Tillman Zofia, Peterson Darren J, Dowe Nancy, Wolfrum Ed
National Renewable Energy Laboratory, 15013 Denver West Pkwy, Golden, CO, 80401, USA.
Biotechnol Biofuels Bioprod. 2025 Jun 7;18(1):60. doi: 10.1186/s13068-025-02662-1.
2,3-butanediol (2,3-BDO) is an economically important platform chemical that can be produced by the fermentation of sugars using an engineered strain of Zymomonas mobilis. These fermentations require continuous monitoring and modification of fermentation conditions to maximize 2,3-BDO yields and minimize the production of the undesired coproducts glycerol and acetoin. Because of the time required for sampling and off-line chromatographic measurement of fermentation samples, the ability of fermentation scientists to modify fermentation conditions in a timely manner is limited. The goal of this study was to test if near-infrared spectroscopy (NIRS) along with multivariate statistics could reduce the time needed for this analysis and enable real-time monitoring and control of the fermentation.
In this work we developed partial least squares (PLS) calibration models to predict the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol in fermentations via NIRS using two different spectrometers and two different spectroscopy modalities. We first evaluated the feasibility of rapid NIRS monitoring through experiments where we measured the signals from each analyte of interest and built NIRS-based PLS models using spectra from synthetic samples containing uncorrelated concentrations of these analytes. All analytes showed unique spectral signatures, and this initial modeling showed that all analytes could be detected simultaneously. We then began work with samples from laboratory fermentation experiments and tested the feasibility of regression model development across two spectral collection modalities (at-line and on-line) and two instruments: a laboratory-grade instrument and a low-cost instrument with a more limited spectral range. All modalities showed promise in the ability to monitor Z. mobilis fermentations of glucose and xylose to 2,3-BDO. The low-cost instrument displayed a lower signal-to-noise ratio than the laboratory-grade instrument, which led to comparatively lower performance overall, but still provided sufficient accuracy to monitor fermentation trends. While the ease of use of on-line monitoring systems was favored as compared to at-line systems due to the lack of sampling required and potential for automated process control, we observed some decrease in performance due to the additional complexity of the sample matrix.
We have demonstrated that NIRS combined with multivariate analysis can be used for at-line and on-line monitoring of the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol during Z. mobilis fermentations. The decrease in signal-to-noise ratio when using a low-cost spectrometer led to greater prediction error than the laboratory-grade spectrometer for at-line monitoring. The on-line monitoring modality showed great promise for real time process control via NIRS.
2,3-丁二醇（2,3-BDO）是一种具有重要经济价值的平台化学品，可通过工程改造的运动发酵单胞菌菌株发酵糖类来生产。这些发酵过程需要持续监测和调整发酵条件，以实现2,3-BDO产量最大化，并将不需要的副产物甘油和乙偶姻的生成量降至最低。由于对发酵样品进行采样和离线色谱测量需要时间，发酵科学家及时调整发酵条件的能力受到限制。本研究的目的是测试近红外光谱（NIRS）结合多元统计方法是否可以减少该分析所需的时间，并实现发酵过程的实时监测和控制。
在本研究中，我们开发了偏最小二乘法（PLS）校准模型，通过使用两种不同的光谱仪和两种不同的光谱模式，利用近红外光谱预测发酵过程中葡萄糖、木糖、2,3-丁二醇、乙偶姻和甘油的浓度。我们首先通过实验评估了近红外光谱快速监测的可行性，在实验中我们测量了每种目标分析物的信号，并使用来自含有这些分析物不相关浓度的合成样品的光谱建立了基于近红外光谱的PLS模型。所有分析物都显示出独特的光谱特征，并且初步建模表明所有分析物都可以同时被检测到。然后，我们开始处理来自实验室发酵实验的样品，并测试了在两种光谱采集模式（在线和离线）以及两种仪器（实验室级仪器和光谱范围更有限的低成本仪器）上开发回归模型的可行性。所有模式在监测运动发酵单胞菌将葡萄糖和木糖发酵为2,3-丁二醇的能力方面都显示出前景。低成本仪器的信噪比低于实验室级仪器，这导致其整体性能相对较低，但仍提供了足够的准确性来监测发酵趋势。虽然与离线系统相比，在线监测系统由于无需采样且具有自动过程控制的潜力而更受青睐，但我们观察到由于样品基质的额外复杂性，其性能有所下降。
我们已经证明，近红外光谱结合多变量分析可用于在线和离线监测运动发酵单胞菌发酵过程中葡萄糖、木糖、2,3-丁二醇、乙偶姻和甘油的浓度。使用低成本光谱仪时信噪比的降低导致在线监测时预测误差比实验室级光谱仪更大。在线监测模式在通过近红外光谱进行实时过程控制方面显示出巨大潜力。
