Modal Analysis of Cellular Dynamics in the Morphospace in Epithelial-Mesenchymal Transition
Akash Chandra Das, Debanga Raj Neog, Biplab Bose

TL;DR
This study analyzes the continuous morphological dynamics of epithelial-mesenchymal transition (EMT) using modal analysis, revealing key features like reversibility, distinct transition paths, and increased diversity during reversal.
Contribution
It introduces a novel approach to study EMT as a continuous process in morphospace and applies modal analysis to identify dominant dynamical features.
Findings
Detected reversible transition in EMT.
Identified distinct phenotypic transition paths.
Observed increased cellular diversity during EMT reversal.
Abstract
During epithelial-mesenchymal transition (EMT), epithelial cells change their morphology, disperse, and gain mesenchymal-like characteristics. Usually, cells are categorized into discrete cell types or states based on gene expression and other cellular features. Subsequently, EMT is investigated as a dynamical process where cells jump from one discrete state to another. In the current work, we moved away from this idea of discrete state transition and investigated EMT dynamics in a continuous phenotypic space. We used morphology to define the phenotype of a cell. We used the data from quantitative image analysis of MDA-MB-468 cells undergoing EGF-induced EMT. We defined the morphological state space or 'morphospace' using the morphological features extracted through image analysis. During EMT, as the morphology changed, the distribution of cells in the morphospace also changed. However,…
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Taxonomy
TopicsCell Image Analysis Techniques
