Development of a metabolic network design and optimization framework incorporating implementation constraints: a succinate production case study.
We have developed a pathway design and optimization scheme that accommodates genetically and/or environmentally derived operational constraints. We express the full set of theoretically optimal pathways in terms of the underlying elementary flux modes and then examine the sensitivity of the optimal yield to a wide class of physiological perturbations. Though the scheme is general it is best appreciated in a concrete context: we here take succinate production as our model system. The scheme produces novel pathway designs and leads to the construction of optimal succinate production pathway networks. The model predictions compare very favorably with experimental observations.
Cox
Steven J
SJ
Department of Computational and Applied Mathematics, Rice University, Houston, TX 77001,USA.
Shalel Levanon
Sagit
S
Sanchez
Ailen
A
Lin
Henry
H
Peercy
Brad
B
Bennett
George N
GN
San
Ka-Yiu
KY
D003198:Computer Simulation; D004926:Escherichia coli / Q000378:metabolism*; D008954:Models, Biological; D019802:Succinic Acid / Q000378:metabolism*
D019802:Succinic Acid