1

Applications of Mass Spectrometry to Proteomics

Akhilesh Pandey, M.D., Ph.D.

McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry

Why Proteomics?

2

One Gene, Many Proteins

Gene mRNA Protein

Gene

mRNA1mRNA2mRNA3mRNA4mRNA5

Alternativesplicing

Protein1Protein2Protein3Protein4Protein5Protein6....

Proteini

Co/post-translational processing

Biological changes(morphogenesis)

Profiling of proteins

Proteome ‘n’Proteome 1

Proteome 1 Proteome 2 Proteome ‘n’Proteome 3Proteome 4

Genomics and Proteomics

3

mRNA and Protein Correlation

Peptide Sequencing by MS/MS

Y7

Select one peptide

Fragments containingCarboxyl-terminus

Collision

Y6

Y5

Y4

Y3

4

MS/MS spectrum (sequencing)

Micromass QTOF Finnigan LCQ Deca LC/MSD Trap XCT

5

1D Liquid Chromatography Setup

Manual 3-port valve for peak ”parking valve”

Peptide Mixture from pump

diverter valve

Analytical column

C18

Split line

Emitter

8µm tip

80nL/min with valve open

A matchstick Needle with a very small opening and containing a reverse phase Column for separation

6

Multidimensional Liquid Chromatography (MudPIT) Setup

Liu, H. et al. (2002)

MS

Offline Fractionation in the First Dimension

Pump

Auto Sampler

Manual Injector

UV Detector

Reverse phase LCMS

Fraction Collector

SCX Column

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Automated nanoLC-MS/MS

• Purification of sample• Very complex samples

can be analyzed• Identical peptides will

elute in one peak (enhanced signal)

• Automated• Many proteins can be

identified in one run (100-2,000 proteins)

Quantitative Proteomics

• Based on difference in intensity

• By relative quantitation using MS

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Quantitative Proteomics

• Based on difference in intensity– 1D gels– 2D gels– Use of fluorescence-based methods

1D Gel-based Comparison

200

110

73

47

28

IP : anti-pTyr

EGF :

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2D Gel-based Comparison

Normal Cancer

2D Gels - Limitations

• Sample preparation - lot of optimization required

• Loading capacity limited• Do not resolve very small (<10 kD) or

large (>100 kD) proteins• Do not resolve hydrophobic (e.g.

membrane) proteins• Issues with reproducibility

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Quantitative Proteomics

• Fluorescence-based quantitation– DIGE (Difference in-gel electrophoresis)

DIGE

• Samples to be labeled are labeled with Cy3 (green) and Cy5 (red)

• Samples are ‘mixed’ and resolved by 2D gels

• Fluorescence measured and quantitated

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2D-DIGE of Pancreatic Juice

Cancer

Normal

Cy5

Cy3

Cy3-Cy5

Quantitative Proteomics

• By relative quantitation using MS– in vitro labeling

• 18O-labeling• Peptide mass tagging (ICAT)

– in vivo labeling• Labeling with stable isotope containing amino

acids (SILAC)

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18O-labelingnormal cancer

Excise gel band Excise gel band

In-gel digestion with H2

16O waterIn-gel digestion with H2

18O water

Mix 1:1

MS-analysis

N C

18O-labeling

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Isotope-Coded Affinity Tag (ICAT)

1 2 3

4Structure of ICAT reagent

Stable Isotope Labeling in Cell Culture (SILAC) for Protein Quantitation

• Mammalian cell culture models are used for studying a number of biological processes

• In the SILAC approach, cells are grown continuously in media containing one or more stable isotopes (e.g. 13C). All the proteins in the cells are heavier and can be used to ‘mark’ a given state in mass spectrometric analysis

14

Time Course of Heavy Amino Acid Incorporation

Advantages of the SILAC Method

• Simple• In vivo• Does not require any extra processing steps• All proteins are uniformly labeled• Complete and predictable incorporation• Choice of labeled amino acids• De novo sequencing can be performed

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General strategy for stable isotope labeling by amino acids

12C6 Labeled Lysine

Mix and run on SDS-PAGE

Elute, Digest with Trypsin and Analyze by MS

SILAC for Quantitation of Secreted Proteins

m/z

Rel

ativ

e In

tens

ity

13C6 Labeled Lysine

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Day 1

Day 4

Day 1

Day 9

Day 1

Day 7

MixDays 1+4

MixDays 1+9

MixDays 1+7

Profile of Proteins Secreted by Adipocytes

m/z770 772 774 776 778

0

100772.40

772.90

775.42

773.41

773.91

775.90

776.41

50

Ratio 1:0.5Ratio 1:0.4

m/z770 772 774 776 778

0

100772.39

772.88

775.39773.39

773.88

775.89

776.40

50

Ratio 1:0.24

m/z770 772 774 776 778

0

100 772.40

772.91

773.40775.40

775.91776.41

50

m/z800 802 804 806 808

0

100 805.44

802.43802.94

803.43

805.94

806.45

50

Ratio 1:2.4

m/z800 802 804 806 808

0

100 805.42

802.40802.92

803.40

805.91

806.42

50

Ratio 1:2.7

m/z800 802 804 806 8080

100 805.44

802.43

802.92803.43

805.95

806.4650

Ratio 1:1.6

Fibronectin expression is downregulated

Collagen alpha 3 expression is upregulated

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Studying Dynamics Using SILAC

786.2

786.7

787.3

788.2

789.2

789.7790.2790.7

791.2

791.7

792.2

792.7

793.1

0.00

0.25

0.50

0.75

1.00

1.25

1.50

5x10

786 788 790 792 794 796 798 m/z

VSHLLGINVTDFTR6Da 4Da

Inte

nsity

Biomarker Discovery Using Proteomics

• Ideal targets for biomarker– Protein (differential expressed proteins)– DNA (mutations, methylation)– RNA (differential expressed genes)

• Biological specimen– Tissue (whole tissue or isolated tumor cells)– Pancreatic juice– Serum– Plasma

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Pancreatic juice

Physiological proteome of human pancreatic juice

• Collection of pancreatic juice (cancer) during surgery

• Run on 1D gel• LC-MS/MS analysis• Bioinformatic analysis of

identified proteins• Compare data with

known microarray data

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Differential Proteomic Analysis of Pancreatic Cancer Secretome

• In-vivo labeling with both arginine and lysine

• Collect conditioned media and concentrate with centricon 3,000 Da MWCO

• Normalize and mix in 1:1 ratio• Resolve proteins by 1D gel

electrophoresis• Excise bands and digest proteins

by trypsin• Identify proteins by nanoLC-MS/MS

(2x30 bands)• Verify identified proteins (manually)• Relative quantitation of ID proteins

(manually)

Quantitation of Secreted Proteins

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Post-translational Modifications

• Peptides can have a number of modifications• During database searching, a variable

modification has to be specified – otherwise, no ‘hit’

• Common PTMs are phosphorylation, acetylation, ubiquitination, glycosylation etc.

Protein Phosphorylation

• One-third of all cellular proteins are phosphorylated at one time or another

• Phosphoamino acid content of a vertebrate cell:Serine - 90%; Threonine - 10%; Tyrosine - 0.05%

• Ser:Thr:Tyr - 1800:200:1• Tyrosine phosphorylation is tightly regulated

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Why is Phosphorylation Analysis Difficult?

• Stoichiometry of phosphorylation is low• Complete coverage of proteins is difficult to obtain • Phosphorylated serine and threonine residues are labile

whereas phosphotyrosines are more stable • Phosphoserines and phosphothreonine residues can be

subjected to a beta-elimination reaction but not phosphotyrosine residues

• Antibodies to enrich for serine and threonine phosphorylated proteins are not available

• Phosphopeptides are ‘suppressed’ in a mass spectrum

Phosphotyrosine Immonium Ion (216.043 Da)

NH CH

CH2

O

PHO OHO

C

OHN CH2

CH2

O

PHO OHO

Immonium Ion of Phosphotyrosine as a Reporter Ion

+

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Phosphotyrosine-Specific Precursor Ion Scanning – Bcr/Abl

97

200

68

43

28 ******

500 700 900

590 600 610 608 616 624

Phosphotyrosine-Specific Precursor Ion Scan

MS Scan

Con

trol

p185

Bcr

/Abl

IP: anti-pTyr

538 540 542 544

Large scale IP with an anti-pSer/Thr antibody

WB: Anti-pSer/Thr

Lysates

Calyculin A:

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In Vivo Labeling with 32P

IP: Anti-pSer/Thr

Calyculin A: - +

10RLpSPAPQLGP19

Identification of Phosphorylated Ser/Thr residues

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200

110

73

47

28

IP : anti-pTyr

EGF :

MS-Based Identification of a 130 kDa Protein in the EGF Receptor Signaling Pathway

Silver stained gel

>KIAA0229 (1180 residues) FRAGMENT

SWGKGREGVVSPAGLGGALPGDGKFGSPSRLGCSLGEGVQRVAALGMGKEQELLRAARTGHLPAVEKLLSGKRLSSGFGGGGGGGSGGGGGGSGGGGGGLGSSSHPLSSLLSMWRGPNVNCVDSTGYTPLHHAALNGHHRRSSSSRSQDSAEGQDGQVPEQFSGLLHGSSPVCEVGQDPFQLLCTAGQSHPDGSPQQGACHKASMQLEETGVHAPGASQPSALDQSKRVGYLTGLPTTNSRSHPETLTHTASPHPGGAEEGDRSGAR

Assignment of the initiator methionine in a cDNA ‘fragment’ based on an N-terminal peptide

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>KIAA0229 (1180 residues) FRAGMENT

SWGKGREGVVSPAGLGGALPGDGKFGSPSRLGCSLGEGVQRVAALGMGKEQLLRAARTGHLPAVEKLLSGKRLSSGFGGGGGGGSGGGGGGSGGGGGGLGSSSHPLSSLLSMWRGPNVNCVDSTGYTPLHHAALNGHHRRSSSSRSQDSAEGQDGQVPEQFSGLLHGSSPVCEVGQDPFQLLCTAGQSHPDGSPQQGACHKASMQLEETGVHAPGASQPSALDQSKRVGYLTGLPTTNSRSHPETLTHTASPHPGGAEEGDRSGAR

Assignment of the initiator methionine in a cDNA ‘fragment’ based on an N-terminal peptide

RCH3 C

O

H2N Q L LG K E

Acetylated lysineTri-methylated lysine

128.095

Mono-methylated lysine

142.111

Di-methylated lysine

156.127 170.143 170.105Mass (Da)

Massgain

- 14.016 Da 28.032 Da 42.048 Da 42.010 Da

NH 2

CO CH 3

Lysine

NH 2 CH CO

CH 2

CH 2

CH 2

CH 2

NH 2

OHNH 2 CH C

OCH 2

CH 2

CH 2

CH 3

OHNH 2 CH C

OCH 2

CH 2

CH 2

CH 3

OHNH 2 CH C

OCH 2

CH 2

CH 2

CH 2

NH

OH

CH 3

NCH 3 CH 3

NH 2 CH CO

CH 2

CH 2

CH 2

CH 3

OH

N+

CH 3CH 3

CH 3

Lysine Modifications

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Di-glycyl lysine

NH 2 CH CO

CH 2

CH 2

CH 2

CH 2

NH

OH

Gly

Gly

Isopeptide bond

Lysine residue

Lysine Modifications

Massgain

114.05 Da

100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400m/z

0

100

50

175.12

232.14

1016.51

717.35

589.30347.17 476.21

959.49

1234.621087.55

1347.72

Tryptic Digest of Ubiquitylated Peptide

LIFAGKQLEDGRGG

242.14 Da

GG

K

27

100 110 120 130 140 150 158

m/z

0

1000

100 120.07

112.08 116.06

158.09

141.10129.10

121.08

129.10

120.07

112.08

158.09

Di-glycine Containing Peptide

Non Di-glycine Containing Peptide

Signature of a Ubiquitylated Peptide

Immonium ion