1. Sequencing of Mammalian Genomes Predicts 30,000 genes 20012002

2. What is the Proteome All the proteins expressed in a particular cell or tissue. By definition this will vary by tissue and cell type. –Cardiovascular –Neuromuscular –Islet cell –Endothelial cell –Muscle cell

3. Why Study Proteomics? Gives a better understanding of the function of gene products. Allow for the design of rational drug therapies. Provide new and specific markers of disease.

4. Will Proteomics Provide a Stronger Means to Stratify Disease Greater Complexity=Greater Specificity YES

5. Protein Modifications Phosphorylation Glycosolation Ubiquitination Cleavage Lipid etc. Dictates Function and Intracellular Localization

6. 30,000 Genes How Many Proteins? 30,000 genes 4-6 splice variants 120,000 possible mRNAS >200 Post-translational Modifications 24,000,000 Possible Protein Isoforms 2,000,000 Predicted Proteins

7. How Gene and Protein Expression is Regulated or Modified from Transcription to Post-translation

8. Synaptojanin 2

9. Biomarker ID vrs Protein ID BIOMARKER CHANGE +/- IDENTITY ? SPECIFIC EASE BODY FLUID PROTEIN INTERACTION PRESENCE ISOFORMS MODIFICATIONS FUNCTION

10. Using Proteomics to Identify Biomarkers of Disease

11. How do You ID Biomarkers 2D-PAGE  MALDI-TOF MS ICAT  MALDI-TOF MS SELDI-TOF MS

12. Proteomic flow 1D and 2D gels Proexpress ImagerProgestProMSPropicker Q Star XL -MS/MS-TOF Vision Station Biacore

15. ICAT (Isotope Coded Affinity Tag) Deuterium BiotinLinker Thiol Reactive Group

16. ICAT Provides Relative Levels of Expression Between Two Proteins Which is Reflected by the Ratio of the Amount of Peptide

17. Surface Enhanced Laser Desorption Ionization Time of Flight (SELDI-TOF) Protein Chip

18. Protein Chip

19. Different Protein Profiles from Different Chip Surfaces

21. Laser Capture Microscopy Allows for the Dissection of Cells Directly from Sectioned Tissues

22. LCM of Normal and Cancerous Prostate

23. Protein Profile from Prostrate Cancer Tissue Procured by LCM

24. Do we Need all Three Approaches? 2D-PAGE  MALDI-TOF MS –Greatest resolving power –Large data base –Labor and time consuming ICAT  MALDI-TOF MS –Mostly abundant proteins –Needs cysteine residue SELDI-TOF MS –Resolves from 8-50 kDa –Small amounts of sample