拉曼光谱分析技术在资源微生物发酵性能评价中的应用

Applications of Raman spectroscopy in fermentation evaluation of resource microorganisms

摘要:

微生物发酵过程是细胞新陈代谢进行物质转化的过程，为了提高目标产物的转化率，需要对微生物发酵动态特性进行实时分析，以便实时优化发酵过程。拉曼光谱(Raman spectroscopy)量化测试作为一种有应用前景的在线过程分析技术，可以在避免微生物污染的条件下，实现精准监测，进而用于优化控制微生物发酵过程。【目的】以运动发酵单胞菌(Zymomonas mobilis)为例，建立微生物发酵过程中葡萄糖、木糖、乙醇和乳酸浓度拉曼光谱预测模型，并进行准确性验证。【方法】采用浸入式在线拉曼探头，收集运动发酵单胞菌发酵过程中多个组分的拉曼光谱，采用偏最小二乘法对光谱信号进行预处理和多元数据分析，结合离线色谱分析数据，对拉曼光谱进行建模分析和浓度预测。【结果】针对运动发酵单胞菌，首先实现拉曼分析仪对单一产品乙醇发酵过程的精准检测，其次基于多元变量分析，建立葡萄糖、乙醇和乳酸浓度变化的预测模型，实现对发酵过程中各成分浓度变化的准确有效分析。【结论】成功建立了一种评价资源微生物尤其是工业菌株发酵液多种组分的拉曼光谱分析方法。该方法为运动发酵单胞菌等工业菌株利用多组分底物工业化生产不同产物的实时检测，以及其他微生物尤其工业菌株的选育和过程优化提供了新方法。

Abstract:

Microbial fermentation is a process of substrate transformation by cell metabolism. In order to improve the yield of target products, we need to analyze the dynamic characteristics of microbial fermentation in a real-time manner so as to optimize the fermentation process. As a promising inline process analysis technology, Raman spectroscopy can achieve accurate monitoring under the in-situ conditions without causing microbial pollution and help optimize the microbial fermentation process. [Objective] To develop the prediction models with the inline Raman measurement technology and evaluate model performance so as to accurately monitor the concentration changes of glucose, xylose, ethanol, and lactic acid in the whole fermentation process of Zymomonas mobilis. [Methods] Raman spectra for multiple components in the fermentation process of Z. mobilis were collected in situ by the immersion probe, and then the partial least square method was adopted to conduct spectral processing and multivariate data analysis. The multivariate models were developed via the combination of Raman spectra with the HPLC data and then used to predict the concentrations of multiple components in the fermentation broth. [Results] The established models accurately measured the single products in the fermentation broth of Z. mobilis. Then, the prediction models for the concentrations of glucose, ethanol, and lactic acid were developed through multivariate analysis and validated, which can be used for real-time accurate determination of multiple components in the fermentation process. [Conclusion] We successfully established a Raman spectral analysis method for monitoring multiple chemicals in the fermentation broth. This is a promising technology for real-time monitoring of multiple substrates and products in industrial fermentation and can be used for strain development and process optimization of microorganisms.