Chair of Brewing and Beverage Technology, Technical University of Munich, TUM School of Life Science, Weihenstephaner Steig 20, 85354, Freising, Germany.
Chair of Bioseparation Engineering, Technical University of Munich, TUM School of Engineering and Design, Boltzmannstr. 15, 85748, Garching, Germany.
Anal Bioanal Chem. 2023 Jul;415(16):3201-3213. doi: 10.1007/s00216-023-04676-w. Epub 2023 Apr 21.
For industrial processes, a fast, precise, and reliable method of determining the physiological state of yeast cells, especially viability, is essential. However, an increasing number of processes use magnetic nanoparticles (MNPs) for yeast cell manipulation, but their impact on yeast cell viability and the assay itself is unclear. This study tested the viability of Saccharomyces pastorianus ssp. carlsbergensis and Pichia pastoris by comparing traditional colourimetric, high-throughput, and growth assays with membrane fluidity. Results showed that methylene blue staining is only reliable for S. pastorianus cells with good viability, being erroneous in low viability (R = 0.945; [Formula: see text] = 5.78%). In comparison, the fluorescence microscopy-based assay of S. pastorianus demonstrated a coefficient of determination of R = 0.991 at [Formula: see text] ([Formula: see text] = 2.50%) and flow cytometric viability determination using carboxyfluorescein diacetate (CFDA), enabling high-throughput analysis of representative cell numbers; R = 0.972 ([Formula: see text]; [Formula: see text] = 3.89%). Membrane fluidity resulted in a non-linear relationship with the viability of the yeast cells ([Formula: see text]). We also determined similar results using P. pastoris yeast. In addition, we demonstrated that MNPs affected methylene blue staining by overestimating viability. The random forest model has been shown to be a precise method for classifying nanoparticles and yeast cells and viability differentiation in flow cytometry by using CFDA. Moreover, CFDA and membrane fluidity revealed precise results for both yeasts, also in the presence of nanoparticles, enabling fast and reliable determination of viability in many experiments using MNPs for yeast cell manipulation or separation.
对于工业过程而言,快速、准确和可靠的方法来确定酵母细胞的生理状态,尤其是生存力,是至关重要的。然而,越来越多的工艺使用磁性纳米颗粒(MNPs)来操作酵母细胞,但它们对酵母细胞生存力和测定本身的影响尚不清楚。本研究通过比较传统的比色法、高通量法和生长测定法与膜流动性,来测试卡尔酵母和巴斯德毕赤酵母的生存力。结果表明,亚甲基蓝染色仅适用于生存力良好的卡尔酵母细胞,在低生存力时会出现错误(R=0.945;[Formula: see text] = 5.78%)。相比之下,基于荧光显微镜的卡尔酵母检测显示出 R=0.991 的决定系数,在[Formula: see text]时([Formula: see text] = 2.50%)和使用羧基荧光素二乙酸酯(CFDA)的流式细胞术生存力测定,能够对代表性细胞数量进行高通量分析;R=0.972([Formula: see text];[Formula: see text] = 3.89%)。膜流动性与酵母细胞的生存力呈非线性关系([Formula: see text])。我们使用巴斯德毕赤酵母也得到了类似的结果。此外,我们证明 MNPs 通过高估生存力来影响亚甲基蓝染色。随机森林模型已被证明是一种精确的方法,可用于通过使用 CFDA 在流式细胞术对纳米颗粒和酵母细胞以及生存力分化进行分类。此外,CFDA 和膜流动性揭示了两种酵母的精确结果,即使在存在纳米颗粒的情况下,也能够在使用 MNPs 进行酵母细胞操作或分离的许多实验中快速可靠地确定生存力。