Automated analytical platform facilitates identification of proteins

October 01, 2001

CHAMPAIGN, Ill. -- Now that the human genome has been sequenced, one of the hottest areas in life sciences is characterizing the human proteome. Researchers at the University of Illinois have developed techniques that facilitate the rapid identification and characterization of proteins.

"New analytical methodologies are needed to identify the form and function of the hundreds of thousands of proteins encoded by genes," said Neil Kelleher, a UI professor of chemistry. "Part of the problem is retrieving intact proteins from databases using high-resolution, tandem mass spectrometric data and correlating their predicted structures with those actually present in mature proteins."

Contemporary approaches to protein identification using mass spectrometry have involved the measurement of peptide masses, but the direct fragmentation of protein ions "can be far more efficient than exhaustive peptide mapping," Kelleher said. "This is a new strategy for proteome analysis."

Kelleher's instrumentation combines Fourier-Transform Mass Spectrometry with electrospray ionization and separation methods. At the heart of the system is a liquid-helium cooled superconducting magnet. A vacuum system and mass spectrometer extend into the magnet's center.

"This is a relatively new breed of magnet," Kelleher said. "Instead of using 12 tons of bulky steel, the magnet is actively shielded with a counter-propagating magnetic field. The fields cancel one another outside the magnet, but at the magnet's center the field strength is a hefty 9.4 tesla."

Fractionated proteins are squirted into the vacuum system and then transported into the magnet, where they begin to spin. "The proteins spin at different frequencies, depending on their mass and charge," Kelleher said. "We gradually excite their orbits to higher and higher radii, and they eventually fly past sensitive detector plates in the mass spectrometer."

Computers then analyze the data to identify and characterize the proteins. The entire system is becoming increasingly automated for ease and efficiency of operation.

For their initial studies, Kelleher and his students selected two representative life forms: Mycoplasma pneumoniae - a simple bacteria with a tiny genome - and Methanococcus jannaschii - an archaeon found in submarine hydrothermal vents.

First, the researchers showed that multiple proteins could be processed simultaneously. Then they tested a predictive model for database search specificity.

The model agreed well with actual searches from a database of about 3,500 protein forms predicted from the genomic sequence of M. jannaschii. The method also should work for the millions of possible protein forms predicted from the human genome.

"These conceptual and technical advances provide a powerful tool for protein characterization in the post-genomic era," Kelleher said. "By better characterizing proteins, we can improve our fundamental understanding of the blueprint of life." The researchers described their technique in the October issue of Nature Biotechnology.

University of Illinois at Urbana-Champaign

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