Background:
Transplantation of sheet-shaped autologous skeletal muscle-derived cells (SMDCs) has been shown to produce therapeutic effects via paracrine factors in ischemic cardiomyopathy. SMDCs are heterogeneous cell population consist of myoblasts and non-myogenic cells, and their detailed characteristic and paracrine factors has not been fully analyzed. We herein applied single-cell RNA sequencing (scRNA-seq) to profile the population and paracrine factors of SMDCs.
Methods and Results:
Primary SMDCs of human origin were subjected to scRNA-seq and divided into 5 populations, expressing myogenic markers differently. These included four myogenic populations with higher expression of
MYF5
(myoblasts),
myogenin
(early differentiated cells), mitosis-related gene (proliferating cells), and
MYL3
(moderately differentiated cells) and non-myogenic population with lower expression of myogenic genes. On the other hand,
PAX7
, quiescent satellite cell marker, and
MYH4
, terminally differentiated marker, were not expressed in any populations. Furthermore, regarding the expression of key angiogenic factors,
VEGF
and
HGF
were highly expressed in the non-myogenic population and
HMGB1
was expressed in both populations. Moreover, analysis of the gene expression of angiogenic factors differentially expressed in each population indicated that myoblast population highly expressed
PDGFA
and
CCN
(Cellular communication network factor)
1
, and early differentiated population highly expressed
CCN2
. Although these factors were expressed in other populations, their expression tended to be lower in the moderately differentiated cell population.
Conclusion:
Analysis of SMDCs using scRNA-seq revealed that they are heterogeneous cells consisting of multiple myogenic populations with different degrees of differentiation and cytokine production, suggesting that single-cell gene profiling may be useful for the evaluation on characters of effector cells.
Single-cell gene profiling defines differential progenitor subclasses in mammalian neurogenesis