Combining metagenomics, metatranscriptomics and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome
Open accessAbstract
The advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome.
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Shotgun metagenomics employs random fragmentation and adapter ligation to sequence in an unbiased manner all extracted DNA, enabling more in-depth analyses of the pan-genomic gene content in microbiomes.
“This approach employs random fragmentation and adapter ligation sequence in an unbiased manner all extracted DNA, enabling more in‐depth analyses of the pan‐genomic gene content in microbiomes.3”
From The oral microbiome: Role of key organisms and complex networks in oral health and disease (2021) · cites this paper as [3]
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Karamichalis, R., Lila Kari, A., Konstantinidis, S., Kopecki, S., & Solis-Reyes, S. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1157-8 · Cited by 25 · see citing works
Huang, D., Yuan, M., Chen, J., Zheng, X., Wong, D., Alvarez, P. J. J., & Yu, P. (2023) · ISME Communications · doi:10.1038/s43705-023-00249-1 · Cited by 24 · see citing works
Naya-Català, F., Piazzon, M. C., Calduch-Giner, J. À., Sitjà‐Bobadilla, A., & Pérez‐Sánchez, J. (2022) · Frontiers in Microbiology · doi:10.3389/fmicb.2022.883738 · Cited by 24 · see citing works
- Authors
- Bikel, S., Valdez-Lara, A., Cornejo-Granados, F., Rico, K., Canizales-Quinteros, S., Soberón, X., Del Pozo-Yauner, L., & Ochoa-Leyva, A.
- Affiliations
- National Institute of Genomic Medicine (MX)
- Unidad de Genómica de Poblaciones Aplicada la Salud, Facultad de Química, UNAM, Instituto Nacional de Medicina Genómica (INMEGEN), México, D.F. 14610, Mexico
- Instituto Nacional de Medicina Genómica (INMEGEN), México, D.F., Mexico
- Venue
- Computational and Structural Biotechnology Journal
- Published
- 2015-01
- Volume
- 13
- Pages
- 390-401
- ISSN
- 2001-0370 (ISSN-L)
- PMC
- PMC4484546
- OpenAlex
- W1222064643
- Cited by
- 263
- References
- 181
- Citations by year
- 2026: 19 · 2025: 26 · 2024: 26 · 2023: 27 · 2022: 26 · 2021: 34 · 2020: 28 · 2019: 20 · 2018: 20 · 2017: 18 · 2016: 18 · 2015: 1
- FWCI
- 1.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- CONACyT (CB-2013-223279, SALUD-2014-C01-234188)
- 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
- Physical Sciences › Environmental Science › Ecology › Bacteriophages and microbial interactions
- Keywords
- human microbiome, metagenomics, metatranscriptomics, viromics, oral microbiota, gut microbiota, dysbiosis, 16S rRNA gene profiling, shotgun sequencing
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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