Biology subjects

Knight, G. M.

Publications and source records attributed to Knight, G. M..

6 recordsLinked to original sources

bioRxiv2026

AMRgen: an R package for antimicrobial resistance genotype-phenotype analysis

Microbial whole-genome sequence data is now generated at scale, including to support antimicrobial resistance (AMR) surveillance and understand resistance mechanisms, yet analytical infrastructure for systematically linking AMR genotypes to measured phenotypes remains fragmented. Here we present AMRgen, an R package to support systematic AMR genotype-phenotype analysis. AMRgen imports and harmonises genotypic data from common bioinformatics tools, alongside phenotypic data from automated antimicrobial susceptibility testing instruments and public repositories. It supports common analyses linking data to reference distributions, modelling associations, quantifying concordance, and producing publication-ready visualisations including UpSet plots that jointly display genotypic marker combination frequencies and associated phenotypic distributions. We demonstrate AMRgens utility using publicly available surveillance data for World Health Organization priority AMR pathogens, Neisseria gonorrhoeae, Klebsiella pneumoniae, Escherichia coli and Salmonella enterica. AMRgen, available free and open-source at https://AMRgen.org, provides a reproducible end-to-end foundation for genotype-phenotype research in AMR genomics, clinical microbiology, and public health surveillance.

microbiology↗

bioRxiv2025

Barriers to Antimicrobial Resistance Gene Exchange in Methicillin Resistant Staphylococcus aureus Cluster into Transfer Islands

Horizontal gene transfer (HGT) via generalised transduction is a major driver of antimicrobial resistance (AMR) in Staphylococcus aureus, yet the genetic barriers regulating phage-mediated transfer remain poorly defined. Using a co-culture gene transfer rate assay (COGTRA) that quantifies phage-dependent resistance gene exchange under competitive, antibiotic-free conditions, we screened 1,920 mutants from the Nebraska Transposon Mutant Library for elevated transfer. We identified 32 validated high-transfer mutants that act as HGT barriers, 66% of which clustered within two chromosomal regions that we term S. aureus Transfer Islands (SauTI1 and SauTI2). SauTI loci restricted generalised transduction bidirectionally, and SauTI1 genes were widespread across S. aureus genomes yet showed lineage-specific variation. SauTI1 encodes an SMC2-Cbf1 condensin-nuclease module whose disruption markedly increases generalised transduction and plasmid transfer, resembling Wadjet-like restriction systems. Together, these findings identify clustered defence loci that restrict HGT in S. aureus and identify SauTIs as key regulators of AMR evolution.

genetics↗

bioRxiv2022

Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: killers and drivers of resistance evolution

Bacteriophage (phage) are bacterial predators that can also spread antimicrobial resistance (AMR) genes between bacteria by generalised transduction. Phage are often present alongside antibiotics in the environment, yet evidence of their joint killing effect on bacteria is conflicted, and the dynamics of transduction in such systems are unknown. Here, we combine in vitro data and mathematical modelling to identify conditions where phage and antibiotics act in synergy to remove bacteria or drive AMR evolution. We adapt a published model of phage-bacteria dynamics, including transduction, to add the pharmacodynamics of erythromycin and tetracycline, parameterised from new in vitro data. We simulate a system where two strains of Staphylococcus aureus are present at stationary phase, each carrying either an erythromycin or tetracycline resistance gene, and where multidrug-resistant bacteria can be generated by transduction only. We determine rates of bacterial clearance and multidrug-resistant bacteria appearance, when either or both antibiotics and phage are present at varying timings and concentrations. Although phage and antibiotics act in synergy to kill bacteria, by reducing bacterial growth antibiotics reduce phage production. A low concentration of phage introduced shortly after antibiotics fails to replicate and exert a strong killing pressure on bacteria, instead generating multidrug-resistant bacteria by transduction which are then selected for by the antibiotics. Multidrug-resistant bacteria numbers were highest when antibiotics and phage were introduced simultaneously. The interaction between phage and antibiotics leads to a trade-off between a slower clearing rate of bacteria (if antibiotics are added before phage), and a higher risk of multidrug-resistance evolution (if phage are added before antibiotics), exacerbated by low concentrations of phage or antibiotics. Our results form hypotheses to guide future experimental and clinical work on the impact of phage on AMR evolution, notably for studies of phage therapy which should investigate varying timings and concentrations of phage and antibiotics. AUTHOR SUMMARYBacteriophage ("phage") are viruses that can infect and kill bacteria, but also natural drivers of antimicrobial resistance (AMR) evolution by transduction, when they carry non-phage DNA between bacteria, including AMR genes. Phage are often present alongside antibiotics in the environment and in humans, yet the joint dynamics of phage, antibiotics, and bacteria are unclear. Using laboratory work and mathematical modelling, we show for the first time that depending on timing and concentration, phage and antibiotics can either work together to kill bacteria faster, or phage can generate multidrug-resistant bacteria by transduction which are then selected for by antibiotics. This may be particularly important in the context of phage therapy, where phage are used to treat bacterial infections, often alongside antibiotics. Our conclusions highlight the urgent need for clinical and laboratory work to quantify the currently unknown contribution of phage to AMR evolution in humans. Otherwise, we may be missing opportunities to reduce the global public health burden of AMR.

microbiology↗

bioRxiv2021

The dual nature of bacteriophage: growth-dependent predation and generalised transduction of antimicrobial resistance

Bacteriophage ("phage") are both predators and evolutionary drivers for bacteria, notably contributing to the spread of antimicrobial resistance (AMR) genes by generalised transduction. Our current understanding of the dual nature of this relationship is limited. We used an interdisciplinary approach to quantify how these interacting dynamics can lead to the evolution of multi-drug resistant bacteria. We co-cultured two strains of Methicillin-resistant Staphylococcus aureus, each harbouring a different antibiotic resistance gene, with 80 generalized transducing phage. After a growth phase of 8h, bacteria and phage surprisingly coexisted at a stable equilibrium in our culture, the level of which was dependent on the starting concentration of phage. We detected double-resistant bacteria as early as 7h, indicating that transduction of AMR genes had occurred. We developed multiple mathematical models of the bacteria and phage relationship, and found that phage-bacteria dynamics were best captured by a model in which the phage burst size decreases as the bacteria population reaches stationary phase, and where phage predation is frequency-dependent. We estimated that one in every 108 new phage generated was a transducing phage carrying an AMR gene, and that double-resistant bacteria were always predominantly generated by transduction rather than by growth. Our results suggest a shift in how we understand and model phage-bacteria dynamics. Although rates of generalised transduction could be interpreted as too rare to be significant, they are sufficient to consistently lead to the evolution of multi-drug resistant bacteria. Currently, the potential of phage to contribute to the growing burden of AMR is likely underestimated.

microbiology↗

bioRxiv2017

The relative fitness of drug resistant Mycobacterium tuberculosis: a modelling study of household transmission in Lima, Peru

The relative fitness of drug resistant versus susceptible bacteria in an environment dictates resistance prevalence. Estimates for the relative fitness of resistant Mycobacterium tuberculosis (Mtb) strains are highly heterogeneous and mostly derived from in-vitro experiments. Measuring fitness in the field allows us to determine how the environment influences resistance spread.\n\nWe designed a household structured, stochastic mathematical model to estimate the fitness costs associated with multi-drug resistance (MDR) carriage in Mtb in Lima, Peru between 2010-2013. By fitting the model to data from a large prospective cohort study of TB disease in household contacts we estimated the fitness, relative to susceptible strains with a fitness of 1, of MDR-Mtb to be 0.33 (95% credible interval: 0.17-0.54) or 0.39 (0.26-0.58), if only transmission or progression to disease, respectively, was affected. The relative fitness of MDR-Mtb increased to 0.57 (0.43-0.73) when the fitness cost influenced both transmission and progression to disease equally.\n\nWe found the average relative fitness of MDR-Mtb circulating within households in Lima, Peru between 2010-2013 to be significantly lower than concurrent susceptible-Mtb. If these fitness levels do not change, then existing TB control programmes are likely to keep MDR-TB prevalence at current levels in Lima, Peru.

epidemiology↗

bioRxiv2017

A National Estimate of the Health and Cost Burden of Escherichia coli Bacteraemia in the Hospital Setting: The Importance of Antibiotic Resistance.

BackgroundAntibiotic resistance poses a threat to public health and a burden to healthcare systems. Escherichia coli causes more bacteraemia cases in England than any other bacterial species, these infections, in part due to their high incidence, also pose a significant antibiotic resistance burden. The main aim of this study was to estimate the impact of E. coli bacteraemia on patient in-hospital mortality and length of stay. Secondarily, this study also aimed to estimate the effect of antibiotic resistance on these outcomes.\n\nMethods and FindingsCase patients were adult E. coli bacteraemia patients infected between July 2011 and June 2012, as reported in an English national mandatory surveillance database, with susceptibility data taken from a national laboratory surveillance database. Control patients were all non-case, adult patients with an English hospital admission record. Case and control patient characteristics and admission information were taken from NHS Digital Datasets. Resistance was defined as non-susceptible and intermediate isolates, whilst susceptible was defined as susceptible and non-tested isolates. Time to in-hospital mortality and discharge was investigated through Cox proportional hazards models. To acquire estimates of excess length of stay, multistate models were constructed, with a unit bed day cost applied to estimate cost burden. The total number of case and control hospital spells was 14,051 and 8,919,275 respectively. Acquisition of E. coli bacteraemia was associated with a statistically significant increased daily risk of in-hospital mortality, especially for the first eight days of someones hospital admission [Hazard Ratio = 2.77 (95% confidence interval; 2.61-2.94)]. Antibiotic resistance did not seem to significantly increase this risk further, though did significantly reduce risk of experiencing a discharge event (dead or alive). E.coli bacteraemia was estimated to cost {pound}14,340,900 over the study period (rounded to the nearest {pound}100), with resistance associated with excess costs per infection of {pound}220 - {pound}420 dependent on resistance type, for those where a significant impact was found (rounded to the nearest {pound}10).\n\nConclusionsE. coli bacteraemia places a significant burden on patient health and on the hospital sector in England. Resistance is an important factor on length of stay with regards to such infections.

epidemiology↗