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Proteomics Informatics – Protein characterization I: post-translational modifications (Week 10)

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Proteomics Informatics – Protein characterization I: post-translational modifications  (Week 10). Post-translational modification. Biologically important post-translational modification ( phosphorylation , acetylation , glycosylation , etc.) - PowerPoint PPT Presentation

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Page 1: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Proteomics Informatics – Protein characterization I:

post-translational modifications (Week 10)

Page 2: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Post-translational modification

• Biologically important post-translational modification (phosphorylation, acetylation, glycosylation, etc.)

• Introduced on purpose during sample preparation (alkylation, iTRAQ, TMT etc.)

• Side-products of sample preparation (oxidation, deamidation, carbamylation, formylation etc.)

Page 3: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Post-translational modification

Mann and Jensen, Nature Biotech. 21, 255 (2003)

Page 4: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Unmodified pS18 pT5b y b y b y"--- 1 F --- --- 1 F --- --- 1 F ---261.1556 2 I 2163.024 261.1556 2 I 2243.024 261.1556 2 I 2243.024421.1862 3 C 2049.94 421.1862 3 C 2129.94 421.1862 3 C 2129.94520.2546 4 V 1889.909 520.2546 4 V 1969.909 520.2546 4 V 1969.909621.3022 5 T 1790.841 621.3022 5 T 1870.841 701.3022 5 T 1870.841718.3549 6 P 1689.793 718.3549 6 P 1769.793 798.3549 6 P 1689.793819.4025 7 T 1592.741 819.4025 7 T 1672.741 899.4025 7 T 1592.741920.4502 8 T 1491.693 920.4502 8 T 1571.693 1000.45 8 T 1491.6931080.481 9 C 1390.645 1080.481 9 C 1470.645 1160.481 9 C 1390.6451167.513 10 S 1230.615 1167.513 10 S 1310.615 1247.513 10 S 1230.6151281.556 11 N 1143.583 1281.556 11 N 1223.583 1361.556 11 N 1143.5831382.603 12 T 1029.54 1382.603 12 T 1109.54 1462.603 12 T 1029.541495.687 13 I 928.4923 1495.687 13 I 1008.492 1575.687 13 I 928.49231610.714 14 D 815.4083 1610.714 14 D 895.4083 1690.714 14 D 815.40831723.798 15 L 700.3814 1723.798 15 L 780.3814 1803.798 15 L 700.38141820.851 16 P 587.2974 1820.851 16 P 667.2974 1900.851 16 P 587.29741951.891 17 M 490.2447 1951.891 17 M 570.2446 2031.891 17 M 490.24472038.923 18 S 359.2042 2118.923 18 S 439.2042 2118.923 18 S 359.20422135.976 19 P 272.1722 2215.976 19 P 272.1722 2215.976 19 P 272.1722--- 20 R 175.1195 --- 20 R 175.1195 --- 20 R 175.1195

Phosphorylation examples

Page 5: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Potential modifications

Page 6: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Enrichment Strategies for the Detection of Phosphorylated Peptides

Page 7: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Enrichment Strategies for the Detection of Phosphorylated Peptides

• Hydrophilic Interaction Chromatography (HILIC)• Phosphopeptides elute later than their unphosphorylated

counterparts• Stationary phase is hydrophilic• Mobile phase is hydrophobic

Unphosphorylated

single phosphorylation

multiple phosphorylation

Page 8: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Time (min)

neutral peptides basic peptides

SCX

• Strong Cation Exchange Chromatography• Stationary phase is negatively charged• Mobile phase is a buffer that is increasing the pH (if peptide

becomes neutral it elutes)• Neutral peptides elute earlier: XXpSxxxxxR/K• Positive peptides elute late: XXXXHXXXXR/K

Enrichment Strategies for the Detection of Phosphorylated Peptides

Page 9: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Several Strategies are often combined

Page 10: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Loss of the phosphate group

Page 11: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25Number of fragment ions

Pro

babi

lity

of L

ocal

izat

ion

Phosphopeptide identification

mprecursor = 2000 DaDmprecursor = 1 DaDmfragment = 0.5 DaPhosphorylation

Localization of modifications

Page 12: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

Prob

abili

ty o

f Loc

aliz

atio

n

Number of fragment ions

ID3

Localization (dmin=3)

mprecursor = 2000 DaDmprecursor = 1 DaDmfragment = 0.5 DaPhosphorylation

dmin>=3 for 47% of human tryptic peptides

Localization of modifications

Page 13: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

Prob

abili

ty o

f Loc

aliz

atio

n

Number of fragment ions

ID32

Localization (dmin=2)

mprecursor = 2000 DaDmprecursor = 1 DaDmfragment = 0.5 DaPhosphorylation

dmin=2 for 33% of human tryptic peptides

Localization of modifications

Page 14: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

Prob

abili

ty o

f Loc

aliz

atio

n

Number of fragment ions

ID321

Localization (dmin=1)

mprecursor = 2000 DaDmprecursor = 1 DaDmfragment = 0.5 DaPhosphorylation

dmin=1 for 20% of human tryptic peptides

Localization of modifications

Page 15: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

0

0.2

0.4

0.6

0.8

1

1.2

0 5 10 15 20 25

Prob

abili

ty o

f Loc

aliz

atio

n

Number of fragment ions

ID3211*

Localization(d=1*)

mprecursor = 2000 DaDmprecursor = 1 DaDmfragment = 0.5 DaPhosphorylation

Localization of modifications

Page 16: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Peptide with two possible modification sites

Localization of modifications

Page 17: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Peptide with two possible modification sites

MS/MS spectrum

m/z

Inte

nsity

Localization of modifications

Page 18: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Peptide with two possible modification sites

MS/MS spectrum

m/z

Inte

nsity

Matching

Localization of modifications

Page 19: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Peptide with two possible modification sites

MS/MS spectrum

m/z

Inte

nsity

Matching

Which assignment doesthe data support?

1, 1 or 2, or 1 and 2?

Localization of modifications

Page 20: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

AAYYQK

Visualization of evidence for localization

AAYYQK

Page 21: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Visualization of evidence for localization

AAYYQK

AAYYQK

Page 22: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Visualization of evidence for localization

3

2

1

3

2

1

Page 23: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Estimation of global false localization rate using decoy sites

By counting how many times the phosphorylation is localized to amino acids that can not be phosphorylated we can estimate the false localization rate as a function of amino acid frequency.

0

0.005

0.01

0.015

0.02

0 0.05 0.1 0.15

0

0.005

0.01

0.015

0.02

0 0.05 0.1 0.15

Amino acid frequency

Fals

e lo

caliz

atio

n fr

eque

ncy

Y

Page 24: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

S21

Sm1

How much can we trust a single localization assignment?

If we can generate the distribution of scores for assignment 1 when 2 is the correct assignment, it is possible to estimate the probability of obtaining a certain score by chance for a given peptide sequence and MS/MS spectrum assignment.

SS mm21

0

2

1

21

2

0

2

1

21

2

2

1

1

dSSFdSSFp

S m

)(

)(

1.

2.

Page 25: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Is it a mixture or not?If we can generate the distribution of scores for assignment 2 when 1 is the correct assignment, it is possible to estimate the probability of obtaining a certain score by chance for a given peptide sequence and MS/MS spectrum assignment.

S12

Sm2

SS mm21

0

12

12

1

0

12

12

11

2)(

)(2

dSSF

dSSFp

Sm

1.

2.

Page 26: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

ppppthth

and1

2

2

1 1 and 2 pppp

ththand

1

2

2

1 1 pppp

ththand

1

2

2

1

ppppthth

and1

2

2

1 1 or 2Ø )( ppSS mm

1

2

2

121

Peptide with two possible modification sites

MS/MS spectrum

m/zIn

tens

ity

Matching

Which assignment doesthe data support?

1, 1 or 2, or 1 and 2?

Localization of modifications

Page 27: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Top down / bottom up

Top down

Bottom up

mass/charge

inte

nsity

Page 28: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Top down Bottom up

Charge distribution

mass/chargein

tens

itymass/charge

inte

nsity

1+

2+

3+

4+

27+

31+

Page 29: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Top down Bottom upm = 1035 Da m = 1878 Da m = 2234 Da

Isotope distribution

mass/chargein

tens

itymass/charge

inte

nsity

Page 30: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Fragmentation

Top down Bottom up

Fragmentation

Page 31: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Alternative Splicing

Top down

Bottom up

Exon 1 2 3

Page 32: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Correlations between modifications

Top down

Bottom up

Page 33: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

The Nucleosome Core Complex

H3

H4

H2A

H2B

H3 ‘tail’

Luger et al., Nature, 389, 251-260, 1997

Page 34: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

The N-terminal Tails of Histone H3 and H4

Methylation: mono-, di-, or trimethylation

Acetylation

Phosphorylation

Ac

H3 1-ARTKQTARKSTGGKAPRKQLATKAARKSAPATGGVKKPHRYRPTVALRE-50

M MMMM

PM Ac

M Ac M Ac PPP

M P

H4 1-SGRGKGGKGLGKGGAKRHRKVLRDNIQGITKPAIRRLARRGGVKRISGLIYE-52

MM Ac AcAc Ac AcP

Ac

M

Ac

P

Page 35: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Specific post translational modifications (PTMs) of the N-terminal tails of histones function as a scaffold for binding of protein factors leading to transcriptional activation or inactivation. Jenuwein, T., Allis, C.D., Science, 293, 2001

The Histone Code Hypothesis

Page 36: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Ac

KSTGGKAPR 9-17

TKQTAR 3-8

KQLATKAAR 18-26

KSAPATGGVKKPHR 27-40

41-50 YRPTVALRE

M

Ac

Ac

Ac

H3 1-ARTKQTARKSTGGKAPRKQLATKAARKSAPATGGVKKPHRYRPTVALRE-50

MP

M

PPP

P

Interdependence of Modifications is lost in Standard Mass Spectrometry Analysis

Ac

AcAc

M AcM M M MM

M

M

P

M

M

Page 37: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Histone Proteins are a Highly Complex Mixture of a Single Protein….

ARTKQTARKSTGAKAPRKQLASKAARKSAPATGGIKKPHRFRPGTVALRE

ARTKQTARKSTGAKAPRKQLASKAARKSAPATGGIKKPHRFRPGTVALRE

ARTKQTARKSTGAKAPRKQLASKAARKSAPATGGIKKPHRFRPGTVALRE

ARTKQTARKSTGAKAPRKQLASKAARKSAPATGGIKKPHRFRPGTVALRE

ARTKQTARKSTGAKAPRKQLASKAARKSAPATGGIKKPHRFRPGTVALRE

ARTKQTARKSTGAKAPRKQLASKAARKSAPATGGIKKPHRFRPGTVALRE

M

MM

MM

Ac

MM M M

AcM

MMMM

……………… and many many more!

M MMM

Page 38: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Protocol

• Isolate m/z ± 0.5 Da• 60 ms ETD• ~ 3 min acquisition

Glu-C generated N-terminal H3 peptide (1-50)

m/z

245.2

346.3

982.5502.4

824.5

892.5

630.5 731.5

1647.9672.3 1055.6288.1 571.3

802.5479.9

958.6 1715.01216.7401.8 1784.1

1129.61878.21515.41255.2

1373.8 1424.81937.81616.0

LTQ-FTMSLTQ-ETD/PTR

4 9 14 18 23 27 36N 50

37

m/z

+10+11

+9+8

+7+12

m/z

+ 10 charge states

D 1.4 DaD 1.4 Da

D 1.4 Da

546.3547.6

549.1

550.4551.9

544.9

Page 39: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Group ‘4’: 4 Acetyl Groups

c6

400 8000

100R

elat

ive

Abu

ndan

cec2 c3

c4

c5

z2z3

z4z5

z6

z7

****

* * *

1200 1600 2000m/z

c9

c13

c7 c8c10

c11c12

c16c17

z9

z10 z11 z12

z14 z15

*

**

*

*

***

*

***

*

*

**

z16

A R T K Q T A R K S T G A K A P R K Q L A S K A A R K S A P A T G G I K K P H R F R P G T V A L R E

A R T K Q T A R K S T G A K A P R K Q L A S K A A R K S A P A T G G I K K P H R F R P G T V A L R E

A R T K Q T A R K S T G A K A P R K Q L A S K A A R K S A P A T G G I K K P H R F R P G T V A L R E

MM

MMM

M

MMM

Ac Ac AcAc

Ac Ac AcAc

Ac Ac AcAc

Page 40: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Group ‘5’: 5 Acetyl Groups

400 600 800 1000 1200 1400 1600 1800 2000

m/z

0

100

Rel

ativ

e A

bund

ance

K4: trimethylc3

c4

c5

c9c13

c6

c7

c8c10

c11

c12 c16z2

z3

z4z5

z6z7

z9

z10

z11 z12 z14

z15

**

*

*

** *

*

**

* * **

c2

** c14

z16z17 c17

A R T K Q T A R K S T G A K A P R K Q L A S K A A R K S A P A T G G I K K P H R F R P G T V A L R E

AcAcAcAc AcM

MM

Page 41: Proteomics Informatics –  Protein characterization I:  post-translational modifications  (Week 10)

Proteomics Informatics – Protein characterization I:

post-translational modifications (Week 10)