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Proceedings -Wednesday, October 10, 2001
WOA1
Qualitative and Quantitative Mass Spectrometry for Proteomics
David R. Goodlett, The Institute for Systems Biology
Background:
Traditionally, biology has focused on studying individual genes,
proteins and organisms in isolation. Systems biology, however, has
demonstrated that biologically significant phenomena arise from
complex interactions of numerous gene, protein and cell elements
that form informational networks and systems. Proteins are vital
components of this system and are important for the functioning of
cells. Like genes, proteins are critical for controlling biological
systems. The capabilities of technology in the future include being
able to identify a large percentage of the proteins in both healthy
and diseased cells and analyze them all at the same time via
advanced mass spectrometry techniques.
Premise:
General research goals of the Institute for Systems Biology are to:
- Acquire data for modeling cells; demonstrate the feasibility of
creating models for accurately predicting molecular interactions
within cells.
- Allow the global data to suggest an appropriate hypothesis.
- Write algorithms that are predictive. By integrating
different types of information, a mathematical model can ultimately
be constructed describing the structure and behavior of the cells.
Analysis
As an example of the integration of methods and technologies, huge
amounts of data were gathered from genes, proteins and molecular
interactions within yeast cells. These data were generated by
exposing the pathway of galactose utilization in yeast to a battery
of test conditions in which known genes and other molecular
components were removed one by one. For each test condition,
responses were recorded at several different levels of biological
information utilizing state-of-the-art technology:
- DNA microarrays gathered genomic information revealing which genes
were turned on or off under each condition
- Proteomics techniques measured the types and quantities of the
proteins produced by each expressed gene
- Existing biological databases were mined to identify molecules
known to interact in each condition, including data on interactions
among proteins as well as between proteins and DNA.
The diverse data types were then integrated using high-throughput
computational facilities. The research succeeded in identifying a
number of new interactions not previously documented through
traditional research methods, opening whole new fields of study.
Protein quantitation and identification techniques can be performed
via the unique Isotope Coded Affinity Tag (ICATTM) reagent method.
ICAT has been shown to be very promising in its ability to precisely
identify, quantify and analyze most of the proteins expressed in a
cell or tissue. The figure below represents the range of protein
types that can be identified using this technique.
By building on the ICAT technology, a research goal is to take
post-genome biology to the next level with high-speed capabilities
in proteomics comparable to those that have transformed genomics.
Then a true integration of genomics and proteomics will help to
understand how biological systems work.
Value of the Technology
The Institute for Systems Biology is formed around the realization
that advancing biology in the 21st Century will rely on using
advanced biological and computational technologies to generate and
correlate many different levels and types of biological information.
Unlike traditional scientific approaches that examine single genes
or proteins, systems biology focuses on simultaneously studying the
complex interaction of vast numbers of biological elements.
Ultimately, the modeling approach used promises to revolutionize the
study of disease and illness by generating information needed to
develop new medical treatments in a much shorter timeframe.
References
Trey Ideker et al., Science, 292, 929-934 (2001).
Links
Institute for
Systems Biology
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