This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Antibiotic resistance is medicine’s climate change: caused by human activity, and resulting in more extreme outcomes. Resistance emerges in microbial populations when antibiotics act on phenotypic variance within the population. This can arise from either genotypic diversity (resulting from a mutation or horizontal gene transfer), or from ‘adaptive’ differences in gene expression due to environmental variation. Adaptive changes can increase fitness allowing bacteria to survive at higher concentrations of the antibiotic. They can also decrease fitness, potentially leading to selection for antibiotic resistance at lower concentrations. There are opportunities for other environmental stressors to promote antibiotic resistance in ways that are hard to predict using conventional assays. Exploiting our observation that commonly used herbicides can increase or decrease the minimum inhibitory concentration (MIC) of different antibiotics, we provide the first comprehensive test of the hypothesis that the rate of antibiotic resistance evolution under specified conditions can increase, regardless of whether a herbicide increases or decreases the antibiotic MIC. Short term evolution experiments were used for various herbicide and antibiotic combinations. We found conditions where acquired resistance arises more frequently regardless of whether the exogenous non-antibiotic agent increased or decreased antibiotic effectiveness. This “damned if you do/damned if you don’t” outcome suggests that the emergence of antibiotic resistance is exacerbated by additional environmental factors that influence competition between bacteria. Our work demonstrates that bacteria may acquire antibiotic resistance in the environment at rates substantially faster than predicted from laboratory conditions.
This is a submission to PeerJ for review.
Growth curves of selectively resistant strains of E. coli in monoculture with or without herbicide, antibiotic, or both
A, C: determination of the growth rate r of Strhigh/low (AH204/AH211) and Tethigh/low (AH201/AH214), respectively. The gray line represents log transformed OD600 values; the dotted black line represents our estimate of growth during the exponential phase calculated using log(OD) values between 48 and 150 min, the period between the grey dashed vertical lines. In this period log(OD) increased approximately linearly with time indicating exponential growth. B, D: determination of the carrying capacity k of Strhigh/low (AH204/AH211) and Tethigh/low (AH201/AH214), respectively. The gray line represents OD600 values; the dotted black line represents the estimated logistic curve calculated by fitting a logistic growth model using non-linear least squares. Antibiotics were used 0.25µg/mL for Str and 0.05µg/mL for Tet; herbicide concentrations were 1830 ppm ae Kamba and 311 ppm ae Roundup.