Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/41331

TitleReconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data
Author(s)Faria, J.
Overbeek, Ross
Taylor, Ronald C
Conrad, Neal
Vonstein, Veronika
Goelzer, Anne
Fromion, Vincent
Rocha, Miguel
Rocha, I.
Henry, Christopher Scott
KeywordsAtomic Regulon
regulatory network
stimuli
regulation
Bacillus subtilis
Issue date2016
PublisherFrontiers Media
JournalFrontiers in Microbiology
CitationFaria, J.; Overbeek, Ross; Taylor, Ronald C; Conrad, Neal; Vonstein, Veronika; Goelzer, Anne; Fromion, Vincent; Rocha, Miguel; Rocha, I.; Henry, Christopher Scott, Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data. Frontiers in Microbiology, 7(275), 1-11, 2016
Abstract(s)We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same ON and OFF gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions, gaining insights into novel biology.
TypeArticle
DescriptionThe Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275
URIhttp://hdl.handle.net/1822/41331
DOI10.3389/fmicb.2016.00275
ISSN1664-302X
e-ISSN1664-302X
Publisher versionhttp://journal.frontiersin.org/journal/microbiology
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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