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Morgan, M.

Publications and source records attributed to Morgan, M..

52 records · Page 3Linked to original sources

Multi-omic analysis supports a developmental hierarchy of molecular subtypes in high-grade serous ovarian carcinoma

Multiple studies have identified transcriptome subtypes of high-grade serous ovarian carcinoma (HGSOC), but these have yet to impact clinical practice. Interpretation and translation of HGSOC subtypes are complicated by tumor evolution and polyclonality accompanied by accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. The chronology of HGSOC subtype evolution was examined in the context of these factors by a novel integrative analysis of bulk absolute somatic copy number analysis and gene expression in The Cancer Genome Atlas, complemented by single-cell RNA-seq analysis of six independent tumors. The approach was validated by contrast to soft-tissue sarcoma. Genomic lesions associated with HGSOC subtypes tend to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations is particularly evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors are characterized by largely intact genome integrity, high immune infiltration, and younger patient age. We propose an alternative model to discrete subtypes of HGSOC, in which tumors develop from an early differentiated spectrum to a late proliferative spectrum, along a timeline characterized by increasing genomic instability and subclonal expansion. The proposed methods provide a new approach to investigating tumor evolution through multi-omic analysis. Statement of SignificanceThis study proposes a method to infer whether transcriptome-based groupings of tumors differentiate early in carcinogenesis and are therefore potentially appropriate targets for therapy, and demonstrates that this is not the case for high-grade serous ovarian carcinoma (HGSOC). Significant findings for HGSOC include: O_LITumor purity, ploidy, and subclonality can be reliably inferred from different genomic platforms and show marked differences between subtypes C_LIO_LIRecurrent DNA alterations are associated with subtypes and tend to occur more frequently in subclones C_LIO_LISingle-cell sequencing of 42,000 tumor cells reveals widespread heterogeneity in tumor cell type composition that drives bulk subtype calls, but demonstrates a lack of intrinsic subtypes among tumor epithelial cells C_LIO_LIFindings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tissue of origin and tumor stage, and evolution between properties previously associated with discrete subtypes C_LI

cancer biology↗

Reliable analysis of clinical tumor-only whole exome sequencing data

BackgroundAllele-specific copy number alteration (CNA) analysis is essential to study the functional impact of single nucleotide variants (SNV) and the process of tumorigenesis. Most commonly used tools in the field rely on high quality genome-wide data with matched normal profiles, limiting their applicability in clinical settings. MethodsWe propose a workflow, based on the open-source PureCN R/Bioconductor package in conjunction with widely used variant-calling and copy number segmentation algorithms, for allele-specific CNA analysis from whole exome sequencing (WES) without matched normals. We use The Cancer Genome Atlas (TCGA) ovarian carcinoma (OV) and lung adenocarcinoma (LUAD) datasets to benchmark its performance against gold standard SNP6 microarray and WES datasets with matched normal samples. Our workflow further classifies SNVs by somatic status and then uses this information to infer somatic mutational signatures and tumor mutational burden (TMB). ResultsApplication of our workflow to tumor-only WES data produces tumor purity and ploidy estimates that are highly concordant with estimates from SNP6 microarray data and matched-normal WES data. The presence of cancer type-specific somatic mutational signatures was inferred with high accuracy. We also demonstrate high concordance of TMB between our tumor-only workflow and matched normal pipelines. ConclusionThe proposed workflow provides, to our knowledge, the only open-source option for comprehensive allele-specific CNA analysis and SNV classification of tumor-only WES with demonstrated high accuracy.

bioinformatics↗

Reconciling the potentially irreconcilable? Genotypic and phenotypic amoxicillin-clavulanate resistance in Escherichia coli

Resistance to amoxicillin-clavulanate, a widely used beta-lactam/beta-lactamase inhibitor combination antibiotic, is rising globally, yet susceptibility testing remains challenging. To test whether whole-genome sequencing (WGS) could provide a more reliable assessment of susceptibility than traditional methods, we predicted resistance from WGS for 976 E. coli bloodstream infection isolates from Oxfordshire, UK, comparing against phenotypes from the BD Phoenix (calibrated against EUCAST guidelines). 339/976 (35%) isolates were amoxicillin-clavulanate resistant. Predictions based solely on beta-lactamase presence/absence performed poorly (sensitivity 23% (78/339)) but improved when genetic features associated with penicillinase hyper-production (e.g. promoter mutations, copy number estimates) were considered (sensitivity 82% (277/339); p<0.0001). Most discrepancies occurred in isolates with peri-breakpoint MICs. We investigated two potential causes; the phenotypic reference and the binary resistant/susceptible classification. We performed reference standard, replicated phenotyping in a random stratified subsample of 261/976 (27%) isolates using agar dilution, following both EUCAST and CLSI guidelines, which use different clavulanate concentrations. As well as disagreeing with each other, neither agar dilution phenotype aligned perfectly with genetic features. A random-effects model investigating associations between genetic features and MICs showed that some genetic features had small, variable and additive effects, resulting in variable resistance classification. Using model fixed-effects to predict MICs for the non-agar dilution isolates, predicted MICs were in essential agreement ({+/-}1 doubling dilution) with observed (BD Phoenix) MICs for 691/715 (97%) isolates. This suggests amoxicillin-clavulanate resistance in E. coli is quantitative, rather than qualitative, explaining the poorly reproducible binary (resistant/susceptible) phenotypes and suboptimal concordance between different phenotypic methods and with WGS-based predictions.

microbiology↗

Correlations between holistic processing, Autism quotient, extraversion, and experience and the own-gender bias in face recognition

The variability in the own-gender bias (OGB) in face-recognition is thought to be based on experience (Herlitz & Loven, 2013) and the engagement of expert face processing mechanisms for own-gender faces. Experience is also associated with personality characteristics such as extraversion and Autism, yet the effects of these variables on the own-gender bias has not been explored. We ran a face recognition study exploring the relationships between opposite-gender experience, holistic processing (measured using the face-inversion effect, composite face effect, and the parts-and-wholes test), personality characteristics (extraversion and Autism Quotient) and the OGB. Findings did not support a mediational account where experience increases holistic processing and this increases the OGB. Rather, there was a direct relationship between extraversion and Autism Quotient and the OGB. We interpret this as personality characteristics having an effect on the motivation to process own-gender faces more deeply than opposite-gender faces.

neuroscience↗

MinION Nanopore Sequencing of Multiple Displacement Amplified Mycobacteria DNA Direct from Sputum

Sequencing of pathogen DNA directly from clinical samples offers the possibilities of rapid diagnosis, faster antimicrobial resistance prediction and enhanced outbreak investigation. The approach is especially advantageous for infections caused by species which grow very slowly in culture, such as Mycobacteria tuberculosis. Since the pathogen of interest may represent as little as 0.01% of the total DNA, enrichment of the input material for target sequences by specific amplification and, or depletion of non-target DNA (human, other bacteria) is essential for success. Here, we investigated the potential of isothermal multiple displacement amplification by Phi29 polymerase. We directed the amplification reaction towards Mycobacteria DNA in sputum samples by exploiting in our oligonucleotide primer design, their high GC content (approximately 65%) relative to human DNA. Amplified DNA was then sequenced using the Oxford Nanopore Technology MinION. In addition, a model system comprising standardised mock clinical samples was designed. Pooled infection negative human sputum samples were spiked with enumerated Mycobacterium bovis (BCG) Pasteur strain at concentrations spanning the typical range at which Mycobacterium tuberculosis is found in human sputum samples (106 - 101 BCG cells/ml). To assess the amount of BCG sequence enrichment achieved, sample DNA was sequenced both before, and after amplification. Reads from amplified samples, which mapped to a BCG reference genome, comprised short repeated sequences - apparently transcribed multiple times from the same fragment of BCG DNA. Therefore post-amplification, the samples were enriched for BCG sequences relative to unamplified sequences (8,101 BCG reference mapped reads, increasing to 28,617 at 106 BCG cells/ml sample), but BCG genome coverage declined markedly (for example 89.4% to 4.1%). In summary, the use of standardised mock clinical samples allowed direct comparison of data from different Mycobacteria enrichment experiments and sequencing runs. However, optimal conditions for multiple displacement amplification of minority Mycobacteria DNAs, remain to be identified.

microbiology↗

Attention and the motion after effect: New measurements with visual search reveal important individual differences in adaptability.

It is usually assumed that sensory adaptation is a universal property of human vision. However, in two experiments designed to measure adaptation without bias, we have discovered a minority of participants who were unusual in the extent of their adaptation to motion. One experiment was designed so that targets would be invisible without adaptation; the other, so that adaptation would interfere with target detection. In the first, participants adapted to a spatial array of moving Gabor patches. On each trial the adapting array was followed by a test array in which but all of the test patches except one were identical to their spatially corresponding adaptors; the target moved in the opposite direction to its adaptor. Participants were required to identify the location of the changed target with a mouse click. The ability to do so increased with the number of adapting trials. Neither search speed nor accuracy was affected by an attentionally-demanding conjunction task at the fixation point during adaptation, suggesting low-level (pre-attentive) sites in the visual pathway for the adaptation. However, a minority of participants found the task virtually impossible. In the second experiment the same participants were required to identify the one element in the test array that was slowly moving: reaction times in this case were elevated following adaptation. The putatively weak adapters from the first experiment found this task easier than the strong adapters.

neuroscience↗

gwasurvivr: an R package for genome wide survival analysis

SummaryTo address the limited software options for performing survival analyses with millions of SNPs, we developed gwasurvivr, an R/Bioconductor package with a simple interface for conducting genome wide survival analyses using VCF (outputted from Michigan or Sanger imputation servers), IMPUTE2 or PLINK files. To decrease the number of iterations needed for convergence when optimizing the parameter estimates in the Cox model we modified the R package survival; covariates in the model are first fit without the SNP, and those parameter estimates are used as initial points. We benchmarked gwasurvivr with other software capable of conducting genome wide survival analysis (genipe, SurvivalGWAS_SV, and GWASTools). gwasurvivr is significantly faster and shows better scalability as sample size, number of SNPs and number of covariates increases.\n\nAvailability and implementationgwasurvivr, including source code, documentation, and vignette are available at: http://bioconductor.org/packages/gwasurvivr\n\nContactAbbas Rizvi, rizvi.33@osu.edu; Lara E Sucheston-Campbell, suchestoncampbell.1@osu.edu\n\nSupplementary information: Supplementary data are available at https://github.com/suchestoncampbelllab/gwasurvivr_manuscript

genomics↗

Whole genome sequencing for predicting Mycobacterium abscessus drug susceptibility

Mycobacterium abscessus is emerging as an important pathogen in chronic lung diseases with concern regarding patient to patient transmission. The recent introduction of routine whole genome sequencing (WGS) as a replacement for existing reference techniques in England provides an opportunity to characterise the genetic determinants of resistance. We conducted a systematic review to catalogue all known resistance determining mutations. This knowledge was used to construct a predictive algorithm based on mutations in the erm(41) and rrl genes which was tested on a collection of 203 sequentially acquired clinical isolates for which there was paired genotype/phenotype data. A search for novel resistance determining mutations was conducted using an heuristic algorithm.\n\nThe sensitivity of existing knowledge for predicting resistance in clarithromycin was 95% (95% CI 89 - 98%) and the specificity was 66% (95% CI 54 - 76%). Subspecies alone was a poor predictor of resistance to clarithromycin. Eight potential new resistance conferring SNPs were identified. WGS demonstrates probable resistance determining SNPs in regions the NTM-DR line probe cannot detect. These mutations are potentially clinically important as they all occurred in samples predicted to be inducibly resistant, and for which a macrolide would therefore currently be indicated. We were unable to explain all resistance, raising the possibility of the involvement of other as yet unidentified genes.

microbiology↗

Active site alanine substitutions can convert deubiquitinating enzymes into avid ubiquitin-binding domains

A common strategy for studying the biological role of deubiquitinating enzymes (DUBs) in different pathways is to study the effects of replacing the wild type DUB with a catalytically inactive mutant in cells. We report here that a commonly studied DUB mutation, in which the catalytic cysteine is replaced with alanine, can dramatically increase the affinity of some DUBs for ubiquitin. Overexpression of these tight-binding mutants thus has the potential to sequester cellular pools of monoubiquitin and ubiquitin chains. As a result, cells expressing these mutants may display unpredictable dominant negative physiological effects that are not related to loss of DUB activity. The structure of the SAGA DUB module bound to free ubiquitin reveals the structural basis for the 30-fold higher affinity of Ubp8C146A for ubiquitin. We show that an alternative option, substituting the active site cysteine with arginine, can inactivate DUBs while also decreasing the affinity for ubiquitin.

biochemistry↗

Trends in Escherichia coli bloodstream infection, urinary tract infections and antibiotic susceptibilities in Oxfordshire, 1998-2016: an observational study

BackgroundThe incidence of Escherichia coli bloodstream infections (EC-BSIs), particularly those caused by antibiotic-resistant strains, is increasing in the UK and internationally. This is a major public health concern but the evidence base to guide interventions is limited.\n\nMethodsIncidence of EC-BSIs and E. coli urinary tract infections (EC-UTIs) in one UK region (Oxfordshire) were estimated from anonymised linked microbiological and hospital electronic health records, and modelled using negative binomial regression based on microbiological, clinical and healthcare exposure risk factors. Infection severity, 30-day allcause mortality, and community and hospital co-amoxiclav use were also investigated.\n\nFindingsFrom 1998-2016, 5706 EC-BSIs occurred in 5215 patients, and 228376 EC-UTIs in 137075 patients. 1365(24%) EC-BSIs were nosocomial (onset >48h post-admission), 1863(33%) were community (>365 days post-discharge), 1346(24%) were quasi-community (31-365 days post-discharge), and 1132(20%) were quasi-nosocomial ([&le;]30 days postdischarge). 1413(20%) EC-BSIs and 36270(13%) EC-UTIs were co-amoxiclav-resistant (41% and 30%, respectively, in 2016). Increases in EC-BSIs were driven by increases in community (10%/year (95% CI:7%-13%)) and quasi-community (8%/year (95% CI:7%-10%)) cases. Changes in EC-BSI-associated 30-day mortality were at most modest (p>0{middle dot}03), and mortality was substantial (14-25% across groups). By contrast, co-amoxiclav-resistant EC-BSIs increased in all groups (by 11%-19%/year, significantly faster than susceptible EC-BSIs, pheterogeneity<0{middle dot}001), as did co-amoxiclav-resistant EC-UTIs (by 13%-29%/year, pheterogeneity*0{middle dot}001). Co-amoxiclav use in primary-care facilities was associated with subsequent co-amoxiclav-resistant EC-UTIs (p=0{middle dot}03) and all EC-UTIs (p=0{middle dot}002).\n\nInterpretationCurrent increases in EC-BSIs in Oxfordshire are primarily community-associated, with high rates of co-amoxiclav resistance, nevertheless not impacting mortality. Interventions should target primary-care facilities with high co-amoxiclav usage.\n\nFundingNational Institute for Health Research.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for publications from inception up until October 26, 2017, with the terms \"Escherichia coli\", \"E. coli\", \"bacteraemia\", \"bloodstream infection\", restricting the search to English language articles, and also reviewed references from retrieved articles. Escherichia coli (E. coli) is the most common cause of bloodstream infection, and the incidence of E. coli bloodstream infection, and particularly antibiotic-resistant infections, is increasing in the UK and internationally. Although the UK government aims to reduce healthcare-associated E. coli bloodstream infection, there is only limited evidence to inform appropriate interventions.\n\nAdded value of this studyWe investigated potential drivers for these increases in incidence by exploiting available linked electronic health records over 19 years for ~5200 patients with E. coli bloodstream infection and ~140000 with E. coli urinary tract infection, together with community antimicrobial prescribing data for the most recent six years. Our study identified several findings with significant implications for health policy and patient care: O_LIIncreases in the incidence of E. coli bloodstream infections were driven mainly by non-hospital-associated cases; however, neither patients with previous urinary tract infections nor having previously had urine specimens sent from catheters appeared to be driving the increases\nC_LIO_LICo-amoxiclav-resistant bloodstream infections rose significantly faster than co-amoxiclav-susceptible bloodstream infections, with the greatest number of co-amoxiclav-resistant bloodstream infections in 2016 being in patients discharged more than a month previously (i.e. community-associated)\nC_LIO_LIHigher co-amoxiclav use in primary care was associated with higher rates of both co-amoxiclav-resistant E. coli urinary tract infections and E. coli urinary tract infections overall, supporting drives to reduce broad-spectrum and inappropriate antibiotic use in primary care\nC_LIO_LIDespite substantial increases in co-amoxiclav-resistant bloodstream infections there was no evidence that mortality was increasing in these cases; this does not support moving to broader empiric antibiotic prescribing in hospitals (i.e. carbapenems, piperacillin-tazobactam)\nC_LI\n\nImplications of all available adviceThis suggests that government strategies to effectively reduce E. coli bloodstream infections should target community settings, as well as healthcare-associated settings. The absence of an increased mortality signal suggests that co-amoxiclav resistant E. coli infections are either being successfully treated by dual empiric therapy in severe cases (e.g. with concomitant gentamicin), can be \"rescued\" once isolate susceptibilities become available, or currently deployed phenotypic susceptibility testing breakpoints do not adequately correlate with clinical outcome.

epidemiology↗

A semi-synthetic strategy for derivatization of the violacein natural product scaffold

Natural products and their analogues are often challenging to synthesise due to their complex scaffolds and embedded functional groups. Solely relying on engineering the biosynthesis of natural products may lead to limited compound diversity. Integrating synthetic biology with synthetic chemistry allows rapid access to much more diverse portfolios of xenobiotic compounds which may accelerate the discovery of new therapeutics. As a proof-of-concept, by supplementing an Escherichia coli strain expressing the violacein biosynthesis pathway with 5-bromo-tryptophan in vitro or tryptophan 7-halogenase RebH in vivo, 6 halogenated analogues of violacein or deoxyviolacein were generated, demonstrating promiscuity of the violacein biosynthesis pathway. Furthermore, 20 new derivatives were generated from 5-brominated violacein analogues via Suzuki-Miyaura cross-coupling reaction directly using the crude extract without prior purification. Herein, we demonstrate a flexible and rapid approach to access diverse chemical space that can be applied to a wide range of natural product scaffolds.

synthetic biology↗

Terminal uridylyltransferases target RNA viruses as part of the innate immune system in animals

RNA viruses are a major threat to animals and plants. RNA interference (RNAi) and the interferon response provide innate antiviral defense against RNA viruses. Here we performed a large-scale screen using C. elegans and its natural pathogen, the Orsay virus (OrV), and identified cde-1 as important for antiviral defense. CDE-1 is a homologue of the mammalian TUT4/7 terminal uridylyltransferases; its catalytic activity is required for its antiviral function. CDE-1 uridylates the 3' end of the OrV RNA genome and promotes its degradation, independently of the RNAi pathway. Likewise, TUT4/7 uridylate influenza A virus (IAV) mRNAs in mammalian cells. Deletion of TUT4/7 leads to increased IAV mRNA and protein levels. We have defined 3' terminal uridylation of viral RNAs as a conserved antiviral defense mechanism.

immunology↗

Post-transcriptional modulation of Dscam1 enhances axonal growth in development and after injury

Injury to the adult central nervous systems (CNS) results in severe long-term disability because damaged CNS connections rarely regenerate. Although several axon regeneration regulators have been proposed, intrinsic regenerative mechanisms remain largely unexplored. Here, we use a Drosophila CNS injury model to identify a novel pro-regeneration signaling pathway. We conducted a genetic screen of approximately three hundred candidate genes and identified three strong inducers of axonal growth and regeneration: the Down Syndrome Cell Adhesion Molecule (Dscam1), the de-ubiquitinating enzyme Fat Facets (Faf)/Usp9x and the Jun N-Terminal Kinase (JNK) pathway transcription factor Kayak (Kay)/Fos. Genetic and biochemical analyses link these genes in a common signaling pathway whereby Faf stabilizes Dscam1 protein levels, by acting on the 3-UTR of its mRNA, and Dscam1 acts upstream of the growth-promoting JNK signal. The mammalian homolog of Faf, Usp9x/FAM, shares both the regenerative and Dscam1 stabilizing activities, suggesting a conserved mechanism.

neuroscience↗

Software For The Integration Of Multi-Omics Experiments In Bioconductor

Multi-omics experiments are increasingly commonplace in biomedical research, and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multi-omics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide all of the multiple omics data for each cancer tissue in The Cancer Genome Atlas (TCGA) as ready-to-analyze MultiAssayExperiment objects, and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable and reproducible statistical analysis of multi-omics data and enhances data science applications of multiple omics datasets.

bioinformatics↗

GenomicDataCommons: a Bioconductor Interface to the NCI Genomic Data Commons

The National Cancer Institute (NCI) Genomic Data Commons (Grossman et al. 2016, https://gdc.cancer.gov/) provides the cancer research community with an open and unified repository for sharing and accessing data across numerous cancer studies and projects via a high-performance data transfer and query infrastructure. The Bioconductor project (Huber et al. 2015) is an open source and open development software project built on the R statistical programming environment (R Core Team 2016). A major goal of the Bioconductor project is to facilitate the use, analysis, and comprehension of genomic data. The GenomicDataCommons Bioconductor package provides basic infrastructure for querying, accessing, and mining genomic datasets available from the GDC. We expect that Bioconductor developer and bioinformatics community will build on the GenomicDataCommons package to add higher-level functionality and expose cancer genomics data to many state-of-the-art bioinformatics methods available in Bioconductor.\n\nAvailabilityhttps://github.com/Bioconductor/GenomicDataCommons (& soon in Bioconductor).

bioinformatics↗

Accessible, curated metagenomic data through ExperimentHub

We present curatedMetagenomicData, a Bioconductor and command-line interface to thousands of metagenomic profiles from the Human Microbiome Project and other publicly available datasets, and ExperimentHub, a platform for convenient cloud-based distribution of data to the R desktop. The resource provides standardized per-participant metadata linked to bacterial, fungal, archaeal, and viral taxonomic abundances, as well as quantitative metabolic functional profiles. The datasets can be immediately analyzed in R or other software with a minimum of bioinformatic expertise and no preprocessing of data. We demonstrate identification of taxonomic/functional correlations, an investigation of gut \"enterotypes\", and a comparison of the accuracy of disease classification from different data types. These documented analyses can be reproduced efficiently on a laptop, without the barriers of working with large-scale, raw sequencing data. The building and expansion of curatedMetagenomicData is based entirely on open source software and pipelines, to facilitate the addition of new microbiome datasets and methods.

bioinformatics↗