proteomics informatics workshop part iii: protein quantitation david fenyö february 25, 2011

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 )(


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//


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


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


pppp M

j

L

j

M

j

L

j iiii mmnn

HL

Fractionation

Digestion

LC-MS

Lysis

MS

Light

RecombinantProteins (Heavy)

Quantitation – Labeled Proteins


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


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


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



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


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

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



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]


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]


line

Uncorrected

corrected

0.1

1

10

100

1000

1 10 100 1000

Mea

sure

d co

ncen

tratio

n [fm

ol/u

l]


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


line

Uncorrected

Corrected

0.1

1

10

100

1000

1 10 100 1000

Mea

sure

d co

ncen

tratio

n [fm

ol/u

l]


line

Uncorrected

corrected

0.1

1

10

100

1000

1 10 100 1000

Mea

sure

d co

ncen

tratio

n [fm

ol/u

l]


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


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


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

proteomics informatics workshop part iii: protein quantitation david fenyö february 25, 2011

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