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Updated: Jun 24, 2026

Live Calcium Imaging of Virus-Infected Human Intestinal Organoid Monolayers Using Genetically Encoded Calcium Indicators
Published on: January 19, 2024
High-throughput quantitation of pathogen-induced calcium signals captured through live-cell fluorescence microscopy
J Thomas Gebert1, Ethan M Huleatt1, Francesca J Scribano1
1Department of Molecular Virology & Microbiology, Baylor College of Medicine, Houston, TX 77030, USA.
Abstract:
Many intracellular pathogens manipulate host cell calcium to facilitate their survival and replication. Live-cell microscopy using fluorescent calcium indicators has become an indispensable tool for characterizing the mechanisms underlying both homeostatic and pathogen-induced cellular calcium dynamics, but such imaging must be coupled with robust quantitative analysis. Further, calcium imaging is most powerful when paired with reductive studies targeting calcium-modulating proteins. The lack of specific inhibitors or agonists to directly target most pathogen-induced calcium signals precludes many of the approaches that have allowed for robust characterization of major eukaryotic cell calcium signaling mechanisms, such as ER Ca2+ release by inositol triphosphate receptors. Given this, we sought to develop quantitative imaging pipelines tailored for the characterization of pathogen-induced calcium signals. Using rotavirus as a prototypical calcium-modulating pathogen, we developed and optimized a suite of computational tools for automated quantitation of both intra- and inter-cellular calcium signals detected via live-cell imaging of infected epithelial monolayers expressing genetically encoded calcium indicators. Using recombinant strains of rotavirus that express fluorescent markers, we developed a system that allows for automated detection of rotavirus-infected cells and normalization of signals to infectivity. All tools were built in ImageJ, making them freely available and adaptable across operating systems and microscope setups. These tools required minimal active time from the user and allowed for the extraction of signal parameters previously unquantifiable, increasing the speed and breadth of characterization.
Insights
Researchers developed new ImageJ tools for quantifying cellular calcium signals in pathogen-infected cells. This enables faster, more detailed analysis of host-pathogen interactions and calcium dynamics.
Area of Science:
- Cellular Biology
- Microbiology
- Biophysics
Background:
- Intracellular pathogens manipulate host cell calcium for survival and replication.
- Live-cell microscopy with calcium indicators is crucial for studying cellular calcium dynamics.
- Lack of specific inhibitors for pathogen-induced calcium signals hinders research.
Purpose of the Study:
- To develop quantitative imaging pipelines for characterizing pathogen-induced calcium signals.
- To create computational tools for automated analysis of cellular calcium dynamics during infection.
- To enable robust quantification of previously unmeasurable signal parameters.
Main Methods:
- Utilized live-cell microscopy with genetically encoded calcium indicators.
- Developed automated computational tools in ImageJ for signal quantitation.
- Employed rotavirus as a model pathogen and used fluorescently tagged recombinant strains.
- Normalized calcium signals to infectivity for accurate analysis.
Main Results:
- Created a suite of computational tools for automated quantification of intra- and inter-cellular calcium signals.
- Enabled automated detection of infected cells and signal normalization.
- Tools are freely available, adaptable, and require minimal user input.
- Allowed extraction of previously unquantifiable signal parameters, enhancing characterization speed and breadth.
Conclusions:
- The developed ImageJ tools provide a robust and efficient method for analyzing pathogen-induced calcium dynamics.
- These tools facilitate deeper understanding of host-pathogen interactions at the cellular level.
- The freely available nature of the tools promotes broader adoption and advancement in the field.

