Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session F24: Noise-Driven Dynamics in Far-From-Equilibrium Systems I
8:00 AM–11:00 AM,
Tuesday, March 3, 2020
Room: 401
Sponsoring
Units:
GSNP DBIO
Chair: Stephen Teitsworth, Duke University
Abstract: F24.00004 : Large scale kinetic modeling of metabolic networks*
Presenter:
Xiaomei Zhu
(Shanghai University)
Authors:
Yong-Cong CHEN
(Shanghai University)
Xiaomei Zhu
(Shanghai University)
Ping Ao
(Shanghai University)
Minjuan Xu
(Shanghai Jiaotong University)
While the biochemistry of metabolism in many organisms is well studied, details of the metabolic dynamics are yet fully explored.
Unless the parameters of a vast number of enzyme-catalyzed reactions happened to fall into very special ranges, a kinetic model on a large metabolic network would fail to reach a steady state.
Acquiring adequate in vivo kinetic parameters experimentally has always been an obstacle.
Approach:
A stable metabolic network can be systematically established via a biologically/evolutionally motivated regulatory process.
May be understood via a landscape description of metabolism as a stochastic system, which draws enzymatic parameters towards stable phase spaces.
Allows explicit thermodynamics constraints on concentrations and optimal balance of efficiency vs viability (i.e. stability/fitness/robustness).
The strategy was applied sucessfully to the central metabolism of Methylobacterium extorquens AM1 and the secondary metabolism and metabolic switches in Streptomyces xiamenensis 318.
*The work was partially supported by the Natural Science Foundation of China No. 91329301 and No. 91529306 (PA), No. 81273404 and No. 81473105 (MJX).
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