Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes
2016; Elsevier BV; Volume: 15; Issue: 5 Linguagem: Inglês
10.1074/mcp.m116.058354
ISSN1535-9484
AutoresJennifer G. Abelin, Jinal Patel, Xiaodong Lü, Caitlin M. Feeney, Lọla Fagbami, Amanda L. Creech, Roger Hu, Daniel D. Lam, Desiree Davison, Lindsay K. Pino, Jana Qiao, Eric Kuhn, Adam Officer, Jianxue Li, Susan E. Abbatiello, Aravind Subramanian, Richard L. Sidman, Evan Snyder, Steven A. Carr, Jacob D. Jaffe,
Tópico(s)Advanced Biosensing Techniques and Applications
ResumoProfiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures. Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens. To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples. The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures. Our understanding of disease mechanisms and therapeutic opportunities is rapidly expanding because of incredible advances in molecular profiling technologies. Within the last decade, the broad application of high-throughput transcriptional profiling has resulted in rich sets of gene expression data collected from biological samples subjected to drug and genetic perturbations (1Edgar R. Domrachev M. Lash A.E. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository Nucleic Acids Res. 2002; 30: 207-210Crossref PubMed Scopus (8467) Google Scholar, 2Barrett T. Troup D.B. Wilhite S.E. Ledoux P. Evangelista C. Kim I.F. Tomashevsky M. Marshall K.A. Phillippy K.H. Sherman P.M. Muertter R.N. Holko M. Ayanbule O. Yefanov A. Soboleva A. NCBI GEO: archive for functional genomics data sets—update.Nucleic Acids Res. 2013; 41: D991-D995Crossref PubMed Scopus (5058) Google Scholar). 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Initial and sustained signals to environmental changes (such as drug treatment and neomorphic disease states) are frequently mediated by changes of post-translational modifications on proteins. Protein phosphorylation in particular is known to be a strong mediator of cellular signaling (5Freeman M. Feedback control of intercellular signalling in development.Nature. 2000; 408: 313-319Crossref PubMed Scopus (431) Google Scholar, 6Lalli E. Sassone-Corsi P. Signal transduction and gene regulation: the nuclear response to cAMP.J. Biol. Chem. 1994; 269: 17359-17362Abstract Full Text PDF PubMed Google Scholar). Changes in the phosphoproteome can result in subsequent disruptions in protein-protein interactions (7Nishi H. Hashimoto K. Panchenko A.R. Phosphorylation in protein-protein binding: effect on stability and function.Structure. 2011; 19: 1807-1815Abstract Full Text Full Text PDF PubMed Scopus (190) Google Scholar, 8Ubersax J.A. Ferrell Jr, J.E. 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Signal. 2010; 3: ra3Crossref PubMed Scopus (1145) Google Scholar). However, to facilitate modern "omics" analyses and leverage techniques pioneered in gene expression studies, it would be highly desirable to have reproducible observations of phosphopeptide analytes across large numbers of samples generated under different conditions. Yet, even with the fastest and most sensitive MS instruments currently available, it is not possible to reproducibly measure all of the same peptides or modified peptides across multiple experiments using data-dependent analysis methods. Comparisons across even small numbers of proteomic experiments are difficult because differences in sample processing protocols and mass spectrometry data acquisition methods can cause sampling variation (28Jedrychowski M.P. Huttlin E.L. Haas W. Sowa M.E. Rad R. Gygi S.P. Evaluation of HCD- and CID-type fragmentation within their respective detection platforms for murine phosphoproteomics.Mol. Cell. 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As a result, it is currently not possible to reproducibly and quantitatively monitor all known phosphosites in a large number of human phosphoproteome samples. To overcome these challenges, we considered that phosphorylation is mediated by just a few hundred protein kinases and phosphatases that can modify hundreds of thousands of amino acid sites on various protein targets. We hypothesized that the implicit one-to-many relationship of kinases to substrates suggests that there is some redundancy in the cellular information conveyed by phosphorylation and that collapsing the number of monitored sites based on their coordinate activity could provide a core set of highly informative phosphopeptide probes. This idea is consistent with work published by Alcolea et al., where phosphosignaling events within acute myeloid leukemia cell lines with different sensitivities to kinase inhibitors were profiled to reveal several hundred correlated phosphorylation sites that were involved in parallel kinase pathways (32Alcolea M.P. Casado P. Rodríguez-Prados J.-C. Vanhaesebroeck B. Cutillas P.R. Phosphoproteomic analysis of leukemia cells under basal and drug-treated conditions identifies markers of kinase pathway activation and mechanisms of resistance.Mol. Cell. Proteomics. 2012; 11: 453-466Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar). In addition, a similar strategy was used to develop the "L1000" reduced-representation transcriptional profiling assay that is the basis for the transcriptional Connectivity Map project. The L1000 assay retains 80% of information content at <1% of the cost of microarray or RNA-Seq-based expression profiling (33Duan Q. Flynn C. Niepel M. Hafner M. Muhlich J.L. Fernandez N.F. Rouillard A.D. Tan C.M. Chen E.Y. Golub T.R. Sorger P.K. Subramanian A. Ma'ayan A. LINCS canvas browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures.Nucleic Acids Res. 2014; 42: W449-W460Crossref PubMed Scopus (186) Google Scholar). Monitoring a reduced-representation set of phosphopeptide probes using a targeted MS approach could be a time- and cost-effective approach to monitor changes in phosphosignaling in response to multiple drug and genetic perturbations. Such an assay could identify connections between molecular perturbations and elucidate cell type-specific cell signal transduction using analysis methods similar to those utilized in the transcriptional profiling field. A similar approach was recently reported by Picotti and colleagues, who developed a targeted proteomic assay to probe biological processes in Saccharomyces cerevisiae in response to environmental perturbations by selecting sentinel proteins from existing data (34Soste M. Hrabakova R. Wanka S. Melnik A. Boersema P. Maiolica A. Wernas T. Tognetti M. von Mering C. Picotti P. A sentinel protein assay for simultaneously quantifying cellular processes.Nat. Meth. 2014; 11: 1045-1048Crossref PubMed Scopus (51) Google Scholar). Such targeted approaches could eliminate stochastic sampling effects and allow for accurate quantification across large sample sets without significant loss in information content relative to a full phosphoproteome. The work described below explores this possibility and consists of three main sections: (1) a discovery arm where we identify a high-value set of phosphopeptide probes from traditional, data-dependent large scale SILAC-based phosphoproteomic data, (2) a configuration arm where we develop a targeted, internally standardized phosphopeptide assay that generates almost complete data (data that contains observations for all phosphopeptides), and (3) a proof-of-principle arm where we explore the sensitivity of the assay to diverse perturbations and biological systems and demonstrate its general utility. In our discovery arm we produced global phosphorylation data representing 156 samples that included 26 chemical perturbations in three different cell lines using conventional phosphopeptide enrichment and MS-based techniques. From these data we selected representative phosphosites (and their associated observable peptides) from clusters of sites that exhibited coordinated regulation across discovery experiments. We then configured a targeted parallel reaction monitoring (PRM) assay against these phosphopeptide probes using isotopically-labeled synthetic analogs, and in parallel, developed automated workflows that enabled proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment from 96 samples simultaneously in anticipation of scaling the assay to generate a large corpus of data. Our initial evaluation of the configured assay was to regenerate samples under similar conditions to those used in our discovery experiments to see if we could recapitulate the previously observed relationships using only the reduced-representation phosphoproteome at a fraction of the effort required for deeper phosphoproteomic profiling. Finally, in our proof-of-principle arm we extended our experimental conditions to vary the treatments, cell types, and time points measured with the explicit goal of demonstrating that the assay could generate phosphoproteomic profiles outside of the parameters under which it was developed and to demonstrate that the assay is responsive to disruptions of signaling pathways of known biological importance. We call this assay "P100" because it measures ∼100 phosphopeptide probes in a single 60 min assay. This assay is a phosphosignaling analog of our Global Chromatin Profiling assay (35Creech A.L. Taylor J.E. Maier V.K. Wu X. Feeney C.M. Udeshi N.D. Peach S.E. Boehm J.S. Lee J.T. Carr S.A. Jaffe J.D. Building the connectivity map of epigenetics: chromatin profiling by quantitative targeted mass spectrometry.Methods. 2015; 72: 57-64Crossref PubMed Scopus (34) Google Scholar, 36Jaffe J.D. Wang Y. Chan H.M. Zhang J. Huether R. Kryukov G.V. Bhang H.E. Taylor J.E. Hu M. Englund N.P. Yan F. Wang Z. Robert McDonald 3rd, E. Wei L. Ma J. Easton J. Yu Z. deBeaumount R. Gibaja V. Venkatesan K. Schlegel R. Sellers W.R. Keen N. Liu J. Caponigro G. Barretina J. Cooke V.G. Mullighan C. Carr S.A. Downing J.R. Garraway L.A. Stegmeier F. Global chromatin profiling reveals NSD2 mutations in pediatric acute lymphoblastic leukemia.Nat. Genet. 2013; 45: 1386-1391Crossref PubMed Scopus (185) Google Scholar) that has already proven to be of great utility. We believe that the P100 assay will prove highly useful for classification and stratification of drug and genetic mechanisms as facilitated through comparison of phosphoproteomic signatures of known chemical and genetic perturbations to those of novel perturbations or those where mechanistic insight is currently lacking. Together, these proteomic signature generation assays can form the basis for proteomic Connectivity Maps to complement their transcriptional analogs. MCF7 cells were cultured in DMEM GlutaMAX medium (Gibco, 10567–014, Waltham, MA) supplemented with 10% FBS (Sigma, F4135, St. Louis, MO), 1% penicillin/streptomycin (Gibco, 10378–016), and 0.8% glucose (Sigma, G8769). PC3 cells were cultured in RPMI medium (Gibco, 11875–093) supplemented with 10% FBS (Sigma, F4135), 1% penicillin/streptomycin (Gibco, 10378–016), 1% HEPES (Gibco, 15630), and 1% sodium pyruvate (Gibco, 11360). HL60 cells were cultured in RPMI medium (Gibco, 11875) supplemented with 10% FBS (Sigma, F4135), and 1% penicillin/streptomycin (Gibco, 10378–016). Either normal l-lysine (K0) and l-arginine (R0) or heavy-labeled 13C6-15N2 lysine (K8) and 13C6-15N4arginine (R10) were supplemented at concentrations of 40 mg/L and 120 mg/L, respectively, for SILAC cell culture. MCF7 cells were cultured in DMEM GlutaMAX medium (Gibco, 10567–014) supplemented with 10% FBS (Sigma, F4135), 1% penicillin/streptomycin (Gibco, 10378–016), and 0.8% glucose (Sigma, G8769). PC3 cells were cultured in RPMI medium (Gibco, 11875–093) supplemented with 10% FBS (Sigma, F4135), 1% penicillin/streptomycin (Gibco, 10378–016), 1% HEPES (Gibco, 15630), and 1% sodium pyruvate (Gibco, 11360). HL60 cells were cultured in RPMI medium (Gibco, 11875) supplemented with 10% FBS (Sigma, F4135), and 1% penicillin/streptomycin (Gibco, 10378–016). Lines were propagated according to standard tissue-culture practices. The following applies to discovery, configuration, and confirmation experiments. Compounds were obtained from Sigma (St. Louis, MO) or EMD Millipore (Darmstadt, Germany), with the exception of JQ-1 which was the generous gift of Dr. James Bradner (Dana-Farber Cancer Institute, Boston, MA). Once cells reached ∼95% confluence, they were treated with the compounds listed in Table I and supplemental Table S1 for 6 h at 37 °C. After 6 h, the cells were washed twice with cold PBS (Gibco, 10010–023) and harvested by scraping. Cells were pelleted at 1000 × g for 2 min. The supernatant was then removed, and the cell pellet was frozen in liquid nitrogen until cell lysis and phosphopeptide enrichment.Table ICompounds and concentrations used for discovery experimentsCompoundTreatment concentration (μm)CompoundTreatment concentration (μm)Captopril17.2Mesalazine26.2Ambroxol9.6Anisomycin15Paclitaxel1Digitoxigenin10.6Carmustine100Digoxigenin10.2Fulvestrant1Digoxin5.2Clindamycin8.6Lanatoside C4Chlortetracycline7.8Irinotecan100Chlorzoxazone23.6Scriptaid10Doxorubicin6.8Trichostatin A1Daunorubicin7MS-27510GW-851010Valproic acid1000Staurosporine1H-7100Dexverapamil10Geldanamycin1 Open table in a new tab For discovery experiments, we used three-state SILAC labeling to determine quantification of phosphoproteomic changes. In these experiments, we held the "light" channel constant as DMSO and varied the drugs in the medium and heavy channels (as schematically depicted in Fig. 1C and listed in Table I). For each drug/cell type combination, two complete biological repeats (grown several weeks apart) were performed. Ratios were determined using MaxQuant (see below) of treatment versus DMSO for each drug. The entirety of the discovery data set, including a table that specifies SILAC labeling states for each of the 26 drug combinations, can be found in ftp://[email protected] This data set has been deposited in MassIVE with accession ftp://[email protected] For all other experiments, cells were grown in typical growth medium without metabolic labeling of proteins. Instead, the synthetic versions of the P100 assay peptides (probes) are used to derive quantitative information. Compounds were obtained from Sigma or EMD Millipore (Darmstadt, Germany). Once cells reached ∼95% confluence, they were treated with the compounds in supplemental Table S5 for either 3, 6, or 24 h at 37 °C. After 3, 6, or 24 h, the cells were washed twice with cold PBS (Gibco, 10010–023), lysed in plate in urea buffer (8 m urea; 75 mm NaCl, 50 mm Tris HCl pH 8.0, 1 mm EDTA, 2 μg/ml aprotinin (Sigma, A6103), 10 μg/ml leupeptin (Roche, #11017101001, Basel, Switzerland), 1 mm PMSF (Sigma, 78830), 10 mm NaF, Phosphatase Inhibitor Mixture 2 (1:100, Sigma, P5726), Phosphatase Inhibitor Mixture 3 (1:100, Sigma, P0044), and harvested by scraping. Cells were lysed for 30 min at 4 °C and then frozen at −80 °C. Prior to phosphopeptide enrichment, cell lysates were clarified by centrifugation at 15,000 × g for 15 min. Individual colonies of H9 human embryonic stem cells (ESCs) were cultured with mouse embryonic fibroblast-conditioned media (MEF-CM; provided by Sanford-Burhnam Research Institute, La Jolla, CA) in matrigel (BD, 356231)-coated plates. For neural progenitor cell (NPC) induction, ESC cell colonies of 60–80% confluence were incubated in MEF-CM containing each 5 μm of dorsomorphin (Sigma, P5499), A83–01 (Sigma, SML0788) and PNU 74654 (Sigma, P0052). Once NPC cells and reached ∼95% confluence, they were treated with the compounds listed in Supplemental Table S2 for 24 h at 37 °C. H9 cells or NPCs were harvested by washing twice with cold PBS (Gibco, 10010–023) and centrifugation at 1000 × g for 2 min. The supernatant was removed, and the cell pellets were frozen in liquid nitrogen until cell lysis and phosphopeptide enrichment. Frozen cell pellets were lysed for 30 min at 4 °C in urea buffer (8 m urea; 75 mm NaCl, 50 mm Tris HCl pH 8.0, 1 mm EDTA, 2 μg/ml aprotinin (Sigma,
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