neo4jsbml: import systems biology markup language data into the graph database Neo4j.

Systems Biology Markup Language (SBML) has emerged as a standard for representing biological models, facilitating model sharing and interoperability. It stores many types of data and complex relationships, complicating data management and analysis. Traditional database management systems struggle to effectively capture these complex networks of interactions within biological systems. Graph-oriented databases perform well in managing interactions between different entities. We present neo4jsbml, a new solution that bridges the gap between the Systems Biology Markup Language data and the Neo4j database, for storing, querying and analyzing data. The Systems Biology Markup Language organizes biological entities in a hierarchical structure, reflecting their interdependencies. The inherent graphical structure represents these hierarchical relationships, offering a natural and efficient means of navigating and exploring the model's components. Neo4j is an excellent solution for handling this type of data. By representing entities as nodes and their relationships as edges, Cypher, Neo4j's query language, efficiently traverses this type of graph representing complex biological networks. We have developed neo4jsbml, a Python library for importing Systems Biology Markup Language data into a Neo4j database using a user-defined schema. By leveraging Neo4j's graphical database technology, exploration of complex biological networks becomes intuitive and information retrieval efficient. Neo4jsbml is a tool designed to import Systems Biology Markup Language data into a Neo4j database. Only the desired data is loaded into the Neo4j database. neo4jsbml is user-friendly and can become a useful new companion for visualizing and analyzing metabolic models through the Neo4j graphical database. neo4jsbml is open source software and available at https://github.com/brsynth/neo4jsbml.

Direct comparison of spatial transcriptional heterogeneity across diverse Bacillus subtilis biofilm communities.

Bacillus subtilis can form various types of spatially organised communities on surfaces, such as colonies, pellicles and submerged biofilms. These communities share similarities and differences, and phenotypic heterogeneity has been reported for each type of community. Here, we studied spatial transcriptional heterogeneity across the three types of surface-associated communities. Using RNA-seq analysis of different regions or populations for each community type, we identified genes that are specifically expressed within each selected population. We constructed fluorescent transcriptional fusions for 17 of these genes, and observed their expression in submerged biofilms using time-lapse confocal laser scanning microscopy (CLSM). We found mosaic expression patterns for some genes; in particular, we observed spatially segregated cells displaying opposite regulation of carbon metabolism genes (gapA and gapB), indicative of distinct glycolytic or gluconeogenic regimes coexisting in the same biofilm region. Overall, our study provides a direct comparison of spatial transcriptional heterogeneity, at different scales, for the three main models of B. subtilis surface-associated communities.

Greedy reduction of Bacillus subtilis genome yields emergent phenotypes of high resistance to a DNA damaging agent and low evolvability.

Genome-scale engineering enables rational removal of dispensable genes in chassis genomes. Deviating from this approach, we applied greedy accumulation of deletions of large dispensable regions in the Bacillus subtilis genome, yielding a library of 298 strains with genomes reduced up to 1.48 Mb in size. High-throughput physiological phenotyping of these strains confirmed that genome reduction is associated with substantial loss of cell fitness and accumulation of synthetic-sick interactions. Transcriptome analysis indicated that <15% of the genes conserved in our genome-reduced strains exhibited a twofold or higher differential expression and revealed a thiol-oxidative stress response. Most transcriptional changes can be explained by loss of known functions and by aberrant transcription at deletion boundaries. Genome-reduced strains exhibited striking new phenotypes relative to wild type, including a very high resistance (increased >300-fold) to the DNA-damaging agent mitomycin C and a very low spontaneous mutagenesis (reduced 100-fold). Adaptive laboratory evolution failed to restore cell fitness, except when coupled with a synthetic increase of the mutation rate, confirming low evolvability. Although mechanisms underlying this emergent phenotype are not understood, we propose that low evolvability can be leveraged in an engineering strategy coupling reductive cycles with evolutive cycles under induced mutagenesis.

Termination factor Rho mediates transcriptional reprogramming of Bacillus subtilis stationary phase.

Transcription termination factor Rho is known for its ubiquitous role in suppression of pervasive, mostly antisense, transcription. In the model Gram-positive bacterium Bacillus subtilis, de-repression of pervasive transcription by inactivation of rho revealed the role of Rho in the regulation of post-exponential differentiation programs. To identify other aspects of the regulatory role of Rho during adaptation to starvation, we have constructed a B. subtilis strain (Rho+) that expresses rho at a relatively stable high level in order to compensate for its decrease in the wild-type cells entering stationary phase. The RNAseq analysis of Rho+, WT and Δrho strains (expression profiles can be visualized at http://genoscapist.migale.inrae.fr/seb_rho/) shows that Rho over-production enhances the termination efficiency of Rho-sensitive terminators, thus reducing transcriptional read-through and antisense transcription genome-wide. Moreover, the Rho+ strain exhibits global alterations of sense transcription with the most significant changes observed for the AbrB, CodY, and stringent response regulons, forming the pathways governing the transition to stationary phase. Subsequent physiological analyses demonstrated that maintaining rho expression at a stable elevated level modifies stationary phase-specific physiology of B. subtilis cells, weakens stringent response, and thereby negatively affects the cellular adaptation to nutrient limitations and other stresses, and blocks the development of genetic competence and sporulation. These results highlight the Rho-specific termination of transcription as a novel element controlling stationary phase. The release of this control by decreasing Rho levels during the transition to stationary phase appears crucial for the functionality of complex gene networks ensuring B. subtilis survival in stationary phase.

Omnicrobe, an open-access database of microbial habitats and phenotypes using a comprehensive text mining and data fusion approach.

The dramatic increase in the number of microbe descriptions in databases, reports, and papers presents a two-fold challenge for accessing the information: integration of heterogeneous data in a standard ontology-based representation and normalization of the textual descriptions by semantic analysis. Recent text mining methods offer powerful ways to extract textual information and generate ontology-based representation. This paper describes the design of the Omnicrobe application that gathers comprehensive information on habitats, phenotypes, and usages of microbes from scientific sources of high interest to the microbiology community. The Omnicrobe database contains around 1 million descriptions of microbe properties. These descriptions are created by analyzing and combining six information sources of various kinds, i.e. biological resource catalogs, sequence databases and scientific literature. The microbe properties are indexed by the Ontobiotope ontology and their taxa are indexed by an extended version of the taxonomy maintained by the National Center for Biotechnology Information. The Omnicrobe application covers all domains of microbiology. With simple or rich ontology-based queries, it provides easy-to-use support in the resolution of scientific questions related to the habitats, phenotypes, and uses of microbes. We illustrate the potential of Omnicrobe with a use case from the food innovation domain.

Genoscapist: online exploration of quantitative profiles along genomes via interactively customized graphical representations.

SUMMARY: Genoscapist is a tool to design web interfaces generating high-quality images for interactive visualization of hundreds of quantitative profiles along a reference genome together with various annotations. Relevance is demonstrated by deployment of two websites dedicated to large condition-dependent transcriptome datasets available for Bacillus subtilis and Staphylococcus aureus. AVAILABILITY AND IMPLEMENTATION: Websites and source code freely accessible at https://genoscapist.migale.inrae.fr.

Staphylococcus aureus Transcriptome Architecture: From Laboratory to Infection-Mimicking Conditions.

Staphylococcus aureus is a major pathogen that colonizes about 20% of the human population. Intriguingly, this Gram-positive bacterium can survive and thrive under a wide range of different conditions, both inside and outside the human body. Here, we investigated the transcriptional adaptation of S. aureus HG001, a derivative of strain NCTC 8325, across experimental conditions ranging from optimal growth in vitro to intracellular growth in host cells. These data establish an extensive repertoire of transcription units and non-coding RNAs, a classification of 1412 promoters according to their dependence on the RNA polymerase sigma factors SigA or SigB, and allow identification of new potential targets for several known transcription factors. In particular, this study revealed a relatively low abundance of antisense RNAs in S. aureus, where they overlap only 6% of the coding genes, and only 19 antisense RNAs not co-transcribed with other genes were found. Promoter analysis and comparison with Bacillus subtilis links the small number of antisense RNAs to a less profound impact of alternative sigma factors in S. aureus. Furthermore, we revealed that Rho-dependent transcription termination suppresses pervasive antisense transcription, presumably originating from abundant spurious transcription initiation in this A+T-rich genome, which would otherwise affect expression of the overlapped genes. In summary, our study provides genome-wide information on transcriptional regulation and non-coding RNAs in S. aureus as well as new insights into the biological function of Rho and the implications of spurious transcription in bacteria.

Technical challenges in metatranscriptomic studies applied to the bacterial communities of freshwater ecosystems.

Metatranscriptome analysis relates to the transcriptome of microbial communities directly sampled in the environment. Accessing the mRNA pool in natural bacterial communities presents some technical challenges such as the RNA extraction, rRNA depletion, and the choice of the high-throughput sequencing technique. The lack of technical details in scientific articles is a major problem to correctly obtained mRNA from a microbial community and thus the corresponding sequencing data. In our study, we present the methodological procedure that was developed in order to access to the metatranscriptome of the microbial communities during two cyanobacterial blooms successively occurring in a freshwater eutrophic lake. Each procedure step was detailed and discussed with regard to the choices and difficulties encountered and to the recent literature. Finally, the two major limits for metatranscriptomic approaches targeting bacterial communities from natural environments were (i) the removal of rRNA in order to increase the putative mRNA reads number after sequencing, and (ii) for most of the bacterial communities living in natural environments, the lack of reference genomes in databases that leads to the non-assignation of numerous reads. Once these challenges overcome, we managed to access putative mRNA of dominant species, i.e. cyanobacteria (from 6 to 72 % of mRNA assigned), and of the surrounding bacteria (from 1 to 5 % of mRNA assigned).

Integrative epigenomic mapping defines four main chromatin states in Arabidopsis.

Post-translational modification of histones and DNA methylation are important components of chromatin-level control of genome activity in eukaryotes. However, principles governing the combinatorial association of chromatin marks along the genome remain poorly understood. Here, we have generated epigenomic maps for eight histone modifications (H3K4me2 and 3, H3K27me1 and 2, H3K36me3, H3K56ac, H4K20me1 and H2Bub) in the model plant Arabidopsis and we have combined these maps with others, produced under identical conditions, for H3K9me2, H3K9me3, H3K27me3 and DNA methylation. Integrative analysis indicates that these 12 chromatin marks, which collectively cover ∼90% of the genome, are present at any given position in a very limited number of combinations. Moreover, we show that the distribution of the 12 marks along the genomic sequence defines four main chromatin states, which preferentially index active genes, repressed genes, silent repeat elements and intergenic regions. Given the compact nature of the Arabidopsis genome, these four indexing states typically translate into short chromatin domains interspersed with each other. This first combinatorial view of the Arabidopsis epigenome points to simple principles of organization as in metazoans and provides a framework for further studies of chromatin-based regulatory mechanisms in plants.

Exploration of plant genomes in the FLAGdb++ environment.

BACKGROUND: In the contexts of genomics, post-genomics and systems biology approaches, data integration presents a major concern. Databases provide crucial solutions: they store, organize and allow information to be queried, they enhance the visibility of newly produced data by comparing them with previously published results, and facilitate the exploration and development of both existing hypotheses and new ideas. RESULTS: The FLAGdb++ information system was developed with the aim of using whole plant genomes as physical references in order to gather and merge available genomic data from in silico or experimental approaches. Available through a JAVA application, original interfaces and tools assist the functional study of plant genes by considering them in their specific context: chromosome, gene family, orthology group, co-expression cluster and functional network. FLAGdb++ is mainly dedicated to the exploration of large gene groups in order to decipher functional connections, to highlight shared or specific structural or functional features, and to facilitate translational tasks between plant species (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Vitis vinifera). CONCLUSION: Combining original data with the output of experts and graphical displays that differ from classical plant genome browsers, FLAGdb++ presents a powerful complementary tool for exploring plant genomes and exploiting structural and functional resources, without the need for computer programming knowledge. First launched in 2002, a 15th version of FLAGdb++ is now available and comprises four model plant genomes and over eight million genomic features.