Related Experiment Video
Updated: Mar 13, 2026

10:37
Induction and Analysis of Epithelial to Mesenchymal Transition
Published on: August 27, 2013
36.7K
Morphological single cell profiling of the epithelial-mesenchymal transition
Susan E Leggett1, Jea Yun Sim2, Jonathan E Rubins2
1Center for Biomedical Engineering, School of Engineering, Providence, RI 02912, USA and Pathobiology Graduate Program Brown University, Providence, RI 02912, USA. ian_wong@brown.edu.
Integrative Biology : Quantitative Biosciences From Nano to Macro
|October 11, 2016
Summary
Single cell analysis using high content imaging reveals distinct phenotypes during the epithelial-mesenchymal transition (EMT). This morphological classification method accurately identifies cell states, aiding in therapeutic assessment.
Area of Science:
- Cell Biology
- Biomedical Imaging
- Quantitative Biology
Background:
- Cellular heterogeneity complicates experimental analysis, especially during stress-induced transformations like the epithelial-mesenchymal transition (EMT).
- Traditional population-based measurements fail to capture single-cell plasticity and diverse responses.
- The epithelial-mesenchymal transition (EMT) confers resistance and an elongated phenotype, crucial in development and disease.
Purpose of the Study:
- To develop and validate a single-cell morphology-based method for classifying phenotypic subpopulations.
- To quantify morphological changes associated with EMT induced by various stimuli.
- To assess the potential of this approach as a predictive preclinical assay.
Main Methods:
- High content imaging of single cells to capture detailed morphology.
- Characterization of EMT using the Snail regulator in mammary epithelial cells.
- Development of a Gaussian mixture model integrating morphological features (vimentin area, nucleus, and cytoplasm elongation).
- Application of the model to heterogeneous cell populations induced by TGF-β1, cell density, and Taxol.
Main Results:
- EMT induction led to increased vimentin area and significant elongation of nucleus and cytoplasm.
- The Gaussian mixture model accurately classified epithelial and mesenchymal phenotypes (>92% accuracy).
- The method successfully analyzed heterogeneous cell populations under diverse EMT-inducing conditions.
Conclusions:
- Single-cell morphological analysis provides a powerful tool to resolve cellular heterogeneity during EMT.
- This quantitative approach offers a promising predictive assay for evaluating targeted therapeutics in preclinical settings.
- The method's ability to screen diverse phenotypic variability enhances its utility in complex biological systems.

