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Pascoe, B.

Publications and source records attributed to Pascoe, B..

24 records · Page 2Linked to original sources

Multiple clones of colistin-resistant Salmonella enterica carrying mcr-1 plasmids in meat products and patients in Northern Thailand

Salmonella spp. is an important foodborne pathogen associated with consumption of contaminated food, especially livestock products. Antimicrobial resistance (AMR) in Salmonella has been reported globally and increasing AMR in food production is a major public health issue worldwide. The objective of this study was to describe the genetic relatedness among Salmonella enterica isolates, which displayed identical DNA fingerprint profiles. Ten S. enterica isolates were selected from meat and human cases with an identical rep-PCR profile of serovars Rissen (n=4), Weltevreden (n=4), and Stanley (n=2). We used long-read whole genome sequencing (WGS) on the MinION sequencing platform to type isolates and investigate in silico the presence of specific AMR genes. Antimicrobial susceptibility testing was tested by disk diffusion and gradient diffusion method to corroborate the AMR phenotype. Multidrug resistance and resistance to more than one antimicrobial agent were observed in eight and nine isolates, respectively. Resistance to colistin with an accompanying mcr-1 gene was observed among the Salmonella isolates. The analysis of core genome and whole genome MLST revealed that the Salmonella from meat and human salmonellosis were closely genetic related. Hence, it could be concluded that meat is one of the important sources for Salmonella infection in human. HighlightsO_LIColistin resistance detected in 2 clones from 2 different Salmonella enterica serovars (Rissen and Weltevreden) with accompanying plasmid-borne mcr-1 gene from the food production chain and human clinical salmonellosis. C_LIO_LIHigh prevalence of multidrug resistant isolates and resistance to more than one antimicrobial agent. C_LIO_LIMinION has potential for mobile, rapid and accurate application in veterinary genomic epidemiology studies. C_LI

microbiology↗

Quantifying bacterial evolution in the wild: a birthday problem for Campylobacter lineages

Measuring molecular evolution in bacteria typically requires estimation of the rate at which nucleotide changes accumulate in strains sampled at different times that share a common ancestor. This approach has been useful for dating ecological and evolutionary events that coincide with the emergence of important lineages, such as outbreak strains and obligate human pathogens. However, in multi-host (niche) transmission scenarios, where the pathogen is essentially an opportunistic environmental organism, sampling is often sporadic and rarely reflects the overall population, particularly when concentrated on clinical isolates. This means that approaches that assume recent common ancestry are not applicable. Here we present a new approach to estimate the molecular clock rate in Campylobacter that draws on the popular probability conundrum known as the birthday problem. Using large genomic datasets and comparative genomic approaches, we use isolate pairs that share recent common ancestry to estimate the rate of nucleotide change for the population. Identifying synonymous and non-synonymous nucleotide changes, both within and outside of recombined regions of the genome, we quantify clock-like diversification to estimate synonymous rates of nucleotide change for the common pathogenic bacteria Campylobacter coli (2.4 x 10-6 s/s/y) and Campylobacter jejuni (3.4 x 10-6 s/s/y). Finally, using estimated total rates of nucleotide change, we infer the number of effective lineages within the sample time-frame - analogous to a shared birthdays - and assess the rate of turnover of lineages in our sample set over short evolutionary timescales. This provides a generalizable approach to calibrating rates in populations of environmental bacteria and shows that multiple lineages are maintained, implying that large-scale clonal sweeps may take hundreds of years or more in these species. Author SummaryGrowth and reproduction in living organisms require DNA replication but this process is error prone. Along with variation introduced by horizontal gene transfer, it can lead to alterations in the nucleotide sequence. These nucleotide changes accumulate over time in successive generations at an approximately constant rate termed the molecular clock. Therefore, if this rate is known, one can estimate the date when two or more lineages diverged. In bacteria, this can be informative for understanding the time-scale of emergence and spread of pathogenic strains. Such analyses are robust when the ancestral population is known, such as for obligate pathogens that only infect humans. However, when the bacterium inhabits multiple hosts or niches it is difficult to infer direct ancestry from one strain to another, reducing the accuracy of molecular clock estimates. Here we focus on one such multi-host organism, Campylobacter, a leading cause of food-borne gastroenteritis. Reconstructing the population history by estimating empirical nucleotide change rates from carefully selected isolate pairs, and evaluating the maintenance of multiple lineages over time, we provide information about strain diversification. Our method is a new addition to the bacterial genomics toolkit that will help in understanding the spread of opportunistic pathogens.

genomics↗

Hermes: an ensemble machine learning architecture for protein secondary structure prediction

MotivationProtein structure predictions, that combine theoretical chemistry and bioinformatics, are an increasingly important technique in biotechnology and biomedical research, for example in the design of novel enzymes and drugs. Here, we present a new ensemble bi-layered machine learning architecture, that directly builds on ten existing pipelines providing rapid, high accuracy, 3-State secondary structure prediction of proteins.\n\nResultsAfter training on 1348 solved protein structures, we evaluated the model with four independent datasets: JPRED4 - compiled by the authors of the successful predictor with the same name, and CASP11, CASP12 & CASP13 - assembled by the Critical Assessment of protein Structure Prediction consortium who run biannual experiments focused on objective testing of predictors. These rigorous, pre-established protocols included 7-fold cross-validation and blind testing. This led to a mean Hermes accuracy of 95.5%, significantly (p<0.05) better than the ten previously published models analysed in this paper. Furthermore, Hermes yielded a reduction in standard deviation, lower boundary outliers, and reduced dependency on solved structures of homologous proteins, as measured by NEFF score. This architecture provides advantages over other pipelines, while remaining accessible to users at any level of bioinformatics experience.\n\nAvailability and ImplementationThe source code for Hermes is freely available at: https://github.com/HermesPrediction/Hermes. This page also includes the cross-validation with corresponding models, and all training/testing data presented in this study with predictions and accuracy.

bioinformatics↗

Domestication of Campylobacter jejuni NCTC 11168

Reference and type strains of well-known bacteria have been a cornerstone of microbiology research for decades. The sharing of well-characterised isolates among laboratories has parallelised research efforts and enhanced the reproducibility of experiments, leading to a wealth of knowledge about trait variation in different species and the underlying genetics. Campylobacter jejuni strain NCTC 11168, deposited at the National Collection of Type Cultures in 1977, has been adopted widely as a reference strain by researchers worldwide and was the first Campylobacter for which the complete genome was published (in 2000). In this study, we collected 23 C. jejuni NCTC 11168 reference isolates from laboratories across the UK and compared variation in simple laboratory phenotypes with genetic variation in sequenced genomes. Putatively identical isolates identified previously to have aberrant phenotypes varied by up to 281 SNPs (in 15 genes) compared to the most recent reference strain. Isolates also display considerable phenotype variation in motility, morphology, growth at 37{degrees}C, invasion of chicken and human cell lines and susceptibility to ampicillin. This study provides evidence of ongoing evolutionary change among C. jejuni isolates as they are cultured in different laboratories and highlights the need for careful consideration of genetic variation within laboratory reference strains.\n\nImpact statementIn this paper, we comment on the changing role of laboratory reference strains. While the model organism allows basic comparison within and among laboratories, it is important to remember the effect even small differences in isolate genomes can have on the validity and reproducibility of experimental work. We quantify differences in 23 reference Campylobacter genomes and compare them with observable differences in common laboratory phenotypes.\n\nData summaryShort read data are archived on the NCBI SRA associated with BioProject accession PRJNA517467 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517467).\n\nAll assembled genomes are also available on FigShare (doi: 10.6084/m9.figshare.7849268). Phylogeny visualised on microreact: https://microreact.org/project/NCTC11168.\n\nRepositoriesShort read data are archived on the NCBI SRA repository, associated with BioProject accession PRJNA517467 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA517467; Table S1).\n\nThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗

High-resolution sweep metagenomics using ultrafast read mapping and inference

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP method for identifying and estimating the relative abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our method facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

bioinformatics↗

Epistasis mediated alleviation of the cost of antibiotic resistance for MRSA

Understanding how multi-drug resistant pathogens evolve is key to identifying means of curtailing their further emergence and dissemination. Fitness costs imposed on bacteria by resistance mechanisms are believed to hamper their dissemination in an antibiotic free environment, however, some have been reported to have little or no cost, which suggests there are few barriers preventing their global spread. One such apparently cost-free resistance mechanism acquired by the major human pathogen Staphylococcus aureus is to the clinically important antibiotic mupirocin, which is mediated by mutation of the highly-conserved and essential isoleucyl-tRNA synthethase (ileS) gene. In Genome Wide Association Studies (GWAS) on two genetically and geographically distinct MRSA lineages we have found this mutation to be associated with changes in bacterial virulence, driven through epistatic interactions with other loci. Given the potential dual effect of this mutation on both antibiotic resistance and virulence we adopted a proteomic approach and observed pleiotropic effects. This analysis revealed that the activity of the secretory apparatus of the PSM family of cytolytic toxins, the Pmt system, is affected in the mupirocin resistant mutant, which explains why it is less toxic. As an energetically costly activity, this reduction in toxicity masks the fitness costs associated with this resistance mutation, a cost that becomes apparent when toxin production is required. Given the widespread use of this antibiotic, and that this resistance often results from a single nucleotide substitution in the ileS gene, these hidden fitness costs provide an explanation for why this resistance mechanism is not more prevalent. This work also demonstrates how population-based genomic analysis of virulence and antibiotic resistance can contribute to uncovering hidden features of the biology of microbial pathogens.

microbiology↗