quantitative phosphoproteomics - an emerging key technology in

REVIEW

Quantitative phosphoproteomics – an emerging key

technology in signal-transduction research

Thiemo B. Schreiber, Nina Mäusbacher, Susanne B. Breitkopf,Kathrin Grundner-Culemann and Henrik Daub

Cell Signaling Group, Department of Molecular Biology, Max Planck Institute ofBiochemistry, Martinsried, Germany

Protein phosphorylation is the most important type of reversible post-translational modificationinvolved in the regulation of cellular signal-transduction processes. In addition to controllingnormal cellular physiology on the molecular level, perturbations of phosphorylation-based sig-naling networks and cascades have been implicated in the onset and progression of various hu-man diseases. Recent advances in mass spectrometry-based proteomics helped to overcomemany of the previous limitations in protein phosphorylation analysis. Improved isotope labelingand phosphopeptide enrichment strategies in conjunction with more powerful mass spectro-meters and advances in data analysis have been integrated in highly efficient phosphoproteomicsworkflows, which are capable of monitoring up to several thousands of site-specific phosphoryl-ation events within one large-scale analysis. Combined with ongoing efforts to define kinase-substrate relationships in intact cells, these major achievements have considerable potential toassess phosphorylation-based signaling networks on a system-wide scale. Here, we provide anoverview of these exciting developments and their potential to transform signal-transduction re-search into a technology-driven, high-throughput science.

Received: February 18, 2008Revised: April 11, 2008

Accepted: May 13, 2008

Keywords:

Liquid chromatography-tandem mass spectrometry / Phosphoproteomics / Proteinkinases / Quantitative analysis / Signal transduction

4416 Proteomics 2008, 8, 4416–4432

1 Introduction

Protein phosphorylation represents the most widespreadtype of PTM in eukaryotic cells. Catalyzed by protein kinases,which form with more than 500 distinct members one of the

largest enzyme families encoded by the human genome,reversible and site-specific phosphorylations control variousmolecular aspects such as the activity, localization, bindingproperties or stability of about one third of all proteins in anyhuman eukaryotic cell [1, 2]. These regulatory events triggersignal propagation and modulation across phosphorylation-controlled signaling cascades and networks, which convergeand co-operate to govern fundamental physiological pro-cesses including cell division, proliferation, migration, dif-ferentiation and survival [3]. Moreover, distortions in phos-phorylation-dependent signaling, for example through aber-rant inactivation or hyperactivation of protein kinases, canlead to the onset and progression of diseases such as diabetesand cancer [2, 4]. Thus, in addition to contributing to themechanistic understanding of the molecular aspects of cel-lular physiology, information on cellular protein phospho-rylation permits pinpointing of drug targets, thus rationaliz-ing the development of kinase-specific, therapeutic strategies[5–7].

Correspondence: Dr. Henrik Daub, Cell Signaling Group, Depart-ment of Molecular Biology, Max Planck Institute of Biochemistry,Am Klopferspitz 18, D-82152 Martinsried, GermanyE-mail: [email protected]: 149-89-8578-2454

Abbreviations: ATM, ataxia telangiectasia-mutated; ATR, ataxiatelangiectasia-mutated and Rad3-related; DDA, data-dependentacquisition; DDR, DNA damage response; EGFR, epidermalgrowth factor receptor; ETD, electron transfer dissociation;MRM, multiple reaction monitoring; NHS, N-hydroxysuccimide;PDGF(R), platelet-derived growth factor (receptor); PTK, proteintyrosine kinases; SILAC, stable isotope labeling with amino acidsin cell culture; XIC, extracted ion chromatograms

DOI 10.1002/pmic.200800132

© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.com

Proteomics 2008, 8, 4416–4432 Cell Biology 4417

Not that long time ago, the identification of proteinphosphorylation sites was tedious, time-consuming and oflow-throughput - phosphopeptide characterization relied onnow classical techniques such as in vitro or in vivo labelingwith radioactive 32P-phosphate, phosphopeptide mappingand peptide sequencing by Edman degradation, often com-bined with mutational analysis to localize and verify themodified residue(s) [8, 9].

Recent methodological advances in biological MS had adramatic impact on protein phosphorylation research. Spur-red by spectacular improvements on MS instrumentation,phosphopeptide fractionation protocols and data processingprocedures, the identification of hundreds to thousands ofphosphorylation sites in cell or tissue extracts has practicallybecome routine, transforming cellular biochemistry into ahigh-throughput proteomics science. Moreover, innovativenew tools and techniques are constantly reported. Consider-able challenges remain to be addressed, in particular the taskto translate catalogs of protein phosphorylation sites intocomprehensive descriptions of cellular signaling networks.MS-based phosphoproteomics can be considered as the keytechnique in these ongoing research efforts, albeit not with-out drawing on other techniques such as in vitro phospho-rylation assays or chemical-genetic approaches. Importantly,in contrast to techniques relying on phosphoepitope-specificantibodies [10], phosphoproteomics by MS represents anunbiased approach capable of monitoring cellular phospo-rylation events in the absence of a priori knowledge. AlthoughMALDI-MS is occasionally used for phosphopeptide analysisin protein samples of low complexity [11], we focus here onphosphoproteomics studies performed on LC-ESI-MS sys-tems, as this setup enables the most comprehensive analysisof the complex peptide mixtures encountered in large-scalephosphoproteomics analysis. We will further address thecurrent concepts for defining protein kinase-substrate inter-actions and discuss the importance of relevant com-plementary techniques for the field of phosphoproteomics.Moreover, LC-MS-based strategies have largely superseded2-DE combined with MS in the field of phosphoproteomics.The latter has been discussed by Morandell et al. [12] and isnot covered in this article. Several other excellent reviewsabout protein phosphorylation research have been publishedrecently [13–17]. However, major studies and developmentsare being constantly reported in this rapidly growing field.Here, we review these new results in the context of the mostimportant aspects of contemporary phosphoproteomics.

2 MS-based phosphopeptide analysis andidentification

Recent advances in LC-MS-based phosphopeptide identifica-tion have been propelled by the introduction of new types ofhybrid mass spectrometers, which consist of a linear IT as afront end coupled to either Fourier transform-ion cyclotronresonance (LTQ-FT-ICR) or orbitrap (LTQ-Orbitrap) mass

analyzers (Thermo Scientific). These modern instrumentsoffer excellent analytical performance owing to rapid dutycycles, high sensitivity as well as an exceptional average massaccuracy in the sub-ppm range when real-time calibration to“lock mass” ions is implemented [18]. As database searchspace increases by about 15-fold when serine, threonine andtyrosine phosphorylations are allowed as variable modifica-tions, high mass accuracy in the MS mode is particularlyadvantageous for phosphopeptide identification. MS/MSspectra are often acquired in the LTQ part of these hybridinstruments. This strategy enables higher sensitivity andshorter duty cycles compared to fragment ion detection inthe orbitrap mass analyzer, albeit at the cost of lower resolu-tion and mass accuracy [19]. In addition to IT and IT hybridinstruments, quadrupole (Q)-TOF instruments have beenwidely used in phosphoproteomics studies. An approachdesignated MSE has been implemented on the Q-TOFinstruments from Waters, which is based on the concurrentfragmentation of all precursor ions. The resulting complexMS/MS spectra can be de-convoluted as the product ionintensities follow their precursor ion elution profiles mon-itored in the MS mode [20]. This parallel sequencingapproach benefits from the good mass accuracy in the alter-nating MS and MS/MS scans and can enhance the duty cyclecompared to other acquisition modes. However, it remains tobe established whether or how phosphoproteomics analysiscan gain from MSE approaches. Moreover, hybrid triplequadrupole-linear IT instruments such as the QSTAR sys-tem (Applied Biosystems) not only offer strong neutral lossscanning capabilities useful for targeted phosphopeptidefragmentation, but can also be configured for multiple reac-tion monitoring (MRM) for hypothesis-driven monitoring ofphosphorylation events with high sensitivity and reproduci-bility [21].

To specifically select phosphopeptides for fragmentationin LC-MS/MS experiments, precursor ion scanning for char-acteristic phosphotyrosine immonium ions at m/z 216.043or neutral loss-triggered occurrence of PO3

2 at m/z 79 can beperformed in the positive or negative ion modes, respectively[22–25]. Due to the decreased stability of ions in the low m/zrange, informative fragments such as phosphotyrosineimmonium ions are usually not recorded in MS/MS spectragenerated upon collision-activated dissociation (CAD) inquadrupole IT instruments. Recent method developmentsnow permit the detection of low-molecular weight fragmen-tation products by means of pulsed Q dissociation (PQD) inlinear IT or higher-energy C-trap dissociation (HCD) in lin-ear IT-orbitrap hybrid instruments [26, 27]. As demonstratedby Olsen et al. [26] on a LTQ-Orbitrap mass spectrometer,high resolution, full-mass-range MS/MS could be recordedin the orbitrap mass analyzer when peptides were frag-mented by HCD either in the C-trap itself (which is used tostore ions accumulated in the LTQ part prior to their transferinto the orbitrap) or, with even better results, in an additionaloctopole collision cell available in the most recent instru-ment version marketed as LTQ-Orbitrap XL.


4418 T. B. Schreiber et al. Proteomics 2008, 8, 4416–4432

CAD and the analysis of the resulting b- and y-type ionsby MS/MS is the most commonly used fragmentation tech-nique. Upon CAD, phosphoserine- and phosphothreonine-harboring peptides often undergo b-elimination of phos-phoric acid (neutral loss), which is particularly prominent inIT instruments. The resulting MS/MS spectra are dominatedby the neutral loss product and hence suffer from a lack ofsequence-specific information, thus necessitating the acqui-sition of MS3 spectra or multistage activation (pseudo-MS3)of neutral loss product ions [28, 29]. Internal cleavage uponCAD-induced fragmentation can be strongly influenced byboth the amino acid composition as well as PTMs like phos-phorylation, sulfonation and glycosylation, thus frequentlyfailing to deliver continuous fragment ion series. Moreover,cleavage efficiency is highest for small peptides (,20 resi-dues), thus limiting the analysis of longer multi-phospho-rylated peptides.

Electron capture dissociation (ECD) has been developedto preserve PTM and achieve sequence-independent frag-mentation [30], but is restricted to FT-ICR mass spectro-meters. Instead of the near-thermal electrons used in ECD,radical anions with low electron affinities can be used aselectron donors in a method called electron transfer dis-sociation (ETD) developed by Syka et al. [31], which has beenimplemented on IT instruments and is commercially avail-able with the HCTultra II (Bruker Daltonics) or the LTQ-Orbitrap XL ETD (Thermo Scientific). As phosphorylation ispreserved during ETD and the generated MS/MS spectraoften include almost complete c- and z-type ion series, ETDcan provide comprehensive information about peptidesequence and PTM localization, albeit at the cost of reducedion intensities [32]. ETD works best with longer, multiplycharged peptides, facilitating the investigation of multiplyphosphorylated peptides. However, the doubly charged ionspecies commonly fragmented with CAD tend to undergonon-dissociative electron transfer in ETD. To address thislimitation, ETD has been combined with consecutive CAD toimprove overall peptide coverage and identification fromcomplex mixtures [33, 34]. ETD has recently been imple-mented as a powerful fragmentation technique for phos-phoproteomics applications [35, 36]. In Saccharomyces cerevi-siae extracts, 1252 phosphorylation sites could be detectedfrom as little as 30 mg of total protein [35].

3 Quantification strategies inphosphoproteomics

Most approaches in quantitative proteomics rely on the spe-cific incorporation of stable isotopes, which are used tointroduce defined mass increments into proteolyticallyderived peptides from different cellular states. As the iso-topic variants of chemically identical peptides usually co-elute from RP columns, the relative intensities of parental orreporter ions can be recorded in MS or MS/MS spectra,respectively, thereby enabling relative quantification of indi-

vidual peptides in LC-MS experiments. Here, we provide anoverview of stable isotope-based quantification methods thathave been successfully applied in phosphoproteomics stud-ies. For more detailed surveys of further aspects associatedwith this topic, we would like to refer to recent review articles[37–40]. In phosphoproteomic applications, the accuracy andreliability of the quantification approach is of key impor-tance, in particular when individual peptide species arequantified to monitor site-specific phosphorylation changes.To minimize potential variations that can be introduced byparallel MS sample preparation, isotope encoding at an earlystage, ideally done already in vivo by metabolic incorporationhas considerable advantages. The differential labeling ofproteomes can be effectively accomplished with the SILACapproach (stable isotope labeling with amino acids in cellculture) devised by Mann and coworkers (Fig. 1A) [19, 38,39]. SILAC relies on the almost complete and specific incor-poration of isotopic variants of essential amino acids, whichare supplied with the cell-culture medium. To perform com-prehensive phosphopeptide quantification, it is necessarythat almost all peptides ultimately generated by proteolyticdigestion are labeled. Therefore, cultured cells are propa-gated in the presence of arginine (normal, 13C6 or 13C6/

15N4-labeled) and/or lysine (normal, 2H4 or 13C6/

15N2-labeled) var-iants for at least five cell doublings until full incorporationthrough protein biosynthesis has occurred [39]. Subsequentdigestion with trypsin then ensures that all generated pep-tides (except those derived from the very carboxy-terminalend) carry at least one arginine or lysine residue. As thechemically identical, isotopic variants typically co-elutefrom RP columns, they are simultaneously recorded ascharacteristic doublets or triplets with defined mass offsetsin MS spectra. The metabolically introduced mass offsets ofat least 4 Da over the respective isotopic counterpartsensure sufficient separation of isotopic envelopes for mostpeptides (except for very long ones). Since their ion inten-sities are representative of relative peptide abundance,quantification can be performed by averaging the respectiveratios for the monoisotopic peaks of the peptide speciesoriginating from the differentially SILAC-encoded proteinsamples over consecutive MS survey scans. Alternatively,the extracted ion chromatograms (XIC) of the isotopicallylabeled peptide variants (the area under the curve of ionintensity plotted versus elution time) are proportional to thepeptide amounts and can be used for relative quantifica-tion. The reliability of MS survey scan-based quantificationschemes in general and SILAC in particular have con-siderably benefited from the introduction of hybrid linearIT-FT-ICR and orbitrap mass spectrometers, as the highresolution provided by these instruments allows to differ-entiate nearly isobaric peptides that otherwise would mergeinto single peaks and thereby give rise to quantificationerrors [18]. Practically, SILAC is rather straightforward forthe majority of cultured mammalian cells that replicate ingrowth medium supplemented with dialyzed serum. How-ever, SILAC-based, quantitative phosphoproteomics is not



Figure 1. Two major quantification strategies in phosphoproteomics. (A) Principle of SILAC-based quantification. Up to three cell popula-tions can be differentially labeled by metabolic incorporation of isotope-containing forms of arginine and lysine. Upon cell lysis, extractscan be combined prior to further MS sample preparation steps. The isotopic peptide variants can be distinguished and quantified in MSspectra due to their defined mass offsets (14/18 Da for lysine, 16/110 Da for arginine). (B) Isobaric iTRAQ reagent-derived tags arechemically attached by NHS-chemistry to free amino groups after tryptic digestion. The tags are fragmented during MS/MS, generatinglabel-specific reporter ions that are detected and quantified in MS/MS spectra.

restricted to mammalian systems and has been success-fully applied to yeast-cell analysis [41]. Some additionalefforts are required to establish culture conditions for cellsrelying on low-molecular weight growth factors that arelost during dialysis [39, 42]. Moreover, certain cell linesmetabolically convert arginine to proline. In these cases, itis favorable to carefully titrate the arginine concentration inorder to minimize such a diversion of isotopic label, whichresults in satellite peaks for labeled, proline-containingpeptides and thereby compromises quantification accuracy[39]. Alternatively, both experimental and mathematicalstrategies have been reported that can correct for quantifi-cation errors caused by cellular arginine to proline conver-sion [41, 43].

In contrast to peptide mixtures from unlabeled material,sample complexity increases by two- and threefold in doubleand triple-labeling SILAC experiments. Moreover, peptideswith intensity values close to the background level might beunequivocally identified but prove hard to quantify with high

accuracy. Therefore, the overall number of identified andquantified peptides will be reduced in SILAC experiments,which can be compensated by additional sample pre-frac-tionation or prolonged elution gradients in combination withLC-MS/MS in the data-dependent acquisition (DDA) mode.Although a maximum of three different conditions can becomparatively evaluated in an individual SILAC experiment,further multiplexing is possible by merging quantitativedatasets from, for example, two triple labeling experimentsthat have one shared condition as a common reference. Suchan extension allows the comparative analysis of five differentsamples and has been employed to record temporal profilesof phosphopeptide and -protein abundance [19, 44].

The same quantification principle as for SILAC can beapplied to monitor individual phosphorylation sites by add-ing synthetic, isotopically labeled peptide variants as internalstandards. This absolute quantification (AQUA) strategy canbe used to measure the absolute amounts of pre-selectedphosphopeptides in proteolytic digests, but not necessarily in



cells, as losses during protein extraction and further sampleprocessing are not accounted for in the AQUA approach [45,46].

SILAC has the obvious advantages that metabolic incor-poration of isotope tags is highly specific and that samplescan be combined immediately after lysis, which eliminatesthe risk of introducing quantitative errors during furthersample processing [42]. These aspects contribute to highquantification accuracy and reliability, which makes SILACparticularly useful for the quantitative assessment of PTMsuch as protein phosphorylation. In addition to SILAC-enabled phosphoproteomics studies through site-specificarginine and/or lysine incorporation, other variants ofmetabolic tagging have been described such as the targetedquantitative analysis of phosphotyrosine-containing pep-tides upon 13C9-tyrosine labeling and general 15N/14Nencoding of proteins by means of isotopically enrichedamino acid mixes or media [47, 48]. Data analysis in thelatter approach is complicated by the variable mass offsetsfor different peptide pairs (depending on the number ofnitrogen atoms) and changes in the isotopic distributionpattern caused by a relative isotope abundance of less than100% (due to partial labeling of peptides possessing manynitrogen atoms) [49].

However, metabolic labeling is not always an option (forexample, for primary tissue material), and in these caseschemical tagging strategies provide useful alternatives. Alarge variety of chemical labeling strategies has been de-scribed over the last years that are conceptually similar toSILAC with respect to the extraction of quantitative infor-mation from MS scans (for a recent review, see [40]). How-ever, only few of them have been convincingly applied to thephosphoproteomics analysis of biological samples. As thesite-specific analysis of PTM necessitates the labeling of allproteolytically generated peptides, chemical tagging ofamino, carboxyl or phosphate groups represent obviousstrategies. The concomitant tagging of peptide N termini ande-amino groups of lysine residues can be accomplished by N-hydroxysuccimide (NHS) chemistry. Formation of NHS-esters with a reagent termed N-isotag introduces a specificmass increment of 6 Da through covalent linkage of either“light” g-aminobutyric acid or a deuterium containing“heavy” variant [50, 51]. Alternatively, the C termini of pep-tides together with side chain carboxyl groups of aspartateand glutamate acids were modified by esterification witheither normal or deuterated methanol in previous phospho-proteomics studies [52–55]. However, it has to be taken intoaccount that deuterated peptides can elute earlier in LC-MSthan their non-deuterated counterparts. Depending on thecomposition of the peptide and the tagging reagent, thesedeuterium isotope effects can have a significant impact onpeptide binding to the RP chromatography resin, thusnecessitating XIC-based quantification for accurate meas-urement of relative peptide abundance [56, 57]. Notably,peptide labeling with 15N, 13C and 18O has no significanteffect on chromatographic retention. The latter isotope has

been utilized to some extent in phosphoproteomics to incor-porate 18O versus 16O from water by an enzymatic exchangereaction catalyzed by trypsin, which is typically performed ina second incubation step after proteolytic cleavage and intro-duces a mass offset of 4 Da through incorporation of two 18Oonto C-terminal carboxylates [58, 59].

All aforementioned approaches have in common thatquantification is based on the intensity values of parentalpeptide ions in MS spectra. In contrast, isobaric taggingusing the amine-reactive iTRAQ reagents results in differ-entially labeled peptides of identical mass and has gainedpopularity in phosphoproteomic applications [60–62].Chemical coupling is achieved through NHS chemistry,similar to the N-isotag reagent. Isobaric tags introduced viaiTRAQ consist of differentially labeled reporter and balancergroups, which add up to a constant mass and thereby resultin peptide adducts undistinguishable in MS survey scans.Thus, apart from peptide species that might result from sidereactions or incomplete labeling, spectral complexity is notelevated upon combination of iTRAQ-labeled peptide sam-ples. Only upon peptide fragmentation, reporter ions of dif-ferent m/z values are generated and can be recorded in thelow m/z range, with their intensities reflecting the relativepeptide amounts in the compared samples (Fig. 1B). Thistechnique allows multiplexing and was initially introducedwith four tags generating reporter ions of 114.1 to 117.1 Da[60]. Recently, by increasing the size of the balancer group,isobaric reagents with eight distinct reporter ion masses inthe range of 113.1 to 121.1 were described, omitting the massof 120.1 to avoid interference by the phenylalanine immo-nium ion at an m/z value of 120.08 Da [63]. Due to the low-molecular weight cut-off of MS/MS spectra acquired uponCAD in IT mass spectrometers, iTRAQ was mostly imple-mented on Q-TOF instruments. Recently, quantification ofiTRAQ-labeled peptides was shown to be feasible on a linearIT upon careful adjustment of the applied collision energyusing PQD as fragmentation technique [27]. In addition toPQD, the recently introduced higher-energy C-trap dissocia-tion on the LTQ-Orbitrap provides the opportunity to detectand quantify iTRAQ reporter ions in MS/MS spectra recor-ded in the orbitrap mass analyzer [26]. These technicaladvances now enable the implementation of iTRAQ-basedquantification on powerful hybrid IT-orbitrap instrumentsand have considerable potential for future phosphopro-teomic applications. However, two potential limitationsassociated with iTRAQ labeling have to be kept in mind,especially when quantifying individual peptides in highlycomplex phosphopeptide samples: First, quantification isoften based on single measurements in contrast to repeatedquantification across the chromatographic elution profile innon-isobaric labeling approaches such as SILAC. Secondly,as a range of typically up to several m/z units is selected toisolate peptides for fragmentation, all analytes in this m/zwindow can contribute tag ions to the recorded MS/MSspectra and thereby compromise quantification accuracy, inparticular for low intensity peptides.



In addition to the introduction of isotopically distin-guishable mass tags, label-free approaches have been appliedto a lesser extent in quantitative phosphoproteomics. Oneapproach is based on calculating XIC ratios of peptides fromseparate LC-MS experiments and often includes an addi-tional normalization step [64–67]. For example, Cutillas et al.[65] added defined amounts of standard proteins just prior todigestion with trypsin, and the resulting, proteolyticallyderived peptides were used as references to account for run-to-run variability. Finally, the simple and straightforwardspectral counting approach, in which total numbers ofacquired MS/MS spectra assigned to proteins are used as aread-out, was recently employed as a semi-quantitativemeasure of phosphoprotein abundance [68, 69].

4 Targeted proteomics analysis ofphosphotyrosine-mediated signaling

As established in the classical study by Hunter and Sefton[70], phosphorylation on tyrosine residues accounts for only0.05% of cellular protein phosphorylation and is thus by twoto three orders of magnitude less frequent than proteinthreonine (10%) and serine (90%) phosphorylation. How-ever, despite its relative low cellular abundance, regulatedtyrosine phosphorylation is critically involved in most mem-brane-proximal signal-transduction processes [2]. Its overallimportance in higher organisms is further exemplified bythe fact that almost one fifth of the kinome encodes for pro-tein tyrosine kinases (PTK). Importantly, overexpression ormutational activation of PTK drives many human malig-nancies and both cytoplasmic (such as the Bcr-Abl fusionprotein) and transmembrane-spanning (such as the epi-dermal growth factor receptor family members EGFR andHER2) tyrosine kinases are being successfully targeted innew therapeutic regimens of human cancers [5, 71, 72].

Since the larger size of phosphotyrosine makes thismodified amino acid much more immunogenic than phos-phoserine or –threonine, excellent antibodies are availablefor the purification of tyrosine phosphorylated protein andpeptide species from complex cellular extracts. In fact, phos-photyrosine-specific antibodies efficiently compensate forthe low cellular abundance of phosphotyrosine and haveserved as essential enrichment tools in all quantitative pro-teomics studies on regulated tyrosine phosphorylationreported to date. These studies analyzed ligand-activatedsignaling through a wide range of transmembrane receptorspossessing intrinsic tyrosine kinase activity (including stud-ies on EGFR [44, 62, 73], HER2 [74, 75], platelet-derivedgrowth factor receptor (PDGFR) [76], insulin receptor [77],FGFR [78] and EphB2 [79]) as well as through various recep-tors that utilize associated, cytoplasmic kinases for signalpropagation [53, 55, 64, 80]. Moreover, phosphotyrosine-spe-cific proteomics provides a straightforward way to monitorcellular responses upon treatment with low-molecularweight antagonists of tyrosine kinase activity [68, 81, 82]. Two

different experimental strategies can be distinguished inwhich enrichment with phosphotyrosine-specific antibodiesis performed either before or after proteolytic digestion(Fig. 2).

The first approach involves the precipitation of intactproteins and their associating binding partners. Usually,enriched protein samples are resolved into various molecularweight fractions by gel electrophoresis, which are then sub-jected to trypsin digestion and further analyzed by LC-MS/MS for protein identification. Together with quantitative MS,this experimental strategy can be employed to comparephosphotyrosine-dependent signaling between different cel-lular states [48, 74, 76, 78, 79, 82] or even analyzing it withtemporal resolution [44, 65, 83]. For example, by employingthree different isotope variants of arginine in two parallel,triple-labeling SILAC experiments, Mann and coworkers [44]quantified five different time points in ligand-induced EGFRsignaling. In addition to recapitulating almost all previouslyknown downstream components in just one analysis, thisstudy demonstrated the power of proteomics strategies toreveal new components of phosphotyrosine-based signaltransmission, even for the most intensely characterized sig-naling networks such as those controlled through EGFRfunction. The same strategy was employed to compare

Figure 2. Principal enrichment strategies for proteome-wideanalysis of tyrosine phosphorylation. A complex sample includ-ing a minor sub-population of tyrosine-phosphorylated proteinscan be directly digested and resulting phosphotyrosine-contain-ing peptides can be enriched by immunopurification on the pep-tide level. The resulting peptide fraction can either be directlyanalyzed or subjected to a consecutive IMAC step to furtherreduce the amount of non-phosphorylated peptides. Alter-natively, intact tyrosine phosphorylated proteins and their inter-action partners can be purified by immunoprecipitation withphosphotyrosine-specific antibodies. The enriched proteins canbe either proteolytically cleaved prior to final phosphopeptideisolation by IMAC or, alternatively, separated by gel electropho-resis prior in-gel digestion and LC-MS analysis.



EGF- and PDGF-induced changes of the phosphotyrosine-dependent proteome in mesenchymal stem cells [76]. In thiscell system, EGF treatment induces a differentiation pro-gram resulting in osteoblast formation, whereas PDGFstimulation has no such effect. This biological outcome wasfound to correlate with differential activation of phosphati-dylinositol 3-kinase (PI3K) upon PDGF treatment. Remark-ably, PI3K was identified as a critical effector molecule sup-pressing the differentiation process, based on evidence thatpretreatment with selective PI3K inhibitor conferred EGF-like differentiation potential to PDGF both in cell culture andin an animal model [76]. In general, quantitative data of pro-tein abundance in anti-phosphotyrosine immunoprecipi-tates reflects the regulation of phosphotyrosine-containingprotein complexes, but does not differentiate between directtyrosine kinase substrates and associating protein factors.Notably, site-specific changes of tyrosine phosphorylationmight not be detected in the case of a constitutive phospho-tyrosine present elsewhere in a protein. This potential lim-itation can be addressed to some extent and more compre-hensive data about the individual sites of tyrosine phospho-rylation can be acquired by adding a second enrichment stepon the peptide level, for example by performing immobilizedmetal affinity chromatography (IMAC) on tryptic digests(Fig. 2). Several quantitative studies on T cell signaling havecombined this sequential enrichment of phosphotyrosine-containing peptides with methyl esterification prior toIMAC. This reaction not only introduces stable isotope tags,but can also reduce unspecific binding of acidic peptides inIMAC enrichments [53–55]. However, it is noteworthy thatinterpretation of quantitative data about individual phos-photyrosine site changes can become complicated by apply-ing consecutive enrichment steps.

Alternatively, immunoaffinity purification on the level oftyrosine-phosphorylated peptides offers the possibility to di-rectly measure site-specific changes [62, 64, 68, 73, 75, 77, 80,81, 84]. Potential limitations of this strategy derive from thefact that some tyrosine-phosphorylated proteins can escapedetection, for example if they are solely represented byphosphotyrosine-containing peptides outside the detectablem/z range. The immunoprecipitation of phosphotyrosine-containing peptides can be less efficient than the immuno-precipitation of intact proteins, thus requiring more startingmaterial to attain the same level of overall analytical sensi-tivity. Additional phosphopeptide enrichment by IMAC hasbeen used in combination with an initial anti-phosphotyr-osine immunoprecipitation step to further enrich for tyro-sine phosphorylated peptide species prior to LC-MS analysis[62, 64, 73, 75, 77, 80]. By combining such a two-step enrich-ment of tyrosine-phosphorylated peptides with iTRAQ-basedquantitification, White and coworkers [62] initially appliedthis strategy to generate temporal profiles of individual tyro-sine phosphorylation sites upon EGF treatment. Interest-ingly, clustering analysis by means of self-organizing mapsrevealed sub-groups of tyrosine residues with similar tem-poral phosphorylation profiles. For example, clusters com-

prising immediate-early and more delayed signaling eventscould be clearly distinguished, with the latter cluster includ-ing many known factors involved in receptor-mediatedendocytosis. These and other bioinformatic approaches cansuggest potential roles for poorly understood proteins show-ing similar behavior as well characterized ones, thereby gen-erating testable and high-quality hypotheses for furtherfunctional validation of regulated phosphorylation events[62]. As further shown for EGFR signaling, the manageablenumber of phosphotyrosine-containing peptides makes thisPTM particular amenable for targeted analysis by MRM,which does not suffer from the high run-to-run variability ofpeak selection for MS/MS fragmentation inherent to thecommonly used DDA mode of LC-MS analysis [21, 73].MRM, however, requires a priori knowledge about the pep-tides to be analyzed, such as chromatographic elution timeand the m/z ratios of peptide precursor ions as well as ofcharacteristic fragments generated during MS/MS. Wolf-Yadlin et al. [73] reported a strategy in which informationabout tyrosine phosphorylated peptides was first acquired inthe DDA mode and could then be used to construct andimplement a “tailor-made” MRM method on a triple-quad-rupole mass spectrometer. Remarkably, the experimental re-producibility of the MRM approach was as high as 88%,compared to only 34% in the DDA mode. This enabledrobust multiplexing of quantitative data across two iTRAQexperiments reflecting seven different time points in an EGFtime course [73].

The enhanced multiplexing capabilities provided byDDA-MRM method combinations are likely to prove partic-ularly useful when temporal profiles of tyrosine phosphoryl-ation are recorded in the comparative analysis of differentgrowth factors and/or cell systems, which has been reportedfor DDA-based MS. As shown for EGF and heregulin (whichactivates HER2 signaling HER2/HER3 heterodimer forma-tion) stimulation of either wild-type or HER2-overexpressingcells, bioinformatic analysis enabled to relate quantitativedata on tyrosine phosphorylation to the differential induc-tion of cell migration and cell proliferation for all four cellline/growth factor combinations [75]. Strikingly, clusteringanalysis and partial least squares regression (PLSR) model-ing revealed a subset of tyrosine phosphorylation events thatshowed a strong correlation with either one of the two orboth biological outcomes. Further modeling efforts on thesedata extracted nine highly relevant phosphorylation eventson just six proteins, whose regulation provided enoughinformation to predict cell behavior in this model system [75,85]. It will be interesting to learn how quantitative data aboutphosphotyrosine-dependent signaling can be used in thefuture to generally predict cell type- and ligand-specific bio-logical outcomes or the responsiveness of cancer patients totargeted therapies, for example by gaining a better under-standing of relevant targets driving tumor genesis and sur-vival [86]. As recently shown in an extensive phosphopro-teomics survey across 41 non-small cell lung cancer(NSCLC) cell lines and 150 NSCLC tumors, the technical



feasibility of acquiring large datasets of cellular tyrosinephosphorylation has been impressively demonstrated [68].By using a semi-quantitative spectral counting approach fortyrosine-phosphorylated peptides, the overall prevalence ofphosphorylated PTK and their substrates was assessedacross all samples and used as a measure to cluster tumorsinto several groups characterized, for example, by distinctPTK profiles [68]. In addition to validating known oncogenickinases in NSCLC such as the EGFR and Met receptor tyro-sine kinase (RTK), additional RTK such as ALK, ROS,PDGFRa and discoidin domain receptor 1 (DDR1) were fre-quently identified with tyrosine phosphorylation levels intumor specimens. Interestingly, DDR1 also emerged as themost widely expressed activated RTK with its expressionfound in about 40% of all analyzed tumor samples. As DDR1was recently reported as a high affinity target of the marketedkinase inhibitor imatinib mesylate (Gleevec), it will be veryimportant to gain a better understanding of DDR1 functionin tumor biology given that a targeted therapy is alreadyavailable [87]. A further major outcome of the study byRikova et al. [68] was the sheer number of more than 4500phosphotyrosine sites found on more than 2700 proteins,despite the fact that tyrosine is the by far least abundantphosphorylated amino acid. This unexpected complexity ofthe phosphotyrosine-dependent proteome further indicatesthat phosphotyrosine-based signaling can be highly diverseand potentially fulfill a wide range of regulatory functions ina cell-type specific manner.

5 Current concepts and strategies in large-scale phosphoproteomics

Despite the utility and straightforwardness of experimentalstrategies slanted towards the analysis of protein tyrosinephosphorylation, the vast majority of cellular phosphoryla-tion events occurring on serine and threonine residues arenot monitored by these specific approaches. The con-comitant analysis of all three types of protein phosphoryla-tion poses considerable challenges, in particular when highlycomplex peptide mixtures are generated from un-fraction-ated cell extracts. The common notion that phosphopeptideionization is rather inefficient and further suppressed in thepresence of prominent non-phosphorylated peptide speciescould not be upheld upon systematic examination [88].However, non-modified peptides are preferentially selectedfor MS/MS in the DDA mode due to their higher abundanceover phosphopeptides, which mostly result from sub-stoi-chiometric phosphorylation events. To address this key issuein phosphoproteomics, a variety of fractionation strategieshave been developed to reduce sample complexity in con-junction with selective phosphopeptide and/or phosphopro-tein enrichment.

On the protein level, sample fractionation has been con-ducted by methods such as gel electrophoresis [89], immu-noprecipitation with phosphoserine/phosphothreonine-

selective antibodies [90] or protein IMAC [22]. Moreover,fractionation protocols for the isolation of either functionalprotein classes or organelle-specific protein subsets havebeen implemented in phosphoproteomics studies [59, 87, 89,91]. After proteolysis, peptide fractionation has been per-formed with phosphomotif-specific antibodies [92], by strongcation exchange chromatography [93], IEF [47] or free flowelectrophoresis (FFE)-IEF [94]. As these methods usually donot sharply discriminate between phosphopeptides and non-phosphopeptides, they have further been combined with ad-ditional phosphopeptide-selective enrichment. In addition toIMAC with chelated metal ions (Fe31, Ga31, Zr41) [95-97],affinity-based enrichment with TiO2 [98, 99] or ZrO2 [100]microspheres in the presence of dihydroxybenzoic, phtalic,glycolic or lactic acid has recently gained popularity based onresults that these acidic additives considerably enhance theselectivity of phosphopeptide absorbance [101–104]. Further-more, reversible covalent linkage by means of phosphor-amidate chemistry (PAC) has been reported to permit theefficient isolation of phosphorylated peptide species [54].

As recently demonstrated by Bodenmiller et al. [94, 103],fractionation of tryptic peptide samples by IMAC, TiO2 orPAC purification methods resulted in distinct, albeit to someextent overlapping sets of phosphopeptides. These resultscreated a rationale for using these different techniques inparallel to obtain maximum phosphopeptide coverage(Fig. 3A). Indeed, when all were applied to 42 fractionsobtained by FFE-IEF of a peptide mixture from different cellstates, more than 10 000 distinct phosphorylation sites couldbe identified in cultured Drosophila melanogaster cells. Thiscurrently largest phosphorylation dataset from a single bio-logical source was deposited in a searchable spectral library

Figure 3. Phosphoproteomics workflows relying on differentphosphopeptide enrichment strategies to reduce sample com-plexity, as, for example, applied in the studies by (A) Bodenmilleret al. [94], (B) Li et al. [111], (C) Olsen et al. [19] and (D) Matsuokaet al. [92].



and mapped on the protein components of functional sig-naling networks, thus providing a useful resource for follow-up studies [94].

A considerable number of “qualitative” phosphopro-teomics studies reporting hundreds to thousands of phos-phorylation sites have been published [22, 36, 91, 105–110],such as the analysis of mouse liver [93] (5635 non-redun-dant phosphorylation sites) and Saccharomyces cerevisiae[111] (2288 non-redundant phosphorylation sites, Fig. 3B)phosphoproteomes relying on an initial fractionation ofpeptides by SCX chromatography or proteins by gel elec-trophoresis to reduce sample complexity prior to a finalIMAC step, respectively. These two studies further imple-mented a software algorithm designated Motif-X to extractboth known as well as novel phosphorylation motifs fromthe large-scale datasets [112]. As exemplified by these andother studies, considerable progress has also been made inthe automation of data processing in phosphoproteomicsprojects. In an approach that recently gained popularity,MS/MS spectra are searched against concatenated data-bases composed of all protein sequences in the normal andreversed orientation. Based on the proportion of spectraassigned to random spectra derived from reversed peptidesequences, an estimated false-discovery rate (FDR) forincorrect peptide assignments can be determined acrossthe whole dataset. Subsequently, the dataset is filteredaccording to criteria such as search score and mass devia-tion to reduce the overall FDR to typically less than 1% [19,113, 114]. Moreover, to circumvent the time-consumingmanual validation of phosphorylation site localization, analgorithm initially described by Olsen and Mann to assignprobability scores to MS3 spectra was implemented for

phosphopeptide analysis. For all possible combinations ofserine, threonine or tyrosine phosphorylation, the algo-rithm computes probability-based scores from the num-bers of matches of expected and observed fragment ions topinpoint the most likely phosphorylation site(s) [19, 29,115].

In addition to fully computational data processing, auto-mation of sample fractionation prior to LC-MS holds greatpromise to increase the reproducibility and throughput ofphosphoproteome mapping efforts. Pinkse et al. [116]reported an optimized chromatography setup that includedthe on-line separation of phosphopeptides on a TiO2 columnand permitted the consecutive analysis of both phosphoryl-ated and non-phosphorylated peptide populations in anautomated fashion.

By defining the phosphorylation site inventory of agiven proteome, the aforementioned studies providedhighly informative catalogs of potential sites of regulationdespite being performed in a non-quantitative fashion.However, only quantitative data of cellular phosphorylationchanges permit the direct identification of regulated phos-phoproteins with potential functional roles in specific sig-naling processes (Table 1). The feasibility of quantitativephosphoproteomics in a large-scale setting was firstdemonstrated by Gruhler et al. [41], who used a SILAC pro-tocol to monitor site-specific phosphorylation changes upontreatment of S. cerevisiae cells with the mating pheromonea-factor. Out of more than 700 quantified phosphopeptides,139 were differentially regulated by more than twofold andcould be assigned to proteins involved in various cellularprocesses such as actin re-organization, transcriptional reg-ulation and cell-cycle control.

Table 1. Quantitative large-scale studies in the field of phosphoproteomics

Organism Cell/Tissue Treatment Labeling Protein enrichment Peptideseparation

Proteins Phospho-sites/peptides

Refer-ence

Human HeLa EGF SILAC Centrifugation(cytosolic/nuclear)

SCX-TiO2 2244 6600 sites [19]

Human HeLa TNF-a 14N /15N – Peptide IEF-IMAC 1934 223 peptides [47]Human K562 Abl kinase inhibitors iTRAQ Affinity purification/PAGE IMAC 1404 379 sites [87]Human 293T Ionizing radiation SILAC – Peptide IP 700 905 sites [92]Human 293 Wnt3a SILAC Phosphoprotein

enrichment/PAGE– 1057 54 sites [117]

Yeast Mec1/Tel1– / –

Alkylating agent Isobarictags

– SCX-IMAC 1109 2689 sites [51]

Yeast – a-factor SILAC – SCX-IMAC 503 729 sites [41]Mouse Brain – iTRAQ Centrifugation (synaptic

membranes)SCX-TiO2 2159 1564 sites [61]

Monkey Cos7 LPA 16O/18O Pseudopodia/cellbodyisolation

IMAC 3509 228 peptides [59]

Arabidopsisthaliana

Suspension cells Xylanase, flg22 14N/15N Centrifugation (plasmamembranes)

SCX- TiO2 472 1172 peptides [118]

Arabidopsisthaliana

Suspension cells Flg22 iTRAQ Centrifugation (plasmamembranes)

SCX-IMAC – 208 peptides [119]



The most comprehensive quantitative study to date ana-lyzed the temporal dynamics of phosphorylation-based sig-naling upon EGF treatment of HeLa cells [19]. By fractiona-tion of total cell lysates into nuclear and cytosolic fractionsfollowed by SCX chromatography on the peptide level andsubsequent TiO2 enrichment, Olsen et al. [19] could quanti-tatively monitor an impressive 6600 phosphorylation sites on2244 distinct proteins (Fig. 3C). Interestingly, with 1.8% ofall phosphorylation sites detected on tyrosine residues, thecellular prevalence of tyrosine phosphorylation appeared tobe considerably higher than originally determined by phos-phoamino acid analysis almost three decades ago [70]. Thisdifference could be due to an overall lower cellular abun-dance of phosphotyrosine-containing proteins and/or to anon average lower stoichiometry of tyrosine phosphorylationevents. As two triple labeling SILAC experiments were com-bined through a shared condition in the study by Olsen et al.[19], five time point profiles were generated for relativephosphopeptide abundance. It was found that 14% of allquantified phosphorylation sites were regulated by morethan twofold upon EGF stimulation. Importantly, therecorded temporal profiles could be assigned to clusters thatwere enriched for functionally related signaling componentsinvolved at different stages of signal propagation or down-regulation. Intriguingly, the majority of all regulated phos-phoproteins contained more than one phosphorylation sitethat was differentially affected, emphasizing the importanceof site-specific analysis in the context of multiple signalsconverging on most cellular signaling components. Site-specific information is not acquired when changes in overallphosphoprotein abundance are recorded. Such a strategybased on phosphoprotein enrichment has been applied in arecent SILAC study, which revealed both known as well asnovel protein factors of Wnt-regulated signaling modules[117]. Moreover, the comprehensive extraction of quantitativeinformation from MS spectra requires high-resolutioninstruments such as ideally LTQ-FT-ICR or LTQ-Orbitrapmass spectrometers. In a quantitative study of tumor necro-sis factor-a signal transduction conducted with a linear IT,only 223 out of 701 phosphopeptides could be quantifiedwith high confidence [47].

Quantitative phosphoproteomics studies upon metabolicisotope labeling are not necessarily limited to mammalian oryeast cell culture systems, as demonstrated by work on earlyelicitor signaling in Arabidopsis thaliana cells [118]. Differ-ential 14N/15N labeling was employed to quantify phospho-rylation events in plasma membrane fractions upon short-term treatment with either bacterial or fungal elicitors ofplant innate immune responses. In addition to revealingcomplex patterns of phosphorylation changes on an NADPHoxidase involved in defense-related reactive oxygen produc-tion, results from this phosphoproteomics analysis furtherrevealed potential molecular mechanisms of protein translo-cation and vesicle transport control upon induction of plantelicitor signaling. Similar results on plant NADPH oxidaseregulation upon bacterial elicitor treatment were obtained in

a study by Nühse et al. [119], who used iTRAQ reagent-basedquantification in a time-course analysis of early signalingevents in this system.

In addition to following phosphorylation changes upongrowth factor treatment, an iTRAQ strategy has beenemployed to quantitatively compare synaptic phosphoproteinsfrom four brain regions, and 16O/18O labeling was used toassess the spatial organization of the phosphoproteome bycomparing fractions from protruding pseudopodia and resid-ing cell bodies in polarized cells [59, 61]. These two studiesdemonstrated the utility of quantitative phosphoproteomics toreveal differential regulation and distribution of phosphopro-teins among different tissues, cell types or cellular compart-ments. Trinidad et al. and Wang et al. [59, 61] further deter-mined relative protein expression in the compared sub-pro-teomes in addition to quantitative phosphopeptide analysis,thus permitting the normalization of phosphorylation forchanges in protein abundance in case both phosphorylatedand non-phosphorylated peptide species were quantified for agiven phosphoprotein. Importantly, this combined informa-tion can be used to determine whether phosphopeptidechanges are due to real phosphorylation/dephosphorylationevents or instead result from altered phosphoprotein abun-dance upon changes in sub-cellular distribution and/or pro-tein expression. As protein translocation and degradation canbe rapidly induced upon growth factor treatment, and sincephosphoprotein expression changes resulting from transcrip-tional regulation can occur within the first hour after stimula-tion, the parallel acquisition of both quantitative proteome andphosphoproteome datasets is likely to become highly relevantfor future signal-transduction analyses.

Despite impressive recent advances resulting in datasetscontaining thousands of phosphorylation sites, these num-bers might still represent a rather incomplete subset of theentire phosphoproteome. It is not yet clear how many of the,700,000 potentially phosphorylatable residues, which arepresent in a mammalian cell, are actually modified, and towhich extent phosphoproteome composition will vary amongthe many different cell types in a higher organism [3]. Keyregulatory enzymes of low cellular abundance, such as manymembers of the protein kinase family, have been under-represented in previous large-scale experiments, thus sup-porting the notion that only partial phosphoproteome cover-age has been attained so far. As site-specific phosphorylationsplay key roles in the activity control of protein kinases, kinase-derived phosphopeptides represent a particular informativesubset of the phosphoproteome. To analyze protein kinaseswith considerably higher analytical sensitivity than possiblefrom total cell extracts, efficient pre-fractionation techniqueshave been reported that employ combinations of immobilizedkinase inhibitors as affinity capture reagents for selectivekinase enrichment [87, 91]. These procedures have also beenimplemented for phosphorylation site analysis and, amongstother techniques to target sub-proteomes of special interest,have considerable potential for signal transduction analysisupon further method optimization.



6 Kinase substrate identification

In order to deduce the molecular architecture of signalingnetworks from quantitative phosphoproteomic data, knowl-edge about the kinase-substrate interactions occurring in agiven cellular proteome is required. Methods such as yeasttwo-hybrid screens, genetic techniques as well as biochem-ical purification strategies have been used to identify indi-vidual kinase-substrate pairs and verify their in vivo relevance(reviewed in [120]). A complete workflow for substrate iden-tification and validation termed KESTREL [121] has beendeveloped that can even account for rather subtle differencesin substrate phosphorylation by closely related kinases.However, the limited throughput of these approaches doesnot allow comprehensive mapping of kinase-substrate inter-actions on a more global scale. A straightforward alternativeconcept involves the determination of short linear sequencemotifs preferentially phosphorylated by recombinant proteinkinases in vitro. The initial implementation of this approachwas reported by Songyang et al. [122], who subjected adegenerated, oriented library of more than 2.5 billion peptidesubstrates to in vitro kinase reactions catalyzed by proteinkinase A (PKA) or cyclin-dependent kinases. Upon enrich-ment of fractionated peptide species by IMAC, Edman se-quencing was performed to determine the preferred aminoacids at the positions surrounding the phosphorylated aminoacid, which then permitted extracting kinase-specific con-sensus motifs. These and related in-solution techniques aswell as peptide microarrays have been extensively used formany years [123]. A more recent implementation of thisstrategy utilized a positional scanning peptide library, inwhich sub-libraries with fixed residues around the phos-phoacceptor site were assayed in parallel for kinase-mediatedphosphate incorporation [124]. Moreover, the integration ofavailable information on the PKA consensus motif in anevolutionary proteomics approach was shown to improvekinase substrate prediction [125].

As an alternative to using peptides for kinase profiling,protein microarrays have proven to be a suitable tool for thein vitro analysis of protein substrate phosphorylation [126–130]. As distal docking sites in addition to the phos-phoacceptor region often influence the strength and speci-ficity of substrate recognition, in vitro phosphorylation ofprotein substrates is closer to the physiological situationthan reflected on peptide arrays. The most comprehensiveprotein microarray study to date was performed by Ptacek etal. [128], who assayed 87 yeast protein kinases against morethan 4000 yeast proteins and identified about 4200 phos-phorylation events on 1325 proteins. The acquired in vitrodata indicated specific differences in substrate recognition,even among closely related kinases or the same kinase incomplex with different regulatory subunits. Of all observedkinase-substrate interactions, 33% of the identified pairslocalized to the same cellular compartment and 18% couldbe mapped to the same functional category. However, astested for a subset of six kinases and their identified sub-

strates, only about 10% of these interactions could be ver-ified in intact yeast cells. Owing to limitations of the cellularassays used in these validation efforts, some of the observedin vitro interactions might have escaped detection in intactcells. Nevertheless, many factors contributing to cellularsubstrate recognition are not recapitulated on recombinantprotein arrays, as recently reviewed by Ubersax and Ferrell[3]. The local cellular concentrations of protein kinases andtheir substrates, which result from their actual expressionlevels and their sub-cellular localization profiles, are vastlydifferent in cells than in in vitro assays. In addition, primingphosphorylation events by other kinases or essential scaf-folding proteins are missing, and cellular competitionamong different substrates for being phosphorylated by akinase is not adequately represented on recombinant pro-teome chips.

Despite the aforementioned limitations, useful data hasbeen obtained by peptide- and protein-based in vitro sub-strate approaches. Linear substrate phosphorylation motifshave been determined for a considerable number of proteinkinases, and all available information has been recentlycompiled by Amanchy et al. [131]. Such linear kinase con-sensus motifs can simply be matched to the sites of phos-phorylation determined in phosphoproteomics experimentsto assign potential upstream kinases [19]. Alternatively,identified sites can be analyzed with a variety of softwaretools for kinase prediction. Several algorithms have beendeveloped to predict general or kinase-specific phosphoryla-tion sites within proteins, such as Scansite 2.0 [132], Pre-diKin [133] NetPhos/NetPhosK [134–136], KinasePhos 2.0[137], and others [138]. Some of these are based on peptidelibrary studies (e.g. Scansite 2.0), rely on the primarysequence of the protein kinases catalytic domains (PrediKin)or on published phosphorylation sites (NetPhos/NetPhosK).A more detailed compilation of computational tools anddatabases for phosphorylation analysis, which are publiclyavailable as web resources, has been published elsewhere[17, 135]. The recently reported approach denoted NetworKinaugments consensus phosphorylation motifs with additionalcontextual information about protein-protein interactions,(co-)expression and sub-cellular (co-)localization, aiming forhigher prediction accuracy.

Although these useful predictive tools are still limited intheir precision and comprehensiveness, accuracy willimprove as they can draw on constantly growing knowledgeand datasets, and in particular on emerging experimentalconcepts to define cellular kinase-substrate relationships bymeans of quantitative proteomics techniques. These strate-gies are exemplified by two recent studies on protein kinasesignaling in the DNA damage response (DDR) [51, 92]. Mat-suoka et al. used a large collection of different phosphoepi-tope-specific antibodies that had been generated againsteither known substrates of the human DDR kinases, ataxiatelangiectasia-mutated (ATM) kinase and ATM and Rad3-related (ATR) kinase, or sequences encompassing phospho-rylated forms of the SQ/TQ motifs selectively recognized by



these kinases. Upon SILAC labeling of 293Tcells and irradia-tion of one cell population to trigger the DDR, tryptic digestswere prepared and subjected to parallel peptide immunopre-cipitations with all available phosphoepitope-specific anti-bodies (Fig. 3D). Because these fractionation tools exhibit aconsiderable degree of cross-reactivity, about 700 direct sub-strates of ATM and ATR could be identified based on theirinduced phosphorylation within SQ/TQ motifs [92]. In addi-tion to recapitulating interactions with known DDR net-works, further functional annotation revealed many proteinmodules that comprised direct ATM/ATR substrates and hadnot been previously linked to the DDR.

In vivo targets of DNA damage checkpoint kinases havealso been the focus of work reported by Smolka et al. [51].Using N-isotag reagent-based quantification, phosphoryla-tion changes upon DNA damage were compared in wild-typeyeast cells versus mutant strains lacking either the ATR/ATMorthologs Mec1/Tel1 or their downstream target kinaseRad53 (ortholog of human checkpoint kinase 2). Out of atotal of 2689 identified phosphorylation sites, 62 underwentMec1/Tel1-dependent phosphorylation upon DNA damageand 32 of those were found to be regulated by the Mec1/Tel1downstream effector Rad53. Interestingly, 24 out of theremaining 30 Mec1/Tel1-dependent regulated sites occurredin the sequence context of the above-mentioned S/T-Q con-sensus motif, thereby fulfilling the criteria of direct Mec1/Tel1 substrate sequences.

Genetic ablation represents a valid strategy for phospho-proteomic substrate identification in case a kinase is non-essential and inactive under normal growth conditions and isonly activated by an external stimulus, such as ATM/ATRupon DNA damage. However, kinase inactivation upongenetic knockout or RNA interference does not discriminatebetween catalytic and non-catalytic functions of proteinkinases. Moreover, due to the unavoidable time delay be-tween, for example, siRNA transfection or shRNA expressionand subsequent cellular analysis, it might become impos-sible to dissect whether observed protein phosphorylationchanges result from direct kinase inhibition or are instead aconsequence of more general effects on cellular physiology(such as kinase-related effects on cell proliferation or divi-sion). Therefore, to establish kinase-substrate relationshipswithin signal-transduction networks, rapid pharmacologicalinterference by means of fast-acting, low-molecular weightantagonists has obvious advantages. However, small mole-cule inhibitors of protein kinases are often relatively unse-lective, which could considerably complicate data interpreta-tion in phosphoproteomics experiments [139]. Strategies toobviate these potential complications could draw fromchemical genetics approaches developed by Shokat and co-workers [140, 141]. By mutating a conserved, usually rela-tively large “gate keeper” amino acid to a small glycine oralanine residue, access to a new cavity is created near theATP binding pocket of protein kinases. Such an enlargedbinding pocket, which is not present in naturally occurringkinases, can accommodate kinase inhibitors with an addi-

tional, space-filling substituent. Thus, mutant kinase allelescan be selectively inhibited by pharmacological interferencein intact cells. This elegant concept has been adapted for aconsiderable number of protein kinases and found manyapplications in cell biology research [142, 143]. Moreover, incases of kinases that became inactive upon mutation of the“gate keeper” amino acid, mutation of second site suppressorresidues was demonstrated to restore catalytic activity [144].Exemplary studies include substrate identifications of var-ious cyclin-dependent kinases [145, 146] as well as yeast polo-like kinase Cdc5 [147] and the Yersinia protein kinase A [148].Analog-sensitive kinase inhibitors have previously been usedfor the targeted and hypothesis-driven identification ofsmaller substrate subsets. The unbiased application of thisapproach to large-scale phosphoproteomic substrate analysisholds great potential for the future.

In addition, chemically modified, bulky ATP derivativeshave been used for selective substrate phosphorylation bymutant kinases in vitro [141, 146]. Recently, Allen et al. [142]have reported a new variant employing a bio-orthogonalATPgS analog for the direct thiophosphorylation of sub-strates by sensitized kinase mutants. Upon alkylation ofthiophosphorylated residues, selectively modified proteinswere immunoprecipitated with thiophosphate ester-specificantibodies. Although only one already known Erk2 substratecould be identified when applied to permeabilized cells, thestrategy could become highly useful for defining kinase-substrates relationships upon further method optimization.

7 Outlook

Enormous progress in proteomics has led to powerful newexperimental concepts of analyzing phosphoproteins. Whileautomated phosphopeptide and phosphorylation site identi-fication have dramatically accelerated qualitative phospho-protein analysis, the extraction of reliable quantitative datafrom phosphoproteomics experiments required substantialamounts of time and therefore has often been a major bottle-neck in previous large-scale studies. Ongoing software devel-opments might overcome these earlier limitations [149, 150]and thus bear considerable potential to perform quantitativephosphoproteomics experiments on a time scale quite similarto classical methods of signal-transduction analysis. Thus,with the investigation of phosphorylation-based signalinglikely to become increasingly common on a system-wide level,major challenges for future research will involve the func-tional interrogation of the individual phosphorylation sitechanges on a similar scale. High-throughput RNAi screeningmethods can be used as complementary genomic techniquesto assign functions to regulated phosphoproteins, but havesome limitations with respect to signal transduction analysis[151]. The overall protein function is typically analyzed 24 to48 h after initiation of the knock-down and thus does notnecessarily reflect the functional role of site-specific phos-phorylation events triggered within minutes after, for exam-



ple, growth-factor stimulation. Nevertheless, by accountingfor approach-specific strengths and limitations, the integra-tion of functional genomic and phosphoproteomic datarepresents a powerful strategy for constructing comprehen-sive maps of signaling networks and understanding thefunctional roles of their individual components. Importantly,in combination with refined strategies of bioinformatic pro-cessing and annotation, future signal transduction analysiscan build on datasets of already known phosphorylationevents accessible in rapidly expanding databases such asPhosphoSite, Phosida, and others [17, 152, 153].

Regarding the functional analysis of individual phospho-rylation sites, computational modeling will likely gain impor-tance in addition to targeted studies relying on mutationalanalysis, in particular modeling approaches that link specificregulatory events to cellular phenotypes and behavior [85, 154,155]. Complemented by other, less comprehensive tech-niques of collecting protein data from cells [156], quantitativephosphoproteomics is likely to become the key technology inthe systems biology of cellular signal transduction. In theyears to come, it will be exciting to follow how quantitativephosphoproteomics will expand our understanding of cel-lular signaling processes, and how this knowledge can beemployed to define the underlying molecular mechanisms ofhuman diseases and thus contribute to improved strategiesfor therapeutic intervention and disease management.

We thank Prof. Axel Ullrich for his generous support withfunding from the Department of Molecular Biology, Max PlanckInstitute of Biochemistry. This work was further supported inparts by grants from the Deutsche Forschungsgemeinschaft, theGerman Bundesministerium für Bildung und Forschung(BMBF), and the Novartis-Stiftung für therapeutische For-schung. We further thank our colleagues from the Ullrich andMann departments for many fruitful and stimulating discussions.

The authors have declared no conflict of interest.

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