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Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: Killers and drivers of resistance evolution.

Leclerc, QJ; Lindsay, JA; Knight, GM (2022) Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: Killers and drivers of resistance evolution. PLoS Comput Biol, 18 (11). e1010746. ISSN 1553-7358 https://doi.org/10.1371/journal.pcbi.1010746
SGUL Authors: Lindsay, Jodi Anne

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Abstract

Bacteriophage (phage) are bacterial predators that can also spread antimicrobial resistance (AMR) genes between bacteria by generalised transduction. Phage are often present alongside antibiotics in the environment, yet evidence of their joint killing effect on bacteria is conflicted, and the dynamics of transduction in such systems are unknown. Here, we combine in vitro data and mathematical modelling to identify conditions where phage and antibiotics act in synergy to remove bacteria or drive AMR evolution. We adapt a published model of phage-bacteria dynamics, including transduction, to add the pharmacodynamics of erythromycin and tetracycline, parameterised from new in vitro data. We simulate a system where two strains of Staphylococcus aureus are present at stationary phase, each carrying either an erythromycin or tetracycline resistance gene, and where multidrug-resistant bacteria can be generated by transduction only. We determine rates of bacterial clearance and multidrug-resistant bacteria appearance, when either or both antibiotics and phage are present at varying timings and concentrations. Although phage and antibiotics act in synergy to kill bacteria, by reducing bacterial growth antibiotics reduce phage production. A low concentration of phage introduced shortly after antibiotics fails to replicate and exert a strong killing pressure on bacteria, instead generating multidrug-resistant bacteria by transduction which are then selected for by the antibiotics. Multidrug-resistant bacteria numbers were highest when antibiotics and phage were introduced simultaneously. The interaction between phage and antibiotics leads to a trade-off between a slower clearing rate of bacteria (if antibiotics are added before phage), and a higher risk of multidrug-resistance evolution (if phage are added before antibiotics), exacerbated by low concentrations of phage or antibiotics. Our results form hypotheses to guide future experimental and clinical work on the impact of phage on AMR evolution, notably for studies of phage therapy which should investigate varying timings and concentrations of phage and antibiotics.

Item Type: Article
Additional Information: Copyright: © 2022 Leclerc et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: Anti-Bacterial Agents, Bacteriophages, Phage Therapy, Staphylococcus aureus, Bacteria, Tetracycline, Erythromycin, Bacteria, Staphylococcus aureus, Bacteriophages, Erythromycin, Tetracycline, Anti-Bacterial Agents, Phage Therapy, 01 Mathematical Sciences, 06 Biological Sciences, 08 Information and Computing Sciences, Bioinformatics
SGUL Research Institute / Research Centre: Academic Structure > Infection and Immunity Research Institute (INII)
Journal or Publication Title: PLoS Comput Biol
ISSN: 1553-7358
Language: eng
Dates:
DateEvent
30 November 2022Published
17 November 2022Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
MR/P014658/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/P028322/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/N013638/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
PubMed ID: 36449520
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/115130
Publisher's version: https://doi.org/10.1371/journal.pcbi.1010746

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