Proteomics Informatics Workshop
Part 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
Proteomics Informatics
Biological System
Experimental
Design
Samples
MS/MS
MS
Sample
Preparation
Measurements
Data Analysis
Information about each sample
Information
Integration
Information about the biological system
What does the
sample contain?
How much?
Proteomic Bioinformatics – Quantitation
C ij
p
p
p
Lysis
L
ij
p
D
ijk
LC
Fractionation
Pr
p
ij
Digestion
p
ik
I
Sample i
Protein j
Peptide k
ik
Pep



k  C ij
j 
Cij 
k
L
Pr
ij
ij
p p
ik
I
LC-MS
ik
MS

pijk
D
MS
ik
Pep
LC
MS
ik
ik
ik
p p p
I
 p p p p p p
ik
k
L
Pr
D
Pep
LC
MS
ij
ij
ijk
ik
ik
ik

k
Quantitation – Label-Free (Standard Curve)
Sample i
Protein j
Peptide k
Lysis
Fractionation
Digestion
LC-MS
MS
C
k
ij
 f ( I ik )  
I
ik
Quantitation – Label-Free (MS)
Sample i
Protein j
Peptide k
Lysis
Fractionation
Digestion
LC-MS
MS
Assumption:
 p p p p p p
k
L
Pr
D
Pep
LC
MS
ij
ij
ijk
ik
ik
ik
constant for all samples
Ci / Ci
n
MS
j
m
j
I
in j / I im j
Quantitation – Metabolic Labeling
L
Ci
n
j
H
Light
Heavy
n
m
j
M
M
pi
Ci
pi
Lysis
j
j
Assumption: All
Fractionation
losses after mixing
are identical for the
Digestion
heavy and light
isotopes
and
M
M
LC-MS
pi j  pi j
n
Sample i
Protein j
Peptide k
m
L
Ii
n
k
L
H MS
m
H
Ii
m
k
Oda et al. PNAS 96 (1999) 6591
Ong et al. MCP 1 (2002) 376
Comparison of metabolic labeling
and label-free quantitation
SILAC
Metabolic
Label free assumption:
Label-Free
 p p p p p p
k
L
Pr
D
Pep
LC
MS
ij
ij
ijk
ik
ik
ik
constant for all samples
Metabolic labeling assumption:
p
-1
-0.5
0
log2(ratio)
0.5
1
M
ij
constant for all samples and
the behavior of heavy and light
isotopes is identical
G. Zhang et al., JPR 8 (2008) 1285-1292
Intensity variation between runs
Replicates
1 IP
1 Fractionation
1 Digestion
1-1-1
3-3-1
vs
3 IP
3 Fractionations
1 Digestion
-1
-0.5
0
log2(ratio)
0.5
1
G. Zhang et al., JPR 8 (2008) 1285-1292
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.
SILAC
Metabolic
Label-Free
-1
-0.5
0
log2(ratio)
0.5
1
Protein Complexes – specific/non-specific binding
Tackett et al. JPR 2005
Protein Turnover
Heavy
dC
C
H
j
dt
L
j
Move heavy
labeled cells to
light medium
(t )
Newly produced
proteins will have
light label
 (K C  K T ) C
(t )  C
H
j
(t )  C
H
j
H
j
(t )
(0)
C
H
j
(t )  C
H
j
Light
(

)t
(0) e K C K T
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.
I
log(
H
j
(t )  I j (t )
L
I
H
j
(t )
) t(
1
t
C

1
t
T
) log( 2)
Super-SILAC
Geiger et al., Nature Methods 2010
Quantitation – Protein Labeling
Light
Lysis
Heavy
Fractionation
Digestion
Assumption: All
losses after mixing
are identical for the
heavy and light
isotopes
and
L
M
L
M
p i j pi j  p i j pi j
n
n
m
m
LC-MS
L
H MS
Gygi et al. Nature Biotech 17 (1999) 994
Quantitation – Labeled Proteins
Recombinant
Proteins (Heavy)
Lysis
Light
Fractionation
Digestion
LC-MS
L
H MS
Assumption: All
losses after mixing
are identical for the
heavy and light
isotopes
and
L
M
M
pi j pi j  pi j
n
n
m
Quantitation – Labeled Chimeric Proteins
Recombinant
Chimeric
Proteins (Heavy)
Lysis
Fractionation
Light
Digestion
LC-MS
L
H MS
Beynon et al. Nature Methods 2 (2005) 587
Anderson & Hunter MCP 5 (2006) 573
Quantitation – Peptide Labeling
Assumption: All
losses after mixing
are identical for the
heavy and light
isotopes and
Lysis
Fractionation
L
Light
Heavy
D
M
pi pi pi pi
n
Digestion
Pr

j
n
L
j
n
Pr
jk
D
n
k

M
pi pi pi pi
m
j
m
j
m
jk
m
k
LC-MS
L
H MS
Gygi et al. Nature Biotech 17 (1999) 994
Mirgorodskaya et al. RCMS 14 (2000) 1226
Quantitation – Labeled Synthetic Peptides
Lysis
Fractionation
Assumption: All
losses after mixing
are identical for the
heavy and light
isotopes and
L
Enrichment with
Peptide antibody
Light
Anderson, N.L., et al.
Proteomics 3 (2004) 235-44
LC-MS
L
D
M
pi pi pi pi
n
Digestion
Pr
j
n
j
n
jk
n
k

p
M
sk
Synthetic
Peptides
(Heavy)
H MS
Gerber et al. PNAS 100 (2003) 6940
Quantitation – Label-Free (MS/MS)
Lysis
Fractionation
Digestion
LC-MS
SRM/MRM
MS/MS
MS
MS
MS/MS
Quantitation – Labeled Synthetic Peptides
Light
Lysis/Fractionation
Synthetic
Peptides
(Heavy)
Digestion
LC-MS
L
L
MS/MS
Synthetic
Peptides
(Heavy)
H
H
MS
MS/MS
L
L
H
MS/MS
MS
H
MS/MS
Quantitation – Isobaric Peptide Labeling
Lysis
Fractionation
Digestion
Light
Heavy
LC-MS
MS
L
Ross et al. MCP 3 (2004) 1154
H MS/MS
Quantitation – Label-Free (MS)
Quantitation – Label-Free (MS/MS)
Quantitation – Label-Free (Standard Curve)
Lysis
Lysis
Lysis
Fractionation
Fractionation
Fractionation
Digestion
Digestion
Digestion
LC-MS
LC-MS
LC-MS
MS
MS
Quantitation – Metabolic Labeling
Light
MS/MS
MS
MS
MS
MS/MS
Quantitation – Protein Labeling
Quantitation – Labeled Chimeric Proteins
Recombinant
Chimeric
Proteins (Heavy)
Heavy
Lysis
Lysis
Light
Fractionation
Lysis
Heavy
Fractionation
Fractionation
Light
Digestion
Digestion
Digestion
LC-MS
LC-MS
LC-MS
L
H MS
L
H MS
L
H MS
Quantitation – Peptide Labeling
Quantitation – Isobaric Peptide Labeling
Quantitation – Labeled Synthetic Peptides
Lysis
Lysis
Lysis
Fractionation
Fractionation
Fractionation
Digestion
Light
Heavy
LC-MS
L
H MS
Digestion
Light
Digestion
Light
Heavy
LC-MS
LC-MS
MS
L
H MS/MS
L
H MS
Synthetic
Peptides
(Heavy)
Isotope distributions
m = 1878 Da
m = 2234 Da
Intensity
m = 1035 Da
m/z
m/z
m/z
Intensity
Peak Finding
Find maxima of
S (l )   I (k )
|k l |w / 2
m/z
The signal in a peak can be
estimated with the RMSD
 (I (k )  I )
2
|k l |w / 2
w /2
and the signal-to-noise ratio of a peak
can be estimated by dividing the signal
with the RMSD of the background
Intensity
Background subtraction
m/z
Estimating peptide quantity
Intensity
Peak height
Curve fitting
Peak area
m/z
Intensity
Time dimension
Time
Time
m/z
m/z
Intensity
Sampling
Retention Time
Sampling
140
3 points
120
100
80
60
5%
40
20
0
0.8
0.85
0.9
0.95
1
0.95
1
30
3 points
25
20
5%
15
10
5
0
0.8
0.85
0.9
Acquisition time = 0.05s
Sampling
Thresholds (90%)
1.1
1
0.9
0.8
0.7
0.6
0.5
1
2
3
4
5
6
7
# of points
8
9
10
Time
Estimating peptide quantity by spectrum counting
m/z
Liu 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
Intensity ratio
Intensity ratio
Isotope distributions
Peptide mass
Peptide mass
Intensity
Intensity
Intensity
AADDTWEPFASGK
Time
2
2
1
Ratio
1
0
2
0
2
Ratio
Intensity
Intensity
Intensity
AADDTWEPFASGK
1
1
0
0
Time
m/z
m/z
m/z
Intensity
Intensity
Intensity
AADDTWEPFASGK
G
H
I
Intensity
Intensity
Intensity
YVLTQPPSVSVAPGQTAR
Time
2
2
1
Ratio
1
0
2
0
2
Ratio
Intensity
Intensity
Intensity
YVLTQPPSVSVAPGQTAR
1
1
0
0
Time
m/z
m/z
m/z
Intensity
Intensity
Intensity
YVLTQPPSVSVAPGQTAR
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
LC-MS
Data
Standardization
Retention time alignment
Mass calibration
Intensity normalization
Quality Control
Detection of problems with
samples and analysis
Quantitation
Peak detection
Background subtraction
Limits for integration in time and mass
Exclusion of interfering peaks
Standardization
Quality
Control
Quantitation
Peptide
Quantities
Biomarker discovery
Lysis
Fractionation
Digestion
LC-MS
MS
MS
Reproducibility
Paulovich et al., MCP 2010
Biomarker verification
Light
Lysis/Fractionation
Synthetic
Peptides
(Heavy)
Digestion
LC-MS
L
L
MS/MS
Synthetic
Peptides
(Heavy)
H
H
MS
MS/MS
L
L
H
MS/MS
MS
H
MS/MS
Reproducibility
CPTAC
Verification
Work Group
Study 7
10 peptides
3 transitions
per peptide
Conc. 1-500 fmol/μl
Human plasma
Background
8 laboratories
4 repeat analyses
per lab
Addona et al., Nat. Biotech. 2009
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
1000
Peptide 1
Measured concentration [fmol/ul]
Measured concentration [fmol/ul]
1000
100
10
line
tr1
tr2
tr3
1
0.1
100
10
line
tr1
tr2
tr3
1
0.1
1
10
100
Actual concentration [fmol/ul]
1000
1
Peptide 1
4
tr2/tr1
tr3/tr1
3
10
100
Actual concentration [fmol/ul]
1000
Peptide 2
100
Intensity ratio
Intensity ratio
Peptide 2
2
1
0
tr1/tr2
tr3/tr2
10
1
0.1
1
10
100
Concentration
1000
1
10
100
Concentration
1000
Detection of interference
Interference is detected by comparing the ratio of the
intensity of pairs of transitions with the expected ratio and
finding outliers.
Transition i has interference if
z
threshold
z i
where Zthreshold is the interference detection threshold;
z  max z
i
j i
ji
 max
j i
r
ji
I
s
j
I
i
;
ji
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;
and
sji is the noise in the ratio.
Correction for interference in experimental data
1000
Peptide 1
100
10
line
1
Uncorrected
corrected
0.1
Measured concentration [fmol/ul]
Measured concentration [fmol/ul]
1000
Peptide 2
100
10
line
1
Uncorrected
corrected
0.1
1
10
100
Actual concentration [fmol/ul]
1000
1
10
100
Actual concentration [fmol/ul]
1000
Correction for interference in experimental data
1000
Peptide 1
100
10
line
1
Uncorrected
corrected
Measured concentration [fmol/ul]
Measured concentration [fmol/ul]
1000
100
0.1
10
line
1
Uncorrected
corrected
0.1
1
0.2
10
100
Actual concentration [fmol/ul]
1000
1
1000
Peptide
2
line
40
0.6
error
Relative
Relative error
0
line
-0.1
10
100
Actual concentration [fmol/ul]
0.8
50
Peptide 1
0.1
Relative error
Peptide 2
Uncorrected
Corrected
Uncorrected
Corrected
30
0.4
20
0.2
10
0
0
Uncorrected
Corrected
-0.2
-10
-0.2
1
10
100
Actual concentration [fmol/ul]
1000
11
10
100
Actual
Actual concentration [fmol/ul]
1000
1000
Proteomics Informatics Workshop
Part I: Protein Identification, February 4, 2011
Part II: Protein Characterization, February 18, 2011
Part III: Protein Quantitation, February 25, 2011