Control of ATP homeostasis during the respiro‐fermentative transition in yeast

Walther, Thomas; Novo, Maïté; Rössger, Katrin; Létisse, Fabien; Loret, M.; Portais, Jean‐Charles; François, Jean

doi:10.1038/msb.2009.100

Cited by 75 publications

(111 citation statements)

References 84 publications

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“…Second, none of these strains exhibited measurable trehalose-6P synthase activity, whereas wild type (TPS1) cells led to a specific activity of 6.5 nmol/ min/mg protein. Third, none of these strains could lead to trehalose-6P accumulation upon glucose addition to trehalosegrown cells according to experimental conditions described in (31). Contrary to the control strain that showed a burst of trehalose-6P 5 min after the glucose pulse (8 mol/g DW), trehalose-6P was below the detection level in cells expressing the different tps1 alleles.…”

Section: Construction and Validation Of Inactive Catalytic Variants Omentioning

confidence: 93%

Yeast Tolerance to Various Stresses Relies on the Trehalose-6P Synthase (Tps1) Protein, Not on Trehalose

Petitjean

Teste

François

et al. 2015

Journal of Biological Chemistry

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Background: Decades of observations strengthened the idea that trehalose is a chemical chaperone. Results: A catalytically inactive variant of the trehalose-6P synthase (Tps1) maintains cell survival and energy homeostasis under stress exposure. Conclusion: The Tps1 protein itself, not trehalose, is crucial for cell integrity. Significance: This work provides unbiased evidence for an alternative function of Tps1, a new "moonlighting" protein.

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Section: Construction and Validation Of Inactive Catalytic Variants Omentioning

confidence: 93%

Yeast Tolerance to Various Stresses Relies on the Trehalose-6P Synthase (Tps1) Protein, Not on Trehalose

Petitjean

Teste

François

et al. 2015

Journal of Biological Chemistry

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“…This transiently buffers energy charge but in the long term can result in fatal nucleotide depletion (Walther et al 2010). Subsequent catabolism of the resulting IMP can yield ribose phosphate, a potential energy substrate.…”

Section: Mechanisms Underlying Rescue By Glutamine or Nucleosidesmentioning

confidence: 99%

“…Other nucleotide monophosphates can be similarly degraded to release ribose phosphate ( Fig. 6A; Walther et al 2010;Xu et al 2013). Upon supplementation of the starving cells with nucleosides, in addition to restoration of energy charge and nucleotide pools (Fig.…”

Section: Mechanisms Underlying Rescue By Glutamine or Nucleosidesmentioning

confidence: 99%

Autophagy provides metabolic substrates to maintain energy charge and nucleotide pools in Ras-driven lung cancer cells

et al. 2016

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Autophagy degrades and is thought to recycle proteins, other macromolecules, and organelles. In genetically engineered mouse models (GEMMs) for Kras-driven lung cancer, autophagy prevents the accumulation of defective mitochondria and promotes malignancy. Autophagy-deficient tumor-derived cell lines are respiration-impaired and starvation-sensitive. However, to what extent their sensitivity to starvation arises from defective mitochondria or an impaired supply of metabolic substrates remains unclear. Here, we sequenced the mitochondrial genomes of wild-type or autophagy-deficient (Atg7) Kras-driven lung tumors. Although Atg7 deletion resulted in increased mitochondrial mutations, there were too few nonsynonymous mutations to cause generalized mitochondrial dysfunction. In contrast, pulse-chase studies with isotope-labeled nutrients revealed impaired mitochondrial substrate supply during starvation of the autophagy-deficient cells. This was associated with increased reactive oxygen species (ROS), lower energy charge, and a dramatic drop in total nucleotide pools. While starvation survival of the autophagy-deficient cells was not rescued by the general antioxidant N-acetyl-cysteine, it was fully rescued by glutamine or glutamate (both amino acids that feed the TCA cycle and nucleotide synthesis) or nucleosides. Thus, maintenance of nucleotide pools is a critical challenge for starving Kras-driven tumor cells. By providing bioenergetic and biosynthetic substrates, autophagy supports nucleotide pools and thereby starvation survival.

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“…ebi.ac.uk/metabolights (study identifier: MTBLS29). To demonstrate that MAMS is indeed able to retrieve biological information from a single or a small ensemble of yeast cells positioned in the MAMS reservoirs, we perturbed them with 2-deoxy-D-glucose (2DG), a drug that blocks glycolysis (16,17). We dynamically monitored the response both with MAMS on the single-cell and near-single-cell level, and with traditional MALDI-MS on the population level, and compared the response of the two measurements.…”

Section: Mams Is Capable To Detect Biological Information From Singlementioning

confidence: 99%

“…3 A and B). This is expected, because 2DG6P inhibits the glycolysis pathway upstream of the phosphofructokinase (Pfk) enzyme, which generates F16BP (16,17), rendering the production of ATP (and thus the observed ATP/ADP ratio) independent of the amount of F16BP present in the cell.…”

Section: Mams Is Capable To Detect Biological Information From Singlementioning

confidence: 99%

Mass spectrometry-based metabolomics of single yeast cells

Ibáñez¹,

Fagerer²,

Schmidt³

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

214

123

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Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.single-cell measurements | MALDI mass spectrometry | baker's yeast E ven genetically identical cells present in the same microenvironment can express different phenotypes, for a number of reasons: cell-to-cell heterogeneity can stem from differences in the cell age and differences in the cell cycle stage, and stochastic effects together with feedback mechanisms can lead to distinctively different phenotypes, too (1-6). As population-level measurement techniques inherently average out such cell-to-cell differences, biochemical mechanisms underlying a studied system cannot be deduced from such measurements. Thus, to detect and exploit this heterogeneity, new analytical platforms with a sensitivity at the single-cell level and the ability to perform quantitative analyses must be developed and validated.Motivated by advances of mass spectrometry (MS) in metabolomics, the analytical chemistry community has stepped up its efforts toward realizing MS-based single-cell metabolomics (1, 2). A number of analytical approaches were developed with detection limits low enough for single-cell metabolite analyses [e.g., nanostructured surfaces (7, 8), postionization techniques (9, 10), modified laser optics (11), the use of microsampling tools (12, 13), microarrays for MS measurements (14, 15), etc.]. Until now, however, most MS studies targeting single-cell metabolite analysis have only shown the analytical capabilities, but have not demonstrated that true biological information can be retrieved from studying the metabolism of single cells.Here, using the unicellular eukaryotic model organism Saccharomyces cerevisiae, we present an analytical validation of a single-cell metabolite analysis using the microarrays for mass spectrometry (MAMS) platform. This validation concerns both the analytical methodology and the biological information, by monitoring expected cellular responses upon an environmental and a genetic perturbation. Furthermore, we present examples of biological insight that are only accessible with a platform such as MAMS. Specifically, we unravel metabolite-metabolite correlations, and visualize coexisting subpopulations in an isogenic cell culture. This technology can now be used to reveal metabolic differences in cells of isogenic cell populations, such as differences caused by cell cycles stages, cell ages, or stochastically induced phenotypic differences. Results and ...

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Control of ATP homeostasis during the respiro‐fermentative transition in yeast

Cited by 75 publications

References 84 publications

Yeast Tolerance to Various Stresses Relies on the Trehalose-6P Synthase (Tps1) Protein, Not on Trehalose

Yeast Tolerance to Various Stresses Relies on the Trehalose-6P Synthase (Tps1) Protein, Not on Trehalose

Autophagy provides metabolic substrates to maintain energy charge and nucleotide pools in Ras-driven lung cancer cells

Mass spectrometry-based metabolomics of single yeast cells

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