Mathieu Gand, Indre Navickaite, Lee-Julia Bartsch, Josephine Grützke, Søren Overballe-Petersen, Astrid Rasmussen, Saria Otani, Valeria Michelacci, Bosco Rodríguez Matamoros, Bruno González-Zorn, Michael S M Brouwer, Lisa Di Marcantonio, Bram Bloemen, Kevin Vanneste, Nancy H C J Roosens, Manal AbuOun, Sigrid C J De Keersmaecker
Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k- mer read alignment tool...
2024: Frontiers in Microbiology