The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Use of Metatranscriptomics in Microbiome Research
Open accessAbstract
The human intestinal microbiome is a microbial ecosystem that expresses as many as 100 times more genes than the human host, thereby constituting an important component of the human holobiome, which contributes to multiple health and disease processes. As most commensal species are difficult or impossible to culture, genomic characterization of microbiome composition and function, under various environmental conditions, comprises a central tool in understanding its roles in health and disease. The first decade of microbiome research was mainly characterized by usage of DNA sequencing-based 16S rDNA and shotgun metagenome sequencing, allowing for the elucidation of microbial composition and genome structure. Technological advances in RNA-seq have recently provided us with an ability to gain insight into the genes that are actively expressed in complex bacterial communities, enabling the elucidation of the functional changes that dictate the microbiome functions at given contexts, its interactions with the host, and functional alterations that accompany the conversion of a healthy microbiome toward a disease-driving configuration. Here, we highlight some of the key metatranscriptomics strategies that are implemented to determine microbiota gene expression and its regulation and discuss the advantages and potential challenges associated with these approaches.
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Cites
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Cited by
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Metadata
- Authors
- Bashiardes, S., Zilberman-Schapira, G., & Elinav, E.
- Venue
- Bioinformatics and Biology Insights
- Publisher
- SAGE Publications
- Published
- 2016-01
- Volume
- 10
- Pages
- BBI.S34610
- ISSN
- 1177-9322 (ISSN-L)
- OpenAlex
- W2339590532
- Cited by
- 465
- References
- 19
- FWCI
- 15.65
- Type
- journal article
- Language
- en
- Open access
- gold
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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).
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