Bridging from single to collective cell migration: A review of models and links to experiments

Abstract

Mathematical and computational models can assist in gaining an understanding of cell behavior at many levels of organization. Here, we review models in the literature that focus on eukaryotic cell motility at 3 size scales: intracellular signaling that regulates cell shape and movement, single cell motility, and collective cell behavior from a few cells to tissues. We survey recent literature to summarize distinct computational methods (phase-field, polygonal, Cellular Potts, and spherical cells). We discuss models that bridge between levels of organization, and describe levels of detail, both biochemical and geometric, included in the models. We also highlight links between models and experiments. We find that models that span the 3 levels are still in the minority.

The epithelial-mesenchymal transition and the cytoskeleton in bioengineered systems

“…An interesting possibility is the use of machine learning and convolutional neural networks to profile distinct patterns of cytoskeletal organization that correlate with enhanced invasion and EMT [168], both in these bioengineered models as well as for intravital imaging and patient histology. Moreover, computational modeling can approximate single cells as discrete "agents" with some representation of intracellular signaling networks, along with cell and matrix mechanics (see recent reviews in [169,170]). These agents can further interact with a surrounding microenvironment that models hypoxia, chemotactic gradients, etc.…”

Artistoo, a library to build, share, and explore simulations of cells and tissues in the web browser

“…For example, criticisms have included their lack of scalability, as well as difficulties in linking CPM parameters to measurable, real-world quantities. We note that ongoing developments in the field are addressing some of these concerns; for details on CPM strengths and limitations (and efforts to overcome these), we refer the reader elsewhere (Tapia and D'Souza, 2011;Liedekerke et al, 2015;Magno et al, 2015;Rens and Edelstein-Keshet, 2019;Buttenschön and Edelstein-Keshet, 2020 sharing of CPM simulations with students, collaborators, and readers or reviewers of a paper. Unlike existing frameworks, Artistoo allows building simulations that run in the web browser without the need to install any software: Artistoo models run on any platform providing a standards-compliant web browser -be it a desktop computer, a tablet, or a mobile phone.…”

“…For example, criticisms have included their lack of scalability, as well as difficulties in linking CPM parameters to measurable, real-world quantities. We note that ongoing developments in the field are addressing some of these concerns; for details on CPM strengths and limitations (and efforts to overcome these), we refer the reader elsewhere ( Tapia and D'Souza, 2011 ; Van Liedekerke et al, 2015 ; Magno et al, 2015 ; Rens and Edelstein-Keshet, 2019 ; Buttenschön and Edelstein-Keshet, 2020 ).…”

PalaCell2D: A framework for detailed tissue morphogenesis

“…Despite recent advances in developmental biology (molecular biology, live-imaging and ex vivo methodologies [St Johnston, 2015]), we are mainly able to explain key mechanisms of morphogenesis in an isolated manner. In addition, obtaining quantitative results in a reproducible manner remains a tedious task, hence, the growing interest in computational methods [Fletcher et al, 2014; Van Liedekerke et al, 2015; Tanaka, 2016; Sharpe, 2017; Merzouki, 2018; Buttenschoön and Edelstein-Keshet, 2020]. These methods obviously rely on empirical observations and ad-hoc parameters in order to compensate for our reduced understanding of active and mechanical properties of living cells.…”