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

Exploring a unique class of flavoenzymes: Identification and biochemical characterization of ribosomal RNA dihydrouridine synthase

Dihydrouridine (D), a prevalent and evolutionarily conserved base in the transcriptome, primarily resides in tRNAs and, to a lesser extent, in mRNAs. Notably, this modification is found at position 2449 in the Escherichia coli 23S rRNA, strategically positioned near the ribosome's peptidyl transferase site. Despite the prior identification, in E. coli genome, of three dihydrouridine synthases (DUS), a set of NADPH and FMN-dependent enzymes known for introducing D in tRNAs and mRNAs, characterization of the enzyme responsible for D2449 deposition has remained elusive. This study introduces a rapid method for detecting D in rRNA, involving reverse transcriptase-blockage at the rhodamine-labeled D2449 site, followed by PCR amplification (RhoRT-PCR). Through analysis of rRNA from diverse E. coli strains, harboring chromosomal or single-gene deletions, we pinpoint the yhiN gene as the ribosomal dihydrouridine synthase, now designated as RdsA. Biochemical characterizations uncovered RdsA as a unique class of flavoenzymes, dependent on FAD and NADH, with a complex structural topology. In vitro assays demonstrated that RdsA dihydrouridylates a short rRNA transcript mimicking the local structure of the peptidyl transferase site. This suggests an early introduction of this modification before ribosome assembly. Phylogenetic studies unveiled the widespread distribution of the yhiN gene in the bacterial kingdom, emphasizing the conservation of rRNA dihydrouridylation. In a broader context, these findings underscore nature's preference for utilizing reduced flavin in the reduction of uridines and their derivatives.

Alternate routes to mnm5s2U synthesis in Gram-positive bacteria

The wobble bases of tRNAs that decode split codons are often heavily modified. In bacteria, tRNAGlu, Gln, Asp contains a variety of xnm5s2U derivatives. The synthesis pathway for these modifications is complex and fully elucidated only in a handful of organisms, including the Gram-negative Escherichia coli K12 model. Despite the ubiquitous presence of mnm5s2U modification, genomic analysis shows the absence of mnmC orthologous genes, suggesting the occurrence of alternate biosynthetic schemes for the conversion of cmnm5s2U to mnm5s2U. Using a combination of comparative genomics and genetic studies, a member of the YtqA subgroup of the radical Sam superfamily was found to be involved in the synthesis of mnm5s2U in both Bacillus subtilis and Streptococcus mutans. This protein, renamed MnmL, is encoded in an operon with the recently discovered MnmM methylase involved in the methylation of the pathway intermediate nm5s2U into mnm5s2U in B. subtilis. Analysis of tRNA modifications of both S. mutans and Streptococcus pneumoniae shows that growth conditions and genetic backgrounds influence the ratios of pathway intermediates owing to regulatory loops that are not yet understood. The MnmLM pathway is widespread along the bacterial tree, with some phyla, such as Bacilli, relying exclusively on these two enzymes. Although mechanistic details of these newly discovered components are not fully resolved, the occurrence of fusion proteins, alternate arrangements of biosynthetic components, and loss of biosynthetic branches provide examples of biosynthetic diversity to retain a conserved tRNA modification in Nature.IMPORTANCEThe xnm5s2U modifications found in several tRNAs at the wobble base position are widespread in bacteria where they have an important role in decoding efficiency and accuracy. This work identifies a novel enzyme (MnmL) that is a member of a subgroup of the very versatile radical SAM superfamily and is involved in the synthesis of mnm5s2U in several Gram-positive bacteria, including human pathogens. This is another novel example of a non-orthologous displacement in the field of tRNA modification synthesis, showing how different solutions evolve to retain U34 tRNA modifications.

Alternate routes to mnm 5 s 2 U synthesis in Gram-positive bacteria

The wobble bases of tRNAs that decode split codons are often heavily modified. In Bacteria tRNA Glu, Gln, Asp contain a variety of xnm 5 s 2 U derivatives. The synthesis pathway for these modifications is complex and fully elucidated only in a handful of organisms, including the Gram-negative Escherichia coli K12 model. Despite the ubiquitous presence of mnm 5 s 2 U modification, genomic analysis shows the absence of mnmC orthologous genes, suggesting the occurrence of alternate biosynthetic schemes for the installation of this modification. Using a combination of comparative genomics and genetic studies, a member of the YtqA subgroup of the Radical Sam superfamily was found to be involved in the synthesis of mnm 5 s 2 U in both Bacillus subtilis and Streptococcus mutans . This protein, renamed MnmL, is encoded in an operon with the recently discovered MnmM methylase involved in the methylation of the pathway intermediate nm 5 s 2 U into mnm 5 s 2 U in B. subtilis . Analysis of tRNA modifications of both S. mutans and Streptococcus pneumoniae shows that growth conditions and genetic backgrounds influence the ratios of pathways intermediates in regulatory loops that are not yet understood. The MnmLM pathway is widespread along the bacterial tree, with some phyla, such as Bacilli, relying exclusively on these two enzymes. The occurrence of fusion proteins, alternate arrangements of biosynthetic components, and loss of biosynthetic branches provide examples of biosynthetic diversity to retain a conserved tRNA modification in nature.

Importance

The xnm 5 s 2 U modifications found in several tRNAs at the wobble base position are widespread in Bacteria where they have an important role in decoding efficiency and accuracy. This work identifies a novel enzyme (MnmL) that is a member of a subgroup of the very versatile Radical SAM superfamily and is involved in the synthesis of mnm 5 s 2 U in several Gram-positive bacteria, including human pathogens. This is another novel example of a non-orthologous displacement in the field of tRNA modification synthesis, showing how different solutions evolve to retain U34 tRNA modifications.

Survey and Validation of tRNA Modifications and Their Corresponding Genes in Bacillus subtilis sp Subtilis Strain 168

Extensive knowledge of both the nature and position of tRNA modifications in all cellular tRNAs has been limited to two bacteria, Escherichia coli and Mycoplasma capricolum. Bacillus subtilis sp subtilis strain 168 is the model Gram-positive bacteria and the list of the genes involved in tRNA modifications in this organism is far from complete. Mass spectrometry analysis of bulk tRNA extracted from B. subtilis, combined with next generation sequencing technologies and comparative genomic analyses, led to the identification of 41 tRNA modification genes with associated confidence scores. Many differences were found in this model Gram-positive bacteria when compared to E. coli. In general, B. subtilis tRNAs are less modified than those in E. coli, even if some modifications, such as m1A22 or ms2t6A, are only found in the model Gram-positive bacteria. Many examples of non-orthologous displacements and of variations in the most complex pathways are described. Paralog issues make uncertain direct annotation transfer from E. coli to B. subtilis based on homology only without further experimental validation. This difficulty was shown with the identification of the B. subtilis enzyme that introduces ψ at positions 31/32 of the tRNAs. This work presents the most up to date list of tRNA modification genes in B. subtilis, identifies the gaps in knowledge, and lays the foundation for further work to decipher the physiological role of tRNA modifications in this important model organism and other bacteria.

SubtiWiki in 2018: from genes and proteins to functional network annotation of the model organism Bacillus subtilis

Living cells are made up of individual parts, i.e. the genome, the proteins, the RNA and lipid molecules as well as the metabolites and ions. However, life depends on the functional interaction among these components which is often organized in networks. Here, we present the recent development of SubtiWiki, the integrated database for the model bacterium Bacillus subtilis (http://subtiwiki.uni-goettingen.de/). SubtiWiki is based on a relational database and provides access to published information about the genes and proteins of B. subtilis and about metabolic and regulatory pathways. We have included a network visualization tool that can be used to visualize regulatory as well as protein-protein interaction networks. The resulting interactive graphical presentations allow the user to detect novel associations and thus to develop novel hypotheses that can then be tested experimentally. To facilitate the mobile use of SubtiWiki, we provide enhanced versions of the SubtiWiki App that are available for iOS and Android devices. Importantly, the App allows to link private notes and pictures to the gene/protein pages that can be synchronized on multiple devices. SubtiWiki has become one of the most complete resources of knowledge on a living organism.

Listeriomics: an Interactive Web Platform for Systems Biology of Listeria

In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.

As for many model organisms, the amount of Listeria omics data produced has recently increased exponentially. There are now >80 published complete Listeria genomes, around 350 different transcriptomic data sets, and 25 proteomic data sets available. The analysis of these data sets through a systems biology approach and the generation of tools for biologists to browse these various data are a challenge for bioinformaticians. We have developed a web-based platform, named Listeriomics, that integrates different tools for omics data analyses, i.e., (i) an interactive genome viewer to display gene expression arrays, tiling arrays, and sequencing data sets along with proteomics and genomics data sets; (ii) an expression and protein atlas that connects every gene, small RNA, antisense RNA, or protein with the most relevant omics data; (iii) a specific tool for exploring protein conservation through the Listeria phylogenomic tree; and (iv) a coexpression network tool for the discovery of potential new regulations. Our platform integrates all the complete Listeria species genomes, transcriptomes, and proteomes published to date. This website allows navigation among all these data sets with enriched metadata in a user-friendly format and can be used as a central database for systems biology analysis.

IMPORTANCE In the last decades, Listeria has become a key model organism for the study of host-pathogen interactions, noncoding RNA regulation, and bacterial adaptation to stress. To study these mechanisms, several genomics, transcriptomics, and proteomics data sets have been produced. We have developed Listeriomics, an interactive web platform to browse and correlate these heterogeneous sources of information. Our website will allow listeriologists and microbiologists to decipher key regulation mechanism by using a systems biology approach.

Linking Bacillus cereus Genotypes and Carbohydrate Utilization Capacity

We characterised carbohydrate utilisation of 20 newly sequenced Bacillus cereus strains isolated from food products and food processing environments and two laboratory strains, B. cereus ATCC 10987 and B. cereus ATCC 14579. Subsequently, genome sequences of these strains were analysed together with 11 additional B. cereus reference genomes to provide an overview of the different types of carbohydrate transporters and utilization systems found in B. cereus strains. The combined application of API tests, defined growth media experiments and comparative genomics enabled us to link the carbohydrate utilisation capacity of 22 B. cereus strains with their genome content and in some cases to the panC phylogenetic grouping. A core set of carbohydrates including glucose, fructose, maltose, trehalose, N-acetyl-glucosamine, and ribose could be used by all strains, whereas utilisation of other carbohydrates like xylose, galactose, and lactose, and typical host-derived carbohydrates such as fucose, mannose, N-acetyl-galactosamine and inositol is limited to a subset of strains. Finally, the roles of selected carbohydrate transporters and utilisation systems in specific niches such as soil, foods and the human host are discussed.

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

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.

Reconstruction of gene networks using prior knowledge

Background

Reconstructing gene regulatory networks (GRNs) from expression data is a challenging task that has become essential to the understanding of complex regulatory mechanisms in cells. The major issues are the usually very high ratio of number of genes to sample size, and the noise in the available data. Integrating biological prior knowledge to the learning process is a natural and promising way to partially compensate for the lack of reliable expression data and to increase the accuracy of network reconstruction algorithms.

Results

In this manuscript, we present PriorPC, a new algorithm based on the PC algorithm. PC algorithm is one of the most popular methods for Bayesian network reconstruction. The result of PC is known to depend on the order in which conditional independence tests are processed, especially for large networks. PriorPC uses prior knowledge to exclude unlikely edges from network estimation and introduces a particular ordering for the conditional independence tests. We show on synthetic data that the structural accuracy of networks obtained with PriorPC is greatly improved compared to PC.

Conclusion

PriorPC improves structural accuracy of inferred gene networks by using soft priors which assign to edges a probability of existence. It is robust to false prior which is not avoidable in the context of biological data. PriorPC is also fast and scales well for large networks which is important for its applicability to real data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0233-4) contains supplementary material, which is available to authorized users.

Transcriptional Profile of Bacillus subtilis sigF-Mutant during Vegetative Growth

Sigma factor F is the first forespore specific transcription factor in Bacillus subtilis and controls genes required for the early stages of prespore development. The role of sigF is well studied under conditions that induce sporulation. Here, the impact of sigF disruption on the transcriptome of exponentially growing cultures is studied by micro-array analysis. Under these conditions that typically don’t induce sporulation, the transcriptome showed minor signs of sporulation initiation. The number of genes differentially expressed and the magnitude of expression were, as expected, quite small in comparison with sporulation conditions. The genes mildly down-regulated were mostly involved in anabolism and the genes mildly up-regulated, in particular fatty acid degradation genes, were mostly involved in catabolism. This is probably related to the arrest at sporulation stage II occurring in the sigF mutant, because continuation of growth from the formed disporic sporangia may require additional energy. The obtained knowledge is relevant for various experiments, such as industrial fermentation, prolonged experimental evolution or zero-growth studies, where sporulation is an undesirable trait that should be avoided, e.g by a sigF mutation.

Physiological and cell morphology adaptation of Bacillus subtilis at near-zero specific growth rates: a transcriptome analysis

Nutrient scarcity is a common condition in nature, but the resulting extremely low growth rates (below 0.025 h(-1) ) are an unexplored research area in Bacillus subtilis. To understand microbial life in natural environments, studying the adaptation of B. subtilis to near-zero growth conditions is relevant. To this end, a chemostat modified for culturing an asporogenous B. subtilis sigF mutant strain at extremely low growth rates (also named a retentostat) was set up, and biomass accumulation, culture viability, metabolite production and cell morphology were analysed. During retentostat culturing, the specific growth rate decreased to a minimum of 0.00006 h(-1) , corresponding to a doubling time of 470 days. The energy distribution between growth and maintenance-related processes showed that a state of near-zero growth was reached. Remarkably, a filamentous cell morphology emerged, suggesting that cell separation is impaired under near-zero growth conditions. To evaluate the corresponding molecular adaptations to extremely low specific growth, transcriptome changes were analysed. These revealed that cellular responses to near-zero growth conditions share several similarities with those of cells during the stationary phase of batch growth. However, fundamental differences between these two non-growing states are apparent by their high viability and absence of stationary phase mutagenesis under near-zero growth conditions.

Bacillus subtilis Systems Biology: Applications of -Omics Techniques to the Study of Endospore Formation

Endospore-forming bacteria, with Bacillus subtilis being the prevalent model organism, belong to the phylum Firmicutes. Although the last common ancestor of all Firmicutes is likely to have been an endospore-forming species, not every lineage in the phylum has maintained the ability to produce endospores (hereafter, spores). In 1997, the release of the full genome sequence for B. subtilis strain 168 marked the beginning of the genomic era for the study of spore formation (sporulation). In this original genome sequence, 139 of the 4,100 protein-coding genes were annotated as sporulation genes. By the time a revised genome sequence with updated annotations was published in 2009, that number had increased significantly, especially since transcriptional profiling studies (transcriptomics) led to the identification of several genes expressed under the control of known sporulation transcription factors. Over the past decade, genome sequences for multiple spore-forming species have been released (including several strains in the Bacillus anthracis / Bacillus cereus group and many Clostridium species), and phylogenomic analyses have revealed many conserved sporulation genes. Parallel advances in transcriptomics led to the identification of small untranslated regulatory RNAs (sRNAs), including some that are expressed during sporulation. An extended array of -omics techniques, i.e., techniques designed to probe gene function on a genome-wide scale, such as proteomics, metabolomics, and high-throughput protein localization studies, have been implemented in microbiology. Combined with the use of new computational methods for predicting gene function and inferring regulatory relationships on a global scale, these -omics approaches are uncovering novel information about sporulation and a variety of other bacterial cell processes.

SubtiWiki-a database for the model organism Bacillus subtilis that links pathway, interaction and expression information

Genome annotation and access to information from large-scale experimental approaches at the genome level are essential to improve our understanding of living cells and organisms. This is even more the case for model organisms that are the basis to study pathogens and technologically important species. We have generated SubtiWiki, a database for the Gram-positive model bacterium Bacillus subtilis (http://subtiwiki.uni-goettingen.de/). In addition to the established companion modules of SubtiWiki, SubtiPathways and SubtInteract, we have now created SubtiExpress, a third module, to visualize genome scale transcription data that are of unprecedented quality and density. Today, SubtiWiki is one of the most complete collections of knowledge on a living organism in one single resource.

Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks

MOTIVATION

Inferring global regulatory networks (GRNs) from genome-wide data is a computational challenge central to the field of systems biology. Although the primary data currently used to infer GRNs consist of gene expression and proteomics measurements, there is a growing abundance of alternate data types that can reveal regulatory interactions, e.g. ChIP-Chip, literature-derived interactions, protein-protein interactions. GRN inference requires the development of integrative methods capable of using these alternate data as priors on the GRN structure. Each source of structure priors has its unique biases and inherent potential errors; thus, GRN methods using these data must be robust to noisy inputs.

RESULTS

We developed two methods for incorporating structure priors into GRN inference. Both methods [Modified Elastic Net (MEN) and Bayesian Best Subset Regression (BBSR)] extend the previously described Inferelator framework, enabling the use of prior information. We test our methods on one synthetic and two bacterial datasets, and show that both MEN and BBSR infer accurate GRNs even when the structure prior used has significant amounts of error (>90% erroneous interactions). We find that BBSR outperforms MEN at inferring GRNs from expression data and noisy structure priors.

AVAILABILITY AND IMPLEMENTATION

Code, datasets and networks presented in this article are available at http://bonneaulab.bio.nyu.edu/software.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Definition of the σ(W) regulon of Bacillus subtilis in the absence of stress

Bacteria employ extracytoplasmic function (ECF) sigma factors for their responses to environmental stresses. Despite intensive research, the molecular dissection of ECF sigma factor regulons has remained a major challenge due to overlaps in the ECF sigma factor-regulated genes and the stimuli that activate the different ECF sigma factors. Here we have employed tiling arrays to single out the ECF σ^W regulon of the Gram-positive bacterium Bacillus subtilis from the overlapping ECF σ^X, σ^Y, and σ^M regulons. For this purpose, we profiled the transcriptome of a B. subtilis sigW mutant under non-stress conditions to select candidate genes that are strictly σ^W-regulated. Under these conditions, σ^W exhibits a basal level of activity. Subsequently, we verified the σ^W-dependency of candidate genes by comparing their transcript profiles to transcriptome data obtained with the parental B. subtilis strain 168 grown under 104 different conditions, including relevant stress conditions, such as salt shock. In addition, we investigated the transcriptomes of rasP or prsW mutant strains that lack the proteases involved in the degradation of the σ^W anti-sigma factor RsiW and subsequent activation of the σ^W-regulon. Taken together, our studies identify 89 genes as being strictly σ^W-regulated, including several genes for non-coding RNAs. The effects of rasP or prsW mutations on the expression of σ^W-dependent genes were relatively mild, which implies that σ^W-dependent transcription under non-stress conditions is not strictly related to RasP and PrsW. Lastly, we show that the pleiotropic phenotype of rasP mutant cells, which have defects in competence development, protein secretion and membrane protein production, is not mirrored in the transcript profile of these cells. This implies that RasP is not only important for transcriptional regulation via σ^W, but that this membrane protease also exerts other important post-transcriptional regulatory functions.

BioNLP Shared Task--The Bacteria Track

BACKGROUND

We present the BioNLP 2011 Shared Task Bacteria Track, the first Information Extraction challenge entirely dedicated to bacteria. It includes three tasks that cover different levels of biological knowledge. The Bacteria Gene Renaming supporting task is aimed at extracting gene renaming and gene name synonymy in PubMed abstracts. The Bacteria Gene Interaction is a gene/protein interaction extraction task from individual sentences. The interactions have been categorized into ten different sub-types, thus giving a detailed account of genetic regulations at the molecular level. Finally, the Bacteria Biotopes task focuses on the localization and environment of bacteria mentioned in textbook articles. We describe the process of creation for the three corpora, including document acquisition and manual annotation, as well as the metrics used to evaluate the participants' submissions.

RESULTS

Three teams submitted to the Bacteria Gene Renaming task; the best team achieved an F-score of 87%. For the Bacteria Gene Interaction task, the only participant's score had reached a global F-score of 77%, although the system efficiency varies significantly from one sub-type to another. Three teams submitted to the Bacteria Biotopes task with very different approaches; the best team achieved an F-score of 45%. However, the detailed study of the participating systems efficiency reveals the strengths and weaknesses of each participating system.

CONCLUSIONS

The three tasks of the Bacteria Track offer participants a chance to address a wide range of issues in Information Extraction, including entity recognition, semantic typing and coreference resolution. We found common trends in the most efficient systems: the systematic use of syntactic dependencies and machine learning. Nevertheless, the originality of the Bacteria Biotopes task encouraged the use of interesting novel methods and techniques, such as term compositionality, scopes wider than the sentence.

Linking genes to diseases with a SNPedia-Gene Wiki mashup

Background

A variety of topic-focused wikis are used in the biomedical sciences to enable the mass-collaborative synthesis and distribution of diverse bodies of knowledge. To address complex problems such as defining the relationships between genes and disease, it is important to bring the knowledge from many different domains together. Here we show how advances in wiki technology and natural language processing can be used to automatically assemble ‘meta-wikis’ that present integrated views over the data collaboratively created in multiple source wikis.

Results

We produced a semantic meta-wiki called the Gene Wiki+ that automatically mirrors and integrates data from the Gene Wiki and SNPedia. The Gene Wiki+, available at (http://genewikiplus.org/), captures 8,047 distinct gene-disease relationships. SNPedia accounts for 4,149 of the gene-disease pairs, the Gene Wiki provides 4,377 and only 479 appear independently in both sources. All of this content is available to query and browse and is provided as linked open data.

Conclusions

Wikis contain increasing amounts of diverse, biological information useful for elucidating the connections between genes and disease. The Gene Wiki+ shows how wiki technology can be used in concert with natural language processing to provide integrated views over diverse underlying data sources.

Comparative analysis of gene content evolution in phytoplasmas and mycoplasmas

Phytoplasmas and mycoplasmas are two groups of important pathogens in the bacterial class Mollicutes. Because of their economical and clinical importance, these obligate pathogens have attracted much research attention. However, difficulties involved in the empirical study of these bacteria, particularly the fact that phytoplasmas have not yet been successfully cultivated outside of their hosts despite decades of attempts, have greatly hampered research progress. With the rapid advancements in genome sequencing, comparative genome analysis provides a new approach to facilitate our understanding of these bacteria. In this study, our main focus is to investigate the evolution of gene content in phytoplasmas, mycoplasmas, and their common ancestor. By using a phylogenetic framework for comparative analysis of 12 complete genome sequences, we characterized the putative gains and losses of genes in these obligate parasites. Our results demonstrated that the degradation of metabolic capacities in these bacteria has occurred predominantly in the common ancestor of Mollicutes, prior to the evolutionary split of phytoplasmas and mycoplasmas. Furthermore, we identified a list of genes that are acquired by the common ancestor of phytoplasmas and are conserved across all strains with complete genome sequences available. These genes include several putative effectors for the interactions with hosts and may be good candidates for future functional characterization.

Defining the structure of the general stress regulon of Bacillus subtilis using targeted microarray analysis and random forest classification

The structure of the SigB-dependent general stress regulon of Bacillus subtilis has previously been characterized by proteomics approaches as well as DNA array-based expression studies. However, comparing the SigB targets published in three previous major transcriptional profiling studies it is obvious that although each of them identified well above 100 target genes, only 67 were identified in all three studies. These substantial differences can likely be attributed to the different strains, growth conditions, microarray platforms and experimental setups used in the studies. In order to gain a better understanding of the structure of this important regulon, a targeted DNA microarray analysis covering most of the known SigB-inducing conditions was performed, and the changes in expression kinetics of 252 potential members of the SigB regulon and appropriate control genes were recorded. Transcriptional data for the B. subtilis wild-type strain 168 and its isogenic sigB mutant BSM29 were analysed using random forest, a machine learning algorithm, by incorporating the knowledge from previous studies. This analysis revealed a strictly SigB-dependent expression pattern for 166 genes following ethanol, butanol, osmotic and oxidative stress, low-temperature growth and heat shock, as well as limitation of oxygen or glucose. Kinetic analysis of the data for the wild-type strain identified 30 additional members of the SigB regulon, which were also subject to control by additional transcriptional regulators, thus displaying atypical SigB-independent induction patterns in the mutant strain under some of the conditions tested. For 19 of these 30 SigB regulon members, published reports support control by secondary regulators along with SigB. Thus, this microarray-based study assigns a total of 196 genes to the SigB-dependent general stress regulon of B. subtilis.

Mining the Gene Wiki for functional genomic knowledge

Background

Ontology-based gene annotations are important tools for organizing and analyzing genome-scale biological data. Collecting these annotations is a valuable but costly endeavor. The Gene Wiki makes use of Wikipedia as a low-cost, mass-collaborative platform for assembling text-based gene annotations. The Gene Wiki is comprised of more than 10,000 review articles, each describing one human gene. The goal of this study is to define and assess a computational strategy for translating the text of Gene Wiki articles into ontology-based gene annotations. We specifically explore the generation of structured annotations using the Gene Ontology and the Human Disease Ontology.

Results

Our system produced 2,983 candidate gene annotations using the Disease Ontology and 11,022 candidate annotations using the Gene Ontology from the text of the Gene Wiki. Based on manual evaluations and comparisons to reference annotation sets, we estimate a precision of 90-93% for the Disease Ontology annotations and 48-64% for the Gene Ontology annotations. We further demonstrate that this data set can systematically improve the results from gene set enrichment analyses.

Conclusions

The Gene Wiki is a rapidly growing corpus of text focused on human gene function. Here, we demonstrate that the Gene Wiki can be a powerful resource for generating ontology-based gene annotations. These annotations can be used immediately to improve workflows for building curated gene annotation databases and knowledge-based statistical analyses.

GONUTS: the Gene Ontology Normal Usage Tracking System

The Gene Ontology Normal Usage Tracking System (GONUTS) is a community-based browser and usage guide for Gene Ontology (GO) terms and a community system for general GO annotation of proteins. GONUTS uses wiki technology to allow registered users to share and edit notes on the use of each term in GO, and to contribute annotations for specific genes of interest. By providing a site for generation of third-party documentation at the granularity of individual terms, GONUTS complements the official documentation of the Gene Ontology Consortium. To provide examples for community users, GONUTS displays the complete GO annotations from seven model organisms: Saccharomyces cerevisiae, Dictyostelium discoideum, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Mus musculus and Arabidopsis thaliana. To support community annotation, GONUTS allows automated creation of gene pages for gene products in UniProt. GONUTS will improve the consistency of annotation efforts across genome projects, and should be useful in training new annotators and consumers in the production of GO annotations and the use of GO terms. GONUTS can be accessed at http://gowiki.tamu.edu. The source code for generating the content of GONUTS is available upon request.

SubtiWiki--a comprehensive community resource for the model organism Bacillus subtilis

In the post-genomic era, most components of a cell are known and they can be quantified by large-scale functional genomics approaches. However, genome annotation is the bottleneck that hampers our understanding of living cells and organisms. Up-to-date functional annotation is of special importance for model organisms that provide a frame of reference for studies with other relevant organisms. We have generated a Wiki-type database for the Gram-positive model bacterium Bacillus subtilis, SubtiWiki (http://subtiwiki.uni-goettingen.de/). This Wiki is centered around the individual genes and gene products of B. subtilis and provides information on each aspect of gene function and expression as well as protein activity and its control. SubtiWiki is accompanied by two companion databases SubtiPathways and SubtInteract that provide graphical representations of B. subtilis metabolism and its regulation and of protein-protein interactions, respectively. The diagrams of both databases are easily navigatable using the popular Google maps API, and they are extensively linked with the SubtiWiki gene pages. Moreover, each gene/gene product was assigned to one or more functional categories and transcription factor regulons. Pages for the specific categories and regulons provide a rapid overview of functionally related genes/proteins. Today, SubtiWiki can be regarded as one of the most complete inventories of knowledge on a living organism in one single resource.

EcoliWiki: a wiki-based community resource for Escherichia coli

EcoliWiki is the community annotation component of the PortEco (http://porteco.org; formerly EcoliHub) project, an online data resource that integrates information on laboratory strains of Escherichia coli, its phages, plasmids and mobile genetic elements. As one of the early adopters of the wiki approach to model organism databases, EcoliWiki was designed to not only facilitate community-driven sharing of biological knowledge about E. coli as a model organism, but also to be interoperable with other data resources. EcoliWiki content currently covers genes from five laboratory E. coli strains, 21 bacteriophage genomes, F plasmid and eight transposons. EcoliWiki integrates the Mediawiki wiki platform with other open-source software tools and in-house software development to extend how wikis can be used for model organism databases. EcoliWiki can be accessed online at http://ecoliwiki.net.

Systems-wide temporal proteomic profiling in glucose-starved Bacillus subtilis

Functional genomics of the Gram-positive model organism Bacillus subtilis reveals valuable insights into basic concepts of cell physiology. In this study, we monitor temporal changes in the proteome, transcriptome and extracellular metabolome of B. subtilis caused by glucose starvation. For proteomic profiling, a combination of in vivo metabolic labelling and shotgun mass spectrometric analysis was carried out for five different proteomic subfractions (cytosolic, integral membrane, membrane, surface and extracellular proteome fraction), leading to the identification of ∼52% of the predicted proteome of B. subtilis. Quantitative proteomic and corresponding transcriptomic data were analysed with Voronoi treemaps linking functional classification and relative expression changes of gene products according to their fate in the stationary phase. The obtained data comprise the first comprehensive profiling of changes in the membrane subfraction and allow in-depth analysis of major physiological processes, including monitoring of protein degradation.

Identifying the transcripts and proteins that fluctuate in response to stimuli provides important information for understanding cell physiology. In this study, 52% of the Bacillus subtilis predicted proteome is identified following glucose starvation, revealing further insight into protein dynamics at a global scale.

Hierarchical evolution of the bacterial sporulation network

Genome sequencing of multiple species makes it possible to understand the main principles behind the evolution of developmental regulatory networks. It is especially interesting to analyze the evolution of well-defined model systems in which conservation patterns can be directly correlated with the functional roles of various network components. Endospore formation (sporulation), extensively studied in Bacillus subtilis, is driven by such a model bacterial network of cellular development and differentiation. In this review, we analyze the evolution of the sporulation network in multiple endospore-forming bacteria. Importantly, the network evolution is not random but primarily follows the hierarchical organization and functional logic of the sporulation process. Specifically, the sporulation sigma factors and the master regulator of sporulation, Spo0A, are conserved in all considered spore-formers. The sequential activation of these global regulators is also strongly conserved. The feed-forward loops, which are likely used to fine-tune waves of gene expression within regulatory modules, show an intermediate level of conservation. These loops are less conserved than the sigma factors but significantly more than the structural sporulation genes, which form the lowest level in the functional and evolutionary hierarchy of the sporulation network. Interestingly, in spore-forming bacteria, gene regulation is more conserved than gene presence for sporulation genes, while the opposite is true for non-sporulation genes. The observed patterns suggest that, by understanding the functional organization of a developmental network in a model organism, it is possible to understand the logic behind the evolution of this network in multiple related species.

A proteomic and transcriptional view of acidogenic and solventogenic steady-state cells of Clostridium acetobutylicum in a chemostat culture

The complex changes in the life cycle of Clostridium acetobutylicum, a promising biofuel producer, are not well understood. During exponential growth, sugars are fermented to acetate and butyrate, and in the transition phase, the metabolism switches to the production of the solvents acetone and butanol accompanied by the initiation of endospore formation. Using phosphate-limited chemostat cultures at pH 5.7, C. acetobutylicum was kept at a steady state of acidogenic metabolism, whereas at pH 4.5, the cells showed stable solvent production without sporulation. Novel proteome reference maps of cytosolic proteins from both acidogenesis and solventogenesis with a high degree of reproducibility were generated. Yielding a 21% coverage, 15 protein spots were specifically assigned to the acidogenic phase, and 29 protein spots exhibited a significantly higher abundance in the solventogenic phase. Besides well-known metabolic proteins, unexpected proteins were also identified. Among these, the two proteins CAP0036 and CAP0037 of unknown function were found as major striking indicator proteins in acidogenic cells. Proteome data were confirmed by genome-wide DNA microarray analyses of the identical cultures. Thus, a first systematic study of acidogenic and solventogenic chemostat cultures is presented, and similarities as well as differences to previous studies of batch cultures are discussed.

Copper stress affects iron homeostasis by destabilizing iron-sulfur cluster formation in Bacillus subtilis

Copper and iron are essential elements for cellular growth. Although bacteria have to overcome limitations of these metals by affine and selective uptake, excessive amounts of both metals are toxic for the cells. Here we investigated the influences of copper stress on iron homeostasis in Bacillus subtilis, and we present evidence that copper excess leads to imbalances of intracellular iron metabolism by disturbing assembly of iron-sulfur cofactors. Connections between copper and iron homeostasis were initially observed in microarray studies showing upregulation of Fur-dependent genes under conditions of copper excess. This effect was found to be relieved in a csoR mutant showing constitutive copper efflux. In contrast, stronger Fur-dependent gene induction was found in a copper efflux-deficient copA mutant. A significant induction of the PerR regulon was not observed under copper stress, indicating that oxidative stress did not play a major role under these conditions. Intracellular iron and copper quantification revealed that the total iron content was stable during different states of copper excess or efflux and hence that global iron limitation did not account for copper-dependent Fur derepression. Strikingly, the microarray data for copper stress revealed a broad effect on the expression of genes coding for iron-sulfur cluster biogenesis (suf genes) and associated pathways such as cysteine biosynthesis and genes coding for iron-sulfur cluster proteins. Since these effects suggested an interaction of copper and iron-sulfur cluster maturation, a mutant with a conditional mutation of sufU, encoding the essential iron-sulfur scaffold protein in B. subtilis, was assayed for copper sensitivity, and its growth was found to be highly susceptible to copper stress. Further, different intracellular levels of SufU were found to influence the strength of Fur-dependent gene expression. By investigating the influence of copper on cluster-loaded SufU in vitro, Cu(I) was found to destabilize the scaffolded cluster at submicromolar concentrations. Thus, by interfering with iron-sulfur cluster formation, copper stress leads to enhanced expression of cluster scaffold and target proteins as well as iron and sulfur acquisition pathways, suggesting a possible feedback strategy to reestablish cluster biogenesis.

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.