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

Antibiotic drug discovery: Challenges and perspectives in the light of emerging antibiotic resistance

Amid a rising threat of antimicrobial resistance in a global scenario, our huge investments and high-throughput technologies injected for rejuvenating the key therapeutic scaffolds to suppress these rising superbugs has been diminishing severely. This has grasped world-wide attention, with increased consideration being given to the discovery of new chemical entities. Research has now proven that the relatively tiny and simpler microbes possess enhanced capability of generating novel and diverse chemical constituents with huge therapeutic leads. The usage of these beneficial organisms could help in producing new chemical scaffolds that govern the power to suppress the spread of obnoxious superbugs. Here in this review, we have explicitly focused on several appealing strategies employed for the generation of new chemical scaffolds. Also, efforts on providing novel insights on some of the unresolved questions in the production of metabolites, metabolic profiling and also the serendipity of getting "hit molecules" have been rigorously discussed. However, we are highly aware that biosynthetic pathway of different classes of secondary metabolites and their biosynthetic route is a vast topic, thus we have avoided discussion on this topic.

The enemy from within: a prophage of Roseburia intestinalis systematically turns lytic in the mouse gut, driving bacterial adaptation by CRISPR spacer acquisition

Despite an overall temporal stability in time of the human gut microbiota at the phylum level, strong variations in species abundance have been observed. We are far from a clear understanding of what promotes or disrupts the stability of microbiome communities. Environmental factors, like food or antibiotic use, modify the gut microbiota composition, but their overall impacts remain relatively low. Phages, the viruses that infect bacteria, might constitute important factors explaining temporal variations in species abundance. Gut bacteria harbour numerous prophages, or dormant viruses, which can evolve to become ultravirulent phage mutants, potentially leading to important bacterial death. Whether such phenomenon occurs in the mammal's microbiota has been largely unexplored. Here we studied temperate phage-bacteria coevolution in gnotoxenic mice colonised with Roseburia intestinalis, a dominant symbiont of the human gut microbiota, and Escherichia coli, a sub-dominant member of the same microbiota. We show that R. intestinalis L1-82 harbours two active prophages, Jekyll and Shimadzu. We observed the systematic evolution in mice of ultravirulent Shimadzu phage mutants, which led to a collapse of R. intestinalis population. In a second step, phage infection drove the fast counter-evolution of host phage resistance mainly through phage-derived spacer acquisition in a clustered regularly interspaced short palindromic repeats array. Alternatively, phage resistance was conferred by a prophage originating from an ultravirulent phage with a restored ability to lysogenize. Our results demonstrate that prophages are a potential source of ultravirulent phages that can successfully infect most of the susceptible bacteria. This suggests that prophages can play important roles in the short-term temporal variations observed in the composition of the gut microbiota.

2-Methylcitrate cycle: a well-regulated controller of Bacillus sporulation

Bacillus thuringiensis is the most widely used eco-friendly biopesticide, containing two primary determinants of biocontrol, endospore and insecticidal crystal proteins (ICPs). The 2-methylcitrate cycle is a widespread carbon metabolic pathway playing a crucial role in channelling propionyl-CoA, but with poorly understood metabolic regulatory mechanisms. Here, we dissect the transcriptional regulation of the 2-methylcitrate cycle operon prpCDB and report its unprecedented role in controlling the sporulation process of B. thuringiensis. We found that the transcriptional activity of the prp operon encoding the three critical enzymes PrpC, PrpD, and PrpB in the 2-methylcitrate cycle was negatively regulated by the two global transcription factors CcpA and AbrB, while positively regulated by the LysR family regulator CcpC, which jointly account for the fact that the 2-methylcitrate cycle is specifically and highly active in the stationary phase of growth. We also found that the prpD mutant accumulated 2-methylcitrate, the intermediate metabolite of the 2-methylcitrate cycle, which delayed and inhibited sporulation at the early stage. Thus, our results not only revealed sophisticated transcriptional regulatory mechanisms for the metabolic 2-methylcitrate cycle but also identified 2-methylcitrate as a novel regulator of sporulation in B. thuringiensis.

A plasmid-based genomic screening system for transcriptional regulators of non-adjacent xenobiotic catabolism genes

Bacteria play an important role in the catabolism of environmental xenobiotics. The study of transcriptional regulation has greatly enhanced our understanding of the molecular mechanisms associated with these processes. However, genes encoding transcription factors (TFs) for xenobiotic catabolism are usually not located in the immediate vicinity of the catabolic genes that they regulate; therefore, functional identification of these TFs is difficult. Significantly modified from a metagenome screening method substrate-induced gene expression (SIGEX), here we propose a synthetic pSRGFP-18 plasmid-based tool as a TF reporter system. In short, two multiple cloning sites (MCS) were designed; one in front of an egfp reporter gene was constructed for promoter insertion, and the other MCS was used for shotgun cloning of genomic DNA. Based on the regulatory relationship between TFs and the promoter of their associated catabolic genes, this approach allowed us to screen for TF genes using a genome shotgun approach. This system performed well when testing the known operons. Following statistical analysis of known catabolic operons in Escherichia coli and Bacillus subtilis, the suggested region of the target promoter for this system was from - 250 to + 150. Furthermore, to broaden the applicability of this plasmid, a series of pSRGFP-18 and pBBR1-based pSRGFP-X plasmids were constructed, which had broad host ranges and contained different antibiotic markers. This study outlines a powerful tool to enable functional identification of TFs for bacterial xenobiotic catabolism.

Engineering strong and stress-responsive promoters in Bacillus subtilis by interlocking sigma factor binding motifs

Prokaryotic gene expression is largely regulated on transcriptional levels with the involvement of promoters, RNA polymerase and sigma factors. Developing new promoters to customize gene transcriptional regulation becomes increasingly demanded in synthetic biology and biotechnology. In this study, we designed synthetic promoters in the Gram-positive model bacterium Bacillus subtilis by interlocking the binding motifs of σ^A for house-keeping gene expression and that of two alternative sigma factors σ^H and σ^B which are involved in responding post-exponential growth and general stress, respectively. The developed promoters are recognized by multiple sigma factors and hence generate strong transcriptional strength when host cells grow under normal or stressed conditions. With green fluorescent protein as the reporter, a set of strong promoters were identified, in which the transcription activities of P_HA-1, P_HAB-4, P_HAB-7 were 18.6, 4.1, 3.3 fold of that of the commonly used promoter P₄₃, respectively. Moreover, some of the promoters such as P_HA-1, P_HAB-4, P_HAB-7, P_BA-2 displayed increased transcriptional activities in response to high salinity or low pH. The promoters developed in this study should enrich the biotechnological toolboxes of B. subtilis.

Global Transcriptional Response of Three Highly Acid-Tolerant Field Strains of Listeria monocytogenes to HCl Stress

Tolerance to acid is of dual importance for the food-borne pathogen Listeria monocytogenes: acids are used as a preservative, and gastric acid is one of the first defenses within the host. There are considerable differences in the acid tolerance of strains. Here we present the transcriptomic response of acid-tolerant field strains of L. monocytogenes to HCl at pH 3.0. RNAseq revealed significant differential expression of genes involved in phosphotransferase systems, oxidative phosphorylation, cell morphology, motility, and biofilm formation. Genes in the acetoin biosynthesis pathway were upregulated, suggesting that L. monocytogenes shifts to metabolizing pyruvate to acetoin under organic acid stress. We also identified the formation of cell aggregates in microcolonies as a potential relief strategy. A motif search within the first 150 bp upstream of differentially expressed genes identified a novel potential regulatory sequence that may have a function in the regulation of virulence gene expression. Our data support a model where an excess of intracellular H+ ions is counteracted by pumping H+ out of the cytosol via cytochrome C under reduced activity of the ATP synthase. The observed morphological changes suggest that acid stress may cause cells to aggregate in biofilm microcolonies to create a more favorable microenvironment. Additionally, HCl stress in the host stomach may serve as (i) a signal to downregulate highly immunogenic flagella, and (ii) as an indicator for the imminent contact with host cells which triggers early stage virulence genes.

Toward Algorithms for Automation of Postgenomic Data Analyses: Bacillus subtilis Promoter Prediction with Artificial Neural Network

In the present postgenomic era, the capacity to generate big data has far exceeded the capacity to analyze, contextualize, and make sense of the data in clinical, biological, and ecological applications. There is a great unmet need for automation and algorithms to aid in analyses of big data, in biology in particular. In this context, it is noteworthy that computational methods used to analyze the regulation of bacterial gene expression have in the past focused mainly on Escherichia coli promoters due to the large amount of data available. The challenge and prospects of automation in prediction and recognition of bacteria sequences as promoters have not been properly addressed due to the promoter size and degenerate pattern. We report here an original neural network approach for recognition and prediction of Bacillus subtilis promoters. The artificial neural network used as input 767 B. subtilis promoter sequences, while also aiming at identifying the architecture, provides the most optimal prediction. Two multilayer perceptron neural network architectures offered the highest accuracy: one with five, and another with seven neurons in the hidden layer. Each architecture achieved an accuracy of 98.57% and 97.69%, respectively. The results collectively indicate the promise of the application of neural network approaches to the B. subtilis promoter recognition problem, while also suggesting the broader potential of algorithms for automation of data analyses in the postgenomic era.

Interaction of enzymes of the tricarboxylic acid cycle in Bacillus subtilis and Escherichia coli: a comparative study

We studied the interaction of the tricarboxylic acid cycle enzymes citrate synthase, isocitrate dehydrogenase and malate dehydrogenase in the bacteria Bacillus subtilis and Escherichia coli in vivo. In B. subtilis, the genes encoding citrate synthase, isocitrate dehydrogenase and malate dehydrogenase form an operon (citZ-icd-mdh) and predominantly are co-transcribed from a single promoter. In E. coli the corresponding genes gltA, icd and mdh do not form a transcription unit, are scattered around the chromosome and are expressed from different promoters. We found that co-transcription of genes and subsequent co-translation of the corresponding mRNAs promotes the formation of protein complexes and give support for the previous findings that in B. subtilis citrate synthase, isocitrate dehydrogenase and malate dehydrogenase form an enzyme complex (metabolon).

dbCAN-seq: a database of carbohydrate-active enzyme (CAZyme) sequence and annotation

Carbohydrate-active enzyme (CAZymes) are not only the most important enzymes for bioenergy and agricultural industries, but also very important for human health, in that human gut microbiota encode hundreds of CAZyme genes in their genomes for degrading various dietary and host carbohydrates. We have built an online database dbCAN-seq (http://cys.bios.niu.edu/dbCAN_seq) to provide pre-computed CAZyme sequence and annotation data for 5,349 bacterial genomes. Compared to the other CAZyme resources, dbCAN-seq has the following new features: (i) a convenient download page to allow batch download of all the sequence and annotation data; (ii) an annotation page for every CAZyme to provide the most comprehensive annotation data; (iii) a metadata page to organize the bacterial genomes according to species metadata such as disease, habitat, oxygen requirement, temperature, metabolism; (iv) a very fast tool to identify physically linked CAZyme gene clusters (CGCs) and (v) a powerful search function to allow fast and efficient data query. With these unique utilities, dbCAN-seq will become a valuable web resource for CAZyme research, with a focus complementary to dbCAN (automated CAZyme annotation server) and CAZy (CAZyme family classification and reference database).

PRODORIC2: the bacterial gene regulation database in 2018

Bacteria adapt to changes in their environment via differential gene expression mediated by DNA binding transcriptional regulators. The PRODORIC2 database hosts one of the largest collections of DNA binding sites for prokaryotic transcription factors. It is the result of the thoroughly redesigned PRODORIC database. PRODORIC2 is more intuitive and user-friendly. Besides significant technical improvements, the new update offers more than 1000 new transcription factor binding sites and 110 new position weight matrices for genome-wide pattern searches with the Virtual Footprint tool. Moreover, binding sites deduced from high-throughput experiments were included. Data for 6 new bacterial species including bacteria of the Rhodobacteraceae family were added. Finally, a comprehensive collection of sigma- and transcription factor data for the nosocomial pathogen Clostridium difficile is now part of the database. PRODORIC2 is publicly available at http://www.prodoric2.de.

Microbial life cycles link global modularity in regulation to mosaic evolution

Microbes are exposed to changing environments, to which they can respond by adopting various lifestyles such as swimming, colony formation or dormancy. These lifestyles are often studied in isolation, thereby giving a fragmented view of the life cycle as a whole. Here, we study lifestyles in the context of this whole. We first use machine learning to reconstruct the expression changes underlying life cycle progression in the bacterium Bacillus subtilis, based on hundreds of previously acquired expression profiles. This yields a timeline that reveals the modular organization of the life cycle. By analysing over 380 Bacillales genomes, we then show that life cycle modularity gives rise to mosaic evolution in which life stages such as motility and sporulation are conserved and lost as discrete units. We postulate that this mosaic conservation pattern results from habitat changes that make these life stages obsolete or detrimental. Indeed, when evolving eight distinct Bacillales strains and species under laboratory conditions that favour colony growth, we observe rapid and parallel losses of the sporulation life stage across species, induced by mutations that affect the same global regulator. We conclude that a life cycle perspective is pivotal to understanding the causes and consequences of modularity in both regulation and evolution.

The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database

Background

High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook.

Results

We describe the MultiOmics Explainer, a new tool within the Pathway Tools software suite that leverages what is known about an organism’s metabolic and regulatory network to suggest explanations for the results of omics experiments. Querying a database such as EcoCyc, the MultiOmics Explainer searches the organism’s network of metabolic reactions, transporters, cofactors, enzyme substrate-level activation and inhibition relationships, and transcriptional and translational regulation relationships to identify paths of influence among input genes, proteins and metabolites. Results are presented in a combined metabolic and regulatory diagram. We present several examples of explanations generated for associations found in the Escherichia coli literature.

Conclusions

The MultiOmics Explainer is a valuable tool that helps researchers understand and interpret the results of their omics experiments in the context of what is known about an organism’s metabolic and regulatory network. It showcases the rich set of computational inferences that can be drawn from a database such as EcoCyc that encodes a diverse range of biological interactions.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2971-6) contains supplementary material, which is available to authorized users.

iProEP: A Computational Predictor for Predicting Promoter

Promoter is a fundamental DNA element located around the transcription start site (TSS) and could regulate gene transcription. Promoter recognition is of great significance in determining transcription units, studying gene structure, analyzing gene regulation mechanisms, and annotating gene functional information. Many models have already been proposed to predict promoters. However, the performances of these methods still need to be improved. In this work, we combined pseudo k-tuple nucleotide composition (PseKNC) with position-correlation scoring function (PCSF) to formulate promoter sequences of Homo sapiens (H. sapiens), Drosophila melanogaster (D. melanogaster), Caenorhabditis elegans (C. elegans), Bacillus subtilis (B. subtilis), and Escherichia coli (E. coli). Minimum Redundancy Maximum Relevance (mRMR) algorithm and increment feature selection strategy were then adopted to find out optimal feature subsets. Support vector machine (SVM) was used to distinguish between promoters and non-promoters. In the 10-fold cross-validation test, accuracies of 93.3%, 93.9%, 95.7%, 95.2%, and 93.1% were obtained for H. sapiens, D. melanogaster, C. elegans, B. subtilis, and E. coli, with the areas under receiver operating curves (AUCs) of 0.974, 0.975, 0.981, 0.988, and 0.976, respectively. Comparative results demonstrated that our method outperforms existing methods for identifying promoters. An online web server was established that can be freely accessed (http://lin-group.cn/server/iProEP/).

CRISPR-assisted multi-dimensional regulation for fine-tuning gene expression in Bacillus subtilis

Fine-tuning of gene expression is crucial for protein expression and pathway construction, but it still faces formidable challenges due to the hierarchical gene regulation at multiple levels in a context-dependent manner. In this study, we defined the optimal targeting windows for CRISPRa and CRISPRi of the dCas9-α/ω system, and demonstrated that this system could act as a single master regulator to simultaneously activate and repress the expression of different genes by designing position-specific gRNAs. The application scope of dCas9-ω was further expanded by a newly developed CRISPR-assisted Oligonucleotide Annealing based Promoter Shuffling (OAPS) strategy, which could generate a high proportion of functional promoter mutants and facilitate the construction of effective promoter libraries in microorganisms with low transformation efficiency. Combing OAPS and dCas9-ω, the influences of promoter-based transcription, molecular chaperone-assisted protein folding and protease-mediated degradation on the expression of amylase BLA in Bacillus subtilis were systematically evaluated, and a 260-fold enhancement of BLA production was obtained. The success of the OAPS strategy and dCas9-ω for BLA production in this study thus demonstrated that it could serve as a powerful tool kit to regulate the expression of multiple genes multi-directionally and multi-dimensionally in bacteria.

A computational system for identifying operons based on RNA-seq data

An operon is a set of neighboring genes in a genome that is transcribed as a single polycistronic message. Genes that are part of the same operon often have related functional roles or participate in the same metabolic pathways. The majority of all bacterial genes are co-transcribed with one or more other genes as part of a multi-gene operon. Thus, accurate identification of operons is important in understanding co-regulation of genes and their functional relationships. Here, we present a computational system that uses RNA-seq data to determine operons throughout a genome. The system takes the name of a genome and one or more files of RNA-seq data as input. Our method combines primary genomic sequence information with expression data from the RNA-seq files in a unified probabilistic model in order to identify operons. We assess our method's ability to accurately identify operons in a range of species through comparison to external databases of operons, both experimentally confirmed and computationally predicted, and through focused experiments that confirm new operons identified by our method. Our system is freely available at https://cs.wellesley.edu/~btjaden/Rockhopper/.

Evolutionary constraints on the complexity of genetic regulatory networks allow predictions of the total number of genetic interactions

Genetic regulatory networks (GRNs) have been widely studied, yet there is a lack of understanding with regards to the final size and properties of these networks, mainly due to no network currently being complete. In this study, we analyzed the distribution of GRN structural properties across a large set of distinct prokaryotic organisms and found a set of constrained characteristics such as network density and number of regulators. Our results allowed us to estimate the number of interactions that complete networks would have, a valuable insight that could aid in the daunting task of network curation, prediction, and validation. Using state-of-the-art statistical approaches, we also provided new evidence to settle a previously stated controversy that raised the possibility of complete biological networks being random and therefore attributing the observed scale-free properties to an artifact emerging from the sampling process during network discovery. Furthermore, we identified a set of properties that enabled us to assess the consistency of the connectivity distribution for various GRNs against different alternative statistical distributions. Our results favor the hypothesis that highly connected nodes (hubs) are not a consequence of network incompleteness. Finally, an interaction coverage computed for the GRNs as a proxy for completeness revealed that high-throughput based reconstructions of GRNs could yield biased networks with a low average clustering coefficient, showing that classical targeted discovery of interactions is still needed.

Petrobactin Protects against Oxidative Stress and Enhances Sporulation Efficiency in Bacillus anthracis Sterne

Bacillus anthracis causes the disease anthrax, which is transmitted via its dormant, spore phase. However, conversion from bacillus to spore is a complex, energetically costly process that requires many nutrients, including iron. B. anthracis requires the siderophore petrobactin to scavenge iron from host environments. We show that, in the Sterne strain, petrobactin is required for efficient sporulation, even when ample iron is available. The petrobactin biosynthesis operon is expressed during sporulation, and petrobactin is biosynthesized during growth in high-iron sporulation medium, but instead of being exported, the petrobactin remains intracellular to protect against oxidative stress and improve sporulation. It is also required for full growth and sporulation in blood (bovine), an essential step for anthrax transmission between mammalian hosts.

Bacillus anthracis is a Gram-positive bacillus that under conditions of environmental stress, such as low nutrients, can convert from a vegetative bacillus to a highly durable spore that enables long-term survival. The sporulation process is regulated by a sequential cascade of dedicated transcription factors but requires key nutrients to complete, one of which is iron. Iron acquisition by the iron-scavenging siderophore petrobactin is required for vegetative growth of B. anthracis under iron-depleted conditions and in the host. However, the extent to which petrobactin is involved in spore formation is unknown. This work shows that efficient in vitro sporulation of B. anthracis requires petrobactin, that the petrobactin biosynthesis operon (asbA to -F) is induced prior to sporulation, and that the siderophore itself associates with spores. Petrobactin is also required for oxidative stress protection during late-stage growth and for wild-type levels of sporulation in sporulation medium. Sporulation in bovine blood was found to be petrobactin dependent. Collectively, the in vitro contributions of petrobactin to sporulation as well as growth imply that petrobactin may be required for B. anthracis transmission via the spore during natural infections, in addition to its key known functions during active anthrax infections.

Feedbacks from the metabolic network to the genetic network reveal regulatory modules in E. coli and B. subtilis

The genetic regulatory network (GRN) plays a key role in controlling the response of the cell to changes in the environment. Although the structure of GRNs has been the subject of many studies, their large scale structure in the light of feedbacks from the metabolic network (MN) has received relatively little attention. Here we study the causal structure of the GRNs, namely the chain of influence of one component on the other, taking into account feedback from the MN. First we consider the GRNs of E. coli and B. subtilis without feedback from MN and illustrate their causal structure. Next we augment the GRNs with feedback from their respective MNs by including (a) links from genes coding for enzymes to metabolites produced or consumed in reactions catalyzed by those enzymes and (b) links from metabolites to genes coding for transcription factors whose transcriptional activity the metabolites alter by binding to them. We find that the inclusion of feedback from MN into GRN significantly affects its causal structure, in particular the number of levels and relative positions of nodes in the hierarchy, and the number and size of the strongly connected components (SCCs). We then study the functional significance of the SCCs. For this we identify condition specific feedbacks from the MN into the GRN by retaining only those enzymes that are essential for growth in specific environmental conditions simulated via the technique of flux balance analysis (FBA). We find that the SCCs of the GRN augmented by these feedbacks can be ascribed specific functional roles in the organism. Our algorithmic approach thus reveals relatively autonomous subsystems with specific functionality, or regulatory modules in the organism. This automated approach could be useful in identifying biologically relevant modules in other organisms for which network data is available, but whose biology is less well studied.

Recurrence-based information processing in gene regulatory networks

Cellular information processing is generally attributed to the complex networks of genes and proteins that regulate cell behavior. It is still unclear, however, what are the main features of those networks that allow a cell to encode and interpret its ever changing environment. Here, we address this question by studying the computational capabilities of the transcriptional regulatory networks of five evolutionary distant organisms. We identify in all cases a cyclic recurrent structure, formed by a small core of genes, that is essential for dynamical encoding and information integration. The recent history of the cell is projected nonlinearly into this recurrent reservoir of nodes, where it is encoded by its transient dynamics, while the rest of the network forms a readout layer devoted to decode and interpret the high-dimensional dynamical state of the recurrent core. In that way, gene regulatory networks act as echo-state networks that perform optimally in standard memory-demanding tasks, with most of their memory residing in the recurrent reservoir. The biological significance of these results is analyzed in the particular case of the bacterium Escherichia coli. Our work thus suggests that recurrent nonlinear dynamics is a key element for the processing of complex time-dependent information by cells.

NagRBt Is a Pleiotropic and Dual Transcriptional Regulator in Bacillus thuringiensis

NagR, belonging to the GntR/HutC family, is a negative regulator that directly represses the nagP and nagAB genes, which are involved in GlcNAc transport and utilization in Bacillus subtilis. Our previous work confirmed that the chitinase B gene (chiB) of Bacillus thuringiensis strain Bti75 is also negatively controlled by YvoA_Bt, the ortholog of NagR from B. subtilis. In this work, we investigated its regulatory network in Bti75 and found that YvoA_Bt is an N-acetylglucosamine utilization regulator primarily involved in GlcNAc catabolism; therefore YvoA_Bt is renamed as NagR_Bt. The RNA-seq data revealed that 27 genes were upregulated and 14 genes were downregulated in the ΔnagR mutant compared with the wild-type strain. The regulon (exponential phase) was characterized by RNA-seq, bioinformatics software, electrophoretic mobility shift assays, and quantitative real-time reverse transcription PCR. In the Bti75 genome, 19 genes that were directly regulated and 30 genes that were indirectly regulated by NagR_Bt were identified. We compiled in silico, in vitro, and in vivo evidence that NagR_Bt behaves as a repressor and activator to directly or indirectly influence major biological processes involved in amino sugar metabolism, nucleotide metabolism, fatty acid metabolism, phosphotransferase system, and the Embden-Meyerhof-Parnas pathway.

Efficient inference for sparse latent variable models of transcriptional regulation

Motivation

Regulation of gene expression in prokaryotes involves complex co-regulatory mechanisms involving large numbers of transcriptional regulatory proteins and their target genes. Uncovering these genome-scale interactions constitutes a major bottleneck in systems biology. Sparse latent factor models, assuming activity of transcription factors (TFs) as unobserved, provide a biologically interpretable modelling framework, integrating gene expression and genome-wide binding data, but at the same time pose a hard computational inference problem. Existing probabilistic inference methods for such models rely on subjective filtering and suffer from scalability issues, thus are not well-suited for realistic genome-scale applications.

Results

We present a fast Bayesian sparse factor model, which takes input gene expression and binding sites data, either from ChIP-seq experiments or motif predictions, and outputs active TF-gene links as well as latent TF activities. Our method employs an efficient variational Bayes scheme for model inference enabling its application to large datasets which was not feasible with existing MCMC-based inference methods for such models. We validate our method on synthetic data against a similar model in the literature, employing MCMC for inference, and obtain comparable results with a small fraction of the computational time. We also apply our method to large-scale data from Mycobacterium tuberculosis involving ChIP-seq data on 113 TFs and matched gene expression data for 3863 putative target genes. We evaluate our predictions using an independent transcriptomics experiment involving over-expression of TFs.

Availability and implementation

An easy-to-use Jupyter notebook demo of our method with data is available at https://github.com/zhenwendai/SITAR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Bacillus subtilis promoter sequences data set for promoter prediction in Gram-positive bacteria

This paper presents a prediction of Bacillus subtilis promoters using a Support Vector Machine system. In the literature, there is a lack of information on Gram-positive bacterial promoter sequences compared to Gram-negative bacteria. Promoter sequence identification is essential for studying gene expression. Initially, we collected the B. subtilis genome sequence from the NCBI database, and promoters were identified by their sigma factors in the DBTBS database. We then grouped the promoters according to 15 factors in 2 domains, corresponding to sigma 54 and sigma 70 of Gram-negative bacteria. Based on these data we developed a script in Python to search for promoters in the B. subtilis genome. After processing the data, we obtained 767 promoter sequences for B. subtilis, most of which were recognized by sigma SigA. To validate the data we found, we developed a software package called BacSVM+, which receives promoters as input and returns the best combination of parameters in a LibSVM library to predict promoter regions in the bacteria used in the simulation. All data gathered as well as the BacSVM+ software is available for download at http://bacpp.bioinfoucs.com/rafael/Sigmas.zip.

Computational operon prediction in whole-genomes and metagenomes

Microbial diversity in unique environmental settings enables abrupt responses catalysed by altering the gene regulation and formation of gene clusters called operons. Operons increases bacterial adaptability, which in turn increases their survival. This review article presents the emergence of computational operon prediction methods for whole microbial genomes and metagenomes, and discusses their strengths and limitations. Most of the whole-genome operon prediction methods struggle to generalize on unrelated genomes. The applicability of universal whole-genome operon prediction methods to metagenomic data is an interesting yet less investigated question. We have evaluated the potential of various operon prediction features for genomic and metagenomic data. Most of operon prediction methods with high accuracy have been compiled into databases. Despite of the high predictive performance, the data among many databases are not completely consistent for similar species. We performed a correlation analysis between the computationally predicted operon databases and experimentally validated data for Escherichia coli, Bacillus subtilis and Mycobacterium tuberculosis. Operon prediction for most of the less characterized microbes cannot be verified due to absence of experimentally validated operons. The generation of validated information for other microbes would test the authenticity of operon databases for other less annotated microbes as well. Advances in sequencing technologies and development of better analysis methods will help researchers to overcome the technological hurdles (such as long sequencing reads and improved contig size) and further improve operon predictions and better utilize operonic information.

Transcription and translation of the sigG gene is tuned for proper execution of the switch from early to late gene expression in the developing Bacillus subtilis spore

A cascade of alternative sigma factors directs developmental gene expression during spore formation by the bacterium Bacillus subtilis. As the spore develops, a tightly regulated switch occurs in which the early-acting sigma factor σ^F is replaced by the late-acting sigma factor σ^G. The gene encoding σ^G (sigG) is transcribed by σ^F and by σ^G itself in an autoregulatory loop; yet σ^G activity is not detected until σ^F-dependent gene expression is complete. This separation in σ^F and σ^G activities has been suggested to be due at least in part to a poorly understood intercellular checkpoint pathway that delays sigG expression by σ^F. Here we report the results of a careful examination of sigG expression during sporulation. Unexpectedly, our findings argue against the existence of a regulatory mechanism to delay sigG transcription by σ^F and instead support a model in which sigG is transcribed by σ^F with normal timing, but at levels that are very low. This low-level expression of sigG is the consequence of several intrinsic features of the sigG regulatory and coding sequence—promoter spacing, secondary structure potential of the mRNA, and start codon identity—that dampen its transcription and translation. Especially notable is the presence of a conserved hairpin in the 5’ leader sequence of the sigG mRNA that occludes the ribosome-binding site, reducing translation by up to 4-fold. Finally, we demonstrate that misexpression of sigG from regulatory and coding sequences lacking these features triggers premature σ^G activity in the forespore during sporulation, as well as inappropriate σ^G activity during vegetative growth. Altogether, these data indicate that transcription and translation of the sigG gene is tuned to prevent vegetative expression of σ^G and to ensure the precise timing of the switch from σ^F to σ^G in the developing spore.

Global changes in gene expression occur during normal cellular growth and development, as well as during cancer cell transformation and bacterial pathogenesis. In this study we have investigated the molecular mechanisms that drive the switch from early to late developmental gene expression during spore formation by the model bacterium Bacillus subtilis. At early times, gene expression in the developing spore is directed by the transcription factor σ^F; at later times σ^F is replaced by σ^G. An important, yet poorly understood aspect of this σ^F-to-σ^G transition is how σ^G activation is delayed until the early, σ^F-directed phase of gene expression is complete. Here we have carefully examined expression of the gene encoding σ^G, sigG, and found that its transcription and translation are ordinarily dampened by several features of its regulatory and coding sequences. Moreover, we have found that this “tuning” of sigG expression is required for proper timing of the switch to σ^G. These results reframe our understanding of how sigG is regulated during B. subtilis sporulation and, more broadly, advance our understanding of how global changes in gene expression can be precisely executed at the molecular/genetic level.

Evolutionary Convergence of Pathway-Specific Enzyme Expression Stoichiometry

Coexpression of proteins in response to pathway-inducing signals is the founding paradigm of gene regulation. However, it remains unexplored whether the relative abundance of co-regulated proteins requires precise tuning. Here, we present large-scale analyses of protein stoichiometry and corresponding regulatory strategies for 21 pathways and 67-224 operons in divergent bacteria separated by 0.6-2 billion years. Using end-enriched RNA-sequencing (Rend-seq) with single-nucleotide resolution, we found that many bacterial gene clusters encoding conserved pathways have undergone massive divergence in transcript abundance and architectures via remodeling of internal promoters and terminators. Remarkably, these evolutionary changes are compensated post-transcriptionally to maintain preferred stoichiometry of protein synthesis rates. Even more strikingly, in eukaryotic budding yeast, functionally analogous proteins that arose independently from bacterial counterparts also evolved to convergent in-pathway expression. The broad requirement for exact protein stoichiometries despite regulatory divergence provides an unexpected principle for building biological pathways both in nature and for synthetic activities.

RelA/DTD-mediated regulation of spore formation and toxin production by Clostridium perfringens type A strain SM101

RelA is a global regulator for stationary phase development in the model bacterium Bacillus subtilis. The relA gene forms a bicistronic operon with the downstream dtd gene. In this study, we evaluated the significance of RelA and DTD proteins in spore formation and toxin production by an important gastrointestinal pathogen Clostridium perfringens. Our β-glucuronidase assay showed that in C. perfringens strain SM101, relA forms a bicistronic operon with its downstream dtd gene, and the relA promoter is expressed during both vegetative and sporulation conditions. By constructing double relA dtd and single dtd mutants in C. perfringens SM101, we found that: (1) RelA is required for maintaining the efficient growth capacity of SM101 cells during vegetative conditions; (2) both RelA and DTD are required for spore formation and enterotoxin (CPE) production by SM101; (3) RelA/DTD activate CodY, which is known to activate spore formation and CPE production in SM101 by activating a key sporulation-specific σ factor F; (4) as expected, RelA/DTD activate sporulation-specific σ factors (σ^E, σ^F, σ^G and σ^K) by positively regulating Spo0A production; and finally (5) RelA, but not DTD, negatively regulates phospholipase C (PLC) production by repressing plc gene expression. Collectively, our results demonstrate that RelA modulates cellular physiology such as growth, spore formation and toxin production by C. perfringens type A strain SM101, although DTD also plays a role in these pleiotropic functions in coordination with RelA during sporulation. These findings have implications for the understanding of the mechanisms involved in the infectious cycle of C. perfringens.

Abundance, diversity and domain architecture variability in prokaryotic DNA-binding transcription factors

Gene regulation at the transcriptional level is a central process in all organisms, and DNA-binding transcription factors, known as TFs, play a fundamental role. This class of proteins usually binds at specific DNA sequences, activating or repressing gene expression. In general, TFs are composed of two domains: the DNA-binding domain (DBD) and an extra domain, which in this work we have named “companion domain” (CD). This latter could be involved in one or more functions such as ligand binding, protein-protein interactions or even with enzymatic activity. In contrast to DBDs, which have been widely characterized both experimentally and bioinformatically, information on the abundance, distribution, variability and possible role of the CDs is scarce. Here, we investigated these issues associated with the domain architectures of TFs in prokaryotic genomes. To this end, 19 families of TFs in 761 non-redundant bacterial and archaeal genomes were evaluated. In this regard we found four main groups based on the abundance and distribution in the analyzed genomes: i) LysR and TetR/AcrR; ii) AraC/XylS, SinR, and others; iii) Lrp, Fis, ArsR, and others; and iv) a group that included only two families, ArgR and BirA. Based on a classification of the organisms according to the life-styles, a major abundance of regulatory families in free-living organisms, in contrast with pathogenic, extremophilic or intracellular organisms, was identified. Finally, the protein architecture diversity associated to the 19 families considering a weight score for domain promiscuity evidenced which regulatory families were characterized by either a large diversity of CDs, here named as “promiscuous” families given the elevated number of variable domains found in those TFs, or a low diversity of CDs. Altogether this information helped us to understand the diversity and distribution of the 19 Prokaryotes TF families. Moreover, initial steps were taken to comprehend the variability of the extra domain in those TFs, which eventually might assist in evolutionary and functional studies.

Universal and idiosyncratic characteristic lengths in bacterial genomes

In condensed matter physics, simplified descriptions are obtained by coarse-graining the features of a system at a certain characteristic length, defined as the typical length beyond which some properties are no longer correlated. From a physics standpoint, in vitro DNA has thus a characteristic length of 300 base pairs (bp), the Kuhn length of the molecule beyond which correlations in its orientations are typically lost. From a biology standpoint, in vivo DNA has a characteristic length of 1000 bp, the typical length of genes. Since bacteria live in very different physico-chemical conditions and since their genomes lack translational invariance, whether larger, universal characteristic lengths exist is a non-trivial question. Here, we examine this problem by leveraging the large number of fully sequenced genomes available in public databases. By analyzing GC content correlations and the evolutionary conservation of gene contexts (synteny) in hundreds of bacterial chromosomes, we conclude that a fundamental characteristic length around 10-20 kb can be defined. This characteristic length reflects elementary structures involved in the coordination of gene expression, which are present all along the genome of nearly all bacteria. Technically, reaching this conclusion required us to implement methods that are insensitive to the presence of large idiosyncratic genomic features, which may co-exist along these fundamental universal structures.

The parasporal crystals of Bacillus pumilus strain 15.1: a potential virulence factor?

Bacillus pumilus strain 15.1 was previously found to cause larval mortality in the Med-fly Ceratitis capitata and was shown to produce crystals in association with the spore. As parasporal crystals are well-known as invertebrate-active toxins in entomopathogenic bacteria such as Bacillus thuringiensis (Cry and Cyt toxins) and Lysinibacillus sphaericus (Bin and Cry toxins), the B. pumilus crystals were characterized. The crystals were composed of a 45 kDa protein that was identified as an oxalate decarboxylase by peptide mass fingerprinting, N-terminal sequencing and by comparison with the genome sequence of strain 15.1. Synthesis of crystals by a plasmid-cured derivative of strain 15.1 (produced using a novel curing strategy), demonstrated that the oxalate decarboxylase was encoded chromosomally. Crystals spontaneously solubilized when kept at low temperatures, and the protein produced was resistant to trypsin treatment. The insoluble crystals produced by B. pumilus 15.1 did not show significant toxicity when bioassayed against C. capitata larvae, but once the OxdD protein was solubilized, an increase of toxicity was observed. We also demonstrate that the OxdD present in the crystals has oxalate decarboxylate activity as the formation of formate was detected, which suggests a possible mechanism for B. pumilus 15.1 activity. To our knowledge, the characterization of the B. pumilus crystals as oxalate decarboxylase is the first report of the natural production of parasporal inclusions of an enzyme.

The Genome-Scale Integrated Networks in Microorganisms

The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types) of the molecular networks, for example, genome-scale metabolic network (GMN), transcriptional regulatory network (TRN), and signal transduction network (STN). It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling) of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Genomics of Clostridium taeniosporum, an organism which forms endospores with ribbon-like appendages

Clostridium taeniosporum, a non-pathogenic anaerobe closely related to the C. botulinum Group II members, was isolated from Crimean lake silt about 60 years ago. Its endospores are surrounded by an encasement layer which forms a trunk at one spore pole to which about 12–14 large, ribbon-like appendages are attached. The genome consists of one 3,264,813 bp, circular chromosome (with 26.6% GC) and three plasmids. The chromosome contains 2,892 potential protein coding sequences: 2,124 have specific functions, 147 have general functions, 228 are conserved but without known function and 393 are hypothetical based on the fact that no statistically significant orthologs were found. The chromosome also contains 101 genes for stable RNAs, including 7 rRNA clusters. Over 84% of the protein coding sequences and 96% of the stable RNA coding regions are oriented in the same direction as replication. The three known appendage genes are located within a single cluster with five other genes, the protein products of which are closely related, in terms of sequence, to the known appendage proteins. The relatedness of the deduced protein products suggests that all or some of the closely related genes might code for minor appendage proteins or assembly factors. The appendage genes might be unique among the known clostridia; no statistically significant orthologs were found within other clostridial genomes for which sequence data are available. The C. taeniosporum chromosome contains two functional prophages, one Siphoviridae and one Myoviridae, and one defective prophage. Three plasmids of 5.9, 69.7 and 163.1 Kbp are present. These data are expected to contribute to future studies of developmental, structural and evolutionary biology and to potential industrial applications of this organism.

Detailed transcriptome analysis of the plant growth promoting Paenibacillus riograndensis SBR5 by using RNA-seq technology

BACKGROUND

The plant growth promoting rhizobacterium Paenibacillus riograndensis SBR5 is a promising candidate to serve as crop inoculant. Despite its potential in providing environmental and economic benefits, the species P. riograndensis is poorly characterized. Here, we performed for the first time a detailed transcriptome analysis of P. riograndensis SBR5 using RNA-seq technology.

RESULTS

RNA was isolated from P. riograndensis SBR5 cultivated under 15 different growth conditions and combined together in order to analyze an RNA pool representing a large set of expressed genes. The resultant total RNA was used to generate 2 different libraries, one enriched in 5'-ends of the primary transcripts and the other representing the whole transcriptome. Both libraries were sequenced and analyzed to identify the conserved sequences of ribosome biding sites and translation start motifs, and to elucidate operon structures present in the transcriptome of P. riograndensis. Sequence analysis of the library enriched in 5'-ends of the primary transcripts was used to identify 1082 transcription start sites (TSS) belonging to novel transcripts and allowed us to determine a promoter consensus sequence and regulatory sequences in 5' untranslated regions including riboswitches. A putative thiamine pyrophosphate dependent riboswitch upstream of the thiamine biosynthesis gene thiC was characterized by translational fusion to a fluorescent reporter gene and shown to function in P. riograndensis SBR5.

CONCLUSIONS

Our RNA-seq analysis provides insight into the P. riograndensis SBR5 transcriptome at the systems level and will be a valuable basis for differential RNA-seq analysis of this bacterium.

Determination and optimization of a strong promoter element from Bacillus amyloliquefaciens by using a promoter probe vector

OBJECTIVE

To construct a promoter probe vector, pBE-bgaB, to screen strong promoters from Bacillus amyloliquefaciens.

RESULTS

266 colonies containing active promoter elements from the genomic DNA of B. amyloliquefaciens were identified. Among these, promoter P41 exhibited the strongest β-Gal activity in Escherichia coli and B. amyloliquefaciens. Sequence analysis showed that promoter P41 contained P _ykuN , a ykuN gene encoding flavodoxin. Optimization of the ribosome-binding site from P41 to P₃₈₂ improved β-Gal activity by ~ 200%.

CONCLUSION

A new strong promoter for protein expression and genetic engineering of Bacillus species.

Eukaryotic and prokaryotic promoter databases as valuable tools in exploring the regulation of gene transcription: a comprehensive overview

The complete exploration of the regulation of gene expression remains one of the top-priority goals for researchers. As the regulation is mainly controlled at the level of transcription by promoters, study on promoters and findings are of great importance. This review summarizes forty selected databases that centralize experimental and theoretical knowledge regarding the organization of promoters, interacting transcription factors (TFs) and microRNAs (miRNAs) in many eukaryotic and prokaryotic species. The presented databases offer researchers valuable support in elucidating the regulation of gene transcription.

Dissecting the protein architecture of DNA-binding transcription factors in bacteria and archaea

Gene regulation at the transcriptional level is a central process in all organisms where DNA-binding transcription factors play a fundamental role. This class of proteins binds specifically at DNA sequences, activating or repressing gene expression as a function of the cell's metabolic status, operator context and ligand-binding status, among other factors, through the DNA-binding domain (DBD). In addition, TFs may contain partner domains (PaDos), which are involved in ligand binding and protein-protein interactions. In this work, we systematically evaluated the distribution, abundance and domain organization of DNA-binding TFs in 799 non-redundant bacterial and archaeal genomes. We found that the distributions of the DBDs and their corresponding PaDos correlated with the size of the genome. We also identified specific combinations between the DBDs and their corresponding PaDos. Within each class of DBDs there are differences in the actual angle formed at the dimerization interface, responding to the presence/absence of ligands and/or crystallization conditions, setting the orientation of the resulting helices and wings facing the DNA. Our results highlight the importance of PaDos as central elements that enhance the diversity of regulatory functions in all bacterial and archaeal organisms, and our results also demonstrate the role of PaDos in sensing diverse signal compounds. The highly specific interactions between DBDs and PaDos observed in this work, together with our structural analysis highlighting the difficulty in predicting both inter-domain geometry and quaternary structure, suggest that these systems appeared once and evolved with diverse duplication events in all the analysed organisms.

Genetic networks controlled by the bacterial replication initiator and transcription factor DnaA in Bacillus subtilis

DnaA is the widely conserved bacterial AAA+ ATPase that functions as both the replication initiator and a transcription factor. In many organisms, DnaA controls expression of its own gene and likely several others during growth and in response to replication stress. To evaluate the effects of DnaA on gene expression, separate from its role in replication initiation, we analyzed changes in mRNA levels in Bacillus subtilis cells with and without dnaA, using engineered strains in which dnaA is not essential. We found that dnaA was required for many of the changes in gene expression in response to replication stress. We also found that dnaA indirectly affected expression of several regulons during growth, including those controlled by the transcription factors Spo0A, AbrB, PhoP, SinR, RemA, Rok and YvrH. These effects were largely mediated by the effects of DnaA on expression of sda. DnaA activates transcription of sda, and Sda inhibits histidine protein kinases required for activation of the transcription factor Spo0A. We also found that loss of dnaA caused a decrease in the development of genetic competence. Together, our results indicate that DnaA plays an important role in modulating cell physiology, separate from its role in replication initiation.

The LacI family protein GlyR3 co-regulates the celC operon and manB in Clostridium thermocellum

BACKGROUND

Clostridium thermocellum utilizes a wide variety of free and cellulosomal cellulases and accessory enzymes to hydrolyze polysaccharides present in complex substrates. To date only a few studies have unveiled the details by which the expression of these cellulases are regulated. Recent studies have described the auto regulation of the celC operon and determined that the celC-glyR3-licA gene cluster and nearby manB-celT gene cluster are co-transcribed as polycistronic mRNA.

RESULTS

In this paper, we demonstrate that the GlyR3 protein mediates the regulation of manB. We first identify putative GlyR3 binding sites within or just upstream of the coding regions of manB and celT. Using an electrophoretic mobility shift assay (EMSA), we determined that a higher concentration of GlyR3 is required to effectively bind to the putative manB site in comparison to the celC site. Neither the putative celT site nor random DNA significantly binds GlyR3. While laminaribiose interfered with GlyR3 binding to the celC binding site, binding to the manB site was unaffected. In the presence of laminaribiose, in vivo transcription of the celC-glyR3-licA gene cluster increases, while manB expression is repressed, compared to in the absence of laminaribiose, consistent with the results from the EMSA. An in vitro transcription assay demonstrated that GlyR3 and laminaribiose interactions were responsible for the observed patters of in vivo transcription.

CONCLUSIONS

Together these results reveal a mechanism by which manB is expressed at low concentrations of GlyR3 but repressed at high concentrations. In this way, C. thermocellum is able to co-regulate both the celC and manB gene clusters in response to the availability of β-1,3-polysaccharides in its environment.

Kinetic modelling and meta-analysis of the B. subtilis SigA regulatory network during spore germination and outgrowth

This study describes the meta-analysis and kinetic modelling of gene expression control by sigma factor SigA of Bacillus subtilis during germination and outgrowth based on microarray data from 14 time points. The analysis computationally models the direct interaction among SigA, SigA-controlled sigma factor genes (sigM, sigH, sigD, sigX), and their target genes. Of the >800 known genes in the SigA regulon, as extracted from databases, 311 genes were analysed, and 190 were confirmed by the kinetic model as being controlled by SigA. For the remaining genes, alternative regulators satisfying kinetic constraints were suggested. The kinetic analysis suggested another 214 genes as potential SigA targets. The modelling was able to (i) create a particular SigA-controlled gene expression network that is active under the conditions for which the expression time series was obtained, and where SigA is the dominant regulator, (ii) suggest new potential SigA target genes, and (iii) find other possible regulators of a given gene or suggest a new mechanism of its control by identifying a matching profile of unknown regulator(s). Selected predicted regulatory interactions were experimentally tested, thus validating the model.

Transposition of insertion sequence IS256Bsu1 in Bacillus subtilis 168 is strictly dependent on recA

We developed an insertion sequence transposition detection system called the "jumping cat assay" and applied it to the Bacillus subtilis chromosome using IS256Bsu1 derived from B. subtilis natto. The high frequency of transposition enabled us to explore host factors; combining the assay and genetic analyses revealed that recA is essential for the transposition of IS256Bsu1. Detailed analyses using various domain mutants of recA demonstrated that this essentiality is not related to the function of recA in homologous recombination. Instead, the ATP binding and hydrolysis function seemed to be crucial for IS transposition. To elucidate the role of recA, we focused on the muB gene of the enterobacteriophage Mu. Based on information from the NCBI Conserved Domain Database, both MuB and RecA belong to the P-loop dNTPase superfamily. Further experiments revealed that muB complements the transposition-defective phenotype of a recA deletant, although it could not rescue UV sensitivity. These results suggest that recA shares a common function with muB that helps the transposition of IS256Bsu1 in B. subtilis.

SeqTU: A Web Server for Identification of Bacterial Transcription Units

A transcription unit (TU) consists of K ≥ 1consecutive genes on the same strand of a bacterial genome that are transcribed into a single mRNA molecule under certain conditions. Their identification is an essential step in elucidation of transcriptional regulatory networks. We have recently developed a machine-learning method to accurately identify TUs from RNA-seq data, based on two features of the assembled RNA reads: the continuity and stability of RNA-seq coverage across a genomic region. While good performance was achieved by the method on Escherichia coli and Clostridium thermocellum, substantial work is needed to make the program generally applicable to all bacteria, knowing that the program requires organism specific information. A web server, named SeqTU, was developed to automatically identify TUs with given RNA-seq data of any bacterium using a machine-learning approach. The server consists of a number of utility tools, in addition to TU identification, such as data preparation, data quality check and RNA-read mapping. SeqTU provides a user-friendly interface and automated prediction of TUs from given RNA-seq data. The predicted TUs are displayed intuitively using HTML format along with a graphic visualization of the prediction.

Transcription Profiling of Bacillus subtilis Cells Infected with AR9, a Giant Phage Encoding Two Multisubunit RNA Polymerases

Bacteriophage AR9 is a recently sequenced jumbo phage that encodes two multisubunit RNA polymerases. Here we investigated the AR9 transcription strategy and the effect of AR9 infection on the transcription of its host, Bacillus subtilis. Analysis of whole-genome transcription revealed early, late, and continuously expressed AR9 genes. Alignment of sequences upstream of the 5′ ends of AR9 transcripts revealed consensus sequences that define early and late phage promoters. Continuously expressed AR9 genes have both early and late promoters in front of them. Early AR9 transcription is independent of protein synthesis and must be determined by virion RNA polymerase injected together with viral DNA. During infection, the overall amount of host mRNAs is significantly decreased. Analysis of relative amounts of host transcripts revealed notable differences in the levels of some mRNAs. The physiological significance of up- or downregulation of host genes for AR9 phage infection remains to be established. AR9 infection is significantly affected by rifampin, an inhibitor of host RNA polymerase transcription. The effect is likely caused by the antibiotic-induced killing of host cells, while phage genome transcription is solely performed by viral RNA polymerases.

Phages regulate the timing of the expression of their own genes to coordinate processes in the infected cell and maximize the release of viral progeny. Phages also alter the levels of host transcripts. Here we present the results of a temporal analysis of the host and viral transcriptomes of Bacillus subtilis infected with a giant phage, AR9. We identify viral promoters recognized by two virus-encoded RNA polymerases that are a unique feature of the phiKZ-related group of phages to which AR9 belongs. Our results set the stage for future analyses of highly unusual RNA polymerases encoded by AR9 and other phiKZ-related phages.

A novel signal transduction protein: Combination of solute binding and tandem PAS-like sensor domains in one polypeptide chain

We report the structural and biochemical characterization of a novel periplasmic ligand-binding protein, Dret_0059, from Desulfohalobium retbaense DSM 5692, an organism isolated from Lake Retba, in Senegal. The structure of the protein consists of a unique combination of a periplasmic solute binding protein (SBP) domain at the N-terminal and a tandem PAS-like sensor domain at the C-terminal region. SBP domains are found ubiquitously, and their best known function is in solute transport across membranes. PAS-like sensor domains are commonly found in signal transduction proteins. These domains are widely observed as parts of many protein architectures and complexes but have not been observed previously within the same polypeptide chain. In the structure of Dret_0059, a ketoleucine moiety is bound to the SBP, whereas a cytosine molecule is bound in the distal PAS-like domain of the tandem PAS-like domain. Differential scanning flourimetry support the binding of ligands observed in the crystal structure. There is significant interaction between the SBP and tandem PAS-like domains, and it is possible that the binding of one ligand could have an effect on the binding of the other. We uncovered three other proteins with this structural architecture in the non-redundant sequence data base, and predict that they too bind the same substrates. The genomic context of this protein did not offer any clues for its function. We did not find any biological process in which the two observed ligands are coupled. The protein Dret_0059 could be involved in either signal transduction or solute transport.

Sigma Factor Regulated Cellular Response in a Non-solvent Producing Clostridium beijerinckii Degenerated Strain: A Comparative Transcriptome Analysis

Clostridium beijerinckii DG-8052, derived from NCIMB 8052, cannot produce solvent or form spores, a phenomenon known as degeneration. To explore the mechanisms of degeneration at the gene level, transcriptomic profiles of the wild-type 8052 and DG-8052 strains were compared. Expression of 5168 genes comprising 98.6% of the genome was assessed. Interestingly, 548 and 702 genes were significantly up-regulated in the acidogenesis and solventogenesis phases of DG-8052, respectively, and mainly responsible for the phosphotransferase system, sugar metabolic pathways, and chemotaxis; meanwhile, 699 and 797 genes were significantly down-regulated, respectively, and mainly responsible for sporulation, oxidoreduction, and solventogenesis. The functions of some altered genes, including 286 and 333 at the acidogenesis and solventogenesis phases, respectively, remain unknown. Dysregulation of the fermentation machinery was accompanied by lower transcription levels of glycolysis rate-limiting enzymes (pfk and pyk), and higher transcription of cell chemotaxis genes (cheA, cheB, cheR, cheW, and cheY), controlled mainly by σ⁵⁴ at acidogenesis. Meanwhile, abnormal spore formation was associated with repressed spo0A, sigE, sigF, sigG, and sigK which are positively regulated by σ⁷⁰, and correspondingly inhibited expression of CoA-transferase at the solventogenesis phase. These findings indicated that morphological and physiological changes in the degenerated Clostridium strain may be related to altered expression of sigma factors, providing valuable targets for strain development of Clostridium species.