Dataset Information

TCDD influences reservoir of antibiotic resistance genes in murine gut microbiome.

ABSTRACT: Dysbiosis of the gut microbiome via antibiotics, changes in diet and infection can select for bacterial groups that more frequently harbor antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs). However, the impact of environmental toxicants on the reservoir of ARGs in the gut microbiome has received less attention. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a potent aryl hydrocarbon receptor (AhR) agonist with multiple toxic health effects including immune dysfunction. The selective pressure of TCDD on the abundance of ARG and MGE-harboring gut populations was examined using C57BL/6 mice exposed to 0-30 ?g/kg TCDD for 28 and 92 days with the latter having a 30-day recovery period. DNA extracted from temporally collected fecal pellets was characterized using a qPCR array with 384 assays targeting ARGs and MGEs. Fourteen genes, typically observed in Enterobacteriaceae, increased significantly within 8 days of initial dosing, persisted throughout the treatment period, and remained induced 30 days post dosing. A qPCR primer set targeting Enterobacteriaceae also showed 10- to 100-fold higher abundance in TCDD-treated groups, which was further verified using metagenomics. Results show a bloom of ARG-harboring bacterial groups in the gut due to a xenobiotic compound that is not a metal, biocide or antimicrobial.

SUBMITTER: Stedtfeld RD

PROVIDER: S-EPMC5458050 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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TCDD influences reservoir of antibiotic resistance genes in murine gut microbiome.

Stedtfeld Robert D RD Stedtfeld Tiffany M TM Fader Kelly A KA Williams Maggie R MR Bhaduri Prianca P Quensen John J Zacharewski Timothy R TR Tiedje James M JM Hashsham Syed A SA

FEMS microbiology ecology 20170501 5

Dysbiosis of the gut microbiome via antibiotics, changes in diet and infection can select for bacterial groups that more frequently harbor antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs). However, the impact of environmental toxicants on the reservoir of ARGs in the gut microbiome has received less attention. 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a potent aryl hydrocarbon receptor (AhR) agonist with multiple toxic health effects including immune dysfunction. The ...[more]

PMID: 28475713

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Project description:Antibiotic resistance in pathogens is extensively studied, and yet little is known about how antibiotic resistance genes of typical gut bacteria influence microbiome dynamics. Here, we leveraged genomes from metagenomes to investigate how genes of the premature infant gut resistome correspond to the ability of bacteria to survive under certain environmental and clinical conditions. We found that formula feeding impacts the resistome. Random forest models corroborated by statistical tests revealed that the gut resistome of formula-fed infants is enriched in class D beta-lactamase genes. Interestingly, Clostridium difficile strains harboring this gene are at higher abundance in formula-fed infants than C. difficile strains lacking this gene. Organisms with genes for major facilitator superfamily drug efflux pumps have higher replication rates under all conditions, even in the absence of antibiotic therapy. Using a machine learning approach, we identified genes that are predictive of an organism's direction of change in relative abundance after administration of vancomycin and cephalosporin antibiotics. The most accurate results were obtained by reducing annotated genomic data to five principal components classified by boosted decision trees. Among the genes involved in predicting whether an organism increased in relative abundance after treatment are those that encode subclass B2 beta-lactamases and transcriptional regulators of vancomycin resistance. This demonstrates that machine learning applied to genome-resolved metagenomics data can identify key genes for survival after antibiotics treatment and predict how organisms in the gut microbiome will respond to antibiotic administration. IMPORTANCE The process of reconstructing genomes from environmental sequence data (genome-resolved metagenomics) allows unique insight into microbial systems. We apply this technique to investigate how the antibiotic resistance genes of bacteria affect their ability to flourish in the gut under various conditions. Our analysis reveals that strain-level selection in formula-fed infants drives enrichment of beta-lactamase genes in the gut resistome. Using genomes from metagenomes, we built a machine learning model to predict how organisms in the gut microbial community respond to perturbation by antibiotics. This may eventually have clinical applications.

Dataset Information

TCDD influences reservoir of antibiotic resistance genes in murine gut microbiome.

Publications

TCDD influences reservoir of antibiotic resistance genes in murine gut microbiome.

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