High accuracy operon prediction method based on STRING database scores

Deep learning of multimodal networks with topological regularization for drug repositioning

MOTIVATION

Computational techniques for drug-disease prediction are essential in enhancing drug discovery and repositioning. While many methods utilize multimodal networks from various biological databases, few integrate comprehensive multi-omics data, including transcriptomes, proteomes, and metabolomes. We introduce STRGNN, a novel graph deep learning approach that predicts drug-disease relationships using extensive multimodal networks comprising proteins, RNAs, metabolites, and compounds. We have constructed a detailed dataset incorporating multi-omics data and developed a learning algorithm with topological regularization. This algorithm selectively leverages informative modalities while filtering out redundancies.

RESULTS

STRGNN demonstrates superior accuracy compared to existing methods and has identified several novel drug effects, corroborating existing literature. STRGNN emerges as a powerful tool for drug prediction and discovery. The source code for STRGNN, along with the dataset for performance evaluation, is available at https://github.com/yuto-ohnuki/STRGNN.git .

Systematic elucidation of independently modulated genes in Lactiplantibacillus plantarum reveals a trade-off between secondary and primary metabolism

Lactiplantibacillus plantarum is a probiotic bacterium widely used in food and health industries, but its gene regulatory information is limited in existing databases, which impedes the research of its physiology and its applications. To obtain a better understanding of the transcriptional regulatory network of L. plantarum, independent component analysis of its transcriptomes was used to derive 45 sets of independently modulated genes (iModulons). Those iModulons were annotated for associated transcription factors and functional pathways, and active iModulons in response to different growth conditions were identified and characterized in detail. Eventually, the analysis of iModulon activities reveals a trade-off between regulatory activities of secondary and primary metabolism in L. plantarum.

The Azotobacter vinelandii AlgU regulon during vegetative growth and encysting conditions: A proteomic approach

In the Pseduomonadacea family, the extracytoplasmic function sigma factor AlgU is crucial to withstand adverse conditions. Azotobacter vinelandii, a closed relative of Pseudomonas aeruginosa, has been a model for cellular differentiation in Gram-negative bacteria since it forms desiccation-resistant cysts. Previous work demonstrated the essential role of AlgU to withstand oxidative stress and on A. vinelandii differentiation, particularly for the positive control of alginate production. In this study, the AlgU regulon was dissected by a proteomic approach under vegetative growing conditions and upon encystment induction. Our results revealed several molecular targets that explained the requirement of this sigma factor during oxidative stress and extended its role in alginate production. Furthermore, we demonstrate that AlgU was necessary to produce alkyl resorcinols, a type of aromatic lipids that conform the cell membrane of the differentiated cell. AlgU was also found to positively regulate stress resistance proteins such as OsmC, LEA-1, or proteins involved in trehalose synthesis. A position-specific scoring-matrix (PSSM) was generated based on the consensus sequence recognized by AlgU in P. aeruginosa, which allowed the identification of direct AlgU targets in the A. vinelandii genome. This work further expands our knowledge about the function of the ECF sigma factor AlgU in A. vinelandii and contributes to explains its key regulatory role under adverse conditions.

Disorder and amino acid composition in proteins: their potential role in the adaptation of extracellular pilins to the acidic media, where Acidithiobacillus thiooxidans grows

There are few biophysical studies or structural characterizations of the type IV pilin system of extremophile bacteria, such as the acidophilic Acidithiobacillus thiooxidans. We set out to analyze their pili-comprising proteins, pilins, because these extracellular proteins are in constant interaction with protons of the acidic medium in which At. thiooxidans grows. We used the web server Operon Mapper to analyze and identify the cluster codified by the minor pilin of At. thiooxidans. In addition, we carried an in-silico characterization of such pilins using the VL-XT algorithm of PONDR® server. Our results showed that structural disorder prevails more in pilins of At. thiooxidans than in non-acidophilic bacteria. Further computational characterization showed that the pilins of At. thiooxidans are significantly enriched in hydroxy (serine and threonine) and amide (glutamine and asparagine) residues, and significantly reduced in charged residues (aspartic acid, glutamic acid, arginine and lysine). Similar results were obtained when comparing pilins from other Acidithiobacillus and other acidophilic bacteria from another genus versus neutrophilic bacteria, suggesting that these properties are intrinsic to pilins from acidic environments, most likely by maintaining solubility and stability in harsh conditions. These results give guidelines for the application of extracellular proteins of acidophiles in protein engineering.

Antisense-acting riboswitches: A poorly characterized yet important model of transcriptional regulation in prokaryotic organisms

Riboswitches are RNA elements involved in regulating genes that participate in the biosynthesis or transport of essential metabolites. They are characterized by their ability to recognize their target molecules with high affinity and specificity. Riboswitches are commonly cotranscribed with their target genes and are located at the 5' end of their transcriptional units. To date, only two exceptional cases of riboswitches being situated at the 3' end and transcribing in the antisense direction of their regulated genes have been described. The first case involves a SAM riboswitch located at the 3' end of the ubiG-mccB-mccA operon in Clostridium acetobutylicum involved in converting methionine to cysteine. The second case concerns a Cobalamin riboswitch in Listeria monocytogenes that regulates the transcription factor PocR related to this organism's pathogenic process. In almost a decade since the first descriptions of antisense-acting riboswitches, no new examples have been described. In this work, we performed a computational analysis to identify new examples of antisense-acting riboswitches. We found 292 cases in which, according to the available information, we infer that the expected regulation of the riboswitch is consistent with the signaling molecule it senses and the metabolic function of the regulated gene. The metabolic implications of this novel type of regulation are thoroughly discussed.

Proteome-wide analysis of lysine 2-hydroxyisobutyrylation in Frankliniella occidentalis

BACKGROUND

Lysine 2-hydroxyisobutyrylation (Khib) is a novel and conserved post-translational modification (PTM). Frankliniella occidentalis are economically important agricultural pests globally and also notorious for vectoring destructive plant viruses. To better study the disease transmission mechanism of F. occidentalis, it is necessary to conduct in-depth analysis of it. So far, no Khib modification of insects has been reported.

RESULTS

In this study, a proteome-wide analysis of Khib modifications in F. occidentalis was analyzed for the first time through the combination of high performance liquid chromatography fractionation technology and 2-hydroxyisobutyrylated peptide enrichment and other advanced technologies, 4093 Khib sites were identified on 1125 modified proteins. Bioinformatics and functional enrichment analyses showed that Khib-modified proteins were significantly enriched in many cell compartments and pathways, especially related to various cellular components and biological processes, and were more concentrated in ribosomes and proteasome subunits, involved in energy metabolism, protein synthesis and degradation, compared to the other nine species including Japonica rice, Homo sapiens, P. patens, Botrytis, Ustilaginoidea virens, Saccharomyces cerevisiae, T. gondii, C. albicans, and F. oxysporum. And Khib sites on virus-interacting insect proteins were discovered for the first time, such as cyclophilin and endoCP-GN.

CONCLUSIONS

After three repeated experiments, we found a total of 4093 Khib sites on 1125 proteins. These modified proteins are mainly concentrated in ribosomes and proteasome subunits, and are widely involved in a variety of critical biological activities and metabolic processes of F. occidentalis. In addition, for the first time, Khib modification sites are found on the proteome of F. occidentalis, and these sites could be acted as for the virus interaction, including cyclophilin and endoCP-GN. The global map of 2-hydroxyisobutyrylation in thrips is an invaluable resource to better understand the biological processes of thrips and provide new means for disease control and mitigation of pest damage to crops.

Current and emerging tools of computational biology to improve the detoxification of mycotoxins

Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we will focus on mycotoxins-fungi-produced toxins that contaminate food and feed-and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.

A novel computational framework for genome-scale alternative transcription units prediction

Alternative transcription units (ATUs) are dynamically encoded under different conditions and display overlapping patterns (sharing one or more genes) under a specific condition in bacterial genomes. Genome-scale identification of ATUs is essential for studying the emergence of human diseases caused by bacterial organisms. However, it is unrealistic to identify all ATUs using experimental techniques because of the complexity and dynamic nature of ATUs. Here, we present the first-of-its-kind computational framework, named SeqATU, for genome-scale ATU prediction based on next-generation RNA-Seq data. The framework utilizes a convex quadratic programming model to seek an optimum expression combination of all of the to-be-identified ATUs. The predicted ATUs in Escherichia coli reached a precision of 0.77/0.74 and a recall of 0.75/0.76 in the two RNA-Sequencing datasets compared with the benchmarked ATUs from third-generation RNA-Seq data. In addition, the proportion of 5'- or 3'-end genes of the predicted ATUs, having documented transcription factor binding sites and transcription termination sites, was three times greater than that of no 5'- or 3'-end genes. We further evaluated the predicted ATUs by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses. The results suggested that gene pairs frequently encoded in the same ATUs are more functionally related than those that can belong to two distinct ATUs. Overall, these results demonstrated the high reliability of predicted ATUs. We expect that the new insights derived by SeqATU will not only improve the understanding of the transcription mechanism of bacteria but also guide the reconstruction of a genome-scale transcriptional regulatory network.

Profiles of Two Glycaemia Modifying Drugs on the Expression of Rat and Human Sulfotransferases

AIMS

To study the effects of blood glucose regulating compounds on human and rat sulfotransferases (SULTs) expressions.

BACKGROUND

Phase-II enzymes, sulfotransferases catalyze the sulfuryl-group-transfer to endogenous/exogenous compounds. The alteration of expressions of SULTs may have influence on the sulfation of its substrate and other biomolecules.

OBJECTIVES

The influence of the altered biotransformation might alter different biochemical events, drug-drug interactions and bioaccumulation or excretion pattern of certain drug.

METHODS

In this brief study, diabetes-inducing drug streptozotocin (STZ; 10 or 50 mg/kg to male Sprague Dawley rat for 2 weeks) or hyperglycemia controlling drug tolbutamide (TLB 0.1 or 10μM to human hepato-carcinoma cells, HepG2 for 10 days) was applied and the SULTs expressions were verified. Extensive protein-protein (STa, SULT2A1/DHEAST) interactions were studied by the STRING (Search-Tool-for-the-Retrieval-of-Interacting Genes/Proteins) Bioinformatics-software.

RESULTS

Present result suggests that while STZ increased the STa (in rat) (dehydroepiandrosterone catalyzing SULT; DHEAST in human HepG2), tolbutamide decreased PPST (phenol catalyzing SULT) and DHEAST activity in human HepG2 cells. Moderate decreases of MPST (monoamine catalyzing SULT) and EST (estrogen catalyzing) activities are noticed in this case. STa/DHEAST was found to be highly interactive to SHBG/- sex-hormone-binding-globulin; PPARα/lipid-metabolism-regulator; FABP1/fatty-acid-binding-protein.

CONCLUSION

Streptozotocin and tolbutamide, these two glycaemia-modifying drugs demonstrated regulation of rat and human SULTs activities. The reciprocal nature of these two drugs on SULTs expression may be associated with their contrasting abilities in influencing glucose-homeostasis. Possible association of certain SULT-isoform with hepatic fat-regulations may indicate an unfocused link between calorie-metabolism and the glycemic-state of an individual. Explorations of this work may uncover the role of sulfation metabolism of specific biomolecule on cellular glycemic regulation.

Detecting operons in bacterial genomes via visual representation learning

Contiguous genes in prokaryotes are often arranged into operons. Detecting operons plays a critical role in inferring gene functionality and regulatory networks. Human experts annotate operons by visually inspecting gene neighborhoods across pileups of related genomes. These visual representations capture the inter-genic distance, strand direction, gene size, functional relatedness, and gene neighborhood conservation, which are the most prominent operon features mentioned in the literature. By studying these features, an expert can then decide whether a genomic region is part of an operon. We propose a deep learning based method named Operon Hunter that uses visual representations of genomic fragments to make operon predictions. Using transfer learning and data augmentation techniques facilitates leveraging the powerful neural networks trained on image datasets by re-training them on a more limited dataset of extensively validated operons. Our method outperforms the previously reported state-of-the-art tools, especially when it comes to predicting full operons and their boundaries accurately. Furthermore, our approach makes it possible to visually identify the features influencing the network’s decisions to be subsequently cross-checked by human experts.

Prediction and analysis of metagenomic operons via MetaRon: a pipeline for prediction of Metagenome and whole-genome opeRons

Background

Efficient regulation of bacterial genes in response to the environmental stimulus results in unique gene clusters known as operons. Lack of complete operonic reference and functional information makes the prediction of metagenomic operons a challenging task; thus, opening new perspectives on the interpretation of the host-microbe interactions.

Results

In this work, we identified whole-genome and metagenomic operons via MetaRon (Metagenome and whole-genome opeRon prediction pipeline). MetaRon identifies operons without any experimental or functional information. MetaRon was implemented on datasets with different levels of complexity and information. Starting from its application on whole-genome to simulated mixture of three whole-genomes (E. coli MG1655, Mycobacterium tuberculosis H37Rv and Bacillus subtilis str. 16), E. coli c20 draft genome extracted from chicken gut and finally on 145 whole-metagenome data samples from human gut. MetaRon consistently achieved high operon prediction sensitivity, specificity and accuracy across E. coli whole-genome (97.8, 94.1 and 92.4%), simulated genome (93.7, 75.5 and 88.1%) and E. coli c20 (87, 91 and 88%,), respectively. Finally, we identified 1,232,407 unique operons from 145 paired-end human gut metagenome samples. We also report strong association of type 2 diabetes with Maltose phosphorylase (K00691), 3-deoxy-D-glycero-D-galacto-nononate 9-phosphate synthase (K21279) and an uncharacterized protein (K07101).

Conclusion

With MetaRon, we were able to remove two notable limitations of existing whole-genome operon prediction methods: (1) generalizability (ability to predict operons in unrelated bacterial genomes), and (2) whole-genome and metagenomic data management. We also demonstrate the use of operons as a subset to represent the trends of secondary metabolites in whole-metagenome data and the role of secondary metabolites in the occurrence of disease condition. Using operonic data from metagenome to study secondary metabolic trends will significantly reduce the data volume to more precise data. Furthermore, the identification of metabolic pathways associated with the occurrence of type 2 diabetes (T2D) also presents another dimension of analyzing the human gut metagenome. Presumably, this study is the first organized effort to predict metagenomic operons and perform a detailed analysis in association with a disease, in this case type 2 diabetes. The application of MetaRon to metagenomic data at diverse scale will be beneficial to understand the gene regulation and therapeutic metagenomics.

STING controls intestinal homeostasis through promoting antimicrobial peptide expression in epithelial cells

Stimulator of interferon genes (STING) has been shown to play a critical role in orchestrating immune responses to various pathogens through sensing cyclic dinucleotides. However, how STING regulates intestinal homeostasis is still not completely understood. In this study, we found that STING^-/- mice were more susceptible to enteric infection with Citrobacter rodentium compared to wild-type (WT) mice evidenced by more severe intestinal inflammation and impaired bacterial clearance. STING^-/- mice demonstrated lower expression of REG3γ but not β-defensins and Cramp in IECs. Consistently, STING^-/- IECs showed reduced capacity to inhibit bacterial growth. STING agonists, both 10-carboxymethyl-9-acridanone (CMA) and 5,6-dimethylxanthenone-4-acetic acid (DMXAA), promoted REG3γ expression IECs. Furthermore, STING agonists promoted WT but not REG3γ-deficient IEC bacterial killing. Mechanistically, STING agonists activated STAT3 and promoted glycolysis in IECs. Inhibition of STAT3 pathway and glycolysis suppressed STING-induced REG3γ production in IECs, and abrogated STING-mediated IEC killing of C. rodentium. Additionally, treatment with the STING ligand, 2,3-cGAMP, inhibited C. rodentium-induced colitis in vivo. Overall, STING promotes IEC REG3γ expression to inhibit enteric infection and intestinal inflammation, thus, maintaining the intestinal homeostasis.

Structure and Evolution of Acinetobacter baumannii Plasmids

Acinetobacter baumannii is an emergent bacterial pathogen that provokes many types of infections in hospitals around the world. The genome of this organism consists of a chromosome and plasmids. These plasmids vary over a wide size range and many of them have been linked to the acquisition of antibiotic-resistance genes. Our bioinformatic analyses indicate that A. baumannii plasmids belong to a small number of plasmid lineages. The general structure of these lineages seems to be very stable and consists not only of genes involved in plasmid maintenance functions but of gene sets encoding poorly characterized proteins, not obviously linked to survival in the hospital setting, and opening the possibility that they improve the parasitic properties of plasmids. An analysis of genes involved in replication, suggests that members of the same plasmid lineage are part of the same plasmid incompatibility group. The same analysis showed the necessity of classifying the Rep proteins in ten new groups, under the scheme proposed by Bertini et al. (2010). Also, we show that some plasmid lineages have the potential capacity to replicate in many bacterial genera including those embracing human pathogen species, while others seem to replicate only within the limits of the Acinetobacter genus. Moreover, some plasmid lineages are widely distributed along the A. baumannii phylogenetic tree. Despite this, a number of them lack genes involved in conjugation or mobilization functions. Interestingly, only 34.6% of the plasmids analyzed here possess antibiotic resistance genes and most of them belong to fourteen plasmid lineages of the twenty one described here. Gene flux between plasmid lineages appears primarily limited to transposable elements, which sometimes carry antibiotic resistance genes. In most plasmid lineages transposable elements and antibiotic resistance genes are secondary acquisitions. Finally, broad host-range plasmids appear to have played a crucial role.

Mining the proliferative diabetic retinopathy-associated genes and pathways by integrated bioinformatic analysis

PURPOSE

Diabetic retinopathy (DR) especially proliferative diabetic retinopathy (PDR) is a serious eye disease. We aimed to identify key pathway and hub genes associated with PDR by analyzing the expression of retinal fibrovascular tissue in PDR patients.

METHODS

First raw data were downloaded from the Gene Expression Omnibus database. Median normalization was subsequently applied to preprocess. Differentially expressed genes (DEGs) analyzed with the Limma package. Weighted correlation network analysis (WGCNA) was utilized to build the co-expression network for all genes. Then, we compared the DEGs and modules filtered out by WGCNA. A protein-protein interaction network based on the STRING web site and the Cytoscape software was constructed by the overlapping DEGs. Next, the Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Finally, we used the Comparative Toxicogenomics Database to identify some important pathways and hub genes tightly related to PDR.

RESULTS

Functional enrichment analysis showed that the pathway of cytokine-cytokine receptor interaction was significantly related to PDR eight hub genes which were associated with pathway including tumor necrosis factor (TNF), tumor necrosis factor receptor superfamily member 12A (TNFRSF12A), C-C chemokine 20 (CCL20), chemokine (C-X-C motif) ligand 2 (CXCL2), oncostatin M (OSM) interleukin 10 (IL10), interleukin 15 (IL 15), and interleukin 1B (IL1B).

CONCLUSIONS

We identified one pathway and eight hub genes, which were associated with PDR. The pathway provided references that will advance the understanding of mechanisms of PDR. Moreover, the hub genes may serve as therapeutic targets for precise diagnosis and treatment of PDR in the future.

The actinobacterium Tsukamurella paurometabola has a functionally divergent arylamine N-acetyltransferase (NAT) homolog

Actinobacteria in the Tsukamurella genus are aerobic, high-GC, Gram-positive mycolata, considered as opportunistic pathogens and isolated from various environmental sources, including sites contaminated with oil, urban or industrial waste and pesticides. Although studies look into xenobiotic biotransformation by Tsukamurella isolates, the relevant enzymes remain uncharacterized. We investigated the arylamine N-acetyltransferase (NAT) enzyme family, known for its role in the xenobiotic metabolism of prokaryotes and eukaryotes. Xenobiotic sensitivity of Tsukamurella paurometabola type strain DSM 20162^T was assessed, followed by cloning, recombinant expression and functional characterization of its single NAT homolog (TSUPD)NAT1. The bacterium appeared quite robust against chloroanilines, but more sensitive to 4-anisidine and 2-aminophenol. However, metabolic activity was not evident towards those compounds, presumably due to mechanisms protecting cells from xenobiotic entry. Of the pharmaceutical arylhydrazines tested, hydralazine was toxic, but the bacterium was less sensitive to isoniazid, a drug targeting mycolic acid biosynthesis in mycobacteria. Although (TSUPD)NAT1 protein has an atypical Cys-His-Glu (instead of the expected Cys-His-Asp) catalytic triad, it is enzymatically active, suggesting that this deviation is likely due to evolutionary adaptation potentially serving a different function. The protein was indeed found to use malonyl-CoA, instead of the archetypal acetyl-CoA, as its preferred donor substrate. Malonyl-CoA is important for microbial biosynthesis of fatty acids (including mycolic acids) and polyketide chains, and the corresponding enzymatic systems have common evolutionary histories, also linked to xenobiotic metabolism. This study adds to accummulating evidence suggesting broad phylogenetic and functional divergence of microbial NAT enzymes that goes beyond xenobiotic metabolism and merits investigation.

Handling Noise in Protein Interaction Networks

Protein-protein interactions (PPIs) can be conveniently represented as networks, allowing the use of graph theory for their study. Network topology studies may reveal patterns associated with specific organisms. Here, we propose a new methodology to denoise PPI networks and predict missing links solely based on the network topology, the organization measurement (OM) method. The OM methodology was applied in the denoising of the PPI networks of two Saccharomyces cerevisiae datasets (Yeast and CS2007) and one Homo sapiens dataset (Human). To evaluate the denoising capabilities of the OM methodology, two strategies were applied. The first strategy compared its application in random networks and in the reference set networks, while the second strategy perturbed the networks with the gradual random addition and removal of edges. The application of the OM methodology to the Yeast and Human reference sets achieved an AUC of 0.95 and 0.87, in Yeast and Human networks, respectively. The random removal of 80% of the Yeast and Human reference set interactions resulted in an AUC of 0.71 and 0.62, whereas the random addition of 80% interactions resulted in an AUC of 0.75 and 0.72, respectively. Applying the OM methodology to the CS2007 dataset yields an AUC of 0.99. We also perturbed the network of the CS2007 dataset by randomly inserting and removing edges in the same proportions previously described. The false positives identified and removed from the network varied from 97%, when inserting 20% more edges, to 89%, when 80% more edges were inserted. The true positives identified and inserted in the network varied from 95%, when removing 20% of the edges, to 40%, after the random deletion of 80% edges. The OM methodology is sensitive to the topological structure of the biological networks. The obtained results suggest that the present approach can efficiently be used to denoise PPI networks.

Prediction of protein architectures involved in the signaling-pathway initiating sporulation in Firmicutes

Objectives

Like many other proteins, those belonging to the signal transduction cascade initiating sporulation (Spo0 pathway) have conserved protein domains (Capra and Laub in Annu Rev Microbiol 66:325–47, 2012). Improvements in bioinformatics applications to discover proteins involved in the initiation of the sporulating cascade in newly sequenced genomes is an important task that requires rigorous comparative genomic methods and manual curation to identify endospore-forming bacteria. This note aims to present a collection of predicted proteins involved in the Spo0 pathway found in the proteomes of fully sequenced and manually curated endospore-forming Firmicutes species. This collection may serve as a guide to conduct future experiments in endospore formers in genomic and metagenomic projects.

Data description

Similar to the report of Davidson et al. (PLoS Genet 14:1–33, 2018), we used Pfam profiles (El-Gebali et al. in Nucleic Acids Res 47:D427–32, 2019) defining each protein and the genomic context surrounding the query gene to predict probable orthologs of the Spo0 pathway in Firmicutes. We present in this note a collection of 325 Firmicutes species organized by phylogenetic class and classified as spore formers, non-spore formers or unknown spore phenotype based on published literature, for which we predicted probable orthologs defining the signal transduction pathway initiating sporulation.

Operon-mapper: a web server for precise operon identification in bacterial and archaeal genomes

Summary

Operon-mapper is a web server that accurately, easily and directly predicts the operons of any bacterial or archaeal genome sequence. The operon predictions are based on the intergenic distance of neighboring genes as well as the functional relationships of their protein-coding products. To this end, Operon-mapper finds all the ORFs within a given nucleotide sequence, along with their genomic coordinates, orthology groups and functional relationships. We believe that Operon-mapper, due to its accuracy, simplicity and speed, as well as the relevant information that it generates, will be a useful tool for annotating and characterizing genomic sequences.

Availability and implementation

http://biocomputo.ibt.unam.mx/operon_mapper/

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/.

Oxidant stress induction and signalling in xenografted (human breast cancer-tissues) plus estradiol treated or N-ethyl-N-nitrosourea treated female rats via altered estrogen sulfotransferase (rSULT1E1) expressions and SOD1/catalase regulations

N-ethyl-N-nitrosourea (ENU) is highly used in rodent models of tumerogenesis/carcinogenesis. Xenografting human-cancer tissues/cells with estradiol (E2) treatment is also used to generate rodent-models of gynaecological cancers. The altered metabolic-redox environment leading to establishment of pre-tumorigenesis condition and their mechanism are less studied. Here, female Wister rats were treated with these drugs at their pre-tumerogenic dosage (one group ENU single intra-peritoneal dose of 90 mg/kg b.w. and another group were implanted with human breast tumor (stage-IIIB) and fed with 2.5 mg of 17β-estradiol once in a week for 4 months). After 4 months, animals were sacrificed; their serum and liver tissues were tested. A brief comparison was made with a rat model (regarded as positive control) of toxicity induced by mutagenic environmental pollutant arsenic (0.6 ppm daily/4 weeks). The increase in serum alkaline phosphatase and glutamate-pyruvate transaminase suggests the possible organ toxicity is favoured by the increase in hepatic/systemic free radicals and oxidative stress in all drug application models. But the increase in the serum E2 level as noted in the ELISA data with impairment in the hepatic estrogen sulfotransferase (SULT1E1) protein expression (immuno-blot data) were noticed with interfered hepatic free-thiols only in ENU and xenograft-E2 group compared to arsenic group. It is also evident in the in vitro result from E2/GSH/NAC added hepatic slices with altered antioxidant regulations. Moreover, impairment in hepatic SOD1, catalase and glutathiole peroxidase activities (PAGEzymographic data), especially in the ENU-treated group makes them more vulnerable to the oxidative threat in creating pre-tumerogenic microenvironment. This is evident in the result of their higher DNA-damage and histological abnormalities. The Bioinformatics study revealed an important role of rSULT1E1 in the regulations of E2 metabolism. This study is important for the exploration of the pre-tumerogenic condition by ENU and E2 by impairing SULT1E1 expression and E2 regulations via oxidant-stress signalling. The finding may help to find new therapeutic-targets to treat gynaecological-cancers more effectively.

Design Strategy of Multi-electron Transfer Catalysts Based on a Bioinformatic Analysis of Oxygen Evolution and Reduction Enzymes

Understanding the design strategy of photosynthetic and respiratory enzymes is important to develop efficient artificial catalysts for oxygen evolution and reduction reactions. Here, based on a bioinformatic analysis of cyanobacterial oxygen evolution and reduction enzymes (photosystem II: PS II and cytochrome c oxidase: COX, respectively), the gene encoding the catalytic D1 subunit of PS II was found to be expressed individually across 38 phylogenetically diverse strains, which is in contrast to the operon structure of the genes encoding major COX subunits. Selective synthesis of the D1 subunit minimizes the repair cost of PS II, which allows compensation for its instability by lowering the turnover number required to generate a net positive energy yield. The different bioenergetics observed between PS II and COX suggest that in addition to the catalytic activity rationalized by the Sabatier principle, stability factors have also provided a major influence on the design strategy of biological multi-electron transfer enzymes.

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.

Detection of retromer assembly in Plasmodium falciparum by immunosensing coupled to Surface Plasmon Resonance

Retromer complex plays a crucial role in intracellular protein trafficking and is conserved throughout the eukaryotes including malaria parasite, Plasmodium falciparum, where it is partially conserved. The assembly of retromer complex in RBC stages of malarial parasite is extremely difficult to explore because of its complicated physiology, small size, and intra-erythrocytic location. Nonetheless, understanding of retromer assembly may pave new ways for the development of novel antimalarials targeting parasite-specific protein trafficking pathways. Here, we investigated the assembly of retromer complex in P. falciparum, by an immunosensing method through highly sensitive Surface Plasmon Resonance (SPR) technique. After taking leads from the bioinformatics search and literature, different interacting proteins were identified and specific antibodies were raised against them. The sensor chip was prepared by covalently linking antibody specific to one component and the whole cell lysate was passed through it in order to trap the interacting complex. Antibodies raised against other interacting components were used to detect them in the trapped complex on the SPR chip. We were able to detect three different components in the retromer complex trapped by the immobilized antibody specific against a different component on a sensor chip. The assay was reproduced and validated in a different two-component CD74-MIF system in mammalian cells. We, thus, illustrate the assembly of retromer complex in P. falciparum through a bio-sensing approach that combines SPR with immunosensing requiring a very small amount of sample from the native source.

1,2-Diacylglycerol choline phosphotransferase catalyzes the final step in the unique Treponema denticola phosphatidylcholine biosynthesis pathway

Treponema denticola synthesizes phosphatidylcholine through a licCA-dependent CDP-choline pathway identified only in the genus Treponema. However, the mechanism of conversion of CDP-choline to phosphatidylcholine remained unclear. We report here characterization of TDE0021 (herein designated cpt) encoding a 1,2-diacylglycerol choline phosphotransferase homologous to choline phosphotransferases that catalyze the final step of the highly conserved Kennedy pathway for phosphatidylcholine synthesis in eukaryotes. T. denticola Cpt catalyzed in vitro phosphatidylcholine formation from CDP-choline and diacylglycerol, and full activity required divalent manganese. Allelic replacement mutagenesis of cpt in T. denticola resulted in abrogation of phosphatidylcholine synthesis. T. denticola Cpt complemented a Saccharomyces cerevisiae CPT1 mutant, and expression of the entire T. denticola LicCA-Cpt pathway in E. coli resulted in phosphatidylcholine biosynthesis. Our findings show that T. denticola possesses a unique phosphatidylcholine synthesis pathway combining conserved prokaryotic choline kinase and CTP:phosphocholine cytidylyltransferase activities with a 1,2-diacylglycerol choline phosphotransferase that is common in eukaryotes. Other than in a subset of mammalian host-associated Treponema that includes T. pallidum, this pathway is found in neither bacteria nor Archaea. Molecular dating analysis of the Cpt gene family suggests that a horizontal gene transfer event introduced this gene into an ancestral Treponema well after its divergence from other spirochetes.

Investigating Evolutionary Dynamics of RHA1 Operons

Grouping genes as operons is an important genomic feature of prokaryotic organisms. The comprehensive understanding of the operon organizations would be helpful to decipher transcriptional mechanisms, cellular pathways, and the evolutionary landscape of prokaryotic genomes. Although thousands of prokaryotes have been sequenced, genome-wide investigation of the evolutionary dynamics (division and recombination) of operons among these genomes remains unexplored. Here, we systematically analyzed the operon dynamics of Rhodococcus jostii RHA1 (RHA1), an oleaginous bacterium with high potential applications in biofuel, by comparing 340 prokaryotic genomes that were carefully selected from different genera. Interestingly, 99% of RHA1 operons were observed to exhibit evolutionary events of division and recombination among the 340 compared genomes. An operon that encodes all enzymes related to histidine biosynthesis in RHA1 (His-operon) was found to be segmented into smaller gene groups (sub-operons) in diverse genomes. These sub-operons were further reorganized with different functional genes as novel operons that are related to different biochemical processes. Comparatively, the operons involved in the functional categories of lipid transport and metabolism are relatively conserved among the 340 compared genomes. At the pathway level, RHA1 operons found to be significantly conserved were involved in ribosome synthesis, oxidative phosphorylation, and fatty acid synthesis. These analyses provide evolutionary insights of operon organization and the dynamic associations of various biochemical pathways in different prokaryotes.

The archaeal Ced system imports DNA

The intercellular transfer of DNA is a phenomenon that occurs in all domains of life and is a major driving force of evolution. Upon UV-light treatment, cells of the crenarchaeal genus Sulfolobus express Ups pili, which initiate cell aggregate formation. Within these aggregates, chromosomal DNA, which is used for the repair of DNA double-strand breaks, is exchanged. Because so far no clear homologs of bacterial DNA transporters have been identified among the genomes of Archaea, the mechanisms of archaeal DNA transport have remained a puzzling and underinvestigated topic. Here we identify saci_0568 and saci_0748, two genes from Sulfolobus acidocaldarius that are highly induced upon UV treatment, encoding a transmembrane protein and a membrane-bound VirB4/HerA homolog, respectively. DNA transfer assays showed that both proteins are essential for DNA transfer between Sulfolobus cells and act downstream of the Ups pili system. Our results moreover revealed that the system is involved in the import of DNA rather than the export. We therefore propose that both Saci_0568 and Saci_0748 are part of a previously unidentified DNA importer. Given the fact that we found this transporter system to be widely spread among the Crenarchaeota, we propose to name it the Crenarchaeal system for exchange of DNA (Ced). In this study we have for the first time to our knowledge described an archaeal DNA transporter.

An analysis of the validity and utility of the proximon proposition

The utilization of metagenomic functional interactions represents a key technique for metagenomic functional annotation efforts. By definition, metagenomic operons represent such interactions, but many operon predictions protocols rely on information about orthology and/or gene function that is frequently unavailable for metagenomic genes. Recently, the concept of the metagenomic proximon was proposed for use in metagenomic scenarios where supplemental information is sparse. In this paper, we examine the validity and utility of the proximon proposition by measuring the extent to which proximons emulate actual operons. Using the Escherichia coli K-12 genome, we compare proximons and operons from the same genome and observe the configurations and cardinalities among their corresponding mappings. The results demonstrate that the vast majority of proximons map discretely to a single operon in a conservative fashion where a typical proximon is synonymous to an equivalent or truncated operon. However, a large proportion of operons had no corresponding mappings to any proximon. Various perspectives of operon and proximon intersection are discussed, along with the potential limitations for proximon detection and usage.

IRES-dependent translated genes in fungi: computational prediction, phylogenetic conservation and functional association

Background

The initiation of translation via cellular internal ribosome entry sites plays an important role in the stress response and certain physiological conditions in which canonical cap-dependent translation initiation is compromised. Currently, only a limited number of these regulatory elements have been experimentally identified. Notably, cellular internal ribosome entry sites lack conservation of both the primary sequence and mRNA secondary structure, rendering their identification difficult. Despite their biological importance, the currently available computational strategies to predict them have had limited success. We developed a bioinformatic method based on a support vector machine for the prediction of internal ribosome entry sites in fungi using the 5’-UTR sequences of 20 non-redundant fungal organisms. Additionally, we performed a comparative analysis and characterization of the functional relationships among the gene products predicted to be translated by this cap-independent mechanism.

Results

Using our method, we predicted 6,532 internal ribosome entry sites in 20 non-redundant fungal organisms. Some orthologous groups were enriched with our positive predictions. This is the case of the HSP70 chaperone family, which remarkably has two verified internal ribosome entry sites, one in humans and the other in flies. A second example is the orthologous group of the eIF4G repression protein Sbp1p, which has two homologous genes known to be translated by this cap-independent mechanism, one in mice and the other in yeast. These examples emphasize the wide conservation of these regulatory elements as a result of selective pressure. In addition, we performed a protein-protein interaction network characterization of the gene products of our positive predictions using Saccharomyces cerevisiae as a model, which revealed a highly connected and modular topology, suggesting a functional association. A remarkable example of this functional association is our prediction of internal ribosome entry sites elements in three components of the RNA polymerase II mediator complex.

Conclusions

We developed a method for the prediction of cellular internal ribosome entry sites that may guide experimental and bioinformatic analyses to increase our understanding of protein translation regulation. Our analysis suggests that fungi show evolutionary conservation and functional association of proteins translated by this cap-independent mechanism.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2266-x) contains supplementary material, which is available to authorized users.

Carboxydotrophic growth of Geobacter sulfurreducens

This study shows that Geobacter sulfurreducens grows on carbon monoxide (CO) as electron donor with fumarate as electron acceptor. Geobacter sulfurreducens was tolerant to high CO levels, with up to 150 kPa in the headspace tested. During growth, hydrogen was detected in very slight amounts (∼5 Pa). In assays with cell-free extract of cells grown with CO and fumarate, production of hydrogen from CO was not observed, and hydrogenase activity with benzyl viologen as electron acceptor was very low. Taken together, this suggested that CO is not utilized via hydrogen as intermediate. In the presence of CO, reduction of NADP⁺ was observed at a rate comparable to CO oxidation coupled to fumarate reduction in vivo. The G. sulfurreducens genome contains a single putative carbon monoxide dehydrogenase-encoding gene. The gene is part of a predicted operon also comprising a putative Fe–S cluster-binding subunit (CooF) and a FAD–NAD(P) oxidoreductase and is preceded by a putative CO-sensing transcription factor. This cluster may be involved in a novel pathway for CO oxidation, but further studies are necessary to ascertain this. Similar gene clusters are present in several other species belonging to the Deltaproteobacteria and Firmicutes, for which CO utilization is currently not known.

The conserved carboxyl domain of MorC, an inner membrane protein of Aggregatibacter actinomycetemcomitans, is essential for membrane function

Morphogenesis protein C (MorC) of Aggregatibacter actinomycetemcomitans is important for maintaining the membrane morphology and integrity of the cell envelope of this oral pathogen. The MorC sequence and operon organization were found to be conserved in Gammaproteobacteria, based on a bioinformatic analysis of 435 sequences from representative organisms. Functional conservation of MorC was investigated using an A. actinomycetemcomitans morC mutant as a model system to express MorC homologs from four phylogenetically diverse representatives of the Gammaproteobacteria: Haemophilus influenzae, Escherichia coli, Pseudomonas aeruginosa, and Moraxella catarrhalis. The A. actinomycetemcomitans strains expressing the homologous proteins were assessed for sensitivity to bile salts, leukotoxin secretion, autoaggregation and membrane morphology. MorC from the most closely related organism (H. influenzae) was functionally identical to MorC from A. actinomycetemcomitans. However, the genes from more distantly related organisms restored some but not all A. actinomycetemcomitans mutant phenotypes. In addition, deletion mutagenesis indicated that the most conserved portion of the protein, the C-terminus DUF490 domain, was necessary to maintain the integrity of the membrane. Deletion of the last 10 amino acids of this domain of the A. actinomycetemcomitans MorC protein was sufficient to disrupt membrane stability and leukotoxin secretion. The data suggest that the MorC sequence is functionally conserved across Gammaproteobacteria and the C-terminus of the protein is essential for maintaining membrane physiology.

Streptococcus mutans copes with heat stress by multiple transcriptional regulons modulating virulence and energy metabolism

Dental caries is closely associated with the virulence of Streptococcus mutans. The virulence expression of S. mutans is linked to its stress adaptation to the changes in the oral environment. In this work we used whole-genome microarrays to profile the dynamic transcriptomic responses of S. mutans during physiological heat stress. In addition, we evaluated the phenotypic changes, including, eDNA release, initial biofilm formation, extracellular polysaccharides generation, acid production/acid tolerance, and ATP turnover of S. mutans during heat stress. There were distinct patterns observed in the way that S. mutans responded to heat stress that included 66 transcription factors for the expression of functional genes being differentially expressed. Especially, response regulators of two component systems (TCSs), the repressors of heat shock proteins and regulators involved in sugar transporting and metabolism co-ordinated to enhance the cell’s survival and energy generation against heat stress in S. mutans.

A novel method to identify pathways associated with renal cell carcinoma based on a gene co-expression network

The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson's correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson's correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis.

Extensive Identification of Bacterial Riboflavin Transporters and Their Distribution across Bacterial Species

Riboflavin, the precursor for the cofactors flavin mononucleotide (FMN) and flavin adenine dinucleotide, is an essential metabolite in all organisms. While the functions for de novo riboflavin biosynthesis and riboflavin import may coexist in bacteria, the extent of this co-occurrence is undetermined. The RibM, RibN, RfuABCD and the energy-coupling factor-RibU bacterial riboflavin transporters have been experimentally characterized. In addition, ImpX, RfnT and RibXY are proposed as riboflavin transporters based on positional clustering with riboflavin biosynthetic pathway (RBP) genes or conservation of the FMN riboswitch regulatory element. Here, we searched for the FMN riboswitch in bacterial genomes to identify genes encoding riboflavin transporters and assessed their distribution among bacteria. Two new putative riboflavin transporters were identified: RibZ in Clostridium and RibV in Mesoplasma florum. Trans-complementation of an Escherichia coli riboflavin auxotroph strain confirmed the riboflavin transport activity of RibZ from Clostridium difficile, RibXY from Chloroflexus aurantiacus, ImpX from Fusobacterium nucleatum and RfnT from Ochrobactrum anthropi. The analysis of the genomic distribution of all known bacterial riboflavin transporters revealed that most occur in species possessing the RBP and that some bacteria may even encode functional riboflavin transporters from two different families. Our results indicate that some species possess ancestral riboflavin transporters, while others possess transporters that appear to have evolved recently. Moreover, our data suggest that unidentified riboflavin transporters also exist. The present study doubles the number of experimentally characterized riboflavin transporters and suggests a specific, non-accessory role for these proteins in riboflavin-prototrophic bacteria.

Elucidation of operon structures across closely related bacterial genomes

About half of the protein-coding genes in prokaryotic genomes are organized into operons to facilitate co-regulation during transcription. With the evolution of genomes, operon structures are undergoing changes which could coordinate diverse gene expression patterns in response to various stimuli during the life cycle of a bacterial cell. Here we developed a graph-based model to elucidate the diversity of operon structures across a set of closely related bacterial genomes. In the constructed graph, each node represents one orthologous gene group (OGG) and a pair of nodes will be connected if any two genes, from the corresponding two OGGs respectively, are located in the same operon as immediate neighbors in any of the considered genomes. Through identifying the connected components in the above graph, we found that genes in a connected component are likely to be functionally related and these identified components tend to form treelike topology, such as paths and stars, corresponding to different biological mechanisms in transcriptional regulation as follows. Specifically, (i) a path-structure component integrates genes encoding a protein complex, such as ribosome; and (ii) a star-structure component not only groups related genes together, but also reflects the key functional roles of the central node of this component, such as the ABC transporter with a transporter permease and substrate-binding proteins surrounding it. Most interestingly, the genes from organisms with highly diverse living environments, i.e., biomass degraders and animal pathogens of clostridia in our study, can be clearly classified into different topological groups on some connected components.

Transcriptome dynamics-based operon prediction in prokaryotes

Background

Inferring operon maps is crucial to understanding the regulatory networks of prokaryotic genomes. Recently, RNA-seq based transcriptome studies revealed that in many bacterial species the operon structure vary with the change of environmental conditions. Therefore, new computational solutions that use both static and dynamic data are necessary to create condition specific operon predictions.

Results

In this work, we propose a novel classification method that integrates RNA-seq based transcriptome profiles with genomic sequence features to accurately identify the operons that are expressed under a measured condition. The classifiers are trained on a small set of confirmed operons and then used to classify the remaining gene pairs of the organism studied. Finally, by linking consecutive gene pairs classified as operons, our computational approach produces condition-dependent operon maps. We evaluated our approach on various RNA-seq expression profiles of the bacteria Haemophilus somni, Porphyromonas gingivalis, Escherichia coli and Salmonella enterica. Our results demonstrate that, using features depending on both transcriptome dynamics and genome sequence characteristics, we can identify operon pairs with high accuracy. Moreover, the combination of DNA sequence and expression data results in more accurate predictions than each one alone.

Conclusion

We present a computational strategy for the comprehensive analysis of condition-dependent operon maps in prokaryotes. Our method can be used to generate condition specific operon maps of many bacterial organisms for which high-resolution transcriptome data is available.

Operon prediction using chaos embedded particle swarm optimization

Operons contain valuable information for drug design and determining protein functions. Genes within an operon are co-transcribed to a single-strand mRNA and must be coregulated. The identification of operons is, thus, critical for a detailed understanding of the gene regulations. However, currently used experimental methods for operon detection are generally difficult to implement and time consuming. In this paper, we propose a chaotic binary particle swarm optimization (CBPSO) to predict operons in bacterial genomes. The intergenic distance, participation in the same metabolic pathway and the cluster of orthologous groups (COG) properties of the Escherichia coli genome are used to design a fitness function. Furthermore, the Bacillus subtilis, Pseudomonas aeruginosa PA01, Staphylococcus aureus and Mycobacterium tuberculosis genomes are tested and evaluated for accuracy, sensitivity, and specificity. The computational results indicate that the proposed method works effectively in terms of enhancing the performance of the operon prediction. The proposed method also achieved a good balance between sensitivity and specificity when compared to methods from the literature.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

BACKGROUND

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads.

RESULTS

To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases.

CONCLUSIONS

As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Structure of Neisseria meningitidis lipoprotein GNA1162

GNA1162, a predicted lipoprotein from Neisseria meningitidis, is a potential candidate for a universal vaccine against meningococcal disease caused by N. meningitidis serogroup B. Here, the crystal structure of GNA1162 at 1.89 Å resolution determined by single-wavelength anomalous dispersion (SAD) is reported. The structure of GNA1162 appears to be a dimer in the crystallographic asymmetric unit as well as in solution. The overall structure of the dimer indicates that each monomer inserts its C-terminal α5 helix into the hydrophobic groove of the other molecule. Moreover, the β4 strands of each monomer lie antiparallel to each other and interact through multiple main-chain hydrogen bonds. Through structural comparisons and operon predictions, it is hypothesized that GNA1162 is part of a transport system and assists in transport and reassembly. The crystal structure of GNA1162 sheds light on its possible function and provides potentially valuable information for the design of a vaccine against meningococcal disease.

Lactic acid bacteria producing B-group vitamins: a great potential for functional cereals products

Wheat contains various essential nutrients including the B group of vitamins. However, B group vitamins, normally present in cereals-derived products, are easily removed or destroyed during milling, food processing or cooking. Lactic acid bacteria (LAB) are widely used as starter cultures for the fermentation of a large variety of foods and can improve the safety, shelf life, nutritional value, flavor and overall quality of the fermented products. In this regard, the identification and application of strains delivering health-promoting compounds is a fascinating field. Besides their key role in food fermentations, several LAB found in the gastrointestinal tract of humans and animals are commercially used as probiotics and possess generally recognized as safe status. LAB are usually auxotrophic for several vitamins although certain strains of LAB have the capability to synthesize water-soluble vitamins such as those included in the B group. In recent years, a number of biotechnological processes have been explored to perform a more economical and sustainable vitamin production than that obtained via chemical synthesis. This review article will briefly report the current knowledge on lactic acid bacteria synthesis of vitamins B2, B11 and B12 and the potential strategies to increase B-group vitamin content in cereals-based products, where vitamins-producing LAB have been leading to the elaboration of novel fermented functional foods. In addition, the use of genetic strategies to increase vitamin production or to create novel vitamin-producing strains will be also discussed.

Systematic characterization of hypothetical proteins in Synechocystis sp. PCC 6803 reveals proteins functionally relevant to stress responses

We described here a global detection and functional inference of hypothetical proteins involved in stress response in Synechocystis sp. PCC 6803. In the study, we first applied an iTRAQ-LC-MS/MS based quantitative proteomics to the Synechocystis cells grown under five stress conditions. The analysis detected a total of 807 hypothetical proteins with high confidence. Among them, 480 were differentially regulated. We then applied a Weighted Gene Co-expression Network Analysis approach to construct transcriptional networks for Synechocystis under nutrient limitation and osmotic stress conditions using transcriptome datasets. The analysis showed that 305 and 467 coding genes of hypothetical proteins were functionally relevant to nutrient limitation and osmotic stress, respectively. A comparison of responsive hypothetical proteins to all stress conditions allowed identification of 22 hypothetical proteins commonly responsive to all stresses, suggesting they may be part of the core stress responses in Synechocystis. Finally, functional inference of these core stress responsive proteins using both sequence similarity and non-similarity approaches was conducted. The study provided new insights into the stress response networks in Synechocystis, and also demonstrated that a combination of experimental "OMICS" and bioinformatics methodologies could improve functional annotation for hypothetical proteins.

Elucidating metabolic pathways and digging for genes of unknown function in microbial communities: the riboswitch approach

In the current post-genomic era, only 3% of all genes have been annotated based on experimental evidence. Even though functions can readily be predicted for many genes, 25% of these are likely to be wrong. The most widely used methods for function prediction rely on sequence similarity, which might be misleading in many cases. Other methods such as genomic context or phylogenetic profiles have been developed to increase gene annotation accuracy; nevertheless these are only efficient when complete genome sequences are available. Here we propose a new approach based on riboswitch identification. Riboswitches are highly conserved regulators of gene expression located in the 5' untranslated region of certain genes. When transcribed they adopt three-dimensional structures that recognize their ligands with great affinity and specificity. This specificity is a key issue for our method, allowing functional assignment with great accuracy.

Motif analysis unveils the possible co-regulation of chloroplast genes and nuclear genes encoding chloroplast proteins

Chloroplasts play critical roles in land plant cells. Despite their importance and the availability of at least 200 sequenced chloroplast genomes, the number of known DNA regulatory sequences in chloroplast genomes are limited. In this paper, we designed computational methods to systematically study putative DNA regulatory sequences in intergenic regions near chloroplast genes in seven plant species and in promoter sequences of nuclear genes in Arabidopsis and rice. We found that -35/-10 elements alone cannot explain the transcriptional regulation of chloroplast genes. We also concluded that there are unlikely motifs shared by intergenic sequences of most of chloroplast genes, indicating that these genes are regulated differently. Finally and surprisingly, we found five conserved motifs, each of which occurs in no more than six chloroplast intergenic sequences, are significantly shared by promoters of nuclear-genes encoding chloroplast proteins. By integrating information from gene function annotation, protein subcellular localization analyses, protein-protein interaction data, and gene expression data, we further showed support of the functionality of these conserved motifs. Our study implies the existence of unknown nuclear-encoded transcription factors that regulate both chloroplast genes and nuclear genes encoding chloroplast protein, which sheds light on the understanding of the transcriptional regulation of chloroplast genes.

Features for computational operon prediction in prokaryotes

Accurate prediction of operons can improve the functional annotation and application of genes within operons in prokaryotes. Here, we review several features: (i) intergenic distance, (ii) metabolic pathways, (iii) homologous genes, (iv) promoters and terminators, (v) gene order conservation, (vi) microarray, (vii) clusters of orthologous groups, (viii) gene length ratio, (ix) phylogenetic profiles, (x) operon length/size and (xi) STRING database scores, as well as some other features, which have been applied in recent operon prediction methods in prokaryotes in the literature. Based on a comparison of the prediction performances of these features, we conclude that other, as yet undiscovered features, or feature selection with a receiver operating characteristic analysis before algorithm processing can improve operon prediction in prokaryotes.

ProOpDB: Prokaryotic Operon DataBase

The Prokaryotic Operon DataBase (ProOpDB, http://operons.ibt.unam.mx/OperonPredictor) constitutes one of the most precise and complete repositories of operon predictions now available. Using our novel and highly accurate operon identification algorithm, we have predicted the operon structures of more than 1200 prokaryotic genomes. ProOpDB offers diverse alternatives by which a set of operon predictions can be retrieved including: (i) organism name, (ii) metabolic pathways, as defined by the KEGG database, (iii) gene orthology, as defined by the COG database, (iv) conserved protein domains, as defined by the Pfam database, (v) reference gene and (vi) reference operon, among others. In order to limit the operon output to non-redundant organisms, ProOpDB offers an efficient method to select the most representative organisms based on a precompiled phylogenetic distances matrix. In addition, the ProOpDB operon predictions are used directly as the input data of our Gene Context Tool to visualize their genomic context and retrieve the sequence of their corresponding 5′ regulatory regions, as well as the nucleotide or amino acid sequences of their genes.

Novel transmembrane lipases of alpha/beta hydrolase fold

Processing of exogenous glycerol esters is an initial step in energy derivation for many bacterial cells. Lipid-rich environments settled by a variety of organisms exert strong evolutionary pressure for establishing enzymatic pathways involved in lipid metabolism. However, a certain number of enzymes involved in this process remain unknown since they do not share detectable sequence similarity with any known protein domains. Using distant homology detection and fold recognition we predict that bacterial transmembrane proteins belonging to the uncharacterized domain of unknown function 2319 (DUF2319) family possess the alpha/beta hydrolase fold domain together with the catalytic triad critical for hydrolysis. A detailed analysis of sequence/structure features and genomic context indicates that DUF2319 proteins may be involved in lipid metabolism. Therefore, these enzymes are likely to serve as extracellular lipases.