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Grid computing aids battle to reduce groundwater toxicity

Ball-and-stick model of the 1,2,3-trichloropropane molecule. Image courtesy Wikimedia Commons.

For centuries, humankind has created and harnessed various chemicals in industry and research. They are not all benign, though, and contamination of land and water is a potential risk. Millions of years of evolution have created an astonishing diversity of bacteria that can process countless naturally existing chemicals into more harmless substances. These too have been taken advantage of, but some chemical compounds used by humans do not exist naturally.

TCP (1,2,3-trichloropropane) is one such compound. First created during the industrial revolution, it is now used as a pesticide and in chemical manufacturing. It is also toxic and persistent. Once released into groundwater, it can stay there for over 100 years.

A potential solution is a bacterium that could convert TCP into a harmless compound, quickly and cost-effectively. Now, a group of scientists at Loschmidt Laboratories of Masaryk University in the Czech Republic have used the grid to engineer synthetic bacteria that can metabolize TCP into harmless glycerol.

The team, led by Jan Brezovsky and Zbynek Prokop, used a combination of grid-powered mathematical modeling and laboratory experiments to design and test a five-step metabolic pathway for a new bacterium. The key is balancing the activity of multiple enzymes to keep the bacterium alive, while sustaining a high processing rate. The team was also able to engineer new enzyme variants, which adds further modeling complications regarding what variants to create and their most effective combinations and concentrations.

The scientists used computer-assisted directed evolution to predict and plan the creation of the enzyme variants. These were created and tested for their performance. The values obtained were then used in a model that simulates the vast number of possible enzyme ratios, in order to find the optimum combination for balancing toxicity and glycerol production.

The team consumed around 100 CPU days using the grid computing resources provided by Metacentrum, the National Grid Infrastructure of the Czech Republic. The grid-assisted approach offered a twofold advantage: “We could explore combinations in much higher detail since we could afford to run variants with minimal mutual differences,” says Jiri Damborsky, one of the scientists in the group. More importantly, grid resources enabled tight interaction between rounds of experimental work and the ongoing refinements and predictions of the model. “Taking into account the requirements for high accuracy and the time demand of computationally intensive calculations of differential equations, grid calculation was the only reasonable choice,” he adds.

The predictions of the model were used to create bacterial strains containing the optimal enzyme ratios. The behavior of these real-life bacteria matched predictions closely. The model also revealed limitations of specific enzyme variants, and predicted ways to improve pathway function. Damborsky concludes: “Our study highlights the potential of forward engineering of micro-organisms for the degradation of toxic anthropogenic compounds, and the essential role of grid computing to design complex biological systems.”


This is an edited version of a case study that was originally published on the European Grid Infrastructure (EGI) website, here.

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