Label-free, live-cell classification of neural stem cell activation state and dynamics

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PROJECT SUMMARY Neural stem cells (NSCs) in the brain proliferate and generate newborn neurons throughout life. Dysfunctions in neurogenesis have been associated with neurological diseases such as epilepsy, depression, and Alzheimer’s Disease. A significant rate-limiting step in adult neurogenesis is NSC quiescence exit, when a non-dividing quiescent NSC (qNSC) enters the cell cycle prior to population expansion and differentiation. Further, during aging and disease, extrinsic and intrinsic factors drive NSCs deeper into quiescence, reducing neurogenesis, and contributing to cognitive decline. Therefore, identifying factors controlling NSC quiescence and quiescence exit are critical to improving neurogenesis and enhancing cognitive function. Currently our understanding of NSC quiescence is incomplete due to technical limitations imposed by the bias of markers used to isolate each population of NSCs and the lack of live cell labeling strategies. However, recently we observed distinct optical signatures separating activated NSCs (aNSCs) from qNSCs using fluorescence-lifetime imaging (FLIM) and the relative abundance of two signals: 1) the metabolite NAD(P)H, and 2) autofluorescence within lysosomes (LAF), a technique we refer to as optical cell state imaging (OCSI). OCSI is a non-invasive tool capable of tracking NSC cell state in living cells over time, without exogenous label. OCSI collects 2 types of data from each cell: the relative abundance of NAD(P)H and LAF through fluorescence intensity, and a decay rate of fluorescent photons from NAD(P)H and LAF using FLIM. This decay rate can change based on fluorophore binding to protein partners or chemical state, which is dependent on the metabolic pathways used by a given cell. Importantly, many studies have shown that qNSCs and aNSCs preferentially rely on different types of cellular metabolism for generating energy. Using dimension reduction analyses of the 8 measures collected with OCSI in young mouse NSCs, we have not only identified distinct signatures separating qNSCs and aNSCs and tracked the dynamic changes of these measures through live cell imaging during quiescence exit, but also prospectively sorted NSCs based on this autofluorescent signal to successfully predict their proliferative behavior and identity from in vitro cultures and acutely isolated NSCs. These results reveal OCSI as a novel tool that uses the energetics of a cell to define its cell state, allowing us to unbiasedly address unanswered questions about NSC quiescence and activation to advance our understanding of these processes. We here propose to 1) identify the molecular signal associated with LAF, one of the primary contributors to OCSI’s predictive ability, 2) determine which quiescent populations current methods of NSC identification target, and 3) develop and validate a FLIM-based cell sorter to increase the throughput for future studies while maintaining the high-resolution separation of quiescent to activated cell states. Completion of these Aims will provide a novel tool and establish OCSI as a method to answer critical questions regarding the mechanisms and regulators underlying NSC quiescence and activation that can be targeted to drive NSC proliferation.