Genomic diversity and ecology of human-associated Akkermansia species in the gut microbiome revealed by extensive metagenomic assembly

Abstract Background Akkermansia muciniphila is a human gut microbe with a key role in the physiology of the intestinal mucus layer and reported associations with decreased body mass and increased gut barrier function and health. Despite its biomedical relevance, the genomic diversity of A. muciniphila remains understudied and that of closely related species, except for A. glycaniphila, unexplored. Results We present a large-scale population genomics analysis of the Akkermansia genus using 188 isolate genomes and 2226 genomes assembled from 18,600 metagenomes from humans and other animals. While we do not detect A. glycaniphila, the Akkermansia strains in the human gut can be grouped into five distinct candidate species, including A. muciniphila, that show remarkable whole-genome divergence despite surprisingly similar 16S rRNA gene sequences. These candidate species are likely human-specific, as they are detected in mice and non-human primates almost exclusively when kept in captivity. In humans, Akkermansia candidate species display ecological co-exclusion, diversified functional capabilities, and distinct patterns of associations with host body mass. Analysis of CRISPR-Cas loci reveals new variants and spacers targeting newly discovered putative bacteriophages. Remarkably, we observe an increased relative abundance of Akkermansia when cognate predicted bacteriophages are present, suggesting ecological interactions. A. muciniphila further exhibits subspecies-level genetic stratification with associated functional differences such as a putative exo/lipopolysaccharide operon. Conclusions We uncover a large phylogenetic and functional diversity of the Akkermansia genus in humans. This variability should be considered in the ongoing experimental and metagenomic efforts to characterize the health-associated properties of A. muciniphila and related bacteria.

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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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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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Enlightening the Taxonomy Darkness of Human Gut Microbiomes With Cultured Biobank

10.21203/rs.3.rs-74101/v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

Chang Liu ◽

Meng-Xuan Du ◽

Rexiding Abuduaini ◽

Hai-Ying Yu ◽

Dan-Hua Li ◽

...

Keyword(s):

New Species ◽

Large Scale ◽

Human Microbiome ◽

Human Microbiome Project ◽

Public Access ◽

Rrna Gene ◽

New Genera ◽

Human Gut ◽

Isolation And Identification ◽

Gut Microbes

Abstract Background The cultivated gut microbial resource plays essential role in gut microbiome studies such as gut microbial function and their interactions with host. Though several major studies had been performed to understand the cultured human gut microbiota, up to 70% of the Unified Human Gastrointestinal Genome species remain uncultivated and their taxonomy is not clear. Large-scale gut microbial isolation and identification and their access to pubic are imperative for gut microbial studies and for understanding of the human gut microbial functions.Results Here, we report the construction of an human Gut Microbial Biobank (hGMB) (homepage: hgmb.nmdc.cn) by large-scale cultivation of 10,558 isolates from 239 feces of healthy Chinese volunteers, and deposited 1,170 strains representing 404 different species in International Depository Authority for long-term preservation and public access worldwidely. We discovered and denominated 107 new species, and proposed 28 new genera and 3 new families. The new species and their newly sequenced genomes uncovered 16 “most-wanted” or “medium priority” taxa proposed by the Human Microbiome Project and 42 previously-uncultured MAGs in IGGdb, respectively. The hGMB represented over 80% of the common and dominant human gut microbial genera or species of global human gut 16S rRNA gene amplicon data (n=11,647), and covered 70% of the known genes (KEGG Orthologys) and 10% of the functionally-unknown genes in the global human gut gene catalogs. Conclusions A publically accessible human Gut Microbial Biobank (hGMB) that contains 1,170 strains and represents 404 human gut microbial speces is estabolished. The hGMB expands the currently known, taxonomically-characterized gut microbial resources and genomic repository by adding 107 new species and 115 new genomes of human gut microbes. Based on the newly discovered species in this study, 28 new genera and 3 new families of human gut microbes were identified and proposed.

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

10.1101/2020.07.16.207845 ◽

2020 ◽

Author(s):

Nicholas D. Youngblut ◽

Jacobo de la Cuesta-Zuluaga ◽

Ruth E. Ley

Keyword(s):

Microbial Communities ◽

Large Scale ◽

Alpha Diversity ◽

Reference Database ◽

Rrna Gene ◽

Human Gut ◽

Shotgun Metagenomics ◽

Diversity Measures ◽

Microbiome Diversity ◽

A Genome

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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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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Enlightening the Taxonomy Darkness of Human Gut Microbiomes With a Cultured Biobank

10.21203/rs.3.rs-168279/v1 ◽

2021 ◽

Author(s):

Chang Liu ◽

Mengxuan Du ◽

Rexiding Abuduaini ◽

Hai-Ying Yu ◽

Dan-Hua Li ◽

...

Keyword(s):

Large Scale ◽

Human Microbiome ◽

Human Microbiome Project ◽

Public Access ◽

Rrna Gene ◽

New Genera ◽

Human Gut ◽

Isolation And Identification ◽

Culture Collections ◽

Host Microbe Interactions

Abstract BackgroundThe cultivated gut microbial resource plays essential roles in gut microbiome studies such as unraveling gut microbial functions and host-microbe interactions. Though several major studies have been performed to understand the cultured human gut microbiota, up to 70% of the Unified Human Gastrointestinal Genome species remain uncultivated. Large-scale gut microbial isolation and identification and their access to public are imperative for gut microbial studies and further understanding of the human gut microbial functions.ResultsHere, we report the construction of a human Gut Microbial Biobank (hGMB) (homepage: hgmb.nmdc.cn) by cultivation of 10,558 isolates from 239 feces samples of healthy Chinese volunteers, and deposited 1,170 strains representing 400 different species in culture collections of International Depository Authority for long-term preservation and public access worldwide. The hGMB enriched the existing cultivable gut microbial repository and represented over 80% of the common and dominant human gut microbial genera and species of global human gut 16S rRNA gene amplicon data (n=11,647).Moreover, 102 new species were characterized and denominated and 28 new genera and 3 new families were proposed, following the rules of International Code of Nomenclature of Prokaryotes. The hGMB uncovered 24 “most-wanted” and “medium priority” taxa proposed by the Human Microbiome Project, while the novel-taxon genomes represented 22 previously-uncultured species in Unified Human Gastrointestinal Genome (UHGG) and contributed 24 potentially “dark-taxon” representatives that were not discovered by UHGG. The 115 newly-sequenced hGMB genomes covered over 50% of the known genes (KEGG Orthologs) in the global human gut gene catalogs and over 10% of the “most-wanted” functionally unknown proteins in FUnkFams database.ConclusionsA publicly accessible human Gut Microbial Biobank (hGMB) is established and contains 1,170 strains and represents 400 human gut microbial species. The hGMB expands gut microbial resources and genomic repository by adding 102 novel species, 28 new genera and 3 new families, and 115 new genomes of human gut microbes.

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Flavonoid-Modifying Capabilities of the Human Gut Microbiome—An In Silico Study

Nutrients ◽

10.3390/nu13082688 ◽

2021 ◽

Vol 13 (8) ◽

pp. 2688

Author(s):

Tobias Goris ◽

Rafael R. C. Cuadrat ◽

Annett Braune

Keyword(s):

Gut Microbiome ◽

Large Scale ◽

Health Impact ◽

Gut Bacteria ◽

Human Gut ◽

Positive Health ◽

Human Gut Microbiome ◽

Nutritional Recommendations ◽

Genes Encoding ◽

A Minor

Flavonoids are a major group of dietary plant polyphenols and have a positive health impact, but their modification and degradation in the human gut is still widely unknown. Due to the rise of metagenome data of the human gut microbiome and the assembly of hundreds of thousands of bacterial metagenome-assembled genomes (MAGs), large-scale screening for potential flavonoid-modifying enzymes of human gut bacteria is now feasible. With sequences of characterized flavonoid-transforming enzymes as queries, the Unified Human Gastrointestinal Protein catalog was analyzed and genes encoding putative flavonoid-modifying enzymes were quantified. The results revealed that flavonoid-modifying enzymes are often encoded in gut bacteria hitherto not considered to modify flavonoids. The enzymes for the physiologically important daidzein-to-equol conversion, well studied in Slackiaisoflavoniconvertens, were encoded only to a minor extent in Slackia MAGs, but were more abundant in Adlercreutzia equolifaciens and an uncharacterized Eggerthellaceae species. In addition, enzymes with a sequence identity of about 35% were encoded in highly abundant MAGs of uncultivated Collinsella species, which suggests a hitherto uncharacterized daidzein-to-equol potential in these bacteria. Of all potential flavonoid modification steps, O-deglycosylation (including derhamnosylation) was by far the most abundant in this analysis. In contrast, enzymes putatively involved in C-deglycosylation were detected less often in human gut bacteria and mainly found in Agathobacter faecis (formerly Roseburia faecis). Homologs to phloretin hydrolase, flavanonol/flavanone-cleaving reductase and flavone reductase were of intermediate abundance (several hundred MAGs) and mainly prevalent in Flavonifractor plautii. This first comprehensive insight into the black box of flavonoid modification in the human gut highlights many hitherto overlooked and uncultured bacterial genera and species as potential key organisms in flavonoid modification. This could lead to a significant contribution to future biochemical-microbiological investigations on gut bacterial flavonoid transformation. In addition, our results are important for individual nutritional recommendations and for biotechnological applications that rely on novel enzymes catalyzing potentially useful flavonoid modification reactions.

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Identification of an N-acetylneuraminic acid-presenting bacteria isolated from a human microbiome

Scientific Reports ◽

10.1038/s41598-021-83875-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhen Han ◽

Peter S. Thuy-Boun ◽

Wayne Pfeiffer ◽

Vincent F. Vartabedian ◽

Ali Torkamani ◽

...

Keyword(s):

Pathogenic Bacteria ◽

Human Microbiome ◽

Host Immunity ◽

Rrna Gene ◽

Metabolic Labeling ◽

Selective Labeling ◽

Fecal Microbiome ◽

Acetylneuraminic Acid ◽

Intestinal Mucus ◽

Microbial Systems

AbstractN-Acetylneuraminic acid is the most abundant sialic acid (SA) in humans and is expressed as the terminal sugar on intestinal mucus glycans. Several pathogenic bacteria harvest and display host SA on their own surfaces to evade Siglec-mediated host immunity. While previous studies have identified bacterial enzymes associated with SA catabolism, no reported methods permit the selective labeling, tracking, and quantitation of SA-presenting microbes within complex multi-microbial systems. We combined metabolic labeling, click chemistry, 16S rRNA gene, and whole-genome sequencing to track and identify SA-presenting microbes from a cultured human fecal microbiome. We isolated a new strain of Escherichia coli that incorporates SA onto its own surface and encodes for the nanT, neuA, and neuS genes necessary for harvesting and presenting SA. Our method is applicable to the identification of SA-presenting bacteria from human, animal, and environmental microbiomes, as well as providing an entry point for the investigation of surface-expressed SA-associated structures.

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Meta-Apo improves accuracy of 16S-amplicon-based prediction of microbiome function

BMC Genomics ◽

10.1186/s12864-020-07307-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Gongchao Jing ◽

Yufeng Zhang ◽

Wenzhi Cui ◽

Lu Liu ◽

Jian Xu ◽

...

Keyword(s):

16S Rrna ◽

Large Scale ◽

Low Cost ◽

Human Microbiome ◽

Amplicon Sequencing ◽

Training Sample ◽

Rrna Gene ◽

16S Amplicon Sequencing ◽

Cross Platform ◽

Functional Profiles

Abstract Background Due to their much lower costs in experiment and computation than metagenomic whole-genome sequencing (WGS), 16S rRNA gene amplicons have been widely used for predicting the functional profiles of microbiome, via software tools such as PICRUSt 2. However, due to the potential PCR bias and gene profile variation among phylogenetically related genomes, functional profiles predicted from 16S amplicons may deviate from WGS-derived ones, resulting in misleading results. Results Here we present Meta-Apo, which greatly reduces or even eliminates such deviation, thus deduces much more consistent diversity patterns between the two approaches. Tests of Meta-Apo on > 5000 16S-rRNA amplicon human microbiome samples from 4 body sites showed the deviation between the two strategies is significantly reduced by using only 15 WGS-amplicon training sample pairs. Moreover, Meta-Apo enables cross-platform functional comparison between WGS and amplicon samples, thus greatly improve 16S-based microbiome diagnosis, e.g. accuracy of gingivitis diagnosis via 16S-derived functional profiles was elevated from 65 to 95% by WGS-based classification. Therefore, with the low cost of 16S-amplicon sequencing, Meta-Apo can produce a reliable, high-resolution view of microbiome function equivalent to that offered by shotgun WGS. Conclusions This suggests that large-scale, function-oriented microbiome sequencing projects can probably benefit from the lower cost of 16S-amplicon strategy, without sacrificing the precision in functional reconstruction that otherwise requires WGS. An optimized C++ implementation of Meta-Apo is available on GitHub (https://github.com/qibebt-bioinfo/meta-apo) under a GNU GPL license. It takes the functional profiles of a few paired WGS:16S-amplicon samples as training, and outputs the calibrated functional profiles for the much larger number of 16S-amplicon samples.

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Population genomics and antimicrobial resistance dynamics of Escherichia coli in wastewater and river environments

Communications Biology ◽

10.1038/s42003-021-01949-x ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Jose F. Delgado-Blas ◽

Cristina M. Ovejero ◽

Sophia David ◽

Natalia Montero ◽

William Calero-Caceres ◽

...

Keyword(s):

Escherichia Coli ◽

Antimicrobial Resistance ◽

Population Genomics ◽

Population Diversity ◽

Genomic Diversity ◽

Resistant Bacteria ◽

Aquatic Environments ◽

E Coli ◽

Water Ecosystems ◽

Sequence Types

AbstractAquatic environments are key niches for the emergence, evolution and dissemination of antimicrobial resistance. However, the population diversity and the genetic elements that drive the dynamics of resistant bacteria in different aquatic environments are still largely unknown. The aim of this study was to understand the population genomics and evolutionary events of Escherichia coli resistant to clinically important antibiotics including aminoglycosides, in anthropogenic and natural water ecosystems. Here we show that less different E. coli sequence types (STs) are identified in wastewater than in rivers, albeit more resistant to antibiotics, and with significantly more plasmids/cell (6.36 vs 3.72). However, the genomic diversity within E. coli STs in both aquatic environments is similar. Wastewater environments favor the selection of conserved chromosomal structures associated with diverse flexible plasmids, unraveling promiscuous interplasmidic resistance genes flux. On the contrary, the key driver for river E. coli adaptation is a mutable chromosome along with few plasmid types shared between diverse STs harboring a limited resistance gene content.

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