Project description:In Saccharomyces cerevisiae, acyl-coenzyme A desaturation by Ole1 requires molecular oxygen. Tween 80, a poly-ethoxylated sorbitan-oleate ester, is therefore routinely included in anaerobic growth media as a source of unsaturated fatty acids (UFAs). During optimization of protocols for anaerobic bioreactor cultivation of this yeast, we consistently observed growth of the laboratory strain S. cerevisiae CEN.PK113-7D in media that contained the anaerobic growth factor ergosterol, but lacked UFAs. To minimize oxygen contamination, additional experiments were performed in an anaerobic chamber. After anaerobic precultivation without ergosterol and Tween 80, strain CEN.PK113-7D and a congenic ole1Δ strain both grew during three consecutive batch-cultivation cycles on medium that contained ergosterol, but not Tween 80. During these three cycles, no UFAs were detected in biomass of cultures grown without Tween 80, while contents of C10 to C14 saturated fatty acids were higher than in biomass from Tween 80-supplemented cultures. In contrast to its UFA-independent anaerobic growth, aerobic growth of the ole1Δ strain strictly depended on Tween 80 supplementation. This study shows that the requirement of anaerobic cultures of S. cerevisiae for UFA supplementation is not absolute and provides a basis for further research on the effects of lipid composition on yeast viability and robustness.
Project description:Completion of eukaryal genomes can be difficult task with the highly repetitive sequences along the chromosomes and short read lengths of second-generation sequencing. Saccharomyces cerevisiae strain CEN.PK113-7D, widely used as a model organism and a cell factory, was selected for this study to demonstrate the superior capability of very long sequence reads for de novo genome assembly. We generated long reads using two common third-generation sequencing technologies (Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)) and used short reads obtained using Illumina sequencing for error correction. Assembly of the reads derived from all three technologies resulted in complete sequences for all 16 yeast chromosomes, as well as the mitochondrial chromosome, in one step. Further, we identified three types of DNA methylation (5mC, 4mC and 6mA). Comparison between the reference strain S288C and strain CEN.PK113-7D identified chromosomal rearrangements against a background of similar gene content between the two strains. We identified full-length transcripts through ONT direct RNA sequencing technology. This allows for the identification of transcriptional landscapes, including untranslated regions (UTRs) (5' UTR and 3' UTR) as well as differential gene expression quantification. About 91% of the predicted transcripts could be consistently detected across biological replicates grown either on glucose or ethanol. Direct RNA sequencing identified many polyadenylated non-coding RNAs, rRNAs, telomere-RNA, long non-coding RNA and antisense RNA. This work demonstrates a strategy to obtain complete genome sequences and transcriptional landscapes that can be applied to other eukaryal organisms.
Project description:BACKGROUND: The need 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. RESULTS: In this work we performed 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 5,596 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being nonsynonymous (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. CONCLUSIONS: 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 http://www.sysbio.se/cenpk.
Project description:Relative quantification of protein abundances of three yeast strains (Saccharomyces cerevisiae CEN.PK113-7D, Kluyveromyces marxianus CBS6556 and Yarrowia lipolytica W29) cultivate in chemostats under different conditions. The conditions for Saccharomyces cerevisiae CEN.PK113-7D are: - Standard condition – 30°C, pH 5.5 - High temperature - 36°C, pH 5.5 - Low pH - 30°C, pH 3.5 - Osmotic stress – 30°C, pH 5.5, 1M KCl The conditions for Kluyveromyces marxianus CBS6556 are: - Standard condition – 30°C, pH 5.5 - High temperature - 40°C, pH 5.5 - Low pH - 30°C, pH 3.5 - Osmotic stress – 30°C, pH 5.5, 0.6 M KCl The conditions for Yarrowia lipolytica W29 are: - Standard condition - 28°C, pH 5.5 - High temperature - 32°C, pH 5.5 - Low pH - 28°C, pH 3.5 This study is part of the OMICS data generation of CHASSY project (European Union’s Horizon 2020 grant agreement No 720824).
Project description:The RNA sequencing experiment was performed in four different chemostat conditions as control for a CAGE sequencing experiment performed in the same conditions using the industrial relevant S. Cerevisiae strain CEN.PK113-7D
Project description:The CAGE experiment was performed in four different chemostat conditions to assess if and how much the Transcription start site landscape changes in the industrial relevant S. Cerevisiae strain CEN.PK113-7D in different conditions. CAGE was also used to obtain accurate TSS annotations for each expressed gene.