1. Proteomics Technology: the Next Generation Akos Vertes Department of Chemistry Institute for Proteomics Technology and Applications

2. Facets of Proteomics P.R. Graves and T.A.J. Haystead, Microbiol. Mol. Biol. Rev., 66 (2002) 39.

3. Multiplicity of Expression P.R. Graves and T.A.J. Haystead, Microbiol. Mol. Biol. Rev., 66 (2002) 39. task is enormous, – even compared to genomics

4. Current Technologies Separation methods: 2D gel electrophoresis, HPLC Soft ionization methods and mass spectrometry Peptide mapping Secondary and tertiary structure determination Non-covalent complexes Tandem mass spectrometry Isotope coded affinity tagging Protein databases

5. Paradigm Shift in Mass Spectrometry m/z<5000 m/z<200000 Proteins in kidney 2D gel

6. Protein Expression Profiling P.R. Graves and T.A.J. Haystead, Microbiol. Mol. Biol. Rev., 66 (2002) 39.

7. Obstacles and Future Technologies Protein distributions in tissues and cells (in vivo) Temporal variation of protein concentrations Quantitation of protein levels Detection of low copy number species (10 6 dynamic range) Molecular recognition Manipulation of tertiary and quaternary structure Protein chips Proteome mining (error tolerant algorithms)

8. Spatially resolved proteomics – biomolecular imaging http://www.microscopy-uk.org.uk

9. How to Make MALDI “Softer?” Objective: direct analysis of cells and tissues Two obstacles:denaturing matrices vacuum conditions Proposed solutions: IR-MALDI with water as matrix atmospheric pressure (AP) MALDI

10. In Vivo Trace Analysis Why mass spectrometry? Unique combination of sensitivity and selectivity High throughput Biomolecules under physiological conditions

11. Next Step: In Vivo AP-MALDI Atmospheric pressure Water as matrix Cell cultures Tissues and sections Non-covalent complexes

12. The Step Beyond Spatial resolution is limited by laser wavelength, i.e., ~10  m SNOM + AP-MALDI ~200 nm resolution Stockle et al., Anal. Chem., 2001, 73, 1399.

13. Time dependence in proteomics – cell cycle dependence J.J. Tyson et al., Nature Rev. Mol. Cell Biol., 2 (2001) 908. Cell cycle of fission yeast

14. Time dependence in proteomics – physiological cycles http://ase.tufts.edu/biology/firefly Photuris eats Photinus Luciferin is transformed by luciferase => flashing

15. Ultratrace Analysis of Biomolecules T.E. Ryan and S.D. Patterson, Drug Discovery World, Winter, 2001/2, 43. Detection limits: High attomol range

16. Quantitation Isotope coded affinity tagging (ICAT) P.R. Graves and T.A.J. Haystead, Microbiol. Mol. Biol. Rev., 66 (2002) 39.

17. Inroads at GWU Spatially resolved proteomics – biomolecular imaging (SNOM-MALDI, proteins at interfaces) Time dependence in proteomics – cell cycle dependence (NMR, folding dynamics) Detection limits (low copy number proteins) Noncovalent interactions – molecular recognition (light scattering with fractal analysis) Quantitation (differential proteomics – healthy vs. diseased state)