Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples

Pekka Ruusuvuori, Lassi Paavolainen, Kalle Rutanen, Anita Maki, Heikki Huttunen, Varpu Marjomaki

    Research output: Contribution to journalArticleScientificpeer-review

    3 Citations (Scopus)

    Abstract

    Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle association between image channels. Results for a large set of synthetic images shows that the novel association method based on point-pattern matching demonstrates robust capability to detect association of closely located vesicles in live cell-microscopy where traditional colocalization methods fail to produce results. In addition, the method outperforms compared Iterated Closest Points registration method. Results for fixed and live experimental data shows the association method to perform comparably to traditional methods in colocalization studies for fixed cells and to perform favorably in association studies for live cells.

    Original languageEnglish
    Article number94245
    Number of pages11
    JournalPLoS ONE
    Volume9
    Issue number4
    DOIs
    Publication statusPublished - 2014
    Publication typeA1 Journal article-refereed

    Keywords

    • IMAGES
    • algorithm
    • colocalization
    • microscopy
    • objects
    • registration
    • tracking

    Publication forum classification

    • Publication forum level 2

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