Saccharomyces cerevisiae AWRI1631
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA445767 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6913590.fastq.gz | Fastqsanger.gz | |||
| SRR6913600.fastq.gz | Fastqsanger.gz | |||
| SRR6913610.fastq.gz | Fastqsanger.gz | |||
| SRR6913620.fastq.gz | Fastqsanger.gz | |||
| SRR6913630.fastq.gz | Fastqsanger.gz |
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Project description:Reprogramming a non-methylotrophic industrial host, such as Saccharomyces cerevisiae, to a synthetic methylotroph reprents a huge challenge due to the complex regulation in yeast. Through TMC strategy together with ALE strategy, we completed a strict synthetic methylotrophic yeast that could use methanol as the sole carbon source. However, how cells respond to methanol and remodel cellular metabolic network on methanol were not clear. Therefore, genome-scale transcriptional analysis was performed to unravel the cellular reprograming mechanisms underlying the improved growth phenotype.
2024-05-02 | GSE173802 | GEO
Project description:High-level production of pharmaceutical proteins in industrial microorganism is often limited due to the increased cellular stress from misfolded proteins or protein aggregates. Here, we explore the feasibility of applying a yeast Alzheimer’s disease (AD) model with accumulation of amyloid-β peptides (Aβ42), which presents similar phenotypes of cellular stress. We utilize the suppressors of Aβ42 cytotoxicity as potential metabolic engineering targets to improve industrial protein production. The transcriptomics analyses provide new insights towards developing synthetic yeast cell factories for biosynthesis of valuable pharmaceutical proteins.
2022-05-16 | GSE185570 | GEO
Project description:In the search for renewable sources of energy, bioethanol stands out as a benchmark biofuel because its production is based on a proven technological platform. Bioethanol is produced mainly from the fermentation of carbohydrates derived from agricultural feedstocks by the yeast Saccharomyces cerevisiae. One of the most widely adopted strains is PE-2, a heterothallic diploid naturally adapted to the sugar cane fermentation process used in Brazil. Here we report the molecular genetic analysis of a PE-2 derived diploid (JAY270), and the complete genome sequence of a haploid derivative (JAY291). The JAY270 genome is highly heterozygous (~2 SNPs per kilobase), and has several structural polymorphisms between homologous chromosomes. These chromosomal rearrangements are confined to the peripheral regions of the chromosomes, and appear to reflect ectopic homologous recombination between repetitive DNA sequences. Despite the complex karyotype of JAY270, this diploid, when sporulated, had a high frequency of viable spores (~93%). Crosses of haploids derived from JAY270 to a haploid of the unrelated laboratory strain S288c also resulted in diploids that had good spore viability (75-95%). Thus, the rearrangements that exist near the ends of chromosomes do not impair meiosis and spore viability, as they do not span regions that contain essential genes. This observation is consistent with a model in which the peripheral regions of chromosomes represent plastic domains of the genome that are free to recombine ectopically and experiment with alternative structures that may be associated with a fitness benefit. We also explore features of the JAY270 and JAY291 genomes that help explain their high adaptation to industrial environments, exhibiting desirable phenotypes such as high cell mass production and fermentation kinetics, high temperature growth and oxidative stress tolerance. The genomic manipulation of such strains could enable the creation a new generation of industrial organisms, ideally suited for use as delivery vehicles for future bioenergy technologies.
2009-08-12 | GSE17578 | GEO
Project description:The needs for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering. In this work we establish proof-of-concept that whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between Saccharomyces cerevisiae strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the Saccharomyces Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,873 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being non-silent (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (GAL1, GAL10) and ergosterol biosynthetic pathway (ERG8, ERG9). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function. With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at www.sysbio.se/cenpk. Keywords: Two strains and two different carbon sources Two conditions (glucose and galactose) with two biological replicates for S. cerevisiae strains S288c and CEN.PK113-7D
2010-12-22 | E-GEOD-21479 | biostudies-arrayexpress
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. Experiment Overall Design: Five different Saccharomyces cerevisiae strains used in industrial winemaking processes were used in synthetic must (MS300) fermentations. All fermentations were carried out in triplicate, so each sample is represented by three completely independent biological repeats. Samples for microarray analysis were taken at three different time points during fermentation, representative of the exponential (day2), early stationary (day5) and late stationary (day14) growth stages.
2008-10-21 | E-GEOD-11651 | biostudies-arrayexpress
Project description:The needs for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering. In this work we establish proof-of-concept that whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between Saccharomyces cerevisiae strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the Saccharomyces Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,873 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being non-silent (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (GAL1, GAL10) and ergosterol biosynthetic pathway (ERG8, ERG9). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function. With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at www.sysbio.se/cenpk. Keywords: Two strains and two different carbon sources
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Project description:Improved statistical analysis of budding yeast TAG microarrays
| PRJNA92461 | ENA
Project description:In the search for renewable sources of energy, bioethanol stands out as a benchmark biofuel because its production is based on a proven technological platform. Bioethanol is produced mainly from the fermentation of carbohydrates derived from agricultural feedstocks by the yeast Saccharomyces cerevisiae. One of the most widely adopted strains is PE-2, a heterothallic diploid naturally adapted to the sugar cane fermentation process used in Brazil. Here we report the molecular genetic analysis of a PE-2 derived diploid (JAY270), and the complete genome sequence of a haploid derivative (JAY291). The JAY270 genome is highly heterozygous (~2 SNPs per kilobase), and has several structural polymorphisms between homologous chromosomes. These chromosomal rearrangements are confined to the peripheral regions of the chromosomes, and appear to reflect ectopic homologous recombination between repetitive DNA sequences. Despite the complex karyotype of JAY270, this diploid, when sporulated, had a high frequency of viable spores (~93%). Crosses of haploids derived from JAY270 to a haploid of the unrelated laboratory strain S288c also resulted in diploids that had good spore viability (75-95%). Thus, the rearrangements that exist near the ends of chromosomes do not impair meiosis and spore viability, as they do not span regions that contain essential genes. This observation is consistent with a model in which the peripheral regions of chromosomes represent plastic domains of the genome that are free to recombine ectopically and experiment with alternative structures that may be associated with a fitness benefit. We also explore features of the JAY270 and JAY291 genomes that help explain their high adaptation to industrial environments, exhibiting desirable phenotypes such as high cell mass production and fermentation kinetics, high temperature growth and oxidative stress tolerance. The genomic manipulation of such strains could enable the creation a new generation of industrial organisms, ideally suited for use as delivery vehicles for future bioenergy technologies. This microarray experiment was used to compare the relative gene expression levels between two unrelated S. cerevisiae strain backgrounds: JAY270 and JAY309. Total RNA from each strain was prepared and used to synthesize differentially labeled cDNAs (Cy5 and C3 respectively). A positive Log2 (Red/Green) ratio indicates transcripts more abundant in JAY270, while a negative Log2 (Red/Green) ration indicates transcripts more abundant in JAY309.
2010-05-15 | E-GEOD-17578 | biostudies-arrayexpress
Project description:Analysis of yeast genome instability during industrial-scale bioethanol fermentation
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Project description:The oomycete pathogen Phytophthora sojae causes root rot of soybean. During infection, the pathogen is thought to deliver dozens, if not hundreds, of effector proteins into the host to manipulate intracellular systems. Although these pathogen proteins often exhibit similar N-terminal delivery domains, the remaining effector region is rarely homologous to known protein domains, making it difficult to predict its biochemical function during infection. As a complement to studies in the natural host, Saccharomyces cerevisiae has been successfully used as a model system to explore the biochemical function of individual pathogen effectors. The presumption is that many effectors target conserved eukaryotic pathways in the host and consequently the expression of effectors in yeast will confer corresponding phenotypes. Indeed, putative effector functions identified using yeast functional genomic approaches have subsequently been validated in the natural host. Over-expression of the Phytophthora sojae effector Avh172 (PsAvh172) inhibits the growth of Saccharomyces cerevisiae, suggesting that the effector targets a biological pathway conserved with plants. In this study, the transcriptomes of yeast expressing PsAvh172 or an empty vector were compared to examine the global transcriptional response, in hopes of discerning the effectors biochemical target.
2021-01-01 | E-MTAB-4682 | biostudies-arrayexpress