title: Bayesian-based selection of metabolic objective functions.
abstract: BACKGROUND
  A critical component of in silico analysis of underdetermined metabolic systems is the identification of the appropriate objective function. A common assumption is that the objective of the cell is to maximize growth. This objective function has been shown to be consistent in a few limited experimental cases, but may not be universally appropriate. Here a method is presented to quantitatively determine the most probable objective function.
  
  
  RESULTS
  The genome-scale metabolism of Escherichia coli growing on succinate was used as a case-study for analysis. Five different objective functions, including maximization of growth rate, were chosen based on biological plausibility. A combination of flux balance analysis and linear programming was used to simulate cellular metabolism, which was then compared to independent experimental data using a Bayesian objective function discrimination technique. After comparing rates of oxygen uptake and acetate production, minimization of the production rate of redox potential was determined to be the most probable objective function. Given the appropriate reaction network and experimental data, the discrimination technique can be applied to any bacterium to test a variety of different possible objective functions.
  
  
  BACKGROUND
  Additional files, code and a program for carrying out model discrimination are available at http://www.engr.uconn.edu/~srivasta/modisc.html.
authors.affiliation: Department of Chemical, Materials and Biomolecular Engineering, University of Connecticut, 191 Auditorium Road U3222, Storrs, CT 06269-3222, USA.
authors.forename: Andrea L
authors.initials: AL
authors.lastname: Knorr
authors.forename: Rishi
authors.initials: R
authors.lastname: Jain
authors.forename: Ranjan
authors.initials: R
authors.lastname: Srivastava
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D049109:Cell Proliferation; D003198:Computer Simulation; D016002:Discriminant Analysis; D004734:Energy Metabolism / Q000502:physiology*; D004926:Escherichia coli / Q000502:physiology*; D029968:Escherichia coli Proteins / Q000378:metabolism*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D019802:Succinic Acid / Q000378:metabolism
chemical_list: D029968:Escherichia coli Proteins; D019802:Succinic Acid