The DOI matches its Crossref record; 51 of the 53 references it cites were found in a registry or an index.
Structural variation in the gut microbiome associates with host health
Open accessAbstract
Differences in the presence of even a few genes between otherwise identical bacterial strains may result in critical phenotypic differences. Here we systematically identify microbial genomic structural variants (SVs) and find them to be prevalent in the human gut microbiome across phyla and to replicate in different cohorts. SVs are enriched for CRISPR-associated and antibiotic-producing functions and depleted from housekeeping genes, suggesting that they have a role in microbial adaptation. We find multiple associations between SVs and host disease risk factors, many of which replicate in an independent cohort. Exploring genes that are clustered in the same SV, we uncover several possible mechanistic links between the microbiome and its host, including a region in Anaerostipes hadrus that encodes a composite inositol catabolism-butyrate biosynthesis pathway, the presence of which is associated with lower host metabolic disease risk. Overall, our results uncover a nascent layer of variability in the microbiome that is associated with microbial adaptation and host health.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“recent findings have identified an elementary layer of variability in the microbiome identified as microbial genomic structural variants (the term pertaining to the existence of a few genes which are different between otherwise identical bacterial strains) that are specifically unique to the host microbiota and demonstrate a strong association with host metabolic health (Zeevi et al., 2019).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Zeevi et al., 2019
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Fast and sensitive protein alignment using DIAMOND
Buchfink, B., Xie, C., & Huson, D. H. (2015) · Nature Methods · doi:10.1038/nmeth.3176 · Cited by 14,201
A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762
The Pfam protein families database in 2019
El-Gebali, S., Mistry, J., Bateman, A., Eddy, S. R., Luciani, A., Potter, S. C., Qureshi, M., Richardson, L. J., Salazar, G. A., Smart, A., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky995 · Cited by 4,602
Kraken: ultrafast metagenomic sequence classification using exact alignments
Wood, D. E., & Salzberg, S. L. (2014) · Genome Biology · doi:10.1186/gb-2014-15-3-r46 · Cited by 4,521
Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis
Koeth, R. A., Wang, Z., Levison, B. S., Buffa, J. A., Org, E., Sheehy, B. T., Britt, E. B., Fu, X., Wu, Y., Li, L., et al. (2013) · Nature Medicine · doi:10.1038/nm.3145 · Cited by 4,386
The innate immune response to bacterial flagellin is mediated by Toll-like receptor 5
Hayashi, F., Smith, K. D., Ozinsky, A., Hawn, T. R., Yi, E. C., Goodlett, D. R., Eng, J. K., Akira, S., Underhill, D. M., & Aderem, A. A. (2001) · Nature · doi:10.1038/35074106 · Cited by 3,605
Gut metagenome in European women with normal, impaired and diabetic glucose control
Karlsson, F. H., Tremaroli, V., Nookaew, I., Bergström, G., Behre, C. J., Fagerberg, B., Nielsen, J., & Bäckhed, F. (2013) · Nature · doi:10.1038/nature12198 · Cited by 3,115
Olm, M. R., Brown, C. T., Brooks, B., & Banfield, J. F. (2017) · The ISME Journal · doi:10.1038/ismej.2017.126 · Cited by 3,031
Personalized nutrition by prediction of glycemic responses
Zeevi, D., Korem, T., Zmora, N., Israeli, D., Rothschild, D., Weinberger, A., Ben-Yacov, O., Lador, D., Avnit-Sagi, T., Lotan-Pompan, M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.001 · Cited by 2,929
Self-citationEnvironment dominates over host genetics in shaping human gut microbiota
Rothschild, D., Weissbrod, O., Barkan, E., Kurilshikov, A., Korem, T., Zeevi, D., Costea, P. I., Godneva, A., Kalka, I. N., Bar, N., et al. (2018) · Nature · doi:10.1038/nature25973 · Cited by 2,859
Self-citationEnergy contributions of volatile fatty acids from the gastrointestinal tract in various species
Bergman, E. N. (1990) · Physiological Reviews · doi:10.1152/physrev.1990.70.2.567 · Cited by 2,750
Potter, S. C., Luciani, A., Eddy, S. R., Park, Y., Lopez, R., & Finn, R. D. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky448 · Cited by 2,607
Zerbino, D. R., Achuthan, P., Akanni, W., Amode, M. R., Barrell, D., Bhai, J., Billis, K., Cummins, C., Gall, A., Girón, C. G., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1098 · Cited by 2,605
Bracken: estimating species abundance in metagenomics data
(2016) · doi:10.7717/peerj-cs.104 · Cited by 2,333
Butyrate improves insulin sensitivity and increases energy expenditure in mice
Gao, Z., Yin, J., Zhang, J., Ward, R. E., Martin, R. J., Lefevre, M., Cefalu, W. T., & Ye, J. (2009) · Diabetes · doi:10.2337/db08-1637 · Cited by 2,204
MetaPhlAn2 for enhanced metagenomic taxonomic profiling
Truong, D. T., Franzosa, E. A., Tickle, T. L., Scholz, M., Weingart, G., Pasolli, E., Tett, A., Huttenhower, C., & Segata, N. (2015) · Nature Methods · doi:10.1038/nmeth.3589 · Cited by 2,185
An integrated catalog of reference genes in the human gut microbiome
MetaHIT Consortium, Li, J., Jia, H., Cai, X., Zhong, H., Feng, Q., Sunagawa, S., Arumugam, M., Kultima, J. R., Prifti, E., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2942 · Cited by 2,164
Artificial sweeteners induce glucose intolerance by altering the gut microbiota
Suez, J., Korem, T., Zeevi, D., Zilberman-Schapira, G., Thaiss, C. A., Maza, O., Israeli, D., Zmora, N., Gilad, S., Weinberger, A., et al. (2014) · Nature · doi:10.1038/nature13793 · Cited by 2,067
Self-citationQuantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells
Taniguchi, Y., Choi, P. J., Li, G.-W., Chen, H., Babu, M., Hearn, J., Emili, A., & Xie, X. S. (2010) · Science · doi:10.1126/science.1188308 · Cited by 1,982
Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity
Zhernakova, A., Kurilshikov, A., Bonder, M. J., Tigchelaar, E. F., Schirmer, M., Vatanen, T., Mujagic, Z., Vila, A. V., Falony, G., Vieira-Silva, S., et al. (2016) · Science · doi:10.1126/science.aad3369 · Cited by 1,914
Self-citationSpecies-level functional profiling of metagenomes and metatranscriptomes
Franzosa, E. A., McIver, L. J., Rahnavard, G., Thompson, L. R., Schirmer, M., Weingart, G., Lipson, K. S., Knight, R., Caporaso, J. G., Segata, N., et al. (2018) · Nature Methods · doi:10.1038/s41592-018-0176-y · Cited by 1,693
Genome structural variation discovery and genotyping
Alkan, C., Coe, B. P., & Eichler, E. E. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2958 · Cited by 1,630
Bacteria as vitamin suppliers to their host: A gut microbiota perspective
LeBlanc, J. G., Milani, C., de Giori, G. S., Sesma, F., van Sinderen, D., & Ventura, M. (2013) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2012.08.005 · Cited by 1,613
Dynamics of the human gut microbiome in inflammatory bowel disease
Halfvarson, J., Brislawn, C. J., Lamendella, R., Vázquez-Baeza, Y., Walters, W. A., Bramer, L. M., D'Amato, M., Bonfiglio, F., McDonald, D., Gonzalez, A., et al. (2017) · Nature Microbiology · doi:10.1038/nmicrobiol.2017.4 · Cited by 1,204
Gill, S. R., Fouts, D. E., Archer, G. L., Mongodin, E. F., DeBoy, R. T., Ravel, J., Paulsen, I. T., Kolonay, J. F., Brinkac, L. M., Beanan, M., et al. (2005) · Journal of Bacteriology · doi:10.1128/jb.187.7.2426-2438.2005 · Cited by 1,026
Levy, M., Thaiss, C. A., Zeevi, D., Dohnalová, L., Zilberman-Schapira, G., Mahdi, J. A., David, E., Savidor, A., Korem, T., Herzig, Y., et al. (2015) · Cell · doi:10.1016/j.cell.2015.10.048 · Cited by 960
Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software
Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., Majda, S., Fiedler, J., Dahms, E., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4458 · Cited by 858
A microbial signature for Crohn's disease
Pascal, V., Pozuelo, M., Borruel, N., Casellas, F., Campos, D., Santiago, A., Martínez, X., Varela, E., Sarrabayrouse, G., Machiels, K., et al. (2017) · Gut · doi:10.1136/gutjnl-2016-313235 · Cited by 842
Treatment of Diversion Colitis with Short-Chain-Fatty Acid Irrigation
Harig, J. M., Soergel, K. H., KOMOROWSKI, R. A., & Wood, C. M. (1989) · New England Journal of Medicine · doi:10.1056/nejm198901053200105 · Cited by 751
Systemic gut microbial modulation of bile acid metabolism in host tissue compartments
Swann, J. R., Want, E. J., Geier, F. M., Spagou, K., Wilson, I. D., Sidaway, J. E., Nicholson, J. K., & Holmes, E. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1006734107 · Cited by 726
Copy-number variation and association studies of human disease
McCarroll, S. A., & Altshuler, D. M. (2007) · Nature Genetics · doi:10.1038/ng2080 · Cited by 622
The GEM mapper: fast, accurate and versatile alignment by filtration
Marco‐Sola, S., Sammeth, M., Guigó, R., & Ribeca, P. (2012) · Nature Methods · doi:10.1038/nmeth.2221 · Cited by 545
Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples
Korem, T., Zeevi, D., Suez, J., Weinberger, A., Avnit-Sagi, T., Lotan‐Pompan, M., Matot, E., Jona, G., Harmelin, A., Cohen, N., et al. (2015) · Science · doi:10.1126/science.aac4812 · Cited by 445
Self-citationPathogenic adaptation of Escherichia coli by natural variation of the FimH adhesin
Sokurenko, E. V., Чеснокова, В. Л., Dykhuizen, D. E., Ofek, I., Wu, X., Krogfelt, K. A., Struve, C., Schembri, M. A., & Hasty, D. L. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.15.8922 · Cited by 373
Ross, J. I., Eady, E. A., Cove, J. H., Cunliffe, W. J., Baumberg, S., & Wootton, J. C. (1990) · Molecular Microbiology · doi:10.1111/j.1365-2958.1990.tb00696.x · Cited by 358
Microbial Genetic Composition Tunes Host Longevity
Han, B., Sivaramakrishnan, P., Lin, C.-C., Neve, I. A. A., He, J., Tay, L. W. R., Sowa, J. N., Sizovs, A., Du, G., Wang, J., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.036 · Cited by 355
Bread Affects Clinical Parameters and Induces Gut Microbiome-Associated Personal Glycemic Responses
Korem, T., Zeevi, D., Zmora, N., Weissbrod, O., Bar, N., Lotan-Pompan, M., Avnit-Sagi, T., Kosower, N., Malka, G., Rein, M., et al. (2017) · Cell Metabolism · doi:10.1016/j.cmet.2017.05.002 · Cited by 318
Self-citationWeiser, J. N., Pan, N., McGowan, K. L., Musher, D. M., Martin, A., & Richards, J. (1998) · The Journal of Experimental Medicine · doi:10.1084/jem.187.4.631 · Cited by 304
Rowan, S., Jiang, S., Korem, T., Szymanski, J., Chang, M.-L., Szelog, J., Cassalman, C., Dasuri, K., McGuire, C., Nagai, R., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1702302114 · Cited by 272
Self-citationExtensive Strain-Level Copy-Number Variation across Human Gut Microbiome Species
Greenblum, S. I., Carr, R., & Borenstein, E. (2015) · Cell · doi:10.1016/j.cell.2014.12.038 · Cited by 242
Analysis of the Gut Microbiota in the Old Order Amish and Its Relation to the Metabolic Syndrome
Zupancic, M. L., Cantarel, B. L., Liu, Z., Drábek, E. F., Ryan, K. A., Cirimotich, S., Jones, C., Knight, R. D., Walters, W. A., Knights, D., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0043052 · Cited by 215
Quantifying E. coli Proteome and Transcriptome with Single-molecule Sensitivity in Single Cells
Taniguchi, Y. (2011) · Seibutsu Butsuri · doi:10.2142/biophys.51.136 · Cited by 157
myo-Inositol Catabolism in Bacillus subtilis
Yoshida, K., Yamaguchi, M., Morinaga, T., et al. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m708043200 · Cited by 140
proGenomes: a resource for consistent functional and taxonomic annotations of prokaryotic genomes
Mende, D. R., Letunić, I., Huerta‐Cepas, J., Li, S. S., Forslund, S. K., Sunagawa, S., & Bork, P. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw989 · Cited by 137
Manor, O., & Borenstein, E. (2017) · Cell Host & Microbe · doi:10.1016/j.chom.2016.12.014 · Cited by 132
MetaPhyler: Taxonomic profiling for metagenomic sequences
Liu, B., Gibbons, T., Ghodsi, M., & Pop, M. (2010) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2010.5706544 · Cited by 74
Pathogenic adaptation of Escherichia coli by natural variation of the fimH adhesin
Sokurenko, E. V., Чеснокова, В. Л., Dykhuizen, D. E., Ofek, I., Wu, X., Krogfelt, K. A., Struve, C., Schembri, M. A., Hasty, D. L., & Cowan, M. M. (1999) · Europe PMC (PubMed Central) · Cited by 45
Shen, Y., Chen, L., Wang, M., Lin, D., Liang, Z. T., Song, P., Yuan, Q., Tang, H., Li, W., Duan, K., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-01619-1 · Cited by 41
Cited by
Sorted by citations
Cryan, J. F., O'Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., et al. (2019) · Physiological Reviews · doi:10.1152/physrev.00018.2018 · Cited by 5,286
Gut microbiota in human metabolic health and disease
Fan, Y., & Pedersen, O. (2021) · Nature Reviews Microbiology · doi:10.1038/s41579-020-0433-9 · Cited by 4,724
Longitudinal Multi-omics Reveals Subset-Specific Mechanisms Underlying Irritable Bowel Syndrome
Mars, R. A. T., Yang, Y., Ward, T., Houtti, M., Priya, S., Lekatz, H. R., Tang, X., Sun, Z., Kalari, K. R., Korem, T., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.007 · Cited by 456
“We therefore tested for specific bacterial genomic regions that may be responsible for the variation in metabolic output between the groups using the recently described method that associates structurally variable genomic regions to metabolite abundances (SV association) (Zeevi et al., 2019).”
Self-citationA reference map of potential determinants for the human serum metabolome
Bar, N., Korem, T., Weissbrod, O., Zeevi, D., Rothschild, D., Leviatan, S., Kosower, N., Lotan‐Pompan, M., Weinberger, A., Roy, C. I. L., et al. (2020) · Nature · doi:10.1038/s41586-020-2896-2 · Cited by 440
Self-citationDiversity within Species: Interpreting Strains in Microbiomes
Van Rossum, T., Ferretti, P., Maistrenko, O. M., & Bork, P. (2020) · Nature Reviews Microbiology · doi:10.1038/s41579-020-0368-1 · Cited by 441
Metadata
- Authors
- Zeevi, D., Korem, T., Godneva, A., Bar, N., Kurilshikov, A., Lotan-Pompan, M., Weinberger, A., Fu, J., Wijmenga, C., Zhernakova, A., & Segal, E.
- Affiliations
- Weizmann Institute of Science (IL)
- Columbia University Irving Medical Center (US)
- University Medical Center Groningen (NL)
- Corresponding author
- Zeevi, David
- Segal, Eran
- ORCID
- Venue
- Nature
- Published
- 2019-03-27
- Volume
- 568
- Issue
- 7750
- Pages
- 43-48
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2924485771
- Cited by
- 351
- References
- 53
- Citations by year
- 2026: 33 · 2025: 40 · 2024: 58 · 2023: 46 · 2022: 55 · 2021: 51 · 2020: 45 · 2019: 23
- FWCI
- 14.39
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- James S. McDonnell Foundation
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (864.13.013, 016.Vidi.178.056)
- 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
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- gut microbiota, structural variants, bacterial genomes, antibiotic production, Anaerostipes hadrus, metabolic disorders, host-microbe interactions, bacterial adaptation
- MeSH terms
- Gastrointestinal Microbiome, Host Microbial Interactions, Adaptation, Physiological, Bacteria, Butyrates, Disease Susceptibility, Eubacterium, Feces, Genes, Bacterial, Health, Humans, Inositol, Risk Factors, Genetic Variation, Cohort Studies, Ecosystem, Microbial Viability, Metagenomics
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 ›
Are you an author, or do you see a problem with this page? Request a review
