654 research outputs found

    Functions of ceramide synthase paralogs YPR114w and YJR116w of Saccharomyces cerevisiae

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    Ceramide is synthesized in yeast by two redundant acyl-CoA dependent synthases, Lag1 and Lac1. In lag1∆ lac1∆ cells, free fatty acids and sphingoid bases are elevated, and ceramides are produced through the redundant alkaline ceramidases Ypc1 and Ydc1, working backwards. Even with all four of these genes deleted, cells are surviving and continue to contain small amounts of complex sphingolipids. Here we show that these residual sphingolipids are not synthesized by YPR114w or YJR116w, proteins of unknown function showing a high degree of homology to Lag1 and Lac1. Indeed, the hextuple lag1∆ lac1∆ ypc1∆ ydc1∆ ypr114w∆ yjr116w∆ mutant still contains ceramides and complex sphingolipids. Yjr116w∆ exhibit an oxygen-dependent hypersensitivity to Cu2+ due to an increased mitochondrial production of reactive oxygen species (ROS) and a mitochondrially orchestrated programmed cell death in presence of copper, but also a general copper hypersensitivity that cannot be counteracted by the antioxidant N-acetyl-cysteine (NAC). Myriocin efficiently represses the synthesis of sphingoid bases of ypr114w∆, but not its growth. Both yjr116w∆ and ypr114w∆ have fragmented vacuoles and produce less ROS than wild type, before and after diauxic shift. Ypr114w∆/ypr114w∆ have an increased chronological life span. Thus, Yjr116w and Ypr114w are related, but not functionally redundant

    The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

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    BACKGROUND: Signaling systems typically involve large, structured molecules each consisting of a large number of subunits called molecule domains. In modeling such systems these domains can be considered as the main players. In order to handle the resulting combinatorial complexity, rule-based modeling has been established as the tool of choice. In contrast to the detailed quantitative rule-based modeling, qualitative modeling approaches like logical modeling rely solely on the network structure and are particularly useful for analyzing structural and functional properties of signaling systems. RESULTS: We introduce the Process-Interaction-Model (PIM) concept. It defines a common representation (or basis) of rule-based models and site-specific logical models, and, furthermore, includes methods to derive models of both types from a given PIM. A PIM is based on directed graphs with nodes representing processes like post-translational modifications or binding processes and edges representing the interactions among processes. The applicability of the concept has been demonstrated by applying it to a model describing EGF insulin crosstalk. A prototypic implementation of the PIM concept has been integrated in the modeling software ProMoT. CONCLUSIONS: The PIM concept provides a common basis for two modeling formalisms tailored to the study of signaling systems: a quantitative (rule-based) and a qualitative (logical) modeling formalism. Every PIM is a compact specification of a rule-based model and facilitates the systematic set-up of a rule-based model, while at the same time facilitating the automatic generation of a site-specific logical model. Consequently, modifications can be made on the underlying basis and then be propagated into the different model specifications – ensuring consistency of all models, regardless of the modeling formalism. This facilitates the analysis of a system on different levels of detail as it guarantees the application of established simulation and analysis methods to consistent descriptions (rule-based and logical) of a particular signaling system

    Saccharomyces cerevisiae depend on vesicular traffic between Golgi and vacuole when Inositolphosphorylceramide synthase Aur1 is inactivated

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    Inositolphosphorylceramide (IPC) and its mannosylated derivatives are the only complex sphingolipids of yeast. Their synthesis can be reduced by aureobasidin A (AbA), which specifically inhibits the IPC synthase Aur1. AbA reportedly, by diminishing IPC levels, causes endoplasmic reticulum (ER) stress, an increase in cytosolic calcium, reactive oxygen production, and mitochondrial damage leading to apoptosis. We found that when Aur1 is gradually depleted by transcriptional downregulation, the accumulation of ceramides becomes a major hindrance to cell survival. Overexpression of the alkaline ceramidase YPC1 rescues cells under this condition. We established hydroxylated C(26) fatty acids as a reliable hallmark of ceramide hydrolysis. Such hydrolysis occurs only when YPC1 is overexpressed. In contrast, overexpression of YPC1 has no beneficial effect when Aur1 is acutely repressed by AbA. A high-throughput genetic screen revealed that vesicle-mediated transport between Golgi apparatus, endosomes, and vacuole becomes crucial for survival when Aur1 is repressed, irrespective of the mode of repression. In addition, vacuolar acidification becomes essential when cells are acutely stressed by AbA, and quinacrine uptake into vacuoles shows that AbA activates vacuolar acidification. The antioxidant N-acetylcysteine does not improve cell growth on AbA, indicating that reactive oxygen radicals induced by AbA play a minor role in its toxicity. AbA strongly induces the cell wall integrity pathway, but osmotic support does not improve the viability of wild-type cells on AbA. Altogether, the data support and refine current models of AbA-mediated cell death and add vacuolar protein transport and acidification as novel critical elements of stress resistance

    A novel brain receptor is expressed in a distinct population of olfactory sensory neurons

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    Three novel G-protein-coupled receptor genes related to the previously described RA1c gene have been isolated from the mouse genome. Expression of these genes has been detected in distinct areas of the brain and also in the olfactory epithelium of the nose. Developmental studies revealed a differential onset of expression: in the brain at embryonic stage 17, in the olfactory system at stage E12. In order to determine which cell type in the olfactory epithelium expresses this unique receptor type, a transgenic approach was employed which allowed a coexpression of histological markers together with the receptor and thus visualization of the appropriate cell population. It was found that the receptor-expressing cells were located very close to the basal membrane of the epithelium; however, the cells extended a dendritic process to the epithelial surface and their axons projected into the main olfactory bulb where they converged onto two or three glomeruli in the dorsal and posterior region of the bulb. Thus, these data provide evidence that this unique type of receptor is expressed in mature olfactory neurons and suggests that it may be involved in the detection of special odour molecules

    Characterization of yeast mutants lacking alkaline ceramidases YPC1 and YDC1

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    Humans and yeast possess alkaline ceramidases located in the early secretory pathway. Single deletions of the highly homologous yeast alkaline ceramidases YPC1 and YDC1 have very little genetic interactions or phenotypes. Here, we performed chemical-genetic screens to find deletions/conditions that would alter the growth of ypc1∆ydc1∆ double mutants. These screens were essentially negative, demonstrating that ceramidase activity is not required for cell growth even under genetic stresses. A previously reported protein targeting defect of ypc1∆ could not be reproduced and reported abnormalities in sphingolipid biosynthesis detected by metabolic labeling do not alter the mass spectrometric lipid profile of ypc1∆ydc1∆ cells. Ceramides of ypc1∆ydc1∆ remained normal even in presence of aureobasidin A, an inhibitor of inositolphosphorylceramide synthase. Moreover, in caloric restriction conditions Ypc1p reduces chronological life span. A novel finding is that, when working backwards as a ceramide synthase in vivo, Ypc1p prefers C24 and C26 fatty acids as substrates, whereas it prefers C16:0, when solubilized in detergent and working in vitro. Therefore, its physiological activity may not only concern the minor ceramides containing C14 and C16. Intriguingly, so far the sole discernable benefit of conserving YPC1 for yeast resides with its ability to convey relative resistance toward H₂O₂

    A serial multiplex immunogold labeling method for identifying peptidergic neurons in connectomes.

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    This is the final version of the article.Available from eLife Sciences Publications via the DOI in this record.Electron microscopy-based connectomics aims to comprehensively map synaptic connections in neural tissue. However, current approaches are limited in their capacity to directly assign molecular identities to neurons. Here, we use serial multiplex immunogold labeling (siGOLD) and serial-section transmission electron microscopy (ssTEM) to identify multiple peptidergic neurons in a connectome. The high immunogenicity of neuropeptides and their broad distribution along axons, allowed us to identify distinct neurons by immunolabeling small subsets of sections within larger series. We demonstrate the scalability of siGOLD by using 11 neuropeptide antibodies on a full-body larval ssTEM dataset of the annelid Platynereis. We also reconstruct a peptidergic circuitry comprising the sensory nuchal organs, found by siGOLD to express pigment-dispersing factor, a circadian neuropeptide. Our approach enables the direct overlaying of chemical neuromodulatory maps onto synaptic connectomic maps in the study of nervous systems.The research leading to these results received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/European Research Council Grant Agreement 260821. This project is supported by the Marie Curie ITN "Neptune", GA 317172, funded under the FP7, PEOPLE Work Programme of the European Commission

    Syntactic Markovian Bisimulation for Chemical Reaction Networks

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    In chemical reaction networks (CRNs) with stochastic semantics based on continuous-time Markov chains (CTMCs), the typically large populations of species cause combinatorially large state spaces. This makes the analysis very difficult in practice and represents the major bottleneck for the applicability of minimization techniques based, for instance, on lumpability. In this paper we present syntactic Markovian bisimulation (SMB), a notion of bisimulation developed in the Larsen-Skou style of probabilistic bisimulation, defined over the structure of a CRN rather than over its underlying CTMC. SMB identifies a lumpable partition of the CTMC state space a priori, in the sense that it is an equivalence relation over species implying that two CTMC states are lumpable when they are invariant with respect to the total population of species within the same equivalence class. We develop an efficient partition-refinement algorithm which computes the largest SMB of a CRN in polynomial time in the number of species and reactions. We also provide an algorithm for obtaining a quotient network from an SMB that induces the lumped CTMC directly, thus avoiding the generation of the state space of the original CRN altogether. In practice, we show that SMB allows significant reductions in a number of models from the literature. Finally, we study SMB with respect to the deterministic semantics of CRNs based on ordinary differential equations (ODEs), where each equation gives the time-course evolution of the concentration of a species. SMB implies forward CRN bisimulation, a recently developed behavioral notion of equivalence for the ODE semantics, in an analogous sense: it yields a smaller ODE system that keeps track of the sums of the solutions for equivalent species.Comment: Extended version (with proofs), of the corresponding paper published at KimFest 2017 (http://kimfest.cs.aau.dk/

    Exact model reduction of combinatorial reaction networks

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    Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models
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