Bacterial community structure transformed after thermophilically composting human waste in Haiti

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Abstract

Recycling human waste for beneficial use has been practiced for millennia. Aerobic (thermophilic) composting of sewage sludge has been shown to reduce populations of opportunistically pathogenic bacteria and to inactivate both Ascaris eggs and culturable Escherichia coli in raw waste, but there is still a question about the fate of most fecal bacteria when raw material is composted directly. This study undertook a comprehensive microbial community analysis of composting material at various stages collected over 6 months at two composting facilities in Haiti. The fecal microbiota signal was monitored using a high-density DNA microarray (PhyloChip). Thermophilic composting altered the bacterial community structure of the starting material. Typical fecal bacteria classified in the following groups were present in at least half the starting material samples, yet were reduced below detection in finished compost: Prevotella and Erysipelotrichaceae (100% reduction of initial presence), Ruminococcaceae (98–99%), Lachnospiraceae (83–94%, primarily unclassified taxa remained), Escherichia and Shigella (100%). Opportunistic pathogens were reduced below the level of detection in the final product with the exception of Clostridium tetani, which could have survived in a spore state or been reintroduced late in the outdoor maturation process. Conversely, thermotolerant or thermophilic Actinomycetes and Firmicutes (e.g., Thermobifida, Bacillus, Geobacillus) typically found in compost increased substantially during the thermophilic stage. This community DNA-based assessment of the fate of human fecal microbiota during thermophilic composting will help optimize this process as a sanitation solution in areas where infrastructure and resources are limited.

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Nontuberculous mycobacterial pulmonary infections.

J Odell, M. Johnson (2014)

Pulmonary infections due to nontuberculous mycobacteria (NTM) are increasingly recognized worldwide. Although over 150 different species of NTM have been described, pulmonary infections are most commonly due to Mycobacterium avium complex (MAC), Mycobacterium kansasii, and Mycobacterium abscessus. The identification of these organisms in pulmonary specimens does not always equate with active infection; supportive radiographic and clinical findings are needed to establish the diagnosis. It is difficult to eradicate NTM infections. A prolonged course of therapy with a combination of drugs is required. Unfortunately, recurrent infection with new strains of mycobacteria or a relapse of infection caused by the original organism is not uncommon. Surgical resection is appropriate in selected cases of localized disease or in cases in which the infecting organism is resistant to medical therapy. Additionally, surgery may be required for infections complicated by hemoptysis or abscess formation. This review will summarize the practical aspects of the diagnosis and management of NTM thoracic infections, with emphasis on the indications for surgery and the results of surgical intervention. The management of NTM disease in patients with human immunodeficiency virus (HIV) infections is beyond the scope of this article and, unless otherwise noted, comments apply to hosts without HIV infection.

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

Alexander Tyakht, Elena Kostryukova, Anna S. Popenko … (2013)

The human gut microbiota represents the ‘last discovered organ’ of the human body1, showing functions ranging from digestion and protection against pathogen colonization to host immunity and central nervous system regulation. Its composition is influenced by genetics, the mode of delivery, diet, lifestyle, medical treatments and other factors2. The elucidation of global microbiota diversity is important for understanding the role of the microbiota in host health and for discovering ways to modulate the microbial community for disease prevention and treatment. Culture-independent methods, such as high-throughput DNA sequencing, provide insight into the total genomic composition (metagenome) of samples from both taxonomic and metabolic perspectives. Recently, several studies have produced large metagenomic data sets for the gut microbiota of populations from different countries. A catalogue of prevalent gut microbial genes was derived from the metagenomic analysis of stool samples obtained from 124 European individuals3. Long-term diet was found to be one of the significant factors linked to microbiota composition in US subjects4. Functions and structure of human gut microbiota were determined in a large cohort of US population5. Distinctions in microbiota composition were discovered between European, United States, African and Amerindian populations6 7. Other national metagenomic initiatives include Irish8, Korean9 and Chinese10 populations. However, metagenomic studies performed in Russia are underrepresented. In this study, we conduct a descriptive analysis of the gut microbiota of several diverse parts of Russian population using whole-genome sequencing. Although taxonomic analysis shows that the prevalent bacterial taxa are similar to those found in Western European and North American populations, we discovered novel community structures (dominated by Firmicutes and Actinobacteria) in healthy gut samples from Eastern Russia and rural regions. Gene repertoire analysis demonstrates that the novel community structures observed in the Russian metagenomes are distinctly enriched in functional pathways associated with Gram-positive Firmicutes. We suggest that further exploration of metagenomes in rural and remote areas will reveal even broader variation in community structures, representing historically stable variants of microbiota diversity before the widespread consumption of industrial food and antibiotics. Results Examination of the Russian microbiota We characterized the microbial communities of adult individuals living in metropolitan (n=50) and rural (n=46) areas by analysing stool samples (for the subject enrolment criteria, see Methods). The sampling geography covered a substantial part of the densely populated territory of Russia, including areas in Europe and south of Siberia (Fig. 1a). The urban settlements were represented by four of the top ten most populated cities in Russia (Saint Petersburg, Saratov, Rostov-on-Don and Novosibirsk), whereas the rural centres were represented by eleven villages and small towns in the Tatarstan, Omsk, Tyva and Khakassia regions. The average subject age was 36±18 years (mean±s.d.), and the sexes were equally represented (48 females, 48 males) (for detailed metadata, see Supplementary Data 1). The metagenomic composition of the microbiota was investigated via high-throughput shotgun sequencing using a SOLiD 4 sequencer, which produced 2.7±1.1 Gbp of 50 bp reads. The taxonomic and functional compositions of the samples were determined by mapping the reads against reference sets of microbial genomes and genes, respectively (details, including methodological validation, are described in the Methods and Supplementary Note 1). De novo assembly did not reveal any novel high-abundance taxa in the Russian metagenomes (see Methods). To check for distinctive features of the Russian metagenome composition in a global context, we performed a comparative analysis using existing sets of human gut shotgun reads from urban adult populations from Western Europe3 (Denmark, n=85) and North America4 (United States, n=137), rural communities from South America (Venezuela, n=10) and Africa5 (Malawi, n=5), and 70 healthy subjects from China9. The applied DNA extraction and sample preparation methods were similar in all of these studies (see Methods). To evaluate the variation in the shotgun metagenomic composition across multiple sequencing platforms, we sequenced a subset of the Russian metagenomes using the SOLiD, Ion Torrent, 454 and Illumina platforms. The subsequent composition analysis produced highly correlated taxonomic profiles (see Supplementary Note 2), thus supporting the validity of comparisons between studies. Although the fraction of identified reads was similar between the Russian and non-Russian groups (Supplementary Data 2 and Supplementary Note 3), the abundances of a number of microbial taxa were significantly different (Supplementary Figs S1 and S2, and Supplementary Data 3). Significant differences were found between the gut microbial communities of the Russian and the US, Danish and Chinese groups (Fig. 1b) via analysis of similarities (ANOSIM)11 using a modified weighted UniFrac12 metric (pair-wise ANOSIM, R=0.74, 0.50 and 0.26, respectively; P=9.999 × 10−5, 10,000 permutations, see Supplementary Table S1). A hierarchical representation of global diversity is shown in Supplementary Fig. S3. Original microbial community structures in Russian samples The diversity of Russian metagenomes (Supplementary Fig. S4) includes microbial communities that lack Prevotella or Bacteroides dominance; these two genera are ‘drivers’ of two of the three enterotypes13. Almost two-thirds of the Russian samples were not dominated by either of these genera (which is a higher fraction by 3.8±7.1 (median±s.d.) times than in the other populations (see Supplementary Table S2). Some of these mixed-type Russian metagenomes contained novel community structures that were not observed in non-Russian metagenomes. To assess the dominant taxa in these communities, sets of three of the most abundant genera were selected from each sample. For 92% of the combined metagenomes, more than 50% of the total abundance was contributed by these triplet sets. Approximately half (43 of 96) of the Russian metagenomes were dominated by triplets that were not found in non-Russian groups (see Supplementary Data 4). The majority of the triplets belonged to Firmicutes, followed by Bacteroidetes, Verrucomicrobia, Actinobacteria, Proteobacteria and Tenericutes, as well as Archaea. At a more detailed level, the novelty of the Russian metagenome composition was supported by the mean UniFrac distance from the non-Russian samples, which was significantly greater than that from the other Russian samples (Mann–Whitney’s one-sided test, P=1.202 × 10−9). Sequencing of a variety of Russian metagenomes (n=5) on both the SOLiD and Illumina platforms confirmed that the sets of three dominant genera were stable across different sequencing technologies (93% of the genera in triplets were preserved). For several samples, we discovered that the most abundant genus was unusual, that is, Bifidobacterium, Megamonas, Phascolarctobacterium, Lactobacillus or Akkermansia. Among other communities with unusual ‘drivers’, a number of the samples contained a high fraction of Escherichia coli. Differences in the corresponding genome-wise compositions suggested that this finding was not associated with laboratory contamination. One sample (Spb_73_13P) was dominated by a bacterium related to pathogenic Streptococcus infantarius subsp. infantarius BAA-102 (18.7% of the total abundance). Archaea were also distinctive contributors: although the major member of this group, Methanobrevibacter smithii, was generally more abundant in the Russian population than in all non-Russian cohorts, except the Amerindian group (Mann–Whitney’s one-sided test, P≤0.00995), it was included in the top triplet in two of the Russian samples, showing abundances as high as 11.25% and 13.85%. Compact distinct subgroups share rural origins To explore the substructure of the microbiota diversity in the Russian samples, we searched for dense subgroups (showing similar structures). Significant cluster mining with bootstrapping using the R package pvclust14 identified several subgroups with typical bacterial community structures (Supplementary Figs S5, S6). Interestingly, each of the three largest subgroups mostly corresponded to a single rural area, that is, the Omsk, Tatarstan or Tyva regions (Fig. 2). For each subgroup, 67–100% of the samples were dominated by the novel most-prevalent genus triplets. A specific feature found in the Omsk subgroup was that it consisted of six of seven related metagenomes from the same family living in one village. The major genera identified in this group were Prevotella (36.6±13.4%; mean±s.d.), Lachnospiraceae (15.3±3.2%), Coprococcus (13.1±5.5%) and Faecalibacterium (7.9±2.7%), indicating a community structure resembling the Malawian and Amerindian metagenomes. The similarity between the cluster samples varied with the choice of distance metric applied: the bacterial proportions were similar based on Spearman’s correlation (0.97±0.02, mean± s.d., with a pair-wise correlation across Russian samples of 0.78±0.07), but the UniFrac distance between the samples was quite high (0.03±0.02, with a mean of 0.07±0.03 across all Russian samples). This dependence of the similarity on the distance metric employed demonstrates that family metagenomes share genus compositions with similar ranks of abundance, as influenced by common genetics and past environmental exposure, consistent with a previous study of family metagenomes5. However, the quantitative proportions of genera may vary significantly depending on other variables. In the Tatarstan subgroup, all eight samples belonged to rural residents of this region. The community structure was characterized by the prevalence of Roseburia, Coprococcus, Faecalibacterium and Ruminococcus genera of the Firmicutes phylum (each forming 15–25% of the relative abundance), which were primarily contributed by the reference genomes Eubacterium rectale, Coprococcus eutactus, Faecalibacterium prausnitzii and Ruminococcus bromii, respectively. No similarity in community structures with non-Russian samples was observed during our meta-analysis (see Supplementary Table S4), suggesting that this represents an original subtype of microbiota within the Russian population. The third dense subgroup was dominated by samples from Tyva (12 of its 15 samples). Only three of the Tyva samples did not belong to the subgroup. The structure of these communities was defined by high proportions of Bifidobacterium (9.4±11.3%, mean±s.d., maximum 32.9%), which is more typical of infant microbiota5. At the genome level, the most abundant genus was represented by Bifidobacterium adolescentis, certain strains of which are reported to exhibit probiotic activity15. Moreover, this taxon was the most abundant genus in three of the samples, corresponding to a microbiota community type that was not observed in the non-Russian samples (except for a single Chinese sample dominated by Bifidobacterium breve). The other bacterial genera in the Tyva subgroup were similar to those in the Tatarstan group. Microbiota in urban and rural populations The small number of samples for each geographic site and the specific age ranges and other metadata associated with each site confounded comparisons between separate geographic sites in Russia. However, when the samples were pooled by settlement size, the age and body mass index (BMI) distributions were generally not significantly different (Mann–Whitney’s two-sided test, P=0.5423 and 0.1316, respectively; see Fig. 3). There was no clear separation between the urban and rural metagenomes detected based on their taxonomic compositions (ANOSIM of UniFrac dissimilarity values, R=0.096, P=5 × 10−4, 10,000 permutations). The metagenomes from Russian cities were more similar to those of Western countries: despite equal representation of rural and urban populations, the original microbial community structures occurred in hosts from urban populations 2.6-fold less frequently than in the rural hosts (being found in 31 and 12 samples from these groups, respectively). The aforementioned compact subgroups were also found more often among rural populations, with only 2 of the 29 samples from these subgroups belonging to urban hosts. Taxonomic typing of the Russian microbiota Cluster analyses of human gut microbial metagenomes are somewhat controversial. Although some studies demonstrate the existence of discrete categories of bacterial communities (enterotypes)6 9 13 16, others suggest that the distribution of bacterial components is more likely to exhibit a smooth, continuous structure5 17. In view of this ongoing discussion, we applied a cluster analysis based on enterotypes methodology to determine whether the observed Russian metagenomic diversity could be divided into distinctive clusters. Several common dissimilarity measures were used to generate the clusters (Supplementary Data 5). For each metric, the optimal number of clusters was determined using the Calinski–Harabasz index and was assessed with multiple cluster quality metrics, including the average silhouette width (ASW), predictive strength18 and comparison with randomized simulated communities13 (see Methods). Overall, although the optimal number of clusters varied from two to three, all of the clusterings only achieved moderate support, as determined by the ASW value (Supplementary Table S3). Even the highest ASW value (from the UniFrac metric) was low (0.389). However, using various metrics, the ASW was shown to be two to three times higher than the mean ASW for randomized simulated communities (1,000 simulations of 96 samples), and the predictive strength was quite high (Fig. 4). Interestingly, two clusters were obtained: the first was driven by the genus Prevotella, and the second exhibited a high representation of Bifidobacterium and various genera of the phylum Firmicutes. Thus, the previously reported cluster with a high abundance of Bacteroides 6 13 was not observed, and the contribution of this genus was not significantly different between the two clusters (P=0.8857, Mann–Whitney’s test). The urban and rural metagenomes were distributed equally between the clusters: 53% of the first and 52% of the second cluster were urban. When non-Russians were added to the Russian samples, the analysis produced two clusters: the first was driven by Prevotella, Bifidobacterium and various Firmicutes (it included most Russian samples) and the second by Bacteroides (Supplementary Data 5). Rural subgroups and metabolic benefits to the host Analysis of the microbial drivers of the Tyva- and Tatarstan-dominated compact subgroups showed that they are prevalent in the healthy gut and complement mutual metabolism in ways that may be beneficial to host health. In particular, R. bromii, B. adolescentis and E. rectale are essential fermenters of type 2 and type 3 resistant starches19. During cocultivation in vitro, the first species significantly increases type 3 resistant starch utilization by the last two, having an essential role in the metabolism of these substrates, which have health benefits20. In addition, B. adolescentis is involved in metabolic cross-feeding with Roseburia and Eubacterium spp. bacteria through providing them with oligosaccharides released from complex substrates, as well as fermentation end products (lactate and acetate)21. High proportions of Coprococcus and Roseburia found in elderly people differentiate the microbiota of healthy community dwellers from long-term care patients, whereas the loss of Ruminococcus is associated with the transition to frailty8. Metabolomic analysis of fecal water have demonstrated that these species are associated with higher levels of butyrate8, which has an important role in gut homeostasis and integrity22. Another driver of the Tyva and Tatarstan metagenomes, F. prausnitzii, is a prominent butyrate producer23. F. prausnitzii, E. rectale and Roseburia spp. are prevalent in controls compared with type 2 diabetes patients9, and the latter two bacteria are more abundant in controls compared with atherosclerosis patients16. On the basis of the features of the novel communities found in the Tatarstan and Tyva populations, we suggest that these metagenomes provide examples of microbiota that promote human health. Comparative functional profiling In contrast to 16S rRNA sequencing, shotgun sequencing examines not only the taxonomic composition but also the total functional genetic potential of a microbial community. Thus, sequencing reads were aligned to the MetaHIT reference catalogue of prevalent human gut microbial genes, which contains 3.3 million sequences3, and were aggregated based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) terms (see Methods). To determine significant large-scale variations in metabolism, we identified differentially abundant pathways using R package piano24 for gene set enrichment analysis (see Methods). The Malawian and Amerindian groups were not considered in this part of the comparative analysis because of their low coverage depth and possible biases. The majority of the pathways that were differentially abundant in the Russian populations compared with the US and Danish groups coincided with the observed changes in the Bacteroidetes/Firmicutes ratio (Supplementary Data 6). Enrichment of the following pathways was obviously linked to the higher levels of Firmicutes25 26: the phosphotransferase system and flagellar assembly (Russian versus Western) and ATP-binding cassette transporters (rural Russian versus urban Russian). The relative overrepresentation of the phosphotransferase system pathway in Russian metagenomes (Fig. 5) corresponded to the fact that Firmicutes are more specialized towards oligosaccharides than Bacteroidetes, which possess a repertoire of degradation enzymes for a wide variety of carbohydrates27. In contrast, Bacteroidetes-abundant groups were enriched in glycosaminoglycan degradation, amino sugar and nucleotide sugar metabolism (United States, Danish and Chinese versus Russian) and lipopolysaccharide biosynthesis (urban Russian versus rural Russian and Chinese versus Russian). These effects reflect the wealth of genes encoding glycosaminoglycan degradation enzymes in the genomes of Gram-negative Bacteroides 27 28. The small number of differentially abundant pathways identified between taxonomically distinct groups suggests that although the dominant bacteria in the Russian metagenomes varied markedly, the total microbiome remained in functional equilibrium. This conclusion is supported by the enzyme-level functional similarity of the Russian samples (pair-wise Spearman’s correlation of KO abundance 0.92±0.03, mean±s.d.) underlying the observed taxonomic diversity (pair-wise correlation for genera abundance was 0.77±0.08). This finding of metabolic homeostasis is in agreement with previous studies3 4. Discussion Few cross-national comparative studies of gut microbiomes have been performed to date5 10 17 29. Shotgun sequencing-based comparisons of functional metabolic potential and genomic diversity are only beginning to appear30 31. In this study, we performed a descriptive analysis of gut microbiomes in the Russian population, and we demonstrated their unique properties in the global context of large metagenomic studies from both taxonomic and functional perspectives. The novel features of the Russian microbiomes included original gut microbial communities (driven by genera from the Firmicutes and Actinobacteria phyla, which are associated with a healthy intestine) and underrepresented Bacteroides-driven communities. We assessed potential factors that would confound the outcomes of comparative analyses based on the available metadata, including the sample preparation method, choice of sequencing platform, and subject age and BMI. Our analyses, performed using multiple sequencing technologies, suggested that the technical bias was minimal and that DNA extraction methods were similar in all studies (see Supplementary Note 2, Methods). In particular, the original sets of three dominant genera discovered through SOLiD sequencing were almost completely reproduced using the Illumina platform, which is the most prevalent platform for whole-genome sequencing of human microbiomes. Analysis of the subjects’ age and BMI in the Russian versus non-Russian groups showed that the differences were small (Supplementary Table S3) and could, therefore, not have confounded obvious phylum-level effects. We suggest that the observed differences in microbiota composition are due to differences in diet, lifestyle and environment. The ‘drivers’ of the novel Russian communities are predominantly bacteria from the Firmicutes and Actinobacteria phyla that are nutritionally specialized towards starch27. Some of the representative species in these groups (R. bromii and E. rectale) demonstrated an increase in fraction when resistant starch was introduced into the diet32. Presumably, the novel communities are supported by high consumption of starch-rich bread and potatoes, which are typical staple foods in rural Russia, and natural products that are available even to low-income socioeconomic groups from their household plots33 34. The underrepresentation of this special microbiota in Western cohorts is correlated with the reduced consumption of resistant starch in the West compared with developing countries and increased food industrialization35 36. The similarities between the microbiota of Russian city populations and those found in Western cities are presumably associated with higher social standards and a Western lifestyle, which is particularly reflected in the diet in the form of increased consumption of meat products and processed food. We speculate that the ‘drift from the land’, which is significant in modern Russia, contributes to the greater variety of microbiota found in each city (as the three most significant compact subgroups detected by pvclust contained few urban samples). Russia comprises more than 150 ethnic groups with diverse cultural and social traditions, and a significant part of the population lives in rural areas. Thus, even a limited assessment of microbiota composition, as performed in the present study, can reveal novel communities that have not been previously observed in large metagenomic studies in other countries. We expect that broader global sampling of the microbiota of local rural cohorts, including isolated communities, will identify even greater variability in gut microbial communities. As some of the identified novel communities are primarily composed of species associated with a healthy gut, this research is of significant interest for identifying indigenous configurations of human microbiota before food industrialization and modulating the functions of the microbiota in health and disease. Although our analysis of collective metabolic capabilities revealed few differences in metabolism between different data sets, suggesting that the human microbiota is functionally stable, we expect that the real degree to which the metabolic potential is utilized will be demonstrated via metatranscriptomic and metaproteomic studies, especially on the mucosa-associated colonies at the interface of host–microbe interactions. In conclusion, we conducted a whole-genome analysis of the gut microbiomes of healthy Russian population and demonstrated that the metagenomic data was comparable across the most prevalent sequencing platforms. These data were also compared with published large-scale studies. Although the set of dominant gut bacteria was similar to those found in other populations, we identified some unique community structures. This information deepens our understanding of healthy human microbiome ecology and serves as a reference point for future epidemiological studies and translational applications. Moreover, we examined the Russian microbiota from a functional perspective, and although our results agree with earlier studies showing functional homeostasis independent of taxonomic composition, we also observed certain signatures related to carbohydrate metabolism. We further suggested possible explanations linking diet and lifestyle with microbial community functions and, finally, we showed that studying gut bacterial communities across regional cohorts with distinctive sociocultural features extends our knowledge of the landscape of healthy human gut microbiome diversity. Methods Subject enrolment criteria The Ethics Committee of the Research Institute of Physico-Chemical Medicine approved the study protocol. All participants provided written informed consent. Inclusion criteria: Male or female inhabitants of large Russian Federation cities with a prevalence of processed food in the diet, without intestinal dyspepsia symptoms, and who did not receive anti-inflammatory or antimicrobial therapy for at least 3 months before inclusion were included in the study. Male or female inhabitants of villages or small towns in the Russian Federation with a prevalence of natural food in the diet, without intestinal dyspepsia symptoms, and who did not receive anti-inflammatory or antimicrobial therapy for at least 3 months before inclusion were included in the study. Exclusion criteria: The exclusion criteria were as follows: age 0.001 and length >100) was 33,688. These sequences were extended using contigs assembled from reads that failed to map to the gene catalogue (with redundant sequences being removed). The resulting set contained 41,474 genes, representing 1.26% novel additions to the gene catalogue. Author contributions The project was designed by V.M.G., I.V.M, E.S.K., D.G.A. and V.I.S. D.G.A., E.S.K., V.M.G., I.V.M., V.V.V., R.Z.S. and V.I.S. managed the project. S.V.C., Y.A.K., V.B.G., O.I.E., E.I.S., R.A.A., S.R.A., E.A.L., M.A.L., V.V.T., M.F.O., I.V.K. and A.V.Tk. performed sample collection and clinical analysis. A.K.L, I.Y.K, O.V.S., T.A.S., E.A.O., V.V.B. and E.S.K. performed DNA extraction and sequencing. A.S.P., A.V.Ty. and M.S.B. designed and performed data analysis. A.V.Ty., A.S.P. and A.V.P. wrote the paper. D.G.A., V.M.G. and E.S.K. revised the paper. Additional information Accession codes: Gut metagenome sequences have been deposited in the Sequence Read Archive under accession code SRA059011. The contigs are available for download from the Russian Metagenome Project website ( http://www.metagenome.ru/files/rus_met/). How to cite this article: Tyakht, A.V. et al. Human gut microbiota community structures in urban and rural populations in Russia. Nat. Commun. 4:2469 doi: 10.1038/ncomms3469 (2013). Supplementary Material Supplementary Figures, Supplementary Tables and Supplementary Notes Supplementary Figures S1-S9, Supplementary Tables S1-S4, and Supplementary Notes 1-3 Supplementary Data 1 Information about the 96 human subjects in the Russian cohort. Supplementary Data 2 Fraction of the reads that were successfully mapped to the reference sets. Supplementary Data 3 Major microbial genera that varied significantly in abundance between Russians and other groups. Supplementary Data 4 Top 3 prevalent genera in the worldwide samples. Supplementary Data 5 Clustering sample assignment and optimal cluster number using various dissimilarity metrics. Supplementary Data 6 Differences in metabolic potential between the groups on the level of pathways. Supplementary Data 7 List of 444 reference microbial genomes. Supplementary Data 8 Relative abundance vectors for Russian samples and de novo assembly statistics.

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The gut microbiota of Colombians differs from that of Americans, Europeans and Asians

Juan Escobar, Bernadette Klotz, Beatriz Valdes … (2014)

Background The composition of the gut microbiota has recently been associated with health and disease, particularly with obesity. Some studies suggested a higher proportion of Firmicutes and a lower proportion of Bacteroidetes in obese compared to lean people; others found discordant patterns. Most studies, however, focused on Americans or Europeans, giving a limited picture of the gut microbiome. To determine the generality of previous observations and expand our knowledge of the human gut microbiota, it is important to replicate studies in overlooked populations. Thus, we describe here, for the first time, the gut microbiota of Colombian adults via the pyrosequencing of the 16S ribosomal DNA (rDNA), comparing it with results obtained in Americans, Europeans, Japanese and South Koreans, and testing the generality of previous observations concerning changes in Firmicutes and Bacteroidetes with increasing body mass index (BMI). Results We found that the composition of the gut microbiota of Colombians was significantly different from that of Americans, Europeans and Asians. The geographic origin of the population explained more variance in the composition of this bacterial community than BMI or gender. Concerning changes in Firmicutes and Bacteroidetes with obesity, in Colombians we found a tendency in Firmicutes to diminish with increasing BMI, whereas no change was observed in Bacteroidetes. A similar result was found in Americans. A more detailed inspection of the Colombian dataset revealed that five fiber-degrading bacteria, including Akkermansia, Dialister, Oscillospira, Ruminococcaceae and Clostridiales, became less abundant in obese subjects. Conclusion We contributed data from unstudied Colombians that showed that the geographic origin of the studied population had a greater impact on the composition of the gut microbiota than BMI or gender. Any strategy aiming to modulate or control obesity via manipulation of this bacterial community should consider this effect. Electronic supplementary material The online version of this article (doi:10.1186/s12866-014-0311-6) contains supplementary material, which is available to authorized users.

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Jae-Ho Shin: Role: Editor

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Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 1 June 2017

Publication date Collection: 2017

Volume: 12

Issue: 6

Electronic Location Identifier: e0177626

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[1 ]Ecology Department, Earth and Environmental Sciences Area, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America

[2 ]Agricultural & Environmental Chemistry Graduate Group, University of California, Davis, CA, United States of America

[3 ]Sustainable Organic Integrated Livelihoods, Port-au-Prince, Haiti

Kyungpook National University, REPUBLIC OF KOREA

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Competing Interests: The authors have declared that no competing interests exist.

Conceptualization: GLA GP-B SK.
Data curation: YMP.
Formal analysis: YMP EAD.
Funding acquisition: GLA.
Investigation: GP-B FCR YMP.
Methodology: GP-B FCR SK.
Project administration: GLA.
Resources: SK GLA.
Supervision: SK MR GLA.
Validation: GLA GP-B.
Visualization: YMP.
Writing – original draft: YMP.
Writing – review & editing: YMP EAD GLA GP-B SK MR.

* E-mail: glandersen@ 123456lbl.gov

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Gary L. Andersen http://orcid.org/0000-0002-1618-9827

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Publisher ID: PONE-D-16-21294

DOI: 10.1371/journal.pone.0177626

PMC ID: 5453478

PubMed ID: 28570610

SO-VID: e60cdfba-0d23-4890-96de-ffb3522f5d00

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This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Date received : 26 May 2016

Date accepted : 1 May 2017

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Figures: 4, Tables: 2, Pages: 30

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This work was funded by a grant from the 11th Hour Project, Palo Alto CA ( http://www.11thhourproject.org/) to GA. The Rathmann Family Foundation provided additional funding ( http://www.rathmannfamilyfoundation.org/ to GA). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Data Availability The PhyloChip data is being hosted online and is available for immediate download at http://greengenes.secondgenome.com/downloads/phylochip_datasets in LBL_MIAME_PhyloChip_Haiti-thermophilic-composting_Piceno_2017.zip.

Bacterial community structure transformed after thermophilically composting human waste in Haiti

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

The gut microbiota of Colombians differs from that of Americans, Europeans and Asians

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