Kitty F. Cardwell

Rapid and accurate detection of respiratory pathogens is essential for timely diagnosis, effective treatment, and outbreak monitoring in both human and veterinary medicine. We evaluated the Microbe Finder (MiFi ^® ) software for detection of nine RNA viruses of human and veterinary clinical importance. Species specific signature sequences in the different pathogen genomes were identified, and specific electronic probe sets were curated using the MiFi ^® software. Analytical specificity and sensitivity were evaluated through simulated metagenomes and public sequence databases, respectively. Host-specific internal control probes were designed to ensure diagnostic reliability and quality control. Diagnostic performance was assessed using Oxford Nanopore sequence data from clinical nasal swab samples. In silico validation showed 100% specificity across 83 datasets and limits of detection as low as 0.0010% of total reads (10 reads per 10 ⁶ ) for some targets. Internal controls generated stable background signals without interfering with pathogen detection. In vivo testing of 44 clinical samples matched PCR performance for Human respiratory syncytial virus (HRSV), Influenza B virus (IBV), Influenza A virus (IAV), Bovine respiratory syncytial virus (BRSV), and Canine distemper virus (CDV). These findings demonstrate that the MiFi ^® software enables rapid, multiplex, and strain-specific detection of respiratory viruses in metagenomic sequence data without the need for advanced bioinformatics expertise. The approach supports scalable use in clinical laboratories, veterinary diagnostics for surveillance and triage, offering a valuable tool for improving respiratory pathogen detection across diverse settings.

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. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Global citriculture faces significant challenges from graft-transmissible pathogens, which threaten both productivity and biosecurity. To address these challenges, citrus quarantine germplasm programs worldwide are responsible for producing and maintaining pathogen-tested tree sources to supply propagative materials for the commercial citrus industry, as well as for non-commercial uses such as research, landscaping, and public distribution. The success of these programs relies on the availability of reliable pathogen detection assays. We developed and validated a suite of electronic probes (e-probes) for Electronic Diagnostic Nucleic Acid Analysis (EDNA) to detect 20 citrus pathogens, including viroids, viruses, and bacteria, from raw high-throughput sequencing data. These e-probes were optimized using the MiFi bioinformatics platform for specificity, sensitivity, and detection limits through both in silico and in planta testing. Validation included comparisons with real-time PCR and extensive ring tests across multiple users to ensure robustness and reproducibility. The results demonstrated that EDNA consistently matched the diagnostic capabilities of conventional molecular methods, accurately identifying pathogens with high precision and enabling multiplex testing without compromising sensitivity. This innovative approach offers a scalable, efficient, and cost-effective pathogen detection tool to enhance citrus disease prevention and management and safeguard citrus germplasm at a global scale. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

To have confidence that results from diagnostic assays for plant pathogens are accurate and to identify potential problems with false negatives and false positives, it is essential that the appropriate control reactions are included in the assay design. This review discusses control reactions that, depending on the technology used, should be either run in parallel or multiplexed with the diagnostic assay to ensure accuracy. The discussion includes immunoassays such as enzyme-linked immunosorbent assay and lateral flow devices, as well as molecular diagnostic techniques including PCR, isothermal technologies (recombinant polymerase amplification and loop-mediated isothermal amplification), and high-throughput sequencing. Additional details are provided for RNA virus assays that account for the need for a control reaction during the generation of complementary DNA. Although concepts of control reaction design and the reasons for their inclusion are discussed, the reader is directed to the Diagnostic Assay Validation Network website hosted on the American Phytopathological Society website for specific examples of control reactions reported in the literature that may be useful to consider when designing new diagnostic assays. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Agricultural biosecurity, economical production, and safe trade require a reliable and extensive validated diagnostic assay testing process, which is crucial for plant health management. To support this, the United States Department of Agriculture–National Institute of Food and Agriculture (USDA–NIFA) biosecurity grant program funded the creation of the Diagnostic Assay Validation Network (DAVN) in 2022. This perspective article outlines the various activities, tools, and resources the newly developed DAVN has built since its inception to support biosecurity and enhance the science of plant disease diagnostics through validated assays. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Dichorhavirus is a recently accepted plant virus genus within the family Rhabdoviridae. Species assigned to the genus consist of bi-segmented, negative sense, single-stranded RNA viruses and are transmitted by Brevipalpus spp. Currently, there are five recognized species and two unclassified members in the genus Dichorhavirus. Four out of seven-orchid fleck virus (OFV), citrus leprosis virus N, citrus chlorotic spot virus, and citrus bright spot virus-can infect citrus and produce leprosis disease-like symptoms. The E-probe Diagnostic for Nucleic Acid Analysis (EDNA) was developed to reduce computational effort and then integrated within Microbe-Finder (MiFi^®) online platform to design and evaluate e-probes in raw High Throughput Sequencing (HTS) data. During this study, Dichorhavirus genomes were downloaded from public databases and e-probes were designed using the MiProbe incorporated into the MiFi^® platform. Three different sizes of e-probes, 40, 60, and 80 nucleotides, were developed and selected based on whole genome comparisons with near-neighbor genomes. For curation, each e-probe was searched in the NCBI nucleotide sequence database using BLASTn. All the e-probes that had hits with non-target species with ≥90% identities were removed. The sensitivity and specificity of Dichorhavirus genus, species, strain, and variant-specific e-probes were validated in vivo using HTS meta-transcriptomic libraries generated from Dichorhavirus-suspected citrus, orchid, and ornamentals. Through downstream analysis of HTS data, EDNA not only detected the known hosts of OFV but also discovered an unknown host leopard plant (Farfugium japonicum), and the possible existence of a new ornamental strain of OFV in nature.

Red leaf blotch is a severe soybean disease caused by the select agent fungal pathogen Coniothyrium glycines. With little information about the pathogen, no molecular detection methods are available. Here, we report genome assemblies of five isolates, including reference isolates. These datasets provide a valuable resource for ongoing studies that include marker development, diagnostics, and population diversity. [ ] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Introduction. With expanding demand for diagnostics, newer methodologies are needed for faster, user-friendly and multiplexed pathogen detection. Metagenome-based diagnostics offer potential solutions to address these needs as sequencing technologies have become affordable. However, the diagnostic utility of sequencing technologies is currently limited since analysis of the large amounts of data generated, are either computationally expensive or carry lower sensitivity and specificity for pathogen detection. Hypothesis/Gap Statement. There is a need for novel, user friendly, and computationally inexpensive platforms for metagenome sequence analysis for diagnostic applications. Methods. In this study, we report the use of MiFi^® (Microbe Finder), a computationally inexpensive algorithm with a user-friendly online interface, for accurate, rapid and multiplexed pathogen detection from metagenome sequence data. Detection is accomplished based on identification of signature genomic sequence segments of the target pathogen in metagenome sequence data. In this study we used bovine respiratory disease (BRD) complex as a model. Results and Conclusions. Using MiFi^®, multiple target bacteria and a DNA virus were successfully detected in a multiplex format from metagenome sequences acquired from bovine lung tissue. Overall, 51 clinical samples were assessed and MiFi^® showed 100 % analytical specificity and varying levels of analytical sensitivity (62.5 %–100 %) when compared with other traditional pathogen detection techniques, such as PCR. Consistent detection of bacteria was possible from lung samples artificially spiked with 10⁹–10⁴ c.f.u. of Mannheimia haemolytica .