Quantitative GTPase Affinity Purification Identifies Rho Family Protein Interaction Partners

Abstract

Although Rho GTPases are essential molecular switches involved in many cellular processes, an unbiased experimental comparison of their interaction partners was not yet performed. Here, we develop quantitative GTPase affinity purification (qGAP) to systematically identify interaction partners of six Rho GTPases (Cdc42, Rac1, RhoA, RhoB, RhoC, and RhoD), depending on their nucleotide loading state. The method works with cell line or tissue-derived protein lysates in combination with SILAC-based or label-free quantification, respectively. We demonstrate that qGAP identifies known and novel binding partners that can be validated in an independent assay. Our interaction network for six Rho GTPases contains many novel binding partners, reveals highly promiscuous interaction of several effectors, and mirrors evolutionary relationships among Rho GTPases.

Fig. 1.

Identification of Cdc42 interaction partners with SILAC-qGAP. (A) Rho GTPases were expressed, purified, loaded with either GDP or GTPγS, and bound to a Sepharose matrix. Protein samples were obtained from SILAC-labeled cells. Proteins from H- and l-labeled cells were pulled down with Cdc42GTPγS and Cdc42GDP in a forward (arrows) and reverse experiment. Bound proteins were eluted and analyzed via mass spectrometry. Significant outliers were calculated (labeled in orange) for the forward (B) and reverse (C) experiment. Proteins that are significant outliers in the forward and reverse experiment and that were specific to one nucleotide form in both experiments are considered specific interaction partners of Cdc42 (D, labeled in orange).

Fig. 2.

Identification of Cdc42 interaction partners with LF-qGAP from mouse cerebellum. (A) Protein lysates from mouse cerebellum (n = 3 independent samples) were incubated with Cdc42GTPγS or Cdc42GDP coupled to beads. Bound proteins were eluted and analyzed via mass spectrometry in triplicates. Differences in intensities between runs (Log2 Cdc42GTPγS/Cdc42GDP) and statistical significance (-Log10(p value t test)) were calculated. (B) Specific interactors are distinguished from background proteins based on a combination of the log2 fold change and the t test p value (significantly different proteins in orange), Cdc42GTPγS (right) or Cdc42GDP (left) (colored in red). (C) We identified more interaction partners for LF-qGAP (44 proteins) than for SILAC-qGAP (25) with a significant overlap (15).

Fig. 3.

LF-qGAP from brain lysates for six Rho GTPases. Cerebrum pull-downs for (A) Cdc42, (B) Rac1, (C) RhoA. Pull-downs from whole brain lysates for (D) RhoB, (E) RhoC, (F) RhoD. As before, specific interactors (colored in orange) are distinguished from background proteins based on a combination of the log2 fold change and the t test p value. GTPγS-specific interactors are expected in the upper right corner, interactors of the GDP-form in the upper left corner.

Fig. 4.

Overlap with published interactions. Interactors identified by qGAP (GDP specific interactors in turquoise; GTPγS specific interactors in red) with interactors listed in the HIPPIE protein-protein interaction Database (gray circle). p values indicate significance of the enrichment of overlapping interactors between qGAP and HIPPIE and are given above each Venn diagram.

Fig. 6.

(A) Interaction network between Rho GTPases and identified binding partners of the GTPγS-loaded form. Known (gray) and new (colored) interactions are visualized by line colors and the pie charts for every Rho GTPase. The width of edges corresponds to relative intensity ratio between GDP- and GTPγS-bound Rho GTPase. (B) Clustering Rho GTPases based on shared binding partners mirrors their phylogenetic relationships.

Fig. 5.

Validation of loading-state-dependent interactions in situ with the proximity ligation assay (PLA). (A) Cells were treated with CNF_Y (for RhoA activation) or with CNF1 (Cdc42 and Rac1 activation), fixed, costained with oligonucleotide-coupled antibodies against the Rho GTPase and interactors. The basal PLA signal (red) increased upon toxin treatment for RhoA-Rock2 (known interaction), Rac1-Rock2 and Cdc42-IQSEC3 (both novel). (B) Automated quantification shows that toxin treatment significantly increased PLA signals for 9/11 tested novel interactions.