bluuebunny/crossref_metadata_2025 huggingface dataset:
Metabolite identification through multiple kernel learning on fragmentation trees
Authors: Shen Huibin , Dührkop Kai , Böcker Sebastian , Rousu Juho
Published: June 2014

Motivation: Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures.

Results: Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list.

Contact:  huibin.shen@aalto.fi

Supplementary information:  Supplementary data are available at Bioinformatics online.
Deep learning of the tissue-regulated splicing code
Authors: Leung Michael K. K. , Xiong Hui Yuan , Lee Leo J. , Frey Brendan J.
Published: June 2014

Motivation: Alternative splicing (AS) is a regulated process that directs the generation of different transcripts from single genes. A computational model that can accurately predict splicing patterns based on genomic features and cellular context is highly desirable, both in understanding this widespread phenomenon, and in exploring the effects of genetic variations on AS.

Methods: Using a deep neural network, we developed a model inferred from mouse RNA-Seq data that can predict splicing patterns in individual tissues and differences in splicing patterns across tissues. Our architecture uses hidden variables that jointly represent features in genomic sequences and tissue types when making predictions. A graphics processing unit was used to greatly reduce the training time of our models with millions of parameters.

Results: We show that the deep architecture surpasses the performance of the previous Bayesian method for predicting AS patterns. With the proper optimization procedure and selection of hyperparameters, we demonstrate that deep architectures can be beneficial, even with a moderately sparse dataset. An analysis of what the model has learned in terms of the genomic features is presented.

Contact:  frey@psi.toronto.edu

Supplementary information:  Supplementary data are available at Bioinformatics online.
DrugComboRanker: drug combination discovery based on target network analysis
Authors: Huang Lei , Li Fuhai , Sheng Jianting , Xia Xiaofeng , Ma Jinwen , Zhan Ming , Wong Stephen T.C.
Published: June 2014

Motivation: Currently there are no curative anticancer drugs, and drug resistance is often acquired after drug treatment. One of the reasons is that cancers are complex diseases, regulated by multiple signaling pathways and cross talks among the pathways. It is expected that drug combinations can reduce drug resistance and improve patients’ outcomes. In clinical practice, the ideal and feasible drug combinations are combinations of existing Food and Drug Administration-approved drugs or bioactive compounds that are already used on patients or have entered clinical trials and passed safety tests. These drug combinations could directly be used on patients with less concern of toxic effects. However, there is so far no effective computational approach to search effective drug combinations from the enormous number of possibilities.

Results: In this study, we propose a novel systematic computational tool DrugComboRanker to prioritize synergistic drug combinations and uncover their mechanisms of action. We first build a drug functional network based on their genomic profiles, and partition the network into numerous drug network communities by using a Bayesian non-negative matrix factorization approach. As drugs within overlapping community share common mechanisms of action, we next uncover potential targets of drugs by applying a recommendation system on drug communities. We meanwhile build disease-specific signaling networks based on patients’ genomic profiles and interactome data. We then identify drug combinations by searching drugs whose targets are enriched in the complementary signaling modules of the disease signaling network. The novel method was evaluated on lung adenocarcinoma and endocrine receptor positive breast cancer, and compared with other drug combination approaches. These case studies discovered a set of effective drug combinations top ranked in our prediction list, and mapped the drug targets on the disease signaling network to highlight the mechanisms of action of the drug combinations.

Availability and implementation: The program is available on request.

Contact:  stwong@tmhs.org
Ragout—a reference-assisted assembly tool for bacterial genomes
Authors: Kolmogorov Mikhail , Raney Brian , Paten Benedict , Pham Son
Published: June 2014

Summary: Bacterial genomes are simpler than mammalian ones, and yet assembling the former from the data currently generated by high-throughput short-read sequencing machines still results in hundreds of contigs. To improve assembly quality, recent studies have utilized longer Pacific Biosciences (PacBio) reads or jumping libraries to connect contigs into larger scaffolds or help assemblers resolve ambiguities in repetitive regions of the genome. However, their popularity in contemporary genomic research is still limited by high cost and error rates. In this work, we explore the possibility of improving assemblies by using complete genomes from closely related species/strains. We present Ragout, a genome rearrangement approach, to address this problem. In contrast with most reference-guided algorithms, where only one reference genome is used, Ragout uses multiple references along with the evolutionary relationship among these references in order to determine the correct order of the contigs. Additionally, Ragout uses the assembly graph and multi-scale synteny blocks to reduce assembly gaps caused by small contigs from the input assembly. In simulations as well as real datasets, we believe that for common bacterial species, where many complete genome sequences from related strains have been available, the current high-throughput short-read sequencing paradigm is sufficient to obtain a single high-quality scaffold for each chromosome.

Availability: The Ragout software is freely available at: https://github.com/fenderglass/Ragout.

Contact:  spham@salk.edu
Tertiary structure-based prediction of conformational B-cell epitopes through B factors
Authors: Ren Jing , Liu Qian , Ellis John , Li Jinyan
Published: June 2014

Motivation: B-cell epitope is a small area on the surface of an antigen that binds to an antibody. Accurately locating epitopes is of critical importance for vaccine development. Compared with wet-lab methods, computational methods have strong potential for efficient and large-scale epitope prediction for antigen candidates at much lower cost. However, it is still not clear which features are good determinants for accurate epitope prediction, leading to the unsatisfactory performance of existing prediction methods.

Method and results: We propose a much more accurate B-cell epitope prediction method. Our method uses a new feature B factor (obtained from X-ray crystallography), combined with other basic physicochemical, statistical, evolutionary and structural features of each residue. These basic features are extended by a sequence window and a structure window. All these features are then learned by a two-stage random forest model to identify clusters of antigenic residues and to remove isolated outliers. Tested on a dataset of 55 epitopes from 45 tertiary structures, we prove that our method significantly outperforms all three existing structure-based epitope predictors. Following comprehensive analysis, it is found that features such as B factor, relative accessible surface area and protrusion index play an important role in characterizing B-cell epitopes. Our detailed case studies on an HIV antigen and an influenza antigen confirm that our second stage learning is effective for clustering true antigenic residues and for eliminating self-made prediction errors introduced by the first-stage learning.

Availability and implementation: Source codes are available on request.

Contact:  jinyan.li@uts.edu.au

Supplementary information:  Supplementary data are available at Bioinformatics online.
Inferring gene ontologies from pairwise similarity data
Authors: Kramer Michael , Dutkowski Janusz , Yu Michael , Bafna Vineet , Ideker Trey
Published: June 2014

Motivation: While the manually curated Gene Ontology (GO) is widely used, inferring a GO directly from -omics data is a compelling new problem. Recognizing that ontologies are a directed acyclic graph (DAG) of terms and hierarchical relations, algorithms are needed that: analyze a full matrix of gene–gene pairwise similarities from -omics data;infer true hierarchical structure in these data rather than enforcing hierarchy as a computational artifact; andrespect biological pleiotropy, by which a term in the hierarchy can relate to multiple higher level terms.

Methods addressing these requirements are just beginning to emerge—none has been evaluated for GO inference.

Methods: We consider two algorithms [Clique Extracted Ontology (CliXO), LocalFitness] that uniquely satisfy these requirements, compared with methods including standard clustering. CliXO is a new approach that finds maximal cliques in a network induced by progressive thresholding of a similarity matrix. We evaluate each method’s ability to reconstruct the GO biological process ontology from a similarity matrix based on (a) semantic similarities for GO itself or (b) three -omics datasets for yeast.

Results: For task (a) using semantic similarity, CliXO accurately reconstructs GO (>99% precision, recall) and outperforms other approaches (<20% precision, <20% recall). For task (b) using -omics data, CliXO outperforms other methods using two -omics datasets and achieves ∼30% precision and recall using YeastNet v3, similar to an earlier approach (Network Extracted Ontology) and better than LocalFitness or standard clustering (20–25% precision, recall).

Conclusion: This study provides algorithmic foundation for building gene ontologies by capturing hierarchical and pleiotropic structure embedded in biomolecular data.

Contact:  tideker@ucsd.edu
Scale-space measures for graph topology link protein network architecture to function
Authors: Hulsman Marc , Dimitrakopoulos Christos , de Ridder Jeroen
Published: June 2014

Motivation: The network architecture of physical protein interactions is an important determinant for the molecular functions that are carried out within each cell. To study this relation, the network architecture can be characterized by graph topological characteristics such as shortest paths and network hubs. These characteristics have an important shortcoming: they do not take into account that interactions occur across different scales. This is important because some cellular functions may involve a single direct protein interaction (small scale), whereas others require more and/or indirect interactions, such as protein complexes (medium scale) and interactions between large modules of proteins (large scale).

Results: In this work, we derive generalized scale-aware versions of known graph topological measures based on diffusion kernels. We apply these to characterize the topology of networks across all scales simultaneously, generating a so-called graph topological scale-space. The comprehensive physical interaction network in yeast is used to show that scale-space based measures consistently give superior performance when distinguishing protein functional categories and three major types of functional interactions—genetic interaction, co-expression and perturbation interactions. Moreover, we demonstrate that graph topological scale spaces capture biologically meaningful features that provide new insights into the link between function and protein network architecture.

Availability and implementation: MatlabTM code to calculate the scale-aware topological measures (STMs) is available at http://bioinformatics.tudelft.nl/TSSA

Contact:  j.deridder@tudelft.nl

Supplementary information:  Supplementary data are available at Bioinformatics online.
Stochastic EM-based TFBS motif discovery with MITSU
Authors: Kilpatrick Alastair M. , Ward Bruce , Aitken Stuart
Published: June 2014

Motivation: The Expectation–Maximization (EM) algorithm has been successfully applied to the problem of transcription factor binding site (TFBS) motif discovery and underlies the most widely used motif discovery algorithms. In the wider field of probabilistic modelling, the stochastic EM (sEM) algorithm has been used to overcome some of the limitations of the EM algorithm; however, the application of sEM to motif discovery has not been fully explored.

Results: We present MITSU (Motif discovery by ITerative Sampling and Updating), a novel algorithm for motif discovery, which combines sEM with an improved approximation to the likelihood function, which is unconstrained with regard to the distribution of motif occurrences within the input dataset. The algorithm is evaluated quantitatively on realistic synthetic data and several collections of characterized prokaryotic TFBS motifs and shown to outperform EM and an alternative sEM-based algorithm, particularly in terms of site-level positive predictive value.

Availability and implementation: Java executable available for download at http://www.sourceforge.net/p/mitsu-motif/, supported on Linux/OS X.

Contact:  a.m.kilpatrick@sms.ed.ac.uk
RNA-Skim: a rapid method for RNA-Seq quantification at transcript level
Authors: Zhang Zhaojun , Wang Wei
Published: June 2014

Motivation: RNA-Seq technique has been demonstrated as a revolutionary means for exploring transcriptome because it provides deep coverage and base pair-level resolution. RNA-Seq quantification is proven to be an efficient alternative to Microarray technique in gene expression study, and it is a critical component in RNA-Seq differential expression analysis. Most existing RNA-Seq quantification tools require the alignments of fragments to either a genome or a transcriptome, entailing a time-consuming and intricate alignment step. To improve the performance of RNA-Seq quantification, an alignment-free method, Sailfish, has been recently proposed to quantify transcript abundances using all k-mers in the transcriptome, demonstrating the feasibility of designing an efficient alignment-free method for transcriptome quantification. Even though Sailfish is substantially faster than alternative alignment-dependent methods such as Cufflinks, using all k-mers in the transcriptome quantification impedes the scalability of the method.

Results: We propose a novel RNA-Seq quantification method, RNA-Skim, which partitions the transcriptome into disjoint transcript clusters based on sequence similarity, and introduces the notion of sig-mers, which are a special type of k-mers uniquely associated with each cluster. We demonstrate that the sig-mer counts within a cluster are sufficient for estimating transcript abundances with accuracy comparable with any state-of-the-art method. This enables RNA-Skim to perform transcript quantification on each cluster independently, reducing a complex optimization problem into smaller optimization tasks that can be run in parallel. As a result, RNA-Skim uses <4% of the k-mers and <10% of the CPU time required by Sailfish. It is able to finish transcriptome quantification in <10 min per sample by using just a single thread on a commodity computer, which represents >100 speedup over the state-of-the-art alignment-based methods, while delivering comparable or higher accuracy.

Availability and implementation: The software is available at http://www.csbio.unc.edu/rs.

Contact:  weiwang@cs.ucla.edu

Supplementary information:  Supplementary data are available at Bioinformatics online.
MIRA: mutual information-based reporter algorithm for metabolic networks
Authors: Cicek A. Ercument , Roeder Kathryn , Ozsoyoglu Gultekin
Published: June 2014

Motivation: Discovering the transcriptional regulatory architecture of the metabolism has been an important topic to understand the implications of transcriptional fluctuations on metabolism. The reporter algorithm (RA) was proposed to determine the hot spots in metabolic networks, around which transcriptional regulation is focused owing to a disease or a genetic perturbation. Using a z-score-based scoring scheme, RA calculates the average statistical change in the expression levels of genes that are neighbors to a target metabolite in the metabolic network. The RA approach has been used in numerous studies to analyze cellular responses to the downstream genetic changes. In this article, we propose a mutual information-based multivariate reporter algorithm (MIRA) with the goal of eliminating the following problems in detecting reporter metabolites: (i) conventional statistical methods suffer from small sample sizes, (ii) as z-score ranges from minus to plus infinity, calculating average scores can lead to canceling out opposite effects and (iii) analyzing genes one by one, then aggregating results can lead to information loss. MIRA is a multivariate and combinatorial algorithm that calculates the aggregate transcriptional response around a metabolite using mutual information. We show that MIRA’s results are biologically sound, empirically significant and more reliable than RA.

Results: We apply MIRA to gene expression analysis of six knockout strains of Escherichia coli and show that MIRA captures the underlying metabolic dynamics of the switch from aerobic to anaerobic respiration. We also apply MIRA to an Autism Spectrum Disorder gene expression dataset. Results indicate that MIRA reports metabolites that highly overlap with recently found metabolic biomarkers in the autism literature. Overall, MIRA is a promising algorithm for detecting metabolic drug targets and understanding the relation between gene expression and metabolic activity.

Availability and implementation: The code is implemented in C# language using .NET framework. Project is available upon request.

Contact:  cicek@cs.cmu.edu

Supplementary information:  Supplementary data are available at Bioinformatics online
Accurate viral population assembly from ultra-deep sequencing data
Authors: Mangul Serghei , Wu Nicholas C. , Mancuso Nicholas , Zelikovsky Alex , Sun Ren , Eskin Eleazar
Published: June 2014

Motivation: Next-generation sequencing technologies sequence viruses with ultra-deep coverage, thus promising to revolutionize our understanding of the underlying diversity of viral populations. While the sequencing coverage is high enough that even rare viral variants are sequenced, the presence of sequencing errors makes it difficult to distinguish between rare variants and sequencing errors. Results: In this article, we present a method to overcome the limitations of sequencing technologies and assemble a diverse viral population that allows for the detection of previously undiscovered rare variants. The proposed method consists of a high-fidelity sequencing protocol and an accurate viral population assembly method, referred to as Viral Genome Assembler (VGA). The proposed protocol is able to eliminate sequencing errors by using individual barcodes attached to the sequencing fragments. Highly accurate data in combination with deep coverage allow VGA to assemble rare variants. VGA uses an expectation–maximization algorithm to estimate abundances of the assembled viral variants in the population. Results on both synthetic and real datasets show that our method is able to accurately assemble an HIV viral population and detect rare variants previously undetectable due to sequencing errors. VGA outperforms state-of-the-art methods for genome-wide viral assembly. Furthermore, our method is the first viral assembly method that scales to millions of sequencing reads. Availability: Our tool VGA is freely available at http://genetics.cs.ucla.edu/vga/

Contact:  serghei@cs.ucla.edu; eeskin@cs.ucla.edu
miR-PREFeR: an accurate, fast and easy-to-use plant miRNA prediction tool using small RNA-Seq data
Authors: Lei Jikai , Sun Yanni
Published: June 2014

Summary: Plant microRNA prediction tools that use small RNA-sequencing data are emerging quickly. These existing tools have at least one of the following problems: (i) high false-positive rate; (ii) long running time; (iii) work only for genomes in their databases; (iv) hard to install or use. We developed miR-PREFeR (miRNA PREdiction From small RNA-Seq data), which uses expression patterns of miRNA and follows the criteria for plant microRNA annotation to accurately predict plant miRNAs from one or more small RNA-Seq data samples of the same species. We tested miR-PREFeR on several plant species. The results show that miR-PREFeR is sensitive, accurate, fast and has low-memory footprint.

Availability and implementation:  https://github.com/hangelwen/miR-PREFeR

Contact:  yannisun@msu.edu

Supplementary information:  Supplementary data are available at Bioinformatics online.
Evaluation and validation ofde novoand hybrid assembly techniques to derive high-quality genome sequences
Authors: Utturkar Sagar M. , Klingeman Dawn M. , Land Miriam L. , Schadt Christopher W. , Doktycz Mitchel J. , Pelletier Dale A. , Brown Steven D.
Published: June 2014

Motivation: To assess the potential of different types of sequence data combined with de novo and hybrid assembly approaches to improve existing draft genome sequences.

Results: Illumina, 454 and PacBio sequencing technologies were used to generate de novo and hybrid genome assemblies for four different bacteria, which were assessed for quality using summary statistics (e.g. number of contigs, N50) and in silico evaluation tools. Differences in predictions of multiple copies of rDNA operons for each respective bacterium were evaluated by PCR and Sanger sequencing, and then the validated results were applied as an additional criterion to rank assemblies. In general, assemblies using longer PacBio reads were better able to resolve repetitive regions. In this study, the combination of Illumina and PacBio sequence data assembled through the ALLPATHS-LG algorithm gave the best summary statistics and most accurate rDNA operon number predictions. This study will aid others looking to improve existing draft genome assemblies.

Availability and implementation: All assembly tools except CLC Genomics Workbench are freely available under GNU General Public License.

Contact:  brownsd@ornl.gov

Supplementary information:  Supplementary data are available at Bioinformatics online.
circlizeimplements and enhances circular visualization in R
Authors: Gu Zuguang , Gu Lei , Eils Roland , Schlesner Matthias , Brors Benedikt
Published: June 2014

Summary: Circular layout is an efficient way for the visualization of huge amounts of genomic information. Here we present the circlize package, which provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of this package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, circlize gives users more convenience and freedom to design figures for better understanding genomic patterns behind multi-dimensional data.

Availability and implementation:  circlize is available at the Comprehensive R Archive Network (CRAN): http://cran.r-project.org/web/packages/circlize/

Contact:  b.brors@dkfz.de

Supplementary information:  Supplementary data are available at Bioinformatics online.
Possible influence of salmon farming on long-term resident behaviour of wild saithe (Pollachius virens L.)
Authors: Otterå Håkon , Skilbrei Ove T.
Published: June 2014

The culture of Atlantic salmon is one of the most developed aquaculture industries in the world. The production from smolt to market size usually takes place in sea cages in open waters, and these structures tend to attract wild fish, as they do for other farmed species. For salmon farming, saithe (Pollachius virens) is one of the most-frequently observed species around sea cages. An important question is whether the large concentration of salmon farms in some areas might alter the natural behaviour and migration pattern of wild saithe. We tagged 62 wild saithe with acoustic tags and followed their movements for up to 2 years in an area in Southwestern Norway with many salmon farms. Furthermore, nearly 2000 saithe were tagged with external T-bar tags to study migration beyond the study area. The recaptures of the T-bar tagged saithe from offshore areas suggest that the offshore migration routes of saithe are similar to published results from before salmon farming became significant in the area. However, a large proportion of the saithe population appears to remain in the release area and was observed at the salmon farms for much of the time. We conclude that the aquaculture industry is influencing the local saithe distribution. Large-scale population effects are more difficult to prove, but it is possible that the dynamic relationship between the coastal and oceanic phases has been altered.
Paenibacillus lupini sp. nov., isolated from nodules of Lupinus albus
Authors: Carro Lorena , Flores-Félix José David , Ramírez-Bahena Martha-Helena , García-Fraile Paula , Martínez-Hidalgo Pilar , Igual José M. , Tejedor Carmen , Peix Alvaro , Velázquez Encarna
Published: June 2014

A bacterial strain designated RLAHU15T was isolated from root nodules of Lupinus albus in Spain. Phylogenetic analyses based on 16S rRNA gene sequences placed the isolate in the genus

Paenibacillus

, with its closest relatives being

Paenibacillus catalpae

D75T,

Paenibacillus glycanilyticus

DS-1T,

Paenibacillus endophyticus

PECAE04T and

Paenibacillus xinjiangensis

B538T with 98.8 %, 98.9 %, 97.4 % and 97.4 % similarity, respectively. DNA–DNA hybridization studies showed values lower than 45 % between the strain RLAHU15T and any of these species. The isolate was a Gram-stain positive, motile and sporulating rod. Catalase activity was weak and oxidase activity was positive. Casein and starch were hydrolysed but gelatin was not. Growth was supported by many carbohydrates and organic acids as carbon sources. MK-7 was the only menaquinone detected and anteiso-C15 : 0 and iso-C16 : 0 were the major fatty acids. The major polar lipids were diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, three unidentified phospholipids and an unidentified lipid. meso-Diaminopimelic acid was detected in the peptidoglycan. The DNA G+C content was 54.4 mol%. Phylogenetic, chemotaxonomic and phenotypic analyses showed that strain RLAHU15T represents a novel species of the genus

Paenibacillus

, for which the name Paenibacillus lupini sp. nov. is proposed. The type strain is RLAHU15T ( = LMG 27296T = CECT 8235T).
Morphology and phylogenetic analysis of two oxytrichid soil ciliates from China, Oxytricha paragranulifera n. sp. and Oxytricha granulifera Foissner and Adam, 1983 (Protista, Ciliophora, Hypotrichia)
Authors: Shao Chen , Lv Zhao , Pan Ying , Al-Rasheid Khaled A. S. , Yi Zhenzhen
Published: June 2014

The morphology and infraciliature of two hypotrichous ciliates, Oxytricha paragranulifera n. sp. and Oxytricha granulifera Foissner and Adam, 1983, collected respectively from the surface of a sandy soil in the Huguang mangrove forest, Zhanjiang, China, and the surface of soil in a forest beside Ziwu Road, Xian, north-west China, were examined. O. paragranulifera n. sp. is characterized by an elongate body with slightly tapered anterior end, two macronuclear nodules and two micronuclei, paroral and endoral in Stylonychia-pattern, colourless cortical granules distributed in clusters or irregular short rows, adoral zone occupying 37 % of the body length, marginal rows almost confluent posteriorly, six dorsal kineties and three caudal cirri, caudal cirri and dorsal bristles almost indistinguishable when viewed in vivo. The well-known O. granulifera Foissner and Adam, 1983 was also redescribed and can be separated from the novel species by having cortical granules arranged along dorsal kineties and marginal rows on both sides (vs grouped in clusters as well as in short irregular rows), paroral and endoral in Oxytricha-pattern (vs in Stylonychia-pattern), macronuclear nodules obviously detached (vs adjacent) and a non-saline terrestrial habitat (vs saline terrestrial). The separation of these two taxa is also firmly supported by the molecular data, which show a significant difference between the two in their SSU rRNA gene sequences (similarity 97.1 %). Phylogenetic analyses based on SSU rRNA gene sequence data suggest a close relationship within the Oxytrichidae assemblage between O. paragranulifera n. sp. and O. granulifera.
Basidioascus persicus sp. nov., a yeast-like species of the order Geminibasidiales isolated from soil
Authors: Nasr Shaghayegh , Soudi Mohammad Reza , Nasrabadi Seyyedeh Maryam Zamanzadeh , Nikou Mahdi Moshtaghi , Salmanian Ali Hatef , Nguyen Hai D. T.
Published: June 2014

A novel species of basidiomycetes was isolated from kitchen garden soil in Shahryar city, Tehran province, Iran. Molecular and conventional methods were employed to identify and classify this single isolate. Morphologically, the isolate was considered yeast-like with hyaline and oval cells reproducing by monopolar budding, forming ballistoconidia, hyphae, arthroconidia and didymospores. Basidia and basidiospores resembling those produced by Basidioascus species were observed. Sequencing and Bayesian phylogenetic analysis of rRNA genes and the internal transcribed spacer region revealed its sister relationship to described species of the genus Basidioascus. Assimilation and fermentation tests, cell-wall carbohydrate analysis and enzyme activity tests were performed to provide insight into the metabolism of the isolate. Based on morphology, physiology and phylogeny of rRNA gene sequences, the isolate was shown to represent a novel species of the genus Basidioascus, described as Basidioascus persicus sp. nov. (holotype IBRC P1010180T = ex-type IBRC M30078T = isotype CBS 12808T). The MycoBank number of the novel species is MB 804703. An emended description of the genus Basidioascus is also provided.
A Galleria mellonella infection model reveals double and triple antibiotic combination therapies with enhanced efficacy versus a multidrug-resistant strain of Pseudomonas aeruginosa
Authors: Krezdorn Jessica , Adams Sophie , Coote Peter J.
Published: June 2014

The aim of this study was to compare the inhibitory effect of antibiotic combinations in vitro with efficacy in Galleria mellonella larvae in vivo to identify efficacious combinations that target Pseudomonas aeruginosa. P. aeruginosa NCTC 13437, a multidrug-resistant strain resistant to β-lactams and aminoglycosides, was used. Susceptibility to cefotaxime, piperacillin, meropenem, amikacin, levofloxacin and colistin alone, or in dual or triple combinations, was measured in vitro via a 24 h time-kill assay. In vitro results were then compared with the efficacy of the same dual or triple antibiotic combinations versus G. mellonella larvae infected with P. aeruginosa. G. mellonella haemolymph burden of P. aeruginosa was determined over 96 h post-infection and treatment with the most potent combination therapies. Many dual and triple combinations of antibiotics displayed synergistic inhibition of multidrug-resistant P. aeruginosa in vitro. There was little correlation between combinations that were synergistic in vitro and those that showed enhanced efficacy in vivo versus infected G. mellonella larvae. The most potent dual and triple combinations in vivo were cefotaxime plus piperacillin, and meropenem plus piperacillin and amikacin, respectively. Fewer combinations were found to offer enhanced therapeutic benefit in vivo compared with in vitro. The therapeutic benefit arising from treatment with antibiotic combinations in vivo correlated with reduced larval burden of P. aeruginosa. This study has identified antibiotic combinations that merit further investigation for their clinical potential and has demonstrated the utility of using G. mellonella to screen for novel antibiotic treatments that demonstrate efficacy in vivo.
Intermediate and C-terminal regions of leptospiral adhesin Lsa66 are responsible for binding with plasminogen and extracellular matrix components
Authors: Oliveira Rosane , Domingos Renan F. , de Morais Zenaide M. , Vasconcellos Silvio A. , Alves Ivy J. , Romero Eliete C. , Nascimento Ana L. T. O.
Published: June 2014

Leptospirosis, a worldwide zoonotic infection, is an important human and veterinary health problem. We have previously identified a leptospiral multipurpose adhesin, Lsa66, capable of binding extracellular matrix (ECM) components and plasminogen (PLG). In this work, we report the cloning, expression, purification and characterization of three fragments derived from the full-length Lsa66: N-terminal, intermediate and C-terminal regions. We employed Escherichia coli BL21-SI as expression cells. The recombinant fragments tagged with N-terminal His6 were purified by metal-charged chromatography to major protein bands that were recognized by anti-His-tag mAbs. The recombinant fragments were evaluated for their capacity to attach to ECM components and to PLG. The intermediate region bound to laminin, plasma fibronectin and PLG. Laminin also bound to the C-terminal region. Antibodies in leptospirosis-positive serum samples recognized Lsa66, being the immune epitopes located at the N-terminal and intermediate fragments. The data confirm that Lsa66 is expressed during infection and that this protein might have a role in bacterial infection.
The lone S41 family C-terminal processing protease in Staphylococcus aureus is localized to the cell wall and contributes to virulence
Authors: Carroll Ronan K. , Rivera Frances E. , Cavaco Courtney K. , Johnson Grant M. , Martin David , Shaw Lindsey N.
Published: June 2014

Staphylococcus aureusis a versatile pathogen of humans and a continued public health concern due to the rise and spread of multidrug-resistant strains. As part of an ongoing investigation into the pathogenic mechanisms of this organism we previously demonstrated that an intracellular N-terminal processing protease is required forS. aureusvirulence. Following on from this, here we examine the role of CtpA, the lone C-terminal processing protease ofS. aureus. CtpA, a member of the S41 family, is a serine protease whose homologues in Gram-negative bacteria have been implicated in a range of biological functions, including pathogenesis. We demonstrate thatS. aureusCtpA is localized to the bacterial cell wall and expression of thectpAgene is maximal upon exposure to conditions encountered during infection. Disruption of thectpAgene leads to decreased heat tolerance and increased sensitivity when exposed to components of the host immune system. Finally we demonstrate that thectpA−mutant strain is attenuated for virulence in a murine model of infection. Our results represent the first characterization of a C-terminal processing protease in a pathogenic Gram-positive bacterium and show that it plays a critical role during infection.
Host factors determine differential disease progression after infection with nef-deleted simian immunodeficiency virus
Authors: Sopper Sieghart , Mätz-Rensing Kerstin , Mühl Thorsten , Heeney Jonathan , Stahl-Hennig Christiane , Sauermann Ulrike
Published: June 2014

Infection of macaques with live attenuated simian immunodeficiency virus (SIV) usually results in long-lasting efficient protection against infection with pathogenic immunodeficiency viruses. However, attenuation by deletion of regulatory genes such as nef is not complete, leading to a high viral load and fatal disease in some animals. To characterize immunological parameters and polymorphic host factors, we studied 17 rhesus macaques infected with attenuated SIVmac239ΔNU. Eight animals were able to control viral replication, whereas the remaining animals (non-controllers) displayed variable set-point viral loads. Peak viral load at 2 weeks post-infection (p.i.) correlated significantly with set-point viral load (P<0.0001). CD4+ T-cell frequencies differed significantly soon after infection between controllers and non-controllers. Abnormal B-cell activation previously ascribed to Nef function could already be observed in non-controllers 8 weeks after infection despite the absence of Nef. Two non-controllers developed an AIDS-like disease within 102 weeks p.i. Virus from these animals transmitted to naïve animals replicated at low levels and the recipients did not develop immunodeficiency. This suggested that host factors determined differential viral load and subsequent disease course. Known Mhc class I alleles associated with disease progression in SIV WT infection only marginally influenced the viral load in Δnef-infected animals. Protection from SIVmac251 was associated with homozygosity for MHC class II in conjunction with a TLR7 polymorphism and showed a trend with initial viral replication. We speculated that host factors whose effects were usually masked by Nef were responsible for the different disease courses in individual animals upon infection with nef-deleted viruses.
Establishment of regions of genomic activity during theDrosophilamaternal to zygotic transition
Authors: Li Xiao-Yong , Harrison Melissa M. , Kaplan Tommy , Eisen Michael B.
Published: June 2014

A conspicuous feature of early animal development is the lack of transcription from the embryonic genome, and it typically takes several hours to several days (depending on the species) until widespread transcription of the embryonic genome begins. Although this transition is ubiquitous, relatively little is known about how the shift from a transcriptionally quiescent to transcriptionally active genome is controlled. We describe here the genome-wide distributions and temporal dynamics of nucleosomes and post-translational histone modifications through the maternal-to-zygotic transition in embryos of the pomace flyDrosophila melanogaster. At mitotic cycle 8, when few zygotic genes are being transcribed, embryonic chromatin is in a relatively simple state: there are few nucleosome free regions, undetectable levels of the histone methylation marks characteristic of mature chromatin, and low levels of histone acetylation at a relatively small number of loci. Histone acetylation increases by cycle 11, but it is not until cycle 13 that nucleosome free regions and domains of histone methylation become widespread. Early histone acetylation is strongly associated with regions that we have previously shown are bound in early embryos by the maternally deposited transcription factor Zelda. Most of these Zelda-bound regions are destined to be enhancers or promoters active during mitotic cycle 14, and our data demonstrate that they are biochemically distinct long before they become active, raising the possibility that Zelda triggers a cascade of events, including the accumulation of specific histone modifications, that plays a role in the subsequent activation of these sequences. Many of these Zelda-associated active regions occur in larger domains that we find strongly enriched for histone marks characteristic of Polycomb-mediated repression, suggesting a dynamic balance between Zelda activation and Polycomb repression. Collectively, these data paint a complex picture of a genome in transition from a quiescent to an active state, and highlight the role of Zelda in mediating this transition.
Diverse modes of binding in structures ofLeishmania majorN-myristoyltransferase with selective inhibitors
Authors: Brannigan James A. , Roberts Shirley M. , Bell Andrew S. , Hutton Jennie A. , Hodgkinson Michael R. , Tate Edward W. , Leatherbarrow Robin J. , Smith Deborah F. , Wilkinson Anthony J.
Published: June 2014

The leishmaniases are a spectrum of global diseases of poverty associated with immune dysfunction and are the cause of high morbidity. Despite the long history of these diseases, no effective vaccine is available and the currently used drugs are variously compromised by moderate efficacy, complex side effects and the emergence of resistance. It is therefore widely accepted that new therapies are needed.N-Myristoyltransferase (NMT) has been validated pre-clinically as a target for the treatment of fungal and parasitic infections. In a previously reported high-throughput screening program, a number of hit compounds with activity against NMT fromLeishmania donovanihave been identified. Here, high-resolution crystal structures of representative compounds from four hit series in ternary complexes with myristoyl-CoA and NMT from the closely relatedL. majorare reported. The structures reveal that the inhibitors associate with the peptide-binding groove at a site adjacent to the bound myristoyl-CoA and the catalytic α-carboxylate of Leu421. Each inhibitor makes extensive apolar contacts as well as a small number of polar contacts with the protein. Remarkably, the compounds exploit different features of the peptide-binding groove and collectively occupy a substantial volume of this pocket, suggesting that there is potential for the design of chimaeric inhibitors with significantly enhanced binding. Despite the high conservation of the active sites of the parasite and human NMTs, the inhibitors act selectively over the host enzyme. The role of conformational flexibility in the side chain of Tyr217 in conferring selectivity is discussed.
A low-temperature modification of hexa-tert-butyldisilane and a new polymorph of 1,1,2,2-tetra-tert-butyl-1,2-diphenyldisilane
Authors: Scholz Stefan , Lerner Hans-Wolfram , Bats Jan W.
Published: June 2014

Crystals of hexa-tert-butyldisilane, C24H54Si2, undergo a reversible phase transition at 179 (2) K. The space group changes fromIbca(high temperature) toPbca(low temperature), but the lattice constantsa,bandcdo not change significantly during the phase transition. The crystallographic twofold axis of the molecule in the high-temperature phase is replaced by a noncrystallographic twofold axis in the low-temperature phase. The angle between the two axes is 2.36 (4)°. The centre of the molecule undergoes a translation of 0.123 (1) Å during the phase transition, but the conformation angles of the molecule remain unchanged. Between the two tri-tert-butylsilyl subunits there are six short repulsive intramolecular C—H...H—C contacts, with H...H distances between 2.02 and 2.04 Å, resulting in a significant lengthening of the Si—Si and Si—C bonds. The Si—Si bond length is 2.6863 (5) Å and the Si—C bond lengths are between 1.9860 (14) and 1.9933 (14) Å. Torsion angles about the Si—Si and Si—C bonds deviate by approximately 15° from the values expected for staggered conformations due to intramolecular steric H...H repulsions. A new polymorph is reported for the crystal structure of 1,1,2,2-tetra-tert-butyl-1,2-diphenyldisilane, C28H46Si2. It has two independent molecules with rather similar conformations. The Si—Si bond lengths are 2.4869 (8) and 2.4944 (8) Å. The C—Si—Si—C torsion angles deviate by between −3.4 (1) and −18.5 (1)° from the values expected for a staggered conformation. These deviations result from steric interactions. Four Si—C(t-Bu) bonds are almost staggered, while the other four Si—C(t-Bu) bonds are intermediate between a staggered and an eclipsed conformation. The latter Si—C(t-Bu) bonds are about 0.019 (2) Å longer than the staggered Si—C(t-Bu) bonds.
The development of cultural entrepreneurship
Authors: Cheung Leung Chi
Published: June 2014

Purpose

– The aim of the study is to examine the development of four not-for-profit Chinese orchestras in Hong Kong, aiming to identify their key characteristics in management and operational practices, and highlight a probable proposal on how the concept of cultural entrepreneurship could be brought about for the growth of an orchestra.

Design/methodology/approach

– This study looks into the cases of the development of four not-for-profit community Chinese orchestras in Hong Kong in accordance to the theoretical framework built on the reviewed literature. A self-assessment questionnaire survey was conducted among the key leaders in the orchestras, asking them to evaluate themselves about their features as a cultural entrepreneur, and the extent of the development of the orchestras towards entrepreneurship. The survey serves as preliminary reference data for follow-up phone interviews, with questions asked in accordance to the results of the survey.

Findings

– The study shows that the four leaders of the Chinese orchestras have different qualities of a cultural entrepreneur. The four orchestras use different strategies to promote Chinese music, and adopt diversified approaches to survive. Four models of community orchestra having different features are identified, namely new generation model, affiliation-based model, mentor-mentee model, and developmental model. The findings suggest that community orchestras have limitations to the development of cultural entrepreneurship in Hong Kong, and they need the support of the right person and policy to grow and foster.

Originality/value

– The results inform and give insights to cultural entrepreneur-to-bes and practitioners in the cultural industries as well as policy makers on some of the probable innovations employed by not-for-profit community performing groups.
Consumers’ beliefs, attitudes, and loyalty in purchasing organic foods
Authors: Lee Hyun-Joo , Goudeau Cynthia
Published: June 2014

Purpose

– The purpose of this paper is to apply the standard learning hierarchy to the study of organic foods. More specifically, this research is intended to examine if cognition in the form of beliefs and utilitarian attitudes, affect in the form of hedonic attitudes, and behavior in the form of attitudinal loyalty and behavioral loyalty occur successively.

Design/methodology/approach

– A total of 725 consumer panel data were obtained through a web-based survey. A two-stage structural equation modeling with AMOS graphics version 18.0 was used to validate the measurement models and test the proposed hypotheses.

Findings

– While health benefits positively influenced utilitarian attitudes, no significant effect of ecological welfare benefits was detected. The results also indicate that utilitarian attitudes had a significant and positive relationship with hedonic attitudes, which in turn led to attitudinal loyalty. Lastly, the relation between attitudinal loyalty and behavioral loyalty was significant and positive.

Research limitations/implications

– Global attitudes and loyalty toward organic foods were examined in this research. Thus, future research could investigate more domain-specific attitudes and loyalty to various organic food items.

Practical implications

– The development of positive attitudes toward organic foods among consumers is important for the long-term success of organic food products or brands.

Originality/value

– There is a little research that adopts an established theory or theoretical approach to explain a purchase behavior of organic foods. For this reason, the standard learning hierarchy was incorporated in order to study how cognition, affect, and behavior are formed when a purchase decision involving organic foods.