Cell shape characteristics of human skeletal muscle cells as a predictor of myogenic competency: A new paradigm towards precision cell therapy

Journal of Tissue Engineering(2023)

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摘要
Skeletal muscle-derived cells (SMDC) hold tremendous potential for replenishing dysfunctional muscle lost due to disease or trauma. Current therapeutic usage of SMDC relies on harvesting autologous cells from muscle biopsies that are subsequently expanded in vitro before re-implantation into the patient. Heterogeneity can arise from multiple factors including quality of the starting biopsy, age and comorbidity affecting the processed SMDC. Quality attributes intended for clinical use often focus on minimum levels of myogenic cell marker expression. Such approaches do not evaluate the likelihood of SMDC to differentiate and form myofibres when implanted in vivo, which ultimately determines the likelihood of muscle regeneration. Predicting the therapeutic potency of SMDC in vitro prior to implantation is key to developing successful therapeutics in regenerative medicine and reducing implementation costs. Here, we report on the development of a novel SMDC profiling tool to examine populations of cells in vitro derived from different donors. We developed an image-based pipeline to quantify morphological features and extracted cell shape descriptors. We investigated whether these could predict heterogeneity in the formation of myotubes and correlate with the myogenic fusion index. Several of the early cell shape characteristics were found to negatively correlate with the fusion index. These included total area occupied by cells, area shape, bounding box area, compactness, equivalent diameter, minimum ferret diameter, minor axis length and perimeter of SMDC at 24 h after initiating culture. The information extracted with our approach indicates live cell imaging can detect a range of cell phenotypes based on cell-shape alone and preserving cell integrity could be used to predict propensity to form myotubes in vitro and functional tissue in vivo.
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