Biology subjects

Brown, N.

Publications and source records attributed to Brown, N..

45 records · Page 3Linked to original sources

bioRxiv2019

Contrasting approaches to genome-wide association studies impact the detection of resistance mechanisms in Staphylococcus aureus

Rapid detection of antibiotic resistance using whole-genome sequencing (WGS) could improve clinical outcomes and limit the spread of resistance. For this to succeed, we need an accurate way of linking genotype to phenotype, that identifies new resistance mechanisms as they appear. To assess how close we are to this goal, we characterized antimicrobial resistance determinants in >4,000 Staphylococcus aureus genomes of isolates associated with bloodstream infection in the United Kingdom and Ireland. We sought to answer three questions: 1) how well did known resistance mechanisms explain phenotypic resistance in our collection, 2) how many previously identified resistance mechanisms appeared in our collection, and 3) how many of these were detectable using four contrasting genome-wide association study (GWAS) methods. Resistance prediction based on the detection of known resistance determinants was 98.8% accurate. We identified challenges in correcting for population structure, clustering orthologous genes, and identifying causal mechanisms in rare or common phenotypes, which reduced the recovery of known mechanisms. Limited sensitivity and specificity of these methods made prediction using GWAS-discovered hits alone less accurate than using literature-derived genetic determinants. However, GWAS methods identified novel mutations associated with resistance, including five mutations in rpsJ, which improved tetracycline resistance prediction for 28 isolates, and a T118I substitution in fusA which resulted in better fusidic acid resistance prediction for 5 isolates. Thus, GWAS approaches in conjunction with phenotypic testing data can support the development of comprehensive databases to enable real-time use of WGS for patient management.

bioinformatics↗

bioRxiv2019

Moving Targets: Monitoring Target Trends in Drug Discovery by Mapping Targets, GO Terms, and Diseases

Drug Discovery is a lengthy and costly process and has faced a period of declining productivity within the last two decades. As a consequence, integrative data-driven approaches are nowadays on the rise in pharmaceutical research, making use of an inter-connected (network) view on diseases. In addition, evidence-based decisions are alleviated by studying the time evolution of innovation trends in drug discovery.\n\nIn this paper a new approach leveraging data mining and data integration for inspecting target innovation trends protein family-wise is presented. The study highlights protein families which are receiving emerging interest in the drug discovery community (mainly kinases and G protein coupled receptors) and those with areas of interest in target space that have just emerged in the scientific literature (mainly kinases and transporters) highlighting novel opportunities for drug intervention.\n\nIn order to delineate the evolution of target-driven research interest from a biological perspective, trends in biological process annotations from Gene Ontology (GO) and disease annotations from DisGeNet for major target families are captured. The analysis reveals an increasing interest in targets related to immune system processes, and a recurrent trend for targets involved in circulatory system processes. At the level of disease annotations, targets associated to e.g., cancer-related pathologies as well as to intellectual disability and schizophrenia are increasingly investigated nowadays.\n\nCan this knowledge be used to study the \"movement of targets\" in a network view and unravel new links between diseases and biological processes? We tackled this question by creating dynamic network representations considering data from different time periods. The dynamic network for immune system process-associated targets suggest that e.g. breast cancer as well as schizophrenia are linked to the same targets (cannabinoid receptor CB2 and VEGFR2) thus suggesting similar treatment options which could be confirmed by literature search. The methodology has the potential to identify other drug repurposing candidates and enables researchers to capture trends in research attention in target space at an early stage.\n\nThe KNIME workflows and R scripts used in this study are publicly available from https://github.com/BZdrazil/Moving_Targets.\n\nAuthor summaryIn this study we have investigated target innovation in drug discovery over a period of 22 years (1995-2016) by extracting time trends of research interest (as published in the scientific literature and stored in the ChEMBL database) in certain protein classes inspecting different measures (numbers of pharmacological measurements, targets, papers, and drugs). Focusing on the most relevant protein classes in drug discovery (G protein-coupled receptors, kinases, ion channels, nuclear receptors, proteases, and transporters), we further linked single targets to Gene Ontology (GO) biological process annotations and inspected steep increasing or decreasing trends of GO annotations within target families over time. We also tracked trends in disease annotations from DisGeNET by filtering out diseases linked to targets with emerging trends in research interest. Finally, targets, GO terms, and diseases are interconnected in network representations and shifts in research foci are investigated over time. This new methodology which utilizes data mapping and data analysis can be used to explore trends in research attention target family-wise, to uncover previously unknown links between diseases and biological processes and to identify potential candidates for drug repurposing.

bioinformatics↗

bioRxiv2018

One Health genomic surveillance of Escherichia coli demonstrates distinct lineages and mobile genetic elements in isolates from humans versus livestock

Livestock have been proposed as a reservoir for drug-resistant Escherichia coli that infect humans. We isolated and sequenced 431 E. coli (including 155 ESBL-producing isolates) from cross-sectional surveys of livestock farms and retail meat in the East of England. These were compared with the genomes of 1517 E. coli associated with bloodstream infection in the United Kingdom. Phylogenetic core genome comparisons demonstrated that livestock and patient isolates were genetically distinct, indicating that E. coli causing serious human infection do not directly originate from livestock. By contrast, we observed highly related isolates from the same animal species on different farms. Analysis of accessory (variable) genomes identified a virulence cassette associated previously with cystitis and neonatal meningitis that was only present in isolates from humans. Screening all 1948 isolates for accessory genes encoding antibiotic resistance revealed 41 different genes present in variable proportions of humans and livestock isolates. We identified a low prevalence of shared antimicrobial resistance genes between livestock and humans based on analysis of mobile genetic elements and long-read sequencing. We conclude that in this setting, there was limited evidence to support the suggestion that antimicrobial resistant pathogens that cause serious infection in humans originate from livestock.\n\nImportanceThe increasing prevalence of E. coli bloodstream infections is a serious public health problem. We used genomic epidemiology in a One Health study conducted in the East of England to examine putative sources of E. coli associated with serious human disease. E. coli from 1517 patients with bloodstream infection were compared with 431 isolates from livestock farms and meat. Livestock-associated and bloodstream isolates were genetically distinct populations based on core genome and accessory genome analyses. Identical antimicrobial resistance genes were found in livestock and human isolates, but there was little overlap in the mobile elements carrying these genes. In addition, a virulence cassette found in humans isolates was not identified in any livestock-associated isolate. Our findings do not support the idea that E. coli causing invasive disease or their resistance genes are commonly acquired from livestock.

genomics↗

bioRxiv2018

Effects of exposure to sublethal concentrations of methoxyfenozide on honey bee colony activity and thermoregulation

Methoxyfenozide is an insect growth regulator (IGR) commonly used in agricultural to simultaneously control pests and preserve beneficial insect populations; however, its impact on honey bees in not fully understood. We conducted field and laboratory experiments to investigate bee health in response to field-relevant doses of this pesticide. Significant effects were observed in honey bee colony flight activity and thermoregulation after being treated with methoxyfenozide. Data collected indicated that hives fed 500 ppb methoxyfenozide treated pollen patty had: 1) a significantly reduced rate of daily hive weight loss due to forager departure at the start of the colonys daily activity; 2) the end of the colonys daily activity delayed by 17-21 minutes compared to Control; and 3) higher temperature variability during the winter. Colonies in the 125 ppb treatment group had fewer differences with the Control group, but did show a delay in the foraging end time by 30-46 minutes compared to the Control. Bee colony metrics of adult bee mass and brood surface area, and individual bee measurements of head weight, newly-emerged bee weight, and hypopharyngeal gland size were not significantly affected by the methoxyfenozide exposure levels of our experiments. An experiment conducted using the same treatment groups in the spring resulted in fewer differences among groups than did the experiments conducted in the fall. Analyses of methoxyfenozide concentrations in the treatment patty, wax, and bee bread showed that: 1) observed methoxyfenozide concentrations were about 18-60% lower than the calculated concentrations; 2) no residues were observed in wax in any treatment; and 3) methoxyfenozide was detected in stored bee bread in the 500 ppb treatment, at concentrations about 1-2.5% of the observed concentration for that treatment. These results suggest that there may be significant effects on honey bee colony behavior (and possibly health) in the field that are difficult to detect through traditional hive inspections and individual metrics.

zoology↗

bioRxiv2018

Salmonella effectors SseK1 and SseK3 target death domain proteins in the TNF and TRAIL signaling pathways

Strains of Salmonella utilise two distinct type three secretion systems to deliver effector proteins directly into host cells. The Salmonella effectors SseK1 and SseK3 are arginine glycosyltransferases that modify mammalian death domain containing proteins with N-acetyl glucosamine (GlcNAc) when overexpressed ectopically or as recombinant protein fusions. Here, we combined Arg-GlcNAc glycopeptide immunoprecipitation and mass spectrometry to identify host proteins GlcNAcylated by endogenous levels of SseK1 and SseK3 during Salmonella infection. We observed that SseK1 modified the mammalian signaling protein TRADD, but not FADD as previously reported. Overexpression of SseK1 greatly broadened substrate specificity, while ectopic co-expression of SseK1 and TRADD increased the range of modified arginine residues within the death domain of TRADD. In contrast, endogenous levels of SseK3 resulted in modification of the death domains of receptors of the mammalian TNF superfamily, TNFR1 and TRAILR, at residues Arg376 and Arg293 respectively. Structural studies on SseK3 showed that the enzyme displays a classic GT-A glycosyltransferase fold and binds UDP-GlcNAc in a narrow and deep cleft with the GlcNAc facing the surface. Together our data suggests that Salmonellae carrying sseK1 and sseK3 employ the glycosyltransferase effectors to antagonise different components of death receptor signaling.

microbiology↗

bioRxiv2018

A three dimensional multiplane kinematic model for bilateral hind limb gait analysis in cats

Background: Kinematic gait analysis is an important noninvasive technique used for quantitative evaluation and description of locomotion and other movements in healthy and injured populations. Three dimensional (3D) kinematic analysis offers additional outcome measures including internal-external rotation not characterized using sagittal plane analysis techniques.\n\nMethods: The objectives of this study were to 1) develop and evaluate a 3D hind limb multiplane kinematic model for gait analysis in cats using joint coordinate systems, 2) implement and compare two 3D stifle (knee) prediction techniques, and 3) compare flexion-extension determined using the multiplane model to a sagittal plane model. Walking gait was recorded in 3 female adult cats (age = 2.9 years, weight = 3.5 {+/-} 0.2 kg). Kinematic outcomes included flexion-extension, internal-external rotation, and abduction-adduction of the hip, stifle, and tarsal (ankle) joints.\n\nResults: Each multiplane stifle prediction technique yielded similar findings. Joint angles determined using markers placed on skin above bony landmarks in vivo were similar to joint angles determined using a feline hind limb skeleton in which markers were placed directly on landmarks ex vivo. Differences in hip, stifle, and tarsal joint flexion-extension were demonstrated when comparing the multiplane model to the sagittal plane model.\n\nConclusions: This multiplane cat kinematic model can predict joint rotational kinematics as a tool that can quantify frontal, transverse, and sagittal plane motion. This model has multiple advantages given its ability to characterize joint internal-external rotation and abduction-adduction. A further, important benefit is greater accuracy in representing joint flexion-extension movements.

neuroscience↗

bioRxiv2018

Novel functions for integrin-associated proteins revealed by myofibril attachment in Drosophila

We use the myotendinous junction of Drosophila flight muscles to explore why many integrin associated proteins (IAPs) are needed and how their function is coordinated. These muscles revealed new functions for IAPs not required for viability: Focal Adhesion Kinase (FAK), RSU1, tensin and vinculin. Genetic interactions demonstrated a balance between positive and negative activities, with vinculin and tensin positively regulating adhesion, while FAK inhibits elevation of integrin activity by tensin, and RSU1 keeps PINCH activity in check. The molecular composition of myofibril termini resolves into 4 distinct layers, one of which is built by a mechanotransduction cascade: vinculin facilitates mechanical opening of filamin, which works with the Arp2/3 activator WASH to build an actin-rich layer positioned between integrins and the first sarcomere. Thus, integration of IAP activity is needed to build the complex architecture of the myotendinous junction, linking the membrane anchor to the sarcomere.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC=\"FIGDIR/small/296699_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (39K):\norg.highwire.dtl.DTLVardef@14a8f07org.highwire.dtl.DTLVardef@1f4446aorg.highwire.dtl.DTLVardef@1b7b114org.highwire.dtl.DTLVardef@cabac7_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2017

Characterization of Glycosylphosphatidylinositol Biosynthesis Defects by Clinical Features, Flow Cytometry, and Automated Image Analysis

BackgroundGlycosylphosphatidylinositol Biosynthesis Defects (GPIBDs) cause a group of phenotypically overlapping recessive syndromes with intellectual disability, for which pathogenic mutations have been described in 16 genes of the corresponding molecular pathway. An elevated serum activity of alkaline phosphatase (AP), a GPI-linked enzyme, has been used to assign GPIBDs to the phenotypic series of Hyperphosphatasia with Mental Retardation Syndrome (HPMRS) and to distinguish them from another subset of GPIBDs, termed Multiple Congenital Anomalies Hypotonia Seizures syndrome (MCAHS). However, the increasing number of individuals with a GPIBD shows that hyperphosphatasia is a variable feature that is not ideal for a clinical classification.\n\nMethodsWe studied the discriminatory power of multiple GPI-linked substrates that were assessed by flow cytometry in blood cells and fibroblasts of 39 and 14 individuals with a GPIBD, respectively. On the phenotypic level, we evaluated the frequency of occurrence of clinical symptoms and analyzed the performance of computer-assisted image analysis of the facial gestalt in 91 individuals.\n\nResultsWe found that certain malformations such as Morbus Hirschsprung and Diaphragmatic defects are more likely to be associated with particular gene defects (PIGV, PGAP3, PIGN). However, especially at the severe end of the clinical spectrum of HPMRS, there is a high phenotypic overlap with MCAHS. Elevation of AP has also been documented in some of the individuals with MCAHS, namely those with PIGA mutations. Although the impairment of GPI-linked substrates is supposed to play the key role in the pathophysiology of GPIBDs, we could not observe gene-specific profiles for flow cytometric markers or a correlation between their cell surface levels and the severity of the phenotype. In contrast, it was facial recognition software that achieved the highest accuracy in predicting the disease-causing gene in a GPIBD.\n\nConclusionsDue to the overlapping clinical spectrum of both, HPMRS and MCAHS, in the majority of affected individuals, the elevation of AP and the reduced surface levels of GPI-linked markers in both groups, a common classification as GPIBDs is recommended. The effectiveness of computer-assisted gestalt analysis for the correct gene inference in a GPIBD and probably beyond is remarkable and illustrates how the information contained in human faces is pivotal in the delineation of genetic entities.

genetics↗

bioRxiv2017

Genome-wide analysis of genetic risk factors for rheumatic heart disease in Aboriginal Australians provides support for pathogenic molecular mimicry

BackgroundRheumatic heart disease (RHD) following Group A Streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers pro-inflammatory cardiac valve-reactive T-cells.\n\nMethodsGenome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single nucleotide polymorphisms (SNPs) were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6.\n\nResultsThe strongest genetic association was intronic to HLA-DQA1 (rs9272622; P=1.86x10-7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (OR 1.44, 95%CI 1.09-1.90, P=9.56x10-3) and HLA-DQA1*0103_DQB1*0601 (OR 1.27, 95%CI 1.07-1.52, P=7.15x10-3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14-0.65, P=2.36x10-3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the two risk haplotypes than the protective haplotype.\n\nConclusionsVariation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

genetics↗