Physiological characterization of glucose repression in the strains with SNF1 and SNF4 genes deleted

Usaite, Renata; Nielsen, Jens; Olsson, Lisbeth

doi:10.1016/j.jbiotec.2007.09.001

Cited by 12 publications

(12 citation statements)

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“…no growth on non‐fermentable carbon sources (Fig. 2E), which is comparable with the behaviour of the mutant strain snf1 Δ (Usaite et al ., 2008). It produced 20% more ethanol and 50% more glycerol compared with other strains during growth on glucose.…”

Section: Resultsmentioning

confidence: 99%

“…To prepare the pre‐culture, 100 ml of defined medium was inoculated with a single colony and grown in 500 ml of baffled shake flasks at 150 r.p.m. for 16 h. Four litres of defined medium containing 30 g l −1 of glucose was inoculated with an amount of pre‐culture that resulted in a final optical density of 0.01 at 600 nm (OD600; Usaite et al ., 2008). Samples were taken during the exponential growth phase with intervals of about 2 h. To measure the cellular dry weight, 10 ml of culture was filtered through a nitrocellulose filter membrane (pore size of 0.45 µm) as described previously (Ostergaard et al ., 2000).…”

Section: Methodsmentioning

confidence: 99%

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The β‐subunits of the Snf1 kinase in Saccharomyces cerevisiae, Gal83 and Sip2, but not Sip1, are redundant in glucose derepression and regulation of sterol biosynthesis

Zhang

Olsson

Nielsen³

2010

Molecular Microbiology

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SummaryThe conserved Snf1/AMP-activated protein kinase family is one of the central components in the nutrient sensing and regulation of the carbon metabolism in eukaryotes. It is also involved in several other processes such as stress resistance, invasive growth and ageing. Snf1 kinase is composed of a catalytic a-subunit Snf1, a regulatory g-subunit Snf4 and one of three possible b-subunits, Sip1, Sip2 or Gal83. We used a systematic approach to study the role of the three b-subunits by analysing all seven possible combinations of b-subunit deletions together with the reference strain. Previous studies showed that the three b-subunits are redundant for growth on alternative carbon sources. Here we report that the mutant strain with only SIP1 expressed (sip2D gal83D) could utilize acetate, but neither ethanol nor glycerol, as alternative carbon source. We also showed that Gal83 is the most important isoform not only for the growth on non-fermentable carbon sources, but also for regulation of ergosterol biosynthetic genes, under glucoselimited condition. Furthermore, we found that Sip2, but not Sip1, can take over when Gal83 is deleted, but to a lesser extent. However, Sip1 may be sufficient for some other processes such as regulation of the nitrogen metabolism and meiosis.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The β‐subunits of the Snf1 kinase in Saccharomyces cerevisiae, Gal83 and Sip2, but not Sip1, are redundant in glucose derepression and regulation of sterol biosynthesis

Zhang

Olsson

Nielsen³

2010

Molecular Microbiology

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“…The CO 2 emission and residual O 2 were monitored from the exhaust gas using the off-gas analyzer GA4 (DASGIP, Germany), based on zirconium dioxide and a two-beam infrared sensor, respectively. Cultivation medium contained 40 g of ethanol, 15 g of (NH 4 ) 2 SO 4 , 3 g of KH 2 PO 4 , 1.5 g of MgSO 4 × 7 H 2 O, 1 mL of vitamin solution 43 , 1 mL of trace metal solution 43 , and 50 µL of Antiform 204 (Sigma-Aldrich, USA). Osmostress (0.4 M NaCl) was applied when biomass had reached 1.2 g L −1 .…”

Section: Methodsmentioning

confidence: 99%

The yeast osmostress response is carbon source dependent

Babazadeh

Lahtvee

Adiels

et al. 2017

Sci Rep

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Adaptation to altered osmotic conditions is a fundamental property of living cells and has been studied in detail in the yeast Saccharomyces cerevisiae. Yeast cells accumulate glycerol as compatible solute, controlled at different levels by the High Osmolarity Glycerol (HOG) response pathway. Up to now, essentially all osmostress studies in yeast have been performed with glucose as carbon and energy source, which is metabolised by glycolysis with glycerol as a by-product. Here we investigated the response of yeast to osmotic stress when yeast is respiring ethanol as carbon and energy source. Remarkably, yeast cells do not accumulate glycerol under these conditions and it appears that trehalose may partly take over the role as compatible solute. The HOG pathway is activated in very much the same way as during growth on glucose and is also required for osmotic adaptation. Slower volume recovery was observed in ethanol-grown cells as compared to glucose-grown cells. Dependence on key regulators as well as the global gene expression profile were similar in many ways to those previously observed in glucose-grown cells. However, there are indications that cells re-arrange redox-metabolism when respiration is hampered under osmostress, a feature that could not be observed in glucose-grown cells.

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“…Blue area denotes the number of random correlations that were higher than those obtained for the correlation based on the actual data. Each row of plots represents a different dataset (from top to bottom), 1, 2, 3 –[38], [51]; 4 –[41]; 5 –[40]; 6 –[41].…”

Section: Supporting Informationmentioning

confidence: 99%

Contribution of Network Connectivity in Determining the Relationship between Gene Expression and Metabolite Concentration Changes

2014

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One of the primary mechanisms through which a cell exerts control over its metabolic state is by modulating expression levels of its enzyme-coding genes. However, the changes at the level of enzyme expression allow only indirect control over metabolite levels, for two main reasons. First, at the level of individual reactions, metabolite levels are non-linearly dependent on enzyme abundances as per the reaction kinetics mechanisms. Secondly, specific metabolite pools are tightly interlinked with the rest of the metabolic network through their production and consumption reactions. While the role of reaction kinetics in metabolite concentration control is well studied at the level of individual reactions, the contribution of network connectivity has remained relatively unclear. Here we report a modeling framework that integrates both reaction kinetics and network connectivity constraints for describing the interplay between metabolite concentrations and mRNA levels. We used this framework to investigate correlations between the gene expression and the metabolite concentration changes in Saccharomyces cerevisiae during its metabolic cycle, as well as in response to three fundamentally different biological perturbations, namely gene knockout, nutrient shock and nutrient change. While the kinetic constraints applied at the level of individual reactions were found to be poor descriptors of the mRNA-metabolite relationship, their use in the context of the network enabled us to correlate changes in the expression of enzyme-coding genes to the alterations in metabolite levels. Our results highlight the key contribution of metabolic network connectivity in mediating cellular control over metabolite levels, and have implications towards bridging the gap between genotype and metabolic phenotype.

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Physiological characterization of glucose repression in the strains with SNF1 and SNF4 genes deleted

Cited by 12 publications

References 50 publications

The β‐subunits of the Snf1 kinase in Saccharomyces cerevisiae, Gal83 and Sip2, but not Sip1, are redundant in glucose derepression and regulation of sterol biosynthesis

The β‐subunits of the Snf1 kinase in Saccharomyces cerevisiae, Gal83 and Sip2, but not Sip1, are redundant in glucose derepression and regulation of sterol biosynthesis

The yeast osmostress response is carbon source dependent

Contribution of Network Connectivity in Determining the Relationship between Gene Expression and Metabolite Concentration Changes

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