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Title: Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

Here, 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 themore » 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.« less
Authors:
 [1] ;  [2] ;  [3] ;  [4] ;  [2] ;  [5] ;  [5] ;  [6] ;  [6] ;  [7]
  1. Univ. of Chicago, Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Minho, Braga (Portugal)
  2. Fellowship for Interpretation of Genomes, Burr Ridge, IL (United States)
  3. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  4. Argonne National Lab. (ANL), Argonne, IL (United States)
  5. Paris-Saclay Univ., Jouy-en-Josas (France)
  6. Univ. of Minho, Braga (Portugal)
  7. Univ. of Chicago, Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Report Number(s):
PNNL-SA-115053
Journal ID: ISSN 1664-302X; KP1601010
Grant/Contract Number:
AC05-76RL01830; AC02-06CH11357
Type:
Accepted Manuscript
Journal Name:
Frontiers in Microbiology
Additional Journal Information:
Journal Volume: 7; Journal ID: ISSN 1664-302X
Publisher:
Frontiers Research Foundation
Research Org:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Science Foundation (NSF)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Atomic Regulon; regulatory network; stimuli; regulation; Bacillus subtilis
OSTI Identifier:
1337227
Alternate Identifier(s):
OSTI ID: 1393150