Early Stem Cell Aging in the Mature Brain

Abstract

Stem cell dysfunction drives many age-related disorders. Identifying mechanisms that initiate stem cell dysfunction represent early targets to enhance tissue resiliency throughout life. Here, we pinpoint multiple factors that compromise neural stem cell (NSC) behavior in the adult hippocampus. We find that NSCs exhibit asynchronous depletion by identifying short-term (ST-NSC) and intermediate-term NSCs (IT-NSCs). ST-NSC divide rapidly to generate neurons and deplete in the young brain. Meanwhile, multipotent IT-NSCs are maintained for months, but are pushed out of homeostasis by lengthening quiescence. Single cell transcriptome analysis of deep NSC quiescence revealed several hallmarks of cellular aging in the mature brain, including changes in tyrosine-protein kinases Abl1 and Abl2. Treatment with the Abl-inhibitor Imatinib was sufficient to overcome deep quiescence and restore NSC proliferation in the middle-aged brain. Further examination of mature NSC with old epidermal, hematopoietic and muscle stem cell transcriptomes identified consensus changes in stem cell aging. Our study elucidates multiple origins of adult neurogenesis decline and reveals that hippocampal NSCs are particularly vulnerable to a shared stem cell aging signature.

Progressive changes in hippocampal stem cell properties ensure lifelong neurogenesis

“…This progression into deeper quiescence did not result in mis-regulation of pathways associated with pathological features of aging, emphasising the difference between a deep quiescent state and senescence (Kwon et al, 2017). The deepening quiescence of dormant NSCs may instead enable these cells to act as a reserve pool of stem cells, suggesting that these cells should not necessarily be considered as targets to enhance tissue resiliency (Ibrayeva et al, 2019).…”

“…returning to quiescence, remained unclear. Our scRNA-seq dataset, which contains approximately 10-20 fold more adult hippocampal NSCs than the largest previous study (Hochgerner et al, 2018), and includes tracing with the Ki67-creER T2 allele allowing for the unbiased sampling of active NSCs unlike lines featured in other studies (Ibrayeva et al, 2019;Pilz et al, 2018), reveals two distinct quiescent states. We find in particular that hippocampal NSCs that have recently divided and returned to a resting state are in much shallower quiescent state than NSCs that have never left quiescence.…”

“…Importantly, we found that these changes in NSC behaviour arise early (in mice as young as 1-month of age; Figure 1I) and take place mostly during the first 12 months of life. These changes are therefore distinct from ageing-associated pathological changes that lead to NSC dysfunction (Ibrayeva et al, 2019;Leeman et al, 2018;Miranda et al, 2012;Seib et al, 2013;Yousef et al, 2015) Resting NSCs increasingly contribute to the proliferative NSC pool…”

Metabolic control of adult neural stem cell self-renewal by the mitochondrial protease YME1L

“…In young adult mice, a significant fraction of NSPCs undergoes a limited number of self-renewing divisions interspersed by temporary quiescent states, before being eventually depleted (Bonaguidi et al, 2011;Encinas et al, 2011;Pilz et al, 2018). However, populations of NSPCs with extended periods of quiescence favouring long-term self-renewing capacity exist, and likely critically contribute to continuous neurogenesis during adulthood (Bottes et al, 2021;Harris et al, 2021;Ibrayeva et al, 2021). By examining changes in the mitochondrial proteome mirroring the acquisition of active and quiescent states, we have identified an unexpected role for the protease YME1L in maintaining the self-renewing potential of adult NSPCs seemingly independent from its role in balancing mitochondrial dynamics via OPA1 processing (Anand et al, 2014;Wai et al, 2015).…”

Characterization of the neurogenic niche in the aging dentate gyrus using iterative immunofluorescence imaging

“…Future experiments will aim to selectively manipulate newly identified aspects of niche interactions and composition that were identified here, probing for their functional significance. Together with other omics-based approaches that aim to identify age-dependent changes in the aging brain and within NSCs and their progeny (Shavlakadze et al, 2019;Ximerakis et al, 2019;Ibrayeva et al, 2020), the tissue 4i-based dataset we provide here will contribute to future work with the aim to enhance neurogenesis in aged brains. Tissue 4ibased data will contribute to such efforts by not only allowing for high spatial resolution of obtained expression data within complex tissues but also allowing for the characterization of interactions in the three-dimensional space, which is at this time a unique feature of tissue 4i.…”