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Fermentation Conditions Optimization And Kinetics For Phenazine-1-Carboxylic Acid Production By Pseudomonas Sp. M18G

Posted on:2009-10-22Degree:MasterType:Thesis
Country:ChinaCandidate:L HeFull Text:PDF
GTID:2121360242477010Subject:Biochemical Engineering
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Pseudomonas sp. M18 is a rhizomatic fluorescent bacterium that can produce two antibiotics, phenazine-1-carboxylic acid (PCA) and pyoluteorin (Plt). M18G, a mutant strain in gacA gene of M18, was constructed by means of homologues recombination. It was found that in M18G Plt production was inhibited completely, but PCA production was increased by up to 30-fold above that in the wild-type strain.To further increase the production of PCA by M18G, single factor analysis was accomplished first. Glucose was chosen as the optimal carbon source and soy peptone as the nitrogen source. Large amounts of PCA were yieled by a 10.5-h-old culture and a 5% inoculum. A Plackett-Burman design revealed that glucose, soy peptone and NaCl were the most significant factors in PCA fermentation. Response surface methodology (RSM) and artificial neural network (ANN) models involving the significant factors were developed using common data. The prediction accuracy of ANN was slightly higher compared to RSM. The genetic algorithm (GA) was used to search the optimal input space of the trained ANN model and find the corresponding PCA yield. The optimum composition was found to be: glucose 34.3 g/L, soy peptone 43.2 g/L, NaCl 5.7 g/L, and the predictive maximum PCA yield reached 980.1μg/mL. The optimized medium allowed PCA yield to be increased by 43.6%, from 673.3 to 966.7μg/mL, after verification experiment tests.PCA fermentation kinetics was investigated. Kinetic models based on the modified Logistic and Luedeking-Piret equations were developed, providing a good description of temporal variations of biomass (X), product (P) and substrate (S) in PCA fermentation. These models were applicable in batch fermentations with initial glucose concentration from 15 to 30 g/L.Operation conditions of PCA fermentation was investigated based on kinetic models anysis. A pulse feeding strategy was used to maintain the glucose concentration between 14-16 g/L and made PCA yield a 12.6% increasement. In repeated fed-batch culture, the fresh culture was inoculate with 20% centrifugated cells. Under this condition, the productivity of PCA was up to 27.5μg/mL·h, which was a 13.6% increasement than that of the batch culture.
Keywords/Search Tags:Pseudomonas sp. M18G, phenazine-1-carboxylic acid (PCA), artificial neural network (ANN), fermentation kinetic model, optimization
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