Effect of cytochrome bc1 complex inhibition during fermentation and growth of<i>Scheffersomyces stipitis</i>using glucose, xylose or arabinose as carbon sources

Granados-Arvizu, J.A.; Madrigal‐Perez, Luis Alberto; Canizal-García, Melina; González‐Hernández, Juan Carlos; García-Almendárez, Blanca E.; Regalado‐González, Carlos

doi:10.1093/femsyr/foy126

Cited by 10 publications

(4 citation statements)

References 24 publications

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“…Our strains were also able to metabolize l ‐arabinose under aerobic conditions, as previously observed for other yeasts, such as M. guilliermondii PYCC 3012, C. arabinofermentans PYCC 5603 and S. stipitis (Fonseca et al, 2007; Granados‐Arvizu et al, 2019). However, similar to that in d ‐xylose, cells did not produce ethanol from l ‐arabinose, with a preferential targeting for biomass formation (Y x/s 0.54, 0.54 and 0.59; Figure 2 and Table 3), parallel to that observed for S. passalidarum CMUWF1–2 (Rodrussamee et al, 2018).…”

Section: Resultssupporting

confidence: 85%

Fermentation profiles of the yeast Brettanomyces bruxellensis in d‐xylose and l‐arabinose aiming its application as a second‐generation ethanol producer

Silva

Ribeiro

Teles

et al. 2020

Yeast

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The yeast Brettanomyces bruxellensis is able to ferment the main sugars used in firstgeneration ethanol production. However, its employment in this industry is prohibitive because the ethanol productivity reached is significantly lower than the observed for Saccharomyces cerevisiae. On the other hand, a possible application of B. bruxellensis in the second-generation ethanol production has been suggested because this yeast is also able to use D-xylose and L-arabinose, the major pentoses released from lignocellulosic material. Although the latter application seems to be reasonable, it has been poorly explored. Therefore, we aimed to evaluate whether or not different industrial strains of B. bruxellensis are able to ferment D-xylose and Larabinose, both in aerobiosis and oxygen-limited conditions. Three out of nine tested strains were able to assimilate those sugars. When in aerobiosis, B. bruxellensis cells exclusively used them to support biomass formation, and no ethanol was produced. Moreover, whereas L-arabinose was not consumed under oxygen limitation, D-xylose was only slightly used, which resulted in low ethanol yield and productivity. In conclusion, our results showed that D-xylose and L-arabinose are not efficiently converted to ethanol by B. bruxellensis, most likely due to a redox imbalance in the assimilatory pathways of these sugars. Therefore, despite presenting other industrially relevant traits, the employment of B. bruxellensis in second-generation ethanol production depends on the development of genetic engineering strategies to overcome this metabolic bottleneck.

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Section: Resultssupporting

confidence: 85%

Fermentation profiles of the yeast Brettanomyces bruxellensis in d‐xylose and l‐arabinose aiming its application as a second‐generation ethanol producer

Silva

Ribeiro

Teles

et al. 2020

Yeast

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“…[43]. Granados-Arvizu et al [44] also concluded that cytochrome bc 1 complex repression would be a promising way to enhance ethanol production in Saccharomyces stipitis. ALD6 or Aldehyde dehydrogenases is activated by Mg and have a distinct role in the formation of acetate from pyruvate in an alternate pyruvate dehydrogenase bypass pathway [45].…”

Section: Discussionmentioning

confidence: 99%

Mining transcriptomic data to identifySaccharomyces cerevisiaesignatures related to improved and repressed ethanol production under fermentation

Sazegari

Niazi‎

Zinati

et al. 2021

Preprint

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Saccharomyces cerevisiae is known for its outstanding ability to produce ethanol in industry. Identifying the dynamic of gene expression in S. cerevisiae in response to fermentation is required for the establishment of any ethanol production improvement program. The goal of this study was to identify the discriminative genes between improved and repressed ethanol production as well as clarifying the molecular responses to this process through mining the transcriptomic data. Through 11 machine learning based algorithms from RapidMiner employed on available microarray datasets related to yeast fermentation performance under Mg 2+ and Cu 2+ supplementation, 172 probe sets were identified by at least 5 AWAs. Some have been identified as being involved in carbohydrate metabolism, oxidative phosphorylation, and ethanol fermentation. Principal component analysis (PCA) and heatmap clustering were also validated the top-ranked selective probe sets. According to decision tree models, 17 roots with 100% performance were identified. OLI1 and CYC3 were identified as the roots with the best performance, demonstrated by the most weighting algorithms and linked to top two significant enriched pathways including porphyrin biosynthesis and oxidative phosphorylation. ADH5 and PDA1 are also recognized as differential top-ranked genes that contribute to ethanol production. According to the regulatory clustering analysis, Tup1 has a significant effect on the top-ranked target genes CYC3 and ADH5 genes. This study provides a basic understanding of the S. cerevisiae cell molecular mechanism and responses to two different medium conditions (Mg 2+ and Cu 2+ ) during the fermentation process.

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“…[ 46 ]. Granados-Arvizu et al [ 47 ] also concluded that cytochrome bc 1 complex repression would be a promising way to enhance ethanol production in Saccharomyces stipites . ALD6 or Aldehyde dehydrogenases is activated by Mg and have a distinct role in the formation of acetate from pyruvate in an alternate pyruvate dehydrogenase bypass pathway [ 48 ].…”

Section: Discussionmentioning

confidence: 99%

Mining transcriptomic data to identify Saccharomyces cerevisiae signatures related to improved and repressed ethanol production under fermentation

et al. 2022

View full text Add to dashboard Cite

Saccharomyces cerevisiae is known for its outstanding ability to produce ethanol in industry. Underlying the dynamics of gene expression in S. cerevisiae in response to fermentation could provide informative results, required for the establishment of any ethanol production improvement program. Thus, representing a new approach, this study was conducted to identify the discriminative genes between improved and repressed ethanol production as well as clarifying the molecular responses to this process through mining the transcriptomic data. The significant differential expression probe sets were extracted from available microarray datasets related to yeast fermentation performance. To identify the most effective probe sets contributing to discriminate ethanol content, 11 machine learning algorithms from RapidMiner were employed. Further analysis including pathway enrichment and regulatory analysis were performed on discriminative probe sets. Besides, the decision tree models were constructed, the performance of each model was evaluated and the roots were identified. Based on the results, 171 probe sets were identified by at least 5 attribute weighting algorithms (AWAs) and 17 roots were recognized with 100% performance Some of the top ranked presets were found to be involved in carbohydrate metabolism, oxidative phosphorylation, and ethanol fermentation. Principal component analysis (PCA) and heatmap clustering validated the top-ranked selective probe sets. In addition, the top-ranked genes were validated based on GSE78759 and GSE5185 dataset. From all discriminative probe sets, OLI1 and CYC3 were identified as the roots with the best performance, demonstrated by the most weighting algorithms and linked to top two significant enriched pathways including porphyrin biosynthesis and oxidative phosphorylation. ADH5 and PDA1 were also recognized as differential top-ranked genes that contribute to ethanol production. According to the regulatory clustering analysis, Tup1 has a significant effect on the top-ranked target genes CYC3 and ADH5 genes. This study provides a basic understanding of the S. cerevisiae cell molecular mechanism and responses to two different medium conditions (Mg2+ and Cu2+) during the fermentation process.

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Effect of cytochrome bc1 complex inhibition during fermentation and growth ofScheffersomyces stipitisusing glucose, xylose or arabinose as carbon sources

Cited by 10 publications

References 24 publications

Fermentation profiles of the yeast Brettanomyces bruxellensis in d‐xylose and l‐arabinose aiming its application as a second‐generation ethanol producer

Fermentation profiles of the yeast Brettanomyces bruxellensis in d‐xylose and l‐arabinose aiming its application as a second‐generation ethanol producer

Mining transcriptomic data to identifySaccharomyces cerevisiaesignatures related to improved and repressed ethanol production under fermentation

Mining transcriptomic data to identify Saccharomyces cerevisiae signatures related to improved and repressed ethanol production under fermentation

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