Abstract

Antimicrobial resistance (AMR) is a major threat to human, animal, and crop health. AMR can be directly selected for by antibiotics, and indirectly co-selected for by biocides and metals, at environmentally relevant concentrations. Some evidence suggests that non-antibiotic drugs (NADs) can co-select for AMR, but previous work focused on exposing single model bacterial species to predominately high concentrations of NADs. There is a significant knowledge gap in understanding a range of NAD concentrations, (including lower µg/L concentrations found in the environment) on mixed bacterial communities containing a diverse mobile resistome. Here, we determined the antimicrobial effect and selective potential of diclofenac, metformin, and 17-β-estradiol, NADs that are commonly found environmental pollutants, in a complex bacterial community using a combination of culture based, metagenome, and metratranscriptome approaches. We found that diclofenac, metformin, and 17-β-estradiol at 50 µg/L, 26 µg/L, and 24 µg/L respectively, significantly reduced growth of a bacterial community although only 17-β-estradiol selected for an AMR marker using qPCR (from 7 µg/L to 5400 µg/L). Whole metagenome sequencing indicated that there was no clear selection by NADs for antibiotic resistance genes, or effects on community composition. Additionally, increases in relative abundance of some specific metal resistance genes (such as arsB) were observed after exposure to diclofenac, metformin, and 17-β-estradiol. These results indicate that environmentally relevant concentrations of NADs are likely to affect community growth, function, and potentially selection for specific metal resistance genes.

Original languageEnglish
Article number109490
JournalEnvironment International
Volume199
Early online date20 Apr 2025
DOIs
Publication statusPublished - 31 May 2025

Data Availability Statement

The datasets generated and analysis code used in this study are available at Zenodo https://doi.org/10.5281/zenodo.11109355. The raw metagenome and metatranscriptome sequence files generated as part of this study are available at ENA with Accession PRJEB74464.

Acknowledgements

We thank the Exeter Sequencing Service for their work sequencing the Illumina metagenomic sequencing. This project utilised equipment funded by the Wellcome Trust (Multi-User Equipment Grant award number 218247/Z/19/Z). We would also like to acknowledge the use of the University of Exeter High-Performance Computing (HPC) ISCA facility in carrying out this work. For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.

Funding

AH was supported by a FRESH CDT/AstraZeneca PhD Studentship (NE/R011524/1). WHG was supported by a NERC Knowledge Exchange Fellowship (NE/S006257/1). AKM was supported by a NERC Industrial Innovation Fellowship (NE/R01373X/1). The funders had no role in the conception nor writing of this paper.

FundersFunder number
Natural Environment Research CouncilNE/S006257/1, NE/R01373X/1

Keywords

  • Antimicrobial resistance
  • Co-selection
  • Environmental pollution
  • Non-antibiotic drugs
  • Pharmaceutical pollution

ASJC Scopus subject areas

  • General Environmental Science

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