Sensitive multiplexed analysis of kinase activities and activity-based kinase identification

Abstract

Constitutive activation of one or more kinase signaling pathways is a hallmark of many cancers. Here we extend the previously described mass spectrometry-based KAYAK approach by monitoring kinase activities from multiple signaling pathways simultaneously. This improved single-reaction strategy, which quantifies the phosphorylation of 90 synthetic peptides in a single mass spectrometry run, is compatible with nanogram to microgram amounts of cell lysate. Furthermore, the approach enhances kinase monospecificity through substrate competition effects, faithfully reporting the signatures of many signaling pathways after mitogen stimulation or of basal pathway activation differences across a panel of well-studied cancer cell lines. Hierarchical clustering of activities from related experiments groups peptides phosphorylated by similar kinases together and, when combined with pathway alteration using pharmacological inhibitors, distinguishes underlying differences in potency, off-target effects and genetic backgrounds. Finally, we introduce a strategy to identify the kinase, and even associated protein complex members, responsible for phosphorylation events of interest.

Figure 1

Workflow for a single-reaction, 90-substrate in vitro kinase assay. Synthetic substrate peptides are pooled and incubated with cell lysate. After kinase reactions are quenched, stable isotope–labeled phosphopeptides (internal standards; heavy label on italicized proline) of identical sequence to substrate peptides are added at a known concentration. Phosphorylated substrate peptides and internal standard phosphopeptides are enriched using immobilized metal-ion affinity chromatography and analyzed by LC-MS techniques. Pairs of light (product) and heavy (internal standard) peptides co-elute perfectly, but because they differ in mass by 6 Da, can be quantified by direct ratio of light-to-heavy areas under the curve from high-resolution data. Each assay produces 90 activity measurements in core signaling pathways.

Figure 2

Sensitivity and reproducibility of the single-reaction KAYAK assay. (a) Sensitivity and linearity of the 90-peptide KAYAK approach. Seven different amounts of lysate from HEK-293 cells treated with insulin were used. Product amounts are shown as a heat map of white to red. Products of <50 fmol were empirically considered not observed (gray). The Pearson product-moment correlation coefficients for lysate-to-product amounts for each peptide are shown using green intensity scaling. (b) Examples of peptides from a, including a serine-phosphorylated peptide (F6) and a tyrosine-phosphorylated peptide (G2). The data are shown as means of duplicates with error bars to the minimum and maximum values. (c) Comparison between single-reaction (competing peptides) and 90 individual kinase assays (no competition). The fold change for each peptide’s activity measurement for HEK-293 cells with and without insulin treatment is shown. Each reaction involved 20 μg of lysate. Product amounts were normalized to untreated cell lysate and are displayed as means ± s.d. (n = 3).

Figure 3

Induced core pathway phosphorylation changes in human cell lines are faithfully reported by profiling using the single-reaction KAYAK assay. (a) Heat map of triplicate KAYAK activity experiments. Kinase activities using lysates (20 μg) from HEK-293 cells and HeLa cells untreated or treated with insulin, EGF or PMA were measured using 90 peptides. The phosphorylation rates for the 68 observed peptides were normalized by reference to the most phosphorylated sample and analyzed by Pearson coefficient hierarchical clustering to group similar responders together. Each row represents the phosphorylation rate of a different peptide normalized to the highest value in the row. The fold change representations from ‘No treatment’ are shown in Supplementary Figure 6. (b) Examples of peptides in a. The data are shown as averages ± s.d. (n = 3). Candidate kinases are listed based on phosphorylation using purified kinases (Supplementary Fig. 1). (c) Western blot analysis of the lysates using antibodies as indicated. Full length blots are presented in Supplementary Figure 21.

Figure 4

Profiling of 11 human cell lines using the single-reaction KAYAK assay demonstrates heterogeneity in basal kinase activities and activation state of core pathways. (a) Heat map of kinase activities. The 11 cell lines included U-87 MG (glioblastoma), MCF7 (breast), T-47D (breast), SUM-159 (breast), HT-1080 (fibrosarcoma), HeLa (cervical), DU 145 (prostate), U-2 OS (osteosarcoma), Jurkat (T lymphocyte), BJ (foreskin fibroblast) and HEK-293 (embryonic kidney). Each was cultured under ATCC recommended or equivalent conditions and lysed. Lysates (20 μg) were subjected to KAYAK profiling. Using 68 peptides with observable phosphorylation, activities were normalized to the highest value in each row, followed by hierarchical cluster analysis, which groups peptides with similar responses together. (b) Examples of several peptides from a. The data are shown as the mean from duplicate analyses with minimum and maximum values as error bars. (c) Western blot analysis of the lysates using antibodies as indicated. Full-length blots are presented in Supplementary Figure 21.

Figure 5

Cancer cell lines with elevated Akt activity differ markedly in their response to inhibitors of Akt and PDK1. (a) Heat map of normalized kinase activities. Three commonly-used cell lines (PC-3, LNCaP and A2780) with a constitutively active PI3K/Akt pathway were treated with DMSO, an allosteric Akt inhibitor (Akti-1) or one of four PDK1 inhibitors (PDK1i-1–4) (Supplementary Fig. 12 for compound information). Kinase activities were profiled using 10 μg of each cell lysate and 90 KAYAK peptides. The phosphorylation rates for 54 observed peptides were normalized to the highest value for that peptide followed by hierarchical cluster analysis. (b) Examples of select peptides from panel a. The data are shown as the mean of duplicates with error bars to minimum and maximum values. (c) Dendrograms of activity profiles in response to inhibitor treatment for the three cell lines.

Figure 6

Identification of Cdc2/Cyclin B1 complex as an activated kinase in mitosis. (a) Heat map of kinase activities from cell cycle lysates. HeLa cells were cultured under standard conditions (asynchronous), or synchronized in either G1/S or G2/M phase of the cell cycle. Kinase activities from lysates (20 μg) were analyzed by KAYAK profiling. Phosphorylation rates were normalized and clustered as in Figure 3. (b) Examples of peptides in a. Seven peptides (underlined in a) showing this pattern were chosen for correlation profiling to identify the mitotic kinase. (c) UV chromatogram of protein elution into 36 fractions from the anion exchange column using G2/M phase cell lysate. (d) Kinase activity profile (normalized to the highest value) using seven upregulated peptides and the fractions in panel c. (e) Correlation profiles of kinase activity and protein quantification. 3,933 proteins (114 kinases) were identified by ‘shotgun’ LC-MS/MS analysis of flow-through (FT) and 36 fractions. Protein amount was estimated based on peptide identifications (Online Methods) and normalized to the highest value. Correlation profiling ranked Cdc2 as the most likely kinase (1/114) and eighth best ranked protein overall (8/3933). In addition, the amount of Cyclin B1 was highly correlated. r-values represent Pearson product-moment correlation coefficients between peak kinase activity and protein abundance in active fractions. (f) KAYAK profiling of 90 peptides using purified Cdc2/Cyclin B1. The product amounts for the seven peptides in panel d are shown as red squares.