Dataset Information

Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis.

ABSTRACT: The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Bacillales species. For transcription factor (TF) regulons, we combined the available information from the DBTBS database and the literature with bioinformatics tools, allowing inference of TF binding sites (TFBSs), comparative analysis of the genomic context of predicted TFBSs, functional assignment of target genes, and effector prediction. For RNA regulons, we used known RNA regulatory motifs collected in the Rfam database to scan genomes and analyze the genomic context of new RNA sites. The inferred TRN in B. subtilis comprises regulons for 129 TFs and 24 regulatory RNA families. First, we analyzed 66 TF regulons with previously known TFBSs in B. subtilis and projected them to other Bacillales genomes, resulting in refinement of TFBS motifs and identification of novel regulon members. Second, we inferred motifs and described regulons for 28 experimentally studied TFs with previously unknown TFBSs. Third, we discovered novel motifs and reconstructed regulons for 36 previously uncharacterized TFs. The inferred collection of regulons is available in the RegPrecise database (http://regprecise.lbl.gov/) and can be used in genetic experiments, metabolic modeling, and evolutionary analysis.

SUBMITTER: Leyn SA

PROVIDER: S-EPMC3676070 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis.

Leyn Semen A SA Kazanov Marat D MD Sernova Natalia V NV Ermakova Ekaterina O EO Novichkov Pavel S PS Rodionov Dmitry A DA

Journal of bacteriology 20130315 11

The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Baci ...[more]

PMID: 23504016

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Project description: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.

Project description:BACKGROUND: The Bacillus subtilis genome (BGM) vector is a novel cloning system for large DNA fragments, in which the entire 4.2 Mb genome of B. subtilis functions as a vector. The BGM vector system has several attractive properties, such as a large cloning capacity of over 3 Mb, stable propagation of cloned DNA and various modification strategies using RecA-mediated homologous recombination. However, genetic modifications using the BGM vector system have not been fully established, and this system has not been applied to transgenesis. In this study, we developed important additions to the genetic modification methods of the BGM vector system. To explore the potential of the BGM vector, we focused on the fish-like odorant receptor (class I OR) gene family, which consists of 158 genes and forms a single gene cluster. Although a cis-acting locus control region is expected to regulate transcription, this has not yet been determined experimentally. RESULTS: Using two contiguous bacterial artificial chromosome clones containing several class I OR genes, we constructed two transgenes in the BGM vector by inserting a reporter gene cassette into one class I OR gene. Because they were oriented in opposite directions, we performed an inversion modification to align their orientation and then fused them to enlarge the genomic structure. DNA sequencing revealed that no mutations occurred during gene manipulations with the BGM vector. We further demonstrated that the modified, reconstructed genomic DNA fragments could be used to generate transgenic mice. Transgenic mice carrying the enlarged transgene recapitulated the expression and axonal projection patterns of the target class I OR gene in the main olfactory system. CONCLUSION: We offer a complete genetic modification method for the BGM vector system, including insertion, deletion, inversion and fusion, to engineer genomic DNA fragments without any trace of modifications. In addition, we demonstrate that this system can be used for mouse transgenesis. Thus, the BGM vector system can be an alternative platform for engineering large DNA fragments in addition to conventional systems such as bacterial and yeast artificial chromosomes. Using this system, we provide the first experimental evidence of a cis-acting element for a class I OR gene.

Dataset Information

Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis.

Publications

Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis.

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