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Microbiome Insights Into Zoonotic Risk at Wildlife-Human Interfaces in a Transitioning Landscape in Thailand
Pauline Van Leeuwen1,2, Chuanpot Thinphovong3, Vincent Sluydts1
1Evolutionary Ecology Group, University of Antwerp, Antwerpen, Belgium.
Abstract:
Land-use change is accelerating worldwide and is one of the strongest predictors of emerging zoonotic disease. These ecological transitions can disrupt host microbiomes, change pathogen carriage, and create novel opportunities for spillover at wildlife-livestock-human interfaces. Yet, little is known about how reforested landscapes influence microbiome diversity and the distribution of zoonotic bacteria in key reservoir hosts such as bats, rodents, treeshrews, and domestic dogs. We characterized the rectal microbiome of bats, rodents, and domestic dogs sampled across a land-use gradient in Nan Province, Thailand, spanning caves, forests, reforested zones, plantations, and village habitats. Full-length 16S rRNA sequencing was used to assess host- and habitat-specific patterns at the bacteria species level. Pathogen-associated taxa were identified, and their potential transmission pathways were explored using network analysis and qPCR validation targeting Salmonella spp. From 102 samples, 1816 taxa were identified, including 354 documented human pathogens. Hierarchical Modeling of Species Communities models confirmed that host species explained far more variation in pathogen occurrences than habitat type, with dogs, Menetes berdmorei, and Scotophilus heathii exhibiting particularly high pathogen diversity. Domestic dogs also displayed high network centrality and move freely across habitats, positioning them as a key bridging host. Salmonella screening detected both Salmonella enterica (serovars Newport/Typhimurium) and the reptile-associated Salmonella bongori, the latter unexpectedly in bats and rodents, with variable concordance between metabarcoding and qPCR results. Our findings demonstrate that host identity, more than habitat type, structures pathogen-associated microbiomes across a reforested landscape. Understanding these dynamics is essential to anticipate pathogen flow and strengthen One Health surveillance.
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