Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs - PubMed (original) (raw)

. 2010 Feb 16;3(109):ra12.

doi: 10.1126/scisignal.2000482.

Philip M Kim, Hugo Y K Lam, Stacy Piccirillo, Xiuqiong Zhou, Grace R Jeschke, Douglas L Sheridan, Sirlester A Parker, Ved Desai, Miri Jwa, Elisabetta Cameroni, Hengyao Niu, Matthew Good, Attila Remenyi, Jia-Lin Nianhan Ma, Yi-Jun Sheu, Holly E Sassi, Richelle Sopko, Clarence S M Chan, Claudio De Virgilio, Nancy M Hollingsworth, Wendell A Lim, David F Stern, Bruce Stillman, Brenda J Andrews, Mark B Gerstein, Michael Snyder, Benjamin E Turk

Affiliations

Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs

Janine Mok et al. Sci Signal. 2010.

Abstract

Phosphorylation is a universal mechanism for regulating cell behavior in eukaryotes. Although protein kinases target short linear sequence motifs on their substrates, the rules for kinase substrate recognition are not completely understood. We used a rapid peptide screening approach to determine consensus phosphorylation site motifs targeted by 61 of the 122 kinases in Saccharomyces cerevisiae. By correlating these motifs with kinase primary sequence, we uncovered previously unappreciated rules for determining specificity within the kinase family, including a residue determining P-3 arginine specificity among members of the CMGC [CDK (cyclin-dependent kinase), MAPK (mitogen-activated protein kinase), GSK (glycogen synthase kinase), and CDK-like] group of kinases. Furthermore, computational scanning of the yeast proteome enabled the prediction of thousands of new kinase-substrate relationships. We experimentally verified several candidate substrates of the Prk1 family of kinases in vitro and in vivo and identified a protein substrate of the kinase Vhs1. Together, these results elucidate how kinase catalytic domains recognize their phosphorylation targets and suggest general avenues for the identification of previously unknown kinase substrates across eukaryotes.

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Conflict of interest statement

Competing interests: M.S. consults for Affomix, which has an interest in proteomics, including phosphoproteomics.

Figures

Fig. 1

Fig. 1

Miniaturized peptide array approach enables high-throughput analysis of kinase consensus phosphorylation motifs. (A) Scheme for kinase peptide screening. Capillary pin-based liquid transfer devices were used to add components to reactions (2 _μ_l per well) and spot 0.2 _μ_l aliquots onto the streptavidin-coated membrane following incubation. The 1536-well format allows four kinases to be analyzed simultaneously. (B) Representative peptide screening results for Atg1, Gin4, Mps1, and Prk1. (C) Phosphorylation of consensus peptide substrates by Atg1, Gin4, Mps1, and Prk1. The sequence of each peptide is as follows: ATGtide, YANWLAASIYLDGKKK; GINtide, YALRRSRSMWNLGKKK; MPStide, YADHDDDTMHFRGKKK; and PRKtide, YALKPQYTGPRGKKK. Peptide phosphorylation was assayed at 10 _μ_M concentration by radiolabel kinase assay. Incorporation of radiolabeled phosphate into peptides was determined by phosphocellulose filter binding assay. Maximal rates for each kinase in these assays were: Atg1, 250 nM/min, Gin4, 510 nM/min, Mps1, 130 nM/min, Prk1, 330 nM/min. (D) Rates of Atg1 phosphorylation of ATGtide variants with individual point substitutions. Peptide phosphorylation was assayed as for panel C.

Fig. 2

Fig. 2

Heat map ranking kinases by their specificity quotients as calculated from their average PWMs. Kinases are ranked from least specific (top) to most specific (bottom). The specificity in each position is defined as the information content in each position, equivalent to the total height of the sequence logo (see table S1 for logos).

Fig. 3

Fig. 3

Dendrogram of yeast kinases clustered by specificity. Specificity categories are indicated by shading: red, acidophilic; orange, Pro-directed; cyan, P−3 Arg selecting; blue, P−2 Arg selecting; green, other. Because there were multiple distinct acidophilic motifs in which selectivity is varied by position, some kinases selecting primarily acidic residues clustered in the “other” category. Sequence logos (74) are shown for selected kinases from each group.

Fig. 4

Fig. 4

Comparison of kinase consensus phosphorylation site motifs to primary sequence reveals specificity-determining residues. (A) Sequence alignment of the regions surrounding residues 127 and 170 (human PKA numbering) in the catalytic domain of representative Snf1 family kinases (Gin4, Snf1, Kin1), and the CMGC kinases Yak1 and Kss1. The presence of an acidic residue at position 127 correlates with Arg selectivity at the P−3 position for the Snf1 family, but not the CMGC group. Conversely, a Glu residue at position 170 correlates with Arg selectivity for CMGC group kinases, but not for the Snf1 family. (B) Stereo view of the crystal structure of PKA with bound pseudosubstrate peptide (shown in cyan in stick representation; for clarity only the portion falling within the active site cleft is shown) highlighting predicted specificity determining residues (in sphere representation). Residues 127 and 170 are shown in yellow and magenta, respectively. The figure was generated using Pymol from the coordinates in PDB code 1ATP. (C) Kss1 mutagenesis. Mutation Kss1 Ser147 to Glu confers selectivity for Arg at P−3. The bar graph shows normalized spot intensities for the P−3 position taken from screens of the full peptide library (shown in Fig. S2).

Fig. 5

Fig. 5

MOTIPS ranking of known and predicted kinase-substrate pairs. (A) Bar graph showing the number of protein substrates reported in the literature (true positives) that have at least one phosphorylation site falling within the indicated rank value of predicted substrates for its respective kinase. Shown are the 99 sites of 174 known kinase-substrate pairs analyzed that fall within the top 0.5% predicted sites for that kinase among all Ser or Thr residues in the yeast proteome. (B) GO analysis of predicted kinase-substrate relationships that fall within the top 100 predicted substrates for all 61 kinases analyzed. The graph shows the ratio of predicted kinase-substrate pairs sharing either an annotated biological process (left bars) or subcellular compartment (right bars) in comparison to pairs of proteins chosen at random. For both pairs, the probability that the observed value falls within the random distribution is extremely low (p < 10−35) based on the calculated area under the Gaussian curve corresponding to the random distribution.

Fig. 6

Fig. 6

Prediction and confirmation of kinase-substrate relationships. (A) Top 15 hits from the trained Prk1 MOTIPS output. The Prk1 hit list of candidate substrates was subjected to machine learning using a training set consisting of 19 true positives (experimentally derived) and ~480 true negatives (experimentally derived and supplemented with those proteins that are known to solely localize to non-cytosolic compartments). Known in vivo substrates of Prk1 are highlighted in yellow. (B) Electrophoretic mobility shift analyses of Bem2 and Ede1. TAP−tagged Bem2 and Ede1 were purified from WT or prk1 Δ ark1 Δ strains by immobilized IgG, and then incubated in the presence or absence of phosphatases followed by immunoblotting against the TAP tag. (C) Mobility shift confirms Sol2 as an in vivo substrate of Vhs1. Lysates from WT or vhs1 Δ strains expressing TAP−tagged Sol2 were fractionated on denaturing polyacrylamide gels impregnated with Phos-tag (57), which retards the mobility of phosphoproteins, followed by immunoblotting against the TAP tag.

References

    1. Manning G, Plowman GD, Hunter T, Sudarsanam S. Evolution of protein kinase signaling from yeast to man. Trends Biochem Sci. 2002;27:514–520. - PubMed
    1. Moffat J, Sabatini DM. Building mammalian signalling pathways with RNAi screens. Nat Rev Mol Cell Biol. 2006;7:177–187. - PubMed
    1. Schmelzle K, White FM. Phosphoproteomic approaches to elucidate cellular signaling networks. Curr Opin Biotechnol. 2006;17:406–414. - PubMed
    1. Ptacek J, Devgan G, Michaud G, Zhu H, Zhu X, Fasolo J, Guo H, Jona G, Breitkreutz A, Sopko R, McCartney RR, Schmidt MC, Rachidi N, Lee SJ, Mah AS, Meng L, Stark MJ, Stern DF, De Virgilio C, Tyers M, Andrews B, Gerstein M, Schweitzer B, Predki PF, Snyder M. Global analysis of protein phosphorylation in yeast. Nature. 2005;438:679–684. - PubMed
    1. Elphick LM, Lee SE, Gouverneur V, Mann DJ. Using chemical genetics and ATP analogues to dissect protein kinase function. ACS Chem Biol. 2007;2:299–314. - PubMed

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