peptide / protein quantification - university of minnesota · text from thermo site:\爀屲in june...

$: Peptide / Protein Quantification - University of Minnesota · Text from Thermo site:\爀屲In June 2003, Dr. Steve Gygi and his team presented an innovative strategy, Protein AQUA,$
Center for Mass Spectrometry and Proteomics | Phone | (612)625-2280 | (612)625-2279

Peptide / Protein Quantification


Outline

• MS Quantification • Why variance matters • Label-free / normalization • Labelled

– iTRAQ

• Peptides to proteins

Terminology

• Absolute Quantification • Relative Quantification • Bias • Variability / Variance • Label-free • Normalization • Labelled • iTRAQ • Isobaric • Reporter ions


Peptide / Protein Quantification

• Absolute – Estimate the molar amount of protein / peptide in the biological sample – PTMs – Validation

• Relative –Fold change / statistically significant difference between 2 biological states – Biological variation – Biomarker studies


Label-free

• Area Under Curve – MS1 – Integrate XIC

• Spectral Counting – MS2 – High abundant proteins

Käll L, Vitek O (2011) Computational Mass Spectrometry–Based Proteomics. PLoS Comput Biol 7(12): e1002277. doi:10.1371/journal.pcbi.1002277

MS1 AUC


y = f(x)

Area = ∫ 𝑓𝑓(𝑥𝑥)𝑏𝑏𝑎𝑎

XIC for m/z = 421.76

Patient Group A Patient Group B

Prepare Samples

Peptides

Preprocess

Quantify Identify

Analyze Statistically

MS1 & MS2

Spectra

Differentially Abundant

Peptides/Proteins

HPLC-MS/MS

Population Biological

Sample Handling

Instrument

Sources of Bias and Variability

Typical Discovery Experiment



MS Quantification

• MS not inherently quantitative • Physiochemical properties invoke different MS

responses • MS only samples a small percentage of total peptides • Bias and variability

Population Biological

Sample Handling

Instrument


Why Variance Matters


Normalization

• Remove bias and variability between runs • Global – commonly used

– Median scale – Total ion current (TIC)

• Local – very recent development – Proximity-based intensity normalization (PIN)


Labeled Quantification

• Run samples simultaneously on in a single run • Add label to samples • Mix samples together • Compute ratios / statistically significant diffs.


Labeled

• Isobaric – MS2, iTRAQ – Number of samples

• Synthetic Peptides – MS1 – Absolute (AQUA)

• Metabolic – MS1, SILAC – Not higher life forms

Käll L, Vitek O (2011) Computational Mass Spectrometry–Based Proteomics. PLoS Comput Biol 7(12): e1002277. doi:10.1371/journal.pcbi.1002277

Presenter

Presentation Notes

Text from Thermo site: In June 2003, Dr. Steve Gygi and his team presented an innovative strategy, Protein AQUA, enabling absolute protein quantitation using stable isotope labeled peptides and HPLC-MS. By applying a common principle, the use of a labeled molecule as an internal standard, to protein analysis, Gygi’s team has advanced the abilities of protein researchers to study complex biological samples quantitatively and has provided a valuable new tool for Proteomics. An AQUA Peptide is simply a synthetic tryptic peptide corresponding to a peptide of interest. Each AQUA peptide incorporates one stable isotope labeled amino acid, creating a slight increase (6-10 daltons) in molecular weight. When mixed, the native peptide and the synthetic AQUA Peptide elute together chromatographically, migrate together electrophoreticly, and ionize with the same intensity. However, by mass spectrometry, the native peptide and the synthetic AQUA Peptide are easily distinguished. In a typical AQUA experiment, a known amount of AQUA Peptide is added to a biological protein sample. The sample is then digested and analyzed by HPLC-MS. Extracted ion chromatograms are generated for the native peptide and the synthetic AQUA Peptide internal standard. Using peak ratios, the quantity of native peptide is calculated. Protein-AQUA is a powerful, enabling technology, the limits of which are only now being explored. For proteomics researchers, it facilitates focused, quantitative studies of not only specific protein expression, but specific amino acid modification as well.

www.moffitt.org


Isobaric Example - iTRAQ

Isobaric Tag Total mass = 305

Reporter Group 113 –119, 121 m/z

Balance Group (?) Mass 184, 186 – 192 m/z

Amine specific peptide reactive group (NHS) N-hydroxysuccinimide O

N

O

ON

N~~~~~~~

N+

N

N+

N

13CH2

15N+

N

13CH2

13CH2

13CH215N+

N

13CH2

13CH2

13CH215N+

15N

13CH3

13CH2

13CH215N+

15N

13CH2

13CH3

13CH2

13CH215N+

N

13CH2

13CH215N+

13CH2

13CH2

15N

13CH2

13CH3

113 114 115 116

117 118 119 121

Applied Biosystems has granted permission to use this slide.

Isob

aric

Rep

orte

r Gro

ups

113

–119

, 121

m/z

iTRAQ® 8-Plex Reagent Chemical Structure


Presenter

Presentation Notes

113:

Reduce, alkylate Cysteines

Trypsin Digest


Trypsin Digest


Trypsin Digest


Trypsin Digest

Proteolytic Digestion

iTRAQ TAG 114

iTRAQ TAG 115

iTRAQ TAG 116

iTRAQ TAG 117

Label peptides with iTRAQ® Reagents

Tissue Images: Rosas HD et al, (2002) Neurology, 58, 695

MIX

2D LC-MS/MS

Normal Brain Tissue-1

Normal Brain Tissue-2

Obtain protein-containing sample, extract protein

Huntington’s Disease-1

Huntington’s Disease-2

iTRAQ Experiment


50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900m/z, amu

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

216.2255.1

145.1

428.3

114.1

244.2 782.5513.3

400.2117.1175.1

315.2

598.4499.3185.1212.1

881.6711.4272.2

70.1383.386.1 527.4

199.1 343.2 412.3230.2 326.2 440.3

a1

b1

I

b2

y8

a3

b3

y7

I

a4

b4

y6

I

a5y5

I

y4

y3

y2I

y1

y9(+2)

y9

Inte

nsity

, cou

nts

Peptide = VAIVVGAPRMW = 1024.6249Protein ID = platelet membrane

glycoprotein 11b

“Reporter Ion Mass Tags” from which quantitation is calculated

Peptide iTQVAIVVGAPR MWmono 1024.62 Protein Match Platelet

membrane glycoprotein 11b

Peptide match is made from product ions, e.g., b- and y-ion series

iTRAQ Experiment MS2 Spectrum


Presenter

Presentation Notes

Peptide Tandem Mass Spectrum of iTRAQ®-labeled Peptide Peptide originates from all samples processed in experiment since chemical tag is isobaric

112.72493 113.91559 115.10626 116.29692 117.48759 118.67826

Mass (m/z)

976.9

0

10

20

30

40

50

60

70

80

90

100

% In

tens

ity

115.13

114.13 116.13 117.13

113.11No change disease:control

control disease

iTRAQ Results

• Reporter ion intensities reflect relative peptide amounts


112.74415 113.88269 115.02123 116.15977 117.29831 118.43685

Mass (m/z)

1.1E +4

0

10

20

30

40

50

60

70

80

90

100

% Int

ensit

y

116.14117.14

115.14

114.14

113.12

112.52129 113.84865 115.17602 116.50338 117.83075 119.15811

Mass (m/z)

3070.1

0

10

20

30

40

50

60

70

80

90

100

% Int

ensit

y

115.12

114.12

116.12117.12

113.11

control

control disease

disease

Increase disease:control

Decrease disease:control

iTRAQ Results • What fold changes are significant?

• Do they represent biological relevance as opposed to

experimental variability?



From Käll L, Vitek O (2011) Computational Mass Spectrometry–Based Proteomics. PLoS Comput Biol 7(12): e1002277. doi:10.1371/journal.pcbi.1002277

Labe

led

& L

abel

-free


From Peptides to Proteins

Lu, et al., Nature Biotechnology 25, 117 - 124 (2007)

APEX

peptide / protein quantification - university of minnesota · text from thermo site:\爀屲in june...

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