Wildlife disease surveillance and monitoring poses unique challenges when assessing rates of population vaccination, immunity, or infection prevalence. Non-invasively detected biomarkers can help reduce risk to both animal and field personnel during wildlife disease management activities. In this study, we investigated the utility of fecal microbiome data collected from captive striped skunks (Mephitis mephitis) in predicting rabies virus vaccination and infection status. We sequenced the hypervariable region 4 (V4) of the bacterial 16S gene and estimated alpha and beta diversity across timepoints in three groups of skunks: vaccination then rabies virus infection, sham vaccination then rabies virus infection, and rabies virus infected without vaccination. Alpha diversity did not differ among treatment groups but beta diversity between treatments was statistically significant. The phyla Firmicutes and Proteobacteria were dominant among all samples. Using Random Forests, we identified operational taxonomic units (OTUs) that greatly influenced classification of fecal samples into treatment groups. Each of these OTUs was correlated with fecal volatile organic compounds detected from the samples for companion treatment groups in another study. This research is the first to highlight striped skunk microbiome biodiversity as a vaccination biomarker which pushes the frontier on alternative methods for surveillance and monitoring of vaccination and disease in wildlife populations.
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