bioRxivCell BiologyPreprint
Dynamical modeling reveals RNA decay mediates the effect of matrix stiffness on aged muscle stem cell fate
Z. R. Hettinger, S. Hu, H. Mamiya, A. Sahu, H. Iijima, K. Wang, G. Gilmer, A. Miller, G. Nasello, A. D'Amore, D. A. Vorp, T. A. Rando, J. Xing, F. Ambrosio
Abstract
Loss of muscle stem cell (MuSC) self-renewal with aging reflects a combination of influences from the intracellular (e.g., post-transcriptional modifications) and extracellular (e.g., matrix stiffness) environment. Whereas conventional single cell analyses have revealed valuable insights into factors contributing to impaired self-renewal with age, most are limited by static measurements that fail to capture nonlinear dynamics. Using bioengineered matrices mimicking the stiffness of young and old muscle, we showed that while young MuSCs were unaffected by aged matrices, old MuSCs were phenotypically rejuvenated by young matrices. Dynamical modeling of RNA velocity vector fields in silico revealed that soft matrices promoted a self-renewing state in old MuSCs by attenuating RNA decay. Vector field perturbations demonstrated that the effects of matrix stiffness on MuSC self-renewal could be circumvented by fine-tuning the expression of the RNA decay machinery. These results demonstrate that post-transcriptional dynamics dictate the negative effect of aged matrices on MuSC self-renewal. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/529950v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1a840corg.highwire.dtl.DTLVardef@d354cforg.highwire.dtl.DTLVardef@650556org.highwire.dtl.DTLVardef@41587c_HPS_FORMAT_FIGEXP M_FIG Graphical abstract description: The balance of self-renewal and differentiation in young muscle stem cells (MuSCs) is robust to perturbations of the biophysical microenvironment. In contrast, aged MuSCs are highly sensitive to extrinsic perturbations, and exposure to a youthful microenvironment rejuvenates the self-renewing potential of aged MuSCs by modulating post-transcriptional RNA dynamics. C_FIG
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: diffusion model
- approach: statistical model
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