Integrating In Silico and In Vitro Approaches for Detecting Coniothyrium glycines in High-Throughput Sequencing (HTS) Datasets Using EDNA-MiFi - Fernanda Proaño-Cuenca; Daniel Carrera-López; Kurt Zeller; Andrés S. Espindola; Kitty Cardwell (PhytoFrontiers, 2025)
Coniothyrium glycines causes red leaf blotch in soybeans and poses significant risk to agriculture and food security. Though it is not present in the United States, molecular data have been made available to support the development of rapid diagnostic tools. Using these genotypic data, this study used e-probe diagnostic nucleic acid analysis (EDNA) integrated with Microbe Finder (MiFi) technology to design and validate species-specific e-probes for detecting C. glycines. These e-probes, tailored for the species using genomic data from multiple C. glycines isolates as well as taxonomically important relatives, were tested using simulated metagenomic sequencing data and in vitro sample sequences. We assessed performance criteria, including analytical and diagnostic sensitivity, analytical specificity, and limit of detection, with consistent results from both in silico and in vitro experiments. The MiFi system successfully detected C. glycines with longer e-probes, demonstrating superior performance by requiring fewer reads to classify true positive metagenomes. Notably, Nanopore sequencing proved to be more efficient than Illumina sequencing, requiring fewer reads to achieve detection. Results from in silico and in vitro testing revealed that shorter e-probes exhibited higher sensitivity (fewer false negatives), whereas longer e-probes provided greater specificity (fewer false positives). The MiFi system achieved 100% diagnostic sensitivity in detecting C. glycines in metagenomes when at least 10 to 100 pg of pathogen DNA was present in the metagenomes. These findings demonstrate the potential of EDNA-MiFi as a powerful tool for pathogen detection and microbial forensics, supporting further research on its cost-effectiveness and scalability to enhance routine diagnostic practices. [Figure: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.