Abstract
Information on the composition of protein complexes can accelerate mechanistic analyses of cellular systems. Protein complex composition identifies genes that function together and provides clues about regulation within and between cellular pathways. Cytosolic protein complexes control metabolic flux, signal transduction, protein abundance, and the activities of cytoskeletal and endomembrane systems. It has been estimated that one third of all cytosolic proteins in leaves exist in an oligomeric state, yet the composition of nearly all remain unknown. Subunits of stable protein complexes copurify, and combinations of mass-spectrometry-based protein correlation profiling and bioinformatic analyses have been used to predict protein complex subunits. Because of uncertainty regarding the power or availability of bioinformatic data to inform protein complex predictions across diverse species, it would be highly advantageous to predict composition based on elution profile data alone. Here we describe a mass spectrometry-based protein correlation profiling approach to predict the composition of hundreds of protein complexes based on biochemical data. Extracts were obtained from an intact organ and separated in parallel by size and charge under nondenaturing conditions. More than 1000 proteins with reproducible elution profiles across all replicates were subjected to clustering analyses. The resulting dendrograms were used to predict the composition of known and novel protein complexes, including many that are likely to assemble through self-interaction. An array of validation experiments demonstrated that this new method can drive protein complex discovery, guide hypothesis testing, and enable systems-level analyses of protein complex dynamics in any organism with a sequenced genome.
Highlights
Endogenous protein complex composition was predicted using orthogonal protein separations, protein correlation profiling, and novel data filtering scripts
A Workflow for Protein Correlation Profiling-based Predictions of Protein Complex Composition—The objective of this work was to create a label-free proteomic method to predict the composition of endogenous protein complexes from leaf extracts (Fig. 1)
Each biological replicate was split into two samples: half was separated by SEC to obtain an estimate of the apparent mass of the endogenous protein based on its hydrodynamic radius and the other half was separated by charge using a mixed bed IEX column
Summary
Endogenous protein complex composition was predicted using orthogonal protein separations, protein correlation profiling, and novel data filtering scripts. Information about protein oligomerization is some of the most valuable biological data that can provide insight into the control of metabolic pathways and cellular systems [3,4,5]. Using the plant model Arabidopsis, it is estimated that about one third of the cytosolic proteins exist as a subunit of a stable complex [13]; the composition of the vast majority remains unknown. This is largely because proteinprotein interactions cannot be predicted by genome sequence or expression data alone, and a biochemical experiment is required to detect physical interactions. From the ‡Department of Botany and Plant Pathology, Purdue University, West Lafayette, Indiana; §Department of Statistics, Purdue University, West Lafayette, Indiana; ¶Purdue Proteomics Facility, Bindley Biosciences Center, Discovery Park, Purdue University, West Lafayette, Indiana; ʈDepartment of Biological Sciences, Purdue University, West Lafayette, Indiana
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