proteomics mass spectrometry

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Outline Proteomics Mass Spectrometry Protein Identification Peptide Mass Fingerprint Tandem Mass Spectrometry

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Proteomics & Mass Spectrometry

Nathan EdwardsCenter for Bioinformatics and Computational Biology

2

Outline

• Proteomics

• Mass Spectrometry

• Protein Identification• Peptide Mass Fingerprint• Tandem Mass Spectrometry

3

Proteomics

• Proteins are the machines that drive much of biology• Genes are merely the recipe

• The direct characterization of a sample’s proteins en masse. • What proteins are present?• How much of each protein is present?

4

Systems Biology

• Establish relationships by• Choosing related samples,• Global characterization, and• Comparison.

Gene / Transcript / ProteinMeasurement Predetermined UnknownDiscrete (DNA) Genotyping Sequencing

Continuous Gene Expression Proteomics

5

Samples

• Healthy / Diseased• Cancerous / Benign• Drug resistant / Drug susceptible• Bound / Unbound• Tissue specific• Cellular location specific

• Mitochondria, Membrane

6

2D Gel-Electrophoresis

• Protein separation• Molecular weight (MW)• Isoelectric point (pI)

• Staining

• Birds-eye view of protein abundance

7

2D Gel-Electrophoresis

Bécamel et al., Biol. Proced. Online 2002;4:94-104.

8

Paradigm Shift

• Traditional protein chemistry assay methods struggle to establish identity.

• Identity requires:• Specificity of measurement (Precision)

• Mass spectrometry• A reference for comparison

(Measurement → Identity)• Protein sequence databases

9

Mass Spectrometer

Ionizer

Sample

+_

Mass Analyzer Detector• MALDI• Electro-Spray

Ionization (ESI)

• Time-Of-Flight (TOF)• Quadrapole• Ion-Trap

• ElectronMultiplier(EM)

10

Mass Spectrometer (MALDI-TOF)

Source

Length = s

Field-free drift zone

Length = D

Ed = 0

Microchannel plate detector

Backing plate(grounded) Extraction grid

(source voltage -Vs)

UV (337 nm)

Detector grid -Vs

Pulse voltage

Analyte/matrix

11

Mass Spectrum

12

Mass is fundamental

13

Peptide Mass Fingerprint

Cut out2D-GelSpot

14

Peptide Mass Fingerprint

Trypsin Digest

15

Peptide Mass Fingerprint

MS

16

Peptide Mass Fingerprint

17

Peptide Mass Fingerprint

• Trypsin: digestion enzyme• Highly specific• Cuts after K & R except if followed by P

• Protein sequence from sequence database• In silico digest• Mass computation

• For each protein sequence in turn:• Compare computer generated masses with

observed spectrum

18

Protein Sequence

• Myoglobin - Plains zebra

GLSDGEWQQV LNVWGKVEAD IAGHGQEVLI RLFTGHPETL EKFDKFKHLK TEAEMKASED LKKHGTVVLT ALGGILKKKG HHEAELKPLA QSHATKHKIP IKYLEFISDA IIHVLHSKHP GDFGADAQGA MTKALELFRN DIAAKYKELG FQG

19

Protein Sequence

• Myoglobin - Plains zebra

GLSDGEWQQV LNVWGKVEAD IAGHGQEVLI RLFTGHPETL EKFDKFKHLK TEAEMKASED LKKHGTVVLT ALGGILKKKG HHEAELKPLA QSHATKHKIP IKYLEFISDA IIHVLHSKHP GDFGADAQGA MTKALELFRN DIAAKYKELG FQG

20

Peptide Masses

1811.90 GLSDGEWQQVLNVWGK 1606.85 VEADIAGHGQEVLIR 1271.66 LFTGHPETLEK 1378.83 HGTVVLTALGGILK 1982.05 KGHHEAELKPLAQSHATK 1853.95 GHHEAELKPLAQSHATK 1884.01 YLEFISDAIIHVLHSK 1502.66 HPGDFGADAQGAMTK 748.43 ALELFR

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Peptide Mass Fingerprint

GLS

DG

EWQ

QVL

NVW

GK

VEA

DIA

GH

GQ

EVLI

R

LFTG

HPE

TLEK

HG

TVVL

TALG

GIL

K

KG

HH

EAEL

KPL

AQ

SHA

TK

GH

HEA

ELK

PLA

QSH

ATK

YLEF

ISD

AIIH

VLH

SK

HPG

DFG

AD

AQ

GA

MTK

ALE

LFR

22

Mass Spectrometry

• Strengths• Precise molecular weight• Fragmentation• Automated

• Weaknesses• Best for a few molecules at a time• Best for small molecules• Mass-to-charge ratio, not mass• Intensity ≠ Abundance

23

Sample Preparation for MS/MS

Enzymatic Digestand

Fractionation

24

Single Stage MS

MS

25

Tandem Mass Spectrometry(MS/MS)

Precursor selection

26

Tandem Mass Spectrometry(MS/MS)

Precursor selection + collision induced dissociation

(CID)

MS/MS

27

Peptide Fragmentation

H…-HN-CH-CO-NH-CH-CO-NH-CH-CO-…OH

Ri-1 Ri Ri+1

AA residuei-1 AA residuei AA residuei+1

N-terminus

C-terminus

Peptides consist of amino-acids arranged in a linear backbone.

28

Peptide Fragmentation

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i+1

Peptide Fragmentation

-HN-CH-CO-NH-CH-CO-NH-

Ri CH-R’

bi

yn-iyn-i-1

bi+1

R”i+1

30

Peptide Fragmentation

Peptide: S-G-F-L-E-E-D-E-L-KMW ion ion MW

88 b1 S GFLEEDELK y9 1080

145 b2 SG FLEEDELK y8 1022

292 b3 SGF LEEDELK y7 875

405 b4 SGFL EEDELK y6 762

534 b5 SGFLE EDELK y5 633

663 b6 SGFLEE DELK y4 504

778 b7 SGFLEED ELK y3 389

907 b8 SGFLEEDE LK y2 260

1020 b9 SGFLEEDEL K y1 147

31

Peptide Fragmentation

100

0250 500 750 1000 m/z

% In

tens

ity

K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

147260389504633762875102210801166 y ions

32

Peptide Fragmentation

K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

100

0250 500 750 1000 m/z

% In

tens

ity

147260389504633762875102210801166 y ionsy6

y7

y2 y3 y4

y5

y8 y9

b3

b5 b6 b7b8 b9

b4

33

Peptide Identification

Given:• The mass of the precursor ion, and• The MS/MS spectrum

Output:• The amino-acid sequence of the peptide

34

Peptide Identification

Two paradigms:

• De novo interpretation

• Sequence database search

35

De Novo Interpretation

100

0250 500 750 1000 m/z

% In

tens

ity

36

De Novo Interpretation

100

0250 500 750 1000 m/z

% In

tens

ity

E L

37

De Novo Interpretation

100

0250 500 750 1000 m/z

% In

tens

ity

E L F

KL

SGF G

E DE

L E

E D E L

38

De Novo Interpretation

Amino-Acid Residual MW Amino-Acid Residual MWA Alanine 71.03712 M Methionine 131.04049 C Cysteine 103.00919 N Asparagine 114.04293 D Aspartic acid 115.02695 P Proline 97.05277 E Glutamic acid 129.04260 Q Glutamine 128.05858 F Phenylalanine 147.06842 R Arginine 156.10112 G Glycine 57.02147 S Serine 87.03203

H Histidine 137.05891 T Threonine 101.04768 I Isoleucine 113.08407 V Valine 99.06842 K Lysine 128.09497 W Tryptophan 186.07932 L Leucine 113.08407 Y Tyrosine 163.06333

39

De Novo Interpretation

…from Lu and Chen (2003), JCB 10:1

40

De Novo Interpretation

41

De Novo Interpretation

…from Lu and Chen (2003), JCB 10:1

42

De Novo Interpretation

• Find good paths in spectrum graph• Can’t use same peak twice• Simple peptide fragmentation model• Usually many apparently good solutions• Amino-acids have duplicate masses!• “Best” de novo interpretation may have no

biological relevance• Identifies relatively few peptides in high-

throughput workflows

43

Sequence Database Search• Compares peptides from a protein

sequence database with spectra• Filter peptide candidates by

• Precursor mass• Digest motif

• Score each peptide against spectrum• Generate all possible peptide fragments• Match putative fragments with peaks• Score and rank

44

Peptide Fragmentation

100

0250 500 750 1000 m/z

% In

tens

ity

KLEDEELFGS

45

Peptide Fragmentation

100

0250 500 750 1000 m/z

% In

tens

ity

K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

147260389504633762875102210801166 y ions

46

Peptide Fragmentation

K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

100

0250 500 750 1000 m/z

% In

tens

ity

147260389504633762875102210801166 y ionsy6

y7

y2 y3 y4

y5

y8 y9

b3

b5 b6 b7b8 b9

b4

47

Sequence Database Search

• Sequence fills in gaps in the spectrum• All candidates have biological relevance• Practical for high-throughput peptide

identification• Correct peptide might be missing from

database!

48

Peptide Candidate FilteringDigestion Enzyme: Trypsin• Cuts just after K or R unless followed

by a P.• Must allow for “missed” cleavage sites• “Average” peptide length about 10-15

amino-acids

49

Peptide Candidate Filtering>ALBU_HUMAN MKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

No missed cleavage sitesMKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

50

Peptide Candidate Filtering>ALBU_HUMAN MKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

One missed cleavage siteMKWVTFISLLFLFSSAYSRWVTFISLLFLFSSAYSRGVFRGVFRRRDAHKDAHKSEVAHRSEVAHRFKFKDLGEENFKDLGEENFKALVLIAFAQYLQQCPFEDHVKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

51

Peptide Scoring

• Peptide fragments vary based on• The instrument• The peptide’s amino-acid sequence• The peptide’s charge state• Etc…

• Search engines model peptide fragmentation to various degrees. • Speed vs. sensitivity tradeoff• y-ions & b-ions occur most frequently

52

Mascot Search Engine

53

Mascot MS/MS Ions Search

54

Mascot MS/MS Search Results

55

Mascot MS/MS Search Results

56

Mascot MS/MS Search Results

57

Mascot MS/MS Search Results

58

Mascot MS/MS Search Results

59

Mascot MS/MS Search Results

60

Mascot MS/MS Search Results

61

Mascot MS/MS Search Results

62

Mascot MS/MS Search Results

63

Mascot MS/MS Search Results

64

Summary

• Protein identification by mass spectrometry is a key element of proteomics and systems biology.

• Mass spectrometry + sequence databases represent a huge leap for protein (bio-)chemistry.

• Sample prep, instruments and algorithms still maturing, much work to be done.

65

Further Reading

• Matrix Science (Mascot) Web Site• www.matrixscience.com

• Seattle Proteome Center (ISB)• www.proteomecenter.org

• Proteomic Mass Spectrometry Lab at The Scripps Research Institute • fields.scripps.edu

• UCSF ProteinProspector• prospector.ucsf.edu

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