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A model-based approach to characterize enzyme-mediated response to antibiotic treatments: going beyond the SIR classification

View ORCID ProfileVirgile Andreani, View ORCID ProfileLingchong You, View ORCID ProfilePhilippe Glaser, View ORCID ProfileGregory Batt
doi: https://doi.org/10.1101/2021.07.16.452741
Virgile Andreani
1Inria Paris, 2 rue Simone Iff, 75012 Paris, France
2Institut Pasteur, 28 rue du Docteur Roux, 75015 Paris, France
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  • For correspondence: virgile.andreani@inria.fr gregory.batt@inria.fr
Lingchong You
3Department of Biomedical Engineering and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
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Philippe Glaser
4Unité EERA, CNRS UMR 3525, Institut Pasteur, APHP, Université Paris–Saclay, 28 rue du Docteur Roux, 75015 Paris, France
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Gregory Batt
1Inria Paris, 2 rue Simone Iff, 75012 Paris, France
2Institut Pasteur, 28 rue du Docteur Roux, 75015 Paris, France
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  • For correspondence: virgile.andreani@inria.fr gregory.batt@inria.fr
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Abstract

To design appropriate treatments, one must be able to characterize accurately the response of bacteria to antibiotics. When exposed to β-lactam treatments, bacteria can be resistant and/or tolerant, and populations can exhibit resilience. Disentangling these phenomena is challenging and no consolidated understanding has been proposed so far. Because these responses involve processes happening at several levels, including the molecular level (e.g. antibiotic degradation), the cell physiology level (filamentation) and the population level (release of β-lactamases into the environment), quantitative modelling approaches are needed. Here, we propose a model of bacterial response to β-lactam treatments that accounts for bacterial resistance, tolerance, and population resilience. Our model can be calibrated solely based on optical density readouts, can predict the inoculum effect, and leads to a mechanistically relevant classification of bacterial response to treatments that goes beyond the classical susceptible / intermediate / resistant classification. Filamentation-mediated tolerance and collective enzyme-mediated antibiotic degradation are essential model features to explain the complex observed response of cell populations to antibiotic treatments.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://doi.org/10.5281/zenodo.5111026

  • https://gitlab.inria.fr/InBio/Public/esbl-escape

  • https://gitlab.inria.fr/InBio/Public/platerider

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted July 17, 2021.
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A model-based approach to characterize enzyme-mediated response to antibiotic treatments: going beyond the SIR classification
Virgile Andreani, Lingchong You, Philippe Glaser, Gregory Batt
bioRxiv 2021.07.16.452741; doi: https://doi.org/10.1101/2021.07.16.452741
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A model-based approach to characterize enzyme-mediated response to antibiotic treatments: going beyond the SIR classification
Virgile Andreani, Lingchong You, Philippe Glaser, Gregory Batt
bioRxiv 2021.07.16.452741; doi: https://doi.org/10.1101/2021.07.16.452741

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