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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 lipi...

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Autores principales: Chmielarz, Mikołaj, Sampels, Sabine, Blomqvist, Johanna, Brandenburg, Jule, Wende, Frida, Sandgren, Mats, Passoth, Volkmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599325/
https://www.ncbi.nlm.nih.gov/pubmed/31297157
http://dx.doi.org/10.1186/s13068-019-1513-9
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author Chmielarz, Mikołaj
Sampels, Sabine
Blomqvist, Johanna
Brandenburg, Jule
Wende, Frida
Sandgren, Mats
Passoth, Volkmar
author_facet Chmielarz, Mikołaj
Sampels, Sabine
Blomqvist, Johanna
Brandenburg, Jule
Wende, Frida
Sandgren, Mats
Passoth, Volkmar
author_sort Chmielarz, Mikołaj
collection PubMed
description 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 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. RESULTS: The R(2) 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 R(2) of the Lipomyces model was 96%, with RMSECV 2.4 and RMSEP 3.8. The R(2) 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.
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spelling pubmed-65993252019-07-11 FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts Chmielarz, Mikołaj Sampels, Sabine Blomqvist, Johanna Brandenburg, Jule Wende, Frida Sandgren, Mats Passoth, Volkmar Biotechnol Biofuels Methodology 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 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. RESULTS: The R(2) 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 R(2) of the Lipomyces model was 96%, with RMSECV 2.4 and RMSEP 3.8. The R(2) 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. BioMed Central 2019-06-29 /pmc/articles/PMC6599325/ /pubmed/31297157 http://dx.doi.org/10.1186/s13068-019-1513-9 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Chmielarz, Mikołaj
Sampels, Sabine
Blomqvist, Johanna
Brandenburg, Jule
Wende, Frida
Sandgren, Mats
Passoth, Volkmar
FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts
title FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts
title_full FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts
title_fullStr FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts
title_full_unstemmed FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts
title_short FT-NIR: a tool for rapid intracellular lipid quantification in oleaginous yeasts
title_sort ft-nir: a tool for rapid intracellular lipid quantification in oleaginous yeasts
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6599325/
https://www.ncbi.nlm.nih.gov/pubmed/31297157
http://dx.doi.org/10.1186/s13068-019-1513-9
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