Intracellular Macrophage Infections with E. coli under Nitrosative Stress

Stacey L Bateman1, Patrick Seed1

  • 1Department of Molecular Genetics and Microbiology Center for Microbial Pathogenesis, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA.

Bio-Protocol
|January 1, 2012
PubMed

Insights

This study presents an in vitro method to study how Escherichia coli (E. coli) survives within macrophages. The protocol modulates nitric oxide levels to mimic host defense mechanisms against E. coli infections.

Area of Science:

  • Microbiology
  • Immunology
  • Cell Biology

Background:

  • Extraintestinal pathogenic Escherichia coli (ExPEC) causes severe infections and can survive inside macrophages.
  • Macrophages use reactive nitrogen intermediates (RNI) to combat bacterial infections.
  • Understanding intracellular bacterial survival is crucial for developing new treatments.

Purpose of the Study:

  • To detail an in vitro protocol for modeling host-pathogen interactions between E. coli and macrophages.
  • To investigate the role of nitric oxide (NO) in macrophage defense against E. coli.
  • To provide a adaptable model for studying ExPEC virulence factors and host responses.

Main Methods:

  • Utilizing RAW 264.7 murine macrophage-like cells for in vitro infection models.
  • Manipulating host nitrosative stress by modulating nitric oxide (NO) levels.
  • Pre-incubating cells with L-arginine or IFNγ for high NO state, or L-NAME for low NO state.

Main Results:

  • The protocol allows for the assessment of E. coli intracellular survival within macrophages.
  • It enables the study of host nitrosative stress response modulation.
  • The method has been previously used to evaluate bacterial regulators' contribution to survival.

Conclusions:

  • This protocol provides a robust in vitro system for studying E. coli-macrophage interactions.
  • It facilitates the investigation of host immune responses, specifically NO production, against bacterial pathogens.
  • The adaptable nature of this model allows for diverse applications in infectious disease research.