Development of an Immunoassay Platform Targeting β-1,3- and β-1,6-Glucans for Rapid Detection of Fungi

Fungal infections pose diagnostic challenges in both human and veterinary medicine, as traditional detection methods such as fungal culture are time-consuming, microscopy is operator-dependent, and molecular detection assays often require specialized instrumentation and trained personnel, which can limit their routine clinical application. This study developed a sandwich immunoassay to detect β-1,3- and β-1,6-glucans, two major components of the fungal cell wall, based on two catalytically inactive glucanase mutants, LamAE175Q and Neg1E321Q. The sandwich ELISA exhibited higher detection sensitivity than conventional ITS-based PCR for Saccharomyces cerevisiae and Candida albicans under the conditions of this study. Using pre-coated plates, the sample-processing and detection workflow can be completed in approximately 40 min. It effectively detected a wide range of fungal species, including yeasts (Saccharomyces cerevisiae, Candida albicans) and filamentous fungi such as dermatophytes and non-dermatophyte molds. In a preliminary clinical cohort, the assay identified β-glucan signals in all 21 samples confirmed positive for dermatophytes, while no signal was detected in 20 negative samples, suggesting potential clinical applicability. This dual-enzyme sandwich immunoassay provides a rapid and low-cost complementary tool for broad-spectrum fungal screening, which may help guide further confirmatory diagnostics and timely clinical decision-making.

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Publication Details

Journal
Journal of Fungi
Published
2026-06-19
DOI
https://doi.org/10.3390/jof12060448
Primary Topic
Antifungal resistance and susceptibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of an Immunoassay Platform Targeting β-1,3- and β-1,6-Glucans for Rapid Detection of Fungi

Zhibo Yang, Yueping Zhang, Wenzhuang Zhu, Di Zhang et al.
Journal of Fungi
Antifungal resistance and susceptibility
article

Development of an Immunoassay Platform Targeting β-1,3- and β-1,6-Glucans for Rapid Detection of Fungi

Zhibo Yang, Yueping Zhang, Wenzhuang Zhu, Di Zhang, Wei Yuan, Zan Chen, Yingyin Gao, Changbin Jin
article en

Abstract

Fungal infections pose diagnostic challenges in both human and veterinary medicine, as traditional detection methods such as fungal culture are time-consuming, microscopy is operator-dependent, and molecular detection assays often require specialized instrumentation and trained personnel, which can limit their routine clinical application. This study developed a sandwich immunoassay to detect β-1,3- and β-1,6-glucans, two major components of the fungal cell wall, based on two catalytically inactive glucanase mutants, LamAE175Q and Neg1E321Q. The sandwich ELISA exhibited higher detection sensitivity than conventional ITS-based PCR for Saccharomyces cerevisiae and Candida albicans under the conditions of this study. Using pre-coated plates, the sample-processing and detection workflow can be completed in approximately 40 min. It effectively detected a wide range of fungal species, including yeasts (Saccharomyces cerevisiae, Candida albicans) and filamentous fungi such as dermatophytes and non-dermatophyte molds. In a preliminary clinical cohort, the assay identified β-glucan signals in all 21 samples confirmed positive for dermatophytes, while no signal was detected in 20 negative samples, suggesting potential clinical applicability. This dual-enzyme sandwich immunoassay provides a rapid and low-cost complementary tool for broad-spectrum fungal screening, which may help guide further confirmatory diagnostics and timely clinical decision-making.

Journal of FungiVol. 12(6)
China Agricultural University (CN)
National Natural Science Foundation of China
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Antifungal resistance and susceptibility
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Development of an Immunoassay Platform Targeting β-1,3- and β-1,6-Glucans for Rapid Detection of Fungi — Zhibo Yang, Yueping Zhang, et al. · Journal of Fungi (2026) | TGRS Research Map | TGRS