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New model could increase genomic knowledge of metabolic profile
Researchers have developed a global model that is expected to enable future research of human metabolism and its role in health and disease, according to data published in Nature Biotechnology.
The model may explain the relationship between individual patients’ metabolic profile and their reaction to environmental or dietary factors, according to a press release.
According to study researcher Nicolas Le Novère, PhD, of the Babraham Institute in Cambridge, United Kingdom, the model contains more than 8,000 molecular species and 7,000 chemical reactions.
“This research is the second important stage of our understanding of the human genome,” study researcher Pedro Mendes, PhD, a professor of computational systems biology at the University of Manchester’s School of Computer Science, said in a press release. “If the sequencing of the human genome provided us with a list of the biological parts, then our study explains how these parts operate within different individuals.”
The international study, conducted by researchers from the United Kingdom, Iceland, San Diego and Berlin, mapped 65 different human cell types into Recon 2, a community-driven, consensus “metabolic reconstruction,” which is a comprehensive representation of human metabolism applicable to computational modeling, the researchers wrote. In addition, they used proteomics data to generate cell type-specific metabolic models and investigated them for functional properties.
“To understand the behavior of a system, one must have a model of it,” study researcher Douglas B. Kell, PhD, professor of bioanalytical science at the Manchester Institute of Biotechnology, said in the press release. “By converting our biological knowledge into a mathematical model format, this work provides a freely accessible tool that will offer an in-depth understanding of human metabolism and its key role in many major human diseases.”
Disclosure: The researchers report no relevant financial disclosures.
Perspective
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Theory has occupied a relatively minor place in the biological sciences, in contrast to both physics and chemistry. This paper reports the construction of Recon 2, a mathematical model of human organism-level metabolism. Drawing on a wide array of existing data, and using a manual, face-to-face, community curation effort, Recon 2 has improved considerably on Recon 1. It includes approximately twice as many reactions, 80% more metabolites, and 30% more genes than Recon 1, and agrees much better with experimental data. However, there is still much ground to cover before a truly adequate mathematical model of human metabolism is generated. Recon 2 still contains many "dead end" metabolites, regarding whose generation is included but whose clearance is not. It still performs poorly at predicting down-regulated metabolites. Recon 2 and other human metabolism models still include substantial non-overlapping reactions and compounds.
How will this work impact clinical practice? In the short term, it will only be used in the research setting. Its primary utility will be to generate hypotheses for experimental tests of potential drugs. The model will be particularly useful for examining cross-talk between pathways, e.g. between ion transport and energy utilization. Given the expense of drug development, models such as this one will facilitate the "quick kill" of potential drugs before development expenses pile up.