Dataset Information

Physiological mechanism of improved tolerance of Saccharomyces cerevisiae to lignin-derived phenolic acids in lignocellulosic ethanol fermentation by short-term adaptation.

ABSTRACT:

Background

Phenolic acids are lignin-derived fermentation inhibitors formed during many pretreatment processes of lignocellulosic biomass. In this study, vanillic, p-hydroxybenzoic, and syringic acids were selected as the model compounds of phenolic acids, and the effect of short-term adaptation strategies on the tolerance of S. cerevisiae to phenolic acids was investigated. The mechanism of phenolic acids tolerance in the adapted yeast strains was studied at the morphological and physiological levels.

Results

The multiple phenolic acids exerted the synergistic inhibitory effect on the yeast cell growth. In particular, a significant interaction between vanillic and hydroxybenzoic acids was found. The optimal short-term adaptation strategies could efficiently improve the growth and fermentation performance of the yeast strain not only in the synthetic media with phenolic acids, but also in the simultaneous saccharification and ethanol fermentation of corncob residue. Morphological analysis showed that phenolic acids caused the parental strain to generate many cytoplasmic membrane invaginations with crack at the top of these sites and some mitochondria gathered around. The adapted strain presented the thicker cell wall and membrane and smaller cell size than those of the parental strain. In particular, the cytoplasmic membrane generated many little protrusions with regular shape. The cytoplasmic membrane integrity was analyzed by testing the relative electrical conductivity, leakage of intracellular substance, and permeation of fluorescent probe. The results indicated that the short-term adaptation improved the membrane integrity of yeast cell.

Conclusion

The inhibition mechanism of phenolic acid might be attributed to the combined effect of the cytoplasmic membrane damage and the intracellular acidification. The short-term adaptation strategy with varied stressors levels and adaptive processes accelerated the stress response of yeast cell structure to tolerate phenolic acids. This strategy will contribute to the development of robust microbials for biofuel production from lignocellulosic biomass.

SUBMITTER: Gu H

PROVIDER: S-EPMC6854637 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Physiological mechanism of improved tolerance of <i>Saccharomyces cerevisiae</i> to lignin-derived phenolic acids in lignocellulosic ethanol fermentation by short-term adaptation.

Gu Hanqi H Zhu Yuyong Y Peng Yanfang Y Liang Xiujun X Liu Xiaoguang X Shao Lingzhi L Xu Yanyan Y Xu Zhaohe Z Liu Ran R Li Jie J

Biotechnology for biofuels 20191114

<h4>Background</h4>Phenolic acids are lignin-derived fermentation inhibitors formed during many pretreatment processes of lignocellulosic biomass. In this study, vanillic, <i>p</i>-hydroxybenzoic, and syringic acids were selected as the model compounds of phenolic acids, and the effect of short-term adaptation strategies on the tolerance of <i>S. cerevisiae</i> to phenolic acids was investigated. The mechanism of phenolic acids tolerance in the adapted yeast strains was studied at the morphologi ...[more]

PMID: 31755875

Similar Datasets

Project description:BACKGROUND:Genetic engineering of industrial microorganisms often suffers from undesirable side effects on essential functions. Reverse engineering is an alternative strategy to improve multifactorial traits like low glycerol/high ethanol yield in yeast fermentation. Previous rational engineering of this trait always affected essential functions like growth and stress tolerance. We have screened Saccharomyces cerevisiae biodiversity for specific alleles causing lower glycerol/higher ethanol yield, assuming higher compatibility with normal cellular functionality. Previous work identified ssk1E330N…K356N as causative allele in strain CBS6412, which displayed the lowest glycerol/ethanol ratio. RESULTS:We have now identified a unique segregant, 26B, that shows similar low glycerol/high ethanol production as the superior parent, but lacks the ssk1E330N…K356N allele. Using segregants from the backcross of 26B with the inferior parent strain, we applied pooled-segregant whole-genome sequence analysis and identified three minor quantitative trait loci (QTLs) linked to low glycerol/high ethanol production. Within these QTLs, we identified three novel alleles of known regulatory and structural genes of glycerol metabolism, smp1R110Q,P269Q, hot1P107S,H274Y and gpd1L164P as causative genes. All three genes separately caused a significant drop in the glycerol/ethanol production ratio, while gpd1L164P appeared to be epistatically suppressed by other alleles in the superior parent. The order of potency in reducing the glycerol/ethanol ratio of the three alleles was: gpd1L164P?>?hot1P107S,H274Y???smp1R110Q,P269Q. CONCLUSIONS:Our results show that natural yeast strains harbor multiple specific alleles of genes controlling essential functions, that are apparently compatible with survival in the natural environment. These newly identified alleles can be used as gene tools for engineering industrial yeast strains with multiple subtle changes, minimizing the risk of negatively affecting other essential functions. The gene tools act at the transcriptional, regulatory or structural gene level, distributing the impact over multiple targets and thus further minimizing possible side-effects. In addition, the results suggest polygenic analysis of complex traits as a promising new avenue to identify novel components involved in cellular functions, including those important in industrial applications.

Project description: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.

Project description:This work was designed to identify yeast cellular functions specifically affected by the stress factors predominating during the early stages of wine fermentation, and genes required for optimal growth under these conditions. The main experimental method was quantitative fitness analysis by means of competition experiments in continuous culture of whole genome barcoded yeast knockout collections. This methodology allowed the identification of haploinsufficient genes, and homozygous deletions resulting in growth impairment in synthetic must. However, genes identified as haploproficient, or homozygous deletions resulting in fitness advantage, were of little predictive power concerning optimal growth in this medium. The relevance of these functions for enological performance of yeast was assessed in batch cultures with single strains. Previous studies addressing yeast adaptation to winemaking conditions by quantitative fitness analysis were not specifically focused on the proliferative stages. In some instances our results highlight the importance of genes not previously linked to winemaking. In other cases they are complementary to those reported in previous studies concerning, for example, the relevance of some genes involved in vacuolar, peroxisomal, or ribosomal functions. Our results indicate that adaptation to the quickly changing growth conditions during grape must fermentation require the function of different gene sets in different moments of the process. Transport processes and glucose signaling seem to be negatively affected by the stress factors encountered by yeast in synthetic must. Vacuolar activity is important for continued growth during the transition to stationary phase. Finally, reduced biogenesis of peroxisomes also seems to be advantageous. However, in contrast to what was described for later stages, reduced protein synthesis is not advantageous for the early (proliferative) stages of the fermentation process. Finally, we found adenine and lysine to be in short supply for yeast growth in some natural grape musts.