Metabolic networks in motion: 13C-based flux analysis.
Many properties of complex networks cannot be understood from monitoring the components--not even when comprehensively monitoring all protein or metabolite concentrations--unless such information is connected and integrated through mathematical models. The reason is that static component concentrations, albeit extremely informative, do not contain functional information per se. The functional behavior of a network emerges only through the nonlinear gene, protein, and metabolite interactions across multiple metabolic and regulatory layers. I argue here that intracellular reaction rates are the functional end points of these interactions in metabolic networks, hence are highly relevant for systems biology. Methods for experimental determination of metabolic fluxes differ fundamentally from component concentration measurements; that is, intracellular reaction rates cannot be detected directly, but must be estimated through computer model-based interpretation of stable isotope patterns in products of metabolism.
Sauer
Uwe
U
Institute of Molecular Systems Biology, ETH Zurich, Switzerland. sauer@ethz.ch
D000818:Animals; D001698:Biomedical Engineering; D001709:Biotechnology / Q000379:methods; D002250:Carbon Radioisotopes / Q000493:pharmacokinetics*; D003198:Computer Simulation; D019143:Evolution, Molecular; D006801:Humans; D007424:Intracellular Fluid / Q000000981:diagnostic imaging; D053858:Metabolic Networks and Pathways / Q000187:drug effects / Q000502:physiology*; D008954:Models, Biological; D011849:Radioactive Tracers; D011877:Radionuclide Imaging; D015398:Signal Transduction
D002250:Carbon Radioisotopes; D011849:Radioactive Tracers