Campylobacter and associated organisms on retail chicken – using metagenomics to investigate the potential of utilising co-resident microbes for pathogen control

Abstract Background Campylobacter is the leading cause of bacterial gastroenteritis, with retail chicken meat representing a major source of infection. Campylobacter isolation from retail meat can be difficult due to the complex growth requirements of the organism. Metagenomic sequencing may be a useful alternative approach for the direct identification of pathogens like Campylobacter from food samples, while also allowing characterisation of the overall sample microbiome. Results Here, metagenomes of 58 retail chicken samples cultured for Campylobacter were assessed. Campylobacter relative abundance within the metagenome reads varied between samples (0.00086-0.47%), with overlap between culture positive and negative samples. Characterisation of Campylobacter to sequence type (ST) level was possible in one sample. There were no significant differences in alpha or beta diversity of taxa between the Campylobacter culture positive and negative samples, and individual differentially abundant taxa were not identified using ALDEx2 based on Benjamini-Hochberg adjusted Wilcoxon p-values. Preliminary analysis of metabolic reaction relative abundances indicated that several individual reactions differed in abundance between the Campylobacter culture positive and negative samples. However, these were found to not be statistically significant following multiple testing correction, nor through beta diversity and ALDEx2 analysis. Differences in taxa diversity metrics between chicken sample cuts and types were observed, which may be relevant for associations with Campylobacter but a larger study is required to investigate this fully. Conclusions Metagenomic analysis of the retail chicken meat microbiome indicates that the identification of Campylobacter and microbial signatures associated with Campylobacter presence and absence on retail chicken meat is difficult, at least with current methods. Alternatively, such signatures may be absent altogether. While the small sample size in this study may have restricted our ability to identify important taxa or metabolic reactions, we outline an approach that future studies can use to investigate differences in microbial communities.