To implement this framework, the researchers had to deal with the sheer scale and complexity of simulating any realistic biological system. They had to keep track of hundreds of genes, proteins, and other biological factors in the microbial population, and observe them as they varied over millions of time points. "Simulations at this scale and complexity would have been impossible in the past," says Tagkopoulos. Even with the vast number crunching power the supercomputers provided by the University's Computational Science and Engineering Support Group, their experiments took nearly 18 months to run, says Tagkopoulos.
In this virtual world, microbes are more likely to survive if they conserve energy by mostly turning off the biological processes that allow them to eat. The challenge they face then is to anticipate the arrival of food and turn up their metabolism just in time. To help them along, the researchers gave the bugs cues before feeding them, but the cues had to appear in just the right pattern to indicate that food was on its way.
"To predict mealtimes accurately, the microbes would have to solve logic problems," says Tagkopoulos, a fifth-year graduate student in electrical engineering and the principal architect of the Evolution in Variable Environment framework.
And sure enough, after a few thousand generations, an ecologically fit strain of microbe emerged which did exactly that. This happened for every pattern of cues that the researchers tried. The feeding res
|Contact: Steven Schultz|
Princeton University, Engineering School