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High-Resolution Quantification of Focal Adhesion Spatiotemporal Dynamics in Living Cells

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  • Mathew E Berginski
  • Eric A Vitriol
  • Klaus M Hahn
  • Shawn M Gomez

Abstract

Focal adhesions (FAs) are macromolecular complexes that provide a linkage between the cell and its external environment. In a motile cell, focal adhesions change size and position to govern cell migration, through the dynamic processes of assembly and disassembly. To better understand the dynamic regulation of focal adhesions, we have developed an analysis system for the automated detection, tracking, and data extraction of these structures in living cells. This analysis system was used to quantify the dynamics of fluorescently tagged Paxillin and FAK in NIH 3T3 fibroblasts followed via Total Internal Reflection Fluorescence Microscopy (TIRF). High content time series included the size, shape, intensity, and position of every adhesion present in a living cell. These properties were followed over time, revealing adhesion lifetime and turnover rates, and segregation of properties into distinct zones. As a proof-of-concept, we show how a single point mutation in Paxillin at the Jun-kinase phosphorylation site Serine 178 changes FA size, distribution, and rate of assembly. This study provides a detailed, quantitative picture of FA spatiotemporal dynamics as well as a set of tools and methodologies for advancing our understanding of how focal adhesions are dynamically regulated in living cells. A full, open-source software implementation of this pipeline is provided at http://gomezlab.bme.unc.edu/tools.

Suggested Citation

  • Mathew E Berginski & Eric A Vitriol & Klaus M Hahn & Shawn M Gomez, 2011. "High-Resolution Quantification of Focal Adhesion Spatiotemporal Dynamics in Living Cells," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-13, July.
    • Handle: RePEc:plo:pone00:0022025
    DOI: 10.1371/journal.pone.0022025
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    Cited by:

    1. Lisa Laux & Marie F A Cutiongco & Nikolaj Gadegaard & Bjørn Sand Jensen, 2020. "Interactive machine learning for fast and robust cell profiling," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    2. Vincent On & Atena Zahedi & Iryna M Ethell & Bir Bhanu, 2017. "Automated spatio-temporal analysis of dendritic spines and related protein dynamics," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-23, August.
    3. Tim Toplak & Benoit Palmieri & Alba Juanes-García & Miguel Vicente-Manzanares & Martin Grant & Paul W Wiseman, 2017. "Wavelet Imaging on Multiple Scales (WIMS) reveals focal adhesion distributions, dynamics and coupling between actomyosin bundle stability," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-24, October.

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