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Mol Cell Proteomics. 2017 Nov;16(11):1972-1989. doi: 10.1074/mcp.RA117.000276. Epub 2017 Sep 8.

Global Analysis of Membrane-associated Protein Oligomerization Using Protein Correlation Profiling.

Author information

1
‡Department of Biological Sciences, Purdue University, West Lafayette, Indiana.
2
§Department of Statistics, Purdue University, West Lafayette, Indiana.
3
¶College of Osteopathic Medicine, Marian University, Indianapolis.
4
‡Department of Biological Sciences, Purdue University, West Lafayette, Indiana; dszyman@purdue.edu.
5
‖Department of Botany and Plant Pathology, Purdue University, West Lafayette, Indiana.

Abstract

Membrane-associated proteins are required for essential processes like transport, organelle biogenesis, and signaling. Many are expected to function as part of an oligomeric protein complex. However, membrane-associated proteins are challenging to work with, and large-scale data sets on the oligomerization state of this important class of proteins is missing. Here we combined cell fractionation of Arabidopsis leaves with nondenaturing detergent solubilization and LC/MS-based profiling of size exclusion chromatography fractions to measure the apparent masses of >1350 membrane-associated proteins. Our method identified proteins from all of the major organelles, with more than 50% of them predicted to be part of a stable complex. The plasma membrane was the most highly enriched in large protein complexes compared with other organelles. Hundreds of novel protein complexes were identified. Over 150 proteins had a complicated localization pattern, and were clearly partitioned between cytosolic and membrane-associated pools. A subset of these dual localized proteins had oligomerization states that differed based on localization. Our data set is an important resource for the community that includes new functionally relevant data for membrane-localized protein complexes that could not be predicted based on sequence alone. Our method enables the analysis of protein complex localization and dynamics, and is a first step in the development of a method in which LC/MS profile data can be used to predict the composition of membrane-associated protein complexes.

PMID:
28887381
PMCID:
PMC5672003
DOI:
10.1074/mcp.RA117.000276
[Indexed for MEDLINE]
Free PMC Article

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