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Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis.

ABSTRACT: Measuring protein interactions is key to understanding cell signaling mechanisms, but quantitative analysis of these interactions in situ has remained a major challenge. Here, we present spatial intensity distribution analysis (SpIDA), an analysis technique for image data obtained using standard fluorescence microscopy. SpIDA directly measures fluorescent macromolecule densities and oligomerization states sampled within single images. The method is based on fitting intensity histograms calculated from images to obtain density maps of fluorescent molecules and their quantal brightness. Because spatial distributions are acquired by imaging, SpIDA can be applied to the analysis of images of chemically fixed tissue as well as live cells. However, the technique does not rely on spatial correlations, freeing it from biases caused by subcellular compartmentalization and heterogeneity within tissue samples. Analysis of computer-based simulations and immunocytochemically stained GABA(B) receptors in spinal cord samples shows that the approach yields accurate measurements over a broader range of densities than established procedures. SpIDA is applicable to sampling within small areas (6 ?m(2)) and reveals the presence of monomers and dimers with single-dye labeling. Finally, using GFP-tagged receptor subunits, we show that SpIDA can resolve dynamic changes in receptor oligomerization in live cells. The advantages and greater versatility of SpIDA over current techniques open the door to quantificative studies of protein interactions in native tissue using standard fluorescence microscopy.

SUBMITTER: Godin AG

PROVIDER: S-EPMC3084122 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis.

Godin Antoine G AG Costantino Santiago S Lorenzo Louis-Etienne LE Swift Jody L JL Sergeev Mikhail M Ribeiro-da-Silva Alfredo A De Koninck Yves Y Wiseman Paul W PW

Proceedings of the National Academy of Sciences of the United States of America 20110411 17

Measuring protein interactions is key to understanding cell signaling mechanisms, but quantitative analysis of these interactions in situ has remained a major challenge. Here, we present spatial intensity distribution analysis (SpIDA), an analysis technique for image data obtained using standard fluorescence microscopy. SpIDA directly measures fluorescent macromolecule densities and oligomerization states sampled within single images. The method is based on fitting intensity histograms calculate ...[more]

PMID: 21482753

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Project description:Knowledge of membrane receptor organization is essential for understanding the initial steps in cell signaling and trafficking mechanisms, but quantitative analysis of receptor interactions at the single-cell level and in different cellular compartments has remained highly challenging. To achieve this, we apply a quantitative image analysis technique-spatial intensity distribution analysis (SpIDA)-that can measure fluorescent particle concentrations and oligomerization states within different subcellular compartments in live cells. An important technical challenge faced by fluorescence microscopy-based measurement of oligomerization is the fidelity of receptor labeling. In practice, imperfect labeling biases the distribution of oligomeric states measured within an aggregated system. We extend SpIDA to enable analysis of high-order oligomers from fluorescence microscopy images, by including a probability weighted correction algorithm for nonemitting labels. We demonstrated that this fraction of nonemitting probes could be estimated in single cells using SpIDA measurements on model systems with known oligomerization state. Previously, this artifact was measured using single-step photobleaching. This approach was validated using computer-simulated data and the imperfect labeling was quantified in cells with ion channels of known oligomer subunit count. It was then applied to quantify the oligomerization states in different cell compartments of the proteolipid protein (PLP) expressed in COS-7 cells. Expression of a mutant PLP linked to impaired trafficking resulted in the detection of PLP tetramers that persist in the endoplasmic reticulum, while no difference was measured at the membrane between the distributions of wild-type and mutated PLPs. Our results demonstrate that SpIDA allows measurement of protein oligomerization in different compartments of intact cells, even when fractional mislabeling occurs as well as photobleaching during the imaging process, and reveals insights into the mechanism underlying impaired trafficking of PLP.

Dataset Information

Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis.

Publications

Revealing protein oligomerization and densities in situ using spatial intensity distribution analysis.

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