bioRxivMicrobiologyPreprint
Skin lipid chemistry influences host-microbiome-pathogen interactions in snake fungal disease (ophidiomycosis)
Kaitlyn MurphyiD, Jason W. DallasiD, Mitra GhotbiiD, Lluvia Vargas‐GastélumiD, Charlotte Van MoorleghemiD, Joshua L. PhillipsiD, David W. LudwigiD, Tingting SuniD, Robert T. MasoniD, John H. Niedzwiecki, M. Rockwell ParkeriD, Jeffrey D. LeblondiD, J. Michael MilleriD, Clay Stalzer, Ori Bergman, Melinda S. Chue DonaheyiD, Marc G. ChevretteiD, Donald W Walker
Abstract
Within host-microbiome-pathogen systems, the host chemical microenvironment is often overlooked despite its inherent role in host physiology. We used a multifaceted experimental approach encompassing culture-dependent and independent methods, metagenomic and genomic data, and deep neural network modeling to assess the impact of host skin lipid chemistry and the bacterial microbiome on the growth of Ophidiomyces ophidiicola (ophidiomycosis, snake fungal disease). Results suggest that host skin lipid chemistry (e.g., oleic acid, squalene) and bacteria isolated from wild snake skins (e.g., Chryseobacterium sp. and Stenotrophomonas maltophilia) suppress O. ophidiicola growth. Notably, the O. ophidiicola genome contains biosynthetic gene clusters (BGCs) that encode metabolites that may suppress host lipid production, facilitating fungal pathogenicity. The contrastive deep neural network produced a near-perfect alignment of snake skin lipid and microbiome profiles for both individual snakes and disease states. BGCs from bacterial genomes isolated from snake skin overlap with metagenome profiles from wild snakes and correlate with disease state. We highlight antifungal activity found in the diverse lipid milieu of snake skin and bacterial-fungal interactions (BFIs) that structure the skin microbiome. Our results illustrate a strong relationship among a fungal pathogen, the microbiome, and host skin lipid chemistry.
- organism: non-human primate
- assay: metagenomics
- research focus: host-pathogen & immune response
- approach: deep learning
- Citations
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