Rapid identification of Sporothrix brasiliensis by MALDI-TOF MS directly from clinical cultures in an Amazonian epidemic setting.

Authors

Daniel Dos Santos Caldas, Gabriel Silas Marinho de Sousa, Pedro Henrique Oliveira Favacho, Rodrigo Santos de Oliveira, Elaine Patrícia Tavares do Espírito Santo, Silvia Helena Marques da Silva

Published in

Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]. Volume 57. Issue 1. Jul 01, 2026. Epub Jul 01, 2026.

Abstract

Sporotrichosis caused by Sporothrix brasiliensis is a highly virulent zoonotic mycosis rapidly expanding in Brazil, with increasing records in Pará since 2018. The reference diagnosis relies on culture and the time-consuming induction of fungal dimorphism, which delays taxonomic confirmation for weeks. The objective of the study was to develop and validate an in-house spectral library by MALDI-TOF MS for the rapid identification of S. brasiliensis in the Amazon region of Pará, prioritizing the feasibility of direct identification from the filamentous phase (primary growth). Thirty-seven Main Spectral Profiles (MSPs) from regional isolates were created, with 24 derived from the yeast phase and 13 from the filamentous phase. For validation, 46 molecularly characterized isolates were used in both filamentous and yeast-like morphologies, followed by the application of 39 routine clinical isolates obtained from primary culture. The library achieved 100% accuracy (score ≥ 2.0) in species identification for both fungal phases. Notably, all 39 routine clinical isolates were correctly identified directly from the filamentous growth, reducing the diagnostic time to an interval of 5 to 7 days. Although the yeast phase presented superior scores and greater proteomic stability, the mycelial signature proved robust for clinical use. The customized library overcomes the gaps in commercial databases and establishes a high-throughput workflow for the surveillance of S. brasiliensis. This technical optimization allows for more agile One Health surveillance, which is essential for epidemiological mapping and the control of zoonotic expansion in the region.

PMID:
42384273
Bibliographic data and abstract were imported from PubMed on 01 Jul 2026.

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