Analysis and prediction of the effect of uncertain boundary values in modeling a metabolic pathway

The integration of large quantifies of biological information into mathemat ical models of cell metabolism provides a way for quantitatively evaluating the effect of parameter changes on simultaneous, coupled, and, often, coun teracting processes. From a practical point of view, the validity of the mo del's predictions would critically depend on its quality. Among others, one of the critical steps that may compromise this quality is to decide which are the boundaries of the model. That is, we must decide which metabolites are assumed to be constants, and which fluxes are considered to be the inpu ts and outputs of the system, in this article, we analyze the effect of the experimental uncertainty on these variables on the system's characterizati on. Using a previously defined model of glucose fermentation in Saccharomyc es cerevisiae, we characterize the effect of the uncertainty on some key va riables commonly considered to be constants in many models of glucose metab olism, i.e., the intracellular pH and the pool of nucleotides. Witt-rout co nsidering if this variability corresponds to a possible true physiological phenomenon, the goal of this article is to illustrate how this uncertainty may result in an important variability in the systemic responses predicted by the model. To characterize this variability, we analyze the utility and limitations of computing the sensitivities of logarithmic-gains (control co efficients) to the boundary parameters. With the exception of some special cases, our analysis shows that these sensitivities are good indicators of t he dependence of the model systemic behavior on the parameters of interest. (C) 2000 John Wiley & Sons, Inc.