More than 1,900 parameters and 28 modules were needed to recreate the life of a bacteria with only 525 genes - the least of any free-living organism. (Photo : Covert Lab)
It may not be too long before computers can accurately simulate complex life forms such as houseflies, and one day, even humans. In the first step towards computer simulation of life, scientists from Stanford University have developed the world's first computational model of a living organism, the bacteria, Mycoplasma genitalium.
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The model could lead to other advances that might replace lab testing on animals one day if the simulations become sophisticated enough.
"This achievement demonstrates a transforming approach to answering questions about fundamental biological processes," said James M. Anderson, director of the National Institutes of Health Division of Program Coordination, Planning and Strategic Initiatives. "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."
The 2008 video game Spore allowed gamers to create a simple one-celled organism and lead it through the evolutionary processes, including war, that eventually make it a full blown society capable of traversing space. This computer simulation is slightly more complex. To create it, the team poured over 90 papers to document every molecular interaction that takes place during life of Mycoplasma genitalium.
The scientists chose Mycoplasma genitalium as the candidate because it has the smallest genome of any free-living organism - only 525. Escherichia coli, a more common lab bacteria, has over 4,000. Even for bacteria as simple as this, more than 1,900 experimental parameters and 28 separate interactive modules had to be programmed.
The team has already have used the model to form some conclusions on the varying lengths of the stages of cell cycles. And although real-world confirmation is needed to make the results acceptable, the computer model is still a valuable tool.
"If you use a model to guide your experiments, you're going to discover things faster. We've shown that time and time again," said team leader and author of the paper Marcus Covert.