Proteomics Technology and Protein Identification Nathan Edwards Center for Bioinformatics and Computational Biology

Proteomics Technology

and Protein Identification

Proteomics Technology

and Protein Identification

Nathan EdwardsCenter for Bioinformatics and Computational Biology

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Outline

• Proteomics• Mass Spectrometry• Protein Quantitation

• Protein Identification

• Computer Lab

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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?• What isoform of each protein is present?• How much of each protein is present?

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Systems Biology

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

Gene / Transcript / Protein

Measurement Predetermined Unknown

Discrete (DNA) Genotyping Sequencing

Continuous Gene Expression Proteomics

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Samples

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

• Mitochondria, Membrane

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Protein Chemistry Assay Techniques• Gel Electrophoresis

• Isoelectric point• Molecular weight

• Liquid Chromatography• Hydrophobicity

• Digestion Enzymes• Cut protein at motif

• Fluorescence• Staining

• Affinity capture• Phosphorylation

• Protein Binding • Receptors• Complexes

• Flow Cytometry• Mass Spectrometry

• Accurate molecular weight

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2D Gel-Electrophoresis

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

• Staining

• Birds-eye view of protein abundance

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2D Gel-Electrophoresis

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

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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

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Mass Spectrometer

Ionizer

Sample

+_

Mass Analyzer Detector

• MALDI• Electro-Spray

Ionization (ESI)

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

• ElectronMultiplier(EM)

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Mass Spectrometer(MALDI-TOF)

Detector (linear mode)

Reflectron

N2 Laser

LensDetector (reflectron mode)

Target plate with sample

(b) M@LDITM LR by Micromass, UK

Energy transfer from matrix to sample

Matrix Sample

Laser

Ionization

Schematic of the MALDI process(a)

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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

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Mass Spectrum

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Mass is fundamental

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Mass Spectrum

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Mass Spectrum

Isotope Cluster• 12C ≈ 99%• 13C ≈ 1%

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Peptide Mass Fingerprint

Cut out2D-Gel

Spot

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Trypsin Digest

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• 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

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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

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Proteomics Quantitation

• 2D-Gel Electrophoresis

• Replicate LC/MS acquisitions

• Stable Isotope Labeling

• Protein profiling

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LC/MS for Peptide Abundance

Enzymatic Digestand

Fractionation

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LC/MS: 1 MS spectrum every 1-2 seconds

MassSpectrometry

Liquid Chromatography

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Stable Isotope Labeling

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Stable Isotope Labeling

• SILAC: Lysine with 12C6 vs 13C6

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MALDI Protein Profiling

• Hundreds of healthy and diseased samples• Single MS spectrum per sample• Statistical datamining to find “biomarkers”

• Commercialization for ovarian cancer under name “Ovacheck”

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MALDI Protein ProfilingMale Spectra

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MALDI Protein ProfilingFemale Spectra

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Protein Profiling Statgram

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Peptide Identification by MS/MS

• Most mature proteomics workflow• Sample preparation• Instruments• Software

• Compatible with quantitation by• Replicate LC/MS acquisitions• Stable isotope labeling• 2D-Gels (but essentially unnecessary)

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Sample Preparation for MS/MS

Enzymatic Digestand

Fractionation

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Single Stage MS

MS

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Tandem Mass Spectrometry(MS/MS)

Precursor selection

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Tandem Mass Spectrometry(MS/MS)

Precursor selection + collision induced dissociation

(CID)

MS/MS

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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.

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41

i+1


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

RiCH-R’

bi

yn-iyn-i-1

bi+1

R”

i+1

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i+1


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

RiCH-R’

bi

yn-iyn-i-1

bi+1

R”

i+1

ai

xn-i

ci

zn-i

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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

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100

0250 500 750 1000

m/z

% I

nte

nsit

y

K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

147260389504633762875102210801166 y ions

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K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

100

0250 500 750 1000

m/z

% I

nte

nsit

y

147260389504633762875102210801166 y ions

y6

y7

y2 y3 y4

y5

y8 y9

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K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

100

0250 500 750 1000

m/z

% I

nte

nsit

y

147260389504633762875102210801166 y ions

y6

y7

y2 y3 y4

y5

y8 y9

b3

b5 b6 b7b8 b9

b4

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Peptide Identification

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

Output:• The amino-acid sequence of the peptide

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Peptide Identification

Two paradigms:

• De novo interpretation

• Sequence database search

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De Novo Interpretation

100

0250 500 750 1000

m/z

% I

nte

nsit

y

50


100

0250 500 750 1000

m/z

% I

nte

nsit

y

E L

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100

0250 500 750 1000

m/z

% I

nte

nsit

y

E L F

KL

SGF G

E DE

L E

E D E L

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Amino-Acid Residual MW Amino-Acid Residual MW

A 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

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…from Lu and Chen (2003), JCB 10:1

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…from Lu and Chen (2003), JCB 10:1

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• Find good paths in spectrum graph• Can’t use same peak twice

• Forbidden pairs: NP-hard• “Nested” forbidden pairs: Dynamic Prog.

• Simple peptide fragmentation model• Usually many apparently good solutions• Needs better fragmentation model• Needs better path scoring

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• Amino-acids have duplicate masses!• Incomplete ladders create ambiguity.• Noise peaks and unmodeled fragments

create ambiguity• “Best” de novo interpretation may have no

biological relevance• Current algorithms cannot model many

aspects of peptide fragmentation• Identifies relatively few peptides in high-

throughput workflows

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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

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100

0250 500 750 1000

m/z

% I

nte

nsit

y

KLEDEELFGS

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100

0250 500 750 1000

m/z

% I

nte

nsit

y

K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

147260389504633762875102210801166 y ions

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K1166

L1020

E907

D778

E663

E534

L405

F292

G145

S88 b ions

100

0250 500 750 1000

m/z

% I

nte

nsit

y

147260389504633762875102210801166 y ions

y6

y7

y2 y3 y4

y5

y8 y9

b3

b5 b6 b7b8 b9

b4

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Sequence Database Search

• No need for complete ladders• Possible to model all known peptide

fragments• Sequence permutations eliminated• All candidates have some biological

relevance• Practical for high-throughput peptide

identification• Correct peptide might be missing from

database!

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Peptide Candidate Filtering

Digestion Enzyme: Trypsin• Cuts just after K or R unless followed by a

P.• Basic residues (K & R) at C-terminal

attract ionizing charge, leading to strong y-ions

• “Average” peptide length about 10-15 amino-acids

• Must allow for “missed” cleavage sites

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Peptide Candidate Filtering>ALBU_HUMAN MKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

No missed cleavage sitesMKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

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Peptide Candidate Filtering>ALBU_HUMAN MKWVTFISLLFLFSSAYSRGVFRRDAHKSEVAHRFKDLGEENFKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

One missed cleavage site

MKWVTFISLLFLFSSAYSRWVTFISLLFLFSSAYSRGVFRGVFRRRDAHKDAHKSEVAHRSEVAHRFKFKDLGEENFKDLGEENFKALVLIAFAQYLQQCPFEDHVKALVLIAFAQYLQQCPFEDHVKLVNEVTEFAK…

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Peptide Candidate Filtering

Peptide molecular weight• Only have m/z value

• Need to determine charge state• Ion selection tolerance• Mass for each amino-acid symbol?

• Monoisotopic vs. Average• “Default” residual mass• Depends on sample preparation protocol• Cysteine almost always modified

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Peptide Molecular Weight

Same peptide,i = # of C13 isotope

i=0

i=1

i=2

i=3i=4

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Same peptide,i = # of C13 isotope

i=0

i=1

i=2

i=3i=4

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…from “Isotopes” – An IonSource.Com Tutorial

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• Peptide sequence WVTFISLLFLFSSAYSR• Potential phosphorylation?

• S,T,Y + 80 DaWVTFISLLFLFSSAYSR 2018.06

WVTFISLLFLFSSAYSR 2098.06








… …


- 7 Molecular Weights- 64 “Peptides”

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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

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Mascot Search Engine

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Mascot MS/MS Ions Search

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Sequence Database SearchTraps and Pitfalls

Search options may eliminate the correct peptide

• Parent mass tolerance too small• Fragment m/z tolerance too small• Incorrect parent ion charge state• Non-tryptic or semi-tryptic peptide• Incorrect or unexpected modification• Sequence database too conservative• Unreliable taxonomy annotation

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Search options can cause infinite search times

• Variable modifications increase search times exponentially

• Non-tryptic search increases search time by two orders of magnitude

• Large sequence databases contain many irrelevant peptide candidates

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Best available peptide isn’t necessarily correct!

• Score statistics (e-values) are essential!• What is the chance a peptide could score this

well by chance alone?• The wrong peptide can look correct if the

right peptide is missing!• Need scores (or e-values) that are invariant

to spectrum quality and peptide properties

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Search engines often make incorrect assumptions about sample prep

• Proteins with lots of identified peptides are not more likely to be present

• Peptide identifications do not represent independent observations

• All proteins are not equally interesting to report

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Good spectral processing can make a big difference

• Poorly calibrated spectra require large m/z tolerances

• Poorly baselined spectra make small peaks hard to believe

• Poorly de-isotoped spectra have extra peaks and misleading charge state assignments

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Summary

• Protein identification from tandem mass spectra is a key proteomics technology.

• Protein identifications should be treated with healthy skepticism.• Look at all the evidence!

• Spectra remain unidentified for a variety of reasons.

• Lots of open algorithmic problems!

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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

http://www.matrixscience.com/

http://www.proteomecenter.org/

http://fields.scripps.edu/

http://prospector.ucsf.edu/

Documents

Proteomics Technology and Protein Identification Nathan Edwards Center for Bioinformatics and Computational Biology