Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1070026 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27942510.fastq.gz | Fastqsanger.gz | |||
| SRR27942511.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:Second fermentation in a bottle supposes such specific conditions that undergo yeasts to a set of stress situations like high ethanol, low nitrogen, low pH or sub-optimal temperature. Also, yeast have to grow until 1 or 2 generations and ferment all sugar available while they resist increasing CO2 pressure produced along with fermentation. Because of this, yeast for second fermentation must be selected depending on different technological criteria such as resistance to ethanol, pressure, high flocculation capacity, and good autolytic and foaming properties. All of these stress factors appear sequentially or simultaneously, and their superposition could amplify their inhibitory effects over yeast growth. Considering all of the above, it has supposed interesting to characterize the adaptive response of commercial yeast strain EC1118 during second-fermentation experiments under oenological/industrial conditions by transcriptomic profiling. We have pointed ethanol as the most relevant environmental condition in the induction of genes involved in respiratory metabolism, oxidative stress, autophagy, vacuolar and peroxisomal function, after comparison between time-course transcriptomic analysis in alcoholic fermentation and transcriptomic profiling in second fermentation. Other examples of parallelism include overexpression of cellular homeostasis and sugar metabolism genes. Finally, this study brings out the role of low-temperature on yeast physiology during second-fermentation.
2011-05-31 | GSE29273 | GEO
Project description:We used genome-wide expression analyses to study the response of Saccharomyces cerevisiae to stress throughout a 15-day wine fermentation. Forty percent of the yeast genome significantly changed expression levels to mediate long-term adaptation to an environment in which ethanol is both a stressor and a carbon source. Within this set, we identify a group of 223 genes, designated as the Fermentation Stress Response (FSR), that are dramatically and permanently induced; FSR genes exhibited changes ranging from four-to eighty-fold. The FSR is novel; 62% of the genes involved have not been implicated in global stress responses and 28% of the 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, was responsible for entry of yeast cells into stationary phase. Ethanol seems to regulate yeast metabolism through hitherto undiscovered regulatory networks during wine fermentation. Keywords: time course, stress response, fermentation
2008-04-17 | GSE8536 | GEO
Project description:In our previous work, we showed the positive effect of the magnesium and the negative effect of the copper on yeast fermentation performance. The magnesium increases the ethanol yield and a faster glucose consumption by the yeast, on the other hand, the copper provides an opposite effect in yeast under fermentation condition. Therefore, from this contrasting effect we performed the gene-wide expression analysis in the industrial yeast Saccharomyces cerevisiae JP1 under fermentation condition in order to reveal the gene expression profile upon magnesium and copper supplementation.
2015-12-09 | GSE75803 | GEO
Project description:The yeast Saccharomyces cerevisiae is well known for its high ethanol production performances. An original fermentation process that allows the yeast S. cerevisiae to produce in less than 45 h more than 150 g/l ethanol (i.e. 18.9°GL) was set up in our laboratory [1]. Under this condition, the yeast cells induce a dynamic process to adapt to increased ethanol concentration by a mechanism that is likely different to the stress response triggered by sudden ethanol addition to exponentially growing cells [2]. Kinetic analysis of the growth curve identified two main phases: a growth phase that ended up at 90 g/l ethanol and then an uncoupling phase during which non-growing cells kept producing ethanol. This latter phase is also characterized with an increased loss of viability. In order to investigate on a genome scale the expression changes occurring during this process, gene expression was quantified using DNA chips technology at six different time-points during fed-batch fermentation. [1] Alfenore et al, Appl. Microbiol. Biotechnol. 60 : 67-72, 2002. [2] Alexandre H. et al., FEBS Lett. 498(1) : 98-103, 2001.
2009-09-01 | GSE15493 | GEO
Project description:Second fermentation in a bottle supposes such specific conditions that undergo yeasts to a set of stress situations like high ethanol, low nitrogen, low pH or sub-optimal temperature. Also, yeast have to grow until 1 or 2 generations and ferment all sugar available while they resist increasing CO2 pressure produced along with fermentation. Because of this, yeast for second fermentation must be selected depending on different technological criteria such as resistance to ethanol, pressure, high flocculation capacity, and good autolytic and foaming properties. All of these stress factors appear sequentially or simultaneously, and their superposition could amplify their inhibitory effects over yeast growth. Considering all of the above, it has supposed interesting to characterize the adaptive response of commercial yeast strain EC1118 during second-fermentation experiments under oenological/industrial conditions by transcriptomic profiling. We have pointed ethanol as the most relevant environmental condition in the induction of genes involved in respiratory metabolism, oxidative stress, autophagy, vacuolar and peroxisomal function, after comparison between time-course transcriptomic analysis in alcoholic fermentation and transcriptomic profiling in second fermentation. Other examples of parallelism include overexpression of cellular homeostasis and sugar metabolism genes. Finally, this study brings out the role of low-temperature on yeast physiology during second-fermentation. S. cerevisiae EC1118 pre-adapted to ethanol cells and sucrose (20 g/L) were added to 20 L of base wine (Cavas Freixenet, Sant Sadurní D’Anoia, Spain). Complete volume was bottled with 350 mL each one. All were sealed and incubated in static conditions at 16ºC for approximately 40 days after tirage. Three samples were taken during the process for transcriptional study of the physiological adaptation of yeast cells to industrial second fermentation conditions. A sample corresponding to exponential-growth phase under unstressed conditions (in YPD at 28ºC) was used as an external reference. Three timepoints from second-fermentation were monitored and three biological replicates from each timepoint were analyzed.
2011-05-31 | E-GEOD-29273 | biostudies-arrayexpress
Project description:Solid State Fermentation (SSF) processes have been explored for yeast growth and protein and metabolites production. However, most of these processes lack standardization. In this work, we present a polylactic acid (PLA) 3D printed matrix that dramatically enhances yeast growth when embedded in liquid media compared to equivalent static cultures, and changes yeast expression patterns at the proteome level. Moreover, differences in sugar assimilation and ethanol production, as the main product of alcoholic fermentation, are observed. Our results suggest that these matrixes may be useful for a vast range of biotechnological applications based on yeast fermentation.
2023-09-07 | PXD043759 | Pride
Project description:Yeast transcriptomics in sugarcane-based ethanol fermentation
| PRJNA182143 | ENA
Project description:We used genome-wide expression analyses to study the response of Saccharomyces cerevisiae to stress throughout a 15-day wine fermentation. Forty percent of the yeast genome significantly changed expression levels to mediate long-term adaptation to an environment in which ethanol is both a stressor and a carbon source. Within this set, we identify a group of 223 genes, designated as the Fermentation Stress Response (FSR), that are dramatically and permanently induced; FSR genes exhibited changes ranging from four-to eighty-fold. The FSR is novel; 62% of the genes involved have not been implicated in global stress responses and 28% of the 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, was responsible for entry of yeast cells into stationary phase. Ethanol seems to regulate yeast metabolism through hitherto undiscovered regulatory networks during wine fermentation. Experiment Overall Design: The main study is based on expression measurements at 0.5,2,3.5,7 and 10 % ethanol (corresponding to roughly 24,48,60,120 and 340 hours). Experiments were done in triplicate (biological replicates). This submission also includes the files at 1 hour and at 12 hours for completeness. (also in triplicate)
2008-06-16 | E-GEOD-8536 | biostudies-arrayexpress
Project description:In our previous work, we showed the positive effect of the magnesium and the negative effect of the copper on yeast fermentation performance. The magnesium increases the ethanol yield and a faster glucose consumption by the yeast, on the other hand, the copper provides an opposite effect in yeast under fermentation condition. Therefore, from this contrasting effect we performed the gene-wide expression analysis in the industrial yeast Saccharomyces cerevisiae JP1 under fermentation condition in order to reveal the gene expression profile upon magnesium and copper supplementation. Fermentation assays was performed with the industrial yeast S. cerevisiae JP1 in reference medium (mineral concentration balanced), in the medium supplemented with 500 mg/L of magnesium (Mg2+ medium) and in the medium supplemented with 1 mg/L of copper (Cu2+ medium).
2015-12-09 | E-GEOD-75803 | biostudies-arrayexpress
Project description:The yeast Saccharomyces cerevisiae is well known for its high ethanol production performances. An original fermentation process that allows the yeast S. cerevisiae to produce in less than 45 h more than 150 g/l ethanol (i.e. 18.9°GL) was set up in our laboratory [1]. Under this condition, the yeast cells induce a dynamic process to adapt to increased ethanol concentration by a mechanism that is likely different to the stress response triggered by sudden ethanol addition to exponentially growing cells [2]. Kinetic analysis of the growth curve identified two main phases: a growth phase that ended up at 90 g/l ethanol and then an uncoupling phase during which non-growing cells kept producing ethanol. This latter phase is also characterized with an increased loss of viability. In order to investigate on a genome scale the expression changes occurring during this process, gene expression was quantified using DNA chips technology at six different time-points during fed-batch fermentation. [1] Alfenore et al, Appl. Microbiol. Biotechnol. 60 : 67-72, 2002. [2] Alexandre H. et al., FEBS Lett. 498(1) : 98-103, 2001. We measure the changes in the gene expression of ethanol stressed culture at five different time-points during fed-batch fermentation compared to a common reference consisting of exponentially growing yeast cells ( sample number 1 : growing cells ; low ethanol concentration of 17 g/l ; specific growth rate of 0.3 h-1) . The sets corresponded to sample number 2 : growing cells/ethanol concentration of 60 g/l ; sample number 3 : before growth arrest/ethanol concentration of 90 g/l ; sample number 4 : growth arrest/ethanol concentration of 95 g/l ; sample number 5 : 1 hour after growth arrest/ethanol concentration of 100 g/l and sample number 6 : uncoupling phase/ethanol concentration of 125 g/l. For each sample, total RNAs from one yeast culture (no biological replicate) were extracted three times (technical replicates -extract). For labelling, we labelled the common reference with dCTP-Cy5 and labelled the sample with dCTP-Cy3 and hybridized cDNA on three independent microarrays, given rise to six data value per gene (each gene is duplicate in the slide).
2009-09-01 | E-GEOD-15493 | biostudies-arrayexpress