Data-driven Classification of Cell Subtypes Based on Time-Lapse Microscopy of Single Cells with Manasa Kesapragada, UC Santa Cruz

Single-cell time-lapse microscopy allows researchers to track the dynamic response of cellular processes in real-time. Observing these dynamics to external stimuli can help researchers understand the regulation mechanisms underlying complex biological processes. When studying the evolution of cell subtypes, it can become difficult to identify the cell types. Cell size and shape have been used to characterize these cell subtypes, but quality images that can provide cell morphology are difficult to come by. We propose that motility properties can be mapped to cell morphology and, hence, cell subtype. We applied this to macrophages, critical players in our body's defense and wound healing. We found that different types of macrophages move uniquely. We developed methods to track single cells and linked cell movement to its shape using machine learning. Through this study, we demonstrate that mapping migratory patterns and motility properties to cell morphology can inform the classification of cell subtypes.