Skeletal muscle regeneration is highly impaired in patients suffering from skeletal muscle disorders like muscular dystrophies, volumetric muscle loss or sarcopenia. Clinically relevant in-vitro skeletal muscle models are needed to better understand these disorders and develop personalized therapeutic strategies. Closely mimicking the developmental myogenesis and the anisotropic organization of the skeletal muscle tissue are crucial for engineering physiologically accurate in-vitro models. In the first part of this study, the paraxial mesoderm differentiation of human induced pluripotent stem cells (hiPSCs) using a non-transgenic protocol was validated. We learned that optimal Matrigel concentrations and starting cell seeding number are crucial for the successful in-vitro differentiation of hiPSCs. The second part of the study aimed to achieve aligned differentiation of C2C12 myoblasts confined to line patterns created by photopatterning of ECM proteins. Interestingly, the differentiated myotubes preferentially aligned with a rightward orientation bias deviating from the line patterns. The angle of the rightward orientation bias increased when the spacing between the line patterns was increased. A protocol to binarize immunofluorescence images was developed in this study. Lastly, the orientation of the aligned myotubes were analyzed using two automated tools, Alignment by Fourier Transform (AFT) and OrientationJ. AFT was superior in alignment scoring accuracy and in providing controllable analysis parameters. But OrientationJ outperformed AFT in terms of diversity of quantitative functionalities. The future goal is to develop a 2D platform to train a machine learning algorithm using aligned myotubes confined to pre-defined geometries and orientations that can enable full automation of the orientation analysis process.
Read more here: Source link