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

Background: Lipid 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.

Methods: The FT-NIR calibration sets were constructed from spectra of freeze-dried cells of the oleaginous yeasts CBS 14, CBS 1807 and 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 model was additionally tested on DBVPG 8058 and CBS 2387.

Results: The of the FT-NIR model for was 98%, and the root mean square error of cross-validation (RMSECV) was 1.53. The model was validated using a separate set of samples with a root mean square error of prediction (RMSEP) of 3.21. The of the model was 96%, with RMSECV 2.4 and RMSEP 3.8. The 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.

Conclusions: Using 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.