Mass Spectrometry-based Proteomics
Application in Human Health and Bioenergy
Wei-Jun Qian
Integrative OmicsBiological Sciences Division
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Outline
Introduction
Proteomics: How it works
Proteomic quantificationGlobal shotgunTargeted
Applications
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3 3
Measurement technologies
DNA
Genome
Info (codes) Readout Execution
RNA
Transcriptome
Proteins
Proteome
The central dogma of biology
Proteins are the workhorses of cells
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Proteomics seeks to gain a systems-level understanding of cellular functions by measuring the dynamics of proteins.
Systems biology
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Life’s complexity pyramid, Oltvai & Barabasi, Science, 2002
Question: Will genome inform you everything?
Systems Biology
Many proteins are functionally linked through allosteric or other mechanisms into biochemical 'circuits' that perform a variety of simple computational tasks including amplification, integration and information storage. (D Bray, Nature, 1995)
While long-term information is stored in the genome, the proteome is crucial for short-term information storage or learned behaviors
The cell’s large scale functional organization provides a multi-level network view of motifs, pathways, and modules, ect.
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From systems biology to synthetic biology
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Design
BuildTest
Outline
Introduction
Proteomics: How it works
Proteomic quantificationGlobal shotgunTargeted
Applications
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Proteomics(PROTEOme DynaMICS)
Proteome: the entire complement of proteinsexpressed in a cell, tissue or organism.
Proteomics deals with the dynamics of the proteome. In a simple term, proteomics primarily focuses on:
Identify Quantify
as many proteins as possible in biological samples
Proteomics is a high-throughput technology for the systems level study of proteins.
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Unique Aspects of Proteomics
Not just another version of gene expression
Quantitative proteomics can provide multi-dimensional dynamics information.
Protein expression/abundancePosttranslational modifications (phosphorylation, glycosylation, etc.)Protein isoforms (splicing variants, protein fragments)Protein-protein interactionssubcellular localization & translocation
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Protein Post-Translational Modifications (PTMs)
DNA encodes functions
mRNA transfersfunctions
Proteins fulfillfunctions
PTMs regulatefunctions
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Impact of proteomicsHuman disease
Improving diagnosticsNovel Biomarkers for diseases
Drug discoveryNew levels of understanding of biology and disease mechanisms
Bioenergy.Systems level understanding of Biomass fermentation by microbesNew engineering targets for enhanced biofuel production
Indispensable tool in systems biology
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How does proteomics work?
Protein Peptide
Enzymedigestion
Liquid chromatography-mass spectrometry
or LC-MS
How does proteomics work?
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200 600 1,000 1,400 1,800
y9
y8
b10
y7
b9b8
y6
y12
y10y11
b12b6
y5b7
b11
y13b14b13y4
200 600 1,000 1,400 1,800m/z
y9
y8
b10
y7
b9b8
y6
y12
y10y11
b12b6
y5b7
b11
y13b14b13y4
Trypsin enzyme digestion
Proteins
Peptide mixture
Peptide identifications(including possible PTMs)
LC-MS and MS/MS
LC elution time 300 1000 1700
Full MS Spectrum
m/z
l
i
MS/MS fragment Spectrum LC
Quantification
Break selected peptide
Cells, tissue, biofluids
PNNL Proteomics
Integrative Functional Proteomics
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Protein abundances
Protein activities
Multiple types of PTMs
Broad quantification
Targeted quantification
PTM crosstalk and pathways/networks
Outline
Introduction
Proteomics: How it works
Proteomic quantificationGlobal shotgunTargeted
Applications
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Relative Quantification by Spectral Counting
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Stochastic sampling
200 600 1,000 1,400 1,800
y9
y8
b10
y7
b9b8
y6
y12
y10y11
b12b6
y5b7
b11
y13b14b13y4
200 600 1,000 1,400 1,800m/z
y9
y8
b10
y7
b9b8
y6
y12
y10y11
b12b6
y5b7
b11
y13b14b13y4
MS/MS Spectrum for peptide XXXXX
Counting the number of MS/MS spectra
0
20
40
60
80
100
A B C A B C A B C
Samples
Ave
rage
spe
ctru
m c
ount 25
1
5
Qian et al., Proteomics, 2005, 5:572.
Accurate Quantification: Stable Isotope Dilution Concept
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Light (12C, 16O, 14N) and heavy isotope (13C, 18O, 15N) labeled peptide pairs have exactly identical chemical properties
Pass together through LC, ESI, In all ion transmission spaces
Sample A
Sample BHeavy
Light
Inte
nsity
m/z
HL
L/H ratio
Heavy isotope (13C, 18O, 15N) labeled peptides serve as internal standards
Quantitative Proteomics Using 16O/18O LabelingCH CR
O18OH
HO E.18OH2
H2O
CH CR
OHO18
HO E+
CH CR
O18HO18 HO E
+
CH CR
O18OH
HO E.18OH2
H2O
CH CR
OHO18
HO E+
CH CR
O18HO18 HO E
+
795.83 799.66 803.48m/z
945.01 948.65 952.29m/z
4 Da4 Da
Dry
Peptides
Resuspendin H2
18O 1:50 Trypsin:Peptide (w/w)
Boil for 10 minutes
STOP
18O-Labeling37 oC, 450 rpm
5hr
Efficient for all tryptic peptides from all samples
1,229.0
1,230.0
1,231.0
1,232.0
1,233.0
1,234.0
1,235.0
1,236.0
1,237.0
1,458 1,463 1,468 1,473 1,478 1,483
Monoisotopic mass
4.0085 Da
Scan number
0 . 0 E + 0 0
5 . 0 E + 0 6
1 . 0 E + 0 7
1 . 5 E + 0 7
1 4 6 4 1 4 6 6 1 4 6 8 1 4 7 0 1 4 7 2 1 4 7 4 1 4 7 6 1 4 7 8 1 4 8 0 1 4 8 2
Pair #372; Charge used = 2 AR = 1.03(Light ÷Heavy)
1,229.0
1,230.0
1,231.0
1,232.0
1,233.0
1,234.0
1,235.0
1,236.0
1,237.0
1,458 1,463 1,468 1,473 1,478 1,483
Monoisotopic mass
4.0085 Da4.0085 Da
Scan number
0 . 0 E + 0 0
5 . 0 E + 0 6
1 . 0 E + 0 7
1 . 5 E + 0 7
1 4 6 4 1 4 6 6 1 4 6 8 1 4 7 0 1 4 7 2 1 4 7 4 1 4 7 6 1 4 7 8 1 4 8 0 1 4 8 2
Pair #372; Charge used = 2 AR = 1.03(Light ÷Heavy)
0 . 0 E + 0 0
5 . 0 E + 0 6
1 . 0 E + 0 7
1 . 5 E + 0 7
1 4 6 4 1 4 6 6 1 4 6 8 1 4 7 0 1 4 7 2 1 4 7 4 1 4 7 6 1 4 7 8 1 4 8 0 1 4 8 2
Pair #372; Charge used = 2 AR = 1.03(Light ÷Heavy)
Petritis, et al. J. Proteome Res. 2009.
From Global Discovery to Targeted Quantification
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Limitations of global discovery: Not reproducible in terms of low overlap between large number of biological replicates or missing data.
Limited sensitivity for detecting low-abundance proteins
90 % overlap
81 % overlap
39 % overlap
10 replicates
Time (min)
Product ion chromatogram
Q1
Triple Quadrupole MS
DetectorLC-ESI
Q2 Q3
Precursor ion selection
Product ion selection
Selected SRMTransitions:
544.90
Targeted quantification and multiplexed assays
445.90601.52
Selected Reaction Monitoring (SRM) mode.50-100 proteins can be tested in a single analysis.
150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900m/z
544.90601.52
535.95
217.09
y92+
y82+
Cathepsin LMIELHNQEYRm/z = 445.90
MS/MS spectrum
Targeted mass spectrometry for quantification
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~100% reproducible detection (Only selected candidates
will be screened)
Better sensitivity and no missing data (10-50 fold more
sensitive)
High specificity and absolute quantification
Multiplexed (>100 proteins per analysis) and affinity-
reagent free
Targeted mass spectrometry can quantify almost
proteins, isoforms…
PRISM‐SRM
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PRISM: high‐pressure high‐resolution separations with intelligent selection and multiplexing
Shi et al., PNAS, 2012, 109, 15395‐400.
3 µm, C18 column(200 µm i.d. × 50 cm)
Intelligent Selection of targeted peptides
96 well plate
Capillary LC (high pH)
#2 #6 #10
Fraction multiplexing(based on partial orthogonality between low and high pH RPLC)
On-line monitoring heavy internal standard peptides
LC-SRM
Tujin Shi
Outline
Introduction
Proteomics: How it works
Proteomic quantificationGlobal shotgunTargeted
Applications
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Post-translational modifications
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Many types of important PTMs can be measured by proteomics:
Phosphorylation Ubiquitination AcetylationProteolytic processing (N-terminal and C-terminal)Thiol-based redox modifications
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Cysteine, the archetypal redox regulatory amino acid
Ciriolo et al. Cell Death and Differentiation 2005.p1555
Thiol-based redox modifications are fundamental posttranslational regulatory systems in all organisms, playing essential role in regulating metabolism, gene expression, and many other cellular processes
Protein
SH
Protein
SNO·/GSNO
GSSG/GSHH2O2
GSH
GSH
Enzymatic Reducing Systemse.g., Thioredoxin/Glutaredoxin
ROS/RNS
O2-·/H2O2 Protein
SOH
S-sulfenylation
Protein
SNO
S-nitrosylation
Protein
SO3H
Protein
SO2H
Sulfinic acid
Protein
SSG
S-glutathionylation
H+
pH> pKa
REVERSIBLE IRREVERSIBLE
SIGNALING PATHOLOGY
Sulfonic acid
Reactive Cys Thiolate anion
OxyR: a molecular code for redox signaling
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Kim et al., Cell, 2002, 109, 383-396
Conformation changes
Redox Proteomics Approaches
Ascorbate
NEM Blocking free thiols
Glutaredoxin DTT Hydroxylamine
S-glutathionylation
S-acylation
S-nitrosylation
Selective reduction
Protein
SNO SSG Total oxidation S-acylation
LC-MS/MS
Peptides
Thiol‐affinity enrichment
On‐resin tryptic digestion
On‐resin multiplex isobaric labeling
(6-10 biological samples multiplexing)
Guo, et al., Nature Protocols, 2014Guo, et al., Mol Cell Proteomics, 2014
Application: Total thiol oxidation
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CyanobacteriumSynechocystis sp.PCC6803
Light/dark redox modulation
In collaboration with Dr. HimadriPakrasi at Washington Uni.
Jia Guo
LC-MS/MS analysis
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Proteome-wide Light/Dark Modulation of Protein Thiol Oxidation in Cyanobacteria
32Jia Guo, et al., Mol Cell Proteomics, 2014
oxidation
0.5 1 2
Dark DCMULight
Redox dynamics on ~2000 Cys-sites
Site stoichiometry
0
50
100
150
200
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 >90
Num
ber o
f Cys‐site
s
% Oxidation (Reversible)
LightDarkDCMU
Redox sensitive proteins
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Sedoheptulose‐1,7‐bisP
Aspartate
Oxaloacetate Pyruvate
CO2
Glycerate 3P
1,3‐bisphosphoglycerate
Glyceraldehyde‐3P
Fructose‐1,6‐P2Fructose‐6P
Sedoheptulose‐7P
Ribulose‐5P
Ribulose‐1,5‐P2Prk
Cbbl
Gap2
Fda
Slr2094
Fda
Slr2094
AspCPykCarbon fixation
H2O
PET and phycobilisome
PSII PSICytb
Fd
ATPase
H2O⅟2O2+ H+ PC
PQ
NADP++H+
NADPH PetFPetH
PsbO AtpAAtpG
ApcBApcDApcFCpcB
FNR
0%
30%
60%
90%
120%
150%
% Oxida
tion (Reversible)
Carbon Fixation Light
Dark
DCMU
Jia Guo, et al., Mol Cell Proteomics, 2014
Redox sensitivity predicts enzyme functional sites
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(a) (b)
0
1
2
3
4
5
Relativ
e oxidation level Light
DarkDCMU
(c)Gap2
WT C154S C154/C158SC292S
3.22 Å
NADP Cys154
0
2
4
6
8
10
Relativ
e Qua
ntita
tion Light
DarkDCMU
H2O H2O2 DTT DTT/H2O2
mU
/mg
prot
ein
0
200
400
600
800
1000
1200 Peroxiredoxin
(d) (e) (f)
Jia Guo, et al., Mol Cell Proteomics, 2014
Obesity, insulin resistance, and pancreatic islet hyperplasia
LIRKO
LiverInsulin resistance
More insulin secretion
Control
Pancreas
Blood circulatory factors
Islet hyperplasia
Liver Insulin Receptor Knockout (LIRKO) Model (mimic a level of stress)
In collaboration with Rohit Kulkarni at Joslin Diabetes Center
Evidence of Blood Circulatory Factors by Parabiosis Experiments
A LIRKO mouse and awild-type mouse weresurgically joined tocreate a commoncirculation. The beta cellreplication wasevaluated by BrdU after14 weeks.
LIRKO
wild-type
Enriched canonical pathways (mouse islets)
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0
2
4
6
8
10
12
14‐Log
(p‐value
)Global data
Phospho data
Based on significantly altered proteins & phosphoproteins
The story of a cell under stress
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Compensatory Response of the Islet Proteome
Productivity
Efficiency
Summary
Proteomics has become an indispensable technology for biological research, especially systems biology
New technologies are continually being developed for highly sensitive quantification of proteins, isoforms, and PTMs
It would be interested to see how the technologies are being applied and integrated with other tools to achieve predictive biology and more effective synthetic biology
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