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

Florian Levet,Aleš Benda,Tomáš Brdička,Marek Cebecauer,Sebastian Letschert,Tomáš Lukeš,Markus Sauer,Daniela Glatzová,Zuzana Kvíčalová,Theo Lasser

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.

Highlights

Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed superresolution imaging techniques
For quantifying the protein distribution in the plasma membrane of T cells, we acquired image sequences with a total internal reflection fluorescence (TIRF) microscope equipped with an EMCCD camera to detect the fluorescence originating from individual fluorescent emitters
The method shows an unbiased performance over a broad spectrum of non-ideal experimental conditions, which are common in single-molecule localization microscopy and microscopy in general

Summary

Introduction

Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed superresolution 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. The efficiency of currently available tools for cluster analysis is limited in high-density regions by the ability to identify and localize individual molecules in raw images, as well as the blinking properties of the emitters[7, 8]. This has motivated us to develop a robust method for investigation of molecular organization of cell membranes that tolerates diverse experimental conditions. ICS intends to measure fast molecular processes such as diffusion or number of molecules, but does not provide super-resolution

Methods

Results

Conclusion