Publication | Open Access
Novel approach to measure the size of plasma‐membrane nanodomains in single molecule localization microscopy
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Citations
19
References
2015
Year
Proteinlipid InteractionMicroscopyNovel ApproachMolecular BiologyAnalytical UltracentrifugationLipid MovementElliptical ShapesSingle Molecule BiophysicsMicroscopy MethodPlasma‐membrane NanodomainsBioimagingSingle MoleculeLight MicroscopyMolecular ImagingBiophysicsApparent Domain SizeMembrane BiologyGpi‐anchor ProteinMembrane SystemCell BiologyBiomolecular ScienceSingle-molecule DetectionBiomedical DiagnosticsNatural SciencesCellular BiochemistryMedicineCell Detection
Abstract Many membrane proteins are not evenly distributed over the plasma membrane, but gathered in domains assumed to have a particular lipid composition. Using single molecule localization microscopy (SMLM) we have immunolocalized a glycosylphosphatidylinositol (GPI)‐anchor protein that labels nanodomains in a specialized plant cell type, and compared the suitability of three methods to estimate their size. As conventional methods full width at half maximum (FWHM) and the full diameter (FWMin) of domains were used. A boundary detection method of the domain area (DA) was performed in order to take irregular shapes into account. In order to compare the influence of the chosen measurement methods, we have developed a MatLab program that allows for automated analysis of domain sizes from multiple SMLM images and provides the statistics of three key features of domains: FWHM and FWMin along their long and short axes as well as the DA, derived from the molecular density. Domains formed by the GPI‐anchor protein are approximating elliptical shapes. Direct and indirect immunolabeling resulted in a statistically significant difference in apparent domain size, reflecting the fact that the secondary antibody molecules extend the uncertainty along the nanodomain border. FWMin values along the long and short axis give good estimates of regular, geometrically centred domain shapes, while the DA value matches regular as well as irregular shapes best, as derived from computer‐generated, irregular point clusters. © 2015 International Society for Advancement of Cytometry
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