and the tube contents (tissue and buffer) were poured directly into a dounce homogenizer and manually dounced 5 times on ice. The homogenized samples were centrifuged at 614 × g for 10 minutes at 4°C (P1 sample is the pellet). The supernatant was removed and centrifuged at 11,269 × g for 10 minutes at 4°C (P2 is the pellet). The supernatant was removed and fresh RIPA buffer (Li et al., 2010) was added to the pellet (400 μL) just prior to probe sonication. The sonicated samples were centrifuged for 1 minute at the maximum speed of a table top centrifuge (approximately 14000 rpm) and a protein assay was run on the supernatants to normalize gel loading. The samples (15 μg per well) were run on a 4–20% gradient tris-glycine gel and then wet transferred to nitrocellulose membranes for Western blotting. Blots were scanned on an Odyssey 9120 infrared scanner (Li-Cor, Lincoln, NB, USA). Local background was subtracted from all bands prior to normalizing each phospho-protein of interest to its control. For details on the antibodies being used see Table 1.\n\nAnimals. Adult male Sprague Dawley rats (300–400g; Charles River, France) were housed in pairs in a temperature controlled room with food and water ad lib and under a 12-h light/dark cycle with lights on from 8 am. All procedures were performed in conformity with the National (JO 887-848) and European (86/609/EEC) legislations on animal experimentation.\n\nDrug administration and harvesting of tissue. Animals were anesthetized with pentobarbital (60 mg/kg ip); ketamine was administered (10 mg/kg i.p.; ketamine hydrochloride, LGC Standards) immediately after. Animals were sacrificed 30 min after ketamine administration under isoflurane anesthesia. Brains were dissected into medial and lateral cortices, dorsal and ventral hippocampi and were snap frozen as previously described (Svenningsson et al., 2000) and stored at -80°C until processed.\n\nPreparation of synaptosomal fraction and Western blotting. The cortical samples were sonicated in 1% sodium dodecyl sulfate (SDS), 10mM NaF, transferred to Eppendorf tubes and boiled for 10 min. The protein concentration in each sample was thereafter determined with a BCA-based kit (Pierce, Rockford, Il, USA). Twenty five micrograms of each sample was re-suspended in sample buffer and separated by SDS-PAGE using a 12% running gel and transferred to an Immobilon P transfer membrane (Millipore). The membranes were incubated for 1 h at room temperature with 5% (w/v) dry milk in TBS-Tween 20. Primary antibodies were diluted in 5% dry milk dissolved in TBS-Tween 20 and immunoblotting was performed overnight. Membranes were washed three times with TBS-Tween 20 and incubated with secondary HRP anti-rabbit antibody for 1 h at room temperature. At the end of the incubation, membranes were washed six times with TBS-Tween 20 and the immunoreactive bands were detected by chemiluminescence using ECL reagents (Perkin Elmer). A series of primary, secondary antibody dilutions and exposure times were used to optimize the experimental conditions for the linear sensitivity range of the autoradiography films (Kodak Biomax MR). Films were scanned and the density of each band was quantified using the NIH ImageJ 1.63 software. The levels of phosphorylated proteins were normalized to total levels.\n\nAnimals. Male Sprague Dawley rats (275–300 g; Charles River, Kingston, NY, USA) were pair-housed and allowed to acclimate to the animal colony and handled for at least 3–4 days prior to experimentation. Rats were maintained on a 12:12-h light-dark cycle (0600:1800 h light; 1800:0600 h dark) with a room temperature of 22±3°C and a relative humidity level of 45±10%. Food and water were available ad libitum and rats used for these studies were housed, managed and cared for in accordance with the Guide for the Care and Use of Laboratory Animals (National Research Council, 2011). All experiments were approved by the Alkermes Institutional Animal Care and Use Committee. Animal studies conducted by Alkermes were reviewed and approved by its IACUC. All animal work conducted by Alkermes is compliant with PHS policies governing the humane care and use of laboratory animals.\n\nDrug administration and tissue collection. Ketamine HCl (Ketaset® 100 mg/mL; Fort Dodge Animal Health, IA, USA) was used to prepare a 10 mg/mL solution in sterile 0.9% saline for injection. Rats received a single acute i.p. injection of ketamine and were killed 30 min later for phosphorylated mTOR (p-mTOR) or 24 hr for PSD-95 via CO2 asphyxiation followed by decapitation. Brains were removed, placed on wet ice and the prefrontal cortex was free-hand dissected and snap frozen on dry ice. Samples were stored at -80°C until further analysis.\n\nSynaptosomal preparation and capillary electrophoresis. Crude synaptosomes were prepared from frozen prefrontal cortex samples. Tissues were weighed and dounce homogenized (10:1; wt:vol) in ice-cold Syn-PER™ synaptic protein extraction reagent (Thermo Scientific; Rockford, IL, USA) supplemented with Halt™ protease and phosphatase inhibitor cocktail (1X, Thermo Scientific). Homogenates were centrifuged at 1200 × g for 10 min at 4°C. The supernatant was centrifuged at 15,000 × g for 20 min at 4°C. After centrifugation, the supernatant was discarded and pellets were resuspended in 200 μL of Syn-PER reagent with inhibitors and proteases. Protein concentration was determined by BCA protein assay according to the manufacturer’s instructions (Thermo Scientific).\n\nProtein levels were quantified using an automated size resolving capillary electrophoresis system, “WES”, from Protein Simple (San Jose, CA, USA). All procedures were performed according to manufacturer’s instructions. Briefly, 8 μL of 0.1 mg/mL of homogenate was mixed with 2 μL of 5X fluorescent master mix and heated at 95°C for 5 min. The samples, blocking reagent, primary antibody, anti-rabbit secondary antibody, chemiluminescent substrate, and wash buffer were loaded into a microplate provided with a 12-230 kDa WES kit (PSD-95) or a 66-440 kDa WES kit (p-mTOR). Primary antibodies used were PSD-95 (rabbit; Cell Signaling [#2507]; 1:50) and p-mTOR (rabbit; Cell Signaling [#5536]; 1:50) (see Table 1). Separation and immunodetection was performed automatically using default plate settings for each kit in Compass software (version 2.7.1; Protein Simple, San Jose, CA, USA). Signal and quantitation of immunodetected proteins were generated automatically by Compass software and the data were graphed using GraphPad Prism 6.0 (GraphPad Software, La Jolla, CA, USA).\n\nData are presented as the percentage change from vehicle for each analyte (± SEM). To assess treatment effects of ketamine on p-mTOR, PSD-95 and pp70S6K, pairwise group comparisons were conducted using two-tailed t-test (GraphPad Prism 6.0, San Diego, CA, USA).\n\n\nResults\n\nMore than a dozen independent experiments conducted by these four teams failed to detect robust effects of ketamine on markers reported to be affected in the study by Li et al. (2010). Given the number of studies and markers analyzed, vehicle- and ketamine-treated groups occasionally appeared to be different but there were no overall consistent and robust differences. Figure 1, Figure 2 and Figure 3 present results from the studies that assessed effects of ketamine on pmTOR, PSD-95 and pp70S6K. Table 2 summarizes experimental conditions that were systematically manipulated in order to enable detection of ketamine-induced biochemical effects.\n\nValues represent mean ± SEM, n is indicated in the bars for each independent experiment, *p<0.05; student’s t-test. Samples were collected at different time points after drug application as indicated in the figure. Karolinska-Servier distinguished between the medial (m PFC) and lateral (lat PFC) prefrontal cortex.\n\nValues represent mean ± SEM, n is indicated in the bars for each independent experiment, *p<0.05; student’s t-test. Samples were collected at different time points after drug application as indicated in the figure.\n\nValues represent mean ± SEM, n is indicated in the bars for each independent experiment, *p<0.05; student’s t-test. Samples were collected at different time points after drug application as indicated in the figure.\n\nIndependent correspondence with Ronald Duman (senior author in the Li et al. publication) and S. Popp (AbbVie) or J. Joshi (Pfizer) did not help to identify methodological factor(s) that may account for the failure to reproduce ketamine’s effects.\n\n\nDiscussion\n\nWhat makes clinical effects of ketamine quite appealing is that they are strong enough to be seen even in small studies conducted by different institutions under varying conditions. In contrast, effects of ketamine on mTOR seem to require special conditions that are difficult to identify and establish at least in some labs. Many of these phosphorylation events are very sensitive, and subject to high amounts of variability even when environmental conditions are well-controlled. Thus, these kinds of measurements may not be reliable pharmacodynamic markers of efficacy.\n\nTaken together, these data call into question the robustness of the preclinical ketamine mTOR findings and challenge the mTOR hypothesis of ketamine’s antidepressant action. We would also like to emphasize the importance of publishing detailed methods either within the papers or as supplementary materials. This information is essential for follow-up studies that any significant research is likely to trigger.\n\nEfforts to identify individual lab efforts to establish ketamine’s effects on mTOR have followed the peer-to-peer mechanism of information exchange that is being developed by the ECNP Preclinical Data Forum (https://www.ecnp.eu/projects-initiatives/ECNP-networks/List-ECNP-Networks/Preclinical-Data-Forum.aspx) and is suggested as a general tool to identify unpublished data that, when put together and disclosed, could present a value to the scientific community.\n\nWe feel that information about failed attempts to establish ketamine’s effects should be disclosed to allow scientific community to judge on the robustness of these effects.\n\nAfter the manuscript was prepared for submission, the authors have received information from colleagues at the Lilly Research Labs, Indianapolis, IN USA (H. Wang, J.M. Witkin, and J.W. Ryder, personal communication) that their lab was also unable to establish effects of ketamine on p-mTOR(pS2448), consistent with the data reported in this manuscript.\n\n\nData availability\n\nF1000Research: Dataset 1. Figure 1 raw data, 10.5256/f1000research.8236.d117437 (Popp et al., 2016a).\n\nF1000Research: Dataset 2. Figure 2 raw data, 10.5256/f1000research.8236.d117438 (Popp et al., 2016b).\n\nF1000Research: Dataset 3. Figure 3 raw data, 10.5256/f1000research.8236.d117439 (Popp et al., 2016c).",
"appendix": "Author contributions\n\n\n\nStudy design: SP, BB, MS, TL, PS, ES, TMJ, JC, DD, AB; Conducted experiments: SP, BB, DC, JJJ, TMJ, JC; Analysis: SP, MS, ES, BB, DC, PS, DD; Writing: AB, SP, TL, DD.\n\n\nCompeting interests\n\n\n\nNo other interests beyond employment indicated in this manuscript. MS was a Servier employee at the time when studies were conducted.\n\n\nGrant information\n\nThis research was funded by AbbVie (SP, BB, AB), Pfizer (TL, JJJ), Servier (ES, PS, DC, TMJ), Alkermes (JC, DD), INSERM (TMJ) and IMI-Newmeds (TMJ).\n\n\nReferences\n\nAan Het Rot M, Zarate CA Jr, Charney DS, et al.: Ketamine for depression: where do we go from here? Biol Psychiatry. 2012; 72(7): 537–547. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLi N, Lee B, Liu RJ, et al.: mTOR-dependent synapse formation underlies the rapid antidepressant effects of NMDA antagonists. Science. 2010; 329(5994): 959–964. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu RJ, Fuchikami M, Dwyer JM, et al.: GSK-3 inhibition potentiates the synaptogenic and antidepressant-like effects of subthreshold doses of ketamine. Neuropsychopharmacology. 2013; 38(11): 2268–2277. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPaul RK, Singh NS, Khadeer M, et al.: (R,S)-Ketamine metabolites (R,S)-norketamine and (2S,6S)-hydroxynorketamine increase the mammalian target of rapamycin function. Anesthesiology. 2014; 121(1): 149–59. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPopp S, Behl B, Joshi JJ, et al.: Dataset 1 in: In search of the mechanisms of ketamine’s antidepressant effects: How robust is the evidence behind the mTor activation hypothesis. F1000Research. 2016a. Data Source\n\nPopp S, Behl B, Joshi JJ, et al.: Dataset 2 in: In search of the mechanisms of ketamine’s antidepressant effects: How robust is the evidence behind the mTor activation hypothesis. F1000Research. 2016b. Data Source\n\nPopp S, Behl B, Joshi JJ, et al.: Dataset 3 in: In search of the mechanisms of ketamine’s antidepressant effects: How robust is the evidence behind the mTor activation hypothesis. F1000Research. 2016c. Data Source\n\nPreskorn SH, Baker B, Kolluri S, et al.: An innovative design to establish proof of concept of the antidepressant effects of the NR2B subunit selective N-methyl-D-aspartate antagonist, CP-101,606, in patients with treatment-refractory major depressive disorder. J Clin Psychopharmacol. 2008; 28(6): 631–637. PubMed Abstract | Publisher Full Text\n\nSanacora G, Johnson M, Khan A, et al.: Adjunctive lanicemine (AZD6765) in patients with major depressive disorder and a history of inadequate response to antidepressants: primary results from a randomized, placebo-controlled study (PURSUIT). Poster presented on 18 June at the 2014 American Society of Clinical Psychopharmacology Annual Meeting in Hollywood, FL, 2014.\n\nYang C, Hu YM, Zhou ZQ, et al.: Acute administration of ketamine in rats increases hippocampal BDNF and mTOR levels during forced swimming test. Ups J Med Sci. 2013; 118(1): 3–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZarate CA Jr, Singh JB, Carlson PJ, et al.: A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry. 2006a; 63(8): 856–864. PubMed Abstract | Publisher Full Text\n\nZarate CA Jr, Singh JB, Quiroz JA, et al.: A double-blind, placebo-controlled study of memantine in the treatment of major depression. Am J Psychiatry. 2006b; 163(1): 153–155. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13300",
"date": "27 Apr 2016",
"name": "John D. Graef",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors have highlighted an important issue concerning the inability to reproduce published data supporting the activation of mTOR-dependent pathways as a potential mechanism for the rapid antidepressant effects of ketamine. The authors have provided in-depth methodological details from all labs involved, allowing for a direct comparison of the experimental procedures carried out by all research groups involved in the study. The authors suggestions of including detailed methods within the manuscript or as supplementary information as well as the disclosure of failed attempts to reproduce published data, are valid and would be a benefit to the scientific community.",
"responses": []
},
{
"id": "13697",
"date": "04 May 2016",
"name": "Eero Castren",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIt is very important that also negative results get published, especially failures to replicate previously published data, in this regard, this paper is welcome. However, I feel that the results and conclusions are presented in an unnecessarily negative light. Although several sites are involved, many of them report essentially pilot data with a very low n. For pm-TOR, the apparently most thorough study from the Alkermes group robustly confirmed the finding of Li et al. at 30 min after ketamine (12 rats in the ketamine and control groups, P= 0.0109) and the other group studying the same time point (Pfizer) found an almost significant increase (P=0.0509) with only 5 and 3 animals in ketamine and control groups, respectively, begging for a replication with higher n. In the Servier/Karolinska/INSERM lab, the assay does not seem to be working, with almost 4 fold differences between samples in the control group and there are too few rats for any clear conclusions. So the only site where the results were clearly not replicated was AbbViel lab, assayed at 1 h after ketamine. To me these data provide evidence that ketamine increases pmTor at 30 min after ketamine, as reported by Li et al, but apparently not at 1 h or later. As pointed out by the authors, phosphorylation events are sensitive and may take place rapidly which may contribute to the finding that pmTor as the mediator of ketamine effects may not be as robust as the initial studies suggest, but altogether I find that the data is presented and discussed in unnecessarily negative light.One source of variation between the groups in the consortium and between them an others is what gets included into PFC. I am wondering whether the consortium attempted to standardize their dissection, at least this was not discussed. The consortium has listed a long list of antibodies used, but data is shown only for 3 targets. Why is that? Please publish the rest of the data as well. In sum, I do not think that this study represents \"failed attempts to establish ketamine's effects\", rather it provides suggestive, albeit not conclusive evidence that pm-Tor levels are increased by ketamine at 30 min, but perhaps not later. The authors correctly point out that methods should be described better",
"responses": []
}
] | 1
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https://f1000research.com/articles/5-634
|
https://f1000research.com/articles/4-1030/v1
|
09 Oct 15
|
{
"type": "Software Tool Article",
"title": "DREAMTools: a Python package for scoring collaborative challenges",
"authors": [
"Thomas Cokelaer",
"Mukesh Bansal",
"Christopher Bare",
"Erhan Bilal",
"Brian M. Bot",
"Elias Chaibub Neto",
"Federica Eduati",
"Mehmet Gönen",
"Steven M. Hill",
"Bruce Hoff",
"Jonathan R. Karr",
"Robert Küffner",
"Michael P. Menden",
"Pablo Meyer",
"Raquel Norel",
"Abhishek Pratap",
"Robert J. Prill",
"Matthew T. Weirauch",
"James C. Costello",
"Gustavo Stolovitzky",
"Julio Saez-Rodriguez",
"Mukesh Bansal",
"Christopher Bare",
"Erhan Bilal",
"Brian M. Bot",
"Elias Chaibub Neto",
"Federica Eduati",
"Mehmet Gönen",
"Steven M. Hill",
"Bruce Hoff",
"Jonathan R. Karr",
"Robert Küffner",
"Michael P. Menden",
"Pablo Meyer",
"Raquel Norel",
"Abhishek Pratap",
"Robert J. Prill",
"Matthew T. Weirauch",
"James C. Costello"
],
"abstract": "DREAM challenges are community competitions designed to advance computational methods and address fundamental questions in system biology and translational medicine. Each challenge asks participants to develop and apply computational methods to either predict unobserved outcomes or to identify unknown model parameters given a set of training data. Computational methods are evaluated using an automated scoring metric, scores are posted to a public leaderboard, and methods are published to facilitate community discussions on how to build improved methods. By engaging participants from a wide range of science and engineering backgrounds, DREAM challenges can comparatively evaluate a wide range of statistical, machine learning, and biophysical methods. Here, we describe DREAMTools, a Python package for evaluating DREAM challenge scoring metrics. DREAMTools provides a command line interface that enables researchers to test new methods on past challenges, as well as a framework for scoring new challenges. As of September 2015, DREAMTools includes more than 80% of completed DREAM challenges. DREAMTools complements the data, metadata, and software tools available at the DREAM website http://dreamchallenges.org and on the Synapse platform https://www.synapse.org.Availability: DREAMTools is a Python package. Releases and documentation are available at http://pypi.python.org/pypi/dreamtools. The source code is available at http://github.com/dreamtools.",
"keywords": [
"DREAM",
"collaborative competition",
"machine learning",
"crowdsourcing",
"systems biology",
"translational medicine",
"method evaluation",
"benchmarking"
],
"content": "Introduction\n\nCrowd-sourcing has gained considerable attention over the last years as an approach to solve complex problems. A specific variant of crowd-sourcing is based on setting up challenges or collaborative competitions, whereby the scientific community is invited to provide solutions for a given problem. Typically, the challenge organizers withhold a gold standard and use it to evaluate the performance of the submissions by comparing the latter to the former. At the end of such an exercise, the organizers perform a meta analysis with the aim of deriving lessons about which type of methods seem to be more suitable, which features seem to be good predictors regardless of the method, etc. Importantly, the challenge’s results remain as a resource for the community representing a snapshot of the state-of-the-art and to aide in further method development and benchmarking.\n\nIn the context of computational biology, there have been several of these initiatives, including CASP, CAFA, CAPRI, FlowCAP1, CAGI, and Dialogue for Reverse Engineering Assessment and Methods (DREAM; www.dreamchallenges.org)2. The DREAM challenges started with a focus on the field of biomolecular network inference3–5 but now cover questions ranging from prediction of transcription factor sequence specificity6, to toxicity of chemical compounds7 and the progression of Amyotropic Lateral Sclerosis (ALS) patients8 or survival of breast cancer patients9. Since 2013, DREAM has partnered with Sage Bionetworks and challenges are hosted on Sage’s Synapse platform. Each challenge has a dedicated project space in Synapse where the description, training data set, gold standard and scoring methodology are provided. The scored predictions are also available on a public leaderboard.\n\nA fundamental step in DREAM challenges, or any other collaborative competition, is to assess how well the different predictions fare against the gold standard. This may seem obvious at first glance; for example, for a question of predicting a set of numbers, one can compute the sum of the squared differences between predicted and observed values, and identify the submission for which this sum is the smallest. However, multiple aspects have to be taken into account such as the fact that often the confidence on the different measured values is not the same, or that the differences between the submissions may or may not be different enough to declare one method superior to the other. Over the years, within the DREAM challenges, these questions have been addressed leading to the generation of multiple scoring methods.\n\nScoring methods developed by challenge organizers are reported in the publications that describe the challenges, but the corresponding code is typically provided only in pseudo-code or at best as a script in an arbitrary language (R, Python, Perl...) and syntax by different developers leading to a set of heterogeneous code. In addition, templates and gold standards need to be retrieved manually. All of these factors present obstacles to maximize the scientific value of DREAM challenges as a framework for a posteriori evaluation of a method’s performance in comparison with those used in the challenges. Similarly, reuse of scoring code for future challenges becomes complicated when at all possible.\n\nTo facilitate the a posteriori use of the challenges resources by the scientific community, we have gathered DREAM scoring functions within a single software called DREAMTools that provides a single entry point to the DREAM scoring functions. We also provide a standalone executable for end-users and the ability to share and re-use existing code within a common framework to ease the development of new scoring functions for future challenges. DREAMTools does not provide code to generate the data or to manage leaderboards (which happens within Synapse), but focuses on the scoring functions. Note that organizers interested in setting up automatic scoring and publishing of leaderboards should instead refer to the section ‘Create a Scoring application’ from the Synapse project 2453886. Currently, DREAMTools includes about 80% of the past challenges. For a few challenges where integration in DREAMTools was not possible, references to external resources are provided.\n\nHere, we first describe the framework used in DREAMTools software from the point of view of both an organizer/developer and an end-user. We then review the challenges and the scoring functions that are available until now.\n\n\nMethods\n\nThe diversity of challenges proposed by DREAM (see Available challenges section) and the plethora of languages that have been used in past challenges has led to a fragmentation of the software designed to score submissions. In order to tackle this problem, we chose Python as a glue language. In addition to a clear syntax and the ability to scale-up software, Python can include compiled codes (e.g., Fortran and C) or call other scripting languages (Perl, R). Besides, languages such as Ruby or MATLAB can also be easily translated to Python, which was an invaluable asset to incorporate many of the earlier challenges that were originally encoded in MATLAB.\n\nDREAMTools is an open-source library. Consequently, it can be used directly to evaluate a method against the gold standard of the corresponding challenge, and can also be used as a framework to develop further scoring schemes within the DREAM umbrella or elsewhere.\n\nWith about four challenges a year, we use a convention to easily refer to a given DREAM challenge. We decided to closely follow the convention adopted on the DREAM website and use a nickname that takes the form DXCY, where X is set to the DREAM version and Y is set to the challenge number. For example, the HPN-DREAM Breast Cancer challenge10 will be referred to as D8C1. If a challenge has sub-challenges, we will also need to provide names to identify them. We do not enforce any convention on sub-challenge names. The nicknames can be found here below in Table 1.\n\nThe first column provides the nickname used in DREAMTools to refer to a challenge. The challenge’s title (second column) and its Synapse identifier (fourth column) can be used to retrieve all details about a challenge. The third column gives the challenge status within DREAMTools: most of the challenges’ scoring functions are implemented in DREAMTools (green boxes); open challenges are not yet available (blue boxes); a couple of challenges did not release the gold standard and may not be implemented (red boxes labelled ’No GS’ for no gold standard); some are to be implemented in future releases (orange boxes labelled ’TBD’ for to be done).\n\nIn this section we provide a brief overview of these functions, and for further details we point the reader to the detailed documentation on https://pypi.python.org/pypi/dreamtools/.\n\nDREAMTools provides a standalone application called dreamtools, which is installed with the DREAMTools library (see Installation section for details). Note that the application’s name uses lower cases to facilitate the user’s experience. The dreamtools application needs a few arguments. The first argument is the challenge name using --challenge followed by the challenge nickname (e.g., D7C2). The second compulsory argument is the filename containing the prediction or submission using the --submission or --filename argument. Some challenges have sub-challenges, in which case an extra argument called --sub-challenge is added. Let us consider the case of the D3C3 challenge (Gene Expression Prediction)11. In order to obtain the score, call dreamtools as follows:\n\n\n\nThe scoring function of that particular challenge returns a score based on a Spearman rank correlation. Other challenges may return more complex information.\n\nThe dreamtools standalone application allows one to quickly compute the score of a prediction. However, users or developers may want to script it, which remains concise as shown in the following Python script:\n\n\n\nNote that all challenges follow the same structure with three main functions: to retrieve a template example, to retrieve a gold standard, and to score a prediction. In addition, dreamtools may give access to more functions. For example, the D5C2 challenge6 has a plot method to compare a prediction with the official submissions, that facilitates inspection of the results, as shown in Figure 2. The figure is generated with an IPython notebook12, which is available in the source code repository of DREAMTools.\n\nAnother useful option from the dreamtools executable is the --info option, which provides information such as the title and summary of the challenge but also the list of sub-challenges and the Synapse project page where all details about the challenge can be found:\n\n\n\nMost challenges require a gold standard to score a prediction. Small-size gold standards are provided within the library and, to keep DREAMTools light-weight, large-size gold standards are stored through Synapse and automatically downloaded when required – using the official Synapse client (see Sec about installation and dependencies). A similar strategy is applied to templates. Users will need to have a login on the Synapse platform to access these files. The downloaded files are stored locally in a standard place (e.g., /home/user/.config/dreamtools directory under Linux systems).\n\nUsers can retrieve the location of the templates and gold standards with the dreamtools application as follows:\n\n\n\nIf sub-challenges are available, a sub-challenge name must be provided. The valid sub-challenge names can be obtained with the --info argument:\n\n\n\nDREAMTools library also provides a framework to ease the addition of other challenges by encouraging the usage of a consistent layout. In order to incorporate a new challenge, a developer can look at previous instances and create manually its own tree structure. However, we provide another standalone application called dreamtools-layout. This application requires only one argument: the challenge nickname.\n\n\n\nThis command creates a directory named after the challenge nickname. Inside the directory, sub-directories are created to store the templates, gold standards and possibly other data sets. For instance, data to compute p-values may be stored in the data directory. Code related to training data generation could be stored in the generator directory, and so on.\n\nIn addition to the tree directory, some files are created amongst them a README file that should be filled with information about the challenge (e.g. Synapse identifier, acronym, summary) and a Python script called scoring.py. The basic structure of the scoring script is to provide the same interface for each challenge. In particular, we enforce the implementation of a function to download a template, a function to download a gold standard and a function to score the submission. Here is an example of such a file, which needs to be filled by the developer:\n\n\n\nDREAM challenges are described at the DREAM website (http://dreamchallenges.org) where researchers can get an overview of the past and current challenges. Each challenge has its own project page within the Synapse framework (http://synapse.org) where details about the challenge are available. The final leaderboard showing benchmarks achieved at the end of the challenge are also shown in the Synapse project. DREAMTools provides a Python library that allows researchers to retrieve a template for each closed challenge and to easily score a prediction/template against the gold standard. In a few lines of code, the score of a prediction can then be compared to the official leaderboard, as illustrated in the example in the green box on the right hand side of the figure.\n\nUsing the code above, the challenge will be automatically available in the standalone application without extra costs to the developer. The download_template( ) method is not strictly speaking required; it helps a user to create a prediction though and is provided for all challenges. Developers should consider adding tests and documentation in the existing framework. The last release of DREAMTools contains a test suite (collection of test cases used to check the software) with a code coverage higher than 80%; it guarantees that the DREAMTools functionalities (especially the scoring functions) do work as expected.\n\nThe source code of the DREAMTools software library is available on GitHub. It can be downloaded as follows:\n\n\n\nThen, the following commands should install the library\n\n\n\nThe source code is not required strictly speaking. Indeed, releases are provided on the Python repository website (pypi/dreamtools) and consequently, the pip tool can be used in a shell command:\n\n\n\nDREAMTools relies on established scientific libraries such as Pandas13 for the data mangling, SciKit-learn14 for some computations (e.g., ROC curves) and more generally NumPy/SciPy15 for statistical analysis. Those libraries are recognized in the scientific community and there is an ample set of on-line resources that cover installation procedure.\n\nIn order to keep DREAMTools light-weight, we mentioned earlier that we keep large files in Synapse. DREAMTools will then download files automatically on request. The download is achieved using the Python Synapse client (also available for the R language).\n\nHowever, as shown in this figure, other functions may be provided. For instance, the plot() method available in the D5C2 challenge shows 4 sub-figures with the score of a submission (blue square) compared to the official participants (black crosses) for 4 metrics (AUROC, AUPR, Spearman versus Pearson correlation). This example is available as an IPython notebook in the DREAMTools repository.\n\n\nAvailable challenges and scoring metrics\n\nDREAMTools covers about 80% of the past DREAM challenges, as shown in Table 1. Although there is a wide range of biological problems addressed in the DREAM challenges, most of the scoring functions revolve around a set of established methods. A majority of the challenges are posed as binary classification questions. Here, scoring metrics compare the predictions against a gold standard and derive metrics such as the AUROC (area under the receiver operating characteristic) or AUPR (area under the precision/recall curve). The rest of the challenges are posed as prediction of quantitative values, and use scoring metrics that compare the predicted values and gold standard by computing their correlation, either between the actual values using e.g. Pearson correlation, or between their ranks, using either Spearman’s rank correlation or concordance index (CI).\n\nSome final scores are based on the empirical null distribution of random sets of predictions so that the final scores are p-values. In addition, while scoring metrics such as Spearman’s rank correlation provide an absolute value that can be compared to the leaderboard, in some cases the rank of the prediction when compared to the other participants is also involved in the scoring. In such cases, even if the scores reported in DREAMTools use the same scoring functions as those used while the challenge was open, the score reported by DREAMTools may be different from what can be found in the published leaderboard.\n\nIn this section we provide a short description of each challenge and the scoring metric(s) used. Details about the methods can be found in the Supplementary material (see Section 1). Full details about the data format and scoring metrics for each of those challenges can be found on the dedicated Synapse project, whose identifiers are provided in Table 1. We will use the following conventions whenever possible: the final score (if unique) is denoted S. A rank is denoted R. A p-value is denoted p with a label (e.g., p-value of the AUROC metric is denoted pAUROC). The gold standard data set is denoted X and a prediction from a participant is denoted X^.\n\nDREAM2 conducted 5 challenges16. The scoring functions are all based on the AUROC and AUPR metrics (see Supplementary material for details).\n\nDescription: BCL6 is a transcription factor that plays a key role in both normal and pathological B cell physiology. The intersection of two independent data sets of transcriptional targets of BCL6 (based on (i) ChIP-on-ChIP data and (ii) molecular perturbations) provided 53 functional BCL6 gene targets. In this challenge a set of 147 decoy genes were randomly selected (with no evidence of being BCL6 targets) and combined with the 53 functional BCL6 genes to a list of 200 genes in total. The challenge consisted of identifying which genes are the true targets (and the decoys); to do so, participants were given an independent panel of gene expression data17.\n\nScoring metric: Using a binary classifier, the AUPR and AUROC metrics are computed.\n\nDescription: The challenge consisted of determining the set of true positive and true negative protein-protein interactions among all the pairwise interactions possible within a network of 47 proteins (yeast)16.\n\nScoring metric: The list of gene pairs are ordered according to the confidence. Using a binary classifier and a gold standard of gene pairs, the AUPR and AUROC metrics are computed.\n\nDescription: In this challenge, a 5-gene synthetic-biology network was created and transfected to an in vivo model organism. Participants were asked to predict the connectivity of this network using in vivo measurements. Two slightly different networks were built using quantitative PCR or Affymetrix chips. Each version had 6 variants depending on the nature of the networks (e.g., signed vs unsigned networks).\n\nScoring metric: Each submitted network is scored independently using the AUPR and AUROC metrics.\n\nDescription: Three in silico networks were created and endowed with deterministic dynamics that simulate biological interactions. The challenge consisted in reverse engineering those networks. The first and second networks had about 50 nodes and 100 directed edges with Erdos-Renyi and scale-free topology, respectively. The third network was a full in-silico biochemical network with 23 proteins, 24 metabolites and 20 genes through 146 directed edges16. Each network had 5 variants depending on the nature of the networks (e.g., signed vs unsigned networks).\n\nScoring metric: Same as D2C3.\n\nDescription: A panel of normalized E. coli Affymetrix microarrays were provided. The challenge consisted of reconstructing a genome-scale transcriptional network of 3456 genes and 320 transcription factors18.\n\nScoring metric: Same as D2C3.\n\nDREAM3 had 5 challenges fully described in 19.\n\nDescription: Protein concentrations of four intracellular proteins involved in a signaling cascade were measured in single cells by antibody staining and flow cytometry. The task was to identify each of the measured proteins from among the seven molecular species: complex, kinase, phosphorylated complex, phosphorylated protein, protein, phosphatase, and activated phosphatase)3.\n\nScoring metric: The number of correctly assigned protein identities. Final score is the probability of having k or more correct predictions as compared to a random assignment.\n\nDescription: The goal of this challenge was to predict the response to perturbations of a signaling pathway in normal and cancer human hepatocytes. There were 2 sub-challenges: (i) prediction of a subset of phosphoproteomic data points measured but removed from normal and cancer hepatocytes data sets (ii) prediction of the concentration of the 20 cytokines measured but removed from the training data sets3,4.\n\nScoring metric: The distance between the prediction and gold standard is computed as the normalized squared error E:\n\n\n\nwith i a time index, σb = 0.1 represents a baseline, signal independent, measurement noise and σs = 0.2 represents a signal dependent measurement noise. Finally, a probability distribution for this metric was estimated by simulation of a null model and a p-value reported as the final score.\n\nDescription: Gene expression time course data were provided for four different strains of yeast (S. cerevisiae): one wild type and three mutants11. Participants were asked to predict the relative expression levels for 50 genes (not part of the training data set) at eight time points in one mutant. For each time point, predictions were submitted as a ranked list (with values from 1 to 50 sorted from most induced to most repressed compared to the wild type expression).\n\nScoring metric: Submissions are scored using Spearman’s rank correlation coefficient between the predicted and measured gene expression at each of the eight time points. The same statistic is also computed with respect to each gene across all time points. Thus, two tests of similarity to the gold standard are computed (time-profiles T and gene-profiles G). P-values are computed using a test for association between paired samples. The final score is:\n\n\n\nwhere pT and pG are the p-value for the time-profiles and gene-profiles, respectively.\n\nDescription: The goal of this challenge was to reverse engineer a gene network from time series and steady state data. Participants were asked to predict the directed unsigned network topology from the given in silico generated gene expression data sets3. There were 3 sub-challenges with different network sizes (10, 50 and 100) for 5 different data sets.\n\nScoring metric: For a given sub-challenge, predictions are required to be ranked edge-list. The 5 data set predictions are assessed based on the AUPR and AUROC and their respective p-values. Intermediate scores are computed using the log-transformed average of the p-values:\n\n\n\nand\n\n\n\nThe final score is the mean of those 2 scores.\n\nDescription: Peptide Recognition Domain (PRD) binds short linear sequence motifs in other proteins. Many protein-protein interactions are mediated by PRD. For example, PDZ domains recognize hydrophobic C-terminal tails, SH3 domains recognize proline-rich motifs, and kinases recognize short sequence regions around a phosphorylatable residue20. This challenge consisted of predicting a position weight matrix (PWM) that describes the specificity profile of each of the domains to their target peptides.\n\nScoring metric: PWM predictions are judged exclusively by similarity to the experimentally mapped PWM using the distance induced by the Frobenius norm, defined as the square root of the sum of the absolute squares of its elements:\n\n\n\nIn the kinase case, distances for N = 3 PWMs are computed using the Frobenius distance. The p-values of those distances are computed based on random PWMs (a random PWM is formed by entries with values identically and uniformly distributed such that each column normalizes to one). Final score is then the log-transformed average of these p-values:\n\n\n\nSimilarly for the PDZ and SH3 sub-challenges with N = 4 and N = 3, respectively.\n\nDescription: Similarly to D3C4, the goal of the challenge was to reverse engineer gene regulation networks from simulated steady-state and time-series data. Participants were asked to infer the network structure from in silico gene expression data sets21.\n\nScoring metric: See D3C4 challenge scoring metric.\n\nDescription: Participants were asked to create a cell-type specific model of signal transduction using the measured activity levels of signaling proteins in HepG2 cell lines3.\n\nScoring metric: The score is the sum of squared errors over all the predictions (see Equation 1) for each protein. Then, p-values are computed and the prediction score is defined as Spred=−1N∑iN=7logpi with pi the p-value for a given protein. The final score being:\n\n\n\nwith r a weight per edge computed as the minimum over all participants of the prediction score divided by edge count and Ne the number of edge in the network (asked on the prompt). The parameter r is used to take into account the parsimony of the submitted network.\n\nDescription: Antibody-protein interactions play a critical role in medicinal disciplines (e.g., oncology). Ideally, one specific antibody exclusively binds one specific sequence, however, many antibodies bind to a set of related peptides (or even distinct) and do so with different affinities. A key question is to be able to predict common peptide/epitope sequences that can be recognized by human antibodies. In this challenge, a pool of about 7000 epitope sequences containing peptide sequences reactive with human immunoglobulins was experimentally identified22 to constitute the positive set. Conversely, about 20,000 peptides showed no antibody binding activity and constituted the negative set. Given a training set, the challenge consisted in determining whether each peptide in the test set belongs to the positive or negative set.\n\nScoring metric: The AUROC and AUPR metrics are computed. Their p-values are obtained from null distributions. The overall score is:\n\n\n\nDescription: Transcription factors (TFs) control the expression of genes through sequence-specific interactions with genomic DNA. Modeling the sequence specificities of TFs is a central problem in understanding the function and evolution of the genome. In this challenge, binding preferences of 86 mouse TFs were provided in the form of double-stranded DNA probe intensity signals from protein binding microarrays23. A training data set of 20 TFs was provided and the challenge consisted of predicting the signal intensities for the remaining TFs6. Note that DREAMTools also include a plotting functionality with this challenge (see Figure 2).\n\nScoring metric: Spearman and Pearson correlations as well as AUROC and AUPR metrics are used, however, the Pearson correlation is used for the final ranking.\n\nDescription: In this challenge, participants were asked to predict disease phenotypes and infer gene networks from Systems Genetics data. A first sub-challenge (SysGenA) made of simulated data considered 3 independent network sizes (100, 300 are 999), with 5 networks for each size. A second sub-challenge (SysGenB) provided training sets including phenotype, genotype, and gene expression data. Predictions of two phenotypes were required for 3 independent cases based on (1) only genotype data, (2) only gene expression data, and (3) both genotype and gene expression data24.\n\nScoring metric: In the SysGenA sub-challenge, the final score is a function of AUPR and AUROC metrics (see D3C4 for details). In SysGenB, two phenotypes are scored using Spearman’s rank correlation. Their p-values are computed and the final score is then:\n\n\n\nDescription: The goal of this challenge was to reverse engineer gene regulatory networks from gene expression data sets in E. coli, S. cerevisiae, S. aureus, and an in silico compendium. Each compendium is made of an expression matrix of g genes by c chip measurements. A set of decoy genes (about 5% of the compendium) were introduced by randomly selecting gene expression values from the compendium itself. The software GeneNetWeaver25 was used to create the gene expression profiles for the in silico network.\n\nScoring metric: The final score is a function of AUPR and AUROC metrics (see D3C4 for details).\n\nDescription: RNA-splicing is the process of combining different exons of one gene towards the production of mature mRNA transcripts. Alternative splicing consists of assembling different combinations of exons; it plays an important role in transcriptome diversity including mammals. Shuffling of exons makes it possible for the same gene to code for different proteins. Besides, correct splicing is important for cells to function correctly. The challenge consisted of using short read RNA-seq data from Mandrill and Rhinoceros fibroblasts (about 100 nucleotides) so as to predict as many transcript isoforms as possible (generated by alternative splicing). The gold standard was created using selected target transcripts with read lengths between 1Kb and 2Kb nucleotides.\n\nScoring metric: Predictions are evaluated using the AUPR curve using a global alignment strategy: (1) precision at depth i in the prediction list was obtained by dividing by i the number of predicted transcripts in the first i predictions to which at least a gold standard transcript could be matched with a coverage and an identity of 95% or more. (2) Recall at depth i in the predicted list is calculated by dividing the number of gold standard transcripts that could be matched to the first i predicted transcripts with a coverage and an identity of 95% by the total number of transcripts in the gold standard.\n\nThe AUPR values are computed for hESC (human embryonic stem cells) and Rhino IPSC (induced pluri-potent stem cells). The final score is the sum of the two AUPRs.\n\nThis challenge was about the inference of the kinetic parameters of three gene regulatory networks using iterative optimization and a virtual experimental design26. The challenge was proposed again in DREAM7 (see D7C2 section for details).\n\nDescription: The level by which genes are transcribed is largely determined by the DNA sequence upstream to the gene, known as the promoter region. The challenge consisted of predicting the promoter activity derived by a ribosomal protein (RP) promoter sequence. Participants were given a training set (90 RP promoters) for which both the promoter sequence and their activities are known and a test set (53 promoters) for which only the promoter sequence is known. The goal was to predict the promoter activity of the promoters in the test set27.\n\nScoring metric: Four metrics are used27: two distances between measured and predicted values and two differences in rank between measured and predicted values. The distances are based on a Pearson metric and a chi-square metric. The rank differences are based on the Spearman’s rank correlation and rank-square metric. Those 4 metrics have p-values denoted pj with j = 1..4 derived from null distributions based on participants’ submissions. The overall score is then:\n\n\n\nDescription: Flow cytometry (FCM) has been widely used by immunologists and cancer biologists in the last decades as a biomedical research tool to distinguish different cell types in mixed populations, based on the expression of cellular markers. The goal of this challenge was to diagnose Acute Myeloid Leukaemia (AML) from patient samples using FCM data. In particular, participants were asked to find homogeneous clusters of cells, which can be used to discriminate between AML positive patients and healthy donors1.\n\nScoring metric: Four metrics are used: AUPR, Matthews correlation coefficient (see Supplementary material), Jaccard similarity coefficient (size of the intersection divided by the size of the union of two sample sets), and Pearson correlation. The final score is the average of those four metrics and ranking amongst top performers is based on the Pearson correlation.\n\nDescription: Accurate estimation of parameters of biochemical models is required to characterize the dynamics of molecular processes. Consequently, effective experimental strategies for parameter identification and for distinguishing among alternative network topologies are essential. In this challenge, we created an in silico test framework under which participants could probe a network with hidden parameters. In addition, a virtual budget was provided to participants to buy experimental data (generated in silico with the model) mimicking the features of different common experimental techniques (e.g., microarrays and fluorescence microscopy). In a first sub-challenge, the topology and underlying biochemical structure of a 9-gene regulatory network was provided. Participants were asked to (i) estimate the 18 parameters of the model and (ii) predict outcomes of perturbations (time courses). The second sub-challenge provided an 11-gene regulatory network with 3 missing regulatory links to be guessed26.\n\nScoring metric: For the first sub-challenge, two distances are computed. First, a distance Dparam that is the mean of the mismatch between estimated and true parameters on a log-scale:\n\n\n\nwith the number of parameters Np = 45. Second, a distance Dtime course that is similar to Equation 1 (square errors):\n\n\n\nwhere k is a time course index, i a time index and the parameters σb and σs are set to 0.1 and 0.2, respectively (see D3C2 challenge for details). Since the initial time point was provided, the first 10 data points are ignored. From the participants’ submission a null distribution and p-values are computed and the final score is:\n\n\n\nIn the network topology sub-challenge, an ad-hoc distance based on the link and nature of the 3 missing regulations is used26. Again, from the participant’s submission a null distribution and p-value is computed. The final score is then:\n\n\n\nDescription: In the breast cancer prognosis challenge, the goal was to assess the accuracy of computational models designed to predict breast cancer survival. Participants were asked to build computational models based on clinical information about the patient’s tumor. In addition, genome-wide molecular profiling data including gene expression and copy number profiles were provided9.\n\nScoring metric: Models were scored by calculating the exact concordance index between the predicted survival and the true survival information in the validation data set (accounting for the censor variable indicating whether the patient was alive at last follow-up). See Supplementary material for details.\n\nDescription: ALS is a fatal neurodegenerative disease. One important obstacle to understanding and developing an effective treatment for ALS is the heterogeneity of the disease course, ranging from under a year to over 10 years. The more heterogeneous the disease, the more difficult it is to predict how a given patient’s disease will progress. ALS status is defined by a functional scale called ALS Functional Rating Scale (ALSFRS). ALS progression between two time points can be defined as the slope between two ALSFRS values. The goal of the challenge was to predict the future progression of disease in ALS patients based on the patient’s current disease status and data (e.g., family history data, vital signs, lab data...)8.\n\nScoring metric: Two ALSFRS values are available for each patient, providing the actual slope X across patients. The accuracy of predicted slopes X^ from participants is assessed using the root mean square error.\n\nDescription: The connection between molecular measurements and cellular drug response is central to precision medicine. Two sub-challenges were run to evaluate methods that leveraged -omics measurements to predict drug response in human cell lines. The first sub-challenge was to predict drug sensitivity in breast cancer cell lines by integrating multiple–omics data types28. The second sub-challenge was to predict drug synergy/antagonism in a B cell lymphoma cell using gene expression and copy number alterations29.\n\nScoring metric: In sub-challenge 1, teams were asked to predict the rank order of cell lines treated with 28 drugs. An aggregate scoring method was developed that we called the weighted, probabilistic concordance-index (wpc-index), a variant of the concordance index (see Section 1.2.4 for details). Indeed, drug measurements vary across experiments and gold standard ranked list of cell lines by drugs is subject to noise. The pooled variance was calculated and taken into account when scoring and the final wpc-index was the weighted average over all drugs. Statistical significance was calculated by comparing a team’s wpc-index to the empirical null distribution of random sets of predictions. False Discovery Rates (FDRs) were calculated to account for the multiple testing hypotheses given by the number of teams that submitted predictions to the challenge. Teams were also scored according to a resampled Spearman correlation. Full details of the scoring methodology can be found in the Supplementary Note 3 in Costello, et al.28.\n\nIn sub-challenge 2, teams were asked to predict the rank order of drug combinations for 14 drugs from the most synergistic to most antagonistic. For each drug combination, drug response was measured on the Ly3 cell line and Excess over Bliss (EoB) was calculated as the average over five replicates ei with the corresponding standard deviation si. The definition of Bliss additivisim (or Bliss independence) can be found in Borisy et al.30. Similar to sub-challenge 1, the scoring method was a modification of the concordance index, taking into account the probabilistic nature of the EoB calculations. A leave-one-out approach (leave-one-drug-out) was used for p-value estimation and FDR correction was applied. Additionally, the resampled Spearman scoring approach was used as a second scoring method. Full details of the scoring methodology can be found in Supplementary Note 1 in Bansal et al.29.\n\nDescription: This challenge aimed to advance and assess our ability to infer causal protein signaling networks and predict protein time-courses in a complex, mammalian setting. Participants were provided with protein time-course data from four breast cancer cell lines under various ligand stimuli and inhibitor perturbations. The challenge consisted of three sub-challenges. Sub-challenge 1 tasked teams with inferring causal signaling networks specific to each of 32 contexts defined by combination of cell line and stimulus. In contrast to networks that simply describe correlations between nodes, a directed edge in a causal network predicts that an intervention on the parent node will lead to a change in abundance of the child node. For sub-challenge 2, teams were asked to predict context-specific phosphoprotein time-courses under an unseen inhibitor perturbation. Sub-challenges 1 and 2 also consisted of companion tasks based on in silico data. Sub-challenge 3 (not part of DREAMTools) asked teams to devise novel ways to visualize these data. A full description of the challenge can be found in 10.\n\nScoring metric: For sub-challenge 1, since there were no gold standard causal networks for the experimental data task, a scoring procedure was developed that used held-out interventional test data to assess the causal validity of submitted networks. In brief (for full details see 10), the held-out test data consisted of time-courses for the same 32 contexts, but obtained under an inhibitor not contained in the training data (an mTOR inhibitor). The test data were used to identify, for each context, proteins that show salient changes in abundance under mTOR inhibition (relative to baseline). This provides a ’gold standard’ set of descendants of mTOR for each context and these were compared against descendants of mTOR in submitted networks, resulting in 32 AUROC scores for each team. Teams were ranked within each context and the final score was the mean rank across the 32 contexts. For the in silico data task, the gold standard (data-generating) causal network was known and could be directly compared against submissions to calculate AUROC scores. For sub-challenge 2 experimental data task, team predictions of protein time-courses under mTOR inhibition were directly compared against the held-out test data (also obtained under mTOR inhibition). Performance was assessed using root mean squared error (RMSE). Teams were ranked by RMSE within each (cell line, phosphoprotein) pair and the final score was the mean rank across all pairs. A similar procedure was used for the in silico data task.\n\nDescription: The challenge was designed to investigate the predictability of cytotoxicity in a population in response to environmental compounds and drugs. In vitro cytotoxicity screening was performed for 884 lymphoblastoid cell lines perturbed with 156 compounds. Genotype and transcriptional data for the cell lines were available as part of the 1000 Genomes Project (www.1000genomes.org) and structural attributes for the compounds were also provided. Participants were provided with training data consisting of the cytotoxic response for 620 cell lines and 106 compounds. Two sub-challenges were proposed: (1) prediction of individual cytotoxicity for 264 new individuals in response to the 106 compounds of the training set and (2) prediction at a population-level cytotoxicity (median and interquantile range) for 50 new compounds. Full description of the challenge is available in 7.\n\nScoring metric: Sub-challenge 1: for each submission, Pearson correlation and probabilistic concordance index (wpc) are computed for each of the 106 compounds in the test set across the 264 individuals. For each metric, teams are ranked separately for each compound and an average rank is then computed across compounds. The final rank is the average of the two intermediate ranks.\n\nSub-challenge 2: for each submission, Pearson correlation and Spearman correlation are computed for the predicted median cytotoxicity and interquantile range across the 50 compounds in the test set. Submissions are ranked separately for each population parameter (i.e. median and interquantile range) and then the final rank is the average of the two intermediate ranks.\n\nDescription: Participants were challenged to estimate the parameters of a modified whole-cell model of a slow-growing mutant strain of the bacterium Mycoplasma genitalium31. Participants were given eight types of simulated data generated using the mutant strain. Participants were also given credits to purchase additional perturbation data generated by modifying the values of individual parameters of the mutant strain. Full description of the challenge is available in 32.\n\nScoring metric: As in the D7C1 challenge (See D7C1 section), submissions were scored based on a combination of their parameter and prediction distances (Equation 13). The parameter distance was computed as the average log ratio of the estimated and true parameter values (Equation 11). The prediction distance was computed as the average Euclidean distance between the estimated and true in silico phenotypes, scaled by their variances. This scoring function is not included in DREAMTools. This scoring function is implemented in MATLAB, and is available open-source at GitHub (https://github.com/CovertLab/wholecell). A complete working example of this scoring function, including the gold standard, is available at Synapse (https://www.synapse.org/#!Synapse:syn1876068/wiki/232963).\n\nDescription: The goal of this challenge was to use a crowd-based competition framework to develop a validated molecular predictor of anti-TNF response in Rheumatoid Arthritis (RA). We used the whole genome SNP data derived from two cohorts: 2,706 anti-TNF treated RA patients combined across 13 collections of European ancestry33, and 591 patients in the CORRONA CERTAIN study34. Treatment efficacy was measured using the absolute change in disease activity score in 28 joints35 (DAS28) following 3–6 months of anti-TNF treatment. The challenge was devised into two components. Sub-challenge 1: predict treatment response as measured by the change in disease activity score (DAS28) in response to anti-TNF therapy. Sub-Challenge 2: identify poor responders as defined by EULAR36 criteria for non-response (20% of the study population).\n\nScoring metric: In sub-challenge 1, each participant submission is scored independently using the Spearman correlation. In sub-challenge 2, each submission is scored independently using the AUPR and AUROC metrics (same as D2C3).\n\nDescription: Essential genes are those genes of an organism that are thought to be critical for its survival. In this challenge, participants were given a set of training gene dependency/essentiality scores from a set of cancer cell lines with expression data, copy number data, and mutation data. The goal was to develop predictive models that can infer gene dependencies/essentialities using the provided molecular features. Three sub-challenges included (i) building a model that predicts all gene essentiality scores in a held-out test set, using any feature data, (ii) predicting a subset of gene essentiality scores using only N = 10 gene expression, copy number, or mutation features per gene and (iii) same as sub-challenge 2 with N = 100. For sub-challenges 2 and 3, a smaller list of prioritised 2647 genes was selected considering profiles of the gene essentiality data, cancer related genes and evidence of the gene to be a potential drug target.\n\nScoring metric: For all sub-challenges, prediction performances are assessed in terms of Spearman’s rank correlation coefficient. We first calculate the Spearman’s rank correlation coefficient for each gene between the measured and predicted gene-level scores over held-out cell lines. For each submission, the overall score is calculated as the average correlation over all genes (all genes for sub-challenge 1 and all prioritized genes for sub-challenges 2 and 3).\n\nDescription: AML is a cancer of the bone marrow and the blood. Mutations in the myeloid line of blood stem cells lead to the formation of aberrant myeloid blasts and white blood cells. If untreated, these highly proliferative cancerous cells impede the development of normal blood cells and eventually cause death. In this challenge, participants had to predict the outcome of treatment of AML patients (resistant or remission) as well as their remission duration and overall survival based on clinical cytogenetics, known genetics markers and phosphoproteomic data. Three sub-challenges were conducted. In the first, participants were asked to predict which AML patients will have complete remission or will be primary resistant. In sub-challenge 2, participants were asked to predict remission duration for patients who have complete remission.\n\nScoring metric: In sub-challenge 1, the scoring methods are the AUROC and balanced accuracy (BAC), defined in Section 1.1. In sub-challenge 2 and 3, the scoring methods are the concordance index (CI) and Pearson correlation coefficient (see Section 1.2.4). The Pearson correlation coefficient is used to measure correlation between predictions of remission duration and actual remission duration. In those sub-challenges, the final rank is the average of the two intermediate ranks.\n\nDescription: The goal of the Alzheimer’s Disease (AD) challenge was to identify accurate predictive biomarkers that can be used to improve AD diagnosis and treatment. In order to build predictive models, participants were given genetics and brain imaging data in combination with cognitive assessments, biomarkers and demographic information from cohorts ranging from Cognitively Normal (CN) to Mild Cognitively Impaired (MCI) to individuals with Alzheimer’s Disease (AD). An essential metric for diagnosis is the Mini-mental state examination (MMSE) score at baseline and at the 24 month follow-up visit. Three sub-challenges were conducted to (i) predict the change in cognitive scores 24 months after initial assessment (ii) predict the set of cognitively normal individuals whose biomarkers are suggestive of amyloid perturbation and (iii) classify individuals into diagnosis groups using MR imaging.\n\nScoring metric: In the first sub-challenge, participants were asked to predict the change in cognitive scores using (i) clinical covariate only or (ii) clinical covariate and additional genetics variables. Those two predictions are scored using Pearson and Spearman correlations leading to 4 ranks across submissions, which are average to provide the final rank.\n\nIn the second sub-challenge, the problem was to understand how some people maintain normal cognitive function in the presence of amyloid pathology. The set of cognitively normal individuals predicted by participants includes the ranking of these subjects (from the most discordant to the least discordant), the confidence in the ranking, and if the subject is discordant or concordant. The final score is the average of the AUROC and BAC values.\n\nIn the third sub-challenge, participants were asked to classify individuals to differentiate AD patients from others using MR imaging using the MMSE as a confidence score. Two scores are computed to rank the submissions based on (1) the Pearson correlation of the predicted MMSE with the measured MMSE scores and (2) the concordance correlation coefficient (CCC) (see Section 1.2.3) for agreement on a continuous measure between observed and predicted MMSE. Again, final ranking is the average of these two ranks. Note that the percentage of correctly classified subjects in each of the three diagnostic classes is used to resolve ties.\n\nDescription: The detection of somatic mutations from cancer genome sequences is key to understanding the genetic basis of disease progression, patient survival and response to therapy. The goal of the somatic mutation calling (SMC) challenge is to identify the most accurate mutation detection algorithms using as input whole-genome sequencing (WGS) data from tumor (prostate and pancreatic) and normal samples37.\n\nThere were two sub-challenges called Intel-10 SNV and ITM1-10 SV. Single nucleotide variants (SNVs) are alterations of a single base within the DNA code, and often cause sensitivity to specific drugs. A typical cancer may contain tens of thousands of SNVs. Structural variations (SVs) are duplications, deletions or rearrangements of large segments of the genome and are often described as being the primary cause of cancer.\n\nScoring metric: Genomic variant detectors are classifiers. The performance of the predictive algorithms from the participating challenge teams are ranked using the validation data to compute the sensitivity, specificity and balanced accuracy.\n\nDescription: The goal of this challenge was to predict how a molecule smells from its physical and chemical features. We provided a large unpublished data set based on extensive smell-testing of 49 human subjects asked to sniff 476 different odor chemicals. Subjects were asked to tell us how pleasant the odor is, how strong the odor is, and how well the smell percept matches a list of 19 descriptors. To complement these perceptual data, we provided physical-chemical information about each odor molecule. Two sub-challenges were proposed. In the first, participants had to predict individual odor intensity, odor valence (pleasantness/unpleasantness) and the matrix of 19 odor descriptors (at high intensity) for each of the 49 subjects. In the second sub-challenge, the mean and standard deviation of the odor intensity, odor valence (pleasantness) and matrix of 19 odor descriptors (at high intensity) were requested.\n\nScoring metric: Out of the 476 odor chemicals, 338 were provided as a training set and 69 were used as a test set for the final scoring. In sub-challenge 1, the Pearson correlation across the 69 odors for intensity (int) and pleasantness/valence (ple) are computed and denoted rint and rple, respectively. The mean for all 49 individuals is computed and denoted r¯int and r¯ple. Similarly, for the descriptors, the Pearson coefficient for each of the 69 odor is averaged across the individuals and descriptors and denoted r¯dec. The z-scores are calculated by subtracting the average Pearson correlations and scaling by the standard deviation of a distribution based on a randomization of the gold standard. The final score is the average of the z-scores.\n\nFor sub-challenge 2: Instead of using the mean (across 49 individuals) of the Pearson correlation (across the 69 odors), the Pearson correlation of the mean intensity and standard deviation (across 49 individuals) was used. This leads to 6 values (2 for intensity, 2 for valence and 2 for descriptors). Again, z-scores are calculated from an empirical null distributions and the final score is the average of the z-scores.\n\nDescription: This challenge focused on predicting survival using patients’ clinical variables with the goal to improve prognostic models and toxicity of docetaxel treatment in patients with metastatic castrate resistant prostate cancer (mCRPC). Over 100 clinical variables were summarized across four phase III clinical trials with over 2,000 mCRPC patients treated with first-line docetaxel. There were two sub-challenges. Sub-challenge 1a was to predict overall patient survival and sub-challenge 1b was to predict the exact time to event for each patient. Sub-challenge 2 was to predict if a patient will be discontinued from docetaxel treatment because of adverse events. The primary benefit of this Challenge will be to establish new quantitative benchmarks for prognostic modeling in mCRPC, with a potential impact for clinical decision making and ultimately understanding the mechanism of disease progression.\n\nScoring metric: Participants were asked to produce “risk scores” for each patient for sub-challenge 1a and the exact time to death for sub-challenge 1b. There were two metrics used to score participants for sub-challenge 1a, namely the integrated AUC (iAUC) as defined in the timeROC package in R and the concordance index (see Section 1.2.4). Sub-challenge 1b was scored using the root mean squared error (RMSE).\n\nFor sub-challenge 2, participants were asked to supply a “risk score” and a discrete variable equal to 1 if the patient is predicted to discontinue within 3 months and 0 otherwise. Submissions were scored using the AUPR metric as defined in the ROCR package in R.\n\nDescription: This challenge is a follow-up on to the DREAM 7 ALS Prize 4 Life Challenge (see D7C3 for details). It focuses on predicting the progression and survival of ALS patients. One objective of the challenge is to leverage the PRO-ACT database of more than 8,000 cases as the challenge training set. The challenge will include several unpublished data sets to be used for model validation.\n\nScoring metric: This is an on-going challenge. The scoring metric will be based on concordance index, Pearson correlation and root-mean-squared deviation.\n\nDescription: This challenge is a follow-up on to D9C4 challenge (somatic mutation calling). This challenge’s focus is to identify the best subclonal reconstruction algorithms and to identify the conditions that affect their performance. See Section D9C4 for details.\n\nScoring metric: This is an on-going challenge. The scoring metric has not been released yet (September 2015).\n\nDescription: This challenge is a follow-up on to D9C4 challenge (somatic mutation calling). See Section D9C4 for details.\n\nScoring metric: This is an on-going challenge. The scoring metric has not been released yet (September 2015).\n\n\nConclusions\n\nThe organization of a collaborative competition such as the DREAM challenges is a complex task that starts by identifying a currently important and unresolved scientific problem, acquiring relevant data sets, engaging a community of participants, and implementing an appropriate scoring methodology. Participants can submit their solutions (e.g., predictive models or predictions) which are then scored and ranked, and the results are shown on a public leaderboard. Once the challenge is closed, those leaderboards can be used as a benchmark for further development of methods. To promote scientific reproducibility as well as post-challenge use, DREAM provides via Sage Bionetwork’s Synapse platform the resources to help researchers access data and leaderboards of previous challenges.\n\nIn this paper, we presented DREAMTools to provide a uniform framework where researchers can easily assess and compare new methods against benchmarks. DREAMTools gathers most of the scoring functions used in previous DREAM challenges. DREAMTools uses Python as a glue language known for its flexibility and ability to call other languages. Currently, about 80% of the closed challenges are available. The remaining challenges are either in the process of being included or hosted on external websites. Future versions of DREAMTools will aim at making available as many closed challenges as possible including newly closed challenges.\n\nDREAMTools will help researchers who wish to test their algorithms against existing benchmarks. Indeed, templates can be downloaded and used to create predictions, which can then be tested. The gold standards are also available together with the relevant scoring functions. Since DREAMTools makes use of an object oriented approach, it will ease the integration of future challenges thereby facilitating scoring in upcoming challenges. DREAMTools can also be used as a place to retrieve metadata and information about a challenge. DREAMTools can be used as a standalone application or as a library making it a useful tools to be included in other software or pipelines. Developers who use the proposed layout will not need to change anything regarding the standalone application that will automatically recognize the challenge. In summary, we hope that DREAMTools will be a useful tool for researchers interested in benchmarking their methods against the state-of-the-art as defined by previous DREAM challenges, and to those developing new collaborative competitions within DREAM or elsewhere.\n\n\nSoftware availability\n\nhttps://pypi.python.org/pypi/dreamtools\n\nhttp://github.com/dreamtools\n\nhttp://www.dx.doi.org/10.5281/zenodo.3143638\n\nhttps://github.com/dreamtools/dreamtools/issues\n\nhttp://pythonhosted.org/dreamtools/\n\nBSD 3-clause license (“BSD NEW” or “BSD Simplified”) http://opensource.org/licenses/BSD-3-Clause",
"appendix": "Author contributions\n\n\n\nTC designed the DREAMTools framework including documentation, tests, API and dreamtools standalone application.\n\nScoring functions (design and implementation) being challenge-dependent, contributions arise from various individuals. As far as we are aware of, scoring functions currently available where originally developed as follows: all DREAM2 challenges (GS), all DREAM3 and DREAM4 challenges (GS, RP), D5C1 (GS, RP, ALF), D5C2 (RN, MTW), D5C3 (GS, RP), D5C4 (GS, RP), D6C1 (RP), D6C2 (PM, TC), D6C3 (PM), D6C4 (RN), D7C1 (PM, TC), D7C2 (EB), D7C3 (RK), D7C4 (MPM, JC, MB), D8C1 (SH, TC), D8C2 (FE), D8C3 (JK, PM), D8.5C1 (AP), D9C1 (MG), D9C3 (GS, CB, ECN), D9.5C1 (PM, RN), D9.5C2 (CB, JC), D10 challenges (work in progress). In addition, BH, BB, CB contributed in particular to the interface between scoring functions and leaderboards posted on Synapse projects (DREAM7 onwards).\n\nGS supervised the development of all scores and developed several of them himself. JSR supervised the development of some scores and the DREAMTools project.\n\n\nCompeting interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nJRK was supported by a NSF Graduate Fellowship and a James S. McDonnell Foundation Postdoctoral Award in Studying Complex Systems.\n\n\nAcknowledgements\n\nThe authors would like to thank all DREAM participants, organisers and data providers for their contributions to the DREAM challenges.\n\n\nSupplementary material\n\nThis section covers tools used in the DREAM scoring functions.\n\nBinary classification is the task of classifying the elements of a data set into two groups (e.g., a medical testing to determine if a patient has certain disease or not). It has been used in many of the DREAM challenges16 to evaluate prediction performance as compared to a gold standard. Given a binary classifier, there are four possible outcomes that can be arranged in a 2 × 2 contingency table filled with true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN). False positives are also known as false alarms or type I error and the false negative are also known as miss or type II error. The contingency table generally fills columns with actual values and rows with the prediction. True positive being in the top left corner. See Supplementary Table 1.\n\nFrom the contingency table, many metrics can be used to measure the performance of a classifier. Some may be more appropriate than others depending on the problem posed or the prevalence of the classes considered (see below). A useful technique to visualize and select classifiers is the Receiver Operating Characteristics (ROC) graph, which have long been used in signal detection theory39. Efficient algorithms to compute ROC graphs and practical issues can be found in 40. The next section will describe the ROC analysis in details. Before, let us provide some common equations and terminology used in the evaluation of binary classifiers and ROC analysis.\n\nThe prevalence mentioned earlier (also known as balance) is the ratio of positive conditions to the total population:\n\n\n\nwhere P is the total number of positives (i.e., TP + FN) and N the total number of negatives (i.e., TN + FP). The total population is denoted T = P + N.\n\nFrom the 4 basic numbers of the contingency table, 8 ratios can be obtained by dividing those numbers by either the sum of the rows or the sum of the columns.\n\nThe column ratios are the proportion of the population with a given condition (positive or negative).\n\n1. The true positive rate (TPR) is the ratio of true positive by the sum of positive conditions. The TPR value also known as sensitivity or recall is a measure of completeness:\n\n\n\n2. The false negative rate (FNR) also known as miss rate is:\n\n\n\n3. The false positive rate (FPR):\n\n\n\n4. The true negative rate (TNR) also known as specificity:\n\n\n\nNote that these ratios are independent of the total number of conditions (i.e., there are independent of the prevalence).\n\nThe row ratios are computed as follows:\n\n1. The positive predictive values (PPV) or precision is a measure of fidelity:\n\n\n\n2. The false discovery rate (FDR):\n\n\n\n3. The false omission rate (FOR):\n\n\n\n4. The negative predictive values (NPV):\n\n\n\nNote that these ratios have denominator that combines positive and negative (i.e. they depends on the prevalence).\n\nThere are a number of other metrics derived from those 8 numbers. We can mention the accuracy and F-measure. The accuracy measures the fraction of all instances that are correctly categorized:\n\n\n\nAnother related measure used for instance in D9C2 challenge (See Section D9C2) is balanced accuracy (BAC):\n\n\n\nin other words, the arithmetic average of the sensitivity and specificity. The BAC metric avoids inflated performance estimates on imbalanced data sets.\n\nThe F-measure or balanced F-score (F1 score) is the harmonic mean of precision and recall:\n\n\n\nThe F-measure is often used in the field of information retrieval for document classification with large scale data where performance needs to place more emphasis on either precision or recall. Note, however, that the F-measure does not take the true negatives into account, which appears clearly in this other formulation of the F-measure/F1 score:\n\n\n\nIt is common to explore complementary metrics simultaneously varying a cutoff of the decision boundary. The pair precision-recall is used to estimate a first metric known as the precision-recall curve (AUPR). The true positive rate and false positive rate pair is used to estimate a second metric called AUROC (Area Under the receiver operating characteristic (ROC) curve).\n\nThe precision and recall are therefore functions of a varying parameter, k, in a precision-recall curve and can be expressed as:\n\n\n\nand:\n\n\n\nsimilarly, the receiver operating characteristic (ROC) curve explores the trade-off between true and false positive rates as a function of a varying k parameter. The TPR and FPR are denoted:\n\n\n\nand:\n\n\n\nThe AUROC is a single measure that is the integral of the TPF/FPR curve. Similarly the AUPR is a single measure that is the integral of the recall-precision curve.\n\nThe values of recall and precision range from zero to one with one being the optimal value for precision and min(k/P, 1) being the optimum for recall at depth k. The precision-recall curve explores changes in accuracy as k increases.\n\nNote that in the case of a discrete classification, the ROC curves contains only 1 point.\n\n1.2.1 Matthews correlation coefficient. An additional measure that can easily be computed is the Matthews correlation coefficient (MCC), which is a measure of the quality of a binary classification41. It can be used even if the classes are of very different sizes (low or high prevalence). The MCC can be calculated directly from the confusion matrix using the formula:\n\n\n\nThe MCC is also known as the phi coefficient, which is the chi-square statistic for a 2 × 2 contingency table:\n\n\n\nwhere T is the total number of observations.\n\n1.2.2 Spearman’s rank correlation. Spearman’s rank correlation coefficient or Spearman’s rho denoted ρ is a nonparametric measure of statistical dependence between two variables. It assesses how well the relationship between two variables can be described using a monotonic function. Spearman’s coefficient is appropriate for continuous and discrete variables, including ordinal variables.\n\nThe Spearman correlation coefficient is defined as the Pearson correlation coefficient between the ranks of variables. For a sample of size N, the N raw scores Xi, Yi are converted to ranks xi, yi, and ρ is computed from:\n\n\n\nwhere di = xi - yi, is the difference between ranks. Note that identical values are assigned a rank equal to the average of their positions in the ascending order of the values.\n\n1.2.3 Concordance correlation coefficient. The concordance correlation coefficient (CCC) measures the agreement between two variables42 and is denoted ρc:\n\n\n\nIt can be used as a measure of the correlation between two variables around the 45 degree line from the origin. It is used for instance in challenge D9C342.\n\n1.2.4 Concordance index. In D7C2 challenge (See Section D7C2), an exact concordance index was used as a scoring metric. The concordance index (c-index) was first introduced to the biomedical community in 43. It is a measure of association between the predicted and observed failures in case of right censored data. In the absence of censored data, the c-index estimates the Mann–Whitney parameter. Note that censoring is a condition in which the value of a measurement or observation is only partially known (e.g., impact of a drug on mortality rate for living subjects that may die before the end of the study).\n\nWe use here below the same formulation as in the Supplementary Note 3 in Costello, et al.28. For a given drug d, we define Rd = {r1, r2,..., rN} a rank order for N predictions (e.g., N cell lines). Similarly, we define Gd = {g1, g2,..., gN} a rank order for the gold standard.\n\n\n\nwhere\n\n\n\nIn the previous formulation of the c-index, the variance of the gold standard data set is not taken into account. A probabilistic c-index (denoted pc-index) was introduced in Costello et al.28, Bansal et al.29 and calculated as follows:\n\n\n\nwhere\n\n\n\nand sd2 is the pooled variance to account for the uncertainties of the gold standard. The equation erf is the standard error function erf(a)=2π∫0ae−t2dt.\n\nIn the case of the NCI-DREAM challenges, the final score was a weighted average of the pc-index, which we termed the weighted, probabilistic c-index (wpc-index), where the weights wd for each drug d reflect the quality of the measured data for d, accounting for the range of total response and missing values. The wpc-index is calculated as:\n\n\n\n\nReferences\n\nAghaeepour N, Finak G; FlowCAP Consortium, et al.: Critical assessment of automated flow cytometry data analysis techniques. Nat Methods. 2013; 10(3): 228–38. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCostello JC, Stolovitzky G: Seeking the wisdom of crowds through challenge-based competitions in biomedical research. 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}
|
[
{
"id": "11288",
"date": "26 Nov 2015",
"name": "Konrad Hinsen",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article describes a software tool that implements in a transparent and reusable way the scoring of DREAM challenges, covering 80% of the challenges that have taken place. The tool thus ensures replicability of past challenges and also permits researchers to use them in evaluating their future work.The software is fully open and well documented, conforming to the highest standards of open science. The article is clear and explains both the motivation for and the design of the software in sufficient detail.Unfortunately I did not succeed in installing and running the software following the provided instructions (see https://github.com/dreamtools/dreamtools/issues/60 and https://github.com/dreamtools/dreamtools/issues/59 for the details). These issues seem minor, but prevent a full evaluation at this time. This is my only reason for approving this article with reservations.",
"responses": [
{
"c_id": "1720",
"date": "04 Dec 2015",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Konrad,First of all thanks a lot for your review and comments. The main issue you had was that the installation failed, which is unfortunate indeed. It appears that you tried to install DREAMTools using Python3 and we developed the software for Python2 only. The paper did not mention the Python2/3 compatibility and this may have misled you as it would misled many people. Even though we were mentionning in the README file that DREAMTools is developed for Python2 only, we fully understand that users may use Python3 by default. The rationale for sticking to Python2 was that a few librariries on which we were relying were not available for Python3 at the time we developed DREAMTools. Meanwhile, most of them have been ported to Python3 but one. Yet, we decided to port DREAMTools to Python3 since we also provide of temporary python3 version of the library that is not yet available for Python3. Consequently, DREAMTools is now available for Python2.7 and various variant of Python3.X . We hope that this should help you to further test the software. The README/installation section have been modified to reflect those changes and guide users in the installation process.As for the issues that you have reported https://github.com/dreamtools/dreamtools/issues/60 and https://github.com/dreamtools/dreamtools/issues/59 we believe that they should be fixed by now. (The first error was enterily related Python3 and second issue has been solved by providing informative message to the user and additional documentation).We have released a new version of DREAMTools on pypi website and the current official release is 1.1.1We thank again the reviewer for his time and comments that motivated us to port DREAMTools to Python3 so as to give access to the software to a wider community.BestThomas Cokelaer on behalf of the DREAMTools team."
},
{
"c_id": "1725",
"date": "08 Dec 2015",
"name": "Konrad Hinsen",
"role": "Reviewer Response",
"response": "Dear Thomas,thanks for looking into this, and working on Python 3 compatibility. I do understand that Python 3 compatibility is not trivial!I tried once more to install dreamtools for Python 3, following the instructions, but failed again. The problem comes from a dependency (see https://github.com/dreamtools/dreamtools/issues/61), so I am not sure there is much you can do about it.Next I tried installing dreamtools with Python 2. That fails as well, again because of a dependency (again gevent!) that fails to install correctly. That may well be specific to the MacOS platform, or to some other detail of my computational environment. I suspect there isn't much you can do about it, but it still means that I cannot test-drive dreamtools at all."
},
{
"c_id": "1726",
"date": "09 Dec 2015",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Konrad,I'm sorry to see that the installation causes problems. The portage of DREAMTools to Python3 was done under Linux systems for different versions of Python3 (3.3, 3.4, 3.5) and tested on Travis (https://travis-ci.org/dreamtools/dreamtools). The gevent external library may not be needed strictly speaking so we can probably find a workaround.Another solution that we will provide very soon is to use Anaconda environment with pre-installed packages (e.g. gevent). In the next version of DREAMTools, we will provide a conda-compatible package to guarantee that the installation is possible on all systems. We have tested this option recently on another software with success.Again sorry to hear that you cannot test the software easily and we'll work on making this possible as soon as possilble.RegardsThomas Cokelaer"
},
{
"c_id": "1728",
"date": "10 Dec 2015",
"name": "Konrad Hinsen",
"role": "Reviewer Response",
"response": "The gevent problem I ran into under Python 2.7 turned out to be known already: https://github.com/gevent/gevent/issues/656. Since it is specific to MacOS 10.9, I tried on a machine that runs 10.10 and I managed to install dreamtools there with no(!) problems (Python 2.7, I didn't try Python 3 yet).Unfortunately, fragile dependencies are becoming more and more of a problem in the Python universe. I wish you all the luck you need with an approach based on Anaconda - my own experiences with that approach are mixed to say the least.To get a first experience with dreamtools, I tried running the command lines given as examples in the README. Unfortunately, I ran into serious usability issues (see https://github.com/dreamtools/dreamtools/issues/63), and in particular it seems that the example dataset is not open. Could you suggest another dataset I can work with?"
},
{
"c_id": "1767",
"date": "19 Jan 2016",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Konrad,Having a Python software that runs on all platforms/systems is a challenge by itself ! The issue with gevent on MacOS 10.9 you got is an example, which is not unique. This is a general issue for the scientific community and as you pointed out both for users and developers. I think Anaconda does help a lot. I have started to use Anaconda only recently but I see a great value for future development even though not all problems are fixed. So, we decided to provide a solution based on Anaconda for DREAMTools. We do not yet provide a pre-compiled version of DREAMTools within anaconda.org but this may be the best solution for future versions. For now, DREAMTools is still downloaded from Pypi but most dependencies (e.g., numpy) can be obtained as pre-compiled version from Anaconda packages.As for the problems you reported in the issue 63 on github, I fully appreciate your concerns and the API and examples have been updated to make user's experience a bit better. One of the major issue was that the example in the documentation failed because synapse expected the condition of use (of the data) to be accepted inside the browser. So, the code was changed to tell the user what to do in this situation.Other cryptic messages and issues reported in the issue 63 should have been addressed as well.We also suggest another challenge in the examples, which do not require access to synapse (challenge D6C3).Thomas Cokelaer"
},
{
"c_id": "1895",
"date": "08 Apr 2016",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Konrad,For your information, DREAMTools is now available on the bioconda (https://bioconda.github.io/) channel of Anaconda (https://www.continuum.io/downloads). Installation of the latest DREAMTools release should now be easier for MAC and Linux users as explained within the online documentation (http://dreamtools.readthedocs.org/en/latest/#installation).BestThomas"
}
]
},
{
"id": "11489",
"date": "21 Dec 2015",
"name": "Rafael Najmanovich",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors set out to create a framework to easily access data from a large number past DREAM challenges and assess new predictions for these using appropriate the evaluation metrics defined in the respective challenges. My main reservation is that I find that the DREAMTools package is, contrary to what the authors claim, of little use at the moment. Perhaps in a future where the official DREAM challenges make currently open challenges available via DREAMTools, this will be more useful. At the moment, any group interested in benchmarking their prediction method for a particular challenge can easily access and download the data as well as implement the evaluation metrics. I have have not judged the technical aspects of DREAMTools but I note that the difficulties is installing the software experienced by Konrad Hinsen points to the fact that is it of limited usability at this moment. In summary, I believe that DREAMTools can be approved in the off chance that new DREAM challenges use the package but at the moment it is difficult to install and of little use.",
"responses": [
{
"c_id": "1768",
"date": "19 Jan 2016",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Rafael,First of all, thank you very much for your time in reviewing this paper.From your experience and concerns, we'd like to clarify why DREAMTools is a valuable tools for the scientific community.First of all, we acknowledge that the installation does not work for every platform and system; the fact is that we did not consider all platforms and systems during our development ! Even though the Python language is cross-platform by definition, it is nevertheless also linked to packages that require compilation (e.g., numpy). Although DREAMTools provides a Python API, behind the scene we also use R and Perl and C languages. Today, Python and R lead the data science but new languages (e.g., Julia) will also enter the scene. It is clear that one of the struggles many data scientists face nowadays is to design software that would work for everyone in this complex multi-language scenario. People have worked hard for the last decades without a definite solution. This does not mean we cannot and the Anaconda solution is one example of a great initiative that aim at alleviate this general issue.We are moving towards that direction by proposing to use Anaconda to install some of the dependencies on which DREAMTools relies. Ideally, we'd like to provide also DREAMTools as an Anaconda package, which would solve lots of the problems we are currently facing.Note that once Anaconda is installed, the DREAMTools package can be installed under Linux in a couple of minutes (See our Travis continous integration https://travis-ci.org/dreamtools/dreamtools). This is also true under Windows 7 and Mac 10.10Coming back on DREAMTools itself and its scientific interest, we believe that DREAMTools has already been valuable. First, because it was used in a few challenges (e.g., DREAM7, parameter estimation challenge, DREAM8 HPN Breast Cancer challenge) as the base code for the scoring functions during the challenge itself and to produce results and figures in publications. Second, because it assembles data and scoring functions from old challenges (DREAM2 to DREAM6) that would not have been available otherwise. Besides, all codes in DREAM2 to DREAM6 were originally written in matlab. One of our aim was to provide open source codes, which are now available inside DREAMTools. We also do not agree with this statement:\"At the moment, any group interested in benchmarking their prediction method for a particular challenge can easily access and download the data as well as implement the evaluation metrics\"Data are accessible indeed but scoring metrics needed to be recoded and are now available thanks to the effort that have been put in DREAMTools. Of course each group can recode its own evaluation metric but what is the point since it has been done and gathered in a single place. The idea of DREAMTools is that each group can just re-use our code since it is supported by the authors who wrote the scoring functions used in DREAM challenges !You also wrote: \"I believe that DREAMTools can be approved in the off chance that new DREAM challenges use the package\". More than 15 scoring functions for 15 of the earlier DREAM challenges have been made available to the open-source community. Another 15 scoring functions for more recent challenges have been made available within a single framework factorising code in the process. We believe that new challenges will be added either by DREAM developers or members of the open-source community.Again we thank you for your time and feedbacks.Thomas Cokelaer on behalf of DREAMTools developers"
},
{
"c_id": "1894",
"date": "08 Apr 2016",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Rafael,For your information, DREAMTools is now available on the bioconda (https://bioconda.github.io/) channel of Anaconda (https://www.continuum.io/downloads). Installation of the latest DREAMTools release should now be easier for MAC and Linux users as explained within the online documentation (http://dreamtools.readthedocs.org/en/latest/#installation).BestThomas"
}
]
},
{
"id": "11442",
"date": "23 Dec 2015",
"name": "Nicola J. Mulder",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper describes DREAMTools, which is a package that enables scoring of submissions for DREAM challenges. The paper is well written and this is certainly a useful tool. Benchmarking is essential in all aspects of tool or algorithm development, and the package described here will be helpful for evaluating the challenges. I did find the paper a bit too long. While it is interesting reading about the different examples DREAM challenges, these have been available on the DREAM challenges website, so perhaps a few representative examples could be selected from all those presented in the paper to illustrate the point.Like the other reviewer, my only reservation is the difficulty in getting the package installed, and though work has been done to make it compatible with Python 3, perhaps some troubleshooting tips would help users to overcome dependency issues.",
"responses": [
{
"c_id": "1769",
"date": "19 Jan 2016",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Nicola,Thanks a lot for your review and comments.It is true that more challenges will be added in the future and that the paper would be become even longer ! We are thinking about reducing the paper's length in future versions and representative examples would be a good solution.As for the installation issues that other reviewers' faced, we have improved the code and documentation to take into account any issues and will keep improving the installation. As mentionned in other reports's comments, we will provide a DREAMTools pre-compiled package in the close future that should help even more.Thanks again.Thomas Cokelaer on behalf of DREAMTools developers."
},
{
"c_id": "1893",
"date": "08 Apr 2016",
"name": "Thomas Cokelaer",
"role": "Author Response",
"response": "Dear Nicola,For your information, DREAMTools is now available on the bioconda (https://bioconda.github.io/) channel of Anaconda (https://www.continuum.io/downloads). Installation of the latest DREAMTools release should now be easier for MAC and Linux users as explained within the online documentation (http://dreamtools.readthedocs.org/en/latest/#installation).BestThomas"
}
]
}
] | 1
|
https://f1000research.com/articles/4-1030
|
https://f1000research.com/articles/5-599/v1
|
07 Apr 16
|
{
"type": "Review",
"title": "Advances in understanding – genetic basis of intellectual disability",
"authors": [
"Pietro Chiurazzi",
"Filomena Pirozzi",
"Filomena Pirozzi"
],
"abstract": "Intellectual disability is the most common developmental disorder characterized by a congenital limitation in intellectual functioning and adaptive behavior. It often co-occurs with other mental conditions like attention deficit/hyperactivity disorder and autism spectrum disorder, and can be part of a malformation syndrome that affects other organs. Considering the heterogeneity of its causes (environmental and genetic), its frequency worldwide varies greatly. This review focuses on known genes underlying (syndromic and non-syndromic) intellectual disability, it provides a succinct analysis of their Gene Ontology, and it suggests the use of transcriptional profiling for the prioritization of candidate genes.",
"keywords": [
"The advances in scientific technology related to gene sequencing and discovery in recent years",
"such as high-throughput whole genome sequencing (WGS) and single-cell sequencing",
"have led to an increasing number of studies aimed at finding new causative genes for human diseases."
],
"content": "Introduction\n\nThe advances in scientific technology related to gene sequencing and discovery in recent years, such as high-throughput whole genome sequencing (WGS) and single-cell sequencing, have led to an increasing number of studies aimed at finding new causative genes for human diseases.\n\nOwing to the heterogeneity of clinical features and causative factors (both genetic and environmental), characterization of intellectual disability (ID) has benefited from these advances, as shown by the significant increase of publications (Figure 1). As defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), ID is characterized by significant limitations in intellectual functioning and adaptive behavior, which include conceptual, social, and practical skills, arising “prior to age 18” (but it would be fair to say “with a prenatal origin”). The disorder is considered chronic and often co-occurs with other mental conditions like depression, attention deficit/hyperactivity disorder, and autism spectrum disorder (ASD). Furthermore, ID is often part of a malformation syndrome that affects other organs and their functions.\n\nID is the most common developmental disorder; however, given the heterogeneity of its causes, estimates of its frequency worldwide are highly variable (reviewed by 1). The prevalence of ID also varies depending on the age of patients, as illustrated by two Australian surveys in which prevalence was 3.3/1000 if the age range of 20 to 50 years was considered2 but increased to 14.3/1000 if the age range was lowered to 6 to 15 years3.\n\nThe purposes of this review are to update the list of known genes related to ID and to provide a brief bioinformatic analysis of their Gene Ontology (GO). Eventually, we propose the use of a relative expression ratio (“Brain ratio”) to prioritize new candidate genes for ID.\n\n\nNomenclature: mental retardation versus intellectual disability\n\nChanges in nomenclature (i.e. how we name things and concepts) are particularly delicate in science, since consistency in terminology allows more precise communication4. As discussed elsewhere5, “mental retardation” has recently been substituted by the new term ID, which in our opinion is less accurate since it does not refer to the developmental nature of the disease and it does not reflect the progress of mental acquisitions that could nonetheless be achieved but at a slower pace. That said, we should remember that ID is not the only term employed to indicate delayed acquisition of psychomotor milestones. In fact, “developmental delay” is the second most common term found in the Clinical Synopsis of OMIM (Online Mendelian Inheritance in Man) (after “mental retardation”) and is widely used by pediatricians6. Other more complex terms that have been proposed, such as “intellectual developmental disorder”, “neurodevelopmental disorder”, or “developmental cognitive impairment”7, though certainly more accurate than ID, have not gained in popularity. However, all of these terms refer to the slower acquisition of psychomotor milestones, resulting in a significant impairment of cognitive functions (a) and adaptive behavior (b), obviously with an early onset (c), compared with peers. Cognitive abilities can be measured by using a panoply of psychological tests, including the Wechsler Intelligence Scale for Children, that have as the output a numerical value known as “intelligence quotient” (IQ).\n\nIt is worth remembering that the term “pervasive developmental disorder” (PDD) is often used by psychologists and psychiatrists to refer to a group of conditions characterized by altered development of multiple basic functions, including socialization and communication. In May 2013, the DSM-5 was released and the term PDD was abandoned and substituted by ASDs. Finally, the term “learning disability” is usually reserved for specific impairments, like dyslexia and dyscalculia, that are associated with a child’s academic underperformance but not with a lower IQ.\n\nNomenclature also reflects social trends and sensibilities that vary with time and according to the different cultural context. Social perception has become a decisive factor in changing nomenclature: the term “mental retardation” is not considered politically correct any longer because of the pejorative term “retard” that is used to stigmatize affected individuals4. The community of parents and patients has indeed shown strong disagreement with the term “mental retardation”, leading to “Rosa’s law”, signed by President Obama on October 5, 2010. The new bill requires the federal government to replace the term “mental retardation” with ID in every context. Therefore, we will use the term ID in this article to refer to “mental retardation” from now on.\n\n\nEnvironmental and genetic causes of intellectual disability\n\nID can be caused by a variety of environmental and genetic causes, often combined with each other8–12. As illustrated in Figure 2, most of these causes exert their effects already during prenatal life. As indicated in table 1 of Chiurazzi and Oostra13, the severity of the clinical presentation is loosely correlated with the causal factor, and gross chromosomal imbalances, perinatal asphyxia, prenatal infections, or vascular accidents are related to the most severe cases. Variable (and dose-related) effects result from maternal exposure to toxic substances during pregnancy (e.g. environmental chemicals, use of drugs, and alcohol abuse), maternal conditions such as diabetes or phenylketonuria, and premature birth. Common (but preventable) environmental causes of ID are iodine deficiency and malnutrition (of both mother and child), affecting millions of people in “developing countries”. The frequency of these various factors varies greatly among different countries and depends on (maternal) lifestyle as well as health-care quality.\n\n*For genetic factors, the onset of symptoms or time of detection is shown. Modified from 79.\n\nMendelian causes of ID result in highly variable phenotypes ranging from mild (IQ of 55–70) to moderate (IQ of 40–55), severe (IQ of 25–40), and profound (IQ of less than 25), depending on the gene or genes involved, the effects of the mutation (dosage changes, loss-of-function mutation, and gain-of-function mutations), and the function(s) of the altered protein(s).\n\nClinically, it is useful to distinguish syndromic from nonsyndromic forms of ID, depending on the involvement of other organs and the presence (or absence) of malformations or a typical (facial) gestalt (or both). However, it is not uncommon to observe that some mutations in a given gene cause a syndrome but that other mutations in the same gene lead to nonsyndromic or “pure” forms of ID. Comorbidity with autism, epilepsy, and neuromuscular deficits (e.g. ataxia, spastic paraplegia, sensory/motor neuropathy, and muscular dystrophy) is common for nonsyndromic ID.\n\nDevelopment of a functional brain depends on a precise and complex sequence of neuronal and glial cell proliferation, migration, and maturation. Some ID syndromes are associated with gross brain malformations (e.g. holoprosencephaly, schizencephaly, porencephaly, hydrocephalus, agenesis of corpus callosum, and cerebellar hypoplasia) or with neuronal migration disorders (e.g. lissencephaly, micropolygyria, double cortex, and ventricular nodular heterotopia) that can be assessed by neuroimaging techniques. However, even in the presence of a morphologically normal brain, neuronal connectivity could be altered by a dysfunction of the glia (e.g. disorders of myelination) or neuronal crosstalk might be altered at the synaptic level, either because of a reduced number of mature dendritic spines or because of inefficient (or excessive) synaptic transmission14. Finally, even if both neurons and glial cells are well positioned, connected, and working, they could be damaged by toxic compounds accumulating in metabolic disorders (toxic neurodegeneration). A careful clinical evaluation of the patient(s), including reconstruction of personal and family history, possibly integrated by neuroimaging or neurophysiological tests or both, may provide essential clues to reach a diagnosis and identify a specific cause of ID6,15,16.\n\nA special note must be made for the extensive overlap between causes (and pathogenic pathways) of ID and those of autism or ASDs, since many patients have both ID and compromised social interaction and communication and vice versa17–19. For example, more than 100 genes and 40 genomic loci associated with ASD had been reviewed by Betancur in 201120 and all of these were also involved in ID.\n\n\nCounting conditions with intellectual disability using OMIM\n\nCurated lists of genes involved in ID have been published by some groups. Gilissen et al.21 created two lists including 528 genes with a “confirmed” pathogenetic role and 628 “candidate” genes with mutations reported in fewer than five patients. Another comprehensive list (DDG2P) was prepared to assist the Deciphering Developmental Disorders Study22, including 925 “confirmed” developmental disorder genes up to November 201323. Yet another list of 565 genes associated with ID (253 “known” and 312 “candidate”) has been reported by Grozeva et al.24, who used the two previous lists as a starting point.\n\nWe decided to obtain an independent gene list by using OMIM and the National Center for Biotechnology Information (NCBI) GENE databases. To identify most (if not all) conditions with ID, we searched for entries with either “mental retardation” or “developmental delay”, “intellectual disability”, and “cognitive impairment” in the Clinical Synopsis. It is worth noting that, at least in OMIM, the term “mental retardation” is still the most common (followed by “developmental delay”) term found in the Clinical Synopsis of 981 OMIM entries. Furthermore, only conditions for which at least one gene has been identified were included. This OMIM search resulted in 900 conditions (listed in Supplementary Table 1) and was performed by using the following search string:\n\n((((mental retardation[Clinical Synopsis]) OR developmental delay[Clinical Synopsis]) OR intellectual disability[Clinical Synopsis]) OR cognitive impairment[Clinical Synopsis]) AND “prefix pound”[Properties].\n\nThese 900 conditions include several “genomic disorders” (i.e. microdeletion/duplication conditions such as Williams, velo-cardio-facial, and Wolf-Hirschhorn) and even Down syndrome. It is known that a few syndromes associated with these recurrent submicroscopic chromosomal aberrations are actually due to the altered dosage of just one gene25–27. However, to obtain a list of single genes underlying ID, after transferring the 900 conditions from OMIM to the NCBI GENE database (Figure 3) and finding 897 items, we manually removed 79 entries without a precise chromosomal location, including those corresponding to genomic disorders (that may be potentially due to more than one gene). This final list contains 818 protein-coding genes and has been ordered either by map_location or by alphabetical order of gene symbol (see Supplementary Table 2). In both lists, removed items are indicated in red.\n\nThe largest number indicated in black on the upper left of each term is the total number of counts without any limits, whereas the number of entries with the term specified in the Clinical Synopsis is indicated in blue on the lower left. To the right of each term are the counts of entries containing the term linked to at least one gene (upper right with a pound prefix [#], in black) and all entries containing the term in their Clinical Synopsis AND being linked to at least one gene (lower right with a pound prefix [#], in red). OMIM, Online Mendelian Inheritance in Man.\n\n\nMapping intellectual disability genes and enrichment on the X chromosome\n\nWe then used the Genome Decoration page at NCBI to map the identified genes on the human karyogram (Figure 4). Not surprisingly, the density of ID genes is higher in G-negative bands that are typically richer in protein-coding genes. Figure 5 is derived from Supplementary Table 2 and counts the number and proportion of ID genes relative to all protein-coding genes for each individual chromosome. The X chromosome appears to be enriched for genes mutated in patients with ID, be they syndromic or not (10% of all protein-coding genes on the X compared with 4% of the genomic average). Actually, the total number of X-linked ID (XLID) genes is higher than that (86) shown in Figure 5: now (March 2016) the total number of XLID genes is more than 100 out of about 800 protein-coding genes on the X chromosome28–30. XLID genes have been identified earlier than autosomal ID genes because of their inheritance pattern that allows transmission through several unaffected carrier females, and they may explain part of the reported excess of male patients with ID31,32. However, is this enrichment real or simply due to ascertainment bias, since the identification of X-linked families is easier? Twenty-five years after the cloning of the first XLMR gene (FMR1, inactivated in the fragile X syndrome), we still do not have a definitive answer to this question and we may have to wait until all ID genes have been identified to settle the dispute. However, several authors suggested the possibility that “intelligence genes” actually concentrated on the X chromosome because of a selective advantage in males32–34; this evolutionary effect would also explain why intelligence scores appear to be more variable in males compared with females (i.e. males tend to be over-represented at both ends of the general intelligence overall distribution)35.\n\nSee website at http://www.ncbi.nlm.nih.gov/genome/tools/gdp. Please note that genes causing ID tend to concentrate in G-negative bands, like all other genes. CI, cognitive impairment; DD, developmental delay; ID, intellectual disability; MR, mental retardation.\n\nlongnc, long non-coding; Mb, megabase; miscnc, miscellaneous non-coding; MR/ID, known mental retardation/intellectual disability genes; shortnc, short non-coding.\n\nOver the years, we and others have kept track of XLID conditions and genes29,36–39, and both sequencing40,41 as well as microdeletion/duplication searches42 have been used to identify genetic determinants of XLID. More genes are still being identified with exome sequencing of informative families30.\n\nOn the other hand, many syndromes with ID have been linked to autosomal loci, and in recent years a quest for ID genes on the autosomes has progressed rapidly. Recessive forms of both syndromic and “pure” ID have been identified thanks to the study of large consanguineous families coming from non-European countries like Iran43,44. However, large recessive pedigrees are rare, whereas many sporadic cases are observed among children of non-consanguineous parents, suggesting an autosomal dominant de novo origin45,46. These cases can be diagnosed by using next-generation sequencing (NGS) analysis techniques47 that have become available at more affordable prices in recent years.\n\nDepending on the clinical signs and after an initial screening for fragile X syndrome (mostly with polymerase chain reaction [PCR]-based techniques) and for copy number variants (CNVs), usually with array comparative genomic hybridization (array-CGH), many patients will hopefully receive a diagnosis thanks to NGS using resequencing gene panels, whole exome sequencing (WES), or WGS. Resequencing panels with tens or even hundreds of genes are very useful to screen large cohorts of patients in a cost-effective way and with sufficient confidence to write a report. For example, a diagnostic NGS test screening 99 X-linked and 118 autosomal genes48 has identified a causative mutation in 25% of 96 male and 10 female patients with ID (who had previously tested negative for fragile X and had a normal array-CGH). If WES or WGS is employed and a de novo mutation is suspected, it is useful to analyze the proband-parents trio in order to reduce the number of variants. Finally, a note of caution should be made about the interpretation of rare variants: even a de novo loss-of-function mutation should not be automatically considered pathogenic, as pointed out by Piton et al.29 for some XLID genes.\n\n\nGene Ontology analysis of intellectual disability genes\n\nTo provide an overview of the functions of the proteins encoded by genes listed in Supplementary Table 2, we performed a GO analysis using the free tool DAVID (Database for Annotation, Visualization, and Integrated Discovery) 6.7 (https://david.ncifcrf.gov/)49. We analyzed the 818 official gene symbols with the following DAVID tools: functional clustering, functional annotation, and functional table. To perform the analysis, we selected only the three main GO categories: Biological Process (BP_all), Molecular Function (MF_all), and Cellular Component (CC_all). We used medium stringency and default settings for the analysis, selecting Homo sapiens as the background species.\n\nOf the 818 gene symbols, 774 (95%) were present in the DAVID GO dataset. Unmapped IDs are listed in Supplementary Table 3a. The three DAVID functionalities summarize the results in different ways, providing a clustering of the GO terms on the basis of fold enrichment and relationships among ontology terms (functional clustering; see Supplementary Table 3b) or providing statistics of the ontology terms present in the results (functional annotation; see Supplementary Table 3c). The functional chart (see Supplementary Table 3d) reports the GO description for each gene present in the input list. We used functional clustering to highlight the over-represented GO terms, using an arbitrary fold enrichment cutoff of 10.00 (see Supplementary Table 3e). These clusters show an enrichment of cellular organelle (mainly mitochondria) assembly and functions.\n\nGO results, by definition, are redundant and thus can be difficult to visualize. In fact, GO vocabularies are created as acyclic graphs, in which each term follows a hierarchical structure and has a “parent term” and a “child term”, and the complexity is increased by the fact that each term is allowed to have multiple parent and child terms. This confers multiple levels of interpretation to the GO analysis, although the increasing number of parent/child terms does not always add useful information50,51. To overcome this issue, DAVID functional annotation results, together with their relative p values and fold enrichment values (see Supplementary Table 3f), were further used for REViGO (Reduce + Visualize Gene Ontology) analysis (http://revigo.irb.hr/)52. All terms were included, using the following parameters: allowed similarity = 0.5 (small); first values provided = p values; database with GO term sizes = Homo sapiens; semantic similarity measure = SimRel. We decided to use the tree view for each main category (Biological Process, Cellular Component, and Molecular Function). Figure 6 shows the two graphs obtained with REViGO summarizing the over-represented (a) Biological Process or (b) Cellular Component GO terms associated with the 818 ID genes. These pictures underline that multiple essential metabolic pathways, especially those related to energy production, are highly associated with the 818 ID genes (a). Also, the Cellular Component GO terms are diversified (b), and mitochondria are well represented.\n\nPanel (a) shows Biological Process terms and panel (b) shows Cellular Component terms. DAVID, Database for Annotation, Visualization, and Integrated Discovery; REViGO, Reduce + Visualize Gene Ontology.\n\nFinally, we evaluated the 818 ID gene list with g:Profiler53,54, another useful GO annotation tool (http://biit.cs.ut.ee/gprofiler/), which scans not only GO terms but also other datasets like the Human Phenotype Ontology project55. Results obtained with g:Profiler are reported in detail in Supplementary Table 4 and confirm the variety of cellular components involved in ID pathogenesis, and mitochondria again show up in the list (see Supplementary Table 4c), and among the top GO Biological Processes are “(central) nervous system development” and “neurogenesis” (see Supplementary Table 4b). Interestingly, when the Human Phenotype Ontology terms are examined (see Supplementary Table 4e), the first two terms of the list (with a highly significant p value of 9.61 × 10-297) are “Neurodevelopmental abnormality” and “Intellectual disability”, followed by “Abnormality of nervous system physiology” (p value: 7.36 × 10-169) and “Neurodevelopmental delay” (p value: 9.14 × 10-143).\n\n\nIdentification of (new) intellectual disability genes\n\nSeveral strategies have been employed to identify ID genes over the years. A thorough clinical examination of the proband(s) and the reconstruction of the family history are mandatory15 before any attempt is made to pinpoint the responsible gene. In fact, understanding the genetic context (sporadic/familial and dominant/recessive) and collecting all clinical evidence (“diagnostic handles”) facilitate reaching a diagnosis. Furthermore, fragile X syndrome should be excluded by using the available PCR-based tests, considering the frequency of this condition and the dynamic nature of most mutations in the FMR1 gene56, and array-CGH should be performed as a first-tier test to detect or exclude the presence of potentially relevant CNVs57. It is important to remember that if a CNV is detected, not only is the gene content of the deleted/duplicated region important but also the potential “position effects” (due to deletion or displacement of enhancers) are extremely relevant58–60. However, even if array-CGH results were normal, a standard karyotype and confirmatory fluorescence in situ hybridization (FISH) analysis would still be necessary if a balanced translocation/inversion is suspected.\n\nThen, if clinical examination and the first-tier tests (fragile X and array-CGH) are normal and balanced chromosomal aberrations have been excluded, direct searching for single-nucleotide variants (SNVs) or small insertions/deletions (indels) may be performed by using NGS techniques. Depending on the available resources, including bioinformatic support, either a large panel of known or candidate ID genes can be screened (as shown by 48) or the (currently known) human exome (WES) or genome (WGS) could be investigated. These latter approaches can potentially identify “new genes” responsible for ID, although the number of variants identified in each patient is challenging and not always easily interpreted41. The availability of at least the patient’s parents (trio analysis) facilitates variant interpretation45, and many laboratories prefer to invest the extra resources in order to increase the chances of reaching a diagnosis.\n\nWhen examining the results of any WES/WGS experiment, known disease genes (e.g. OMIM genes) should be examined first if mutations are identified in any of them, even if the phenotype of proband(s) does not correspond to that already reported in the literature, since phenotypic heterogeneity is common in human genetics. Furthermore, SNV or indels identified in regulatory and untranscribed or untranslated regions of a specific ID gene could eventually be linked to abnormal transcript levels that cause the disease phenotype, as was found to occur in the X-linked HCFC1 gene61; however, such sequence changes are extremely difficult to detect since they do not fall in the open reading frame and their effect might be appreciated only if mRNA levels were quantitated62.\n\nIn any case, a (long) list of potentially causative variants in several genes is the typical result of WES/WGS experiments and therefore prioritization of candidate variants (based on the presumed effect on the encoded protein)63 is very important to identify the (new) causative ID genes64. Gene prioritization establishes a ranking of candidate genes on the basis of their relevance to the biological process of interest: this is a critical process since the “real” causative gene might be excluded from further analysis depending on the criteria chosen by the researcher. Several computational approaches have been developed for selecting disease candidate genes65,66 on the basis of either functional (what they do) or topological (where they do it) similarity to known disease genes.\n\nIn the postgenomic era, when large sets of data are available on the majority of human genes, numerous correlations can be established to connect genes in networks on the basis of their sequence similarity (paralogues encoding similar proteins), similar transcriptional profile (genes with the same expression in various tissues), similar protein function (GO description), or interaction of the encoded proteins (genes encoding interacting proteins). Systems biology, by integrating heterogeneous datasets such as expression data, sequence information, functional annotation, and the biomedical literature, allows reconstruction of gene networks and molecular pathways relevant for the different physiological and pathological conditions and accelerates the interpretation of monogenic as well as complex neurodevelopmental conditions67.\n\nVery recently, software packages like Exomizer68, PhenIX69, and OVA70 have been made available that also incorporate phenotypic information in the prioritization process, significantly increasing its efficiency71. This extra layer of information, directly related to the specific disease affecting the patient(s), can be added to the bioinformatics analysis pipeline thanks to the terminology standardization efforts of the Human Phenotype Ontology project55.\n\nFinally, given the association between some human diseases and non-coding RNAs72, it is important to keep in mind the possible role of non-coding RNAs in the pathogenesis of ID, as suggested by the analysis performed by Gudenas and Wang73 on long non-coding RNAs and CNVs in ID patients. In fact, pathogenic mutations in RNAs that do not code for proteins shall not be detected by WES and may also be missed by WGS, depending on the quality of sequence annotation.\n\n\nTranscriptional profiles, Brain ratio, and Fetal Brain ratio\n\nProbably one of the most relevant factors determining the relevance of a specific gene in causing a given phenotype is its transcriptional profile. When manually inspecting the results of WES/WGS experiments, immediately after scoring for the effect of identified variants on protein sequence, researchers ask about the expression of the candidate gene in the relevant tissue (e.g. brain for the ID phenotype). A number of databases collect mRNA expression data of multiple experiments (for example, the Gene Expression Omnibus [GEO] database, which is available at http://www.ncbi.nlm.nih.gov/geo/). A user-friendly gene expression portal is BioGPS (available at http://biogps.org/), initially established by the Genomics Institute of the Novartis Research Foundation74,75. Five reference datasets can be visualized with BioGPS, but the most reliable human dataset (GEO dataset GSE1133) explores 79 human tissues—including 21 from the central nervous system (CNS)—and was obtained in 2004 with the Affymetrix U133A arrays76.\n\nWe decided to reanalyze the transcriptional profile of 30 brain areas and 49 other tissues of the human body (all in triplicate) that were explored with the Affymetrix U133 Plus 2.0 (a more recent chip with more identified transcripts) by Neurocrine (GEO dataset GSE7307 entitled “Human body index - transcriptional profiling”). Part of this dataset (comprising 20 CNS areas) has been reported by Roth et al.77 (2006), but the complete dataset is more comprehensive and gives the opportunity to visualize the transcriptional profile of 20,588 annotated genes and to compare the CNS and the rest of the body. In our analysis, we used the Neurocrine dataset to prioritize all available protein-coding genes on the basis of their relative expression level in the brain78. In fact, since the absolute expression value of a given transcript varies considerably compared with others, we first calculated an average level of expression in both CNS and non-CNS tissues for each available transcript and then we derived a “Brain ratio” (BR) defined as the average expression in (adult) CNS divided by the average expression in all other tissues. Such a ratio allows an easy and efficient comparison between genes with different “absolute” levels of transcription, highlighting those that are relatively more expressed in brain and therefore presumably more important for CNS function (and presumably cognition). We then ranked all 20,588 annotated genes by decreasing BR and found that approximately 8% of all protein-coding genes have a BR above 2 but that approximately 10% of the 818 ID genes and approximately 25% of all XLID genes have a BR above 278. Supplementary Table 5 reports the list of the 84 ID genes with a BR of more than 2 (plus two more genes immediately following in the ranking in positions 85 and 86) and their corresponding calculated BRs as well as the functional clustering and annotation obtained with DAVID and the list of GO terms used for REViGO. Finally, we also calculated a “Fetal Brain ratio” (fBR) (expression in fetal brain divided by average expression in adult CNS), and the list of 64 (out of the 818) ID genes with an fBR above 2 is reported in Supplementary Table 6 along with the results of the DAVID analysis.\n\nCareful inspection of Supplementary Table 5a suggests that genes with a high BR are usually mutated in nonsyndromic (“pure”) forms of ID but that ID genes with a lower BR (being more ubiquitously expressed) associate with syndromic ID conditions. Similarly, examination of Supplementary Table 6a suggests that genes with a high fBR are sometimes mutated in brain malformations, consistent with their developmental function78. Figure 6 and Figure 7 visually illustrate the above-mentioned concepts thanks to the REViGO analysis of GO terms, and the comparison of the two figures is important: whereas REViGO analysis of all 818 ID genes showed a patchwork of very different Biological Process (Figure 6a) GO terms, Figure 7a (based on the 84 ID genes with a BR of more than 2) clearly points to cell-cell signaling, synaptic function, and transmission of the nervous impulse and Figure 7b (based on the 64 ID genes with an fBR of more than 2) has 50% of GO terms pointing to regulation of transcription and the other 50% pointing to cell movements and developmental patterning. These differences are also apparent when g:Profiler is used to analyze the GO terms over-represented in these two lists (see Supplementary Table 7).\n\nPanel (a) shows GO (Biological Process) terms associated with the 86 intellectual disability (ID) genes with a Brain ratio of 2 or more, while panel (b) shows GO (Biological Process) terms associated with the 64 ID genes with a Fetal Brain ratio of 2 or more. DAVID, Database for Annotation, Visualization, and Integrated Discovery; REViGO, Reduce + Visualize Gene Ontology.\n\n\nConclusions\n\nTo date, more than 800 genes are known to be involved in the pathogenesis of syndromic and nonsyndromic conditions with ID (see Supplementary Table 2), and the functions of their respective proteins are very different. Since 800 out of ~4500 human disease genes currently listed in OMIM is ~18%, if we suppose that the same proportion of all human genes (~20,000) is related to ID, this would suggest that up to 3500 human genes (when mutated) could cause a Mendelian condition that includes ID as one of its components. However, this could be an overestimation since many human morbid genes currently reported by OMIM might have been identified also thanks to their ID phenotype: a more conservative estimate, based on the proportion of 10.5% of all protein-coding genes on the X involved in ID (Figure 5) that could be extended to the autosomes, leads to an estimate of approximately 2000 genes that, if mutated, would cause syndromic or nonsyndromic ID. Mutations in some of these genes might actually prove lethal during embryogenesis, but thanks to the new powerful sequencing techniques and more sophisticated bioinformatics pipelines, we might eventually identify all remaining protein-coding ID genes.\n\nIn any case, analysis of a gene’s transcriptional profile will be useful for the prioritization of candidate genes, and their relative expression in the adult or fetal CNS, estimated with the BR (or fBR), will facilitate comparison among genes with very different absolute levels of transcription. We have to remember that, although we expect that most genes with a high BR (e.g. above 2) will mainly impair cognition whenever mutated, the majority of ID genes are also expressed in many other tissues (i.e. have a low BR) and will usually have a syndromic clinical presentation.\n\n\nSupplementary material\n\nSupplementary Table 1 - OMIM terms search results.\n\nClick here to access the data.\n\nSupplementary Table 2 - ID Genes identified through OMIM and NCBI Gene.\n\nClick here to access the data.\n\nSupplementary Table 3 - DAVID analysis of ID genes.\n\nClick here to access the data.\n\nSupplementary Table 4 - gProfiler analysis of ID genes.\n\nClick here to access the data.\n\nSupplementary Table 5 - DAVID and REVIGO analysis of genes with Brain Ratio above 2.\n\nClick here to access the data.\n\nSupplementary Table 6 - DAVID and REVIGO analysis of genes with Fetal Brain Ratio above 2.\n\nClick here to access the data.\n\nSupplementary Table 7 - gProfiler analysis of genes with Brain/Fetal Brain Ratio above 2.\n\nClick here to access the data.",
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{
"id": "13267",
"date": "07 Apr 2016",
"name": "Jozef Gécz",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13268",
"date": "07 Apr 2016",
"name": "Hans van Bokhoven",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-599
|
https://f1000research.com/articles/4-484/v1
|
05 Aug 15
|
{
"type": "Software Tool Article",
"title": "Finding the shortest path with PesCa: a tool for network reconstruction",
"authors": [
"Giovanni Scardoni",
"Gabriele Tosadori",
"Sakshi Pratap",
"Fausto Spoto",
"Carlo Laudanna",
"Gabriele Tosadori",
"Sakshi Pratap",
"Fausto Spoto",
"Carlo Laudanna"
],
"abstract": "Network analysis is of growing interest in several fields ranging from economics to biology. Several methods have been developed to investigate different properties of physical networks abstracted as graphs, including quantification of specific topological properties, contextual data enrichment, simulation of pathway dynamics and visual representation. In this context, the PesCa app for the Cytoscape network analysis environment is specifically designed to help researchers infer and manipulate networks based on the shortest path principle. PesCa offers different algorithms allowing network reconstruction and analysis starting from a list of genes, proteins and in general a set of interconnected nodes. The app is useful in the early stage of network analysis, i.e. to create networks or generate clusters based on shortest path computation, but can also help further investigations and, in general, it is suitable for every situation requiring the connection of a set of nodes that apparently do not share links, such as isolated nodes in sub-networks. Overall, the plugin enhances the ability of discovering interesting and not obvious relations between high dimensional sets of interacting objects.",
"keywords": [
"biological networks",
"shortest path",
"pesca",
"protein protein interaction networks",
"connect isolated node",
"cytoscape"
],
"content": "Introduction\n\nNetwork analysis is a hot area of investigation in different, apparently unrelated, research fields. In particular in biology, biotechnology, and biomedical research, consistent efforts are being carried out in order to investigate how complex biological processes work1. In this scenario a disease, a metabolic pathway or a coexpression microarray could be analyzed by means of network theroretical formalisms such that the structural properties of such models can be quantified2. The central point of this approach concerns the emergence of peculiar properties3 arising when a set of distinct objects reciprocally interact generating a functionally integrated system. In this context, the goal is to uncover the complex behaviors, hidden by system complexity, that are specific to a particular system. The interactions between objects are abstracted as graphs and analyzed by means of graph theory. Thus, it is possible to study the topological role of each network component (node), to uncover hidden structural patterns, find clusters, or even simulate the time evolution of specific network topologies.\n\nIn order to identify the hidden properties of a complex system, as a first step it is necessary to reconstruct a network representing the system under investigation. Cytoscape4 has several built-in tools allowing network reconstruction and analysis. Notably, in systems biology one general assumption implies that the informational flow follows a maximum parsimony principle (see Box 3 in 5). Consequently, computing the shortest path in a network can have direct functional implications. Such capability is, however, lacking in the basic Cytoscape core. Several algorithms have been developed in order to solve the shortest paths problem, such as Dijkstra6, Floyd-Warshall7, Bellman-Ford8. Here we describe PesCa, a novel Cytoscape app specifically designed to compute the shortest paths between two or more nodes in a network, thus permitting the reconstruction of sub-networks based on the maximum parsimony principle. The generated clusters allow focusing the analysis on sets of nodes characterized by reduced topological complexity. Many options are also implemented, enabling the users to investigate different aspects of network complexity.\n\n\nMethods\n\nPesCa is a Cytoscape app, thus it is not standalone, but only works in conjunction with the Cytoscape environment. The release of PesCa presented here is developed for the 3.x Cytoscape series. The version for the 2.x series is no longer updated and lacks the features of the new release. Since the new version of Cytoscape has a new structure and uses a different architecture the new PesCa is developed and maintained only for the 3.x platform.\n\nThe PesCa core is based on the All Pair Shortest Paths (APSP) version of the basic Dijkstra algorithm, single thread; it performs a modified version of the APSP search that finds all the shortest paths between each couple of nodes. Furthermore, PesCa offers further options: for example the Multi Shortest Paths (S-P Cluster) is an APSP version computing the shortest paths between all selected nodes in a specific network. The Multi Shortest Paths Tree is a modified version of an APSP searching all the shortest paths connecting a single selected node to all other nodes in a network. PesCa is also designed to extract a fully connected sub-network from a giant network component, thus allowing connecting nodes that apparently do not interact with other network regions (isolated nodes).\n\nFigure 1 shows the main panel and the tasks that can be accomplished with PesCa:\n\nMulti Shortest Paths Tree allows computing all the shortest paths connecting a node to all other nodes in a network.\n\nMulti Shortest Paths (S-P Cluster) allows computing the shortest paths connecting two or more selected nodes in the network. It allows generating network sub-clusters (modules) based on minimal cost.\n\nConnect isolated nodes allows finding all the connecting shortest paths between the isolated node and a group of other nodes in a network (the so called Giant component).\n\nNotably, the Connect isolated nodes function connects a node to the nearest nodes in the selected sub-network: this means that the task does not return, as a result, all the shortest paths between the node and the selected subnetwork. Only the shortest paths between the node and the nearest node(s) in the selected cluster are given. It is important to note that the nodes that form the Giant component don’t have to share links. The so called Giant component is a set of nodes that is considered as a unique target for this task: the shortest paths are found from the isolated node to this set of nodes. Upon selection of the Connect isolated nodes function, a wizard dialog opens guiding the user through the sequence of steps necessary to complete the task.\n\nFor each function PesCa has a button, indicated with a question mark, that opens a new window defining the characteristics and the steps concerning the selected task. The app has several windows that appear during usage, designed to help users. For instance, by selecting the Multi Shortest Paths (S-P Cluster) option and then clicking on the Start button without choosing the minimum number of nodes required, the app presents a window prompting to the user to select two or more nodes. Every time that the selected input does not correspond to the expected input, PesCa presents a dialog in order to help the user in selecting the appropriate entries.\n\nIt is also possible to analyze directed and undirected networks, depending on the characteristics of the edges. Analysis of networks with weighted edges is also allowed. Notably, edges can have positive and negative weights. If this option is selected, after clicking Start, a window will appear asking for the name of the attribute that stores the information about the weights (edge attribute). Notably, weighted edges can simply correspond to edge length but also provide information about the functional influence of a node on another node(s), such as, for instance, in transcriptomics networks. Thus, this PesCa function may introduce interesting possibilities in the analysis of gene expression networks.\n\nWith relatively small networks, e.g. the IntegrinActivation_FN.sif pre-loaded network, PesCa does not require high rates of memory nor long computational times; for instance, only a few seconds are necessary to perform a Multi Shortest Paths Tree on a Xubuntu 13.10 machine with an Intel®i5, 2.80GHz CPU and 4 GB of RAM. This network has 3091 nodes and 97115 edges and can be automatically loaded within PesCa. Indeed, the PesCa panel also offers a Select network scrollable menu that permits loading a set of pre-loaded biological networks, in different file formats. The description of these networks is provided at http://dp.univr.it/~laudanna/LCTST/downloads/index.html. These networks, and many others, are freely available for the download from this website.\n\n\nUse cases\n\nA few case studies are now provided, illustrating the functionality of PesCa. The first example describes how to perform a Multi Shortest Paths (S-P Cluster) retrieval: the goal is to find all the shortest paths that link two, or more, selected nodes. Figure 2 shows the analysed network (which is provided as Supplementary material): ten numbered nodes and 14 undirected edges. The nodes that were used to compute the shortest paths are in yellow: Node 1 and Node 9. After node selection, by clicking the Start button PesCa performed the search.\n\nThe result panel in Figure 3 shows the output. The table on the top of the panel lists the retrieved shortest paths, the source for each path and its size. The size, i.e. the length, of a shortest paths is given in terms of how many edges are needed to reach the target. PesCa found four shortest paths, two starting from Node 1 to Node 9 and two starting from Node 9 to Node 1: their length is four. The table below the one already described shows how many paths have a specific length: it groups the paths by their size. In this example PesCa found two shortest paths of length four. It states two shortest paths because the network is undirected and, since the edges are bidirectional, PesCa considers the path \"Node 1 to Node 9” equal to the path \"Node 9 to Node 1”. Consequently only two paths are listed: one passes through Node 8, 7 and 4, the other one passes through the Node 8, 10 and 4. The last table, at the bottom, shows some characteristics of the network: the average path length is four, the number of unique short paths is two and two other parameters are not relevant to this example.\n\nPesCa retrieved the shortest paths giving the sequence of the nodes that are involved which could be highlighted by selecting a specific path in the table. Furthermore, the button in the top left corner, pass through S-P, enables the user to highlight the shortest paths passing through a selected node.\n\nThe second example is used to describe the third table in the results panel, the one with the missing values. By using the network in Figure 2 a Multi Shortest Path Tree was computed. To carry out this analysis it is necessary to select a node; in this case Node 1 is used. In Figure 7 the results are shown. The interesting point here is the bottom table; all the options are now defined by a value: the average path length, the number of unique shortest paths, the number of expected paths, and the Connected column. The number of expected paths refers to the total number of shortest paths a network is supposed to develop if it is fully connected. The Connected column could be True or False and states if all the nodes are able to communicate together by means of a path. The network in Figure 2 is connected and the column states True. Now, if the edge between Node 4 and Node 7 is removed, then two different connected components will appear. The network is now disconnected and the value will be False. Furthermore, if a network is directed, see Figure 4, the returned value can be both True or False. In the example it will be True if the Multi Shortest Path Tree is computed from Node 1. It will be False if the Multi Shortest Path Tree is computed from Node 2 and 3 because neither are able to reach Node 1.\n\nThe third example describes how to use the Connect isolated component. Figure 5 shows the network used for the analysis. Again, there are ten nodes, fourteen edges, and a few highlighted nodes in yellow. In this analysis, PesCa retrieved the paths from Node 6 to the cluster formed by Node 8, 9 and 10. After selecting the option, by clicking Start, a window shows up like the one in Figure 6, and guides the user in selecting the Giant component. The Giant component is the cluster to which PesCa will connect the node. In this example the component is represented by Node 8, 9 and 10. By selecting it and then clicking Ok the user is able to choose the Isolated Node: highlight Node 6 and then click on Ok. Finally by clicking Start, PesCa will run the algorithm.\n\nThe results show two shortest paths, one reaching Node 8 and one reaching Node 10; Node 9 is not considered as a target because it does not develop a shortest path with Node 6 since it is connected to Node 6 by means of Node 8 and 10.\n\n\nSummary\n\nWe have briefly introduced the main functionalities of PesCa. We described a few application cases by using a very simple network in order to show how to setup the input and how the output panel works. Overall, PesCa is designed for sub-network retrieval and shortest paths search and, in the Cytoscape context, it is the only app that performs this task. It can be used to enhance the predictive power of biological networks by reducing the complexity of the processes under investigation and, in conjunction with other apps, it permits the researcher to deeply investigate the properties of subsets of nodes.\n\n\nSoftware availability\n\n1. Software available from: http://apps.cytoscape.org/apps/pesca30\n\n2. Latest source code: https://bitbucket.org/giovanniscardoni/pescareleaseforcy3public\n\n3. Link to archived source code as at time of publication: http://dx.doi.org/10.5281/zenodo.211459\n\n4. Software license: Lesser GNU Public License 3.0: https://www.gnu.org/licenses/lgpl.html",
"appendix": "Author contributions\n\n\n\nGS designed and implemented the software, GT wrote the manuscript, SP implemented the software, FS participated in the design, CL participated in the design and in the revision of the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interest were disclosed.\n\n\nGrant information\n\nThis work was supported by: Italian Association for Cancer Research (AIRC, IG 8690) (C.L.); Fondazione Cariverona; Nanomedicine project University of Verona and Fondazione Cariverona (C.L.). Part of the software was developed thanks to the Google Summer of Code 2014.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nSupplementary material\n\nAnalysed network for use cases. Available as a simple interaction file.\n\nClick here to access the data\n\n\nReferences\n\nIdeker T, Galitski T, Hood L: A new approach to decoding life: Systems biology. Annu Rev Genomics Hum Genet. 2001; 2(1): 343–372. PubMed Abstract | Publisher Full Text\n\nPavlopoulos GA, Secrier M, Moschopoulos CN, et al.: Using graph theory to analyze biological networks. BioData Min. 2011; 4(1): 10. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBhalla US, Iyengar R: Emergent properties of networks of biological signaling pathways. Science. 1999; 283(5400): 381–387. PubMed Abstract | Publisher Full Text\n\nShannon P, Markiel A, Ozier O, et al.: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003; 13(11): 2498–2504. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBarabasi AL, Gulbahce N, Loscalzo J: Network medicine: a network-based approach to human disease. Nat Rev Gene. 2011; 12(1): 56–68. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDijkstra EW: A note on two problems in connexion with graphs. Numer Math. 1959; 1(1): 269–271. Publisher Full Text\n\nFloyd RW: Algorithm 97: Shortest path. Commun ACM. 1962; 5(6): 345. Publisher Full Text\n\nBellman R: On a routing problem. Quart Appl Math. 1958; 16(1): 87–90. Reference Source\n\nScardoni G, Tosadori G, Pratap S, et al.: Finding the shortest path with PesCa: a tool for network reconstruction. Zenodo. 2015. Data Source"
}
|
[
{
"id": "9882",
"date": "24 Aug 2015",
"name": "Ferenc Jordán",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe Authors present a useful Cytoscape app for calculating shortest paths in networks.This is useful with the following comments to be considered:I do not suggest to use the words \"isolate\" and \"giant component\" for the situation when the distance between a well-defined node a well-defined subnetworks is to calculated. In network science, there is enough confusion about certain concepts, it is better to avoid adding more. If you refer to a \"selected node\" and a \"selected subgraph\", everything is perfectly understandable and there is no confusion.In the second paragraph (4th line) of the Introduction, you speak about \"reconstructing\" networks. Why not simply \"constructing\"?The maximum parsimony principle may work well or may not work at all, depending on the actual problem. I do not suggest to use it as a general assumption. It would be more interesting (and a lot more useful) to dedicate a brief paragraph for this isssue: when does it make sense (network flows flow shortest paths) and when it does not (network flows do not prefer shortest paths).In the legend of Figure 2, you mention node 6 instead of node 1.In Figure 5, I suggest to keep nodes 8, 9 and 10 yellow but to use another colour for node 6.Please add a bit more explanation about how to manage information about link direction, link weight and link sign in the database. Can you convert (symmetrize, binarize) and if yes, how does it happen (e.g. how to determine weight if you symmetrize AB and BA with different weights?).What happens if a node is really isolated (degree equals zero in the original graph)? Can you perform a calculation based on the reciprocal distance matrix?",
"responses": []
},
{
"id": "9885",
"date": "01 Sep 2015",
"name": "Ankush Sharma",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors describe the useful PesCa app for Cytoscape version 3.x for computing the shortest paths in networks and shortest paths connecting any two selected nodes and reconstruction of subnetworks based on maximum parsimony principle. The PesCa app scales well with efficiency in computation time on large networks. I agree with the point raised by reviewer 1 in version 1 of referee report. Minor concernUsing terminology such as isolated nodes (nodes with no connection) and giant networks is making article confusing. Maximum parsimony principle needs to be elaborated in details. and how it scores over other methods such as maximum likelihood used for reconstruction of weighted and unweighted networks along with one illustrative example will help in better understanding of the concept. The representational figure 2 for demonstrating short paths from node 1 to node 9 can be improved by coloring edges involved in short paths with different color.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/4-484
|
https://f1000research.com/articles/5-165/v1
|
12 Feb 16
|
{
"type": "Research Article",
"title": "Sequence and intramolecular distance scoring analyses of microbial rhodopsins",
"authors": [
"Miki Asano",
"Shunta Ide",
"Atsushi Kamata",
"Kiyohiro Takahasi",
"Tetsuji Okada",
"Miki Asano",
"Shunta Ide",
"Atsushi Kamata",
"Kiyohiro Takahasi"
],
"abstract": "Recent accumulation of sequence and structural data, in conjunction with systematical classification into a set of families, has significantly advanced our understanding of diverse and specific protein functions. Analysis and interpretation of protein family data requires comprehensive sequence and structural alignments. Here, we present a simple scheme for analyzing a set of experimental structures of a given protein or family of proteins, using microbial rhodopsins as an example. For a data set comprised of around a dozen highly similar structures to each other (overall pairwise root-mean-squared deviation < 2.3 Å), intramolecular distance scoring analysis yielded valuable information with respect to structural properties, such as differences in the relative variability of transmembrane helices. Furthermore, a comparison with recent results for G protein-coupled receptors demonstrates how the results of the present analysis can be interpreted and effectively utilized for structural characterization of diverse protein families in general.",
"keywords": [
"Membrane",
"receptor",
"opsin",
"crystallography",
"coordinates"
],
"content": "Introduction\n\nMicrobial rhodopsins (MRs) are retinal proteins found in archaea, bacteria and eukaryotic algae. They share a common architecture including a heptahelical transmembrane (7TM) bundle and function as either light-dependent proton/ion transporters or photon sensors. Recent introduction of these proteins to brain research has substantially advanced our understanding of neuronal functions1,2. As a prototypical member of this family, bacteriorhodopsin (bR) and its proton-pumping mechanism have been studied extensively over the past forty years3,4. There are more than 130 wild type and mutant crystal structure entries of bR deposited in the Protein Data Bank (PDB). In addition to other retinal proteins found early in archaea, such as halorhodopsins and sensory rhodopsins, recent studies have demonstrated the presence of a number of proteins belonging to MR family in a wide range of organisms5,6. Crystal structures obtained for some of these proteins have shown that the arrangement of the seven helices is conserved7,8, and their 7TM domains are valuable for examinations of the effects of experimental conditions and sequence variation on structure.\n\nAnother class of well-known 7TM proteins are G protein-coupled receptors (GPCRs), for which more than 120 crystal structure entries are available in PDB. They all activate heterotrimeric G proteins upon agonist binding, but their seven helices exhibit significant divergence, reflecting a high degree of ligand variation, from small amines to peptide hormones9,10. A recent study demonstrated that, despite such variation among GPCRs, some conserved features in terms of intramolecular atomic distances were discernible11. This observation was based on a systematic analysis of Cα−Cα distances in crystal structures archived in PDB and hereafter we refer to this method as distance scoring analysis (DSA). For DSA, scoring of distance conservation among a set of crystal structures is simply made by taking the inverse of the coefficient of variation, wherein this coefficient is the average divided by the standard deviation.\n\nIf the number of available structures for this analysis was enough, it would be expected that structural differences due to either experimental conditions or sequence variation could be separately evaluated. In the previous analysis on GPCRs, we mainly focused on how the scores for Cα−Cα distances in the 7TM bundle change as more variation in sequence was included because the apparent structural differences among receptors from different classes (rhodopsin-like, and others) were so large11.\n\nIn the present study, we show that the DSA approach previously applied to GPCRs is also useful for highlighting bR and other MR helical regions that are relatively insensitive to the factors possibly affecting 7TM bundle structures. From the analysis of wild-type dark-state bR structures, we found that crystal packing could affect variability of a specific region of the 7TM bundle. On the other hand, the analysis of all MRs of known structure suggests that the regions involving high-score Cα−Cα distances appear to be highly correlated with the functional importance. Furthermore, a comparison between two classes of 7TM proteins, MRs and GPCRs, demonstrates how the present analysis can be applied to diverse proteins families in general.\n\n\nResults\n\nAside from the conventional serial numbering of polypeptide amino acids from the amino terminus, a common numbering system for a set of proteins based on conserved positions is expected to facilitate comparative protein family studies. A remarkable example involves GPCRs, for which an amino acid position in 7TM helices is given a common number (a BW number)12. For example, the most highly conserved asparagine in helix I is referred to as 1.50 and the other residues in the helix are numbered in descending order toward the amino-terminal side or increasing order toward the carboxyl-terminal side. Thus, our selection of helix I in the previous analysis corresponds to a polypeptide range of 1.35 to 1.59 (25 residues). Such a clear definition of polypeptide positions is very important for the quantitative analysis of structures that have different underlying sequences.\n\nSince no such numbering scheme has been proposed for MRs, we first analyzed the amino acid sequences for this family archived in the InterPro database (www.ebi.ac.uk/interpro/) and identified the most conserved position in each of 7TM helices. Based on 603 sequences that include archaeal (178), bacterial (182), and algal (243) retinal proteins, an alignment was created and the distribution of amino acid types at each position was obtained, as shown in Table S1. The most highly conserved residue position in each helix was identified (Figure S1) and assigned a number, *.50, in which “*” indicates a letter for helix identification. Since helix assignment with A to G has been frequently used for MRs, we follow this convention for helix description of this family. However, for residue numbering, we use numerals 1 to 7 for “*” in the present study in order to avoid confusion with single letter representation of amino acids.\n\nSince we only considered possible retinal proteins, the amino acid type at 7.50 was Lys, and it exhibited 100% conservation (Table 1). Helix F contained three highly conserved residues, which we designated 6.50 (Trp), 6.53 (Tyr), and 6.54 (Pro). The degree of conservation was very similar for 6.50 and 6.53, and higher than 97% among the 603 sequences. Helix C also contained a set of positions that exhibited greater than 95% conservation. At all these positions, the amino acid types, except 5.50 in helix E, were identical among the 13 MRs examined by DSA in the present study (Figure S2).\n\nAs of February 5_2015, there were 135 entries for MRs in PDB and the contents are summarized on our website (www.gses.jp), which does not include redundant or outdated structures. By examining the superimposed chains from various proteins, we selected a range of amino acids for each of the seven helices with at least 22 residues per helix (~ 6 turns for regular geometry), resulting in a total of 170 residue bundles. Thus, we considered 14,365 Cα−Cα pairs per 7TM bundle for the present analysis. From this archive, we made several data sets containing different combinations of polypeptide chains. Set 1 consisted of 9 chains of wild-type, dark-state bR, each of which represents a structure solved in a distinct space group or by a different research group. Set 2 (Figure 1A) was more redundant than set 1, including multiple chains per entry, resulting in a total of 22 chains (Table S2). Set 3 contained a set of 13 chains (Figure 1B), each from structures with a unique sequence, as shown in Table 2. The other sets included, for instance, bR mutants, dark-state halorhodopsins and sensory rhodopsins. The results for these sets, other than 1 to 3, will be described elsewhere (Ono et al. unpublished report).\n\nA. 22 polypeptide chains in set 2 (dark-state wild-type bR structures) and B. 13 unique chains in set 3 (MRs of different sequences).\n\nIn all PDB entries for MRs, the most abundant structure was bacteriorhodopsin from Halobacterium salinarum. Thus, we are interested in determining how effective DSA is in detecting the intramolecular structural conservation among the ground-state wild-type bRs. The superimposed projection view of 22 chains in set 2 is shown in Figure 1A. These are obviously very similar to each other and are within the overall pairwise root-mean-squared deviation of 1.2 Å for 170 Cα positions (Table S4). This similarity corresponds to a pairwise correlation coefficient of more than 0.993 calculated for the 14,365 Cα−Cα distances.\n\nDSA results obtained from these 22 chains in set 2 and from 9 chains in set 1 are shown in Figures 2B and 2A, respectively. Scores for Cα−Cα distances estimated by DSA are defined as the inverse of the coefficient of variation11, and should be higher when the variation among chains is smaller. The plot that includes all 14,365 points demonstrates the distribution of scores against the average distances. The overall pattern depicted in these plots is in contrast to a previous report for GPCRs11 and the updated analysis (Figure S3). In the case of GPCRs of various sequences, populations with high scores are dominated by the contribution from intrahelical pairs, whereas interhelical pairs exhibit high scores in the bR sets. This result for bR shows that interhelical residue pairs exhibit high scores in a set containing very similar chains, and also suggests that external factors such as crystal lattice packing and solvent conditions that possibly affect the structures tend to highlight single helix geometry changes rather than changes in interhelical arrangements. A comparison between the results for set 1 and 2 indicates that high scores are biased toward longer distances for the interhelical pairs in set 2. This may result from the inclusion of highly similar structures (Table S4) in set 2.\n\nA. set 1, B. set 2, and C. set 3. Intrahelical and interhelical Cα−Cα pairs are colored in red and blue, respectively.\n\nWhen the intrahelical components were examined in detail, some pairs with high scores were found to originate from helices B and D in both sets 1 (Figure 3) and 2 (Figure S4). This finding is more clearly demonstrated by the cumulative numbers (expressed as ratios relative to the total number) of the Cα pairs ranked in the top 1,000 (Figure 3, lower panels). This feature of helices B and D is in contrast to the nearby helices A and C, for which few pairs appear in the top 1,000 ranks. Pairs with the highest scores for helix B were between the residues of inward-facing intracellular region and the residues of lipid-facing extracellular region, and for helix D involved the cytoplasmic (amino) terminal residues. The implications of these findings will be discussed later.\n\nA. Correlation between score and average distance. B. Cumulative ratio of the number of Cα−Cα pairs in the top-ranked 1,000. The pairs are colored as follows; purple, helix A; blue, helix B; cyan, helix C; green, helix D; yellow, helix E; orange, helix F; red, helix G.\n\nTo examine whether useful information can be obtained by analyzing interhelical components, we first checked the distance dependence of scores. In principle, this is easily done when a comparison is made among the helix pairs such as A-B, A-C, and A-D, the latter of which contains longer-distance pairs. As shown in Figure S5A, it is apparent that A-D pairs tended to exhibit higher scores than A-B, and A-C in the case of set 2. Therefore, a baseline correction or comparison of scores within a limited range of distances should be made when evaluating the pairs with high scores in such cases. When we compare helix pairs of similar distances, like A-B, B-C, and C-D, however, such distance dependence was not obvious (Figure S5B) and some remarkably high scores are found for B-C pairs. Importantly, more conserved B-C pairs were discernible even when the number of chains considered was limited to 9 as in set 1 (Figure S5C), which contains chains of either different space groups or research groups who solved the structure (Table S2). The high score B-C pairs were between the residues of lipid-facing extracellular region in helix B and the residues of intracellular region in helix C. The former is consistent with the above-mentioned results for intrahelical pairs and the latter contains a cluster of leucines and Asp96 (3.64) which is implicated to be important for proton pumping function. From these results, we suggest that just under 10 chains of very similar structures can provide statistically significant information regarding the relatively insensitive intramolecular spacing of a protein against external forces.\n\nThe results for wild-type bR ground-state chains demonstrate how DSA scores represent intramolecular distance changes against environmental factors even in the absence of sequence variation. On the other hand, analysis of set 3, which contains 13 chains of unique MR sequences, is expected to clarify the part of 7TM that is the most structurally conserved among the evolutionally related proteins. Although the number of available chains is fewer than the previously examined sets of GPCRs, we found that the overall pattern observed for all 14,365 pairs (Figure 2C) was more similar to that of 18,915 pairs of GPCRs (Figure S3A) than that of 14,365 pairs of dark-state wild-type bR (Figure 2A, 2B). This observation confirms that the contribution of interhelical pairs to the high-score population becomes insignificant when sequence variation is involved.\n\nThe most prominent intrahelical pairs with high scores were from helix G (Figure 4), to which retinal chromophore is attached. This finding is reasonable if we consider that all 13 proteins require retinal binding to a specific site, Lys(7.50), for their function as photoreceptors. Interestingly, the middle of this helix contains a π bulge within which Lys(7.50) resides (Table S5). Thus, it appears that intrahelical distance conservation is not dependent on whether a helix assumes a regular geometry or not. This finding adds an important revision to the previous view that the remarkably high score observed for helix III in the 7TM bundle of GPCRs might be partly explained by its regular helical structure11.\n\nA. Correlation between score and average distance. B. Cumulative ratio of the number of Cα−Cα pairs in the top-ranked 1,000. Coloring of the plots is the same as that in Figure 3.\n\nIt should also be noted that helix C appeared to be the most variable among the seven helices of MRs (Figure 4B). This was rather unexpected taking into account the fact that this helix contains highly conserved residues in addition to Arg(3.50), including Tyr(3.51), Trp(3.54), and Pro(3.59) (Table S1), and these residue types are completely conserved in 13 chains examined here by DSA (Figure S2). These observations suggest that intramolecular distance conservation among a set of evolutionally related proteins cannot always be inferred from the degree of sequence conservation. The structurally variable nature of helix C among 13 MRs may be in line with the finding that it does not contain many high score pairs in top 1000 ranks of dark-state wild-type bR sets (Figure 3). Another possible explanation for low scores of the pairs in helix C appears to be a substantial displacement in the backbone position in 2 halorhodopsin chains around the 3.53 position (Asp in most MRs, and Thr in 2 hRs), whereas an Asp to Asn mutation at this position in the structure of blue-absorbing proteorhodopsin (D97N) does not affect the structure of this region significantly.\n\nAs Figure 2C demonstrates, there was little distance dependency among the interhelical pairs in set 3; therefore, we examined the pairs in detail and noticed that a remarkable contribution to the high scores was attributed to the pairs between helices C and G (Figure 5, cyan). Since other interhelical pairs did not exhibit significant features, only E-G pairs are colored in yellow as a reference. The pairs with the highest scores involved the residues on the intracellular side of helix C and extracellular side of helix G, as shown in Figure 6. Relatively conserved spacing between these two regions is likely to ensure the binding and Schiff base protonation of all-trans-retinal chromophores to the cavity within a 7TM bundle of all MRs of known structure.\n\nA. Correlation between score and the average distance. B. Cumulative ratio of the number of Cα−Cα pairs in the top-ranked 1,000. The pairs are colored as follows; cyan, C-G; yellow, E-G; gray, others.\n\n\nDiscussion\n\nIn the present study, we first examined how different crystallization conditions affect the structure of ground-state wild-type bR. We used 22 chains for this purpose, the resolutions of which ranged from 1.8 to 3.5, including 2 chains obtained by cryo-electron microscopy. These structures were solved in different solvent environments and lattice packing. Obvious differences among 22 chains were discernible mainly at the cytoplasmic terminal region of helix E by visual inspection after superimposition (Figure 1A). This observation appears to explain why pairs with very low scores come mostly from this particular helix (Figure 3A, yellow). On the other hand, other regions in the 7TM bundle exhibit only moderate deviation, so our quantitative study by DSA is expected to work well for extracting information regarding structural conservation rather than variation.\n\nOur finding that helix B is the most insensitive to external factors may reflect its inherent properties. A previous simulation study on the individual helices of bR suggested that the structures of helices A, B, and E are stable in sodium dodecyl sulfate micelles13. Another possibility is that helix B does not suffer from crystal packing effect. To address this, we examined the molecular arrangement in all 6 space groups. In 5 of the 6 space groups, including native P3 observed by electron microscopy on purple membranes, lateral interactions between helices B and D were found. Therefore, pairs with high scores found in these two helices (Figure 3) may reflect a stabilization effect owing to crystal lattice contact. Alternatively, inherently stable parts of helices B and D might contribute to the preference of trimeric arrangement for bR by providing suitable intermolecular interactions.\n\nConsidering that helix C contains a few residues that are important for the proton-pumping function of bR14,15, such as Asp85 (3.53) and Asp96 (3.64), it may sound curious that this helix does not contribute to pairs with high scores in sets 1 and 2. In fact, removal of a chain that exhibits distinct features can substantially affect the results and result in higher scores for some pairs in helix C (Figure S6) in set 1 (9 chains) but not in set 2 (22 chains). Therefore, careful examination of each data set is required especially when the number of chains is limited.\n\nWe further performed DSA on the crystallographic models of 13 MRs, the sequences of which vary. The pairwise sequence identity (Table S3) ranges from 18.2% (between anabaena sensory rhodopsin and blue-absorbing proteorhodopsin) to 88.8% (between archaerhodopsin-1 and 2). This variation was less than that observed among previously analyzed and updated GPCRs (Table S3). Accordingly, the overall pairwise root-mean-squared deviation was smaller among the 13 MRs (~2.3 Å at most between xanthorhodopsin and blue-absorbing proteorhodopsin) than among GPCRs (~6 Å at most between PAR1 thrombin receptor and CRF1 receptor) (Table S4) and this is reflected in the relatively higher scores in MRs than GPCRs (Figure 2C, Figure S3). However, both sets exhibited higher scores for intrahelical residue pairs than interhelical pairs, the latter of which might be more affected by sequence variation.\n\nThe high distance conservation between pairs in helices C and G found in the present study suggests that the DSA procedure is useful for detecting structural conditions necessary for common functionality of evolutionally related proteins. Whereas it appears that a slight distance dependency of scores may exist (Figure 5A), the largest contribution to populations exhibiting high scores for the pairs between helices C and G is not likely explained by such an effect.\n\nIn the case of MRs, all members are required to ensure binding of all-trans-retinal molecules in a cavity surrounded by 7 TM helices. Whereas helices C and G are in contrast to each other with regard to the degree of intrahelical structural conservation (Figure 4), our results suggest that a strict condition of spacing between the cytoplasmic terminal region of helix C and the extracellular side of helix G must be fulfilled in all MRs (Figure 5, Figure 6). Interestingly, retinal Schiff base bound to the side chain of Lys(7.50) resides just in the middle of this conserved spacing (Figure 6). We suspect that definite structural requirement for MRs, whatever the functions are (pumps, channels, or sensors), would be proper relative positioning of Lys(7.50) and a set of residues from helix C which contribute significantly to holding of the retinal polyene chain and protonation of the Schiff base.\n\nA. Top view from the cytoplasmic side. B. Side view from helices F and G. The pairs between helices C and G with high scores are connected by green lines drawn on chain A of 1PY6 (bR). A retinal chromophore attached to Lys(7.50) is also shown in the center.\n\nIntramolecular distance information from existing crystal structures has long been utilized in the field of structural biology for such purposes as domain recognition16, construction of new models17, and detection of conformational changes18. Although the DSA method might require further improvements, it can be applied in the current form, to the detailed mining of information from larger sets of data than previously examined, and specifically to a number of protein families given that reliable alignments can be obtained. Among the membrane proteins in PDB, the largest category with more than 180 entries is ion channels that transport potassium, sodium, and protons. These proteins function as multi-subunit complexes and exhibit no similarity with any of the 7TM proteins. The second and third-most represented membrane protein families in PDB, MRs and GPCRs studied by DSA, had an advantage in that their alignments were rather straightforward. The present study suggests that around a dozen experimental structures with related and aligned sequences or obtained under distinct conditions can be used to infer statistically significant features of a protein or protein family. From this perspective, a structural archive would be a far more valuable source of information to improve our understanding of biological macromolecules.\n\n\nMethods\n\nMicrobial rhodopsin sequences were obtained from InterPro (www.ebi.ac.uk/interpro/) v.48 under the classes archaeal/bacterial/fungal rhodopsin (IPR001425) and archaeal/bacterial/fungal rhodopsin-like (IPR029730). Archaeal proteins did not differ significantly between the two classes, while bacterial and eukaryotic proteins were highly enriched in the IPR029730 class. As the excess bacterial proteins in the IPR029730 class were mostly proteorhodopsins, the sequence set was constructed from the IPR001425 archaeal and bacterial proteins (518 and 298 sequences, respectively) and IPR029730 eukaryotic proteins (651 sequences). A multiple sequence alignment was performed with ClustalW19 implemented in BioEdit 7.2.520 for each of the three domains. Based on manual inspection of the results, misaligned or extremely short or long sequences were removed from each domain set. The results for each domain were then merged and an additional alignment was carried out. The distribution of amino acid types at each position was obtained using the Positional Amino Acid Numerical Summary function implemented in BioEdit.\n\nCrystallographic models of MRs were obtained from PDB (www.rcsb.org/pdb/) and classified manually as listed in our web site (www.gses.jp/7tmsp/) into several groups such as wild-type and mutant bRs, halorhodopsins, and sensory rhodopsins. These PDB entries (accession numbers are as noted in Table S2~Table S4) were processed to make single polypeptide chains and further truncated to 7TM bundles of 170 residues manually by Discovery Studio Visualizer 3.1 (Accelrys Inc.), ensuring that the alignments for different receptors were correct. The overall pairwise root-mean-squared deviation and correlation coefficient were obtained by Discovery Studio Visualizer 3.1 (Accelrys Inc.) and pca-excel 1.0 (ss-nakano Inc.), respectively. DSA was performed on the Cαs of the MR bundles as well as 23 GPCRs with unique sequences (19 rhodopsin-like and 4 non rhodopsin-like receptors), following a recently described procedure11. Briefly, the average, standard deviation, and the inverse of coefficient of variation (score) of each Cα pair distance were calculated in each of the sets (Dataset 1). The 7TM bundle of the P2Y12 receptor (PDB ID: 4NTJ) aligned to rhodopsin-like receptors was assumed to lack a residue at the amino terminus of helix VI (6.29). Similarly, the 7TM bundles of the class C mGluR1 (PDB ID: 4OR2) and mGluR5 (PDB ID: 4OO9) receptors were assumed to lack two residues at the carboxyl termini of helix II (2.66 and 2.67) and VI (6.59 and 6.60). The resulting number of Cα pairs was 18,915.\n\nScore vs distance plots were prepared with matplotlib (matplotlib.org/) by implementing in an original python script for DSA (Dataset 2), and other graphs were drawn using Igor Pro 6.37 (WaveMetrix Inc.). Protein graphics were prepared with either CCP4MG 2.8.121 or Discovery Studio Visualizer 3.1 (Accelrys Inc.).\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for DSA (Figure 2–Figure 6, Figure S3–FigureS6), 10.5256/f1000research.7920.d11328522\n\nF1000Research: Dataset 2. Python script for making a score vs distance plot, 10.5256/f1000research.7920.d11388923",
"appendix": "Author contributions\n\n\n\nM.A., S.I., A.K., and T.O. performed analysis, K.T., and T.O. validated data, T.O. designed research, and wrote the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nSupported by the Ministry of Education, Culture, Sports, Science and Technology of Japan (S1312002 to Department of Life Science, Gakushuin University).\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nSupplementary material\n\nThe numbers attached to the helices are the selected ranges in the bR sequence.\n\nThe conserved positions are colored as follows: dark blue, identical; blue, strong similarity; light blue, weak similarity, according to PAM250 matrix definition. The small squares on the ruler indicate the *.50 positions of the numbering proposed for MRs.\n\n(A) Correlation between score and average distance. Intrahelical and interhelical Cα−Cα pairs are colored in red and blue, respectively. (B) Cumulative ratio of the number of 2,661 intrahelical Cα−Cα pairs in the top-ranked 1,000. Coloring of the plots is the same as that used in Figure 3. (C) Cumulative ratio of the number of 16,254 interhelical Cα−Cα pairs in the top-ranked 1,000. Purple, I-VI; cyan, I-III, blue, I-II; gray, others.\n\n(A) Correlation between score and average distance. (B) Cumulative ratio of the number of Cα−Cα pairs in the top-ranked 1,000. The pairs are colored as follows; purple, helix A; blue, helix B; cyan, helix C; green, helix D; yellow, helix E; orange, helix F; red, helix G.\n\n(A) set 2, blue, A-B; cyan, A-C; green, A-D. (B) set 2, blue, A-B; cyan, B-C; green, C-D. (C) set 1, blue, A-B; cyan, B-C; green, C-D.\n\nCorrelation between score and the average distance for 1,992 intrahelical pairs without a chain obtained from cryo-electron microscopy entry 2AT9 in (A) set 1 and (B) set 2, The pairs are colored as follows; purple, helix A; blue, helix B; cyan, helix C; green, helix D; yellow, helix E; orange, helix F; red, helix G.\n\nTable S1. Distribution of amino acid types obtained from 603 sequences of MRs.\n\nTable S2. Details of structures used as set 1 and 2 (wild-type, dark-state bR).\n\nTable S3. Sequence identity among 13 MRs and 23 GPCRs.\n\nTable S4. Pair wise RMSDs in set 1, set 2, set 3, and GPCRs.\n\nTable S5. Secondary structure types (by DSSP) of 13 MRs.\n\n\nReferences\n\nZhang F, Vierock J, Yizhar O, et al.: The microbial opsin family of optogenetic tools. Cell. 2011; 147(7): 1446–1457. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiu X, Ramirez S, Pang PT, et al.: Optogenetic stimulation of a hippocampal engram activates fear memory recall. Nature. 2012; 484(7394): 381–385. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOesterhelt D, Stoeckenius W: Rhodopsin-like protein from the purple membrane of Halobacterium halobium. Nat New Biol. 1971; 233(39): 149–152. PubMed Abstract | Publisher Full Text\n\nLanyi JK, Luecke H: Bacteriorhodopsin. Curr Opin Struct Biol. 2001; 11(4): 415–419. PubMed Abstract | Publisher Full Text\n\nSabehi G, Loy A, Jung KH, et al.: New insights into metabolic properties of marine bacteria encoding proteorhodopsins. PLoS Biol. 2005; 3(8): e273. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBéjà O, Lanyi JK: Nature's toolkit for microbial rhodopsin ion pumps. Proc Natl Acad Sci U S A. 2014; 111(18): 6538–6539. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRan T, Ozorowski G, Gao Y, et al.: Cross-protomer interaction with the photoactive site in oligomeric proteorhodopsin complexes. Acta Crystallogr D Biol Crystallogr. 2013; 69(Pt 10): 1965–1980. PubMed Abstract | Publisher Full Text\n\nGushchin I, Chervakov P, Kuzmichev P, et al.: Structural insights into the proton pumping by unusual proteorhodopsin from nonmarine bacteria. Proc Natl Acad Sci U S A. 2013; 110(31): 12631–12636. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRosenbaum DM, Rasmussen SG, Kobilka BK: The structure and function of G-protein-coupled receptors. Nature. 2009; 459(7245): 356–363. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhang X, Stevens RC, Xu F: The importance of ligands for G protein-coupled receptor stability. Trends Biochem Sci. 2015; 40(2): 79–87. PubMed Abstract | Publisher Full Text\n\nKinoshita M, Okada T: Structural conservation among the rhodopsin-like and other G protein-coupled receptors. Sci Rep. 2015; 5: 9176. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBallesteros JA, Weinstein H: Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors. Methods Neurosci. 1995; 25: 366–428. Publisher Full Text\n\nKrishnamani V, Lanyi JK: Molecular dynamics simulation of the unfolding of individual bacteriorhodopsin helices in sodium dodecyl sulfate micelles. Biochemistry. 2012; 51(6): 1061–1069. PubMed Abstract | Publisher Full Text\n\nButt HJ, Fendler K, Bamberg E, et al.: Aspartic acids 96 and 85 play a central role in the function of bacteriorhodopsin as a proton pump. EMBO J. 1989; 8(6): 1657–1663. PubMed Abstract | Free Full Text\n\nKataoka M, Kamikubo H, Tokunaga F, et al.: Energy coupling in an ion pump. The reprotonation switch of bacteriorhodopsin. J Mol Biol. 1994; 243(4): 621–638. PubMed Abstract | Publisher Full Text\n\nRossman MG, Liljas A: Letter: Recognition of structural domains in globular proteins. J Mol Biol. 1974; 85(1): 177–181. PubMed Abstract | Publisher Full Text\n\nJones TA, Thirup S: Using known substructures in protein model building and crystallography. EMBO J. 1986; 5(4): 819–822. PubMed Abstract | Free Full Text\n\nSchneider TR: Objective comparison of protein structures: error-scaled difference distance matrices. Acta Crystallogr D Biol Crystallogr. 2000; 56(Pt 6): 714–721. PubMed Abstract | Publisher Full Text\n\nThompson JD, Higgins DG, Gibson TJ: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994; 22(22): 4673–4680. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHall TA: BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser. 1999; 41: 95–98. Reference Source\n\nMcNicholas S, Potterton E, Wilson KS, et al.: Presenting your structures: the CCP4mg molecular-graphics software. Acta Crystallogr D Biol Crystallogr. 2011; 67(Pt 4): 386–394. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAsano M, Ide S, Kamata A, et al.: Dataset 1 in: Sequence and intramolecular distance scoring analyses of microbial rhodopsins. F1000Research. 2016a. Data Source\n\nAsano M, Ide S, Kamata A, et al.: Dataset 2 in: Sequence and intramolecular distance scoring analyses of microbial rhodopsins. F1000Research. 2016b. Data Source"
}
|
[
{
"id": "12678",
"date": "01 Mar 2016",
"name": "Javier V. Navarro",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article describes a novel structural analysis of microbial photoreceptors by scoring intramolecular distances derived from their high resolution crystal structures. This work could potentially provide the structural foundation to explain the diverse photoreceptor phenotypes, including identifying the structural factors governing their colour tuning, which is still an unresolved problem.",
"responses": [
{
"c_id": "1843",
"date": "02 Mar 2016",
"name": "Tetsuji Okada",
"role": "Author Response F1000Research Advisory Board Member",
"response": "We appreciate the positive referee comment. Further results on the MR subfamilies will be discussed in terms of the color tuning mechanism."
}
]
},
{
"id": "12405",
"date": "14 Mar 2016",
"name": "Minoru Sugihara",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this manuscript, Asano et al. have applied the own developed method, SDS, to microbial rhodopsins. The basic idea of this scoring is to calculate all Carbon-alpha pairwise distances in each crystal structure and to avoid the ambiguity from the structure-matching.The manuscript is well presented and the method/results will be of interest to broad readers. I would recommend it for acceptance.Some minor comments:Authors propose a new numbering scheme (*.50) from the conservation rate of residues. Adding conservation rates of key residues to the legend of Fig.S1 or Table 1 is useful (one need not to check Table S1). Also in Figure S1 only the residue number “216” of Helix 7 (7.50) is shown and other numbers are missing.The different numbering in Figure S1 and Figure S2 is a bit confusing. Adding the numbers of the *.50 residue in the bR sequence (27, 57, 82, 122, 152, 182, and 216) at the bottom of the sequencing alignment (Figure S2) might be helpful.",
"responses": [
{
"c_id": "1883",
"date": "06 Apr 2016",
"name": "Tetsuji Okada",
"role": "Author Response F1000Research Advisory Board Member",
"response": "Thank you for the critical reading and valuable comments on our DSA (not SDS) method. According to your suggestions, we have revised Table 1, Figures S1 and S2. An accidental error found in the previous Table S1 is also resolved."
}
]
}
] | 1
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https://f1000research.com/articles/5-165
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https://f1000research.com/articles/5-568/v1
|
05 Apr 16
|
{
"type": "Research Note",
"title": "Mapping Zika virus infection using geographical information systems in Tolima, Colombia, 2015-2016",
"authors": [
"Alfonso J. Rodriguez-Morales",
"Maria Leonor Galindo-Marquez",
"Carlos Julian García-Loaiza",
"Juan Alejandro Sabogal-Roman",
"Santiago Marin-Loaiza",
"Andrés Felipe Ayala",
"Carlos O. Lozada-Riascos",
"Andrea Sarmiento-Ospina",
"Heriberto Vásquez-Serna",
"Carlos E. Jimenez-Canizales",
"Juan Pablo Escalera-Antezana",
"Maria Leonor Galindo-Marquez",
"Carlos Julian García-Loaiza",
"Juan Alejandro Sabogal-Roman",
"Santiago Marin-Loaiza",
"Andrés Felipe Ayala",
"Carlos O. Lozada-Riascos",
"Andrea Sarmiento-Ospina",
"Heriberto Vásquez-Serna",
"Carlos E. Jimenez-Canizales",
"Juan Pablo Escalera-Antezana"
],
"abstract": "Objective: Geographical information systems (GIS) have been extensively used for the development of epidemiological maps of tropical diseases, however not yet specifically for Zika virus (ZIKV) infection.Methods: Surveillance case data of the ongoing epidemics of ZIKV in the Tolima department, Colombia (2015-2016) were used to estimate cumulative incidence rates (cases/100,000 pop.) to develop the first maps in the department and its municipalities, including detail for the capital, Ibagué. The GIS software used was Kosmo Desktop 3.0RC1®. Two thematic maps were developed according to municipality and communes incidence rates.Results: Up to March 5, 2016, 4,094 cases of ZIKV were reported in Tolima, for cumulated rates of 289.9 cases/100,000 pop. (7.95% of the country). Burden of ZIKV infection has been concentrated in its east area, where municipalities have reported >500 cases/100,000 pop. These municipalities are bordered by two other departments, Cundinamarca (3,778 cases) and Huila (5,338 cases), which also have high incidences of ZIKV infection. Seven municipalities of Tolima ranged from 250-499.99 cases/100,000 pop., of this group five border with high incidence municipalities (>250), including the capital, where almost half of the reported cases of ZIKV in Tolima are concentrated.Conclusions: Use of GIS-based epidemiological maps helps to guide decisions for the prevention and control of diseases that represent significant issues in the region and the country, but also in emerging conditions such as ZIKV.",
"keywords": [
"Zika",
"epidemiology",
"public health",
"travelers",
"Colombia",
"Latin America."
],
"content": "Introduction\n\nZika virus (ZIKV) epidemics are progressing across most of the territories of Latin America without effective control1. In particular, some areas of Colombia are being impacted with a high incidence of cases, nevertheless without show their incidence rates and detailed geographical distribution in most reports. Areas where cocirculation of dengue and chikungunya have occurred2,3, are particularly at risk. In this setting updated epidemiological information is of utmost importance, which should include the availability of risk maps in order to address recommendations to prioritize interventions as well for the identification of areas of risk by visitors or people returning from visiting specific places4,5. Accordingly, we have developed epidemiological maps for ZIKV in Colombia using geographical information systems (GIS) at one of the high incidence departments (Tolima) located in the central area of the country. We have previously provided GIS-based epidemiological maps for CHIKV in other areas of the country5.\n\n\nMethods\n\nScientific publications using GIS for development of epidemiological maps in ZIKV lack in Latin America and Colombia. Tolima, a department surrounded by seven departments (five at the west and two at the east) with 47 municipalities (for a total population of 1,412,230 habitants) is one of the territories significantly affected by the 2015–2016 outbreak. Its capital, the Ibagué municipality, constitutes 13 urban communes and a rural area, comprising 39.6% of the total population of the department.\n\nSurveillance case data (2015–2016; officially reported by the National Institute of Health, Colombia)6 were used to estimate the cumulative incidence rates using reference population data (2016), on ZIKV infections (cases/100,000 pop.) and to develop the first maps in the municipalities of Tolima and in the communes of the Ibagué municipality. Data for this study were gathered from 47 primary notification units, one per municipality, and later consolidated at the department level. In the case of the Ibagué municipality, data were collected from healthcare institutions of the 13 communes, and later consolidated at the municipality level. Diagnosis of ZIKV infection included either laboratory and/or syndromic surveillance (clinical definition of fever, rash, conjunctivitis and arthralgias in a municipality with previously ZIKV circulation, at least one case confirmed by RT-PCR). The software Microsoft Access (version 365)® was used to design the spatial database, and to import incidence rates for municipalities in Tolima and communes in Ibagué to the GIS software. The open source GIS software used was Kosmo Desktop 3.0 RC1®. Geographic data (municipalities and department polygons) required for the department and the Ibagué municipality were provided by the Regional Information System of the Coffee-Triangle region. The shapefiles (based on official cartography) of municipalities and communes (.shp) were linked to the data table database through a spatial join operation, in order to produce digital maps of the incidence rates.\n\n\nResults\n\nUp to March 5, 2016, 4,094 cases of ZIKV were reported in Tolima (5.93% diagnosed by RT-PCR for ZIKV), for cumulative rates of 289.9 cases/100,000 pop. (7.95% of the country). Rates ranged from 0 to 1,120.5 cases/100,000 pop. (Carmen de Apicalá, 2.4% of the department cases), followed by Dolores (786.0 cases/100,000 pop.; 1.5%), Piedras (780.1 cases/100,000 pop.; 1.1%), Flandes (760.3 cases/100,000 pop.; 5.4%), Melgar (693.5 cases/100,000 pop.; 6.2%) (Figure 1). These five municipalities (out of 47), reported 16.61% of cases of the department (Table 1). The capital municipality, Ibagué have reported 2,004 cases (358.6 cases/100,000 pop.; 48.9%) (Figure 1). The other five municipalities reported incidence rates between 387.3 and 469.2 cases/100,000 pop. These ten territories together with the capital reported more than 83% of the ZIKV cases in the department of Tolima (Table 1).\n\n*Up to epidemiological week 9th, March 5, 2016\n\n(*Up to the 9th epidemiological week, March 5, 2016).\n\nFor the Ibagué communes, rates ranged from 43.64 (rural area) to 514.52 cases/100,000 pop. (commune 7, 10.88% of the municipality’s cases, located at the east of the municipality) (Figure 2), followed by commune 9 (375.19 cases/100,000 pop.; 11.73%) and commune 12 (358.79 cases/100,000 pop.; 7.53%). These three communes do not share a common border. The other eight communes had incidence rates ranging between 250–499.99 cases/100,000 pop. (Table 1, Figure 2). Only three communes had rates higher than the whole Ibagué municipality and of them, only one with a rate >500 cases/100,000 pop. (commune 7) (Table 1, Figure 2). Five communes (7, 9, 12, 8 and 4) concentrated more than 50% of the cases of the Ibagué municipality and more than 25% of the whole department (Table 1).\n\n(*Up to the 9th epidemiological week, March 5, 2016). Aerial photography obtained from the Geographical Institute Agustin Codazzi, Colombia, at: http://ssiglwps.igac.gov.co/ssigl2.0/visor/galeria.req?mapaId=44\n\nColombia have officially reported a total of 51,473 cases (up to the 9th epidemiological week of 2016); almost 8% from Tolima (4,094). There, burden of ZIKV infection has been concentrated in its east area, were those municipalities with >500 cases/100,000 pop. border two other departments, Cundinamarca (3,778 cases) and Huila (5,338 cases), also with high incidences of ZIKV infection (Figure 1). Seven municipalities ranged from 250–499.99 cases/100,000 pop., of them five border with high incidence municipalities, including the capital where almost half of the reported cases of ZIKV in Tolima are concentrated (Figure 1).\n\n\nDiscussion\n\nGiven the ecoepidemiological conditions, particularly of these municipalities, they are now becoming endemic for ZIKV. They have been also endemic of dengue and CHIKV7. Among ZIKV cases in Tolima, 427 (10.43%) were in pregnant women (28 confirmed by RT-PCR for ZIKV)6. Particularly, detailed evaluation of pregnant women morbidity and its mapping due to this arbovirus should be performed8,9. Even more, the enhanced surveillance of ZIKV-associated neurological syndromes reported eight cases in Tolima as well as three cases of acute flaccid paralysis with history of ZIKV infection6. Public health policies and strategies for integral control of ZIKV in people living, but also in visitors10, in these areas, should be considered and urgently implemented, particularly in the capital, Ibagué. At Ibagué, as well as Tolima, other arboviruses, such as dengue and chikungunya are also cocirculating.\n\nAlthough ZIKV was isolated in 19471, only significant research has been done during the past months (ending 2015-beginning 2016)11, in countries such as Brazil and Colombia in particular, due to multiple negative potentially linked outcomes.\n\nUse of GIS-based epidemiological maps allows for the integration of preventive and control strategies, as well as public health policies, for joint control of this vector-borne disease in this and other areas of the country4,5. As other arboviruses are cocirculating (dengue, CHIKV and ZIKV), maps for each as well as for coinfections are needed12,13. Simultaneous or subsequent arboviral infections occur and should be also assessed. Preparedness in this setting should also consider the potential arrival of Mayaro and yellow fever in Aedes infested areas. Finally, maps provide relevant information in order to assess the risk of travelers to specific destinations in high transmission areas allowing detailed prevention advice. Migrant and traveler populations also play an important role in the virus spread as they would arrive viremic from endemic areas to non-endemic areas, with vectors that may allow transmission to susceptible individuals4,5,10, as occurred in Colombia (including the Tolima department) in 2015–2016.\n\n\nEthics\n\nThis study was approved by the Secretary of Health of Tolima IRB as not requiring ethics approval given the study is about secondary grouped data.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for 'Mapping Zika virus infection using geographical information systems in Tolima, Colombia, 2015–2016', 10.5256/f1000research.8436.d11825614",
"appendix": "Author contributions\n\n\n\nStudy design: AJRM, Data collection: MLGM, CJGL, JASR, SML, AFA, COLR, ASO, Data analysis: AJRM, COLR, Writing: All authors. All authors read the final version submitted.\n\n\nCompeting interests\n\n\n\nThere is no conflict of interest.\n\n\nGrant information\n\nThis study was funded by the Universidad Tecnologica de Pereira, Pereira, Risaralda, Colombia.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nRodriguez-Morales AJ: Zika: the new arbovirus threat for Latin America. J Infect Dev Ctries. 2015; 9(6): 684–5. PubMed Abstract | Publisher Full Text\n\nAlfaro-Toloza P, Clouet-Huerta DE, Rodríguez-Morales AJ: Chikungunya, the emerging migratory rheumatism. Lancet Infect Dis. 2015; 15(5): 510–2. PubMed Abstract | Publisher Full Text\n\nRodríguez-Morales AJ, Paniz-Mondolfi AE: Venezuela: far from the path to dengue and chikungunya control. J Clin Virol. 2015; 66: 60–1. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales AJ, Bedoya-Arias JE, Ramírez-Jaramillo V, et al.: Using geographic information system (GIS) to mapping and assess changes in transmission patterns of chikungunya fever in municipalities of the Coffee-Triangle region of Colombia during 2014–2015 outbreak: Implications for travel advice. Travel Med Infect Dis. 2016; 14(1): 62–5. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales AJ, Cárdenas-Giraldo EV, Montoya-Arias CP, et al.: Mapping chikungunya fever in municipalities of one coastal department of Colombia (Sucre) using Geographic information system (GIS) during 2014 outbreak: Implications for travel advice. Travel Med Infect Dis. 2015; 13(3): 256–8. PubMed Abstract | Publisher Full Text\n\nInstituto Nacional de Salud de Bogotá: Zika a semana epidemiológica 09 de 2016. Instituto Nacional de Salud de Bogotá, 2016. Reference Source\n\nRodríguez-Morales AJ, Calvache-Benavides CE, Giraldo-Gómez J, et al.: Post-chikungunya chronic arthralgia: Results from a retrospective follow-up study of 131 cases in Tolima, Colombia. Travel Med Infect Dis. 2016; 14(1): 58–9. PubMed Abstract | Publisher Full Text\n\nRodríguez-Morales AJ: Zika and microcephaly in Latin America: An emerging threat for pregnant travelers? Travel Med Infect Dis. 2016; 14(1): 5–6. PubMed Abstract | Publisher Full Text\n\nVillamil-Gómez WE, Mendoza-Guete A, Villalobos E, et al.: Diagnosis, Management and Follow-up of Pregnant Women with Zika virus infection: A preliminary report of the ZIKERNCOL cohort study on Sincelejo, Colombia. Travel Med Infect Dis. 2016; pii: S1477-8939(16)00030-2. PubMed Abstract | Publisher Full Text\n\nMaria AT, Maquart M, Makinson A, et al.: Zika virus infections in three travellers returning from South America and the Caribbean respectively, to Montpellier, France, December 2015 to January 2016. Euro Surveill. 2016; 21(6). PubMed Abstract | Publisher Full Text\n\nMartinez-Pulgarin DF, Acevedo-Mendoza WF, Cardona-Ospina JA, et al.: A bibliometric analysis of global Zika research. Travel Med Infect Dis. 2016; 14(1): 55–57. PubMed Abstract | Publisher Full Text\n\nVillamil-Gómez WE, González-Camargo O, Rodriguez-Ayubi J, et al.: Dengue, Chikungunya and Zika co-infection in a patient from Colombia. J Infect Public Health. 2016; pii: S1876-0341(15)00221-X. PubMed Abstract | Publisher Full Text\n\nVillamil-Gómez WE, Rodríguez-Morales AJ: Reply: Dengue RT-PCR-Positive, Chikungunya IgM-Positive and Zika RT-PCR-Positive co-infection in a patient from Colombia. J Infect Public Health. 2016; pii: S1876-0341(16)00039-3. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales A, Galindo-Marquez ML, García-Loaiza CJ, et al.: Dataset 1 in: Mapping Zika virus infection using geographical information systems in Tolima, Colombia, 2015–2016. F1000Research. 2016. Data Source"
}
|
[
{
"id": "13208",
"date": "06 Apr 2016",
"name": "Kateryna Kon",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article provides very interesting information on geographical mapping of Zika virus in Tolima (Colombia). The title and abstract are totally appropriate and represent an adequate summary of the article. There is a comprehensive explanation of the study design with detail description of all methods used, and with appropriate citations. Results are well illustrated in table and figures, and the article is written in grammatically correct and well-understandable scientific language. The conclusions are balanced and totally justified on the basis of the results. All sufficient information has been provided for replication of calculations performed by authors. For the further researches, it would be interesting to compare provided by authors results with results obtained in other areas of Colombia and with results from other countries of Latin America.",
"responses": [
{
"c_id": "1906",
"date": "06 Apr 2016",
"name": "Alfonso Rodriguez-Morales",
"role": "Author Response",
"response": "Thanks for your comments. We fully agree with all your appreciations. In the near future, when other similar studies would be published we expect to make those comparisons."
}
]
},
{
"id": "13330",
"date": "13 Apr 2016",
"name": "Luis Cuauhtémoc Haro-García",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript illustrated–through geographic mapping–the epidemiological behavior of Zika virus infection in the municipality of Tolima, Colombia, which results in an easy and understandable way for the decision makers in order to face an emerging problem like the one analyzed.I think the title and the abstract are accurate; the methodology clearly stands that the study was conducted at one of the high incidence departments located in the central area of Colombia. In general, I think the results are arranged clearly enough; besides, the findings in the municipality of Ibagué, capital of the municipality, given that it comprising almost 40% of the total population of the department, the data are shown independently It would be desirable at a given moment to develop this same method of mapping conjointly with the municipalities of Cundinamarca and Huila, bordering areas with Tolima, Colombia, where there was also a high incidence of Zika virus infection, at least until March 5, 2016. The article highlights, in a balanced manner, the advantages of performing this type of mapping, considering that the authors also note the area on study as endemic for dengue and chikungunya.",
"responses": [
{
"c_id": "1923",
"date": "15 Apr 2016",
"name": "Alfonso Rodriguez-Morales",
"role": "Author Response",
"response": "Thanks for your valuable and positive comments regard this paper. We fully agree with about the assessment of Cundinamarca and Huila Zika incidence rates, given the fact these are bordering areas with Tolima, Colombia, where there was also a high incidence of Zika virus infection. In a future paper we will perform that for those other areas of the country."
}
]
}
] | 1
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https://f1000research.com/articles/5-568
|
https://f1000research.com/articles/5-121/v1
|
29 Jan 16
|
{
"type": "Research Article",
"title": "Profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis ",
"authors": [
"Metin Atila",
"Yu Luo",
"Metin Atila"
],
"abstract": "Cationic modulation of the dominantly negative electrostatic structure of phospholipids plays an important role in bacterial response to changes in the environment. In addition to zwitterionic phosphatidylethanolamine, Gram-positive bacteria are also abundant in positively charged lysyl-phosphatidylglycerol. Increased amounts of both types of lipids render Gram-positive bacterial cells more resistant to cationic antibiotic peptides such as defensins. Lysyl and alanyl-phosphatidylglycerol as well as alanyl-cardiolipin have also been studied by mass spectroscopy. Phospholipids modified by other amino acids have been discovered by chemical analysis of the lipid lysate but have yet to be studied by mass spectroscopy. We exploited the high sensitivity of modern mass spectroscopy in searching for substructures in complex mixtures to establish a sensitive and thorough screen for aminoacylated phospholipids. The search for deprotonated aminoacyl anions in lipid extracted from Bacillus subtilis strain 168 yielded strong evidence as well as relative abundance of aminoacyl-phosphatidylglycerols, which serves as a crude measure of the specificity of aminoacyl-phosphatidylglycerol synthase MprF. No aminoacyl-cardiolipin was found. More importantly, the second most abundant species in this category is D-alanyl-phosphatidylglycerol, suggesting a possible role in the D-alanylation pathway of wall- and lipo-teichoic acids.",
"keywords": [
"Gram-positive",
"Antibiotic resistance",
"Membrane",
"Charge",
"Phospholipid",
"Teichoic acid",
"alanyl-phosphatidylglycerol",
"lysyl-phosphatidylglycerol",
"aminoacylated phospholipids",
"D-alanylation"
],
"content": "Introduction\n\nIn most bacteria, phospholipids are the dominant cell membrane component1. The phosphate moieties in these lipid molecules dictate the overall negative nature of bacterial membranes. This electrostatic feature makes them susceptible to cationic antibiotic peptides such as defensins2–4. In response to environmental challenges, bacteria constantly change their membrane composition1,5. Incorporation of less saturated and shorter fatty acyl chains makes the membrane more fluidic1. Gram-negative bacteria generally have a high concentration of zwitterionic phosphatidylethanolamine (PE) which masks this anionic surface feature1,6. In comparison, Gram-positive bacteria in general have much less PE1. However, they are abundant in aminoacylated phosphatidylglycerol (aminoacyl-PG), especially L-lysyl-PG5,7. The pivotal protein for aminoacyl-PG biosynthesis from L-aminoacyl-tRNA and PG is the lysyl-PG synthase MprF (multiple peptide resistance factor)8 which appears to have a broad range of specificity for L-aminoacyl-tRNAs9,10. The crystal structures of the cytoplasmic catalytic domains of two MprFs, with one specific for lysyl- the other for alanyl-PG biosynthesis, have recently been elucidated11. The catalytic domains of the two MprF enzymes have a long tunnel for accommodating PG with the catalytic site located at the narrowest part of the tunnel11. The primary and tertiary structures of MprF resemble that of FemX which catalyzes L-alanyl transfer from tRNA to a peptidoglycan precursor12. Both proteins are potential targets for novel antibiotics. MprF of Bacillus subtilis over-expressed in Escherichia coli has been observed to synthesize both L-lysyl-PG and L-alanyl-PG in the presence of aminoacyl-t-RNA10. We expect to find both lysyl- and alanyl-PGs in B. subtilis lipids.\n\nIn comparison to Gram-negative bacteria, Gram-positive bacteria have profoundly different cell-envelope structures; they lack the outer membrane, and the cell wall is usually much thicker, with multiple peptidoglycan layers. In addition to PE and aminoacyl-PG biosynthesis, which modulate bacterial surface charge, one constant signature of Gram-positive cell envelopes, however, is the presence of additional glycopolymers including peptitoglycan-attached wall-teichoic acids and lipid-anchored lipoteichoic acids. This type of cell surface polymer was discovered in the late 1950s13. It carries multiple negative charges due to its phosphodiester bonds between repetitive glycerol or ribitol residues. Its association with the cell envelope is anchored by covalent attachment to either membrane glycolipids or peptidoglycan14–16. The most common modification of this biopolymer is D-alanine esterification13,15,17, which is carried out by four proteins (DltA, DltB, DltC and DltD) coded by the dlt operon18. This surface charge modulation by D-alanylation appears to have profound effects on the antigenicity of the bacteria and immune response of host cells2. The D-alanyl carrier protein ligase DltA (~500 amino acid residues)18 is an enzyme resembling the adenylation domains (also called AMP-forming domains) found in modular nonribosomal peptide synthetases19. Its remote homologues include the acyl-coenzyme A synthetases and firefly luciferases20. DltA catalyzes the ATP-driven adenylation of the carboxyl group of D-alanine and the transfer of the activated D-alanyl to the thiol group of 4’-phosphopantetheine which is covalently attached to a serine side chain of D-alanyl carrier protein DltC (~80 amino acid residues)18,21,22. The functional role has not been firmly established for DltB (~400 amino acid residues), an integral membrane protein. DltD (~400 amino acid residues), a membrane-bound protein via a putative N-terminal transmembrane helix, appears to bind DltC and possibly catalyzes the final D-alanyl transfer from DltC to teichoic acid23. We suspect that a D-alanylated lipid species may serve as the intermediate between cytosolic D-alanyl-DltC and lipo- and wall-teichoic acids on the outside of cell membrane.\n\nLipid profiling of aminoacyl-PG using mass spectroscopy has been reported recently for E. coli and B. subtilis24. L-alanyl-PG has been found to be abundant in Gram-negative Pseudonomas aeruginosa25, which has a MprF homolog specific for L-analyl-tRNA substrate10. D-alanyl- and L-lysyl-cardiolipin (CL) have also been separated from Vagococcus fluvialis26,27. However, only lysyl-PG has been identified in B. subtilis lipid by mass spectrometry24. Serine, glycine and ornithine-containing lipids are also known to exist in bacteria28. Here we report a more thorough profiling of aminoacyl-PGs. We also established sensitive scans for lysyl-PE as well as alanyl-PE. Importantly, the second most abundant aminoacyl-PG, alanyl-PG, appeared to be D-alanyl-PG, implying a role in the D-alanylation pathway of wall- and lipo-teichoic acids.\n\n\nMaterials and methods\n\nBacterial strain and cell culture. The BL21 (DE3) strain of E. coli was acquired from Novagen. Strain 168 of B. subtilis was acquired from Bacillus Genetic Stock Center (BGSC). Both types of cells were first plated on LB-agar media. A single colony was inoculated into 10 ml of LB media. After over-night incubation at 37°C and 220 rpm in an environmental shaker, it was transferred to 1 liter of LB media. When the cell culture just reached an optical density of ~2.0 at 600 nm, the cell pellet was collected by centrifugation at 5,500 rpm for 16 min in a Beckman JLA-8.1 rotor at 4°C.\n\nLipid extraction. HPLC-grade organic solvents (Fisher Scientific) are used throughout the experiment. The lipid extraction procedure was adapted to get maximal yield of aminoacylated lipids based on the protocol developed by Folch29. The wet cell pellet was re-suspended in equal weight of distilled and deionized water. The lipid extraction was carried out at a room temperature of 21°C except that the cells were kept on ice. 1.8 ml of the cell suspension was transferred to a glass centrifuge tube. Addition of 4 ml chloroform and 2 ml of methanol was followed by vortexing for 1 minute. 2 ml of methanol was added followed by 1 minute of vortexing. 2 ml of buffer solution (0.1 M NaAc at pH 4.5) was added followed by 1 minute of vortexing. Then the tube was placed on a rocking incubator for 3 hours. After that, the phase separation was assisted by centrifugation at 1,300 rpm for 5 minutes with a Beckman Allegro X-22R centrifuge. The heavier chloroform-rich phase was transferred by a glass syringe to a second glass centrifuge tube. The water-rich phase in the first tube was further extracted three times. Each time, 2 ml of chloroform was added, the mixture vortexed, the phase separation assisted by centrifugation, and the chloroform-rich phase transferred to the second glass tube. The combined chloroform-rich phase (~10 ml) in the second tube was first washed by adding 1 ml DI water followed by vortexing for 5 seconds. The lighter water-rich phase was removed after centrifugation. Another wash and dehydration cycle with 1.0 ml 0.5 M NaCl followed. After vortexing and subsequent centrifugation at 1,300 rpm, the chloroform-rich phase was collected into a third tube. This final sample was placed in a heater at 30°C and dried in an argon stream for approximately 2–3 hours. The empty tube was weighted, and again after drying. Typically, approximately 5 mg of total lipids were obtained and dissolved in chloroform to a concentration of 4 mg/ml.\n\nChemical syntheses of aminoacylated derivatives of PE – Lipids of PE with fatty acyl chains 16:0–18:1 were acquired from Avanti Polar Lipids. Fluorenylmethyloxycarbonyl chloride (Fmoc)-protected L-alanine as well as Fmoc and t-Butyloxycarbonyl (Boc)-protected L-Lysine were purchased from Sigma-Aldrich. 10 ml of dichloromethane (DCM) was added into a round bottom flask on ice with continuous stirring. 0.014 mmol Fmoc-Ala or Fmoc-Lys-Boc (2.0 × equivalents) was dissolved in the solvent followed by the addition of 0.016 mmol (2.2 × equivalents) NN-Dicyclohexylcarbodiimide (DCC). The PE chloroform solution was washed with saturated sodium bicarbonate. Then 0.007 mmol (1 × equivalent) PE was added dropwise in 1 minute. After 5 minutes of incubation on ice, the reaction mixture was placed in a water bath at the room temperature of 21°C for 1–2 hours. The reaction mixture was filtered through a 100 ml glass filter with fritted disc and then washed first with 1.0 ml of saturated sodium bicarbonate and then 1.0 ml of 0.5% HCl. The organic phase was dried by rotary evaporation, and was redissolved in 50% piperidine in dimethylformamide for the deprotection of Fmoc. Deprotection of Fmoc was carried out at room temperature for 4 hours, followed by the double wash and drying procedure described above. The lysyl-PE product was dissolved in DCM containing 10–20% trifluoroacetic acid (TFA) and incubated at room temperature for 30 minutes to remove Boc protection. The final product was double washed, dried, and redissolved in chloroform for storage at -80°C.\n\nLipid analysis by thin-layer chromatography. A total volume of 15 ul of lipid samples (4 mg/ml) were spotted 1.5 cm above the bottom edge on 0.25 mm thick silica gel on plastic sheet (Millipore) cut to a size of 10 cm × 20 cm. Alternatively, 100 ul of lipid samples were spotted on 1.0 mm thick silica gel on a glass plate (Fluka). After drying over a heater set at 50°C for ~10 minutes, the TLC sheet/plate was placed into a TLC chamber pre-equilibrated with a mixed solvent of chloroform : methanol : water (65:25:4). After ~30 minutes, the TLC sheet/plate was removed from the TLC chamber and dried for 5 minutes at 50°C. The TLC sheet/plate was first stained by spraying 0.01% primuline (Sigma-Aldrich) solution in acetone : water (80:20), dried in air or with mild heating for ~5 minutes. The fluorescent image was recorded with a Syngene G:BOX system. The fluorescent bands on the thicker gel were lifted and extracted by 100 ul of chloroform in a glass tube. The gel debris was discarded after centrifugation at 1,300 rpm for 1 minute. The TLC sheet was stained again by 0.1% ninhydrin (Sigma-Aldrich) in acetone : acetic acid (100:1), dried in air for ~5 minutes and heated at 100°C until purple spots appeared in a few minutes. The visible light image was recorded with the Syngene system.\n\nLipid profiling by mass spectroscopy. The lipid samples were diluted by adding 9-fold volume of methanol to a concentration of 0.4 mg/ml (or 400 ppm) for direct infusion at a rate of 0.6 ml/hour to a SCIEX 4000 QTRAP mass spectrometer. Electrospray ionization was achieved at a temperature of 500°C and a pressure of 20 psi for curtain gas as well as ion source gas 1 and 2. The collision energy in the ion trap was set at +45 or -65 electronvolts in positive and negative mode, respectively. A total of 30 MCA cycles of ion counts were accumulated as the mass spectra of precursor scans and neutral loss scans. The SCIEX Analyst software (version 1.6) was used to acquire and export averaged mass spectra. MS spectra in the figures were generated by Mass++ software (version 2.7.3)30 or Microsoft Excel.\n\nTandem mass spectroscopy. The targeted MS/MS spectra were first acquired using the SCIEX 4000 QTRAP system. The parameters were the same as those for the profiling. High-accuracy MS/MS spectra were later acquired using an Agilent Q-TOF 6550 system. Direct infusion was set at a slower rate of 0.1 ml/hour for the Q-TOF 6550 system.\n\nAlkaline hydrolysis of lipids – All lipids from one extraction procedure from 0.9 g of wet cells, dissolved in ~0.6 ml chloroform, was partially hydrolyzed by adding 0.25 ml of methanol and 0.04 ml of 1.0 M NH4OH and incubating at 37°C for 90 minutes without stirring. A volume of 0.05 ml 1.0 M formic acid was added to the solution followed by 0.5 ml of water. The mixture was vortexed for a few seconds and gently shaken in hand to partially remove bubbles. Then the mixture was centrifuged at 1,300 rpm for 5 minutes. The top water-rich layer was collected into a glass beaker and thoroughly dried at 90°C. The residue was dissolved in 0.1 ml water.\n\nAlkaline hydrolysis of bacterial cells – 1.5 ml of cells at early stationary phase with an OD600 value (optical density at 600 nm) of ~2.0, were centrifuged at 13,000 rpm for 5 minutes. The cell pellet was subjected to 3 rounds of washing with 1.0 ml of water and centrifugation to discard the wash. The cells were deactivated by heating in boiling water bath for 10 minutes. Then the cells were suspended in 0.1 ml of 1.0 M NH4OH. The sample was incubated at 37°C for 90 minutes without stirring. The supernatant after centrifugation at 13,000 rpm for 5 minutes was transferred to a glass beaker and thoroughly dried (1 minute). The residue was dissolved in 0.1 ml of water.\n\nConjugation with Marfey’s reagent – 0.1 ml of 2 mM L- or D-alanine, or the samples from alkaline hydrolysis, was transferred to a glass vial with cap. Then 0.2 ml acetone, 0.05 ml 1% (~30 mM) Marfey’s reagent31 in acetone, and 0.04 ml 1.0 M NaHCO3 were added and mixed by gentle shaking. The reaction solution was kept at 37°C for 90 minutes without stirring. As the reaction progressed, the bright yellow color of the solution turned into a darker color resembling maple syrup. The reaction was stopped by adding 0.05 ml 1.0 M formic acid.\n\nLC/MS analysis of conjugated alanine – The reaction solution with Marfey’s reagent was diluted 10-fold into acetone. 2 ul of the diluted sample was injected into the LC system for inline LC/MS analysis using the SCIEX 4000 QTRAP system. An Agilent ZORBRAX Eclipse Plus C18 (2.1 mm × 100 mm) reverse-phase column was used. The aqueous solution A contained 10 mM NH4Ac at pH 4.6. The organic solution B is HPLC-grade acetone. The flow rate was set at 0.2 ml/minute. The gradient from 20% B to 80% B was developed in 10 minutes, followed by 2 extra minutes of column regeneration at 80% B and 8 minutes of equilibration at 20% B. The molecular anion of 340 amu corresponding to the alanyl-derivative of Marfey’s reagent was monitored by the mass spectrometer. The mixed alanine standard was a 1:1 mix of the diluted reaction solutions of D- and L-alanine.\n\n\nResults\n\nProfiling of major bacterial lipids - We first modified the lipid extraction protocol using chloroform and methanol based on Folch method29. Polar lipids from E. coli strain BL21(DE3) and B. subtilis strain 168 were extracted. Thin-layer chromatography was carried out to analyze the major components. Every primuline-stained major band on the TLC plate was collected using a razor and redissolved in 100 ul chloroform. We then acquired MS spectra of the total lipids as well as the TLC-separated lipids and tandem MS/MS spectra of dominant molecular ions. The major component of each primuline-stained band on the TLC plate was assigned (Figure 1) based on the MS and MS/MS spectra. As expected, lipids extracted from E. coli strain BL21(DE3) were mainly composed of PE and PG (Figure 1)6. As expected, lipids from B. subtilis strain 168 were also rich in lysyl-PG and cardiolipin (CL) (Figure 1). The relative abundance of PE was much lower in B. subtilis than E. coli. The most abundant ninhydrin-stained amino group-containing band was that of lysyl-PG. A third ninhydrin-stained band, which was visible in only a small fraction of lipid preparations, overlapped with the PG-rich band. The amino group in this band likely comes from alanyl-PG as indicated by mass spectroscopy. The ninhydrin-stained spot at the origin likely corresponds to free amino acids.\n\nMajor components of the bands are shown. Bright panels: Primuline-stained TLC sheet. Dark panels: Ninhydrin-stained TLC sheet. The fluorescent primuline (bright spots) is absorbed to hydrophobic molecules. Ninhydrin reacts with amino groups to produce purple products (dark spots). Lysyl-phospholipids form a distinct band with slow mobility. Alanyl-PG migrates slightly faster than PG, but significantly slower than PE. The Gram-negative E. coli has little CL.\n\nTandem MS/MS spectra of lysyl- and alanyl-PGs – The most abundant fragments of negative (deprotonated) molecular ions of phospholipids were fatty acyl anions ([FA-H]-) of various sizes. Deprotonated molecular ions of PG and CL also dissociated to form a cyclo-glycerol-phosphate anion (153 amu), which is widely used to search for precursors that have a phosphoglycerol backbone32. Lipids from the E. coli strain were richest in saturated pentadecanoic acid (15:0) and hexadecanoic acid (16:0). The B. subtilis lipids, on the other hand, were most abundant in pentadecanoic acid (15:0) and heptadecanoic acid (17:0). The dominance of odd numbers of carbon atoms in the fatty acyl chain indicates that both bacteria likely utilize leucine or isoleucine primers for branch-chain fatty acid biosynthesis33. The loss of a neutral head group from positive (protonated or sodiated) molecular ions of phospholipids produced dehydroxyl-diacylglycerol cations ([DAG-OH]+) as the most abundant fragments. This neutral loss feature is commonly used to search for phospholipids with certain head groups34. For instance, PE can be identified by a scan for the neutral loss of phosphoethanolamine (141 amu). We acquired tandem MS/MS spectra of lysyl- and alanyl-PGs in both positive and negative mode. The spectra in negative mode with a collision energy of -65 electronvolts were dominated by [FA-H]- and deprotonated aminoacyl ions: [Ala-H]- (88 amu) and [Lys-H]- (145 amu) (Figure 2).\n\nMajor peaks in the MS/MS spectra are labeled. FA – fatty acid, LPG – (30:0) lysyl-PG, APG – (32:0) alanyl-PG, cGP – cyclo-glycerol-phosphate. A. MS/MS spectrum of lysyl-PG. B. MS/MS spectrum of alanyl-PG.\n\nPrecursor scans for aminoacyl-PGs – Besides lysyl- and alanyl-PGs, there were no molecular ions in the MS spectra which matched expected m/z values for other types of aminoacyl-PG ions. The abundance of the deprotonated aminoacyl ions prompted us to utilize this structural feature to search with high sensitivity for lipid precursors which produce such fragment ions. We first tested this protocol on lysyl- and alanyl-PGs and similarly esterized CL. The dominant molecular anions from the precursor scans at a collision energy of -65 electronvolts matched the expected m/z values of lysyl-PG and alanyl-PG species with two (15:0) or (17:0) fatty acyl chains (Figure 3A & 3B). The two types of lipid species with less abundant fatty-acyl compositions were also identified as peaks separated by 14 amu that corresponds to a methylene group. No aminoacyl-CL was identified in higher mass range around 1500 amu. We then applied such precursor scans to search for other aminoacylated PGs or CLs. With the exception of cysteine, the scans identified correct sized candidates of molecular anions of 17 aminoacyl-PGs with two clearest examples of leucyl-PG and aspartyl-PG shown in Figure 3C & 3D. The scans were not able to differentiate between glutamine and lysine, or between leucine and isoleucine, which share similar or identical molecular mass.\n\nMajor peaks in the spectra are labeled with fatty acid composition (number of carbon atoms: number of desaturation). A. Scan for precursors of a 145 amu anion. B. Scan for precursors of a 88 amu anion. C. Scan for precursors of a 130 amu anion. D. Scan for precursors of a 132 amu anion.\n\nNeutral loss and precursor scans for aminoacyl-PEs – There were no major peaks which corresponded to molecular ions of aminoacyl-PEs. We first employed a scan at an optimized collision energy of +45 electronvolts that searches for precursors of the most abundant [(30:0) DAG-OH]+ fragment ion (523 amu). The major hits corresponded to protonated as well as sodiated PE, PG, lysyl-PG, alanyl-PG as well as several other less abundant species including one at 792 amu which corresponded to the expected size of a protonated lysyl-PE species (Figure 4A). No other ions matched expected m/z values of aminoacyl-PEs. We then employed scans for molecular cations, also at +45 electronvolts, which produced fragments that resulted from the neutral loss of head groups (269 amu for lysyl-phosphoethanolamine, 212 amu for alanyl-phosphoethanolamine). The scan for the neutral loss of 269 amu found strong candidates for lysyl-PEs (Figure 4B). It is worth noting that their putative fatty acyl compositions (30:0, 31:0, 32:0) matched those of the dominant molecular ions of PE, PG, lysyl-PG and alanyl-PG. We then synthesized (16:0–18:1) lysyl-PE and alanyl-PE. The tandem MS/MS spectra of chemically synthesized lysyl-PE and alanyl-PE were also acquired (Figure 5). In addition to the major fragment [DAG-OH]+ ion, the sodiated molecular cations also dissociate to produce intense fragment peaks which corresponded to the sizes of the sodiated head groups (292 amu and 235 amu, respectively). Additional scans at a collision energy of +45 electronvolts for precursors which generate such sodiated head group ions revealed hits which were in agreement with the neutral loss scan for lysyl-PE (Figure 4B & 4C), and implied the existence of alanyl-PE (757, 771 and 785 amu ions in Figure 4D).\n\nMajor peaks in the MS/MS spectra are labeled. LPG – lysyl-PG, APG – alanyl-PG, LPE – lysyl-PE, APE – alanyl-PE. A. Scan for precursors of a 523.3 amu DAG fragment. B. Scan for a neutral loss of a 269.1 amu fragment. C. Scan for precursors of a 292.1 amu fragment. D. Scan for precursors of a 235.1 amu fragment.\n\nProtonated and sodiated ions are shown. LPE – (16:0–18:1) lysyl-PE, APE – (16:0–18:1) alanyl-PE, PA – phosphatidyl acid, DAG – diacylglycerol, Head – head group, cAE – cyclo-alanyl-ethanolamine, cK – cyclo-lysine, cKE – cyclo-lysyl-ethanolamine. A & B. Lysyl-PE. C & D. Alanyl-PE.\n\nIrreproducibility of aminoacyl-PEs – Although the presence of aminoacyl-PEs was interesting at first, we no longer found their presence when several new batches of the bacterial polar lipids were extracted without the final drying step at 30°C. It appears that the drying process may have caused existing species PE and aminoacyl-PGs in the lipids to chemically react to produce aminoacyl-PEs. This should be a caution which needs attention while sensitive profiling by mass spectrometry is employed.\n\nTandem mass spectra of L-lysyl-PG – The 4000 QTRAP system for liquid profiling has a practical resolution of 0.7 amu and accuracy of 0.2 amu. The Q-TOF 6550 system, optimized for proteomic research in positive mode, was tuned to reach a much higher accuracy of ~2 ppm or within 0.001 amu. We acquired high-accuracy MS/MS spectra of putative molecular ions of lysyl- and alanyl-PGs to further verify our assignments and to obtain clues for devising sensitive scans for lipid profiling. There were only two aminoacyl-PGs, lysyl-PG and alanyl-PG, that produced abundant enough (over 1000 counts) molecular ions for tandem mass spectrometry study. In fact, lysyl-PG was expectedly one of the most abundant phospholipids in the bacterium. It is certainly L-lysyl-PG as its lysyl group is known to have originated from L-lysyl-tRNA. In negative mode with collision energy set at -50 electronvolts, lysyl-PG ions of 821 and 849 amu produced an abundance of deprotonated lysyl ions besides two major – (15:0) and (17:0) - fatty acyl anions at 241 and 269 amu. The observed mass of [Lys-H]- was 145.0972, matching the calculated monoisotopic mass of 145.0978. A deprotonated glutamine ion would have a distinctively different mass of 145.0613. We also acquired MS/MS spectrum of sodiated (32:0) lysyl-PG cation (873 amu) at a collision energy of +40 electronvolts (Figure 6). Although protonated lysyl-PG ions were also abundant (823 amu and 851 amu), they produced less prominent fragments than the sodiated ions. Since a sodiated lysyl-PG but not a protonated lysyl-PG has a potent neutral amino group for intramolecular nucleophilic substitution, it is not surprising that we observed plenty of prominent structural features (Table 1) from the sodiated lysyl-PG ion (873 amu). For instance, it produced sodiated cyclo-lysine (151.0841 amu vs a calculated mass of 151.0848 amu) to verify the presence of lysyl residue along with the deprotonated lysyl ion in negative mode. It produced cyclo-lysyl-glycerol in both protonated (185.1275 vs 185.1291) and sodiated form (225.1205 vs 225.1216) to further indicate that the lysyl residue is attached to the glycerol head group. The fragments of sodiated cyclo-lysyl-glycerolphosphate (305.0868 vs 305.0879) and lysyl-glycerolphosphate (323.0972 vs 323.0985) finally completed the head group assignment. The outstanding abundance of the 323 amu fragment made a precursor scan for this fragment in positive mode the second best behind the precursor scan for deprotonated lysyl ion (145 amu) in negative mode. Both protonated and sodiated dehydrated DAG fragments were abundant (551 and 573 amu, respectively). So was sodiated DAG (591 amu). The neutral loss of the cyclo-lysyl-glycerol head group (202 amu) produced sodiated phosphatidic acid (671 amu) and that of cyclo-lysine (128 amu) produced sodiated PG (745 amu). It is worth noting that neutral losses of fatty acid (RCOOH) or ketene (R-C=C=O) produced minor peaks less than 100 counts, which are not shown in Figure 6.\n\nNote: The alphabetically labeled scissile bonds are shown in Figure 6 and Figure 7. PA – phosphatidic acid; PG – phosphatidylglycerol; DAG – diacylglycerol; Pho – phosphate; Lys – lysine; Gro – glycerol. A cyclic compound in mass is equivalent to a dehydrated compound.\n\nMS/MS spectrum of sodiated lysyl-PG (873 amu) ions is shown. The molecular structure is shown on the top with scissile bonds labeled alphabetically. The horizontal axis represents m/z values. The vertical axis represents ion counts.\n\nTandem mass spectra of alanyl-PG – Since alanyl-PG appeared to be much less abundant than lysyl-PG, we first chose the lipid preparation with the highest abundance of alanyl-PG as revealed by TLC analysis (Figure 1) for tandem mass spectra acquisition. The most abundant putative alanyl-PG anions were observed at 764 and 792 amu, corresponding to (30:0) and (32:0) alanyl-PG, respectively. Besides the fatty acyl anions, they produced an abundance of alanyl anion at 88.0396 amu, closely matching expected value of 88.0399. Fragmentation at putative protonated alanyl-PG ions (766 and 794 amu) did not produce meaningful results. We conclude that they are not abundant enough for tandem MS analysis. The sodiated alanyl-PG cation (816 amu), corresponding to (32:0) alanyl-PG, was abundant enough to produce a simpler MS/MS spectrum (Figure 7 and Table 2) than that of its lysyl-PG counter-part (Figure 6 and Table 1). The presence of the 168 amu ion was critical for the assignment of the alanyl-glycerol attachment, as it corresponds to sodiated cyclo-alanyl-glycerol (168.0623 vs 168.0640). The presence of the whole alanyl-glycerolphosphate head group was verified by the presence of sodiated cyclo-alanyl-glycerolphosphate (248.0287 vs 248.0300) and sodiated alanyl-glycerolphosphate (266.0395 vs 266.0410). In fact, the outstanding abundance of the 266 amu cation makes a precursor scan for this fragment the second most sensitive lipid profiling scan for alanyl-PG behind the scan for deprotonated alanine (88 amu). As for lysyl-PG, the DAG residues were also abundant (551 and 573 amu).\n\nMS/MS spectrum of sodiated alanyl-PG (816 amu) ions is shown. The molecular structure is shown on the top with scissile bonds labeled alphabetically. The horizontal axis represents m/z values. The vertical axis represents ion counts.\n\nNote: The alphabetically labeled scissile bonds are shown in Figure 6 and Figure 7. The abbreviation are the same as in Table 1. Ala - alanine.\n\nLC/MS analysis of D- and L-alanine in lipid and whole cell lysates – Alanyl groups in the bacterial lipids as well as on bacterial cell surface are known to be labile under mild alkaline conditions35,36. We established a set of alkaline hydrolysis and alanine extraction protocols that were practically complete at both hydrolysis and extraction stages. Since ammonia and formic acid residues were removed by evaporation, these reagents did not pose any interference with later experimental steps of TLC, conjugation with Marfey’s reagent, and mass spectrometry. By Marfey’s design, the derivatives of D-amino acids tend to have longer retention times on a reverse-phase column than their respective L-amino acid derivatives. The D-alanyl-derivative of Marfey’s reagent eluted significantly later and as a higher and sharper peak at 9.16 minutes than that of the L-alanyl-derivative which eluted at 7.55 minutes (Figure 8). The alanine released by alkaline hydrolysis of bacterial cells was predominantly D-alanine (~90%), while that of lipids was exclusively D-alanine. By comparing the ion counts with the standard D- and L-alanine solution (equivalent to 1 mM each), the 0.1 ml lysate from 1.5 ml of bacterial cells contained ~0.05 mM D-alanine, while the 0.1 ml lipid lysate contained ~0.05 mM D-alanine. Considering that the lipid lysate was derived from ~100-fold more bacterial cells than the whole cell sample, there appeared to be 1000-fold more D-alanine on the cell surface than that in the membrane. We typically obtained 5–10 mg dried lipids from 0.9 g wet cell pellet, which corresponds to a weight ratio of approximately 100. By taking into account this weight ratio, we estimate that whole cell still has ~10-fold denser D-alanine than membrane. Importantly, the alanylated phosphatidylglycerol is D-alanyl-PG, it is therefore not synthesized from tRNA-carried L-alanyl by a reaction catalyzed by MprF. Instead, another well-known source of activated alanine carried by D-alanine carrier protein DltC in the form of thioester22,37 may be the most likely origin.\n\nThe 340 amu molecular anion was monitored. The horizontal axis corresponds to retention time (minute). Peak retention times are marked. The peaks at 8.05 minutes, which correspond to a background 339 amu anion, is marked with “339”.\n\n\nDiscussion\n\nAminoacylated lipids play an important role in regulating the surface charge of Gram-positive bacteria5. It appears that mass spectrometry can be exploited to successfully search for trace amounts of aminoacylated phospholipids. Mass spectrometry also makes identification of known as well as unknown lipids possible even without separation or chemical synthesis. The positive results on a broad range of aminoacylated-PGs are consistent with previous work on lipid hydrolysate7. The intensities of various aminoacyl anions dissociated from the bacterial lipids span at least 3 orders of magnitude with lysyl anion being the strongest (6 × 106) followed by alanyl (9 × 105), leucyl/isoleucyl (4 × 104) and aspartyl (7 × 103) (Figure 3). It is worth noting that the latter two molecular ions did not show appreciable peaks in the MS spectrum. The aminoacyl-PG synthase MprF is known to have a broad range of aminoacyl-tRNA specificity10. Our results may have provided a semi-quantitative measure of the specificity of B. subtilis MprF.\n\nSince PE is a major component of bacterial lipids, we also searched for aminoacylated derivatives of PE. The amide-linked PE derivative cannot be identified by their PG counterparts’ dissociation into deprotonated aminoacyl ions. We therefore employed the neutral loss (NL) scanning methodology based on those commonly used for identifying phosphatidylethanolamine (NL of 141 amu head group), phosphatidylserine (NL of 185 amu head group), phosphatitylacid (NL of 115 amu ammoniated head group) and phosphatidylinositol (NL of 277 amu ammoniated head group)34. We also searched for precursors of the most abundant dehydroxyl-diacylglycerol cation (523 amu) which has the dominant fatty acyl composition of (30:0). The resulting spectrum provided a representative survey of all major species of phospholipids (Figure 4A). MS/MS spectra of chemically synthesized lysyl-PE and alanyl-PE revealed intense peaks corresponding to sodiated head groups, which led to high-sensitivity precursor scans. The sodium ion appeared to have played an important role in generating intense peaks of head group fragments as well as contributing to high yield in lipid extraction due to its inert chemical property in comparison to commonly used ammonium salt. Other metal ions such as cesium which, like sodium, has only one stable isotope, can be further exploited for enhanced sensitivity in lipid profiling38. Although the presence of lysyl- and alanyl-PEs appeared to be accidentally introduced in the lipid drying process, we did have established a sensitive enough lipid profiling method to rule out their biological relevance in B. subtilis.\n\nImportantly, the identification of D-alanyl-PG rather than L-alanyl-PG apparently rules out the relevance of the aminoacyl-tRNA-dependent MprF in its biosynthesis. Instead, the dlt operon, which codes four proteins named sequentially as DltA-D, comes into focus. The cytosolic DltC protein serves as the alanyl carrier protein with a serine-attached 4’-phosphopantetheine as the site for alanyl-thioester formation in the presence of ATP and catalyzed by DltA. Biological functions of the two membrane-bound proteins DltB and DltD have yet to be fully characterized. Mysteriously, the targets of DltC-carried alanyl group are lipoteichoic acid located at the outer leaflet of cytoplasmic membrane, and wall-teichoic acid covalently attached to peptidoglycan. We have long suspected the presence of a D-alanylated lipid as an intermediate for the eventual transfer of D-alanine from the cytosol to lipoteichoic acid. D-alanyl-PG may just be this putative intermediate D-alanyl carrier. Figure 9 illustrates a list of possible pathways for the transfer of D-alanine to lipo- and wall-teichoic acids. First, the D-alanylated lipid may be produced by DltD, and transported to the outer leaflet by a flippase such as the integral membrane protein DltB or the pore domain of MprF which is known to transport L-lysyl-PG and other L-aminoacyl-PGs9. Second, D-alanyl-PG can be transferred to lipo- and wall-teichoic acids by a transferase such as DltB, a putative membrane-bound O-acyltransferase39, or incorporated as D-alanyl-glycerolphosphate units from D-alanyl-PG into the growing ends of teichoic acids by their respective polymerases LtaS40,41 and TagF42,43. It is worth noting that D-alanyl-CL has been reported before27. As alanyl-PG and alanyl-CL share an ester bond with the glycerol head group, both are candidates for the lipid intermediate for D-alanylation of teichoic acids. Our hypothesis is also based on the best biochemical evidence, or the lack thereof, on DltB and DltD. DltD was previously observed to bind specifically to DltC and possess thioesterase activity on D-alanyl-acyl carrier protein23. If we substitute the water nucleophile in the thioesterase-catalyzed reaction for hydroxyl in the head group of PG, DltD would become a D-alanyl transferase. In addition, our bioinformatics analysis of crystal structure of Streptococcus pneumoniae DltD (PDB entry 3BMA, deposited by New York SGX Research Center for Structural Genomics) using ProFunc44 revealed a Ser-His-Asp triad embed in a structure (Figure 10) with overall similarity to platelet-activating factor, which belongs to the phospholipase A2 category. Apparently, the putative catalytic triad is conserved in all known DltD orthologs in Gram-positive bacteria. Since many phospholipid synthases belong to a superfamily of phospholipase D1, a synthase in the superfamily of phospholipase A2 would not be surprising. We therefore hypothesize that DltD may serve as the synthase of D-alanyl-PG, which may serve as the key lipid D-alanyl carrier for the D-alanylation pathway of teichoic acids.\n\nArrows depict either transport or transfer processes. The dihexosyl parts of teichoic acids are shown as twin hexagons. The head group of phosphatidylglycerol and repeating glycerolphosphate units in teichoic acids are shown in grey circle and ellipse, respectively.\n\nA, Ribbons diagram of DltD. The side chains in the Ser-His-Asp triad are shown in ball-and-stick model. B, Space-filling model of DltD. The most conserved residues are shown in red, and the least conserved in green. The putative catalytic triad is shown in blue.\n\n\nData availability\n\nF1000Research: Dataset 1. MS scans in search for aminoacylated phospholipids and tandem mass spectra of aminoacylated phosphatidylglycerol and aminoacylated phosphatidylethanolamine, 10.5256/f1000research.7842.d11202145",
"appendix": "Author contributions\n\n\n\nYL conceived the study, carried out the bioinformatics analysis of DltD, optimized alkaline hydrolysis of lipids and bacterial cell, characterized the D-enantiomer of alanine by LC/MS, interpreted the QTOF MS/MS spectra, and wrote the manuscript. MA carried out cell culture, chemical synthesis, lipid extraction and lipid profiling, and drew Figure 9.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work is supported by Saskatchewan Health Research Foundation Group Grant (2008–2010) and Phase 3 Team Grant (2010–2013) to the Molecular Design Research Group at University of Saskatchewan, a Natural Sciences and Engineering Research Council Discovery Grant (2010–2015) 261981-2010 to YL.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgement\n\nWe thank Ms. Deborah Michel for training both authors on the use of the SCIEX 4000 QTRAP system at the Core Mass Spectrometry Facility at the University of Saskatchewan. 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PubMed Abstract | Free Full Text\n\nWelti R, Li W, Li M, et al.: Profiling membrane lipids in plant stress responses. Role of phospholipase D alpha in freezing-induced lipid changes in Arabidopsis. J Biol Chem. 2002; 277(35): 31994–2002. PubMed Abstract | Publisher Full Text\n\nArchibald AR, Baddiley J, Heptinstall S: The alanine ester content and magnesium binding capacity of walls of Staphylococcus aureus H grown at different pH values. Biochim Biophys Acta. 1973; 291(3): 629–34. PubMed Abstract | Publisher Full Text\n\nChilds WC 3rd, Neuhaus FC: Biosynthesis of D-alanyl-lipoteichoic acid: characterization of ester-linked D-alanine in the in vitro-synthesized product. J Bacteriol. 1980; 143(1): 293–301. PubMed Abstract | Free Full Text\n\nDebabov DV, Heaton MP, Zhang Q, et al.: The D-Alanyl carrier protein in Lactobacillus casei: cloning, sequencing, and expression of dltC. J Bacteriol. 1996; 178(13): 3869–76. PubMed Abstract | Free Full Text\n\nGriffiths RL, Bunch J: A survey of useful salt additives in matrix-assisted laser desorption/ionization mass spectrometry and tandem mass spectrometry of lipids: introducing nitrates for improved analysis. Rapid Commun Mass Spectrom. 2012; 26(13): 1557–66. PubMed Abstract | Publisher Full Text\n\nHofmann K: A superfamily of membrane-bound O-acyltransferases with implications for wnt signaling. Trends Biochem Sci. 2000; 25(3): 111–2. PubMed Abstract | Publisher Full Text\n\nGrundling A, Schneewind O: Synthesis of glycerol phosphate lipoteichoic acid in Staphylococcus aureus. Proc Natl Acad Sci U S A. 2007; 104(20): 8478–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLu D, Wörmann ME, Zhang X, et al.: Structure-based mechanism of lipoteichoic acid synthesis by Staphylococcus aureus LtaS. Proc Natl Acad Sci U S A. 2009; 106(5): 1584–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFitzgerald SN, Foster TJ: Molecular analysis of the tagF gene, encoding CDP-Glycerol:Poly(glycerophosphate) glycerophosphotransferase of Staphylococcus epidermidis ATCC 14990. J Bacteriol. 2000; 182(4): 1046–52. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLovering AL, Lin LY, Sewell EW, et al.: Structure of the bacterial teichoic acid polymerase TagF provides insights into membrane association and catalysis. Nat Struct Mol Biol. 2010; 17(5): 582–9. PubMed Abstract | Publisher Full Text\n\nLaskowski RA, Watson JD, Thornton JM: ProFunc: a server for predicting protein function from 3D structure. Nucleic Acids Res. 2005; 33(Web Server issue): W89–93. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLuo Y, Atila M: Dataset 1 in: Profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis. F1000Research. 2016. Data Source"
}
|
[
{
"id": "12605",
"date": "23 Feb 2016",
"name": "Otto Geiger",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis manuscript by Atila and Luo reports on the profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis. Lipids from Escherichia coli and B. subtilis are analyzed by thin-layer chromatography and mass spectrometry, but no mass spectral data are shown for E. coli lipids or anything that supports the claim that E. coli lipids were rich in C15:0 fatty acid. Other mass spectral data presented suggest that phosphatidylglycerol (PG) can be substituted with most proteinogenic amino acids, however, lysyl- and alanyl-PG are certainly the most abundant. The authors report extensively (Figs. 4, 5) on lysyl- and alanyl-phosphatidylethanolamine (PE) but come to the conclusion that that these structures were artifacts generated during the isolation procedure. The potentially most interesting finding is that alanyl-PG is almost exclusively substituted with the D-alanyl isomer. In general, the manuscript seems scientifically sound. The mainly mass spectral analysis data make the manuscript somehow descriptive and leave much room for speculation. Instead, one would like to see some complementary data that solidify some of the ideas presented here. Major Comments:It is not exactly clear why Escherichia coli is used at all in this study. – As a reference strain? If so, why then a strain that is used for expression of genes? What really surprises me is that the authors find that “Lipids from the E. coli strain were richest in saturated pentadecanoic acid (C15:0) and …”. - Whatever previous references you consult, C15:0 is never mentioned as a major fatty acyl residue in E. coli. For example, see Mejía et al. (1999). If it is true that C15:0 is a major fatty acid in E. coli, this finding would certainly put in doubt some dogmas. Membrane lipid biosynthesis and composition of Bacillus subtilis strain 168 has been studied by numerous groups to a considerable extent. One of the major results of the present paper is that alanyl-PG carries exclusively the D-alanyl form and the authors discussed extensively that D-alanyl-PG should be formed by a mprF-independent pathway. There are MprF-deficient mutants available from John Helman´s group (Salzberg and Helman, 2008) and if the authors are correct, one would expect that these mutants still can make D-alanyl-PG. Fig. Legend 8: Mention here or somewhere that the “340 amu molecular anion” corresponds to alanine + Marley´s ?I don´t understand the last part of the Discussion “with overall similarity to platelet-activating factor”. Platelet-activating factor is a relatively hydrophilic lipid; so which similarity can it have to a protein? Minor Comments:Page 2, second paragraph of Introduction: change “peptitoglycan” to “peptidoglycan” Page 3, left column, third paragraph, and elsewhere: The symbol for “micro” used here is an “u” not the Greek symbol as it should be. Table 1: change “Calculated Msss” to “Calculated mass”.",
"responses": [
{
"c_id": "1844",
"date": "05 Apr 2016",
"name": "Yu Luo",
"role": "Author Response",
"response": "This manuscript by Atila and Luo reports on the profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis. Lipids from Escherichia coli and B. subtilis are analyzed by thin-layer chromatography and mass spectrometry, but no mass spectral data are shown for E. coli lipids or anything that supports the claim that E. coli lipids were rich in C15:0 fatty acid. Other mass spectral data presented suggest that phosphatidylglycerol (PG) can be substituted with most proteinogenic amino acids, however, lysyl- and alanyl-PG are certainly the most abundant. The authors report extensively (Figs. 4, 5) on lysyl- and alanyl-phosphatidylethanolamine (PE) but come to the conclusion that that these structures were artifacts generated during the isolation procedure. The potentially most interesting finding is that alanyl-PG is almost exclusively substituted with the D-alanyl isomer. In general, the manuscript seems scientifically sound. The mainly mass spectral analysis data make the manuscript somehow descriptive and leave much room for speculation. Instead, one would like to see some complementary data that solidify some of the ideas presented here. YL: We appreciate Dr. Otto Geiger's comments and suggestions. Our response as listed below and clarification will be incorporated in the revised version. It was a fact, perhaps an unfortunate distraction, that we had spent a lot of time on aminoacylated PE. Major Comments:It is not exactly clear why Escherichia coli is used at all in this study. – As a reference strain? If so, why then a strain that is used for expression of genes? YL: This strain is first used as a reference strain which is not expected to produce aminoacylated PG. It is also planned to be used in the near future as the host for expressing DltABCD proteins. What really surprises me is that the authors find that “Lipids from the E. coli strain were richest in saturated pentadecanoic acid (C15:0) and …”. - Whatever previous references you consult, C15:0 is never mentioned as a major fatty acyl residue in E. coli. For example, see Mejía et al. (1999). If it is true that C15:0 is a major fatty acid in E. coli, this finding would certainly put in doubt some dogmas. YL: The mass spectra of the E. coli strain were similar to that reported in reference 24 with (33:1) PG and PE being the most abundant. It was richest in (16:0) and (14:0) saturated fatty acids along with (17:1) and (18:1) monounsaturated or cyclopropane fatty acids. There was a less abundant 241 amu fragment ion matching deprotonated (15:0) saturated fatty acid or (14:0) epoxy fatty acid. However, it was not the aim of this study to characterize the fatty acid composition.Membrane lipid biosynthesis and composition of Bacillus subtilis strain 168 has been studied by numerous groups to a considerable extent. One of the major results of the present paper is that alanyl-PG carries exclusively the D-alanyl form and the authors discussed extensively that D-alanyl-PG should be formed by a mprF-independent pathway. There are MprF-deficient mutants available from John Helman´s group (Salzberg and Helman, 2008) and if the authors are correct, one would expect that these mutants still can make D-alanyl-PG. YL: We have a plan to gather mutants of Bacillus subtilis strain 168, which are relevant to lipid biosynthesis. Since MprF's substrate is L-aminoacylated tRNA, we reasoned that the overwhelming abundance of D- over L-alanine in the lipid lysate implied that an mprF-dependent pathway likely produced D-alanyl-PG. During the past week, the MprF-deficient strain has been acquired as suggested and its lipid extract studied. As expected, the lipid did not contain lysyl-PG. Importantly, it did contain alanyl-PG, which is consistent to our hypothesis.Fig. Legend 8: Mention here or somewhere that the “340 amu molecular anion” corresponds to alanine + Marfey´s ? YL: We will add a statement that the 340 amu molecular anion corresponds to alanine derivatized by Marfey’s reagent.I don´t understand the last part of the Discussion “with overall similarity to platelet-activating factor”. Platelet-activating factor is a relatively hydrophilic lipid; so which similarity can it have to a protein? YL: We are sorry to have missed the word “acetylhydrolase”. The remote homolog is platelet-activating factor acetylhydrolase. ProFunc server found a possible match with an E-score of 0.078 to a platelet-activating factor acetylhydrolase (PDB entry 1BWR). A hydrogen-bonded triad of Ser-47 / Asp376 / His 379 corresponding to the active site of this acetylhydrolase was found conserved in the DltD structure. Minor Comments:1. Page 2, second paragraph of Introduction: change “peptitoglycan” to “peptidoglycan” 2. Page 3, left column, third paragraph, and elsewhere: The symbol for “micro” used here is an “u” not the Greek symbol as it should be. 3. Table 1: change “Calculated Msss” to “Calculated mass”.YL: We will correct these errors in the revised version.References1. Mejía R, Gómez-Eichelmann MC, Fernández MS: Fatty acid profile of Escherichia coli during the heat-shock response.Biochem Mol Biol Int. 1999; 47 (5): 835-44 PubMed Abstract YL: We appreciate this reference. .2. Salzberg LI, Helmann JD: Phenotypic and transcriptomic characterization of Bacillus subtilis mutants with grossly altered membrane composition.J Bacteriol. 2008; 190 (23): 7797-807 PubMed Abstract | Publisher Full Text YL: We plan to request all the mutant strains produced by the authors of this article. We have since acquired and studied the pssA and mprF mutants."
}
]
},
{
"id": "12662",
"date": "09 Mar 2016",
"name": "Zeeshan Ahmed",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript \"Profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis\" reports the contribution of authors in profiling and tandem mass spectrometry analysis of aminoacylated phospholipids in Bacillus subtilis. In general manuscript isvery well written,language is good,citations are up to date,writing is to the point, in scope of the journal,justified Introduction,very well described Materials and methods,very well presented and discussed Results,Quality of figure is good and legends are well described,Good points raised in Discussion,Data is provided.I am personally satisfied with the paper and I would like to congratulate authors of good work. I wanted to mention some points but most of those have been already addressed by the other reviewer (Otto Geiger). I agree with Dr Geiger's publicly available comments, especially:Addressing \"why Escherichia coli is used at all in this study as a reference strain?\".Minor comments.I would like to request authors to please address these before final submission.Thanks.",
"responses": [
{
"c_id": "1864",
"date": "05 Apr 2016",
"name": "Yu Luo",
"role": "Author Response",
"response": "YL: Thank you Dr. Ahmed for your comments. I am personally satisfied with the paper and I would like to congratulate authors of good work. I wanted to mention some points but most of those have been already addressed by the other reviewer (Otto Geiger). I agree with Dr Geiger's publicly available comments, especially:Addressing \"why Escherichia coli is used at all in this study as a reference strain?\".YL: This strain was used as the negative reference for its absence of aminoacylated lipids. Indeed its lipid composition was essentially identical to that reported for the K12 strain in reference 24.We will describe this in the revised version.YL: As suggested by Dr. Geiger, we have now acquired and studied the mprF mutant strain of B. subtilis 168. It indeed produced alanyl-PG but not lysyl-PG. We will mention this result in the revised discussion section. Since we are in the process of acquiring and studying several other lipid synthase mutant strains, we will report this piece of experimental data in a future publication."
}
]
},
{
"id": "12660",
"date": "14 Mar 2016",
"name": "Markus Ralser",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript by Atila and Luo presents a helpful, descriptive mass spectrometric analysis of the aminoacylated phospholipids in Bacillus subtilis. The authors acquired product ion scans of lysyl and alanyl phosphatidylglycerol, as well as precursor ion scans and neutral loss scans for different aminoacyl phosphatidylglycerols and aminoacyl phosphatidylethanolamine. They found 17 different aminoacyl phosphatidylglecerols but no aminoacyl phosphatidylethanolamine in the lipid extracts. Furthermore, D- and L- alanine were quantified after alkaline hydrolysis of the lipid extracts, and only the D enantiomer was found. The authors conclude that D-alanyl phosphatidylglycerol is present, which is a D-alanine carrier from the cytosol to lipoteichoic acid.As already mentioned by the referee 1, the most interesting finding of this study is that alanyl phosphatidylglecerol is composed solely of the D enantiomer. However additional control measurements which support this finding are highly recommended. I support the suggestion of referee 1 to test if alanyl-PG is formed in MprF deficient mutants, other controls with chemical standards are possible as well.In Figure 8, the ion count of D-alanine in the cell lysate seems much larger as in the lipid lysate; it is difficult to understand how this leads to the same concentration estimate (0.05 mM). In general the assumption that “the cell has ~10 fold denser d-alanine than membrane” appears speculative and is based on several assumptions (linear response of the instrument, quantitative hydrolysis and extraction). I suggest to remove this part or to make a more elaborate analysis. Have the authors analysed alanyl PGs in the chloroform rich phase after hydrolysis to check the efficiency of the hydrolysis? Furthermore the authors could measure the concentrations of free alanine by applying the same protocols without adding NH4OH to check the efficiency of the hydrolysis step.The authors reported an irreproducible measurement of aminoacyl PE, potentially caused by the drying process. How long did this 30C drying procedure take? The formation of aminoacyl PEs due to chemical reactions of PE and aminoacyl PGs would indicate an instability of the aminoacyl PGs. Therefore, how reproducible are the measurements of the aminoacyl PGs (variation in ion count)? Are these also influenced by the drying process?The authors used collision energies of +45 and -65eV with the QTRAP MS and -40 and +50 eV with the Q-Tof system. Potential caveats resulting from the differently chosen fragmentation settings should be discussed.What is the m/z of the precursor ion for the tandem MS measurements of deprotonated lysyl and alanyl PG (Figure 2)? m/z 821.5 and 792.5?We suggest to remove figure 10, as it provides no relevant information in the context of the findings reported in this study.",
"responses": [
{
"c_id": "1865",
"date": "05 Apr 2016",
"name": "Yu Luo",
"role": "Author Response",
"response": "YL: Thank you Dr. Rasler for your comments. We will incorporate part of our response to your comments in the revised version. For your comments on the methodologies, our response is listed below. The manuscript by Atila and Luo presents a helpful, descriptive mass spectrometric analysis of the aminoacylated phospholipids in Bacillus subtilis. The authors acquired product ion scans of lysyl and alanyl phosphatidylglycerol, as well as precursor ion scans and neutral loss scans for different aminoacyl phosphatidylglycerols and aminoacyl phosphatidylethanolamine. They found 17 different aminoacyl phosphatidylglecerols but no aminoacyl phosphatidylethanolamine in the lipid extracts. Furthermore, D- and L- alanine were quantified after alkaline hydrolysis of the lipid extracts, and only the D enantiomer was found. The authors conclude that D-alanyl phosphatidylglycerol is present, which is a D-alanine carrier from the cytosol to lipoteichoic acid.YL: We hypothesize that D-alanyl-PG may serve as the intermediate for D-alanylation of wall- and lipo-teichoic acids. We haven’t proved this.As already mentioned by referee 1, the most interesting finding of this study is that alanyl phosphatidylglecerol is composed solely of the D enantiomer. However additional control measurements which support this finding are highly recommended. I support the suggestion of referee 1 to test if alanyl-PG is formed in MprF deficient mutants, other controls with chemical standards are possible as well. YL: We have acquired and studied the lipid composition of the mprF mutant strain. This mprF mutant strain indeed produced alanyl-PG, which is consistent to our hypothesis. In Figure 8, the ion count of D-alanine in the cell lysate seems much larger as in the lipid lysate; it is difficult to understand how this leads to the same concentration estimate (0.05 mM). In general the assumption that “the cell has ~10 fold denser d-alanine than membrane” appears speculative and is based on several assumptions (linear response of the instrument, quantitative hydrolysis and extraction). I suggest to remove this part or to make a more elaborate analysis.YL: It was an error. Thanks for pointing this out. The correct value of the alanine concentration in the 0.1 ml lipid lysate should be ~0.005 mM. The peak width stayed the same, and the peak high was linear to the concentration of D-alanine derivative. The linear intrapolation was valid. Have the authors analysed alanyl PGs in the chloroform rich phase after hydrolysis to check the efficiency of the hydrolysis? Furthermore the authors could measure the concentrations of free alanine by applying the same protocols without adding NH4OH to check the efficiency of the hydrolysis step. YL: We found that HCl and NaOH at less than 50 mM was compatible with TLC analysis without distorting the lanes. So was 1.0 M of volatile NH4OH, formic acid and acetic acid. Completion of hydrolysis and partitioning of alanine in the aqueous phase were both traced by TLC with ninhydrin staining. The three acidic conditions were inefficient in releasing alanine. NaOH and NH4OH were found to be efficient in releasing alanine. We further chose to use the low concentration of NaOH in lipid hydrolysis for its relative ease to acidify by formic acid, which facilitates free fatty acid partitioning in the chloroform-rich phase.The authors reported an irreproducible measurement of aminoacyl PE, potentially caused by the drying process. How long did this 30C drying procedure take? The formation of aminoacyl PEs due to chemical reactions of PE and aminoacyl PGs would indicate an instability of the aminoacyl PGs. Therefore, how reproducible are the measurements of the aminoacyl PGs (variation in ion count)? Are these also influenced by the drying process? YL: The drying process typically took a few hours. Unlike aminoacylated PEs, aminoacylated PGs were always detected in ~10 samples with a range of ion counts within 10 fold prior to manuscript preparation. The fluctuation could be partially addressed to constant optimization process which changes experimental parameters such as pH and buffer concentration. Now we have standardized cell culture protocol with 10 mM pH 7 sodium phosphate buffer in the LB media and standardized lipid extraction protocol, the most recent triplicates showed ion counts within 2 fold.The authors used collision energies of +45 and -65eV with the QTRAP MS and -40 and +50 eV with the Q-Tof system. Potential caveats resulting from the differently chosen fragmentation settings should be discussed.YL: The design of the two system are too different to address the implication of different energies on the fragmentation pattern. As far as we know, the tandem MS spectra were consistent within a 20 eV range with changes in ion counts but not in the overall fragmentation pattern. Tandem MS spectra were acquired at multiple collision energies. Generally, higher collision energy enriches smaller fragments, while lower energy enriches larger fragments. Only the spectra with the most fragments detected with adequate abundance were analysed.What is the m/z of the precursor ion for the tandem MS measurements of deprotonated lysyl and alanyl PG (Figure 2)? m/z 821.5 and 792.5? YL: The [M-H]- precursor ion of the alanyl-PG had an observed m/z value of 792.5405 amu. Its calculated mass is 792.5394 amu. The precursor lysyl-PG anion had an observed m/z value of 821.5672 amu versus the calculated value of 821.5660 amu. However, figure 2 shows the data acquired with the Sciex 400 QTRAP system which has a lower resolution than the Agilent Q-TOF 6550 system.We suggest to remove figure 10, as it provides no relevant information in the context of the findings reported in this study. YL: We felt it is somewhat useful to describe the bioinformatics analysis which indicated that DltD is likely a lipase-like enzyme."
}
]
}
] | 1
|
https://f1000research.com/articles/5-121
|
https://f1000research.com/articles/5-360/v1
|
16 Mar 16
|
{
"type": "Research Article",
"title": "Post-chikungunya chronic inflammatory rheumatism: results from a retrospective follow-up study of 283 adult and child cases in La Virginia, Risaralda, Colombia",
"authors": [
"Alfonso J. Rodriguez-Morales",
"Andrés F. Gil-Restrepo",
"Valeria Ramírez-Jaramillo",
"Cindy P. Montoya-Arias",
"Wilmer F. Acevedo-Mendoza",
"Juan E. Bedoya-Arias",
"Laura A. Chica-Quintero",
"David R. Murillo-García",
"Juan E. García-Robledo",
"Juan D. Castrillón-Spitia",
"Jose J. Londoño",
"Hector D. Bedoya-Rendón",
"Javier de Jesús Cárdenas-Pérez",
"Jaime A. Cardona-Ospina",
"Guillermo J. Lagos-Grisales",
"Andrés F. Gil-Restrepo",
"Valeria Ramírez-Jaramillo",
"Cindy P. Montoya-Arias",
"Wilmer F. Acevedo-Mendoza",
"Juan E. Bedoya-Arias",
"Laura A. Chica-Quintero",
"David R. Murillo-García",
"Juan E. García-Robledo",
"Juan D. Castrillón-Spitia",
"Jose J. Londoño",
"Hector D. Bedoya-Rendón",
"Javier de Jesús Cárdenas-Pérez",
"Jaime A. Cardona-Ospina",
"Guillermo J. Lagos-Grisales"
],
"abstract": "Objective: There are limited studies in Latin America regarding the chronic consequences of the Chikungunya virus (CHIK), such as post-CHIK chronic inflammatory rheumatism (pCHIK-CIR). We assessed the largest cohort so far of pCHIK-CIR in Latin America, at the municipality of La Virginia, Risaralda, a new endemic area of CHIK in Colombia.Methods: We conducted a cohort retrospective study in Colombia of 283 patients diagnosed with CHIK that persisted with pCHIK-CIR after a minimum of 6 weeks and up to a maximum of 26.1 weeks. pCHIK cases were identified according to validated criteria via telephone.Results: Of the total CHIK-infected subjects, 152 (53.7%) reported persistent rheumatological symptoms (pCHIK-CIR). All of these patients reported joint pains (chronic polyarthralgia, pCHIK-CPA), 49.5% morning stiffness, 40.6% joint edema, and 16.6% joint redness. Of all patients, 19.4% required and attended for care prior to the current study assessment (1.4% consulting rheumatologists). Significant differences in the frequency were observed according to age groups and gender. Patients aged >40 years old required more medical attention (39.5%) than those ≤40 years-old (12.1%) (RR=4.748, 95%CI 2.550-8.840).Conclusions: According to our results, at least half of the patients with CHIK developed chronic rheumatologic sequelae, and from those with pCHIK-CPA, nearly half presented clinical symptoms consistent with inflammatory forms of the disease. These results support previous estimates obtained from pooled data of studies in La Reunion (France) and India and are consistent with the results published previously from other Colombian cohorts in Venadillo (Tolima) and Since (Sucre).",
"keywords": [
"Chikungunya",
"Chronic complications",
"Epidemiology",
"Colombia"
],
"content": "Introduction\n\nChronic rheumatologic sequelae after Chikungunya virus infection (CHIK) are expected to become an important public health issue in the new endemic areas of Latin America, where the virus has been spreading without proper control1. Previous estimates have shown that nearly 48% of people affected develop post-CHIK chronic inflammatory rheumatism (pCHIK-CIR)2, with the derived burden of disease assessed by disability adjusted life years (DALYs) lost. In Latin American countries these DALYs are now consistently higher than those reported in previous epidemics in India in 2006. DALYs in Colombia are high as 2/3 of those for ischemic heart disease and are related mainly to chronic rheumatologic sequelae3–5.\n\nHowever, previous estimates were the result of pooled data from prior studies conducted in India and La Reunion (France) epidemics2. Due to possible virus lineage disparity, different host genetic or immune response, or even environmental variations, those results could not be fully extrapolated to Latin American countries. For these reasons, two retrospective cohorts have been published from Colombia and Latin America, reporting a higher proportion of patients evolving to pCHIK-CIR, particularly chronic polyarthralgia (pCHIK-CPA). Unfortunately, in those studies, the number of patients followed and the assessment of clinical inflammatory characteristics is still limited6,7.\n\nIn this setting, there is still a need to continue assessment and establish the proportion of patients evolving to pCHIK-CIR, both CPA and chronic arthritis (pCHIK-CA), in Latin American countries in order to reveal the real scenario we could face in terms of clinical consequences and chronic disability. Hence, we assessed this issue in the municipality of La Virginia in the department of Risaralda, a new endemic area of CHIK in Colombia, where autochthonous transmission and cases have been detected since January 2015.\n\n\nMethods\n\nEthics approval was obtained from the ESE Hospital IRB.\n\nThis retrospective cohort study included patients that suffered CHIK (diagnosed by positive CHIK specific serology, IgM/IgG anti-CHIK, and negative serology for dengue) between February–June 2015 attending in La Virginia, Risaralda (one of the newly endemic departments), Colombia (Figure 1), with at least 6 weeks between diagnosis and minimal follow-up time for reassessment. The primary outcome was the development of persistent polyarthralgia (pCHIK-CPA) that met the American College of Rheumatology/European League Against Rheumatism 2010 criteria for (seronegative) Rheumatoid Arthritis (RA)8. The patient report of articular inflammatory clinical symptoms was assessed. This included: morning stiffness, joint edema and joint redness. This was assessed via phone calls made by trained authors of this study. A structured questionnaire, previously employed in other studies6,7 was used (see Dataset 1, which includes all the variables assessed in these patients).\n\nCase definition of acute CHIK infection was made according to the National Institute of Health, Bogotá, Colombia, including serology plus fever (temperature ≥39°C) and polyarthralgia or arthritis. Patient consent was sought at the beginning of the interview.\n\nClinical assessment included interrogatory and physical examination on initial suspicion of CHIK. Following this, blood tests were performed in order to assess by RT-PCR and serology for IgG and IgM for chikungunya.\n\nRelative frequency of pCHIK-CPA as well other pCHIK chronic rheumatological manifestations (morning stiffness, joint edema and joint redness) were assessed overall, by sex, and by age groups estimating the relative risk (RR) with the corresponding 95% confidence intervals (95%CI). Furthermore, using censoring time, a pCHIK-CPA curve was drawn using the Kaplan-Meier method to describe the pCHIK-CPA persistence time, expressed in weeks. Also a Cox regression was performed to assess differences according age groups and sex in the outcome by time, estimating the hazard ratio (HR) and its corresponding 95%CI.\n\nAll data were recorded in a predesigned format, tabulated and the results analyzed statistically by SPSS® statistical software (version 20).\n\n\nResults\n\nA total of 283 subjects consented to participate. In total, this group was comprised of 173 (61%) women and 110 (39%) men, with a median age of 29.0 years (IQR 17.0–42.0), 84% of whom were from La Virginia, Risaralda, Colombia. All patients presented with fever and acute polyarthralgia. These cases were diagnosed between February and June 2015, with a median follow-up of 9.7 weeks (2.3 months) and a maximum time of 26.1 weeks (6.1 months).\n\nOut of the total CHIK-infected subjects, 152 (53.7%) reported persistent rheumatological symptoms (pCHIK-CIR) (Table 1). All of these patients reported joint pains (pCHIK-CPA). Regarding symptoms consistent with pCHIK-CA, 49.5% presented morning stiffness, 40.6% joint edema and 16.6% joint redness. Of those with pCHIK-CPA, 19.4% required and attended for care before the current study assessment (1.4% consulting rheumatologists). Among those who presented pCHIK-CIR, the maximum censored persistence time was 26.1 weeks (6.1 months). From the total, 17 patients where followed ≥20 weeks, and 13 of these patients (76.5%) are still presenting with pCHIK-CPA.\n\nRR=Relative risk; 95%CI=95% confidence interval; pCHIK-CPA=post-Chikungunya chronic polyarthralgia.\n\nThe cumulative prevalence of pCHIK-CPA varied significantly (p=0.0326) between those aged >40 years old (69.7%) and those ≤40 years old (47.8%) (RR=1.46, 95%CI 1.04–2.04). As expected, frequency increased with age group (Table 1). There was also a significant difference (p=0.014) between genders, with pCHIK-CPA being higher in women (59.5%) than in men (44.5%) (RR=1.337, 95%CI 1.049–1.703) (Table 1), which was also seen among those ≥30 years old (Table 1).\n\nA cumulative prevalence of pCHIK-CPA curve was drawn using the Kaplan-Meier method to describe the pCHIK-CPA persistence time (Figure 2). After the follow-up, only 46.3% patients remain free of polyarthralgia. The median time for pCHIK-CPA in this cohort was 14.6 weeks (>3 months) (95%CI 12.3–16.8). No significant difference (p>0.05) in the survival function according to age group (HR=1.086, 95%CI 0.774–1.523) or gender (HR=1.086, 95%CI 0.753–1.495) was observed.\n\nOther pCHIK chronic rheumatological symptoms also varied significantly by age. Morning stiffness in those aged >40 years old (60.5%) was significantly higher (p=0.024) than in those ≤40 years old (45.4%) (RR=1.843, 95%CI 1.079–3.148). Joint edema also was significantly higher in those aged >40 years old (53.9%) compared to those ≤40 years old (35.7%) (RR=2.105, 95%CI 1.235–3.588). Patients aged >40 years-old required more medical attention (39.5%) than those ≤40 years old (12.1%) (RR=4.748, 95%CI 2.550–8.840). As expected, there was a trend of frequency increasing by age groups with significant differences between females and males in some of them (Table 2).\n\nRR=Relative risk; 95%CI=95% confidence interval; pCHIK=post-Chikungunya.\n\nFrom the total of patients, 38.2% presented polyarthralgia and morning stiffness simultaneously. Polyarthralgia and morning stiffness was this significantly higher in those aged >40 years old (52.6%) was significantly higher (p=0.002) than in those ≤40 years old (32.9%) (RR=1.418, 95%CI 1.098–1.830) as well in females (46.2%) compared with males (25.5%) (RR=1.817, 95%CI 1.270–2.598); 11.3% presented also redness with polyarthralgia and morning stiffness simultaneously, being this significantly higher in females (15.6%) was significantly higher (p=0.004) than in males (4.5%) (RR=3.434, 95%CI 1.363–8.649); 9.9% presented joint edema, redness, polyarthralgia and morning stiffness simultaneously, being this significantly higher (p=0.005) in females (13.9%) was significantly higher than in males (3.6%) (RR=3.815, 95%CI 1.360–10.699).\n\nFinally, in patients <20 years old, >20% of patients in each age group presented with pCHIK-CPA (Table 3); in general pCHIK-CPA prevalence was higher in female patients, with the exception of the <10 years old age group where 31.3% of males presented with pCHIK-CPA (Table 3).\n\nRR=Relative risk; 95%CI=95% confidence interval; pCHIK-CPA=post-Chikungunya chronic polyarthralgia.\n\n\nDiscussion\n\nAccording to our results, at least half of the patients with CHIK could develop chronic rheumatologic sequelae, and from those with pCHIK-CPA, nearly half could present clinical symptoms consistent with inflammatory forms of the disease. These results support previous estimates obtained from pooled data of studies in La Reunion (France) and India2 and are consistent with the results published before from other Colombian cohorts in Venadillo (Tolima) and Since (Sucre)6,7. Indeed, our results suggest that the proportion of patients developing pCHIK-CIR could be even higher in some groups, especially women and older patients. Some patients persisted with rheumatism many months after CHIK infection. Furthermore, the symptoms led nearly 20% of patients to seek care, with some patients requiring attention by a rheumatologist. This highlights the incapacitating character of the symptoms.\n\nThis study represents the largest cohort of CHIK patients in Latin America followed to-date for chronic rheumatologic sequelae. Also, this is the first study to assess the development of both inflammatory and non-inflammatory rheumatologic complications post-CHIK infection in this region; previous local studies centered on the presence of CPA without examining clinical inflammatory characteristics such as morning stiffness, joint edema or joint redness6,7. The epidemiology of the CHIK epidemic in 20159 highlights the importance of the assessment of pCHIK-CIR, which should be included in the surveillance of endemic countries such as Colombia.\n\nAlthough limited due to the possible bias derived from the way in which information was collected (telephone interview), the consistency of the findings related to the proportion of patients that presented CPA and articular inflammatory symptoms with the variables of age and gender, supports the reliability of the obtained data. Smaller studies (<150 patients) recently have also employed telephone interviews to collect data10. One such study found that one third (37%) of study participants reported ongoing complaints related to Chikungunya including joint pain (32%), muscle pain (32%), and joint swelling (26%). A presumptive diagnosis of pCHIK chronic inflammatory arthritis (n = 4) and pCHIK musculoskeletal disorder (n = 3) was established10.\n\nHowever, the absence of confirmation of chronic articular inflammatory signs by a physician, the lack of information regarding the previous rheumatologic history, number and location of the ongoing articular involvement, received treatment (both prescribed and self-provided), and laboratory and radiographic assessment are important limitations of this work.\n\nWhile some studies have failed to demonstrate any factors associated with chronic pain11, other works have pointed to risks factors linked to the persistence of chronic rheumatologic manifestations and lack of recovery. In this study older age and female gender where significantly associated with pCHIK-CIR. Nevertheless, in prospective studies, severe initial joint pain, longer acute stage, underlying rheumatologic disease, added comorbidities, overweight and higher IgG anti-CHIK titers, should be also assessed as has been suggested12–16. Moreover, we also found that patients older than 40 years old and females consulted more frequently and tended to exhibit inflammatory symptoms, which raises concern about the possibility that those patients not only evolve more frequently to pCHIK-CIR but to more severe forms of the disease such as pCHIK-CA. However, also of great concern, is the fact that pCHIK-CIR was seen in a considerable proportion (almost 25%) of young people (<20 years old). Although the current study was not specifically designed to assess pCHIK-CPA in the pediatric population, it shows pCHIK-CPA occurrence in this age group for the first time in Colombia and Latin America. Globally, there is also a lack of cohort studies assessing pCHIK-CIR in children. Prior to this work, the largest study included 69 children <16 years old17; we assessed 88 patients <20 years old (57 <15 years old). This age group also deserves and requires specific studies assessing pCHIK-CIR given all the potential implications, including assessment by pediatric rheumatologists.\n\nPrevious cohorts, from France and India, have reported prevalences of pCHIK-CIR ranging from 4.4% to 81.1% with different follow up times (between 2.5 to 72 months) and different assessment procedures, including in-person, via telephone, imaging and laboratory11,14,17–21. Estimations from those studies showed a prevalence of pCHIK-CIR of 41.57% (95%CI 45.08–50.13) in a median time of 20.12 months2. And, in the two previous published cohorts from Colombia the proportion ranged from 44.3 to 89.7%6,7. Hence, the real risk of developing chronic rheumatologic forms of the disease remains unclear and, despite the fact that bone and articular erosions have been reported even after three years of follow up18, the duration of the articular involvement remains uncertain. The proportion of patients that develop inflammatory forms of the disease needs further assessments. Recent studies have found that pCHIK-CIR can persist even after 6 years of follow-up, as was the case for 59% of patients from 2006–2012 in La Reunion, France20. Nonetheless, our findings are consistent with previous results and certainly raise concern about the future burden of CHIK since assessment using these estimates is already high3,4,22,23.\n\nBesides that, the treatment of inflammatory pCHIK-CIR in Colombia is currently guided by the recommendations to treat rheumatoid arthritis with the consequent economical burden to the health system24. However, there is a lack of high quality evidence to guide treatment and to reassure risk reduction of musculoskeletal sequelae, although non-steroidal anti-inflammatory drugs and disease modifying anti-rheumatic drugs have shown good results in previous works25,26.\n\nHence, more studies are needed, particularly prospective studies in order to clarify risk factors, clinical forms, derived disability from rheumatologic symptoms, evolution and treatment. CHIK spread remains without proper control in Latin America, the development of an effective vaccine does not seem like a plausible scenario in the near future and the more expeditious way to mitigate its spread seems to be vector control and educational strategies. If policy makers do not address the problem of disease spread and research needs in this area, cost and burden of chronic sequelae could debilitate already fragile health systems. Recently the National Institute of Health of Colombia (Instituto Nacional de Salud, Bogotá), have estimated that the 817,442 cases (August 2014–August 2015) cost around US$ 25.4–384.2 million (currency change of September 15, 2015) (US$ 31–470 per case, just considering acute phase)27. However, data from our group, recently published28, considering both, acute and chronic phases (estimating the number of patients that will persist with pCHIK-CIR)2, have found that 106,592 cases (August 2014–December 2014) cost around US$ 65.1–164.2 million (US$ 611–1540 per case)28. This represents very high costs for the country, even in the most conservative scenario.\n\nMore health authorities frankly need to consider the importance of surveillance for chronic patients in this setting. Governments must face the reality that CHIK is a vector borne disease that is likely here to stay, representing more than 3,000 new cases in 2016. Since September 2015, in addition to CHIK, another arthritogenic arbovirus is cocirculating in the country, Zika, needing studies that assess if chronic complication with it are also possible.\n\n\nData availability\n\nF1000Research: Dataset 1. Raw data for ‘Post-chikungunya chronic inflammatory rheumatism: results from a retrospective follow-up study of 283 adult and child cases in La Virginia, Risaralda, Colombia’., 10.5256/f1000research.8235.d11655929\n\n\nConsent\n\nWritten informed consent for publication of their clinical details was obtained from the patients/parents of the patients. The IRB of the hospital approved this study.",
"appendix": "Author contributions\n\n\n\nStudy design: AJRM, Data collection: AFGR, VRJ, CPMA, WFAM, JEBA, LACQ, DRMG, JEGR, JDCE, HDBR, Data analysis: AJRM, JACO, GJLG, Writing: All authors. All authors read the final version submitted.\n\n\nCompeting interests\n\n\n\nThere is no conflict of interest.\n\n\nGrant information\n\nThis study was funded by the Universidad Tecnologica de Pereira, Pereira, Risaralda, Colombia.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nAlfaro-Toloza P, Clouet-Huerta DE, Rodriguez-Morales AJ: Chikungunya, the emerging migratory rheumatism. Lancet Infect Dis. 2015; 15(5): 510–2. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales AJ, Cardona-Ospina JA, Villamil-Gómez W, et al.: How many patients with post-chikungunya chronic inflammatory rheumatism can we expect in the new endemic areas of Latin America? Rheumatol Int. 2015; 35(12): 2091–4. PubMed Abstract | Publisher Full Text\n\nCardona-Ospina JA, Rodriguez-Morales AJ, Villamil-Gomez WE: The burden of Chikungunya in one coastal department of Colombia (Sucre): Estimates of the disability adjusted life years (DALY) lost in the 2014 epidemic. J Infect Public Health. 2015; 8(6): 644–6. PubMed Abstract | Publisher Full Text\n\nCardona-Ospina JA, Diaz-Quijano FA, Rodriguez-Morales AJ: Burden of chikungunya in Latin American countries: estimates of disability-adjusted life-years (DALY) lost in the 2014 epidemic. Int J Infect Dis. 2015; 38: 60–1. PubMed Abstract | Publisher Full Text\n\nKrishnamoorthy K, Harichandrakumar KT, Krishna Kumari A, et al.: Burden of chikungunya in India: estimates of disability adjusted life years (DALY) lost in 2006 epidemic. J Vector Borne Dis. 2009; 46(1): 26–35. PubMed Abstract\n\nRodriguez-Morales AJ, Villamil-Gomez W, Merlano-Espinosa M, et al.: Post-chikungunya chronic arthralgia: a first retrospective follow-up study of 39 cases in Colombia. Clin Rheumatol. 2015; 35(3): 831–832. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales AJ, Calvache-Benavides CE, Giraldo-Gomez J, et al.: Post-chikungunya chronic arthralgia: Results from a retrospective follow-up study of 131 cases in Tolima, Colombia. Travel Med Infect Dis. 2016; 14(1): 58–9. PubMed Abstract | Publisher Full Text\n\nAletaha D, Neogi T, Silman AJ, et al.: 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 2010; 62(9): 2569–81. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales AJ, Bedoya-Arias JE, Ramirez-Jaramillo V, et al.: Using geographic information system (GIS) to mapping and assess changes in transmission patterns of chikungunya fever in municipalities of the Coffee-Triangle region of Colombia during 2014-2015 outbreak: Implications for travel advice. Travel Med Infect Dis. 2016; 14(1): 62–5. PubMed Abstract | Publisher Full Text\n\nZeana C, Kelly P, Heredia W, et al.: Post-chikungunya rheumatic disorders in travelers after return from the Caribbean. Travel Med Infect Dis. 2016; 14(1): 21–5. PubMed Abstract | Publisher Full Text\n\nChopra A, Venugopalan A: Persistent rheumatic musculoskeletal pain and disorders at one year post-chikungunya epidemic in south Maharashtra—a rural community based observational study with special focus on naïve persistent rheumatic musculoskeletal cases and selected cytokine expression. Indian Journal of Rheumatology. 2011; 6: 5–11. Publisher Full Text\n\nSissoko D, Malvy D, Ezzedine K, et al.: Post-epidemic Chikungunya disease on Reunion Island: course of rheumatic manifestations and associated factors over a 15-month period. PLoS Negl Trop Dis. 2009; 3(3): e389. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCouturier E, Guillemin F, Mura M, et al.: Impaired quality of life after chikungunya virus infection: a 2-year follow-up study. Rheumatology (Oxford). 2012; 51(7): 1315–22. PubMed Abstract | Publisher Full Text\n\nGerardin P, Fianu A, Malvy D, et al.: Perceived morbidity and community burden after a Chikungunya outbreak: the TELECHIK survey, a population-based cohort study. BMC Med. 2011; 9: 5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGerardin P, Fianu A, Michault A, et al.: Predictors of Chikungunya rheumatism: a prognostic survey ancillary to the TELECHIK cohort study. Arthritis Res Ther. 2013; 15(1): R9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMoro ML, Grilli E, Corvetta A, et al.: Long-term chikungunya infection clinical manifestations after an outbreak in Italy: a prognostic cohort study. J Infect. 2012; 65(2): 165–72. PubMed Abstract | Publisher Full Text\n\nChopra A, Anuradha V, Ghorpade R, et al.: Acute Chikungunya and persistent musculoskeletal pain following the 2006 Indian epidemic: a 2-year prospective rural community study. Epidemiol Infect. 2012; 140(5): 842–50. PubMed Abstract | Publisher Full Text\n\nChaaithanya IK, Muruganandam N, Raghuraj U, et al.: Chronic inflammatory arthritis with persisting bony erosions in patients following chikungunya infection. Indian J Med Res. 2014; 140(1): 142–5. PubMed Abstract | Free Full Text\n\nMiner JJ, Aw Yeang HX, Fox JM, et al.: Chikungunya viral arthritis in the United States: a mimic of seronegative rheumatoid arthritis. Arthritis Rheumatol. 2015; 67(5): 1214–20. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJavelle E, Ribera A, Degasne I, et al.: Specific management of post-chikungunya rheumatic disorders: a retrospective study of 159 cases in Reunion Island from 2006-2012. PLoS Negl Trop Dis. 2015; 9(3): e0003603. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBouquillard E, Combe B: Rheumatoid arthritis after Chikungunya fever: a prospective follow-up study of 21 cases. Ann Rheum Dis. 2009; 68(9): 1505–6. PubMed Abstract | Publisher Full Text\n\nHoz JM, Bayona B, Viloria S, et al.: Fatal cases of Chikungunya virus infection in Colombia: Diagnostic and treatment challenges. J Clin Virol. 2015; 69: 27–9. PubMed Abstract | Publisher Full Text\n\nCardona-Ospina JA, Henao-SanMartin V, Paniz-Mondolfi AE, et al.: Mortality and fatality due to Chikungunya virus infection in Colombia. J Clin Virol. 2015; 70: 14–5. PubMed Abstract | Publisher Full Text\n\nMinisterio de Salud y Protección Social: Lineamientos para el manejo clínico de los pacientes con virus del Chikungunya (CHIKV). Bogotá D.C.: Ministerio de Salud y Protección Social; 2014.\n\nGanu MA, Ganu AS: Post-chikungunya chronic arthritis--our experience with DMARDs over two year follow up. J Assoc Physicians India. 2011; 59: 83–6. PubMed Abstract\n\nChopra A, Saluja M, Venugopalan A: Effectiveness of chloroquine and inflammatory cytokine response in patients with early persistent musculoskeletal pain and arthritis following chikungunya virus infection. Arthritis Rheumatol. 2014; 66(2): 319–26. PubMed Abstract | Publisher Full Text\n\nBogotá INdSd: Costos económicos asociados a la atención de pacientes con infección por Chikungunya en Colombia. 2015. Reference Source\n\nCardona-Ospina JA, Villamil-Gómez WE, Jimenez-Canizales CE, et al.: Estimating the burden of disease and the economic cost attributable to chikungunya, Colombia, 2014. Trans R Soc Trop Med Hyg. 2015; 109(12): 793–802. PubMed Abstract | Publisher Full Text\n\nRodriguez-Morales A, Gil-Restrepo AF, Ramírez-Jaramillo V, et al.: Dataset 1 in: Post-chikungunya chronic inflammatory rheumatism: results from a retrospective follow-up study of 283 adult and child cases in La Virginia, Risaralda, Colombia. F1000Research. 2016. Data Source"
}
|
[
{
"id": "12911",
"date": "23 Mar 2016",
"name": "Jaime R Torres",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article is well written and both the design and conclusions are sound. In the title, the term \"chronic inflammatory rheumatism\" is not widely used and should be replaced by \"chronic rheumatic manifestations\"",
"responses": [
{
"c_id": "1882",
"date": "24 Mar 2016",
"name": "Alfonso Rodriguez-Morales",
"role": "Author Response",
"response": "Thank you very much for your comments. Regard your recommendation to replace in the current title the expression \"chronic inflammatory rheumatism\", as would be not widely used and should be replaced by \"chronic rheumatic manifestations\"; although we truly appreciate your recommendation, we can not proceed according it, because the expression \"chronic inflammatory rheumatism\" has been used as part of articles title in 105 records in Medline up to March 23, 2016, as can be seen at: https://www.ncbi.nlm.nih.gov/pubmed/?term=chronic+inflammatory+rheumatism+[ti]; conversely, \"chronic rheumatic manifestations\", has been used just in four: https://www.ncbi.nlm.nih.gov/pubmed/?term=chronic+inflammatory+manifestations+[ti]. Then, is clearly more used \"chronic inflammatory rheumatism\" than \"chronic rheumatic manifestations\"."
}
]
},
{
"id": "12907",
"date": "24 Mar 2016",
"name": "Lin H. Chen",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a nicely done survey that assessed the persistence of rheumatologic symptoms in patients diagnosed with chikungunya. I presume the virus was the Asian lineage (rather than the Indian Ocean lineage that caused the outbreak in La Reunion), so it's interesting to see the impact of different virus lineages. The term \"censoring time\" may need clarification.",
"responses": [
{
"c_id": "1884",
"date": "29 Mar 2016",
"name": "Alfonso Rodriguez-Morales",
"role": "Author Response",
"response": "Thank you very much for your comments. Regarding the comment on the Asian genotype, this is in fact the one is circulating in Colombia as in Latin America, has been evidenced in different studies. We agree on the possibility of different potential impacts regard genotype. Nevertheless, other genotypes of CHIK are not circulating yet here. But in the future, if occurs, definitively should be assessed. Then, considering this, we have included a comment on it at the discussion, including a pertinent supporting reference, as well new information from a recently accepted meta-analysis from our group at Arthritis Care and Research about pCHIK-CIR:\"Finally, in Colombia 29, as well in other countries in the region, the genotype circulating is the Asian. In the future, if other CHIK genotypes begun to circulate in the same areas, comparison would allow to assess if they impose different clinical impacts, as currently assessing this with past epidemics where other genotypes and lineages were present, as the Indian Ocean one, would also imply potential differences in population immunogenetics and responses probably based in HLA and other ethnic factors. This has been recently showed regard the differences of pCHIK-CIR prevalences between studies in La Reunión island, France and India, being higher in the first, as evidenced in a meta-analysis which is coming out in the next weeks from our group 30.References:29 Mattar S, Miranda J, Pinzon H, et al.: Outbreak of Chikungunya virus in the north Caribbean area of Colombia: clinical presentation and phylogenetic analysis. J Infect Dev Ctries. 2015;9:1126–32. 26517488 10.3855/jidc.667030 Rodríguez-Morales AJ, Cardona-Ospina JA, Urbano-Garzón SF, et al.: Prevalence of post-Chikungunya Chronic Inflammatory Rheumatism: A Systematic Review and Meta-Analysis. Arthritis Care Res (Hoboken). 2016. (accepted, in press, ACR-15-0598.R2)\"Regard, the clarification of \"censoring time\", although this a pretty standard term in the analyses of survival and Kaplan-Meier curves, we have added a detail on this:\"Furthermore, using censoring time (the status at last observation for the time in which was assessed),...\"Thanks again for your constructive comments."
},
{
"c_id": "1891",
"date": "04 Apr 2016",
"name": "Alfonso Rodriguez-Morales",
"role": "Author Response",
"response": "References 30 is live online now (as accepted manuscript):Rodríguez-Morales AJ, Cardona-Ospina JA, Urbano-Garzón SF, Hurtado-Zapata JS. Prevalence of post-Chikungunya Chronic Inflammatory Rheumatism: A Systematic Review and Meta-Analysis. Arthritis Care Res (Hoboken) 2016 Epub Ahead Mar 25; available online at: http://onlinelibrary.wiley.com/doi/10.1002/acr.22900/abstract (Indexed on Medline/Index Medicus)"
}
]
},
{
"id": "13074",
"date": "29 Mar 2016",
"name": "Jorge L. Alvarado-Socarras",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIt would be interesting in future studies, evaluate Laboratories data, such as rheumatologic profile and autoimmune diseases.",
"responses": [
{
"c_id": "1889",
"date": "29 Mar 2016",
"name": "Alfonso Rodriguez-Morales",
"role": "Author Response",
"response": "Thanks for your comments. The plan now is to perform prospective cohort studies, including more detailed laboratory findings, such as those related to rhematological profile and autoimmune diseases."
}
]
}
] | 1
|
https://f1000research.com/articles/5-360
|
https://f1000research.com/articles/5-422/v1
|
31 Mar 16
|
{
"type": "Review",
"title": "The emerging role of phosphoinositide clustering in intracellular trafficking and signal transduction",
"authors": [
"Laura Picas",
"Frederique Gaits-Iacovoni",
"Bruno Goud",
"Laura Picas",
"Frederique Gaits-Iacovoni"
],
"abstract": "Phosphoinositides are master regulators of multiple cellular processes: from vesicular trafficking to signaling, cytoskeleton dynamics, and cell growth. They are synthesized by the spatiotemporal regulated activity of phosphoinositide-metabolizing enzymes. The recent observation that some protein modules are able to cluster phosphoinositides suggests that alternative or complementary mechanisms might operate to stabilize the different phosphoinositide pools within cellular compartments. Herein, we discuss the different known and potential molecular players that are prone to engage phosphoinositide clustering and elaborate on how such a mechanism might take part in the regulation of intracellular trafficking and signal transduction.",
"keywords": [
"Phosphoinositides",
"membrane organization",
"trafficking",
"signal transduction."
],
"content": "Introduction\n\nPhosphoinositides (PIs) are essential phospholipids that control, either directly or indirectly, multiple cellular functions including membrane trafficking, signal transduction, cell growth, cytoskeletal dynamics, lipid transport/exchange between organelles, and the regulation of transmembrane proteins1,2. PIs are the phosphorylated products of phosphatidylinositol. The reversible phosphorylation of the inositol ring at positions 3, 4, and 5 gives rise to the seven PI isoforms identified in eukaryotic cells (Figure 1). Inter-conversion of the phosphate group(s) is selectively tuned by numerous kinases and phosphatases, precisely regulated in space and time3 (Figure 1). The active metabolism of PIs is intimately linked to their role as precursors of second messengers during signal transduction4. The accumulation of the different PI species in specific membrane compartments is also directly related to their role in vesicular trafficking including endocytosis and exocytosis, endosome dynamics and trafficking from and towards the Golgi, among many others5 (Figure 1). Proteins with multiple trafficking functions are targeted to various membrane compartments based on the selective recognition of their PI-binding motifs. The distribution of protein residues folded in a 3D structure provides the PI-binding motifs with a “PI code”, which is based on the stereospecific recognition of the unique phosphate group’s organization around the inositol ring6 (Figure 1). There are at least 11 different structured motifs with a wide range of affinities and specificities for the different PI species. They include the PH (pleckstrin homology), the FYVE (Fab1, YOTB, Vac1, and EEA1), the PX (Phox homology), the ANTH and ENTH (AP180 and Epsin N-terminal homology), and the FERM (4.1, ezrin, radixin, moesin) modules.\n\nRepresentation of the phosphatidylinositol phospholipid structure: the inositol ring can be phosphorylated in three different positions and is linked to a diacylglycerol backbone by a phosphodiester linker. Schematics of the localization of the different PI isoforms on the cellular compartments.\n\n\nPIs and the lateral organization of membranes: the needle in a haystack\n\nCellular membranes are highly heterogeneous composites built of different types of lipids and proteins. For instance, in eukaryotic cells, more than 1000 different lipid species build up the different membrane compartments7. Lipid molecules freely diffuse in the 2D membrane plane (D ~2.6 × 10-7 cm2·s-1)8 and interact with protein effectors based on their association (Kon) and dissociation (Koff) rates. As a result, lipid-protein interactions are, in general, highly dynamic and thus strongly depend on their respective local concentration.\n\nPIs constitute less than 1% of the steady-state cell lipids7, yet they work as unique docking sites for the multiple PI effectors on membranes, which in turn either compete or cooperate with each other to interact with downstream partners and elicit specific responses. Thus, what are the driving mechanisms that ensure such a thorough spatiotemporal recognition and membrane association of host PI-binding motifs?\n\nAn attractive hypothesis is that PIs might be organized as specialized membrane subdomains with distinct organelle localizations5. PI pools within the same compartment are locally synthesized thanks to the spatiotemporal regulation of different PI-metabolizing enzymes3,5. In addition, small GTPases of the ARF and RAB family also contribute to the generation and regulation of PI turnover on membranes9.\n\nConsidering the diffusion coefficient of lipid molecules within the membrane plane, it is likely that complementary mechanisms need to operate in order to spatially preserve the turnover of different PI subdomains. Indeed, several mechanisms have been reported in the literature to play roles as selective and reversible PI sinks by locally sequestering and releasing PIs. This is the case for the myristoylated alanine-rich C-kinase substrate (MARCKS) protein and the growth-associated protein 43 (GAP43)10. The unstructured basic cluster on the effector domain of the MARCKS protein is able to bind up to at least three PI(4,5)P2 molecules by means of nonspecific electrostatic interactions at physiologic pH. The Ca2+/calmodulin complex reversibly controls the association of MARCKS with the plasma membrane11. Interestingly, a growing number of studies report the local enrichment of PI subdomains independently of the catalytic activity of PI-metabolizing enzymes. Jahn and co-workers have shown that the SNAP receptor protein syntaxin-1A co-clusters with PI(4,5)P2 via electrostatic interactions with its juxtamembrane polybasic sequence12. The segregation of PI(4,5)P2 microdomains by syntaxin-1A has been proposed to work as a molecular beacon at sites of synaptic vesicle docking during exocytosis13. Similar polybasic clusters to that of the MARCKS protein or syntaxin-1A are found in the cytosolic membrane interface of many plasma membrane proteins14,15, including the epidermal growth factor receptor (EGFR) and the NMDA receptor as well as the voltage-gated potassium and calcium ion channels11. In vitro studies have shown that divalent cations such as Ca2+ are also capable of clustering together PI(4,5)P2 molecules, although the exact correlation with the activity of ion channels inside the cell has yet to be established. Following in vitro approaches on giant unilamellar vesicles (GUVs), clustering of PI(4,5)P2 was initially reported for ezrin16. Later on, using the yeast endocytic F-BAR/BAR domains, Lappalainen and co-authors have shown that the scaffolding effect of these proteins leads to the formation of stable PI(4,5)P2 microdomains with reduced lateral diffusion in the membrane plane17,18. Since then, the list of proteins involved in the formation of PI(4,5)P2 clusters has been extended to other endocytic proteins such as Epsin2, AP180, and the N-BAR domain proteins amphiphysin1 and BIN119. So far, the formation of PI clusters has been mainly restricted to PI(4,5)P2, possibly owing to its multiple regulatory functions at the plasma membrane. In addition, PI(4,5)P2 is more abundant than other more elusive PI isoforms and has therefore been the focus of many studies for several years. However, we recently reported that the monophosphate PIs PI4P and PI5P can also be clustered19.\n\n\nPI clustering is a diffusion-driven process\n\nPI clustering has initially been proposed to originate from electrostatic interactions and, to a lesser extent, from hydrogen bonding between PI headgroups. PI molecules appear thus sequestered beneath positively charged surfaces, which results in a significant reduction of lateral diffusion in the membrane plane17. The number of PI molecules that interact with basic residues is determined by the negative net charge of the PIs at a given pH. For instance, the charge of the PI(4,5)P2 molecules at pH 3 is −1.5e, whereas at pH 7.4, which is close to the pH of the cytosol (7.2), it is −4e20. For a N-BAR homodimer of charge +8e, one could estimate that at cytosolic pH, the stoichiometry of PI-interacting molecules per protein module is 2:1, which gives an estimated 1.5-fold increase of local PI(4,5)P2. However, experimental studies have shown that the binding of the N-BAR module on PI-containing membranes induces a local enrichment of at least 10-fold19. How could such a difference in the local PIs’ enrichment be explained?\n\nTheoretical studies have shown that the binding of a positively charged protein with a negatively charged membrane induces lipid demixing near to the protein surface19,21. This phenomenon is the result of the combination of electrostatic interactions and an entropic effect. Upon protein-membrane binding, charged lipids diffuse in the plane of the membrane towards the protein surface to preserve charge neutrality (Figure 2). In the case of monovalent lipids such as phosphatidylserine (PS), lipid demixing is almost negligible as a result of the fast Kon/Koff rates between the protein and the membrane, which prevents charged lipids to locally segregate22 (Figure 2, left panel). However, for multivalent lipids such as some PI species, the transient interaction with a positively charged protein generates an electrostatic potential well, which results in a reduction of the Kon/Koff rates and in protein diffusion. Consequently, transient demixing of PI molecules can take place22 (Figure 2, right panel). As shown by numerical simulations and consistent with the estimated ~10-fold increase from experimental data, PIs can cluster together up to nine lipid molecules per protein module. The trajectory of PI molecules in the plane of the membrane showed the existence of PI-protein dissociation events, thus pointing out that clustered PI molecules are not sequestered19. Importantly, this behavior is observed at initial physiological relevant concentrations of 1% PI(4,5)P2.\n\nAs an example, lateral view of the ENTH domain of Epsin (PDB code 1H0A) in cyan upon binding to a membrane that contains monovalent lipids such as phosphatidylserine (PS) (in orange, left panel) or PI(4,5)P2 (in magenta, right panel). Cyan arrows represent the Kon/Koff rates of the ENTH domain binding on membranes, being faster for PS over PI(4,5)P2. As a result, transient demixing of PI(4,5)P2 molecules can take place. The diffusion of PS and PI(4,5)P2 in the plane of the membrane is depicted by orange and magenta arrows, respectively. Right panel shows a top view of PI(4,5)P2 clustering coarse-grain molecular dynamics simulations (as described in 19) on spontaneous membrane biding of an ENTH domain. The panels are snapshots at t = 0 μs and 4 μs of the individual position of PI(4,5)P2 molecules (in magenta) along the simulation. Scale bar, 1 nm.\n\nPI demixing has been reported in both flat and curved membranes. In the latter case, the segregation of PI molecules is likely to be amplified by membrane curvature since it is reported to significantly reduce protein diffusion23 and lipid dynamics17. This is in agreement with recent molecular simulations that show that clustering of lipids such as PIs and GM3 correlates with membrane curvature8.\n\n\nThe “PI clustering” toolbox: electrostatic interactions and beyond\n\nLocal segregation of PIs into submicron domains has been mostly described for proteins with the intrinsic property to polymerize on membranes, such as the BAR domain family. Proteins of the BAR family can sense and generate membrane curvature, owing to the scaffolding structure that results from the homodimerization of the BAR module. Association of BAR proteins with membranes takes place through electrostatic interactions between positively charged amino acids on the concave/convex face of the dimeric module and acidic phospholipids24. PI clustering has been reported for proteins with F-BAR, BAR, N-BAR, and I-BAR modules17–19. The tendency of multivalent PIs to engage lipid demixing over the monovalent PS provides BAR proteins with some specificity to generate PI subdomains at the plasma membrane, where PI(4,5)P2 and PI(3,4,5)P3 are the predominant affected PI isoforms. According to the structural homology within members of the BAR superfamily, it is likely that the formation of PI-enriched microdomains could be a general feature of any protein hosting a BAR module. Combination of the BAR module with PI-binding motifs within the same protein might provide an additional layer of regulation and, possibly, production of monophosphate PI pools in other organelles than the plasma membrane, as observed in the case of BIN119. This suggests that the property of PI clustering might be extrapolated to some members of the sorting nexin (SNX) family holding a BAR module and a PX motif25, although this link has yet to be established.\n\nThe clustering of PIs is, however, not necessarily associated with the intrinsic ability of proteins to self-assemble. Indeed, the transient segregation of PIs is likely to generate a positive feedback loop. As a result, proteins that selectively interact with PIs can locally accumulate on PI-enriched areas, independently of their ability to polymerize, as observed for the ENTH and ANTH domains19. Therefore, PI clustering seems to be a general property of proteins that directly interact with PIs via electrostatic interactions with more or less specificity for a given PI isoform. Accordingly, natively unstructured polybasic protein domains have also been shown to induce local segregation of PIs at the plasma membrane, as observed for MARCKS, GAP43, CAPS23, and syntaxin-1A10,13. The number of proteins that associate with acidic lipids at the plasma membrane through polybasic sequences is large14,15. For instance, several small GTPases have been shown to interact with plasma membrane PI(3,4,5)P3 and PI(4,5)P2 by means of polybasic clusters26.\n\nPI clustering might be solely limited to ionic protein-lipid interactions, although it is tempting to speculate that alternative or complementary mechanisms might take on the stabilization of PI pools. For instance, recent studies have shown that the pinning of the cytoskeleton on membranes preserves liquid-ordered and liquid-disordered (Lo-Ld) phase coexistence at physiological temperatures (37°C)27,28. The polymerization of actin cytoskeleton was also shown to promote segregation of lipid phases in in vitro models29. These observations are in agreement with the “picket fence” model, which predicts that the cytoskeletal network might act as a diffusion barrier for lipids and proteins30. The exact partition of PI(4,5)P2 into Lo-Ld domains is not yet clear, but the depletion of cholesterol with methyl-β-cyclodextrin was shown to reduce PI(4,5)P2 levels at the plasma membrane31. The partition of PI(4,5)P2 to cholesterol-dependent domains was also reported using the targeting of a 5-phosphatase32. In addition, the sequestration of syntaxin-1A microdomains at sites of synaptic vesicle exocytosis in the plasma membrane was shown to require the formation of cholesterol and PI(4,5)P2-mediated clusters, which are both distinct from lipid “rafts”12,33. An interesting observation is that Ld domains were found to align along actin fibers independently of the lipid phase to which actin was pinned28. This might be explained by local changes in membrane curvature induced by the actin network. Indeed, Ld domains appear to favor lipid sorting and membrane deformation34. Recently, numerical simulations have shown that clustering of lipids such as PI(4,5)P2 correlates with membrane curvature8. The exact contribution of membrane curvature itself in PI clustering is not yet established, but lipid packing defects associated with membrane curvature might favor a better exposure of PI(4,5)P2 headgroups19,35. Here, one will have to take into account in future experiments the nature of the fatty acids present on PI molecules, which might also impact on the rigidity and shape of the lipid bilayers to which they belong.\n\n\nPI clustering: a novel regulator of intracellular trafficking and signaling?\n\nImportantly, after PI clustering, protein-PI dissociation can still take place independently of the initial concentration of PIs19. This suggests that PI clusters are more dynamic than initially anticipated and that a given PI cluster could sequentially interact with different effectors. Thus, PI clustering induced by an upstream protein could favor the recruitment of a downstream PI-binding partner, providing a mechanism to coordinate trafficking or signaling events.\n\nOne process that PI clustering could regulate is clathrin-mediated endocytosis (CME). Indeed, the F-BAR, ANTH, ENTH, and N-BAR domains are present in central molecular players involved in CME36. All of these protein modules have been shown to engage local segregation of PI(4,5)P217,19, which is the key PI isoform in CME. Therefore, PI clustering could participate in the spatiotemporal regulation of CME based on the affinity constant of the different protein intermediates and their interaction with PI(4,5)P2. A hypothetical example of how PI clustering might operate in CME is shown in Figure 3, although the number of PI(4,5)P2 effectors implicated in CME is much larger (see Table 1). The polymerization of the N-BAR module along the bud neck is likely to establish a diffusion barrier37, highly enriched in PIs, which would thereby be shielded from the activity of kinases and phosphatases. These features might be relevant at different stages of clathrin-coated vesicle biogenesis. Indeed, the metabolic evolution of PIs during CME has been shown to be important for the maturation of clathrin-coated vesicles38. In addition, the segregation of lipid phases has been reported to generate sufficient line tension to induce membrane scission39. It is therefore possible that the PI demixing induced by BAR proteins plays an additional role in line tension-mediated fission at the last stage of CME, as suggested by theoretical studies40.\n\nThe table shows an overview of all the possible options that exist in the PI(4,5)P2-mediated protein recruitment during the different stages of CME. Notice that although the interaction with PI(4,5)P2 is mostly electrostatically driven, some effectors hold structured motifs with specific affinities/selectivity for PI(4,5)P2. In addition, effectors can act as either monomers or larger assemblies, although PI(4,5)P2 clustering can engage the local accumulation of proteins that typically do not self-assemble as a result of positive feedback19.\n\nThe F-BAR domain (Protein Data Bank [PDB] code 2V0O) of FCHo2 binds to the plasma membrane, driving PI(4,5)P2 segregation into clusters. The local PI(4,5)P2 enrichment drives the binding of Epsin through the interaction of its ENTH domain (PDB code 1H0A) with PI(4,5)P2. The Asn-Pro-Phe (NPF) domain of Epsin can interact with the EH domain (PDB code 3FIA) of Intersectin, which in addition hosts a PH domain (PDB code 1MAI) that binds to PI(4,5)P2. The dynamics of the system is likely influenced by the affinity constant of the PI(4,5)P2-binding motifs, which will determine the Kon/Koff of PI(4,5)P2-mediated membrane binding, and by the affinity constant between the different protein domains.\n\nIt is tempting to propose that the coordinated action of PIs and scaffolding protein complexes, in particular BAR proteins, is a general feature of the biogenesis of transport vesicles67. For instance, the N-BAR protein Arfaptin 1 has been shown to participate in the biogenesis of secretory storage granules through the interaction with PI4P at the trans-Golgi network68. The ArfGAP ASAP1 also carries a BAR module along with a PI-binding motif and has been shown to provide a platform to regulate Arf4 and Rab8/Rab11-mediated targeting of rhodopsin transport carriers to cilium69. Finally, some members of the SNX family also hold a BAR module in addition to the characteristic PX domain, which typically binds to PI3P6. The SNX-BAR proteins are implicated in tubule-based endosomal sorting70. This includes the two retromer subunits SNX1 and SNX2, SNX5, and SNX6 or SNX4 among others71,72. One may speculate that the formation of PI clustering together with the binding affinity for different PI effectors might be linked to the ability of SNX-BAR proteins to define tubular endosomal subdomains.\n\nPI clustering could also play an important role in the coordination of signaling events. Interestingly, the juxtamembrane segment of the EGFR, which is implicated in the activation of the receptor, is also composed of a cluster of basic residues that interact with PI(4,5)P273,74. Indeed, natively unstructured polybasic protein domains have been shown to engage PI(4,5)P2 clustering11. The interaction of the EGFR with PI(4,5)P2 is required for the activation and downstream signaling of the receptor at the plasma membrane and seems also to regulate its fate in the endosomal compartments. The first observation that PI4P 5-kinase activity generating PI(4,5)P2 pools was associated with the EGFR and required for appropriate activation and downstream signaling originates from the early 90s75. Later studies demonstrated that PI(4,5)P2 clustering induced by the binding and antiparallel dimerization of the juxtamembrane segments of two associated EGFRs can lead to the activation of the receptor even in the absence of ligand76. This property was suggested to be important at a high density of EGFR monomers (>800/µm2), as is often observed in aberrant activation of the receptor in cancers73,77. In this condition, formation of EGFR nanoclusters takes place as a result of the electrostatic interaction between PI(4,5)P2 molecules at the plasma membrane and the juxtamembrane region of the receptor78.\n\nRecent evidence demonstrates that PI(4,5)P2 generated on endosomes is required for the appropriate sorting of active EGFR towards multivesicular bodies and further termination of the signal. This process relies on the recruitment of the endosomal type Iγ PIP kinase, PIPKIγi5, that gets targeted to early endosomes by association with SNX5, an effector of PI(4,5)P2. The kinase will then increase local pools of PI(4,5)P2, also required for association of SNX5 with Hrs proteins that will then interact with ubiquitinated EGFR and ensure its proper sorting79.\n\nIt is noteworthy that most of the tyrosine kinase receptors of the EGFR family harbor a polybasic juxtamembrane domain that could play the same role in terms of ligand free activation or sorting and signal transduction (e.g. insulin-like growth factor 1 receptor [IGF1R], vascular endothelial growth factor receptor [VEGFR], platelet-derived growth factor receptor [PDGFR], and fibroblast growth factor receptor 1 [FGFR1], among others)76. Although PI clustering being a general feature of membrane-associated polybasic domains provides an attractive hypothesis to activate receptors and trigger signaling, work is still needed to define whether it is a broad mechanism or applies only to some specific proteins.\n\n\nConclusions\n\nThe spatiotemporal remodeling of PI pools within distinct organelles is an intrinsic feature that makes possible the orchestration of PI-mediated cellular functions. Indeed, PIs are constantly subjected to the activity of PI-metabolizing enzymes and must be in addition accessible to effectors. Because the lateral diffusion of lipid molecules within the membrane plane is extremely fast, PI clustering comes up as a realistic mechanism to locally preserve newly metabolized PI pools on cellular membranes. Indeed, Balla and co-workers already anticipated that PI4P replenishment from the Golgi was not essential to preserve the plasma membrane pool, although it does contribute to its formation80. Irvine and co-authors also showed that the maintenance of the steady-state pool of PI(4,5)P2 at the plasma membrane does not require localization of its synthetic precursor PI4P on the same cellular compartment81. It is tempting to speculate that PI clusters might work as potential platforms to coordinate PI-mediated protein interactions or as molecular beacons, as previously proposed13. Nevertheless, the myriad of protein modules capable of engaging PI clustering is becoming broad. Based on structural homologies, one might predict that the list will progressively increase. An interesting feature to point out is that PI clustering seems to be a general mechanism for either multivalent or monophosphate PIs19. The precise regulatory role of PI clustering in trafficking and signal transduction has still to be established, but it certainly opens up exciting perspectives in the field. For instance, PI clustering might orchestrate the different steps in carrier biogenesis. Also, the ability of cellular receptors to engage PI clustering might determine their sorting to the appropriate compartment. The physiological implication of PI clustering in living organisms has yet to be established. Recent studies have already shown that the oligomerization of Sec14-nodulin proteins controls the localization of PI(4,5)P2 and signaling landscape in polarized membrane morphogenesis in Arabidopsis thaliana root hairs82,83. Despite the role of PIs in many cellular processes, certain PI isoforms and functions have often been elusive due to the lack of detection or labeling strategies, which is typically limited to the use of PI-binding motifs with all of the associated side effects. The development of novel experimental strategies capable of detecting the intrinsic dynamics of PIs or of exploiting the recently developed sub-100nm life cell imaging techniques84 will be key to unraveling the regulatory role of PI clustering.",
"appendix": "Author contributions\n\n\n\nAll authors contributed equally to this work.\n\n\nCompeting interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThis work was supported by grants from the Agence Nationale de la Recherche (ANR) (ANR-13-BSV2-0004-01) and the ERC (MYODYN, # 339847).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe thank Dr. Stefano Vanni (Institut de Pharmacologie Moléculaire et Cellulaire, UMR 7275, France) for kindly performing and providing the numerical simulations shown in Figure 2.\n\n\nReferences\n\nDi Paolo G, De Camilli P: Phosphoinositides in cell regulation and membrane dynamics. Nature. 2006; 443(7112): 651–7. PubMed Abstract | Publisher Full Text\n\nMoser von Filseck J, Čopič A, Delfosse V, et al.: INTRACELLULAR TRANSPORT. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFaelber K, Posor Y, Gao S, et al.: Crystal structure of nucleotide-free dynamin. Nature. 2011; 477(7366): 556–60. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKlein DE, Lee A, Frank DW, et al.: The pleckstrin homology domains of dynamin isoforms require oligomerization for high affinity phosphoinositide binding. J Biol Chem. 1998; 273(42): 27725–33. PubMed Abstract | Publisher Full Text\n\nMao Y, Balkin DM, Zoncu R, et al.: A PH domain within OCRL bridges clathrin-mediated membrane trafficking to phosphoinositide metabolism. EMBO J. 2009; 28(13): 1831–42. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDho SE, French MB, Woods SA, et al.: Characterization of four mammalian numb protein isoforms. Identification of cytoplasmic and membrane-associated variants of the phosphotyrosine binding domain. J Biol Chem. 1999; 274(46): 33097–104. 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EMBO J. 2008; 27(19): 2457–70. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCruz-Garcia D, Ortega-Bellido M, Scarpa M, et al.: Recruitment of arfaptins to the trans-Golgi network by PI(4)P and their involvement in cargo export. EMBO J. 2013; 32(12): 1717–29. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWang J, Morita Y, Mazelova J, et al.: The Arf GAP ASAP1 provides a platform to regulate Arf4- and Rab11-Rab8-mediated ciliary receptor targeting. EMBO J. 2012; 31(20): 4057–71. PubMed Abstract | Publisher Full Text | Free Full Text\n\nvan Weering JR, Sessions RB, Traer CJ, et al.: Molecular basis for SNX-BAR-mediated assembly of distinct endosomal sorting tubules. EMBO J. 2012; 31(23): 4466–80. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBonifacino JS, Hurley JH: Retromer. Curr Opin Cell Biol. 2008; 20(4): 427–36. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSzentpetery Z, Várnai P, Balla T: Acute manipulation of Golgi phosphoinositides to assess their importance in cellular trafficking and signaling. Proc Natl Acad Sci U S A. 2010; 107(18): 8225–30. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHammond GR, Fischer MJ, Anderson KE, et al.: PI4P and PI(4,5)P2 are essential but independent lipid determinants of membrane identity. Science. 2012; 337(6095): 727–30. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGhosh R, de Campos MK, Huang J, et al.: Sec14-nodulin proteins and the patterning of phosphoinositide landmarks for developmental control of membrane morphogenesis. Mol Biol Cell. 2015; 26(9): 1764–81. 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"id": "13159",
"date": "31 Mar 2016",
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"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
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"id": "13160",
"date": "31 Mar 2016",
"name": "Vytas A Bankaitis",
"expertise": [],
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"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
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"id": "13161",
"date": "31 Mar 2016",
"name": "Volker Haucke",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
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"id": "13162",
"date": "31 Mar 2016",
"name": "Peter Mayinger",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
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] | 1
|
https://f1000research.com/articles/5-422
|
https://f1000research.com/articles/5-421/v1
|
31 Mar 16
|
{
"type": "Review",
"title": "Utilization and control of ecological interactions in polymicrobial infections and community-based microbial cell factories",
"authors": [
"Vinoth Wigneswaran",
"Cristina Isabel Amador",
"Lotte Jelsbak",
"Claus Sternberg",
"Lars Jelsbak",
"Vinoth Wigneswaran",
"Cristina Isabel Amador",
"Lotte Jelsbak",
"Claus Sternberg"
],
"abstract": "Microbial activities are most often shaped by interactions between co-existing microbes within mixed-species communities. Dissection of the molecular mechanisms of species interactions within communities is a central issue in microbial ecology, and our ability to engineer and control microbial communities depends, to a large extent, on our knowledge of these interactions. This review highlights the recent advances regarding molecular characterization of microbe-microbe interactions that modulate community structure, activity, and stability, and aims to illustrate how these findings have helped us reach an engineering-level understanding of microbial communities in relation to both human health and industrial biotechnology.",
"keywords": [
"microbial cell factories",
"microbial communities",
"microbe-microbe interactions"
],
"content": "Introduction\n\nMost microbial species are embedded within ecological communities containing many species that interact with one another and their physical environment. Virtually all important microbial activities are shaped by interactions between co-existing microbes within mixed-species communities. These interactions (e.g. in the form of physical, chemical, and genetic signals such as cell-cell contact1, metabolite exchange2, and horizontal gene transfer3) control synergistic, antagonistic, or neutral relationships among the interacting partners and are thus responsible for overall community properties such as species composition and function. In addition, microbial interactions may be dynamic and dependent on environmental context, and microbial communities can have different spatial interactive distributions ranging from metabolic interactions between unassociated planktonic cells in the ocean4 and long-distance electrical signaling within microbial communities5,6 to local cell-cell interactions occurring within surface-attached biofilms7. Furthermore, a series of recent studies have shown that microbe-microbe and microbe-host interactions can also be mediated by small, air-transmittable molecules8–10.\n\nGiven this complexity among microbial interactive processes, it remains a central challenge to improve our understanding of the molecular mechanisms underlying these interaction processes, their combinatorial effects, and how these interactions ultimately modulate the diversity, behaviors, and activities of the individual species within complex microbial communities.\n\nDissection of the molecular mechanisms of species interactions within communities is an important issue in microbial ecology. Recently, studies of a diverse range of microbial ecosystems have provided new insight into this area by combining omics methods with classical microbiology cultivation techniques. These systems include multispecies microbial communities formed during the production of fermented food11,12, microbial communities in acid mine drainages and other polluted habitats13, the commensal microbiota of corals14, as well as several other ecosystems. In this review, we focus primarily on studies of microbe-microbe interactions in host-associated microbial communities and with respect to the engineering of mixed-species microbial cell factories. We use these two examples to broadly illustrate and discuss how knowledge of species interactions is of importance in relation to our ability to control and utilize microbial systems.\n\n\nAdvances in studies of pathogen-microbiota interactions\n\nIn relation to infectious diseases, it is becoming increasingly clear that interactions between bacterial pathogens and other microbial species present at the infection site (for example, co-infecting pathogens or commensal bacteria) can influence disease phenotype or clinical outcome. One example of the importance of such pathogen-microbiota interactions is the well-established role of the intestinal commensal microbiota regarding the prevention of colonization of invading microorganisms including bacterial pathogens in a process known as colonization resistance15. The ability to characterize microbial community structures using 16S ribosomal RNA (rRNA)-based phylogenies or full metagenomic sequencing has now resulted in a much deeper understanding of the interplay between the human microbiome and bacterial pathogens with respect to infectious disease development. For example, studies of the microbial communities in certain chronic infections such as cystic fibrosis (CF) have revealed clear correlations between loss of community diversity and disease progression16–18. CF patients are predisposed to airway infections from a number of bacterial opportunistic pathogens, among which Pseudomonas aeruginosa, Staphylococcus aureus, Haemophilus influenzae, and Burkholderia cepacia complex (BCC) have been directly associated with CF lung disease19–21. However, recent studies based on culture-independent methods have demonstrated the presence of many additional bacterial species previously undetected by culture and have revealed a greater microbial diversity in CF airways than previously recognized20. CF airways clearly represent a complex and diverse polymicrobial ecosystem, and, as the disease symptoms become more severe, the CF lung microbiota becomes dominated by the primary pathogen (which most often is the opportunistic pathogen P. aeruginosa)16–18. These results are suggestive of a wider role of the respiratory microbiota and highlight the importance of interactions between the primary pathogen and the microbiota in relation to disease progression.\n\nThere are several recent and parallel examples of interactions between the commensal microbiota and possible pathogens which are responsible for limiting colonization and infections by bacterial pathogens such as Staphylococcus aureus in the nasal cavity22 and enteropathogenic Escherichia coli23 and Vibrio cholera24 in the gut. Despite these exciting observations, we are still far from being able to efficiently harness the protective capability of the commensal microbiota against pathogens. Nevertheless, these and related findings clearly point toward chemical and/or biological interference with microbial interaction networks within diseased hosts as alternative treatment strategies against pathogens.\n\nThe findings mentioned above highlight the importance of research aimed at systematic mapping of interspecies interactions regarding different types of bacterial infections in combination with the identification and molecular characterization of these interactions. In other words, it is now critical to move beyond correlative research and studies focused on generating microbiome “parts” lists and to instead begin to focus on causality and function at the molecular level. Indeed, a few pioneering studies have recently illustrated these points very clearly, and there are now clear examples of identified microbe-microbe interactions mediated by bacterial metabolites and gene products that function either to limit pathogen colonization22–25 or to potentiate pathogen expansion or virulence26–28. Although it is obviously challenging to identify and characterize microbial interspecies interactions in infected hosts, interdisciplinary approaches that combine classical microbiological in vitro cultivation techniques with advancing technologies such as three-dimensional (3D) printing29, imaging mass spectrometry28,30, and development of realistic and controllable in vitro model systems31 now make it possible to begin systematically teasing apart the interactions among cultivated key community members and to determine how these interactions modify pathogen behaviors.\n\n\nEngineering synthetic multispecies communities for bioproduction purposes\n\nIn nature, microbes form interacting mixed-species communities to accomplish complex chemical conversions through division of labor among the individual organisms. We have successfully harnessed the power of such natural microbial communities in food and other industries for decades32,33, and this has logically led to the emerging concept of community-based cell factories in which synthetic microbial communities are rationally designed and engineered to produce valuable chemicals. Recent studies have indeed demonstrated the potential value of such engineered mixed-species communities as production platforms. In one recent example, a synthetic mixed-species community of E. coli and Saccharomyces cerevisiae was engineered to produce complex pharmaceutical molecules including precursors of the anti-cancer drug paclitaxel34. By engineering the two organisms to host specific portions of the biosynthetic pathways, it was possible to construct a co-culture system in which an intermediate metabolite was first produced by E. coli and then further functionalized by S. cerevisiae to give the final product. This study is the first demonstration of the segregation of long and complex biosynthetic pathways into separate organisms each carrying portions of the pathway, which not only enables parallel optimization of the independent pathway modules but also makes it possible to use the best match between particular pathway modules and specific hosts. In another recent study, a fungal-bacterial community was engineered to convert lignocellulosic biomass into biofuels35. Here, the community contained the fungus Trichoderma reesei, which can hydrolyze lignocellulosic biomass into soluble saccharides, and the bacterium E. coli, which can metabolize these saccharides into isopropanol. In this example, one species provided the carbon source for the second species, which in turn was able to produce the final product on its own.\n\nIt is clear from these and other studies that successful engineering of community-based microbial cell factories relies greatly on our molecular understanding of microbe-microbe interactions and how these influence community assembly, stability, and activity.\n\n\nControlling the stability of community-based cell factories\n\nUnlike their natural counterparts, synthetic communities are often unstable. For example, different growth rates among the constituent organisms and secretion of toxic metabolites during growth can influence the stability of the community and will often lead to single-species domination or extinction of the community36. This general instability of synthetic communities limits their translation into real-world applications in industrial biotechnology, and achieving long-term maintenance of synthetic communities is a significant challenge that must be solved.\n\nAlthough we still have an incomplete understanding of the multiple competitive and cooperative interactions that control microbial community assembly and activity, many different strategies have been successfully employed to increase the stability of synthetic communities. In the first example described above, Zhou et al.34 used knowledge of the metabolic capacities of the constituent organisms to construct a specific environment that favored community stability: E. coli can use xylose as a carbon source, but when grown on this carbon source, E. coli excretes acetate, which is inhibitory to its own growth. On the other hand, S. cerevisiae can use acetate as a carbon source but not xylose. The use of a specific carbon source (in this case xylose) thus created a mutualistic interaction between the two organisms, which in turn stabilized the community.\n\nIn the other mixed-species community (containing T. reesei and E. coli) described in the previous section, Minty et al.35 took advantage of the particular co-operator/cheater relationship that existed in their engineered fungal-bacterial community and used ecological theory to establish specific conditions (in terms of population sizes) that could stabilize this interaction.\n\nHowever, community-stabilizing culture conditions—similar to the ones described in these two examples—may be difficult to design and construct for other synthetic communities. Most likely, it is reasonable to expect that alternative approaches will be required in most other situations. These alternative methods may include the construction of synthetic interactions by genetic engineering of the participating species to enforce their interaction. For example, genetic construction of pairs of auxotrophs that cross-feed and support the growth of one another when co-cultured has been shown to be an effective approach for improving community maintenance37,38. Other strategies have relied on programming specific mutualistic interactions by means of synthetic intercellular signaling circuits39–41. However, such synthetic interactions are of course also targets of evolutionary process and the long-term stability of these genetic modifications is currently not well understood.\n\n\nForm and function in microbial communities\n\nA fundamental principle in biology is that structure (form) and function are inseparable elements. For example, spatial separation of cells that are then subsequently linked together through controlled proximity is an organizational theme frequently observed at all levels in biology42. In relation to natural microbial communities, it is well established that spatial organization of the component species has significant impact on the function and activity of the systems43–45. Interestingly, such structure/function considerations are often not included in the design of synthetic microbial communities or considered in relation to human infections where the spatial and dynamic distribution of bacteria (including pathogens) and their activities within the human host have been found to be more complex than previously realized46–48.\n\nRegarding the construction of community-based cell factories, it is certainly a possibility that alternative community-stabilizing methods should build on knowledge of structure/function relationships. Indeed, it has been shown that spatial separation and artificial positioning of cells within synthetic microbial communities improve community function and stability36. Recent advances in fluidics-based bacterial cultivation chambers49, 3D printing methods29, and other micro-patterning techniques50 represent exciting areas in this direction that may advance our ability to efficiently design and control the spatial organization of cells within microbial communities.\n\n\nSummary\n\nAs either members of infection communities within colonized hosts or part of synthetic communities for sustainable bioproduction, both pathogenic and industrially relevant bacteria are placed in polymicrobial environments in which interactions and spatial position modulate their activity. In both areas, there is a clear need to move beyond the current sequenced-based technologies often used to characterize complex microbial communities and to begin to identify and characterize the function of microbial interactions and the role of spatial organization. The examples shown here illustrate that such knowledge can provide new strategies for better control of bacterial infection and optimized utilization of community-based microbial cell factories. Finally, we emphasize that although our discussion is focused on examples of multispecies bacterial systems in relation to disease and biosynthesis, we believe these are indeed representative examples of an awakening field within microbial ecology focused on understanding species interactions in many types of polymicrobial ecosystems.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe Villum Foundation provided funding for this study to Lars Jelsbak (Grant number VKR023113). Lars Jelsbak acknowledges additional funding from the Novo Nordisk Foundation and the Lundbeck Foundation.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nDubey GP, Ben-Yehuda S: Intercellular nanotubes mediate bacterial communication. Cell. 2011; 144(4): 590–600. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMøller S, Sternberg C, Andersen JB, et al.: In situ gene expression in mixed-culture biofilms: evidence of metabolic interactions between community members. Appl Environ Microbiol. 1998; 64(2): 721–732. 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PubMed Abstract | Publisher Full Text\n\nBohnhoff M, Miller CP: Enhanced susceptibility to Salmonella infection in streptomycin-treated mice. J Infect Dis. 1962; 111(2): 117–127. PubMed Abstract | Publisher Full Text\n\nZhao J, Schloss PD, Kalikin LM, et al.: Decade-long bacterial community dynamics in cystic fibrosis airways. Proc Natl Acad Sci U S A. 2012; 109(15): 5809–5814. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCox MJ, Allgaier M, Taylor B, et al.: Airway microbiota and pathogen abundance in age-stratified cystic fibrosis patients. PLoS One. 2010; 5(6): e11044. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBlainey PC, Milla CE, Cornfield DN, et al.: Quantitative analysis of the human airway microbial ecology reveals a pervasive signature for cystic fibrosis. Sci Transl Med. 2012; 4(153): 153ra130. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nHoiby N: Epidemiological investigations of the respiratory tract bacteriology in patients with cystic fibrosis. Acta Pathol Microbiol Scand B Microbiol Immunol. 1974; 82(4): 541–550. PubMed Abstract | Publisher Full Text\n\nHarrison F: Microbial ecology of the cystic fibrosis lung. Microbiology. 2007; 153(Pt 4): 917–923. PubMed Abstract | Publisher Full Text\n\nYang L, Jelsbak L, Molin S: Microbial ecology and adaptation in cystic fibrosis airways. Environ Microbiol. 2011; 13(7): 1682–1689. PubMed Abstract | Publisher Full Text\n\nIwase T, Uehara Y, Shinji H, et al.: Staphylococcus epidermidis Esp inhibits Staphylococcus aureus biofilm formation and nasal colonization. Nature. 2010; 465(7296): 346–349. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nFukuda S, Toh H, Hase K, et al.: Bifidobacteria can protect from enteropathogenic infection through production of acetate. Nature. 2011; 469(7331): 543–547. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHsiao A, Ahmed AM, Subramanian S, et al.: Members of the human gut microbiota involved in recovery from Vibrio cholerae infection. Nature. 2014; 515(7527): 423–426. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nBuffie CG, Bucci V, Stein RR, et al.: Precision microbiome reconstitution restores bile acid mediated resistance to Clostridium difficile. Nature. 2015; 517(7533): 205–208. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nStacy A, Everett J, Jorth P, et al.: Bacterial fight-and-flight responses enhance virulence in a polymicrobial infection. Proc Natl Acad Sci U S A. 2014; 111(21): 7819–7824. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nKorgaonkar A, Trivedi U, Rumbaugh KP, et al.: Community surveillance enhances Pseudomonas aeruginosa virulence during polymicrobial infection. Proc Natl Acad Sci U S A. 2013; 110(3): 1059–1064. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFrydenlund Michelsen C, Hossein Khademi SM, Krogh Johansen H, et al.: Evolution of metabolic divergence in Pseudomonas aeruginosa during long-term infection facilitates a proto-cooperative interspecies interaction. ISME J. 2015. PubMed Abstract | Publisher Full Text\n\nConnell JL, Kim J, Shear JB, et al.: Real-time monitoring of quorum sensing in 3D-printed bacterial aggregates using scanning electrochemical microscopy. Proc Natl Acad Sci U S A. 2014; 111(51): 18255–18260. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMoree WJ, Phelan VV, Wu CH, et al.: Interkingdom metabolic transformations captured by microbial imaging mass spectrometry. Proc Natl Acad Sci U S A. 2012; 109(34): 13811–13816. 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PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nBrenner K, Arnold FH: Self-organization, layered structure, and aggregation enhance persistence of a synthetic biofilm consortium. PLoS One. 2011; 6(2): e16791. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBrenner K, Karig DK, Weiss R, et al.: Engineered bidirectional communication mediates a consensus in a microbial biofilm consortium. Proc Natl Acad Sci U S A. 2007; 104(44): 17300–17304. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHong SH, Hegde M, Kim J, et al.: Synthetic quorum-sensing circuit to control consortial biofilm formation and dispersal in a microfluidic device. Nat Commun. 2012; 3: 613. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGijzen HJ, Barugahare M: Contribution of anaerobic protozoa and methanogens to hindgut metabolic activities of the American cockroach, Periplaneta americana. Appl Environ Microbiol. 1992; 58(8): 2565–2570. 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}
|
[
{
"id": "13156",
"date": "31 Mar 2016",
"name": "Juan Luis Ramos",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13157",
"date": "31 Mar 2016",
"name": "Willem M de Vos",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13158",
"date": "31 Mar 2016",
"name": "Robert J Palmer",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-421
|
https://f1000research.com/articles/5-420/v1
|
31 Mar 16
|
{
"type": "Review",
"title": "Recent advances in central cardiovascular control: sex, ROS, gas and inflammation",
"authors": [
"Pauline M. Smith",
"Alastair V. Ferguson",
"Pauline M. Smith"
],
"abstract": "The central nervous system (CNS) in concert with the heart and vasculature is essential to maintaining cardiovascular (CV) homeostasis. In recent years, our understanding of CNS control of blood pressure regulation (and dysregulation leading to hypertension) has evolved substantially to include (i) the actions of signaling molecules that are not classically viewed as CV signaling molecules, some of which exert effects at CNS targets in a non-traditional manner, and (ii) CNS locations not traditionally viewed as central autonomic cardiovascular centers. This review summarizes recent work implicating immune signals and reproductive hormones, as well as gasotransmitters and reactive oxygen species in the pathogenesis of hypertension at traditional CV control centers. Additionally, recent work implicating non-conventional CNS structures in CV regulation is discussed.",
"keywords": [
"hypertension",
"hydrogen sulfide",
"reactive oxygen species",
"reproductive hormones",
"cardiovascular homeostasis"
],
"content": "Introduction\n\nAccording to the World Health Organization (WHO), cardiovascular (CV) disease accounts for approximately 17 million deaths a year worldwide1, of which more than half (9.4 million) are attributable to complications of hypertension2. In 2008, a staggering 40% of adults over the age of 25 had been diagnosed with hypertension3.\n\nThe central nervous system (CNS) is essential to maintaining CV homeostasis. Traditional central autonomic CV control centers include the nucleus tractus solitarius (NTS), the rostral ventral lateral medulla (RVLM), and the caudal ventral lateral medulla in the brainstem; the parabrachial nucleus in the pons; and the paraventricular nucleus (PVN) in the hypothalamus. In addition, the area postrema (AP) in the hindbrain, and the organum vasculosum of the lamina terminalis (OVLT) and subfornical organ (SFO) in the forebrain, are sensory circumventricular organs (CVOs) characterized by the presence of a wide variety of receptors and the lack of the normal blood-brain barrier, which have also been implicated in central CV regulation. The renin-angiotensin aldosterone system (RAAS) has also been extensively implicated as a critical signaling system, components of which play central roles both as circulating hormones and as CNS neurotransmitters in the regulation of blood pressure (BP). There is growing evidence that the development and progression of hypertension involves dysregulation of the sympathetic nervous system (SNS) (SNS over-activity) (for review, see 4–6) and activation of the RAAS7,8.\n\nOver the past 20 years, our understanding of CNS control of BP regulation (and dysregulation leading to hypertension) has evolved substantially. This review will summarize some of these paradigm shifts, focussing primarily on signaling molecules that either (i) are not classically viewed as CV signaling molecules (i.e. immune signals and reproductive hormones) or (ii) exert effects at CNS targets in a non-traditional manner, acting via membrane receptor-independent signaling mechanisms (i.e. gasotransmitters and reactive oxygen species [ROS]), all of which have been shown to have profound effects on the central control of BP. CNS structures, not conventionally thought of as CV control centers but that more recently have been shown to influence CV regulation, are also discussed.\n\n\nInflammation and immune regulators as modulators of cardiovascular regulation and contributors to hypertension\n\nAlthough it had been speculated decades ago that there was a relationship between the immune system and hypertension9, the demonstration of systemic markers of inflammation in patients with essential hypertension in the early 2000s10,11 was a catalyst for renewed interest in the relationship between hypertension and the immune system. Emerging evidence suggests that both the innate and acquired immune systems are activated in hypertension, as inflammations in the kidney, vasculature (arteries), and CNS have all been shown to be involved in the pathogenesis of hypertension.\n\nAs an immediate first-line defence mechanism to infections or tissue injury, the innate immune system initiates a generalized inflammatory response involving dendritic cells, macrophages, natural killer (NK) T cells, and Toll-like receptors (TLRs), all of which have been shown to be activated in hypertension.\n\nDendritic cell activation has been shown to promote hypertension by stimulating T-cell proliferation which infiltrates both the kidney and arterial walls12,13. Similarly, macrophage infiltration of the kidney and arteries has been documented in experimental models of hypertension, and a decrease in macrophage infiltration is associated with an improvement of hypertension in these models of hypertension14–17. Recently, NK T-cell activation and TLRs (TLR4, in particular) have been suggested to play a role in hypertension-related inflammation18,19.\n\nThe adaptive immune system responds to specific antigens and involves antigen presentation, lymphocyte activation, and antibody production. T cells have been shown to play a role in angiotensin II (ANG II)-induced hypertension20 whereas endogenously produced ANG II increases T-cell activation21. Pro-inflammatory T-cell activation and the subsequent release of pro-inflammatory cytokines are associated with hypertension22–24 whereas inhibition or genetic ablation of the B7/CD28 T cell costimulatory pathway has been shown to prevent experimental hypertension12. RAG-1−/− mice and SCID mice, which lack both T and B cells, exhibited a blunted hypertensive response to ANG II infusion20,25, a response that returned when T cells were transferred into RAG-1−/− mice20. T cell-produced cytokines (such as tumor necrosis factor alpha, or TNFα) and many of the interleukins (such as IL-6) have been shown to play a role in hypertension. TNFα antagonism20,26 or genetic knockout of IL-627 has been shown to blunt ANG II-induced hypertension. The presence of agonist antibodies to ANG II receptors has been identified in a number of conditions that are characterized by elevated BP, such as preeclampsia28,29, refractory hypertension30,31, and malignant hypertension32.\n\nMany studies have suggested that arterial inflammation within specific CNS locations is involved in the pathogenesis of hypertension. A role for inflammation in the NTS, a pivotal region for regulating arterial pressure baroreceptor reflex sensitivity, has been suggested in the development of hypertension, as studies have shown not only leukocyte accumulation within the NTS microvasculature33 but also changes in gene expression of a variety of inflammatory molecules34,35 and neurotrophic factors36 in the NTS of spontaneously hypertensive rats (SHRs).\n\nIn addition, many of the cytokines, released as a consequence of immune system activation, have been shown to directly influence cardiovascular control centers in the CNS. Microinjection of IL-6 into the NTS attenuates baroreceptor function37 and leads to speculation that abnormal gene expression of IL-6 in the NTS may be associated with hypertension. Augmentation of IL-1β, IL-6, or TNF-α expression and increased ROS observed in the RVLM following chronic intraperitoneal lipopolysaccharide administration have been suggested to be contributing factors to neurogenic hypertension induced by systemic inflammation38.\n\nEarly studies identified the anteroventral third ventricle (AV3V), a broad-based region located along the wall of the third ventricle which includes the OVLT, as a critical CNS structure in the pathogenesis of hypertension39. A more recent study not only confirmed that lesions of the AV3V region attenuate ANG II-induced hypertension but also implicated immune system involvement as AV3V lesions eliminated circulating T-cell activation and vascular infiltration normally observed in response to ANG II administration40. IL-1β has been shown to influence the excitability of SFO neurons41, and recent studies have demonstrated that microinjection of IL-1β (and of TNFα) into SFO increases BP and renal sympathetic nerve activity (SNA)42.\n\nThe PVN, a hypothalamic autonomic control center with well-documented roles in CV regulation, has been implicated as a CNS structure in which immune signals may act to cause hypertension. Chronic ANG II infusion causes the expression of pro-inflammatory cytokines and markers of oxidative stress in the PVN, effects blocked by central administration of TNFα blocker26. Angiotensin-converting enzyme 2 (ACE2) overexpression in the PVN has also been shown to attenuate both ANG II-induced hypertension and expression of the pro-inflammatory cytokines TNFα, IL-1β, and IL-6 in the PVN43. Blockade of nuclear factor-kappa-B (NFκB), a prominent transcription factor that governs inflammatory responses, in the PVN of rats resulted in decreased BP, pro-inflammatory cytokines, and ROS, as well as upregulation of key protective anti-hypertensive RAAS components, suggesting an important role for NFκB in PVN in the hypertensive response44. Finally, rats fed a high-salt diet demonstrated increased expression of IL-1β and decreased expression of the anti-inflammatory cytokine IL-10, in the PVN. These expression levels were augmented by stimulation of ROS production within the PVN45.\n\n\nReproductive hormones and cardiovascular regulation\n\nThe interest in the role of sex hormones in hypertension has been driven by a number of observations regarding sexual dimorphism in BP regulation in humans and animals. Epidemiological findings that prior to menopause the prevalence of essential hypertension is lower in women than in men of the same age46 and that young women have lower resting SNA than men47, differences that disappear after menopause, suggest that estradiol is important in BP regulation and, in fact, may protect against hypertension. Findings that estradiol administration attenuates increases in BP normally exhibited by intact males and ovariectomized females, and prevents development of hypertension in experimental models of hypertension48,49, suggest a role for estradiol in the regulation of BP.\n\nStudies in humans and animals suggest that exogenous testosterone may also play a crucial role in BP regulation. In humans, low testosterone levels have been correlated with higher BP50,51 whereas testosterone replacement has been shown to cause significant reductions in BP52,53, suggesting a role for testosterone in BP regulation. Moreover, in experimental models of hypertension high BP develops more rapidly and becomes more severe in the male than in the female, effects which were shown to be androgen-dependent48,54,55. Further support for a role of testosterone in the etiology of hypertension is derived from studies showing that castration prevents the development of hypertension in SHR rats56.\n\nEvidence for a role for central actions of estradiol on BP regulation is derived from a variety of sources. Firstly, many of the CNS sites with well-documented roles in CV regulation have been shown to possess estrogen receptors (ERα and ERβ)57–61. Moreover, intracerebroventicular (icv) administration of estradiol in ovariectomized mice and in male mice attenuated the increase in BP normally elicited by ANG II62. In rats, aldosterone/salt-induced hypertension is exhibited by intact males and ovariectomized females, effects attenuated by activation of central ER receptors. Central ER blockade63 or icv injections of small interfering RNA-ERα (siRNA-ERα) or siRNA-ERβ64, on the other hand, augmented aldosterone-induced hypertension in intact females.\n\nFurther to these findings, estradiol has been shown to act via ERα or ERβ (or both) at specific brain regions in both males and females to influence sympathetic outflow and baroreflex function. The AP and SFO predominantly express ERα57–62, and estradiol has been shown to decrease the activity of AP65 and SFO neurons66, and inhibits ANG II activation of AP67 and SFO neurons66, whereas genetic knockdown of ERα in the SFO enhances ANG II-induced hypertension in female mice68.\n\nEstrogen actions at ERβ in PVN inhibit hypertensive effects of glutamate activation69. In the RVLM, estradiol actions at ERβ receptors have been shown to cause decreases in BP in normotensive rats70 and to attenuate aldosterone-induced increases in SNA and BP64 whereas ERβ knockdown in RVLM or PVN results in the augmentation of aldosterone-induced increases in SNA and BP64, effects that are not seen in intact females64.\n\nRelaxin, a member of the insulin family best known for its role in pregnancy, has also been shown to influence BP. Early studies revealed that chronic intravenous (iv) administration of relaxin elicited a decrease in BP in SHRs71. Relaxin binding sites and relaxin receptors have been shown to be widely distributed throughout the brain, including the SFO, NTS, and PVN72, suggesting that relaxin may be involved in the central control of BP. Hypertensive effects of central administration of relaxin into the dorsal third ventricle are totally abolished by lesions of the SFO73, identifying this CVO as one central target mediating these cardiovascular effects. A recent study demonstrating that acute microinjection of relaxin-2 into the PVN increased sympathetic outflow and BP in SHR, whereas chronic PVN administration caused a profound increase in BP in normotensive rats74, supports the conclusion that there are multiple central targets for this reproductive hormone/neurotransmitter. Moreover, this same study revealed that neutralization of endogenous relaxin reduced BP in SHR but had no significant effect in WKY74, suggesting a role for relaxin in the pathogenesis of hypertension.\n\nAnother reproductive peptide that warrants further investigation into its potential contribution to the pathogenesis of hypertension is prolactin, a hormone best known for its involvement in lactation and reproduction. Very few studies have investigated the role of prolactin in the central control of CV regulation despite epidemiological evidence suggesting correlations between circulating prolactin levels and increased BP. Plasma prolactin has been shown to be elevated in patients with essential hypertension75 and preeclampsia76,77. Furthermore, higher plasma prolactin levels have been shown to be associated with increased risk of hypertension in menopausal78 and post-menopausal79 women and in preeclampsia54. Prolactin receptors are widely distributed throughout the body80 and brain81. mRNA for the prolactin receptor has been reported in the PVN81,82, and we have identified the presence of the prolactin receptor at levels similar to the AT1 receptor in the SFO83. However, to our knowledge, studies investigating the CV consequences of central administration of prolactin (icv or microinjection into discrete brain nuclei) on BP, or the effects of prolactin on neuronal excitability in central CV control centers, are lacking.\n\n\nGasotransmitters and cardiovascular regulation: hydrogen sulfide\n\nGasotransmitters are endogenously produced membrane permeable gas molecules which act at specific, targeted cells via membrane receptor-independent signaling mechanisms to exert well-defined physiological effects. The action(s) of nitric oxide (NO) and carbon monoxide (CO) at peripheral tissues and in the CNS to influence cardiovascular regulation are well documented84,85. More recently, a third gasotransmitter, hydrogen sulfide (H2S), an environmental air pollutant with well-known deleterious health effects, has been identified and suggested to play a role in the pathogenesis of hypertension. H2S is endogenously produced from catalysis of L-cysteine by using four enzymes: cystathionine β-synthase (CBS), cystathionine γ-lysase (CSE), or 3-mercaptopyruvate sulfur transferase (3MST) in tandem with cysteine aminotransferase (CAT). CBS is highly expressed in the CNS where it produces H2S from L-cysteine86, whereas CSE is the predominant enzyme expressed in the myocardium and vasculature smooth muscle cells87. Though predominantly found in the mitochondria where they work in tandem to produce H2S, 3MST and CAT are also expressed in the brain and vascular endothelium88. In addition, H2S can be produced in red blood cells by the conversion of polysulfides which are obtained from dietary sources89.\n\nEvidence for a role of H2S in the pathogenesis of hypertension is suggested by the observation that plasma H2S concentrations are lower in patients with grade 2 or grade 3 hypertension, portal hypertension, and pulmonary hypertension90–92 and in preeclampsia where plasma H2S levels and placental CBS mRNA expression are decreased93,94.\n\nH2S has been shown to be endogenously produced in peripheral vascular tissues and has been demonstrated to be a potent vasodilator, causing vasorelaxation in mesenteric arteries95, aortic rings96,97, the ductus arteriosis96, and pulmonary arteries98 via actions on vascular smooth muscle cells. Unlike its gasotransmitter counterparts, NO and CO, vascular smooth muscle relaxation occurs independently of cGMP pathway activation. Activations of Ca2+-activated potassium channels (BKCa)99, ATP-sensitive potassium channels (KATP)100, Kv7 voltage-gated potassium channels97, and cytochrome P-450 2C (Cyp2C)99 have all been implicated as mechanisms of the H2S vasorelaxation.\n\nA bolus iv injection of H2S elicited an immediate depressor response in normotensive rats100 whereas chronic intraperitoneal administration of H2S decreases BP in hypertensive rats101–104. These findings, along with the fact that mice lacking CSE exhibit hypertension and reduced endothelium-dependent vasorelaxation105, provide evidence of a direct role for H2S in BP regulation.\n\nA role for H2S in the central control of BP stems from studies demonstrating that icv administration of H2S has been shown to dose-dependently decrease BP, effects which are followed by potent long-lasting hypertension actions attributed to modulation of H2S on KATP channels and α adrenergic stimulation, respectively106. Furthermore, microinjection of H2S into discrete brain nuclei known for their involvement in CV regulation has also been shown to affect BP. H2S administration into the RVLM elicits decreases in BP, effects again mediated by KATP channels107, whereas similar microinjections into the PVN108 and SFO109 have been shown to dose-dependently increase BP. Moreover, H2S has been shown to influence the excitability of neurons in the NTS110, PVN111, and SFO109, CNS areas involved in CV regulation.\n\n\nReactive oxygen species and cardiovascular control\n\nWhen produced at appropriate concentrations, ROS have been implicated in the regulation of many critical physiological processes, including cell signaling, maintenance of appropriate vascular tone, inflammation, and immune responses. ROS overproduction, on the other hand, is a feature common to a number of pathological conditions, including hypertension.\n\nA role for ROS in hypertension is suggested in humans as a positive correlation between BP and biomarkers of oxidative stress in patients with essential hypertension has been reported112,113. Furthermore, mice lacking nicotinamide adenine dinucleotide phosphate (NADPH) oxidases, key enzymes in the production of ROS, are protected against experimental hypertension114, whereas overexpression potentiates ANG II-induced hypertension115.\n\nROS production in specific CNS cardiovascular control centers, including both brain stem (NTS, RVLM) and hypothalamic (PVN) nuclei, and within the CVOs (SFO) has been shown to play a role in neurogenic hypertension116–118. Superoxide dismutase (SOD), an enzyme that metabolizes superoxide, overexpression in the brain abolished the hypertensive response normally observed in response to icv ANG II administration119, whereas specific SOD3 deletion in the SFO increased baseline BP and potentiated ANG II-induced increases in BP120. Interestingly, this same study showed that ROS in the SFO leads to infiltration by activated lymphocytes in the peripheral vasculature120, linking oxidative stress in the CNS with immune activation in the periphery, which in concert would serve to intensify hypertension.\n\nA high-salt diet increases NADPH oxidase (NOX-2 and NOX-4) expression in the PVN, whereas microinjection of amino-triazole (ATZ), a catalase inhibitor which increases ROS, into the PVN augments renovascular hypertension as well as increasing BP in normal rats45.\n\n\nA role for ‘other’ central nervous system structures in the central control of blood pressure\n\nThis review has focussed on actions of non-traditional CV signaling molecules at CNS structures with well-documented roles in CV regulation. Another emerging area that warrants mention is the role of CNS regions not classically viewed as CV control centers that have been suggested to play a role in the pathogenesis of hypertension, secondarily or as a co-morbidity to other disease states. For example, the explosion of obesity research further to the discovery of leptin in the 1990s121 has highlighted the involvement of a number of CNS autonomic control centers not typically viewed as CV control centers, such as the arcuate nucleus and the anterior hypothalamus, in the pathogenesis of hypertension as a consequence of direct actions of metabolic signals in these areas (for review, see 122,123). Furthermore, many metabolic signals associated with obesity have been demonstrated to influence BP regulation via actions at the ‘classical’ CNS CV control centers. Further study of the actions of traditional CV signals (such as ANG II) within these non-traditional CV CNS centers may elucidate previously unknown roles of these regions in normal CV regulation.\n\n\nConclusions\n\nIn this brief review, we have highlighted some emerging new perspectives which over the past 20 years contributed new and important information to the evolution of our understanding of CNS mechanisms involved in central CV control. The areas we have chosen to discuss are far from an exhaustive list of what is new and interesting, but do emphasize that this is a continually developing area of research with an inherent complexity associated with the requirement for integration of diverse autonomic systems. This points us in the direction of understanding that we perhaps should not expect to consider either single brain areas or single signalling molecules as “cardiovascular” at the expense of also describing their roles in other systems. Such conclusions point us to the broader perspective that all of these brain areas, signaling molecules, and autonomic systems contribute to the complex homeostatic regulation which maintains our “milieu interior” in a state of optimal health.",
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PubMed Abstract | Publisher Full Text\n\nCarmichael CY, Wainford RD: Hypothalamic signaling mechanisms in hypertension. Curr Hypertens Rep. 2015; 17(5): 39. PubMed Abstract | Publisher Full Text | Free Full Text\n\nStump M, Mukohda M, Hu C, et al.: PPARγ Regulation in Hypertension and Metabolic Syndrome. Curr Hypertens Rep. 2015; 17(12): 89. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "12964",
"date": "31 Mar 2016",
"name": "Leo Renaud",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12965",
"date": "31 Mar 2016",
"name": "John Ciriello",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-420
|
https://f1000research.com/articles/5-419/v1
|
31 Mar 16
|
{
"type": "Review",
"title": "Technical advances in proteomics: new developments in data-independent acquisition",
"authors": [
"Alex Hu",
"William S. Noble",
"Alejandro Wolf-Yadlin",
"Alex Hu",
"William S. Noble"
],
"abstract": "The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low‑abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.",
"keywords": [
"proteomics",
"data-independent acquisition",
"mass spectrometry"
],
"content": "Introduction\n\nFor the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics has provided broad detection and relative quantification—through chemical or metabolic labeling—of thousands of proteins across a variety of biological samples using a data-dependent acquisition (DDA) strategy1–4. In recent years, alternative LC-MS/MS targeted acquisition strategies, such as multiple-reaction monitoring (MRM)5–7 and parallel reaction monitoring (PRM)8, have provided precise and reproducible absolute quantification of up to hundreds of proteins. The ultimate goal of proteomics is the development of acquisition strategies that have both the breadth of DDA and the precision of MRM/PRM to provide reproducible identification and quantification of every protein in any biological sample. Although no single acquisition strategy can yet achieve this goal, recent advances in hardware and software show that a recently resurfaced strategy9, data-independent acquisition (DIA), may provide a viable path to this goal10. Below is a discussion of DDA, MRM/PRM’s shortcomings, DIA’s circumvention of these shortcomings, current software to analyze DIA spectra, and efforts to further improve DIA analysis.\n\nAll LC-MS/MS methods discussed in this article are bottom-up proteomics: Proteins are enzymatically digested into peptides which then are separated using high-performance liquid chromatography (HPLC), ionized, isolated, fragmented, and detected in the mass spectrometer as they elute from the HPLC. HPLC delivers peptides into the mass spectrometer for a period of time (tens of minutes to a few hours, depending on the application), separating the peptides according to their physicochemical characteristics4,11, thus increasing sample coverage. In LC-MS/MS methods, three events occur in the mass spectrometer: (a) ionization: peptides elute into the mass spectrometer from the HPLC and are ionized; (b) MS1 scan: the abundance and mass-to-charge ratios (m/z) of all ions eluting at a given time are measured; and (c) MS2 scan: some or all detected ions are fragmented, and the abundances and m/z’s of the fragments are measured and recorded. Different LC-MS/MS methods vary in how ions are selected and measured in the MS2 scan. Figure 1 shows a cartoon schematic of how peptides are isolated, fragmented, and analyzed by a mass spectrometer working on DDA, MRM, PRM, or DIA modes.\n\nIn DDA, MRM, and PRM, single precursor ions are isolated, fragmented, and analyzed in an MS2 scan by the mass spectrometer. In DDA mode, the precursor ions are chosen by the instrument on the basis of abundance. In MRM and PRM, the precursor ions to be analyzed are fixed by the user. DIA is different form the methods above in that all precursor ions within a selected mass range are isolated, fragmented, and analyzed in a single MS2 scan. MS1, scan in which the peptide ions entering the mass spectrometer at a given time are identified; MS2, scan in which the fragments of all (or some) of the peptides that are in the mass spectrometer at a given time are identified.\n\nIn DDA, a subset of the most abundant ions reaching the mass spectrometer detector during an MS1 scan are individually isolated and fragmented in sequential MS2 scans (Figure 1 and Figure 2A), and each MS2 scan (Figure 2C) can be analyzed with a database search algorithm1,4. Currently, most instruments can perform a DDA cycle with one MS1 scan and 10 MS2 scans within 2 seconds. DDA typically yields thousands of protein identifications. Unfortunately, irreproducibility and imprecision are fundamental to DDA’s design; if too many peptide species co-elute and appear in a single MS1 scan, then DDA stochastically samples only the most abundant peptides and misses the rest. This approach diminishes reproducibility and prevents the measurement of low-abundance peptides9. Additionally, to survey as many peptides as possible, DDA deliberately samples each peptide species only once or twice, preventing precise absolute quantification that requires multiple measurements per peptide. DDA analysis has been used for a variety of studies, including the characterization of epidermal growth factor receptor (EGFR) signaling networks12,13, the characterization of the proteome on different mouse organs14,15, identification of protein interaction partners16–18, and description of the role of viral infections in modulating host proteomes18–21, which had been thoroughly covered in a special issue of the journal Proteomics22. In spite of its flaws, DDA’s flexibility, breadth of detection, and the simplicity of its setup and analysis, make DDA the preferred LC-MS/MS method among the wider scientific community. Additionally, DDA allows relative quantification of peptides between selected samples through a variety of chemical labeling schemes—e.g., isotopic (stable isotope labeling by amino acids in cell culture, or SILAC)23 or isobaric (isobaric tags for relative and absolute quantitation, or iTRAQ)24 labeling.\n\n(A) Data-dependent acquisition (DDA) acquires MS/MS scans with narrow isolation windows centered on peptide precursors detected in an MS scan over a wide range of masses: 400 to 1,600 mass-to-charge ratio (m/z) here. (B) Data-independent acquisition (DIA) acquires MS/MS scans with wide isolation windows that do not target any particular peptide precursor. Instead, the scans are arranged side-by-side to collectively cover a desired precursor m/z range (500 to 900 m/z here) comprehensively, and several precursors are fragmented together in a single MS2 event (four here: identified peptide M and peptides N, O, and P). (C) Fragment ion information for the peptide precursor VLENTEIGDSIFDK++ is present in a single MS/MS spectrum in a DDA analysis, (D) but it can be extracted over time from DIA data and used for quantification owing to the repetitive MS/MS sampling cycle of DIA. Adapted with permission from Egertson et al.46.\n\nAlternatively, the targeted methods MRM and PRM avoid the imprecision and irreproducibility of DDA by focusing MS2 scans on only a small set of predetermined and previously identified peptides. Instead of selecting the top n precursors in an MS1 scan for further fragmentation in MS2 scans, these methods select only precursors and fragments with the m/z and elution time that match a pre-specified peptide of interest. The knowledge of a peptide’s elution time, MS1 m/z value, and robustly detectable fragments is determined prior to the MRM/PRM experiments by previous DDA identification or MS/MS measurement of its synthetic version in a simplified background or both. In MRM, for each MS1 scan, a subset of fragment ions is measured in the subsequent MS2 scan25, whereas in PRM, all of the fragment ions are measured8. In both, the same precursors are selected and fragmented multiple times to acquire more precise quantification of fewer peptides, compared with DDA. MRM was developed first and has been shown to robustly quantify tens of blood plasma biomarkers of low abundance across laboratories toward clinical use6 and tens of low-abundance transcription factors and kinases in human cells7. Currently, the Clinical Proteomics Tumor Analysis Consortium (CPTAC)26 database hosts a collection of 679 MRM assays for human proteins. PRM, which succeeded MRM, outperforms it in terms of throughput and absolute quantification thanks to the use of high-resolution spectrometers capable of parallel fragment analysis8,27. PRM is still evolving; however, it has already been used successfully to address difficult proteomics problems in human health, such as the role of low-abundance polyubiquitin chains28 in Parkinson’s disease29, and in plant biology to monitor the degradation of low-abundance peptides in Arabidopsis thaliana30.\n\nDIA is like MRM/PRM in that it repeatedly samples the same peptides for more precise quantification, but it differs from them and DDA by dispensing with the isolation of individual peptide species and instead repeatedly selecting mixtures of peptide species within large, pre-specified mass ranges (Figure 1 and Figure 2B) for MS2 scans. DIA is therefore guaranteed to sample all peptides within the selected mass ranges, allowing for the identification of all sufficiently abundant peptides within them if the resulting spectra are properly interpreted10.\n\nProper interpretation of DIA data is currently problematic because the complex MS2 scans contain mixtures of peptides and therefore are more difficult to analyze. Fortunately, recent developments in bioinformatics software have adequately overcome this DIA issue, so that DIA now closely matches DDA in the number of peptide identifications while still allowing precise quantification of most of them. Quantification relies on comparing DIA spectra to sets of annotated and refined peptide-MS2 spectrum matches from DDA experiments (or the same DIA experiment in DIA-Umpire’s algorithm) called spectral libraries that show accurate, empirically determined fragmentation patterns for each peptide in the library. However, DIA is currently unable to match the precision of MRM or PRM in measuring very low-abundance peptides, likely because their signals are dwarfed by those from abundant co-eluting peptides. A brief comparison of DDA, DIA, and MRM/PRM with respect to precision of quantification, breadth of identification, ease of setup and analysis, and reproducibility, is shown in Table 1.\n\nDDA, data-dependent acquisition; DIA, data-independent acquisition; MRM, multiple reaction monitoring; MS1, scan in which the peptide ions entering the mass spectrometer at a given time are identified; MS2, scan in which the fragments of all (or some) of the peptides that are in the mass spectrometer at a given time are identified; m/z, mass-to-charge ratio; PRM, parallel reaction monitoring; SILAC, stable isotope labeling by amino acids in cell culture.\n\nThe complexity of MS2 spectra greatly impacts the sensitivity of the downstream analyses and therefore must be considered when planning a DIA experiment. Two main variables determine the complexity and interpretability of the spectra: the number of proteins present in the sample and the precursor m/z window widths from which ions are isolated and fragmented. The effect of the number of proteins present is shown in Figure 3, which describes the results of a study in which 345 synthetic peptides were spiked into water, yeast lysate, or human lysate backgrounds in concentrations varying from 30 to 0.058 fmol/µL and then analyzed via relatively wide precursor isolation windows of 25 m/z31 (see Supplementary material). The sensitivity of peptide detection decreases with the protein complexity of the organism, where the yeast lysate is more complex than the water background and the human lysate is more complex than the yeast lysate, with an average of 32,993 unique human, trypsin-digested peptide ions possibly falling within each 25-m/z window compared with the 7,287 yeast peptide ions. Sensitivity and precision may be increased by shortening the width of the precursor isolation window, thereby decreasing the number of peptides represented in each MS2 spectrum. However, this decreases coverage across the total precursor m/z range and therefore the number of peptides to which the analysis may be sensitive. Therefore, experimentalists must balance the effects of sample complexity, isolation window width, and desired coverage on sensitivity.\n\nVarying concentrations of 345 synthetic peptides were spiked into three sample backgrounds, subjected to data-independent acquisition (DIA), and analyzed by OpenSWATH. Lines show the number of spike in peptides identified at a 5% false discovery rate (FDR) in the different samples.\n\nThe main reason for the decrease in sensitivity is the increased likelihood of fragment ion interference in complex spectra, which occurs when multiple co-eluting peptides share a fragment ion peak. Interference undermines the elution profile correlation between a peptide’s fragments and the fragments’ correlation to spectral libraries on which many DIA analysis methods rely. In an analysis of synthetic peptides spiked into human urine, SWATHProphet32, a software tool further described below, estimated that at least 24% of confidently identified peptides showed evidence of fragment ion interference that increased the variance of their quantification. This percentage is likely much higher in unidentified peptides and this is the likely cause of the peptides’ invisibility to the software. Therefore, further progress in the interpretation of DIA spectra should circumvent the problem of interference, which SWATHProphet32 has begun to do by identifying and disregarding fragments affected by interference.\n\n\nData-independent acquisition strategies\n\nIn all DIA methods, each MS2 scan contains fragments from every peptide within one or more pre-specified precursor m/z windows. Each window is repeatedly sampled so that each peptide is fragmented multiple times. The earliest and most common DIA method is a sequential sampling strategy9,33 (Figure 2B), in which an m/z range covering most peptides of interest is split into a sequence of non-overlapping windows, usually of equal but sometimes of variable size depending on the m/z distribution of the peptides of interest. For each window in the sequence, all of the precursors falling into that window are fragmented together and measured in an MS2 scan. The machine repeats the sequence throughout the full HPLC elution gradient. The time needed to complete the traversal of the sequence is on the order of a few seconds, such that every peptide can be sampled at least a few times during its elution.\n\nAn alternative DIA method, MSX34, incorporates multiplexing and an element of randomness to the sequential sequencing to increase precision in associating a precursor ion to its fragments. However, this method is compatible only with selected mass spectrometers in which software controllers have been modified to accept random sampling of mass range windows. The precursor m/z windows are smaller and more numerous than in the sequential method, but each MS2 scan is multiplexed. Each scan contains fragmented precursors from multiple, randomly chosen non-contiguous windows, such that the precursors span the same total m/z length in each MS2 scan. Post-processing of the MS2 spectra solves a system of linear equations to infer from which smaller precursor window each fragment ion peak originated. The resulting de-multiplexed MS2 scans allow a modest increase in peptide identifications compared with scans produced from non-random, contiguous windows.\n\n\nComputational analysis of spectra\n\nAlthough traditional algorithms for identifying peptides from DDA spectra can be applied to DIA spectra analysis, these algorithms are not appropriate for DIA for two reasons: they incorrectly assume that each MS2 scan contains fragments from just one peptide, and they ignore the dynamic pattern of elution profiles in DIA spectra. Consequently, three main classes of computational algorithms have emerged to specifically analyze DIA data that accommodate the complexity and time variation in DIA spectra. The first two classes are for untargeted, discovery-based identification, and the third is for precise quantification of previously identified peptides from spectral libraries. The main challenge of the algorithms below is controlling the false discovery rate among the identified peptides while identifying all (or most) real peptides in the sample of interest.\n\nThese methods use a pre-processing step that deconvolves DIA MS2 scans into multiple pseudo-spectra, each containing the fragments of only a single peptide species in the mixture. The intensities of different fragments of the same peptide species should correlate over elution time, and the pre-processing step uses this correlation to assign fragment ions from MS2 scans to their intact peptide species in MS1 scans. These pseudo-spectra then can be searched by using a traditional DDA database search method.\n\nDIA-Umpire35 and DeMux36 are two strategies that take this approach. They differ in the specific algorithms used to group ions and compile them into deconvolved spectra. DIA-Umpire tends to work better because it considers isotope peak distributions in MS1 scans to narrow down candidate peptides, finding up to 89% of the peptides identified by analogous DDA experiments. DIA-Umpire also includes additional methods that generate new reference/library spectra, incorporates prior library spectra, and uses them for further steps in protein identification and quantification, achieving on average a 0.931 R2 correlation in the quantifications of peptides between replicates. This strategy works in a fashion analogous to DDA experiments in that it identifies many peptides, but also the strategy provides precise DIA quantification of the identified peptides35.\n\nThese strategies are inspired by traditional database searching and do not focus on using dynamic patterns to identify peptides. Instead, they include other heuristics to adapt searching to a DIA context. They score each peptide against each observed spectrum by computing the dot-product of the peptide’s theoretical spectrum against each observed spectrum, much like traditional DDA search algorithms. However, these methods introduce additional heuristic filtering steps, such as considering only observed spectra that match a threshold number of peaks in a theoretical spectrum. The first example of this strategy was FT-ARM37. However, a more recent method, Pecan38, contains additional heuristics as well as a discriminative model to combine them, so it performs better than FT-ARM. Pecan is available through the Skyline34–37,39 graphical user interface, which provides convenient visualization, annotation, and analysis of mass spectra acquired by DDA, DIA, and MRM/PRM.\n\nStrategies in this category are adapted from methods used to analyze PRM/MRM spectra, because both DIA and MRM/PRM repeatedly sample the same peptides to obtain sequences of fragment ion intensities over elution time (fragment ion chromatograms; Figure 2D). These methods take library spectra as input (compiled from prior DDA peptide identifications or prior DIA-Umpire identifications) and extract fragment ion chromatograms at the peaks in the library spectra. Potential elution peaks of each peptide from these fragment ion chromatograms are evaluated on the basis of many criteria, including how well the fragment ions correlate over elution time and how well their relative intensities match their corresponding library spectrum. Elution peaks are evaluated by using a discriminative model that combines these criteria to distinguish real peptide signals from decoy peptide signals. These methods also quantify proteins by quantifying the fragment ion chromatograms of their peptides.\n\nOpenSWATH31, SWATHProphet32, Spectronaut40, and a module in DIA-Umpire35 all implement this strategy. Skyline39 provides elution peak quantification but not statistical validation. OpenSWATH31 has been shown to achieve coefficients of variation of between 0% and 20% on 345 spike-in peptides across 256-fold concentration differences in a yeast lysate. In a series of human lysate runs, Spectronaut40 achieved a 98% peptide identification reproducibility rate from run to run on DIA data compared with 49% on DDA data on 26,738 peptides covering 3,690 proteins.\n\nThe class of search methods to be used depends on the specific context of the experiment. If no library spectra are available, then Pecan or DIA-Umpire must be used. No published direct comparison yet exists between the two, so the choice depends on how they fit into your bioinformatics pipeline. DIA-Umpire includes its own pipeline for library spectrum generation and automated quantification. Pecan is incorporated into Skyline39 such that visualization, annotation, and semi-automated quantification are convenient. If library spectra are available, then a method with chromatogram scoring should be used. Again, no direct comparison is available, but the different chromatogram scoring algorithms are similar enough such that one can use the tool that best fits into one’s pipeline.\n\n\nExamples of studies facilitated by the increased breadth and precision of DIA\n\nHere, we describe the use of algorithm 3, chromatogram scoring with spectral libraries, on two large quantitative studies whose insights critically depend on the breadth, reproducibility, and quantitative precision of DIA. The first study characterizes plasma proteome variation between monozygotic and dizygotic twins41 and elucidates biomarker variation over time. Its inclusion of both types of twins allows the quantification of variation caused by genetics, the environment, and time. The study sampled, at two time points, blood from each person in 22 pairs of adult fraternal twins and 36 pairs of adult identical twins, resulting in 232 sets of DIA experiments. The spectral library used to identify and quantify peptides consists of 43,000 peptides that represent 1,667 unique proteins, compiled from a pre-existing library42 and supplementary DDA data. OpenSWATH analysis was able to identify 1,904 of these peptides (342 proteins) in all 232 samples and quantify 76% of these with coefficients of variation of less than 25%. Notably, 42 of the identified proteins are approved by the US Food and Drug Administration for clinical assays. The breadth and precision of quantification vastly surpassed prior attempts using antibody arrays43 and could be achieved only by using DIA rather than PRM or DDA.\n\nA thorough survey of the successfully identified proteins characterized the main causes of their variability: proteins involved in blood coagulation, inflammation, and high-density lipoproteins that regulate cholesterol levels are controlled more by genetics than environmental influences. These results corroborate findings from several prior studies. Moreover, the survey discovered previously uncharacterized dependencies of eight of the clinically relevant proteins on age, which could confound their clinical interpretation. For example, plasma level of soluble CD14 is used as an independent predictor for HIV infection, and 14-3-3 protein zeta/delta is used as a prognostic for lung and breast cancers; both of these proteins naturally vary over time41.\n\nIn a second study, DIA and OpenSWATH successfully mapped the interactomes of four well-characterized human proteins via affinity purification of Flag-tagged proteins and discovered how the interactions of two of them with the chaperone protein HSP90 differ in response to melanoma-associated mutations44. In particular, DIA analysis of CDK4 affinity-purified samples out-identified and out-quantified analogous DDA experiments: 5,089 peptides were identified in all three DIA replicates, whereas 2,741 were identified in all three DDA replicates. Of peptides identified by both DIA and DDA, DIA quantified 82.1% with a coefficient of variation of less than 20% compared with the 74.5% achieved by DDA. Samples affinity-purified for melanoma-associated mutant versions of CDK4 showed increases in HSP90 abundance, suggesting that these mutants associate more or form a stronger association than wild-type CDK4 with HSP90.\n\n\nFuture directions\n\nAlthough DIA has been gradually accepted by the proteomics community, improvements in hardware and software tools are still required to facilitate its use by the larger scientific community. From a hardware standpoint, parallel improvements in duty-cycle speed, sensitivity, and peak resolution, especially at the MS2 level, will be critical for the improvement of DIA. Faster duty-cycle speed could allow increases in the mass regions analyzed by a DIA experiment in a single run. Currently, DIA experiments typically range from 100 to 400 m/z units (500 to 900 m/z region), whereas DDA usually covers 1,600 m/z units (400 to 2000 m/z region). Moreover, increases in duty cycle would allow a reduction of the size of the fragmentation windows on DIA methods from 15 to 25 m/z units on average to 2 to 5 m/z units without needing to reduce the mass range to be analyzed in a single run. Much like MRM methods, isolating small regions for fragmentation would result in increased signal-to-noise ratios at the MS2 level, which combined with increased sensitivity would allow the detection of fragment ions formerly lost in the noise. Moreover, the use of smaller fragmentation windows combined with increases in instrument resolution, currently provided by high-end instruments, would result in improved deconvolution of mixed spectra because the mixtures are simpler (fewer peptides fragmented in each MS2 event) and fragments that are close in mass are easier to differentiate (higher resolution). No mass spectrometers yet combine the resolving power and speed needed to cover the same mass range that DDA does using small windows for DIA analysis; however, mass spectrometry speed, sensitivity, and resolution have greatly improved over the last 5 years, and we are yet to reach the physical limits of hardware improvements45. If the rate of instrumentation advances continues, then within the next 5 years we should be able to cover the same m/z range that DDA covers using small, overlapping DIA windows. Thus, the main challenge is how these large DIA datasets will be deconvoluted and analyzed.\n\nTo further improve the deconvolution of complex DIA spectra and increase their identification and quantification efficiency, researchers are developing more sophisticated sampling and computational algorithms to analyze biological samples using DIA. Though yet unpublished, several such methods were presented at the American Society of Mass Spectrometry conference. Three of the most promising analysis methods are outlined below.\n\nThe first method draws a parallel between the analysis of DIA spectra and the field of compressed sensing to precisely infer the precursor masses of the detected fragment ions46. It uses the random, multiplexed sampling of MSX34 but improves the deconvolution of multiplexed spectra by adding further constraints to the system of linear equations posed by deconvolution, inspired by the field of compressed sensing. Compressed sensing takes advantage of the fact that if a signal is sparse, then one need not measure all of the signal to accurately reconstruct it47. DIA data are sparse; at any time during the chromatography, only a small fraction of possible precursor peaks is observed. To precisely match precursor ions to their fragments, it is unnecessary to dedicate fragment scans to all small individual precursor windows if most windows are devoid of peptides. Indeed, DIA methods use wide, contiguous precursor isolation windows of width up to 25 m/z. However, compressed sensing states that repeated sampling from these predetermined windows are suboptimal to match fragment ions to their precursors. Instead, if one randomly combines smaller, not necessarily adjacent windows into large composite windows that overall span 25 m/z, then one can match fragments to precursors within these smaller, more precise windows. The published MSX34 method already leverages this fact but does not use the theoretical techniques developed in compressed sensing to get the most accurate deconvolution.\n\nThe second method attempts to improve identifications by using linear regression to jointly identify the whole set of present peptides simultaneously rather than one at a time48. Unlike current methods, the regression can deconvolve fragment ion interference in a principled way, which occurs when multiple precursor ions contribute to intensity at the same fragment ion peak, such that its chromatographic profile no longer matches the chromatographic profiles of the other fragment ions. Estimates have shown that approximately 24% of peptides may exhibit interference in a human urine sample32. This phenomenon prevents current methods from attributing the fragment ion peak to any single precursor ion, but the regression approach can in principle properly attribute the peak to all appropriate precursor ions simultaneously.\n\nThe third method extends traditional DDA search methods with peak filtering to take into account the correlation of fragment ion peaks from the same peptide49. When scoring matches between candidate peptides and observed MS2 scans, some shared peaks can be explained by multiple candidate peptides and some unique peaks can be explained by just one. The method restricts each shared peak to contribute to the score of only the single peptide whose unique peaks correlate best over time with the shared peak. This restriction prevents the spurious high scores of falsely discovered peptides that depend entirely on peaks originating from other peptides. These techniques to better associate fragment ions to their precursor ions are in developmental stages and, if successful, will broaden the usefulness of any DIA dataset.\n\n\nConclusions\n\nBecause DIA combines the breadth of protein identification provided by DDA and approaches the sensitivity and precision of MRM/PRM, it will be the best choice for discovery bottom-up proteomics and large-scale quantification in the near future. Sampling schemes and analysis methods already allow flexibility to adapt DIA to most biological problems and researcher needs. However, because DIA is still a work in progress, DDA data are still easier to acquire and analyze for most researchers and DDA is the method of choice for most biology and proteomics laboratories. Finally, using DIA implies trading off some precision and sensitivity for breadth when compared with targeted methods. Thus, if quantification of specific lowly abundant peptides is required, then MRM and PRM targeting the ions of interest are still the better option.\n\n\nAbbreviations\n\nDDA, data-dependent acquisition; DIA, data-independent acquisition; HPLC, high performance liquid chromatography; LC-MS/MS, liquid chromatography-tandem mass spectrometry; MRM, multiple reaction monitoring; MS1, scan in which the peptide ions entering the mass spectrometer at a given time are identified; MS2, scan in which the fragments of all (or some) of the peptides that are in the mass spectrometer at a given time are identified; m/z, mass-to-charge ratio; PRM, parallel reaction monitoring.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe authors thank Dina Fomina Yadlin for helpful discussions and suggestions. This work was supported by National Institutes of Health award R01 GM096306 and by National Science Foundation award 1549932.\n\n\nSupplementary material\n\nDataset 1. Zip file contains 4 files: 3 files that show false discovery rates and metadata for the 345 Synthetic Gold Standard peptides spiked into the yeast, human, and water backgrounds from the experiments shown in Figure 3. Each file is associated with one background and contains identifications from 30 experiments spanning 10 spike-in concentrations with 3 replicates each. The \"m_score\" column denotes the false discovery rates reported by OpenSWATH. The 4th file \"mf_files.txt\" further annotates the 90 experiments.\n\nClick here to access the data.\n\n\nReferences\n\nMann M, Hendrickson RC, Pandey A: Analysis of proteins and proteomes by mass spectrometry. Annu Rev Biochem. 2001; 70: 437–73. PubMed Abstract | Publisher Full Text\n\nOng SE, Blagoev B, Kratchmarova I, et al.: Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol Cell Proteomics. 2002; 1(5): 376–86. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nRoss PL, Huang YN, Marchese JN, et al.: Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics. 2004; 3(12): 1154–69. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBateman NW, Goulding SP, Shulman NJ, et al.: Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA). 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PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGavin AC, Maeda K, Kühner S: Recent advances in charting protein-protein interaction: mass spectrometry-based approaches. Curr Opin Biotechnol. 2011; 22(1): 42–9. PubMed Abstract | Publisher Full Text\n\nDavis ZH, Verschueren E, Jang GM, et al.: Global mapping of herpesvirus-host protein complexes reveals a transcription strategy for late genes. Mol Cell. 2015; 57(2): 349–60. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMeyniel-Schicklin L, de Chassey B, André P, et al.: Viruses and interactomes in translation. Mol Cell Proteomics. 2012; 11(7): M111.014738. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNavare AT, Sova P, Purdy DE, et al.: Quantitative proteomic analysis of HIV-1 infected CD4+ T cells reveals an early host response in important biological pathways: protein synthesis, cell proliferation, and T-cell activation. Virology. 2012; 429(1): 37–46. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDiner BA, Lum KK, Javitt A, et al.: Interactions of the Antiviral Factor Interferon Gamma-Inducible Protein 16 (IFI16) Mediate Immune Signaling and Herpes Simplex Virus-1 Immunosuppression. Mol Cell Proteomics. 2015; 14(9): 2341–56. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nCristea IM, Graham D: Virology meets Proteomics. Proteomics. 2015; 15(12): 1941–2. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOng SE, Mann M: A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nat Protoc. 2006; 1(6): 2650–60. PubMed Abstract | Publisher Full Text\n\nWiese S, Reidegeld KA, Meyer HE, et al.: Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research. Proteomics. 2007; 7(3): 340–50. PubMed Abstract | Publisher Full Text\n\nLange V, Picotti P, Domon B, et al.: Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol. 2008; 4(1): 222. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWhiteaker JR, Halusa GN, Hoofnagle AN, et al.: CPTAC Assay Portal: a repository of targeted proteomic assays. Nat Methods. 2014; 11(7): 703–4. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKim YJ, Gallien S, van Oostrum J, et al.: Targeted proteomics strategy applied to biomarker evaluation. Proteomics Clin Appl. 2013; 7(11–12): 739–47. PubMed Abstract | Publisher Full Text\n\nTsuchiya H, Tanaka K, Saeki Y: The parallel reaction monitoring method contributes to a highly sensitive polyubiquitin chain quantification. Biochem Biophys Res Commun. 2013; 436(2): 223–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKoyano F, Okatsu K, Kosako H, et al.: Ubiquitin is phosphorylated by PINK1 to activate parkin. Nature. 2014; 510(7503): 162–6. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMajovsky P, Naumann C, Lee CW, et al.: Targeted proteomics analysis of protein degradation in plant signaling on an LTQ-Orbitrap mass spectrometer. J Proteome Res. 2014; 13(10): 4246–58. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nRöst HL, Rosenberger G, Navarro P, et al.: OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nat Biotechnol. 2014; 32(3): 219–23. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKeller A, Bader SL, Shteynberg D, et al.: Automated Validation of Results and Removal of Fragment Ion Interferences in Targeted Analysis of Data-independent Acquisition Mass Spectrometry (MS) using SWATHProphet. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBern M, Finney G, Hoopmann MR, et al.: Deconvolution of mixture spectra from ion-trap data-independent-acquisition tandem mass spectrometry. Anal Chem. 2010; 82(3): 833–41. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWeisbrod CR, Eng JK, Hoopmann MR, et al.: Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification. J Proteome Res. 2012; 11(3): 1621–32. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nTing YS, Egertson J, Maclean B, et al.: Pecan: Peptide identification directly from data-independent acquisition (DIA) MS/MS data. Poster at ASMS, 2014.\n\nMacLean B, Tomazela DM, Shulman N, et al.: Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 2010; 26(7): 966–8. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBruderer R, Bernhardt OM, Gandhi T, et al.: Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues. Mol Cell Proteomics. 2015; 14(5): 1400–10. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLiu Y, Buil A, Collins BC, et al.: Quantitative variability of 342 plasma proteins in a human twin population. Mol Syst Biol. 2015; 11(1): 786. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFarrah T, Deutsch EW, Omenn GS, et al.: A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas. Mol Cell Proteomics. 2011; 10(9): M110.006353. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKato BS, Nicholson G, Neiman M, et al.: Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model. Proteome Sci. 2011; 9: 73. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLambert JP, Ivosev G, Couzens AL, et al.: Mapping differential interactomes by affinity purification coupled with data-independent mass spectrometry acquisition. Nat Methods. 2013; 10(12): 1239–45. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nRichards AL, Merrill AE, Coon JJ: Proteome sequencing goes deep. Curr Opin Chem Biol. 2015; 24: 11–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nEgertson J, Johnson RS, Xuan Y, et al.: Improved Computational Demultiplexing for Data Independent Acquisition Data Acquired by MSX or with Overlapping Windows. Presentation at ASMS, 2015.\n\nMackenzie D: Compressed Sensing Makes Every Pixel Count. What's Happening in the Mathematical Sciences. Providence, RI: American Mathematical Society; 2009; 115–27. Reference Source\n\nHu A, Howbert JJ, Bilmes J, et al.: A regularized linear regression model for the identification of peptides from data-independent acquisition mass spectra. Poster at ASMS, 2015.\n\nAfkham HM, Kim S, Käll L: Improving DIA peptide identification via local time profile similarity. Poster at ASMS, 2015.\n\nEgertson JD, MacLean B, Johnson R, et al.: Multiplexed peptide analysis using data-independent acquisition and Skyline. Nat Protoc. 2015; 10(6): 887–903. PubMed Abstract | Publisher Full Text\n\nDeutsch EW, Mendoza L, Shteynberg D, et al.: A guided tour of the Trans-Proteomic Pipeline. Proteomics. 2010; 10(6): 1150–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMcIlwain S, Tamura K, Kertesz-Farkas A, et al.: Crux: rapid open source protein tandem mass spectrometry analysis. J Proteome Res. 2014; 13(10): 4488–91. 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}
|
[
{
"id": "13131",
"date": "31 Mar 2016",
"name": "Paul Huang",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13132",
"date": "31 Mar 2016",
"name": "Jarrod Marto",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13133",
"date": "31 Mar 2016",
"name": "Ileana Cristea",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-419
|
https://f1000research.com/articles/5-418/v1
|
31 Mar 16
|
{
"type": "Review",
"title": "Concerning immune synapses: a spatiotemporal timeline",
"authors": [
"Alvaro Ortega-Carrion",
"Miguel Vicente-Manzanares",
"Alvaro Ortega-Carrion"
],
"abstract": "The term “immune synapse” was originally coined to highlight the similarities between the synaptic contacts between neurons in the central nervous system and the cognate, antigen-dependent interactions between T cells and antigen-presenting cells. Here, instead of offering a comprehensive molecular catalogue of molecules involved in the establishment, stabilization, function, and resolution of the immune synapse, we follow a spatiotemporal timeline that begins at the initiation of exploratory contacts between the T cell and the antigen-presenting cell and ends with the termination of the contact. We focus on specific aspects that distinguish synapses established by cytotoxic and T helper cells as well as unresolved issues and controversies regarding the formation of this intercellular structure.",
"keywords": [
"Immune synapse",
"T-Cell",
"antigen presenting cell",
"T cell activation"
],
"content": "Introduction\n\nThe immune synapse (IS) is a central event in the development of the adaptive immune response that results in the activation of the T cell. The “synapse-like” nature of the intimate contact between the T cell and the antigen-presenting cell (APC) during T cell activation was initially proposed by Norcross in the early 1980s1, although the term “immunological synapse” first appeared in a review by Paul and Seder in 19942. The specifics of molecular segregation into activation clusters at the T cell:APC interface dates back to the seminal observations of Kupfer’s group in 19983. At the same time, Dustin and Shaw conjoined both concepts (the IS as the physical manifestation of T cell activation, and molecular segregation as the functional reflection of the T cell:APC interaction), adding crucial early data on the composition of the activation clusters4. The IS can be defined as a stimulus-driven, spatiotemporal segregation of molecules that participate in T cell activation. Segregation requires the establishment of an intimate contact between a T lymphocyte and an APC. The molecular redistribution is antigen dependent, requiring the interaction of an antigen-specific T cell receptor (TCR) with an antigen-loaded major histocompatibility complex (MHC) molecule. The features and outcome of the IS depend on the type of T cell and APC. The interaction of a CD4+ T helper (TH) cell with an antigen-loaded MHC-II-bearing APC results in the specific recognition of the antigen and the activation of the T cell, i.e. proliferation, cytokine secretion, expression of effector molecules, etc. In the case of CD8+ T (CTL) cells interacting with cells displaying antigen-associated MHC-I, the outcome depends on the pre-exposure of the CTL to the antigen. Naïve CTL encountering specific antigens presented by APCs (e.g. dendritic cells [DCs] expressing antigen associated with class I via cross-presentation) are primed (“armed”) to kill target cells and proliferate. Primed CTL also form transient IS with target cells (tumor cells or cells infected by a virus), resulting in specific killing.\n\nThe IS displays remarkable similarities with the neuronal synapse (NS), to which it owes its name. For spatial and functional reference, the APC is better compared to the pre-synaptic terminal, and the T cell to the post-synaptic terminal. The presynaptic portal provides the initiating signal, soluble in the NS (neurotransmitters), but membrane bound in the IS (antigen-bearing MHC). Upon ligation of the key receptor in the post-synaptic terminal (neurotransmitter receptors in the NS; TCR and its signaling co-receptor CD3 in the IS), downstream signaling ensues, including calcium mobilization, actin remodeling, and functional activation of the post-synaptic cell1,5. However, a unique feature of the IS consists of specific antigenic recognition, which is absent in the central nervous system (CNS). Another difference is the duration of the contact: whereas some NS can last for days, weeks, or even months, IS between CTL and target cells resolve in minutes, whereas between TH cells and APCs they can last from several hours to two days6,7. This feature change implies a different meaning for the concept of plasticity. In the NS, it refers to the modifications to the post-synaptic terminal that involve the consolidation and adaptation of the post-synaptic terminal to the flux of signal stemming from the pre-synaptic portal. In the IS, plasticity follows contact resolution and could be used to describe the functional changes to the T cell caused by the establishment of a productive synapse. These include activation (TH), activation (naïve CTL) or kill (primed CTL), and functional anergy or apoptosis, e.g. during thymic selection of naïve T cells. A major manifestation of functional plasticity is the development of immunological memory, i.e. the generation of long-lived T cells primed to respond to a specific antigen that trigger a much faster and more efficient response to repeated exposure to the same antigen.\n\n\nOverview of the spatiotemporal events of the IS\n\nThe study of the IS has focused on the establishment of hierarchical, spatiotemporally segregated events during the contact between the APC and the T cell. These events include the following:\n\n1) Establishment of low-affinity, exploratory contacts between the T cell and the APC\n\n2) Initial, scattered contact of the TCR with the antigen-loaded MHC on the APC, followed by initiation of TCR-dependent signaling pathways upon specific recognition of the MHC-peptide complex. Such activation is “umbrella shaped” (simultaneous activation and amplification of multiple pathways through different sets of effectors) and induces the activation of multiple effectors, including membrane-bound molecules, e.g. integrins, signaling adaptors, cytoskeletal elements, and transcription factors\n\n3) Transactivation of adhesion molecules (integrins) that consolidate the interaction between the T cell and the APC. This step actually begins after initial TCR activation (step 2), but they evolve in parallel\n\n4) Cytoskeleton- and signaling-dependent clustering of adhesion molecules and the TCR/CD3 complex at the contact interface between the T cell and the APC. In most cases, clustering is spatiotemporally segregated, i.e. the TCR/CD3 clusters and the integrin clusters, and their respective sets of adaptors, are separated\n\n5) Signaling- and motor-dependent positioning of the secretory apparatus (including microtubules and microtubule-binding proteins) to the contact interface of the T cell\n\n6) (Primed CTL only, also natural killer [NK] cells) Actin clearance at the center of the contact interface, enabling a tight association of the secretory apparatus with the plasma membrane\n\n7-i) (TH cells) Stabilization of the contact and transcriptional activation of the T cell, including cytokine production and the expression of activation markers\n\n7-ii) (Naïve CTL) Stabilization of the contact, priming and activation\n\n7-iii) (Primed CTL and NK cells) Degranulation and target cell killing\n\n8) Termination of the contact\n\nFrom this flowchart, it becomes obvious that a major difference between the IS established by CTL and that established by TH cells is the overall duration of the process and its immediate repeatability. CTL contacts are quick (to eliminate target cells rapidly), and CTLs can establish multiple IS with different target cells over short periods of time. Conversely, TH cells establish prolonged IS and do not form consecutive IS once activated properly.\n\nIn the following sections, we will develop emerging concepts pertaining to each of these spatiotemporal events.\n\nExploratory contacts are mediated by low-affinity interactions between specific ligands and receptors. A major factor is the glycocalyx, which establishes charge-dependent repulsive interactions between the APC and the T cell (reviewed in 8). Additional contacts are mediated by glycosylation-dependent, low-affinity interactions, e.g. via galectins. For example, galectins bind TCR molecules with low affinity, thus the TCR does not activate9. Antigen-loaded MHC molecules successfully compete with galectin to trigger TCR/CD3 activation and subsequent cytoskeletal remodeling and transcriptional activation (see below). Chemokine receptors also participate in the formation and subsequent stabilization of the initial contacts and localize in the IS. Possible functions for chemokine receptors in this subcellular region are likely to involve co-stimulation, cell attraction, enhancement of actin polymerization, etc.10. Other exploratory contacts depend on specific protein-protein interactions, e.g. LFA-1 (αLβ2) (APC) with ICAM-3 (T cell)11, and LFA-3 (APC) with CD2 (T cell). LFA-1 interacts with ICAM-3 while in a low-affinity conformation12. Likewise, LFA-3 interacts with CD2 with suitable low affinity13, although the glycocalyces are likely to hinder their interaction sterically14. These contacts allow the transient interaction of the TCR with peptide-loaded MHC. If such interaction bears enough affinity, it overcomes the repulsive forces between the glycocalyces; if not, repulsion dominates and the unproductive contact between the mismatched T cell and APC is resolved.\n\nSuccessful interaction of the TCR/CD3 complex with peptide-loaded MHC initiates signaling. It is important to point out that very few TCR-MHC interactions are sufficient to trigger T cell activation15. Recent reviews have described the current viewpoints on TCR/CD3 signaling16,17. Here, we will focus on several aspects of TCR binding and initial signaling that are specific to IS formation and shape the rest of the process.\n\nProductive TCR engagement promotes its immobilization and clustering in the contact area18. This is mediated in part by its interaction with the MHC on the APC, which restricts the possible lateral movement of the TCR to the interacting portion of the plasma membrane of the T cell with the APC. However, the TCR/CD3 complex appears more immobile and clustered than predicted by a model of free diffusion in a semi-planar layer8, suggesting additional mechanisms of immobilization and aggregation. A crucial mechanism is the association of the TCR/CD3 complex with the actin cortex19,20. A recent study has shown that ligated TCR/CD3 molecules modify the flow of actin underneath them, indicating binding-dependent interactions between the TCR and cortical actin21, which are essential for sustained TCR-dependent signaling22. Such interaction is not direct but relies on the recruitment of actin-binding adaptors, e.g. Nck23.\n\nAnother important topic is cluster size. There is evidence of small (nanosized) TCR clusters even before their interaction with the MHC. These nanoclusters are continually generated throughout the plasma membrane of the T cell24 and migrate and coalesce at the center of the contact to form micron-scale structures, termed central Supramolecular Activation Clusters (cSMACs) (Figure 1, top)25, which concentrate signaling components (reviewed in 26) as well as molecules involved in co-stimulation, e.g. CD2827. The mechanism of coalescence is also unclear, but it also depends on actin and TCR ligation28. Possible explanations involve increases in homotypic TCR lateral affinity, actin coalescence that would “drag” the TCR nanoclusters together, or changes to the size/position of the membrane nanoclusters based on alterations to the regional composition of the plasma membrane. The principles of spatiotemporal assembly of such structures remain unclear, mainly because of differences depending on the type of T cell and APC. In general, T cells that bear a higher basal activation state (e.g. leukemic T cells or memory T cells) form large clusters more readily than resting, naïve T cells. In the latter, TCR/CD3 clusters often remain small and sparse along the contact area between the T cell and the APC29,30. The difference could pertain to the expression of additional components in activated cells that promote, or facilitate, TCR/CD3 clustering in more pre-activated cells and/or that signals emanating from the TCR/CD3 are more intense in pre-activated cells owing to a higher activation baseline.\n\nTop, diagram represents the adhesion of the T cell (left) to the antigen-presenting cell (APC) (right), and the early formation of discrete domains, central supramolecular activation cluster (cSMAC) (red) containing the T cell receptor (TCR)/CD3 complex and signaling proteins, and the peripheral SMAC (pSMAC) (blue) displaying integrins and their adaptor proteins. Bottom left column, events in the T helper (TH) formation of a synapse with a professional APC, including F-actin accumulation (top, in red) and juxtaposition of the secretory apparatus (green) and the microtubule-directing centrosome (bottom, in black), resulting in the polarized secretion of exosomes (bright-green spheres) and the non-polarized secretion of cytokines (stars). Bottom right column, events in the CD8+ T (CTL) synapse, including F-actin accumulation and the formation of a secretory domain with weak actin presence (top) and the juxtaposition of the secretory apparatus (purple) and the microtubule-directing centrosome (bottom, in black), resulting in the highly polarized secretion of lytic particles that kill the target cell.\n\nTCR-dependent inside-out signals trigger the conformational extension of integrin LFA-1, enabling its interaction with APC-expressed ICAM-1 (reviewed in 31). This process is similar to the inside-out signaling that activates integrins during extravasation32, and it results in stable adhesion between the APC and the T cell.\n\nTCR signals that mediate LFA-1 trans-activation go through several adaptor circuits, including Rap1-RapL-RIAM and SLP-76/ADAP/SKAP (Figure 2). Rap1 is a small Ras-like GTPase that is activated by RasGEFs triggered by the TCR, e.g. CalDAG-1. Active Rap1 forms a complex with RapL and RIAM that targets talin to the plasma membrane33, where it promotes the conformational extension of LFA-134. SLP-76/ADAP/SKAP-55 bind to the TCR effector LAT, triggering their association to RIAM, thereby participating in the delivery of talin to the integrin35.\n\nAnother important molecule for the inside-out activation of LFA-1 via TCR is kindlin-3. Kindlin-3 mutations cause a severe form of immunodeficiency, named Leukocyte Adhesion Deficiency (LAD)-III36,37. LAD-III T cells do not migrate properly and activate poorly due to impaired adhesion mediated by LFA-138. There are two possible mechanisms to explain the role of kindlin-3 in LFA-1 transactivation. One mechanism postulates that kindlin-3 triggers inside-out activation of LFA-1 by binding directly to the β chain cytoplasmic domain. The other mechanism suggests that kindlin-3 could facilitate the binding of talin, or its effect on the conformational extension of LFA-1 (reviewed in 39). Recruitment of kindlin-3 to LFA-1 is likely mediated by its interaction with ADAP, as in platelet integrin αIIBβ340 (Figure 2).\n\nDiagram depicts the major interactions involved in actin-dependent T cell receptor (TCR) and integrin immobilization at the immune synapse (IS), including the signaling modules involved in LFA-1 transactivation. The diagram focuses on the role of SLP-76/ADAP/SKAP-55 in recruiting kindlin-3 and RIAM in proximity to integrin, and the role of Rap/RapL/RIAM in promoting talin association with the β chain of the LFA-1 dimer.\n\nLFA-1 is the predominant integrin that mediates the interaction of TH cells with APC. It is also important for the formation of IS between CTL and target cells. However, it is unlikely that every target cell expresses ICAM-1, thus additional integrins may be implicated in the formation of IS. Prior studies have described possible roles for VLA-4 (α4β1) and VLA-5 (α5β1) in the IS (reviewed in 41), but their ligands as well as their redundant/unique functions with respect to LFA-1 remain unclear. Spatially, integrins localize throughout the contact area of the T cell and the APC. In activated cells (e.g. super-antigen-triggered clonal leukemic T cells), integrins localize in the outer edge of the contact zone, defining a peripheral SMAC (pSMAC) (Figure 1, top).\n\nOutside-in signals stemming from the TCR and integrins promote actin polymerization and clustering at the T cell:APC interface (Figure 1). As discussed above, actin accumulation is fundamental for the clustering of the TCR and the integrins, forming a positive feedback loop. TCR/CD3 and integrins trigger actin polymerization through several pathways. A major pathway of TCR-mediated actin polymerization depends on the small GTPase Rac1. The TCR activates several Rac GEFs, including Vav142 and Tiam143. Rac promotes branched actin accumulation by activating a multi-molecular complex that includes WAVE (Scar), HSP300, ABL2, SRA1, and NAP1. This complex associates with the Arp2/3 complex, triggering actin polymerization, as reviewed elsewhere44. Wiskott-Aldrich syndrome protein (WASP) is a protein related to WAVE that also induces Arp2/3-dependent actin polymerization downstream of the TCR, but it is activated by the small GTPase Cdc4245.\n\nThe contribution of other mechanisms of actin polymerization to the congregation of actin at the contact area with the APC is less clear. During the first steps of the formation of the IS, molecular regulators of actin assembly, e.g. ADF/cofilin, are involved in the dynamic reorganization and accumulation of actin at the contact region. For example, depletion of ADF/cofilin function in T cells enhances the accumulation of actin at the IS46. Formins, e.g. mDia, are barbed end nucleators that bind to the uncapped actin filament through one domain and to G-actin-loaded profilin through another, thereby catalyzing G-actin transfer from profilin to the barbed end. mDia-deficient T cells activate and migrate deficiently47. Finally, the Arp2/3 complex, which nucleates dendritic actin polymerization at the lamellipodium of migrating cells48, also participates in the formation of actin lamellae at the IS, although differently shaped actin can accumulate at the IS in the absence of the Arp2/3 complex, in a formin-dependent manner49.\n\nActin accumulation is also regulated by the function of actin-binding proteins involved in its cross-linking. For example, α-actinin and filamin accumulate at the IS and are required for proper T cell activation in response to antigen-loaded MHC50,51. It is important to note that these two actin cross-linkers also bind directly to the cytoplasmic tail of β integrins52,53 (Figure 2), hence they play a dual function facilitating actin and integrin accumulation at the synapse. Other cross-linkers, e.g. non-muscle myosin II (NMII), are also involved in the formation of efficient synapses. However, the role of NMII in IS formation is controversial. Some studies have shown that NMII affects TCR clustering into the cSMAC54,55, likely due to impaired actin-dependent flux of the TCR towards the contact area56, but other studies suggest a minimal involvement of this molecule in the formation of the IS57,58. The differences between these studies likely reside in the type of T cell and APC used. NMII may play an additional role by regulating the mechanics of the contact interface of the T cell and the APC. In this regard, changes to the rigidity of the APC surface (and NMII inhibition) affect T cell activation59, indicating that the mechanics of the interfacing surfaces also play a role in the process.\n\nTCR and integrin signaling promotes a dramatic redistribution of cellular components in the T cell, most notably the redistribution of the secretory apparatus (centrosome and Golgi, reviewed recently in 60) and machinery involved in the generation of extracellular vesicles61 towards the contact area with the APC (Figure 1, both columns). A major difference with the neuronal synapse is that the secretory apparatus of the APC does not polarize towards the post-synaptic cell (the T cell). This is a crucial event during this process that is often used as a marker of IS maturation. It depends on the activation of microtubule motors, e.g. dynein, which “reel in” the centrosome and the associated secretory elements towards the signaling area. This process has been reviewed in detail elsewhere62–64. In IS formed between CTL and target cells, this polarization ensures the rapid and specific lysis of the target cell (Figure 1, bottom right column, and next two sections). A major argument to explain the polarization of the secretory apparatus in TH cells has emerged recently with the discovery of the unidirectional transmission of microRNA-containing exosomes from the TH cell to the APC65 (Figure 1, bottom left column), which could influence the activation state of the APC, inducing functional activation or anergy of the APC depending on the microRNAs contained in the exosomes.\n\nActin accumulation at the IS facilitates the initial activation of the T cell by immobilizing receptors involved in the contact with the APC and sustaining localized signaling. However, it also constitutes a steric hindrance for polarized secretion. In the early 2000s, Griffiths’ group described the clearance of a part of central actin in maturing cytotoxic IS (Figure 1, right column). Such a zone, containing less actin than its surroundings, coincided with the localization of intracellular granzyme66, suggesting that the region of actin clearance acted as a gate that enabled efficient secretion towards the target cell. However, recent studies have indicated that very small openings in the cortical actin may be sufficient for efficient vesicle delivery67,68. The mechanism of actin clearance at the cytotoxic synapse remains unclear. A recent study indicates that coronin 1A is a key mediator of actin remodeling and clearance at the contact area to form the secretory domain69. The contribution of other actin mediators of depolymerization, e.g. cofilin, has been suggested but not directly demonstrated70. This scenario implicates that the depolymerization signal stems from receptors localized at the CTL side of the IS. An intriguing possibility, untested yet, is that secretory granules directly depolymerize actin at the IS by carrying actin remodeling factors in their surface.\n\nIn the case of pre-primed CTL-contacting target cells bearing antigen-loaded MHC-I, the subsequent steps of this process involve the secretion of granzyme- and perforin-loaded vesicles to kill the target cell (Figure 1, bottom right column). This has been reviewed in detail elsewhere71–73. Before that, naïve CTLs undergo priming (i.e. expression of lytic enzymes and their load into the secretory apparatus) at the secondary lymphoid organs (SLOs) when they enter into contact with mature DCs bearing suitable antigens associated with MHC-I. Direct priming occurs only when a) the pathogen infects and activates DCs directly and b) the pathogen-infected cell (or tumor cell) migrates directly into the SLO. Importantly, the establishment of IS between naïve CTLs and immature DCs leads to cross-tolerance, i.e. the inability of the CTL to activate properly74. This is likely an important mechanism of induction of tolerance involved in tumor evasion.\n\nOn the other hand, TH–APC contacts trigger a transcriptional program that results in the activation of the TH, including expression of activation markers, e.g. CD69 and CD25, and cytokine secretion, e.g. IFN-γ and IL-2 (Figure 1, bottom left column). The main function of these cytokines is to create an activating microenvironment for other immune cells in a paracrine manner. At the site of infection, these cytokines activate other effector cells, particularly macrophages involved in pathogen clearance, CTLs, and NK cells.\n\nAdditional molecules induced by the establishment of IS include mediators of cell proliferation downstream of NF-AT, AP1, and NF-kB (reviewed in 75) as well as receptors implicated in the migration of the activated cell to the inflammatory site, e.g. CCR576.\n\nThe specific signals that promote termination of the IS are unclear. In the case of IS of CTL with target cells, a clear candidate to promote termination of the contact is the flip-flop of the plasma membrane of the target cell due to the effect of the lytic enzymes secreted by the CTL. In such a mechanism, the CTL would recognize phosphatidylserine, annexin V, or other components of the inner leaflet of the plasma membrane of the target cell. In the case of naïve CTL or TH cells, the mechanism is less clear but likely involves the exhaustion of the TCR recycling process over extended periods of stimulation77. Importantly, signaling molecules involved in the formation and function of the IS, e.g. PKCtheta, are also involved in synapse breakdown, constituting a possible mechanism of early remodeling of the IS78.\n\n\nConcluding remarks: towards the application of manipulating the IS in biomedicine\n\nIn recent years, the need for new therapies against multidrug-resistant tumors and the secondary effects of current therapies, e.g. chemotherapy, have led to the study and the development of better \"targeted\" therapies with less deleterious side effects for patients. Therefore, enhancing the ability of the immune system to detect and remove pathological cells through recognition of tumor or different expression patterns of the target cells is a crucial step to develop better therapies. Another important issue is to counteract the evasive mechanisms developed by pathogens and tumor cells.\n\nOne approach aimed at improving the immune response against tumor cells consists of autologous or allogeneic tumor vaccination (Figure 3, top right). These approaches are aimed at generating strong CTL responses against tumor cells based on their specific molecular makeup. The underlying mechanism consists of vaccine-mediated CTL priming by vaccine-stimulated APC (mainly DCs), which would then home to the tumor and rapidly form an IS with the tumor cells, killing them. Several trials based on this approach are reviewed here79. Another possibility is the genetic immunization of patients (DNA vaccination) through DCs. The major limiting factor is the need for safe and specific carriers. An attractive possibility is the use of in vivo DC-targeting liposomal DNA vaccine carriers80.\n\nTop left, poorly responding T cells are treated with antibodies that block inhibitory molecules such as CTLA-4 and PD-1, or inhibitory ligands of the latter, e.g. PD-L1/2. Bottom left inlay, representation of the effect of anti-CTLA-4 blockade, which blocks inhibitory signals emanating from CTLA-4 that counteract TCR/CD3-dependent signals and also releases CD80 to co-stimulate via interaction with CD28; also depicted is the effect of anti-PD-1 or anti-PD-L1/2 monoclonal antibodies (mAbs), which prevent their interaction and the generation of inhibitory signals. Top right, direct vaccination of dendritic cells with tumor DNA or autologous or allogeneic tumor extracts. Bottom right, either treatment should enhance T cell response against tumor antigens.\n\nApproaches aimed at suppressing the effects of the evasive maneuvers of tumor cells have also been tested in recent years (Figure 3, top left). For example, tumor cells are believed to promote the expression of CTLA-4, which is a molecule expressed by T cells that competes with CD28 for the co-stimulatory molecule CD80 (B7.1), thereby suppressing T cell activation. The US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have approved the use of a humanized monoclonal antibody against CTLA-4 for the treatment of late-stage melanoma81. Similar approaches have been developed for PD-1, which is another inhibitory receptor that suppresses T cell responses independent of CD28 but dependent of its ligands PD-L1 and PD-L2, which are abundantly expressed by several types of tumor cells82. A number of antibodies against PD-1 and PD-L1/2 are being developed by big pharmaceutical companies aiming to find different anti-tumor therapies83–85. At a molecular level, CTLA-4 binding to CD28 disrupts TCR clustering, effectively destabilizing the IS86. Likewise, PD-1 accumulation at the IS recruits protein phosphatases, such as SHP-2, that quench the stimulating signals emanating from the synapse87.\n\nClearly, these studies and novel forms of treatment are of outstanding importance in the development of new treatments for the more aggressive and less-tractable types of cancer and are likely the beginning of a new era of molecular treatment of cancer.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nMiguel Vicente-Manzanares is funded by the Ramon y Cajal Program (RYC2010-06094) and grants SAF2014-54705-R from MINECO and the BBVA Foundation.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nThe authors thank fellow F1000 Faculty member Francisco Sanchez-Madrid for critical reading of the manuscript and Drs Michael Dustin and Pedro Roda-Navarro for their insights as part of the peer review process. We also regret a large number of studies that had to be left out due to space limitations.\n\n\nReferences\n\nNorcross MA: A synaptic basis for T-lymphocyte activation. Ann Immunol (Paris). 1984; 135D(2): 113–34. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPaul WE, Seder RA: Lymphocyte responses and cytokines. Cell. 1994; 76(2): 241–51. 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PLoS Biol. 2011; 9(9): e1001151. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMace EM, Orange JS: Lytic immune synapse function requires filamentous actin deconstruction by Coronin 1A. Proc Natl Acad Sci U S A. 2014; 111(18): 6708–13. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMace EM, Dongre P, Hsu HT, et al.: Cell biological steps and checkpoints in accessing NK cell cytotoxicity. Immunol Cell Biol. 2014; 92(3): 245–55. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSusanto O, Trapani JA, Brasacchio D: Controversies in granzyme biology. Tissue Antigens. 2012; 80(6): 477–87. PubMed Abstract | Publisher Full Text\n\nWilliams MA, Bevan MJ: Effector and memory CTL differentiation. Annu Rev Immunol. 2007; 25: 171–92. PubMed Abstract | Publisher Full Text\n\nStinchcombe JC, Griffiths GM: Secretory mechanisms in cell-mediated cytotoxicity. Annu Rev Cell Dev Biol. 2007; 23: 495–517. PubMed Abstract | Publisher Full Text\n\nMelief CJ: Mini-review: Regulation of cytotoxic T lymphocyte responses by dendritic cells: peaceful coexistence of cross-priming and direct priming? Eur J Immunol. 2003; 33(10): 2645–54. PubMed Abstract | Publisher Full Text\n\nPadhan K, Varma R: Immunological synapse: a multi-protein signalling cellular apparatus for controlling gene expression. Immunology. 2010; 129(3): 322–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nEbert LM, McColl SR: Up-regulation of CCR5 and CCR6 on distinct subpopulations of antigen-activated CD4+ T lymphocytes. J Immunol. 2002; 168(1): 65–72. PubMed Abstract | Publisher Full Text\n\nLasserre R, Cuche C, Blecher-Gonen R, et al.: Release of serine/threonine-phosphorylated adaptors from signaling microclusters down-regulates T cell activation. J Cell Biol. 2011; 195(5): 839–53. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSims TN, Soos TJ, Xenias HS, et al.: Opposing effects of PKCtheta and WASp on symmetry breaking and relocation of the immunological synapse. Cell. 2007; 129(4): 773–85. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSrivatsan S, Patel JM, Bozeman EN, et al.: Allogeneic tumor cell vaccines: the promise and limitations in clinical trials. Hum Vaccin Immunother. 2014; 10(1): 52–63. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGaru A, Moku G, Gulla SK, et al.: Genetic Immunization With In Vivo Dendritic Cell-targeting Liposomal DNA Vaccine Carrier Induces Long-lasting Antitumor Immune Response. Mol Ther. 2016; 24(2): 385–97. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLipson EJ, Drake CG: Ipilimumab: an anti-CTLA-4 antibody for metastatic melanoma. Clin Cancer Res. 2011; 17(22): 6958–62. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nNoh H, Hu J, Wang X, et al.: Immune checkpoint regulator PD-L1 expression on tumor cells by contacting CD11b positive bone marrow derived stromal cells. Cell Commun Signal. 2015; 13: 14. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTopalian SL, Hodi FS, Brahmer JR, et al.: Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012; 366(26): 2443–54. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBrahmer JR, Tykodi SS, Chow LQ, et al.: Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med. 2012; 366(26): 2455–65. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nRibas A: Tumor immunotherapy directed at PD-1. N Engl J Med. 2012; 366(26): 2517–9. PubMed Abstract | Publisher Full Text\n\nJackman RP, Balamuth F, Bottomly K: CTLA-4 differentially regulates the immunological synapse in CD4 T cell subsets. J Immunol. 2007; 178(9): 5543–51. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nYokosuka T, Takamatsu M, Kobayashi-Imanishi W, et al.: Programmed cell death 1 forms negative costimulatory microclusters that directly inhibit T cell receptor signaling by recruiting phosphatase SHP2. J Exp Med. 2012; 209(6): 1201–17. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "13123",
"date": "31 Mar 2016",
"name": "Michael Dustin",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13130",
"date": "31 Mar 2016",
"name": "Pedro Roda-Navarro",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-418
|
https://f1000research.com/articles/5-415/v1
|
30 Mar 16
|
{
"type": "Opinion Article",
"title": "A failure to reproduce: How bad biomedical science is holding us back",
"authors": [
"Hussein Jaafar",
"Robert M. Maweni",
"Robert M. Maweni"
],
"abstract": "Irreproducibility is a common problem in the biomedical sciences. Numerous studies have revealed the systemic and chronic nature of the problem, yet not enough is being down to combat it. The financial cost is estimated to be 28 billion dollars in the United States alone. Combine this financial cost with the time spent on irreproducible studies and the net effect is staggering. The factors for this lack of reproducibility are however identifiable and concrete steps can be taken to improve the situation. This article describes some of the factors leading to irreproducibility in the biomedical sciences and how stakeholders at every level of the field can act to reverse them.",
"keywords": [
"Reproducibility",
"Biomedical Science",
"Irreproducibility",
"publishing",
"funding",
"standards and practises",
"institutions"
],
"content": "A tale of two papers\n\nIn 2005 a paper was published by Dr. John Ioannidis entitled “Why most published research findings are false” (Ioannidis, 2005b). It was essentially Dr. Ioannidis’s claim that “false findings may be the majority or even the vast majority of published research claims”. The strange thing about this paper was that it wasn’t exaggerating.\n\nIn his paper Dr. Ioannidis used a mathematical proof that assumed modest levels of researcher bias. This bias could be human error, bad methodology or any number of other factors. He argued that a sufficiently motivated researcher that wishes to prove a theory correct, can do so most of the time regardless of whether the theory is actually correct. The rates of “wrongness” his model predicted in various fields of medical research corresponded to the observed rates at which findings were later refuted. And these rates of “wrongness” were not insignificant. 80 percent of non-randomized studies, 25 percent of “gold-standard” randomized trials and even as much as 10 percent of the “platinum-standard” large randomized trials turn out to be irreproducible.\n\nA second paper by Dr. Ioannidis was published that same year. In this paper Dr. Ioannidis looked at 49 of the most citied articles in the most citied journals (Ioannidis, 2005a). 45 of these papers claimed to have described effective interventions for various diseases ranging from heart attacks to cancer. Of these 45, seven were contradicted by subsequent studies, seven others had their reported effects diminished by subsequent studies and 11 were largely unchallenged. Only 20/45 (44%) of the field guiding papers had been replicated successfully. And in a finding that shows how these irreproducible papers are impacting the field, Dr. Ioannidis found that even when a research paper is later soundly refuted its findings can persist, with researchers continuing to cite them as correct for years afterwards.\n\nThe counterargument is of course that despite all this the system clearly does work on the whole. Even if mistakes are being made and inefficiency is rampant, if something is wrong it will eventually be found out and corrected. Take for example the now infamous recent controversy regarding stimulus-triggered acquisition of pluripotency cells or STAP cells. Published in Nature, these two papers were considered a massive breakthrough in stem cell research (Obokata et al., 2014a; Obokata et al., 2014b). However very quickly problems emerged with the data presented in the paper. An investigation by the hosting institute found the lead investigator guilty of misconduct and the papers were subsequently retracted (Editorial, 2014). This is one example showing how the checks and balances in place within biomedical research can work and work well. Despite these measures the price of irreproducible research remains a substantial one.\n\n\nThe price we pay\n\nA recent study estimated the cost of irreproducible pre-clinical research at 28 billion dollars in the US alone (Freedman et al., 2015). The study estimated the overall rate of irreproducibility at 53%, but warned that the true rate could be anywhere between 18% and 89%. While the exact figures are certainly debateable the clear message is that this is a significant issue even if we assume the rate of irreproducibility is at the lower end of their scale. Even big pharma companies have noted the lack of reproducibility coming from academia. They report that their attempts to replicate the conclusions of peer-reviewed papers fail at rates upwards of 75% (Prinz et al., 2011).\n\nGoing hand in hand with the financial costs we cannot forget about the time invested on these irreproducible studies. One could argue that this is indeed the more damaging factor given that it slows the development of potentially lifesaving treatments and interventions that would significantly improve quality of life for large proportions of society. This is of course an even more difficult if not impossible metric to measure accurately but it logically must be impacted upon. For example consider this: a researcher has a hypothesis and carries out 3 experiments to test this hypothesis. The first 2 experiments are successful and seem to confirm the researcher’s hypothesis. The findings from these first two experiments are thus published. This naturally leads to a third experiment which seems to strongly disprove the hypothesis and so the researcher abandons this line of work to move onto something else. The researcher is unlikely to publish the findings of the third experiment but the 2 other papers will remain published. This may lead other research groups to continue this work from the first 2 papers, perhaps even carrying out the same failed experiments, unware that it had already been tried and rejected. Again it is difficult to know how often something like this happens simply because we don’t know how often researchers are leaving their negative results unpublished. However even a cursory read through some biomedical journals will reveal that papers with negative results are few and far between.\n\nYet another group that believes this is a major issue in need of addressing is the Global Biological Standards Institute or GBSI. The GBSI carried out a study in which they interviewed 60 individuals throughout the life science community including biopharmaceutical R&D executives, academic & industry researchers, editors of peer-reviewed journals, leaders of scientific professional societies, experts in quality management, experts in standards, academic research leaders and many more disciplines (GBSI, 2013). In the extensive interviews with these professionals a systemic and pervasive problem with reproducibility was reported. Over 80% of academic research leaders they interviewed had some experience with irreproducibility. The reasons for this irreproducibility included inconsistencies between labs, non-standardised reagents, variability in assays, cell lines, experimental bias, differences in statistical methods, lack of appropriate controls and several others.\n\n\nWhy we falter\n\nThere is a perception amongst the general public that scientists are a group of meticulous, highly organised, extremely intelligent section of society (Castell et al., 2014). This perception is certainly not without a basis in reality but fails to appreciate the human aspect of scientists and our work. Mistakes happen, negligence occurs. Politics, money, bureaucracy and rivalries all get in the way of scientific research (GBSI, 2013; Wilmshurst, 2007). This all happens on a pretty regular basis according to the GBSI report with one researcher quoted as saying “We’ve had to address issues with replicating published work many times. Sometimes it’s a technical issue, sometimes a reagent issue, sometimes it’s that the technique was not being used appropriately” (GBSI, 2013). Within the biomedical research community these obstacles are a disliked but tolerated part of doing science. They are unfortunately sometimes considered part of the job and just how the system works as is demonstrated by their prevalence (Tavare, 2012; Wilmshurst, 2007).\n\nThis is a dangerous and irresponsible attitude to allow to continue within our community. It is precisely because of our line of work that we should seek to uphold to highest professional and academic standards. Our work which can quite literally be the difference between someone living or dying, or having to suffer from debilitating illness on a daily basis. Just because our impact is delayed by its long journey from bench to bedside does not make it any less crucial to people’s lives.\n\nYes, there are reasons for things being the way they are. The publishing process is outdated. There’s never enough funding to go around and what little there is goes often has strict criteria attached to it (Editors, 2011). When applying for positions in academia, publications are king with quantity being above quality or accuracy in many cases and these publications are being dominated by a select few in the field (Ioannidis et al., 2014). It is therefore unfortunately often necessary for scientists to play the game and submit to the demands of the system. Corners are cut, statistics are “reinterpreted” and results exaggerated all in the hopes of getting past the journals review panel, or having a grant proposal approved (Baker, 2016; GBSI, 2013). None of this is maliciously done of course, at least not usually, but malicious or not the negative effects are the same. Whatever the reason it’s still bad science.\n\n\nThe solutions\n\nSo what is the solution? First we must appreciate that the problems leading to this situation are clearly multifaceted and require concerted efforts from groups and individuals at all levels throughout the community. We will discuss 4 of the main areas that could be improved upon.\n\nOne change that could have the most wide reaching effect would be a greater emphasis on the importance of replicability in studies. Just as the number of citations a researcher has today is considered an important metric for the quality of their work, the number of a researcher’s papers that have been reproduced by other groups should be strongly considered too. Standardised metrics such as this will help place greater importance on the quality of a piece of work, rather than just the exciting nature of its claims. This can help us to reduce the pressure to publish in the highest impact factor journals. With standardised metrics the prestige of a journal won’t necessarily matter as long as the papers quality metrics are solid.\n\nFor this to work however journals need to be more accepting of papers whose sole purpose is to reproduce or confirm another group’s work instead of favouring papers that report new discoveries or interventions. In addition journals could allow researchers to pre-register their planned experiments with them in exchange for a potential fast track to publication if they then carry out those experiments, even if they give negative results. This would go a long way to improving transparency and encouraging researchers to not discard unfavourable experiments. It would also help avoid situations like the one we discussed above where researchers continued to work on the basis of experiments they were unaware had already been disproven. Some examples of initiatives moving towards these goals include the All Trials campaign and the registered reports approach (AllTrials, 2016; Chambers, 2016).\n\nNext there needs to be an expanded development and adoption of standards and best practices. Standards can be physical standards like standardised assays and cell lines or they can be documental standards such as protocols and practises. To do this guidelines for best practises and standards need to be easily accessible and widely available, which is one of the aims of the EQUATOR network (EQUATOR, 2016). Improvement in standards is arguably the most important factor for increasing reliability but given its wide ranging, complicated and technical nature we will leave discussion of it for others to pursue.\n\nSimilar to journals, funding bodies could introduce mechanisms to reward reproducibility in a researcher’s work. They should look at an investigator’s past record with producing reproducible work (new journal metrics would complement this) and also look at his/her current grant application to see if it’s set up to produce reproducible results. The NIH for example has introduced new guidelines beginning in January 2016 to improve reproducibility in grant in applications (NIH, 2016). The 4 main areas the guidelines seek to address include the scientific premise of the proposed research, rigorous experimental design for robust and unbiased results, the consideration of relevant biological variables and the authentication of key biological and/or chemical resources proposed in a grant application.\n\nFinally and perhaps ultimately, the responsibility of producing high quality reproducible work is down to the principle Investigators, their lab group and the institution that hosts them. These are the people that can have the most immediate impact through self-correction and adherence to the best standards and practises whenever and wherever possible.\n\n\nThe bottom line\n\nThis article is in no way all-encompassing regarding the issue of reproducibility. Several problems and solutions exist which we have not discussed in detail, not least of which the troubling subject of researcher bias, for example. The references below do however discuss some of these in greater detail. Many will argue that implementing the above proposals will of course require additional work and possibly some significant upfront costs but we would counter that the longer term impact to biomedical research would be immense and one we cannot afford to miss out on.",
"appendix": "Author contributions\n\n\n\nHJ conceived of the article topic. HJ and RM contributed to researching, writing and referencing the article. HJ drafted the manuscript which RM reviewed and agreed to the final content therein.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nAcknowledgments\n\nThank you to Matt, Laura and Zein for reading and advising me in the course of writing this article.\n\n\nReferences\n\nAllTrials: All Trials Registered. All Results Reported. AllTrials, 2016. Reference Source\n\nBaker M: Statisticians issue warning over misuse of P values. Nature. 2016; 531(7593): 151. PubMed Abstract | Publisher Full Text\n\nCastell S, Charlton A, Clemence M, et al.: Public Attitudes to Science Ipsos MORI. 2014. Reference Source\n\nChambers C: Registered Reports: A step change in scientific publishing. Elseviercom, 2016. Reference Source\n\nEditorial N: STAP retracted. Nature. 2014; 511(7507): 5–6. PubMed Abstract | Publisher Full Text\n\nEditors T: Dr. No Money: The Broken Science Funding System. Sci Am. 2011. Reference Source\n\nEQUATOR: About us | The EQUATOR Network. 2016. Reference Source\n\nFreedman LP, Cockburn IM, Simcoe TS: The Economics of Reproducibility in Preclinical Research. PLoS Biol. 2015; 13(6): e1002165. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGBSI: The Case for Standards in Life Science Research: Seizing Opportunities at a Time of Critical Need. Global Biological Standards Institute, 2013. Reference Source\n\nIoannidis JP: Contradicted and initially stronger effects in highly cited clinical research. JAMA. 2005a; 294(2): 218–228. PubMed Abstract | Publisher Full Text\n\nIoannidis JP: Why most published research findings are false. PLoS Med. 2005b; 2(8): e124. PubMed Abstract | Publisher Full Text | Free Full Text\n\nIoannidis JP, Boyack KW, Klavans R: Estimates of the continuously publishing core in the scientific workforce. PLoS One. 2014; 9(7): e101698. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNIH: Rigor and Reproducibility. 2016. Reference Source\n\nObokata H, Sasai Y, Niwa H, et al.: Bidirectional developmental potential in reprogrammed cells with acquired pluripotency. Nature. 2014a; 505(7485): 676–680. PubMed Abstract | Publisher Full Text\n\nObokata H, Wakayama T, Sasai Y, et al.: Stimulus-triggered fate conversion of somatic cells into pluripotency. Nature. 2014b; 505(7485): 641–647. PubMed Abstract | Publisher Full Text\n\nPrinz F, Schlange T, Asadullah K: Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov. 2011; 10(9): 712. PubMed Abstract | Publisher Full Text\n\nTavare A: Scientific misconduct is worryingly prevalent in the UK, shows BMJ survey. BMJ. 2012; 344: e377. PubMed Abstract | Publisher Full Text\n\nWilmshurst P: Dishonesty in medical research. Med Leg J. 2007; 75(Pt 1): 3–12. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13424",
"date": "20 Apr 2016",
"name": "Gary G Borisy",
"expertise": [],
"suggestion": "Not Approved",
"report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nJaafar and Maweni are entitled to their opinion but I don't believe they have contributed in a sufficiently significant way to warrant being indexed. They provide no original analysis of their own; they provide a brief overview of contributions by other authors and they provide only a brief, cursory statement of \"solutions\". The proposed solutions in part reiterate suggestions of others but a more serious problem is that they miss the mark in how basic research is actually done. Productive researchers rarely replicate previous work explicitly. They build on previous work. To successfully build essentially validates the previous work but the point of research is to extend into the unknown, not to merely replicate. From this point of view, the emphasis on 'reproducibility' in their solutions does not capture the heart of the matter.",
"responses": [
{
"c_id": "1938",
"date": "21 Apr 2016",
"name": "Hussein Jaafar",
"role": "Author Response",
"response": "Thank you for your review Dr. Borisy. We would like to respond to your critiques.“They provide no original analysis of their own; they provide a brief overview of contributions by other authors and they provide only a brief, cursory statement of \"solutions\".This critique is understandable however this is an opinion article and as such is it intended to be brief and not all encompassing, as a full review might be. According to F1000Research guidelines \"Opinion Articles give the authors’ perspective on a topical issue, providing a balanced view of different opinions in the field\". We believe this article achieves this. As such your comment about not providing an original analysis is a little perplexing. This is not a piece of research nor does it proclaim to be. The purpose of an opinion article as we see it is to gather relevant information and present that information in a logical and educational format, along with, of course, our opinions on the matter.“The proposed solutions in part reiterate suggestions of others but a more serious problem is that they miss the mark in how basic research is actually done. Productive researchers rarely replicate previous work explicitly. They build on previous work. To successfully build essentially validates the previous work but the point of research is to extend into the unknown, not to merely replicate.”It is true that basic research builds on previous work and success would validate that previous work. But the point of this article is to highlight the fact that in the process of building on that previous work much time and money is wasted on research that is simply incorrect. We are not suggesting that the point of research is to merely replicate. We are saying that it would be of great benefit to science if we could make our experiments more replicable from the onset and subsequently emphasize and merit researchers whose work can be consistently replicated (either by building on it or by explicitly replicating it).It’s important for us to highlight that when we use the word “reproducible” we are clearly emphasising the implementation of procedures and systems which would encourage reproducibility at the experimental design stage. We are not exclusively speaking about reproducing already completed studies. We are talking about making experiments inherently more likely to be successfully reproduced from the get go, thus saving a lot of time and money down the road."
}
]
},
{
"id": "13428",
"date": "09 May 2016",
"name": "Krzysztof Gorgolewski",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis is a very well written paper discussing the important and timely topic of reproducibility. As an opinion piece it is factually accurate, but despite promising introduction to the topic, it provides very little in terms of practical solutions. Listed proposal lack detail (How is the replication going to be defined in the new metric? Who decides if experiment A replicates experiment B? Why would commercial publishers bother implementing and maintaining such metric?) and poor understanding of the complex system of incentives in the academic world (Why the NIH does not have a stronger position on replicability and data sharing? Why there aren’t enough good quality standards in life sciences? Why PIs chase high impact factor journals instead of replicating other people work?).Unless the second part of the paper undergoes a major revision and provides practical, detailed and feasible solutions I doubt this publication will have a non-negligible influence on the reproducibility crisis.Other comments:You say “When applying for positions in academia, publications are king with quantity being above quality (...)” - all I keep hearing is that it takes one Nature paper to get a tenure. Do you have any evidence of the “more papers is better than good papers in terms of landing a job” claim? You also mention the it is hard to assess how many null results are not published. However, in the context of meta-analysis there are techniques to assess publication bias from the expected shape of the effect size distribution. Isn’t there any piece of meta-research assessing what percentage of experiments should by chance yield a null result? It would be definitely worth looking for.",
"responses": []
},
{
"id": "13423",
"date": "15 Jul 2016",
"name": "Neil Chue Hong",
"expertise": [],
"suggestion": "Not Approved",
"report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI carry out this review following the guidelines set in \"An Open Science Peer Review Oath\".\nThere have been increasing scrutiny of the many fields of research, with reproducible research being used as one of the key drivers for many different concerns: trust, economic efficiency, reliability, transferability of research research.\nThis opinion article by Jaafar and Maweni presents an overview of previous research, current status of and potential solutions for irreproducibility in the biomedical sciences.\nOverall, I thought the structure and style of the paper was suited to an opinion article, but felt that in its current version it lacked the \"authors’ perspective on a topical issue that has not yet been covered in the same way in the existing literature\". Basically, it does not cover more ground or add the unique perspective of the authors to make it stand out from existing articles in this area.\nWhilst the authors have done a good job of collecting together an up-to-date reference list of studies in the area, it's not clear to me that the opinions they express in the article move the discussion on further from comment pieces such as Begley or work by journals. Many of their arguments are at a high level e.g. advocating for adopting of standards is not backed up with an opinion on which types of standards will lead to improvements in which particular types of reproducibility.\nI think that the area where the authors could most readily formulate, justify and argue an opinion would be in the area of investigators and institutions - what are their roles, and how do they interact. Do the authors perceive the drivers of each to be complementary or divisive? What will this mean for the future of biomedical research?\nTo do this, I think they need to extend their literature search to cover more on the related work to do with trends in the way research is being carried out in the biomedical sciences, and related work on the influences and incentives for principal investigators, researchers and heads of research of at institutions carrying out the research, and then provide an opinion on whether these can be used to address the issues of irreproducibility in the biomedical sciences that they summarise.\nIn addition, I think it would be useful in an opinion piece to give some element of personal perspective - as researchers working in the field of biomedical sciences themselves, the authors could give an opinion on how it affects them in their day to day work, and what solutions they feel would work if applied in their own institutions.\nI am categorising this as \"Not approved\" as even though my criticisms of the piece could be addressed with specific, major revisions, I believe that this opinion article needs substantial new material to be added for it to be a useful addition to the literature in this area and therefore does not meet the criteria for an F1000 opinion article. A revision of the paper, concentrating on extending the second half would be the most obvious suggestion to address this. As an alternative suggestion to the authors, it may be that this article would be better presented as a review article if taken forward in its current form.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-415
|
https://f1000research.com/articles/4-483/v1
|
05 Aug 15
|
{
"type": "Software Tool Article",
"title": "Towards reproducible research: From data analysis (in R) to a typeset laboratory notebook (as .pdf) using the text editor Emacs with the 'mp' package",
"authors": [
"Christopher Dardis",
"Eric C Woolf",
"Adrienne C Scheck",
"Eric C Woolf",
"Adrienne C Scheck"
],
"abstract": "Much scientific research makes use of commonly available ’office’ software. While numerous more fully-featured open-source alternatives exist, the integration of diverse tools and platforms which their use often entails can be challenging. The mp package for Emacs aims to bring together a number of these elements with the goal of simplifying the process of converting an .R file, as used for data analysis, to a nicely formatted .pdf which includes the complete description of an experiment. We discuss the rationale for development of the package and illustrate its applications and options with a series of experiments from our laboratory.",
"keywords": [
"latex",
"R",
"knitr",
"emacs",
"reproducible research",
"beta-hydroxybutyrate",
"melanoma",
"brain metastases"
],
"content": "Introduction\n\nOne of the primary goals of any experimental research is to produce a nicely typeset document which explains the methods and results. This should be sufficient to allow the reader to recreate the work and thus to verify the results (given the correct tools).\n\nIn practice, much research is documented by adapting existing ‘office’-type software for this purpose (Microsoft, OpenOffice etc.). While there is much to be said for the ease of use of these techniques, they are not ideally suited to the purpose.\n\nIn particular, those that employ a ‘point-and-click’ graphical user interface (GUI) make it impossible to recreate these steps (mouse movements and clicks). The options for generating graphs and analyzing data are typically limited and often require the use of separate ‘third-party’ software for these steps (e.g. SPSS, GraphPad Prism). This again makes the reproduction of results a challenge.\n\nThere are many free and open source alternatives which are designed with the needs of the laboratory researcher in mind. Ease of use appears to be the principle reason for their lack of widespread use. The mp (for ‘make-pdf’) package came about as an attempt to bring elements from a number of these diverse sources together under one roof. It was also motivated by the repetitive nature of much laboratory research. Successive experiments often differ little in method, so that the analysis often uses the same techniques, with new experimental data being supplied each time.\n\nDetails of the experiment are documented and the R code for analysis is checked as usual; the mp package automates much of the rest of the process with one keystroke. Typesetting is performed using LaTeX, which has become the industry standard for publishers of scientific journals1.\n\nEmacs is the text editor which brings these methods together. Emacs itself has been criticized for lack of ease of use, although if used purely as a text/file editor, as in the examples here, it remains quite simple2. Some familiarity with setting customizable variables is required when moving beyond the default settings for the mp package.\n\nThe examples below do assume some familiarity with R. The transition from familiar GUI-style data-analysis to terminal-based output may appear daunting at first. For those considering taking the plunge, we hope that these simple examples will help to illustrate how easy the R language can be to use. As a long-term investment, we feel that the time taken to become familiar with these methods is likely to be more than compensated by subsequent improvements in the speed and simplicity of workflow.\n\nThere are already a number of tools useful in converting R source code to a nicely displayed .pdf file. The goal of the mp package is to generate such .pdfs ‘at the touch of a button’. It allows for conversion of the source .R file to the final .pdf3. Further editing, when required, is performed on an intermediary (or ‘go-between’) file - either a no-web (.Rnw) or an .org file4,5. mp can also generate documentation for an elisp package from the package’s own source code.\n\nCurrently, there are three widely used converters when generating a .pdf from an .R file. These are:\n\nknitr (‘knitter’).\n\nSweave (‘S-weave’).\n\nEmacs’ own Org mode (herein org-mode).\n\nFollowing the existing trend to name these tools after processes involved in fabric making, we refer to them collectively as ‘entwiners’.\n\nAn allied approach, converting from .org to .Rnw has also been implemented using the ravel package for Emacs6. Another similarly themed project is the pander package for R, which integrates R with the Haskell library pandoc7,8. This could serve as an alternative to any of the above or be used in conjunction with them. For the sake of simplicity, the range of alternatives provided by the following three ‘entwiners’ appears sufficient for most needs.\n\nSweave. The oldest and best-supported of these converters is Sweave9. It is arguably the best integrated with R and remains the standard tool for R package developers writing accompanying vignettes. It remains widely used in generating statistical reports.\n\nIt does suffer from a number of limitations relative to its counterparts. In particular, the displayed code ‘as-is’ has little formatting or use of color.\n\nAlso, by default, only one figure per ‘chunk’ (i.e. block of code) is supported. Outputting multiple figures typically means writing to, and reading from files explicitly in R, which can be tedious to implement.\n\nKnitr. The knitr package for R generates code for display which is arguably ‘prettier’ than Sweave10. It also allows for multiple figures per chunk. It also allows the chunks to be kept in a separate source file - as opposed to requiring them to be part of the .Rnw file. There are more options for the display of terminal output e.g. including error messages. Like Sweave, it can be used to build R package vignettes.\n\nknitr already integrates well with some existing GUI-style .tex editors, particularly LyX. The latter is part of ‘Scientific Workplace’ (SW), which, like mp, tries to make life easier for the laboratory researcher by providing a simplified workspace. In the case of SW, a GUI is preferred to directly editing files11.\n\norg-mode. .org files are arguably easier/more intuitive to read and edit than .tex, particularly for users new to the latter. In particular, tables are much more straightforward to read, create and modify. Also, the use of ‘collapsible’ section headers makes it easy to see the structure of a document at-a-glance before focusing on one section for editing.\n\nOrg-mode in Emacs allows for the export of code chunks/blocks. Like Sweave, org-mode chunks suffer from the drawback that multiple figures per chunk are not supported by default.\n\nWhile org-mode loses the attractive code printing of knitr, some worthy alternatives are provided by the LaTeX package listings12. These include the option to include LaTeX maths markup in the code commentary, for example to display equations.\n\nOrg-mode allows for conversion/export to multiple file types. By default, mp converts .tex to .pdf but alternatives are straightforward, such as to .html or to .MARKDOWN.\n\nIn mp, the settings adopted for listings are modeled on those of the knitr defaults. We acknowledge that they are perhaps not as attractive. These are the same settings used for the code listings in this article.\n\nAn alternative to listings is the minted package for LaTeX. While probably more attractive for code display in general, its use involves a package for another language (Pygments, written for python). Also, outlining multi-page blocks with background coloring is tricky to automate.\n\nMuch scientific research is reported in the form of a summary and it is not traditional for researchers to provide detailed accounts of the original experiments along with the original observations/results made at the time.\n\nThe classic quote on the subject is from Buckheit and Donoho13:\n\nAn article about computational science in a scientific publication is not the scholarship itself, it is merely advertising of the scholarship. The actual scholarship is the complete software development environment and complete set of instructions which generated the figures.\n\nThe same may well be said of biology. With a traditional print-form journal, the constraints of space limit the length of articles and thus providing content as a summary is sensible. However, the option to refer to online-only Supplementary material now obviates such impediments.\n\nSuch supplements may be be valuable for those seeking to reproduce steps in the research. They may also may be of interest to researchers working on closely related problems, particularly by saving time on preparatory work. Providing original data may allow such data to be combined with that from subsequent experiments. Also, analytic techniques beyond those used in the original paper may later be brought to bear by other researchers.\n\nThe details of individual experiments, particularly ‘pilot’ studies of an exploratory nature or those which yielded negative results are likely to be of limited interest to a general readership. Including these resources as supplements appears reasonable.\n\nThe supplements of this main paper illustrate the applicability of the mp software to a series of experiments from our laboratory which demonstrate the inhibitory effects of beta-hydroxybutyrate (BHB) on the growth and migration of a melanoma cell line, selected for its propensity to form brain metastases, in vitro.\n\n\nMethods\n\nPackage details. mp is written in elisp, the native language of Emacs14. The package aims to automate the workflow associated with converting from .R files to .pdfs. Data analysis is done primarily from the .R file directly - in preference to the intermediary .Rnw or .org file, which can become cumbersome.\n\nmp is ‘opinionated’ when generating intermediary files. Certain defaults have been chosen based on the authors’ experience, for example with the settings for the LaTeX hyperref package.\n\nIn order to streamline the whole process, most of the processing takes place asynchronously. That is, document editing can proceed as the Emacs terminal is not ‘frozen’ during the process of .pdf generation.\n\nNo support for caching is provided, although with short documents similar in scale to the examples below this should not result in much loss of performance. The time to compile is <10 secs with an Intel i5-2430M processor for all of the examples given.\n\nThe manual for the mp package is given as Supplementary material (this is generated from the code itself, using an .org intermediary file.).\n\nThe package defines the mp minor mode for Emacs. The only keybinding involves the function mp-mp with Ctrl-Alt-|(usually found above the ‘Return’ key; in Emacs parlance this is also known as C-M-|). This is intended as a gateway to all of the package functions, all of which can also be run individually (or ‘interactively’).\n\nmp-mp will prompt for a filename; if none is supplied, it will look first at the current buffer. If this is not an .R, .Rnw, .org.tex or .el file it will select the appropriate file from the default-directory as that which has most recently modified. Thereafter it will search up the directory tree if no such file is found.\n\nInstead of a filename, the single character ‘p’ may be given to display the appropriate .pdf associated with the current file or directory.\n\nControl flow. A simplified flow diagram of the mp package is presented in Figure 1.\n\nThe red arrow shows the default flow path.\n\nA more detailed diagram, which also shows the customizable variables, is available as Supplementary material (mpFlow.pdf). While the latter may appear complex, all of the functions and variables are accessed through the ‘umbrella’ mp-mp function so that in a typical use case there is no need to alter the default settings.\n\nFor more experienced users, this use of multiple functions and variables allows for highly granular control, if desired.\n\nUse case. A typical use-case for experimental work proceeds as follows:\n\n1. Create a new directory to hold all the files below.\n\n2. Draft the code for analysis in .R. Arbitrary ‘placeholder’ data may be used at this stage.\n\n3. Create a ‘skeleton‘\n\n4. Use the intermediary file generated to draft the experimental protocol.\n\n5. Complete the experiment.\n\n6. Update the .R or intermediary file generated (.Rnw or .org) with the results of the experiment and the conclusions.\n\n7. Generate the final .pdf from the intermediary file.\n\nTypically, the user will begin with an .R file which contains a number of chunks of R code. These are designated by the header ## ---- chunkName. This follows the convention introduced by knitr for naming chunks. Each chunk continues until the following chunk starts.\n\nThe chunks are processed by the option given by the customizable variable mp-entwiner, which is knitr by default.\n\nIf no .Rnw file exists in the current directory, one is created by mp-skeleton-nw. If an .Rnw file does exist, it is updated using mp-update-nw; those chunks matching the names in the .R file are updated and new chunks are added if required.\n\nThe default workflow is shown in Figure 1 by the path through the red arrows. Some of the pros and cons of different choices of mp-entwiner are shown in 11.\n\n‘Hello world’ with mp. We begin with the simplest use case. We create the directory hello and place the contents of Listing 1 into hello.R. With this file open in Emacs, we then run mp-mp with the key combination C-M-|.\n\n\n\n\n\nThe final product, hello.pdf is shown in Figure 2.\n\nThe intermediary file hello.Rnw will be left open in Emacs for further modification and this is shown in Listing 2. There is a lengthy preamble which sets defaults for multiple options, here in LaTeX and R (including knitr). Of course, most of this is not relevant to such a simple example.\n\n\n\n\n\nExamples of use. Some examples more relevant to the laboratory follow. These are summarized in Table 2. These are all available as Supplementary material and we encourage the reader to refer to the relevant files while reading the present article. Further details of the experimental work are given at the end of this section.\n\n* = file available as Supplementary material\n\nThe ‘file-stems’ (i.e. the filename without a suffix) refer to the starting quantity of cells per 12-well plate. ‘sa’ in the last example stands for ‘scratch assay’.\n\nThe variable mp-preamble is used to set some defaults useful for typesetting documentation for the laboratory. For example, the LaTeX package siunitx is used for the correct display of scientific units15.\n\nExample 1: 8k.pdf\n\nExperiment: Establish number of cells required to establish sustained growth. Start with 8000 cells per 12-well plate. Our first aim was to establish the optimal number of B16-F1-Luc2-BR2 cells with which to seed a growth curve. We wished to establish sustained growth over the period of the experiment, without reaching a ceiling (i.e. maximum density).\n\nTypesetting: default settings. The file 8k.R is given in Listing 3:\n\n\n\n\n\nWith the above file open, we call mp-mp to generate the a.pdf; page 1 of the result is shown in part in Figure 3.\n\nAs an intermediary step, the file 8k.Rnw is generated. This is an R no-web file, which is essentially a typical .tex file with the additional code chunks inserted4. The term ‘web’ is not in reference to the world-wide web but to distinguish it from a contemporaneous approach to literate programming known as ‘web’.\n\nWe modify this to add details of the experimental protocol, written in LaTeX. The principal modifications are the use of 12pt for typesetting, which we adopt from hereon and the inclusion of some graphics with the LaTeX subfig package16.\n\nWith 8k.Rnw still open, we call mp-mp again to generate the final .pdf.\n\nExample 2: 16k.pdf\n\nExperiment: Number of cells required to establish sustained growth. 16000 cells per 12-well plate. Again, we tried to establish the optimal number of B16-F1-Luc2-BR2 cells with which to seed a growth curve. We increased the starting number of cells per well from 8000 to 16000. This appeared to be more promising.\n\nTypesetting: using R to generate .tex output. We again begin with an .R file. This time however, we use R to create LaTeX output, rather than displaying the results of a chunk as R code. The output from R is interpreted as LaTeX directly - rather than as typical terminal output. We use the R xtable package for this purpose; there are many good alternatives17.\n\nAn example of R code generating output which can be interpreted by LaTeX is shown in Listing 4.\n\n\n\n\n\nAgain, the .Rnw file needs some modification. The main change is to set the knitr option results= ‘markup ’ to results= ‘asis ’ to allow the results to be interpreted as .tex.\n\nWe can also restructure the document to allow the code output (here, in the form of tables or single lines of terminal output) to be mixed with the main text. This ensures there is no needless duplication of data entry, as is the case in the earlier example.\n\nThe output is shown as Supplementary material in 16k.pdf. Most of the materials and methods are unchanged from 8k.pdf.\n\nExample 3: 16k2.pdf\n\nExperiment: Demonstrate impaired growth in the presence of BHB. 16000 cells per 12-well plate. We sought to determine whether the growth of B16-F1-Luc2-BR2 cells would be impaired in the presence of BHB at a concentration of 10 mmol/L.\n\nDue to the large standard error on day 4, no difference could be demonstrated via a t-test. However comparing linear models with and without treatment did show a significant effect (analysis of variance (ANOVA) p = 0.048).\n\nTypesetting: Using Sweave and XeTeX. Here, we change the variable mp-entwiner to Sweave. We also change mp-latex to XeLaTeX to allow the use of an OpenType font (by default this is ‘Linx Libertine’). While certain OpenType fonts are available as packages for LaTeX, XeTeX allows for a greater range and greater flexibility.\n\nAs in example 2, the output from each chunk is again typically interpreted as .tex (rather than displayed as R code) by including results=tex in mp-Sweave-opts.\n\nSome modifications to the .Rnw file generated follow. There is one chunk where we prefer the output to retain typical R code formatting. Also we need to change the variable mp-Sweave-opts to fig=TRUE for the chunk which produces a plot.\n\nThis example also shows the value of LaTeX for typesetting equations - calculation of correct masses are nicely displayed and easy to follow. This is shown in Figure 4.\n\nExample 4: 32k.pdf\n\nExperiment: Demonstrate impaired growth in the presence of BHB. 32000 cells per 12-well plate. As the preceding experiment was inconclusive, we tried the same technique again, this time using a higher number of cells to start with.\n\nUnfortunately, no observations were taken on day 3 of the experiment. This meant that both the t-test on day 4 and the ANOVA comparing linear models were not significant, although the latter did come close (p = 0.07).\n\nTypesetting: using Org. Changing mp-entwiner to Org allows us to use an .org file as the intermediary step.\n\nThe output from this process is given as 32k.pdf. Again, some minor modifications to the intermediary file are required. In this case we need to change the headers for the chunk which produces a plot to specify the output of graphics (as opposed to text) and to specify an external file for the graphical output.\n\nWe also change some of the results to latex and pp (pretty print) to give examples of different styles of output. 32k.pdf also features a printout of help for an R function.\n\nExample 5: 32k2.pdf\n\nExperiment: Demonstrate impaired growth in the presence of BHB. 32000 cells per 12-well plate. We repeated the preceding experiment and this time there was a conclusive difference between the cell counts in those grown with BHB vs. controls.\n\nTypesetting: Using Org to generate HTML output. This example shows how the .org intermediary can be converted to .html as an alternative to .pdf. Converting to HTML means we lose all but the simplest LaTeX commands and so the document needs to be written in a simpler style. While we lose some of the nice typesetting features of LaTeX, this simplicity has its own attraction.\n\nThese files are faster to produce and smaller than their .pdf counterparts (1/5 the size in this example). HTML is also likely to be simpler to integrate into an existing website and offers the possibility of almost ‘real-time’ reporting of experimental results.\n\nExample 6: sa.pdf\n\nExperiment: Demonstrate impaired cell mobility in the presence of BHB. Here we use a scratch assay18. A line is made in the center of the wells on a 12-well plate with confluent cell growth. Images taken at various timepoints are analyzed with freely available imageJ software. The distance between the cells on either side of the scratch decreases as they migrate back to the center. This corresponds to a decrease in ‘image density’ as measured by imageJ. This may be downloaded from:\n\nhttp://rsbweb.nih.gov/ij/download.html\n\nTypesetting: Emulating a laboratory notebook with XeTeX. The final example shows how a cursive font may be used to mimic a handwritten lab notebook. We set mp-entwiner to knitr and set mp-latex to XeTeX to allow the use of an unusual font. A sample is shown in Figure 5.\n\nWhen combining multiple images on a single page, fitting them into the cells of a table can be helpful for clarity and this example features a number of such tables.\n\nSystem requirements: this should work with any recent version of Emacs, which is platform independent (i.e. works on Windows, Linux, Mac-OS). Version ≥ 24.4 is recommended to allow for automated export of .org to .tex.\n\nTo export to HTML, the elisp package htmlize is required19. Links to the package source may be found at:\n\nhttp://emacswiki.org/emacs/Htmlize\n\nA recent installation of R (>3.0) and TeX (2013 and on) is also assumed. We used TeX Live 2013 for these examples.\n\nThe package should work with LuaTeX as well as LaTeX, although this has not been thoroughly tested.\n\nThe purpose of these experiments was to demonstrate an inhibitory effect of BHB on the growth and migration of a melanoma cell line in vitro. Details of the aims, methods, results and conclusions are given for each experiment separately (see Table 2).\n\nA summary of these experiments would normally make up just one part of an article; further details of the individual experiments could be combined and made available as a supplement. We provide the experiments separately to provide a typical use-case for the mp package.\n\nCells. B-16 melanoma cells were obtained from American Type Culture Collection (ATCC). To facilitate quantitative measurement of tumor growth, they were modified as described previously20. Briefly, the cells were stably transfected with the gene encoding luc2 (luciferase) using the pGL4.51 [luc2/CMV/Neo] vector (Promega Corp, Madison, WI) and FuGENE 6 Transfection Reagent (Roche Applied Science, Indianapolis, IN) following conditions specified by the manufacturer. They were then injected into the heart (the right ventricle) of a mouse. These animals were sacrificed when bioluminescence was detected in the brain. Cells metastatic to the brain were recovered and were put into culture.\n\nThe same procedure was repeated again (injection into mouse heart and recovery of brain metastases). These cells are designated B16-F1-Luc2-BR2.\n\nAnimal handling. This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The protocol was approved by the Institutional Animal Care and Use Committee of St. Josephs Hospital and Medical Center (protocol number 334 (A3510-01)). All surgery was performed under ketamine/xylazine anesthesia, and every effort was made to minimize suffering.\n\nEffects of BHB on growth. Firstly, it was necessary to determine the optimal starting number of cells to use for a growth curve. If the cells are plated too sparsely, they have a tendency not to grow. Likewise if the concentration is too great to start with, then this will make any difference due to the effect of BHB difficult to see. This is complicated further by growing the cells in a circular well - the cells are in closer communication close to the center and more separated close to the edge. In choosing a starting number, we were guided primarily by prior work in our own laboratory.\n\nTo determine whether BHB would inhibit cell growth, we chose a concentration of 10 mmol/L, again based primarily on our prior experience. Under normal conditions, serum BHB has an upper reference limit of 0.3–0.5 mmol/L. Tests of BHB concentration (for patients) are available commercially and can be used in by those adhering to the ketogenic diet. This diet is most commonly employed in the treatment of drug-resistant epilepsy, where serum BHB concentration has been shown to correlate with the degree of seizure control21. In this study of 74 children, median levels were 8–10 mmol/L.\n\nWe chose a concentration of 10 mmol/L in order to be certain that an effect was present, before considering whether lower levels would be similarly efficacious.\n\nEffects of BHB on migration. The scratch assay is a simple and widely used test to assess cell migration. Details of a typical protocol for the technique are available18. Using the same cell line, we sought to illustrate impaired migration in the presence of BHB.\n\n\nResults\n\nAs shown in Figure 6, we were able to demonstrate a difference in growth rates with an initial concentration of cells of 32,000 per well and a BHB concentration of 10 mmol/L. This is shown in full in 32k2.html.\n\nTaken from 32k2.html (Supplementary material).\n\nWe were also able to demonstrate a decrease in cell migration using the scratch assay, as shown in Figure 7, which is taken from sa.pdf.\n\nTaken from sa.pdf (Supplementary material).\n\n\nDiscussion\n\nThe inhibitory effects of BHB on the growth of neoplastic cells has now been observed in a number of cells lines in our laboratory and those of other investigators22. Similarly it has been shown to impair apoptosis and necrosis of the L929 mouse cell line (taken from normal subcutaneous areolar and adipose tissue)23.\n\nImpairment of growth of neoplastic cells due to ketones has been suggested to be in part due to the polyacetylation of histones24. Ketone bodies also impair glycolysis, on which neoplastic cells are more heavily dependent. This occurs in part through inhibition of the activity of phosphofructokinase and hexokinase25,26.\n\nThe finding that inhibition of growth occurs in a cell line selected for their propensity to metastasize to the brain is novel. Brain metastases are a significant contributor to morbidity and mortality in patients with cancer27. We feel that this approach deserves further investigation. In particular, it would be of interest to determine whether the same phenomenon would be observed in breast and lung cancer cell lines with a propensity to metastasize to the brain. It would also be interesting to determine whether the inhibitory effects of BHB on cancer cells are evident in vivo when ketones are given as a dietary supplement with a relatively normal diet - as opposed to the ketogenic diet, which may be challenging to adopt for patients affected by cancer.\n\n\nConclusions\n\nWe have demonstrated here that BHB, at a concentration of 10 mmol/L, is inhibitory to the growth and migration of B16-F1-Luc2-BR2 melanoma cells that were selected for their propensity to form brain metastases.\n\nThe mp package appears to be a useful addition to the tools available for facilitating reproducible research. Future development will likely include increased support for the LaTeX package biblatex. Collaboration and suggestions for improvement are welcome. Please try to address these to the development site on GitHub if possible.\n\n\nData availability\n\nThe datasets for all experiments are available as part of the Supplementary material.\n\nOne of the primary motivations for developing this package was to facilitate sharing of datasets such as these.\n\n\nSoftware availability\n\nhttps://wwww.github.com/dardisco/mp\n\nhttp://dx.doi.org/10.5281/zenodo.2118345\n\nGPL >= 3",
"appendix": "Author contributions\n\n\n\nCD - carried out the experiments (except for the scratch assay), wrote the software, performed the data analysis and drafted the manuscript.\n\nECW - carried out the scratch assay experiment; he was also closely involved in the design and execution of the other protocols.\n\nACS - supervised the experimental protocols and interpreted the results.\n\nAll authors have revised and approved the final manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nAcknowledgments\n\nThe authors would like to thank Students Supporting Brain Tumor Research for their support.\n\nwww.ssbtr.org\n\n\nSupplementary material\n\nManual for mp package. Documentation, including all functions and variables in the package. Generated from the source code. This package is ‘self-documenting’. mp.pdf is the manual for the package, which was generated with mp-el-tex. The option INCLUDESOURCE is set to t, so that the source code is shown for all functions. The intermediary file is .org which allows package documentation to be nicely displayed in list or table format using TeX, as appropriate.\n\nClick here to access the data.\n\nFlow diagram for mp package. An image, showing the control flow for the package, including file types, functions and customizable variables.\n\nClick here to access the data.\n\nEstablish a 5-day growth curve starting with 8,000 cells/well. Example 1; default settings. Intermediary .Rnw file, typeset with knitr.\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6800.s97727\n\nEstablish a 5-day growth curve starting with 16,000 cells/well. Example 2; using R to generate LaTeX output. Intermediary .Rnw file, typeset with knitr.\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6800.s97728\n\nEffects of BHB on growth starting with 16,000 cells/well. Example 3; using Sweave. Intermediary .Rnw file, typeset with Sweave (and XeTeX).\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6800.s97729\n\nEffects of BHB on growth starting with 32,000 cells/well. Example 4; using org-mode. Intermediary .org file, typeset with org-mode and listings.\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6800.s97730\n\nEffects of BHB on growth starting with 32,000 cells/well. Example 5; using org-mode to generate .html output. Intermediary .org file, typeset with org-mode and listings.\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6800.s97731\n\nEffects of BHB on migration, via scratch assay. Example 6; using a cursive font and placing images in a table. Intermediary.Rnw file, typeset with knitr (and XeTeX).\n\nClick here to access the data.\n\nhttp://dx.doi.org/10.5256/f1000research.6800.s97732\n\n\nReferences\n\nLamport L: LaTeX A Document Preparation System–User’s Guide and Reference Manual. pub-AW. 1985. Reference Source\n\nTwidale MB, Jones MC: “let them use emacs”: the interaction of simplicity and appropriation. Int Rep Socio-inform. 2005; 2(2): 78–84. Reference Source\n\nR Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. 2013. Reference Source\n\nRamsey N: Literate programming simplified. IEEE software. 1994; 11(5): 97–105. Publisher Full Text\n\nDominik C: The compact Org-mode Guide. Release 8.2.10. 2014. Reference Source\n\nBerry C: orgmode-accessories: Ravel. 2015. Reference Source\n\nDarczi G: pander: An R Pandoc Writer. R package version 0.3.7. 2013. Reference Source\n\nMacFarlane J: Pandoc. 2013. Reference Source\n\nLeisch F: Sweave: Dynamic generation of statistical reports using literate data analysis. Compstat. 2002, Springer: 575–580. Publisher Full Text\n\nXie Y: knitr: A general-purpose Tool for dynamic report generation in R. R package version 1.4.1. 2013. Reference Source\n\nKarlsson A: Scientific workplace 5.5 and lyx 1.4. 2. J Stat Softw. 2006; 17: 1–11. Reference Source\n\nHeinz C, Moses B, Hoffmann J: The listings package. 1996. Reference Source\n\nBuckheit JB, Donoho DL: Wavelab and reproducible research. Wavelets and Statistics. Springer. 1995; 103: 55–81. Publisher Full Text\n\nLewis B, LaLiberte D, Stallman R, et al.: GNU Emacs Lisp Reference Manual. Free Software Foundation. Revision 3.1, for Emacs Version 24.4. 2014. Reference Source\n\nWright J: siunitx: A comprehensive (si) units package. TUGboat-TeX Users Group. 2011; 32(1): 95. Reference Source\n\nCochran SD: The subfig package. 2005. Reference Source\n\nDahl DB: xtable: Export tables to LaTeX or HTML. R package version 1.7-1. 2013. Reference Source\n\nLiang CC, Park AY, Guan JL: In vitro scratch assay: a convenient and inexpensive method for analysis of cell migration in vitro. Nat Protoc. 2007; 2(2): 329–333. PubMed Abstract | Publisher Full Text\n\nNiksic H: htmlize - Convert buffer text and decorations to HTML. Package version 1.43. 2013. Reference Source\n\nAbdelwahab MG, Fenton KE, Preul MC, et al.: The ketogenic diet is an effective adjuvant to radiation therapy for the treatment of malignant glioma. PLoS One. 2012; 7(5): e36197. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGilbert DL, Pyzik PL, Freeman JM: The ketogenic diet: seizure control correlates better with serum beta-hydroxybutyrate than with urine ketones. J Child Neurol. 2000; 15(12): 787–790. PubMed Abstract | Publisher Full Text\n\nMagee BA, Potezny N, Rofe AM, et al.: The inhibition of malignant cell growth by ketone bodies. Aust J Exp Biol Med Sci. 1979; 57(5): 529–539. PubMed Abstract | Publisher Full Text\n\nCheng S, Chen GQ, Leski M, et al.: The effect of D,L-beta-hydroxybutyric acid on cell death and proliferation in L929 cells. Biomaterials. 2006; 27(20): 3758–3765. PubMed Abstract | Publisher Full Text\n\nRiggs MG, Whittaker RG, Neumann JR, et al.: n-Butyrate causes histone modification in HeLa and Friend erythroleukaemia cells. Nature. 1977; 268(5619): 462–4. PubMed Abstract\n\nNewsholme EA, Randle PJ, Manchester KL: Inhibition of the phosphofructokinase reaction in perfused rat heart by respiration of ketone bodies, fatty acids and pyruvate. Nature. 1962; 193: 270–271. PubMed Abstract | Publisher Full Text\n\nLaManna JC, Salem N, Puchowicz M, et al.: Ketones suppress brain glucose consumption. Adv Exp Med Biol. In Oxygen Transport to Tissue XXX. 2009; 645: 301–306. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPerez-Larraya JG, Hildebrand J: Brain metastases. Neurologic Aspects of Systemic Disease Part III: Handbook of Clinical Neurology. (Series Editors: Aminoff, Boller and Swaab). 2014; 121: 1143. Reference Source\n\nSchulte E, Davison D, Dye T, et al.: A multi-language computing environment for literate programming and reproducible research. J Stat Softw. 2012; 46(3): 1–24. Reference Source\n\nRawal V: Using emacs, org-mode and R for research writing in social sciences: A toolkit for writing reproducible research papers and monographs. 2014: 1–27. Reference Source\n\nHrynaszkiewicz I, Li P, Edmunds S: Open Science and the Role of Publishers in Reproducible Research. CRC Press, 2014. Reference Source\n\nLonza BioResearch: Guideline for generation of stable cell lines. Technical Report CD-DS007, Lonza Cologne, GmbH. 2012. Reference Source\n\nRudolph K: The minted package: Highlighted source code in LaTeX. 2011. Reference Source\n\nRossini AJ, Heiberger RM, Sparapani RA, et al.: Emacs speaks statistics: A multiplatform, multipackage development environment for statistical analysis. J Comput Graph Stat. 2004; 13(1): 247–261. Publisher Full Text\n\nWoolf EC, Stafford P, Abdelwahab MG, et al.: The ketogenic diet potentiates radiation therapy in a mouse model of glioma: effects on inflammatory pathways and reactive oxygen species. Cancer Res. 2013; 73(8): 4441. Publisher Full Text\n\nWoolf EC, Scheck AC: The ketogenic diet for the treatment of malignant glioma. J Lipid Res. 2015; 56(1): 5–10. PubMed Abstract | Publisher Full Text | Free Full Text\n\nScheck AC, Abdelwahab MG, Fenton KE, et al.: The ketogenic diet for the treatment of glioma: Insights from genetic profiling. Epilepsy Res. 2012; 100(3): 327–337. PubMed Abstract | Publisher Full Text\n\nMaurer GD, Brucker DP, Bähr O, et al.: Differential utilization of ketone bodies by neurons and glioma cell lines: a rationale for ketogenic diet as experimental glioma therapy. BMC Cancer. 2011; 11(1): 315. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhou W, Mukherjee P, Kiebish MA, et al.: The calorically restricted ketogenic diet, an effective alternative therapy for malignant brain cancer. Nutr Metab (Lond). 2007; 4(5): 5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSeyfried TN, Kiebish MA, Marsh J, et al.: Metabolic management of brain cancer. Biochim Biophys Acta. 2011; 1807(6): 577–594. PubMed Abstract | Publisher Full Text\n\nSeyfried TN, Mukherjee P: Targeting energy metabolism in brain cancer: review and hypothesis. Nutr Metab (Lond). 2005; 2(1): 30. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTisdale MJ, Brennan RA: Loss of acetoacetate coenzyme A transferase activity in tumours of peripheral tissues. Br J Cancer. 1983; 47(2): 293–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFredericks M, Ramsey RB: 3-Oxo acid coenzyme A transferase activity in brain and tumors of the nervous system. J Neurochem. 1978; 31(6): 1529–1531. PubMed Abstract | Publisher Full Text\n\nSeyfried T: Cancer as a metabolic disease: on the origin, management, and prevention of cancer. John Wiley & Sons. 2012. Reference Source\n\nSkinner R, Trujillo A, Ma X, et al.: Ketone bodies inhibit the viability of human neuroblastoma cells. J Pediatr Surg. 2009; 44(1): 212–216; discussion 216. PubMed Abstract | Publisher Full Text\n\nChris: mp: First release. Zenodo. 2015. Data Source"
}
|
[
{
"id": "10253",
"date": "10 Sep 2015",
"name": "Eric Schulte",
"expertise": [],
"suggestion": "Not Approved",
"report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe report is insufficiently well written for me to evaluate the importance of the suggested tool.The current version of this article is unclear as to (1) the functionality provided by mp, (2) the intended usage model of mp. It also (3) conflates an overly-detailed example with the main paper. Is mp merely a translator from a .R format to multiple text document formats? Does mp perform any processing of the input data? Does mp provide stylistic control of the output from within a particular .R file or only through configuration variables? I don't fully understand the usage model. Is prose written within the .R file itself, or in the automatically generated .org, .Rnw or .tex files? If the former what markup syntax does mp provide? If the later does subsequent evaluations of mp overwrite the manually edited intermediate file? These questions should be addressed early on in the article. Finally, an inappropriate emphasis is placed on the “example” experiment. All portions of the example experiment should be typeset to indicate that they are example and their technical content is not part of this publication and has not been peer reviewed. As it reads the “results” and “discussion” sections seemed to discuss the content of the example more than the content of the tool. While it seems very likely that the mp tool is a significant contribution to the practice of reproducible research, I am unable to evaluate its significance from this article.",
"responses": [
{
"c_id": "1855",
"date": "30 Mar 2016",
"name": "Chris Dardis",
"role": "Author Response",
"response": "Apologies for the delay in responding. Thank you for this review; your points are well-taken. I have tried to clarify things by re-structuring the document and adding some new material. We hope that things will appear simpler if you get a chance to try out the package.1 and 2) Functionality - we have tried to clarify this in the introduction and added a new 'What does mp do?' which should address these points.3) The experiments *are* part of this publication; they are not present for purely illustrative purposes. The original focus of the manuscript was on the experimental work rather than the software; following discussion with the editorial office at F1000 research, we changed the focus to bring the software to the foreground (which is likely to be of more general interest).Arguably, the experiments should have been the subject of a separate paper. However, the experiments are short and simple and some 'negative' results are included. Thus we felt it would be more appropiate to include both together (avoiding needless duplication).Reporting novel methods with new experimental work is reasonably common; it is hard to see how this alone would lead to the conclusion that the material is unworthy of publication.Understandably, it has been challenging to find reviewers willing to assess the quality of the software *and* of the experiments. It would be reasonable to considered the experimental work 'not peer reviewed' at present if you feel that this lies outside your expertise."
}
]
},
{
"id": "11299",
"date": "23 Nov 2015",
"name": "Frank Harrell",
"expertise": [],
"suggestion": "Not Approved",
"report": "Not Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nI cannot approve this article in its current form. The authors may be able to undertake a major revision that makes the paper acceptable.I realize that this is a subjective opinion, but I just cannot agree with the software implementation chosen by the authors, for the following reasons:Even though I've been using Emacs for more than 20 years and am an advocate of it for the user productivity it brings, I cannot agree that Emacs is the best choice of platform for this application. I say that primarily because RStudio provides the most elegant integrated development environment for R and it is elegantly tied to LaTeX and Markdown, two engines that the authors rightfully advocate. The idea of hiding various complexities from researchers is a noble one, but this can be accomplished in more flexible ways using LaTeX packages. For example, a new Github project at https://github.com/harrelfe/rlatex developed by the reviewer provides LaTeX packages spaper and knitrl that streamline reproducible LaTeX reports. Another way to accomplish this is to write R functions that output the needed LaTeX preamble.The authors refer to both Sweave and knitr but knitr has now completely replaced Sweave. In addition, knitr provides an elegant way to specify figure size and captions.",
"responses": [
{
"c_id": "1854",
"date": "30 Mar 2016",
"name": "Chris Dardis",
"role": "Author Response",
"response": "Apologies for the delay in responding. Thank you for this review; we appreciate the points you raise and feel the article has been improved in addressing these.1) I (first author) began with RStudio and used the platform for at least 2 years. Ultimately, I moved entirely to Emacs as I found it to be more productive. While not a fully fledged 'integrated development environment', I found this to be more than compensated for by speed and simplicity, particularly in regards to text editing.Most of my work takes place within R; I did feel that integration with LaTeX within Emacs left something to be desired; hence the current package, which allows me to compile documents without leaving Emacs or 'freezing' my R session/ text editing while waiting for a document to compile.I do acknowledge that RStudio my be a more suitable choice for a particular user. The article has been modified to reflect this; for those who are new to EMACs *and* R/LaTeX integration, I agree that RStudio is likely to be the best initial choice.We are not recommending 'mp' as the 'best' way to achive this integration but rather as a viable alternative to RStudio. Surely having a greater range of tools available can do no harm?2) I did consider developing a package in LaTeX or R for this end. I was not aware of the tools you yourself have created and am grateful to you for bringing them to my attention; I have referenced these in the main paper. I discuss their merits in the new 'Allied approaches' section in the paper. As far as elisp goes, I think it is well suited for the task at hand; not to say that everything could not be done with R or LaTeX. In the case of the former, it's facilities for processing text/ strings are not, in my view, as simple or as developed as those available in elisp. In the case of the latter, I find development in a non-interpreted language to be slower and more challenging.\"knitr has now completely replaced Sweave\" - I disagree; while this may be the case for most practical purposes, Sweave retains the support of R-core and I am not aware of plans for knitr to receive such support. Given the amount of 'legacy' documents generated using Sweave, it is hard to see this changing; thus it will continue to remain important, if increasingly for historical reasons. I agree that knitr should be recommended for most tasks. Sweave does have the advantage of prodcuing .tex files which are simpler to read; it is also a little faster.\"knitr provides an elegant way to specify figure size and captions\" - agreed; which I have highlighted this in the main manuscript."
}
]
}
] | 1
|
https://f1000research.com/articles/4-483
|
https://f1000research.com/articles/5-414/v1
|
30 Mar 16
|
{
"type": "Data Note",
"title": "A curated transcriptome dataset collection to investigate the functional programming of human hematopoietic cells in early life",
"authors": [
"Mahbuba Rahman",
"Sabri Boughorbel",
"Scott Presnell",
"Charlie Quinn",
"Chiara Cugno",
"Damien Chaussabel",
"Nico Marr",
"Mahbuba Rahman",
"Sabri Boughorbel",
"Scott Presnell",
"Charlie Quinn",
"Chiara Cugno",
"Damien Chaussabel"
],
"abstract": "Compendia of large-scale datasets made available in public repositories provide an opportunity to identify and fill gaps in biomedical knowledge. But first, these data need to be made readily accessible to research investigators for interpretation. Here we make available a collection of transcriptome datasets to investigate the functional programming of human hematopoietic cells in early life. Thirty two datasets were retrieved from the NCBI Gene Expression Omnibus (GEO) and loaded in a custom web application called the Gene Expression Browser (GXB), which was designed for interactive query and visualization of integrated large-scale data. Quality control checks were performed. Multiple sample groupings and gene rank lists were created allowing users to reveal age-related differences in transcriptome profiles, changes in the gene expression of neonatal hematopoietic cells to a variety of immune stimulators and modulators, as well as during cell differentiation. Available demographic, clinical, and cell phenotypic information can be overlaid with the gene expression data and used to sort samples. Web links to customized graphical views can be generated and subsequently inserted in manuscripts to report novel findings. GXB also enables browsing of a single gene across projects, thereby providing new perspectives on age- and developmental stage-specific expression of a given gene across the human hematopoietic system. This dataset collection is available at: http://developmentalimmunology.gxbsidra.org/dm3/geneBrowser/list.",
"keywords": [
"transcriptomics",
"fetal",
"peripheral blood",
"umbilical cord blood",
"immune ontogeny",
"hematopoietic cells",
"PBMC",
"T cells",
"Tregs",
"B cells"
],
"content": "Introduction\n\nHuman immune defenses are highly dynamic and vary with age, reflecting the different environmental challenges and needs for adaptation during the fetal, neonatal and postnatal period, and throughout life. Not surprisingly, functional differences of the human immune system are most profound very early in life due to the limited antigen exposure in utero, and a variety of developmental, maternal, nutritional, and environmental factors that can act in concert to modulate innate and adaptive effector functions of hematopoietic cells1–3. At the same time, newborns and young infants are particularly vulnerable to infection, with each developmental stage representing a ‘window of vulnerability’ to a very specific subset of pathogenic microbes4. In this context, an increasing number of studies have been designed to gain a deeper understanding of immunity in early life, and ultimately, to reveal the underlying immune defense and regulatory mechanisms that determine the clinical outcome of primary infections, and responses to early childhood vaccination1–3. Nonetheless, our understanding of the developing immune system in early life remains very limited, in part because of the difficulty to access biological specimen from human fetuses, neonates, and young children. Most often, in vitro studies utilizing umbilical cord and peripheral blood samples were used to assess neonatal immune defenses, and in particular to reveal critical differences in the functional programming of neonatal hematopoietic cells in comparison to that of adults. Aside from the limited repertoire of memory B and T lymphocytes in neonates, such studies have revealed substantial gestational- and postnatal age-dependent differences in the phenotype and function of a variety of hematopoietic cell types upon in vitro stimulation of (whole) cord/peripheral blood and isolated blood mononuclear cells with a variety of immune stimulators and modulators, including purified Toll-like receptor (TLR) and RIG-I-like receptor (RLR) agonists, cytokines, and whole pathogens, which engage a variety of pattern recognition receptors (PRRs) and signaling pathways5–14. The underlying reasons for the functional differences between hematopoietic cells obtained at different gestational and postnatal ages remain largely unclear. There is little evidence for postnatal age-specific variation in the PRR gene expression at baseline (i.e. in the absence of infection or in vitro stimulation)8,15,16, suggesting critical differences in downstream signaling networks and regulatory mechanisms by which hematopoietic cells exert their specific effector functions. These age-specific differences have yet to be revealed.\n\nHere we make available, via an interactive web application, a curated collection of transcriptome datasets of either whole blood samples, isolated blood mononuclear cells, or a variety of sort-purified hematopoietic cell populations obtained from human neonates or fetal tissue. In the selected datasets, transcriptional profiles were obtained in the absence or presence of various intrinsic and exogenous immune modulators. For comparison, these datasets contain samples from other age groups (most often from healthy adult volunteers), or cell populations at multiple differentiation stages. The ability to pool and analyze samples across various age and risk groups, and across various hematopoietic cell types, offers a unique opportunity to define common denominators of early life immunity and to reveal critical differences in the functional programming of fetal and neonatal hematopoietic cells.\n\nTo this date, over 65,000 high-throughput functional genomics studies have been deposited in the NCBI Gene Expression Omnibus (GEO), a public repository of transcriptome profiles. However, identifying datasets relevant to a particular research area is not straightforward, because GEO is primarily designed as a repository for the storage of data, rather than browsing and interaction with the deposited data. Thus, we used a custom interactive web application, called the Gene Expression Browser (GXB)17, to host the datasets we identified as particularly relevant to reveal gestational and postnatal age-specific differences in the gene expression pattern of fetal and neonatal hematopoietic cells. GXB allows seamless browsing and interactive visualization of our GEO dataset collection containing large volumes of heterogeneous data, such as transcriptome profiles, demographic information, as well as clinical information. Users can easily customize data plots by adding multiple layers of information (such as postnatal age, weeks of gestation at birth, and gender), modify the ordering of samples and genes, change the plot type, and generate links (mini URLs) capturing the user’s settings, which can then be inserted in email communications or in publications. These user-generated mini URLs provide access not only the transcription data but also to rich contextual information and data interpretation, including gene information, relevant literature, a description of the study design, as well as detailed sample information that was supplied along with the transcriptome data submission to GEO.\n\n\nMaterial and methods\n\nPotentially relevant datasets deposited in GEO were identified using two search queries which were designed to retrieve entries where the title and description of the datasets contained the words newborn OR neonate OR neonatal OR fetal OR cord. The search was restricted to datasets that were generated from human whole blood, human blood mononuclear cells, or sort-purified human hematopoietic cells using Illumina or Affymetrix platforms. Studies on cancer patients or cell lines were excluded. First, the following query was used: Homo sapiens[Organism] AND (newborn[DESC] OR neonate[DESC] OR neonatal[DESC] OR fetal[DESC] OR cord[DESC]) AND (blood[DESC] OR PBMC[DESC] OR PBMCs[DESC] OR lymphocyte[DESC] OR lymphocytes[DESC] OR \"B cell\"[DESC] OR \"B cells\"[DESC] OR \"plasma cells\"[DESC] OR \"T cell\"[DESC] OR \"T cells\"[DESC] OR Treg[DESC] OR Tregs[DESC] OR monocyte[DESC] OR monocytes[DESC] OR dendritic[DESC] OR DC[DESC] OR DCs[DESC] OR \"natural killer\"[DESC] OR NK[DESC] OR NKT[DESC] OR neutrophil[DESC] OR neutrophils[DESC] OR erythroblast[DESC] OR erythroid[DESC] OR CD19[DESC] OR CD20[DESC] OR CD3[DESC] OR CD4[DESC] OR CD8[DESC] OR CD71[DESC]) AND (\"Expression profiling by array\"[gdsType] OR \"Expression profiling by high throughput sequencing\"[gdsType]) NOT (cancer[DESC] OR leukemia[DESC] OR lymphoma[DESC] OR \"cell line\"[DESC] OR myeloma[DESC] OR mesenchymal[DESC] OR endothelial[DESC]). In addition, we used the following query to specifically retrieve datasets containing samples from neonatal sepsis patients: sepsis AND (neonate OR newborn). In total, more than 450 datasets were retrieved by the two queries. The list of datasets retrieved from the 2 queries was manually curated and restricted to datasets that: (i) contained transcriptional profiles from primary hematopoietic cells; (ii) contained samples of fetal or neonatal origin; (iii) contained a minimum of 3 samples (i.e. biological repeats) for each of the major variables assessed in the respective study; and (iv) allowed within the same dataset, the comparison of transcriptional profiles either between different age groups (e.g. neonate versus adult), between infants born at different gestational ages, between different risk groups (e.g. infants with low birth weight versus those with normal birth weight), or between cell differentiation stages. This process involved reading through the descriptions and examining the list of available samples and their annotations. For the filtering of the dataset list, the Bioconductor package GEOmetadb, version 1.30.0, and its SQLite database was used to capture detailed information on selected GEO datasets in a single table (https://www.bioconductor.org/packages/release/bioc/html/GEOmetadb.html)18. Sometimes, it also required accessing the original published report in which the design of the study and generation of the dataset is described in more detail. Using the stringent criteria detailed above, we reduced the list down to 41 GEO datasets (excluding SuperSeries), of which 32 GEO datasets were uploaded into our interactive web application, GXB, together with corresponding SuperSeries if available (4 additional GEO datasets). For the remaining datasets the platform used to generate the transcriptome profiles was not supported by GXB (9 datasets). Out of the 32 curated datasets, 8 include samples of fetal origin, and 25 datasets include samples of neonatal origin, usually in conjunction with samples of adult subjects (including 3 datasets containing peripheral blood samples from the mothers). The majority of neonatal samples were obtained from healthy subjects, mostly utilizing umbilical cord blood. In these studies, a variety of factors were assessed that may induce and/or reveal differences in the functional programing of neonatal hematopoietic cells, including the effect of active/passive smoking of the mothers during pregnancy (GSE27272, GSE30032)19,20, standards of living and hygiene (GSE53471, GSE53472, GSE53473)21, as well as in vitro exposure of neonatal and adult cells to purified TLR ligands (GSE67057, GSE3140), and to whole pathogens (GSE24132). In 6 studies, peripheral blood samples were obtained from babies with neonatal sepsis (GSE25504, GSE26440, GSE26378, GSE69686)22–24 bronchopulmonary dysplasia (GSE32472)25, or from babies with low birth weight (GSE29807). The transcriptional profiles were either generated from whole blood (11 datasets), cord and peripheral blood mononuclear cells (1 dataset), or a variety of sort-purified hematopoietic cell populations at different differentiation stages, including cells derived from neonatal and adult hematopoietic stem cells as well as erythroid cells. The latter cells have recently been shown to play an important immunosuppressive role in the context of neonatal infection26. The datasets that make up our collection are listed in Table 1. We also generated a word cloud from the title of published journal articles where the datasets were first reported (or the dataset title if no journal article was available), which provides information on the type of studies that make up our dataset collection (Figure 1).\n\nWB, whole blood; HSC, hematopoietic stem cells; DC, dendritic cells; QC, quality control; NA, not applicable (http://developmentalimmunology.gxbsidra.org/dm3/geneBrowser/list).\n\nThe word size is proportional to the frequency of each word.\n\nOnce a final selection has been made, each dataset was downloaded from GEO using the SOFT file format. For GEO datasets generated using multiple platforms (GSE1460, GSE25504), the series matrix file format was used instead, and separate datasets for each platform were downloaded. The retrieved datasets were in turn uploaded on an instance of GXB hosted on the Amazon Web Services cloud (39 datasets in total, including 4 SuperSeries and 3 additional datasets that were uploaded due to the use of multiple platforms per GEO dataset). The GXB software has been described in detail in a recent publication17. This custom software interface provides the user with the means to easily navigate and filter the dataset collection, and is available at http://developmentalimmunology.gxbsidra.org/dm3/geneBrowser/list. A web tutorial is also available online: https://gxb.benaroyaresearch.org/dm3/tutorials.gsp#gxbtut. Annotation and functionality of the web software interface were described previously by our group27,28, and is reproduced here so that readers can use this article as a standalone resource. Available sample and study information were uploaded along with the gene expression data. Samples of each dataset were grouped according to study design and gene rankings were computed for the different group comparisons. Datasets of interest can be quickly identified either by filtering on criteria from pre-defined sections on the left or by entering a query term in the search box at the top of the dataset navigation page. Clicking on one of the studies listed in the dataset navigation page opens a viewer designed to provide interactive browsing and graphic representations of large-scale data in an interpretable format. This interface is designed to present ranked gene lists and display expression results graphically in a context-rich environment. Selecting a gene from the rank ordered list on the left of the data-viewing interface will display its expression values graphically in the screen’s central panel. Directly above the graphical display drop down menus give users the ability: a) To change how the gene list is ranked - this allows the user to change the method used to rank the genes, or to only include genes that are selected for specific biological interest; b) To change sample grouping (Group Set button) - in some datasets, a user can switch between groups based on cell type to groups based on disease type, for example; c) To sort individual samples within a group based on associated categorical or continuous variables (e.g. gender or age); d) To toggle between the bar chart view and a box plot view, with expression values represented as a single point for each sample. Samples are split into the same groups whether displayed as a bar chart or box plot; e) To provide a color legend for the sample groups; f) To select categorical information that is to be overlaid at the bottom of the graph - for example, the user can display gender or smoking status in this manner; g) To provide a color legend for the categorical information overlaid at the bottom of the graph; h) To download the graph as a portable network graphics (png) image. Measurements have no intrinsic utility in absence of contextual information. It is this contextual information that makes the results of a study or experiment interpretable. It is therefore important to capture, integrate and display information that will give users the ability to interpret data and gain new insights from it. We have organized this information under different tabs directly above the graphical display. The tabs can be hidden to make more room for displaying the data plots, or revealed by clicking on the blue “show info panel” button on the top right corner of the display. Information about the gene selected from the list on the left side of the display is available under the “Gene” tab. Information about the study is available under the “Study” tab. Rolling the mouse cursor over a bar chart feature while displaying the “Sample” tab lists any clinical, demographic, or laboratory information available for the selected sample. Finally, the “Downloads” tab allows advanced users to retrieve the original dataset for analysis outside this tool. It also provides all available sample annotation data for use alongside the expression data in third party analysis software. Other functionalities are provided under the “Tools” drop-down menu located in the top right corner of the user interface. Some of the notable functionalities available through this menu include: a) Annotations, which provides access to all the ancillary information about the study, samples and dataset organized across different tabs; b) Cross-project view; which provides the ability for a given gene to browse through all available studies; c) Copy link, which generates a mini-URL encapsulating information about the display settings in use and that can be saved and shared with others (clicking on the envelope icon on the toolbar inserts the URL in an email message via the local email client); d) Chart options; which gives user the option to customize chart labels.\n\n\nQuality control\n\nThe ‘Copy Link’ function from the “Tools” drop down menu described above was used to generate links to a variety of known hematopoietic markers, allowing the user to perform quality control checks on each dataset by examining the expression profiles of specific sort-purified hematopoietic cell populations, or to determine the degree of contamination of the sample by other cell populations. For our dataset collection, relevant biological indicators included: CD3 (CD3D), a T cell marker; CD4 and CD8 (CD8A), markers of CD4+ and CD8+ T cells respectively; FOXP3, a regulatory T cell marker; CD19, a B cell marker; TFRC, a transferrin receptor required for erythropoiesis; CD34, a stem and progenitor cell marker; CD11c (ITGAX), a conventional DC marker; IL-3 receptor alpha (IL3RA), a plasmacytoid DC marker; or CD14, expressed by monocytes and macrophages. For those datasets that contained gender information, we also examined expression of XIST, to determine the concordance between higher XIST expression in female- compared to male samples with the gender information provided with the GEO submission. We hyperlinked this information with the quality control markers given in Table 1 for most of the GEO datasets included in our collection.\n\n\nData availability\n\nAll datasets included in our curated collection are also available publically via the NCBI GEO website: www.ncbi.gov/geo; and are referenced throughout the manuscript by their GEO accession numbers (e.g. GSE25087). Signal files and sample description files can also be downloaded from the GXB tool under the “downloads” tab.",
"appendix": "Author contributions\n\n\n\nNM and MR conceived the theme for this dataset collection. MR, NM, SB, and CC contributed to the query, selection, loading and curation of datasets. SP, CQ and DC participated in the design and testing of the software. MR, DC and NM prepared the first draft of the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe authors listed on this publication with the exception of CQ and SP received support from the Qatar Foundation.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe would like to thank all the investigators who decided to make their datasets publically available by depositing them in GEO.\n\n\nReferences\n\nDowling DJ, Levy O: Ontogeny of early life immunity. Trends Immunol. 2014; 35(7): 299–310. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBasha S, Surendran N, Pichichero M: Immune responses in neonates. Expert Rev Clin Immunol. 2014; 10(9): 1171–84. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLevy O: Innate immunity of the newborn: basic mechanisms and clinical correlates. Nat Rev Immunol. 2007; 7(5): 379–90. PubMed Abstract | Publisher Full Text\n\nLozano R, Naghavi M, Foreman K, et al.: Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012; 380(9859): 2095–128. PubMed Abstract | Publisher Full Text\n\nKollmann TR, Crabtree J, Rein-Weston A, et al.: Neonatal innate TLR-mediated responses are distinct from those of adults. J Immunol. 2009; 183(11): 7150–60. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCorbett NP, Blimkie D, Ho KC, et al.: Ontogeny of Toll-like receptor mediated cytokine responses of human blood mononuclear cells. PLoS One. 2010; 5(11): e15041. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLiao SL, Yeh KW, Lai SH, et al.: Maturation of Toll-like receptor 1-4 responsiveness during early life. Early Hum Dev. 2013; 89(7): 473–8. PubMed Abstract | Publisher Full Text\n\nMarr N, Wang TI, Kam SH, et al.: Attenuation of respiratory syncytial virus-induced and RIG-I-dependent type I IFN responses in human neonates and very young children. J Immunol. 2014; 192(3): 948–57. PubMed Abstract | Publisher Full Text\n\nSharma AA, Jen R, Brant R, et al.: Hierarchical maturation of innate immune defences in very preterm neonates. Neonatology. 2014; 106(1): 1–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKollmann TR, Levy O, Montgomery RR, et al.: Innate immune function by Toll-like receptors: distinct responses in newborns and the elderly. Immunity. 2012; 37(5): 771–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMarchant EA, Kan B, Sharma AA, et al.: Attenuated innate immune defenses in very premature neonates during the neonatal period. Pediatr Res. 2015; 78(5): 492–7. PubMed Abstract | Publisher Full Text\n\nLavoie PM, Huang Q, Jolette E, et al.: Profound lack of interleukin (IL)-12/IL-23p40 in neonates born early in gestation is associated with an increased risk of sepsis. J Infect Dis. 2010; 202(11): 1754–63. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYou D, Marr N, Saravia J, et al.: IL-4Rα on CD4+ T cells plays a pathogenic role in respiratory syncytial virus reinfection in mice infected initially as neonates. J Leukoc Biol. 2013; 93(6): 933–42. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGuilmot A, Carlier Y, Truyens C: Differential IFN-γ production by adult and neonatal blood CD56+ natural killer (NK) and NK-like-T cells in response to Trypanosoma cruzi and IL-15. Parasite Immunol. 2014; 36(1): 43–52. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDasari P, Zola H, Nicholson IC: Expression of Toll-like receptors by neonatal leukocytes. Pediatr Allergy Immunol. 2011; 22(2): 221–8. PubMed Abstract | Publisher Full Text\n\nViemann D, Dubbel G, Schleifenbaum S, et al.: Expression of toll-like receptors in neonatal sepsis. Pediatr Res. 2005; 58(4): 654–9. PubMed Abstract | Publisher Full Text\n\nSpeake C, Presnell S, Domico K, et al.: An interactive web application for the dissemination of human systems immunology data. J Transl Med. 2015; 13: 196. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhu Y, Davis S, Stephens R, et al.: GEOmetadb: powerful alternative search engine for the Gene Expression Omnibus. Bioinformatics. 2008; 24(23): 2798–800. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVotavova H, Dostalova Merkerova M, Fejglova K, et al.: Transcriptome alterations in maternal and fetal cells induced by tobacco smoke. Placenta. 2011; 32(10): 763–70. PubMed Abstract | Publisher Full Text\n\nVotavova H, Dostalova Merkerova M, Krejcik Z, et al.: Deregulation of gene expression induced by environmental tobacco smoke exposure in pregnancy. Nicotine Tob Res. 2012; 14(9): 1073–82. PubMed Abstract | Publisher Full Text\n\nKallionpää H, Laajala E, Öling V, et al.: Standard of hygiene and immune adaptation in newborn infants. Clin Immunol. 2014; 155(1): 136–47. PubMed Abstract | Publisher Full Text\n\nDickinson P, Smith CL, Forster T, et al.: Whole blood gene expression profiling of neonates with confirmed bacterial sepsis. Genom Data. 2014; 3: 41–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWynn JL, Cvijanovich NZ, Allen GL, et al.: The influence of developmental age on the early transcriptomic response of children with septic shock. Mol Med. 2011; 17(11–12): 1146–56. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWynn JL, Guthrie SO, Wong HR, et al.: Postnatal Age Is a Critical Determinant of the Neonatal Host Response to Sepsis. Mol Med. 2015; 21: 496–504. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPietrzyk JJ, Kwinta P, Wollen EJ, et al.: Gene expression profiling in preterm infants: new aspects of bronchopulmonary dysplasia development. PLoS One. 2013; 8(10): e78585. PubMed Abstract | Publisher Full Text | Free Full Text\n\nElahi S, Ertelt JM, Kinder JM, et al.: Immunosuppressive CD71+ erythroid cells compromise neonatal host defence against infection. Nature. 2013; 504(7478): 158–62. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMarr AK, Boughorbel S, Presnell S, et al.: A curated transcriptome dataset collection to investigate the development and differentiation of the human placenta and its associated pathologies [version 1; referees: awaiting peer review]. F1000Res. 2016; 5: 305. Publisher Full Text\n\nRinchai D, Boughorbel S, Presnell S, et al.: A compendium of monocyte transcriptome datasets to foster biomedical knowledge discovery [version 1; referees: 1 approved]. F1000Res. 2016; 5: 291. Publisher Full Text\n\nMason E, Tronc G, Nones K, et al.: Maternal influences on the transmission of leukocyte gene expression profiles in population samples from Brisbane, Australia. PLoS One. 2010; 5(12): e14479. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKoch L, Linderkamp O, Ittrich C, et al.: Gene expression profiles of adult peripheral and cord blood mononuclear cells altered by lipopolysaccharide. Neonatology. 2008; 93(2): 87–100. PubMed Abstract | Publisher Full Text\n\nNoh SJ, Miller SH, Lee YT, et al.: Let-7 microRNAs are developmentally regulated in circulating human erythroid cells. J Transl Med. 2009; 7: 98. PubMed Abstract | Publisher Full Text | Free Full Text\n\nXu J, Shao Z, Glass K, et al.: Combinatorial assembly of developmental stage-specific enhancers controls gene expression programs during human erythropoiesis. Dev Cell. 2012; 23(4): 796–811. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLi B, Ding L, Yang C, et al.: Characterization of transcription factor networks involved in umbilical cord blood CD34+ stem cells-derived erythropoiesis. PLoS One. 2014; 9(9): e107133. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNovershtern N, Subramanian A, Lawton LN, et al.: Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell. 2011; 144(2): 296–309. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKrow-Lucal ER, Kim CC, Burt TD, et al.: Distinct functional programming of human fetal and adult monocytes. Blood. 2014; 123(12): 1897–904. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLee J, Breton G, Oliveira TY, et al.: Restricted dendritic cell and monocyte progenitors in human cord blood and bone marrow. J Exp Med. 2015; 212(3): 385–99. PubMed Abstract | Publisher Full Text | Free Full Text\n\nThornburg NJ, Shepherd B, Crowe JE Jr: Transforming growth factor beta is a major regulator of human neonatal immune responses following respiratory syncytial virus infection. J Virol. 2010; 84(24): 12895–902. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSantner-Nanan B, Straubinger K, Hsu P, et al.: Fetal-maternal alignment of regulatory T cells correlates with IL-10 and Bcl-2 upregulation in pregnancy. J Immunol. 2013; 191(1): 145–53. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMold JE, Venkatasubrahmanyam S, Burt TD, et al.: Fetal and adult hematopoietic stem cells give rise to distinct T cell lineages in humans. Science. 2010; 330(6011): 1695–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLee MS, Hanspers K, Barker CS, et al.: Gene expression profiles during human CD4+ T cell differentiation. Int Immunol. 2004; 16(8): 1109–24. PubMed Abstract | Publisher Full Text\n\nGibbons D, Fleming P, Virasami A, et al.: Interleukin-8 (CXCL8) production is a signatory T cell effector function of human newborn infants. Nat Med. 2014; 20(10): 1206–10. PubMed Abstract | Publisher Full Text\n\nWalker LJ, Kang YH, Smith MO, et al.: Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells. Blood. 2012; 119(2): 422–33. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "13168",
"date": "13 Apr 2016",
"name": "Stanislas Goriely",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis report by Nico Marr and colleagues puts together publicly available expression datasets pertinent to the function/development of human immune and hematological cells in early life. The authors use a Web-based application (Gene Expression Browser1) to facilitate exploration and visualization of the data. This tool is useful for the field and user-friendly. However, the current collection is rather heterogenous (clinical samples from septic shock patients, expression profile in progenitor cells after shRNA knockdown for specific transcription factors, general data on different hematopoietic subpopulations without special emphasis on infant/adult comparison...) so it might not be that easy for researchers or clinicians to navigate between the datasets with a specific question in mind. Furthermore, is not clear whether it will be updated on a regular basis. Will other genome-wide datasets (ChIP-Seq, Methylation Arrays..) be incorporated?",
"responses": []
},
{
"id": "14443",
"date": "17 Jun 2016",
"name": "Peter Ghazal",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe report by Marr and colleagues compiles a valuable set of human early-life publically available expression datasets from the Gene Expression Omnibus (GEO) resource. Obtaining consent and sufficient amounts of sample for this population group is problematical and the limited number of datasets presented reflects the scarcity of studies in this area. The authors have made these datasets web accessible through the Gene Expression Browser (GXB). Interrogating these datasets using GXB application is straightforward but is quite limited providing a restrictive gene analytic view. Incorporating pathway-querying and visualization functions could enhance the overall utility of GXB. Further this would benefit with a note regarding the update frequency for new relevant datasets – during the review process new datasets have already become available. The usefulness and research value of this resource will only be met with continued effort to routinely curate new datasets.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-414
|
https://f1000research.com/articles/5-413/v1
|
30 Mar 16
|
{
"type": "Review",
"title": "Eph-ephrin signaling in nervous system development",
"authors": [
"Karina S. Cramer",
"Ilona J. Miko",
"Ilona J. Miko"
],
"abstract": "Ephrins and Eph receptors enable contact-mediated interactions between cells at every stage of nervous system development. In spite of their broad binding affinities, Eph proteins facilitate specificity in neuronal migration and axon targeting. This review focuses on recent studies that demonstrate how these proteins interact with each other, and with other signaling pathways, to guide specificity in a diverse set of developmental processes.",
"keywords": [
"Ephrins",
"Eph receptors",
"neuronal migration",
"nervous system development",
"Axon guidance"
],
"content": "Introduction\n\nThe complexity of nervous system function reflects a vast underlying diversity of neuronal cells and their integration in precise circuitry. During development, newly born neurons migrate to their final destination, become the right type of cell, and form precise connections with their synaptic partners. Given the relatively small number of genes in our genome, how is this complexity generated? A major contributor to the formation of neural circuitry is the Eph family of proteins, which comprises Eph receptors and their ephrin binding partners. These membrane-associated proteins participate throughout neuronal development, during which they display promiscuous binding properties yet specify uniquely targeted events from proliferation to synaptogenesis.\n\nIn this large family of signaling molecules, such event specificity does not generally arise from binding selectivity between Eph receptors and ephrins. Instead, multiple modes of Eph-ephrin signaling provide combinatorial codes that differentiate between groups of cells and coordinate multiple aspects of neural development, including cell migration and axon targeting.\n\nRecent studies have demonstrated that differential responses depending on ephrin expression levels and expression of ephrin-associated molecules allow cells born in one place at the same time to adopt distinct migratory routes. In addition, studies have shown how multiple signaling pathways enable distinct axons that grow through a common pathway to terminate in distinct locations.\n\nSpecification of neural circuits arises from multiple interacting signaling molecules. The large family of Eph proteins uses both redundancy in expression and multiple modes of signaling to direct this specificity, causing neurons to migrate to their final locations and make synaptic connections there that are appropriate for their function. How can a large family of molecules with broad binding capabilities and redundant expression confer this precision? Here, we discuss recent work focused on factors that determine specificity during cell migration, axon guidance, and midline specializations.\n\n\nEph-ephrin signaling\n\nEph receptors and ephrins display broad spatial and temporal expression throughout nervous system development. During early development, they contribute to neurogenesis (reviewed in 1) and differentiation2. Some interesting new perspectives that take into account the unique features of Eph-ephrin signaling have emerged.\n\nThe Eph receptors are the largest known class of receptor tyrosine kinase. Together with the ephrins, they are divided into the A and B classes on the basis of sequence homology and binding affinities3. The EphA receptors (EphA1-10 in mammals) bind to all ephrin-A molecules (ephrin-A1-6), and the EphB receptors (1–6) bind to all ephrin-Bs (1–3); some variability has been reported in the binding affinities of individual pairs within a class4. There is some crosstalk between classes in that EphB2 can bind to ephrin-A5 and EphA4 can bind to ephrin-B23,5,6.\n\nUnlike most ligands for receptor tyrosine kinases, the ephrins are associated with cell membranes. Ephrin-B proteins contain a transmembrane domain, and ephrin-A proteins are associated with cell membranes through a glycosylphosphatidylinositol linkage. A major consequence of this membrane association is that Eph-ephrin signaling mediates short-range cell-cell communication, although in some cases soluble forms of ephrin molecules can provide longer-range cues7–9. The communication between receptors and membrane ligands operates in both directions upon the binding of an Eph receptor in one cell with an ephrin on another cell. Forward signaling refers to signal transduction in a cell expressing the Eph receptor, which upon ligand binding initiates tyrosine phosphorylation. In reverse signaling, signal transduction events are initiated in a cell expressing an ephrin upon its binding with an Eph receptor. Both ephrin-A and ephrin-B proteins can mediate reverse signaling10–12.\n\nIn cell migration and axon guidance, movement ultimately relies on the integration of signals that influence the cytoskeleton. Eph-ephrin signaling influences the functions of Rho GTPase proteins, which in turn regulate the actin cytoskeleton (reviewed in 4,13). Although Eph-ephrin signaling was initially thought to mediate chemorepulsive interactions, later evidence showed that both attractive and repulsive interactions occur. Recent studies have begun to illuminate the factors that determine how Eph-ephrin interactions influence cell migration, adhesion, and axon guidance.\n\nOne potential switch for determining attractive versus repulsive interactions relates to the assembly of higher-order clusters upon ephrin binding to Eph receptors, a prominent feature unique to Eph receptors among the receptor tyrosine kinases14,15. Cluster formation relies on the ligand-binding domains as well as on interactions between adjacent receptors16,17. These clusters, needed for initiation of signal transduction pathways, can be expansive and can include more than one type of Eph receptor within a cluster18. Large clusters can include inactive receptors that can be phosphorylated within the cluster; consequently, a single ligand can result in phosphorylation of multiple receptors of both classes4,14,15.\n\nSeveral new studies have shed light on the role of clustering in the unique responses of Eph-ephrin signaling. EphA4 and EphA2 have similar affinities to ephrin-A5 but have opposing responses in cell assays, whereby EphA4 promotes repulsion while EphA2 promotes adhesion. Seiradake and colleagues19 studied the crystal structure and clustering properties and determined that EphA4 forms small clusters while EphA2 forms large arrays and that these clusters largely determine the cellular response. Along these lines, Klein and colleagues20 prepared clusters of EphB2 of varying sizes and compared effects on phosphorylation, cell collapse, and growth cone collapse. They determined that whilst dimers were associated with a lack of response, trimers and tetramers produced a functional response and that the relative abundance of multimers correlated with the degree of the response. These studies suggest that factors influencing the clustering of Eph receptors are critical for determining how cells will respond to ephrin binding.\n\nReceptor clustering represents a cis interaction; that is, two Eph receptor molecules signaling within a single cell. Another type of cis interaction observed is the interaction of ephrins and Eph receptors within the same cell, where they are often co-expressed. These interactions have been shown to decrease forward signaling21–23 and may play an important role in topographic mapping24,25 as well as axon guidance for spinal motor neurons21.\n\n\nDifferential control of cortical cell migration\n\nEph-ephrin interactions regulate cell migration throughout development and are important for establishing boundaries and regulating intermixing of cells26,27. Several new studies highlight the complexity in the regulation of cell movement by Eph-ephrin signaling. Cell sorting is accomplished by using both repulsive and attractive interactions, both forward and reverse signaling, and a range of selective downstream targets of Eph-ephrin signaling.\n\nThe diverse and coordinated functions of Eph-ephrin signaling in cell migration are demonstrated by recent studies of cerebral cortex formation. Early in neural tube development, adhesion of neural progenitors to the apical surface is associated with symmetric cell division. A study of null mutations in ephrin-B1 found that these mice exhibited abnormal neuroepithelia and exencephaly28 and that the mutation further disrupted the apical localization of integrin β1. The authors used biochemical assays and culture approaches to show that ephrin-B1 negatively regulates the GTPase Arf6, which is essential for maintaining appropriate integrin β1 localization and adhesion of apical progenitors. In cortical development, some of the first cells to populate the nascent cortical surface are the Cajal-Retzius (CR) cells. This transient population of cells plays a critical role in cortical layering through its release of reelin, which is essential for the characteristic “inside-out” formation of layers. Although apical progenitors require ephrin-B1-mediated adhesion, a recent study used in vivo time-lapse imaging together with modeling of cell movement to show that tangential dispersion of CR cells relies on contact-mediated repulsion29. Pharmacological and genetic disruption of Eph signaling showed that both EphA and EphB signaling contribute critically to this repulsion29. Interestingly, the function of reelin in establishing the cortical layers depends extensively on ephrin-B-EphB signaling. Reelin enhances clustering of ephrin-Bs and EphBs, in addition to binding to its receptors. Mutant mice lacking ephrin-B-EphB signaling display severe migration phenotypes with inverted lamination, similar to those seen in reeler mice, and activation of ephrin-B-EphB signaling can rescue migration phenotypes in reeler mice30,31.\n\nAnother influence of Eph proteins occurs during radial migration. During cortical development, electrical synapses form preferentially between radial glial cells and their sister neurons, forming networks of lineage-related cells in radial columns. When inside-out radial migration is genetically disrupted, the preferential coupling between sister cells is lost32. The tangential dispersion of a subpopulation of these developing cortical neurons promotes crosstalk between clonal columnar units and is significantly reduced in mutant mice lacking ephrin-A signaling33.\n\nIn addition to regulating radial migration and cell dispersion, Eph-ephrin signaling is critical for the tangential migration of interneurons. Excitatory cortical neurons are born at the ventricular zone and migrate radially. In contrast, inhibitory interneurons are generated in the basal telencephalon and migrate extensively along a tangential route. Cortical interneurons born in the medial ganglionic eminence (MGE) migrate along a deep route, whereas preoptic area (POA)-derived interneurons migrate along a superficial route. These routes exhibit complementary expression of EphA4 and ephrin-B3, respectively. A study using organotypic cultures and stripe assays together with gene knockdown and pharmacological approaches showed that forward signaling through EphA4 and reverse signaling through ephrin-B3 induce repulsion of MGE and POA interneurons in the inappropriate routes34. MGE interneurons also express ephrin-As, and reverse signaling induced in ephrin-As by EphA4 enhances motility in these migrating MGE interneurons35.\n\nThe POA also generates striatal neurons, which are generated at a similar time and also express ephrin-B3. However, striatal neurons traverse an intermediate route and terminate in the striatum, which expresses EphB1. Reverse signaling through ephrin-B3 elicited by striatal EphB1 is repulsive for migrating cortical interneurons but is an attractive stop signal for migrating striatal cells36. What accounts for these divergent effects? In cortical interneurons, EphB1-ephrin-B3 reverse signaling leads to enhanced phosphorylation of Src tyrosine kinase and of focal adhesion kinase (FAK), leading to enhanced repulsion. For striatal neurons, this same signaling leads to a dephosphorylation of Src and FAK, which leads to attraction36. These divergent effects might arise from endogenously high levels of phosphorylated Src and FAK in striatal cells and/or to distinct combinations of transcription factors in these two cell populations that can influence elements of signal transduction pathways.\n\nStriatal interneurons are generated in the MGE along with cortical interneurons. They are attracted to the striatum through Nrg1/ErbB4 signaling and are simultaneously repelled from the adjacent cortex through EphB forward signaling37. These authors used chromatin immunoprecipitation and luciferase assays to show that the expression of EphB1 and EphB3 is enhanced by Nkx2-1, which is expressed in striatal but not in cortical interneurons born in the MGE.\n\nEph-ephrin signaling thus provides both repulsive and attractive cues for tangentially migrating neurons. The determination of migratory route depends on the ensemble of Eph receptors expressed along with the molecular context within cells destined for different routes.\n\n\nAxon guidance\n\nThe function of Eph-ephrin signaling in axon guidance was originally discovered in the context of topographic mapping. Graded expression of ephrin-As in the optic tectum and opposing gradients of EphA receptors were found to be necessary for forming the high degree of topography seen in this pathway38–40. Since then, further evidence has shown that Eph-ephrin signaling is critical for establishing topographic projections in the auditory system10,41,42, somatosensory system43, olfactory system44, and others45–47. Both forward and reverse signaling play a role, as do attractive and repulsive interactions and interactions in cis.\n\nFormation of topography thus uses graded, or continuous, targeting signals. However, Eph-ephrin signaling also contributes significantly to selection of discrete, or discontinuous, synaptic targets, and these modes of targeting often occur together in a single neural pathway. Interestingly, the function of individual Eph or ephrin family members is specialized within a structure, so that family members regulating topography are distinct from those regulating modular48, laminar49, or ipsilateral versus contralateral50 axon targeting decisions.\n\nEph-ephrin signaling plays an important role in axon targeting at choice points, where axons select between two alternative routes. For example, null mutations in EphB1 result in reduced numbers of retinal ganglion cells that project ipsilaterally through the optic chiasm to the ipsilateral region of the lateral geniculate nucleus51. This phenotype is recapitulated when the cytoplasmic domain of EphB1 is deleted, suggesting that reverse signaling is not necessary for this targeting choice. Conversely, overexpression of EphB1 in mouse embryos is sufficient to direct retinal ganglion cell axons to the ipsilateral trajectory52. Interestingly, loss or gain of EphB1 reduces or increases ipsilateral targeting, respectively, whereas changes in EphB2 and EphB3 are relatively ineffective, even though these receptors are co-expressed to varying degrees in retinal ganglion cell axons51,52. Analysis of the effectiveness of overexpressed chimeric receptors suggests that unique sequences in both the juxtamembrane and the extracellular domains of EphB1 work together to direct axons ipsilaterally. The selective role for EphB1 might result from differences in its ability to engage downstream signaling pathways. Additionally, crossing axons might express additional proteins that normally overcome this ipsilateral cue. In this study, the authors overexpressed the zinc finger transcription factor Zic2, which is expressed in retinal ganglion cells and which activates EphB1 and regulates numerous other genes as well. They found that early exogenous expression of Zic2 was significantly more effective at inducing ipsilateral projections than EphB1, consistent with the view that a network of genes is needed to balance responses to ipsilateral versus contralateral cues. The identification of these genes and the integration of their roles in target selection, which may require a computational modeling approach, will greatly facilitate our understanding of how Eph-ephrin signaling leads to precision in axon targeting.\n\nSeveral other studies highlight the broad significance for Eph-ephrin signaling in determining whether axons cross the midline53–56. Eph family molecules play key roles in establishing the crossed projections of the central nervous system54,57. Repulsion from ephrins expressed at the midline may serve to limit crossing projections spatially58 or temporally53. Eph-ephrin signaling is a significant factor in determining whether axons make ipsilateral or contralateral synaptic target selections. This role has been demonstrated in the auditory brainstem pathway from the cochlear nucleus to the medial nucleus of the trapezoid body, a strictly contralateral projection in the normal brain. Mutations that reduce reverse signaling through ephrin-B proteins59 and null mutations in ephrin-A2 or ephrin-A5 (or both) similarly reduce the specificity of this pathway, resulting in a significant ipsilateral projection50. The similarity in these phenotypes suggests crosstalk between the classes and redundancy in cues for generating the crossed projection. Unlike the optic chiasm, in which a subset of axons is selectively targeted ipsilaterally by EphB1, this auditory projection uses multiple Eph-ephrin signaling molecules to prevent the formation of any ipsilateral projections. In this case, downstream signaling molecules might be similarly engaged by both classes of Eph proteins.\n\nRecent studies of motor neuron axon guidance have shed new light on the molecular mechanisms by which Eph-ephrin signaling coordinates distinct choices. Two groups of motor neurons of the lateral motor column (LMC) in the spinal cord innervate the limb. The medial LMC (LMCM) motor neurons innervate ventral limb muscles, whereas the lateral LMC (LMCL) motor neurons innervate the dorsal limb muscles60. The axons of the LMC motor neurons grow out of the spinal cord together in one fascicle and make a dorsal versus ventral choice as they enter the limb. Another group of motor neurons in the medial portion of the medial motor column (MMCM) at the level of the hindlimb initially project axons together with the LMC axons but abruptly change course toward dorsal axial muscle targets. Both LMCL and MMCM axons express EphA4 and encounter ephrin-A5 along their trajectories. In ovo electroporation studies in chick embryos revealed that the two populations have opposite responses to ephrin-A5: LMCL axons avoid ephrin-A5 in the limb, whereas MMCM axons grow through ephrin-A5-positive somite regions61.\n\nThe distinct responses of these EphA4-positive axons are further complicated by the fact that these axons also express ephrin-A proteins. EphAs and ephrin-As in LMCL motor axons are maintained in separate membrane compartments62, so that trans interactions are favored, whereas in LMCM motor axons, EphAs and ephrin-As can reside in the same membrane compartments and interact in cis21. LMCM motor neurons are also guided by EphB signaling63.\n\nIn the trans signaling guiding LMCL motor neurons, the effects of forward signaling through EphA receptors are repulsive, whereas reverse ephrin-A signaling is attractive62,64. Both forward and reverse signaling are necessary to target LMCL axons to the dorsal limb. Using co-immunoprecipitation assays to identify novel ephrin-A co-receptors, Bonanomi and colleagues64 found that the selective attraction of LMCL axons through ephrin-A reverse signaling is mediated by Ret, a tyrosine kinase. Ret also interacts with GFRα1, a GPI-linked receptor for glial-derived neurotrophic factor, which is secreted in the limb. Ret thus integrates signals from these two sources and generates a synergistic interaction that promotes axon attraction. This study highlights the significance of combinatorial codes in establishing diversity and precision in neuronal contacts.\n\n\nMidline specializations\n\nEph proteins play a key role in establishing midline structures. In humans, mutations in EFNB1, the gene coding for ephrin-B1, leads to craniofrontonasal syndrome (CFNS). This syndrome is characterized by abnormally large distance between the eyes, a central nasal groove, cleft palate, and skeletal/sternum abnormalities, along with other midline distortions in the body. CFNS is also associated with agenesis of the corpus callosum, a large neural tract that interconnects the cerebral hemispheres65,66.\n\nThe mouse model for CFNS parallels many of the cranial deformities and also exhibits incomplete formation of the corpus callosum65, which depends on ephrin-B1 reverse signaling67. Deeper examination of corpus callosum formation in several Eph family mutant mice revealed axon outgrowth defects near the midline, after axons have progressed out of cortical layers and traveled medially toward their contralateral journey. These axons coalesce and turn to project longitudinally, not medially via the commissure, similar to the human CFNS phenotype54. Axon guidance across the midline is largely dependent on ephrin-Bs and EphBs, which are expressed in growing callosal fibers. Furthermore, abnormal glial proliferation at the midline in mutant mice brains suggested that Eph family proteins regulate this population through growth suppression54. These studies suggest that agenesis of the corpus callosum in CFNS results from defects in axon guidance regulated by Eph-ephrin signaling.\n\nOwing to the large morphological impact of the EFNB1 mutation in CFNS, investigations into the mechanisms have focused on earlier developmental stages. Indeed, in vivo manipulation of ephrin-B1 expression in the developing mouse results in perturbations of cephalic neural crest cell precursors68, which give rise to the bone and cartilage of the head. Whereas neural crest cell migration is known to be regulated by Eph proteins69, craniofacial defects in ephrin-B1 mutants largely arise from impaired cell proliferation in the developing palate68 as well as from impaired cell survival70. Craniofacial development relies on ephrin-B1 reverse signaling67. Interestingly, loss of ephrin-B1 in the developing palate leads to increased expression of EphB3, as forward signaling normally modifies EphB3 so as to promote endocytosis and degradation68. Together, these studies show that loss of ephrin-B1 affects several aspects of central and peripheral development through multiple molecular interactions.\n\n\nNew research directions\n\nApart from CFNS, an understanding of the impact of mutations affecting Eph-ephrin signaling on human brain conditions is in its very early stages. Genetic studies have linked these mutations with neurodevelopmental disorders, including autism spectrum disorder (ASD)71, characterized by dysfunction in social interactions, repetitive behaviors, and sensory abnormalities. Some of these behaviors can be identified in simplified form in mouse models of ASD. To explore the potential link with Eph proteins, Wurzman and colleagues72 performed a comprehensive series of behavioral tests on ephrin-A2/A3 double-knockout mice. In a three-chamber social interaction test, the knockout mice spent significantly less time than wild-types did in a chamber exposed to a novel mouse, indicating social aversion. Compared with wild-type mice, the ephrin-A2/A3 mice exhibited significantly greater repetitive and self-injurious grooming behavior. They also showed decreased acoustic startle response and increased prepulse inhibition of the startle reflex. These behavioral phenotypes are similar to those in other mouse models of ASD. This work, though still in its early stages, expands the relevance of developmental Eph-ephrin signaling in establishing normal sensory function and behavior.\n\n\nSummary\n\nA large body of work on the roles of Eph proteins and the mechanisms underlying their versatility has emerged. Recent work demonstrates the breadth of roles throughout development and the significance for assembly of sensory, motor, and cognitive neural systems. Determining how these multiple functions are coordinated remains a significant challenge. The recent studies highlighted here have begun to shed light on this complex issue, showing that specificity arises from differential clustering, forward and reverse signaling, and unique combinations of protein family members that engage distinct signaling pathways.\n\n\nAbbreviations\n\nASD, autism spectrum disorder; CFNS, craniofrontonasal syndrome; CR, Cajal-Retzius; FAK, focal adhesion kinase; LMC, lateral motor column; LMCL, lateral lateral motor column; LMCM, medial lateral motor column; MGE, medial ganglionic eminence; MMCM, medial motor column; POA, preoptic area.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no disclosures.\n\n\nGrant information\n\nResearch in the laboratory of KSC is supported by NIH R01DC010796.\n\n\nReferences\n\nLaussu J, Khuong A, Gautrais J, et al.: Beyond boundaries--Eph:ephrin signaling in neurogenesis. Cell Adh Migr. 2014; 8(4): 349–359. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWilkinson DG: Regulation of cell differentiation by Eph receptor and ephrin signaling. Cell Adh Migr. 2014; 8(4): 339–348. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGale NW, Holland SJ, Valenzuela DM, et al.: Eph receptors and ligands comprise two major specificity subclasses and are reciprocally compartmentalized during embryogenesis. Neuron. 1996; 17(1): 9–19. PubMed Abstract | Publisher Full Text\n\nLisabeth EM, Falivelli G, Pasquale EB: Eph receptor signaling and ephrins. Cold Spring Harb Perspect Biol. 2013; 5(9): pii: a009159. 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PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nZimmer G, Rudolph J, Landmann J, et al.: Bidirectional ephrinB3/EphA4 signaling mediates the segregation of medial ganglionic eminence- and preoptic area-derived interneurons in the deep and superficial migratory stream. J Neurosci. 2011; 31(50): 18364–18380. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSteinecke A, Gampe C, Zimmer G, et al.: EphA/ephrin A reverse signaling promotes the migration of cortical interneurons from the medial ganglionic eminence. Development. 2014; 141(2): 460–471. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nRudolph J, Gerstmann K, Zimmer G, et al.: A dual role of EphB1/ephrin-B3 reverse signaling on migrating striatal and cortical neurons originating in the preoptic area: should I stay or go away? Front Cell Neurosci. 2014; 8: 185. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nVillar-Cerviño V, Kappeler C, Nóbrega-Pereira S, et al.: Molecular mechanisms controlling the migration of striatal interneurons. J Neurosci. 2015; 35(23): 8718–8729. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nCheng HJ, Nakamoto M, Bergemann AD, et al.: Complementary gradients in expression and binding of ELF-1 and Mek4 in development of the topographic retinotectal projection map. Cell. 1995; 82(3): 371–381. PubMed Abstract | Publisher Full Text\n\nDrescher U, Kremoser C, Handwerker C, et al.: In vitro guidance of retinal ganglion cell axons by RAGS, a 25 kDa tectal protein related to ligands for Eph receptor tyrosine kinases. Cell. 1995; 82(3): 359–370. PubMed Abstract | Publisher Full Text\n\nFeldheim DA, Kim YI, Bergemann AD, et al.: Genetic analysis of ephrin-A2 and ephrin-A5 shows their requirement in multiple aspects of retinocollicular mapping. Neuron. 2000; 25(3): 563–574. PubMed Abstract | Publisher Full Text\n\nHuffman KJ, Cramer KS: EphA4 regulates tonotopic ordering of projections in the chick auditory brainstem. Soc Neurosci Abstr. 2006. Reference Source\n\nMiko IJ, Nakamura PA, Henkemeyer M, et al.: Auditory brainstem neural activation patterns are altered in EphA4- and ephrin-B2-deficient mice. J Comp Neurol. 2007; 505(6): 669–681. PubMed Abstract | Publisher Full Text\n\nPrakash N, Vanderhaeghen P, Cohen-Cory S, et al.: Malformation of the functional organization of somatosensory cortex in adult ephrin-A5 knock-out mice revealed by in vivo functional imaging. J Neurosci. 2000; 20(15): 5841–5847. PubMed Abstract\n\nSerizawa S, Miyamichi K, Takeuchi H, et al.: A neuronal identity code for the odorant receptor-specific and activity-dependent axon sorting. Cell. 2006; 127(5): 1057–1069. 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}
|
[
{
"id": "13108",
"date": "30 Mar 2016",
"name": "David Feldheim",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13109",
"date": "30 Mar 2016",
"name": "Matthew Kelley",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-413
|
https://f1000research.com/articles/5-412/v1
|
30 Mar 16
|
{
"type": "Review",
"title": "Cell biology and genetics of minimal change disease",
"authors": [
"Moin A. Saleem",
"Yasuko Kobayashi",
"Yasuko Kobayashi"
],
"abstract": "Minimal change disease (MCD) is an important cause of nephrotic syndrome and is characterized by massive proteinuria and hypoalbuminemia, resulting in edema and hypercholesterolemia. The podocyte plays a key role in filtration and its disruption results in a dramatic loss of function leading to proteinuria. Immunologic disturbance has been suggested in the pathogenesis of MCD. Because of its clinical features, such as recurrent relapse/remission course, steroid response in most patients, and rare familial cases, a genetic defect has been thought to be less likely in MCD. Recent progress in whole-exome sequencing reveals pathogenic mutations in familial cases in steroid-sensitive nephrotic syndrome (SSNS) and sheds light on possible mechanisms and key molecules in podocytes in MCD. On the other hand, in the majority of cases, the existence of circulating permeability factors has been implicated along with T lymphocyte dysfunction. Observations of benefit with rituximab added B cell involvement to the disease. Animal models are unsatisfactory, and the humanized mouse may be a good model that well reflects MCD pathophysiology to investigate suggested “T cell dysfunction” directly related to podocytes in vivo. Several candidate circulating factors and their effects on podocytes have been proposed but are still not sufficient to explain whole mechanisms and clinical features in MCD. Another circulating factor disease is focal segmental glomerulosclerosis (FSGS), and it is not clear if this is a distinct entity, or on the same spectrum, implicating the same circulating factor(s). These patients are mostly steroid resistant and often have a rapid relapse after transplantation. In clinical practice, predicting relapse or disease activity and response to steroids is important and is an area where novel biomarkers can be developed based on our growing knowledge of podocyte signaling pathways. In this review, we discuss recent findings in genetics and podocyte biology in MCD.",
"keywords": [
"Minimal change disease",
"steroid-sensitive nephrotic syndrome",
"focal segmental glomerulosclerosis",
"steroid-resistant nephrotic syndrome",
"circulating factor",
"permeability",
"podocyte"
],
"content": "Introduction\n\nMinimal change disease (MCD) is characterized by massive proteinuria without histological evidence of immune-mediated damage in the glomeruli. The glomerular podocyte plays a key role in filtration and its loss of function results in loss of protein, mainly albumin or smaller proteins, into the urine with high selectivity1. Proteinuria in MCD is typically reversible with corticosteroid therapy2. T cell dysfunction and circulating factors have long been implicated as a cause of the podocyte dysfunction in MCD3, but their nature still remains to be elucidated.\n\nRecent progress in genetics and cell biology has revealed the molecular mechanisms of dysfunction in podocytes4. These findings give us clues to focus on target molecules on the podocyte to deduce what those circulating factors may be. At the same time, we can utilize those molecules as biomarkers not only as a diagnostic tool but also in predicting the disease activity or prognosis. This allows us to administer more accurate and precise treatment to patients with MCD while minimizing side effects caused by drugs.\n\nAlongside MCD as one circulating factor disease is a subset of patients with the histological finding of focal segmental glomerulosclerosis (FSGS). These patients are mostly steroid resistant, and therefore the term steroid-resistant nephrotic syndrome (SRNS) is also used here. These patients often have a rapid relapse after transplantation, indicating another circulating factor disease. It is likely that at least a subset of patients with MCD progress to FSGS/SRNS, with a consistent circulating factor in both. The most compelling evidence for this is the observation that patients with initial steroid sensitivity (assumed to be MCD at that stage) who over subsequent years develop steroid resistance/FSGS, and renal failure, have a 90% chance of post-transplant disease recurrence – the archetypal manifestation of circulating factor disease5. In this article, known pathogenesis and mechanisms underlying MCD are reviewed.\n\n\nClinical features of MCD\n\nMCD is the most common cause of nephrotic syndrome in children6 and around 15–20% of cases in adults7, and is characterized by massive proteinuria and hypoalbuminemia, resulting in edema and hypercholesterolemia. Histological findings of the disease in glomeruli are typically normal by light microscopy and only electron microscopy shows effacement of podocyte foot processes without electron-dense immune deposits8. These manifestations are typically reversible with the use of corticosteroid therapy in steroid-sensitive nephrotic syndrome (SSNS), so that progressive loss of renal function is rare.\n\nThe incidence of MCD in childhood is twofold higher in boys, with a prevalence that is inversely proportional to age. Relapse occurs in 50–80% of patients, and recurrent relapse tends to lessen after adolescence9. A genetic defect cannot explain these phenomena in MCD.\n\n\nGenetics in MCD\n\nFamilial cases are rather rare in MCD, therefore the genetic background of SSNS is largely unknown, while 23.6% of SRNS cases10 and 29.5% of familial SRNS cases11 are caused by gene mutation. More than 24 genes are currently known to be pathogenic in SRNS12 and have already been clinically utilized in practice in SRNS cases.\n\nRecently, using whole-exome sequencing, several mutations were found in pedigrees with SSNS, which shed light on new mechanisms of podocyte disruption in MCD. Epithelial membrane protein 2 (EMP2) is known to regulate the amount of caveolin-113, which contributes to endocytosis and the transcytosis of cholesterol and albumin14. Lipopolysaccharide (LPS)-induced caveolin-1 phosphorylation was reported to lead to the increase of transcellular permeability15.\n\nMore recently, recessive mutations in the KANK gene were identified in familial SSNS and in sporadic SRNS cases16. Kidney ankyrin repeat-containing protein (KANK) family proteins have essential roles in podocyte/nephrocyte function and regulate Rho GTPase activity. KANK2 interacted with Rho GDP dissociation inhibitor alpha (ARHGDIA), a known regulator of Rho GTPases in podocytes found to be dysfunctional in SRNS17. Knockdown of KANK2 in cultured podocytes increased active GTP-bound RHOA and decreased migration.\n\nIn these cases, we might have evidence of overlap of SSNS and SRNS. Also, it is important to know the mechanisms of how corticosteroid and immunosuppressants have their effect on nephrotic syndrome caused by single gene mutation.\n\n\nT cell dysfunction in MCD\n\nT cell dysfunction has long been postulated and many types of cytokines have been investigated. One of the difficulties in examining a hypothesis that immunological disruption underlies MCD in the laboratory is the lack of an animal model that reflects the pathophysiological mechanism. Haddad et al. employed unique methods and established a nephrotic syndrome model by injecting CD34+ peripheral stem cells obtained from FSGS and MCD patients18 rather than injecting the supernatant of T cells or peripheral blood mononuclear cells (PBMCs) obtained from the patients19. The injected cells successfully induced the engraftment of human CD45 leukocytes in the thymus, and only the injection of CD34+ stem cells from patients induced albuminuria. Interestingly, stem-cell-injected mice did not have CD3+ mature T cells, suggesting that the cells responsible for the pathogenesis of idiopathic nephrotic syndrome are more likely to be immature differentiating cells rather than mature peripheral T cells. Naïve T cells (Th0s) have been focused on to investigate the difference in DNA methylation in MCD patients20. The change in DNA methylation patterns from remission to relapse occurs predominantly in Th0s. Epigenetic involvement in the pathogenesis of minimal change nephrotic syndrome in T cells has also been suggested in a report showing that nuclear factor related to kappaB binding protein (NFRKB) was highly expressed in the nuclear compartment in T lymphocytes of MCD patients during relapse and that NFRKB promotes hypomethylation of genomic DNA in HEK cells transfected with NFRKB expression plasmid21.\n\nAnother T cell dysfunction is a Th17 skew in MCD22,23 (Figure 1). Patients with SSNS demonstrated after corticosteroid treatment that the Th17/regulatory T cell (Treg) balance returned to normal24. More recently, it was reported that Th17 cells are strong candidate drivers for steroid resistance in immune diseases and have selective attenuation by cyclosporine A25. This could be utilized to predict steroid response in early stages of nephrotic syndrome onset by testing peripheral Th17 levels.\n\nBy immune trigger such as viral infection, vaccination, and exposure to allergen, antigen-presenting cells and memory B cells present antigen to T lymphocyte. These cells are stimulated to secrete circulating factors in MCD. Rituximab depletes B cells and induces remission; on the other hand, rituximab has an effect on cytoskeleton stability of podocytes and blocks albumin permeability. Th17 skew in MCD may cause steroid resistance and cyclosporine A selectively attenuates Th17. Abbreviations: APCs, antigen presenting cells; CysA, cyclosporine A; CF, circulating factor; IL17, interleukin 17; Th17, helper T subset 17; TNF-a, tumor necrosis factor alpha.\n\n\nRituximab and B cell dysfunction\n\nA potential close pathophysiological relationship between MCD and chronic lymphoid neoplasms such as Hodgkin and non-Hodgkin lymphoma has been known since the 1950s, supporting a potential role for B cells in the pathogenesis of MCD (Figure 1). A significant association of HLA-DQA1 (a major histocompatibility complex [MHC] class II) missense coding variants with SSNS recently suggested the possible role of an immune response and the implication of B cells in the pathogenesis of MCD26.\n\nThough the accurate mechanism by which rituximab, a monoclonal antibody against CD20, induces remission in MCD patients remains uncertain, recent observations of the effect of rituximab on complicated refractory SSNS27–29 suggests a pathophysiological role for B cells in MCD30,31 (Figure 1). B cell depletion by rituximab resets and suppresses B cell and T cell interactions and keeps the Th17/Treg balance normal, which may lead to sustainable remission32,33. On the other hand, a direct role for rituximab on podocyte cytoskeleton stabilization was suggested: rituximab prevents disruption of the actin cytoskeleton in cultured normal human podocytes that have been exposed to FSGS patient sera in a sphingomyelin phosphodiesterase acid-like 3b-dependent manner34.\n\n\nCirculating factors and podocyte cell biology in MCD\n\nA direct test of “circulating factor” activity is to expose human podocytes in culture to active human disease plasma and examine the direct cellular effects on this target cell. It has been shown using this method that nephrotic plasma alters slit diaphragm-dependent signaling and translocates nephrin, podocin, and CD2-associated protein in cultured human podocytes35. This indicated that there is a certain factor increasing or missing in MCD disease plasma.\n\n\nHemopexin\n\nHemopexin (Hpx) is a circulating plasma protease that is synthesized in the liver. The active isoform of Hpx is increased in children with MCD36. In vitro, podocytes showed dramatic reorganization of actin with loss of stress fibers after Hpx treatment37. The Hpx effect on actin is dependent on nephrin followed by RhoA activation and protein kinase B phosphorylation in the downstream intracellular signaling pathway. The effects were reversible and were inhibited by pre-incubation with healthy human plasma or serine protease inhibitors. Though the mechanisms of Hpx activation in the disease are unclear, LPS and tumor necrosis factor (TNF)-α are indicated as possible triggers to activate Hpx in MCD38.\n\n\nPAR1 signaling axis and VASPp, or suPAR\n\nBecause it has serine protease activity39, Hpx may act via the family of protease-activated receptors. There are also matrix metalloproteinases among those proteins that have Hpx homology domains. Recent studies investigated the possibility of a matrix metalloproteinase–protease-activated receptor 1 (PAR1) signaling axis40. It was recently reported that proteases present in nephrotic plasma obtained from patients with FSGS can activate PAR1, leading to the podocin-dependent phosphorylation of the actin-associated protein vasodilator-stimulated phosphoprotein (VASP) in human podocytes and increased cell migration, suggesting a novel role for proteases and PARs in the pathogenesis of FSGS41,42. Although the exact component(s) of FSGS plasma that causes this response remains unknown, the soluble urokinase plasminogen activator receptor (suPAR) has been identified as a potential circulating factor in FSGS via activation of β3 integrin in podocytes and promotes cell motility43–45. However, correlation of disease activity with suPAR levels has been inconsistent in subsequent reports46,47. Urinary suPAR was increased in MCD relapse, but it is thought it may simply be a surrogate for proteinuria48. These factors are found in FSGS but are potentially also relevant to MCD; this needs experimental verification.\n\nCD80 (B7-1) is a T cell co-stimulatory molecule involved in antigen processing that is also unexpectedly expressed on podocytes in certain experimental and clinical disease states. Podocyte CD80 activation through Toll-like receptor (TLR) 3 and 4 by LPS, independent of T cells, causes proteinuria and foot process effacement49.\n\nUrinary CD80 levels are increased in MCD during relapse but are not increased in FSGS patients or MCD patients in remission50. Sera from MCD patients in relapse, but not in remission, stimulated CD80 expression in cultured podocytes51. The factor(s) in patients’ serum that stimulates podocytes is unknown. Most recently, it was reported that no significant up-regulation of podocyte CD80 was detected in MCD and FSGS patients' biopsies compared with controls using different primary antibodies and immunohistochemical assays, suggesting further confirmation is needed with CD80 in MCD52.\n\nTNF-α is suggested to be one of the circulating factors that exists in patient plasma of post-transplant recurrent FSGS53,54. The effect on the podocyte was actin cytoskeleton disruption and activation of β3 integrin. In MCD, it has been suggested that TNF-α synthesis in peripheral mononuclear cells from relapse is increased55. Genome-wide DNA methylation analysis was performed in naïve T helper cells both in relapse and in remission of MCD20 and it was found that the promoter region of TNF-α from relapse has a significant reduction in DNA methylation compared to that from remission in the same individuals, indicating predisposition of TNF-α synthesis in relapse in MCD [personal communication, Dr Yasuko Kobayashi].\n\nSummarizing the data, an excess factor or missing/imbalance of factors in relapse plasma could be the primary cause of MCD, and interesting candidates with biological plausibility are Hpx, suPAR, and TNF-α. PAR1 or uPAR and β3 integrin are therefore potentially activated by circulating factors, and VASP-p is in the pathway downstream of PAR1 or integrins. CD80 is a product of podocyte stimulation by circulating factors. Reorganization of actin by Hpx is dependent on nephrin. The structural changes in actin result in foot process effacement and increase of permeability, which is the core feature in the disease.\n\nThe circulating factors might be secreted by peripheral blood cells such as T or B cells by mesangial or endothelial cells in a paracrine manner or by the podocyte itself in an autocrine manner.\n\n\nConclusion\n\nPathogenic gene mutation analysis in familial MCD has started to reveal insights into underlying mechanisms of pathophysiology in the podocyte, such as endocytosis or Rho GTPase, related to permeability.\n\nWe have less evidence of circulating factor activity or from genetic disease in MCD compared to FSGS, perhaps because of less disease severity and lower availability of patient samples in MCD. In terms of circulating factor diseases, findings in FSGS can be examined in relation to MCD. A humanized mouse model might give us a good tool to investigate T cell dysfunction directly related to podocytes.\n\nThere are several candidates for biomarkers to predict disease activity or steroid response that allow us to choose precise and acceptable treatment for each individual patient while reducing the side effects of long-term treatment.\n\nNew components might be inducible targeting of a specific molecule that is involved in the pathogenesis of MCD both for screening and for treatment.\n\n\nAbbreviations\n\nMCD, minimal change disease; SSNS, steroid-sensitive nephrotic syndrome; FSGS, focal segmental glomerulosclerosis; SRNS, steroid-resistant nephrotic syndrome; EMP2, epithelial membrane protein 2; LPS, lipopolysaccharide; KANK, kidney ankyrin repeat-containing protein; ARHGDIA, Rho GDP dissociation inhibitor (GDI) alpha; Th0s, naïve T cells; NFRKB, nuclear factor related to kappaB binding protein; Th17, helper T subset 17; Treg, regulatory T cell; PBMC, peripheral mononuclear cell; PAR1, protease activated receptor 1; VASP, vasodilator stimulated phosphoprotein; suPAR, soluble urokinase plasminogen activator receptor; TLR, Toll-like receptor; TNF-α, tumor necrosis factor alpha.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nSaleem MA: One hundred ways to kill a podocyte. Nephrol Dial Transplant. 2015; 30(8): 1266–71. PubMed Abstract | Publisher Full Text\n\nKDIGO: Chapter 3: Steroid-sensitive nephrotic syndrome in children. Kidney Int Suppl (2011). 2012; 2(2): 163–71. PubMed Abstract | Publisher Full Text | Free Full Text\n\nShalhoub RJ: Pathogenesis of lipoid nephrosis: a disorder of T-cell function. Lancet. 1974; 2(7880): 556–60. PubMed Abstract | Publisher Full Text\n\nSaleem MA: New developments in steroid-resistant nephrotic syndrome. Pediatr Nephrol. 2013; 28(5): 699–709. PubMed Abstract | Publisher Full Text\n\nDing WY, Koziell A, McCarthy HJ, et al.: Initial steroid sensitivity in children with steroid-resistant nephrotic syndrome predicts post-transplant recurrence. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGee HY, Saisawat P, Ashraf S, et al.: ARHGDIA mutations cause nephrotic syndrome via defective RHO GTPase signaling. J Clin Invest. 2013; 123(8): 3243–53. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSellier-Leclerc AL, Duval A, Riveron S, et al.: A humanized mouse model of idiopathic nephrotic syndrome suggests a pathogenic role for immature cells. J Am Soc Nephrol. 2007; 18(10): 2732–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMaruyama K, Tomizawa S, Shimabukuro N, et al.: Effect of supernatants derived from T lymphocyte culture in minimal change nephrotic syndrome on rat kidney capillaries. Nephron. 1989; 51(1): 73–6. PubMed Abstract | Publisher Full Text\n\nKobayashi Y, Aizawa A, Takizawa T, et al.: DNA methylation changes between relapse and remission of minimal change nephrotic syndrome. Pediatr Nephrol. 2012; 27(12 ): 2233–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAudard V, Pawlak A, Candelier M, et al.: Upregulation of nuclear factor-related kappa B suggests a disorder of transcriptional regulation in minimal change nephrotic syndrome. PLoS One. 2012; 7(1): e30523. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nAraya C, Diaz L, Wasserfall C, et al.: T regulatory cell function in idiopathic minimal lesion nephrotic syndrome. Pediatr Nephrol. 2009; 24(9): 1691–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWang L, Li Q, Wang L, et al.: The role of Th17/IL-17 in the pathogenesis of primary nephrotic syndrome in children. Kidney Blood Press Res. 2013; 37(4–5): 332–45. PubMed Abstract | Publisher Full Text\n\nLiu LL, Qin Y, Cai JF, et al.: Th17/Treg imbalance in adult patients with minimal change nephrotic syndrome. Clin Immunol. 2011; 139(3): 314–20. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSchewitz-Bowers LP, Lait PJ, Copland DA, et al.: Glucocorticoid-resistant Th17 cells are selectively attenuated by cyclosporine A. Proc Natl Acad Sci U S A. 2015; 112(13): 4080–5. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGbadegesin RA, Adeyemo A, Webb NJ, et al.: HLA-DQA1 and PLCG2 Are Candidate Risk Loci for Childhood-Onset Steroid-Sensitive Nephrotic Syndrome. J Am Soc Nephrol. 2015; 26(7): 1701–10. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nIijima K, Sako M, Nozu K, et al.: Rituximab for childhood-onset, complicated, frequently relapsing nephrotic syndrome or steroid-dependent nephrotic syndrome: a multicentre, double-blind, randomised, placebo-controlled trial. Lancet. 2014; 384(9950): 1273–81. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBruchfeld A, Benedek S, Hilderman M, et al.: Rituximab for minimal change disease in adults: long-term follow-up. Nephrol Dial Transplant. 2014; 29(4): 851–6. PubMed Abstract | Publisher Full Text\n\nKronbichler A, Bruchfeld A: Rituximab in adult minimal change disease and focal segmental glomerulosclerosis. Nephron Clin Pract. 2014; 128(3–4): 277–82. PubMed Abstract | Publisher Full Text\n\nLiu K, Mohan C: Altered B-cell signaling in lupus. Autoimmun Rev. 2009; 8(3): 214–8. PubMed Abstract | Publisher Full Text\n\nChan OT, Hannum LG, Haberman AM, et al.: A novel mouse with B cells but lacking serum antibody reveals an antibody-independent role for B cells in murine lupus. J Exp Med. 1999; 189(10): 1639–48. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSfikakis PP, Boletis JN, Lionaki S, et al.: Remission of proliferative lupus nephritis following B cell depletion therapy is preceded by down-regulation of the T cell costimulatory molecule CD40 ligand: an open-label trial. Arthritis Rheum. 2005; 52(2): 501–13. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nStasi R, Cooper N, Del Poeta G, et al.: Analysis of regulatory T-cell changes in patients with idiopathic thrombocytopenic purpura receiving B cell-depleting therapy with rituximab. Blood. 2008; 112(4): 1147–50. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nFornoni A, Sageshima J, Wei C, et al.: Rituximab targets podocytes in recurrent focal segmental glomerulosclerosis. Sci Transl Med. 2011; 3(85): 85ra46. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nCoward RJ, Foster RR, Patton D, et al.: Nephrotic plasma alters slit diaphragm-dependent signaling and translocates nephrin, Podocin, and CD2 associated protein in cultured human podocytes. J Am Soc Nephrol. 2005; 16(3): 629–37. PubMed Abstract | Publisher Full Text\n\nBakker WW, van Dael CM, Pierik LJ, et al.: Altered activity of plasma hemopexin in patients with minimal change disease in relapse. Pediatr Nephrol. 2005; 20(10): 1410–5. PubMed Abstract | Publisher Full Text\n\nLennon R, Singh A, Welsh GI, et al.: Hemopexin induces nephrin-dependent reorganization of the actin cytoskeleton in podocytes. J Am Soc Nephrol. 2008; 19(11): 2140–9. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKapojos JJ, Poelstra K, Borghuis T, et al.: Regulation of plasma hemopexin activity by stimulated endothelial or mesangial cells. Nephron Physiol. 2004; 96(1): P1–10. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBakker WW, Borghuis T, Harmsen MC, et al.: Protease activity of plasma hemopexin. Kidney Int. 2005; 68(2): 603–10. PubMed Abstract | Publisher Full Text\n\nGoerge T, Barg A, Schnaeker EM, et al.: Tumor-derived matrix metalloproteinase-1 targets endothelial proteinase-activated receptor 1 promoting endothelial cell activation. Cancer Res. 2006; 66(15): 7766–74. PubMed Abstract | Publisher Full Text\n\nHarris JJ, McCarthy HJ, Ni L, et al.: Active proteases in nephrotic plasma lead to a podocin-dependent phosphorylation of VASP in podocytes via protease activated receptor-1. J Pathol. 2013; 229(5): 660–71. PubMed Abstract | Publisher Full Text\n\nPiccard H, Van den Steen PE, Opdenakker G: Hemopexin domains as multifunctional liganding modules in matrix metalloproteinases and other proteins. J Leukoc Biol. 2007; 81(4): 870–92. PubMed Abstract | Publisher Full Text\n\nAlfano M, Cinque P, Giusti G, et al.: Full-length soluble urokinase plasminogen activator receptor down-modulates nephrin expression in podocytes. Sci Rep. 2015; 5: 13647. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWei C, Möller CC, Altintas MM, et al.: Modification of kidney barrier function by the urokinase receptor. Nat Med. 2008; 14(1): 55–63. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWei C, El Hindi S, Li J, et al.: Circulating urokinase receptor as a cause of focal segmental glomerulosclerosis. Nat Med. 2011; 17(8): 952–60. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSinha A, Bajpai J, Saini S, et al.: Serum-soluble urokinase receptor levels do not distinguish focal segmental glomerulosclerosis from other causes of nephrotic syndrome in children. Kidney Int. 2014; 85(3): 649–58. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWada T, Nangaku M, Maruyama S, et al.: A multicenter cross-sectional study of circulating soluble urokinase receptor in Japanese patients with glomerular disease. Kidney Int. 2014; 85(3): 641–8. PubMed Abstract | Publisher Full Text\n\nCara-Fuentes G, Wei C, Segarra A, et al.: CD80 and suPAR in patients with minimal change disease and focal segmental glomerulosclerosis: diagnostic and pathogenic significance. Pediatr Nephrol. 2014; 29(8): 1363–71. PubMed Abstract | Publisher Full Text | Free Full Text\n\nReiser J, von Gersdorff G, Loos M, et al.: Induction of B7-1 in podocytes is associated with nephrotic syndrome. J Clin Invest. 2004; 113(10): 1390–7. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGarin EH, Mu W, Arthur JM, et al.: Urinary CD80 is elevated in minimal change disease but not in focal segmental glomerulosclerosis. Kidney Int. 2010; 78(3): 296–302. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nIshimoto T, Cara-Fuentes G, Wang H, et al.: Serum from minimal change patients in relapse increases CD80 expression in cultured podocytes. Pediatr Nephrol. 2013; 28(9): 1803–12. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNovelli R, Gagliardini E, Ruggiero B, et al.: Any value of podocyte B7-1 as a biomarker in human MCD and FSGS? Am J Physiol Renal Physiol. 2016; 310(5): F335–41. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSaleem MA: The phenomenon of focal segmental glomerulosclerosis post-transplantation--a one-hit wonder? Pediatr Nephrol. 2012; 27(12): 2163–6. PubMed Abstract | Publisher Full Text\n\nBitzan M, Babayeva S, Vasudevan A, et al.: TNFα pathway blockade ameliorates toxic effects of FSGS plasma on podocyte cytoskeleton and β3 integrin activation. Pediatr Nephrol. 2012; 27(12): 2217–26. PubMed Abstract | Publisher Full Text\n\nBakr A, Shokeir M, El-Chenawi F, et al.: Tumor necrosis factor-alpha production from mononuclear cells in nephrotic syndrome. Pediatr Nephrol. 2003; 18(6): 516–20. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "13095",
"date": "30 Mar 2016",
"name": "Annette Bruchfeld",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13096",
"date": "30 Mar 2016",
"name": "Vincent Audard",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-412
|
https://f1000research.com/articles/5-408/v1
|
29 Mar 16
|
{
"type": "Review",
"title": "Strategically targeting MYC in cancer",
"authors": [
"Valeriya Posternak",
"Michael D. Cole",
"Valeriya Posternak"
],
"abstract": "MYC is a major driver of cancer cell growth and mediates a transcriptional program spanning cell growth, the cell cycle, metabolism, and cell survival. Many efforts have been made to deliberately target MYC for cancer therapy. A variety of compounds have been generated to inhibit MYC function or stability, either directly or indirectly. The most direct inhibitors target the interaction between MYC and MAX, which is required for DNA binding. Unfortunately, these compounds do not have the desired pharmacokinetics and pharmacodynamics for in vivo application. Recent studies report the indirect inhibition of MYC through the development of two compounds, JQ1 and THZ1, which target factors involved in unique stages of transcription. These compounds appear to have significant therapeutic value for cancers with high levels of MYC, although some effects are MYC-independent. These approaches serve as a foundation for developing novel compounds to pharmacologically target MYC-driven cancers.",
"keywords": [
"MYC",
"cancer",
"transcriptional control",
"cancer therapy",
"inhibitors"
],
"content": "Introduction\n\nThe MYC protein plays a crucial role in a variety of cellular processes, including cell proliferation and differentiation, cell cycle progression, metabolism, and apoptosis1,2. MYC is a pleiotropic transcription factor that regulates a variety of functions by promoting activation or repression of genes on a global scale3–5. As a transcription factor, MYC heterodimerizes with MAX and directly binds to a consensus sequence on DNA, CACGTG6. MYC-mediated transcriptional activation involves an interaction between MYC and a nuclear cofactor, transformation/transcription domain-associated protein (TRRAP), through a conserved domain on MYC, MYC Box II (MBII)7. TRRAP is in complex with histone acetyltransferases that acetylate histones around gene promoters, inducing an open chromatin conformation, making it possible for RNA polymerase II (RNA Pol II) recruitment and productive transcription8,9.\n\nMYC expression is tightly regulated under normal circumstances and is increased in response to extracellular stimuli, such as growth factors10,11. Chromosomal translocation, gene amplification, and mutations in signaling pathways promote MYC overexpression independently of growth factor stimulation, which leads to unrestrained cell proliferation and tumorigenesis12. MYC is deregulated in approximately 70% of human cancers3, and many studies have observed that MYC inhibition can result in tumor regression and cell differentiation in a host- and cell-dependent manner13. Widespread activation of MYC in a range of tumors and the reversibility of MYC-induced tumorigenesis have made MYC an appealing target for cancer therapy. However, MYC lacks innate enzymatic function and small-molecule interactions that facilitate most pharmacological strategies. Furthermore, as a transcription factor, MYC is localized in the nucleus and hence is inaccessible to any antibody-based therapies. For these reasons, MYC is widely considered ‘undruggable’, a frustrating limitation for such a well-established driver of cancer. Nevertheless, numerous strategies have been employed to target MYC at various stages of biological and pathological development, and there have been significant advances in understanding the MYC dependence of cancer and developing novel approaches to targeting MYC activity in the past five years (Figure 1). To date, directly targeting MYC’s interaction with MAX by using compounds like 10058-F4 has proven unsuccessful in vivo, although a biological agent, Omomyc, has proven informative. However, a new library screen resulted in the identification of a potent in vivo MYC-MAX inhibitor, KJ-Pyr-9, that has some efficacy14. More recent studies have demonstrated that indirect approaches using compounds designed to inhibit key factors involved in transcriptional initiation and elongation seem selective for the MYC oncogenic pathway15–18. These new developments in therapeutic targeting of MYC in cancer have broad implications in a challenging field where inhibition of MYC has been shown to result in tumor regression but has proven problematic to execute because of difficulties in delivery or specificity.\n\n(A) Targeting the MYC/MAX interface by using 10058-F4, KJ-Pyr-9, or Omomyc inhibits binding to DNA and the MYC transcriptional pathway. (B) Indirect targeting of MYC expression through inhibition of CDK7 or BRD4, key factors involved in transcriptional initiation and elongation, using JQ1/dBET1 or THZ1/THZ2, respectively. Targeting CDK7 or BRD4 results in specific downregulation of MYC protein expression.\n\n\nTargeting the MYC and MAX interface\n\nSince dimerization with MAX is essential for MYC DNA-binding activity19, disruption of the MYC/MAX interaction by using small molecules is an obvious strategy of targeting MYC functionality. A number of selective low molecular weight inhibitors that disrupt the interaction between MYC and MAX have been developed20. One of these is 10058-F4, a molecule that prevents heterodimerization and is capable of penetrating cells with low non-specific toxicity21,22. The compound has demonstrated the ability to inhibit mammalian cell growth, cell cycle progression, and expression of MYC target genes in vitro. A number of studies have reported that short-term pharmacological inhibition of MYC using 10058-F4 or more potent analogs leads to tumor regression in vivo. More recently, KJ-Pyr-9, a compound identified in a pyridine library screen, was identified as a potent inhibitor of the MYC/MAX interaction and it displays the correct pharmacokinetic properties necessary for in vivo administration14. Although these compounds have shown specificity for the MYC/MAX interaction, targeting a bHLH-LZ domain is inherently inefficient and potentially non-specific since many other proteins contain these motifs. Nevertheless, 10058-F4 and KJ-Pyr-9 appear to have differential efficacy in vivo, depending on tumor type, differential metabolism of the compounds, and tumor model14,23–25. Taken together, these data suggest that direct inhibition of MYC through disruption of the MYC/MAX interaction is promising but requires further experimentation to establish specificity and efficiency in humans.\n\nA second strategy to inhibit MYC/MAX dimerization is Omomyc, a mutant basic helix-loop-helix domain that acts as a potent dominant negative molecule by sequestering MYC and preventing its binding to MAX and DNA26,27. Under normal circumstances, MYC is unable to homodimerize, but Omomyc is a MYC homolog that contains four amino acid substitutions augmenting homodimerization and non-functional heterodimerization with MYC. Although Omomyc cannot penetrate human tumors and hence is ineffective as a cancer therapeutic, it has proven useful to explore the consequences of MYC inhibition in vivo. Omomyc can stimulate MYC-induced apoptosis of NIH3T3 cells in a MYC-dependent manner in vitro and of MYC-overexpressing tumor cells in a mouse model of K-Ras-driven lung adenocarcinoma28,29. Recent studies have demonstrated that the bHLH-LZ domain of MAX (MAX*) can be transduced across cell membranes through endocytosis and is able to translocate to the nucleus, suggesting that compounds mimicking the bHLH-LZ domain may be efficacious in vivo30. Another recent study extended the efficacy of MYC inhibition as a therapeutic strategy (using Omomyc) in the treatment of human glioma in a mouse model of astrocytoma, human glioblastoma cell lines, and patient-derived tumors in vitro and in vivo31. Interestingly, general inhibition of MYC activity is tolerated in the mouse, albeit with severely reduced proliferation in the skin, testes, gastrointestinal tract, and hematopoietic lineages29. Remarkably, the proliferation defects were fully reversible, suggesting that anti-MYC therapy could be used to treat human disease since tumor cells often apoptose upon MYC inhibition whereas normal cells simply fail to proliferate.\n\n\nIndirectly targeting MYC through BRD4 bromodomain inhibition\n\nRecent findings suggest that MYC promotes gene expression by global transcriptional amplification, although there have been other interpretations of the data4,5,32,33. The transcriptional amplification model proposes that MYC binds to virtually all active promoters in any cells and enhances transcriptional elongation. These studies have established a positive correlation between MYC levels and phosphorylation of serine-2 (S2) on the carboxy-terminal domain (CTD) of RNA Pol II, which is linked to transcriptional elongation. Phosphorylation of S2 on the CTD is catalyzed by P-TEFb (positive transcription elongation factor b), which can be activated by binding to the bromodomain protein BRD434. Bromodomains bind to acetylated lysines (Ac-K) on histones and other proteins, and the binding of BRD4 to P-TEFb results in recruitment to promoters and productive transcriptional elongation34–37. BRD4 is a member of the BET family of proteins and by itself is a key mediator of an aggressive squamous cancer, NUT midline carcinoma38. Small-molecule screens have identified compounds that inhibit the binding of the BRD4 bromodomain to Ac-K39,40. The most extensively characterized compound developed for this purpose is JQ1, a powerful inhibitor of BRD439. JQ1 binds to the Ac-K-binding site of BET bromodomains and effectively displaces BRD4 from chromatin, preventing transcriptional elongation. Treatment with JQ1 results in cell differentiation of NUT cells and attenuates growth of BRD4-dependent carcinomas in vivo. Efficacy of JQ1 in a number of myeloid-derived tumors, such as acute myeloid leukemia (AML) and multiple myeloma, has been demonstrated. Notably, these studies have revealed that the effect of JQ1 on tumor regression appears to be specifically mediated by downregulation of MYC itself, its downstream targets, and inflammatory signals12,16,41,42. The link between JQ1 and MYC expression is not totally clear but may involve the dependence of MYC on multiple enhancers and ‘super-enhancers’ that are highly dependent on BRD443. These findings have led to a number of potential combination therapies in conjunction with JQ1 that synergistically result in tumor regression. These therapies include indirectly targeting MYC in combination with the PI3K pathway, mechanistic target of rapamycin (mTOR), or histone deacetylases (HDACs) for the treatment of T-cell acute lymphoblastic leukemia, pancreatic ductal adenocarcinoma, and osteosarcoma, respectively44–46. BET inhibitors have also been shown to induce apoptosis of osteosarcoma cells independently of MYC downregulation and display synergistic effects when combined with CDK inhibitors, indicating that this strategy could be employed in the treatment of osteosarcoma47.\n\nThe use of bromodomain-binding compounds has very recently been developed into a new strategy to target BRD4 and subsequently MYC. dBET1 is a novel compound developed to target BRD4 for protein degradation, in contrast to JQ1, which inhibits the bromodomain of BRD417,18. dBET1 is a bivalent compound composed of JQ1 and thalidomide that creates a link between BRD4 and cereblon (CRBN), a component of a cullin-RING ubiquitin ligase that catalyzes proteasomal degradation48. dBET1 is potent and highly specific, targeting BRD2, BRD3, and BRD4 for degradation. As with JQ1, the MYC protein and its transcriptional pathway appear to be the most strongly affected. Treatment with dBET1 produces an improved apoptotic response at lower concentrations in AML and lymphoma cell lines, accompanied by a decrease in MYC levels compared with JQ1. This strategy can be exercised to target a wide variety of proteins that may have no innate enzymatic function as long as high-affinity ligands are available.\n\n\nTargeting CDK7 as an indirect inhibitor of MYC\n\nAnother very recent study suggests a second indirect approach to target MYC. TFIIH, a complex involved as a basal factor in transcriptional initiation, is composed of a number of proteins, including the catalytic subunit cyclin-dependent kinase 7 (CDK7)49,50. CDK7 phosphorylates serine-5 (S5) on the CTD of RNA Pol II, which induces transcriptional initiation, production of nascent mRNA, mRNA capping and methylation, and promoter proximal pausing51,52. THZ1 was developed as a novel covalent inhibitor of CDK7, and its high selectivity for CDK7 results from chemical linkage to a cysteine residue that resides outside of the canonical kinase domain53. Interestingly, THZ1 specifically downregulates MYC in MYCN-driven neuroblastomas compared with normal cells, and this effect is attributed to the presence of super-enhancers upstream of the MYCN gene15. Although the mechanism accounting for MYC specificity requires further investigation, targeting CDK7 in tumors addicted to super-enhancer-associated transcription factors provides a novel platform for targeting multiple aberrant genes with a single agent. Therapeutically, THZ1 was shown to be highly effective in killing MYC-driven tumors, including neuroblastoma, small cell lung cancer, and triple-negative breast cancer15,54,55. Treatment with THZ1 leads to a substantial reduction in tumor volume by suppressing cell proliferation and inducing apoptosis. THZ2, an analog of THZ1, was developed to overcome the instability of THZ1 in vivo and demonstrated improved pharmacokinetics with an amended half-life and high potency for CDK755. Together, these data provide a rationale for targeting CDK7 in tumors that are dependent on high levels of MYC for transcription.\n\n\nSynthetic lethal interactions with MYC\n\nAlthough MYC itself is difficult to drug, tumor cells often exhibit ‘oncogene addiction’ or changes in gene expression and physiology that make them extremely dependent on a specific oncogenic pathway for growth or survival or both. This dependence theoretically can be exploited to search for a tumor cell’s Achilles heel (that is, pathways that become rate-limiting for the growth/survival of tumor cells but not their normal counterparts). An early study identified AMPK (AMP-dependent kinase) as critical for the survival of cells with high levels of MYC56. Synthetic lethality has also been observed in MYC-overexpressing cells when spliceosome core factors or metabolic pathways are targeted for inhibition57,58. A more general approach has been taken to uncover new therapeutics for cancer by interrogating the connection between genomic aberrations and response to a wide panel of anti-cancer drugs59. Bioinformatic tools were used to identify a synthetic lethal relationship between MYC overexpression and sensitivity to dasatinib, a multikinase inhibitor. This platform sets a framework for the discovery of novel combination therapies to target MYC-driven tumors.\n\n\nConclusions and Future directions\n\nA large number of direct and indirect MYC inhibitors have been developed in the last decade, and some are more efficacious and specific than others. Although direct inhibitors of MYC, precisely those targeting the interaction between MYC and MAX, are more specific for MYC itself, they target a bHLH-LZ domain conserved between many transcription factors. Chemical inhibition of a domain present in MYC alone would provide a more targeted approach for MYC inhibition. The mechanisms by which indirect inhibitors of MYC, such as JQ1 and THZ1, act remain to be well characterized. Furthermore, additional experimentation is required to determine the efficacy of these compounds in human cancer. Ultimately, it may be necessary to strategically target MYC from a multitude of angles, taking advantage of its well-established role as a master regulator of transcription in cancer cells.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nMeyer N, Penn LZ: Reflecting on 25 years with MYC. Nat Rev Cancer. 2008; 8(12): 976–90. PubMed Abstract | Publisher Full Text\n\nTrumpp A, Refaeli Y, Oskarsson T, et al.: c-Myc regulates mammalian body size by controlling cell number but not cell size. Nature. 2001; 414(6865): 768–73. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nDang CV, O'Donnell KA, Zeller KI, et al.: The c-Myc target gene network. Semin Cancer Biol. 2006; 16(4): 253–64. PubMed Abstract | Publisher Full Text\n\nLin CY, Lovén J, Rahl PB, et al.: Transcriptional amplification in tumor cells with elevated c-Myc. Cell. 2012; 151(1): 56–67. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBaker EK, Taylor S, Gupte A, et al.: BET inhibitors induce apoptosis through a MYC independent mechanism and synergise with CDK inhibitors to kill osteosarcoma cells. Sci Rep. 2015; 5: 10120. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nIto T, Ando H, Suzuki T, et al.: Identification of a primary target of thalidomide teratogenicity. Science. 2010; 327(5971): 1345–50. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCompe E, Egly JM: TFIIH: when transcription met DNA repair. Nat Rev Mol Cell Biol. 2012; 13(6): 343–54. PubMed Abstract | Publisher Full Text\n\nEgly JM, Coin F: A history of TFIIH: two decades of molecular biology on a pivotal transcription/repair factor. DNA Repair (Amst). 2011; 10(7): 714–21. PubMed Abstract | Publisher Full Text\n\nHeidemann M, Hintermair C, Voß K, et al.: Dynamic phosphorylation patterns of RNA polymerase II CTD during transcription. Biochim Biophys Acta. 2013; 1829(1): 55–62. PubMed Abstract | Publisher Full Text\n\nNilson KA, Guo J, Turek ME, et al.: THZ1 Reveals Roles for Cdk7 in Co-transcriptional Capping and Pausing. Mol Cell. 2015; 59(4): 576–87. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKwiatkowski N, Zhang T, Rahl PB, et al.: Targeting transcription regulation in cancer with a covalent CDK7 inhibitor. Nature. 2014; 511(7511): 616–20. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nChristensen CL, Kwiatkowski N, Abraham BJ, et al.: Targeting transcriptional addictions in small cell lung cancer with a covalent CDK7 inhibitor. Cancer Cell. 2014; 26(6): 909–22. 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}
|
[
{
"id": "13092",
"date": "29 Mar 2016",
"name": "Chi Dang",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13093",
"date": "29 Mar 2016",
"name": "David L Levens",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-408
|
https://f1000research.com/articles/5-407/v1
|
29 Mar 16
|
{
"type": "Review",
"title": "Probiotics in critically ill children",
"authors": [
"Sunit C. Singhi",
"Suresh Kumar",
"Suresh Kumar"
],
"abstract": "Gut microflora contribute greatly to immune and nutritive functions and act as a physical barrier against pathogenic organisms across the gut mucosa. Critical illness disrupts the balance between host and gut microflora, facilitating colonization, overgrowth, and translocation of pathogens and microbial products across intestinal mucosal barrier and causing systemic inflammatory response syndrome and sepsis. Commonly used probiotics, which have been developed from organisms that form gut microbiota, singly or in combination, can restore gut microflora and offer the benefits similar to those offered by normal gut flora, namely immune enhancement, improved barrier function of the gastrointestinal tract (GIT), and prevention of bacterial translocation. Enteral supplementation of probiotic strains containing either Lactobacillus alone or in combination with Bifidobacterium reduced the incidence and severity of necrotizing enterocolitis and all-cause mortality in preterm infants. Orally administered Lactobacillus casei subspecies rhamnosus, Lactobacillus reuteri, and Lactobacillus rhamnosus were effective in the prevention of late-onset sepsis and GIT colonization by Candida in preterm very low birth weight infants. In critically ill children, probiotics are effective in the prevention and treatment of antibiotic-associated diarrhea. Oral administration of a mix of probiotics for 1 week to children on broad-spectrum antibiotics in a pediatric intensive care unit decreased GIT colonization by Candida, led to a 50% reduction in candiduria, and showed a trend toward decreased incidence of candidemia. However, routine use of probiotics cannot be supported on the basis of current scientific evidence. Safety of probiotics is also a concern; rarely, probiotics may cause bacteremia, fungemia, and sepsis in immunocompromised critically ill children. More studies are needed to answer questions on the effectiveness of a mix versus single-strain probiotics, optimum dosage regimens and duration of treatment, cost effectiveness, and risk-benefit potential for the prevention and treatment of various critical illnesses.",
"keywords": [
"Antibiotic associated Diarrhea",
"Candida colonization",
"candidemia",
"Critical illness",
"Critically ill children",
"Nosocomial Infections",
"Probiotics",
"Ventilator Associated Pneumonia"
],
"content": "Introduction\n\nCritically ill patients are predisposed to altered gut microflora, which can lead to infective and non-infective complications and adverse outcome1–3. Probiotic bacteria have the potential to restore the balance of gut microflora in critically ill children and confer a health benefit when given for various indications. Probiotics are defined by a joint working group of the Food and Agriculture Organization of the United Nations/World Health Organization as “live microbes which when administered in adequate amount confer health benefit to the host”4. In addition, probiotics should be non-pathogenic, stable in acid and bile, able to adhere to and colonize human gut mucosa, and retain viability during storage and use. They should be scientifically demonstrated to have beneficial physiological effects and safety so that they can be used to improve microbial balance and to confer health benefit. In recent years, probiotics have been increasingly used in critical care settings for the prevention of certain diseases that are otherwise associated with high mortality. In this review, we examine the current status of probiotics in the care of critically ill children on the basis of available literature and identify directions for future research.\n\n\nGut microflora\n\nThe human gut represents a complex ecosystem where a delicate balance exists between the host and the microflora. More than 400 different species of microbes live in the gut as commensal; the total estimated number is more than 10 times the number of eukaryotic cells in the human body3,5. Human gut microflora consists principally of obligate anaerobes (95%; Bifidobacterium, Clostridium, Eubacterium, Fusobacterium, Peptostreptococcus, and Bacteriodes) and facultative anaerobes (1–10%; Lactobacillus, Escherichia coli, Klebsiella, Streptococcus, Staphylococcus, and Bacillus). Bifidobacteria are predominant microbes that represent up to 80% of the cultivable fecal bacteria in infants and 25% in adults. Each human being has his or her own unique microbial composition, especially of lactic acid bacterial (LAB) strains3. Most of these microbes have health-promoting effects; however, a few are potentially pathogenic. Normally, the ‘good’ microbes outnumber potentially pathogenic bacteria and live in symbiosis with the host. The optimal balance, composition, and function of gut microflora depend on the supply of food (fermentable fibers and complex proteins) and fluctuate with antibiotic usage, diarrheal diseases, and critical illness3. The gut microflora benefits the host by performing various crucial functions (Table 1).\n\n\nCritical illness and gut microflora\n\nCritical illness and its treatment create a hostile environment in the gastrointestinal tract (GIT) and alter the microflora that tilts the balance to favor overgrowth of pathogens. The hostile environment is exacerbated by the use of broad-spectrum antibiotics, invasive central lines, endotracheal intubation, mechanical ventilation, antacids, H2 blockers, steroids, and immunosuppressive and cytotoxic therapy. Multiple organ dysfunction syndrome (MODS), burns, malnutrition, changes in nutrient availability, gut motility, pH, redox state, osmolality, and the release of high amounts of stress hormones (including catecholamines) further compromise the critical balance2,3.\n\nStudies in experimental models have shown that after onset of acute pancreatitis there was disappearance of beneficial LAB within 6 to 12 hours6–8. In patients with systemic inflammatory response syndrome (SIRS), there is a reduction in beneficial bacteria (Bifidobacterium and Lactobacillus) that leads to a decrease in short-chain fatty acid levels and elevation of intestinal pH, indicating a disturbed intestinal environment9. Hostile gut environment and disruption of the balance of gut microflora alter local defense mechanisms and lead to colonization and overgrowth of potentially pathogenic commensals such as Salmonella, E. coli, Yersinia, and Pseudomonas aeruginosa. These pathogenic commensals cause cytokine release, cell apoptosis, activation of neutrophils, and disruption in epithelial tight junctions1,2. With loss of “colonization resistance”, the gut is unable to prevent the translocation of pathogens and toxins across the gut wall into the bloodstream, leading to SIRS, MODS, and mortality. Interestingly, the gut has been identified as the originator and promoter of health care-associated infections (HCAIs) and MODS in critically ill patients1,10. Restoring the beneficial gut microflora with an exogenous supply of new and effective microbes (probiotics) seems an attractive option to restore the “colonization resistance”.\n\n\nCommonly used probiotics\n\nThe most frequently used probiotic strains are Lactobacillus and Bifidobacterium11; other species of probiotics are enlisted in Table 2. These probiotics are used either singly or in combination. Multi-strain probiotics are likely to be better than single-strain probiotics, as individual probiotics have different functions and have synergistic effects when administered together. A daily intake of 106–109 colony-forming units (CFUs) is reportedly the minimum effective dose for therapeutic purposes11,12.\n\n\nMechanism of beneficial effects of probiotics\n\nThe beneficial effects of probiotics are due to change in the composition of gut flora and modification of immune response13. Probiotic strains activate mucosal immunity and stimulate cytokine production, IgA secretion, phagocytosis, and production of substances (such as organic acids, hydrogen peroxide, and bacteriocins) that are inhibitory to pathogens. They also compete for nutrients with pathogenic bacteria and inhibit pathogen attachment and action of microbial toxin. Probiotics also have a trophic effect on intestinal mucosa (by stimulating the proliferation of normal epithelium that maintains mucosal barrier defenses), modulate innate and adaptive immune defense mechanisms via the normalization of altered gut flora, and prevent bacterial translocation12–16. Table 3 and Table 4 provide a summary of various studies demonstrating different mechanisms of action of probiotics in experimental and clinical studies, respectively.\n\n\nProbiotic use in critically ill children\n\nStudies have evaluated the role of probiotics in critically ill children for the prevention and treatment of necrotizing enterocolitis (NEC), antibiotic-associated diarrhea (AAD), and HCAIs, including ventilator-associated pneumonia (VAP), Candida colonization, and invasive candidiasis.\n\nIn 1999, a study showed that oral administration of Lactobacillus acidophilus and Bifidobacterium infantis reduced NEC17. This was followed by a negative study showing that 7 days of L. rhamnosus GG supplementation starting with the first feed was not effective in reducing the incidence of urinary tract infection, NEC, or sepsis in preterm infants18. However, subsequent randomized controlled trials (RCTs) with different strains of Lactobacilli and Bifidobacteria showed a significant reduction in the development of NEC19,20. A systematic review and meta-analysis by Alfaleh et al.21 in 2008 concluded that probiotic supplementation reduced the incidence of NEC stage II (or more) and mortality. A more recent meta-analysis by the same authors, involving 24 trials in preterm neonates, found that supplementation with probiotic preparations containing Lactobacillus either alone or in combination with Bifidobacterium prevents severe NEC and reduces all-cause mortality22.\n\nThe osmotic and invasive AAD is often observed among critically ill children receiving broad-spectrum antibiotics. It is attributed to overgrowth of pathogens and a decrease in population of microbes that have beneficial metabolic functions23. Several investigators have shown that probiotics could prevent AAD. The results of meta-analyses on the effect of probiotics for the prevention of AAD are given in Table 5.\n\nThere are limited studies in this field in critically ill children. Most of the studies are in critically ill adults. These studied have yielded mixed results. A randomized trial that included mechanically ventilated, multiple-trauma patients (n = 65) demonstrated that 15 days of multi-strain probiotic therapy led to a significant reduction in the rate of infection, SIRS, severe sepsis, duration of ventilation, intensive care unit (ICU) stay, and mortality24. In contrast, a systematic review (eight RCTs; n = 999) revealed no beneficial effect of probiotics or synbiotics on critically ill adults in terms of clinical outcomes, namely length of ICU stay, incidence of HCAIs, pneumonia, and hospital mortality25. A meta-analysis of 12 RCTs that included 1546 critically ill adult patients found that the use of probiotics was associated with a statistically significant reduction in nosocomial pneumonia (odds ratio [OR] = 0.75, 95% confidence interval [CI] = 0.57–0.97, P = 0.03, I[2] = 46%), although there was no statistically significant effect on ICU and in-hospital mortality and duration of ICU and hospital stay26. In the same year, another systemic review of 23 RCTs, by Petrof et al.27, involving critically ill adults, demonstrated that probiotics were associated with reduced infectious complications (risk ratio = 0.82, 95% CI = 0.69–0.99; P = 0.03; test for heterogeneity P = 0.05; I = 44%), VAP rates (risk ratio = 0.75, 95% CI = 0.59–0.97; P = 0.03; test for heterogeneity P = 0.16; I = 35%), and ICU mortality (risk ratio = 0.80, 95% CI = 0.59–1.09; P = 0.16; test for heterogeneity P = 0.89; I = 0%). There was no influence on in-hospital mortality or length of ICU and hospital stay. The results of a meta-analysis by Bo et al.28 that included eight RCTs (n = 1083) in adults found that probiotics resulted in decreased incidence of VAP (OR = 0.70, 95% CI = 0.52–0.95, low-quality evidence).\n\nIn critically ill children, Honeycutt et al.29 observed a statistically non-significant trend toward an increased rate of infection with probiotic strain (11 versus 4, relative risk [RR] = 1.94, 95% CI 0.53–7.04; P = 0.31). They had randomly assigned 61 critically ill children to receive either a probiotic (one capsule of L. rhamnosus strain GG and inulin daily) or placebo (one capsule of inulin) until discharge from the hospital. However, these findings were not substantiated by subsequent studies in children. Wang et al.30, in an RCT comprising 100 critically ill full-term infants, found that administration of a probiotics mix (L. casei, L. acidophilus, Bacillus subtilis, and Enterococcus faecalis) three times daily for 8 days enhanced immune activity, decreased incidence of nosocomial pneumonia and MODS, and reduced length of hospital stay. Recently, Banupriya et al.31 published an open-label randomized trial that included 150 children, aged 12 years or younger, who were likely to need mechanical ventilation for more than 48 hours. The intervention group received a probiotics mix of L. acidophilus, L. rhamnosus, Lactobacillus plantarum, L. casei, Lactobacillus bulgaricus, Bifidobacterium longum, B. infantis, Bifidobacterium breve, and Streptococcus thermophilus for 7 days or until discharge, whichever was earlier; the controls did not receive either probiotics or any placebo. The authors found that probiotics resulted in a significant decrease in incidence of VAP, duration of pediatric ICU (PICU) and hospital stay, and mechanical ventilation. Also, the probiotic group had lower colonization rates with potentially pathogenic organisms (Klebsiella and Pseudomonas) (34.3% versus 51.4%; P = 0.058) and reductions of VAP caused by Klebsiella (4.2% versus 19.4%, P = 0.01) and Pseudomonas (4.2% versus 16.7%, P = 0.03). There were no complications due to the administration of probiotics.\n\nSeveral RCTs have addressed the role of probiotics in the prevention of Candida colonization and invasive candidiasis in neonates. Manzoni et al.32, in an RCT involving 80 very low birth weight (VLBW) neonates, demonstrated that orally administered L. casei subspecies rhamnosus significantly reduced the incidence and the intensity of enteric colonization by Candida species. Romeo et al.33, in a study of 249 preterm neonates who were subdivided to receive L. reuteri (n = 83), L. rhamnosus (n = 83), and no supplementation (n = 83), found that both the probiotics were effective in reducing Candida colonization in the GIT, late-onset sepsis, and abnormal neurological outcomes. Another RCT, by Demirel et al.34, found that in VLBW infants (gestational age of not more than 32 weeks and birth weight of not more than 1500g) prophylactic Saccharomyces boulardii supplementation was as effective as nystatin in reducing fungal colonization and invasive fungal infection and was more effective in reducing the incidence of clinical sepsis and number of sepsis attacks. An RCT by Roy et al.35 demonstrated that supplementation with a mix of multiple probiotics (a mix of L. acidophilus, B. longum, Bifidobacterium bifidum, and Bifidobacterium lactis) in preterm infants and neonates led to reduced enteral fungal colonization and invasive fungal sepsis, earlier establishment of full enteral feeds, and reduced duration of hospital stay. More recently, Oncel et al.36, in a RCT, demonstrated that prophylactic oral administration of L. reuteri in preterm infants (gestational age of not more than 32 weeks and birth weight of not more than 1500g) was as effective as nystatin in the prevention of fungal colonization and invasive candidiasis and reduced the incidence of sepsis, feeding intolerance, and duration of hospitalization.\n\nLimited data are available on the role of probiotics in the prevention of Candida colonization and Candida infection in critically ill pediatric patients. In a placebo-controlled RCT, we found that administration of a mix of probiotics (L. acidophilus, L. rhamnosus, B. longum, B. bifidum, S. boulardii, and S. thermophilus) for 1 week to children being treated in a PICU with broad-spectrum antibiotics decreased the prevalence of Candida colonization of the GIT by 34.5% and 37.2% on days 7 and 14, respectively, and led to an almost 50% reduction in the incidence of candiduria37. We also observed that the rate of Candida bloodstream infection was lower in the probiotic group as compared with the placebo group; the difference, however, was not statistically significant, as the sample size was not sufficient to evaluate this outcome. To test the hypothesis that the enteral supplementation with probiotics in critically ill children can decrease the prevalence of invasive candidiasis, we conducted a retrospective “before and after” study that included critically ill children on broad-spectrum antibiotics for at least 48 hours. The study showed that the probiotics group (4 of 344, 1.2%) had a significantly lower incidence of candidemia than the control group (14 of 376, 3.7%, RR 0.31; 95% CI 0.10–0.94; P = 0.03)38. Candiduria was noted in 10.7% of patients in the probiotic group and 22% in the control group (RR 0.48; 95% CI 0.34–0.7; P = 0.0001)38.\n\nComplementing these clinical studies, laboratory studies have also shown that several probiotic strains prevent Candida colonization by inhibiting adhesion and biofilm formation, germination, and conversion of yeast to germ (filamentation)14,39. Overall, the current evidence shows that supplementation of probiotics could be a potentially effective strategy in reducing Candida colonization as well as invasive candidiasis in critically ill children.\n\n\nSafety of probiotics\n\nAlthough most commercially available probiotic strains are widely regarded as safe, there are some concerns with respect to safety, particularly in severely debilitated or immunosuppressed patients3. Though L. rhamnosus belongs to the normal human rectal, oral, and vaginal mucosal flora, there are a few case reports of liver abscess due to L. rhamnosus, lactobacillemia, and infective endocarditis40–46. Lactobacillus sepsis has been documented in a few reports and was directly linked with the ingestion of probiotic supplements, especially among immunocompromised patients and those with endocarditis40. Kunz et al.47 described two premature infants with short gut syndrome who were fed via gastrostomy or jejunostomy and developed Lactobacillus bacteremia while taking Lactobacillus GG supplements. Land et al.48 reported two children with definitive probiotic sepsis: a 4-month-old infant with AAD after cardiac surgery who developed Lactobacillus GG endocarditis 3 weeks after commencing Lactobacillus GG supplementation and a 6-year-old girl with cerebral palsy and AAD who developed Lactobacillus GG bacteremia on day 44 of treatment. The use of L. rhamnosus GG in critically ill children was found to have a statistically non-significant trend toward increase in nosocomial infection29. Nonetheless, the risk of infection due to Lactobacilli is extremely rare and is estimated to cause 0.05 to 0.4% of cases of infective endocarditis and bacteremia49. There are rare reports of fungemia and septicemia in immunocompromised patients and critically ill patients with the use of S. boulardii50–52. Recently, there have been case reports of B. longum bacteremia in preterm infants receiving probiotics53,54.\n\nSeveral studies support the general safety of probiotics in a wide range of settings. Manzoni et al.55, in a retrospective 6-year cohort study involving VLBW infants, demonstrated that administration of Lactobacillus GG as a single dose of 3×109 CFU/day from the fourth day of life for 4 to 6 weeks was well tolerated without any adverse effects and that none had bacteremia or sepsis episode attributable to Lactobacillus GG. Srinivasan et al.56 conducted a prospective study on children admitted to a PICU (n = 28) to establish clinical safety (invasive infection/colonization) of L. casei Shirota by bacteriologic surveillance in surface swabs and endotracheal aspirates (colonization) as well as blood, urine, and sterile body fluid cultures. They found no evidence of either colonization or bacteremia with L. casei Shirota, and the preparation was well tolerated with no apparent side effects. Simakachorn et al.57, in an RCT involving 94 mechanically ventilated children (1 to 3 years), demonstrated that test formula containing a synbiotic blend (L. paracasei NCC 2461, B. longum NCC 3001, fructooligosaccharides, inulin, and Acacia gum) was well tolerated.\n\nIt has been suggested that the presence of a single major risk factor (immunocompromised state and premature infants) or more than one minor risk factor (cardiac valvular disease, central venous catheter, impaired intestinal epithelial barrier, administration of probiotics by jejunostomy, and probiotics with properties of high mucosal adhesion or known pathogenicity) merits caution in using probiotics because of the risk of probiotics-sepsis58.\n\nOther safety concerns of theoretical importance are genetic transfer of antibiotic resistance from probiotic strains to more pathogenic bacteria in intestinal microbiota (particularly Enterococcus and Staphylococcus aureus)59,60, deleterious metabolic activities, and excessive immune stimulation in susceptible individuals3,14. Many strains of Lactobacilli are naturally resistant to vancomycin.\n\n\nFuture directions\n\nAs is evident from many recent studies, probiotics have a promising role in prophylaxis and the treatment of various conditions in critically ill children. However, these results are derived mainly from studies conducted in single centers and are limited by many factors, including small sample sizes, different populations and disease conditions studied, and heterogeneity in the probiotic strains, dose, and duration used. For probiotics to exert their action, it is important that they achieve tight adhesion to intestinal mucosa, and this may be difficult in critical illness. Most of the strains colonize the intestine only after 1 week of consumption, whereas early and effective mucosal adherence is needed to prevent MODS in critically ill children. Well-designed, large multi-center studies are needed for a better understanding of the role of probiotics in critically ill children as well as their pharmacokinetics, mechanisms of action, appropriate dose, administrative regimens, interactions, side effects, risk-benefit potential, and selection of specific probiotics (single-strain or multi-strain), dose, and duration for specific critical care conditions.\n\n\nConclusions\n\nProbiotics have the ability to restore the imbalance of intestinal microbiota and function in critically ill children and have been used for various indications, including the prevention of AAD, HCAIs, VAP, Candida colonization, and invasive candidiasis. Safety may be of concern in critically ill, fragile children, as probiotic strains may (albeit rarely) cause bacteremia, fungemia, and sepsis. Well-designed multi-center RCTs are needed to address these issues before the routine use of probiotics is recommended in critically ill children.",
"appendix": "Author contributions\n\n\n\nSunit C. Singhi conceived the plan of the review, drafted the broad outline, critically reviewed the draft, and finalized the manuscript. Suresh Kumar carried out the literature search and drafted the manuscript. Both authors read and approved the final manuscript.\n\n\nCompeting interests\n\n\n\nThe author(s) declared that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nMarshall JC, Christou NV, Meakins JL: The gastrointestinal tract. The \"undrained abscess\" of multiple organ failure. Ann Surg. 1993; 218(2): 111–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAlverdy JC, Laughlin RS, Wu L: Influence of the critically ill state on host-pathogen interactions within the intestine: gut-derived sepsis redefined. Crit Care Med. 2003; 31(2): 598–607. 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Clin Exp Allergy. 2005; 35(12): 1511–20. PubMed Abstract | Publisher Full Text\n\nWeinstein PD, Cebra JJ: The preference for switching to IgA expression by Peyer's patch germinal center B cells is likely due to the intrinsic influence of their microenvironment. J Immunol. 1991; 147(12): 4126–35. PubMed Abstract\n\nCorr SC, Li Y, Riedel CU, et al.: Bacteriocin production as a mechanism for the antiinfective activity of Lactobacillus salivarius UCC118. Proc Natl Acad Sci U S A. 2007; 104(18): 7617–21. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRoberfroid MB, Bornet F, Bouley C, et al.: Colonic microflora: nutrition and health. Summary and conclusions of an International Life Sciences Institute (ILSI) [Europe] workshop held in Barcelona, Spain. Nutr Rev. 1995; 53(5): 127–30. PubMed Abstract | Publisher Full Text\n\nConly JM, Stein K, Worobetz L, et al.: The contribution of vitamin K2 (menaquinones) produced by the intestinal microflora to human nutritional requirements for vitamin K. Am J Gastroenterol. 1994; 89(6): 915–23. PubMed Abstract\n\nYounes H, Coudray C, Bellanger J, et al.: Effects of two fermentable carbohydrates (inulin and resistant starch) and their combination on calcium and magnesium balance in rats. Br J Nutr. 2001; 86(4): 479–85. PubMed Abstract | Publisher Full Text\n\nMachairas N, Pistiki A, Droggiti DI, et al.: Pre-treatment with probiotics prolongs survival after experimental infection by multidrug-resistant Pseudomonas aeruginosa in rodents: an effect on sepsis-induced immunosuppression. Int J Antimicrob Agents. 2015; 45(4): 376–84. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMangell P, Lennernäs P, Wang M, et al.: Adhesive capability of Lactobacillus plantarum 299v is important for preventing bacterial translocation in endotoxemic rats. APMIS. 2006; 114(9): 611–8. PubMed Abstract | Publisher Full Text\n\nRuan X, Shi H, Xia G, et al.: Encapsulated Bifidobacteria reduced bacterial translocation in rats following hemorrhagic shock and resuscitation. Nutrition. 2007; 23(10): 754–61. PubMed Abstract | Publisher Full Text\n\nSánchez E, Nieto JC, Boullosa A, et al.: VSL#3 probiotic treatment decreases bacterial translocation in rats with carbon tetrachloride-induced cirrhosis. Liver Int. 2015; 35(3): 735–45. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nShimizu K, Ogura H, Goto M, et al.: Synbiotics decrease the incidence of septic complications in patients with severe SIRS: a preliminary report. Dig Dis Sci. 2009; 54(5): 1071–8. PubMed Abstract | Publisher Full Text\n\nHayakawa M, Asahara T, Ishitani T, et al.: Synbiotic therapy reduces the pathological gram-negative rods caused by an increased acetic acid concentration in the gut. Dig Dis Sci. 2012; 57(10): 2642–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJain PK, McNaught CE, Anderson AD, et al.: Influence of synbiotic containing Lactobacillus acidophilus La5, Bifidobacterium lactis Bb 12, Streptococcus thermophilus, Lactobacillus bulgaricus and oligofructose on gut barrier function and sepsis in critically ill patients: a randomised controlled trial. Clin Nutr. 2004; 23(4): 467–75. PubMed Abstract | Publisher Full Text\n\nMohan R, Koebnick C, Schildt J, et al.: Effects of Bifidobacterium lactis Bb12 supplementation on intestinal microbiota of preterm infants: a double-blind, placebo-controlled, randomized study. J Clin Microbiol. 2006; 44(11): 4025–31. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSanaie S, Ebrahimi-Mameghani M, Hamishehkar H, et al.: Effect of a multispecies probiotic on inflammatory markers in critically ill patients: A randomized, double-blind, placebo-controlled trial. J Res Med Sci. 2014; 19(9): 827–33. PubMed Abstract | Free Full Text | F1000 Recommendation\n\nMcNaught CE, Woodcock NP, Anderson AD, et al.: A prospective randomised trial of probiotics in critically ill patients. Clin Nutr. 2005; 24(2): 211–9. PubMed Abstract | Publisher Full Text\n\nEbrahimi-Mameghani M, Sanaie S, Mahmoodpoor A, et al.: Effect of a probiotic preparation (VSL#3) in critically ill patients: A randomized, double-blind, placebo-controlled trial (Pilot Study). Pak J Med Sci. 2013; 29(2): 490–4. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nD'Souza AL, Rajkumar C, Cooke J, et al.: Probiotics in prevention of antibiotic associated diarrhoea: meta-analysis. BMJ. 2002; 324(7350): 1361. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSzajewska H, Ruszczyński M, Radzikowski A: Probiotics in the prevention of antibiotic-associated diarrhea in children: a meta-analysis of randomized controlled trials. J Pediatr. 2006; 149(3): 367–72. PubMed Abstract | Publisher Full Text\n\nJohnston BC, Supina AL, Vohra S: Probiotics for pediatric antibiotic-associated diarrhea: a meta-analysis of randomized placebo-controlled trials. CMAJ. 2006; 175(4): 377–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHempel S, Newberry SJ, Maher AR, et al.: Probiotics for the prevention and treatment of antibiotic-associated diarrhea: a systematic review and meta-analysis. JAMA. 2012; 307(18): 1959–69. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSzajewska H, Kołodziej M: Systematic review with meta-analysis: Saccharomyces boulardii in the prevention of antibiotic-associated diarrhoea. Aliment Pharmacol Ther. 2015; 42(7): 793–801. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSzajewska H, Kołodziej M: Systematic review with meta-analysis: Lactobacillus rhamnosus GG in the prevention of antibiotic-associated diarrhoea in children and adults. Aliment Pharmacol Ther. 2015; 42(10): 1149–57. PubMed Abstract | Publisher Full Text | F1000 Recommendation"
}
|
[
{
"id": "13090",
"date": "29 Mar 2016",
"name": "Margaret Parker",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13091",
"date": "29 Mar 2016",
"name": "Evangelos J. Giamarellos-Bourboulis",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-407
|
https://f1000research.com/articles/5-406/v1
|
29 Mar 16
|
{
"type": "Review",
"title": "Finding Ponce de Leon’s Pill: Challenges in Screening for Anti-Aging Molecules",
"authors": [
"Surinder Kumar",
"David B. Lombard"
],
"abstract": "Aging is characterized by the progressive accumulation of degenerative changes, culminating in impaired function and increased probability of death. It is the major risk factor for many human pathologies – including cancer, type 2 diabetes, and cardiovascular and neurodegenerative diseases – and consequently exerts an enormous social and economic toll. The major goal of aging research is to develop interventions that can delay the onset of multiple age-related diseases and prolong healthy lifespan (healthspan). The observation that enhanced longevity and health can be achieved in model organisms by dietary restriction or simple genetic manipulations has prompted the hunt for chemical compounds that can increase lifespan. Most of the pathways that modulate the rate of aging in mammals have homologs in yeast, flies, and worms, suggesting that initial screening to identify such pharmacological interventions may be possible using invertebrate models. In recent years, several compounds have been identified that can extend lifespan in invertebrates, and even in rodents. Here, we summarize the strategies employed, and the progress made, in identifying compounds capable of extending lifespan in organisms ranging from invertebrates to mice and discuss the formidable challenges in translating this work to human therapies.",
"keywords": [
"aging",
"anti-aging medicine",
"age-related diseases"
],
"content": "Introduction\n\nAging is characterized by molecular, cellular, and organismal changes that culminate in the inability of an organism to maintain physiological integrity1. In humans, aging is associated with a greatly increased predisposition to a wide variety of diseases, including cancer, type 2 diabetes (T2D), neurodegeneration, and cardiovascular disease, leading to increased morbidity and mortality1,2. The long-term objective of aging research is to develop interventions that can delay the onset of age-associated diseases and promote longevity. With this goal, research in biogerontology is focused on elucidating basic mechanisms of aging. Current evidence suggests that many of these mechanisms are conserved among eukaryotes, from yeast to mammals.\n\nIn recent decades, work in diverse organisms has identified cellular signaling pathways that modulate the aging rate3,4. Many of these pathways normally function to sense the nutritional status of the organism (Figure 1) and initiate signaling cascades that modulate specific inter- and intra-cellular pathways and alter target cell physiology accordingly2. These nutrient-sensing pathways, which include insulin and insulin-like growth factor (IGF) signaling (IIS)5, target of rapamycin (mTOR) signaling6, adenosine monophosphate (AMP)-activated protein kinase (AMPK) signaling7, and sirtuins8, coordinate cellular growth- and metabolism-related processes and integrate them with levels of nutrients, energy, growth factors, and stress. When nutrient levels and growth cues are reduced, signaling through these pathways is altered. Genetic or, in some cases, pharmacologic manipulation of these pathways can lead to lifespan extension, whereas their age-associated dysregulation may contribute to organismal senescence.\n\nDysregulation of nutrient-sensing pathways, mitochondrial dysfunction, loss of proteostasis, stem cell attrition, accumulated DNA damage, reduced autophagy, accumulation of senescent cells, and increased sterile inflammation are some important pathways thought to drive aging1.\n\nDietary restriction (DR), a dietary regimen involving either a reduction in overall calorie ingestion without malnutrition or diminished intake of specific dietary components such as amino acids, is the best-characterized intervention that slows aging and delays disease in a wide range of species9,10. Molecular effectors implicated in mediating the remarkable effects of DR include these nutrient-sensing pathways9. Initial evidence suggests that some of these same pathways may impact aging and disease in humans as well. For example, genetic variants in the FOXO3A gene, encoding a transcription factor downstream of IIS, have been linked to human longevity11–16. Individuals with Laron dwarfism have greatly reduced serum IGF1 levels and profound protection from T2D and cancer17. Pharmacological interventions that partially mimic DR by modulating activities of these nutrient-sensing pathways have the potential to improve healthspan and promote longevity. For example, rapamycin, a specific inhibitor of mTOR, has been proposed to provoke some of the beneficial effects of DR under standard feeding and nutrient conditions18. Similarly, a handful of other molecules such as metformin and resveratrol have been shown to modulate nutrient signaling and promote healthspan in multiple model organisms and are discussed in detail subsequently.\n\nIn addition to dysregulation of nutrient-sensing pathways, other conserved mechanisms implicated in the deleterious manifestations of aging include (Figure 1) i) mitochondrial dysfunction, leading to impaired respiratory metabolism, increased generation of reactive oxygen species (ROS), as well as potentially other sequelae, ii) increased accumulation of DNA damage, induced by exogenous insults and endogenous hazards including DNA replication errors and ROS, iii) diminished proteostasis associated with increased protein misfolding and aggregation, iv) cellular senescence, contributing to tissue dysfunction, v) increased sterile inflammation, vi) stem cell attrition, and vii) epigenetic alterations1,19. For a more complete discussion of conserved aging mechanisms, the reader is referred elsewhere1. Pharmacological agents targeting some of these changes represent candidate anti-aging drugs. In this review, we will provide an overview of pharmacological interventions with known or potential ability to delay aging and promote late-life health. First, we summarize the major contributions that studies in invertebrate model systems have made towards screening efforts to identify small molecule anti-aging drugs. Then we focus in depth on molecules currently under study for their potential to extend lifespan and delay disease. Finally, challenges in screening for new anti-aging drugs and in translating this work to humans will be discussed.\n\n\nInvertebrates as model systems to screen pro-longevity small molecules\n\nDue to a variety of factors – notably including ease of genetic manipulation and a physiology similar to that of humans – the mouse has become the pre-eminent mammalian model organism in aging biology20. However, in light of the high housing costs and relatively long lifespan of mice, large-scale unbiased screening to identify anti-aging medicines is not feasible in this organism. With the realization that many aging-related pathways are evolutionarily conserved, even among widely divergent species, short-lived invertebrate models have instead been employed for such screening. The nematode Caenorhabditis elegans – with its short lifespan of ~3 weeks, ease of culture and genetic manipulation, and well-characterized aging biology – represents a very attractive model system for chemical screening to identify compounds that modulate lifespan and age-related phenotypes. Indeed, several studies have identified a number of candidate anti-aging compounds using C. elegans as a model organism. To date, the most comprehensive small molecule lifespan screen using C. elegans was conducted by Petrascheck et al., who evaluated 88,000 chemicals for their ability to enhance longevity21. They identified 115 compounds that significantly increased worm lifespan. Interestingly, one of these displayed structural resemblance to human antidepressants that affect signaling by the neurotransmitter serotonin. They subsequently found that mianserin, a serotonin receptor antagonist used as an antidepressant in humans, extends C. elegans lifespan when administered at 50 μM, likely via mechanisms linked to DR21. In an evaluation of 19 compounds with known effects on human physiology, Evason et al. reported that the anticonvulsants ethosuximide (dosed at 2 and 4 mg/mL), trimethadione (4 mg/mL), and 3,3-diethyl-2-pyrrolidinone (2 mg/mL) delayed age-related changes and increased C. elegans lifespan22.\n\nUsing a bioinformatics approach to identify DR mimetics, Calvert et al. analyzed drugs that induce gene expression changes similar to those associated with DR and identified 11 small molecules with this property23. Interestingly, among five drugs tested, four – rapamycin (administered at 10 μM), allantoin (250 μM), trichostatin A (100 μM), and LY-294002 (100 μM) – provoked increased lifespan and healthspan in wild-type (WT) C. elegans. Conversely, no longevity effects were observed in the eat-2 mutant background, a genetic DR model, suggesting that the life-extending effects of these drugs may indeed occur via DR-related mechanisms23.\n\nA study by Alavez et al. reported that amyloid-binding compounds maintain protein homeostasis and extend lifespan in C. elegans24. Exposure of WT worms to the amyloid-binding dye Thioflavin T (ThT) at either 50 or 100 μM throughout adulthood increased median lifespan by 60% and maximal lifespan by 43–78%24. ThT treatment reduced Aβ-aggregation and preserved muscle integrity in C. elegans models of Alzheimer’s disease (AD), resulting in a decreased proportion of paralyzed worms. ThT administration also suppressed the toxicity associated with metastable proteins in mutant worms24. ThT-mediated suppression of protein aggregation and lifespan extension depended upon molecular chaperones, autophagy, proteosomal function, the proteostasis regulator heat shock factor 1 (HSF-1), and the stress resistance and longevity transcription factor SKN-124. Compounds with structural similarity to ThT also extended worm lifespan by up to 40%, but at significantly lower concentrations than ThT. Moreover, exposure to other protein-aggregate-binding compounds like curcumin (100 μM) and rifampicin (10–100 μM) extended worm lifespan by up to 45%24. These results highlight the importance of proteostasis in worm healthspan and lifespan, and provide further impetus for the development of interventions capable of maintaining proteostasis to suppress aging and age-related diseases.\n\nThe National Institute of Aging has recently sponsored a pharmacological intervention program using Caenorhabditis as a model system, analogous to similar ongoing efforts in the mouse. The Caenorhabditis Intervention Testing Program (CITP) is a multi-institutional effort aimed at identifying compounds with the ability to extend lifespan and enhance healthspan, using multiple Caenorhabditis species and multiple strains of C. elegans. The identification of compounds that are effective in genetically diverse worm populations may accelerate the discovery of interventions that can extend lifespan/healthspan in other species, potentially including humans.\n\nThe fruit fly Drosophila melanogaster represents another model suitable for the screening of anti-aging compounds25. A wide variety of genetic strains of D. melanogaster are available, with different mean lifespans, useful for validation of compound efficacy across multiple genetic backgrounds. Similar to C. elegans, Drosophila has a short lifespan, and the many genetic tools available in this organism facilitate mechanistic study of lead compounds25. The first study reporting lifespan extension in Drosophila by administration of a drug was performed by Kang et al., who showed that feeding Drosophila 4-phenylbutyrate at 5–10 mM – a drug with multiple activities, including histone deacetylase inhibition – significantly increased both median and maximum lifespan without negative impacts on locomotion, stress resistance, or reproduction26. A more recent study described the screening of protein kinase inhibitors for effects on Drosophila lifespan27. Among the 80 inhibitors tested in this study, 17 significantly increased Drosophila lifespan without affecting food intake or consumption, indicating that the effects of these inhibitors on Drosophila lifespan do not involve DR27. In this regard, a recent study by Slack et al. reported that attenuation of RAS-Erk-ETS signaling results in reduced IIS and provokes lifespan extension in Drosophila28. Trametinib (1.56–15.6 μM), a highly specific MEK inhibitor that attenuates signaling downstream of RAS, can prolong median lifespan of female Drosophila by up to 12% (p=1.92 × 10-10), and at higher doses (156 μM), improves late-life survival28. Trametinib administration was effective in promoting fly longevity even when administered to middle-aged animals. These and similar findings with other drugs – cf. extension of mouse lifespan by rapamycin treatment initiated in middle age, see below – raise the possibility that anti-aging medicines in humans might be effective even when administered to older individuals, thus avoiding potential developmental side effects of these drugs.\n\n\nCompounds that modulate aging and age-associated phenotypes in mammals\n\nmTOR is a conserved serine/threonine kinase that senses and responds to nutrient availability, growth factors, and environmental stress and plays a key role in triggering growth6,29. In multicellular eukaryotes, mTOR exists in two distinct multi-protein complexes, mTORC1 and mTORC2, distinguished by their association with regulatory-associated protein of mTOR (RAPTOR) and rapamycin-insensitive companion of mTOR (RICTOR), respectively30,31. Rapamycin forms a complex with the FKBP12 protein, which binds to mTORC1 and inhibits its activity32. Importantly, chronic treatment with rapamycin also inhibits mTORC233. mTORC1 activity is regulated by nutrients (glucose and amino acids), cytokines, hormones (insulin or IGF1), energy (ATP levels), and oxidative stress via PI3K, AKT, and AMPK signaling6. Key downstream mediators of mTORC1 signaling are pathways that control cell growth, proliferation, stress response, and autophagy29,34. mTORC1, therefore, critically integrates cellular growth and maintenance with nutrient availability, hormonal cues, and other environmental stimuli.\n\nA number of studies have established a link between mTOR signaling pathways and longevity in organisms ranging from yeast to mammals. Inhibition of mTOR signaling by genetic or pharmacologic means extends lifespan in yeast35–37, nematodes38,39, fruit flies40, and mice33,41–47. Likewise, genetic deletion in mice of the downstream mTORC1 effector, S6 kinase 1, increases oxidative metabolism, protects against age- and diet-induced obesity, and increases female lifespan47,48. Consistently, enhanced activity of the mTORC1 target 4E-BP1 in skeletal muscle results in increased oxidative metabolism and protects mice from diet- and age-induced metabolic dysfunction49.\n\nIn a landmark study, NIA’s Interventions Testing Program (ITP) showed that treatment of a genetically heterogeneous mouse stock with the mTOR inhibitor rapamycin (administered at 14 mg/kg food; 2.24 mg/kg body weight/day) initiated at either 9 months or 20 months of age extended lifespan in both sexes43,50. A follow-up study demonstrated that the increase in mouse lifespan induced by rapamycin is dose and sex dependent. At a given chow concentration of rapamycin, female mice showed a greater increase in lifespan than did males, which correlated with higher blood levels of rapamycin achieved in females relative to males51. Rapamycin treatment induced entirely distinct gene expression changes in males and females, implying the existence of sex-specific responses to mTOR inhibition51. Furthermore, the expression patterns of xenobiotic-metabolizing enzymes in the livers of rapamycin-treated (14 mg/kg food) mice differed strikingly from those in DR-exposed animals at 12 months of age51. Indeed, DR is less effective in lifespan extension when initiated later in life52–54, while rapamycin treatment extends the lifespan of mice, even when started in middle age43,55. Crucially, rapamycin-induced lifespan extension in mice has also been observed in diverse genetic backgrounds41,42,44,56.\n\nMechanisms of longevity extension by rapamycin remain a hotly debated topic in aging biology56,57. Rapamycin has anti-neoplastic properties58–60, and cancer is the major cause of death in most mouse strains that show rapamycin-mediated lifespan extension43,61. In this context, one plausible explanation for the extension of mouse lifespan by rapamycin is that this drug suppresses the onset and/or aggressiveness of lethal cancers. However, some investigators have reported that rapamycin also inhibits age-associated phenotypes besides neoplasia62,63, strongly suggesting that this drug has broader anti-aging effects. In contrast, a recent exhaustive study by Neff et al. claimed that the effects of rapamycin on aging phenotypes per se were quite limited56. In this regard, conflicting observations have been made concerning the effects of rapamycin treatment in mouse models of AD64. Long-term rapamycin treatment led to behavioral improvements in mouse AD models and induced an autophagy-mediated decrease in Aβ and hyperphosphorylated tau levels65,66. Conversely, rapamycin has been shown to promote Aβ production67,68 and led to an increase in Aβ-induced cell death69.\n\nRapamycin has significant side effects – metabolic dysfunction, cataract, and testicular atrophy in particular – that may limit its long-term utility as an anti-aging treatment in humans70,71. Most importantly, due to the immunomodulatory effects of mTOR inhibitors, treatment of human patients with the rapamycin-like drug everolimus/RAD001 is associated with a higher incidence of infection in individuals with diseases such as cancer72,73 and tuberous sclerosis complex (TSC)74. Conversely, a recent study showed that short-term administration of everolimus/RAD001 to healthy older individuals enhanced the immunological response to influenza vaccination, with modest side effects75. Decreased influenza vaccine response is a major clinical challenge in older populations76. These findings suggest that intermittent or short-term administration of rapamycin or other mTOR inhibitors might suppress certain functionally important effects of aging, such as poor immunization response, while avoiding the negative consequences associated with chronic use of these agents. A recent study in mice is consistent with this view, identifying an intermittent rapamycin administration regimen in mice that minimizes metabolic dysfunction, while maintaining chronic mTORC1 suppression in adipose tissue, though not in other tissues77. It will be of great interest to evaluate the effects of such intermittent dosing regimens on a wide range of age-associated phenotypes and on lifespan.\n\nMetformin, an oral biguanide antiglycemic agent, is the most widely used drug in the treatment of metabolic syndrome and T2D. Metformin’s mechanism of action is not completely understood and is likely to be multi-factorial. It was reported to decrease serum glucose levels by inhibiting respiratory chain Complex I in hepatocytes78, resulting in reduced ATP production, leading to activation of the LKB1 and AMPK kinases, suppressing hepatic gluconeogenesis79,80. Metformin has been reported to activate AMPK in many other tissues, including adipose, skeletal muscle, heart, pancreatic β-cells, and hypothalamus with potential beneficial physiological effects in patients with T2D81,82. However, metformin also exerts important effects independent of AMPK and LKB183, e.g. by antagonizing the action of glucagon84. Recently, another AMPK-independent mechanism has been revealed for metformin. A study by Madiraju et al. showed that metformin non-competitively inhibits the redox shuttle enzyme mitochondrial glycerophosphate dehydrogenase, increasing the cytosolic redox state and decreasing the mitochondrial redox state85. This suppresses hepatic gluconeogenesis by reducing the conversion of lactate and glycerol to glucose85. Although metformin is currently approved for treatment of T2D, a large literature suggests efficacy of metformin against other conditions, particularly cardiovascular diseases and cancer78. In this regard, a recent study demonstrated that metformin reduces tumorigenesis by inhibiting mitochondrial Complex I in cancer cells86.\n\nAMPK activation provokes longevity in flies and worms87,88. A number of studies suggest that metformin treatment can recapitulate some effects of DR. In this context, several studies have examined the effects of metformin and other biguanides on lifespan and reported a variety of outcomes. Metformin and other biguanides extend C. elegans lifespan in a dose-dependent manner89–91. The increase in C. elegans lifespan by metformin is mediated through inhibition of bacterial folate and methionine metabolism, which in turn alters methionine metabolism in the worm, resulting in reduced S-adenosylmethionine and increased S-adenosylhomocysteine levels89. However, metformin apparently does not extend longevity in D. melanogaster92,93. Indeed, despite robust activation of AMPK, high doses of metformin actually decrease lifespan of both male and female flies93, perhaps due to disruption of intestinal fluid homeostasis93. However, metformin treatment suppressed age-related phenotypes in intestinal midgut stem cells94 and also exerted beneficial effects in a fly obesity model95. A recent study showed that metformin treatment causes a significant extension in mean and maximal lifespan in both sexes of the cricket Acheta domesticus96.\n\nSeveral studies have been performed in rodents to test the effects of metformin and other biguanides on lifespan; the outcomes have varied with genotype, sex, and dose and duration of treatment97. Chronic treatment with metformin (100 mg/kg in the drinking water) enhanced the mean lifespan of cancer-prone HER-2/neu transgenic, outbred SHR, and inbred 129/Sv female mice by 8% (p<0.05), 37.8% (p<0.01), and 4.4% (p<0.05), respectively98–100. Metformin treatment also extended the maximum lifespan of HER-2/neu transgenic and outbred SHR female mice by 9% and 10.3%, respectively, while no effect was observed on maximal lifespan in inbred 129/Sv female mice98–100. Conversely, treatment of inbred 129/Sv male mice with a similar dose of metformin actually reduced mean lifespan by 13.4%100. However, metformin treatment (2 mg/mL in drinking water) in a transgenic mouse model of Huntington disease (HD) prolonged male mean lifespan by 20.1% (p=0.017), but did not affect female survival101. It has been reported that metformin treatment (100 mg/kg in the drinking water) of female outbred SHR mice initiated at 3 months of age induced a trend towards increased mean lifespan102. Metformin treatment also postponed the onset of detectable tumors when started at young or middle ages, but not at old age102. Neonatal metformin treatment of 129/Sv mice (100 mg/kg via subcutaneous injection) led to a 20% (p<0.001) increase in male mean lifespan and also slightly increased maximum lifespan by 3.5%103. However, in females, the mean and maximum lifespan in metformin-treated groups were decreased by 9.1% and 3.8%, respectively103. In a recent study by Martin-Montalvo et al., male C57BL/6 mice supplemented with 0.1% metformin in the diet showed a 5.8% increase in mean lifespan (p=0.02, Gehan–Breslow survival test), whereas supplementation with 1% metformin was toxic and reduced mean lifespan by 14.4%104. However, supplementation of B6C3F1 male mice with 0.1% metformin resulted in extension of mean lifespan only by 4.2% (p=0.064, Gehan–Breslow)104. Treatment with another biguanide, phenformin (2 mg/mouse in 0.2 mL of drinking water), significantly reduced spontaneous tumor development in female C3H/Sn mice and prolonged mean lifespan by 21% or more (p<0.05)105,106 and maximum lifespan by 26%105. Evaluation of the lifespan effects of metformin in mice by the ITP consortium is ongoing, and the results should be available soon.\n\nIn rats, buformin treatment (5 mg/rat in 1 mL of drinking water) led to a non-significant 7.3% increase in mean lifespan of female LIO animals, while phenformin (5 mg/rat in 1 mL of drinking water) had no effect105. However, administration of both buformin and phenformin increased the maximum lifespan of female LIO rats by 5.5% and 9.8%, respectively105. Treatment with metformin (300 mg/kg/day) did not increase either mean or maximum lifespan of male F344 rats107. However, in the same report, a parallel group of male F344 rats exposed to DR also failed to exhibit lifespan extension107, leaving the metformin results in this study somewhat inconclusive. Mechanistically, treatment with metformin has been proposed to mimic some effects of DR, in particular by increasing AMPK activity and also activating antioxidant responses, leading to a reduction in both oxidative damage accumulation and chronic inflammation104.\n\nAlthough no study has formally analyzed the effects of long-term metformin treatment on lifespan in healthy humans, randomized clinical trials of metformin showed beneficial effects on health and survival in overweight/obese patients with T2D, as shown by decreased incidences of cardiovascular disease and cancer and reduced overall mortality108–110. However, when combined with sulfonylurea, metformin increased the risk of diabetes-related death and all-cause mortality in a mixed group of non-overweight and overweight/obese individuals with T2D78,108. Consistent with these observations, a recent study by Bannister et al. reported that patients with T2D treated with metformin displayed improved survival compared to matched, non-diabetic controls, whereas those treated with sulfonylureas showed reduced survival111.\n\nGiven the relatively promising rodent data, the hints that metformin might suppress cancer and other age-associated conditions in humans, and metformin’s relatively benign safety profile, there is great current interest in formally testing the ability of this drug to delay age-associated disease in humans112. Indeed, the US Food and Drug Administration (FDA) recently approved a study termed Targeting Aging With Metformin (TAME) for the evaluation of metformin as an anti-aging drug. The TAME project will involve approximately 3000 participants between the ages of 70 years and 80 years who either already have one, two, or all three of the conditions: cancer, heart disease, or cognitive impairment or are at risk of developing them. The trial will take place at roughly 15 centers around the United States over 5–7 years, costing approximately $50 million113. The goal of the study is to determine whether metformin can prevent the onset of age-associated disease. This landmark trial will represent the first testing of a candidate anti-aging compound in humans.\n\nThe sirtuins are a family of NAD+-dependent deacetylases/ADP-ribosyltransferases/deacylases implicated in regulating nutrient responses and numerous other aspects of cell biology8. Overexpression of Sir2, the founding member of the sirtuin family, extends replicative lifespan in the budding yeast Saccharomyces cerevisiae by repressing the accumulation of extrachromosomal rDNA plasmids, promoting segregation of an undamaged proteome to the daughter cell, enforcing subtelomeric silencing, and perhaps other mechanisms114,115. Several, though not all, investigators have found that overexpression of sirtuins in worms and flies modestly increases lifespan in these organisms116–123. Interestingly, the Sir2 homolog Sir-2.1 can extend C. elegans lifespan in a manner independent of its deacetylase activity116. Indeed, nicotinamide (NAM), a product of sirtuin activity, and its metabolite, 1-methylnicotinamide (MNA), are capable of extending worm lifespan, potentially by inducing transient ROS signaling116. In mammals, SIRT1 is the closest Sir2 homolog; overexpression of this protein in the brain (but not the whole organism) extends lifespan124, probably by enhancing hypothalamic function during aging125. Global overexpression of another sirtuin, SIRT6, extends mouse lifespan in males specifically, at least in part via suppression of lung cancer, a major cause of death in males of the mouse stock used126,127. SIRT2 overexpression stabilizes levels of the mitotic checkpoint protein BubR1 in progeroid BubR1H/H mice and extends both median and maximum lifespan in male mice of this strain128. No information is available concerning the potential effects of chronic SIRT2 overexpression in WT animals. Accumulating evidence suggests that NAD+ levels may decline during aging, impairing sirtuin activity, and that the ability of sirtuin overexpression to increase lifespan partially counters this effect by maintaining sirtuin function in the face of a diminished NAD+ pool in older organisms129.\n\nResveratrol and certain other polyphenols were originally identified as Sir2/SIRT1 activators that extended the average and maximal lifespan of yeast130. It is important to note that resveratrol is a highly promiscuous drug and exerts functionally important effects on many cellular targets131. Treatment of worms and flies with resveratrol (dosed at 100 μM in worms and 10–100 μM in flies) has also been reported to extend lifespan, dependent on the presence of functional Sir-2.1 and dSir2, respectively132. However, a study by Bass et al. claimed that resveratrol treatment (1–1000 μM) had no significant effects on Drosophila lifespan133. The same study also reported that resveratrol treatment at 100 μM induced only a slight and sporadic increase in C. elegans lifespan in both WT and sir-2.1 mutant animals, suggesting that these small increases in C. elegans lifespan induced by resveratrol may be Sir-2.1 independent133. Resveratrol protects worms from oxidative stress, radiation-induced damage, and amyloid toxicity134–136 and also induces radioprotection in flies137. Resveratrol treatment increases mean and maximum lifespan in the honeybee138 and the short-lived fishes Nothobranchius furzeri and Nothobranchius guentheri139–141.\n\nIt was reported that resveratrol and other sirtuin-activating compounds (STACs) activate Sir2/SIRT1 allosterically130. However, other groups have found that these compounds were unable to enhance SIRT1 activity towards native peptides in vitro142,143. In this context, it has been suggested that increased SIRT1 activity induced by resveratrol depends on the presence of a non-native fluorophore conjugated to the peptide sequence originally used in screening for SIRT1 activators142,143. Recent reports, however, have shown that resveratrol and other STACs directly bind to SIRT1 and allosterically enhance its deacetylase activity towards non-tagged peptide substrates144,145. Resveratrol has also been reported to inhibit the catalytic activity of human tyrosyl transfer-RNA (tRNA) synthetase (TyrRS), resulting in its nuclear translocation and stimulation of NAD+-dependent activation of poly (ADP-ribose) polymerase 1 (PARP1)146. PARP1 plays important roles in both DNA repair and transcription147.\n\nIn mice, resveratrol is protective against some damaging effects of high-fat/high-calorie diets148–151, substantially reduces the growth and development of multiple types of cancers152–154, and delays or prevents the onset of AD155,156. Moreover, in rodents and humans, resveratrol is protective against both type 1 diabetes and T2D157,158 and cardiovascular disease159 and possesses anti-inflammatory160 and anti-viral activities161. Resveratrol supplementation (either at 0.016–0.1% of diet or 25 mg/kg/day) has been reported to increase lifespan in mouse models of obesity148, AD162, HD163, and amyotrophic lateral sclerosis164,165. Resveratrol treatment (2–8 mg/kg/day) increases the lifespan of LPS-treated mice166 and attenuates catecholamine-induced mortality in obese rats (20 mg/kg/day)167. Furthermore, resveratrol (10 mg/mL, intraperitoneal injection) prolongs survival in a mouse model of sepsis-induced acute kidney injury and restores renal microcirculation168. Resveratrol administration (18 mg/kg/day in the diet) also improves survival in a rat hypertension model169. Importantly, however, resveratrol treatment (100–1200 mg/kg food) does not increase lifespan in normal chow-fed mice50,170,171. Resveratrol supplementation induces gene expression changes in several tissues that resemble those associated with calorie restriction in mice171,172.\n\nIn humans, 30-day resveratrol supplementation (150 mg/day) in obese men induced metabolic changes, including reductions in sleeping and resting metabolic rate, intrahepatic lipid content, circulating glucose levels, inflammatory markers, and systolic blood pressure173. Skeletal muscle from resveratrol-treated objects displayed increased AMPK activity, increased SIRT1 and PGC-1α protein levels, and improved mitochondrial respiration of fatty acids173. In contrast, 12 weeks’ supplementation with resveratrol (75 mg/day) in non-obese, postmenopausal women with normal glucose tolerance induced no apparent change in body composition, insulin sensitivity, resting metabolic rate, plasma lipids, or inflammatory markers174. Moreover, resveratrol supplementation had no effect on its putative molecular targets, including AMPK, SIRT1, NAMPT, and PPARGC1A, in either skeletal muscle or adipose tissue174.\n\nAn important recent study by Cai et al. demonstrated a non-linear dose response for the protective effects of resveratrol in humans and mice175. When co-administered with high-fat diet (HFD), low-dose resveratrol (~0.07 mg/kg/day) appeared to be more efficacious than high-dose (14 mg/kg/day) in reducing adenoma number and decreasing overall tumor burden in Apcmin mice, a model of intestinal carcinogenesis. Interestingly, female mice on the lower dose of resveratrol exhibited significantly higher expression and activation of AMPK in intestinal mucosa than those in the high-dose group175. Consistently, human colorectal tissues exposed to low dietary concentrations (0.01 to 0.1 μM) of resveratrol ex vivo displayed rapid AMPK activation and increased autophagy at low concentrations and a less pronounced or even no effect at higher doses (1 to 10 μM)175. This unusual effect may help rationalize the conflicting reports of resveratrol’s efficacies in humans, and future human studies using resveratrol must be designed with careful attention paid to dosage and serum levels and to a thorough assessment of effects on resveratrol’s putative molecular targets.\n\nOther STACs have been synthesized and are reported to enhance healthspan and extend lifespan in mice. The STAC SRT1720 (100 mg/kg/day) has been reported to extend mean lifespan of adult male C57BL/6J mice fed a standard diet by 8.8% (p=0.096), and up to 21.7% (p=0.0193) on a HFD, without increasing maximal lifespan in either context176,177. SRT1720 treatment improved physiological parameters in HFD-fed animals, reducing liver steatosis, increasing insulin sensitivity, enhancing locomotor activity, and also inducing a gene expression profile similar to that associated with a standard diet176. SRT1720 supplementation inhibited pro-inflammatory gene expression in liver and muscle of mice fed a standard chow diet and delayed the onset of age-related metabolic disease177. Similarly, dietary supplementation (100 mg/kg) with SRT2104, another synthetic STAC, increased both mean and maximal lifespan of male C57BL/6J mice fed a chow diet by 9.7% (p<0.05) and 4.9% (p<0.001), respectively, and increased insulin sensitivity and motor coordination while reducing inflammation178. Short-term treatment with SRT2104 preserves bone and muscle mass in an experimental atrophy model178. These findings indicate that resveratrol and other STACs can exert beneficial effects on health, particularly in the context of HFD, and that some STACs can modestly extend lifespan under normal feeding conditions; however, additional studies are warranted to better evaluate their effects on longevity in females and other strains of mice. In this regard, there is great current interest in evaluating the effects of NAD+ precursors as therapies for metabolic disease and candidate anti-aging drugs129.\n\nIn recent decades, numerous compounds with pro-healthspan and -longevity effects have been identified. Due to space limitations, we restrict our discussion to a few key small molecules that have shown beneficial effects, from invertebrate models to mice (Figure 2).\n\nRepresentative compounds (yellow boxes) target various processes or pathways that contribute to aging and either promote or suppress their activities/progression, resulting in improved health and enhanced lifespan.\n\nSpermidine is a member of the polyamine family, involved in numerous critical cellular processes including DNA stability, transcription, translation, apoptosis, cell proliferation, and cell growth179. In multiple organs, levels of polyamines have been reported to decline with age180,181. Indeed, a study by Pucciarelli et al. suggested that maintaining high levels of spermidine during aging might promote longevity182. Administration of exogenous spermidine extended the lifespan of yeast, flies, worms, and cultured human peripheral blood mononuclear cells183. Spermidine also reduces the age-related decline of locomotor performance in flies184. Furthermore, it has been reported that a polyamine-rich diet reduced age-related pathology and increased lifespan in Jcl:ICR male mice185. Conversely, depletion of endogenous spermidine by genetic manipulation of the polyamine pathway shortens lifespan in yeast183 and mice186. Spermidine supplementation reduces levels of age-related oxidative damage in mice183 and also increases stress resistance in yeast183 and flies187. The beneficial effects of spermidine are mediated mainly via induction of autophagy183,187, allowing the regulated degradation and recycling of dysfunctional cellular components188. Defective autophagy prevented the onset of spermidine supplementation-associated benefits183,187.\n\nAspirin, a derivative of salicylic acid, is the prototypical cyclooxygenase inhibitor and non-steroidal anti-inflammatory agent189. Aspirin is a versatile drug, with antithrombotic and antioxidant properties190,191. Indeed, chronic aspirin use in humans reduces the risk of mortality from a variety of age-associated diseases, including atherosclerosis, diabetes, and a variety of cancers192–196. Aspirin use has been reported to be associated with increased survival in extreme old age in humans197. In a recent study by Ayyadevara et al., aspirin was shown to upregulate the expression of antioxidant genes (superoxide dismutase, catalases, and glutathione-S-transferases), resulting in attenuation of endogenous ROS levels and extension of C. elegans lifespan198. Another study showed that aspirin treatment leads to lifespan extension in the cricket A. domesticus96. In studies by the ITP, aspirin treatment (21 mg/kg diet) led to an increase in the mean lifespan of male mice, but there was no effect in females199.\n\nNordihydroguaiaretic acid (NDGA), also known as masoprocol, is a naturally occurring dicatechol, with antioxidant, antiviral, antineoplastic, and anti-inflammatory activities200. It has been reported to be a potent antagonist of the inflammatory cytokine TNFα. Dietary administration with NDGA delayed motor deterioration in a mouse model of amyotrophic lateral sclerosis and significantly extended lifespan201. Consistently, the ITP reported that NDGA (2500 mg/kg diet) increased the lifespan of UM-HET3 male mice199,202. Lifespan extension by NDGA was not observed in female mice, even at a dose that produced blood levels equivalent to those in males202. One possible explanation for this sex discrepancy could be that male controls in this study showed a somewhat short lifespan at two of the three ITP testing sites202. Additional studies will be required to fully address this issue.\n\nAcarbose is an inhibitor of α-glucosidases, intestinal enzymes that convert complex carbohydrates into simple sugars to facilitate their absorption203. Acarbose treatment thus impairs carbohydrate digestion and inhibits the normal postprandial glucose rise203. The ITP found that acarbose administration (1000 mg/kg diet) induced a significant increase in median and maximal lifespan in both sexes, although the impact was much more pronounced in males202. Acarbose treatment increased male median lifespan by 22% (p<0.0001), but female median lifespan by only 5% (p=0.01). Similarly, maximum lifespan extension in males and females was 11% (p<0.001) and 9% (p=0.001), respectively202. Acarbose-treated mice had a significant increase in levels of serum fibroblast growth factor 21 (FGF21) and also a mild reduction in IGF1 levels202. FGF21 plays important roles in the regulation of glucose, lipid, and energy homeostasis204. Transgenic mice with constitutive FGF21 secretion displayed an increase in both mean and maximal lifespan, probably occurring via reduced IIS205,206.\n\n17-α-estradiol is a non-feminizing estrogen, with reduced binding affinity for estrogen receptors202. It inhibits the activity of the enzyme 5α-reductase, responsible for the reduction of testosterone to the more potent androgen dihydrotestosterone207, which has higher affinity for the androgen receptor than does testosterone208. 17-α-estradiol has been reported to be neuroprotective against cerebral ischemia, Parkinson’s disease, and cerebrovascular disease209–211. Recently, it has been shown to diminish metabolic and inflammatory impairment in old male mice by reducing calorie intake and altering nutrient sensing and inflammatory pathways in visceral white adipose tissues, without inducing feminization212. In ITP studies, administration of 17-α-estradiol (4.8 mg/kg diet) from 10 months of age increased male median lifespan by 12%, without significant effect on maximum lifespan or effects on female lifespan202. Similar to NDGA, the relatively short lifespan of male controls might contribute to this apparent sex discrepancy202 and further longevity studies are warranted using this drug.\n\nβ-adrenergic receptor (β-AR) antagonists bind to β-ARs (β1, 2, and 3-AR) and block the action of the endogenous catecholamines epinephrine and norepinephrine. Increased activity of β-ARs may hasten the development of age-related pathologies and increase mortality in genetically modified mice213–218. Consistently, chronic administration of β-AR agonists leads to increased mortality and morbidity219. In humans, increased production of β2-AR due to specific genetic variants is associated with reduced lifespan220. Conversely, dietary administration of β-AR blockers metoprolol (1.1 g/kg in the diet) and nebivolol (0.27 g/kg in the diet) increased the median lifespan of C3B6F1 male mice by 10% (p=0.016) and 6.4% (p=0.023), respectively, without affecting food intake or utilization221. However, no effect was observed on maximal lifespan. Consistently, treatment with metoprolol (5 mg/mL diet) and nebivolol (100 μg/mL diet) extended the median lifespan of Drosophila by 23% (p≤0.0001) and 15% (p≤0.001), respectively, without impact on food intake or locomotion221. Similar to β-AR blockers, an α1-AR antagonist, doxazosin mesylate, which inhibits the binding of norepinephrine to α1-AR on the membrane of vascular smooth muscle cells, extends C. elegans lifespan by 15%222. Given that some of these agents are routinely administered clinically as antihypertensives and their safety profiles are well characterized, they may warrant further evaluation in humans specifically for their potential anti-aging effects.\n\nAntioxidants, compounds conferring resistance to oxidative stress, have in some cases also proven successful in increasing lifespan, particularly in lower organisms. Dietary supplementation with the glutathione precursor N-acetylcysteine (NAC) increased resistance to oxidative stress, heat stress, and UV irradiation and significantly extended both the mean and the maximum lifespan of C. elegans223 and D. melanogaster224. Furthermore, treatment with EUK-134 and EUK-8, small molecule synthetic catalytic mimetics of superoxide dismutase (SOD) and catalase, was reported to extend C. elegans lifespan225; however, as discussed by Gems and Doonan, other groups have not observed this effect226. Treatment of a mixed group of male and female C57BL/6 mice with another SOD mimetic, carboxyfullerene (C3, at 10 mg/kg/day), reduced age-associated oxidative stress and mitochondrial superoxide production and modestly extended mean lifespan227. Consistently, oral administration of carboxyfullerene (C60; 4 mg/kg/day) dissolved in olive oil to male Wistar rats leads to a 90% increase in median lifespan as compared to water-treated controls228. Similarly, some other studies have shown an ability of antioxidants to extend lifespan in multiple organisms229,230.\n\nConversely, there are many reports that do not support the idea that dietary supplementation with antioxidants can increase the lifespan of healthy animals or humans as a general rule. Dietary supplementation with either vitamin E (α-tocopherol) or vitamin C (ascorbic acid) significantly shortened the lifespan of short-tailed field voles231. Similarly, treatment of male mice with a nutraceutical mixture enriched in antioxidants was ineffective in extending lifespan232. Moreover, as described in a recent review by Bjelakovic et al., systematic review and meta-analyses of a large number of randomized clinical trials evaluating the effects of dietary supplementation with various anti-oxidants (β-carotene, vitamin A, vitamin C, vitamin E, and selenium) in humans did not reveal any overall benefit; indeed, in some cases, there was evidence for increased mortality occurring in response to these agents233. Deleterious effects of antioxidant supplementation may result from inappropriate suppression of the normal signaling functions ROS play in cells, including in crucial cell populations such as stem cells234.\n\nCellular senescence refers to permanent cellular growth arrest, which can be induced by multiple stressors, including serial passage, telomere attrition, inappropriate mitotic stimuli, and genotoxic insult235. Senescence is thought to play an important role in tumor suppression in mammals236,237. However, senescent cells develop an altered secretory phenotype (termed the SASP) characterized by the release of factors such as proteases, growth factors, interleukins, chemokines, and extracellular remodeling proteins238. With advancing age, senescent cells accumulate in various tissues239–241 and potentially contribute to pathological states, as factors they secrete induce chronic inflammation, loss of function in progenitor cells, and extracellular matrix dysfunction236,242. The functional impact of senescent cells in vivo has been a hotly debated topic in aging biology for many years. Recently, genetic approaches to delete senescent cells in mice have been described, via activation of a drug-inducible “suicide gene”243. Depleting senescent cells in a progeroid mouse model substantially delayed the onset of multiple age-related phenotypes, including lordokyphosis (a measure of sarcopenia in this model), cataract, loss of adipose tissue, and impaired muscle function243. However, the overall survival of these mice was not extended substantially by deletion of senescent cells, perhaps because the suicide gene was not expressed in the heart or aorta; cardiac failure is thought to represent a major cause of mortality in this strain243. A recent landmark study by Baker et al. showed that clearance of naturally occurring senescence cells in non-progeroid mice maintained the functionality of several organs with age, delayed lethal tumorigenesis, and extended median lifespan in mixed and pure C57BL/6 genetic backgrounds by 27% (p<0.001) and 24% (p<0.001), respectively244. This study provides very strong evidence that age-associated accumulation of senescent cells contributes to age-associated pathologies and shortens lifespan in WT animals.\n\nPharmacologic, as opposed to genetic, approaches to deplete senescent cells have posed a major technical and conceptual challenge. A recent study showed that senescent cells display increased expression of pro-survival factors, responsible for their well-known resistance to apoptosis245. Interestingly, small interfering RNA (siRNA)-mediated silencing of many of these factors (ephrins, PI3Kδ, p21, BCL-xL, and others) selectively killed senescent cells but left dividing and quiescent cells unaffected. These siRNAs were termed “senolytic” siRNAs245. Small molecules (senolytic drugs) targeting the same factors also selectively killed senescent cells. Out of 46 agents tested, dasatinib and quercetin were particularly effective in eliminating senescent cells. Dasatinib, used in cancer treatment, is an inhibitor of multiple tyrosine kinases246. Quercetin is a natural flavonol that inhibits PI3K, other kinases, and serpins247,248. Dasatinib preferentially eliminated senescent human preadipocytes, while quercetin was more effective against senescent human endothelial cells and senescent bone marrow-derived murine mesenchymal stem cells (BM-MSCs). The combination of dasatinib and quercetin was effective in selective killing of senescent BM-MSCs, human preadipocytes, and endothelial cells245. The combination was more effective in killing senescent mouse embryonic fibroblasts compared to either drug alone. Treatment of chronologically aged WT mice, radiation-exposed WT mice, and progeroid Ercc1 hypomorphic mice with the combination of dasatinib and quercetin reduced the burden of senescent cells. Following drug treatment, old WT mice showed improved cardiac function and carotid vascular reactivity, irradiated mice displayed improved exercise capacity, and progeroid Ercc1-/Δ mutants demonstrated delay of age-related symptoms and pathologies245. Similarly, a recent study by Chang et al. identified ABT263 (Navitoclax, a specific inhibitor of the anti-apoptotic proteins BCL-2 and BCL-xL) as another potent senolytic agent249. ABT263, which is used for the treatment of multiple cancers250–252, induced apoptosis and selectively killed senescent cells in a manner independent of cell type or species249. In culture, senescent human lung fibroblasts (IMR90), human renal epithelial cells, and mouse embryo fibroblasts (MEFs) were more sensitive to ABT263 treatment than their non-senescent counterparts249. In contrast, another study found that ABT263 is not a broad-spectrum senolytic; instead it acts in a cell type-specific manner253. In this study, ABT263 was found to be senolytic in human umbilical vein cells (HUVECs), IMR90 cells, and MEFs, but not in human primary preadipocytes253.\n\nTreatment of either irradiated or naturally aged mice with ABT263 not only reduced the burden of senescent cells, including those among bone marrow hematopoietic stem cell (HSC) and muscle stem cell (MuSC) populations, but also suppressed the expression of several SASP factors and rejuvenated the function of aged HSCs and MuSCs249. These results, together with the impressive results obtained in genetic models described previously, indicate that senolytic drugs may have a role in improving tissue function during aging. However, some senolytic drugs are associated with toxic side effects, like thrombocytopenia and neutropenia in the case of ABT263, which are major potential hurdles in their use as anti-aging therapies. These toxicities may be mitigated somewhat if these drugs can be administered intermittently, rather than chronically, to achieve their senolytic effects.\n\nMajor results concerning the small molecules discussed in this review are summarized in Figure 2.\n\n\nFrom model organisms to humans: the challenges of screening for anti-aging drugs\n\nSeveral drugs have demonstrated great promise in the laboratory setting in enhancing the healthspan and lifespan of multiple species, including mice, raising the possibility that efficacious pharmacologic anti-aging therapy in people may be possible. However, screening for novel small molecules with anti-aging effects in mammals in an unbiased fashion represents an enormous, potentially insurmountable challenge. Alternatively, since it is clear that several cellular pathways affect longevity in an evolutionarily conserved manner, invertebrate models may be quite useful for such screening endeavors. However, some known molecular factors with major effects on mammalian lifespan (e.g. GH) are not well conserved between invertebrates and mammals. Consequently, small molecule screening efforts relying exclusively on the use of invertebrates will likely miss drugs with potent effects on mammalian aging. Moreover, many of the key physiologic features of humans and other mammals are not well modeled in invertebrates, as the latter lack specific tissues like heart and kidney and complex endocrine, nervous, and circulatory systems that are crucial targets of mammalian aging and age-related pathologies. Most invertebrate aging models possess limited regenerative capabilities and incompletely recapitulate processes such as stem cell renewal, which are required for tissue repair mechanisms that maintain tissue homeostasis in mammals, in order to sustain organ function over years and decades.\n\nThe development of new, shorter-lived vertebrate aging systems could be tremendously beneficial in screening for drugs with anti-aging activities. In this context, several features of the naturally short-lived vertebrate African turquoise killfish (N. furzeri) make this organism an attractive model system to study various aspects of vertebrate aging and potentially as a drug-screening system254–258. Recently, using a de novo-assembled genome and CRISPR/Cas9 technology, Harel et al. described a genotype-to-phenotype platform in N. furzeri, opening up the possibility of screening for gene mutations and drugs that increase lifespan in this organism in an integrative fashion259. One current major limitation of N. furzeri is the need for individual housing in aging studies, greatly increasing husbandry costs. Moreover, it is possible that some of the factors modulating aging in fish and other cold-blooded vertebrates may be dissimilar to those in mammals.\n\nAlthough mice faithfully recapitulate many aspects of human aging and age-associated diseases, their use in primary screening/testing of a large number of potential anti-aging compounds is not feasible because of the high associated costs. The use of progeroid models, such as Ercc1 hypomorphs or Lmna mutants, with accelerated pathology and short lifespan, might allow the evaluation of many more compounds than could be reasonably tested in WT mice260,261; however, whether or not such animals suffer from aging per se is a hotly debated topic262,263. Likewise, it is possible that rigorous delineation of appropriate surrogate markers of aging – e.g. increased p16 expression264 or altered DNA methylation (DNAm)265 – may allow initial evaluation of a large number of compounds in mice for potential anti-aging effects, without the need to perform costly and lengthy lifespan studies on many different cohorts, each treated with different candidate anti-aging compounds. In this regard, the Horvath group has developed an approach that allows estimation of the age of most tissues and cell types based on age-associated alterations in DNAm levels at 353 CpG sites266. To the author’s knowledge, longevity screens using surrogate markers such as DNAm have not been attempted in mice.\n\nTo date, the discovery of anti-aging compounds has so far been carried out via two basic approaches. One of these is phenotypic, defined as the screening of compounds in cellular or animal models to identify drugs conferring desired biological effects, i.e. lifespan extension267,268. Although this approach has proven enormously valuable in many areas of biochemical research, identifying drugs that can modulate lifespan is more time consuming, complex, and expensive than for many other phenotypes267,268. Moreover, elucidating the mechanism of action of agents identified in such phenotypic, “black box” screens represents a formidable challenge, though the powerful genetic tools available in invertebrate models can facilitate such efforts. One currently underutilized system with respect to small molecule-based longevity screens is the budding yeast, S. cerevisiae. Two distinct forms of aging have been characterized in this organism, replicative and chronological (population based)269. In principle, either might serve as the basis for screens for anti-aging compounds, though chronological aging is far more amenable to high-throughput analysis. A complementary approach involves target-based screening for modulators of pathways known or strongly suspected to modulate the aging rate267. However, by definition, such efforts are unlikely to identify novel cellular factors and pathways involved in longevity.\n\nTo address these complications, a holistic approach, involving complementary efforts in invertebrates, mammalian cells, and mice, might represent a powerful combination in the quest for anti-aging compounds. With the important caveats noted above, invertebrates can be efficiently used for primary screening of thousands of compounds to identify a few selected candidates with potential anti-aging effects for further testing in mice. In this context, in our Center (http://www.med.umich.edu/geriatrics/research/glenn/), supported by the Glenn Foundation for Medical Research, compounds are screened for their ability to increase healthspan and lifespan in Drosophila and C. elegans and for enhancement of stress resistance in mammalian fibroblasts, a correlate of longevity in mammals270. Compounds that are efficacious in all of these assays are candidates for more in-depth mechanistic evaluation and for further testing in mice (Figure 3).\n\nDrugs identified for their ability to increase healthspan and lifespan in Drosophila and Caenorhabditis elegans and to enhance stress resistance in mammalian fibroblasts are potential candidates for further in-depth mechanistic evaluation and testing in mice.\n\nA related challenge in aging research at present is the lack of primate model systems with reasonably short lifespan for preclinical testing of candidate anti-aging drugs. The most commonly used model, the rhesus monkey, lives for three to four decades20. Another primate, the common marmoset, has several advantages over rhesus monkeys in terms of size, availability, and other biological characteristics271. Because of their small size, marmosets generally cost less to feed and house in comparison with the rhesus monkey. Furthermore, the marmoset has a gestation period of ~147 days and usually gives birth to 2–3 offspring per delivery. Some marmoset traits more closely resemble those of humans than do those of rhesus, including their disease susceptibility profile. In Europe, the marmoset is used as a non-rodent species for drug safety assessment and toxicology271. In this regard, in a recent report, Tardif et al. described the dosing procedure, pharmacokinetics, and downstream signaling changes for rapamycin administration to marmosets272. However, their maximal lifespan is ~17 years – shorter than the rhesus monkey, but still highly impractical for testing pharmacological interventions aimed at extending longevity. The development of new mammalian aging models besides the mouse would be extremely helpful to better elucidate the biological processes underlying mammalian aging and to expedite the translation of pharmacological interventions from the laboratory to actual clinical use in humans.\n\nOne model to consider in this regard is dogs, which share their social environment with humans273. Furthermore, dogs are relatively well understood with regard to aging and disease, exhibit great heterogeneity in body size and lifespan, and provide a large pool of genetic diversity. Dogs might represent a relatively inexpensive model system, particularly if some dog owners were willing to test candidate lifespan-extending drugs that had previously been validated in invertebrate and rodent models. Indeed, identifying interventions that can promote healthspan and lifespan in dogs may represent an excellent entrée to achieving the same goals in humans. In this context, Matthew Kaeberlein and Daniel Promislow at the University of Washington in Seattle have launched a pilot trial involving 30 dogs aimed at testing the efficacy of rapamycin in improving overall health and extending lifespan in large dogs that usually survive for 8 to 10 years274.\n\nTesting candidate anti-aging compounds in humans represents an enormous challenge112. It is highly unlikely that pharmaceutical companies can be persuaded to engage in decades-long clinical trials of candidate anti-aging medicines with lifespan as an endpoint. The evaluation of shorter-term surrogate phenotypes, such as molecular markers or age-associated defects such as impaired responses to vaccination75, may permit initial clinical evaluation of candidate anti-aging compounds in a more reasonable timeframe.\n\n\nConclusion\n\nSince ancient times, humanity has dreamed of interventions to slow the aging process and prolong lifespan. However, only in the modern era has biological aging research progressed to the point where interventions that delay human aging may eventually represent a real possibility. Accumulating work in invertebrate models and rodents has identified an ever-growing list of molecules with the ability to extend lifespan and promote late-life health in mammals. Given the intimate link between aging and disease, such drugs may dramatically improve human health if the major challenges in their testing and deployment can be overcome.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nWork in our laboratory is supported by the Glenn Foundation for Medical Research, National Institutes of Health grant R01GM101171 (DL), Department of Defense grant OC140123 (DL), the National Center for Advancing Translational Sciences of the National Institutes of Health under award UL1TR000433, and the John S. and Suzanne C. Munn Cancer Fund of the University of Michigan Comprehensive Cancer Center. Some graphics in the figures were obtained and modified from Servier Medical Art from Servier (http://www.servier.com/Powerpoint-image-bank).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nWe thank Dr Richard A. 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Nature. 2016; 530(7589): 184–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nZhu Y, Tchkonia T, Pirtskhalava T, et al.: The Achilles' heel of senescent cells: from transcriptome to senolytic drugs. Aging Cell. 2015; 14(4): 644–58. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMontero JC, Seoane S, Ocaña A, et al.: Inhibition of SRC family kinases and receptor tyrosine kinases by dasatinib: possible combinations in solid tumors. Clin Cancer Res. 2011; 17(17): 5546–52. PubMed Abstract | Publisher Full Text\n\nOlave NC, Grenett MH, Cadeiras M, et al.: Upstream stimulatory factor-2 mediates quercetin-induced suppression of PAI-1 gene expression in human endothelial cells. J Cell Biochem. 2010; 111(3): 720–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBruning A: Inhibition of mTOR signaling by quercetin in cancer treatment and prevention. Anticancer Agents Med Chem. 2013; 13(7): 1025–31. PubMed Abstract | Publisher Full Text\n\nChang J, Wang Y, Shao L, et al.: Clearance of senescent cells by ABT263 rejuvenates aged hematopoietic stem cells in mice. Nat Med. 2016; 22(1): 78–83. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWendt MD: Discovery of ABT-263, a Bcl-family protein inhibitor: observations on targeting a large protein-protein interaction. Expert Opin Drug Discov. 2008; 3(9): 1123–43. PubMed Abstract | Publisher Full Text\n\nVogler M, Dinsdale D, Dyer MJ, et al.: Bcl-2 inhibitors: small molecules with a big impact on cancer therapy. Cell Death Differ. 2009; 16(3): 360–7. PubMed Abstract | Publisher Full Text\n\nBillard C: BH3 mimetics: status of the field and new developments. Mol Cancer Ther. 2013; 12(9): 1691–700. PubMed Abstract | Publisher Full Text\n\nZhu Y, Tchkonia T, Fuhrmann-Stroissnigg H, et al.: Identification of a Novel Senolytic Agent, Navitoclax, Targeting the Bcl-2 Family of Anti-Apoptotic Factors. Aging Cell. 2015. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nDi Cicco E, Tozzini ET, Rossi G, et al.: The short-lived annual fish Nothobranchius furzeri shows a typical teleost aging process reinforced by high incidence of age-dependent neoplasias. Exp Gerontol. 2011; 46(4): 249–56. PubMed Abstract | Publisher Full Text\n\nGenade T, Benedetti M, Terzibasi E, et al.: Annual fishes of the genus Nothobranchius as a model system for aging research. Aging Cell. 2005; 4(5): 223–33. PubMed Abstract | Publisher Full Text\n\nTerzibasi E, Valenzano DR, Benedetti M, et al.: Large differences in aging phenotype between strains of the short-lived annual fish Nothobranchius furzeri. PLoS One. 2008; 3(12): e3866. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTerzibasi E, Valenzano DR, Cellerino A: The short-lived fish Nothobranchius furzeri as a new model system for aging studies. Exp Gerontol. 2007; 42(1–2): 81–9. PubMed Abstract | Publisher Full Text\n\nValenzano DR, Terzibasi E, Cattaneo A, et al.: Temperature affects longevity and age-related locomotor and cognitive decay in the short-lived fish Nothobranchius furzeri. Aging Cell. 2006; 5(3): 275–8. PubMed Abstract | Publisher Full Text\n\nHarel I, Benayoun BA, Machado B, et al.: A platform for rapid exploration of aging and diseases in a naturally short-lived vertebrate. Cell. 2015; 160(5): 1013–26. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nRamos FJ, Chen SC, Garelick MG, et al.: Rapamycin reverses elevated mTORC1 signaling in lamin A/C-deficient mice, rescues cardiac and skeletal muscle function, and extends survival. Sci Transl Med. 2012; 4: 144ra103. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhao J, Li X, McGowan S, et al.: NF-κB activation with aging: characterization and therapeutic inhibition. Methods Mol Biol. 2015; 1280: 543–57. PubMed Abstract | Publisher Full Text\n\nHasty P, Vijg J: Rebuttal to Miller: 'Accelerated aging': a primrose path to insight?' Aging Cell. 2004; 3(2): 67–9. PubMed Abstract | Publisher Full Text\n\nMiller RA: 'Accelerated aging': a primrose path to insight? Aging Cell. 2004; 3(2): 47–51. PubMed Abstract | Publisher Full Text\n\nSharpless NE, Sherr CJ: Forging a signature of in vivo senescence. Nat Rev Cancer. 2015; 15(7): 397–408. PubMed Abstract | Publisher Full Text\n\nJones MJ, Goodman SJ, Kobor MS: DNA methylation and healthy human aging. Aging Cell. 2015; 14(6): 924–32. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHorvath S: DNA methylation age of human tissues and cell types. Genome Biol. 2013; 14(10): R115. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nCarretero M, Gomez-Amaro RL, Petrascheck M: Pharmacological classes that extend lifespan of Caenorhabditis elegans. Front Genet. 2015; 6: 77. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPrior M, Chiruta C, Currais A, et al.: Back to the future with phenotypic screening. ACS Chem Neurosci. 2014; 5(7): 503–13. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLongo VD, Shadel GS, Kaeberlein M, et al.: Replicative and chronological aging in Saccharomyces cerevisiae. Cell Metab. 2012; 16(1): 18–31. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMiller RA: Cell stress and aging: new emphasis on multiplex resistance mechanisms. J Gerontol A Biol Sci Med Sci. 2009; 64(2): 179–82. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKishi N, Sato K, Sasaki E, et al.: Common marmoset as a new model animal for neuroscience research and genome editing technology. Dev Growth Differ. 2014; 56(1): 53–62. PubMed Abstract | Publisher Full Text\n\nTardif S, Ross C, Bergman P, et al.: Testing efficacy of administration of the antiaging drug rapamycin in a nonhuman primate, the common marmoset. J Gerontol A Biol Sci Med Sci. 2015; 70(5): 577–87. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKaeberlein M: The Biology of Aging: Citizen Scientists and Their Pets as a Bridge Between Research on Model Organisms and Human Subjects. Vet Pathol. 2016; 53(2): 291–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCheck Hayden E: Pet dogs set to test anti-ageing drug. Nature. 2014; 514(7524): 546. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13087",
"date": "29 Mar 2016",
"name": "Michael Petrascheck",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13088",
"date": "29 Mar 2016",
"name": "Joseph Baur",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13089",
"date": "29 Mar 2016",
"name": "Dudley Lamming",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-406
|
https://f1000research.com/articles/5-397/v1
|
24 Mar 16
|
{
"type": "Review",
"title": "Accessing Nature’s diversity through metabolic engineering and synthetic biology",
"authors": [
"Jason R. King",
"Steven Edgar",
"Kangjian Qiao",
"Gregory Stephanopoulos",
"Jason R. King",
"Steven Edgar",
"Kangjian Qiao"
],
"abstract": "In this perspective, we highlight recent examples and trends in metabolic engineering and synthetic biology that demonstrate the synthetic potential of enzyme and pathway engineering for natural product discovery. In doing so, we introduce natural paradigms of secondary metabolism whereby simple carbon substrates are combined into complex molecules through “scaffold diversification”, and subsequent “derivatization” of these scaffolds is used to synthesize distinct complex natural products. We provide examples in which modern pathway engineering efforts including combinatorial biosynthesis and biological retrosynthesis can be coupled to directed enzyme evolution and rational enzyme engineering to allow access to the “privileged” chemical space of natural products in industry-proven microbes. Finally, we forecast the potential to produce natural product-like discovery platforms in biological systems that are amenable to single-step discovery, validation, and synthesis for streamlined discovery and production of biologically active agents.",
"keywords": [
"metabolic engineering",
"synthetic biology",
"natural product discovery"
],
"content": "Introduction\n\nSmall molecules play an important role in enhancing our understanding of metabolic control in multistep reaction networks that underlie mechanisms of disease and orchestrate industrial biocatalysts. As such, small molecules account for a large fraction of the new drugs introduced each year, especially those emerging from natural products research. Metabolic probes and drug candidates are born from small molecule libraries that are typically limited in structural diversity, a key constraint for the discovery of new bioactive small molecules1.\n\nOrganic chemists have boundless potential to create drugs with diverse molecular topologies from commodity chemicals using the immense diversity of reactions at their disposal. On the other hand, without selective pressures to guide the chemistry, practical discovery of biologically active agents is limited to the manipulation of known natural compounds and the use of combinatorial high-throughput screens2. The de novo synthesis of complex natural products is a cost- and labor-intensive process, requiring world-class expertise. While traditional combinatorial chemistries employed orthogonal reactions to join small, flat, multi-functional building blocks, recent biology-inspired diversity-oriented methodologies are exploring a greater array of chemotypes with increased dimensionality and complexity, as one finds with natural secondary metabolites (Figure 1)1,2. Unsurprisingly, chemically derived, biologically active compounds tend to resemble natural products. The similarities inform structural signatures of bioactivity, like the number of stereogenic carbons, scaffold rigidity, and the carbon/heteroatom ratio of the molecules2,3. Such descriptors of biological activity reveal that natural products provide a pool of “privileged” scaffolds as starting points for molecular probes and drugs3. Combinatorial biosynthesis alleviates many of the concerns with traditional combinatorial chemistry by producing only those compounds with properties similar to natural products. In combinatorial biosynthesis, cells or enzymes are programed for diverse compound generation by systematically switching enzymes in a biosynthetic pathway (e.g. polyketide pathways) or using enzymes with broad substrate ranges (e.g. glycosyltransferases [GTs]) to produce product libraries (Figure 1)4–6. Enzyme- and cell-based library generation emulates the natural means for creating chemical diversity by employing genetically encoded catalysts that co-evolve with their products in response to environmental pressures.\n\nComplex metabolites diverge from a common pool of primary building blocks. Secondary metabolites and their respective precursors are grouped by colored areas: green (isoprenoids), purple (polyketides), red (non-ribosomal peptides), and orange (glycosides). Paradigmatic structures of each metabolite class are shown with the structure cores highlighted in blue. Colored arrows denote simplified enzymatic transformations. Black arrows and nodes correspond to central metabolism in heterotrophs to denote the origin of primary metabolites from central carbon.\n\nGiven immense recent interest in natural product biosynthesis and discovery2,7–12, here we provide perspective on how synthetic biology and metabolic engineering are enabling compound discovery and biosynthesis. We parameterize natural themes for exploring chemical diversity under the guide of evolution. Finally, we forecast the potential for metabolic engineering to consolidate cell-based platforms for library generation and hit validation, as well as scalable synthesis in the practical discovery of biologically active compounds.\n\n\nEngineering small molecule discovery platforms: derivatization vs. diversification\n\nAdvances in chemical biology and metabolic engineering are providing insights into the biological routes to create natural product diversity while also offering the potential to harness and manipulate this diversity under the guide of selective pressure. Armed with an arsenal of robust genetic tools and proven hosts for prokaryotic (e.g. Escherichia coli, Bacillus subtilis, Streptomyces sp.) and eukaryotic (e.g. Saccharomyces cerevisiae) production platforms, biological engineers have begun exploring diversity in both natural and unnatural contexts (Figure 2)13. Natural product diversity results from two themes of chemical evolution: derivatization of a shared molecular scaffold by variable functionalization of a common core, or diversification to enable the synthesis of various scaffold cores with distinct shapes from common building blocks (Figure 2A). Below we describe recent trends and specific advances that highlight the importance of exploring chemical diversity in molecule discovery and underscore the role of synthetic biology and related fields towards this end.\n\nA) schematic of isoprenoid diversification in which distinct terpenes (2–5) arise from common building blocks (1a–e) and are subsequently functionalized into diverse isoprenoids (6–13); B) engineering secondary metabolite production requires augmented flux through biosynthetic pathways to access compound precursors, such as the buildup of isopentenyl diphosphate building blocks for the overproduction of taxadiene (3)92 and amorphadiene (4)93; C) scaffold diversification is emulated through enzyme engineering as shown in mutagenesis of the plant-derived levopimaradiene synthase (LPS)79 and humulene synthase88; D) scaffold derivatization is performed by engineered enzymes as in the P450-catalyzed hydroxylation of compactin (16) to produce the drug pravastatin (17), or by naturally promiscuous enzymes as with variable glycosylation of vicenilactam (18) with glycosyltransferase VinC25,36.\n\nChemical transformations of complex molecules often suffer from a lack of regioselectivity and stereoselectivity, poor discrimination between functional groups of similar reactivity, and an incompatibility with biological media. Enzymes, however, catalyze site-specific and stereoselective chemistries in water—often within a microorganism. Numerous enzyme-mediated chemical functionalizations of natural products are known, including scaffold alkylation14–16, acylation17, oxidation18,19, glycosylation4,20, and halogenation21. Here we focus the discussion of enzyme-tailored scaffold derivatization on the mature cases of natural product tailoring by cytochrome P450 oxidases (P450s or CYPs) and GTs. It is worth noting the biosynthetic potential of the lesser-utilized bio-acylation and bio-halogenation reactions for natural product derivatization, as these reactions can introduce orthogonally reactive handles for late-stage library differentiation21.\n\nA robust derivatization strategy employs naturally promiscuous P450s that have been engineered to harness multiple natural and novel chemistries in vivo22–24. For example, Keasling and co-workers used rational enzyme mutagenesis of a plant-mimicking bacterial enzyme (P450-BM3) capable of epoxidizing the plant-derived taxane amorpha-4,11-diene (Figure 2 [4]) to obtain a more thermostable and selective epoxidation catalyst. P450-BM3 mutant G3A328L enabled the biosynthesis of the value-added compound artemisinic-11S,12-epoxide at 250 mg/L in E. coli, thereby improving the semi-synthesis of the antimalarial drug artemisinin (Figure 2 [10])18. Recently, McLean et al. evolved CYP105AS1 from Amycolatopsis orientalis to hydroxylate the pravastatin (Figure 2 [17]) precursor compactin (Figure 2 [16]) in the engineered Penicillium chrysogenum strain D550662, ultimately achieving titers of 6 g/L of the blockbuster drug after 200 h in a 10 L fed-batch fermentation (Figure 2D)25.\n\nP450-catalyzed metabolite derivatization is likewise offering avenues to explore chemical space that was previously unavailable in a biological setting. Frances Arnold’s lab has developed an impressive array of P450 catalysts including an engineered diazoester-derived carbene transferase (P450BM3/CYP102A1) for the stereoselective cyclopropanation of styrenes, which have concomitantly become available biologically via the metabolic engineering of E. coli for styrene production from L-phenylalanine at a titer of 260 mg/L26,27. Arnold’s team expanded the work to enable incorporation of the cyclopropane in vivo by engineering the electronics of the enzyme active site to accommodate NAD(P)H as an electron donor, and upon altering the active site architecture, they further engineered the catalyst for cyclopropanation of N,N-diethyl-2-phenylacrylamide, a putative intermediate in the formal synthesis of the serotonin and norepinephrine reuptake inhibitor levomilnacipran—marketed by Actavis Inc. as Fetzima for the treatment of clinical depression28–30. On the chemical front, Wallace and Balskus have developed porphyrin-iron(III) chloride catalysts that function similarly to Arnold’s P450-BM3 mutants while presenting biocompatible reactions with living styrene-producing E. coli31. Such approaches highlight the potential to meld chemical and biological approaches for tailored molecule derivatization in engineered organisms32,33.\n\nGTs are also attracting attention in the derivatization of natural products, including polyketides, non-ribosomal peptides, and terpenoids, for the discovery of novel antimicrobial agents with tailored pharmacological properties, including augmented target recognition and improved bio-availability4,20,34,35. In this regard, dNDP-glycosides (Figure 1) represent a biosynthetically viable class of saccharide donors for promiscuous and engineered GTs that exhibit substrate tolerances for both the saccharide and aglycone portions of the reaction products. For instance, Minami et al. exploited the broad substrate tolerance of vicenisaminyltransferase VinC from Streptomyces halstedii HC 34 in the discovery of 22 novel glycosides from 50 sets of reactions for the glycodiversification of natural polyketide scaffolds (Figure 2D)36. More recently, Pandey et al. demonstrated the derivatization of clinically relevant resveratrol glycosides, producing ten different derivatives of the plant-derived metabolite, all accommodated by YjiC, a bacterial GT from Bacillus licheniformis34,37. However, in order for GT-catalyzed glyco-derivatization to be realized in vivo, the prerequisite biosynthesis of NDP-glycosides as glycosyl donors and acceptors must be engineered from bacterial monosaccharide and nucleotide triphosphate pools. A key advance in the supply of glycosyl donors was the discovery of the reversibility of GT-catalyzed reactions whereby Thorson and co-workers were able to generate more than 70 analogs of the natural products calicheamicin and vancomycin (Figure 1) using various nucleotide sugars38. Using OleD as the initial model enzyme, Thorson’s team evolved the substrate tolerance of GTs to enable glycosylation of not only natural products but also non-natural compounds and proteins4,39. More recently, Gantt et al. enabled the rapid, colorimetric screening of engineered GTs, and subsequently evolved an enzyme (OleD Loki) for the combinatorial enzymatic synthesis of 30 distinct NDP-sugars that are putatively amenable to further enzymatic manipulation in common microbial hosts4,40.\n\nMetabolic engineering strategies for in vivo combinatorial glyco-derivatization of secondary metabolites have also demonstrated success by combining heterologous saccharide biosynthesis genes into non-natural pathways. In 1998, Madduri et al. demonstrated the fermentation of the antitumor drug epirubicin (Figure 1) in Streptomyces peucetius and sparked intense interest in the role of metabolic engineering and combinatorial biosynthesis for the discovery and production of glyco-pharmaceuticals20,41–44. These efforts have begun to impact glyco-engineering in more common microbial hosts, such as an in vivo small molecule “glyco-randomization” study in E. coli by Thorson and co-workers4 or the variable derivatization of erythromycin by Pfeifer and co-workers45; however, much success for in vivo glyco-derivatization remains in Streptomyces4,41,46–48.\n\nScaffold derivatization enables the fine-tuning of compound activity by increasing compound resolution in a defined chemical space. The production of novel secondary metabolites through scaffold diversification, on the other hand, is a common theme of biosynthesis in plants and fungi that enables the exploration of completely new areas of chemical space. In order to generate beneficial molecules, it has been proposed that microbes and plants generate a diverse library of small molecules. Many liken these broad ranges of natural products to the host’s chemical “immune system”, where producing compounds with no known target could allow for resistance to an as-yet unencountered pathogen and provide evolutionary fitness of organisms with more diverse natural product portfolios49–51. Natural metabolite diversification has recently inspired diversity-oriented chemical syntheses that emulate the biological reaction cascades in the generation of new, drug-like scaffolds1,52,53. Others have attempted to simplify metabolite archetypes to common core structures that may serve as starting points for discovery through derivatization; however, metabolite profiling of novel compounds from marine life and fungi continues to produce novel scaffold core structures, suggesting that to limit discovery to known scaffolds would severely curb the biosynthetic potential of evolutionary pressure2,54–56. Engineering whole cells for scaffold diversification, on the other hand, was recently demonstrated by Wang et al., who combined the biosynthetic potential of plant, fungal, and bacterial enzymes for the production of 12 novel phenylpropanoid derivatives from L-tyrosine and L-phenylalanine in E. coli57. Evolva reported the discovery of novel antiviral scaffolds using a heterologous flavonoid biosynthesis platform in S. cerevisiae3,58. By consolidating biosynthesis and screening into a single cell, the team was able to synthesize, validate, and structurally characterize 74 new compounds—28 of which showed activity in a secondary Brome Mosaic Virus assay—in less than nine months3.\n\nAiding the discovery of new scaffolds, non-ribosomal peptide synthetases (NRPS) and polyketide synthases (PKS) comprise equally useful, and often interconnected, classes of “assembly line” enzymes for in vivo scaffold diversification. The utility of NRPS/PKS enzymes for complex scaffold synthesis and elaboration emerges from the simplicity and modularity of their catalytic domains59. Core NRPS/PKS genes encode for ketosynthase (KS), acyl transferase (AT), acyl/peptidyl carrier protein (ACP/PCP), condensation domain (C), and adenyltransferase (A) that catalyze the elongation of the polyketide/ peptide skeleton, and a terminal thioesterase (TE) severs the formed macrolide from the multi-domain synthetase. Along with auxiliary ketoreductase (KR), dehydratase (DH), and enoyl reductase (ER) domains, the core domains allow for the programmable building of variable macrolide and macrolactone scaffolds from divergent pools of ketoacids and amino acids17,59–61. Once formed, the core scaffolds are natively derivatized by so-called “tailoring enzymes” to introduce native and non-native functionality as per the discussion of engineered P450s and GTs (vide supra)59.\n\nThe modularity of the biosynthetic machinery of NRPS/PKS megasynthases allows for the rational engineering of combinatorial biosyntheses to access novel chemical space7,62. Combinatorial NRPS/PKS systems have enabled predictable changes to the scaffold core, derived from three programmable inputs into the biosynthesis. The inputs include the following: 1) variable use of organic building blocks such as short-chained acyl-coenzyme A (CoA) molecules or amino acids for the chain elongation step of scaffold synthesis61,63–68; 2) chain length variations originating from KS and TE engineering69–70; and 3) alterations in the reduction program of the scaffold as a result of DH, KR, and ER engineering71–72. Yan et al. exemplified the biosynthetic potential to diversify antimycin (ANT) scaffolds through the metabolic engineering of promiscuous NRPS/PKS enzymes in the ANT-producing Streptomyces sp. NRRL 2288 (Figure 3)17. Following the in vivo production of ANT scaffolds with variable fluorination at C5’ and alkylation at C7, the authors further derivatized the ANT library at C8 with a promiscuous acylating protein (AntB) and various acyl-CoAs in vitro, generating 380 total and 356 novel ANT variants. Chemler et al. recently exploited the biosynthetic prowess of homologous recombination—a natural paradigm of NRPS/PKS evolution—to create PKS libraries for the programmable biosynthesis of engineered polyketide chimeras of known macrolide and macrolactone antibiotics pikromycin and erythromycin (Figure 1)60. Similarly, Sugimoto et al. demonstrated that engineering of an artificial PKS pathway by domain swapping in Streptomyces albus allowed reprogramming of the aureothin (Figure 1) system for production of luteoreticulin and novel derivatives thereof73. Despite significant challenges for NRPS/PKS engineering5,71,74, recent successes with homologous recombination and structure-guided domain swapping of NRPS/PKS’s, coupled to the increased efficiency of Cas9-accelerated gene editing, forecast a time when functional NRPS/PKS variation may be routine6,60,64,66,73,75–76.\n\nDomain key: T = thioylation (e.g. acyl/peptidyl carrier protein ACP/PCP), C = condensation, A = adenylation, KR = ketoreductase, KS = ketosynthase, AT = acyl transacylase, TE = thioesterase. Green ball represents variable use of H or F-modified starting material. Red vs. blue star depicts unsaturated and carboxylated acyl substituent at C7, respectively. Orange triangle depicts variation in the alkyl chain of the C8 acyl substituent.\n\nIsoprenoids, enumerating over 55,000 compounds, comprise perhaps the richest source of diversity among secondary metabolites77. The ability to emulate the natural evolution of this diversity will likely allow the access to known and new plant-derived isoprenoids (Figure 2). Isoprenoid biosynthesis is characterized by four reactions of the five-carbon units isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP): chain elongation, branching, cyclopropanation, and cyclobutanation77. Metabolic engineers have manipulated microbial pathways around the chain elongation reaction to build up terpenoid precursors of different lengths and stereochemistries, including IPP/DMAPP (Figure 2 [1a–b]), geranyl diphosphate (Figure 2 [1c]), farnesyl diphosphate (Figure 2 [1d]), and others78–83. The strategy for introducing diversity as well as directing flux to a desired metabolite then comes from the subsequent pathway and enzyme engineering of terpene synthases that cyclize these building blocks, forming various scaffolds amenable to derivatization with downstream enzymes (Figure 2C). A natural paradigm of terpene synthases and cyclases is the combination of substrate specificity with structural plasticity—a pairing of characteristics that enables rapid evolution of the enzyme for the production of product profiles that meet the environmental demands of the host organism84. In support of this hypothesis, multiple groups have confirmed that through evolution and rational engineering, diterpene synthase activities can be altered to produce multiple, non-native terpenes (Figure 2C)9,84–88. Salmon et al. demonstrated that a convergent point mutation from a library of the Artemisia annua amorpha-4,11-diene synthase (Y420L) enabled the production of numerous cyclized products without compromising catalytic activity89. Rising et al. discovered the serendipitous conversion of a non-natural substrate of tobacco 5-epi-aristolochene synthase, anilinogeranyl diphosphate, to the novel paracyclophane terpene alkaloid 3,7-dimethyl-trans,trans-3,7-aza[9]paracyclophane-diene, which they dubbed “geraniline”90. The finding demonstrates that terpene precursor diversity and bioavailability, in addition to terpene synthase engineering, are key inputs for programmable scaffold diversification. The explicit application of terpene diversification to diversity-oriented molecule discovery is gaining interest, but to realize the full biosynthetic potential of terpenes will likely require more insight into the mechanism of terpene synthases and the directed biosynthesis of terpene precursors9,91.\n\n\nEngineering systems from discovery to production\n\nSecondary metabolites are a treasure trove for the discovery of biologically active compounds, but they are metabolically “expensive”, leading organisms to match production to natural demands of the environment. To meet the demands for human need, microbial cells can be engineered to over-produce complex secondary metabolites—typically plant or fungal in origin—at the expense of host resources including energy storage molecules and biomass. High titers of non-native metabolites are possible via rational pathway engineering as shown in the case of taxadiene (Figure 2 [3]) and amorpha-4,11-diene (Figure 2 [4]) syntheses in E. coli, which detail that metabolite balance through modular pathways is crucial to high production (Figure 2A)92,93. Bypassing regulation also allows increased production of native secondary metabolites, as shown recently by Tan et al. with validamycin (Figure 1) biosynthesis in Streptomyces94. The team generated a double deletion mutant (S. hygroscopicus 5008 ∆shbR1/R3) to remove feedback inhibition and increase validamycin titers to 24 g/L and productivities to 9.7 g/L/d, which are the highest capacities yet reported94.\n\nMetabolic engineering can harvest synthetic genes from marine, plant, and fungal systems for the production of a diverse set of known compounds including terpenoids, flavonoids, and alkaloids in industrially useful microbial hosts70,95,96. The reconstitution of heterologous pathways in fast-growing microbes is akin to hijacking evolution for efficient and expedient production. To this end, modular pathway reconstruction, or “retrobiosynthesis”, effectively maximizes a cell’s capacity to integrate new biological circuits and appropriate valuable cell resources for high secondary metabolite production97–99. Retrobiosynthesis allows for the systematic evaluation of complex multi-step pathways by isolating key transformations of a complete pathway into a series of independent modules that can be engineered in parallel99. Leonard et al. demonstrated modular pathway engineering for the high-level production of levopimaradiene, a branch-point precursor to pharmaceutically relevant plant-derived ginkgolides79. Upon increasing IPP/DMAPP titers through overexpression of mono-erythritol phosphate pathway enzymes in E. coli and separately engineering the geranylgeranyl pyrophosphate synthase/levopimaradiene synthase system for increased selectivity and productivity, the team achieved a 700 mg/L titer in a bench-scale bioreactor. This is one of the first applications whereby metabolic engineering was combined with protein engineering to maximize production and selectivity of a desired compound.\n\nSynthetic consortia offer another tool in which the metabolic burden of complex molecule synthesis can be distributed over multiple hosts. Recently, Zhou et al. engineered a cross-kingdom co-culture to produce oxygenated taxane precursors to the potent, plant-derived, anti-tumor drug paclitaxel (Figure 1), achieving titers of 33 mg/L100. Mimicking the general engineering strategy for spatially controlled production of branched-chain alcohols and mevalonate-derived terpenes in yeast101,102, Zhou et al. combined the divergent advantages of efficient cytochrome P450 expression in S. cerevisiae and the efficient taxadiene (Figure 2 [3]) production in E. coli92. The system emulates the native plant platform in which oxygen-sensitive taxadiene production is sequestered from the subsequent oxidations to form paclitaxel and other oxygenated taxanes in the peroxyzome100,102. The synthetic consortium put forth by Zhou et al. could represent a natural paradigm of plant isoprenoid production in plant-associated endophytes, further validating the general premise whereby metabolic engineering allows for the directed use of natural evolution for success in biosynthesis103.\n\nIn the post-genomic era, gene mining for compound discovery is adding to the engineer’s toolbox. Hwang and others purport that multiplexed “omics” and bioinformatics enable the simultaneous identification of bacterial biosynthetic gene clusters, their encoded enzymes, and the structures of the resultant secondary metabolites for streamlined discovery of molecular structure and function41,104–106. Systems-level analyses will further aid compound discovery by unveiling biosynthetic pathways of unknown secondary metabolites and antibiotics in actinomycetes and other organisms107–109. Of spectacular interest is the growing evidence for compound discovery by bioprospecting “unculturable” actinomycetes and uncharacterized bacteria by mapping, transforming, and editing their DNA heterologously in genetically tractable hosts with “out-of-the-box” genetic systems and clever metabolic engineering110–114.\n\nStreamlined molecule discovery and production is likewise aided through the engineering of microbial systems for concomitant compound discovery, validation, and scale-up (e.g. the yeast discovery platform from Evolva; vide supra)3. Recently, DeLoache et al. engineered S. cerevisiae to fluoresce orange in the presence of L-3,4-dihydroxyphenylalanine (L-DOPA), an early intermediate en route to (S)-reticuline, and purple in the presence of L-dopaquinone, an unwanted byproduct of L-DOPA oxidation115. PCR mutagenesis of a tyrosine P450 oxidase (CYP76AD1) produced a yeast library that could be easily screened by comparison of the orange:purple fluorescence of single cells with flow cytometry. The team identified P450 mutant CYP76AD1W13L F309L as a selective catalyst for reduced L-DOPA production and continued to engineer a de novo pathway for (S)-reticuline production from glucose at titers of 80.6 µg/L. Albeit low titer, this approach has already been recognized for the ability to streamline microbial opioid production116.\n\n\nConclusions\n\nA reinvigoration of the potential for engineered enzymes and microorganisms to explore foreign biochemical space and discover molecular probes and therapeutics is clear from a number of recent commentaries and reviews9,11,41,117. Here, we describe examples from enzyme and pathway engineering to illustrate the successes, promises, and challenges for mining the plant, fungal, and microbial metabolomes to produce natural product-like molecules. We outline the underlying themes whereby nature explores chemical diversity through the diversification and derivatization of secondary metabolites—a robust strategy that has inspired recent diversity-oriented chemical syntheses. The co-evolution of natural products with their biosynthetic enzymes in response to environmental pressures is a theme whereby natural diversity begets evolutionary fitness. Several factors highlight the burgeoning potential of modern metabolic engineering to explore chemical diversity: 1) incredible investment into the genetic characterization of secondary metabolism over the last two decades has led to organization of natural product biosyntheses into standardized data sets12,118; 2) engineering promiscuous, biosynthetic enzymes has allowed for the DNA-encoded diversification of natural product libraries; 3) successful metabolic engineering of industrially proven microbes has allowed complex metabolite biosyntheses with high titers and productivities, and 4) recent technical advances for efficient homologous recombination and consolidated bioprospecting are allowing for biosynthetic compound library creation, validation, and scale-up with increasing simplicity. Perhaps a most critical advantage is that, once an active new structure is identified, through either scaffold derivatization or diversification in an engineered microbe, an actual biochemical process is also available for the synthesis of the target compound in substantial amounts required for toxicity and clinical trials. This path is more efficient compared to the many steps of a new chemical synthesis approach typically followed when promising compounds are identified from prospecting samples of natural sources. Broadly, the potential to apply metabolic engineering to access chemical diversity inspired by natural product biosynthesis illustrates an elegant pairing of science and engineering for biochemical progress.",
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PubMed Abstract | Publisher Full Text\n\nPrather KL, Martin CH: De novo biosynthetic pathways: rational design of microbial chemical factories. Curr Opin Biotechnol. 2008; 19(5): 468–74. PubMed Abstract | Publisher Full Text\n\nZhou K, Qiao K, Edgar S, et al.: Distributing a metabolic pathway among a microbial consortium enhances production of natural products. Nat Biotechnol. 2015; 33(4): 377–83. PubMed Abstract | Publisher Full Text\n\nAvalos JL, Fink GR, Stephanopoulos G: Compartmentalization of metabolic pathways in yeast mitochondria improves the production of branched-chain alcohols. Nat Biotechnol. 2013; 31(4): 335–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFarhi M, Marhevka E, Masci T, et al.: Harnessing yeast subcellular compartments for the production of plant terpenoids. Metab Eng. 2011; 13(5): 474–81. PubMed Abstract | Publisher Full Text\n\nKusari S, Pandey SP, Spiteller M: Untapped mutualistic paradigms linking host plant and endophytic fungal production of similar bioactive secondary metabolites. Phytochemistry. 2013; 91: 81–7. PubMed Abstract | Publisher Full Text\n\nChooi YH, Solomon PS: A chemical ecogenomics approach to understand the roles of secondary metabolites in fungal cereal pathogens. Front Microbiol. 2014; 5: 640. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHofberger JA, Ramirez AM, Bergh Ev, et al.: Large-Scale Evolutionary Analysis of Genes and Supergene Clusters from Terpenoid Modular Pathways Provides Insights into Metabolic Diversification in Flowering Plants. PLoS One. 2015; 10(6): e0128808. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYadav VG, De Mey M, Lim CG, et al.: The future of metabolic engineering and synthetic biology: towards a systematic practice. Metab Eng. 2012; 14(3): 233–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAnnadurai RS, Neethiraj R, Jayakumar V, et al.: De Novo transcriptome assembly (NGS) of Curcuma longa L. rhizome reveals novel transcripts related to anticancer and antimalarial terpenoids. PLoS One. 2013; 8(2): e56217. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGuo F, Xiang S, Li L, et al.: Targeted activation of silent natural product biosynthesis pathways by reporter-guided mutant selection. Metab Eng. 2015; 28: 134–42. PubMed Abstract | Publisher Full Text\n\nRutledge PJ, Challis GL: Discovery of microbial natural products by activation of silent biosynthetic gene clusters. Nat Rev Microbiol. 2015; 13(8): 509–23. PubMed Abstract | Publisher Full Text\n\nGaida SM, Sandoval NR, Nicolaou SA, et al.: Expression of heterologous sigma factors enables functional screening of metagenomic and heterologous genomic libraries. Nat Commun. 2015; 6: 7045. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nKushwaha M, Salis HM: A portable expression resource for engineering cross-species genetic circuits and pathways. Nat Commun. 2015; 6: 7832. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nOwen JG, Charlop-Powers Z, Smith AG, et al.: Multiplexed metagenome mining using short DNA sequence tags facilitates targeted discovery of epoxyketone proteasome inhibitors. Proc Natl Acad Sci U S A. 2015; 112(14): 4221–6. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nOwen JG, Reddy BV, Ternei MA, et al.: Mapping gene clusters within arrayed metagenomic libraries to expand the structural diversity of biomedically relevant natural products. Proc Natl Acad Sci U S A. 2013; 110(29): 11797–802. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nYamanaka K, Reynolds KA, Kersten RD, et al.: Direct cloning and refactoring of a silent lipopeptide biosynthetic gene cluster yields the antibiotic taromycin A. Proc Natl Acad Sci U S A. 2014; 111(5): 1957–62. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nDeLoache WC, Russ ZN, Narcross L, et al.: An enzyme-coupled biosensor enables (S)-reticuline production in yeast from glucose. Nat Chem Biol. 2015; 11(7): 465–71. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nEhrenberg R: Engineered yeast paves way for home-brew heroin. Nature. 2015; 521(7552): 267–8. PubMed Abstract | Publisher Full Text\n\nSun H, Liu Z, Zhao H, et al.: Recent advances in combinatorial biosynthesis for drug discovery. Drug Des Devel Ther. 2015; 9: 823–33. 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}
|
[
{
"id": "13072",
"date": "24 Mar 2016",
"name": "Frances H. Arnold",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13073",
"date": "24 Mar 2016",
"name": "Jon S Thorson",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-397
|
https://f1000research.com/articles/4-1379/v1
|
30 Nov 15
|
{
"type": "Study Protocol",
"title": "A protocol to examine vision and gait in Parkinson’s disease: impact of cognition and response to visual cues",
"authors": [
"Samuel Stuart",
"Brook Galna",
"Sue Lord",
"Lynn Rochester",
"Samuel Stuart",
"Brook Galna",
"Sue Lord"
],
"abstract": "BackgroundCognitive and visual impairments are common in Parkinson’s disease (PD) and contribute to gait deficit and falls. To date, cognition and vision in gait in PD have been assessed separately. Impact of both functions (which we term ‘visuo-cognition’) on gait however is likely interactive and can be tested using visual sampling (specifically saccadic eye movements) to provide an online behavioural measure of performance. Although experiments using static paradigms show saccadic impairment in PD, few studies have quantified visual sampling during dynamic motor tasks such as gait.This article describes a protocol developed for testing visuo-cognition during gait in order to examine the: 1) independent roles of cognition and vision in gait in PD, 2) interaction between both functions, and 3) role of visuo-cognition in gait in PD.Methods Two groups of older adults (≥50 years old) were recruited; non-demented people with PD (n=60) and age-matched controls (n=40). Participants attended one session and a sub-group (n=25) attended two further sessions in order to establish mobile eye-tracker reliability. Participants walked in a gait laboratory under different attentional (single and dual task), environmental (walk straight, through a door and turning), and cueing (no visual cues and visual cues) conditions. Visual sampling was recorded using synchronised mobile eye-tracker and electrooculography systems, and gait was measured using 3D motion analysis.Discussion This exploratory study examined visuo-cognitive processes and their impact on gait in PD. Improved understanding of the influence of cognitive and visual functions on visual sampling during gait and gait in PD will assist in development of interventions to improve gait and reduce falls risk. This study will also help establish robust mobile eye-tracking methods in older adults and people with PD.",
"keywords": [
"Parkinson’s disease",
"eye-tracking",
"vision",
"cognition",
"visual sampling",
"gait",
"eye movements"
],
"content": "Introduction\n\nParkinson’s disease (PD) is a common neurodegenerative disease1 characterised by the death and dysfunction of dopaminergic neurons in the substantia nigra2. PD causes progressive motor symptoms such as problems with gait3 and non-motor symptoms such as visual and cognitive impairment1. Cognitive impairment is common in PD with reports of dementia ranging up to ~80%4, and may occur early in the disease process5. Visual dysfunction is also common in people with PD, with up to 78% of people with PD reporting at least one visual problem6. Gait impairment in PD is complex, involving multi-system dysfunction and has been widely related to cognitive, and to a lesser extent visual deficits. A more robust understanding of these complex processes and their interactions will inform underlying mechanisms of gait impairment in PD, which may provide insight for future therapeutic intervention. Interventions, such as visual cues (prompts; transverse tape lines to step over) are currently used to ameliorate features of gait disturbance in PD resistant to dopaminergic medication, such as festination, hesitation and freezing of gait7,8. However, visual cue response is selective9 and the mechanisms that contribute to the response are unclear.\n\nTo date, associative (correlational) and online manipulation (via dual tasks and environmental changes) studies have investigated the independent contribution of cognition and vision in gait in PD. However, cognitive and visual functions likely interact and have a combined - impact on gait in PD. Recent technological progress has enabled the monitoring of online visuo-cognition through behavioural outcomes such as visual sampling which reflects both visual10,11 and cognitive12–14 processes. Visual sampling is the combination of saccadic fast eye-movements and fixations (pauses between saccades on areas of interest) made during real-world activities15. However, research is compromised by several technological limitations which need to be addressed to ensure robust data collection and analysis. For example, there is currently no ‘gold standard’ visual sampling measurement device or outcome measure and there is also a lack of device accuracy or reliability reporting in all previous studies15.\n\nVisual sampling (specifically saccades) allow orientation to the visual environment bringing areas of interest into high visual acuity (foveation or focus)16. Saccades are impaired in PD and exhibit reduced speed, amplitudes and latencies17–22. Impaired saccadic eye movements, with reduced latencies and increased error rates have also been reported in PD dementia and dementia with Lewy Bodies, further implicating central neuro-degeneration as a determinant of ocular motor function23,24. However, the specific contribution of cognitive and/or visual functions to visual sampling during gait in PD and how this impacts gait deficit is currently poorly understood.\n\nMuch of the previous saccadic activity research is limited due to the almost exclusive use of static testing protocols (e.g. computerised tasks in sitting)18,25, which may not be applicable to real-world situations. A recent review of dynamic motor tasks (e.g. gait, obstacle crossing, turning etc.) in PD and older adults15, demonstrated that visual sampling is task dependent and relates to specific goals26. For example: during locomotion over even terrain, saccades may not be required. Over uneven (complex) terrain or during turning saccadic frequency, amplitude and fixations increase27–30. However many previous visual sampling protocols during dynamic task studies use small cohorts and often do not assess cognitive or visual functions15, which limits interpretation and conclusions regarding underlying mechanisms. Visual sampling during gait therefore has not been fully investigated and further research is required to understand this important feature of gait control. Improved understanding will assist with interventions to improve gait performance in PD.\n\n\nAims\n\nThe aims of this study are to better understand: 1) the independent roles of cognition and vision in gait in PD, 2) the interaction between both functions (termed visuo-cognition), and 3) the role of visuo-cognition in gait in PD.\n\nSecondary aims were to:\n\n1. Investigate accuracy and reliability of mobile eye-tracking during gait in people with PD and older adults\n\n\nMethods/Design\n\nWe used a repeated-measures observational design of visual sampling during gait. We also embedded accuracy and reliability testing of a mobile eye-tracker within the study. It involved 100 older adult participants who were separated into two groups (people with PD and older adult controls).\n\nTwo groups of participants were recruited: i) People with idiopathic PD (PD) (n=60); and ii) Age-matched older adults (controls) (n=40). Inclusion criteria and exclusion criteria are highlighted in Table 1. Vision-specific criteria (identified through medical notes) were included due to the impact of certain conditions on eye-tracking capabilities. The setting for the study was the gait laboratory at the Clinical Ageing Research Unit (CARU), Campus for Ageing and Vitality, Newcastle University, United Kingdom.\n\nPeople with PD were identified through the Movement Disorders Clinic at the Clinics for Research and Service in Themed Assessments (CRESTA) in Newcastle upon-Tyne. Research personnel were available at clinics as required to invite participants to consider the study. If sufficiently interested, participants were given a Participant Information Sheet (PIS) and letter concerning the study. The invitation was followed up by a telephone call during the week to assess willingness to participate. If willing, a mutually convenient time for assessment was organised and the invitation to attend was extended to a carer or spouse.\n\nThe older adult control group was recruited via advertisement using posters placed within neurology and geriatric departments. The advertisement was sent via the university email system to staff and students at Newcastle University. Recipients were asked to pass on the poster to potential interested parties (i.e. family or friends). Participants received reimbursement of travel expenses for their own vehicle or for public transport, if this is preferred.\n\n\nMeasures and procedures\n\nGlobal cognition was assessed using the Montreal cognitive assessment (MoCA) and Addenbrookes cognitive examination (ACE-R)37. The MoCA was performed during screening to exclude control participants with cognitive impairment (MoCA <26) and PD participants with dementia (MoCA <21)5 (Table 1). The MoCA is a valid and standardized neuropsychological test for rapid screening of global cognitive dysfunction37, and assesses several different cognitive domains (attention and concentration, executive functions, memory, language, visuo-constructional skills, conceptual thinking, calculations, and orientation). ACE-R has also been shown to be valuable in differential diagnosis of PD when compared to the mini-mental state examination (MMSE)38. Similar to the MoCA, the ACE-R involves testing multiple cognitive domains, such as; attention, orientation, memory, fluency, language and visuospatial abilities.\n\nAttention. Attention was measured via the Cognitive Drug Research (CDR) battery (United Biosource Corporation, UK). This provides specific measures of attention, including Power of attention which is the sum of Simple reaction time, Digit vigilance and Choice reaction time39. The attention CDR is a valid test of attention and has been used in a number of studies involving both PD and cognitively impaired individuals40. The attention CDR involves a series of computerised tests, which the participants respond to by pressing one of two buttons (YES or NO buttons).\n\nExecutive function. Clock drawing (specifically Royall’s CLOX 1)41 was used as a measure of executive function (i.e. planning). Clock drawing assessment is a measure of cognitive impairment, which is an internally consistent measure that is easy to administer and has good reliability. Participants were required to plan and draw a clock from memory with the numbers and arrows pointed at a particular time, which is then marked out of 15 for certain criteria (e.g. hour hand shorter than the minute hand = one point).\n\nWorking Memory. Working memory was assessed using the maximal Wechsler forward digit span42, performed while seated. The forward digit span is reported as a simple span test, which measures storage and manipulation of information by working memory43.\n\nThe forward digit span consists initially of two numbers being played over loud speaker at a rate of 1 per second for the participant to recall, and continues to a maximum of nine numbers43. Three trials per span length were conducted and the test continued until a participant fails two out of three trials. The maximal length of the digit span was determined, defined as the most numbers a participant could remember two out of three times without error.\n\nClock copying (specifically Royall’s CLOX 2)41 measured visuo-spatial ability (i.e. ability to identify the spatial relationship of objects). Clock copying is considered a valid measure of visuo-spatial ability linked with right parietal pathology41,44. For CLOX 2 the researcher draws a clock and the participant must then copy the clock drawn, similar to the cube copying in the MoCA.\n\nBenton’s Judgement of Line Orientation (JLO) test was also used as a measure of visuo-spatial ability. The JLO test has been shown to be a valid and reliable measure of visuo-spatial abilities45. The JLO test involves a participant viewing a set of numbered lines and then being shown two lines of the same orientation. They then have to name the numbers that the shown lines correspond to.\n\nSpecific sections of the visual object and space perception (VOSP) battery was used for more specific visuo-spatial assessment, such as; incomplete letters (visual object perception), dot counting and position discrimination (both spatial perception). The VOSP has been shown to be a valid measure of visuo-spatial abilities46 and consists of a screening test to establish requisite sensory acuity and specific clinical tests47. The VOSP test has been used before in older adults and neurological disorder studies48–50.\n\nVisual function assessment included measurement of visual acuity (VA) and contrast sensitivity (CS) using basic eye-charts.\n\nVisual acuity (VA). VA was measured binocularly using a standard LogMAR chart51. Participants were seated at a distance of 4m from the chart. Participants were instructed to read aloud down the chart starting from the top left. All correct answers are recorded on a pre-set score sheet. The test is terminated if the participant makes two consecutive errors52. Assessment was done for each eye and binocularly.\n\nContrast sensitivity (CS). CS was measured using the Mars CS sheets (Mars letter CS chart, Mars Percetrix™, New York, USA) placed on an adjustable holder53. The sheet consists of 48 Latin letters of uniform height; the contrast from the white background decreases with subsequent letters. Room illumination was adjusted so that average CS sheet luminance was between 80 and 120cd/m² (measured via a luminance meter). Assessment was done for each eye and binocularly with the average distance from the participants eyes being 50cm. Participants read aloud down the sheet starting at the top left. Errors were recorded on the pre-set score sheet and testing was terminated after two consecutive errors.\n\nThe Unified Parkinson's disease Rating Scale (UPDRS). The Unified Parkinson's Disease Rating Scale54 (Movement Disorder Society revised version) was used to assess motor and non-motor features of PD and disease severity. The UPDRS was scored from a total of 195 points; higher scores reflect worsening disability.\n\nHoehn & Yahr (H & Y). The Hoehn and Yahr rating scale55 is a widely used clinical rating scale, which defines broad categories of motor function in PD. Only PD participants with mild to moderately severe motor function (H&Y stages I–III) were included.\n\nThe FOG questionnaire (FOGQ). Freezing of gait (FOG) was evaluated using the FOG questionnaire56,57. This is a ten-item questionnaire intended to classify FOG. The questionnaire has three parts; distinction of freezers from non-freezers, freezing severity, frequency and duration and impact of freezing on daily life.\n\nThe Geriatric Depression Scale (GDS-15) short form. The geriatric depression scale (GDS-15) short form54,55 was used to evaluate participant depression. The GDS-15 was created in 1986 by Sheikh and Yesavage and involves 15 questions about the mood of participants56. The GDS-15 classifies depression via the following scores; 0 to 4 indicates a normal range, 5 to 9 indicates mild depression, and 10 to 15 indicates moderate to severe depression57.\n\nFalls Efficacy Scale – International version (FES-I). Fear of falling was measured using the falls efficacy scale – international version (FES-I). This is a short validated measure of fear of falling in older adults, which assesses basic and demanding activities (both physical and social)58. It consists of 16 scenarios (e.g. cleaning the house) and participants must rate their fear of falling on a scale from 1 (Not at all concerned) to 4 (Very concerned).\n\n\nMeasurement of visual sampling during gait\n\nParticipants walked under different environmental (Figure 1) and attentional conditions in order to assess the impact of more complex (visual) environments and (cognitive) tasks.\n\nEnvironmental conditions included; walking straight, walking straight through a doorway and turning while walking through a doorway (see Figure 1). The visual sampling during gait testing was also repeated with a visual cue in place for the straight walks. The visual cue consisted of transverse black tape lines on a white floor placed 50cm apart (approx. a ‘normal’ step length) as depicted in Figure 1, which participants were asked to step over as they complete the walk. A visual cue was used as they are known to help ameliorate gait impairments in PD61, which may be due to the increased task-related visual information62 or greater attention being allocated to gait61.\n\nAttentional conditions included; single task (i.e. just walking) and dual task (i.e. repeating numbers while walking based on a maximal forward digit span obtained in sitting). A dual task was used as a representative of real-world walking, in which carrying out several tasks at once is common (i.e. walking and talking)60.\n\nBoth groups (PD and controls) performed the same walking conditions (Figure 1); with repeat measures (three trials for each condition) taken for an average to be created.\n\nVisual sampling (the combination of saccades and fixations) was assessed with a Dikablis (Ergoneers, Germany) head-mounted infra-red eye tracking system, synchronised with a 3D motion capture system (Vicon, Oxford, UK) and an electrooculography (EOG) system (Zerowire, Aurion, Italy), to allow for simultaneous and comprehensive recording and analysis of gait and eye movement data. Dikablis calibration was performed while standing using the manufacturer 4-point procedure for each participant prior to data collection. Similar to our previous research29, EOG was also calibrated prior to data collection via asking participants to blink for 30 secs and move their eyes horizontally between set-distance visual targets (5°, 10° and 15°) for 30 secs in time with an auditory cue (a metronome beat) while seated.\n\nThe Dikablis eye-tracker recorded eye movement using an infra-red camera63–65, this data was combined with EOG data which involves two small electrodes being applied bi-temporally on the forehead of the participant. Importantly, the Dikablis has an adequate sampling frequency (50Hz) to detect saccades during gait66,67 and EOG has a high sampling frequency (1000Hz) which allows accurate acquisition of specific visual sampling characteristics such as velocity, acceleration, distance etc.15. The Dikablis device includes two aspects; a head unit and a transmitter bag. Both the head unit (approx. the same size as a pair of glasses) and the bag (approx. 1kg) are lightweight. The head unit was taped, with a small amount of double sided tape, to the forehead of the participants to prevent error due to slippage. Eye movement data from the Dikablis was collected at 50Hz and from the EOG system at 1000Hz; this was saved onto a computer to be analysed using proprietary software66.\n\nVideo recording and the Vicon 3D motion capture system recorded participants movement during walking using a camcorder and infra-red sensors attached to the skin of the participants at specific locations (Figure 2; 2× shoulders, 1× sternum, 2× anterior superior iliac spine (ASIS), 2× posterior superior iliac spine (PSIS), 2× big toe, 2× instep, 2× heel and 4× head) using a small amount of double sided tape. Participants were required to bring their own shorts and a vest to wear in order for the markers to be placed onto the appropriate body locations. Vicon 3D motion analysis is a valid and reliable method of assessing the spatiotemporal parameters of gait in older adults and in people with PD68.\n\nMobile infra-red eye-tracking and EOG have been shown to be a valid and reliable method for assessing saccadic activity in younger adults69, and both have previously been used in older adults and in people with PD29,70–73. We were interested in the accuracy and test-retest reliability of mobile eye-tracking in people with PD and older adult controls to ensure the robustness of data interpretation. Therefore, a subgroup (PD and control; up to n=25) were asked to return approx. one week later for a second and third visit for accuracy and test re-test reliability testing (Table 2). The Dikablis eye-tracker recorded eye movement and was used in the same manner as the previous study63–65, combined with video recording of individuals body movement and a tri-axial accelerometer (Axivitiy, AX3, York, UK) recording head movement.\n\nIn the second session the sub-group of participants were asked to repeat the walking tasks from session 1 (single task, without a visual cue) to provide visual sampling during gait reliability data. Accuracy of visual sampling measurement was determined by asking participants to sit (with chin rest in situ), stand (without moving their head) and walk (free head movement) on a treadmill, while performing several eye movements to visual targets (horizontal and vertical visual angles such as 5°, 10°, 15°) in time with an auditory cue (a metronome). The subgroup was asked to return for a third visit (within approx. 1 week of the second visit) to repeat the accuracy testing (as above) in order to derive test-retest reliability results.\n\n\nPrimary outcome measure\n\nThe primary outcome measure was saccade frequency (number of fast eye movements per second when walking) during gait, which was recorded via the Dikablis mobile eye-tracker and EOG systems.\n\nVisual sampling. Secondary visual sampling outcomes included: saccade number, velocity, acceleration, amplitude and duration, as well as fixation number and duration.\n\nGait characteristics. Gait characteristics were measured via video recording and a Vicon 3D motion capture system for all walking conditions in order to examine associations between cognitive and visual functions and gait, and saccadic frequency and gait (Figure 1). Spatiotemporal gait characteristics included step velocity, step length, step time, single support time and double support time, which were chosen because they have been selectively associated with cognitive74 and visual functions75,76 in people with PD and older adults in previous research.\n\nSafety considerations. All measurements were non-invasive and placed the participant at no risk other than those that normally may occur during walking. To prevent excessive fatigue, participants were encouraged to take breaks as needed throughout all study procedures. The hypoallergenic double-sided tape used to fix the infra-red markers and Dikablis head unit onto the skin of the participants did not cause any adverse effects. The amount of tape was small and it has been used on numerous occasions in other research projects at the CARU and no issues have been reported. The bi-temporal EOG electrodes also did not cause any adverse effects. The treadmill used within the accuracy and reliability testing was equipped with a safety harness to avoid any falls-related injuries, as the harness could support the participant and trigger the treadmill to automatically stop in the event of a fall.\n\nEthical approval. Ethical approval for this project was obtained from the NRES Committee North East -Newcastle and North Tyneside 1 Research Ethics Committee (approved 6th June 2013, Reference 13/NE/0128). Written informed consent was obtained for every participant prior to testing. The study began 1st July 2013.\n\nDissemination. Data collection for the study finished in July 2015 and results will be published within peer reviewed scientific journals, open-access publication will be preferred. A public engagement event will also be used to disseminate findings to participants and public. All participants were assigned participant numbers, allowing data to be anonymised and reported confidentially. All results from the study will be uploaded to Clinicaltrails.gov (ID: NCT02610634) once analysed. No contractual agreement limits access to data.\n\n\nStatistical analysis\n\nThis was an exploratory study and therefore few specific previous examples were available to guide estimates for sample size. We have based the estimate (≥40 participants in each group) on our previous work (PD; n=21)29 and other previous similar studies. Similar studies in this research area72,73,77–80 have used small sample sizes (n=2–26) and reported between-group differences, demonstrating that we will be able to see differences between our sizable PD and control groups. It is a general recommendation to include 30 cases per group to be able to carry out basic statistical tests (e.g. between group comparisons)81. This study will inform future power calculations.\n\nData analysis will follow a predetermined plan:\n\nStatistical analysis will be undertaken using SPSS version 21 (SPPS, Inc. an IBM company). Demographic characteristics and baseline data will be summarized using descriptive statistics, including means, standard deviations, median, minimum, maximum and inter-quartile ranges for continuous or ordinal data and percentages for categorical data. The descriptive statistics will be tabulated and presented graphically for clarity. One-sample Kolmogorov-Smirnov tests will be used to check for normally distributed data. Non-normally distributed continuous distributions will be transformed where appropriate to meet the requirements of parametric tests; otherwise equivalent non-parametric tests will be adopted. Data will also be assessed graphically (such as histograms or scatter plots) for clarity of information. As this is an exploratory study a threshold of p < .05 (two-sided) will guide statistical interpretation.\n\nTo analyse visual sampling during gait, a series of mixed analysis of variance (ANOVA) will be used with effect of PD (PD and control) as between participant factor and attention (single task, dual task) and environment (Straight walk, Door, Turn) as within group factors. Pearson’s correlations will be used to test the strength and direction of the relationships between clinical, gait and saccade frequency outcomes. Gait characteristics will also be assessed with the same mixed ANOVA method.\n\nTo test the effect of visual cueing on visual sampling and gait; a mixed ANOVA will be used with group (PD and control), visual cue (no cue and cue) and attention (single task, dual task). Comparison with and without a visual cue will also be made via the same mixed ANOVA for the various gait characteristics, while controlling for the influence height.\n\nAssociations between cognitive and visual functions will be made using Pearson correlations. Cognitive and visual function contribution to visual sampling will be assessed using multiple regression analysis, while controlling for demographic factors (age, motor severity, depression, global cognition).\n\nTo analyse reliability; repeated-measure t-tests, Bland and Altman plots, intra-class correlation coefficients (Model 2, 1) and Pearson’s correlations (or non-parametric equivalents) will be used to assess bias, absolute and relative agreement and consistency of saccadic outcomes measured with the Dikablis eye-tracker on two separate occasions a week apart. A similar statistical approach will be used to assess accuracy of the Dikablis system against targets of a known angle (5°, 10° and 15°).\n\n\nDiscussion\n\nThe aims of this study were to provide a greater understanding of the roles that cognition and vision play in gait in PD. Specifically this study provided data regarding the role that visuo-cognition plays in gait in PD, as well as relationships between cognitive and visual functions (termed visuo-cognition). What sets this project apart from other work in this field is that the study is taking into consideration the combined and interactive impact that cognitive and visual function impairments have on gait in PD.\n\nThe study protocol was developed in response to recently reviewed evidence and study recommendations for visual sampling during a dynamic motor task15. The protocol focussed not only on cognitive impairments but also visual dysfunction which is commonly reported in PD and until now has not been fully investigated. Little quantitative data has been previously reported regarding visual sampling during real-world tasks (e.g. gait, reaching etc.) in PD and the few previous studies available only involve small cohorts often performing simple static motor tasks (i.e. mouse clicks or button pressing or reaching82,83).\n\nThis study investigated the online visuo-cognitive behavioural measure of visual sampling during a real-world task (i.e. gait), and data analysis will examine interaction between visual sampling, cognitive and visual functions and task performance. The study will determine the influence of cognitive and visual functions on visual sampling during gait and gait characteristics in PD. This will allow us to determine whether gait impairments in PD are influenced by basic visual function (CS and VA) impairment or cognitive impairment (particularly attention) or a combination of these aspects.\n\nFinally, an important feature of this study is that it is expected to provide the first evidence on the accuracy and reliability of using mobile eye-tracking equipment during gait with older adults and people with PD, which will develop the standard of research being conducted in this area and allow for more definitive conclusions.\n\n\nConclusion\n\nThis exploratory observational study will assist with understanding the role that cognition and vision play in gait in PD and how combined visuo-cognitive processes influence gait outcomes. In addition, it will provide evidence on the interaction between cognitive and visual functions in PD, as well as how visual sampling during gait is affected by the use of clinical interventions such as visual cues.\n\n\nList of Abbreviations\n\nACE-R: Addenbrookes cognitive examination (revised version)\n\nANOVA: analysis of variance\n\nCARU: clinical ageing research unit\n\nCDR: Cognitive drug battery\n\nCRESTA: Clinics for Research and Service in Themed Assessments\n\nCS: Contrast sensitivity\n\nEOG: Electro-oculography\n\nFES-I: Falls efficacy scale (international version)\n\nFOG: Freezing of gait\n\nFOGQ: Freezing of gait questionnaire\n\nGDS-15: Geriatric depression scale (short form)\n\nJLO: Judgement of line orientation\n\nMMSE: Mini mental state examination\n\nMoCA: Montreal cognitive assessment\n\nPD: Parkinson’s disease\n\nPIS: Participant information sheet\n\nUPDRS: Unified Parkinson’s disease rating scale (Movement Disorder Society revised version)\n\nVA: Visual acuity\n\nVOSP: Visual object and space perception battery",
"appendix": "Author contributions\n\n\n\nLR is the Chief/Principle Investigator for the study. SS is carrying out this study as part of his PhD and is responsible for the day to day running of the study. He drafted this manuscript and also wrote the study protocol with BG, SL and LR from its inception. SS and BG designed the statistical analyses, along with Dr Shirley Coleman (Statistician, Industrial Statistics Research Unit, Newcastle University) and SL is involved with participant recruitment. All authors are involved in academic oversight of the study and were involved in the revising this manuscript, giving final approval for publication.\n\n\nCompeting interests\n\n\n\nThe author(s) declare that they have no competing interests.\n\n\nGrant information\n\nThis study is funded by the National Institute for Health Research (NIHR) Biomedical Research Unit, based at the Newcastle upon Tyne Hospitals NHS Foundation Trust and administered by Newcastle University (REF: BH120877). The grant was awarded to Professor Lynn Rochester for the project and supports the PhD studies of Samuel Stuart.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nThe authors acknowledge Dr Alan Godfrey (Brain and Movement Research Group at Newcastle University) for his engineering assistance with the extraction and analysis of the eye-tracking and gait data involved in the study. We would also like to acknowledge Dr Shirley Coleman (Statistician, Industrial Statistics Research Unit, Newcastle University) for her guidance with statistical analysis.\n\nThis research is supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Unit (BRU) and centre (BRC) based at Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. The research was also supported by NIHR Newcastle CRF Infrastructure funding. 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}
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[
{
"id": "11401",
"date": "07 Dec 2015",
"name": "Rebecca J Reed-Jones",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis protocol seeks to understand whether visual-cognition influences gait performance and visual sampling behaviour in individuals with Parkinson's disease. Overall the protocol is well written and the details provided are sufficient to replicate the study. The sample sizes are good for gait and eye tracking data analysis. The tests used for evaluation of cognition and visual spatial ability are validated and appropriate tests. However, there are several methods and/or analyses the authors should consider in their protocol that will help to address their aims. In addition, there are several minor additions that the authors should also consider.Major points:Is the 4-point calibration matrix for the eye tracker sufficient? The accuracy of eye trackers increases with the number of points used in the calibration. Some indication as to the accuracy of using only four points should be made. In addition, what was the size of the calibration field used? The calibration field should be as large as the filed of view intended for the activity. In gait, the visual field is relatively large and therefore making the calibration field as large as possible is important. For visual sampling dependent variables, I would recommend the addition of examining areas of interest. In addition to whether participants are moving their eyes (how much, how often and how quickly), WHAT they are looking at is also of value. This is particularly relevant to the research question of understanding the influence of cognition as WHAT they are looking at may give you an indication of attention to particular objects or areas that may or may not be relevant to the task. For example, some work done by Shirley Rietdyk that was presented at ISPGR in Seville showed some interesting results of increased obstacle collisions when young adults looked off the travel pathway. Given the number of visual spatial and cognitive tests used to assess these domains, would a more sophisticated regression model be more valuable? The use of principal component analyses (PCAs) or separate hierarchical linear regression models could examine the interrelationships of the variables. Details on these types of analyses that may be useful can be found in the following papers.Pua YH, Liang Z, Ong PH, Bryant AL, Lo NN, Clark RA. (2011) Associations of knee extensor strength and standing balance with physical function in knee osteoarthritis. Arthritis Care and Research 2011;63(12):1706–14. doi: 10.1002/acr.206151Reed-Jones RJ, et al. WiiFitTM Plus balance test scores for the assessment of balance and mobility in older adults. Gait & Posture 36(3):430-3. doi:10.1016/j.gaitpost.2012.03.0272Minor points:The aims are stated clearly, however when it comes to the methods there are a large number of tests described. Reading through the tests in the methods it is not clear what these will be used for and how they address the aims of the research. Perhaps within the aims section an additional sentence or two that indicates how each aim will be tested would help the reader to follow along with the tests described in the methods more clearly. The authors provide details on the inclusion/exclusion criteria for participants. However, for the PD participants, a summary of the demographics of the participants in the study should be provided. In particular, the distribution of H&Y stages in the group, the distribution of medication versus DBS, versus a combination of the two.",
"responses": [
{
"c_id": "1868",
"date": "24 Mar 2016",
"name": "Sam Stuart",
"role": "Author Response",
"response": "We thank the reviewer for their time and comments which we believe have improved the manuscript. Please find below a list of reviewer comments and our reply.Comments (Q) & Response (A)Major Points:Q: Is the 4-point calibration matrix for the eye tracker sufficient? The accuracy of eye trackers increases with the number of points used in the calibration. Some indication as to the accuracy of using only four points should be made. In addition, what was the size of the calibration field used? The calibration field should be as large as the field of view intended for the activity. In gait, the visual field is relatively large and therefore making the calibration field as large as possible is important.A: The four-point calibration procedure has been developed by the manufacturer and we are unable to increase or decrease the number of points used. We agree that it may increase the accuracy of the calibration with more points, but this has yet to be investigated. We calibrated the eye tracker to the dimensions of the gaitlab where the individuals would walk, which meant that the calibration was as large as possible. This was done by placing four cones with markers on top in the area to be walked through, which were used as the four points for the calibration.Q: For visual sampling dependent variables, I would recommend the addition of examining areas of interest. In addition to whether participants are moving their eyes (how much, how often and how quickly), WHAT they are looking at is also of value. This is particularly relevant to the research question of understanding the influence of cognition as WHAT they are looking at may give you an indication of attention to particular objects or areas that may or may not be relevant to the task. For example, some work done by Shirley Rietdyk that was presented at ISPGR in Seville showed some interesting results of increased obstacle collisions when young adults looked off the travel pathway.A: Examining areas of interest is certainly a topic for future investigation in this field of research. However mobile eye-tracking technology is not capable of automatically performing area of interest analysis with sufficient accuracy for our purpose. Currently only frame-by-frame manual analysis of the area of interest data is possible, which with large numbers of participants and trials can be time consuming.Our recent mobile eye-tracker accuracy and reliability article (Stuart et al., 2016a) also showed that during walking the device (i.e. the cross hair on the field camera, that signifies where an individual is looking) can be up to 8 degrees off target, which can be the difference between looking at an obstacle and not looking at one. This does not affect the temporal data, as eye movements are still detected regardless of location of the cross hair on the field camera, but may impact area of interest analysis. Therefore the current study will focus on the temporal data, specifically saccade frequency during gait. Q: Given the number of visual spatial and cognitive tests used to assess these domains, would a more sophisticated regression model be more valuable? The use of principal component analyses (PCAs) or separate hierarchical linear regression models could examine the interrelationships of the variables. Details on these types of analyses that may be useful can be found in the following papers.Pua YH, Liang Z, Ong PH, Bryant AL, Lo NN, Clark RA. (2011) Associations of knee extensor strength and standing balance with physical function in knee osteoarthritis. Arthritis Care and Research 2011;63(12):1706–14. doi: 10.1002/acr.206151Reed-Jones RJ, et al. WiiFitTM Plus balance test scores for the assessment of balance and mobility in older adults. Gait & Posture 36(3):430-3. doi:10.1016/j.gaitpost.2012.03.0272 A: The contribution of cognitive and visual functions to visual sampling will be investigated based upon our a priori hypothesis that cognitive and visual functions, as well as demographic features will be associated with visual sampling (specifically saccade frequency). This will be done using multiple linear regression, performed in four separate steps;Step 1: Demographics (Age, UPDRS III, MoCA, GDS-15)Step 2: Cognition (Attention, Executive function, Visuo-spatial ability, Working memory)Step 3: Visual Functions (visual acuity, contrast sensitivity)Step 4: Visuo-cognition (combination of all of the variables in the above steps) Variables entered into the steps will be determined through univariate and bivariate analysis. Variables that best represent each cognitive outcome will be used within the analysis.Text has been added to the statistical analysis section which describes this analysis.Structural equation modelling (SEM) will be used to examine our a priori model of visuo-cognition in gait in PD (For a review pertaining to the model see; (Stuart et al., 2016b). This model will examine the inter-relationships between cognition, visual function, visual sampling (saccade frequency) and gait in PD. This technique is an ideal statistical method for assessing a priori hypotheses, as it allows for hypothesised interactions to be represented within the model. SEM also provides direct and indirect relationships between variables, which are not provided by regression analysis. This has been added to the statistical analysis section of the article. Minor points:Q: The aims are stated clearly, however when it comes to the methods there are a large number of tests described. Reading through the tests in the methods it is not clear what these will be used for and how they address the aims of the research. Perhaps within the aims section an additional sentence or two that indicates how each aim will be tested would help the reader to follow along with the tests described in the methods more clearly. A: The study aims with specific analysis are now provided within the statistical analysis section of the article.Q: The authors provide details on the inclusion/exclusion criteria for participants. However, for the PD participants, a summary of the demographics of the participants in the study should be provided. In particular, the distribution of H&Y stages in the group, the distribution of medication versus DBS, versus a combination of the two. A: A brief summary table for all participant demographic and clinical features is now provided within the article; Table 3. There are no individuals within the study that had Deep Brain Stimulation (DBS)."
}
]
},
{
"id": "11399",
"date": "10 Dec 2015",
"name": "Rodrigo Vitório",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this paper, S. Stuart and colleagues present an elegant and thorough protocol for testing visuo-cognition during gait. Authors aim to examine the contribution of cognition and vision in gait in Parkinson's Disease (independent roles and interaction between both functions), and the role of visuo-cognition in gait in Parkinson's Disease.The novelty of current study is taking into consideration the combined and interactive impact that cognitive and visual function impairments have on gait in Parkinson's Disease. To date, previous studies in this field have investigated the independent contribution of cognition and vision to gait in Parkinson's Disease.The described experimental design, including controls and methods, is totally adequate. Although the current version does not report the results, my expectation is that this study, once complete, will impact the field.",
"responses": [
{
"c_id": "1869",
"date": "24 Mar 2016",
"name": "Sam Stuart",
"role": "Author Response",
"response": "We thank the reviewer for their time and comments."
}
]
}
] | 1
|
https://f1000research.com/articles/4-1379
|
https://f1000research.com/articles/4-419/v1
|
29 Jul 15
|
{
"type": "Opinion Article",
"title": "The Inherent Drawbacks of the Pressure to Publish in Health Sciences: Good or Bad Science",
"authors": [
"Ricardo Jorge Dinis-Oliveira",
"Teresa Magalhães",
"Teresa Magalhães"
],
"abstract": "In recent years, there has been a significant increase in the number of scientific publications– it is the era of “hunting the article”. This commentary discusses the drawbacks of the pressure to publish that certainly contribute to the ‘dark side’ of science. In fact, health science career progression greatly relies on the number of scientific publications a researcher has, and in many cases these may be more valorized than the health services provided. Of course, scientific publications help to develop the skills of health care professionals, but as Einstein highlighted “not everything that counts can be counted, and not everything that can be counted counts”.",
"keywords": [
"pressure for publication",
"fraud",
"peer-review",
"impact factor",
"open access and traditional journals"
],
"content": "Introduction\n\nIn recent years, a significant increase in the number of scientific health publications has been registered. Some possible explanations include: (a) the feeling that nowadays “there is no science without being published”, as it corresponds to the permanent record of our research, reputation and “immortality”; (b) the author’s “motivation” to publish due to their need to obtain funding and further their career; (c) the perception that to publish is the individual or team effort to ensure the wide sharing of results; on the other hand, to not publish may suggest that the author is not committed to sharing knowledge and, in some cases, wishes to avoid scientific discussion with peers.\n\nPerhaps in the past it was more difficult to publish than it is at the present. Database access to publications was scarce or nonexistent, and the cycle of publication was time consuming without an online platform. Nevertheless, the competition to publish was not as aggressive, the impact factor and the h index were not a concern, and scientists were not constantly scrutinized according to their publication records/numbers. Nowadays, these aspects have become new worries, increased by new ethical and conflict of interest issues. Thus, to publish is both almost compulsory (a “question of survival”) and simultaneously a very hard task; we are in the era of “hunting the article”, which in some cases may promote fraud and corruption.\n\nHow could we explain the 1.7 to 1.8 million articles in 2013 in journals with peer-review (a supposed certificate of quality), or approximately one article every 18 seconds?1 Moreover, and in spite of significant innovation, some studies suggest that the average peer-review takes approximately 10.9 and 6.5 hours for young versus experienced reviewers, respectively2. In addition, according to Mabe3 the number of new peer reviewed journals and articles published annually has been growing at a very steady rate of about 3–3.5% per year for over three centuries, but in the last few years this increase has become more pronounced.\n\nPublishing is also a business and some authors even suggest that it is becoming pathological, with psychological and legal implications4. Indeed, the area of scientific publication moves many materials and human resources. The International Association of Scientific, Technical and Medical (STM) Publishers that holds 66% of the publication market and each year publishes nearly two-thirds of all journal articles, handled $9.4 billion in 2011 (up from $8 billion comparatively in 2008) solely in scientific journals, and employs about 110,000 people. Although the United States of America (USA) continues to dominate the global production of research papers, significant growth has also been registered for China and East Asia.\n\nThis commentary aims to highlight some relevant aspects of scientific publications that all health care providers and researchers, as well as medical students, should better understand in order to avoid publication misconduct.\n\n\nConcerns in selecting scientific journals\n\nIn traditional journals, articles are usually behind a ‘pay-wall’, meaning that readers must have a subscription or pay a fee to read content. In opposition to this traditional method, the number of open access (OA) journals have been increasing in the last few years5. OA journal models comprise two main approaches:\n\nThis model of OA publishing has been increasing in popularity6 and represents direct publication in OA journals, with the majority requiring payment of the cost of publication. Nevertheless, some are sponsored, which means that the author does not pay or some institutions may have an agreement with publishers (i.e. the OA membership). A hybrid or optional variant exists (i.e. only part of the article is immediately OA and, if wanted, the author may pay for the full article to be OA);\n\nIn this case, some traditional journals, after an embargo (necessary to recover the investment by publishers), allow the publication of some articles in free repositories (e.g. MEDLINE, PsyDok). For free access after the embargo these journals may require the payment of article processing charges.\n\nThere are around 10,128 fully OA journals listed on the Directory of Open Access Journals7. This publication model is important for future citation and therefore to maximize the impact of research. The clients of the publishers are the authors and not the readers, but the exaggeration in the number of journals and articles may even disquiet the best proponents of the OA model. For example, in 2013 PLOS ONE published approximately 31,500 articles (a staggering increase from 138 articles in 2006), meaning almost one in every 60 PubMed articles if from PLOS ONE8. This “megajournal” structure is widely accepted as one of the most trusted OA journals, practicing a very broad scope and a rapid “non-selective” peer review based on “soundness not significance” (i.e. selecting papers on the basis that science is soundly conducted rather than more subjective criteria of impact, significance or relevance to a particular community)2. Currently, Brazil is the country with the most OA journals after the USA; more than one thousand. That abundance was recently described as “a plague of Brazilian science: articles of second class”9.\n\nIn our opinion one of the best papers alerting the community to this problem was published by Bohannon10. The author investigates the peer-review process of the fee-charging OA journals. Between January and August 2013, Bohannon submitted obvious false articles to 304 scientific journals. In the author’s opinion the article should have been immediately rejected by the editors and reviewers, but 60% of journals accepted it. The article was based on multiple combinations of the “X molecule of species Y lichens that inhibits the growth of cancer cells Z”. For each article, Bohannon even faked the authors and affiliations. All articles essentially concluded that those molecules had therapeutic activity in several cancer types. The study also showed a map of the geographical location of the editors and publishers and their bank accounts. The author concluded that any reviewer with basic knowledge of chemistry and with skills to analyze an elementary graph should have immediately detected the article’s faults. He concluded that “it was easy to jump directly from the test tube to the clinic”.\n\nSubsequently, Hvistendahl11 reported that in China, a black market has been developed by some agencies to allow authors to write articles without a need to perform experimental work. The prices depend on whether the person paying wishes to be listed as the primary writer, or as merely a co-author, or even as just one of the team members. Authors suggested that this black market may have contributed to China’s rapid growth in the number of Science Citation Index (SCI) articles, with China’s contribution now the second largest, after the USA. Curiously, a running joke in China offered another meaning for SCI: “Stupid Chinese Idea”12.\n\nFurthermore, researchers are bothered with several invitations to review or submit articles that are not within their main area of research, and the same invitations are distributed to many email accounts. Perhaps also sharing the same annoyance at this state of affairs, Jeffrey Beall in August 2012 published the first edition of the “Criteria for Determining Predatory Open-Access Publishers”. These criteria were the start point to generate a list of potential, possible, or probable predatory OA scholarly publishers.\n\nSimilar problems may also occur with traditional journals, even peer-reviewed. The question is no longer if we should have OA journals. In fact, they are a very positive way to share scientific knowledge for all researchers, and many possess great credibility. The question now is what journals we should choose and how to assess their credibility. To help to solve this problem, it is now possible for readers to perform a continuous re-reviewing of published articles as it occurs for F1000Research. Through the readers’ opinions, journal credibility will be scrutinized.\n\n\nConstraints of the peer review cycle\n\nPeer review is a methodological evaluation on the soundness of the topic, originality, methodology, results and conclusions highlighted by the author and the authorities cited. Although it cannot generally assure that the data is truthful or not, peer review unquestionably increases the quality of most manuscripts. Nevertheless, this procedure is sometimes slow, expensive, profligate, subjective, prone to bias, poor at detecting gross defects, and almost useless in detecting fraud13.\n\nTypically pre- (e.g. double and single-blind, and open) or post-publication peer review is practiced. Double-blind peer review is more common in the humanities and social sciences than in the exact sciences. Although the identity of the reviewers is not disclosed and vice-versa (which removes the potential influence of the involved countries, institutions or eventual personal conflicts), the process sometimes fails, because the method, style of writing, acknowledgments and abuse of self-citations can suggest the source. In single-blind peer review the author is unaware of the identity of the reviewers; it is the most common process, especially in life sciences and is useful for the reviewer in order to consult previous authors’ works. By the same reasons listed for the double-blind peer-review, the process may sometimes fail. Although less common than the previous peer reviews, the open peer review process is increasing: nevertheless, it results in less acceptances to review since reviewers are afraid of being identified if commenting negatively on the article14. Nevertheless, it is expected that reviewers produce better revisions and avoid offensive or rude words. The name of the reviewers and comments may be published alongside the article as it occurs in the British Medical Journal.\n\nOnce the pre-publication peer review process is completed, the decision to publish is made by the journal editor on the advice of the reviewers. The editor of a journal is usually an independent, leading expert in his/her field appointed and sometimes financially supported by the publisher. An apparent misuse of editorial privileges was practiced by the editor of “Chaos, Solitons and Fractals” (a theoretical-physics journal), who was criticized by using its pages to publish numerous articles written by himself (e.g. 36 papers in the December 2008 issue)15.\n\nFinally, in post-publication peer review, the quality is assessed by the sapient of crowds and readers can also judge the quality of the review process. This peer review is outside the editor’s monopoly and journals usually also provide a discussion forum about the article in order for researchers to comment on and read other’s comments. Similar to the British Medical Journal, referee reports and names are published alongside the article, together with the authors' responses to raised points. It is believed that both invited and un-invited (i.e., commenting) post publication peer review helps to increase the quality of the final publication and it is certainly more transparent. F1000Research follows this model and advocates that time is not lost in reviews, since each article is only subjected to editorial verification and within approximately one week is published online already formatted and can be read and cited (http://f1000research.com/about).\n\n\nLimitations of the impact factor\n\nIn 1960, the Institute for Scientific Information (ISI) was founded by Eugene Garfield and later he proposed the impact factor (IF) as a tool for journal evaluation by librarians to help them with journal purchasing decisions16. The ISI was purchased by Thomson Scientific & Healthcare in 1992 becoming the “Thomson ISI”. IF it is not a perfect tool to measure the prestige of the journal, but there is no better. Falagas and colleagues performed a very interesting discussion on metrics for scientific journals as well as for researchers17. Some biases of the IF include: (a) it is not statistically representative of individual articles; (b) review articles (often highly cited) greatly skew the results; (c) extensive articles always have many citations and yield a high IF; (d) it includes self-citations; (e) books do not count for citations; (f) databases primarily index articles in English (but the IF also exists for non-English journals) and are dominated by USA publications; (g) it is dynamic since it depends on fluctuations of research in a given area; (h) paid access of some journals; (i) journals with tight scope tend to have low IF; (j) it does not take into account the subjects variability (e.g., immunology and cancer are usually highly cited); (k) editors aware of the importance of the IF tend to accept articles that may be highly cited and to reduce the number of articles accepted; (l) the absence of an IF in a given journal can result in low submissions; (m) it is only applied to ISI journals; (n) one highly cited article can boost the IF in a given journal (e.g., the impressive IF of 49.9 for Acta Crystallographica Section A: Foundations of Crystallography; the primary cause of this high impact factor was a single feature article by Sheldrick18).\n\n\nFraud in life sciences\n\nNowadays, there is rising interest in research and publication ethics. Proof of that is the increased importance of organizations such as the Committee on Publication Ethics (COPE) and the development of software to detect plagiarism. Although, the number of journal article retractions has grown in the last decade19, it is the general consensus that this may be the result of increased awareness rather than misconduct2. Nevertheless, several fraudulent/misconduct cases have been made publicly available.\n\nAndrew Jeremy Wakefield, a former British surgeon and researcher, published a fraudulent study in 1998 claiming that there was an association between the administration of the measles, mumps and rubella vaccine, and the development of autism and Crohn’s disease20,21.\n\nThe German physicist Jan Hendrik Schön, starred a scandal related to semiconductors that triggered a series of retractions, six of them out of Science22. Hwang Woo-suk (i.e. the pride of South Korea) was sentenced to two years in prison with suspended sentence after distorting the results published in two Science articles related to cloning of human embryonic stem cells23,24.\n\nMore recently in January 2014, Haruko Obokata, a young researcher in Japan published in Nature, showed stem cells can now be made quickly just by dipping blood cells into acid25,26. On June 2014, Obokata agreed to retract both the papers and 2 months later Obokata’s mentor and co-author, Yoshiki Sasai, committed suicide by hanging. Although investigation cleared him of misconduct, he was not free of critiques for inadequate supervision of Haruko Obokata.\n\nIn 2005, the researchers David Mazières and Eddie Kohler designed an anecdote manuscript, to send in response to unsolicited congress invitations. Later in 2014, Peter Vamplew, an associate professor at the Federation University Australia School of Engineering and Information Technology, after receiving a spam email from the International Journal of Advanced Computer Technology (classified as predatory OA on Beale’s list’), forwarded Mazières’ and Kohler’s old paper as a response. The journal’s peer-review process classified the manuscript as “excellent” and accepted it for publication27. At the end, the manuscript was not actually published since Vamplew declined to pay the article processing charge. Acceptance of a paper consisting entirely of 863 repetitions of “Get me off your fucking mailing list” has led commenters to question whether the enterprise is more interested in collecting publication fees than in contributing first-rate peer reviewed articles to the advancement of computer science27.\n\nSome epic/record examples of fraud were practiced by Joachim Boldt and Yoshitaka Fujii. Joachim Boldt is a German anesthesiologist who was dismissed of his professorship and is under criminal investigation for having allegedly faked of up to 90 research studies28. Yoshitaka Fujii is a Japanese researcher in anesthesiology, who in 2012 was found to have fabricated data in at least 172 scientific papers over the past 19 years, setting what is believed to be a record for the number of papers by a single author requiring retractions29,30. Many of the listed co-authors did not know they were authors and their signatures had been forged in the copyright transfer.\n\n\nConcluding remarks\n\nBeing a scientist is a stimulating and gratifying task, but full of difficulties. Scientists do not have schedules and need to fight for financial support; their careers grow exponentially when they publish (especially in high IF journals) and their job security frequently depends on the number of publications. But first of all, scientists are human beings, with families, needs and emotions. Therefore, the motivation to be successful and remain employed may increase the risk of involvement in scientific fraud or even corruption. This may lead authors, journals and publishers to lose their credibility. Particularly problematic is the impact of fraud in areas that have significant impact on the health, safety and welfare of the world’s population, as are the cases of life and health sciences. Moreover, scientific research slows since it is necessary to spend more time confirming published results. Taradi and colleagues show that over 90% of the medical students of Croatia admitted to engaging in education dishonesty and over 78% engaging in academic misconduct31. Indeed, fraud can help the scientist rise, but also fall rapidly.\n\nWe need to change the paradigm of scientific research. We cannot grow at all costs. It is also relevant to make peer review more transparent to produce publications that are more genuine and free from bias. The increase in publications, research studies split into multiple publications (rather than single, longer articles), the proliferation of journals, the ways in which academic promotion fosters this proliferation of publications, and the ways in which these changes can encourage bad or even fraudulent science are important topics that will certainly dictate the future of life and health sciences research.\n\nFortunately, fraud and corruption are punctual cases. Nevertheless, we will face problematic times if financial issues superimpose the ethics in publishing. This “crisis” may be an opportunity and challenge to reflect on these topics.",
"appendix": "Author contributions\n\n\n\nRJ Dinis-Oliveira prepared the first draft of the manuscript.\n\nRJ Dinis-Oliveira and Magalhães T discussed the content and wrote the final version. Both authors assume the full responsibility for the article and agreed with the final content.\n\n\nCompeting interests\n\n\n\nThe authors declare no competing interests.\n\n\nGrant information\n\nRicardo Dinis-Oliveira acknowledges Fundação para a Ciência e a Tecnologia (FCT) for his Investigator Grant (IF/01147/2013).\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nBjörk BC, Roos A, Lauri M: Scientific journal publishing: Yearly volume and open access availability. Information Research. 2009; 14(1). Reference Source\n\nWare M, Mabe M: The stm report: an overview of scientific and scholarly journal publishing. 3rd ed. Netherlands: International Association of Scientific, Technical and Medical Publishers. 2012. Reference Source\n\nMabe M: The growth and number of journals. Serials: The Journal for the Serials Community. 2003; 16(2): 191–7. Reference Source\n\nBuela-Casal G: Pathological publishing: A new psychological disorder with legal consequences? Eur J Psychol Appl L. 2014; 6(2): 91–7. Publisher Full Text\n\nVan Noorden R: Open access: The true cost of science publishing. Nature. 2013; 495(7442): 426–9. PubMed Abstract | Publisher Full Text\n\nVan Noorden R: Britain aims for broad open access. Nature. 2012; 486(7403): 302–3. PubMed Abstract | Publisher Full Text\n\nNumber of listed open access journals. 2015. Reference Source\n\nGraham K: Thanking our peer reviewers. Plos One Community Blog. 2014. Reference Source\n\nUma praga da ciência brasileira: os artigos de segunda. Veja. 2014. Reference Source\n\nBohannon J: Who's Afraid of Peer Review? Science. 2013; 342(6154): 60–5. PubMed Abstract | Publisher Full Text\n\nHvistendahl M: China's publication bazaar. Science. 2013; 342(6162): 1035–9. PubMed Abstract | Publisher Full Text\n\nSun Q, Xin Q, Wei L, et al.: “Science Citation Index Worship” in China. Iran J Public Health. 2013; 42(8): 921–2. PubMed Abstract | Free Full Text\n\nSmith R: Opening up BMJ peer review. BMJ. 1999; 318(7175): 4–5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWare M, Monkman M: Peer Review in scholarly journals: an international study into the perspective of the scholarly community. Bristol: Mark Ware Consulting. 2008. Reference Source\n\nSchiermeier Q: Self-publishing editor set to retire. Nature. 2008; 456(7221): 432. PubMed Abstract | Publisher Full Text\n\nGarfield E: Citation analysis as a tool in journal evaluation. Science. 1972; 178(4060): 471–9. PubMed Abstract | Publisher Full Text\n\nFalagas ME, Kouranos VD, Arencibia-Jorge R, et al.: Comparison of SCImago journal rank indicator with journal impact factor. FASEB J. 2008; 22(8): 2623–8. PubMed Abstract | Publisher Full Text\n\nSheldrick GM: A short history of SHELX. Acta Crystallogr A. 2008; 64(Pt 1): 112–22. PubMed Abstract | Publisher Full Text\n\nVan Noorden R: Science publishing: The trouble with retractions. Nature. 2011; 478(7367): 26–8. PubMed Abstract | Publisher Full Text\n\nWakefield AJ, Murch SH, Anthony A, et al.: Ileal-lymphoid-nodular hyperplasia, non-specific colitis, and pervasive developmental disorder in children. Lancet. 1998; 351(9103): 637–41. PubMed Abstract | Publisher Full Text\n\nGodlee F, Smith J, Marcovitch H, et al.: Wakefield’s article linking MMR vaccine and autism was fraudulent. BMJ. 2011; 342: c7452. PubMed Abstract | Publisher Full Text\n\nBao Z, Batlogg B, Berg S, et al.: Retraction. Science. 2002; 298(5595): 961. PubMed Abstract | Publisher Full Text\n\nHwang WS, Ryu YJ, Park JH, et al.: Evidence of a pluripotent human embryonic stem cell line derived from a cloned blastocyst. Science. 2004; 303(5664): 1669–74. PubMed Abstract | Publisher Full Text\n\nHwang WS, Roh SI, Lee BC, et al.: Patient-specific embryonic stem cells derived from human SCNT blastocysts. Science. 2005; 308(5729): 1777–83. PubMed Abstract | Publisher Full Text\n\nObokata H, Wakayama T, Sasai Y, et al.: Stimulus-triggered fate conversion of somatic cells into pluripotency. Nature. 2014; 505(7485): 641–7. PubMed Abstract | Publisher Full Text\n\nObokata H, Sasai Y, Niwa H, et al.: Bidirectional developmental potential in reprogrammed cells with acquired pluripotency. Nature. 2014; 505(7485): 676–80. PubMed Abstract | Publisher Full Text\n\nBogus journal accepts profanity-laced anti-spam paper. Scholarly Open Access. 2014. Reference Source\n\nMillions of surgery patients at risk in drug research fraud scandal. The Telegraph. 2011. Reference Source\n\nA New Record for Retractions? (Part 2). Scienceinsider. 2012. Reference Source\n\nAnesthesiologist Fabricates 172 Papers. 2012. Reference Source\n\nKukolja Taradi S, Taradi M, Knežević T, et al.: Students come to medical schools prepared to cheat: a multi-campus investigation. J Med Ethics. 2010; 36(11): 666–70. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "10656",
"date": "02 Oct 2015",
"name": "Frederico Pereira",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis opinion article timely captures the air du temps` concerning the overwhelming pressure to publish in health sciences. The authors specifically delved into the core of concerns about selecting scientific journals, constrains of peer review processes and limitations of impact factor. Finally I should stress the title provides an appropriate summary of the content of the paper and warrants readership.",
"responses": []
},
{
"id": "10709",
"date": "15 Oct 2015",
"name": "Rita Ferreira",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nWe found the opinion article of Dinis-Oliveira and Magalhães very pertinent as it highlights the pressure that researchers face to show scientific production indicators. Such pressure for “hunting the article”, one of the most used indicators of scientific production, clearly distorts the ideal of any young scientist, to make scientific discoveries with relevance to humankind. It would be interesting to add some discussion on the association between funding and scientific production, as it is not always straightforward.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/4-419
|
https://f1000research.com/articles/5-396/v1
|
24 Mar 16
|
{
"type": "Review",
"title": "Extremophiles and biotechnology: current uses and prospects",
"authors": [
"James A. Coker"
],
"abstract": "Biotechnology has almost unlimited potential to change our lives in very exciting ways. Many of the chemical reactions that produce these products can be fully optimized by performing them at extremes of temperature, pressure, salinity, and pH for efficient and cost-effective outcomes. Fortunately, there are many organisms (extremophiles) that thrive in extreme environments found in nature and offer an excellent source of replacement enzymes in lieu of mesophilic ones currently used in these processes. In this review, I discuss the current uses and some potential new applications of extremophiles and their products, including enzymes, in biotechnology.",
"keywords": [
"Extremophiles",
"Biotechnology",
"biofuels",
"Carotenoids",
"Proteases",
"Lipases"
],
"content": "Introduction\n\nThe impact of biotechnology on our lives is inescapable. Some of these impacts are well publicized, like the process of generating biofuels. However, there are numerous other applications that are not widely known outside of specialist circles that affect our daily life, such as food and drink (e.g. lactose-free milk1 and bioinsecticides2), how we make and wash our clothes (e.g. cellulases to produce ‘stone-washed’ jeans3, lipases4, and proteases5 in detergents), and the medications we take to remain healthy, just to name a few examples.\n\nMany of the reactions performed in the process of making these products are often not optimized because mesophilic enzymes are used at extremes of temperature, pressure, salinity, and pH6. The efficiency of these enzymes is often improved through genetic and/or chemical modification7,8 as well as immobilization strategies9, all of which are designed to produce biocatalysts with improved properties such as increased activity and/or stability to use in specific industrial processes. This can be a lengthy and (more importantly) costly enterprise, especially since nature provides many readily available alternatives in the form of extremozymes, which are found in organisms that thrive in extremes of temperature (as high as 122°C and as low as −12°C), pressure (as high as 1000 atm), salinity (up to and including saturating levels), and pH (from 0 to 6 and 8 to 12)10–15. As such, their enzymes are already adapted to work under the extreme conditions of many industrial processes.\n\nTo date, few extremophiles/extremozymes have found their way into large-scale use in the field of biotechnology16; however, their potential is undeniable in many applications. Four success stories are the thermostable DNA polymerases used in the polymerase chain reaction (PCR)17, various enzymes used in the process of making biofuels18, organisms used in the mining process19, and carotenoids used in the food and cosmetic industries20. Other potential applications include making lactose-free milk1; the production of antibiotics, anticancer, and antifungal drugs6; and the production of electricity or, more accurately, the leaching of electrons to generate current that can be used or stored21.\n\nThis review initially focuses on the four success stories of extremozymes in biotechnology. Then it discusses the most prominent sectors of the enzyme market (glycosyl hydrolases, lipases, proteases, and those of medical importance) where the application of extremophiles/extremozymes could replace currently used enzymes to make reactions more efficient and/or cost effective.\n\n\nDNA polymerases\n\nIt is difficult to overstate the success or impact the DNA polymerases from the thermophiles Thermus aquaticus, Pyrococcus furiosus, and Thermococcus litoralis, otherwise known as Taq22, Pfu23, and Vent24, respectively, have had in biotechnology. Without a doubt, the automated version of the PCR would not have been possible without these enzymes. During its patent lifetime, PCR earned its rights holders over $2 billion in royalties25. It is difficult to imagine our lives without PCR, especially for a typical bench scientist. However, fields once thought to be far removed from science, like law enforcement, have also benefitted greatly from PCR by making it more readily possible to identify and rule out suspects on the basis of their DNA profile26. Even the entertainment industry, with its many movies, novels, and TV shows centered on forensic science and PCR-based technologies, has greatly benefitted from PCR. The impact these three hyperthermophilic enzymes have had on biotechnology and our current culture can only be described as immense.\n\n\nBiofuel production\n\nIn an effort to supplement the planet’s dwindling supply of fossil fuels, there has been a concerted effort to generate similar fuels using biomass (e.g. corn, beets, wheat, and sugar cane). Depending on the specific source, biofuels can be categorized into first and second generation. First-generation biofuels are those derived from the ‘easily’ hydrolyzed sugars, starches, and oils of available crops, whereas second-generation biofuels are derived from lignocellulosic material, which is more resistant to hydrolysis.\n\nBiofuels can also be categorized by the eventual end products: butanol, ethanol, hydrogen, methane, and biodiesel. Traditional methods of biobutanol and bioethanol production involve the use of a chemical process supplemented with the use of mesophilic microorganisms such as Saccharomyces cerevisiae and Clostridium species27. The production of hydrogen traditionally relies on a chemical/catalyst process28; however, larger-scale microorganism-based systems using the thermophiles Caldicellulosiruptor saccharolyticus and Thermotoga elfii have been developed recently29. In contrast to the other products, methane has always been produced using a consortium of microorganisms, which include methanogens (extremophiles that are the only known biologic producers of methane)18.\n\nMany of the steps in biofuel production involve high temperatures and extremes of pH; therefore, extremophiles are ideal candidates to replace the mesophilic organisms used in traditional methods. For example, Thermoanaerobacterium saccharolyticum is able to utilize hemicellulose and pentose sugars like xylose as a starting material to produce ethanol30. Engineered versions of this thermophile have shown great promise in producing large quantities of ethanol and minimizing other side reactions/products31. There are also numerous applications for extremophiles in the production of hydrogen through anaerobic fermentation and hydrogenases. The use of strains of Caldicellulosiruptor, Thermoanaerobacterium32, Pyrococcus33, and Aeropyrum34 shows immense potential. The research is still very preliminary; however, recent advances such as the engineering of a hyperthermophile are quite promising35,36.\n\nThe two products produced by microorganisms that show the most commercial success are biodiesel and butanol. Biodiesel harvests the power of high lipid content (>75% dry weight) algae, most of which contain long-chain hydrocarbons like those found in petroleum. There are several extremophilic algae (e.g. Cyanidium caldarium37 and Galdieria sulphuraria38) that meet these requirements. Engineered halophilic algae also hold great promise, as they can be grown in open containers since the high salinity required for their growth inhibits other microbes. This means they can be grown in underutilized environments such as the oceans and arid/desert environments39.\n\nButanol is quite inhibiting to the growth of microorganisms compared with ethanol (most organisms cannot tolerate more than 2%). As such, organisms need to be modified in order to overcome product inhibition and withstand large quantities of butanol. Currently, Green Biologics is producing biobutanol from corn stock by using thermophilic Clostridium. Other companies such as Gevo, Joule Unlimited, and Solazyme are also able to produce large-scale volumes of bioethanol and biodiesel as well as jet fuel for both civilian and military use. Additionally, Sapphire Energy has moved one step back in the process and generates what it calls ‘Green Crude’, which can act as a replacement for crude oil in the existing petroleum infrastructure.\n\n\nBiomining\n\nIn addition to biofuels, another important application of extremophiles and their enzymes can be found in the mining sector40. This process, also known as bioleaching, is the removal of insoluble metal sulfides or oxides by using microorganisms41. It is a safer and more environmentally friendly way to extract metals compared with traditional heap leaching, which involves the use of several chemicals, including cyanide, to bind and separate specific minerals/metals from others.\n\nIn 1992, biomining accounted for 10% of worldwide copper production6, but current estimates place it at around 15% for copper and 5% for gold42. Extraction rates are around 90% from biomining compared with 60% for traditional heap leaching41. Biomining techniques have successfully been employed to mine metals such as gold, silver, copper, zinc, nickel, and uranium. The organisms used in this process are acidophiles such as Acidithiobacillus and Ferroplasma. However, depending on the conditions, more thermophilic strains, like Sulfolobus and Metallosphaera40,41, may have to be employed.\n\nAlthough biomining is generally safe, it does need to be tightly controlled, since it can result in acid mine drainage (AMD), which occurs when acidic water, generated by the oxidation of sulfides from the mine, begins flowing or leaching out of the mine. Since the acidophiles employed in biomining thrive in acidic and usually heavy-metal environments, AMD results in an environment that is not only very acidic but also rich in heavy metals. Copper, zinc, and nickel mines are the most common sources of AMD41. Interestingly, mesophilic and sometimes psychrophilic acidophiles are the main culprits of AMD41. However, when thermophiles are used in biomining, the possibilities of AMD are reduced and costs associated with the cooling of processing tanks are kept to a minimum.\n\n\nCarotenoids\n\nCarotenoids are natural pigments and in extremophiles are most often associated with the halophilic archaea and algae43. Most carotenoids cannot be synthesized/extracted from organisms at levels that are useful for industry; however, there are three exceptions to this: bacteriorhodopsin, canthaxanthin, and β-carotene44.\n\nBacteriorhodopsin is a membrane-bound retinal pigment as well as a proton pump that functions as a rudimentary form of photosynthesis. It is a very stable molecule and harvested from the extreme halophilic archaeon Halobacterium salinarum43. It has been adapted for use in a wide range of applications from holography, artificial retinas, photochromic dyes, spatial light modulators, and the renewal of biochemical energy45.\n\nCanthaxanthin is a lipid-soluble antioxidant used as a food dye and a feed additive. As a feed additive, it is used in fish, crustacean, and poultry farms. It is also used in the cosmetics industry and usually is the primary ingredient in tanning pills46. As with bacteriorhodopsin, halophilic archaea are the producers of choice with Haloferax alexandrinus being the preferred strain47.\n\nβ-carotene is a red/orange pigment and the primary colorant in carrots, pumpkins, and halophilic microorganisms. The halophilic alga Dunaliella salina is the major source for β-carotene, as its commercial-scale growth results in 30–40 g dry weight/m2 per day39. Due to its chemical nature, it is a lipid/oil- and water-soluble molecule, which makes it excellent as an additive in the baking process (e.g. food coloring) and emulsions (e.g. confectionery and prepared foods). However, its primary use is probably as a food supplement39.\n\n\nProteases/lipases\n\nProteases and lipases, combined with the gylcosyl hydrolases, account for more than 70% of all enzymes sold48 while proteases alone are the most widely used class of enzyme. Proteases have numerous applications in diverse fields; however, the largest application is in laundry detergents, where they have been a standard component since 1985 and are used to break apart and remove protein-based stains49. The other major uses for proteases are in the fields of cheese making, brewing, and baking. Typically, the microbial proteases used are mesophilic and derived from Bacillus species and produced by companies such as Novozymes and Genencor. However, explorations using psychrophilic proteases to enhance cold water washing have taken place. Unfortunately, most psychrophilic enzymes have proven to be unusable due to low stability at room temperature. However, through directed evolution, a chimeric psychrophilic/mesophilic protease was generated that improved performance during cold water washing50.\n\nLipases are a billion-dollar industry51 and very attractive for use in industrial settings because of their broad range of substrates, high degree of specificity, and stability52. Although their applications in laundry detergents (i.e. low temperatures and alkaline conditions) and organic synthesis (i.e. low water activity) require lipases to be active under extreme conditions, most lipases used are mesophilic. Many mesophilic lipases, which typically come from organisms like Bacillus and Aspergillus species, are active at high temperatures. As a result, extremophilic lipases are often overlooked; however, lipases from thermophilic Bacillus species have been shown to be more efficient than currently used enzymes53.\n\n\nGlycosyl hydrolases and sugars\n\nGlycosyl hydrolases hydrolyze the glycosidic bond between a carbohydrate and another moiety and are categorized into well over 100 families. The hydrolysis generally takes place with the use of only two amino acids—a proton donor and a nucleophile/base—and results in retention or inversion of the anomeric configuration of the resulting carbohydrate.\n\nRoughly 70% of the world’s population54 suffers from lactose intolerance resulting from a lack or loss of β-galactosidase activity. For this majority of the population, the best way to avoid the often embarrassing symptoms of lactose intolerance is through the consumption of lactose-free milk and other dairy products, which are generated via the use of the lactase (β-galactosidase) from organisms like Kluyveromyces lactis54. However, for the enzyme to be active, the temperature of the dairy product must be raised (from about 5°C to 25°C). This elevation in temperature creates the potential for pathogens to grow as well as for altering the flavor profile of the milk. A simple solution to both issues is to use a β-galactosidase from a psychrophile1. This enzyme would be active at low temperature and hydrolyze lactose throughout the entire process from production to shipment and storage by the consumer55. This approach could save significant amounts of money by eliminating the heating step as well as achieve a high percentage of lactose hydrolysis. Currently, several cold-adapted enzymes have been characterized and developed that perform on par with the currently used mesophilic enzymes when compared at their respective temperature optima (i.e. 15°C and 37°C)1,55,56.\n\nSimilar to the industrial-scale hydrolysis of lactose, that of starch traditionally uses mesophilic enzymes. Starch-hydrolyzing enzymes comprise about 25% of the worldwide enzyme market; however, several adjustments in temperature and pH are needed for most of the reactions to ensure optimal conditions.\n\nSince the industrial processes involved in hydrolyzing starch require high temperatures (95°C for one step and 60°C for the other) and high pH, polyextremophilic (thermophilic and alkaliphilic) enzymes would be ideal. Currently, an α-amylase from Bacillus acidicola57, glucoamylases from Picrophilus58, and a pullulanase from Thermococcus kodakarensis59 show great promise in replacing their mesophilic counterparts. However, amylases have also been isolated from halophiles, such as Halomonas meridian and Natronococcus amylolyticus, that could be useful in the process of producing high-fructose corn syrup, which is produced by hydrolyzing corn starch43.\n\nIn addition to sugar hydrolysis, another promising application for extremophiles is the production of carbohydrates like trehalose and ectoine, which can be used as stabilizers for products like antibodies and vaccines60,61. The production of trehalose from Sulfolobus solfataricus in a bioreactor has been perfected and could easily replace the currently used mesophilic enzymes from Arthrobacter species Q3643. Another example is ectoine, which has been shown to protect skin from UVA-induced damage. RonaCare™ Ectoin, produced by Merck KGaA (Darmstadt, Germany) is used as a moisturizer and comes from halophilic microorganisms39. In addition to trehalose and ectoine, several other carbohydrates are produced by halophiles as compatible solutes that can also be employed as preservatives62.\n\n\nMedical applications\n\nSurprisingly, microorganisms, including extremophiles, are producers of a host of antibiotics, antifungals, and antitumor molecules63. In truth, this should come as little surprise, as microorganisms have been killing each other and fighting for survival for billions of years. After that long a time, it should be clear that microorganisms have perfected the art of warfare, but it is up to us to take advantage of it.\n\nIn addition to the typical antibiotics known from mesophilic microorganisms64,65, extremophiles are known to generate antimicrobial peptides and diketopiperazines66. Antimicrobial peptides have been found in the Halobacteriaceae (phylogenetic family containing all halophilic archaea) as well as Sulfolobus species. These peptides (halocins) from halophilic archaea are thought to be found in all species of the family. Each halocin has a specific range of activity, and some act on a broader range of microorganisms than others39. Halocins have been shown to be effective at killing archaeal cells; however, there are no data to show that halocins kill microorganisms pathogenic to humans. Interestingly, there is evidence that they assist canines in recovering from surgery67.\n\nDiketopiperazines (also known as cyclic dipeptides) have been shown to affect blood-clotting functions as well as having antimicrobial, antifungal, antiviral, and antitumor properties. They are found in halophiles like Naloterrigena hispanica and Natronococcus occultus45 and have been shown to activate and inhibit quorum-sensing pathways66. These pathways are important in pathogens such as Pseudomonas aeruginosa, which is one of the causative agents of pneumonia and a typical infection found in patients with cystic fibrosis68,69. Therefore, this could be an alternative treatment for the tens of thousands of drug-resistant Pseudomonas aeruginosa infections that occur each year (http://www.cdc.gov/hai/organisms/pseudomonas.html).\n\nIn addition to molecules that kill other organisms and tissues, extremophiles can also play a role in the medical field through the use of bioplastics. Several species of extremophiles produce polyhydroxyalkanoates (PHAs), which are a heterogeneous group of polyesters; however, they are most commonly found in the halophilic archaea39. For example, it has been shown that Haloferax medeterrani can be grown with 65% of its dry weight as PHAs, which translates into 6 g/L of culture when grown in media supplemented with starch45. PHAs are often used as carbon storage for microbial cells but have been harnessed to generate bioplastics and have been lauded for their biocompatibility, resistance to water, and biodegrading properties, all of which make them an attractive alternative to petroleum-based plastics45.\n\nFinally, a very interesting extremophile contribution to the field of medicine comes in the form of an alternative vaccine delivery system70. Several microorganisms produce internal gas vesicles, small gas-filled proteinaceous structures, the best-studied coming from the halophilic archaea. These structures have been engineered in Halobacterium species NRC-1 to generate a recombinant form that expresses portions of the simian immunodeficiency virus on the external surface71. Once collected, these recombinant vesicles have shown a strong antibody response and immune memory when injected into mice. Typically, vaccines derived from recombinant methods require the addition of adjuvants (e.g. cholera toxin B) to elicit a large enough immune response71. However, in the case of the recombinant gas vesicles from Halobacterium species NRC-1, the organism’s own polar lipids can be used as an adjuvant, as they raise a large immune response since they are ether linked as opposed to the more typical ester-linked molecules. Experiments using NRC-1’s polar lipids and recombinant gas vesicles as a nasal-delivered vaccine in mice were quite encouraging and showed no toxicity71.\n\n\nConclusions\n\nWith established commercial success in the DNA polymerase, biofuels, biomining, and carotenoid sectors of biotechnology, extremophiles and their enzymes have an extensive foothold in the market that is expected to keep growing. However, to fulfill this great potential, innovative methods will have to be developed to overcome current roadblocks. The most significant is a current lack of ability to produce most extremophiles/extremozymes on the large scale required by industrial processes. Some recombinant extremozymes can be produced in large quantities by mesophilic organisms like Escherichia coli; however, this is not true for most. Therefore, new expression systems will have to be developed with extremophilic organisms as the host to achieve high expression of soluble proteins. Another significant roadblock is the general lack of partnerships among academia, industry, and government. More opportunities for ties between all three groups should be encouraged, nurtured, and supported from all sides. For it is only with all three working together that the most progress will be made.\n\n\nAbbreviations\n\nAMD, acid mine drainage; PCR, polymerase chain reaction; PHA, polyhydroxyalkanoate.",
"appendix": "Competing interests\n\n\n\nThe author declares that he has no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nAcknowledgments\n\nI would like to thank all of my students and members of my laboratory as well as my colleagues for the discussions we have had over the years. I have learned a lot from you all and look forward to many more years of the same.\n\n\nReferences\n\nCoker JA, Brenchley JE: Protein engineering of a cold-active beta-galactosidase from Arthrobacter sp. SB to increase lactose hydrolysis reveals new sites affecting low temperature activity. Extremophiles. 2006; 10(6): 515–24. PubMed Abstract | Publisher Full Text\n\nRubio-Infante N, Moreno-Fierros L: An overview of the safety and biological effects of Bacillus thuringiensis Cry toxins in mammals. J Appl Toxicol. 2015. 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PubMed Abstract | Publisher Full Text\n\nTindbaek N, Svendsen A, Oestergaard PR, et al.: Engineering a substrate-specific cold-adapted subtilisin. Protein Eng Des Sel. 2004; 17(2): 149–56. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJaeger KE, Dijkstra BW, Reetz MT: Bacterial biocatalysts: molecular biology, three-dimensional structures, and biotechnological applications of lipases. Annu Rev Microbiol. 1999; 53: 315–51. PubMed Abstract | Publisher Full Text\n\nHasan F, Shah AA, Hameed A: Industrial applications of microbial lipases. Enzyme Microb Technol. 2006; 39(2): 235–51. Publisher Full Text\n\nImamura S, Kitaura S: Purification and characterization of a monoacylglycerol lipase from the moderately thermophilic Bacillus sp. H-257. J Biochem. 2000; 127(3): 419–25. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMessia MC, Candigliota T, Marconi E: Assessment of quality and technological characterization of lactose-hydrolyzed milk. Food Chem. 2007; 104(3): 910–7. Publisher Full Text\n\nCoker JA: Structure and function relationships in the cold-active beta-galactosidase, BgaS, examining theories of enzyme cold-adaptation. Doctoral dissertation. Penn State. 2004. Reference Source\n\nCoker JA, Sheridan PP, Loveland-Curtze J, et al.: Biochemical characterization of a beta-galactosidase with a low temperature optimum obtained from an Antarctic Arthrobacter isolate. J Bacteriol. 2003; 185(18): 5473–82. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSharma A, Satyanarayana T: Cloning and expression of acidstable, high maltose-forming, Ca2+-independent α-amylase from an acidophile Bacillus acidicola and its applicability in starch hydrolysis. Extremophiles. 2012; 16(3): 515–22. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSerour E, Antranikian G: Novel thermoactive glucoamylases from the thermoacidophilic Archaea Thermoplasma acidophilum, Picrophilus torridus and Picrophilus oshimae. Antonie Van Leeuwenhoek. 2002; 81(1–4): 73–83. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHan T, Zeng F, Li Z, et al.: Biochemical characterization of a recombinant pullulanase from Thermococcus kodakarensis KOD1. Lett Appl Microbiol. 2013; 57(4): 336–43. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nArgüelles JC: Physiological roles of trehalose in bacteria and yeasts: a comparative analysis. Arch Microbiol. 2000; 174(4): 217–24. PubMed Abstract | Publisher Full Text\n\nGuo N, Puhlev I, Brown DR, et al.: Trehalose expression confers desiccation tolerance on human cells. Nat Biotechnol. 2000; 18(2): 168–71. PubMed Abstract | Publisher Full Text\n\nRoberts MF: Organic compatible solutes of halotolerant and halophilic microorganisms. Saline Syst. 2005; 1: 5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLittlechild JA: Archaeal Enzymes and Applications in Industrial Biocatalysts. Archaea. 2015; 2015: 147671. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLechevalier H: Actinomycetes and their products: a look at the future. World J Microbiol Biotechnol. 1992; 8(Suppl 1): 72–3. PubMed Abstract | Publisher Full Text\n\nWaksman SA, Schatz A, Reynolds DM: Production of antibiotic substances by actinomycetes. Ann N Y Acad Sci. 2010; 1213: 112–24. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMartins MB, Carvalho I: Diketopiperazines: Biological activity and synthesis. Tetrahedron. 2007; 63(40): 9923–32. Publisher Full Text\n\nShand RF, Leyva K: Archaeal antimicrobials: an undiscovered country. In: Paul Blum ed. Archaea: new models for prokaryotic biology. Norfolk, UK: Caister Academic Press, 2008; 233–44.\n\nAbed RM, Dobretsov S, Al-Fori M, et al.: Quorum-sensing inhibitory compounds from extremophilic microorganisms isolated from a hypersaline cyanobacterial mat. J Ind Microbiol Biotechnol. 2013; 40(7): 759–72. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKalia VC: Quorum sensing inhibitors: an overview. Biotechnol Adv. 2013; 31(2): 224–45. PubMed Abstract | Publisher Full Text\n\nStuart ES, Morshed F, Sremac M, et al.: Antigen presentation using novel particulate organelles from halophilic archaea. J Biotechnol. 2001; 88(2): 119–28. PubMed Abstract | Publisher Full Text\n\nStuart ES, Morshed F, Sremac M, et al.: Cassette-based presentation of SIV epitopes with recombinant gas vesicles from halophilic archaea. J Biotechnol. 2004; 114(3): 225–37. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13045",
"date": "24 Mar 2016",
"name": "Khawar Sohail Siddiqui",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13046",
"date": "24 Mar 2016",
"name": "Melanie Mormile",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-396
|
https://f1000research.com/articles/5-190/v1
|
18 Feb 16
|
{
"type": "Research Note",
"title": "Possible repurposing of seasonal influenza vaccine for prevention of Zika virus infection",
"authors": [
"Veljko Veljkovic",
"Slobodan Paessler",
"Slobodan Paessler"
],
"abstract": "The in silico analysis shows that the envelope glycoproteins E of Zika viruses (ZIKV) isolated in Asia, Africa and South and Central America encode highly conserved information determining their interacting profile and immunological properties. Previously it was shown that the same information is encoded in the primary structure of the hemagglutinin subunit 1 (HA1) from pdmH1N1 influenza A virus. This similarity suggests possible repurposing of the seasonal influenza vaccine containing pdmH1N1 component for prevention of the ZIKV infection.",
"keywords": [
"Zika virus",
"vaccine",
"influenza virus",
"vaccine repurposing",
"in silico analysis",
"hemagglutinin",
"envelope glycoprotein E",
"informational spectrum method"
],
"content": "Introduction\n\nThe recent pandemic of the pdmH1N1 influenza virus and epidemic of the Ebola virus in West Africa showed a lack of preparedness to adequately respond to emerging infectious diseases with potential catastrophic consequences. One of the main obstacles to a fast and efficient response to emerging new infectious disease is insufficient knowledge of the biological, immunological and pathogenic properties of new pathogens and a lack of an appropriate experimental system for testing drugs and vaccines. The new emergence of the ZIKV showed that despite significant progress in molecular biology, biochemistry, immunology, medicine and pharmacology which allows better understanding, prevention and therapy of infectious diseases, the world once again is not prepared for early and decisive action which would prevent hundreds of unnecessary cases of ZIKV infections and potential congenital abnormalities in newborns caused by this virus.\n\nPreviously, at the beginning of the HIV epidemic1, and recently during the swine flu pandemic2 and Ebola epidemic in West Africa3, we demonstrated that the bioinformatics tool which is based on the informational spectrum method (ISM)4 can give some useful information about the host-pathogen interaction and help in selection of drug and vaccine candidates. An essential advantage of ISM over other bioinformatics approaches is in the use of DNA and protein sequences as the only input information which allows analysis of new pathogens. Because data about the sequencing of new pathogens usually are available at the beginning of the outbreaks, the ISM analysis can start immediately and provide some information which could accelerate development of vaccines and drugs.\n\nThe ZIKV, native to parts of Africa and Asia, has for the first time been introduced into the Americas. The ZIKV epidemic in Brazil currently is estimated at 440000–1300000 cases, and in February 2016 it has spread to other Latin-American countries, the USA and Europe (http://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(16)00014-3.pdf), threatening to become a pandemic. Recently, the World Health Organization (WHO) declared an international public health emergency (http://www.who.int/mediacentre/news/statements/2016/emergency-committee-zika-microcephaly/en/). There is no vaccine against the virus or any antiviral treatment.\n\nHere we analyzed ZIKV E proteins using ISM. Results of this in silico analysis revealed that these viral proteins encode the highly conserved information which determines their interacting profile and immunological properties. Previously, we reported that the human interacting profile of HA1 from pdmH1N1 influenza viruses is characterized by the same information2. This result suggests possible repurposing of the seasonal influenza vaccine containing pdmH1N1 for prevention of ZIKV infection.\n\n\nMaterial and methods\n\nAll sequences of the ZIKV E protein are taken from the NCBI databank (http://www.ncbi.nlm.nih.gov/nuccore/?term=zika) and are given in Dataset 1 (accessions: KU312314, KU312315, KU312313, KU312312, KJ776791, KJ634273, KF993678, JN860885, EU545988, HQ234499, KF268950, KF268948, KF268949, AY632535, LC002520, DQ859059, HQ234501, HQ234500, FSS13025, AHL43505, AHL43503, AHL43502, AMA12087). Sequences for HA1 from influenza viruses were taken from the GISAID database (http://platform.gisaid.org) and are given in Dataset 2 (accessions: EPI705910, EPI696955).\n\nThe ISM is a virtual spectroscopy technique, developed for the study of protein-protein interactions. The physical and mathematical base of ISM was described in detail elsewhere (5 and references therein), and here we will only in brief present this bioinformatics method.\n\nThe ISM technique is based on a model of the primary structure of a protein using a sequence of numbers, by assigning to each amino acid the correspondence value of the electron ion interaction potential (EIIP; L 0.0000, I 0.0000, N 0.0036, G 0.0050, V 0.0057, E 0.0058, P 0.0198, H 0.0242, K 0.0371, A 0.0373, Y 0.0516, W 0.0548, Q 0.0761, M 0.0823, S 0.0829, C 0.0829, T 0.0941, F 0.0946, R 0.0959, D 0.1263). The EIIP values are in Rydbergs (Ry).\n\nThe obtained numerical sequence is then subjected to a discrete Fourier transformation which is defined as follows:\n\n\n\nwhere x(m) is the m-th member of a given numerical series, N is the total number of points in this series, and X(n) are discrete Fourier transformation coefficients. These coefficients describe the amplitude, phase and frequency of sinusoids, which comprised the original signal. Relevant information encoded in the primary structure is presented in an energy density spectrum which is defined as follows:\n\n\n\nIn this way, sequences are analyzed as discrete signals. It is assumed that their points are equidistant with the distance d = 1. The maximal frequency in a spectrum defined as above is F = 1/2d = 0.5. The frequency range is independent of the total number of points in the sequence. The total number of points in a sequence influences only the resolution of the spectrum. The resolution of the N-point sequence is 1/n. The n-th point in the spectral function corresponds to a frequency f(n) = nf = n/N. Thus, the initial information defined by the sequence of amino acids can now be presented in the form of the informational spectrum (IS), representing the series of frequencies and their amplitudes.\n\nThe IS frequencies correspond to the distribution of structural motifs with defined physicochemical properties determining a biological function of a protein. When comparing proteins, which share the same biological or biochemical function, the ISM technique allows detection of code/frequency pairs which are specific for their common biological properties, or which correlate with their specific interaction. These common informational characteristics of sequences are determined by the cross-spectrum (CS) which is obtained by the following equation:\n\n\n\nwhere Π(i,j) is the j-th element of the i-th power spectrum and C(j) is the j-th element of CS. Peak frequencies in CS represent the common information encoded in the primary structure of analyzed sequences. This information corresponds to the mutual interaction between analyzed proteins or their interaction with the common interactor.\n\n\nResults and discussion\n\nThe envelope glycoprotein (protein E) which mediates the virus cell entry is highly conserved and virtually identical in all ZIKV isolated during 2015 in countries of Central and South America. Figure 1A shows the IS of ZIKV E isolated in 2015 in Brazil (AMA12087) which is characterized by a dominant peak at frequency F(0.295). Figure 1B shows the CIS of protein E from ZIKV isolated between 1968 and 2015 in diverse countries of Asia and Africa (Dataset 1). This CIS contains only one dominant peak at frequency F(0.295). This result suggests that all analyzed ZIKV E encode the same highly conserved information which is represented by the IS frequency F(0.295). According to the ISM concept6–9, this information determines the interacting profile of ZIKV E.\n\n(A) The informational spectrum of ZIKV E protein. (B) The consensus informational spectrum of protein E from ZIKV isolated in Asia, Africa and South/Central America.\n\nPreviously, it has been shown that frequency F(0.295) characterizes the human interacting profile of pdmH1N1 HA12. It has also been shown that antigens which share a common frequency component in their IS are immunologically cross-reactive (10 and references therein). Presence of the frequency component F(0.295) in ZIKV E and pdmH1N1 HA indicates that antibodies elicited by this protein of influenza virus could affect interaction between ZIKV E and host proteins. We compared the IS of ZIKV E and HA1 from A/California/07/2009(H1N1) and A/Switzerland/9715293/2013(H3N2) viruses, which are components of the 2015/2016 seasonal influenza vaccine. Results given in Figure 2 and Figure 3A show that ZIKV E and A/California/07/2009(H1N1) encode the common information represented in their IS with the dominant peak at frequency F(0.295). As can be seen in Figure 3B, this frequency component is not present in the IS of A/Switzerland/9715293/2013(H3N2) HA1. These results indicate that antibodies elicited by the vaccine virus A/California/07/2009(H1N1) could affect interaction between ZIKA E and host proteins mediating virus cell entry.\n\n(A) The informational spectrum of ZIKV E protein. (B) The informational spectrum of HA1 from A/California/07/2009(H1N1) influenza virus.\n\n(A) The cross-spectrum of ZIKV E protein and HA1 from A/California/07/2009(H1N1) influenza virus. (B) The cross-spectrum of ZIKV E protein and HA1 from A/Switzerland/9715293/2013(H3N2) influenza virus.\n\n\nConclusions\n\nThe presented results of the in silico analysis of ZIKV E and host factors mediating viral infection suggest that the seasonal influenza vaccines containing pdmH1N1 as a component, could protect to some extent against the ZIKV infection. Because of the lack of prevention and therapy of the ZIKV disease, in a situation when the ZIKV infection is explosively spreading, this possible safe and inexpensive solution is worth being seriously considered.\n\n\nData availability\n\nF1000Research: Dataset 1. Sequences of the ZIKV E protein taken from the NCBI databank (accessions: KU312314, KU312315, KU312313, KU312312, KJ776791, KJ634273, KF993678, JN860885, EU545988, HQ234499, KF268950, KF268948, KF268949, AY632535, LC002520, DQ859059, HQ234501, HQ234500, FSS13025, AHL43505, AHL43503, AHL43502, AMA12087)., 10.5256/f1000research.8102.d11432511\n\nF1000Research: Dataset 2. Sequences of HA of A/California/07/2009(H1N1) and HA of A/Switzerland/9715293/2013(H3N2) taken from the GSAID database (accessions: EPI705910, EPI696955)., 10.5256/f1000research.8102.d11432612",
"appendix": "Author contributions\n\n\n\nConceived and designed the study: VV SP. Analyzed the data: VV. Wrote the paper: VV SP.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nVeljković V, Metlas R: Identification of nanopeptide from HTLV-III, ARV-2 and LAVBRU envelope gp120 determining binding to T4 cell surface protein. Cancer Biochem Biophys. 1988; 10(2): 91–106. PubMed Abstract\n\nVeljkovic V, Niman HL, Glisic S, et al.: Identification of hemagglutinin structural domain and polymorphisms which may modulate swine H1N1 interactions with human receptor. BMC Struct Biol. 2009; 9: 62. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVeljkovic V, Glisic S, Muller CP, et al.: In silico analysis suggests interaction between Ebola virus and the extracellular matrix. Front Microbiol. 2015; 6: 135. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVeljković V, Cosić I, Dimitrijević B, et al.: Is it possible to analyze DNA and protein sequences by the methods of digital signal processing? IEEE Trans Biomed Eng. 1985; 32(5): 337–341. PubMed Abstract | Publisher Full Text\n\nVeljkovic N, Glisic S, Prljic J, et al.: Discovery of new therapeutic targets by the informational spectrum method. Curr Protein Pept Sci. 2008; 9(5): 493–506. PubMed Abstract | Publisher Full Text\n\nVeljkovic V, Veljkovic N, Muller CP, et al.: Characterization of conserved properties of hemagglutinin of H5N1 and human influenza viruses: possible consequences for therapy and infection control. BMC Struct Biol. 2009; 9: 21. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPerovic VR, Muller CP, Niman HL, et al.: Novel phylogenetic algorithm to monitor human tropism in Egyptian H5N1-HPAIV reveals evolution toward efficient human-to-human transmission. PLoS One. 2013; 8(4): e61572. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSchmier S, Mostafa A, Haarmann T, et al.: In Silico Prediction and Experimental Confirmation of HA Residues Conferring Enhanced Human Receptor Specificity of H5N1 Influenza A Viruses. Sci Rep. 2015; 5: 11434. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVeljkovic V, Paessler S, Glisic S, et al.: Evolution of 2014/15 H3N2 Influenza Viruses Circulating in US: Consequences for Vaccine Effectiveness and Possible New Pandemic. Front Microbiol. 2015; 6: 1456. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVeljkovic V, Glisic S, Veljkovic N, et al.: Influenza vaccine as prevention for cardiovascular diseases: possible molecular mechanism. Vaccine. 2014; 32(48): 6569–6575. PubMed Abstract | Publisher Full Text\n\nVeljkovic V, Paessler S: Dataset 1 in: Possible repurposing of seasonal influenza vaccine for prevention of Zika virus infection. F1000Research. 2016. Data Source\n\nVeljkovic V, Paessler S: Dataset 2 in: Possible repurposing of seasonal influenza vaccine for prevention of Zika virus infection. F1000Research. 2016. Data Source"
}
|
[
{
"id": "12535",
"date": "03 Mar 2016",
"name": "Patrizio Arrigo",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper summarizes an application of well established and efficient ISM method to compare ZIKA and H1N1. I would like to underline two points that I guess to be better describe. I suggest that Figure 2 can contain also the consensus spectrum as Figure 1.The second point is the description of Figure 3 in the result section. I guess that the authors could extended the illustration of the differences of the cross-spectrum. These differences are very interesting data for discrimination. Another small remark is about the aim of the paper. The authors suggest a 'repositioning' of H1N1 vaccine if it is possible I would like to ask them if they have considered the possibility to elicit unfavourable effect of cross reactivity with the consequence to reduce the vaccine efficiency.",
"responses": []
},
{
"id": "12533",
"date": "14 Mar 2016",
"name": "Heinz Kohler",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis manuscript provides important information on the envelope of Zika virus that will help to produce a vaccine.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-190
|
https://f1000research.com/articles/5-393/v1
|
23 Mar 16
|
{
"type": "Review",
"title": "Overexpression of angiotensin-converting enzyme in myelomonocytic cells enhances the immune response",
"authors": [
"Kenneth E. Bernstein",
"Zakir Khan",
"Jorge F. Giani",
"Tuantuan Zhao",
"Masahiro Eriguchi",
"Ellen A. Bernstein",
"Romer A. Gonzalez-Villalobos",
"Xiao Z. Shen",
"Zakir Khan",
"Jorge F. Giani",
"Tuantuan Zhao",
"Masahiro Eriguchi",
"Ellen A. Bernstein",
"Romer A. Gonzalez-Villalobos",
"Xiao Z. Shen"
],
"abstract": "Angiotensin-converting enzyme (ACE) converts angiotensin I to the vasoconstrictor angiotensin II and thereby plays an important role in blood pressure control. However, ACE is relatively non-specific in its substrate specificity and cleaves many other peptides. Recent analysis of mice overexpressing ACE in monocytes, macrophages, and other myelomonocytic cells shows that these animals have a marked increase in resistance to experimental melanoma and to infection by Listeria monocytogenes or methicillin-resistant Staphylococcus aureus (MRSA). Several other measures of immune responsiveness, including antibody production, are enhanced in these animals. These studies complement a variety of studies indicating an important role of ACE in the immune response.",
"keywords": [
"Angiotensin-converting enzyme",
"ACE",
"angiotensin",
"immune response",
"renin-angiotensin system"
],
"content": "Introduction\n\nThe renin-angiotensin system (RAS) is composed of the substrate angiotensinogen, a protein produced by the liver, which is sequentially degraded by the enzymes renin and angiotensin-converting enzyme (ACE) into the vasoconstrictor angiotensin II. The workings of this system and its role as a central regulator of blood pressure control have been the subject of thousands of scientific publications1. Although there are voluminous biochemical data on each of the components of the RAS, an interesting question is the origins of this system. Such a question recognizes that blood pressure is a function of higher organisms, whereas the origins of the proteins composing the RAS go back to a time when simpler organisms had neither blood nor blood pressure. Angiotensinogen is a liver acute-phase protein; it is an α2 globulin related to haptoglobin and α2-microglobulin. Renin, made in the kidney, is an aspartyl protease related to pepsin, whereas ACE, made by endothelium and many other tissues, is a zinc-dependent peptidase. Whereas angiotensinogen and renin have evolved to the point where they participate only in blood pressure regulation, ACE plays additional roles and has been implicated in normal male reproduction, several aspects of hematopoiesis, the degradation of β-amyloid peptides, and several other physiologic and pathologic processes2–7.\n\nOne of the most interesting areas of ACE biology is its role in the immune response. Early evidence for this came from the analysis of ACE expression by the macrophages and giant cells found in granuloma. The formation of a granuloma is the immune system’s response to organisms or inorganic materials that are difficult to phagocytize8. The classic granuloma is associated with tuberculosis, but granuloma formation is also seen in sarcoid, leprosy, and several other diseases. It has been known for many years that the epithelial macrophages and giant cells that are a prominent feature of granulomas express ACE9. Thus, there is an association between the immune activation of the monocytic-derived cells in a granuloma and ACE expression. What remained unknown was whether ACE expression was also a contributor to this process.\n\n\nACE 10/10 mice\n\nOur experience with ACE and the immune response first came from the study of mice with genetic mutations in the ACE gene. The wild-type (WT) ACE protein contains two independent catalytic domains that resulted from an ancient gene duplication, estimated to have occurred over 300 million years ago1. Each catalytic domain independently binds zinc, which is required for catalytic activity. To understand the function of each catalytic domain, mice were made in which point mutations were introduced into the mouse genome that specifically inactivated either the ACE N- or C-domain zinc binding site10,11. Thus, the mutations specifically inactivated the N- or C-domain catalytic sites. These mice are called ACE N-KO and ACE C-KO, respectively. In these animals, the non-targeted domain remained fully catalytic and the tissue expression levels of the mutated ACE proteins were identical to those of WT mice. When peritoneal macrophages from these animals were isolated and exposed in vitro overnight to lipopolysaccharide (LPS), the macrophages were activated and secreted tumor necrosis factor alpha (TNFα) into the media (Figure 1)12. While mice lacking ACE C-domain catalytic activity produced roughly equivalent levels of TNFα as WT mice, macrophages from mice lacking N-domain activity (ACE N-KO) produced approximately fourfold higher levels. Thus, ACE activity can have profound effects on the ability of macrophages to produce the important pro-inflammatory cytokine TNFα.\n\nThioglycolate-elicited peritoneal macrophages were collected and purified by adhesion. After an overnight incubation with 1 μg/mL lipopolysaccharide, the concentration of TNFα was determined by enzyme-linked immunosorbent assay. The figure shows data for individual mice and the group mean ± standard error of the mean. C-KO, macrophages lacking the angiotensin-converting enzyme C-catalytic domain; N-KO, macrophages lacking the angiotensin-converting enzyme N-catalytic domain.\n\nA second model giving insight into the role of ACE in the immune function is a genetically engineered mouse line termed ACE 10/10. Here, gene targeting was used to insert a neomycin resistance cassette and strong transcriptional stop signal 3′ to the ACE promoter13. This acts as a barrier to endogenous ACE promoter activity. 3′ to the neomycin cassette, we inserted a c-fms promoter cassette that now controls tissue expression of the ACE gene. c-fms encodes the receptor for macrophage colony-stimulating factor and is normally expressed at high levels by myelomonocytic lineage cells14,15. Mice that are heterozygous or homozygous for the ACE 10/10 allele overexpress active ACE in monocytic cells such as monocytes and macrophages. Other myelomonocytic cells, such as neutrophils and dendritic cells, also overexpress ACE but at only 4% and 17% of macrophage levels, respectively. ACE expression by T or B cells is very low, similar to WT mice. Homozygous ACE 10/10 mice lack ACE expression by endothelial cells and renal epithelial cells. Despite this, ACE 10/10 mice have normal body weights, serum ACE levels, renal function, and blood pressure. They live normal life spans and have no evidence of auto-immune disease.\n\nThe first inkling that ACE 10/10 mice were unusual came from challenging the mice with B16-F10 (H-2b) melanoma tumor cells13. Tumor volumes were assessed 2 weeks after the intradermal injection of tumor cells. A typical response is shown in Figure 2. Whereas tumors in WT mice averaged 540 mm3, tumors in ACE 10/10 mice averaged only 90 mm3. This difference was seen using different B16 sublines and in both inbred and outbred ACE 10/10 mice. The decrease in tumor growth was dependent on CD8+ T cells; in ACE 10/10 mice, depletion of CD8+ T cells, but not CD4+ T cells, led to rapid tumor growth. When B16 tumor cells constitutively expressing ovalbumin were used, tetramer analysis of T-cell receptors showed that ACE 10/10 mice have more circulating tumor-specific CD8+ T cells with specificity for the ovalbumin epitope SIINFEKL and the B16 TRP-2 epitope (SVYDFFVWL) than WT mice. Tumor resistance was dependent on ACE catalytic activity, as demonstrated by WT levels of tumor growth in ACE 10/10 mice treated with an ACE inhibitor13. In contrast, treatment of the mice with an angiotensin II receptor antagonist had no effect on tumor growth.\n\nBoth ACE 10/10 and wild-type (WT) mice were injected intradermally with one million B16-F10 melanoma cells. After 14 days, there was a very significant difference in tumor growth, with WT mice having much larger tumors than ACE 10/10 mice. These photos show typical results. The fur of the ACE 10/10 was shaved to demonstrate the reduction in tumor size in these animals.\n\nAn insight into the mode of tumor resistance in ACE 10/10 mice was provided by histological examination of the small tumors present in these mice. This revealed far larger numbers of inflammatory cells, including monocytes, macrophages, and some lymphocytes within the tumor blood vessels and the tumor itself than in tumors from WT mice. Furthermore, tumor resistance was transferable by bone marrow transplantation from ACE 10/10 into WT mice. This transplant experiment was important since WT mice chimeric for ACE 10/10 bone marrow have normal ACE expression in all tissues except bone marrow-derived cells. Thus, these data and several other lines of investigation indicated that it was the presence of ACE activity in bone marrow-derived cells, and not the lack of ACE expression in endothelium, that was important in the enhanced immune response of the ACE 10/10 mice.\n\nThe ACE 10/10 mice were also tested in a tumor metastasis model where the mice were injected intravenously with B16 tumor cells16. After 14 days, melanotic modules in the lungs were quantitated. In this protocol, ACE 10/10 mice averaged only one third the number of visible lung metastases as in WT mice.\n\nA detailed analysis of macrophage function in ACE 10/10 mice indicated that these cells have a pronounced pro-inflammatory “M1” phenotype, as compared with equivalent WT cells. Specifically, macrophages from ACE 10/10 mice produced more interleukin-12 (IL-12) p40, TNFα, and nitric oxide synthase II (inducible nitric oxide synthase, or iNOS) in response to tumor cells or LPS. On the other hand, the ACE 10/10 cells made less of the immunosuppressive cytokine IL-1013,17,18.\n\n\nInnate immunity in ACE 10/10 mice\n\nResistance to B16 melanoma is typically thought to be mediated by the adaptive immune response. In order to assess innate immunity, the resistance of the ACE 10/10 mice to infection with either L. monocytogenes or methicillin-resistant S. aureus (MRSA) was evaluated17. Resistance to L. monocytogenes was assessed following intravenous injection of the strain EGD. Mice were sacrificed 3 or 5 days after infection, and bacterial counts were determined in the spleen and liver. This showed consistently fewer bacteria in ACE 10/10 mice as compared with WT. Pre-treatment of the ACE 10/10 mice for several days with the ACE inhibitor ramipril eliminated any significant differences between these mice and WT. In contrast, the angiotensin II receptor antagonist losartan had no significant effect.\n\nPeritoneal macrophages were also tested in vitro for their ability to kill L. monocytogenes. In the absence of interferon-gamma (IFNγ) priming, there was no significant difference between ACE 10/10 and WT macrophages in the killing of L. monocytogenes. As ACE 10/10 macrophages express abundant surface ACE, these data demonstrate that ACE has no direct bactericidal effect. However, after IFNγ priming, ACE 10/10 macrophages were much more effective in killing bacteria than WT macrophages were17.\n\nACE 10/10 mice were also challenged by intradermal infection with MRSA (USA300, strain SAF8300). After 4 days, bacterial counts in the skin lesions were determined. ACE 10/10 mice averaged 50-fold less bacteria within the MRSA lesions than WT mice. Again, this difference was eliminated by the ACE inhibitor lisinopril, and enhanced resistance to MRSA could be conferred by bone marrow transplant of ACE 10/10 bone marrow cells into WT mice17.\n\n\nImmunological memory and antibody production\n\nTo investigate immunological memory, female ACE 10/10 and WT mice were infected with polyoma virus. By 28 days, the mice clear serum polyoma and were re-challenged with either WT vaccinia virus (V-WT) or vaccinia virus modified to express the polyoma large T epitope LT359–368 (V-PLT)18. Four days after V-WT infection, there was no difference in ovarian vaccinia viral titers as measured by a plaque assay (Figure 3). However, when mice were challenged with V-PLT, there was a marked difference in viral titers. Thus, in a viral recall assay, these data indicate an increased immune response in the ACE 10/10 mice.\n\nWild-type (WT) and angiotensin-converting enzyme (ACE) 10/10 mice were infected with mouse polyoma virus. After 1 month, the mice were challenged with either WT vaccinia virus (V-WT) or a modified vaccinia virus which expressed a portion of the polyoma large T protein (V-PLT). Viral titers in the ovary were measured using a plaque assay. Whereas there is no difference in response to V-WT, the ACE 10/10 mice have a much better immune recall response to V-PLT.\n\nFinally, antibody production in ACE 10/10 mice was assessed after immunization with ovalbumin in complete Freund’s adjuvant (Figure 4). Ten days after immunization, plasma was collected and titers of antibody subtypes specific to ovalbumin were determined by enzyme-linked immunosorbent assay. The major anti-ovalbumin antibody was IgG1, which showed a 22-fold increase in the ACE 10/10 mice versus WT. A similar pattern of antibody increase was seen for IgG2b, IgG2c, and IgG3 antibodies, though at substantially lower levels of antibody expression.\n\nWild-type (WT) and angiotensin-converting enzyme (ACE) 10/10 mice were immunized subcutaneously with 100 μg of ovalbumin in complete Freund’s adjuvant. Ten days later, plasma was collected and titers of antibody subtypes specific to ovalbumin were determined by enzyme-linked immunosorbent assay. The major anti-ovalbumin antibody was IgG1, which showed a marked increase in the ACE 10/10 mice versus WT (990 versus 45 μg/mL). A similar pattern of increased antibody expression was seen for IgG2b, IgG2c, and IgG3 antibodies, though at lower levels of antibody expression. These data are for illustrative purposes only. The results are currently unpublished and have not been peer-reviewed but will be peer-reviewed and published elsewhere.\n\nThe data summarized here support the idea that ACE plays an important role in the immune response in addition to its role in regulating blood pressure. These data complement other studies implicating ACE in immunity to disease. These include a role of ACE and angiotensin II in the immune response to experimental auto-immune encephalomyelitis19–22, and rheumatoid and other types of arthritis23–26, in the production of the immuno-dominant epitope of the HIV protein gp16027,28, and in generating the peptide repertoire diversity displayed by major histocompatibility complex (MHC) class I proteins29,30.\n\n\nConclusions\n\nACE 10/10 mice are a model in which ACE is overexpressed in myelomonocytic cells, particularly monocytes and macrophages. It may be that this model recapitulates the expression of ACE by monocytic cells found in granuloma but that now supranormal expression levels generate a more pronounced immune phenotype than under natural conditions. We think that the most likely mechanistic explanation for the ACE 10/10 phenotype is that ACE overexpression fundamentally modifies the differentiation program of monocytes and macrophages. As indicated by the elimination of the phenotype after the administration of ACE inhibitors, the ACE 10/10 phenotype requires the catalytic activity of ACE and thus must be hypothesized to be a downstream effect of some ACE product(s). The precise peptides that have such a dramatic effect on the immune response are not known at present. The discovery that ACE overexpression enhances both innate and acquired monocytic function holds promise for an entirely new approach for improving the immune response to a variety of stimuli, including infections and tumors.\n\n\nAbbreviations\n\nACE, angiotensin-converting enzyme; IFNγ, interferon gamma; IL, interleukin; LPS, lipopolysaccharide; MRSA, methicillin-resistant Staphylococcus aureus; RAS, renin-angiotensin system; TNFα, tumor necrosis factor alpha; V-PLT, polyoma large T protein; V-WT, wild-type vaccinia virus; WT, wild-type.",
"appendix": "Competing interests\n\n\n\nRomer A. Gonzalez-Villalobos is a visiting scientist at Cedars-Sinai Medical Center. He is employed by the Pfizer Inc Drug Safety Research and Development (DSRD) Immunotoxicology Center of Emphasis (CoE) (Groton, CT, USA). The other authors declare that they have no competing interests.\n\n\nGrant information\n\nThis work was supported by National Institutes of Health grants R01 HL110353, R21 AI114965, and R03DK101592.\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nThe authors thank Brian Taylor for administrative assistance.\n\n\nReferences\n\nBernstein KE, Ong FS, Blackwell WB, et al.: A modern understanding of the traditional and nontraditional biological functions of angiotensin-converting enzyme. Pharmacol Rev. 2013; 65(1): 1–46. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKrege JH, John SW, Langenbach LL, et al.: Male-female differences in fertility and blood pressure in ACE-deficient mice. Nature. 1995; 375(6527): 146–148. PubMed Abstract | Publisher Full Text\n\nEsther CR, Howard TE, Marino EM, et al.: Mice lacking angiotensin-converting enzyme have low blood pressure, renal pathology, and reduced male fertility. Lab Invest. 1996; 74(5): 953–965. PubMed Abstract\n\nFuchs S, Frenzel K, Hubert C, et al.: Male fertility is dependent on dipeptidase activity of testis ACE. Nat Med. 2005; 11(11): 1140–2; author reply 1142–3. PubMed Abstract | Publisher Full Text\n\nHubert C, Savary K, Gasc J, et al.: The hematopoietic system: a new niche for the renin-angiotensin system. Nat Clin Pract Cardiovasc Med. 2006; 3(2): 80–85. PubMed Abstract | Publisher Full Text\n\nLin C, Datta V, Okwan-Duodu D, et al.: Angiotensin-converting enzyme is required for normal myelopoiesis. FASEB J. 2011; 25(4): 1145–1155. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBernstein KE, Koronyo Y, Salumbides BC, et al.: Angiotensin-converting enzyme overexpression in myelomonocytes prevents Alzheimer's-like cognitive decline. J Clin Invest. 2014; 124(3): 1000–1012. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRamakrishnan L: Revisiting the role of the granuloma in tuberculosis. Nat Rev Immunol. 2012; 12(5): 352–366. PubMed Abstract | Publisher Full Text\n\nStanton L, Fenhalls G, Lucas A, et al.: Immunophenotyping of macrophages in human pulmonary tuberculosis and sarcoidosis. Int J Exp Pathol. 2003; 84(6): 289–304. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nFuchs S, Xiao HD, Cole JM, et al.: Role of the N-terminal catalytic domain of angiotensin-converting enzyme investigated by targeted inactivation in mice. J Biol Chem. 2004; 279(16): 15946–15953. PubMed Abstract | Publisher Full Text\n\nFuchs S, Xiao HD, Hubert C, et al.: Angiotensin-converting enzyme C-terminal catalytic domain is the main site of angiotensin I cleavage in vivo. Hypertension. 2008; 51(2): 267–274. PubMed Abstract | Publisher Full Text\n\nOng FS, Lin CX, Campbell DJ, et al.: Increased angiotensin II-induced hypertension and inflammatory cytokines in mice lacking angiotensin-converting enzyme N domain activity. Hypertension. 2012; 59(2): 283–290. PubMed Abstract | Publisher Full Text | Free Full Text\n\nShen XZ, Li P, Weiss D, et al.: Mice with enhanced macrophage angiotensin-converting enzyme are resistant to melanoma. Am J Pathol. 2007; 170(6): 2122–2134. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHimes SR, Tagoh H, Goonetilleke N, et al.: A highly conserved c-fms gene intronic element controls macrophage-specific and regulated expression. J Leukoc Biol. 2001; 70(5): 812–820. PubMed Abstract | Faculty Opinions Recommendation\n\nSasmono RT, Oceandy D, Pollard JW, et al.: A macrophage colony-stimulating factor receptor-green fluorescent protein transgene is expressed throughout the mononuclear phagocyte system of the mouse. Blood. 2003; 101(3): 1155–1163. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nShen XZ, Okwan-Duodu D, Blackwell WL, et al.: Myeloid expression of angiotensin-converting enzyme facilitates myeloid maturation and inhibits the development of myeloid-derived suppressor cells. Lab Invest. 2014; 94(5): 536–544. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOkwan-Duodu D, Datta V, Shen XZ, et al.: Angiotensin-converting enzyme overexpression in mouse myelomonocytic cells augments resistance to Listeria and methicillin-resistant Staphylococcus aureus. J Biol Chem. 2010; 285(50): 39051–39060. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGonzalez-Villalobos RA, Shen XZ, Bernstein EA, et al.: Rediscovering ACE: novel insights into the many roles of the angiotensin-converting enzyme. J Mol Med (Berl). 2013; 91(10): 1143–1154. PubMed Abstract | Publisher Full Text | Free Full Text\n\nConstantinescu CS, Ventura E, Hilliard B, et al.: Effects of the angiotensin converting enzyme inhibitor captopril on experimental autoimmune encephalomyelitis. Immunopharmacol Immunotoxicol. 1995; 17(3): 471–491. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nPlatten M, Youssef S, Hur EM, et al.: Blocking angiotensin-converting enzyme induces potent regulatory T cells and modulates TH1- and TH17-mediated autoimmunity. Proc Natl Acad Sci U S A. 2009; 106(35): 14948–14953. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nStegbauer J, Lee DH, Seubert S, et al.: Role of the renin-angiotensin system in autoimmune inflammation of the central nervous system. Proc Natl Acad Sci U S A. 2009; 106(35): 14942–14947. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSteinman L: Development of therapies for autoimmune disease at Stanford: a tale of multiple shots and one goal. Immunol Res. 2014; 58(2–3): 307–314. PubMed Abstract | Publisher Full Text\n\nLühder F, Lee DH, Gold R, et al.: Small but powerful: short peptide hormones and their role in autoimmune inflammation. J Neuroimmunol. 2009; 217(1–2): 1–7. PubMed Abstract | Publisher Full Text\n\nDalbeth N, Edwards J, Fairchild S, et al.: The non-thiol angiotensin-converting enzyme inhibitor quinapril suppresses inflammatory arthritis. Rheumatology (Oxford, England). 2005; 44(1): 24–31. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nFahmy Wahba MG, Shehata Messiha BA, Abo-Saif AA: Ramipril and haloperidol as promising approaches in managing rheumatoid arthritis in rats. Eur J Pharmacol. 2015; 765: 307–315. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSagawa K, Nagatani K, Komagata Y, et al.: Angiotensin receptor blockers suppress antigen-specific T cell responses and ameliorate collagen-induced arthritis in mice. Arthritis Rheum. 2005; 52(6): 1920–1928. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKozlowski S, Corr M, Takeshita T, et al.: Serum angiotensin-1 converting enzyme activity processes a human immunodeficiency virus 1 gp160 peptide for presentation by major histocompatibility complex class I molecules. J Exp Med. 1992; 175(6): 1417–1422. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nNakagawa Y, Takeshita T, Berzofsky JA, et al.: Analysis of the mechanism for extracellular processing in the presentation of human immunodeficiency virus-1 envelope protein-derived peptide to epitope-specific cytotoxic T lymphocytes. Immunology. 2000; 101(1): 76–82. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nEisenlohr LC, Bacik I, Bennink JR, et al.: Expression of a membrane protease enhances presentation of endogenous antigens to MHC class I-restricted T lymphocytes. Cell. 1992; 71(6): 963–972. PubMed Abstract | Publisher Full Text\n\nShen XZ, Billet S, Lin C, et al.: The carboxypeptidase ACE shapes the MHC class I peptide repertoire. Nat Immunol. 2011; 12(11): 1078–1085. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "13040",
"date": "23 Mar 2016",
"name": "Paul Overbeek",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13041",
"date": "23 Mar 2016",
"name": "Markus Kalkum",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13042",
"date": "23 Mar 2016",
"name": "Ifor Williams",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-393
|
https://f1000research.com/articles/5-391/v1
|
23 Mar 16
|
{
"type": "Review",
"title": "Recent advances in the management of renal cell carcinoma",
"authors": [
"Ana M. Molina",
"David M. Nanus",
"David M. Nanus"
],
"abstract": "Therapeutic options for patients with metastatic renal cell carcinoma have significantly improved over the past few years with the recent approval of two new agents resulting in prolonged progression-free and overall survival.",
"keywords": [
"renal cell carcinoma",
"cancer",
"kidney",
"therapy",
"management"
],
"content": "Introduction\n\nIn 2016, there will be an estimated 62,700 new cases of kidney cancer and over 14,000 deaths1. Clear cell renal cell carcinoma (ccRCC) is the most common cancer of the kidney. The mainstay of treatment for many years was cytokine therapy with interferon alpha (IFN-α) and interleukin-2 (IL-2). Before the year 2000, high-dose IL-2 was the only approved treatment for patients with metastatic RCC (mRCC) based on objective response rates (ORRs) of 10% and 15% with complete and durable responses reported2–4. However, identification of the Von Hippel-Lindau (VHL) tumor-suppressor gene, and that its inactivation in ccRCC led to increased expression of hypoxia-inducible factor alpha (HIF-α) and angiogenesis-related proteins such as vascular endothelial growth factor (VEGF) and platelet-derived growth factor B chain (PDGF-B), led to the development of targeted therapies that specifically inhibit VEGF signaling pathways. Today, most patients with mRCC are treated with sunitinib, pazopanib, or bevacizumab as first-line therapy based on phase III randomized studies that have demonstrated significant improvement in progression-free survival (PFS) and/or overall survival5. Until recently, patients who progressed on first-line therapy subsequently received the mTOR inhibitor everolimus based on a 2008 randomized phase III study that demonstrated a median PFS of 4.9 months in patients receiving everolimus versus 1.9 months in patients on placebo6. A number of recent studies have changed this paradigm and expanded the therapeutic option for patients who have progressed on first-line anti-VEGF therapy. This review will summarize these data.\n\n\nFirst-line therapy for mRCC\n\nSunitinib was approved by the US Food and Drug Administration (FDA) in 2006 for the treatment of patients with mRCC and became a standard first-line therapy. Pazopanib, another multi-kinase inhibitor targeting VEGF receptor (VEGFR), PDGF receptor (PDGFR), and c-KIT, was approved by the FDA for the treatment of advanced RCC in 2009. The COMPARZ phase III study compared the efficacy and safety of pazopanib and sunitinib as first-line therapy7. In this trial, ORRs were 31% for pazopanib and 24% for sunitinib. Pazopanib was non-inferior to sunitinib with a median PFS of 8.4 months and 9.5 months, respectively. Overall survival was similar in the two groups.\n\nBevacizumab, a humanized VEGF-neutralizing antibody, was FDA approved in 2009 based on two multicenter phase III studies comparing bevacizumab plus IFN to IFN alone as first-line treatment in patients with mRCC8,9. Both studies demonstrated a significant improvement in PFS in patients receiving bevacizumab (10.2 versus 5.4 months and 8.5 versus 5.6 months) as well as an increase in the objective tumor response rate (30.6% versus 12.4% and 25.5% versus 13.1%). Based on these trials, sunitinib, pazopanib, and bevacizumab plus IFN are each considered an option for first-line therapy in patients with mRCC5.\n\n\nSecond-line therapy after anti-VEGF therapy for mRCC\n\nUntil 2012, everolimus was the only second-line therapy to demonstrate improvement in PFS after first-line anti-VEGF therapy. Axitinib, another VEGFR kinase inhibitor, was approved in 2012 for the treatment of mRCC following failure of a prior systemic therapy based on results from the Axitinib Versus Sorafenib (AXIS) trial, a global, randomized phase III trial comparing axitinib with sorafenib as second-line therapy in patients with treatment-refractory mRCC10. Median PFS was significantly longer in patients treated with axitinib versus sorafenib (6.7 versus 4.7 months). Importantly, this PFS benefit was significant in patients who had previously received treatment with cytokines (12.1 versus 6.5 months) or sunitinib (4.8 versus 3.4 months). Axitinib also led to a significantly higher ORR.\n\n\nEmerging new agents\n\nAlthough VEGF-targeted agents have significantly impacted patients with mRCC, most patients fail to achieve a complete response, long-term survival rates remain low, and most patients develop resistance. Consequently, the search for newer agents has continued. Cabozantinib is a small-molecule tyrosine kinase inhibitor (TKI) that targets VEGFR, as well as MET and AXL, each of which has been implicated in the development of resistance to anti-angiogenic drugs11. Cabozantinib first demonstrated anti-tumor activity in heavily pretreated RCC patients with a response rate of 28% and median PFS of 12.9 months12. A recent randomized phase III trial (METEOR) compared the efficacy of cabozantinib with that of everolimus in patients with RCC who had progressed after VEGFR-targeted therapy. In this trial, patients treated with cabozantinib demonstrated 21% ORR and a median PFS of 7.4 months, while patients treated with everolimus experienced a 5% ORR and a median PFS of 3.8 months11. PFS benefit was consistent in subgroup analyses independent of Memorial Sloan-Kettering Cancer Center (MSKCC) risk group and Eastern Cooperative Oncology Group (ECOG) status, organ involvement including bone and tumor burden, and extent of prior VEGFR-TKI and prior programmed cell death protein 1 (PD-1)/PD-L1 therapy13. The overall survival data at the time of the pre-specified interim analysis were immature. However, there was a strong trend toward longer survival in patients treated with cabozantinib. Common adverse events with cabozantinib included fatigue, diarrhea, nausea, decreased appetite, hypertension, and hand-foot syndrome11. Dose reductions occurred in 60% of patients who received cabozantinib and in 10% of those treated with everolimus.\n\nThe clinical development of immune checkpoint inhibitors has led investigators to revisit the role of immunotherapy in RCC. Nivolumab is a human monoclonal antibody that targets the co-inhibitory receptor PD-1, which is expressed on activated T cells14. Upregulation of PD-1 expression in tumor lymphocytes is associated with aggressive disease and poor prognosis in RCC15. Nivolumab first demonstrated anti-tumor activity and durable responses in 9 out of 33 patients (27%) with RCC16. Nivolumab resulted in objective responses in 20 to 22% of patients with mRCC and overall survival ranging from 18.2 to 25.5 months in a phase II dose-ranging trial17. Recently, a randomized phase III trial (CheckMate 025) compared nivolumab with everolimus in patients with RCC previously treated with one or two anti-angiogenic regimens18. In this trial, patients treated with nivolumab demonstrated a 25% ORR, median PFS of 4.6 months, and overall survival of 25 months, while patients treated with everolimus experienced a 5% ORR, a median PFS of 4.4 months, and overall survival of 19.6 months. Consistent with the benefit observed in the overall population of CheckMate 025, nivolumab demonstrated both an overall survival and an ORR benefit across key subgroups including risk groups, number and sites of metastases, and prior therapies19. Fatigue, nausea, and pruritus were the most common treatment-related adverse events in patients treated with nivolumab. Eight percent of patients discontinued treatment with nivolumab owing to treatment-related adverse events. Based on the positive results, the trial was stopped early and nivolumab was granted breakthrough therapy designation from the FDA for advanced RCC in 2015.\n\n\nThe changing paradigm for mRCC treatment\n\nThe introduction of targeted therapies for the treatment of mRCC has vastly changed the treatment landscape of this disease. Now, with the availability of seven approved targeted agents and two approved immunotherapy agents, clinicians must consider the best way to incorporate these therapies into the management of patients with mRCC. Clinicians are now faced with questions such as how many therapies can a patient receive and what is the optimal sequence of treatment? Results from recent phase III clinical trials have established the role of targeted agents in the management of advanced RCC in the first- and second-line settings. The survival benefit and favorable safety profile demonstrated in the CheckMate 025 phase III trial supports nivolumab as a new standard of care for patients with advanced RCC in the second-line setting. The response and PFS data on cabozantinib are striking. The survival data for cabozantinib, when mature and if positive, will provide a new treatment option for second-line therapy as well. In the short term, patient preference (oral versus intravenous administration) and cost will play a role in treatment decision making. Ongoing studies are investigating optimal sequential therapy and combination therapy with existing and novel targeted and immunotherapy agents. In addition, studies identifying prognostic factors, biomarkers, and mechanisms of resistance are underway.\n\n\nAbbreviations\n\nccRCC – Clear Cell Renal Cell Carcinoma\n\nIFN – Interferon\n\nIL – Interleukin\n\nmRCC – Metastatic Renal Cell Carcinoma\n\nORR – Objective Response Rate\n\nPDGFR – Platelet-Derived Growth Factor Receptor\n\nPD-1 – Programmed cell death protein 1\n\nPFS – Progression-Free Survival\n\nRCC – Renal Cell Carcinoma\n\nTKI – Tyrosine Kinase Inhibitor\n\nVEGF – Vascular Endothelial Growth Factor\n\nVEGFR – Vascular Endothelial Growth Factor Receptor",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing disclosures.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nSiegel RL, Miller KD, Jemal A: Cancer statistics, 2016. CA Cancer J Clin. 2016; 66(1): 7–30. PubMed Abstract | Publisher Full Text\n\nFyfe G, Fisher RI, Rosenberg SA, et al.: Results of treatment of 255 patients with metastatic renal cell carcinoma who received high-dose recombinant interleukin-2 therapy. J Clin Oncol. 1995; 13(3): 688–96. PubMed Abstract\n\nFisher RI, Rosenberg SA, Fyfe G: Long-term survival update for high-dose recombinant interleukin-2 in patients with renal cell carcinoma. Cancer J Sci Am. 2000; 6(Suppl 1): S55–7. PubMed Abstract\n\nMcDermott DF: Update on the application of interleukin-2 in the treatment of renal cell carcinoma. Clin Cancer Res. 2007; 13(2 Pt 2): 716s–720s. PubMed Abstract | Publisher Full Text\n\nLjungberg B, Bensalah K, Canfield S, et al.: EAU guidelines on renal cell carcinoma: 2014 update. Eur Urol. 2015; 67(5): 913–24. PubMed Abstract | Publisher Full Text\n\nMotzer RJ, Escudier B, Oudard S, et al.: Phase 3 trial of everolimus for metastatic renal cell carcinoma: Final results and analysis of prognostic factors. Cancer. 2010; 116(18): 4256–65. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMotzer RJ, Hutson TE, Cella D, et al.: Pazopanib versus sunitinib in metastatic renal-cell carcinoma. N Engl J Med. 2013; 369(8): 722–31. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nEscudier B, Pluzanska A, Koralewski P, et al.: Bevacizumab plus interferon alfa-2a for treatment of metastatic renal cell carcinoma: a randomised, double-blind phase III trial. Lancet. 2007; 370(9605): 2103–11. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nRini BI, Halabi S, Rosenberg JE, et al.: Phase III trial of bevacizumab plus interferon alfa versus interferon alfa monotherapy in patients with metastatic renal cell carcinoma: final results of CALGB 90206. J Clin Oncol. 2010; 28(13): 2137–43. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nRini BI, Escudier B, Tomczak P, et al.: Comparative effectiveness of axitinib versus sorafenib in advanced renal cell carcinoma (AXIS): a randomised phase 3 trial. Lancet. 2011; 378(9807): 1931–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nChoueiri TK, Escudier B, Powles T, et al.: Cabozantinib versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med. 2015; 373(19): 1814–23. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nChoueiri TK, Pal SK, McDermott DF, et al.: A phase I study of cabozantinib (XL184) in patients with renal cell cancer. Ann Oncol. 2014; 25(8): 1603–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nEscudier B, Motzer RJ, Powles T, et al.: Subgroup analyses of METEOR, a randomized phase 3 trial of cabozantinib versus everolimus in patients (pts) with advanced renal cell carcinoma (RCC). J Clin Oncol. 2016; 34(suppl 2S; abstr 499). Reference Source\n\nKline J, Gajewski TF: Clinical development of mAbs to block the PD1 pathway as an immunotherapy for cancer. Curr Opin Investig Drugs. 2010; 11(12): 1354–9. PubMed Abstract | F1000 Recommendation\n\nThompson RH, Dong H, Lohse CM, et al.: PD-1 is expressed by tumor-infiltrating immune cells and is associated with poor outcome for patients with renal cell carcinoma. Clin Cancer Res. 2007; 13(6): 1757–61. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nTopalian SL, Hodi FS, Brahmer JR, et al.: Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012; 366(26): 2443–54. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nMotzer RJ, Rini BI, McDermott DF, et al.: Nivolumab for Metastatic Renal Cell Carcinoma: Results of a Randomized Phase II Trial. J Clin Oncol. 2015; 33(13): 1430–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMotzer RJ, Escudier B, McDermott DF, et al.: Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med. 2015; 373(19): 1803–13. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMotzer RJ, Sharma P, McDermott DF, et al.: CheckMate 025 phase III trial: Outcomes by key baseline factors and prior therapy for nivolumab (NIVO) versus everolimus (EVE) in advanced renal cell carcinoma (RCC). J Clin Oncol. 2016; 34(suppl 2S; abstr 498). Reference Source"
}
|
[
{
"id": "13036",
"date": "23 Mar 2016",
"name": "Toni Choueiri",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13037",
"date": "23 Mar 2016",
"name": "Eric Jonasch",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12890",
"date": "23 Mar 2016",
"name": "Giuseppe Procopio",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-391
|
https://f1000research.com/articles/5-389/v1
|
23 Mar 16
|
{
"type": "Review",
"title": "The importance of understanding individual differences in Down syndrome",
"authors": [
"Annette Karmiloff-Smith",
"Tamara Al-Janabi",
"Hana D'Souza",
"Jurgen Groet",
"Esha Massand",
"Kin Mok",
"Carla Startin",
"Elizabeth Fisher",
"John Hardy",
"Dean Nizetic",
"Victor Tybulewicz",
"Andre Strydom",
"Tamara Al-Janabi",
"Hana D'Souza",
"Jurgen Groet",
"Esha Massand",
"Kin Mok",
"Carla Startin",
"Elizabeth Fisher",
"John Hardy",
"Dean Nizetic",
"Victor Tybulewicz",
"Andre Strydom"
],
"abstract": "In this article, we first present a summary of the general assumptions about Down syndrome (DS) still to be found in the literature. We go on to show how new research has modified these assumptions, pointing to a wide range of individual differences at every level of description. We argue that, in the context of significant increases in DS life expectancy, a focus on individual differences in trisomy 21 at all levels—genetic, cellular, neural, cognitive, behavioral, and environmental—constitutes one of the best approaches for understanding genotype/phenotype relations in DS and for exploring risk and protective factors for Alzheimer’s disease in this high-risk population.",
"keywords": [
"Down syndrome",
"Alzheimer’s disease",
"neurodevelopmental disorder",
"trisomy 21"
],
"content": "Introduction\n\nDown syndrome (DS) is the most common neurodevelopmental disorder of known genetic cause, with an incidence of between 1:750 and 1:1000 live births1,2. The syndrome has been extensively described at the group level, downplaying individual variation and treating DS as a homogeneous group. So, why do we argue in this paper that individual differences across DS at all levels—genetic, cellular, neural, cognitive, behavioral, and environmental— really matter? Our argument is that, in the context of significant increases in DS life expectancy3,4, a focus on individual differences in trisomy 21 constitutes one of the best approaches for exploring genotype/phenotype relations in DS and for identifying risk and protective factors for Alzheimer’s disease (AD).\n\nDS has usually been described simply as arising from an extra copy of chromosome 21 and presenting with characteristic features including facial dysmorphology, a proportionally large tongue, low muscle tone, short stature, and intellectual disability. Associated conditions may include obstructive sleep apnea, as well as visual and hearing problems. Receptive language usually outstrips language production, spatial memory is thought to be better than verbal memory, and global processing is deemed to be superior to local processing. In adulthood, DS presents with accelerated aging and an increased likelihood of developing AD. The DS brain has been typically described as developing relatively normally during the first few months postnatally5, after which growth slows, with cortical areas being particularly reduced6.\n\nYet underlying these group-level accounts are large individual differences at every level of description. We start with a consideration of individual differences in the genetics of DS and go on to examine studies of DS cell biology. We focus next on the broad individual differences in the DS brain, which recent studies have now identified as occurring as early as during fetal development. We go on to explore briefly some of the widespread individual differences in cognitive outcomes in DS, particularly with respect to language and memory, and challenge assumptions that individuals with DS are global rather than local processors7. In the following section, we argue that individual differences in sleep patterns in DS are likely to be an important contributor to the differences in language, memory, and AD outcome. We then look briefly at mouse models of DS and AD. We finally conclude that a focus on individual differences at every level across the syndrome is likely to yield deeper insights into genotype/phenotype associations.\n\n\nIndividual differences in Down syndrome genetics\n\nThe most common cause of DS is the additional copy of an entire chromosome 21. In ~88% of cases, the extra copy is maternally derived, through an error in cell division called non-disjunction. The extra chromosomal content can occur through different mechanisms and at different points during the formation of germ cells. Non-disjunction8 can arise during meiosis I (~65% maternal; ~3% paternal), during meiosis II (~23% maternal; ~5% paternal), or from a mitotic error (~3%). DS can also occur when only a segment of chromosome 21 has three copies (partial trisomy)9 or when the whole chromosome is triplicated but only a proportion of the cells are trisomic (mosaicism) with other cells being normal. Mosaicism is found in ~1.3–5% of cases10, but it is possible that mosaicism occurs more frequently, the low percentage being due to ascertainment bias, especially in cases with low-level mosaicism. Further genetic differences can be introduced by variation in the amount of crossover during meiosis I. Research on parental origin or the mechanism of mosaicism is currently sparse, making it difficult to identify the main mechanism. While mosaicism has sometimes been claimed to yield a milder cognitive phenotype9,11, data addressing this are very sparse and, where they do exist, the degree of mosaicism does not correlate with phenotypic severity. Interestingly, though, mosaicism provides an excellent opportunity to study phenotypic differences, since disomic and trisomic cell lines derived from mosaics only differ in the extra chromosome 2112.\n\nTranslocation is another mechanism yielding DS, whereby some of the genetic material from chromosome 21, usually from the long arm, is moved to chromosome 14 or 22, or from the long to the short arm of chromosome 21. Translocation occurs in some ~4% of cases2,13–15.\n\nThese multiple origins of DS need to be taken into account when considering differences between individuals with trisomy 21. Additionally, individual differences exist on other chromosomes. The euploid population, while free from gross chromosomal abnormalities, is nonetheless genetically different from one another, due to copy number variations (CNVs), single nucleotide polymorphisms (SNPs), and de novo mutations. Such differences also apply to people with DS, of course, who have many of these variants in addition to their extra copy of all or part of chromosome 21.\n\nWith full trisomy, intuitively it might be assumed that expression levels of triplicated genes are 1.5-fold that of the euploid population. However, this is not so. Gene expression is differentially regulated in different tissues, and each gene is subject to the potential of feedback control of expression levels. One recent study of whole genome expression in fibroblasts and lymphoblasts suggested that only a small majority of genes were over-expressed in the range predicted by gene dosage. In contrast, about a quarter showed no difference in expression between DS and diploid cells, and another quarter had intermediate expression16. In a second study, also in lymphoblastoid cells, only 22% of the genes analyzed on chromosome 21 were actually over-expressed 1.5-fold17. In this second study, a few were significantly more amplified (~7%), whereas, despite the three copies, many (>1/2) turned out to have near normal levels of expression, presumably due to compensatory mechanisms. It must be remembered that these studies were carried out in cell lines; the results may therefore not reflect the gene expression profiles of the cells from which they were derived and certainly will not represent the expression levels in other tissues. Interestingly, both of these cell studies additionally reported a considerable amount of inter-individual differences in gene expression. Expression studies are notoriously inconsistent. Nonetheless, however tentative the findings of the above two studies, it is clear that we cannot take for granted that an extra copy of chromosome 21 will result in a 1.5-fold increase in the level of gene expression. How irregular expression levels of triplicated genes on chromosome 21 (particularly those that may vary substantially between trisomic individuals), coupled with the heterogeneous origins, influence the DS neurocognitive phenotype remains an open but critical question.\n\nWhilst the expression and role of individual genes are undoubtedly important, the genome-wide implications of trisomy 21 are too often neglected. Functionally, genes sit in a complex biological network. The breadth of influence of genes varies, but those involved in epigenetic mechanisms warrant special attention. Epigenetic mechanisms, including DNA methylation and post-translational histone modifications, contribute substantially to the regulation of gene expression across the genome, and so the effects of changes in epigenetic gene dosage are far-reaching. There are at least 11 genes and multiple microRNAs (miRNAs) on chromosome 21 that are involved in epigenetic mechanisms18, including DNMT3L (a DNA methyltransferase), DYRK1A (a kinase), and H2AFZP (a histone variant). Relatively little research has gone into epigenetic processes in trisomy 21, although some studies indicate that people with DS have different DNA methylation from the euploid population19. As mentioned above, in some of these genes, expression levels may vary between individuals (such as BRWD1, a transcriptional regulator). Trisomy 21 causes major disturbances in the level, activity, and subcellular localization of two major non-HSA21 transcription factors: NFAT20 and NRSF/REST21,22. Both of these control the spatiotemporal expression patterns of thousands of downstream target genes, many of which are also transcription factors, generating a whole new layer of complexity. Individual differences in epigenetic regulation can of course also occur on genes not otherwise involved with chromosome 21, yielding potentially even wider individual differences in the mosaic DS population and those with DS arising from translocation.\n\nOne of the reasons why individuals with DS are at higher risk for AD than the general population is that the amyloid precursor protein (APP) gene, implicated in the brain pathology of AD, lies on chromosome 21. Individuals with a translocation below the APP gene (i.e. without APP triplication) get DS but not AD. A number of genes that are functionally linked to APP are dysregulated in the DS brain, including BACE2, APOE, CLU, PSEN1, PSEN2, and MAPT22. While amyloid pathology is necessary, triplication of APP alone is not sufficient to cause AD. Whereas many people with DS present with dementia in their 30s, even by age 70 or 80 some adults with DS do not have dementia despite their significant plaque pathology24,25.\n\nGenes on other chromosomes also play an important role in AD and here, too, individual differences exist. The apolipoprotein gene (APOE) on chromosome 19, also implicated in AD, harbors common variants: ε2, considered protective for AD (~7% of the general population); ε3, the most common allele (~79% frequency), neutral regarding AD risk; and ε4 (~14% frequency), thought to harbor the greatest risk for AD, particularly in carriers of two ε4 alleles. APOE variants modulate the age of onset of AD in DS26. Interestingly, the distribution of the APOE polymorphisms differs across ethnicities, the above figures holding for Caucasians.\n\nThe effects of these APOE allelic differences are detectable early in life. A recent study of euploid babies between 2 and 25 months of age showed that those who carried the ε4 variant differed from non-carriers in their rate of myelin development, with ε4 carriers showing decreased growth in the mid and posterior brain regions27. Similar allelic differences and their neural repercussions are likely also to occur in children with DS, impacting on other individual differences.\n\nOther genes, e.g. DYRK1A and RCAN1, located on chromosome 21, have been shown to be functionally important in the pathogenesis of DS and AD when expression is increased28,29. Individual ethnic differences also matter. Indeed, the common variants of these genes are not significantly associated with AD in Caucasians, but there is some suggestion of an association of the RCAN1 polymorphism in a small Chinese cohort30. Other research has suggested that BACE2 alleles, also located on chromosome 21, are important in AD, also affecting the age of dementia onset in DS31,32.\n\n\nIndividual differences in Down syndrome cell biology\n\nThe advent of human induced pluripotent stem cells (iPSCs) has added an exciting new tool for understanding individual differences in DS and their relationship to AD12,33. Shi et al.33 found that cortical neurons generated from iPSCs and embryonic stem cells from patients with DS developed AD pathologies in the form of insoluble intracellular and extracellular amyloid aggregates over months in culture, rather than years in vivo. Hyperphosphorylated tau protein, a hallmark of AD, was also localized to cell bodies and dendrites in iPS-derived cortical neurons from the patients with DS, recapitulating later stages of the AD pathogenic process. Interestingly, the same research group showed growth of amyloid-β plaques in iPSCs grown from tissue from a DS infant as young as 17 months33, attesting to the developmental nature of the brain pathology. Furthermore, an isogenic iPSC model of DS derived from a 16 year old with mosaic DS12 recapitulated these AD-related phenotypes and demonstrated that neurons from trisomy 21 iPSCs accumulate DNA double-strand breaks much faster than those from isogenic euploid controls. It is currently not known whether, but it is assumed that, such accumulated DNA damage is randomly distributed in the genome and as such may increase the variability of pathological phenotypes on the cellular level12.\n\n\nIndividual differences in Down syndrome brains\n\nAs mentioned, it used to be thought that the DS brain developed relatively normally throughout fetal life and during the first months postnatally5. This assumption has turned out to be incorrect. New studies reveal that DS prenatal brain size is only relatively normal until about 20–24 weeks gestation, after which individual differences in fetal brain development emerge (unpublished data, Rutherford & Patkee 2015). Some DS brains show reduced volume of the hippocampus, cerebellum, and occipital-frontal areas already during fetal life. In some DS brains, there is initially more or less normal dendritic formation and arborization, but this is followed by a stagnation in the developmental process; subsequently dendrites increase neither in number nor in complexity as the DS fetus develops34. At birth, many DS brains already have smaller dendritic arborization35–37 and fewer synapses38,39, likely to contribute to the reduced functional brain connectivity found in many newborns with DS40.\n\nDespite large individual differences, some DS brains are difficult to distinguish from the neurotypical case during fetal development (unpublished data, Rutherford & Patkee 2015), but the neural phenotype becomes progressively more pronounced in DS as development proceeds, with increasing dissociations between cortical thickness (increased) and surface area (reduced) in, for example, frontal and temporal regions41. However, yet again, individual differences are apparent, particularly in the early stages of development. In other words, individual differences at both the structural and the functional levels can start very early in the DS developmental trajectory, subsequently yielding large individual differences in functional connectivity, which correlate, for instance, with communication skills42. Finally, 40% of infants with DS are born with congenital heart disease, which also potentially compromises blood flow to the brain, but even those without heart problems ultimately go on to develop atypical brains43.\n\nExamining the brains of adults with DS, MRI studies have demonstrated that the size of the cerebellum, hippocampus, and cortex is significantly smaller than in the neurotypical case, while basal ganglia are similar in size and ventricles are enlarged44. Individual differences are particularly apparent when comparing DS adults with or without dementia; the former have reduced ventricular, hippocampal, and caudate volumes, as well as increased levels of peripheral cerebrospinal fluid (CSF), compared to those without dementia45. The differences between those with and without dementia can start very early. In vivo studies of children with DS identified plaques in DS brains as early as 8 years of age46. To be noted, however, were the large individual differences, with some DS brains having no plaques until early adulthood.\n\n\nIndividual differences in Down syndrome cognition\n\nAtypical cognitive phenotypes in DS become increasingly evident across the lifespan47. Children under 12 months old often show few cognitive differences from neurotypical controls on standardized tests (due, perhaps, to a lack of sensitivity to detect them) but, as they get older, the rate of intellectual development in DS slows considerably.\n\nMost of the cognitive studies of DS have reported group data, comparing DS either to neurotypical controls48–50 or to other neurodevelopmental disorders51–56. Yet hidden within these group data are wide individual differences, particularly in IQ scores, language, and other measures57–61. And these differences start early; in our recent research on infants/toddlers with DS, standard composite scores (not dissimilar to IQ scores) on the Mullen Scales of Early Learning62 show significant variation, with many young children scoring at floor, while some others’ scores reach the 80s to 90s. In adults with DS, some 50% have IQs at floor, whereas a few have IQs in the 70s or above63. The significance of these individual differences is being increasingly recognized, such that we are developing new task batteries to detect the wide range of scores more precisely64,65.\n\nIndividual differences in basic-level processes like reaction time, attention, and memory impact on developmental trajectories over time. For example, the DS memory profile is associated with poor short-term verbal memory66 and poor long-term visual memory54. In contrast, implicit memory is thought to be comparable to age-matched neurotypicals49. However, again these observations are based on group data, with individual memory profiles being significantly more variable67. In Vicari et al.’s49 paper, implicit memory—measured by reaction time—was on average longer in DS than in neurotypicals, but the standard deviations were almost three times larger in the DS group. This might mean that some individuals with DS had shorter reaction times even than the controls. Such individual differences are camouflaged when reporting average group data yet are critical to fully understand the DS phenotype.\n\nAs mentioned in the introduction, DS is often described as having better visuospatial memory than verbal memory, as well as better global processing than local processing. First, individual differences are large, and, second, in-depth probing of processing across modalities (visual/auditory) and across levels of processing (low-level perceptual processes vs. high-level) yielded no consistent global processing style7.\n\nAnother domain that yields wide individual differences in DS is language—for some, considered the domain of greatest vulnerability in the syndrome59,68. This claim is made from comparisons of children with DS to neurotypicals at the group level. A very different picture emerges when individual differences are taken into consideration. For example, Zampini and D’Odorico69 reported that, in their longitudinal study of DS vocabulary acquisition, at 36 months the lowest scoring child was nonverbal, while the highest scoring child was close to the normal range, producing 243 words. When the same children were assessed 6 months later, the nonverbal child remained nonverbal, whereas the one with the most developed language had doubled production to nearly 500 words. This highlights the wide individual differences in DS language development, which persists into adulthood70.\n\nHowever, in order to fully understand how those with DS develop, it is crucial to study how individual differences in underlying processes (e.g., auditory/visual attention, motor control) constrain higher-level cognitive outcomes (e.g. language). For example, there is much greater variability in the timing of the onset of muscle activation in DS than in neurotypicals71,72, such that distal muscles are often activated before proximal muscles. It is possible, then, that the variability in underlying mechanisms, such as muscle activation, becomes subsequently measurable as differences in DS cognitive abilities.\n\nAnother example from our recent work on very young children with DS reveals that individual differences in an electrophysiological measure of auditory attention in toddlers with DS are associated with differences in language ability73. On average, the toddlers with DS oriented to changes in pitch more than changes in speech, but wide individual differences emerged: toddlers with DS who oriented more to changes in pitch had worse expressive language, suggesting that those who rely excessively on global properties of sounds (e.g., tone, changes in pitch) are not using an optimal strategy for language learning. As a group, the toddlers were also slow at disengaging attention from visual stimuli, but again individual differences indicated that those who were particularly poor at disengaging visual attention had worse language ability.\n\nThus, individual differences in both visual and auditory attention predict language differences in the DS children, indicating that small differences in attention during very early development impact the subsequent development of other higher-level domains like language74.\n\n\nIndividual differences in Down syndrome sleep\n\nSleep has a crucial function in ensuring metabolic homeostasis and the clearance of toxins like β-amyloid from the brain. Using real-time assessments of tetramethylammonium diffusion and two-photon imaging in live mice, Xie and colleagues75 showed that deep sleep is associated with a 60% increase in the interstitial space, resulting in a striking increase in convective exchange of CSF with interstitial fluid. The researchers showed that convective fluxes of interstitial fluid increase the rate of β-amyloid clearance during sleep. The restorative function of sleep may thus be a consequence of the enhanced removal of potentially neurotoxic waste products that accumulate in the central nervous system when awake. Therefore, if individuals with DS show differences in their sleep architecture, such β-amyloid clearance may be differentially compromised.\n\nIndeed, there is an increased risk of sleep fragmentation in DS because of obstructive sleep apnea in this population76–79. Edgin and collaborators found that children with DS with obstructive sleep apnea syndrome had impaired executive function as well as verbal IQs nine points lower than those without apnea79. Even in the euploid population, poor sleep quality, particularly sleep fragmentation, is a strong predictor of lower academic performance80, reduced attentional capacities81, poor executive function82, and challenging behaviors83. As far as young adults with DS are concerned, our ongoing work suggests that 16–35 year olds with disturbed sleep have poorer cognitive scores, lower adaptive behavior scores, and poorer verbal fluency65. Again, individual differences in sleep patterns start early. Our current work with infants and toddlers with DS is revealing correlations between increased sleep fragmentation (not duration) and decreased memory, language, and attention shifts84. If amyloid clearance is subject to wide individual differences in DS due to varying levels of sleep fragmentation, this may be a clue to one of the reasons why some individuals go on to present with dementia and others do not. It is therefore possible that individual differences in sleep patterns in the DS population across the lifespan, together with other factors, impact on risk and protective factors for AD.\n\n\nIndividual differences in Down syndrome animal models\n\nMurine models of DS and of AD-DS exist, based on ortholog genes to human chromosome 21, which are located on chromosomes 10, 16, and 17 in the mouse85,86. Most are kept on inbred, identical genetic backgrounds and are used to identify genes associated with neurobehavioral traits. Although rarely reported, it is clear that, even in inbred strains, phenotypic variability occurs in terms of rate of development, disease, and behavioral traits. Using prenatal and postnatal cross-fostering methods, several studies have shown that these individual differences stem from environmental factors, such as amount of maternal licking/grooming, i.e. epigenetic programming by maternal behavior87, rather than genetic differences between offspring88–90. It is becoming increasingly likely that individual epigenetic changes arising from experience of a parent can be transmitted to their offspring and to future generations91. Variations in rat maternal care have been shown to affect hippocampal function as well as performance on hippocampal-dependent learning and memory tests in the offspring88. There is every reason to believe that mouse models of DS would reveal similar effects (see discussion in 86). For instance, transgenic mice overexpressing Dyrk1A, a candidate gene on chromosome 21, show serious alterations in adult neurogenesis, including reduced cell proliferation rate, altered cell cycle progression, and reduced cell cycle exit, leading to premature migration, differentiation, and reduced survival of newly born cells. In addition, less proportion of newborn hippocampal TgDyrk1A neurons are activated upon learning, suggesting reduced integration in learning circuits. A number of these alterations can be normalized both pharmacologically and by environmental stimulation92.\n\n\nConcluding thoughts\n\nThe fact that DS presents with so many individual differences, at so many levels, clearly indicates that thinking of DS merely in terms of an extra copy of chromosome 21 would be simplistic. Many other genetic, epigenetic, and environmental factors play a role in how the DS phenotype expresses itself in each individual. Whereas mosaicism has sometimes been claimed to yield a milder cognitive phenotype, albeit with few data to support the claim, it remains unknown whether genetic differences in the original, individual causes of DS lead to corresponding differences in neurocognitive outcomes. Numerous other interacting factors are likely to contribute to individual differences and cognitive-level outcomes in DS, including early neural development, sleep, attention, memory, and the environment.\n\nIt is also important to note that having a neurodevelopmental disorder like DS actually changes the environment (both social and physical) in which infants and children develop, in terms of parental expectations and their interactions with their child61,93. A more complex, dynamic view is thus required of how individual differences in the child’s social, cultural, and physical environments interact with individual differences in genetics and epigenetics.\n\nOne thing is clear: scientists cannot consider those with DS as a homogeneous group. Consideration of individual variation at multiple levels opens a series of new questions raised in this review that remained hidden in studies at the DS group level. Thus, scientists must take on board the crucial importance of individual differences if we are to understand fully the relationships between genotype and the emerging phenotype, and why some individuals with DS do not go on to present with dementia despite their brain histopathology. Moreover, it is becoming increasingly clear that Alzheimer’s dementia is a developmental disease74 and that trisomy 21 is a particularly good model for understanding many of the complexities of that developmental process across the lifespan.\n\n\nAbbreviations\n\nAD Alzheimer’s disease\n\nAPOE Apolipoprotein\n\nAPP Amyloid precursor protein\n\nCSF Cerebrospinal fluid\n\nDS Down syndrome\n\niPSCs Induced pluripotent stem cells",
"appendix": "Competing interests\n\n\n\nAll the authors declare that the writing of this paper took place in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\n\n\nGrant information\n\nAll the authors of this paper are funded by Wellcome Trust Strategic Grant No. 098330/Z/12/Z conferred upon The LonDownS Consortium UK. Dean Nizetic is funded also by the Lee Kong Chian School of Medicine, Nanyang Technological University-Singapore Start-up Grant.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nParker SE, Mai CT, Canfield MA, et al.: Updated National Birth Prevalence estimates for selected birth defects in the United States, 2004–2006. Birth Defects Res A Clin Mol Teratol. 2010; 88(12): 1008–1016. 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East Asian Arch Psychiatry. 2011; 21(2): 79–84. PubMed Abstract | F1000 Recommendation\n\nMyllykangas L, Wavrant-De Vrièze F, Polvikoski T, et al.: Chromosome 21 BACE2 haplotype associates with Alzheimer's disease: a two-stage study. J Neurol Sci. 2005; 236(1–2): 17–24. PubMed Abstract | Publisher Full Text\n\nMok KY, Jones EL, Hanney M, et al.: Polymorphisms in BACE2 may affect the age of onset Alzheimer's dementia in Down syndrome. Neurobiol Aging. 2014; 35(6): 1513.e1–5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nShi Y, Kirwan P, Smith J, et al.: A human stem cell model of early Alzheimer's disease pathology in Down syndrome. Sci Transl Med. 2012; 4(124): 124ra29. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nMrak RE, Griffin WS: Trisomy 21 and the brain. J Neuropathol Exp Neurol. 2004; 63(7): 679–685. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBecker LE, Armstrong DL, Chan F: Dendritic atrophy in children with Down's syndrome. Ann Neurol. 1986; 20(4): 520–526. PubMed Abstract | Publisher Full Text\n\nBenavides-Piccione R, Ballesteros-Yáñez I, de Lagrán MM, et al.: On dendrites in Down syndrome and DS murine models: a spiny way to learn. Prog Neurobiol. 2004; 74(2): 111–126. PubMed Abstract | Publisher Full Text\n\nTakashima S, Ieshima A, Nakamura H, et al.: Dendrites, dementia and the Down syndrome. Brain Dev. 1989; 11(2): 131–133. PubMed Abstract | Publisher Full Text\n\nPetit TL, LeBoutillier JC, Alfano DP, et al.: Synaptic development in the human fetus: a morphometric analysis of normal and Down's syndrome neocortex. Exp Neurol. 1984; 83(1): 13–23. PubMed Abstract | Publisher Full Text\n\nWeitzdoerfer R, Dierssen M, Fountoulakis M, et al.: Fetal life in Down syndrome starts with normal neuronal density but impaired dendritic spines and synaptosomal structure. J Neural Transm Suppl. 2001; (61): 59–70. PubMed Abstract | Publisher Full Text\n\nImai M, Watanabe H, Yasui K, et al.: Functional connectivity of the cortex of term and preterm infants and infants with Down's syndrome. Neuroimage. 2014; 85(Pt 1): 272–278. PubMed Abstract | Publisher Full Text\n\nLee NR, Adeyemi EI, Lin A, et al.: Dissociations in Cortical Morphometry in Youth with Down Syndrome: Evidence for Reduced Surface Area but Increased Thickness. Cereb Cortex. 2015. pii: bhv107. PubMed Abstract | Publisher Full Text\n\nPujol J, del Hoyo L, Blanco-Hinojo L, et al.: Anomalous brain functional connectivity contributing to poor adaptive behavior in Down syndrome. Cortex. 2015; 64: 148–156. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nDay JJ, Sweatt JD: Cognitive neuroepigenetics: a role for epigenetic mechanisms in learning and memory. Neurobiol Learn Mem. 2011; 96(1): 2–12. PubMed Abstract | Publisher Full Text | Free Full Text\n\nStrydom A, Hassiotis A, Walker Z: Magnetic resonance imaging in people with Down's syndrome and Alzheimer's disease. J Intellect Disabil Res. 2004; 48(Pt 8): 769–770. PubMed Abstract | Publisher Full Text\n\nBeacher F, Daly E, Simmons A, et al.: Alzheimer's disease and Down's syndrome: an in vivo MRI study. Psychol Med. 2009; 39(4): 675–684. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLeverenz JB, Raskind MA: Early amyloid deposition in the medial temporal lobe of young Down syndrome patients: a regional quantitative analysis. Exp Neurol. 1998; 150(2): 296–304. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nChapman RS, Hesketh LJ: Behavioral phenotype of individuals with Down syndrome. Ment Retard Dev Disabil Res Rev. 2000; 6(2): 84–95. PubMed Abstract | Publisher Full Text\n\nRaitano Lee N, Pennington BF, Keenan JM: Verbal short-term memory deficits in Down syndrome: phonological, semantic, or both? J Neurodev Disord. 2010; 2(1): 9–25. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVicari S, Bellucci S, Carlesimo GA: Implicit and explicit memory: a functional dissociation in persons with Down syndrome. Neuropsychologia. 2000; 38(3): 240–251. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nWright I, Lewis V, Collis GM: Imitation and representational development in young children with Down syndrome. Br J Dev Psychol. 2006; 24(2): 429–450. Publisher Full Text\n\nAnnaz D, Karmiloff-Smith A, Johnson MH, et al.: A cross-syndrome study of the development of holistic face recognition in children with autism, Down syndrome, and Williams syndrome. J Exp Child Psychol. 2009; 102(4): 456–486. PubMed Abstract | Publisher Full Text\n\nBrown JH, Johnson MH, Paterson SJ, et al.: Spatial representation and attention in toddlers with Williams syndrome and Down syndrome. Neuropsychologia. 2003; 41(8): 1037–1046. PubMed Abstract | Publisher Full Text\n\nDimitriou D, Leonard HC, Karmiloff-Smith A, et al.: Atypical development of configural face recognition in children with autism, Down syndrome and Williams syndrome. J Intellect Disabil Res. 2015; 59(5): 422–438. PubMed Abstract | Publisher Full Text\n\nJarrold C, Baddeley AD, Phillips C: Long-term memory for verbal and visual information in Down syndrome and Williams syndrome: performance on the Doors and People test. Cortex. 2007; 43(2): 233–247. PubMed Abstract | Publisher Full Text\n\nKarmiloff-Smith A, D'Souza D, Dekker TM, et al.: Genetic and environmental vulnerabilities in children with neurodevelopmental disorders. Proc Natl Acad Sci U S A. 2012; 109(Suppl 2): 17261–17265. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKarmiloff-Smith A, Brown JH, Grice S, et al.: Dethroning the myth: cognitive dissociations and innate modularity in Williams syndrome. Dev Neuropsychol. 2003; 23(1–2): 227–242. PubMed Abstract | Publisher Full Text\n\nPennington BF, Moon J, Edgin J, et al.: The neuropsychology of Down syndrome: evidence for hippocampal dysfunction. Child Dev. 2003; 74(1): 75–93. PubMed Abstract | Publisher Full Text\n\nAnn L, Brahm N: Special Teaching For Special Children? A Pedagogies for Inclusion. McGraw-Hill Education (UK), 2005. Reference Source\n\nAbbeduto L, Warren SF, Conners FA: Language development in Down syndrome: from the prelinguistic period to the acquisition of literacy. Ment Retard Dev Disabil Res Rev. 2007; 13(3): 247–261. PubMed Abstract | Publisher Full Text\n\nChapman RS: In (ed. Retardation, B.-I. R. of R. in M.). Academic Press, 2003; 27: 1–34.\n\nCebula KR, Moore DG, Wishart JG: Social cognition in children with Down's syndrome: challenges to research and theory building. J Intellect Disabil Res. 2010; 54(2): 113–134. PubMed Abstract | Publisher Full Text\n\nMullen EM: Mullen scales of early learning. American Guidance Service, 1995.\n\nGlenn S, Cunningham C: Performance of young people with Down syndrome on the Leiter-R and British picture vocabulary scales. J Intellect Disabil Res. 2005; 49(Pt 4): 239–244. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nStartin C, Rodger E, Fodor-Wynne L, et al.: The Cognitive Scale for Down Syndrome (CSDS). Submitted.\n\nStartin C, Hamburg S, Hithersay R, et al.: The London Down Syndrome Consortium (LonDownS): protocol for cognitive assessments. Prep.\n\nJarrold C, Baddeley AD, Phillips CE: Verbal short-term memory in Down syndrome: a problem of memory, audition, or speech? J Speech Lang Hear Res. 2002; 45(3): 531–544. PubMed Abstract | Publisher Full Text\n\nEdgin JO, Pennington BF, Mervis CB: Neuropsychological components of intellectual disability: the contributions of immediate, working, and associative memory. J Intellect Disabil Res. 2010; 54(5): 406–417. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFidler DJ, Philofsky A, Hepburn SL, et al.: Nonverbal requesting and problem-solving by toddlers with Down syndrome. Am J Ment Retard. 2005; 110(4): 312–322. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZampini L, D'Odorico L: Communicative gestures and vocabulary development in 36-month-old children with Down's syndrome. Int J Lang Commun Disord. 2009; 44(6): 1063–1073. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nNelson LD, Orme D, Osann K, et al.: Neurological changes and emotional functioning in adults with Down Syndrome. J Intellect Disabil Res. 2001; 45(Pt 5): 450–456. PubMed Abstract | Publisher Full Text\n\nAlmeida GL, Corcos DM, Hasan Z: Horizontal-plane arm movements with direction reversals performed by normal individuals and individuals with Down syndrome. J Neurophysiol. 2000; 84(4): 1949–1960. PubMed Abstract\n\nHinnell C, Virji-Babul N: Mental rotation abilities in individuals with Down syndrome--a pilot study. Downs Syndr Res Pract. 2004; 9(1): 12–16. PubMed Abstract\n\nD'Souza D, D'Souza H, Johnson MH, et al.: Are early neurophysiological markers of ASD syndrome-specific? A cross-syndrome comparison. Paper presented at the XIX Biennial International Conference on Infant Studies, International Society on Infant Studies, Berlin, Germany. 2014.\n\nKarmiloff-Smith A: Development itself is the key to understanding developmental disorders. Trends Cogn Sci. 1998; 2(10): 389–398. PubMed Abstract | Publisher Full Text\n\nXie L, Kang H, Xu Q, et al.: Sleep drives metabolite clearance from the adult brain. Science. 2013; 342(6156): 373–377. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nDiomedi M, Placidi F, Cupini LM, et al.: Cerebral hemodynamic changes in sleep apnea syndrome and effect of continuous positive airway pressure treatment. Neurology. 1998; 51(4): 1051–1056. PubMed Abstract | Publisher Full Text\n\nDykens EM, Hodapp RM, Evans DW: Profiles and development of adaptive behavior in children with Down syndrome. Am J Ment Retard. 1994; 98(5): 580–587. PubMed Abstract\n\nBreslin JH, Edgin JO, Bootzin RR, et al.: Parental report of sleep problems in Down syndrome. J Intellect Disabil Res. 2011; 55(11): 1086–1091. PubMed Abstract | Publisher Full Text\n\nEdgin JO, Tooley U, Demara B, et al.: Sleep Disturbance and Expressive Language Development in Preschool-Age Children With Down Syndrome. Child Dev. 2015; 86(6): 1984–1998. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nFredriksen K, Rhodes J, Reddy R, et al.: Sleepless in Chicago: tracking the effects of adolescent sleep loss during the middle school years. Child Dev. 2004; 75(1): 84–95. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAshworth A, Hill CM, Karmiloff-Smith A, et al.: Cross syndrome comparison of sleep problems in children with Down syndrome and Williams syndrome. Res Dev Disabil. 2013; 34(5): 1572–1580. PubMed Abstract | Publisher Full Text\n\nArchbold KH, Giordani B, Ruzicka DL, et al.: Cognitive executive dysfunction in children with mild sleep-disordered breathing. Biol Res Nurs. 2004; 5(3): 168–176. PubMed Abstract | F1000 Recommendation\n\nLewin DS, Rosen RC, England SJ, et al.: Preliminary evidence of behavioral and cognitive sequelae of obstructive sleep apnea in children. Sleep Med. 2002; 3(1): 5–13. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMassand E, Ball G, Erikkson M, et al.: Sleep fragmentation in infants/toddlers with Down syndrome: Relationships with language, motor abilities and attention. Prep.\n\nDierssen M, Herault Y, Estivill X: Aneuploidy: from a physiological mechanism of variance to Down syndrome. Physiol Rev. 2009; 89(3): 887–920. PubMed Abstract | Publisher Full Text\n\nChoong XY, Tosh JL, Pulford LJ, et al.: Dissecting Alzheimer disease in Down syndrome using mouse models. Front Behav Neurosci. 2015; 9: 268. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWeaver IC, Cervoni N, Champagne FA, et al.: Epigenetic programming by maternal behavior. Nat Neurosci. 2004; 7(8): 847–854. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nFish EW, Shahrokh D, Bagot R, et al.: Epigenetic programming of stress responses through variations in maternal care. Ann N Y Acad Sci. 2004; 1036: 167–180. PubMed Abstract | Publisher Full Text\n\nFrancis DD, Szegda K, Campbell G, et al.: Epigenetic sources of behavioral differences in mice. Nat Neurosci. 2003; 6(5): 445–446. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCrabbe JC, Phillips TJ: Mother nature meets mother nurture. Nat Neurosci. 2003; 6(5): 440–442. PubMed Abstract | Publisher Full Text\n\nBohacek J, Mansuy IM: Molecular insights into transgenerational non-genetic inheritance of acquired behaviours. Nat Rev Genet. 2015; 16(11): 641–652. PubMed Abstract | Publisher Full Text\n\nPons-Espinal M, de Lagran MM, Dierssen M: Functional implications of hippocampal adult neurogenesis in intellectual disabilities. Amino Acids. 2013; 45(1): 113–131. PubMed Abstract | Publisher Full Text\n\nMoore DG, Oates JM, Hobson RP, et al.: Cognitive and social factors in the development of infants with Down syndrome. Downs Syndr Res Pract. 2002; 8(2): 43–52. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "13028",
"date": "23 Mar 2016",
"name": "Roger H. Reeves",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "13029",
"date": "23 Mar 2016",
"name": "Jennifer Wishart",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-389
|
https://f1000research.com/articles/4-115/v1
|
12 May 15
|
{
"type": "Opinion Article",
"title": "The \"Hyper-Visible World\" hypothesis for the dazzling colours of coral reef fish",
"authors": [
"Wladimir J. Alonso"
],
"abstract": "No evolutionary explanation for the striking colouration of coral reef fish has been established to date. Here I present the \"Hyper-Visible World” hypothesis, which proposes that coral reef habitats impose special conditions on the evolution of body-colour communication for mobile fish – that is, fish that roam across coral reef formations. The special conditions are: 1) the high clarity of water during daylight hours, and 2) the unpredictable pattern/ visual complexity of the coral habitat itself. The hypothesis suggests that, in a signal transmission framework, the visual exposure (signal) of mobile fish cannot be effectively reduced so as to make a difference to predator-prey interactions. This negates the possibility of effective colour-based camouflage. In contrast, the selective pressures that usually come secondary to camouflage (such as sexual, aposematic or territorial display) benefit from these same conditions, driving the evolution of the colour patterns in this environment – the conspicuousness and dazzling colour diversity that we commonly associate with coral reef fish.",
"keywords": [
"coral reefs",
"fish",
"colours",
"camouflage",
"signal-transmission",
"evolution",
"conspicuousness"
],
"content": "Introduction\n\nBeing able to hide in plain sight is a major selective pressure for both prey and predator species1,2. Traits increasing the ability of individuals to camouflage in the environment have likely been under strong selection since vision emerged, having guided to a great extent the evolution of visual displays in the animal world. It is in this context that the dazzling colouration of fish inhabiting coral reefs and other tropical bodies of water has puzzled scientists since the formulation of natural selection theory3–9. This flamboyance of colour patterns seems not only to disregard any pressure for blending in with the environment, but in fact suggests the opposite purpose: to make an individual stand out as much as possible, competing for attention.\n\nAlfred Russel Wallace, co-proponent of the natural selection theory, put forward a hypothesis that relied instead on the existence of a camouflage purpose of those colours and patterns, whereby “brilliantly-coloured fishes from warm seas are many of them well concealed when surrounded by the brilliant sea-weeds, corals, sea-anemones, and other marine animals, which make the sea-bottom sometimes resemble a fantastic flower-garden”3. Even though camouflage may also work by disrupting, or breaking up, contrasting patterns that can make a prey/predator easily recognizable1,10, the fact is that most fish inhabiting coral reefs can be easily seen to the point that, in fact, 1973 Nobel Prize winner, Konrad Lorenz, proposed a hypothesis which is based in a total denial of disguise function in that context. Instead, Lorenz suggested these dazzling colour patterns would be a robust means of species-recognition in the highly diverse and multi-niche environment of coral reefs, where such distinct signalling patterns would be needed to prevent aggression among non-competitor species4. However, many of the colourful fish found in corals are not necessarily aggressive or territorial11. Therefore, to date no hypothesis has in fact proven resilient to existing empirical data and this evolutionary puzzle remains at large4–9.\n\n\nThe hypothesis\n\nHere I present the “Hyper-Visible World” hypothesis, which proposes that coral reef habitats impose special conditions on the evolution of body-colour communication for mobile fish – that is, fish that roam across coral reef formations-leading to an impossibility of the use of camouflage while promoting the selective forces that benefit from conspicuousness. The special conditions are: 1) the high clarity of water during daylight hours, and 2) the unpredictable pattern/visual complexity of the coral habitat itself. These conditions negate the possibility of camouflage for most mobile animals in such habitats (some species can change the body coloration in real time as they roam over different backgrounds, but this is a highly sophisticated and demanding feature restricted to a few species like some octopuses). Because signalling patterns evolve as a trade-off between predation and other selective pressures12, when predation under varying degrees of visual conspicuousness is similarly efficient, other selective pressures for communication that benefit from conspicuousness (e.g. sexual or warning signalling) can evolve without the constraints imposed by the need for camouflage.\n\nThe hypothesis may be also understood within a signal transmission framework, where the visual conspicuousness of an individual represents the signal. As such, in coral reefs, the intensity of the signal conveyed by mobile fish cannot be reduced as to lessen predatory pressures. The exceptionally good environment for signal transmission (clear waters) and the unpredictability of the “background noise” (diverse coral reef) for a dislocating individual, makes the reduction of signal-to-noise ratio exceptionally difficult. In fact, the Hyper-Visible World hypothesis lays out a specific and falsifiable (sensu Popper13) prediction: other traits being equal, roaming fish with any degree of visual prominence will endure equivalent predatory pressure (or success) in coral reefs, but not when swimming against a predictable background.\n\nIt is important to highlight spatiotemporal dynamics14 involved in this theory: the degree of mobility of fish in the geography of coral reef habitats plays a pivotal role in the predictability of the background, and hence in the evolution of camouflage. If a fish roams against a variety of backdrops, the likelihood of effective camouflage is close to null. If, on the other hand, a fish spends most of his time in one location, natural selection will favour pigmentation and morphologies that match that predictable substrate (be it a coral species, type of rock or sand). Interestingly, because visual acuity is so high in the transparent waters of coral reefs, the need to “deceive with perfection” is also exceptionally high, leading to the “hyper-naturalism” found in the camouflage patterns of fish like pygmy sea horse or anglerfish, which is more typical of terrestrial environments (where visibility is also usually excellent) than of other marine habitats.\n\nSelective pressures driving the evolution of colour patterns (but that usually come secondary to camouflage) benefit precisely from those conditions that are adverse to concealment. Those selective pressures range from hostile to friendly signalling. Among conspecifics, for example, signals range from those communicating willingness to engage in dispute over resources to stressing bonding forces for school formation and sexual attraction. In interspecific interactions, signals may range from warnings of retaliatory weaponry (e.g. aposematism by poisonous fishes) to the marketing of services (e.g. special colours and approaching behaviours of cleaner fishes4,15). However, while selective pressures for conspicuousness are favoured by the transparency of the medium, they are hampered by the complex and colour-rich background of the coral reef - hence the pressure for the “hyper-unnatural” (i.e. not often found in nature) colour patterns of many reef fish.\n\nAlthough the Hyper-Visible World hypothesis relies on the notion that camouflage in coral reefs is not an option for many mobile species, selection for camouflage can be also relaxed in other contexts. One such case is that of non-predatory species endowed with effective defence mechanisms against predators. The hummingbirds’ speed or the nut-cracking beaks of parrots probably did not evolve as defences against predation, but are effective in that sense, freeing those animals from the need to visually blend in with their surroundings. Similarly to what is found in coral reefs, other evolutionary pressures for colouration could then take over.\n\nA Hyper-Visible World, we speculate, can also help drive biological diversity. Signalling in high visual resolution can promote the genesis of new species through sensory-drive12,16, a process whereby subtle changes in either colour patterns or in sensory/cognitive biases for attraction to those patterns can lead to the reproductive isolation of part of a population. In this sense, the high resolution of signals coupled with the high productivity of coral reefs might account for the high rates of sympatric speciation observed in these habitats.\n\nJustin Marshall, a specialist in the study of colour vision observed that it “is almost inconceivable for only one evolutionary force to be behind the colours of such a diverse assemblage”6. Indeed, should the Hyper-Visible World hypothesis prove accurate, it is paradoxically the very elimination of only one evolutionary force (camouflage) that sets the artistic boldness of several other pressures free for drawing the magnificent mosaic of colours and shapes found in these marine ecological wonders.",
"appendix": "Competing interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nAcknowledgments\n\nI am grateful to Gil Rosenthal, for his comments on an earlier version on this paper, and to Cynthia Schuck-Paim, Nigel Pearn and Veronique Vicera for their comments and editorial content revisions. This paper is dedicated to the dear friends of the memorable 2014 sailing trip, the occasion when I formulated this theory while diving in the outstanding Caribbean waters.\n\n\nReferences\n\nCott HB: Adaptive Coloration in Animals. New Ed edition. Oxford University Press, 1940. Reference Source\n\nDarwin C: On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. John Murray III, 1859. Publisher Full Text\n\nWallace AR: The Protective Colours of Animals, by Alfred Russel Wallace. “Science for All”, Editor Charles H Smith’s, 1879. Reference Source\n\nLorenz K: The function of colour in coral reef fishes. Proc Roy Inst Great Brit. 1962; 39: 282–296.\n\nMarshall J: Pacific Ocean: Why Are Reef Fish So Colorful? Scientific American: The Oceans, 1998. Reference Source\n\nMarshall JJ: Signalling and signal design in animal communication. in Animal signals Signalling and signal design in animal communication. (eds. Espmark Y, Amundsen T and Rosenqvist G) Tapir, Trondheim, Norway, 2000; 59–96.\n\nMilius S: Hide and See-Conflicting views of reef-fish colors. Science News. 2004; 166: 296.\n\nPrice AC, Weadick CJ, Shim J, et al.: Pigments, patterns, and fish behavior. Zebrafish. 2008; 5(4): 297–307. PubMed Abstract | Publisher Full Text\n\nSiebeck UE, Wallis GM, Litherland L: Colour vision in coral reef fish. J Exp Biol. 2008; 211(Pt 3): 354–360. PubMed Abstract | Publisher Full Text\n\nMarshall J: Why Are Animals Colourful? Sex and Violence, Seeing and Signals. JAIC - Journal of the International Colour Association. 2010; 5. Reference Source\n\nRosenthal GG, Marshall JJ: Communication Behavior: Visual. Encyclopedia of Fish Physiology: From Genome to Environment. Academic Press, 2011; 692–698.\n\nEndler JA: Signals, signal conditions, and the direction of evolution. American Naturalist. 1992; 139: 125–53. Publisher Full Text\n\nPopper KR: Science as Falsification. Conjectures and Refutations. London: Routledge & Kegan Paul. 1963. Reference Source\n\nRosenthal GG: Spatiotemporal Dimensions of Visual Signals in Animal Communication. Annual Review of Ecology, Evolution, and Systematics. 2007; 38: 155–178. Publisher Full Text\n\nCheney KL, Grutter AS, Blomberg SP, et al.: Blue and yellow signal cleaning behavior in coral reef fishes. Curr Biol. 2009; 19(15): 1283–1287. PubMed Abstract | Publisher Full Text\n\nEndler JA, Basolo AL: Sensory ecology, receiver biases and sexual selection. Trends Ecol Evol. 1998; 13(10): 415–420. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "9330",
"date": "08 Jul 2015",
"name": "Brian Langerhans",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe paper offers a hypothesis concerning the \"striking colouration of coral reef fish.\" The idea is that coral reef fish roam across complex/unpredictable background colors and patterns within a transmission environment which permits highly effective perception of a range of light (color) to a variety of organisms capable of receiving and processing the respective light waves (during daytime). The argument rests on a number of assumptions, leading to the conclusion that selection will not favor camouflage in such an environment, and thus selection favoring conspicuous signaling is largely unconstrained. I think there is a useful hypothesis described here, which points out several testable ideas. However, I think each key assumption should be more directly addressed in the paper. Otherwise, one can see that the entire \"Hyper-Visible World Hypothesis\" could come crumbling down if those assumptions are wrong.The first assumption needs more support: that coral reef fishes actually exhibit significantly higher color conspicuity or diversity than most other organismal assemblages. The entire hypothesis rests on this premise. Have studies tested whether coral reef fish actually exhibit such remarkable color patterns compared to other assemblages throughout the world? I agree that they surely must represent one of the more colorful, conspicuous, and diverse assemblages--but I'm not sure they are so remarkable that they deserve a special hypothesis unto themselves. It'd be nice to see some support for this premise. If this premise were untrue, then there is no need for a unique explanation for the colors of coral reef fishes.The next assumption is that coral reefs provide a background of complex and unpredictable colors. I recall some studies showing low diversity of color during daytime and under ambient light for coral reefs. The author suggests that reefs are extremely colorful and complex, but I'd like to see some support for this. I agree they do seem fairly colorful and complex to us humans, but I can actually think of a number of other environments which seem pretty colorful and complex as well. What have previous studies found regarding the actual background colors of reefs? Are they really that complex and unpredictable from the perspective of a predator? Or is the background mostly blue/green/brown?The next assumption is that coral reef waters actually are \"hyper visible.\" That is, do these waters provide a transmission environment for which an especially wide range of color signals are accurately and efficiently transmitted? The waters are generally quite clear (low turbidity, high visibility), but air actually provides more effective transmission of light across all the relevant wavelengths. It seems to me that these waters actually truncate the red/yellow/orange wavelengths (to various extents), and thus are not \"hyper visible\" in that sense. Perhaps some further discussion of this point is warranted, as I'm not sure in what sense the waters are actually hyper-visible, but rather the organisms within the environment are highly visible due to a combination of water clarity and colors. The next assumption is that many resident organisms have well developed color vision. This is actually quite well supported by the literature, although it'd be nice for this paper to explicitly support this assumption as well.The final assumption is really more of a prediction: that selection will not favor crypticity in such an environment, and thus we should not see cryptic organisms (but rather the evolution of conspicuous colors, which is the heart of the hypothesis). I doubt this is as universal as suggested in this paper. There are actually many examples of cryptic organisms inhabiting coral reefs (at least during a substantial part of their lives), including many fishes. Not only are there many coral reef fishes which are quite cryptic (e.g., peacock and leopard flounders, scorpionfish, frogfish, many blennies and gobies, trumpetfish...), but also many exhibit some cryptic components, such as countershading and disruptive coloration (including false eyes for misdirection). The prevalence of countershading seems to suggest that some crypticity has long continued to be advantageous in reef environments, although highly conspicuous signals are additionally advantageous. Moreover, the author's hypothesis that crypticity should primarily be favored in relatively sessile fishes could be directly tested (this could be mentioned in the paper)--and if the author could support this contention, that would be great (that most known examples of camouflage in reef fishes are in relatively stationary species).",
"responses": [
{
"c_id": "1852",
"date": "22 Mar 2016",
"name": "Wladimir Alonso",
"role": "Author Response",
"response": "Dear Brian, Thank you very much for your review, relevant comments and for allowing me the opportunity to provide more evidence and clarify the assumptions on which my proposed hypothesis rests on. Your name, together with others –who provided me with feedback, will be included in the acknowledgment section of this manuscript, in recognition of your time and expert feedback. In totality, the constructive criticism and discussion this paper has generated has helped me realize that I should also somehow present these ideas in a systematized and slightly more organized format. The current version therefore provides a framework that more formally addresses the topic of the conspicuous coloration of certain animal species, like macaws and hummingbirds, which were just included as an additional note in previous version. Without adding too much extra content, I managed to create a couple of new sections including a new designation - \"the carefree world\" in addition to a figure that both integrates and summarizes those ideas. Below I have addressed the assumptions you specifically mentioned and that would need further support and clarification: #1 \"coral reef fishes actually exhibit significantly higher color conspicuity or diversity than most other organismal assemblages. The entire hypothesis rests on this premise. Have studies tested whether coral reef fish actually exhibit such remarkable color patterns compared to other assemblages throughout the world?\" WJA Reply:I haven't succeeded in finding a reference of a study that quantifies that coral reef fish exhibit higher colour conspicuity of diversity than most other organismal assemblages. It seems that it is a given in the field, and scientists express in sorts of ways like this:\"There is in all the world, no other biotope which has produce, in so short a time or, which means the same thing, in so closely allied groups of animals, an equal number of extremely specialized forms\" (1) or \"A coral reef is perhaps the most colorful of all the world's ecosystems. During the day it throngs with multicoloured fish and invertebrates\" and \"there is nowhere on earth where one can find so many colourful animals packed into such small space\" (2) Nevertheless, despite perhaps not being quantified in the way we would like it, this is an observation that is widely supported and the one which all the hypothesis mentioned in this text since Wallace's one, try to find an answer. Furthermore, allow me to also address your remark that \"I agree that they surely must represent one of the more colorful, conspicuous, and diverse assemblages--but I'm not sure they are so remarkable that they deserve a special hypothesis unto themselves. It'd be nice to see some support for this premise. If this premise were untrue, then there is no need for a unique explanation for the colors of coral reef fishes\". WJA Reply: As surprising as it may seem, the abundance of bright and colourful fish in coral reef , that so markedly stands out visually, -where we should expect to witness animals trying to blend into the surroundings, so they do not become “an obvious meal”(3) is still an open question and the subject itself, has given rise to several studies and conjectures to address it (as shown in the introduction of the paper). I do agree with you on your point that any hypothesis looking at it should aim for a broader scope, as mechanisms in nature rarely are specific to only one circumstance. I just found a passage in Cott's 1940 book that can be considered another example of a \"hyper-visible world,\" which I am including as a opening citation in the \"Hyper-visible world\" section of the new version #2 \" coral reefs provide a background of complex and unpredictable colors. I recall some studies showing low diversity of color during daytime and under ambient light for coral reefs. The author suggests that reefs are extremely colorful and complex, but I'd like to see some support for this. I agree they do seem fairly colorful and complex to us humans, but I can actually think of a number of other environments which seem pretty colorful and complex as well. What have previous studies found regarding the actual background colors of reefs? Are they really that complex and unpredictable from the perspective of a predator? Or is the background mostly blue/green/brown? WJA Reply: Matz et al (4) used spectrometry data and visual system modelling to answer the question posed in the title of their article \"Are Corals Colourful?\" This article attempted to answer such questions from the perspective of the fish and found that \"Some GFP-like proteins, most notably fluorescent greens and nonfluorescent chromoproteins, indeed generate intense color signals.\" They go on to explain that \"fluorescent proteins might also make corals appear less colorful to fish, counterbalancing the effect of absorption by the photosynthetic pigments of the endosymbiotic algae, which might be a form of protection against herbivores.\" But as they even discuss at the end, \"It is tempting to speculate that the evolution of diverse coral colors in early Mesozoic (3) might have prompted the specialization of the fish visual systems in the process of adaptation to the environment, eventually leading to appearance of very unusual color signaling displayed by present-day reef fishes.\" Therefore, I believe it is a sound assumption that coral reefs are not only perceived as colourful to humans but are also perceived as such by (often chromatically more sophisticated eyes (5)) their aquatic inhabitants as well. I modified the text accordingly to include these references and a summary of those considerations. In any case, please note that if colour vision were not found in predatory interactions within the context of the hypothesis presented, this would not be an issue for the hypothesis since mobile fish in the \"hyper-visible world\" cannot hide, regardless of their colour, meaning predators/prey also need not use colour vision (again, for their interactions). This is also valid in the \"carefree world\" scenario, where, if a predator cannot risk hunting a dazzlingly colourful macaw, why would evolution bother providing that predator with the visual capabilities customized to detect a macaw? # 3 \"coral reef waters actually are \"hyper visible.\" That is, do these waters provide a transmission environment for which an especially wide range of color signals are accurately and efficiently transmitted? The waters are generally quite clear (low turbidity, high visibility), but air actually provides more effective transmission of light across all the relevant wavelengths. It seems to me that these waters actually truncate the red/yellow/orange wavelengths (to various extents), and thus are not \"hyper visible\" in that sense. Perhaps some further discussion of this point is warranted, as I'm not sure in what sense the waters are actually hyper-visible, but rather the organisms within the environment are highly visible due to a combination of water clarity and colors\" WJA Reply: Coral reefs are usually found in shallow, clear tropical waters where the spectral attenuation of light by transmission medium (water) has not yet been severe. (2). In fact, only very little of the downwelling light, while the horizontal light is \"less intense, narrower and shifted to the blue\" (5)(6). Many fish can see even UV light, so they are able to perceive an even greater variety of colours than we do. You are correct in pointing out (and I do also points this out in the paper) that the excellent visibility of coral reefs habitats are nonetheless inferior to most of the terrestrial. But do note that the \"hyper-visible world\" is a way to express the impossibility of matching a background pattern in certain conditions and that difficulty is imposed not only because of the good transparency and luminosity of the medium, but equally important is the unpredictability of the background to be matched. Terrestrial environments (as discussed in the first answer) seem to be more predictable (but, again, please see the first new paragraph of the Hyper-visible World section quoting an interesting parallel explanation in Cott's 1940 book) . While this is true for visual signals, perhaps this is not the case for acoustic and olfactory signals (which is why I added that small discussion at the end of the paper in the current version. # 4 \"many resident organisms have well developed color vision. This is actually quite well supported by the literature, although it'd be nice for this paper to explicitly support this assumption as well\" WJA Reply: As suggested, I added Bennet et al review (7), which explains how vision in those environments can be more sophisticated than ours (including UV vision and a higher number of different photoreceptors, which are common in marine species. # 5 \"The final assumption is really more of a prediction: that selection will not favor crypticity in such an environment, and thus we should not see cryptic organisms (but rather the evolution of conspicuous colors, which is the heart of the hypothesis). I doubt this is as universal as suggested in this paper. There are actually many examples of cryptic organisms inhabiting coral reefs (at least during a substantial part of their lives), including many fishes. Not only are there many coral reef fishes which are quite cryptic (e.g., peacock and leopard flounders, scorpionfish, frogfish, many blennies and gobies, trumpetfish...), but also many exhibit some cryptic components, such as countershading and disruptive coloration (including false eyes for misdirection).\" WJA Reply: You spotted an error that was also pointed out by a comment from Benjamin Geffroy; that is, I incorrectly used the expression \"will\" where it should read \"can.\" I have since corrected it in the revised version. But please do note that this hypothesis stresses the importance of the \"mobile\" (i.e. spatio-temporal) feature for making it very difficult for organisms to evolutionary develop a pattern that can provide some concealment against predators or preys. I hope that the new figure added to the paper helps to further clarify the circumstances where coral reefs can indeed support camouflage (which basically occurs when animals are loyal to one specific background during daylight hours). #6 \"The prevalence of countershading seems to suggest that some crypticity has long continued to be advantageous in reef environments, although highly conspicuous signals are additionally advantageous. Moreover, the author's hypothesis that crypticity should primarily be favored in relatively sessile fishes could be directly tested (this could be mentioned in the paper)--and if the author could support this contention, that would be great (that most known examples of camouflage in reef fishes are in relatively stationary species)\". WJA Reply: Indeed, countershading, disruptive camouflage and other forms of concealment are not negated among diurnal mobile fish in coral reefs. The extraordinary abundance of life forms and solutions to the constant predator/prey interactions certainly include these mechanisms (and possibly others we haven't described yet). Nevertheless, the question remains of why there are so many fish that are so easily detectable, even for humans. Furthermore, this species is only a visitor in the described environments and the reason for why senses which do not define the need to see those species - is not covered by those explanations. It has been shown that fish can develop visual capabilities that are far better than ours - if doing so would provide them with the ability to escape from or catch those colourful fish, it would be surprising that they would not use/develop those very capabilities. Thank you once again for your appreciated input. Best,Wladimir 1. Lorenz K. The function of colour in coral reef fishes. Proc Roy Inst Gt Brit. 1962;39:282–96. 2. Marshall JJ. The visual ecology of reef fish colours. Animal signals: signaling and signals design in animal communication In: Espmark, Y, Amundsen, D, and Rosenqvist, G (eds) Animal signals: signaling and signals design in animal communication. Norway: Tapir Academic Press; 1999. 3. Marshall J. Pacific Ocean: Why Are Reef Fish So Colorful? Sci Am Oceans. 1998;August. 4. Matz MV, Marshall NJ, Vorobyev M. Are Corals Colorful? Photochem Photobiol. 2006 Mar 1;82(2):345–50. 5. McFarland WN, Munz FW. Part III: The evolution of photopic visual pigments in fishes. Vision Res. 1975 Oct;15:1071–80. 6. McFarland WN, Munz FW. Part II: The photic environment of clear tropical seas during the day. Vision Res. 1975 Oct;15:1063–70. 7. Bennett ATD, Cuthill IC, Norris KJ. Sexual Selection and the Mismeasure of Color. Am Nat. 1994 Nov 1;144(5):848–60."
}
]
}
] | 1
|
https://f1000research.com/articles/4-115
|
https://f1000research.com/articles/4-79/v1
|
26 Mar 15
|
{
"type": "Research Article",
"title": "Signaling mechanism by the Staphylococcus aureus two-component system LytSR: role of acetyl phosphate in bypassing the cell membrane electrical potential sensor LytS",
"authors": [
"Kevin Patel",
"Dasantila Golemi-Kotra",
"Kevin Patel"
],
"abstract": "The two-component system LytSR has been linked to the signal transduction of cell membrane electrical potential perturbation and is involved in the adaptation of Staphylococcus aureus to cationic antimicrobial peptides. It consists of a membrane-bound histidine kinase, LytS, which belongs to the family of multiple transmembrane-spanning domains receptors, and a response regulator, LytR, which belongs to the novel family of non-helix-turn-helix DNA-binding domain proteins. LytR regulates the expression of cidABC and lrgAB operons, the gene products of which are involved in programmed cell death and lysis. In vivo studies have demonstrated involvement of two overlapping regulatory networks in regulating the lrgAB operon, both depending on LytR. One regulatory network responds to glucose metabolism and the other responds to changes in the cell membrane potential. Herein, we show that LytS has autokinase activity and can catalyze a fast phosphotransfer reaction, with 50% of its phosphoryl group lost within 1 minute of incubation with LytR. LytS has also phosphatase activity. Notably, LytR undergoes phosphorylation by acetyl phosphate at a rate that is 2-fold faster than the phosphorylation by LytS. This observation is significant in lieu of the in vivo observations that regulation of the lrgAB operon is LytR-dependent in the presence of excess glucose in the medium. The latter condition does not lead to perturbation of the cell membrane potential but rather to the accumulation of acetate in the cell. Our, study provides for the first time the molecular basis for regulation of lrgAB in a LytR-dependent manner under conditions that do not involve sensing by LytS.",
"keywords": [
"LytSR",
"Histidine kinase",
"Response Regulator",
"Phosphotransfer",
"Staphylococcus Aureus"
],
"content": "Summary statement\n\nThe molecular basis of signal transduction by LytSR is unknown. We show that LytS has kinase and phosphatase activity. LytR undergoes rapid phosphorylation by acetyl phosphate. Activity of LytR is regulated either through LytS or acetyl phosphate. LytSR is at the interface of two regulatory pathways that respond to excess glucose metabolism and cell membrane electrical potential, respectively.\n\n\nIntroduction\n\nThe two-component system LytSR of Staphylococcus aureus is reported to function as a sense-response system for detecting subtle changes in the electrical potential of the cell membrane. It is also involved in adaptation of S. aureus to cationic antimicrobial peptides (CAMPs)1–3. CAMPs are bactericidal agents released by the host innate immune system during colonization by S. aureus4,5. Their mechanism of action is believed to involve perturbation of cell membranes which, in turn, alters the electrical potential of the cell membrane3,6. The function of LytSR in the cell is reported as a regulator of cell wall lysis during programmed cell death and biofilm formation7–12.\n\nA typical two component system (TCS) consists of a membrane bound histidine kinase (HK) which intercepts an environmental cue and through an act of auto-phosphorylation transduces the signal intracellularly. The response to the cue is mediated through a phosphotransfer process whereby a second protein, in response to a regulator protein, receives the phosphoryl group from the cognate histidine kinase (HK) at a conserved aspartate residue. The response regulator (RR) protein is often a transcription factor and in some cases an enzyme13. LytSR is comprised of the membrane-bound sensor HK LytS and the RR protein LytR. LytS belongs to a family of bacterial receptor proteins that contain five transmembrane-spanning domains. LytR is a transcription factor that falls into a novel family of proteins that contain non-helix-turn-helix DNA-binding domains, known as LytTRs14,15.\n\nLytR regulates cidABC and lrgAB operons in response to alterations in the electrical potential of the cell membrane16. Both operons are involved in the control of programmed cell death and lysis during biofilm formation12,17,18; the gene products of the cid operon enhance murein hydrolysis activity and antibiotic tolerance19 while the lrg genes inhibit these processes9. Interestingly, both operons were also shown to be induced by carbohydrate metabolism and proposed to be regulated through a cidR-dependent signaling pathway20. The cidR gene encodes a LysR-type transcription factor which has been proposed to be activated by acetyl phosphate that accumulates as a result of metabolism of excess glucose by S. aureus during logarithmic growth20,21. Recent work by Sharma-Kuinkel et al.2 demonstrated that lrgAB is instead regulated only through LytR, either in response to carbohydrate metabolism (e.g. excess of glucose) or as a result of disruption of cell membrane electrical potential. However, the molecular basis for this observation remains obscure.\n\nTo examine the signal transduction mechanism of LytSR and probe its involvement in the regulation of lrgAB in response to carbohydrate metabolism as a result of a phosphorylation-induced activation of LytR by acetyl phosphate, we cloned and purified LytS and LytR and investigated the autokinase activity of LytS, the kinetics of the phosphotransfer between LytS and LytR, and the kinetics of phosphorylation of LytR by acetyl phosphate. Our study shows that LytSR is capable of mediating signaling either through LytS in response to cell membrane electrical potential or through LytR in response to carbohydrate metabolism. Furthermore, phosphorylation-induced activation of LytR by either LytS or acetyl phosphate is likely to involve dimerization of LytR at the receiver domain.\n\n\nMaterials and methods\n\nChemicals and antibiotics were purchased from Sigma (Oakville, Canada) or Thermo-Fisher (Whitby, Canada), unless otherwise stated. Chromatography media and columns were purchased from GE Healthcare (Quebec, Canada). Growth media were purchased from Fisher. Escherichia coli strains, NovaBlue and BL21 (DE3), and cloning and expression plasmids were purchased from EMD4 Biosciences (New Jersey, USA). The pGEX-4T vector was purchased from GE Healthcare (Quebec, Canada). Restriction enzymes were obtained from New England Biolabs (Pickering, Canada) or Thermo-Fisher. The [γ-32P] Adenosine triphosphate (ATP) was purchased from Perkin Elmer LAS Canada Inc. (Toronto, Canada) or GE Healthcare. The Proteo Extract All-in-One Trypsin Digestion Kit was purchased from EMD4 Bioscience. The genome of the S. aureus strain Mu50 was obtained from Cedarlane (Burlington, Canada).\n\nThe gene sequence of lytS (SAV0260, as per gene numbering in S. aureus Mu50 strain) encoding the cytoplasmic region of the protein (amino acid residues 355–584) was amplified from S. aureus Mu50 genome using the primers: Dir 5'- CACCGCAGAAGGATTGGCAAAT-3' and Rev 5'-TTATTCCTCCTCTTG TCTTT CA-3'. To enable directional cloning, the forward primer contained a specific 4 base pair (bp) sequence (italicized) at the 5' end of the primer. The 701 bp lytS gene was amplified using Phusion High-Fidelity DNA polymerase with the following PCR conditions: initial denaturation at 98°C for 30 s, followed by 30 cycles at 98°C at 10 s, annealing at 61°C for 20 s, extension at 72°C for 20 s and final extension at 72°C for 10 min. The blunt ended amplicon was then ligated to pET151/D-TOPO vector using the Champion™ pET Directional TOPO® Expression Kit. The ligated pET151/D-TOPO::lytS construct was used to transform E. coli NovaBlue cells for further amplification. The correct sequence of lytS was confirmed by DNA sequencing (The Centre for Applied Genomics, the Hospital for Sick Kids, Toronto, Canada. The pET151/D-TOPO::lytS plasmid was used to transform the E. coli BL21 (DE3) to facilitate protein expression. This cloning strategy resulted in introduction of an NH2-terminous 6xHis tag upstream of lytS.\n\nE. coli BL21(DE3) cells carrying the construct pET151/D-TOPO::lytS were used to inoculate 5 mL of Luria Bertani (LB) medium supplemented with 100 µg/mL final concentration of ampicillin and allowed to grow overnight at 37°C by shaking. An aliquot of 1 mL of the overnight cell culture was used to inoculate 1 L of Terrific Broth (TB) medium supplemented with 100 µg/mL of ampicillin. Cells were allowed to grow at 37°C by shaking at 200 rpm until the cell culture reached an optical density of 0.6 to 0.8 absorbance units at 600 nm (OD600nm). At this point, the cell culture was cooled to 4°C and protein production initiated by adding isopropyl β‐D‐1‐thiogalactopyranoside (IPTG) at a final concentration of 0.1 mM. Cell culture was shaken at 200 rpm at 18°C for 12 hrs. Cells were harvested by centrifugation at 3,300 × g for 20 min.\n\nFor isolation of His-LytS, the cell pellet was resuspended in 50 mM sodium phosphate pH 7.5, supplemented with 300 mM NaCl and 10 mM Imidazole. The cellular content was liberated by sonication while cooling on ice for 10 min (10s on/15s off) and cell debris was removed by centrifugation at 18,000 × g for 1 h at 4°C. Purification of His-LytS was carried out by loading the supernatant onto a self-assembled affinity column (Generon, UK) packed with 8 mL of Ni-NTA resin. All purification steps were carried out at 4°C using the AktÄ purifier 10 (GE Healthcare). The unbound protein was removed by washing with buffer for three column volumes (CV). The protein of interest was eluted using a step gradient of 10%, 40%, 70% and 100% of 300 mM imidazole in 50 mM sodium phosphate pH 7.5 buffer, supplemented with 300 mM NaCl, at a flow rate of 1.5 mL/min in three CV. Fractions of 5 mL containing the protein were concentrated using Amicon Ultra-10K concentrator (Millipore) followed by dialysis into the storage buffer: 50 mM Tris pH 7.5, supplemented with 150 mM NaCl and 5 mM MgCl2. The homogeneity of protein was assessed by loading samples onto a 15% sodium dodecyl sulphate-polyacrimide gel electrophoresis (SDS-PAGE) apparatus and staining the gel with Coomassie blue.\n\nThe gene sequence of lytR (SAV0261) was amplified from the S. aureus Mu50 genome using the primers: Dir 5'-GGAATTCCATATGAAAGCATTAATCATAGATGATG-3' and Rev 5'-CGGAATTCTTAT TAAAGTAATCCTA TCGACG-3'. The primers were designed to introduce the NdeI and EcoRI restriction sites (italicized sequences) at 5' and 3' of lytR, respectively. Amplification of the 741 bp lytR gene was carried out using Phusion® High-Fidelity DNA polymerase following these conditions: initial denaturation at 98°C for 30 s, followed by 30 cycles at 98°C at 10 s, annealing at 62°C for 20 s, extension at 72°C for 20 s and final extension at 72°C for 10 min. The resulting amplicon was purified and together with the host vector, pET26b, was digested with NdeI and EcoRI. The digestion products were gel purified from 1% agarose gel using the QIAquick Gel Extraction Kit (Qiagen) and subjected to ligation using T4 DNA ligase (NOVAGEN). The subsequent construct was referred to as pET26b::lytR and was used to transform E. coli NovaBlue cells for further amplification. The correct sequence of the lytR gene was confirmed by DNA sequencing (The Centre for Applied Genomics, the Hospital for Sick Kids, Toronto, Canada). The pET26b::lytR plasmid was used to transform the E. coli BL21 (DE3) expression cells. This cloning strategy resulted in introduction of no tags or additional amino acids to LytR.\n\nTo clone the receiver domain of the LytR protein, LytRN (residues 1-134), a stop codon after the 134th amino acid residue was introduced using the QuikChange® Site-Directed Mutagenesis method (Thermo Fisher). The process of site directed mutagenesis was carried out using the Pfu Turbo® DNA polymerase and the following mutagenic primers: 5'-GCGAATGATATGTCGTAGAATTTTGATCAAAGC-3' and 3'-GCTTTGATCAAAATTCTA CGACATATCATTCGC-5' (mutated nucleotides are italicized). The construct pET26b::lytR was used as the template. The amplified mutagenic construct, pET26b::lytRN was treated with the restriction endonuclease DpnI and used to transform E. coli NovaBlue cells. Successful insertion of the stop codon was confirmed by DNA sequencing (The Centre for Applied Genomics, the Hospital for Sick Kids, Toronto, Canada) and the pET26b::lytRN vector was used to transform E. coli BL21 (DE3).\n\nThe following primer set was used to clone the full length lytR into pGEX-4T-1 to enable fusion of the protein to the C-terminal of GST, Dir 5'-AGTCGGGATCCATGAAAGCATTAATCATA GATG-3' and Rev 5'-CG GAATTCTTATTAAAGTAATCCTATCG ACG-3'. The primers were designed to introduce BamHI and EcoRI restriction sites (italicized sequences) at 5' and 3' of lytR ends respectively, to enable cloning.\n\nThe Asp-53 residue of LytR was mutated to an Ala residue using QuikChange® Site-Directed Mutagenesis (Thermo Fisher). Briefly, the process of site directed mutagenesis was carried out using the Pfu Turbo® DNA polymerase with the designed mutagenic primers: 5'-AC ATTATATTTTTAGCTGTCAATTTAATGG-3' and 3'-CCATTAAATTGACAGCTAAAA AT ATAATGTC- 5' (mutated nucleotides are italicized). The construct pGEX-4T1::lytR was used as a template. The amplified mutagenic construct, referred to as pGEX-4T::lytRAsp53Ala, was treated with the restriction endonuclease DpnI and used to transform E. coli NovaBlue. Successful mutation of Asp to Ala was confirmed by DNA sequencing (The Centre for Applied Genomics, the Hospital for Sick Kids, Toronto, Canada). The pGEX-4T::lytRAsp53Ala plasmid was used to transform the E. coli BL21 (DE3).\n\nIn general, E. coli BL21 (DE3) carrying the appropriate plasmid was used to inoculate 5 mL of LB in the presence of 50 µg/mL of kanamycin. An aliquot of 1 mL of the overnight cell culture was used to inoculate 1 L of TB supplemented with 50 µg/mL of kanamycin. The cells were allowed to grow to OD600nm = 0.6–0.8 with shaking at 200 rpm at 37°C. Once desired growth was achieved the media was cooled to 4°C and protein production was induced by adding IPTG to a final concentration of 0.1 mM. Cell culture was allowed to shake for an additional 12 h at 18°C. Cells were harvested by centrifugation at 3,300 × g for 20 min.\n\nTo isolate LytR the method of protein precipitation by ammonium sulfate was employed. All purifications steps were carried out at 4°C. Cell pellet was suspended in 1:10 (w/v) of 50 mM Tris, pH 8.0, 100 mM NaCl, 5 mM MgCl2 supplemented with 10% glycerol. The cellular content was liberated by sonication and cell debris was removed by centrifugation at 18,000 × g for 1 h at 4°C. Total volume of supernatant was adjusted to be 50 mL (for 5 g cell) and 2.67 g of ammonium sulfate was added gently while stirring, to achieve saturation of 10%. The solution was incubated while stirring at 4°C for 30 min. The precipitated protein was collected by centrifugation at 3,300 × g for 5 min. The protein pellet was dissolved in 10 mL of 50 mM Tris, pH 8.0, 100 mM NaCl, 5 mM MgCl2 supplemented with 10% glycerol. The purity of the protein was evaluated by 15% SDS-PAGE stained with Coomassie blue. The protein solution was dialysed to remove ammonium sulfate.\n\nE. coli BL21 (DE3) harboring pET26b::lytRN was used to inoculate 5 mL of LB in the presence of 50 µg/mL kanamycin. An aliquot of 1 mL of the overnight cell culture was used to inoculate 1 L of TB supplemented with 50 µg/mL of kanamycin. The cells were allowed to grow to an OD600nm = 0.6–0.8 while shaking at 200 rpm at 37°C. The cell culture was cooled to 4°C and protein production initiated by addition of 0.5 mM IPTG. The cell culture was allowed to shake for an additional 12 h at 25°C for. Cells were harvested by centrifugation at 3,300 × g for 20 min.\n\nTo isolate LytRN, cell pellet was suspended in 1:10 (w/v) of 20 mM Tris pH 7.5, supplemented with 5 mM MgCl2. The cellular content was liberated by sonication and cell debris was removed by centrifugation at 18,000 × g for 1 h at 4°C. The supernatant was loaded onto a DEAE-Sepharose™ column (GE Healthcare) and mounted into the AktÄ purifier 10. The protein was eluted over ten column volumes in a linear gradient of 20–500 mM Tris (pH 7.5) (supplemented with 5 mM MgCl2) at a flow rate of 3 mL/min. Elution fractions containing protein were pooled together and concentrated by centrifugation using Amicon Ultra-3K concentrator (Millipore) to a final volume of 5 mL. The protein was loaded onto a HiPrep 26/60 Sephacryl S-200 HR gel-filtration column (GE Healthcare). The homogeneity of the protein was determined using 18% SDS-PAGE.\n\nE. coli BL21 (DE3) carrying the desired plasmid were used to inoculate 5 mL of LB in the presence of 100 µg/mL ampicillin. An aliquot of 1 mL of the overnight grown seed culture was used to inoculate 1 L of TB supplemented with 100 µg/mL of ampicillin. Cells were allowed to grow to an OD600nm = 0.6–0.8 at 37°C while shaking at 200 rpm. Then the cell culture was cooled to 4°C and protein production was initiated by addition of 0.5 mM IPTG and incubated further at 18°C for 12 h. The cells were harvested by centrifugation at 3,300 × g for 20 min.\n\nFor purification of the wild type or mutant GST-LytR protein, the cell pellet was suspended in 1:10 (w/v) of 50 mM Tris pH 7.5, supplemented with 100 mM NaCl and 5 mM MgCl2. The cellular content was liberated by sonication and cell debris was removed by centrifugation at 18,000 × g for 1 hour at 4°C. Purification was carried out by loading the supernatant onto a self-assembled affinity column packed with 5 mL of GST affinity resin (Generon). The protein of interest was eluted at a flow rate of 1.5 mL/min with 10 mM reduced glutathione in 50 mM Tris-HCl pH 8.0 buffer over three CV. Fractions containing the protein were concentrated using Amicon Ultra-10K concentrator (Millipore) followed by dialysis to exchange the buffer into 50 mM Tris pH 7.5, supplemented with 100 mM NaCl and 5 mM MgCl2. The homogeneity of protein was assessed by 12.5% SDS-PAGE stained with Coomassie blue.\n\nThe identities of the all proteins isolated in this study were confirmed by cutting the protein band from the SDS-PAGE gel, subjecting this to trypsin digestion and submitting the digest for mass spectrometry analysis. The molecular mass of the purified proteins was determined by electrospray ionization mass spectrometry (ESI-MS). All the mass spectrometry analyses were done at the Advanced Protein Technology Centre, Hospital for Sick Kids (Toronto, Canada).\n\nHis-LytS at 5 µM was equilibrated in phosphorylation buffer (PB: 50 mM Tris, pH 7.4, 50 mM KCl, 5 mM MgCl2) supplemented with 10 mM CaCl2. The phosphorylation reaction was initiated by the addition of [γ-32P]-ATP (10 Ci/mmol) mixed with cold ATP to prepare reaction mixtures at different ATP final concentrations. Samples were incubated at room temperature. The reaction was stopped at different time intervals by adding 5 × SDS sample buffer (125 mM Tris, pH 6.8, 2.5% SDS, 25% glycerol, 100 mM dithiothretiol (DTT), 0.0025% bromophenol blue). Samples were loaded onto a 15% SDS-PAGE. The SDS-PAGE gels were washed in water containing 2% (v/v) glycerol and were exposed to a phosphor screen (GE Healthcare) overnight and imaged using a Typhoon Trio+ imager (GE Healthcare). The radioactive gels were stained by Coomassie blue dye to analyze protein content of the samples.\n\nEach time-dependent phosphorylation experiment was repeated twice. The progress of the reaction was assessed by analyzing the phosphor-image of the radioactive gels using NIH ImageJ software (Version 1.45s) (freely available at http://imagej.nih.gov/ij/download.htmL). The progress curves were fitted to the first-order rate Equation 1, where I is the band intensity quantified by NIH ImageJ, kobs is the observed rate constant, t is the incubation time and A is the proportionality constant relating intensity with concentration of phosphorylated His-LytS.\n\nI = A×{1 – exp(–kobs × t)} (1)\n\nThe data were fitted using Erithacus GraFit software (version 5.0.10) (available at http://www.erithacus.com/grafit/Software_Updates.htm). The observed phosphorylation rate constant was calculated for each ATP concentration and was plotted against each ATP concentration to determine the rate constant of autophosphorylation of LytS using the equation (2), where kobs is the observed rate constant measured at each ATP concentration, k is the autophosphorylation rate constant for LytS, Ks, is the dissociation constant of ATP and [S] the ATP concentration.\n\n\n\nTo study the effect of salt ions on the phosphorylation of His-LytS, we looked at the effect of K+ and Ca2+. His-LytS at 3 µM was equilibrated in the phosphorylation buffer (PB: 50 mM Tris, pH 7.4, 5 mM MgCl2) with varying concentrations of either KCl or CaCl2. The phosphorylation reaction was initiated by the addition of [γ-32P]-ATP (10 Ci/mmol) to a final concentration of 20 µM. The reaction was incubated for 90 min at RT then quenched by adding 5 × SDS sample buffer. Samples were loaded onto a 15% SDS-PAGE. The radioactive gels were washed in water containing 2% (v/v) glycerol and gels were exposed to a phosphor screen (GE Healthcare) overnight. The screen was imaged using a Typhoon Trio+ imager (GE Healthcare).\n\nTo investigate the stability of the phosphorylated state of LytS, His-LytS at 10 µM was allowed to undergo autophosphorylation for 90 min by adding [γ-32P]-ATP (10 Ci/mmol) to a final concentration of 20 µM. Excess [γ-32P]-ATP was removed by desalting using the Zeba Spin Desalting column (Pierce, Thermo Scientific) equilibrated with PB. The reaction mixture was further incubated at room temperature and aliquots were removed at different time intervals and quenched by adding 5 × SDS sample buffer. Samples were loaded onto 15% SDS-PAGE and the gel was analyzed as described above.\n\nThe ability of LytS to phosphorylate LytR was examined as described earlier22. Briefly, His-LytS at 15 µM was phosphorylated for 90 min. Excess [γ-32P]-ATP was removed by desalting using the Zeba Spin Desalting column which was equilibrated with PB. Phosphorylated His-LytS (4 µM) was incubated with GST-LytR (10 µM) in the PB buffer at room temperature. Aliquots of 10 µL were removed at different time intervals and quenched by adding 10 µL of 5 × SDS-PAGE sample buffer. Samples were loaded onto a 15% SDS-PAGE. The radioactive gels were washed with water containing 2% (v/v) glycerol and gels were exposed to phosphor screen (GE Healthcare) overnight and imaged using a Typhoon Trio+ imager (GE Healthcare). The radioactive gels were stained by Coomassie blue dye. The phosphor images of the radioactive gels were quantified using NIH ImageJ software (Version 1.45s). Similar experiments were carried out using GST-LytR-D53A mutant and LytRN.\n\nTo investigate phosphorylation of LytR by small molecule phosphate donors, lithium potassium acetyl phosphate was used as described earlier22. Briefly, LytR at 10 µM or LytRN at 20 µM was equilibrated in PB20 buffer (PB: 50 mM Tris, pH 7.4, 50 mM KCl, 20 mM MgCl2) and phosphorylation was initiated by addition of lithium potassium acetyl phosphate to a final concentration of 50 mM. The reaction mixture was incubated at 37°C and 15 µL aliquots were removed and quenched by adding 5 × SDS sample buffer. The phosphorylated species were separated from unphosphorylated species using a 15% SDS-PAGE containing Acrylamide-pendant Phos-tag™ AAL-107 at 50 µmol/L (Wako chemical USA, inc., Cedarlane)23. The gels were stained by Coomassie blue dye. Band intensities of the phosphorylated species were quantified using NIH ImageJ and plotted against incubation time. These data were fitted to Equation 1 using Erithacus GraFit software (version 5.0.10) to determine the phosphorylation rate constants of LytR and LytRN by acetyl phosphate.\n\nTo investigate the effect of phosphorylation on oligomerization state of LytR or LytRN, each protein was phosphorylated by acetyl phosphate as described above. Unphosphorylated and phosphorylated samples of LytRN (10 µM, 20 µM and 40 µM) were loaded onto a 10% native-PAGE. The internal temperature of the buffer during the gel electrophoresis was maintained at 4°C. The gels were stained with Coomassie blue to visualize the protein bands. We analyzed phosphorylated and unphosphorylated LytRN (80 µM) also by size exclusion chromatography TSKgel G2000SWXL (7.8 × 300mm, 5 µm, TOSOH Biosciences LLC) on HPLC.\n\nTo assess the phosphatase activity of LytS, LytRN was phosphorylated by acetyl phosphate as described above. Excess acetyl phosphate was removed by the desalting column. LytRN-P (80 µM) was incubated with 5 µM of LytS at different time intervals, in the absence or presence of 200 µM ATP, at 37°C. Samples were quenched with native-PAGE loading buffer and loaded onto a 15% native-PAGE. Native-PAGE was stained with Coomassie blue to visualize the protein bands which were quantified by NIH ImageJ.\n\nFar UV circular dichroism (CD) spectra (200–260 nm) of LytR and LytRN were recorded using a Jasco J-180 instrument at 20°C. The buffer composition in these experiments was 20 mM Tris, 5 mM MgCl2 pH 8.0. Two spectra scans were averaged for the sample and the buffer. Later, buffer contribution was subtracted from each protein spectrum. To assess the thermal stability of LytR and LytRN, thermal melting of each protein was recorded by monitoring the change in the CD signal at 222 nm by ramping up the temperature from 20°C to 90°C at a rate of 3°C/min. Typically for these experiments, 20 µM of the respective protein was buffer exchanged into 10 mM sodium phosphate buffer at pH 7.4.\n\n\nResults\n\nThe predicted domain architectures of LytS and LytR are shown in Figure 1. LytS belongs to the family of LytS-YhcK multi-transmembrane domain bacterial receptors which carry at their intracellular C-terminal a GAF (cyclic Guanosine Monophosphate-specific phosphor-diesterases, Adenylyl cyclases and the FhlA proteins24) domain, and a kinase domain25. The amino acid analysis of LytS by InterPro (EMBL-EBI; available online at http://www.ebi.ac.uk/interpro/) predicted that this protein has five transmembrane regions (TMs), an extracellular NH2-terminus, and an intracellular GAF domain and a kinase domain. The intracellular kinase domain harbors the dimerization and histidine phosphotransfer (DHp) domain and the catalytic and ATP-binding (CA) domain.\n\nDomain organizations of LytS (P60612) and LytR (P60609) as predicted by InterPro (EMBL-EBI) (“TM” stands for transmembrane regions; “*” denotes the phosphorylation sites, His-390 in LytS and Asp-53 in LytR; “R” stands for receiver domain; “E”, stands for the effector domain).\n\nLytR consists of two domains, the conserved N-terminal receiver domain (LytRN) and the variable C-terminal DNA-binding domain referred to as the effector domain (LytRC). In general, the receiver domain of the RRs harbors a conserved Asp residue that undergoes a reversible phosphorylation by the conjugated HK26,27. The sequence analysis of LytR reveals that the receiver domain is homologous to the receiver domains of the OmpR/NarL protein families. Based on the sequence alignments with these RRs, we determined the phosphorylation site in LytR to be Asp-53. Sequence analysis of LytR also indicates that the DNA-binding domain is homologous to that found in the novel family of non-helix-turn-helix DNA-binding domains, known as LytTR14,15. This family of proteins consists of AlgR and AgrA transcription factors15 which are involved in regulation of important virulence factors in pathogenic bacteria28. These groups of effector domains are unique in their ability to bind to DNA and account for ~2.7% of all prokaryotic RRs28.\n\nThe cloning strategy of lytS aimed to clone the cytoplasmic region of LytS spanning the amino acids 355-584, which harbors the DHp and CA domains. The cytoplasmic domain of LytS was fused at the C-terminus of a six-histidine tag (calculated molecular mass of the His-LytS is 28,359 D). The (His)6-tag aided purification of LytS to homogeneity as assessed by SDS-PAGE.\n\nCloning of lytR (246 amino acids) led to the expression of LytR without tags or additional amino acids (calculated molecular mass 28,221 D). Expression of LytR was good but its purification was challenging. Conventional chromatographic methods failed, and it was evident that the actual isoelectric point (pI) was different from the theoretical one (pI ~5.68). We resorted to the use of ammonium sulfate precipitation to purify the protein. The protein precipitated out at 10% ammonium sulfate and the purity was assessed to be 80%. The protein was prone to aggregation at concentrations higher than 3 mg/mL. To facilitate purification and solubility of the protein, we cloned LytR fused to the COOH-terminus of GST. GST-LytR was purified to homogeneity by affinity chromatography.\n\nCloning of the receiver domain of LytR, LytRN, spanning amino acids 1-134, led to the expression of a soluble protein with a molecular mass of 15,028 D without additional amino acids or tags. The protein was expressed at a higher level than LytR or GST-LytR. Moreover the protein was purified by conventional chromatographic methods based on the theoretical value of pI ~4.44. The protein was very stable and soluble at concentrations as high as 10 mg/mL.\n\nThe thermal melting points of LytR and LytRN were measured to be 55°C and 70°C, respectively. The 15 degree difference in the thermal stabilities between these two proteins is an indication that the effector domain may destabilize the N-terminal domain in the context of the full-length protein.\n\nWe monitored the level of autophosphorylation of His-LytS at different time intervals and at different ATP concentrations (Figure 2, Dataset 1). The pseudo first-order rate constant of the autokinase activity of His-LytS was determined to be 0.030 ± 0.001 min-1. The autophosphorylation rate constant of LytS is smaller compared to the S. aureus cell wall damage sensing HK VraS (0.07 min-1)22, Enterococcus faecium vancomycin resistance factor HK VanS of (0.17 min-1)29 or S. aureus essential HK WalK (0.36 min-1)30. However, it is similar to the autophosphorylation rate constants for other HKs such as E. coli nitrate sensing HK NarQ (0.014 min-1)31, and E. coli citrate sensing HK DcuS (0.043 min-1)32. The binding affinity of LytS for ATP (Ks = 7.9 ± 0.6 µM) is higher in comparison to other kinase such as, VanS (KmATP = 620 ± 42 µM)29, VraS (KmATP = 230 ± 42 µM (Belcheva et al. unpublished data)) and WalK (KmATP = 130 µM)30.\n\n(A) His-LytS at 5 µM was incubated with [γ-32P]-ATP (100 µM) in PB at room temperature. Reaction was quenched at different time intervals and samples were analyzed by 15% SDS-PAGE. (B) Progress curve of His-LytS autophosphorylation. The quantified band intensities of phosphorylation were plotted against time. The data were fitted using Origin software to pseudo first order equation (1) to calculate the rate constant. Errors are the standard deviation from two independent trials (Dataset 1). (C) Stability of the phosphorylated His-LytS species. His-LytS at 5 µM was phosphorylated for 90 min in PB buffer (50 mM Tris, pH 7.4, 5 mM MgCl2) at room temperature. Excessive ATP was removed by desalting and stability was monitored over 3 hours at different time intervals. Samples were analyzed by 15% SDS-PAGE. All gels were exposed to phosphor-screen (GE Healthcare) overnight and imaged using a Typhoon Trio+ imager (GE Healthcare). The gel in panel (A) was also stained with Coomassie blue to view the protein bands.\n\nWe investigated phosphorylation of LytR through its cognate HK, LytS, and the small molecule phosphate donor, acetyl phosphate. Our efforts to investigate the phosphotransfer between His-LytS and LytR were hampered by the fact that the molecular masses of His-LytS and LytR were similar and this affected their separation by SDS-PAGE. To remove this obstacle, LytR was fused to GST which increased the molecular mass of LytR by 26 kD. When P32-labeled His-LytS was incubated with GST-LytR, we observed a time-dependent reduction in signal from P32-labeled His-LytS, which was associated with an increase in P32-labeling of GST-LytR (Figure 3A). The observed rate constant for the phosphotransfer process is 0.3 ± 0.1 min-1. When incubation of P32-labeled His-LytS was done in the presence of GST-LytRAsp55Asn, no reduction in signal from phosphorylated His-LytS was observed (Figure 3B). These experiments show that LytS is capable of phosphorylating LytR for as long as the phosphorylation site in LytR is available.\n\n(A) Phosphorylated His-LytS at 4 µM was incubated with GST-LytR at 10 µM in PB at room temperature. The reaction was quenched at various time intervals and samples were analyzed by 15% SDS-PAGE. (B) Similar reaction as shown in (A), performed with GST-LytRAsp53Ala. The reaction was quenched at various time intervals and samples were analyzed by 15% SDS-PAGE. Gels were exposed to phosphor screen (GE Healthcare) overnight and imaged (top gels) using a Typhoon Trio+ imager (GE Healthcare) followed with Coomassie blue staining (bottom gels).\n\nIncubation of LytR with a small molecule phosphate donor such as acetyl phosphate resulted in rapid phosphorylation of LytR (Figure 4A, Dataset 2). The observed phosphorylation rate constant for LytR was 0.6 ± 0.1 min-1. This rate is about 30-fold faster than phosphorylation of VraR by acetyl phosphate (0.022 min-1)22, or MtrA (0.014 min-1) and PrrA (0.028 min-1), 10-fold faster than DrrD (0.10 min-1), and comparable to PhoB (0.45 min-1)33. In the case of the stand-alone receiver domain, LytRN, the observed phosphorylation rate constant was 0.9 ± 0.2 min-1 (Figure 4B). The higher phosphorylation rate constant measured for the LytRN (1.5-fold compared to LytR) is another indication that the effector domain may perturb the receiver domain and very likely it does so through an interdomain interaction. Barbieri et al. recently reported a correlation between a higher phosphorylation rate constant for the receiver domains compared to the full-length RRs in cases where domains in RRs were engaged in interdomain interactions33.\n\n(A) LytR at 10 µM was phosphorylated by acetyl phosphate (50 mM) in PB for 1 h at 37oC. (B) Quantitative analysis of the data using NIH ImageJ (Dataset 2) The data were fitted using Origin software to pseudo first order equation (1) to calculate the rate constant. Errors are the standard deviation from two independent trials. (C) LytRN at 20 µM was phosphorylated by acetyl phosphate (50 mM) in PB buffer at 37oC and reactions were quenched at various time intervals. The phosphorylated proteins were separated from the unphosphorylated protein by 15% Phos-tag gel. The gels were stained with Coomassie blue to view the protein bands. (D) Quantitative analysis of the data using NIH ImageJ. The data were fitted using Origin software to pseudo first order equation (1) to calculate the rate constant. Errors are the standard deviation from two independent trials (Dataset 3).\n\nInvestigation of the oligomerization state of LytR was not possible through native-PAGE (Tris-Glycine, pH 8.3) as the protein was not resolved under this buffer condition. Instead, we analyzed the oligomerization state of the phosphorylated LytRN, which resolved well in native-PAGE. These experiments showed that phosphorylation of LytRN led to dimerization (Figure 5). These results can be used to predict the oligomerization state of phosphorylated LytR and it is very likely this protein dimerizes upon phosphorylation, and it does so at the receiver domain.\n\nLytRN and LytRN–P at 10 µM, 20 µM and 40 µM were analyzed by 15% native-PAGE and stained with Coomassie blue.\n\nThe propensity of LytRN to dimerize upon phosphorylation was used to monitor the phosphatase activity of LytS; dephosphorylation of LytRN will lead to disintegration of the dimer which can readily be monitored in a native-PAGE system. Indeed, incubation of the phosphorylated LytRN with LytS led to conversion of the dimer to monomer species indicating that LytS has phosphatase activity (Figure 6A, Dataset 4). Interestingly, the phosphatase activity of LytS was more prominent in the presence of ATP similar to the observations made with E. coli osmosensor HK EnvZ; this phenomenon was proposed to be due to the allosteric effect that binding of ATP to CA domain had on the phosphatase activity of the DHp domain of EnvZ34.\n\n(A) LytS at 5 µM was incubated with LytRN-P at 80 µM at different time intervals, in the absence or presence of 200 µM ATP, at 37°C. (B) The stability of phosphorylated LytRN-P at 37°C. (C) Time-dependence of the phosphatase activity of LytS in the absence of ATP (empty squares) or presence of ATP (solid squares) and autophosphatase activity of LytR (empty triangles). The data points were taken from the analyses of panels A and B using NIH ImageJ (Dataset 4).\n\nLytRN underwent slow dephosphorylation at 37°C (Figure 6B, Dataset 4). This is an indication that LytR has autophosphatase activity. However, the rate of auto-dephosphorylation of LytR is about 10% of the dephosphorylation rate by LytS (Figure 6C) hence, it may not be relevant in vivo.\n\n\n\n\nDiscussion\n\nLytSR is involved with sense-response to alterations of the cell electrical membrane potential due to cell membrane perturbations2,3. Its function is related to regulation of genes controlling cell apoptosis, autolysin activity and biofilm formation9,19. LytR regulates the lrgAB and cidABC operons7 whereby cid genes encode holin-like proteins that enhance murein hydrolysis activity and trigger cell lysis19 and antibiotic tolerance, while the lrg genes products encode antiholin-like proteins that inhibit these processes.\n\nTo the present day, molecular details and functionality of the LytSR signal transduction pathway have only been presumed. We undertook in vitro characterization of LytS and LytR and probed their involvement in the signal transduction process. Signal transduction processes mediated by TCSs involve two reversible phosphorylation-mediated processes, autophosphorylation of the HK and transfer of its phosphoryl group to the cognate RR. Quite often the role of HK is to control the phosphorylation level of RRs, which in turn regulates the transcriptional activity of RR. It does so by possessing phosphatase activity toward RR, in addition to the kinase activity13. The phosphorylation level of RRs, however, can also be regulated through phosphorylation by small molecule phosphate donors such as acetyl phosphate and the autophosphatase activity of RRs26.\n\nOur study demonstrates that the cytoplasmic domain of LytS has autokinase activity (k = 0.030 ± 0.001 min-1). The LytS phosphorylation rate constant is comparable to other HKs. The unusually low dissociation constant measured for ATP with LytS in comparison to other RRs, such as VraR, WalK, or VanS, suggests that the autophosphorylation efficiency for LytS is high and the kinase is well positioned to participate directly in the signaling process induced by changes in the cytoplasmic membrane electrical potential. The fast phosphotransfer process that we observed between LytS and LytR (0.3 min-1) suggests that any alteration in the cell membrane electrical potential sensed by LytS is efficiently transduced intracellularly.\n\nIt is well established that most RRs are also equipped with the ability to catalyze their own phosphorylation, independently of their cognate kinases, using endogenous low molecular weight phosphoryl group donors36. In fact, phosphorylation of RRs by low molecular weight phosphoryl group donors such as acetyl phosphate, carbamyl phosphate or phosphoramide appears to be more common than phosphorylation by non-cognate HKs35. Intracellular concentration of acetyl phosphate ranges from 1 mM to 3 mM in vivo, suggesting that this phosphate group donor is available in the cell in similar quantities as ATP33,35,36. Herein, we show that LytR undergoes rapid and quantitative phosphorylation by acetyl phosphate (k = 0.6 min-1). Further, phosphorylation of the receiver domain by acetyl phosphate leads to dimerization of this domain demonstrating that phosphorylation-induced activation of LytR involves formation of dimers at the receiver domain. The differences in the thermal denaturation and phosphorylation rates by acetyl phosphate of LyR and LytRN provide evidence that the effector domain has a destabilizing effect on the receiver domain, which could plausibly be due to an interdomain interaction.\n\nThe rapid phosphorylation of LytR by acetyl phosphate observed in our study (about 2-fold faster than phosphorylation by LytS) strongly suggests that this pathway is important in vivo. Interestingly, in vivo studies have demonstrated presence of two overlapping regulatory networks in regulation of the lrgAB operon20. One regulatory network responds to excess glucose metabolism and the other responds to changes in the cell membrane potential2. Induction of lrgAB in response to glucose metabolism was shown in vivo to rely on LytR2, however, metabolism of excess glucose does not lead to changes in the cytoplasmic membrane electrical potential1, hence it is less likely that signaling occurs through LytS in this case. The fast kinetics of LytR phosphorylation by acetyl phosphate makes this pathway an efficient signaling and regulatory mechanism of lrgAB in response to the glucose metabolism. Moreover, the phosphatase activity of LytS toward phosphorylated-LytR, which otherwise is stable during the cell division time, provides the regulatory means to shut-down this pathway when the glucose level in the medium goes down.\n\nIn summary, our study shows that LytSR can participate in two signal transduction pathways through two phosphorylation processes: phosphorylation of LytR by LytS and phosphorylation of LytR by acetyl phosphate (Figure 7). Further, our findings provide the molecular mechanism for the in vivo observation that regulation of lrgAB operon is LytR dependent, either in response to excess of glucose metabolism or perturbation of cell membrane electrical potential.\n\nOur data support two pathways of activation of LytR: through LytS as a result of perturbation of the membrane electric potential, and through acetyl phosphate as a result of accumulation of acetate during metabolism of excess glucose.\n\n\nData availability\n\nFigshare: Raw data for the role of acetyl phosphate in bypassing the cell membrane electrical potential sensor LytS doi: 10.6084/m9.figshare.133984337",
"appendix": "Author contributions\n\n\n\nKP designed, carried out the experiments, analyzed the data and revised the manuscript. DGK designed the project and prepared the manuscript. All authors have agreed to the final content of the manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThis work was funded in full by a grant to DGK from Natural Sciences and Engineering Research Council of Canada and in part by the Early Researcher Award from Ontario Ministry of Research and Innovation.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nWe thank Sivadarshini Pathmanathan for her assistance in analyzing the phosphatase activity of LytS.\n\n\nReferences\n\nPatton TG, Yang SJ, Bayles KW: The role of proton motive force in expression of the Staphylococcus aureus cid and lrg operons. 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PubMed Abstract | Publisher Full Text | Free Full Text\n\nSidote DJ, Barbieri CM, Wu T, et al.: Structure of the Staphylococcus aureus AgrA LytTR domain bound to DNA reveals a beta fold with an unusual mode of binding. Structure. 2008; 16(5): 727–735. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRice KC, Nelson JB, Patton TG, et al.: Acetic acid induces expression of the Staphylococcus aureus cidABC and lrgAB murein hydrolase regulator operons. J Bacteriol. 2005; 187(3): 813–821. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBayles KW: The biological role of death and lysis in biofilm development. Nat Rev Microbiol. 2007; 5(9): 721–726. PubMed Abstract | Publisher Full Text\n\nRice KC, Bayles KW: Molecular control of bacterial death and lysis. Microbiol Mol Biol Rev. 2008; 72(1): 85–109. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRice KC, Firek BA, Nelson JB, et al.: The Staphylococcus aureus cidAB operon: evaluation of its role in regulation of murein hydrolase activity and penicillin tolerance. J Bacteriol. 2003; 185(8): 2635–2643. PubMed Abstract | Publisher Full Text | Free Full Text\n\nYang SJ, Rice KC, Brown RJ, et al.: A LysR-type regulator, CidR, is required for induction of the Staphylococcus aureus cidABC operon. J Bacteriol. 2005; 187(17): 5893–5900. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPatton TG, Rice KC, Foster MK, et al.: The Staphylococcus aureus cidC gene encodes a pyruvate oxidase that affects acetate metabolism and cell death in stationary phase. Mol Microbiol. 2005; 56(6): 1664–1674. PubMed Abstract | Publisher Full Text\n\nBelcheva A, Golemi-Kotra D: A close-up view of the VraSR two-component system. A mediator of Staphylococcus aureus response to cell wall damage. J Biol Chem. 2008; 283(18): 12354–12364. PubMed Abstract | Publisher Full Text\n\nKinoshita E, Kinoshita-Kikuta E, Koike T: A single nucleotide polymorphism genotyping method using phosphate-affinity polyacrylamide gel electrophoresis. Anal Biochem. 2007; 361(2): 294–298. PubMed Abstract | Publisher Full Text\n\nCann MJ: Sodium regulation of GAF domain function. Biochem Soc Trans. 2007; 35(pt 5): 1032–1034. PubMed Abstract | Publisher Full Text\n\nAnantharaman V, Aravind L: Application of comparative genomics in the identification and analysis of novel families of membrane-associated receptors in bacteria. BMC genomics. 2003; 4(1): 34. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGao R, Mack TR, Stock AM: Bacterial response regulators: versatile regulatory strategies from common domains. Trends Biochem Sci. 2007; 32(5): 225–234. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGao R, Stock AM: Molecular strategies for phosphorylation-mediated regulation of response regulator activity. Curr Opin Microbiol. 2010; 13(2): 160–167. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGalperin MY: Telling bacteria: do not LytTR. Structure. 2008; 16(5): 657–659. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWright GD, Holman TR, Walsh CT: Purification and characterization of VanR and the cytosolic domain of VanS: a two-component regulatory system required for vancomycin resistance in Enterococcus faecium BM4147. Biochemistry. 1993; 32(19): 5057–5063. PubMed Abstract | Publisher Full Text\n\nClausen VA, Bae WH, Throup J, et al.: Biochemical characterization of the first essential two-component signal transduction system from Staphylococcus aureus and Streptococcus pneumoniae. J Mol Microbiol Biotechnol. 2003; 5(4): 252–260. PubMed Abstract | Publisher Full Text\n\nNoriega CE, Schmidt R, Gray MJ, et al.: Autophosphorylation and dephosphorylation by soluble forms of the nitrate-responsive sensors NarX and NarQ from Escherichia coli K-12. J Bacteriol. 2008; 190(11): 3869–3876. PubMed Abstract | Publisher Full Text | Free Full Text\n\nJanausch IG, Garcia-Moreno I, Unden G: Function of DcuS from Escherichia coli as a fumarate-stimulated histidine protein kinase in vitro. J Biol Chem. 2002; 277(42): 39809–39814. PubMed Abstract | Publisher Full Text\n\nBarbieri CM, Mack TR, Robinson VL, et al.: Regulation of response regulator autophosphorylation through interdomain contacts. J Biol Chem. 2010; 285(42): 32325–32335. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhu Y, Qin L, Yoshida T, et al.: Phosphatase activity of histidine kinase EnvZ without kinase catalytic domain. Proc Natl Acad Sci U S A. 2000; 97(14): 7808–7813. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMcCleary WR, Stock JB, Ninfa AJ: Is acetyl phosphate a global signal in Escherichia coli? J Bacteriol. 1993; 175(10): 2793–2798. PubMed Abstract | Free Full Text\n\nLukat GS, McCleary WR, Stock AM, et al.: Phosphorylation of bacterial response regulator proteins by low molecular weight phospho-donors. Proc Natl Acad Sci U S A. 1992; 89(2): 718–722. PubMed Abstract | Free Full Text\n\nPatel K, Golemi-Kotra D: Raw data for the role of acetyl phosphate in bypassing the cell membrane electrical potential sensor LytS. Figshare. 2015. Data Source"
}
|
[
{
"id": "12500",
"date": "24 Feb 2016",
"name": "Taeok Bae",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn Staphylococcus aureus, transcription of the lrgAB operon is positively regulated by the LytSR two component system. Previous studies demonstrated that LytS, the sensor histidine kinase, is activated by two different kinds of signals: the loss of membrane potential and glucose/acetic acid. In this paper, using purified proteins, the authors assessed the enzymatic activities of LytS and phosphorylation of LytR by LytS and acetyl phosphate. The autophosphorylation of LytS was rather slow, and the LytS-P was stable. The phosphotransfer from LytS-P to LytR was very slow while the LytR phosphorylation by acetyl phosphate was very efficient. When phosphorylated, the receptor domain of LytR formed a dimer. The phosphatase activity of LytS was also demonstrated. Based on these results, the authors concluded that acetyl phosphate is the signal transducer from the glucose signal.This manuscript is well-written and, overall, experiments are properly conducted. However, I have concerns on the interpretation of the experiment results. Those concerns are listed below.Abstract“Herein, we show that LytS has autokinase activity and can catalyze a fast phosphotransfer reaction, with 50% of its phosphoryl group lost within 1 minute of incubation with LytR.”: Indeed, in Fig. 3, the His-LytS-P signal at 1 min was significantly reduced as compared with that at 0 min. However, the reduction was not accompanied by increase of GST-LytR-P, indicating that the disappeared phosphoryl group was not transferred to GST-LytR. In addition, from 0.5 min to 90 min, the decrease of His-LytS-P signal was very slow. Therefore, the phosphotransfer reaction appears very slow in the condition employed.Introduction3rd paragraph: The references 20 and 21 do NOT say that CidR is activated by acetyl phosphate. Ref 20 shows that the acetate (glucose) activates the transcription of cidABC operon through CidR. Ref 21 reports that CidC is a pyruvate oxidase.The last paragraph: The in vitro phosphorylation of LytR by acetyl phosphate does not guarantee that acetyl phosphate phosphorylates LytR in vivo. To my understanding, acetyl phosphate can phosphorylate many response regulators whose phosphorylation is not affected by carbohydrate metabolism.Materials and methods2nd paragraph, 4th line from bottom: … for Sick Kids, Toronto, Canada. -> ..for Sick Kids, Toronto, Canada).Page 5, 1st paragraph, 2nd line from bottom: delete “for” after 25C.ResultsPage 7, 1st sentence: “cognate” might be a better word than “conjugated”.Page 8, Figure 3: The results, in particular GST-LytR-P signals, are not clear. Nonetheless, the phosphotransfer from LytS-P to LytR is very slow: even at 90 min, a significant amount of His-LytS-P still remains. The authors reported that the observed rate constant for the reaction is 0.3 min-1. Although I am not an expert in biochemistry, the rate constant seems too high for the slow reaction. In addition, I wonder how the rate constant was calculated: was it based on the phosphorylation of GST-LytR or dephosphorylation of His-LytS-P?Page 8, the last sentence: (Figure 4B) -> (Figure 4C & D).Page 8 & Figure 4: The observed phosphorylation rate constant for LytR was 0.6 min-1 while it was 0.9 min-1 for LytRN. However, Fig. 4A shows that a majority of LytR was phosphorylated at 1 min while less than half of LytRN was phosphorylated at the time point (Fig. 4C). I understand that two different concentrations (10 uM for LytR and 20 uM for LytRN) were used. But still, to me, the LytR seems to be phosphorylated faster than LytRN.Page 9, last sentence and Page 10, the first sentence: The authors say “the phosphatase activity of LytS was more prominent in the presence of ATP..”. However, to me, the dephosphorylation rates are very similar, regardless of ATP (Fig. 6A). I wonder whether the difference shown in Fig. 6C at 5 min is statistically significant.DiscussionPage 10 (right column), top sentence: The authors say “The fast phosphotransfer process that we observed between LytS and LytR (0.3 min-1) suggests that any alteration in the cell membrane electrical potential sensed by LytS is efficiently transduced intracellularly.” In my view, the phosphotransfer process is rather slow, and the rate constant (0.3 min-1) might be miscalculated. If I understand the rate constant correctly, 30% of LytR would be phosphorylated within 1 min (or 30% of LytS-P will be dephosphorylated within 1 min?). Nonetheless, Fig. 3A shows that either reaction does not proceed that fast.Page 10 (right column), the second paragraph from bottom: The authors say “The rapid phosphorylation of LytR by acetyl phosphate observed in our study (about 2-fold faster than phosphorylation by LytS) strongly suggests that this pathway is important in vivo.” Although I also think it is likely, the in vitro phosphorylation of LytR by acetyl phosphate cannot serve as a definitive evidence for the in vivo phosphorylation of LytR by acetyl phosphate. To provide direct evidence, the authors can grow wild type and the mutants of pta (phosphate acetyltransferase) and ackA (acetate kinase) in the presence of glucose; then they can compare the transcript levels of the lrgAB operon. Since Pta synthesizes acetyl phosphate, no acetyl phosphate will be present in the pta mutant. On the other hand, ackA is converting acetyl phosphate into ATP; therefore, in the ackA mutant, the level of acetyl phosphate will be higher than that in wild type. If acetyl phosphate is indeed the in vivo mediator of the glucose signal, the transcript level of lrgAB will be lower in the pta mutant while higher in the ackA mutant,as compared with wild type cells.Page 10 (right column), the second paragraph from bottom: The authors used the reference 20 to introduce two different regulation mechanism of the lrgAB operon. However, the reference 20 is about the regulation of cidABC operon by CidR. I think the reference 1 is more appropriate.Fig. 7. The model.To me, the following model fits better to the data presented in the paper.1. No glucose (nor acetate), full membrane potential: In this condition, LytS will have a net phosphatase activity due to slow autokinase activity (Fig. 2A), very inefficient phosphotransferase activity (Fig. 3A), and relatively higher phosphatase activity (Fig. 6), resulting in a low expression of lrgAB.2. No glucose, loss of membrane potential (e.g., gramicidin, CCCP etc): The loss of membrane potential will activate the kinase activity of LytS, converting LytS from a phosphatase to kinase. The level of LytR-P will increase, resulting in higher expression of lrgAB.3. Glucose, full membrane potential: The efficient phosphorylation of LytR by acetyl phosphate will overcome the phosphatase activity of LytS, resulting in higher expression of lrgAB.4. Glucose, loss of membrane potential (e.g., gramicidin, CCCP etc): LytR will be phosphorylated by both LytS and acetyl phosphate, resulting in maximal expression of lrgAB.",
"responses": [
{
"c_id": "1860",
"date": "22 Mar 2016",
"name": "Dasantila Golemi-Kotra",
"role": "Author Response",
"response": "Reviewer 2We are very thankful to the reviewer’s comments and suggestions. We have addressed them point-by-point below: In Staphylococcus aureus, transcription of the lrgAB operon is positively regulated by the LytSR two component system. Previous studies demonstrated that LytS, the sensor histidine kinase, is activated by two different kinds of signals: the loss of membrane potential and glucose/acetic acid. In this paper, using purified proteins, the authors assessed the enzymatic activities of LytS and phosphorylation of LytR by LytS and acetyl phosphate. The autophosphorylation of LytS was rather slow, and the LytS-P was stable. The phosphotransfer from LytS-P to LytR was very slow while the LytR phosphorylation by acetyl phosphate was very efficient. When phosphorylated, the receptor domain of LytR formed a dimer. The phosphatase activity of LytS was also demonstrated. Based on these results, the authors concluded that acetyl phosphate is the signal transducer from the glucose signal.This manuscript is well-written and, overall, experiments are properly conducted. However, I have concerns on the interpretation of the experiment results. Those concerns are listed below.Abstract“Herein, we show that LytS has autokinase activity and can catalyze a fast phosphotransfer reaction, with 50% of its phosphoryl group lost within 1 minute of incubation with LytR.”: Indeed, in Fig. 3, the His-LytS-P signal at 1 min was significantly reduced as compared with that at 0 min. However, the reduction was not accompanied by increase of GST-LytR-P, indicating that the disappeared phosphoryl group was not transferred to GST-LytR. In addition, from 0.5 min to 90 min, the decrease of His-LytS-P signal was very slow. Therefore, the phosphotransfer reaction appears very slow in the condition employed.When comparing panels A and B of Figure 3 (top figures), it is clear that majority of phosphor-transfer, as with any other histidine kinase, occurs within 1 min, followed by a slow decrease in phosphor-signal of LytS-P as LytR undergoes dephosphorylation (by LytS) and then, probably, phosphorylated back by LytS-P. We acknowledge that the LytR-P band is faint under the current quality of the picture in this print.The experimental data in Fig3A, the dephosphorylation of LytS-P, were fitted into first-order rate kinetics to determine the rate constant of the phosphor-transfer. However, a quick view at the phosphor image (although it is only an estimation method) (Fig 3A top) shows that in about 1 min, 50% of the 32P-signal is lost from LytS-P. Dephosphorylation of LytS follows first-order rate kinetics, hence, t1/2 = ln2/k (where t1/2 is the time that is takes for 50% of the reaction to complete, and k is the observed first-order rate constant), then k = ln2/t1/2, from which one can readily determine the k value.Introduction3rd paragraph: The references 20 and 21 do NOT say that CidR is activated by acetyl phosphate. Ref 20 shows that the acetate (glucose) activates the transcription of cidABC operon through CidR. Ref 21 reports that CidC is a pyruvate oxidase.Ref. 21 shows among others that cidABC operon is involved in generation of acetate in cell under high content of glucose, and Ref 20 shows that CidR regulates the cidABC operon in response to accumulation of acetate at high concentrations of glucose. It is known that (Ref 35 in the discussion) synthesis of acetyl phosphate from acetate and ATP are reversible processes and the enzymes that catalyse these reactions, are encoded by genes (pta and ackA) that are nearly constitutive. In addition, it is known that levels of acetyl phosphate vary with the carbon source in the growth medium (Ref 35). We have made the connection here that the loner response regulator CidR (it is not part of a two-component signal transduction) is activated by acetate through acetyl phosphate. However, we have replaced “acetyl phosphate” with “acetate” as to remain closer to the results in Refs. 20 and 21.The last paragraph: The in vitro phosphorylation of LytR by acetyl phosphate does not guarantee that acetyl phosphate phosphorylates LytR in vivo. To my understanding, acetyl phosphate can phosphorylate many response regulators whose phosphorylation is not affected by carbohydrate metabolism.This is a good point. It is true that acetyl phosphate is present in the cell. The notion that it could serve as a phosphorylation agent in the response regulator proteins it may seem to contradict the working of two-component systems. However, the kinetics of phosphorylation of response regulators by their cognate kinases and acetyl phosphate will determine whether phosphorylation by acetyl phosphate is relavent in vivo. In the case of LytR, our study shows that phosphorylation by acetyl phosphate is faster than phosphorylation by LytS (and faster than phosphorylation of other response regulator). Hence, it is likely to play a role in vivo. A recent paper by Lehman et al shows that our findings have correctly predicted what happens in vivo.Materials and methods2nd paragraph, 4th line from bottom: … for Sick Kids, Toronto, Canada. -> ..for Sick Kids, Toronto, Canada).Corrected.Page 5, 1st paragraph, 2nd line from bottom: delete “for” after 25C.Corrected.ResultsPage 7, 1st sentence: “cognate” might be a better word than “conjugated”.Corrected.Page 8, Figure 3: The results, in particular GST-LytR-P signals, are not clear. Nonetheless, the phosphotransfer from LytS-P to LytR is very slow: even at 90 min, a significant amount of His-LytS-P still remains. The authors reported that the observed rate constant for the reaction is 0.3 min-1. Although I am not an expert in biochemistry, the rate constant seems too high for the slow reaction. In addition, I wonder how the rate constant was calculated: was it based on the phosphorylation of GST-LytR or dephosphorylation of His-LytS-P?The rate constant of phosphotransfer from LytS to LytR is 0.3 min-1. It was measured from monitoring the loss of P32-signal from LytS-P in Figure 3A (LytR-P signal is relatively low to be measured accurately). In comparison to the phosphorylation by acetyl phosphate, this process is slower, indeed.Page 8, the last sentence: (Figure 4B) -> (Figure 4C & D).Page 8 & Figure 4: The observed phosphorylation rate constant for LytR was 0.6 min-1 while it was 0.9 min-1 for LytRN. However, Fig. 4A shows that a majority of LytR was phosphorylated at 1 min while less than half of LytRN was phosphorylated at the time point (Fig. 4C). I understand that two different concentrations (10 uM for LytR and 20 uM for LytRN) were used. But still, to me, the LytR seems to be phosphorylated faster than LytRN.We have shown one representative gel for each case. The data, obtained from quantification of the band intensities are provided in the datasets 2 and 3. These data are grafted in Figs 4B and D. Although from the gel it seems as if that at 0.5 min the signal for LytR-P is higher than LytRN-P, overall the fitting of all the date points shows that for LytRN-P the signal increases faster when considering all the data points.Page 9, last sentence and Page 10, the first sentence: The authors say “the phosphatase activity of LytS was more prominent in the presence of ATP..”. However, to me, the dephosphorylation rates are very similar, regardless of ATP (Fig. 6A). I wonder whether the difference shown in Fig. 6C at 5 min is statistically significant.To provide objectivity on analysing these data, we have plotted the data in Fig. 6C. To us it was interesting that others have observed similar phenomenon as we did. The data are reproducible (but we only have three different trials to comment on statistically significance). Whether it has any relevance in vivo, it needs to be investigated further.DiscussionPage 10 (right column), top sentence: The authors say “The fast phosphotransfer process that we observed between LytS and LytR (0.3 min-1) suggests that any alteration in the cell membrane electrical potential sensed by LytS is efficiently transduced intracellularly.” In my view, the phosphotransfer process is rather slow, and the rate constant (0.3 min-1) might be miscalculated. If I understand the rate constant correctly, 30% of LytR would be phosphorylated within 1 min (or 30% of LytS-P will be dephosphorylated within 1 min?). Nonetheless, Fig. 3A shows that either reaction does not proceed that fast.The experimental data in Fig3A, the dephosphorylation of LytS-P, were fitted into first-order rate kinetics. However, a quick view at the phosphor image shows that in about 1 min, 50% of the 32P-signal is lost from LytS-P. Dephosphorylation of LytS follows first-order rate kinetics, hence, t1/2 = ln2/k (where t1/2 is the time that is takes for 50% of the reaction to complete, and k is the observed first-order rate constant), k = ln2/t1/2. One can estimate the value of k from this single data point.Page 10 (right column), the second paragraph from bottom: The authors say “The rapid phosphorylation of LytR by acetyl phosphate observed in our study (about 2-fold faster than phosphorylation by LytS) strongly suggests that this pathway is important in vivo.” Although I also think it is likely, the in vitro phosphorylation of LytR by acetyl phosphate cannot serve as a definitive evidence for the in vivo phosphorylation of LytR by acetyl phosphate. To provide direct evidence, the authors can grow wild type and the mutants of pta (phosphate acetyltransferase) and ackA (acetate kinase) in the presence of glucose; then they can compare the transcript levels of the lrgAB operon. Since Pta synthesizes acetyl phosphate, no acetyl phosphate will be present in the pta mutant. On the other hand, ackA is converting acetyl phosphate into ATP; therefore, in the ackA mutant, the level of acetyl phosphate will be higher than that in wild type. If acetyl phosphate is indeed the in vivo mediator of the glucose signal, the transcript level of lrgAB will be lower in the pta mutant while higher in the ackA mutant,as compared with wild type cells.We agree. The recent work by Lehman et al. have carried out the above experiments (Ref 37 in the new version of manuscript).Page 10 (right column), the second paragraph from bottom: The authors used the reference 20 to introduce two different regulation mechanism of the lrgAB operon. However, the reference 20 is about the regulation of cidABC operon by CidR. I think the reference 1 is more appropriate. Yes, that is correct.Fig. 7. The model.To me, the following model fits better to the data presented in the paper.1. No glucose (nor acetate), full membrane potential: In this condition, LytS will have a net phosphatase activity due to slow autokinase activity (Fig. 2A), very inefficient phosphotransferase activity (Fig. 3A), and relatively higher phosphatase activity (Fig. 6), resulting in a low expression of lrgAB.2. No glucose, loss of membrane potential (e.g., gramicidin, CCCP etc): The loss of membrane potential will activate the kinase activity of LytS, converting LytS from a phosphatase to kinase. The level of LytR-P will increase, resulting in higher expression of lrgAB.3. Glucose, full membrane potential: The efficient phosphorylation of LytR by acetyl phosphate will overcome the phosphatase activity of LytS, resulting in higher expression of lrgAB.4. Glucose, loss of membrane potential (e.g., gramicidin, CCCP etc): LytR will be phosphorylated by both LytS and acetyl phosphate, resulting in maximal expression of lrgAB. We agree. Ref. 1 study supports the above models, in the addition to the recent work by Lehman et al. (Ref 37 in the new version of the manuscript)."
}
]
},
{
"id": "12502",
"date": "07 Mar 2016",
"name": "Kenneth W Bayles",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe authors of this paper sought to further characterize the signal mechanism of the Staphylococcus aureus LytSR two-component system. Previous studies have identified two signals that LytSR responds to: dissipation of membrane potential and excess glucose. Using purified protein, the authors characterize the kinetics of the autophosphorylation of LytS and the phosphorylation of LytR by LytS and acetyl-phosphate. The findings include a higher first-order rate constant for the phosphorylation of LytR by acetyl-phosphate as compared to its cognate kinase, LytS. In addition, the first-order rate constant of LytS autophosphorylation indicates a slow reaction as compared to other kinases. It was also demonstrated that LytR forms a dimer once phosphorylated, that LytS has phosphatase activity which is much more efficient that the auto-dephosphorylation of LytR.The results of the paper confirm and add greater insight into the molecular signaling mechanism of LytSR as previously described by Lehman et al, 2015. Overall, manuscript is well written and the experiments nicely executed. However, as can be seen from the comments below, the primary concern is that the authors seemed to have completely missed the work of Lehman et al, 2015, which describes much of what is presented in the current manuscript. Thus, the authors should include references to this work as indicated below.AbstractThe closing statement of the abstract seems to be a bit overstated as this is not the “first time” these results have been generated. Indeed, very similar results were presented by Lehman et al 2015 that acetyl-phosphate is responsible for the LytS-independent phosphorylation of LytR. In fact, the Lehman et al paper goes further using in vivo studies of mutants affecting acetyl-phosphate levels to show that under conditions of excess glucose acetyl-phosphate contributes to the signaling of LytSR.IntroductionParagraph 3: The authors state “both operons were also shown to be induced by carbohydrate metabolism and proposed to be regulated through a CidR-dependent signaling pathway20.” This is an inaccurate reference, as cidABC has only been shown to be regulated by CidR, whereas lrgAB expression is dependent on LytSR.Paragraph 3: The authors should include a reference to the Lehman et al 2015 paper, which followed up the work performed by Sharma et al (from the same lab). As stated above, the Lehman et al 2015 paper demonstrated that acetyl-phosphate does influence LytS-independent phosphorylation of LytR. Thus, the statement that the “molecular basis for this observation remains obscure” (referring to the Sharma et al. paper) is misleading.Paragraph 4: The authors state “Our study shows that LytSR is capable of mediating signaling either through LytS in response to cell membrane electrical potential or through LytR in response to carbohydrate metabolism.” This is overstated as there were no experiments to demonstrate this conclusion.ResultsParagraph 2: It was published by Brunskill and Bayles 1996 that Asp-53 is the likely site of LytR phosphorylation. This observation was confirmed in Lehman et al. 2015.DiscussionParagraph 1: LytR does not regulate the cidABC operon as stated.Paragraphs 2 and 5: See Lehman et al 2015 which characterized the LytSR signal transduction pathway in vitro and in vivo.",
"responses": [
{
"c_id": "1859",
"date": "22 Mar 2016",
"name": "Dasantila Golemi-Kotra",
"role": "Author Response",
"response": "We are very thankful to the reviewer’s comments and suggestions. We have addressed them point-by-point below:The authors of this paper sought to further characterize the signal mechanism of the Staphylococcus aureus LytSR two-component system. Previous studies have identified two signals that LytSR responds to: dissipation of membrane potential and excess glucose. Using purified protein, the authors characterize the kinetics of the autophosphorylation of LytS and the phosphorylation of LytR by LytS and acetyl-phosphate. The findings include a higher first-order rate constant for the phosphorylation of LytR by acetyl-phosphate as compared to its cognate kinase, LytS. In addition, the first-order rate constant of LytS autophosphorylation indicates a slow reaction as compared to other kinases. It was also demonstrated that LytR forms a dimer once phosphorylated, that LytS has phosphatase activity which is much more efficient that the auto-dephosphorylation of LytR.The results of the paper confirm and add greater insight into the molecular signaling mechanism of LytSR as previously described by Lehman et al, 2015. Overall, manuscript is well written and the experiments nicely executed. However, as can be seen from the comments below, the primary concern is that the authors seemed to have completely missed the work of Lehman et al,2015, which describes much of what is presented in the current manuscript. Thus, the authors should include references to this work as indicated below.AbstractThe closing statement of the abstract seems to be a bit overstated as this is not the “first time” these results have been generated. Indeed, very similar results were presented by Lehman et al 2015 that acetyl-phosphate is responsible for the LytS-independent phosphorylation of LytR. In fact, the Lehman et al paper goes further using in vivo studies of mutants affecting acetyl-phosphate levels to show that under conditions of excess glucose acetyl-phosphate contributes to the signaling of LytSR.To acknowledge the study by Lehman et al. we have included this reference in the new version of the manuscript. We have removed “first time” from abstract as to not divert the attention from the essence of this study.IntroductionParagraph 3: The authors state “both operons were also shown to be induced by carbohydrate metabolism and proposed to be regulated through a CidR-dependent signaling pathway20.” This is an inaccurate reference, as cidABC has only been shown to be regulated by CidR, whereas lrgAB expression is dependent on LytSR.Paragraph 3 has been modified now to address the reviewers concerns. Of note, it is proposed in several papers that CidR is involved in regulation of both operons. We have cited the work by Patton et al. 2006. The figure 6 in this work indicates the proposed model. We have replaced Ref 20 with Patton et al. report. We have also added the work by Yang et al 2006.Paragraph 3: The authors should include a reference to the Lehman et al 2015 paper, which followed up the work performed by Sharma et al (from the same lab). As stated above, the Lehman et al 2015 paper demonstrated that acetyl-phosphate does influence LytS-independent phosphorylation of LytR. Thus, the statement that the “molecular basis for this observation remains obscure” (referring to the Sharma et al. paper) is misleading.We have included Lehman et al. paper in the new version of the manuscript.Paragraph 4: The authors state “Our study shows that LytSR is capable of mediating signaling either through LytS in response to cell membrane electrical potential or through LytR in response to carbohydrate metabolism.” This is overstated as there were no experiments to demonstrate this conclusion.We have been very careful with the use of the language here. We wrote that out study shows that “LytSR is capable of mediating signaling….”. Indeed, autophosphorylation activity of kinase LytS, indicates that LytS is capable of participating directly (with no need for accessary) in signal transduction, and fast phosphorylation of LytR by acetyl phosphate indicates that LytR is capable of participating in signal transduction independently of LytS.ResultsParagraph 2: It was published by Brunskill and Bayles 1996 that Asp-53 is the likely site of LytR phosphorylation. This observation was confirmed in Lehman et al. 2015. Because the phosphorylation site in all response regulators is conserved, the purpose of mutating Asp53 to Ala in this study was to confirm that signal can be transduced from LytS to LytR as an act of phosphotransfer between LytS and LytR. Kindly refer to Figure 3.DiscussionParagraph 1: LytR does not regulate the cidABC operon as stated.We agree. We have removed this statement.Paragraphs 2 and 5: See Lehman et al 2015 which characterized the LytSR signal transduction pathway in vitro and in vivo.We have recognized the work my Lehman et al. in the new version of the manuscript."
}
]
}
] | 1
|
https://f1000research.com/articles/4-79
|
https://f1000research.com/articles/5-370/v1
|
18 Mar 16
|
{
"type": "Review",
"title": "Epileptogenesis in neurocutaneous disorders with focus in Sturge Weber syndrome",
"authors": [
"Anna Pinto",
"Mustafa Sahin",
"Phillip L. Pearl",
"Anna Pinto",
"Mustafa Sahin"
],
"abstract": "Epilepsy is a major morbidity in Sturge Weber syndrome, a segmental vascular neurocutaneous disorder classically associated with facial angiomas, glaucoma, and leptomeningeal capillary-venous type vascular malformations. The extent of the latter correlates with neurological outcome. Post-zygotic mosaicism for the activating mutation p.R183Q of the GNAQ gene has been identified as the major cause. GNAQ encodes for an alpha subunit of a heterotrimeric G protein critical to blood vessel development. The earlier the timing of the mutation in development, the more severe the involvement, e.g. from isolated port-wine stains to the full syndrome. The strongest predictors of adverse outcomes are MRI and the presence of angiomas involving any part of the forehead, delineated inferiorly from the outer canthus of the eye to the top of the ear, and including the upper eyelid. The neurological course may be progressive and the typical constellation of symptoms is focal onset seizures, hemiparesis, headache, stroke-like episodes, behavior problems, intellectual disability, and visual field deficits. Antiseizure medications are effective in about half of patients. The presence of localized seizures, focal neurological deficits, and drug resistant epilepsy indicate epilepsy surgical evaluation. Earlier seizure onset, i.e. before six months of age, is associated with a more severe course with significant residual deficits. Factors contributing to epileptogenesis include decreased brain tissue perfusion due to abnormal venous drainage, anoxic injury contributing to cerebral calcification, breakdown of the blood-brain barrier, and the presence of developmental cortical malformations. Pre-symptomatic prophylactic treatment may be a future option to modify the course of the disease including the associated epileptogenesis.",
"keywords": [
"epilepsy",
"Sturge Weber syndrome",
"seizures",
"epileptogenesis",
"neurocutaneous syndromes"
],
"content": "Introduction\n\nThe phakomatoses or neurocutaneous syndromes comprise a heterogeneous group of diseases that are mostly hereditary and characterized by the association of skin lesions with a variety of central and/or peripheral nervous system manifestations. Of the common phakomatoses, tuberous sclerosis and Sturge-Weber syndrome (SWS) feature epilepsy as a major morbidity to a complex phenotype of variable severity. SWS is a segmental vascular neurocutaneous disorder classically associated with facial angiomas known as port-wine stains, glaucoma associated with vascular ocular abnormalities, and leptomeningeal capillary-venous type vascular malformations. The extent of the latter correlates with the neurological outcome.\n\nRecent groundbreaking research identified a somatic activating mutation of the gene GNAQ as the likely cause of the majority of cases of SWS as well as non-syndromic port-wine stains. Interestingly, the timing of the somatic mutation in GNAQ during development likely impacts the clinical phenotype1.\n\nThe neurological manifestations in SWS are often progressive. Brain involvement is common with the capillary malformation causing progressive epilepsy and cerebral atrophy. The extent of the capillary malformation is correlated with the severity of seizures, extent of atrophy, and cognitive outcome. The pathophysiological processes leading to epileptogenesis and atrophy are not entirely known. This review outlines possible mechanisms of epileptogenesis in SWS2.\n\n\nPathophysiology\n\nA somatic activating mutation in the GNAQ (p.R183Q) gene was identified in the affected skin of individuals with non-syndromic port-wine stains and in SWS patients1. Thus, post-zygotic mosaicism for this GNAQ mutation has been described as the major cause of SWS.\n\nGNAQ encodes Gαq, an alpha subunit of the heterotrimeric G-protein that links G-protein-coupled receptors to activation of phospholipase C (PLC), transient increases in cytosolic calcium, and activation of Rac and Rho. The arginine (R) residue at position 183 in Gαq is a conserved amino acid in the GTP-binding pocket. R183Q mutation leads to a decrease in function of the GTPase and to constitutive activation of downstream effector pathways. Several of the G-protein-coupled receptors linked to Gαq, such as Gβ and Gγ subunits, are critical to blood vessel development and function; therefore, the abnormal signaling may result in vascular malformations3.\n\nGαq effectors increase downstream signaling through the RAS signaling pathway (Figure 1), and this is an implicated mechanism to explain the increased cell proliferation and inhibition of apoptosis in the affected skin and leptomeningeal capillary malformation samples in patients with SWS. The cell of origin affected by the mutation is not yet known4,5. Recent research showed that endothelial cells in capillary malformations are enriched for GNAQ mutations and are likely responsible for the pathophysiology underlying capillary malformations6. It is likely that the mutation occurs earlier in development in SWS than in isolated port-wine stains, thus affecting an earlier progenitor with wider potential downstream effects. Somatic mutations in GNAQ at other amino acids are also seen in uveal melanoma and more recently in the extended spectrum of clinical presentation from phakomatosis pigmentovascularis (PPV) to extensive dermal melanocytosis7. Based on the diversity of conditions and spectrum of severity, it seems that the mutation occurring at different times in development will influence the phenotype and severity of the condition. Microscopic examination of SWS brain tissue shows deposition of calcium in the cortex, hypoplastic blood vessels, gliosis, and sometimes loss of neurons or focal cortical dysgenesis8,9. The current evidence suggests that observed malformation of brain development in patients with SWS is likely secondary to abnormal vascular development concomitant to the cortical developmental stages.\n\n\nClinical considerations on neurological aspects of SWS\n\nThe clinical course of SWS is variable and can be devastating. In a cohort of 192 patients with facial port-wine stains, a strong predictor of adverse outcomes was an angioma involving any part of the forehead, delineated at its inferior border by a line joining the outer canthus of the eye to the top of the ear, and including the upper eyelid10. Abnormal MRI was a better predictor of all clinical adverse outcome measures than port-wine stain distribution, although for practical reasons guidelines based on clinical phenotype are proposed. Typically, the progressive neurological problems evolve over time causing medication-resistant epilepsy and brain atrophy. The constellation of symptoms is characterized by focal onset of seizures, hemiparesis, headache, stroke-like episodes, behavioral problems, intellectual disability, and visual field defects.\n\nSeizures occur in 75–80% of all SWS patients and in over 90% of patients with bilateral involvement. Onset of seizures occurs in 75% of children before 1 year of age, 86% by 2 years of age, and 95% by the age of 5 years. Medications are effective in preventing seizures in approximately 50% of patients. Patients with localized seizures, focal neurological deficits, and drug-resistant epilepsy should be considered for epilepsy surgery11,12.\n\nBased on the revised International League Against Epilepsy (ILAE) classification, the most common seizure type is focal seizures with an observable motor component and without impairment of awareness. Seizures with variable degrees of impairment of consciousness are also frequently observed along with autonomic features and evolution to bilateral convulsive events. Seizures can be subtle, and prompt recognition of an epileptic episode is important because prolonged seizures and status epilepticus are commonly seen13.\n\nAbout 30% of cases may have onset of seizures during febrile episodes, and there is an increased susceptibility for fever-induced seizures at any age14. Apneic seizures have been associated with SWS and present in nearly half of drug-resistant patients who require epilepsy surgery (Pinto et al., in press). Unusual seizure types such as ictal laughter have also been described in SWS patients15. Children with epilepsy due to focal lesions can develop secondary bilateral synchrony. There are also reports of myoclonic astatic seizures, infantile spasms including asymmetric features, and prolonged post-ictal paralysis15,16.\n\nSome patients with SWS may present with initial clusters of frequent epileptic events and then remain seizure-free for several months or years. Remissions may last several months before recurrence occurs. The variable course of the epilepsy renders surgical disposition difficult, and the trajectory of associated developmental progress or decline is often a deciding factor14.\n\nA descriptive study of 77 children and adults with epilepsy secondary to SWS disclosed a dichotomy based on age at seizure onset. Early onset patients (onset of seizures before 6 months of age) had a severe early course with significant residual deficits, while late-onset patients (onset of seizures after 6 months of age) did better. Focal cerebral atrophy worsened in early onset cases. The course of the epilepsy in the late-onset cohort stabilized after 5 years of age in most cases. The authors described that aspirin use correlated with stable course of epilepsy in six patients. Leptomeningeal enhancement appears to increase on imaging studies during acute events before returning to baseline, suggesting that extent of disease is probably best judged during the interictal state. The use of aspirin routinely is still controversial17,18.\n\n\nElectroencephalography in SWS\n\nThe typical electroencephalogram (EEG) in patients with SWS consists of asymmetric background frequencies and voltages19. A large cohort study with emphasis on EEG evolution analyzed 81 EEGs from 44 children and adults with SWS. This study documented the evolutional changes that have been previously described. Recordings evolve to show asymmetric slowing over the course of 1 year; 2 to 3 years later, interictal epileptiform activity with focal sharp waves and increasingly frequent spike discharges appear. One limitation of the study was the potential modification of the EEG pattern due to modern anti-seizure medications or treatment with low-dose aspirin. The detailed EEG analysis did not, however, show a correlation between the EEG severity score and clinical function or seizure control20.\n\nAtypical findings in ictal EEG have been reported. For instance, patients with unilateral brain insults have shown ictal contralateral slow waves. A patient reported with this pattern became seizure free after hemispherectomy, and the abnormalities seen in the healthy contralateral hemisphere were not a sign of an ictal hemisphere but instead could indicate prominent ischemic changes resulting from a vascular steal phenomenon during the seizure21.\n\nMost recently, analysis of infraslow EEG activity (ISA) was effective in identifying refractory subclinical focal status epilepticus in a pediatric patient who presented with a 96-hour refractory encephalopathy and non-ischemic hemiparesis, which successfully resolved after midazolam administration. In general, ISA has shown potential in the evaluation of patients with epilepsy and in the differentiation between focal and generalized epilepsies22.\n\n\nNeuroimaging in SWS\n\nContrast-enhanced MR studies are the most accurate single imaging studies to demonstrate the extent of brain involvement; contrast enhanced T2-weighted FLAIR images improve detection of leptomeningeal disease compared to post-contrast T1-weighted images22–24. Other typical features include enlargement of the choroid plexus, cortical calcifications, and cerebral atrophy. The demonstration of the extent of the capillary malformation is critical in determining the patient’s prognosis and the necessary approach for cortical resection for epilepsy surgery24,25. Dynamic MR perfusion studies suggest hypoperfusion in the underlying brain is connected to the abnormal pial angioma. Cerebral hypoperfusion is essentially secondary to impaired venous drainage. Perfusion imaging reveals increased mean transit time and in more severe cases reduced regional blood flow25–27. Proton MR spectroscopy of the affected brain region reveals elevated choline, reduced N-acetylaspartate, and slightly elevated lactate, probably resulting from ongoing ischemia and secondary gray and white matter injury. The increased choline peak is possibly related to accelerated myelination observed in early stages of SWS. Multimodality neuroimaging can be of use to identify areas at risk for future metabolic and functional deterioration24.\n\n\nPositron emission tomography/single photon emission computed tomography\n\nPatients with refractory seizures, including those with SWS, often undergo functional studies in preparation for surgery. Given the unique neurovascular coupling mechanism in SWS, functional studies should be interpreted carefully because the vascular malformation in SWS is associated with impairment of the cerebral hemodynamic response to seizure activity.\n\nIncreased glucose metabolism detected by positron emission tomography (PET) has been observed in the lesioned hemisphere. A prospective cohort study was designed with the objective of verifying the significance of interictal hypermetabolism on PET images of children with SWS28. The authors studied the prevalence and clinical correlates of focal increases in cerebral glucose metabolism with seizure onset as well as evolution to drug-resistant epilepsy. Patients with foci of increased cortical glucose metabolism were significantly younger than those with decreased cortical metabolism. Interictal glucose hypermetabolism in young children with SWS is most often seen within a short time before or after the onset of first clinical seizures, and this finding was associated with the presumed period of epileptogenesis. Increased glucose metabolism detected by PET may predict future demise of the affected cortex based on a progressive loss of metabolism and may be an imaging marker of the most malignant cases of intractable epilepsy requiring surgery in SWS28.\n\nSingle photon emission computed tomography (SPECT) detects cerebral blood flow (CBF) asymmetry in infants with SWS, which tends to shift with age. The cortex involved in the vascular malformation is hyperperfused during the first year of life before seizure onset. The classic hypoperfusion appears after 1 year of age, even in patients who do not experience seizures29. The hypoperfusion seems to result from post-ictal phenomena as well as chronic ischemia. SPECT imaging generally demonstrates hypoperfusion in the diseased tissue. The affected cerebral tissue typically shows increased CBF during the ictal state. Decreased blood flow during seizures, however, can also be observed. These findings point to the variable results of functional studies in SWS that might lead to miscalculation of the lesioned area while planning for surgery30.\n\nPrevious studies using SPECT imaging have shown massive steal phenomena in affected areas during seizures, which could lead to a critical ischemic condition in remote brain regions. Therefore, progressive worsening could be partially explained by repeated seizures with severe ischemia of previously unaffected brain parenchyma21.\n\n\nRole of ischemia in epileptogenesis\n\nThe hallmark signs of SWS are tortuous and abnormal vascular structures in thickened leptomeninges. These vessels all have similar appearance, caliber, and morphological characteristics. The areas of capillary malformation are described as capillary-venous type vascular malformations. Underlying brain tissue can be atrophic and display neuronal loss, astrogliosis, dysgenic cortex, and calcification in the cortical layers. The cortical vessels underlying the meningeal angiomas are thin-walled, narrowed by hyalinization and subendothelial proliferation, and increased in number. Cerebral angiography demonstrates an aberrant pattern of both the arterial and venous cerebral circulation. Along with areas of arterial thrombosis, there is abnormal venous drainage, with manifest paucity of the superficial draining veins, venous occlusions, and alternative venous flow through deep subependymal channels11,12.\n\nLow brain tissue perfusion due to abnormal venous drainage is part of the central mechanism of brain damage in SWS. Decreased quantitative white matter perfusion has been associated with frequent seizures, duration of epilepsy, and brain atrophy31. The authors used MR perfusion-weighted imaging (PWI) of the affected cerebral white matter to study dynamic perfusion abnormalities in children with SWS. They concluded that increased perfusion in mostly younger patients may represent a transient phenomenon before severe brain atrophy occurs in the affected brain regions. Decreased perfusion is associated with high seizure frequency, long epilepsy duration, and severe brain atrophy, suggesting a detrimental effect of chronic seizures on brain structure and function.\n\nRegional perfusion and cortical metabolic abnormalities can extend beyond lobes affected by leptomeningeal vascular malformations and are related to epilepsy in SWS. PWI along with fluorodeoxyglucose PET (FDG-PET) has been used to study the relationship between regional metabolic and perfusion abnormalities in SWS. While decreased perfusion was associated with hypometabolism in most cases, increased regional CBF was commonly associated with relatively mild or no hypometabolism. Despite a general correlation between perfusion and metabolism, increased white matter perfusion with preserved cortical metabolism in overlying cortex is a common pattern of a perfusion/metabolic mismatch. This may represent a disease stage where cortical function is preserved while increased white matter perfusion provides collateral drainage of cortex via the deep venous system32.\n\n\nCalcification as source of seizure\n\nAnoxic injury to endothelial cells secondary to impaired venous drainage may contribute to cerebral calcification. However, enhancement of leptomeningeal vessels and enlarged deep venous vessels suggest breakdown of the blood–brain barrier; thus, calcification could also result from increased blood vessel permeability. The calcification typically occurs exclusively in areas subjacent to the abnormal vasculature. It begins in the subcortical white matter and later develops in the cortex affecting predominantly layers II and III. The common sites are the parietal-occipital regions33.\n\nIn a study of 15 children with unilateral SWS, the degree of cortical calcification was assessed using susceptibility-weighted imaging (SWI) while perfusion status was quantified using dynamic susceptibility contrast PWI (DSC-PWI). Prospective data show that prominent calcification in the affected hemisphere reflects markedly decreased perfusion in underlying white matter and is associated with more severe epilepsy in SWS patients33.\n\n\nEpilepsy in SWS associated with cortical malformation\n\nAlthough some malformations of cortical development are caused by environmental insults that occur during cortical development in utero, genetic factors also play a critical role in the pathogenesis of many cortical malformations34. Morphological anomalies have been reported on histological examination of surgical samples from SWS patients. One of the common findings associated with developmental cortical malformations in patients with SWS is polymicrogyria. Like other types of cortical malformations, there is a range of severity from very focal, unilateral forms to extensive bilateral involvement. Traditionally, many cases of polymicrogyria were thought to result from environmental insults during later stages of cortical development, typically during cortical organization following neuronal migration. However, some genetic causes have recently been identified9,35.\n\n\nFuture research\n\nGiven the high incidence of epilepsy in patients with SWS, pre-symptomatic prophylactic treatment has been proposed. A prospective study showed possible improvement in cognitive impairment in a group that were given prophylactic treatment36. Perhaps the use of anti-seizure drug therapy before clinical seizure onset can modify the course of severe epilepsy in SWS patients. Multicenter studies with appropriate patient selection and medication choices will be helpful to study this possibility.\n\nSWS is a progressive and potentially devastating neurocutaneous disorder that typically evolves over time and may result in drug-resistant epilepsy and brain atrophy. Future research aimed at understanding the mechanisms of this condition and comorbidities will have a high impact on our understanding of early stages of brain involvement and will provide the means to assess responses to novel interventions. Multicenter studies are imperative to determine possible candidates for early biomarkers for brain involvement prior to irreversible structural changes.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nShirley MD, Tang H, Gallione CJ, et al.: Sturge-Weber syndrome and port-wine stains caused by somatic mutation in GNAQ. N Engl J Med. 2013; 368(21): 1971–1979. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLo W, Marchuk DA, Ball KL, et al.: Updates and future horizons on the understanding, diagnosis, and treatment of Sturge-Weber syndrome brain involvement. Dev Med Child Neurol. 2012; 54(3): 214–223. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKimple AJ, Bosch DE, Giguère PM, et al.: Regulators of G-protein signaling and their Gα substrates: promises and challenges in their use as drug discovery targets. Pharmacol Rev. 2011; 63(3): 728–749. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNakashima M, Miyajima M, Sugano H, et al.: The somatic GNAQ mutation c.548G>A (p.R183Q) is consistently found in Sturge-Weber syndrome. J Hum Genet. 2014; 59(12): 691–693. PubMed Abstract | Publisher Full Text\n\nMizuno N, Itoh H: Functions and regulatory mechanisms of Gq-signaling pathways. Neurosignals. 2009; 17(1): 42–54. PubMed Abstract | Publisher Full Text\n\nCouto JA, Huang L, Vivero MP, et al.: Endothelial Cells from Capillary Malformations Are Enriched for Somatic GNAQ Mutations. Plast Reconstr Surg. 2016; 137(1): 77e–82e. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nThomas AC, Zeng Z, Rivière JB, et al.: Mosaic activating mutations in GNA11 and GNAQ are associated with Phakomatosis Pigmentovascularis and Extensive Dermal Melanocytosis. J Invest Dermatol. 2016; pii: S0022-202X(16)00332-8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nPrayson RA, Bingaman W, Frater JL, et al.: Histopathologic findings in 37 cases of functional hemispherectomy. Ann Diagn Pathol. 1999; 3(4): 205–212. PubMed Abstract | Publisher Full Text\n\nMaton B, Krsek P, Jayakar P, et al.: Medically intractable epilepsy in Sturge-Weber syndrome is associated with cortical malformation: implications for surgical therapy. Epilepsia. 2010; 51(2): 257–267. PubMed Abstract | Publisher Full Text\n\nMaslin JS, Dorairaj SK, Ritch R: Sturge-Weber Syndrome (Encephalotrigeminal Angiomatosis): Recent Advances and Future Challenges. Asia Pac J Ophthalmol (Phila). 2014; 3(6): 361–367. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nComi AM: Presentation, diagnosis, pathophysiology, and treatment of the neurological features of Sturge-Weber syndrome. Neurologist. 2011; 17(4): 179–184. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCaraballo R, Bartuluchi M, Cersósimo R, et al.: Hemispherectomy in pediatric patients with epilepsy: a study of 45 cases with special emphasis on epileptic syndromes. Childs Nerv Syst. 2011; 27(12): 2131–2136. PubMed Abstract | Publisher Full Text\n\nBerg AT, Millichap JJ: The 2010 revised classification of seizures and epilepsy. Continuum (Minneap Minn). 2013; 19(3 Epilepsy): 571–597. PubMed Abstract | Publisher Full Text\n\nSudarsanam A, Ardern-Holmes SL: Sturge-Weber syndrome: from the past to the present. Eur J Paediatr Neurol. 2014; 18(3): 257–266. PubMed Abstract | Publisher Full Text\n\nBarnett W, Vieregge P, Kömpf D: Gelastic epilepsy: Sturge-Weber syndrome with seizure facilitation. Schweiz Arch Neurol Psychiatr. 1995; 146(2): 61–63. PubMed Abstract\n\nEwen JB, Comi AM, Kossoff EH: Myoclonic-astatic epilepsy in a child with Sturge-Weber syndrome. Pediatr Neurol. 2007; 36(2): 115–117. PubMed Abstract | Publisher Full Text\n\nKossoff EH, Ferenc L, Comi AM: An infantile-onset, severe, yet sporadic seizure pattern is common in Sturge-Weber syndrome. Epilepsia. 2009; 50(9): 2154–2157. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLance EI, Sreenivasan AK, Zabel TA, et al.: Aspirin use in Sturge-Weber syndrome: side effects and clinical outcomes. J Child Neurol. 2013; 28(2): 213–218. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nEwen JB, Kossoff EH, Crone NE, et al.: Use of quantitative EEG in infants with port-wine birthmark to assess for Sturge-Weber brain involvement. Clin Neurophysiol. 2009; 120(8): 1433–1440. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKossoff EH, Bachur CD, Quain AM, et al.: EEG evolution in Sturge-Weber syndrome. Epilepsy Res. 2014; 108(4): 816–819. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLimotai C, Go CY, Baba S, et al.: Steal phenomenon in Sturge-Weber syndrome imitating an ictal electroencephalography change in the contralateral hemisphere: report of 2 cases. J Neurosurg Pediatr. 2015; 16(2): 212–216. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBello-Espinosa LE: Infraslow status epilepticus: A new form of subclinical status epilepticus recorded in a child with Sturge-Weber syndrome. Epilepsy Behav. 2015; 49: 193–197. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGriffiths PD, Coley SC, Romanowski CA, et al.: Contrast-enhanced fluid-attenuated inversion recovery imaging for leptomeningeal disease in children. AJNR Am J Neuroradiol. 2003; 24(4): 719–723. PubMed Abstract\n\nNabbout R, Juhász C: Sturge-Weber syndrome. Handb Clin Neurol. 2013; 111: 315–321. PubMed Abstract | Publisher Full Text\n\nBenedikt RA, Brown DC, Walker R, et al.: Sturge-Weber syndrome: cranial MR imaging with Gd-DTPA. AJNR Am J Neuroradiol. 1993; 14(2): 409–415. PubMed Abstract\n\nLin DD, Barker PB, Hatfield LA, et al.: Dynamic MR perfusion and proton MR spectroscopic imaging in Sturge-Weber syndrome: correlation with neurological symptoms. J Magn Reson Imaging. 2006; 24(2): 274–281. PubMed Abstract | Publisher Full Text\n\nEvans AL, Widjaja E, Connolly DJ, et al.: Cerebral perfusion abnormalities in children with Sturge-Weber syndrome shown by dynamic contrast bolus magnetic resonance perfusion imaging. Pediatrics. 2006; 117(6): 2119–2125. PubMed Abstract | Publisher Full Text\n\nAlkonyi B, Chugani HT, Juhász C: Transient focal cortical increase of interictal glucose metabolism in Sturge-Weber syndrome: implications for epileptogenesis. Epilepsia. 2011; 52(7): 1265–1272. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPinton F, Chiron C, Enjolras O, et al.: Early single photon emission computed tomography in Sturge-Weber syndrome. J Neurol Neurosurg Psychiatry. 1997; 63(5): 616–621. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nOguz KK, Senturk S, Ozturk A, et al.: Impact of recent seizures on cerebral blood flow in patients with Sturge-Weber syndrome: study of 2 cases. J Child Neurol. 2007; 22(5): 617–620. PubMed Abstract | Publisher Full Text\n\nMiao Y, Juhász C, Wu J, et al.: Clinical correlates of white matter blood flow perfusion changes in Sturge-Weber syndrome: a dynamic MR perfusion-weighted imaging study. AJNR Am J Neuroradiol. 2011; 32(7): 1280–1285. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nAlkonyi B, Miao Y, Wu J, et al.: A perfusion-metabolic mismatch in Sturge-Weber syndrome: a multimodality imaging study. Brain Dev. 2012; 34(7): 553–562. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWu J, Tarabishy B, Hu J, et al.: Cortical calcification in Sturge-Weber Syndrome on MRI-SWI: relation to brain perfusion status and seizure severity. J Magn Reson Imaging. 2011; 34(4): 791–798. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGuerrini R, Dobyns WB: Malformations of cortical development: clinical features and genetic causes. Lancet Neurol. 2014; 13(7): 710–726. PubMed Abstract | Publisher Full Text\n\nWang DD, Blümcke I, Coras R, et al.: Sturge-Weber Syndrome Is Associated with Cortical Dysplasia ILAE Type IIIc and Excessive Hypertrophic Pyramidal Neurons in Brain Resections for Intractable Epilepsy. Brain Pathol. 2015; 25(3): 248–255. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nVille D, Enjolras O, Chiron C, et al.: Prophylactic antiepileptic treatment in Sturge-Weber disease. Seizure. 2002; 11(3): 145–150. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "12960",
"date": "18 Mar 2016",
"name": "Jeffrey Noebels",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12961",
"date": "18 Mar 2016",
"name": "Jerome Engel Jr",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-370
|
https://f1000research.com/articles/5-369/v1
|
18 Mar 16
|
{
"type": "Review",
"title": "Advances in the treatment of erectile dysfunction: what’s new and upcoming?",
"authors": [
"Chintan K. Patel",
"Nelson Bennett",
"Chintan K. Patel"
],
"abstract": "Erectile dysfunction adversely affects up to 20% of all men and is the most commonly treated sexual disorder. The public health implications of this condition are significant and represent a challenge for our healthcare system. The physiological pathways responsible for erections have been extensively studied, and much advancement has been made since the introduction of phosphodiesterase 5 inhibitors. Newer agents, such as dopaminergic and melanocortin receptor agonists, which target central erectogenic pathways, are under investigation. Newer formulations and delivery methods of existing medications such as alprostadil will also be introduced in the near future. Furthermore, low-intensity shockwave lithotripsy and stem cell regenerative techniques are innovative approaches to the treatment of erectile dysfunction.",
"keywords": [
"erectile dysfunction",
"public health",
"erectile dysfunction treatment"
],
"content": "Introduction\n\nErectile dysfunction (ED) is a prevalent condition among men that has significant public health implications, and is defined as the inability to initiate or maintain an erection that is satisfactory for sexual intercourse1. ED is estimated to affect approximately 20% of adult males over the age of 202, and by 2025, it is projected to afflict 322 million men worldwide3. ED risk is increased with comorbid conditions such as type II diabetes mellitus (DM), obesity, cardiovascular disease, hypertension, and dyslipidemia4. Interestingly, recent studies have confirmed that ED can serve as a predictor for future cardiovascular disease. In the Prostate Cancer Prevention Trial, the authors reported that men with ED were 45% more likely than men without ED to experience a cardiac event after 5 years of follow up5. ED is well recognized to adversely affect quality of life, decrease work productivity, and increase healthcare costs. Furthermore, it has a considerable financial burden on the public with total expenditures for outpatient management estimated to be $330 million, excluding pharmaceutical costs6. Needless to say, ED is a significant health condition that affects the individual patient and healthcare system as a whole. As such, effective treatment for this condition is paramount.\n\nCurrently, there are several treatment options for patients with ED, both non-invasive and invasive. The hallmark of ED treatment has been phosphodiesterase 5 inhibitors (PDE5-Is). These remain the first-line therapy for ED. Currently, there are four PDE5-Is that are FDA approved in the United States: sildenafil (Viagra®), vardenafil (Levitra®), tadalafil (Cialis®), and avanafil (Stendra®), and all have comparable efficacy and side effect profiles. Sildenafil and vardenafil have similar half-lives of 4 hours, while tadalafil has the longest (17.5 hours) and avanafil has the shortest (3 hours). Vardenafil should be used with caution in patients with prolonged QT interval. Second-line therapies include intracavernosal injections with vasogenic agents. These agents can be used alone or in combination and include prostaglandin E1, phentolamine, vasoactive intestinal peptide, and papaverine and/or atropine. An alternative second-line therapy consists of intraurethral prostaglandin E1 pellets and vacuum erection devices. These options are invasive, which can be troublesome for patients, and also have side effect profiles. Finally, the most invasive treatment of ED consists of insertion of a penile prosthesis.\n\nEven though there are many treatment options for ED currently, there are still patients who do not respond to or cannot tolerate the above therapies. The focus of this article will not be on the current therapies but rather newer medications and procedures that are currently under investigation in both preclinical and clinical settings for the treatment of ED.\n\n\nNon PDE5-I oral agents\n\nNewer pharmacological treatments are focused on targeting alternative pathways in the erectile process, both centrally and peripherally.\n\nDopaminergic agents. Dopamine operates in the brain as a neurotransmitter and in the periphery it functions like a local messenger. Apomorphine (Uprima) is a dopaminergic agent activating dopamine receptors D1 and D2 at a central level within the paraventricular nucleus of the brain. This medication was first introduced in 1987 by Lal and colleagues7 and has been studied extensively since its debut. It has a rapid onset of action, with a mean time to erection of 12 minutes with approximately 50% efficacy. In the first phase III parallel arm cross-over double-blind study of 854 ED patients, erections occurred rapidly (10–25 minutes) and in 54.4% of attempts at 4 mg (vs. 33.8% placebo), with 50.6% success at intercourse8. This drug achieved regulatory approval in Europe in early 2001, but its use has not been authorized in the United States because of hypotension side effects. Along this same pathway, two dopamine agonists (ABT-724 and ABT-670) selected for the D4 receptor are currently being studied in pre-clinical trials and demonstrated physiologic erections in in vivo rat models without the side effects seen with other dopaminergic agents9. Even though ABT-760 and ABT-724 were stopped after phase II trials, the use of similar agents in combination with PDE5-Is appears to be an exciting area of future research.\n\nMelanocortin receptor agonists. Melanocortins are involved in many processes, and their role in controlling sexual function was first reported in the 1960s10. They are linked to the induction of penile erection and the regulation of sexual behavior11. Two well-studied melanocortin receptor agonists are melanotan II and bremelanotide. Early clinical trials showed penile erection in 17 of 20 men who received melanotan II with tip rigidity >80% for an average of 41 minutes12. Side effects reported with melanotan II include nausea, yawning, and a delayed onset of erection (approximately 2 hours). This in turn led to the development of bremelanotide, which can be administered intranasally and has a quicker onset of action. A phase IIB trial with administration of bremelanotide over a 3-month period in patients with DM-induced ED reported significant increases in the International Index of Erectile Function (IIEF) scores13. Intranasal forms of bremelanotide have also shown side effects of nausea and hypertension, and this has led to the development of subcutaneous forms of this therapy. Combination therapy of a subcutaneous melanocortin analogue (PT-141) with sildenafil has been shown to enhance erectile response in a small sample of patients14.\n\nSoluble guanylate cyclase stimulators and activators. PDE5-I efficacy depends on the production of cGMP, which in turn is dependent on nitric oxide (NO) activation of soluble guanylate cyclase (sGC). In some patients, especially post-prostatectomy and DM patients, this pathway is disturbed because of varying amounts of nerve damage15 and the effectiveness of PDE5-Is is reduced significantly. There are two types of compounds that can stimulate sGC: heme-dependent stimulators (BAY 63-2521 and BAY 60-4552) and heme-independent activators (BAY 58-2667). Heme-dependent sGC stimulator functionality depends on the reduced prosthetic heme moiety in the sGC enzyme and synergistic enzyme activation when administered with NO. The activation of sGC by heme-independent activators functions after oxidation or removal of the prosthetic heme group of sGC, highlighting a previously unknown mechanism of enzyme activation. A study using an in vivo model using human corpora cavernosal tissue from 16 PDE5-I non-responders found that combination of sGC stimulator and vardenafil enhanced relaxation of the corpora cavernosa16. In this study, human corpora cavernosal tissues were harvested after consent from individuals undergoing penile prosthesis implantation and potent patients undergoing transurethral surgery.\n\nRho-kinase inhibitors. As mentioned above, endothelial-derived NO plays a critical role in the relaxation of corporal tissue and this pathway is impaired in diabetic patients, which leads to poor erectile function. Phosphorylation of myosin light chain kinase regulates the contraction of smooth muscle in the corpora and dephosphorylation is mediated by smooth muscle myosin phosphatase enzyme. A key regulator of this phosphatase is the serine/threonine kinase Rho-kinase17. Two inhibitors of this Rho-kinase, fasudil and Y-27632, were the first to be studied in rat models, and it was found that relaxation of the corpora was not impaired when subjects were given these medications18. SAR407899 is a more recently developed Rho-kinase inhibitor and has shown promising results in one study when compared to placebo and sildenafil. In this phase II clinical trial, a single dose of SAR407899 was used to assess the increased duration of rigidity of erection. The investigators reported almost double the duration of rigidity (>60%) at the base of the penis with SAR407899 when compared to the placebo group19.\n\n\nTopical therapy\n\nTopical therapies are a promising alterative to the current second-line therapies, as they can be safe and easy to use and do not require intraurethral or intracavernosal instrumentation. One of the leading candidates for this type of administration is a medication termed Topiglan. It consists of prostaglandin E1 (alprostadil) combined with SEPA (soft enhancer of percutaneous absorption). Topical alprostadil has been studied in cats and humans and has been shown to induce erectile responses with minimal side effects20. The benefit of this topical therapy is maximized when used as part of a combination regimen such as those including PDE5-Is. This medication has been approved in Canada. Another topical therapy being investigated is topical sildenafil, currently in phase IIa and actively recruiting study participants21. Limitations of this therapy include variable penetration based on individual penile tissue characteristics as well as reported allergic skin reactions.\n\n\nLow-intensity shockwave therapy\n\nExtracorporeal low-intensity shockwave therapy (LIST) to the penis has recently emerged as a novel and promising treatment modality for ED. LIST has been previously used to treat a wide variety of urological and non-urological conditions22. The mechanism of action for this treatment consists of sending acoustic waves that generate pressure impulses, which can treat patients with kidney stones, tendinitis, and peripheral vascular disease23. For the treatment of ED24, it is hypothesized that LIST causes cell membrane microtrauma and mechanical stress, which causes an upregulation of angiogenic factors such as vascular endothelial growth factor (VEGF), NO synthase, and von Willebrand factor, which increase angiogenesis and vascularization of tissues25. As such, it is postulated that LIST increases blood flow and endothelial function and results in improvement in erectile function.\n\nData from initial human trials are promising but are still in the investigational stage26. Gruenwald25 and colleagues performed an open-label, prospective study on patients with severe ED who previously failed PDE5-I therapy. In this group of 29 patients, LIST treatments were administered twice per week for 3 weeks. There was a 3.5-point increase in the IIEF in this patient population, and, furthermore, these men had improved penile hemodynamics and increased blood flow as assessed by plethysmography. The same group of authors more recently published a randomized, double-blinded, sham-controlled study with 58 men27. Significant improvements were again seen in components of the IIEF and penile hemodynamics. More than 50% of patients in the LIST group (vs. none in the sham group) had an erection rigid enough for vaginal penetration. Even though there were no immediate adverse outcomes reported, the true long-term effects of this therapy are yet to be defined. Future studies with longer follow up will be necessary to see if the remodeling of the penile arterial system causes any long-term damage. In summation, current data suggest that LIST is effective in patients with ED and also men who are PDE5-I non-responders. Penile LIST is a novel therapeutic concept and represents another exciting avenue for the treatment of ED.\n\n\nStem cell transplant\n\nStem cell therapy is a new treatment option that offers the potential to reverse the underlying causes of ED and reduce patient reliance on the transitory effects of PDE5-I medications. It has been studied in several animal models in subjects who poorly respond to PDE5-Is (cavernous nerve injury and DM). Stem cell regenerative therapy is based on the rationale that stem cells can differentiate into a wide variety of cells including endothelial cells, Schwann cells, smooth muscle cells, and neurons28. In ED research, three types of stem cells are commonly used: adipose tissue-derived stem cells, bone marrow-derived stem cells, and muscle-derived stem cells. These can all differentiate into various cell types within the mesodermal germ line. It is hypothesized that multipotent stem cells have beneficial effects on damaged or diseased tissues by releasing various molecular mediators, which lead the host tissue to initiate a regenerative or healing response to diseased or injured tissue responsible for ED. The majority of published studies are based on animal models, but there has been one reported case series of seven men from Korea29. In this study, all diabetic patients, with ages ranging from 57 to 87, were treated with an intracavernosal injection of 15 million allogeneic umbilical cord blood stem cells. Morning erection was regained in six out of the seven men at 6 months from time of injection. With concomitant use of sildenafil, all of these men were able to obtain vaginal penetration. No adverse events were reported. A more recent study reported on a phase I/II clinical trial of intracavernosal autologous bone marrow-mononuclear cells in patients with post-prostatectomy erectile dysfunction30. In the authors’ sample size of 12 patients, they used escalating doses of bone marrow-mononuclear cells and no serious side effects were noted. At 6 months, significant improvements of intercourse satisfaction and erectile function were noted in these patients. These results were preliminary and need to be confirmed in phase II trials. Stem cell transplant therapy is a new frontier in medicine. Larger controlled studies are needed to show any potential benefit at the human level, and further investigation is paramount.\n\n\nGene therapy\n\nGene therapy is a potential therapeutic option that is another area of investigation for the treatment of ED. Genetic material can be easily injected into the penis, which is advantageous as this direct injection avoids potential systemic complications. Furthermore, the effects of gene therapy are more prolonged in the penis because of a slow turnover rate of the tunica albuginea31. In the first human trial, Melman et al. administered a single-dose cavernosal injection of hMaxi-K, a ‘naked’ DNA plasmid carrying the human cDNA encoding the gene for the alpha subunit of the human smooth muscle Maxi-K channel32. No adverse events were noted in the 11 patients who received this therapy. Patients given the two highest doses of hMaxi-K had apparent sustained improvements in erectile function as indicated by improved IIEF domain scores over the length of the study. This was a small study, but the encouraging safety profiles and effectiveness provide evidence that gene therapy is a viable option for the future. The role of stem cell regenerative therapy, in conjunction with gene therapy, will be heavily researched for the treatment of ED in the coming years.\n\n\nConclusion\n\nPDE5-Is have been the cornerstone of ED therapy and because of their effectiveness, the incentive to develop newer drugs has been lacking. Over the past decade, however, we have gained more insight into the molecular and physiologic pathways involving normal erections. This has allowed for the development of new pharmacotherapies for the treatment of ED, especially for patients who are PDE5-I non-responders. Topical alprostadil, shockwave lithotripsy, and stem cell transplants represent innovative treatments and show promise for the next decade. In the future, the treatment of ED will be based on the specific etiologies causing ED, and treatment protocols will be tailored to the particular needs of each individual patient. A larger armamentarium of ED therapies, as summarized by this review, will play a big role in this change, as we will have additional therapies and novel routes of administration that can be offered based on an individual’s specific pathology. Personalized medicine is the future of medicine and will indeed be an important component of ED treatment in the years to come.\n\n\nAbbreviations\n\nED, erectile dysfunction\n\nPDE5-Is, phosphodiesterase 5 inhibitors\n\nDM, diabetes mellitus\n\nsGC, soluble guanylate cyclase\n\nIIEF, International Index of Erectile Function\n\nLIST, low-intensity shockwave lithotripsy\n\nNO, nitric oxide\n\nSEPA, soft enhancer of percutaneous absorption",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no disclosures.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nMontorsi F, Adaikan G, Becher E, et al.: Summary of the recommendations on sexual dysfunctions in men. J Sex Med. 2010; 7(11): 3572–88. PubMed Abstract | Publisher Full Text\n\nDerogatis LR, Burnett AL: The epidemiology of sexual dysfunctions. J Sex Med. 2008; 5(2): 289–300. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAyta IA, McKinlay JB, Krane RJ: The likely worldwide increase in erectile dysfunction between 1995 and 2025 and some possible policy consequences. BJU Int. 1999; 84(1): 50–6. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSelvin E, Burnett AL, Platz EA: Prevalence and risk factors for erectile dysfunction in the US. Am J Med. 2007; 120(2): 151–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nThompson IM, Tangen CM, Goodman PJ, et al.: Erectile dysfunction and subsequent cardiovascular disease. JAMA. 2005; 294(23): 2996–3002. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLitwin MS, Saigal CS, Yano EM, et al.: Urologic diseases in America Project: analytical methods and principal findings. J Urol. 2005; 173(3): 933–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLal S, Laryea E, Thavundayil JX, et al.: Apomorphine-induced penile tumescence in impotent patients--preliminary findings. Prog Neuropsychopharmacol Biol Psychiatry. 1987; 11(2–3): 235–42. PubMed Abstract | Publisher Full Text\n\nHeaton JP: Apomorphine: an update of clinical trial results. Int J Impot Res. 2000; 12(Suppl 4): S67–73. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCowart M, Latshaw SP, Bhatia P, et al.: Discovery of 2-(4-pyridin-2-ylpiperazin-1-ylmethyl)-1H-benzimidazole (ABT-724), a dopaminergic agent with a novel mode of action for the potential treatment of erectile dysfunction. J Med Chem. 2004; 47(15): 3853–64. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHawksworth DJ, Burnett AL: Pharmacotherapeutic management of erectile dysfunction. Clin Pharmacol Ther. 2015; 98(6): 602–10. PubMed Abstract | Publisher Full Text\n\nWessells H, Hruby VJ, Hackett J, et al.: MT-II induces penile erection via brain and spinal mechanisms. Ann N Y Acad Sci. 2003; 994: 90–5. PubMed Abstract | Publisher Full Text\n\nWessells H, Levine N, Hadley ME, et al.: Melanocortin receptor agonists, penile erection, and sexual motivation: human studies with Melanotan II. Int J Impot Res. 2000; 12(Suppl 4): S74–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKaminetsky J, Zinner N, Gittleman M, et al.: Phase IIb study of bremelanotide in the treatment of ED in non-diabetic males. Proceedings of the American Urology Association Annual Meeting; Anaheim, USA. 19–24 May 2007.\n\nDiamond LE, Earle DC, Garcia WD, et al.: Co-administration of low doses of intranasal PT-141, a melanocortin receptor agonist, and sildenafil to men with erectile dysfunction results in an enhanced erectile response. Urology. 2005; 65(4): 755–9. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nPeak TC, Yafi FA, Sangkum P, et al.: Emerging drugs for the treatment of erectile dysfunction. Expert Opin Emerg Drugs. 2015; 20(2): 263–75. PubMed Abstract | Publisher Full Text\n\nAlbersen M, Linsen L, Tinel H, et al.: Synergistic effects of BAY 60-4552 and vardenafil on relaxation of corpus cavernosum tissue of patients with erectile dysfunction and clinical phosphodiesterase type 5 inhibitor failure. J Sex Med. 2013; 10(5): 1268–77. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBivalacqua TJ, Champion HC, Usta MF, et al.: RhoA/Rho-kinase suppresses endothelial nitric oxide synthase in the penis: a mechanism for diabetes-associated erectile dysfunction. Proc Natl Acad Sci U S A. 2004; 101(24): 9121–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBüyükafşar K, Un I: Effects of the Rho-kinase inhibitors, Y-27632 and fasudil, on the corpus cavernosum from diabetic mice. Eur J Pharmacol. 2003; 472(3): 235–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSAR407899 single-dose in treatment of mild to moderate erectile dysfunction (RHOKET). (NCT00914277) Study completion date: September 2009. Reference Source\n\nUsta MF, Sanabria J, Bivalacqua TJ, et al.: Feline penile erection induced by topical glans penis application of combination alprostadil and SEPA (Topiglan). Int J Impot Res. 2004; 16(1): 73–7. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nA phase 2a, single-dose, double-blind, placebo-controlled, 2-way crossover study using penile plethysmography to evaluate the efficacy and safety of SST-6006, a topical sildenafil cream (5% w/w), compared to placebo in the treatment of erectile dysfunction. (NCT02390960) Estimated study completion date: June 2016. Reference Source\n\nSkolarikos A, Alargof E, Rigas A, et al.: Shockwave therapy as first-line treatment for Peyronie's disease: a prospective study. J Endourol. 2005; 19(1): 11–4. PubMed Abstract | Publisher Full Text\n\nCiccone MM, Notarnicola A, Scicchitano P, et al.: Shockwave therapy in patients with peripheral artery disease. Adv Ther. 2012; 29(8): 698–707. PubMed Abstract | Publisher Full Text\n\nLiu J, Zhou F, Li GY, et al.: Evaluation of the effect of different doses of low energy shock wave therapy on the erectile function of streptozotocin (STZ)-induced diabetic rats. Int J Mol Sci. 2013; 14(5): 10661–73. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGruenwald I, Appel B, Vardi Y: Low-intensity extracorporeal shock wave therapy--a novel effective treatment for erectile dysfunction in severe ED patients who respond poorly to PDE5 inhibitor therapy. J Sex Med. 2012; 9(1): 259–64. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nPan MM, Raees A, Kovac JR: Low-Intensity Extracorporeal Shock Wave as a Novel Treatment for Erectile Dysfunction. Am J Mens Health. 2016; 10(2): 146–8. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nKitrey ND, Gruenwald I, Appel B, et al.: Penile Low Intensity Shock Wave Treatment Is Able to Shift PDE5i Nonresponders to Responders: A Double-Blind, Sham Controlled Study. J Urol. 2015; pii: S0022-5347(15)05422-1. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLin CS, Xin ZC, Wang Z, et al.: Stem cell therapy for erectile dysfunction: a critical review. Stem Cells Dev. 2012; 21(3): 343–51. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBahk JY, Jung JH, Han H, et al.: Treatment of diabetic impotence with umbilical cord blood stem cell intracavernosal transplant: preliminary report of 7 cases. Exp Clin Transplant. 2010; 8(2): 150–60. PubMed Abstract | F1000 Recommendation\n\nYiou R, Hamidou L, Birebent B, et al.: Safety of Intracavernous Bone Marrow-Mononuclear Cells for Postradical Prostatectomy Erectile Dysfunction: An Open Dose-Escalation Pilot Study. Eur Urol. 2015; pii: S0302-2838(15)00934-3. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBivalacqua TJ, Hellstrom WJ: Potential application of gene therapy for the treatment of erectile dysfunction. J Androl. 2001; 22(2): 183–90. PubMed Abstract\n\nMelman A, Bar-Chama N, McCullough A, et al.: hMaxi-K gene transfer in males with erectile dysfunction: results of the first human trial. Hum Gene Ther. 2006; 17(12): 1165–76. PubMed Abstract | Publisher Full Text | F1000 Recommendation"
}
|
[
{
"id": "12948",
"date": "18 Mar 2016",
"name": "Arthur Burnett",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12949",
"date": "18 Mar 2016",
"name": "Wayne J. G. Hellstrom",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-369
|
https://f1000research.com/articles/5-368/v1
|
17 Mar 16
|
{
"type": "Review",
"title": "Immunological Functions of the Membrane Proximal Region of MHC Class II Molecules",
"authors": [
"Jonathan Harton",
"Lei Jin",
"Amy Hahn",
"James Drake",
"Jonathan Harton",
"Lei Jin",
"Amy Hahn"
],
"abstract": "Major histocompatibility complex (MHC) class II molecules present exogenously derived antigen peptides to CD4 T cells, driving activation of naïve T cells and supporting CD4-driven immune functions. However, MHC class II molecules are not inert protein pedestals that simply bind and present peptides. These molecules also serve as multi-functional signaling molecules delivering activation, differentiation, or death signals (or a combination of these) to B cells, macrophages, as well as MHC class II-expressing T cells and tumor cells. Although multiple proteins are known to associate with MHC class II, interaction with STING (stimulator of interferon genes) and CD79 is essential for signaling. In addition, alternative transmembrane domain pairing between class II α and β chains influences association with membrane lipid sub-domains, impacting both signaling and antigen presentation. In contrast to the membrane-distal region of the class II molecule responsible for peptide binding and T-cell receptor engagement, the membrane-proximal region (composed of the connecting peptide, transmembrane domain, and cytoplasmic tail) mediates these “non-traditional” class II functions. Here, we review the literature on the function of the membrane-proximal region of the MHC class II molecule and discuss the impact of this aspect of class II immunobiology on immune regulation and human disease.",
"keywords": [
"Myasthenia gravis",
"membrane proximal region",
"membrane distal region",
"immubiology",
"Class II connecting peptide"
],
"content": "Introduction\n\nMajor histocompatibility complex (MHC) class II molecules present antigen-derived peptides to T cells to drive immunological events such as thymic selection, activation of naïve CD4 T cells, and triggering of CD4 T-cell effector function. These events depend on T-cell receptor (TCR) recognition of peptide-class II complexes, the biochemistry and immunology of which have been the focus of much research. Both peptide binding and TCR engagement involve the membrane-distal region of the class II molecule. However, the class II membrane-proximal region (MPR), comprised of the extracellular connecting peptide (CP), transmembrane domain (TM), and intracellular cytoplasmic tail (CT), is not an inert base, merely supporting the molecule’s peptide binding/TCR-interacting region. The MPR (Figure 1) drives multiple functions such as trafficking, signaling, and membrane partitioning, which are discussed below.\n\nThe major histocompatibility complex class II membrane-proximal region (MPR green) is composed of the connecting peptide (CP), transmembrane (TM) domain, and cytoplasmic tail (CT). The α chain connecting peptide (αCP) controls class II association with both CD79 (which bears a cytoplasmic ITAM motif) and STING (which bears a cytoplasmic ITIM motif). CD79 association is dependent on an αCP motif, composed of four glutamic acid (E) residues. The class II TM is the site of palmitoylation and contains both GxxxG dimerization motifs and a cholesterol-binding motif. Together, these motifs control association of the α and β chain TM domains, which control lipid raft partitioning, CD79 association, and the structure and function of the class II extracellular domain. The class II β chain CT bears three known motifs: a membrane-proximal YFR motif that regulates activity of the invariant chain (Ii) endoplasmic reticulum (ER)-retention motif, a lysine (K) residue that is the target of MARCH1-mediated class II ubiquitination, and a membrane-distal GP motif that is necessary and sufficient to drive cyclic AMP (cAMP)-based class II signaling. ITAM, immunoreceptor tyrosine-based activation motif; ITIM, immunoreceptor tyrosine-based inhibitory motif; PKC, protein kinase C; STING, stimulator of interferon genes.\n\n\nOverview\n\nAs the study of class II immunobiology grew, both antigen presentation and other class II functions were reported. However, the desire to understand the role of class II in TCR engagement/T-cell activation led investigators to focus on peptide-class II complex generation and recognition, leaving the now non-traditional class II functions in relative obscurity. This review revisits some early findings as well as more recent discoveries that shed new light on these frequently overlooked but significant class II functions.\n\nClass II immunobiology is more complex than simple presentation of peptides for TCR recognition. Class II molecules are multi-functional and have complex biological properties. For example, class II localization within lipid rafts and its association with tetraspan protein domains and cytoskeleton all impact the ability of antigen-presenting cells (APCs) to present antigen to T cells. Class II also drives intracellular signals activating tyrosine, serine/threonine, and inositol kinases through mediators, including intracellular calcium and cyclic AMP (cAMP). These pathways can lead to APC activation or death. In most cases, proteins such as class II-associated CD791,2 and STING3 drive these events. Importantly, the class II MPR mediates essentially all of these functions.\n\nThis review provides an up-to-date analysis of the documented functions of the class II MPR, considers how human polymorphisms in the class II MPR might impact function (potentially providing insights into the molecular mechanism of disease), and highlights outstanding questions that should be the focus of future study.\n\n\nHuman major histocompatibility complex class II polymorphisms\n\nThe human class II molecules HLA-DR, -DP, and -DQ have been linked to numerous diseases, including rheumatoid arthritis4–6, Goodpasture’s disease7, multiple sclerosis8,9, narcolepsy10, type I diabetes6, Grave’s disease11, celiac disease4, and sarcoidosis/Lofgren’s syndrome12,13. Human leukocyte antigen (HLA) class II molecules also play a critical role in tissue/organ allograft success and susceptibility to infectious disease. Hence, an understanding of HLA immunobiology is essential to understanding the role of HLA in human health.\n\nMuch of the work to understand mechanisms linking class II to human health has focused on disease-associated polymorphisms in and around the membrane-distal peptide/TCR-binding region of the molecule. This approach has yielded a large body of information. For example, the principal HLA association for celiac disease is the heterodimer DQA1*05:01, DQB1*02:01 with a secondary association of DQA1*03, DQB1*03:02, encoded in cis or trans14. These heterodimers present wheat gluten gliadin peptides modified by tissue transglutaminase 2 (released from damaged intestinal tissue), which converts glutamine residues to glutamic acid. Presentation of the modified peptides by the disease-associated class II leads to CD4 T-cell responses, cytokine production, additional tissue damage, and upregulation of HLA-DQ, causing amplification of the response15. However, mechanisms underlying other disease linkages are less clear, and the MPR may hold some important clues.\n\nContrary to some statements in the literature, HLA class II polymorphisms are not restricted to the membrane-distal region of the molecule. Even though the sequence of the class II MPR is under-studied/under-reported (see below), analysis of existing databases illustrates the high level of MPR polymorphism (Table 1). Moreover, many of these polymorphisms lie in or near functional domains (discussed in detail below), suggesting that they impact class II structure or function (or both) and thus human health.\n\n1. Motifs: Connecting Peptide, CD79 association heavy underline (I-A only); Transmembrane Domain, GxxxG motifs indicated by dark grey box, putative cholesterol binding motif indicated by light grey boxes (I-A only); C targets of palmitoylation (not highlighted); Cytoplasmic Domain, G̲P̲ – cAMP motif double underlined, K – ubiquitination sites. DRB – CT GHS motif mediates cytoskeletal interaction (not indicated)\n\n2. Missense polymorphisms compiled from the IMGT/HLA (http://www.ebi.ac.uk/ipd/imgt/hla/) and SNP (ensembl.org) databases.\n\n\nClass II cytoplasmic tail\n\nThe class II CT controls multiple aspects of class II immunobiology such as endoplasmic reticulum (ER) retention of class II-invariant chain (Ii) complexes and MARCH-mediated class II ubiquitination, which controls trafficking within the antigen-processing pathway. Together, the CT and TM domains control cytoskeletal association, which impacts T-cell activation. Finally, the CT is essential for certain class II-mediated signals, of which the cAMP pathway is the most studied.\n\nIn the ER, class II αβ dimers assemble on Ii trimers to form nonameric complexes that can exit the ER and traffic to peptide-loading compartments. Ii is a type II membrane protein with an N-terminal CT. Studies by Thibodeau and colleagues revealed that the human Ii p35 and p45 isoforms have an N-terminal extension (due to alternative upstream start sites) possessing an ER-retention motif, which allows ER retention of incomplete class II-Ii complexes16,17. They also demonstrated that the β chain CT of all three human class II molecules can mask the retention motif to allow egress of assembled complexes16,17. Interestingly, masking requires only the three β chain membrane-proximal CT residues (i.e. YFR in HLA-DR; Figure 1), suggesting that simple steric hindrance of the retention motif is not the mechanism of masking. Thus, the CT has an important role in controlling the early steps of class II biosynthesis.\n\nSubsequent to Ii dissociation, class II molecules bind antigen-derived peptide and are delivered to the plasma membrane, from which they can cycle through the endocytic pathway. Roche and colleagues have shown that, within early endosomes, the ubiquitin ligase MARCH1 can ubiquitinate the class II CT18,19, which causes class II to be shunted out of the recycling pathway and into deep endocytic compartments for degradation20,21. Although there are reports of other ubiquitin ligases such as MARCH8 and MARCH9 ubiquitinating class II22,23, MARCH1 appears to be the main class II ubiquitin ligase in dendritic cells, B cells, and macrophages20,21.\n\nMARCH1 targets the single conserved β chain CT lysine residue. Although arginine substitution of this lysine prevents class II ubiquitination, it is unclear whether and how flanking residues or the α chain CT impacts MARCH-mediated class II ubiquitination. A study by Thibodeau and colleagues revealed that the MARCH1 TM domain is critical for class II interaction/ubiquitination24, suggesting a role for the class II TM domain in controlling class II ubiquitination. Consistent with this idea, Kelly and colleagues reported a role for the class II TM domain in HLA-DR interactions with the MARCH1 homologue MARCH822. However, some of these interactions were defined with a chimeric molecule bearing an unpaired β chain TM domain, which may behave differently than the class II heterodimer (see below). Nevertheless, a picture is emerging where the class II CT and TM domains control both ER egress of class II-Ii complexes and ubiquitin-dependent delivery of class II to late endocytic compartments, influencing class II trafficking throughout the antigen-processing pathway.\n\nCell surface peptide-class II complexes interact with the APC cytoskeleton, impacting the ability of the APC to drive T-cell activation25–28. Using anti-class II antibodies, multiple labs have demonstrated the existence of class II-cytoskeleton interactions. It should be noted that many studies have employed somewhat ambiguous definitions of “cytoskeleton” (e.g., detergent-insoluble material) and have not defined the underlying molecular mechanisms. Nevertheless, in these studies, deletion of either class II α or β chain CT alone fails to completely sever cytoskeletal association, suggesting that both class II CTs are involved. Similarly, a substantial increase in class II lateral translation within the plasma membrane of the cell is seen only when both CTs are deleted29,30. In one study of human class II, Mourad and colleagues26 demonstrate that, in the absence of an HLA-DR α CT, the DR β chain CT mediates cytoskeletal interaction and that this interaction is mediated at least in part by the β chain CT GHS motif (Table 1).\n\nEngagement of class II molecules leads to activation of multiple downstream signaling pathways. In many cases, class II-associated “accessory molecules” such as CD79 mediate signaling pathway activation (see below). However, in B cells, class II-driven intracellular cAMP signaling is directly dependent on the class II β chain CT31,32. Class II-driven cAMP signaling (or the addition of dibutyryl-cAMP) both enhances B-cell receptor (BCR)-mediated antigen processing33,34 and drives plasma cell differentiation35. Thus, signals emanating directly from the class II CT synergize with signals emanating from other class II-associated signaling molecules to drive efficient APC activation.\n\nA β chain CT GP or GQ motif (Table 1) is necessary and sufficient for class II-driven cAMP production and protein kinase C (PKC) activation32,36,37. This GP motif is present in I-A and HLA-DQ, while I-E has a comparably active GQ motif32. The GH motif of HLA-DR bears some similarity to GQ and GP, and CT truncation mutants lacking the GH motif fail to activate PKC38, but whether the specific GH motif is active is untested. In contrast, the VQ in HLA-DP is predicted to be incapable of driving a cAMP response based on loss-of-function GA mutants32. The GP motif most likely couples class II to an undefined adenylate cyclase responsible for cAMP production and activation of downstream signaling molecules such as PKC.\n\nInterestingly, the close proximity of the class II β chain CT ubiquitination, cytoskeletal, and cAMP signaling motifs (Table 1) suggests that at a molecular level these functions may be mutually exclusive. For example, individual class II molecules that have undergone MARCH1-mediated ubiquitination (which attaches a large ubiquitin molecule to the small CT) may sterically block the adenylate cyclase interactions needed to drive cAMP signaling. This would mean that subsets of class II molecules (possibly bearing different sets of peptides such as self versus foreign antigen) could be biased toward particular CT-dependent functions such as cAMP signaling versus MARCH1-dependent ubiquitination. This would allow an APC to tailor both the expression of various peptide-class II complexes for TCR engagement and the APC’s response to TCR engagement of these complexes. This extent of regulation would provide a previously unappreciated level of sophistication to regulation of peptide-class II expression and signaling.\n\n• What mechanism couples class II engagement to cAMP production? Which adenylate cyclase is responsible? What signaling pathways and in vivo immunological functions are cAMP-dependent?\n\n• How is class II ubiquitination controlled? Is there a MARCH1 recognition motif? What are the immunological roles of class II ubiquitination?\n\n• How does the class II β chain CT control activity of the Ii ER retention motif?\n\n• What level of crosstalk is there between the CT ubiquitination, cAMP signaling, and cytosleletal interaction motifs?\n\n\nClass II transmembrane domain\n\nThe class II TM domain controls membrane domain partitioning and class II structure, both of which influence antigen presentation and T-cell activation. The TM domain also controls class II association with the CD79 signaling complex (see below) and with MARCH family ubiquitin ligases (see above), which regulate class II signaling and expression. Class II molecules also associate with tetraspan family member proteins such as CD82, which can form a web of interacting tetraspan proteins39–41. Although it is likely that these associations are driven by interactions between the TM domains of class II and the tetraspan proteins, the precise role of the class II TM domains versus other regions of the class II molecule such as the CT and CP is currently unclear (see discussion of class II-STING interactions below).\n\nMany membrane proteins undergo fatty acylation (e.g., palmitoylation) of TM domain cysteine residues, which can control association with membrane domains such as lipid rafts. The TM domain of all class II α chains contains a highly conserved cysteine residue, as does the TM domain of the I-A and HLA-DP β chain (Table 1). These conserved cysteine residues represent putative palmitoylation sites, and both I-A and HLA-DR have been shown to incorporate palmitic acid42,43. Moreover, mutation of I-A TM domain cysteine residues has been shown to decrease class II lipid raft partitioning and, when transduced into thymic epithelial cells, decreased class II-driven positive selection of CD4+ T cells43. However, the molecular mechanism of class II palmitoylation and how it is controlled are currently not known.\n\nCosson and Bonifacino first demonstrated the impact of the class II TM domain on extracellular domain structure and function44. They noted the unique enrichment/positioning of multiple TM domain glycine residues and demonstrated that mutation of these conserved residues results in an I-Ak class II molecule that is recognized by a conformation-insensitive monoclonal antibody (mAb) (10-2.16) but not by a conformation-specific mAb (11-5.2). Subsequent work by King and Dixon revealed that the TM domain glycine residues form GxxxG dimerization motifs, which function by one-to-one pairing to facilitate TM domain interactions45. The authors noted that while the class II β chain contains one GxxxG motif, the α chain contains two (an N-terminal M1 motif and a C-terminal M2 motif), and, using both in silico and in vitro studies, demonstrated that the HLA-DR β chain motif is able to pair with either α chain motif, albeit with differing “affinity”45. Taken together, these studies revealed previously unknown dimerization motifs within the class II TM domain and suggest a critical role in class II structure/function.\n\nFurther studies established that the 11-5.2 anti-I-Ak mAb is unique in that it selectively binds to M1 paired I-Ak class II molecules, and that these molecules are enriched in plasma membrane lipid rafts46 and have unique signaling properties47. Although other anti-class II antibodies may discriminate conformers on the basis of alternative pairing of TM domain GxxxG dimerization motifs, we are unaware of any that have been identified and characterized. Interestingly, although M1 paired class II represents approximately 10% of cell surface I-Ak molecules46, they carry up to 100% of class II immunological function. Specifically, the 11-5.2 mAb blocks over 90% of antigen-specific B cell-T cell interactions in vitro46 and in vivo T-cell activation48. These findings are compatible with the results of Roche and colleagues, who demonstrated that lipid raft-resident peptide-class II (such as M1 paired class II) is more efficient at activating CD4 T cells, in part due to the clustering of the raft-resident complexes49.\n\nFormation of M1 paired class II is invariant chain (Ii)-dependent, as the addition of a class II tethered peptide that blocks Ii binding also blocks their formation46. Because previous studies established that the Ii TM domain can interact with the class II TM domain50, these results suggest that Ii may guide the pairing of class II TM domains, which would be consistent with the presence of M1 paired class II in the ER of the cell51. Interestingly, GxxxG dimerization motifs are also present in the DM and DO molecules that control class II peptide loading (Table 2), suggesting that this type of TM domain interaction may have additional functions within the class II antigen-processing pathway.\n\nHuman Sequences from “http://www.ebi.ac.uk/imgt/hla/align.html”\n\nIn additional studies, Roy and colleagues have shown that membrane cholesterol, which is important for lipid raft structure, can affect expression of 11-5.2-reactive M1 paired I-Ak class II molecules52. The authors used a combined in situ and in silico approach to identify a putative TM domain cholesterol binding motif and demonstrated that mutation of this motif blocks both formation of M1 paired class II and the ability of cells to effectively present antigen to CD4 T cells.\n\nMost recently, we have shown that M1 paired class II uniquely binds intracellular antigen-BCR complexes in a putative MHC class II peptide-loading complex (PLC)1. In the PLC, M1 paired class II appears to acquire both peptide derived from the processing of BCR-bound antigen and a CD79 signaling module1,2. In contrast, peptide derived from fluid-phase processing of non-cognate antigen is loaded onto both M1 and M2 paired class II (Figure 2). This finding is consistent with the observation that the B-cell response to engagement of peptide-class II complexes formed via BCR-mediated versus fluid-phase antigen processing is different53, and could explain why in vivo B cell-T cell interactions subsequent to BCR-mediated antigen processing are prolonged and highly dynamic, whereas interactions in the absence of cognate antigen (presumably mediated by self-peptide loaded onto M1 and M2 paired class II) are transient54.\n\nB cells were pulsed with hen egg lysozyme (HEL) antigen under conditions that lead to expression of similar levels of C4H3-reactive HEL46-61–I-Ak peptide-class II complexes53. For B-cell receptor-mediated processing (BCR), MD4.B10.Br B cells (expressing a transgenic HEL-specific BCR) were pulsed with 100 nM HEL protein. For fluid-phase processing (F-P), B10.Br B cells were pulsed with 100 µM HEL protein. As previously reported1, cells were lysed and pre-cleared with protein G-Sepharose (PGS) only (No Pre-clear), 10-3.6 + PGS (Pre-clear all), or 11-5.2 + PGS (Pre-clear M1 Paired). Remaining (non-pre-cleared) HEL46-61–I-Ak complexes were immunoprecipitated with the C4H3 monoclonal antibody. The amount of major histocompatibility complex class II β chain remaining in each sample was determined by Western blot1. Although the 11-5.2 anti-M1 paired class II monoclonal antibody pre-cleared essentially all of the BCR-generated peptide-class II complexes, it pre-cleared only a fraction of complexes generated by fluid-phase antigen processing. Shown are representative results from one of three independent experiments.\n\nTaken together, these studies reveal that TM domain pairing is controlled by both GxxxG dimerization motifs and a cholesterol-binding motif, impacting extracellular domain structure and the binding of the 11-5.2 mAb, which binds an epitope near the class II peptide-binding groove/TCR contact site46,55. TM domain pairing also controls both entry into the MHC class II PLC and class II lipid raft partitioning. Hence, the TM domain has profound effects on both the structure and immune function of class II molecules.\n\n• How is class II palmitoylation and GxxxG motif pairing controlled?\n\n• Is there crosstalk between TM domain palmitoylation, GxxxG motif pairing, and cholesterol binding?\n\n• How do changes in the orientation of TM domain pairing impact the structure or function (or both) of the extracellular domain of the molecule (TCR binding, peptide binding, DM binding, CD4 binding, and CD79 binding; see below)?\n\n• Does GxxxG motif pairing impact the functions of HLA-DM or HLA-DO?\n\n\nClass II connecting peptide\n\nThe class II extracellular domain is tethered to the cell surface via α and β chain CPs, which are 15 and 10 amino acids long, respectively (Table 1). In addition to linking the extracellular and TM domains, CPs control class II interactions with signaling molecules. Studies on the function of the class II CP have focused on B cells, but some of the observations such as control of STING-mediated cell death are likely transposable to other APCs such as dendritic cells and macrophages.\n\nIn a recent study of the class II CP, Jin and colleagues established that in B cells the α chain CP (αCP) mediates class II interaction with CD79 (typically regarded solely as the BCR signaling subunit) and a then-uncharacterized molecule critical for class II-driven B-cell death (later determined to be STING, also known as MPYS, which is an integral membrane protein with four TM domains but not a member of the tetraspan family of proteins3)56. The authors also discovered that mutation of the four αCP glutamic acid residues causes decreases in CD79 association and downstream signaling pathways. This result is interesting as it reveals that extracellular domains control class II-CD79 interactions, distinct from CD79-BCR associations that are mediated instead by TM domain interactions. Subsequent work revealed that CD79 preferentially associates with M1 paired class II (see above)1, suggesting that both the class II CP and TM domain may affect class II-CD79 association. Here, the impact of the class II TM domain could be either direct (the class II TM domain could interact with the CD79 TM domain) or indirect (class II TM domain pairing could affect the availability of αCP to interact with the CD79 extracellular domain).\n\nThe reported signaling of class II via CD792,56, as well as the reported association of class II with intact antigen-BCR complexes in a putative MHC class II peptide loading complex (PLC, 1), raises questions about the form of class II-associated CD79. Is the class II-associated CD79 just the CD79a/CD79b heterodimer, or is it part of an intact BCR complex? In the original report by Lang and colleagues2, the authors demonstrate that class II engagement leads to selective phosphorylation of class II-associated CD79a but that membrane immunoglobulin engagement leads to selective phosphorylation of membrane immunoglobulin-associated CD79a, suggesting that class II is associated with a distinct pool of CD79 not associated with membrane immunoglobulin. This would be consistent with our finding that induction of BCR endocytosis fails to result in downregulation of cell surface class II molecules (suggesting that membrane immunoglobulin and class II are not physically associated at the cell surface; Drake, unpublished data). Moreover, these findings are consistent with the scenario suggested above, where complexes of intact cell surface BCR molecules (i.e. membrane IgH/L plus CD79) and bound cognate antigen are internalized and trafficked to the intracellular PLC, where BCR-bound antigen is converted to class II-bound peptide and the BCR CD79 signaling subunit is transferred to the newly formed peptide-class II complex. The ability of class II engagement to drive intracellular calcium signaling in resting B cells under some conditions47 would suggest that constitutively internalized BCR molecules may also enter this pathway, generating some “baseline” level of class II-CD79 complexes even on resting cells.\n\nSTING has recently received attention as an innate immune receptor for cyclic dinucleotides. However, STING is also a class II-associated homodimer that possesses a cytoplasmic immunoreceptor tyrosine-based inhibitory motif (ITIM)3, which can recruit the tyrosine and inositol phosphatases SHP-1 and SHIP. Hence, class II signaling is somewhat similar to BCR signaling in that engagement can elicit immunoreceptor tyrosine-based activation motif (ITAM) or ITIM signaling (or both) depending on conditions. Antigen engagement of the BCR results in CD79-driven ITAM signaling, whereas co-engagement of the BCR and ITIM-bearing FcγRII by immune complexes results in mixed ITAM/ITIM signaling. For class II, selective engagement of CD79-associated class II, such as with the M1 conformer-specific 11-5.2 mAb, results in robust BCR-like ITAM signaling. In contrast, ligation of all class II molecules with the pan-reactive 10-3.6 mAb fails to elicit a detectable intracellular calcium flux47, likely because of recruitment of ITIM-bearing STING-associated class II molecules. Consistent with this scenario, ectopic overexpression of STING blocks CD79-mediated class II-driven intracellular calcium signaling3.\n\nThese findings suggest that the relative levels of CD79 and STING associated with any particular MHC class II-peptide complex may be variable. Therefore, TCR engagement of peptide-class II complexes formed under different conditions or via different pathways (e.g., fluid-phase versus BCR-mediated antigen processing) may have profoundly different effects on the APC. TCR engagement of peptide-class II complexes having a high ratio of CD79 to STING would lead to predominantly ITAM-based class II signaling and APC activation, whereas TCR engagement of peptide-class II complexes having a lower ratio of CD79 to STING would result in predominantly ITIM-based class II signaling and APC death. This highlights the profound impact that functions mediated by the MPR of the class II molecule could have on the outcome of APC-T cell interaction.\n\n• Is binding of CD79 and STING to class II a mutually exclusive event?\n\n• Do all class II molecules associate with CD79 or STING or both? What controls class II association with CD79 and STING?\n\n• What are the immunological functions of peptide-class II complexes associated with CD79, STING or both molecules?\n\n\nHuman class II membrane-proximal region and disease\n\nCurrent sequence-based protocols for clinical typing of HLA class II molecules focus on the extracellular domain of the molecule, extending from the leader peptide to the C-terminal end of the immunoglobulin domain, leaving the MPR of the molecule under-analyzed and under-reported (Table 3). Considering the numerous functional motifs present in this region of the molecule, the high degree of regional polymorphism (Table 1), and the potential effects of these polymorphisms on class II function, we encourage the HLA typing community to accelerate adoption of new protocols such as next-generation sequencing, which allow analysis of the entire length of each HLA molecule, and to include this important information is future database entries. This approach will provide information that could be used to divide existing HLA alleles into “sub-alleles” that may differ only in the MPR of the molecule, and could provide information crucial to determining the molecular mechanisms linking HLA class II to human disease. Two examples are discussed below.\n\naTotal number of alleles for each locus listed in the IMGT/HLA database (http://www.ebi.ac.uk/ipd/imgt/hla/) as of 4 Nov. 15.\n\nbNumber of alleles in IMGT/HLA database with sequence information for the membrane-proximal region of the molecule as of 4 Nov. 15.\n\nHLA, human leukocyte antigen.\n\nMyasthenia gravis (MG) is an autoimmune disease with production of high-affinity antibodies to molecules of the neuromuscular junction (particularly the acetylcholine receptor). Generation of these antibodies requires HLA class II-restricted interactions between auto-reactive B cells and T cells. However, the molecular mechanisms underlying disease are not fully understood. Although a role for HLA class II in MG was appreciated in 1990, a series of articles between 2006 and 2012 established a crucial role for HLA-DQ in the disease57–61. Interestingly, many MG-associated HLA-DQ alleles bear multiple MPR polymorphisms when compared with the non-MG-associated “reference” alleles of DQA1*01:01:01 and DQB1*05:01:01 (Table 1). These MPR polymorphisms are present in both chains and could impact class II-CD79 association, TM domain pairing/cholesterol binding, CT cAMP signaling, and CT ubiquitination. Because the precise molecular mechanism underlying the link between HLA-DQ and MG is still unclear, studies of MG-associated MPR polymorphisms and their effect on class II function may provide important new insights into the molecular mechanism of disease.\n\nA relatively common variation in the HLA-DQ MPR is the presence of a CT proline-rich insert of eight amino acids (PQGPPPAG; Table 1) in approximately 10% of sequenced HLA-DQ β chains (8 out of 71). Interestingly, the first residue of this insert is the proline of the GP cAMP-signaling motif (see above). In alleles lacking the insert, the GP cAMP signaling motif is replaced by GL, which is unable to drive cAMP signaling. Because the cAMP signaling capability of the other HLA class II molecules is either untested (HLA-DR) or lacking (HLA-DP), it is possible that individuals bearing two DQ alleles lacking this insert and the resulting GP motif (likely about 1% of the population) could lack all HLA class II-driven cAMP signaling, which is known to be important for B-cell activation and antibody production. It would be interesting to see whether such individuals have a compromised humoral immune response.\n\n• Are there HLA class II alleles that differ only in their MPR?\n\n• What is the contribution of MPR polymorphisms in the molecular mechanisms linking HLA class II to human diseases?\n\n\nWhat lies ahead\n\nMHC class II molecules mediate inter-cellular communications between class II-expressing APCs and CD4 T cells, meaning that peptide-class II complexes mediate bidirectional communications between these two populations of cells. The membrane-distal region of the class II molecule mediates peptide binding and TCR engagement, which functions to drive T-cell activation. However, the class II MPR impacts T-cell activation in multiple ways. By controlling class II ER retention, endocytic trafficking, and PLC entry, the MPR directly controls the class II peptidome available to drive T-cell activation. By controlling association with membrane sub-domains and the APC cytoskeleton, the MPR controls the “potency” of each peptide-class II complex. Future studies will need to elucidate how these MPR-driven functions are controlled for each and every peptide-class II complex and define their immunological impact. Answering the first part of the question will require the continued application of cutting-edge cellular and molecular approaches, as well as an appreciation of the molecular heterogeneity of the peptide-class II complexes under study. Answering the second part of the question will require extension into in vivo systems by using either genetically engineered experimental animals or samples from humans with MPR polymorphisms. Although results from some studies have been reported, such as a mouse expressing tail-less MHC class II molecules36, these animals were tested under a limited set of experimental conditions. Future progress will require analysis of a greater number of mutations tested under a wider range of physiological conditions.\n\nIn addition to driving T-cell activation, class II molecules are signaling molecules and the MPR mediates all of these signaling events. Class II signaling is driven directly by the class II molecule (as in the case of cAMP signaling), by class II-associated signaling molecules such as CD79 and STING, or by membrane domains such as lipid rafts. Here, two pressing questions remain. First, given the heterogeneity of peptide-class II complexes, which peptide-class II complexes are capable of which forms of class II signaling and how is this regulated as a molecular level? Second, given the range of APCs, such as dendritic cells, B cells, and macrophages, what types of class II signaling are functional/important in which cells? Whereas some forms of signaling such as cAMP production may occur in many/all APCs, others such as CD79-driven signaling are more likely to be highly APC-specific. Here again, it will be critical to move to in vivo experimental systems to begin to unravel the immunological impact of these various class II pathways in relevant APC populations.\n\nThe function of the membrane-distal region of the class II molecule has been a long-term focus of immunologists. This emphasis has led to a detailed understanding of the biology and immunology of this molecular domain, which has provided the foundation for a deeper understanding of the role of class II in the human immune response. However, our understanding of the function of the class II MPR has lagged and future focus on this understudied topic holds much promise for significant strides. Future studies will not only increase our knowledge and appreciation of the immunological functions of this region of the molecule but will also form a foundation to understand how human polymorphisms impacting this region drive the molecular mechanisms of human disease. This next phase of investigation promises to be both exciting and enlightening.\n\n\nAbbreviations\n\nαCP, alpha chain connecting peptide; APC, antigen-presenting cell; BCR, B-cell receptor; cAMP, cyclic AMP; CP, connecting peptide; CT, cytoplasmic tail; ER, endoplasmic reticulum; HLA, human leukocyte antigen; Ii, invariant chain (CD74); ITAM, immunoreceptor tyrosine-based activation motif; ITIM, immunoreceptor tyrosine-based inhibitory motif; mAb, monoclonal antibody; MG, myasthenia gravis; MHC, major histocompatibility complex; MPR, membrane-proximal region; PKC, protein kinase C; PLC, peptide-loading complex; STING, stimulator of interferon genes; TCR, T-cell receptor; TM, transmembrane.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nFinancial support was provided by grants AI-097673 (JRD), AI-056320 and AI-083922 (JRD and JAH), and AI-110606 (LJ).\n\n\nAcknowledgements\n\nWe thank Steven G. E. Marsh and Anup R. Soormally, of the IMGT/HLA Database and Anthony Nolan Research Institute, for information on HLA class II entries in the database and Heidi Tucker for generation of the data presented in Figure 2.\n\n\nReferences\n\nBarroso M, Tucker H, Drake L, et al.: Antigen-B Cell Receptor Complexes Associate with Intracellular major histocompatibility complex (MHC) Class II Molecules. J Biol Chem. 2015; 290(45): 27101–27112. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLang P, Stolpa JC, Freiberg BA, et al.: TCR-induced transmembrane signaling by peptide/MHC class II via associated Ig-alpha/beta dimers. Science. 2001; 291(5508): 1537–1540. 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PubMed Abstract | Publisher Full Text\n\nWade WF, Ward ED, Rosloniec EF, et al.: Truncation of the A alpha chain of MHC class II molecules results in inefficient antigen presentation to antigen-specific T cells. Int Immunol. 1994; 6(10): 1457–1465. PubMed Abstract | Publisher Full Text\n\nMunnelly HM, Brady CJ, Hagen GM, et al.: Rotational and lateral dynamics of I-Ak molecules expressing cytoplasmic truncations. Int Immunol. 2000; 12(9): 1319–1328. PubMed Abstract | Publisher Full Text\n\nWade WF, Freed JH, Edidin M: Translational diffusion of class II major histocompatibility complex molecules is constrained by their cytoplasmic domains. J Cell Biol. 1989; 109(6 Pt 2): 3325–3331. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChen ZZ, McGuire JC, Leach KL, et al.: Transmembrane signaling through B cell MHC class II molecules: anti-Ia antibodies induce protein kinase C translocation to the nuclear fraction. J Immunol. 1987; 138(7): 2345–2352. PubMed Abstract\n\nHarton JA, Van Hagen AE, Bishop GA: The cytoplasmic and transmembrane domains of MHC class II beta chains deliver distinct signals required for MHC class II-mediated B cell activation. Immunity. 1995; 3(3): 349–358. PubMed Abstract\n\nFaassen AE, Dalke DP, Berton MT, et al.: CD40-CD40 ligand interactions stimulate B cell antigen processing. Eur J Immunol. 1995; 25(12): 3249–3255. PubMed Abstract | Publisher Full Text\n\nFaassen AE, Pierce SK: Cross-linking cell surface class II molecules stimulates Ig-mediated B cell antigen processing. J Immunol. 1995; 155(4): 1737–1745. PubMed Abstract\n\nBishop GA: Requirements of class II-mediated B cell differentiation for class II cross-linking and cyclic AMP. J Immunol. 1991; 147(4): 1107–1114. PubMed Abstract\n\nSmiley ST, Laufer TM, Lo D, et al.: Transgenic mice expressing MHC class II molecules with truncated A beta cytoplasmic domains reveal signaling-independent defects in antigen presentation. Int Immunol. 1995; 7(4): 665–677. PubMed Abstract\n\nWade WF, Chen ZZ, Maki R, et al.: Altered I-A protein-mediated transmembrane signaling in B cells that express truncated I-Ak protein. Proc Natl Acad Sci U S A. 1989; 86(16): 6297–6301. PubMed Abstract | Publisher Full Text\n\nRich T, Lawler SE, Lord JM, et al.: HLA class II-induced translocation of PKC alpha and PKC beta II isoforms is abrogated following truncation of DR beta cytoplasmic domains. J Immunol. 1997; 159(8): 3792–3798. PubMed Abstract\n\nHammond C, Denzin LK, Pan M, et al.: The tetraspan protein CD82 is a resident of MHC class II compartments where it associates with HLA-DR, -DM, and -DO molecules. J Immunol. 1998; 161(7): 3282–3291. PubMed Abstract\n\nKropshofer H, Spindeldreher S, Röhn TA, et al.: Tetraspan microdomains distinct from lipid rafts enrich select peptide-MHC class II complexes. Nat Immunol. 2002; 3(1): 61–68. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nVogt AB, Spindeldreher S, Kropshofer H: Clustering of MHC-peptide complexes prior to their engagement in the immunological synapse: lipid raft and tetraspan microdomains. Immunol Rev. 2002; 189(1): 136–151. PubMed Abstract | Publisher Full Text\n\nKaufman JF, Krangel MS, Strominger JL: Cysteines in the transmembrane region of major histocompatibility complex antigens are fatty acylated via thioester bonds. J Biol Chem. 1984; 259(11): 7230–7238. PubMed Abstract\n\nKomaniwa S, Hayashi H, Kawamoto H, et al.: Lipid-mediated presentation of MHC class II molecules guides thymocytes to the CD4 lineage. Eur J Immunol. 2009; 39(1): 96–112. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCosson P, Bonifacino JS: Role of transmembrane domain interactions in the assembly of class II MHC molecules. Science. 1992; 258(5082): 659–662. PubMed Abstract | Publisher Full Text\n\nKing G, Dixon AM: Evidence for role of transmembrane helix-helix interactions in the assembly of the Class II major histocompatibility complex. Mol Biosyst. 2010; 6(9): 1650–1661. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBusman-Sahay K, Sargent E, Harton JA, et al.: The Ia.2 epitope defines a subset of lipid raft-resident MHC class II molecules crucial to effective antigen presentation. J Immunol. 2011; 186(12): 6710–6717. PubMed Abstract | Publisher Full Text\n\nNashar TO, Drake JR: Dynamics of MHC class II-activating signals in murine resting B cells. J Immunol. 2006; 176(2): 827–838. PubMed Abstract | Publisher Full Text\n\nSprent J, Lerner EA, Bruce J, et al.: Inhibition of T cell activation in vivo with mixtures of monoclonal antibodies specific for I-A and I-A/E molecules. J Exp Med. 1981; 154(1): 188–192. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPoloso NJ, Roche PA: Association of MHC class II-peptide complexes with plasma membrane lipid microdomains. Curr Opin Immunol. 2004; 16(1): 103–107. PubMed Abstract | Publisher Full Text\n\nCastellino F, Han R, Germain RN: The transmembrane segment of invariant chain mediates binding to MHC class II molecules in a CLIP-independent manner. Eur J Immunol. 2001; 31(3): 841–850. PubMed Abstract | Publisher Full Text\n\nDixon AM, Drake L, Hughes KT, et al.: Differential transmembrane domain GXXXG motif pairing impacts major histocompatibility complex (MHC) class II structure. J Biol Chem. 2014; 289(17): 11695–11703. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRoy K, Ghosh M, Pal TK, et al.: Cholesterol lowering drug may influence cellular immune response by altering MHC II function. J Lipid Res. 2013; 54(11): 3106–3115. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nNashar TO, Drake JR: The pathway of antigen uptake and processing dictates MHC class II-mediated B cell survival and activation. J Immunol. 2005; 174(3): 1306–1316. PubMed Abstract | Publisher Full Text\n\nOkada T, Miller MJ, Parker I, et al.: Antigen-engaged B cells undergo chemotaxis toward the T zone and form motile conjugates with helper T cells. PLoS Biol. 2005; 3(6): e150. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLandias D, Beck BN, Buerstedde JM, et al.: The assignment of chain specificities for anti-Ia monoclonal antibodies using L cell transfectants. J Immunol. 1986; 137(9): 3002–3005. PubMed Abstract\n\nJin L, Stolpa JC, Young RM, et al.: MHC class II structural requirements for the association with Igalpha/beta, and signaling of calcium mobilization and cell death. Immunol Lett. 2008; 116(2): 184–194. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDeitiker PR, Oshima M, Smith RG, et al.: Association with HLA DQ of early onset myasthenia gravis in Southeast Texas region of the United States. Int J Immunogenet. 2011; 38(1): 55–62. PubMed Abstract | Publisher Full Text\n\nFekih-Mrissa N, Klai S, Zaouali J, et al.: Association of HLA-DR/DQ polymorphism with myasthenia gravis in Tunisian patients. Clin Neurol Neurosurg. 2013; 115(1): 32–36. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLee KW, Jung YA, Oh DH: Four novel human leukocyte antigen-DQA1 alleles identified in the Korean population. Tissue Antigens. 2006; 68(2): 167–172. PubMed Abstract | Publisher Full Text\n\nSaruhan-Direskeneli G, Kiliç A, Parman Y, et al.: HLA-DQ polymorphism in Turkish patients with myasthenia gravis. Hum Immunol. 2006; 67(4–5): 352–358. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nZhu WH, Lu JH, Lin J, et al.: HLA-DQA1*03:02/DQB1*03:03:02 is strongly associated with susceptibility to childhood-onset ocular myasthenia gravis in Southern Han Chinese. J Neuroimmunol. 2012; 247(1–2): 81–85. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "12820",
"date": "17 Mar 2016",
"name": "Michael Reth",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12819",
"date": "17 Mar 2016",
"name": "Lisa K Denzin",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12818",
"date": "17 Mar 2016",
"name": "Jacques Thibodeau",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-368
|
https://f1000research.com/articles/5-367/v1
|
17 Mar 16
|
{
"type": "Review",
"title": "Recent advances in managing chronic HCV infection: focus on therapy in patients with severe liver disease",
"authors": [
"Raoel Maan",
"Adriaan J. van der Meer"
],
"abstract": "Chronic hepatitis C virus (HCV) infection still represents a major public health problem, as it is thought to be responsible for more than 350,000 deaths around the globe on a yearly basis. Fortunately, successful eradication of the virus has been associated with improved clinical outcome and reduced mortality rates. In the past few years, treatment has improved considerably by the implementation of direct-acting antivirals (DAAs). From 2014 onwards, sofosbuvir, simeprevir, daclatasvir, ledipasvir, paritaprevir, ombitasvir, and dasabuvir have been approved by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA). Regimens with various combinations of these new drugs, without the use of interferon (IFN), proved to be very effective and well tolerated, even among patients with advanced liver disease. Moreover, treatment duration could be shortened to 12 weeks in the majority of patients. The high costs of these DAAs, however, limit the availability of IFN-free therapy worldwide. Even in wealthy countries, it is deemed necessary to prioritize DAA treatment in order to limit the immediate impact on the health budget. As patients with advanced liver disease are in most need of HCV clearance, many countries decided to treat those patients first. In the current review, we focus on the currently available IFN-free treatment options for patients with cirrhosis. We discuss the virological efficacy as well as the clinical relevance of these regimens among this specific patient population.",
"keywords": [
"HCV",
"Hepatitis C Virus",
"hepatitis treatment",
"Liver disease",
"Chronic hepatitis C virus",
"interferon"
],
"content": "Natural history\n\nChronic hepatitis C virus (HCV) infection continues to be a major global public health problem, with recent estimates suggesting that 64–103 million people are infected worldwide1. Chronic infection leads to slowly progressive hepatic fibrosis, which may eventually lead to cirrhosis2,3. Once cirrhosis is established, patients have an increased risk of developing complications such as ascites, spontaneous bacterial peritonitis, hepatic encephalopathy, variceal bleeding, and hepatocellular carcinoma (HCC). Although the incidence of HCV infection is declining in the West, it has been estimated that the incidence of patients with HCV-induced cirrhosis will not peak until 20304. At the moment, chronic HCV infection is already the leading indication for liver transplantation in many Western countries5. Not to be forgotten, however, is that the natural history of chronic HCV infection extends beyond the liver as well. Before the stage of cirrhosis, there may already be extrahepatic manifestations that impair the patient’s health-related quality of life (HRQoL), of which fatigue is most frequently reported (approximately 50% of patients)6–8. In terms of solid clinical endpoints, patients are at increased risk of diabetes mellitus, renal failure, cardiovascular events, and malignant lymphoma9. The impaired overall survival among those with chronic HCV infection is thus the result of an increase in both liver-related as well as non-liver-related deaths, as was recently highlighted in an unique natural history study from Taiwan which included 19,636 participants who were followed for a mean duration of 16.2 years10.\n\n\nAntiviral therapy\n\nBefore 2011, treatment for chronic HCV infection depended on the administration of pegylated interferon alpha (PegIFN) and ribavirin (RBV), which was accompanied by the occurrence of many side effects such as flu-like symptoms, depression, and cytopenias. These side effects were bothersome, especially because the IFN-based regimens had a limited chance of attaining a sustained virological response (SVR [HCV RNA negativity in the circulation 12–24 weeks after cessation of antiviral therapy]). If physicians were not already reluctant to treat out of fear for severe adverse events in the specific population of patients with advanced liver disease, PegIFN and RBV were often unsuccessful. In patients with compensated cirrhosis, SVR rates ranged from 10 to 44% for HCV genotypes 1 and 4 and 33 to 72% for HCV genotypes 2 and 3. When patients were known to have decompensated cirrhosis, SVR rates even dropped to 0–16% for HCV genotypes 1 and 4 and 44–57% for HCV genotypes 2 and 311. However, because of safety issues, IFN therapy, in case of unstable liver disease, was mostly restricted to specialized centers. As a result, many patients were unable to attain an SVR, which is considered to be the marker for viral clearance based on its long-term durability12.\n\nThe successful development of protease inhibitors for the treatment of the human immunodeficiency virus initiated the development of the first direct-acting antivirals (DAAs) for the treatment of HCV infection. In 2011, the protease inhibitors telaprevir and boceprevir were the first DAAs to be introduced. When added to PegIFN and RBV, the duration of therapy could be halved to 24–28 weeks in about 50% of patients, while SVR rates improved substantially in both treatment-naïve and treatment-experienced patients with HCV genotype 113–17. Unfortunately, among those with cirrhosis, the treatment duration could not be easily reduced and the improvement in the rate of SVR was only limited with an increase to approximately 50%. The downsides include the following: these first two DAAs were not very effective against HCV genotypes other than genotype 1; treatment became more complex with various dosing schedules, durations, and stopping rules; the pill burden was large; the rates of resistance-associated variants (RAVs) were high; and there were many potential drug-drug interactions. Moreover, the first real-world data raised important safety issues, especially among patients with compensated cirrhosis, and PegIFN remained a necessity18. The development of antiviral therapy has moved at an incredible pace during the 3 years following the first proof-of-concept that chronic HCV infection could be eradicated without PegIFN19. At the moment, IFN-free regimens, in which multiple classes of DAAs are combined, revolutionize the treatment of chronic HCV infection. Short and well-tolerated regimens have reported SVR rates of around 95%, even among patients with cirrhosis20–24. Unfortunately, the high costs of the DAAs currently make these drugs unavailable for the majority of patients worldwide. Also, in wealthy countries it is deemed necessary to prioritize DAA treatment in order to limit the immediate impact on the health budget, even though modeling data indicated that the IFN-free regimens are cost effective in the long term. As a consequence, physicians are often limited to treat only those patients with advanced liver disease, the specific population on which we will focus in the current review.\n\n\nLife cycle of the hepatitis C virus\n\nHepatitis C virus is a small enveloped virus of approximately 55–65 nanometers in size and is a member of the genus Hepacivirus, belonging to the Flaviviridae family. It contains a single-stranded RNA genome of positive polarity. This genome is approximately 9600 nucleotides in length and consists of a highly conserved 59 untranslated region, followed by a single open reading frame that encodes a polyprotein of 3010 to 3033 amino acids. Cellular and viral proteases cleave this large protein into ten smaller viral gene products: three structural proteins (core, E1, and E2); an ion channel (p7); and six nonstructural proteins (NS2, NS3A, NS4A, NS4B, NS5A, and NS5B) (Figure 1). Structural proteins are required for assembly and are used for the determination of the seven main HCV genotypes (and subgenotypes)5. The p7 and NS2 protease are required for the release of infectious particles. The other nonstructural proteins (NS3A, NS4A, NS4B, NS5A, and NS5B) are closely involved in HCV replication25. NS3 and its cofactor NS4A form a stable heterodimeric complex, which cleaves the HCV polyprotein at four sites. NS4B is the presumed central organizer of the HCV replicase complex and a main inducer of intracellular membrane rearrangements. The NS5A protein is essential for RNA replication and assembly of infectious virus particles. The RNA-dependent NS5B protein is the RNA polymerase catalyzing the amplification of the viral RNA genome25,26. Figure 2 shows the entry of HCV into the hepatocytes, as well as its life cycle and replication process26. In addition, several host factors have been involved in the HCV life cycle, which may represent new targets for antiviral treatment. These include epidermal growth factor receptor (EGFR) and ephrin receptor A2 (EphA2), which are two receptor tyrosine kinases that have recently been identified as HCV entry factors27. Another host factor, microRNA-122 (miR-122), is a hepatocyte-abundant microRNA which binds to the 5’ untranslated region of the HCV genome. Hereby, it is thought to promote HCV RNA stability and accumulation and to protect the HCV genome from the innate immune response28. Cyclophilin A (CypA) is a protein that is involved in the replication of HCV by binding to the NS5A protein of all HCV genotypes29. Lastly, apolipoprotein E (apoE) is a component of lipoviral particles, which is involved in the HCV infection of hepatocytes30.\n\nThe hepatitis C virus (HCV) genome encoding three structural proteins and seven non-structural proteins. The direct-acting antivirals are listed below the proteins and include the NS3/4A (or protease) inhibitors, the NS5A inhibitors, and the NS5B polymerase inhibitors (both nucleosides and non-nucleosides). The direct-acting antivirals approved by the US Food and Drug Administration and the European Medicines Agency are highlighted in bold.\n\nAdapted from Feeney et al.26. Schematic overview of the life cycle of the hepatitis C virus (HCV). In order to enter the hepatocyte, HCV interacts with co-receptors, resulting in its endocytosis. Then the virus fuses with the endosome and uncoats its RNA. Host ribosomes translate the RNA into a polyprotein, which is cleaved by host and virally encoded proteases into the three structural and seven non-structural proteins. The non-structural proteins form a complex on a “membranous web” that replicates HCV RNA. The Golgi assembles the HCV RNA with viral structural proteins, leading to the formation of infectious viral particles, which are exocytosed from the cell. © 2015 BMJ Publishing Group Ltd. All rights reserved.\n\n\nMechanism of action of antiviral drugs\n\nAlthough still not fully elucidated, IFN is thought to induce a large number of genes (called IFN-stimulated genes) with antiviral properties, leading to a multi-faceted attack on the virus. In addition, it also has some direct antiviral actions as well as important interactions with the adaptive and innate immune responses31. RBV is a guanosine analogue with activity against several RNA and DNA viruses. Different hypotheses regarding its mechanism of action have been proposed, of which the theory of lethal mutagenesis seems most reasonable31. Protease inhibitors target the NS3/4A serine protease and thereby inhibit the cleavage of this protein and thus HCV replication26. Current approved “-previrs” include telaprevir, boceprevir, simeprevir, and paritaprevir (Figure 1). The NS5A inhibitors, also known as “-asvirs”, target another nonstructural protein and block the replication of HCV RNA at the stage of membranous web biogenesis32. So far, daclatasvir, ledipasvir, and ombitasvir have been approved (Figure 1). Both NS3/4A protease inhibitors and NS5A inhibitors have very potent antiviral activity but exhibit a low barrier to viral resistance. The NS5B inhibitors, or “-buvirs”, can be divided into two main classes: nucleos(t)ide inhibitors and non-nucleotide inhibitors (Figure 1). By binding to the active site of the NS5B RNA-dependent RNA polymerase, nucleos(t)ide inhibitors (e.g., sofosbuvir) cause premature chain termination. The non-nucleotide inhibitors (e.g., dasabuvir) bind outside the active site, causing a conformational change, and thereby decrease the polymerase activity of the enzyme26.\n\n\nCurrent treatment regimens\n\nThere are extensive data from phase III or IV studies on the efficacy of IFN-free regimens, but patients with compensated and decompensated cirrhosis were often underrepresented. Currently, more data are emerging from real-world studies on the efficacy of these regimens, which included patients with the most severe cirrhosis. Table 1–Table 4 show the data from phase III or IV studies available on the efficacy of IFN-free antiviral therapy. Below, we will discuss the treatment regimens in a more conceptual way for the treatment of patients with compensated cirrhosis.\n\na. Abbreviations: ASV, asunaprevir; BCV; beclabuvir; DCV, daclatasvir; DSV, dasabuvir; ELB, elbasvir; GPV, grazoprevir; HCV, hepatitis C virus; LDV, ledipasvir; OMB, ombitasvir; PAR/r, paritaprevir/ritonavir; RBV, ribavirin; SIM, simeprevir; SOF, sofosbuvir; SVR, sustained virological response; TE, treatment-experienced; VPV, velpatasvir\n\na. Abbreviations: DCV, daclatasvir; HCV, hepatitis C virus; RBV, ribavirin; SOF, sofosbuvir; SVR, sustained virological response; TE, treatment-experienced; VPV, velpatasvir\n\na. Abbreviations: DCV, daclatasvir; HCV, hepatitis C virus; LDV, ledipasvir; RBV, ribavirin; SIM, simeprevir; SOF, sofosbuvir; SVR, sustained virological response; TE, treatment-experienced; VPV, velpatasvir\n\nb. *Also included patients with HCV genotype 2, 3, and 4\n\nc. #Fewer than 10 patients were included in a specific subgroup\n\na. Abbreviations: DCV, daclatasvir; HCV, hepatitis C virus; LDV, ledipasvir; RBV, ribavirin; SIM, simeprevir; SOF, sofosbuvir; SVR, sustained virological response; TE, treatment-experienced\n\nb. *Also included patients with HCV genotype 2, 3, and 4\n\nc. #Fewer than 10 patients were included in a specific subgroup\n\nIn the Western world, HCV genotype 1 is the most prevalent (>50%). The initial development of DAAs was therefore mainly focused on this genotype. Although IFN-free therapy is preferred, the combination of a second-generation NS3/4A protease inhibitor, a NS5A inhibitor, or a NS5B inhibitor with PegIFN and RBV for 12–48 weeks has been assessed33–36. Although not approved, even the addition of a NS3/4A protease inhibitor and a NS5A inhibitor to PegIFN and RBV for 24 weeks could have been an option for the treatment of chronic HCV genotype 1 infection37. For patients who are unable to tolerate PegIFN, the combination of a NS5B inhibitor and RBV was assessed, but phase III studies were never performed due to the lack of efficacy. When focusing on the regimens that did reach SVR rates of more than 90%, the optimal regimen consists of at least two classes of DAAs, with or without the addition of RBV. The combination of a NS5B inhibitor with a NS5A inhibitor and/or a NS3/4A protease inhibitor is enough to create a high barrier to resistance20–22. In cirrhotic patients, some regimens show lack of efficacy, which could be improved by the addition of RBV and/or the extension of antiviral therapy to 24 weeks. As the development of novel DAAs is still ongoing, recent data have shown that second-generation regimens, including a NS5A inhibitor and a NS3/4A protease inhibitor, may be equally effective for this genotype38. Thus, inclusion of a NS5B inhibitor may not be a necessity.\n\nSince there is a difference in efficacy among patients with HCV genotype 1a and 1b, different regimens were applied among these patients23,24. RAVs that are present at baseline or emerge during antiviral therapy may account for this difference between the two subtypes. Therefore, before initiating most regimens, subtyping of the HCV genotype 1 is required. However, lower response rates in patients with HCV genotype 1a seem to be a problem only when a NS3/4A protease inhibitor is incorporated into the treatment regimen20,21,23. At the price of additional side effects, this effect may be partly overcome by adding RBV to the treatment regimen.\n\nHistorically, patients with HCV genotype 2 were the easiest to treat, even when patients had cirrhosis. Currently, an IFN-free combination including a NS5B inhibitor and RBV seems sufficient to clear the virus39–41. When patients are intolerant to RBV, a regimen with a NS5B inhibitor and a NS5A inhibitor could be an attractive option, as both have antiviral activity against this genotype. This combination, however, has not been extensively investigated in clinical trials42.\n\nPatients with HCV genotypes 2 and 3 were found to be relatively IFN sensitive and required a shorter duration of therapy with lower doses of RBV to achieve higher rates of SVR as compared to patients with HCV genotypes 1 and 4. Even with PegIFN and RBV, however, HCV genotype 3 was more difficult to cure than genotype 2, particularly in patients with established cirrhosis. In the current IFN-free era, HCV genotype 3 has actually replaced HCV genotype 1 as the most challenging genotype. In contrast to its effect in non-cirrhotic patients with HCV genotype 3, the combination of a NS5B inhibitor and RBV in cirrhotic patients is suboptimal and has a high virological relapse rate39–41. The addition of a NS5A inhibitor to this regimen could improve response rates, but the incremental efficacy of a 12-week regimen remains limited43. Although the duration has not been investigated within clinical trials, current guidelines recommend a 24-week regimen including a NS5B inhibitor and a NS5A inhibitor with or without RBV. So far, none of the currently approved DAAs have optimal antiviral activity against HCV genotype 3, so the “re-introduction” of PegIFN for this genotype needs to be considered among those who are able to tolerate its side effects44. Recently, a pan-genotypic regimen for 12 weeks, including a NS5B and NS5A inhibitor, seemed highly effective for HCV genotype 3, even among treatment-experienced patients with cirrhosis45.\n\nWhen PegIFN-based treatment was considered, patients with HCV genotype 4 used to be grouped with patients infected with HCV genotype 1. With the DAAs, these patients respond to the same regimens as well, and possibly even better. Although data in cirrhotic patients are scarce, due to the low prevalence of this genotype in most Western countries, the combination of a NS5B inhibitor and RBV is a plausible option. A regimen including two DAAs from separate classes (a NS5B inhibitor, a NS5A inhibitor, or a second-generation NS3/4A protease inhibitor) could also be used to eradicate chronic HCV genotype 4. When physicians want to reduce the chance of virological relapse, RBV could be added to the regimen, provided that patients are able to tolerate this.\n\n\nDecompensated cirrhosis\n\nIn general, patients with decompensated cirrhosis (Child-Pugh B/C) have lower response rates than patients with compensated cirrhosis (Child-Pugh A)46. Reasons for these lower response rates may include reduced drug delivery due to shunting leading to HCV reservoirs, altered drug metabolism and uptake due to impaired liver synthetic function, or impaired immune responses which are present in cirrhotic patients47.\n\nObviously, among patients with decompensated cirrhosis, the IFN-free regimens are far better tolerated as compared to the PegIFN and RBV combination therapy, which has been the standard of care for the last 15 years. However, as more real-world data are emerging, safety issues regarding the use of DAAs among those patients with the most advanced liver disease have arisen. Two patients with hepatic decompensation developed severe drug-induced liver injury leading to death and liver transplantation. Both patients were treated with sofosbuvir, a NS5A inhibitor, and RBV48. A recent study by Welker et al. described the occurrence of lactate acidosis among patients treated with sofosbuvir-based regimens, with or without the addition of RBV49. Whether the clinical deterioration could be attributed to the use of DAAs or RBV or whether this is merely in line with the poor natural history of patients with decompensated cirrhosis remains a matter of debate. Likewise, the occurrence of hepatic decompensation during antiviral treatment has been reported for several treatment regimens, leading the FDA to discourage the use of dasabuvir, ombitasvir, and paritaprevir/ritonavir for patients with decompensated liver disease50. Also, because of the real-world safety issues which were encountered with the first-generation protease inhibitors telaprevir and boceprevir among patients with cirrhosis and low platelets or low albumin levels, one could argue that protease inhibitors may not represent an ideal class of DAAs for those with the most severe cirrhosis18. Simeprevir, a first-generation second-wave protease inhibitor, has actually never been registered for patients with decompensated cirrhosis. It is clear that further studies with a focus on the safety profile of the IFN-free regimens among patients with decompensated liver disease are urgently needed. It would be highly relevant to be able to predict which of these patients can and cannot be safely treated with the IFN-free regimens.\n\n\nResistance-associated variants\n\nThe high efficacy of IFN-free regimens will lead to high rates of SVR, even among the population that was difficult to treat and/or difficult to cure in the era of IFN-based therapy. However, as pointed out earlier, lower response rates were observed among patients with advanced liver disease. The emergence of RAVs seems a relevant factor in case antiviral therapy is not successful. Although heterogeneous methods were used to detect RAVs, it has been estimated that 53–91% of patients with virological relapse harbor HCV isolates that are resistant to one, two, or three DAAs51. The presence of RAVs before IFN-free treatment initiation could be an important cause of virological failure as well, and fuels the ongoing debate of whether we should perform pretreatment viral sequencing. Relevant in this respect is that the second-generation DAAs, which are coming shortly, are thought to have a higher genetic barrier to resistance. Another option to overcome the RAVs are the advanced cellular drugs that target the host factors involved in the HCV life cycle, which have the general advantage of being pan-genotypic. Silencing of miR-122 in vitro showed remarkable inhibition of HCV replication and led to the possibility of targeting miR-122 as an antiviral strategy28,52. Other possible options include the HCV entry inhibitors erlotinib and dasatinib, or the cyclophilin inhibitor alisporivir27,53. In combination with DAAs, the drugs targeting host factors could be effective, especially for those patients with resistant viral strains. Still, in order to globally eradicate HCV, an effective vaccine seems necessary54.\n\n\nClinical relevance of successful antiviral therapy\n\nIn parallel with the impressive development of highly potent and well-tolerated DAAs, various cohort studies increased our understanding of the clinical relevance of these new drugs. Over the last couple of years, many researchers have published results that indicate that patients who attain SVR have a beneficial clinical outcome in terms of both liver-related and liver-unrelated endpoints. The growing body of evidence in favor of SVR is, obviously, relevant for patients and physicians. However, it is also very much needed for policy-makers who need to decide on the reimbursement of the highly effective but costly IFN-free regimens.\n\n\nLiver histology\n\nIn contrast to what was believed during the largest part of the last century, it is now widely accepted that hepatic fibrosis can regress in cases where the underlying cause of liver damage is adequately treated. Chronic HCV infection is probably the liver disease in which this is best documented. The largest histological study in which patients underwent a second liver biopsy 24 weeks after cessation of antiviral therapy indicated that, on average, the degree of hepatic fibrosis regressed among those with SVR and was rather stable among those without SVR55. The most impressive result of this study, however, was that 75 of the 153 patients with cirrhosis before therapy no longer scored a METAVIR F4 in their post-treatment liver biopsy. Yet, from a previous study from Japan, we already learned that regression of hepatic fibrosis is likely to take more time56. Shiratori et al. included 593 patients in whom the time to the post-treatment liver biopsy ranged from 1 to 10 years. Among those with SVR, the authors found that regression of fibrosis was more pronounced in cases where the biopsy was repeated after more than 3 years of follow-up. Still, even in cases with much longer follow-up, histological studies have been unable to show that all HCV-infected patients with cirrhosis who attained SVR improve their METAVIR F4 score. The concept of a point of no return with respect to the extent of liver damage seems plausible, especially because the vascular abnormalities within a cirrhotic liver have never been shown to improve, and shunting of blood through vascularized portacaval septa can lead to hypoperfusion of liver parenchyma, with hypoxemia as a contributing factor for hepatic inflammation and fibrosis57–59. On the other hand, the semi-quantitative fibrosis scores may also be somewhat too crude to appreciate all histological improvements following the eradication of HCV infection. Indeed, a recent study assessed the change in the total area of fibrosis among 38 Italian patients with cirrhosis who attained SVR60. Among the minority (39%), in whom the METAVIR F4 score was not reduced after a median duration of 5.6 years in between both liver biopsies, the total area of hepatic fibrosis was still significantly reduced. While the discussion on whether cirrhosis is reversible is ongoing, it may actually be more relevant to consider the relationship between HCV eradication and the clinical sequelae of cirrhosis61.\n\n\nLiver-related morbidity and mortality\n\nMost of the Western studies that assessed the association between HCV eradication and hepatic decompensation or HCC have solely included patients with advanced liver disease, who are most at risk for these cirrhosis-related complications. However, as we have long depended on IFN-based treatment regimens, these studies predominantly included cirrhotic patients with relatively favorable characteristics. Veldt et al. were one of the first groups to show that the incidence in liver failure was markedly reduced among patients with chronic HCV infection and advanced liver fibrosis who attained SVR62. Interestingly, this beneficial outcome was apparent immediately upon HCV clearance. Hereafter, larger studies with longer follow-up duration not only confirmed these results but also showed a significant association between SVR and a reduced occurrence of HCC, with strong hazard ratios (HRs) adjusted for many potential confounders63–65. In a recent meta-analysis, in which the results of all available cohort studies among patients with advanced liver disease were pooled, the results indicated that within this population the HR of SVR for the occurrence of HCC was 0.23 (95% confidence interval [CI] 0.16–0.35)66. Combining studies that included patients with all stages of fibrosis resulted in a pooled HR of 0.24 (95% CI 0.18–0.31) regarding SVR and HCC occurrence, although these studies were mostly performed in Japan, where the incidence of HCC is substantially higher. Considering the potential benefits of SVR on these cirrhosis-related morbidities, it is not surprising that patients with cirrhosis who clear their chronic HCV infection have a reduced liver-related mortality65,67. Still, it is noteworthy that patients with advanced liver disease are not free from cirrhosis-related complications following HCV eradication. A combined cohort including 1000 patients with advanced liver fibrosis and IFN-induced SVR showed that the annual risk of HCC remains at about 1% following HCV eradication in patients with cirrhosis68. The risk of HCC depends on age, the presence of diabetes mellitus, and laboratory markers of liver disease severity. One may thus expect a rising incidence of HCC following successful antiviral therapy in the era of DAAs, which will enable older patients with more advanced liver disease to attain SVR.\n\n\nExtrahepatic consequences\n\nWhile a large number of studies indicated potential liver-related benefits of SVR, more recent efforts have focused on the association between antiviral therapy and extrahepatic disease. With respect to patient-reported outcomes, eradication of HCV infection decreases both the frequency and the severity of fatigue8. This may be an important reason for the improved HRQoL which has been observed upon SVR69. Although difficult to quantify in daily practice, these effects are probably more directly noticeable for patients and their health-care providers than the prevention of future clinical complications.\n\nEven a few years ago, it was reported that the risk of diabetes mellitus is about three times lower among patients with SVR as compared to patients without SVR70. The deteriorating consequences of diabetes mellitus are diverse but surely include renal failure and cardiovascular events. A reduced incidence of both of these solid endpoints in cases of antiviral therapy use was recently shown in a nationwide cohort study from Taiwan, in which 12,384 treated patients and 24,768 propensity score-matched untreated controls were included. The cumulative 8-year incidences of end-stage renal disease (0.15% vs. 1.32%), acute coronary syndrome (2.21% vs. 2.96%), and ischemic stroke (1.31% vs. 1.76%) were significantly lower among treated as compared to untreated patients (p<0.05 for all), and the effect of antiviral therapy remained statistically significant in multivariate analysis71. These findings were immediately confirmed, and assigned to SVR, in a large population-based study which is expected to include about 80% of all IFN-treated chronic HCV-infected patients in Scotland72. Apart from diabetes mellitus, we were recently presented with another possible explanation for these findings, as Gragnani et al. showed that HCV eradication led to the disappearance of cryoglobulinemia and resolved manifestations of the mixed cryoglobulinemia syndrome in nearly all patients73. Other potential extrahepatic benefits of SVR that have been presented within recent years include a reduced occurrence of malignant lymphomas and reduced hospitalization because of acute alcohol intoxication or violence-related injuries72,74. Through these effects on extrahepatic morbidity, patients with SVR have not only a reduced liver-related mortality but also a reduced liver-unrelated mortality72,75.\n\n\nAll-cause mortality\n\nThe most important new insights with regard to the clinical benefit of antiviral therapy probably concern the association between SVR and a prolonged overall survival as the most definitive clinical endpoint. In 2011, Backus et al. were the first to show that SVR was statistically significantly associated with a reduced all-cause mortality (HR 0.70, 0.64, and 0.51 for HCV genotype 1, 2, and 3, respectively) in a large cohort of 16,864 patients with chronic HCV infection who were followed for a median duration of 3.8 years76. However, these results were derived from the specific patient population of American veterans, among which there is substantial comorbidity, risk behavior, and a rather high mortality rate. Another report extended this finding to the general HCV-infected patient population with advanced liver disease67. Among the 530 patients with chronic HCV infection and advanced liver fibrosis who were followed for a median of 8.4 years, the cumulative 10-year overall survival was 91% among those with SVR, versus 74% among those without SVR (HR 0.26, 95% CI 0.14–1.49). In contrast to those who were unsuccessfully treated, patients with SVR had a survival rate that was comparable to that of the age- and sex-matched general population77. Importantly, in both reports, the HR of SVR for all-cause mortality was extensively adjusted for baseline characteristics known to influence both the chance of successful IFN therapy and the long-term clinical outcome. Various representable cohorts have confirmed the strong association between SVR and reduced all-cause mortality hereafter72,78. The pooled HR of SVR was 0.50 (95% CI 0.37–0.76) based on all studies which did not specifically include patients with advanced fibrosis and 0.26 (95% CI 0.18–0.37) when only studies among those with advanced liver disease were considered79.\n\n\nDecompensated cirrhosis\n\nThe above-described studies, which suggest a clinical benefit of SVR, were performed among patients treated with IFN-based regimens, so that even those included with cirrhosis had relatively favorable baseline characteristics. Indeed, in the IFN era, patients with decompensated cirrhosis were frequently withheld from antiviral therapy but were also unlikely to attain SVR if treatment was initiated. Consequently, the clinical relevance of attaining SVR is largely unknown apart from the fact that achievement of SVR would be desirable to prevent HCV recurrence in cases of liver transplantation. Because of the beneficial safety profile of the DAAs, our experience with antiviral therapy in patients with chronic HCV infection and decompensated cirrhosis is increasing rapidly. Still, because these therapeutic options have just surfaced, studies with sufficient follow-up to assess the true clinical impact of IFN-free therapy among the patients with the most advanced liver disease have to be awaited. In the meantime, several interesting observations in the short term have been presented, which focus on the Model for End-Stage Liver Disease (MELD) score. Deterding et al. treated 34 HCV-infected patients with Child-Pugh B/C with various IFN-free regimens. At 12 weeks post-treatment, the MELD score improved in 68%, remained stable in 23%, and worsened in 10% of patients80. Based on the first experiences in England, Foster et al. reported the change in MELD score 4 weeks after the cessation of DAA therapy81. Of the 220 patients, 105 (47.7%) had no significant change in MELD score; in 92 (41.8%) patients, MELD score improved by ≥2 points; and in 23 (10.5%) patients, MELD score worsened by ≥2 points. Additional analyses indicated that the MELD score more frequently improved rather than declined among younger patients (<65 years) and patients with a high albumin level (>35 g/L). Still, MELD improvements are mostly moderate, so the important question of whether liver transplantation can really be averted remains. If not, the slight improvement in MELD score may actually negatively impact the patient’s chances on the waiting list. Because clinical trials showed excellent SVR rates with IFN-free therapy among liver transplant recipients with chronic HCV infection, it may be questioned whether patients with decompensated cirrhosis should be treated before or after transplantation82,83. Within the next 2 years, more data will hopefully become available, which may be able to guide this decision for the individual patient. Preferably, patients with decompensated cirrhosis should therefore be treated within registry studies during the upcoming years.\n\n\nConclusion\n\nThe implementation of IFN-free treatment regimens has broadened the horizon for patients with chronic HCV infection tremendously. Within a timeframe of 5 years, important treatment developments resulted in near-perfect SVR rates, even among patients with the most advanced liver disease. As successful antiviral therapy may be lifesaving, these developments were long awaited. Some hurdles have to be taken, however, before the health burden of this chronic disease can truly be reduced. For instance, the access to DAAs needs to be broadened so that patients can be treated regardless of the severity of hepatic fibrosis. Reducing the costs of these drugs probably remains a key factor before this goal can be achieved. As developments are still ongoing, prices will hopefully fall as a result of mutual competition. Also, it is important to increase the number of patients who are diagnosed, as the majority of patients are currently unaware of their chronic viral hepatitis. Pan-genotypic regimens are currently being evaluated in phase III trials as well, which will hopefully simplify antiviral therapy even more. Until that time, treatment selection is required and prioritizing treatment is needed to limit the economic burden. Treating those with advanced hepatic disease first seems reasonable, but remains far from ideal.\n\n\nAbbreviations\n\nDAAs, direct-acting antivirals; FDA, US Food and Drug Administration; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; HR, hazard ratio; HRQoL, health-related quality of life; IFN, interferon; MELD, Model for End-Stage Liver Disease; miR-122, microRNA-122; PegIFN, pegylated interferon alpha; RAVs, resistance-associated variants; RBV, ribavirin; SVR, sustained virological response.",
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PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCardoso AC, Moucari R, Figueiredo-Mendes C, et al.: Impact of peginterferon and ribavirin therapy on hepatocellular carcinoma: incidence and survival in hepatitis C patients with advanced fibrosis. J Hepatol. 2010; 52(5): 652–657. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMorgan TR, Ghany MG, Kim HY, et al.: Outcome of sustained virological responders with histologically advanced chronic hepatitis C. Hepatology. 2010; 52(3): 833–844. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMorgan RL, Baack B, Smith BD, et al.: Eradication of hepatitis C virus infection and the development of hepatocellular carcinoma: a meta-analysis of observational studies. Ann Intern Med. 2013; 158(5 Pt 1): 329–337. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nvan der Meer AJ, Veldt BJ, Feld JJ, et al.: Association between sustained virological response and all-cause mortality among patients with chronic hepatitis C and advanced hepatic fibrosis. JAMA. 2012; 308(24): 2584–2593. PubMed Abstract | Publisher Full Text\n\nvan der Meer AJ, Feld JJ, Hofer H, et al.: The risk for hepatocellular carcinoma among patients with chronic HCV infection and advanced hepatic fibrosis following sustained virological response. Hepatology. 2013; 58(4): 280A.\n\nSpiegel BM, Younossi ZM, Hays RD, et al.: Impact of hepatitis C on health related quality of life: a systematic review and quantitative assessment. Hepatology. 2005; 41(4): 790–800. PubMed Abstract | Publisher Full Text\n\nArase Y, Suzuki F, Suzuki Y, et al.: Sustained virological response reduces incidence of onset of type 2 diabetes in chronic hepatitis C. Hepatology. 2009; 49(3): 739–744. PubMed Abstract | Publisher Full Text\n\nHsu YC, Ho HJ, Huang YT, et al.: Association between antiviral treatment and extrahepatic outcomes in patients with hepatitis C virus infection. Gut. 2015; 64(3): 495–503. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nInnes HA, McDonald SA, Dillon JF, et al.: Toward a more complete understanding of the association between a hepatitis C sustained viral response and cause-specific outcomes. Hepatology. 2015; 62(2): 355–364. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGragnani L, Fognani E, Piluso A, et al.: Long-term effect of HCV eradication in patients with mixed cryoglobulinemia: a prospective, controlled, open-label, cohort study. Hepatology. 2015; 61(4): 1145–1153. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKawamura Y, Ikeda K, Arase Y, et al.: Viral elimination reduces incidence of malignant lymphoma in patients with hepatitis C. Am J Med. 2007; 120(12): 1034–1041. PubMed Abstract | Publisher Full Text\n\nBerenguer J, Rodríguez E, Miralles P, et al.: Sustained virological response to interferon plus ribavirin reduces non-liver-related mortality in patients coinfected with HIV and Hepatitis C virus. Clin Infect Dis. 2012; 55(5): 728–736. PubMed Abstract | Publisher Full Text\n\nBackus LI, Boothroyd DB, Phillips BR, et al.: A sustained virologic response reduces risk of all-cause mortality in patients with hepatitis C. Clin Gastroenterol Hepatol. 2011; 9(6): 509–516.e1. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nvan der Meer AJ, Wedemeyer H, Feld JJ, et al.: Life expectancy in patients with chronic HCV infection and cirrhosis compared with a general population. JAMA. 2014; 312(18): 1927–1928. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nAleman S, Rahbin N, Weiland O, et al.: A risk for hepatocellular carcinoma persists long-term after sustained virologic response in patients with hepatitis C-associated liver cirrhosis. Clin Infect Dis. 2013; 57(2): 230–236. PubMed Abstract | Publisher Full Text\n\nSimmons B, Saleem J, Heath K, et al.: Long-Term Treatment Outcomes of Patients Infected With Hepatitis C Virus: A Systematic Review and Meta-analysis of the Survival Benefit of Achieving a Sustained Virological Response. Clin Infect Dis. 2015; 61(5): 730–740. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDeterding K, Höner Zu Siederdissen C, Port K, et al.: Improvement of liver function parameters in advanced HCV-associated liver cirrhosis by IFN-free antiviral therapies. Aliment Pharmacol Ther. 2015; 42(7): 889–901. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nFoster GR, Irving WL, Cheung MC, et al.: Cohort study of the impact of direct acting antiviral therapy in patients with chronic hepatitis C and decompensated cirrhosis. J Hepatol. 2016; pii: S0168-8278(16)00065-9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCharlton M, Gane E, Manns MP, et al.: Sofosbuvir and ribavirin for treatment of compensated recurrent hepatitis C virus infection after liver transplantation. Gastroenterology. 2015; 148(1): 108–117. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKwo PY, Mantry PS, Coakley E, et al.: An interferon-free antiviral regimen for HCV after liver transplantation. N Engl J Med. 2014; 371(25): 2375–2382. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nBourlière M, Bronowicki JP, de Ledinghen V, et al.: Ledipasvir-sofosbuvir with or without ribavirin to treat patients with HCV genotype 1 infection and cirrhosis non-responsive to previous protease-inhibitor therapy: a randomised, double-blind, phase 2 trial (SIRIUS). Lancet Infect Dis. 2015; 15(4): 397–404. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nDieterich D, Bacon B, Flamm S, et al.: P0775 : Final evaluation of 955 HCV patients treated with 12 week regimens containing sofosbuvir +/- simeprevir in the trio network: Academic and community treatment of a real-world, heterogeneous population. J Hepatol. 2015; 62(Supplement 2): S621. Publisher Full Text\n\nJensen DM, O'Leary JG, Pockros PJ, et al.: Safety and efficacy of sofosbuvir-containing regimens for hepatitis C: Real-world experience in a diverse, longitudinal observational cohort. Hepatology. 2014; 60: 219A–220A. Reference Source\n\nZeuzem S, Ghalib R, Reddy KR, et al.: Grazoprevir-Elbasvir Combination Therapy for Treatment-Naive Cirrhotic and Noncirrhotic Patients With Chronic Hepatitis C Virus Genotype 1, 4, or 6 Infection: A Randomized Trial. Ann Intern Med. 2015; 163(1): 1–13. PubMed Abstract | Publisher Full Text\n\nPearlman BL, Ehleben C, Perrys M: The combination of simeprevir and sofosbuvir is more effective than that of peginterferon, ribavirin, and sofosbuvir for patients with hepatitis C-related Child's class A cirrhosis. Gastroenterology. 2015; 148(4): 762–70.e2; quiz e11–2. PubMed Abstract | Publisher Full Text\n\nAqel BA, Pungpapong S, Leise M, et al.: Multicenter experience using simeprevir and sofosbuvir with or without ribavirin to treat hepatitis C genotype 1 in patients with cirrhosis. Hepatology. 2015; 62(4): 1004–1012. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nShiffman ML, James AM, Long AG, et al.: Treatment of chronic HCV with sofosbuvir and simeprevir in patients with cirrhosis and contraindications to interferon and/or ribavirin. Am J Gastroenterol. 2015; 110(8): 1179–1185. PubMed Abstract | Publisher Full Text\n\nPoordad F, Sievert W, Mollison L, et al.: Fixed-dose combination therapy with daclatasvir, asunaprevir, and beclabuvir for noncirrhotic patients with HCV genotype 1 infection. JAMA. 2015; 313(17): 1728–1735. PubMed Abstract | Publisher Full Text\n\nZeuzem S, Dusheiko GM, Salupere R, et al.: Sofosbuvir and ribavirin in HCV genotypes 2 and 3. N Engl J Med. 2014; 370(21): 1993–2001. PubMed Abstract | Publisher Full Text\n\nFoster GR, Afdhal N, Roberts SK, et al.: Sofosbuvir and Velpatasvir for HCV Genotype 2 and 3 Infection. N Engl J Med. 2015; 373(27): 2608–2617. PubMed Abstract | Publisher Full Text\n\nLeroy V, Angus P, Bronowicki JP, et al.: Daclatasvir, Sofosbuvir, and Ribavirin for Hepatitis C Virus Genotype 3 and Advanced Liver Disease: A Randomized Phase III Study (ALLY-3+). Hepatology. 2016. PubMed Abstract | Publisher Full Text\n\nManns M, Forns X, Samuel D, et al.: G02 : Ledipasvir/sofosbuvir with ribavirin is safe and efficacious in decompensated and post liver transplantation patients with HCV infection: Preliminary results of the prospective solar 2 trial. J Hepatol. 2015; 62(Supplement 2): S187–S188. Publisher Full Text\n\nReddy R, Lim JK, Kuo A, et al.: O007 : All oral HCV therapy is safe and effective in patients with decompensated cirrhosis: Interim report from the HCV-target real world experience. J Hepatol. 2015; 62(Supplement 2): S193. Publisher Full Text\n\nPoordad F, Schiff ER, Vierling JM, et al.: Daclatasvir With Sofosbuvir and Ribavirin for HCV Infection With Advanced Cirrhosis or Post-Liver Transplant Recurrence. Hepatology. 2016. PubMed Abstract | Publisher Full Text\n\nBackus LI, Belperio PS, Shahoumian TA, et al.: Effectiveness of sofosbuvir-based regimens in genotype 1 and 2 hepatitis C virus infection in 4026 U.S. Veterans. Aliment Pharmacol Ther. 2015; 42(5): 559–573. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nCurry MP, O'Leary JG, Bzowej N, et al.: Sofosbuvir and Velpatasvir for HCV in Patients with Decompensated Cirrhosis. N Engl J Med. 2015; 373(27): 2618–2628. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation"
}
|
[
{
"id": "12927",
"date": "17 Mar 2016",
"name": "Thomas von Hahn",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12928",
"date": "17 Mar 2016",
"name": "Thomas F. Baumert",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12929",
"date": "17 Mar 2016",
"name": "Thomas Berg",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-367
|
https://f1000research.com/articles/5-366/v1
|
17 Mar 16
|
{
"type": "Review",
"title": "Metals and Neurodegeneration",
"authors": [
"Pan Chen",
"Mahfuzur Rahman Miah",
"Michael Aschner",
"Mahfuzur Rahman Miah"
],
"abstract": "Metals play important roles in the human body, maintaining cell structure and regulating gene expression, neurotransmission, and antioxidant response, to name a few. However, excessive metal accumulation in the nervous system may be toxic, inducing oxidative stress, disrupting mitochondrial function, and impairing the activity of numerous enzymes. Damage caused by metal accumulation may result in permanent injuries, including severe neurological disorders. Epidemiological and clinical studies have shown a strong correlation between aberrant metal exposure and a number of neurological diseases, including Alzheimer’s disease, amyotrophic lateral sclerosis, autism spectrum disorders, Guillain–Barré disease, Gulf War syndrome, Huntington’s disease, multiple sclerosis, Parkinson’s disease, and Wilson’s disease. Here, we briefly survey the literature relating to the role of metals in neurodegeneration.",
"keywords": [
"metal accumulation",
"neurological disorders",
"Alzheimer’s disease",
"neurodegeneration",
"Huntington’s disease",
"Parkinson’s disease"
],
"content": "Introduction\n\nMetals are a component of the earth’s crust and exist in the water, air, and a variety of ecosystems. They can generally be divided into two groups: essential and non-essential metals. Essential metals include chromium, cobalt, copper (Cu), iron (Fe), lithium, magnesium, manganese (Mn), nickel, selenium, and zinc (Zn). These trace metals usually act as a cofactor of enzymes to regulate cellular activities. For example, Mn is required for the activity of arginase, hydrolases, lyases, glutamine synthetase, and superoxide dismutase (SOD)1. Thus, these metals are involved in a whole host of physiological processes, such as electron transport, oxygen transportation, protein modification, neurotransmitter synthesis2,3, redox reactions, immune responses, cell adhesion, and protein and carbohydrate metabolism1, to name a few. Metals accumulate in the brain, indicating their important roles in the nervous system. Deficiency of these metals has been associated with various neurological diseases. For example, Fe deficiency is related to restless leg syndrome, pediatric stroke, breath-holding spells, pseudotumor cerebri, and cranial nerve palsy4,5.\n\nAlthough metals are important for animals and plants, they usually are required in trace amounts. Excessive metal levels accumulate in various organs, including the brain. Elevated levels of metals may induce various detrimental intracellular events, including oxidative stress, mitochondrial dysfunction, DNA fragmentation, protein misfolding, endoplasmic reticulum (ER) stress, autophagy dysregulation, and activation of apoptosis6–13. These effects may alter neurotransmission and lead to neurodegeneration, which can manifest as cognitive problems, movement disorders, and learning and memory dysfunction. To date, metal-induced neurotoxicity has been associated with multiple neurological diseases in humans, including Alzheimer’s disease (AD), amyotrophic lateral sclerosis (ALS), autism spectrum disorders (ASDs), Guillain–Barré disease (GBD), Gulf War syndrome (GWS), Huntington’s disease (HD), manganism, multiple sclerosis, Parkinson’s disease (PD), and Wilson’s disease (WD)3,14–18. Here, we address the neurotoxicity of several metals as well as the human neurological diseases associated with these metals.\n\n\nEssential metals\n\nCu is an essential trace element and a transition metal required for physiological activities in mammals. Cu acts as a cofactor of various enzymes (such as cytochrome c oxidase and SODs), playing an important role in electron transport, oxygen transportation, protein modification, and neurotransmitter synthesis2,3. However, elevated Cu levels may result in the generation of reactive oxygen species (ROS), DNA damage, and mitochondrial dysfunction3. Excessive Cu has been associated with AD, ALS, HD, PD, WD, and prion diseases in humans3,16,19. Cu may enhance the self-aggregation of amyloid precursor proteins and β-amyloid peptide20, and increased levels of Cu in cerebrospinal fluid have been found in some patients with AD21. Similarly, Cu interacts with α-synuclein and promotes its aggregation, which could result in PD22. Gain-of-function mutations in Cu/Zn-SOD might result in oxidative stress through production of free radicals, possibly leading to motor neuron degeneration in patients with ALS3,21. It is also noteworthy that metals such as Cu and Zn are controlled by overlapping proteins, such as metallothionein23. Notably, Cu levels are also higher in HD patients compared with controls24.\n\nPrion diseases are characterized by altered structure, changing from a normal cellular isoform (PrPC) to an abnormal scrapie isoform (PrPSc), which contains high-affinity Cu-binding sites. The binding of Cu enhances the stability of prion proteins, making them resistant to proteasomal degradation and leading to neurodegeneration3. However, the binding capability of Cu to the prions does not explain its role in the progression of prion disease. It is noteworthy that metal mixtures, such as silver and Cu, have been shown to change the affinity of PrPC to Cu19. In addition, an inverse correlation between Cu and Mn has been noted in patients with prion disease25,26. Cu does not appear in the formation of PrPSc, and increases in Cu in the diet have been associated with delays in the onset of prion disease27–29. Given both the beneficial and neurotoxic effect of Cu in the brain, new biomarkers and improved measurement of Cu trafficking are needed to predict potential risks, and novel therapeutics need to be developed for Cu-induced neurotoxicity and cognitive dysfunction.\n\nFe is an essential metal, serving as a cofactor for a variety of enzymes and proteins, most prominently hemoglobin30. Fe’s ability to interact with oxygen makes it important for oxygen transport in the cellular respiration pathway as well as for a variety of redox reactions31. Exposure to Fe is primarily through food consumption, although toxic levels of Fe accumulation are usually due to disrupted Fe homeostasis and metabolism in the brain32,33. Hemolysis, the breakdown of red blood cells, in the young brain with an immature blood-brain barrier (BBB) can also lead to aberrant Fe accumulation, which results in neuronal damages34. Fe accumulation can cause increased ROS levels, lipid peroxidation, protein oxidation, DNA damage, dopamine autoxidation, and mitochondrial fragmentation35–38.\n\nFe dyshomeostasis has been linked to a variety of neurological disorders, including PD, AD, HD, ALS, and neurodegeneration with brain iron accumulation (NBIA)36,39–42. Increased brain Fe deposition has been observed and Fe has been shown to promote aggregation of α-synuclein, which is found in patients with PD43–45. Increased Fe accumulation in the brains of patients with AD has also been observed along with evidence of Fe contributing to β-amyloid aberrant aggregation and toxicity, a hallmark of the disease46–48. Increased Fe is also seen in patients with HD, and Huntingtin (htt), the central protein in HD pathology, is thought to mediate Fe homeostasis49,50. Patients with ALS show accumulation of Fe in the motor cortex, and SOD-1, a gene mutated in patients with ALS, has been shown to cause damage via Fe-induced oxidative stress51–54. Finally, NBIA, as the name implies, is an umbrella of heterogeneous neurodegenerative diseases that present with simultaneous Fe accumulation. Genetic studies indicate that the majority of the genes mutated in patients with NBIA are related not to Fe homeostasis but rather to autophagy, mitochondria metabolism, and lipid metabolism. This suggests that Fe accumulation in patients with NBIA may not be the initial insult of a disease pathology but rather a downstream phenomenon that serves to exacerbate already-present issues41. Alternatively, these genes may have currently unknown Fe regulatory functions that have yet to be examined. This question of whether Fe is part of the cause of a disease, or vice versa, continues to be a point of controversy.\n\nMn is a trace element and nutrient necessary for biological processes within the human body55. Low concentrations of Mn are essential to the body; Mn serves as a cofactor in a variety of metalloproteins, including MnSOD and arginase, and is important in the function of a variety of enzymes, including glutamine synthetase, hydrolases, and lyases55,56. Exposure to high levels of Mn may be toxic. Consumption of food is the primary route for entrance into the body56,57. Mn can be inhaled as well, and this serves as an occupational hazard for those who work in welding and mining industries1,58,59. Soy-based infant formula has been suggested as an exposure route for excess Mn, which may lead to mild neurological defects during critical stages of development60,61. Chronic Mn exposure can cause debilitating neurological effects. Mn overexposure leads to a type of parkinsonism known as manganism and has been suggested as part of PD etiology as well55,59. Manganism is characterized by tremors, lethargy, and speech impediments, with the occasional accompaniment of psychosis60,62. Mn is elevated in dopaminergic (DAergic) neurons of the substantia nigra, providing a possible basis for the motor deficits observed in manganism63. Elevated Mn has been shown to affect a variety of cellular processes, including increased levels of transcription for ER-related genes64, ROS production65, mitochondrial dysfunction66, autophagy67, altered acetylcholinesterase (AChE) activity68, changes in cyclic AMP (cAMP) signaling69, iron dyshomeostatis70, and dysfunctional astrocytic activity61. Many markers of programmed cell death, including increased TUNEL (terminal deoxynucleotidyl transferase dUTP nick end labeling) staining, internucleosomal DNA cleavage, activation of JNK, p38, the apoptotic initiator caspase-12, and pro-apoptotic effector caspase-3, have been observed in neurons in the presence of Mn exposure9,71. Specifically, Mn has been shown to induce proteolytic cleavage of protein kinase C-δ (PKC-δ) as an essential player in Mn-induced neuronal death and in the neuroprotective activity of α-synuclein protein aggregation upon chronic Mn exposure72–74. The induction of apoptosis is possibly mediated through ER stress and autophagy. In DAergic SH-SY5Y cells exposed to Mn, the levels of ER stress response proteins, including the ER chaperone GRP94 and the pro-apoptotic GADD153/CHOP protein, as well as phosphorylated eIF2α (eukaryotic translation initiation factor 2α) are increased significantly9. In Mn-treated DAergic neurons, increased abnormal lysosomes, decreased expression of autophagy-related protein Beclin1, and activation of mammalian target of rapamycin (mTOR)/p70 ribosomal protein S6 kinase (p70s6k) signaling have been observed, possibly leading to DAergic neurodegeneration8.\n\nIn addition, PD-related mutant genes (such as ATPase 12A3) have been shown to alter Mn homeostasis, supporting the link between Mn dyshomeostasis and PD. Interestingly, the newly identified Mn transporter SLC30A10 has been associated with dystonia, parkinsonism, and hypermanganesemia when mutated75–77. This protein is expressed at high levels in the liver and the basal ganglia77. Loss-of-function mutants prevent Mn excretion and result in high levels of plasma Mn, which eventually accumulates in the basal ganglia of the brain75,77. Indeed, Mn can also catalyze the autoxidation of dopamine, whose toxic metabolites can wreak havoc on DAergic cells, suggestive of similar pathology between PD and manganism37,59. In regard to prion disease, a protective role for prion protein against Mn neurotoxicity has been suggested upon short-term exposure to Mn, although prolonged Mn exposure was shown to promote the stabilization and aggregation of the infectious protein78,79. Although Mn is an essential metal, Mn homeostatic and signaling pathways are still being delineated, and further investigation may give insight into not only Mn regulation but also manganism and other forms of parkinsonism.\n\nZn is an essential trace metal (the second most abundant transition metal after Fe) required for humans and many other living organisms. It is a cofactor for over 300 enzymes and metalloproteins80, regulating gene transcription and the antioxidant response. The majority of Zn is in the testes, muscle, liver, and brain81. In childhood, Zn deficiency affects mental and physical development as well as learning abilities81,82. However, excess levels of Zn suppresses Cu and Fe absorption83, promoting ROS production in the mitochondria, disrupting activities of metabolic enzymes, and activating apoptotic processes6. Disruption of Zn homeostasis has been associated with AD, brain trauma, cerebral ischemia, epilepsy, and vascular-type dementia (VD)6,81. At low concentrations (a few micromolar), Zn suppresses β-amyloid-induced neurotoxicity by selectively precipitating aggregation intermediates84,85. However, at high levels, the binding of Zn to β-amyloid may enhance formation of fibrillar β-amyloid aggregation, leading to neurodegeneration86,87. Zn also plays a critical role in ischemia-induced neuronal death and the pathogenesis of VD, evidenced by a correlation of increased Zn concentration with glutamate being packaged into synaptic clefts during membrane depolarization under ischemic conditions81,88. Future research should assess the intracellular activities of supplemental and neurotoxic Zn in the nervous system and investigate optimal Zn doses needed for different groups of people, especially infants and children.\n\n\nNon-essential metals\n\nAluminum (Al) is the third most abundant element and the most abundant metal in the earth’s crust. It has a wide range of uses, including in food preservation, cans, cookware, cars, and vaccine adjuvants, to name a few14. The exact function of Al in animals remains unknown. Al is highly reactive with carbon and oxygen, making it toxic to living organisms. In humans, Al from dietary intake and environmental exposure is rapidly cleared by the kidney. However, Al salts in vaccine adjuvants remain biologically available and accumulate in the nervous system. Al has been associated with AD, ALS, ASDs, GBD, multiple sclerosis, and GWS in humans14,15. In patients with dialysis-associated encephalopathy, Al accumulation was found in the brain together with β-amyloid peptide accumulation89,90. Interestingly, the symptoms quickly abated after removal of Al from the dialysis solution91. Recently, a meta-analysis showed that chronic Al exposure increased the risk of AD by approximately 70%92. In addition, a correlation between the number of children with ASD and exposure to Al-adjuvanted vaccines was observed14; higher levels of Al were found in the hair, blood, and urine of children with autism93. In mice, injection of Al hydroxide results in loss of long-term memory, increased anxiety, and neuronal death in the spinal cord and motor cortex14. The neurological damage may be due to oxidative stress12,13 and mitochondrial dysfunction94–96. However, the results of many of these reports do not address confounding variables such as genetic backgrounds that may predispose an organism to the susceptibility of Al-induced neurological damage. Taken together, genetic polymorphisms combined with environmental factors likely trigger Al-induced neurotoxicity. Future studies could be profitably directed at investigating the relationship between Al exposure and genetic risk factors of these neurological diseases.\n\nCommonly used as a wood preservative in the past and known for its contamination of groundwater, Arsenic (As) is a toxic metalloid and well-known carcinogen, which over 200 million people worldwide are chronically exposed to97–100. Research suggests that As exposure induces mitochondrial oxidative stress, imbalance of intracellular Ca2+, disruption in ATP production, altered membrane potential, changes in cytoskeletal morphology, and neuronal cell death, among other effects97,101. Studies have shown that early-life exposure to As can cause lower brain weight and a reduction in glia and neurons98. As exposure is associated with AD and ALS101,102. Dimethylarsenic acid, a metabolite of As in humans, has been shown to increase β-amyloid levels, a key feature of AD103. Translocation of neurofilament (NF) was inhibited by As exposure and is linked to decreased NF content at peripheral nerves. This may be important in understanding the aberrant NF distribution that is a hallmark of ALS104. Owing to the persistent exposure of As to the human population, further investigation into the mechanisms of As poisoning is warranted.\n\nCadmium (Cd) is a non-essential transition heavy metal and known human carcinogen105. It can enter the peripheral and central neurons from the nasal mucosa or the olfactory bulb, which damages permeability of the BBB106. Miners, welders, smokers, and workers in battery production are at risk of high Cd exposure106. In cells, Cd can induce oxidative stress, suppress gene expression, and inhibit DNA damage repair and apoptosis107. Chronic exposure to Cd may severely interfere with normal function of the nervous system, and infants and children are more susceptible than adults106. Cd is a possible etiological factor of neurodegenerative diseases, including AD108 and PD17. The symptoms include headache, megrim, olfactory dysfunction, slowing of vasomotor functioning, decreased equilibrium and learning ability, and PD-like symptoms106. Jiang et al. found that Cd accelerates self-aggregation of Alzheimer’s tau peptide R3108, and it has been reported in a case study that a 64-year-old man developed PD symptoms 3 months after acute exposure to Cd fumes17. In zebrafish, Cd exposure resulted in decreased head size and unclear brain subdivision boundaries in the mid-hindbrain region109. In addition, Cd exposure has been shown to result in morphological changes of rat cortical neurons (axons and dendrites)110 and inhibited neurite outgrowth in PC12 cells111. Owing to Cd’s role as a carcinogen, the neurotoxicity induced by Cd is underestimated. Thus, future research should further investigate the mechanism of neurotoxic effect of Cd, especially that of chronic low-level Cd exposure.\n\nLead (Pb) is a non-essential heavy metal and a ubiquitously present pollutant in the ecosystem. In humans, inhalation and oral ingestion are the major routes of Pb exposure. In the body, Pb can be excreted in urine and bile, and some Pb can bind to red blood cells and eventually accumulate in bone112. Pb exposure results in oxidative stress, mitochondrial dysfunction, changes to the Golgi apparatus, and increased gliofilaments in astrocytes113. It also disrupts Ca2+ homeostasis114, interferes with the phosphorylation of PKC115, and decreases nitric oxide production116. The main target of Pb-induced toxicity is the nervous system, and children are particularly sensitive to Pb intoxication. The hippocampus is the primary region of Pb accumulation, although the metal may also accumulate in several other brain regions117. It has been reported that Pb exposure results in deficits in intelligence, memory, executive functioning and attention, processing speed, language, emotion, and visuospatial and motor skills112. For example, in children, Pb exposure results in decreased intellectual ability in a dose-dependent manner118,119, impaired verbal concept formation120, grammatical reasoning difficulty121, poor command following122, and so on. In adults, workers with occupational exposure to Pb have shown impairment of verbal memory and visual memory performance123, lower decision-making speed118, deficit in visuomotor coordination120, and increased interpersonal conflict124. Given the severe health issues caused by Pb, novel techniques for early diagnosis of Pb exposure (especially during pregnancy and childhood) and effective treatment after Pb exposure should be the focus of future research on Pb.\n\nMethylmercury (MeHg) is a xenobiotic toxic organic metal compound derived from inorganic mercury (Hg). Hg finds itself in our environment primarily through anthropogenic sources such as industrial waste, coal mining, and natural sources such as volcanoes and forest fires that release Hg back into the atmosphere125. Hg that pollutes the aquatic arena through these paths can be readily methylated into MeHg by sulfate-reducing bacteria and a variety of other anaerobic bacteria126. MeHg bioaccumulates in the aquatic food chain, and seafood consumption remains one of the main forms of exposure for humans127. MeHg has a high affinity for sulfur and can cross the BBB by binding onto thiol groups of proteins; it can also bind to lone cysteine, mimicking the structure of methionine, allowing for the possibility of uptake by amino acid transporters128,129. MeHg can accumulate in the brain and has led to epidemics in the past at Minamata Bay and Iraq, where those affected, particularly children, presented with a variety of central nervous system (CNS) disorders, including ataxia, paralysis, retardation, dysarthria, dysesthesia, and cerebral palsy130. A case study of autopsies in a family that was exposed to high levels of MeHg revealed that exposure to MeHg leads to inorganic Hg buildup in the brain. Furthermore, cerebellar and occipital lobe atrophy was observed in patients who had experienced motor and vision issues. Differential distribution of Hg content was also observed, and the greatest amounts were in the occipital lobe and cerebellum and basal ganglia, reflective of the areas important for vision and movement131. At the cellular level, MeHg is known to affect a variety of neuronal activities including dopamine metabolism132, neural stem cell differentiation133, generation of ROS134, increased calcium influx135, aberrant autophagy136,137, DNA damage, and mitochondrial dysfunction138. In addition, MeHg exposure has been shown to increase β-amyloid in the hippocampus and decrease it in the cerebrospinal fluid, both hallmarks of AD139. Currently, treatment options for those exposed to MeHg are not prevalent. Prevention of exposure has been the major development in the past few decades whereby government advisories have been established to inform and protect their respective populations140. Limitations on fully understanding the effect of MeHg on the CNS include the confounding beneficial nature of seafood by which MeHg usually enters the human body141.\n\nThallium (Tl), a naturally occurring trace element, is an extremely toxic heavy metal, sparsely found in the earth’s crust142,143. Sources of Tl include industrial processing of cement and non-industrial means such as rodenticide and eating foods from contaminated soils. Tl can make its way into the body not only through consumption but also via the skin and inhalation142,144. Non-neurological symptoms include alopecia, hepatic dysfunction, gastroenteritis, and Mees’ lines, and CNS-related disorders include polyneuropathy, cranial nerve deficits, paresthesia, loss of sensation, ataxia, and psychosis142,144–146. Victims of Tl poisoning complain of peripheral neuropathy146,147. It has been shown that Tl exposure can lead to inhibition of AChE, an enzyme catalyzing breakdown of the neurotransmitter acetylcholine (Ach), which may explain peripheral neuropathy148. Studies have shown that Tl concentrations in the brain are lower than in other parts of the body149,150 and that the highest concentrations in the brain are in the hypothalamus150. Tl+ interferes with a host of K+-dependent processes because of similarities in size and the univalent nature of the two ions; one of the affected processes is ATP generation142,149,151. At the cellular level, higher levels of Tl have been shown to cause a decrease in ATP production, increase in ROS formation, glutathione oxidation, and decreases in dopamine and serotonin levels in the brain142,151,152. Owing to available treatments for this xenobiotic metal and lack of major risk of exposure to the general public, clarity in signaling pathways remains an issue. Furthermore, the complicated symptoms may cause misdiagnosis of Tl poisoning, which points to the need for health professionals to be more aware of the features of Tl-induced poisoning and neurotoxicity153.\n\nThe neurotoxicity of metals is usually studied on an individual metal basis. However, the fact is that we are exposed to an environment of mixed metals, which makes it more complicated to study. It is noteworthy that changes in the level of one metal may have significant effect on the homeostasis of other metals, given that various metals (such as Mn, Fe, Cd, Cu, and Zn) are transported by shared transporters or controlled by overlapping signaling pathways. There are limited studies focusing on the combined effect of mixed metal exposure. The neurotoxicity of Pb with other metals (As, Cd, Hg, and Mn) is well studied154. Prenatal exposure to Pb and As tends to increase the probability of intellectual disability when compared with exposure to a single metal155. High Pb levels might affect mental and psychomotor development in children with high prenatal Cd exposure154,156. Co-exposure to high levels of Pb and Mn together in the prenatal period led to larger deficits in cognition and language development in children at two years of age compared with single-metal exposure157. Pb exposure was associated with lower IQ scores but only among children with high blood Mn levels158. In contrast to the synergetic effect between Pb and As, Pb along with Cd, Mn, or Hg exposure tends to work in an antagonistic way, given that the combined effect on cognitive deficits caused by MeHg and Pb exposure was less than additive159.\n\nIn rodents, it has been reported that co-administration of two metals might increase the retention and redistribution of individual metals160. Co-exposure of Se and Hg increased the retention of both metals and resulted in a redistribution of Hg in the blood and organs160. Chandra et al. reported that oral intake of Mn and intraperitoneal administration of Pb in rats resulted in alternations in motor activity, learning ability, and biogenic amine levels and Pb levels in the brain, which were more severe than in rats exposed to either Mn or Pb alone161. Similarly, rat brain weight decreased to a larger degree under conditions of co-exposure to both Mn and Pb than with either metal alone161. An interaction of As/Pb has been reported to affect the central monaminergic systems in mice. The As/Pb mixture enhanced Pb accumulation but reduced As accumulation in the brain, decreased norepinephrine levels in the hippocampus, and increased serotonin levels in the midbrain and frontal cortex, when compared with single-metal exposure162. In rats with oral consumption of mining waste (containing As, Cd, Mn, and Pb), accumulation of As and Mn was found in the brain, and dopamine release decreased with a long-standing polarization, when compared with the control163. Mn may exacerbate the well-documented neurotoxic effects of Pb among children, particularly at younger ages154. The metal mixture (As, Mn, and Pb) significantly decreased rat motor parameters compared with the single-metal exposure164. Given that humans are exposed to multiple metals simultaneously in real life and neurotoxicity is commonly accompanied with metal overexposure, more studies are needed to investigate the health impacts of metal mixture in the near future to better understand their synergetic or antagonistic effect.\n\n\nTreatment for metal-induced neurotoxicity\n\nUpon occurrence of metal poisoning, patients should be transferred out of the exposing environment first, followed by gastrointestinal decontamination. For example, a rapid decrease in blood plasma Mn levels has been noticed with discontinued Mn supplementation in children with cholestasis receiving total parental nutrition165. However, this therapy might not work well for patients with chronic metal exposure, given that metals have already accumulated in the nervous system, bones, and other tissues rather than in the plasma. Currently, chelation therapy is a common treatment to remove additional metals in the body for both chronic and acute metal poisoning. Chelators include British antilewisite (BAL), succimer (DMSA), Prussian blue, calcium disodium edetate (CaNa2EDTA), and D-Penicillamine (Cuprimine)166. However, the chelators themselves may have adverse effects, such as headache, fatigue, renal failure, nasal congestion, gastrointestinal side effects, and life-threatening hypocalcemia, to name a few166. The specificity of these chelators and the dosage to use are the major concerns when performing chelation therapy. The discovery of specific metal exporters provides novel therapeutics for metal-induced neurotoxicity. For example, SLC30A10 is a newly identified Mn transporter facilitating efflux of excessive intracellular Mn; patients with mutations in the gene presented with dystonia, hypermanganesemia, parkinsonism, and manganism56,77,78,167. Although a study of its complete substrates has not been finished, this protein seems to transport Mn exclusively167,168. Pharmaceutical compounds enhancing the exporting activity of SLC30A10 will promote specifically Mn efflux but leave other metals untouched. This can bypass the side effects caused by chelation to a great degree. Unfortunately, specific transporters for different metals like SLC30A10 for Mn remain largely unknown. Future studies to identify metal-specific transporters are in great need to design therapeutics to treat metal-induced toxicity.\n\n\nConclusions and future directions\n\nMetals play an important role in our daily life as they are widely involved in numerous enzymatic activities. Some of them are essential at trace amounts; however, excessive amounts in the human body usually result in neurotoxicity. AD, ALS, autism, and PD are commonly associated with metal overexposure. Once metals have accumulated in the nervous system, oxidative stress, mitochondrial dysfunction, and protein misfolding are the most common deficits associated with metal-induced toxicity6–13. Once injured, neurons have to expend greater energy to synthesize neurotransmitters and maintain homeostasis. The increased burden combined with the neurotoxicity may lead to neuronal death. When some neurons are lost, the job has to be passed on to other neurons, initiating a vicious cycle of toxicity. Given that the nervous system does not regenerate as well as other systems do, the neurodegeneration and impairments usually become progressive with age, as typically seen in AD and PD. With the increase of lifespan among the general population, there is arguably a longer duration of exposure to greater levels of metals for individuals and potential increase in frequency of occurrence of neurological diseases. Accordingly, there is a growing demand to investigate the neurotoxicity resulting from metal exposure. Future studies need to focus more on the joint effect of metal mixture exposure, identifying specific transporters of each metal as well as developing target-specific therapeutics for patients with metal poisoning.",
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PubMed Abstract | Publisher Full Text | Free Full Text\n\nDavis LE, Kornfeld M, Mooney HS, et al.: Methylmercury poisoning: long-term clinical, radiological, toxicological, and pathological studies of an affected family. Ann Neurol. 1994; 35(6): 680–8. PubMed Abstract | Publisher Full Text\n\nTiernan CT, Edwin EA, Hawong HY, et al.: Methylmercury impairs canonical dopamine metabolism in rat undifferentiated pheochromocytoma (PC12) cells by indirect inhibition of aldehyde dehydrogenase. Toxicol Sci. 2015; 144(2): 347–56. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTamm C, Duckworth JK, Hermanson O, et al.: Methylmercury inhibits differentiation of rat neural stem cells via Notch signalling. Neuroreport. 2008; 19(3): 339–43. PubMed Abstract | Publisher Full Text\n\nPetroni D, Tsai J, Agrawal K, et al.: Low-dose methylmercury-induced oxidative stress, cytotoxicity, and tau-hyperphosphorylation in human neuroblastoma (SH-SY5Y) cells. Environ Toxicol. 2012; 27(9): 549–55. PubMed Abstract | Publisher Full Text\n\nSadiq S, Ghazala Z, Chowdhury A, et al.: Metal toxicity at the synapse: presynaptic, postsynaptic, and long-term effects. J Toxicol. 2012; 2012: 132671. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChang SH, Lee HJ, Kang B, et al.: Methylmercury induces caspase-dependent apoptosis and autophagy in human neural stem cells. J Toxicol Sci. 2013; 38(6): 823–31. PubMed Abstract | Publisher Full Text\n\nYuntao F, Chenjia G, Panpan Z, et al.: Role of autophagy in methylmercury-induced neurotoxicity in rat primary astrocytes. Arch Toxicol. 2016; 90(2): 333–45. PubMed Abstract | Publisher Full Text\n\nRice KM, Walker EM Jr, Wu M, et al.: Environmental mercury and its toxic effects. J Prev Med Public Health. 2014; 47(2): 74–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKim DK, Park JD, Choi BS: Mercury-induced amyloid-beta (Aβ) accumulation in the brain is mediated by disruption of Aβ transport. J Toxicol Sci. 2014; 39(4): 625–35. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nSer PH, Watanabe C: Fish advisories in the USA and Japan: risk communication and public awareness of a common idea with different backgrounds. Asia Pac J Clin Nutr. 2012; 21(4): 487–94. PubMed Abstract\n\nBudtz-Jørgensen E, Grandjean P, Weihe P: Separation of risks and benefits of seafood intake. Environ Health Perspect. 2007; 115(3): 323–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGalván-Arzate S, Santamaría A: Thallium toxicity. Toxicol Lett. 1998; 99(1): 1–13. PubMed Abstract | Publisher Full Text\n\nCvjetko P, Cvjetko I, Pavlica M: Thallium toxicity in humans. Arh Hig Rada Toksikol. 2010; 61(1): 111–9. PubMed Abstract | Publisher Full Text\n\nSaha A: Thallium toxicity: A growing concern. Indian J Occup Environ Med. 2005; 9(2): 53–56. Publisher Full Text\n\nZhao G, Ding M, Zhang B, et al.: Clinical manifestations and management of acute thallium poisoning. 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}
|
[
{
"id": "12924",
"date": "17 Mar 2016",
"name": "George Perry",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12925",
"date": "17 Mar 2016",
"name": "Anthony White",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12926",
"date": "17 Mar 2016",
"name": "Anumantha Kanthasamy",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-366
|
https://f1000research.com/articles/5-364/v1
|
16 Mar 16
|
{
"type": "Review",
"title": "Nanoparticle-Based Antimicrobials: Surface Functionality is Critical",
"authors": [
"Akash Gupta",
"Ryan F. Landis",
"Vincent M. Rotello",
"Akash Gupta",
"Ryan F. Landis"
],
"abstract": "Bacterial infections cause 300 million cases of severe illness each year worldwide. Rapidly accelerating drug resistance further exacerbates this threat to human health. While dispersed (planktonic) bacteria represent a therapeutic challenge, bacterial biofilms present major hurdles for both diagnosis and treatment. Nanoparticles have emerged recently as tools for fighting drug-resistant planktonic bacteria and biofilms. In this review, we present the use of nanoparticles as active antimicrobial agents and drug delivery vehicles for antibacterial therapeutics. We further focus on how surface functionality of nanomaterials can be used to target both planktonic bacteria and biofilms.",
"keywords": [
"Antimicrobials",
"nanoparticles",
"bacteria",
"biofilms",
"antibacterial"
],
"content": "Introduction\n\nBacterial infections cause 300 million cases of severe illness every year with 16 million, including 2 million children, killed1. Infections caused by multi-drug-resistant (MDR) bacteria greatly increase the threat generated by bacterial infections. In addition to acute illness, bacterial infections can result in chronic disease states, where bacterial colonization develops into a biofilm, a complex three-dimensional bacterial community2. The complexity of the biofilm matrix makes biofilm-associated diseases more clinically challenging than planktonic bacteria in both diagnosis and treatment3. Finally, there has been a significant decrease in the number of approved antibiotics recently, contributing to the urgency of developing alternative antimicrobial agents4.\n\nNanoparticles (NPs) are emerging as weapons in our antimicrobial arsenal owing to their unique nanoscale physical and chemical properties5,6. For example, NP size is commensurate with biomolecular and bacterial cellular systems, providing a platform where nanomaterial-bacteria interactions can be fine-tuned through appropriate surface functionalization7,8. Moreover, the high surface area to volume ratio of nanomaterials enables high loading of therapeutics, with promising synergy arising from multivalent interactions. NPs provide a way to address the common mechanisms of antibiotic resistance, such as permeability regulation9,10, multi-drug efflux pumps11, antibiotic degradation12,13, and target site binding affinity mutations14. NPs also provide alternative pathways to combat biofilm/MDR infections and significantly lower bacteria resistance over time15–17. NPs utilize multiple mechanisms to kill bacteria, making it difficult for them to adapt existing strategies for developing resistance18. Following this strategy, several NP-based systems have been developed to improve antimicrobial efficacy (Figure 1)19–21. In this review, we will focus on recent studies that use engineered NPs as active therapeutic agents or as delivery vehicles to transport drugs to the site of infection.\n\n\nNanoparticle interactions with bacteria and biofilms\n\nEngineering the interactions of nanomaterials with bacteria/biofilm matrices plays a crucial role in designing NP-based antimicrobial systems. The surface properties of NPs are highly versatile and can be easily modulated through ligand engineering to generate particles with new and emergent properties22–24. These NPs can be utilized for not only therapeutic applications but also fundamental studies on bacterial behavior. In early studies of NP-microbe interactions, Rotello and co-workers showed that cationic gold NPs (AuNPs) possessed toxicity against bacteria25. Subsequently, they demonstrated that hydrophobic, cationic AuNPs developed spatiotemporal aggregate patterns on the bacterial surface. The aggregate patterns depended upon the nature of the bacteria as well as the size of the NPs. In this work, 6 nm AuNPs were found to have low toxicity, whereas 2 nm AuNPs rapidly lysed Bacillus subtilis but not Escherichia coli26. In a similar study, Feng and co-workers further corroborated the fact that NP and bacterial surface chemistry impact NP-bacteria interactions and toxicity. They reported that the NPs with maximal cationic charge associated most significantly with the bacterial surfaces, inducing the greatest membrane damage and toxicity27. These studies provide valuable insight into designing therapeutic constructs for planktonic bacteria treatment.\n\nBacteria can self-colonize to form biofilms. Biofilm infections are difficult to treat because the extracellular matrix produced by bacteria creates a microenvironment within the host. This allows bacteria to evade immune responses and dramatically increase resistance to traditional antibiotic treatments28,29. The complex architecture, dynamics, and composition of extracellular polymeric substances (EPS) in the matrix are profoundly responsible for the low penetration of therapeutic agents30. Diffusion of therapeutics inside the biofilm can be affected by several genetic and physiological heterogeneities such as the hydrophobicity of bacterial cell walls31. Hence, fundamentally understanding the interactions between NPs and complex biofilm matrices is crucial in designing materials for biofilm treatment.\n\nThe penetration and deposition of NPs within the biofilms are key components for the design of biofilm therapeutics. Peulen and Wilkinson reported that the penetration ability of NPs decreased inversely to their size due to small pore sizes within biofilms32. Furthermore, NP deposition inside the biofilms is largely dependent upon the electrostatic interaction as well as the homogeneity of the charges across the biofilm surface. In a related study, Rotello and co-workers provided further insight on the penetration ability of the NPs inside the biofilms. They demonstrated that the neutral and anionic quantum dots (QDs) did not show any penetration inside the biofilms, while cationic QDs were widely distributed throughout the biofilm. Furthermore, cationic QDs with hydrophobic terminal groups were found inside the bacterial cells, whereas their hydrophilic counterparts remained in the EPS matrix of the biofilm (Figure 2)33.\n\na) Quantum dots used in study. b) Micrographs of microtomed slices of the biofilm showing no penetration by anionic and neutral particles and efficient infiltration by cationic quantum dots33.\n\n\nNanoparticles as active antimicrobial agents\n\nNPs provide multiple attributes that facilitate the development of unique antimicrobial strategies34,35. NPs can interact with and penetrate bacterial cells with unique bacteriostatic and bactericidal mechanisms36. For example, possessing slightly larger diameters than drug efflux pumps, NPs can potentially reduce efflux-mediated extrusion37,38. Exploiting these characteristic properties, several NP-based systems have been employed for antimicrobial applications. Xu and co-workers demonstrated enhanced in vitro antibacterial activities of vancomycin-capped AuNPs (Au-Van) against vancomycin-resistant enterococci and E. coli strains39. Similarly, Feldheim and co-workers demonstrated that antimicrobial activity of NPs functionalized with non-antibiotic molecules depended upon their composition on the surface40. These studies indicate that modulating NP surfaces exhibits great potential for antimicrobial therapy. However, further studies on how NP surface functionality modulates antimicrobial activity can provide valuable information for future NP-based antimicrobial agents.\n\nIn a recent study, the Rotello group reported a strategy to combat MDR bacteria by engineering the ligands on NP surfaces. Cationic and hydrophobic functionalized AuNPs effectively suppressed the growth of 11 clinical MDR isolates at low concentrations (Figure 3). The minimum inhibitory concentrations (MICs) observed for these systems with most bacteria strains was 16 nM. Moreover, bacteria strains did not develop resistance against NPs, even after 20 passages at sub-MIC concentrations, which is far beyond that of traditional antibiotics41. Overall, this study provides an excellent starting platform to design antibacterial therapeutics in future studies.\n\na) Nanoparticles studied, featuring 2 nm gold cores. b) Toxicity of nanoparticles to a laboratory Escherichia coli strain. c) Minimum inhibitory concentrations of nanoparticle 3 against multi-drug-resistant bacteria41.\n\nThe antibacterial activity of silver has been well established. High surface area and concomitant increase in dissolution rate are key to its use in silver-based antimicrobials, where free Ag+ ions are the active agents42. However, they face certain shortcomings, such as high toxicity to mammalian cells and limited penetration in biofilm matrices43,44. Recent studies have focused on countering these issues by using inherent NP properties and surface functionalization as their toolkit. For example, Mahmoudi and co-workers developed silver ring-coated superparamagnetic iron oxide NPs (SPIONS) with ligand gaps that demonstrated high antimicrobial activity and remarkable compatibility with healthy cells. Additionally, these NPs exhibited enhanced activity against biofilm infections due to deeper penetration under an external magnetic field45.\n\nGraphene NPs46, AuNPs47, and carbon nanotubes48 possess photothermal properties that can be utilized to design therapeutic agents. These nanomaterials absorb light (700–1100 nm) and release heat. Ling and co-workers designed graphene-based photothermal NPs that captured and killed Staphylococcus aureus and E. coli bacteria upon near-infrared (NIR) laser irradiation. In this approach, graphene oxide was reduced and functionalized with magnetic NPs (MRGO). These NPs were functionalized with glutaraldehyde (GA) to induce excellent crosslinking properties with Gram-positive and Gram-negative bacteria (Figure 4). Rapid and effective killing of 99% of both bacterial species was achieved upon NIR irradiation49.\n\n\nNanoparticles as drug delivery vehicles for antibacterial therapy\n\nBacterial infections are able to evade antibiotic treatment through reduced bactericidal concentration or reduced antimicrobial activity of therapeutic agents at the site of infection50,51. Localized delivery of the drugs/antimicrobials can increase their therapeutic efficacy. Therefore, NPs can serve as promising drug delivery vehicles owing to their tunable surface functionality, biocompatibility, and high drug loading capacity17.\n\nNPs such as mesoporous silica possess a uniquely large surface area and tunable pore size that make them promising candidates for designing drug delivery vehicles52. For example, Schoenfisch and co-workers designed amine-functionalized silica NPs that were able to readily penetrate and eradicate pathogenic biofilms through rapid nitric oxide release53. Similarly, silica NPs have been fabricated as scaffolds for silver NP (AgNP) release54. Using NPs for controlled antimicrobial release can markedly improve their biocompatibility with mammalian cells and mitigate their hazardous environmental impact55–57. In one such study, biodegradable lignin-core NPs (EbNPs) infused with silver ions were proposed as greener alternatives to AgNPs. EbNPs were coated with cationic polyelectrolytes and loaded with Ag+ ions. These NPs exhibited broad-spectrum biocidal action against Gram-positive and Gram-negative bacteria at lower Ag+ ion concentrations than conventional AgNPs58.\n\nTherapeutic selectivity is critical when designing effective drug delivery vehicles. Triggered release of antimicrobials from these nanocarriers can be an alternative strategy to diminish their undesirable side effects59,60. In one particular study, Langer and co-workers designed PLGA-PLH-PEG NPs as a carrier to deliver vancomycin to bacterial cells, exploiting their localized acidity. PLGA-PLH-PEG NPs demonstrated high binding affinity to bacterial cells at pH 6.0 as compared to 7.4. Vancomycin-encapsulated NPs exhibited a 1.3-fold increase in the MIC against S. aureus as compared to 2.0-fold and 2.3-fold for free and PLGA-PEG-encapsulated vancomycin, respectively61. In a similar study, pH-responsive NPs were used to deliver hydrophobic drugs to biofilm moieties. Polymeric NPs used in this study consisted of a cationic outer shell to bind with the EPS matrix and a pH-responsive hydrophobic inner shell to release encapsulated farnesol molecules on demand. These scaffolds resulted in a 2-fold increase in efficacy in the treatment of biofilms as compared to the drug alone62.\n\nApart from acidic microenvironments, NPs can be designed to trigger antibiotic release upon exposure to bacterial toxins. For example, Zhang and co-workers designed AuNP-stabilized phospholipid liposomes (AuChi-liposomes) that respond to bacterial toxins. Chitosan-functionalized AuNPs were adsorbed on the liposomal surfaces to provide stability and prevent undesirable antibiotic leakage. In the presence of α-toxin-secreting S. aureus bacteria, AuChi-liposomes released vancomycin that effectively inhibited their growth63.\n\nCationic NPs exhibit excellent penetration ability in biofilms64. Moreover, they can self-assemble at the oil-water interfaces to generate nanocapsules65. Combining these two characteristic features, Rotello and co-workers generated a highly effective therapeutic system for the treatment of bacterial biofilm infections. Peppermint oil and cinnamaldehyde were chosen as the therapeutic oil template, owing to their inherent antimicrobial nature, in combination with amine-functionalized cationic silica NPs that stabilized the oil-water interface to generate nanocapsules (CP-caps) (Figure 5). These capsules were further stabilized by the formation of hydrophobic Schiff bases upon reacting with cinnamaldehyde. The cationic NPs enabled the capsules to readily penetrate the biofilms and release the antimicrobial oils to eradicate the biofilm infections. Moreover, the therapeutic selectivity of CP-caps was tested on a biofilm-fibroblast cell co-culture model. These studies showed effective biofilm infection eradication with simultaneous growth enhancement of fibroblast cells66.\n\na) Fabrication of capsules. b) Efficacy of cinnamaldehyde dissolved in peppermint oil capsule (CP-Cap) and controls against a clinical isolate of methicillin-resistant Staphylococcus aureus. c) Toxicity of CP-Cap against Escherichia coli cells while enhancing fibroblast viability66.\n\nHigh therapeutic selectivity makes these capsules useful antimicrobial agents for topical administration. Use of these nanomaterials systemically, however, requires an understanding of NP pharmacokinetics (PK) and biodistribution (BD). The PK and BD properties of NPs depend on several factors such as their size, shape, and surface functionalization67,68. Apart from their physiochemical characteristics, the administration route of NPs likewise determines their systemic or local effect. For example, intravenous injection is used for targeting the liver and spleen, whereas mucoadhesive NPs are used for oral and nasal drug delivery69. Similarly, uptake and elimination of NPs in cells/tissues are dependent upon their physiochemical properties70. For example, cationic NPs have higher uptake and slower rate of exocytosis in cells as compared to their anionic counterparts25,71. Hence, evaluating the PK behavior of the current antimicrobial systems is important for their translation into the clinic.\n\n\nConclusion\n\nNPs provide a versatile platform in designing materials for antimicrobial therapy. Tunable surface functionality and multivalency makes them promising candidates to target planktonic bacteria. Moreover, excellent biofilm penetration enhances their activity towards a range of biofilm-based infections. NP-based antimicrobial agents can be readily used for ex vivo applications such as sterilizers for surfaces and devices. The most accessible target in the near future includes the topical applications of NP-based systems for wound healing. However, further studies at the fundamental, biological, and pharmacological level are required to enable systemic administration of these antimicrobials. In conclusion, NPs have offered promising avenues to design effective next-generation therapeutics against bacterial threats.\n\n\nAbbreviations\n\nAgNP, silver nanoparticle; AuChi-liposomes, AuNP stabilized phospholipid liposomes; AuNPs, gold nanoparticles; Au-Van, vancomycin-capped AuNPs; CP-caps, cinnamaldehyde dissolved in peppermint oil capsules; EbNPs, lignin-core nanoparticles; EPS, extracellular polymeric substances; GA, glutaraldehyde; MDR, multi-drug resistance; MIC, minimum inhibitory concentration; MRGO, mildly reduced graphene oxide functionalized with magnetic nanoparticles; NIR, near-infrared; NPs, nanoparticles; PK, pharmacokinetics; PLGA-PLH-PEG, poly(D,L-lactic-co-glycolic acid)-b-poly(L-histidine)-b-poly-(ethylene glycol); QDs, quantum dots; SPIONS, superparamagnetic iron oxide nanoparticles.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThis research was funded by the National Institutes of Health (GM077173) and the National Science Foundation (CHE- 1307021).\n\nThe funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nPrüss A, Kay D, Fewtrell L, et al.: Estimating the burden of disease from water, sanitation, and hygiene at a global level. Environ Health Perspect. 2002; 110(5): 537–42. PubMed Abstract | Free Full Text\n\nCosterton JW, Cheng KJ, Geesey GG, et al.: Bacterial biofilms in nature and disease. Annu Rev Microbiol. 1987; 41: 435–64. PubMed Abstract | Publisher Full Text\n\nCosterton JW, Stewart PS, Greenberg EP: Bacterial biofilms: a common cause of persistent infections. Science. 1999; 284(5418): 1318–22. 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}
|
[
{
"id": "12920",
"date": "16 Mar 2016",
"name": "Marco Siccardi",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12921",
"date": "16 Mar 2016",
"name": "Charles Flexner",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-364
|
https://f1000research.com/articles/5-361/v1
|
16 Mar 16
|
{
"type": "Research Article",
"title": "Promoting development and uptake of health innovations: The Nose to Tail Tool",
"authors": [
"Archna Gupta",
"Cathy Thorpe",
"Onil Bhattacharyya",
"Merrick Zwarenstein",
"Cathy Thorpe",
"Onil Bhattacharyya",
"Merrick Zwarenstein"
],
"abstract": "IntroductionHealth sector management is increasingly complex as new health technologies, treatments, and innovative service delivery strategies are developed. Many of these innovations are implemented prematurely, or fail to be implemented at scale, resulting in substantial wasted resources. MethodsA scoping review was conducted to identify articles that described the scale up process conceptually or that described an instance in which a healthcare innovation was scaled up. We define scale up as the expansion and extension of delivery or access to an innovation for all end users in a jurisdiction who will benefit from it.ResultsSixty nine articles were eligible for review. Frequently described stages in the innovation process and contextual issues that influence progress through each stage were mapped. 16 stages were identified: 12 deliberation and 4 action stages. Included papers suggest that innovations progress through stages of maturity and the uptake of innovation depends on the innovation aligning with the interests of 3 critical stakeholder groups (innovators, end users and the decision makers) and is also influenced by 3 broader contexts (social and physical environment, the health system, and the regulatory, political and economic environment). The 16 stages form the rows of the Nose to Tail Tool (NTT) grid and the 6 contingency factors form columns. The resulting stage-by-issue grid consists of 72 cells, each populated with cell-specific questions, prompts and considerations from the reviewed literature.ConclusionWe offer a tool that helps stakeholders identify the stage of maturity of their innovation, helps facilitate deliberative discussions on the key considerations for each major stakeholder group and the major contextual barriers that the innovation faces. We believe the NTT will help to identify potential problems that the innovation will face and facilitates early modification, before large investments are made in a potentially flawed solution.",
"keywords": [
"Health innovation",
"pilot test",
"implementation",
"scale up",
"stakeholders",
"researchers",
"end users",
"decision makers"
],
"content": "Introduction\n\nWhile innovation in drugs, technologies, procedures and healthcare delivery approaches is a major influence on health systems, uncertainty around their benefits and unintended consequences complicates the management of innovation in the healthcare system. While innovation is almost universally attempted the vast majority of health innovation ideas do not progress into viable products, services or changes in healthcare delivery. Few of those that are successfully developed and pilot tested in one locale are implemented effectively or achieve expected outcomes in that initial locale, and even fewer scale up to their full potential, eventually to be institutionalized into common practice: fewer than 5 percent of drug or technology innovations reach scale and are sustained1. And yet, this low success rate for scaling up a new health intervention takes on average 14 years and 2 billion US dollars per successful effort; the cost of the unsuccessful efforts is unknown and not included. The proportion of successes is simply not known for health service delivery or policy changes, nor is the cost known. Given the relatively low investment in early stage development and evaluation of healthcare delivery innovations, and the absence of a regulatory framework judging the balance of benefits, cost and harm, the success rate may be even lower.\n\nAnalyses of unsuccessful efforts to scale up innovations provides insights into why scale up is rare2. Common challenges include underestimating the resources required for scale up, failure to understand the importance of politics and policy in successful scale up, not considering the conditions needed for scale up early in the process of innovation development and an overemphasis of either the vertical or horizontal spread of innovations as opposed to considering both2. This relatively simple set of causes is belied by the chaos of the theoretical literature on the same topic. A recent review of models and frameworks for dissemination and implementation found 61 such frameworks3,4, many overlapping conceptually, but with no common terminology. A shared terminology would improve communication among and between researchers and implementation groups3.\n\nBased on the apparent simplicity of the problems inhibiting successful scale up, and doubting the value of yet another theoretical framework, we elected to take a different approach to the problem of improving success in the scale up of innovations5. In this paper we describe an atheoretical, stage based tool that was developed for stakeholders, who may be developing, testing, implementing, funding or regulating a particular innovation. The tool helps stakeholders identify the stage of maturity of their innovation and helps facilitate deliberative discussions on the key considerations for major stakeholder groups and the major contextual barriers that the innovation faces. The goal is to help innovation teams identify which issues have been successfully managed up to their present stage of development and identify issues that still need to be addressed to move the innovation forward towards scale up. The tool incorporates research papers from several “disciplines”, such as rapid cycle innovation, dissemination and implementation science, knowledge translation and quality improvement that currently study innovation development and deployment. We merge ideas from all of these into an overarching tool that goes from nose (the problem and the initial idea for its solution) to tail (scale up and sustaining the solution) of the innovation process.\n\nThe Nose to Tail Tool (NTT) is intended to offer innovation teams, consisting of innovators and the essential stakeholders including end users and decision makers, a guide to: (a) identify what stage in the process their idea/innovation is at; (b) identify key considerations from each stakeholder perspective that should be addressed at the stage that their innovation has reached; and (c) identify contextual barriers at that stage that may be fatal to an innovation’s success and which must be overcome to move forward. The NTT is a comprehensive and consistent way of prompting context and stakeholder aware planning through the entire innovation process. The tool was designed with the belief that if stakeholders of an innovation consider the end stages from the very beginning of the process their innovation is more likely to achieve scale up and institutionalization2,6,7. This tool helps innovation teams identify barriers, both those that can be overcome, and those that cannot, early in the innovation process, giving teams an opportunity to re-design the innovation at an early stage, or the opportunity to cease work on the project before too many resources have been invested.\n\nThe tool is aimed at newly developed innovations in healthcare and it is assumed that innovators have already excluded the availability of an existing intervention, either from the health field or products in another field that could potentially address the problem. The tool however can also be used to adapt existing innovations, developed elsewhere or for another situation or problem, into a different context.\n\nHealth innovations can be described as discrete innovations, multicomponent interventions and paradigmatic innovations2. Discrete innovations are simple and well defined such as zinc in early childhood8, combination therapy ART9 or the use of new technology for diagnosis and treatment of TB10. Multicomponent interventions involve several interacting program elements to produce a composite set of innovations that may also be targeted at multiple system levels2. Examples include multilevel initiatives to decrease childhood obesity11 or scale up of post abortion care services12. Paradigmatic innovations require a shift in the way we understand health problems and the potential solutions to address them2. China’s quality of care reforms for family planning, is an example, which required a systems wide approach, and partnerships between international groups and all levels of governments in China, including those that extend outside of public health13. Paradigmatic innovations attempt to address the causes of poor health by using a determinants of health approach; they are complex, require a systems level approach and partnerships among key stakeholders from across sectors2. Given their size and complexity, paradigmatic innovations are more difficult to stage and assess feasibility; however, in many cases they can be broken down into several smaller components similar to individual discrete or multicomponent innovations working together. The NTT may be most usefully applied to simple and multicomponent innovations; including service delivery, diagnostic, product, device or information technology innovations.\n\n\nMethodology\n\nWe conducted a scoping review of the literature to identify whether a pre-existing dialogue or tool existed that could be used to help innovators and decision makers successfully implement and scale up innovations14. Through this review it was identified that such a tool did not exist.\n\nThe initial search terms used for the scoping review were duplicated from Yamey’s article, “Scaling Up Global Health Interventions: A proposed Framework for Success.”15 The search terms “global health” in text or “international health” in text and “implementation science” in title [ti] and abstract [ab] or “scaling up” in title or “scaling-up” in title were used in PubMed on June 19, 2013. Non-English articles were excluded. This search resulted in 13 full text articles. The titles and abstracts for these articles were reviewed by MZ and 5 articles were selected. Articles were selected if they described a process whereby an innovation was scaled up or if authors conceptually described the scale up process. We were specifically interested in papers that highlighted the process of jurisdiction or organization wide scale up. To broaden the review for global coverage, a second search was done in PubMed excluding the terms “global health” and “international health, leaving “implementation science[tiab] OR scaling up[ti] OR scaling-up[ti]”. This search strategy retrieved 383 full text articles. The titles and abstracts for these articles were reviewed by MZ and 60 additional articles from this second set were deemed relevant for a total of 65 articles. Articles were then read in full and validated by AG and two articles were excluded. Additional articles (n=6) were then included from the reference lists of papers identified in PubMed searches, from key informants in the field, and from the investigator’s own files. In total 69 articles were included. Over half of the articles reviewed (n=35) come from literature based in or describing innovations in the low and middle income country (LMIC) context.\n\nThe scoping review was not meant to be an extensive literature review, but rather a means to identify, using the qualitative research concept of saturation, enough relevant studies to describe a coherent set of stages of the innovation process and the major considerations for each stage. Key information from the literature was sorted and charted according to the key issues and themes using a narrative review approach. All articles were printed and read in full with key phrases and sections typed manually into an Excel spreadsheet (Dataset 1). Information was recorded under the following headings: Authors, Title, Summary and Purpose, Referenced Papers and Theories, Stages Discussed, Methods Used, Research Values, and Details of the Stages Discussed. The information was then collated and summarized paying attention to the frequency in which ideas appeared. The literature was reviewed until saturation was reached. The scoping review was conducted using a realist approach utilizing a heterogeneous collection of studies including primary papers as well as reviews; papers were included if they described a process whereby an innovation was scaled up or conceptually described the scale up process; data extraction and analysis used an iterative approach; and an iterative approach was also used to extract and analyze data16.\n\nThe included articles from the search (n=63) were reviewed by AG to define and map frequently described stages in the innovation process and themes that influence success in these stages. The articles were reviewed again to identify contingency factors and important considerations that should be asked at each stage. These contingency factors were sub-categorized under the two broad themes.\n\nDevelopment of the tool, including stages, definitions and contingency factors was an iterative process. In the first iteration AG reviewed the articles and proposed a number of stages. After discussion with MZ and CT, stages were agreed on, which were then validated against the included articles. We repeated this process for both themes and then contingency factors. Each of the three categorizations (stages, themes and contingency factors) went through three iterations. After these three iterations, we reached the point where the stages and contingency factors were well defined and mutually exclusive. We regarded this process as complete when AG and MZ could use the tool independently to categorize both stage and contingency factors for a large group of innovations in the same way. From these 63 articles we successfully built a grid with series of rows (stages) and columns (contingency factors) resulting in 72 cells, into which content from these articles were added and edited to avoid duplication within each cell. This text was reframed in the form of asking questions to the user of the tool. When we completed the extraction of information from the 63 articles we felt some cells were insufficiently detailed so we then snowballed from the reference lists of the included papers and sought suggestions for other papers from authors and experts. An additional 6 articles were included to increase content in these identified cells. At this point we agreed that each cell had sufficient coverage. Finally, the tool was compared by AG to other frameworks and tools that were described in the literature reviewed to identify similarities and differences.\n\n\nResults\n\nFrom the primary literature we identified sixteen commonly described stages of innovation development: (1) identify the problem12,17–24, (2) develop the innovation15,21,22,24–31; (3) design the pilot test17,22,29–31; (4) pilot test; (5) evaluate the pilot test13,22,24–26,31–34; (6) decide to implement12,15,17,19,21,22,28,35–41; (7) plan the implementation15,17,21–25,27,28,33,35–40,42–49; (8) implement; (9) evaluate the implementation22–27,31,32,42,48,50–53; (10) test for extensibility25,26,31,51,53,54; (11) decide to scale up12,18,20,52,53,55–59; (12) plan the scale up12,13,20,27,31,33,34,36,42,47,52,55–67; (13) scale up; (14) evaluate the scale up11,18,31,42,52,68; (15) monitor the scale up17,36,56,68; and (16) institutionalize12,13,42,47. These sixteen stages are used as the rows of the NTT grid (Figure 1). Of the sixteen stages 12 are considered deliberation stages (1–3, 5–7, 9–13, 14–16) and 4 are action stages (4,8,13,16). Stages 3, 7, 12 and 15 are considered design and planning stages which prepare innovation teams for the action stages 4, 8, 13 and 16. Stages 5, 9, and 14 are evaluation stages. Stages 6 and 11 are unique in that they are decision stages that encourage innovation teams to consider critically whether they are ready for implementation or scale up.\n\nStage 10, testing for extensibility, is unique because the concept of the stage was acquired by the scoping review, however nowhere in the literature was it defined. It was typically described as an undertaking that would aid with successful scale up, however given its significance, we defined it as a stage in itself. Extensibility in the NTT defines the stage where innovation teams should “conduct multiple studies in various settings and with variable populations” to ensure that the innovation can produce positive outcomes in contextually different, or heterogeneous, environments54. If through testing it is shown that the innovation is no longer as effective, innovation teams should try modifying adaptable components of the innovation. Many interventions are complex and can be conceptualized as being composed of core essential components that cannot be altered without harming integrity and adaptable components that can be altered to fit context25,31. In our model, it is during the first 5 stages that innovation teams should be preparing for future extensibility; considering the need for future adjustment, adaption or growth. The term “extensibility” is borrowed from the field of software and systems engineering which describes it as “the ability of a system to be extended with new functionality with minimal or no effects on its internal structure”69 or the “capability to adjust and adopt to a variety of reporting [or environment] demands”70.\n\nScale up is most commonly described as the general process of increasing or spreading coverage of health interventions. However, given that the reviewed literature proposes that testing for extensibility is a facilitator of successful scale up, or a pre-requisite, we propose that scale up requires two steps; spread to first similar and second to different settings. This spread can be to more units, patients, facilities or settings that are rather similar to those in which initial implementation took place which we name as expansion, or spread to sites which may be different, which we name as extension. While presently there is no distinguishing use of the term expansion in knowledge translation we propose its use to mean spread to homogenous sites, contrasting nicely with extension, and its attendant meaning of stretching.\n\nIn addition to the literature suggesting that innovations progress through several stages on route to scale up and institutionalization, it also suggests that the ability to progress forward is contingent on several factors. It is dependent on the characteristics of the innovation itself21,23–25,29–31,33,34,36–38,40,42,53,55,57,62,68,71,72 and the interests of the key stakeholders including: a) innovators (researchers) who are involved in developing the innovation11,15,20,22–25,27–34,37,41–44,48,52,53,56; b) end users (the practice community and innovation users) from the health system unit (i.e. organization, clinic, hospital, community, province etc.) or patients11–13,18,20–25,27,29–31,33–39,41–43,47,48,53,56,62,65,72; and c) decision makers (government and non-government policy makers) who have policy jurisdiction within the health system unit12,13,15,18–20,25,28,32,34,36,37,40,42,43,48,53,61,62,67,72. It is also dependent on the broader context including the social and physical environment11,15,17–19,22–25,28,31,34,40,53,56,58,67, the health system unit where the innovation will be integrated (i.e. organization, clinic, hospital, community, province etc.)11,15,17,22–25,27,28,31,33,34,37,39,43,47,48,53,56–58,67, and the regulatory, political and economic environment12,13,15,17–19,22,24,25,28,34,39,40,43,48,52,53,55,57,58,61,67,68,72–74. These contingency factors are grouped into two themes including stakeholders and context factors, and are used as the headings of the columns of the NTT grid (Figure 1 and Box 1).\n\nCOLUMNS:\n\nResearchers (Innovators): Individuals involved in developing the innovation.\n\nPractice Community and Innovation Users (End Users): Individuals from the “health system unit” who will use the innovation (whether that is a health professional, administrator or patient).\n\nGovernment and non-government Policy Makers (Decision Makers): Individuals with policy jurisdiction with the end “health system unit”.\n\nPhysical and Social Environment: The broader physical and social environment where the innovation will be implemented/scaled up.\n\nHealth System (unit): Where the innovation will be integrated (organization, hospital, community, system etc.).\n\nRegulatory, Legislative and Economic Environment: The broader political and economic landscape.\n\nROWS:\n\nPilot Test: Small scale preliminary study conducted in order to evaluate questions such as the general characteristics of the innovation, cost, and potential impact and capacity to improve health outcomes.\n\nImplement: Is the process of putting an innovation into practice in such a way that it meets the necessary standards to achieve the innovations desired outcomes within specific settings. The implementation phase in the tool assumes that the innovation will be implemented in a single setting, or among sites that are contextually homogeneous.\n\nScale Up: Describes an increase in the coverage of health innovations, to both populations that are contextually similar (expand) and diverse (extend), that have been tested in order to benefit more people at a large, national, or international scale.\n\nInstitutionalize: The sustainable integration of the innovation into existing health systems as a part of their regular service delivery.\n\nThe NTT is designed such that the user’s first task is to determine which of the sixteen stages best represents the current level of maturity of the innovation. The characteristics of the innovation, along with evaluation results, for each stage are described as a standard against which users can gauge where their innovation is in the process. Figure 2 provides an example of the staging guideline used to determine if the user is at stage 6 (decide to implement).\n\nWe suggest that all stakeholders (innovators, end users, and decision makers) deliberate together to determine which stage they are at; and that they should start by reviewing the definitions from stage 1 and move forward from there, stopping when they feel they have reached a stage that is not yet completed. This first incomplete stage they reach is the stage their innovation is at.\n\nThe second task is for the users to move across the grid for that row, and review, column by column, the specific considerations for that stage, based on the 6 themes represented in the columns (3 stakeholder perspectives and 3 context factors). The questions, prompts and considerations in each cell are extracted from the reviewed literature. Users should review the questions and prompts to identify potential gaps in their innovation process and to bring attention to factors that may not have been considered sufficiently. Discussion among different stakeholders facilitates consensus on what response or development is required to move forward. Figure 3 provides an example of the types of questions decision makers should consider at stage 6 (decide to implement stage). Of note, in the NTT, action stages (4, 8, 13, and 16) do not have any questions associated with them, as the relevant questions are all considered in the planning (3, 7, and 12) or evaluation stages (5, 9, and 14) preceding and proceeding the action. Evaluation suggestions are embedded throughout the innovation process and formally included after each of the main action stages, highlighting the recognition in the literature of the importance of implementing and scaling up innovations with demonstrated effectiveness and discouraging forward movement, or promoting redevelopment, of those that do not achieve the desired results.\n\nThe tool is meant to be used by innovation teams collectively and as such, the questions associated with each stakeholder perspective are directed to that specific stakeholder group (for example, questions under end users are directed to and should be answered primarily by end users who are involved in the innovation development process). However, users of the tool are encouraged to think of the innovation process from all of the stakeholder perspectives and thus consider the questions in each of the columns, as opposed to their own column only, particularly if your team does not have key players from each of these three groups. The questions asked under the context themes are directed to all three stakeholder groups’ collectively.\n\nAlthough the NTT model appears to follow a simple, single linear path, it is anticipated that not all innovations follow this trajectory. The NTT is built such that users may enter the model at any stage, may go forwards or backwards through the stages, or may skip stages all together. The NTT is meant to be a guide to thoughtful deliberation of the innovation process and not a rigid doctrine.\n\nThe NTT grid is available at: http://nosetotailtool.org/. To access this tool, please follow the instructions available at: http://nosetotailtool.org/consent/. In brief, following registration users are provided with the password required to access the tool automatically via email.\n\nWe compared the NTT to each existing framework or implementation tool found in our search to ensure that the NTT was not duplicative. In our review we found 11 papers describing 7 different frameworks/models which defined one or more stages to the process of innovation, along with contextual factors. None of the frameworks reviewed described more than 7 of the NTT stages (stages 7–14 in Yamey’s Framework for Success in Scaling Up15) while others described as few as 3 stages (stages 7–9 in the QIF23). Individual non-framework papers touched on one or more stages, with 4 papers describing stage 16, institutionalization12,13,42,47, a stage not covered in any of the frameworks reviewed. With respect to the context columns, only one pre-existing framework (CFIR25) considered all of the contextual themes considered in the NTT. Although many frameworks described the importance of working with collaborators, only one (QIF23) developed their framework to be used by all three of the stakeholder groups (decision makers, end users, and innovators). We concluded that the NTT tool offers a more comprehensive and thus potentially useful approach to innovation in healthcare. The Supplementary material provides a descriptive comparison of the NTT in contrast to the five frameworks and two tools we found. A summary of the comparisons can be found in Table 1.\n\nPARIHS – Promoting Action on Research Implementation in Health Services (Stetler)\n\n*PARIHS was orginally developed by Kitson et al. in 1998 and was revised by Stetler in 2011. This review looked at Stetler’s revised version.\n\nCFIR – Consilidated Framework for Implementation Research (Damschroder)\n\nT0 – T4 - Glasgow’s 5 Key phases in moving Research to Practice/Policy (Glasgow)\n\nQIF – Quality Implementation Framework (Meyers)\n\nFramework for Success in Scaling Up (Yamey)\n\nAIDED (Perez-Escamillla)\n\nConceptual Model of Evidenced-Based Practice Implementaiton (Aarons)\n\n\nDiscussion\n\nA striking, yet common theme in much of the literature was the need for improved collaborations among key stakeholders, which we identified as innovators, end users and decision makers. Deliberation is more than just a discussion of issues; it is collective “problem solving” that allows “individuals with different backgrounds, interests and values to listen, understand, potentially persuade and ultimately come to more reasoned and informed decisions”75.\n\nThe NTT has the potential to start the process of closing the gap between research and policy. Despite 40 years of attempting to translate research into evidenced based policy, barriers continue to persist76. Ellen et al. conducted a qualitative study to identify barriers and facilitators for implementing supports for evidenced informed decision making and highlights three main areas: facilitating pull efforts, establishing a climate for research use, and linkage and exchange77. Pull efforts include implementing technical infrastructures that allow “easy access” to research through physical tools; and linkage and exchange efforts which ensure that “decision makers have the necessary skills and connections to acquire, assess, adapt and apply the necessary evidence” to decision making77. From these findings however, it is evident that the authors assume that problems identified by decision makers have existing solutions or answers and the challenge is simply in finding them. We challenge that this is often not the case, and that the healthcare system is too complex to simply “join [found] solutions to problems”76. There is a process required for solving healthcare problems and that requires all stakeholders to work collaboratively from the onset and not just at the point of implementation or scale up. The NTT proposes that decision makers, end users and innovators be involved from the very beginning, the point of identifying problems in the healthcare system and remain involved throughout the development of the innovation. This allows mutual exchange of information throughout the process; it allows decision makers to discuss with innovators at the onset whether they feel that the problem at hand is a priority that needs to be solved and therefore will have support for it; it allows decision makers and end users to provide input into the design of the innovation, how it’s pilot tested, and can highlight which outcomes are important for them to support moving forward with the project. It ensures that decision makers, end users and innovators share common goals throughout the process. The NTT facilitates the potential to co-create and co-produce knowledge, developing a bridge between research and policy, which allows for a more democratic and useful knowledge exchange76.\n\nThe NTT also emphasizes the importance of collaborative decision making with end users. The field of co-creation and design is an evolving field that was born from the merging of user-centred design (“user as subject”) and the participatory approach (“user as partner”)78. Co-design and creation can broadly be defined as the creativity of designers (innovators) and people not trained in design (end users and decision makers) working together in the development process78. Healthcare innovators need to start embracing the attitudes that have led to success in the private business sector; “we believe the key ingredient of innovation is to provide a compelling experience to all participants based on network effects for value creation… a platform of innovation for convergence of expertise/ideas, collaboration among participating organizations, and co-creation of the shared value with customers should be the core of co-innovation”79. Integrating users in the early stages of the development process can have impacts with positive, long range consequences”78. Integration and collaboration throughout the innovation process at all key moments of decision making is believed to be the missing ingredient needed for sustainable solutions.\n\nThe NTT covers the innovation process from problem identification through to institutionalization, where the innovation becomes integrated into common practice. It was intentionally designed to provide a single tool covering the entire process of innovation, from the beginning to end, hence the name, Nose to Tail. The NTT prompts consideration of the most important contextual barriers, categorized in broad domains: social and physical environment, regulatory and economic considerations and health system context. Although several of the models take into consideration some of these contextual domains, only one other, the CFIR25, takes into consideration all of these, and none groups them in a way that optimizes discussion among stakeholders, as the NTT does. This comprehensiveness is intended to mimic the real world process of innovation, and allow users to assess success or delay in innovations at any stage of their lifecycle; only a comprehensive view from beginning to end allows all successes and failures to be identified. This has a practical value as it improves the continuity of the discussions between stakeholders on a given innovation.\n\nAs a tool, the NTT is intended for iterative use, by the deliberating stakeholders, alone and together, at or before each stage of the process. The NTT creates a grid which connects the stages of innovation to the relevant contextual issues, and at each stage identifies the specific concerns that might arise at that stage in relation to each of the contextual domains. This allows a stage specific, and thus more focussed, discussion on what barriers may require adaptations to the innovation, rather than a broad and generalized discussion of barriers, unconnected to the current stage of development of the innovation.\n\nThe NTT is designed to be deliberative and thus preventative, focussing discussion between multiple stakeholders, including health innovators, decision makers and end users on potential barriers to scale up as they come into view, allowing for innovations to be sequentially adapted before meeting these problems in the “real world” setting. The use of the tool is meant to practically support an innovation from the stages of development through to sustainment, or alternatively to propose the appropriate discarding of unadaptable, unacceptable, or ineffective innovations, whereby one or more stakeholder group finds an insurmountable barrier to supporting further development or implementation of the innovation.\n\nIn addition to being comprehensive in covering the entire process of innovation, the NTT is also all-inclusive in that it can support health innovation development in any healthcare system setting, whether it be in a LMIC or high income country (HIC). Over half of the literature reviewed comes from the LMIC setting. Examples of the entire innovation process, from idea to institutionalization, are more likely to be seen in LMICs given their distinctive characteristics that provide powerful incentives, or “gaps” that drive innovation80. These gaps include: (1) a performance gap that requires higher volumes of satisfactory performing innovations for lower prices boosting development low-cost innovations of acceptable quality; (2) an infrastructure gap that provides a “clean slate” where building and implementing from scratch eliminates the need to overcome existing infrastructure barriers; (3) a sustainability gap that emphasizes development of “green” solutions that will not deplete existing natural resources or cause further damage in settings with large populations; (4) a regulatory gap that reduces policy barriers on implementation and scale up of innovations; (5) and a preference gap where unique preferences from different populations promote creativity in design80,81. In the context of health care, overwhelming need adds motive to create effective solutions that are scalable80. These gaps describe why reverse innovation (RI) is possible; the process of first identifying or fostering a successful innovation in the LIC that addresses an unmet need in a HIC80,81. The NTT is consistent with RI, highlighting that lessons around innovation development can be learned from LMICs and applied to HICs; even if expenditures are different, facilitators and barriers are common in all health systems.\n\nThe NTT attempts to address the need raised by Colquhoun for a shared and overarching approach that could promote effective communication between all stakeholders3. It does so, not by creating a common language for discussing behavioural, organizational or other social sciences theories among researchers in the knowledge translation, dissemination and implementation communities, but by creating a simple scaffolding for deliberative discussion among stakeholders involved in developing, implementing and scaling up a given innovation. Its intent is practical, not theoretical5,82.\n\nAlthough the argument has been made that a shift towards theoretically driven implementation interventions is necessary83, the choice to be atheoretical was purposeful. The ICEBeRG authors assert that through the use of explicit behavioural theories that produce quantifiable results in implementation research, researchers will be better able to identify predictors of success that are common across different contexts; and should thus use these predictors to design interventions which may be more widely applicable83. We argue that the plethora of overlapping and contradicting theories makes it difficult to judge the applicability of a piece of empirical evidence in supporting one theory over another; and from a practical viewpoint argue that the usefulness of the theoretical enterprise is undermined by the challenge in designing interventions which closely match only one among several overlapping theories82. Oxman states that is time for us to “work collaboratively, based on common sense (sound practical judgment that is independent of specialized knowledge or training), sound logic and rigorous evidence to help people make informed choices about health care5. The NTT is an attempt to organize published opinion and empirical experience for this purpose.\n\nThe NTT tool could also, if the reader prefers, be considered to be an implicit, mid-range “theory”83,84 along the following rather common sense lines:\n\n1. Innovations progress through stages on route to scale up or failure to scale.\n\n2. Progress through these stages is contingent on overcoming hurdles through adaptation of the innovation.\n\n3. The hurdles are related to\n\na) features of the innovation itself;\n\nb) the broader context in which the innovation is being implemented or scaled; and\n\nc) support for development and scale up of the innovation from all stakeholders.\n\nThis “theory” gives rise to an intervention hypothesis: the process of developing a shared understanding of the different stakeholders’ perspectives through discussion improves adaptation and progress of an innovation through the stages outlined in the NTT (or leads to appropriate abandonment at an early stage).\n\nWe have derived each of the NTT stages and the contents of each cell’s prompts and issues for consideration from the literature that we reviewed. In that sense, this tool is evidence based rather than theoretical. Admittedly, many of the included papers are themselves not empirical; and even those that are descriptions of instances of innovation, at one or more stages, are not necessarily methodologically excellent, neither in qualitative nor quantitative terms. So in this sense, the NTT is taking as its raw material, a set of opinions and described experiences, and organizing these into patterns for ease of use. We find the simplicity and coherence of the grid to be attractive.\n\nThis scoping review which led to the development of the NTT used “scale up” as the central term. It was selected given the widespread agreement that many effective interventions exist to address many of the health problems but fail to be effectively implemented or scaled to sustainment. While further searching, especially using a less specific and wider set of terms e.g., “dissemination” would undoubtedly increase the number of retrieved articles enormously, it is not clear to us that this wider search would improve on the framework of stages and domains which we have assembled and for this reason we elected to move forward with our smaller range of papers now, but leave open the door for further inputs and we do not exclude the possibility of a systematic review in the future.\n\nThe NTT is not attempting to replace any of the competing theoretical frameworks, which will presumably strengthen over time, as evidence for one or another framework, or aspects of a framework, accumulates from empirical studies of innovation processes83. The NTT could be used to collect data on a large number of innovations, and the descriptive and analytic epidemiology of these instances of innovation could contribute to an empirical evidence base for these theories.\n\nUsing a brief, sensitive and specific search strategy we have identified and abstracted information from 69 published papers describing empirical instances of scale up or descriptions of frameworks for understanding or planning parts of scale up. This scoping review is only the first stage of data gathering for this tool, and was not intended to be comprehensive, but has nevertheless given us sufficient information to compose a grid of 16 distinct and well defined stages and 6 distinct and well defined contextual domains relevant to the progress of an innovation in healthcare from problem identification to sustained solution. This relatively small number of included papers allowed us to reach initial conceptual saturation, which we defined for each cell (the intersection of a stage and contextual domain) as having one or more relevant issues for deliberation between stakeholders. The number of papers contributing to each cell in the table was obviously often much smaller than that supporting most of the stages or domains and so it seems that increasing the deliberation material for each cell warrants further searching, We propose a new approach for obtaining information on issues that should be considered for each cell, namely crowdsourcing, to contribute this added detail. Crowdsourcing can be simply defined as the posting of a problem online whereby a large number of individuals have the opportunity to offer solutions to the problem85. Alongside publication of this paper, we have set up a website (nosetotailtool.org) containing the grid, with a straightforward process by which any member of the stakeholder communities can provide comments and feedback on any of the stages, domains or individual cells which we will use to improve the tool. We seek readers’ comments, preferably with specific citations to the literature or brief factual descriptions of their experiences. We will never quote you without permission, never use your information or email details other than to contact you to discuss your comment or request permission to quote you, we will delete your personal information every 24 months, and will at all times store your details in encrypted format.\n\nAt this time, we believe the NTT 1.0 is a minimally viable product (MVP)29 (positioned in stage 2 of the NTT, “Develop the Innovation”) that will evolve over time and we strongly believe that the underlying evidence base will strengthen over time. An MVP is an early prototype of the innovation that is typically deployed to as subset of possible customers, such as early adopters that are more likely to give feedback and able to grasp the innovation vision and hypothesis29. It is the version of the innovation which allows the team to collect validated learning about from users before large investments are made in its development29.\n\nIn addition to crowdsourcing we are currently conducting “hypothesis testing”29 using our prototype with healthcare innovation teams within Ontario, Canada and preliminary feedback has been positive. From this testing we have seen that the stages in the tool seem to match the users (innovators) perceptions of stages they have gone through and that the questions asked at each stage expose assumptions requiring further deliberation.\n\nIn addition to this, we are investigating some new uses to the NTT (in our terminology, extensions): we are working with healthcare funders to assess the value of the tool in innovation portfolio analysis, whereby the tool could provide an overview of the progress of a portfolio of innovations for which they are currently funding; and, although the tool already emphasizes the importance of evaluation at each stage, we are working on a review to determine what patterns or sequences of evaluation designs best support advancement of the innovation at each stage.\n\n\nConclusion\n\nThere is a mismatch between good science and the complexity of health systems. Even if you have a good idea and a good innovation that is supported by empirical science that is simply not enough; the health system is complex and good innovations alone will not necessarily be scaled in real world settings. Successful development, implementation and scale up of health innovations is a multi-stage process that requires appraisal at every stage and it is a team effort that requires true collaborations from all stakeholders at every stage. It is essential to be constantly aware of what stage the innovation is at and to identify what contextual barriers require overcoming before moving forward in the process. At present, innovations are commonly rushed through stages and even skip essential stages all together; innovations are implemented or scaled up prematurely without evaluations to verify that they are mature enough to advance forward.\n\nThe NTT tool is an atheoretical, stage based and context aware tool that helps innovators, decision makers and end users identify in a deliberative and potentially collaborative fashion, what they have done to get the innovation to its current stage and identify what needs to be done to move it forward successfully. The NTT tool is meant to be a guide to iterative deliberation through the innovation process. This tool emphasizes the need to identify barriers early and repeatedly at each stage in the innovation process. The tool may suggest a need to go back to earlier stages and re-design the innovation, or in some cases to abandon the project all together.\n\nThe NTT tool is a comprehensive and consistent way of thinking of the entire innovation process. We believe that if the end goal of widespread jurisdictional scale up and sustainment of appropriately chosen and carefully adapted innovations is kept in mind from the beginning, success is more likely.\n\n\nData availability\n\nF1000Research: Dataset 1. NTT scoping review. Includes the initial information collected from the initial 63 articles reviewed which were used to determine the stages (rows) and contingency factors (columns) for the NTT, 10.5256/f1000research.8145.d11565186",
"appendix": "Author contributions\n\n\n\nMZ, CT, AG, OB contributed to the underlying concept. AG, CT, and MZ developed the methodology and collected the data. AG produced the final design of the tool in discussions with MZ and CT. AG and MZ wrote and CT edited the manuscript. All authors read and approved the final manuscript.\n\n\nCompeting interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThis research was conducted under the Knowledge Translation and Exchange project, INSPIRE-PHC Program, supported by a grant from the Government of Ontario [#06547]. The views expressed are those of the authors and do not necessarily reflect those of the funder.\n\n\nAcknowledgements\n\nWe would like to acknowledge contributions to the initial conceptualization of this work and comments from Amanda Terry and Sandra Regan and comments from members of the Scale-Up Committee of a CIHR funded Community-Based Primary Healthcare Research Team, “Patient-Centred Innovations for Persons with Multimorbidity (PACE in MM)\", and team members of the INnovations Strengthening PrImary Healthcare through REsearch (INSPIRE-PHC) program. We would also like to acknowledge Maureen Kennedy for her work in developing the search strategy for this review.\n\n\nSupplementary material\n\nA descriptive comparison of the NTT in contrast to the five frameworks and two tools found in the scoping review.\n\n\nReferences\n\nNational Institute of Health: Clinical and translational science. 2014. Reference Source\n\nEdwards N: Scaling-up health innovations and interventions in public health: A brief review of the current state-of-the-science. 2014; 1–45. Reference Source\n\nColquhoun H, Leeman J, Michie S, et al.: Towards a common terminology: a simplified framework of interventions to promote and integrate evidence into health practices, systems, and policies. Implement Sci. 2014; 9: 51. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTabak RG, Khoong EC, Chambers DA, et al.: Bridging research and practice: models for dissemination and implementation research. Am J Prev Med. 2012; 43(3): 337–350. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOxman AD, Fretheim A, Flottorp S: The OFF theory of research utilization. J Clin Epidemiol. 2005; 58(2): 113–116; discussion 117–20. PubMed Abstract | Publisher Full Text\n\nCanadian Institutes for Health Reserach: Phase I – eHealth innovations partnership program – long description. 2014. Reference Source\n\nNilsen P: Making sense of implementation theories, models and frameworks. Implement Sci. 2015; 10: 53. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLarson CP, Saha UR, Nazrul H: Impact monitoring of the national scale up of zinc treatment for childhood diarrhea in Bangladesh: repeat ecologic surveys. PLoS Med. 2009; 6(11): e1000175. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHarries AD, Makombe SD, Schouten EJ, et al.: How operational research influenced the scale up of antiretroviral therapy in Malawi. Health Care Manag Sci. 2012; 15(3): 197–205. PubMed Abstract | Publisher Full Text\n\nMeyer-Rath G, Schnippel K, Long L, et al.: The impact and cost of scaling up GeneXpert MTB/RIF in South Africa. PLoS One. 2012; 7(5): e36966. PubMed Abstract | Publisher Full Text | Free Full Text\n\nde Silva-Sanigorski AM, Bolton K, Haby M, et al.: Scaling up community-based obesity prevention in Australia: background and evaluation design of the Health Promoting Communities: Being Active Eating Well initiative. BMC Public Health. 2010; 10: 65. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBillings DL, Crane BB, Benson J, et al.: Scaling-up a public health innovation: a comparative study of post-abortion care in Bolivia and Mexico. Soc Sci Med. 2007; 64(11): 2210–2222. PubMed Abstract | Publisher Full Text\n\nKaufman J, Erli Z, Zhenming X: Quality of care in China: scaling up a pilot project into a national reform program. Stud Fam Plann. 2006; 37(1): 17–28. PubMed Abstract | Publisher Full Text\n\nArksey H, O'Malley L: Scoping studies: towards a methodological framework. Int J Soc Res Meth. 2005; 8(1): 19–32. Publisher Full Text\n\nYamey G: Scaling up global health interventions: a proposed framework for success. PLoS Med. 2011; 8(6): e1001049. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPawson R, Greenhalgh T, Harvey G, et al.: Realist synthesis: an introduction. 2004. Reference Source\n\nAarons GA, Hurlburt M, Horwitz SM: Advancing a conceptual model of evidence-based practice implementation in public service sectors. Adm Policy Ment Health. 2011; 38(1): 4–23. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBezanson K, Isenman P: Scaling up nutrition: a framework for action. Food Nutr Bull. 2010; 31(1): 178–186. PubMed Abstract\n\nBuse K, Lalji N, Mayhew SH, et al.: Political feasibility of scaling-up five evidence-informed HIV interventions in Pakistan: a policy analysis. Sex Transm Infect. 2009; 85(Suppl 2): ii37–42. PubMed Abstract | Publisher Full Text\n\nChamberlain P, Roberts R, Jones H, et al.: Three collaborative models for scaling up evidence-based practices. Adm Policy Ment Health. 2012; 39(4): 278–290. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFassier JB, Durand MJ, Loisel P: 2nd place, PREMUS best paper competition: implementing return-to-work interventions for workers with low-back pain--a conceptual framework to identify barriers and facilitators. Scand J Work Environ Health. 2011; 37(2): 99–108. PubMed Abstract | Publisher Full Text\n\nGlasgow RE, Vinson C, Chambers D, et al.: National Institutes of Health approaches to dissemination and implementation science: current and future directions. Am J Public Health. 2012; 102(7): 1274–1281. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMeyers DC, Durlak JA, Wandersman A: The quality implementation framework: a synthesis of critical steps in the implementation process. 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PubMed Abstract | Publisher Full Text\n\nNyonator FK, Awoonor-Williams JK, Phillips JF, et al.: The Ghana community-based health planning and services initiative for scaling up service delivery innovation. Health Policy Plan. 2005; 20(1): 25–34. PubMed Abstract | Publisher Full Text\n\nPérez-Escamilla R, Curry L, Minhas D, et al.: Scaling up of breastfeeding promotion programs in low- and middle-income countries: the \"breastfeeding gear\" model. Adv Nutr. 2012; 3(6): 790–800. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChambers DA: The interactive systems framework for dissemination and implementation: enhancing the opportunity for implementation science. Am J Community Psychol. 2012; 50(3–4): 282–284. PubMed Abstract | Publisher Full Text\n\nLarson CP, Koehlmoos TP, Sack DA: Scaling Up of Zinc for Young Children (SUZY) Project Team. Scaling up zinc treatment of childhood diarrhoea in Bangladesh: theoretical and practical considerations guiding the SUZY Project. Health Policy Plan. 2012; 27(2): 102–114. PubMed Abstract | Publisher Full Text\n\nLeon N, Schneider H, Daviaud E: Applying a framework for assessing the health system challenges to scaling up mHealth in South Africa. BMC Med Inform Decis Mak. 2012; 12: 123. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPrata N, Passano P, Sreenivas A, et al.: Maternal mortality in developing countries: challenges in scaling-up priority interventions. Womens Health (Lond Engl). 2010; 6(2): 311–327. PubMed Abstract | Publisher Full Text\n\nRinaldi M, Miller L, Perkins R: Implementing the individual placement and support (IPS) approach for people with mental health conditions in England. Int Rev Psychiatry. 2010; 22(2): 163–172. PubMed Abstract | Publisher Full Text\n\nTkatchenko-Schmidt E, Renton A, Gevorgyan R, et al.: Prevention of HIV/AIDS among injecting drug users in Russia: opportunities and barriers to scaling-up of harm reduction programmes. Health Policy. 2008; 85(2): 162–171. PubMed Abstract | Publisher Full Text\n\nFixsen DL, Blase KA, Naoom SF, et al.: Core implementation components. Res Social Work Prac. 2009; 19(5): 531–540. Publisher Full Text\n\nHanson K, Nathan R, Marchant T, et al.: Vouchers for scaling up insecticide-treated nets in Tanzania: methods for monitoring and evaluation of a national health system intervention. BMC Public Health. 2008; 8(Suppl 1): 205. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHarvey G, Fitzgerald L, Fielden S, et al.: The NIHR Collaborations for Leadership in Applied Health Research and Care (CLAHRC) for Greater Manchester: combining empirical, theoretical and experiential evidence to design and evaluate a large-scale implementation strategy. Implement Sci. 2011; 6: 96. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHuicho L, Dávila M, Campos M, et al.: Scaling up integrated management of childhood illness to the national level: achievements and challenges in Peru. Health Policy Plan. 2005; 20(1): 14–24. PubMed Abstract | Publisher Full Text\n\nKnapp H, Anaya HD, Feld JE, et al.: Launching nurse-initiated HIV rapid testing in Veterans Affairs primary care: a comprehensive overview of a self-sustaining implementation. Int J STD AIDS. 2011; 22(12): 734–737. PubMed Abstract | Publisher Full Text\n\nNilsen P, Ståhl C, Roback K, et al.: Never the twain shall meet?--a comparison of implementation science and policy implementation research. Implement Sci. 2013; 8: 63. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPérez D, Lefèvre P, Castro M, et al.: Process-oriented fidelity research assists in evaluation, adjustment and scaling-up of community-based interventions. Health Policy Plan. 2011; 26(5): 413–422. PubMed Abstract | Publisher Full Text\n\nPowell BJ, McMillen JC, Proctor EK, et al.: A compilation of strategies for implementing clinical innovations in health and mental health. Med Care Res Rev. 2012; 69(2): 123–157. 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PubMed Abstract | Publisher Full Text\n\nMilat AJ, King L, Bauman AE, et al.: The concept of scalability: increasing the scale and potential adoption of health promotion interventions into policy and practice. Health Promot Int. 2012; 28(3): 285–298. PubMed Abstract | Publisher Full Text\n\nMcDonald SK, Keesler VA, Kauffman NJ, et al.: Scaling-up exemplary interventions. Educ Res. 2006; 35(3): 15–24. Publisher Full Text\n\nCleary SM: Commentary: Trade-offs in scaling up HIV treatment in South Africa. Health Policy Plan. 2010; 25(2): 99–101. PubMed Abstract | Publisher Full Text\n\nGilson L, Schneider H: Commentary: Managing scaling up: what are the key issues? Health Policy Plan. 2010; 25(2): 97–98. PubMed Abstract | Publisher Full Text\n\nGloyd S, Montoya P, Floriano F, et al.: Scaling up antenatal syphilis screening in Mozambique: transforming policy to action. Sex Transm Dis. 2007; 34(7 Suppl): S31–6. PubMed Abstract | Publisher Full Text\n\nHanson K, Ranson MK, Oliveira-Cruz V, et al.: Expanding access to priority health interventions: A framework for understanding the constraints to scaling-up. J Int Dev. 2003; 15(1): 1–14. Publisher Full Text\n\nMangham LJ, Hanson K: Scaling up in international health: what are the key issues? Health Policy Plan. 2010; 25(2): 85–96. PubMed Abstract | Publisher Full Text\n\nBlanchard JF, Bhattacharjee P, Kumaran S, et al.: Concepts and strategies for scaling up focused prevention for sex workers in India. Sex Transm Infect. 2008; 84(Suppl 2): ii19–23. PubMed Abstract | Publisher Full Text\n\nHanson K, Cleary S, Schneider H, et al.: Scaling up health policies and services in low- and middle-income settings. BMC Health Serv Res. 2010; 10(Suppl 1): I1. PubMed Abstract | Free Full Text\n\nHarries AD, Zachariah R, Jahn A, et al.: Scaling up antiretroviral therapy in Malawi-implications for managing other chronic diseases in resource-limited countries. J Acquir Immune Defic Syndr. 2009; 52(Suppl 1): S14–6. PubMed Abstract | Publisher Full Text\n\nLister S: 'Scaling-up' in emergencies: British NGOs after Hurricane Mitch. Disasters. 2001; 25(1): 36–47. PubMed Abstract | Publisher Full Text\n\nNorton WE, McCannon CJ, Schall MW, et al.: A stakeholder-driven agenda for advancing the science and practice of scale-up and spread in health. Implement Sci. 2012; 7: 118. PubMed Abstract | Publisher Full Text | Free Full Text\n\nQuelapio MI, Mira NR, Orillaza-Chi RB, et al.: Responding to the multidrug-resistant tuberculosis crisis: mainstreaming programmatic management to the Philippine National Tuberculosis Programme. Int J Tuberc Lung Dis. 2010; 14(6): 751–757. PubMed Abstract\n\nTansella M, Thornicroft G: Implementation science: understanding the translation of evidence into practice. Br J Psychiatry. 2009; 195(4): 283–285. PubMed Abstract | Publisher Full Text\n\nSubramanian S, Naimoli J, Matsubayashi T, et al.: Do we have the right models for scaling up health services to achieve the Millennium Development Goals? BMC Health Serv Res. 2011; 11: 336. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKumaranayake L: The economics of scaling up: cost estimation for HIV/AIDS interventions. AIDS. 2008; 22(Suppl 1): S23–33. PubMed Abstract | Publisher Full Text\n\nJohansson N, Lofgren A: Designing for extensibility: An action research study of maximizing extensibility by means of design principles. [Bachelor of Applied Information Technology]. University of Gothenburg; 2009. Reference Source\n\nDebrecency R, Felden C, Ochocki B, et al.: XBRL for interactive data: Engineering the information value chain. Berlin: Springer; 2009. Publisher Full Text\n\nKnapp H, Anaya HD, Goetz MB: Attributes of an independently self-sustaining implementation: nurse-administered HIV rapid testing in VA primary care. Qual Manag Health Care. 2010; 19(4): 292–297. PubMed Abstract | Publisher Full Text\n\nMushi HP, Mullei K, Macha J, et al.: The challenges of achieving high training coverage for IMCI: case studies from Kenya and Tanzania. Health Policy Plan. 2011; 26(5): 395–404. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLewis S: Can a learning-disabled nation learn healthcare lessons from abroad? Healthc Policy. 2007; 3(2): 19–28. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChambers DA, Glasgow RE, Stange KC: The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change. Implement Sci. 2013; 8: 117. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAbelson J, Forest PG, Eyles J, et al.: Deliberations about deliberative methods: issues in the design and evaluation of public participation processes. Soc Sci Med. 2003; 57(2): 239–251. PubMed Abstract | Publisher Full Text\n\nOliver K, Lorenc T, Innvaer S: New directions in evidence-based policy research: a critical analysis of the literature. Health Res Policy Syst. 2014; 12: 34. PubMed Abstract | Publisher Full Text | Free Full Text\n\nEllen ME, Léon G, Bouchard G, et al.: Barriers, facilitators and views about next steps to implementing supports for evidence-informed decision-making in health systems: a qualitative study. Implement Sci. 2014; 9: 179. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSanders EBN, Strappers PJ: Co-creation and the new landscapes of design. CoDesign. 2008; 4(1): 5–18. Reference Source\n\nLee SM, Olson DL, Trimi S: Co-innovation: Convergenomics, collaboration, and co-creation for organizational values. Management Decision. 2012; 50(5): 817–831. Publisher Full Text\n\nDePasse JW, Lee PT: A model for ‘reverse innovation’ in health care. Global Health. 2013; 9: 40. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGovindarajan V, Trimble C: Reverse innovation: Create far from home, win everywhere. Harvard Business Review. 2010.\n\nBhattacharyya O, Reeves S, Garfinkel S, et al.: Designing theoretically-informed implementation interventions: fine in theory, but evidence of effectiveness in practice is needed. Implement Sci. 2006; 1: 5. PubMed Abstract | Publisher Full Text | Free Full Text\n\nImproved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implement Sci. 2006; 1: 4. PubMed Abstract | Publisher Full Text | Free Full Text\n\nReeves S, Albert M, Kuper A, et al.: Why use theories in qualitative research? BMJ. 2008; 337: a949. PubMed Abstract | Publisher Full Text\n\nBrabham D: Crowdsourcing as a model for problem solving: An introduction and cases. Convergence. 2008; 14(1): 75–90. Publisher Full Text\n\nGupta A, Thorpe C, Bhattacharyya O, et al.: Dataset 1 in: Promoting development and uptake of health innovations: The Nose to Tail Tool. F1000Research. 2016. Data Source"
}
|
[
{
"id": "13086",
"date": "29 Mar 2016",
"name": "Elizabeth Molyneux",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nMuch innovation research is all about developing an innovation, with too little attention paid to how the new tool or idea will be, or can be, implemented. Gupta et al. have done a literature search of the subject to review how innovators plan (or not) for the whole process from development and funding through to implementation and commercialisation. They have developed a planning programme called the Nose to Tail Tool which provides steps for action and steps for deliberation, by all the players concerned along the entire process of innovation implementation. Specific questions are raised with different groups of people during the course of development. The NTT tool is a planning grid (of 72 boxes) which helps bring everyone together early in the development phase so that problems further down the line can be anticipated or avoided. Discussions may even lead the team to decide not to waste further time and effort on the project.Gupta states that the tool is being put to use in Canada; it will be interesting to see how effective it is; experience with using the tool will probably lead to some fine-tuning.I like the idea of the NTT. I think the paper is long, with quite a bit of repetition; but it is worth a read and the NTT could save innovators both time and money. But the proof of the pudding will be in its successful use.",
"responses": []
},
{
"id": "13642",
"date": "10 May 2016",
"name": "Jeffrey Braithwaite",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper represents a very useful development. The authors have painstakingly reviewed and synthesised the articles useful for scaling up interventions (specifically, innovations) and created a model for innovators to follow, or check their progress. This kind of staged approach is useful for those who follow logical, structured ways of thinking and working.My sole reservation is that models such as this downplay the point that health care is a complex adaptive system. In the real world, people are busy, challenged, and stressed, for the most part, and rarely use tools and frameworks in a logical, structured manner. And innovations rarely unfold in neat and tidy ways. I would like to see some recognition of this in papers such as this. Perhaps the authors in a future piece of work could factor in the complexities, and the fact that most clinicians flex and adjust their practices to meet exigencies as the real world unfurls before them.",
"responses": []
},
{
"id": "13537",
"date": "20 May 2016",
"name": "Saravana Kumar",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThank you for asking me to review this manuscript. Overall, I was pleased to read this manuscript which outlines the development of a unique tool called Nose to Tail Tool (NTT). It is innovative and in an area which has so much theoretical science (evidence implementation/implementing change) it was refreshing to read about process which resulted in the development of a practical tool that could be utilised by a range of health care stakeholders. I commend the authors for extensively reviewing the literature (although the methodology is a bit weak) and placing the NNT in comparison to other frameworks in this space.\nWhile there is a lot to like about this manuscript, there are some issues to consider too. They are:\nThe methodology – while I understand that this is a scoping review and as such a formal critical appraisal was not undertaken, I was surprised to note that the searching was confined to PubMed only. Why was this the case? PubMed is quite rudimentary and given the amount of work that has been undertaken, this could have extended to other mainstream databases too (such as Cinahl, Embase, Medline etc). I also would have liked a bit more information about the developmental process. For example, the authors state that “Each of the three categorizations (stages, themes and contingency factors) went through three iterations.” What happened during those stages? How did the authors respond to the findings during those stages?\n\nThe burden of complexity – While the NNT is quite detailed, I worry if it will also be its Achilles Heel. I suspect these tools are aimed at those at the coal face and given the complexity of the tool (I understand the reasons underpinning it), I worry many clinicians could be put off by it. A tool needs to have good clinical utility and I suspect while this may be useful for research and/or evaluation purposes, how readily and effectively clinicians use this remains to be seen. I will be interested to know about the pilot study findings.\n\nThe manuscript itself – I must say the manuscript is very long and verbose! While I am aware that F1000Research may not have a word limit, it is the duty of the researchers to ensure what is presented is reader-friendly and engaging. Given that most manuscripts are 4000 words (approx.), I think this would be double that word count. As it stands, this manuscript could be trimmed down to make it more succinct and punchy.",
"responses": []
},
{
"id": "14091",
"date": "01 Jun 2016",
"name": "Nerges Mistry",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article is extremely useful for intervention and operations researchers who examine a systemic innovation, have a successful proof of concept studies and attempt to upscale simple or complex interventions on a national or even a regional scale.\n\nThe paper aims to detangle the thought jungle that accompanies this effort and give a procedural element to this effort. This detangling itself is a laudable effort and deserves to be indexed but it maybe an effort that is fraught with deviations in various parts of the world with different dynamics between innovators, end users and the decision making environment. It would be nice for the authors to identify those willing to use the NTT in different parts of the world to guage its utility in different scenarios. Within countries also end users maybe heterogenous so the limits of scalability in a particular setting need to be contextualized. It would be interesting to see articles on NTT use in a variety of innovations a couple of years from now.\n\nSecondly as soon as an innovation is framed, a concept which seems to be missed out in the NTT is the gauging of its life span. This requires information on the evolution stage of the condition for which the innovation is planned as also the stage of parallel competitive technologies or approaches that are being worked on to obtain the same or similar output. Perhaps this is one sort of additionality that maybe inserted in Fig 1 .\n\nThe NTT would serve as a valuable checklist for both simple and complex innovations and looks promising as a reliable guidance tool. However the proof of the pudding is in the eating for which a platform may need to be consciously created to get views on its utility and the omissions.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-361
|
https://f1000research.com/articles/5-340/v1
|
14 Mar 16
|
{
"type": "Review",
"title": "Emerging Concepts in Transesophageal Echocardiography",
"authors": [
"Cory Maxwell",
"Ryan Konoske",
"Jonathan Mark",
"Ryan Konoske",
"Jonathan Mark"
],
"abstract": "Introduced in 1977, transesophageal echocardiography (TEE) offered imaging through a new acoustic window sitting directly behind the heart, allowing improved evaluation of many cardiac conditions. Shortly thereafter, TEE was applied to the intraoperative environment, as investigators quickly recognized that continuous cardiac evaluation and monitoring during surgery, particularly cardiac operations, were now possible. Among the many applications for perioperative TEE, this review will focus on four recent advances: three-dimensional TEE imaging, continuous TEE monitoring in the intensive care unit, strain imaging, and assessment of diastolic ventricular function.",
"keywords": [
"transesophageal echocardiography",
"cardiac ultrasound",
"cardiac imaging",
"Three-dimensional imaging",
"Strain imaging",
"arrhythmias"
],
"content": "Introduction\n\nClinical cardiac ultrasound, or echocardiography, is a technology that was pioneered in the post-World War II era with evolving naval sonar technology. Initial images consisted of the time-motion approach, displaying images along a single vector over time, or what we term today “M-mode” imaging1 (Figure 1). Over the subsequent 60 years, technological advances facilitated the introduction of two-dimensional (1971)2 and three-dimensional (3D) (1990s)3–5 imaging into clinical practice and have led to greater accessibility and ease of interpretation by clinicians. Transesophageal echocardiography (TEE) was introduced in 19776 and offered imaging through a new acoustic window sitting directly behind the heart, allowing improved evaluation of many cardiac conditions. It was only a short time until TEE was applied to the intraoperative environment (in 1981)7, as investigators quickly recognized that continuous cardiac evaluation and monitoring during surgery, particularly cardiac operations, were now possible. Perioperative TEE guidelines were first established by the joint efforts of the American Society of Anesthesiologists and the Society of Cardiac Anesthesiologists in 19968. European guidelines for this procedure soon followed, and there have been multiple updates published in recent years as newer TEE technologies have been developed9–12. The recent technological advances have significantly improved the perioperative care of patients with complex cardiac pathophysiology and will continue to advance both diagnostic and prognostic abilities of physicians via ultrasonography.\n\nIt is clinically useful for diagnosing and characterizing many clinical conditions, such as right ventricular function, by measuring tricuspid annular plane systolic excursion (left) or assessing dynamic left ventricular outflow tract obstruction hallmarked by fluttering and premature closure of the aortic valve leaflets (right). 2D, two-dimensional; bpm, beats per minute; MM, M-mode; PAT T, patient temperature; TEE T, transesophageal echocardiography temperature.\n\n\nThree-dimensional imaging\n\nMost major manufacturers of TEE equipment and software have developed and improved 3D technology in recent years. Owing to the limitations of the physical properties of sound, tissue, and the TEE piezoelectric crystals, both the temporal resolution and the spatial resolution are significantly decreased in this imaging modality. Advances have improved real-time 3D imaging to the point where it has now become diagnostic-quality in multiple clinical scenarios, necessitating consensus clinical guidelines for utilization13. For example, precise placement of percutaneous mitral valve edge-to-edge repair devices using 3D TEE alone has been described14. This live imaging is accomplished without the use of ionizing radiation or contrast dye, both of which are potentially harmful. The temporal resolution of imaging can be improved by decreasing the visual field or sector width or by gated acquisition (dividing the imaging sector into two, four, or six sections and splicing these images back together). Though helpful for improved resolution, gated acquisition is more demanding from a clinical perspective because artifact-free images are impaired by patient movement (including cardiac translation during respiration), cardiac arrhythmias, and surgical electrocautery. As a result, higher-resolution imaging is generally limited to the intraoperative setting, when patients are anesthetized and mechanically ventilated, so that ventilation can be interrupted to provide a cardiac target that is not distorted by respiratory movements. The improved imaging has been particularly helpful in mitral valve repair15 (Figure 2) and percutaneous transcatheter aortic valve replacement16 (Figure 3).\n\nThe native mitral valve (left) shows an anterior leaflet cleft and a posterior leaflet prolapse. Surgical repair includes mitral annuloplasty ring and Alfieri stitch (right), resulting in two distinct inflow orifices. 3D, three-dimensional; bpm, beats per minute; PAT T, patient temperature; TEE T, transesophageal echocardiography temperature.\n\nThis technique is used to guide percutaneous aortic valve replacement and has been shown to be equivalent to computed tomography angiography for this purpose. 3D, three-dimensional; bpm, beats per minute; PAT T, patient temperature; TEE T, transesophageal echocardiography temperature.\n\nIn addition to advances in 3D image quality, improvements in post-processing capabilities have led to new applications. Several investigators have shown that 3D modeling of the mitral valve can assist with surgical decision-making and improve the quality of surgical repair or predict dynamic left ventricular outflow tract obstruction after the procedure17. In patients undergoing transcatheter aortic valve replacement, computed tomographic angiography is the standard of care for measuring the aortic valve annulus; precise measurement is important to prevent an oversized valve and damage to the aorta or an undersized valve leading to perivalvular leaks. Accuracy of 3D TEE measurement of the aortic valve annulus has been shown to be equivalent to that of computed tomographic angiography and can be done without exposure to radiation or contrast dye during the actual procedure18,19 (Video 1).\n\n\nContinuous critical care monitoring\n\nThe volume status and cardiac function of critically ill patients, particularly following cardiac surgery, have traditionally been determined by using a pulmonary artery catheter, which is invasive and carries a small but non-zero risk of pulmonary artery rupture and other life-threatening complications. The efficacy of TEE as an alternative modality to accurately differentiate between cardiogenic shock or hypovolemic shock and guide management in the intensive care unit (ICU) is well established20. An emerging technology is that of the “continuous TEE” using a disposable TEE probe, which can remain in the patient for up to 72 hours in the ICU. This has shown some promise as a useful diagnostic tool for tracheally intubated patients with complex pathophysiology. The use of continuous TEE has been demonstrated to help predict neurologic outcomes of patients following cardiac arrest which is treated with hypothermic cooling21. Additionally, following valve replacement, continuous TEE monitoring has been helpful in guiding management in patients with hemodynamic instability22. Continuous TEE monitoring is a fledgling technology and as such does not have extensive cost efficacy or outcome data associated with it. Nonetheless, its role in the management of critically ill patients may be expanded and should be better defined in coming years (Video 2).\n\n\nStrain imaging\n\nOne of the more recent, yet infrequently used, technologies in clinical practice is myocardial strain analysis. Strain (ε), defined as (L − L0)/L0 where L = length at end-systole and L0 is the initial length at end-diastole, is a unit-less percentage change in myocardial deformation. Directly tracking myocardial compression and expansion throughout the cardiac cycle may offer a more load-independent measure of cardiac function. Strain essentially measures changes in sarcomere length over each cardiac cycle as opposed to percentage volume change in the left ventricular cavity, which is highly susceptible to loading, chronotropic, and inotropic states. This is particularly pertinent during intraoperative imaging, where there are abrupt changes in the aforementioned variables. Strain rate, or strain over time, may offer an even more load-independent measure of intrinsic myocardial function23.\n\nTwo modalities have been developed to assess ventricular deformation or strain. Tissue Doppler imaging uses relative tissue velocities but suffers from the limitations of Doppler imaging, most notably angle dependence24. The second method, speckle-tracking echocardiography, measures strain with acoustic markers or “speckles” on B-mode imaging and tracks their motion relative to one another. Although this method requires an adequate frame rate, it has emerged as a more robust method of strain measurement because speckles can be tracked at any angle. Longitudinal, circumferential, and radial strain can all be analyzed fully with this method. With multiple options for imaging platforms and software, strain is rapidly becoming a viable tool with multiple applications for the echocardiographer25 (Figure 4).\n\nApL, apical lateral; ApS, apical septal; BAL, basal anterolateral; BIS, basal inferoseptal; bpm, beats per minute; HR, heart rate; MAL, mid anterolateral; MIS, mid inferoseptal; SD, standard deviation; AVC, aortic valve closure; AVR-R, aortic valve R-R interval; EDV, end-diastolic volume; EF, ejection fraction; ESV, end-systolic volume; MVR-R, mitral valve R-R interval.\n\nMost of the research for use of strain in the clinical arena is focused on patients with diagnosed heart failure and preserved left ventricular ejection fraction, often termed diastolic heart failure. Patients who have normal left ventricular ejection fraction but who demonstrate reduced global longitudinal strain values have more hospital readmissions for heart failure and suffer higher mortality26. Similarly, in patients with chronic atrial fibrillation, reduced global longitudinal strain has been shown to be a stronger predictor than ejection fraction for adverse cardiac events27. Echocardiographic strain analysis is also used to assess patients being considered for cardiac resynchronization therapy. Also known as bi-ventricular pacing, resynchronization therapy is aimed at correcting intraventricular electromechanical dyssynchrony and is reserved for patients with heart failure symptoms that meet certain criteria, such as QRS duration of more than 120 ms, left ventricular ejection fraction of less than 35%, and sinus rhythm28. Recent investigations have focused on speckle-tracking echocardiography to characterize mechanical dyssynchrony as well as to optimize pacing lead positioning to achieve maximal ventricular synchrony29,30. Beyond its clinical applications in patients with heart failure, there is limited research evaluating the intraoperative application of speckle-tracking strain analysis, but a recent study has demonstrated an association of reduced global longitudinal strain with development of post-operative atrial fibrillation in patients undergoing isolated aortic valve replacement31 (Video 3).\n\n\nAssessment of diastolic function\n\nDiastology, or the study of cardiac diastolic function, has gained steam in the past decade. Historically, echocardiographic attention has been focused on the quantification of left ventricular systolic function. However, systolic dysfunction is not always the cause of heart failure: roughly 50% of patients with symptomatic heart failure have a preserved left ventricular ejection fraction32. Furthermore, specific therapies for diastolic heart failure are limited. Current guidelines promulgated by the American College of Cardiology and the American Heart Association recommend blood pressure control and diuretics in volume overloaded states, but note that there is little evidence to support additional therapies33.\n\nComprehensive assessment of left ventricular diastolic function has included multiple quantitative echocardiographic measurements, including pulsed wave Doppler assessment of mitral and pulmonary venous inflow velocities, tissue Doppler assessment of mitral annular velocities, color M-mode assessment of mitral inflow propagation velocity, and a variety of other methods. Many studies have looked at different measurement variables in the quantification of diastolic function. Therefore, in 2009, the European Association of Echocardiography, in conjunction with the American Society of Echocardiography, published guidelines for the assessment, quantification, and grading of diastolic function34. With limited therapies available for diastolic heart failure, classification of diastolic dysfunction carries mostly a prognostic value rather than serving to guide treatment options. Similarly, intraoperative decision-making based on diastolic function classification in patients undergoing cardiac surgery has limited evidence to guide specific therapy.\n\nIn 2011, Swaminathan et al. proposed a relatively simple and effective algorithm for intraoperative TEE evaluation and classification of left ventricular diastolic function35. This algorithm incorporates the measure of mitral annular tissue velocity recorded from the lateral mitral annulus in early diastole (e′), with a value of more than 10 cm/s indicating normal diastolic function. Further stratification of left ventricular diastolic dysfunction for mitral tissue Doppler velocities of less than 10 cm/s uses the ratio of early mitral inflow velocities (E) to e′. Higher E/e′ ratios are indicative of worsening left ventricular diastolic function, as early mitral inflow velocities increase while annular velocities are reduced with later stages of diastolic dysfunction (Figure 5). Despite the algorithm’s ease of use, there is an ongoing debate as to the clinical applicability of classifying degrees of left ventricular diastolic dysfunction. Although patients undergoing coronary artery bypass grafting who have left ventricular diastolic dysfunction are known to have an increased incidence of major adverse cardiac events35, there are few targeted therapies for this condition and even fewer specific guidelines for perioperative management.\n\nAccurate identification of each Doppler spectral peak requires an accompanying electrocardiographic tracing. Conditions such as atrial fibrillation, mitral annular calcification, mitral valve surgery, or extracorporeal circulatory support generally preclude using these Doppler techniques. A, late mitral inflow velocity resulting from atrial contraction; E, early mitral inflow velocity; e′, early mitral annular velocity recorded from the lateral mitral annulus.\n\nProponents of intraoperative classification argue that hemodynamic manipulation based on the underlying class of diastolic dysfunction may improve stability in the perioperative period. For example, in patients with grade 1 dysfunction (e′ < 10 cm/s and E/e′ ≤ 8), also known as impaired relaxation, maintenance of sinus rhythm with an adequate diastolic filling time (slower heart rate) is favorable, owing to a longer time period for ventricular relaxation (Figure 5). Conversely, patients presenting with more advanced (grade 2 or 3) left ventricular diastolic dysfunction (E/e′ ≥ 9) should be carefully monitored for increased intravascular volume because these patients typically have increased left atrial pressures and are at risk for development of pulmonary edema. Furthermore, higher heart rates will likely maintain cardiac output when stroke volume is relatively fixed, as seen in more advanced diastolic dysfunction36.\n\nThose who criticize efforts to assess and classify left ventricular diastolic function cite the limited evidence for targeted therapies37–39, including hemodynamic manipulation, in improving outcomes in these patients. Given the conflicting evidence for the effects of inotropic drugs on diastolic function, it is understandable that many clinicians remain skeptical of current efforts to use TEE to assess diastolic function parameters in the perioperative environment.\n\n\nConclusions\n\nWith the pace of improvement in TEE technologies that we have seen since its introduction, it is likely that further refinements and novel imaging modalities will continue to be introduced in coming years. Three-dimensional echocardiography has made the diagnosis of complex pathologies more accurate and is essential for guiding procedural interventions in real time. Improvements in real-time 3D resolution will facilitate high-quality imaging without the artifacts caused by arrhythmias and cardiac translation. Continuous TEE monitoring in the ICU has shown some early promise and in coming years may replace the pulmonary artery catheter for hemodynamic evaluation of unstable tracheally intubated patients.\n\nSpeckle-tracking and strain analysis have now been incorporated into the management of patients with chronic heart failure, but the practical use of these methods in the perioperative setting has yet to be elucidated. Current challenges include the time-consuming nature of speckle-tracking methods, which are not conducive to measurement in a busy intraoperative setting, and the clinical utility of detecting subtle reductions in systolic function. There is some evidence that in patients with preserved ejection fractions, global longitudinal strain may have predictive value in the development of post-operative atrial fibrillation. Additional studies are needed to determine the relevance of these findings.\n\nAlthough assessment and classification of diastolic function have improved and offer valuable prognostic information, there is currently little evidence to suggest that this leads to interventions that improve clinical outcomes. Despite the many advances in perioperative TEE in the past few decades, we still have opportunities ahead to improve the use of this technology for our patients.\n\n\nData availability\n\nF1000Research: Dataset 1. Video 1, 10.5256/f1000research.7169.d11545840\n\nF1000Research: Dataset 2. Video 2, 10.5256/f1000research.7169.d11545941\n\nF1000Research: Dataset 3. Video 3, 10.5256/f1000research.7169.d11546042",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nFeigenbaum H: Evolution of echocardiography. Circulation. 1996; 93(7): 1321–7. PubMed Abstract | Publisher Full Text\n\nBom N, Lancée CT, Honkoop J, et al.: Ultrasonic viewer for cross-sectional analyses of moving cardiac structures. Biomed Eng. 1971; 6(11): 500–3, 5. PubMed Abstract\n\nvon Ramm OT, Smith SW: Real time volumetric ultrasound imaging system. J Digit Imaging. 1990; 3(4): 261–6. PubMed Abstract | Publisher Full Text\n\nKühl HP, Franke A, Janssens U, et al.: Three-dimensional echocardiographic determination of left ventricular volumes and function by multiplane transesophageal transducer: dynamic in vitro validation and in vivo comparison with angiography and thermodilution. J Am Soc Echocardiogr. 1998; 11(12): 1113–24. PubMed Abstract | Publisher Full Text\n\nMartin RW, Graham MM, Kao R, et al.: Measurement of left ventricular ejection fraction and volumes with three-dimensional reconstructed transesophageal ultrasound scans: comparison to radionuclide and thermal dilution measurements. J Cardiothorac Anesth. 1989; 3(3): 260–8. PubMed Abstract | Publisher Full Text\n\nHisanaga K, Hisanaga A, Hibi N, et al.: High speed rotating scanner for transesophageal cross-sectional echocardiography. Am J Cardiol. 1980; 46(5): 837–42. PubMed Abstract | Publisher Full Text\n\nMatsumoto M, Oka Y, Strom J, et al.: Application of transesophageal echocardiography to continuous intraoperative monitoring of left ventricular performance. Am J Cardiol. 1980; 46(1): 95–105. PubMed Abstract | Publisher Full Text\n\nPractice guidelines for perioperative transesophageal echocardiography. A report by the American Society of Anesthesiologists and the Society of Cardiovascular Anesthesiologists Task Force on Transesophageal Echocardiography. Anesthesiology. 1996; 84(4): 986–1006. PubMed Abstract\n\nReeves ST, Finley AC, Skubas NJ, et al.: Basic perioperative transesophageal echocardiography examination: a consensus statement of the American Society of Echocardiography and the Society of Cardiovascular Anesthesiologists. J Am Soc Echocardiogr. 2013; 26(5): 443–56. PubMed Abstract | Publisher Full Text\n\nHahn RT, Abraham T, Adams MS, et al.: Guidelines for performing a comprehensive transesophageal echocardiographic examination: recommendations from the American Society of Echocardiography and the Society of Cardiovascular Anesthesiologists. Anesth Analg. 2014; 118(1): 21–68. PubMed Abstract | Publisher Full Text\n\nHahn RT, Abraham T, Adams MS, et al.: Guidelines for performing a comprehensive transesophageal echocardiographic examination: recommendations from the American Society of Echocardiography and the Society of Cardiovascular Anesthesiologists. J Am Soc Echocardiogr. 2013; 26(9): 921–64. PubMed Abstract | Publisher Full Text\n\nFlachskampf FA, Badano L, Daniel WG, et al.: Recommendations for transoesophageal echocardiography: update 2010. Eur J Echocardiogr. 2010; 11(7): 557–76. PubMed Abstract | Publisher Full Text\n\nLang RM, Badano LP, Tsang W, et al.: EAE/ASE recommendations for image acquisition and display using three-dimensional echocardiography. J Am Soc Echocardiogr. 2012; 25(1): 3–46. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nAltiok E, Becker M, Hamada S, et al.: Real-time 3D TEE allows optimized guidance of percutaneous edge-to-edge repair of the mitral valve. JACC Cardiovasc Imaging. 2010; 3(11): 1196–8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nFedak PW, McCarthy PM, Bonow RO: Evolving concepts and technologies in mitral valve repair. Circulation. 2008; 117(7): 963–74. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nJilaihawi H, Doctor N, Kashif M, et al.: Aortic annular sizing for transcatheter aortic valve replacement using cross-sectional 3-dimensional transesophageal echocardiography. J Am Coll Cardiol. 2013; 61(9): 908–16. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nEnder J, Sgouropoulou S: Value of transesophageal echocardiography (TEE) guidance in minimally invasive mitral valve surgery. Ann Cardiothorac Surg. 2013; 2(6): 796–802. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHahn RT, Little SH, Monaghan MJ, et al.: Recommendations for comprehensive intraprocedural echocardiographic imaging during TAVR. JACC Cardiovasc Imaging. 2015; 8(3): 261–87. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKhalique OK, Kodali SK, Paradis JM, et al.: Aortic annular sizing using a novel 3-dimensional echocardiographic method: use and comparison with cardiac computed tomography. Circ Cardiovasc Imaging. 2014; 7(1): 155–63. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nVincent JL, Rhodes A, Perel A, et al.: Clinical review: Update on hemodynamic monitoring--a consensus of 16. Crit Care. 2011; 15(4): 229. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWagner C, Fredi J, Bick J, et al.: Monitoring myocardial recovery during induced hypothermia with a disposable monoplane TEE probe. Resuscitation. 2011; 82(3): 355–7. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWagner CE, Bick JS, Webster BH, et al.: Use of a miniaturized transesophageal echocardiographic probe in the intensive care unit for diagnosis and treatment of a hemodynamically unstable patient after aortic valve replacement. J Cardiothorac Vasc Anesth. 2012; 26(1): 95–7. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nWeidemann F, Jamal F, Sutherland GR, et al.: Myocardial function defined by strain rate and strain during alterations in inotropic states and heart rate. Am J Physiol Heart Circ Physiol. 2002; 283(2): H792–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nDuncan AE, Alfirevic A, Sessler DI, et al.: Perioperative assessment of myocardial deformation. Anesth Analg. 2014; 118(3): 525–44. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFarsalinos KE, Daraban AM, Ünlü S, et al.: Head-to-Head Comparison of Global Longitudinal Strain Measurements among Nine Different Vendors: The EACVI/ASE Inter-Vendor Comparison Study. J Am Soc Echocardiogr. 2015; 28(10): 1171–1181.e2. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSaito M, Negishi K, Eskandari M, et al.: Association of left ventricular strain with 30-day mortality and readmission in patients with heart failure. J Am Soc Echocardiogr. 2015; 28(6): 652–66. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSu HM, Lin TH, Hsu PC, et al.: Global left ventricular longitudinal systolic strain as a major predictor of cardiovascular events in patients with atrial fibrillation. Heart. 2013; 99(21): 1588–96. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nEpstein AE, DiMarco JP, Ellenbogen KA, et al.: ACC/AHA/HRS 2008 Guidelines for Device-Based Therapy of Cardiac Rhythm Abnormalities: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the ACC/AHA/NASPE 2002 Guideline Update for Implantation of Cardiac Pacemakers and Antiarrhythmia Devices) developed in collaboration with the American Association for Thoracic Surgery and Society of Thoracic Surgeons. J Am Coll Cardiol. 2008; 51(21): e1–62. PubMed Abstract | Publisher Full Text\n\nZhang X, Ha S, Wang X, et al.: Speckle tracking echocardiography: clinical applications in cardiac resynchronization therapy. Int J Clin Exp Med. 2015; 8(5): 6668–76. PubMed Abstract | Free Full Text | Faculty Opinions Recommendation\n\nBernard A, Donal E, Leclercq C, et al.: Impact of Cardiac Resynchronization Therapy on Left Ventricular Mechanics: Understanding the Response through a New Quantitative Approach Based on Longitudinal Strain Integrals. J Am Soc Echocardiogr. 2015; 28(6): 700–8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nHu J, Peng L, Qian H, et al.: Transoesophageal echocardiography for prediction of postoperative atrial fibrillation after isolated aortic valve replacement: two-dimensional speckle tracking for intraoperative assessment of left ventricular longitudinal strain. Eur J Cardiothorac Surg. 2015; 47(5): 833–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nKane GC, Karon BL, Mahoney DW, et al.: Progression of left ventricular diastolic dysfunction and risk of heart failure. JAMA. 2011; 306(8): 856–63. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWriting Committee Members, Yancy CW, Jessup M, et al.: 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. Circulation. 2013; 128(16): e240–327. PubMed Abstract | Publisher Full Text\n\nNagueh SF, Appleton CP, Gillebert TC, et al.: Recommendations for the evaluation of left ventricular diastolic function by echocardiography. Eur J Echocardiogr. 2009; 10(2): 165–93. PubMed Abstract | Publisher Full Text\n\nSwaminathan M, Nicoara A, Phillips-Bute BG, et al.: Utility of a simple algorithm to grade diastolic dysfunction and predict outcome after coronary artery bypass graft surgery. Ann Thorac Surg. 2011; 91(6): 1844–50. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nNicoara A, Swaminathan M: Diastolic dysfunction, diagnostic and perioperative management in cardiac surgery. Curr Opin Anaesthesiol. 2015; 28(1): 60–6. PubMed Abstract | Publisher Full Text\n\nCouture P, Denault AY, Pellerin M, et al.: Milrinone enhances systolic, but not diastolic function during coronary artery bypass grafting surgery. Can J Anaesth. 2007; 54(7): 509–22. PubMed Abstract | Publisher Full Text\n\nLobato EB, Gravenstein N, Martin TD: Milrinone, not epinephrine, improves left ventricular compliance after cardiopulmonary bypass. J Cardiothorac Vasc Anesth. 2000; 14(4): 374–7. PubMed Abstract | Publisher Full Text\n\nLobato EB, Willert JL, Looke TD, et al.: Effects of milrinone versus epinephrine on left ventricular relaxation after cardiopulmonary bypass following myocardial revascularization: assessment by color m-mode and tissue Doppler. J Cardiothorac Vasc Anesth. 2005; 19(3): 334–9. PubMed Abstract | Publisher Full Text\n\nMaxwell C, Konoske R, Mark J: Dataset 1 in: Emerging Concepts in Transesophageal Echocardiography. F1000Research. 2016. Data Source\n\nMaxwell C, Konoske R, Mark J: Dataset 2 in: Emerging Concepts in Transesophageal Echocardiography. F1000Research. 2016. Data Source\n\nMaxwell C, Konoske R, Mark J: Dataset 3 in: Emerging Concepts in Transesophageal Echocardiography. F1000Research. 2016. Data Source"
}
|
[
{
"id": "12886",
"date": "14 Mar 2016",
"name": "Manfred Seeberger",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12887",
"date": "14 Mar 2016",
"name": "Yong G Peng",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12888",
"date": "14 Mar 2016",
"name": "Rebecca T. Hahn",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-340
|
https://f1000research.com/articles/4-1429/v1
|
11 Dec 15
|
{
"type": "Research Article",
"title": "Transcription factor motif quality assessment requires systematic comparative analysis",
"authors": [
"Caleb Kipkurui Kibet",
"Philip Machanick"
],
"abstract": "Transcription factor (TF) binding site prediction remains a challenge in gene regulatory research due to degeneracy and potential variability in binding sites in the genome. Dozens of algorithms designed to learn binding models (motifs) have generated many motifs available in research papers with a subset making it to databases like JASPAR, UniPROBE and Transfac. The presence of many versions of motifs from the various databases for a single TF and the lack of a standardized assessment technique makes it difficult for biologists to make an appropriate choice of binding model and for algorithm developers to benchmark, test and improve on their models. In this study, we review and evaluate the approaches in use, highlight differences and demonstrate the difficulty of defining a standardized motif assessment approach. We review scoring functions, motif length, test data and the type of performance metrics used in prior studies as some of the factors that influence the outcome of a motif assessment. We show that the scoring functions and statistics used in motif assessment influence ranking of motifs in a TF-specific manner. We also show that TF binding specificity can vary by source of genomic binding data. Finally, we demonstrate that information content of a motif is not in isolation a measure of motif quality but is influenced by TF binding behaviour. We conclude that there is a need for an easy-to-use tool that presents all available evidence for a comparative analysis.",
"keywords": [
"Motif assessment",
"Motif comparison",
"Motif scoring functions",
"ChIP-seq",
"Motif enrichment",
"Motif quality"
],
"content": "Background\n\nUnderstanding gene regulation remains a long-standing problem in biological research. The main players, transcription factors (TFs), are proteins that bind to short and potentially degenerate sequence patterns (motifs) at gene regulatory sites to promote or repress expression of target genes. The search for a code to predict binding sites and model binding affinity of TFs has led to several experimental techniques and motif discovery algorithms being developed (Figure 1).\n\nTompa et al.15 and Hu et al.16 assessed the motifs by binding site prediction while Orenstein et al.25 and Weirauch et al.6 used scoring. The scoring techniques are colour coded for the motif discovery or assessment where they were used.\n\nA position weight matrix (PWM) is the common form of representing TF binding specificity. For a motif of length L, the corresponding PWM is a 4×L matrix of probabilities of observing a base b (A, C, G or T) at position i through L. Other variations have been introduced1–4, but a PWM remains popular due to its simplicity and ease of use as well as the ease of visualizing a PWM using a sequence logo5. Besides, Weirauch et al. showed that a well-trained PWM performs comparably to more complex models6. Motifs can be found using a variety of methods including algorithms that do de novo motif discovery from sequences containing binding sites7–9 and in vitro methods such as protein binding microarrays (PBM)10 and high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX)11.\n\nInitially, the low resolution of the available experimental techniques for TF binding specificity detection was a hindrance to the quality of binding models. However, next generation sequencing and techniques like chromatin immunoprecipitation (ChIP) followed by deep sequencing (ChIP-seq)12 and exonuclease cleavage in ChIP-exo13 that measure TF in vivo occupancy, have improved the resolution to single-nucleotide level. In addition to providing high resolution data for motif discovery, they are a useful resource to test the quality of the available motifs since they are TF specific. However, no benchmark capable of assessing the growing range of published motifs is available, with largely subjective quality measures14.\n\nDespite the advance in techniques analysing TF binding specificity, both in vitro and in vivo, the quality of models derived has not improved in a comparative measure. Although this may be explained by the saturation of PWM models’ ability to describe TF binding, the lack of a robust approach to test the quality of the model and maximize the best-performing ones is also probable. How are the algorithms being developed, tested and improved? Furthermore, the number of motif finding algorithms from dissimilar data sets and subsequently the number of motif models for a single TF generated, continue to increase. There are at least 44 PWM motif models available in 14 different databases for Hnf4a alone. How does the end-user decide which motif to use? In this study, we review and test the approaches used to evaluate TF binding models.\n\nThe available motif assessment techniques can be divided into three categories: assess by binding site prediction, motif comparison or by sequence scoring, and classification.\n\nBinding site prediction. Early review and assessment of motif-finding algorithms tested tools on the ability to predict sites, known or inserted into the sequence. Tompa et al. tested motif discovery algorithms by their ability to predict sites of inserted motifs using statistical measures for site sensitivity and correlation coefficient15. In this first comprehensive study, they found that a motif assessment problem is complex and admitted inserting random motifs fails to capture the biological condition of TF binding. Later, Hu et al.16 used real RegulonDB binding data in a large-scale analysis of five motif-finding algorithms. The tools available at that time performed poorly–“15–25% accuracy at the nucleotide level and 25–35% at the binding site level for sequences of 400 nt long”–largely due to the poor quality of RegulonDB annotations17.\n\nSandev and colleagues18–20 tested motif discovery algorithms using sequences with real and inserted binding sites as benchmarks; from Transfac, and the third-order Markov model respectively. Quest and colleagues21 developed the Motif Tool Assessment Platform (MTAP) as an automated test of motif discovery tools. However, this was computationally expensive and was made obsolete by new experimental data and algorithms.\n\nThe most comprehensive assessment based on binding site prediction so far has been by the Regulatory Sequence Analysis Tools (RSAT) consortium. In their ‘matrix quality’ script, they use theoretical – information content (IC) and E-values – and empirical scores computed by predicting binding sites in RegulonDB, ChIP-chip and ChIP-seq positive and negative control sequences17.\n\nInadequate knowledge of TF binding sites has mainly hampered the ability to assess motifs and algorithms by binding site prediction. Predicting binding sites that are inserted or known in the sequences cannot accurately identify unknown true sites. Techniques that identify such sites may be penalized. Until TF binding sites are well annotated, this technique cannot be confidently utilized.\n\nMotif comparison. Novel motifs can be assessed by comparison to ‘reference motifs’ using the sum of square deviation, Euclidean distance and other statistics that measure divergence between two PWMs22,23. Thomas-Chollier et al. proposed a motif comparison approach for their RSAT algorithm where they combine multiple metrics, including Pearson’s correlation, width normalized correlation, logo dot product, correlation of IC, normalized Sandelinâ-Wasserman, sum of squared distances and normalized Euclidean similarity for each matrix pair24. They then unified all of these scores to ranks whereby the mean of the ranks is considered the overall score.\n\nAssessing motifs by comparison, as currently implemented, only tests similarity to the available motifs with little information on quality and ranks of the motifs. It assumes accuracy of ‘reference motifs’, with no way of assessing novel ones. In addition, the definition of ‘reference motifs’ remains largely subjective.\n\nAssessment by scoring. Motif assessment has since shifted towards scoring positive sequences known to contain binding sites and negative background sequences without binding sites, driven by high-throughput sequencing techniques6,25–27. This avoids the need to identify binding sites a priori by focusing on the ability to classify the two sets of sequences. The differences in the assessments arise from the choice of sequences to use as positive and negative, the thresholds used to identify binding sites, the length of the sequences in both sets, the scoring function and the statistic used to quantify the performance of the tool.\n\nFor ChIP-seq data, the main difference is that the length of sequences (250bp25, 600bp27, 100bp6 or 60bp28) and the choice of negative sets (300bp downstream25,27; random sequences, 5000bp from a transcription start site (TSS) or random genomic sequences6, or flanking sequences28) used. In addition Agius et al.28, tested PWMs and support vector regression (SVR) models in the 36bp sliding window of the test sequences, a deviation from the rest of the techniques. All these differences, in addition to the scoring functions and statistics used, can lead to variations in the results of comparative analyses. Users and algorithm developers therefore have to frequently re-invent the wheel to test their tools.\n\nFigure 1 shows the evolution of experimental motif discovery assessment techniques. We have not focused on the experimental techniques or motif discovery algorithms as excellent reviews are already available14,29. Rather, we focus on TF binding models represented as a PWM and aim to determine how the choice and length of benchmark sequences, scoring functions, and the statistics influence motif assessment. We hope that this study will highlight some of the pitfalls in the previous motif assessments and advise design of a standard in motif assessment that will ensure comparability and reuse of results.\n\n\nMethods\n\nHuman uniform ChIP-seq data were downloaded from the ENCODE consortium30 (http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeAwgTfbsUniform). For each peak file, we used BEDTools v2.17.031 to extract the 500 highest scored sequences (after eliminating repeat masked sites) of 50, 100, and 250bp centred on the ChIP-seq peaks as a positive set. A similar negative set was extracted 500bp downstream from the positive sequences.\n\nWe used motifs from a number of databases and publications listed in Table 1. We converted these motifs from their various formats into MEME format and scored the positive and negative sequences with GOMER, occupancy, energy and log-odds scoring functions. We quantify how each motif performs using AUC, Spearman’s, MNCP and Pearson correlation (Figure 2). This was implemented in a Python module which is available free from https://github.com/kipkurui/Kibet-F1000Research. This repository also contains raw data and an Ipython notebook that documents how to reproduce the analysis we describe in this paper.\n\n“Source” refers to the experimental technique used to generate the motifs.\n\nWe show the source databases, data processing and scoring techniques used in the analysis.\n\nWhen testing motifs by scoring ChIP-seq data, multiple scoring functions are available, which may affect the outcome. In the section that follows, we describe the scoring functions tested, as well as provide a review of how they have been previously applied.\n\nGOMER scoring. The GOMER scoring framework was introduced by Granek et al.44 but adapted for PBM sequence scoring45,46. It seeks to compute the probability g(siΘ) that a TF, given PWM Θ, will bind to at least one of the sub-sequences (k) of Si of length L, where L is the length (number of sites) of the PWM model. This assumes that each site can be bound independently.\n\n\n\nSee Chen et al.45 for more details.\n\nOccupancy score. The occupancy score calculates the occupancy of a PWM (Θ) of length l for subsequence of length k as the product of the probabilities of each base in S using Equation 1.\n\n\n\nFor a sequence, the sum of the occupancies of all subsequences (sum occupancy)25,47, the maximum score (maximum occupancy)27, or the average occupancy (average motif affinity–AMA) have been used.\n\nSum occupancy is defined in Equation 3:\n\n\n\nBEEML-PBM energy scoring. The energy scoring framework of binding energy estimation by maximum likelihood for protein binding microarrays (BEEML-PBM)4, computes the logarithm of base frequencies with the idea that this is proportional to the energy contributions of the bases. The binding energy at each location is computed; the lower the binding energy, the higher the binding affinity. It has mainly been used to score PBM data6,27.\n\nThe probability that sequence Si is bound is given by Equation 4,\n\n\n\nwhere, for a sequence S of length T, E(Si) is given Equation 5,\n\n\n\nfor binding site of length L, ∈(b, m) is the energy contribution of base b while Si(b, m) is an indicator function of site m (1 with base b, 0 otherwise).\n\nLog likelihood scoring. In log likelihood scoring, used by a majority of the MEME Suite tools48, the score for a given site is the sum of the log-odds ratios at a PWM at the match site. For a sequence S of length N scored using PWM Θ, the log-odds score is given by Equation 6,\n\n\n\nwhere p the background probability and l is the indicator function for base b at position i (1 with base, 0 otherwise).\n\nThe score for a given sequence can then be derived by summing individual scores or by finding the maximum score. Sum log-odd scoring has generally been used by MEME Suite tools while maximum log-odds scoring has also been used to compare motifs represented differently (PWM, k-mer and SVM models) against one another27,28. Each of these approaches has inherent advantages but may produce inconsistent results.\n\nWith the scores of each motif for the sequences acquired, binding prediction can be evaluated by various statistics. The area under the receiver operating characteristic curve (AUC)49 has been widely used, especially with the advent of PBM6,25,45. In addition to popularizing AUC, Clarke et al.49 also introduced a novel metric, minimum normalized conditional probability (MNCP), for quantifying the correlation between DNA features and gene regulation. This statistic has been applied in motif assessment in GIMME motifs50 and is said to be less affected by the presence of false positives compared with AUC since it places emphasis on true positives. We use MNCP to test how it contributes to better prediction in an effort to encourage its use.\n\nPearson and Spearman’s rank correlation are still widely used as a measure of motif performance. Spearman’s rank correlation has been used for PBM and ChIP-seq sequences25 while Pearson’s correlation was used by Weirauch et al.6. However, Weirauch et al. cautioned on the use of Spearman’s correlation for PBM data citing its inability to exclude low intensity probes. We wish to check the usefulness of correlation in motif assessment.\n\nIn addition to comparing the scoring approaches, we use CentriMo version 4.10.0 in differential mode51 – an option that tests differences in motif enrichment between two sequence sets – in a novel way for motif assessment. We set differential mode parameters for local rather than central enrichment of all the input motifs in the positive (primary) and negative (control) set, as described in the Data section above, by using a very large threshold. The negative log of the E-value is used as the measure of a motif’s enrichment and rank. Motif enrichment has previously been performed43 using the FIMO algorithm52 to scan for motif matches in sequences and calculate an enrichment value.\n\n\nResults\n\nThe size of the putative binding region – length of the sequences in each data set – is to some extent a proxy for how accurate the ChIP-seq experiment was. If the result was accurate a narrow region should contain the true site.\n\nFor the three variants of sequence length, we did not observe a significant effect (p=0.113, for 50 and 100; p=0.0545, 50 and 250; p=0.678, 100 and 250bp–Wilcoxon rank-sum test) on the scoring of the sequences (Figure 3). The scores assigned for each sequence length, however, seems to indicate how the TFs bind. Motifs with higher scores at lower sequence length (50 or 250bp) are generally enriched at the ChIP-seq peak, which is also a strong indicator of direct binding53. This is consistent with a previous observation that a successful ChIP-seq experiment localizes binding within about 100bp of the true site54. Others with significantly better AUC values at 250bp sequence length like Elf1 (p=0.017, Wilcoxon rank-sum test) and Sp1 (p=0.013, Wilcoxon rank-sum test)55, are known to bind cooperatively.\n\nUsing all the motifs for the 15 TFs, we tested the effect of sequence length (50bp, 100bp and 250bp) using GOMER scoring on ChIP-seq data. Performance is quantified using AUC values.\n\nTranscription factors bind to their possible sites in a sequence-specific manner. Some actually have alternative binding motifs depending on the tissue or cell line. Unless the interest is tissue-specific binding, if more than one set of data is available, an average should be used. For example, as shown in Figure 4, the Foxa motif from the POUR data set is significantly differentially enriched only in the A549 cell line and not so much in the other cell lines.\n\nThe cluster map displays how some motifs are specific to certain cell lines. Foxa motifs used to score 5 cell lines using energy scoring and quantified with AUC values. Similar results are obtained with other scoring functions.\n\nIn light of this possible effect, the results displayed throughout this paper are based on the mean score of all the available ChIP-seq data sets to avoid a bias towards cell line-specific motifs.\n\nGenerally, the AUC and MNCP statistics are in strong agreement. However, in some situations like Hnf4a and Ctcf, they are not (Figure 5). The motifs that are ranked higher only by MNCP are generally long or with high IC (Table 2). Those are highly specific motifs confirming that MNCP prefers specific motifs, which will have more true positives. When energy scoring is used, there is agreement between the scores assigned by AUC and MNCP hinting that, like MNCP, energy scoring also puts emphasis on true positive hits.\n\nWe score the positive sets of sequences using GOMER and energy functions and quantify performance using AUC, MNCP. Results show some motifs ranked poorly by GOMER AUC scores. However, the scores are in agreement in when energy scoring is used.\n\nWe tested the ability of PWM models to discriminate positive (top 500 peaks of width 100bp centred on the peak) and negative (500 peaks 100bp wide located 500bp downstream from the positive) sequence sets using five scoring functions. Maximum and sum log-odds scoring had low discriminative power for most of the motifs when all three statistical measures are used (Figure 6). However, sum log-odds scoring had some good performance (over 0.55 AUC scores) for some TF motifs like Max, Nrf1, Tcf3 and Pax5.\n\nSumlog: Sum log-odds function, Sumoc: sum occupancy score.\n\nThere is no significant difference in performance when GOMER, energy or occupancy scores (sum, maximum and AMA) are used for scoring (Figure 6) with AUC statistic (see Table_S1 for details of statistical significance). Also, we did not observe any significant difference (p=0.85, Wilcoxon rank-sum test) between sum occupancy and maximum (Table 3), contrary to a claim by Orenstein et al.25. The variation in the scores is particularly reduced when MNCP statistic is used (Figure 7); though Ctcf, Egr1 and Hnf4a score significantly higher in energy. For other TFs like Pou2f2 and Esrra, the preference is reversed. These observations are reflective of the inherent features of the scoring functions or the statistics used.\n\nSumlog: Sum log-odds function, Sumoc: sum occupancy score.\n\nMotif length has little bearing on the quality of motif, independent of other factors. However, specific motifs with very high IC such as those from POUR have a lower performance (Figure 8). In the same light, those motifs with low IC also have a lower performance in vivo.\n\nFor each motif, the information content is calculated based on information theory for the whole length as well as normalized for length. The results for AMA and max occupancy are similar to sum occupancy, and are not included.\n\nThe heat map in Figure 8 shows how the motif scores from the four discriminative functions correlate with motif length, full-length IC and average IC. The examples have no consistent correlation between the IC and the scores (Figure 8A). However, there is a negative correlation between both the total IC and motif length, and the scores except for sum log-odds scoring, which has no significant correlation (p=0.34, correlation p-value). This shows that motif length, rather than the IC of the motifs, negatively influences the scores assigned by these functions. This is not a general rule. Some TFs exemplify a different scenario. For example, Egr1 (Figure 8B) has a strong positive correlation between IC and scores and a negative correlation with motif length, showing that it has a highly specific binding site56. Mef2a, on the other hand, has a positive correlation between motif length and scores showing preference for longer low information motifs (Figure 8C). This could also reflect variability in binding sites. Ctcf has the highest negative correlation for average IC, with a neutral to positive correlation for motif length (Figure 8D), which may indicate preference for longer low IC motifs.\n\nWe have shown that the effect of scoring algorithms is TF-specific. We also test to see how, overall, the different databases (DBs) are ranked against each other. For TFs with more than one motif in a given DB, we use the best performing one to represent the DB. We also use motif enrichment-based assessment using CentriMo version 4.10.0 to provide more evidence to scoring based techniques’ results. Motif enrichment analysis compares how various motifs in foreground sequences are enriched compared with background sequences. In comparing how two or more motifs for the same TF perform, the level of enrichment of the motif in sequences known to contain possible binding sites of the TF compared to some background should provide a measure of the quality of the motif.\n\nFigure 9 provides a summary of ranking of the various databases for the given TFs. We observed that the performance of a majority of the motif databases did not differ much, except for TF2DNA motifs, but the ranking or the performance of individual motifs differs. This further supports the observation of TF-specific performance of scoring function, algorithms and DBs. It also shows that no single database currently outperforms the others for all TFs. There is agreement in ranking of the best (ZLAB and HOCOMOCO) and worst performing (TF2DNA and SWISSREGULON) DBs. We observe that, compared with GOMER (Figure 9A), the score for all DBs drops when using energy (Figure 9B) except for POUR motifs. This shows that POUR motifs, or at least the best performing ones, are favoured by energy scoring. It is also noteworthy that POUR and GUERTIN DB motifs, discovered and tested on ENCODE ChIP-seq data, perform poorly.\n\nWe compare the motif databases by using the best ranking for each motif using GOMER and energy AUC and MNCP values, and CentriMo enrichment values.\n\n\nDiscussion\n\nWe have described a comparative analysis on the effect of scoring functions, ChIP-seq test data processing and statistics on motif assessment. We chose to focus on TF binding models represented as PWM, since it is most commonly used. The review reveals the complexity of the motif assessment problem, showing no appropriate solution is available so far. The available techniques focus on testing motif algorithms or the experimental techniques used, but little has been done to compare the available motifs for a given TF. There is a need for a tool, accessible and easy to use by end-users, to aid in choosing motifs.\n\nThe use of 100 or 250bp sequence length provides necessary discrimination for the TFs tested (Figure 3). The performance was also found to be TF specific, an observation that could reflect inherent binding behaviour; direct, indirect or cooperative binding of the TF. This supports the observation that direct binding can be inferred from ChIP-seq peaks53. We also confirm that 100bp provides acceptable specificity in motif assessment given that most TF binding sites are less than 30bp54.\n\nSince TF binding is cell line specific57, users should be aware of bias caused by use of one cell line in an assessment. We observe that the use of more than one cell line reduces the bias towards cell line specific motifs (Figure 4).\n\nThe MNCP rank-order metric is similar to AUC but derived by plotting true positive hits against all sequences’ scores. This places emphasis on true positives, and therefore, less affected by false positives. Our analysis confirms this observation and demonstrates the power of MNCP compared with AUC, which penalize specific motifs (Figure 5). We propose that energy scoring has the same benefit, though further research may be needed to validate this. Although there is no clear winner among the scoring function, occupancy based (GOMER, AMA, sum and max) and energy scoring functions are preferred. We recommend using occupancy scoring with MNCP statistic or energy scoring with normal AUC or MNCP statistic.\n\nThere is no significant correlation (p=0.513, correlation p-value) between the IC and the motif scores (Figure 8). This contrasts with the observation that the best-quality motifs may have low IC motifs6, or high IC motifs58. Weirauch et al. did not normalize for motif length, which results in high IC motifs that are generally longer but not necessarily more specific6. A shorter motif with higher IC per position will be more specific but have lower total IC. We argue that the effect of IC on motif quality is dependent on the TF binding behaviour. TFs with short and specific binding sites will favour high IC while those with long and variable binding sites will be more accurately modelled with low IC. Furthermore, it has been shown the low IC flanking motif sites contribute to specificity of binding in vivo58.\n\nWe have also shown that the techniques used in motif assessment have a direct effect on motif discovery. We observe how motifs generated from similar data using the same techniques could have highly variable performance in POUR, ZLAB and GUERTIN motifs (Figure 9). This difference in quality can be explained by motif discovery algorithms used, data processing as well as the assessment techniques used in each motif discovery pipeline. POUR motifs are learned from full-length sequences of the top 250 peaks using five motif finding algorithms (MEME, MDscan, Trawler, AlignAce and Weeder)34, the ZLAB group used 100bp of the top 500 sequences centred on the ChIP-seq peaks using MEME-ChIP59, while GUERTIN reports the top 5 motifs for each technique generated using MEME. For quality assessment, POUR34 used a TFM-PVALUE60 to match motifs against the testing ChIP-seq data set and the most enriched motifs against a background composed of intergenic non-repetitive regions. ZLAB group used FIMO52, which uses a log likelihood score for motif scanning.\n\nThe worst performing motifs, from TF2DNA, are generated from 3D models of TF from experimental or homology-modelled PDB files. When generating these models, they determined the accuracy of the models based on similarity to UniPROBE and JASPAR motifs at a given threshold. They claimed their technique successfully identifies true motifs 41–81% of the time depending on the quality of templates used in modelling 3D structures. This supports our view that use of motif comparison against ‘reference motifs’ as a measure of motif quality is not reliable. Although JASPAR and UniPROBE are widely used, reliance on reference motifs is problematic, especially with the advent of motif databases like HOCOMOCO and CIS-BP that have motifs with better prediction quality. As a general principle, it is not reasonable to use historical data as a benchmark for assessing potentially better new methods.\n\nWe have confirmed that motif assessment has transcription-specific variability, an observation previously made61. Assessments should be less focused on how a particular motif database or algorithm performs but on how different motifs, for a particular TF, perform compared to the other potential motifs. For the end user, no single database can provide the sole measure of quality of new data. This raises the need for collation of the different motifs tested using a variety of motif assessments to provide information to the end user on their ranks.\n\n\nConclusions\n\nWe have demonstrated that the scoring techniques used in motif assessment influence ranking of motifs in a TF-specific manner. Motif assessments and tools developed to date have focused on comparing algorithms, experimental techniques or databases. This does not help the user choose which motif to use for a given TF. Some TFs reviewed here have at least 44 PWM motifs available, raising the need for a tool that can be utilized to rank these motifs. We have also shown that data processing as well as motif assessment can have a significant influence on the quality of motifs derived. Therefore, the choice of an assessment approach should be given as much thought as that of the motif discovery algorithm to use. We have also shown the effect of IC on motif quality is influenced by TF binding behaviour.\n\nIn short, a single measure of motif quality is likely to remain elusive, pointing to the need for tools and methods for comparative analysis using multiple methods. Lessons learned from this analysis will be useful in a number of ways. Firstly, we are working on a web-based application that can allow users to compare motifs available in different databases for a specific TF. Secondly, we intend to extend the motif by comparison approach to avoid ‘reference motifs’ bias. Thirdly, we have shown the effect of motif scoring on motif discovery. We intend to use the robust motif assessment techniques we introduce to improve motif finding.\n\n\nData and software availability\n\nData, software, supplementary files and documentation for ‘Transcription factor motif quality assessment requires systematic comparative analysis’ are available from Github: https://github.com/kipkurui/Kibet-F1000Research.\n\nArchived files at the time of publication are available from Zenodo: doi: 10.5281/zenodo.3372669.",
"appendix": "Author contributions\n\n\n\nCK designed and performed the analysis and wrote the first draft. PM supervised the work and contributed to subsequent drafts. All authors read and approved the final manuscript.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nThe financial assistance of the South African National Research Foundation (NRF) towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the authors and are not necessarily to be attributed to the NRF. PM funding: NRF/IFR Grant 85362; CK: DST Innovation Doctoral Scholarship.\n\n\nReferences\n\nAnnala M, Laurila K, Lähdesmäki H, et al.: A linear model for transcription factor binding affinity prediction in protein binding microarrays. PLoS One. 2011; 6(5): 1–13, e20059. 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PubMed Abstract | Publisher Full Text\n\nBadis G, Berger MF, Philippakis AA, et al.: Diversity and complexity in DNA recognition by transcription factors. Science. 2009; 324(5935): 1720–1723. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFoat BC, Morozov AV, Bussemaker HJ: Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE. Bioinformatics. 2006; 22(14): e141–9. PubMed Abstract | Publisher Full Text\n\nBailey TL, Boden M, Buske FA, et al.: MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 2009; 37(Web Server issue): W202–W208. PubMed Abstract | Publisher Full Text | Free Full Text\n\nClarke ND, Granek JA: Rank order metrics for quantifying the association of sequence features with gene regulation. Bioinformatics. 2003; 19(2): 212–218. PubMed Abstract | Publisher Full Text\n\nvan Heeringen SJ, Veenstra GJ: GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments. Bioinformatics. 2011; 27(2): 270–271. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLesluyes T, Johnson J, Machanick P, et al.: Differential motif enrichment analysis of paired ChIP-seq experiments. BMC Genomics. 2014; 15(1): 752. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGrant CE, Bailey TL, Noble WS: FIMO: scanning for occurrences of a given motif. Bioinformatics. 2011; 27(7): 1017–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBailey TL, Machanick P: Inferring direct DNA binding from ChIP-seq. Nucleic Acids Res. 2012; 40(17): e128. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWilbanks EG, Facciotti MT: Evaluation of algorithm performance in ChIP-seq peak detection. PLoS One. 2010; 5(7): e11471. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTakahashi K, Hayashi N, Shimokawa T, et al.: Cooperative regulation of Fc receptor gamma-chain gene expression by multiple transcription factors, including Sp1, GABP, and Elf-1. J Biol Chem. 2008; 283(22): 15134–41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKubosaki A, Tomaru Y, Tagami M, et al.: Genome-wide investigation of in vivo EGR-1 binding sites in monocytic differentiation. Genome Biol. 2009; 10(4): R41. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLower KM, De Gobbi M, Hughes JR, et al.: Analysis of sequence variation underlying tissue-specific transcription factor binding and gene expression. Hum Mutat. 2013; 34(8): 1140–1148. PubMed Abstract | Publisher Full Text\n\nOrenstein Y, Mick E, Shamir R: RAP: accurate and fast motif finding based on protein-binding microarray data. J Comput Biol. 2013; 20(5): 375–82. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMachanick P, Bailey TL: MEME-ChIP: motif analysis of large DNA datasets. Bioinformatics. 2011; 27(12): 1696–1697. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTouzet H, Varré JS: Efficient and accurate P-value computation for Position Weight Matrices. Algorithms Mol Biol. 2007; 2: 15. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhang Y, He Y, Zheng G, et al.: MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures. BMC Genomics. 2015; 16(Suppl 7): S13. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZambelli F, Pesole G, Pavesi G: PscanChIP: Finding over-represented transcription factor-binding site motifs and their correlations in sequences from ChIP-Seq experiments. Nucleic Acids Res. 2013; 41(Web Server issue): W535–W543. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMcLeay RC, Bailey TL: Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data. BMC Bioinformatics. 2010; 11: 165. PubMed Abstract | Publisher Full Text | Free Full Text\n\nENCODE Project Consortium: The ENCODE (ENCyclopedia Of DNA Elements) Project. Science. 2004; 306(5696): 636–640. PubMed Abstract | Publisher Full Text\n\nZhao Y, Ruan S, Pandey M, et al.: Improved models for transcription factor binding site identification using nonindependent interactions. Genetics. 2012; 191(3): 781–790. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGuo Y, Mahony S, Gifford DK: High resolution genome wide binding event finding and motif discovery reveals transcription factor spatial binding constraints. PLoS Comput Biol. 2012; 8(8): e1002638. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBengtsen M, Klepper K, Gundersen S, et al.: c-Myb Binding Sites in Haematopoietic Chromatin Landscapes. PLoS One. 2015; 10(7): e0133280. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHardison RC, Taylor J: Genomic approaches towards finding cis-regulatory modules in animals. Nat Rev Genet. 2012; 13(7): 469–483. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKibet CK: Kibet-F1000Research. Zenodo. 2015. Data Source"
}
|
[
{
"id": "11604",
"date": "05 Jan 2016",
"name": "Trevor W. Siggers",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript by Kibet et al. “Transcription factor motif quality assessment requires systematic comparative analysis” addresses an important issue in the field of regulatory genomics, namely how we analyze motif enrichment in genomic datasets. The authors have addressed this issue in a systematic way by compiling many datasets and versions of motifs, and analyzing the impact of different scoring methods.This type of meta-analysis will be of interest to a wide audience. However, the current manuscript needs considerable revision. In particular, the connections between the data presented and the conclusions reached need to be strengthened and clarified. Furthermore, a lot more clarification about what is being shown in the figures is needed to properly evaluate the conclusions. Below I have outlined specific examples through to Figure 8. The figure legends could definitely use more detail to help clarify what is being shown, and there needs to be more explicit and careful connection between the data and the conclusions (see examples below). I think that the type of analyses contained in this manuscript will be of interest to a wide audience; however, the manuscript needs to be substantially revised. Table 1. Is Chen2008 databases, Reference 39, really PBM data? Methods/Data. For each peak file, the 500 highest scored sequences were identified “after eliminating repeat masked sites”. It is a little unclear what this statement means. Does that mean that no peak was selected if there was any repeat masked seqeuence within the 50, 100 and 250bp windows? Or was the repeat masked sequence just masked and the genomic window extended to attain the 50, 100 and 250 bp cutoffs? Also, for the negative set, does ‘similar’ mean length-matched? It was exactly clear how this negative set was constructed. Figure 3 /results. It was not clear why only a subset of 15 of the Encode ChIP-seq datasets were used and shown here, and how many datasets were used in the ‘Average’? Also, the figure caption notes that ‘all the motifs for the 15 TFs’ were used, but it’s not clear how many that was and whether the reported AUC values were averages over their individual AUC values? I little more clarification would be helpful. Page 6. The authors write, “Unless the interest is tissue-specific binding, if more than one set of data is available, an average should be used”. Used for what? For motif discovery? Figure 4. Why was ‘energy scoring’ used for this enrichment analysis, while GOMER scoring was used in Figure 3? Are the results dependent on these scoring differences? If not, then for consistency sake, it would be helpful to limit the enrichment analyses to a single scoring scheme. Page 6/Figure 4. The authors conclude, “the Foxa motif from the POUR data set is significantly differentially enriched only in the A549 cell line and not so much in the other cell lines”. I have no idea to what the authors are referring here, and this is the only conclusion from Figure 4. There are 5 different FOXA_discX.POUR motifs, all of which seem to score about the same on the different ChIP datasets. There is a FOXA1_2.GUERTIN that seems to be quite different, but this seems like an outlier within the dataset. I do not see how the data supports the contention that there are specific FOXA motifs that are better suited to particular ChIP datasets, it seems that for the most part they agree. Much more clarity is needed here.\n\nPage 8 / Figure 5. “However, in some situations like Hnf4a and Ctcf, they are not (Figure 5)”. I only see Ctcf data represented in Figure 5, this should be clarified. “The motifs ranked higher only by MNCP are generally long or with high IC (Table 2)”. It would be much easier to see this if they were indicated somehow in Figure 5, perhaps with arrows are stars or something. Second, these conclusions don’t seem to follow from the data at all. The CTCF_disc1.POUR seems also to score high with Energy_AUC, so it’s not clear that the MNCP is the only factor of relevance here. The CTCF.1_5.ZLAB seems to be most affected by the Energy vs GOMER scoring, and not the MNCP approach. Even if these issues were resolved, it is impossible to know whether these motifs are ‘generally long or with high IC’ from Table 2, because the other motifs aren’t shown. It would be much clearer if the mean and variance of the length & IC for all motifs were also provided for context, or even better correlate the relative score AUC to MNCP differences by length or IC, to truly see if a trend exists. Figure 6. Please clarify in the figure legend whether these values are for averages over multiple ChIP datasets (as was discussed above), and if so how these averages are determined. “Maximum and sum log-odds scoring had low discriminative power for most of the motifs when all three statistical measures are used (Figure 6)”. What are the three statistical measures you’re referring to, and where’s the data? I only see data for AUC. Please clarify. Table 3. Please be explicit in the figure legend about what the ‘Mean’ and ‘Median’ refer to (i.e., mean and median AUC values calculated over X single motif analyses described in Figure 6) Figure 7/ page 10. “The variation in the scores is particularly reduced when MNCP statistic is used (Figure 7)”. How am I supposed to see this? What is a significant difference in MNCP and how does it compare to a difference in AUC. Based on the coloring scheme presented the results in Figure 6 and Figure 7 look very similar- it is not clear at all that there is any qualitative difference between these two figures except for the different measures used (i.e., an appropriate normalization might make them near equivalent). Figure 8. It is not clear (nor mentioned) what is being shown in this figure. I assume – but I could be wrong – that we’re looking at AUC values for each factor (i.e., Mef2a etc) averaged over some ChIP-seq datasets, but how are these being compared to each other? Further, how is Motif_IC which is a function just of the PWM being compared to a scoring function. I can’t speak to the conclusions being reached as I don’t currently know what data is being shown. Much more clarification is warranted in the text and figure caption.",
"responses": [
{
"c_id": "1809",
"date": "14 Mar 2016",
"name": "Caleb Kipkurui",
"role": "Author Response",
"response": "Thank you very much for taking the time to review our paper and provide recommendations.Your comments have been very helpful in improving the paper.Table 1CorrectedMethods/DataOn repeat masked sequences, we have updated the paper to clarify the we did not include any sequences in test or negative sequences that contained masked positions. By a similar set of negative sequences, we mean matched in length and number of sequences. Figure 3/ResultsThe figure caption is updated to clarify. The number of the TFs used was decided based on the availability of ChIP-seq data as well as having motifs in more than 10 of the databases used. A list of the motifs used is provided in the data repository as well as the specific ChIP-seq data used. See also Methods / Data paragraph 3. Page 6:On cell line specific binding, an average of the scores of all the available cell lines should be used in motif assessment. We have updated the statement for clarity.Figure 4We have changed to using results from GOMER scoring since they are similar; the effect described is only pronounced in Energy scoring. Page 6/Figure 4We had incorrectly mentioned the wrong motif to be significantly enriched. We have corrected this and also provided further evidence to the effect that the cell line used in the assessment does actually have an effect on the ranking of the motifs. The conclusions remain valid. Page 8/Figure 5 (now Figure 6).We acknowledge that the figure we had used did not present the intended information correctly. We changed the figure to present the general information on the effect of statistics on the ranking of the motifs. We observe that, when normalized, the MNCP and AUC scores do not differ, except for slight difference in some TFs like Hnf4a, Ctcf, Gata3. However, the Pearson and Spearman's correlation scores vary greatly. The plot of the standard deviation of scores as represented by error bars in Figure 6 demonstrates why we consider correlation scores to be reliable than the other scores. We have added clarification of this point to the paper. Thank you again for pointing out the problem.Figure 6 (now Figure 7)The caption has been updated for clarity. Table 3 (Now Table 2)ClarifiedFigure 7 (now Figure 8)/page 10The figure has been updated to include information on correlation statistics. Figure 8 (now Figure 9)Our apologies for the lack of detail. The figure caption has been updated for clarity. We correlate the scores for the various motifs (for each scoring function) to the length and information content of the motifs to determine whether the scores obtained are in any way influenced by the motif characteristics."
}
]
},
{
"id": "11721",
"date": "15 Jan 2016",
"name": "Jan Grau",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe manuscript \"Transcription factor motif quality assessment requires systematic comparative analysis\" by Kibet and Machanick addresses the assessment of transcription factor binding motifs. This question is especially important for selecting appropriate motifs for computational predictions given the large number of different motifs for the same transcription factor available from databases. Kibet and Machanick specifically consider different measures for motif scoring and assessment, and investigate different factors that might influence the assessment and, hence, the chosen motif.The topic is of great relevance in any research dealing with sequence motifs and a systematic analysis of the factors influencing their assessment may help to develop a standardized framework for motif assessment.However, I have several reservations regarding the current version of the manuscript as outlined below.As a general comment (that does not necessarily require a response by the authors), I found it slightly disappointing that the present manuscript does pose many important questions and potential obstacles in motif assessment, but does not provide a solution, be it guidelines for reasonable motif assessment or be it even a platform for performing such analyses.DATA:1. I wonder why the authors decided to only consider ChIP-seq data but no in-vitro data (PBMs or SELEX). While in-vivo binding may of greater relevance for many applications, problems like cell type-specificity of motifs (also addressed by the authors) would have a minor influence. In addition, competitive or interaction effects with other transcription factors might be ruled out. Finally, some of the motif sources considered derive their PWMs from in-vitro data. In summary, an analysis also using in-vitro data might affect the conclusions of the paper.2. For all ChIP-seq data sets under consideration, the authors extract (only) the top 500 highest scoring sequences for the assessment. This may have largely differing effects for different transcription factors, where, for instance, one transcription factor might have several hundred ChIP-seq positive regions, whereas another transcription factor might have tens of thousands of ChIP-seq positive regions. Hence, in one case also lowly occupied sequences are collected whereas in the other case, the positive data set may only contain the most stringent binding sequences. This may affect all downstream analyses and, for instance, could be one of the reasons why the authors observe transcription factor-specific effects for some factors. Hence, I would strongly suggest to conduct the analysis with a transcription factor-specific selection of sequences (where the simplest idea might be to use just a percentile).3. a) The authors state that they construct a \"similar\" negative set. Here, the authors should clearly define what \"similar\" means, how sequences are selected, and how many negative sequences are in the set. b) In addition, the specific selection of negative sequences described by the authors (500bp \"downstream\", where \"downstream\" is also unclear as ChIP-seq regions lack an orientation), might introduce a specific bias, because under the assumption that transcription factor binding sites are often located close to the transcription start, which might mean that the negative sequences may already be coding and, hence, per se different from promoter sequences.c) Finally, from my experience, the choice of the negative data set strongly affects the performance assessment of motifs. Hence, the authors might consider to test an additional set of negative sequences (e.g., di-nucleotide shuffled positive sequences) in their analysis.METHODS:4. The \"Methods\" section, especially formulas needs substantial revision:a) In general, notation should be harmonized between the different formulas. For instance, the sequence S appears with different indexes with different meanings; the indicator function is denoted by S_i(b,m) in eqn. (5) and by I(S_{i,b}) in equation (6).In addition:b) In eqn. (1), parentheses are missing around (1 - P(...)). In addition, the notation S_{t+1:t+k}^{i} is not explainedc) In eqn. (2), it is unclear if i and [S_{t=i}] are indexes or if this should denote a product of \\theta, i and S_{t=i} (which I consider unlikely). In addition, the variable t (in the index) is neither bound nor explained.d) In eqn. (3), the upper limit of the sum is |s|, where it should be |S|, I assume. In addition, there seems to be something missing (a \\theta?) in the product.e) Before eqn. (5), the authors refer to T as the length of the sequence. However, considering the formula, the length should be L, and the first sum from A to T refers to the alphabet. In addition, eqn. (6) again denotes the sum over the alphabet differently.f) In eqn. (5), the text refers to sequence S but the formula to sequence S_ig) In eq. (6), the variable P_b is not defined (the authors later only refer to p, which might have the same meaning). In addition, the authors to not explain, which background distribution they use in the assessment, which will be relevant, e.g., for the results presented in Fig. 6.5. The energy scoring framework (eqn. 4 and 5) and the LogOdds scoring framework are formally defined only for sub-sequences and it remains unclear how these are applied to longer sequences from ChIP-seq. Are those subjected to the occupancy definitions (maximum and/or average) as well?6. LogOdds scoring is referred to as \"Log likelihood scoring\" in the section's title (page 6, left column), which is not fully correct.7. On page 6, right column, second paragraph, the authors state that they \"wish to check the usefulness of correlation in motif assessment\" (which I would find interesting), but I did not find any results regarding correlation as performance measure in the results.RESULTS:8. In several cases, the figure captions are too minimalistic to understand the contents of the figure. I would suggest to spend a few more sentences in the captions to explain the main idea of each figure. In addition, not all of the abbreviations are explained in the caption of Fig. 6.9. On page 6, penultimate paragraph, the authors state that \"the Foxa motif from the POUR data set is significantly differentially enriched only in the A549 cell line\", which I could not read from Fig. 4. Please clarify.10. On page 8, right column, the authors state that \"MNCP prefers specific motifs, which will have more true positives\". Could the authors elaborate on these findings and also possibly give an (mathematical) explanation?11. In Fig. 6, the authors show AUC values for different motifs and scoring functions. a) First, it remains unclear which data sets have been used in this analysis for the different transcription factors. Is it just the average over all motifs and data sets for each factor? b) Second, I did, unfortunately, not get the general idea of this analysis. If I understood it correctly, the main question of this manuscript is to study the effects of different factors on motif assessment with the goal of selecting the most appropriate motif for a given transcription factor. However, here it seems to be that exactly this information is averaged out. Wouldn't be the more interesting question how the scoring functions affect the ranking (by AUC) of the different motifs for each transcription factor?12. On page 10, left column, the authors state that they \"did not observe any significant difference (p=0.85, Wilcoxon rank-sum test) between sum occupancy and maximum (Table 3)\". However, I did not find maximum occupancy listed in Tab. 3.13. On page 11, right column, the authors state that Egr1 has strong positive correlation between IC and scores. However, I found this correlation not too strong for Average_IC and in most cases not even positive for Motif_IC.14. a) In remains unclear, what exactly is shown in Fig. 8. I speculate that the authors computed the correlation of AUC values, IC and motif length for different data sets and motifs? Or is it really correlation between occupancy/energy and IC/length? b) In addition, most of the entries of the heatmaps show correlations between the occupancies/energy, which, however, is not discussed. If correlation between occupancies/energy is not of interest, the authors might consider omitting all but the first three rows of the heatmaps. c) Further, I wonder why the correlation between identical entries (e.g., Motif_IC with Motif_IC) is not equal to 1 in panel A.15. On page 12, second paragraph, the authors explain that they used the best performing motif to represent each database. However, this will introduce a bias towards larger databases, because these may contain a larger number of motifs for a transcription factor and, hence, are allowed to try a larger number of options, of which the best is chosen. I would suggest to use another, less biased statistic (e.g., the median) instead/in addition.16. The authors also use CentriMo scoring for comparing databases, which they did not consider before, and I wonder what is the reasoning behind using CentriMo in this case (and not before).17. In Figure 9, panel C, the authors rank the databases by average CentriMo score, while the magnitude of scores differs greatly between transcription factors and, hence, is dominated by data sets with large scores (e.g., cebp). I would suggest to level the influence of transcription factors, for instance by dividing the values in each column by their maximum value before averaging.18. On page 12/14, the author state that \"This supports our view that use of motif comparison against ‘reference motifs’ as a measure of motif quality is not reliable\". While I agree with the general conclusion of the authors, I do not see why the performance of TF2DNA supports this conclusion. If only 41-81% of the TF2DNA motifs are correct (according to comparison against reference motifs), I would have expected a lower performance compared to the other databases.OTHER/MINOR:19. In section \"Background\", second paragraph, the authors refer to Weirauch et al., stating that a well-trained PWM performs comparably to more complex models. While this correctly describes the finding of Weirauch et al., several publication in the meantime came to different conclusions (e.g., Kulakovskiy et al., 20131; Mathelier & Wasserman, 20132; Mordelet et al., 20133; Keilwagen & Grau, 20154). Hence, the authors might consider to make this statement more balanced.20. In section \"Background\", fourth paragraph, the authors state that \"the quality of models derived has not improved in a comparative manner\". I am not fully sure if I understand the statement correctly, but if the authors mean that the experimental techniques have improved, but the motifs did not (or much less), I would challenge this statement and at least encourage the authors to provide a reference.21. The authors should provide a list (or a link to a list in their repository) of the specific ENCODE data sets used in the analysis.22. Table 1: Chen2008 should be ChIP-seq data.23. As performance measures, the authors consider the area under the ROC curve and MNCP. While the former might be familiar for most working in the field, the authors might consider to give a short formal definition of MNCP. In addition, the area under the precision-recall curve might be another useful measure for imbalanced data sets. [However, depending on the construction of the negative data set, the test data might even be balanced.]24. Typos & Grammar:- Page 4, second paragraph: \"Sandev\" should be \"Sandve\"- Page 4, 5th paragraph: \"Sandelinâ-Wasserman\" should be \"Sandelin-Wasserman\"",
"responses": [
{
"c_id": "1808",
"date": "14 Mar 2016",
"name": "Caleb Kipkurui",
"role": "Author Response",
"response": "Thank you very much for your insightful comments and recommendations. They have helped us improve the paper.The main aim of this paper is to identify the weaknesses and potential pitfalls in the current techniques used in motif assessment. As part of our conclusions, we state that we will use the findings of this paper to develop a motif assessment platform to address the questions and the gaps. That work is almost done and should be available by March 2016, and is therefore out of the scope of this paper.1. We focused on ChIP-seq data in assessment since we believe that, for most cases, the final utility of the motifs learned is predicting in vivo binding of the motifs. That said, we agree that data used in testing the motifs does have an effect on the ranking of the motifs. This is an observation we confirm with our re-analysis using PBM data. We have included a section on how assessment in PBM and ChIP-seq are influenced differently (Effect of PBM data on motif assessment). 2. Our choice for top 500 sequences was informed by our understanding of previous research. However we did not make it clear that such prior work supports this point, and we have now cited a reference. As advised, we decided to test if this would affect the results from this analysis. The ChIP-seq peaks we use have a median of 14000 peaks, the highest having 92,258 peaks and a minimum of 101 peaks. Where the number of the available peaks was less than 500, we used all the peaks. Given the median number of peaks, we found 5% of the peaks to be appropriate and we used this when 5% the of the total was more than 500, else we used top 500 peaks (or all of them, for data sets smaller than this). We also tested for 10% of the peaks. In all this, we found that the size of the peaks used had no significant effect on the results obtained. We, therefore, eliminate that as being one of the reasons for cell line specific binding. This may, however, have an effect on cell line specific ranking behaviour even if we did not observe that in our examples, given that the number of peaks differs for a given TF in different cell lines. We will definitely consider this suggestion when developing our tool to avoid any potential bias caused by this.3. a) The manuscript has been updated. By similar we mean in size and sequence length.b) In our analysis, downstream is based on the coordinates of the peaks. We extracted sequences located 500bp from the highest coordinate (highest coordinate + 500). Our focus was to get negative sequences which are not expected to contain binding sites for the given TF but which maintains the nucleotide composition. That distance, whether it falls in a promoter region or not, should be appropriate in for our specific analysis. c) On other negative sequences that can be chosen, we agree that this can have some influence in the analysis. The scores obtained when a negative set generated using dinucleotide shuffled positive sequences were always lower than those from downstream sequences. However, the ranking of the motifs did not change in any significant manner. We expect random negative sets to have a significant influence on the ranks of the motifs and their probable difference in GC content from the binding region makes their appropriateness questionable. 4. The notations used in the formulas have been updated for uniformity. Thank you!5. For energy scoring, the subsequence with the lowest energy is used to represent the sequence while for logOdds scoring, the score can either be obtained by getting the sum or the maximum score for all the sub-sequences. Clarified in the paper, thank you.6. Corrections have been made in response to 6, 8 and 9.7. We have updated the Figure 5 to include details on the usefulness of correlation statistics. We find them to produce significantly different ranks from MNCP or AUC or even between Pearson and Spearman correlations.8. Done9. Done10. We have updated the paper in to add a line giving more information about MNCP. Simply put, the MNCP is a rank-based statistic that determines if the mean occurrence of a motif in test sequences is higher that the mean occurrence in a random set. Each set of sequences is ranked based on the mean occurrence, and the MNCP is calculated by finding the mean of the normalized ratio of the two ranks. 11. We have updated Figure 6 (now Figure 7) to address the comments. Our earlier figure actually averaged the information on the effect of scoring functions on the ranks of the motifs. We have updated by using the rank correlation of the motifs for various TFs to show how it affects ranking. 12. Table 3 (now Table 2) has been updated to include maximum occupancy.13. On Egr1 motifs correlation of motif IC and scores, we have updated the statement to be in accordance with the data. 14. In Figure 8 (now Figure 9) we have updated the figure to only retain relevant columns. We have also corrected the error that led to identical entries’ correlation being more than 1. 15. On why we chose to use the best motif's score to represent a database, we argue that since the focus of this analysis is to test our ability to choose for the best motif, irrespective of the database, we find using the best motif score to represent the DB to be sufficient. Besides, using median will still lead to biased results since DBs with many motifs of low quality and a few of high quality will be poorly ranked. 16. We only introduce CentriMo at a later stage of our analysis as an alternative method of scoring techniques to motif assessment. The focus of the paper was to systematically assess the factors that do influence motif assessment, so we wanted to maintain that focus. 17. We have taken your suggestion on Figure 9 (now 10) to normalize the scores. Thank you.18. On the performance of TF2DNA, we agree that the low performance would be expected. We also believe that a different approach to motif assessment during motif discovery may have produced better motifs. In addition, testing using PBM data produced a much better performance. This may be a consequence of the motifs being short and only generated using in vitro methods.19. The background section has been updated to include to making the observations balanced and including recent citations.20. We accept that our statement on the lack of significant improvement of the motifs may have been misleading and unsupported. We have updated it to reflect current evidence. 21. A list of the ENCODE data we use has been added to the repository22. The source of Chen2008 updated to ChIP-seq from PBM in table 1. Thank you23. A definition of MNCP has been added to the paper. We had previously tested area under a precision-recall curve and found it to produce similar results to AUC. 24. Typos correctedOnce again, thank you."
}
]
}
] | 1
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https://f1000research.com/articles/4-1429
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https://f1000research.com/articles/5-331/v1
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11 Mar 16
|
{
"type": "Review",
"title": "Renal protection in cardiovascular surgery",
"authors": [
"Nora Di Tomasso",
"Fabrizio Monaco",
"Giovanni Landoni",
"Nora Di Tomasso",
"Fabrizio Monaco"
],
"abstract": "Acute kidney injury (AKI) is one of the most relevant complications after major surgery and is a predictor of mortality. In Western countries, patients at risk of developing AKI are mainly those undergoing cardiovascular surgical procedures. In this category of patients, AKI depends on a multifactorial etiology, including low ejection fraction, use of contrast media, hemodynamic instability, cardiopulmonary bypass, and bleeding. Despite a growing body of literature, the treatment of renal failure remains mainly supportive (e.g. hemodynamic stability, fluid management, and avoidance of further damage); therefore, the management of patients at risk of AKI should aim at prevention of renal damage. Thus, the present narrative review analyzes the pathophysiology underlying AKI (specifically in high-risk patients), the preoperative risk factors that predispose to renal damage, early biomarkers related to AKI, and the strategies employed for perioperative renal protection. The most recent scientific evidence has been considered, and whenever conflicting data were encountered possible suggestions are provided.",
"keywords": [
"Acute kidney injury",
"cardiovascular surgery",
"biomarkers"
],
"content": "Introduction/Pathogenesis\n\nRenal damage is the first step of a potentially fatal cascade leading to kidney failure1. Therefore, it is considered an independent risk factor for death in the general population undergoing surgery2. Timely detection of early signs of renal damage, together with preventive kidney measures and renal protection, plays a key role in the patient’s outcome3, potentially reducing mortality, hospital length of stay, and costs4,5.\n\nAcute kidney injury (AKI) is defined as loss of excretory function, accumulation of nitrogen side-products, and reduction in urinary output, all leading to volume overload6. This corresponds, within 48 hours, to an increase in serum creatinine (sCr) between 1.5 to 1.9 times the baseline sCr (AKI stage 1), 2 to 2.9 times baseline (AKI stage 2), or more than 3 times baseline (AKI stage 3) and respectively to a reduction in urinary output of less than 0.5 mL/kg per hour for 6 to 12 hours, of less than 0.5 mL/kg per hour for more than 12 hours, and of less than 0.3 mL/kg per hour for 24 hours or anuria7,8.\n\nThe pathogenesis behind AKI is extremely complex and dependent on a variety of factors; however, in the perioperative setting, one of the most common causes is prolonged hypoperfusion (pre-renal AKI) associated with septic shock, cardiogenic shock, hypovolemia, and bleeding. Moreover, perioperative use of nephrotoxic drugs and contrast medium may further impair renal function8. Therefore, key steps in improving renal function and outcome are the identification of patients at high risk of AKI, avoidance of nephrotoxic agents, and adoption of protective renal strategies.\n\nWith the present review, we aim at analyzing, specifically in the cardiovascular surgery setting, possible risk factors for kidney damage, perioperative strategies for renal protection and optimization, and identifying potential screening tests able to determine patients at higher risk of AKI.\n\n\nPatients’ stratification\n\nPatients’ stratification to detect those at high risk of AKI is the first step to guarantee an individualized management7. The vast majority of randomized control studies and meta-analyses on perioperative renal protection measures were performed on patients undergoing cardiovascular surgeries. These patients are at increased risk of renal damage and failure due to preoperative critical heart function, the need for diagnostic procedures requiring contrast media, the effect of cardiopulmonary bypass (CPB), and the increased incidence of bleeding and low cardiac output syndrome (LCOS)9. More specifically, chronic kidney disease (CKD), systolic or diastolic left ventricular dysfunction, diabetes, and drugs such as angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, non-steroidal anti-inflammatory drugs (NSAIDs), and intravenous contrast medium are all preoperative factors that increase the risk of developing postoperative AKI10. On the other hand, complex cardiac surgery procedures with prolonged CPB and aortic cross-clamp time, hemodilution, and protracted low blood pressure are all intraoperative conditions that may further damage renal function.\n\nSeveral predictive scores for cardiac surgery-related AKI have been proposed as prognostic elements for anticipating patient treatment. The AKICS11 (Acute Kidney Injury following Cardiac Surgery) score, for example, evaluates preoperative (age of more than 65, preoperative creatinine of more than 1.2 mg/dL, preoperative capillary glucose of more than 140 mg/dL, and heart failure), intraoperative (combined surgeries and CPB time of more than 2 hours), and postoperative (low cardiac output [CO] and low central venous pressure) parameters associated with AKI. It seems to accurately predict post-cardiac surgery AKI.\n\nThe score by Thakar et al.12, which considers the major preoperative risk factors, such as higher sCr, diabetes, chronic obstructive pulmonary disease, previous cardiac surgery, severe cardiovascular disease, and female gender, seems to have the highest predictive value13 in the discrimination of patients at risk of developing Kidney Disease Improving Global Outcomes AKI (KDIGO-AKI).\n\nAnother interesting score for predicting the risk of postoperative dialysis, developed from a huge dataset of 449,524 patients by Mehta et al.14, showed that the risk of postoperative dialysis is correlated with preoperative kidney function (sCr of at least 2.6 mg/dL indicates extreme risk for dialysis), but other important factors can also influence postoperative renal function, such as advanced age and insulin-dependent diabetes, which are associated with glomerular sclerosis, and chronic respiratory disease, associated with prolonged ventilation.\n\nAlthough these scores provide a good starting point for early management of patients at risk for AKI, unfortunately no established and well-performing scoring system in cardiac surgery is able to stratify patients according to their risk of developing AKI. Great debate and further investigations are needed on the use of available mortality scores, like the additive EuroSCORE15.\n\n\nDiagnostic tests and biomarkers\n\nsCr and urinary output are routinely performed to assess renal function—Acute Kidney Injury Network (AKIN) and Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease (RIFLE) scores—even if both of them can be considered late (sCr increases only when glomerular filtration decreases by more than 50%) and indirect expressions of kidney damage6. More recent studies on functional genomics and proteomics have identified possible renal biomarkers that are still under investigation and that may act as early markers of renal impairment. Among these, the most promising are neutrophil gelatinase-associated lipocalin (NGAL), a “real-time” serum and urinary marker of tubular stress/injury16, and cystatin C (CyC), which detects changes in glomerular filtration rates17–19. NGAL has also been evaluated as a sensible marker of renal recovery in critically ill patients20,21, and CyC has shown a high rate of false-positive results in acute inflammation states (for example, following CPB)22. However, in complex cases with multiple comorbidities, the combination of CyC and NGAL may increase the sensitivity and specificity of such tests23. Recently, Prowle et al.24 have shown a possible correlation between serum and urinary levels of hepcidin in the 24 hours following cardiac surgery and postoperative AKI. However, these results require further investigation.\n\nMoreover, in different clinical settings such as severe sepsis and septic shock, markers such as liver-type fatty acid-binding protein (L-FABP)25, interleukin-18 (IL-18), kidney injury molecule-1 (KIM-1)26, and endogenous ouabain27, an adrenal gland stress hormone, have shown a good discriminant power between patients who will develop AKI and those who will not23. Although preliminary results seem promising and useful in clarifying the pathophysiology of renal dysfunction, new renal biomarkers are still not widely adopted in clinical practice and require further investigation.\n\n\nContrast-induced acute kidney injury\n\nNo specific treatment has been identified as effective in preventing AKI, and only few measures have been shown to reduce mortality in such patients6. Avoidance of nephrotoxic drugs, like NSAIDs, aminoglycosides, and radio-contrast agents, can significantly reduce the risk of AKI occurrence7. Among these, the use of contrast media is relevant, as it is associated with the so-called contrast-induced AKI (CI-AKI)28. Contrast medium affects kidney perfusion, mainly involving the renal medulla, causing a modest and transient decrease in renal blood flow. This leads to ischemia and tubular cell injury, which accounts for a considerable percentage of in-hospital cases of renal dysfunction29. CI-AKI is commonly defined as an increase of 25% or more (>0.5 mg/dL) in sCr levels 48 hours following contrast medium injection30. Specific results regarding CI-AKI in cardiac surgery are still lacking, and great debate persists. Hennessy et al. observed AKI onset after contrast agent administration, especially in patients undergoing valve surgery31. On the contrary, several other authors have not reported a worsening of renal function in the overall population when contrast media was administered the day before the surgical procedure32–34. Interestingly, Calzavacca et al.35, in a randomized cross-over experimental study, noted that administration of radio-contrast media does not induce vasoconstriction injury or a reduction of renal blood flow. A possible explanation for this finding may be that low-risk patients, with an overall uneventful perioperative course and preserved renal function, maintain adequate/sufficient kidney flow reserve, resulting in subclinical organ damage. On the other hand, high-risk patients, with CKD31,36, previous nephrectomy, or hemodynamic instability, further lose the capacity of renal blood flow auto-regulation when contrast medium is administered, resulting in medullary ischemia37. Moreover, in this specific population subset, AKI most commonly results from the overlap of baseline clinical characteristics, CI-AKI, and cardiovascular surgery-related injury38.\n\nBecause AKI is such a prominent in-hospital complication, many studies have been conducted to try to identify possible predictors of CI-AKI. Mehran et al.30, after analyzing 8357 patients undergoing percutaneous coronary intervention (PCI), proposed a clinical score including the patient’s demographics (age and sex), medical history (CKD: sCr >1.5 mg/dL), hematocrit (Ht), diabetes, advanced NYHA (New York Heart Association) class, previous pulmonary edema, and procedure-related variables (systolic arterial blood pressure of less than 80 mmHg and need for inotropic drugs or mechanical circulatory support or both) to predict the onset of post-procedural CI-AKI. Further considerations involve the administered volume of contrast medium, an elevated contrast medium volume-to-glomerular filtration rate ratio, and low left ventricular ejection fraction. Therefore, according to the Mehran Score, patients scoring positive for at least three risk factors will have a 26% probability of developing CI-AKI and a 1% probability of needing dialysis following PCI30.\n\nStrategies or drugs capable of preventing and reducing the risk of CI-AKI are still few and largely debated39. In clinical practice, perioperative hydration is commonly used along with an intravenous isotonic saline infusion rate of 1 mL/kg per hour from 4 to 12 hours before the procedure to 18 to 24 hours after the procedure40. Particular attention should be paid when dealing with heart failure patients for an increased risk of volume overload and exacerbation of unstable hemodynamic condition. Other measures are reduced volume of contrast medium, preferably using iso-osmolar or low-osmolar iodinated contrast medium (Table 1), and urine alkalinization with sodium bicarbonate despite conflicting results41. Several prospective studies and meta-analyses have analyzed N-acetylcysteine (NAC), reporting protective effects on renal function due to antioxidant properties42. However, the lack of well-designed randomized control studies with adequate sample size and statistical power and subsequent trials with negative findings strongly limited the widespread use of the compound43–45. Most of the previously reported limitations may be overcome with the conclusion of the ongoing large, adequately powered, randomized controlled trial (RCT) on the prevention of serious adverse events following angiography (PRESERVE). This study was designed to test the efficacy of sodium bicarbonate and NAC in the prevention of CI-AKI following angiography43. In this context, fenoldopam has shown no benefits in patients with CKD45.\n\n*First do not harm. ACEI, angiotensin-converting enzyme inhibitor; AKI, acute kidney injury; CPB, cardiopulmonary bypass; HES, hydroxyethyl starch; Ht, hematocrit; MAP, mean arterial pressure; NSAID, non-steroidal anti-inflammatory drug.\n\nTo date, even current guidelines are divided between KDIGO, which recommends volume expansion and oral NAC only in patients at risk of CI-AKI, and the American College of Cardiology, American Heart Association, and Society for Cardiovascular Angiography, which discourage instead NAC administration.\n\n\nAcute kidney injury in cardiac surgery\n\nThe incidence of AKI following cardiac surgery varies from 0.3% to 30%, and 3% of patients require temporary or long-term renal replacement therapy (RRT). Ischemia-reperfusion injury, exogenous and endogenous toxins, metabolic factors, oxidative stress, micro-embolization, neuro-humoral activation, inflammation, non-pulsatile CPB flow, and hemodynamic instability are the main determinants of AKI46. These factors can be present at the same time, acting synergistically or more often occurring randomly and with different importance.\n\nCPB is strongly believed to play a fundamental role in the development of AKI; thus, whenever possible, CPB avoidance is desirable. A recent, large RCT comparing patients undergoing coronary bypass surgery with or without CPB showed a reduced risk of postoperative AKI after off-pump coronary artery bypass grafting (CABG) surgery, although it failed to demonstrate a better preserved kidney function at 1 year47. Therefore, hemodynamic optimization rather than CPB utilization is the cornerstone for AKI prevention.\n\nConsequently, perioperative hypotension should be avoided and a mean arterial pressure (MAP) able to guarantee an adequate glomerular capillary filtration pressure is desirable. Although there is no optimal target MAP demonstrated to reduce the risk of AKI during CPB48, MAP values of more than 60 to 65 mmHg are a reasonable threshold to secure adequate renal perfusion. In patients with a clinical history reporting chronic hypertension or diabetes, higher MAP values should be considered.\n\nAccording to physiology, the kidneys are the second organ in terms of oxygen consumption and receive a high amount of blood flow. Nevertheless, the oxygen extraction fraction is low compared with other organs, making the kidneys extremely sensitive to changes in blood flow. Acute alterations in oxygen delivery (DO2) occurring during CPB may be responsible for renal function impairment. In fact, DO2 is given by the product between Ht and CO, the latter being replaced by pump flow during CPB; therefore, greater hemodilution corresponds to a lower DO2, unless CO or pump flow is increased. In a recent single-center retrospective cohort study, Ranucci et al. explored the relationship between low Ht levels (Ht of less than 24%) during CPB, decreased renal oxygen delivery, and postoperative AKI49. They found that strategies aiming at reducing hemodilution during CPB are effective in reducing AKI. This further recommends maintaining Ht levels above such a threshold and concomitantly setting the CO/pump flow according to the level of Ht. In the perioperative setting of cardiac and non-cardiac surgery, a liberal transfusion strategy has been recently proposed50 as not detrimental and even beneficial to improve survival.\n\nThis is of particular importance when dealing with high-risk patients undergoing cardiovascular surgical procedures, in which CO, DO2, and perfusion pressure as targets of a goal-directed therapy play a fundamental role in preventing cardiorenal syndrome that may develop and worsen the outcome. This complex disorder is characterized by LCOS secondary to heart failure, acute or chronic kidney dysfunction, and progressive organ involvement, leading to multi-organ failure.\n\nEarly signs of LCOS should be promptly recognized or preventively treated, optimizing heart rate and rhythm, improving bi-ventricular contractility, minimizing oxygen demand, and increasing oxygen delivery by using fluids, inotropes, or advanced extracorporeal assist devices (aortic balloon pump, extracorporeal membrane oxygenator, and left ventricular assist device). A recent meta-analysis by Zangrillo et al.51 confirmed the beneficial effects on 30-day survival of preoperative intra-aortic balloon pump in high-risk patients undergoing elective CABG.\n\nIn case of vasodilatory shock and sepsis, the use of vasopressors such as norepinephrine is mandatory to counteract renal hypoperfusion52. Interestingly, it was recently demonstrated for the first time that, according to published randomized evidence, inotropes and vasoconstrictors do not increase mortality in the perioperative period or in critically ill patients and are probably beneficial in some settings53.\n\nTherefore, inotropes and vasoconstrictors together with fluid and transfusion management are of central importance to prevent kidney injury through early hemodynamic optimization54.\n\nMoreover, fluid overload may have detrimental effects on renal function by ultimately worsening the outcome, especially when considering cardiac surgery patients55,56. In fact, elevated central venous pressure decreases the driving venous return pressure, possibly leading to interstitial space congestion, abdominal compartment syndrome, and renal congestion57. The last of these results in an increased renal intratubular pressure and a reduced glomerular filtration gradient. In critically ill patients, it may be challenging to distinguish whether fluid overload is a cause or the effect of AKI; however, a positive fluid balance is often associated with AKI58,59.\n\nRegardless of the amount of fluid administered, the type of fluid may also have an impact on the development of AKI. Current recommendations suggest using isotonic crystalloids for initial fluid expansion (in the absence of hemorrhagic shock), avoiding hydroxyethyl starch (HES) perioperatively, with the aim to prevent or treat AKI60,61. Uncertainty exists on the nephrotoxic risk when older colloids are administered62–64 instead of iso-oncotic solutions (third-generation colloids). On the other hand, a recent meta-analysis of randomized trials65 showed no evidence of a higher risk associated with third-generation HESs in cardiac surgery but did recommend further investigations in the future.\n\nAmong crystalloid solutions, saline is associated with hyperchloremia66 and reduced renal flow67, whereas buffered crystalloid solutions remain the fluid of choice in critically ill patients68, although a recent RCT showed no reduced risk of AKI with buffered crystalloids compared with saline69. Other RCTs with adequate statistical power and assessing high-risk population are needed for more conclusive results.\n\n\nOther treatments\n\nAlthough optimization of CO and reduction in CPB time are the key factors to reduce AKI incidence in cardiovascular surgery70, several other supportive therapies have been proposed (Table 2).\n\n*Too much is better than not enough. CABG, coronary artery bypass grafting; CO, cardiac output; DO2, oxygen delivery; GDT, goal-directed therapy; Hb, hemoglobin; HR, heart rate; Ht, hematocrit; MAP, mean arterial pressure; paO2, partial pressure of oxygen in arterial blood.\n\nFenoldopam has a selective vasodilatory effect on renal circulation and therefore is associated with an increased blood flow. Unfortunately, a recent large RCT demonstrated that fenoldopam infusion does not prevent worsening of AKI after cardiac surgery and is not associated with a reduced need for RRT71. A potential explanation is the underlying multifactorial nature of AKI; fenoldopam may theoretically be an effective treatment in the case of hypoperfusion AKI but not with ischemic insults. As previously mentioned, fenoldopam has also been found to be ineffective in preventing CI-AKI in patients with CKD72.\n\nDiuretics are the most commonly used drugs in critically ill patients for fluid overload management; however, they have shown no effect in AKI prevention and treatment (level of evidence 1B)7 and might be detrimental73,74. When AKI occurs, RRT represents the main treatment, although optimal timing and dose are still matters of debate75,76.\n\nGlucose management may prevent the occurrence of AKI. Some studies have reported a benefit whenever glycemic levels were strictly controlled77. However, further RCTs are needed to confirm the involvement of hyperglycemia in the development of AKI and on survival following cardiovascular surgery, and differences might exist between diabetic and non-diabetic patients78.\n\nStatins, in this context, play an important role as agents that exert antioxidant, antithrombotic, and anti-inflammatory effects. Indeed, according to an RCT79 and a recent meta-analysis80, statins seem to reduce mortality in patients undergoing cardiovascular surgery.\n\nCuriel-Balsera et al.81, on the other hand, in a prospective cohort study analyzing 7276 patients undergoing cardiac surgery, reported no benefit of statin administration in prevention of AKI. These results are in agreement with a previous study performed by Brunelli et al.82, in which the effect of statins on AKI was less prominent in the cardiac surgery population (high-risk patients) with respect to a general surgery group. Once again, these findings may be explained by the fact that, in this specific context, AKI is dependent on multiple factors, and simply correcting one single component within a multifactorial picture does not exert sufficient effects to impact the renal outcome.\n\nThe hemoadsorption device, a relatively new technique used as a filter able to eliminate cytokines and molecules producing cytokines, has potential anti-inflammatory properties. Mostly investigated in animal models of septic shock83 and patients with sepsis-related organ failure84, the hemoadsorption device seems to drastically reduce tumor necrosis factor, IL-6, IL-10, and procalcitonin other than free hemoglobin, myoglobin, and bilirubin. Its use is associated with an improvement in hemodynamic, renal, and liver function and a better outcome in a case report85. In cardiac surgery, retrospective observational studies showed the reliability and safety of the hemoadsorption device in reducing postoperative systemic inflammatory response syndrome86,87. Therefore, the hemoadsorption device represents a reasonable approach to prevent or improve anti-inflammatory-related renal injury after CPB, although RCTs in cardiac surgery patients are required.\n\nAspirin, a commonly used antiplatelet, has been suggested to be protective for postoperative renal injury. However, the risks associated with this drug, such as perioperative bleeding, may be deleterious for high-risk patient instability and may directly or indirectly provoke AKI88.\n\n\nFuture perspectives\n\nRRT before kidney injury has been proposed as a prophylactic intervention in patients at particularly high risk of developing kidney dysfunction89. Unfortunately, data supporting a preventive use of RRT in high-risk patients are insufficient90, although an early start of RRT may be beneficial to outcomes in patients with AKI91. The rationale of both early and prophylactic RRT is to restore homeostasis and support residual kidney function as soon as possible within different settings, such as fluid overload, immense pro- and anti-inflammatory response, and nephrotoxic agent-induced nephropathy. Future trials in cardiovascular surgery are warranted to support these data.\n\nRemote ischemic preconditioning is a promising, intriguing, and economic method to reduce postoperative AKI in cardiovascular surgery92. This strategy has additive effects when volatile agents are used because the latter can reduce mortality through cardiac protection and improve renal outcomes through a cardiorenal mechanism93. The beneficial organ-protective effects of remote ischemic preconditioning vanish when intravenous propofol is used94, and this may interfere with organ protection95.\n\nLevosimendan, a drug known as a calcium sensitizer with inotropic properties, has recently shown a promising beneficial effect on renal function and a reduction in the need for RRT96 in critically ill patients, including cardiovascular surgery patients. This molecule has beneficial effects on ventricular contraction (inotropic effect) and relaxation (improvement of diastolic function) without increasing myocardial oxygen demand and also has anti-inflammatory qualities97. All these properties, together with its action on venodilation and depression of central venous pressure, may play an important role in reducing renal congestion and increasing renal perfusion pressure. Further well-powered RCTs aiming to validate renal protection by levosimendan are warranted.\n\nEpidural anesthesia has been considered an effective anesthetic strategy, combined with general anesthesia, in improving perioperative outcomes, such as mortality, mechanical ventilation, and myocardial infarction and consequently related organ failure98. Recently, Landoni et al., in an updated meta-analysis, showed a mortality reduction in patients undergoing cardiac surgery with an epidural catheter99 and estimated a risk of epidural hematoma of 1:3552. However, we should always weigh the risk of the procedure, which requires adequate skills and specific care of anticoagulation administration. Therefore, future well-powered RCTs are needed to validate the efficacy of epidural anesthesia.\n\nEndothelin A-receptor antagonist (ET [A]-RA), assessed in animal models100, is a promising therapy for the prevention of post-cardiac surgery AKI. Indeed, the administration of ET (A)-RA during CPB has been associated with a reduction in endothelin-1 (ET-1) and in the numbers of inflammatory cells and an improvement in creatinine clearance. The rationale is that after CPB there is evidence of endothelial dysfunction caused by a reduction in endothelial nitric oxide synthase expression in the vascular endothelium and glomeruli and an increase in ET-1 expression in the tubular epithelium100. ET-1 itself induces renal vasoconstriction that could potentially have a critical pathogenic role in the development and progression of AKI101.\n\nThis setting determines loss of endothelial integrity and an oxidative cascade, so that the potential reverse of this insult could be beneficial. Unfortunately, only few animal studies102,103 support the possible therapeutic role of ET (A)-RA, and further trials on humans are urgently warranted.\n\n\nConclusions\n\nCardiovascular surgery-related AKI is a common and often dreadful event, frequently associated with higher morbidity and mortality. A number of preventive interventions are currently available, but only a restricted number of them are supported by a reasonable amount of evidence and are therefore recommended. The most feasible measures are to carefully analyze all the preoperative risk factors, in order to optimize medical therapy and management, and to prevent or promptly treat AKI. Timely intervention is of paramount importance because, once nephropathy is established, no available efficacious treatment exists, and this leads to an exponentially increased mortality.\n\nHence, regardless of the controversies behind the treatment and management of AKI, we strongly suggest a perioperative optimization of renal function, peripheral perfusion, and DO2 and an attentive avoidance of nephrotoxic drugs and fluid overload. This is of particular importance in a cardiovascular surgical setting, where patients are exposed to a major risk of developing AKI.\n\nFurther fields of research should focus on the identification of underlying risk factors or possible high-risk genetic traits, the investigation of novel and early biomarkers capable of recognizing patients with higher degrees of renal injury, and the development of new pharmacological or mechanical support measures aimed at the reduction of AKI occurrence.",
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PubMed Abstract | Publisher Full Text | Free Full Text\n\nSong S, Lee SH, Lee HC, et al.: Preoperative coronary angiography within one day of valve surgery is not associated with postoperative acute kidney injury in patients with preserved renal function. J Card Surg. 2015; 30(1): 7–12. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nOzkaynak B, Kayalar N, Gümüş F, et al.: Time from cardiac catheterization to cardiac surgery: a risk factor for acute kidney injury? Interact Cardiovasc Thorac Surg. 2014; 18(6): 706–711. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBrown ML, Holmes DR, Tajik AJ, et al.: Safety of same-day coronary angiography in patients undergoing elective valvular heart surgery. Mayo Clin Proc. 2007; 82(5): 572–574. PubMed Abstract | Publisher Full Text\n\nCalzavacca P, Ishikawa K, Bailey M, et al.: Systemic and renal hemodynamic effects of intra-arterial radiocontrast. Intensive Care Med Exp. 2014; 2(1): 32. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nGruberg L, Mintz GS, Mehran R, et al.: The prognostic implications of further renal function deterioration within 48 h of interventional coronary procedures in patients with pre-existent chronic renal insufficiency. J Am Coll Cardiol. 2000; 36(5): 1542–1548. PubMed Abstract | Publisher Full Text\n\nBaloria KA, Pillai BS, Goel S, et al.: Acute renal dysfunction: time from coronary angiography to cardiac surgery. Asian Cardiovasc Thorac Ann. 2013; 21(6): 649–654. PubMed Abstract | Publisher Full Text\n\nRanucci M, Ballotta A, Agnelli B, et al.: Acute kidney injury in patients undergoing cardiac surgery and coronary angiography on the same day. Ann Thorac Surg. 2013; 95(2): 513–519. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLi JH, He NS: Prevention of iodinated contrast-induced nephropathy. Chin Med J (Engl). 2011; 124(23): 4079–4082. PubMed Abstract\n\nChen SL, Zhang J, Yei F, et al.: Clinical outcomes of contrast-induced nephropathy in patients undergoing percutaneous coronary intervention: a prospective, multicenter, randomized study to analyze the effect of hydration and acetylcysteine. Int J Cardiol. 2008; 126(3): 407–413. PubMed Abstract | Publisher Full Text\n\nPannu N, Wiebe N, Tonelli M: Prophylaxis strategies for contrast-induced nephropathy. JAMA. 2006; 295(23): 2765–2779. PubMed Abstract | Publisher Full Text\n\nAnderson SM, Park ZH, Patel RV: Intravenous N-acetylcysteine in the prevention of contrast media-induced nephropathy. Ann Pharmacother. 2011; 45(1): 101–107. PubMed Abstract | Publisher Full Text\n\nWeisbord SD, Gallagher M, Kaufman J, et al.: Prevention of contrast-induced AKI: a review of published trials and the design of the prevention of serious adverse events following angiography (PRESERVE) trial. Clin J Am Soc Nephrol. 2013; 8(9): 1618–1631. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nZagler A, Azadpour M, Mercado C, et al.: N-acetylcysteine and contrast-induced nephropathy: a meta-analysis of 13 randomized trials. Am Heart J. 2006; 151(1): 140–145. PubMed Abstract | Publisher Full Text\n\nBriguori C, Colombo A, Airoldi F, et al.: N-Acetylcysteine versus fenoldopam mesylate to prevent contrast agent-associated nephrotoxicity. J Am Coll Cardiol. 2004; 44(4): 762–765. PubMed Abstract | Publisher Full Text\n\nDi Tomasso N, Monaco F, Landoni G: Hepatic and renal effects of cardiopulmonary bypass. Best Pract Res Clin Anaesthesiol. 2015; 29(2): 151–161. PubMed Abstract | Publisher Full Text\n\nGarg AX, Devereaux PJ, Yusuf S, et al.: Kidney function after off-pump or on-pump coronary artery bypass graft surgery: a randomized clinical trial. JAMA. 2014; 311(21): 2191–2198. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nAzau A, Markowicz P, Corbeau JJ, et al.: Increasing mean arterial pressure during cardiac surgery does not reduce the rate of postoperative acute kidney injury. Perfusion. 2014; 29(6): 496–504. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nRanucci M, Aloisio T, Carboni G, et al.: Acute Kidney Injury and Hemodilution During Cardiopulmonary Bypass: A Changing Scenario. Ann Thorac Surg. 2015; 100(1): 95–100. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nFominskiy E, Putzu A, Monaco F, et al.: Liberal transfusion strategy improves survival in perioperative but not in critically ill patients. A meta-analysis of randomised trials. Br J Anaesth. 2015; 115(4): 511–519. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZangrillo A, Pappalardo F, Dossi R, et al.: Preoperative intra-aortic balloon pump to reduce mortality in coronary artery bypass graft: a meta-analysis of randomized controlled trials. Crit Care. 2015; 19(1): 10. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRedfors B, Bragadottir G, Sellgren J, et al.: Effects of norepinephrine on renal perfusion, filtration and oxygenation in vasodilatory shock and acute kidney injury. Intensive Care Med. 2011; 37(1): 60–67. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBelletti A, Castro ML, Silvetti S, et al.: The Effect of inotropes and vasopressors on mortality: a meta-analysis of randomized clinical trials. Br J Anaesth. 2015; 115(5): 656–675. PubMed Abstract | Publisher Full Text\n\nBrienza N, Giglio MT, Marucci M, et al.: Does perioperative hemodynamic optimization protect renal function in surgical patients? A meta-analytic study. Crit Care Med. 2009; 37(6): 2079–2090. PubMed Abstract | Publisher Full Text\n\nKambhampati G, Ross EA, Alsabbagh MM, et al.: Perioperative fluid balance and acute kidney injury. Clin Exp Nephrol. 2012; 16(5): 730–738. PubMed Abstract | Publisher Full Text\n\nDass B, Shimada M, Kambhampati G, et al.: Fluid balance as an early indicator of acute kidney injury in CV surgery. Clin Nephrol. 2012; 77(6): 438–444. PubMed Abstract | Publisher Full Text\n\nLi X, Liu M, Bedja D, et al.: Acute renal venous obstruction is more detrimental to the kidney than arterial occlusion: implication for murine models of acute kidney injury. Am J Physiol Renal Physiol. 2012; 302(5): F519–25. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFülöp T, Pathak MB, Schmidt DW, et al.: Volume-related weight gain and subsequent mortality in acute renal failure patients treated with continuous renal replacement therapy. ASAIO J. 2010; 56(4): 333–337. PubMed Abstract | Free Full Text\n\nGrams ME, Estrella MM, Coresh J, et al.: Fluid balance, diuretic use, and mortality in acute kidney injury. Clin J Am Soc Nephrol. 2011; 6(5): 966–973. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nde Saint-Aurin RG, Kloeckner M, Annane D: Crystalloids versus colloids for fluid resuscitation in critically-ill patients. Acta Clin Belg Suppl. 2007; 62(2): 412–416. PubMed Abstract | Publisher Full Text\n\nVincent JL: Fluid resuscitation: colloids vs crystalloids. Acta Clin Belg Suppl. 2007; 62(2): 408–411. PubMed Abstract | Publisher Full Text\n\nSakr Y, Payen D, Reinhart K, et al.: Effects of hydroxyethyl starch administration on renal function in critically ill patients. Br J Anaesth. 2007; 98(2): 216–224. PubMed Abstract | Publisher Full Text\n\nMagder S, Potter BJ, Varennes BD, et al.: Fluids after cardiac surgery: a pilot study of the use of colloids versus crystalloids. Crit Care Med. 2010; 38(11): 2117–2124. PubMed Abstract | Publisher Full Text\n\nAnnane D, Siami S, Jaber S, et al.: Effects of fluid resuscitation with colloids vs crystalloids on mortality in critically ill patients presenting with hypovolemic shock: the CRISTAL randomized trial. JAMA. 2013; 310(17): 1809–1817. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nJacob M, Fellahi JL, Chappell D, et al.: The impact of hydroxyethyl starches in cardiac surgery: a meta-analysis. Crit Care. 2014; 18(6): 656. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nKaplan LJ, Kellum JA: Fluids, pH, ions and electrolytes. Curr Opin Crit Care. 2010; 16(4): 323–331. PubMed Abstract | Publisher Full Text\n\nReid F, Lobo DN, Williams RN, et al.: (Ab)normal saline and physiological Hartmann's solution: a randomized double-blind crossover study. Clin Sci (Lond). 2003; 104(1): 17–24. PubMed Abstract | Publisher Full Text\n\nSchick MA, Isbary TJ, Schlegel N, et al.: The impact of crystalloid and colloid infusion on the kidney in rodent sepsis. Intensive Care Med. 2010; 36(3): 541–548. PubMed Abstract | Publisher Full Text\n\nYoung P, Bailey M, Beasley R, et al.: Effect of a Buffered Crystalloid Solution vs Saline on Acute Kidney Injury Among Patients in the Intensive Care Unit: The SPLIT Randomized Clinical Trial. JAMA. 2015; 314(16): 1701–1710. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBove T, Calabrò MG, Landoni G, et al.: The incidence and risk of acute renal failure after cardiac surgery. J Cardiothorac Vasc Anesth. 2004; 18(4): 442–445. PubMed Abstract | Publisher Full Text\n\nBove T, Zangrillo A, Guarracino F, et al.: Effect of fenoldopam on use of renal replacement therapy among patients with acute kidney injury after cardiac surgery: a randomized clinical trial. JAMA. 2014; 312(21): 2244–2253. PubMed Abstract | Publisher Full Text\n\nStone GW, McCullough PA, Tumlin JA, et al.: Fenoldopam mesylate for the prevention of contrast-induced nephropathy: a randomized controlled trial. JAMA. 2003; 290(17): 2284–2291. PubMed Abstract | Publisher Full Text\n\nEjaz AA, Mohandas R: Are diuretics harmful in the management of acute kidney injury? Curr Opin Nephrol Hypertens. 2014; 23(2): 155–160. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nPalazzuoli A, Pellegrini M, Ruocco G, et al.: Continuous versus bolus intermittent loop diuretic infusion in acutely decompensated heart failure: a prospective randomized trial. Crit Care. 2014; 18(3): R134. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nOh HJ, Shin DH, Lee MJ, et al.: Early initiation of continuous renal replacement therapy improves patient survival in severe progressive septic acute kidney injury. J Crit Care. 2012; 27(6): 743.e9–18. PubMed Abstract | Publisher Full Text\n\nShum HP, Chan KC, Kwan MC, et al.: Timing for initiation of continuous renal replacement therapy in patients with septic shock and acute kidney injury. Ther Apher Dial. 2013; 17(3): 305–310. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLazar HL, McDonnell M, Chipkin SR, et al.: The Society of Thoracic Surgeons practice guideline series: Blood glucose management during adult cardiac surgery. Ann Thorac Surg. 2009; 87(2): 663–669. PubMed Abstract | Publisher Full Text\n\nKrinsley JS, Meyfroidt G, van den Berghe G, et al.: The impact of premorbid diabetic status on the relationship between the three domains of glycemic control and mortality in critically ill patients. Curr Opin Clin Nutr Metab Care. 2012; 15(2): 151–160. PubMed Abstract | Publisher Full Text\n\nSchouten O, Boersma E, Hoeks SE, et al.: Fluvastatin and perioperative events in patients undergoing vascular surgery. N Engl J Med. 2009; 361(10): 980–989. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nde Waal BA, Buise MP, van Zundert AA: Perioperative statin therapy in patients at high risk for cardiovascular morbidity undergoing surgery: a review. Br J Anaesth. 2015; 114(1): 44–52. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nCuriel-Balsera E, Muñoz-Bono J, Olea-Jimenez V, et al.: Preoperative use of statins does not improve outcomes and development of acute renal failure after cardiac surgery. A propensity score analysis of ARIAM-Andalucía database. Minerva Anestesiol. 2015; 81(7): 723–733. PubMed Abstract | F1000 Recommendation\n\nBrunelli SM, Waikar SS, Bateman BT, et al.: Preoperative statin use and postoperative acute kidney injury. Am J Med. 2012; 125(12): 1195–1204.e3. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nPeng ZY, Carter MJ, Kellum JA: Effects of hemoadsorption on cytokine removal and short-term survival in septic rats. Crit Care Med. 2008; 36(5): 1573–1577. PubMed Abstract | Publisher Full Text | Free Full Text\n\nForni LG, Ricci Z, Ronco C: Extracorporeal renal replacement therapies in the treatment of sepsis: where are we? Semin Nephrol. 2015; 35(1): 55–63. PubMed Abstract | Publisher Full Text\n\nZoller M, Döbbeler G, Maier B, et al.: Can cytokine adsorber treatment affect antibiotic concentrations? A case report. J Antimicrob Chemother. 2015; 70(7): 2169–2171. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBruenger F, Kizner L, Weile J, et al.: First successful combination of ECMO with cytokine removal therapy in cardiogenic septic shock: a case report. Int J Artif Organs. 2015; 38(2): 113–116. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBorn F, Pichlmaier M, Perterß S, et al.: Systemic Inflammatory Response Syndrome in der Herzchirurgie: Neue Therapie- möglichkeiten durch den Ein- satz eines Cytokin-Adsorbers während EKZ? Kardiotechnik. 2014; 23: 41–46. Reference Source\n\nGarg AX, Kurz A, Sessler DI, et al.: Perioperative aspirin and clonidine and risk of acute kidney injury: a randomized clinical trial. JAMA. 2014; 312(21): 2254–2264. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nMarenzi G, Marana I, Lauri G, et al.: The prevention of radiocontrast-agent-induced nephropathy by hemofiltration. N Engl J Med. 2003; 349(14): 1333–1340. PubMed Abstract | Publisher Full Text\n\nCruz DN, Goh CY, Marenzi G, et al.: Renal replacement therapies for prevention of radiocontrast-induced nephropathy: a systematic review. Am J Med. 2012; 125(1): 66–78.e3. PubMed Abstract | Publisher Full Text\n\nVilla G, Ricci Z, Ronco C: Renal Replacement Therapy. Crit Care Clin. 2015; 31(4): 839–848. PubMed Abstract | Publisher Full Text\n\nZarbock A, Schmidt C, Van Aken H, et al.: Effect of remote ischemic preconditioning on kidney injury among high-risk patients undergoing cardiac surgery: a randomized clinical trial. JAMA. 2015; 313(21): 2133–2141. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nZangrillo A, Musu M, Greco T, et al.: Additive Effect on Survival of Anaesthetic Cardiac Protection and Remote Ischemic Preconditioning in Cardiac Surgery: A Bayesian Network Meta-Analysis of Randomized Trials. PLoS One. 2015; 10(7): e0134264. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMeybohm P, Bein B, Brosteanu O, et al.: A Multicenter Trial of Remote Ischemic Preconditioning for Heart Surgery. N Engl J Med. 2015; 373(15): 1397–1407. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nHausenloy DJ, Candilio L, Evans R, et al.: Remote Ischemic Preconditioning and Outcomes of Cardiac Surgery. N Engl J Med. 2015; 373(15): 1408–1417. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nBove T, Matteazzi A, Belletti A, et al.: Beneficial impact of levosimendan in critically ill patients with or at risk for acute renal failure: a meta-analysis of randomized clinical trials. Heart Lung Vessel. 2015; 7(1): 35–46. PubMed Abstract | Free Full Text | F1000 Recommendation\n\nParissis JT, Adamopoulos S, Antoniades C, et al.: Effects of levosimendan on circulating pro-inflammatory cytokines and soluble apoptosis mediators in patients with decompensated advanced heart failure. Am J Cardiol. 2004; 93(10): 1309–1312. PubMed Abstract | Publisher Full Text\n\nSvircevic V, van Dijk D, Nierich AP, et al.: Meta-analysis of thoracic epidural anesthesia versus general anesthesia for cardiac surgery. Anesthesiology. 2011; 114(2): 271–282. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nLandoni G, Isella F, Greco M, et al.: Benefits and risks of epidural analgesia in cardiac surgery. Br J Anaesth. 2015; 115(1): 25–32. PubMed Abstract | Publisher Full Text\n\nPatel NN, Toth T, Jones C, et al.: Prevention of post-cardiopulmonary bypass acute kidney injury by endothelin A receptor blockade. Crit Care Med. 2011; 39(4): 793–802. PubMed Abstract | Publisher Full Text\n\nZager RA, Johnson AC, Andress D, et al.: Progressive endothelin-1 gene activation initiates chronic/end-stage renal disease following experimental ischemic/reperfusion injury. Kidney Int. 2013; 84(4): 703–712. PubMed Abstract | Publisher Full Text | Free Full Text | F1000 Recommendation\n\nArfian N, Emoto N, Vignon-Zellweger N, et al.: ET-1 deletion from endothelial cells protects the kidney during the extension phase of ischemia/reperfusion injury. Biochem Biophys Res Commun. 2012; 425(2): 443–449. PubMed Abstract | Publisher Full Text\n\nGellai M, Jugus M, Fletcher T, et al.: Reversal of postischemic acute renal failure with a selective endothelinA receptor antagonist in the rat. J Clin Invest. 1994; 93(2): 900–906. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "12879",
"date": "11 Mar 2016",
"name": "Zoltán Szabó",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12880",
"date": "11 Mar 2016",
"name": "Nader Nader",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-331
|
https://f1000research.com/articles/5-54/v1
|
12 Jan 16
|
{
"type": "Antibody Validation Article",
"title": "Antibody performance in ChIP-sequencing assays: From quality scores of public data sets to quantitative certification",
"authors": [
"Marco-Antonio Mendoza-Parra",
"Vincent Saravaki",
"Pierre-Etienne Cholley",
"Matthias Blum",
"Benjamin Billoré",
"Hinrich Gronemeyer",
"Vincent Saravaki",
"Pierre-Etienne Cholley",
"Matthias Blum",
"Benjamin Billoré"
],
"abstract": "We have established a certification system for antibodies to be used in chromatin immunoprecipitation assays coupled to massive parallel sequencing (ChIP-seq). This certification comprises a standardized ChIP procedure and the attribution of a numerical quality control indicator (QCi) to biological replicate experiments. The QCi computation is based on a universally applicable quality assessment that quantitates the global deviation of randomly sampled subsets of ChIP-seq dataset with the original genome-aligned sequence reads. Comparison with a QCi database for >28,000 ChIP-seq assays were used to attribute quality grades (ranging from ‘AAA’ to ‘DDD’) to a given dataset. In the present report we used the numerical QC system to assess the factors influencing the quality of ChIP-seq assays, including the nature of the target, the sequencing depth and the commercial source of the antibody. We have used this approach specifically to certify mono and polyclonal antibodies obtained from Active Motif directed against the histone modification marks H3K4me3, H3K27ac and H3K9ac for ChIP-seq. The antibodies received the grades AAA to BBC (www.ngs-qc.org). We propose to attribute such quantitative grading of all antibodies attributed with the label “ChIP-seq grade”.",
"keywords": [
"ChIP-sequencing",
"antibody",
"quality",
"massive parallel sequencing"
],
"content": "Introduction\n\nChromatin immunoprecipitation combined with massive parallel sequencing (herein described as ChIP-sequencing or ChIP-seq) is currently intensively used as a method for assessing protein-DNA interactions and/or chromatin modifications on a genome-wide scale. It is well-accepted that optimal ChIP-sequencing assays require highly specific and sensitive antibodies, thus an important battery of validation tests is strongly recommended for their characterisation1. In addition to the concerns of the scientific community about the current strategies for validating antibodies, which are commercially promoted for certain various applications, also the assessment of antibody performances in ChIP-sequencing assays remains still a major issue, mainly due to the absence of quantitative approaches for qualifying ChIP-seq assays.\n\nWe have previously described a universal in silico approach to generate quality descriptors for any ChIP-sequencing and related datasets2. Importantly, this concept has been used to establish the largest database worldwide, which harbors currently the quality scores for more than 28,000 publicly available datasets (www.ngs-qc.org). Notably, in contrast to other metrics previously described for the qualification of ChIP-seq assays3, this system evaluates the robustness of the enrichment patterns populating a given profile by comparative analyses of the original profile and profiles generated after random sub-sampling from a reduced fraction of the total mapped reads. This methodology is applicable to any type of enrichment-related dataset and the inferred quality indicators can thus be used for comparative purposes. In order to provide simple and intuitive quality designations the quality indicators were discretised using a three letter grading score; accordingly, the profiles range from highest “AAA” to the lowest “DDD” quality.\n\nIn this study, we present first an analysis concerning the quality of the available >28,000 data sets in the context of their sequencing-depths used and of the antibody sources. Thereafter, we introduce a certification procedure, which should be used to associate a defined referenced batch of an antibody with a reliable validated ChIP-sequencing grade.\n\n\nMaterials and methods\n\nAll datasets presented in the retrospective analysis were originally retrieved from the GEO database and processed with the NGS-QC Generator algorithm. Quality indicators (QCis) were computed as previously reported2. Briefly, QCis were generated by comparing the original read intensity profile with those observed in a fraction of the total mapped reads. For this, total mapped reads (TMRs) were first randomly sub-sampled at three defined subsets (90%, 70% and 50% respectively), then the read counts in 500 nt bins of the genome were computed for each of the random sub-sampled as well as in the original dataset. In the ideal theoretical case the read counts in all genomic bins are expected to decrease proportionally to the random subsampling (e.g., a 50% decrease of the read count intensity (RCI) when 50% of the original TMRs were sub-sampled). Genomic regions presenting the lowest variations from this theoretically expected value are considered “robust” to the random sampling and thus of high quality. For quantitation we calculated the fraction of genomic windows with RCI dispersions within defined levels (2.5, 5 and 10%).\n\nQuality scores for all analysed publicly available datasets are available at www.ngs-qc.org. The antibody references associated with the ChIP-seq datasets analysed in this study are given in Table 1.\n\nWe propose the following certification procedure for antibodies to be used in ChIP-seq and related enrichment-based technologies. Clearly, this certification will not replace but rather complement the molecular biology assays currently used for validating antibody specificity. Indeed, it provides a certificate of antibody performance specifically in ChIP-seq assays. The following experimental conditions were used for the certification of antibodies described in this study:\n\nCell culture. HeLa cells were grown in DMEM 1g/L glucose, 5% Fetal Calf Serum and 40µg Gentamicin to a density of 15–20 millions cells/15cm plates. Cells were fixed for 30min with paraformaldehyde (1% in PBS). Fixation was quenched with 0.2M glycine in PBS, then cells were washed three times with PBS, collected and stored at -80°C.\n\nChromatin immunoprecipitation. Sonication: 40 million cells were sonicated in 500µL of Lysis Buffer (1% Na-deoxychlorate, 50mM TrisHCl pH8, 140mM NaCl, 1mM EDTA, 1% Triton X-100) containing 5-times diluted Protease Inhibitor Cocktail (PIC; Roche Diagnostic; 1 tablet solubilized in 10ml Lysis Buffer). Sonication was performed with a Bioblock Scientific instrument (Vibra Cell 75043; 40 cycles, 30s ON end 59s OFF; 38% power). Chromatin fragmentation was evaluated by agarose gel electrophoresis as follows: 20µL of sonicated chromatin was diluted with 20µL TE (10mM Tris-HCl pH 8, 1mM EDTA) and 5µL 5M NaCl was added. Diluted chromatin was incubated at 100°C for 30 min, centrifuged at 12,000 rpm at room temperature and the supernatant was loaded onto a 2% agarose gel.\n\nChromatin Immunoprecipitation: 25µL of ChIP-IT Protein G Magnetic Beads (ActiveMotif) were incubated with the antibody under evaluation (the amounts of antibody in use corresponded to that indicated by the supplier’s information) in presence of 100µL PIC-containing Lysis Buffer. After two hours at 4°C on a rotating shaker, chromatin from 3 million cells was added and the final volume was adjusted to 500µL with PIC-containing Lysis Buffer and incubation on a rotating shaker was continued overnight at 4°C. The immunoprecipitated chromatin was recovered by magnetic bead separation, followed by multiple washing steps on a custom liquid handling platform (TECAN EVO75). Specifically, the washing is performed as follows: (1) Low salt washing (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM TrisHCl pH 8, 150mM NaCl); (2) High salt washing (0.1% SDS, 1% Triton X-100, 2mM EDTA, 20mM TrisHCl pH 8, 500mM NaCl); (3) LiCl-washing (0.25M LiCl, 1% IGEPAL CA630, 1% Na-deoxycholate, 1mM EDTA, 10mM Tris pH 8) and (4) 1×TE washing. The immunoprecipitated chromatin was eluted and de-crosslinked in 100µL of elution buffer (1% SDS, 100mM NaHCO3, 250mM NaCl, 0.2mg/ml Proteinase K) and incubated for 4 hours at 65°C. The eluted chromatin was supplemented with 200µL H2O and 300µL phenol/chloroform/isoamyl alcohol (25/24/1) mix was added. After two extraction steps, the aqueous phase was subjected to ethanol precipitation in presence of 1µL GlycoBlue (Invitrogen; 15mg/ml). The precipitated material was re-suspended in 45µL H2O; 5µL was used for validation by quantitative PCR, the remaining 40µL was used for DNA library preparation.\n\nDNA library preparation and massive parallel sequencing. The DNA library preparation for massive parallel sequencing was performed according to standard procedures (NEXTFlex ChIP-Seq Kit (Biooscientific)) adapted to automation by our custom liquid handling platform (TECAN EVO75). Prior to DNA sequencing library preparation was monitored using a Tapestation (Agilent). Samples were sequenced on an Illumina HiSeq2500 platform following manufacturer’s standard procedures.\n\nNGS-QC certification. The antibody certification is based on the quality control system previously described2. The certification is based on two biological replicate ChIP-seq assays performed at high sequencing depths (~50 million mapped reads per dataset). For each replicate the global quality grades were computed. In addition the following issues were part of the certification:\n\nOptimal sequencing depth: This is performed by re-computing quality grades at decreasing fractions of the initial total mapped reads (TMRs). Briefly, defined TMR subsets were generated by random sampling (20%, 40%, 60%, 80% and 100% of TMRs) and quality scores were assessed. The sequencing depth at which the quality grades transit from A to B is extrapolated and designated as optimal sequencing depth.\n\nLocal QC Irreproducibility Discovery Rate (local QC-IDR): Concordance among biological ChIP-seq replicate assays were previously assessed by the Irreproducibility Discovery Rate assay4. Similarly, we have established an IDR-type assay based on the comparison of the location of genomic regions (500nt length) presenting the lowest read count intensity dispersion (dRCI). Briefly, genomic regions displaying a dRCI <10% in the two biological replicates were paired and ranked on the basis of their lower absolute difference between paired dRCI values (genomic regions present in only one dataset are kept and paired with a “penalty genomic window” for which a dRCI=15% was allocated). Finally, the local QC-IDR was defined as the fraction of the top 5,000 windows using a sliding window of 500nt.\n\nComparing QC scores with those assessed for publicly available data. Antibody certification scores were compared with quality scores computed from publicly available data in the context of their TMRs. For it, a scatter-plot displaying quality scores (y-axis) relative to the TMRs (x-axis) was generated for all datasets associated to the particular target molecule, as well as for that related to the certified antibodies.\n\n\nResults\n\nThe NGS-QC Generator database hosts currently quality scores for >28,000 datasets (www.ngs-qc.org; December 2015), covering a variety of ChIP-sequencing and related assays (e.g. Dnase-seq, FAIRE-seq, MBD-seq, GRO-seq, etc) performed from 9 species (Homo sapiens: 54%; Mus musculus: 34%; D. melanogaster: 6%; etc) (Figure 1A). As it is based on datasets available from GEO, we retrieved antibody sources for 12,036 datasets from the complementary information; 96% of these corresponded to human or mouse-related assays (Figure 1B). Furthermore, these datasets concern 680 different target molecules, with several histone modifications being highly represented (Figure 1C). Finally, thanks to the information provided by the authors, we managed to trace the commercial sources of the antibodies (Figure 1D). Overall, this analysis reflects the interest of the scientific community in studying the role of epigenetic factors in human and mouse systems. The data reveal also that three companies dominate the market, as they provided the antibodies for 75% of the evaluated datasets.\n\n(A). The NGS-QC Generator database hosts currently quality scores for 28,108 datasets from a variety of organisms. For about 50% of the datasets the commercial source of the used antibodies could be retrieved from the information present in GEO. (B). Classification per organism of the qualified datasets for which the antibody source is known. Note that nearly 90% correspond to Homo sapiens or Mus musculus datasets. (C). Top ranked target molecules for which the antibody source is known. (D). Ten most-used commercial antibodies retrieved from the NGS-QC database.\n\nAs ChIP-seq datasets for the histone modifications H3K4me3, H3K27ac, H3K27me3 and H3K4me1 are the most represented in the collection (Figure 1C), we focused our analyses on these datasets.\n\nWe first evaluated quality grades in the context of sequencing depths. Importantly, the expected increase in quality relative upon increased sequencing-depth is not uniform but is rather target-dependent, as is supported by the different slopes of the datasets (Figure 2A). Indeed, while H3K4me3 datasets reach high quality even with relatively low sequencing depth (~25M TMR), the profiles for H3K27me3, which display broad signals, require >60M TMRs for reaching an “AAA” qualification (Figure 2A). Figure 2B illustrates the differences in quality that correspond to the different quality grades (Figure 2B); note that these data have been obtained with human embryonic stem (ES) cells using the same antibody5–7.\n\n(A) Scatter-plot illustrating global quality scores relative to sequencing depth for ChIP-seq assays concerning the indicated histone modification marks. All illustrated mouse or human datasets were retrieved from the public domain and qualified with the NGS-QC Generator. Quality scores were computed for a read count intensity dispersion (dRCI) of 2.5%. Broken lines depict to the transition borders between discretized quality grades (“A”, “B”, “C” or “D”) defined as the quartiles of the quality distribution computed from the entire NGS-QC collection (>28,000 datasets). The continuous lines correspond to the locally weighted scatter-plot smoothened (LOWESS) regression curves (displayed confidence interval p-value: 0.995). (B) Local genomic view (HoxD cluster) displaying read count intensity patterns for the histone modification mark H3K27me3 derived from three different datasets. In all cases the same cell type (human ES cells) and antibody source (Millipore: # 07–449) has been used, while different DNA sequencing coverage was applied. Note that the associated quality grades correlate with the sequencing depth.\n\nAnother aspect to highlight is the fact that there is a high variability of quality scores for profiles from <50M TMRs. In contrast, all datasets with higher sequencing depths tend to have quality grades between “B” and “A” but the number of such datasets is low compared to those with less sequencing coverage. These observations clearly support the notion that in addition to the sequencing depth, other experimental factors - including the commercial source of the antibody - directly influence the global quality of ChIP-sequencing assays.\n\nTo further explore the role of the antibody source, we have classified the different datasets for antibody vendors and TMR intervals, such that the quality grades per datasets are displayed in context of these two parameters. As illustrated in Figure 3, this classification recapitulates the influence of the sequence depth irrespective of the antibody source and reveals the target–specific quality differences. For example at <50 million TMRs most of the evaluated H3K27me3 datasets (Figure 3A) have quality grades lower than “A”. However, while datasets generated with an antibody from a particular vendor would rapidly gain in quality grades with increased TMRs, those from other sources improve only weakly and require much more TMRs to reach the highest quality grades; examples are the H3K27me3 antibodies of Millipore and Abcam with the Millipore one exhibiting the higher robustness. Similarly, H3K4me1 datasets require >20M TMRs to reach high quality grades but a few antibodies yielded datasets at 20–30M TMRs that got grade “A”, while others needed much higher coverage to reach “A” grades; examples are again the Abcam and Millipore antibodies, which show the inverse robustness of their H3K27me3 counterparts (Figure 3B). Notably, datasets related to the histone modification marks H3K27ac and H3K4me3 present high quality grades even for lower TMRs. In fact a minimum of 10–20 million reads was sufficient to attribute quality grade “A” to some H3K27ac datasets (Figure 3C) and even lower DNA sequencing coverage was required to reach such quality scores for H3K4me3 datasets (Figure 3D).\n\nDatasets for each target were categorized on the basis of their sequencing coverage (X-axis: from 1 to 100 total mapped million reads; intervals of 10 million and a last category from 100–500 million), as well as on their quality grade (Y-axis: from “A” to “D”, defined on the basis of a read count intensity dispersion (dRCI) threshold criterion of 2.5%). The illustrated bar graph correspond to the fraction of datasets related to a given vendor per TMRs interval. A to D. Frequency bar graphs corresponding to H3K27me3, H3K4me1, H3K27ac and H3K4me3, respectively.\n\nTaken together this analysis reveals that while there is a general direct correlation between the sequencing depth and the quality scores of the corresponding profiles, there are three important considerations: (i) a minimal sequencing depth is required to ensure an acceptable quality of the assay; (ii) the nature of the histone mark has a profound impact on the sequencing depth needed to reach high quality grades, as the increase in quality with increasing coverage is not genuine and differs between marks; and (iii) the source of the antibody has a significant impact on the quality of the profile that can be obtained at a certain sequencing depth.\n\nOverall, this meta analysis provides not only numerical values to assess the effect of the sequencing depth on ChIP-seq quality, but it offers in addition the possibility to rate the performance of new antibodies and antibody batches. Note, however, that a multitude of additional factors affects the quality of ChIP-seq datasets independently of the antibody source; these factors include cell types/tissues in use, the chromatin fixation conditions, experimenter variability, and many more. Indeed, the scatter of QCis observed at defined TMR intervals (Figure 2A) results most likely from such effects. As a consequence antibody certification for ChIP-seq assays should be based on standardized experimental conditions together with quality assessment derived from biological duplicates at high sequencing depth, such that optimal sequencing depths can be recommended to the users.\n\nTo respond to the needs of the scientific community for highly reliable, target specific, low background polyclonal (and monoclonal) antibody sources for epigenome or any other ChIP-based studies commercial antibody suppliers have incorporated “ChIP-seq grade” antibodies in their portfolio and based this grade on visual inspection of generally a single selected genomic region from a ChIP-seq profile. However, there are several problems associated with this procedure: First, the screenshot of a rather short genomic region says next to nothing about the quality of the entire genome-wide profile. Second, the assay conditions and sequencing statistics are generally not provided, and third, information on replicate and batch variation is generally missing.\n\nTo improve this situation we have set up a certification procedure which is based on (i) the use of a highly reproducible pipeline for performing ChIP-seq samples preparation and (ii) the use of the NGS-QC Generator tool for assessing quality grades from biological replicates that can this time reflect the performance of the antibody (Figure 4A). The procedure involves an extensive documentation including experimental details, full sequencing statistics and quality analysis of the profiles obtained from biological replicates together with recommendations for how to use this antibody to obtain optimal quality grades.\n\n(A). Scheme of the antibody certification procedure comprising the standardization of the experimental steps involved in sample preparation and computational treatment of ChIP-seq datasets. (B) to (F). Examples of some of the key analytical data generated from biological replicates during the certification process using the Active Motif anti-H3K27ac antibody # 39685. (B). Quantitative RT-PCR validation of the chromatin enrichment efficacy performed at the end of the standardized experimental procedure. DPP10 and MB (Myoglobin) refer to reference regions devoid of H3K27ac, while GAPDH and CCNA2 promoter regions are used for the evaluation of the enrichment levels (Fold occupancy relative to DPP10). (C). Extrapolation of the optimal sequencing depth by sub-sampling of the initial TMRs. The inferred quality scores are displayed relative to the mapped reads. The vertical green line defines the reads at which the transition of quality grade from “A” to “B” is observed. (D). Irreproducibility discovery rate (IDR) of biological replicates. The local QC IDR is defined as the fraction of genomic regions (500nt window size) which exhibit reproducibly read count intensity dispersion levels (dRCI) below 10%. For computation, all genomic regions were subdivided in groups of 5,000 windows (sliding window with a span of 500nt) followed by ranking according to their RCI dispersion. The X-axis displays the ranked genomic regions for which the local QC IDRs (Y-axis) were computed. The broken horizontal line delimits a local QC IDR threshold of 0.1, which is used to define the number of genomic windows with sub-threshold IDR levels. (E). Scatter-plot displaying the quality scores computed during the antibody certification (triangles correspond to the two biological replicates used in the certification process) relative to those of publicly available H3K27ac ChIP-seq datasets. (F). Genomic region (chromosome 12), illustrating the local enrichment of H3K27ac mark generated by the certified antibody. Below each read count intensity profile, a heatmap illustrates the robustness of genomic bins (500nt) to random sampling as measured by their dRCI levels (yellow to black: 0–10%). The certification grade attributed to this antibody is quality grade “AAA” as indicated.\n\nThis certification procedure, which is based on the use of an automated liquid handling platform for ChIP assays and subsequent preparation of the corresponding sequencing library, has been set up with a panel of six antibodies kindly provided by Brian Egan of Active Motif. Specifically, antibodies targeting the histone modification marks H3K4me3, H3K27ac and H3K9ac were enrolled in the certification process; for each of them monoclonal and polyclonal preparations were assessed. ChIP assays were performed with Hela cells cultured and formaldehyde-fixed (see Materials and methods). The efficacy of the ChIP was verified by quantitative RT-PCR (Figure 4B). The conditions for the automated preparation of the sequencing library were also standardized.\n\nMassive parallel sequencing was performed at high depth such that coverage was not a limiting factor for quality assessment and that the minimal sequencing depth to obtain “A” quality scores could be predicted (Figure 4C). An important component is the evaluation of the irreproducibility discovery rate of biological replicates as an integral part of the certification process (Figure 4C). Finally, we also performed a comparison with the quality grades assessed relative to the publicly available datasets (Figure 4D) and we provide screenshots of several local genomic regions to illustrate the read count enrichment for the biological replicates and to provide a local quality score (500nt window, heatmap; Figure 4E).\n\nOverall, this certification procedure provides quantitative means for assessing antibody performance in ChIP-sequencing assays, thus their \"ChIP-seq grade\" would not represent a questionable marketing argument but rather a solid certification label.\n\n\nConclusion\n\nAs ChIP-sequencing assays are becoming widely used for studies in epigenetics/chromatin modification and the definition of chromatin interactions with transcription factors and other regulatory factors/machineries, it is of highest importance that scientist have access to antibodies of high quality and reliability such that the antibody performance can be excluded as a source of low quality and variability between datasets. Such quality differences are obvious from QC indicator database that we have established (www.ngs-qc.org). This database comprises more than 28,000 qualified datasets and this number is expected to increase largely within the years with the “democratisation” of this technology. It is important to point out that the present retrospective analysis revealed that an important fraction of the datasets in the public domain is below acceptable quality standards to perform for example multi-profile comparisons.\n\nHere we clearly demonstrate, on the basis of a numerical quality evaluation of a large number of datasets, several features which impact on ChIP-seq quality. First, there is a direct correlation with the sequencing depth. Second, we reveal the direct influence of the nature of the molecular factor as another parameter to consider for the minimal sequencing depth that has to be used to get high quality datasets. As a rule of thumb transcription factors and histone modifications that produce locally confined signals (“sharp peaks”) in the corresponding profiles can be sequenced at lower coverage that for example histone marks which generate “broad peaks”. Third, given that analysis is based on a rather comprehensive collection of datasets, we were for the first time in a position to evaluate the effect of the commercial source of an antibody on the quality of the obtained datasets. Importantly, while we did not observe dramatic differences among the various antibodies at high sequence coverage, there are indeed significant differences when sequencing was performed at lower coverage. Fourth, there is a large difference between the quality of experiments even when the same antibody and the same cell type is used; most plausibly this is due to difference in the performance/materials/methods that have been used in the various laboratories.\n\nFor this reason we have developed an antibody certification procedure dedicated to ChIP-sequencing applications, in which (i) sample preparation is performed under standardized conditions; and (ii) quantitative analytical metrics are applied for assessing the antibody performance. With such a certification at hand the experimenter knows the performance of a given antibody and can follow the guidelines for its use to obtain maximal quality at minimal cost.\n\nThis methodology has been set up with multiple antibodies provided by Active Motif; the corresponding quality certification reports are freely available from our website (www.ngs-qc.org). Considering that this approach provides quantitative data for attributing the \"ChIP-seq grade\" to a particular antibody batch, the use of such metrics will significantly improve consumer confidence in this label.\n\n\nData access\n\nQuality reports for all ChIP-sequencing datasets discussed in this study are available via the NGS-QC database (www.ngs-qc.org). Raw data associated to the discussed antibody certification procedure is available at the NCBI Gene expression Omnibus database under accession number GSE76618.",
"appendix": "Author contributions\n\n\n\nM.A.M-P. developed the concept of quality control for ChIP-sequencing assays, as well as the structure of the presented antibody certification procedure. M.B. and P-E.C. work in the maintenance of the NGS-QC database and the corresponding implementations. M.B. implemented together with M.A.M-P, the various computational modules dedicated to the antibody certification procedure. B.B. performed the standardization of ChIP samples and library preparation under the guidance of M.A.M-P and H.G. V. S. performed the retrospective analysis under the guidance of M.A.M-P and H.G. M.A.M-P and H.G. wrote the manuscript. All authors have seen and agreed to the final content of the manuscript.\n\n\nCompeting interests\n\n\n\nThe authors have no competing interests. Note that albeit Active Motif provided antibodies to set up the certification procedure, they did not participate in nor influence any step of its development.\n\n\nGrant information\n\nThis work was supported by funds from the Alliance Nationale pour les Sciences de la Vie et de la Santé (Aviesan) –Institut Thématique Multi-organismes Cancer (ITMO Cancer) –Institut National du Cancer (INCa) and the Ligue National Contre le Cancer (Equipe Labellisée). B. Billoré has been supported by SATT-Conectus Alsace during the development of the antibody certification procedure. P.-E. Cholley has been supported by the Fondation pour la Recherche Médicale (FRM).\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgements\n\nWe thank B. Egan from Active Motif for kindly providing sets of poly and monoclonal antibodies. Furthermore, we would like to thank the IGBMC Microarray and Sequencing platform, for DNA massive parallel sequencing. The sequencing platform is supported by the FG National Infrastructure, funded as part of the “Investissements d’Avenir” program managed by the Agence Nationale pour la Recherche (ANR-10-INBS-0009).\n\n\nReferences\n\nWardle FC, Tan H: A ChIP on the shoulder? Chromatin immunoprecipitation and validation strategies for ChIP antibodies [version 1; referees: 2 approved]. F1000Res. 2015; 4: 235. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMendoza-Parra MA, Van Gool W, Mohamed Saleem MA, et al.: A quality control system for profiles obtained by ChIP sequencing. Nucleic Acids Res. 2013; 41(21): e196. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLandt SG, Marinov GK, Kundaje A, et al.: ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 2012; 22(9): 1813–1831. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLi Q, Brown JB, Huang H, et al.: Measuring reproducibility of high-throughput experiments. Ann Appl Stat. 2011; 5(3): 1752–1779. Publisher Full Text\n\nGafni O, Weinberger L, Mansour AA, et al.: Derivation of novel human ground state naive pluripotent stem cells. Nature. 2013; 504(7479): 282–286. PubMed Abstract | Publisher Full Text\n\nGafni O, Weinberger L, Mansour AA, et al.: Corrigendum: Derivation of novel human ground state naive pluripotent stem cells. Nature. 2015; 520(7549): 710. PubMed Abstract | Publisher Full Text\n\nOnder TT, Kara N, Cherry A, et al.: Chromatin-modifying enzymes as modulators of reprogramming. Nature. 2012; 483(7391): 598–602. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "12201",
"date": "12 Feb 2016",
"name": "Antonio Hurtado",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis paper suggest a quantitative approach for certification of ChIP-seq grade antibodies. This is an interesting aim and the authors point out several factors influencing the quality of ChIP-Seq data sets.In the paper they have retrieved antibody sources for 12036 datasets from GEO, and these data are illustrated in different figures. Using data from GEO they have also produced a figure illustration how different sequencing depth can be needed for different histone modification analyzed. The authors have also used 3 antibodies from Active Motif to illustrate how they can give scoring to a given antibody. However, if the authors aim to make certification of specific antibodies they should provide a more detailed and standardized protocol. Moreover, they should also comment why they choose to x-link 30 min in paraformaldehyde, rather than more common 10 min in 1% formaldehyde. The choice of kit for making library should be discussed, and also why they have used a not so common kit in their procedure.Also variation in performance between different lot of polyclonal antibodies should be discussed. It would also be interesting with a discussion of the practical relevance of the different grades from scoring for a specific antibody.",
"responses": [
{
"c_id": "1858",
"date": "11 Mar 2016",
"name": "Marco-Antonio Mendoza-Parra",
"role": "Author Response",
"response": "We are very grateful to Antonio Hurtado for reviewing our manuscript, and for his useful comments/suggestions to improve our manuscript. Following the reviewer’s suggestions, we have included additional elements in the revised version of the manuscript. Specifically we would like to emphasize that the described certification procedure does not imply to imperatively use a given library preparation kit nor any of the other reagents. Our aim was solely to advocate for the use of a standardized protocol, which includes the use of an automated procedure to minimize the impact of experimenter-derived variability. Along the same lines, paraformaldehyde cross-linking conditions were those previously used for various types of assays, including the ChIP-seq of transcription factors. This being said, we do agree with the reviewer that shorter crosslinking times are currently used by several laboratories; nevertheless we would like to emphasize that 30 minutes paraformaldehyde fixation did not prohibit multiple assays to perform with the top level \"triple A\" quality.We have also included modifications in the Conclusion part of the manuscript concerning the evaluation of antibody batches. Indeed, in the same manner that different antibodies sources can affect with the performance of the assay, we believe that different batches of polyclonal antibodies may present variable quality performances. However, it is difficult to perform population studies using public data in the context of antibody batches, as there is no systematic information about the antibody batch in public databases. In this context, we want to point out that the scientific community would benefit significantly if repositories like GEO would ask authors at the time of submission to include a mandatory description, of the experiments corresponding to the datasets provided, including among others the target, cell line or tissue, the antibody source and batch, and all other relevant experimental descriptions."
}
]
},
{
"id": "12202",
"date": "04 Mar 2016",
"name": "Jason S. Carroll",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nChIP-seq is becoming a standard tool for transcription factor or histone mark mapping, but many assumptions are made about the reproducibility of this method, particularly between factors. There is a general assumption that one set of parameters are appropriate for all ChIP-seq experiments, regardless of the factors being purified. No genuine gold standard exists for ChIP-seq and the current accepted guidelines defined by Encode, may or may not be of sufficient robustness (i.e. Encode recommend two ChIP-seq replicates, which eliminates any possibility for statistical differential analysis and simply wouldn’t be acceptable for almost any other genomic analysis). One big issue in ChIP-seq, is the quality of the antibody and the number of required reads to get robust data. This manuscript provides a very useful and important tool for dealing with this critical issue. The QC indicator described and tested in this manuscript, provides a user-friendly way of gaining insight into the best antibody for a factor and the minimum read depth needed for an experiment to capture most binding sites and to therefore be considered successful. The system described here provides information about the best reagents and the appropriate sequencing depth, using a clear and informative grading system. The findings from this paper show that different sources of antibodies have distinct efficiencies and that different sequencing depth is required for individual factors, an importantly and largely unknown finding. Whilst the method is based on a priori knowledge and doesn’t account for non-specific antibodies or isn’t appropriate for novel factors that haven’t been previously explored, the QCi approach is an important and much needed resource, for both novices and experts. This tool will undoubtedly improve the quality of the data that is being produced and analysed by the community and this should be the first place to start for anyone thinking of doing ChIP-seq experiments.",
"responses": [
{
"c_id": "1857",
"date": "11 Mar 2016",
"name": "Marco-Antonio Mendoza-Parra",
"role": "Author Response",
"response": "We would like to thank Jason Caroll and Adam Nelson for investing time in the revision of our manuscript. Specially, we are very pleased to learn that we share a common interest in identifying the parameters that impact on the performance of ChIP-seq and related assays. Indeed, it is our aim to describe in this manuscript the usefulness of the NGS QC system, which we have provided freely to the scientific community to infer optimal sequencing depth levels, in addition to providing a resource that specifies the relative performance of previously used antibodies in ChIP-seq assays on the basis of numerical quality indicators. Finally, we describe an antibody certification procedure, which can be used to assess the ChIP-seq “grade” of any existing or novel antibody batch."
}
]
}
] | 1
|
https://f1000research.com/articles/5-54
|
https://f1000research.com/articles/5-330/v1
|
11 Mar 16
|
{
"type": "Review",
"title": "Towards understanding the evolution and functional diversification of DNA-containing plant organelles",
"authors": [
"Dario Leister"
],
"abstract": "Plastids and mitochondria derive from prokaryotic symbionts that lost most of their genes after the establishment of endosymbiosis. In consequence, relatively few of the thousands of different proteins in these organelles are actually encoded there. Most are now specified by nuclear genes. The most direct way to reconstruct the evolutionary history of plastids and mitochondria is to sequence and analyze their relatively small genomes. However, understanding the functional diversification of these organelles requires the identification of their complete protein repertoires – which is the ultimate goal of organellar proteomics. In the meantime, judicious combination of proteomics-based data with analyses of nuclear genes that include interspecies comparisons and/or predictions of subcellular location is the method of choice. Such genome-wide approaches can now make use of the entire sequences of plant nuclear genomes that have emerged since 2000. Here I review the results of these attempts to reconstruct the evolution and functions of plant DNA-containing organelles, focusing in particular on data from nuclear genomes. In addition, I discuss proteomic approaches to the direct identification of organellar proteins and briefly refer to ongoing research on non-coding nuclear DNAs of organellar origin (specifically, nuclear mitochondrial DNA and nuclear plastid DNA).",
"keywords": [
"mitochondria",
"nuclear mitochondrial DNA",
"nuclear plastid DNA",
"phylogenomics",
"proteome",
"chloroplast"
],
"content": "Introduction\n\nThe progenitors of the non-nuclear DNA-containing organelles of plants – plastids and mitochondria – were originally acquired as cyanobacterial and proteobacterial endosymbionts, respectively (reviewed in 1–4). As they co-evolved with their host cells, the original endosymbionts lost most of their genetic repertoires, either definitively or through transfer to the host’s nuclear genome. In parallel, having picked up suitable signal sequences, the products of many nuclear genes of endosymbiotic origin were re-routed back to their original compartment, together with new nucleus-encoded proteins, via intracellular trafficking routes5–10. As a result, complex organellar proteomes now consist of several thousand different proteins – similar in the total number of different proteins, though less so in composition, to the proteomes of their closest prokaryotic relatives.\n\nTo reconstruct the evolutionary history of plastids and mitochondria, analysis of the coding regions of the relatively small residual organellar genomes is the most straightforward approach and has helped us to understand such post-endosymbiotic events as gene loss, nuclear transfer of organellar genes, and organelle evolution in general. Moreover, coding and non-coding organellar DNA can be used as a barcode to elucidate relationships between species11. However, to approach the diversification of the functions of organelles in a comprehensive way, ideally their entire proteomes must be identified. Since only partial organellar proteomes can be identified by proteomics, a powerful complementation (or alternative when proteomics is impracticable) is to bioinformatically analyze the corresponding complement of their nuclear genes. This is a formidable challenge and only became feasible when entire nuclear genome sequences of plant species became available. In this review, I summarize genome-wide approaches to the definition of the protein contents of organelles, as well as interspecies comparisons of entire organellar and nuclear genomes (phylogenomics) that have contributed to our understanding of the evolution of organellar proteomes. In addition, I will discuss selected proteomic analyses of organellar proteins and briefly introduce non-coding nuclear DNA sequences of organellar origin as “by-products” of organelle evolution.\n\n\nPhylogenomic approaches employing organellar DNA sequences\n\nTraditionally, plant molecular phylogenetics has involved amplifying, sequencing, and analyzing one or a few genes from many species. Alternatively, entire genomes can be sequenced and analyzed (phylogenomics), providing much larger amounts of data per taxon but often for a smaller number of species12. Nowadays, ample sequence information on DNA-containing organelles is available, i.e. the ChloroMitoSSRDB database currently provides access to 2161 organellar genomes (1982 mitochondrial and 179 chloroplast genomes)13. Because of their small size, mitochondrial and plastid genomes from different species were the first to be analyzed by phylogenomic approaches. The outcome of such interspecific comparisons turns out to be highly dependent on the sample size. This is illustrated by two pioneering studies performed 4 years apart by the same group with a view to reconstructing plastid evolution14,15. In these analyses, 9 and 15 plastid genomes, respectively, were compared, and a total of 210 and 274 different protein-coding plastid genes were identified. Of these, 45 and 44, respectively, were found in all plastid genomes in the respective set, while 44 and 117 proteins found in at least one plastid genome had nucleus-encoded counterparts in other species14,15.\n\nWhereas the first complete plastid DNA (ptDNA) sequences were published 30 years ago16,17, it took a while longer for the first two plant mitochondrial genomes to be sequenced18,19, primarily because plant mitochondrial DNAs (mtDNAs) are much larger (e.g. ~370 kbps: Arabidopsis thaliana) than animal mtDNAs20,21 or ptDNAs (e.g. ~150 kbps for A. thaliana). Because mitochondria are common to all eukaryotes, their phylogenetic and phylogenomic analysis markedly contributed to the elucidation of the deep branching order of all eukaryotes, including protist, fungal, animal, and plant lineages (reviewed by 22). However, in the mitochondria of land plants, frequent genomic rearrangements, the incorporation of foreign DNA from nuclear and chloroplast genomes, and peculiarities of gene expression – most notably RNA editing and trans-splicing – are significantly more prominent than in chloroplasts (reviewed by 23). Furthermore, the physical organization of plant mtDNAs includes a mixture of linear, circular, and branched structures, resulting from homologous recombination – which appears to be an essential characteristic of plant mitochondrial genetic processes, both in shaping and in maintaining the genome (reviewed by 24).\n\n\nEstimating organellar proteomes\n\nThe first publication predicting the size and evolutionary origin of the chloroplast proteome encoded in the (at that time incompletely sequenced) nuclear genome of the flowering plant A. thaliana identified the genes for chloroplast proteins based on the fact that their predicted products bore chloroplast transit peptides (cTPs)25 (Table 1). The study predicted between 1900 and 2500 nucleus-encoded chloroplast proteins, of which a minimum of 35% derived from the cyanobacterial ancestor. In the entire A. thaliana genome sequence, 3574 (14.0%) genes coding for chloroplast proteins were identified by a prediction program26, but the total number of cTPs obtained was not corrected for the expected numbers of false positives and negatives. Such genome-wide predictions have been repeated several times, employing different versions (with continuously improved annotation) of the Arabidopsis genome and different types or combinations of predictors (see Table 1). Interspecies comparisons of the sets of predicted chloroplast proteins have also been performed. The first such comparison published, between Arabidopsis and rice, conservatively estimated that some 2100 (A. thaliana) and 4800 (Oryza sativa) proteins carried cTPs, and defined a subset of around 900 tentative chloroplast proteins, predominantly derived from the cyanobacterial endosymbiont and with functions mostly related to metabolism, energy, and transcription, that is shared by both species27.\n\nNote that for the predictor TPpred only the total number of 3194 Arabidopsis proteins with either chloroplast transit peptides (cTP) or mitochondrial transit peptides (mTP) was reported68.\n\nAs outlined above and shown in Table 1, genome-wide cTP predictions vary markedly in their outcome, depending on the type or combination of predictors used, and their sensitivity and specificity. In fact, a detailed comparative analysis of the performance of five different predictors for subcellular targeting demonstrated a disappointingly small overlap between the outcomes of different predictions. Conversely, when all predicted proteins that had been identified by at least one of the programs were considered, far too many proteins were found to have been assigned to a specific compartment28. This clearly shows that predictive models inevitably involve a trade-off. Tightly constrained models which pinpoint only proteins that are truly located in the respective compartment (i.e. with high specificity) will fail to detect all of the proteins actually localized there (many false negatives), whereas saturated predictions that identify most of the truly located proteins (i.e. with high sensitivity) will also turn up many proteins that are actually destined for other compartments (many false positives). Moreover, a subset of chloroplast proteins does not contain cTPs, either because these proteins are inserted in the outer membrane or because they employ another ER-dependent pathway for targeting and import into chloroplasts (reviewed by 9,29) – although the latter fraction may well be quite small30.\n\nInstead of first predicting the entire set of chloroplast proteins and then analyzing their homology with proteins from other species (in particular cyanobacteria, to identify proteins derived from the original endosymbiont), one can do the reverse. In fact, a comparison of all A. thaliana proteins with those encoded in cyanobacterial genomes, other prokaryotic reference genomes, and yeast allowed its authors to extrapolate that ~4500 A. thaliana protein-coding genes had been acquired from the cyanobacterial ancestor of plastids15 and the products of some 1300 should belong to the predicted chloroplast proteome of 3100 proteins31. Since then, the identity of the ancient cyanobacterial endosymbiont that gave rise to all contemporary plastids was narrowed down to the progenitors of diazotrophic cyanobacterial lineages because the gene set possessed by their modern-day representatives shows the greatest similarity to that predicted for the plastid ancestor32.\n\nInterspecies comparisons of nuclear genomes that do not also consider the predicted subcellular location of their products do not in themselves permit reliable conclusions regarding plastid or mitochondrial functions. However, if the species to be compared are appropriately selected, indirect but important conclusions can be drawn with respect to the protein repertoires of organelles and their evolutionary diversification. An early phylogenomic study compared all protein-coding genes from only one plant species (A. thaliana) with the genes from several animals, yeasts, and combined sets of bacteria and Archaea33 and identified 3848 plant-specific proteins, of which about 27% were predicted to localize to chloroplasts or mitochondria. In 2007, the phylogenomic comparison of several photosynthetic eukaryotes with non-photosynthetic eukaryotes, cyanobacteria, non-photosynthetic eubacteria, and Archaea enabled researchers to define sets of plant proteins with plastid-associated functions without having to depend primarily on cTP predictions34. The original set, the so-called GreenCut, comprised proteins that were conserved in the green algae Chlamydomonas reinhardtii and Ostreococcus tauri, the moss Physcomitrella patens, and the flowering plant A. thaliana, but were absent from non-photosynthetic organisms, and consisted of 349 proteins in C. reinhardtii. The more restrictive PlastidCut (with 90 proteins in C. reinhardtii) was made up of GreenCut proteins which were also conserved in one diatom and one red alga species. In 2011, a revised version of this analysis (with GreenCut2 and PlastidCut2) became available, which was based on the analysis of a larger set of sequenced genomes35. To qualify for GreenCut2, a protein must (i) have orthologs in A. thaliana, P. patens, O. sativa, Populus trichocarpa, C. reinhardtii, and one of the three Ostreococcus species with fully sequenced genomes and (ii) not have orthologs in a number of bacterial, fungal, and animal species. GreenCut2 contained 597 Chlamydomonas (and 710 Arabidopsis orthologs due to gene duplications) and PlastidCut2 covers 124 proteins in C. reinhardtii. A subset (84%) of the PlastidCut2 proteins were experimentally localized to, or are predicted to be targeted to, the plastid and 52% of all GreenCut2 proteins were experimentally localized to the chloroplast, implying that the majority of GreenCut2 proteins are involved in plastid-specific functions. In line with this tentative assignment of plastid-related functions of GreenCut proteins, mutations in GreenCut2 genes were sixfold over-represented in a screen for photosynthetic mutants in C. reinhardtii which used large-scale random insertional mutagenesis36. However, it is intriguing that 6% (11%) of all PlastidCut2 (GreenCut2) proteins have been experimentally located in non-plastid sites.\n\nOf the 597 GreenCut2 proteins in C. reinhardtii, 105 were missing in at least one of the other green algae analyzed, and diatoms too display a reduced number of GreenCut2 proteins. These findings suggest that (i) adaptation of green algae to specific environmental niches leads to genome specialization and/or reduction and (ii) several core plastid functions in the green lineage are either not essential or are performed by different pathways/processes in diatoms35. In contrast, almost all GreenCut2 proteins are conserved in the other plant genomes analyzed, suggesting that the GreenCut2 proteins are especially relevant to, and representative of, all land plants of the green lineage35. The suggestion that the extent of conservation of the GreenCut2 inventory in a plant could serve as an indicator of a particular genome’s degree of specialization might be an oversimplification35 – at least when applied to plastid proteome complexity – because one must take account of the fact that plants contain multiple types of plastids, such that each variant might be of similar complexity to those from green algae. Indeed, analysis of chloroplast differentiation in maize, rice, and tomato reveals remarkably dynamic changes in plastid proteomes during plant development. For instance, to accommodate C4 photosynthesis, maize chloroplasts differentiate along the developmental axis of the leaf blade, leading from an undifferentiated leaf base into highly specialized bundle sheath (BS) and mesophyll (M) types. Hundreds of proteins detected by proteomics show differential BS/M accumulation37, displaying five developmental transitions38. Analysis of etioplast-to-chloroplast differentiation in rice by proteomics has shown that etioplast metabolism is already primed to accommodate the metabolic changes that occur during the onset of photosynthesis, such that only minor metabolic network reconstruction and modification of enzyme levels occurs during the first phase of etioplast-to-chloroplast differentiation39. During the chloroplast-to-chromoplast transition in tomato, proteomic analyses detected a strong decrease in the abundance of proteins required for the light reactions and carbohydrate metabolism, and an increase in terpenoid biosynthesis and stress-response proteins was noted40.\n\nThe first phylogenomic approach that indirectly addressed the evolution of nuclear genes for mitochondrial proteins compared the nuclear protein-coding genes from Saccharomyces cerevisiae to the ones encoded by Bacteria and Archaea and found that about 75% of all yeast nuclear genes of tentatively prokaryotic origin are more similar to eubacterial than to archaebacterial homologs41. This suggested that the common ancestor of eukaryotes may also have possessed a majority of eubacterial genes, though it is still unclear how many of these ultimately come from the ancestral mitochondrial genome. Subsequent analysis of a sample of 27 sequenced eukaryotic and 994 sequenced prokaryotic genomes identified a set of 571 genes that was presumed to be present in the common ancestor of eukaryotes, underscoring the archaebacterial (host) nature of the eukaryotic informational genes and the eubacterial (mitochondrial) nature of eukaryotic energy metabolism42. A similar type of analysis indicated that gene transfer from bacteria to eukaryotes is episodic and coincides with major evolutionary transitions at the origin of chloroplasts and mitochondria43.\n\nPlant proteomics has also contributed to our understanding of the evolution of the mitochondrial proteome. For instance, a comparison of more than 347 mitochondrial proteins identified by proteomics in Chlamydomonas, with their homologs predicted from 354 sequenced genomes, indicated that Arabidopsis is the non-algal eukaryote most closely related to C. reinhardtii and that free-living α-proteobacteria belonging to the orders Rhizobiales and Rhodobacterales better reflect the gene content of the ancestor of the chlorophyte mitochondrion than parasitic α-proteobacteria do44.\n\n\nNon-coding nuclear sequences of chloroplast or mitochondrial origin\n\nThe continuous transfer of genetic material from organelles to the nucleus can result in various outcomes with respect to the functionality of the resulting nuclear sequences (reviewed in 3,45–47): (i) rarely, but with high impact on gene evolution, functional genes are generated when the transferred open reading frame recruits appropriate elements for its expression. The product of the relocated gene can then be retargeted to its original compartment or acquire new subcellular locations and functions31; (ii) Parts of the transferred organellar DNA can remain/become functional as material for new exons in other genes48; (iii) In the vast majority of cases, the transferred organellar DNA becomes non-functional and accumulates mutations, resulting in the so-called nuclear mtDNA (NUMT) sequences (see e.g. 49–55) and nuclear ptDNA (NUPT) sequences (see e.g. 56–62). In plants, NUPTs and NUMTs can account for several hundred kbps of nuclear genomes, ranging from very small insertions to larger segments of mtDNA and/or ptDNA >100 kbps in length63, which further facilitates study of the fate of alien DNA in the nuclear genome.\n\n\nConclusions\n\nAs yet, no single prediction program and no single proteomics experiment can accurately identify the full complement of proteins located in plastids or mitochondria. At least for model plants like C. reinhardtii and A. thaliana, a combination of predictions, large-scale fluorescence tagging, epitope tagging, proteomics of multiple subfractions of organelles, and studies of individual genes/proteins will remain the method of choice for identifying entire organelle proteomes. To this end, public and searchable databases with a web-accessible interface like SUBA3 (http://suba3.plantenergy.uwa.edu.au/)64 and PPDB (http://ppdb.tc.cornell.edu/)65 are now available, which integrate the results of various prediction programs of subcellular targeting proteins with large-scale proteomic datasets from cellular compartments. It needs to be remembered, however, that in the case of plants with distinct plastid variants, prediction programs will have their limitations. Here, only proteomics can reliably discriminate the diverse proteomes in the several differentiation types of plastids.\n\nEvolutionary trees obtained by phylogenomic analyses have changed our perspective on the origin of eukaryotes by supporting hypotheses which postulate that the mitochondrial endosymbiont was acquired by an archaeon, thus placing eukaryotes within the Archaea. Therefore, phylogenomic analyses provided support for only two primary domains of life – Archaea and Bacteria – and eukaryotes arose through partnership between them (reviewed by 66). Moreover, the outcomes of phylogenomic analyses also strikingly illustrate the concept of “evolutionary tinkering”67. The nucleus can recruit novel exons even from “junk DNA” derived from plastids and mitochondria, and genes from cyanobacteria or proteobacteria now code in plants for many proteins that are not in their original compartment but have ended up elsewhere in the cell.",
"appendix": "Competing interests\n\n\n\nThe author(s) declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nZimorski V, Ku C, Martin WF, et al.: Endosymbiotic theory for organelle origins. Curr Opin Microbiol. 2014; 22: 38–48. PubMed Abstract | Publisher Full Text\n\nMartin W: Evolutionary origins of metabolic compartmentalization in eukaryotes. Philos Trans R Soc Lond B Biol Sci. 2010; 365(1541): 847–55. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKleine T, Maier UG, Leister D: DNA transfer from organelles to the nucleus: the idiosyncratic genetics of endosymbiosis. Annu Rev Plant Biol. 2009; 60: 115–38. PubMed Abstract | Publisher Full Text\n\nKeeling PJ: The number, speed, and impact of plastid endosymbioses in eukaryotic evolution. Annu Rev Plant Biol. 2013; 64: 583–607. 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}
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[
{
"id": "12867",
"date": "11 Mar 2016",
"name": "Felix Kessler",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12866",
"date": "11 Mar 2016",
"name": "William F. Martin",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12865",
"date": "11 Mar 2016",
"name": "John Allen",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
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https://f1000research.com/articles/5-330
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https://f1000research.com/articles/5-328/v1
|
11 Mar 16
|
{
"type": "Review",
"title": "Recent advances in colonoscopy",
"authors": [
"Thomas J.W. Lee",
"Shelley Nair",
"Iosif Beintaris",
"Matthew D. Rutter",
"Shelley Nair",
"Iosif Beintaris",
"Matthew D. Rutter"
],
"abstract": "Colonoscopy is an important and frequently performed procedure. It is effective in the prevention of colorectal cancer and is an important test in the investigation of many gastrointestinal symptoms. This review focuses on developments over the last 5 years that have led to changes in aspects of colonoscopy, including patient preparation, technical factors, therapeutic procedures, safety, and quality.",
"keywords": [
"Colonoscopy",
"colorectal cancer"
],
"content": "Introduction\n\nColonoscopy remains the gold-standard investigation for inspecting the mucosa of the colon for pathology such as cancer, adenomas, or inflammation. It remains preferable, in many situations, to other imaging modalities such as computed tomography (CT) colonography or barium enema due to the capacity to intervene and sample or remove pathology encountered.\n\nEmerging evidence over the last 5 years has led to important changes in the practice of colonoscopy throughout the patient journey. This review will focus on important practical developments and areas of interest. We will look at all aspects of colonoscopy, from the preparation, through the procedure and endoscopic therapy, to safety and quality assurance.\n\n\nIndications for colonoscopy\n\nColorectal cancer is the second most common cancer worldwide1. There is variation in screening practices globally2. Most screening programs employ a non-invasive test such as fecal occult blood testing to identify higher risk patients needing to undergo colonoscopy. Many screening programs are now using or moving towards using newer non-invasive tests, such as fecal immunochemical testing (FIT) or fecal DNA tests, which are associated with greater uptake and detection rates for adenomas and colorectal cancer3,4. In higher income settings, colonoscopy may be offered as the screening test. In the USA, a national survey estimated 65% of adults to be engaged with colorectal cancer screening, with colonoscopy being the most commonly used test5. Such widespread colonoscopy screening appears to be reducing colorectal cancer incidence in the USA6.\n\n\nPreparation for colonoscopy\n\nAn adequate level of bowel cleansing is critical for the efficacy of colonoscopy. Key quality indicators including cecal intubation rate and adenoma detection rate (ADR) are higher in patients with adequate bowel preparation7. Furthermore, there is an improved rate of detection of flat lesions within the proximal colon in patients with adequate bowel preparation compared to those with inadequate preparation8. Up to 1 in 5 colonoscopies are considered to have imperfect bowel preparation quality9. Inadequate bowel preparation leads to lower ADRs and more missed lesions, and results in increased costs associated with rescheduling of the colonoscopy or organization of alternative investigations10.\n\nRecent years have seen the development of bowel cleansers that are more acceptable to patients. Preparations have evolved from large-volume (7–12 L) solutions with hypertonic saline to osmotically balanced solutions containing polyethylene glycol (PEG) and electrolytes. Introduction of split-dose bowel preparation regimens, where half the dose is given the day before the test and half on the day of the test, has significantly enhanced the ability to achieve high-quality cleansing with adequate preparation achieved in 85% compared with 63% in single-dose preparations11. Split-dose regimens have resulted in improved ADRs and detection of flat lesions5. The timing between the last dose of bowel preparation and colonoscopy has been shown to correlate with the quality of bowel preparation, and ideally should be less than 4 hours12. Safety concerns have been raised regarding the use of sodium phosphate preparations and the associated risk of major fluid shift and electrolytes as well as chronic kidney disease from acute phosphate nephropathy13. These risks make it an unsuitable first-line bowel preparation agent, and careful patient selection and appropriate cautions need to be taken before its use. In patients with renal failure, PEG is now the main recommended bowel preparation.\n\nPatient education and willingness to participate in bowel preparation improves the outcome of cleansing. The delivery of both oral and written instructions for bowel preparation, as opposed to written alone, has been shown to be an independent predictor of adequate level of cleansing14.\n\nThe above evolutionary changes in bowel preparation have increased its efficacy, safety, and patient tolerability, resulting in higher quality colonoscopy.\n\nCurrent UK practice in colonoscopy is to use light conscious sedation or an unsedated approach. Maximum recommended doses of commonly used agents include midazolam (up to 5 mg) and fentanyl (up to 100 mcg) or pethidine (up to 50 mg). Unsedated colonoscopy, often using Entonox, is increasingly prevalent owing to improvements in technique. In the English Bowel Cancer Screening Program in 2014, 29.4% of colonoscopies were performed unsedated (personal correspondence, Professor M.D. Rutter). No difference in adenoma detection was observed in the unsedated group15.\n\nIn some areas of the world, deeper sedation with propofol or general anesthesia is the preferred approach, although this may not be associated with improved adenoma detection, patient experience, or cost effectiveness, and has been shown to be associated with increased risk of complications16,17.\n\n\nProcedural developments\n\nAn important objective of screening and surveillance colonoscopy is adenoma detection. Decreased incidence of post-colonoscopy colorectal cancer has been observed among colonoscopists with higher ADRs18. An important paper by Corley et al. has also demonstrated an inverse relationship between ADR and interval cancer incidence and mortality from colorectal cancer. Based on 314,872 colonoscopies performed by 136 gastroenterologists, each 1.0% increase in ADR was associated with a 3.0% decrease in the risk of colorectal cancer (hazard ratio, 0.97; 95% confidence interval, 0.96–0.98)19. The progress in understanding the importance and relevance of ADR has led to its recognition as the key performance indicator of colonoscopy and a useful tool for quality improvement, as discussed later in this paper.\n\nA number of recent advances have sought to overcome some of the barriers to adenoma detection. Regular feedback of performance indicators to colonoscopists, ideally with peer comparators, has been shown to positively affect adenoma detection20. The introduction of a simple training package and a bundle of simple maneuvers (withdrawal time >6 minutes, rectal retroversion, Buscopan use, and right lateral positioning on withdrawal) led to an increase in adenoma detection among a group of colonoscopists in the Quality Improvement in Colonoscopy (QIC) study21.\n\nNew technologies to facilitate examination of difficult-to-access mucosa are currently being evaluated, although not all studies of quality improvement have been successful. These aim to increase the exposure of mucosa behind haustral folds, rectal valves, the ileocecal valve, and at flexures. Innovations included cap-assisted colonoscopy22, the Third Eye® Retroscope®23, wider-angle colonoscopes24, and the Endocuff® device25. Improving the definition of the colonoscopy image has been shown to increase adenoma detection, particularly small and flat lesions26.\n\nChromoendoscopy is the technique of enhancing mucosal inspection using a dye applied to the mucosa. Commonly used dyes include indigo carmine and methylene blue. Dye spray chromoendoscopy has become the standard technique for colonoscopic surveillance for dysplasia in inflammatory bowel disease, increasing pathology detection and reducing unnecessary biopsies when compared to random biopsy protocols27.\n\nDye spray colonoscopy may also increase adenoma detection in routine colonoscopy, but the incremental gain in detection of diminutive lesions is offset by increased procedure time28.\n\nElectronic image processing allows “virtual chromoendoscopy” with mucosal enhancement without physical dye application. Systems such as Narrow Band Imaging (Olympus), FICE (Fujinon), and i-scan (Pentax) have made such technology widely available. These techniques are particularly useful for lesion classification but have not consistently been shown to improve adenoma detection. The NICE system and Kudo’s pit pattern can help differentiate hyperplastic lesions from neoplastic lesions and identify higher grades of dysplasia that may be associated with submucosal invasion. This has become an important tool in planning management of lesions and deciding whether a lesion is resectable endoscopically or may require a surgical approach.\n\nImproved lesion interrogation using electronic image enhancement has been proposed as an alternative to conventional polypectomy and histology. The American Society of Gastrointestinal Endoscopy (ASGE) has proposed a Preservation and Integration of Valuable endoscopic Innovations (PIVI) statement identifying criteria that a resect and discard strategy would have to meet to be acceptable for widespread use. An important driver for this strategy is the cost associated with pathological examination of small polyps which have an extremely low risk of containing advanced dysplasia. The DISCARD study demonstrated that in a single center with expert endoscopists, a resect and discard strategy accurately recognized adenomas with a sensitivity of 94% and accurately predicted appropriate surveillance strategy in 98%29.\n\n\nWater-assisted colonoscopy\n\nThe first report of a water-based colonoscopy technique was from Falchuk and colleagues in 1984, which showed that water infusion facilitates scope insertion in patients with diverticulosis30. Water-assisted colonoscopy (WAC) involves water infusion during scope insertion, instead of traditional air or CO2 insufflation. Main variations include water immersion (WI), during which water is infused to inflate the lumen during scope insertion and then aspirated during withdrawal, and water exchange (WE), where removal of infused water occurs predominantly during insertion31.\n\nRecent reports have shown that WAC, especially the WE technique, may lead to improved patient comfort with less sedation, aid in completion of difficult or previously incomplete procedures (due to angulations or redundant colons), as well as increase ADRs, the latter being a well-acknowledged predictor of interval cancer risk between colonoscopies14,32,33. Therapeutic indications of WAC have also been described, such as endoscopic resolution of sigmoid volvulus in patients with high surgical risks, as well as polypectomy34. Underwater endoscopic mucosal resection (EMR) has recently been proposed as an option in the excision of challenging lesions, such as in cases of failed conventional EMR and recurrent polyps, with promising outcomes in terms of recurrence and complication rates17,35.\n\nProlongation of cecal intubation time (CIT) is the main limitation of WAC. Some studies point to a significant prolongation, while others describe similar CIT36,37. With regard to safety, data so far show that the procedure is safe and does not interfere with patients’ fluid and electrolyte status36.\n\n\nManagement of colonic pathology\n\nEndoscopic removal of large pre-malignant or suspected early malignant gastrointestinal (GI) lesions poses a challenge in that a complete resection that allows for staging and appropriate further management is warranted in these cases.\n\nTraditionally, EMR, a technique that comprises submucosal injection of lifting solution followed by snare excision, has been used for such lesions. However, EMR is considered suboptimal for large lesions where there is an increased risk of submucosal invasion and therefore a need for a more oncologically sound, en-bloc resection that allows adequate staging. With piecemeal EMR, recurrence rates are significant (16% in a large Australian series), but recurrence is manageable endoscopically in the majority of cases38 for colorectal lesions larger than 10 mm39. The obvious need for a technique that allows for en-bloc removal of large, advanced esophagogastric and colorectal lesions recently led Japanese endoscopists to develop endoscopic submucosal dissection (ESD) as a more efficient alternative. This technique is based on the use of endoscopic knives to achieve a deep submucosal, en-bloc excision that allows for accurate histopathologic staging40. Excellent pre-excision lesion assessment is warranted based on size, morphology, and surface pattern. To justify an attempt of endoscopic resection, advanced imaging modalities, mainly high-definition and chromoendoscopy, are utilized to achieve a meticulous lesion assessment.\n\nTherapeutic indications of ESD in the colorectum include polyps that are suspicious of early neoplastic submucosal involvement as defined by endoscopic appearance (lesions with focal depression, irregular surface patterns, or poor submucosal lift), polyps larger than 2 cm, and polyps that pose difficulties to conventional EMR, such as areas of recurrence after previous polypectomy23,34.\n\nAccurate recognition of colonic lesions with submucosal invasion can be challenging, and considerable variation in proficiency has been demonstrated among western endoscopists41.\n\nIt should be stressed that ESD is a highly demanding modality in terms of endoscopist skill and requires specialized training and a certain volume of procedures to ensure competency42. Perforation is a potentially severe complication of the technique, with a risk of 6–20% in colorectal lesions43,44. Surgery is still considered the gold standard for the treatment of most lesions that also fulfill criteria for ESD, although the latter appears to be superior in terms of periprocedural morbidity and mortality when performed by experienced endoscopists23,34.\n\nDiscussion of the management options for large colonic polyps by a multidisciplinary team is recommended, as regional variation in surgical management rates has been observed in England45. Recent consensus guidelines on the management of large non-pedunculated colonic polyps have suggested a range of key performance indicators that aim to measure and improve standards of management of large polyps46. There is likely to be a variation in performance of advanced polypectomy techniques and a subsequent variation in recurrence rates (which may be associated with risk of interval cancer)47.\n\nPreviously, the majority of colorectal cancers were thought to arise from the “adenoma-carcinoma” sequence as a result of an accumulation of genetic mutations48. This process is slow, taking 10–15 years for normal mucosa to progress to malignancy, thus offering the opportunity of a long latent phase in which to detect and remove the malignant precursor (adenoma).\n\nRecent years have seen the increasing recognition and understanding of an alternative pathway for the development of colorectal cancer. This arose from the appreciation of the hyperplastic polyposis syndrome, in which multiple hyperplastic polyps are present in the colon and associated with an increased lifetime risk of colorectal cancer of 20–50%49.\n\nSerrated lesions are now thought to represent an alternative pathway to colorectal cancer through mutations in BRAF, CpG island methylation, and subsequently methylation of MLH150. Hyperplastic polyps, which are very common and occur in up to 95% of individuals, progress to sessile serrated adenomas (SSAs), of which a proportion may have cytological dysplasia. A separate, morphologically and histologically different polyp called a traditional serrated adenoma (TSA) is recognized. SSAs or TSAs can be challenging to detect at colonoscopy due to their flat appearance and relative lack of differentiation from the background mucosa. They tend to occur in the proximal colon where lesion detection is impaired by prominent haustral folds51.\n\nSerrated lesions are thought to be clinically important due to their association with the presence of synchronous advanced neoplasia52. They may also be a significant cause of advanced neoplasia or cancer detected following colonoscopy, presumably due to the increased likelihood of not being detected and subsequent rapid progression53.\n\nIncreased awareness of serrated lesions and appreciation of their subtle appearance may aid detection54. They commonly have an adherent mucosal cap, which obscures detection. Recently, an open shape pit pattern (type II-O) has been described to aid differentiation of dysplastic SSA from hyperplastic polyps; however, the clinical applicability of this is limited55.\n\n\nPost procedure management\n\nRecognized important or commonly occurring complications of colonoscopy include bleeding, colonic perforation, and those related to sedation or anesthetic use. Current estimates of the frequency of such events depend on the indication for the colonoscopy, relevant patient factors, such as comorbidity, and whether endoscopic therapy is delivered during the procedure.\n\nIn the English NHS Bowel Cancer Screening Program, the overall rate of bleeding following colonoscopy is 0.65%, bleeding requiring transfusion 0.04%, and colonic perforation 0.06%. Risk of adverse events increases if polypectomy is performed. Factors relating to the polyp, including cecal location and increasing size, are associated with increasing risk of bleeding or perforation56.\n\nEndoscopic management of bleeding and perforation, including clip placement, over-the-scope closure devices, and endoscopic suturing techniques, may reduce the need for surgical intervention following such complications57,58.\n\n\nQuality assessment\n\nMeasurement and monitoring of colonoscopy quality is central to ensuring consistently high levels of performance, patient experience and safety. A variety of key performance indicators are used to measure colonoscopic performance, the most widely used being ADR. This requires histological confirmation of polyp type and is therefore potentially time consuming. Polyp detection rate is simpler to measure and can be used as a surrogate marker59. The importance of ADR as a measure of colonoscopic performance is discussed earlier in this review.\n\nLimitations of ADR include its restriction to counting only one or more adenomas. Detection of multiple adenomas is not reflected. In patient populations with a high prevalence of adenomas, such as higher risk screening populations, measures of the total number of adenomas detected, such as mean number of adenomas per procedure, may be more appropriate13.\n\nOther technical measures of colonoscopic performance, including cecal intubation rate, complication rates, and sedation rates, are widely used. Patient-reported measures are under-represented, and a validated patient-reported experience measure for colonoscopy could improve our ability to measure and enhance patient experience.\n\nThe ability to benchmark individual or unit measures of colonoscopic performance against regional or national measures is crucial to continuous improvement in quality. The National Endoscopy Database (NED) Project in the United Kingdom and the GI Quality Improvement Consortium (GIQUiC) initiative in the USA aim to provide high-quality, large-volume data to generate individual, regional, and national metrics to aid benchmarking, drive quality improvement, and identify gaps in quality or understanding that could be improved through further research.\n\n\nConclusion\n\nColonoscopy is a commonly performed investigation. In the era of mass population screening for colorectal cancer, it is being performed more frequently than ever before. Advances in patient preparation, technical components of the procedure, and management of pathology will contribute to improvements in performance quality, safety, and ultimately patient experience.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nGLOBOCAN: Estimated cancer incidence, mortality and prevalence worldwide in 2012. 2012. Reference Source\n\nSchreuders EH, Ruco A, Rabeneck L, et al.: Colorectal cancer screening: a global overview of existing programmes. Gut. 2015; 64(10): 1637–49. PubMed Abstract | Publisher Full Text\n\nZorzi M, Fedeli U, Schievano E, et al.: Impact on colorectal cancer mortality of screening programmes based on the faecal immunochemical test. Gut. 2015; 64(5): 784–90. PubMed Abstract | Publisher Full Text | F1000 Recommendation\n\nImperiale TF, Ransohoff DF, Itzkowitz SH, et al.: Multitarget stool DNA testing for colorectal-cancer screening. N Engl J Med. 2014; 370(14): 1287–97. 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}
|
[
{
"id": "12875",
"date": "11 Mar 2016",
"name": "Rajesh N Keswani",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12876",
"date": "11 Mar 2016",
"name": "Paul C Schroy III",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-328
|
https://f1000research.com/articles/5-327/v1
|
11 Mar 16
|
{
"type": "Data Note",
"title": "A curated transcriptome dataset collection to investigate the immunobiology of HIV infection",
"authors": [
"Jana Blazkova",
"Sabri Boughorbel",
"Scott Presnell",
"Charlie Quinn",
"Damien Chaussabel",
"Sabri Boughorbel",
"Scott Presnell",
"Charlie Quinn",
"Damien Chaussabel"
],
"abstract": "Compendia of large-scale datasets available in public repositories provide an opportunity to identify and fill current gaps in biomedical knowledge. But first, these data need to be readily accessible to research investigators for interpretation. Here, we make available a collection of transcriptome datasets relevant to HIV infection. A total of 2717 unique transcriptional profiles distributed among 34 datasets were identified, retrieved from the NCBI Gene Expression Omnibus (GEO), and loaded in a custom web application, the Gene Expression Browser (GXB), designed for interactive query and visualization of integrated large-scale data. Multiple sample groupings and rank lists were created to facilitate dataset query and interpretation via this interface. Web links to customized graphical views can be generated by users and subsequently inserted in manuscripts reporting novel findings, such as discovery notes. The tool also enables browsing of a single gene across projects, which can provide new perspectives on the role of a given molecule across biological systems. This curated dataset collection is available at: http://hiv.gxbsidra.org/dm3/geneBrowser/list.",
"keywords": [
"Transcriptomics",
"Bioinformatics",
"Software",
"HIV",
"Immune Response",
"Big Data"
],
"content": "Introduction\n\nUncovering the gene transcription signature associated with different outcomes of HIV infection is paramount to a deeper understanding of HIV pathogenesis and to identifying potential therapeutic targets for improving immunological response and for eradicating HIV infection1. HIV has a complex life cycle during which it engages multiple host cellular components, including the immune cells in which it replicates, undermining immune functions. It also highjacks host transcription factors and enzymes to assure viral production and subsequent infections2. HIV dysregulates host genes resulting in aberrant immune response, disease progression, and opportunistic infections3,4. The ability to pool and analyze samples across various groups of HIV infected individuals with different disease outcomes and across various cell types or tissues, offers a unique opportunity to define common denominators of the immune control of HIV infection, the regulation of HIV replication, and/or the virus-host interaction. With this in mind, we make available, via an interactive web application, a curated collection of transcriptome datasets relevant to HIV infection.\n\nWith over 65,000 studies deposited in the NCBI Gene Expression Omnibus (GEO), a public repository of transcriptome profiles, the identification of datasets relevant to a particular research area is not straightforward. Furthermore, GEO is primarily designed as a repository for storing data, rather than for browsing and interacting with the data. Thus, we used a custom web application, the gene expression browser (GXB), to host a collection of datasets that we identified as particularly relevant to the study of the immunobiology of HIV infection. This tool has been described in detail and the source code released as part of a recent publication5. It allows seamless browsing and interactive visualization of large volumes of heterogeneous data. Users can easily customize data plots by adding multiple layers of information, modifying the sample order and generating links that capture these settings and can be inserted in email communications or in publications. Accessing the tool via these links also provides access to rich contextual information essential for data interpretation. This includes for instance access to gene information and relevant literature, study design, and detailed sample information.\n\n\nMaterial and methods\n\nPotentially relevant datasets deposited in GEO were identified using an advanced query based on the Bioconductor package GEOmetadb, version 1.30.0, and on the SQLite database that captures detailed information on GEO data structure (https://www.bioconductor.org/packages/release/bioc/html/GEOmetadb.html)6. The search query was designed to retrieve entries where the title or summary contained the word HIV, and were generated from human samples using Illumina or Affymetrix commercial platforms.\n\nThe relevance of each entry returned by this query was assessed individually. This process involved reading through the descriptions and examining the list of available samples and their annotations. Sometimes it was also necessary to review the original published report in which the design of the study and generation of the dataset are described in more details. We identified 87 datasets meeting the search criteria and containing HIV infected samples (some studies related to HIV problematics contained uninfected samples only). Out of the 87 datasets, 41 were generated from tissues or cells isolated from HIV infected individuals, 46 contained cell lines or primary cells infected in vitro. Since molecular, cellular and physiological processes involved in the context of in vivo and in vitro infections are dramatically different, we decided to create two separate collections. Here we describe the “in vivo collection” composed of 34 curated datasets (after filtering out datasets that did not meet quality control criteria, as described in “Dataset Validation” section, or datasets generated using an unsupported array platform). Of the 34 datasets, 7 are from whole blood, 7 from peripheral blood mononuclear cells (PBMCs), 8 from CD4+ and/or CD8+ T-cells, 4 from monocytes, 1 from dendritic cells (DCs), and 7 from tissues different from blood (Figure 1). Four datasets comprise samples from patients co-infected with tuberculosis (TB)7–10, one dataset comprises samples from AIDS related lymphomas11, and four datasets addressed HIV infected patients with neurological disorders, such as HIV related fatigue syndrome12, major depression disorder (MDD)13, or HIV-Associated Neurocognitive Disorder (HAND)14,15. Among the many noteworthy datasets, several stood out, such as the extensive study of the transcriptional signature of early acute HIV infection in whole blood samples of both antiretroviral-treated and untreated populations over the course of infection16 [GXB: GSE29429-GPL10558 and GSE29429-GPL6947]. Several datasets investigate differences in gene expression between distinct stages of HIV infection (early/acute, chronic)17,18 [GXB: GSE6740, GSE16363], or different host responses to infection (progressors, non-progressors, elite controllers)19–23 [GXB: GSE28128, GSE24081, GSE56837, GSE23879, GSE18233]. Other studies address different stages or responses to antiretroviral therapy24–26 [GXB: GSE44228, GSE19087, GSE52900], or transcriptional changes after therapy interruption27–29 [GXB: GSE10924, GSE28177, GSE5220]. The entirety of the datasets that makes up our collection is listed in Table 1. Thematic composition of our collection is illustrated by a graphical representation of relative occurrences of terms in the list of titles loaded into the GXB tool (Figure 2).\n\nPie charts representing the numbers of datasets (a) or transcriptome profiles (b) for different cell types and tissues.\n\nWord frequencies extracted from titles of the studies loaded into the GXB tool are depicted as a word cloud. The size of the word is proportional to its frequency.\n\nOnce a final selection had been made, each dataset was downloaded from GEO as a Simple Omnibus Format in Text (SOFT) file. It was in turn uploaded on a dedicated instance of the GXB, an interactive web application developed at the Benaroya Research Institute, hosted on the Amazon Web Services cloud. Available sample and study information were also uploaded. Samples were grouped according to possible interpretations of study results and gene rankings were computed based on different group comparisons (e.g. comparing samples form HIV negative vs HIV positive patients, with or without antiretroviral therapy, in different stages of disease progression, or with or without co-infection, depending on the focus of respective studies).\n\nThe GXB software has been described in detail in a recent publication5. This custom software interface provides users with a means to easily navigate and filter the dataset collection available at http://hiv.gxbsidra.org/dm3/geneBrowser/list. A web tutorial is also available online: https://gxb.benaroyaresearch.org/dm3/tutorials.gsp#gxbtut. Briefly, datasets of interest can be quickly identified either by filtering on criteria from pre-defined lists on the left side of the dataset navigation page, or by entering a query term in the search box at the top of the dataset navigation page. Clicking on one of the studies listed in the dataset navigation page opens a viewer designed to provide interactive browsing and graphic representations of large-scale data in an interpretable format. This interface is designed to present ranked gene lists and to display expression results graphically in a context-rich environment. Selecting a gene from the rank-ordered list on the left of the data-viewing interface will display its expression values graphically in the screen’s central panel. Directly above the graphical display, drop down menus give users the ability: a) To change the rank list by selecting different comparisons (in cases where the dataset is split in more than two groups), or to only include genes that are selected for specific biological interest. b) To change sample grouping (Group Set button); in some datasets, user can switch between interpretations where samples are grouped based on cell type or disease, for example. c) To sort individual samples within a group based on associated categorical or continuous variables (e.g. gender or age). d) To toggle between a bar plot view and a box plot view, with expression values represented as a single point for each sample. Samples are split into the same groups whether displayed as a bar plot or a box plot. e) To provide a color legend for the sample groups. f) To select categorical information to be overlaid at the bottom of the graph. For example, the user can display gender or smoking status in this manner. g) To provide a color legend for the categorical information overlaid at the bottom of the graph. h) To download the graph as a portable network graphics (png) image or the table with expression values as a comma separated values (csv) file. Measurements have no intrinsic utility in absence of contextual information. It is this contextual information that makes the results of a study or experiment interpretable. It is therefore important to capture, integrate and display information that will give users the ability to interpret data and gain new insights from it. We have organized this information under different tabs directly above the graphical display. The tabs can be hidden to make more room for displaying the data plots, or revealed by clicking on the blue “hide/show info panel” button on the top right corner of the display. Information about the gene selected from the list on the left side of the display is available under the “Gene” tab. Information about the study is available under the “Study” tab. Information available about individual samples is provided under the “Sample” tab. Rolling the mouse cursor over a bar plot, while displaying the “Sample” tab, lists any clinical, demographic, or laboratory information available for the selected sample. Finally, the “Downloads” tab allows advanced users to retrieve the original dataset for analysis outside this tool. It also provides all available sample annotation data for use alongside the expression data in third party analysis software. Other functionalities are provided under the “Tools” drop-down menu located in the top right corner of the user interface. These functionalities include notably: a) “Annotations”, which provides access to all the ancillary information about the study, samples and the dataset, organized across different tabs; b) “Cross Project View”, which provides the ability to browse across all available studies for a given gene; c) “Copy Link”, which generates a mini-URL encapsulating information about the display settings in use and that can be saved and shared with others (clicking on the envelope icon on the toolbar inserts the url in an email message via the local email client); and d) “Chart Options”, which gives user the option to customize chart labels.\n\nQuality control checks were performed by examination of profiles of relevant biological markers. Known leukocyte surface markers were used to verify consistency of the information provided by dataset depositors, and to identify instances where contamination of samples by other leukocyte populations may be confounding. The markers that were used include: CD3 (CD3D), a T-cell marker; CD4 and CD8 (CD8A), markers of CD4+ and CD8+ T cells respectively; CD11c (ITGAX), an mDC marker; CD14, expressed by monocytes and macrophages; or Adiponectin (ADIPOQ), expressed in adipose tissue. Expression of the XIST transcripts, which expression is gender-specific, was also examined in datasets containing relevant information, to determine its concordance with demographic information provided with the GEO submission (respective links in Table 1).\n\n\nData availability\n\nAll datasets included in our curated collection are also available publically via the NCBI GEO website: www.ncbi.gov/geo; and are referenced throughout the manuscript by their GEO accession numbers (e.g. GSE44228). Signal files and sample description files can also be downloaded from the GXB tool under the “downloads” tab.\n\nF1000Research: Dataset 1. Raw data for Figure 1, 10.5256/f1000research.8204.d11558139",
"appendix": "Author contributions\n\n\n\nJB and DC conceived the theme for this dataset collection. DC, SP and CQ designed the software. SP, CQ and SB installed and tested the software and programmed portions of the web application. SB uploaded datasets. JB curated and annotated datasets. JB and DC prepared the first draft of the manuscript. All authors were involved in the revision of the draft manuscript and have agreed to the final content.\n\n\nCompeting interests\n\n\n\nNo competing interests were disclosed.\n\n\nGrant information\n\nJB, SB and DC were supported by the Qatar Foundation.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe would like to thank all the investigators who decided to make their datasets publically available by depositing them in GEO.\n\n\nReferences\n\nMartin AR, Siliciano RF: Progress Toward HIV Eradication: Case Reports, Current Efforts, and the Challenges Associated with Cure. Annu Rev Med. 2016; 67: 215–28. PubMed Abstract | Publisher Full Text\n\nMoir S, Chun TW, Fauci AS: Pathogenic mechanisms of HIV disease. Annu Rev Pathol. 2011; 6: 223–48. PubMed Abstract | Publisher Full Text\n\nSauter D, Kirchhoff F: HIV replication: a game of hide and sense. Curr Opin HIV AIDS. 2016; 11(2): 173–81. PubMed Abstract | Publisher Full Text\n\nMohan T, Bhatnagar S, Gupta DL, et al.: Current understanding of HIV-1 and T-cell adaptive immunity: progress to date. Microb Pathog. 2014; 73: 60–9. PubMed Abstract | Publisher Full Text\n\nSpeake C, Presnell S, Domico K, et al.: An interactive web application for the dissemination of human systems immunology data. J Transl Med. 2015; 13: 196. PubMed Abstract | Publisher Full Text | Free Full Text\n\nZhu Y, Davis S, Stephens R, et al.: GEOmetadb: powerful alternative search engine for the Gene Expression Omnibus. Bioinformatics. 2008; 24(23): 2798–800. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLai RP, Meintjes G, Wilkinson KA, et al.: HIV-tuberculosis-associated immune reconstitution inflammatory syndrome is characterized by Toll-like receptor and inflammasome signalling. Nat Commun. 2015; 6: 8451. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDawany N, Showe LC, Kossenkov AV, et al.: Identification of a 251 gene expression signature that can accurately detect M. tuberculosis in patients with and without HIV co-infection. PLoS One. 2014; 9(2): e89925. PubMed Abstract | Publisher Full Text | Free Full Text\n\nAnderson ST, Kaforou M, Brent AJ, et al.: Diagnosis of childhood tuberculosis and host RNA expression in Africa. N Engl J Med. 2014; 370(18): 1712–23. PubMed Abstract | Publisher Full Text | Free Full Text\n\nKaforou M, Wright VJ, Oni T, et al.: Detection of tuberculosis in HIV-infected and -uninfected African adults using whole blood RNA expression signatures: a case-control study. PLoS Med. 2013; 10(10): e1001538. PubMed Abstract | Publisher Full Text | Free Full Text\n\nDeffenbacher KE, Iqbal J, Liu Z, et al.: Recurrent chromosomal alterations in molecularly classified AIDS-related lymphomas: an integrated analysis of DNA copy number and gene expression. J Acquir Immune Defic Syndr. 2010; 54(1): 18–26. PubMed Abstract\n\nVoss JG, Dobra A, Morse C, et al.: Fatigue-related gene networks identified in CD14+ cells isolated from HIV-infected patients: part II: statistical analysis. Biol Res Nurs. 2013; 15(2): 152–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTatro ET, Scott ER, Nguyen TB, et al.: Evidence for Alteration of Gene Regulatory Networks through MicroRNAs of the HIV-infected brain: novel analysis of retrospective cases. PLoS One. 2010; 5(4): e10337. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGelman BB, Chen T, Lisinicchia JG, et al.: The National NeuroAIDS Tissue Consortium brain gene array: two types of HIV-associated neurocognitive impairment. PLoS One. 2012; 7(9): e46178. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLevine AJ, Horvath S, Miller EN, et al.: Transcriptome analysis of HIV-infected peripheral blood monocytes: gene transcripts and networks associated with neurocognitive functioning. J Neuroimmunol. 2013; 265(1–2): 96–105. PubMed Abstract | Publisher Full Text | Free Full Text\n\nChang HH, Soderberg K, Skinner JA, et al.: Transcriptional network predicts viral set point during acute HIV-1 infection. J Am Med Inform Assoc. 2012; 19(6): 1103–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHyrcza MD, Kovacs C, Loutfy M, et al.: Distinct transcriptional profiles in ex vivo CD4+ and CD8+ T cells are established early in human immunodeficiency virus type 1 infection and are characterized by a chronic interferon response as well as extensive transcriptional changes in CD8+ T cells. J Virol. 2007; 81(7): 3477–86. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLi Q, Smith AJ, Schacker TW, et al.: Microarray analysis of lymphatic tissue reveals stage-specific, gene expression signatures in HIV-1 infection. J Immunol. 2009; 183(3): 1975–82. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRotger M, Dalmau J, Rauch A, et al.: Comparative transcriptomics of extreme phenotypes of human HIV-1 infection and SIV infection in sooty mangabey and rhesus macaque. J Clin Invest. 2011; 121(6): 2391–400. PubMed Abstract | Publisher Full Text | Free Full Text\n\nQuigley M, Pereyra F, Nilsson B, et al.: Transcriptional analysis of HIV-specific CD8+ T cells shows that PD-1 inhibits T cell function by upregulating BATF. Nat Med. 2010; 16(10): 1147–51. PubMed Abstract | Publisher Full Text | Free Full Text\n\nXu X, Qiu C, Zhu L, et al.: IFN-stimulated gene LY6E in monocytes regulates the CD14/TLR4 pathway but inadequately restrains the hyperactivation of monocytes during chronic HIV-1 infection. J Immunol. 2014; 193(8): 4125–36. PubMed Abstract | Publisher Full Text\n\nVigneault F, Woods M, Buzon MJ, et al.: Transcriptional profiling of CD4 T cells identifies distinct subgroups of HIV-1 elite controllers. J Virol. 2011; 85(6): 3015–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRotger M, Dang KK, Fellay J, et al.: Genome-wide mRNA expression correlates of viral control in CD4+ T-cells from HIV-1-infected individuals. PLoS Pathog. 2010; 6(2): e1000781. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMassanella M, Singhania A, Beliakova-Bethell N, et al.: Differential gene expression in HIV-infected individuals following ART. Antiviral Res. 2013; 100(2): 420–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWoelk CH, Beliakova-Bethell N, Goicoechea M, et al.: Gene expression before HAART initiation predicts HIV-infected individuals at risk of poor CD4+ T-cell recovery. AIDS. 2010; 24(2): 217–22. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWu JQ, Sassé TR, Saksena MM, et al.: Transcriptome analysis of primary monocytes from HIV-positive patients with differential responses to antiretroviral therapy. Virol J. 2013; 10: 361. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVahey MT, Wang Z, Su Z, et al.: CD4+ T-cell decline after the interruption of antiretroviral therapy in ACTG A5170 is predicted by differential expression of genes in the ras signaling pathway. AIDS Res Hum Retroviruses. 2008; 24(8): 1047–66. PubMed Abstract | Publisher Full Text | Free Full Text\n\nLerner P, Guadalupe M, Donovan R, et al.: The gut mucosal viral reservoir in HIV-infected patients is not the major source of rebound plasma viremia following interruption of highly active antiretroviral therapy. J Virol. 2011; 85(10): 4772–82. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTilton JC, Johnson AJ, Luskin MR, et al.: Diminished production of monocyte proinflammatory cytokines during human immunodeficiency virus viremia is mediated by type I interferons. J Virol. 2006; 80(23): 11486–97. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBeliakova-Bethell N, Jain S, Woelk CH, et al.: Maraviroc intensification in patients with suppressed HIV viremia has limited effects on CD4+ T cell recovery and gene expression. Antiviral Res. 2014; 107: 42–9. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSedaghat AR, German J, Teslovich TM, et al.: Chronic CD4+ T-cell activation and depletion in human immunodeficiency virus type 1 infection: type I interferon-mediated disruption of T-cell dynamics. J Virol. 2008; 82(4): 1870–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMcLaren PJ, Ball TB, Wachihi C, et al.: HIV-exposed seronegative commercial sex workers show a quiescent phenotype in the CD4+ T cell compartment and reduced expression of HIV-dependent host factors. J Infect Dis. 2010; 202(Suppl 3): S339–44. PubMed Abstract | Publisher Full Text\n\nKatz BZ, Salimi B, Gadd SL, et al.: Differential gene expression of soluble CD8+ T-cell mediated suppression of HIV replication in three older children. J Med Virol. 2011; 83(1): 24–32. PubMed Abstract | Publisher Full Text\n\nNagy LH, Grishina I, Macal M, et al.: Chronic HIV infection enhances the responsiveness of antigen presenting cells to commensal Lactobacillus. PLoS One. 2013; 8(8): e72789. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSongok EM, Luo M, Liang B, et al.: Microarray analysis of HIV resistant female sex workers reveal a gene expression signature pattern reminiscent of a lowered immune activation state. PLoS One. 2012; 7(1): e30048. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMontano M, Rarick M, Sebastiani P, et al.: Gene-expression profiling of HIV-1 infection and perinatal transmission in Botswana. Genes Immun. 2006; 7(4): 298–309. PubMed Abstract | Publisher Full Text\n\nOckenhouse CF, Bernstein WB, Wang Z, et al.: Functional genomic relationships in HIV-1 disease revealed by gene-expression profiling of primary human peripheral blood mononuclear cells. J Infect Dis. 2005; 191(12): 2064–74. PubMed Abstract | Publisher Full Text\n\nSmith AJ, Li Q, Wietgrefe SW, et al.: Host genes associated with HIV-1 replication in lymphatic tissue. J Immunol. 2010; 185(9): 5417–24. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBlazkova J, Boughorbel S, Presnell S, et al.: Dataset 1 in: A curated transcriptome dataset collection to investigate the immunobiology of HIV infection. F1000Research. 2016. Data Source"
}
|
[
{
"id": "12874",
"date": "12 Apr 2016",
"name": "Amalio Telenti",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article by Blazkova and colleagues constitutes an important contribution to the HIV field. It crystallizes the efforts of multiple groups that characterized the host transcriptional response to infection by providing a viewer of data that are not immediately accessible in a structured interface. I have assessed the performance of the tool, and found it intuitive and user-friendly.It extends efforts of my group to provide facilitated access to gnomic data in HIV disease (http://www.guavah.org/).I would bring two aspects up for discussion. First, that this tool should evolve to display RNAseq data = new generation sequencing data are increasingly available, effectively displacing microarrays. RNAseq is also easier for standardization across studies. Second, that users should be attentive to the subtleties of analysis: covariates such as gender, age, cellularity, analytical platforms and batch effects can influence expression profiles significantly. In-depth analysis may thus require downloading of original expression data.",
"responses": [
{
"c_id": "1986",
"date": "16 May 2016",
"name": "Jana Blazkova",
"role": "Author Response",
"response": "Thank you for your positive review and valuable comments.1. We are actually working on extending the supported platforms to high-throughput RNA sequencing. For now, a trial RNA-seq dataset concerning gene expression profiling of immune cell subsets across several diseases has been uploaded (GSE60424, https://gxb.benaroyaresearch.org/dm3/geneBrowser/show/396, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0109760).Concerning HIV immunobiology, we identified 13 datasets generated by high-throughput RNA sequencing, and only 2 of them (65 transcriptional profiles in total) were generated using cells from HIV infected individuals. Thus, not including the RNA-seq generated data doesn’t have a major impact on comprehensiveness of the collection so far, nevertheless, we will definitely include this platform in the future.2. We agree with the reviewer, that the covariates may have an influence on data interpretation; unfortunately, it should be noted that relevant information is not always available. In the case of batch information we estimate this number to be 5-10% of submissions. This is probably a point worth opening for discussion between GEO and community stakeholders. An advantage of relying on multiple studies however lies in the fact that independent validation can be obtained readily and outlier studies can be identified and further analyze for potential effect of another variable. It should also be noted that from within the GXB, the original expression data can be downloaded under the “Downloads” tab, as a SOFT format or series matrix data file (e.g. https://www.youtube.com/watch?v=TbMTht2Z2NU). The same dataset can also be directly accessed from GEO, in various formats (e.g. https://www.youtube.com/watch?v=O7RgeYD4SPs)."
}
]
},
{
"id": "13356",
"date": "15 Apr 2016",
"name": "Nicolas Chomont",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nIn this interesting article, Blazkova and colleagues describe the development of an interactive web application that allows HIV researchers to access a collection of transcriptome datasets relevant to HIV infection. The collection includes 34 datasets generated with human samples that have been carefully selected based on their relevance and quality control checks. This is a very useful tool that can be easily used by non-experts in transcriptomics analyses. I have used it and I am convinced that it potentially represents an important contribution to the work performed by HIV researchers. I tested the accuracy of the tool (not in a formal way) by examining differences in the expression for several genes that are well-known to be modulated by HIV infection. The results are clearly presented and can be easily exported to be included in presentations/publications. A few suggestions: I anticipate that the database will be updated on a regular basis. Therefore, it would be great to specify the date of the last update of the data set available online. Also, the possibility of adding RNAseq data would be important in the future. Maybe a brief description of each dataset would be useful too.",
"responses": [
{
"c_id": "1987",
"date": "16 May 2016",
"name": "Jana Blazkova",
"role": "Author Response",
"response": "Thank you for your positive review and helpful suggestions.1. That is a very good point, thank you for bringing it up. We will include the date of the last update on the webpage. F1000Research editors also encourage us to take advantage of the fact that their platform supports versioning. Also we will be able to update the table and list of studies as they become available. It is not clear whether this would require an additional round of review but we do not anticipate updates to be made more than once or twice yearly.2. We are working on including RNA-seq data (see answer to a similar comment made by Amalio Telenti).3. A brief description is included under the “Study” tab of each dataset (e.g. https://www.youtube.com/watch?v=Te0lggbXjIY). We envisage to set this view as a default, when opening individual studies."
}
]
},
{
"id": "12871",
"date": "20 Apr 2016",
"name": "José Alcamí Pertejo",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nBlazkova et al. describe an interactive web application that includes 34 different transcriptome datasets. This open tool facilitates access to transcriptome analysis in the HIV field allowing meta-analyses on transcriptomic changes in HIV infection.As strengths of the article I will highlight:The application is friendly and easy to use and allowed us to compare our results with a large collection of databases in a comprehensive way. The software allows searches related with a particular gene and how its expression is modified in different scenarios (infected vs non-infected, long term non-progressors vs typical progressors, treated vs untreated). The cellular types in which dataset have been obtained are indicated. Datasets included have been selected according to their interest and high methodological standards. For example, when contamination with cell types different from those initially targeted are detected the studies are not considered for the final dataset thus enhancing the quality of the results. I would propose some suggestions to improve this interesting tool:All the studies were performed with microarrays. It would be important to discuss if the inclusion of data using RNA-seq approaches and the current units used in these studies (FPKMs, RPKMs,TPMs) could be incorporated in the future. It should be clarified if the results among the different studies are normalized or just described with the units used in each study. If data normalization has been performed it would important to describe how it was done. Overall it represents an important effort that can be useful for many researchers working in the field of HIV genetics and pathogenesis.",
"responses": [
{
"c_id": "1988",
"date": "16 May 2016",
"name": "Jana Blazkova",
"role": "Author Response",
"response": "Thank you for your positive review and valuable feedback.1. We are working on including RNA-seq data (see answer to a similar comment made by Amalio Telenti).2. The data are not normalized among the different studies, but there is a normalization for individual studies. We are uploading raw or background subtracted data (based on the input in GEO), we then floor the data (give it a minimum value of 10, if it is below 10), and perform quantile normalization. In case that only normalized data are available, we present them as they are."
}
]
}
] | 1
|
https://f1000research.com/articles/5-327
|
https://f1000research.com/articles/5-317/v1
|
10 Mar 16
|
{
"type": "Research Article",
"title": "Autocrine and paracrine Wingless signalling in the Drosophila midgut by both continuous gradient and asynchronous bursts of wingless expression",
"authors": [
"Hsiao Yu Fang",
"Alfonso Martinez-Arias",
"Joaquín de Navascués",
"Hsiao Yu Fang"
],
"abstract": "Wingless (Wg)/ Wnt signalling is a major regulator of homeostasis in both the mammalian and Drosophila intestine. In Drosophila the organisation and function of Wingless signalling in the adult intestine remain poorly understood. Here we characterise the pattern of expression of wg, the stabilisation of its effector Armadillo in the adult Drosophila midgut, and correlate them with the response of the cells to Wg signalling activation. We show that in normal homeostasis there is a gradient of Wingless signalling in the intestinal stem cell (ISC) and the undifferentiated progenitor cell (enteroblast, EB) populations along the posterior midgut, with a high point at the midgut-hindgut boundary (pylorus). This gradient results from a combination of two sources of Wingless: a distant source outside the epithelium (the pylorus) and a local one from the ISCs and EBs themselves. Altogether, our studies show that Wingless expression and signalling in the epithelium is not continuous, but operates through bursts that occur randomly in space and time.",
"keywords": [
"Drosophila midgut",
"Wingless",
"Intestinal stem cells",
"Homeostasis"
],
"content": "Abbreviations\n\nApc Adenomatous polyposis coli\n\nArm Armadillo\n\nBBS Borate buffered solution\n\nEB Enteroblast\n\nEC Enterocyte\n\nEE Enteroendocrine\n\nEsg Escargot\n\nFLP Flippase\n\nFRT Flippase recognition target\n\nFz Frizzled\n\nGFP Green fluorescent protein\n\nHRP Horseradish peroxidase\n\nISC Intestinal stem cell\n\nMARCM Mosaic analysis with a repressible cell marker\n\nPros Prospero\n\nRFP Red fluorescent protein\n\nSu(H) Suppressor of hairless\n\nTA Transit amplifying\n\nTARGET Temporal and regional gene expression targeting\n\nTS Temperature sensitive\n\nTub Tubulin\n\nWg Wingless\n\n\nIntroduction\n\nThe discovery of intestinal stem cells (ISCs) in the adult Drosophila midgut established an attractive model for the study of tissue homeostasis (Micchelli & Perrimon, 2006; Ohlstein & Spradling, 2006). The Drosophila midgut displays similarities with the mammalian intestine in various aspects, such as cell composition and regulatory mechanisms (Micchelli & Perrimon, 2006; Ohlstein & Spradling, 2006). Like the mammalian intestine, the Drosophila adult midgut consists of a tubular, monolayered epithelium lining the length of the midgut, surrounded by the basement membrane and two layers of visceral muscles (Micchelli & Perrimon, 2006). The ISCs are dispersed among the differentiated cells throughout the enteric epithelium (Micchelli & Perrimon, 2006; Ohlstein & Spradling, 2006).\n\nTwo fully differentiated cells types populate the Drosophila midgut: large, polyploid enterocytes (ECs), the main absorptive cells in the epithelium, and small, diploid enteroendocrine (EEs) cells, the secretory cell type. ECs/EEs come from the differentiation of an intermediate cell type, called enteroblasts (EBs). EBs are conceptually similar to the Transit Amplifying (TA) cells in mammals, though unlike the TA cells, EBs do not divide before terminal differentiation. Lineage analysis has shown that ISCs undergo asymmetric divisions as well as symmetric self-renewal and symmetric differentiation (de Navascués et al., 2012; O'Brien et al., 2011), resulting in homeostasis by population asymmetry (de Navascués et al., 2012; Klein & Simons, 2011).\n\nWnt signalling plays an indispensable role in the regulation of mammalian ISCs. In the mammalian intestine, Wnt signalling is crucial in the maintenance of stem cell crypts (Barker et al., 2007; Barker et al., 2009; Van der Flier & Clevers, 2009; Van der Flier et al., 2007). Wingless (Wg), the Drosophila homologue of Wnt1, is expressed in the adult midgut, and Wg signalling has been shown to play a crucial role in tissue regeneration (Cordero et al., 2012). Studies have shown that stress-induced epithelial Wg production from EBs is essential for ISC proliferation during tissue renewal, but not required for midgut maintenance under homeostatic conditions (Cordero et al., 2012; Micchelli & Perrimon, 2006). However, other works reported that Wg signalling is required for ISC self-renewal: reduced proliferation and premature differentiation occur as a consequence of inhibiting downstream Wnt signalling (Lin et al., 2008). By contrast, a separate study proposed that the loss of Drosophila adenomatous polyposis coli, Apc, does not affect ISC self-renewal nor EB cell fate specification (de Navascués et al., 2012; Lee et al., 2009; Lin et al., 2008; O'Brien et al., 2011). Lee et al. (2009) showed that Apc is required for midgut homeostasis and regulates ISC proliferation, and its absence leads to midgut hyperplasia and multilayering. Moreover, a recent work indicated that Wg signalling in ECs act non-autonomously to prevent ISC proliferation (Tian et al., 2016). Thus the exact function of Wg signalling on ISC proliferation and EB differentiation remains controversial.\n\nReports have shown wg expression in the epithelium of the foregut-midgut and midgut-hindgut boundaries (pylorus) (Lee et al., 2009; Singh et al., 2011; Takashima et al., 2008; Tian et al., 2016), and also in the visceral muscle (Cordero et al., 2012; Lin et al., 2008; Tian et al., 2016). The expression of wg at the midgut boundaries may take part in regulating foregut and hindgut development (Lee et al., 2009; Singh et al., 2011; Takashima et al., 2008), though its function during adulthood is unclear. Moreover, the function of Wg emanating from the muscle has not been examined.\n\nUsing a Wg-responsive reporter transgene, frizzled3-RFP (fz3-RFP) (Olson et al., 2011), it was observed that fz3-RFP is expressed in gradients in the midgut epithelium, comprising both ISCs/ECs, and coinciding with regional boundaries (Buchon et al., 2013; Tian et al., 2016). At the pylorus, the gradient of fz3-RFP correlates with other gene expression gradients and the morphology of enterocytes, suggesting that Wg signalling activity affects gene expression and enterocyte architecture (Buchon et al., 2013; Lin et al., 2008; Micchelli & Perrimon, 2006; Ohlstein & Spradling, 2006).\n\nHere, we investigated the expression and localisation of Wg, several components of the signalling pathway, and the signalling reporter, fz3-RFP. Our results showed a Wg concentration gradient at the adult Drosophila posterior midgut, in agreement with previous reports (Tian et al., 2016). The Wg protein is produced from two sources, one at the pylorus, and the other from the epithelial cells themselves. We show that in unchallenged conditions wg is sporadically expressed within the midgut epithelium, without any apparent spatial or temporal pattern. Using the stability of Arm as an instantaneous readout of Wg signalling, we further showed that the epithelial cells respond to Wg signalling in a similarly stochastic manner. In this study, we describe in detail the expression and activity patterns of Wg signalling in the Drosophila midgut, as well as depicting the response of the midgut tissue to Wg signalling.\n\n\nResults\n\nTo observe the pattern of wg expression in the adult Drosophila posterior midgut (regions R4 and R5, (Buchon et al., 2013)), we used the Wg antibody and several wg transcriptional reporters. An enhancer trap insertion in the wg locus (wg-Gal4 > UAS-GFP) (Pfeiffer et al., 2000) coincided with the anti-Wg antibody, and revealed that wg is highly expressed at the pylorus (Figure 1A–B), in agreement with previous reports (Singh et al., 2011; Takashima et al., 2008). We did not observe Wg expression in the midgut cells adjacent to the pylorus, as recently reported (Tian et al., 2016). Our observation was further confirmed with a wg-lacZ enhancer trap insertion (wg02657), which showed a strong pyloric expression (Figure S1). To evaluate whether this Wg protein could be emanating from the pylorus, or instead came from areas of wg expression in the midgut that were not recapitulated by the enhancer trap insertions, we used wg-Gal4 to drive the expression of a GFP-tagged Wg (wg-Gal4 > UAS-GFP:wg) (Packard et al., 2002). We observed GFP:Wg accumulation at the pylorus, and a decreasing gradient from the pylorus towards the anterior end of the midgut (Figure 1C–D and Figure S2). Notably, GFP:Wg diffused from the pylorus much further into the posterior midgut than into the hindgut epithelium. Interestingly, Wg travels in the midgut tissue to a distance longer than the width of the third larval instar imaginal wing primordium, where a Wg gradient is also established (Neumann & Cohen, 1997).\n\n(A–A’) Anti-Wg (red, A; grey, A’) (B–B’) wg-Gal4, UAS-GFP (green, B; grey, B’) show high levels at the pylorus (arrowheads). (C–C’) wg-Gal4, UAS-GFP:wg (green, C; grey, C’) shows signalling gradient with high levels at the pylorus (arrowheads). (D) Intensity values of wg-Gal4, UAS-GFP:wg along thirteen parallel lines (as in the arrow in C’), averaged and smoothened with a Gaussian filter (5 µm wide) (black line). The corresponding raw data is represented in Figure S2. The limits of the grey area mark one standard deviation from the average value. (E–E’) Flies expressing only NRT-Wg showed high Wg signals (anti-Wg) (red, E; grey, E’) at the pylorus (arrowheads). EEs are marked by nuclear anti-Prospero staining (red, E; grey, E’). Scale bars: 25 μm.\n\nWe also looked at flies expressing a membrane-tethered form of Wg (NRT-Wg) from the endogenous wg locus (Alexandre et al., 2015). Anti-Wg again showed high Wg signals at the pylorus, with no obvious signalling gradient (Figure 1E,E'). These results suggest that the pylorus is the main source of Wg signal for the adult Drosophila posterior midgut, and that the Wg ligand can diffuse from this region, forming a gradient.\n\nOur results so far indicate that most of the Wg protein in the posterior midgut comes from the pylorus. However, we still detected faint Wg antibody staining in midgut areas anterior to the lowest point of the Wg gradient, and we also observed low activity of wg transcriptional reporters (Figure 1). To ascertain whether there was wg expression in the homeostatic midgut epithelium, as reported during regeneration (Cordero et al., 2012), we made use of the wg{KO; Gal4} line. In this line, the wg locus was edited to express Gal4 instead of Wg (Alexandre et al., 2015), and therefore is expected to accurately reproduce the expression of wild-type wg.\n\nTo amplify the signal of expression, wg{KO; Gal4} was crossed to UAS-Flp, act<stop<lacZ; tub-Gal80ts (wg{KO}ts>Flp, act<<lacZ). After switching to the restrictive temperature, Gal4 activates and over time all Wg-producing cells and their offspring will be strongly labelled with LacZ, even at minimal levels of wg expression. When the wg{KO}ts>Flp, act<<lacZ flies were cultured at 18°C until 13–20 days of adulthood, some background activation was detected, as scattered, individual LacZ+ cells (Figure 2A,A’) plus a field of cells in the posterior R5 region, abutting the pylorus (Figure S3A). However, after 2 days of incubation at 29°C (6–10 days old flies at dissection), the pylorus was marked with LacZ expression (Figure S3B–C), as expected, and the midgut epithelium showed more, sparse LacZ+ cells, either isolated or in pairs (Figure 2B,B’). When cultured for 8 days at 29°C (11–18 days old flies at dissection), more cells expressed lacZ in a salt and pepper pattern, with bigger groups that included polyploid ECs as well as diploid cells (Figure 2C,C’). These observations are likely the result of additional clonal induction accompanied by clonal expansion of previously labelled ISC, rather than of wg being expressed coordinately by patches of cells of multiple differentiated cell types. For the flies cultured for 8 days at 29°C, we also inspected the muscle layer of the entire posterior midgut, which showed no wg expression from the muscle cells (Figure 3). Taken together, our results indicate that under homeostatic conditions, wg is expressed intermittently and asynchronously in the Drosophila midgut epithelium, possibly in diploid cells including the ISCs.\n\n(A,A’) wg[KO]-Gal4, UAS-Flp, tub-Gal80ts, Act<stop<lacZ guts at 18°C (13–20 day old flies). (B–C’) wg[KO]-Gal4, UAS-Flp, tub-Gal80ts, Act<stop<lacZ guts after 2 days (6–10 day-old flies) or 8 days (11–18 day-old flies) of incubation at 29°C for Gal4 activation. (B,B’)Small LacZ+ (anti-βGal) (grey, B; green, B’) clusters of 1~2 cells, mostly diploid, after 2 days at 29°C. (C,C’) Larger LacZ+ (anti-βGal) (grey, C; green, C’) clusters of both diploid and polyploid cells after 8 days at 29°C. DAPI nuclear staining is shown in magenta. Inset boxes show selected regions at higher magnification. Scale bars: 50 μm. Fields of view correspond to the anterior R5 region.\n\nThe muscle layer of the wg[KO]-Gal4, UAS-Flp, tub-Gal80ts, Act<stop<lacZ gut after 8 days of incubation at 29°C for signal induction. No LacZ signals (anti-βGal, green) are detected in the muscle cells. DAPI nuclear staining is shown in magenta. Arrowhead points to the pylorus. Scale bar: 50 μm.\n\nIn order to further characterise the spatial organisation of the Wg signalling pathway in the Drosophila midgut, we observed the expression patterns of the receptor frizzled2 and the component of the destruction complex shaggy (sgg). Using a frizzled-2 enhancer trap insertion (fz2-GFP), we found that fz2-GFP was highly expressed at the pylorus (Figure 4A,A’). fz2-GFP could also be observed in diploid cells (presumably ISCs and EBs) and EEs away from the pylorus (Figure 4A’). There was no fz2-GFP expression in ECs.\n\n(A,A’) fz2-GFP (green) is expressed in the small cells and the pylorus (arrowheads). (B,B’) sgg-GFP (green) is expressed in all cell types, with strong signals at the pylorus (arrowheads). Prospero (red) marks the EEs. DAPI nuclear staining is shown in grey. Scale bars: 25 μm.\n\nTo examine the expression pattern of sgg, we used a Sgg:GFP protein trap. Sgg:GFP could be detected throughout the posterior midgut, in all cell types, with strong expression at the pylorus (Figure 4B,B’).\n\nNext we wanted to examine the activation of Wg signalling in the adult Drosophila midgut. We used a frizzled-3 (fz3) reporter to monitor Wg signalling activity, fz3-RFP, since fz3 is a direct target of the Wg pathway (Olson et al., 2011). We inspected flies expressing fz3-RFP and wg-Gal4 > UAS-GFP, which both showed high expression at the pylorus (Figure 5A,C–C’), with fz3-RFP exhibiting a signalling gradient, culminating at the pylorus (Figure 5C). fz3-RFP also displayed strong epithelial expression in the region abutting the gastric zone (Figure 5A,C’). To identify the cell types expressing fz3-RFP, we used esg-lacZ to label ISCs/EBs, and GBE-Su(H)-GFP to distinguish EBs. We observed that in the regions of the gut away from the pylorus, fz3-RFP is only expressed in ISCs and EBs (Figure 6). However, the stability of RFP in this tissue is unknown, presumably long, and therefore fz3-RFP expression could be indicative of long-past Wg pathway activation.\n\nfz3-RFP (red, A; grey, C) and wg-Gal4>UAS-GFP (green, A; grey, C’) are both highly expressed at the pylorus (arrowheads). fz3-RFP also displays epithelial expression in the region abutting the gastric zone (red, A; grey, B). (B,B’) and (C,C’) each show the region of the midgut within the dashed box above. Scale bars: 100 μm.\n\n(A) Su(H)GBE-GFP (green) labels EBs. (A’) Fz3-RFP (red) marks the cells responding to Wg signalling. (A’’) Esg-lacZ (anti-βGal, blue) labels ISCs and EBs. (A’’’) Merged. Fz3-RFP (red) is detected only in the ISCs and EBs, and all the ISCs and EBs showed fz3-RFP expression. DAPI nuclear staining is shown in grey. Inset boxes show selected regions at higher magnification. Scale bar: 50 μm.\n\nA more instantaneous reporter for Wnt signalling is the cytosolic levels of the overexpressed nuclear effector of the pathway, Armadillo/β-catenin (Alexandre et al., 2015; Hayward et al., 2005; Lin et al., 2008). When full-length armadillo (armFL) is overexpressed in the epithelium of the imaginal wing disc, Armadillo protein is only accumulated close to the domains of wg expression (Hayward et al., 2005). Arm is so rapidly degraded that its overexpression is only detected in cells where Wg signalling stabilises the protein. Therefore, the accumulation of UAS-ArmFL correlates with presently active Wg signalling. We tested whether ISCs/EBs showed stabilisation of UAS-armFL using esg-Gal4, UAS-GFP. Surprisingly, only a proportion of the GFP-expressing ISCs and EBs showed elevated levels of Arm (Arm+GFP+/GFP+ per field of view: average% = 29%, highest% = 52%, lowest% = 19%) (Figure 7 and Table S1). This suggests that Wg signalling is activated in selected ISCs and EBs only in short periods of time, without any obvious spatial pattern. This is in good agreement with our observations of wg expression, especially as reported with the “tracer amplifier”, wg{KO}ts>Flp, act<<lacZ. The results indicate that Wg production from the ISCs and EBs occurs randomly, eliciting a paracrine/autocrine response that is similarly unpatterned.\n\n(A–A’’) esg-Gal4[TS], UAS-arm, UAS-GFP intestines at 18°C show no GFP nor ArmFL induction. (B–B’’) GFP (anti-GFP, green) is detected in esg+ cells without ArmFL accumulation (anti-Arm) (grey, B; red, B’) (arrows). DAPI nuclear staining is shown in grey. Inset boxes show selected regions at higher magnification. Scale bars: 50 μm.\n\nWe also overexpressed armFL in all cells with the tub<stop<GAL4 driver, which was induced at adulthood by hs-Flp. Only a fraction of the cells, which included both differentiated and undifferentiated cells (ISCs/EBs, marked by anti-HRP), showed high levels of both cytoplasmic and nuclear Arm (Figure 8B–B’’). Arm antibody detected irregular Arm distribution at the cell membranes (Figure 8B–B’’). By contrast, uninduced tissue showed regular wild-type Arm staining at the cell membranes, with higher levels in ISCs and EBs (Figure 8A–A’’). Global arm overexpression suggests that cells in the midgut tissue respond to Wg signalling asynchronously. Also, this forced global Arm induction appeared to perturb regular Arm distribution in the midgut, and possibly disrupting cell packaging, leading to tissue dysplasia. Taken together, the adult Drosophila midgut tissue appears to respond to Wg signalling and stabilise Arm in an unpatterned way.\n\n(A–A’’) heat-shock FLP, tub<STOP<Gal4, UAS-arm without heat-shock induction of UAS-ArmFL overexpression. (B–B’’) With the tub<stop<GAL4 driver, UAS-ArmFL is induced in all cells, but only a proportion of the cells shows elevated Arm (anti-Arm, red) signals in the cytoplasm and nucleus. HRP (anti-HRP, green) labels ISCs and EBs. DAPI nuclear staining is shown in grey. Inset boxes show selected regions at higher magnification. Scale bars: 50 μm.\n\n\nDiscussion\n\nWnt signalling is the primary driving force in intestinal homeostasis and tumorigenesis in mammals. The adult Drosophila midgut is a powerful system to study intestinal homeostasis, but the role and organisation of Wg signalling in this tissue is still not well understood. We studied the expression, localisation and activity of Wg, and found that in homeostasis, Wg forms a gradient from the pylorus into the posterior midgut, and is also expressed in the diploid cells of the midgut. Moreover, midgut expression appears to be discontinuous and asynchronous, eliciting Wg immediate response in a seemingly random pattern, in turn possibly maintaining long-term expression of Wg signalling reporters.\n\nPrevious studies have suggested the visceral muscle as the main production site of Wg in the adult Drosophila midgut, which acts as a stem cell niche (Lin et al., 2008). However, a source of Wg that could comprehensively regulate the widely distributed ISC lineages throughout the midgut is unclear. Using a variety of reagents, we observed a gradient of Wg signalling across the midgut with a source of high wg expression in the epithelium of the pylorus, which agrees with previous reports (Takashima et al., 2008). However, in contrast to Lin et al. (2008) and Tian et al. (2016), we observed minimal levels of wg expression in the muscle cells using different lines and methods. It is possible that the wg expression detected in the muscle is confined to a specific region of the midgut, and that Wg is not being secreted from the entire muscle layer of the midgut, though we have not observed any area of wg expression from the visceral muscles. There might be discrepancies between the distribution of the Wg protein and the wg transcriptional reporters, which might differ in the readouts of the endogenous wg expression. This highlights the significance of the wg{KO}>Flp, act<<lacZ experiment we conducted, in which LacZ could precisely and sensitively reflect the spatial and temporal distribution of Wg. In these experiments, we were able to confirm Wg production from the midgut epithelial cells. Surprisingly, we observed sporadic LacZ+ clones composed of mainly diploid cells after a short gene induction time, while LacZ+ polyploid cells could be detected after longer gene induction. This suggests that wg is only expressed in the diploid cells including ISCs, which later give rise to polyploid ECs.\n\nUsing Wg signalling reporters, our work further showed that ISCs and EBs are the cell types responsive to Wg signalling, and that they respond in a stochastic manner. The fz3-RFP reporter seems to reveal a ‘memory’ of past Wg signalling, possibly explaining the results of Tian et al. (2016), where they saw that ISCs and EBs maintain fz3-RFP expression in the absence of Wg signalling. However, Arm stabilisation acts as a readout of the instantaneous response to Wg signalling, and this indicates that ISCs/EBs are indeed responding to Wg signalling. Depending on the stability of the fz3-RFP reporter, it is possible that the midgut epithelium only needs occasional bursts of Wg production to maintain signalling levels. Together with our findings on the sources of Wg production, these results suggest that Wg might act as both paracrine and autocrine signals in the Drosophila midgut, and the two types of signals act in a complementary manner. The paracrine Wg signals would elicit a stronger cellular response in the vicinity of the pylorus, where Wg production is high, and contribute to the spatial patterning of ECs (Buchon et al., 2013; Tian et al., 2016). On the other hand, at the regions further away from the pylorus, where paracrine Wg signalling is weak, ISCs and EBs themselves produce, in asynchronous bursts, the required Wg signals.\n\n\nMaterials and methods\n\nFlies were raised and maintained at 18, 25 or 29°C with 65–75% humidity and a 12 hour light/12 hour dark cycle on standard cornmeal/yeast medium (consisting of 1.25% agar, 10.5% dextrose, 10.5% maize, 2.1% killed yeast, and 3.5% nipagin. Supplier: Brian Drewitt, Cambridge, UK) seeded with live yeast. Stocks were obtained from the Bloomington Drosophila Resource Center unless otherwise stated. The NRT-Wg and UAS-GFP:Wg lines were provided by J. Vincent. The fz3-RFP line is from R. DasGupta. Experiments were conducted in well-fed, mated females, 3–20 days old of the following genotypes:\n\nFigure 1:\n\nOregon R.\n\n+; wg-Gal4/ CyO; UAS-GFP/ TM3, Ser\n\n+/ w; wg-Gal4/ UAS-GFP:Wg; +/ MKRS or TM6B\n\n+; NRT-wg; +\n\nFigure 2,3:\n\nw; wg{KO; Gal4}/ UAS-Flp; tub-Gal80ts/ Act<stop<lacZ\n\nFigure 4:\n\nw; +; fz2CB02997\n\nw, sggCPTI000023; +; +\n\nFigure 5:\n\nw; fz3-RFP/ wg-Gal4; UAS-GFP/ TM6B, Sb, Tb\n\nFigure 6:\n\ny, w; esg-lacZ/ fz3-RFP; Su(H)GBE-GFP/ TM6B\n\nFigure 7:\n\ny, w; esgNP7397/ +; UAS-arm/ tub-Gal80ts, UAS-GFP\n\nFigure 8:\n\ny, w, hs-FLP1.22; tub<GFP, stop<Gal4 / +; UAS-arm / +\n\nFigure S1:\n\n+; wg02657 cn1/ CyO; ry506\n\nThe following fixation methods were used: (1) Adult intestines were dissected and collected in BBS for up to 30 minutes, then fixed for 2 hours at room temperature in 4% PFA diluted in BBS. This method was used for most of the experiments. (2) Adult intestines were dissected in ice-cold “wash solution” (ddH2O + 0.7% NaCl + 0.05% Triton) for up to 15 minutes and collected within a mesh basket. The basket was submerged in a “double beaker” with wash solution at 90°C for 5 seconds, and then immediately placed in ice-cold wash solution for 2 minutes. The double beaker was prepared placing a 250 ml beaker inside a 600 ml beaker, both containing wash solution and set on a hotplate until the temperature in the 250 ml beaker reached 90°C (about 30–45 minutes). This method was used for stainings of Armadillo.\n\nAfter fixation, the tissue was rinsed three times in PBT (PBS containing 0.1% Triton X-100), then washed three times with blocking buffer (PBT containing 2% BSA and 2% FCS), each time 15 minutes on the rotator at room temperature. Primary antibody incubations were overnight at 4°C. After washing with PBT (3 × 15 minutes), secondary antibodies were incubated for 2–4 hours rotating in the dark at room temperature. DAPI (1 μg/ml) was added after the final wash.\n\nPrimary antibodies were mouse monoclonal anti-Wg (1:100, gift from J. Vincent) (Alexandre et al., 2015), goat polyclonal anti-HRP (1:500, Jackson, code number 123-001-021) (Hönigsmann et al., 1975), rabbit polyclonal anti-βGal (1:10,000, Cappel) (de Navascués et al., 2012), mouse monoclonal anti-Pros (1:200, Developmental Studies Hybridoma Bank) (de Navascués et al., 2012), mouse monoclonal anti-N27 Arm (1:20, made in the Martinez-Arias lab), chicken polyclonal anti-GFP (1:200, Abcam, ab13970) (de Navascués et al., 2012). Alexa fluorophor-conjugated secondary antibodies (1:500) were from Invitrogen: anti-mouse 568 (Catalog #A-11004, A10037), anti-rabbit 488 (Catalog #A-11034, R37118), anti-rabbit 633 (Catalog #A-21071), anti-goat A488 (Catalog #A-11055), anti-goat A633 (Catalog #A-21082), anti-chicken A488 (Catalog #A-11039). DNA dye was DAPI (Invitrogen).\n\nTissues were mounted in Vectashield and imaged on Zeiss LSM 700 confocal system using 40× objective and numerical aperture of 1.2.\n\nTo induce gene expression, the temporal and regional gene expression targeting (TARGET) method was used with the GAL4, UAS and GAL80ts elements (McGuire et al., 2004). The flies were crossed at the restrictive temperature (18°C), and then the progeny of the desired genotype was allowed to age at 18°C for 3 to 20 days post-eclosion to reach homeostatic condition. The flies were then incubated at 29°C to allow GAL4 activity, inducing the transcription of the UAS transgenes.\n\nThe heat-shock flip out system was also used to induce transgene expression (Gordon & Scott, 2009). Adult flies were raised at 25°C until they were 3–20 days old, then they were treated with heat-shock for 30 minutes in a 37°C water-bath. The hs-FLP recombinase was activated upon heat treatment, eliminating the GFP gene and the stop cassette. This activates tub-GAL4, leading to the stimulation of UAS-regulated genes.\n\nImages and figures were assembled using ImageJ (1.47v). Images are maximum intensity projections or selected, representative layers of confocal stacks. The intensity values of wg-Gal4, UAS-GFP:wg were obtained by ImageJ (1.47v) (Figure 1C’), then plotted using RStudio (0.99.491) and Adobe Illustrator CS6 (Figure 1D and Figure S2). Cell counts were conducted using the PointPicker plugin in ImageJ (1.47v) (Table S1). The cellular percentages were calculated using Microsoft Excel 2011 (Table S1).\n\n\nData availability\n\nF1000Research: Dataset 1. Raw microscopy images, 10.5256/f1000research.8170.d115432 (Fang et al., 2016a).\n\nF1000Research: Dataset 2. Raw data for the intensity values of wg-Gal4, UAS-GFP:wg (as plotted in Supplementary Figure S2), 10.5256/f1000research.8170.d115434 (Fang et al., 2016b).",
"appendix": "Author contributions\n\n\n\nAMA and JdN conceived the project. HYF performed the experiments and collected the data. HYF and JdN analysed the results and wrote the manuscript. AMA discussed the results and commented on the manuscript.\n\n\nCompeting interests\n\n\n\nThe authors declare no competing or financial interests.\n\n\nGrant information\n\nWork by AMA, HYF and JdN was partially supported by the Wellcome Trust. HYF acknowledges the Krishnan-Ang Studentship provided by Trinity College, University of Cambridge.\n\n\nAcknowledgements\n\nWe thank Jean-Paul Vincent, Ramanuj DasGupta, the Bloomington Drosophila Resource Center, and the Kyoto Drosophila Resource Center for fly stocks, and the Developmental Studies Hybridoma Bank and Jean-Paul Vincent for antibodies.\n\n\nSupplementary material\n\n(A) Nuclear β-galactosidase (green) is detected at the pylorus (arrowhead). (B) Prospero (red) identifies the EEs. HRP (magenta) marks ISCs and EBs. DAPI nuclear staining is shown in grey. Scale bar: 30 μm.\n\nIntensity values of wg-Gal4, UAS-GFP:wg (Figure 1C–C’) along thirteen parallel lines from the pylorus into the posterior midgut (example shown as arrow in Figure 1C’), of which the smoothened average is shown in Figure 1D.\n\n(A,A’) wg[KO]-Gal4, UAS-Flp, tub-Gal80ts, Act<stop<lacZ guts at 18°C (13–20 day-old flies). Note the non-specific induction at the midgut region connecting with the pylorus. (B–C’) wg[KO]-Gal4, UAS-Flp, tub-Gal80ts, Act<stop<lacZ clones after 2 (6–10 day-old flies; B,B’) or 8 days (11–18 day-old flies; C,C’) of incubation at 29°C for clonal induction. LacZ+ cells (anti-βGal, green) are detected in the pylorus (arrowheads) after induction at 29°C (B–C’), but not at 18°C (A,A’). Scale bars: 50 μm.\n\nThe percentage of esg+ cells overexpressing armFL is calculated for 5 guts (G1–G5), each with 3 fields of view (F1–F3), from the pylorus into the posterior midgut.\n\n\nReferences\n\nAlexandre C, Baena-Lopez A, Vincent JP: Patterning and growth control by membrane-tethered Wingless. Nature. 2015; 505(7482): 180–185. PubMed Abstract | Publisher Full Text\n\nBarker N, Ridgway RA, van Es JH, et al.: Crypt stem cells as the cells-of-origin of intestinal cancer. Nature. 2009; 457(7229): 608–611. PubMed Abstract | Publisher Full Text\n\nBarker N, van Es JH, Kuipers J, et al.: Identification of stem cells in small intestine and colon by marker gene Lgr5. Nature. 2007; 449(7165): 1003–1007. PubMed Abstract | Publisher Full Text\n\nBuchon N, Osman D, David FP, et al.: Morphological and molecular characterization of adult midgut compartmentalization in Drosophila. Cell Rep. 2013; 3(5): 1725–1738. PubMed Abstract | Publisher Full Text\n\nCordero JB, Stefanatos RK, Scopelliti A, et al.: Inducible progenitor-derived Wingless regulates adult midgut regeneration in Drosophila. EMBO J. 2012; 31(19): 3901–3917. PubMed Abstract | Publisher Full Text | Free Full Text\n\nde Navascués J, Perdigoto CN, Bian Y, et al.: Drosophila midgut homeostasis involves neutral competition between symmetrically dividing intestinal stem cells. EMBO J. 2012; 31(11): 2473–2485. PubMed Abstract | Publisher Full Text | Free Full Text\n\nFang HY, Martinez-Arias A, de Navascués J: Dataset 1 in: Autocrine and paracrine Wingless signalling in the Drosophila midgut by both continuous gradient and asynchronous bursts of Wingless expression. F1000Research. 2016a. Data Source\n\nFang HY, Martinez-Arias A, de Navascués J: Dataset 2 in: Autocrine and paracrine Wingless signalling in the Drosophila midgut by both continuous gradient and asynchronous bursts of Wingless expression. F1000Research. 2016b. Data Source\n\nGordon MD, Scott K: Motor control in a Drosophila taste circuit. Neuron. 2009; 61(3): 373–384. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHayward P, Brennan K, Sanders P, et al.: Notch modulates Wnt signalling by associating with Armadillo/beta-catenin and regulating its transcriptional activity. Development. 2005; 132(8): 1819–1830. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHönigsmann H, Holubar K, Wolff K, et al.: Immunochemical localization of in vivo bound immunoglobulins in pemphigus vulgaris epidermis. Employment of a peroxidase-antiperoxidase multistep technique for light and electron microscopy. Arch Dermatol Res. 1975; 254(2): 113–120. PubMed Abstract | Publisher Full Text\n\nKlein AM, Simons BD: Universal patterns of stem cell fate in cycling adult tissues. Development. 2011; 138(15): 3103–3111. PubMed Abstract | Publisher Full Text\n\nLee WC, Beebe K, Sudmeier L, et al.: Adenomatous polyposis coli regulates Drosophila intestinal stem cell proliferation. Development. 2009; 136(13): 2255–2264. PubMed Abstract | Publisher Full Text\n\nLin G, Xu N, Xi R: Paracrine Wingless signalling controls self-renewal of Drosophila intestinal stem cells. Nature. 2008; 455(7216): 1119–1123. PubMed Abstract | Publisher Full Text\n\nMcGuire SE, Mao Z, Davis RL: Spatiotemporal gene expression targeting with the TARGET and gene-switch systems in Drosophila. Sci STKE. 2004; 2004(220): pl6. PubMed Abstract | Publisher Full Text\n\nMicchelli CA, Perrimon N: Evidence that stem cells reside in the adult Drosophila midgut epithelium. Nature. 2006; 439(7075): 475–479. PubMed Abstract | Publisher Full Text\n\nNeumann CJ, Cohen SM: Long-range action of Wingless organizes the dorsal-ventral axis of the Drosophila wing. Development. 1997; 124(4): 871–880. PubMed Abstract\n\nO'Brien LE, Soliman SS, Li X, et al.: Altered modes of stem cell division drive adaptive intestinal growth. Cell. 2011; 147(3): 603–614. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOhlstein B, Spradling A: The adult Drosophila posterior midgut is maintained by pluripotent stem cells. Nature. 2006; 439(7075): 470–474. PubMed Abstract | Publisher Full Text\n\nOlson ER, Pancratov R, Chatterjee SS, et al.: Yan, an ETS-domain transcription factor, negatively modulates the Wingless pathway in the Drosophila eye. EMBO Rep. 2011; 12(10): 1047–1054. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPackard M, Koo ES, Gorczyca M, et al.: The Drosophila Wnt, Wingless, provides an essential signal for pre- and postsynaptic differentiation. Cell. 2002; 111(3): 319–330. PubMed Abstract | Publisher Full Text | Free Full Text\n\nPfeiffer S, Alexandre C, Calleja M, et al.: The progeny of Wingless-expressing cells deliver the signal at a distance in Drosophila embryos. Curr Biol. 2000; 10(6): 321–324. PubMed Abstract | Publisher Full Text\n\nSingh SR, Zeng X, Zheng Z, et al.: The adult Drosophila gastric and stomach organs are maintained by a multipotent stem cell pool at the foregut/midgut junction in the cardia (proventriculus). Cell Cycle. 2011; 10(7): 1109–1120. PubMed Abstract | Publisher Full Text | Free Full Text\n\nTakashima S, Mkrtchyan M, Younossi-Hartenstein A, et al.: The behaviour of Drosophila adult hindgut stem cells is controlled by Wnt and Hh signalling. Nature. 2008; 454(7204): 651–655. PubMed Abstract | Publisher Full Text\n\nTian A, Benchabane H, Wang Z, et al.: Regulation of Stem Cell Proliferation and Cell Fate Specification by Wingless/Wnt Signaling Gradients Enriched at Adult Intestinal Compartment Boundaries. PLoS Genet. 2016; 12(2): e1005822. PubMed Abstract | Publisher Full Text | Free Full Text\n\nVan der Flier LG, Clevers H: Stem cells, self-renewal, and differentiation in the intestinal epithelium. Annu Rev Physiol. 2009; 71: 241–260. PubMed Abstract | Publisher Full Text\n\nVan der Flier LG, Sabates-Bellver J, Oving I, et al.: The Intestinal Wnt/TCF Signature. Gastroenterology. 2007; 132(2): 628–632. PubMed Abstract | Publisher Full Text"
}
|
[
{
"id": "12861",
"date": "31 Mar 2016",
"name": "Todd Nystul",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSummary:In this study, the authors investigate the expression of Wg and the activation of Wg signaling in the Drosophila intestine. They find that wingless is expressed in the pylorus, consistent with previous studies, and also sporadically by diploid cells throughout the midgut epithelium. However, in contrast with other studies, they do not observe Wg expression in the visceral muscle. The source of wingless in the intestine has been investigated in multiple studies now and appears to be a vexing problem. The reason for the inconsistency between the studies remains unclear, but this study will contribute to the overall effort in the field to find the answer. In addition, we find their observation that Wingless signaling is activated sporadically to be an interesting and understudied aspect of wingless signaling in this tissue. Comments:Figures 1A and B show results from two methods of detecting Wg expression in the pylorus (antibody stain and Wg-Gal4 > UAS-GFP) but the differences in the presentation of the tissue in the two experiments make it difficult to compare the results. The Wg-Gal4 image is at a lower magnification and the relevant section of the tissue is not well centered in the panel. Comparable images for these two approaches should be provided. Referring to these same panels, the authors contrast their findings to those reported in Tian, et al 2016, but we cannot see any apparent contradiction between these two studies. From the images presented, it would seem that approximately 3-4 rows of cells anterior to the pylorus express wingless as detected by antibody staining (Fig 1A’ of this study) or Wg-LacZ expression (Fig 1I of Tian et al, 2016). The Wg-LacZ expression in Fig S1 of this study shows slightly more restricted expression, confined to maybe only 2 rows, but the row of lacZ+ cells in this image does not even extend across the width of the intestine (as one would expect based on the antibody stain presented in Fig 1A’), suggesting that this image is not representative of all of the wg expressing cells in this region of the tissue. More convincing images should be provided and the precise differences between the studies (if there are any) should be described in more detail. In figure 2, the observation that the frequency of clones increases between 2 and 8 days after temperature shift is interpreted as an indication that Wg is expressed intermittently, but this could also be due to the inefficiency of flippase. Even in cell populations in which flippase is expressed constitutively, all cells do not undergo FRT recombination immediately. Instead, FRT recombination seems to depend at least in part on the phase of the cell cycle as well as the stochastic nature of the reaction, resulting in an inconsistent rate of clone induction. Although other data in this study support the notion that wingless signaling is intermittent, it is important to acknowledge the caveats of this clonal induction approach.\n\nThe authors state in the discussion “in contrast to Lin et al. (2008) and Tian et al. (2016), we observed minimal levels of wg expression in the muscle cells using different lines and methods.” But the only method presented was the use of the wg-Gal4, UAS-flp system for inducing clones, which is not the same method used by these other studies. In addition, muscle cell nuclei are not visible (even by DAPI staining) in the low magnification image shown in figure 3. Moreover, there appear to be no LacZ positive clones in this tissue at all whereas the segment of intestine shown in figure 2c (also 8 days after temperature shift) has several LacZ positive clones. A much more careful analysis is required, especially because these observations appear to contradict published work. To validate the clonal labeling approach, it would be essential to (1) provide images in which the muscle cell nuclei are clearly visible and preferably stained with a muscle cell marker; (2) quantify the number of intestines analyzed and provide some description of number of muscle cells observed and where they were located in the intestine; (3) ensure that the intestines analyzed contained the expected frequency of LacZ+ clones in the epithelium, as a positive control. In addition, if the images of wg-LacZ+ muscle cell nuclei in the published studies are wrong for some reason, the authors should replicate this simple experiment (i.e. stain intestines from wg-LacZ+ flies for LacZ and obtain high magnification images of the muscle cells in the same regions of the intestine that were analyzed in these studies) and incorporate the result with their other results into a discussion of whether muscle cells do or do not express wg. What part of the gut is imaged in Figure 6? Is this still part of the posterior midgut? In the assay using overexpression of full length arm to identify cells with active wg signaling, why do some cells express arm but not GFP, such as the cell just below the inset in Fig 7B-B” and the pair of cells in the lower right corner in these same panels? In figure 8, the assumption that “UAS-armFL is induced in all cells”, as stated in the figure legend, is inaccurate. In these experiments UAS-armFL is expressed within flipout clones generated by heat-shock induction of flippase. This would result in the random labeling of a subset of cells in the tissue and a clonal marker (such as GFP) would be necessary to determine which cells were part of a clone and which were not. The authors conclude from these experiments that the midgut tissue is responding to Wg signaling in a non-uniform way, but a much more likely possibility is that the cells with elevated arm signal are part of a clone and thus expressing UAS-armFL whereas those with lower arm signal are not part of a clone. A comparison of multiple cells that are all clearly part of a UAS-armFL-expressing clone (identified by the expression of a clonal marker such as GFP) is essential for this approach. Please provide a reference or justification for the use of anti-HRP to detect ISCs and EBs",
"responses": []
},
{
"id": "15309",
"date": "08 Aug 2016",
"name": "Zhouhua Li",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nSummary:\nIt was previously shown that Wingless (Wg)/Wnt signaling is required for the proliferation and differentiation of intestinal stem cells (ISCs) during development and tissue homeostasis. In this study, the authors examine the expression pattern of Wg ligand and the activation of Wg signaling in the posterior midgut of adult Drosophila. Consistent with previous studies, they find that Wg is expressed in the pylorus, but also sporadically in the diploid cells in the midgut epithelium. For unknown reason, they do not observe Wg expression in the visceral muscles (VMs), which is different from previous reports (Lin et al., 2008; Takashima et al., 2008; Tian et al., 2016). Their observation complicates the expression pattern of Wg in adult posterior midgut. They should carefully examine Wg expression in the visceral muscles. Nevertheless, their examination of Wg expression and signaling activation in adult posterior midgut will contribute to the overall effort of understanding the function of Wnt signaling in stem cell biology and tissue homeostasis control.\nComments:\nThe panels in Figure 1 are randomly arranged. The panels should be uniformly arranged with the pylorus to the right side. Same rule should be applied for other Figure.\n\nHigher magnification of Fig. 1B is required to better compare Wg expression with Fig.1A. It is very difficult to compare between the Wg antibody staining and wg>GFP results.\n\nThe authors examine flies expressing a membrane-tethered form of Wg (NRT-Wg) using anti-Wg antibody staining, and claim that “Anti-Wg again showed high Wg signals at the pylorus, with no obvious signaling gradient (Fig. 1E)”. They do not detect the signaling activation of Wg in this experiment, thereby it should be more proper to state “with no obvious Wg protein gradient”. Furthermore, the immunofluorescent intensity of Wg staining in Fig.1E is weaker than that in Fig.1A, could the authors explain the difference?\n\nDid the authors use the wgKO-Gal4 line to drive the expression of UAS-GFP to compare whether the results they obtain is same as that of wg-Gal4>UAS-GFP? Results obtained from wgKO-Gal4 line should be more convincing as this KO line faithfully recapitulates endogenous Wg expression.\n\nThe authors do not find Wg expression in the VMs even though they use the same lines as previous studies. LacZ signal can be easily detected the VMs when wg-lacZ lines are examined. Can the authors explain why they fail to observe Wg expression in the VMs? Carefully examination of the lines they used, including wgKO-Gal4 (by UAS-GFP), is required.\n\nThe authors claim that “However, we still detected faint Wg antibody staining in midgut areas anterior to the lowest point of the Wg gradient, and we also observed low activity of wg transcriptional reporters (Figure 1)”. However, where in the posterior midgut is the so-called low activity of wg transcriptional reporters the authors are referred to in Figure 1?\n\nFlp-out system is used to detect Wg expressing cells. However, the experiment is not carried out in a strict manner. When the flies are put into the 18℃ incubator? Immediately after cross setup or at some stage after cross setup? The authors should specify it, as leaky lacZ expression is observed in flies raised in 18℃ for 13-20 days. It maybe due to the strong activity of wgKO-Gal4, or just handling problem. If it is due to the strong activity of wgKO-Gal4, the authors should observe the lacZ expression in the VMs. Moreover, it is critical to examine control flies from 18℃ at the time points of 2 days and 8 days in order to compare side-by-side to those of flies in 29℃. To further confirm that the identity of lacZ+ cells at 2 days in 29℃, it is better to perform Dl and Pros staining.\n\nIn Figure 4, it is not clear to observe a gradient of Wg signaling activation using Dfz2-GFP and sgg-GFP. Lower magnification panels should be included to show whether a gradient exists, like Figure 5.\n\nGreen signal (likely GFP) can be observed in the left side of the lower dashed box in Fig. 5A. What are those cells? Midgut epithelium or VMs or other tissue? Is it true signal? Interestingly, this signal is not observed in Fig. 5C'.\n\nIn Figure 7, why do some cell shows strong Arm staining, but no GFP signal?\n\nIn Page 7, the authors state that “Global arm overexpression suggests that cells in the midgut tissue respond to Wg signalling asynchronously. Also, this forced global Arm induction appeared to perturb regular Arm distribution in the midgut....”. This statement is inaccurate, as the authors use flp-out system to induce clones expressing uas-ArmFL in adult flies, which could only randomly result in a subset, not all, of cells expressing uas-ArmFL. Same phenomena as in Figure 7 are seen in Fig 8B, why some GFP negative cells show very high Arm signal? Closer examinations or explanations are needed.\n\nIf the authors indeed can not observe the expression of Wg in the VMs after further trials as suggested, they should explain the discrepancy in the discussion part.",
"responses": []
},
{
"id": "16248",
"date": "13 Sep 2016",
"name": "Bruce A. Edgar",
"expertise": [],
"suggestion": "Approved With Reservations",
"report": "Approved With Reservations\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThis article addresses a topic of interest (Wnt signalling in the Drosophila gut), and brings new, relevant data to an issue that has remained controversial despite numerous publications. The article is well written, includes a complete up-to-date introduction, and the data that are shown are good quality and believable. Indeed the various methods employed to assess the spatio-temporal patterns of Wnt signalling in this organ are ingenious. Interest from the field is documented by the large number of internet hits already sustained (307). Notwithstanding these strengths, the paper has some notable weaknesses that should really be addressed before it is finalized for indexing.\nFirst of all, it needs to be said that there is no data on Wnt function in this paper, and this is a limitation. Secondly, the two assays used to assess Wg activity, namely fz3-RFP expression and Arm stabilization, are not validated with the necessary controls. Although references are cited that support the accuracy of these markers, these references looked in different cell types and so controls in the gut still need to be done. The obvious controls would involve increasing or decreasing Wg expression and seeing increases or decreases in the activity reporters. Finally, the authors need to note that Wg is not the only Wnt expressed in the fly intestine, and so some of the activity patterns might be due to other ligands.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-317
|
https://f1000research.com/articles/5-314/v1
|
10 Mar 16
|
{
"type": "Review",
"title": "Ahead of the Curve: New Insights into Microtubule Dynamics",
"authors": [
"Ryoma Ohi",
"Marija Zanic"
],
"abstract": "Microtubule dynamics are fundamental for many aspects of cell physiology, but their mechanistic underpinnings remain unclear despite 40 years of intense research. In recent years, the continued union of reconstitution biochemistry, structural biology, and modeling has yielded important discoveries that deepen our understanding of microtubule dynamics. These studies, which we review here, underscore the importance of GTP hydrolysis-induced changes in tubulin structure as microtubules assemble, and highlight the fact that each aspect of microtubule behavior is the output of complex, multi-step processes. Although this body of work moves us closer to appreciating the key features of microtubule biochemistry that drive dynamic instability, the divide between our understanding of microtubules in isolation versus within the cellular milieu remains vast. Bridging this gap will serve as fertile grounds of cytoskeleton-focused research for many years to come.",
"keywords": [
"Microtubule dynamics",
"microtubule biochemistry",
"cytoskeleton"
],
"content": "Introduction\n\nMicrotubules are hollow, cylindrical polymers of αβ-tubulin that are vital for many biological processes, including cell division, polarization, and migration. In cells, microtubules are composed of 13 laterally associated protofilaments, strands of αβ-tubulin subunits lined up in a head-to-tail fashion. Key to their functional versatility is that microtubules are capable of assembling and disassembling over many cycles, as first revealed by Shinya Inoue’s seminal polarization microscopy studies of mitosis1. The dynamic nature of microtubules is intrinsic to tubulin, as microtubules formed in vitro with tubulin alone coexist as growing and shortening polymers that switch between these states2. This non-equilibrium behavior, termed dynamic instability, is in turn dependent on the ability of β-tubulin to bind and hydrolyze GTP: an αβ-tubulin heterodimer that contains GTP-β-tubulin can add on to the growing end of a microtubule, but polymerization induces GTP hydrolysis. GDP-β-tubulin is restricted to the lattice, as ends rich in GDP-β-tubulin are unstable and prone to depolymerization. These observations laid the foundation for the “GTP cap” model, which postulates that microtubules can grow only when non-hydrolyzed GTP-β-tubulin subunits crown the end of a microtubule3,4. Although GTP hydrolysis plays an indisputable role in fueling dynamic instability, structural aspects of microtubule subunit interactions—both longitudinally and laterally—ultimately lie at the heart of microtubule dynamics.\n\nWhereas the general principles of dynamic instability are well established, individual aspects of a microtubule’s life—nucleation, growth, and the growth-to-shortening transition (catastrophe)—are complex and represent the output of poorly understood multi-step processes. In this commentary, we review recent progress in the field, focusing on nucleation and microtubule assembly, where significant advances have been made. This progress reflects our improved understanding of key microtubule-associated proteins (MAPs), development of in vitro assays that probe novel aspects of microtubule assembly and disassembly, and technological breakthroughs that have increased the resolving power of cryo-electron microscopy (cryo-EM)-based structural approaches.\n\n\nNucleation\n\nFor a microtubule to form, it must first be nucleated. What does this mean in the context of microtubules? A nucleus is a multimer that forms through sequential subunit addition and allows growth to be thermodynamically favorable5. Nuclei can assemble in the absence of cellular factors and have been observed by EM to be two-dimensional sheets6,7 or short oligomers8, which presumably grow until tube closure is possible. Such spontaneous nucleation is a slow and energetically unfavorable process, involving a considerable lag phase. Importantly, cells bypass the kinetic barrier to nucleation by using factors that accelerate microtubule formation.\n\nThe best-understood microtubule nucleation factor is a protein complex that contains γ-tubulin, a protein closely related to α- and β-tubulin. The γ-tubulin ring complex (γ-TuRC) specifically templates 13-protofilament microtubules9 and participates in microtubule nucleation at microtubule-organizing centers such as the centrosome, as well as in the chromosome-mediated10–12, Golgi-mediated13,14, and microtubule-dependent15–17 microtubule nucleation pathways. The γ-TuRC fulfills the expected function of a microtubule nucleating factor; that is, microtubules form more rapidly in its presence18, and it is easy to imagine how it does so: the γ-TuRC mimics an early assembly intermediate of αβ-tubulin19. However, studies of the chromosome-mediated microtubule nucleation pathway have demonstrated that two additional MAPs—TPX220 and XMAP21521—also play key roles in facilitating microtubule nucleation22,23. In fact, these proteins can nucleate microtubules independently of the γ-TuRC23,24 when added to concentrations of tubulin at which polymer does not form. As MAPs, the γ-TuRC, TPX2, and XMAP215 have distinct biochemical properties. XMAP215, through the concerted activities of an array of tubulin-binding TOG domains, processively catalyzes microtubule assembly25, increasing microtubule growth rates up to 10-fold26. This activity depends on the ability of XMAP215 to bind tubulin subunits while retaining a grip on the microtubule plus end27. TPX2, on the other hand, has not been reported to bind tubulin subunits and therefore seems to be a conventional MAP that stabilizes and crosslinks microtubules24. On a molecular level, these findings suggest that multiple non-redundant activities can be integrated during microtubule nucleation, providing support that nucleation is a multi-step process. Interestingly, TPX2 and XMAP215 interact with proteins that co-locate their activities with the γ-TuRC at the centrosome. TPX2 binds RHAMM28, which is present in a microtubule nucleation complex that contains γ-TuRC, and NEDD1, a centrosome-targeting factor29. XMAP215 family proteins are targeted to the centrosome through direct interaction with a group of coiled-coil proteins called TACCs30. Therefore, it is likely that TPX2 and XMAP215 family proteins synergize with γ-TuRC in the context of the cell, but how they do so remains unclear.\n\nAt a molecular level, recent studies have shed light on how TPX2 and XMAP215 promote nucleation31,32. Previous in vitro work showed that TPX2 induces the formation of disordered tubulin aggregates, which were speculated to be small oligomers capable of elongation24. This finding has recently been recapitulated by the Surrey laboratory by using total internal reflection microscopy-based assays; TPX2 induces the formation of granular tubulin foci (“stubs”), which elongate in solution31. In addition, Roostalu et al. show that chTOG, the human ortholog of XMAP215, only mildly promotes microtubule nucleation31. Interestingly, this result differs from conclusions reached through previous work, where XMAP215 alone was sufficient for robust microtubule formation23. However, it is worth noting that the ability of XMAP215 to nucleate microtubules in the previous study was dependent on its conjugation to beads, an experimental setup that locally concentrates the protein. Strikingly, Roostalu et al. find that a combination of chTOG and TPX2 produces more microtubule polymer, leading to the idea that chTOG and TPX2 perform distinct functions during the nucleation process. The authors speculate that TPX2 promotes nucleation by stabilizing early oligomeric intermediates, whereas chTOG acts by accelerating subunit addition to nuclei31. chTOG activity may be crucial for oligomers to form a sheet large enough to fold into a tube. In this view, the γ-TuRC may simply act to ensure that microtubules are built using 13 protofilaments, as microtubules nucleated by TPX2 and chTOG are likely of mixed protofilament composition.\n\nWhereas nucleation de novo can easily be imagined to be a multi-step process, microtubule assembly on pre-existing templates such as axonemes is also complex, as initially demonstrated by Walker et al.33. This problem was revisited in a recent article from the Brouhard laboratory32. Wieczorek et al. found that a lag phase always precedes microtubule assembly, regardless of whether the nucleating source is a centrosome, axoneme, or a pre-formed microtubule end32. This lag phase is attenuated by TPX2 and XMAP215, or extended by catastrophe factors such as MCAK and EB1. Although the Roostalu et al. and Wieczorek et al. studies demonstrate a role for TPX2 and XMAP215 in microtubule nucleation, it is important to note that the two proteins may act differently during templated nucleation versus microtubule formation de novo. Both reports show that TPX2 is a strong anti-catastrophe factor that slows depolymerization31,32. Therefore, it is possible that TPX2 acts as a traditional MAP during templated nucleation, simply increasing a filament’s probability to extend. Mechanism aside, the picture we are left with is that the birth of a microtubule is complex, requiring the formation of a plus-end structure that is compatible with subunit addition.\n\n\nMicrotubule assembly and tubulin structure\n\nOnce formed from a nucleus, the growing microtubule will continue to elongate, sometimes for minutes at a time. Our understanding of the structure of the elongating microtubule end is shaped by early cryo-EM studies34,35. These images show that growing microtubule ends display “sheets” of interconnected protofilaments, which are thought to dynamically close into a tube as the microtubule grows. After more than 20 years, direct visualization of the structure of growing microtubule ends in real time remains an open challenge.\n\nThe highest-resolution studies of microtubule growth dynamics to date employed optical trapping methods to observe changes in microtubule length with up to 3.5 nm resolution36,37. In these experiments, microtubules were grown against barriers, such that the observed length fluctuations represent the length changes of the longest individual protofilament or group of protofilaments, and do not uncover the structure of the end. Nevertheless, these studies showed that microtubule growth is irregular with frequent shortening excursions that can retract the longest protofilaments more than 40 nm (corresponding to the length of five tubulin dimer subunits) while a microtubule remains in the overall growth phase.\n\nLarge fluctuations in polymer length observed during microtubule growth can be understood as a consequence of a very unproductive growth process38. Indeed, further studies by Gardner et al.39 found that the vast majority of tubulin subunits that associate with the growing microtubule end rapidly dissociate. The underlying cause of this high tubulin off-rate is unclear; efficient subunit incorporation into the microtubule lattice might require an additional step (for example, a structural alteration that would promote formation of stabilizing lateral bonds). The exact structure of tubulin subunits when bound to different nucleotides, both in solution as well as within the microtubule polymer, has been somewhat controversial. Whereas earlier studies proposed that GTP-tubulin is straight40–42, allowing it to readily incorporate into the microtubule lattice, more recent studies suggest that GTP-tubulin dimers are curved, similar to their hydrolyzed, GDP-bound counterparts43–45. Additionally, detailed structural changes that accompany GTP hydrolysis once a subunit is incorporated in the microtubule polymer have, until recently, been unknown.\n\nA recent study by Alushin et al.46 used high-resolution cryo-EM, combined with computational modeling, to investigate the effect of GTP-hydrolysis on the structure of tubulin dimers within the microtubule lattice. With a 5Å resolution, the authors report that GDP-bound tubulin dimers undergo longitudinal compaction close to the exchangeable nucleotide site with tubulin dimers within microtubules grown with a slowly hydrolyzable GTP-analog GMPCPP. In contrast to a previous lower-resolution EM study, performed with a different nucleotide analog (GTPyS)47, Alushin et al. found no evidence for changes in lateral interactions between the tubulin dimers. Rather, the authors hypothesize that the observed structural rearrangements in the intermediate domain and the H7 helix of α-tubulin increase lattice strain, which ultimately results in microtubule lattice destabilization. A new study by Geyer et al.48 supports the idea that structural changes associated with GTP-hydrolysis underlie microtubule instability. Here, the authors studied the polymerization dynamics of purified yeast tubulin with a mutation in helix H7 of β-tubulin (T238A), which is expected to block H7 movement upon nucleotide hydrolysis. Although the GTPase activity of these microtubules was unaffected, the mutation indeed appeared to prevent structural changes that accompany hydrolysis. Interestingly, microtubules assembled from T238A tubulin are hyperstable, suggesting that allosteric effects of GTP hydrolysis, rather than hydrolysis itself, drive microtubule instability. Future studies with additional tubulin mutants are likely to provide a more detailed link between tubulin structure and microtubule dynamics.\n\n\nMicrotubule-associated proteins recognize and modulate microtubule structure\n\nStructural features at the microtubule plus end also govern the action of MAPs. XMAP215, for example, is thought to promote microtubule assembly by tethering a weakly bound tubulin dimer to the microtubule end until it becomes stably incorporated into the microtubule lattice25. In the absence of soluble tubulin, XMAP215 is thought to convert a tightly bound subunit at the microtubule end into one that is only loosely associated. This can explain why XMAP215 can promote microtubule depolymerization49 in addition to assembly. Indeed, recent structural studies with TOG domains of Stu2, the yeast homolog of XMAP215, report that TOG domains preferably bind the curved GTP-like conformation of tubulin50. The authors propose that the TOG domain dissociates from the tubulin dimer once it straightens, a structural transition that presumably accompanies its stable incorporation into the microtubule lattice. This “hand-off” mechanism in turn allows the TOG domain to move forward and processively add the next tubulin dimer. Thus, XMAP215 is thought to bind a specific curved conformation of tubulin dimers expected to be found only at the very end of the growing microtubule.\n\nEB proteins comprise another major family of proteins known for their ability to bind growing microtubule ends. In vitro studies with nucleotide analogs established that EBs recognize the nucleotide state of tubulin dimers in the microtubule, preferentially binding to GTP-like tubulin over GDP-tubulin51,52. Interestingly, EBs discriminate between microtubules formed from two GTP mimics—GMPCPP and GTPγS—favoring the latter51. In this context, it is noteworthy that EBs form comets that lag behind the distal microtubule tip occupied by XMAP215, both in vitro and in cells53,54. It is thus speculated that GTPγS mimics GDP-Pi-tubulin, a post-GTP hydrolysis state wherein phosphate has not yet dissociated.\n\nGiven that XMAP215 and EB proteins bind different features of the growing microtubule end, it is interesting that the two proteins synergize in vitro to promote fast microtubule growth, with rates matching those previously observed only inside of cells55. This synergy is not realized through direct interaction between XMAP215 and EB1. Rather, it is due to an allosteric interaction involving the microtubule end structure. The authors hypothesized that EBs induce structural changes, such as protofilament straightening, that could in turn promote lateral protofilament interactions and sheet closure. Such EB-induced structural changes at the plus end could increase the polymerase activity of XMAP215 by accelerating subunit “hand-off”50.\n\nPrevious studies have reported that EB family proteins can affect the structure of the microtubule lattice56 as well as modulate the number of microtubule protofilaments47,57. Binding of EBs at the interface of four tubulin dimers47 could facilitate such structural effects. The latest evidence that EBs modulate the structure of the tubulin dimers in the microtubule lattice comes from a new study by the Nogales lab58. Here, the authors determined the structures of GMPCPP-, GTPγS-, and GDP-bound microtubules copolymerized with EB3 at an unprecedented resolution of 3.5Å. The authors found all three structures grown with EB3 to be compacted, similar to GDP lattice in the absence of EB3, suggesting that EB binding induces compaction of the microtubule lattice. Unfortunately, the authors were unable to obtain the structure of the GTPγS lattice in the absence of EBs, leaving open the question of whether compaction occurs prior to, or after, phosphate release. In either case, induction of lattice compaction via EBs is consistent with the view that EBs promote GTP hydrolysis in the microtubule lattice.\n\nAllosteric interactions between MAPs are not limited to XMAP215 and EB159. A recent study found similar interactions between EB1 and another TOG-domain protein, CLASP60. The authors reported that EBs have a lower binding affinity for microtubules that are grown in the presence of CLASP. The exact features encoded in the microtubule by CLASP that are recognized by EBs remain unknown. Interestingly, the CLASP TOG2 domain exhibits a strongly bent conformation, raising the possibility that CLASP is binding highly curved protofilaments at the microtubule end61. The theme of MAPs recognizing aspects of microtubule curvature is highlighted by other recent studies. Doublecortin, which preferentially binds 13-protofilament microtubules62,63, enriches on curved microtubule segments64. TPX2 was found to strongly bind curved microtubule ends31. CENP-F associates more strongly with vinblastine-generated tubulin curls compared with straight protofilaments that are found within the microtubule lattice65. Kinesin-5 has been found to associate with curved tubulin protofilaments at growing microtubule ends, where it stimulates microtubule assembly66. Lastly, kinesin-13s, the most potent catastrophe factors known, are well appreciated to recognize and stabilize a bent tubulin protofilament conformation67,68 observed on depolymerizing microtubule ends34,35.\n\n\nCatastrophe\n\nEven though the link between GTP hydrolysis, structure, and dynamics might be established, we still do not know what features define the stabilizing cap. The observations that EB end binding is largely lost well before the onset of catastrophe47,53,55 might imply that GDP-Pi subunits also confer stability to the growing end, if GTPγS tubulin dimers are indeed to be viewed as a model of GDP-Pi state. In that context, and given that EBs bind very strongly to GTPγS microtubule lattice, and much more weakly to the GDP lattice, it is interesting that the only structural difference observed between these two is a small relative rotation of tubulin dimers along a protofilament, resulting in a different lattice twist58. Whether it is this twist that ultimately leads to the high off-rate of GDP tubulin remains to be understood.\n\nWhatever the stabilizing cap looks like, its loss is a complex process intimately linked to structural features of the microtubule end. Recently, Gardner et al. reported that the probability of undergoing catastrophe grows with microtubule age69, a finding that confirms older work performed by Odde et al.70. Thus, catastrophe cannot be caused by a single-step mechanism unless catalyzed by protein factors such as kinesin-1369. The process by which microtubule aging causes catastrophes could involve changes in protofilament numbers and/or structural evolution of the growing microtubule end such as tapering and protofilament curling71–74. In any case, the fate of the microtubule is likely to be encoded in the structure of its end.\n\n\nClosing statements\n\nThe work reviewed here has significantly advanced our understanding of microtubule assembly and disassembly, but many questions remain. The complexity of the microtubule cytoskeleton in cells, difficult to capture in reconstitution-based approaches, can and should provide a useful framework for posing further questions. An interesting discrepancy concerning the relationship between microtubule end structure and dynamics, for example, is highlighted by the observation that all protofilaments are curved at the plus ends of microtubules during mitosis75. The implication of this finding is that microtubule growth in cells may be governed by different constraints that permit assembly to occur without a sheet-like intermediate that has been observed in vitro. Cell cycle-dependent variations involved in the regulation of microtubule biology are also likely to exist. Recent studies on microtubule nucleation have focused on factors that are principally active during cell division. TPX2, for example, is sequestered in the nucleus during interphase76 and requires Ran-GTP to become active during mitosis24. The factors and mechanisms that regulate microtubule nucleation during interphase remain to be elucidated. Lastly, given that most, if not all, aspects of microtubule dynamics involve multi-step processes, an important challenge will be to understand the emergent properties of the network of MAPs that synergistically modulate the kinetics of microtubule assembly and disassembly in ways relevant for cell physiology.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nWork in the laboratory of RO is supported by a grant from the National Institutes of Health (GM086610) and a Scholar Career Development Award from the Leukemia and Lymphoma Society. MZ is supported by a Career Development Award from the Human Frontier Science Program.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nAcknowledgments\n\nWe thank William Hancock, Chad Pearson, Gary Brouhard, Elizabeth Lawrence, and Marija Podolski for comments on the manuscript.\n\n\nReferences\n\nInoué S, Sato H: Cell motility by labile association of molecules. The nature of mitotic spindle fibers and their role in chromosome movement. J Gen Physiol. 1967; 50(6): Suppl: 259–292. 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}
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[
{
"id": "12842",
"date": "10 Mar 2016",
"name": "William Hancock",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12845",
"date": "10 Mar 2016",
"name": "Chad Pearson",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-314
|
https://f1000research.com/articles/5-313/v1
|
10 Mar 16
|
{
"type": "Review",
"title": "The biological significance of brain barrier mechanisms: help or hindrance in drug delivery to the central nervous system?",
"authors": [
"Norman R. Saunders",
"Mark D. Habgood",
"Kjeld Møllgård",
"Katarzyna M. Dziegielewska",
"Mark D. Habgood",
"Kjeld Møllgård",
"Katarzyna M. Dziegielewska"
],
"abstract": "Barrier mechanisms in the brain are important for its normal functioning and development. Stability of the brain’s internal environment, particularly with respect to its ionic composition, is a prerequisite for the fundamental basis of its function, namely transmission of nerve impulses. In addition, the appropriate and controlled supply of a wide range of nutrients such as glucose, amino acids, monocarboxylates, and vitamins is also essential for normal development and function. These are all cellular functions across the interfaces that separate the brain from the rest of the internal environment of the body. An essential morphological component of all but one of the barriers is the presence of specialized intercellular tight junctions between the cells comprising the interface: endothelial cells in the blood-brain barrier itself, cells of the arachnoid membrane, choroid plexus epithelial cells, and tanycytes (specialized glial cells) in the circumventricular organs. In the ependyma lining the cerebral ventricles in the adult brain, the cells are joined by gap junctions, which are not restrictive for intercellular movement of molecules. But in the developing brain, the forerunners of these cells form the neuroepithelium, which restricts exchange of all but the smallest molecules between cerebrospinal fluid and brain interstitial fluid because of the presence of strap junctions between the cells. The intercellular junctions in all these interfaces are the physical basis for their barrier properties. In the blood-brain barrier proper, this is combined with a paucity of vesicular transport that is a characteristic of other vascular beds. Without such a diffusional restrain, the cellular transport mechanisms in the barrier interfaces would be ineffective. Superimposed on these physical structures are physiological mechanisms as the cells of the interfaces contain various metabolic transporters and efflux pumps, often ATP-binding cassette (ABC) transporters, that provide an important component of the barrier functions by either preventing entry of or expelling numerous molecules including toxins, drugs, and other xenobiotics.In this review, we summarize these influx and efflux mechanisms in normal developing and adult brain, as well as indicating their likely involvement in a wide range of neuropathologies.There have been extensive attempts to overcome the barrier mechanisms that prevent the entry of many drugs of therapeutic potential into the brain. We outline those that have been tried and discuss why they may so far have been largely unsuccessful. Currently, a promising approach appears to be focal, reversible disruption of the blood-brain barrier using focused ultrasound, but more work is required to evaluate the method before it can be tried in patients. Overall, our view is that much more fundamental knowledge of barrier mechanisms and development of new experimental methods will be required before drug targeting to the brain is likely to be a successful endeavor. In addition, such studies, if applied to brain pathologies such as stroke, trauma, or multiple sclerosis, will aid in defining the contribution of brain barrier pathology to these conditions, either causative or secondary.",
"keywords": [
"Blood-brain barrier",
"cerebrospinal barrier",
"CSF-brain barrier",
"transporters",
"tight junctions",
"drug delivery"
],
"content": "Introduction\n\nThe term blood-brain barrier has a long history. Its current usage describes the structural, physiological, and molecular mechanisms that control the exchange (entry and exit) of molecules between the blood and the brain. The sum of these mechanisms results in the characteristically stable internal environment of the brain, both during development and in the adult. This has been an often confused and misunderstood field of neuroscience.\n\nThe main aim of this review is to explain what is known about brain barrier mechanisms and why understanding these mechanisms is fundamental to understanding normal brain development and normal brain function and how disorders of brain barrier mechanisms may contribute to a range of neuropathological conditions. We suggest that the neuroscience community should pay more attention to this topic and we advocate the need for new researchers to move into this intriguing and important field, as major advances in many fields have often come from an influx of new people unfettered by the prevailing dogmas.\n\nThe other focus of this review will be to consider the clinically important problem of developing ways to deliver drugs to the brain for treating neurological and psychiatric disorders. This has been a major effort in the blood-brain barrier field for the past 20–30 years but has yielded little of practical value. We list the diverse attempts that have been tried, we analyze some of the possible reasons why they have been unsuccessful, and we suggest some alternative/new approaches to the problem.\n\n\nWhat is meant by the term “blood-brain barrier”?\n\nThe use of the term “barrier” is in many ways unfortunate1, as for those outside the field it disguises the multiplicity of mechanisms involved. Perhaps this also explains the almost exclusive focus of people interested in pathological conditions involving the blood-brain barrier on tests of its integrity, largely ignoring until recently the numerous cellular mechanisms at the various blood-brain interfaces that may be disrupted. Almost all of the early work on the blood-brain barrier involved the use of dyes, which could be visualized. This field has recently been reviewed with translations from key oft-cited papers published in their original languages showing that many of the citations were incorrect2. To set the record straight, it was Lena Stern who was the first to coin the term blood-brain barrier (“barrière hémato-encéphalique”3) and not, as often cited, Ehrlich4, Lewandowsky5, or Goldmann6. The current understanding of the term “blood-brain barrier” is that it covers a number of morphological entities and a plethora of cellular transport mechanisms both inward and outward, which we next describe briefly.\n\n\nMorphology of blood-brain barrier interfaces\n\nThere are six interfaces to be considered. Figure 1 illustrates their sites and main morphological features. An essential component of all interfaces with barrier properties is the presence of specialized junctions between the cells of the interface. In most of the barriers, these junctions are tight junctions; they restrict the movement of molecules between the endothelial and the epithelial cells. As a direct consequence of this restriction, the intercellular junctions have the important functional effect of allowing the numerous transporters within individual cells to operate over the large surface of the barrier interfaces; without this permeability restriction, the inward and outward transporter mechanisms would be ineffective. In recent years, it has become increasingly apparent that there is a much greater complexity involved in the structural organization of the brain barriers; in the case of the blood-brain barrier itself, this includes astrocytes, pericytes, basement membrane, and extracellular matrix (Figure 1). However, there is much to be learned about the precise role of individual morphological components of the brain barriers and their interactions in normal and pathological brains7–10. We shall now consider each barrier interface in turn: (a) the meningeal barrier, shown in Figure 1(a), is structurally the most complex of all the brain barriers and is situated at the meninges (pia, arachnoid, and dura mater). The barrier-forming cells are the outer layer of the arachnoid membrane (the arachnoid barrier cells), which have tight junctions between adjacent cells forming a physical barrier between the outer cerebrospinal fluid (CSF) in the subarachnoid space and more superficial dural layers (dural border cells and the dura mater). The blood vessels in the subarachnoid space have tight junctions with similar barrier characteristics as cerebral blood vessels, although lacking the surrounding pericytes and astrocytic end-feet11–13. In contrast, blood vessels within the dura mater are fenestrated; other important components of the barrier are the basement membrane and glia limitans. (b) The blood-brain barrier, shown in Figure 1(b), is situated at the level of cerebral blood vessels between the lumen of the vessel and brain parenchyma. Tight junctions are present between the endothelial cells restricting permeability of the paracellular cleft (11 and Text Box). A basement membrane and extracellular matrix14 surround both the endothelial cells and the pericytes15,16. End feet from astroglial cells progressively encircle cerebral blood vessels during development17. These cellular structures are known collectively as the neurovascular unit18. (c) The blood-CSF barrier, shown in Figure 1(c), is situated in the choroid plexus within each brain ventricle. In contrast to other cerebral blood vessels, the endothelial cells forming choroid plexus blood vessels are fenestrated and do not form a barrier. The barrier-forming cells are the epithelial cells, which have tight junctions11 at their apical (CSF) side. Choroid plexus cells have microvilli on their apical side, increasing their exchange surface to the internal CSF. (d) Circumventricular organs, shown in Figure 1(d). These include the median eminence, pineal gland, area postrema, and subfornical organ. The blood vessels have permeability characteristics similar to elsewhere in the body and have the functional property of allowing feedback penetration of peptide hormones controlled by the hypothalamic-pituitary axis. These peptides and other molecules are prevented from entering the CSF by tanycytes, the specialized ependymal cells of these brain areas, connected by tight junctions between their apices; entry into the rest of the brain is prevented by tight junctions between astroglial cells19,20. (e) Ependyma in adult brain, shown in Figure 1(e). Apart from areas where there are specialized tanycytes, ependymal cells are linked by gap junctions that do not restrict exchange of even large molecules, such as proteins, between CSF and interstitial space of brain11,21. (f) The embryonic CSF-brain barrier, shown in Figure 1(f). In the ventricular zone is a temporary barrier between the CSF and brain parenchyma21. In early brain development, strap junctions are present between adjacent neuroepithelial cells; these form a physical barrier restricting the movement of larger molecules, such as proteins, but not smaller molecules22,23. At later stages of development and in the adult brain, these strap junctions are no longer present when this interface becomes ependyma.\n\nThe barrier-forming cellular layers at each interface are colored green. (a) The meningeal barrier is structurally the most complex of all the brain barriers. Barrier-forming cells are the outer layer of the arachnoid membrane (the arachnoid barrier cells [ABC]); these have tight junctions (arrowheads) between adjacent cells forming a barrier between the outer cerebrospinal fluid (o-CSF) in the subarachnoid space (SAS) and more superficial dural layers (dural border cells [DBC] and the dura mater). Blood vessels (BV) in the SAS have tight junctions with similar barrier characteristics as cerebral blood vessels without surrounding pericytes and astrocytic end-feet11–13. Blood vessels within the dura mater are fenestrated (f-BV); bm = basement membrane, gl = glia limitans. (b) The blood-brain barrier is situated at the level of cerebral blood vessels (BV). Tight junctions (tj, arrowhead) are present between the endothelial cells (EC) restricting the paracellular cleft (11 and Text Box); bm = basement membrane, PC = pericytes, AE = end feet from astroglial cells. (c) The blood-CSF barrier is situated in the choroid plexus within each brain ventricle. Barrier-forming cells are the epithelial cells (CPE), which have tight junctions11 at their apical side (CSF facing, arrowheads). Blood vessels (BV) are fenestrated and do not form a barrier (arrows); apical microvilli increase exchange surface of epithelial cells to the internal CSF (i-CSF). (d) Circumventricular organs (including median eminence, pineal gland, area postrema, subfornical organ). Blood vessels have permeability characteristics similar to elsewhere in the body and have the functional property of allowing feedback penetration of peptide hormones controlled by the hypothalamic-pituitary axis. These peptides and other molecules are prevented from entering the CSF by tanycytes (TC), the specialized ependymal cells of these brain areas, connected by tight junctions between their apices (arrowhead); entry into the rest of the brain is prevented by tight junctions between astroglial cells (GC19,20). Away from the tanycyte layer, ependymal cells lining the ventricular system are linked by gap junctions that do not hinder free exchange between the CSF and brain interstitial fluid (broken arrow). (e) Ependyma in adult brain. Apart from areas where there are specialized tanycytes, ependymal cells are linked by gap junctions that do not restrict exchange of even large molecules, such as proteins, between CSF and interstitial space of brain (solid arrows). (f) The embryonic CSF-brain barrier. In early brain development, strap junctions (open arrowheads) are present between adjacent neuroepithelial cells (NE); these form a barrier restricting the movement of larger molecules, such as proteins, but not smaller molecules.\n\n\nTransport mechanisms at barrier interfaces\n\nThis is absolutely critical for normal function of the brain. As Hugh Davson once put it (paraphrased), without this control our sensory experience would be limited to a series of flashes and bangs. The ionic composition of the interstitial fluid is usually taken to be synonymous with the composition of CSF24. This, plus the obvious practical point that it is relatively easy to sample CSF, has led to a focus on CSF and the choroid plexus in both the adult25 and the developing26 brain; however, CSF composition generally does not reflect blood-brain barrier function (see Text Box). There is a good correlation between expression levels of transporters and ionic concentrations at different ages, at least in the rat (Figure 2 and Figure 3).\n\nData for the localization of transporters and ion channels are from Damkier et al.25 and Brown et al.96. CSF secretion results from coordinated transport of ions and water from basolateral membrane to cytoplasm, then sequentially across apical membrane into ventricles25. The genes for many of these transporters and ion channels are differentially expressed in the embryo compared to the adult. This is represented in the three panels. It is emphasized that this represents differential expression, not the absence of a gene at one age (details are in 35). On the plasma-facing membrane is parallel Cl-/HCO3- exchange (AE2 [Slc4a2] > in adult and AEI [Slc4a1], AE3 [Slc4a3] > in embryo) and Na+/HCO3- co-transport (NBC1 [Slc4a4] > in embryo) with net function bringing Cl- into cells in exchange for HCO3-97. Also basolaterally located is an Na-dependent Cl-/HCO3- exchange (NCBE [Slc4a10] > in adult) that modulates pH and perhaps CSF formation98. Apical Na+ efflux by NHE5 (Slc9a5 > in embryo) and ATB1 (Atb1b1 [Na+/K+-ATPase] > in adult) maintains a low cell Na+ that sets up a favorable basolateral gradient to drive Na+ uptake99. Na+ is extruded into CSF mainly via the Na+/K+-ATPase pump (ATB1 [Atb1b1]) and, under some conditions, the Na+/K+-Cl- co-transporter NKCC1, Slc12a2 (see 100 for review). Aquaporin (AQP1/3/4) channels on CSF-facing membrane mediate water flux into ventricles101. Polarized distribution of carbonic anhydrase (CAR) and Na+/K+-ATPases, and aquaporins, enable net ion and water translocation to CSF (see 100 and 102 for reviews). CLCKA (CLCK1) is an inwardly rectifying chloride channel; its gene (Clcnka) in embryonic choroid plexus is expressed many orders of magnitude higher than in the adult. Clcnkb is expressed at a higher level in the adult. CAR2 has an intracellular distribution and is functionally important for catalyzing the equilibrium that generates H+ and HCO3-, which is an important part of the mechanism secreting CSF. There are many more channels that show age-related differential expression in choroid plexus, the functions of which are unclear26.\n\nA characteristic of CSF is its stable ionic composition that differs from that of plasma to an extent that cannot be explained by ultrafiltration, as was once thought24. Data for CSF and plasma (m-equiv/L water) are from 103 and for intracellular ions (mmol/L water) from Figure 8 in 104. The gradients are the consequence of the complex interactions between enzymes (notably carbonic anhydrase) ion transporters and ion channels, as illustrated in Figure 2. The CSF secretion rate in the embryo and newborn is much lower than in the adult105–107, which is perhaps explained by the much lower expression of carbonic anhydrase and ATPases in the developing choroid plexus.\n\nThese have been extensively studied only at the blood-brain barrier itself and at the blood-CSF barrier (choroid plexuses). A limitation of early studies with radiolabeled molecules, such as glucose and amino acids, was that it was difficult to distinguish between brain entry and incorporation of labeled molecules into metabolic pathways. This problem was solved by Oldendorf27 with his short pass technique. In general, essential amino acids were transported into the brain to a greater extent than non-essential amino acids; there was also a high uptake of D-glucose27. The molecular basis for these inward transport mechanisms has been extensively investigated using gene expression techniques to study the blood-brain barrier itself28–30 and also the choroid plexuses26,31–33. These studies have revealed a plethora of genes, particularly those classed as solute linked carriers (SLCs)34. These are summarized in Figure 4 for transporters identified in both the transcriptome and the proteome in human endothelial cells29. Some of these carriers will transport only compounds that closely resemble endogenous substrates, as they exhibit high substrate specificity (e.g. GLUT1). Many others (e.g. organic anion transporters [OATs], OAT polypeptides [OATPs], and large amino acid transporter [LAT1]) will accept a broader range of substrates; they provide a potential route of entry into the central nervous system (CNS) for exogenous compounds. Members of the OAT family of solute carriers (SLC) are known to transport a wide range of drugs, such as aspirin, ibuprofen, and various antibiotics, and pesticides (e.g. 2,4-D-dichlorophenoxyacetic acid [2,4-D]). The plant-derived neurotoxin β-N-methylamino-L-alanine (MeAA) and the drug L-DOPA both have amino acid structures that allow entry via the amino acid transporter LAT1. Some environmental toxins are also able to gain entry into the CNS by attaching themselves to an endogenous substrate to be co-transported; for example, methyl-mercury (MeHg) and lead (Pb2+) attached to cysteine enter via amino acid transporters specific for this amino acid, e.g. SLC1A5 and SLC7A10.\n\nIndividual transporters shown are ones identified in human material29. Tight junctions (tj) between adjacent cells prevent the paracellular passage of hydrophilic compounds. R-M = receptor-mediated, GLUT = glucose transporters, NTs = nucleoside transporters, AAs = amino acid transporters (includes LAT), OATP = organic anion transporting polypeptides, OAT = organic anion transporters, OCT = organic cation transporters, MCT = monocarboxylate transporters, FATP = fatty acid transport protein. Many of these transporters are solute linked carriers (SLCs). Both SLC designations and the original abbreviations are included here. SLC1A2/EAAT2, SLC1A3/EAAT1 high-affinity glutamate, SLC1A4/ASCT1 glutamate/neutral amino acids, SLC2A1/GLUT1, SLC2A3,14/GLUT3 glucose, SLC3A2/4F2hc amino acid transporter heavy chain, SLC6A12/BGT1 neurotransmitter, SLC7A1/CAT1 cationic amino acid, y+ system, SLC7A5/LAT1 amino acid light chain, L system, SLC10A1/NTCP sodium/bile acid cotransporter. SLC16A1/MCT1, SLC16A2/MCT8 monocarboxylates, SLC19A1/RFC folate, SLC22A1/OCT1 organic cations, SLC22A3/OCTN3 organic cations, SLC22A5/OCTN2 organic cation/carnitine, SLC27A1/FATP1 fatty acid, SLC29A1/ENT1 equilibrative nucleosides, SLCO2B1/OATP2B1 organic anions, SLCO1B1/OATP1B1 organic anions. Examples of receptor-mediated transporters are insulin receptor (INSR), transferrin receptor (TFR1), leptin receptor (LEPR), low-density lipoprotein receptor (LDLR), and insulin-like growth factor receptor (IGFR).\n\nMany more Slc genes have been identified in the transcriptome of mouse endothelial cells28. A large number was also identified in mouse lateral ventricular choroid plexuses33. For comparison between the two interfaces, see 34. It is striking that the expression of some Slc genes in brain barriers is much higher in the developing brain28,35; this correlates with limited information of greater transport of some labeled amino acids and glucose into the developing brain, suggesting that the high expression levels correlate with transporter function (reviewed in 36). Probably several Slcs are responsible for the transport of the same molecules, indicating a significant degree of redundancy.\n\nOf particular importance in relation to drug entry into the brain, or rather the failure of most drugs to enter the brain, are the ABC efflux transporters37,38. There are 49 members of the ABC protein superfamily (http://nutrigene.4t.com/humanabc.htm). Many of these are efflux transporters. At the blood-brain barrier interface (Figure 5), the efflux transporters that have been shown to be expressed and present and appear to be of particular functional importance are ABCB1 (also known as P-glycoprotein [PGP] or MDR1) and ABCG2 (breast cancer resistance protein [BCRP]). ABCC2 (multidrug resistance protein 2 [MRP2]) and ABCC4 (MRP4) have also been demonstrated at this interface39. At the blood-CSF interface (Figure 5), ABCC1 (multidrug resistance protein 1 [MRP1]) appears to be the predominant efflux transporter, but ABCC4 (MRP4) and ABCG2 (BCRP) have also been shown to be present39,40. In cerebral capillary endothelial cells (blood-brain barrier), PGP41–43, BCRP44,45, MRP246, MRP446, and MRP547 are localized to the luminal membrane, where they export compounds into the blood. In choroid plexus epithelial cells (blood-CSF barrier), MRP1, MRP4, and BCRP are localized to the basolateral membranes where they export compounds into the stroma of the plexus40,48,49. The subcellular localization of PGP in choroid plexus is not clear. Some studies report staining too low to be able to determine localization40,48 or positive staining, but localization was not able to be determined50,51. Other studies report cytosolic52 or subapical localization42. One study has reported apical membrane localization in cultured choroid plexus epithelial cells53. A common feature of these outwardly directed efflux transporters is a broad substrate specificity and considerable overlap between transporters (see 54). PGP is unusual in that it intercepts lipid-soluble compounds (red symbols, Figure 5) as they pass through the internal leaflet of the plasma membrane and returns them to the extracellular fluid55, whereas BCRP and the MRPs bind their substrates from within the cell cytoplasm. Compounds can be exported from the cell by one or more of these efflux pathways. For example, a lipid-soluble compound that manages to avoid interception by PGP as it passes into the cell may then be metabolized by phase I enzymes (e.g. cytochrome P450 oxidases), conjugated by phase II enzymes (sulfotransferases [SULTs], uridine-diphospho-glucuronosyltransferase [UGT], or glutathione S-transferase [GST]), and exported by BCRP and/or MRP.\n\nThe main efflux transporters at the blood-brain and blood-CSF interfaces are P-glycoprotein (PGP, MDR1, ABCB1), breast cancer resistance protein (BCRP, ABCG2), and several members of the multidrug resistance protein subfamily (MRP1 ABCC1, MRP2 ABCC2, MRP4 ABCC4, MRP5 ABCC5). In cerebral capillary endothelial cells (blood-brain barrier), PGP41–43, BCRP44,45, MRP246, MRP446, and MRP547 are localized to the luminal membrane where they export compounds into the blood. In choroid plexus epithelial cells (blood-CSF barrier), MRP1, MRP4, and BCRP are localized to the basolateral membranes where they export compounds into the stroma of the plexus40,48,49. The subcellular localization of PGP in choroid plexus is not clear. Some studies report staining too low to be able to determine localization40,48 or positive staining, but localization was not able to be determined50,51. Other studies report cytosolic52 or subapical localization42. One study has reported apical membrane localization in cultured choroid plexus epithelial cells53. A common feature of these outwardly directed efflux transporters is a broad substrate specificity and considerable overlap between transporters (see 54). PGP is unusual in that it intercepts lipid-soluble compounds (red symbols) as they pass through the internal leaflet of the plasma membrane and returns them to the extracellular fluid55, whereas BCRP and the MRPs bind their substrates from within the cell cytoplasm. Compounds can be exported from the cell by one or more of these efflux pathways. For example, a lipid-soluble compound that manages to avoid interception by PGP as it passes into the cell may then be metabolized by phase I enzymes (e.g. cytochrome P450 oxidases), conjugated by phase II enzymes (sulfotransferases [SULTs], uridine-diphospho-glucuronosyltransferase [UGT], or glutathione S-transferase [GST]), and exported by BCRP and/or MRP.\n\nThere are probably species differences in the level of expression and function of these various efflux transporters, and it is known that their expression changes with age during brain development at both interfaces28,35,40,56,57. No doubt with further studies other members of this large group of transporters will be found to be functional at one or more of the brain barrier interfaces. ABC transporters that have been identified at different brain barriers are shown in Figure 5, together with an indication of differences in mechanisms of their function.\n\n\nSome dogmas and controversies\n\n\n\n\nDrug targeting to the central nervous system\n\nThis has been a major field of endeavor over the past 20–30 years. It has been largely unsuccessful in that few of the proposed methods appear to have been independently replicated, and we are not aware of any neuropharmaceutical drugs that have been identified using these methods. There are several comprehensive reviews of the methods that have been developed58–60. Here, we provide only a list of these methods (Table 1), with some observations on their limitations. We deal in more detail with methods designed to allow entry of drugs into the brain by disruption of the blood-brain barrier. This is the only method of drug delivery that has translated to clinical practice, albeit on a limited basis. Newer, more focal methods hold promise of significant advances using this approach.\n\nThe following drug delivery approaches have been tried:\n\n(i) In vitro blood-brain or blood-CSF barrier models (see reviews in 61–64)\n\nThe hallmarks of success of such systems are generally held to be a high transendothelial resistance (TEER) and limited permeability to barrier integrity markers such as 14C-sucrose64. The only in vivo TEER values that have been measured are for pial blood vessels65. It is unclear whether these reflect the properties of vessels within the brain. The type of endothelial cells isolated in preparation of the cultures is often not clear66. But perhaps the biggest limitation of these systems is that few attempts have been made to characterize at the molecular level the barrier and transport properties in vitro compared to those in vivo. This would seem to be particularly important given the propensity for cells to transform in culture. Where attempts have been made, the extent to which the in vivo properties are retained is limited67.\n\n(ii) Receptor-mediated and adsorptive-mediated transcytosis (see Table 1)\n\nLajoie and Shusta60 review a number of more recent developments using alternative targets on cerebral endothelial cells, but it is too soon to tell whether these will be more successful than earlier developed methods.\n\n(iii) Influx transporters\n\nAs indicated above, there are numerous influx transporters in brain endothelial cells. In the case of only a few, it has been possible to use these to achieve penetration of a therapeutic compound into the brain. The best known, and one of the earliest to be described, is L-DOPA for the treatment of Parkinson’s disease, e.g. 68. Its introduction transformed the treatment of this condition, but, after prolonged experience, it is clear that it has serious clinical limitations.\n\n(iv) Inhibition of efflux transporters (see above, 69, and Table 1)\n\nThe number of ABC transporters that have been shown to be functionally effective at the blood-brain barrier is only a small proportion of the known total of 49. A huge number of drugs and other xenobiotics are excluded from the brain70, which explains the lack of specificity of ABC transporters. Unless some way could be found to limit the effect of the inhibitor to cerebral endothelial cells, and preferably only those in the neurological target area of the brain, this is unlikely to be a viable method of promoting drug entry to the brain.\n\n(v) Modulation of integrity of the blood-brain barrier\n\nThree methods have been tried − osmotic opening, ultrasound, and electrical stimulation (Table 2).\n\nReversible osmotic opening of the blood-brain barrier was first demonstrated in animals by Rapoport et al.71 using a variety of hypertonic electrolyte and non-electrolyte solutions. Brightman et al.72 showed that barrier opening to horseradish peroxidase was due to opening of cerebral vessel tight junctions. Since 1979, Neuwelt has pioneered the use of osmotic opening of the blood-brain barrier as a means of delivering chemotherapeutic agents to treat brain tumors73. He has built up an impressive array of animal and patient imaging techniques, which allowed careful evaluation of the use of hypertonic solutions to open the barrier under well-controlled, carefully monitored conditions and to develop methods for mitigating some of the potentially devastating side effects74,75. Reversible osmotic opening of the blood-brain barrier is the only technique for improving drug delivery to the brain that has successfully translated to the clinic. It is not widely used, probably because it requires repeated hospital admissions and general anesthesia, as well as being associated with increased risk of stroke and epileptic seizures76 and other surgical and neurological problems75.\n\nFocused ultrasound disruption of the blood-brain barrier in laboratory animals was first investigated in the 1950s77. In that study and in subsequent ones, it was necessary to perform a craniectomy in order to achieve sufficient ultrasound energy to produce effects in the brain (e.g. 78). A major advance was to combine intravenous injection of gas bubbles, previously developed as a contrast agent for ultrasound imaging, with focused ultrasound79; this reduced the ultrasound power required to disrupt the blood-brain barrier and was shown to be effective through the intact skull in rabbits. Subsequent studies have evaluated the safety of the procedure80, effects of different anesthetic agents80, and feasibility in large animals81. The mechanism of the interaction between the micro-bubbles and the focused ultrasound beam is unclear. Several possibilities are discussed by Burgess and Hynynen82 and by Timbie et al.83. The advantages of this approach compared to osmotic disruption of the blood-brain barrier are that (a) it is non-invasive (does not require craniotomy), (b) it can be targeted to a specific lesion, e.g. tumor, or region of neurological disorder such as the basal ganglia in Parkinson’s disease, (c) it is transient, although the estimates of duration barrier opening have varied from 6 to 24 hours in different studies, and (d) under well-defined conditions of ultrasound parameters, there appears to be no evidence of ischemia, apoptosis, or cognitive dysfunction (tested in primates82). Investigations so far have concentrated on the mechanical disruptive effects of the method, but studies are needed to investigate possible effects on cellular transport across cerebral endothelial cells84. Also, it needs to be considered whether the effects might be different in pathological brains.\n\n\nWhat next?\n\nThe concentration in the past 25 years on developing in vitro systems for testing barrier permeability to drugs and the various drug delivery methods outlined above has been at the expense of fundamental research aimed at better understanding of brain barrier mechanisms. We list here some major questions, the answers to which might aid the development of more effective drug delivery strategies as well as our understanding of the involvement of brain barrier mechanisms in a wide range of neuropsychiatric conditions.\n\n(i) Different approaches to drug development\n\nGiven the overwhelming importance of efflux transporters in excluding drugs from the brain, we need better understanding of the molecular nature of their mechanism(s) of action, as this would allow the development of drugs that evade these mechanisms. However, there would still be a need to develop ways of targeting the drugs not just to the cerebral vasculature but also to specific brain regions. This might come from better knowledge of the molecular characteristics of cerebral endothelial and peripheral endothelial cells as well as identifying such differences in different brain regions, as suggested by Pachter’s work66,85.\n\n(ii) Rapid high-throughput screening of drugs with potential for neurotherapeutic treatments\n\nIn the past, most such drugs have been developed in vitro but failed as useful agents in vivo because of inability to cross the blood-brain barrier86. Two plausible approaches, on which a start has been made, are (a) to use in initial screens organisms that are easily available in large numbers, e.g. flies87,88 and zebrafish89,90. These organisms utilize ABC efflux transporters as in mammals, although the morphological sites at which they function are different in invertebrates87 and the actual ABC transporters that are functionally important may be different in different species. Also, (b) we require a better understanding of the ABC transporters in human brain barriers (adult and developing) and their level of function. It should then be possible to devise appropriate cell-based screens using fluorophore-tagged drugs and competitors91.\n\n(iii) What is the risk to the developing brain of drugs administered to pregnant women?\n\nAs indicated above, several ABC transporters are expressed at high levels in embryonic brain both in blood vessels and in the choroid plexuses28,35. However, it is uncertain if expression levels can be equated to functional exclusion of drugs from the brain. If this can be shown, then coupled with similar transporter activity in the placenta, this suggests that the developing brain may be much better protected than is implied by the discredited but still current dogma that the blood-brain barrier in the embryo is unformed or “leaky” (see Text Box). Nevertheless, the loss of the placental protection in prematurely born infants may mean that they are more vulnerable to the ill effects of drugs than their full-term counterparts.\n\n(iv) Involvement of barrier mechanism in brain disorders\n\nThe literature on possible involvement of blood-brain barrier mechanisms is too extensive to cover in this review. Recent papers describing different aspects of the pathobiology of brain barrier mechanisms are 92, which is particularly comprehensive, and 69,93–95. For decades, the focus has been on dysfunction defined by supposed disruption of the blood-brain barrier often defined with unsuitable markers (see Text Box). Only comparatively recently has attention turned to the possibility that transporter dysfunction may be involved. It is usually unclear whether barrier dysfunction is a cause or a consequence of a particular neurological disorder. This is an area in which further research with modern technology is likely to be fruitful.",
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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nde Lange EC, Danhof M: Considerations in the use of cerebrospinal fluid pharmacokinetics to predict brain target concentrations in the clinical setting: implications of the barriers between blood and brain. Clin Pharmacokinet. 2002; 41(10): 691–703. PubMed Abstract | Publisher Full Text\n\nLouveau A, Smirnov I, Keyes TJ, et al.: Structural and functional features of central nervous system lymphatic vessels. Nature. 2015; 523(7560): 337–341. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "12840",
"date": "10 Mar 2016",
"name": "Daniela Virgintino",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12841",
"date": "10 Mar 2016",
"name": "Patrizia Ferretti",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-313
|
https://f1000research.com/articles/5-310/v1
|
09 Mar 16
|
{
"type": "Review",
"title": "Advances of gene therapy for primary immunodeficiencies",
"authors": [
"Fabio Candotti"
],
"abstract": "In the recent past, the gene therapy field has witnessed a remarkable series of successes, many of which have involved primary immunodeficiency diseases, such as X-linked severe combined immunodeficiency, adenosine deaminase deficiency, chronic granulomatous disease, and Wiskott-Aldrich syndrome. While such progress has widened the choice of therapeutic options in some specific cases of primary immunodeficiency, much remains to be done to extend the geographical availability of such an advanced approach and to increase the number of diseases that can be targeted. At the same time, emerging technologies are stimulating intensive investigations that may lead to the application of precise genetic editing as the next form of gene therapy for these and other human genetic diseases.",
"keywords": [
"Gene Therapy",
"Primary immunodeficiency diseases",
"Immunodeficiencies",
"X-linked severe combined immunodeficiency",
"SCID"
],
"content": "Introduction\n\nPrimary immunodeficiency diseases (PIDs) are a heterogeneous group of mostly rare genetic diseases comprising over 250 different clinical entities and resulting from a vast variety of aberrations affecting the biological pathways of development and differentiation of the immune system1. The most severe forms of PIDs are characterized by recurrent and life-threatening infections, the risk of which can be obviated only with the reconstitution of a normally functioning immune system. Since the late 1960s, allogeneic hematopoietic stem cell transplantation (HSCT) has been successfully used to treat severe PIDs and it still represents the treatment of choice. While its results have been improving steadily over the past few decades, HSCT remains an intensive procedure burdened by significant morbidity and mortality, especially when affected patients cannot benefit from HLA-identical sibling donors2. Based on the notion that genetic correction of autologous hematopoietic stem cells (HSCs) could provide a safer alternative for any patient from whom HSCs can be obtained, gene therapy approaches for PIDs were developed starting in the mid-1980s and were initially based on the use of gene transfer vectors derived from murine gamma-retroviruses3. These pioneer clinical protocols made their entry into the clinical arena in the early 1990s and focused on patients affected with adenosine deaminase (ADA)-deficient severe combined immunodeficiency (SCID) who derived limited benefit from the genetic correction of either their peripheral blood lymphocytes or CD34+ hematopoietic progenitors4–7. Following technical progress led to the identification of effective combinations of cytokines and growth factors (e.g. SCF, TPO, and Flt-3 ligand) that, together with culture supports such as fibronectin, resulted in major improvements in the ability to introduce genes into HSCs8,9. These improvements preluded to the first unambiguous successful clinical applications of gene therapy in patients affected with X-linked SCID (SCIDX-1), ADA-SCID, and Wiskott-Aldrich syndrome (WAS)10–13 (Figure 1). Unfortunately, with the initial clear clinical benefits, the first serious complications of gene therapy also occurred. In a significant number of patients treated using murine gamma-retroviral vectors, insertional oncogenesis events driven by the presence of the powerful viral enhancer elements resulted in acute leukemias that, in some cases, have had fatal outcomes14–16. These serious adverse events have sparked a revision of the assessment of risks and benefits of integrating gene transfer as therapy for PIDs and prompted the development and application of new generations of viral vectors with increased safety characteristics.\n\nCD43+ hematopoietic progenitors are obtained through bone marrow harvest or peripheral blood apheresis after pharmacological mobilization. Cells are then cultured in vitro with cytokines and growth factors (e.g. SCF, TPO, and Flt-3 ligand) and exposed to viral vectors. Finally, transduced cells are collected and reinfused to the patient through a peripheral vein. If the gene therapy protocol involves myeloreductive chemotherapy, the cytoreductive agent is administered ~24 hours before the infusion of gene-corrected cells. (Graphics modified from original illustrations by Derryl Leja, NHGRI, Image Gallery, www.genome.gov).\n\nThis commentary will summarize the results of the current clinical trials that are making use of such newer vectors with the goal of continuing the expansion of successful applications of gene therapy for PIDs, while increasing the safety of clinical investigations.\n\n\nImproving the safety of gene therapy for primary immunodeficiencies\n\nThis form of SCID is caused by mutations affecting the expression of the common gamma chain (γc) of the receptors for IL-2, IL-4, IL-7, IL-9, IL-15, and IL-2117,18 and, similar to other SCID diseases, is characterized by combined impairment of T- and B-cell immunity and early susceptibility to overwhelming infections. Clinical gene therapy trials using murine gamma-retroviral vectors expressing γc were developed in the mid 1990s as an alternative therapeutic option to HSCT and, in the early 2000s, yielded the first convincing results that gene therapy could provide a cure for human genetic diseases10,12. Unfortunately, five out of the 20 SCIDX-1 patients treated in these trials developed T-cell leukemia between 2 and 5 years after gene therapy. In all cases, evidence pointed to the integration of the γc retroviral vector in the vicinity of oncogenes (LMO2 or CCND2) as the promoting factor due to the presence of a powerful enhancer element within the retroviral construct that is accepted to have caused aberrant oncogene activation and consequent leukemogenesis14,15.\n\nInvestigators in the field reacted to these adverse events by developing safer γc gene transfer vector alternatives. A gamma-retroviral vector devoid of enhancer sequences was demonstrated to be effective in the mouse model of SCIDX-119 and then brought to the clinic in a consortium study including centers in Paris, Boston, Cincinnati, Los Angeles, and London. Recently published data show that seven out of eight evaluable patients achieved significant numbers of corrected, diverse, and functional circulating T-lymphocytes with temporal kinetics that did not differ from earlier γc gene therapy trials. In contrast to T cells, there was not significant correction of the B-cell compartment, with all patients remaining on immunoglobulin replacement therapy. Importantly, at 12–39 months post-gene therapy, no clonal expansions were detected and analysis of retroviral integration sites showed significantly less clustering near LMO-2, EVI1, or other lymphoid oncogenes compared to the earlier γc gene therapy trials20. If confirmed after extended follow-up, these findings would indicate that the use of enhancer-deleted retroviral vectors can result in similar restoration of immune function for SCIDX-1 patients compared to first-generation gamma-retroviral vectors, while affording superior safety.\n\nAs another alternative to gamma-retroviral vectors for gene therapy of SCIDX-1 and other PIDs, investigators turned to gene transfer constructs based on human immunodeficiency virus type 1 (HIV-1) that are accepted as integrating vectors with lower potential to cause activation of oncogenes located near their genomic integration sites21. A γc-expressing lentiviral vector based on HIV-1 has been developed22 and is being used in a two-site clinical trial open at the St. Jude Children’s Research Center in Memphis, where typical SCIDX-1 patients will be enrolled, and at the National Institutes of Health, where atypical, older patients are treated. The latter arm of the trial uses non-myeloablative conditioning to improve the efficacy of engraftment of gene-corrected cells and has enrolled five patients with encouraging preliminary results of reconstitution of B-lymphocyte function in two patients at >2.5 years post-treatment23. Whether or not lentiviral-mediated gene therapy for SCIDX-1 represents a safe and effective alternative will need to be established based on extended patient accrual and follow-up.\n\nWAS is an X-linked disorder with a spectrum of clinical presentations ranging from isolated mild thrombocytopenia to life-threatening bleeding episodes, severe eczema, recurrent infections, autoimmune disorders, and high incidence of lymphomas. Functional abnormalities affect all major lymphoid and myeloid cell populations and contribute to the heterogeneous and medically challenging clinical presentation of affected patients24. HSCT can be curative for WAS, but its outcome is unsatisfactory when HLA-identical donors are not available2,25, which supported the development of gene therapy for this disease.\n\nThe first clinical gene therapy trial for WAS was carried out in Germany and used a gamma-retroviral vector to correct CD34+ cells from ten WAS patients, nine of whom showed significant increase of platelet counts and restoration of immune responses. Unfortunately, seven patients developed acute leukemia likely due to vector-mediated activation of the LMO2, MDS1, or MN1 genes16. Therefore, gamma-retroviral vector-mediated gene therapy of WAS appears to carry an unacceptably high level of risk of insertional oncogenesis. Providing an alternative to the use of murine gamma-retroviral vectors, WAS gene transfer constructs based on HIV-1 had also become available26, which allowed for their application to two clinical trials, the initial results of which have been recently published. In the first trial, Italian investigators showed improvement of platelet counts, immune function, and clinical manifestations of the disease in three patients at ≥1 year after gene therapy. Importantly, comparison of retroviral and lentiviral vector integration sites in samples from the German and Italian studies showed lack of overrepresentation of sites targeting oncogenes in the Italian patient group, while demonstrating early enrichment of oncogenic targets in patients from the German trial27. In the second trial, six out of seven patients treated in London and Paris also showed improvement of immune function and clinical manifestations 6–42 months after treatment, during which no vector-mediated clonal expansions were noted28. Of note, for reasons that are not yet clear, neither trial resulted in reconstitution of normal platelet numbers, although bleeding episodes significantly reduced in number and severity, and treated patients became independent from transfusion and need for thrombopoiesis stimulator factors27,28. More recently, a trial using the same lentiviral vector used in the Italian and French sites described above has launched in Boston, MA, USA and has enrolled four patients as of December 2015 with similar results29. Based on these observations, it can be concluded that lentiviral-mediated gene therapy for WAS is feasible and can result in significant benefit for treated patients. Clearly, however, long-term observation is warranted to confirm the superior safety of lentiviral gene transfer as an alternative treatment option for this disease.\n\nGene therapy has long been considered an attractive alternative therapeutic option for X-linked chronic granulomatous disease (CGD), a genetic defect affecting the expression of the gp91phox molecule and characterized by impaired superoxide production in phagocytic cells with consequent susceptibility to life-threatening abscesses and/or granuloma formations in the skin, liver, lungs, or bone of affected patients30. Early clinical trials were performed in the late 1990s with limited success due to low engraftment of gene-corrected hematopoietic progenitor cells and often only transitory functional correction of 0.5–1% of peripheral blood granulocytes31–35. A trial performed in Germany in 2004 using a gamma-retroviral vector expressing gp91phox under the transcriptional control of the spleen focus-forming virus long terminal repeat (LTR) appeared to have achieved superior results in two CGD patients when around 15% of neutrophils were found to be functionally corrected early after treatment. This fraction increased due to insertional activation of the PRDM16 and MDS1/EVI1 genes in clonal cell populations that expanded with time. Unfortunately, both patients eventually presented with myelodysplasia that was likely caused by the activation of the EVI1 gene and that resulted in lethal complications36–38. The same clonal expansion was observed in two children with CGD treated in Switzerland with the same protocol with significant correction of functional neutrophils and eradication of fungal infections. In one of these two cases, the clonal expansion was also followed by the occurrence of myelodysplasia and both patients were rescued with allogeneic stem cell transplantation39,40.\n\nSimilar to what ensued after the cases of leukemogenesis in the SCIDX-1 and WAS trials, an enhancer element-devoid gamma-retroviral vector and a lentiviral vector expressing gp91phox have been developed for safer gene therapy approaches for CGD41,42 and multicenter clinical trials are planned in Europe and the USA to determine their efficacy. In addition to the needed improvements in safety, gene therapy approaches for CGD are confronting the as-yet-unexplained difficulty in achieving long-term engraftment of significant levels of transduced cells. The lack of a strong selective advantage of gene-corrected populations in this disease may imply that higher levels of HSC transduction and engraftment will be needed to obtain clinical benefit. In this respect, the gene therapy field is likely to borrow from the experience of HSCT in CGD to identify preparative conditioning regimens that are effective and well tolerated43. Finally, with the aim of avoiding possible toxic effects of gp91phox expression in hematopoietic progenitors, the newer constructs for gene therapy of CGD carry myeloid-specific promoters and/or allow for microRNA-mediated post-transcriptional downregulation of expression in hematopoietic stem/progenitor cells42,44.\n\nThis form of SCID is caused by genetic defects of ADA and presents with extreme reduction of lymphocyte numbers and impairment of immune functions that can lead to early death from infections45. HSCT and enzyme replacement therapy (ERT) are available forms of treatment for this disease, but each has drawbacks that limit their efficacy46,47. As mentioned above, in the mid-1980s, ADA deficiency was identified as an ideal candidate disorder for trials of gene therapy. A series of clinical trials tested gamma-retroviral vector-mediated ADA gene transfer into patients’ peripheral blood T lymphocytes4,5,48–51, bone marrow, or cord blood HSCs6,7,52 as an alternative treatment option to HSCT and ERT, but failed to result in self-standing improvements of the disease in treated patients.\n\nThe turning point was when the experimental protocols were changed to include administration of mild myeloreductive chemotherapy with busulfan (e.g. 4 mg/kg) or melphalan (140 mg/m2), and the withholding of ERT, as steps aimed at increasing the initial advantage of gene-corrected HSCs. As shown initially by Aiuti and collaborators in Italy, this approach was revealed to be extremely effective in achieving immune reconstitution (increases in T-cell counts, normalization of T-cell function, and restoration of responses to vaccinations) in the majority of ten treated patients who remained off ERT in the long term11,53.\n\nThese encouraging results were confirmed in a similar gene therapy trial conducted in the UK, in which four out of six treated patients showed increases in T-cell and B-cell numbers, with normalization of in vitro lymphocyte responses and adequate immunoglobulin production in three subjects54,55.\n\nOur own investigations performed at the Children’s Hospital Los Angeles, University of California Los Angeles, and the National Institutes of Health compared the immune reconstitution observed in four patients treated without prior administration of chemotherapy and while on ERT to that of six patients whose treatment strategy involved low-dose busulfan chemotherapy (75–90 mg/m2) and withdrawal of ERT. The results demonstrated that the use of reduced-intensity conditioning favored engraftment of gene-modified stem cells and the generation of ADA-expressing lymphocytes and consequent immune reconstitution56.\n\nIt is important to note that the immune recovery observed in ADA-SCID patients after gene therapy with gamma-retroviral vectors occurred in the absence of insertional oncogenesis events, which distinguishes the experience in this disease from the other PIDs discussed above. The reasons underlying this contrast remain unclear, but they may reflect biological differences between ADA, γc, and the WAS protein and their possible contributing roles in leukemogenesis. Regardless of the current safety record of gamma-retroviral vector-mediated gene therapy for ADA-SCID, compelling reasons existed to generate a newer, more efficient, and safer ADA vector, which was accomplished with the development of a lentiviral construct57 that is being tested in the UK and USA with very encouraging preliminary results58.\n\n\nFuture prospects and challenges\n\nPreclinical development is underway for several other forms of PID that would benefit from gene therapy approaches (Table 1). Promising results have been obtained using lentiviral vectors to correct SCID due to RAG1, RAG2, and Artemis deficiencies in mouse and xenotransplant models59–65 and are expected to translate into clinical experiments in the near future. Gene therapy for PIDs such as purine nucleoside phosphorylase (PNP) deficiency, Janus kinase (JAK)-3-deficient SCID, and leukocyte adhesion deficiency type 1 (LAD-1) was considered and/or unsuccessfully carried out before technological advances established the current levels of feasibility of clinical gene transfer66–68. Better outcomes would be expected if these experiments were to be re-attempted at present times. For several other forms of PIDs, the tissue-restricted or finely regulated characteristics of expression of the causal genes represent significant challenges and will require additional technical progress. It is hoped that the expanding application of “gene editing” strategies (e.g. zinc-finger nucleases [ZFNs], transcription activator-like effector nucleases [TALENs], and clustered regularly interspaced short palindromic repeats [CRISPR]/CRISPR-associated endonuclease [Cas-9] technology) will ultimately provide the ability of performing precise genetic correction of PID-causing mutations, while respecting the physiological machineries of gene expression regulation and avoiding the problems of ectopic gene expression that are inherent in current “gene addition” approaches. Important proofs-of-concept have already been obtained using ZFN technology, including the repair of γc mutations in in vitro and in vivo xenotransplant models69,70 and the site-directed addition of the gp91phox complementary DNA (cDNA) in induced pluripotent stem cells (iPSCs)71.\n\n*In addition to biological patient samples.\n\nJAK3, Janus kinase 3; LAD-1, leukocyte adhesion deficiency type 1; PNP, purine nucleoside phosphorylase; RAG, recombination activating gene; X-HIM, X-linked hyper-IgM syndrome; XLA, X-linked agammaglobulinemia; XLP, X-linked lymphoproliferative syndrome; ZAP70, zeta-chain-associated protein kinase 70; KO, knockout; IPSCs, induced pluripotent stem cells.\n\nWhile there are excellent prospects for the safer implementation of gene therapy for an increasing number of PIDs, it is difficult to ignore that clinical gene transfer remains a laborious procedure restricted to a very small number of highly specialized academic centers worldwide. For PIDs like ADA-SCID, SCIDX-1, and WAS, the current results make gene therapy a realistic therapeutic alternative that can be considered as part of the clinical management plan. Access to this therapeutic modality, however, is far from simple owing to financial and geographical considerations. As a possible solution, strategies are being developed that would allow hematopoietic progenitors to be collected at the patient’s local institution and sent to gene therapy centers where the gene transfer procedure would be performed. Cryopreserved, gene-corrected samples would then be sent back for infusion. The involvement of pharmaceutical and biotechnology companies would make these objectives easier to achieve, and it is encouraging that corporate interest in supporting clinical gene therapy trials for PIDs is increasing.\n\nThirty years after proof-of-principle experiments demonstrating the first corrections of genetic disease phenotypes in vitro72,73, gene transfer is fulfilling its promise by achieving convincing curative potential for a variety of human disorders. Since the very beginning of the field of human gene therapy, PIDs have played a major role in driving the evolution and implementation of the initial theoretical strategies of this discipline. Cutting-edge activity continues to characterize this area of gene therapy and will undoubtedly foster further applications against human diseases.\n\n\nAbbreviations\n\nADA: adenosine deaminase\n\nCGD: chronic granulomatous disease\n\nERT: enzyme replacement therapy\n\nFlt-3: fms-like tyrosine kinase\n\ngc: gamma chain\n\nHSC: hematopoietic stem cell\n\nHSCT: hematopoietic stem cell transplantation\n\nHIV-1: human immunodeficiency virus type 1\n\nIL: interleukin\n\nIPSCs: induced pluripotent stem cells\n\nJAK: Janus kinase\n\nLAD: leukocyte adhesion deficiency\n\nPIDs: primary immunodeficiency diseases\n\nRAG: recombination activating gene\n\nSCF: stem cell factor\n\nSCID: severe combined immunodeficiency\n\nSCIDX-1: X-linked severe combined immunodeficiency\n\nWAS: Wiskott-Aldrich syndrome\n\nZFNs: zinc-finger nucleases",
"appendix": "Competing interests\n\n\n\nThe author has no competing interests to declare.\n\n\nGrant information\n\nThis work was supported by funding jointly granted by the University of Lausanne (UNIL) and the University Hospital of Lausanne (CHUV), Switzerland.\n\nI confirm that the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\n\n\nReferences\n\nPicard C, Al-Herz W, Bousfiha A, et al.: Primary Immunodeficiency Diseases: an Update on the Classification from the International Union of Immunological Societies Expert Committee for Primary Immunodeficiency 2015. J Clin Immunol. 2015. 35(8): 696–726.PubMed Abstract | Publisher Full Text | Free Full Text\n\nGennery AR, Slatter MA, Grandin L, et al.: Transplantation of hematopoietic stem cells and long-term survival for primary immunodeficiencies in Europe: entering a new century, do we do better? J Allergy Clin Immunol. 2010; 126(3): 602–10.e1–11. PubMed Abstract | Publisher Full Text\n\nMiller AD: Retroviral vectors. Curr Top Microbiol Immunol. 1992; 158: 1–24. PubMed Abstract\n\nBlaese RM, Culver KW, Miller AD, et al.: T lymphocyte-directed gene therapy for ADA- SCID: initial trial results after 4 years. Science. 1995; 270(5235): 475–80. PubMed Abstract | Publisher Full Text\n\nBordignon C, Notarangelo LD, Nobili N, et al.: Gene therapy in peripheral blood lymphocytes and bone marrow for ADA- immunodeficient patients. Science. 1995; 270(5235): 470–5. PubMed Abstract | Publisher Full Text\n\nKohn DB, Weinberg KI, Nolta JA, et al.: Engraftment of gene-modified umbilical cord blood cells in neonates with adenosine deaminase deficiency. Nat Med. 1995; 1(10): 1017–23. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHoogerbrugge PM, van Beusechem VW, Fischer A, et al.: Bone marrow gene transfer in three patients with adenosine deaminase deficiency. Gene Ther. 1996; 3(2): 179–83. PubMed Abstract\n\nKiem HP, Andrews RG, Morris J, et al.: Improved gene transfer into baboon marrow repopulating cells using recombinant human fibronectin fragment CH-296 in combination with interleukin-6, stem cell factor, FLT-3 ligand, and megakaryocyte growth and development factor. Blood. 1998; 92(6): 1878–86. PubMed Abstract\n\nTisdale JF, Hanazono Y, Sellers SE, et al.: Ex vivo expansion of genetically marked rhesus peripheral blood progenitor cells results in diminished long-term repopulating ability. Blood. 1998; 92(4): 1131–41. PubMed Abstract\n\nCavazzana-Calvo M, Hacein-Bey S, de Saint Basile G, et al.: Gene therapy of human severe combined immunodeficiency (SCID)-X1 disease. Science. 2000; 288(5466): 669–72. PubMed Abstract | Publisher Full Text\n\nAiuti A, Slavin S, Aker M, et al.: Correction of ADA-SCID by stem cell gene therapy combined with nonmyeloablative conditioning. Science. 2002; 296(5577): 2410–3. 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J Clin Invest. 2008; 118(9): 3143–50. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBraun CJ, Boztug K, Paruzynski A, et al.: Gene therapy for Wiskott-Aldrich syndrome--long-term efficacy and genotoxicity. Sci Transl Med. 2014; 6(227): 227ra33. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nNoguchi M, Yi H, Rosenblatt HM, et al.: Interleukin-2 receptor gamma chain mutation results in X-linked severe combined immunodeficiency in humans. Cell. 1993; 73(1): 147–57. PubMed Abstract | Publisher Full Text\n\nPuck JM, Deschênes SM, Porter JC, et al.: The interleukin-2 receptor gamma chain maps to Xq13.1 and is mutated in X-linked severe combined immunodeficiency, SCIDX1. Hum Mol Genet. 1993; 2(8): 1099–104. PubMed Abstract | Publisher Full Text\n\nThornhill SI, Schambach A, Howe SJ, et al.: Self-inactivating gammaretroviral vectors for gene therapy of X-linked severe combined immunodeficiency. Mol Ther. 2008; 16(3): 590–8. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHacein-Bey Abina S, Gaspar HB, Blondeau J, et al.: Outcomes following gene therapy in patients with severe Wiskott-Aldrich syndrome. JAMA. 2015; 313(15): 1550–63. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nChu JI, Henderson LA, Armant M, et al.: Gene Therapy Using a Self-Inactivating Lentiviral Vector Improves Clinical and Laboratory Manifestations of Wiskott-Aldrich Syndrome. Blood. 2015; 126: 260–260. Reference Source\n\nKang EM, Marciano BE, DeRavin S, et al.: Chronic granulomatous disease: overview and hematopoietic stem cell transplantation. J Allergy Clin Immunol. 2011; 127(6): 1319–26; quiz 1327–8. PubMed Abstract | Publisher Full Text | Free Full Text\n\nMalech HL, Sekhsaria S, Whiting Theobald N, et al.: Prolonged detection of oxidase-positive neutrophils in the peripheral blood of five patients following a single cycle of gene therapy for chronic granulomatous disease. Blood. 1996; 88((abstr. suppl. 1)): 486a.\n\nMalech HL, Horwitz ME, Linton GF, et al.: Extended production of oxidase normal neutrophils in X-linked chronic granulomatous disease (CGD) following gene therapy with gp91(phox) transduced CD34+ cells. Blood. 1998; 92: 690A.\n\nGoebel WS, Dinauer MC: Gene therapy for chronic granulomatous disease. Acta Haematol. 2003; 110(2–3): 86–92. PubMed Abstract | Publisher Full Text\n\nKang EM, Choi U, Theobald N, et al.: Retrovirus gene therapy for X-linked chronic granulomatous disease can achieve stable long-term correction of oxidase activity in peripheral blood neutrophils. Blood. 2010; 115(4): 783–91. PubMed Abstract | Publisher Full Text | Free Full Text\n\nGrez M, Reichenbach J, Schwäble J, et al.: Gene therapy of chronic granulomatous disease: the engraftment dilemma. Mol Ther. 2011; 19(1): 28–35. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOtt MG, Schmidt M, Schwarzwaelder K, et al.: Correction of X-linked chronic granulomatous disease by gene therapy, augmented by insertional activation of MDS1-EVI1, PRDM16 or SETBP1. Nat Med. 2006; 12(4): 401–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nStein S, Ott MG, Schultze-Strasser S, et al.: Genomic instability and myelodysplasia with monosomy 7 consequent to EVI1 activation after gene therapy for chronic granulomatous disease. Nat Med. 2010; 16(2): 198–204. PubMed Abstract | Publisher Full Text\n\nAiuti A, Bacchetta R, Seger R, et al.: Gene therapy for primary immunodeficiencies: Part 2. Curr Opin Immunol. 2012; 24(5): 585–91. PubMed Abstract | Publisher Full Text\n\nBianchi M, Hakkim A, Brinkmann V, et al.: Restoration of NET formation by gene therapy in CGD controls aspergillosis. Blood. 2009; 114(13): 2619–22. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nSiler U, Paruzynski A, Holtgreve-Grez H, et al.: Successful Combination of Sequential Gene Therapy and Rescue Allo-HSCT in Two Children with X-CGD - Importance of Timing. Curr Gene Ther. 2015; 15(4): 416–27. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nMoreno-Carranza B, Gentsch M, Stein S, et al.: Transgene optimization significantly improves SIN vector titers, gp91phox expression and reconstitution of superoxide production in X-CGD cells. Gene Ther. 2009; 16(1): 111–8. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nSantilli G, Almarza E, Brendel C, et al.: Biochemical correction of X-CGD by a novel chimeric promoter regulating high levels of transgene expression in myeloid cells. Mol Ther. 2011; 19(1): 122–32. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGüngör T, Teira P, Slatter M, et al.: Reduced-intensity conditioning and HLA-matched haemopoietic stem-cell transplantation in patients with chronic granulomatous disease: a prospective multicentre study. Lancet. 2014; 383(9915): 436–48. PubMed Abstract | Publisher Full Text\n\nChiriaco M, Farinelli G, Capo V, et al.: Dual-regulated lentiviral vector for gene therapy of X-linked chronic granulomatosis. Mol Ther. 2014; 22(8): 1472–83. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHirschhorn R, Grunebaum E, Roifman C, et al.: Immunodeficiency Due to Defects of Purine Metabolism: Territorial Administration under Attack in Orleans and Washington. In: Hans D. Ochs, MD, Dr.med, C. I. Edvard Smith, PhD, Jennifer M. Puck, MD, editors. Primary Immunodeficiency Diseases: A Molecular and Genetic Approach. Oxford University Press, 2013; 188–230. Publisher Full Text\n\nGaspar HB, Aiuti A, Porta F, et al.: How I treat ADA deficiency. Blood. 2009; 114(17): 3524–32. PubMed Abstract | Publisher Full Text | Free Full Text\n\nHassan A, Booth C, Brightwell A, et al.: Outcome of hematopoietic stem cell transplantation for adenosine deaminase-deficient severe combined immunodeficiency. Blood. 2012; 120(17): 3615–24; quiz 3626. PubMed Abstract | Publisher Full Text\n\nOnodera M, Ariga T, Kawamura N, et al.: Successful peripheral T-lymphocyte-directed gene transfer for a patient with severe combined immune deficiency caused by adenosine deaminase deficiency. Blood. 1998; 91(1): 30–6. PubMed Abstract\n\nMisaki Y, Ezaki I, Ariga T, et al.: Gene-transferred oligoclonal T cells predominantly persist in peripheral blood from an adenosine deaminase-deficient patient during gene therapy. Mol Ther. 2001; 3(1): 24–7. PubMed Abstract | Publisher Full Text\n\nAiuti A, Vai S, Mortellaro A, et al.: Immune reconstitution in ADA-SCID after PBL gene therapy and discontinuation of enzyme replacement. Nat Med. 2002; 8(5): 423–5. PubMed Abstract | Publisher Full Text\n\nMuul LM, Tuschong LM, Soenen SL, et al.: Persistence and expression of the adenosine deaminase gene for 12 years and immune reaction to gene transfer components: long-term results of the first clinical gene therapy trial. Blood. 2003; 101(7): 2563–9. PubMed Abstract | Publisher Full Text\n\nOtsu M, et al.: Update on a Japanese clinical trial of stem cell gene therapy for ADA-deficiency. Human Gene Therapy. 2010; 21(10): 1437–1437.\n\nAiuti A, Cattaneo F, Galimberti S, et al.: Gene therapy for immunodeficiency due to adenosine deaminase deficiency. N Engl J Med. 2009; 360(5): 447–58. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGaspar HB, Bjorkegren E, Parsley K, et al.: Successful reconstitution of immunity in ADA-SCID by stem cell gene therapy following cessation of PEG-ADA and use of mild preconditioning. Mol Ther. 2006; 14(4): 505–13. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGaspar HB, Cooray S, Gilmour KC, et al.: Hematopoietic stem cell gene therapy for adenosine deaminase-deficient severe combined immunodeficiency leads to long-term immunological recovery and metabolic correction. Sci Transl Med. 2011; 3(97): 97ra80. PubMed Abstract | Faculty Opinions Recommendation\n\nCandotti F, Shaw KL, Muul L, et al.: Gene therapy for adenosine deaminase-deficient severe combined immune deficiency: clinical comparison of retroviral vectors and treatment plans. Blood. 2012; 120(18): 3635–46. PubMed Abstract | Publisher Full Text | Free Full Text\n\nCarbonaro DA, Zhang L, Jin X, et al.: Preclinical demonstration of lentiviral vector-mediated correction of immunological and metabolic abnormalities in models of adenosine deaminase deficiency. Mol Ther. 2014; 22(3): 607–22. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nGaspar B, Buckland K, Rivat C, et al.: Immunological and Metabolic Correction After Lentiviral Vector Mediated Haematopoietic Stem Cell Gene Therapy for ADA Deficiency. Journal of Clinical Immunology. 2014; 34: S167–S168.\n\nPike-Overzet K, Rodijk M, Ng YY, et al.: Correction of murine Rag1 deficiency by self-inactivating lentiviral vector-mediated gene transfer. Leukemia. 2011; 25(9): 1471–83. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nvan Til NP, de Boer H, Mashamba N, et al.: Correction of murine Rag2 severe combined immunodeficiency by lentiviral gene therapy using a codon-optimized RAG2 therapeutic transgene. Mol Ther. 2012; 20(10): 1968–80. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nvan Til NP, Sarwari R, Visser TP, et al.: Recombination-activating gene 1 (Rag1)-deficient mice with severe combined immunodeficiency treated with lentiviral gene therapy demonstrate autoimmune Omenn-like syndrome. J Allergy Clin Immunol. 2014; 133(4): 1116–23. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nPike-Overzet K, Baum C, Bredius RG, et al.: Successful RAG1-SCID gene therapy depends on the level of RAG1 expression. J Allergy Clin Immunol. 2014; 134(1): 242–3. PubMed Abstract | Publisher Full Text\n\nMostoslavsky G, Fabian AJ, Rooney S, et al.: Complete correction of murine Artemis immunodeficiency by lentiviral vector-mediated gene transfer. Proc Natl Acad Sci U S A. 2006; 103(44): 16406–11. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBenjelloun F, Garrigue A, Demerens-de Chappedelaine C, et al.: Stable and functional lymphoid reconstitution in artemis-deficient mice following lentiviral artemis gene transfer into hematopoietic stem cells. Mol Ther. 2008; 16(8): 1490–9. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nLagresle-Peyrou C, Benjelloun F, Hue C, et al.: Restoration of human B-cell differentiation into NOD-SCID mice engrafted with gene-corrected CD34+ cells isolated from Artemis or RAG1-deficient patients. Mol Ther. 2008; 16(2): 396–403. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nNelson DM, Butters KA, Markert ML, et al.: Correction of proliferative responses in purine nucleoside phosphorylase (PNP)-deficient T lymphocytes by retroviral-mediated PNP gene transfer and expression. J Immunol. 1995; 154(6): 3006–14. PubMed Abstract\n\nBauer TR, Hickstein DD: Gene therapy for leukocyte adhesion deficiency. Curr Opin Mol Ther. 2000; 2(4): 383–8. PubMed Abstract\n\nSorrentino BP, Lu T, Ihle J, et al.: A clinical attempt to treat JAK3-deficient SCID using retroviral-mediated gene transfer to bone marrow CD34+ cells. Molecular Therapy. 2003; 7: S449. Reference Source\n\nUrnov FD, Miller JC, Lee Y, et al.: Highly efficient endogenous human gene correction using designed zinc-finger nucleases. Nature. 2005; 435(7042): 646–51. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nGenovese P, Schiroli G, Escobar G, et al.: Targeted genome editing in human repopulating haematopoietic stem cells. Nature. 2014; 510(7504): 235–40. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nZou J, Sweeney CL, Chou BK, et al.: Oxidase-deficient neutrophils from X-linked chronic granulomatous disease iPS cells: functional correction by zinc finger nuclease-mediated safe harbor targeting. Blood. 2011; 117(21): 5561–72. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nWillis RC, Jolly DJ, Miller AD, et al.: Partial phenotypic correction of human Lesch-Nyhan (hypoxanthine-guanine phosphoribosyltransferase-deficient) lymphoblasts with a transmissible retroviral vector. J Biol Chem. 1984; 259(12): 7842–9. PubMed Abstract\n\nKantoff PW, Kohn DB, Mitsuya H, et al.: Correction of adenosine deaminase deficiency in cultured human T and B cells by retrovirus-mediated gene transfer. Proc Natl Acad Sci U S A. 1986; 83(17): 6563–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSun JY, Pacheco-Castro A, Borroto A, et al.: Construction of retroviral vectors carrying human CD3 gamma cDNA and reconstitution of CD3 gamma expression and T cell receptor surface expression and function in a CD3 gamma-deficient mutant T cell line. Hum Gene Ther. 1997; 8(9): 1041–8. PubMed Abstract | Publisher Full Text\n\nCandotti F, Oakes SA, Johnston JA, et al.: In vitro correction of JAK3-deficient severe combined immunodeficiency by retroviral-mediated gene transduction. J Exp Med. 1996; 183(6): 2687–92. PubMed Abstract | Publisher Full Text | Free Full Text\n\nOakes SA, Candotti F, Johnston JA, et al.: Signaling via IL-2 and IL-4 in JAK3-deficient severe combined immunodeficiency lymphocytes: JAK3-dependent and independent pathways. Immunity. 1996; 5(6): 605–15. PubMed Abstract | Publisher Full Text\n\nBunting KD, Sangster MY, Ihle JN, et al.: Restoration of lymphocyte function in Janus kinase 3-deficient mice by retroviral-mediated gene transfer. Nat Med. 1998; 4(1): 58–64. PubMed Abstract | Publisher Full Text\n\nBunting KD, Flynn KJ, Riberdy JM, et al.: Virus-specific immunity after gene therapy in a murine model of severe combined immunodeficiency. Proc Natl Acad Sci U S A. 1999; 96(1): 232–7. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBunting KD, Lu T, Kelly PF, et al.: Self-selection by genetically modified committed lymphocyte precursors reverses the phenotype of JAK3-deficient mice without myeloablation. Hum Gene Ther. 2000; 11(17): 2353–64. PubMed Abstract | Publisher Full Text\n\nLagresle-Peyrou C, Yates F, Malassis-Séris M, et al.: Long-term immune reconstitution in RAG-1-deficient mice treated by retroviral gene therapy: a balance between efficiency and toxicity. Blood. 2006; 107(1): 63–72. PubMed Abstract | Publisher Full Text\n\nYates F, Malassis-Séris M, Stockholm D, et al.: Gene therapy of RAG-2-/- mice: sustained correction of the immunodeficiency. Blood. 2002; 100(12): 3942–9. PubMed Abstract | Publisher Full Text\n\nLagresle-Peyrou C, Six EM, Picard C, et al.: Human adenylate kinase 2 deficiency causes a profound hematopoietic defect associated with sensorineural deafness. Nat Genet. 2009; 41(1): 106–11. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nLiao P, Toro A, Min W, et al.: Lentivirus gene therapy for purine nucleoside phosphorylase deficiency. J Gene Med. 2008; 10(12): 1282–93. PubMed Abstract | Publisher Full Text\n\nTaylor N, Bacon KB, Smith S, et al.: Reconstitution of T cell receptor signaling in ZAP-70-deficient cells by retroviral transduction of the ZAP-70 gene. J Exp Med. 1996; 184(5): 2031–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nSteinberg M, Swainson L, Schwarz K, et al.: Retrovirus-mediated transduction of primary ZAP-70-deficient human T cells results in the selective growth advantage of gene-corrected cells: implications for gene therapy. Gene Ther. 2000; 7(16): 1392–400. PubMed Abstract | Publisher Full Text\n\nOtsu M, Steinberg M, Ferrand C, et al.: Reconstitution of lymphoid development and function in ZAP-70-deficient mice following gene transfer into bone marrow cells. Blood. 2002; 100(4): 1248–56. PubMed Abstract | Publisher Full Text\n\nAdjali O, Marodon G, Steinberg M, et al.: In vivo correction of ZAP-70 immunodeficiency by intrathymic gene transfer. J Clin Invest. 2005; 115(8): 2287–95. PubMed Abstract | Publisher Full Text | Free Full Text\n\nIrla M, Saade M, Kissenpfennig A, et al.: ZAP-70 restoration in mice by in vivo thymic electroporation. PLoS One. 2008; 3(4): e2059. PubMed Abstract | Publisher Full Text | Free Full Text\n\nBradley MB, Fernandez JM, Ungers G, et al.: Correction of defective expression in MHC class II deficiency (bare lymphocyte syndrome) cells by retroviral transduction of CIITA. J Immunol. 1997; 159(3): 1086–95. PubMed Abstract\n\nYu PW, Tabuchi RS, Kato RM, et al.: Sustained correction of B-cell development and function in a murine model of X-linked agammaglobulinemia (XLA) using retroviral-mediated gene transfer. Blood. 2004; 104(5): 1281–90. PubMed Abstract | Publisher Full Text\n\nMoreau T, Barlogis V, Bardin F, et al.: Development of an enhanced B-specific lentiviral vector expressing BTK: a tool for gene therapy of XLA. Gene Ther. 2008; 15(12): 942–52. PubMed Abstract | Publisher Full Text\n\nKerns HM, Ryu BY, Stirling BV, et al.: B cell-specific lentiviral gene therapy leads to sustained B-cell functional recovery in a murine model of X-linked agammaglobulinemia. Blood. 2010; 115(11): 2146–55. PubMed Abstract | Publisher Full Text | Free Full Text\n\nNg YY, Baert MR, Pike-Overzet K, et al.: Correction of B-cell development in Btk-deficient mice using lentiviral vectors with codon-optimized human BTK. Leukemia. 2010; 24(9): 1617–30. PubMed Abstract | Publisher Full Text\n\nBrown MP, Topham DJ, Sangster MY, et al.: Thymic lymphoproliferative disease after successful correction of CD40 ligand deficiency by gene transfer in mice. Nat Med. 1998; 4(11): 1253–60. PubMed Abstract | Publisher Full Text\n\nTahara M, Pergolizzi RG, Kobayashi H, et al.: Trans-splicing repair of CD40 ligand deficiency results in naturally regulated correction of a mouse model of hyper-IgM X-linked immunodeficiency. Nat Med. 2004; 10(8): 835–41. PubMed Abstract | Publisher Full Text\n\nRomero Z, Torres S, Cobo M, et al.: A tissue-specific, activation-inducible, lentiviral vector regulated by human CD40L proximal promoter sequences. Gene Ther. 2011; 18(4): 364–71. PubMed Abstract | Publisher Full Text\n\nCarmo M, Risma KA, Arumugam P, et al.: Perforin gene transfer into hematopoietic stem cells improves immune dysregulation in murine models of perforin deficiency. Mol Ther. 2015; 23(4): 737–45. PubMed Abstract | Publisher Full Text | Free Full Text\n\nRivat C, Booth C, Alonso-Ferrero M, et al.: SAP gene transfer restores cellular and humoral immune function in a murine model of X-linked lymphoproliferative disease. Blood. 2013; 121(7): 1073–6. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWilson JM, Ping AJ, Krauss JC, et al.: Correction of CD18-deficient lymphocytes by retrovirus-mediated gene transfer. Science. 1990; 248(4961): 1413–6. PubMed Abstract | Publisher Full Text\n\nBauer TR Jr, Miller AD, Hickstein DD: Improved transfer of the leukocyte integrin CD18 subunit into hematopoietic cell lines by using retroviral vectors having a gibbon ape leukemia virus envelope. Blood. 1995; 86(6): 2379–87. PubMed Abstract\n\nBauer TR, Schwartz BR, Liles WC, et al.: Retroviral-mediated gene transfer of the leukocyte integrin CD18 into peripheral blood CD34+ cells derived from a patient with leukocyte adhesion deficiency type 1. Blood. 1998; 91(5): 1520–6. PubMed Abstract\n\nYorifuji T, Wilson RW, Beaudet AL: Retroviral mediated expression of CD18 in normal and deficient human bone marrow progenitor cells. Hum Mol Genet. 1993; 2(9): 1443–8. 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}
|
[
{
"id": "12836",
"date": "09 Mar 2016",
"name": "Ramsay Fuleihan",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12837",
"date": "09 Mar 2016",
"name": "Anete Grumach",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-310
|
https://f1000research.com/articles/5-309/v1
|
09 Mar 16
|
{
"type": "Review",
"title": "Oocyte Maturation and Development",
"authors": [
"Marie-Hélène Verlhac",
"Marie-Emilie Terret",
"Marie-Emilie Terret"
],
"abstract": "Sexual reproduction is essential for many organisms to propagate themselves. It requires the formation of haploid female and male gametes: oocytes and sperms. These specialized cells are generated through meiosis, a particular type of cell division that produces cells with recombined genomes that differ from their parental origin. In this review, we highlight the end process of female meiosis, the divisions per se, and how they can give rise to a functional female gamete preparing itself for the ensuing zygotic development. In particular, we discuss why such an essential process in the propagation of species is so poorly controlled, producing a strong percentage of abnormal female gametes in the end. Eventually, we examine aspects related to the lack of centrosomes in female oocytes, the asymmetry in size of the mammalian oocyte upon division, and in mammals the direct consequences of these long-lived cells in the ovary.",
"keywords": [
"meiosis",
"gamete",
"zygotic development",
"oocyte",
"oocyte maturation"
],
"content": "Introduction: definitions\n\nAll oocytes undergo induced arrest at the dictyate stage of prophase I during meiosis in the ovary. This arrest takes place after chromosome pairing and crossing-over formation between parental chromosomes. It can last months in mice and decades in humans. Upon hormonal surge, oocytes will exit the prophase I arrest and resume meiosis. All stages from meiosis resumption, starting with nuclear envelope breakdown (NEBD) until the next arrest where oocytes are fertilized, belong to the meiotic maturation process (Figure 1). This process terminates meiosis, allowing the gamete to go through two successive rounds of extremely asymmetric divisions in size. Between these divisions, there is no intervening DNA replication, truly rendering the gamete haploid after, at, or before the second meiotic arrest at fertilization. Indeed, depending on the species, this second arrest will take place at different cell cycle stages: coincident with meiosis resumption at NEBD in nematodes, in metaphase I in Drosophila, in metaphase II for most vertebrates, or after the end of the second meiotic division in starfish oocytes.\n\nMeiotic maturation starts with nuclear envelope breakdown (NEBD) and is followed by the first meiotic division where bivalents are separated, the first polar body is extruded and then, in vertebrates, arrest in metaphase of the second meiotic division (MII stage) occurs. The oocyte is ovulated at the MII stage. Sister chromatids will be segregated after fertilization. Zygotic development follows fertilization. Oocytes (in gray) are surrounded by a protective glycoprotein layer, the zona pellucida (beige). DNA is in pink, microtubules in green.\n\nThere are three essential features that we would like to highlight in this review: (1) meiotic divisions take place in the absence of centrosomes in most animals; (2) these divisions are highly asymmetric in size to produce large oocytes; and (3) in mammals, oocytes display an extreme longevity in the ovary.\n\nWe would like to propose that these three features, among other things, predispose oocytes to errors in chromosome segregation. In mammals, this aspect has been particularly well studied, especially in human oocytes, which present a basal rate of errors close to 20% in women younger than 35 years of age and which can be as high as 60% in older women1–3. Indeed, it remains puzzling that given the extreme parental investment in juvenile care in many species, such little attention is being paid to oocyte ploidy, as if errors in chromosome segregation were part of a selection process for gamete fitness.\n\n\nAcentriolar divisions\n\nCentrosomes, consisting of a pair of centrioles surrounded by a cloud of pericentriolar material (PCM), are the major centers for microtubule assembly (microtubule-organizing center). Most oocytes lose their centrioles during oogenesis; if not, like in starfish, they are progressively eliminated and inactivated during meiotic divisions4–8. Even though centrosomes are not strictly required to segregate chromosomes (as shown in flies, planarians, or mice 9–12), they contribute to the coordination of spindle assembly and increase its robustness. The immediate consequence of centrosome loss is that meiotic spindles are devoid of astral microtubules and so lack the main connector between the spindle poles and the cell cortex (Figure 2). Hence, spindle positioning cannot rely on astral microtubules as it happens in most somatic cells13–16. Furthermore, centrosome-nucleated microtubules cannot capture chromosomes14. In mitotic cells, duplicated centrosomes are positioned on opposite sides of the nucleus such that in prometaphase the spindle axis is already set17–20. On the contrary, meiotic spindle bipolarity is not predefined by the position of the two centrosomes. Instead, during meiosis I, spindle bipolarity is progressively established and this can take about 40 minutes in Drosophila, 3 hours in mouse, and up to 6.5 hours in human oocytes21–25. Not only is meiotic spindle bipolarity an extremely slow process in meiosis I but it appears that assembly of K fibers (microtubule bundles that connect the kinetochores of chromosomes) is quite long: 50 minutes in Drosophila, 6 to 7 hours in mice, and about 16 hours in humans26–28. The biological significance of such a progressive K fiber assembly during oocyte meiosis I remains unknown, but it is clear that in both Drosophila and mice precocious stabilization of K fibers is deleterious for bivalent alignment, orientation, and segregation28,29.\n\nCells are in gray, and oocytes are surrounded by a protective glycoprotein layer, the zona pellucida (beige). DNA is in pink, microtubules in green, centrioles in black, and pericentriolar material (PCM) in yellow.\n\nOocytes use an inside/outside mode of spindle assembly, first promoting the assembly of microtubules around chromatin and then defining the spindle poles25,30–33. As a result, meiotic spindle poles in oocytes appear less robust, not being anchored into unique and well-defined centrosomes. In some species, like Drosophila, nematodes, Xenopus, and even human oocytes, microtubule minus ends at spindle poles are not even connected or anchored to discrete PCM foci25,34–38, unlike in rodents25,34–38. The lack of anchoring raises issues not only on spindle pole organization and maintenance but also on the nature of the force integration that allows all chromosomes to end up midway in between both poles, on the metaphase plate. As a consequence of having poles formed by more than one entity, pole integrity can be compromised and splitting of poles may occur, as in cancer cells with extra-centrosomes presenting unbalanced poles composed of multiple centrosomes23,31,39. It may not be so surprising that the rate of chromosome mis-segregation in oocytes is very high compared with most somatic cells in the presence of non-equilibrated spindle poles, which favor merotelic attachments not detected by the spindle assembly checkpoint (SAC)40 as shown in cells with extra-centrosomes41,42.\n\nIn addition to lacking robust spindle poles, many oocytes use actin-based propulsion forces to position their chromosomes43–50. In starfish oocytes, an actin fishnet is transiently formed at meiosis resumption, prior to the microtubule capture, to maintain all chromosomes spatially confined, avoiding their dispersal in the huge volume of the nucleus, beyond the reach of microtubules51–53. In mitotic cells, even though astral microtubules dictate the orientation of the spindle apparatus, they are also connected to F-actin, which helps transmit forces exerted by the cell environing tissue54–57. In mitosis, microfilaments cooperate in spindle assembly: they help separate the two centrosomes in prometaphase, hence promoting spindle bipolarization58, and they modulate spindle orientation and favor spindle assembly through mitotic cell rounding59. However, in mammalian oocytes, where spindle bipolarization in meiosis I can take hours, it seems important that microfilaments do not interfere with spindle assembly and are thus nucleated around the microtubule spindle only once the latter is robust enough60. It was very recently shown that the centrosome can also be a major filament-organizing center (it could be named an FTOC)61. The centrosome thus acts as a coordinator of microtubule and microfilament networks inside the cytoplasm. In oocytes, this coordination is missing. Therefore, it is conceivable that other mechanisms have emerged to avoid premature interference between the two meshes and also to modulate their interaction.\n\n\nExtremely asymmetric divisions in size\n\nOocytes undergo extremely asymmetric divisions, leading to the formation of a large cell, the oocyte, and two minuscule polar bodies. This size asymmetry is essential to maintain the maternal reserves accumulated during oogenesis in order to sustain embryo development. For this, they rely on very asymmetric spindle positioning. In the case of the Xenopus oocyte, 1 mm wide (Figure 3), the asymmetry is clearly extreme where one spindle pole is anchored at the cortex while the other pole cannot reach the opposite cortex (the spindle being approximately 30 μm long). The asymmetric anchoring of the meiotic spindle to the cortex generates a strong imbalance of the forces experienced by each spindle pole, converted into asymmetric forces exerted on the chromosomes. How do oocytes achieve the equilibrium of tension on both sides of each bivalent (meiosis I) or univalent (meiosis II)? Moreover, when somatic cells enter mitosis, they round up and their cortical tension increases and this helps to equilibrate forces coming from each spindle poles to the chromosomes54,62–64. Unexpectedly, mouse oocytes experience a drop in cortical tension during meiosis and this is absolutely necessary for spindle positioning as well as for the asymmetry of the division65–67. One can easily understand that a soft and deformable cortex favors the extrusion of polar bodies tailored to the chromatin mass better than a stiff cortex, as in mitosis. However, it is difficult to conceive how spindle microtubules can transmit and propagate the tension to chromosomes when their poles are not symmetrically anchored and when one pole is actually anchored on a soft material. One has to imagine that pushing or pulling forces might be transmitted more locally or maybe via yet-to-be-discovered structures/mechanisms inside the meiotic spindle. In worm oocytes, a solution has emerged with extensive meiotic spindle pole depolymerization at anaphase I and with most microtubule forces required to separate bivalent chromosomes coming from local microtubule assembly at the chiasmata, allowing the chromosomes to be pushed apart68.\n\nCells are in gray and oocytes are surrounded by a protective glycoprotein layer, the zona pellucida (beige). DNA is in pink, kinetochores in dark pink, microtubules in green, centrioles in black, and pericentriolar material (PCM) in yellow.\n\nAnother feature which characterizes oocytes is the poor sensitivity of the SAC to errors in chromosome alignment or to a global drop in tension exerted on bivalents69–73. In nematodes and Xenopus oocytes, there is no SAC response, and no cell cycle arrest is observed in Caenorhabditis elegans mutants with severe meiotic spindle defects or after complete microtubule depolymerization in the frog74–77. Similarly, mutations in multiple SAC genes do not affect cyclin B levels or chromosome segregation in Drosophila oocytes78. In contrast, SAC-deficient Drosophila neuroblasts, genetically modified to lack centrosomes, present a higher incidence of chromosome segregation errors than acentrosomal neuroblasts with a functional SAC. This shows that, in Drosophila mitosis, a functional SAC is required, in the absence of centrosomes, contrary to what is observed in oocytes79. Interestingly, all three of the above species assemble meiotic spindles without discrete PCM foci at their poles and this might contribute to the absence of a SAC response (Figure 3).\n\nAs suggested by pioneering work from Xenopus early development, the origin of the poor SAC response in oocytes might come from their large size (Figure 3)80. The SAC signal, which inhibits the activation of the anaphase-promoting complex/cyclosome (APC/C) and thus the degradation of two key substrates, cyclin B and securin that trigger the metaphase-to-anaphase transition, is produced by unattached kinetochores and might be diluted in the large cytoplasmic volume. It will be very interesting to reduce oocyte size and see whether this restores a mitotic-like SAC response. Alternatively, it may not be strictly the oocyte size per se, but rather its size with respect to the dimensions of the adult female (Figure 3). This ratio might relate better to the amount of energy invested by the species in its reproductive capacity. It could explain why, in nematodes and Drosophila, organisms a thousand times smaller than a mouse but producing eggs of comparable size as mammals, there is no SAC response during oocyte meiosis, as in Xenopus oocytes that lay eggs 12.5 times larger than mouse eggs for a comparable adult body size.\n\n\nExacerbated longevity of mammalian oocytes\n\nThanks to a renewable population of germ cells that supports gametogenesis in their ovaries, nematodes, Drosophila, and amphibian females produce oocytes during their whole life. On the contrary, eutherian mammals possess a finite reserve of germ cells that are formed and stored during embryogenesis. The different reproductive strategies used by these model organisms might also explain the differences in SAC sensitivity (Figure 3). Rapidly spawning a lot of eggs at the right season might have been selected to allow frog dissemination at the expense of gamete quality production. In contrast to species that lay eggs or embryos in the external milieu, in mammals, the longevity of oocytes from birth to ovulation can reach decades. This raises issues about chromatin architecture maintenance to sustain such a long-lived metabolism, in particular for the turnover of key elements involved in chromosome segregation. Meiotic spindle morphology is altered, with poor chromosome alignment and split poles in aging human oocytes obtained from normal naturally cycling women81. Also, it has been clearly established that the amount of maternal mRNA encoding for genes involved in the SAC response, spindle integrity, and spindle positioning decreases in aged mouse oocytes82,83. More importantly, the number of proteins maintaining chromosome pairing reaches a critical low level in aged mouse and human oocytes, which impedes the integrity of chiasmata84–86. Furthermore, artificially abolishing one key meiotic cohesin, SMC1β, by gene targeting already has profound effects on the integrity of bivalents, and aged oocytes deficient for SMC1β display evidence of chiasma terminalization87. The reduction in cohesin levels can be attributed to their lack of turnover. Indeed, genetic studies aimed at assessing the turnover of key cohesin subunits, such as the meiotic cohesin Rec8 or SMC1β, have demonstrated that these cohesins are not replenished after birth in the growing follicles of the mouse88,89. The progressive deterioration of cohesion could potentially be a leading cause for the increase in errors in chromosome segregation (in particular, errors in meiosis I) observed with age1,3,90. Nonetheless, in Drosophila oocytes, evidence for cohesin rejuvenation during oogenesis has been shown91. Whether this aspect is specific to Drosophila or can be extended to mammals is currently unknown.\n\nThe effect of cohesin deterioration can be further amplified by the poor sensitivity of the SAC, at least in mice, to a reduction in tension on bivalents71. Recently, direct observations made on human oocytes have shown that sister kinetochores tend to split prematurely during meiosis I and that this effect increases with age92,93. Premature splitting potentially favors precocious bivalent dissociation into univalent, contributing to aneuploidy.\n\n\nConclusions\n\nAmazing progress has been made since the pioneering review that put into the limelight the fact that human oocytes are error prone and that the rate of errors increases with the age of the mother1. This review challenged scientists in the field to try to understand a major societal issue of our modern societies where women postpone childbearing and to which female scientists were maybe already particularly exposed. Advance has come from studies on diverse model systems presenting both similarities and differences with human oocyte meiosis. Importantly, observations made in human oocytes have been challenged by hypotheses tested in model systems where genetics or biochemistry can be performed. Obviously, it is a combination of factors that seem to predispose oocytes to aneuploidy: their confounding fragile mode of spindle assembly and positioning, coupled to the pressure to preserve maternal stores in a gigantic cell via extreme asymmetry in size of their divisions as well as their longevity. Of course, many other factors not highlighted here, such as the distribution as well as the rate of recombination between homologues, which have a direct influence on chromosome segregation, can also predispose for aneuploidy in oocytes3. The major discovery of PRDM9, a key factor controlling the distribution of hot spots for recombination in some species but not others, will certainly help us to understand the impact of recombination on aneuploidy in oocytes94–96. Indeed, meiotic maturation is embedded in a continuous process that started in the embryo and that resumes later in the life of an animal. Meiotic maturation also prepares the gamete for fertilization and early development; hence, gamete quality does greatly influence the chances of a successful pregnancy.",
"appendix": "Competing interests\n\n\n\nThe authors declare that they have no competing interests.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nAcknowledgments\n\nWe wish to thank Maria Almonacid (CIRB, Collège de France, Paris) for her help with the iconography of figures and Agathe Chaigne (Laboratory for Molecular Biology, University College London, UK), Julien Dumont (Institut Jacques Monod, Paris), and Renata Basto (Institut Curie, Paris) as well as all the members of the Verlhac lab for constructive comments on this review. We would like to apologize to those whose work we have not cited here, owing to space constraints.\n\n\nReferences\n\nHassold T, Hunt P: To err (meiotically) is human: the genesis of human aneuploidy. Nat Rev Genet. 2001; 2(4): 280–91. PubMed Abstract | Publisher Full Text\n\nHassold T, Hall H, Hunt P: The origin of human aneuploidy: where we have been, where we are going. 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PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nHodges CA, Revenkova E, Jessberger R, et al.: SMC1beta-deficient female mice provide evidence that cohesins are a missing link in age-related nondisjunction. Nat Genet. 2005; 37(12): 1351–5. PubMed Abstract | Publisher Full Text | Faculty Opinions Recommendation\n\nRevenkova E, Herrmann K, Adelfalk C, et al.: Oocyte cohesin expression restricted to predictyate stages provides full fertility and prevents aneuploidy. Curr Biol. 2010; 20(17): 1529–33. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nTachibana-Konwalski K, Godwin J, van der Weyden L, et al.: Rec8-containing cohesin maintains bivalents without turnover during the growing phase of mouse oocytes. Genes Dev. 2010; 24(22): 2505–16. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nJessberger R: Age-related aneuploidy through cohesion exhaustion. EMBO Rep. 2012; 13(6): 539–46. PubMed Abstract | Publisher Full Text | Free Full Text\n\nWeng KA, Jeffreys CA, Bickel SE: Rejuvenation of meiotic cohesion in oocytes during prophase I is required for chiasma maintenance and accurate chromosome segregation. PLoS Genet. 2014; 10(9): e1004607. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nPatel J, Tan SL, Hartshorne GM, et al.: Unique geometry of sister kinetochores in human oocytes during meiosis I may explain maternal age-associated increases in chromosomal abnormalities. Biol Open. 2015; 5(2): 178–84. PubMed Abstract | Publisher Full Text\n\nZielinska AP, Holubcova Z, Blayney M, et al.: Sister kinetochore splitting and precocious disintegration of bivalents could explain the maternal age effect. eLife. 2015; 4: pii: e11389. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nBaudat F, Buard J, Grey C, et al.: PRDM9 is a major determinant of meiotic recombination hotspots in humans and mice. Science. 2010; 327(5967): 836–40. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nMyers S, Bowden R, Tumian A, et al.: Drive against hotspot motifs in primates implicates the PRDM9 gene in meiotic recombination. Science. 2010; 327(5967): 876–9. PubMed Abstract | Publisher Full Text | Free Full Text | Faculty Opinions Recommendation\n\nParvanov ED, Petkov PM, Paigen K: Prdm9 controls activation of mammalian recombination hotspots. Science. 2010; 327(5967): 835. PubMed Abstract | Publisher Full Text | Free Full Text"
}
|
[
{
"id": "12838",
"date": "09 Mar 2016",
"name": "Keith T. Jones",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
},
{
"id": "12839",
"date": "09 Mar 2016",
"name": "John Carroll",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-309
|
https://f1000research.com/articles/5-308/v1
|
09 Mar 16
|
{
"type": "Opinion Article",
"title": "siRNA knockdown validation 101: Incorporating negative controls in antibody research",
"authors": [
"Will Olds",
"Jason Li"
],
"abstract": "More antibody validation protocols would identify non-specific reagents – a major source of irreproducible research – with the inclusion of negative controls. This article presents an overview of one such method: siRNA knockdown. The authors outline a general protocol, the knockdown mechanism, and tips for evaluating knockdown experiments.",
"keywords": [
"knockdown",
"siRNA",
"negative control",
"specificity",
"Western Blot",
"shRNA",
"transfection",
"vector"
],
"content": "Introduction\n\nPoor quality, unverified antibodies are a major factor underlying the crisis of reproducibility in research1, resulting in an estimated $800 million of waste each year2 and a ten-fold spike in retractions over the past decade3. Behind those numbers are researchers with mounting frustration each time a new batch of reagents fails to reproduce their previous work. If we as a scientific community are to eliminate this problem plaguing our research, we must develop new and more thorough validation methods to fortify and standardize routine studies.\n\nWe invite industry to respond to the need for more rigorous validation by incorporating negative controls, an essential part of experimental design that has nonetheless been overlooked historically by antibody manufacturers and distributors. Companies typically validate with Western blots but seldom test routinely whether antibodies still produce a signal when the target protein is suppressed or removed.\n\nShort interfering RNA (siRNA) knockdown is a technology that makes routine use of this strategy more feasible. This technology degrades target messenger RNA to ‘knock down’ the production of a protein in the cell. The combination of siRNA-treated cells and a specific antibody will result in a significant drop in signal compared to an untreated sample by Western blot (Figure 1).\n\nsiRNA knockdown has not been the only validation initiative put forward to identify non-specific antibodies4. CRISPR and other gene editing methods knock out a gene from DNA, preventing the associated protein from ever being produced. By default, an antibody binding to any protein in this environment is binding to the wrong protein. Knock-out is a powerful negative control, however one concern with this method is the risk of cell death when a target protein is vital to cell survival. Other initiatives dispense with negative controls and verify positive identification instead. Mass spectrometry, for example, yields unique spectra that differentiate an antibody-bound protein of interest from any other bound molecule but is limited only to those proteins that can be immunoprecipitated.\n\nWhile all of these approaches sound simple, their methodologies can be complex. Anyone seeking a deeper understanding of siRNA knockdown validation studies, or considering their own validation protocol, may find the following overview useful. These steps are based on Proteintech methods, which have been tested and refined over years. However, they are by no means the only way to perform this validation.\n\n\nDesign and engineer a vector\n\nSelecting a target and designing an appropriate vector to transfect into cells is a relatively straightforward process, with an abundance of literature and online resources available to guide the process (RNAi Consortium, Dharmacon, Ui-Tei, and Genelink). The actual engineering, of course, requires a bit more hands-on finesse to create the short hairpin RNA that is the precursor form of the siRNA. The ultimate aim is to design two single-stranded 19-22mer DNA oligonucleotides (one sense strand, one antisense strand) whose transcription products will eventually anneal together, linked at one end by a short loop sequence. Proteintech uses the loop sequence TTCAAGACG.\n\n\nTransfect and culture\n\nOnce the vector has been generated and produced in sufficient quantity, scientists need to determine an appropriate transfection method for delivery into cells. Upon successful transfection, the cells transcribe the foreign DNA to generate the shRNA described above (Figure 2). Afterward, Dicer processes the shRNA into siRNA by removing the loop sequence. The resulting siRNA binds with RISC (RNA-induced silencing complex), which separates the two strands of the RNA and activates the complex. RISC remains bound to one strand, that complementarily binds to a target mRNA and cleaves it. This suppresses production of the associated protein. Scientists need to allow time for the biological processes to be carried out, while culturing the cells to produce enough sample for a Western blot.\n\nCell death can be a major source of frustration, particularly if the target protein is vital to cell survival. Fortunately, most cells can propagate normally if the protein is suppressed, but not completely eliminated. In such cases, knockdown methods can be fine tuned and are likely a preferred alternative to knock out validation, which prevents any transcription through gene editing.\n\n\nTest and evaluate\n\nA strong signal for the empty-vector cells next to a weak signal for the siRNA-transfected cells in a Western blot means that the antibody is specific and that the knockdown experiment was successful. Any nonspecific bands should raise questions, as these could indicate that the antibodies themselves are nonspecific. Bands should also be consistent across all lanes of the Western blot membrane. If not, something may have gone wrong in the experiment, and protocol and experimental design should be reviewed.\n\nWhile the value of negative controls to antibody validation protocols should not be understated, it is also understood that such validation is not widely available and that it consumes time and resources to perform in individual labs. Thorough Western blot validation with only positive controls can be a second-best alternative, provided that there is a sufficient quantity of data, and corroborated by published studies that reference the reagent catalog number and manufacturer. We encourage the development and use of negative controls such as siRNA knockdown as the new standard in antibody validation. Doing so will elevate reproducible research and accelerate scientific progress.",
"appendix": "Author contributions\n\n\n\nWO wrote and JL critically reviewed and edited the article. All authors have agreed to the final content of the manuscript.\n\n\nCompeting interests\n\n\n\nWill Olds is a scientific officer at Proteintech Group. Jason Li is CEO of Proteintech Group.\n\n\nGrant information\n\nThe author(s) declared that no grants were involved in supporting this work.\n\n\nReferences\n\nBaker M: Reproducibility crisis: Blame it on the antibodies. Nature. 2015; 521(7552): 274–276. PubMed Abstract | Publisher Full Text\n\nBaker M: Antibody anarchy: A call to order. Nature. 2015; 527(7579): 545–551. PubMed Abstract | Publisher Full Text\n\nMcLeod J, Ferrigno PK: Antibody Alternatives. The Scientist. 2016. Reference Source\n\nDance A: Exercises for Your Abs. The Scientist. 2016. Reference Source"
}
|
[
{
"id": "12832",
"date": "11 Mar 2016",
"name": "Md. Golam Sharoar",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe article describes an excellent method of antibody specificity validation before commercial release. Non- specific binding of antibody is a major constrain for reproducibility and for acceptable quality of data. Thus, knocking down the target gene utilizing siRNA is a suitable method to determine the specificity of the antibody. The author explained a suitable method to develop high quality antibody commercialization. I believe that the article is appropriate as published in F1000Research.",
"responses": []
},
{
"id": "12835",
"date": "14 Mar 2016",
"name": "Angus C. Nairn",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nThe suggestion to routinely incorporate negative controls such as siRNA knockdown for the validation of antibodies is a good one. The article is clearly written and timely. The authors might have included an appropriate reference to the discovery of the siRNA knockdown mechanism. Further, the authors might have discussed the basis for choice of cell line used as the positive control.",
"responses": []
},
{
"id": "12834",
"date": "23 Mar 2016",
"name": "Shi-Jiang Lu",
"expertise": [],
"suggestion": "Approved",
"report": "Approved\n\ninfo_outline\nAlongside their report, reviewers assign a status to the article:\n\nApproved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested\n\nApproved with reservations\nA number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.\n\nNot approved Fundamental flaws in the paper seriously undermine the findings and conclusions\n\nAntibody has been widely used in bio-research fields, and discrepancies among publications using antibodies from different vendors are frequently observed. The main reason is the specificity of antibodies used by different researchers. This article described a siRNA knockdown strategy to validate the specificity of antibodies, which provides a negative control that may serve as an alternative way to exclude non-specific antibodies. This strategy may, at least partially, solve the irreproducible results among researches using antibodies as detecting reagents.",
"responses": []
}
] | 1
|
https://f1000research.com/articles/5-308
|
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