As the world's leading cause of human gastro-enteritis, the food- and waterborne pathogen Campylobacter needs to be intensively monitored through a One Health approach. Particularly, wild birds have been hypothesized to contribute to the spread of human clinical recurring C. jejuni genotypes across several countries. A major concern in studying epidemiological dynamics is resolving the large genomic diversity of strains circulating in the environment and various reservoirs, challenging to achieve with isolation techniques. Here, we applied a passive-filtration method to obtain isolates and in parallel recovered genotypes from metagenomic sequencing data from associated filter sweeps. For genotyping mixed strains, a reference-based computational workflow to predict allelic profiles of nine extended-MLST loci was utilized. We validated the pipeline by sequencing artificial mixtures of C. jejuni strains and observed the highest prediction accuracy when including obtained isolates as references. By analyzing metagenomic samples, we were able to detect over 20% additional genetic diversity and observed an over 50% increase in the potential to connect genotypes across wild-bird samples. With an optimized filtration method and a computational approach for genotyping strain mixtures, we provide the foundation for future studies assessing C. jejuni diversity in environmental and clinical settings at improved throughput and resolution.
Keywords: Campylobacter jejuni; metagenomics; molecular epidemiology; strain typing; wild birds.