Best practices for the experimental design of one health studies on companion animal and owner microbiomes – From data collection to analysis

The relationship between owner and companion animal represents an underestimated opportunity for the studying of One Health relationships between humans, animals, and the environment they share. Microbiome exchanges between owner and pet have been documented for the gut, skin, oral, and nasal microbiomes. These studies give a unique insight into bacterial flows between humans and animals, but come with their specific challenges. This review discusses the data and sample collection challenges, as well as laboratory, bioinformatic and data analysis challenges specific to One Health studies on companion animal and owner microbiomes. We provide an overview of possible data to be collected and pitfalls to avoid during sample collection and conservation, DNA extraction, and library preparation. We present the main bioinformatics pipelines in sequencing-data microbiome analysis, as well as data analysis specific to pet-owner microbiome comparison. We review and compare three beta-diversity measures (Bray-Curtis dissimilarity, unweighted, and weighted UniFrac distances) for pet-owner distances and the tests to compare them. Finally, we propose a framework with key considerations to bear in mind when designing and carrying out owner-companion animal studies, as well as best practices to implement them. Although these studies come with additional difficulties compared to species-specific microbiome studies, they offer the opportunity to identify biomarkers, environmental triggers, and impacts of pet-owner interactions across species. [Display omitted] •Studies on pet and owner microbiome give unique insights on human-animal interactions.•Investigation of pet-owner interactions can benefit from the guidelines here outlined.•These studies bear specific challenges in data collection, preparation, and analysis.•Defining the obstacles faced in these One Health studies can help further studies.