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Quantitative systems-based prediction of antimicrobial resistance evolution.

ABSTRACT: Predicting evolution is a fundamental problem in biology with practical implications for treating antimicrobial resistance, which is a complex system-level phenomenon. In this perspective article, we explore the limits of predicting antimicrobial resistance evolution, quantitatively define the predictability and repeatability of microevolutionary processes, and speculate on how these quantities vary across temporal, biological, and complexity scales. The opportunities and challenges for predicting antimicrobial resistance in the context of systems biology are also discussed. Based on recent research, we conclude that the evolution of antimicrobial resistance can be predicted using a systems biology approach integrating quantitative models with multiscale data from microbial evolution experiments.

SUBMITTER: Charlebois DA

PROVIDER: S-EPMC10485028 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Quantitative systems-based prediction of antimicrobial resistance evolution.

Charlebois Daniel A DA

NPJ systems biology and applications 20230907 1

Predicting evolution is a fundamental problem in biology with practical implications for treating antimicrobial resistance, which is a complex system-level phenomenon. In this perspective article, we explore the limits of predicting antimicrobial resistance evolution, quantitatively define the predictability and repeatability of microevolutionary processes, and speculate on how these quantities vary across temporal, biological, and complexity scales. The opportunities and challenges for predicti ...[more]

PMID: 37679446

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