Genome-scale metabolic models have been widely used in bacterial evolution analysis, unknown gene function annotation, physiological metabolic phenotype analysis, and metabolic engineering strategy design. Flux Balance Analysis (FBA) is the core algorithm, which is used to calculate the flux distribution at steady state. However, since the essence of FBA is linear programming, in most cases there is inevitably an equivalent solution.
In collaboration with researchers from the Institute of Microbiology of the Chinese Academy of Sciences and the Tianjin Institute of Industrial Biotechnology, in order to solve the problem of equivalent solutions in FBA, according to the theory of non-equilibrium systems tending to maximize the direction of entropy generation, a new set of solutions, namely thermodynamics Optimal search algorithm (Thermodynamic Optimum Searching, TOS). Under the condition of ensuring the conservation of material energy, by maximizing the entropy generation rate of the system, minimizing the Gibbs free energy change of the biochemical reaction process, and making the biochemical reaction satisfy the second law of thermodynamics as much as possible, the FBA equivalent solution can be calculated Thermodynamic optimal solution. ,
The TOS algorithm was used to calculate the E. coli metabolic flux distribution, and the obtained results were compared with the measured data of 5 groups of 13C flux groups. It was found that the TOS algorithm can improve the prediction accuracy of FBA by 10.7% -48.5%. TOS can predict the paths that FBA cannot predict; or it can prove that some of the paths predicted by FBA contribute little to the actual flux distribution.
Using this algorithm, the thermodynamic driving force of biochemical reactions in the metabolic network can be accurately calculated, which provides a reference for theoretically designing, constructing and optimizing biochemical reaction pathways. The research results have been published online in Biotechnology and Bioengineering. (ZHU Yan, SONG Jiangning, XU Zixiang, SUN Jibin, ZHANG Yanping, LI Yin *, MA Yanhe. 2012. Development of thermodynamic optimum searching (TOS) to improve the prediction accuracy of flux balance analysis. Biotechnology and Bioengineering, DOI: 10.1002 /bit.24739)
The first author of the thesis is doctoral student Zhu Yan, and the instructor is researcher Li Yin. The research was funded by the 973 project's major scientific problem-oriented project "Synthetic Cell Factory".
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