Download Vertes Proteomi.at GWU 2003

Proteomics Technology:
the Next Generation
Akos Vertes
Department of Chemistry
Institute for Proteomics
Technology and Applications
Facets of Proteomics
P.R. Graves and T.A.J. Haystead, Microbiol. Mol. Biol. Rev., 66 (2002) 39.
Multiplicity of Expression
task is enormous, – even compared to genomics
P.R. Graves and T.A.J. Haystead, Microbiol. Mol. Biol. Rev., 66 (2002) 39.
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
Paradigm Shift
in Mass Spectrometry
Proteins
in kidney
2D gel
m/z<200000
m/z<5000
Protein Expression Profiling
P.R. Graves and T.A.J. Haystead,
Microbiol. Mol. Biol. Rev., 66 (2002) 39.
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
(106 dynamic range)
• Molecular recognition
• Manipulation of tertiary and quaternary structure
• Protein chips
• Proteome mining (error tolerant algorithms)
Spatially resolved proteomics –
biomolecular imaging
http://www.microscopy-uk.org.uk
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
In Vivo Trace Analysis
• Why
mass spectrometry?
• Unique combination
of sensitivity and
selectivity
• High throughput
•Biomolecules under
physiological
conditions
Next Step: In Vivo AP-MALDI
• Atmospheric pressure
• Water as matrix
• Cell cultures
• Tissues and sections
• Non-covalent complexes
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.
Time dependence in proteomics –
cell cycle dependence
Cell cycle of fission yeast
J.J. Tyson et al., Nature Rev. Mol. Cell Biol., 2 (2001) 908.
Time dependence in proteomics –
physiological cycles
Photuris eats Photinus
Luciferin is transformed
by luciferase => flashing
http://ase.tufts.edu/biology/firefly
Ultratrace Analysis of Biomolecules
Detection limits:
• High attomol range
T.E. Ryan and S.D. Patterson,
Drug Discovery World,
Winter, 2001/2, 43.
Quantitation
Isotope coded
affinity tagging (ICAT)
P.R. Graves and T.A.J. Haystead,
Microbiol. Mol. Biol. Rev., 66 (2002) 39.
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)