期刊
DEVELOPMENT
卷 147, 期 9, 页码 -出版社
COMPANY BIOLOGISTS LTD
DOI: 10.1242/dev.183855
关键词
Aging; Muscle stem cell; Single cell RNA-seq; Time-lapse imaging; State transition; Stem cell activation
资金
- National Institutes of Health [R35 GM130327, AR060868, AR061002, AG063416]
- National Science Foundation (NSF) [1650113, 1548297]
- Pharmaceutical Research and Manufacturers of America Foundation (Informatics Fellowship)
- Human Frontier Science Project [LT000781/2016-L]
- Nvidia (graphics processing unit grant)
Murine 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.
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