Work

Development of a multiplex detection system for toxic Amanita species based on isothermal recombinase polymerase amplification and CRISPR/Cas12b technology

Year: 2026

Type: article

Abstract: Background Toxic Amanita species are a major cause of fatal mushroom poisoning worldwide. Their morphological similarities to the edible species of mushrooms increase the risk of accidental ingestion, highlighting the need for rapid and accurate identification. Objective We aimed to develop a multiplex detection system using isothermal recombinase polymerase amplification (RPA) and CRISPR/Cas12b technology for rapid and specific detection of multiple toxic Amanita species. Methods Species-specific RPA primers and single guide RNAs (sgRNAs) were designed and optimized for six toxic Amanita species ( A. exitialis , A. pallidorosea , A. subjunquillea , A. rimosa , A. molliuscula , and A. fuligineoides ). The detection system combined RPA with Cas12b-mediated fluorescence readout to evaluate the specificity and sensitivity, and the results were visualized using lateral flow strips and a microfluidic disc chip for parallel detection. Results The selected primer–sgRNA combinations showed high specificity values without cross-reactivity and a low detection limit of 10 pg of genomic DNA per reaction. The lateral flow strips enabled intuitive and reliable detection. Furthermore, the microfluidic disc chip enabled multiplex detection for both single-species and four-species mixed samples. Conclusion We successfully established a rapid, sensitive, and specific multiplex detection system for toxic Amanita species using purified genomic DNA from authenticated specimens, providing a proof-of-concept analytical strategy for informing future development of instrument–light species identification tools in mushroom poisoning cases. We also summarize the evaluations required for further optimization of the current design prior to practical application.

Source: Frontiers in Molecular Biosciences

DOI: 10.3389/fmolb.2026.1832406

Authors: Hao Li, Xinyu Ying, Zhidan Luo, Chen Lu, Ping Zhang

Institutions: Hunan Normal University, Jiangsu Ocean University

Language: English

Topic: Biosensors and Analytical Detection

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,801

Funder: National Natural Science Foundation of China