Evidence map›Paper›PMID 31178928›Full record

ArticleBiotechnology for biofuels2019

Biochemical profiling, prediction of total lipid content and fatty acid profile in oleaginous yeasts by FTIR spectroscopy.

Volha Shapaval, Jule Brandenburg, Johanna Blomqvist, Valeria Tafintseva, Volkmar Passoth, Mats Sandgren, Achim Kohler

Abstract read
In one paragraph

Article in Biotechnology for biofuels, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Volha Shapaval1Faculty of Science and Technology, Norwegian University of Life Science, P.O. Box 5003, 1432 Ås, Norway.
Jule Brandenburg2Department of Molecular Sciences, Swedish University of Agricultural Sciences, BioCenter, Box 7015, 75007 Uppsala, Sweden.
Johanna Blomqvist1Faculty of Science and Technology, Norwegian University of Life Science, P.O. Box 5003, 1432 Ås, Norway.
Valeria Tafintseva1Faculty of Science and Technology, Norwegian University of Life Science, P.O. Box 5003, 1432 Ås, Norway.
Volkmar Passoth2Department of Molecular Sciences, Swedish University of Agricultural Sciences, BioCenter, Box 7015, 75007 Uppsala, Sweden.
Mats Sandgren2Department of Molecular Sciences, Swedish University of Agricultural Sciences, BioCenter, Box 7015, 75007 Uppsala, Sweden.
Achim Kohler1Faculty of Science and Technology, Norwegian University of Life Science, P.O. Box 5003, 1432 Ås, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOleaginous yeasts are considered as a potential lipid source for food, feed and biofuel production. In order to make the yeast-based lipid production environmentally and economically sustainable, there is a need for screening studies in order to find the best yeast lipid producers on different substrates, and to optimize cultivation conditions. Since the target parameter of such screening studies are lipid amounts and profiles, an analytical technique that is able to perform lipid analyses rapidly, reproducible and with high precision is highly desirable. The main objective of this study was to establish the non-invasive high-throughput Fourier transform infrared (FTIR) spectroscopy analysis for the prediction of lipid content and profile in oleaginous yeasts.

resultsHigh-throughput FTIR spectroscopy allowed characterizing the total biochemical profile of oleaginous yeasts and enabled us to identify strains and substrate(s) providing the highest total lipid content. Some of the yeast strains grown under nitrogen-limiting conditions with glucose/xylose/mixture of glucose and xylose as carbon sources were accumulating lipids with a high proportion of free fatty acids. FTIR spectra were used to predict gravimetric and gas chromatography data by establishing multivariate calibration models. Coefficients of determination (

conclusionsApplying FTIR spectroscopy combined with multivariate data analysis allows performing rapid, non-invasive, reproducible and precise quantitative predictions of total lipid content and lipid profile. It allows also detecting different lipid fractions as triacylglycerols (TAGs) and free fatty acids and evaluating the total biochemical profile of cells. Several yeast strains with high lipid accumulation were identified.

Indexed as

BiodieselFTIR spectroscopyLipid profileLipidsOleaginous yeastsTotal lipid content

Identifiers

PMID31178928
PMCPMC6551905

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.