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Human Gut Microbiota: Repertoire and Variations
Open accessAbstract
The composition of human gut microbiota and their relationship with the host and, consequently, with human health and disease, presents several challenges to microbiologists. Originally dominated by culture-dependent methods for exploring this ecosystem, the advent of molecular tools has revolutionized our ability to investigate these relationships. However, many biases that have led to contradictory results have been identified. Microbial culturomics, a recent concept based on a use of several culture conditions with identification by MALDI-TOF followed by the genome sequencing of the new species cultured had allowed a complementarity with metagenomics. Culturomics allowed to isolate 31 new bacterial species, the largest human virus, the largest bacteria, and the largest Archaea from human. Moreover, some members of this ecosystem, such as Eukaryotes, giant viruses, Archaea, and Planctomycetes, have been neglected by the majority of studies. In addition, numerous factors, such as age, geographic provenance, dietary habits, antibiotics, or probiotics, can influence the composition of the microbiota. Finally, in addition to the countless biases associated with the study techniques, a considerable limitation to the interpretation of studies of human gut microbiota is associated with funding sources and transparency disclosures. In the future, studies independent of food industry funding and using complementary methods from a broad range of both culture-based and molecular tools will increase our knowledge of the repertoire of this complex ecosystem and host-microbiota mutualism.
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The abundance and variety of carbohydrate-active enzymes in the human gut microbiota
Kaoutari, A. E., Armougom, F., Gordon, J. I., Raoult, D., & Henrissat, B. (2013) · Nature Reviews Microbiology · doi:10.1038/nrmicro3050 · Cited by 1,683
Self-citationThe first 1000 cultured species of the human gastrointestinal microbiota
Rajilić-Stojanović, M., & de Vos, W. M. (2014) · FEMS Microbiology Reviews · doi:10.1111/1574-6976.12075 · Cited by 1,182
Lagier, J.-C., Khelaifia, S., Alou, M. T., Ndongo, S., Dione, N., Hugon, P., Caputo, A., Cadoret, F., Traore, S. I., Seck, E. H., et al. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.203 · Cited by 951
Self-citationRetractedCulturing the human microbiota and culturomics
Lagier, J.-C., Dubourg, G., Million, M., Cadoret, F., Bilen, M., Fenollar, F., Levasseur, A., Rolain, J.-M., Fournier, P.-E., & Raoult, D. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0041-0 · Cited by 872
Self-citationLagier, J.-C., Hugon, P., Khelaifia, S., Fournier, P.-E., La Scola, B., & Raoult, D. (2015) · Clinical Microbiology Reviews · doi:10.1128/cmr.00014-14 · Cited by 831
Self-citation
Metadata
- Authors
- Lagier, J.-C., Million, M., Hugon, P., Armougom, F., & Raoult, D.
- Venue
- Frontiers in Cellular and Infection Microbiology
- Publisher
- Frontiers Media SA
- Published
- 2012
- Volume
- 2
- Pages
- 136-136
- ISSN
- 2235-2988 (ISSN-L)
- OpenAlex
- W2015820526
- Cited by
- 329
- References
- 202
- FWCI
- 9.29
- Type
- journal article
- Language
- en
- Open access
- gold
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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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
