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Researchers at the University of California San Diego have developed a genome-scale model that can accurately predict how E. coli bacteria respond to temperature changes and genetic mutations. The work is aimed at providing a comprehensive, systems-level understanding of how cells adapt under environmental stress. The work has applications in precision medicine, where adaptive cell modeling could provide patient-specific treatments for bacterial infections.
A team led by Bernhard Palsson, a professor of bioengineering at UC San Diego, published the work on Oct. 10 in Proceedings of the National Academy of Sciences.
Order - Control - Living - Cells - Mechanisms
"In order to have full control over living cells, we need to understand the fundamental mechanisms by which they survive and quickly adapt to changing environments," said Ke Chen, a postdoctoral researcher at UC San Diego and the study's first author.
A fundamental principle behind this work is that changes in the environment cause changes in a cell's protein structure. For example, higher temperatures destabilize protein molecules. The new genome-scale computational model, called FoldME, predicts how E. coli cells respond to temperature stress and then reallocate their resources to stabilize proteins. "The more the proteins destabilize, the more resources are devoted to re-stabilize them, making resources less available for growth and other cellular functions," Palsson explained.
FoldME - Team - Structures - Protein - E
To construct FoldME, the team first compiled the structures of all the protein molecules in E. coli cells and then integrated that data into existing genome-scale models of metabolism and protein expression for E. coli. Next, they calculated a biophysical profile that represents how well each protein folds at different temperatures. Since proteins usually need small molecules called chaperones to help them fold at high temperatures, the researchers also incorporated chaperone-assisted folding reactions into the model. They then set the model to maximize cell growth rate.
FoldME accurately simulated the response of E. coli cells throughout a wide...
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