The complete genome sequence of Escherichia coli EC958: a high quality reference sequence for the globally disseminated multidrug resistant E. coli O25b:H4-ST131 clone

Escherichia coli ST131 is now recognised as a leading contributor to urinary tract and bloodstream infections in both community and clinical settings. Here we present the complete, annotated genome of E. coli EC958, which was isolated from the urine of a patient presenting with a urinary tract infection in the Northwest region of England and represents the most well characterised ST131 strain. Sequencing was carried out using the Pacific Biosciences platform, which provided sufficient depth and read-length to produce a complete genome without the need for other technologies. The discovery of spurious contigs within the assembly that correspond to site-specific inversions in the tail fibre regions of prophages demonstrates the potential for this technology to reveal dynamic evolutionary mechanisms. E. coli EC958 belongs to the major subgroup of ST131 strains that produce the CTX-M-15 extended spectrum β-lactamase, are fluoroquinolone resistant and encode the fimH30 type 1 fimbrial adhesin. This subgroup includes the Indian strain NA114 and the North American strain JJ1886. A comparison of the genomes of EC958, JJ1886 and NA114 revealed that differences in the arrangement of genomic islands, prophages and other repetitive elements in the NA114 genome are not biologically relevant and are due to misassembly. The availability of a high quality uropathogenic E. coli ST131 genome provides a reference for understanding this multidrug resistant pathogen and will facilitate novel functional, comparative and clinical studies of the E. coli ST131 clonal lineage.

Insights into a multidrug resistant Escherichia coli pathogen of the globally disseminated ST131 lineage : genome analysis and virulence mechanisms

Escherichia coli strains causing urinary tract infection (UTI) are increasingly recognized as belonging to specific clones. E. coli clone O25b:H4-ST131 has recently emerged globally as a leading multi-drug resistant pathogen causing urinary tract and bloodstream infections in hospitals and the community. While most molecular studies to date examine the mechanisms conferring multi-drug resistance in E. coli ST131, relatively little is known about their virulence potential. Here we examined E. coli ST131 clinical isolates from two geographically diverse collections, one representing the major pathogenic lineages causing UTI across the United Kingdom and a second representing UTI isolates from patients presenting at two large hospitals in Australia. We determined a draft genome sequence for one representative isolate, E. coli EC958, which produced CTX-M-15 extended-spectrum β-lactamase, CMY-23 type AmpC cephalosporinase and was resistant to ciprofloxacin. Comparative genome analysis indicated that EC958 encodes virulence genes commonly associated with uropathogenic E. coli (UPEC). The genome sequence of EC958 revealed a transposon insertion in the fimB gene encoding the activator of type 1 fimbriae, an important UPEC bladder colonization factor. We identified the same fimB transposon insertion in 59% of the ST131 UK isolates, as well as 71% of ST131 isolates from Australia, suggesting this mutation is common among E. coli ST131 strains. Insertional inactivation of fimB resulted in a phenotype resembling a slower off-to-on switching for type 1 fimbriae. Type 1 fimbriae expression could still be induced in fimB-null isolates; this correlated strongly with adherence to and invasion of human bladder cells and bladder colonisation in a mouse UTI model. We conclude that E. coli ST131 is a geographically widespread, antibiotic resistant clone that has the capacity to produce numerous virulence factors associated with UTI.

Whole-genome multiparametric screening to identify modulators of epithelial-to-mesenchymal transition

Metastasis accounts for the poor prognosis of the majority of solid tumors. The phenotypic transition of nonmotile epithelial tumor cells to migratory and invasive “mesenchymal” cells (epithelial-to-mesenchymal transition [EMT]) enables the transit of cancer cells from the primary tumor to distant sites. There is no single marker of EMT; rather, multiple measures are required to define cell state. Thus, the multiparametric capability of high-content screening is ideally suited for the comprehensive analysis of EMT regulators. The aim of this study was to generate a platform to systematically identify functional modulators of tumor cell plasticity using the bladder cancer cell line TSU-Pr1-B1 as a model system. A platform enabling the quantification of key EMT characteristics, cell morphology and mesenchymal intermediate filament vimentin, was developed using the fluorescent whole-cell-tracking reagent CMFDA and a fluorescent promoter reporter construct, respectively. The functional effect of genome-wide modulation of protein-coding genes and miRNAs coupled with those of a collection of small-molecule kinase inhibitors on EMT was assessed using the Target Activation Bioapplication integrated in the Cellomics ArrayScan platform. Data from each of the three screens were integrated to identify a cohort of targets that were subsequently examined in a validation assay using siRNA duplexes. Identification of established regulators of EMT supports the utility of this screening approach and indicated capacity to identify novel regulators of this plasticity program. Pathway analysis coupled with interrogation of cancer-related expression profile databases and other EMT-related screens provided key evidence to prioritize further experimental investigation into the molecular regulators of EMT in cancer cells.

Design, manufacturing and maintenance of sugar milling equipment : observations from the 2008 ISSCT Engineering Workshop

An International Society of Sugar Cane Technologists (ISSCT) Engineering Workshop was held in Piracicaba, Brazil from 30 June to 4 July 2008. The theme of the workshop was Design, manufacturing and maintenance of sugar mill equipment. The workshop consisted of a series of technical sessions and site visits. The Brazilian sugar industry is growing rapidly. The growth has occurred as the result of the sugar industry’s position as a key provider of renewable energy in the form of ethanol and, more recently, electricity. The increased focus on electricity is seeing investment in high pressure (100 bar) boilers, cane cleaning plants that allow an increased biomass supply from trash and digesters that produce biogas from dunder. It is clear that the Brazilian sugar industry has a well defined place in the country’s future. The ISSCT workshop provided a good opportunity to gain information from equipment suppliers and discuss new technology that may have application in Australia. The new technologies of interest included IMCO sintered carbide shredder hammer tips, Fives Cail MillMax mills, planetary mill gearboxes, Bosch Projects chainless diffusers, Fives Cail Zuka centrifugals and Vaperma Siftek membrane systems.

Learning-based Relevance Feedback for Web-based Relation Completion

In a pilot application based on web search engine calledWeb-based Relation Completion (WebRC), we propose to join two columns of entities linked by a predefined relation by mining knowledge from the web through a web search engine. To achieve this, a novel retrieval task Relation Query Expansion (RelQE) is modelled: given an entity (query), the task is to retrieve documents containing entities in predefined relation to the given one. Solving this problem entails expanding the query before submitting it to a web search engine to ensure that mostly documents containing the linked entity are returned in the top K search results. In this paper, we propose a novel Learning-based Relevance Feedback (LRF) approach to solve this retrieval task. Expansion terms are learned from training pairs of entities linked by the predefined relation and applied to new entity-queries to find entities linked by the same relation. After describing the approach, we present experimental results on real-world web data collections, which show that the LRF approach always improves the precision of top-ranked search results to up to 8.6 times the baseline. Using LRF, WebRC also shows performances way above the baseline.

Injury narrative text classification : a preliminary study

Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

The plasticity of NBS resistance genes in sorghum is driven by multiple evolutionary processes

Background Increased disease resistance is a key target of cereal breeding programs, with disease outbreaks continuing to threaten global food production, particularly in Africa. Of the disease resistance gene families, the nucleotide-binding site plus leucine-rich repeat (NBS-LRR) family is the most prevalent and ancient and is also one of the largest gene families known in plants. The sequence diversity in NBS-encoding genes was explored in sorghum, a critical food staple in Africa, with comparisons to rice and maize and with comparisons to fungal pathogen resistance QTL. Results In sorghum, NBS-encoding genes had significantly higher diversity in comparison to non NBS-encoding genes and were significantly enriched in regions of the genome under purifying and balancing selection, both through domestication and improvement. Ancestral genes, pre-dating species divergence, were more abundant in regions with signatures of selection than in regions not under selection. Sorghum NBS-encoding genes were also significantly enriched in the regions of the genome containing fungal pathogen disease resistance QTL; with the diversity of the NBS-encoding genes influenced by the type of co-locating biotic stress resistance QTL. Conclusions NBS-encoding genes are under strong selection pressure in sorghum, through the contrasting evolutionary processes of purifying and balancing selection. Such contrasting evolutionary processes have impacted ancestral genes more than species-specific genes. Fungal disease resistance hot-spots in the genome, with resistance against multiple pathogens, provides further insight into the mechanisms that cereals use in the “arms race” with rapidly evolving pathogens in addition to providing plant breeders with selection targets for fast-tracking the development of high performing varieties with more durable pathogen resistance.

A transcriptome resource for the koala (Phascolarctos cinereus) : insights into koala retrovirus transcription and sequence diversity

Background The koala, Phascolarctos cinereus, is a biologically unique and evolutionarily distinct Australian arboreal marsupial. The goal of this study was to sequence the transcriptome from several tissues of two geographically separate koalas, and to create the first comprehensive catalog of annotated transcripts for this species, enabling detailed analysis of the unique attributes of this threatened native marsupial, including infection by the koala retrovirus. Results RNA-Seq data was generated from a range of tissues from one male and one female koala and assembled de novo into transcripts using Velvet-Oases. Transcript abundance in each tissue was estimated. Transcripts were searched for likely protein-coding regions and a non-redundant set of 117,563 putative protein sequences was produced. In similarity searches there were 84,907 (72%) sequences that aligned to at least one sequence in the NCBI nr protein database. The best alignments were to sequences from other marsupials. After applying a reciprocal best hit requirement of koala sequences to those from tammar wallaby, Tasmanian devil and the gray short-tailed opossum, we estimate that our transcriptome dataset represents approximately 15,000 koala genes. The marsupial alignment information was used to look for potential gene duplications and we report evidence for copy number expansion of the alpha amylase gene, and of an aldehyde reductase gene. Koala retrovirus (KoRV) transcripts were detected in the transcriptomes. These were analysed in detail and the structure of the spliced envelope gene transcript was determined. There was appreciable sequence diversity within KoRV, with 233 sites in the KoRV genome showing small insertions/deletions or single nucleotide polymorphisms. Both koalas had sequences from the KoRV-A subtype, but the male koala transcriptome has, in addition, sequences more closely related to the KoRV-B subtype. This is the first report of a KoRV-B-like sequence in a wild population. Conclusions This transcriptomic dataset is a useful resource for molecular genetic studies of the koala, for evolutionary genetic studies of marsupials, for validation and annotation of the koala genome sequence, and for investigation of koala retrovirus. Annotated transcripts can be browsed and queried at http://koalagenome.org

Sexual selection in true fruit flies (Diptera: Tephritidae) : transcriptome and experimental evidences for phytochemicals increasing male competitive ability

In male tephritid fruit flies of the genus Bactrocera, feeding on secondary plant compounds (sensu lato male lures = methyl eugenol, raspberry ketone and zingerone) increases male mating success. Ingested male lures alter the male pheromonal blend, normally making it more attractive to females and this is considered the primary mechanism for the enhanced mating success. However, the male lures raspberry ketone and zingerone are known, across a diverse range of other organisms, to be involved in increasing energy metabolism. If this also occurs in Bactrocera, then this may represent an additional benefit to males as courtship is metabolically expensive and lure feeding may increase a fly's short-term energy. We tested this hypothesis by performing comparative RNA-seq analysis between zingerone-fed and unfed males of Bactrocera tryoni. We also carried out behavioural assays with zingerone- and cuelure-fed males to test whether they became more active. RNA-seq analysis revealed, in zingerone-fed flies, up-regulation of 3183 genes with homologues transcripts to those known to regulate intermale aggression, pheromone synthesis, mating and accessory gland proteins, along with significant enrichment of several energy metabolic pathways and gene ontology terms. Behavioural assays show significant increases in locomotor activity, weight reduction and successful mating after mounting; all direct/indirect measures of increased activity. These results suggest that feeding on lures leads to complex physiological changes, which result in more competitive males. These results do not negate the pheromone effect, but do strongly suggest that the phytochemical-induced sexual selection is governed by both female preference and male competitive mechanisms.

A new ambiguity acceptance test threshold determination method with controllable failure rate

The ambiguity acceptance test is an important quality control procedure in high precision GNSS data processing. Although the ambiguity acceptance test methods have been extensively investigated, its threshold determine method is still not well understood. Currently, the threshold is determined with the empirical approach or the fixed failure rate (FF-) approach. The empirical approach is simple but lacking in theoretical basis, while the FF-approach is theoretical rigorous but computationally demanding. Hence, the key of the threshold determination problem is how to efficiently determine the threshold in a reasonable way. In this study, a new threshold determination method named threshold function method is proposed to reduce the complexity of the FF-approach. The threshold function method simplifies the FF-approach by a modeling procedure and an approximation procedure. The modeling procedure uses a rational function model to describe the relationship between the FF-difference test threshold and the integer least-squares (ILS) success rate. The approximation procedure replaces the ILS success rate with the easy-to-calculate integer bootstrapping (IB) success rate. Corresponding modeling error and approximation error are analysed with simulation data to avoid nuisance biases and unrealistic stochastic model impact. The results indicate the proposed method can greatly simplify the FF-approach without introducing significant modeling error. The threshold function method makes the fixed failure rate threshold determination method feasible for real-time applications.

Towards Vision-Based Pose- and Condition-Invariant Place Recognition along Routes

Vision-based place recognition involves recognising familiar places despite changes in environmental conditions or camera viewpoint (pose). Existing training-free methods exhibit excellent invariance to either of these challenges, but not both simultaneously. In this paper, we present a technique for condition-invariant place recognition across large lateral platform pose variance for vehicles or robots travelling along routes. Our approach combines sideways facing cameras with a new multi-scale image comparison technique that generates synthetic views for input into the condition-invariant Sequence Matching Across Route Traversals (SMART) algorithm. We evaluate the system’s performance on multi-lane roads in two different environments across day-night cycles. In the extreme case of day-night place recognition across the entire width of a four-lane-plus-median-strip highway, we demonstrate performance of up to 44% recall at 100% precision, where current state-of-the-art fails.