Relevance of intracellular polarity to accuracy of eukaryotic chemotaxis

Abstract

Eukaryotic chemotaxis is usually mediated by intracellular signals that tend to localize at the front or back of the cell. Such intracellular polarities frequently require no extracellular guidance cues, indicating that spontaneous polarization occurs in the signal network. Spontaneous polarization activity is considered relevant to the persistent motions in random cell migrations and chemotaxis. In this study, we propose a theoretical model that connects spontaneous intracellular polarity and motile ability in a chemoattractant solution. We demonstrate that the intracellular polarity can enhance the accuracy of chemotaxis. Chemotactic accuracy should also depend on chemoattractant concentration through the concentration-dependent correlation time in the polarity direction. Both the polarity correlation time and the chemotactic accuracy depend on the degree of responsiveness to the chemical gradient. We show that optimally accurate chemotaxis occurs at an intermediate responsiveness of intracellular polarity. Experimentally, we find that the persistence time of randomly migrating Dictyostelium cells depends on the chemoattractant concentration, as predicted by our theory. At the optimum responsiveness, this ameboid cell can enhance its chemotactic accuracy tenfold.

Polar pattern formation induced by contact following locomotion in a multicellular system

“…In the model, particle i at position r i self-propels at a constant velocity ν 0 in the direction of its own polarity q i subjected to white Gaussian noise. Thus, without interactions, the particles exhibit a persistent random walk(Hiraiwa et al, 2014). The effect of CFL is introduced so that polarity q i orients to the location of the adjacent particle j , when particle i is located at the tail of particle j (parameterized by ζ ).…”

“…In the model, self-propelled particle i at position r i moves at a constant velocity ν 0 in the direction of its own polarity q i subjected to white Gaussian noise. Thus, without interactions, the particles exhibit persistent random walk(Hiraiwa et al, 2014). Collective motion can be modeled by assuming particle-particle interactions(Hiraiwa, 2019).…”

Modeling cell crawling strategies with a bistable model: From amoeboid to fan-shaped cell motion

“…We should distinguish between the characteristic times obtained for example from the autocorrelation functions and the persistence time, which refer to different concepts. In contrast with the calculations using autocorrelation functions, the persistence times are typically calculated from mean square displacements (MSD) [57,28].…”

Dynamic self-organization of migrating cells under constraints by spatial confinement and epithelial integrity

“…1 c). The basal side of each cell is modeled by a so-called self-propelled particle, meaning that the particle is spontaneously moving on the substrate according to its intrinsic polarity [ 14 , 19 ]. This mimics the spontaneous migration ability of each cell on the basal substrate.…”

“…(ii) Epithelial integrity at the apical side is modeled based on the cellular vertex model in two dimensions [ 18 ], and for brevity the constraints due to this vertex model at the apical side are termed apical constraint. (iii) The basal side of each cell is modeled by a single disk which spontaneously move on the two-dimensional substrate according to its intrinsic polarity [ 19 ]. (iv) The apical and basal sides of each cell are connected to each other through a linear elastic spring.…”