bioGWAS: A Simple and Flexible Tool for Simulating GWAS Datasets.

Genome-wide association studies (GWAS) have proven to be a powerful tool for the identification of genetic susceptibility loci affecting human complex traits. In addition to pinpointing individual genes involved in a particular trait, GWAS results can be used to discover relevant biological processes for these traits. The development of new tools for extracting such information from GWAS results requires large-scale datasets with known biological ground truth. Simulation of GWAS results is a powerful method that may provide such datasets and facilitate the development of new methods. In this work, we developed bioGWAS, a simple and flexible pipeline for the simulation of genotypes, phenotypes, and GWAS summary statistics. Unlike existing methods, bioGWAS can be used to generate GWAS results for simulated quantitative and binary traits with a predefined set of causal genetic variants and/or molecular pathways. We demonstrate that the proposed method can recapitulate complete GWAS datasets using a set of reported genome-wide associations. We also used our method to benchmark several tools for gene set enrichment analysis for GWAS data. Taken together, our results suggest that bioGWAS provides an important set of functionalities that would aid the development of new methods for downstream processing of GWAS results.

Prevention of High Glucose-Mediated EMT by Inhibition of Hsp70 Chaperone.

Hyperglycemia may contribute to the progression of carcinomas by triggering epithelial-to-mesenchymal transition (EMT). Some proteostasis systems are involved in metastasis; in this paper, we sought to explore the mechanism of Hsp70 chaperone in EMT. We showed that knockdown of Hsp70 reduced cell migration capacity concomitantly with levels of mRNA of the Slug, Snail, and Twist markers of EMT, in colon cancer cells incubated in high glucose medium. Conversely, treatment of cells with Hsp70 inducer U-133 were found to elevate cell motility, along with the other EMT markers. To prove that inhibiting Hsp70 may reduce EMT efficiency, we treated cells with a CL-43 inhibitor of the HSF1 transcription factor, which lowered Hsp70 and HSF1 content in the control and induced EMT in carcinoma cells. Importantly, CL-43 reduced migration capacity, EMT-linked transcription factors, and increased content of epithelial marker E-cadherin in colon cancer cells of three lines, including one derived from a clinical sample. To prove that Hsp70 chaperone should be targeted when inhibiting the EMT pathway, we treated cancer cells with 2-phenylethynesulfonamide (PES) and demonstrated that the compound inhibited substrate-binding capacity of Hsp70. Furthermore, PES suppressed EMT features, cell motility, and expression of specific transcription factors. In conclusion, the Hsp70 chaperone machine efficiently protects mechanisms of the EMT, and the safe inhibitors of the chaperone are needed to hamper metastasis at its initial stage.

Gut microbiome signature of Viliuisk encephalomyelitis in Yakuts includes an increase in microbes linked to lean body mass and eating behaviour.

BACKGROUND: Viliuisk encephalomyelitis (VE) is a rare endemic neurodegenerative disease occurring in the Yakut population of Northeastern Siberia. The main clinical features of VE are spasticity, dysarthria, dementia, central paresis and paralysis, and cortical atrophy observed via MRI. Many hypotheses have been proposed regarding its etiology, including infectious agents, genetics, environmental factors, and immunopathology. Each of these hypotheses has been supported to some extent by epidemiological and experimental data. Nevertheless, none of them has been decisively proven. Gut microbiome is one of the factors that might be involved in VE pathogenesis. RESULTS: Here we performed a pilot survey of the stool microbiomes of Yakut subjects with VE (n = 6) and without VE (n = 11). 16S rRNA sequencing showed that in comparison with the control group, the Yakuts with VE had increased proportions of Methanobrevibacter and Christensenella, which are reported to be linked to body mass index, metabolism, dietary habits and potentially to neurodegenerative disorders. The identified associations suggest that the microbiome may be involved in VE. Overall, the Yakut microbiome was quite specific in comparison with other populations, such as metropolitan Russians and native inhabitants of the Canadian Arctic. CONCLUSIONS: Describing the gut microbiome of indigenous human populations will help to elucidate the impact of dietary and environmental factors on microbial community structure and identify risks linked to the lifestyles of such groups as well as endemic diseases.

Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies.

Genome-wide association studies have led to a significant progress in identification of genomic loci affecting coronary artery disease (CAD) risk. However, revealing the causal genes responsible for the observed associations is challenging. In the present study, we aimed to prioritize CAD-relevant genes based on cumulative evidence from the published studies and our own study of colocalization between eQTLs and loci associated with CAD using SMR/HEIDI approach. Prior knowledge of candidate genes was extracted from both experimental and in silico studies, employing different prioritization algorithms. Our review systematized information for a total of 51 CAD-associated loci. We pinpointed 37 genes in 36 loci. For 27 genes we infer they are causal for CAD, and for 10 further genes we judge them most likely causal. Colocalization analysis showed that for 18 out of these loci, association with CAD can be explained by changes in gene expression in one or more CAD-relevant tissues. Furthermore, for 8 out of 36 loci, existing evidence suggested additional CAD-associated genes. For the remaining 15 loci, we concluded that evidence for gene prioritization remains inconsistent, insufficient, or absent. Our results provide deeper insights into the genetic etiology of CAD and demonstrate knowledge gaps where further research is warranted.

Development of qPCR platform with probes for quantifying prevalent and biomedically relevant human gut microbial taxa.

Nowadays the advent of innovative high-throughput sequencing allows obtaining high-quality microbiome profiling. However, PCR-based tests are still considered the "golden standard" for many clinical applications. Here, we designed a qPCR-based platform with fluorescent-labeled oligonucleotide probes for assessing human gut microbiome composition. The system allows conducting qualitative and semiquantitative analysis for 12 prokaryotic taxa that are prevalent in the human gut and associated with diseases, diet, age and other factors. The platform was validated by comparing microbiome profile data obtained with two different methods - the platform and high-throughput 16S rRNA sequencing - across 42 stool samples. The test can form the basis for precise and cost-efficient microbiome assay for large-scale surveys including clinical trials with interventions related to diet and disease risks.

Co-occurrence patterns of bacteria within microbiome of Moscow subway.

Microbial ecosystems of the built environments have become key mediators of health as people worldwide tend to spend large amount of time indoors. Underexposure to microbes at an early age is linked to increased risks of allergic and autoimmune diseases. Transportation systems are of particular interest, as they are globally the largest space for interactions between city-dwellers. Here we performed the first pilot study of the Moscow subway microbiome by analyzing swabs collected from 5 types of surfaces at 4 stations using high-throughput 16S rRNA gene sequencing. The study was conducted as a part of The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) project. The most abundant microbial taxa comprising the subway microbiome originated from soil and human skin. Microbiome diversity was positively correlated with passenger traffic. No substantial evidence of major human pathogens presence was found. Co-occurrence analysis revealed clusters of microbial genera including combinations of microbes likely originating from different niches. The clusters as well as the most abundant microbes were similar to ones obtained for the published data on New-York City subway microbiome. Our results suggest that people are the main source and driving force of diversity in subway-associated microbiome. The data form a basis for a wider survey of Moscow subway microbiome to explore its longitudinal dynamics by analyzing an extended set of sample types and stations. Complementation of methods with viability testing, "shotgun" metagenomics, sequencing of bacterial isolates and culturomics will provide insights for public health, biosafety, microbial ecology and urban design.

Human Gut Microbiome Response Induced by Fermented Dairy Product Intake in Healthy Volunteers.

Accumulated data suggests that the gut microbiome can rapidly respond to changes in diet. Consumption of fermented dairy products (FDP) fortified with probiotic microbes may be associated with positive impact on human health. However, the extent and details of the possible impact of FDP consumption on gut community structure tends to vary across individuals. We used microbiome analysis to characterize changes in gut microbiota composition after 30 days of oral intake of a yoghurt fortified with Bifidobacterium animalis subsp. lactis BB-12. 16S rRNA gene sequencing was used to assess the gut microbial composition before and after FDP consumption in healthy adults (n = 150). Paired comparison of gut microbial content demonstrated an increase in presence of potentially beneficial bacteria, particularly, Bifidobacterium genus, as well as Adlercreutzia equolifaciens and Slackia isoflavoniconvertens. At a functional level, an increased capacity to metabolize lactose and synthesize amino acids was observed accompanied by a lowered potential for synthesis of lipopolysaccharides. Cluster analysis revealed that study volunteers segregated into two groups with post-intervention microbiota response that was dependent on the baseline microbial community structure.

Genetic diversity of Escherichia coli in gut microbiota of patients with Crohn's disease discovered using metagenomic and genomic analyses.

BACKGROUND: Crohn's disease is associated with gut dysbiosis. Independent studies have shown an increase in the abundance of certain bacterial species, particularly Escherichia coli with the adherent-invasive pathotype, in the gut. The role of these species in this disease needs to be elucidated. METHODS: We performed a metagenomic study investigating the gut microbiota of patients with Crohn's disease. A metagenomic reconstruction of the consensus genome content of the species was used to assess the genetic variability. RESULTS: The abnormal shifts in the microbial community structures in Crohn's disease were heterogeneous among the patients. The metagenomic data suggested the existence of multiple E. coli strains within individual patients. We discovered that the genetic diversity of the species was high and that only a few samples manifested similarity to the adherent-invasive varieties. The other species demonstrated genetic diversity comparable to that observed in the healthy subjects. Our results were supported by a comparison of the sequenced genomes of isolates from the same microbiota samples and a meta-analysis of published gut metagenomes. CONCLUSIONS: The genomic diversity of Crohn's disease-associated E. coli within and among the patients paves the way towards an understanding of the microbial mechanisms underlying the onset and progression of the Crohn's disease and the development of new strategies for the prevention and treatment of this disease.

AGTR2 and sprint/power performance: a case-control replication study for rs11091046 polymorphism in two ethnicities.

We aimed to replicate, in a specific athletic event cohort (only track and field) and in two different ethnicities (Japanese and East European, i.e. Russian and Polish), original findings showing the association of the angiotensin-II receptor type-2 gene (AGTR2) rs11091046 A>C polymorphism with athlete status. We compared genotypic frequencies of the AGTR2 rs11091046 polymorphism among 282 track and field sprint/power athletes (200 men and 82 women), including several national record holders and Olympic medallists (214 Japanese, 68 Russian and Polish), and 2024 control subjects (842 men and 1182 women) (804 Japanese, 1220 Russian and Polish). In men, a meta-analysis from the two combined cohorts showed a significantly higher frequency of the C allele in athletes than in controls (odds ratio: 1.62, P=0.008, heterogeneity index I 2 =0%). With regard to respective cohorts, C allele frequency was higher in Japanese male athletes than in controls (67.7% vs. 55.9%, P=0.022), but not in Russian/Polish male athletes (61.9% vs. 51.0%, P=0.172). In women, no significant results were obtained by meta-analysis for the two cohorts combination (P=0.850). The AC genotype frequency was significantly higher in Russian/Polish women athletes than in controls (69.2% vs. 42.1%, P=0.022), but not in Japanese women athletes (P=0.226). Our results, in contrast to previous findings, suggested by meta-analysis that the C allele of the AGTR2 rs11091046 polymorphism is associated with sprint/power track and field athlete status in men, but not in women.

Knomics-Biota - a system for exploratory analysis of human gut microbiota data.

BACKGROUND: Metagenomic surveys of human microbiota are becoming increasingly widespread in academic research as well as in food and pharmaceutical industries and clinical context. Intuitive tools for investigating experimental data are of high interest to researchers. RESULTS: Knomics-Biota is a web-based resource for exploratory analysis of human gut metagenomes. Users can generate and share analytical reports corresponding to common experimental schemes (like case-control study or paired comparison). Interactive visualizations and statistical analysis are provided in association with the external factors and in the context of thousands of publicly available datasets arranged into thematic collections. The web-service is available at https://biota.knomics.ru. CONCLUSIONS: Knomics-Biota web service is a comprehensive tool for interactive metagenomic data analysis.

Gut Microbiota in Patients with Different Metabolic Statuses: Moscow Study.

The aim of this paper was to study gut microbiota composition in patients with different metabolic statuses. METHODS: 92 participants aged 25⁻76 years (26 of whom were men), with confirmed absence of cardiovascular and other chronic diseases (but with the possible presence of cardiovascular risk factors) were included. Carotid ultrasound examinations, 16S rRNA sequencing of stool samples and diet assessments were performed. Statistical analysis was performed using R programming language, 3.1.0. RESULTS: Enterotyping yielded two clusters differentiated by alpha-diversity. Intima-media thickness was higher in the cluster with lower diversity (adj. p < 0.001). Obesity was associated with higher Serratia (adj. p = 0.003) and Prevotella (adj. p < 0.0003) in relative abundance. Abdominal obesity was associated with higher abundance of Serratia (adj. p = 0.004) and Prevotella (adj. p = 0.0008) and lower levels of Oscillospira (adj. p = 0.0005). Glucose metabolism disturbances were associated with higher Blautia (adj. p = 0.0007) and Serratia (adj. p = 0.003) prevalence. Arterial hypertension was associated with high Blautia levels (adj. p = 0.002). The Blautia genus strongly correlated with low resistant starch consumption (adj. p = 0.007). A combination of high-fat diet and elevated Blautia levels was very common for diabetes mellitus type 2 patients (adj. p = 0.0001). CONCLUSION: The results show that there is a relationship between metabolic changes and higher representation of opportunistic pathogens and low diversity of gut microbiota even in apparently healthy participants.

IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes.

GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach.

Microbiome Responses to an Uncontrolled Short-Term Diet Intervention in the Frame of the Citizen Science Project.

Personalized nutrition is of increasing interest to individuals actively monitoring their health. The relations between the duration of diet intervention and the effects on gut microbiota have yet to be elucidated. Here we examined the associations of short-term dietary changes, long-term dietary habits and lifestyle with gut microbiota. Stool samples from 248 citizen-science volunteers were collected before and after a self-reported 2-week personalized diet intervention, then analyzed using 16S rRNA sequencing. Considerable correlations between long-term dietary habits and gut community structure were detected. A higher intake of vegetables and fruits was associated with increased levels of butyrate-producing Clostridiales and higher community richness. A paired comparison of the metagenomes before and after the 2-week intervention showed that even a brief, uncontrolled intervention produced profound changes in community structure: resulting in decreased levels of Bacteroidaceae, Porphyromonadaceae and Rikenellaceae families and decreased alpha-diversity coupled with an increase of Methanobrevibacter, Bifidobacterium, Clostridium and butyrate-producing Lachnospiraceae- as well as the prevalence of a permatype (a bootstrapping-based variation of enterotype) associated with a higher diversity of diet. The response of microbiota to the intervention was dependent on the initial microbiota state. These findings pave the way for the development of an individualized diet.

Dissection of affinity captured LINE-1 macromolecular complexes.

Long Interspersed Nuclear Element-1 (LINE-1, L1) is a mobile genetic element active in human genomes. L1-encoded ORF1 and ORF2 proteins bind L1 RNAs, forming ribonucleoproteins (RNPs). These RNPs interact with diverse host proteins, some repressive and others required for the L1 lifecycle. Using differential affinity purifications, quantitative mass spectrometry, and next generation RNA sequencing, we have characterized the proteins and nucleic acids associated with distinctive, enzymatically active L1 macromolecular complexes. Among them, we describe a cytoplasmic intermediate that we hypothesize to be the canonical ORF1p/ORF2p/L1-RNA-containing RNP, and we describe a nuclear population containing ORF2p, but lacking ORF1p, which likely contains host factors participating in target-primed reverse transcription.

Links of gut microbiota composition with alcohol dependence syndrome and alcoholic liver disease.

BACKGROUND: Alcohol abuse has deleterious effects on human health by disrupting the functions of many organs and systems. Gut microbiota has been implicated in the pathogenesis of alcohol-related liver diseases, with its composition manifesting expressed dysbiosis in patients suffering from alcoholic dependence. Due to its inherent plasticity, gut microbiota is an important target for prevention and treatment of these diseases. Identification of the impact of alcohol abuse with associated psychiatric symptoms on the gut community structure is confounded by the liver dysfunction. In order to differentiate the effects of these two factors, we conducted a comparative "shotgun" metagenomic survey of 99 patients with the alcohol dependence syndrome represented by two cohorts-with and without liver cirrhosis. The taxonomic and functional composition of the gut microbiota was subjected to a multifactor analysis including comparison with the external control group. RESULTS: Alcoholic dependence and liver cirrhosis were associated with profound shifts in gut community structures and metabolic potential across the patients. The specific effects on species-level community composition were remarkably different between cohorts with and without liver cirrhosis. In both cases, the commensal microbiota was found to be depleted. Alcoholic dependence was inversely associated with the levels of butyrate-producing species from the Clostridiales order, while the cirrhosis-with multiple members of the Bacteroidales order. The opportunist pathogens linked to alcoholic dependence included pro-inflammatory Enterobacteriaceae, while the hallmarks of cirrhosis included an increase of oral microbes in the gut and more frequent occurrence of abnormal community structures. Interestingly, each of the two factors was associated with the expressed enrichment in many Bifidobacterium and Lactobacillus-but the exact set of the species was different between alcoholic dependence and liver cirrhosis. At the level of functional potential, the patients showed different patterns of increase in functions related to alcohol metabolism and virulence factors, as well as pathways related to inflammation. CONCLUSIONS: Multiple shifts in the community structure and metabolic potential suggest strong negative influence of alcohol dependence and associated liver dysfunction on gut microbiota. The identified differences in patterns of impact between these two factors are important for planning of personalized treatment and prevention of these pathologies via microbiota modulation. Particularly, the expansion of Bifidobacterium and Lactobacillus suggests that probiotic interventions for patients with alcohol-related disorders using representatives of the same taxa should be considered with caution. Taxonomic and functional analysis shows an increased propensity of the gut microbiota to synthesis of the toxic acetaldehyde, suggesting higher risk of colorectal cancer and other pathologies in alcoholics.

Genome analysis of E. coli isolated from Crohn's disease patients.

BACKGROUND: Escherichia coli (E. coli) has been increasingly implicated in the pathogenesis of Crohn's disease (CD). The phylogeny of E. coli isolated from Crohn's disease patients (CDEC) was controversial, and while genotyping results suggested heterogeneity, the sequenced strains of E. coli from CD patients were closely related. RESULTS: We performed the shotgun genome sequencing of 28 E. coli isolates from ten CD patients and compared genomes from these isolates with already published genomes of CD strains and other pathogenic and non-pathogenic strains. CDEC was shown to belong to A, B1, B2 and D phylogenetic groups. The plasmid and several operons from the reference CD-associated E. coli strain LF82 were demonstrated to be more often present in CDEC genomes belonging to different phylogenetic groups than in genomes of commensal strains. The operons include carbon-source induced invasion GimA island, prophage I, iron uptake operons I and II, capsular assembly pathogenetic island IV and propanediol and galactitol utilization operons. CONCLUSIONS: Our findings suggest that CDEC are phylogenetically diverse. However, some strains isolated from independent sources possess highly similar chromosome or plasmids. Though no CD-specific genes or functional domains were present in all CD-associated strains, some genes and operons are more often found in the genomes of CDEC than in commensal E. coli. They are principally linked to gut colonization and utilization of propanediol and other sugar alcohols.

Respiratory Pathways Reconstructed by Multi-Omics Analysis in Melioribacter roseus, Residing in a Deep Thermal Aquifer of the West-Siberian Megabasin.

Melioribacter roseus, a representative of recently proposed Ignavibacteriae phylum, is a metabolically versatile thermophilic bacterium, inhabiting subsurface biosphere of the West-Siberian megabasin and capable of growing on various substrates and electron acceptors. Genomic analysis followed by inhibitor studies and membrane potential measurements of aerobically grown M. roseus cells revealed the activity of aerobic respiratory electron transfer chain comprised of respiratory complexes I and IV, and an alternative complex III. Phylogeny reconstruction revealed that oxygen reductases belonged to atypical cc(o/b)o3 -type and canonical cbb3 -type cytochrome oxidases. Also, two molybdoenzymes of M. roseus were affiliated either with Ttr or Psr/Phs clades, but not with typical respiratory arsenate reductases of the Arr clade. Expression profiling, both at transcripts and protein level, allowed us to assign the role of the terminal respiratory oxidase under atmospheric oxygen concentration for the cc(o/b)o3 cytochrome oxidase, previously proposed to serve for oxygen detoxification only. Transcriptomic analysis revealed the involvement of both molybdoenzymes of M. roseus in As(V) respiration, yet differences in the genomic context of their gene clusters allow to hypothesize about their distinct roles in arsenate metabolism with the 'Psr/Phs'-type molybdoenzyme being the most probable candidate respiratory arsenate reductase. Basing on multi-omics data, the pathways for aerobic and arsenate respiration were proposed. Our results start to bridge the vigorously increasing gap between homology-based predictions and experimentally verified metabolic processes, what is especially important for understudied microorganisms of novel lineages from deep subsurface environments of Eurasia, which remained separated from the rest of the biosphere for several geological periods.

Guidelines to Statistical Analysis of Microbial Composition Data Inferred from Metagenomic Sequencing.

Metagenomics, the application of high-throughput DNA sequencing for surveys of environmental samples, has revolutionized our view on the taxonomic and genetic composition of complex microbial communities. An enormous richness of microbiota keeps unfolding in the context of various fields ranging from biomedicine and food industry to geology. Primary analysis of metagenomic reads allows to infer semi-quantitative data describing the community structure. However, such compositional data possess statistical specific properties that are important to be considered during preprocessing, hypothesis testing and interpreting the results of statistical tests. Failure to account for these specifics may lead to essentially wrong conclusions as a result of the survey. Here we present a researcher introduced to the field of metagenomics with the basic properties of microbial compositional data including statistical power and proposed distribution models, perform a review of the publicly available software tools developed specifically for such data and outline the recommendations for the application of the methods.

Methods for The Metagenomic Data Visualization and Analysis.

Surveys of environmental microbial communities using metagenomic approach produce vast volumes of multidimensional data regarding the phylogenetic and functional composition of the microbiota. Faced with such complex data, a metagenomic researcher needs to select the means for data analysis properly. Data visualization became an indispensable part of the exploratory data analysis and serves a key to the discoveries. While the molecular-genetic analysis of even a single bacterium presents multiple layers of data to be properly displayed and perceived, the studies of microbiota are significantly more challenging. Here we present a review of the state-of-art methods for the visualization of metagenomic data in a multi-level manner: from the methods applicable to an in-depth analysis of a single metagenome to the techniques appropriate for large-scale studies containing hundreds of environmental samples.

Abundance profiling of specific gene groups using precomputed gut metagenomes yields novel biological hypotheses.

The gut microbiota is essentially a multifunctional bioreactor within a human being. The exploration of its enormous metabolic potential provides insights into the mechanisms underlying microbial ecology and interactions with the host. The data obtained using "shotgun" metagenomics capture information about the whole spectrum of microbial functions. However, each new study presenting new sequencing data tends to extract only a little of the information concerning the metabolic potential and often omits specific functions. A meta-analysis of the available data with an emphasis on biomedically relevant gene groups can unveil new global trends in the gut microbiota. As a step toward the reuse of metagenomic data, we developed a method for the quantitative profiling of user-defined groups of genes in human gut metagenomes. This method is based on the quick analysis of a gene coverage matrix obtained by pre-mapping the metagenomic reads to a global gut microbial catalogue. The method was applied to profile the abundance of several gene groups related to antibiotic resistance, phages, biosynthesis clusters and carbohydrate degradation in 784 metagenomes from healthy populations worldwide and patients with inflammatory bowel diseases and obesity. We discovered country-wise functional specifics in gut resistome and virome compositions. The most distinct features of the disease microbiota were found for Crohn's disease, followed by ulcerative colitis and obesity. Profiling of the genes belonging to crAssphage showed that its abundance varied across the world populations and was not associated with clinical status. We demonstrated temporal resilience of crAssphage and the influence of the sample preparation protocol on its detected abundance. Our approach offers a convenient method to add value to accumulated "shotgun" metagenomic data by helping researchers state and assess novel biological hypotheses.