Cell decision capture and control via joint Raman live and omics profiling
▶Summary
The developing nervous system generates an extraordinary diversity of cell types through a series of critical fate decisions made by neural progenitors. Despite recent progress in cataloging the heterogeneity of brain cells, we lack an understanding of the factors orchestrating their fine specification, especially in humans. As a result, many decision processes have uncharacterized determinants and are accounted for as stochastic, leaving us without control over them. This knowledge gap stems from the absence of a systematic approach to capture dynamic moments of cell decision-making and discover the factors controlling them.I hypothesize that most fate decisions in the human developing nervous system are not stochastic and, instead, depend on many fine-grained, dynamic mechanisms of cell decision-making. However, only a limited number have been characterized, too few to explain the thousands of cell types in the human brain. To explore this hypothesis, I propose a novel experimental paradigm to elucidate the molecular determinants governing cell decisions. The approach combines live-cell Raman spectrometry imaging, omics profiling, and inducible degrons. I designed it to operate on cell decisions like a film-editing machine, a Moviola: from an outcome, it learns how to “rewind” to a cell’s decision, “halts” the cell and profiles it for decision determinants, and “edits” it to steer it away from the original outcome.By applying this approach, we expect to find factors influencing fate decisions in human neural specification and reveal a more deterministic control of neural cell fates, illuminating how the vast cellular diversity originates from decision-making events. The insights gained will offer ways to improve in vitro models and cell therapies, with potential implications in the attenuation of neural disorders. This groundbreaking paradigm revolutionizes the study of cell decision-making, with far-reaching implications across diverse fields of biology.