An optogenetic smart microscopy platform reveals signaling dynamics-dependent control over collective cell migration

In cell biology, optical techniques can measure cells' internal states (biosensors) and stimulate cellular responses (optogenetics). Yet the design of all-optical experiments is often manual: a predetermined stimulus pattern is applied to cells, biosensors are measured over time, and data are processed offline. Here, we develop PyCLM, a Python-based suite enabling closed-loop measurement, image segmentation, and optogenetic control of thousands of cells per experiment. We showcase PyCLM on diverse applications, including performing feedback control on single cells and delivering developmental signaling patterns to Drosophila embryos. We compare single-cell versus tissue-scale optogenetic control of epithelial migration, revealing that fast and slow waves of receptor tyrosine kinase activity determine the direction of tissue movement, matching prior in vivo observations in zebrafish and mouse. PyCLM enables simple setup of dynamic experiments to probe cell and tissue properties and provides a first step toward real-time control of single-cell states at the tissue scale.