Kinetic modelling and meta-analysis of the B. subtilis SigA regulatory network during spore germination and outgrowth
Language English Country Netherlands Media print-electronic
Document type Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't
PubMed
28648455
DOI
10.1016/j.bbagrm.2017.06.003
PII: S1874-9399(17)30099-8
Knihovny.cz E-resources
- Keywords
- Bacillus subtilis, Gene expression, Kinetic modelling, Regulatory network, Sigma A,
- MeSH
- Bacillus subtilis genetics MeSH
- Bacterial Proteins genetics MeSH
- Transcription, Genetic genetics MeSH
- Gene Regulatory Networks genetics MeSH
- Kinetics MeSH
- Gene Expression Regulation, Bacterial genetics MeSH
- Sigma Factor genetics MeSH
- Spores, Bacterial genetics MeSH
- Transcription Factors genetics MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Bacterial Proteins MeSH
- Sigma Factor MeSH
- Transcription Factors MeSH
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 (sigM, 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) find 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.
References provided by Crossref.org
σE of Streptomyces coelicolor can function both as a direct activator or repressor of transcription
The torpedo effect in Bacillus subtilis: RNase J1 resolves stalled transcription complexes
