Kinetic Monte Carlo and Cellular Particle Dynamics Simulations of Multicellular Systems

TL;DR

This paper introduces two new simulation methods, kinetic Monte Carlo and cellular particle dynamics, for modeling multicellular systems in real time, improving upon previous Monte Carlo approaches.

Contribution

It presents KMC and CPD as novel, real-time capable alternatives to traditional Monte Carlo simulations for multicellular dynamics modeling.

Findings

KMC and CPD successfully simulate cell-sorting phenomena.

Both methods accurately model aggregate fusion.

Real-time simulation capability is demonstrated.

Abstract

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Computer simulations based on Metropolis Monte Carlo (MMC) algorithms were successful in explaining and predicting the resulting stationary structures (corresponding to the lowest adhesion energy state). Here we present two alternatives to the MMC approach for modeling cellular motion and self-assembly: (1) a kinetic Monte Carlo (KMC), and (2) a cellular particle dynamics (CPD) method. Unlike MMC, both KMC and CPD methods are capable of simulating the dynamics of the cellular system in real time. In the KMC approach a transition rate is associated with possible rearrangements of the cellular system, and the corresponding time evolution is expressed in terms of these rates. In the CPD approach cells are modeled as interacting cellular particles (CPs) and the time evolution of the multicellular system is determined by integrating the equations of motion of all CPs. The KMC and CPD methods are tested and compared by simulating two experimentally well known phenomena: (1) cell-sorting within an aggregate formed by two types of cells with different adhesivities, and (2) fusion of two spherical aggregates of living cells.