Project description:Glycolysis is upregulated in cells under specific conditions, such as hypoxia and high energy demand, to achieve the metabolic requirements for continued cell proliferation. However, the mechanism of this increased glycolytic rate remains poorly understood. In the budding yeast Saccharomyces cerevisiae, we discovered that hypoxia induces concentration of many glycolytic enzymes, including the Pfk2p subunit of the ratelimiting enzyme, phosphofructokinase, into a single, non-membrane-bound granule that we define as the "glycolytic body" or "G body". Pfk2p localization to G bodies depends on its N-terminal, intrinsically disordered region. In order to identify factors important for G body formation, we conducted a yeast kinome screen and identified the AMP kinase ortholog, Snf1p, to be required for the localization of multiple glycolytic enzymes to G bodies. Further, proteomic analyses of purified G bodies identified a core set of resident factors, many of which are essential for G body integrity. Cells incapable of forming G bodies in hypoxic conditions display abnormal cell division and produce inviable daughter cells. Conversely, cells that form G bodies show increased glucose consumption and decreased levels of glycolytic intermediates. Importantly, G bodies also form in human, hepatocarcinoma cells upon hypoxic stress. Together, our results suggest that G body formation is a conserved, adaptive response to increase glycolytic output during hypoxia or tumorigenesis.
Project description:Glycolytic (G) bodies were purified from hypoxic yeast using differential centrifugation and immunoprecipitation by Pfk2-GFP-Flag in order to determine the RNAs that localize to G bodies by determining the enrichment of RNAs copurified with G bodies over both the flow through and total RNA fractions. We find significant overlap between enriched RNAs and RNAs bound by glycolysis enzymes in normoxic conditions. Our study determined that RNA is an integral component of G bodies and is required for G body formation. Specific mRNAs are only slightly enriched in G bodies.
Project description:Metabolic fluxes may be regulated "hierarchically," e.g., by changes of gene expression that adjust enzyme capacities (V(max)) and/or "metabolically" by interactions of enzymes with substrates, products, or allosteric effectors. In the present study, a method is developed to dissect the hierarchical regulation into contributions by transcription, translation, protein degradation, and posttranslational modification. The method was applied to the regulation of fluxes through individual glycolytic enzymes when the yeast Saccharomyces cerevisiae was confronted with the absence of oxygen and the presence of benzoic acid depleting its ATP. Metabolic regulation largely contributed to the approximately 10-fold change in flux through the glycolytic enzymes. This contribution varied from 50 to 80%, depending on the glycolytic step and the cultivation condition tested. Within the 50-20% hierarchical regulation of fluxes, transcription played a minor role, whereas regulation of protein synthesis or degradation was the most important. These also contributed to 75-100% of the regulation of protein levels. Keywords: Condition comparison
Project description:Analysis of the transcriptome of the wild-type strain BY4741 and its isogenic derivative ixr1 null, grown in aerobic, hypoxic conditions and after a hypoxic shift
Project description:Analysis of the transcriptome of the wild-type strain BY4741 and its isogenic derivative ixr1 null, grown in aerobic, hypoxic conditions and after a hypoxic shift Two biological replicates in two technical replicates for each growth condition
Project description:As a result of ancestral whole genome and small-scale duplication events, the genome of Saccharomyces cerevisiaeM-bM-^@M-^Ys, and of many eukaryotes, still contain a substantial fraction of duplicated genes. In all investigated organisms, metabolic pathways, and more particularly glycolysis, are specifically enriched for functionally redundant paralogs. In ancestors of the Saccharomyces lineage, the duplication of glycolytic genes is purported to have played an important role leading to S. cerevisiae current lifestyle favoring fermentative metabolism even in the presence of oxygen and characterized by a high glycolytic capacity. In modern S. cerevisiae, the 12 glycolytic reactions leading to the biochemical conversion from glucose to ethanol are encoded by 27 paralogs. In order to experimentally explore the physiological role of this genetic redundancy, a yeast strain with a minimal set of 14 paralogs was constructed (MG strain). Remarkably, a combination of quantitative, systems approach and of semi-quantitative analysis in a wide array of growth environments revealed the absence of phenotypic response to the cumulative deletion of 13 glycolytic paralogs. This observation indicates that duplication of glycolytic genes is not a prerequisite for achieving the high glycolytic fluxes and fermentative capacities that are characteristic for S. cerevisiae and essential for many of its industrial applications and argues against gene dosage effects as a means for fixing minor glycolytic paralogs in the yeast genome. MG was carefully designed and constructed to provide a robust, prototrophic platform for quantitative studies, and is made available to the scientific community. The goals of the present study are to experimentally explore genetic redundancy in yeast glycolysis by cumulative deletion of minor paralogs and to provide a new experimental platform for fundamental yeast research by constructing a yeast strain with a functional M-bM-^@M-^Xminimal glycolysisM-bM-^@M-^Y. To this end, we deleted 13 minor paralogs, leaving only the 14 major paralogs for the S. cerevisiae glycolytic pathway. The cumulative impact of deleting all minor paralogs was investigated by two complementary approaches. A first, quantitative analysis focused on the impact on glycolytic flux under a number of controlled cultivation conditions that, in wild-type strains, result in different glycolytic fluxes. These quantitative growth studies were combined with transcriptome, enzyme-activity and intracellular metabolite assays to capture potential small phenotypic effects. A second, semi-quantitative characterization explored the phenotype of the M-bM-^@M-^Xminimal glycolysisM-bM-^@M-^Y strain under a wide array of experimental conditions to identify potential context-dependent phenotypes
Project description:Simpler is not always better: transplantation of the whole glycolytic pathway from Yarrowia lipolytica to Saccharomyces cerevisiae reveals essential regulatory mechanisms
Project description:Iron is an essential cofactor for enzymes involved in numerous cellular processes. We analyzed the metabolomes and transcriptomes of yeast grown in iron-rich and iron-poor media to determine which biosynthetic processes are altered when iron availability falls.
Project description:<p><em>Saccharomyces cerevisiae</em> is a widely used cell factory; therefore, it is important to understand how it organizes key functional parts when cultured under different conditions. Here, we perform a multiomics analysis of <em>S. cerevisiae</em> by culturing the strain with a wide range of specific growth rates using glucose as the sole limiting nutrient. Under these different conditions, we measure the absolute transcriptome, the absolute proteome, the phosphoproteome, and the metabolome. Most functional protein groups show a linear dependence on the specific growth rate. Proteins engaged in translation show a perfect linear increase with the specific growth rate, while glycolysis and chaperone proteins show a linear decrease under respiratory conditions. Glycolytic enzymes and chaperones, however, show decreased phosphorylation with increasing specific growth rates; at the same time, an overall increased flux through these pathways is observed. Further analysis show that even though mRNA levels do not correlate with protein levels for all individual genes, the transcriptome level of functional groups correlates very well with its corresponding proteome. Finally, using enzyme-constrained genome-scale modeling, we find that enzyme usage plays an important role in controlling flux in amino acid biosynthesis.</p>