Incorporating genome-based phylogeny and trait similarity into diversity assessments helps to resolve a global collection of human gut metagenomes

AbstractTree-based diversity measures incorporate phylogenetic or phenotypic relatedness into comparisons of microbial communities. This improves the identification of explanatory factors compared to tree-agnostic diversity measures. However, applying tree-based diversity measures to metagenome data is more challenging than for single-locus sequencing (e.g., 16S rRNA gene). The Genome Taxonomy Database (GTDB) provides a genome-based reference database that can be used for species-level metagenome profiling, and a multi-locus phylogeny of all genomes that can be employed for diversity calculations. Moreover, traits can be inferred from the genomic content of each representative, allowing for trait-based diversity measures. Still, it is unclear how metagenome-based assessments of microbiome diversity benefit from incorporating phylogeny or phenotype into measures of diversity. We assessed this by measuring phylogeny-based, trait-based, and tree-agnostic diversity measures from a large, global collection of human gut metagenomes composed of 33 studies and 3348 samples. We found phylogeny- and trait-based alpha diversity to better differentiate samples by westernization, age, and gender. PCoA ordinations of phylogeny- or trait-based weighted UniFrac explained more variance than tree-agnostic measures, which was largely a result of these measures emphasizing inter-phylum differences between Bacteroidaceae (Bacteroidota) and Enterobacteriaceae (Proteobacteria) versus just differences within Bacteroidaceae (Bacteroidota). The disease state of samples was better explained by tree-based weighted UniFrac, especially the presence of Shiga toxin-producing E. coli (STEC) and hypertension. Our findings show that metagenome diversity estimation benefits from incorporating a genome-derived phylogeny or traits.ImportanceEstimations of microbiome diversity are fundamental to understanding spatiotemporal changes of microbial communities and identifying which factors mediate such changes. Tree-based measures of diversity are widespread for amplicon-based microbiome studies due to their utility relative to tree-agnostic measures; however, tree-based measures are seldomly applied to shotgun metagenomics data. We evaluated the utility of phylogeny-, trait-, and tree-agnostic diversity measures on a large scale human gut metagenome dataset to help guide researchers with the complex task of evaluating microbiome diversity via metagenomics.

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Whole-Genome Metagenomic Analysis of the Gut Microbiome in HIV-1-Infected Individuals on Antiretroviral Therapy

Frontiers in Microbiology ◽

10.3389/fmicb.2021.667718 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiangning Bai ◽

Aswathy Narayanan ◽

Piotr Nowak ◽

Shilpa Ray ◽

Ujjwal Neogi ◽

...

Keyword(s):

Antiretroviral Therapy ◽

Gut Microbiome ◽

Alpha Diversity ◽

16S Rrna Gene Sequencing ◽

Taxonomic Resolution ◽

Rrna Gene ◽

Human Gut ◽

Shotgun Metagenomics ◽

Human Gut Microbiome ◽

Hiv 1

Gut microbiome plays a significant role in HIV-1 immunopathogenesis and HIV-1-associated complications. Previous studies have mostly been based on 16S rRNA gene sequencing, which is limited in taxonomic resolution at the genus level and inferred functionality. Herein, we performed a deep shotgun metagenomics study with the aim to obtain a more precise landscape of gut microbiome dysbiosis in HIV-1 infection. A reduced tendency of alpha diversity and significantly higher beta diversity were found in HIV-1-infected individuals on antiretroviral therapy (ART) compared to HIV-1-negative controls. Several species, such as Streptococcus anginosus, Actinomyces odontolyticus, and Rothia mucilaginosa, were significantly enriched in the HIV-1-ART group. Correlations were observed between the degree of immunodeficiency and gut microbiome in terms of microbiota composition and metabolic pathways. Furthermore, microbial shift in HIV-1-infected individuals was found to be associated with changes in microbial virulome and resistome. From the perspective of methodological evaluations, our study showed that different DNA extraction protocols significantly affect the genomic DNA quantity and quality. Moreover, whole metagenome sequencing depth affects critically the recovery of microbial genes, including virulome and resistome, while less than 5 million reads per sample is sufficient for taxonomy profiling in human fecal metagenomic samples. These findings advance our understanding of human gut microbiome and their potential associations with HIV-1 infection. The methodological assessment assists in future study design to accurately assess human gut microbiome.

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A Comparative Evaluation of Tools to Predict Metabolite Profiles From Microbiome Sequencing Data

Frontiers in Microbiology ◽

10.3389/fmicb.2020.595910 ◽

2020 ◽

Vol 11 ◽

Author(s):

Xiaochen Yin ◽

Tomer Altman ◽

Erica Rutherford ◽

Kiana A. West ◽

Yonggan Wu ◽

...

Keyword(s):

Large Scale ◽

Disease Diagnosis ◽

Therapeutic Drug ◽

Resonance Spectroscopy ◽

Rrna Gene ◽

Sequencing Data ◽

Human Gut ◽

Metabolic Potential ◽

Shotgun Metagenomics ◽

Prediction Approach

Metabolomic analyses of human gut microbiome samples can unveil the metabolic potential of host tissues and the numerous microorganisms they support, concurrently. As such, metabolomic information bears immense potential to improve disease diagnosis and therapeutic drug discovery. Unfortunately, as cohort sizes increase, comprehensive metabolomic profiling becomes costly and logistically difficult to perform at a large scale. To address these difficulties, we tested the feasibility of predicting the metabolites of a microbial community based solely on microbiome sequencing data. Paired microbiome sequencing (16S rRNA gene amplicons, shotgun metagenomics, and metatranscriptomics) and metabolome (mass spectrometry and nuclear magnetic resonance spectroscopy) datasets were collected from six independent studies spanning multiple diseases. We used these datasets to evaluate two reference-based gene-to-metabolite prediction pipelines and a machine-learning (ML) based metabolic profile prediction approach. With the pre-trained model on over 900 microbiome-metabolome paired samples, the ML approach yielded the most accurate predictions (i.e., highest F1 scores) of metabolite occurrences in the human gut and outperformed reference-based pipelines in predicting differential metabolites between case and control subjects. Our findings demonstrate the possibility of predicting metabolites from microbiome sequencing data, while highlighting certain limitations in detecting differential metabolites, and provide a framework to evaluate metabolite prediction pipelines, which will ultimately facilitate future investigations on microbial metabolites and human health.

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Markers of metabolic health and gut microbiome diversity: findings from two population-based cohort studies

Diabetologia ◽

10.1007/s00125-021-05464-w ◽

2021 ◽

Author(s):

Semi Zouiouich ◽

Erikka Loftfield ◽

Inge Huybrechts ◽

Vivian Viallon ◽

Panayiotis Louca ◽

...

Keyword(s):

Gut Microbiome ◽

Sequence Data ◽

Alpha Diversity ◽

Population Based ◽

Metabolic Health ◽

Rrna Gene ◽

Diversity Measures ◽

Microbiome Diversity ◽

Metabolic Variables ◽

Faecal Microbiome

Abstract Aims/hypothesis The gut microbiome is hypothesised to be related to insulin resistance and other metabolic variables. However, data from population-based studies are limited. We investigated associations between serologic measures of metabolic health and the gut microbiome in the Northern Finland Birth Cohort 1966 (NFBC1966) and the TwinsUK cohort. Methods Among 506 individuals from the NFBC1966 with available faecal microbiome (16S rRNA gene sequence) data, we estimated associations between gut microbiome diversity metrics and serologic levels of HOMA for insulin resistance (HOMA-IR), HbA1c and C-reactive protein (CRP) using multivariable linear regression models adjusted for sex, smoking status and BMI. Associations between gut microbiome diversity measures and HOMA-IR and CRP were replicated in 1140 adult participants from TwinsUK, with available faecal microbiome (16S rRNA gene sequence) data. For both cohorts, we used general linear models with a quasi-Poisson distribution and Microbiome Regression-based Kernel Association Test (MiRKAT) to estimate associations of metabolic variables with alpha- and beta diversity metrics, respectively, and generalised additive models for location scale and shape (GAMLSS) fitted with the zero-inflated beta distribution to identify taxa associated with the metabolic markers. Results In NFBC1966, alpha diversity was lower in individuals with higher HOMA-IR with a mean of 74.4 (95% CI 70.7, 78.3) amplicon sequence variants (ASVs) for the first quartile of HOMA-IR and 66.6 (95% CI 62.9, 70.4) for the fourth quartile of HOMA-IR. Alpha diversity was also lower with higher HbA1c (number of ASVs and Shannon’s diversity, p < 0.001 and p = 0.003, respectively) and higher CRP (number of ASVs, p = 0.025), even after adjustment for BMI and other potential confounders. In TwinsUK, alpha diversity measures were also lower among participants with higher measures of HOMA-IR and CRP. When considering beta diversity measures, we found that microbial community profiles were associated with HOMA-IR in NFBC1966 and TwinsUK, using multivariate MiRKAT models, with binomial deviance dissimilarity p values of <0.001. In GAMLSS models, the relative abundances of individual genera Prevotella and Blautia were associated with HOMA-IR in both cohorts. Conclusions/interpretation Overall, higher levels of HOMA-IR, CRP and HbA1c were associated with lower microbiome diversity in both the NFBC1966 and TwinsUK cohorts, even after adjustment for BMI and other variables. These results from two distinct population-based cohorts provide evidence for an association between metabolic variables and gut microbial diversity. Further experimental and mechanistic insights are now needed to provide understanding of the potential causal mechanisms that may link the gut microbiota with metabolic health. Graphical abstract

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Metagenomic and Metatranscriptomic Responses of Chemical Dispersant Application during a Marine Dilbit Spill

Applied and Environmental Microbiology ◽

10.1128/aem.02151-21 ◽

2022 ◽

Author(s):

Yiqi Cao ◽

Baiyu Zhang ◽

Charles W. Greer ◽

Kenneth Lee ◽

Qinhong Cai ◽

...

Keyword(s):

Microbial Community ◽

Late Stage ◽

Large Scale ◽

Community Dynamics ◽

Early Stage ◽

Small Scale ◽

Rrna Gene ◽

Shotgun Metagenomics ◽

Microcosm Studies ◽

Over Time

The global increase in marine transportation of dilbit (diluted bitumen) can increase the risk of spills, and the application of chemical dispersants remains a common response practice in spill events. To reliably evaluate dispersant effects on dilbit biodegradation over time, we set large-scale (1500 mL) microcosms without nutrients addition using low dilbit concentration (30 ppm). Shotgun metagenomics and metatranscriptomics were deployed to investigate microbial community responses to naturally and chemically dispersed dilbit. We found that the large-scale microcosms could produce more reproducible community trajectories than small-scale (250 mL) ones based on the 16S rRNA gene amplicon sequencing. In the early-stage large-scale microcosms, multiple genera were involved into the biodegradation of dilbit, while dispersant addition enriched primarily Alteromonas and competed for the utilization of dilbit, causing depressed degradation of aromatics. The metatranscriptomic based Metagenome Assembled Genomes (MAG) further elucidated early-stage microbial antioxidation mechanism, which showed dispersant addition triggered the increased expression of the antioxidation process genes of Alteromonas species. Differently, in the late stage, the microbial communities showed high diversity and richness and similar compositions and metabolic functions regardless of dispersant addition, indicating the biotransformation of remaining compounds can occur within the post-oil communities. These findings can guide future microcosm studies and the application of chemical dispersants for responding to a marine dilbit spill. Importance In this study, we employed microcosms to study the effects of marine dilbit spill and dispersant application on microbial community dynamics over time. We evaluated the impacts of microcosm scale and found that increasing the scale is beneficial for reducing community stochasticity, especially in the late stage of biodegradation. We observed that dispersant application suppressed aromatics biodegradation in the early stage (6 days) whereas exerting insignificant effects in the late stage (50 days), from both substances removal and metagenomic/metatranscriptomic perspectives. We further found that Alteromonas species are vital for the early-stage chemically dispersed oil biodegradation, and clarified their degradation and antioxidation mechanisms. The findings would help to better understand microcosm studies and microbial roles for biodegrading dilbit and chemically dispersed dilbit, and suggest that dispersant evaluation in large-scale systems and even through field trails would be more realistic after marine oil spill response.

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Association between the microbiomes of tonsil and saliva samples isolated from pediatric patients subjected to tonsillectomy for the treatment of tonsillar hyperplasia

Experimental & Molecular Medicine ◽

10.1038/s12276-020-00487-6 ◽

2020 ◽

Vol 52 (9) ◽

pp. 1564-1573

Author(s):

Da Hyeon Choi ◽

Jiwon Park ◽

Ju Kwang Choi ◽

Kyeong Eun Lee ◽

Won Hee Lee ◽

...

Keyword(s):

Oral Cavity ◽

Microbial Communities ◽

Alpha Diversity ◽

16S Rrna Gene Sequencing ◽

Diversity Indices ◽

Rrna Gene ◽

Strong Positive Correlation ◽

Korean Children ◽

Positive Correlation ◽

Tonsillar Hyperplasia

Abstract Oral microbes have the capacity to spread throughout the gastrointestinal system and are strongly associated with multiple diseases. Given that tonsils are located between the oral cavity and the laryngopharynx at the gateway of the alimentary and respiratory tracts, tonsillar tissue may also be affected by microbiota from both the oral cavity (saliva) and the alimentary tract. Here, we analyzed the distribution and association of the microbial communities in the saliva and tonsils of Korean children subjected to tonsillectomy because of tonsil hyperplasia (n = 29). The microbiome profiles of saliva and tonsils were established via 16S rRNA gene sequencing. Based on the alpha diversity indices, the microbial communities of the two groups showed high similarities. According to Spearman’s ranking correlation analysis, the distribution of Treponema, the causative bacterium of periodontitis, in saliva and tonsils was found to have a significant positive correlation. Two representative microbes, Prevotella in saliva and Alloprevotella in tonsils, were negatively correlated, while Treponema 2 showed a strong positive correlation between saliva and tonsils. Taken together, strong similarities in the microbial communities of the tonsils and saliva are evident in terms of diversity and composition. The saliva microbiome is expected to significantly affect the tonsil microbiome. Furthermore, we suggest that our study creates an opportunity for tonsillar microbiome research to facilitate the development of novel microbiome-based therapeutic strategies.

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Impact of Diabetes on the Gut and Salivary IgA Microbiomes

Infection and Immunity ◽

10.1128/iai.00301-20 ◽

2020 ◽

Vol 88 (12) ◽

Author(s):

Eric L. Brown ◽

Heather T. Essigmann ◽

Kristi L. Hoffman ◽

Noah W. Palm ◽

Sarah M. Gunter ◽

...

Keyword(s):

Microbial Communities ◽

Immunoglobulin A ◽

Alpha Diversity ◽

16S Rrna Gene Sequencing ◽

Rrna Gene ◽

Host Immune Responses ◽

Mucosal Surfaces ◽

Immune Mediated ◽

Rrna Gene Sequencing ◽

Immune Exclusion

ABSTRACT Mucosal surfaces like those present in the lung, gut, and mouth interface with distinct external environments. These mucosal gateways are not only portals of entry for potential pathogens but also homes to microbial communities that impact host health. Secretory immunoglobulin A (SIgA) is the single most abundant acquired immune component secreted onto mucosal surfaces and, via the process of immune exclusion, shapes the architecture of these microbiomes. Not all microorganisms at mucosal surfaces are targeted by SIgA; therefore, a better understanding of the SIgA-coated fraction may identify the microbial constituents that stimulate host immune responses in the context of health and disease. Chronic diseases like type 2 diabetes are associated with altered microbial communities (dysbiosis) that in turn affect immune-mediated homeostasis. 16S rRNA gene sequencing of SIgA-coated/uncoated bacteria (IgA-Biome) was conducted on stool and saliva samples of normoglycemic participants and individuals with prediabetes or diabetes (n = 8/group). These analyses demonstrated shifts in relative abundance in the IgA-Biome profiles between normoglycemic, prediabetic, or diabetic samples distinct from that of the overall microbiome. Differences in IgA-Biome alpha diversity were apparent for both stool and saliva, while overarching bacterial community differences (beta diversity) were also observed in saliva. These data suggest that IgA-Biome analyses can be used to identify novel microbial signatures associated with diabetes and support the need for further studies exploring these communities. Ultimately, an understanding of the IgA-Biome may promote the development of novel strategies to restructure the microbiome as a means of preventing or treating diseases associated with dysbiosis at mucosal surfaces.

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Altered Bacterial-Fungal Interkingdom Networks in the Guts of Ankylosing Spondylitis Patients

mSystems ◽

10.1128/msystems.00176-18 ◽

2019 ◽

Vol 4 (2) ◽

Cited By ~ 8

Author(s):

Ming Li ◽

Bingbing Dai ◽

Yawei Tang ◽

Lei Lei ◽

Ningning Li ◽

...

Keyword(s):

Ankylosing Spondylitis ◽

Disease Activity ◽

Large Scale ◽

Activity Index ◽

Disease Activity Index ◽

Rrna Gene ◽

Human Gut ◽

Reactive Protein ◽

Inflammatory Drugs ◽

Bacteria And Fungi

ABSTRACT Intestinal bacterial dysbiosis has been increasingly linked to ankylosing spondylitis (AS), which is a prototypic and best studied subtype of spondyloarthritis (SpA). Fungi and bacteria coexist in the human gut and interact with each other. Although they have been shown to contribute actively to health or disease, no studies have investigated whether the fungal microbiota in AS patients is perturbed. In this study, fecal samples from 22 AS patients, with clinical and radiographic assessments, and 16 healthy controls (HCs) were collected to systematically characterize the gut microbiota and mycobiota in AS patients by 16S rRNA gene- and ITS2-based DNA sequencing. Our results showed that the microbiota of AS patients was characterized by increased abundance of Proteobacteria and decreased Bacteroidetes, which was contributed by enrichment of Escherichia-Shigella, Veillonella, Lachnospiraceae NK4A136 group, and reduction of Prevotella strain 9, Megamona, and Fusobacterium. The gut mycobiota of AS patients was characterized by higher levels of Ascomycota, especially the class of Dothideomycetes, and decreased abundance of Basidiomycota, which was mainly contributed by the decease of Agaricales. Compared to HCs, decreased ITS2/16S biodiversity ratios and altered bacterial-fungal interkingdom networks were observed in AS patients. Compared with nonsteroidal anti-inflammatory drugs (NSAIDs), treating AS patients with biological agents induced obvious changes in the gut mycobiota, and this result was highly associated with disease activity indexes, including AS disease activity index (ASDAS) C-reactive protein (asCRP), erythrocyte sedimentation rate (ESR), and Bath AS disease activity index (BASDAI). In addition, altered mycobiota in AS patients was also found associated with the degree of radiographic damage. IMPORTANCE The human gut is colonized by diverse fungi (mycobiota), and fungi have long been suspected in the pathogenesis of SpA. Our study unraveled a disease-specific interkingdom network alteration in AS, suggesting that fungi, or the interkingdom interactions between bacteria and fungi, may play an essential role in AS development. However, our study is limited by sample size, and in-depth mechanism studies and additional large-scale investigations characterizing the gut mycobiome in AS patients are needed to form a foundation for research into the relationship between mycobiota dysbiosis and AS development.

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Locally Adapted Mimulus Ecotypes Differentially Impact Rhizosphere Bacterial and Archaeal Communities in an Environment-Dependent Manner

Phytobiomes Journal ◽

10.1094/pbiomes-05-19-0026-r ◽

2020 ◽

Vol 4 (1) ◽

pp. 53-63 ◽

Cited By ~ 2

Author(s):

Alan W. Bowsher ◽

Patrick J. Kearns ◽

Damian Popovic ◽

David B. Lowry ◽

Ashley Shade

Keyword(s):

Microbial Communities ◽

Plant Root ◽

Alpha Diversity ◽

Local Environment ◽

Rrna Gene ◽

Transplant Experiment ◽

Dependent Manner ◽

Reciprocal Transplant Experiment ◽

Soil Microbial Community Structure ◽

Host Identity

Plant root−microbe interactions influence plant productivity, health, and resistance to stress. Although there is evidence that plant species and even genotypes can alter soil microbial community structure, environmental conditions can potentially outweigh plant genetic effects. Here, we used a reciprocal transplant experiment to understand the contributions of the environment and the host plant to rhizosphere microbiome composition in locally adapted ecotypes of Mimulus guttatus (syn. Erythranthe guttata). Two genotypes of a coastal ecotype and two genotypes of an inland ecotype were planted at coastal and inland sites. After 3 months, we collected rhizosphere and bulk soil and assessed microbial communities by 16S rRNA gene sequencing. We found that local environment (coastal versus inland site) strongly influenced rhizosphere communities, at least in part due to distinct local microbial species pools. Host identity played a smaller role: at each site, the ecotypes exhibited remarkably similar composition of microbial communities at the class level, indicating that divergent M. guttatus ecotypes recruit phylogenetically similar rhizosphere communities, even in environments to which they are maladapted. Nevertheless, the two ecotypes significantly differed in community composition at both sites due, in part, to an exclusive set of taxa associated with each ecotype. They also differed in alpha diversity at the inland site. Although this indicates that locally adapted M. guttatus ecotypes are genetically diverged in factors shaping rhizosphere communities, our findings highlight the context-specific interactions between host identity and local environment that shape those communities. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

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Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank

Microbiome ◽

10.1186/s40168-021-01064-3 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Chang Liu ◽

Meng-Xuan Du ◽

Rexiding Abuduaini ◽

Hai-Ying Yu ◽

Dan-Hua Li ◽

...

Keyword(s):

Large Scale ◽

Human Microbiome ◽

In Silico Analysis ◽

Human Microbiome Project ◽

Public Access ◽

Rrna Gene ◽

New Genera ◽

Human Gut ◽

Isolation And Identification ◽

Culture Collections

Abstract Background In gut microbiome studies, the cultured gut microbial resource plays essential roles, such as helping to unravel gut microbial functions and host-microbe interactions. Although several major studies have been performed to elucidate the cultured human gut microbiota, up to 70% of the Unified Human Gastrointestinal Genome species have not been cultured to date. Large-scale gut microbial isolation and identification as well as availability to the public are imperative for gut microbial studies and further characterizing human gut microbial functions. Results In this study, we constructed a human Gut Microbial Biobank (hGMB; homepage: hgmb.nmdc.cn) through the cultivation of 10,558 isolates from 31 sample mixtures of 239 fresh fecal samples from healthy Chinese volunteers, and deposited 1170 strains representing 400 different species in culture collections of the International Depository Authority for long-term preservation and public access worldwide. Following the rules of the International Code of Nomenclature of Prokaryotes, 102 new species were characterized and denominated, while 28 new genera and 3 new families were proposed. hGMB represented over 80% of the common and dominant human gut microbial genera and species characterized from global human gut 16S rRNA gene amplicon data (n = 11,647) and cultured 24 “most-wanted” and “medium priority” taxa proposed by the Human Microbiome Project. We in total sequenced 115 genomes representing 102 novel taxa and 13 previously known species. Further in silico analysis revealed that the newly sequenced hGMB genomes represented 22 previously uncultured species in the Unified Human Gastrointestinal Genome (UHGG) and contributed 24 representatives of potentially “dark taxa” that had not been discovered by UHGG. The nonredundant gene catalogs generated from the hGMB genomes covered over 50% of the functionally known genes (KEGG orthologs) in the largest global human gut gene catalogs and approximately 10% of the “most wanted” functionally unknown proteins in the FUnkFams database. Conclusions A publicly accessible human Gut Microbial Biobank (hGMB) was established that contained 1170 strains and represents 400 human gut microbial species. hGMB expands the gut microbial resources and genomic repository by adding 102 novel species, 28 new genera, 3 new families, and 115 new genomes of human gut microbes.

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Analysis of Human Gut Microbiome: Taxonomy and Metabolic Functions in Thai Adults

Genes ◽

10.3390/genes12030331 ◽

2021 ◽

Vol 12 (3) ◽

pp. 331

Author(s):

Nachon Raethong ◽

Massalin Nakphaichit ◽

Narissara Suratannon ◽

Witida Sathitkowitchai ◽

Wanlapa Weerapakorn ◽

...

Keyword(s):

Gut Microbiome ◽

Asian Country ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Human Gut ◽

Thai Population ◽

Shotgun Metagenomics ◽

Human Gut Microbiome ◽

Metabolic Functions

The gut microbiome plays a major role in the maintenance of human health. Characterizing the taxonomy and metabolic functions of the human gut microbiome is necessary for enhancing health. Here, we analyzed the metagenomic sequencing, assembly and construction of a meta-gene catalogue of the human gut microbiome with the overall aim of investigating the taxonomy and metabolic functions of the gut microbiome in Thai adults. As a result, the integrative analysis of 16S rRNA gene and whole metagenome shotgun (WMGS) sequencing data revealed that the dominant gut bacterial families were Lachnospiraceae and Ruminococcaceae of the Firmicutes phylum. Consistently, across 3.8 million (M) genes annotated from 163.5 gigabases (Gb) of WMGS sequencing data, a significant number of genes associated with carbohydrate metabolism of the dominant bacterial families were identified. Further identification of bacterial community-wide metabolic functions promisingly highlighted the importance of Roseburia and Faecalibacterium involvement in central carbon metabolism, sugar utilization and metabolism towards butyrate biosynthesis. This work presents an initial study of shotgun metagenomics in a Thai population-based cohort in a developing Southeast Asian country.

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