Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle
Open accessAbstract
The body-wide human microbiome plays a role in health, but its full diversity remains uncharacterized, particularly outside of the gut and in international populations. We leveraged 9,428 metagenomes to reconstruct 154,723 microbial genomes (45% of high quality) spanning body sites, ages, countries, and lifestyles. We recapitulated 4,930 species-level genome bins (SGBs), 77% without genomes in public repositories (unknown SGBs [uSGBs]). uSGBs are prevalent (in 93% of well-assembled samples), expand underrepresented phyla, and are enriched in non-Westernized populations (40% of the total SGBs). We annotated 2.85 M genes in SGBs, many associated with conditions including infant development (94,000) or Westernization (106,000). SGBs and uSGBs permit deeper microbiome analyses and increase the average mappability of metagenomic reads from 67.76% to 87.51% in the gut (median 94.26%) and 65.14% to 82.34% in the mouth. We thus identify thousands of microbial genomes from yet-to-be-named species, expand the pangenomes of human-associated microbes, and allow better exploitation of metagenomic technologies.
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A large fraction of the gut microbiome's individual uniqueness is encoded at the level of single strains.
“and a large fraction of this uniqueness is encoded at the level of single strains36–38.”
From Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma (2022) · cites this paper as [37]
The Results section on sample-specific strain recovery reports substantial diversity among gut microbial strains, including previously unsampled diversity within Bacteroides species. It does not establish that a large fraction of the gut microbiome’s uniqueness between individuals is attributable to single strains; no page number is available in our copy. (LLM, conf=0.82)
Experimental — accuracy not yet measuredWhile the inherited genome is essentially stable for the lifetime of the host, the microbiome is immensely diverse, dynamic, and responsive to external input, enhancing its potential as a target for therapeutic intervention.
“While our inherited genome is essentially stable for the lifetime of the host, the microbiome is immensely diverse (Mosca et al., 2016;Pasolli et al., 2019), dynamic (Lloyd-Price et al., 2017), and responsive to external input, enhancing its potential as a target for therapeutic intervention”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Pasolli et al., 2019
Large-scale cultivation projects and massive metagenomic assembly efforts are quickly expanding and completing reference databases needed for taxonomic profiling tools.
“However, particularly for the gut microbiome, largescale cultivation projects 134 and massive metagenomic assembly efforts 135 are quickly expanding and completing reference databases needed for taxonomic profiling tools. 136”
From Key determinants of success in fecal microbiota transplantation: From microbiome to clinic (2023) · cites this paper as [135]
With the vast majority of the microbiome remaining uncultured, phenotypes cannot be tested in a straightforward manner.
“With the vast majority of the microbiome remaining so far uncultured, 135 phenotypes cannot be tested in a straightforward manner.”
From Key determinants of success in fecal microbiota transplantation: From microbiome to clinic (2023) · cites this paper as [135]
Complete characterization of stool composition is so far impossible to achieve, even with the most recent multiomic approaches.
“However, the complete characterization of stool composition is so far impossible to achieve, even with the most recent multiomic approaches.”
From Key determinants of success in fecal microbiota transplantation: From microbiome to clinic (2023) · cites this paper as [135]
80%-90% of metabolites cannot be identified.
“Based on what is known and what is feasible, 20%-50% of shotgun metagenomic reads cannot be mapped, 30%-50% of identified genes are of unknown function, and most strikingly, 80%-90% of metabolites cannot be identified. 135,147”
From Key determinants of success in fecal microbiota transplantation: From microbiome to clinic (2023) · cites this paper as [135]
30%-50% of identified genes are of unknown function.
“Based on what is known and what is feasible, 20%-50% of shotgun metagenomic reads cannot be mapped, 30%-50% of identified genes are of unknown function, and most strikingly, 80%-90% of metabolites cannot be identified. 135,147”
From Key determinants of success in fecal microbiota transplantation: From microbiome to clinic (2023) · cites this paper as [135]
20%-50% of shotgun metagenomic reads cannot be mapped.
“Based on what is known and what is feasible, 20%-50% of shotgun metagenomic reads cannot be mapped, 30%-50% of identified genes are of unknown function, and most strikingly, 80%-90% of metabolites cannot be identified. 135,147”
From Key determinants of success in fecal microbiota transplantation: From microbiome to clinic (2023) · cites this paper as [135]
Dark matter not previously characterized in the laboratory pervades host-associated and especially environmental metagenomes, with most communities containing a plurality, majority, or sometimes supermajority of novel and/or uncharacterized sequences.
“This is supported by the extent to which ‘dark matter’ not previously characterized in the laboratory pervades host-associated and (especially) environmental metagenomes (Parks et al., 2017), with most communities containing a plurality, majority, or sometimes supermajority of novel and/or uncharacterized sequences (Almeida et al., 2019; Pasolli et al., 2019).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Pasolli et al., 2019
The limitation on visibility of high-diversity species applies to both reference-based and assembly-based approaches, with assembly-based approaches often also stymied by highly diverse taxa.
“This is true both for reference-based and for assembly-based approaches, the latter of which are often also stymied by highly diverse taxa (Pasolli et al., 2019).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Pasolli et al., 2019
Because metagenomes can simultaneously access all community members with relatively little bias, comparative genomic studies are now possible for organisms previously overlooked due to absence of obvious phenotypes or convenient culture techniques.
“Since metagenomes can simultaneously access all community members with relatively little bias, such studies are now possible with organisms previously overlooked due to the absence of obviously associated phenotypes or convenient culture techniques (Manara et al., 2019; Pasolli et al., 2019).”
From Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3 (2021) · cites this paper as Pasolli et al., 2019
Microbiome members of individuals from non-westernized populations are underrepresented by current cultivation-based genomic catalogs, causing metagenomic profiling to miss large fractions of microbial diversity.
“Microbiome members of individuals from non-westernized populations are particularly underrepresented by current cultivation-based genomic catalogs causing metagenomic profiling approaches to miss large fractions of the microbial diversity in the samples.”
From Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population (2023) · cites this paper as [23]
Metagenomic assembly can partially mitigate the underrepresentation of non-westernized microbiome members in genomic catalogs.
“Recent efforts showed that metagenomic assembly can partially mitigate this problem,23,25,33,34”
From Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population (2023) · cites this paper as [23]
The higher presence of unknown bacterial species not present in the reference databases is a feature of non-westernized communities.
“the higher presence of unknown bacterial species not present in the reference databases is also a feature of the non-westernized communities,23”
From Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population (2023) · cites this paper as [23]
Similar, albeit less marked, patterns of microbiome composition differences by lifestyle were already observed for adults but were never investigated in younger individuals.
“Similar, albeit less marked, patterns were already observed for adults22,23,24,25 with different lifestyles but were never investigated in younger individuals.”
From Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population (2023) · cites this paper as [23]
Metagenome-assembled genomes (MAGs) were reconstructed through single-sample metagenomic assembly and contig binning, an approach validated elsewhere.
“Metagenome-assembled genomes (MAGs) were reconstructed through single-sample metagenomic assembly and contig binning as validated elsewhere.23”
From Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population (2023) · cites this paper as [23]
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Manara, S., Selma-Royo, M., Huang, K. D., Asnicar, F., Armanini, F., Blanco-Miguez, A., Cumbo, F., Golzato, D., Manghi, P., Pinto, F., et al. (2023) · Current Biology · doi:10.1016/j.cub.2023.04.011 · Cited by 30 · see citing works
Self-citationBifidobacteriaceae diversity in the human microbiome from a large-scale genome-wide analysis
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Self-citationImpact of the ONCOBIOME network in cancer microbiome research
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Self-citationPangenomes of human gut microbiota uncover links between genetic diversity and stress response
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The endocannabinoid system: a bridge between alzheimer’s disease and gut microbiota
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- Authors
- Pasolli, E., Asnicar, F., Manara, S., Zolfo, M., Karcher, N., Armanini, F., Beghini, F., Manghi, P., Tett, A., Ghensi, P., Collado, M. C., Rice, B. L., DuLong, C., Morgan, X. C., Golden, C. D., Quince, C., Huttenhower, C., & Segata, N.
- Affiliations
- University of Trento (IT)
- Harvard University (US)
- University of Otago (NZ)
- University of Warwick (GB)
- Broad Institute (US)
- Corresponding author
- Segata, Nicola
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 176
- Issue
- 3
- Pages
- 649-662.e20
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC6349461
- OpenAlex
- W2910615673
- Cited by
- 1,591
- References
- 82
- Citations by year
- 2026: 131 · 2025: 195 · 2024: 211 · 2023: 206 · 2022: 248 · 2021: 276 · 2020: 203 · 2019: 116 · 2018: 1 · 2012: 1
- FWCI
- 71.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion, cc-by)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- Warwick Research Archive Portal (University of Warwick) (submittedVersion)
- Funders
- EU-H2020 (DiMeTrack-707345)
- NIH NHGRI (R01HG005220)
- NIDDK (R24DK110499, U54DE023798)
- CMIT (6935956)
- ERC (MetaPG-716575)
- MIUR (RBFR13EWWI)
- EU-FP7 (PCIG13-GA-2013-618833)
- CARITRO (2013.0239)
- LEO Pharma Foundation
- Rockefeller Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- human microbiome, metagenome-assembled genomes, microbial diversity, body site, lifestyle, Westernization, infant development, pan-genome, oral microbiota, gut microbiota, genome annotation
- MeSH terms
- Big Data, Geography, Humans, Life Style, Phylogeny, Genetic Variation, Sequence Analysis, DNA, Metagenome, Metagenomics, Microbiota
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