Combination of Chemical Genetics and Phosphoproteomics for Kinase Signaling Analysis Enables Confident Identification of Cellular Downstream Targets

Delineation of phosphorylation-based signaling networks requires reliable data about the underlying cellular kinase-substrate interactions. We report a chemical genetics and quantitative phosphoproteomics approach that encompasses cellular kinase activation in combination with comparative replicate mass spectrometry analyses of cells expressing either inhibitor-sensitive or resistant kinase variant. We applied this workflow to Plk1 (Polo-like kinase 1) in mitotic cells and induced cellular Plk1 activity by wash-out of the bulky kinase inhibitor 3-MB-PP1, which targets a mutant kinase version with an enlarged catalytic pocket while not interfering with wild-type Plk1. We quantified more than 20,000 distinct phosphorylation sites by SILAC, approximately half of which were measured in at least two independent experiments in cells expressing mutant and wild-type Plk1. Based on replicate phosphorylation site quantifications in both mutant and wild-type Plk1 cells, our chemical genetic proteomics concept enabled stringent comparative statistics by significance analysis of microarrays, which unveiled more than 350 cellular downstream targets of Plk1 validated by full concordance of both statistical and experimental data. Our data point to hitherto poorly characterized aspects in Plk1-controlled mitotic progression and provide a largely extended resource for functional studies. We anticipate the described strategies to be of general utility for systematic and confident identification of cellular protein kinase substrates. Delineation of phosphorylation-based signaling networks requires reliable data about the underlying cellular kinase-substrate interactions. We report a chemical genetics and quantitative phosphoproteomics approach that encompasses cellular kinase activation in combination with comparative replicate mass spectrometry analyses of cells expressing either inhibitor-sensitive or resistant kinase variant. We applied this workflow to Plk1 (Polo-like kinase 1) in mitotic cells and induced cellular Plk1 activity by wash-out of the bulky kinase inhibitor 3-MB-PP1, which targets a mutant kinase version with an enlarged catalytic pocket while not interfering with wild-type Plk1. We quantified more than 20,000 distinct phosphorylation sites by SILAC, approximately half of which were measured in at least two independent experiments in cells expressing mutant and wild-type Plk1. Based on replicate phosphorylation site quantifications in both mutant and wild-type Plk1 cells, our chemical genetic proteomics concept enabled stringent comparative statistics by significance analysis of microarrays, which unveiled more than 350 cellular downstream targets of Plk1 validated by full concordance of both statistical and experimental data. Our data point to hitherto poorly characterized aspects in Plk1-controlled mitotic progression and provide a largely extended resource for functional studies. We anticipate the described strategies to be of general utility for systematic and confident identification of cellular protein kinase substrates. Reversible protein phosphorylation by protein kinases represents a key control mechanism in signal transmission and controls nearly all aspects of cellular physiology. Quantitative proteomics approaches that incorporate techniques such as stable isotope labeling by amino acids in cell culture (SILAC), 1The abbreviations used are:SILACstable isotope labeling by amino acids in cell cultureSCXstrong cation exchangeIMACion metal affinity chromatographyIPIInternational Protein IndexFDRfalse discovery rateGOGene OntologyRPEretinal pigment epithelialSAMsignificance analysis of microarraysmTORmammalian target of rapamycinEGFRepidermal growth factor receptor. 1The abbreviations used are:SILACstable isotope labeling by amino acids in cell cultureSCXstrong cation exchangeIMACion metal affinity chromatographyIPIInternational Protein IndexFDRfalse discovery rateGOGene OntologyRPEretinal pigment epithelialSAMsignificance analysis of microarraysmTORmammalian target of rapamycinEGFRepidermal growth factor receptor. phosphopeptide fractionation and enrichment by strong cation exchange (SCX), and ion metal affinity chromatography (IMAC) together with sensitive high resolution MS analysis and automated peptide identification and quantification have made it possible to monitor phosphorylation-based signaling on a global scale (1Dephoure N. Zhou C. Villén J. Beausoleil S.A. Bakalarski C.E. Elledge S.J. Gygi S.P. A quantitative atlas of mitotic phosphorylation.Proc. Natl. Acad. Sci. U.S.A. 2008; 105: 10762-10767Crossref PubMed Scopus (1250) Google Scholar, 2Olsen J.V. de Godoy L.M. Li G. Macek B. Mortensen P. Pesch R. Makarov A. Lange O. Horning S. Mann M. Parts per million mass accuracy on an Orbitrap mass spectrometer via lock mass injection into a C-trap.Mol. Cell. Proteomics. 2005; 4: 2010-2021Abstract Full Text Full Text PDF PubMed Scopus (1241) Google Scholar, 3Schreiber T.B. Mäusbacher N. Breitkopf S.B. Grundner-Culemann K. Daub H. Quantitative phosphoproteomics: An emerging key technology in signal-transduction research.Proteomics. 2008; 8: 4416-4432Crossref PubMed Scopus (56) Google Scholar, 4Cox J. Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9143) Google Scholar). Because signaling networks are defined by the underlying kinase-substrate relationships, systematic approaches are required for the comprehensive and confident assignment of cellular kinase substrates (5Tan C.S. Linding R. Experimental and computational tools useful for (re)construction of dynamic kinase-substrate networks.Proteomics. 2009; 9: 5233-5242Crossref PubMed Scopus (18) Google Scholar). To identify cellular substrates, the catalytic activity of a kinase of interest needs to be rapidly regulated to capture a high fraction of direct phosphorylation events. This implies that protein kinase ablation by genetic knockout or RNA interference can be of limited utility, because of secondary changes that can accumulate during the time required for cellular kinase depletion (3Schreiber T.B. Mäusbacher N. Breitkopf S.B. Grundner-Culemann K. Daub H. Quantitative phosphoproteomics: An emerging key technology in signal-transduction research.Proteomics. 2008; 8: 4416-4432Crossref PubMed Scopus (56) Google Scholar, 5Tan C.S. Linding R. Experimental and computational tools useful for (re)construction of dynamic kinase-substrate networks.Proteomics. 2009; 9: 5233-5242Crossref PubMed Scopus (18) Google Scholar). In contrast, pharmacological interference by small molecules allows for rapid modulation of kinase activity and should therefore enable unbiased monitoring of signaling perturbations when combined with advanced MS-based proteomics. Such approaches are ideally based on mono-selective kinase inhibition. Although generally difficult to achieve for naturally occurring kinases, this is considered feasible by chemical genetics using drug-sensitized kinase mutants possessing an enlarged catalytic pocket to accommodate bulky kinase inhibitors (6Bishop J. 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PubMed Scopus Google Scholar). cellular control is for confident assignment of kinase-substrate stable isotope labeling by amino acids in cell culture strong cation exchange ion metal affinity chromatography Protein discovery pigment significance analysis of target of growth factor receptor. stable isotope labeling by amino acids in cell culture strong cation exchange ion metal affinity chromatography Protein discovery pigment significance analysis of target of growth factor receptor. our interest to strategies for unbiased and confident identification of cellular downstream targets of protein kinases by using Plk1 (Polo-like kinase 1) signaling in cells as a Plk1 is a of cell with key in mitotic and as as and in and 2009; PubMed Scopus Google Scholar). with the Plk1 to at mitotic with and at the and the in the and in and 2009; PubMed Scopus Google Scholar). Plk1 a in the of with a Plk1 to mitotic PubMed Scopus Google Scholar). Plk1 in to into the that Plk1 in a analysis of M. C. J. A and approach to kinase Full Text Full Text PDF PubMed Scopus Google and a of in using as M. J. K. S. S.A. the and as a Plk1 J. 26: PubMed Scopus Google Scholar). a phosphoproteomics Plk1 in the mitotic In this phosphorylation changes were measured Plk1 by either small interference RNA or small inhibitor A. B. S. R. M. A. R. of the mitotic Cell. Proteomics. Google Scholar). of the the of Plk1 modulation on a proteome-wide scale in a report an advanced concept that for the identification of in Our to comprehensive and confident data about of Plk1 downstream targets as for a approach of general utility for kinase signaling pigment cells in which both were and that either wild-type Plk1 or an Plk1 mutant to as as were used this S. C. genetics the for kinase activity in and in Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar). the cells were in a of and and with and either and or the of and cell to cells were per for a to cells in the cells were with and for in and to or cells in in to mutant kinase activity in cells were to either and to cells or the to cells for a cell This labeling used in two replicate experiments with to as and and cells and in two replicate experiments with either cell labeling were used and cells were in of A and inhibitor and per two for on cell were for on by and protein cells were for MS cells were at in cell culture cells were and as in the experiments with the that the both in the and the of with and all and inhibitors used for of cells to and with were to and and with and as H. J.V. M. R. G. O. Mann M. enrichment enables quantitative phosphoproteomics of the the cell Cell. 2008; Full Text Full Text PDF PubMed Scopus Google Scholar). were a and using as described J. Gygi S.P. enrichment approach for global phosphorylation analysis by mass 2008; PubMed Scopus Google Scholar). peptide were in and at were in of and a A and with an at and were by a to 350 by with and J. Gygi S.P. enrichment approach for global phosphorylation analysis by mass 2008; PubMed Scopus Google Scholar). were and based on the measured at to with peptide of the were using to phosphopeptide peptide were in of and with of affinity for at and with were as described J. Gygi S.P. enrichment approach for global phosphorylation analysis by mass 2008; PubMed Scopus Google Scholar, J. Mann M. for and of for proteomics using PubMed Scopus Google Scholar). peptide were to and with an of to MS analysis of of of the analyses were on an ion to a via a ion as described J.V. de Godoy L.M. Li G. Macek B. Mortensen P. Pesch R. Makarov A. Lange O. Horning S. Mann M. Parts per million mass accuracy on an Orbitrap mass spectrometer via lock mass injection into a C-trap.Mol. Cell. Proteomics. 2005; 4: 2010-2021Abstract Full Text Full Text PDF PubMed Scopus (1241) Google Scholar, H. J.V. M. R. G. O. Mann M. enrichment enables quantitative phosphoproteomics of the the cell Cell. 2008; Full Text Full Text PDF PubMed Scopus Google Scholar). were by a with in by a to in and at a of were into the mass with in the to full MS in the at and the of mass of by in the of the J.V. B. Macek B. C. Mortensen P. Mann M. in and phosphorylation in signaling Full Text Full Text PDF PubMed Scopus Google Scholar). activation enabled in the ion to of at or the ion for during J. A activation for phosphopeptide analysis by ion mass PubMed Scopus Google Scholar). all full in the a ion used for as described J.V. de Godoy L.M. Li G. Macek B. Mortensen P. Pesch R. Makarov A. Lange O. Horning S. Mann M. Parts per million mass accuracy on an Orbitrap mass spectrometer via lock mass injection into a C-trap.Mol. Cell. Proteomics. 2005; 4: 2010-2021Abstract Full Text Full Text PDF PubMed Scopus (1241) Google Scholar). mass and for activation in ion for An activation of in this were with the MaxQuant which of discovery rates, peptide to protein and phosphorylation site as described J. Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9143) Google Scholar, J.V. M. A. C. J. S. Mann M. 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This to by cellular and a in the experimental We therefore a to rapidly Plk1 activity in cells and cells by with the inhibitor during phosphorylation this be induced when the inhibitor as by the of the of in cells In contrast, on in control cells expressing wild-type Plk1 not of cells expressing either or wild-type by of inhibitor wash-out cells to kinases in mitotic cells to (1Dephoure N. Zhou C. Villén J. Beausoleil S.A. Bakalarski C.E. Elledge S.J. Gygi S.P. A quantitative atlas of mitotic phosphorylation.Proc. Natl. Acad. Sci. U.S.A. 2008; 105: 10762-10767Crossref PubMed Scopus (1250) Google Scholar, J.V. B. Macek B. C. Mortensen P. Mann M. in and phosphorylation in signaling Full Text Full Text PDF PubMed Scopus Google Scholar). quantitative by into to phosphopeptide enrichment by We replicate analyses of all by on a (1Dephoure N. Zhou C. Villén J. Beausoleil S.A. Bakalarski C.E. Elledge S.J. Gygi S.P. A quantitative atlas of mitotic phosphorylation.Proc. Natl. Acad. Sci. U.S.A. 2008; 105: 10762-10767Crossref PubMed Scopus (1250) Google Scholar, J.V. B. Macek B. C. Mortensen P. Mann M. in and phosphorylation in signaling Full Text Full Text PDF PubMed Scopus Google Scholar). data were with the MaxQuant for peptide and protein identification and the quantification of phosphorylation changes J. Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9143) Google Scholar). phosphorylation site measured in both replicate experiments were to data this and quantified distinct phosphorylation sites in either cell that be to a or with a of at least J.V. B. Macek B. C. Mortensen P. 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G. analysis of applied to the Natl. Acad. Sci. U.S.A. PubMed Scopus Google Scholar). To identify phosphorylation that are induced in control cells our analysis to the at least two replicate experiments in both and cells and for were in the data via a regulated with the for and the not to our experimental data were with the statistical because not a regulated site to in with cells and Such have a identification of a regulated which in this have an to more regulated in either cell of Plk1 This as an for stringent statistical analysis that not by the more in our phosphoproteomics with data. our identification of and a high of in as as of the changes were to wash-out and to contrast, were wash-out cells, which be to of protein of and experimental of all for which wash-out in or in cells were either in or in cells more regulated in regulated in all for which wash-out in or in cells were either in or in cells more in a of Plk1 with induced were not direct substrates. 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A to inhibitors in and PubMed Scopus Google Scholar). our data point to Plk1 as a cellular of that have not to key mitotic We more than in to in and all about and and can be in the data and our data as a resource of for in mitotic our chemical genetics and phosphoproteomics approach the of cellular kinase and high identification of downstream targets to stringent In our experimental can be applied to protein kinase that can be or to small inhibition. We be for to kinase-substrate networks in the cellular experimental strategies to described be for a of comparative MS and enable the identification of or protein changes with high We have advanced the combination of chemical genetics and MS-based phosphoproteomics for the systematic identification of cellular downstream targets regulated by a protein Our approach inhibitor-sensitive and kinase and that enabled confident identification of cellular the mitotic Plk1. Plk1 activity induced by cellular inhibitor wash-out to kinase in to cells expressing Plk1 mutant with to a small control experiments with wild-type Plk1 cells for systematic of inhibitor independent replicate analyses of cells wild-type and inhibitor-sensitive Plk1. This enabled confident identification of regulated phosphorylation sites on Plk1 downstream which by full concordance of statistical and experimental data. Our analysis unveiled on more than distinct and to a of aspects of Plk1-controlled mitotic of have not our data provide a extended resource for of cellular Plk1 Because our experimental strategies can be for protein kinase to small or the in this should be of general utility for the systematic and confident identification of cellular kinase-substrate