An in vitro agent-based modelling approach to optimization of culture medium for generating muscle cells

Abstract

Methodologies for culturing muscle tissue are currently lacking in terms of quality and quantity of mature cells produced. We analyse images from in vitro experiments to quantify the effects of culture media composition on mouse-derived myoblast behaviour and myotube quality. Metrics of early indicators of cell quality were defined. Images of muscle cell differentiation reveal that altering culture media significantly affects quality indicators and myoblast migratory behaviours. To study the effects of early-stage cell behaviours on mature cell quality, metrics drawn from experimental images or inferred by approximate Bayesian computation (ABC) were applied as inputs to an agent-based model (ABM) of skeletal muscle cell differentiation with quality indicator metrics as outputs. Computational modelling was used to inform further in vitro experiments to predict the optimum media composition for culturing muscle cells. Our results suggest that myonuclei production in myotubes is inversely related to early-stage nuclei fusionindex and that myonuclei density and spatial distribution are correlated with residence time of fusing myoblasts, the age at which myotube-myotube fusion ends and the repulsion force between myonuclei. Culture media with 5% serumwas found to produce the optimum cell quality and to make muscle cells cultured in a neuron differentiation medium viable.