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Rofael, S.

Publications and source records attributed to Rofael, S..

2 recordsLinked to original sources

Characterising the microbial and antimicrobial resistance signatures of hospital-acquired pneumonia using nanopore metagenomic sequencing

Hospital-acquired pneumonia (HAP) is a significant burden in nosocomial settings, yet its microbial underpinnings remain poorly understood. Here, we leverage shotgun nanopore sequencing to characterise the respiratory microbiomes of 250 HAP patients in a UK multi-site cohort, validating these using paired PCR and culture assays. Sequencing identified the dominant microbes implicated in HAP, including detection of probable pathogens in 49 PCR- and culture-negative cases. We found a high prevalence of fungi in 81/239 (34%) in HAP patients, of whom 26/81 (32%) were PCR/culture-negative, suggesting that fungi may represent an under-investigated component of HAP, whether as colonists or pathogens. Although HAP is clinically sub-categorised based on the use and duration of ventilation before disease onset, we found that the microbial profiles of these sub-groups were indistinguishable. We also found a concerningly high proportion of multi-drug-resistant microbes in HAP patients, with 21% of assembled bacterial genomes harbouring acquired antimicrobial resistance (AMR) genes that confer resistance to at least three classes of antimicrobials. This included high AMR gene carriage associated to Staphylococcus epidermidis, which may be an important reservoir of AMR, though typically viewed as a commensal. Our work provides extensive metagenomic characterisation of HAP, underscores the value of metagenomics in describing its complex aetiology, and further prompts its potential role for pathogen detection, resistance profiling and treatment.

microbiology↗

A metagenomic approach to One Health surveillance of antimicrobial resistance in a UK veterinary centre

IntroductionThere are currently no standardised guidelines for genomic surveillance of One Health (OH) antimicrobial resistance (AMR). This project aimed to utilise metagenomics to identify AMR genes present in a companion animal hospital and compare these with phenotypic results from bacterial isolates from clinical specimens from the same veterinary hospital. MethodsSamples were collected from sites around a primary companion animal veterinary hospital in North London. Metagenomic DNA was sequenced using Oxford Nanopore Technologies (ONT) MinION. The sequencing data were analysed for AMR genes, plasmids and clinically relevant pathogen species. These data were compared to phenotypic speciation and antibiotic susceptibility tests (ASTs) of bacteria isolates from patients. ResultsThe most common resistance genes identified were aph (n=101 times genes were isolated across 48 metagenomic samples), sul (84), blaCARB (63), tet (58) and blaTEM (46). In clinical isolates, a high proportion of phenotypic resistance to the {beta}-lactams was identified. Rooms with the greatest mean number of resistance genes identified per swab site were the medical preparation room, dog ward and surgical preparation room. Twenty-four Gram-positive and four enterobacterial plasmids were identified. Sequencing reads matched with 14/22 (64%) of the phenotypically isolated bacterial species. DiscussionMetagenomics identified AMR genes, plasmids and species of relevance to human and animal medicine. Communal animal-handling areas harboured more AMR genes than areas animals did not frequent. When considering infection prevention and control (IPC) measures, adherence to, and frequency of, cleaning schedules, alongside potentially more comprehensive disinfection of animal-handling areas may reduce the number of potentially harmful bacteria present. PubMed "veterinary" or "companion" AND "AMR" or "resistan*" NOT (Review[Publication Type]) (2018-2023) "veterinary" or "companion" AND "AMR" or "resist*" AND "sequencing" or "metagenomic*" "veterinary" or "companion" AND "AMR" or "resistan*" NOT (Review[Publication Type]) (2018-2023) https://www.iscaid.org/clinical-practice

genomics↗