Extraocular muscle stem cells exhibit distinct cellular properties associated with non-muscle molecular signatures.
Daniela Di GirolamoMaria Benavente-DiazMelania MuroloAlexandre GrimaldiPriscilla Thomas LopesBrendan EvanoMao KirukiStamatia GioftsidiVincent LavilleJean-Yves TinevezGaelle LetortSebastian MellaShahragim TajbakhshGlenda Evangelina ComaiPublished in: Development (Cambridge, England) (2024)
Skeletal muscle stem cells (MuSC) are recognized as functionally heterogeneous. Cranial MuSCs are reported to have greater proliferative and regenerative capacity when compared to the ones in the limb. A comprehensive understanding of the mechanisms underlying this functional heterogeneity is lacking. Here we used clonal analysis, live imaging and scRNA-seq to identify critical features that distinguish extraocular (EOM) from limb muscle stem cell populations. A MyogenintdTom reporter showed that the increased proliferation capacity of EOM MuSCs correlates with deferred differentiation and lower expression of the myogenic commitment gene Myod. Unexpectedly, in vitro activated EOM MuSCs expressed a large array of extracellular matrix components typical of mesenchymal non-muscle cells. Computational analysis underscored a distinct co-regulatory module, which is absent in limb MuSCs, as driver of these features. The EOM transcription factor network, with Foxc1 as key player, appears to be hardwired to EOM identity as it persists during growth, disease, and in vitro after several passages. Our findings shed light on how high-performing MuSCs regulate myogenic commitment by remodeling of their local environment and adopting properties not generally associated with myogenic cells.
Keyphrases
- stem cells
- skeletal muscle
- extracellular matrix
- insulin resistance
- transcription factor
- induced apoptosis
- cell cycle arrest
- genome wide
- cell therapy
- high resolution
- poor prognosis
- single cell
- oxidative stress
- type diabetes
- high throughput
- metabolic syndrome
- crispr cas
- cell death
- mass spectrometry
- bone marrow
- genome wide identification
- network analysis
- high density