Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation

Antibiotic persistence, characterized by a dormant subpopulation of bacterial cells that causes chronic and recurrent infections, remains poorly understood despite being recognized nearly a century ago. Toxin-antitoxin (TA) systems, which include a toxin and an antitoxin, are promising candidates for elucidating persister formation. We present the first theoretical model of persister formation driven by type I TA systems, in which the antitoxin is a small RNA molecule. Our analyses and simulations reveal two steady states-low toxin (normal growth) and high toxin (persistence)-with stochastic switching between them. Bistability requires both positive and negative feedback mediated by inhibition of antitoxin degradation. We derive stability diagrams that map mechanistic properties to system dynamics. The model suggests that while type I TA systems may not produce persisters under normal conditions, they can enter a bistable regime under stress, such as antibiotic exposure or nutrient limitation, leading to increased toxin expression or slower growth. Moreover, transiently slow-growing cells can be stabilized as long-living persisters through bistable TA dynamics. Using a cusp catastrophe surface, we identify distinct roles for two toxin inhibition mechanisms in modulating steady states and hysteresis. These findings provide a mechanistic basis for experimental observations and a framework for future studies.

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Publication Details

Journal
npj Systems Biology and Applications
Published
2025-12-23
DOI
https://doi.org/10.1038/s41540-025-00639-2
Primary Topic
Bacterial Genetics and Biotechnology
Type
article
Field-Weighted Citation Impact
0.00

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article

Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation

Magdalena Djordjevic, OU Hong-yu, Marko Djordjevic, Sofija Markovic
npj Systems Biology and Applications
Bacterial Genetics and Biotechnology
article

Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation

Magdalena Djordjevic, OU Hong-yu, Marko Djordjevic, Sofija Markovic
article en

Abstract

Antibiotic persistence, characterized by a dormant subpopulation of bacterial cells that causes chronic and recurrent infections, remains poorly understood despite being recognized nearly a century ago. Toxin-antitoxin (TA) systems, which include a toxin and an antitoxin, are promising candidates for elucidating persister formation. We present the first theoretical model of persister formation driven by type I TA systems, in which the antitoxin is a small RNA molecule. Our analyses and simulations reveal two steady states-low toxin (normal growth) and high toxin (persistence)-with stochastic switching between them. Bistability requires both positive and negative feedback mediated by inhibition of antitoxin degradation. We derive stability diagrams that map mechanistic properties to system dynamics. The model suggests that while type I TA systems may not produce persisters under normal conditions, they can enter a bistable regime under stress, such as antibiotic exposure or nutrient limitation, leading to increased toxin expression or slower growth. Moreover, transiently slow-growing cells can be stabilized as long-living persisters through bistable TA dynamics. Using a cusp catastrophe surface, we identify distinct roles for two toxin inhibition mechanisms in modulating steady states and hysteresis. These findings provide a mechanistic basis for experimental observations and a framework for future studies.

npj Systems Biology and ApplicationsVol. 12(1)
Serbian Academy of Sciences and Arts (RS), Shanghai Jiao Tong University (CN), University of Belgrade (RS), Institute of Physics Belgrade (RS)
National Natural Science Foundation of China, Science Fund of the Republic of Serbia
Openalex Percentile: Top 25%
Bacterial Genetics and Biotechnology
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Bistability in type I toxin-antitoxin systems may lead to stress-induced persister formation — Magdalena Djordjevic, OU Hong-yu, et al. · npj Systems Biology and Applications (2025) | TGRS Research Map | TGRS