lecture 10: quantitative proteomics...1 mass spectrometry in an “omics” world. me.330.804...

1

Mass Spectrometry in an “Omics” World. ME.330.804

Lecture 10: Quantitative ProteomicsWednesday, November 14, 2012

Robert N. Cole, Ph.D.Mass Spectrometry and Proteomics Facility Johns Hopkins School of Medicine371 Miller Research Bldg (formally BRB)Ph: (410) 614-6968

email: [email protected]

Quantitative ProteomicsQuantifying Individual Proteins in Complex Mixtures

(Functional Proteomics)

Changes in protein levels(biomarkers, pathways, binding partners)

Applications

( p y g p )

Changes in protein modifications (structure/function)

Changes in subcellular localization (trafficking)

Kinetics (protein turnover, modification dynamics)

Quantitative Proteomics Methods

Label-Free Labeling

ChemicalMetabolic Enzymatic

DIGE (Difference Gel Electrophoresis)Radiolabeling 18O-Labeling

Relative Absolute

ICAT (Isotope-Coded Affinity Tags)

TMT (Tandem Mass Tags)

iTRAQ (Isobaric Tags for Relativeand Absolute Quantitation)

SILAC

DensitometryPeak IntensitySpectral Counting

AQUA (Absolute Quantification)MRM (Multiple Reaction Monitoring)QconCAT (Quantification Concatamers)PSAQ (Protein Standard Absolute Quantification)SWATH

Best Approach?

All approaches are: Complementary

different separation techniquesdifferent sets of proteins identified

There is NO one best approach.

Technically challengingsample preparationdata acquisitiondata analysis

Require fractionation to dig deeper into proteomelimited by dynamic range

2

Best Quantitative Proteomic Experiments

Defined question (i.e. hypothesis driven)

Defined system

Independently measurable phenotype

Sample preparationReproducibleScalableCompatible buffer system

Sample Preparation(Most Important Step!)

Reproducibility

Fractionation(reduce protein amount and complexity,enrich for target proteins)

Buffer Exchange(remove non-compatible buffer reagents)

Must Be Reproducible and Standardized!

Biological Replicates

1 2 3

InitialProtocol

StandardizedProtocol

1 2 3

Reduce Sources of Variability:Technical: “good” < “bad hands”

few < many steps

Biological: cells < tissue < body fluidsyeast < nematode < human

Fractionate to Detect Low Abundance Proteins

MWkD

115

MW

S

BS

A

180

Total Serum

Top 6 proteins removed

1158264

4937

261915

6

4-12% SDS-PAGE, SimplyBlue stain

3

1D

pI3.0 11.0

250150

75

50

37

25

10

pI3.0 11.0

250150

75

50

37

25

10

250150

75

50

37

25

10

2D

versus

7 cm versus 24 cm

10.53.5 5.8 8.2

Buffer Reagents CompatibilityDepends on the Proteomic Method

Three non-compatible categoriesDetergentsSaltsReagents that compete for label

Buffer exchange to make compatibleFiltrationPrecipitationBinding Affinity(Dilution)

Detecting low abundance proteins requires“Clean samples”, no interfering reagents


Label-Free Labeling



Relative Absolute




SILAC

DensitometryPeak IntensitySpectral Counting


Label-Free Methods

No additions to analysis

Separate analysis of Each sample

Biological Variability


Technical Variability (Sample Prep and MS analysis)

4

Bacterial Strain #1 Bacterial Strain #2

pIMW

Label-Free: Densitometry - 2D Gels

Compare spots from different gelsQuantify by relative spot volume (or number of peptides)Gel reproducibility and spot matching criticalGel warping for matching spots can warp out modificationOften more than one protein per spot

Label-Free: Spectral Counting -1D Gels

21

Sample

Slice

2 Sample 1 Sample 2

22 Polymereic Immunoglobulin Receptor 15 5

22 Transferrin 5 1022 Vanin 1 5 5

21 1B-glycoprotein21 Complement component 5

21hGC-1 (human G-CSF-stimulated clone-1

21 1 G F bi di t i

Gel Slice Number

Protein IdentifiedNumber of Spectra

Molecular Cell Proteomics 3:715, 2004.

Comparing protein bands on same gelQuantify by number of peptide spectra from protein At same MW, more spectra = more protein

21 1gG Fc-binding protein21 Mac-2-gining protein

18 antichymotrypsin18 Albumin

Label-Free: Peak AreaQuantify each protein from:

intensity of 3 most intense peptidesaveraged from 3 technical replicates

Each sample separate LCMS/MS experiment

m/z

3DPeak Intensity

Map

sity

Time

Annotate“Spots”

Reproducibility of LCMS/MS is critical

Time (min)

Inte

ns

Compares multiple LCMS/MS experiments

Label-Free: Spectral CountingQuantify each protein from:

number of peptides from protein number of spectra for each peptide

Each sample separate LCMS/MS experiment

sity

n N

um

be

r

Compares multiple LCMS/MS experiments

Reproducibility of LCMS/MS system critical

Time (min)

Inte

ns

Sample

1 32 4Protein Name Ac

ce

ss

ion

MW

5

Gels

Cells Tissue or Fluid

Label-Free Workflows

Protein Extract

ProteolysisGel matching

Fractionation

MSPeak Area

Spectral Counting

Confirmation

MS2

MS3

Peptide/Protein ID

g

Densitometry


Label-Free Labeling



Relative Absolute




SILAC

Gel matchingDensitometryPeak IntensitySpectral Counting


Non-Labeling Methods

No additions to analysis

Separate analysis of Each sample

Biological and Technical Variability


Labeling Methods

Typically adds steps to analysis

Simultaneous analysis of Many samples (Multiplexing)

Biological Variability, Reduces Technical Variability

Cuts instrument time (data collection) by 50-75%

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC)

Metabolic Labeling: No Technical Variability

12C-Arg 13C-Arg

Mix Cells

12C-Arg 13C-Arg

Mix Cells

12C-Arg 13C-Arg

Mix Cells

Control Treated

Only for cell cultureNo added steps

Ong et al. J P t RMix Cells

Isolate proteins and digest with trypsin

Peptide ID and quantify by tandem MS

Mix Cells


Mix Cells



No added stepsStandard Deviations 5%

Quantify mass pairs

J Proteome Res 2: 173, 2003

6

Quantify by 13C to 12C-Arg-labeled peptide ratios

J Proteome Res 2: 173, 2003

By using13C and 15N Arg:Can increase mass difference to 9 Da,Analyze 2 to 4 samples per experiment

Chemical Labeling:Difference Gel Electrophoresis (DIGE)

Disease Protein ExtractLabel with fluor 2

Control Protein ExtractLabel with fluor 1

Separate proteins on one 2-D gel

Mix labeled proteins from both samples

p p g

Excitation wavelength 1


Image gel

View differences

Unlu et al. Electrophoresis 18:2071, 1997

Protein comparison in a single gel!

Three Fluorescent Cy Dyes

Cy2, Cy3, Cy5

-amino group of lysine

Matched for Charge and MW

Third Cy Dye used as an Internal Standard

Cy2

Cy5

Cy3

Third Cy Dye used as an Internal Standard

All possible protein spots overlaid on every gel.

Simplifies gel to gel matching.

Each spot has it’s own internal standard spot fornormalizing across gels.

Reduces experimental variations.

Accounts for differences in sample load.

Separate proteins on one 2-D gel

Mix samples

DIGE Analysis Pooled Samples labeled with Cy2(on all gels to compare one gel to another)

Disease Protein ExtractLabel with Cy5

Control Protein ExtractLabel with Cy3

p p g



One additional stepReduced technical variabilityQuantify intact proteinsCells, tissue, fluids

7

1

2

5

6

9

10

13

14

3

4

7

8

11

12

15

16

Enzymatic Labeling: 18O-labeling ProtocolExperimental Protein Extract

Control Protein Extract

Trypsin Trypsin + 18O-water

Anal. Chem 73:2836, 2001J Proteome Res 2:147, 2003

Cells, tissue, fluidsNo added stepsNo MS technical variability

Variability in protein extractionStandard deviations 10-20%Loss of label to water

Mix labeled peptides


C-terminal C-terminal(adds 4 Da)

Quantify by 18O to 16O peptide ratios

Peptide sequencePeak intensity ratio

± errorNWAAFR 2.5 ± 0.1GNVYWVR 3.4 ± 0.7GVIETVYLR 3.0 ± 0.3LLTPNEFEIK 3.1 ± 0.5VAITFDSSVSWPGNDR 2.9 ± 0.4NLLLLPGSYTYEWNFR 2.8 ± 0.2

(4%)(20%)(10%)(19%)(14%)

(7%)

Only 4 Da mass difference18O exchange with waterCompares only 2 samples per experimentNo good analysis software yet Anal. Chem 73:2836, 2001

Chemical Labeling: Mass Tags (in 3 Flavors)

Mass Tag CompanyNumber of Tags

4-plex iTRAQApplied

Biosystems4

8-plex iTRAQApplied

Biosystems8

TMT ThermoFisher6

iTRAQ = Isobaric Tag for Relative and Absolute Quantitation

TMT = Tandem Mass Tags

8

iTRAQ Tags(Isobaric Tag for Relative and Absolute Quantitation)

Peptide Reactive

Reporter Balance PRG

Reporter Mass Balance Mass

Isobaric Tag(Total mass = 305)

Eight possible tags

Group(binds to amines)

113114115116117118119121

192191190189188187186184 Ross et al. 2004 MCP 3:1154

Pierce et al 2007 MCP 7:853Charged Neutral

Label Peptides

Peptides:

8-plex iTRAQ Workflow

Proteins:

S2114

S3115

S4116

S5117

S6118

S7119

S8121

S1113

S2 S3 S4 S5 S6 S7 S8S1

S2 S3 S4 S5 S6 S7 S8S1

All MixedPeptides

Analyze each SCX Fraction by LC-MS/MS

Fractionate Peptide Mixture on SCX or bRP Column

Mix Labeled Peptides

114 115 116 117 118 119 121113 Mixed

272.17434.25

1173.58

Gates_ITRAQ_8Plex_SCX-1#6263 RT: 62.61 AV: 1 NL: 6.05E5T: FTMS + p NSI d Full ms2 [email protected] [110.00-2000.00]

50

60

70

80

90

100

bu

nd

an

ce

Fragmentation SpectrumiTRAQ-EESPLLIGQQSTVSDVPR

Fragmentation Spectrum

y2272.17 b1

434.25 y111173.58

b3

Sequence b-ionb-ion mass

y-iony-ion mass

iTRAQ-E 1 434.255 18 2259.210E 2 563.298 17 1825.966S 3 650.330 16 1696.923P 4 747.383 15 1609.891L 5 860.467 14 1512.838L 6 973.551 13 1399.754I 7 1086.635 12 1286.670G 8 1143.656 11 1173.586Q 9 1271.715 10 1116.564Q 10 1399.773 9 988.506S 11 1486.806 8 860.447T 12 1587.853 7 773.415V 13 1686.922 6 672.368S 14 1773.954 5 573.299D 15 1888.981 4 486.267V 16 1988.049 3 371.240P 17 2085.102 2 272.172R 18 2241 194 1 175 119

Predicted Fragmentation Masses

650.33563.29

860.46 1609.89

175.12 973.551286.67

1955.011696.921399.75

372.24 1826.97

747.38 1086.64 1512.83

672.37988.50

200 400 600 800 1000 1200 1400 1600 1800 2000m/z

0

10

20

30

40

50

Re

lati

ve A 650.33b2

563.29b5/y8860.46

y151609.89

y1175.12

b6973.55 y12

1286.67y18 – iTRAQ

1955.01y161696.92

b13/y131399.75

372.24y17

1826.97b4747.38

b71086.64

y141512.83

y6672.37 y9

988.50

R 18 2241.194 1 175.119

S3

S5

S6 S8

S1

Gates_ITRAQ_8Plex_SCX-1#6263 RT: 62.61 AV: 1 NL: 6.05E5T: FTMS + p NSI d Full ms2 [email protected] [110.00-2000.00]

50

60

70

80

90

100

ve A

bu

nd

an

ce

117.11

115.11

113.11

Eight reporter ions quantify same peptide from eight samples in

one spectrum

70,000 Interpretable Spectra per iTRAQ Experiment(5% False Discovery Rate)

S2S4 S6

S7

S8

112 113 114 115 116 117 118 119 120 121 122m/z

0

10

20

30

40

50

Re

lati

v

118.11 121.12116.11

114.11119.11

112.09

Cells, tissue, fluidsAdds stepsNo MS technical variabilityQuantification at MS/MS level

9

Protein ExtractGels

Cells

Labeling Workflows

Tissue or Fluid

Gel matching

DIGE

SILAC

18O-Labeling ICAT TMTiTRAQ

Proteolysis

Radiolabeling

g

Peak Area

iTRAQFractionation

MS

MS2Peptide/Protein ID

ConfirmationMS3

Report Ion Intensity

AutoradiographyFluorescence

Changes in Protein Levels

(biomarkers and pathways)(biomarkers and pathways)

Phospholipid Growth Factor (S1P) on Pulmonary Endothelial Permeability

1

1.2

1.4

1.6

Re

sis

tan

ce

S1P

Resistance = Permeability

0

0.2

0.4

0.6

0.8

0 50 100 150 200 250 300

Time (min)

No

rma

lize

d R

Lipid Rafts?

Proteins involved?

Resistance = Permeability

Guo Y et al (2007) Mol Cell Proteomics 6:689

80

85

90

95

100

105

110

115459.31

291.23y1

y3

10

20

115.11

114.11

MRP_HumanGDVTAEEAAGASPAK (3+)

80

85

90

95

100

105

110

115459.31

291.23y1

y3

10

20

115.11

114.11

GDVTAEEAAGASPAK (3+)

iTRAQ Revealed Proteins More Abundant in S1P Stimulated Lipid Rafts

MRP Peptide Fragmentation

Co

ntr

ol

114 S

1P

115

A. Anti-MARCKS

Sample 1 Sample 2

Control S1P Control S1P

A. Anti-MARCKS

Sample 1 Sample 2

Control S1P Control S1P

Western Blots Confirm iTRAQ

100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100m/z, amu

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

Intensity, counts

362.27 423.72230.17

674.42 717.39546.36

259.10

416.24 588.33115.11 846.42200.11

317.17241.10102.06 494.76

273.69523.28 745.46330.15 570.32

b1202.13

b2

b3

517.27

b5

b6

b7

b8917.43 b9

988.47 b101045.49

y2

y4

y5617.37

y6

y7

y32+

y42+

b72+

b92+

b92+

b4

114.0 115.0 116.0 117.0m/z, amu

0

10

100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100m/z, amu

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

Intensity, counts

362.27 423.72230.17

674.42 717.39546.36

259.10

416.24 588.33115.11 846.42200.11

317.17241.10102.06 494.76

273.69523.28 745.46330.15 570.32

b1202.13

b2

b3

517.27

b5

b6

b7

b8917.43 b9

988.47 b101045.49

y2

y4

y5617.37

y6

y7

y32+

y42+

b72+

b92+

b92+

b4

114.0 115.0 116.0 117.0m/z, amu

0

10

MRP is up-regulated using both methods

C. Anti-MRP

D. Anti-Caveolin-1

B. Anti-p-MARCKS

C. Anti-MRP

D. Anti-Caveolin-1

B. Anti-p-MARCKS


10

MRP siRNA Attenuates S1P Stimulated Endothelial Barrier Enhancement

1

1.2

1.4

1.6

sis

tan

ce

S1PS1P+Scrambled MRP S1P+Scrambled MRP siRNAsiRNA

S1P+MRP S1P+MRP siRNAsiRNA

MRPMRP siRNAsiRNA

0

0.2

0.4

0.6

0.8

0 50 100 150 200 250 300

Time (min)

No

rma

lize

d R

es

MRP MRP siRNAsiRNAoror

Scrambled MAP Scrambled MAP siRNAsiRNA


Changes in Protein Modifications

(structure/function)(structure/function)

(acetylation, glycosylation, phosphorylation, nitrosation,

ubiquitination and novel cleavage sites)

Quantitative Phospho-Proteomics Workflow

Protein samples (1 mg per sample)

Peptides

iTRAQ Labeling

Phospho-Peptide enrich (Ti02)LCMS/MS Analysis

5% 95%

LCMS/MS Analysis

Protein ProfilingProtein present

Changes in Protein expression

Phospho-Peptide ProfilingPhosphorylations sites

Changes in Phosphorylation site

Distinguish site occupancy vs protein expression changes

iTRAQ PhosphoProteome Study (1% FDR)

5% BEFORE TiO2

enrichment

95% AFTER TiO2

enrichmentProtein groups identified 2691 2247Phosphoprotein groups identified 326 2134

Gut Epithelial Cell Cultures(+/-Kinase stimulated and Kinase knockout)

Unique Peptide Sequences 13876 5342Unique Peptide Sequences Containing Phosphorylation

445 4992

Peptides with pSer 338 4520Peptides with pThr 63 625Peptides with pTyr 6 28

Mark Donowitz

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Kinetics

(protein turnover modification dynamics)(protein turnover, modification dynamics)

Which peptide is a better substrate?

Experimental Design:

T i ( id )

-Wade Gibson

Can we adapt iTRAQ reagents for kinetics experiments?

-Bob Cole

Two timecourses (one per peptide)

Two iTRAQ experiments (one for each timecourse)

Substrate and products labeled with same iTRAQtag at each timepoint

Different iTRAQ label for different timepoints

Labeling Scheme for Each Time Course

Time (min) iTRAQ Label0 1135 114

15 11530 11645 11760 11890 119

120 121

Mix all iTRAQ labeled substrates and proteins from all timepoints from one timecourse.

Run one MS analysis (LCMS/MS) for each timecourse.

Peptide 1

0

100

200

300

400

500

600

700

800

900

1000

Substrate 1

60

80

100

120

140

Product 1a

Peptide 2

0

10

20

30

40

50

60

70

80

90

100

300

400

500

600

700

800

900

Substrate 2

Product 2a

113 114 115 116 117 118 119 121

0 5 15 30 45 60 90 120

0

20

40

0

50

100

150

200

250

Product 1b

0

100

200

300

0

1

2

3

4

5

6

7

8

113 114 115 116 117 118 119 121

0 5 15 30 45 60 90 120

Product 2b

iTRAQ LabelTime (min)

12

Protein ExtractGelsDIGE

Gel matching

Cells Tissue or FluidSILAC

Proteolysis TMTiTRAQ

Relative Quantitative Proteomics Workflows

18O-Labeling ICAT

Radiolabeling

Spectral Counting

g iTRAQFractionation

MS

MS2

Peak AreaPeptide/Protein ID

ConfirmationMS3

AutoradiographyFluorescence

Report Ion Intensity

Densitometry


Label-Free Labeling



Relative Absolute




SILAC



Absolute Quantification (AQUA)by spiking in a Peptide standard

Protein A to quantify in sample

Selects FragmentsQuantifies

Triple Quadrupole MS

Spike

Heavy Stable Isotope Standard Peptide from Protein A

Meng and VeenstraJ. Proteomics 2011

AQUA PeptidesChoose (software can help)One or more peptides from a previously identified protein Must: Be easily detected by MS

Yield good fragmentation spectraHave an unique sequenceContain no modifiable amino acids (no M,C,S,T,Y,K,R etc)

SynthesizePeptides with stable isotopes (e g 13C 15N etc ) amino acidsPeptides with stable isotopes (e.g., C, N, etc.) amino acids

Standard CurvesCreate standard curves (Intensity vs amount) of synthetic peptide

Spike Stable isotope labeled peptides is spiked into protein sample

Compare peak intesities or areasNative peptide intensities to synthetic peptides Calculate amount from synthetic peptide standard curves

13

Increases sensitivity and signal to noise ratio

Spray

HPLC

Peptide MassSelection

PeptideFragmentation

Fragment MassSelection

Fragment MassSpectrum

Inte

ns

ity

m/zQ3Q2Q1

609/969

969609

Selective Reaction Monitoring (SRM)

Multiple Reaction Monitoring (MRM)

Increases sensitivity and signal-to-noise ratioIncrease chance of detecting in protein extractsSpike stable isotope peptide to quantifyMass accuracy very helpful Many fragment ions

from many peptidesWide (e.g 20 amu) peptide mass selection window

SWATH

Quantification Concatamers (QconCAT)

Quantify known proteins in a complex sampleCombines AQUA and MRM strategiesControls for protein digestion Validates other quantification methodsAlternative to western blotting

Nat Meth 2:585, 2005Nat Protocols 1:1029, 2006Mol Cell Proteomics 6:1416, 2007

Protein Extract

Cells

Protein Standard Absolute Quantification Workflow

Tissue or Fluid

Protein Fractionation

RecombinantHeavy Stable Isotope Standard of Protein to Quantify

Protein Standard Absolute Quantification (PSAQ)

Peak Area

Proteolysis

Peptide Fractionation

MSPeptide/Protein ID

MS2

Protein Extract

Cells

Protein Standard Absolute Quantification Workflow

Tissue or Fluid

Protein FractionationQconCat Chimeras

PSAQ Proteins

Absolute Quantitative Proteomics Workflows

Peak Area

Proteolysis

Peptide Fractionation

MSPeptide/Protein ID

MS2

AQUA Peptides

14

PSAQ ProteinsSlope = 1.05

QconCat ChimerasSlope = 0.58

AQUA PeptidesSlope = 0.21

Accuracy of Absolute

Quantification Workflows

Meng and VeenstraJ. Proteomics 2011

PSAQ ProteinsSlope = 1.08

AQUA PeptidesSlope = 0.0.4

QconCat ChimerasSlope = 0.19


Label-Free Labeling



Relative Absolute




SILAC



lecture 10: quantitative proteomics...1 mass spectrometry in an “omics” world. me.330.804...

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