Dataset Information

Label-Free Automated Cell Tracking: Analysis of the Role of E-cadherin Expression in Collective Electrotaxis.

ABSTRACT: Collective cell migration plays an important role in wound healing, organogenesis, and the progression of metastatic disease. Analysis of collective migration typically involves laborious and time-consuming manual tracking of individual cells within cell clusters over several dozen or hundreds of frames. Herein, we develop a label-free, automated algorithm to identify and track individual epithelial cells within a free-moving cluster. We use this algorithm to analyze the effects of partial E-cadherin knockdown on collective migration of MCF-10A breast epithelial cells directed by an electric field. Our data show that E-cadherin knockdown in free-moving cell clusters diminishes electrotactic potential, with empty vector MCF-10A cells showing 16% higher directedness than cells with E-cadherin knockdown. Decreased electrotaxis is also observed in isolated cells at intermediate electric fields, suggesting an adhesion-independent role of E-cadherin in regulating electrotaxis. In additional support of an adhesion-independent role of E-cadherin, isolated cells with reduced E-cadherin expression reoriented within an applied electric field 60% more quickly than control. These results have implications for the role of E-cadherin expression in electrotaxis and demonstrate proof-of-concept of an automated algorithm that is broadly applicable to the analysis of collective migration in a wide range of physiological and pathophysiological contexts.

SUBMITTER: Lalli ML

PROVIDER: S-EPMC6816619 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Label-Free Automated Cell Tracking: Analysis of the Role of E-cadherin Expression in Collective Electrotaxis.

Lalli Mark L ML Wojeski Brooke B Asthagiri Anand R AR

Cellular and molecular bioengineering 20161021 1

Collective cell migration plays an important role in wound healing, organogenesis, and the progression of metastatic disease. Analysis of collective migration typically involves laborious and time-consuming manual tracking of individual cells within cell clusters over several dozen or hundreds of frames. Herein, we develop a label-free, automated algorithm to identify and track individual epithelial cells within a free-moving cluster. We use this algorithm to analyze the effects of partial E-cad ...[more]

PMID: 31719851

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Project description:By modifying and calibrating an active vertex model to experiments, we have simulated numerically a confluent cellular monolayer spreading on an empty space and the collision of two monolayers of different cells in an antagonistic migration assay. Cells are subject to inertial forces and to active forces that try to align their velocities with those of neighboring ones. In agreement with experiments in the literature, the spreading test exhibits formation of fingers in the moving interfaces, there appear swirls in the velocity field, and the polar order parameter and the correlation and swirl lengths increase with time. Numerical simulations show that cells inside the tissue have smaller area than those at the interface, which has been observed in recent experiments. In the antagonistic migration assay, a population of fluidlike Ras cells invades a population of wild type solidlike cells having shape parameters above and below the geometric critical value, respectively. Cell mixing or segregation depends on the junction tensions between different cells. We reproduce the experimentally observed antagonistic migration assays by assuming that a fraction of cells favor mixing, the others segregation, and that these cells are randomly distributed in space. To characterize and compare the structure of interfaces between cell types or of interfaces of spreading cellular monolayers in an automatic manner, we apply topological data analysis to experimental data and to results of our numerical simulations. We use time series of data generated by numerical simulations to automatically group, track and classify the advancing interfaces of cellular aggregates by means of bottleneck or Wasserstein distances of persistent homologies. These techniques of topological data analysis are scalable and could be used in studies involving large amounts of data. Besides applications to wound healing and metastatic cancer, these studies are relevant for tissue engineering, biological effects of materials, tissue and organ regeneration.

Dataset Information

Label-Free Automated Cell Tracking: Analysis of the Role of E-cadherin Expression in Collective Electrotaxis.

Publications

Label-Free Automated Cell Tracking: Analysis of the Role of E-cadherin Expression in Collective Electrotaxis.

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