摘要
pH值是影响酵母乙醇发酵的重要因素。应用拉曼光谱初步分析不同初始pH值对乙醇发酵过程的影响。结果显示:1)在3.0、4.5、6.5三个不同初始pH值的培养基中,pH 4.5下乙醇产量最高,pH 3.0下最低。2)在发酵的前15h,不同初始pH值下的酵母细胞生物大分子的拉曼信号变化波动大;后期,pH 3.0下胞内脂类和蛋白质的拉曼信号最强,pH 6.5最弱;显示在低pH值环境下部分底物可能被转化为胞内储藏物质。3)主成分分析显示,pH值对酵母细胞生理状态的影响从发酵的初始阶段就开始;1440cm-1和1600cm-1峰一直是影响主成分PC1、PC2、PC3分值的主要特征峰;说明pH环境可能影响了酵母细胞的脂类物质合成和细胞的呼吸代谢,进而影响了底物的代谢方向和产物的合成。结果表明,拉曼光谱和单细胞分析可以用于剖析微生物发酵过程的生理机制,为乙醇发酵提供全新的参考信息。
The pH level is a prominent factor affects the ethanol fermentation. Optical tweezers Raman spectroscopy is used to analyze the process of ethanol fermentation at the initial pH levels of 3.0, 4.5, 6.5. Major results from this work are as follows.. 1) The pH 4.5 level get the highest ethanol production and the pH 3.0 get the lowest one. 2) Raman intensities of bio-macromolecules of yeast cells at all pH levels exhibite dramatic changes in the first 15 hours. However, at the later stage of the fermentation, the pH 3.0 level displayes strong Raman intensities of intracellular lipids and proteins while pH 6.5 level shows weak. This indicates that a portion of substrate may be transformed into intracellular storage material by yeast cells at lower pH level. 3) Principal component analysis reveals that fermentation pH influences the physiological status of yeast cells from the beginning of fermentation, and bands 1440 cm^-1 and 1600 cm^-1 are the prominent contributors to the component loadings in different fermentation stages. This suggests the pH level of medium may affect the synthesis of lipid and the respiratory metabolism of yeast cells, influence the metabolism consequently. The results indicate Raman spectroscopy and single-cell analysis can uncover the physiological mechanism of the microbial cell during the fermentation process and provide new and reference information for the ethanol fermentation.
出处
《中国激光》
EI
CAS
CSCD
北大核心
2013年第2期229-235,共7页
Chinese Journal of Lasers
基金
国家自然科学基金(30760010)
广西自然科学基金(2012GXNSFCA053001
0832022Z
0991079)资助课题
关键词
光谱学
乙醇发酵
拉曼光谱
pH值
单细胞分析
spectroscopy
ethanol fermentation
Raman spectroscopy
pH levels
single-cell analysis