Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework

Corinne Wiesner-Friedman; Rachelle E Beattie; Jill R Stewart; Krassimira R Hristova; Marc L Serre

doi:10.3389/fmicb.2023.1223876

Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework

Front Microbiol. 2023 Sep 5:14:1223876. doi: 10.3389/fmicb.2023.1223876. eCollection 2023.

Authors

Corinne Wiesner-Friedman¹, Rachelle E Beattie^{2

3}, Jill R Stewart⁴, Krassimira R Hristova³, Marc L Serre⁴

Affiliations

¹ Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH, United States.
² U.S. Geological Survey, Columbia Environmental Research Center, Columbia, MO, United States.
³ Department of Biological Sciences, Marquette University, Milwaukee, WI, United States.
⁴ Gillings School of Global Public Health, Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.

Abstract

Introduction: Antimicrobial resistance (AMR) is an increasing public health concern for humans, animals, and the environment. However, the contributions of spatially distributed sources of AMR in the environment are not well defined.

Methods: To identify the sources of environmental AMR, the novel microbial Find, Inform, and Test (FIT) model was applied to a panel of five antibiotic resistance-associated genes (ARGs), namely, erm(B), tet(W), qnrA, sul1, and intI1, quantified from riverbed sediment and surface water from a mixed-use region.

Results: A one standard deviation increase in the modeled contributions of elevated AMR from bovine sources or land-applied waste sources [land application of biosolids, sludge, and industrial wastewater (i.e., food processing) and domestic (i.e., municipal and septage)] was associated with 34-80% and 33-77% increases in the relative abundances of the ARGs in riverbed sediment and surface water, respectively. Sources influenced environmental AMR at overland distances of up to 13 km.

Discussion: Our study corroborates previous evidence of offsite migration of microbial pollution from bovine sources and newly suggests offsite migration from land-applied waste. With FIT, we estimated the distance-based influence range overland and downstream around sources to model the impact these sources may have on AMR at unsampled sites. This modeling supports targeted monitoring of AMR from sources for future exposure and risk mitigation efforts.

Keywords: animal feeding operations; antimicrobial resistance; land application; microbial FIT; sediment; surface water.

Grants and funding

This study was supported by a grant from the National Institute of Environmental Health Sciences (NIEHS) T32ES007018. This study was funded in part by the Marquette University Innovation Grant, NSF grant 1316318 as part of the joint NSF-NIH-USDA Ecology and Evolution of Infectious Diseases program, the Engineering Research Centers Program of the National Science Foundation under NSF Cooperative Agreement no. EEC-2133504, and the Department of Army award W9132T2220001 issued by the Office of Army Research.