FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts

Biotechnology for Biofuels

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[1] 0000 0000 8578 2742, grid.6341.0, Department of Molecular Sciences, Swedish University of Agricultural Sciences, Box 7015, 750 07, Uppsala, Sweden;0000 0004 0607 975X, grid.19477.3c, Faculty of Science and Technology, Norwegian University of Life Sciences: NMBU, P.O.Box 5003, 1432, Ås, Norway;

关键词: FT-NIR;    Lipid quantification;    Rhodotorula toruloides;    Lipomyces starkeyi;    Yarrowia lipolytica;   

DOI  :  10.1186/s13068-019-1513-9

来源: publisher

【 摘 要 】

BackgroundLipid extraction for quantification of fat content in oleaginous yeasts often requires strong acids and harmful organic solvents; it is laborious and time-consuming. Therefore, in most cases just endpoint measurements of lipid accumulation are performed and kinetics of intracellular lipid accumulation is difficult to follow. To address this, we created a prediction model using Fourier-transform near-infrared (FT-NIR) spectroscopy. This method allows to measure lipid content in yeast.MethodsThe FT-NIR calibration sets were constructed from spectra of freeze-dried cells of the oleaginous yeasts Rhodotorula toruloides CBS 14, Lipomyces starkeyi CBS 1807 and Yarrowia lipolytica CBS 6114. The yeast cells were obtained from different cultivation conditions. Freeze-dried cell pellets were scanned using FT-NIR in the Multi Purpose Analyser (MPA) from Bruker. The obtained spectra were assigned corresponding to total fat content, obtained from lipid extraction using a modified Folch method. Quantification models using partial least squares (PLS) regression were built, and the calibration sets were validated on independently cultivated samples. The R. toruloides model was additionally tested on Rhodotorula babjevae DBVPG 8058 and Rhodotorula glutinis CBS 2387.ResultsThe R2 of the FT-NIR model for R. toruloides was 98%, and the root mean square error of cross-validation (RMSECV) was 1.53. The model was validated using a separate set of R. toruloides samples with a root mean square error of prediction (RMSEP) of 3.21. The R2 of the Lipomyces model was 96%, with RMSECV 2.4 and RMSEP 3.8. The R2 of the mixed model, including all tested yeast strains, was 90.5%, with RMSECV 2.76 and RMSEP 3.22, respectively. The models were verified by predicting the total fat content in newly cultivated and freeze-dried samples. Additionally, the kinetics of lipid accumulation of a culture were followed and compared with standard lipid extraction methods.ConclusionsUsing FT-NIR spectroscopy, we have developed a faster, less laborious and non-destructive quantification of yeast intracellular lipid content compared to methods using lipid extraction.

【 授权许可】

CC BY