Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale.

BACKGROUND: Salmonella enterica subsp. enterica is a public health issue related to food safety, and its adaptation to animal sources remains poorly described at the pangenome scale. Firstly, serovars presenting potential mono- and multi-animal sources were selected from a curated and synthetized subset of Enterobase. The corresponding sequencing reads were downloaded from the European Nucleotide Archive (ENA) providing a balanced dataset of 440 Salmonella genomes in terms of serovars and sources (i). Secondly, the coregenome variants and accessory genes were detected (ii). Thirdly, single nucleotide polymorphisms and small insertions/deletions from the coregenome, as well as the accessory genes were associated to animal sources based on a microbial Genome Wide Association Study (GWAS) integrating an advanced correction of the population structure (iii). Lastly, a Gene Ontology Enrichment Analysis (GOEA) was applied to emphasize metabolic pathways mainly impacted by the pangenomic mutations associated to animal sources (iv). RESULTS: Based on a genome dataset including Salmonella serovars from mono- and multi-animal sources (i), 19,130 accessory genes and 178,351 coregenome variants were identified (ii). Among these pangenomic mutations, 52 genomic signatures (iii) and 9 over-enriched metabolic signatures (iv) were associated to avian, bovine, swine and fish sources by GWAS and GOEA, respectively. CONCLUSIONS: Our results suggest that the genetic and metabolic determinants of Salmonella adaptation to animal sources may have been driven by the natural feeding environment of the animal, distinct livestock diets modified by human, environmental stimuli, physiological properties of the animal itself, and work habits for health protection of livestock.

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.

Overview of the gene regulation network and the bacteria biotope tasks in BioNLP'13 shared task.

BACKGROUND: We present the two Bacteria Track tasks of BioNLP 2013 Shared Task (ST): Gene Regulation Network (GRN) and Bacteria Biotope (BB). These tasks were previously introduced in the 2011 BioNLP-ST Bacteria Track as Bacteria Gene Interaction (BI) and Bacteria Biotope (BB). The Bacteria Track was motivated by a need to develop specific BioNLP tools for fine-grained event extraction in bacteria biology. The 2013 tasks expand on the 2011 version by better addressing the biological knowledge modeling needs. New evaluation metrics were designed for the new goals. Moving beyond a list of gene interactions, the goal of the GRN task is to build a gene regulation network from the extracted gene interactions. BB'13 is dedicated to the extraction of bacteria biotopes, i.e. bacterial environmental information, as was BB'11. BB'13 extends the typology of BB'11 to a large diversity of biotopes, as defined by the OntoBiotope ontology. The detection of entities and events is tackled by distinct subtasks in order to measure the progress achieved by the participant systems since 2011. RESULTS: This paper details the corpus preparations and the evaluation metrics, as well as summarizing and discussing the participant results. Five groups participated in each of the two tasks. The high diversity of the participant methods reflects the dynamism of the BioNLP research community. CONCLUSION: The evaluation results suggest new research directions for the improvement and development of Information Extraction for molecular and environmental biology. The Bacteria Track tasks remain publicly open; the BioNLP-ST website provides an online evaluation service, the reference corpora and the evaluation tools.

Bacillus subtilis RNase Y activity in vivo analysed by tiling microarrays.

RNase Y is a key endoribonuclease affecting global mRNA stability in Bacillus subtilis. Its characterization provided the first evidence that endonucleolytic cleavage plays a major role in the mRNA metabolism of this organism. RNase Y shares important functional features with the RNA decay initiating RNase E from Escherichia coli, notably a similar cleavage specificity and a preference for 5' monophosphorylated substrates. We used high-resolution tiling arrays to analyze the effect of RNase Y depletion on RNA abundance covering the entire genome. The data confirm that this endoribonuclease plays a key role in initiating the decay of a large number of mRNAs as well as non coding RNAs. The downstream cleavage products are likely to be degraded by the 5' exonucleolytic activity of RNases J1/J2 as we show for a specific case. Comparison of the data with that of two other recent studies revealed very significant differences. About two thirds of the mRNAs upregulated following RNase Y depletion were different when compared to either one of these studies and only about 10% were in common in all three studies. This highlights that experimental conditions and data analysis play an important role in identifying RNase Y substrates by global transcriptional profiling. Our data confirmed already known RNase Y substrates and due to the precision and reproducibility of the profiles allow an exceptionally detailed view of the turnover of hundreds of new RNA substrates.

Genome-wide identification of genes directly regulated by the pleiotropic transcription factor Spx in Bacillus subtilis.

The transcriptional regulator Spx plays a key role in maintaining the redox homeostasis of Bacillus subtilis cells exposed to disulfide stress. Defects in Spx were previously shown to lead to differential expression of numerous genes but direct and indirect regulatory effects could not be distinguished. Here we identified 283 discrete chromosomal sites potentially bound by the Spx-RNA polymerase (Spx-RNAP) complex using chromatin immunoprecipitation of Spx. Three quarters of these sites were located near Sigma(A)-dependent promoters, and upon diamide treatment, the fraction of the Spx-RNAP complex increased in parallel with the number and occupancy of DNA sites. Correlation of Spx-RNAP-binding sites with gene differential expression in wild-type and Δspx strains exposed or not to diamide revealed that 144 transcription units comprising 275 genes were potentially under direct Spx regulation. Spx-controlled promoters exhibited an extended -35 box in which nucleotide composition at the -43/-44 positions strongly correlated with observed activation. In vitro transcription confirmed activation by oxidized Spx of seven newly identified promoters, of which one was also activated by reduced Spx. Our study globally characterized the Spx regulatory network, revealing its role in the basal expression of some genes and its complex interplay with other stress responses.

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.

Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism.

Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and model-based data analyses of dynamic transcript, protein, and metabolite abundances and promoter activities. Adaptation to malate was rapid and primarily controlled posttranscriptionally compared with the slow, mainly transcriptionally controlled adaptation to glucose that entailed nearly half of the known transcription regulation network. Interactions across multiple levels of regulation were involved in adaptive changes that could also be achieved by controlling single genes. Our analysis suggests that global trade-offs and evolutionary constraints provide incentives to favor complex control programs.

Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis.

Bacteria adapt to environmental stimuli by adjusting their transcriptomes in a complex manner, the full potential of which has yet to be established for any individual bacterial species. Here, we report the transcriptomes of Bacillus subtilis exposed to a wide range of environmental and nutritional conditions that the organism might encounter in nature. We comprehensively mapped transcription units (TUs) and grouped 2935 promoters into regulons controlled by various RNA polymerase sigma factors, accounting for ~66% of the observed variance in transcriptional activity. This global classification of promoters and detailed description of TUs revealed that a large proportion of the detected antisense RNAs arose from potentially spurious transcription initiation by alternative sigma factors and from imperfect control of transcription termination.

Three essential ribonucleases-RNase Y, J1, and III-control the abundance of a majority of Bacillus subtilis mRNAs.

Bacillus subtilis possesses three essential enzymes thought to be involved in mRNA decay to varying degrees, namely RNase Y, RNase J1, and RNase III. Using recently developed high-resolution tiling arrays, we examined the effect of depletion of each of these enzymes on RNA abundance over the whole genome. The data are consistent with a model in which the degradation of a significant number of transcripts is dependent on endonucleolytic cleavage by RNase Y, followed by degradation of the downstream fragment by the 5'-3' exoribonuclease RNase J1. However, many full-size transcripts also accumulate under conditions of RNase J1 insufficiency, compatible with a model whereby RNase J1 degrades transcripts either directly from the 5' end or very close to it. Although the abundance of a large number of transcripts was altered by depletion of RNase III, this appears to result primarily from indirect transcriptional effects. Lastly, RNase depletion led to the stabilization of many low-abundance potential regulatory RNAs, both in intergenic regions and in the antisense orientation to known transcripts.

Large-scale screening of a targeted Enterococcus faecalis mutant library identifies envelope fitness factors.

Spread of antibiotic resistance among bacteria responsible for nosocomial and community-acquired infections urges for novel therapeutic or prophylactic targets and for innovative pathogen-specific antibacterial compounds. Major challenges are posed by opportunistic pathogens belonging to the low GC% gram-positive bacteria. Among those, Enterococcus faecalis is a leading cause of hospital-acquired infections associated with life-threatening issues and increased hospital costs. To better understand the molecular properties of enterococci that may be required for virulence, and that may explain the emergence of these bacteria in nosocomial infections, we performed the first large-scale functional analysis of E. faecalis V583, the first vancomycin-resistant isolate from a human bloodstream infection. E. faecalis V583 is within the high-risk clonal complex 2 group, which comprises mostly isolates derived from hospital infections worldwide. We conducted broad-range screenings of candidate genes likely involved in host adaptation (e.g., colonization and/or virulence). For this purpose, a library was constructed of targeted insertion mutations in 177 genes encoding putative surface or stress-response factors. Individual mutants were subsequently tested for their i) resistance to oxidative stress, ii) antibiotic resistance, iii) resistance to opsonophagocytosis, iv) adherence to the human colon carcinoma Caco-2 epithelial cells and v) virulence in a surrogate insect model. Our results identified a number of factors that are involved in the interaction between enterococci and their host environments. Their predicted functions highlight the importance of cell envelope glycopolymers in E. faecalis host adaptation. This study provides a valuable genetic database for understanding the steps leading E. faecalis to opportunistic virulence.

An expanded protein-protein interaction network in Bacillus subtilis reveals a group of hubs: Exploration by an integrative approach.

We have generated a protein-protein interaction network in Bacillus subtilis focused on several essential cellular processes such as cell division, cell responses to various stresses, the bacterial cytoskeleton, DNA replication and chromosome maintenance by careful application of the yeast two-hybrid approach. This network, composed of 793 interactions linking 287 proteins with an average connectivity of five interactions per protein, represents a valuable resource for future functional analyses. A striking feature of the network is a group of highly connected hubs (GoH) linking many different cellular processes. Most of the proteins of the GoH have unknown functions and are associated to the membrane. By the integration of available knowledge, in particular of transcriptome data sets, the GoH was decomposed into subgroups of party hubs corresponding to protein complexes or regulatory pathways expressed under different conditions. At a global level, the GoH might function as a very robust group of date hubs having partially redundant functions to integrate information from the different cellular pathways. Our analyses also provide a rational way to study the highly redundant functions of the GoH by a genetic approach.

Comprehensive identification and quantification of microbial transcriptomes by genome-wide unbiased methods.

Genomic tiling array transcriptomics and RNA-seq are two powerful and rapidly developing approaches for unbiased transcriptome analysis. Providing comprehensive identification and quantification of transcripts with an unprecedented resolution, they are leading to major breakthroughs in systems biology. Here we review each step of the analysis from library preparation to the interpretation of the data, with particular attention paid to the possible sources of artifacts. Methodological requirements and statistical frameworks are often similar in both the approaches despite differences in the nature of the data. Tiling array analysis does not require rRNA depletion and benefits from a more mature computational workflow, whereas RNA-Seq has a clear lead in terms of background noise and dynamic range with a considerable potential for evolution with the improvements of sequencing technologies. Being independent of prior sequence knowledge, RNA-seq will boost metatranscriptomics and evolutionary transcriptomics applications.

Transcriptional landscape estimation from tiling array data using a model of signal shift and drift.

MOTIVATION: High-density oligonucleotide tiling array technology holds the promise of a better description of the complexity and the dynamics of transcriptional landscapes. In organisms such as bacteria and yeasts, transcription can be measured on a genome-wide scale with a resolution >25 bp. The statistical models currently used to handle these data remain however very simple, the most popular being the piecewise constant Gaussian model with a fixed number of breakpoints. RESULTS: This article describes a new methodology based on a hidden Markov model that embeds the segmentation of a continuous-valued signal in a probabilistic setting. For a computationally affordable cost, this framework (i) alleviates the difficulty of choosing a fixed number of breakpoints, and (ii) permits retrieving more information than a unique segmentation by giving access to the whole probability distribution of the transcription profile. Importantly, the model is also enriched and accounts for subtle effects such as signal 'drift' and covariates. Relevance of this framework is demonstrated on a Bacillus subtilis dataset. AVAILABILITY: A software is distributed under the GPL.

Learning ontological rules to extract multiple relations of genic interactions from text.

INTRODUCTION: Information extraction (IE) systems have been proposed in recent years to extract genic interactions from bibliographical resources. They are limited to single interaction relations, and have to face a trade-off between recall and precision, by focusing either on specific interactions (for precision), or general and unspecified interactions of biological entities (for recall). Yet, biologists need to process more complex data from literature, in order to study biological pathways. An ontology is an adequate formal representation to model this sophisticated knowledge. However, the tight integration of IE systems and ontologies is still a current research issue, a fortiori with complex ones that go beyond hierarchies. METHOD: We propose a rich modeling of genic interactions with an ontology, and show how it can be used within an IE system. The ontology is seen as a language specifying a normalized representation of text. First, IE is performed by extracting instances from natural language processing (NLP) modules. Then, deductive inferences on the ontology language are completed, and new instances are derived from previously extracted ones. Inference rules are learnt with an inductive logic programming (ILP) algorithm, using the ontology as the hypothesis language, and its instantiation on an annotated corpus as the example language. Learning is set in a multi-class setting to deal with the multiple ontological relations. RESULTS: We validated our approach on an annotated corpus of gene transcription regulations in the Bacillus subtilis bacterium. We reach a global recall of 89.3% and a precision of 89.6%, with high scores for the ten semantic relations defined in the ontology.

Towards a semi-automatic functional annotation tool based on decision-tree techniques.

BACKGROUND: Due to the continuous improvements of high throughput technologies and experimental procedures, the number of sequenced genomes is increasing exponentially. Ultimately, the task of annotating these data relies on the expertise of biologists. The necessity for annotation to be supervised by human experts is the rate limiting step of the data analysis. To face the deluge of new genomic data, the need for automating, as much as possible, the annotation process becomes critical. RESULTS: We consider annotation of a protein with terms of the functional hierarchy that has been used to annotate Bacillus subtilis and propose a set of rules that predict classes in terms of elements of the functional hierarchy, i.e., a class is a node or a leaf of the hierarchy tree. The rules are obtained through two decision-trees techniques: first-order decision-trees and multilabel attribute-value decision-trees, by using as training data the proteins from two lactic bacteria: Lactobacillus sakei and Lactobacillus bulgaricus. We tested the two methods, first independently, then in a combined approach, and evaluated the obtained results using hierarchical evaluation measures. Results obtained for the two approaches on both genomes are comparable and show a good precision together with a high prediction rate. Using combined approaches increases the recall and the prediction rate. CONCLUSION: The combination of the two approaches is very encouraging and we will further refine these combinations in order to get rules even more useful for the annotators. This first study is a crucial step towards designing a semi-automatic functional annotation tool.

Reconstruction and analysis of the genetic and metabolic regulatory networks of the central metabolism of Bacillus subtilis.

BACKGROUND: Few genome-scale models of organisms focus on the regulatory networks and none of them integrates all known levels of regulation. In particular, the regulations involving metabolite pools are often neglected. However, metabolite pools link the metabolic to the genetic network through genetic regulations, including those involving effectors of transcription factors or riboswitches. Consequently, they play pivotal roles in the global organization of the genetic and metabolic regulatory networks. RESULTS: We report the manually curated reconstruction of the genetic and metabolic regulatory networks of the central metabolism of Bacillus subtilis (transcriptional, translational and post-translational regulations and modulation of enzymatic activities). We provide a systematic graphic representation of regulations of each metabolic pathway based on the central role of metabolites in regulation. We show that the complex regulatory network of B. subtilis can be decomposed as sets of locally regulated modules, which are coordinated by global regulators. CONCLUSION: This work reveals the strong involvement of metabolite pools in the general regulation of the metabolic network. Breaking the metabolic network down into modules based on the control of metabolite pools reveals the functional organization of the genetic and metabolic regulatory networks of B. subtilis.

A genome-wide survey of short coding sequences in streptococci.

Identification of short genes that encode peptides of fewer than 60 aa is challenging, both experimentally and in silico. As a consequence, the universe of these short coding sequences (CDSs) remains largely unknown, although some are acknowledged to play important roles in cell-cell communication, particularly in Gram-positive bacteria. This paper reports a thorough search for short CDSs across streptococcal genomes. Our bioinformatic approach relied on a combination of advanced intrinsic and extrinsic methods. In the first step, intrinsic sequence information (nucleotide composition and presence of RBSs) served to identify new short putative CDSs (spCDSs) and to eliminate the differences between annotation policies. In the second step, pseudogene fragments and false predictions were filtered out. The last step consisted of screening the remaining spCDSs for lines of extrinsic evidence involving sequence and gene-context comparisons. A total of 789 spCDSs across 20 complete genomes (19 Streptococcus and one Enterococcus) received the support of at least one line of extrinsic evidence, which corresponds to an average of 20 short CDSs per million base pairs. Most of these had no known function, and a significant fraction (31%) are not even annotated as hypothetical genes in GenBank records. As an illustration of the value of this list, we describe a new family of CDSs, encoding very short hydrophobic peptides (20-23 aa) situated just upstream of some of the positive transcriptional regulators of the Rgg family. The expression of seven other short CDSs from Streptococcus thermophilus CNRZ1066 that encode peptides ranging in length from 41 to 56 aa was confirmed by real-time quantitative RT-PCR and revealed a variety of expression patterns. Finally, one peptide from this list, encoded by a gene that is not annotated in GenBank, was identified in a cell-envelope-enriched fraction of S. thermophilus CNRZ1066.

Extensive horizontal transfer of core genome genes between two Lactobacillus species found in the gastrointestinal tract.

BACKGROUND: While genes that are conserved between related bacterial species are usually thought to have evolved along with the species, phylogenetic trees reconstructed for individual genes may contradict this picture and indicate horizontal gene transfer. Individual trees are often not resolved with high confidence, however, and in that case alternative trees are generally not considered as contradicting the species tree, although not confirming it either. Here we conduct an in-depth analysis of 401 protein phylogenetic trees inferred with varying levels of confidence for three lactobacilli from the acidophilus complex. At present the relationship between these bacteria, isolated from environments as diverse as the gastrointestinal tract (Lactobacillus acidophilus and Lactobacillus johnsonii) and yogurt (Lactobacillus delbrueckii ssp. bulgaricus), is ambiguous due to contradictory phenotypical and 16S rRNA based classifications. RESULTS: Among the 401 phylogenetic trees, those that could be reconstructed with high confidence support the 16S-rRNA tree or one alternative topology in an astonishing 3:2 ratio, while the third possible topology is practically absent. Lowering the confidence threshold for trees to be taken into consideration does not significantly affect this ratio, and therefore suggests that gene transfer may have affected as much as 40% of the core genome genes. Gene function bias suggests that the 16S rRNA phylogeny of the acidophilus complex, which indicates that L. acidophilus and L. delbrueckii ssp. bulgaricus are the closest related of these three species, is correct. A novel approach of comparison of interspecies protein divergence data employed in this study allowed to determine that gene transfer most likely took place between the lineages of the two species found in the gastrointestinal tract. CONCLUSION: This case-study reports an unprecedented level of phylogenetic incongruence, presumably resulting from extensive horizontal gene transfer. The data give a first indication of the large extent of gene transfer that may take place in the gastrointestinal tract and its accumulated effect. For future studies, our results should encourage a careful weighing of data on phylogenetic tree topology, confidence and distribution to conclude on the absence or presence and extent of horizontal gene transfer.

Complete genome sequence of the fish pathogen Flavobacterium psychrophilum.

We report here the complete genome sequence of the virulent strain JIP02/86 (ATCC 49511) of Flavobacterium psychrophilum, a widely distributed pathogen of wild and cultured salmonid fish. The genome consists of a 2,861,988-base pair (bp) circular chromosome with 2,432 predicted protein-coding genes. Among these predicted proteins, stress response mediators, gliding motility proteins, adhesins and many putative secreted proteases are probably involved in colonization, invasion and destruction of the host tissues. The genome sequence provides the basis for explaining the relationships of the pathogen to the host and opens new perspectives for the development of more efficient disease control strategies. It also allows for a better understanding of the physiology and evolution of a significant representative of the family Flavobacteriaceae, whose members are associated with an interesting diversity of lifestyles and habitats.

MuGeN: simultaneous exploration of multiple genomes and computer analysis results.

MOTIVATION: The availability of increasing amounts of sequence data about completely sequenced genomes spurs the development of new methods in the fields of automated annotation, and of comparative genomics. Tools allowing the visualization of results produced by analysis methods, superimposed on possibly annotated sequence data, and enabling synchronized navigation in multiple genomes, provide new means for interactive genome exploration. This kind of visual inspection can be used as a basis to assess the quality of new analysis algorithms, or to discover genome portions to be subjected to in-depth studies. RESULTS: We propose a software package, MuGeN, built for navigating through multiple annotated genomes. It is capable of retrieving annotated sequences in several formats, stored in local files, or available in databases over the network. From these, it then generates an interactive display, or an image file, in most common formats suitable for printing, further editing or integrating in Web pages. Genome maps may be mixed with computer analysis results loaded from XML files, whose format is generic enough to be adapted to a majority of sequence oriented analysis methods. AVAILABILITY: MuGeN is available at http://www-mig.jouy.inra.fr/bdsi/MuGeN.