Sub-cellular feature detection and automated extraction of collocalized actin and myosin regions

  • Authors:

  • Justin Martineau;Ronil Mokashi;David Chapman;Michael Grasso;Mary Brady;Yelena Yesha;Yaacov Yesha;Antonio Cardone;Alden Dima

  • Affiliations:

  • UMBC, Baltimore, MD, USA;UMBC, Baltimore, MD, USA;UMBC, Baltimore, MD, USA;University of Maryland School of Medicine, Baltimore, MD, USA;National Institute of Standards and Technology, Gaithersburg, MD, USA;UMBC, Baltimore, MD, USA;UMBC, Baltimore, MD, USA;University of Maryland Institute for Advanced Computer Studies, College Park, MD, USA;National Institute of Standards and Technology, Gaithersburg, MD, USA

  • Venue:
  • Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
  • Year:
  • 2012

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Abstract

We describe a new distance-based metric to measure the strength of collocalization in multi-color microscopy images for user-selected regions. This metric helps to standardize, objectify, quantify, and even automate light microscopy observations. Our new algorithm uses this metric to automatically identify and annotate a donut shaped actomyosin stress fiber bundle evident in vascular smooth muscle cells on certain types of surfaces. Both the metric and the algorithm have been implemented as an open source plugin for the popular ImageJ toolkit. They are available for download at http://code.google.com/p/actin-myosin-plugin/. Using cells stained for the cytoskeletal proteins actin and myosin, we show how characteristics of the identified stress fiber bundle are indicative of the kind of surface the cell is placed upon, and prove that weak spots in this structure are correlated with local membrane extensions. Given the relationship between membrane extension, cell migration, vascular disease, embryonic development, and cancer metastasis we provide that these tools to enable biological research that could improve our quality of life.