Metabolism, Maths, Medicine: If Bacteria Were Calculable
Pseudomonas aeruginosa lives almost everywhere. In water, in the soil, on and in us, and in hospitals. The microbe is especially problematic here, as it can attack and render ill patients with immune deficiency in particular. "Bacteria that exist everywhere naturally have a highly variable metabolism, which makes them extremely flexible," says Martins dos Santos. The talk is of a metabolic convertibility. In the case of Pseudomonas this is based upon a genome that is very large for bacteria. Martins dos Santos: "This means that the bacterium is very robust, versatile and reproduces quickly."
The genome of the Pseudomonas strain PAO1 was already completely sequenced in 2000. However, mere knowledge of the precise sequence of the DNA constituents in genetic material does not make germs truly susceptible to newly synthesised antibiotics or other therapeutic approaches. Genes supply the basis for the construction plans for a cell but only make a limited statement with regard to its biological implementation. "We need to know what individual triggers there are for genetic activity and whether their products such as certain enzymes have an effect in cell metabolism. And we need to know this for each time point and each position of the metabolism," states Martins dos Santos. Consequently, he does not only asks what role an enzyme plays in cell metabolism, he really wants to know how it embedded in a the whole metabolic network and whether he can discover it in the rhythm of the cell cycle - he quantifies.
Vítor Martins dos Santos and his team, together with collaborators at the University of Virginia, therefore investigated which functions and reactions can be directly or indirectly influenced by an enzyme or other genetic products. When the HZI researchers had discovered this for all genetic products, they depicted the processes in the form of a network. This is known as a so-called genome-based, metabolic network.
"Thus, we represented the data of a large bacterial genome in the form of a metabolic network," summarises the researcher. "Now we are able to partially forecast what happens when we interfere with the metabolism of Pseudomonas here or there." These simulations should provide references for medicinal interventions, which are often scarce, in particular with regard to infections. "Research has been carried out into cells and germs for over 330 years and yet they are still a 'black box', with no-one really certain what is happening inside," says Martins dos Santos, inferring that system-biological approaches such as these will now be able to make visible what is actually going on inside the cells.
Original publication: MA Oberhardt et al; "Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginose PAO1."; J. Bacteriol 2008.
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