Lattice Light-Sheet Microscopy Multi-dimensional Analyses (LaMDA) of T-Cell Receptor Dynamics Predict T-Cell...

Area of Science:

• Cell biology
• Immunology
• Bioimaging

Background:

• Lattice light-sheet microscopy generates extensive data on cell surface receptors.
• Existing analysis methods for this data are not user-friendly.
• Understanding T-cell receptor (TCR) dynamics is crucial for immunology.

Purpose of the Study:

• To introduce LaMDA, a user-friendly, end-to-end analysis pipeline for lattice light-sheet microscopy data.
• To analyze surface receptor dynamics and classify cellular signaling states.
• To apply the pipeline to study T-cell receptor microclusters on live T-cells.

Main Methods:

• Developed LaMDA, integrating machine learning, dimensionality reduction, and diffusion maps.
• Utilized publicly available software packages for pipeline construction.
• Analyzed 3D imaging data of T-cell receptors on live primary T-cells.

Main Results:

• Observed global spatial and temporal changes in TCRs across the 3D cell surface.
• Accurately differentiated stimulated from unstimulated T-cells.
• Precisely predicted attenuated T-cell signaling and discriminated TCR ligands.

Conclusions:

• LaMDA provides a powerful, accessible tool for analyzing complex cell surface receptor dynamics.
• The pipeline enables classification of cellular signaling states using imaging data alone.
• LaMDA facilitates deeper understanding of T-cell activation and immune responses.