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Updated: May 7, 2025
Resurrection of Dormant Daphnia magna: Protocol and Applications
Published on: January 19, 2018
An ecological and stochastic perspective on persisters resuscitation
Tania Alonso-Vásquez1, Michele Giovannini1, Gian Luigi Garbini1
1Department of Biology, University of Florence, Via Madonna del Piano 6, Sesto Fiorentino, 50019, Italy.
Abstract:
Resistance, tolerance, and persistence to antibiotics have mainly been studied at the level of a single microbial isolate. However, in recent years it has become evident that microbial interactions play a role in determining the success of antibiotic treatments, in particular by influencing the occurrence of persistence and tolerance within a population. Additionally, the challenge of resuscitation (the capability of a population to revive after antibiotic exposure) and pathogen clearance are strongly linked to the small size of the surviving population and to the presence of fluctuations in cell counts. Indeed, while large population dynamics can be considered deterministic, small populations are influenced by stochastic processes, making their behaviour less predictable. Our study argues that microbe-microbe interactions within a community affect the mode, tempo, and success of persister resuscitation and that these are further influenced by noise. To this aim, we developed a theoretical model of a three-member microbial community and analysed the role of cell-to-cell interactions on pathogen clearance, using both deterministic and stochastic simulations. Our findings highlight the importance of ecological interactions and population size fluctuations (and hence the underlying cellular mechanisms) in determining the resilience of microbial populations following antibiotic treatment.
Insights
Microbial interactions influence antibiotic tolerance and persister resuscitation. Community dynamics and population fluctuations are key to pathogen clearance and microbial resilience after antibiotic treatment.
Area of Science:
- Microbiology
- Theoretical Biology
- Computational Biology
Background:
- Antibiotic resistance, tolerance, and persistence are typically studied in single isolates.
- Microbial interactions are increasingly recognized as crucial for antibiotic treatment success.
- Resuscitation and pathogen clearance depend on surviving population size and fluctuations.
Purpose of the Study:
- To investigate how microbe-microbe interactions affect persister resuscitation and pathogen clearance.
- To analyze the impact of ecological interactions and stochasticity on microbial population dynamics after antibiotic exposure.
Main Methods:
- Development of a theoretical model for a three-member microbial community.
- Utilizing both deterministic and stochastic simulations to analyze population dynamics.
- Examining the role of cell-to-cell interactions and population size fluctuations.
Main Results:
- Microbe-microbe interactions significantly influence the dynamics and success of persister resuscitation.
- Ecological interactions and population size fluctuations impact pathogen clearance.
- Stochastic processes in small populations affect the predictability of microbial behavior.
Conclusions:
- Ecological interactions are critical for microbial population resilience post-antibiotic treatment.
- Population size fluctuations and underlying cellular mechanisms are important determinants of antibiotic treatment outcomes.
- Theoretical modeling provides insights into complex microbial community dynamics under antibiotic stress.
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