Genome‐scale model of <i>Rhodotorula toruloides</i> metabolism

Tiukova, Ievgeniia A.; Prigent, Sylvain; Nielsen, Jens; Sandgren, Mats; Kerkhoven, Eduard J.

doi:10.1002/bit.27162

Cited by 51 publications

(29 citation statements)

References 68 publications

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“…Considering that SBY94 relative expressions of crtE, crtI, and crtYB are, respectively, 4.0, 3.4, and 2.4 lower than SBY93 (Figure 4C), yet the carotenoid titer produced by these strains is statistically the same (Figure 4A), we suggest that expression levels higher than those presented by SBY93 would no longer be beneficial without the overexpression of genes upstream of crtE. Genes from the mevalonate pathway, such as HMG-CoA reductase, are recommended targets for overexpression to increase carotenoid production (Tiukova, 2019) and have already shown positive results for this strategy for other carotenogenic yeats (Wang and Keasling, 2002).…”

Section: Proof Of Concept Of Rtgga For the Overproduction Of Carotenoidsmentioning

confidence: 80%

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Development of a dedicated Golden Gate Assembly platform (RtGGA) for Rhodotorula toruloides

Bonturi

Pinheiro

Oliveira

et al. 2022

Preprint

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Rhodotorula toruloides is a potential chassis to microbial cell factories as this yeast can metabolise different substrates into a diverse range of natural products, but the lack of efficient synthetic biology tools hinders its applicability. In this study, the modular, versatile and efficient Golden Gate DNA assembly system was adapted to the first basidiomycete, an oleaginous yeast R. toruloides (RtGGA). R. toruloides CCT 0783 was sequenced, and used for the RtGGA design. The DNA fragments were assembled with predesigned 4-nt overhangs and a library of standardized parts was created containing promoters, genes, terminators, insertional regions, and resistance genes. The library was combined to create cassettes for the characterization of promoters strength and to overexpress the carotenoid production pathway. A variety of reagents, plasmids, and strategies were used and the RtGGA proved to be robust. The RtGGA was used to build three versions of the carotenoid overexpression cassette were built by using different promoter combinations. The cassettes were transformed into R. toruloides and the three new strains were characterized. Total carotenoid concentration increased by 41%. The dedicated GGA platform fills a gap in the advanced genome engineering toolkit for R. toruloides, enabling the efficient design of complex metabolic pathways.

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Section: Proof Of Concept Of Rtgga For the Overproduction Of Carotenoidsmentioning

confidence: 80%

“…Figure 3. Carotenoid biosynthesis in R. toruloides according to different genome-scale models (GEM)(Dinh et al, 2019;Kim et al, 2021;Tiukova et al, 2019). Geranylgeranyl diphosphate synthase (crtE) catalyzes the formation of precursor of carotenoids.…”

mentioning

confidence: 99%

Development of a dedicated Golden Gate Assembly platform (RtGGA) for Rhodotorula toruloides

Bonturi

Pinheiro

Oliveira

et al. 2022

Preprint

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“…can be provided in a single MATLAB initialization script, minimizing the modifications needed for the generation of a new ecModel. ecModels container: an automatically updated repository Several GEMs that have been published are still subject to continuous development and maintenance [1][2][3]5,6 , this renders GEMs to be dynamic structures that can change rapidly. In order to integrate such continuous updates into the enzyme constrained version of a model in an organized way, an automated pipeline named ecModels container was developed.…”

Section: New Additions To the Gecko Toolboxmentioning

confidence: 99%

“…Genome-scale metabolic models (GEMs) have become an established tool for systematic analyses of metabolism for a wide variety of organisms [1][2][3][4][5][6] . Their myriads of applications span from model-driven development of e cient cell factories 3,7−9 , to their utilization for understanding mechanisms underlying complex human diseases [10][11][12] .…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

Domenzain

Sánchez

Anton

et al. 2021

Preprint

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Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into GEMs was first enabled by the GECKO method, allowing the study of phenotypes constrained by protein limitations. Here, we upgraded the GECKO toolbox in order to enhance models with enzyme and proteomics constraints for any organism with an available GEM reconstruction. With this, enzyme-constrained models (ecModels) for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus were generated, aiming to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions revealed that upregulation and high saturation of enzymes in amino acid metabolism were found to be common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO was further developed by the implementation of an automated framework for continuous and version-controlled update of ecModels, which was validated by producing additional high-quality ecModels for Escherichia coli and Homo sapiens. These efforts aim to facilitate the utilization of ecModels in basic science, metabolic engineering and synthetic biology purposes.

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“…GSMs have been constructed for a wide variety of oleaginous microorganisms, providing novel insight into their metabolic capabilities and behavior (Castañeda et al, 2018;Kim et al, 2019;Levering et al, 2015;Loira et al, 2012;Mishra et al, 2016;Tiukova et al, 2019;Vongsangnak et al, 2013). Many of these GSMs have also been used to propose strategies to enhance both the total lipid content, as well as increasing the fractional PUFA-content (Kim et al, 2019;Levering et al, 2015;Tibocha-Bonilla et al, 2018).…”

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confidence: 99%

High‐quality genome‐scale metabolic model of Aurantiochytrium sp. T66

Simensen

Voigt

Almaas

2021

Biotech & Bioengineering

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The long‐chain, ω‐3 polyunsaturated fatty acids (PUFAs) (e.g., eicosapentaenoic acid [EPA] and docosahexaenoic acid [DHA]), are essential for humans and animals, including marine fish species. Presently, the primary source of these PUFAs is fish oils. As the global production of fish oils appears to be reaching its limits, alternative sources of high‐quality ω‐3 PUFAs is paramount to support the growing aquaculture industry. Thraustochytrids are a group of heterotrophic protists with the capability to synthesize and accrue large amounts of DHA. Thus, the thraustochytrids are prime candidates to solve the increasing demand for ω‐3 PUFAs using microbial cell factories. However, a systems‐level understanding of their metabolic shift from cellular growth into lipid accumulation is, to a large extent, unclear. Here, we reconstructed a high‐quality genome‐scale metabolic model of the thraustochytrid Aurantiochytrium sp. T66 termed iVS1191. Through iterative rounds of model refinement and extensive manual curation, we significantly enhanced the metabolic scope and coverage of the reconstruction from that of previously published models, making considerable improvements with stoichiometric consistency, metabolic connectivity, and model annotations. We show that iVS1191 is highly consistent with experimental growth data, reproducing in vivo growth phenotypes as well as specific growth rates on minimal carbon media. The availability of iVS1191 provides a solid framework for further developing our understanding of T66's metabolic properties, as well as exploring metabolic engineering and process‐optimization strategies in silico for increased ω‐3 PUFA production.

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Genome‐scale model of Rhodotorula toruloides metabolism

Cited by 51 publications

References 68 publications

Development of a dedicated Golden Gate Assembly platform (RtGGA) for Rhodotorula toruloides

Development of a dedicated Golden Gate Assembly platform (RtGGA) for Rhodotorula toruloides

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

High‐quality genome‐scale metabolic model of Aurantiochytrium sp. T66

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