pc219 lecture 5 30 april, 2010 [email protected] · 2010. 4. 12. · ms resolution: 60000 ms2...
TRANSCRIPT
2
Applications of Quantitative Proteomics
Detecting changes in proteomes
in space: cellular and tissue localizationin time: signaling cascades or turnoversample perturbations:
•Comparison of normal and diseased tissue samples
Biomarker discovery
•Drug development
•Diagnostics
•Gene knockdowns or over expression
•Inhibitors: eg antibodies or siRNA
•Growth factors/hormones
•Cell-cell interactions
•Drug treatment
Qualitative protein identification is NOT sufficient to describe a biological system
3
Quantitative Proteomics Methodologies
2D gel electrophoresis
silver stain
Fluorescence Difference Gel Electrophoresis
Pro-Q Diamond
2,4-dinitrophenylhydrazine
Protein expression array analysis
Global epitope tagging(Nature2003v425p737)
MS-based quantification methods
• Quantification• H/D exchange – protein surface mapping• Proteomics dynamics
4
LCMSMS
Quantification
Stable Isotope
Labeling
Label-free
methods
Metabolic
SILAC
In-vitro
iTRAQ
Survey
Intensity based
Spectral
counting
MS1
MS2MRM
Basic Classifications of MS Based Quantification
5
Label Free Quantification
6
Label Free QuantificationSpectral Counting
AnalChem2004v76p4193
•Spectral counts (# of MSMS from a Protein) correlate with protein abundance well
•Spectral counting dynamic range (single runs) is about two orders of magnitude
•10 repeated analysis can reach 95% saturation level
7
Label Free QuantificationSpectral Counting
Minimum protein ratios that can
be determined at 80 and 95%
confidence limits
MCP2005v4p1487
8
Label Free QuantificationSpectral Counting - Formula
NSAF: normalized spectral abundance factor(PNAS2006v103p18928)
SpC: total number of tandem MS spectra matching peptides from protein
L: protein length
n1, n2 - spectral counts for sample 1 and 2
t1, t2 – total spectral count (sampling depth) for samples 1 and 2
f – correction factor 0.5 (Bioinformatics2004v20pi31)
RSC: log2(protein ratio) measured from spectral counts(MCP2005v4p1487)
9
BZR1
C P
In-Vitro Phosphorylation of BZR1 by BIN2 Kinase
E. coli expressed MBP-BZR1 as substrate
E. coli expressed GST-Bin2 as kinase
Phospho sample: BZR1+Bin2+ATP
Control sample: BZR1+Bin2
ZY Wang of Carnegie Institution
Goal: Estimate Stoichiometry of PTMs
Label Free QuantificationExtracted Ion Chromatogram Based Methods
10
m/z
949.38-949.47
RT
35.0
Label Free QuantificationExtracted Ion Chromatogram Based Methods
Retention time - m/z ion map: Phospho sample (BZR1+Bin2+ATP)RT:0.00 - 60.04
0 10 20 30 40 50 60Time (min)
0
10
20
30
40
50
60
70
80
90
100
Rela
tive A
bundance
34.95
400 600 800 1000 1200m/z
0
10
20
30
40
50
60
70
80
90
100
Rela
tive A
bundance
633.29z=3
881.89z=4
949.94z=2599.83
z=21175.52
z=3664.34z=4
750.90z=2
489.29z=2
1055.52z=2
391.29z=1
872.67z=?
1202.50z=?
Spectrum @ rt=35.0
Extracted
Ion chromatogram
for m/z range of
949.38-949.47
11
Label Free QuantificationExtracted Ion Chromatogram Based Methods
Phospho Sample Control Sample
12
Label Free QuantificationExtracted Ion Chromatogram Based Methods
160 170 180 190 200 210 220 230
1750
1800
1850
1900
1950
2000
p3
p2
p1
p0
10 20 30 40 50
p3
p2
p1p0
m/z
Retention TimeRetention Time
170 186
ISNSCPVTPPVSSPTSK
Phosphopeptides
13
Label Free QuantificationExtracted Ion Chromatogram Based Methods
259FAQQQPFSASMVPTSPTFNLVKPAPQQMSPNTAAFQEIGQSSEFK303++++
38 39 40 41 42 43 440
1
2
3
4
5
6x 104
Ret. Time (min)
*Non-constant sampling rate
*Noisy signal
*Initial peak parameters
0.9230.982R2
0.3460.319Peak Width
(min)
7.14X1032.26X104Peak Area
(min)
1.86X1045.67X104Peak Height
40.8140.85Ret. Time
(min)
PhosphoControl
m/z = 1225.63, z = 4
Extracted Ion Chromatogram and Integration
14
Label Free QuantificationExtracted Ion Chromatogram Based Methods
15 20 25 30 35 40 45 50-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
15 20 25 30 35 40 45 50-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Retention Time (min) Retention Time (min)
Sample a
Sample b
Before After
Sample a
Sample b
LC Alignment of base-peak chromatograms:
•Dynamic Time Wrapping (similarity in chromatograms)
•Use “landmark” ions (needs MSMS info)
15
In vitro PhosphorylationEColi MBP
Control
Phosp
ho
Lo
g1
0(s
elec
ted
io
n c
hro
mat
og
ram
pea
k a
rea)
Log10(selected ion chromatogram peak area)3 3.5 4 4.5 5 5.5 6 6.5 7
3
3.5
4
4.5
5
5.5
6
6.5
7
77 peptide ion pairs
Std Dev = 11.4%
Stoichiometry of PTMs
Label Free QuantificationExtracted Ion Chromatogram Based Methods
16
3.5 4 4.5 5 5.5 6 6.5 73.5
4
4.5
5
5.5
6
6.5
7
170ISNSCPVTPPVSSPTSK186++
105VTPYSSQNQSPLSSAFQSPIPSYQVSPSSSSFPSPSR141+++
142GEPNNNM(o)SSTFFPFLR157++
259FAQQQPFSASMVPTSPTFNLVKPAPQQMSPNTAAFQEIGQSSEFK303++++
200Q(q)SMAIAK206+
207QSM(o)ASFNYPFYAVSAPASPTHR228+++
36RER38+
229HQFHTPATIPECDESDSSTVDSGHWISFQK258+++++
187NPKPLPNWESIAK199++
207QSMASFNYPFYAVSAPASPTHR228+++
229HQFHTPATIPECDESDSSTVDSGHWISFQK258++++
207Q(q)SMASFNYPFYAVSAPASPTHR228+++
158NGGIPSSLPSLR169++
200QSM(o)AIAK206++
Phosp
ho
Lo
g1
0(s
elec
ted
io
n c
hro
mat
og
ram
pea
k a
rea)
Control
Log10(selected ion chromatogram peak area)
Stoichiometry of PTMs
Label Free QuantificationExtracted Ion Chromatogram Based Methods
In vitro Phosphorylation: BZR1_ARATH
17
User Interface
- Scatter Plot, Extracted IC, Peptide ID Page
Stoichiometry of PTMs
18
BRASSINAZOLE-RESISTANT 1 protein (BZR1)
Extent of Phosphorylation
S, T, and Y are conformed assignments
in this experiment
S and Y are tentative assignment
10 20 30 40 50
60 70 80 90 100
110 120 130 140 150
160 170 180 190 200
210 220 230 240 250
260 270 280 290 300
310 320 330
---------- ---------- -RRKPSWRER ENNRRRERRR RAVAAKIYTG
LRAQGDYNLP KHCDNNEVLK ALCVEAGWVV EEDGTTYRKG CKPLPGEIAG
TSSRVTPYSS QNQSPLSSAF QSPIPSYQVS PSSSSFPSPS RGEPNNNMSS
TFFPFLRNGG IPSSLPSLRI SNSCPVTPPV SSPTSKNPKP LPNWESIAKQ
SMAIAKQSMA SFNYPFYAVS APASPTHRHQ FHTPATIPEC DESDSSTVDS
GHWISFQKFA QQQPFSASMV PTSPTFNLVK PAPQQMSPNT AAFQEIGQSS
EFKFENSQVK PWEGERIHDV GMEDLELTLG NGKARG
<10%
~85%
~90%
~80%
~45% ~30%
~70%
<10% <10%
Stoichiometry of PTMs
19
Label Free QuantificationExtracted Ion Chromatogram Based Methods
Data Processing Workflow
.Raw File
Survey Scans
MS2 Scans
Peak Extract
IDed
Ion Chrom.
Quantitation
Results
Peptide/
Protein ID
DataBase
SearchRun Comparison
Integration
20
Label Free QuantificationExtracted Ion Chromatogram Based Methods
JProteomeRes2008v7p51
Proteomics2008v8p731
21
Label Free QuantificationExtracted Ion Chromatogram Based Method - OpenMS
BMCBioinformatics2008v9p163
Isotope distribution modeling: wavelet
Software architecture: C++/Linux
22
Label Free QuantificationExtracted Ion Chromatogram Based Method
Experimental
Consistency in sample collection and processing
LC and MS stability
Replicate analysis
Data Prcessing
•Data format
•Data visualization
•Normalization
Mass recalibration
LC retention time alignment
Abundance normalization
•Data quality assessment
•Result analysis
Difference detection
Multivariate analysis
Log(Peptide abundance)Log(R
eplic
ate
peptid
e r
atio)
JProteomeRes2006v5p277
23
Stable Isotope Labeling
24
Experimental StrategiesIntroduction of Controls in Stable Isotope Labeling
(QconCAT:Spiked Q-proteins)
Proteomics2008v8p4873
25
Absolute Quantification (AQUA) with Internal Standard Peptides
PNAS2003v100p6940
26
QconCATTryptic standard peptides from artificial proteins
NatMethods2005v2p587
Artificial protein
Containing
concatenated tryptic Q peptides
and his-tag
27
Stable Isotope Chemical Labeling
28
stable isotope chemical labelingdimethyl labeling of ε-amine
NatProtocol2009v4p484
•Can be performed (a) in-solution, (b) online with LC-MS or (c) on-column(SepPak)
•2 carbons and 6 hydrogens for labeling – in principle
•Quantification in MS or survey scan level
29
stable isotope chemical labelingMethyl esterification of carboxyl groups
•Perform in dry condition (sample, glassware, etc)
if a peptide has 10 Es or Ds and single site labeling efficiency is 99%,
only 90% of peptide is fully labeled
•Help to increase charge states (better sensitivity)
decrease acidic groups (better fragmentation)
improve phosphopeptide enrichment
•Quantification in MS or survey scan level
JProteomeRes2009v8p1431
C
O
OH
+ CH3OH C
O
OCH3
+ H2O
C
O
OH
+ CD3OH C
O
OCD3
+ H2O
30
Isotope coded affinity tag (ICAT)
CurOpinionBiotechnol2000v11p396
•Purify peptides by streptavidin beads
•Only labels cysteines
•The tag is too large for MS
•Difficult to elude peptides
31
Isotope coded affinity tag (ICAT)
http://www.absciex.com/LITERATURE/cms_040324.pdf
•Acid cleavable linker facilitates release•Heavy and light carbon allows for co-eluting peptides•The structure is not disclosed
Early usage: AnalChem2006v78p4543
32
metal-coded affinity tag (MeCAT)
MCP2007v6p1907
thiol-specific labelingspacermetal coding
•Labeling group: cysteines
•Metals used: 159Tb 165Ho 169Tm and 175Lu
•Detection limit: 100amole
33
Isobaric Tags for Relative and Absolute Quantitation (iTRAQ)
MolCelProteomics2004v3p1154
34
Isobaric Tags for Relative and Absolute Quantitation (iTRAQ)
MolCelProteomics2008v7p853
35
Tandem Mass Tag (TMT)
http://www.piercenet.com/Objects/View.cfm?type=Page&ID=B60171CD-5056-8A76-4E36-958F5C186495#tmtstruct
6 Channels
36
MS Instrumentation for iTRAQ
iTRAQ was initially introduced on Q-TOF type instruments
•MS3 in ion traps(http://www.thermo.com/eThermo/CMA/PDFs/Various/File_27402.pdf)
•PQD for detecting fragment ions on ion traps(MCP2008v7p1702)
•HCD for detection on Orbitraps
LTQ Velos Oritrap
•ETD (or combined with CID) can
generate reporter ions(AnalChem2009v81p1693)
m/z
101-108m/z
113-121
“1/3 Rule”
37Jonathan Trinidad
iTRAQBoth quantification and identification info is contained in MSMS
Reporter Ions
Peptide fragment ions contain isobaric tags
38
Quantification with TMT
Mass Spectrometer: Thermo Scientific LTQ Orbitrap VelosMS Resolution: 60000
MS2 Resolution: 7500
MS AGC target: 1e6
MS/MS AGC target: 5e4
Exclusion mass tolerance: 10 ppmInjection Time FTMS/MS: 200 ms
Full MS mass range: 400–1400 m/z
MS/MS Mass range: 100–2000 m/z
Isolation 1.2 Da
MS/MS Events: Full MS in Orbitrap followed by top ten data dependent HCD MS/MS
CE for HCD: 45%
Terry Zhang
E. Coli digestQuantifiable peptides
•74% (40ng)
•81% (80ng)
Quantification Errors
•20% (40ng)
•15% (80ng)
39NatBiotech2007v25p994
iTRAQ
Quantification of Phosphorylation Levels
Kinobeads: ~1000 kinase inhibitors(http://www.cellzome.com/files/kinobeads.pdf)
40
iTRAQ
Phosphorylation Levels and Signaling Pathways
PNAS2007v104p12867
EGFR pathways: Different receptor level in U87MG glioblastoma cell lines
41
iTRAQlocalization of organelle proteins by isotope tagging (LOPIT)
NatProtocols2006v1p1778
vacuolar membrane
ER
PM
Golgi apparatus
mitochondria_plastids
Principal component analysis (PCA)
Reduction of dimensions
42
Quantification
Data Analysis – Clustering Analysis
PNAS2007v104p12867
Self Organized Maps (SOM)
MCP2008v7p684
Hierarchical Clustering
Reference: PNAS1998v95p14863
Freeware: http://rana.lbl.gov/EisenSoftware.htm
43
Proteolytic 18O Labeling
Electrophoresis1996v17p945
Trypsin introduces a mixture of
one and two 18O incorporated
peptides
LysN incorporates a single 18O at
high pH
JProteomeRes2005v4p507
MCP2005v4p1550
AnalChem2001v73p2836
44
Metabolic Stable Isotope Labeling
MCP2010v9p11
MCP2002v1p376
PNAS1999v96p6591
Phytochemistry2004v65p1507
PlantJ2008v56p840
45
Metabolic Stable Isotope LabelingStable Isotope Labeling by Amino Acids in Cell Culture (SILAC)
NatBiotechnol2004v22p1139
46
Multiple Reaction Monitoring(MRM)
Term coined by Cooks et al in 1978(AnalChem1978v50p2017)
Used by pharmaceutical industry for years
Drug metabolites analysis
Performance improved by introduction of Qtrap instruments(DDTtarget2004v3pS31)
Modern instruments have MRM dwell time of 5msec
Sensitivity of <1fmole
47
Multiple Reaction Monitoring(MRM)information-dependent acquisition (IDA) to MRM Transitions
PNAS2007v104p5860
48
Multiple Reaction Monitoring(MRM)Specificity of MRM Transitions – Fragment Ion Coelution
PNAS2007v104p5860
49
TM
Immature MatureSU
Gag
MA
CA
RNANC
MA CA p2 NC p1 p6MA CA p2 NC p1 p6
Gag (55 kDa)
24 kDa
HIV
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
A.G. Marshall
50
Protein or Complex
D
D
D
D
D
D
D
H
H
Dilute 10 fold
w/ D2O
buffer
H/D exchange
Quench
Digest with pepsin in ice water for 3 min
pD 2.5 ~ 3.0
Freeze in
liquid N2
& store
at -70 oC
Thaw
on ice
InjectMicro-bore c8 column
30 µµµµL/min
SplitterSplitterSplitterSplitter
to wasteto wasteto wasteto waste
Online LC/FT-ICR MS
Ice water
Ice water
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
A.G. Marshall
51
PIVQNLQGQM VHQAISPRTL NAWVKVVEEK AFSPEVIPMF SALSEGATPQ
DLNTMLNTVG GHQAAMQMLK ETINEEAAEW DRLHPVHAGP IAPGQMREPR
GSDIAGTTST LQEQIGWMTH NPPIPVGEIY KRWIILGLNK IVRMYSPTSI
LDIRQGPKEP FRDYVDRFYK TLRAEQASQE VKNWMTETLL VQNANPDCKT
ILKALGPGAT LEEMMTACQG VGGPGHKARV L
Peptic Peptides Cover 95% of CA Primary AA Sequence
1
51
101
151
201 231
A.G. Marshall
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
52
H/D Exchange
Period (min)
4080
0
0.5
2
60
240
843 846 849m/z
Assembled CA Monomer CA
Y169-L189
A.G. Marshall
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
53
1 10 100 1000
1490
1491
1492
1493
1494
1495
1496
1497
1498
Time (min)
Bottom of Helix III Protected upon AssemblyCentroidMass CA
Assembled CA
A.G. Marshall
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
54
1 10 100 10001934
1935
1936
1937
1938
1939
1940
1941
Time (min)
CA
Assembled CA
Helices VI and VII Not Protected upon AssemblyCentroidMass
A.G. Marshall
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
55
Hydrogen/Deuterium ExchangeStudy of High Order Protein Structures
AnalChem2009v81p7892
H/D by Topdown Analysis
Fully deuterated protein
+1H2O/CH3CO2N
1H4 at pH 3.5
56
Dynamic ProteomicsStudy Protein Turnover on A Proteomic Scale
FunctionalGenomicsProteomics2005v3p382
57
Dynamic ProteomicsExperimental Strategies
JProteomeRes2009v8p104
AnalChem2004v76p86
Dynamic SILAC
Synthesis/Degradation Ratio
Mass Spectrometry
58
Dynamic ProteomicsDynamic SILAC
FunctionalGenomicsProteomics2005v3p382
Chicken fed with stable isotope labeled valine
VKVGVNGFGR
Re
lative
Iso
top
e A
bunda
nce
59
Dynamic ProteomicsSILAC Mouse
Cell2008v134p353
60MCP2009v8p2653
Dynamic ProteomicsWater Labeling
incorporation of 2H or 18O into plasma albumin
by bolus injection
61
Conclusions
•Label free quantification was originated and is still driven by biomarker discovery
•Absolute quantification is possible with spiked-in or QconCAT calibrant peptides
•SILAC allows mixing at protein level
•iTRAQ has been widely used for studying signaling pathways
•Dynamics of a proteome can be probed by metabolic labeling