MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats

Fungal pathogens threaten the health of humans, animals, and plants. ITS sequencing offers an effective approach for detecting fungal pathogens; however, a comprehensive pathogen database and associated tailored pipeline are still lacking. This study introduces the multiple fungal pathogen detection (MFPD) pipeline, which incorporates an accurate and high-speed sequence alignment algorithm for broad-habitat pathogen identification. The curated MFPD database includes 95 660 full-length ITS sequences from 4924 reported fungal pathogen species. In silico experiments show that the full-length ITS achieves the highest accuracy in pathogen detection (average 99.34%), outperforming both the ITS1 and ITS2 subregions. Benchmarking against existing tools, including FUNGuild, FungalTraits, and ISHAM-ITS, shows that MFPD achieves the highest F1 scores in mock communities (0.89 for both plant and human-animal pathogens) and detects the broadest spectrum of pathogenic taxa in real samples. In addition to identifying causal pathogens, MFPD can also detect coinfecting pathogens in biological and environmental samples. Together, our work supports pathogen surveillance across diverse sectors, including clinical, agricultural, and livestock systems within a One Health framework.

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Publication Details

Journal
Advanced Science
Published
2026-06-09
DOI
https://doi.org/10.1002/advs.202522660
Primary Topic
Fungal Infections and Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats

Xinrun Yang, Gaofei Jiang, Alexandre Jousset, Yangchun Xu et al.
Advanced Science
Fungal Infections and Studies
article

MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats

Xinrun Yang, Gaofei Jiang, Alexandre Jousset, Yangchun Xu, Tianjie Yang, Yang Gao, Waseem Raza, Xiaofang Wang, Yaozhong Zhang, Jiabao Yu, Yi Shen, Zhong Wei, Qirong Shen, Fang‐Jie Zhao
article en

Abstract

Fungal pathogens threaten the health of humans, animals, and plants. ITS sequencing offers an effective approach for detecting fungal pathogens; however, a comprehensive pathogen database and associated tailored pipeline are still lacking. This study introduces the multiple fungal pathogen detection (MFPD) pipeline, which incorporates an accurate and high-speed sequence alignment algorithm for broad-habitat pathogen identification. The curated MFPD database includes 95 660 full-length ITS sequences from 4924 reported fungal pathogen species. In silico experiments show that the full-length ITS achieves the highest accuracy in pathogen detection (average 99.34%), outperforming both the ITS1 and ITS2 subregions. Benchmarking against existing tools, including FUNGuild, FungalTraits, and ISHAM-ITS, shows that MFPD achieves the highest F1 scores in mock communities (0.89 for both plant and human-animal pathogens) and detects the broadest spectrum of pathogenic taxa in real samples. In addition to identifying causal pathogens, MFPD can also detect coinfecting pathogens in biological and environmental samples. Together, our work supports pathogen surveillance across diverse sectors, including clinical, agricultural, and livestock systems within a One Health framework.

Advanced Science
Chinese Academy of Tropical Agricultural Sciences (CN), Nanjing Agricultural University (CN), Genedata (Switzerland) (CH), Guangxi Academy of Agricultural Science (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Jiangsu Province, Fundamental Research Funds for the Central Universities
Zero hunger
Openalex Percentile: Top 7%
Fungal Infections and Studies
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