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Antimicrobial-resistant bacteria are frequently isolated from retail meat and may infect humans. To determine the diversity of antimicrobial-resistant bacteria in Australian retail meat, bacteria were cultured on selective media from raw chicken (n = 244) and pork (n = 160) meat samples obtained from all four major supermarket chains in the ACT/NSW, Australia, between March and June 2021. Antimicrobial susceptibility testing (AST) was performed for 13 critically and 4 highly important antibiotics as categorised by the World Health Organization (WHO) for a wide range of species detected in the meat samples. A total of 288 isolates underwent whole-genome sequencing (WGS) to identify the presence of antimicrobial resistance (AMR) genes, virulence genes, and plasmids. AST testing revealed that 35/288 (12%) of the isolates were found to be multidrug-resistant (MDR). Using WGS data, 232/288 (81%) of the isolates were found to harbour resistance genes for critically or highly important antibiotics. This study reveals a greater diversity of AMR genes in bacteria isolated from retail meat in Australia than previous studies have shown, emphasising the importance of monitoring AMR in not only foodborne pathogenic bacteria, but other species that are capable of transferring AMR genes to pathogenic bacteria.
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INTRODUCTION: Infection causes a vast burden of disease, with significant mortality, morbidity and costs to health-care systems. However, identifying the pathogen causative infection can be challenging, resulting in high use of broad-spectrum antibiotics, much of which may be inappropriate. Novel metagenomic methods have potential to rapidly identify pathogens, however their clinical utility for many infections is currently unclear. Outcome from infection is also impacted by the effectiveness of immune responses, which can be impaired by age, co-morbidity and the infection itself. The aims of this study are twofold: To compare diversity of organisms identified and time-to-result using metagenomic methods versus traditional culture -based techniques, to explore the potential clinical role of metagenomic approaches to pathogen identification in a range of infections.To characterise the ex vivo function of immune cells from patients with acute infection, exploring host and pathogen-specific factors which may affect immune function and overall outcomes. METHODS: This is a prospective observational study of patients with acute infection. Patients with symptoms suggestive of an acute infection will be recruited, and blood and bodily fluid relevant to the site of infection collected (for example, sputum and naso-oropharyngeal swabs for respiratory tract infections, or urine for a suspected urinary tract infection). Metagenomic analysis of samples will be compared to traditional microbiology, alongside the antimicrobials received. Blood and respiratory samples such as bronchoalveolar lavage will be used to isolate immune cells and interrogate immune cell function. Where possible, similar samples will be collected from matched participants without a suspected infection to determine the impact of infection on both microbiome and immune cell function.
Assuntos
Antibacterianos , Infecções Respiratórias , Humanos , Antibacterianos/uso terapêutico , Lavagem Broncoalveolar , Projetos de Pesquisa , Infecções Respiratórias/diagnóstico , Metagenômica , Estudos Observacionais como AssuntoRESUMO
Trimethoprim is recommended as a first-line treatment of urinary tract infections (UTIs) in the UK. In 2018, 31.4% of Escherichia coli isolated from UTIs in England were trimethoprim-resistant, leading to overreliance on other first and second-line antibiotics. Here, we assessed whether, in principle, prior selection with trimethoprim results in collateral effects to other antibiotics recommended for the treatment of UTIs. As collateral effects, we considered changes in susceptibility, mutation-selection window and population establishment probability. We selected 10 trimethoprim-resistant derivatives from three clinical isolates of uropathogenic Escherichia coli. We found that mutations conferring trimethoprim resistance did not have any collateral effects on fosfomycin. In contrast, resistance to trimethoprim resulted in decreased susceptibility (collateral resistance) to nitrofurantoin, below the clinical breakpoint and narrowed the mutation-selection window, thereby reducing the maximum concentration for selection of nitrofurantoin resistance mutations. Our analyses demonstrate that multiple collateral responses should be accounted for when predicting and optimising antibiotic use, limiting future antimicrobial resistance emergence.
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Pan-genome analysis is a fundamental tool for studying bacterial genome evolution; however, the variety of methods used to define and measure the pan-genome poses challenges to the interpretation and reliability of results. To quantify sources of bias and error related to common pan-genome analysis approaches, we evaluated different approaches applied to curated collection of 151 Mycobacterium tuberculosis ( Mtb ) isolates. Mtb is characterized by its clonal evolution, absence of horizontal gene transfer, and limited accessory genome, making it an ideal test case for this study. Using a state-of-the-art graph-genome approach, we found that a majority of the structural variation observed in Mtb originates from rearrangement, deletion, and duplication of redundant nucleotide sequences. In contrast, we found that pan-genome analyses that focus on comparison of coding sequences (at the amino acid level) can yield surprisingly variable results, driven by differences in assembly quality and the softwares used. Upon closer inspection, we found that coding sequence annotation discrepancies were a major contributor to inflated Mtb accessory genome estimates. To address this, we developed panqc, a software that detects annotation discrepancies and collapses nucleotide redundancy in pan-genome estimates. When applied to Mtb and E. coli pan-genomes, panqc exposed distinct biases influenced by the genomic diversity of the population studied. Our findings underscore the need for careful methodological selection and quality control to accurately map the evolutionary dynamics of a bacterial species.