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Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework.
Wiesner-Friedman, Corinne; Beattie, Rachelle E; Stewart, Jill R; Hristova, Krassimira R; Serre, Marc L.
Affiliation
  • Wiesner-Friedman C; Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH, United States.
  • Beattie RE; U.S. Geological Survey, Columbia Environmental Research Center, Columbia, MO, United States.
  • Stewart JR; Department of Biological Sciences, Marquette University, Milwaukee, WI, United States.
  • Hristova KR; Gillings School of Global Public Health, Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
  • Serre ML; Department of Biological Sciences, Marquette University, Milwaukee, WI, United States.
Front Microbiol ; 14: 1223876, 2023.
Article in En | MEDLINE | ID: mdl-37731922
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Microbiol Year: 2023 Document type: Article Affiliation country: United States Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Front Microbiol Year: 2023 Document type: Article Affiliation country: United States Country of publication: Switzerland