Using Data‐Independent LC/MSE for Studying Protein Secretion and Modification Dynamics

Kevin BlackburnMolecular and Structural Biochemistry

North Carolina State UniversityRaleigh, NC

Who we are and what we do…• Mass Spectrometry Facility in the Department of Molecular

and Structural Biochemistry (Michael Goshe, PI)– In operation ~6 years; potential for additional MS faculty hires– In 2007, NSF funded NanoAcquity UPLC/Q-Tof Premier purchase– In 2008, moved into new 1100 ft2 MS lab

• Areas of Interest– Protein structure (crosslinking)– Protein modification (phosphorylation)– Proteomics (interaction and expression)

• Operational Model-collaboration only– Large, diverse group of collaborators from across campus– Significant level of work in plants

NanoAcquity and Q‐Tof Premier Critical Capabilities

• High-resolution chromatographic separations– Critical for resolution of structurally similar species

• Accurate mass, high resolution mass measurement– Specificity and confidence in complex samples

• Parallel fragmentation through LC/MSE

– Increased duty cycle translates into improved protein and proteome coverage compared to MS/MS based approaches

• Low stoichiometry modifications• Low abundance proteins

– Simultaneous identification and quantification• Relative and absolute quantification

Data Dependent Acquisition (DDA):  Serial Interrogation by LC/MS/MS

MS2 is a BIASED processMS2 is a DISCONTINUOUS process

Data‐Independent Acquisition (DIA) by LC/MSE:  Parallel Fragmentation

MSE is a UNBIASED processMSE is a CONTINUOUS process

Undersampling is an unavoidable consequence of DDA

MSE

DDA

Number and replication of peptide matches improves with MSE

MSE

DDA Replication

ProteinUnique Peptide

Matches 3 of 3 2 of 3 1 of 3PYGM_RABIT 2 0 0 2ADH1_YEAST 5 0 1 4ENO1_YEAST 4 0 2 2ALBU_BOVIN 21 4 3 14Totals 32 4 6 22% of Total 12.5 18.8 68.8

Replication

ProteinUnique Peptide

Matches% Increase over DDA 3 of 3 2 of 3 1 of 3

PYGM_RABIT 23 1050 14 7 2ADH1_YEAST 12 140 11 0 1ENO1_YEAST 7 75 6 0 1ALBU_BOVIN 32 52.4 28 3 1Totals 74 59 10 5% of Total 79.7 13.5 6.8

Sequence coverage improves with MSE with lower FPR

MSE

DDA Sequence Coverage (%)Protein Injection 1 Injection 2 Injection 3

PYGM_RABIT 0.0 2.5 0.0ADH1_YEAST 4.3 6.0 6.3ENO1_YEAST 6.6 1.8 4.3ALBU_BOVIN 16.3 26.5 13.0

Sequence Coverage (%)Protein Injection 1 Injection 2 Injection 3

PYGM_RABIT 27.3 30.4 23.7ADH1_YEAST 34.2 28.2 29.9ENO1_YEAST 22.0 22.0 22.0ALBU_BOVIN 44.0 44.5 43.2

Sequence Coverage Summary

Protein MS^E DDA% Increase over DDA Amount

PYGM_RABIT 27.1 0.8 3156 25 fmolADH1_YEAST 30.8 5.5 456 50 fmolENO1_YEAST 22.0 4.2 420 100 fmolALBU_BOVIN 43.9 18.6 136 400 fmol

FPR:  13.4%

FPR:  2.0%

LC/MSE Analysis of Phosphorylation Dynamics of the LRR RLK BRI1

Develop. Cell 2008; 15:220-235

Ligand Binding       Phosphorylation and Downstream Signaling

JUXTAMEMBRANE : 4 in vivo phosphorylation sites,

KINASE DOMAIN : 1 in vivo phosphorylation site

CARBOXY TERMINAL: 1 in vivo phosphorylation site

ACTIVATION LOOP

PREDICTED PHOSPHORYLATION SITES

Summary of BRI1 Phosphorylation Sites Identified by LC/MS/MS

Model of BRI1/BAK1 Interaction

Wang et al., Develop. Cell 2008;15:220-235.

Can we demonstrate transphosphorylation of specific BRI1 sites upon BAK1 hetero‐dimerization by MS?

LC/MS/MS analysis of BRI1 +/‐ BAK1 provides inconclusive site assignment data

T1169

+BAK1 -BAK1

T1169Score 77 Score 67

DDA data suggests phosphorylation of T1169 in both + and – BAK1 conditions.

LC/MSE elution profile suggests multiple phosphoforms of EIQAGSGIDSQSTIR 

Nonphos

MonophosDDA

BPI

Both peaks correspond to mono‐phosphorylated EIQAGSGIDSQSTIR 

XFW_1_flagBRI1_CD_bak1-CD_MSE_25Mar08

Time20.50 21.00 21.50 22.00 22.50 23.00 23.50 24.00 24.50 25.00 25.50 26.00 26.50 27.00 27.50

%

0

100XFW_1_flagBRI1_CD_bak1-CD_MSE_25Mar08 1: TOF MS ES+

821.37 0.10Da4.67e3

23.96

23.42

Capture of site‐specific product ions from MSE enables site assignment

S1166 S1168 T1169 T1169 S1168 S1166b-98 b b-98 b b-98 b y y-98 y y-98 y y-98

15 - - - - - - Arg 175.1 175.1 175.1 114 1369.6 1467.6 1369.6 1467.6 1369.6 1467.6 Ile 288.2 288.2 288.2 213 1256.6 1354.6 1256.6 1354.6 1256.6 1354.6 Thr 469.2 371.2 389.3 389.3 312 1155.5 1253.5 1155.5 1253.5 1173.5 Ser 556.3 458.3 556.3 458.3 476.3 411 1068.5 1166.5 1086.5 1086.5 Gln 684.3 586.3 684.3 586.3 604.3 510 940.4 1038.4 958.5 958.5 Ser 771.3 673.3 771.3 673.3 771.3 673.3 69 871.4 871.4 871.4 Asp 886.7 788.7 886.7 788.7 886.7 788.7 78 756.4 756.4 756.4 Ile 999.5 901.5 999.5 901.5 999.5 901.5 87 643.3 643.3 643.3 Gly 1056.5 958.5 1056.5 958.5 1056.5 958.5 96 586.3 586.3 586.3 Ser 1143.5 1045.5 1143.5 1045.5 1143.5 1045.5 105 499.3 499.3 499.3 Gly 1200.5 1102.5 1200.5 1102.5 1200.5 1102.5 114 442.2 442.2 442.2 Ala 1271.6 1173.6 1271.6 1173.6 1271.6 1173.6 123 371.2 371.2 371.2 Gln 1399.6 1301.6 1399.6 1301.6 1399.6 1301.6 132 243.1 243.1 243.1 Ile 1512.7 1414.7 1512.7 1414.7 1512.7 1414.7 141 130.1 130.1 130.1 Glu - - - - - - 15

S1166: 476.3, 604.3

S1168: 389.3, 556.3, 458.3, 1166.5, 1068.5

T1169: 469.2

Ret. TimeSite 23.4 23.9S1166

476.3 - Y604.3 - Y

S1168389.3 - Y556.3 Y Y458.3 Y -

1166.5 - -1068.5 - Y

T1169469.2 Y -

S1168/T1169S1166

S1166 is clearly assigned at 23.9’ by MSERet. Time

Site 23.4 23.9S1166

476.3 - Y604.3 - Y

S1168389.3 - Y556.3 Y Y458.3 Y -

1166.5 - -1068.5 - Y

T1169469.2 Y -

**

Phosphorylation stoichiometry may be determined from LC/MSE intensity data

%Phos = (Intensity Phos/Total Intensity) * 100%

+ Bak1 - Bak1

S1166 30% 18%

S1168/T1169 23% 22%

LC/MSE quantitation confirms BAK1 transphosphorylates BRI1 at S1166 but not S1168/T1169 

Wang, X., et al. Develop. Cell 2008;15:220-235

Conclusions• NanoAcquity UPLC enables separation of many

chemically related phosphorylated peptide species• Coupled with UPLC, data-independent LC/MSE

minimizes inherent biases associated with DDA – duty cycle – precursor intensity bias– “mixed” precursor interrogation

• Both of the above attributes move us towards comprehensive, unambiguous, site-specific characterization of phosphorylation

Global Analysis of Pathogen‐Induced Protein Secretion Responses in Arabidopsis

• Goals– ID of novel pathogen

response proteins in Arabidopsis

• Approach– Absolute quantitation

by LC/MSE

Cheng et al., J. Prot Res. 2009; 8: 82-93.

Dose‐Response Time‐Course Study Design

• Media contamination assessed with G6PDH activity assay and HK protein blot analysis.

• Each sample spiked with 50 fmol per injection Rabbit Phosphorylase B, duplicate injections

• Absolute quantitation (Silva et al, Molecular and Cellular Proteomics, 2006)

Summary of Results

• 76 proteins were identified in the Arabidopsis secretome, with 67 of these exhibiting SA-induced secretion

• Identification of well characterized pathogen induced proteins– PR3, chitinases, peroxidases

• Identification of a number of SA-induced proteins lacking secretion signal sequences – PBP-1, DREPP, Cu/Zn SOD, Fe SOD

• Absolute quantitation assigned protein amounts spanning 3 orders of magnitude (~ 5 fmol to ~3 pmol), allowing comparisons between quantities (fmol/ng) of secreted proteins– Time course data coupled with abundance data provides insight into functional

roles of some secreted proteins.• Data suggest the existence of non-classical (non-Golgi mediated),

uncharacterized mechanisms of pathogen-induced protein secretion in Arabidopsis

Osmotin 34 (AT4G11650.1)

Jacalin lectin family protein (AT3G16390.1)

Peroxides 32(AT3G32980.1)

AALP Cysteine type peptidase (AT5G60360.2 )

CSD1 Copper/zinc SOD (AT1G08830.1)

GDH1 Glutamate dehydrogenase (AT5G18170.1)

GDH1 Glutamate dehydrogenase (AT5G18170.1)

PR3 (AT3G12500)

Calmodulin binding protein (AT1G08110.4 )

Calmodulin binding protein (AT1G08110.4 )

FAD-binding domain-

containing protein (AT4G20830.1 )

FAD-binding domain-

containing protein (AT4G20830.1 )

BGLU46 Hydrolase(AT1G61820.1 )

BGLU46 Hydrolase(AT1G61820.1 )

Alpha-galactosidase

(AT3G56310.1 )

Alpha-galactosidase

(AT3G56310.1 )

FSD1 Fe Superoxide dimutase (AT4G25100.1)

FSD1 Fe Superoxide dimutase (AT4G25100.1)

LOS2 Low expression of osmotically responsive genes (AT2G36530.1) LOS2 Low expression of osmotically responsive genes (AT2G36530.1)

LTP3 Lipid transfer protein 3 (AT5G59320.1)

LTP3 Lipid transfer protein 3 (AT5G59320.1)

LP2 (AT2G38530.1) LP2 (AT2G38530.1)

A B

C D

Temporal regulation of protein secretion falls into 4 categories

Secretion pattern of individual proteins correspond to their temporal regulation in plant-pathogen interactions All plants respond to pathogen attack by initiating sequential transient or sustained defense process.

Secretion profiles for selected SA‐responsive proteins by LC/MSE absolute quantitation

Signal PeptideNo Signal Peptide

Signal P Prediction

Pathogen attack

Generation and perception of

elicitors

Oxidativeburst

Defense response

Elicitors are signal molecules released

by pathogen or plant cell walls

Rapid, transient production of

ROS

Downstream defense

mechanisms including HR,

SAR

Transient and sustained processes are initiated Transient and sustained processes are initiated after pathogen infectionafter pathogen infection

Pathogen attack

Generation and perception of

elicitors

Oxidativeburst

Defense response

PR3:a chitinase that hydrolyzes fungal cell wall to release chitin fragments/elicitors

fungus

Pathogen attack

Generation and perception of

elicitors

Oxidativeburst

Defense response

Peroxidase 34:Involved in the production of ROS

SOD:Involved in the regulation of ROS generation

Pathogen attack

Generation and perception of

elicitors

Oxidativeburst

Defense response

Extracellular dermal glycoprotein:Similar to tomato XEG inhibitor protein (XEGIP).

fungusFungal XEG

Hydrolysis of plant cell wall

XEGIP (Plant Xyloglucan-specific fungal endoglucanase inhibitor protein)

Conclusions• Data-independent LC/MSE has provided a phenomenally

high resolution picture of pathogen-induced protein secretion dynamics in Arabidopsis– Absolute quantitation provided another layer of functional

information above that of relative quantitation alone• Ongoing work using LC/MSE with absolute quantitation to discover and

quantify novel proteins in the human ciliary axoneme is very promising!– Label free aspects of LC/MSE are attractive

• Minimal chemistry/sample prep• Adaptability to complex multi-factor study designs

– Excellent protein sequence coverage often allows differentiation of protein isoforms

• Distribution of intensity across 14-3-3 proteins in a plant hormone study

AcknowledgementsMolecular and Structural

Biochemistry (NCSU)Dr. Michael B. Goshe

Uma Kota (PhD Candidate)

Waters CorporationScott Geromanos

Hans VissersRoy MartinTom Hayes

Funding SourcesUSDA NRI 2005-35604-15420 NSF MCB-0419819USDA NRI 2005-35604-16739 NSF DBI-0619250USDA NRI 2006-35204-17351North Carolina Agricultural Research Service (NCARS)

Horticultural Science (NCSU)Dr. Steve Clouse

Dr. Xiaofeng WangDr. Srijeet Mitra

Dr. John WilliamsonDr. Fang-yi Cheng