Ontology highlight
ABSTRACT:
PROVIDER: PRJNA891065 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR21926300_1.fastq.gz | Fastqsanger.gz | |||
| SRR21926300_2.fastq.gz | Fastqsanger.gz | |||
| SRR21926275_1.fastq.gz | Fastqsanger.gz | |||
| SRR21926275_2.fastq.gz | Fastqsanger.gz | |||
| SRR21926276_1.fastq.gz | Fastqsanger.gz |
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Project description:Four hybrid yeast strains isolated from a variety of industrial substrates were hybridized to an array-CGH platform containing probes to query the whole genomes of seven different Saccharomyces species. For most of the strains we found evidence of multiple interspecific hybridization events and multiple introgressed regions. The strains queried were GSY205 (isolated from a cider fermentation), GSY505 (a contaminant from a lager beer fermentation), GSY2232 (a commercial wine yeast strain), and GSY312 (a commercial lager beer strain). Additionally, 3 different rare viable spores derived from laboratory-created interspecific S. cerevisiae-S. bayanus (aka S. uvarum) hybrids were queried, before and after evolution in chemostats, via S. cerevisiae-S. bayanus microarrays.
2016-12-01 | GSE35549 | GEO
Project description:Background: The most important risk factors for head and neck squamous carcinoma (HNSCC) are tobacco smoking and alcohol consumption, while subgroups are caused by infection with human papillomaviruses (HPV) or Epstein-Barr virus (EBV). Here, we studied alterations of somatic copy-number in whole genome, p16 protein and TP53 mutations by alcohol drinking, smoking and viral infections. Methods: We conducted a prospective cohort study. DNA obtained from tumors and margin samples as well as peripheral blood was assayed by array comparative genomic hybridization using Agilent Whole Human Genome 180K. Mutations of p53 gene by direct sequencing, detection of HPV by polymerase-chain-reaction (PCR), quantification of EBV by reverse transcription-PCR and p16 immunohistochemical (IHC) staining were also performed. prospective cohort study: 225 tumor samples were analyzed by Agilent-022060 SurePrint G3 Human CGH miroarray 4x180K. Log2 Ratio (tumor sample DNA/normal DNA) were compared among none alcohol drinkers, moderate alcohol drinkers, heavy alcohol drinkers, none smokers, moderate smokers, heavy smokers and both. Sample characteristics weres scored as following; Human Papilloma Virus Infection (gene detected by PCR in tumor sample): positive=1; negative=0 p16 protein immunohistochemistry: positive=1; negative=0 tumor grade: matured=0; moderate=1; immature=2 Radiotherapy with or without chemotherapy after operation: performed =1; not performed =0 Recurrence/relapse: rec =1; not rec =0 suvival status:death=1; survive=0 smoking status (Pack year of smoking): none smoker=0; pack-year <20 = 1 (moderate smoker); pack-year <=20 = 2 (heavy smoker) alcohol drinking: Alcohol drinkers were divided into non-drinker or less than one drink per day =0: one and more but less than two drinks per day = moderate drinker 1: two and more drinks per day=heavy drinker 2: during the 20 years preceding their treatment for HNSCC. One drink was defined as containing approximately 10g of alcohol, which is considered equal to 30 ml of hard liquor, 100 ml of wine containing 12% alcohol, or 360 ml of beer.
2013-07-01 | E-GEOD-47443 | biostudies-arrayexpress
Project description:Alterations in stress-related gene-expression may play a role in stress-related drinking and the risk for alcohol dependence. Microarrays were used to measure changes in gene-expression in peripheral blood in non-smoking, social drinking subjects exposed to three types of personalized imagery: neutral, stressful (but not alcohol- related), and alcohol-related cues. Gene-expression was measured at baseline, immediately after, and 1 hour after stimulus presentation. Subjects were allowed to drink up to 750cc of beer in a “taste-test” following stimulus presentation in each imagery condition, and the amount of beer consumed was recorded. Gene-expression levels were compared in 2 groups of non-smoking subjects (n=11/group): heavy drinkers (HD, defined as regular alcohol use over the past year of at least 8 standard drinks/week for women and at least 15 standard drinks/week for men), and moderate drinkers (MD, defined as up to 7 standard drinks/week for women and 14 standard drinks/week for men).
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Project description:The yeast Dekkera bruxellensis is as ethanol tolerant as Saccharomyces cerevisiae and may be found in bottled wine. It causes the spoilage of wine, beer, cider and soft drinks. In wines, the metabolic products responsible for spoilage by Dekkera bruxellensis are mainly volatile phenols. These chemical compounds are responsible for the taints described as ‘‘medicinal’’ in white wines (due to vinyl phenols) and as ‘‘leather’’, ‘‘horse sweat’’ and ‘‘stable’’ in red wines (due to ethyl phenols mainly 4-ethylphenol). Apart from the negative aroma nuances imparted by these yeasts, positive aromas such as ‘smoky’, ‘spicy’ and ‘toffee’ are also cited. Our goal was to identify the impact that the wine spoilage yeast Dekkera bruxellensis has on fermenting S. cerevisiae cells, especially on its gene expression level. To this end we co-inoculated both yeast species at the start of fermentation in a synthetic wine must, using S. cerevisiae-only fermentations without Dekkera bruxellensis as a control. All fermentations were employed in special membrane reactors (1.2 um pore size cut-off) physically separating Dekkera bruxellensis from wine yeast S. cerevisiae. Biomass separation with this membrane was done to abolish the possibility of hybridizing also D. bruxellensis probes on Agilent V2 (8x15K format) G4813 DNA microarrays designed just for S. cerevisiae ORF targets. The 1.2 um pore membrane separating both yeasts allowed the exchange of ethanol, metabolites and sugars during the fermentation.
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Project description:Although metabolic engineering approaches have benefited the development of industrial strains enormously, they are often only partially successful, such that additional rounds of modification are generally needed to ensure microbial strains meet all the requirements of a particular process. Systems biology approaches can aid in yeast design providing an integrated view of yeast physiology and helping to identify targets for modification. Among other phenotypes, the generation of wine yeasts that are able to produce wines with reduced ethanol concentrations has been the focus of extensive research. However, while producing low-alcohol wines, these strains generally produce off-flavour metabolites as metabolic by-products. We therefore used transcriptomics, proteomics and metabolomics to investigate the physiological changes of such an engineered low-ethanol wine strain during wine fermentation to determine possible strategies for by-product remediation. Integration of ‘omics data led to the identification of several processes, including reactions related to the pyruvate node and redox homeostasis, as significantly different compared to a non-engineered parent strain, with acetaldehyde and 2,4,5-trimethyl 1,3-dioxolane identified as the main off-flavour metabolites. Gene remediation strategies were applied to decrease the formation of these metabolites, while maintaining the ‘low-alcohol’ phenotype.
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Project description:Yeast used for the production of wine and wheat beer
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