Literature DB >> 24418972

Gut microbiota disturbance during antibiotic therapy: a multi-omic approach.

Manuel Ferrer1, Vitor A P Martins dos Santos2, Stephan J Ott3, Andrés Moya4.   

Abstract

It is known that the gastrointestinal tract (GIT) microbiota responds to different antibiotics in different ways and that while some antibiotics do not induce disturbances of the community, others drastically influence the richness, diversity, and prevalence of bacterial taxa. However, the metabolic consequences thereof, independent of the degree of the community shifts, are not clearly understood. In a recent article, we used an integrative OMICS approach to provide new insights into the metabolic shifts caused by antibiotic disturbance. The study presented here further suggests that specific bacterial lineage blooms occurring at defined stages of antibiotic intervention are mostly associated with organisms that possess improved survival and colonization mechanisms, such as those of the Enterococcus, Blautia, Faecalibacterium, and Akkermansia genera. The study also provides an overview of the most variable metabolic functions affected as a consequence of a β-lactam antibiotic intervention. Thus, we observed that anabolic sugar metabolism, the production of acetyl donors and the synthesis and degradation of intestinal/colonic epithelium components were among the most variable functions during the intervention. We are aware that these results have been established with a single patient and will require further confirmation with a larger group of individuals and with other antibiotics. Future directions for exploration of the effects of antibiotic interventions are discussed.

Entities:  

Keywords:  antibiotic therapy; human gut microbiota; metabolomic; metagenomic; metaproteomic; metatranscriptomic

Mesh:

Substances:

Year:  2013        PMID: 24418972      PMCID: PMC4049940          DOI: 10.4161/gmic.27128

Source DB:  PubMed          Journal:  Gut Microbes        ISSN: 1949-0976


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8.  Gut microbiota disturbance during antibiotic therapy: a multi-omic approach.

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