Expression Proteomics: principles and examples of application

Miguel Teixeira

IBB – Institute for Biotechnology and Bioengineering, Centro de Eng. Biológica e Química, IST

Functional Genomics and Bioinformatics

IEF SDS - PAGE

Sample

application

Application of the IPG strip on

top of the SDS –

polyacrylamide gel

1

0

pH pH10

103 103

Previous class – 2D electrophoresis

SDS – polyacrylamide

gel

pH

SDS – polyacrylamide

gelImmobilized pH gradient

pH MM

3 3

1. Incubation of a cell culture under

the stress conditions of the study

2. Fractionation of the

proteome

3. Solubilization of proteins in

IEF buffer

4. 1st Dimension: IEF

5. 2nd Dimension: SDS-PAGE

1.

Control Stress

2.

pH3 10pH3 10

3.

4.

5.

6. Staining of proteins

7. Identification of proteins whose

relative abundance varies

9. Data analysis aiming the identification of

the cell adaptation mechanisms to the

studied agression

5.

6.

7.

9.

8. Protein identification – peptide

mass fingerprinting

2D based proteomics limitations

� Time-consuming (2-5 days)

� Limited number and type of proteins separated in each

gel

� the whole proteome is too complex to separate in a single gel� the whole proteome is too complex to separate in a single gel

� it is difficult to separate proteins with extreme pIs or MWs

� low-copy proteins are hard to detect and identify

� spot matching is difficult in dense areas of the gel, compromising

reliability

�integral membrane proteins cannot be resolved in 2D gels

2-D ZOOMING

3 10

4 7Pre-fractionation of protein mixtures

1. Low abundant protein analysis

Overcomming some of the 2D based proteomics limitations

4.5 5.5

Soluble fraction Membrane fraction

DIGE technology

DIfferential Gel Electrophoresis

1. Low abundant protein analysis2. Spot matching reliability

Overcomming some of the 2D based proteomics limitations

Practical Approach to DIGE

Amersham Pharmacia Biotech, Life Science News, 7, 2001

DIGE technology

DIfferential Gel Electrophoresis

ADVANTAGES:

•Uses an internal standard on every gel

•Detect an increased number of real differences in abundance

•Identify even the smallest differences

•Guarantee statistical confidence

•Eliminate gel-to-gel variation

Why would we use proteomics when we can use

transcriptomics?

• protein concentrations are not necessarily proportional to mRNA concentration• protein concentrations are not necessarily proportional to mRNA concentration

• protein functions are many times controlled at the level of post-translational modifications,

sub-celular localization, interactions with co-factors or other proteins

phosphorilation

glycosilation

Studying proteome-wide post-translational modifications using 2-D

electrophoresis

Pro-Q-Diamond

Pro-Q_Emerald

Importance of the phosphoproteome

Redox Proteomics

Carbonyl groups

• After 2D SDS-PAGE, proteins are transfered to nitrocellulose membranes

• Carbonylated proteins are labelled with dinitrophenol-hydrazine (DNP)

• anti-DNP detection

Thiol groups

• Free thiol groups are radiolabelled with 35[S] compounds or chemically labelled with

maleimides

• After 2D SDS-PAGE, proteins are visualized through autoradiograms

• After 2D SDS-PAGE, western blotting and anti-maleimide immunodetection.

Protein ubiquitination

• Antibodies against ubiquitin or polyubiquitin are used upon 2D SDS-PAGE + western

blotting

• Extremely important in human diseases such as:

� Asthma;

� Cardiovascular disease (ischaemia and reperfusion);

Redox Proteomics

� Cardiovascular disease (ischaemia and reperfusion);

� Diabetes;

� Cirrhosis;

� Alzheimer's, etc..

2D Gel

DNPH – labelled

sample

Western blot

Imunodetection

with anti-DNP

-H2O2 +H2O2

A – silver staining B, C – imundetection with anti-DNP

Frutose-1,6-diphosphate

Glu-6-PD-6-phospho-glucono-δ-lactone

6-phospho-gluconate

ribulose-5-phosphate

ZWF1

GND2

PENTOSE PHOSPHATE PATHWAY

NADP+

NADP+ NADPH

NADPH

Dihydroxyacetone-P

3-phospho-

D-glycerol-P

TDH2/3

ribulose-5-phosphate

GLYCEROL

CYCLEdihydroxyacetone

glycerol

Glycerol-3-P

GPD1

DAK1

NADP+

ARA1

NADPH

GPD2

HOR2

Control

Wild-type

∆∆∆∆transcription_factor

Proteome-wide

kinase targets

Phosphoproteomics

Redox proteomicsProteome oxidation

profile

ProQ Diamond

Flamingo/

Sypro Ruby

∆∆∆∆protein_kinase

vs Global stress

Response

Cy5

Cy3

Cy2

DIGE

Pro-oxidant Stress

Wild-type

∆∆∆∆transcription_factor

∆∆∆∆protein_kinase Organele- or

structure-specifc

stress response

Transcription factor

regulon

Pre-fractionation

Redox proteomicsprofile

membrane proteome

Soluble proteome

DNP-labelled

NEM-labelled

Flamingo/

Sypro Ruby

vs ResponseDIGE

More information

Sá-Correia I., Teixeira M.C., Two-dimensional Electrophoresis-based Expression Proteomics:

a microbiologist’s perspective. Expert Reviews in Proteomics, 7(6), 943-953, 2010

● Espression proteomics: alternatives to 2D

electrophoresis

● Antibody and protein chips

● Interactomics

● Structural proteomics

Global gene expression analysis: expression proteomics

1 2 3 4 5 6 7

1 minute exposure

8

1 200 fmol

2 100 fmol3 50 fmol

Lane Amount

Global analysis of protein expression in yeastS Ghammaghami, WK Huh, K Bower, BW Howson, A Belle, N Dephoure, EK O’Shea & JS Weissman

Nature, 2003, 425: 737-741

Figure S1 Ghaemmaghami et al.

200 100 50 20 10 5 1 fmol5 minute exposure

1 2 3 4 5 6 7 8

3 50 fmol

4 20 fmol

5 10 fmol6 5 fmol

7 2 fmol

8 1 fmol

MudPIT - Multidimensional Protein Identification Technology

Shotgun proteomics – when applied to complete extracts

and complex samples

ICAT – Isotope Coded Affinity Tag

X = Hidrogen (light)

or

Deuterium (heavy)

Relative protein quantification by MS

8 Da diference

Binds to and modifies

cystein residues

(alkylation)

Used for affinity-

capture of cystein

containing peptides

(avidine)

• Samples are labeled with heavy or light tags

• Samples are mixed and then digested

• The labeled tags are purified by a biotin

affinity column

ICAT (isotope-coded affinity tags)

affinity column

MALDI

TOF

General idea: Differential proteomics

“Normal”

mouseAGiant

mouse B

Are there proteins that are different in abundance between mouse A and B that might account for mouse B’s giantness?

Extract proteins from bloodfrom blood

Label Light (1H) Heavy (2H)

mix

Enzymatic digestion (Trypsin)

General idea: Differential proteomics

Enzymatic digestion (Trypsin)

LC/MS/MS

In the LC, heavy and light co-elute

MS

m/z

rela

tive a

bu

nd

an

ce

Normal (1H)

Giant (2H)

Peptide found to be up regulated in giant mouse

MS/MS

rela

tive a

bu

nd

an

ce

MS/MS

Fragment ion masses help to identify peptide

sequence belonging to a specific protein

General idea: Differential proteomics

fragment ions

m/z

rela

tive a

bu

nd

an

ce

Protein determined to be up regulated in giant

mouse

ICAT (isotope-coded affinity tags)

LC MS/MS is then utilized for identity and

quantification (relative abundance based on

peak integration of ∆8Da peaks)

http://dir.niehs.nih.gov/proteomics/emerg2.htm

iTRAQ (isobaric tags for relative and absolute quantification)

• Uses up to 4 tags that bind covalently to the N

terminus of each peptide or to the lateral amine

groups of lysines (global tagging).

• Each sample is digested and labelled with • Each sample is digested and labelled with

specific iTRAQ tags

A B C DDIGEST DIGEST DIGESTDIGEST

Label A Label B Label C Label D

Isotope Tagging for Relative and Absolute protein Quantitation (iTRAQ)

- Can deferentially label and run up to four samples

- Proteins are digested prior to labeling

- Labels react with N-terminus

- No reduction of peptides based on amino acid composition

- Analyze all peptides

- Mass of peptide ions is the same allowing for a single mass to be selected for MS/MS

- Reporter group is lost during fragmentation

- Used to determine relative abundance of selected peptide of interest from the four samples

iTRAQ

Ross, P. L. et al. (2004) Mol Cell Proteomics 3(12): 1154-69

iTRAQ

Ross, P. L. et al. (2004) Mol Cell Proteomics 3(12): 1154-69

- Peptides have the same mass from each of the samples

- MS/MS of selected mass yields

- Fragmentation spectra for the identification of peptide

- Reporter group gives relative abundance information

Relative protein quantification by MS

•Specific site labelling: ICAT - cysteine residues

•N-termini tagging: iTRAQ

•Metabolic labelling: SILAC (Stable Isotope Labeling with Amino

acids in cell Culture) – cells are grown in the presence of isotopic

amino acids

More information

ICAT:Gygi, S. P., B. Rist, et al. (1999). "Quantitative analysis of complex protein mixtures using isotope-coded

affinity tags." Nat Biotechnol 17(10): 994-9.

Turecek, F. (2002). "Mass spectrometry in coupling with affinity capture-release and isotope-coded affinity tags for quantitative protein analysis." J Mass Spectrom 37(1): 1-14.

Ong, S. E., L. J. Foster, et al. (2003). "Mass spectrometric-based approaches in quantitative proteomics." Methods 29(2): 124-30

iTRAQ:DeSouza, L., G. Diehl, et al. (2005). "Search for cancer markers from endometrial tissues using differentially

labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry." J Proteome Res 4(2): 377-86.

SILAC and SILAC-like differential quantification:Ong, S. E., B. Blagoev, et al. (2002). "Stable isotope labeling by amino acids in cell culture, SILAC, as a simple

and accurate approach to expression proteomics." Mol Cell Proteomics 1(5): 376-86.

Oda, Y., K. Huang, et al. (1999). "Accurate quantitation of protein expression and site-specific phosphorylation." Proc Natl Acad Sci U S A 96(12): 6591-6.

Washburn, M. P., R. Ulaszek, et al. (2002). "Analysis of quantitative proteomic data generated via multidimensional protein identification technology." Anal Chem 74(7): 1650-7.

Ross, P. L. et al. (2004). “Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents." Mol Cell Proteomics 3(12): 1154-69.

Applied Biosystems iTRAQ Reference Guide: http://docs.appliedbiosystems.com/pebiodocs/04351918.pdf

Phospho-glicoproteómica por LC-MS

Advantages

� Quicker

� Allows the identification and quantification of

2D or not 2D?

LC-MS -based vs 2DE-based proteomics

� Allows the identification and quantification of

proteins with extreme pIs, low abundance or high

hydrophobicity

Disadvantages

� More expensive

� More complex