Browse
Submit Data
Databases
API
Help

Dataset Information

25 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Herbicide glufosinate inhibits yeast growth and extends longevity during wine fermentation.

ABSTRACT: Glufosinate ammonium (GA) is a widely used herbicide that inhibits glutamine synthetase. This inhibition leads to internal amino acid starvation which, in turn, causes the activation of different nutrient sensing pathways. GA also inhibits the enzyme of the yeast Saccharomyces cerevisiae in such a way that, although it is not used as a fungicide, it may alter yeast performance in industrial processes like winemaking. We describe herein how GA indeed inhibits the yeast growth of a wine strain during the fermentation of grape juice. In turn, GA extends longevity in a variety of growth media. The biochemical analysis indicates that GA partially inhibits the nutrient sensing TORC1 pathway, which may explain these phenotypes. The GCN2 kinase mutant is hypersensitive to GA. Hence the control of translation and amino acid biosynthesis is required to also deal with the damaging effects of this pesticide. A global metabolomics analysis under winemaking conditions indicated that an increase in amino acid and in polyamines occurred. In conclusion, GA affects many different biochemical processes during winemaking, which provides us with some insights into both the effect of this herbicide on yeast physiology and into the relevance of the metabolic step for connecting nitrogen and carbon metabolism.

SUBMITTER: Vallejo B

PROVIDER: S-EPMC5622092 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Transcriptomic profiling of wine yeast strains during colombar fermentation

2009-05-01 | GSE13695 | GEO

Dynamics of the yeast transcriptome during wine fermentation reveals a novel fermentation stress response.

Project description:In this study, genome-wide expression analyses were used to study the response of Saccharomyces cerevisiae to stress throughout a 15-day wine fermentation. Forty per cent of the yeast genome significantly changed expression levels to mediate long-term adaptation to fermenting grape must. Among the genes that changed expression levels, a group of 223 genes was identified, which was designated as fermentation stress response (FSR) genes that were dramatically induced at various points during fermentation. FSR genes sustain high levels of induction up to the final time point and exhibited changes in expression levels ranging from four- to 80-fold. The FSR is novel; 62% of the genes involved have not been implicated in global stress responses and 28% of the FSR genes have no functional annotation. Genes involved in respiratory metabolism and gluconeogenesis were expressed during fermentation despite the presence of high concentrations of glucose. Ethanol, rather than nutrient depletion, seems to be responsible for entry of yeast cells into the stationary phase.

| S-EPMC5065349 | biostudies-literature

Comparative transcriptomic approach to investigate differences in wine yeast physiology and metabolism during fermentation.

Project description:Commercial wine yeast strains of the species Saccharomyces cerevisiae have been selected to satisfy many different, and sometimes highly specific, oenological requirements. As a consequence, more than 200 different strains with significantly diverging phenotypic traits are produced globally. This genetic resource has been rather neglected by the scientific community because industrial strains are less easily manipulated than the limited number of laboratory strains that have been successfully employed to investigate fundamental aspects of cellular biology. However, laboratory strains are unsuitable for the study of many phenotypes that are of significant scientific and industrial interest. Here, we investigate whether a comparative transcriptomics and phenomics approach, based on the analysis of five phenotypically diverging industrial wine yeast strains, can provide insights into the molecular networks that are responsible for the expression of such phenotypes. For this purpose, some oenologically relevant phenotypes, including resistance to various stresses, cell wall properties, and metabolite production of these strains were evaluated and aligned with transcriptomic data collected during alcoholic fermentation. The data reveal significant differences in gene regulation between the five strains. While the genetic complexity underlying the various successive stress responses in a dynamic system such as wine fermentation reveals the limits of the approach, many of the relevant differences in gene expression can be linked to specific phenotypic differences between the strains. This is, in particular, the case for many aspects of metabolic regulation. The comparative approach therefore opens new possibilities to investigate complex phenotypic traits on a molecular level.

| S-EPMC2765138 | biostudies-literature

Transcription profiling of wine yeast strains during colombar fermentation

Project description:Comparative gene expression analysis of two wine yeast strains at three time points (days 2, 5 and 14) during fermentation of colombar must. In our study we conducted parallel fermentations with the VIN13 and BM45 wine yeast strains in two different media, namely MS300 (syntheticmust) and Colombar must. The intersection of transcriptome datasets from both MS300 (simulated wine must;GSE11651) and Colombar fermentations should help to delineate relevant and ânoisyâ changes in gene expression in response to experimental factors such as fermentation stage and strain identity. Experiment Overall Design: Two industrial wine yeast strains (BM45 and VIN13) grown micro-aerobically in Colombar must. Microarray analysis was performed at three time points during fermentation (days 2, 5 and 14), representing the exponential, early and late stationary growth phases respectively.

2009-05-14 | E-GEOD-13695 | biostudies-arrayexpress

Modelling the physiological status of yeast during wine fermentation enables the prediction of secondary metabolism.

Project description:Saccharomyces non-cerevisiae yeasts are gaining momentum in wine fermentation due to their potential to reduce ethanol content and achieve attractive aroma profiles. However, the design of the fermentation process for new species requires intensive experimentation. The use of mechanistic models could automate process design, yet to date, most fermentation models have focused on primary metabolism. Therefore, these models do not provide insight into the production of secondary metabolites essential for wine quality, such as aromas. In this work, we formulate a continuous model that accounts for the physiological status of yeast, that is, exponential growth, growth under nitrogen starvation and transition to stationary or decay phases. To do so, we assumed that nitrogen starvation is associated with carbohydrate accumulation and the induction of a set of transcriptional changes associated with the stationary phase. The model accurately described the dynamics of time series data for biomass and primary and secondary metabolites obtained for various yeast species in single culture fermentations. We also used the proposed model to explore different process designs, showing how the addition of nitrogen could affect the aromatic profile of wine. This study underlines the potential of incorporating yeast physiology into batch fermentation modelling and provides a new means of automating process design.

| S-EPMC10034642 | biostudies-literature

Ecological interactions are a primary driver of population dynamics in wine yeast microbiota during fermentation.

Project description:Spontaneous wine fermentation is characterized by yeast population evolution, modulated by complex physical and metabolic interactions amongst various species. The contribution of any given species to the final wine character and aroma will depend on its numerical persistence during the fermentation process. Studies have primarily evaluated the effect of physical and chemical factors such as osmotic pressure, pH, temperature and nutrient availability on mono- or mixed-cultures comprising 2-3 species, but information about how interspecies ecological interactions in the wine fermentation ecosystem contribute to population dynamics remains scant. Therefore, in the current study, the effect of temperature and sulphur dioxide (SO2) on the dynamics of a multi-species yeast consortium was evaluated in three different matrices including synthetic grape juice, Chenin blanc and Grechetto bianco. The population dynamics were affected by temperature and SO2, reflecting differences in stress resistance and habitat preferences of the different species and influencing the production of most volatile aroma compounds. Evidently at 15 °C and in the absence of SO2 non-Saccharomyces species were dominant, whereas at 25 °C and when 30 mg/L SO2 was added S. cerevisiae dominated. Population growth followed similar patterns in the three matrices independently of the conditions. The data show that fermentation stresses lead to an individual response of each species, but that this response is strongly influenced by the interactions between species within the ecosystem. Thus, our data suggest that ecological interactions, and not only physico-chemical conditions, are a dominant factor in determining the contribution of individual species to the outcome of the fermentation.

| S-EPMC7080794 | biostudies-literature

Characterization and dynamic behavior of wild yeast during spontaneous wine fermentation in steel tanks and amphorae.

Project description:We studied the dynamic behavior of wild yeasts during spontaneous wine fermentation at a winery in the Valais region of Switzerland. Wild yeasts in the winery environment were characterized using a PCR-RFLP method. Up to 11 different yeast species were isolated from the vineyard air, whereas only seven were recovered from the grapes surface. We initially investigated a cultureindependent method in pilot-scale steel fermentation tanks and found a greater diversity of yeasts in the musts from two red grape varieties compared to three white grape varieties. We found that the yeasts Metschnikowia pulcherrima, Rhodotorula mucilaginosa, Pichia kluyveri, P. membranifaciens and Saccharomyces cerevisiae remained active at the end of the fermentation. We also studied the dynamic behavior of yeasts in Qvevris for the first time using a novel, highlysensitive quantitative real-time PCR method. We found that non-Saccharomyces yeasts were present during the entire fermentation process, with R. mucilaginosa and P. anomala the most prominent species. We studied the relationship between the predominance of different species and the output of the fermentation process. We identified so-called spoilage yeasts in all the fermentations, but high levels of acetic acid accumulated only in those fermentations with an extended lag phase.

| S-EPMC3659642 | biostudies-literature

Lifestyle, Lineage, and Geographical Origin Influence Temperature-Dependent Phenotypic Variation across Yeast Strains during Wine Fermentation.

Project description:Saccharomyces cerevisiae yeasts are a diverse group of single-celled eukaryotes with tremendous phenotypic variation in fermentation efficiency, particularly at different temperatures. Yeast can be categorized into subsets based on lifestyle (Clinical, Fermentation, Laboratory, and Wild), genetic lineage (Malaysian, Mosaic, North American, Sake, West African, and Wine), and geographical origin (Africa, Americas, Asia, Europe, and Oceania) to start to understand their ecology; however, little is known regarding the extent to which these groupings drive S. cerevisiae fermentative ability in grape juice at different fermentation temperatures. To investigate the response of yeast within the different subsets, we quantified fermentation performance in grape juice by measuring the lag time, maximal fermentation rate (Vmax), and fermentation finishing efficiency of 34 genetically diverse S. cerevisiae strains in grape juice at five environmentally and industrially relevant temperatures (10, 15, 20, 25, and 30 °C). Extensive multivariate analysis was applied to determine the effects of lifestyle, lineage, geographical origin, strain, and temperature on yeast fermentation phenotypes. We show that fermentation capability is inherent to S. cerevisiae and that all factors are important in shaping strain fermentative ability, with temperature having the greatest impact, and geographical origin playing a lesser role than lifestyle or genetic lineage.

| S-EPMC7565122 | biostudies-literature

Differential gene expression in high and low sulfide-producing yeast strains during wine fermentation

Project description:Comparison between two commercial wine yeast strains (UCD522 and P29) differing in their production of H2S during wine fermentation.

2009-12-03 | GSE16215 | GEO

Transcriptomic profiling of five industrial wine yeast strains at three time points during allcoholic fermentation

Project description:Our study involves a transcriptomic approach to the analysis of industrial yeast metabolism. Historically, among the hundreds of yeast species, Saccharomyces cerevisiae has played an important role in scientific investigations and industrial applications, and it is universally acknowledged as one of the model systems for eukaryotic organisms. Yeast is also an important component of the wine fermentation process and determines various attributes of the final product. Our research takes a holistic approach to the improvement of industrial yeast strains by integrating large data sets from various yeast strains during fermentation. This means that analysis can be done in such a way as to co-evaluate several parameters simultaneously to identify points of interest and target genes for metabolic engineering. Eventually we hope to construct an accurate information matrix and a more complete cellular map for the fermenting yeast. This will enable accurate model-building for industrial yeast and facilitated the design of intelligent yeast improvement strategies which can be applied via traditional avenues of molecular biology.

2008-07-01 | GSE11651 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data