Pangenomes of human gut microbiota uncover links between genetic diversity and stress response
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Abstract
The genetic diversity of the gut microbiota has a central role in host health. Here, we created pangenomes for 728 human gut prokaryotic species, quadrupling the genes of strain-specific genomes. Each of these species has a core set of a thousand genes, differing even between closely related species, and an accessory set of genes unique to the different strains. Functional analysis shows high strain variability associates with sporulation, whereas low variability is linked with antibiotic resistance. We further map the antibiotic resistome across the human gut population and find 237 cases of extreme resistance even to last-resort antibiotics, with a predominance among Enterobacteriaceae. Lastly, the presence of specific genes in the microbiota relates to host age and sex. Our study underscores the genetic complexity of the human gut microbiota, emphasizing its significant implications for host health. The pangenomes and antibiotic resistance map constitute a valuable resource for further research.
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Geographical origin is a major driver of intraspecific diversity, shaping host traits from diet to antibiotic exposure.
“Indeed, geographical origin is a major driver of intraspecific diversity, shaping host traits from diet to antibiotic exposure [94-97] .”
From Genome-scale insights into the metabolic landscape and evolutionary development of Bifidobacterium bifidum (2026) · cites this paper as [96]
The Results section reports variation in antibiotic susceptibility across geographical regions for one species, but does not identify geographical origin as a major driver of intraspecific diversity. The passages on strain variability and host characteristics address genes, age, and sex, not diet or geographic origin. Searches for geographic diversity and diet or antibiotic exposure did not establish the attributed claim. (LLM, conf=0.70)
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Saiprasad, P. V., & Krishnaprasad, K. (2016) · Indian Journal of Medical Microbiology · doi:10.4103/0255-0857.195379 · Cited by 24 · see citing works
Biller, S. J., Wayne, K. J., Winkler, M. E., et al. (2010) · Journal of Bacteriology · doi:10.1128/jb.00594-10 · Cited by 20 · see citing works
An Overlap between the Control of Programmed Cell Death in Bacillus anthracis and Sporulation
Chandramohan, L., Ahn, J., Weaver, K. E., & Bayles, K. W. (2009) · Journal of Bacteriology · doi:10.1128/jb.00314-09 · Cited by 20 · see citing works
Ribosomal Biogenesis and Heterogeneity in Development, Disease, and Aging
Islam, R. A., & Rallis, C. (2023) · Epigenomes · doi:10.3390/epigenomes7030017 · Cited by 16 · see citing works
Comamonas kerstersii Bacteremia of Unknown Origin
Rong, K., Delport, J., & AlMutawa, F. (2022) · Case Reports in Infectious Diseases · doi:10.1155/2022/1129832 · Cited by 14 · see citing works
Zhang, Y., Li, K., Zhan, Y., et al. (2023) · Frontiers in Medicine · doi:10.3389/fmed.2023.1283769 · Cited by 8 · see citing works
Arjes, H. A., Gui, H., Porter, R., et al. (2022) · mBio · doi:10.1128/mbio.01388-22 · Cited by 7 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [39]Hauser, and Alan R (2018). Ovid - Antibiotic Basics for Clinicians: The ABCs of Choosing the Right Antibacterial Agent (Wolters Kluwer). https://www.wolterskluwer.com/en/solutions/ovid/antibiotic-basics-for-clinicians-the-abcs-of-choosing-the-right-antibacterial-agent-14550.
Cited by
Sorted by citations
Selleri, E., Longhi, G., Tarracchini, C., Carolis, E. D., Petraro, S., Mancabelli, L., Milani, C., Turroni, F., Ventura, M., & Lugli, G. A. (2026) · Microbiome Research Reports · doi:10.20517/mrr.2026.19
- Authors
- Shoer, S., Reicher, L., Zhao, C., Pollard, K. S., Pilpel, Y., & Segal, E.
- Affiliations
- Weizmann Institute of Science (IL)
- Tel Aviv Sourasky Medical Center (IL)
- Chan Zuckerberg Biohub San Francisco (US)
- University of California, San Francisco (US)
- Corresponding author
- Segal, Eran
- Venue
- Cell Host & Microbe
- Publisher
- Elsevier BV
- Published
- 2024-10
- Volume
- 32
- Issue
- 10
- Pages
- 1744-1757.e2
- ISSN
- 1931-3128 (ISSN-L)
- PMC
- PMC12060796
- OpenAlex
- W4402966402
- Cited by
- 23
- References
- 100
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 1
- FWCI
- 3.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 373 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell Host & Microbe (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- Funders
- Council for Higher Education
- National Heart, Lung, and Blood Institute (R01HL160862)
- Division of Chemistry
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Medicine › Antibiotic Resistance in Bacteria
- Keywords
- human gut microbiome, pan-genome, core and accessory genome, sporulation, antibiotic resistance, resistome, last-resort antibiotics, Enterobacteriaceae, stress response, host-microbe interactions
- MeSH terms
- Gastrointestinal Microbiome, Adult, Anti-Bacterial Agents, Bacteria, Female, Humans, Male, Middle Aged, Phylogeny, Stress, Physiological, Genetic Variation, Genome, Bacterial, Drug Resistance, Bacterial
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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