Dataset Information

Geographic pattern of antibiotic resistance genes in the metagenomes of the giant panda.

ABSTRACT: The rise in infections by antibiotic-resistant bacteria poses a serious public health problem worldwide. The gut microbiome of animals is a reservoir for antibiotic resistance genes (ARGs). However, the correlation between the gut microbiome of wild animals and ARGs remains controversial. Here, based on the metagenomes of giant pandas (including three wild populations from the Qinling, Qionglai and Xiaoxiangling Mountains, and two major captive populations from Yaan and Chengdu), we investigated the potential correlation between the constitution of the gut microbiome and the composition of ARGs across the different geographic locations and living environments. We found that the types of ARGs were correlated with gut microbiome composition. The NMDS cluster analysis using Jaccard distance of the ARGs composition of the gut microbiome of wild giant pandas displayed a difference based on geographic location. Captivity also had an effect on the differences in ARGs composition. Furthermore, we found that the Qinling population exhibited profound dissimilarities of both gut microbiome composition and ARGs (the highest proportion of Clostridium and vancomycin resistance genes) when compared to the other wild and captive populations studies, which was supported by previous giant panda whole-genome sequencing analysis. In this study, we provide an example of a potential consensus pattern regarding host population genetics, symbiotic gut microbiome and ARGs. We revealed that habitat isolation impacts the ARG structure in the gut microbiome of mammals. Therefore, the difference in ARG composition between giant panda populations will provide some basic information for their conservation and management, especially for captive populations.

SUBMITTER: Hu T

PROVIDER: S-EPMC7888472 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Geographic pattern of antibiotic resistance genes in the metagenomes of the giant panda.

Hu Ting T Dai Qinlong Q Chen Hua H Zhang Zheng Z Dai Qiang Q Gu Xiaodong X Yang Xuyu X Yang Zhisong Z Zhu Lifeng L

Microbial biotechnology 20200818 1

The rise in infections by antibiotic-resistant bacteria poses a serious public health problem worldwide. The gut microbiome of animals is a reservoir for antibiotic resistance genes (ARGs). However, the correlation between the gut microbiome of wild animals and ARGs remains controversial. Here, based on the metagenomes of giant pandas (including three wild populations from the Qinling, Qionglai and Xiaoxiangling Mountains, and two major captive populations from Yaan and Chengdu), we investigated ...[more]

PMID: 32812361

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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

Geographic pattern of antibiotic resistance genes in the metagenomes of the giant panda.

Publications

Geographic pattern of antibiotic resistance genes in the metagenomes of the giant panda.

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