title: Elimination of thermodynamically infeasible loops in steady-state metabolic models.
abstract: The constraint-based reconstruction and analysis (COBRA) framework has been widely used to study steady-state flux solutions in genome-scale metabolic networks. One shortcoming of current COBRA methods is the possible violation of the loop law in the computed steady-state flux solutions. The loop law is analogous to Kirchhoff's second law for electric circuits, and states that at steady state there can be no net flux around a closed network cycle. Although the consequences of the loop law have been known for years, it has been computationally difficult to work with. Therefore, the resulting loop-law constraints have been overlooked. Here, we present a general mixed integer programming approach called loopless COBRA (ll-COBRA), which can be used to eliminate all steady-state flux solutions that are incompatible with the loop law. We apply this approach to improve flux predictions on three common COBRA methods: flux balance analysis, flux variability analysis, and Monte Carlo sampling of the flux space. Moreover, we demonstrate that the imposition of loop-law constraints with ll-COBRA improves the consistency of simulation results with experimental data. This method provides an additional constraint for many COBRA methods, enabling the acquisition of more realistic simulation results.
authors.affiliation: Bioinformatics and Systems Biology Program, University of California, San Diego, California.
authors.forename: Jan
authors.initials: J
authors.lastname: Schellenberger
authors.affiliation: Bioengineering Department, University of California, San Diego, California.
authors.forename: Nathan E
authors.initials: NE
authors.lastname: Lewis
authors.affiliation: Bioengineering Department, University of California, San Diego, California. Electronic address: palsson@ucsd.edu.
authors.forename: Bernhard Ø
authors.initials: BØ
authors.lastname: Palsson
mesh_terms: D004926:Escherichia coli / Q000235:genetics; D007700:Kinetics; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D009010:Monte Carlo Method; D013816:Thermodynamics