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A High-throughput Cell Microarray Platform for Correlative Analysis of Cell Differentiation and Traction Forces
Published on: March 1, 2017
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STRAINS: A big data method for classifying cellular response to stimuli at the tissue scale.
Jingyang Zheng1, Thomas Wyse Jackson1, Lisa A Fortier2
1Department of Physics, Cornell University, Ithaca, NY, United States of America.
Plos One
|December 8, 2022
Summary
Researchers developed a new tool, SpatioTemporal Response Analysis IN Situ (STRAINS), to track cellular behaviors in tissues. This method revealed distinct spatial patterns in chondrocyte responses to mechanical injury, offering insights into osteoarthritis initiation.
Area of Science:
- Biomedical Engineering
- Cell Biology
- Tissue Engineering
Background:
- Cellular responses to stimuli are crucial for tissue development, health, and disease.
- Understanding how cells coordinate responses requires simultaneous spatiotemporal tracking of their behaviors.
Purpose of the Study:
- To introduce a novel tool, SpatioTemporal Response Analysis IN Situ (STRAINS), for measuring cellular behavioral distributions.
- To analyze the mechanotransduction response of chondrocytes in cartilage following mechanical injury.
Main Methods:
- Utilized fluorescent micrographs and advanced cell tracking.
- Employed machine learning algorithms within the STRAINS tool.
- Analyzed over 20 million data points from 5000 chondrocytes in cartilage.
Main Results:
- Chondrocytes exhibited a spectrum of mechanobiological responses.
- Distinct biochemical pathways were activated in response to mechanical stimuli.
- Spatial patterns in cellular responses correlated with induced local strains.
Conclusions:
- The STRAINS tool provides a powerful approach for analyzing cellular responses in tissues.
- The study elucidates the complex spatial patterns of chondrocyte mechanotransduction after injury.
- Findings offer insights into the early stages of osteoarthritis development.
