Connie Jimenez of the VU Amsterdam started her
presentation with a brief history of proteomics. The
proteome
encompasses the complete set of proteins produced by an organism.
Proteomics involves the large-scale study of these
proteins
as the main components of the
metabolic pathways
of
cells.
1993 saw the first single cell peptide profile. But it was the ability
to make large amounts of these profiles − thanks to automation and the
development of tools to handle large datasets − that really marks the
start of proteomics in 1997. The good news is that the proteome links
DNA to phenomena like diseases. Problem, however, is that no linear
correlation exists between the two: the proteome differs from cell to
cell and constantly changes through
biochemical
interactions.
Underlying system
Large-scale screening through advanced mass spectrometry technologies like MALDI-TOF-MS (1995) or MALDI-TOF-TOF (2004) might result in the discovery of thousands of different proteins. But without understanding the underlying biological system these results mean nothing, speakers Connie Jimenez, Ka Wan Li, Paul Hensbergen, Sander Piersma and Madalina Oppermann agreed. That explains why the question ‘Has proteomics revolutionised our understanding of cell function?’ is still valid.
Global analysis
Ka Wan Li focuses this question on molecular events in the brain and the function of synapses for information storage and information integration. According to him, quantitative proteomics is mature enough for global analysis of the brain region. In research on drug addiction, changes of certain proteins were found as a result of addictive behaviour of rats. But these were insufficient to reconstruct cellular processes. So, he says: “It is not a revolution, rather another nice tool to understand biological processes. You always have to interpret the framework in which such changes take place.”
No fishing
And that is why, Paul Hensbergen states, so called ‘fishing expeditions’
into random results are useless. You have to know what you are looking
for in order to find something meaningful. Sander Piersma therefore
says: “Reduce complexity before Mass Spectrometry.” Of nine FDA-approved
biomarkers, none was discovered by proteomics. But carefully targeted
proteomics studies might lead to novel biomarkers, provided one doesn’t
analyse something as complex as blood. Another remark by Piersma: “Most
biomarkers have no proven functional relation to the disease.
Understanding would be nice, but it is not necessary. A biomarker is
good as long as it is selective and sifts out false positives.”
[Leendert van der Ent]
