A critical meta-analysis of predicted no effect concentrations for antimicrobial resistance selection in the environment

Murray, Aimee K.; Stanton, Isobel C. ORCID: https://orcid.org/0000-0002-2700-2407; Tipper, Holly J. ORCID: https://orcid.org/0000-0002-1857-9204; Wilkinson, Helen; Schmidt, Wiebke; Hart, Alwyn; Singer, Andrew C. ORCID: https://orcid.org/0000-0003-4705-6063; Gaze, William H.. 2024 A critical meta-analysis of predicted no effect concentrations for antimicrobial resistance selection in the environment. Water Research, 122310. https://doi.org/10.1016/j.watres.2024.122310

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Official URL: http://dx.doi.org/10.1016/j.watres.2024.122310

Abstract/Summary

Antimicrobial resistance (AMR) is one of the greatest threats to human health with a growing body of evidence demonstrating that selection for AMR can occur at environmental antimicrobial concentrations. Understanding the concentrations at which selection for resistance may occur is critical to help inform environmental risk assessments and highlight where mitigation strategies are required. A variety of experimental and data approaches have been used to determine these concentrations. However, there is minimal standardisation of existing approaches and no consensus on the relative merits of different methods. We conducted a semi-systematic literature review to collect and critically appraise available minimal selective concentration (MSC) and predicted no effect concentration for resistance (PNECR) data and the approaches used to derive them. There were 21 relevant articles providing 331 selective concentrations, ranging from 0.00087 µg/L (ciprofloxacin) to 2,000 µg/L (carbenicillin). Meta-analyses of these data found that selective concentrations are highly compound-dependent, and only a subset of all antimicrobials have been the focus of most of the research. The variety of approaches that have been used, knowledge gaps and future research priorities were identified, as well as recommendations for those considering the selective risks of antimicrobials in the environment.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.watres.2024.122310
UKCEH and CEH Sections/Science Areas:	Pollution (Science Area 2017-) Soils and Land Use (Science Area 2017-)
ISSN:	0043-1354
Additional Keywords:	antimicrobial resistance, risk assessment, selection, predicted no effect concentration for resistance, minimal selective concentration, environment
NORA Subject Terms:	Ecology and Environment Health Data and Information
Date made live:	28 Aug 2024 09:37 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537926

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.watres.2024.122310

UKCEH and CEH Sections/Science Areas:

Pollution (Science Area 2017-)
Soils and Land Use (Science Area 2017-)

ISSN:

0043-1354

Additional Keywords:

antimicrobial resistance, risk assessment, selection, predicted no effect concentration for resistance, minimal selective concentration, environment

NORA Subject Terms:

Ecology and Environment
Health
Data and Information