A statistical and biophysical toolbox to elucidate structure and formation of stress fibers

Abstract

We are concerned with statistically validated early mechanically guided differentiation of human mesenchymal stem cells (hMSCs). This chapter reviews and extends methods of fixed and live imaging of hMSCs, automated reliable and unbiased near real-time filament extraction and digitization for massive data via the FilamentSensor, suitable aggregation of simple (area, mean orientation, aspect ratio and order parameter) and advanced (orientation mode persistence and orientation fields) data descriptors and methods of their non-euclidean inferential statistics. Exemplary, we study the morphology of stress fibers in fixed and live hMSCs within 24 h post seeding on elastic matrices exhibiting Young’s moduli of 1 kPa (soft, brain-like elasticity), 11 kPa (intermediate, muscle-like stiffness) and 30 kPa (hard, pre-calcified bone rigidity). The combination of these methods constitutes a novel integrated toolbox, where for instance, statistical insight may be used to guide experimental design.