Non-invasive Raman spectroscopy for time-resolved in-line lipidomics

Abstract

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 C. oleaginosus – 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 C. oleaginosus throughout the fermentation process.