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A New Approach for Quantitative Phosphoproteomic Dissection of Signaling Pathways Applied to T Cell Receptor Activation*

Open AccessPublished:July 14, 2009DOI:https://doi.org/10.1074/mcp.M800307-MCP200
      Reversible protein phosphorylation plays a pivotal role in the regulation of cellular signaling pathways. Current approaches in phosphoproteomics focus on analysis of the global phosphoproteome in a single cellular state or of receptor stimulation time course experiments, often with a restricted number of time points. Although these studies have provided some insights into newly discovered phosphorylation sites that may be involved in pathways, they alone do not provide enough information to make precise predictions of the placement of individual phosphorylation events within a signaling pathway. Protein disruption and site-directed mutagenesis are essential to clearly define the precise biological roles of the hundreds of newly discovered phosphorylation sites uncovered in modern proteomics experiments. We have combined genetic analysis with quantitative proteomic methods and recently developed visual analysis tools to dissect the tyrosine phosphoproteome of isogenic Zap-70 tyrosine kinase null and reconstituted Jurkat T cells. In our approach, label-free quantitation using normalization to copurified phosphopeptide standards is applied to assemble high density temporal data within a single cell type, either Zap-70 null or reconstituted cells, providing a list of candidate phosphorylation sites that change in abundance after T cell stimulation. Stable isotopic labeling of amino acids in cell culture (SILAC) ratios are then used to compare Zap-70 null and reconstituted cells across a time course of receptor stimulation, providing direct information about the placement of newly observed phosphorylation sites relative to Zap-70. These methods are adaptable to any cell culture signaling system in which isogenic wild type and mutant cells have been or can be derived using any available phosphopeptide enrichment strategy.
      The reversible phosphorylation of serine, threonine, and tyrosine residues directly controls many cellular processes, leading to the activation of a coordinated network of additional phosphorylation events across multiple proteins over time. Clearly, there are benefits to individually identifying and characterizing specific components of a particular pathway, such as a phosphorylation site on a given protein, the kinase responsible for the modification, or the proteins interacting subsequently. However, a thorough understanding of these signaling pathways at the molecular level ultimately requires a global, simultaneous evaluation of these phosphorylation events as they occur over time.
      Currently, the most common method for assessing wide-scale changes in the proteome is two-dimensional gel electrophoresis (
      • Sickmann A.
      • Marcus K.
      • Schäfer H.
      • Butt-Dörje E.
      • Lehr S.
      • Herkner A.
      • Suer S.
      • Bahr I.
      • Meyer H.E.
      Identification of post-translationally modified proteins in proteome studies.
      ), but this methodology is relatively low throughput and not optimal for the analysis of low abundance and hydrophobic signaling proteins (
      • Gygi S.P.
      • Corthals G.L.
      • Zhang Y.
      • Rochon Y.
      • Aebersold R.
      Evaluation of two-dimensional gel electrophoresis-based proteome analysis technology.
      ). Recent publications describe alternate approaches for assessing changes in phosphorylation patterns based primarily on LC/MS methodologies (
      • Beausoleil S.A.
      • Jedrychowski M.
      • Schwartz D.
      • Elias J.E.
      • Villén J.
      • Li J.
      • Cohn M.A.
      • Cantley L.C.
      • Gygi S.P.
      Large-scale characterization of HeLa cell nuclear phosphoproteins.
      ,
      • Ficarro S.B.
      • McCleland M.L.
      • Stukenberg P.T.
      • Burke D.J.
      • Ross M.M.
      • Shabanowitz J.
      • Hunt D.F.
      • White F.M.
      Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae.
      ,
      • Goshe M.B.
      • Conrads T.P.
      • Panisko E.A.
      • Angell N.H.
      • Veenstra T.D.
      • Smith R.D.
      Phosphoprotein isotope-coded affinity tag approach for isolating and quantitating phosphopeptides in proteome-wide analyses.
      ,
      • Olsen J.V.
      • Blagoev B.
      • Gnad F.
      • Macek B.
      • Kumar C.
      • Mortensen P.
      • Mann M.
      Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.
      ,
      • Posewitz M.C.
      • Tempst P.
      Immobilized gallium(III) affinity chromatography of phosphopeptides.
      ,
      • Luo Q.
      • Tang K.
      • Yang F.
      • Elias A.
      • Shen Y.
      • Moore R.J.
      • Zhao R.
      • Hixson K.K.
      • Rossie S.S.
      • Smith R.D.
      More sensitive and quantitative proteomic measurements using very low flow rate porous silica monolithic LC columns with electrospray ionization-mass spectrometry.
      ). A variety of promising purification approaches have been developed to discover hundreds to thousands of phosphorylation sites from complex cell lysates including strong cation exchange/titanium dioxide (SCX/TiO2), IMAC
      The abbreviations used are:
      IMAC
      immobilize metal affinity chromatography
      ADAP
      adhesion and degranulation adaptor protein
      CD
      cluster of differentiation
      Erk1/2
      extracellular signal-regulated kinase-1/2
      ITAM
      immunoreceptor tyrosine activation motif
      ITK
      interleukin-2-inducible T cell kinase
      LAT
      linker for activation of T cells
      Lck
      lymphocyte-specific protein tyrosine kinase
      NTBA
      natural killer-, T- and B-cell antigen
      MAPK
      mitogen-activated protein kinase
      PBS
      phosphate buffered saline
      PH
      pleckstrin homology
      PLCγ1
      phospholipase C gamma 1
      SHP-1/2
      SH2 domain-containing protein tyrosine phosphatase-1/2
      SIC
      selected ion chromatogram
      SILAC
      stable isotopic labeling of amino acids in cell culture
      SKAP55
      src kinase-associated phosphoprotein of 55 kDA
      TCR
      T cell receptor
      Zap-70
      zeta-chain-associated protein kinase 70
      ITIM
      immunoreceptor, the tyrosine-based inhibitory motif
      FTMS
      Fourier transform mass spectrometer.
      1The abbreviations used are:IMAC
      immobilize metal affinity chromatography
      ADAP
      adhesion and degranulation adaptor protein
      CD
      cluster of differentiation
      Erk1/2
      extracellular signal-regulated kinase-1/2
      ITAM
      immunoreceptor tyrosine activation motif
      ITK
      interleukin-2-inducible T cell kinase
      LAT
      linker for activation of T cells
      Lck
      lymphocyte-specific protein tyrosine kinase
      NTBA
      natural killer-, T- and B-cell antigen
      MAPK
      mitogen-activated protein kinase
      PBS
      phosphate buffered saline
      PH
      pleckstrin homology
      PLCγ1
      phospholipase C gamma 1
      SHP-1/2
      SH2 domain-containing protein tyrosine phosphatase-1/2
      SIC
      selected ion chromatogram
      SILAC
      stable isotopic labeling of amino acids in cell culture
      SKAP55
      src kinase-associated phosphoprotein of 55 kDA
      TCR
      T cell receptor
      Zap-70
      zeta-chain-associated protein kinase 70
      ITIM
      immunoreceptor, the tyrosine-based inhibitory motif
      FTMS
      Fourier transform mass spectrometer.
      , and IMAC in tandem with phosphotyrosine peptide immunoprecipitation (
      • Beausoleil S.A.
      • Jedrychowski M.
      • Schwartz D.
      • Elias J.E.
      • Villén J.
      • Li J.
      • Cohn M.A.
      • Cantley L.C.
      • Gygi S.P.
      Large-scale characterization of HeLa cell nuclear phosphoproteins.
      ,
      • Ficarro S.B.
      • McCleland M.L.
      • Stukenberg P.T.
      • Burke D.J.
      • Ross M.M.
      • Shabanowitz J.
      • Hunt D.F.
      • White F.M.
      Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae.
      ,
      • Olsen J.V.
      • Blagoev B.
      • Gnad F.
      • Macek B.
      • Kumar C.
      • Mortensen P.
      • Mann M.
      Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.
      ,
      • Brill L.M.
      • Salomon A.R.
      • Ficarro S.B.
      • Mukherji M.
      • Stettler-Gill M.
      • Peters E.C.
      Robust phosphoproteomic profiling of tyrosine phosphorylation sites from human T cells using immobilized metal affinity chromatography and tandem mass spectrometry.
      ,
      • Cao L.
      • Yu K.
      • Banh C.
      • Nguyen V.
      • Ritz A.
      • Raphael B.J.
      • Kawakami Y.
      • Kawakami T.
      • Salomon A.R.
      Quantitative time-resolved phosphoproteomic analysis of mast cell signaling.
      ,
      • Krüger M.
      • Kratchmarova I.
      • Blagoev B.
      • Tseng Y.H.
      • Kahn C.R.
      • Mann M.
      Dissection of the insulin signaling pathway via quantitative phosphoproteomics.
      ,
      • Schmelzle K.
      • Kane S.
      • Gridley S.
      • Lienhard G.E.
      • White F.M.
      Temporal dynamics of tyrosine phosphorylation in insulin signaling.
      ). These phosphoproteomic methods have been used to survey a large number of phosphorylation sites in a time course after receptor stimulation, where the magnitude of-fold change in phosphorylation and the timing of phosphorylation suggest protein participation and placement within a pathway (
      • Olsen J.V.
      • Blagoev B.
      • Gnad F.
      • Macek B.
      • Kumar C.
      • Mortensen P.
      • Mann M.
      Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.
      ,
      • Cao L.
      • Yu K.
      • Banh C.
      • Nguyen V.
      • Ritz A.
      • Raphael B.J.
      • Kawakami Y.
      • Kawakami T.
      • Salomon A.R.
      Quantitative time-resolved phosphoproteomic analysis of mast cell signaling.
      ,
      • Schmelzle K.
      • Kane S.
      • Gridley S.
      • Lienhard G.E.
      • White F.M.
      Temporal dynamics of tyrosine phosphorylation in insulin signaling.
      ,
      • Salomon A.R.
      • Ficarro S.B.
      • Brill L.M.
      • Brinker A.
      • Phung Q.T.
      • Ericson C.
      • Sauer K.
      • Brock A.
      • Horn D.M.
      • Schultz P.G.
      • Peters E.C.
      Profiling of tyrosine phosphorylation pathways in human cells using mass spectrometry.
      ,
      • Zhang Y.
      • Wolf-Yadlin A.
      • Ross P.L.
      • Pappin D.J.
      • Rush J.
      • Lauffenburger D.A.
      • White F.M.
      Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules.
      ). For example, proteins phosphorylated late after receptor stimulation are expected to represent downstream elements of a pathway whereas rapid phosphorylation is expected in the earlier stages of a pathway, especially at the receptor. Constitutive phosphorylation throughout a receptor stimulation time course is expected for proteins not involved in the pathway (
      • Cao L.
      • Yu K.
      • Banh C.
      • Nguyen V.
      • Ritz A.
      • Raphael B.J.
      • Kawakami Y.
      • Kawakami T.
      • Salomon A.R.
      Quantitative time-resolved phosphoproteomic analysis of mast cell signaling.
      ).
      Although receptor stimulation time course experiments provide clues about placement of phosphorylation sites within a pathway relative to a stimulated receptor, a phosphoproteomic analysis comparing signaling protein null mutants and their reconstituted counterparts would allow for precise placement of novel phosphorylation sites within a signaling pathway relative to signaling landmarks within the canonical pathway (Fig. 1). An ideal quantitative method to perform this analysis would provide both a dense temporal array of information about protein phosphorylation after receptor stimulation as well as precise comparisons between isogenic matched normal cells and cells with altered signaling proteins.
      Figure thumbnail gr1
      Fig. 1Canonical TCR signaling pathway. Established signaling cascades in activated T cells with quantitative Zap-70 null/Zap-70 reconstituted SILAC ratio data represented as heatmaps besides individual proteins. Heatmaps represent averages of five replicate experiments. In the heatmap representation, green represents elevated phosphorylation in response to Zap-70 removal, whereas red represents a decrease in phosphorylation in response to Zap-70 removal. Black represents no change. Blanks in the heatmap indicate that a clearly defined SIC peak was not observed for that phosphopeptide in that time point. The utility of this visual representation is validated by the large number of red heatmap bars downstream of Zap-70 in the canonical pathway. Note that the * next to the phosphorylation site signifies that this site has been previously described in the literature.
      Quantitation in proteomics experiments facilitates the comparison of proteins between various cellular states such as a receptor stimulation time course experiment. Stable Isotope Labeling of Amino Acids in Cell Culture (SILAC) is an effective method for measuring the relative abundance of proteins in cell or tissue samples (
      • Ong S.E.
      • Mann M.
      Mass spectrometry-based proteomics turns quantitative.
      ). In the SILAC technique, heavy or light essential amino acids are incorporated into cellular proteins through metabolic labeling in cell culture before cellular stimulation. This method allows for normalization of errors through the entire process of stimulation of cells, purification of proteins, and acquisition of LC/MS data, providing precise measurements of small differences between samples (
      • Ong S.E.
      • Mann M.
      Mass spectrometry-based proteomics turns quantitative.
      ). However, the number of comparisons possible in a single experiment is often limited in practice by the number of labeled amino acids available (
      • Ong S.E.
      • Blagoev B.
      • Kratchmarova I.
      • Kristensen D.B.
      • Steen H.
      • Pandey A.
      • Mann M.
      Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.
      ). The number of cellular state comparisons may be extended beyond the limits of available labeled amino acids by label-free quantitation using repetition of biological stimulations in separate SILAC experiments (
      • Olsen J.V.
      • Blagoev B.
      • Gnad F.
      • Macek B.
      • Kumar C.
      • Mortensen P.
      • Mann M.
      Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.
      ) or normalization to spiked phosphopeptide standards. Label-free quantitation between separate LC/MS experiments is facilitated by automation of peptide chromatography and data acquisition, resulting in enhanced reproducibility of chromatographic retention times and peak areas (
      • Ficarro S.B.
      • Salomon A.R.
      • Brill L.M.
      • Mason D.E.
      • Stettler-Gill M.
      • Brock A.
      • Peters E.C.
      Automated immobilized metal affinity chromatography/nano-liquid chromatography/electrospray ionization mass spectrometry platform for profiling protein phosphorylation sites.
      ). The automated IMAC/nano-LC/ESI-MS system used here provides the necessary reproducible peak areas (8% relative standard deviation) and retention times (0.2% relative standard deviation) (
      • Ficarro S.B.
      • Salomon A.R.
      • Brill L.M.
      • Mason D.E.
      • Stettler-Gill M.
      • Brock A.
      • Peters E.C.
      Automated immobilized metal affinity chromatography/nano-liquid chromatography/electrospray ionization mass spectrometry platform for profiling protein phosphorylation sites.
      ). The combination of SILAC and label-free quantitation allows for a greatly increased number of receptor stimulation time points while providing highly accurate comparisons between signaling protein null and reconstituted cells at each time point using SILAC.
      Because of its high degree of prior characterization, the T cell receptor (TCR) signaling pathway is an ideal model system for validating our approach for quantitative phosphoproteomic analysis of isogenic signaling pathway mutants. TCR signaling plays an essential role in regulating the adaptive immune response, and many proteins involved in the pathway have been identified (Fig. 1) (
      • Germain R.N.
      • Stefanová I.
      The dynamics of T cell receptor signaling: complex orchestration and the key roles of tempo and cooperation.
      ,
      • Samelson L.E.
      Signal transduction mediated by the T cell antigen receptor: the role of adapter proteins.
      ,
      • Weiss A.
      • Kadlecek T.
      • Iwashima M.
      • Chan A.
      • Van Oers N.
      Molecular and genetic insights into T-cell antigen receptor signaling.
      ). The availability of the highly characterized Jurkat leukemic T cell line has greatly facilitated investigations of TCR signaling by traditional and phosphoproteomic methods (
      • Salomon A.R.
      • Ficarro S.B.
      • Brill L.M.
      • Brinker A.
      • Phung Q.T.
      • Ericson C.
      • Sauer K.
      • Brock A.
      • Horn D.M.
      • Schultz P.G.
      • Peters E.C.
      Profiling of tyrosine phosphorylation pathways in human cells using mass spectrometry.
      ,
      • Abraham R.T.
      • Weiss A.
      Jurkat T cells and development of the T-cell receptor signaling paradigm.
      ). Furthermore, many isogenic disruption mutants of essential TCR signaling proteins have been isolated through genetic screens of mutagenized Jurkat clones, revealing severe phenotypic defects in TCR signaling and function (
      • Finco T.S.
      • Kadlecek T.
      • Zhang W.
      • Samelson L.E.
      • Weiss A.
      LAT is required for TCR-mediated activation of PLCgamma1 and the Ras pathway.
      ,
      • Irvin B.J.
      • Williams B.L.
      • Nilson A.E.
      • Maynor H.O.
      • Abraham R.T.
      Pleiotropic contributions of phospholipase C-gamma1 (PLC-gamma1) to T-cell antigen receptor-mediated signaling: reconstitution studies of a PLC-gamma1-deficient Jurkat T-cell line.
      ,
      • Straus D.B.
      • Weiss A.
      Genetic evidence for the involvement of the lck tyrosine kinase in signal transduction through the T cell antigen receptor.
      ,
      • Williams B.L.
      • Schreiber K.L.
      • Zhang W.
      • Wange R.L.
      • Samelson L.E.
      • Leibson P.J.
      • Abraham R.T.
      Genetic evidence for differential coupling of Syk family kinases to the T-cell receptor: reconstitution studies in a ZAP-70-deficient Jurkat T-cell line.
      ,
      • Yablonski D.
      • Kuhne M.R.
      • Kadlecek T.
      • Weiss A.
      Uncoupling of nonreceptor tyrosine kinases from PLC-gamma1 in an SLP-76-deficient T cell.
      ). In particular, P116, a Zap-70 null clone, displays defects in stimulus-induced calcium mobilization, interleukin-2 production, nuclear factor of activated T cells transcription activation, and protein tyrosine phosphorylation on PLCγ1, ITK, LAT, Erk1/2, and SLP76 (
      • Williams B.L.
      • Schreiber K.L.
      • Zhang W.
      • Wange R.L.
      • Samelson L.E.
      • Leibson P.J.
      • Abraham R.T.
      Genetic evidence for differential coupling of Syk family kinases to the T-cell receptor: reconstitution studies in a ZAP-70-deficient Jurkat T-cell line.
      ,
      • Shan X.
      • Wange R.L.
      Itk/Emt/Tsk activation in response to CD3 cross-linking in Jurkat T cells requires ZAP-70 and Lat and is independent of membrane recruitment.
      ,
      • Martelli M.P.
      • Lin H.
      • Zhang W.
      • Samelson L.E.
      • Bierer B.E.
      Signaling via LAT (linker for T-cell activation) and Syk/ZAP70 is required for ERK activation and NFAT transcriptional activation following CD2 stimulation.
      ,
      • Griffith C.E.
      • Zhang W.
      • Wange R.L.
      ZAP-70-dependent and -independent activation of Erk in Jurkat T cells. Differences in signaling induced by H2o2 and Cd3 cross-linking.
      ). In the present study, a hybrid SILAC/label-free approach was applied to the P116 (Zap-70 null) and P116.c139 (Zap-70 reconstituted to wild type levels) Jurkat clones, and the placement of newly discovered tyrosine phosphorylation sites relative to Zap-70 was determined.

      RESULTS

      Prior to analysis of Zap-70 null Jurkat cells, Jurkat cells were incubated with either 0.3 mm 13C6, 15N4 Arg or 0.18 mm 13C6, 15N2 Lys in dialyzed serum for 7 doublings to test the SILAC labeling conditions. Tyrosine phosphorylated peptides were enriched according to the standard peptide immunoprecipitation procedure described under “Experimental Procedures”. After desalt, IMAC, and LC/MS, the phosphopeptides were identified with SEQUEST and filtered as described under “Experimental Procedures” to compile a nonredundant list of tyrosine phosphopeptides. In the 13C6, 15N4 Arg and 13C6, 15N2 Lys labeled samples a total of 130 and 111 nonredundant phosphopeptides were observed, respectively. There were no unlabeled peptides observed. In the 13C6, 15N4 Arg labeled sample, a single 13C5, 15N1 Pro was observed out of a total of 75 peptides that contained unlabeled proline (supplemental material 5).
      To evaluate its utility, our quantitative phosphoproteomic approach was applied to the human Jurkat T cell clones, P116 (Zap-70 null) and P116.c139 (Zap-70 reconstituted to wild type levels). The removal of Zap-70 protein and decrease in phosphorylation in Erk1/2 in Zap-70 null and reconstituted cells by Western blot was consistent with previous reports on these Jurkat clones (supplemental material 1) (
      • Williams B.L.
      • Schreiber K.L.
      • Zhang W.
      • Wange R.L.
      • Samelson L.E.
      • Leibson P.J.
      • Abraham R.T.
      Genetic evidence for differential coupling of Syk family kinases to the T-cell receptor: reconstitution studies in a ZAP-70-deficient Jurkat T-cell line.
      ,
      • Shan X.
      • Wange R.L.
      Itk/Emt/Tsk activation in response to CD3 cross-linking in Jurkat T cells requires ZAP-70 and Lat and is independent of membrane recruitment.
      ,
      • Martelli M.P.
      • Lin H.
      • Zhang W.
      • Samelson L.E.
      • Bierer B.E.
      Signaling via LAT (linker for T-cell activation) and Syk/ZAP70 is required for ERK activation and NFAT transcriptional activation following CD2 stimulation.
      ,
      • Griffith C.E.
      • Zhang W.
      • Wange R.L.
      ZAP-70-dependent and -independent activation of Erk in Jurkat T cells. Differences in signaling induced by H2o2 and Cd3 cross-linking.
      ). A distribution of six time points was used to detect subtle fluctuations in the timing of phosphorylation. Zap-70 null to Zap-70 reconstituted SILAC phosphopeptide ratios were calculated at each time point in a time course of TCR stimulation (Fig. 2). Before peak area quantitation and SILAC ratio calculation, high-quality sequence assignments were first determined using stringent criteria (Xcorr +1 > 1.5; +2 > 2.0; +3 > 2.5; precursor mass error < 20 ppm, logistic spectral score > 0.7981 (
      • Yu K.
      • Sabelli A.
      • DeKeukelaere L.
      • Park R.
      • Sindi S.
      • Gatsonis C.A.
      • Salomon A.R.
      Integrated platform for high-throughput statistical and manual validation of tandem mass spectra.
      ), minimum SIC peak area threshold of 500 for SILAC and label-free quantitation were required, tyrosine phosphorylated, with observations of each peptide MS/MS spectra in at least three of the six time points). The false discovery rate estimated from decoy database search was 2.22% after all filtering and assembly of non-redundant data into heatmaps. A total of five replicate experiments were performed (as described under “Experimental Procedures”). Quantitative comparisons were generated from SIC peak areas, and heatmaps were generated from the average values from all replicates. The complete list of quantitative replicate data, calculated coefficient of variation and p values are available (supplemental material 6).
      Figure thumbnail gr2
      Fig. 2Experimental procedure. Two cell populations of human Jurkat T cell clones (P116 and P116.c139) are incubated with normal or heavy isotope-labeled arginine and lysine amino acids, physically differentiating the two proteomes by a shift in molecular weights. Each cell population is then pre-incubated with OKT3 and OKT4 antibodies for 10 min at 4 °C and then cross-linked with IgG at 37 °C for the times indicated. After cell lysis, samples are combined at an equal protein concentration ratio of 1:1. Samples are then reduced, alkylated, and trypsin-digested into peptides. Peptides are desalted by Sep-Pak cartridges and then enriched by phosphotyrosine peptide immunoprecipitation and Fe3+ IMAC. Peptides are then subjected to reversed-phase LC-MS/MS analysis.

      Representation of Label-free and SILAC Quantitation

      Two different visual representations in the form of heatmaps of quantitative data were generated for each sequenced phosphopeptide to reflect either the label-free or SILAC ratio data. These two heatmaps provide the relationship between each phosphopeptide sequenced and TCR stimulation (label-free heatmaps) or the removal of Zap-70 (SILAC ratio heatmaps).
      In the label-free heatmap, the abundance of each phosphopeptide in Zap-70 reconstituted cells was compared across the T cell receptor stimulation time course (Fig. 3 and supplemental material 2). This type of quantitative analysis is useful for determining whether newly discovered phosphorylation sites change in abundance after receptor stimulation, providing a list of candidate phosphorylation sites that may participate in the T cell signaling pathway. These data are represented in the form of a heatmap where black corresponds to the average abundance for a given peptide across all time points, yellow corresponds to phosphorylation levels above the average, and blue corresponds to phosphorylation levels below the average. As expected, for many of the phosphorylation sites already known to be involved in TCR signaling, phosphorylation levels increase after receptor stimulation followed by a steady decrease (Fig. 3).
      Figure thumbnail gr3
      Fig. 3Quantitative phosphoproteomic analysis of known TCR signaling proteins in wild type cells. Listed above is a portion of the data collected, representing the known TCR signaling proteins that were observed in our study of human Jurkat P116.c139 (Zap-70 reconstituted) cells. Temporal quantitative changes in phosphorylation state are represented as heatmaps, which represent averages of five replicate experiments. In the heatmap representation, yellow represents levels of phosphorylation above the average, while blue represents levels of phosphorylation below the average. Black represents average abundance for a certain peptide across all time points. Blanks in the heatmap indicate that a clearly defined SIC peak was not observed for that phosphopeptide in that time point. Note that the * next to the phosphorylation site signifies that this site has been described previously in the literature.
      In the second SILAC heatmap, SILAC ratios between Zap-70 null and reconstituted cells are represented for each phosphopeptide and time point (supplemental material 3). These data are represented in the form of a SILAC ratio heatmap, where green corresponds to an increase in phosphorylation, red corresponds to a decrease in phosphorylation, and black corresponds to no difference when Zap-70 is removed from Jurkat T cells for a given phosphopeptide at each time point. The intensity of the color reflects the relative magnitude of the change in phosphorylation. If phosphorylation decreases in cells lacking Zap-70 compared with wild type, the phosphorylation event can be hypothetically positioned downstream of this protein. We then assessed the utility of our isogenic mutant approach by investigating the correlation between the known structure of the T cell signaling pathway and the changes in phosphopeptide abundance upon the removal of Zap-70. The utility of the method is validated by the large number of red heatmap bars downstream of Zap-70 in the canonical pathway (Fig. 1), indicating Zap-70-dependent phosphorylation.

      Phosphoproteomic Profiling of Phosphorylation Sites Identified in Receptor-stimulated Zap-70 Reconstituted Jurkat Cells

      From this analysis, we observed 168 tyrosine phosphorylation sites residing on 135 unique proteins in the Zap-70 reconstituted T cells across 6 time points of receptor stimulation (Fig. 3 and supplemental material 2). Among the 135 proteins identified, 24% of them (32 proteins) were previously functionally characterized in TCR signaling (
      • Weiss A.
      • Kadlecek T.
      • Iwashima M.
      • Chan A.
      • Van Oers N.
      Molecular and genetic insights into T-cell antigen receptor signaling.
      ,
      • Robey E.
      • Allison J.P.
      T-cell activation: integration of signals from the antigen receptor and costimulatory molecules.
      ,
      • Szamel M.
      • Resch K.
      T-cell antigen receptor-induced signal-transduction pathways–activation and function of protein kinases C in T lymphocytes.
      ). Phosphorylation sites were observed on the earliest upstream TCR signaling components (TCR-CD3 subunits γδεζ, tyrosine kinases Lck, Fyn, Zap-70), crucial adaptor proteins (LAT, ITK, PLCγ1), and downstream target proteins (phosphoinositide 3-kinase (PI3K), Erk1, Erk2, CD5) (Fig. 1, Fig. 2, Fig. 3).
      Because phosphorylation sites that do not change in response to TCR stimulation are unlikely to be involved in the TCR pathway, we focused our analysis on sites that showed a change (greater than 3-fold change) across the TCR stimulation time course in reconstituted Jurkat T cells as measured by label-free quantitation. These TCR responsive sites were further classified into a variety of groups with the use of SILAC ratio data to determine the dependence of each site upon the absence or presence of Zap-70 (Fig. 4 ).
      Figure thumbnail gr4
      Fig. 4Classification of ZAP-70 null/reconstituted SILAC ratios. The log2 SILAC ratios of Zap-70 null to Zap-70 reconstituted cells were classified into four major categories: Peptides with substantially decreased phosphorylation; peptides with decreased phosphorylation; peptides with elevated phosphorylation; peptides with no change in phosphorylation. SILAC ratios are calculated from the average of five replicate experiments.

      Clustering of Phosphorylation Sites by Zap-70 Null/Reconstituted SILAC Ratios

      Among the phosphopeptides that showed an increase in abundance with TCR stimulation in the reconstituted T cell time course, SILAC ratios of Zap-70 null to Zap-70 reconstituted cells were classified into four categories (Fig. 4): elevated phosphorylation (greater than 2-fold induction in two or more time points), no differences in phosphorylation (between 2-fold induction and 2-fold reduction in four or more time points), slightly decreased phosphorylation (between 2 to 10-fold reduction in two or more time points), and significantly decreased phosphorylation (greater than 10-fold reduction in two or more time points). From this grouping of phosphopeptide SILAC ratios, 43% showed enhanced phosphorylation, 19% showed no difference, 24% showed slight decrease, 12% showed significant decrease, and 2% represented outliers, which did not fully fall into any of the four major categories yet generally displayed minimal change.
      Proteins with phosphorylation sites in the minimal change group included proteins known to function upstream of Zap-70 (CD3ε, CD3ζ, Lck) (
      • Weiss A.
      • Kadlecek T.
      • Iwashima M.
      • Chan A.
      • Van Oers N.
      Molecular and genetic insights into T-cell antigen receptor signaling.
      ), proteins known to function in other signaling pathways in T cells (GSK3β, phosphoprotein associated with glycolipid-enriched membrane protein (PAG)) (
      • Ohteki T.
      • Parsons M.
      • Zakarian A.
      • Jones R.G.
      • Nguyen L.T.
      • Woodgett J.R.
      • Ohashi P.S.
      Negative regulation of T cell proliferation and interleukin 2 production by the serine threonine kinase GSK-3.
      ,
      • Davidson D.
      • Bakinowski M.
      • Thomas M.L.
      • Horejsi V.
      • Veillette A.
      Phosphorylation-dependent regulation of T-cell activation by PAG/Cbp, a lipid raft-associated transmembrane adaptor.
      ), and ones not known to function in TCR signaling (Filamin B, CDC2, ELMO1).
      In general, sites with decreased phosphorylation levels in P116 (Zap-70 null) cells suggest a position downstream of Zap-70 in the pathway. Through Western blot analysis of TCR-stimulated P116 (Zap-70 null) cells, previous studies have shown decreases in tyrosine phosphorylation on proteins such as PLCγ1, LAT, and Erk1/2 (
      • Williams B.L.
      • Schreiber K.L.
      • Zhang W.
      • Wange R.L.
      • Samelson L.E.
      • Leibson P.J.
      • Abraham R.T.
      Genetic evidence for differential coupling of Syk family kinases to the T-cell receptor: reconstitution studies in a ZAP-70-deficient Jurkat T-cell line.
      ,
      • Shan X.
      • Wange R.L.
      Itk/Emt/Tsk activation in response to CD3 cross-linking in Jurkat T cells requires ZAP-70 and Lat and is independent of membrane recruitment.
      ,
      • Martelli M.P.
      • Lin H.
      • Zhang W.
      • Samelson L.E.
      • Bierer B.E.
      Signaling via LAT (linker for T-cell activation) and Syk/ZAP70 is required for ERK activation and NFAT transcriptional activation following CD2 stimulation.
      ). Our SILAC quantitation results also showed decrease in phosphorylation on these downstream proteins in Zap-70 null cells at PLCγ1 (Tyr-771, significantly decreased at 2 min, p value < 0.05), LAT (Tyr-45, significantly decreased at 2 min, p value < 0.05), Erk1 (Tyr-204, significantly decreased at 7 and 10 min, p value < 0.05), Erk2 (Tyr-187, significantly decreased at 0 and 2 min, p value < 0.05).
      Although phosphorylation sites upstream of Zap-70 would be expected to be unaffected by Zap-70 removal, three tyrosine residues within the TCR CD3ζ (Tyr-111, Tyr-72, Tyr-142) immunoreceptor tyrosine activation motif (ITAM), along with three tyrosine residues on TCR CD3δ (Tyr-160, Tyr-149), and CD3ε (Tyr-199) ITAMs, decreased significantly (p value < 0.05 at various time points among these sites) in Zap-70 null cells (Fig. 5 ). These seemingly upstream perturbations in phosphorylation are, nevertheless, consistent with previous reports for the P116 Jurkat clone (
      • Steinberg M.
      • Adjali O.
      • Swainson L.
      • Merida P.
      • Di Bartolo V.
      • Pelletier L.
      • Taylor N.
      • Noraz N.
      T-cell receptor-induced phosphorylation of the zeta chain is efficiently promoted by ZAP-70 but not Syk.
      ,
      • Thome M.
      • Duplay P.
      • Guttinger M.
      • Acuto O.
      Syk and ZAP-70 mediate recruitment of p56lck/CD4 to the activated T cell receptor/CD3/zeta complex.
      ). Although Lck-mediated phosphorylation of CD3ζ ITAMs is widely believed to precede Zap-70 recruitment and activation (
      • Wange R.L.
      • Samelson L.E.
      Complex complexes: signaling at the TCR.
      ), previous studies have revealed a synergistic role of Zap-70-mediated recruitment as well as stabilization of the interaction between Lck and CD3ζ at the ITAM regions independent of Zap-70 kinase activity (Fig. 5A) (
      • Steinberg M.
      • Adjali O.
      • Swainson L.
      • Merida P.
      • Di Bartolo V.
      • Pelletier L.
      • Taylor N.
      • Noraz N.
      T-cell receptor-induced phosphorylation of the zeta chain is efficiently promoted by ZAP-70 but not Syk.
      ,
      • Thome M.
      • Duplay P.
      • Guttinger M.
      • Acuto O.
      Syk and ZAP-70 mediate recruitment of p56lck/CD4 to the activated T cell receptor/CD3/zeta complex.
      ). Additional reports have indicated an essential role of Lck in the regulation of constitutive phosophorylation of CD3ζ (
      • van Oers N.S.
      • Killeen N.
      • Weiss A.
      Lck regulates the tyrosine phosphorylation of the T cell receptor subunits and ZAP-70 in murine thymocytes.
      ). From these studies, it can be proposed that the removal of Zap-70 would result in a decrease of CD3ζ basal phosphorylation levels, which is consistent with our findings on these sites.
      Figure thumbnail gr5
      Fig. 5Lck phosphorylation of the CD3ζ ITAM motif requires Zap-70. A, TCR/CD3 Zap-70 null/Zap-70 reconstituted SILAC ratio profiles. Differences in phosphopeptide abundance over time were represented as SILAC ratios between P116 (Zap-70 null) and P116.c139 (Zap-70 reconstituted) cells on CD3ζ, CD3ε, and CD3δ chains. SILAC ratios are calculated from the averages of five replicate experiments. B, model of Zap-70-dependent Lck phosphorylation of the CD3ζ ITAM motif as well as CD3/CD4 antibody co-stimulation.

      Novel Phosphorylation Sites Identified

      The use of this quantitative approach to make comparisons between Zap-70 null and reconstituted cells has also led to the generation of a broad test bed of novel, uncharacterized phosphorylation sites that can be positioned within the T cell signaling pathway. Among the 178 total unique phosphorylation sites identified in this analysis, 105 of these sites were found to be novel, i.e. sites that were previously uncharacterized in the Human Protein Reference Database Version 7. Furthermore, of the 105 newly discovered sites, 69 of these sites were changed significantly in abundance with Zap-70 removal. This data provides a wealth of information about the hypothetical placement of these sites relative to Zap-70 and the TCR (Fig. 6).
      Figure thumbnail gr6
      Fig. 6Dynamic effects of Zap-70 removal on novel phosphorylation sites discovered. Listed in this table is a subset of phosphorylation sites identified, representing the novel sites that displayed significant changes in response to Zap-70. Novel sites are defined as sites that were previously uncharacterized in the Human Protein Reference Database Version 7. Also included are the SILAC ratios (Zap-70 null/reconstituted) for the time points that showed significant changes among the five replicate experiments (p value < 0.05) as well as the average SILAC ratio across all time points. If missing data because of the sensitivity limit of the instrument prevented the reproducible observation of SILAC ratios in at least three replicate experiments, or the null hypothesis cannot be rejected, then those squares are left blank in this table.

      DISCUSSION

      The typical approach for elucidation of the structure of cellular signaling networks involves an iterative process of signaling protein disruptions and a large number of site-directed mutants, followed by characterization of every mutant through a battery of assays of cellular activation. One common phenotype employed to evaluate newly created signaling protein mutants is the use of phosphorylation site-specific Western blots. The advantage of this approach is the specificity of the measurement and the ease of quantitation of the change in phosphorylation. However, localization of protein phosphorylation events within signaling pathways requires two separate types of information: the precise timing of each phosphorylation site relative to receptor stimulation as well as the relationship of each phosphorylation site to canonical signaling pathway landmarks. Quantitative phosphoproteomics can provide a means to overcome some of these issues by providing a richer, unbiased site-specific view of the phosphoproteome of cells harboring altered signaling proteins. Quantitation methods, such as SILAC, can provide highly detailed information about differences between distinct populations, but the number of necessary quantitative comparisons quickly outpaces the number of available isotopically labeled amino acids. The combination of SILAC and label-free quantitation allows for a greatly increased number of receptor stimulation time points while providing highly accurate comparisons between signaling protein null and reconstituted cells at each time point using SILAC.
      Mutant compensation could be a complicating factor in the interpretation of differences in phosphorylation between protein null and wild type cells. Downstream targets solely dependent on the removed protein for phosphorylation should show strong decreases in phosphorylation. However, if multiple pathways exist to phosphorylate a downstream target, a pathway independent of the removed protein may mask defects in the protein dependent pathway. For instance, in our analysis, the Zap-70 downstream target Thr-180, Tyr-182 of p38 MAPK showed only slight decreases in phosphorylation in Zap-70 null mutants stimulating the hypothesis of alternative pathways regulating this site and compensating for the loss of Zap-70. Phosphoproteomic data from isogenic mutant analysis must be interpreted with attention for the possibility of compensation.
      The interpretation of phosphoproteomic data obtained by our method could also be complicated by the existence of positive and negative feedback regulatory loops within signaling pathways. Feedback mechanisms make placement of phosphorylation sites within the pathway difficult because they allow upstream components to also be altered by the removal of a protein. C-terminal Src kinase (Csk), CD45, casitas B-lineage lymphoma (c-cbl), and SHP-1 are proteins known to function in negative feedback mechanisms in TCR signaling (
      • Bergman M.
      • Mustelin T.
      • Oetken C.
      • Partanen J.
      • Flint N.A.
      • Amrein K.E.
      • Autero M.
      • Burn P.
      • Alitalo K.
      The human p50csk tyrosine kinase phosphorylates p56lck at Tyr-505 and down regulates its catalytic activity.
      ,
      • Mustelin T.
      • Williams S.
      • Tailor P.
      • Couture C.
      • Zenner G.
      • Burn P.
      • Ashwell J.D.
      • Altman A.
      Regulation of the p70zap tyrosine protein kinase in T cells by the CD45 phosphotyrosine phosphatase.
      ,
      • Murphy M.A.
      • Schnall R.G.
      • Venter D.J.
      • Barnett L.
      • Bertoncello I.
      • Thien C.B.
      • Langdon W.Y.
      • Bowtell D.D.
      Tissue hyperplasia and enhanced T-cell signaling via ZAP-70 in c-Cbl-deficient mice.
      ,
      • Plas D.R.
      • Johnson R.
      • Pingel J.T.
      • Matthews R.J.
      • Dalton M.
      • Roy G.
      • Chan A.C.
      • Thomas M.L.
      Direct regulation of ZAP-70 by SHP-1 in T cell antigen receptor signaling.
      ,
      • Stefanová I.
      • Hemmer B.
      • Vergelli M.
      • Martin R.
      • Biddison W.E.
      • Germain R.N.
      TCR ligand discrimination is enforced by competing ERK positive and SHP-1 negative feedback pathways.
      ). Positive feedback mechanisms have also been observed in T cells such as Erk phosphorylation of Lck (
      • Stefanová I.
      • Hemmer B.
      • Vergelli M.
      • Martin R.
      • Biddison W.E.
      • Germain R.N.
      TCR ligand discrimination is enforced by competing ERK positive and SHP-1 negative feedback pathways.
      ,
      • Altman A.
      • Kaminski S.
      • Busuttil V.
      • Droin N.
      • Hu J.
      • Tadevosyan Y.
      • Hipskind R.A.
      • Villalba M.
      Positive feedback regulation of PLCgamma1/Ca(2+) signaling by PKCtheta in restimulated T cells via a Tec kinase-dependent pathway.
      ,
      • Mueller D.L.
      Tuning the immune system: competing positive and negative feedback loops.
      ). To face this challenge, a theoretical logical model was assembled to predict the effects of feedback inhibition or feedback activation upon SILAC ratios calculated with this method (Fig. 7 ). From this logical model, both feedback inhibition and activation would be expected to affect SILAC ratios of an upstream signaling protein phosphorylation site in a time-dependent manner, while direct downstream inhibition would be expected to decrease phosphorylation constitutively. Consistent with our feedback model, CD3ζ Tyr-123 followed the trends predicted for Zap-70-dependent feedback activation (significantly increased at 0 min (p value < 0.05) followed by significantly decrease at 7 min (p value < 0.05)), stimulating the hypothesis that this site may play a role in positive feedback that has not been previously characterized (Fig. 7D). This observation highlights the importance of studying the kinetics of the phosphoproteomes of isogenic mutants.
      Figure thumbnail gr7
      Fig. 7Theoretical model distinguishing direct inhibition from feedback regulation. A, schematic model of pathway progression in response to T cell activation. At later stages, TCR signaling is regulated by either positive or negative feedback loop functions. Activation is represented by “+” while inhibition is represented by “−”. Theoretical tables of expected wild type (WT) and knock-out (KO) TCR/CD3 phosphorylation temporal profiles for (B1) feedback activation and (B2) feedback inhibition (−, low level phosphorylation; +, moderate level phosphorylation; ++, high level phosphorylation. B1, with positive feedback through Zap-70, phosphorylation of CD3 would fail to be reduced at later time points in wild type cells compared with Zap-70 null cells. B2, with negative feedback through Zap-70, phosphorylation of CD3 would fail to be reduced at later time points in Zap-70 null cells compared with wild type cells. Expected changes in KO/WT SILAC ratios over time for (C1) TCR/CD3 in a Zap-70 independent pathway (SILAC ratio ≈ 1); (C2) downstream proteins affected by direct inhibition in a Zap-70-dependent pathway (SILAC ratio < 1); (C3) positive feedback on CD3, and (C4) negative feedback on CD3. Solid line (–) corresponds to expected SILAC ratio profile. D, observed CD3ζ Tyr-123 Zap-70 null/Zap-70 reconstituted SILAC ratio profile. E1, predicted changes in KO/WT SILAC ratios over time for TCR/CD3 phosphorylation with feedback activation in a Zap-70-dependent pathway followed by feedback inhibition in a Zap-70 dependent pathway. E2, observed CD3ζγδε Zap-70 null/Zap-70 reconstituted SILAC ratios over time.
      Additionally, for the majority of phosphorylation sites identified on the CD3γδζ subunits, we observed a gradual decrease in Zap-70 null/reconstituted SILAC ratios at early time points, followed by a gradual increase in Zap-70 null/reconstituted SILAC ratios at later time points (Fig. 7E2). These trends are consistent with the hypothesis of competing positive and negative feedback loops functioning at different stages of stimulation. At early time points, positive feedback mechanisms could be regulating these sites, leading to a gradual decrease in Zap-70 null/reconstituted SILAC ratios. At later time points, negative feedback mechanisms could be regulating these same sites, leading to an increase in Zap-70 null/reconstituted SILAC ratios when Zap-70 is removed (Fig. 7E1). It has previously been shown that Erk positive and SHP-1 negative feedback pathways can compete to either activate or inhibit Lck function to allow for T cells to discriminate between self and foreign ligands (
      • Stefanová I.
      • Hemmer B.
      • Vergelli M.
      • Martin R.
      • Biddison W.E.
      • Germain R.N.
      TCR ligand discrimination is enforced by competing ERK positive and SHP-1 negative feedback pathways.
      ).
      To determine the biological significance of the 105 novel sites discovered in this study (Fig. 6), they must be placed within canonical pathways and networks of protein-protein interactions. Software tools that accelerate the assessment of existing protein knowledge and exploration of quantitative proteomic data in the context of protein interaction networks are essential. Although the primary literature may be investigated manually, the use of software enables enhanced efficiency. Current interactome database software is primarily web-based, and protein names must be searched one at a time. Because only proteins directly binding to the searched protein are revealed, the proteomics researcher must memorize the network to find longer range interactions. Existing website-driven protein-protein interaction queries do not allow searching by peptide sequence, leading to confusion arising from protein name ambiguity. Quantitative data must also be integrated in a manual fashion with the interactome network. Therefore, new proteomic data visual analysis tools are essential for tackling the overwhelming complexity of massive proteomic data sets and existing protein knowledge to gain insights into novel phosphorylation sites discovered in these types of studies.
      We have recently developed phosphoproteomic exploration software with interactive visual integration of quantitative proteomic data, known signaling pathways, and protein-protein interaction networks to accelerate hypothesis generation, which is described in detail in an upcoming manuscript (www.peptidedepot.com/viz). Using this software, we examined the interactions between proteins observed to change in abundance in the Zap-70 null Jurkat cells. Although this analysis could have been accomplished through manual inspection of protein interactions described in hundreds of manuscripts, our newly developed software facilitates the assimilation of this information into a graphical representation of the T cell signaling pathway scaffold protein-protein interaction network. This depiction facilitates the rapid discovery of protein interactions among proteins observed in our data while providing rapid access to the underlying manuscripts through direct hyperlinks. A user may rapidly crawl through this interaction space in a dilated view that shows just a single protein and directly interacting proteins while maintaining global perspective of the T cell scaffold network (supplemental material 4). The quantitative phosphoproteomic data generated in this manuscript is provided as .pth input file for this software and is available for download without restriction (www.tcellpathway.com).
      The ability to visualize our data in relation to the canonical T cell signaling pathway, focus on meaningful protein groups through the use of filters and selectors, and find possible pathways between multiple proteins with variable degrees of separation were integral in generating the hypotheses described in detail here. For example, this software has helped us to propose an unexpected hypothesis about the potential role of the pleckstrin homology domain (PH domain) of SKAP55 (Tyr-142). This site was observed to have slightly enhanced phosphorylation (significantly increased at 3 and 10 min, p value < 0.05) in Zap-70 null cells compared with its reconstituted counterpart in response to stimulation. Upon T cell activation, Fyn-associated SKAP55, in complex with the cytosolic adaptor protein ADAP, targets RAP1 GTPase to the plasma membrane to initiate cell adhesion (
      • Wu L.
      • Yu Z.
      • Shen S.H.
      SKAP55 recruits to lipid rafts and positively mediates the MAPK pathway upon T cell receptor activation.
      ,
      • Kliche S.
      • Breitling D.
      • Togni M.
      • Pusch R.
      • Heuer K.
      • Wang X.
      • Freund C.
      • Kasirer-Friede A.
      • Menasche G.
      • Koretzky G.A.
      • Schraven B.
      The ADAP/SKAP55 signaling module regulates T-cell receptor-mediated integrin activation through plasma membrane targeting of Rap1.
      ,
      • Wang H.
      • Rudd C.E.
      SKAP-55, SKAP-55-related and ADAP adaptors modulate integrin-mediated immune-cell adhesion.
      ). Although the mechanisms of SKAP55's interaction with Fyn and ADAP are well studied, the specific regulatory mechanisms of SKAP55's membrane targeting is still uncharacterized (
      • Wu L.
      • Yu Z.
      • Shen S.H.
      SKAP55 recruits to lipid rafts and positively mediates the MAPK pathway upon T cell receptor activation.
      ,
      • Kliche S.
      • Breitling D.
      • Togni M.
      • Pusch R.
      • Heuer K.
      • Wang X.
      • Freund C.
      • Kasirer-Friede A.
      • Menasche G.
      • Koretzky G.A.
      • Schraven B.
      The ADAP/SKAP55 signaling module regulates T-cell receptor-mediated integrin activation through plasma membrane targeting of Rap1.
      ). It has been established that the PH domain is involved in membrane recruitment for many cellular proteins (
      • Maffucci T.
      • Falasca M.
      Specificity in pleckstrin homology (PH) domain membrane targeting: a role for a phosphoinositide-protein co-operative mechanism.
      ). More recently, it has been shown that tyrosine phosphorylation of the PH domain of protein kinase D can serve in regulating protein function by possibly releasing the PH domain (undefined still whether it is from itself or the membrane), leading to its activation (
      • Storz P.
      • Döppler H.
      • Johannes F.J.
      • Toker A.
      Tyrosine phosphorylation of protein kinase D in the pleckstrin homology domain leads to activation.
      ). Therefore, we hypothesize that phosphorylation at Tyr-142 of SKAP55 may lead to the inhibition of SKAP55's ability bind to the membrane, which would prevent RAP1 GTPase recruitment to the membrane and cell adhesion. The placement of a negatively charged phosphate group in the PH domain could impede the ability of SKAP55 to bind to polyphosphoinositides found at the membrane (
      • Maffucci T.
      • Falasca M.
      Specificity in pleckstrin homology (PH) domain membrane targeting: a role for a phosphoinositide-protein co-operative mechanism.
      ). Further investigation in the possible function of site Tyr-142 of SKAP55 is necessary to validate this hypothesis. The enhanced phosphorylation of Tyr-142 on SKAP55 that we observed could be explained by the misregulation of Fyn, a known regulator of SKAP55 (
      • Wu L.
      • Yu Z.
      • Shen S.H.
      SKAP55 recruits to lipid rafts and positively mediates the MAPK pathway upon T cell receptor activation.
      ,
      • Wang H.
      • Rudd C.E.
      SKAP-55, SKAP-55-related and ADAP adaptors modulate integrin-mediated immune-cell adhesion.
      ).
      Our results also provide some insight on the possible function of NTBA in T cells. NTBA, an ITIM containing killer Ig-like receptor, has been previously shown to be expressed in all human NK, T, and B lymphocytes (
      • Bottino C.
      • Falco M.
      • Parolini S.
      • Marcenaro E.
      • Augugliaro R.
      • Sivori S.
      • Landi E.
      • Biassoni R.
      • Notarangelo L.D.
      • Moretta L.
      • Moretta A.
      NTB-A [correction of GNTB-A], a novel SH2D1A-associated surface molecule contributing to the inability of natural killer cells to kill Epstein-Barr virus-infected B cells in X-linked lymphoproliferative disease.
      ,
      • Falco M.
      • Marcenaro E.
      • Romeo E.
      • Bellora F.
      • Marras D.
      • Vély F.
      • Ferracci G.
      • Moretta L.
      • Moretta A.
      • Bottino C.
      Homophilic interaction of NTBA, a member of the CD2 molecular family: induction of cytotoxicity and cytokine release in human NK cells.
      ). In NK cells, NTBA has been shown to display inhibitory functions by blocking the ability of NK cells to kill Epstein-Barr virus-infected target cells (
      • Bottino C.
      • Falco M.
      • Parolini S.
      • Marcenaro E.
      • Augugliaro R.
      • Sivori S.
      • Landi E.
      • Biassoni R.
      • Notarangelo L.D.
      • Moretta L.
      • Moretta A.
      NTB-A [correction of GNTB-A], a novel SH2D1A-associated surface molecule contributing to the inability of natural killer cells to kill Epstein-Barr virus-infected B cells in X-linked lymphoproliferative disease.
      ). Little is known about their role in T cells. Recently, certain KIRs (KIR2DL2 and KLRG1) have been shown to disrupt late T cell receptor-stimulated effector functions such the production of IFN-γ and interleukin-2, respectively (
      • Henel G.
      • Singh K.
      • Cui D.
      • Pryshchep S.
      • Lee W.W.
      • Weyand C.M.
      • Goronzy J.J.
      Uncoupling of T-cell effector functions by inhibitory killer immunoglobulin-like receptors.
      ,
      • Tessmer M.S.
      • Fugere C.
      • Stevenaert F.
      • Naidenko O.V.
      • Chong H.J.
      • Leclercq G.
      • Brossay L.
      KLRG1 binds cadherins and preferentially associates with SHIP-1.
      ). Furthermore, site-directed mutagenesis of specific tyrosine residues in the ITIM motif of KLRG1 demonstrates the importance of tyrosine phosphorylation in the inhibitory process in T cells (
      • Tessmer M.S.
      • Fugere C.
      • Stevenaert F.
      • Naidenko O.V.
      • Chong H.J.
      • Leclercq G.
      • Brossay L.
      KLRG1 binds cadherins and preferentially associates with SHIP-1.
      ). In our results, the phosphorylation of site Tyr-308 located within the ITIM motif of NTBA was increased (significantly increased at 7min, p value < 0.05) in response to TCR cross-linking in Zap-70 reconstituted Jurkat cells, suggesting the involvement of NTBA in the T cell activation pathway. It is possible that NTBA, like other KIRs, functions to inhibit late T cell signaling events through phosphorylation of Tyr-308. Such a possibility warrants additional investigation to clearly define the role of site Tyr-308 of NTBA. We also observed a slightly decreased phosphorylation (significantly decreased at 7 min, p value < 0.05) of Tyr-308 in Zap-70 null cells suggesting that this site may be downstream of Zap-70 activation.
      The quantitative phosphoproteomic isogenic mutant approach described here will not only provide greater insights into molecular mechanisms of the TCR signaling pathway, but also provide a generalized approach to elucidation of cell signaling pathways using phosphoproteomics. Although current phosphoproteomic studies have been impressive in their identification and quantitation of changes in phosphorylation abundance across large numbers of proteins (
      • Ficarro S.B.
      • McCleland M.L.
      • Stukenberg P.T.
      • Burke D.J.
      • Ross M.M.
      • Shabanowitz J.
      • Hunt D.F.
      • White F.M.
      Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae.
      ,
      • Brill L.M.
      • Salomon A.R.
      • Ficarro S.B.
      • Mukherji M.
      • Stettler-Gill M.
      • Peters E.C.
      Robust phosphoproteomic profiling of tyrosine phosphorylation sites from human T cells using immobilized metal affinity chromatography and tandem mass spectrometry.
      ,
      • Cao L.
      • Yu K.
      • Banh C.
      • Nguyen V.
      • Ritz A.
      • Raphael B.J.
      • Kawakami Y.
      • Kawakami T.
      • Salomon A.R.
      Quantitative time-resolved phosphoproteomic analysis of mast cell signaling.
      ,
      • Krüger M.
      • Kratchmarova I.
      • Blagoev B.
      • Tseng Y.H.
      • Kahn C.R.
      • Mann M.
      Dissection of the insulin signaling pathway via quantitative phosphoproteomics.
      ,
      • Schmelzle K.
      • Kane S.
      • Gridley S.
      • Lienhard G.E.
      • White F.M.
      Temporal dynamics of tyrosine phosphorylation in insulin signaling.
      ), the development of methodology capable of the multi-dimensional comparison of mutant and wild type cells through a time course of receptor stimulation is critically important. By combining genetic analysis and two well established proteomic quantitation methods, and novel visual analysis tools, our approach facilitates rapid elucidation of the biological significance of high throughput phosphoproteomic data. Comparison of data from removal of multiple signaling proteins at different positions within a single pathway (upstream, middle, and downstream) will provide a means of organizing hundreds to thousands of phosphorylation sites relative to canonical pathway signaling landmarks. Although our hybrid quantitation approach was applied to the analysis of wide-scale tyrosine phosphorylation here, it is generic in design and adaptable to a wide range of phosphopeptide enrichment strategies. Quantitative phosphoproteomic phenotyping of signaling protein mutants will be an ideal complement to traditional signaling approaches, accelerating understanding of the architecture of phosphorylation networks involved in a wide range of biological processes.

      Acknowledgments

      We thank K. Sauer at the Scripps Research Institute, Department of Immunology for his helpful discussions. We would also like to thank L. Samelson at the National Institute of Health for generously providing us with the Jurkat clones P116 (Zap-70 null) and P116.c139 (Zap-70 reconstituted).

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