Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging

Nat Commun. 2017 Nov 23;8(1):1731. doi: 10.1038/s41467-017-01857-x.

Abstract

Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Algorithms
  • CD4 Antigens / genetics
  • CD4 Antigens / metabolism
  • Cell Membrane / metabolism*
  • Cluster Analysis
  • Fluorescent Dyes
  • Humans
  • Jurkat Cells
  • Membrane Proteins / genetics
  • Membrane Proteins / metabolism*
  • Microscopy, Fluorescence / methods
  • Microscopy, Fluorescence / statistics & numerical data
  • Mutant Proteins / genetics
  • Mutant Proteins / metabolism
  • Optical Imaging / methods*
  • Optical Imaging / statistics & numerical data
  • T-Lymphocytes / immunology
  • T-Lymphocytes / metabolism

Substances

  • CD4 Antigens
  • Fluorescent Dyes
  • Membrane Proteins
  • Mutant Proteins