Simplification of the tug-of-war model for cellular transport in cells

TL;DR

This paper simplifies a complex two-motor tug-of-war model for cellular transport into a one-dimensional form, enabling more precise analytical and numerical analysis of its stability and bifurcation properties.

Contribution

The authors reduce the two-dimensional model to a one-dimensional equation, facilitating detailed theoretical analysis and improving computational efficiency.

Findings

Stable stationary points correspond to roots with positive derivatives.

Bifurcation points occur where the simplified equation has roots with zero derivative.

The simplified model allows for more accurate and efficient numerical calculations.

Abstract

The transport of organelles and vesicles in living cells can be well described by a kinetic tug-of-war model advanced by M\"uller, Klumpp and Lipowsky. In which, the cargo is attached by two motor species, kinesin and dynein, and the direction of motion is determined by the number of motors which bind to the track. In recent work [Phys. Rev. E 79, 061918 (2009)], this model was studied by mean field theory, and it was found that, usually the tug-of-war model has one, two, or three distinct stable stationary points. However, the results there are mostly obtained by numerical calculations, since it is hard to do detailed theoretical studies to a two-dimensional nonlinear system. In this paper, we will carry out further detailed analysis about this model, and try to find more properties theoretically. Firstly, the tug-of-war model is simplified to a one-dimensional equation. Then we claim that the stationary points of the tug-of-war model correspond to the roots of the simplified equation, and the stable stationary points correspond to the roots with positive derivative. Bifurcation occurs at the corresponding parameters, under which the simplified one-dimensional equation exists root with zero derivative. Using the simplified equation, not only more properties of the tug-of-war model can be obtained analytically, the related numerical calculations will become more accurate and more efficient. This simplification will be helpful to future studies of the tug-of-war model.