The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
The Rebirth of Culture in Microbiology through the Example of Culturomics To Study Human Gut Microbiota
Open accessAbstract
SUMMARY: Bacterial culture was the first method used to describe the human microbiota, but this method is considered outdated by many researchers. Metagenomics studies have since been applied to clinical microbiology; however, a “dark matter” of prokaryotes, which corresponds to a hole in our knowledge and includes minority bacterial populations, is not elucidated by these studies. By replicating the natural environment, environmental microbiologists were the first to reduce the “great plate count anomaly,” which corresponds to the difference between microscopic and culture counts. The revolution in bacterial identification also allowed rapid progress. 16S rRNA bacterial identification allowed the accurate identification of new species. Mass spectrometry allowed the high-throughput identification of rare species and the detection of new species. By using these methods and by increasing the number of culture conditions, culturomics allowed the extension of the known human gut repertoire to levels equivalent to those of pyrosequencing. Finally, taxonogenomics strategies became an emerging method for describing new species, associating the genome sequence of the bacteria systematically. We provide a comprehensive review on these topics, demonstrating that both empirical and hypothesis-driven approaches will enable a rapid increase in the identification of the human prokaryote repertoire.
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Self-citationRetracted
Metadata
- Authors
- Lagier, J.-C., Hugon, P., Khelaifia, S., Fournier, P.-E., La Scola, B., & Raoult, D.
- Venue
- Clinical Microbiology Reviews
- Publisher
- American Society for Microbiology
- Published
- 2015-01
- Volume
- 28
- Issue
- 1
- Pages
- 237-264
- ISSN
- 0893-8512 (ISSN-L)
- 1098-6618
- OpenAlex
- W2144305368
- Cited by
- 831
- References
- 13
- FWCI
- 40.65
- Type
- journal article
- Language
- en
- Open access
- green
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
