DBTBS: a database of transcriptional regulation in Bacillus subtilis containing upstream intergenic conservation information

Genomic arrangement of bacterial operons is constrained by biological pathways encoded in the genome

It is generally known that bacterial genes working in the same biological pathways tend to group into operons, possibly to facilitate cotranscription and to provide stoichiometry. However, very little is understood about what may determine the global arrangement of bacterial genes in a genome beyond the operon level. Here we present evidence that the global arrangement of operons in a bacterial genome is largely influenced by the tendency that a bacterium keeps its operons encoding the same biological pathway in nearby genomic locations, and by the tendency to keep operons involved in multiple pathways in locations close to the other members of their participating pathways. We also observed that the activation frequencies of pathways also influence the genomic locations of their encoding operons, tending to have operons of the more frequently activated pathways more tightly clustered together. We have quantitatively assessed the influences on the global genomic arrangement of operons by different factors. We found that the current arrangements of operons in most of the bacterial genomes we studied tend to minimize the overall distance between consecutive operons of a same pathway across all pathways encoded in the genome.

Connecting parts with processes: SubtiWiki and SubtiPathways integrate gene and pathway annotation for Bacillus subtilis

Bacillus subtilis is the model organism for a large group of Gram-positive bacteria, the Firmicutes. Several online databases have been established over time to manage its genetic and metabolic information, but they differ greatly in their rate of update and their focus on B. subtilis. Therefore, a European systems biology consortium called for an integrated solution that empowers its users to enrich online content. To meet this goal we created SubtiWiki and SubtiPathways, two complementary online tools for gene and pathway information on B. subtilis 168. SubtiWiki (http://subtiwiki.uni-goettingen.de/) is a scientific wiki for all genes of B. subtilis and their protein or RNA products. Each gene page contains a summary of the most important information; sections on the gene, its product and expression; sections concerning biological materials and laboratories; and a list of references. SubtiWiki has been seeded with key content and can be extended by any researcher after a simple registration, thus keeping it always up to date. As a complement, SubtiPathways (http://subtipathways.uni-goettingen.de/) is an online tool for navigation of the metabolism of B. subtilis and its regulation. Each SubtiPathways diagram presents a metabolic pathway with its participating enzymes, together with the regulatory mechanisms that act on their expression and activity, in an intuitive interface that is based on Google Maps. Together, SubtiWiki and SubtiPathways provide an integrated view of the processes that make up B. subtilis and its components, making it the most comprehensive web resource for B. subtilis researchers.

Identification and genomic analysis of transcription factors in archaeal genomes exemplifies their functional architecture and evolutionary origin

Archaea, which represent a large fraction of the phylogenetic diversity of organisms, are prokaryotes with eukaryote-like basal transcriptional machinery. This organization makes the study of their DNA-binding transcription factors (TFs) and their transcriptional regulatory networks particularly interesting. In addition, there are limited experimental data regarding their TFs. In this work, 3,918 TFs were identified and exhaustively analyzed in 52 archaeal genomes. TFs represented less than 5% of the gene products in all the studied species comparable with the number of TFs identified in parasites or intracellular pathogenic bacteria, suggesting a deficit in this class of proteins. A total of 75 families were identified, of which HTH_3, AsnC, TrmB, and ArsR families were universally and abundantly identified in all the archaeal genomes. We found that archaeal TFs are significantly small compared with other protein-coding genes in archaea as well as bacterial TFs, suggesting that a large fraction of these small-sized TFs could supply the probable deficit of TFs in archaea, by possibly forming different combinations of monomers similar to that observed in eukaryotic transcriptional machinery. Our results show that although the DNA-binding domains of archaeal TFs are similar to bacteria, there is an underrepresentation of ligand-binding domains in smaller TFs, which suggests that protein–protein interactions may act as mediators of regulatory feedback, indicating a chimera of bacterial and eukaryotic TFs’ functionality. The analysis presented here contributes to the understanding of the details of transcriptional apparatus in archaea and provides a framework for the analysis of regulatory networks in these organisms.

Studies on the O3-initiated disinfection from Gram-positive bacteria Bacillus subtilis in aquatic systems

The kinetics of inactivation of Gram-positive strain, Bacillus subtilis in aquatic systems was investigated as function ozone aeration duration under varied conditions. Oxygen flow was in situ enriched with ozone using ozoniser, with [O(3)] ranging from (0.3 - 9.8) x 10(-5) moles per liter of oxygen. The inactivation kinetics of B. subtilis followed pseudo-first-order kinetics with respect to microbe, under excess [O(3)] conditions. The disinfection kinetics had first order dependence on ozone concentration and the overall second-order rate constant was (7.54 +/- 1.37) x 10(3) M(-1) min(-1). The effect initial temperature and pH of the system on the ozone initiated inactivation of microbe was also explored. Relative to hydroxyl radicals, molecular ozone was found more effective in microbial inactivation. Appropriate mechanism for ozone initiated inactivation is proposed. Ozone aeration significantly decreased the BOD levels of natural and B. subtilis spiked waters.

Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry.

Red light activates the sigmaB-mediated general stress response of Bacillus subtilis via the energy branch of the upstream signaling cascade

The sigma(B)-dependent general stress response in the common soil bacterium Bacillus subtilis can be elicited by a range of stress factors, such as starvation or an ethanol, salt, or heat shock, via a complex upstream signaling cascade. Additionally, sigma(B) can be activated by blue light via the phototropin homologue YtvA, a component of the environmental branch of the signaling cascade. Here we use a reporter-gene fusion to show that sigma(B) can also be activated by red light via the energy branch of its upstream signaling cascade. Deletion mutagenesis and homologous overproduction experiments indicate that the RsbP protein (composed of an N-terminal Per-ARNT-Sim [PAS] domain and a C-terminal PP2C-type phosphatase domain) is involved in the red light response. This second light input pathway functions complementarily to YtvA; it shows broader spectral sensitivity but requires higher light intensities. These results are confirmed by transcriptome analyses, which show that both light effects result in upregulation of the sigma(B) regulon, with minimal activation of other responses.

A comprehensive proteomics and transcriptomics analysis of Bacillus subtilis salt stress adaptation

In its natural habitats, Bacillus subtilis is exposed to changing osmolarity, necessitating adaptive stress responses. Transcriptomic and proteomic approaches can provide a picture of the dynamic changes occurring in salt-stressed B. subtilis cultures because these studies provide an unbiased view of cells coping with high salinity. We applied whole-genome microarray technology and metabolic labeling, combined with state-of-the-art proteomic techniques, to provide a global and time-resolved picture of the physiological response of B. subtilis cells exposed to a severe and sudden osmotic upshift. This combined experimental approach provided quantitative data for 3,961 mRNA transcription profiles, 590 expression profiles of proteins detected in the cytosol, and 383 expression profiles of proteins detected in the membrane fraction. Our study uncovered a well-coordinated induction of gene expression subsequent to an osmotic upshift that involves large parts of the SigB, SigW, SigM, and SigX regulons. Additionally osmotic upregulation of a large number of genes that do not belong to these regulons was observed. In total, osmotic upregulation of about 500 B. subtilis genes was detected. Our data provide an unprecedented rich basis for further in-depth investigation of the physiological and genetic responses of B. subtilis to hyperosmotic stress.

RegPrecise: a database of curated genomic inferences of transcriptional regulatory interactions in prokaryotes

The RegPrecise database (http://regprecise.lbl.gov) was developed for capturing, visualization and analysis of predicted transcription factor regulons in prokaryotes that were reconstructed and manually curated by utilizing the comparative genomic approach. A significant number of high-quality inferences of transcriptional regulatory interactions have been already accumulated for diverse taxonomic groups of bacteria. The reconstructed regulons include transcription factors, their cognate DNA motifs and regulated genes/operons linked to the candidate transcription factor binding sites. The RegPrecise allows for browsing the regulon collections for: (i) conservation of DNA binding sites and regulated genes for a particular regulon across diverse taxonomic lineages; (ii) sets of regulons for a family of transcription factors; (iii) repertoire of regulons in a particular taxonomic group of species; (iv) regulons associated with a metabolic pathway or a biological process in various genomes. The initial release of the database includes ∼11 500 candidate binding sites for ∼400 orthologous groups of transcription factors from over 350 prokaryotic genomes. Majority of these data are represented by genome-wide regulon reconstructions in Shewanella and Streptococcus genera and a large-scale prediction of regulons for the LacI family of transcription factors. Another section in the database represents the results of accurate regulon propagation to the closely related genomes.

New insights into the regulatory networks of paralogous genes in bacteria

Extensive genomic studies on gene duplication in model organisms such as Escherichia coli and Saccharomyces cerevisiae have recently been undertaken. In these models, it is commonly considered that a duplication event may include a transcription factor (TF), a target gene, or both. Following a gene duplication episode, varying scenarios have been postulated to describe the evolution of the regulatory network. However, in most of these, the TFs have emerged as the most important and in some cases the only factor shaping the regulatory network as the organism responds to a natural selection process, in order to fulfil its metabolic needs. Recent findings concerning the regulatory role played by elements other than TFs have indicated the need to reassess these early models. Thus, we performed an exhaustive review of paralogous gene regulation in E. coli and Bacillus subtilis based on published information, available in the NCBI PubMed database and in well-established regulatory databases. Our survey reinforces the notion that despite TFs being the most prominent components shaping the regulatory networks, other elements are also important. These include small RNAs, riboswitches, RNA-binding proteins, sigma factors, protein-protein interactions and DNA supercoiling, which modulate the expression of genes involved in particular metabolic processes or induce a more complex response in terms of the regulatory networks of paralogous genes in an integrated interplay with TFs.

A community-curated consensual annotation that is continuously updated: the Bacillus subtilis centred wiki SubtiWiki

Bacillus subtilis is the model organism for Gram-positive bacteria, with a large amount of publications on all aspects of its biology. To facilitate genome annotation and the collection of comprehensive information on B. subtilis, we created SubtiWiki as a community-oriented annotation tool for information retrieval and continuous maintenance. The wiki is focused on the needs and requirements of scientists doing experimental work. This has implications for the design of the interface and for the layout of the individual pages. The pages can be accessed primarily by the gene designations. All pages have a similar flexible structure and provide links to related gene pages in SubtiWiki or to information in the World Wide Web. Each page gives comprehensive information on the gene, the encoded protein or RNA as well as information related to the current investigation of the gene/protein. The wiki has been seeded with information from key publications and from the most relevant general and B. subtilis-specific databases. We think that SubtiWiki might serve as an example for other scientific wikis that are devoted to the genes and proteins of one organism.

Database URL: The wiki can be accessed at http://subtiwiki.uni-goettingen.de/

Apprehending multicellularity: regulatory networks, genomics, and evolution

The genomic revolution has provided the first glimpses of the architecture of regulatory networks. Combined with evolutionary information, the "network view" of life processes leads to remarkable insights into how biological systems have been shaped by various forces. This understanding is critical because biological systems, including regulatory networks, are not products of engineering but of historical contingencies. In this light, we attempt a synthetic overview of the natural history of regulatory networks operating in the development and differentiation of multicellular organisms. We first introduce regulatory networks and their organizational principles as can be deduced using ideas from the graph theory. We then discuss findings from comparative genomics to illustrate the effects of lineage-specific expansions, gene-loss, and nonprotein-coding DNA on the architecture of networks. We consider the interaction between expansions of transcription factors, and cis regulatory and more general chromatin state stabilizing elements in the emergence of morphological complexity. Finally, we consider a case study of the Notch subnetwork, which is present throughout Metazoa, to examine how such a regulatory system has been pieced together in evolution from new innovations and pre-existing components that were originally functionally distinct.

The transcriptionally active regions in the genome of Bacillus subtilis

The majority of all genes have so far been identified and annotated systematically through in silico gene finding. Here we report the finding of 3662 strand-specific transcriptionally active regions (TARs) in the genome of Bacillus subtilis by the use of tiling arrays. We have measured the genome-wide expression during mid-exponential growth on rich (LB) and minimal (M9) medium. The identified TARs account for 77.3% of the genes as they are currently annotated and additionally we find 84 putative non-coding RNAs (ncRNAs) and 127 antisense transcripts. One ncRNA, ncr22, is predicted to act as a translational control on cstA and an antisense transcript was observed opposite the housekeeping sigma factor sigA. Through this work we have discovered a long conserved 3' untranslated region (UTR) in a group of membrane-associated genes that is predicted to fold into a large and highly stable secondary structure. One of the genes having this tail is efeN, which encodes a target of the twin-arginine translocase (Tat) protein translocation system.

Mechanisms and evolution of control logic in prokaryotic transcriptional regulation

A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.

Identification of network topological units coordinating the global expression response to glucose in Bacillus subtilis and its comparison to Escherichia coli

Background

Glucose is the preferred carbon and energy source for Bacillus subtilis and Escherichia coli. A complex regulatory network coordinates gene expression, transport and enzymatic activities, in response to the presence of this sugar. We present a comparison of the cellular response to glucose in these two model organisms, using an approach combining global transcriptome and regulatory network analyses.

Results

Transcriptome data from strains grown in Luria-Bertani medium (LB) or LB+glucose (LB+G) were analyzed, in order to identify differentially transcribed genes in B. subtilis. We detected 503 genes in B. subtilis that change their relative transcript levels in the presence of glucose. A similar previous study identified 380 genes in E. coli, which respond to glucose. Catabolic repression was detected in the case of transport and metabolic interconversion activities for both bacteria in LB+G. We detected an increased capacity for de novo synthesis of nucleotides, amino acids and proteins. A comparison between orthologous genes revealed that global regulatory functions such as transcription, translation, replication and genes relating to the central carbon metabolism, presented similar changes in their levels of expression. An analysis of the regulatory network of a subset of genes in both organisms revealed that the set of regulatory proteins responsible for similar physiological responses observed in the transcriptome analysis are not orthologous. An example of this observation is that of transcription factors mediating catabolic repression for most of the genes that displayed reduced transcript levels in the case of both organisms. In terms of topological functional units in both these bacteria, we found interconnected modules that cluster together genes relating to heat shock, respiratory functions, carbon and peroxide metabolism. Interestingly, B. subtilis functions not found in E. coli, such as sporulation and competence were shown to be interconnected, forming modules subject to catabolic repression at the level of transcription.

Conclusion

Our results demonstrate that the response to glucose is partially conserved in model organisms E. coli and B. subtilis, including genes encoding basic functions such as transcription, translation, replication and genes involved in the central carbon metabolism.

On the basic computational structure of gene regulatory networks

Gene regulatory networks constitute the first layer of the cellular computation for cell adaptation and surveillance. In these webs, a set of causal relations is built up from thousands of interactions between transcription factors and their target genes. The large size of these webs and their entangled nature make it difficult to achieve a global view of their internal organisation. Here, this problem has been addressed through a comparative study of Escherichia coli, Bacillus subtilis and Saccharomyces cerevisiae gene regulatory networks. We extract the minimal core of causal relations, uncovering the hierarchical and modular organisation from a novel dynamical/causal perspective. Our results reveal a marked top-down hierarchy containing several small dynamical modules for E. coli and B. subtilis. Conversely, the yeast network displays a single but large dynamical module in the middle of a bow-tie structure. We found that these dynamical modules capture the relevant wiring among both common and organism-specific biological functions such as transcription initiation, metabolic control, signal transduction, response to stress, sporulation and cell cycle. Functional and topological results suggest that two fundamentally different forms of logic organisation may have evolved in bacteria and yeast.

Stochasticity in protein levels drives colinearity of gene order in metabolic operons of Escherichia coli

Gene order in some bacterial metabolic operons reflects ordering in the metabolic pathway. That this is true uniquely for operons expressed at low levels highlights the selective importance of fluctuations in protein levels.

In bacterial genomes, gene order is not random. This is most evident when looking at operons, these often encoding enzymes involved in the same metabolic pathway or proteins from the same complex. Is gene order within operons nonrandom, however, and if so why? We examine this issue using metabolic operons as a case study. Using the metabolic network of Escherichia coli, we define the temporal order of reactions. We find a pronounced trend for genes to appear in operons in the same order as they are needed in metabolism (colinearity). This is paradoxical as, at steady state, enzymes abundance should be independent of order within the operon. We consider three extensions of the steady-state model that could potentially account for colinearity: (1) increased productivity associated with higher expression levels of the most 5′ genes, (2) a faster metabolic processing immediately after up-regulation, and (3) metabolic stalling owing to stochastic protein loss. We establish the validity of these hypotheses by employing deterministic and stochastic models of enzyme kinetics. The stochastic stalling hypothesis correctly and uniquely predicts that colinearity is more pronounced both for lowly expressed operons and for genes that are not physically adjacent. The alternative models fail to find any support. These results support the view that stochasticity is a pervasive problem to a cell and that gene order evolution can be driven by the selective consequences of fluctuations in protein levels.

In bacteria, different enzymes from the same metabolic pathway are often encoded within one transcriptional unit, an operon. There is also, we show, a tendency for the enzymes that are needed earlier in the pathway to feature earlier in the operon, so-called colinearity. Why might this be? We test three ideas, one old and two new. The prior suggestion supposes that proteins of genes early in operons will be at a higher dose. Although some operons are like this, in general, we see no relationship of protein dose with colinearity. We also find no evidence that operons that frequently need up-regulation are any more likely to be colinear. A third model is, however, supported. If an operon is rarely expressed, then all the proteins for this part of metabolism can be lost by chance. Rebooting such metabolism is fastest if the operon is colinear. This model predicts, correctly, that colinearity should be more frequent in operons that are expressed at a low level. This result is important for at least two reasons. First, it supports the view that chance events (such as protein loss) within cells are important on a day-to-day basis. Second, it challenges the supposition that natural selection will be weakest on lowly expressed genes. Where chance events are concerned, natural selection can be strong on genes expressed at a low level.

Transcriptional regulation of the capsular polysaccharide biosynthesis locus of streptococcus pneumoniae: a bioinformatic analysis

The polysaccharide capsule of Streptococcus pneumoniae is the main virulence factor, which makes the bacterium resistant to phagocytosis. Expression of capsular polysaccharide must be adjusted at different stages of pneumococcal infection, thus, their transcriptional regulation appears to be crucial. To get insight into the existence of regulatory mechanisms common to most serotypes, a bioinformatic analysis of the DNA region located upstream of the capsular locus was performed. With the exception of serotype 37, the capsular locus is located between dexB and aliA on the pneumococcal chromosome. Up to 26 different sequence organizations were found among pneumococci synthesizing their capsule through a Wzy-polymerase-dependent mechanism, mostly varying according to the presence/absence of distinct insertion elements. As a consequence, only ∼250 bp (including a 107 bp RUP_A element) was conserved in 86 sequences, although only a short (ca. 87 bp) region located immediately upstream of cpsA was strictly conserved in all the sequences analyzed. An exhaustive search for possible operator sequences was done. Interestingly, although the promoter region of serotype 3 isolates completely differs from that of other serotypes, most of the proteins proposed to regulate transcription in serotype 3 pneumococci were also predicted to function as possible regulators in non-serotype 3 S. pneumoniae isolates.

Genome-wide de novo prediction of cis-regulatory binding sites in prokaryotes

Although cis-regulatory binding sites (CRBSs) are at least as important as the coding sequences in a genome, our general understanding of them in most sequenced genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization, which has largely hindered our understanding of many important biological processes. In this article, we describe a novel algorithm for genome-wide de novo prediction of CRBSs with high accuracy. We designed our algorithm to circumvent three identified difficulties for CRBS prediction using comparative genomics principles based on a new method for the selection of reference genomes, a new metric for measuring the similarity of CRBSs, and a new graph clustering procedure. When operon structures are correctly predicted, our algorithm can predict 81% of known individual binding sites belonging to 94% of known cis-regulatory motifs in the Escherichia coli K12 genome, while achieving high prediction specificity. Our algorithm has also achieved similar prediction accuracy in the Bacillus subtilis genome, suggesting that it is very robust, and thus can be applied to any other sequenced prokaryotic genome. When compared with the prior state-of-the-art algorithms, our algorithm outperforms them in both prediction sensitivity and specificity.

Reconstructing prokaryotic transcriptional regulatory networks: lessons from actinobacteria

Reconstruction of transcriptional regulatory networks of uncharacterized bacteria is a main challenge for the post-genomic era. Recent studies, including one in BMC Systems Biology, address this problem in the relatively underexplored actinobacteria clade, which includes major pathogenic and economically relevant taxa.

Regulation by transcription factors in bacteria: beyond description

Transcription is an essential step in gene expression and its understanding has been one of the major interests in molecular and cellular biology. By precisely tuning gene expression, transcriptional regulation determines the molecular machinery for developmental plasticity, homeostasis and adaptation. In this review, we transmit the main ideas or concepts behind regulation by transcription factors and give just enough examples to sustain these main ideas, thus avoiding a classical ennumeration of facts. We review recent concepts and developments: cis elements and trans regulatory factors, chromosome organization and structure, transcriptional regulatory networks (TRNs) and transcriptomics. We also summarize new important discoveries that will probably affect the direction of research in gene regulation: epigenetics and stochasticity in transcriptional regulation, synthetic circuits and plasticity and evolution of TRNs. Many of the new discoveries in gene regulation are not extensively tested with wetlab approaches. Consequently, we review this broad area in Inference of TRNs and Dynamical Models of TRNs. Finally, we have stepped backwards to trace the origins of these modern concepts, synthesizing their history in a timeline schema.

Towards the integrated analysis, visualization and reconstruction of microbial gene regulatory networks

To handle changing environmental surroundings and to manage unfavorable conditions, microbial organisms have evolved complex transcriptional regulatory networks. To comprehensively analyze these gene regulatory networks, several online available databases and analysis platforms have been implemented and established. In this article, we address the typical cycle of scientific knowledge exploration and integration in the area of procaryotic transcriptional gene regulation. We briefly review five popular, publicly available systems that support (i) the integration of existing knowledge, (ii) visualization capabilities and (iii) computer analysis to predict promising wet lab targets. We exemplify the benefits of such integrated data analysis platforms by means of four application cases exemplarily performed with the corynebacterial reference database CoryneRegNet.

Using RSAT oligo-analysis and dyad-analysis tools to discover regulatory signals in nucleic sequences

This protocol explains how to discover functional signals in genomic sequences by detecting over- or under-represented oligonucleotides (words) or spaced pairs thereof (dyads) with the Regulatory Sequence Analysis Tools (http://rsat.ulb.ac.be/rsat/). Two typical applications are presented: (i) predicting transcription factor-binding motifs in promoters of coregulated genes and (ii) discovering phylogenetic footprints in promoters of orthologous genes. The steps of this protocol include purging genomic sequences to discard redundant fragments, discovering over-represented patterns and assembling them to obtain degenerate motifs, scanning sequences and drawing feature maps. The main strength of the method is its statistical ground: the binomial significance provides an efficient control on the rate of false positives. In contrast with optimization-based pattern discovery algorithms, the method supports the detection of under- as well as over-represented motifs. Computation times vary from seconds (gene clusters) to minutes (whole genomes). The execution of the whole protocol should take approximately 1 h.

DOOR: a database for prokaryotic operons

We present a database DOOR (Database for prOkaryotic OpeRons) containing computationally predicted operons of all the sequenced prokaryotic genomes. All the operons in DOOR are predicted using our own prediction program, which was ranked to be the best among 14 operon prediction programs by a recent independent review. Currently, the DOOR database contains operons for 675 prokaryotic genomes, and supports a number of search capabilities to facilitate easy access and utilization of the information stored in it.

Querying the database: the database provides a search capability for a user to find desired operons and associated information through multiple querying methods.

Searching for similar operons: the database provides a search capability for a user to find operons that have similar composition and structure to a query operon.

Prediction of cis-regulatory motifs: the database provides a capability for motif identification in the promoter regions of a user-specified group of possibly coregulated operons, using motif-finding tools.

Operons for RNA genes: the database includes operons for RNA genes.

OperonWiki: the database provides a wiki page (OperonWiki) to facilitate interactions between users and the developer of the database.

We believe that DOOR provides a useful resource to many biologists working on bacteria and archaea, which can be accessed at http://csbl1.bmb.uga.edu/OperonDB.

PRODORIC (release 2009): a database and tool platform for the analysis of gene regulation in prokaryotes

PRODORIC is a database that provides annotated information on the regulation of gene expression in prokaryotes. It integrates a large compilation of gene regulatory data including transcription factor binding sites, promoter structures and gene expression patterns. The whole dataset is manually curated and relies on published results extracted from the scientific literature. The current extended version of PRODORIC contains gene regulatory data for several new microorganisms. Major improvements were realized in the design of the web interface and the accessibility of the stored information. The database was further improved by the implementation of various new tools for the elucidation of gene regulatory interactions. Thus, the PRODORIC platform represents a framework for the interactive exploration, prediction and evaluation of gene regulatory networks in prokaryotes. PRODORIC is accessible at http://www.prodoric.de.

Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

Background

Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar expression patterns are more likely to participate in shared biological processes.

Results

We developed Prosecutor, an application that enables researchers to rapidly infer gene function based on available gene expression data and functional annotations. Our parameter-free functional prediction method uses a sensitive algorithm to achieve a high association rate of linking genes with unknown function to annotated genes. Furthermore, Prosecutor utilizes additional biological information such as genomic context and known regulatory mechanisms that are specific for prokaryotes. We analyzed publicly available transcriptome data sets and used literature sources to validate putative functions suggested by Prosecutor. We supply the complete results of our analysis for 11 prokaryotic organisms on a dedicated website.

Conclusion

The Prosecutor software and supplementary datasets available at allow researchers working on any of the analyzed organisms to quickly identify the putative functions of their genes of interest. A de novo analysis allows new organisms to be studied.

Novel small RNA-encoding genes in the intergenic regions of Bacillus subtilis

Small, non-coding RNAs (ncRNAs) perform diverse functions in a variety of organisms, but few ncRNAs have been identified in Bacillus subtilis. To search the B. subtilis genome for genes encoding ncRNAs, we focused on 123 intergenic regions (IGRs) over 500 bp in length and analyzed expression from these regions. Seven IGRs termed bsrC, bsrD, bsrE, bsrF, bsrG, bsrH and bsrI expressed RNAs smaller than 380 nt. All small RNAs except BsrD RNA were expressed in transformed Escherichia coli cells harboring a plasmid with PCR-amplified IGRs of B. subtilis, indicating that their own promoters independently express small RNAs. Under the non-stressed condition, depletion of the genes for the small RNAs did not affect growth. Although their functions are unknown, gene expression profiles at several time points showed that most of the genes except for bsrD were expressed during the vegetative phase (4-6 h), but undetectable during the stationary phase (8 h). Mapping the 5' ends of the 6 small RNAs revealed that the genes for BsrE, BsrF, BsrG, BsrH, and BsrI RNAs are preceded by a recognition site for RNA polymerase sigma factor sigma(A). These small RNAs might lack an SD sequence and exert their actions as ncRNAs.

Genome holography: deciphering function-form motifs from gene expression data

Background

DNA chips allow simultaneous measurements of genome-wide response of thousands of genes, i.e. system level monitoring of the gene-network activity. Advanced analysis methods have been developed to extract meaningful information from the vast amount of raw gene-expression data obtained from the microarray measurements. These methods usually aimed to distinguish between groups of subjects (e.g., cancer patients vs. healthy subjects) or identifying marker genes that help to distinguish between those groups. We assumed that motifs related to the internal structure of operons and gene-networks regulation are also embedded in microarray and can be deciphered by using proper analysis.

Methodology/Principal Findings

The analysis presented here is based on investigating the gene-gene correlations. We analyze a database of gene expression of Bacillus subtilis exposed to sub-lethal levels of 37 different antibiotics. Using unsupervised analysis (dendrogram) of the matrix of normalized gene-gene correlations, we identified the operons as they form distinct clusters of genes in the sorted correlation matrix. Applying dimension-reduction algorithm (Principal Component Analysis, PCA) to the matrices of normalized correlations reveals functional motifs. The genes are placed in a reduced 3-dimensional space of the three leading PCA eigen-vectors according to their corresponding eigen-values. We found that the organization of the genes in the reduced PCA space recovers motifs of the operon internal structure, such as the order of the genes along the genome, gene separation by non-coding segments, and translational start and end regions. In addition to the intra-operon structure, it is also possible to predict inter-operon relationships, operons sharing functional regulation factors, and more. In particular, we demonstrate the above in the context of the competence and sporulation pathways.

Conclusions/Significance

We demonstrated that by analyzing gene-gene correlation from gene-expression data it is possible to identify operons and to predict unknown internal structure of operons and gene-networks regulation.

Autoregulation of swrAA and motility in Bacillus subtilis

We demonstrate that transcription of the gene swrAA, required for swarming migration in Bacillus subtilis, is driven by two promoters: a sigD-dependent promoter and a putative sigA-dependent promoter, which is inactive during growth in liquid Luria-Bertani medium and becomes active in the presence of the phosphorylated form of the response regulator DegU or on semisolid surfaces. Since sigD transcription is enhanced by SwrAA, this finding reveals that swrA expression is controlled by a positive feedback loop. We also demonstrate that the positive action of SwrAA in swimming and swarming motility is prevented in strains carrying a deletion of the two-component system degS-degU and that this effect is independent of swrAA transcription. Therefore, both DegU and SwrAA must be present to achieve full motility in B. subtilis.

ProdoNet: identification and visualization of prokaryotic gene regulatory and metabolic networks

ProdoNet is a web-based application for the mapping of prokaryotic genes and the corresponding proteins to common gene regulatory and metabolic networks. For a given list of genes, the system detects shared operons, identifies co-expressed genes and deduces joint regulators. In addition, the contribution to shared metabolic pathways becomes visible on KEGG maps. Furthermore, the co-occurrence of genes of interest in gene expression profiles can be added to the visualization of the global network. In this way, ProdoNet provides the basis for functional genomics approaches and for the interpretation of transcriptomics and proteomics data. As an example, we present an investigation of an experimental membrane subproteome analysis of Pseudomonas aeruginosa with ProdoNet. The ProdoNet dataset on transcriptional regulation is based on the PRODORIC Prokaryotic Database of Gene Regulation and the Virtual Footprint tool. ProdoNet is accessible at http://www.prodonet.tu-bs.de.

The relative value of operon predictions

For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation, (iv) sequence elements and (v) experimental evidence. The performance estimates of operon predictions reported in literature cannot directly be compared due to differences in methods and data used in these studies. Here, we survey the current status of operon prediction methods. Based on a comparison of the performance of operon predictions on Escherichia coli and Bacillus subtilis we conclude that there is still room for improvement. We expect that existing and newly generated genomics and transcriptomics data will further improve accuracy of operon prediction methods.

Towards the development of Bacillus subtilis as a cell factory for membrane proteins and protein complexes

Background

The Gram-positive bacterium Bacillus subtilis is an important producer of high quality industrial enzymes and a few eukaryotic proteins. Most of these proteins are secreted into the growth medium, but successful examples of cytoplasmic protein production are also known. Therefore, one may anticipate that the high protein production potential of B. subtilis can be exploited for protein complexes and membrane proteins to facilitate their functional and structural analysis. The high quality of proteins produced with B. subtilis results from the action of cellular quality control systems that efficiently remove misfolded or incompletely synthesized proteins. Paradoxically, cellular quality control systems also represent bottlenecks for the production of various heterologous proteins at significant concentrations.

Conclusion

While inactivation of quality control systems has the potential to improve protein production yields, this could be achieved at the expense of product quality. Mechanisms underlying degradation of secretory proteins are nowadays well understood and often controllable. It will therefore be a major challenge for future research to identify and modulate quality control systems of B. subtilis that limit the production of high quality protein complexes and membrane proteins, and to enhance those systems that facilitate assembly of these proteins.

The Bacillus subtilis sigma(M) regulon and its contribution to cell envelope stress responses

The Bacillus subtilis extracytoplasmic function (ECF) sigma(M) factor is activated by cell envelope stress elicited by antibiotics, and by acid, heat, ethanol and superoxide stresses. Here, we have used several complementary approaches to identify genes controlled by sigma(M). In many cases, expression is only partially dependent on sigma(M) because of both overlapping promoter recognition with other ECF sigma factors and the presence of additional promoter elements. Genes regulated by sigma(M) have a characteristic pattern of induction in response to cell envelope-acting antibiotics as evidenced by hierarchical clustering analysis. sigma(M) also contributes to the expression of the Spx transcription factor and thereby indirectly regulates genes of the Spx regulon. Cell envelope stress responses also include regulons controlled by sigma(W), sigma(B) and several two-component regulatory systems (e.g. LiaRS, YycFG, BceRS). Activation of the sigma(M) regulon increases expression of proteins functioning in transcriptional control, cell wall synthesis and shape determination, cell division, DNA damage monitoring, recombinational repair and detoxification.