title: Anin silicoprediction tool for the expansion culture of human skeletal muscle myoblasts.
abstract: Regenerative therapy using autologous skeletal myoblasts requires a large number of cells to be prepared for high-level secretion of cytokines and chemokines to induce good regeneration of damaged regions. However, myoblast expansion culture is hindered by a reduction in growth rate owing to cellular quiescence and differentiation, therefore optimization is required. We have developed a kinetic computational model describing skeletal myoblast proliferation and differentiation, which can be used as a prediction tool for the expansion process. In the model, myoblasts migrate, divide, quiesce and differentiate as observed duringin vitroculture. We assumed cell differentiation initiates following cell-cell attachment for a defined time period. The model parameter values were estimated by fitting to several predetermined experimental datasets. Using an additional experimental dataset, we confirmed validity of the developed model. We then executed simulations using the developed model under several culture conditions and quantitatively predicted that non-uniform cell seeding had adverse effects on the expansion culture, mainly by reducing the existing ratio of proliferative cells. The proposed model is expected to be useful for predicting myoblast behaviours and in designing efficient expansion culture conditions for these cells.
authors.affiliation: Department of Biotechnology, Graduate School of Engineering , Osaka University , 2-1 Yamada-oka, Suita, Osaka 565-0871 , Japan.
authors.forename: Yuki
authors.initials: Y
authors.lastname: Kagawa
authors.affiliation: Department of Biotechnology, Graduate School of Engineering , Osaka University , 2-1 Yamada-oka, Suita, Osaka 565-0871 , Japan.
authors.forename: Masahiro
authors.identifier: 0000-0002-4912-5811
authors.initials: M
authors.lastname: Kino-Oka
keywords: autologous skeletal myoblast; cell migration; cellular automaton; computational modelling; kinetic model