Abstract
ABSTRACTMurine muscle stem cells (MuSCs) experience a transition from quiescence to activation that is required for regeneration, but it remains unknown if the trajectory and dynamics of activation change with age. Here, we use time-lapse imaging and single cell RNA-seq to measure activation trajectories and rates in young and aged MuSCs. We find that the activation trajectory is conserved in aged cells, and we develop effective machine-learning classifiers for cell age. Using cell-behavior analysis and RNA velocity, we find that activation kinetics are delayed in aged MuSCs, suggesting that changes in stem cell dynamics may contribute to impaired stem cell function with age. Intriguingly, we also find that stem cell activation appears to be a random walk-like process, with frequent reversals, rather than a continuous linear progression. These results support a view of the aged stem cell phenotype as a combination of differences in the location of stable cell states and differences in transition rates between them.
Highlights
Stem cells play a keystone role in tissue homeostasis and regeneration in mammalian tissues
Identifying genetic pathways that are altered in both aged muscle stem cells (MuSCs) and non-label retaining cells (nonLRCs), we find that biosynthetic processes activate more slowly in both populations
We demonstrated that quantitative measurements of cell motility behavior from timelapse imaging data are sufficient to resolve states of MuSC activation and state transitions (Kimmel et al, 2018)
Summary
Stem cells play a keystone role in tissue homeostasis and regeneration in mammalian tissues. Age-related decline in regenerative potential has been attributed to differences in cell signaling (Bernet et al, 2014; Brack et al, 2007; Conboy et al, 2003; Cosgrove et al, 2014) and proliferative history (Chakkalakal et al, 2012). These differences in regenerative potential between stem cells are traditionally viewed as the result of differences in the characteristics of stable cell phenotypes (Altschuler and Wu, 2010; Blau et al, 2015; Chakkalakal et al, 2012)
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