Genome-resolved insight into the reservoir of antibiotic resistance genes in aquatic microbial community

Abstract

Aquatic microbial communities are an important reservoir of antibiotic resistance genes (ARGs). However, distribution and diversity of different ARG categories in environmental microbes with different ecological strategies is not yet well studied. Despite the potential exposure of the southern part of the Caspian Sea to the release of antibiotics, little is known about its natural resistome profile. We used a combination of Hidden Markov model (HMM), homology alignment and a deep learning approach for comprehensive screening of the diversity and distribution of ARGs in the Caspian Sea metagenomes at genome resolution. Detected ARGs were classified into five antibiotic resistance categories including prevention of access to target (44%), modification/protection of targets (30%), direct modification of antibiotics (22%), stress resistance (3%), and metal resistance (1%). The 102 detected ARG containing metagenome-assembled genomes of the Caspian Sea were dominated by representatives of Acidimicrobiia, Gammaproteobacteria, and Actinobacteria classes. Comparative analysis revealed that the highly abundant, oligotrophic, and genome streamlined representatives of taxa Acidimicrobiia and Actinobacteria modify the antibiotic target via mutation to develop antibiotic resistance rather than carrying extra resistance genes. Our results help with understanding how the encoded resistance categories of each genome are aligned with its ecological strategies.

Published in

Scientific Reports
2022, Volume: 12, number: 1, article number: 21047

SLU Authors

• Mehrshad, Maliheh

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

SDG3 Good health and well-being


UKÄ Subject classification

Ecology


Publication identifier

DOI: https://doi.org/10.1038/s41598-022-25026-3

Permanent link to this page (URI)

https://res.slu.se/id/publ/120490