Sphingolipid Metabolism In Yeast Research Articles

Fumonisin B1: A Tool for Exploring the Multiple Functions of Sphingolipids in Plants.

Fumonisin toxins are produced by Fusarium fungal pathogens. Fumonisins are structural analogs of sphingosine and potent inhibitors of ceramide synthases (CerSs); they disrupt sphingolipid metabolism and cause disease in plants and animals. Over the past three decades, researchers have used fumonisin B1 (FB1), the most common fumonisin, as a probe to investigate sphingolipid metabolism in yeast and animals. Although the physiological effects of FB1 in plants have yet to be investigated in detail, forward and reverse genetic approaches have revealed many genes involved in these processes. In this review, we discuss the intricate network of signaling pathways affected by FB1, including changes in sphingolipid metabolism and the effects of these changes, with a focus on our current understanding of the multiple effects of FB1 on plant cell death and plant growth. We analyze the major findings that highlight the connections between sphingolipid metabolism and FB1-induced signaling, and we point out where additional research is needed to fill the gaps in our understanding of FB1-induced signaling pathways in plants.

Mdm1 helps the ER and vacuole stay in touch

![Figure][1] Mdm1 (green) localizes to the sites where vacuoles (V) contact the ER (red) surrounding nuclei (N). [Henne et al.][2] reveal that a protein linked to human neurological disease regulates sphingolipid metabolism in yeast by tethering vacuoles to the ER. Little is known about

Harnessing the power of yeast to elucidate the role of sphingolipids in metabolic and signaling processes pertinent to psychiatric disorders.

The development of therapies for neuropsychiatric disorders is hampered by the lack of understanding of the mechanisms underlying their pathologies. While aberrant sphingolipid metabolism is associated with psychiatric illness, the role of sphingolipids in these disorders is not understood. The genetically tractable yeast model can be exploited in order to elucidate the cellular consequences of sphingolipid perturbation. Hypotheses generated from studies in yeast and tested in mammalian cells may contribute to our understanding of the role of sphingolipids in psychiatric disorders and to the development of new treatments. Here, we compare sphingolipid metabolism in yeast and mammalian cells, discuss studies implicating sphingolipids in psychiatric disorders and propose approaches that utilize yeast in order to elucidate sphingolipid function and identify drugs that target sphingolipid synthesis.

Evaluating Sphingolipid Biochemistry in the Consensus Reconstruction of Yeast Metabolism

Abstract Reconstructed metabolic networks are the basis for genome-scale models of cellular metabolism. Such models have demonstrated good predictive accuracy when analyzed with the optimization-based approach of flux balance analysis, so are of particular interest for informing the rational design of metabolic engineering strategies for industrial biotechnology applications. As a preliminary step towards applying a metabolic model of the industrially important yeast Saccharomyces cerevisiae, we validated the underlying reconstruction of yeast metabolism in the Yeast Consensus Reconstruction by examining the model’s representation of yeast sphingolipid metabolism. Sphingolipids, which comprise 30% of the plasma membrane lipids in yeast, incorporate very long chain fatty acids of lengths up to C-26. Such long-chain hydrocarbons are of particular interest for the production of liquid transportation fuels. We began with a literature review and consultation with experts in yeast sphingolipid metabolism to com...

Mathematical Modeling and Validation of the Ergosterol Pathway in Saccharomyces cerevisiae

The de novo biosynthetic machinery for both sphingolipid and ergosterol production in yeast is localized in the endoplasmic reticulum (ER) and Golgi. The interconnections between the two pathways are still poorly understood, but they may be connected in specialized membrane domains, and specific knockouts strongly suggest that both routes have different layers of mutual control and are co-affected by drugs. With the goal of shedding light on the functional integration of the yeast sphingolipid-ergosterol (SL-E) pathway, we constructed a dynamic model of the ergosterol pathway using the guidelines of Biochemical Systems Theory (BST) (Savageau., J. theor. Biol., 25, 365–9, 1969). The resulting model was merged with a previous mathematical model of sphingolipid metabolism in yeast (Alvarez-Vasquez et al., J. theor. Biol., 226, 265–91, 2004; Alvarez-Vasquez et al., Nature 433, 425–30, 2005). The S-system format within BST was used for analyses of consistency, stability, and sensitivity of the SL-E model, while the GMA format was used for dynamic simulations and predictions. Model validation was accomplished by comparing predictions from the model with published results on sterol and sterol-ester dynamics in yeast. The validated model was used to predict the metabolomic dynamics of the SL-E pathway after drug treatment. Specifically, we simulated the action of drugs affecting sphingolipids in the endoplasmic reticulum and studied changes in ergosterol associated with microdomains of the plasma membrane (PM).

Stoichiometric network reconstruction and analysis of yeast sphingolipid metabolism incorporating different states of hydroxylation

The first elaborate metabolic model of Saccharomyces cerevisiae sphingolipid metabolism was reconstructed in silico. The model considers five different states of sphingolipid hydroxylation, rendering it unique among other models. It is aimed to clarify the significance of hydroxylation on sphingolipids and hence to interpret the preferences of the cell between different metabolic pathway branches under different stress conditions. The newly constructed model was validated by single, double and triple gene deletions with experimentally verified phenotypes. Calcium sensitivity and deletion mutations that may suppress calcium sensitivity were examined by CSG1 and CSG2 related deletions. The model enabled the analysis of complex sphingolipid content of the plasma membrane coupled with diacylglycerol and phosphatidic acid biosynthesis and ATP consumption in in silico cell. The flux data belonging to these critically important key metabolites are integrated with the fact of phytoceramide induced cell death to propose novel potential drug targets for cancer therapeutics. In conclusion, we propose that IPT1, GDA1, CSG and AUR1 gene deletions may be novel candidates of drug targets for cancer therapy according to the results of flux balance and variability analyses coupled with robustness analysis.

Stoichiometric network reconstruction and analysis of yeast sphingolipid metabolism: a detailed understanding of the pathway

Stoichiometric network reconstruction and analysis of yeast sphingolipid metabolism: a detailed understanding of the pathway

Coordination of the dynamics of yeast sphingolipid metabolism during the diauxic shift

BackgroundThe diauxic shift in yeast requires cells to coordinate a complicated response that involves numerous genes and metabolic processes. It is unknown whether responses of this type are mediated in vivo through changes in a few "key" genes and enzymes, which are mathematically characterized by high sensitivities, or whether they are based on many small changes in genes and enzymes that are not particularly sensitive. In contrast to global assessments of changes in gene or protein interaction networks, we study here control aspects of the diauxic shift by performing a detailed analysis of one specific pathway–sphingolipid metabolism–which is known to have signaling functions and is associated with a wide variety of stress responses.ResultsThe approach uses two components: publicly available sets of expression data of sphingolipid genes and a recently developed Generalized Mass Action (GMA) mathematical model of the sphingolipid pathway. In one line of exploration, we analyze the sensitivity of the model with respect to enzyme activities, and thus gene expression. Complementary to this approach, we convert the gene expression data into changes in enzyme activities and then predict metabolic consequences by means of the mathematical model. It was found that most of the sensitivities in the model are low in magnitude, but that some stand out as relatively high. This information was then deployed to test whether the cell uses a few of the very sensitive pathway steps to mount a response or whether the control is distributed throughout the pathway. Pilot experiments confirm qualitatively and in part quantitatively the predictions of a group of metabolite simulations.ConclusionThe results indicate that yeast coordinates sphingolipid mediated changes during the diauxic shift through an array of small changes in many genes and enzymes, rather than relying on a strategy involving a few select genes with high sensitivity. This study also highlights a novel approach in coupling data mining with mathematical modeling in order to evaluate specific metabolic pathways.

Simulation and validation of modelled sphingolipid metabolism in Saccharomyces cerevisiae

Mathematical models have become a necessary tool for organizing the rapidly increasing amounts of large-scale data on biochemical pathways and for advanced evaluation of their structure and regulation. Most of these models have addressed specific pathways using either stoichiometric or flux-balance analysis, or fully kinetic Michaelis-Menten representations, metabolic control analysis, or biochemical systems theory. So far, the predictions of kinetic models have rarely been tested using direct experimentation. Here, we validate experimentally a biochemical systems theoretical model of sphingolipid metabolism in yeast. Simulations of metabolic fluxes, enzyme deletion and the effects of inositol (a key regulator of phospholipid metabolism) led to predictions that show significant concordance with experimental results generated post hoc. The model also allowed the simulation of the effects of acute perturbations in fatty-acid precursors of sphingolipids, a situation that is not amenable to direct experimentation. The results demonstrate that modelling now allows testable predictions as well as the design and evaluation of hypothetical 'thought experiments' that may generate new metabolomic approaches.

Yeast sphingolipid metabolism: clues and connections.

This review of sphingolipid metabolism in the budding yeast Saccharomyces cerevisiae contains information on the enzymes and the genes that encode them, as well as connections to other metabolic pathways. Particular attention is given to yeast homologs, domains, and motifs in the sequence, cellular localization of enzymes, and possible protein-protein interactions. Also included are genetic interactions of special interest that provide clues to the cellular biological roles of particular sphingolipid metabolic pathways and specific sphingolipids.

Integration of kinetic information on yeast sphingolipid metabolism in dynamical pathway models

For the first time, kinetic information from the literature was collected and used to construct integrative dynamical mathematical models of sphingolipid metabolism. One model was designed primarily with kinetic equations in the tradition of Michaelis and Menten whereas the other two models were designed as alternative power-law models within the framework of Biochemical Systems Theory. Each model contains about 50 variables, about a quarter of which are dependent (state) variables, while the others are independent inputs and enzyme activities that are considered constant. The models account for known regulatory signals that exert control over the pathway. Standard mathematical testing, repeated revisiting of the literature, and numerous rounds of amendments and refinements resulted in models that are stable and rather insensitive to perturbations in inputs or parameter values. The models also appear to be compatible with the modest amount of experimental experience that lends itself to direct comparisons. Even though the three models are based on different mathematical representations, they show dynamic responses to a variety of perturbations and changes in conditions that are essentially equivalent for small perturbations and similar for large perturbations. The kinetic information used for model construction and the models themselves can serve as a starting point for future analyses and refinements.

Suppressors of the Ca(2+)-sensitive yeast mutant (csg2) identify genes involved in sphingolipid biosynthesis. Cloning and characterization of SCS1, a gene required for serine palmitoyltransferase activity.

Suppressor mutations in Saccharomyces cerevisiae that block Ca(2+)-induced death of csg2 mutant cells were investigated. These mutants, called scs mutants (suppressor of Ca2+ sensitivity), fall into seven complementation groups (scs1-scs7). All mutant strains in two of the complementation groups (scs1 and scs2) simultaneously acquire a requirement for 10 mM Ca2+, whereas wild type grow with only trace amounts of Ca2+. SCS1 was cloned by complementation of its Ca(2+)-requiring phenotype and found to be homologous to a family of pyridoxal phosphate enzymes that catalyze acyltransfer reactions. Secondary phenotypes of the scs1 mutants indicate that SCS1 is required for serine palmitoyltransferase activity which catalyzes the first committed step in sphingolipid biosynthesis (palmitoyl-CoA + serine-->3-ketosphinganine+CoASH+CO2). Other scs mutants as well as the csg2 null mutant have altered sphingolipid metabolism. The data suggest that sphingolipid metabolism in yeast is either regulated by Ca2+ and/or is required for Ca2+ homeostasis.