MicroRNAs Form Triplexes with Double Stranded DNA at Sequence-Specific Binding Sites; a Eukaryotic Mechanism via which microRNAs Could Directly Alter Gene Expression.

MicroRNAs are important regulators of gene expression, acting primarily by binding to sequence-specific locations on already transcribed messenger RNAs (mRNA) and typically down-regulating their stability or translation. Recent studies indicate that microRNAs may also play a role in up-regulating mRNA transcription levels, although a definitive mechanism has not been established. Double-helical DNA is capable of forming triple-helical structures through Hoogsteen and reverse Hoogsteen interactions in the major groove of the duplex, and we show physical evidence (i.e., NMR, FRET, SPR) that purine or pyrimidine-rich microRNAs of appropriate length and sequence form triple-helical structures with purine-rich sequences of duplex DNA, and identify microRNA sequences that favor triplex formation. We developed an algorithm (Trident) to search genome-wide for potential triplex-forming sites and show that several mammalian and non-mammalian genomes are enriched for strong microRNA triplex binding sites. We show that those genes containing sequences favoring microRNA triplex formation are markedly enriched (3.3 fold, p<2.2 × 10(-16)) for genes whose expression is positively correlated with expression of microRNAs targeting triplex binding sequences. This work has thus revealed a new mechanism by which microRNAs could interact with gene promoter regions to modify gene transcription.

Ebolavirus comparative genomics.

The 2014 Ebola outbreak in West Africa is the largest documented for this virus. To examine the dynamics of this genome, we compare more than 100 currently available ebolavirus genomes to each other and to other viral genomes. Based on oligomer frequency analysis, the family Filoviridae forms a distinct group from all other sequenced viral genomes. All filovirus genomes sequenced to date encode proteins with similar functions and gene order, although there is considerable divergence in sequences between the three genera Ebolavirus, Cuevavirus and Marburgvirus within the family Filoviridae. Whereas all ebolavirus genomes are quite similar (multiple sequences of the same strain are often identical), variation is most common in the intergenic regions and within specific areas of the genes encoding the glycoprotein (GP), nucleoprotein (NP) and polymerase (L). We predict regions that could contain epitope-binding sites, which might be good vaccine targets. This information, combined with glycosylation sites and experimentally determined epitopes, can identify the most promising regions for the development of therapeutic strategies.This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Metabolic environments and genomic features associated with pathogenic and mutualistic interactions between bacteria and plants.

Genomic characteristics discriminating parasitic and mutualistic relationship of bacterial symbionts with plants are poorly understood. This study comparatively analyzed the genomes of 54 mutualists and pathogens to discover genomic markers associated with the different phenotypes. Using metabolic network models, we predict external environments associated with free-living and symbiotic lifestyles and quantify dependences of symbionts on the host in terms of the consumed metabolites. We show that specific differences between the phenotypes are pronounced at the levels of metabolic enzymes, especially carbohydrate active, and protein functions. Overall, biosynthetic functions are enriched and more diverse in plant mutualists whereas processes and functions involved in degradation and host invasion are enriched and more diverse in pathogens. A distinctive characteristic of plant pathogens is a putative novel secretion system with a circadian rhythm regulator. A specific marker of plant mutualists is the co-residence of genes encoding nitrogenase and ribulose bisphosphate carboxylase/oxygenase (RuBisCO). We predict that RuBisCO is likely used in a putative metabolic pathway to supplement carbon obtained heterotrophically with low-cost assimilation of carbon from CO2. We validate results of the comparative analysis by predicting correct phenotype, pathogenic or mutualistic, for 20 symbionts in an independent set of 30 pathogens, mutualists, and commensals.

Effect of the amyloid ß hairpin's structure on the handedness of helices formed by its aggregates.

Various structural models for amyloid ß fibrils have been derived from a variety of experimental techniques. However, these models cannot differentiate between the relative position of the two arms of the ß hairpin called the stagger. Amyloid fibrils of various hierarchical levels form left-handed helices composed of ß sheets. However it is unclear if positive, negative and zero staggers all form the macroscopic left-handed helices. To address this issue we have conducted extensive molecular dynamics simulations of amyloid ß sheets of various staggers and shown that only negative staggers lead to the experimentally observed left-handed helices while positive staggers generate the incorrect right-handed helices. This result suggests that the negative staggers are physiologically relevant structure of the amyloid ß fibrils.

Effect of temperature and glycerol on the hydrogen-bond dynamics of water.

The effect of glycerol, water and glycerol-water binary mixtures on the structure and dynamics of biomolecules has been well studied. However, a lot remains to be learned about the effect of varying glycerol concentration and temperature on the dynamics of water. We have studied the effect of concentration and temperature on the hydrogen bonded network formed by water molecules. A strong correlation between the relaxation time of the network and average number of hydrogen bonds per water molecules was found. The radial distribution function of water oxygen and hydrogen atoms clarifies the effect of concentration on the structure and clustering of water.

Initial recognition of a cellodextrin chain in the cellulose-binding tunnel may affect cellobiohydrolase directional specificity.

Cellobiohydrolases processively hydrolyze glycosidic linkages in individual polymer chains of cellulose microfibrils, and typically exhibit specificity for either the reducing or nonreducing end of cellulose. Here, we conduct molecular dynamics simulations and free energy calculations to examine the initial binding of a cellulose chain into the catalytic tunnel of the reducing-end-specific Family 7 cellobiohydrolase (Cel7A) from Hypocrea jecorina. In unrestrained simulations, the cellulose diffuses into the tunnel from the -7 to the -5 positions, and the associated free energy profiles exhibit no barriers for initial processivity. The comparison of the free energy profiles for different cellulose chain orientations show a thermodynamic preference for the reducing end, suggesting that the preferential initial binding may affect the directional specificity of the enzyme by impeding nonproductive (nonreducing end) binding. Finally, the Trp-40 at the tunnel entrance is shown with free energy calculations to have a significant effect on initial chain complexation in Cel7A.

Gene and translation initiation site prediction in metagenomic sequences.

MOTIVATION: Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. RESULTS: We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translation initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements. AVAILABILITY: The Prodigal software is freely available under the General Public License from http://code.google.com/p/prodigal/.

Binding Motifs in Bacterial Gene Promoters Modulate Transcriptional Effects of Global Regulators CRP and ArcA.

Bacterial gene regulation involves transcription factors (TF) that bind to DNA recognition sequences in operon promoters. These recognition sequences, many of which are palindromic, are known as regulatory elements or transcription factor binding sites (TFBS). Some TFs are global regulators that can modulate the expression of hundreds of genes. In this study we examine global regulator half-sites, where a half-site, which we shall call a binding motif (BM), is one half of a palindromic TFBS. We explore the hypothesis that the number of BMs plays an important role in transcriptional regulation, examining empirical data from transcriptional profiling of the CRP and ArcA regulons. We compare the power of BM counts and of full TFBS characteristics to predict induced transcriptional activity. We find that CRP BM counts have a nonlinear effect on CRP-dependent transcriptional activity and predict this activity better than full TFBS quality or location.

Analyzing large biological datasets with association networks.

Due to advances in high-throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches that process collected data into new knowledge in a timely manner. In this study, we propose a computational framework for discovering modular structure, relationships and regularities in complex data. The framework utilizes a semantic-preserving vocabulary to convert records of biological annotations of an object, such as an organism, gene, chemical or sequence, into networks (Anets) of the associated annotations. An association between a pair of annotations in an Anet is determined by the similarity of their co-occurrence pattern with all other annotations in the data. This feature captures associations between annotations that do not necessarily co-occur with each other and facilitates discovery of the most significant relationships in the collected data through clustering and visualization of the Anet. To demonstrate this approach, we applied the framework to the analysis of metadata from the Genomes OnLine Database and produced a biological map of sequenced prokaryotic organisms with three major clusters of metadata that represent pathogens, environmental isolates and plant symbionts.

BESC knowledgebase public portal.

UNLABELLED: The BioEnergy Science Center (BESC) is undertaking large experimental campaigns to understand the biosynthesis and biodegradation of biomass and to develop biofuel solutions. BESC is generating large volumes of diverse data, including genome sequences, omics data and assay results. The purpose of the BESC Knowledgebase is to serve as a centralized repository for experimentally generated data and to provide an integrated, interactive and user-friendly analysis framework. The Portal makes available tools for visualization, integration and analysis of data either produced by BESC or obtained from external resources. AVAILABILITY: http://besckb.ornl.gov.

CAZymes Analysis Toolkit (CAT): web service for searching and analyzing carbohydrate-active enzymes in a newly sequenced organism using CAZy database.

The Carbohydrate-Active Enzyme (CAZy) database provides a rich set of manually annotated enzymes that degrade, modify, or create glycosidic bonds. Despite rich and invaluable information stored in the database, software tools utilizing this information for annotation of newly sequenced genomes by CAZy families are limited. We have employed two annotation approaches to fill the gap between manually curated high-quality protein sequences collected in the CAZy database and the growing number of other protein sequences produced by genome or metagenome sequencing projects. The first approach is based on a similarity search against the entire nonredundant sequences of the CAZy database. The second approach performs annotation using links or correspondences between the CAZy families and protein family domains. The links were discovered using the association rule learning algorithm applied to sequences from the CAZy database. The approaches complement each other and in combination achieved high specificity and sensitivity when cross-evaluated with the manually curated genomes of Clostridium thermocellum ATCC 27405 and Saccharophagus degradans 2-40. The capability of the proposed framework to predict the function of unknown protein domains and of hypothetical proteins in the genome of Neurospora crassa is demonstrated. The framework is implemented as a Web service, the CAZymes Analysis Toolkit, and is available at http://cricket.ornl.gov/cgi-bin/cat.cgi.

Shewanella knowledgebase: integration of the experimental data and computational predictions suggests a biological role for transcription of intergenic regions.

Shewanellae are facultative gamma-proteobacteria whose remarkable respiratory versatility has resulted in interest in their utility for bioremediation of heavy metals and radionuclides and for energy generation in microbial fuel cells. Extensive experimental efforts over the last several years and the availability of 21 sequenced Shewanella genomes made it possible to collect and integrate a wealth of information on the genus into one public resource providing new avenues for making biological discoveries and for developing a system level understanding of the cellular processes. The Shewanella knowledgebase was established in 2005 to provide a framework for integrated genome-based studies on Shewanella ecophysiology. The present version of the knowledgebase provides access to a diverse set of experimental and genomic data along with tools for curation of genome annotations and visualization and integration of genomic data with experimental data. As a demonstration of the utility of this resource, we examined a single microarray data set from Shewanella oneidensis MR-1 for new insights into regulatory processes. The integrated analysis of the data predicted a new type of bacterial transcriptional regulation involving co-transcription of the intergenic region with the downstream gene and suggested a biological role for co-transcription that likely prevents the binding of a regulator of the upstream gene to the regulator binding site located in the intergenic region. Database URL: http://shewanella-knowledgebase.org:8080/Shewanella/ or http://spruce.ornl.gov:8080/Shewanella/

Conserved synteny at the protein family level reveals genes underlying Shewanella species' cold tolerance and predicts their novel phenotypes.

Bacteria of the genus Shewanella can thrive in different environments and demonstrate significant variability in their metabolic and ecophysiological capabilities including cold and salt tolerance. Genomic characteristics underlying this variability across species are largely unknown. In this study, we address the problem by a comparison of the physiological, metabolic, and genomic characteristics of 19 sequenced Shewanella species. We have employed two novel approaches based on association of a phenotypic trait with the number of the trait-specific protein families (Pfam domains) and on the conservation of synteny (order in the genome) of the trait-related genes. Our first approach is top-down and involves experimental evaluation and quantification of the species' cold tolerance followed by identification of the correlated Pfam domains and genes with a conserved synteny. The second, a bottom-up approach, predicts novel phenotypes of the species by calculating profiles of each Pfam domain among their genomes and following pair-wise correlation of the profiles and their network clustering. Using the first approach, we find a link between cold and salt tolerance of the species and the presence in the genome of a Na(+)/H(+) antiporter gene cluster. Other cold-tolerance-related genes include peptidases, chemotaxis sensory transducer proteins, a cysteine exporter, and helicases. Using the bottom-up approach, we found several novel phenotypes in the newly sequenced Shewanella species, including degradation of aromatic compounds by an aerobic hybrid pathway in Shewanella woodyi, degradation of ethanolamine by Shewanella benthica, and propanediol degradation by Shewanella putrefaciens CN32 and Shewanella sp. W3-18-1.

Phenotype fingerprinting suggests the involvement of single-genotype consortia in degradation of aromatic compounds by Rhodopseudomonas palustris.

Anaerobic degradation of complex organic compounds by microorganisms is crucial for development of innovative biotechnologies for bioethanol production and for efficient degradation of environmental pollutants. In natural environments, the degradation is usually accomplished by syntrophic consortia comprised of different bacterial species. This strategy allows consortium organisms to reduce efforts required for maintenance of the redox homeostasis at each syntrophic level. Cellular mechanisms that maintain the redox homeostasis during the degradation of aromatic compounds by one organism are not fully understood. Here we present a hypothesis that the metabolically versatile phototrophic bacterium Rhodopseudomonas palustris forms its own syntrophic consortia, when it grows anaerobically on p-coumarate or benzoate as a sole carbon source. We have revealed the consortia from large-scale measurements of mRNA and protein expressions under p-coumarate, benzoate and succinate degrading conditions using a novel computational approach referred as phenotype fingerprinting. In this approach, marker genes for known R. palustris phenotypes are employed to determine the relative expression levels of genes and proteins in aromatics versus non-aromatics degrading condition. Subpopulations of the consortia are inferred from the expression of phenotypes and known metabolic modes of the R. palustris growth. We find that p-coumarate degrading conditions may lead to at least three R. palustris subpopulations utilizing p-coumarate, benzoate, and CO2 and H2. Benzoate degrading conditions may also produce at least three subpopulations utilizing benzoate, CO2 and H2, and N2 and formate. Communication among syntrophs and inter-syntrophic dynamics in each consortium are indicated by up-regulation of transporters and genes involved in the curli formation and chemotaxis. The N2-fixing subpopulation in the benzoate degrading consortium has preferential activation of the vanadium nitrogenase over the molybdenum nitrogenase. This subpopulation in the consortium was confirmed in an independent experiment by consumption of dissolved nitrogen gas under the benzoate degrading conditions.

Shewregdb: database and visualization environment for experimental and predicted regulatory information in Shewanella oneidensis mr-1.

UNLABELLED: Shewanella oneidensis MR-1 is an important model organism for environmental research as it has an exceptional metabolic and respiratory versatility regulated by a complex regulatory network. We have developed a database to collect experimental and computational data relating to regulation of gene and protein expression, and, a visualization environment that enables integration of these data types. The regulatory information in the database includes predictions of DNA regulator binding sites, sigma factor binding sites, transcription units, operons, promoters, and RNA regulators including non-coding RNAs, riboswitches, and different types of terminators. AVAILABILITY: http://shewanella-knowledgebase.org:8080/Shewanella/gbrowserLanding.jsp.

MASPIC: intensity-based tandem mass spectrometry scoring scheme that improves peptide identification at high confidence.

Algorithmic search engines bridge the gap between large tandem mass spectrometry data sets and the identification of proteins associated with biological samples. Improvements in these tools can greatly enhance biological discovery. We present a new scoring scheme for comparing tandem mass spectra with a protein sequence database. The MASPIC (Multinomial Algorithm for Spectral Profile-based Intensity Comparison) scorer converts an experimental tandem mass spectrum into a m/z profile of probability and then scores peak lists from potential candidate peptides using a multinomial distribution model. The MASPIC scoring scheme incorporates intensity, spectral peak density variations, and m/z error distribution associated with peak matches into a multinomial distribution. The scoring scheme was validated on two standard protein mixtures and an additional set of spectra collected on a complex ribosomal protein mixture from Rhodopseudomonas palustris. The results indicate a 5-15% improvement over Sequest for high-confidence identifications. The performance gap grows as sequence database size increases. Additional tests on spectra from proteinase-K digest data showed similar performance improvements demonstrating the advantages in using MASPIC for studying proteins digested with less specific proteases. All these investigations show MASPIC to be a versatile and reliable system for peptide tandem mass spectral identification.

A computational method for assessing peptide- identification reliability in tandem mass spectrometry analysis with SEQUEST.

High-throughput protein identification in mass spectrometry is predominantly achieved by first identifying tryptic peptides by a database search and then by combining the peptide hits for protein identification. One of the popular tools used for the database search is SEQUEST. Peptide identification is carried out by selecting SEQUEST hits above a specified threshold, the value of which is typically chosen empirically in an attempt to separate true identifications from false ones. These SEQUEST scores are not normalized with respect to the composition, length and other parameters of the peptides. Furthermore, there is no rigorous reliability estimate assigned to the protein identifications derived from these scores. Hence, the interpretation of SEQUEST hits generally requires human involvement, making it difficult to scale up the identification process for genome-scale applications. To overcome these limitations, we have developed a method, which combines a neural network and a statistical model, for normalizing SEQUEST scores, and also for providing a reliability estimate for each SEQUEST hit. This method improves the sensitivity and specificity of peptide identification compared to the standard filtering procedure used in the SEQUEST package, and provides a basis for estimating the reliability of protein identifications.

GrailEXP and Genome Analysis Pipeline for genome annotation.

The Gene Recognition and Analysis Internet Link (GRAIL) is one of the most widely used systems for evaluating the protein-coding potential of anonymous DNA sequences. This unit describes the use of the XGRAIL and genQuest client-server applications to locate exons in DNA sequences, to develop gene models, and to search databases for homologs. A support protocol describes how to obtain the GRAIL and genQuest client software by anonymous FTP.

GrailEXP and Genome Analysis Pipeline for genome annotation.

The Basic Protocol describes the use of GrailEXP, the latest version of the gene finding system from Oak Ridge National Laboratory. GrailEXP provides gene models, by making use of sequence similarity with Expressed Sequence Tags (ESTs) and known genes. GrailEXP also provides alternatively spliced constructs for each gene based on the available EST evidence. The Support Protocol describes the use of the Genome Analysis Pipeline, a web application which allows users to perform comprehensive sequence analysis by offering a selection from a wide choice of supported gene finders, other biological feature finders, and database searches.