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An Image Processing Algorithm for Facile and Reproducible Quantification of Vomocytosis.

Neeraj Senthil1, Noah Pacifici1, Melissa Cruz-Acuña1

  • 1Department of Biomedical Engineering, University of California - Davis, Davis, California 95616, United States.

Chemical & Biomedical Imaging
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Summary

A new MATLAB algorithm automates the quantification of vomocytosis, a fungal pathogen escape process. This high-throughput tool significantly reduces analysis time and human error, accelerating research into fungal infections like Cryptococcus neoformans.

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Area of Science:

  • Immunology
  • Microbiology
  • Computational Biology

Background:

  • Vomocytosis is the escape of fungal pathogens from host phagocytes without cell death.
  • Manual analysis of time-lapse microscopy for vomocytosis is time-consuming and labor-intensive.
  • Studying vomocytosis is crucial for understanding host-pathogen interactions and fungal virulence.

Purpose of the Study:

  • To develop an automated algorithm for high-throughput quantification of vomocytosis.
  • To reduce the time and human error associated with analyzing vomocytosis in microscopy videos.
  • To enable faster characterization of fungal strains, such as Cryptococcus neoformans (CN), for epidemiological and virulence studies.

Main Methods:

  • A MATLAB algorithm was designed to analyze multichannel, time-lapse microscopy videos.
  • The algorithm measures colocalization between phagocytes and fungal cells (CN).
  • Fluorescently stained immune cells and CN were cocultured and imaged.

Main Results:

  • The algorithm quantifies vomocytosis events with high throughput.
  • Analysis time was reduced by 83%, from over 1 hour to 10 minutes per video.
  • The tool minimizes human error in vomocytosis quantification.

Conclusions:

  • The developed algorithm significantly streamlines the vomocytosis analysis pipeline.
  • This tool accelerates research into the mechanisms of vomocytosis and fungal pathogenesis.
  • Automated analysis facilitates rapid characterization of fungal strains for virulence and epidemiology research.