An integrated workflow for charting the human interaction proteome: insights into the PP2A system

Timo Glatter^1,2,a, Alexander Wepf^1,2,a, Ruedi Aebersold^1,2,3,4 & Matthias Gstaiger^1,2

^aThese authors contributed equally to this work

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Synopsis

The majority of proteins function in the context of larger protein complexes. Affinity purification coupled with mass spectrometry (AP-MS) became the method of choice for systematic and direct experimental analysis of protein complexes under near-physiological conditions. Although a lot of progress has been made on the systematic AP-MS analysis of the yeast compendium of protein complexes (Gavin et al, 2006; Krogan et al, 2006), relatively little advance has been reported on the corresponding organization of the human interaction proteome. Despite recent improvements in mass spectrometry instrumentation, the size of the human proteome and the number of 225 000 estimated protein interactions (Hart et al, 2006) challenge existing experimental AP-MS workflows with respect to throughput, sensitivity and data robustness. In this study, we have developed and evaluated an integrated experimental workflow to facilitate system-wide analysis of human protein complexes. We benchmarked the overall performance of the presented workflow using the human PP2A phosphatase system and show how it can be used to increase data robustness and throughput in future AP-MS studies on the human interaction proteome.

The presented workflow builds on the increasing availability of gateway-compatible orfeome resources and FRT-mediated recombination for high-throughput generation of isogenic bait-expressing cell lines within 2 weeks. Expression in these cell lines can be controlled by a tetracycline-inducible promoter to maintain homogenous expression at close to physiological levels throughout the cell population. We have replaced the widely used classical 21 kDa TAP tag by a novel small double-affinity tag to increase sample processing speed and enhance purification yields up to 40%. Samples purified by this procedure can be analysed readily by a direct liquid chromatography tandem mass spectrometry (LC-MS/MS) approach without the need for further SDS–PAGE fractionation commonly used in previous workflows. Direct LC-MS/MS analysis reduces the number of experimental steps and contributes to the obtained overall reproducibility of the approach, which we benchmarked for the human PP2A phosphatase system.

The evolutionary conserved serine/threonine phosphatase PP2A has been linked to a wide range of cellular processes including transcription, apoptosis, cell growth and cellular transformation (Virshup, 2000; Janssens et al, 2005; Westermarck and Hahn, 2008). The human genome encodes two catalytic subunits (PPP2CA, PPP2CB), two scaffolding subunits (PPP2R1A, PPP2R1B) and at least 15 known regulatory B subunits, which, by combinatorial assembly, can potentially form a multitude of different trimeric PP2A complexes (Janssens and Goris, 2001; Lechward et al, 2001). It is believed that the versatile nature of this combinatorial subunit arrangement provides substrate specificity as well as temporal and spatial control of phosphatase activity. So far no systematic study has yet been performed to characterize the set of PP2A complexes that coexist in human cells and to understand how these complexes are connected to specific cellular processes at the level of protein–protein interactions. We have analysed 11 bait proteins selected from the human protein phosphatase 2A (PP2A) system and identified 197 protein interaction with a reproducibility rate of 85% between two biological replicate experiments (Figure 4A). This is among the highest rates reported so far for systematic AP-MS/MS workflows. For further validation, we compared the data to information from the literature and public databases. About two-thirds of the 197 interactions either have been reported previously in the literature or were related to interactions known between human paralogous or yeast orthologous proteins. On the basis of interaction information alone, it is difficult to infer the presence and composition of protein complexes. However, in the case of human PP2A, significant amount of published structural and biochemical data provide valuable information on the composition of several distinct groups of phosphatase complexes (Lechward et al, 2001; Chao et al, 2006; Leulliot et al, 2006; Xu et al, 2006; Xing et al, 2008). We used this information to assign the 150 paralogous interactions identified in our network to five groups of known phosphatase complexes, here referred to as modules (Figure 6). These include the group of trimeric PP2A complexes described above, which represent the majority of PP2A complexes we found, as well as PP2A complexes containing the proteins IGBP1/TAP42 or the protein phosphatase methylesterase (PPME1) in addition to PPP4C containing phosphatase complexes. We estimate that, overall, more than 30 distinct phosphatase complexes coexist in human embryonic kidney cells. On the basis of their interactions with other cellular proteins, these complexes may have specific functions in transcription, cell signalling, DNA damage control and the regulation of mitosis. The presented results thus confirmed and significantly extended our knowledge on combinatorial complex assembly as a molecular principle for the functional diversification within the human PP2A phosphatase system.

Figure 4

Data processing and reproducibility of the overall workflow for a human PP2A protein interaction network. (A) HEK293 cell lines expressing 11 different bait proteins linked previously to the human PP2A network were generated as described in Figure 1. Inducible expression was tested by western blotting (upper panel). Eleven cell lines were used for two independent SH-double affinity purification experiments directly followed by LC-MS/MS (SH-LC-MS/MS). Obtained mass spectra were analysed with XTandem followed by statistical validation of the search results using PeptideProphet and ProteinProphet. Only proteins with minimum ProteinProphet probabilities of 0.9 were considered. Primary interaction data were filtered against a contaminant database resulting in a final list of 242 (replicate A) and 218 (replicate B) bait–prey interactions with an overlap of 85%. To assess the reproducibility rate, the sum of common interactions found in experiments A and B were divided by the total number of interactions identified. (B) Generation of a database containing co-purifying contaminant proteins used for data filtering. Eight independent control purifications were performed using SH-tagged eGFP as a bait protein. Tryptic peptides were analysed twice by LC-MS/MS and identified proteins from all 16 measurements were consecutively added to a contaminant database. A total of 109 proteins were identified and used to subtract unspecific protein contaminants. (C) Robustness of protein interaction data obtained by the integrated workflow. The number of protein interactions (black line) and the percent overlap (red line) across the two replicate data sets shown as a function of increased filtering stringency (number of unique peptides required for protein identification).

Full figure and legend (266K)Figures & Tables index

Figure 6

Protein–protein interactions and different classes of protein complexes within the human PP2A interaction network. Protein–protein interaction data identified in two out of two replicate experiments were vizualized using Cytoscape v.2.5.1. Bait proteins are represented as triangles, and prey proteins are represented as rounded squares. Nodes were classified according to the legend. Edge colour indicates known interactions (orange) or newly identified interactions (blue). Thickness of the edges reflects the number of identified unique peptides. Five classes of PP2A protein complexes could be distinguished on the basis of network topology and literature information and are displayed by dotted lines and colour shading (see legend).

Full figure and legend (630K)Figures & Tables index

When we compared our interaction data with interaction data available for the corresponding yeast orthologous proteins, we found that the interactions particularly within the modules mentioned above are highly conserved. Furthermore, the comparison suggested that functional diversification within the human phosphatase system primarily involved an expansion of regulatory phosphatase subunits and their protein interactions, as the number of PP2A catalytic subunits are the same between humans and yeast.

Large-scale AP-MS represents the method of choice to retrieve high-quality information on the global organization of the human proteome into protein complexes, which in most cases represent the actual functional units of biochemical systems. A comprehensive representation of the human interaction proteome will require a collective effort by the research community using improved analytical workflows with increased throughput, sensitivity and reliability. We believe that the advances collectively achieved by the integrated workflow presented here mark a significant step forward towards these goals.

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