A new article describing a rapid, sequencing-based approach for the identification of bacterial infections and prediction of antimicrobial resistance has attracted media attention. Our recent publication in Microbial Genomics, titled “Rapid metagenomic sequencing for diagnosis and antimicrobial sensitivity prediction of canine bacterial infections” and part of the Implementation of Genomics in Clinical and Public Health Microbiology collection, outlines a method for the metagenomic extraction of DNA from canine urine or skin swab samples, followed by whole genome nanopore sequencing. The DNA can be used to identify which bacteria were present in the original sample, as well as to identify genes and mutations predictive of antimicrobial resistance. This work was led by postdoc Natalie Ring in collaboration with a variety of researchers at the Roslin Institute and vets at the Royal (Dick) School of Veterinary Studies. We now hope to use this method for real in the Hospital for Small Animals, as well as expanding it to other sample types and animals. The work was picked up for publication by a number of veterinary media sources, including the Vet Times, VNonline, Vet Community and MRCVS online.AbstractAntimicrobial resistance is a major threat to human and animal health. There is an urgent need to ensure that antimicrobials are used appropriately to limit the emergence and impact of resistance. In the human and veterinary healthcare setting, traditional culture and antimicrobial sensitivity testing typically requires 48–72 h to identify appropriate antibiotics for treatment. In the meantime, broad-spectrum antimicrobials are often used, which may be ineffective or impact non-target commensal bacteria. Here, we present a rapid, culture-free, diagnostics pipeline, involving metagenomic nanopore sequencing directly from clinical urine and skin samples of dogs. We have planned this pipeline to be versatile and easily implementable in a clinical setting, with the potential for future adaptation to different sample types and animals. Using our approach, we can identify the bacterial pathogen present within 5 h, in some cases detecting species which are difficult to culture. For urine samples, we can predict antibiotic sensitivity with up to 95 % accuracy. Skin swabs usually have lower bacterial abundance and higher host DNA, confounding antibiotic sensitivity prediction; an additional host depletion step will likely be required during the processing of these, and other types of samples with high levels of host cell contamination. In summary, our pipeline represents an important step towards the design of individually tailored veterinary treatment plans on the same day as presentation, facilitating the effective use of antibiotics and promoting better antimicrobial stewardship.Link: https://doi.org/10.1099/mgen.0.001066Full citationRing, N., Low, A.S., Wee, B., Paterson, G.K., Nuttall, T., Gally, D., Mellanby, R. and Fitzgerald, J.R. Rapid metagenomic sequencing for diagnosis and antimicrobial sensitivity prediction of canine bacterial infections. Microbial Genomics 9, 7 (2023).
