(626ab) Rigorous Proton Balancing and Other New Tools to Reduce the Phenotypic Solution Space of a Genome-Scale Model

The usefulness of genome-scale modeling using flux balance analysis is well known.  The resulting phenotypic solution space consists of all possible flux solutions to the flux balancing problem.  Here, three methods are discussed that significantly reduce the size of the phenotypic solution space and allow the user to zero in on unique metabolic solutions.  The first is by considering the rate at which protons enter and leave the cell.  This is largely dictated by the mechanisms of proton exchange inherent to the organism of study and the extracellular environment.  This is currently leading to purely kinetic models to describe this process in several organisms.  The second method presented here is a more rigorous method of proton balancing inside the cell.  The issues of proton balancing given reaction notations common to biochemical databases (e.g., KEGG) are well-documented.  However, the solutions presented in the literature are also not rigorously correct.  Proton balancing should be done considering mixtures of protonated and de-protonated states for compounds, as dictated by their pKa values.  Here, it is shown how this treatment impacts overall quantitative solutions to genome-scale models.  A tutorial is also presented regarding how to obtain and predict necessary model constants for a large metabolic network of complex molecules.  Finally, optimization of the biomass equation has shown to dramatically impact genome-scale model solutions.  For example, artificially setting the ATP maintenance coefficient has been found to let a user achieve a wide number of quantitative solutions.  These issues will be discussed in detail and a variety of possible solutions and guidelines will be presented.  Results will focus on the production of biobutanol from Clostrdidium acetobutylicum ATCC 824.