Transmembrane topology of ceramide synthase in yeast.
Ontology highlight
ABSTRACT:
SUBMITTER: Kageyama-Yahara N
PROVIDER: S-EPMC1559446 | biostudies-other | 2006 Sep
REPOSITORIES: biostudies-other
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Project description:Cell division produces two viable cells of a defined size. Thus, all cells require mechanisms to measure growth and trigger cell division when sufficient growth has occurred. Previous data suggest a model in which growth rate and cell size are mechanistically linked by ceramide-dependent signals in budding yeast. However, the conservation of mechanisms that govern growth control is poorly understood. In fission yeast, ceramide synthase is encoded by two genes, Lac1 and Lag1. Here, we characterize them by using a combination of genetics, microscopy, and lipid analysis. We showed that Lac1 and Lag1 co-immunoprecipitate and co-localize at the endoplasmic reticulum. However, each protein generates different species of ceramides and complex sphingolipids. We further discovered that Lac1, but not Lag1, is specifically required for proper control of cell growth and size in Schizosaccharomyces pombe. We propose that specific ceramide and sphingolipid species produced by Lac1 are required for normal control of cell growth and size in fission yeast.
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Project description:The bioactive sphingolipid ceramide, generated by ceramide synthase, is an adaptive stress effector induced in response to various stress stimuli such as aging. In fact, ceramide synthase (CerS) was first discovered in yeast as a longevity assurance gene (LAG1), as the reduced ceramide generation consequent to LAG1 deletion increased longevity. There are six homologues of mammalian LAG1/ceramide synthases (CerS1-6) that generate ceramides with different fatty acid chain lengths with distinct functions and hydrophobicity. Ceramide can be metabolized by sphingosine kinase 1 or 2 for the generation of pro-survival sphingosine 1-phosphate (S1P), which enhances immune cell egress to the blood stream, activating immune function. Ceramide is known to induce mitophagy and cell death. Here we investigated the role of this sphingolipid pathway in immune function, specifically T cell functions, via high throughput expression profiling.
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Project description:BackgroundAlpha-helical transmembrane (TM) proteins are involved in a wide range of important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion. Many are also prime drug targets, and it has been estimated that more than half of all drugs currently on the market target membrane proteins. However, due to the experimental difficulties involved in obtaining high quality crystals, this class of protein is severely under-represented in structural databases. In the absence of structural data, sequence-based prediction methods allow TM protein topology to be investigated.ResultsWe present a support vector machine-based (SVM) TM protein topology predictor that integrates both signal peptide and re-entrant helix prediction, benchmarked with full cross-validation on a novel data set of 131 sequences with known crystal structures. The method achieves topology prediction accuracy of 89%, while signal peptides and re-entrant helices are predicted with 93% and 44% accuracy respectively. An additional SVM trained to discriminate between globular and TM proteins detected zero false positives, with a low false negative rate of 0.4%. We present the results of applying these tools to a number of complete genomes. Source code, data sets and a web server are freely available from http://bioinf.cs.ucl.ac.uk/psipred/.ConclusionThe high accuracy of TM topology prediction which includes detection of both signal peptides and re-entrant helices, combined with the ability to effectively discriminate between TM and globular proteins, make this method ideally suited to whole genome annotation of alpha-helical transmembrane proteins.
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