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Resolving multi-molecular protein interactions by photoactivated localization microscopy.

ABSTRACT: Multi-molecular protein complexes are critical to many cellular functions, including signaling, DNA transcription and enzymatic reactions. In spite of their importance, current research techniques such as biochemistry and diffraction-limited microscopy cannot resolve the heterogeneity and nanoscale organization of protein complexes in intact cells. Here we describe a technique that enables the study of multi-molecular protein complexes at the single molecule level in intact cells. The technique uses photoactivated localization microscopy (PALM) to resolve individual proteins with a resolution down to 20nm in intact cells, and second-order statistics to study the spatial interactions of the proteins. We demonstrate the feasibility of this technique by studying signaling complexes that form in activated T cells. We first use single color PALM imaging and univariate second-order statistics to resolve the clustering of Linker for Activation of T cells (LAT) at the plasma membrane (PM) of the cells. We then use two color PALM and bivariate second-order statistics to resolve the interaction of LAT with key interacting proteins. We discuss potential caveats in studying molecular clustering and the robustness of the technique to study bimolecular interactions. Our proposed technique, combined with older techniques, could help shed new light on the nature of multimolecular protein complexes and their significance to cell function.

SUBMITTER: Sherman E

PROVIDER: S-EPMC3608816 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Resolving multi-molecular protein interactions by photoactivated localization microscopy.

Sherman Eilon E Barr Valarie A VA Samelson Lawrence E LE

Methods (San Diego, Calif.) 20121222 3

Multi-molecular protein complexes are critical to many cellular functions, including signaling, DNA transcription and enzymatic reactions. In spite of their importance, current research techniques such as biochemistry and diffraction-limited microscopy cannot resolve the heterogeneity and nanoscale organization of protein complexes in intact cells. Here we describe a technique that enables the study of multi-molecular protein complexes at the single molecule level in intact cells. The technique ...[more]

PMID: 23266704

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Project description:Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (t(Thresh) and d(Thresh)) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems.

Dataset Information

Resolving multi-molecular protein interactions by photoactivated localization microscopy.

Publications

Resolving multi-molecular protein interactions by photoactivated localization microscopy.

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