What question did this study set out to answer?

To review multi-scale mathematical and systems-level models linking bacterial physiology, metabolic resource allocation, and population-level antimicrobial resistance.

September 1, 2026Current Opinion in Systems BiologyOpen Access

From cells to populations: multi-scale quantitative approaches to antimicrobial resistance

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Authors

LYLucía Yubero-Fernández JMJavier Molina-Hernández MGMarina de la Fuente García

Discussion

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Overview

Review demonstrates multi-scale quantitative models capture bacterial resistance and metabolic constraints, highlighting pathways to improve antimicrobial therapy.

Key Points

To review multi-scale mathematical and systems-level models linking bacterial physiology, metabolic resource allocation, and population-level antimicrobial resistance.
Synthesized coarse-grained mathematical frameworks spanning single-cell proteome allocation to community-level population dynamics.
Evaluated modeling approaches covering dose optimization, multidrug therapies, epistasis, and physiological persistence across bacteriostatic and bactericidal agents.
Identified that cellular metabolic constraints and proteome partitioning drive non-genetic antibiotic tolerance, persistence, and genetically encoded resistance mechanisms.
Demonstrated that multi-scale models capture nonlinear dynamics, including bistability, threshold effects, and regime-dependent bacterial survival strategies.

Cite This Study

Yubero-Fernández et al. (2026) studied this question.

synapsesocial.com/papers/6aae1abcb45aa193b4c0389b https://doi.org/10.1016/j.coisb.2026.100607

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September 1, 2026Current Opinion in Systems BiologyOpen Access

From cells to populations: multi-scale quantitative approaches to antimicrobial resistance

View Full Paper

Ask AI

Bookmark

Authors

LYLucía Yubero-Fernández JMJavier Molina-Hernández MGMarina de la Fuente García

Discussion

Member takes

Overview

Review demonstrates multi-scale quantitative models capture bacterial resistance and metabolic constraints, highlighting pathways to improve antimicrobial therapy.

Key Points

To review multi-scale mathematical and systems-level models linking bacterial physiology, metabolic resource allocation, and population-level antimicrobial resistance.
Synthesized coarse-grained mathematical frameworks spanning single-cell proteome allocation to community-level population dynamics.
Evaluated modeling approaches covering dose optimization, multidrug therapies, epistasis, and physiological persistence across bacteriostatic and bactericidal agents.
Identified that cellular metabolic constraints and proteome partitioning drive non-genetic antibiotic tolerance, persistence, and genetically encoded resistance mechanisms.
Demonstrated that multi-scale models capture nonlinear dynamics, including bistability, threshold effects, and regime-dependent bacterial survival strategies.

Cite This Study

Yubero-Fernández et al. (2026) studied this question.

synapsesocial.com/papers/6aae1abcb45aa193b4c0389b https://doi.org/10.1016/j.coisb.2026.100607

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