Characterization of relationships between transcriptional units and operon structures in Bacillus subtilis and Escherichia coli

BACKGROUND: Operon structures play an important role in transcriptional regulation in prokaryotes. However, there have been fewer studies on complicated operon structures in which the transcriptional units vary with changing environmental conditions. Information about such complicated operons is helpful for predicting and analyzing operon structures, as well as understanding gene functions and transcriptional regulation. RESULTS: We systematically analyzed the experimentally verified transcriptional units (TUs) in Bacillus subtilis and Escherichia coli obtained from ODB and RegulonDB. To understand the relationships between TUs and operons, we defined a new classification system for adjacent gene pairs, divided into three groups according to the level of gene co-regulation: operon pairs (OP) belong to the same TU, sub-operon pairs (SOP) that are at the transcriptional boundaries within an operon, and non-operon pairs (NOP) belonging to different operons. Consequently, we found that the levels of gene co-regulation was correlated to intergenic distances and gene expression levels. Additional analysis revealed that they were also correlated to the levels of conservation across about 200 prokaryotic genomes. Most interestingly, we found that functional associations in SOPs were more observed in the environmental and genetic information processes. CONCLUSION: Complicated operon strucutures were correlated with genome organization and gene expression profiles. Such intricately regulated operons allow functional differences depending on environmental conditions. These regulatory mechanisms are helpful in accommodating the variety of changes that happen around the cell. In addition, such differences may play an important role in the evolution of gene order across genomes

COMODO: an adaptive coclustering strategy to identify conserved coexpression modules between organisms

Increasingly large-scale expression compendia for different species are becoming available. By exploiting the modularity of the coexpression network, these compendia can be used to identify biological processes for which the expression behavior is conserved over different species. However, comparing module networks across species is not trivial. The definition of a biologically meaningful module is not a fixed one and changing the distance threshold that defines the degree of coexpression gives rise to different modules. As a result when comparing modules across species, many different partially overlapping conserved module pairs across species exist and deciding which pair is most relevant is hard. Therefore, we developed a method referred to as conserved modules across organisms (COMODO) that uses an objective selection criterium to identify conserved expression modules between two species. The method uses as input microarray data and a gene homology map and provides as output pairs of conserved modules and searches for the pair of modules for which the number of sharing homologs is statistically most significant relative to the size of the linked modules. To demonstrate its principle, we applied COMODO to study coexpression conservation between the two well-studied bacteria Escherichia coli and Bacillus subtilis. COMODO is available at: http://homes.esat.kuleuven.be/∼kmarchal/Supplementary_Information_Zarrineh_2010/comodo/index.html

The entire organization of transcription units on the Bacillus subtilis genome

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, comprehension of cellular processes and systems requires global and non-targeted approaches to handle vast amounts of biological information.</p> <p>Results</p> <p>The present study predicts transcription units (TUs) in <it>Bacillus subtilis</it>, based on an integrated approach involving DNA sequence and transcriptome analyses. First, co-expressed gene clusters are predicted by calculating the Pearson correlation coefficients of adjacent genes for all the genes in a series that are transcribed in the same direction with no intervening gene transcribed in the opposite direction. Transcription factor (TF) binding sites are then predicted by detecting statistically significant TF binding sequences on the genome using a position weight matrix. This matrix is a convenient way to identify sites that are more highly conserved than others in the entire genome because any sequence that differs from a consensus sequence has a lower score. We identify genes regulated by each of the TFs by comparing gene expression between wild-type and TF mutants using a one-sided test. By applying the integrated approach to 11 σ factors and 17 TFs of <it>B. subtilis</it>, we are able to identify fewer candidates for genes regulated by the TFs than were identified using any single approach, and also detect the known TUs efficiently.</p> <p>Conclusion</p> <p>This integrated approach is, therefore, an efficient tool for narrowing searches for candidate genes regulated by TFs, identifying TUs, and estimating roles of the σ factors and TFs in cellular processes and functions of genes composing the TUs.</p

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

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00275We 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.AG and VF acknowledge funding from the European Union Basynthecproject(BaSynthecFP7-244093)

Two-component signal transduction in Bacillus cereus and closely related bacteria

Bacillus cereus is a Gram-positive pathogen that is recognised as an important cause of food-borne disease worldwide. Within the genus Bacillus, B. cereus and its closest relatives form a homogeneous subdivision that has been termed the B. cereus group. This group includes B. anthracis, a pathogen that can cause anthrax in mammals, and B. thuringiensis, an insect pathogen that is used as an insecticide worldwide. Members of the B. cereus group can adapt to a wide range of environmental challenges. In bacteria, these challenges are generally monitored by two-component systems (TCS), which consist of a histidine kinase (HK) and a partner response regulator (RR). Upon sensing a specific environmental stimulus, the HK activates its cognate RR, which in turn controls the expression of genes that are involved in the appropriate response. This thesis describes the functional analysis of TCSs in the B. cereus group. By using in silico techniques, 50-58 HKs and 48-52 RRs were identified in eight different B. cereus group genomes. Biological functions, including the involvement in sporulation, biofilm formation and host-microbe interactions were predicted for these TCS proteins. A phylogenetic footprinting approach was developed and used to identify specific binding sites and target genes for over 50% of the B. cereus group DNA-binding RRs. These predictions allowed relating several RRs to a minimal regulon and thereby to a characteristic transcriptional response. To further support these predictions, the transcriptomes of two B. cereus TCS deletion mutants (ΔyvrHG and ΔyufLM) were analysed and compared with the transcriptome of wild-type B. cereus. This revealed that the minimal regulon predictions were correct for the two respective TCSs. Furthermore, the predicted biological roles for these TCSs, including roles in antibiotic resistance (YvrHG) and fumarate metabolism (YufLM), were supported by phenotypic tests. Besides the many “classical” HKs and RRs detected in the B. cereus group, several a-typical TCS proteins were found. These included five RRs without a DNA-binding output domain and two hybrid HKs (HK-RR fusions). Genome analyses revealed that one of the hybrid HK-encoding genes (BC1008) is located in a conserved gene cluster that also encodes the a-typical RR RsbY. In B. cereus, RsbY is known to activate the key stress-responsive sigma factor σB. As a partner HK for RsbY was still “missing”, the role of BC1008 in the σB-mediated stress response was tested. Indeed, a bc1008 deletion strain appeared incapable of inducing σB and its associated regulon upon stress conditions and appeared impaired in its heat adaptive response. In addition, truncation of the BC1008 fused RR receiver domain indicated that this domain plays a role in fine-tuning BC1008 activity. A comparative genome analysis further indicated that BC1008-type hybrid HKs control σB-like sigma factors in at least several other Gram-positive bacteria, including Geobacillus, Paenibacillus and actinobacteria. In summary, the research described in this thesis contributes to our understanding of B. cereus adaptive responses through TCSs. This knowledge may be applied for the development of novel intervention strategies for an improved control of B. cereus in food production environments. <br/

Operon structure of Staphylococcus aureus

In bacteria, gene regulation is one of the fundamental characteristics of survival, colonization and pathogenesis. Operons play a key role in regulating expression of diverse genes involved in metabolism and virulence. However, operon structures in pathogenic bacteria have been determined only by in silico approaches that are dependent on factors such as intergenic distances and terminator/promoter sequences. Knowledge of operon structures is crucial to fully understand the pathophysiology of infections. Presently, transcriptome data obtained from growth curves in a defined medium were used to predict operons in Staphylococcus aureus. This unbiased approach and the use of five highly reproducible biological replicates resulted in 93.5% significantly regulated genes. These data, combined with Pearson’s correlation coefficients of the transcriptional profiles, enabled us to accurately compile 93% of the genome in operon structures. A total of 1640 genes of different functional classes were identified in operons. Interestingly, we found several operons containing virulence genes and showed synergistic effects for two complement convertase inhibitors transcribed in one operon. This is the first experimental approach to fully identify operon structures in S. aureus. It forms the basis for further in vitro regulation studies that will profoundly advance the understanding of bacterial pathophysiology in vivo

From transcriptional landscapes to the identification of biomarkers for robustness

The ability of microorganisms to adapt to changing environments and gain cell robustness, challenges the prediction of their history-dependent behaviour. Using our model organism Bacillus cereus, a notorious Gram-positive food spoilage and pathogenic spore-forming bacterium, a strategy will be described that allows for identification of biomarkers for robustness. First an overview will be presented of its two-component systems that generally include a transmembrane sensor histidine kinase and its cognate response regulator, allowing rapid and robust responses to fluctuations in the environment. The role of the multisensor hybrid kinase RsbK and the PP2C-type phosphatase RsbY system in activation of the general stress sigma factor σB is highlighted. An extensive comparative analysis of transcriptional landscapes derived from B. cereus exposed to mild stress conditions such as heat, acid, salt and oxidative stress, revealed that, amongst others σB regulated genes were induced in most conditions tested. The information derived from the transcriptome data was subsequently implemented in a framework for identifying and selecting cellular biomarkers at their mRNA, protein and/or activity level, for mild stressinduced microbial robustness towards lethal stresses. Exposure of unstressed and mild stress-adapted cells to subsequent lethal stress conditions (heat, acid and oxidative stress) allowed for quantification of the robustness advantage provided by mild stress pretreatment using the plate-count method. The induction levels of the selected candidate-biomarkers, σB protein, catalase activity and transcripts of certain proteases upon mild stress treatment, were significantly correlated to mild stress-induced enhanced robustness towards lethal thermal, oxidative and acid stresses, and were therefore suitable to predict these adaptive traits. Cellular biomarkers that are quantitatively correlated to adaptive behavior will facilitate our ability to predict the impact of adaptive behavior on cell robustness and will allow to control and/or exploit these adaptive traits. Extrapolation to other species and genera is discussed such as avenues towards mechanism-based design of microbial fitness and robustness