The DOI matches its Crossref record; 179 of the 181 references it cites were found in a registry or an index.
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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“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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Best practices for analysing microbiomes
Knight, R., Vrbanac, A., Taylor, B. C., Aksenov, A., Callewaert, C., Debelius, J., Gonzalez, A., Kosciolek, T., McCall, L.-I., McDonald, D., et al. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0029-9 · Cited by 2,030
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Metadata
- 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
- Life Sciences › Immunology and Microbiology › Virology › Bacteriophages and microbial interactions
- Keywords
- human microbiome, metagenomics, metatranscriptomics, viromics, oral microbiota, gut microbiota, dysbiosis, 16S rRNA gene profiling, shotgun sequencing
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