2020
DOI: 10.3389/fbioe.2020.01008
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Xylose Metabolism and the Effect of Oxidative Stress on Lipid and Carotenoid Production in Rhodotorula toruloides: Insights for Future Biorefinery

Abstract: The use of cell factories to convert sugars from lignocellulosic biomass into chemicals in which oleochemicals and food additives, such as carotenoids, is essential for the shift toward sustainable processes. Rhodotorula toruloides is a yeast that naturally metabolises a wide range of substrates, including lignocellulosic hydrolysates, and converts them into lipids and carotenoids. In this study, xylose, the main component of hemicellulose, was used as the sole substrate for R. toruloides, and a detailed physi… Show more

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Cited by 57 publications
(51 citation statements)
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References 80 publications
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“…Multi-omics analysis and metabolic network reconstruction identified unique reactions and enzymes as well as their localization for unique pentose and aromatic compound utilization pathways in R. toruloides. The pentose and aromatic compound utilization pathways proposed in this study have not been suggested in previously published multi-omics studies or genome-scale metabolic models of R. toruloides (Bommareddy et al, 2015;Dinh et al, 2019;Tiukova et al, 2019a,b;Lopes et al, 2020;Pinheiro et al, 2020). The first genome-scale metabolic model for R. toruloides was recently built for strain NP11 (Tiukova et al, 2019b), and a proteomics study of xylose metabolism was conducted by the same research group (Tiukova et al, 2019a).…”
Section: Discussionmentioning
confidence: 80%
See 1 more Smart Citation
“…Multi-omics analysis and metabolic network reconstruction identified unique reactions and enzymes as well as their localization for unique pentose and aromatic compound utilization pathways in R. toruloides. The pentose and aromatic compound utilization pathways proposed in this study have not been suggested in previously published multi-omics studies or genome-scale metabolic models of R. toruloides (Bommareddy et al, 2015;Dinh et al, 2019;Tiukova et al, 2019a,b;Lopes et al, 2020;Pinheiro et al, 2020). The first genome-scale metabolic model for R. toruloides was recently built for strain NP11 (Tiukova et al, 2019b), and a proteomics study of xylose metabolism was conducted by the same research group (Tiukova et al, 2019a).…”
Section: Discussionmentioning
confidence: 80%
“…Another genomescale metabolic model was shortly after published for strain IFO0880 utilizing the functional genomics data (Coradetti et al, 2018). More recent studies utilized these models to study the utilization of different carbon sources, but their focus was primarily on lipid production (Lopes et al, 2020;Pinheiro et al, 2020).The metabolic network model developed in this study was reconstructed and manually curated reproducibly using multiomics data and electronic notebooks, and validated against highthroughput growth phenotypes in 213 growth conditions and conditional gene essentiality in 27 growth conditions with high prediction accuracies, significantly expanding the breadth and depth of metabolic coverage from previously published models (Dinh et al, 2019;Tiukova et al, 2019b). We believe that the developed metabolic network for R. toruloides is most complete and accurate to date, and the multi-omics data and metabolic model presented in this study will be useful for studying and engineering R. toruloides for lignocellulosic biomass conversion.…”
Section: Discussionmentioning
confidence: 99%
“…The data here disclosed are the rst reports of bioreactor scale fermentation of Camelina meal hydrolysate, and therefore they can pave the way for further optimization. To maximize the production of interest several modi cations in uencing lipid and carotenoid production in yeasts, like C/N ratio, initial CDW, pH and oxygenation [30][31][32][33], can be operated.…”
Section: Carotenoids Production In Batch Bioreactorsmentioning
confidence: 99%
“…The data here disclosed are the first reports of the bioreactor scale fermentation of Camelina meal hydrolysate, and therefore they can pave the way for further optimization. To maximize research interests, several modifications influencing lipid and carotenoid production in yeasts, like the C/N ratio, initial CDW, pH and oxygenation [44][45][46][47], can be operated.…”
Section: Carotenoids Production In Batch Bioreactorsmentioning
confidence: 99%