Biology subjects

Kay, G. L.

Publications and source records attributed to Kay, G. L..

5 recordsLinked to original sources

bioRxiv2025

Plasticity in a bacterial global regulatory switch that drives a shift in antibiotic resistance and virulence

Antibiotic resistance and expression of virulence factors can impact the outcome of infection by Pseudomonas aeruginosa. Pathogenesis is often modelled using the P. aeruginosa PAO1 reference strain but laboratory lineages vary in the sequence and activity of MexT, a global regulator impacting virulence, biofilm formation and ciprofloxacin resistance. We defined the impact of active versus inactive MexT in PAO1 and observed global transcriptomic changes affecting the expression of 900 genes. Phenotyping revealed altered metabolism, antibiotic resistance and virulence - resulting in striking variation across a single model organism. We propose that antibiotic-resistance, introduced during work with the original PAO1 strain, has caused plasticity in mexT that accounts for variation across lineages. To test this, we introduced antibiotic resistance into clinical P. aeruginosa isolates and observed downstream mutations in mexT when selective pressure was removed, supporting the proposed evolutionary pathway. Overall, we have demonstrated the transcriptomic basis of MexT as a phenotypic switch in PAO1 and implicated antibiotic resistance as a cause of downstream changes in mexT in P. aeruginosa. Furthermore, MexS/MexT-regulated efflux is implicated in the antibiotic stress response and virulence, helping identify the mechanisms for rapid phenotypic switching through mexT and confirming that PAO1 is a very different organism compared to most isolates. Improved understanding of the regulatory changes linked to antibiotic resistance is particularly relevant to P. aeruginosa where cycles of antibiotic treatment are common.

microbiology↗

bioRxiv2025

Detection of Paracoccus yeei in Spontaneous Bacterial Peritonitis using Rapid, Long Read Sequencing

Ascites is a common complication in patients with decompensated liver cirrhosis. Spontaneous bacterial peritonitis (SBP) is the most frequent infection, affecting up to 30% of hospitalized patients with ascites. Multidrug-resistant bacteria in patients with liver cirrhosis are becoming more common, particularly in nosocomial infections. With early detection and adequate antibiotic therapy, the mortality rate of SBP can be reduced from over 90% to 15-20%. However, the etiologic agent remains undetected by conventional pathogen diagnostics from ascites in more than half of the patients. Here, we describe a robust workflow combining long read metagenome sequencing with best practices for low microbial biomass sample processing and bioinformatic analytics, to detect and characterize pathogens from the cirrhotic ascites of SBP patients, as a complement to routine microbiological diagnostics. This approach identified Paracoccus yeei as a likely etiologic agent for a patient who developed a fever after successful treatment of an Escherichia coli infection. Analysis of the genome of P. yeei recovered directly from ascites delineated pathogenicity-related features and an antimicrobial resistance profile consistent with the patients treatment. Pangenome phylogenetics placed the P. yeei strain closest to isolates associated with abdominal infections. Our study underscores the utility of metagenomics for a rapid and comprehensive assessment of infectious agents, suggesting a novel and rarely reported pathogen contributing to SBP with potential implications for diagnostics and therapeutic strategies. ImportanceOur study demonstrates the clinical utility of real-time, long-read metagenomics in identifying elusive pathogens in Spontaneous Bacterial Peritonitis (SBP), a condition with high mortality and frequently inconclusive conventional diagnostics. By uncovering Paracoccus yeei as a likely secondary etiologic agent and characterizing its pathogenicity and AMR profile, our findings expand the known etiology of SBP and emphasize the potential of metagenomics to improve diagnostic accuracy, guide targeted treatment, and ultimately reduce mortality rates in infectious diseases. This approach could shape future clinical practice for managing complex infections.

microbiology↗

bioRxiv2021

Linking carbohydrate structure with function in the human gut microbiome using hybrid metagenome assemblies

BackgroundComplex carbohydrates that escape digestion in the small intestine, are broken down in the large intestine by enzymes encoded by the gut microbiome. This is a symbiotic relationship between particular microbes and the host, resulting in metabolic products that influence host gut health and are exploited by other microbes. However, the role of carbohydrate structure in directing microbiota community composition and the succession of carbohydrate-degrading microbes is not fully understood. Here we take the approach of combining data from long and short read sequencing allowing recovery of large numbers of high quality genomes, from which we can predict carbohydrate degrading functions, and impact of carbohydrate on microbial communities. ResultsIn this study we evaluate species-level compositional variation within a single microbiome in response to six structurally distinct carbohydrates in a controlled model gut using hybrid metagenome assemblies. We identified 509 high-quality metagenome-assembled genomes (MAGs) belonging to ten bacterial classes and 28 bacterial families. We found dynamic variations in the microbiome amongst carbohydrate treatments, and over time. Using these data, the MAGs were characterised as primary (0h to 6h) and secondary degraders (12h to 24h). Annotating the MAGs with the Carbohydrate Active Enzyme (CAZyme) database we are able to identify species which are enriched through time and have the potential to actively degrade carbohydrate substrates. ConclusionsRecent advances in sequencing technology allowed us to identify significant unexplored diversity amongst starch degrading species in the human gut microbiota including CAZyme profiles and complete MAGs. We have identified changes in microbial community composition in response to structurally distinct carbohydrate substrates, which can be directly related to the CAZyme complement of the enriched MAGs. Through this approach, we have identified a number of species which have not previously been implicated in starch degradation, but which have the potential to play an important role.

microbiology↗

bioRxiv2020

CoronaHiT: large scale multiplexing of SARS-CoV-2 genomes using Nanopore sequencing

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 96 samples at a time. There is a need, however, for a flexible, platform agnostic, method that can provide multiple throughput options depending on changing requirements as the pandemic peaks and troughs. Here we present CoronaHiT, a method capable of multiplexing up to 96 small genomes on a single MinION flowcell or >384 genomes on Illumina NextSeq, using transposase mediated addition of adapters and PCR based addition of barcodes to ARTIC PCR products. We demonstrate the method by sequencing 95 and 59 SARS-CoV-2 genomes for routine and rapid outbreak response runs, respectively, on Nanopore and Illumina platforms and compare to the standard ARTIC LoCost nanopore method. Of the 154 samples sequenced using the three approaches, genomes with [≥] 90% coverage (GISAID criteria) were generated for 64.3% of samples for ARTIC LoCost, 71.4% for CoronaHiT-ONT, and 76.6% for CoronaHiT-Illumina and have almost identical clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 96 SARS-CoV-2 genomes per MinION flowcell and that Illumina sequencing can be performed on the same libraries, which will allow significantly higher throughput. CoronaHiT provides increased coverage for higher Ct samples, thereby increasing the number of high quality genomes that pass the GISAID QC threshold. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.

genomics↗

bioRxiv2018

Rapid Diagnosis of Lower Respiratory Infection using Nanopore-based Clinical Metagenomics

Lower respiratory infections (LRIs) accounted for three million deaths worldwide in 2016, the leading infectious cause of mortality. The \"gold standard\" for investigation of bacterial LRIs is culture, which has poor sensitivity and is too slow to guide early antibiotic therapy. Metagenomic sequencing potentially could replace culture, providing rapid, sensitive and comprehensive results. We developed a metagenomics pipeline for the investigation of bacterial LRIs using saponin-based host DNA depletion combined with rapid nanopore sequencing. The first iteration of the pipeline was tested on respiratory samples from 40 patients. It was then refined to reduce turnaround and increase sensitivity, before testing a further 41 samples. The refined method was 96.6% concordant with culture for detection of pathogens and could accurately detect resistance genes with a turnaround time of six hours. This study demonstrates that nanopore metagenomics can rapidly and accurately characterise bacterial LRIs when combined with efficient human DNA depletion.

microbiology↗