Wieland Karin, Masri Mahmoud, von Poschinger Jeremy, Brück Thomas, Haisch Christoph
Chair of Analytical Chemistry, Technical University of Munich Elisabeth-Winterhalter-Weg 6 81377 Germany
Competence Center CHASE GmbH Altenbergerstraße 69 4040 Linz Austria.
RSC Adv. 2021 Aug 24;11(46):28565-28572. doi: 10.1039/d1ra04254h. eCollection 2021 Aug 23.
Oil-producing yeast cells are a valuable alternative source for palm oil production and, hence, may be one important piece of the puzzle for a more sustainable future. To achieve a high-quality product, the lipid composition inside oil-producing yeast cells is a crucial parameter for effective process control. Typically, the lipid composition is determined by off-line gas chromatography. A faster, less cumbersome approach is proposed here, by using non-invasive in-line Raman spectroscopy. A fed-batch fermentation of - a well-known oleaginous yeast - is used as model experiment to highlight the potential of Raman spectroscopy for in-line lipidomics. The temporal progression of biomass formation, lipid production and glucose consumption are determined based on PLS-regression models allowing process-relevant information on time to be accessed. Additionally, Gaussian curve fitting was applied to extract increasing and decreasing trends of saturated and unsaturated fatty acids produced by throughout the fermentation process.
产油酵母细胞是棕榈油生产的宝贵替代来源，因此，可能是实现更可持续未来难题中的重要一环。为了获得高质量的产品，产油酵母细胞内的脂质组成是有效过程控制的关键参数。通常，脂质组成通过离线气相色谱法测定。本文提出了一种更快、更简便的方法，即使用非侵入式在线拉曼光谱法。以一种著名的产油酵母进行补料分批发酵作为模型实验，以突出拉曼光谱在在线脂质组学中的潜力。基于偏最小二乘回归模型确定生物量形成、脂质产生和葡萄糖消耗的时间进程，从而能够获取与过程相关的实时信息。此外，应用高斯曲线拟合来提取在整个发酵过程中该酵母产生的饱和脂肪酸和不饱和脂肪酸的增减趋势。
