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BBQ methods: streamlined workflows for bacterial burden quantification in infected cells by confocal microscopy.

Jacques Augenstreich1, Michael Shuster1, Yongqiang Fan1

  • 1Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742, USA.

Biology Open
|December 29, 2023
PubMed
Summary

We developed two automated methods for quantifying bacterial burden within macrophages (BBQ). These PyImageJ and Cellpose-based workflows improve accuracy and speed for host-pathogen interaction studies.

Keywords:
Bio-image analysisConfocal microscopyHost–pathogen interaction

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Area of Science:

  • Microbiology
  • Cell Biology
  • Immunology

Background:

  • Accurate quantification of bacterial burden within macrophages (BBQ) is essential for understanding host-pathogen dynamics.
  • Existing BBQ methods have limitations, impacting the reliability of results.
  • Confocal microscopy is a key technique for visualizing intracellular bacteria.

Purpose of the Study:

  • To introduce two novel, automated methods for bacterial burden quantification (BBQ) in macrophages.
  • To overcome limitations of current BBQ techniques using advanced image analysis.
  • To provide reliable, unbiased, and rapid tools for studying host-pathogen interactions.

Main Methods:

  • Development of two automated workflows for BBQ using PyImageJ and Cellpose software.
  • Method 1: Refined total fluorescence quantification with filtering to exclude uninfected cells.
  • Method 2: Calculation of total bacterial volume per cell to reduce fluorescence-based bias.

Main Results:

  • Validated workflows using Salmonella enterica serovar Typhimurium and Mycobacterium tuberculosis models.
  • Demonstrated accurate and reliable quantification of bacterial load within macrophages.
  • Achieved unbiased and rapid assessment of bacterial burden.

Conclusions:

  • The novel automated workflows offer significant improvements for BBQ.
  • These tools enhance the study of bacterial infections within host cells.
  • The methods are applicable to diverse research investigating host-pathogen interactions.