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Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug’s action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.
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This content will become publicly available on January 2, 2027
Single-cell heterogeneity underpins antagonistic antibiotic interactions
Using combinations of existing antibiotics is a promising strategy to treat bacterial infections. Although some drugs act synergistically, other drug combinations inhibit microbial growth less than what is expected from their individual effects. Ciprofloxacin and tetracycline display such antagonistic interaction. In a new study, Broughton and colleagues (Broughton et al, 2025) used single-cell microfluidics to show that exposing E. coli cells to a combination of ciprofloxacin and tetracycline results in highly heterogeneous outcomes. The survival of single cells is linked to the expression of moderate levels of the SOS response, which fixes the double-strand DNA breaks caused by ciprofloxacin. High expression of the SOS response was found only among dying cells. Tetracycline then counteracts ciprofloxacin by increasing the proportion of cells that survive treatment within the low-SOS subpopulation. These findings highlight the importance of single-cell studies in understanding the phenotypic heterogeneity that emerges during antibiotic responses, which decide the success of treatments.
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- PAR ID:
- 10694635
- Publisher / Repository:
- Springer Nature Link
- Date Published:
- Journal Name:
- Molecular Systems Biology
- Volume:
- 22
- Issue:
- 1
- ISSN:
- 1744-4292
- Page Range / eLocation ID:
- 1 to 3
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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