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  • Computational Methods  (62)
  • Pathogens & Pathogenicity  (51)
  • Oxford University Press  (113)
  • Annual Reviews
  • Periodicals Archive Online (PAO)
  • 1
    Publication Date: 2015-09-19
    Description: Sequence alignment is a long standing problem in bioinformatics. The Basic Local Alignment Search Tool (BLAST) is one of the most popular and fundamental alignment tools. The explosive growth of biological sequences calls for speedup of sequence alignment tools such as BLAST. To this end, we develop high speed BLASTN (HS-BLASTN), a parallel and fast nucleotide database search tool that accelerates MegaBLAST—the default module of NCBI-BLASTN. HS-BLASTN builds a new lookup table using the FMD-index of the database and employs an accurate and effective seeding method to find short stretches of identities (called seeds) between the query and the database. HS-BLASTN produces the same alignment results as MegaBLAST and its computational speed is much faster than MegaBLAST. Specifically, our experiments conducted on a 12-core server show that HS-BLASTN can be 22 times faster than MegaBLAST and exhibits better parallel performance than MegaBLAST. HS-BLASTN is written in C++ and the related source code is available at https://github.com/chenying2016/queries under the GPLv3 license.
    Keywords: Computational Methods
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  • 2
    Publication Date: 2015-05-29
    Description: Model evaluation is a necessary step for better prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statistical potentials have also been proposed to evaluate predicted models of RNA tertiary structures. The benchmark tests showed that they can identify the native structures effectively but further improvements are needed to identify near-native structures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dRNAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.
    Keywords: Computational Methods
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  • 3
    Publication Date: 2016-07-15
    Description: Invertebrate animal species that can withstand temperatures as high as 37°C, the human body temperature, are limited. In the present study, we utilized the two-spotted cricket, Gryllus bimaculatus , which lives in tropical and subtropical regions, as an animal model of human pathogenic bacterial infection. Injection of Pseudomonas aeruginosa or Staphylococcus aureus into the hemolymph killed crickets. Injected P. aeruginosa or S. aureus proliferated in the hemolymph until the cricket died. The ability of these pathogenic bacteria to kill the crickets was blocked by the administration of antibiotics. S. aureus gene-knockout mutants of virulence factors, including cvfA, agr and srtA , exhibited decreased killing ability compared with the parent strain. The dose at which 50% of crickets were killed by P. aeruginosa or S. aureus was not decreased at 37°C compared with that at 27°C. Injection of Listeria monocytogenes , which upregulates toxin expression at 37°C, killed crickets, and the dose at which 50% of crickets were killed was decreased at 37°C compared with that at 27°C. These findings suggest that the two-spotted cricket is a useful model animal for evaluating the virulence properties of various human pathogenic bacteria at variable temperature including 37°C.
    Keywords: Pathogens & Pathogenicity
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  • 4
    Publication Date: 2016-07-31
    Description: The OmpA-like protein domain has been associated with peptidoglycan-binding proteins, and is often found in virulence factors of bacterial pathogens. The intracellular pathogen Legionella pneumophila encodes for six proteins that contain the OmpA-like domain, among them the highly conserved uncharacterized protein we named CmpA. Here we set out to characterize the CmpA protein and determine its contribution to intracellular survival of L. pneumophila . Secondary structure analysis suggests that CmpA is an inner membrane protein with a peptidoglycan-binding domain at the C-teminus. A cmpA mutant was able to replicate normally in broth, but failed to compete with an isogenic wild-type strain in an intracellular growth competition assay. The cmpA mutant also displayed significant intracellular growth defects in both the protozoan host Acanthamoeba castellanii and in primary bone marrow-derived macrophages, where uptake into the cells was also impaired. The cmpA phenotypes were completely restored upon expression of CmpA in trans . The data presented here establish CmpA as a novel virulence factor of L. pneumophila that is required for efficient intracellular replication in both mammalian and protozoan hosts.
    Keywords: Pathogens & Pathogenicity
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  • 5
    Publication Date: 2016-08-05
    Description: Shiga toxin-encoding Escherichia coli (STEC) regroup strains that carry genes encoding Shiga toxin (Stx). Among intestinal pathogenic E. coli , enterohaemorrhagic E. coli (EHEC) constitute the major subgroup of virulent STEC. EHEC cause serious human disease such as haemorrhagic colitis and haemolytic-uremic syndrome. While EHEC have evolved from enteropathogenic E. coli , hybrids with enteroaggregative E. coli have recently emerged. Of note, some enteroinvasive E. coli also belong to the STEC group. While the LEE (locus of enterocyte effacement) is a key and prominent molecular determinant in the pathogenicity, neither all EHEC nor STEC contain the LEE, suggesting that they possess additional virulence and colonisation factors. Currently, nine protein secretion systems have been described in diderm-lipopolysaccharide bacteria (archetypal Gram-negative) and can be involved in the secretion of extracellular effectors, cell-surface proteins or assembly of cell-surface organelles, such as flagella or pili. In this review, we focus on the secretome of STEC and related enteropathotypes, which are relevant to the colonisation of biotic and abiotic surfaces. Considering the wealth of potential protein trafficking mechanisms, the different combinations of colonisation factors and modulation of their expression is further emphasised with regard to the ecophysiology of STEC.
    Keywords: Pathogens & Pathogenicity
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  • 6
    Publication Date: 2016-06-21
    Description: The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P -values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.
    Keywords: Computational Methods
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  • 7
    Publication Date: 2016-06-23
    Description: The activity of levofloxacin against planktonic and biofilm Stenotrophomonas maltophilia cells and the role played by the multidrug efflux pump SmeDEF were evaluated under conditions relevant to the cystic fibrosis (CF) lung. MIC, MBC and MBEC of levofloxacin were assessed, against five CF strains, under ‘standard’ (CLSI-recommended) and ‘CF-like’ (pH 6.8, 5% CO 2 , in a synthetic CF sputum) conditions. Levofloxacin was tested against biofilms at concentrations (10, 50 and 100 μg mL –1 ) corresponding to achievable serum levels and sputum levels by aerosolisation. smeD expression was evaluated, under both conditions, in planktonic and biofilm cells by RT-PCR. The bactericidal effect of levofloxacin was decreased, in three out of five strains tested, under ‘CF-like’ conditions (MBC: 2–4 vs 8–16 μg mL –1 , under ‘standard’ and ‘CF-like’ conditions, respectively). Biofilm was intrinsically resistant to levofloxacin, regardless of conditions tested (MBECs ≥ 100 μg mL –1 for all strains). Only under ‘CF-like’ conditions, smeD expression increased during planktonic-to-biofilm transition, and in biofilm cells compared to stationary planktonic cells. Our findings confirmed that S. maltophilia biofilm is intrinsically resistant to therapeutic concentrations of levofloxacin. Under conditions relevant to CF, smeD overexpression could contribute to levofloxacin resistance. Further studies are warranted to define the clinical relevance of our findings .
    Keywords: Pathogens & Pathogenicity
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  • 8
    Publication Date: 2016-06-23
    Description: Auranofin is an FDA-approved gold-containing compound used for the treatment of rheumatoid arthritis. Recent reports of antimicrobial activity against protozoa and bacteria indicate that auranofin targets the reductive enzyme thioredoxin reductase (TrxR). We evaluated auranofin as well as five auranofin analogs containing N- heterocyclic carbenes (instead of the triethylphosphane present in auranofin) and five gold-carbene controls for their ability to inhibit or kill Helicobacter pylori in vitro . Auranofin completely inhibited bacterial growth at 1.2 μM. Purified H. pylori TrxR was inhibited by auranofin in a cell-free assay (IC 50 ~88 nM). The most active gold(I)- N- heterocyclic carbene compounds exhibited MICs comparable to auranofin against H. pylori (2 μM), while also exhibiting lower toxicities for human embryonic kidney cells (HEK-293T cells). Median toxic concentrations (TC 50 ) were 13–20-fold higher compared to auranofin indicating that they were less cytotoxic. The N- heterocyclic carbene analogs maybe well tolerated, but further evaluation is needed in vivo . Finally, auranofin was synergistic with the antibiotic amoxicillin, suggesting that targeting both the reductive enzyme TrxR and cell wall synthesis may be effective against H. pylori infections.
    Keywords: Pathogens & Pathogenicity
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  • 9
    Publication Date: 2016-05-08
    Description: Legionella feeleii is a Gram-negative pathogenic bacterium that causes Pontiac fever and pneumonia in humans. When L. feeleii serogroup 1 (ATCC 35072) was cultured on BCYE agar plates, two types of colonies were observed and exhibited differences in color, opacity and morphology. Since the two colony types are white rugose and brown translucent, they were termed as white rugose L. feeleii (WRLf) and brown translucent L. feeleii (BTLf), respectively. They exhibited different growth capacities in BYE broth in vitro , and it was found that WRLf could transform to BTLf. Under the electron microscope, it was observed that WRLf secreted materials which could be stained with ruthenium red, which was absent in BTLf. When U937 macrophages and HeLa cells were infected with the bacteria, WRLf manifested stronger internalization ability than BTLf. Intracellular growth in murine macrophages and Acanthamoeba cells was affected by the level of initial phagocytosis. WRLf was more resistant to human serum bactericidal action than BTLf. After being inoculated to guinea pigs, both organisms caused fever in the animals. These results suggest that ruthenium red-stained materials secreted in the surroundings may play a crucial role in determining L. feeleii colony morphology and virulence traits.
    Keywords: Pathogens & Pathogenicity
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  • 10
    Publication Date: 2016-05-12
    Description: Piscirickettsia salmonis is a fastidious intracellular pathogen responsible for high mortality rates in farmed salmonids, with serious economic consequences for the Chilean aquaculture industry. Oxytetracycline and florfenicol are the most frequently used antibiotics against P. salmonis , but routine use could contribute to drug resistance. This study identified differentiated florfenicol susceptibilities in two P. salmonis strains, LF-89 and AUSTRAL-005. The less susceptible isolate, AUSTRAL-005, also showed a high ethidium bromide efflux rate, indicating a higher activity of general efflux pump genes than LF-89. The P. salmonis genome presented resistance nodulation division (RND) family members, a family containing typical multidrug resistance-related efflux pumps in Gram-negative bacteria. Additionally, efflux pump acrAB genes were overexpressed in AUSTRAL-005 following exposure to the tolerated maximal concentration of florfenicol, in contrast to LF-89. These results indicate that tolerated maximum concentrations of florfenicol can modulate RND gene expression and increase efflux pump activity. We propose that the acrAB efflux pump is essential for P. salmonis survival at critical florfenicol concentrations and for the generation of antibiotic-resistant bacterial strains.
    Keywords: Pathogens & Pathogenicity
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  • 11
    Publication Date: 2016-05-12
    Description: Pseudomonas aeruginosa is an opportunistic pathogen, known to develop robust biofilms. Its biofilm development increases when antibiotics are presented at subminimal inhibitory concentrations (MICs) for reasons that remain unclear. In order to identify genes that affect biofilm development under such a sublethal antibiotic stress condition, we screened a transposon (Tn) mutant library of PAO1, a prototype P. aeruginosa strain. Among ~5000 mutants, a fiuA gene mutant was verified to form very defective biofilms in the presence of sub-MIC carbenicillin. The fiuA gene encodes ferrichrome receptor A, involved in the iron acquisition process. Of note, biofilm formation was not decreased in the pchpvd mutant defective in the production of pyochelin and pyoverdine, two well-characterized P. aeruginosa siderophore molecules. Moreover, fiuA , a non-polar fiuA deletion mutant, produced a significantly decreased level of elastase, a major virulence determinant. Mouse airway infection experiments revealed that the mutant expressed significantly less pathogenicity. Our results suggest that the fiuA gene has pleiotropic functions that affect P. aeruginosa biofilm development and virulence. The targeting of FiuA could enable the attenuation of P. aeruginosa virulence and may be suitable for the development of a drug that specifically controls the virulence of this important pathogen.
    Keywords: Pathogens & Pathogenicity
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  • 12
    Publication Date: 2016-07-09
    Description: Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at http://jeffbhasin.github.io/goldmine .
    Keywords: Computational Methods
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  • 13
    Publication Date: 2016-07-28
    Description: CCCTC-binding factor (CTCF) is a multi-functional protein that is assigned various, even contradictory roles in the genome. High-throughput sequencing-based technologies such as ChIP-seq and Hi-C provided us the opportunity to assess the multivalent functions of CTCF in the human genome. The location of CTCF-binding sites with respect to genomic features provides insights into the possible roles of this protein. Here we present the first genome-wide survey and characterization of three important functions of CTCF: enhancer insulator, chromatin barrier and enhancer linker. We developed a novel computational framework to discover the multivalent functions of CTCF based on chromatin state and three-dimensional chromatin architecture. We applied our method to five human cell lines and identified ~46 000 non-redundant CTCF sites related to the three functions. Disparate effects of these functions on gene expression were found and distinct genomic features of these CTCF sites were characterized in GM12878 cells. Finally, we investigated the cell-type specificities of CTCF sites related to these functions across five cell types. Our study provides new insights into the multivalent functions of CTCF in the human genome.
    Keywords: Computational Methods
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  • 14
    Publication Date: 2013-09-26
    Description: Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. We have developed an algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.
    Keywords: Computational Methods
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  • 15
    Publication Date: 2013-04-02
    Description: MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5' tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences.
    Keywords: Computational Methods
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  • 16
    Publication Date: 2013-09-26
    Description: It is a challenge to classify protein-coding or non-coding transcripts, especially those re-constructed from high-throughput sequencing data of poorly annotated species. This study developed and evaluated a powerful signature tool, Coding-Non-Coding Index (CNCI), by profiling adjoining nucleotide triplets to effectively distinguish protein-coding and non-coding sequences independent of known annotations. CNCI is effective for classifying incomplete transcripts and sense–antisense pairs. The implementation of CNCI offered highly accurate classification of transcripts assembled from whole-transcriptome sequencing data in a cross-species manner, that demonstrated gene evolutionary divergence between vertebrates, and invertebrates, or between plants, and provided a long non-coding RNA catalog of orangutan. CNCI software is available at http://www.bioinfo.org/software/cnci .
    Keywords: Computational Methods
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  • 17
    Publication Date: 2015-05-03
    Description: MicroRNAs (miRNAs) regulate gene expression by binding to partially complementary sequences on target mRNA transcripts, thereby causing their degradation, deadenylation, or inhibiting their translation. Genomic variants can alter miRNA regulation by modifying miRNA target sites, and multiple human disease phenotypes have been linked to such miRNA target site variants (miR-TSVs). However, systematic genome-wide identification of functional miR-TSVs is difficult due to high false positive rates; functional miRNA recognition sequences can be as short as six nucleotides, with the human genome encoding thousands of miRNAs. Furthermore, while large-scale clinical genomic data sets are becoming increasingly commonplace, existing miR-TSV prediction methods are not designed to analyze these data. Here, we present an open-source tool called SubmiRine that is designed to perform efficient miR-TSV prediction systematically on variants identified in novel clinical genomic data sets. Most importantly, SubmiRine allows for the prioritization of predicted miR-TSVs according to their relative probability of being functional. We present the results of SubmiRine using integrated clinical genomic data from a large-scale cohort study on chronic obstructive pulmonary disease (COPD), making a number of high-scoring, novel miR-TSV predictions. We also demonstrate SubmiRine's ability to predict and prioritize known miR-TSVs that have undergone experimental validation in previous studies.
    Keywords: Computational Methods
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  • 18
    Publication Date: 2014-12-17
    Description: Combinatorial transcription factor (TF) binding is essential for cell-type-specific gene regulation. However, much remains to be learned about the mechanisms of TF interactions, including to what extent constrained spacing and orientation of interacting TFs are critical for regulatory element activity. To examine the relative prevalence of the ‘enhanceosome’ versus the ‘TF collective’ model of combinatorial TF binding, a comprehensive analysis of TF binding site sequences in large scale datasets is necessary. We developed a motif-pair discovery pipeline to identify motif co-occurrences with preferential distance(s) between motifs in TF-bound regions. Utilizing a compendium of 289 mouse haematopoietic TF ChIP-seq datasets, we demonstrate that haematopoietic-related motif-pairs commonly occur with highly conserved constrained spacing and orientation between motifs. Furthermore, motif clustering revealed specific associations for both heterotypic and homotypic motif-pairs with particular haematopoietic cell types. We also showed that disrupting the spacing between motif-pairs significantly affects transcriptional activity in a well-known motif-pair—E-box and GATA, and in two previously unknown motif-pairs with constrained spacing—Ets and Homeobox as well as Ets and E-box. In this study, we provide evidence for widespread sequence-specific TF pair interaction with DNA that conforms to the ‘enhanceosome’ model, and furthermore identify associations between specific haematopoietic cell-types and motif-pairs.
    Keywords: Computational Methods
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  • 19
    Publication Date: 2015-01-24
    Description: Of the ~1.3 million Alu elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which Alu transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq data sets and unique Alu DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual Alu elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci corresponding to detectable transcripts, with ~120 of them expressed in at least three cell lines. In vitro transcription of selected Alu s did not reflect their in vivo expression properties, and required the native 5'-flanking region in addition to internal promoter. We also identified a cluster of expressed Alu Ya5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu -unrelated downstream moiety. Autonomous Pol III transcription was also revealed for Alu s nested within Pol II-transcribed genes. The ability to investigate Alu transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant Alu RNAs and the assessment of Alu expression alteration under pathological conditions.
    Keywords: Computational Methods
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  • 20
    Publication Date: 2014-12-17
    Description: Homologous non-coding RNAs frequently exhibit domain insertions, where a branch of secondary structure is inserted in a sequence with respect to its homologs. Dynamic programming algorithms for common secondary structure prediction of multiple RNA homologs, however, do not account for these domain insertions. This paper introduces a novel dynamic programming algorithm methodology that explicitly accounts for the possibility of inserted domains when predicting common RNA secondary structures. The algorithm is implemented as Dynalign II, an update to the Dynalign software package for predicting the common secondary structure of two RNA homologs. This update is accomplished with negligible increase in computational cost. Benchmarks on ncRNA families with domain insertions validate the method. Over base pairs occurring in inserted domains, Dynalign II improves accuracy over Dynalign, attaining 80.8% sensitivity (compared with 14.4% for Dynalign) and 91.4% positive predictive value (PPV) for tRNA; 66.5% sensitivity (compared with 38.9% for Dynalign) and 57.0% PPV for RNase P RNA; and 50.1% sensitivity (compared with 24.3% for Dynalign) and 58.5% PPV for SRP RNA. Compared with Dynalign, Dynalign II also exhibits statistically significant improvements in overall sensitivity and PPV. Dynalign II is available as a component of RNAstructure, which can be downloaded from http://rna.urmc.rochester.edu/RNAstructure.html .
    Keywords: Computational Methods
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  • 21
    Publication Date: 2016-04-08
    Description: Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based information. We present VIPUR, a computational framework that seamlessly integrates sequence analysis and structural modelling (using the Rosetta protein modelling suite) to identify and interpret deleterious protein variants. To train VIPUR, we collected 9477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models. VIPUR can be applied to mutations in any organism's proteome with improved generalized accuracy (AUROC .83) and interpretability (AUPR .87) compared to other methods. We demonstrate that VIPUR's predictions of deleteriousness match the biological phenotypes in ClinVar and provide a clear ranking of prediction confidence. We use VIPUR to interpret known mutations associated with inflammation and diabetes, demonstrating the structural diversity of disrupted functional sites and improved interpretation of mutations associated with human diseases. Lastly, we demonstrate VIPUR's ability to highlight candidate variants associated with human diseases by applying VIPUR to de novo variants associated with autism spectrum disorders.
    Keywords: Computational Methods
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  • 22
    Publication Date: 2016-04-08
    Description: Activating transcription factor 3 (ATF3) is a stress-induced transcriptional regulator in eukaryote. The role of ATF3 in cancer has been well defined, but how ATF3 functions in bacterial infection is not well understood. Pneumococcal infection has been shown to induce ATF3 expression, which subsequently enhances cytokine production and provides protection from lethal Streptococcus pneumoniae infection, but the role of ATF3 in other Gram-positive (G + ) infections remains unclear. Here, we report that infection with other G + bacteria ( Staphylococcus aureus and Listeria monocytogenes ) and with G – bacteria (uropathogenic Escherichia coli ) also significantly induced ATF3 expression. Moreover, the production of cytokines (tumor necrosis factor alpha [TNF]-α, interleukin [IL]-1β, IL-6 and interferon [IFN]-) was enhanced by ATF3 in S. aureus and L. monocytogenes infection, but decreased in uropathogenic E. coli (UPEC) infection. In addition, in S. aureus and L. monocytogenes infections, ATF3 WT mice cleared bacteria more efficiently and had higher survival rates than ATF3 knockout mice. However, in UPEC infection, no significant difference was found in survival rate. Taken together, these data suggest that ATF3 provides protection from S. aureus and L. monocytogenes infections; however, the role of ATF3 in UPEC infection is more complicated and should be further elucidated.
    Keywords: Pathogens & Pathogenicity
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  • 23
    Publication Date: 2016-07-02
    Description: The presence of carbapenemase gene bla KPC-2 in a wide variety of plasmids, especially conjugative plasmids, is key to the rapid, worldwide spread of carbapenemase enzymes. Thirty-eight, non-duplicated, carbapenem-resistant, clinical Klebsiella pneumoniae isolates were collected, all carrying bla KPC-2 -bearing plasmids. Relaxase analysis was used to classify these plasmids; 8 and 30 plasmids belonged to the MOB P3 and MOB F12 subfamilies, respectively. Phylogenetic analysis revealed two genetic subclades in the MOB F12 subfamily and suggested that these subclades might not have originated from the same ancestor. Crossing PCR, used to sequence fully the type IV secretion system (T4SS, essential structures for conjugative plasmids) of the MOB F12 plasmids, found that T4SSs were distinctively different in certain functional genes, e.g. traS and traG. In conclusion, this study delineated the evolution of bla KPC-2 -bearing plasmids at Huashan Hospital, Shanghai, China. The plasmids bearing bla KPC-2 were diverse and the MOB F12 plasmids were dominant in clinical K. pneumoniae isolates.
    Keywords: Pathogens & Pathogenicity
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  • 24
    Publication Date: 2016-08-28
    Description: Enteroaggregative Escherichia coli (EAEC) is an important diarrhoeal pathogen causing diseases in multiple epidemiological and clinical settings. In developing countries like India, diarrhoeal diseases are one of the major killers among paediatric population and oddly, few studies are available from Indian paediatric population on the variability of EAEC virulence genes. In this study, we examined the distribution of plasmid and chromosomal-encoded virulence determinants in EAEC isolates, and analysed cytokines response generated against EAEC with specific aggregative adherence fimbriae (AAF) type in duodenal biopsies using in vitro organ culture (IVOC) mimicking in vivo conditions. Different virulence marker combinations among strains were reflected as a function of specific adhesins signifying EAEC heterogeneity. fis gene emerged as an important genetic marker apart from aggA and aap . Further, EAEC infection in IVOC showed upregulation of IL-8, IL-1β, IL-6, TNF-α and TLR-5 expression. EAEC with AAFII induced significant TLR-5 and IL-8 response, conceivably owing to more pathogenicity markers. This study sheds light on the pattern of EAEC pathotypes prevalent in North Indian paediatric population and highlights the presence of unique virulence combinations in pathogenic strains. Thus, evident diversity in EAEC virulence and multifaceted bacteria-host crosstalk can provide useful insights for the strategic management of diarrhoeal diseases in India, where diarrhoeal outbreaks are more frequent.
    Keywords: Pathogens & Pathogenicity
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  • 25
    Publication Date: 2015-10-15
    Description: Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro , are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein–protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/
    Keywords: Computational Methods
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  • 26
    Publication Date: 2016-06-03
    Description: The sequential chain of interactions altering the binary state of a biomolecule represents the ‘information flow’ within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein–protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes—network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code ( http://www.NetDecoder.org ) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets.
    Keywords: Computational Methods
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  • 27
    Publication Date: 2016-06-17
    Description: Coagulase-negative staphylococci are thought to act as reservoirs of antibiotic resistance genes that can be transferred to Staphylococcus aureus , thus hindering the combat of this bacterium. In this work, we analyzed the presence of plasmids conferring resistance to the antibiotic mupirocin—widely used to treat and prevent S. aureus infections in hospital environments—in nosocomial S. haemolyticus strains. About 12% of the 75 strains tested were resistant to mupirocin, and this phenotype was correlated with the presence of plasmids. These plasmids were shown to be diverse, being either conjugative or mobilizable, and capable of transferring mupirocin resistance to S. aureus . Our findings reinforce that S. haemolyticus , historically and mistakenly considered as a less important pathogen, is a reservoir of resistance genes which can be transferred to other bacteria, such as S. aureus , emphasizing the necessity of more effective strategies to detect and combat this emergent opportunistic pathogen.
    Keywords: Pathogens & Pathogenicity
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  • 28
    Publication Date: 2016-06-17
    Description: Emergence of races in Fusarium oxysporum f. sp. lycopersici ( Fol ) is caused by loss or mutation of at least one avirulence ( AVR ) gene. The product of AVR1 is a small protein (Avr1) secreted by Fol in tomato xylem sap during infection. This protein triggers Fol race 1 specific resistance (I) in tomato, indicating that AVR1 is an AVR gene. Deletion of AVR1 in race 1 resulted in the emergence of race 2, and an additional mutation in AVR2 generated race 3. Previously, we reported a new biotype of race 3, KoChi-1, in which AVR1 was truncated by a transposon Hormin , which suggested a new route to evolution of races in Fol . However, to date no race 2 isolate carrying Hormin -truncated AVR1 has been reported. In this report, we describe such isolates, represented by Chiba-5, in which Hormin insertion occurred in AVR1 at a position different from that in KoChi-1. AVR1 truncation in both isolates resulted in production of defective Avr1 proteins. Chiba-5 and KoChi-1 belong to different phylogenetic clades, A1 and A2, respectively, suggesting that insertion of Hormin in AVR1 in Chiba-5 and KoChi-1 occurred as independent evolutionary events.
    Keywords: Pathogens & Pathogenicity
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  • 29
    Publication Date: 2016-09-02
    Description: The LBIT-1200 strain of Bacillus thuringiensis was recently isolated from soil, and showed a 6.4 and 9.5 increase in toxicity, against Manduca sexta and Trichoplusia ni , respectively, compared to HD-73. However, LBIT-1200 was still highly similar to HD-73, including the production of bipyramidal crystals containing only one protein of ~130 000 kDa, its flagellin gene sequence related to the kurstaki serotype, plasmid and RepPCR patterns similar to HD-73, no production of β-exotoxin and no presence of VIP genes. Sequencing of its cry gene showed the presence of a cry1Ac -type gene with four amino acid differences, including two amino acid replacements in domain III, compared to Cry1Ac1, which may explain its higher toxicity. In conclusion, the LBIT-1200 strain is a variant of the HD-73 strain but shows a much higher toxicity, which makes this new strain an important candidate to be developed as a bioinsecticide, once it passes other tests, throughout its biotechnological development.
    Keywords: Pathogens & Pathogenicity
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  • 30
    Publication Date: 2016-09-14
    Description: Gastrointestinal (GI) leakage in Clostridium difficile -associated diarrhea (CDAD) is well known but is not routinely assessed in clinical practice. Serum (1-〉3)-β-D-glucan (BG), a fungal cell wall component used as a biomarker for invasive fungal disease, was tested in a CDAD mouse model with and without probiotics. Higher serum fluorescein isothiocyanate-dextran (FITC-dextran) and spontaneous gram-negative bacteremia, GI leakage indicators, were frequently found in CDAD mice, which died compared with those which survived. BG, serum macrophage inflammatory protein-2 and FITC-dextran but not quantitative blood bacterial count differentiated the clinical severity. Interestingly, a specific dose of Lactobacillus rhamnosus L34 attenuated CDAD and decreased serum BG and FITC-dextran, but not other parameters. BG also showed a higher area under the receiver operating characteristic curve for 7-day mortality than FITC-dextran. Fifty-five percent of CDAD mice with BG ≥ 60 pg/ml (the human negative cut-off value for invasive fungal disease) at 1 day after C. difficile gavage died within 7 days. In conclusion, s erum BG was elevated in mice with severe CDAD, an established model of GI leakage with a strong association with mortality rate. BG monitoring in patients with CDAD is of interest as both a potential prognostic tool and a therapeutic efficacy indicator.
    Keywords: Pathogens & Pathogenicity
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  • 31
    Publication Date: 2016-08-28
    Description: Chlamydial species are common intracellular parasites that cause various diseases, mainly characterized by persistent infection, which lead to inflammatory responses modulated by pattern recognition receptors (PRRs). The best understood PRRs are the extracellular Toll-like receptors, but recent significant advances have focused on two important proteins, NOD1 and NOD2, which are members of the intracellular nucleotide-binding oligomerization domain receptor family and are capable of triggering the host innate immune signaling pathways. This results in the production of pro-inflammatory cytokines, which is vital for an adequate host defense against intracellular chlamydial infection. NOD1/2 ligands are known to derive from peptidoglycan, and the latest research has resolved the paradox of whether chlamydial species possess this bacterial cell wall component; this finding is likely to promote in-depth investigations into the interaction between the NOD proteins and chlamydial pathogens. In this review, we summarize the basic characteristics and signal transduction functions of NOD1 and NOD2 and highlight the new research on the roles of NOD1 and NOD2 in the host defense against chlamydial infection.
    Keywords: Pathogens & Pathogenicity
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  • 32
    Publication Date: 2016-08-28
    Description: Two strains of Aeromonas salmonicida , YK and BG, were isolated from largemouth bronze gudgeon and northern whitefish in China, and identified as A. salmonicida subsp. salmonicida based on phylogenetic analysis of vapA and 16S rRNA gene sequences. YK and BG originated from freshwater fish, one of which belonged to the cyprinid family, and the strains showed a difference in virulence. Subsequently, we performed whole genome sequencing of the strains, and comparison of their genomic sequences to the genome of the A449 reference strain revealed various genomic rearrangements, including a new variant of the genomic island AsaGEI in BG, designated as AsaGEI2c . This is the first report on a GEI of A. salmonicida strain from China. Furthermore, both YK and BG strains contained a Tn7 transposon inserted at the same position in the chromosome. Finally, IS-dependent rearrangements on pAsa5 are deemed likely to have occurred, with omission of the resD gene in both strains as well as omission of genes related to the IncF conjugal transfer system in the YK isolate. This study demonstrates that A. salmonicida subsp. salmonicida can infect non-salmonids (cyprinids) in addition to salmonids, and that AsaGEI2c might be useful as a geographical indicator of Chinese A. salmonicida subsp. salmonicida isolates.
    Keywords: Pathogens & Pathogenicity
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  • 33
    Publication Date: 2016-07-09
    Description: Burkholderia pseudomallei is an intracellular Gram-negative bacterial pathogen and the causative agent of melioidosis, a widespread disease in Southeast Asia. Reactive nitrogen, in an intermediate form of nitric oxide (NO), is one of the first lines of defense used by host cells to eliminate intracellular pathogens, through the stimulation of inducible nitric oxide synthase (iNOS). Studies in phagocytotic cells have shown that the iNOS response is muted in B. pseudomallei infection, and implicated the rpoS sigma factor as a key regulatory factor mediating suppression. The liver is a main visceral organ affected by B. pseudomallei , and there is little knowledge about the interaction of liver cells and B. pseudomallei . This study investigated the induction of iNOS, as well as autophagic flux and light-chain 3 (LC3) localization in human liver (HC04) cells in response to infection with B. pseudomallei and its rpoS deficient mutant. Results showed that the rpoS mutant was unable to suppress iNOS induction and that the mutant showed less induction of autophagy and lower co-localization with LC3, and this was coupled with a lower intracellular growth rate. Combining these results suggest that B. pseudomallei rpoS is an important factor in establishing infection in liver cells.
    Keywords: Pathogens & Pathogenicity
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  • 34
    Publication Date: 2015-04-21
    Description: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
    Keywords: Computational Methods
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  • 35
    Publication Date: 2015-02-18
    Description: Protein sequences predicted from metagenomic datasets are annotated by identifying their homologs via sequence comparisons with reference or curated proteins. However, a majority of metagenomic protein sequences are partial-length, arising as a result of identifying genes on sequencing reads or on assembled nucleotide contigs, which themselves are often very fragmented. The fragmented nature of metagenomic protein predictions adversely impacts homology detection and, therefore, the quality of the overall annotation of the dataset. Here we present a novel algorithm called GRASP that accurately identifies the homologs of a given reference protein sequence from a database consisting of partial-length metagenomic proteins. Our homology detection strategy is guided by the reference sequence, and involves the simultaneous search and assembly of overlapping database sequences. GRASP was compared to three commonly used protein sequence search programs (BLASTP, PSI-BLAST and FASTM). Our evaluations using several simulated and real datasets show that GRASP has a significantly higher sensitivity than these programs while maintaining a very high specificity. GRASP can be a very useful program for detecting and quantifying taxonomic and protein family abundances in metagenomic datasets. GRASP is implemented in GNU C++, and is freely available at http://sourceforge.net/projects/grasp-release .
    Keywords: Computational Methods
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  • 36
    Publication Date: 2015-02-18
    Description: Genetic screens of an unprecedented scale have recently been made possible by the availability of high-complexity libraries of synthetic oligonucleotides designed to mediate either gene knockdown or gene knockout, coupled with next-generation sequencing. However, several sources of random noise and statistical biases complicate the interpretation of the resulting high-throughput data. We developed HiTSelect, a comprehensive analysis pipeline for rigorously selecting screen hits and identifying functionally relevant genes and pathways by addressing off-target effects, controlling for variance in both gene silencing efficiency and sequencing depth of coverage and integrating relevant metadata. We document the superior performance of HiTSelect using data from both genome-wide RNAi and CRISPR/Cas9 screens. HiTSelect is implemented as an open-source package, with a user-friendly interface for data visualization and pathway exploration. Binary executables are available at http://sourceforge.net/projects/hitselect/ , and the source code is available at https://github.com/diazlab/HiTSelect .
    Keywords: Computational Methods
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  • 37
    Publication Date: 2015-01-24
    Description: Integrative analyses of epigenetic data promise a deeper understanding of the epigenome. Epidaurus is a bioinformatics tool used to effectively reveal inter-dataset relevance and differences through data aggregation, integration and visualization. In this study, we demonstrated the utility of Epidaurus in validating hypotheses and generating novel biological insights. In particular, we described the use of Epidaurus to (i) integrate epigenetic data from prostate cancer cell lines to validate the activation function of EZH2 in castration-resistant prostate cancer and to (ii) study the mechanism of androgen receptor ( AR ) binding deregulation induced by the knockdown of FOXA1 . We found that EZH2 's noncanonical activation function was reaffirmed by its association with active histone markers and the lack of association with repressive markers. More importantly, we revealed that the binding of AR was selectively reprogramed to promoter regions, leading to the up-regulation of hundreds of cancer-associated genes including EGFR . The prebuilt epigenetic dataset from commonly used cell lines (LNCaP, VCaP, LNCaP-Abl, MCF7, GM12878, K562, HeLa-S3, A549, HePG2) makes Epidaurus a useful online resource for epigenetic research. As standalone software, Epidaurus is specifically designed to process user customized datasets with both efficiency and convenience.
    Keywords: Computational Methods
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  • 38
    Publication Date: 2015-02-18
    Description: RNA-protein complexes are essential in mediating important fundamental cellular processes, such as transport and localization. In particular, ncRNA-protein interactions play an important role in post-transcriptional gene regulation like mRNA localization, mRNA stabilization, poly-adenylation, splicing and translation. The experimental methods to solve RNA-protein interaction prediction problem remain expensive and time-consuming. Here, we present the RPI-Pred (RNA-protein interaction predictor), a new support-vector machine-based method, to predict protein-RNA interaction pairs, based on both the sequences and structures. The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with ~94% prediction accuracy when using sequence and experimentally determined protein and RNA structures, and with ~83% when using sequences and predicted protein and RNA structures. Further, our proposed method RPI-Pred was superior to other existing ones by predicting more experimentally validated ncRNA-protein interaction pairs from different organisms. Motivated by the improved performance of RPI-Pred, we further applied our method for reliable construction of ncRNA-protein interaction networks. The RPI-Pred is publicly available at: http://ctsb.is.wfubmc.edu/projects/rpi-pred .
    Keywords: Computational Methods
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  • 39
    Publication Date: 2015-02-18
    Description: Identifying conserved and divergent response patterns in gene networks is becoming increasingly important. A common approach is integrating expression information with gene association networks in order to find groups of connected genes that are activated or repressed. In many cases, researchers are also interested in comparisons across species (or conditions). Finding an active sub-network is a hard problem and applying it across species requires further considerations (e.g. orthology information, expression data and networks from different sources). To address these challenges we devised ModuleBlast, which uses both expression and network topology to search for highly relevant sub-networks. We have applied ModuleBlast to expression and interaction data from mouse, macaque and human to study immune response and aging. The immune response analysis identified several relevant modules, consistent with recent findings on apoptosis and NFB activation following infection. Temporal analysis of these data revealed cascades of modules that are dynamically activated within and across species. We have experimentally validated some of the novel hypotheses resulting from the analysis of the ModuleBlast results leading to new insights into the mechanisms used by a key mammalian aging protein.
    Keywords: Computational Methods
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  • 40
    Publication Date: 2015-02-18
    Description: Here we used discriminative training methods to uncover the chromatin, transcription factor (TF) binding and sequence features of enhancers underlying gene expression in individual cardiac cells. We used machine learning with TF motifs and ChIP data for a core set of cardiogenic TFs and histone modifications to classify Drosophila cell-type-specific cardiac enhancer activity. We show that the classifier models can be used to predict cardiac cell subtype cis -regulatory activities. Associating the predicted enhancers with an expression atlas of cardiac genes further uncovered clusters of genes with transcription and function limited to individual cardiac cell subtypes. Further, the cell-specific enhancer models revealed chromatin, TF binding and sequence features that distinguish enhancer activities in distinct subsets of heart cells. Collectively, our results show that computational modeling combined with empirical testing provides a powerful platform to uncover the enhancers, TF motifs and gene expression profiles which characterize individual cardiac cell fates.
    Keywords: Computational Methods
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  • 41
    Publication Date: 2015-09-30
    Description: A key aspect of RNA secondary structure prediction is the identification of novel functional elements. This is a challenging task because these elements typically are embedded in longer transcripts where the borders between the element and flanking regions have to be defined. The flanking sequences impact the folding of the functional elements both at the level of computational analyses and when the element is extracted as a transcript for experimental analysis. Here, we analyze how different flanking region lengths impact folding into a constrained structure by computing probabilities of folding for different sizes of flanking regions. Our method, RNAcop (RNA context optimization by probability), is tested on known and de novo predicted structures. In vitro experiments support the computational analysis and suggest that for a number of structures, choosing proper lengths of flanking regions is critical. RNAcop is available as web server and stand-alone software via http://rth.dk/resources/rnacop .
    Keywords: Computational Methods
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  • 42
    Publication Date: 2016-02-20
    Description: Bacteriophages are viruses that infect bacteria. There are an estimated 10 31 phage on the planet, making them the most abundant form of life. We are rapidly approaching the centenary of their identification, and yet still have only a limited understanding of their role in the ecology and evolution of bacterial populations. Temperate prophage carriage is often associated with increased bacterial virulence. The rise in use of technologies, such as genome sequencing and transcriptomics, has highlighted more subtle ways in which prophages contribute to pathogenicity. This review discusses the current knowledge of the multifaceted effects that phage can exert on their hosts and how this may contribute to bacterial adaptation during infection.
    Keywords: Pathogens & Pathogenicity
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  • 43
    Publication Date: 2016-02-20
    Description: Phthiocerol dimycocerosates (PDIMs) and phenolic glycolipids (PGLs) contribute to the pathogenicity of several mycobacteria. Biosynthesis of these virulence factors requires polyketide synthases and other enzymes that represent potential targets for the development of adjuvant antivirulence drugs. We used six isogenic Mycobacterium marinum mutants, each with a different gene knockout in the PDIM/PGL biosynthetic pathway, to probe the pleiotropy of mutations leading to PDIM – PGL – , PDIM + PGL – or PDIM – PGL + phenotypes. We evaluated the M. marinum mutants for changes in antibiotic susceptibility, cell envelope permeability, biofilm formation, surface properties, sliding motility and virulence in an amoeba model. The analysis also permitted us to begin exploring the hypothesis that different gene knockouts rendering the same PDIM and/or PGL deficiency phenotypes lead to M. marinum mutants with equivalent pleiotropic profiles. Overall, the results of our study revealed a complex picture of pleiotropic patterns emerging from different gene knockouts, uncovered unexpected phenotypic inequalities between mutants, and provided new insight into the phenotypic consequences of gene knockouts in the PDIM/PGL biosynthetic pathway.
    Keywords: Pathogens & Pathogenicity
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  • 44
    Publication Date: 2016-02-20
    Description: Culture medium from an isolate of the fungus Aspergillus candidus was extracted, fractionated and examined to discover compounds antagonistic to plant-parasitic nematodes that are important pathogens of agricultural crops. Column, thin layer and preparative chromatographies and spectral and elemental analyses, were used to isolate and identify two major constituents of an active fraction (Fraction F) obtained from the medium. Compound 1 was identified as 2-hydroxypropane-1, 2, 3-tricarboxylic acid (citric acid). Compound 2 was identified as 3-hydroxy-5-methoxy-3-(methoxycarbonyl)-5-oxopentanoic acid, an isomer of 1, 2-dimethyl citrate. Compound 1 and a citric acid standard, each tested at 50 mg mL –1 in water, decreased hatch from eggs of the plant-parasitic nematode Meloidogyne incognita by more than 94%, and completely immobilized second-stage juveniles after 4–6 days exposure. Fraction F and Compounds 1 and 2 decreased the mobility of adults of the plant-parasitic nematode Ditylenchus destructor in vitro . Fraction F (25 mg mL –1 ) inhibited mobility 〉99% at 72 hrs. Compounds 1 and 2 (50 mg mL –1 ) each inhibited mobility more than 25% at 24 hr and more than 50% at 72 hr. This is the first assignment of nematode-antagonistic properties to specifically identified A. candidus metabolites.
    Keywords: Pathogens & Pathogenicity
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  • 45
    Publication Date: 2016-03-01
    Description: It is being increasingly realized that nucleosome organization on DNA crucially regulates DNA–protein interactions and the resulting gene expression. While the spatial character of the nucleosome positioning on DNA has been experimentally and theoretically studied extensively, the temporal character is poorly understood. Accounting for ATPase activity and DNA-sequence effects on nucleosome kinetics, we develop a theoretical method to estimate the time of continuous exposure of binding sites of non-histone proteins (e.g. transcription factors and TATA binding proteins) along any genome. Applying the method to Saccharomyces cerevisiae , we show that the exposure timescales are determined by cooperative dynamics of multiple nucleosomes, and their behavior is often different from expectations based on static nucleosome occupancy. Examining exposure times in the promoters of GAL1 and PHO5, we show that our theoretical predictions are consistent with known experiments. We apply our method genome-wide and discover huge gene-to-gene variability of mean exposure times of TATA boxes and patches adjacent to TSS (+1 nucleosome region); the resulting timescale distributions have non-exponential tails.
    Keywords: Computational Methods
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  • 46
    Publication Date: 2016-02-27
    Keywords: Pathogens & Pathogenicity
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  • 47
    Publication Date: 2016-02-25
    Description: An RNAi system based on T7 RNA polymerase (TRNAP) was designed and examined in Aspergillus fumigatus . This system consists of two elements; an inducible T7RNAP expressing cassette and an AMA1-based episomal RNAi plasmid. These constructs were transformed into the A. fumigatus protoplasts and the efficiency of this system was tested in downregulation of alb1 gene. Upon the induction of T7RNAP expression, the recombinant T7RNAP was able to recognize T7 promoters, which were located on the episomal plasmid and in opposite direction. As a result, the bidirectional transcription of alb1 fragment led to the silencing of the target gene. However, our results demonstrated that this silencing system is unstable and may not be applicable in preparation of RNAi libraries.
    Keywords: Pathogens & Pathogenicity
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  • 48
    Publication Date: 2015-10-31
    Description: Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx .
    Keywords: Computational Methods
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  • 49
    Publication Date: 2015-12-02
    Description: Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.
    Keywords: Computational Methods
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  • 50
    Publication Date: 2015-12-02
    Description: Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein–DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein–DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions.
    Keywords: Computational Methods
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  • 51
    Publication Date: 2012-07-22
    Description: Sequence elements, at all levels—DNA, RNA and protein, play a central role in mediating molecular recognition and thereby molecular regulation and signaling. Studies that focus on measuring and investigating sequence-based recognition make use of statistical and computational tools, including approaches to searching sequence motifs. State-of-the-art motif searching tools are limited in their coverage and ability to address large motif spaces. We develop and present statistical and algorithmic approaches that take as input ranked lists of sequences and return significant motifs. The efficiency of our approach, based on suffix trees, allows searches over motif spaces that are not covered by existing tools. This includes searching variable gap motifs—two half sites with a flexible length gap in between—and searching long motifs over large alphabets. We used our approach to analyze several high-throughput measurement data sets and report some validation results as well as novel suggested motifs and motif refinements. We suggest a refinement of the known estrogen receptor 1 motif in humans, where we observe gaps other than three nucleotides that also serve as significant recognition sites, as well as a variable length motif related to potential tyrosine phosphorylation.
    Keywords: Computational Methods
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  • 52
    Publication Date: 2012-07-22
    Description: Cataloging the association of transcripts to genetic variants in recent years holds the promise for functional dissection of regulatory structure of human transcription. Here, we present a novel approach, which aims at elucidating the joint relationships between transcripts and single-nucleotide polymorphisms (SNPs). This entails detection and analysis of modules of transcripts, each weakly associated to a single genetic variant, together exposing a high-confidence association signal between the module and this ‘main’ SNP. To explore how transcripts in a module are related to causative loci for that module, we represent such dependencies by a graphical model. We applied our method to the existing data on genetics of gene expression in the liver. The modules are significantly more, larger and denser than found in permuted data. Quantification of the confidence in a module as a likelihood score, allows us to detect transcripts that do not reach genome-wide significance level. Topological analysis of each module identifies novel insights regarding the flow of causality between the main SNP and transcripts. We observe similar annotations of modules from two sources of information: the enrichment of a module in gene subsets and locus annotation of the genetic variants. This and further phenotypic analysis provide a validation for our methodology.
    Keywords: Computational Methods
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  • 53
    Publication Date: 2012-07-22
    Description: Phase variation of surface structures occurs in diverse bacterial species due to stochastic, high frequency, reversible mutations. Multiple genes of Campylobacter jejuni are subject to phase variable gene expression due to mutations in polyC/G tracts. A modal length of nine repeats was detected for polyC/G tracts within C. jejuni genomes. Switching rates for these tracts were measured using chromosomally-located reporter constructs and high rates were observed for cj1139 (G8) and cj0031 (G9). Alteration of the cj1139 tract from G8 to G11 increased mutability 10-fold and changed the mutational pattern from predominantly insertions to mainly deletions. Using a multiplex PCR, major changes were detected in ‘on/off’ status for some phase variable genes during passage of C. jejuni in chickens. Utilization of observed switching rates in a stochastic, theoretical model of phase variation demonstrated links between mutability and genetic diversity but could not replicate observed population diversity. We propose that modal repeat numbers have evolved in C. jejuni genomes due to molecular drivers associated with the mutational patterns of these polyC/G repeats, rather than by selection for particular switching rates, and that factors other than mutational drift are responsible for generating genetic diversity during host colonization by this bacterial pathogen.
    Keywords: Computational Methods
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  • 54
    Publication Date: 2012-09-13
    Description: Control of translation in eukaryotes is complex, depending on the binding of various factors to mRNAs. Available data for subsets of mRNAs that are translationally up- and down-regulated in yeast eIF4E-binding protein (4E-BP) deletion mutants are coupled with reported mRNA secondary structure measurements to investigate whether 5'-UTR secondary structure varies between the subsets. Genes with up-regulated translational efficiencies in the caf20 mutant have relatively high averaged 5'-UTR secondary structure. There is no apparent wide-scale correlation of RNA-binding protein preferences with the increased 5'-UTR secondary structure, leading us to speculate that the secondary structure itself may play a role in differential partitioning of mRNAs between eIF4E/4E-BP repression and eIF4E/eIF4G translation initiation. Both Caf20p and Eap1p contain stretches of positive charge in regions of predicted disorder. Such regions are also present in eIF4G and have been reported to associate with mRNA binding. The pattern of these segments, around the canonical eIF4E-binding motif, varies between each 4E-BP and eIF4G. Analysis of gene ontology shows that yeast proteins containing predicted disordered segments, with positive charge runs, are enriched for nucleic acid binding. We propose that the 4E-BPs act, in part, as differential, flexible, polyelectrostatic scaffolds for mRNAs.
    Keywords: Computational Methods
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  • 55
    Publication Date: 2012-05-23
    Description: The activation of cryptic 5' splice sites (5' SSs) is often related to human hereditary diseases. The DNA-based mutation screening strategies are commonly used to recognize the cryptic 5' SSs, because features of the local DNA sequence can influence the choice of cryptic 5' SSs. To improve the identification of the cryptic 5' SSs, we developed a structure-based method, named SPO (structure profiles and odds measure), which combines two parameters, the structural feature derived from hydroxyl radical cleavage pattern and odds measure, to assess the likelihood of a cryptic 5' SS activation in competing with its paired authentic 5' SS. Compared to the current tools for identifying activated cryptic 5' SSs, the SPO algorithm achieves higher prediction accuracy than the other methods, including MaxEnt, MDD, Markov model, weight matrix model, Shapiro and Senapathy matrix, R i and G . In addition, the predicted SPO scores from the SPO algorithm exhibited a greater degree of correlation with the strength of cryptic 5' SS activation than that measured from the other seven methods. In conclusion, the SPO algorithm provides an optimal identification of cryptic 5' SSs, can be applied in designing mutagenesis experiments for various splicing events and may be helpful to investigate the relationship between structural variants and human hereditary diseases.
    Keywords: Computational Methods
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  • 56
    Publication Date: 2014-05-01
    Description: Determining the taxonomic affiliation of sequences assembled from metagenomes remains a major bottleneck that affects research across the fields of environmental, clinical and evolutionary microbiology. Here, we introduce MyTaxa, a homology-based bioinformatics framework to classify metagenomic and genomic sequences with unprecedented accuracy. The distinguishing aspect of MyTaxa is that it employs all genes present in an unknown sequence as classifiers, weighting each gene based on its (predetermined) classifying power at a given taxonomic level and frequency of horizontal gene transfer. MyTaxa also implements a novel classification scheme based on the genome-aggregate average amino acid identity concept to determine the degree of novelty of sequences representing uncharacterized taxa, i.e. whether they represent novel species, genera or phyla. Application of MyTaxa on in silico generated (mock) and real metagenomes of varied read length (100–2000 bp) revealed that it correctly classified at least 5% more sequences than any other tool. The analysis also showed that ~10% of the assembled sequences from human gut metagenomes represent novel species with no sequenced representatives, several of which were highly abundant in situ such as members of the Prevotella genus. Thus, MyTaxa can find several important applications in microbial identification and diversity studies.
    Keywords: Computational Methods
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  • 57
    Publication Date: 2014-02-11
    Description: Increasing numbers of protein structures are solved each year, but many of these structures belong to proteins whose sequences are homologous to sequences in the Protein Data Bank. Nevertheless, the structures of homologous proteins belonging to the same family contain useful information because functionally important residues are expected to preserve physico-chemical, structural and energetic features. This information forms the basis of our method, which detects RNA-binding residues of a given RNA-binding protein as those residues that preserve physico-chemical, structural and energetic features in its homologs. Tests on 81 RNA-bound and 35 RNA-free protein structures showed that our method yields a higher fraction of true RNA-binding residues (higher precision) than two structure-based and two sequence-based machine-learning methods. Because the method requires no training data set and has no parameters, its precision does not degrade when applied to ‘novel’ protein sequences unlike methods that are parameterized for a given training data set. It was used to predict the ‘unknown’ RNA-binding residues in the C-terminal RNA-binding domain of human CPEB3. The two predicted residues, F430 and F474, were experimentally verified to bind RNA, in particular F430, whose mutation to alanine or asparagine nearly abolished RNA binding. The method has been implemented in a webserver called DR_bind1, which is freely available with no login requirement at http://drbind.limlab.ibms.sinica.edu.tw .
    Keywords: Computational Methods
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  • 58
    Publication Date: 2014-10-10
    Description: Nanotechnology and synthetic biology currently constitute one of the most innovative, interdisciplinary fields of research, poised to radically transform society in the 21st century. This paper concerns the synthetic design of ribonucleic acid molecules, using our recent algorithm, RNAiFold , which can determine all RNA sequences whose minimum free energy secondary structure is a user-specified target structure. Using RNAiFold , we design ten cis -cleaving hammerhead ribozymes, all of which are shown to be functional by a cleavage assay. We additionally use RNAiFold to design a functional cis -cleaving hammerhead as a modular unit of a synthetic larger RNA. Analysis of kinetics on this small set of hammerheads suggests that cleavage rate of computationally designed ribozymes may be correlated with positional entropy, ensemble defect, structural flexibility/rigidity and related measures. Artificial ribozymes have been designed in the past either manually or by SELEX (Systematic Evolution of Ligands by Exponential Enrichment); however, this appears to be the first purely computational design and experimental validation of novel functional ribozymes. RNAiFold is available at http://bioinformatics.bc.edu/clotelab/RNAiFold/ .
    Keywords: Computational Methods
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  • 59
    Publication Date: 2014-09-27
    Description: While mRNA stability has been demonstrated to control rates of translation, generating both global and local synonymous codon biases in many unicellular organisms, this explanation cannot adequately explain why codon bias strongly tracks neighboring intergene GC content; suggesting that structural dynamics of DNA might also influence codon choice. Because minor groove width is highly governed by 3-base periodicity in GC, the existence of triplet-based codons might imply a functional role for the optimization of local DNA molecular dynamics via GC content at synonymous sites (GC3). We confirm a strong association between GC3-related intrinsic DNA flexibility and codon bias across 24 different prokaryotic multiple whole-genome alignments. We develop a novel test of natural selection targeting synonymous sites and demonstrate that GC3-related DNA backbone dynamics have been subject to moderate selective pressure, perhaps contributing to our observation that many genes possess extreme DNA backbone dynamics for their given protein space. This dual function of codons may impose universal functional constraints affecting the evolution of synonymous and non-synonymous sites. We propose that synonymous sites may have evolved as an ‘accessory’ during an early expansion of a primordial genetic code, allowing for multiplexed protein coding and structural dynamic information within the same molecular context.
    Keywords: Computational Methods
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  • 60
    Publication Date: 2014-12-17
    Description: The thermophilic fungus Chaetomium thermophilum holds great promise for structural biology. To increase the efficiency of its biochemical and structural characterization and to explore its thermophilic properties beyond those of individual proteins, we obtained transcriptomics and proteomics data, and integrated them with computational annotation methods and a multitude of biochemical experiments conducted by the structural biology community. We considerably improved the genome annotation of Chaetomium thermophilum and characterized the transcripts and expression of thousands of genes. We furthermore show that the composition and structure of the expressed proteome of Chaetomium thermophilum is similar to its mesophilic relatives. Data were deposited in a publicly available repository and provide a rich source to the structural biology community.
    Keywords: Computational Methods
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  • 61
    Publication Date: 2015-03-14
    Description: The rapid discovery of potential driver mutations through large-scale mutational analyses of human cancers generates a need to characterize their cellular phenotypes. Among the techniques for genome editing, recombinant adeno-associated virus (rAAV)-mediated gene targeting is suited for knock-in of single nucleotide substitutions and to a lesser degree for gene knock-outs. However, the generation of gene targeting constructs and the targeting process is time-consuming and labor-intense. To facilitate rAAV-mediated gene targeting, we developed the first software and complementary automation-friendly vector tools to generate optimized targeting constructs for editing human protein encoding genes. By computational approaches, rAAV constructs for editing ~71% of bases in protein-coding exons were designed. Similarly, ~81% of genes were predicted to be targetable by rAAV-mediated knock-out. A Gateway-based cloning system for facile generation of rAAV constructs suitable for robotic automation was developed and used in successful generation of targeting constructs. Together, these tools enable automated rAAV targeting construct design, generation as well as enrichment and expansion of targeted cells with desired integrations.
    Keywords: Computational Methods
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  • 62
    Publication Date: 2015-03-14
    Description: Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.
    Keywords: Computational Methods
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  • 63
    Publication Date: 2015-01-10
    Description: Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo -derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/ .
    Keywords: Computational Methods
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  • 64
    Publication Date: 2012-10-10
    Description: The Joint BioEnergy Institute Inventory of Composable Elements (JBEI-ICEs) is an open source registry platform for managing information about biological parts. It is capable of recording information about ‘legacy’ parts, such as plasmids, microbial host strains and Arabidopsis seeds, as well as DNA parts in various assembly standards. ICE is built on the idea of a web of registries and thus provides strong support for distributed interconnected use. The information deposited in an ICE installation instance is accessible both via a web browser and through the web application programming interfaces, which allows automated access to parts via third-party programs. JBEI-ICE includes several useful web browser-based graphical applications for sequence annotation, manipulation and analysis that are also open source. As with open source software, users are encouraged to install, use and customize JBEI-ICE and its components for their particular purposes. As a web application programming interface, ICE provides well-developed parts storage functionality for other synthetic biology software projects. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects. The ICE software suite is available via Google Code, a hosting site for community-driven open source projects.
    Keywords: Computational Methods
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  • 65
    Publication Date: 2014-05-01
    Description: Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k -mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25 x coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing.
    Keywords: Computational Methods
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  • 66
    Publication Date: 2014-09-02
    Description: Functional mechanisms of biomolecules often manifest themselves precisely in transient conformational substates. Researchers have long sought to structurally characterize dynamic processes in non-coding RNA, combining experimental data with computer algorithms. However, adequate exploration of conformational space for these highly dynamic molecules, starting from static crystal structures, remains challenging. Here, we report a new conformational sampling procedure, KGSrna, which can efficiently probe the native ensemble of RNA molecules in solution. We found that KGSrna ensembles accurately represent the conformational landscapes of 3D RNA encoded by NMR proton chemical shifts. KGSrna resolves motionally averaged NMR data into structural contributions; when coupled with residual dipolar coupling data, a KGSrna ensemble revealed a previously uncharacterized transient excited state of the HIV-1 trans-activation response element stem–loop. Ensemble-based interpretations of averaged data can aid in formulating and testing dynamic, motion-based hypotheses of functional mechanisms in RNAs with broad implications for RNA engineering and therapeutic intervention.
    Keywords: Computational Methods
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  • 67
    Publication Date: 2014-09-02
    Description: Binding of transcription factors to their binding sites in promoter regions is the fundamental event in transcriptional gene regulation. When a transcription factor binding site is located within a nucleosome, the DNA has to partially unwrap from the nucleosome to allow transcription factor binding. This reduces the rate of transcription factor binding and is a known mechanism for regulation of gene expression via chromatin structure. Recently a second mechanism has been reported where transcription factor off-rates are dramatically increased when binding to target sites within the nucleosome. There are two possible explanations for such an increase in off-rate short of an active role of the nucleosome in pushing the transcription factor off the DNA: (i) for dimeric transcription factors the nucleosome can change the equilibrium between monomeric and dimeric binding or (ii) the nucleosome can change the equilibrium between specific and non-specific binding to the DNA. We explicitly model both scenarios and find that dimeric binding can explain a large increase in off-rate while the non-specific binding model cannot be reconciled with the large, experimentally observed increase. Our results suggest a general mechanism how nucleosomes increase transcription factor dissociation to promote exchange of transcription factors and regulate gene expression.
    Keywords: Computational Methods
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  • 68
    Publication Date: 2014-08-15
    Description: High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A , a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.
    Keywords: Computational Methods
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  • 69
    Publication Date: 2016-05-20
    Description: A simple diagnosis of the presence or absence of an infection is an uninformative metric when individuals differ considerably in their tolerance to different infection loads or resistance to rates of disease progression. Models that incorporate the relationship between the progression of the infection with the potential alternate outcomes provide a far more powerful predictive tool than diagnosis alone. The global decline of amphibians has been amplified by Batrachochytrium dendrobatidis , a pathogen that can cause the fatal disease chytridiomycosis. We measured the infection load and observed signs of disease in Litoria aurea . Receiver operating characteristic curves were used to quantify the dissimilarity between the infection loads of L. aurea that showed signs associated with chytridiomycosis and those that did not. Litoria aurea had a 78% probability of developing chytridiomycosis past a threshold of 68 zoospore equivalents (ZE) per swab and chytridiomycosis occurred within a variable range of 0.5–490 ZE. Studies should incorporate a species-specific threshold as a predictor of chytridiomycosis, rather than a binary diagnosis. Measures of susceptibility to chytridiomycosis must account not only for the ability of B. dendrobatidis to increase its abundance on the skin of amphibians but also to determine how each species tolerates these infection loads.
    Keywords: Pathogens & Pathogenicity
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  • 70
    Publication Date: 2016-03-24
    Description: The control and prevention of biofilm-related infections is an important public healthcare issue. Given the increasing antibiotic resistance among bacteria and fungi that cause serious infections in humans, promotion of new strategies combating microorganisms has been essential. One attractive approach to inactivate microorganisms is the use of semiconductor photo-catalysis, which has become the subject of extensive research. In this study, the bactericidal properties of four photo-catalysts, TiO 2 , TiO 2 -S, TiO 2 -Eu and TiO 2 -Eu-S, were investigated against established 24, 48, 72 and 96 h biofilms of Enterococcus . The exposure of biofilms to the catalysts induced the production of superoxide radical anions. The best photo-catalytic inactivation was achieved with the TiO 2 -Eu-S and TiO 2 -S nanopowders and 24 h biofilms. Transmission electron microscopy images showed significant changes in the structure of the biofilm cells following photo-inactivation. The results suggest that doping with europium and modifying the surface with sulphate groups enhanced the bactericidal activity of the TiO 2 nanoparticles against enterococcal biofilms.
    Keywords: Pathogens & Pathogenicity
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  • 71
    Publication Date: 2016-05-25
    Description: The Pseudomonas aeruginosa Chp chemosensory system regulates twitching motility, intracellular adenosine 3 '' 5 ' -cyclic monophosphate (cAMP) levels and is postulated to be involved in directional twitching towards phosphatidylethanolamine (PE). Because PilJ is the only methyl-accepting chemotaxis protein (MCP) identified in the Chp system, we determined the role of PilJ in mediating signal transduction for the distinct outputs of this system. Mutants that lack the periplasmic domain of PilJ ( pilJ 74-273 ) showed lower levels of cAMP but retained directional twitching towards PE. While initial studies revealed reduced twitching motility by PilJ 74-273 , this was due to decreased cAMP levels. Our data illustrate the importance of the periplasmic domain of PilJ in regulating cAMP. This is the first time a defined domain within PilJ has been identified as having a distinct role in signal transduction.
    Keywords: Pathogens & Pathogenicity
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  • 72
    Publication Date: 2016-04-24
    Description: Histone-like nucleoid-structuring (H-NS) proteins, which are conserved in Gram-negative bacteria, bind DNA and act as the global transcriptional repressors. In this study, we identified and characterized the xrvC gene encoding a H-NS protein in Xathomonas oryzae pv. oryzae ( Xoo ) Philippines strain PXO99 A . Compared with the wild type, the xrvC -deficient mutant of PXO99 A (named PXO99 xrvC ) showed a reduced growth rate in both nutrient-rich and nutrient-limited media. Interestingly, PXO99 xrvC exhibited significantly reduced virulence on rice cultivar IRBB214, but its virulence on 31 other rice cultivars was not affected. Transcriptional analysis revealed that the expression of hrpG , hrpX and hpa1 and of 15 out of 18 tested non-TAL (transcription activator-like) effector genes was decreased significantly in the xrvC mutant compared with that in the wild type. In addition, loss of xrvC also impaired the induction of the rice susceptibility gene Os8N3 in IRBB214 by PXO99 A . Our results suggest that the xrvC gene is involved in bacterial growth, and it plays a vital role in virulence by positively regulating the expression of hrp genes and non-TAL effector genes in PXO99 A and the susceptibility gene Os8N3 in rice.
    Keywords: Pathogens & Pathogenicity
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  • 73
    Publication Date: 2016-04-24
    Description: In Xanthomonas oryzae pv. oryzae , the pathogen of bacterial leaf blight of rice, hrp gene expression is regulated by the key hrp regulators HrpG and HrpX. HrpG regulates hrpX and hrpA , and HrpX regulates the other hrp genes on hrpB–hrpF operons. We previously examined the expression of the HrpX-regulated hrp gene hrcU and demonstrated that hrp gene expression is highly induced in a certain nutrient-poor medium containing xylose. In the present study, we found that the induction level of HrpX-regulated hrp genes was higher in medium with xylose than in media with any other sugar sources (glucose, sucrose and fructose), but that expression of hrpG , hrpX and hrpA was independent of the sugar sources. In western blot analysis, the accumulation of HrpX was reduced in media with a sugar other than xylose, probably as a result of proteolysis, but the addition of xylose canceled this reduced accumulation of the protein. The results suggest that proteolysis of HrpX is an important hrp regulatory mechanism and that xylose specifically suppresses this proteolysis, resulting in active hrp gene expression in X. oryzae pv. oryzae .
    Keywords: Pathogens & Pathogenicity
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  • 74
    Publication Date: 2016-04-24
    Description: Antibiotic therapy has long term consequences in the intestinal microbiome. Clostridium difficile has a well-known role in antibiotic-associated diarrhea, but in addition, persistent infection with this organism may increase the risk for developing inflammatory bowel disease. Here, recent literature on how the intestinal microbiome is altered by antibiotic therapy is presented.
    Keywords: Pathogens & Pathogenicity
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  • 75
    Publication Date: 2016-03-19
    Description: The yeast mutant collections are a fundamental tool in deciphering genomic organization and function. Over the last decade, they have been used for the systematic exploration of ~6 000 000 double gene mutants, identifying and cataloging genetic interactions among them. Here we studied the extent to which these data are prone to neighboring gene effects (NGEs), a phenomenon by which the deletion of a gene affects the expression of adjacent genes along the genome. Analyzing ~90,000 negative genetic interactions observed to date, we found that more than 10% of them are incorrectly annotated due to NGEs. We developed a novel algorithm, GINGER, to identify and correct erroneous interaction annotations. We validated the algorithm using a comparative analysis of interactions from Schizosaccharomyces pombe . We further showed that our predictions are significantly more concordant with diverse biological data compared to their mis-annotated counterparts. Our work uncovered about 9500 new genetic interactions in yeast.
    Keywords: Computational Methods
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  • 76
    Publication Date: 2016-03-19
    Description: Transfer RNAs (tRNAs) are essential for encoding the transcribed genetic information from DNA into proteins. Variations in the human tRNAs are involved in diverse clinical phenotypes. Interestingly, all pathogenic variations in tRNAs are located in mitochondrial tRNAs (mt-tRNAs). Therefore, it is crucial to identify pathogenic variations in mt-tRNAs for disease diagnosis and proper treatment. We collected mt-tRNA variations using a classification based on evidence from several sources and used the data to develop a multifactorial probability-based prediction method, PON-mt-tRNA, for classification of mt-tRNA single nucleotide substitutions. We integrated a machine learning-based predictor and an evidence-based likelihood ratio for pathogenicity using evidence of segregation, biochemistry and histochemistry to predict the posterior probability of pathogenicity of variants. The accuracy and Matthews correlation coefficient (MCC) of PON-mt-tRNA are 1.00 and 0.99, respectively. In the absence of evidence from segregation, biochemistry and histochemistry, PON-mt-tRNA classifies variations based on the machine learning method with an accuracy and MCC of 0.69 and 0.39, respectively. We classified all possible single nucleotide substitutions in all human mt-tRNAs using PON-mt-tRNA. The variations in the loops are more often tolerated compared to the variations in stems. The anticodon loop contains comparatively more predicted pathogenic variations than the other loops. PON-mt-tRNA is available at http://structure.bmc.lu.se/PON-mt-tRNA/ .
    Keywords: Computational Methods
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  • 77
    Publication Date: 2016-03-13
    Description: The aim of the present study was to verify whether penicillin-resistant, ampicillin-susceptible Enterococcus faecalis (PRASEF) occurred in Brazil prior to the beginning of the 21st century, and to verify whether ampicillin susceptibility can predict susceptibility to other β-lactams in E. faecalis with this inconsistent phenotype. The presence of polymorphisms in the pbp4 gene and genetic diversity among the isolates were investigated. Of 21 PRASEF analyzed, 5 (23.8%) and 4 (19.0%) were imipenem and piperacillin resistant simultaneously by disk diffusion and broth dilution respectively, contradicting the current internationally accepted standards of susceptibility testing. Sequencing of pbp4 gene revealed an amino acid substitution (Asp-573-〉Glu) in all PRASEF isolates but not in the penicillin-susceptible, ampicillin-susceptible E. faecalis . Most PRASEF (90.5%) had related pulsed-field gel electrophoresis profiles, but were different from other PRASEF described to date. Results demonstrate that penicillin-resistant, ampicillin-susceptible phenotype was already a reality in the 1990s in E. faecalis isolates in different Brazilian states, and some of these isolates were also imipenem- and piperacillin-resistant; therefore, internationally accepted susceptibility criteria cannot be applied to these isolates. According to pbp4 gene sequencing, this study suggests that a specific amino acid substitution in pbp4 gene found in all PRASEF analyzed is associated with penicillin resistance.
    Keywords: Pathogens & Pathogenicity
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  • 78
    Publication Date: 2016-05-05
    Keywords: Pathogens & Pathogenicity
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  • 79
    Publication Date: 2016-04-24
    Description: The Mycobacterium tuberculosis Rv0679c protein is a surface protein that contributes to host cell invasion. We previously showed that a single nucleotide transition of the Rv0679c gene leads to a single amino acid substitution from asparagine to lysine at codon 142 in the Beijing genotype family. In this study, we examined the immunological effect of this substitution. Several recombinant proteins were expressed in Escherichia coli and Mycobacterium smegmatis and characterized with antisera and two monoclonal antibodies named 5D4-C2 and 8G10-H2. A significant reduction of antibody binding was detected by enzyme-linked immunosorbent assay (ELISA) and western blot analysis in the Lys142-type protein. This reduction of 8G10-H2 binding was more significant, with the disappearance of a signal in the proteins expressed by recombinant mycobacteria in western blot analysis. In addition, epitope mapping analysis of the recombinant proteins showed a linear epitope by 5D4-C2 and a discontinuous epitope by 8G10-H2. The antibody recognizing the conformational epitope detected only mycobacterial Asn142-type recombinant protein. Our results suggest that a single amino acid substitution of Rv0679c has potency for antigenic change in Beijing genotype strains.
    Keywords: Pathogens & Pathogenicity
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  • 80
    Publication Date: 2016-05-06
    Description: Sequence Logos and its variants are the most commonly used method for visualization of multiple sequence alignments (MSAs) and sequence motifs. They provide consensus-based summaries of the sequences in the alignment. Consequently, individual sequences cannot be identified in the visualization and covariant sites are not easily discernible. We recently proposed Sequence Bundles , a motif visualization technique that maintains a one-to-one relationship between sequences and their graphical representation and visualizes covariant sites. We here present Alvis, an open-source platform for the joint explorative analysis of MSAs and phylogenetic trees, employing Sequence Bundles as its main visualization method. Alvis combines the power of the visualization method with an interactive toolkit allowing detection of covariant sites, annotation of trees with synapomorphies and homoplasies, and motif detection. It also offers numerical analysis functionality, such as dimension reduction and classification. Alvis is user-friendly, highly customizable and can export results in publication-quality figures. It is available as a full-featured standalone version ( http://www.bitbucket.org/rfs/alvis ) and its Sequence Bundles visualization module is further available as a web application ( http://science-practice.com/projects/sequence-bundles ).
    Keywords: Computational Methods
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  • 81
    Publication Date: 2016-04-20
    Description: Listeria monocytogenes possesses the highest number of leucine-rich repeat (LRR)-containing proteins among all Gram-positive bacteria; these LRR-containing molecules are known as the ‘internalin’ family. To understand the functions of largely uncharacterized LRR-containing molecules, we constructed seven deletion mutants in the L. monocytogenes H7858 strain targeting genes in this family and tested their virulence. Among the seven mutants, the LMOh7858_0369 strain and the LMOh7858_2546 strain showed significantly impaired invasiveness of HepG2 cells. We further tested the virulence of these two strains in the intravascular sepsis model using BALB/c mice. Interestingly, the LMOh7858_0369 strain showed significant reduction in organ colonization, bacteremia and invasion of the brain compared with the parental wild-type strain. Host immune responses to listerial intravascular infection were measured at 24 and 72 h post-infection. Transcript levels of several proinflammatory cytokines and chemokines were significantly lower when induced by the lmOh7858_0369 strain than when induced by the wild type. These results suggest that the putative LRR-containing protein encoded by LMOh7858_0369 might be a novel virulence factor of the L. monocytogenes H7858 strain.
    Keywords: Pathogens & Pathogenicity
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  • 82
    Publication Date: 2016-04-20
    Description: Several Gram-positive pathogens scavenge host-derived heme to satisfy their nutritional iron requirement. However, heme is a toxic molecule capable of damaging the bacterial cell. Gram-positive pathogens within the phylum Firmicutes overcome heme toxicity by sensing heme through HssRS, a two-component system that regulates the heme detoxification transporter HrtAB. Here we show that heme sensing by HssRS and heme detoxification by HrtAB occur in the insect pathogen Bacillus thuringiensis . We find that in B. thuringiensis , HssRS directly regulates an operon, hrmXY , encoding hypothetical membrane proteins that are not found in other Firmicutes with characterized HssRS and HrtAB systems. This novel HssRS-regulated operon or its orthologs BMB171_c3178 and BMB171_c3330 are required for maximal heme resistance. Furthermore, the activity of HrmXY is not dependent on expression of HrtAB. These results suggest that B. thuringiensis senses heme through HssRS and induces expression of separate membrane-localized systems capable of overcoming different aspects of heme toxicity.
    Keywords: Pathogens & Pathogenicity
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  • 83
    Publication Date: 2016-04-20
    Description: The aim of this study was to understand the pathogenesis of motile aeromonas septicemia caused by an emergent, high virulent Aeromonas hydrophila (vAh) in channel catfish, Ictalurus punctatus . Adipose fin clipped catfish were challenged with vAh using a waterborne challenge method, and the distribution of vAh over a time course was detected and quantified using real-time polymerase chain reaction. The results showed that 77.8% of fish died within 48 h post challenge with mean day to death of 1.5 days. At 2 h post challenge, vAh (inferred from genomic DNA copies or genome equivalents) was detected in all external and internal tissues sampled. Gill had the highest vAh cells at 1 h post challenge. Spleen harbored the most vAh cells among internal organs at 4 h post challenge. The tissues/organs with most vAh cells detected at 8 h post challenge were adipose fin, blood, intestine, kidney and skin, while liver showed the highest vAh cells at 24 h post challenge. These results suggest that vAh was able to rapidly proliferate and spread, following wound infection, through the fish blood circulation system and cause mortality within 8–24 h.
    Keywords: Pathogens & Pathogenicity
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  • 84
    Publication Date: 2016-04-20
    Description: The major Staphylococcus aureus autolysin, Atl, has been implicated in attachment to surfaces and release of extracellular DNA during biofilm formation under laboratory conditions. Consistent with this, polyclonal antibodies to the amidase and glucosaminidase domains of Atl inhibited in vitro biofilm formation. However, in a murine model of device-related infection the community-associated S. aureus strain USA300 LAC JE2 established a successful infection in the absence of atl . These data indicate that Atl activity is not required for biofilm production in this infection model and reveal the importance of characterizing the contribution of biofilm phenotypes to virulence under in vivo conditions.
    Keywords: Pathogens & Pathogenicity
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  • 85
    Publication Date: 2013-07-16
    Description: The coupling of chromosome conformation capture (3C) with next-generation sequencing technologies enables the high-throughput detection of long-range genomic interactions, via the generation of ligation products between DNA sequences, which are closely juxtaposed in vivo . These interactions involve promoter regions, enhancers and other regulatory and structural elements of chromosomes and can reveal key details of the regulation of gene expression. 3C-seq is a variant of the method for the detection of interactions between one chosen genomic element (viewpoint) and the rest of the genome. We present r3Cseq , an R/Bioconductor package designed to perform 3C-seq data analysis in a number of different experimental designs. The package reads a common aligned read input format, provides data normalization, allows the visualization of candidate interaction regions and detects statistically significant chromatin interactions, thus greatly facilitating hypothesis generation and the interpretation of experimental results. We further demonstrate its use on a series of real-world applications.
    Keywords: Computational Methods
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  • 86
    Publication Date: 2016-10-26
    Description: Edwardsiella tarda is distributed widely in a variety of hosts. Eha has recently been found to be its virulence regulator. In order to explore the mechanism of its regulation, we investigated the survival rates of wild type strain ET13, and its eha mutant and complemented strains in RAW264.7 macrophages under light microscopic observation as well as by counting bacterial CFUs on the plates. All of the different strains could live within the macrophages; however, the intracellular numbers of the wild type were significantly higher than the mutant when the incubation time extended 4 h or 6 h ( P 〈 0.05). Furthermore, more ROS were produced by the mutant-infected cells, indicating that Eha may enhance ET13's capacity to detoxify ROS. In agreement with this, we found that the mutant exhibited more sensitivity by H 2 O 2 disk inhibitory assay and less survival ability with H 2 O 2 treatment. We further demonstrated that the bacterial antioxidant enzymes SodC and KatG were regulated by Eha with qRT-PCR and β -galactosidase assay. Collectively, our data show Eha is required for E. tarda to resist the oxidative stress from the macrophages.
    Keywords: Pathogens & Pathogenicity
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  • 87
    Publication Date: 2016-08-07
    Description: Direct interaction between pathogens and host cells often is a prerequisite for colonization, infection and dissemination. Regulated production of capsular polysaccharide (CPS), which is made of hyaluronic acid, is essential for the pathogenicity of Streptococcus equi subsp. Zooepidemicus (SEZ). Here, we constructed a CPS-deleted mutant and analyzed it along with the parental wild-type strain in attachment and invasion of mammalian epithelial and endothelial cell lines. The CPS-deleted mutant exhibited significant increase in adherence and invasion by several orders of magnitude compared with the wild-type strain through quantitative analysis and electron microscopy observation. After the wild-type strain was recovered from invaded cells, its morphology was analyzed by visual methods and scanning electron microscopy, which revealed that its capsule was almost completely absent. Capsule measurements showed a similar result in which CPS production was nearly attenuated to the same extent as in the CPS-deleted mutant. qPCR assays revealed a marked reduction in the transcriptional levels of the CPS biosynthesis genes, has operon. Moreover, the repression in capsular production was stable inheritance. Our findings indicate that SEZ is a facultative intracellular bacterium, capsule attenuation in SEZ contributes to attachment and invasion in interactions with host cells, and the active regulation of capsule breakdown is controlled by SEZ during internalization.
    Keywords: Pathogens & Pathogenicity
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  • 88
    Publication Date: 2016-10-14
    Description: Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.
    Keywords: Computational Methods
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  • 89
    Publication Date: 2016-12-01
    Description: Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish ( Danio rerio ), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet ( www.inetbio.org/danionet ), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.
    Keywords: Computational Methods
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  • 90
    Publication Date: 2016-12-04
    Description: Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.
    Keywords: Computational Methods
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  • 91
    Publication Date: 2016-12-17
    Description: A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a single sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e. a sample-specific network (SSN) method, which allows us to construct individual-specific networks based on molecular expressions of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various types of cancer. Biological experiments on drug resistance further validated one important advantage of our method over the traditional methods, i.e. we can even identify such drug resistance genes that actually have no clear differential expression between samples with and without the resistance, due to the additional network information.
    Keywords: Computational Methods
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  • 92
    Publication Date: 2016-12-17
    Description: Motivation: Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. Availability and Implementation: A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm . Contact: peddada@niehs.nih.gov
    Keywords: Computational Methods
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  • 93
    Publication Date: 2016-12-23
    Description: Burkholderia pseudomallei causes melioidosis, a potentially fatal infectious disease in tropical and subtropical countries worldwide. The intracellular behaviour of this pathogen in host cells has been reported to impact the severity of melioidosis, including the development of septicaemia, a consequence of pneumonia melioidosis. We previously identified a predicted cation transporter protein, BPSS1228, that participates in the transitional stage of this intracellular pathogen. For further analysis, in this study B. pseudomallei bpss1228 mutant and complemented strains were constructed and bacterial infectivity on human lung epithelial cells, A549, investigated in vitro . Burkholderia pseudomallei bpss1228 mutant showed impaired bacterial adhesion and invasion into A549 cells compared with wild-type strain, while the deficient phenotypes were restored to wild-type levels by the complemented strain. Additionally, the inactivation of bpss1228 in the mutant strain affected flagella-based swimming on a semi-solid surface and resistance to acid stresses simulating intracellular environments. These observations of BPSS1228 relating to B. pseudomallei infection strategies shed a new light on its association with intracellular B. pseudomallei during the interaction with host cells.
    Keywords: Pathogens & Pathogenicity
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  • 94
    Publication Date: 2016-12-23
    Description: Formation of a transient sub-population of bacteria, referred to as persisters, is one of the most important and least understood mechanisms that bacteria employ to evade elimination. Persister cells appear to be slow-growing bacteria that are broadly protected from a wide range of antibiotics. Using both theoretical and experimental methods, we show that alternating the application and withdrawal of antibiotics can be an effective treatment—as long as the timing of the protocol is estimated with precision. More specifically, we demonstrate that timing the alternating treatment based on theoretical predictions is confirmed using experimental observations. These results support a large class of theoretical studies that show that, even without complete understanding of the biological mechanisms, these models can provide insight into properties of the system.
    Keywords: Pathogens & Pathogenicity
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  • 95
    Publication Date: 2016-12-23
    Description: The phytopathogen Pseudomonas syringae pv. tabaci 11528 ( P. syringae 11528), causing wild-fire disease in soybean and tobacco plants, processes PsyI-PsyR quorum-sensing (QS) system, in which PsyI is the N -(3-oxo-hexanoyl)-homoserine lactone (3OC6-HSL) synthase. In comparison to P. syringae 11528 AHL-deficient mutant, 845 3OC6-HSL-dependent genes were identified using RNA sequencing (RNA-seq) in the AHL-deficient mutant grown with exogenous 3OC6-HSL in the transition from the exponential to the stationary phase, and many of them were associated with virulence, which were negatively regulated. The gene ontology and KEGG pathway enrichment analysis of those genes presented that the most pronounced regulation was involved in bacterial motility. Moreover, similar expression profiles of genes during growth phases were observed in both the wild type and the AHL-deficient mutant with exogenous 3OC6-HSL compared with the AHL-deficient mutant. These findings imply that 3OC6-HSL has a critical contribution to the QS-dependent regulation on gene expression, and 3OC6-HSL-dependent regulation may play a significant role in plant infection.
    Keywords: Pathogens & Pathogenicity
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  • 96
    Publication Date: 2016-12-29
    Description: Helicobacter pylori commonly infects the epithelial layer of the human stomach and in some individuals causes peptic ulcers, gastric adenocarcinoma or gastric lymphoma. Helicobacter pylori is a genetically diverse species, and the most important bacterial virulence factor that increases the risk of developing disease, versus asymptomatic colonization, is the cytotoxin associated gene pathogenicity island ( cag PAI). Socially housed rhesus macaques are often naturally infected with H. pylori similar to that which colonizes humans, but little is known about the cag PAI. Here we show that H. pylori strains isolated from naturally infected rhesus macaques have a cag PAI very similar to that found in human clinical isolates, and like human isolates, it encodes a functional type IV secretion system. These results provide further support for the relevance of rhesus macaques as a valid experimental model for H. pylori infection in humans.
    Keywords: Pathogens & Pathogenicity
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  • 97
    Publication Date: 2016-12-29
    Description: Sporisorium scitamineum is the fungus that causes sugarcane smut disease. Despite of the importance of sugarcane for Brazilian agribusiness and the persistence of the pathogen in most cropping areas, genetic variation studies are still missing for Brazilian isolates. In this study, sets of isolates were analyzed using two molecular markers (AFLP and telRFLP) and ITS sequencing. Twenty-two whips were collected from symptomatic plants in cultivated sugarcane fields of Brazil. A total of 41 haploid strains of compatible mating types were selected from individual teliospores and used for molecular genetic analyses. telRFLP and ITS analyses were expanded to six Argentine isolates, where the sugarcane smut was first recorded in America. Genetic relationship among strains suggests the human-mediated dispersal of S. scitamineum within the Brazilian territory and between the two neighboring countries. Two genetically distinct groups were defined by the combined analysis of AFLP and telRFLP. The opposite mating-type strains derived from single teliospores were clustered together into these main groups, but had not always identical haplotypes. telRFLP markers analyzed over two generations of selfing and controlled outcrossing confirmed the potential for emergence of new variants and occurrence of recombination, which are relevant events for evolution of virulence and environmental adaptation.
    Keywords: Pathogens & Pathogenicity
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  • 98
    Publication Date: 2012-08-08
    Description: Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues.
    Keywords: Computational Methods
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  • 99
    Publication Date: 2012-09-27
    Description: Programmed –1 ribosomal frameshifting is employed in the expression of a number of viral and cellular genes. In this process, the ribosome slips backwards by a single nucleotide and continues translation of an overlapping reading frame, generating a fusion protein. Frameshifting signals comprise a heptanucleotide slippery sequence, where the ribosome changes frame, and a stimulatory RNA structure, a stem–loop or RNA pseudoknot. Antisense oligonucleotides annealed appropriately 3' of a slippery sequence have also shown activity in frameshifting, at least in vitro . Here we examined frameshifting at the U 6 A slippery sequence of the HIV gag/pol signal and found high levels of both –1 and –2 frameshifting with stem–loop, pseudoknot or antisense oligonucleotide stimulators. By examining –1 and –2 frameshifting outcomes on mRNAs with varying slippery sequence-stimulatory RNA spacing distances, we found that –2 frameshifting was optimal at a spacer length 1–2 nucleotides shorter than that optimal for –1 frameshifting with all stimulatory RNAs tested. We propose that the shorter spacer increases the tension on the mRNA such that when the tRNA detaches, it more readily enters the –2 frame on the U 6 A heptamer. We propose that mRNA tension is central to frameshifting, whether promoted by stem–loop, pseudoknot or antisense oligonucleotide stimulator.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 100
    Publication Date: 2012-10-24
    Description: Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped 〉2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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