Metabarcoding reveals fungal community structure and presence of opportunistic pathogens in Brazilian touristic caves
Maria Eduarda Grisolia1,3, Marlon Roger Geraldo2, Ani Beatriz Jackisch Matsuura3, Flávia de Fatima Costa 4, João Lucas Vitório Ribeiro Carvalho1, Bruno Paulo Rodrigues Lustosa1, Jacques F. Meis1,5,10, Cristina Maria de Souza Motta6, Gisele C. Sessegolo7, Sybren de Hoog2,5,8#, Vania Aparecida Vicente1,2,5,9#
1Bioprocess Engineering and Biotechnology Graduate Program, Federal University of Paraná, Curitiba, PR, Brazil; 2Microbiology, Parasitology and Pathology Graduate Program, Federal University of Paraná, Curitiba, PR, Brazil; 3Institute Leonidas and Maria Deane, Fiocruz, Manaus, Brazil; 4Laboratory of Artificial Intelligence Applied to Bioinformatics and Graduate Program in Bioinformatics, SEPT, Federal University of Paraná, Curitiba, PR, Brazil; 5Centre of Expertise for Mycology of Radboud University Medical Centre / Canisius Wilhelmina Hospital, Nijmegen, The Netherlands; 6Mycology Department, Federal University of Pernambuco, Recife, Brazil; 7Ecossistema Environmental Consulting, Curitiba, Brazil; 8Foundation Atlas of Clinical Fungi, Hilversum, The Netherlands; 9Microbiological Collections of Paraná Network – CMRP/Taxonline, Federal University of Paraná, Curitiba, PR, Brazil; 10 Institute of Translational Research, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), Excellence Center for Medical Mycology (ECMM), University of Cologne, 50923 Cologne, Germany
Abstract
Caves are nutrient-limited and environmentally stable ecosystems that host specialized microbial communities. Fungal diversity in Brazilian karst systems remains poorly explored. We used ITS2 metabarcoding to characterize mycobiomes from different substrates and luminosity zones in two limestone caves in the Bonito region, Brazil: Lago Azul (LA), which receives regulated tourism, and Nossa Senhora Aparecida (NSA), closed to visitation. Across 15 samples, we recovered 1,042 ASVs assigned to 219 genera and seven fungal phyla, with Ascomycota and Basidiomycota dominating both caves. Although overall diversity was comparable, the two caves shared few genera, indicating distinct ecological conditions. Functional annotation revealed a high proportion of pathotrophic guilds, including animal, plant, and insect pathogens, reflecting strong ecological connectivity between surface inputs and subterranean environments. Notably, members of Ajellomycetaceae (Histoplasma, Emergomyces, Emmonsiellopsis) occurred primarily in shadow and aphotic sediments and guano. This study includes the first environmental detection of Emergomyces in Brazil, suggesting that subterranean habitats may act as reservoirs for dimorphic opportunistic fungi with clinical overlap with histoplasmosis. Although tourism is restricted to upper zones, airborne spores and sediment transport highlight the relevance of continued microbial monitoring. These findings advance the ecological understanding of Brazilian cave mycobiomes and support the need for integrated microbial and conservation strategies in karst environments.
#Correspondence: sybren.dehoog@radboudumc.nl
vaniava63@gmail.com
Article info:
Received 30 September 2025
Revised 10 December 2025
Accepted 15 December 2025
Appeared online 22 December 2025
One Health Mycology 2(2): 158-167, 2025
doi.org/10.63049/OHM.25.22.7
Cite this article:
Grisolia ME, Geraldo MR, Matsuura ABJ, Costa FF, Ribeiro Carvalho JLV, Lustosa BPR, Meis JF, de Souza Motta CM, Sessegolo GC, de Hoog S, Vicente VA 2025. Metabarcoding reveals fungal community structure and presence of opportunistic pathogens in Brazilian touristic caves. One Health Mycology 2(2), 158-167
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/ licenses/by-nc-nd/4.0/)
Keywords:
Metagenomics, cave microbiology, Emergomyces, Histoplasma, Lago Azul Cave
Article highlights:
- First environmental detection of Emergomyces in Brazil using ITS2 metabarcoding.
- Insights into cave fungal ecology with implications for public-health monitoring.
