Modelling the impact of urban and hospital wastewaters eco-exposomes on the antibiotic-resistance dynamics

Abstract

Antibiotic-resistance emergence and selection have become major public health issues globally. The presence of antibiotic resistant bacteria (ARB) in natural and anthroposophical environments threatens to compromise the sustainability of care in human and animal populations. This study was undertaken to develop a simple model formalizing the selective impact of antibiotics and pollutants on the dynamics of bacterial resistance in water and use the model to analyze longitudinal spatiotemporal data collected in hospital and urban wastewaters. Longitudinal-sampling data were collected between 2012 and 2015 in four different locations in Haute-Savoie, France: hospital and urban wastewaters, before and after water-treatment plants. Concentration in three different types of compounds: 1) heavy metals 2) antibiotics and 3) surfactants; and abundance of 88 individual genes and mobile genetic elements, mostly conferring resistance to antibiotics, were simultaneously collected. A simple hypothesis-driven model describing the weekly ARB dynamics was proposed to fit available data by assuming normalized gene abundance to be proportional to ARB populations in water. Compounds impacts on the dynamics of 17 genes found in multiple sites were estimated. We found that while mercury and vancomycin had relevant effects on ARB dynamics, respectively positively affecting the dynamics of 10 and 12 identified genes, surfactants antagonistically affected genes dynamics (identified for three genes). This simple model enables analyzing the relationship between resistance-gene persistence in aquatic environments and specific compounds inherent to human activities. Applying our model to longitudinal data, we identified compounds that act as co-selectors for antibiotic resistance.HighlightsWe analyzed longitudinal wastewater resistance genes and environmental dataWe developed a simple hypothesis-driven model to assess resistance selectionMercury and vancomycin were key drivers of antibiotic resistance in wastewater

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“…The introduction of HRMS has created new avenues for the identification of previously undiscovered chemicals of concern since it can provide the more probable empirical formula and the MS/MS spectrum to aid with structural elucidation (Gil-Solsona et al, 2021). Despite being less utilized than the top-down approach due to wastewater complexity, it holds promise for discovering unknown substances critical to advancing WBE (Henriot et al, 2024). Furthermore, advances in the most recent HRMS instruments equipped with operational commercial or free tools for wide-scope suspect screening and/or automatic annotation of unknowns, have offered an unparalleled opportunity to decipher those molecules that indicate exposure to pollutants (Picó and Barceló, 2021b).…”

“…In addition to the identification of antimicrobial resistance (AMR) by several microbiological techniques (Sims and Kasprzyk-Hordern, 2020;Chau et al, 2022;Foyle et al, 2023;Larsson et al, 2023;Pandey et al, 2023;Sharma et al, 2023), it is crucial to monitor and assess antibiotic presence in wastewater, and other environmental matrices to address the problem of AMR. WBE is potentially the most reliable approach to estimate antibiotics use (Henriot et al, 2024). WBE has an environmental safety aspect since many of these small molecules of chemical compounds that humans use or are exposed to directly or indirectly (including potential metabolites and degradation products) are currently considered emerging contaminants of concern (CECs).…”