Our recent research shows that what is true in power networks is also true in biological networks. Inflicting a small amount of damage can control what otherwise would be much more significant damage.
With the experimental information assembled, the researchers used their computer model to simulate the organism and its function. They started with a perfect cell and then, with a key gene deletion, damaged the cell so that it was unable to grow or had a significantly reduced growth rate.
Next, the researchers restored growth by deleting additional genes, which stimulated the cell to make a different choice and use different pathways. Interestingly, the cells recovery was stronger when more genes were deleted. They could even restore growth to non-growing mutant cells; the researchers dubbed this the Lazarus effect.
Our research is based on optimizing the use of resources already available in the cell, said Motter. We are exploring existing reactions and genes in the cell that the cell would not use or use to a lesser degree under normal conditions. This is different from traditional gene therapy, which is based on introducing new genes into the cell -- with its own advantages and problems because of that.
The teams use of predictive models is similar to how physicists use models, for example, to determine the position of the moon tomorrow at a specific time. Thanks to the recent wealth of available biological information, computational scientists now are beginning to develop quantitative models of biological systems that allow them to predict cellular behavior.
In one in silico experiment (via computer simulation) with E. coli, the researchers found that the deletion of on
|Contact: Megan Fellman|