A “Tagless” Strategy for Identification of Stable Protein Complexes Genome-wide by Multidimensional Orthogonal Chromatographic Separation and iTRAQ Reagent Tracking

Abstract

Tandem affinity purification is the principal method for purifying and identifying stable protein complexes system-wide in whole cells. Although highly effective, this approach is laborious and impractical in organisms where genetic manipulation is not possible. Here, we propose a novel "tagless" strategy that combines multidimensional separation of endogenous complexes with mass spectrometric monitoring of their composition. In this procedure, putative protein complexes are identified based on the comigration of collections of polypeptides through multiple orthogonal separation steps. We present proof-of-principle evidence for the feasibility of key aspects of this strategy. A majority of Escherichia coli proteins are shown to remain in stable complexes during fractionation of a crude extract through three chromatographic steps. We also demonstrate that iTRAQ reagent-based tracking can quantify relative migration of polypeptides through chromatographic separation media. LC MALDI MS and MS/ MS analysis of the iTRAQ-labeled peptides gave reliable relative quantification of 37 components of 13 known E. coli complexes: 95% of known complex components closely co-eluted and 57% were automatically grouped by a prototype computational clustering method. With further technological improvements in each step, we believe this strategy will dramatically improve the efficiency of the purification and identification of protein complexes in cells.

Nucleoid-Enriched Proteomes in Developing Plastids and Chloroplasts from Maize Leaves: A New Conceptual Framework for Nucleoid Functions

“…Conversely, coexpression in many cases implies the presence of functional linkages between genes or proteins, allowing for the identification of new components of processes or protein complexes. Cluster analysis has been used extensively for transcripts (Eisen et al, 1998;Belacel et al, 2006;Long et al, 2008) and more recently for proteomics (Dong et al, 2008;Huang et al, 2009;Pontén et al, 2009;Quintana et al, 2009;Majeran et al, 2010;Olinares et al, 2010). Cluster analysis is based on the notion of unsupervised learning in which data objects within the same cluster are similar to one another and dissimilar to the objects in other clusters.…”

A Proteomic Strategy for Global Analysis of Plant Protein Complexes

“…An alternative approach to protein complex analysis is to capitalize on the parallel protein detection and quantification capability of liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze endogenous protein complexes (Dong et al, 2008;Liu et al, 2008). In plants, the potential benefits of label-free MS protein quantification have been discussed (Thelen and Peck, 2007), and these methods have been used to analyze the size and putative composition of endogenous protein complexes in the chloroplast stroma that were separated by native gel electrophoresis (Peltier et al, 2006) and size exclusion chromatography (SEC) (Olinares et al, 2010).…”

Multi-dimensional Co-separation Analysis Reveals Protein–Protein Interactions Defining Plasma Lipoprotein Subspecies

“…Unfortunately, tandem affinity purification strategies are impractical in humans, and we have found that immunoprecipitation experiments with human plasma lipoproteins result in a high false-positive rate due to the low abundance of most of these proteins, particularly those in HDLs. Therefore, we took an alternative approach called co-separation analysis, a method based on the principle that stable protein complexes can be identified by tracking their co-migration as they undergo biochemical separation by multiple orthogonal approaches (22). Native proteins are analyzed in an unbiased manner without affinity tags or antibodies, and purification to homogeneity is not necessary for the identification of putative protein complexes.…”