Biology subjects

Beardmore, R. E.

Publications and source records attributed to Beardmore, R. E..

5 recordsLinked to original sources

bioRxiv2025

A comprehensive AMR genotype-phenotype database (CABBAGE)

Addressing the growing threat of antimicrobial resistance (AMR) requires the development of large-scale resources that link bacterial genomic data with phenotypic antimicrobial resistance profiles. Such datasets are essential for advancing genotype-based predictions of resistance to uncover novel resistance mechanisms, as well as identifying and tracking global trends. Here, we describe the development of the Comprehensive Assessment of Bacterial-Based AMR prediction from GEnotypes (CABBAGE) database, linking bacterial genomes to associated antibiotic susceptibility data and relevant metadata across WHO Bacterial Priority Pathogens, sourced from both publications and existing databases, and curated into a format that is compatible with, and extends, both NCBI and ENA formats. The resulting CABBAGE database, comprising over 170,000 unique sequenced isolates and approximately 1.7 million genome-phenotype pairs linked to extensive metadata, represents the largest database of its kind, consolidating existing AMR phenotype-genotype data into a single unified format. CABBAGE encompasses a broad range of antimicrobials, facilitating the analysis of global resistance trends as well as benchmarks of genotype-to-phenotype predictive methods, and empowering further research uses. The database is freely accessible at https://www.ebi.ac.uk/amr and is currently being integrated with the BioSample database, enabling easy access for the AMR research community.

genomics↗

bioRxiv2020

Clinical Antibiotic Resistance Patterns Across 70 Countries

We sought global patterns of antibiotic resistant pathogenic bacteria within the AMR Research Initiative database, Atlas. This consists of 6.5M clinical minimal inhibitory concentrations (MICs) observed in 70 countries in 633k patients between 2004 and 2017. Stratifying MICs according to pathogens (P), antibiotics (A) and countries (C), we found that the frequency of resistance was higher in Atlas than other publicly available databases. We determined global MIC distributions and, after showing they are coherent between years, we predicted MIC changes for 43 pathogens and 827 pathogen-antibiotic (PAs) pairings that exhibit significant resistance dynamics, including MIC increases and even decreases. However, many MIC distributions are multi-modal and some PA pairs exhibit sudden changes in MIC. We therefore analysed Atlas after replacing the clinical classification of pathogens into susceptible, intermediate and resistant with an information-optimal, cluster-based classifier to determine subpopulations with differential resistance that we denote S and R. Accordingly, S and R clusters for different PA pairs exhibit signatures of stabilising, directional and disruptive selection because their respective MICs can have different dynamics. Finally, we discuss clinical applications of a (R, dR/dt) phase plane whereby the MIC of R is regressed against change in MIC (dR/dt), a methodology we use to detect PA pairs at risk of developing clinical resistance.

microbiology↗

bioRxiv2020

Dynamic phenotypic heterogeneity generated by delayed genetic oscillations

Eukaryotes and prokaryotes exploit the ability of genetically identical cells to exhibit different phenotypes in order to enhance their survival. However, the mechanisms by which cells transition from one phenotype to another remain unclear. Canonical models of this dynamic posit that molecular fluctuations provide the noise that drives the cell out of one stable state and into another. Stochastic processes generated by canonical models should, therefore, be good descriptors of phenotype dynamics and between-state transitions should become more likely at greater noise amplitude, for instance at higher extracellular temperatures. To test these predictions, we observed temporal expression dynamics of the promoter of a flagellum gene, fliC, in a microfluidic device using Salmonella enterica serovar Typhimurium and green fluorescent protein (GFP). Our observations show that while cells can exhibit multistable phenotypes, including stable fliC-OFF and fliC-ON states characterised by low and high GFP levels, respectively, between-state transitions can exhibit oscillatory dynamics whose return statistics do not conform to canonical theories. For example, here the fliC-ON state was more frequent following a temperature increase. To better understand our data we developed different dynamical frameworks to predict fliC expression data. We conclude that a stochastic dynamical system tailored to the genetic network of fliC is better suited to our data than prior theories where dynamical features, like oscillations and pulsing, are driven by inevitable delays in the post-translational regulation of fliC. Thus, while transcriptional noise promotes phenotypic heterogeneity, as we show here, regular features like oscillatory heterogeneity can result from delays that fundamental molecular processes impose upon a cells gene regulatory architecture.

systems biology↗

bioRxiv2019

Hotspot Dosages of Most Rapid Antibiotic Resistance Evolution

We treated Escherichia coli with the antibiotic erythromycin from zero to high dosages to determine how the evolutionary dynamics of antibiotic resistant phenotypes and genotypes depend on dose. The most rapid increase in resistance was observed just below erythromycins minimal inhibitory concentration (MIC) and genotype-phenotype correlations determined from whole genome sequencing revealed the molecular basis of this: simultaneous selection for copy number variation in 3 resistance mechanisms which shared an inverted-U pattern of dose-dependent selection with several insertion sequences and an integron. Many genes did not conform to this pattern, however, because of changes in selection as dose increased: media adaptation at zero-to-low dosages gave way to drug target (ribosomal RNA operon) amplification at mid dosages whereas prophage-mediated drug efflux dominated at higher dosages where population densities were lowest. All dosages saw E. coli amplify the efflux operons acr and emrE at rates that correlated strongly with changes in population density that exhibited an inverted-U geometry too. However, we show by example that inverted-U geometries are not a universal feature of dose-resistance relationships.

evolutionary biology↗

bioRxiv2019

Canonical host-pathogen tradeoffs subverted by mutations with dual benefits

Tradeoffs between life history traits impact diverse biological phenomena, including the maintenance of biodiversity. We sought to study two canonical tradeoffs in a model host-parasite system consisting of bacteriophage lambda and Escherichia coli: i) parasite resistance for growth and ii) phage infectivity for host-range. We report that these previously hypothesised tradeoffs are, in fact, tradeups. While the observation of tradeups was surprising, they should be expected because if traits X and Y tradeoff, so too traits Y and Z, then X and Z will tradeup. By considering five different E. coli trait correlations we uncovered several tradeups and tradeoffs. Using mathematical models, we establish that tradeups need not inhibit biodiversity, as previously thought, and can help maintain it through high-dimensional trait interactions. We provide a mechanistic explanation for how tradeups emerge and give reasons for why tradeups can even evolve in well-adapted genomes.\n\nAll data will be posted at https://github.com/rebear217 and mirrored at http://people.exeter.ac.uk/reb217/rebHomePage/data.html on acceptance.

evolutionary biology↗