An experiment designed to show how a usually innocuous bacterium regulates the expression of an unnecessary gene for green color ha...">
In a paper published in the Feb. 16 issue of Nature, researchers at Boston University (BU) and the University of California, San Diego (UCSD) reported that computer modeling predicted the new phenomenon before they confirmed it in laboratory experiments. The group led by James J. Collins, a biomedical engineering professor at BU, and Jeff Hasty, a bioengineering professor at UCSD, reported that the rise and fall in the amount of green-fluorescence protein in computer modeling matched the pattern recorded in E. coli cells grown in various laboratory conditions.
The researchers were surprised that cell-to-cell variation in the expression of the synthetic
Variability in gene expression could offer distinct survival advantages to a bacterium. Like a cruise ship whose life boats have been stocked with different combinations of food, first-aid kits, rain jackets, and flotation devices, a microscopic version of Survivor could occur in which only those individual bacterial cells with opportune combinations of proteins are able to weather harsh growth conditions in a pond or even inside a human body.
“This phenomenon could be relevant to bacterial ‘persisters’ – dormant cells that are highly resistant to antibiotics,” said Collins. “Many bacterial pathogens can generate these persisters, which over many months can become the source of chronic infections. We don’t understand how persisters arise, but we think this unexpected gene-expression variability in bacterial cells is an interesting phenomenon that should be explored.”
The group of researchers came up with the novel finding by using a relatively new research
The authors say their findings demonstrate the value of a so-called “bottom-up” approach to synthetic biology: models of relatively simple cellular processes can be used to predict the behavior of larger, more complex ones.
“We’re excited by this study because the model itself led to a counterintuitive prediction that
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