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 Press Release 062804
FOR IMMEDIATE RELEASE

New Application for ICAT Technology Yields Important New Insights into Identifying the Molecular Basis for Human Diseases

SEATTLE - Monday, June 28, 2004 - A new approach to protein analysis completed in the model organism yeast is helping scientists better identify diseases in humans. In the June 27 online issue of Nature Genetics, researchers at the Institute for Systems Biology (ISB) report that technology developed at the ISB and applied in a new way to yeast has led to an important new insight that could explain the molecular mechanism of Trichothiodystrophy, a rare human disease.

The research, led by ISB scientist Dr. Jeff Ranish has used the Isotope Coded Affinity Tag (ICAT) method and quantitative mass spectrometry to find one or a few proteins that have specific properties in a complex background of other proteins that do not have this property. Normally, the ICAT technology has been applied to detect and identify differences in the complex protein expression patterns between different samples (protein profiling), but in this case, Ranish wanted to examine just a few among many proteins.

"This is essentially a needle in a haystack problem," stated Ranish. "We sought to identify the proteins that control gene expression in the cell. To distinguish this small subset of proteins from all the other proteins in the cell, we devised a scheme to enrich these proteins and then applied the ICAT-based quantitative mass spectrometry technology to directly identify the proteins involved in gene expression."

Model organisms provide relatively simple systems in which to study central biological questions and the insights can then be applied to humans. Although simple, these model systems provide advantageous platforms for technology development, integrative computational research, and biological discovery. For example, the yeast model organism contains approximately 6200 genes, whereas the human has more than 30,000.

While Ranish's work was in progress, Dr. Wim Vermeulen and colleagues at Erasmus University in the Netherlands, were trying to identify the gene(s) responsible for a form of Trichothiodystrophy, a congenital disorder that involves production of abnormal, brittle hair and frequently also involves problems with hair related structures such as the teeth, eyes, and nails. It can also involve stunted growth, mental retardation, skin sensitivity to light and skin ichthyosis. Treatment is very difficult because it is a genetic disease with no form of gene therapy available now or in the foreseeable future. One of the proteins identified by Ranish in yeast appeared to be a likely candidate for the gene product that was defective in this form of Trichothiodystrophy. Vermeulen and colleagues used this information to rapidly identify the single gene defect in this disease.

"The work described in the two papers is a striking validation of the general ISB research strategy," stated Dr. Ruedi Aebersold, ISB co-founder and faculty member. "The first step is to pioneer the development of new technology, then apply and validate such technology in simple, relatively well characterized species and use these results to gain new insights into the molecular basis of human disease."

About the Institute for Systems Biology
The Institute for Systems Biology (ISB) is an internationally renowned non-profit research institute dedicated to the study and application of systems biology. ISB's goal is to unravel the mysteries of human biology and identify strategies for predicting and preventing diseases such as cancer, diabetes and AIDS. The driving force behind the innovative "systems" approach is the integration of biology, computation, and technology. This approach allows scientists to analyze all of the elements in a system rather than one gene or protein at a time. Located in Seattle, Washington, the Institute has grown to seven faculty and more than 170 staff members; an annual budget of $25 million; and an extensive network of academic and industrial partners. For more information, visit: www.systemsbiology.org

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