The DOI matches its Crossref record; 210 of the 210 references it cites were found in a registry or an index.
A clinician's guide to microbiome analysis
Abstract
Microbiome analysis involves determining the composition and function of a community of microorganisms in a particular location. For the gastroenterologist, this technology opens up a rapidly evolving set of challenges and opportunities for generating novel insights into the health of patients on the basis of microbiota characterizations from intestinal, hepatic or extraintestinal samples. Alterations in gut microbiota composition correlate with intestinal and extraintestinal disease and, although only a few mechanisms are known, the microbiota are still an attractive target for developing biomarkers for disease detection and management as well as potential therapeutic applications. In this Review, we summarize the major decision points confronting new entrants to the field or for those designing new projects in microbiome research. We provide recommendations based on current technology options and our experience of sequencing platform choices. We also offer perspectives on future applications of microbiome research, which we hope convey the promise of this technology for clinical applications.
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“Rapid improvements in sequencing technology have facilitated the development of two techniques that are integral to answering these questions: 16S sequencing and whole genome shotgun sequencing (Claesson et al., 2017).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Claesson et al., 2017
In the citing paper
“The large intestine is thus an important host site for microbial metabolism, a convenient truth that fortunately aligns with our reliance on the analysis of stool samples to gain insights into our microbial inhabitants (Fraher et al., 2012;Claesson et al., 2017).”
From Gut reactions: Breaking down xenobiotic–microbiome interactions (2019) · cites this paper as Claesson et al., 2017
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Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669
Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
DADA2: High–resolution sample inference from Illumina amplicon data
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055
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
phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data
McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,942
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
Naive Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy
Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.00062-07 · Cited by 20,145
Research works printed but not linked: 1
- Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. metaSPAdes: a new versatile de novo metagenomics assembler. arXiv 1604.03071 (2016). · arXiv
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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 reactions: Breaking down xenobiotic–microbiome interactions
Clarke, G., Sandhu, K. V., Griffin, B. T., Dinan, T. G., Cryan, J. F., & Hyland, N. P. (2019) · Pharmacological Reviews · doi:10.1124/pr.118.015768 · Cited by 319
Systematic review: human gut dysbiosis induced by non-antibiotic prescription medications
Le Bastard, Q., Al‐Ghalith, G. A., Grégoire, M., Chapelet, G., Javaudin, F., Dailly, E., Batard, E., Knights, D., & Montassier, E. (2018) · Alimentary Pharmacology & Therapeutics · doi:10.1111/apt.14451 · Cited by 263
Age-dependent changes in GI physiology and microbiota: time to reconsider?
An, R., Wilms, E., Masclee, A. A. M., Smidt, H., Zoetendal, E. G., & Jonkers, D. (2018) · Gut · doi:10.1136/gutjnl-2017-315542 · Cited by 209
Cowan, C. S. M., Dinan, T. G., & Cryan, J. F. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13156 · Cited by 176
Metadata
- Authors
- Claesson, M. J., Clooney, A. G., & O'Toole, P. W.
- Affiliations
- University College Cork (IE)
- Corresponding author
- Claesson, Marcus J.
- Venue
- Nature Reviews Gastroenterology & Hepatology
- Published
- 2017-08-09
- Volume
- 14
- Issue
- 10
- Pages
- 585-595
- ISSN
- 1759-5045 (ISSN-L)
- 1759-5053
- OpenAlex
- W2743544008
- Cited by
- 153
- References
- 210
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 18 · 2023: 12 · 2022: 19 · 2021: 25 · 2020: 28 · 2019: 22 · 2018: 11 · 2017: 3
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Gastroenterology & Hepatology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Science Foundation Ireland
- APC Microbiome Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- microbiome analysis, gut microbiota, microbiota composition, microbiota function, biomarkers, microbiota-based therapy, intestinal diseases, extraintestinal diseases
- MeSH terms
- Gastrointestinal Microbiome, Genetic Techniques, Humans, Research Design, Computational Biology, Metagenomics
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