Why the study?
Pluripotent-derived cardiomyocytes exhibit immature, poorly organized, and heterogeneous sarcomeres, and cardiomyopathies involve disrupted sarcomere organization, motivating quantitative methods to assess sarcomeric structure.
The SGFT method provides a novel quantitative technique to characterize sarcomere organization and alignment at the sub-cellular scale in cardiomyocytes and other tissues.
May limit therapeutic use of stem cell-derived cardiomyocytes; leaves open biophysical targets for sarcomere maturation.
Recent advances in stem cell biology have allowed researchers to efficiently produce large numbers of cardiomyocytes from various pluripotent cell sources. Unfortunately, these cells exhibit properties that are characteristics of immature cardiomyocytes such as poor sarcomere organization, limited calcium handling, and reduced cell size and alignment. Specifically, the actin–myosin motor proteins that form sarcomeres within these cardiomyocytes fail to produce large, highly ordered repeating structures that are distinctive for adult myocytes. Instead, these cells produce heterogeneous sarcomeres that vary in thickness, alignment, and level of organization. Additionally, a large number of cardiomyopathies have been linked to mutations in genes encoding for sarcomeric proteins, resulting in disrupted sarcomere organization. This research focuses on a series of algorithms that provide a quantitative analysis technique to characterize the alignment and organization of sarcomere structures within aggregates and single cardiomyocytes. The scanning gradient Fourier transform (SGFT) method incorporates gradient analysis along with fast Fourier transforms to determine regions of sarcomere organization within individual and a population of cells, yielding a quantitative method of determining sarcomere organization and alignment at the sub-cellular scale. The utility of the SGFT technique is also demonstrated for additional applications, such as breast cancer collagen microstructure and neural rosette patterning.
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Salick et al. (2020) studied this question.
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