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Accueil > Plateformes > eBio

Publications

2017


  • C. Esnault, D. Leiber, C. Toffano-Nioche, Z. Tanfin, et M. - J. Virolle, « Another example of enzymatic promiscuity: the polyphosphate kinase of Streptomyces lividans is endowed with phospholipase D activity », Applied Microbiology and Biotechnology, vol. 101, nᵒ 1, p. 139-145, 2017.
    Résumé : Polyphosphate kinases (PPK) from different bacteria, including that of Streptomyces lividans, were shown to contain the typical HKD motif present in phospholipase D (PLD) and showed structural similarities to the latter. This observation prompted us to investigate the PLD activity of PPK of S. lividans, in vitro. The ability of PPK to catalyze the hydrolysis of phosphatidylcholine (PC), the PLD substrate, was assessed by the quantification of [(3)H]phosphatidic acid (PA) released from [(3)H]PC-labeled ELT3 cell membranes. Basal cell membrane PLD activity as well as GTPγS-activated PLD activity was higher in the presence than in absence of PPK. After abolition of the basal PLD activity of the membranes by heat or tryptic treatment, the addition of PPK to cell membranes was still accompanied by an increased production of PA demonstrating that PPK also bears a PLD activity. PLD activity of PPK was also assessed by the production of choline from hydrolysis of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) in the presence of the Amplex Red reagent and compared to two commercial PLD enzymes. These data demonstrated that PPK is endowed with a weak but clearly detectable PLD activity. The question of the biological signification, if any, of this enzymatic promiscuity is discussed.
    Mots-clés : Amino Acid Motifs, Cell Membrane, Choline, DBG, eBio, Hydrolysis, Lipid droplets, MESMIC, MICROBIO, PF, Phosphatidic Acids, Phosphatidylcholines, Phospholipase D, Phosphotransferases (Phosphate Group Acceptor), Polyphosphate kinase, Promiscuous enzyme, Protein Conformation, SSFA, Streptomyces lividans.

2016

2015


  • M. Descrimes, Y. Ben Zouari, M. Wery, R. Legendre, D. Gautheret, et A. Morillon, « VING: a software for visualization of deep sequencing signals », BMC research notes, vol. 8, p. 419, 2015.
    Résumé : BACKGROUND: Next generation sequencing (NGS) data treatment often requires mapping sequenced reads onto a reference genome for further analysis. Mapped data are commonly visualized using genome browsers. However, such software are not suited for a publication-ready and versatile representation of NGS data coverage, especially when multiple experiments are simultaneously treated. RESULTS: We developed 'VING', a stand-alone R script that takes as input NGS mapping files and genome annotations to produce accurate snapshots of the NGS coverage signal for any specified genomic region. VING offers multiple viewing options, including strand-specific views and a special heatmap mode for representing multiple experiments in a single figure. CONCLUSIONS: VING produces high-quality figures for NGS data representation in a genome region of interest. It is available at http://vm-gb.curie.fr/ving/. We also developed a Galaxy wrapper, available in the Galaxy tool shed with installation and usage instructions.
    Mots-clés : Computational Biology, DBG, eBio, Genome, Genomics, High-Throughput Nucleotide Sequencing, Internet, PF, Reproducibility of Results, Sequence Analysis, DNA, Software, SSFA.

  • J. Li, M. - A. Poursat, D. Drubay, A. Motz, Z. Saci, A. Morillon, S. Michiels, et D. Gautheret, « A Dual Model for Prioritizing Cancer Mutations in the Non-coding Genome Based on Germline and Somatic Events », PLoS computational biology, vol. 11, nᵒ 11, p. e1004583, 2015.
    Résumé : We address here the issue of prioritizing non-coding mutations in the tumoral genome. To this aim, we created two independent computational models. The first (germline) model estimates purifying selection based on population SNP data. The second (somatic) model estimates tumor mutation density based on whole genome tumor sequencing. We show that each model reflects a different set of constraints acting either on the normal or tumor genome, and we identify the specific genome features that most contribute to these constraints. Importantly, we show that the somatic mutation model carries independent functional information that can be used to narrow down the non-coding regions that may be relevant to cancer progression. On this basis, we identify positions in non-coding RNAs and the non-coding parts of mRNAs that are both under purifying selection in the germline and protected from mutation in tumors, thus introducing a new strategy for future detection of cancer driver elements in the expressed non-coding genome.
    Mots-clés : Computational Biology, DBG, eBio, Genome, Human, Humans, Models, Genetic, Mutation, Neoplasms, PF, RNA, Untranslated, Sequence Analysis, DNA, SSFA.
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