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Accueil > Départements > Biologie des Génomes > Daniel GAUTHERET : Séquence, Structure et Fonction des ARN

pubmed : ssfa_i2bc

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NCBI : db=pubmed ; Term=(Gautheret D[Author] NOT Dessen P[Author]) OR Leclerc, Fabrice[Full Author Name] OR (Lehmann Jean[Full Author Name] AND (Orsay[AD] OR Gif[AD])) OR Toffano-Nioche C[Author]) AND ("2012"[PDAT] : "2035"[PDAT])

Articles syndiqués

  • CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins.

    25 mai, par Couvin D, Bernheim A, Toffano-Nioche C, Touchon M, Michalik J, Néron B, C Rocha EP, Vergnaud G, Gautheret D, Pourcel C
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    CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins.

    Nucleic Acids Res. 2018 May 22;:

    Authors: Couvin D, Bernheim A, Toffano-Nioche C, Touchon M, Michalik J, Néron B, C Rocha EP, Vergnaud G, Gautheret D, Pourcel C

    Abstract
    CRISPR (clustered regularly interspaced short palindromic repeats) arrays and their associated (Cas) proteins confer bacteria and archaea adaptive immunity against exogenous mobile genetic elements, such as phages or plasmids. CRISPRCasFinder allows the identification of both CRISPR arrays and Cas proteins. The program includes: (i) an improved CRISPR array detection tool facilitating expert validation based on a rating system, (ii) prediction of CRISPR orientation and (iii) a Cas protein detection and typing tool updated to match the latest classification scheme of these systems. CRISPRCasFinder can either be used online or as a standalone tool compatible with Linux operating system. All third-party software packages employed by the program are freely available. CRISPRCasFinder is available at https://crisprcas.i2bc.paris-saclay.fr.

    PMID: 29790974 [PubMed - as supplied by publisher]

  • Assessment of Bona Fide sRNAs in Staphylococcus aureus.

    9 mars, par Liu W, Rochat T, Toffano-Nioche C, Le Lam TN, Bouloc P, Morvan C
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    Assessment of Bona Fide sRNAs in Staphylococcus aureus.

    Front Microbiol. 2018;9:228

    Authors: Liu W, Rochat T, Toffano-Nioche C, Le Lam TN, Bouloc P, Morvan C

    Abstract
    Bacterial regulatory RNAs have been extensively studied for over a decade, and are progressively being integrated into the complex genetic regulatory network. Transcriptomic arrays, recent deep-sequencing data and bioinformatics suggest that bacterial genomes produce hundreds of regulatory RNAs. However, while some have been authenticated, the existence of the others varies according to strains and growth conditions, and their detection fluctuates with the methodologies used for data acquisition and interpretation. For example, several small RNA (sRNA) candidates are now known to be parts of UTR transcripts. Accurate annotation of regulatory RNAs is a complex task essential for molecular and functional studies. We defined bona fide sRNAs as those that (i) likely act in trans and (ii) are not expressed from the opposite strand of a coding gene. Using published data and our own RNA-seq data, we reviewed hundreds of Staphylococcus aureus putative regulatory RNAs using the DETR'PROK computational pipeline and visual inspection of expression data, addressing the question of which transcriptional signals correspond to sRNAs. We conclude that the model strain HG003, a NCTC8325 derivative commonly used for S. aureus genetic regulation studies, has only about 50 bona fide sRNAs, indicating that these RNAs are less numerous than commonly stated. Among them, about half are associated to the S. aureus sp. core genome and a quarter are possibly expressed in other Staphylococci. We hypothesize on their features and regulation using bioinformatic approaches.

    PMID: 29515534 [PubMed]

  • A benchmark study of scoring methods for non-coding mutations.

    18 janvier, par Drubay D, Gautheret D, Michiels S

    A benchmark study of scoring methods for non-coding mutations.

    Bioinformatics. 2018 Jan 11;:

    Authors: Drubay D, Gautheret D, Michiels S

    Abstract
    Motivation: Detailed knowledge of coding sequences has led to different candidate models for pathogenic variant prioritization. Several deleteriousness scores have been proposed for the non-coding part of the genome, but no large-scale comparison has been realized to date to assess their performance.
    Results: We compared the leading scoring tools (CADD, FATHMM-MKL, Funseq2 and GWAVA) and some recent competitors (DANN, SNP and SOM scores) for their ability to discriminate assumed pathogenic variants from assumed benign variants (using the ClinVar, COSMIC and 1000 genomes project databases). Using the ClinVar benchmark, CADD was the best tool for detecting the pathogenic variants that are mainly located in protein coding gene regions. Using the COSMIC benchmark, FATHMM-MKL, GWAVA and SOMliver outperformed the other tools for pathogenic variants that are typically located in lincRNAs, pseudogenes, and other parts of the non-coding genome. However, all tools had low precision, which could potentially be improved by future non-coding genome feature discoveries. These results may have been influenced by the presence of potential benign variants in the COSMIC database. The development of a gold standard as consistent as ClinVar for these regions will be necessary to confirm our tool ranking.
    Availability and Implementation: The Snakemake, C ++ and R codes are freely available from https://github.com/Oncostat/BenchmarkNCVTools and supported on Linux.
    Contact: damien.drubay@gustaveroussy.fr.
    Supplementary information: Supplementary results are available at Bioinformatics online.

    PMID: 29340599 [PubMed - as supplied by publisher]

  • Induced fit of the peptidyl-transferase center of the ribosome and conformational freedom of the esterified amino acids.

    4 janvier, par Lehmann J
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    Induced fit of the peptidyl-transferase center of the ribosome and conformational freedom of the esterified amino acids.

    RNA. 2017 02;23(2):229-239

    Authors: Lehmann J

    Abstract
    The catalytic site of most enzymes can efficiently handle only one substrate. In contrast, the ribosome is capable of polymerizing at a similar rate at least 20 different kinds of amino acids from aminoacyl-tRNA carriers while using just one catalytic site, the peptidyl-transferase center (PTC). An induced-fit mechanism has been uncovered in the PTC, but a possible connection between this mechanism and the uniform handling of the substrates has not been investigated. We present an analysis of published ribosome structures supporting the hypothesis that the induced fit eliminates unreactive rotamers predominantly populated for some A-site aminoacyl esters before induction. We show that this hypothesis is fully consistent with the wealth of kinetic data obtained with these substrates. Our analysis reveals that induction constrains the amino acids into a reactive conformation in a side-chain independent manner. It allows us to highlight the rationale of the PTC structural organization, which confers to the ribosome the very unusual ability to handle large as well as small substrates.

    PMID: 27879432 [PubMed - indexed for MEDLINE]

  • Fundamental amino acid mass distributions and entropy costs in proteomes.

    4 janvier, par Lehmann J, Libchaber A, Greenbaum BD
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    Fundamental amino acid mass distributions and entropy costs in proteomes.

    J Theor Biol. 2016 Dec 07;410:119-124

    Authors: Lehmann J, Libchaber A, Greenbaum BD

    Abstract
    We examine whether the frequency of amino acids across an organism's proteome is primarily determined by optimization to function or other factors, such as the structure of the genetic code. Considering all available proteins together, we first point out that the frequency of an amino acid in a proteome negatively correlates with its mass, suggesting that the genome preserves a fundamental distribution ruled by simple energetics. Given the universality of such distributions, one can use outliers, cysteine and leucine, to identify amino acids that deviate from this simple rule for functional purposes and examine those functions. We quantify the strength of such selection as the entropic cost outliers pay to defy the mass-frequency relation. Codon degeneracy of an amino acid partially explains the correlation between mass and frequency: light amino acids being typically encoded by highly degenerate codon families, with the exception of arginine. While degeneracy may be a factor in hard wiring the relationship between mass and frequency in proteomes, it does not provide a complete explanation. By examining extremophiles, we are able to show that this law weakens with temperature, likely due to protein stability considerations, thus the environment is essential.

    PMID: 27544420 [PubMed - indexed for MEDLINE]

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