Image based validation of dynamical models for cell reorientation.
A key feature of directed cell movement is the ability of cells to reorient quickly in response to changes in the direction of an extracellular stimulus. Mathematical models have suggested quite different regulatory mechanisms to explain reorientation, raising the question of how we can validate these models in a rigorous way. In this study, we fit three reaction-diffusion models to experimental data of Dictyostelium amoebae reorienting in response to alternating gradients of mechanical shear flow. The experimental readouts we use to fit are spatio-temporal distributions of a fluorescent reporter for cortical F-actin labeling the cell front. Experiments performed under different conditions are fitted simultaneously to challenge the models with different types of cellular dynamics. Although the model proposed by Otsuji is unable to provide a satisfactory fit, those suggested by Meinhardt and Levchenko fit equally well. Further, we show that reduction of the three-variable Meinhardt model to a two-variable model also provides an excellent fit, but has the advantage of all parameters being uniquely identifiable. Our work demonstrates that model selection and identifiability analysis, commonly applied to temporal dynamics problems in systems biology, can be a powerful tool when extended to spatio-temporal imaging data.
['Lockley|Robert|R|', 'Ladds|Graham|G|', 'Bretschneider|Till|T|']
D000199:Actins D002465:Cell Movement D019295:Computational Biology D004023:Dictyostelium D057446:Hydrodynamics D007091:Image Processing, Computer-Assisted D008856:Microscopy, Fluorescence D008954:Models, Biological D008962:Models, Theoretical D049490:Systems Biology
cell reorientation Dictyostelium identifiability analysis actin fluorescence microscopy image based model fitting spatio-temporal pattern formation