Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data

José P Faria; Ross Overbeek; Ronald C Taylor; Neal Conrad; Veronika Vonstein; Anne Goelzer; Vincent Fromion; Miguel Rocha; Isabel Rocha; Christopher S Henry

doi:10.3389/fmicb.2016.00275

Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data

Front Microbiol. 2016 Mar 18:7:275. doi: 10.3389/fmicb.2016.00275. eCollection 2016.

Authors

Affiliations

¹ Computation Institute, University of ChicagoChicago, IL, USA; Computing, Environment and Life Sciences, Argonne National LaboratoryArgonne, IL, USA; Centre of Biological Engineering, University of MinhoBraga, Portugal.
² Fellowship for Interpretation of Genomes Burr Ridge, IL, USA.
³ Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory, United States Department of Energy Richland, WA, USA.
⁴ Computing, Environment and Life Sciences, Argonne National Laboratory Argonne, IL, USA.
⁵ UR1404 Applied Mathematics and Computer Science from Genomes to the Environment, INRA, Paris-Saclay University Jouy-en-Josas, France.
⁶ Centre of Biological Engineering, University of Minho Braga, Portugal.
⁷ Computation Institute, University of ChicagoChicago, IL, USA; Mathematics and Computer Science Division, Argonne National LaboratoryArgonne, IL, USA.

Abstract

We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus 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 ∼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 ARs for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how ARs 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.

Keywords: Atomic Regulon; Bacillus subtilis; regulation; regulatory network; stimuli.