Scientists create first computer model of an entire organism
By Ben Coxworth
July 23, 2012
For the first time ever, a computer model of a complete living organism has been created. True, it’s a single-celled organism – in fact, it’s the world’s smallest free-living bacterium, Mycoplasma genitalium. Still, all of its systems and the relationships between them have been replicated in silico, allowing scientists to conduct research that might otherwise have proved impossible. It also paves the way for computer modeling of more complex organisms, such as humans.
The model was created by a team led by assistant professor of bioengineering Markus Covert, at California’s Stanford University.
They chose M. genitalium mainly because at 525 genes, it has the smallest genome of any free-living organism. The more well-known Escherichia coli bacterium, by contrast, has 4,288 genes. While some strains of E. coli have a well-earned reputation for causing maladies such as food poisoning, M. genitalium is itself no angel – the sexually-transmitted bacterium is the source of genital infections such as urethritis and vaginosis.
The team utilized data from over 900 scientific papers on the bacterium, which between them covered every molecular interaction that takes place within the organism’s life cycle. The resulting model incorporates over 1,900 separate parameters, which the scientists grouped into 28 distinct modules. Each module is responsible for a different biological process, and is controlled by its own unique algorithm. The modules also communicate back and forth, accurately replicating the way in which the biological processes within the actual bacterium affect one other.
In fact, that’s one of the most valuable aspects of the model. Traditionally, when experimenting with real bacteria, scientists manipulate one gene and then look for noticeable changes within the organism. With a computer model, however, researchers are instantly made aware of any changes that occur within any of the bacterium’s systems.
Of course, it shouldn’t just be taken for granted that everything observed in the model will be identical to what would happen in an actual M. genitalium. That’s why any conclusions drawn from studying the model would have to be backed up with observations of the bacterium itself – at least with the model, however, scientists would know what to be looking for.
“If you use a model to guide your experiments, you're going to discover things faster,” said Covert. “We've shown that time and time again.”
Already, his team has used the computer model to identify new gene functions, and to study DNA-binding protein dynamics. In one particular study, they looked into a mystery surrounding the individual stages of M. genitalium’s cell-division cycle. While the length of these stages varies between individual bacterium, the length of the entire cycle is more or less the same for all of them. Using the model, it was hypothesized that a built-in negative feedback mechanism was responsible for evening things out, ensuring that all the bacterium ultimately take the same amount of time to divide.
Down the road, the researchers believe that models like theirs could be used in what they call Bio-CAD – CAD standing for computer-aided design. They suggest that microorganisms could be genetically altered or even created, by first working things out on a virtual model, then applying the findings to actual organisms.
Ultimately, if individual peoples’ bodies could be replicated in the form of computer models, then things such as drug treatments or gene therapy could first be tried on those models, then only applied to the actual people if they proved safe and effective (already, it’s possible to create working copies of individuals’ immune systems in lab mice).
Such complex models are reportedly still a long way off, however. “This is potentially the new Human Genome Project,” said biophysics graduate student Jonathan Karr, who is co-author of a paper on the research. “It's going to take a really large community effort to get close to a human model.”
The paper was published last Friday in the journal Cell.Share
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