Talk-InnoMol-Macek

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MaxQuant Summer School

Martinsried, June 26, 2013

Sample preparation and measurement strategies in phosphoproteomics

Boris Maček

Proteome Center Tübingen

1

Central „dogma“ of molecular biology

Genome Transcriptome Proteome

Phosphorylation

Glycosylation

Disulfide bonds

Proteolysis

Acetylation

Methylation

Sulfation

Ubiquitination

GPI Anchor etc...

2

Most (if not all) proteins are modified

Regulatory modifications are dynamic:

• kinase/phosphatase

• acetyltransferase/deacetylase

• ubiquitin ligase/deubiquinating enzyme

• glyosyltransferase/deglycosidase

3

Figure 3-64 Molecular Biology of the Cell (© Garland Science 2008)

MS-based proteomics

Aebersold R and Mann M. 2003. Nature 422: 198-207

4

PTMs analyzed in large scale by MS

Choudhary and Mann. 2010. Nature Rev Mol Cell Biol. 11:427

5

Largest phosphoproteomes reported so far

Choudhary and Mann. 2010. Nature Rev Mol Cell Biol. 11:427

6

Gel-free phosphoproteomics workflow

Antibodies:

4G10 pY20, pY99, pY100

7

1st stage of enrichment:

Strong Cation Exchange (SCX) chromatography

Beausoleil et al. 2004. PNAS 101(33): 12130-12135

8

1st stage of enrichment:

Strong Cation Exchange (SCX) chromatography

9

2nd stage of enrichment:

IMAC or TiO

2 chromatography

10

Quantification of PTMs

Unmodified peptide

(change in protein level)

Modified peptide

(change in modification level)

No change

Upregulation

Downregulation

11

Quantification of PTMs

Unmodified peptide

(change in protein level)

Modified peptide

(change in modification level)

No change

Downregulation

(position?)

12

Intracellular signaling networks:

EGFR Signaling Pathway

13

Global phosphorylation dynamics

Main conclusions:

The EGF induced phosphorylation signal spreads to many different protein classes within 20 min of stimulation

6600 phosphorylation-sites from more than 2000 proteins pS (87%) /pT (12%) /pY (1.5%)

→ www.phosida.com

Less than 15% regulated by EGF treatment

Global understanding of how the cell works

- Systems biology modelling of signaling networks

Generic approach – can be applied to study any phosphorylation dependent signal network

14

Olsen et al., Cell 2006, Volume 127, Issue 3 , p. 635-648

Detection of kinase substrate candidates

• targets of Aurora kinase in S. pombe (with S. Hauf, FMI/MPI)

• Koch et al. 2011. Science Signaling 4 (179):rs6

• targets of Polo and Fin1 in S. pombe

(with I. Hagan, Paterson Institute)

• targets of protein kinase D in human cells (with A. Hausser, Uni Stuttgart)

• Franz-Wachtel et al. 2012. MCP

• targets of S/T kinases and phosphatases in model bacteria

Detection of kinase substrates:

Kinase inactivation

Control cells

WB

Kinase Inactivation

WB

Adapted from Kettenbach et al. Science Signaling 2011, Vol 4 Issue 179 rs5

Kinase inactivation:

1) By chemical inhibition

2) By overexpession of inactive kinase („dominant-negative“ mutant)

3) By gene modification (analog-sensitive kinases)

4) By gene knockout ( only non-essential kinases!

)

Detection of kinase substrates

”normal AA”

Lys12 C

6

14 N

2

”heavy AA” (+8Da)

Lys13 C

6

15 N

2

Kinase Inactivation

Control cells

Combine and lyse

GeLC-MS

(15 slices)

Proteolysis

(Lys-C)

SCX

TiO

2 nanoLC-MS/MS

Dominant–negative kinase mutants

• overexpression of inactive kinase → suppression of endogenous kinase activity

(also called „kinase-dead“ strains)

• problem: some endogenous kinase activity remains

Example: Receptor Tyrosine Kinases

Figure 15-53, 15-54 Molecular Biology of the Cell (© Garland Science 2008)

Construction of analog-sensitive (as) kinases

• „gatekeeper“ amino acid in the ATP-binding pocket is removed

• the ATP-binding pocket can fit an ATP analog or and inhibitor

• specific inhibition!

Example 1: Use of analog-sensitive kinases

Detection of Aurora kinase targets in S. pombe (with S. Hauf, FMI/MPI)

Major mitotic kinases

Adapted from: Alexander et al. 2011. Science Signaling Vol 4 Issue 179 ra42

Aurora kinase family

Mammals

Aurora A

A. thaliana

Aurora B

AtAur1

AtAur2

AtAur3

Aurora C

X. laevis

EG2

D. melanog.

Aurora

C. elegans

AIR-1

S. cerevisiae S. pombe

AIRK2 IAL AIR-2 Ipl1 Ark1

Yeast Aurora or metazoan Aurora B functions and substrates

Regulation of kinetochoremicrotubule attachment

Compaction of chromosomes

Spindle assembly checkpoint

P

P

P

P

P

P

P

P

P

P

P

P

P

Known substrates:

 Histone H3 (Ser 10 )

 Outer kinetochore proteins:

Ndc80/Hec1, Dsn1, KNL1

Dam1/DASH complex

MCAK

 Condensin

 Other substrates?

G2

Replicates and Control

Exp. 1: Aurora inhibition Exp. 2: Aurora inhibition

+ microtubule drug

Exp. 3: Inhibitor side effects

G2 arrest ( cdc25ts )

Aurora-as Aurora-as wild type Aurora

M

+ microtubule drug

Quantitation Results: Phosphoproteome

Exp. 1 + 2:

Aurora inhibition quantified: 4877

Exp. 3:

Inhibitor side effects quantified: 5428

-6 -4 -2 0 log

2

(H/L)

2 4 6 -6 -4 -2 0 log

2

(H/L)

2 4 6

Quantitation Results: Proteome

Classification of downregulated P-sites

-

-1

0

1

Class

Class 1

Class 2

Class 3

Class 4

Exp1

-1

-

-1

-1

-1

0

1

-1

-

-1

-1

-1

0

= downregulated

= 1:1

= upregulated

= not detected

Exp2

-1

-1

-

0

1

-1

-1

-1

-1

-

0

1

-1

Exp3

0

0

0

0

0

0

0

-

-

-

-

-

counts

45

10

15

42

1

45

1

1

9

16

11

2

3

P-sites proteins

45 24

25 23

89

42

65

33

Known substrates identified

P

P

P

P

P

P

P

P

P

P

P

P

P

 Histone H3

 Outer kinetochore proteins:

 Condensin

Refinement of Aurora kinase target sequence

Currently accepted target sequences:

[RK]-X-[ST]-[ILV] ( S. serevisiae )

[RKN]-R-X-[ST]-[ILVM] (human Aurora-A)

R-X-[ST] R-K-R-X-[ST]

R-X-[ST]

Novel Aurora kinase substrates in S. pombe

Novel functions of Aurora kinase

P

Regulation of kinetochoremicrotubule attachment

Compaction of chromosomes

Spindle assembly checkpoint

P

P

P

P

P

P

P

P

P

P

P

P

P

P

P

‘Clearing’ of chromatin, facilitating segregation

Modulation of

DNA damage response

Inheritance of heterochromatin, preserving differentiated state

Setting DNA replication pattern

Example 2: Use of dominant-negative kinase mutants

Detection of PKD targets in HEK 293 cells (with A. Hausser, Uni Stuttgart)

Detection of PKD1 substrate candidates

PKD1: cytosolic serine/threonine-protein kinase

• converts DAG signals into prolonged physiological effects downstream of PKC

• regulation of MAPK8/JNK1 and Ras signaling

• Golgi membrane integrity and trafficking

• cell survival through NF-kappa-B activation

• cell differentiation by mediating HDAC7 nuclear export

• cell proliferation via MAPK1/3 (ERK1/2) signaling

From: Fu and Rubin. 2011. EMBO Reports 12(8): 785-796.

Detection of PKD substrate candidates

PKD-dependent phosphorylation events

PKD motif among significantly regulated sites

Reproducibility

Kinase of interest must be active during experiment

[PKDca/PKDkd] Noco+ [parental/PKDkd] Noco+

Importance of normalization by protein ratio

[PKDca/PKDkd] Noco+ [parental/PKDkd] Noco+

Overexpressed PKDkd

Enrichment of PKD target sequence term membrane organization

Golgi apparatus integral to membrane nuclear membrane steroid metabolic process tubulin binding

PH domain membrane invagination intrinsic to membrane cell proliferation p

Enrichment of GO terms

0,000908619

0,00115072

0,001261707

0,001448047

0,002471298

0,003442023

0,005346906

0,00732811

0,007833636

0,008644158 p.adj

direction m

0,039459278 enrichment

0,039459278 enrichment

0,039459278 enrichment

0,039459278 enrichment

0,053874297 enrichment

0,062530078 enrichment

0,083258961 enrichment

0,094221322 enrichment

0,094221322 enrichment

0,094221322 enrichment

39

42

87

50

64

151

725

51

715

52 x

28

5

5

5

7

5

7

11

31

6

N

5851

5851

5851

5851

5851

5851

5851

5851

5851

5851 k Category proteins

Refinement of PKD target sequence

Currently accepted target sequence:

[LVI]-X-[RK]-X-X-[ST]

[LV]-K-K-K-L-[ST]

Depletion of Pro!

X-X-K-X-X-[ST]

Acknowledgements

Proteome Center Tuebingen

Karsten Krug

Mirita Franz-Wachtel

Silke Wahl

University of Stuttgart

Angelika Hausser

Stephan Eisler

Friedrich Miescher Laboratory

Silke Hauf

Andre Koch

Funding

41

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