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Rewriting Life

Harnessing the Power of Bacteria

Maps that identify the genetic networks controlling cells could lead to better antibiotics and bioremediation methods.

A new method to map all the regulatory interactions in a cell will help scientists better understand the workings of bacteria. Researchers from Boston University tested the method on E. coli, and now they plan to apply it to microorganisms involved in everything from lung infections to bioremediation. The resulting maps could lead to better antibiotics and more-effective ways to contain radioactive waste.

Researchers have created a map showing regulatory interactions of E. coli, a commonly used lab bacteria. Genes are represented by a circle that is linked to the genes it controls. Each controller gene can be in charge of anywhere from a few to hundreds of genes.

“Say you’re interested in producing ethanol and want to optimize that process,” says Jim Frederickson, chief scientist in the Department of Energy’s (DOE) Genomes to Life Program. “This is one tool that allows you to redesign an organism’s metabolism to optimize that process. It has potential for a variety of biotech applications.”


Bacteria sense and respond to their environment through an intricate network of genes and proteins that turn other genes on and off. The system is extremely complex because bacteria have to deal with large fluctuations in their surroundings–competition from other bacteria and changes in food sources or in the surfaces they live on. “In E. coli, over 300 proteins are directly involved in the control of genes, each of these controlling from one to hundreds of different genes,” says Tim Gardner, a bioengineer at Boston University who led the work.

Traditional methods of understanding these networks involve disrupting one or a few genes and then observing changes in the bacteria’s behavior or response to the environment. “We wanted to come up with a more efficient way to determine how that control structure is organized,” says Gardner. Over the past few years, scientists have compiled a massive database of genetic information on E. coli. They’ve used special chips that record changes in the expression of thousands of genes when the bacteria are exposed to different conditions, such as starvation, excess food, low oxygen levels, or a variety of chemicals. Gardner and team developed a computer algorithm to analyze this data and identify genes that change in similar ways when exposed to the same environmental conditions and are therefore likely part of the same regulatory circuit.

The end result is a massive map, published this month in the journal PLoS Biology, identifying a thousand regulatory circuits in E. coli. About 300 of these circuits had been previously identified with standard techniques, confirming that the algorithm can accurately predict these regulatory interactions.

“This is an important advance and a very interesting step toward the full picture of the circuitry of E. coli,” says Kim Lewis, a microbiologist at Northeastern University, in Boston. “But the main importance probably lies in applying this algorithm to other bacteria, like human pathogens, where our knowledge is limited.” Gardner and colleagues are creating a regulatory map for Pseudomonas aeruginosa, a bacterium that infects people with cystic fibrosis and easily becomes resistant to both the immune system and antibiotics. Researchers hope that understanding the regulatory circuits involved in antibiotic resistance will help in the design of better drugs.

They are also working on a map for Shewanella oneidensis, an electricity-producing bacterium. The bacteria normally produce only tiny amounts of energy, and attempts to manipulate single genes to increase yield have shown little success. “Hopefully, the map will show what knobs we can turn to optimize current production,” says Gardner.

At the DOE, Frederickson is studying how Shewanella bacteria use environmental contaminants, such as heavy metals and radioactive waste, in place of oxygen, converting the compounds into forms less likely to spread throughout the area. The findings could ultimately be used to help clean up Superfund and other hazardous-waste sites.

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