Počet záznamů: 1  

Kinetic modelling and meta-analysis of the B. subtilis SigA regulatory network during spore germination and outgrowth

  1. 1.
    0477942 - MBU-M 2018 RIV NL eng J - Článek v odborném periodiku
    Ramaniuk, Olga - Černý, Martin - Krásný, Libor - Vohradský, Jiří
    Kinetic modelling and meta-analysis of the B. subtilis SigA regulatory network during spore germination and outgrowth.
    Biochimica et Biophysica Acta-Gene Regulatory Mechanisms. Roč. 1860, č. 8 (2017), s. 894-904. ISSN 1874-9399
    Grant CEP: GA MŠk(CZ) LM2015055; GA ČR GA13-16842S; GA MZd(CZ) NV17-29680A
    Institucionální podpora: RVO:61388971
    Klíčová slova: Sigma A * Kinetic modelling * Regulatory network
    Kód oboru RIV: EE - Mikrobiologie, virologie
    Obor OECD: Microbiology
    Impakt faktor: 5.179, rok: 2017

    This study describes the meta-analysis and kinetic modelling of gene expression control by sigma factor SigA of Bacillus subtilis during germination and outgrowth based on microarray data from 14 time points. The analysis computationally models the direct interaction among SigA, SigA-controlled sigma factor genes (sigh, sigH, sigD, sigX), and their target genes. Of the > 800 known genes in the SigA regulon, as extracted from databases, 311 genes were analysed, and 190 were confirmed by the kinetic model as being controlled by SigA. For the remaining genes, alternative regulators satisfying kinetic constraints were suggested. The kinetic analysis suggested another 214 genes as potential SigA targets. The modelling was able to (i) create a particular SigA-controlled gene expression network that is active under the conditions for which the expression time series was obtained, and where SigA is the dominant regulator, (ii) suggest new potential SigA target genes, and (iii) fmd other possible regulators of a given gene or suggest a new mechanism of its control by identifying a matching profile of unknown regulator(s). Selected predicted regulatory interactions were experimentally tested, thus validating the model.
    Trvalý link: http://hdl.handle.net/11104/0274192