Majority of these bacteria are commonly found in human gut. These include Bacillus, Clostridium, Enterobacter, Escherichia, Fusobacterium, Salmonella, etc. Interestingly, while pathogens utilize almost all the analyzed pathways, commensals prefer putrescine and H2S production pathways for metabolizing the undigested proteins. Further, comparison of the putrefaction pathways in the gut microbiomes of healthy, carcinoma and adenoma datasets indicate higher abundances of putrefying bacteria in the carcinoma stage of CRC. The insights obtained from the present study indicate utilization of possible microbiome-based therapies to minimize the adverse effects of gut microbiome in enteric diseases.Fermentation of undigested proteins in human gastrointestinal tract (gut) by the resident microbiota, a process called bacterial putrefaction, can sometimes disrupt the gut homeostasis. In this process, essential amino acids  that are required by the host may be utilized by the gut microbes. In addition, some of the products of putrefaction, like ammonia, putrescine, cresol, indole, phenol, etc., have been implicated in the disease pathogenesis of colorectal cancer (CRC). We have investigated bacterial putrefaction pathways that are known to be associated with such metabolites. Results of the comprehensive  Putrefaction inside human gastrointestinal tract (gut) pertains to decomposition or fermentation of undigested proteins by the resident microbiota . The die2S) has been reported to cause disruption of colonocyte barrier function (The deleterious effects of putrefaction (in gut) have been reported to be associated with colorectal cancer (CRC) . For exafunction . Thus, tColorectal cancer is one of the leading causes of cancer related deaths worldwide . DiagnosIn the present study, a comprehensive analysis of bacterial genomes was performed to predict their capabilities of utilizing selected putrefaction pathways that are known to be associated with harmful metabolites. The presence of putrefaction pathways in various bacteria was predicted based on parameters like homology of constituent enzymes, enzyme specificity and genomic proximity of corresponding genes. Apart from obtaining the overall distribution of putrefaction pathways across different bacterial groups, the results of the current study indicate importance of the putrefaction pathways in bacteria commonly associated with gut environment. In addition, the current observations suggest involvement of some of these pathways in bacterial pathogenicity. Further, the insights obtained from genome mining have been utilized to understand the role of these pathways harbored by the gut microbiome in CRC patients.in vivo/in vitro studies have demonstrated the harmful effects of some of the products of amino acid fermentation (putrefaction) on gut. These include ammonia, H2S, amine , cresol, indole, and phenol (N-nitroso compounds (NOCs), which can be formed through nitrosation of amines, have been suggested to exhibit carcinogenic effects (Fusobacterium), has been selected for further analysis. Although phenylacetic acid and branched chain fatty acid (BCFA) have been suggested to be efficient indicators of amino acid fermentation in the colon  which participate in multiple functional pathways. Thus, identification of a particular pathway based on only presence of homologs may lead to false predictions. Therefore, in the current study, in addition to enzyme homology, the genomic proximity of the constituent genes has been utilized for prediction of a pathway. However, it may be noted that the genomic proximity (of the constituent genes) may not be true for all pathways. Therefore, in the current study, the putrefaction pathways leading to production of the selected nine metabolites (as discussed in the previous section) were further filtered to shortlist the following three categories of pathways-I Pathways where proximity of the constituent genes have been reported by previous experimental studies.II Pathways where proximity have been reported for a subset of the constituent genes by previous experimental studies.III A third category of pathways has been considered, where the constituent genes may not be located in close proximity, but are catalyzed by enzymes specific to the corresponding pathways.For each of the harmful metabolites, the experimentally validated putrefaction pathways  have been reported to be encoded by gene clusters in Fusobacterium nucleatum ATCC 25586 , the third ammonia releasing pathway considered here, a subset of the constituent genes has been reported to occur in genomic context in Fusobacterium varium , the enzymes participating in two pathways (histidine → glutamate and histidine → THF) , the one through ‘ornithine’ has been reported to be functional in organisms like Lactobacillus sp. 30a, Oenococcus oeni and Lactobacillus brevis IOEB 9906 , encoded by a gene operonic to ADC, converts agmatine to putrescine and urea  and carbamoylputrescine hydrolase (EC: 3.5.1.53) are encoded by the operon aguBA . In addition, a product of methionine catabolism, decarboxylated S-adenosyl methionine (decarboxylated SAM), acts as a cofactor for spermidine synthesis , the latter reaction depends on SpeD (EC: 4.1.1.50). SpeD and SpeE have been reported to be encoded by two operonic genes   has been reported to be functional in Clostridium difficile, where tyrosine is broken down into the intermediate para-hydroxyphenylacetate (p-HPA) by genes of hpdBCA operon .The pathway for production of cresol , phenol (from tyrosine), and cadaverine (from lysine), each involves single step reaction catalyzed by specific enzymes . Further enzymes . The reaThus, based on the above information, 10 putrefaction pathways corresponding to the production of nine metabolites were shortlisted for further analysis.The methodology used for prediction of the selected 10 putrefaction pathways across bacterial genomes has been described below.Prediction of 6 out of 10 selected putrefaction pathways (producing ammonia/putrescine/cresol/spermidine/spermine) with enzymes encoded by gene clusters included two major steps, namely, (i) identification of homologs of the gene components of putrefaction pathways (ii) demarcation of gene clusters based on genomic distances. Although available algorithms like antiSMASH and ClusterFinder utilize gene context information for prediction of bacterial pathways/function, they primarily focus on identification of cluster of genes involved in biosynthesis of specific group of metabolites (such as secondary metabolites) . For pre1) were then queried against this database using the module ‘hmmscan’ provided in the package ‘HMMER’ (version 3.1)   with an 2S) since each of these pathways involve single step reaction mostly catalyzed by specific enzymes . Thus, the organisms containing the corresponding enzymes were retrieved from ‘Uniprot’ database3.The genomic context based information was not required for prediction of the pathways of ‘category III’  pathways with CRC. Since, the currently available technologies do not allow the identification of all bacteria in a given metagenome at strain level, it was necessary to obtain measures of putrefaction capabilities for bacterial groups at higher taxonomic levels. Thus, based on the proportion of constituent putrefying strains and a confidence value of the corresponding group, a score was evaluated at the levels of phylum and genus. The confidence value was incorporated to assign a higher weightage to the bacterial group having relatively higher representative organisms in the database. For evaluating the confidence score, the number of strains under all bacterial groups was first noted. Based on these counts a percentile value was computed for each of the groups. Subsequently, these percentile values were used to assign ranks (between one and five) to the groups. The final putrefaction score (Pfacs), for a particular putrefaction pathway ‘i’ corresponding to a bacterial group ‘j,’ was calculated using the following equation-S represents the proportion of putrefying organisms of the particular bacterial group and α denotes the confidence value of the corresponding bacterial group.where, Thus, the values of the computed ‘Pfacs’ scores ranged between ‘zero’ and ‘five.’ For a particular putrefaction pathway, a bacterial taxon having a higher ‘Pfacs’ would indicate a greater probability of presence of that pathway in the corresponding strains as opposed to a taxon with a lower ‘Pfacs.’In order to investigate the association between bacterial pathogenicity and putrefaction capability, comprehensive list of known gut commensals and pathogens was collated from ‘Integrated Microbial Genomes and Microbiome’ (IMG/M)  and liteIn order to compare the putrefaction capabilities of the microbes residing in the gut of CRC patients with that of healthy individuals, the gut microbiome data (16S rRNA sequences) provided in five published studies on CRC was analyzed . Detailst-test  were identified as differentially abundant genera in the corresponding cohort. Subsequently, the differentially abundant genera of CRC cohort (corresponding to carcinoma as well as adenoma stages) were compared with those of healthy population, in terms of – (i) abundances of putrefying bacteria and (ii) distribution of putrefaction pathways.For identification of differentially abundant taxa in healthy, adenoma and carcinoma samples, multivariate analysis was performed on the normalized abundance for each taxon. Studies containing two distinct classes or groups  were subjected to Welch t-test . Kruskalt-test  was perfStreptococcus have been reported to be either obligate or facultative anaerobes. Thus, for such cases, a generic classification of ‘anaerobe’ was assigned. Further, the proportion of putrefactors in each of the above mentioned categories were noted.The advanced stage of CRC has been associated with hypoxic (oxygen deficit) tumor micro-environment and subsequent growth of anaerobic pathogenic bacteria . In ordeFigure 2). The distributions of the selected 10 putrefaction pathways which lead to release of nine compounds  indicate presence of all the 10 pathways in Firmicutes. Considering the cumulative contribution of putrefying strains belonging to a phylum, while Proteobacteria was predicted to have nine pathways (except tyrosine → cresol), Fusobacteria and Bacteroidetes, were predicted to contain eight pathways (except tyrosine → cresol and lysine → cadaverine). Further, it is noteworthy that, although the strains of Firmicutes cumulatively represented all the 10 pathways, the corresponding ‘Pfacs’ were relatively lower (≤1.4). This suggests that, the putrefaction capability of the phylum Firmicutes is limited to selected members. In contrast, the phyla Acidobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, and Proteobacteria were observed to have comparatively higher ‘Pfacs’ of at least half of the maximum value (2.5) in one or more of the pathways. Interestingly, bacteria belonging to five  out of six above mentioned phyla have been reported to be common inhabitants of the human gut (The results indicate presence of putrefaction pathways in 1368 (50%) bacteria out of the analyzed 2,738 completely sequenced genomes . The results indicate that, the strains belonging to some of the genera contain diverse combinations of analyzed putrefaction pathways, similar to the trend observed in phyla level analysis. This suggests that these pathways may not have been evolutionary retained, but rather have been acquired by the respective organisms for adaptation to the environment they survive in. Overall, the putrescine production pathway (arginine → putrescine) was observed to have highest occurrence (87.5%) among all other pathways . Putrescine like polyamines have been reported to be involved in functions like growth, cell wall synthesis, cell signaling, biofilm formation in bacteria (2S production (cysteine → H2S) with 50% and 56% occurrence, respectively. Among others, the occurrence of five pathways for production of THF (from histidine), glutamate (from histidine), indole (from tryptophan), spermidine/spermine (from methionine) and cadaverine (from lysine) were observed to vary between 25% and 35%. The remaining two pathways corresponding to phenol (from tyrosine) and cresol (from tyrosine) production were predicted to be present in limited number of genera . The genera observed to have higher ‘Pfacs’ (≥2.5) for at least one pathway include Bacillus, Bacteroides, Enterobacter, Escherichia, Klebsiella, Prevotella, Salmonella, Shigella, Vibrio, and Yersinia. In addition, the group of representative strains of Firmicutes phylum, having as much as nine pathways including exclusive presence of cresol production pathway (as mentioned in previous paragraph) was observed to belong to the genus Clostridium. Earlier studies have also suggested the ability of production of cresol through tyrosine fermentation to be unique to Clostridium genus , acquired from undigested proteins that escape energy metabolism and consequently are likely to affect the gut functioning. In addition, since some of the strains of the above mentioned genera have been reported to exert pathogenicity in gut, further analysis of putrefaction pathways in pathogenic and commensal bacteria were carried out.Given the observed association of the selected bacterial putrefaction pathways and gut environment, further analysis was performed on the bacterial genera previously known to be associated with gut . The three pathways occurring in relatively higher number of pathogens include putrescine, spermidine/spermine production and histidine degradation  . In contrast, only the pathways for H2S and putrescine production were predicted in around 30% of the commensals . Apart from the toxic effect on colonic cells, H2S has been proposed to aid bacteria in the formation of biofilm as well as benefit the host cell through mediating production of colonic mucus layer , belonging to the family Enterobacteriaceae, were found to have the pathway involving agmatinase (arginine → agmatine → putrescine)  pathway   were identified to have these two domains as part of two different proteins encoded by separate genes , which was predicted in 50% of the pathogenic strains . The results suggest that, organisms under Enterobacteriaceae family  and the genus Bacillus probably utilize formiminoglutamase (EC 3.5.3.8) for catalyzing one of the reactions (N-formimino-L-glutamate →L-glutamate) of the pathway. The remaining pathogenic strains belonging to the genera Fusobacterium and Bacteroides were predicted to utilize an alternate enzyme, namely glutamate formyltransferase (EC 2.1.2.5), for catalyzing the same reaction. These observations indicate that, during evolution different bacterial groups may have acquired different genetic elements for fermenting same amino acid (like arginine and histidine). The remaining seven putrefaction pathways, namely glutamate degradation and production of THF, cadaverine, cresol, indole, phenol and H2S, were observed to be present in relatively lesser proportion (≤24%) of the pathogens . Earlier studies have implicated the involvement of some of the pathogens like Salmonella Typhimurium, Bacillus cereus, Escherichia coli O157:H7 in contamination and fermentation of meat leading to release of harmful toxins, which has been reported to cause enteric inflammation . Out of the 10 analyzed putrefaction pathways, the differentially abundant genera in carcinoma and healthy cohorts were observed to represent nine and seven pathways, respectively. However, the percentage of occurrence of these pathways in the carcinoma cohort was relatively higher compared to that in the healthy cohort. For example, although putrescine production pathway was observed to have the highest occurrence in both the cohorts, it was found to be present in 58%  and 26%  in carcinoma and healthy cohorts, respectively. The next highest occurring pathway in carcinoma cohort was found to be histidine degradation (31.5%), occurrence of which was seen to be only 13.3% in healthy cohort. Considering the differentially abundant genera in carcinoma samples, the genus Fusobacterium, containing six of the analyzed putrefaction pathways (distributed among its strains), was observed to be differentially abundant in four out the five datasets. The putrefaction capability of Fusobacterium has also been implicated in promoting periodontitis in oral cavity , predicted to possess at least three putrefaction pathways, were observed to be significantly higher in carcinoma microbiome. It may be noted that, the completely sequenced strains belonging to the ‘Clostridium_XIX’ group corresponded to those under Fusobacterium nucleatum species  which were found to be differentially abundant in healthy cohort, namely, Oscillibacter (containing two pathways) and Faecalibacterium (containing one pathway), were predicted to have putrescine production pathway in common and spermidine/spermine production as an additional pathway in the former. Earlier studies have indicated importance of metabolites like putrescine and H2S in functions like growth and biofilm formation in bacteria  may be utilized by the bacteria for their own benefit, rather than exerting harmful effects in the healthy cohort. Additionally, three of the above mentioned genera from healthy cohort  have been reported to produce butyrate, which is known to participate in multiple functions (including anti-inflammatory role) that are beneficial to gut health (Given the putrefying capabilities of gut associated pathogenic organisms (as discussed in section “Gut Bacteria and Putrefaction Pathways Associated with Release of Harmful Compounds”) and the potential role of some of the putrefaction products in disease etiology of CRC, a comparative analysis was performed on publicly available gut microbiome data of CRC patients and corresponding healthy controls. The differentially abundant bacterial genera in these cohorts were considered for capturing possible distinctness in the putrefaction capabilities of their gut microbiomes. A relative enrichment of putrefying bacteria was observed in carcinoma microbiome as compared to that in healthy samples . Advanced stage of the disease has been shown earlier to be correlated with hypoxic (oxygen deficit) microenvironment and consequent growth of anaerobic pathogenic bacteria . Interestingly, while the differentially abundant anaerobic genera corresponding to one of the adenoma cohort were predicted to have only histidine degradation and production of putrescine, cadaverine, and H2S, the other dataset lacked any putrefaction pathway. The decreased number of putrefaction pathways in adenoma , as observed from the analysis based on the limited number of available datasets, would require further validation on a larger cohort. Such studies are likely to provide better insights on the cause-consequence relationship between hypoxic tumor micro-environment and putrefaction by anaerobic bacteria.The results of the microbiome analysis indicated a relative enrichment of putrefying bacteria in gut microbiome of CRC cohort at later stage of the disease as compared to that in the early adenoma stage  which leads to release of harmful metabolites has been computationally analyzed. The results of our analyses suggest a relatively higher putrefaction abilities of the phyla that are commonly found in the gut , indicating significance of bacterial putrefaction in gut environment. Further, an interesting observation corresponds to the comparative ‘Pfacs’ (Putrefaction score) of Bacteroidetes and Firmicutes. The scores for most of the individual pathways  were observed to be higher in Bacteroidetes than Firmicutes. Earlier experimental studies have reported increase in Bacteroidetes to Firmicutes ratio in dysbiotic gut . Thus, tIt is noteworthy that products/by-products generated by bacterial putrefaction are harmless to human body when present within a certain level. Under such conditions, ammonia produced during putrefaction enters urea or ornithine cycle to get converted to urea, which gets excreted from the system . Also, cFusobacterium which was observed to be not only significantly abundant in majority of the carcinoma datasets, but was also observed to have higher number of putrefaction pathways which lead to release of harmful metabolites. Fusobacterium has also been identified as a risk factor for colorectal carcinoma progression (Fusobacterium nucleatum has been suggested to induce colorectal carcinogenesis in animal models (Fusobacterium has been shown to utilize an ammonia releasing pathway for production of butyrate which plays multiple beneficial roles in gut (Fusobacterium genus, the results of the present study indicate probable role of putrefaction capability of this bacterial group in pathogenesis of CRC. The insights from the current study shed light on importance of bacterial putrefaction pathways in CRC augmentation and progression. Further experimental validations of the findings are expected to help in development of microbiome based diagnostic/therapeutic strategies for effective control of CRC.One of the key results obtained from the current study pertains to the genus gression . An adhel models . This bal models . Earlierl models . Interess in gut . Thus, iHK, CD, and SM conceptualized the work and designed the experiments. HK and CD performed the experiments. HK, CD, and SM analyzed the data and drafted the manuscript. All authors reviewed the results and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


To identify genes related to C4 photosynthesis, Huang et al. looked for evidence of past episodes of adaptive evolution in the genomes of C4 grasses. They identified a large number of candidate genes that evolved under divergent selection, indicating that, besides alterations to expression patterns, the history of C4 involved strong selection on protein-coding sequences.C4 syndrome relies on a series of anatomical and biochemical adaptations that function together to concentrate CO2 in some parts of the leaf .Because each amino acid can be encoded by different nucleotide triplets, some nucleotide changes (substitutions) do not affect the protein. These are synonymous substitutions, while non-synonymous substitutions change the amino acid and so result in a slightly different protein. Under a purely stochastic model, the rates of fixation of these two types of substitutions should be similar and, as such, their ratio (dN/dS) should equal one . Most noet al.: maize (Zea mays), Sorghum bicolor, Setaria viridis , Dichanthelium oligosanthes, Brachypodium distachyon and rice (Oryza sativa). Red branches indicate where the C3 to C4 transitions occurred. Photos courtesy of Pu Huang, James Schnable and Elizabeth Kellogg.Phylogeny of the six species included in the analysis from Huang 4 photosynthesis is not a new idea. The many independent origins of the C4 trait make it particularly amenable to comparative studies, enabling identification of the ecological and physiological changes linked to its evolution , Huang et al. identified 88 genes that evolved under elevated dN/dS on branches belonging to one or several of the C4 lineages. This type of genome scan is inherently subject to false positives. In addition, the methodology cannot strictly differentiate between adaptive evolution and relaxed selection. Finally, the genes might have been under divergent selection along these branches for reasons other than C4 evolution. Fortunately, the putative link with the C4 trait was confirmed for a number of candidates by independent evidence, including a priori knowledge for a few of them and high expression in C4 tissues for many others. The list produced by Huang et al. therefore includes many promising candidates, some of which might be linked to C4 anatomy. If confirmed, their identification would represent a major breakthrough for the engineering of C4 photosynthesis into non-C4 crops. In the short term the results already affect the way we should envision C4 evolution.After screening the genomes of six grasses, including three C4 photosynthesis, the new results show that the modification of promoter sequences and regulatory networks is only one part of the story, which also includes adaptive changes in the coding sequences of a large number of genes. This is impressive, providing even more evidence that the recurrent transition to C4 photosynthesis represents a considerable evolutionary feat. The observations of Huang et al. also reveal a new set of questions; in particular, why did the coding sequences of so many proteins need to be adapted, both in terms of biochemical properties and evolutionary drivers? The biochemical component of this question will remain unanswered until extensive characterization is performed, and yet hints about the evolutionary pressures can already be proposed.For the most part, previous studies have linked phenotypic variation to alterations in gene expression and regulation (4 and non-C4 taxa to the first divergence of two C4 taxa within the same lineage (Box 1). With only six species, this interval is initiated long before the transition to C4 photosynthesis and continues for a long period after C4 evolved, spanning up to 20 million years of changes. As more genomes become available, similar analyses will be able to pin down the timing of these episodes of positive selection with more precision. Until then, we can only speculate.The precise timing of positive selection episodes is beyond the scope of this comparative work because of the limited number of species sampled, which corresponds to the few grasses for which a complete genome is currently available. Indeed, these episodes are inferred along phylogenetic branches that expand from the last divergence of C4 plants were probably spread over long periods of evolutionary time, from the occurrence of capacitating mutations in non-C4 ancestors to changes directly responsible for the emergence of a C4 physiology, and continuous adaptive alterations after its origin (4 cycle in plants with C4-like anatomical traits (4 photosynthesis, and the presence of a working C4 cycle, even if rudimentary, probably created a selective impetus for the fixation of substitutions that improved the C4 syndrome. The genes detected by Huang et al. probably underwent adaptive mutations that improved the fit of the proteins to the new catalytic environment. Their impressive number suggests that the selective pressure for improving the C4 syndrome was very strong or maintained over a long evolutionary period, possibly throughout the diversification of C4 plants.As with any complex trait, the numerous changes that define extant Cs origin . Modelli4 evolution has focused mainly on the events that led to a C4 cycle, largely ignoring those that followed its emergence. The discovery of widespread C4-related selection on coding genes should motivate new research into the changes that contributed to the improvement or diversification of the C4 syndrome. A first step in this direction is to acknowledge the diversity of C4-related traits within each C4 lineage, and design comparative experiments that capture this diversity. With continuous advances in sequencing technology, this goal might soon become achievable for comparative genomics, contributing towards a full elucidation of the changes that were selected, both before and after the first C4 plants emerged.Until now, research on C


Vernonia anthelmintica (L.) remain ambiguous, the herb has been broadly used in Uyghur hospitals to treat vitiligo. The overall objective of the present study aims to identify the potential lead compounds from Vernonia anthelmintica (L.) in the treatment of vitiligo via an oral route as well as the melanogenic mechanisms in the systematic approaches in silico of admetSAR and substructure-drug-target network-based inference (SDTNBI).Vitiligo is a long-term skin disease characterized by the loss of pigment in the skin. The current therapeutic approaches are limited. Although the anti-vitiligo mechanisms of Vernonia anthelmintica (L.) using admetSAR and SDTNBI methods. Among these compounds, Isorhamnetin and Kaempferide, which are methyl-flavonoids, performed 1st and 2nd. Isorhamnetin and Kaempferide significantly increased the expression of melanin-biosynthetic genes  and the tyrosinase activity in B16F10 cells. Isorhamnetin and Kaempferide significantly increased the mRNA-expression of melanin-biosynthetic genes , the protein level of MITF and the tyrosinase activity. Based on the SDTNBI method and experimental verification, Isorhamnetin and Kaempferide effectively increased melanogenesis by targeting the MC1R-MITF signaling pathway, MAPK signaling pathway, PPAR signaling pathway , arachidonic acid metabolism pathway  and serotonergic synapses  in the treatment of vitiligo from a network perspective.The results showed that the top 5 active compounds with a relatively higher bioavailability that interacted with 23 therapeutic targets were identified in Vernonia anthelmintica (L.) by admetSAR and SDTNBI methods.We identified the melanogenic activity of the methyl-flavonoids Isorhamnetin and Kaempferide, which were successfully predicted in a network pharmacological analysis of The online version of this article (10.1186/s12918-017-0486-1) contains supplementary material, which is available to authorized users. Vitiligo is an acquired, progressive depigmentation disorder characterized by the appearance of circumscribed white macules on the skin . ApproxiCurrently, the main purpose of clinical treatment is to increase the melanogenesis of melanocytes in skin lesions and restore skin color to the normal level . SeveralVernonia anthelmintica (L.), which only grows in the high altitude localities in the northwest of China, has been successfully used in the treatment of vitiligo in China [Vernonia anthelmintica (L.), a traditional herb medicine, can treat vitiligo by eliminating abnormal Balgham Hilit (damp and cold) in Uyghur hospitals [Traditional Uyghur Medicine (TUM), particularly in China . Accordiospitals . HoweverRecently, systematic approaches in silico based on network pharmacology have made a significant contribution to disclose the multi-targets of modern medicine through pharmacokinetic evaluation, target prediction and network/pathway analysis . The admVernonia anthelmintica (L.) will provide a novel understanding for vitiligo treatments.The systematic in silico approaches of admetSAR and SDTNBI were employed in the present study. Key molecules were further identified via in vitro methods. The network pharmacological mechanism of The entire pathway-based on SDTNBI and admetSAR methods is illustrated in Fig. Vernonia anthelmintica (L.), all chemicals of Vernonia anthelmintica (L.) were collected from the TCMID database (http://www.megabionet.org/tcmid), the Chinese academy of sciences Chemistry Database (http://www.organchem.csdb.cn) and the TCMSP database (http://ibts.hkbu.edu.hk/LSP/tcmsp.php). All of the compounds collected were normalized to the canonical SMILES format.Based on a review of http://lmmd.ecust.edu.cn/admetsar1/) [TUM has been successfully used via the oral route in the treatment of vitiligo in China. Among the pharmacokinetic properties of ADME, the absorption and metabolism were the most important factors that affected oral bioavailability . A betteetsar1/) . The metetsar1/) .1\documeQ) of each compound, with five major CYP isoforms (index k). The overall predictive accuracies were as follows: CYP450 1A2 Inhibitor (Q = 0.8147), CYP450 2C9 Inhibitor (Q = 0.8018), CYP450 2D6 Inhibitor (Q = 0.8551), CYP450 2C19 Inhibitor (Q = 0.8054) and CYP450 3A4 Inhibitor (Q = 0.6450).Equation  sums thehttp://www.uniprot.org/) as previously described.The targets of the potentially active compounds were predicted using the SDTNBI method, an integrated network and chemoinformatic tool for the systematic prediction of compound-target interactions, particularly new chemical entities . For thihttp://lmmd.ecust.edu.cn/methods/sdtSDTNBI/).The detailed command lines for prediction, cross validation and external validation are presented on our website (http://www.proteinatlas.org/), a database of tissue microarray images labeled with antibodies against 11,250 human proteins [To analyze the target distribution within the keratinocytes and melanocytes, we examined the protein expression data from the Human Protein Atlas database (proteins . We seleVernonia anthelmintica (L.) for vitiligo at a network level, we constructed the compound-target interaction (CTI) network. All active compounds in Vernonia anthelmintica (L.) and their screening targets were utilized to generate a bipartite graph of CTIs, in which a compound and a target are linked with each other if the compound targets the protein or relevant regulators. The bioinformatic functional interaction network analysis of the keratinocyte- and melanocyte-specific targets was determined using the DAVID database (https://david.ncifcrf.gov/home.jsp) [http://string-db.org/) [For the sake of interpreting the therapeutic mechanisms of ome.jsp) . The Prodb.org/) . All visdb.org/) .2 humidified incubator at 37 °C .The B16F10 melanoma cell line was purchased from the Cancer Cell Repository . Cells were cultured in DMEM containing 10% fetal bovine serum and 1% penicillin/streptomycin in a 5% CO5 cells/ml) in 100 μl medium were plated in 96-well microplates. After overnight incubation, 100 μl of different concentrations  of Isorhamnetin and Kaempferide  was added to the well for 24 h. The untreated controls were exposed to fresh medium. Following this, 50 μl 5 mg/ml MTT solution was added to each well and incubated for 4 h. After aspirating the culture medium, the resulting formazan was dissolved with 150 μl dimethylsulfoxide . The plates were then placed on a shaker for 5 min and measured at 570 nm by using a microplate reader .The general viability of the cultured cells was determined through the reduction of 3--2,5-diphenyl tetrazolium bromide (MTT) to formazan . Exponenv/v) was added to 1 mL medium. The optical density (OD) was measured at 405 nm after a calibration curve obtained from a synthetic melanin solution. The cells were collected pelleted and washed twice with PBS . Cells were collected by centrifugation at 5000 rpm for 10 min. After digestion in 1 mL of 1 N NaOH solution for 1 h at 80 °C, the intracellular melanin was measured as described above.The melanin contents were measured in extracellular and intracellular according to a previously described method . The B16Tyrosinase activity was assayed by measuring the L-3,4-dihydroxyphenylalanine (L-DOPA) oxidase activity using a previously described method . The B16-ΔΔCt method. The mRNA expression was normalized using GAPDH as an endogenous control. The amplification was performed for 45 cycles . The primers were synthesized by Sangong Co. Ltd. . The forward and reverse primer sequences were as followed: 5′-GCTAAGGTCAGAGGGAGGGA-3′ and 5′-TCACCATAGAGGCACGAGGA-3′ for MC1R, 5′-CCCGCTTCTGGAAACTTGATCG-3′ and 5′-CTGTACTCTGAGCAGCAGGTG-3′ for MITF, 5′-TGACAAATGGCTGCGAAGGC-3′ and 5′-GGCTTGTTCCAAGTAAGGATC-3′ for TYR, 5′-TCAGGTTTGG GCTCAGTTTC-3′ and 5′-ATGAGCCACAAGGGTCAGTC-3′ for TYRP1, 5′-CGTG CTGAACAAGGAATGC-3′ and 5′-CGAAGGATATAAGGGCCACTC-3′ for DCT, 5′-GGTTGTCTCCTGCGACTTCA-3′ and 5′-TGGTCCAGGGTTTCTTACTCC-3′ for GAPDH.The total cellular RNA was isolated using a commercial kit . RNA quality was tested using the A260/A280 ratio and 1.5% agarose gel electrophoresis. The cDNA synthesis was performed using Moloney murine leukemia virus reverse transcriptase with a First Strand cDNA Synthesis Kit . The cDNA synthesis system was performed according to the manufacturer’s instructions. The abundance of MC1R (241 bp), MITF (414 bp), TYR (223 bp), TYRP1 (116 bp), DCT (132 bp), and GAPDH (183 bp) mRNA in the samples were quantified using SYBR Green-based Rotor-Gene Q  and quantified using the 2Adherent cells were treated with 100 μM 8-MOP and Isorhamnetin and Kaempferide  for 24 h, washed once with DPBS, and lysed with 1% NP-40 buffer  containing 1X protease inhibitors  and 1X phosphatase inhibitors . Lysates were quantified (Bradford assay), normalized, reduced, denatured (95 °C) and resolved by SDS gel electrophoresis on 12% Tris/Glycine gels . Resolved protein was transferred to PVDF membranes  using a Semi-Dry Transfer Cell (Bio-Rad), blocked in 5% BSA in TBS-T and probed with primary antibodies recognizing MITF  and β-Actin . After incubation with the appropriate secondary antibody, proteins were detected using EC3™ 510 Imaging System Manual Platform .P < 0.05 was considered statistically significant. All experiments were done at least 3 times with similar results.All data are expressed as mean ± standard error of the mean (SEM). The means, standard errors, and Student’s t-test results were performed using the SPSS 19.0 for Windows. Vernonia anthelmintica (L.)  and Kaempferide (Score = 1.92963575) using SDTNBI, was related to the positive regulation of the cAMP biosynthetic process and the expression of melanin-biosynthetic genes. Isorhamnetin and Kaempferide along with 17 targets were subsequently used to construct the CTI network  were sorted and could be used as lead compounds in the treatment of vitiligo. To determine whether Isorhamnetin and Kaempferide increased melanin production, Isorhamnetin and Kaempferide were selected for further research.Based on the admetSAR and SDTNBI methods, Isorhamnetin and Kaempferide from The effects of Isorhamnetin and Kaempferide on the viability of B16F10 cells were examined using the MTT assay. Treatment with 8 μM Isorhamnetin and Kaempferide slightly stimulated B16F10 cell viability. Isorhamnetin and Kaempferide were not significantly cytotoxic to B16F10 cells at the concentrations of 16–32 μM for 24 h Fig. .Fig. 3EfTo investigate the effects of Isorhamnetin and Kaempferide on melanin synthesis, B16F10 cells were exposed to Isorhamnetin and Kaempferide in a range from 0 to 32 μM for 24 h. Isorhamnetin significantly increased intracellular and extracellular melanin synthesis in a dose-dependent manner Fig. . KaempfeAs Isorhamnetin and Kaempferide increased melanin synthesis, we further explored whether Isorhamnetin and Kaempferide affected tyrosinase activity, the expression of melanin-biosynthetic genes  and the protein level of MITF. Our data showed that Isorhamnetin and Kaempferide significantly increased tyrosinase activity in a dose-dependent manner Fig. . The mRNVitiligo is the most common depigmentation skin disorder. It is caused by dysfunction or destruction of melanocytes, which are the main pigment-producing cells . AlthougVernonia anthelmintica (L.). It has been reported that Vernonia anthelmintica (L.) injection has a significant therapeutic effect on vitiligo [Vernonia anthelmintica (L.) has been identified to enhance melanin synthesis by activating the p38 MAPK signaling pathway in B16F10 cells and primary melanocytes [Vernonia anthelmintica (L.) could promote melanogenesis, the key active compounds had not been investigated in depth. This issue hindered the modernization development of Vernonia anthelmintica (L.) for the treatment of vitiligo.TUM has been successfully used for the treatment of vitiligo in China, particularly vitiligo . Moreoveanocytes , 28. AltThe admetSAR will be helpful for the in silico sorting of ADMET profiles of drug candidates and environmental chemicals. The admetSAR integrated high quality and predictive QSAR models to predict approximately 50 ADMET end-points, including HIA and Caco-2 permeability (Caco-2), as well as the inhibitors of CYP450 1A2, CYP450 2C9, CYP450 2C19 and CYP450 3A4. The area under the receiver operating characteristic curve (AUC) was used to evaluate the reliability of the predictions of 22 classification models via 5-fold cross validation .score could be used as potential lead compounds in treatment. These top 5 active compounds included Isoliquiritigenin, Apigenin, Liquiritigenin, Kaempferide and Isorhamnetin. Among these compounds, Kaempferide and Isorhamnetin, which are methylated flavones, exhibited the best parameters in absorption and metabolism. Dr. Thomas Walle has also proved that methylated flavones had substantially higher metabolic stability than those of the unmethylated forms [Using admetSAR, the top 5 active compounds with positive absorption and a higher ed forms . TherefoIn the early work of Si et al., Isorhamnetin (0–1500 μM) showed depigmentation activity via a biochemical tyrosinase-inhibitory experiment and a computational simulation approach . HoweverOur pharmacological data in vitro showed that both Isorhamnetin and Kaempferide significantly increased the mRNA-expression of melanin-biosynthetic genes , as well as the protein level of MITF and the tyrosinase activity. All results supported the melanogenesis activity of Isorhamnetin. However, the melanogenic mechanisms of Isorhamnetin and Kaempferide have not yet been reported.As a result of the rapid development of network pharmacology, the identification of new drug-target interactions (DTIs) will help investigators understand the molecular mechanisms of drugs and identify new uses for old drugs –34. The Based on the SDTNBI method and experimental verification, Isorhamnetin and Kaempferide effectively increased melanogenesis by targeting the MC1R-MITF signaling pathway, MAPK signaling pathway, PPAR signaling pathway , arachidonic acid metabolism pathway  and serotonergic synapses . We were more concerned that the MC1R activated adenylate cyclase and increased the cAMP level. Moreover, the secondary messenger cAMP activated a cascade of downstream transcriptional events, which led to the expression of melanin-biosynthetic genes  . The expVernonia anthelmintica (L.) for the treatment of vitiligo. Compared with traditional experimental assays, the systematic in silico approaches of admetSAR and SDTNBI have enabled us to rapidly identify potential lead compounds and CTIs. Further studies are required to validate whether the active compounds promote melanogenesis in vivo.The melanogenic pathway based on the admetSAR and SDTNBI approaches was developed to identify the network pharmacological mechanisms of Vernonia anthelmintica (L.) for vitiligo treatments in silico and in vitro, which provides a novel understanding of TUM for the treatment of vitiligo.In summary, the admetSAR and SDTNBI methods were combined to disclose the complex network pharmacological mechanism of Additional file 1: Table S1.Vernonia anthelmintica (L.). (DOC 54 kb)Chemical properties of 48 compounds from Additional file 2: Table S2.Vernonia anthelmintica (L.) via admetSAR Prediction. (DOC 166 kb)The ADME properties in silico of 48 compounds from Additional file 3: Table S3.The Compounds-Targets interaction information based on SDTNBI method. (DOC 1319 kb)Additional file 4: Table S4.The information of tissue-specific targets. (DOC 144 kb) (DOC 144 kb)Additional file 5: Table S5.The pathway analysis of 72 candidate targets via DAVID database. (DOC 51 kb)Additional file 6: Figure S1.STRING identified a large potential interaction network between 56 vitiligo risk genetic loci and Isorhamnetin/Kaempferide with 13 common targets. The purple nodes represent the targets predicted by SDTNBI. The yellow nodes are closely related to vitiligo risk genetic loci. (TIFF 458 kb)Additional file 7: Figure S2.Computational Docking Simulations of Binding between Tyrosinase structure and Isorhamnetin/Kaempferide/8-MOP. The three different crystal structures  were used to simulate the 3D tyrosinase structure. The Yellow dotted line represented possible hydrogen-bonding interactions of Isorhamnetin/Kaempferide/8-MOP by the software SYBYL-X 2.0. (TIFF 1550 kb)


However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled  As sequencing costs continue to decrease , it is nNatural product chemists often desire to sequence biosynthetic pathways for a number of interconnected reasons. The most basic motivation is perhaps the gleaning of structural information from sequence data. In particular, absolute stereo-configuration can be predicted from the sequence of modular pathways such as polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) systems . Such anNotably, shotgun (random) sequencing campaigns generally associated with cluster identification often unearth much more data besides the sequence of a single pathway. These data can include the entire genome of the producing organism. In the case of metagenomics projects, the genomes of other co-localized species often complicate or obscure the specific pathway of interest. Nevertheless, this information can tie primary  and secoFor these and other reasons, there is currently a great deal of interest in the application of “omics” technologies in the natural products field. Rather than exhaustively covering all “omics” work related to natural products, we concentrate herein on the limitations of current methods and the caveats in data analysis that researchers embarking on sequencing projects need to be aware of when designing experiments and analyzing acquired sequence data. We also discuss some biological, evolutionary, and ecological factors warranting consideration throughout the course of sequencing projects.The genes driving microbial secondary metabolism are typically, but not always, clustered; genes involved in the biosynthesis, modification, transport, and regulation of a particular metabolite are generally adjacent to one another on the chromosome. These biosynthetic gene clusters (BGCs) are often complex and can be larger than 100 kilobases with numerous operons under tight regulatory control. The evolutionary mechanisms that drive gene clustering observed within BGCs remain unclear. One prevailing hypothesis suggests that genes conveying a fitness benefit  will tend to cluster over evolutionary timeframes due to the importance of their “teamwork”  in generBGCs are widely distributed among microbes ,19,28,29Streptomyces sp., BGC variations from strain to strain include functional domain exchanges (dehydratase-ketoreductase units) as well as losses and gains (ketoreductases)  experiment). However, as mentioned above, one must carefully design the PCR experiment to give a unique and diagnostic amplicon, lest the result be unwittingly ambiguous, similar to an HMBC peak where both carbon and proton signals overlap with other parts of the molecule. cis-AT PKS systems, enabling facile prediction of the 2D structure of intermediates that are covalently attached to the PKS/NRPS. The structures of starter and extender units can be predicted from sequence analysis of acyltransferase (AT) [trans-AT PKS pathways, where inactive domains, module “skipping” and noncanonical domain orders and locations are common [Although more repetitive in their sequence composition, if NRPS and type I PKS pathways can be adequately (and accurately) assembled, certain useful aspects of product structure can be predicted from these modular pathways. Both of these types of pathways contain large proteins with multiple enzymatic domains, which act like assembly lines and have been extensively reviewed elsewhere ,158. In ase (AT) ,160,161 ase (AT)  domains e common ,163 presde novo from pathways. For instance, the identification of a RiPP pathway for the biosynthesis of the patellamides was inspired by the discovery of a precursor peptide gene containing amino acids in an order consistent with the generation of biosynthetic precursors for patellamides A and C [type of post-PKS or post-NRPS tailoring reactions that occur from the presence of certain genes in the pathway, but the nature and location of these reactions are often elusive.Despite the useful information provided by genomic analysis and the interesting parallels to chemical analysis, there remain key limitations of structural prediction from biosynthetic pathways. Therefore, it is much easier to assign a biosynthetic pathway (from a list of possible candidates) to a known natural product rather than to predict natural product structures  A and C . Conversde novo BGC analysis, there are a number of studies in the natural products realm demonstrating the balance of computational analysis and experimental design to overcome such challenges. For the purposes of brevity and clarity, we highlight here two studies relevant to marine natural products. Despite the many challenges associated with Ca. E. sertula”, from the metagenome of its bryozoan host, B. neritina. A large section of the bry pathway for the biosynthesis of bryostatins had been sequenced through clone library methods by the Sherman and Haygood groups [Ca. E. sertula” was separately found to co-localize with the bry pathway, suggesting that the pathway belonged to this symbiont [One such recent example was the targeted assembly of the genome of the uncultured, bryostatin-producing symbiont, “d groups ,97. Thissymbiont . Later, symbiont . bry pathway, it was similarly challenging to reconstruct with de novo assembly using Illumina reads [de novo assembly from the shotgun sequencing of B. neritina ovicells produced a different arrangement of the bry pathway than was reported by Sudek et al. [bry pathway suggested by the Sanger sequencing of individual clones [Due to the large exact repeats in the na reads . The firk et al. . Howeverl clones ,97 was vl clones ,124. Botl clones , and onlde novo assembly. Although untargeted sequencing and de novo assembly can present ambiguous or misleading results without proper scrutiny, they also have the potential to uncover new genomic content that would be unseen in reference-based methods and difficult to identify using traditional clone-library methods, due to fragmentation across the chromosome. In addition, because a shotgun sequencing and de novo assembly approach was employed in the study of “Ca. E. sertula”, previously missing components of the bry pathway, as well as a number of deficiencies in the symbiont’s primary metabolism, were successfully identified [This experience highlights the importance of implementing both computational and experimental methods to scrutinize and validate the arrangement of biosynthetic pathways generated via entified .slm pathway, in the Salinispora tropica genome, represents an early and exemplary case of integrating genomic and chemical analysis to simultaneously resolve repeat-laden biosynthetic architecture and its encoded chemical structure. In 2007, Udwary et al. assembled the S. tropica genome and discovered the broad array of biosynthetic potential it contained [slm pathway [J-based NMR analysis [trans-double bonds likely to have very similar proton and carbon chemical shifts. The ontained . One maj pathway ,166. Eluanalysis , but theanalysis  and isolslm BGC, this resolution represents an impressive achievement. However, such genomic analysis would likely not have been possible if the S. tropica had not been isolated and cultured in laboratory settings. This caveat invites an interesting question: is it possible to assemble de novo a BGC of slm’s length and sequence composition using current short read technology available for metagenomic analysis? How could various sequencing parameters be tuned to improve the de novo assembly of such a BGC? In the end, the authors were able to integrate spectroscopic and bioinformatic analyses to elucidate both the chemical structure of the salinilactams and the arrangement of the lengthy BGC encoding them ,166. Thede novo assemblies and BGCs in particular. To explore these effects, we simulated Illumina HiSeq shotgun sequencing data with Art Illumina  and Pacimulator ), focusical data ,166  and higher depths of sequencing (100×), the agmented , especia pathway . Thus, wf 275 bp . However pathway . Further may actually be counterproductive if not explicitly handled using specialized assembly algorithms ,172, duede novo assembly process. The perspectives outlined here are intended to highlight the importance of leveraging all available tools, be they computational or experimental, at researchers’ disposal to interrogate the results of this process. Ultimately, we were not able to assemble the slm BGC using any feasible combination of read length, sequencing depth, or fragment size on a simulated Illumina HiSeq platform, which remains the most relevant platform for de novo metagenomic assembly. The best combination of parameters for Illumina simulation alone was a read length of 125 bp, 100× coverage, and a fragment size of 275 bp . There are a number of problems that do not yet have completely generalizable solutions in BGC analysis and metagenomics. A fundamental problem is that total structure prediction from cluster sequence is not yet possible; this clearly complicates the task of genome mining. Efforts have been made to collate and standardize the annotation of BGCs , which cactoring  to provi


Schizosaccharomyces pombe 5’-to-3’ DNA helicase Pfh1 is known to promote fork progression, its genomic targets, dynamics, and mechanisms of action are largely unknown. Here we address these questions by integrating genome-wide identification of Pfh1 binding sites, comprehensive analysis of the effects of Pfh1 depletion on replication and DNA damage, and proteomic analysis of Pfh1 interaction partners by immunoaffinity purification mass spectrometry. Of the 621 high confidence Pfh1-binding sites in wild type cells, about 40% were sites of fork slowing (as marked by high DNA polymerase occupancy) and/or DNA damage (as marked by high levels of phosphorylated H2A). The replication and integrity of tRNA and 5S rRNA genes, highly transcribed RNA polymerase II genes, and nucleosome depleted regions were particularly Pfh1-dependent. The association of Pfh1 with genomic integrity at highly transcribed genes was S phase dependent, and thus unlikely to be an artifact of high transcription rates. Although Pfh1 affected replication and suppressed DNA damage at discrete sites throughout the genome, Pfh1 and the replicative DNA polymerase bound to similar extents to both Pfh1-dependent and independent sites, suggesting that Pfh1 is proximal to the replication machinery during S phase. Consistent with this interpretation, Pfh1 co-purified with many key replisome components, including the hexameric MCM helicase, replicative DNA polymerases, RPA, and the processivity clamp PCNA in an S phase dependent manner. Thus, we conclude that Pfh1 is an accessory DNA helicase that interacts with the replisome and promotes replication and suppresses DNA damage at hard-to-replicate sites. These data provide insight into mechanisms by which this evolutionarily conserved helicase helps preserve genome integrity.Replicative DNA helicases expose the two strands of the double helix to the replication apparatus, but accessory helicases are often needed to help forks move past naturally occurring hard-to-replicate sites, such as tightly bound proteins, RNA/DNA hybrids, and DNA secondary structures. Although the  Progression of the DNA replication machinery is challenged in every S phase by active transcription, tightly bound protein complexes, and formation of stable DNA secondary structures. Using genome-wide analyses, we show that the evolutionarily conserved fission yeast Pfh1 DNA helicase promotes fork progression and suppresses DNA damage at natural sites of fork pausing, which occur at “hard-to-replicate” sites. Our data suggest that Pfh1 interacts with the replication apparatus. First, mass spectrometry revealed that Pfh1 interacts with many components of the replication machinery. Second, Pfh1 and the leading strand DNA polymerase occupy many common regions genome-wide, not only hard-to-replicate sites, but also sites whose replication is not Pfh1-dependent. The human genome encodes a Pfh1 homolog, hPIF1, and contains all of the same hard-to-replicate features that make fission yeast DNA replication dependent upon Pfh1. Thus, human cells likely also require replicative accessory DNA helicases to facilitate replication at hard-to-replicate sites, and hPIF1 is a good candidate for this role. S. pombe provide genetically tractable systems to identify and characterize genes with important roles in genome preservation whose human orthologs might have similar functions.Faithful and efficient replication of the genome is essential in every cell cycle, yet there are many naturally occurring obstacles that impede fork progression. These sites include stable protein complexes, DNA secondary structures, and ongoing transcription, each of which can challenge replication fork progression. Failure to circumvent these obstacles can cause DNA double strand breaks (DSBs) that impair genome integrity and increase the risk of cancer and other disorders that are associated with genome instability. As many of the proteins involved in DNA replication are highly conserved, model organisms such as Escherichia coli DnaB and the eukaryotic hexameric MCM complex, are required to unwind the double helix to allow DNA polymerases access to the replication template. In addition, accessory helicases, such as the E. coli rep, dinG and UvrD proteins help the polymerase maneuver past protein complexes, RNA transcripts, and other naturally occurring impediments . On. On39]. We also determined the degree of overlap between Cdc20 and γ-H2A peaks in Pfh1-depleted cells. Of the 582 γ-H2A peaks in Pfh1-depleted cells, 71% (411) also had high Cdc20 occupancy; this number is significantly more than expected by chance (p < 0.001). γ-H2A sites that were high occupancy for both γ-H2A and Cdc20 were enriched for multiple genomic features including 5S rRNA and tRNA genes, origins of replication, meiotic DSB hotspots, 3’ and 5’ UTRs, and promoters . This strain also expressed Cdc20-3HA from its endogenous location.Our data indicate that Pfh1 promotes replication and suppresses DNA damage at many discrete sites in the genome. We considered two models to explain this pattern of Pfh1 action. First, Pfh1 could act by binding nearby the replisome and mitigating replication obstacles as the replisome moves past Pfh1-sensitive sites. Alternatively, Pfh1 could be recruited only to sites that are hard to replicate or to stalled replication forks. In that case, Pfh1 would have low or no binding to sites that are Pfh1-insensitive. To distinguish between the two possibilities, we used ChIP-qPCR to monitor association of Pfh1 and Cdc20 in synchronized cells. For these experiments, we used a Cells were arrested in G2 phase by incubation at the non-permissive temperature (37°C) and then released at permissive temperature (25°C). The position in the cell cycle and the quality of the synchrony were determined by FACS analysis . To deteIf Pfh1 were nearby or associated with the replisome, Pfh1 and Cdc20 would have similar temporal patterns of binding to the three origins and their adjacent sites. If Pfh1 were recruited only to hard-to-replicate sites, then Cdc20 and Pfh1 would have different binding patterns. In fact, under the second model, Pfh1 should not bind to any of these sites, as none of them were Pfh1-dependent in the whole genome analysis. Consistent with the first model, Cdc20 and Pfh1 displayed similar association patterns at all three origins and their adjacent regions . We firsNext, we examined the binding of Pfh1 and Cdc20 to the four other Pfh1-insensitive sites ars2004, ars2004_30kb, ars3005, and ars3005_26kb. Pfh1 bound to all these four regions, similarly to Cdc20 . HoweverGLU.05 and tRNAASN.05) and one Pfh1-insensitive site 6 kb away from tRNAASN.05 (tRNAASN.05_6kb).Because the dynamics of Pfh1 and the replisome were not clear from the above experiments, we further investigated the binding pattern of Pfh1 and Cdc20 at five other regions, including both Pfh1-sensitive and Pfh1-insensitve sites . We testAt all five regions, both Pfh1 and Cdc20 had peak binding at 95 min after release from the G2 arrest, which by FACS analysis is mid-S phase . To detein vivo with known replisome subunits. To address this possibility, we used immunoaffinity purification mass spectrometry (IP-MS) to identify the Pfh1 protein interactions in S phase cells  algorithm . Br. Br34]. cdc25-22 strains were grown to early mid-log (0.5 x 107 cells/ml) at the permissive temperature of 25°C. The cells were collected by filtration and shifted to 37°C for G2 arrest. After 4 hours of incubation at 37°C, the media was quickly cooled (2 minutes by swirling in an ice bath) to 25°C for synchronized growth. Cells harvested at the G2 time point were collected at the end of the 4 hour 37°C incubation. Cells harvested at the S phase time point were collected at 84 minutes, corresponding to the start of replication. Cell cycle progression and the timing of DNA replication were confirmed by FACS analysis. Strains expressing either Pfh1-GFP (yKM333) or GFP alone (yKM346) from the S. pombe leu1-32 locus in a strain background containing the cdc25-22 mutant were confirmed to progress normally through the cell cycle by FACS analysis.For cell synchronization, S. pombe cells were either synchronized or grown to mid-log and harvested by centrifugation at 4°C for 10 minutes at 4,000 rpm . Cell pellets were resuspended in freezing buffer , pH 7.4 containing a protease inhibitor cocktail (v/v 1/100) (Sigma) and frozen as cell droplets in liquid nitrogen [4, 1mM DTT, protease inhibitor cocktail (Roche) in a ratio of 5ml of lysis buffer per 1 gram of cells. Cells were gradually added to the lysis buffer with continuous mixing to avoid cell clumps. Lysis buffer conditions of varying salt concentrations (50–900 mM potassium acetate) were optimized for efficiency of Pfh1-GFP purification. Cell lysate was homogenized using a PT 10–35 Poyltron (Kinematica) for 3 sets of 10 seconds  with 1 minute on ice in between each set. Insoluble material from the cell lysate was removed by centrifugation at 8000 rpm (9265 x g) for 10 minutes at 4°C. For immunoaffinity purification of Pfh1-GFP, the cell lysate supernatant was incubated for 30 minutes at 4°C with approximately 20 mg of M-270 epoxy magnetic beads  conjugated with 50 μg of in-house developed rabbit polyclonal anti-GFP [Two liters of nitrogen . Frozen anti-GFP . FollowiTo determine if DNA mediates the interactions of Pfh1-GFP, chromosomal DNA of the cell lysate was incubated with an excess of DNaseI  during the IP experiment immediately before the addition of conjugated beads . DNaseI 2 fragmentation of the top 20 most intense precursor ions by collision-induced dissociation (CID). Parameters for data processing were also followed as described previously [2 data were extracted by Proteome Discoverer  and uploaded to SEQUEST (version 1.20) and searched against a compiled database of the yeast protein sequences from S. cervisiae and S. pombe. Post-search validation of the SEQUEST data was conducted by an X! Tandem algorithm in Scaffold  using the following filter selections to reduce peptide and protein global false discovery rate to < 1%: 99% protein confidence, 95% peptide confidence, and a minimum of two unique peptides per protein.Following immunoaffinity purifications (n = 2) of Pfh1-GFP or NLS-GFP from S phase cells, the isolated protein complexes were separated by gel electrophoresis. Samples were digested in-gel with trypsin and peptides were extracted from gel pieces using 0.5% formic acid. Peptides were concentrated by vacuum centrifugation to approximately 12 μl. 4uL of the sample was injected for nanoscale liquid chromatography tandem mass spectrometry (nLC-MS/MS) analysis on a Dionex Ultimate 3000 RSLC directly coupled to an LTQ-Orbitrap Velos with (ETD (ThermoFisher Scientific) instrument. Data were automatically acquired with MSeviously . Brieflysignificance analysis of interactome) algorithm [Protein interactions were accessed for specificity and enrichment (Pfh1-GFP vs. NLS-GFP control) using the SAINT (lgorithm . A SAINTS. pombe (pax-db.org), and the NSAF/PAX ratio was mapped onto each node (node color).The protein interaction partners of Pfh1 were placed in the context of known protein interaction data from STRING   and visuS1 Fighsp90+, tdh1+, adh1+, hta1+, and ade6+. Data are shown as immunoprecipitated DNA divided by input DNA. Data represent the mean of three independent replicates and error bars are standard deviation. The p-value was determined by two-tailed Student’s t-test and “*” indicates p < 0.05.Samples from asynchronous cells either expressing Pfh1-13Myc or an untagged control were chromatin immunoprecipitated using an anti-Myc antibody. Data for Pfh1-13Myc were also shown in (PDF)Click here for additional data file.S2 Fig(A) Scatter plot comparing Cdc20 peak strength ) at G4 motifs in WT and Pfh1-depleted cells. Each point represents a genomic region with a Cdc20 occupancy peak in at least one context. If a peak was not present in a context, it is plotted at 0 on the corresponding axis. The number in the bottom right of each plot gives the percentage of peaks stronger in Pfh1-depleted cells. (B) Scatter plot comparing γ-H2A peak strength at G4 motifs in WT and Pfh1-depleted cells. The layout is the same as in part (A).(PDF)Click here for additional data file.S3 FigDetails are as in (PDF)Click here for additional data file.S4 FigDetails are as in (PDF)Click here for additional data file.S5 FigImmunoaffinity-purification of Pfh1-GFP from asynchronous cells. Proteins were resolved by SDS-PAGE and visualized by Coomassie stain. Peptides of identified proteins were confirmed by MS with nanoLC LTQ Orbitrap CID analyses. Pfh1 interaction was observed with proteins involved in DNA replication and repair such as the replicative DNA polymerase Pol2, members of the replicative Mcm helicase complex, and the Ku70/Ku80 heterodimer required for DNA repair and telomere maintenance in eukaryotic cells.(PDF)Click here for additional data file.S6 Fig(A) Proteins were resolved by SDS-PAGE and visualized by Coomassie stain. (B) Ethidium bromide stained agarose gel of precipitated DNA from an aliquot of the cell lysate before and after DNAseI treatment (lanes 1 and 2) and with the addition of plasmid DNA (lanes 3 and 4) as a control for DNase I activity in the experimental lysis buffer.(PDF)Click here for additional data file.S7 Fig(A) Fraction of Pfh1-bound features of a given type that overlap Pfh1-bound instances of each other tested feature type. (B) Fraction of Pfh1-sensitive (in terms of Cdc20) features of a given type that overlap Pfh1-bound instances of each other tested feature type. In each panel, the fraction is given in terms of the y-axis feature. For example, the 0.09 in the second entry in the first row of (A), indicates that 9% of the Pfh1-bound 3’ UTRs overlap a Pfh1-bound 5’ UTR.(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S9 Table(DOCX)Click here for additional data file.


N = 114) were invited to complete a 22-item computerized, anonymous survey 6 months before and 6 months after asthma pathway implementation. The survey assessed pathway use and residents (1) pathway knowledge, (2) attitudes and experiences with managing asthma, and (3) perceived educational benefits. Mean pathway knowledge score increased from the case before to the case after implementation , as did high preparedness to manage asthma  and electronic order set use . The top three educational benefits of the pathway endorsed by residents were application of evidence-based medicine (57%), ability to assess exacerbations (52%), and skill at communicating respiratory status (47%). After implementation, residents' knowledge and preparedness to manage asthma improved as well as many endorsed educational benefits.Clinical pathways for asthma management decrease hospital cost and length of stay; however little is known about the educational impact of pathways on residents. Pediatric residents at a children's hospital ( Asthma is a chronic respiratory condition that affects more than six million children and adolescents in the United States and is one of the most common causes of childhood disability . Acute, In response to the high numbers of children with asthma-related hospitalizations and as recommended by national guidelines, many children's hospitals have developed clinical pathways for asthma management . ClinicaClinical pathways guide clinicians towards practicing the most up-to-date evidence-based medicine informed by national guidelines. Barriers to adherence to clinical guidelines may be related to lack of awareness, familiarity, and institutional policies as well as inertia and resistance to change . SimilarA main criticism of clinical pathways used in children's hospitals is that they reinforce “cookbook medicine,” making physicians into technicians by limiting critical thinking, raising concerns that trainees may have negative reactions . On the With permission from the residency training program director, we conducted a prospective survey study of pediatric residents' knowledge, attitudes, and satisfaction with an inpatient clinical asthma management pathway before and after implementation at the Children's Hospital at Montefiore (CHAM), located in Bronx county, NY. This is a low income, urban county with a population of 1.4 million and with rates of asthma-related hospitalizations and deaths about five times and three times higher, respectively, than the national average . CHAM adhttps://SurveyMonkey.com, LLC, Palo Alto CA) in 2014-2015. Trainees were assured that their responses were anonymous and would not impact performance evaluations. As an incentive, respondents were eligible to win one of three $50 Amazon.com gift cards using the software's raffle feature. The study was approved by the Einstein/Montefiore Institutional Review Board.An interdisciplinary committee, with physician expertise in Adolescent Medicine, Pediatric Hospital Medicine, Pediatric Pulmonary Medicine, Emergency Medicine, and Pediatric Critical Care and representation from nursing, pharmacy, respiratory therapy, and pediatric chief residents, was convened in 2014 to create the CHAM inpatient asthma pathway and associated care tools including a respiratory scoring system, an asthma action plan, and a patient education video. Implementation also included an updated electronic asthma order set . This care bundle reflected updated clinical guidelines on asthma management. Three months prior to pathway implementation in 2014, residents attended an educational conference introducing the pathway, explaining the development of the pathway, patient inclusion and exclusion criteria, the use of a respiratory score, and the updated evidence-based management recommendations. Those residents who were unable to attend the seminar were given an introductory written presentation for which they were required to affirm their review. Two additional educational seminars reinforcing the pathway were conducted one month before and after implementation. Materials outlining the pathway and associated care tools were disseminated electronically, through printed posters and cards, as well as through a resource link in the electronic ordering system. The survey was administered 6 months before and 6 months after implementation of the pathway using Survey Monkey software  for the presurvey and 60/114 (53%) for the postsurvey, with no differences by postgraduate training year. Of the postimplementation respondents, 32/60 (53%) reported having attended an educational seminar introducing the pathway. All of the residents who did not attend a seminar affirmed their review of the content of the seminar that was electronically distributed to them.Pediatric residents' experiences with asthma management using the pathway and support tools are shown in p < 0.001]. The highest prescore was 4 and the highest postscore was 6. Pathway scores were not higher in those respondents who attended an in-person educational seminar introducing the pathway. Importantly, more residents reported feeling well prepared to manage acute asthma presentations without supervision  after pathway implementation. Overall, after implementation, 54% of the respondents reported satisfaction with the management pathway.Mean pathway knowledge score (maximum score = 8 correct) was low but increased from the case before to the case after asthma pathway implementation [1.5 ± 1.0 versus 2.6 ± 1.3, p < 0.05). We found no difference before and after implementation in respondents' reported likelihood of practicing evidence-based medicine or their agreement that pathways hinder resident autonomy.Respondents' attitudes about the pathway's influence on resident education were generally positive both before and after pathway implementation. However, more respondents agreed that pathways did not hinder resident education after implementation compared with the case before implementation ; ability to clinically assess exacerbations (52%); and skill at communicating respiratory status (47%). The top 5 barriers to pathway use were disagreement with the content of pathway management (54%); forgetting to use it (50%); lack of education of ancillary staff (50%); lack of access to pathway for reference (24%); and lack of education on pathway use (24%). There was no association between those respondents who cited a lack of education on the pathway use and those who attended an in-person educational seminar introducing the pathway.This study is the first study, to our knowledge, to explore the effects of implementing a clinical asthma management pathway on pediatric resident education and comfort with asthma management. We found that after pathway implementation, residents' knowledge and comfort managing asthma improved, while their overall attitudes towards clinical pathways remained positive. This contradicts previously published opinions highlighting concerns that clinical pathway management tools hinder resident education and provides evidence for using such tools to enhance pediatric education .In keeping with Kirkpatrick's evaluation hierarchy theory, our study has taken a multilevel approach in evaluating pathway implementation as an educational training tool, with a positive reaction as shown by pathway satisfaction, an educational benefit as demonstrated by the increase in knowledge scale as informed by the pathway, and, finally, an impact on changing behavior through the reported use of the pathway and associated care tools . Based oA study of pediatric residents conducted about 10 years prior to this study at an academic ambulatory care center in Bronx county demonstrated low competency among pediatric residents in classifying asthma severity, which is the first step towards evidence-based asthma management . MasteriTraining in a large urban children's hospital exposes residents to a high-volume learning environment. Implementing a clinical pathway in this environment allows for up-to-date evidence-based practice that may improve future patient care as residents complete their training and graduate to practice in both inpatient and outpatient settings. Notably, our trainees' knowledge of inpatient asthma management as reflected by their low mean knowledge scores was suboptimal prior to the asthma management pathway implementation, with a significant improvement after implementation. Despite improvement, the mean scores were still low 6 months after implementation, suggesting that adoption and integration of the new clinical pathway into knowledge and practice may take longer than 6 months.Implementation of the clinical asthma management pathway was successful, with high pathway use reported by residents 6 months after implementation. However, there were notable barriers to pathway use. We were surprised to learn that the number one barrier to pathway use  was disagreement with pathway management and that one-quarter of respondents reported lack of education on pathway use as a barrier. We hypothesize that our pediatric resident respondents experienced discomfort in changing practice in areas where the pathway introduced updated practice management steps. For example, the pathway increased the standard dose of albuterol from 2.5 mg (nebulized) to 5 mg (nebulized), which was a new change from current practice at the institution. Also new to the current standard practice was the fact that the pathway also encouraged the use of metered dose inhalers in hospital settings and gave dosing suggestions for this as well alongside the nebulized doses as an alternative. This highlights an increased need for evidence-based management and further supports the importance of ongoing education of pediatric residents using the literature that provided the evidence for the changes in management.This study has several limitations. The study was conducted at a single children's hospital. However, our pediatric residency program is similar to those at other large urban, academic children's hospitals in cities with high asthma prevalence rates. In addition, the postimplementation survey was completed 6 months after implementation, and it may take longer to fully institutionalize a new clinical pathway. Lastly, it is inherent in residency training programs that over time a trainee gains knowledge and comfort in managing asthma, and our study was unable to control for this factor. To best address this, we specifically assessed knowledge by asking questions informed by the pathway and that highlighted changes in clinical practice rather than general knowledge about asthma classification and management.The findings of this study highlight the educational benefits of a new clinical asthma management pathway for pediatric residents at an urban, academic children's hospital serving a community with rates higher than national asthma prevalence and hospitalization ones. We found that the majority of pediatric residents report using the pathway and they were satisfied with the pathway. Importantly, trainees' comfort and knowledge in managing asthma using management steps that are informed by updated clinical guidelines were improved, which is an educational goal in residency training programs. Attitudes towards clinical pathway use were high before and after implementation, encouraging further exploration on expanding the use of clinical pathways in academic training institutions.


Genome-wide association studies have confirmed the polygenic nature of schizophrenia and suggest that there are hundreds or thousands of alleles associated with increased liability for the disorder. However, the generalizability of any one allelic marker of liability is remarkably low and has bred the notion that schizophrenia may be better conceptualized as a pathway(s) disorder. Here, we empirically tested this notion by conducting a pathway-wide association study (PWAS) encompassing 255 experimentally validated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways among 5033 individuals diagnosed with schizophrenia and 5332 unrelated healthy controls across three distinct ethnic populations; European-American (EA), African-American (AA) and Han Chinese (CH). We identified 103, 74 and 87 pathways associated with schizophrenia liability in the EA, CH and AA populations, respectively. About half of these pathways were uniquely associated with schizophrenia liability in each of the three populations. Five pathways  were shared across all three populations and the single-nucleotide polymorphism sets representing these five pathways were enriched for single-nucleotide polymorphisms with regulatory function. Our findings provide empirical support for schizophrenia as a pathway disorder and suggest schizophrenia is not only a polygenic but likely also a poly-pathway disorder characterized by both genetic and pathway heterogeneity. Thus, identifying schizophrenia-associated SNPs that are generalizable to diverse populations of people with the disorder is unlikely and suggests alternative approaches at identifying genetic markers of schizophrenia liability are needed.Schizophrenia is a severe psychiatric disorder characterized by significant genetic heterogeneity and is commonly referred to as a polygenic disorder.3 whereby one or a number of SNPs within a pathway could result in an increased liability to schizophrenia by altering sensitivity to environmental insults and/or disruption of brain development. In the context of schizophrenia, this pathway approach has been applied in a variety of forms ranging from pathway clustering analysis,4 where SNPs in key genes within a single pathway are examined, to post-hoc pathway enrichment analyses of candidate SNP-sets using the SNP ratio test5 or bioinformatics resources .8 These approaches undoubtedly have a pathway focus but provide an incomplete examination of the compendium of known human biological pathways. Our primary aim was to conduct a comprehensive pathway-wide association study (PWAS) of schizophrenia. Here, we report results of that analysis in which we tested 255 biological pathway-based SNP-sets for their association and potential function in schizophrenia in three ancestral distinct populations.One such approach is to examine SNPs within the biological pathway(s) in which they reside. Underlying this approach is the notion that schizophrenia is a pathway(s) disorder,n=5033) and healthy controls (n=5332) across three distinct ethnic populations; European-American (EA) , Han Chinese (CH)  and African-American (AA)  were obtained . CH GWAS data were collected from multiple collaborating hospitals included in the Chinese Schizophrenia Collaboration Group  and the other a validation dataset .GWAS data from individuals with schizophrenia . A mega KEGG pathway  that encompasses several other pathways was excluded, leaving 300 pathways available for further analysis.SNPs surviving quality control were mapped to gene loci using the annotation provided by the National Center for Biotechnology Information (see 14 For each pathway the discovery dataset for the EA and CH cohorts as well as the single dataset available for the AA cohort were randomly split (maintaining the case:control ratio of the full dataset) 100 times into two subsets, a SNP  selection set (80% of the participants) and a test set (20% of participants). Within each SNP selection set, 80% of participants were randomly selected 10 times (maintaining the case:control ratio of the full dataset) and the resulting subsets were subjected to the maximum relevance minimum redundancy (mRmR) feature selection procedure  using 80% of the discovery dataset followed by testing of the classifiers in the remaining 20% of the discovery dataset. To address inherent imbalances in the case:control ratios of our datasets, under-sampling of the majority class (cases or controls) of each dataset was employed before running the random forest algorithm, as this strategy has previously been shown to be useful for classification in the presence of imbalanced classes.P-values for each of the 255 pathways were generated by comparing the mean OR (based on 100 iterations) from the independent  dataset with the corresponding mean OR from the permutation dataset using a t-test. The Benjamini–Hochberg (BH) procedure was used to adjust for multiple comparisons.18 Furthermore, using the independent validation dataset for the EA and CH cohorts, we calculated the Nagelkerke R2  and odds ratio (OR)) were calculated for each of the pathways using the independent validation dataset for EA and CH cohorts, and the 20% test set for the AA cohort. To further evaluate our pathway analysis pipeline, we selected 129 previously identified gene ontology (GO) pathways associated with schizophrenia and applied our pipeline to each of the 129 pathways in all three populations.19 as well as the functional annotation information obtained from the RegulomeDB, a database that annotates SNPs with known and predicted regulatory elements.20 We hypothesized that the selected features with greater appearance rates within significant schizophrenia liability pathways would be enriched for functional SNPs compared with SNP sets derived from non-significant pathways.To assess whether the mRmR feature selection approach was capable of selecting informative features and to evaluate the potential functional relevance of selected features, we utilized the brain expression quantitative trait loci (eQTLs) dataset obtained from the genotype-tissue expression (GTEx) portal v6.0,cis-eQTLs using genotype and gene expression data derived from human post-mortem frontal cortex (Brodmann area 9) of 92 donors included in the GTEx portal.19 For each of the three cohorts, SNPs within each of our candidate pathways was assigned an appearance rate based on the number of times (out of 100 iterations) the SNP represented the candidate pathway during our feature selection procedure  described above. SNPs were then grouped into quartiles based on their appearance rate  and the proportion of SNPs within each quartile associated  with expression of its corresponding gene was calculated. For comparison, the same analysis was conducted on 152, 181 and 168 non-significant pathways in the EA, CH and AA population, respectively. A one-sample t-test was used to determine if the proportion of eQTLs observed in our overlapping pathway SNP sets differed from the SNP sets derived from non-significant pathways.SNP sets representing pathways associated with schizophrenia in all three cohorts were further assessed as potential http://www.regulomedb.org).20 Similar to the eQTL analysis, SNPs were grouped into quartiles based on their appearance rate and a weighted Regulome score was computed for each quartile group as well as SNP sets derived from non-significant pathways. A one-sample t-test was used to determine if the weighted Regulome score in our candidate SNP sets differed from SNP sets derived from non-significant pathways  and DNA–RNA interaction , we utilized the RegulomeDB (R2=0.03–0.57%) of the variance in the liability to schizophrenia (R2=0.31–0.57%), although when features from all significant pathways were assessed the variance explained ranged from 0.66% in the EA cohort to 2.46% in the CH cohort. Furthermore, among the 129 previously identified schizophrenia-associated GO pathways our analysis pipeline replicated 45, 20 and 56 of these pathways in the EA, CH and AA populations  of the pathways we tested were uniquely associated with schizophrenia liability in only one of the three populations we examined—raising the possibility that schizophrenia is not only a polygenic but also a poly-pathway disorder. In fact, all pathways had an OR<1.35, suggesting multiple pathways of small effect collectively contribute to schizophrenia liability.Pathway heterogeneity has only recently been discussed in the context of schizophreniaFurthermore, our results suggest disruption of certain pathways may be necessary (but perhaps not sufficient) for the development of schizophrenia across populations. About one-fourth (27%) of the pathways we tested were associated with liability to schizophrenia in two or more of the populations, among which five pathways were associated with schizophrenia liability in all three cohorts. These pathways included the serotonergic synapse, ubiquitin mediated proteolysis, hedgehog signaling, renin secretion and adipocytokine signaling, all of which have been implicated in schizophrenia and/or related phenotypes.24 Thus, identification of the serotonergic synapse pathway in the current study is perhaps not surprising. In fact, the largest schizophrenia GWAS to date found SNPs in three genes  within the serotonergic synapse pathway reached GWAS significance (P<5 × 10−8) and SNPs in another 17 genes within this pathway were nominally significant (P<1 × 10−5).2 Furthermore, a recent gene-set enrichment analysis of the SZGene database25 identified 24 pathways significantly enriched for schizophrenia candidate genes among which the serotonin receptor signaling pathway was ranked second.7A number of post-mortem, functional neuroimaging and peripheral biomarker studies have implicated the serotonergic system in the pathophysiology of schizophrenia , a critical system for the removal of damaged/toxic proteins in the cell, has been shown to be dysregulated at the transcript37 dopaminergic neuron development,38 and promotes brain expression of disc1, a candidate gene in schizophrenia.39 The pathway's most well characterized ligand, sonic hedgehog, regulates the generation of functional synaptic contacts,41 and is abundant in the adult human central nervous system.43 Furthermore, hedgehog signaling interacts with the UPP45The hedgehog signaling pathway is a key regulator of oligodendrocyte production,46 and in general exhibit dysregulation of body temperature.47 Rodent studies have demonstrated renin is also synthesized in the brain48 and has considerable effects on anxiety-related behaviors and cognition .49 In the brain, renin is proposed to enzymatically process angiotensinogen to angiotensin, which is then further processed by angiotensin-converting enzyme (ACE).50 ACE activity has been shown to modulate dopamine turnover51 and abnormal levels of ACE in cerebrospinal fluid have been reported in individuals with schizophrenia,53 albeit potential neurotropic and length of illness effects have been noted.55 The interaction between angiotensin II (AT II), a neuropeptide substrate for ACE, and central dopamine has also been associated with schizophrenia.57 Moreover, numerous genetic studies suggested polymorphisms in ACE are associated with susceptibility to schizophrenia and major depression.62The renin secretion pathway is typically associated with regulation of arterial blood pressure, thirst and thermoregulation via the kidney secreted enzyme renin and its interaction with the renin–angiotensin–aldosterone system. Epidemiological studies have reported up to 25% of schizophrenia have polydipsia (excessive thirst)63 hundreds of adipocytokines have been found, such as adiponentin, tumor necrosis factor-alpha and members of the interleukin family. Increased expression of tumor necrosis factor-alpha and a number of interleukins have recently been proposed as markers of schizophrenia in brain64 and blood.65 Furthermore, adipocytokines are recognized not only as regulators of energy metabolism, but also as factors that may be associated with mental disorders. Decreased serum levels of adiponectin have been identified in major depressive disorder and schizophrenia,68 and serum levels of leptin correlate with less severe positive symptoms in schizophrenia patients69 and may regulate the mesolimbic dopamine system.70The adipocytokine signaling pathway is a collective destination of cytokines secreted by the adipose tissue. Since the first adipocytokine leptin was discovered in 1994,71 Third, the dopamine hypothesis of schizophrenia is an enduring, widely accepted, idea but among the three populations we studied the dopaminergic synapse pathway was only a significant liability pathway in the EA  and CH  populations. Although, we failed to detect this pathway in the AA population, the expected trend was evident  and is likely a result of the smaller sample size available for this population. Fourth, our analysis did not look at potential clinical subtypes of schizophrenia based on symptom profiles, despite recognition that schizophrenia is a broader spectrum disorder including a range of symptoms. A PWAS of clinical subtypes may lead to stronger associations by reducing the noise associated with the broad schizophrenia phenotype. However, the clinical symptom data available for this study was inconsistent or minimal across the three cohorts inhibiting such an analysis. Fifth, SNPs eligible for inclusion in our analysis were limited to those that were within a gene using a narrow ‘5 and 3' intergenic window . Intergenic SNPs are known to play functional regulatory roles on genes72 and as such exclusion of more distal intergenic SNPs may have biased our results. In the most recent schizophrenia GWAS,2 45% (57) of the 128 SNPs identified were intergenic but 52% (30) of these intergenic SNPs are in linkage disequilibrium (R2⩾0.50) with one or more SNPs within a gene according to our intergenic window. Thus, our intergenic window was capable of capturing a majority  of the 128 SNPs, suggesting the bias conferred by our SNP inclusion criteria are likely modest. Finally, our feature selection procedure (mRmR) resulted in the loss of many pathways containing smaller SNP pools. In total, 45 pathways cataloged within KEGG were not included in our pathway association study as the number of SNPs selected to represent these pathways was fewer than the required number of SNPs  to run our random forest algorithm.Despite the novelty and many strengths of our study, our findings should be interpreted in the context of several limitations. First, the detection of population differences in schizophrenia liability at the pathway level may, in part, be a result of sampling, allelic frequency and/or linkage disequilibrium differences across the populations studied. These potential confounding factors may also explain why we only identified five overlapping pathways rather than the expected 10 overlaps given the number of significant pathways identified in each population. Although we attempted to reduce these confounding influences by selecting features independently in each population using an mRmR approach, complete restraint of these confounds is not possible and as such our results should be interpreted with caution. Second, an independent validation dataset was not available for the AA population and as such all estimates were based on the 20% holdout dataset derived from the discovery dataset. This may have resulted in over-estimation of associations within this population, although the random forest algorithm we employed internally mitigates this potential bias via the out-of-bag error estimate mechanism.In conclusion, our results empirically support the notion that schizophrenia is a pathway disorder and further suggest that there is a considerable amount of pathway heterogeneity within and across different ethnic populations. We also identified five pathways that may serve as harbors of genotypic markers for schizophrenia across populations. However, future application of our pathway-wide association approach in larger cohorts as well as among ethnic groups not examined here are required before firm conclusions can be drawn.