Hi-C metagenomics facilitate comparative genome analysis of bacteria and yeast from spontaneous beer and cider

Sequence-based analysis of fermented foods and beverages' microbiomes offers insights into their impact on taste and consumer health. High-throughput metagenomics provide detailed taxonomic and functional community profiling, but bacterial and yeast genome reconstruction and mobile genetic elements tracking are to be improved. We established a pipeline for exploring fermented foods microbiomes using metagenomics coupled with chromosome conformation capture (Hi-C metagenomics). The approach was applied to analyze a collection of spontaneously fermented beers and ciders (n = 12). The Hi-C reads were used to reconstruct the metagenome-assembled genomes (MAGs) of bacteria and yeasts facilitating subsequent comparative genomic analysis, assembly scaffolding and exploration of "plasmid-bacteria" links. For a subset of beverages, yeasts were isolated and characterized phenotypically. The reconstructed Hi-C MAGs primarily belonged to the Lactobacillaceae family in beers, along with Acetobacteraceae and Enterobacteriaceae in ciders, exhibiting improved quality compared to conventional metagenomic MAGs. Comparative genomic analysis of Lactobacillaceae Hi-C MAGs revealed clustering by niche and suggested genetic determinants of survival and probiotic potential. For Pediococcus damnosus, Hi-C-based networks of contigs enabled linking bacteria with plasmids. Analyzing phylogeny and accessory genes in the context of known reference genomes offered insights into the niche specialization of beer lactobacilli. The subspecies-level diversity of cider Tatumella spp. was disentangled using a Hi-C-based graph. We obtained highly complete yeast Hi-C MAGs primarily represented by Brettanomyces and Saccharomyces, with Hi-C-facilitated chromosome-level genome assembly for the former. Utilizing Hi-C metagenomics to unravel the genomic content of individual species can provide a deeper understanding of the ecological interactions within the food microbiome, aid in bioprospecting beneficial microorganisms, improving quality control and improving innovative fermented products.

Unraveling the Polysaccharide Biosynthesis Potential of Ganoderma lucidum: A Chromosome-Level Assembly Using Hi-C Sequencing

Ganoderma lucidum exhibits the ability to synthesize a diverse range of biologically active molecules with significant pharmaceutical potential, including xylomannan and fucogalactan, which have demonstrated antitumor activity. However, there exists considerable intra-species variability in the capacity to produce these metabolites at high concentrations, likely reflecting the high genomic diversity observed from a limited number of strains sequenced to date. We employed high-throughput shotgun sequencing to obtain the complete genome sequence of G. lucidum strain 5.1, which is distinguished by its remarkable xylomannan synthesis capabilities. Through the utilization of semi-automatic reordering based on conformation capture (Hi-C) data, we substantially enhanced the assembly process, resulting in the generation of 12 chromosome-level scaffolds with a cumulative length of 39 Mbp. By employing both de novo and homology-based approaches, we performed comprehensive annotation of the genome, thereby identifying a diverse repertoire of genes likely involved in polysaccharide biosynthesis. The genome sequence generated in this study serves as a valuable resource for elucidating the molecular mechanisms underlying the medicinal potential of Ganoderma species, discovering novel pharmaceutically valuable compounds, and elucidating the ecological mechanisms of the species. Furthermore, the chromosome contact map obtained for the first time for this species extends our understanding of 3D fungal genomics and provides insights into the functional and structural organization within the fungal kingdom.

RNA-DNA interactomes of three prokaryotes uncovered by proximity ligation

Proximity ligation approaches, which are widely used to study the spatial organization of the genome, also make it possible to reveal patterns of RNA-DNA interactions. Here, we use RedC, an RNA-DNA proximity ligation approach, to assess the distribution of major RNA types along the genomes of E. coli, B. subtilis, and thermophilic archaeon T. adornatum. We find that (i) messenger RNAs preferentially interact with their cognate genes and the genes located downstream in the same operon, which is consistent with polycistronic transcription; (ii) ribosomal RNAs preferentially interact with active protein-coding genes in both bacteria and archaea, indicating co-transcriptional translation; and (iii) 6S noncoding RNA, a negative regulator of bacterial transcription, is depleted from active genes in E. coli and B. subtilis. We conclude that the RedC data provide a rich resource for studying both transcription dynamics and the function of noncoding RNAs in microbial organisms.

Gut Microbiome in Post-COVID-19 Patients Is Linked to Immune and Cardiovascular Health Status but Not COVID-19 Severity

The composition of the gut microbiome stores the imprints of prior infections and other impacts. COVID-19 can cause changes in inflammatory status that persist for a considerable time after infection ends. As the gut microbiome is closely associated with immunity and inflammation, the infection severity might be linked to its community structure dynamics. Using 16S rRNA sequencing of stool samples, we investigated the microbiome three months after the end of the disease/infection or SARS-CoV-2 contact in 178 post-COVID-19 patients and those who contacted SARS-CoV-2 but were not infected. The cohort included 3 groups: asymptomatic subjects (n = 48), subjects who contacted COVID-19 patients with no further infection (n = 46), and severe patients (n = 86). Using a novel compositional statistical algorithm (nearest balance) and the concept of bacterial co-occurrence clusters (coops), we compared microbiome compositions between the groups as well as with multiple categories of clinical parameters including: immunity, cardiovascular parameters and markers of endothelial dysfunction, and blood metabolites. Although a number of clinical indicators varied drastically across the three groups, no differences in microbiome features were identified between them at this follow-up point. However, there were multiple associations between the microbiome features and clinical data. Among the immunity parameters, the relative lymphocyte number was linked to a balance including 14 genera. Cardiovascular parameters were associated with up to four bacterial cooperatives. Intercellular adhesion molecule 1 was linked to a balance including ten genera and one cooperative. Among the blood biochemistry parameters, calcium was the only parameter associated with the microbiome via a balance of 16 genera. Our results suggest comparable recovery of the gut community structure in the post-COVID-19 period, independently of severity or infection status. The multiple identified associations of clinical analysis data with the microbiome provide hypotheses about the participation of specific taxa in regulating immunity and homeostasis of cardiovascular and other body systems in health, as well as their disruption in SARS-CoV-2 infections and other diseases.

Luminal and Tumor-Associated Gut Microbiome Features Linked to Precancerous Lesions Malignancy Risk: A Compositional Approach

Colorectal cancer is the third most commonly diagnosed cancer worldwide. Human gut microbiome plays important roles in protecting against it, as well as contributing to its onset and progression. Identification of specific bacterial taxa associated with early stages of colorectal cancer may help develop effective microbiome-based diagnostics. For precancerous lesions, links of their characteristics to luminal and tumor-associated microbiome composition are to be elucidated. Paired stool and tumor brush biopsy samples were collected from 50 patients with precancerous lesions and early forms of colon cancer; their microbial communities were profiled using high-throughput 16S rRNA sequencing. We showed that the microbiome differences between stool and biopsy samples can be to a high extent computationally corrected. Compositionality-aware statistical analysis of microbiome composition revealed its associations with the number of lesions, lesion type, location and malignization pathway. A major determinant of precancerous lesions malignancy risk-the number of lesions-was positively associated with the abundance of H2S-producing taxa. Our results contribute to the basis for developing early non-invasive colorectal cancer diagnostics via identifying microorganisms likely participating in early stages of cancer pathogenesis.

The hallmarks of dietary intervention-resilient gut microbiome

Maintaining equilibrium of the gut microbiome is crucial for human health. Diet represents an important and generally accessible natural channel of controlling the nutrients supply to the intestinal microorganisms. Although many studies showed that dietary interventions can specifically modulate gut microbiome composition, further progress of the approach is complicated by interindividual variability of the microbial community response. The reported causes of this variability include the baseline microbiome composition features, but it is unclear whether any of them are intervention-specific. Here, we applied a unified computational framework to investigate the variability of microbiome response measured as beta diversity in eight various dietary interventions using previously published 16S rRNA sequencing datasets. We revealed a number of baseline microbiome features which determine the microbiome response in an intervention-independent manner. One of the most stable associations, reproducible for different interventions and enterotypes, was a negative dependence of the response on the average number of genes per microorganism in the community—an indicator of the community functional redundancy. Meanwhile, many revealed microbiome response determinants were enterotype-specific. In Bact1 and Rum enterotypes, the response was negatively correlated with the baseline abundance of their main drivers. Additionally, we proposed a method for preliminary assessment of the microbiome response. Our study delineats the universal features determining microbiome response to diverse interventions. The proposed approach is promising for understanding the mechanisms of gut microbiome stability and improving the efficacy of personalised microbiome-tailored interventions.

Pentad: a tool for distance-dependent analysis of Hi-C interactions within and between chromatin compartments

Background

Understanding the role of various factors in 3D genome organization is essential to determine their impact on shaping large-scale chromatin units such as euchromatin (A) and heterochromatin (B) compartments. At this level, chromatin compaction is extensively modulated when transcription and epigenetic profiles change upon cell differentiation and response to various external impacts. However, detailed analysis of chromatin contact patterns within and between compartments is complicated because of a lack of suitable computational methods.

Results

We developed a tool, Pentad, to perform calculation, visualisation and quantitative analysis of the average chromatin compartment from the Hi-C matrices in cis, trans, and specified genomic distances. As we demonstrated by applying Pentad to publicly available Hi-C datasets, it helps to reliably detect redistribution of contact frequency in the chromatin compartments and assess alterations in the compartment strength.

Conclusions

Pentad is a simple tool for the analysis of changes in chromatin compartmentalization in various biological conditions. Pentad is freely available at https://github.com/magnitov/pentad.

Suppression of liquid-liquid phase separation by 1,6-hexanediol partially compromises the 3D genome organization in living cells

Liquid-liquid phase separation (LLPS) contributes to the spatial and functional segregation of molecular processes within the cell nucleus. However, the role played by LLPS in chromatin folding in living cells remains unclear. Here, using stochastic optical reconstruction microscopy (STORM) and Hi-C techniques, we studied the effects of 1,6-hexanediol (1,6-HD)-mediated LLPS disruption/modulation on higher-order chromatin organization in living cells. We found that 1,6-HD treatment caused the enlargement of nucleosome clutches and their more uniform distribution in the nuclear space. At a megabase-scale, chromatin underwent moderate but irreversible perturbations that resulted in the partial mixing of A and B compartments. The removal of 1,6-HD from the culture medium did not allow chromatin to acquire initial configurations, and resulted in more compact repressed chromatin than in untreated cells. 1,6-HD treatment also weakened enhancer-promoter interactions and TAD insulation but did not considerably affect CTCF-dependent loops. Our results suggest that 1,6-HD-sensitive LLPS plays a limited role in chromatin spatial organization by constraining its folding patterns and facilitating compartmentalization at different levels.

Metabolic Phenotypes as Potential Biomarkers for Linking Gut Microbiome With Inflammatory Bowel Diseases

The gut microbiome is of utmost importance to human health. While a healthy microbiome can be represented by a variety of structures, its functional capacity appears to be more important. Gene content of the community can be assessed by “shotgun” metagenomics, but this approach is still too expensive. High-throughput amplicon-based surveys are a method of choice for large-scale surveys of links between microbiome, diseases, and diet, but the algorithms for predicting functional composition need to be improved to achieve good precision. Here we show how feature engineering based on microbial phenotypes, an advanced method for functional prediction from 16S rRNA sequencing data, improves identification of alterations of the gut microbiome linked to the disease. We processed a large collection of published gut microbial datasets of inflammatory bowel disease (IBD) patients to derive their community phenotype indices (CPI)—high-precision semiquantitative profiles aggregating metabolic potential of the community members based on genome-wide metabolic reconstructions. The list of selected metabolic functions included metabolism of short-chain fatty acids, vitamins, and carbohydrates. The machine-learning approach based on microbial phenotypes allows us to distinguish the microbiome profiles of healthy controls from patients with Crohn's disease and from ones with ulcerative colitis. The classifiers were comparable in quality to conventional taxonomy-based classifiers but provided new findings giving insights into possible mechanisms of pathogenesis. Feature-wise partial dependence plot (PDP) analysis of contribution to the classification result revealed a diversity of patterns. These observations suggest a constructive basis for defining functional homeostasis of the healthy human gut microbiome. The developed features are promising interpretable candidate biomarkers for assessing microbiome contribution to disease risk for the purposes of personalized medicine and clinical trials.

Benchmark of software tools for prokaryotic chromosomal interaction domain identification

Motivation

The application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes vary in GC content and the density of restriction sites along the chromosome, suggesting that these properties should be considered when planning experiments and choosing appropriate software for data processing. Diverse algorithms are available for the analysis of eukaryotic chromatin contact maps, but their potential application to prokaryotic data has not yet been evaluated.

Results

Here, we present a comparative analysis of domain calling algorithms using available single-microbe experimental data. We evaluated the algorithms’ intra-dataset reproducibility, concordance with other tools and sensitivity to coverage and resolution of contact maps. Using RNA-seq as an example, we showed how orthogonal biological data can be utilized to validate the reliability and significance of annotated domains. We also suggest that in silico simulations of contact maps can be used to choose optimal restriction enzymes and estimate theoretical map resolutions before the experiment. Our results provide guidelines for researchers investigating microbes and microbial communities using high-throughput 3C assays such as Hi-C and 3C-seq.

Availability and implementation

The code of the analysis is available at https://github.com/magnitov/prokaryotic_cids.

Supplementary information

Supplementary data are available at Bioinformatics online.

VERA: agent-based modeling transmission of antibiotic resistance between human pathogens and gut microbiota

MOTIVATION

The resistance of bacterial pathogens to antibiotics is one of the most important issues of modern health care. The human microbiota can accumulate resistance determinants and transfer them to pathogenic microbiota by means of horizontal gene transfer. Thus, it is important to develop methods of prediction and monitoring of antibiotics resistance in human populations.

RESULTS

We present the agent-based VERA model, which allows simulation of the spread of pathogens, including the possible horizontal transfer of resistance determinants from a commensal microbiota community. The model considers the opportunity of residents to stay in the town or in a medical institution, have incorrect self-treatment, treatment with several antibiotics types and transfer and accumulation of resistance determinants from commensal microorganism to a pathogen. In this model, we have also created an assessment of optimum observation frequency of infection spread among the population. Investigating model behavior, we show a number of non-linear dependencies, including the exponential nature of the dependence of the total number of those infected on the average resistance of a pathogen. As the model infection, we chose infection with Shigella spp., though it could be applied to a wide range of other pathogens.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries VERA and VERA.viewer are freely available for download at github.com/lpenguin/microbiota-resistome. The code is written in Java, JavaScript and R for Linux platform.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Microbiome-Metabolome Signature of Acute Kidney Injury

Intestinal microbiota play a considerable role in the host’s organism, broadly affecting its organs and tissues. The kidney can also be the target of the microbiome and its metabolites (especially short-chain fatty acids), which can influence renal tissue, both by direct action and through modulation of the immune response. This impact is crucial, especially during kidney injury, because the modulation of inflammation or reparative processes could affect the severity of the resulting damage or recovery of kidney function. In this study, we compared the composition of rat gut microbiota with its outcome, in experimental acute ischemic kidney injury and named the bacterial taxa that play putatively negative or positive roles in the progression of ischemic kidney injury. We investigated the link between serum creatinine, urea, and a number of metabolites (acylcarnitines and amino acids), and the relative abundance of various bacterial taxa in rat feces. Our analysis revealed an increase in levels of 32 acylcarnitines in serum, after renal ischemia/reperfusion and correlation with creatinine and urea, while levels of three amino acids (tyrosine, tryptophan, and proline) had decreased. We detected associations between bacterial abundance and metabolite levels, using a compositionality-aware approach—Rothia and Staphylococcus levels were positively associated with creatinine and urea levels, respectively. Our findings indicate that the gut microbial community contains specific members whose presence might ameliorate or, on the contrary, aggravate ischemic kidney injury. These bacterial taxa could present perspective targets for therapeutical interventions in kidney pathologies, including acute kidney injury.

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.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Shifts in the Human Gut Microbiota Structure Caused by Quadruple Helicobacter pylori Eradication Therapy

The human gut microbiome plays an important role both in health and disease. Use of antibiotics can alter gut microbiota composition, which can lead to various deleterious events. Here we report a whole genome sequencing metagenomic/genomic study of the intestinal microbiota changes caused by Helicobacter pylori (HP) eradication therapy. Using approaches for metagenomic data analysis we revealed a statistically significant decrease in alpha-diversity and relative abundance of Bifidobacterium adolescentis due to HP eradication therapy, while the relative abundance of Enterococcus faecium increased. We have detected changes in general metagenome resistome profiles as well: after HP eradication therapy, the ermB, CFX group, and tetQ genes were overrepresented, while tetO and tetW genes were underrepresented. We have confirmed these results with genome-resolved metagenomic approaches. MAG (metagenome-assembled genomes) abundance profiles have changed dramatically after HP eradication therapy. Focusing on ermB gene conferring resistance to macrolides, which were included in the HP eradication therapy scheme, we have shown a connection between antibiotic resistance genes (ARGs) and some overrepresented MAGs. Moreover, some E. faecium strains isolated from stool samples obtained after HP eradication have manifested greater antibiotic resistance in vitro in comparison to other isolates, as well as the higher number of ARGs conferring resistance to macrolides and tetracyclines.

Markers of dysbiosis in patients with ulcerative colitis and Crohn's disease

AIM

The aim of the study was to study the taxonomic and functional composition of the gut microbiota in ulcerative colitis (UC) and Crohn's disease (CD) patients to identify key markers of dysbiosis in IBD.

MATERIALS AND METHODS

Fecal samples obtained from 95 IBD patients (78 UC and 17 CD) as well as 96 healthy volunteers were used for whole-genome sequencing carried out on the SOLiD 5500 W platform. Taxonomic profiling was performed by aligning the reeds, not maped on hg19, on MetaPhlAn2 reference database. Reeds were mapped using the HUNAnN2 algorithm to the ChocoPhlAn database to assess the representation of microbial metabolic pathways. Short-chain fatty acids (SCFA) level were measured in fecal samples by gas-liquid chromatographic analysis.

RESULTS

Changes in IBD patients gut microbiota were characterized by an increase in the representation of Proteobacteria and Bacteroidetes phyla bacteria and decrease in the number of Firmicutes phylum bacteria and Euryarchaeota phylum archaea; a decrease in the alpha-diversity index, relative representation of butyrate-producing, hydrogen-utilizing bacteria, and Methanobrevibacter smithii; increase in the relative representation of Ruminococcus gnavus in UC and CD patients and Akkermansia muciniphila in CD patients. Reduction of Butyryl-CoA: acetate CoA transferase gene relative representation in CD patients, decrease of absolute content of SCFA total number as well as particular SCFAs and main SCFAs ratio in IBD patients may indicate inhibition of functional activity and number of anaerobic microflora and/or an change in SCFA utilization by colonocytes.

CONCLUSION

the revealed changes can be considered as typical signs of dysbiosis in IBD patients and can be used as potential targets for IBD patients personalized treatment development.

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.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5306-5) contains supplementary material, which is available to authorized users.

MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota

Motivation

Antibiotic resistance is an important global public health problem. Human gut microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens.

Results

We developed MetaCherchant-an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on a number of simulated and published datasets, as well as applied to new 'shotgun' metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several major resistance genes. Taxonomic annotation of the context suggests that within a single metagenome, the resistance genes can be contained in genomes of multiple species. MetaCherchant allows reconstruction of mobile elements with resistance genes within the genomes of bacteria using metagenomic data. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo basing on metagenomic data.

Availability and implementation

Source code and binaries are freely available for download at https://github.com/ctlab/metacherchant. The code is written in Java and is platform-independent.

Cotanct

ulyantsev@rain.ifmo.ru.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

ResistoMap-online visualization of human gut microbiota antibiotic resistome

Abstract

We created ResistoMap—a Web-based interactive visualization of the presence of genetic determinants conferring resistance to antibiotics, biocides and heavy metals in human gut microbiota. ResistoMap displays the data on more than 1500 published gut metagenomes of world populations including both healthy subjects and patients. Multiparameter display filters allow visual assessment of the associations between the meta-data and proportions of resistome. The geographic map navigation layer allows to state hypotheses regarding the global trends of antibiotic resistance and correlates the gut resistome variations with the national clinical guidelines on antibiotics application.

Availability and Implementation

ResistoMap was implemented using AngularJS, CoffeeScript, D3.js and TopoJSON. The tool is publicly available at http://resistomap.rcpcm.org.

Contact

yarygin@phystech.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

[Correlation Between Emotional-Affective Disorders and Gut Microbiota Composition in Patients with Parkinson’s Disease]

Background

Despite the efforts of scientific community the data available on the correlation between emotional-affective symptoms of Parkinson’s disease and changes in microbiome is still scarce. Deeper studies of nonmotor symptoms evident in premotor stages of the disease and the reciprocal influence of microbiota may help to understand the etiology and pathogenesis of PD neurodegeneration better.

Aim of the Study

Discover the relations between emotional-affective disorders prevalent in PD population and changes in gut microbiota composition.

Methods

51 patient diagnosed with PD participated in the study. Every participant’s emotional-affective state was examined using Beck’s Depression Inventory (BDI) and Hospital Anxiety and Depression Scale (HADS). Taxonomic richness of microbiome was studied using 16S ribosomal RNA gene sequencing, bioinformatics, and statistical analysis.

Results

Anxiety and depression are prevalent affective disorders in patients with PD. In our study, most of the subjects demonstrated certain anxiety and depression. Taxonomic diversity of gut microbiota in BP was increasing with the increase in anxiety levels, reaching the maximum in the group with subclinical anxiety, and decreasing in the group with clinically significant anxiety disorder. At the species level, patients with clinically significant anxiety had higher abundance of Clostridium clariflavum compared to the anxiety-free patients. Patients with moderate depression were characterized by the higher prevalence of Christensenella minuta, Clostridium disporicum, and Oscillibacter valericigenes compared to subjects without depression or with mild depression.

Conclusion

The data we received in our study allow better understanding of PD pathogenesis.

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.

Data on gut metagenomes of the patients with Helicobacter pylori infection before and after the antibiotic therapy

Antibiotic therapy can lead to the disruption of gut microbiota community with possible negative outcomes for human health. One of the diseases for which the treatment scheme commonly included antibiotic intake is Helicobacter pylori infection. The changes in taxonomic and functional composition of microbiota in patients can be assessed using “shotgun” metagenomic sequencing. Ten stool samples were collected from 4 patients with Helicobacter pylori infection before and directly after the H. pylori eradication course. Additionally, for two of the subjects, the samples were collected 1 month after the end of the treatment. The samples were subject to “shotgun” (whole-genome) metagenomic sequencing using Illumina HiSeq platform. The reads are deposited in the ENA (project ID: PRJEB18265).

Data on gut metagenomes of the patients with alcoholic dependence syndrome and alcoholic liver cirrhosis

Alcoholism is associated with significant changes in gut microbiota composition. Metagenomic sequencing allows to assess the altered abundance levels of bacterial taxa and genes in a culture-independent way. We collected 99 stool samples from the patients with alcoholic dependence syndrome (n=72) and alcoholic liver cirrhosis (n=27). Each of the samples was surveyed using “shotgun” (whole-genome) sequencing on SOLiD platform. The reads are deposited in the ENA (project ID: PRJEB18041).

State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells

A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC-MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC-MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (R² ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015-2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126 .

MetaFast: fast reference-free graph-based comparison of shotgun metagenomic data

MOTIVATION

High-throughput metagenomic sequencing has revolutionized our view on the structure and metabolic potential of microbial communities. However, analysis of metagenomic composition is often complicated by the high complexity of the community and the lack of related reference genomic sequences. As a start point for comparative metagenomic analysis, the researchers require efficient means for assessing pairwise similarity of the metagenomes (beta-diversity). A number of approaches were used to address this task, however, most of them have inherent disadvantages that limit their scope of applicability. For instance, the reference-based methods poorly perform on metagenomes from previously unstudied niches, while composition-based methods appear to be too abstract for straightforward interpretation and do not allow to identify the differentially abundant features.

RESULTS

We developed MetaFast, an approach that allows to represent a shotgun metagenome from an arbitrary environment as a modified de Bruijn graph consisting of simplified components. For multiple metagenomes, the resulting representation is used to obtain a pairwise similarity matrix. The dimensional structure of the metagenomic components preserved in our algorithm reflects the inherent subspecies-level diversity of microbiota. The method is computationally efficient and especially promising for an analysis of metagenomes from novel environmental niches.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available for download at https://github.com/ctlab/metafast The code is written in Java and is platform independent (tested on Linux and Windows x86_64).

CONTACT

ulyantsev@rain.ifmo.ru

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

[Comparison Study of Oropharyngeal Microbiota in Case of Bronchial Asthma and Chronic Obstructive Pulmonary Disease in Different Severity Levels]

BACKGRAUND

The result of comparative study of oropharyngeal microbiota taxonomic composition in patients with different severity level of bronchial asthma (BA) and chronic obstructive pulmonary disease (COPD) is presented in this paper.

AIMS

To compare oropharyngeal microbiota composition in case of bronchial asthma and chronic obstructive pulmonary disease in different severity levels.

METODS

138 patients, 50 with BA and 88 with COPD were studied. For each patient was collected anamnesis vitae, swab from the back of the throat and performed physical examination. High-throughput 16S ribosomal RNA gene sequencing and bioinformatic analysis was employed to characterize the microbial communities.

RESULTS

As a result of the study wasfound a number of differences on various taxonomic levels in microbiota's composition within group of patients with different severity level of BA and group of patients with different severity level of COPD and between those groups. COPD patients with GOLD 1-2 in comparison with GOLD 3-4 patiens are marked by prevalence of species Brevibacterium aureum, genus Scardovia, Coprococcus, Haemophilus, Moryella, Dialister, Paludibacter and decrease of Prevotella melaninogenica species. BA patients with severe uncontrolled asthma in comparison with patients which have mild persistent asthma are marked by decrease of Prevotella and increase of species Bifidobacterium longum, Prevotella nanceiensis, Neisseria cinerea, Aggregatibacter segnis and genus Odoribacter, Alloiococcus, Lactobacillus, Megasphaera, Parvimonas, Sneathia. Patient's microbiota in BA group in comparison with COPD group is characterized by the prevalence of Prevotella melaninogenica and genus Selenomonas, Granulicatella u Gemella, and decrease of Prevotella nigrescens, Haemophilus influenza and genus Aggregatibacter, Alloiococcus, Catonella, Mycoplasma, Peptoniphilus u Sediminibacterium. There are no differences between microbiota composition in case of severe uncontrolled BA and very severe COPD.

CONCLUSION

Lack of differences in oropharyngeal microbiota taxonomic composition between patients with severe uncontrolled BA and very severe COPD allow us to suggest a similarity of bronchopulmonary system condition in case of diseases' severe stages.

[Specific features of the enteric microbiota composition in patients with alcoholic liver cirrhosis]

AIM

To establish the specific features of the taxonomic and functional composition of the enteric microbiota in patients with alcoholic liver cirrhosis (LC).

SUBJECTS AND METHODS

Metagenomic analysis was used to study the taxonomic composition and functional potential of the enteric microbiota in 20 patients with alcoholic LC. Total DNA was isolated from the patients' fecal samples; thereafter full genome sequencing was carried out. The metagenomic analysis yielded the results of the relative taxonomic and functional abundance of microbial species in the test samples. These were comparatively analyzed with the previously published metagenomic datasets of healthy population cohorts in the Russian Federation, as well as in Denmark, China, and the USA.

RESULTS

In the majority of patients, the dominant part of the intestinal community represented bacterial species constituting the normal human intestinal flora. At the same time, abnormal gut microbiota composition, which was suggestive of marked dysbacteriosis, was identified in a number of patients. In addition, pooled analysis of the data could identify a number of species with a statistically significantly increase and decrease in the relative abundance as compared to the control groups. Thus, the enteric microbiota of the patients with alcoholic LC showed a high proportion of bacteria characteristic of the oral cavity. Analysis of the pooled metabolic potential of the microbiota in these patients demonstrated the higher abundance of enzyme genes involved in alcohol metabolism.

CONCLUSION

In the patients with alcoholic LC, the microbiota composition changes identified in individual bacterial species may be associated with gastrointestinal comorbidities, such as chronic erosive gastritis, chronic pancreatitis, and gastric ulcer. The alterations occurring in alcoholic cirrhosis promote the penetration and generation of oral cavity-specific microorganisms in the human intestine. This may a potential biomarker for the diagnosis of liver diseases. The bacterial enzyme genes involved in alcohol metabolism have an increased abundance in patients with alcoholic LC and healthy volunteers from the Russian Federation.

[Metagenomic analysis of taxonomic and functional changes in gut microbiota of patients with alcoholic dependence syndrome]

Here we present the first metagenomic study of gut microbiota in patients with alcohol dependence syndrome (ADS) performed in the whole-genome ("shotgun") format. Taxonomic analysis highlighted changes in community "drivers" abundance previously associated with inflammatory processes (including increase in Ruminococcus gnavus and torques, as well as decrease in Faecalibacterium and Akkermansia). Microbiota of alcoholics manifested presence of specific opportunistic pathogens rarely detected in healthy control subjects of the world. Differential analysis of metabolic potential basing on changes in KEGG Orthology groups abundance revealed increase in pathways associated with response to oxidative stress. Analysis of two specific gene groups--alcohol metabolism and virulence factors--also showed increase in comparison with the control groups. We suggest that gut microbiota distinct in alcoholics by both taxonomic and functional composition plays role in modulating the effect of alcohol on host organism.

Assessment of k-mer spectrum applicability for metagenomic dissimilarity analysis

BACKGROUND

A rapidly increasing flow of genomic data requires the development of efficient methods for obtaining its compact representation. Feature extraction facilitates classification, clustering and model analysis for testing and refining biological hypotheses. "Shotgun" metagenome is an analytically challenging type of genomic data - containing sequences of all genes from the totality of a complex microbial community. Recently, researchers started to analyze metagenomes using reference-free methods based on the analysis of oligonucleotides (k-mers) frequency spectrum previously applied to isolated genomes. However, little is known about their correlation with the existing approaches for metagenomic feature extraction, as well as the limits of applicability. Here we evaluated a metagenomic pairwise dissimilarity measure based on short k-mer spectrum using the example of human gut microbiota, a biomedically significant object of study.

RESULTS

We developed a method for calculating pairwise dissimilarity (beta-diversity) of "shotgun" metagenomes based on short k-mer spectra (5 ≤ k ≤ 11). The method was validated on simulated metagenomes and further applied to a large collection of human gut metagenomes from the populations of the world (n=281). The k-mer spectrum-based measure was found to behave similarly to one based on mapping to a reference gene catalog, but different from one using a genome catalog. This difference turned out to be associated with a significant presence of viral reads in a number of metagenomes. Simulations showed limited impact of bacterial genetic variability as well as sequencing errors on k-mer spectra. Specific differences between the datasets from individual populations were identified.

CONCLUSIONS

Our approach allows rapid estimation of pairwise dissimilarity between metagenomes. Though we applied this technique to gut microbiota, it should be useful for arbitrary metagenomes, even metagenomes with novel microbiota. Dissimilarity measure based on k-mer spectrum provides a wider perspective in comparison with the ones based on the alignment against reference sequence sets. It helps not to miss possible outstanding features of metagenomic composition, particularly related to the presence of an unknown bacteria, virus or eukaryote, as well as to technical artifacts (sample contamination, reads of non-biological origin, etc.) at the early stages of bioinformatic analysis. Our method is complementary to reference-based approaches and can be easily integrated into metagenomic analysis pipelines.

RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue

Background

Human hepatoma HepG2 cells are used as an in vitro model of the human liver. High-throughput transcriptomic sequencing is an advanced approach for assessing the functional state of a tissue or cell type. However, the influence of experimental factors, such as the sample preparation method and inter-laboratory variation, on the transcriptomic profile has not been evaluated.

Results

The whole-transcriptome sequencing of HepG2 cells was performed using the SOLiD platform and validated using droplet digital PCR. The gene expression profile was compared to the results obtained with the same sequencing method in another laboratory and using another sample preparation method. We also compared the transcriptomic profile HepG2 cells with that of liver tissue. Comparison of the gene expression profiles between the HepG2 cell line and liver tissue revealed the highest variation, followed by HepG2 cells submitted to two different sample preparation protocols. The lowest variation was observed between HepG2 cells prepared by two different laboratories using the same protocol. The enrichment analysis of the genes that were differentially expressed between HepG2 cells and liver tissue mainly revealed the cancer-associated gene signature of HepG2 cells and the activation of the response to chemical stimuli in the liver tissue. The HepG2 transcriptome obtained with the SOLiD platform was highly correlated with the published transcriptome obtained with the Illumina and Helicos platforms, with moderate correspondence to microarrays.

Conclusions

In the present study, we assessed the influence of experimental factors on the HepG2 transcriptome and identified differences in gene expression between the HepG2 cell line and liver cells. These findings will facilitate robust experimental design in the fields of pharmacology and toxicology. Our results were supported by a comparative analysis with previous HepG2 gene expression studies.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1108) contains supplementary material, which is available to authorized users.

Rural and urban microbiota: To be or not to be?

A multitude of metagenomic studies has brought to light an enormous richness of human gut microbiota compositions. In this space of possible configurations, clinical specialists are trying to mine the markers of healthy microbiota via case-control and longitudinal studies. We have discovered potentially beneficial communities while examining the microbial diversity in rural Russians in comparison with the urban dwellers. In this addendum, we further examine the data by elaborating on some of the less common types and suggesting the possible co-metabolism of their drivers. In the light of the first validated clinically effective bacterial transplantation, we discuss the concept of a reference healthy microbiota, outline the problems encountered on the way to its restoration in the developed world, and speculate if rural communities can serve as a source for its prototype.

Human gut microbiota community structures in urban and rural populations in Russia

The microbial community of the human gut has a crucial role in sustaining host homeostasis. High-throughput DNA sequencing has delineated the structural and functional configurations of gut metagenomes in world populations. The microbiota of the Russian population is of particular interest to researchers, because Russia encompasses a uniquely wide range of environmental conditions and ethnogeographical cohorts. Here we conduct a shotgun metagenomic analysis of gut microbiota samples from 96 healthy Russian adult subjects, which reveals novel microbial community structures. The communities from several rural regions display similarities within each region and are dominated by the bacterial taxa associated with the healthy gut. Functional analysis shows that the metabolic pathways exhibiting differential abundance in the novel types are primarily associated with the trade-off between the Bacteroidetes and Firmicutes phyla. The specific signatures of the Russian gut microbiota are likely linked to the host diet, cultural habits and socioeconomic status.

Chromosome 18 transcriptoproteome of liver tissue and HepG2 cells and targeted proteome mapping in depleted plasma: update 2013

We report the results obtained in 2012-2013 by the Russian Consortium for the Chromosome-centric Human Proteome Project (C-HPP). The main scope of this work was the transcriptome profiling of genes on human chromosome 18 (Chr 18), as well as their encoded proteome, from three types of biomaterials: liver tissue, the hepatocellular carcinoma-derived cell line HepG2, and blood plasma. The transcriptome profiling for liver tissue was independently performed using two RNaseq platforms (SOLiD and Illumina) and also by droplet digital PCR (ddPCR) and quantitative RT-PCR. The proteome profiling of Chr 18 was accomplished by quantitatively measuring protein copy numbers in the three types of biomaterial (the lowest protein concentration measured was 10(-13) M) using selected reaction monitoring (SRM). In total, protein copy numbers were estimated for 228 master proteins, including quantitative data on 164 proteins in plasma, 171 in the HepG2 cell line, and 186 in liver tissue. Most proteins were present in plasma at 10(8) copies/μL, while the median abundance was 10(4) and 10(5) protein copies per cell in HepG2 cells and liver tissue, respectively. In summary, for liver tissue and HepG2 cells a "transcriptoproteome" was produced that reflects the relationship between transcript and protein copy numbers of the genes on Chr 18. The quantitative data acquired by RNaseq, PCR, and SRM were uploaded into the "Update_2013" data set of our knowledgebase (www.kb18.ru) and investigated for linear correlations.

Chromosome 18 transcriptome profiling and targeted proteome mapping in depleted plasma, liver tissue and HepG2 cells

The final goal of the Russian part of the Chromosome-centric Human Proteome Project (C-HPP) was established as the analysis of the chromosome 18 (Chr 18) protein complement in plasma, liver tissue and HepG2 cells with the sensitivity of 10(-18) M. Using SRM, we have recently targeted 277 Chr 18 proteins in plasma, liver, and HepG2 cells. On the basis of the results of the survey, the SRM assays were drafted for 250 proteins: 41 proteins were found only in the liver tissue, 82 proteins were specifically detected in depleted plasma, and 127 proteins were mapped in both samples. The targeted analysis of HepG2 cells was carried out for 49 proteins; 41 of them were successfully registered using ordinary SRM and 5 additional proteins were registered using a combination of irreversible binding of proteins on CN-Br Sepharose 4B with SRM. Transcriptome profiling of HepG2 cells performed by RNAseq and RT-PCR has shown a significant correlation (r = 0.78) for 42 gene transcripts. A pilot affinity-based interactome analysis was performed for cytochrome b5 using analytical and preparative optical biosensor fishing followed by MS analysis of the fished proteins. All of the data on the proteome complement of the Chr 18 have been integrated into our gene-centric knowledgebase ( www.kb18.ru ).

MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads

MALINA is a web service for bioinformatic analysis of whole-genome metagenomic data obtained from human gut microbiota sequencing. As input data, it accepts metagenomic reads of various sequencing technologies, including long reads (such as Sanger and 454 sequencing) and next-generation (including SOLiD and Illumina). It is the first metagenomic web service that is capable of processing SOLiD color-space reads, to authors’ knowledge. The web service allows phylogenetic and functional profiling of metagenomic samples using coverage depth resulting from the alignment of the reads to the catalogue of reference sequences which are built into the pipeline and contain prevalent microbial genomes and genes of human gut microbiota. The obtained metagenomic composition vectors are processed by the statistical analysis and visualization module containing methods for clustering, dimension reduction and group comparison. Additionally, the MALINA database includes vectors of bacterial and functional composition for human gut microbiota samples from a large number of existing studies allowing their comparative analysis together with user samples, namely datasets from Russian Metagenome project, MetaHIT and Human Microbiome Project (downloaded from http://hmpdacc.org). MALINA is made freely available on the web at http://malina.metagenome.ru. The website is implemented in JavaScript (using Ext JS), Microsoft .NET Framework, MS SQL, Python, with all major browsers supported.