Expression Proteomics: principles and examples of application

Transcription

1 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

2 Previous class 2D electrophoresis Sample application IEF Application of the IPG strip on top of the SDS polyacrylamide gel SDS - PAGE ph 10 3 ph 10 ph ph MM 3 3 Immobilized ph gradient SDS polyacrylamide gel SDS polyacrylamide gel

3 1. Incubation of a cell culture under the stress conditions of the study Control Stress 2. Fractionation of the proteome 3. Solubilization of proteins in IEF buffer st Dimension: IEF 4. 3 ph 10 3 ph nd Dimension: SDS-PAGE Staining of proteins 7. Identification of proteins whose relative abundance varies Protein identification peptide mass fingerprinting Data analysis aiming the identification of the cell adaptation mechanisms to the studied agression 9.

4 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 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

5 Overcomming some of the 2D based proteomics limitations 2-D ZOOMING Low abundant protein analysis Pre-fractionation of protein mixtures Soluble fraction Membrane fraction

6 Overcomming some of the 2D based proteomics limitations 1. Low abundant protein analysis 2. Spot matching reliability DIGE technology DIfferential Gel Electrophoresis

7 Practical Approach to DIGE Amersham Pharmacia Biotech, Life Science News, 7, 2001

8 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

9 Why would we use proteomics when we can use transcriptomics? 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

10 Studying proteome-wide post-translational modifications using 2-D electrophoresis phosphorilation glycosilation Pro-Q-Diamond Pro-Q_Emerald

11 Importance of the phosphoproteome

12 Redox Proteomics Carbonyl groups Carbonylated proteins are labelled with dinitrophenol-hydrazine (DNP) After 2D SDS-PAGE, proteins are transfered to nitrocellulose membranes 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

13 Redox Proteomics Extremely important in human diseases such as: Asthma; Cardiovascular disease (ischaemia and reperfusion); Diabetes; Cirrhosis; Alzheimer's, etc..

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15 DNPH labelled sample 2D Gel Western blot Imunodetection with anti-dnp

16 -H 2 O 2 +H 2 O 2 A silver staining B, C imundetection with anti-dnp

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18 3-phospho- D-glycerol-P DAK1 TDH2/3 Glu-6-P NADP + Frutose-1,6-diphosphate Dihydroxyacetone-P ZWF1 NADPH GPD1 GPD2 PENTOSE PHOSPHATE PATHWAY D-6-phospho-glucono-δ-lactone 6-phospho-gluconate NADP + NADPH GND2 ribulose-5-phosphate dihydroxyacetone GLYCEROL CYCLE Glycerol-3-P NADPH ARA1 NADP + glycerol HOR2

19 Proteome-wide kinase targets Phosphoproteomics Flamingo/ Sypro Ruby Cy2 Cy3 Wild-type ProQ Diamond Cy5 transcription_factor protein_kinase Proteome oxidation profile Redox proteomics Control vs Pro-oxidant Stress DIGE Wild-type Global stress Response Pre-fractionation transcription_factor Organele- or structure-specifc stress response protein_kinase NEM-labelled DNP-labelled Soluble proteome Flamingo/ Sypro Ruby Transcription factor regulon membrane proteome

20 More information Sá-Correia I., Teixeira M.C., Two-dimensional Electrophoresis-based Expression Proteomics: a microbiologist s perspective. Expert Reviews in Proteomics, 7(6), , 2010

21 Espression proteomics: alternatives to 2D electrophoresis Antibody and protein chips Interactomics Structural proteomics

22 Global gene expression analysis: expression proteomics Global analysis of protein expression in yeast S Ghammaghami, WK Huh, K Bower, BW Howson, A Belle, N Dephoure, EK O Shea & JS Weissman Nature, 2003, 425: minute exposure fmol 5 minute exposure Lane Amount fmol fmol 3 50 fmol 4 20 fmol 5 10 fmol 6 5 fmol 7 2 fmol 8 1 fmol Figure S1 Ghaemmaghami et al.

23 MudPIT - Multidimensional Protein Identification Technology Shotgun proteomics when applied to complete extracts and complex samples

24 Relative protein quantification by MS ICAT Isotope Coded Affinity Tag X = Hidrogen (light) or Deuterium (heavy) 8 Da diference Used for affinitycapture of cystein containing peptides (avidine) Binds to and modifies cystein residues (alkylation)

25 ICAT (isotope-coded affinity tags) Samples are labeled with heavy or light tags Samples are mixed and then digested The labeled tags are purified by a biotin affinity column MALDI TOF

26 Normal mousea General idea: Differential proteomics Giant 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 blood Label Light ( 1 H) Heavy ( 2 H) mix Enzymatic digestion (Trypsin)

27 General idea: Differential proteomics Enzymatic digestion (Trypsin) LC/MS/MS In the LC, heavy and light co-elute MS relative abundance Normal ( 1 H) Giant ( 2 H) Peptide found to be up regulated in giant mouse m/z MS/MS

28 General idea: Differential proteomics MS/MS relative abundance fragment ions Fragment ion masses help to identify peptide sequence belonging to a specific protein m/z Protein determined to be up regulated in giant mouse

29 ICAT (isotope-coded affinity tags) LC MS/MS is then utilized for identity and quantification (relative abundance based on peak integration of 8Da peaks)

30 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 specific itraq tags A B C D DIGEST DIGEST DIGEST DIGEST Label A Label B Label C Label D

31 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

32 itraq Ross, P. L. et al. (2004) Mol Cell Proteomics 3(12):

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

34 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

35 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): 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): Ong, S. E., L. J. Foster, et al. (2003). "Mass spectrometric-based approaches in quantitative proteomics." Methods 29(2): 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): Ross, P. L. et al. (2004). Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents." Mol Cell Proteomics 3(12): Applied Biosystems itraq Reference Guide: 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): 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): Washburn, M. P., R. Ulaszek, et al. (2002). "Analysis of quantitative proteomic data generated via multidimensional protein identification technology." Anal Chem 74(7):

36 Phospho-glicoproteómica por LC-MS

37 2D or not 2D? LC-MS -based vs 2DE-based proteomics Advantages Quicker Allows the identification and quantification of proteins with extreme pis, low abundance or high hydrophobicity Disadvantages More expensive More complex