BBQ methods: streamlined workflows for bacterial burden quantification in infected cells by confocal microscopy.
Jacques AugenstreichMichael ShusterYongqiang FanZhihui LyuJiqiang LingVolker BrikenPublished in: Biology open (2024)
Accurate quantification of bacterial burden within macrophages, termed bacterial burden quantification (BBQ), is crucial for understanding host-pathogen interactions. Various methods have been employed, each with strengths and weaknesses. This article addresses limitations in existing techniques and introduces two novel, automated methods for BBQ within macrophages based on confocal microscopy data analysis. The first method refines total fluorescence quantification by incorporating filtering steps to exclude uninfected cells, while the second method calculates total bacterial volume per cell to mitigate potential biases in fluorescence-based readouts. These workflows utilize PyImageJ and Cellpose software, providing reliable, unbiased, and rapid quantification of bacterial load. The proposed workflows were validated using Salmonella enterica serovar Typhimurium and Mycobacterium tuberculosis models, demonstrating their effectiveness in accurately assessing bacterial burden. These automated workflows offer valuable tools for studying bacterial interactions within host cells and provide insights for various research applications.
Keyphrases
- induced apoptosis
- data analysis
- mycobacterium tuberculosis
- cell cycle arrest
- machine learning
- deep learning
- systematic review
- high throughput
- risk assessment
- cell death
- stem cells
- oxidative stress
- single cell
- cell proliferation
- mass spectrometry
- mesenchymal stem cells
- antiretroviral therapy
- loop mediated isothermal amplification