The BiGG Picture

A virtual metabolic network represents intracellular traffic

It’s hard to imagine a map depicting the daily flow of traffic on water, wheels and foot throughout San Diego—or any large city—over the course of a day. “That map can have many different functional states which are quite different in the middle of the night and during rush hour,” says Bernhard Palsson, PhD, professor of bioengineering at the University of California, San Diego.

 

But it’s even harder to imagine the map recently assembled by Palsson and his multidisciplinary research team—a virtual metabolic network representing the intracellular traffic catalyzed by more than 2,000 proteins and 3,300 bio-chemical reactions within the human body. Construction of this first-ever genome-scale database, dubbed a BiGG (biochemically, genetically and genomi- cally structured) reconstruction, was described in the February 6, 2007, issue of the Proceedings of the National Academy of Sciences.

 

Overview of the BiGG global human metabolic network. Courtesy of Bernhard Palsson and Neema Jamshidi.Culled from more than a half century of published data, the computational system will allow researchers to explore hun- dreds of human disorders related to metabolism—the chemical processes by which the body breaks down food to build and maintain itself. For example, scientists can use mathematical optimization tools to identify sets of chemical reactions that are turned on or off together when the body makes cholesterol, explains Neema Jamshidi, an MD-PhD student in the Palsson lab who was a co-author on the paper. Knowing which reactions are correlated in this manner could lead researchers to alternative drug targets—components of other biochemical pathways that could be blocked to achieve the same effect as an existing cholesterol-lowering medication, Jamshidi says.

 

Douglas Kell, PhD, director of the Manchester Interdisciplinary Biocentre at the University of Manchester, describes another application of the BiGG database in a systems biology review published in the December 2006 issue of Drug Discovery Today. By computing metabolite levels under various conditions over time, he says, the network could be used to infer patterns of disease progression, providing clues as to whether a drug might reverse the degenerative process.

 

To give the biomedical community a shot at these lofty goals, a team of six UCSD researchers that included Palsson and Jamshidi spent 18 painstaking months gathering data to assemble the BiGG network. They combed through more than 1,500 primary literature articles, reviews and biochemical textbooks.

 

“What we have now is a global network,” Jamshidi says. “If we found any evidence that a certain reaction occurs in a kidney cell, heart cell, whatever, we threw it in there.” In the future, he says, the team will work with experts who study particular cell types—cardiac myocytes, for instance—to refine the pathways in the global system and make them more context-specific.

 

In the meantime, scientists such as Kell are thrilled about what the BiGG network will do for systems biology. “It is the first step on the way to a ‘digital human’ model,” he says, “from which we can model health, disease, the metabolism of pharmaceutical drugs and so on.”

 



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