Comparative mapping of crawling-cell morphodynamics in deep learning-based feature space

Abstract

Navigation of fast migrating cells such as amoeba Dictyostelium and immune cells are tightly associated with their morphologies that range from steady polarized forms that support high directionality to those more complex and variable when making frequent turns. Model simulations are essential for quantitative understanding of these features and their origins, however systematic comparisons with real data are underdeveloped. Here, by employing deep-learning-based feature extraction combined with phase-field modeling framework, we show that a low dimensional feature space for 2D migrating cell morphologies obtained from the shape stereotype of keratocytes, Dictyostelium and neutrophils can be fully mapped by interlinked signaling network of cell-polarization and protrusion dynamics. Our analysis links the data-driven shape analysis to the underlying causalities by identifying key parameters critical for migratory morphologies both normal and aberrant under genetic and pharmacological perturbations. The results underscore the importance of deciphering self-organizing states and their interplay when characterizing morphological phenotypes.

Local actin dynamics couple speed and persistence in a cellular Potts model of cell migration

“…These findings generalize the mechanism behind the UCSP to settings where cells can take on more complex shapes and lack a globally defined polarity. Importantly, they suggest that the UCSP may likewise emerge in other existing models of cell migration, especially those in which cell shape, speed, and persistence emerge from a protrusion mechanism combined with membrane tension (10,(44)(45)(46)(47)(48)(49). In addition, several variations of the original UCSP model have now been developed (36,50,51).…”

Mass-conservation increases robustness in stochastic reaction-diffusion models of cell crawling

“…( 5) respectively, similarly to other models of the motion of Dictyostelium discoideum cells based on global cytosolic quantities [10,46]. The addition of global control quantities which can determine the available concentration inside the cell has previously been employed in other models [30,36,45].…”

“…We have previously used simple stochastic bistable models for the description of the motion of Dictyostelium discoideum cells [32,36] based on the same concept together with a mass-conservation constraint. There are also other models based on similar constraints [45]. Therefore, this constraint is a convenient mechanism to increase robustness in the delicate equilibrium between stochastic fluctuations and a bistable condition.…”

“…In order to reduce the high sensitivity of the movement on the parameter values, we included a conservation constraint on the total quantities of the protein Ras R and the inducer P in the biochemical rates responsible for the bistable transition. Following similar previous approaches [32,45], we included this conservation as a global feedback condition in the reaction-diffusion equations. In Fig.…”

“…Therefore, we propose a constraint on the conservation of a component of the signal pathway, controlling the autocatalytic mechanism, in order to increase the robustness of the model in representing changes in parameter values [44]. Similar types of conservation have previously been employed in other models of motion of Dictyostelium discoideum cells [32,36,45,46], and we show here that a constraint of this kind is an useful and reasonable condition to systematically increase the robustness of the crawling mechanism, increasing the window of parameter values allowing cell migration.…”