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

56
Proteomics Informatics Worksho 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

Upload: thomasine-dickerson

Post on 23-Dec-2015

214 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 2: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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?

Page 3: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 4: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Fractionation

Digestion

LC-MS

Lysis

Quantitation – Label-Free (Standard Curve)

MS

IIC ikik

k

ijf )(

Sample i Protein jPeptide k

Page 5: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Fractionation

Digestion

LC-MS

Lysis

Quantitation – Label-Free (MS)

MS MS

ppppppMS

ik

LC

ik

Pep

ik

D

ijkij

L

ijk

Pr

Assumption:

constant for all samples

IICC jjjj iiii mnmn//

Sample i Protein jPeptide k

Page 6: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

CL

jin

IL

kin

CH

jim

pM

jinpM

jim

IH

kim

Assumption: All losses after mixing are identical for the heavy and light isotopes and

ppM

j

M

j ii mn

Sample i Protein jPeptide k

Page 7: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Comparison of metabolic labeling and label-free quantitation

-1 -0.5 0 0.5 1log2(ratio)

SILAC

Label-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

ppppppMS

ik

LC

ik

Pep

ik

D

ijkij

L

ijk

Pr

pM

ij

Page 8: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 9: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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)

SILAC

Label-Free

Metabolic

Page 10: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Tackett et al. JPR 2005

Protein Complexes – specific/non-specific binding

Page 11: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

)()()(

)()()(

0CCC

CKKdC

H

j

H

j

L

j

H

jTC

H

j

tt

tdt

t

LightNewly produced proteins will have

light label

eCC tH

j

H

jKKt TC

)()()( 0

)log()())(

)()(log( 2

11

ttIII

TC

H

j

L

j

H

j tt

tt

Page 12: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Super-SILAC

Geiger et al., Nature Methods 2010

Page 13: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 14: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 15: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 16: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 17: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

pppppM

sk

M

k

D

jkj

L

j iiii nnnn

Pr

Anderson, N.L., et al. Proteomics 3 (2004) 235-44

Page 18: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Fractionation

Digestion

LC-MS

Lysis

MS/MSMSMSMS/MS

Quantitation – Label-Free (MS/MS)

SRM/MRM

Page 19: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

MS/MS

SyntheticPeptides(Heavy)

SyntheticPeptides(Heavy)

Light

HL

MSH

LMS

MS/MSMS/MSMS/MSL LH H

Digestion

LC-MS

Lysis/Fractionation

Quantitation – Labeled Synthetic Peptides

Page 20: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Fractionation

Digestion

LC-MS

Light Heavy

Lysis

LHMS MS/MS

Quantitation – Isobaric Peptide Labeling

Ross et al. MCP 3 (2004) 1154

Page 21: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

LHMS MS/MS

Quantitation –Isobaric Peptide Labeling

Fractionation

Digestion

LC-MS

Lysis

Quantitation – Label-Free (Standard Curve)

MS

Page 22: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

m = 1035 Da m = 1878 Da m = 2234 Da

Isotope distributions

m/z m/z m/z

Inte

nsi

ty

Page 23: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Peak Finding

m/z

Inte

ns

ity

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

Page 24: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Background subtraction

m/z

Inte

ns

ity

Page 25: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Estimating peptide quantity

Peak heightCurve fittingPeak area

Peak heightCurve fitting

m/z

Inte

ns

ity

Page 26: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Time dimension

m/z

Inte

ns

ity

Tim

e

m/z

Tim

e

Page 27: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Sampling

Retention Time

Inte

nsi

ty

Page 28: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 29: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

0.5

0.6

0.7

0.8

0.9

1

1.1

1 2 3 4 5 6 7 8 9 10

Th

res

ho

lds

(90

%)

# of points

Sampling

Page 30: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Estimating peptide quantity by spectrum counting

m/z

Tim

eLiu et al., Anal. Chem. 2004, 76, 4193

Page 31: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 32: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Examples - qTOF

Page 33: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Examples - Orbitrap

Page 34: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Examples - Orbitrap

Page 35: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Isotope distributions

Peptide mass

Inte

nsi

ty r

atio

Peptide mass

Inte

nsi

ty r

atio

Page 36: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

AADDTWEPFASGK

Inte

nsi

tyIn

ten

sity

Inte

nsi

ty

Time

Page 37: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

AADDTWEPFASGK

Inte

nsi

tyIn

ten

sity

Inte

nsi

ty

0

1

20

1

2

Rat

ioR

atio

0

1

20

1

2

Time

Page 38: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

AADDTWEPFASGK

Inte

nsi

tyIn

ten

sity

Inte

nsi

tym

/zm

/zm

/z

G

H

I

Page 39: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

YVLTQPPSVSVAPGQTAR

TimeIn

ten

sity

Inte

nsi

tyIn

ten

sity

Page 40: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

YVLTQPPSVSVAPGQTAR

Inte

nsi

tyIn

ten

sity

Inte

nsi

ty

0

1

20

1

2R

atio

Rat

io

0

1

20

1

2

Time

Page 41: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

YVLTQPPSVSVAPGQTAR

Inte

nsi

tyIn

ten

sity

Inte

nsi

tym

/zm

/zm

/z

Page 42: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Retention Time Alignment

Page 43: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Mass Calibration

Cox & Mann, Nat. Biotech. 2008

Page 44: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

The accuracy of quantitation is dependent on the signal strength

Cox & Mann, Nat. Biotech. 2008

Page 45: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

Page 46: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Biomarker discovery

Fractionation

Digestion

LC-MS

Lysis

MS MS

Page 47: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Reproducibility

Paulovich et al., MCP 2010

Page 48: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

MS/MS

SyntheticPeptides(Heavy)

SyntheticPeptides(Heavy)

Light

HL

MSH

LMS

MS/MSMS/MSMS/MSL LH H

Digestion

LC-MS

Lysis/Fractionation

Biomarker verification

Page 49: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Addona et al., Nat. Biotech. 2009

Reproducibility

CPTAC 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

Page 50: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Reproducibility

Addona et al., Nat. Biotech. 2009

Page 51: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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.

Page 52: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Ratios of intensities of transitions

0

1

2

3

4

1 10 100 1000

Inte

ns

ity

rati

o

Concentration

tr2/tr1tr3/tr1

0.1

1

10

100

1000

1 10 100 1000

Me

as

ure

d c

on

cen

tra

tio

n [f

mo

l/ul]

Actual concentration [fmol/ul]

linetr1tr2tr3

0.1

1

10

100

1 10 100 1000

Inte

ns

ity

rati

o

Concentration

tr1/tr2tr3/tr2

0.1

1

10

100

1000

1 10 100 1000

Me

as

ure

d c

on

cen

tra

tio

n [f

mo

l/ul]

Actual concentration [fmol/ul]

linetr1tr2tr3

Peptide 1 Peptide 2

Peptide 1 Peptide 2

Page 53: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

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

where 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; and

sji is the noise in the ratio.

zz ithreshold

ji

ijji

ijji

iji

IIrzz

maxmax

Page 54: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

0.1

1

10

100

1000

1 10 100 1000

Me

as

ure

d c

on

cen

tra

tio

n [f

mo

l/ul]

Actual concentration [fmol/ul]

line

Uncorrected

corrected

0.1

1

10

100

1000

1 10 100 1000

Me

as

ure

d c

on

cen

tra

tio

n [f

mo

l/ul]

Actual concentration [fmol/ul]

line

Uncorrected

corrected

Correction for interference in experimental data

Peptide 1 Peptide 2

Page 55: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

-10

0

10

20

30

40

50

1 10 100 1000

Re

lati

ve e

rro

r

Actual concentration [fmol/ul]

line

Uncorrected

Corrected

0.1

1

10

100

1000

1 10 100 1000

Me

as

ure

d c

on

cen

tra

tio

n [f

mo

l/ul]

Actual concentration [fmol/ul]

line

Uncorrected

corrected

0.1

1

10

100

1000

1 10 100 1000

Me

as

ure

d c

on

cen

tra

tio

n [f

mo

l/ul]

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

Re

lati

ve e

rro

r

Actual concentration [fmol/ul]

line

Uncorrected

Corrected

Peptide 1

-0.2

0

0.2

0.4

0.6

0.8

1 10 100 1000

Re

lati

ve e

rro

r

Actual concentration [fmol/ul]

UncorrectedCorrected

Peptide 2

Page 56: Proteomics Informatics Workshop Part III: Protein Quantitation David Fenyö February 25, 2011 Metabolic labeling – SILAC Chemical labeling Label-free quantitation

Proteomics Informatics Workshop

Part I: Protein Identification, February 4, 2011

Part II: Protein Characterization, February 18, 2011

Part III: Protein Quantitation, February 25, 2011