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MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats

Yi Shen1, Xinrun Yang1, Jiabao Yu1

  • 1Jiangsu Provincial Key Lab for Solid Organic Waste Utilization, Key Lab of Organic-based Fertilizers of China, Jiangsu Collaborative Innovation Center of Solid Organic Wastes, Educational Ministry Engineering Center of Resource-Saving Fertilizers, Nanjing Agricultural University, Nanjing, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|June 9, 2026
PubMed

Insights

A new Multiple Fungal Pathogen Detection (MFPD) pipeline and database accurately identify fungal pathogens using ITS sequencing. This tool enhances surveillance across human, animal, and plant health sectors.

Area of Science:

  • Mycology
  • Genomics
  • Bioinformatics

Background:

  • Fungal pathogens pose significant threats to human, animal, and plant health.
  • Current methods for fungal pathogen detection via ITS sequencing lack comprehensive databases and tailored analysis pipelines.
  • There is a need for robust tools to support broad-spectrum fungal pathogen surveillance.

Purpose of the Study:

  • To introduce the Multiple Fungal Pathogen Detection (MFPD) pipeline and its associated curated database.
  • To evaluate the accuracy and efficiency of the MFPD pipeline for identifying fungal pathogens.
  • To compare the performance of MFPD against existing fungal identification tools.

Main Methods:

  • Development of the MFPD pipeline incorporating a high-speed sequence alignment algorithm.
  • Curation of a comprehensive MFPD database with 95,660 full-length ITS sequences from 4924 fungal pathogen species.
  • In silico experiments to assess the accuracy of full-length ITS sequencing versus subregions (ITS1, ITS2).
  • Benchmarking MFPD against FUNGuild, FungalTraits, and ISHAM-ITS using mock and real-world samples.

Main Results:

  • Full-length ITS sequencing achieved the highest accuracy (average 99.34%) for fungal pathogen detection.
  • The MFPD pipeline demonstrated superior performance with the highest F1 scores (0.89) in mock communities for both plant and human-animal pathogens.
  • MFPD identified a broader spectrum of pathogenic taxa in real samples compared to existing tools.
  • The pipeline successfully detected coinfecting fungal pathogens in various biological and environmental samples.

Conclusions:

  • The MFPD pipeline and database provide an accurate and efficient solution for fungal pathogen identification.
  • Full-length ITS sequencing is optimal for maximizing accuracy in fungal pathogen detection.
  • MFPD supports enhanced pathogen surveillance across clinical, agricultural, and livestock sectors within a One Health framework.
Keywords:
ITS sequencingbioinformatics toolsfungal pathogenspathogen detection

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