Immunoaffinity Enrichment and Quantitative Profiling of...
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Klarisa Rikova, Ailan Guo, Kimberly A. Lee, Anthony Possemato, Yi Wang, Sean A. Beausoleil, Daniel E. Mulhern, Jian Min Ren, Michael J. Comb Cell Signaling Technology, Inc., Danvers, MA Immunoaffinity Enrichment and Quantitative Profiling of Protein Phosphorylation, Methylation, and Acetylation in Receptor Tyrosine Kinase Pathway-addicted Cancer Cell Lines Somatic mutation and altered protein expression patterns cause inappropriate activation and deactivation of key players in cellular signaling, result- ing in the oncogenic phenotype. Phosphorylation patterns of oncogenes and other signaling proteins have been studied extensively in the last sev- eral years, resulting in significant advances in our understanding of cancer and our ability to identify and therapeutically target tumor drivers. Here we take the next step in this process, expanding the enriched, identified, and quantified post-translational modification (PTM) space to include not only phosphopeptides but also acetylated, methylated, and ubiquitinated peptides, resulting in a multifaceted analysis of cellular protein modification to better under- stand the complex signaling events of cancer biology. Variation in cellular signaling measured by ten different candidate motif antibodies was evaluated by performing western blot analysis of cell lysates from 22 dif- ferent lung cancer cell lines. This screening tool allowed us to select those antibodies with the most diverse staining patterns across the cell lines for global pro- teomic PTM profiling. Phosphotyrosine, acetyl-lysine, methyl-arginine, ATM/ATR substrate (s/tQ), and AGC/CAMK/STE family kinase motif, which specifically enriches close to 100 active kinase phosphopeptides, were all selected for use in peptide immunoprecipitation, allowing us to characterize and quantify a broad PTM space. Initial method development and PTM profiling were performed using a set of six lung cancer cell lines (A549, H1650, H1703, H3122, H3255, and MKN45) that have different signaling pathways driving their growth and transformation. Phosphotyrosine profiling of these cell lines with tandem mass tag (TMT) quantifica- tion revealed clear quantitative differences in phosphorylation, successfully identifying their activated signaling pathways. The established method of TMT labeling coupled with serial peptide immunoprecipitation was applied to profile drug-treated and untreated RTK pathway-addicted cancer cell lines, with quantitiative analysis of the effects of SU11274 on the Met-addicted MKN45 cell line, Crizotinib on the Alk-addicted H3122 cell line, Gleevec on the PDGFRa-addicted H1703 cell line, and Iressa on the EGFR-addicted H3255 cell line. These samples were combined in 6-plex groups for TMT analysis with the A549 cell line serving as a non-responsive control. Serial fractionation and LCMS/MS analysis resulted in identification and quantification of hundreds of sites of phosphorylation, arginine methylation, and lysine acetylation. Those sites found to be drug-sensitive, including all PTM types, were used for pathway analysis of signaling downstream of each receptor tyrosine kinase (RTK) disease driver. Figure 1. Western blots used to select motif antibodies for phosphopeptide immunoprecipitation. Variation in cell signaling measured by ten different candidate motif antibodies was evaluated by performing Western blots of cell lysates from 22 different lung cancer cell lines. This screening tool allowed us to select those antibodies with the most diverse staining patterns across the cell lines for global pro- teomic PTM profiling. Phosphotyrosine, ATM/ATR substrate (s/tQ), acetyl-lysine, and methyl-arginine were all selected for use in peptide immunoprecipitation, allowing us to characterize and quantify a broad PTM space. In contrast, the CK2 substrate antibody showed less diverse staining and was not used in the cell line profiling studies. METHOD OF QUANTIFICATION Figure 4. Receptor tyrosine kinase disease drivers identified in appropriate cell lines using TMT HCD only method. The expected pat- terns of expressed and phosphorylated RTKs is observed, with PDGFRa in H1703, ALK in H3122, EGFR overexpressed in H3255, and Met in MKN45. EGFR is expressed in all of these immortal cell lines at some level, and phosphorylation of some sites (Y1110 for example) is detected in all cases. GSK3B is also constitutively expressed and phosphorylated. MKN45 has an extremely high level of tyrosine phosphorylation, so some interference is detected in the TMT channel associated with that cell line. Figure 5. Experimental flowchart. Cell lysates were prepared from RTK inhibitor treated and untreated cell lines, proteins were digested with trypsin, peptides were TMT-labeled, and samples were mixed for 6-plex analysis. The peptide mixtures were serially fractionated through immunoprecipitation with antibodies specific for phosphotyrosine, ATM/ATR substrate motif, AGC/CAMK/STE family kinase motif, acetyl-lysine, and methyl-arginine, though any motif-recognizing antibody could be used with this protocol. The enriched peptides from each immunoprecipitation were analyzed by LCMS/MS using an LTQ ® Orbitrap ® Elite, with quantification of the TMT labels enabled by HCD fragmentation. Figure 7. Example drug-responsive modification sites. Figure 8. Pathway diagrams for each cell line were generated using Cytoscape ® . These diagrams include all proteins with modification sites increasing or decreasing at least 2x upon relevant drug treatment. Proteins with PTM site peptides decreasing upon treatment (dark green protein names) are distinguished from those with sites increasing upon drug treatment (red protein names). Proteins identified in different PTM classes (phosphotyrosine, ATM/ ATR substrate phosphorylation, AGC/CAMK/STE kinase family motif phosphorylation, lysine acetylation, and arginine methylation) are distinguished by differ- ent colored protein symbols. Shapes of protein symbols signify protein functionality (cytoskeletal, adaptor, kinase, adhesion protein, etc.). First order interacting partners with the driving RTK are presented in bright yellow. Table 1. Number of modification sites identified and quantified for each PTM type analyzed. The 6-plex sample components are as follows: Sample Mix 1: A549 untreated, A549+Crizotinib, A549+Gleevec, A549+Iressa, A549+SU11274. Sample Mix 2: A549 untreated, A549+Crizotinib, H3122 untreated, H3122+Crizotinib, MKN45 untreated, MKN45+SU11274. Sample Mix 3: A549 untreated, A549+Iressa, H1703 untreated, H1703+Gleevec, H3255 untreated, H3255+Iressa. Figure 6. Percent of sites responsive for each PTM motif studied. At least a two-fold change in reporter ion signal/noise was required to be classified as responding. As expected, phosphotyrosine sites are the most responsive to RTK inhibition, but many other phosphorylation, acetylation, and methylation responses were also observed. COMBINING IMMOBILIZED METAL AFFINITY CHROMATOGRAPHY (IMAC) WITH PHOSPHOPEPTIDE IMMUNOPRECIPITATION :: Establish method for quantitative analysis of multiple classes of post-translational modifications from a single sample :: Apply method to investigate signaling downstream of several different oncogenic receptor tyrosine kinases :: Intelligent fractionation through sequential immunoprecipitation can be used to probe numerous PTM spaces, allowing in-depth pathway mapping of valuable samples :: Quantification and sample multiplexing with TMT labeling increases annotation rate over label-free quantification with lower sample analysis time :: Deep data sets generated through enrichment of different types of modified peptides allow elucidation of novel biological relationships Abstract Antibody Selection Evaluating LCMS methods Validating methods Results Objectives Summary 0 500 1000 1500 2000 2500 3000 label free (6 analyses) TMT - HCD only TMT - MS3 Number identified Quantification method selection: K-Ac redundant peptides unique peptides unique sites redundant peptides unique peptides unique sites 0 200 400 600 800 1000 1200 1400 1600 label free (5 analyses) TMT - HCD only TMT - MS3 Number identified Quantification method selection: R-Me 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 control 1 control 2 IMAC 1 IMAC 2 control 1 control 2 IMAC 1 IMAC 2 H3122 MKN45 Unique peptides identified Coupling IMAC with phosphopeptide IP total peptides phosphopeptides 0 0.2 0.4 0.6 0.8 1 1.2 Y768 Y1507 Y1197 Y1252 Y216 Y1110 PDGFRα ALK EGFR Met GSK3B EGFR Relative reporter ion signal/noise A549 H1650 H1703 H3122 H3255 MKN45 Cell line 1 Cell line 2 Cell line 3 IP ATM/ATR substrate peptides TMT labeling IP AGC kinase motif peptides IP acetyl-lysine peptides IP methyl-arginine peptides IP phosphotyrosine peptides Proteolytic digestion Mix samples LCMS/MS analysis t n a u q e d i t p e p T M T LCMS/MS analysis t n a u q e d i t p e p T M T LCMS/MS analysis t n a u q e d i t p e p T M T LCMS/MS analysis t n a u q e d i t p e p T M T LCMS/MS analysis t n a u q e d i t p e p T M T AGC/CAMK/STE kinase (107 sites total) Phosphotyrosine (532 sites total) ATM/A TR substrate (96 sites total) Acetyl-lysine (2514 sites total) Methyl-arginine (899 sites total) AGC/CAMK/STE kinase (102 sites total) phosphotyrosine Phosphotyrosine (566 sites total) ATM/ATR substrate (294 sites total) Acetyl-lysine (1999 sites total) Methyl-arginine (975 sites total) AGC/CAMK/STE kinase (102 sites total) Phosphotyrosine (1063 sites total) ATM/ATR substrate (329 sites total) Acetyl-lysine (1997 sites total) Methyl-arginine (998 sites total) AGC/CAMK/STE kinase (70 sites total) Acetyl-lysine (2508 sites total) Phosphotyrosine (364 sites total) ATM/ATR substrate (44 sites total) Methyl-arginine (868 sites total) unchanged up 2x down 2x unchanged up 2x down 2x unchanged up 2x down 2x unchanged up 2x down 2x H1703 cell line treated with PDGFRa inhibitor Gleevec MKN45 cell line treated with Met inhibitor SU11274 H3122 treated with ALK inhibitor Crizotinib H3255 treated with EGFR inhibitor Iressa RTK CTK AGC/CAMK/STE Family AGC/CAMK/STE Family Acetylation Acetylation PY PY Methylation Methylation G protein Surface Surface Adaptor Scaffold Adaptor Scaffold Adhesion Extracellular Matrix Adhesion Extracellular Matrix Cytoskeletal Protein Cytoskeletal Protein RNA Processing RNA Processing ATM/ATR Substrate S/T Kinase RTK RTK RTK S/T Kinase S/T Kinase S/T Kinase AGC/CAMK/STE Family AGC/CAMK/STE Family Acetylation Acetylation PY PY Translation Methylation Methylation G protein G protein G protein Transcriptional Regulator Transcriptional Regulator Surface Surface Unknown Function Adaptor Scaffold Adaptor Scaffold Adhesion Extracellular Matrix Adhesion Extracellular Matrix Cytoskeletal Protein Cytoskeletal Protein ATM/ATR ATM/ATR ATM/ATR CTK CTK CTK ALK driven signaling H3122 +/- Crizotinib PDGFRa driven signaling H1703 +/- Gleevec Met driven signaling MKN45 +/- SU11274 EGFR driven signaling H3255 +/- Iressa Contact Information Kimberly A. Lee, Cell Signaling Technology, Inc. Email: [email protected] PTMScan Services Department Email: [email protected] • web: www.cellsignal.com/services Cell Signaling Technology ® and PTMScan ® are trademarks of Cell Signaling Technology, Inc. / LTQ ® and Orbitrap ® are registered trademarks of Thermo Finnigan, LLC. / Cytoscape ® is a registered trademark of The Cytoscape Consortium. Sample Mix 1 Sample Mix 2 Sample Mix 3 Total Sites (nonredundant) phosphotyrosine 236 1111 572 1369 K-Ac 1928 1988 2492 3679 R-Me 757 986 900 1329 ATM/ATR substrate (pSQ) 264 384 135 574 ACG kinase motif 137 173 160 302 0 0.2 0.4 0.6 0.8 1 1.2 K37 K57 K348 K362 K19 K24 ALDH1A1 ALDH1A1 ALDH1A1 ALDH1A1 HIST2H3D HIST2H3D Relative abundance Acetyl-lysine 0 0.2 0.4 0.6 0.8 1 1.2 S836 S1610 S265 MCEF APC MAGE-D2 Relative abundance ATM/ATR substrate A549 A549+Crizotinib H3122 H3122+Crizotinib MKN45 MKN45+SU11274 A549 A549+Crizotinib H3122 H3122+Crizotinib MKN45 MKN45+SU11274 0 0.2 0.4 0.6 0.8 1 1.2 K37 K57 K348 K6 K9 K13 K17 ALDH1A1 ALDH1A1 ALDH1A1 HIST1H4J HIST1H4J HIST1H4J HIST1H4J Relative abundance Acetyl-lysine A549 A549+Iressa H1703 H1703+Gleevec H3255 H3255+Iressa 0 0.2 0.4 0.6 0.8 1 1.2 Y265 Y1367 Y68 EML4 Met cofilin 1 Relative abundance Phosphotyrosine 0 0.2 0.4 0.6 0.8 1 1.2 Y226 T231 S216 S684 RSK2 RSK2 AHNAK ERK3 Relative abundance AGC/CAMK/STE family kinase motif A549 A549+Iressa H1703 H1703+Gleevec H3255 H3255+Iressa 0 0.2 0.4 0.6 0.8 1 1.2 Y849 Y1172 Y68 PDGFRα EGFR cofilin 1 Relative abundance Phosphotyrosine A549 A549+Iressa H1703 H1703+Gleevec H3255 H3255+Iressa A549 A549+Crizotinib H3122 H3122+Crizotinib MKN45 MKN45+SU11274 0 0.2 0.4 0.6 0.8 1 1.2 Y34 T41 S216 S684 4E-BP1 4E-BP1 AHNAK ERK3 Relative abundance AGC/CAMK/STE family kinase motif A549 A549+Crizotinib H3122 H3122+Crizotinib MKN45 MKN45+SU11274 0 0.2 0.4 0.6 0.8 1 1.2 R64 R69 R108 R108 vimentin vimentin BAG4 SLC37A2 Relative abundance Methyl-arginine A549 A549+Iressa H1703 H1703+Gleevec H3255 H3255+Iressa Figure 2. Qualitative comparison of TMT labeling quantified by MS2 or MS3 with label-free quantification. Six cell lines (A549, H1650, H1703, H3122, H3255, and MKN45) either were processed individually and analyzed separately using 45 minute LCMS gradients and CID fragmentation (label-free), or were TMT-labeled and combined for immunoprecipitation. The TMT-labeled samples were analyzed using 150 minute LCMS gradients, either using HCD MS2 for both peptide identification and quantification in a single step (TMT-HCD only), or using CID MS2 for peptide identification with HCD MS3 for TMT quantification (TMT-MS3). The number of modification sites, unique peptides, and total redundant peptides identified using each method is displayed for acetyl-lysine and methyl-arginine immunoprecipitation samples. In all cases, the TMT method with HCD peptide identification and quantifica- tion resulted in discovery of the highest number of PTM sites, and this method was selected for further studies. Figure 3. IMAC sample clean-up step reduces background of non-phosphorylated peptides and allows identification of more phosphopeptides. Identical tyrosine phosphopeptide immunoprecipitations were performed and analyzed with or without subsequent IMAC to further enrich phosphopeptides over background unphosphorylated peptides. IMAC was found to significantly reduce levels of contaminating unphosphorylated peptides and thus increase the number of phosphopeptides identified.
Transcript of Immunoaffinity Enrichment and Quantitative Profiling of...
Klarisa Rikova, Ailan Guo, Kimberly A. Lee, Anthony Possemato, Yi Wang, Sean A. Beausoleil, Daniel E. Mulhern, Jian Min Ren, Michael J. CombCell Signaling Technology, Inc., Danvers, MA
Immunoaffinity Enrichment and Quantitative Profiling of Protein Phosphorylation, Methylation, and Acetylation in Receptor Tyrosine Kinase Pathway-addicted Cancer Cell Lines
Somatic mutation and altered protein expression patterns cause inappropriate activation and deactivation of key players in cellular signaling, result-
ing in the oncogenic phenotype. Phosphorylation patterns of oncogenes and other signaling proteins have been studied extensively in the last sev-
eral years, resulting in significant advances in our understanding of cancer and our ability to identify and therapeutically target tumor drivers.
Here we take the next step in this process, expanding the enriched, identified, and quantified post-translational modification (PTM) space to include not only
phosphopeptides but also acetylated, methylated, and ubiquitinated peptides, resulting in a multifaceted analysis of cellular protein modification to better under-
stand the complex signaling events of cancer biology.
Variation in cellular signaling measured by ten different candidate motif antibodies was evaluated by performing western blot analysis of cell lysates from 22 dif-
ferent lung cancer cell lines. This screening tool allowed us to select those antibodies with the most diverse staining patterns across the cell lines for global pro-
teomic PTM profiling. Phosphotyrosine, acetyl-lysine, methyl-arginine, ATM/ATR substrate (s/tQ), and AGC/CAMK/STE family kinase motif, which specifically
enriches close to 100 active kinase phosphopeptides, were all selected for use in peptide immunoprecipitation, allowing us to characterize and quantify a broad
PTM space.
Initial method development and PTM profiling were performed using a set of six lung cancer cell lines (A549, H1650, H1703, H3122, H3255, and MKN45) that
have different signaling pathways driving their growth and transformation. Phosphotyrosine profiling of these cell lines with tandem mass tag (TMT) quantifica-
tion revealed clear quantitative differences in phosphorylation, successfully identifying their activated signaling pathways.
The established method of TMT labeling coupled with serial peptide immunoprecipitation was applied to profile drug-treated and untreated RTK pathway-addicted
cancer cell lines, with quantitiative analysis of the effects of SU11274 on the Met-addicted MKN45 cell line, Crizotinib on the Alk-addicted H3122 cell line,
Gleevec on the PDGFRa-addicted H1703 cell line, and Iressa on the EGFR-addicted H3255 cell line. These samples were combined in 6-plex groups for TMT
analysis with the A549 cell line serving as a non-responsive control. Serial fractionation and LCMS/MS analysis resulted in identification and quantification of
hundreds of sites of phosphorylation, arginine methylation, and lysine acetylation. Those sites found to be drug-sensitive, including all PTM types, were used for
pathway analysis of signaling downstream of each receptor tyrosine kinase (RTK) disease driver.
Figure 1. Western blots used to select motif antibodies for phosphopeptide immunoprecipitation.
Variation in cell signaling measured by ten different candidate motif antibodies was evaluated by performing Western blots of cell lysates from 22 different
lung cancer cell lines. This screening tool allowed us to select those antibodies with the most diverse staining patterns across the cell lines for global pro-
teomic PTM profiling. Phosphotyrosine, ATM/ATR substrate (s/tQ), acetyl-lysine, and methyl-arginine were all selected for use in peptide immunoprecipitation,
allowing us to characterize and quantify a broad PTM space. In contrast, the CK2 substrate antibody showed less diverse staining and was not used in the
cell line profiling studies.
Method oF quAntiFicAtion
Figure 4. Receptor tyrosine kinase disease drivers identified in appropriate cell lines using tMt hcd only method. The expected pat-
terns of expressed and phosphorylated RTKs is observed, with PDGFRa in H1703, ALK in H3122, EGFR overexpressed in H3255, and Met in MKN45.
EGFR is expressed in all of these immortal cell lines at some level, and phosphorylation of some sites (Y1110 for example) is detected in all cases. GSK3B
is also constitutively expressed and phosphorylated. MKN45 has an extremely high level of tyrosine phosphorylation, so some interference is detected in
the TMT channel associated with that cell line.
Figure 5. experimental flowchart. Cell lysates were prepared from RTK inhibitor treated and untreated cell lines, proteins were digested with trypsin,
peptides were TMT-labeled, and samples were mixed for 6-plex analysis. The peptide mixtures were serially fractionated through immunoprecipitation with
antibodies specific for phosphotyrosine, ATM/ATR substrate motif, AGC/CAMK/STE family kinase motif, acetyl-lysine, and methyl-arginine, though any
motif-recognizing antibody could be used with this protocol. The enriched peptides from each immunoprecipitation were analyzed by LCMS/MS using an
LTQ® Orbitrap® Elite, with quantification of the TMT labels enabled by HCD fragmentation.
Figure 7. example drug-responsive modification sites.
Figure 8. Pathway diagrams for each cell line were generated using cytoscape®. These diagrams include all proteins with modification sites
increasing or decreasing at least 2x upon relevant drug treatment. Proteins with PTM site peptides decreasing upon treatment (dark green protein names) are
distinguished from those with sites increasing upon drug treatment (red protein names). Proteins identified in different PTM classes (phosphotyrosine, ATM/
ATR substrate phosphorylation, AGC/CAMK/STE kinase family motif phosphorylation, lysine acetylation, and arginine methylation) are distinguished by differ-
ent colored protein symbols. Shapes of protein symbols signify protein functionality (cytoskeletal, adaptor, kinase, adhesion protein, etc.). First order interacting
partners with the driving RTK are presented in bright yellow.
table 1. number of modification sites identified and quantified for each PtM type analyzed. The 6-plex sample components are as follows:
Sample Mix 1: A549 untreated, A549+Crizotinib, A549+Gleevec, A549+Iressa, A549+SU11274.
Sample Mix 2: A549 untreated, A549+Crizotinib, H3122 untreated, H3122+Crizotinib, MKN45 untreated, MKN45+SU11274.
Sample Mix 3: A549 untreated, A549+Iressa, H1703 untreated, H1703+Gleevec, H3255 untreated, H3255+Iressa.
Figure 6. Percent of sites responsive for each PtM motif studied. At least a two-fold change in reporter ion signal/noise was required to be
classified as responding. As expected, phosphotyrosine sites are the most responsive to RTK inhibition, but many other phosphorylation, acetylation, and
methylation responses were also observed.
coMbining iMMobiLized MetAL AFFinity chRoMAtogRAPhy (iMAc) With PhosPhoPePtide iMMunoPReciPitAtion
:: establish method for quantitative analysis of multiple classes of post-translational modifications from a single sample
:: Apply method to investigate signaling downstream of several different oncogenic receptor tyrosine kinases
:: intelligent fractionation through sequential immunoprecipitation can be used to probe numerous PtM spaces, allowing in-depth
pathway mapping of valuable samples
:: quantification and sample multiplexing with tMt labeling increases annotation rate over label-free quantification with lower
sample analysis time
:: deep data sets generated through enrichment of different types of modified peptides allow elucidation of novel biological
relationships
Abstract
Antibody Selection
Evaluating LCMS methods
Validating methods
Results
Objectives
Summary
0
500
1000
1500
2000
2500
3000
label free (6 analyses) TMT - HCD only TMT - MS3
Nu
mb
er id
enti
fied
Quantification method selection: K-Ac
redundant peptides
unique peptides
unique sites
redundant peptides
unique peptides
unique sites
0
200
400
600
800
1000
1200
1400
1600
label free (5 analyses) TMT - HCD only TMT - MS3
Nu
mb
er id
enti
fied
Quantification method selection: R-Me
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
control 1 control 2 IMAC 1 IMAC 2 control 1 control 2 IMAC 1 IMAC 2
H3122 MKN45
Un
iqu
e p
epti
des
iden
tifi
ed
Coupling IMAC with phosphopeptide IP
total peptides
phosphopeptides
0
0.2
0.4
0.6
0.8
1
1.2
Y768 Y1507 Y1197 Y1252 Y216 Y1110
PDGFRα ALK EGFR Met GSK3B EGFR
Rel
ativ
e re
po
rter
ion
sig
nal
/no
ise
A549
H1650
H1703
H3122
H3255
MKN45
Cell line 1
Cell line 2
Cell line 3
IP ATM/ATR substrate peptides
TMT labeling
IP AGC kinase motif peptides
IP acetyl-lysine peptides
IP methyl-arginine peptides
IP phosphotyrosine peptides
Proteolytic digestion
Mix samples
LCMS/MS analysis
tnauq editpep TMT
LCMS/MS analysis
tnauq editpep TMT
LCMS/MS analysis
tnauq editpep TMT
LCMS/MS analysis
tnauq editpep TMT
LCMS/MS analysis
tnauq editpep TMT
AGC/CAMK/STE kinase (107 sites total)
Phosphotyrosine (532 sites total)
phosphotyrosine
ATM/ATR substrate (96 sites total)
Acetyl-lysine (2514 sites total)
Methyl-arginine (899 sites total)
AGC/CAMK/STE kinase (102 sites total)
phosphotyrosine
Phosphotyrosine (566 sites total)
ATM/ATR substrate (294 sites total)
Acetyl-lysine (1999 sites total)
Methyl-arginine (975 sites total)
AGC/CAMK/STE kinase (102 sites total)
phosphotyrosine
Phosphotyrosine (1063 sites total)
ATM/ATR substrate (329 sites total)
Acetyl-lysine (1997 sites total)
Methyl-arginine (998 sites total)
AGC/CAMK/STE kinase (70 sites total)
Acetyl-lysine (2508 sites total)
phosphotyrosine
Phosphotyrosine (364 sites total)
ATM/ATR substrate (44 sites total)
Methyl-arginine (868 sites total)
unchanged up 2x down 2x
unchanged up 2x down 2x
unchanged up 2x down 2x
unchanged up 2x down 2x
h1703 cell line treated with PdgFRa inhibitor gleevecMKn45 cell line treated with Met inhibitor su11274
h3122 treated with ALK inhibitor crizotinibh3255 treated with egFR inhibitor iressa
RTK
CTK
AGC/CAMK/STE Family
AGC/CAMK/STE Family
Acetylation
Acetylation
PY
PY
Methylation
Methylation
G protein
Surface
Surface
AdaptorScaffold
AdaptorScaffold
Adhesion Extracellular Matrix
Adhesion Extracellular Matrix
CytoskeletalProtein
CytoskeletalProtein
RNAProcessing
RNAProcessing
ATM/ATR Substrate
S/T Kinase
RTK
RTK
RTK
S/T Kinase
S/T Kinase
S/T Kinase
AGC/CAMK/STE Family
AGC/CAMK/STE Family
Acetylation
Acetylation
PY
PY
Translation
Methylation
Methylation
G protein
G protein
G protein
TranscriptionalRegulator
TranscriptionalRegulator
Surface
Surface
UnknownFunction
AdaptorScaffold
AdaptorScaffold
Adhesion Extracellular Matrix
Adhesion Extracellular Matrix
CytoskeletalProtein
CytoskeletalProtein
ATM/ATR
ATM/ATR
ATM/ATR
CTK
CTK
CTK
ALK driven signaling h3122 +/- crizotinib
PdgFRa driven signaling h1703 +/- gleevec
Met driven signaling MKn45 +/- su11274
egFR driven signaling h3255 +/- iressa
Contact InformationKimberly A. Lee, Cell Signaling Technology, Inc. email: [email protected]
PTMScan Services Department email: [email protected] • web: www.cellsignal.com/servicesCell Signaling Technology® and PTMScan® are trademarks of Cell Signaling Technology, Inc. / LTQ® and Orbitrap® are registered trademarks of Thermo Finnigan, LLC. / Cytoscape® is a registered trademark of The Cytoscape Consortium.
sample Mix 1 sample Mix 2 sample Mix 3 total sites (nonredundant)
phosphotyrosine 236 1111 572 1369K-Ac 1928 1988 2492 3679R-Me 757 986 900 1329ATM/ATR substrate (pSQ) 264 384 135 574ACG kinase motif 137 173 160 302
0
0.2
0.4
0.6
0.8
1
1.2
K37 K57 K348 K362 K19 K24
AL
DH
1A1
AL
DH
1A1
AL
DH
1A1
AL
DH
1A1
HIS
T2H
3D
HIS
T2H
3D
Rel
ativ
e ab
un
dan
ce
Acetyl-lysine
0
0.2
0.4
0.6
0.8
1
1.2
S836 S1610 S265
MC
EF
AP
C
MA
GE
-D2
Rel
ativ
e ab
un
dan
ce
ATM/ATR substrate
A549
A549+Crizotinib
H3122
H3122+Crizotinib
MKN45
MKN45+SU11274
A549
A549+Crizotinib
H3122
H3122+Crizotinib
MKN45
MKN45+SU11274
0
0.2
0.4
0.6
0.8
1
1.2
K37 K57 K348 K6 K9 K13 K17
AL
DH
1A1
AL
DH
1A1
AL
DH
1A1
HIS
T1H
4J
HIS
T1H
4J
HIS
T1H
4J
HIS
T1H
4J
Rel
ativ
e ab
un
dan
ce
Acetyl-lysine
A549
A549+Iressa
H1703
H1703+Gleevec
H3255
H3255+Iressa
0
0.2
0.4
0.6
0.8
1
1.2
Y265 Y1367 Y68
EM
L4
Met
cofi
lin 1
Rel
ativ
e ab
un
dan
ce
Phosphotyrosine
0
0.2
0.4
0.6
0.8
1
1.2
Y226 T231 S216 S684
RS
K2
RS
K2
AH
NA
K
ER
K3
Rel
ativ
e ab
un
dan
ce
AGC/CAMK/STE family kinase motif
A549
A549+Iressa
H1703
H1703+Gleevec
H3255
H3255+Iressa
0
0.2
0.4
0.6
0.8
1
1.2
Y849 Y1172 Y68
PD
GF
Rα
EG
FR
cofi
lin 1
Rel
ativ
e ab
un
dan
ce
Phosphotyrosine
A549
A549+Iressa
H1703
H1703+Gleevec
H3255
H3255+Iressa
A549
A549+Crizotinib
H3122
H3122+Crizotinib
MKN45
MKN45+SU11274
0
0.2
0.4
0.6
0.8
1
1.2
Y34 T41 S216 S684
4E-B
P1
4E-B
P1
AH
NA
K
ER
K3
Rel
ativ
e ab
un
dan
ce
AGC/CAMK/STE family kinase motif
A549
A549+Crizotinib
H3122
H3122+Crizotinib
MKN45
MKN45+SU11274
0
0.2
0.4
0.6
0.8
1
1.2
R64 R69 R108 R108
vim
enti
n
vim
enti
n
BA
G4
SL
C37
A2
Rel
ativ
e ab
un
dan
ce
Methyl-arginine
A549
A549+Iressa
H1703
H1703+Gleevec
H3255
H3255+Iressa
Figure 2. qualitative comparison of tMt labeling quantified by Ms2 or Ms3 with label-free quantification. Six cell lines (A549, H1650,
H1703, H3122, H3255, and MKN45) either were processed individually and analyzed separately using 45 minute LCMS gradients and CID fragmentation
(label-free), or were TMT-labeled and combined for immunoprecipitation. The TMT-labeled samples were analyzed using 150 minute LCMS gradients, either
using HCD MS2 for both peptide identification and quantification in a single step (TMT-HCD only), or using CID MS2 for peptide identification with HCD
MS3 for TMT quantification (TMT-MS3). The number of modification sites, unique peptides, and total redundant peptides identified using each method is
displayed for acetyl-lysine and methyl-arginine immunoprecipitation samples. In all cases, the TMT method with HCD peptide identification and quantifica-
tion resulted in discovery of the highest number of PTM sites, and this method was selected for further studies.
Figure 3. iMAc sample clean-up step reduces background of non-phosphorylated peptides and allows identification of more
phosphopeptides. Identical tyrosine phosphopeptide immunoprecipitations were performed and analyzed with or without subsequent IMAC to further
enrich phosphopeptides over background unphosphorylated peptides. IMAC was found to significantly reduce levels of contaminating unphosphorylated
peptides and thus increase the number of phosphopeptides identified.
