A Phase-field Model for Apoptotic Cell Death

TL;DR

This paper introduces a phase-field computational model to simulate apoptosis, capturing cellular morphological changes and dynamics, which can aid in understanding cell death mechanisms and testing therapeutic strategies.

Contribution

The work presents a novel phase-field framework for modeling apoptosis, including deriving the mechanics and simulating various cellular morphological transitions.

Findings

Simulated cell shrinkage, blebbing, cavity formation, and fragmentation.

Model reproduces morphological features observed in electron microscopy.

Provides a basis for computational testing of apoptosis-related therapies.

Abstract

The process of programmed cell death, namely apoptosis, is a natural mechanism that regulates healthy tissue, multicellular structures, and homeostasis. An improved understanding of apoptosis can significantly enhance our knowledge of biological processes and systems. For instance, pathogens can manipulate the apoptotic process to either evade immune detection or to facilitate their spread. Furthermore, of particular clinical interest is the ability of cancer cells to evade apoptosis, hence allowing them to survive and proliferate uncontrollably. Thus, in this work, we propose a phase-field framework for simulating intrinsic or extrinsic apoptosis induced by an activation field, including deriving the configurational mechanics underlying such phenomena. Along with exploring varying conditions needed to initiate or reduce apoptosis, this can serve as a starting point for computational therapeutic testing. To showcase model capabilities, we present simulations exhibiting different types of cellular dynamics produced when varying the mechanisms underlying apoptosis. The model is subsequently applied to probe different morphological transitions, such as cell shrinkage, membrane blebbing, cavity formation and fragmentation. Lastly, we compare the characteristics observed in our simulations to electron microscopy images, providing additional support for the model.