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Best Practices for the Experimental Design of One Health Studies on Companion Animal and Owner Microbiomes - From Data Collection to Analysis

Overview
Journal One Health
Date 2025 Feb 10
PMID 39925695
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Abstract

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.

References
1.
Misic A, Davis M, Tyldsley A, Hodkinson B, Tolomeo P, Hu B . The shared microbiota of humans and companion animals as evaluated from Staphylococcus carriage sites. Microbiome. 2015; 3:2. PMC: 4335418. DOI: 10.1186/s40168-014-0052-7. View

2.
Bykova N, Litovka N, Popenko A, Musienko S . Pet-Human Gut Microbiome Host Classifier Using Data from Different Studies. Microorganisms. 2020; 8(10). PMC: 7602744. DOI: 10.3390/microorganisms8101591. View

3.
Moore J, Purcaro M, Pratt H, Epstein C, Shoresh N, Adrian J . Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature. 2020; 583(7818):699-710. PMC: 7410828. DOI: 10.1038/s41586-020-2493-4. View

4.
Casals-Pascual C, Gonzalez A, Vazquez-Baeza Y, Song S, Jiang L, Knight R . Microbial Diversity in Clinical Microbiome Studies: Sample Size and Statistical Power Considerations. Gastroenterology. 2020; 158(6):1524-1528. DOI: 10.1053/j.gastro.2019.11.305. View

5.
Xia Y, Sun J . Hypothesis Testing and Statistical Analysis of Microbiome. Genes Dis. 2018; 4(3):138-148. PMC: 6128532. DOI: 10.1016/j.gendis.2017.06.001. View