The identification of fungal pathogens in formalin-fixed paraffin-embedded (FFPE) tissues is an unmet need in human and animal medicine, and sequence-agnostic approaches are needed to identify emerging pathogens. Eleven FFPE biopsy specimens with etiologic diagnoses of fungal disease based on standard testing of paired fresh tissue samples were utilized here to evaluate metabarcoding approaches. The cases included tissues from three dogs, three cats, one box turtle, one goat, one common loon, and one gray tree frog. The diagnoses from the fresh tissues in these cases were Microsporum canis, Penicillium sp., Exophiala sp. (likely E. jeanselmei), Verticillium sp., Rhizopus sp., atypical Cryptococcus neoformans, Conidiobolus spp., Aspergillus fumigatus, Cryptococcus neoformans var grubii, Batrachochytrium dendrobatidis, Fusarium solani, Blastomyces dermatitidis, Coccidiodes immitis, and Histoplasma capsulatum. We compared the ITS1 and 28S D1 rRNA gene genetic markers in combination with several bioinformatic strategies to identify fungal pathogens in the FFPE tissue samples, with a success rate of 9/11. These methods could allow diagnosticians who receive only FFPE tissues and see fungal pathogens to speciate the pathogens and could be of value in retrospective studies wherein FFPE tissue is the only archived tissue. Furthermore, these techniques could be of use to researchers investigating polymicrobial communities where DNA preservation is suboptimal.
