A Saccharomyces cerevisiae strain with a minimal complement of glycolytic genes reveals strong redundancies in central metabolism
ABSTRACT: As a result of ancestral whole genome and small-scale duplication events, the genome of Saccharomyces cerevisiae’s, 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 ‘minimal glycolysis’. 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 ‘minimal glycolysis’ strain under a wide array of experimental conditions to identify potential context-dependent phenotypes
Project description:This a model from the article:
How yeast cells synchronize their glycolytic oscillations: a perturbation analytic treatment
Bier M, Bakker BM, Westerhoff HV.
Biophys. J2000 Mar;78(3):1087-93.
Of all the lifeforms that obtain their energy from glycolysis, yeast cells are among the most basic. Under certain conditions the concentrations of the glycolytic intermediates in yeast cells can oscillate. Individual yeast cells in a suspension can synchronize their oscillations to get in phase with each other. Although the glycolytic oscillations originate in the upper part of the glycolytic chain, the signaling agent in this synchronization appears to be acetaldehyde, a membrane-permeating metabolite at the bottom of the anaerobic part of the glycolytic chain. Here we address the issue of how a metabolite remote from the pacemaking origin of the oscillation may nevertheless control the synchronization. We present a quantitative model for glycolytic oscillations and their synchronization in terms of chemical kinetics. We show that, in essence, the common acetaldehyde concentration can be modeled as a small perturbation on the "pacemaker" whose effect on the period of the oscillations of cells in the same suspension is indeed such that a synchronization develops.
Project description:In Scheffersomyces stipitis and related fungal species the genes for L-rhamnose catabolism RHA1, LRA2, LRA3 and LRA4 but not LADH are clustered. We find that located next to the cluster is a transcription factor, TRC1, which is conserved among related species.Our transcriptome analysis shows that all the catabolic genes and all genes of the cluster are up-regulated on L-rhamnose. Among the genes that were also up-regulated on L-rhamnose were two transcription factors including the TRC1. In addition, in 16 out of the 32 analysed fungal species only RHA1, LRA2 and LRA3 are in a cluster. The clustering of RHA1, LRA3 and TRC1 is also conserved in species not closely related to S. stipitis. Since the LRA4 is often not part of the cluster and it has several paralogs in L-rhamnose utilising yeasts we analysed the function of one of the paralogs, RHA41 by heterologous expression and biochemical characterization. Rha41p has similar catalytic properties but the transcript was not up-regulated on L-rhamnose. The RHA1, LRA2, LRA4 and LADH genes were previously characterized in Sheffersomyces (Pichia) stipitis. We expressed the L-rhamnonate dehydratase, Rha3p, in S. cerevisiae, estimated the kinetic constants of the protein and showed that it indeed has activity with L-rhamnonate. A six chip study using total RNA recovered from three separate cultures of S. stipitis CBS 6054 grown glucose and respectively three separate cultures grown on rhamnose
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. Experiment Overall Design: To quantify the regulation of the Vmax values and the fluxes at the different levels of gene expression, we measured how the fluxes through the glycolytic enzymes, the Vmax values, and the concentrations of these enzymes and their corresponding mRNA concentrations change when yeast is exposed to aerobic and anaerobic (with and without challenges.
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 Overall design: To quantify the regulation of the Vmax values and the fluxes at the different levels of gene expression, we measured how the fluxes through the glycolytic enzymes, the Vmax values, and the concentrations of these enzymes and their corresponding mRNA concentrations change when yeast is exposed to aerobic and anaerobic (with and without challenges.
Project description:We adapted ChIP-Rx method established in cells to fly tissues for quantitative ChIP-seq. We found the deposition of H3K27me3 during aging loses fidelity, resulting its propagation across the epigenome; lowering H3K27me3 by PRCs-deficiency promotes healthy lifespan by mitigating this trend. Quantitative multi-omic analysis converges on a central role of glycolysis, linking H3K27me3 dynamics to the regulation of glycolytic genes, which correspondingly rewire cellular metabolic homeostasis including energy and redox potential that impact lifespan and adult fitness. Overall design: Compare H3K27me3 distribution with age and in two PRC2 trans-heterozygous double mutants. Compare transcriptome changes in normal aging and PRC2 mutants, 3 replicates for each genotype at given age.
Project description:Many cancers rely on glycolytic metabolism to fuel rapid proliferation. This has spurred interest in designing drugs that target tumor glycolysis such as AZD3965, a small molecule inhibitor of Monocarboxylate Transporter 1 (MCT1) currently undergoing Phase I evaluation for cancer treatment. Since MCT1 mediates proton-linked transport of monocarboxylates such as lactate and pyruvate across the plasma membrane (Halestrap and Meredith, 2004), AZD3965 is thought to block tumor growth through disruption of lactate transport and glycolysis. Here we show that MCT1 inhibition impairs proliferation of glycolytic breast cancer cells that express MCT4 via disruption of pyruvate rather than lactate export. We found that MCT1 expression is elevated in glycolytic breast tumors and cell lines as well as in malignant breast and lung tissues. High MCT1 expression predicts poor prognosis in breast and lung cancer patients. Stable knockdown and AZD3965-mediated inhibition of MCT1 promote oxidative metabolism. Acute inhibition of MCT1 reduces pyruvate export rate but does not consistently alter lactate transport or glycolytic flux in breast cancer cells that also express MCT4. Despite the lack of glycolysis impairment, MCT1 loss-of-function decreases breast cancer cell proliferation and blocks growth of mammary fat pad xenograft tumors. Our data suggest that MCT1 expression is elevated in glycolytic cancers to promote pyruvate export, which when inhibited enhances oxidative metabolism and reduces proliferation. This study presents an alternative molecular consequence of MCT1 inhibitors that further supports their use as anti-cancer therapeutics. Since MCT1 levels are elevated in glycolytic and malignant breast tumors, we hypothesized that MCT1 may contribute to the Warburg effect metabolic phenotype. To test this hypothesis, we generated whole genome microarray data from breast cancer cell lines either a) expressing a short hairpin (sh)RNA-mediated stable knockdown of MCT1; or b) treated for 24 hours with an MCT1 inhibitor (AZD3965). Scramble shRNA or DMSO were used as controls, and all conditions were analzed in triplicate. The cell lines used – HS578T, SUM149PT, and SUM159PT – are among the most glycolytic in a panel of 31 breast cancer cell lines.
Project description:Wolf2000 - Cellular interaction on glycolytic
oscillations in yeast
A two-cell model of glycolysis.
This model is described in the article:
Effect of cellular
interaction on glycolytic oscillations in yeast: a theoretical
Wolf J, Heinrich R.
Biochem. J. 2000 Jan; 345 Pt 2:
On the basis of a detailed model of yeast glycolysis, the
effect of intercellular dynamics is analysed theoretically. The
model includes the main steps of anaerobic glycolysis, and the
production of ethanol and glycerol. Transmembrane diffusion of
acetaldehyde is included, since it has been hypothesized that
this substance mediates the interaction. Depending on the
kinetic parameter, the single-cell model shows both stationary
and oscillatory behaviour. This agrees with experimental data
with respect to metabolite concentrations and phase shifts. The
inclusion of intercellular coupling leads to a variety of
dynamical modes, such as synchronous oscillations, and
different kinds of asynchronous behavior. These oscillations
can co-exist, leading to bi- and tri-rhythmicity. The
corresponding parameter regions have been identified by a
bifurcation analysis. The oscillatory dynamics of synchronized
cell populations are investigated by calculating the phase
responses to acetaldehyde pulses. Simulations are performed
with respect to the synchronization of two subpopulations that
are oscillating out of phase before mixing. The effect of the
various process on synchronization is characterized
quantitatively. While continuous exchange of acetaldehyde might
synchronize the oscillations for appropriate sets of parameter
values, the calculated synchronization time is longer than that
observed experimentally. It is concluded either that addition
to the transmembrane exchange of acetaldehyde, other processes
may contribute to intercellular coupling, or that intracellular
regulator feedback plays a role in the acceleration of the
synchronization. for appropriate sets of parameter values, the
calculated synchronization time is longer than that observed
experimentally. It is concluded either that addition to the
transmembrane exchange of acetaldehyde, other processes may
contribute to intercellular coupling, or that intracellular
regulator feedback plays a role in the acceleration of the
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Project description:GAPDHs from human pathogens S. aureus and P. aeruginosa can be readily inhibited by ROS-mediated direct oxidation of their catalytic active cysteines. Because of the rapid degradation of H2O2 by bacterial catalase, only steady-state but not one-dose treatment of H2O2 induces rapid metabolic reroute from glycolysis to pentose phosphate pathway (PPP). We conducted RNA-seq analyses to globally profile the bacterial transcriptomes in response to a steady level of H2O2, which reveals profound transcriptional changes including the induced expression of glycolytic genes in both bacteria. Our results revealed that the inactivation of GAPDH by H2O2 induces a metabolic reroute from glycolysis to PPP; the elevated levels of fructose 1,6-biphosphate (FBP) and 2-keto-3-deoxy-6-phosphogluconate (KDPG) lead to dissociation of their corresponding glycolytic repressors (GapR and HexR, respectively) from their cognate promoters, thus resulting in derepression of the glycolytic genes to overcome H2O2-stalled glycolysis in S. aureus and P. aeruginosa, respectively. Given that H2O2 can be produced constitutively by the host immune response, exposure to the steady-state stress of H2O2 recapitulates more accurately bacterial responses to host immune system in vivo. RNA-seq in Pseudomonas aeruginosa and Staphylococus aureus under steady state of H2O2
Project description:Upon antigen stimulation, the bioenergetic demands of T cells increase dramatically over the resting state. Although a role for the metabolic switch to glycolysis has been suggested to support increased anabolic activities and facilitate T cell growth and proliferation, whether cellular metabolism controls T cell lineage choices remains poorly understood. Here we report that the glycolytic pathway is actively regulated during the differentiation of inflammatory TH17 and Foxp3-expressing regulatory T cells (Treg), and controls cell fate determination. TH17 but not Treg-inducing conditions resulted in strong upregulation of the glycolytic activity and induction of glycolytic enzymes. Blocking glycolysis inhibited TH17 development while promoting Treg cell generation. Moreover, the transcription factor hypoxia-inducible factor 1a (HIF1a) was selectively expressed in TH17 cells and its induction required signaling through mTOR, a central regulator of cellular metabolism. HIF1a-dependent transcriptional program was important for mediating glycolytic activity, thereby contributing to the lineage choices between TH17 and Treg cells. Lack of HIF1a resulted in diminished TH17 development but enhanced Treg differentiation, and protected mice from autoimmune CNS inflammation. Our studies demonstrate that HIF1a-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. Naïve CD4 T cells from wild-type and HIF1a-deficient mice (in triplicates each group) were differentiated under TH17 conditions for 2.5 days, and RNA was analyzed by microarrays.
Project description:Exploring the effect of variable enzyme concentrations in a kinetic model of yeast glycolysis
Jozsef Bruck, Wolfram Liebermeister, Edda Klipp, Genome Inform 2008 20:1-14
Metabolism is one of the best studied fields of biochemistry, but its regulation involves processes on many different levels, some of which are still not understood well enough to allow for quantitative modeling and prediction. Glycolysis in yeast is a good example: although high-quality quantitative data are available, well-established mathematical models typically only cover direct regulation of the involved enzymes by metabolite binding. The effect of various metabolites on the enzyme kinetics is summarized in carefully developed mathematical formulae. However, this approach implicitly assumes that the enzyme concentrations themselves are constant, thus neglecting other regulatory levels - e.g. transcriptional and translational regulation--involved in the regulation of enzyme activities. It is believed, however, that different experimental conditions result in different enzyme activities regulated by the above mechanisms. Detailed modeling of all regulatory levels is still out of reach since some of the necessary data - e.g. quantitative large scale enzyme concentration data sets - are lacking or rare. Nevertheless, a viable approach is to include the regulation of enzyme concentrations into an established model and to investigate whether this improves the predictive capabilities. Proteome data are usually hard to obtain, but levels of mRNA transcripts may be used instead as clues for changes in enzyme concentrations. Here we investigate whether including mRNA data into an established model of yeast glycolysis allows to predict the steady state metabolic concentrations for different experimental conditions. To this end, we modified an established ODE model for the glycolytic pathway of yeast to include changes of enzyme concentrations. Presumable changes were inferred from mRNA transcript level measurement data. We investigate how this approach can be used to predict metabolite concentrations for steady-state yeast cultures at five different oxygen levels ranging from anaerobic to fully aerobic conditions. We were partly able to reproduce the experimental data and present a number of changes that were necessary to improve the modeling result.
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