The model integrates tissue-specific information from healthy or diseased organs and matches it to an existing model of the global human metabolic network to predict metabolic tissue behaviour. Their results, shared with Markus Herrgard and Bernhard Palsson from the University at San Diego, "establish a computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner", stated Professor Ruppin.
The computational model describes metabolism in ten different human tissues, exposing the functions in the body responsible for metabolism - a set of chemical reactions occurring in living organisms that allows tissues to grow, maintain their structures, and function and respond to other bodily cues. And while the research published focuses on ten specific tissues, the tool can be expanded and applied to other tissues, then potentially to entire organs.
"The previous model of human metabolism was a generic one, which did not describe how the metabolism of different tissues work", stated Tomer Shlomi. "Now we can provide large scale descriptions as to how tissues metabolize different compounds and how metabolism actually works in individual organs like the heart, liver, brain or pancreas."
Building on these results, the Tel Aviv University team are now working on developing tools for the discovery of biomarkers - metabolites that can be measured in the blood and urine - that are associated with different diseases. The team is developing computational methods for identifying novel metabolic biomarkers that may be used for diagnosing an array of genetic metabolic disorders - including such disorders with relatively higher incidence in Jewish populations such as G6PD and Tay-Sachs.
More generally, this basic research provides scientists with important knowledge of the metabolism of different body tissues and organs. The consequences of this endeavour and its basic motivation is to help drug developers as they explore new drug targets. The current research is at the basic science level, but such research may lead to unforeseen applications.
Today's cancer-fighting drugs, for example, kill both cancerous and healthy cells. When more becomes known about the metabolism of cancer in different tissues via a combination of experimental and computational studies of the kind described in the research, then hopefully more effective and targeted drugs could be built, according to Professor Ruppin.
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