γ-聚谷氨酸生产菌株的鉴定及发酵培养基优化

目的:鉴定一株高产γ-聚谷氨酸(γ-polyglutamic acid,γ-PGA)的菌株,并优化其发酵培养基。方法:以实验室前期诱变筛选出的菌株N-2出发,通过16s rDNA核酸序列分析,对该菌株进行了鉴定;采用单因素实验、响应面设计对菌株的发酵培养基进行优化,最终确定最佳培养基配方。结果:经过16s rDNA序列分析,菌株N-2被鉴定为Bacillus subtilis。通过Plackett-Burman(PB)试验,筛选出3个显著影响γ-PGA产量的因素:葡萄糖、谷氨酸钠和K₂HPO₄·3H₂O;用最陡爬坡试验逼近最大产量区后,利用box-behnken试验获得响应曲面最优解,确定葡萄糖、谷氨酸钠和K₂HPO₄·3H₂O的最佳浓度分别为42.93、44.85、2.39 g/L。经过54 h发酵γ-PGA终产量为28.51 g/L,比优化前提高了34.48%。结论:响应面法试验次数少、周期短,可以快速优化发酵培养基成分,结果可靠,是提高产量的有效途径。

Identification and Optimization of Fermentational Condition of γ-Polyglutamic Acid Producing Strain

Objective:A strain with a high yield of γ-polyglutamic acid(γ-PGA)was identified,and its fermentation medium was optimized. Methods:Bacillus sp. N-2,a strain previous screened by mutation in our laboratory,was chosen as the starting strain,and then it was identified by its 16S rDNA sequence similarity analysis. In order to achieve a higher production of γ-PGA,the fermentation medium of the strain was optimized by single factor experiment and RSM(response surface method). Results:The result of 16s rDNA sequence analysis showed that the strain N-2 was Bacillus subtilis. In fermentation experiment,three factors(glucose,sodium glutamate,K₂HPO₄·3H₂O)that significantly affect the γ-PGA production of the strain were screened out using plackett burman test and their greatest response area were estimated by the design of steepest ascent approach;Futher,the extreme point of response surface was obtained by box-behnken design. The optimal conditions were as follows:glucose 42.93 g/L,sodium glutamate 44.85 g/L,K₂HPO₄·3H₂O 2.39 g/L. In this condition,the final yield of γ-PGA was 28.51 g/L after 54 h fermentation,which was 34.48% higher than before optimization. Conclusion:It needs less test using RSM,which can quickly optimize the fermentation medium components,get reliable results,and it is an effective way to increase PGA yield.