Title: A live-cell, label-free imaging strategy for the classification of NSC activation state
Legend: (A) Schematic depicting fluorescence lifetime imaging (FLIM) analysis. Data (blue) is modeled by a biexponential decay equation (red). The instrument response function (IRF) is shown in green. (B–D) aNSCs and qNSCs were imaged for Ch1 and Ch2 intensities and fluorescence lifetimes. (B) 2-photon intensity images of Ch1 and Ch2 in qNSCs and aNSCs. (C and D) Violin plots depicting intensity and representative FLIM endpoints for Ch1 and Ch2 in qNSCs (blue) and aNSCs (red) (n = 3, generalized linear model). (E) Principle component analysis of qNSC (red) and aNSC (blue) OCSI data (Ch1 and Ch2 intensity, α1, τ1, and τ2). (F) Receiver operating characteristic curve depicting a random forest model generated to classify NSC activation state using NSC autofluorescence data. Different lines represent random forest models constructed using subsets of NSC autofluorescence data. Scale bars, 50 μm. ∗∗∗p < 0.001.
Citation: Morrow, C. S., Tweed, K., Farhadova, S., Walsh, A. J., Lear, B. P., Roopra, A., Risgaard, R. D., Klosa, P. C., Arndt, Z. P., Peterson, E. R., Chi, M. M., Harris, A. G., Skala, M. C., & Moore, D. L. (2024). Autofluorescence is a biomarker of neural stem cell activation state. Cell stem cell, 31(4), 570–581.e7. https://doi.org/10.1016/j.stem.2024.02.011
Abstract: Neural stem cells (NSCs) must exit quiescence to produce neurons; however, our understanding of this process remains constrained by the technical limitations of current technologies. Fluorescence lifetime imaging (FLIM) of autofluorescent metabolic cofactors has been used in other cell types to study shifts in cell states driven by metabolic remodeling that change the optical properties of these endogenous fluorophores. Using this non-destructive, live-cell, and label-free strategy, we found that quiescent NSCs (qNSCs) and activated NSCs (aNSCs) have unique autofluorescence profiles. Specifically, qNSCs display an enrichment of autofluorescence localizing to a subset of lysosomes, which can be used as a graded marker of NSC quiescence to predict cell behavior at single-cell resolution. Coupling autofluorescence imaging with single-cell RNA sequencing, we provide resources revealing transcriptional features linked to deep quiescence and rapid NSC activation. Together, we describe an approach for tracking mouse NSC activation state and expand our understanding of adult neurogenesis.
Investigator: Darcie L. Moore, PhD
About the Lab: The Moore Lab is interested in understanding the mechanisms that neural stem cells (NSCs) utilize to stay active during aging. More specifically, the Moore Lab is interested in understanding how NSCs utilize asymmetric cell division to maintain a pristine proteome and preserve cellular function. To carry out their research, the Moore lab uses cell biology, biochemistry, molecular biology, genetics, and computational approaches. They also specifically focus on using advanced live imaging technologies, including FLIP, FLIM, FRAP, photoactivation, 4D timelapse, in vivo cranial window imaging, and computer learning-based high-throughput imaging to address scientific questions.