Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane
Author(s) -
Laura Paparelli,
Nikky Corthout,
Benjamin Pavie,
Devin L. Wakefield,
Ragna Sannerud,
Tijana JovanovićTalisman,
Wim Annaert,
Sebastian Munck
Publication year - 2016
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1005095
Subject(s) - microscopy , endocytosis , biological system , cell membrane , lipid raft , biophysics , chemistry , membrane , biology , cell , microbiology and biotechnology , optics , physics , signal transduction , biochemistry
Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Qu antitative A nalysis of the S patial distributions in I mages using Mo saic segmentation and D ual parameter O ptimization in H istograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided.
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