首页|Metabolic flux simulation of microbial systems based on optimal planning algorithms

Metabolic flux simulation of microbial systems based on optimal planning algorithms

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
  • 维普
The genomic scale metabolic networks of the microorganisms can be constructed based on their genome se-quences,functional annotations,and biochemical reactions,reflecting almost all of the metabolic functions.Mathematical simulations of metabolic fluxes could make these functions be visualized,thereby providing guidance for rational engineering design and experimental operations.This review summarized recently devel-oped flux simulation algorithms of microbial systems.For the single microbial systems,the optimal planning algorithm has low complexity because there is no interaction between microorganisms,and it can quickly simulate the stable metabolic states through the pseudo-steady hypothesis.Besides,the experimental conditions of single microbial systems are easier to reach or close to the optimal states of simulation,compared with pol-ymicrobial systems.The polymicrobial culture systems could outcompete the single microbial systems as they could relieve metabolic pressure through metabolic division,resource exchange,and complex substrate co-utilization.Besides,they provide varieties of intracellular production environments,which render them the po-tential to achieve efficient bioproduct synthesis.However,due to the quasi-steady hypothesis that restricts the simulation of the dynamic processes of microbial interactions and the algorithm complexity,there are few re-searches on simulation algorithms of polymicrobial metabolic fluxes.Therefore,this review also analyzed and combed the microbial interactions based on the commonly used hypothesis of maximizing growth rates,and studied the strategies of coupling interactions with optimal planning simulations for metabolism.Finally,this review provided new insights into the genomic scale metabolic flux simulations of polymicrobial systems.

Optimal planning algorithmMetabolic flux simulationMicrobial systemInteraction

Chen Yang、Boyuan Xue、Yiming Zhang、Shaojie Wang、Haijia Su

展开 >

State Key Laboratory of Chemical Resource Engineering,Beijing Key Laboratory of Bioprocess,Beijing Advanced Innovation Center for Soft Matter Science and Engineering,Beijing University of Chemical Technology,Beijing,100029,China

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

2021YFC21007002183800131961133018

2023

10.1016/j.gce.2022.04.003

绿色化学工程(英文)
中国科学院过程工程研究所

绿色化学工程(英文)

CSCD
ISSN：
年,卷(期)：2023.4(2)
  • 131