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Updated: Mar 31, 2026
Imaging Molecular Adhesion in Cell Rolling by Adhesion Footprint Assay
Published on: September 27, 2021
Software for semi-automatic analysis of microscopic images of adhesion structures and protein colocalization in cells
Joanna Hajduk1, Patrycja Twardawa1, Zenon Rajfur2
1Doctoral School of Exact and Natural Sciences, Jagiellonian University, Łojasiewicza 11, Cracow 30-348, Poland; Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Łojasiewicza 11, Cracow 30-348, Poland.
Background And Objective:
Adhesion structures, such as focal and fibrillar adhesions, are protein complexes that mediate cell attachment to extracellular matrix via integrins. These structures participate in the mechanosensing process, transmitting forces from the cellular microenvironment to the cytoskeleton. The interaction between cells and their environment, along with the role of focal adhesion proteins, are areas of significant research interest. Accurate, quantitative analysis of adhesions structures in microscopic images is essential for advancing our understanding of the subject. However, the high variability and complexity of those structures in cells makes image analysis challenging, both in terms of subjectivity and time consumption.
Methods:
We present a novel semi-automatic script for the detection of adhesion structures and analysis of their parameters, developed in MATLAB 2021a, to address the challenge of accurate image analysis of focal and fibrillar adhesions in cells.
Results:
Our script offers a more time-efficient and less subjective alternative to manual analysis, while still allowing the user to retain control over the analytical process. It detects adhesion structures in confocal images and measures key parameters such as shape, orientation, and spatial distribution within cells, additionally providing visual label maps of the identified adhesion structures. The second add-on enables the calculation of correlation coefficients between two confocal microscopy image channels representing different stained cellular structures within the same cell, and generates visual colocalization maps, further enhancing the analysis of cellular architecture.
Conclusion:
The presented open-source script offers a robust solution for the comprehensive, quantitative analysis of adhesion structures in microscopic images, based on user-defined analysis parameters. It is available online at https://github.com/patrycja-twardawa/FA-Colocalization.git.
