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"Long
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July 24, 2012
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First “virtual cell” seen as
unlocking new potential for discovery
July 24, 2012
Courtesy of Stanford University
and World
Science staff
The first complete computer model of an organism has been completed, researchers reported last week in the journal
Cell.
A team led by Markus Covert of Stanford University used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of
Mycoplasma genitalium, the world’s smallest free-living bacterium.
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The Covert Lab at
Stanford University incorporat more than 1,900 experiment observed parameters into their model of the tiny parasite Mycoplasma genitalium. (Illustration: Erik Jacobsen / Covert Lab)
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“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,” said James M. Anderson, director of the Division of Program Coordination, Planning and Strategic Initiatives at the National Institutes of Health, which helped fund the research.
Genetic experiments typically involve deactivating
one gene to see what happens. The drawback to that, Covert said, is that many of the questions biologists need to learn about “aren’t single-gene problems. They’re the complex result of hundreds or thousands of genes interacting.”
This situation has led to a yawning gap between information and understanding that can only be addressed by “bringing all of that data into one place and seeing how it fits together,” said Stanford graduate student Jayodita
Sanghvi, who co-authored the research. “You don’t really understand how something works until you can reproduce it yourself.”
The bacterium modeled is is a humble parasitic one known mainly for showing up uninvited in human urogenital and respiratory tracts. But it also has the distinction of containing the smallest genome of any free-living organism – only 525 genes, as opposed to the 4,288 of
E. coli, a more traditional laboratory bacterium. The minimalism of its genome has made it the focus of several recent
bio-engineering efforts. Notably, these include the J. Craig Venter Institute’s 2008 synthesis of the first artificial chromosome.
“The goal hasn’t only been to understand M. genitalium better,” said Stanford biophysics graduate student Jonathan Karr, who also collaborated on the study. “It’s to understand biology generally.” Even at this small scale, the
quantity of data that the researchers incorporated into the virtual cell’s code was enormous. The final model made use of more than 1,900 experimentally determined parameters.
The computational cell opens up procedures that would be hard to perform in a real organism, and opportunities to revisit experimental data, the researchers said. In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions.
Biologists hope computational models like this one could bring rational design to biology – allowing not only for computer-guided experimental regimes, but also for the wholesale creation of new microorganisms. “This is potentially the new Human Genome Project,” Karr said. “It’s going to take a really large community effort to get close to a human model.”
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The world’s first complete computer model of an organism has been completed, researchers reported last week in the journal Cell.
A team led by Markus Covert of Stanford University used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium, the world’s smallest free-living bacterium.
“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,” said James M. Anderson, director of the Division of Program Coordination, Planning and Strategic Initiatives at the National Institutes of Health, which helped fund the research.
Genetic experiments typically focus on knocking out a single gene and seeing what happens. The drawback to that, Covert said, is that many of the questions biologists need to learn about “aren’t single-gene problems. They’re the complex result of hundreds or thousands of genes interacting.”
This situation has led to a yawning gap between information and understanding that can only be addressed by “bringing all of that data into one place and seeing how it fits together,” said Stanford bioengineering graduate student Jayodita Sanghvi, who co-authored the research. “You don’t really understand how something works until you can reproduce it yourself.”
The bacterium modelled is is a humble parasitic one known mainly for showing up uninvited in human urogenital and respiratory tracts. But it also has the distinction of containing the smallest genome of any free-living organism – only 525 genes, as opposed to the 4,288 of E. coli, a more traditional laboratory bacterium. The minimalism of its genome has made it the focus of several recent bioengineering efforts. Notably, these include the J. Craig Venter Institute’s 2008 synthesis of the first artificial chromosome.
“The goal hasn’t only been to understand M. genitalium better,” said Stanford biophysics graduate student Jonathan Karr, who also collaborated on the study. “It’s to understand biology generally.” Even at this small scale, the quantity of data that the researchers incorporated into the virtual cell’s code was enormous. The final model made use of more than 1,900 experimentally determined parameters.
The computational cell opens up procedures that would be hard to perform in a real organism, and opportunities to revisit experimental data, the researchers said. In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions.
Biologists hope computational models like this one could bring rational design to biology – allowing not only for computer-guided experimental regimes, but also for the wholesale creation of new microorganisms. “This is potentially the new Human Genome Project,” Karr said. “It’s going to take a really large community effort to get close to a human model.”
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