Overcoming Challenges in Metagenomic AMR Surveillance with Nanopore Sequencing: A Case Study on Fluoroquinolone Resistance

Bram Bloemen^1,2Mathieu Gand¹Moniek Ringenier³Bert Bogaerts¹Kevin Vanneste¹Kathleen Marchal^2,4Nancy Roosens¹JEROEN DEWULF³Filip Boyen⁵Sigrid C.J. De Keersmaecker^1*

• ¹Transversal activities in Applied Genomics (TAG), Sciensano, Brussels, Belgium
• ²Department of Plant Biotechnology and Bioinformatics, Faculty of Sciences, Ghent University, Ghent, East Flanders, Belgium
• ³Department of Internal Medicine, Reproduction and Population Medicine, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
• ⁴Department of Information Technology, Faculty of Engineering and Architecture, Ghent University, Ghent, East Flanders, Belgium
• ⁵Department of Pathobiology, Pharmacology and Zoological Medicine, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Flemish Brabant, Belgium

Antimicrobial resistance is an alarming public health problem, and comprehensive surveillance across environments is required to reduce its impact. Phenotypic testing and whole-genome sequencing of isolates are efficient, but culture-free approaches like metagenomic sequencing potentially allow for broader investigation of resistance gene occurrence, evolution and spread. However, technical challenges such as difficulties in associating antimicrobial resistance genes with their bacterial hosts and the collapse of strain-level variation during metagenome assembly, hinder its implementation. To illustrate how these challenges can be overcome, we applied Oxford Nanopore Technologies long-read metagenomic sequencing to a case study focused on fluoroquinolone resistance in chicken faecal samples. We demonstrate plasmid-host linking based on detecting common DNA methylation signatures. Additionally, we use new bioinformatic approaches for strain haplotyping, enabling phylogenomic comparison and uncovering fluoroquinolone resistance determining point mutations in metagenomic datasets. Although some limitations remain, our work demonstrates how ongoing improvements in metagenomic sequencing can be used to enhance antimicrobial resistance surveillance.