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Updated: Mar 31, 2026
Chronic Salmonella Infected Mouse Model
Published on: May 31, 2010
Population Dynamics Analysis of Ciprofloxacin-Persistent S. Typhimurium Cells in a Mouse Model for Salmonella
Patrick Kaiser1, Roland R Regoes2, Wolf-Dietrich Hardt3
1Institute of Microbiology, D-BIOL, Eidgenössische Technische Hochschule ETH Zurich, Office HCI G417, Vladimir-Prelog-Weg 4, Zürich, 8093, Switzerland.
Abstract:
In vivo, antibiotics are often surprisingly inefficient at eliminating bacterial pathogens. In the case of ciprofloxacin therapy in a Salmonella enterica subspecies 1 serovar Typhimurium (S. Typhimurium, S. Tm) mouse infection model, this has been traced to tolerant bacterial cells surviving in lymph node monocytes (i.e., classical dendritic cells). To analyze the growth characteristics of these persisters, we have developed a population dynamics approach using mixtures of wild-type isogenic tagged strains (WITS) and a computational model. Here, we are providing a detailed description of the inoculum, the infection experiments, the computational analysis of the WITS data, and a computer simulation for assessing the quality of the growth parameters of the persistent S. Typhimurium cells. This approach is generic. It may be adapted to any organ infected and to any bacterial pathogen, provided that tools exist for generating, retrieving, and quantifying isogenic tagged strains.
Insights
Antibiotics often fail to eradicate bacterial infections. This study reveals tolerant Salmonella Typhimurium cells survive in immune cells, hindering treatment. A new computational method analyzes these persistent bacterial populations.
Area of Science:
- Microbiology
- Immunology
- Computational Biology
Background:
- Antibiotics exhibit limited efficacy in eradicating bacterial pathogens in vivo.
- Tolerant bacterial cells, specifically Salmonella Typhimurium (S. Typhimurium), survive within host immune cells like monocytes (classical dendritic cells) during ciprofloxacin therapy.
- This survival within immune niches contributes to treatment inefficiency.
Purpose of the Study:
- To analyze the growth characteristics of persistent S. Typhimurium cells that survive antibiotic treatment.
- To develop and describe a novel population dynamics approach for studying bacterial persistence in vivo.
- To provide a computational framework for assessing the growth parameters of persistent bacteria.
Main Methods:
- Development of a population dynamics approach utilizing mixtures of wild-type isogenic tagged strains (WITS).
- Infection of a mouse model with S. Typhimurium.
- Computational analysis of WITS data to quantify bacterial populations.
- Computer simulations to assess the quality of growth parameters for persistent S. Typhimurium.
Main Results:
- Identification of tolerant S. Typhimurium cells surviving within lymph node monocytes.
- Characterization of the growth dynamics of these persistent bacterial populations.
- Validation of a computational model for analyzing bacterial persistence.
Conclusions:
- The developed WITS and computational modeling approach provides a robust method for studying bacterial persistence.
- This generic approach can be adapted to investigate persistent pathogens in various organs and with different bacterial species.
- Understanding the growth characteristics of persistent bacteria is crucial for improving antibiotic therapy efficacy.
