Computational framework for single-cell spatiotemporal dynamics of optogenetic membrane recruitment

Area of Science:

• Computational biology
• Cellular imaging
• Biophysics

Background:

• Analyzing cell-wide spatiotemporal signaling dynamics is complex due to experimental variations.
• Heterogeneous cell morphologies and optical instrumentation introduce geometric and diffractive complexities.
• Accurate interpretation of single-cell signaling requires accounting for these experimental specifics.

Purpose of the Study:

• To develop a modular computational framework for analyzing cell-wide spatiotemporal signaling dynamics in single-cell microscopy.
• To account for experiment-specific geometric and diffractive complexities arising from cell morphology and optical instrumentation.
• To enable direct comparison between simulations and observable images for improved interpretive robustness.

Main Methods:

• Inputting unique cell geometries and protein concentrations from confocal stacks and environmental stimuli.
• Simulating the system with a chosen model and convolving the output with the microscope point-spread function.
• Experimentally validating the approach using a three-dimensional non-linear finite element model with experimentally derived parameters.

Main Results:

• The framework successfully recapitulates observed subcellular and cell-to-cell variability in BcLOV4 signaling.
• Inter-experimental differences originating from cellular and instrumentation factors were elucidated and resolved.
• The approach demonstrated improved interpretive robustness in single-cell signaling studies.

Conclusions:

• The developed computational framework provides a robust method for analyzing spatiotemporal signaling dynamics in microscopy.
• This single-cell approach enhances the field of optogenetics and spatiotemporally resolved signaling studies.
• The framework's ability to resolve experimental complexities improves the reliability of cell signaling research.