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Data_Sheet_2_Metatranscriptomics Reveals Antibiotic-Induced Resistance Gene Expression in the Murine Gut Microbiota.xlsx (1.15 MB)

Data_Sheet_2_Metatranscriptomics Reveals Antibiotic-Induced Resistance Gene Expression in the Murine Gut Microbiota.xlsx

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posted on 2020-03-06, 12:53 authored by Benjamin J. Korry, Damien J. Cabral, Peter Belenky

Antibiotic resistance is a current and expanding threat to the practice of modern medicine. Antibiotic therapy has been shown to perturb the composition of the host microbiome with significant health consequences. In addition, the gut microbiome is known to be a reservoir of antibiotic resistance genes. Work has demonstrated that antibiotics can alter the collection of antibiotic resistance genes within the microbiome through selection and horizontal gene transfer. While antibiotics also have the potential to impact the expression of resistance genes, metagenomic-based pipelines currently lack the ability to detect these shifts. Here, we utilized a dual sequencing approach combining shotgun metagenomics and metatranscriptomics to profile how three antibiotics, amoxicillin, doxycycline, and ciprofloxacin, impact the murine gut resistome at the DNA and RNA level. We found that each antibiotic induced broad, but untargeted impacts on the gene content of the resistome. In contrast, changes in ARG transcript abundance were more targeted to the antibiotic treatment. Doxycycline and amoxicillin induced the expression of tetracycline and beta-lactamase resistance genes, respectively. Furthermore, the increased beta-lactamase resistance gene transcripts could contribute to an observed bloom of Bacteroides thetaiotaomicron during amoxicillin treatment. Based on these findings, we propose that the utilization of a dual sequencing methodology provides a unique capacity to fully understand the response of the resistome to antibiotic perturbation. In particular, the analysis of transcripts reveals that the expression and utilization of resistance genes is far narrower than their abundance at the genomic level would suggest.

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