Metabolic Analysis And Process Optimization For Microbial Conversion Of Glycerol Into 1,3-propanediol By Klebsiella Pneumoniae

Recently,the vigorous development of bioeconomy demands more for the biorefinery field where the bio-based chemicals are produced.In past 30 years,the production of 1,3-propanediol(1,3-PD)by glycerol fermentation has attracted more and more attention.There are several advantages,such as eco-friendly,renewable and waste recycling.But compared to traditional chemical production,biological method is still restricted for the cost.The issue that needs to be solved urgently is that glycerol conversion rate and productivity are not satisfactory.In this thesis,aiming to the process of producing 1,3-PD of glycerol fermentation by Klebsiella pneumoniae,the mathematical modeling was used to analyze the metabolic process,as well as the dynamic behavior of the fermentation process,besides,the optimal control strategy was also proposed.The main research contents are as follows:Firstly,an optimized calculation method was constructed on basis of dynamic flux balance analysis by combining genome-scale flux balance analysis with a kinetic model of extracellular metabolites.Through optimizing calculation and analysis,a more completely expanded metabolic pathway was obtained,which included the previously reported metabolic pathway and additional three pathways or nodes:a pentose phosphate pathway(PPP)elicited at the dihydroxyacetone(DHA)node to provide more reducing equivalents;a branch of synthetic amino acids at the 3-phosphoglycerate(3PG)node;and the a-ketoglutarate site in the tricarboxylic acid(TCA)cycle leading to anabolic pathways for glutamate and other amino acids.On this basis,the relationships between the dynamic flux distribution of the important nodes in the metabolic pathway and the yield of 1,3-PD were analyzed.The results showed that,dynamic flux change from DHA to the PPP is positively correlated with the yield,and variation in flux in the TCA was also positively correlated with the yield of 1,3-PD.In addition,it was found that the TCA cycle formed a complex coupling relationship with other metabolic pathways through a-ketoglutarate acid and cysteine,which was correlated with the yield of 1,3-PD.Moreover,the influence of the feedback loop formed by the tetrahydrofolate on the flux change of TCA in the amino acid anabolic pathway was examined.Secondly,the ensemble modeling approach was used to reduce the model's uncertainty for fermentation process,and effectively improve its prediction performance.Through sensitivity analysis,the parameters having significant influence on the model were determined as the adjustable parameters for the ensemble modeling.After comparison,the appropriate threshold coefficient of the model error was determined,and the sampling method was used to generate as many equivalent parameter sets as possible.On the basis of parallel computing,the application of ensemble modeling was carried out.Compared with the traditional simulation using single parameter set,the ensemble modeling method achieved the lower relative error between the prediction and the experimental value and the greatly improved model prediction performance.In the continuous fermentation process,the average relative error between the predicted and experimental measurements o was reduced from the original 11.90%to 7.95%by using ensemble modeling.Moreover,the optimal productivity and yield of 1,3-PD and the corresponding operating conditions were obtained,respectively.In the batch process,the maximum productivity was 37.45 mmol·L-1·h-1,and the yield was 0.70 mol·mol-1,and the corresponding initial glycerol concentrations were 1020 and 1070 mmol·L-1,respectively.In the continuous process,the maximum productivity was 93.94 mmol·L-1·h-1,and the optimal operating conditions were the initial glycerol concentration of 780 mmol·L-1 and the dilution rate of 0.23 h-1.Besides,the optimal yield was 0.68 mol·mol-1,and the corresponding initial glycerol concentration is 880 mmol·L-1,and the dilution rate was 0.09 h-1.Finally,the multi-steady state and oscillation characteristics of the single-stage and cascade fermentation culture model were analyzed by mathematical method.The results showed that the multi-steady state phenomenon will occur under different initial glycerol concentrations or dilution rates.Furthermore,through two-factor analysis,the critical region of multi-steady state was given,and the steady state located internal critical region was not stable.After that,the dilution rate of each stage and initial glycerol concentration in the cascade fermentation process were optimized by mathematical programming method,and the optimal operating conditions were obtained.In addition,based on the feedback control scheme in the control theory,the dilution rate control strategy influenced by the concentration of residual glycerol and product 1,3-PD was designed and optimized which can be used as the feeding scheme for continuous culture in practice.The controlled dilution rate greatly reduces the system's settling time while increasing the product concentration.During the single-stage and cascade fermentations,the settling time was shortened from 77.82/53.66 h to 31.24/22.68 h,which significantly reduced the loss of glycerol in the early stage of fermentation,while the productivity was increased.In summary,based on the mathematical simulation,the glycerol metabolic pathway of K.pneumoniae was further analyzed,the uncertainty of the model was overcome,the predictive ability was improved,and the fermentation process was optimized and controlled.These work provide theoretical guidance for improving the fermentation performance of 1,3-PD and have potential in application.