Researchers at Stanford University have completed the world’s first complete computer model of an organism. Using research from 900 publications and accounting for over 1900 parameters, they were able to completely simulate the human pathogen, Mycoplasma genitalium. This pathogen is often found in the urinary or respiratory tracts of humans and is known to have the simplest genome of any free-living organism.
The study was partly funded by the NIH Director’s Pioneer Award. “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 study consisted of vast amounts of data and took a lot of computing power to pull off. But you may ask, “Why are we so interested in simulating an organism?” That is a good question. In the simplest of terms, what these scientists are building is called a phenotype, which basically means they are building a model based on observed behaviors or expressions in this organism. Using data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium, the scientists were able to observe things in the computer model that would be hard to see in the real thing. They were also able to reexamine experimental data.
This study opens wide the possibilities of computer aided bio-engineering. If you’ve been around any construction or architectural firms, you know the impact that computer aided design (think AutoCAD) has contributed to the process of planning and engineering a building. In the same way, being able to simulate entire organisms and be able to predict what certain genes will do under certain conditions has so much potential for future applications such as pharmaceuticals and even personalized medicine. However, the study authors are cautious to note that it will be a while before this is possible.