World's first computer model of organism created

Washington, July 22 (IANS) Scientists have created the world's first ever computer model of an organism -- a breakthrough which would catalyse radically new approaches to diagnostics and treatment.

A team led by Markus Covert, assistant professor of bioengineering at the Stanford University, used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium.

M. genitalium, the world's smallest free-living bacterium, shows up uninvited in human urogenital and respiratory tracts.

The pathogen also contains the smallest genome of any free-living organism, only 525 genes, as opposed to the 4,288 of E. coli, a more traditional lab bug, the journal Cell reports.

Even at this small scale, the quantity of data that the Stanford researchers incorporated into the virtual cell's code was enormous.

The final model made use of more than 1,900 experimentally determined parameters, according to a Stanford statement.

"Comprehensive computer models of entire cells have the potential to advance our understanding of cellular function and, ultimately, to inform new approaches for the diagnosis and treatment of disease," said James M. Anderson, director of the National Institutes of Health Division of Programme Coordination, Planning and Strategic Initiatives, which had part funded the research.

Most biological experiments, however, still take a reductionist approach to this vast array of data: knocking out a single gene and seeing what happens.

"Many of the issues we're interested in aren't single-gene problems," said Covert. "They're the complex result of hundreds or thousands of genes interacting."

"You don't really understand how something works until you can reproduce it yourself," said Jayodita Sanghvi, Stanford bioengineering graduate student and study co-author.

"The goal hasn't only been to understand M. genitalium better. It's to understand biology generally," said study co-author and Stanford biophysics graduate student Jonathan Karr.