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Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis.


ABSTRACT: Photoactivated localization microscopy (PALM) is a powerful approach for investigating protein organization, yet tools for quantitative, spatial analysis of PALM datasets are largely missing. Combining pair-correlation analysis with PALM (PC-PALM), we provide a method to analyze complex patterns of protein organization across the plasma membrane without determination of absolute protein numbers. The approach uses an algorithm to distinguish a single protein with multiple appearances from clusters of proteins. This enables quantification of different parameters of spatial organization, including the presence of protein clusters, their size, density and abundance in the plasma membrane. Using this method, we demonstrate distinct nanoscale organization of plasma-membrane proteins with different membrane anchoring and lipid partitioning characteristics in COS-7 cells, and show dramatic changes in glycosylphosphatidylinositol (GPI)-anchored protein arrangement under varying perturbations. PC-PALM is thus an effective tool with broad applicability for analysis of protein heterogeneity and function, adaptable to other single-molecule strategies.

SUBMITTER: Sengupta P 

PROVIDER: S-EPMC3400087 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature

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Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis.

Sengupta Prabuddha P   Jovanovic-Talisman Tijana T   Skoko Dunja D   Renz Malte M   Veatch Sarah L SL   Lippincott-Schwartz Jennifer J  

Nature methods 20110918 11


Photoactivated localization microscopy (PALM) is a powerful approach for investigating protein organization, yet tools for quantitative, spatial analysis of PALM datasets are largely missing. Combining pair-correlation analysis with PALM (PC-PALM), we provide a method to analyze complex patterns of protein organization across the plasma membrane without determination of absolute protein numbers. The approach uses an algorithm to distinguish a single protein with multiple appearances from cluster  ...[more]

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