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Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

ABSTRACT: BACKGROUND:Scheffersomyces stipitis is an important yeast species in the field of biorenewables due to its desired capacity for xylose utilization. It has been recognized that redox balance plays a critical role in S. stipitis due to the different cofactor preferences in xylose assimilation pathway. However, there has not been any systems level understanding on how the shift in redox balance contributes to the overall metabolic shift in S. stipitis to cope with reduced oxygen uptake. Genome-scale metabolic network models (GEMs) offer the opportunity to gain such systems level understanding; however, currently the two published GEMs for S. stipitis cannot be used for this purpose, as neither of them is able to capture the strain's fermentative metabolism reasonably well due to their poor prediction of xylitol production, a key by-product under oxygen limited conditions. RESULTS:A system identification-based (SID-based) framework that we previously developed for GEM validation is expanded and applied to refine a published GEM for S. stipitis, iBB814. After the modified GEM, named iDH814, was validated using literature data, it is used to obtain genome-scale understanding on how redox cofactor shifts when cells respond to reduced oxygen supply. The SID-based framework for GEM analysis was applied to examine how the environmental perturbation (i.e., reduced oxygen supply) propagates through the metabolic network, and key reactions that contribute to the shifts of redox and metabolic state were identified. Finally, the findings obtained through GEM analysis were validated using transcriptomic data. CONCLUSIONS:iDH814, the modified model, was shown to offer significantly improved performance in terms of matching available experimental results and better capturing available knowledge on the organism. More importantly, our analysis based on iDH814 provides the first genome-scale understanding on how redox balance in S. stipitis was shifted as a result of reduced oxygen supply. The systems level analysis identified the key contributors to the overall metabolic state shift, which were validated using transcriptomic data. The analysis confirmed that S. stipitis uses a concerted approach to cope with the stress associated with reduced oxygen supply, and the shift of reducing power from NADPH to NADH seems to be the center theme that directs the overall shift in metabolic states.

SUBMITTER: Hilliard M

PROVIDER: S-EPMC6126012 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

Hilliard Matthew M Damiani Andrew A He Q Peter QP Jeffries Thomas T Wang Jin J

Microbial cell factories 20180905 1

<h4>Background</h4>Scheffersomyces stipitis is an important yeast species in the field of biorenewables due to its desired capacity for xylose utilization. It has been recognized that redox balance plays a critical role in S. stipitis due to the different cofactor preferences in xylose assimilation pathway. However, there has not been any systems level understanding on how the shift in redox balance contributes to the overall metabolic shift in S. stipitis to cope with reduced oxygen uptake. Gen ...[more]

PMID: 30185188

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Project description:BACKGROUND: Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis) has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. RESULTS: We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. CONCLUSION: The genome-scale metabolic model developed for Scheffersomyces stipitis successfully predicted substrate utilization and anaerobic growth requirements. Useful insights were drawn on xylose metabolism, cofactor recycling and mechanism of mitochondrial respiration from model simulations. These insights can be applied for efficient xylose utilization and cofactor recycling in other industrial microorganisms. The developed model forms a basis for rational analysis and design of Scheffersomyces stipitis metabolic network for the production of fuels and chemicals from lignocellulosic biomass.

Project description:BackgroundAs one of the clean and sustainable energies, lignocellulosic ethanol has achieved much attention around the world. The production of lignocellulosic ethanol does not compete with people for food, while the consumption of ethanol could contribute to the carbon dioxide emission reduction. However, the simultaneous transformation of glucose and xylose to ethanol is one of the key technologies for attaining cost-efficient lignocellulosic ethanol production at an industrial scale. Genetic modification of strains and constructing consortia were two approaches to resolve this issue. Compared with strain improvement, the synergistic interaction of consortia in metabolic pathways should be more useful than using each one separately.ResultsIn this study, the consortia consisting of suspended Scheffersomyces stipitis CICC1960 and Zymomonas mobilis 8b were cultivated to successfully depress carbon catabolite repression (CCR) in artificially simulated 80G40XRM. With this strategy, a 5.52% more xylose consumption and a 6.52% higher ethanol titer were achieved by the consortium, in which the inoculation ratio between S. stipitis and Z. mobilis was 1:3, compared with the Z. mobilis 8b mono-fermentation. Subsequently, one copy of the xylose metabolic genes was inserted into the Z. mobilis 8b genome to construct Z. mobilis FR2, leading to the xylose final-consumption amount and ethanol titer improvement by 15.36% and 6.81%, respectively. Finally, various corn stover hydrolysates with different sugar concentrations (glucose and xylose 60, 90, 120 g/L), were used to evaluate the fermentation performance of the consortium consisting of S. stipitis CICC1960 and Z. mobilis FR2. Fermentation results showed that a 1.56-4.59% higher ethanol titer was achieved by the consortium compared with the Z. mobilis FR2 mono-fermentation, and a 46.12-102.14% higher ethanol titer was observed in the consortium fermentation when compared with the S. stipitis CICC1960 mono-fermentation. Furthermore, qRT-PCR analysis of xylose/glucose transporter and other genes responsible for CCR explained the reason why the initial ratio inoculation of 1:3 in artificially simulated 80G40XRM had the best fermentation performance in the consortium.ConclusionsThe fermentation strategy used in this study, i.e., using a genetically modified consortium, had a superior performance in ethanol production, as compared with the S. stipitis CICC1960 mono-fermentation and the Z. mobilis FR2 mono-fermentation alone. This result showed that this strategy has potential for future lignocellulosic ethanol production.

Dataset Information

Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

Publications

Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

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