proteomics informatics workshop part iii: protein quantitation david fenyö february 25, 2011
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Proteomics Informatics WorkshopPart III: Protein Quantitation
David Fenyö
February 25, 2011
• Metabolic labeling – SILAC• Chemical labeling• Label-free quantitation• Spectrum counting• Stoichiometry• Protein processing and degradation• Biomarker discovery and verification
MSMS/MS
Biological System
Samples
Information about each sample
Information about the biological system
Measurements
What does the sample contain?
How much?
Proteomics Informatics
ExperimentalDesign
Data Analysis
InformationIntegration
SamplePreparation
What does the sample contain?
How much?
Fractionation
Digestion
LC-MS
Lysis
MS
C ij
I ik
pij
Pr
pD
ijk pPep
ik
pLC
ik
pMS
ik
pL
ij
ppppppCIMS
ik
LC
ik
Pep
ikj
D
ijkij
L
ijijkik
Pr
Sample i Protein jPeptide k
Proteomic Bioinformatics – Quantitation
ppppppIC MS
ik
LC
ik
Pep
ik
D
ijkij
L
ijk
ikk
ij Pr
k
Fractionation
Digestion
LC-MS
Lysis
Quantitation – Label-Free (Standard Curve)
MS
IIC ikik
k
ijf )(
Sample i Protein jPeptide k
Fractionation
Digestion
LC-MS
Lysis
Quantitation – Label-Free (MS)
MS MS
pppppp MS
ik
LC
ik
Pep
ik
D
ijkij
L
ijk
Pr
Assumption:
constant for all samples
IICC jjjj iiii mnmn//
Sample i Protein jPeptide k
HL
Quantitation – Metabolic Labeling
Fractionation
Digestion
LC-MS
Light Heavy
Lysis
MS
Oda et al. PNAS 96 (1999) 6591Ong et al. MCP 1 (2002) 376
C L
jin
I L kin
CH
jim
pMjin
pM jim
I H kim
Assumption: All losses after mixing are identical for the heavy and light isotopes and
pp M
j
M
j ii mn
Sample i Protein jPeptide k
Comparison of metabolic labeling and label-free quantitation
-1 -0.5 0 0.5 1log2(ratio)
SILACLabel-Free
G. Zhang et al., JPR 8 (2008) 1285-1292
Label free assumption:
constant for all samples
Metabolic labeling assumption:
constant for all samples and the behavior of heavy and light isotopes is identical
Metabolic
pppppp MS
ik
LC
ik
Pep
ik
D
ijkij
L
ijk
Pr
pMij
G. Zhang et al., JPR 8 (2008) 1285-1292
Intensity variation between runs
Replicates
1 IP1 Fractionation
1 Digestion
vs
3 IP3 Fractionations
1 Digestion
-1 -0.5 0 0.5 1log2(ratio)
1-1-13-3-1
How significant is a measured change in amount?
It depends on the size of the random variation of the amount measurement that can be obtained by repeat measurement of identical samples.
-1 -0.5 0 0.5 1log2(ratio)
SILACLabel-FreeMetabolic
Tackett et al. JPR 2005
Protein Complexes – specific/non-specific binding
Protein Turnover
KC=log(2)/tC, tC is the average time it takes for cells to go through the cell cycle, and KT=log(2)/tT, tT is the time it takes for half the proteins to turn over.
Move heavy labeled cells to light medium
Heavy
)()()(
)()()(
0CCCCKKdC
Hj
Hj
Lj
HjTC
Hj
tt
tdtt
LightNewly produced proteins will have
light label
eCC tHj
Hj
KKt TC)()()( 0
)log()())(
)()(log( 211
ttIII
TCHj
Lj
Hj t
t
tt
Super-SILAC
Geiger et al., Nature Methods 2010
HL
Fractionation
Digestion
LC-MS
Light HeavyLysis
Quantitation – Protein Labeling
MS
Gygi et al. Nature Biotech 17 (1999) 994
Assumption: All losses after mixing are identical for the heavy and light isotopes and
pppp M
j
L
j
M
j
L
j iiii mmnn
HL
Fractionation
Digestion
LC-MS
Lysis
MS
Light
RecombinantProteins (Heavy)
Quantitation – Labeled Proteins
Assumption: All losses after mixing are identical for the heavy and light isotopes and
ppp M
j
M
j
L
j iii mnn
HL
Fractionation
Digestion
LC-MS
Lysis
MS
Light
RecombinantChimeric
Proteins (Heavy)
Quantitation – Labeled Chimeric Proteins
Beynon et al. Nature Methods 2 (2005) 587Anderson & Hunter MCP 5 (2006) 573
HL
Fractionation
Digestion
LC-MS
Light Heavy
Lysis
Quantitation – Peptide Labeling
MS
Gygi et al. Nature Biotech 17 (1999) 994Mirgorodskaya et al. RCMS 14 (2000) 1226
Assumption: All losses after mixing are identical for the heavy and light isotopes and
pppp
ppppM
k
D
jkj
L
j
M
k
D
jkj
L
j
iiii
iiii
mmmm
nnnn
Pr
Pr
HL
Fractionation
Digestion
LC-MS
Light
Lysis
SyntheticPeptides(Heavy)
Quantitation – Labeled Synthetic Peptides
MS
Gerber et al. PNAS 100 (2003) 6940
Enrichment withPeptide antibody
Assumption: All losses after mixing are identical for the heavy and light isotopes and
ppppp M
sk
M
k
D
jkj
L
j iiii nnnn
Pr
Anderson, N.L., et al. Proteomics 3 (2004) 235-44
Fractionation
Digestion
LC-MS
Lysis
MS/MSMSMSMS/MS
Quantitation – Label-Free (MS/MS)
SRM/MRM
MS/MS
SyntheticPeptides(Heavy)
SyntheticPeptides(Heavy)
Light
HLMSHL
MS
MS/MSMS/MSMS/MSL LH H
DigestionLC-MS
Lysis/Fractionation
Quantitation – Labeled Synthetic Peptides
Fractionation
Digestion
LC-MS
Light Heavy
Lysis
L HMS MS/MS
Quantitation – Isobaric Peptide Labeling
Ross et al. MCP 3 (2004) 1154
Fractionation
Digestion
LC-MS
Lysis
Quantitation –Label-Free (MS)
MS MS
Fractionation
Digestion
LC-MS
Lysis
MS/MSMSMSMS/MS
Quantitation –Label-Free (MS/MS)
HL
Quantitation –Metabolic Labeling
Fractionation
Digestion
LC-MS
Light Heavy
Lysis
MS HL
Fractionation
Digestion
LC-MS
Light HeavyLysis
Quantitation –Protein Labeling
MS HL
Fractionation
Digestion
LC-MS
Lysis
MS
Light
RecombinantChimeric
Proteins (Heavy)
Quantitation –Labeled Chimeric Proteins
HL
Fractionation
Digestion
LC-MS
Light Heavy
Lysis
Quantitation –Peptide Labeling
MS HL
Fractionation
Digestion
LC-MS
Light
Lysis
SyntheticPeptides(Heavy)
Quantitation –Labeled Synthetic Peptides
MS
Fractionation
Digestion
LC-MS
Light Heavy
Lysis
L HMS MS/MS
Quantitation –Isobaric Peptide Labeling
Fractionation
Digestion
LC-MS
Lysis
Quantitation – Label-Free (Standard Curve)
MS
m = 1035 Da m = 1878 Da m = 2234 Da
Isotope distributions
m/z m/z m/z
Inte
nsity
Peak Finding
m/z
Inte
nsity
2/||
)()(wlk
kIlSFind maxima of
The signal in a peak can beestimated with the RMSD
22
2
//||
))((w
wlkIkI
and the signal-to-noise ratio of a peak can be estimated by dividing the signal with the RMSD of the background
Background subtraction
m/z
Inte
nsity
Estimating peptide quantity
Peak heightCurve fittingPeak area
Peak heightCurve fitting
m/z
Inte
nsity
Time dimension
m/z
Inte
nsity
Tim
e
m/z
Tim
e
Sampling
Retention Time
Inte
nsity
0
5
10
15
20
25
30
0.8 0.85 0.9 0.95 1
3 points
0
20
40
60
80
100
120
140
0.8 0.85 0.9 0.95 1
3 points
5%
Acquisition time = 0.05s
5%
Sampling
0.5
0.6
0.7
0.8
0.9
1
1.1
1 2 3 4 5 6 7 8 9 10
Thre
shol
ds (9
0%)
# of points
Sampling
Estimating peptide quantity by spectrum counting
m/z
Tim
eLiu et al., Anal. Chem. 2004, 76, 4193
What is the best way to estimate quantity?
Peak height - resistant to interference- poor statistics
Peak area - better statistics - more sensitive to interference
Curve fitting - better statistics- needs to know the peak shape- slow
Spectrum counting - resistant to interference- easy to implement- poor statistics for low-abundance proteins
Examples - qTOF
Examples - Orbitrap
Examples - Orbitrap
Isotope distributions
Peptide mass
Inte
nsity
ratio
Peptide massIn
tens
ity ra
tio
AADDTWEPFASGK
Inte
nsity
Inte
nsity
Inte
nsity
Time
AADDTWEPFASGK
Inte
nsity
Inte
nsity
Inte
nsity
0
1
20
1
2
Rat
ioR
atio
0
1
20
1
2
Time
AADDTWEPFASGK
Inte
nsity
Inte
nsity
Inte
nsity
m/z
m/z
m/z
G
H
I
YVLTQPPSVSVAPGQTAR
TimeIn
tens
ityIn
tens
ityIn
tens
ity
YVLTQPPSVSVAPGQTAR
Inte
nsity
Inte
nsity
Inte
nsity
0
1
20
1
2R
atio
Rat
io
0
1
20
1
2
Time
YVLTQPPSVSVAPGQTAR
Inte
nsity
Inte
nsity
Inte
nsity
m/z
m/z
m/z
Retention Time Alignment
Mass Calibration
Cox & Mann, Nat. Biotech. 2008
The accuracy of quantitation is dependent on the signal strength
Cox & Mann, Nat. Biotech. 2008
Workflow for quantitation with LC-MS
Standardization
QualityControl
Quantitation
PeptideQuantities
LC-MSData
StandardizationRetention time alignmentMass calibrationIntensity normalization
Quality ControlDetection of problems with samples and analysis
QuantitationPeak detectionBackground subtractionLimits for integration in time and massExclusion of interfering peaks
Biomarker discovery
Fractionation
Digestion
LC-MS
Lysis
MS MS
Reproducibility
Paulovich et al., MCP 2010
MS/MS
SyntheticPeptides(Heavy)
SyntheticPeptides(Heavy)
Light
HLMSHL
MS
MS/MSMS/MSMS/MSL LH H
DigestionLC-MS
Lysis/Fractionation
Biomarker verification
Addona et al., Nat. Biotech. 2009
ReproducibilityCPTAC Verification Work Group Study 7
10 peptides
3 transitionsper peptide
Conc. 1-500 fmol/μl Human plasma Background
8 laboratories 4 repeat analyses per lab
Reproducibility
Addona et al., Nat. Biotech. 2009
Correction for interference
MRM analysis of low abundance proteins is sensitive to interference from other components of the sample that have the same precursor and fragment masses as the transitions that are monitored.
During development of MRM assays, care is usually taken to avoid interference, but unanticipated interference can appear when the finished assay is applied to real samples.
Ratios of intensities of transitions
0
1
2
3
4
1 10 100 1000
Inte
nsity
ratio
Concentration
tr2/tr1tr3/tr1
0.1
1
10
100
1000
1 10 100 1000
Mea
sure
d co
ncen
tratio
n [fm
ol/u
l]
Actual concentration [fmol/ul]
linetr1tr2tr3
0.1
1
10
100
1 10 100 1000
Inte
nsity
ratio
Concentration
tr1/tr2tr3/tr2
0.1
1
10
100
1000
1 10 100 1000
Mea
sure
d co
ncen
tratio
n [fm
ol/u
l]
Actual concentration [fmol/ul]
linetr1tr2tr3
Peptide 1 Peptide 2
Peptide 1 Peptide 2
Detection of interferenceInterference is detected by comparing the ratio of the intensity of pairs of transitions with the expected ratio and finding outliers. Transition i has interference ifwhere Zthreshold is the interference detection threshold; ;
zji is the number of standard deviations that the ratio between the intensities of transitions j and i deviate from the noise;Ii and Ij are the intensities of transitions i and j; rji is the expected ratio of the intensity of transitions j and i; andsji is the noise in the ratio.
zz ithreshold
s ji
ijji
ijji
iji
IIrzz
maxmax
0.1
1
10
100
1000
1 10 100 1000
Mea
sure
d co
ncen
tratio
n [fm
ol/u
l]
Actual concentration [fmol/ul]
line
Uncorrected
corrected
0.1
1
10
100
1000
1 10 100 1000
Mea
sure
d co
ncen
tratio
n [fm
ol/u
l]
Actual concentration [fmol/ul]
line
Uncorrected
corrected
Correction for interference in experimental data
Peptide 1 Peptide 2
-10
0
10
20
30
40
50
1 10 100 1000
Rel
ativ
e er
ror
Actual concentration [fmol/ul]
line
Uncorrected
Corrected
0.1
1
10
100
1000
1 10 100 1000
Mea
sure
d co
ncen
tratio
n [fm
ol/u
l]
Actual concentration [fmol/ul]
line
Uncorrected
corrected
0.1
1
10
100
1000
1 10 100 1000
Mea
sure
d co
ncen
tratio
n [fm
ol/u
l]
Actual concentration [fmol/ul]
line
Uncorrected
corrected
Correction for interference in experimental data
Peptide 1 Peptide 2
-0.2
-0.1
0
0.1
0.2
1 10 100 1000
Rel
ativ
e er
ror
Actual concentration [fmol/ul]
line
Uncorrected
Corrected
Peptide 1
-0.2
0
0.2
0.4
0.6
0.8
1 10 100 1000
Rel
ativ
e er
ror
Actual concentration [fmol/ul]
UncorrectedCorrected
Peptide 2
Proteomics Informatics WorkshopPart I: Protein Identification, February 4, 2011
Part II: Protein Characterization, February 18, 2011
Part III: Protein Quantitation, February 25, 2011
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