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Updated: Oct 13, 2025

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Using a Bacterial Pathogen to Probe for Cellular and Organismic-level Host Responses
Published on: February 22, 2019
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Analyzing Macrophage Infection at the Organ Level
Ryan G Hames1, Zydrune Jasiunaite1, Joseph J Wanford1
1Department of Genetics and Genome Biology, University of Leicester, Leicester, UK.
Methods in Molecular Biology (Clifton, N.J.)
|November 16, 2021
Summary
This study introduces novel ex vivo and in vivo models to investigate bacterial infection dynamics. These methods offer deeper insights into pathogen-host interactions at the cellular level, overcoming limitations of traditional colony-forming unit (CFU) enumeration.
Area of Science:
- Microbiology
- Pathophysiology
- Infectious Disease Research
Background:
- Classical in vivo infection models often lack detailed physiological context, leading to speculative results.
- Reliance on colony-forming unit (CFU) enumeration alone overlooks crucial unseen physiological factors in infection progression.
- Understanding organ-specific pathophysiology is essential for accurate bacterial infection studies.
Purpose of the Study:
- To present detailed methodologies for two advanced infection models.
- To enable in-depth investigation of pathogen-host interactions within specific organs.
- To overcome limitations of traditional infection models and CFU enumeration.
Main Methods:
- Development and description of an ex vivo porcine liver and spleen coperfusion model.
- Utilization of a complementary murine infection model.
- Integration of diverse experimental outputs from both models for comprehensive analysis.
Main Results:
- The described models provide a framework for detailed analysis of bacterial infection.
- These models allow for the study of pathogen-host interactions at the cellular level within target organs.
- Experimental outputs can be combined for a more thorough understanding of infection dynamics.
Conclusions:
- The presented ex vivo and in vivo models offer enhanced approaches to studying bacterial infections.
- These models facilitate a deeper understanding of pathogen-host interactions beyond traditional methods.
- The integrated use of these models provides richer data for infection research.

