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Morphodynamical cell state description via live-cell imaging trajectory embedding
Jeremy Copperman1, Sean M Gross2, Young Hwan Chang2,3
1Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, 97239, USA. copperma@ohsu.edu.
Communications Biology
|May 4, 2023
Summary
This study introduces trajectory embedding for analyzing cell behavior over time, offering a more dynamic and comprehensive view than traditional snapshot methods. This approach enhances the quantitative analysis of cell morphology and responses in live-cell imaging.
Area of Science:
- Cell biology
- Quantitative imaging
- Bioinformatics
Background:
- Quantitative analysis of dynamic cellular responses via time-lapse imaging is challenging.
- Traditional methods often analyze single time points (snapshots) rather than continuous cellular behavior.
Purpose of the Study:
- To develop and apply a novel trajectory embedding method for analyzing cellular morphological changes over time.
- To quantitatively model cell state transitions and ligand-induced responses in live-cell imaging.
Main Methods:
- Exploited "trajectory embedding" to analyze morphological feature trajectory histories across multiple time points simultaneously.
- Applied the method to live-cell images of MCF10A mammary epithelial cells treated with microenvironmental perturbagens.
- Constructed a shared cell state landscape to reveal ligand-specific regulation of cell state transitions.
Main Results:
- Morphodynamical trajectory embedding enables quantitative and descriptive models of single-cell trajectories.
- Incorporating trajectories improves systematic characterization of cell state dynamics and phenotype separation.
- The analysis provides more descriptive models of ligand-induced cellular differences compared to snapshot-based approaches.
Conclusions:
- Morphodynamical trajectory embedding offers a powerful, broadly applicable approach for quantitative analysis of cell responses in live-cell imaging.
- This method advances the understanding of dynamic cellular behaviors and their regulation by microenvironmental factors.
- The technique is valuable for various biological and biomedical applications requiring detailed analysis of cell dynamics.
