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吩嗪-1-羧酸(phenazine-1-carboxylic acid,PCA)是促进根际生长假单胞菌分泌的重要抗菌物质。采用Plackett-Burman(PB)设计和响应面法(response surface method,RSM)对假单胞菌株M18(Pseudomonas sp.M18)的gacA基因突变株M18G的次级代谢产物PCA发酵的营养条件进行建模。运用Plackett-Burman(PB)设计试验,从12个营养成分中筛选出4个关键的组分,进而采用RSM法对这4个因素进行中心组合设计试验,建立回归方程并进行统计学分析,绘制各营养因子之间的关系图。实验结果表明:建立的模型能合理地模拟并优化发酵中各参数及其浓度,确定发酵培养基的成分和浓度为:黄豆粉33.4g/L,葡萄糖12.7g/L,大豆蛋白胨10.9g/L和乙醇13.8g/L,M18G菌株经60h发酵培养,最高PCA产率能达到1.89g/L,比优化前提高了6倍左右。各营养因子的等值线图表明黄豆粉和乙醇在PCA高产发酵中起到更为关键的作用,因此提供了提高PCA发酵产量的有效方法,并为其未来商业化应用奠定了基础。
Phenazine-1-carboxylic acid (phenazine-1-carboxylic acid, PCA) is to promote rhizobacterium growth of Pseudomonas secretion of important antibacterial substances. The nutritional conditions for the PCA fermentation of the secondary metabolite of the gacA gene mutant M18G from Pseudomonas sp. M18 were modeled using the Plackett-Burman (PB) design and the response surface method (RSM) . Using Plackett-Burman (PB) design test, four key components were screened out from 12 nutrients, and then the RSM method was used to test the four factors in the central design. The regression equations were established and statistically analyzed. The relationship between nutritional factors map. The experimental results show that the model can reasonably simulate and optimize the parameters of fermentation and its concentration, and determine the composition and concentration of fermentation medium as: 33.4g / L soybean powder, 12.7g / L glucose, 10.9g / L soybean peptone And ethanol 13.8g / L, M18G strain after 60h fermentation, the highest PCA yield can reach 1.89g / L, six times higher than before the optimization. Contour plots of various trophic factors show that soy flour and ethanol play a more critical role in the high-yielding fermentation of PCA, thus providing an efficient way to increase the yield of PCA fermentation and lay the foundation for its future commercial use.