A birth–death model to understand bacterial antimicrobial heteroresistance from time-kill curves
Antimicrobial heteroresistance refers to the presence of different subpopulations with heterogeneous antimicrobial responses within the same bacterial isolate, so they show reduced susceptibility compared with the main population. Though it is widely accepted that heteroresistance can play a crucial...
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| Veröffentlicht in: | Mathematical biosciences Jg. 376; S. 109278 |
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| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
Elsevier Inc
01.10.2024
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| Schlagworte: | |
| ISSN: | 0025-5564, 1879-3134, 1879-3134 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Antimicrobial heteroresistance refers to the presence of different subpopulations with heterogeneous antimicrobial responses within the same bacterial isolate, so they show reduced susceptibility compared with the main population. Though it is widely accepted that heteroresistance can play a crucial role in the outcome of antimicrobial treatments, predictive Antimicrobial Resistance (AMR) models accounting for bacterial heteroresistance are still scarce and need to be refined as the techniques to measure heteroresistance become standardised and consistent conclusions are drawn from data. In this work, we propose a multivariate Birth-Death (BD) model of bacterial heteroresistance and analyse its properties in detail. Stochasticity in the population dynamics is considered since heteroresistance is often characterised by low initial frequencies of the less susceptible subpopulations, those mediating AMR transmission and potentially leading to treatment failure. We also discuss the utility of the heteroresistance model for practical applications and calibration under realistic conditions, demonstrating that it is possible to infer the model parameters and heteroresistance distribution from time-kill data, i.e., by measuring total cell counts alone and without performing any heteroresistance test.
•New stochastic model to understand heteroresistance using birth–death processes.•Model calibration is possible from standard experiments measuring time-kill curves.•Parameters are estimated uniquely (structurally & practically identifiable).•Model shows complex known behaviours, as faster regrowth when raising drug pressure. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0025-5564 1879-3134 1879-3134 |
| DOI: | 10.1016/j.mbs.2024.109278 |