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Microbe Finder (MiFi®): Implementation of an Interactive Pathogen Detection Tool in Metagenomic Sequence Data

Agricultural high throughput diagnostics need to be fast, accurate and have multiplexing capacity. Metagenomic sequencing is being widely evaluated for plant and animal diagnostics. Bioinformatic analysis of metagenomic sequence data has been a bottleneck for diagnostic analysis due to the size of the data files. Most available tools for analyzing high-throughput sequencing (HTS) data require that the user have computer coding skills and access to high-performance computing. To overcome constraints to most sequencing-based diagnostic pipelines today, we have developed Microbe Finder (MiFi®). MiFi® is a web application for quick detection and identification of known pathogen species/strains in raw, unassembled HTS metagenomic data. HTS-based diagnostic tools developed through MiFi® must pass rigorous validation, which is outlined in this manuscript. MiFi® allows researchers to collaborate in the development and validation of HTS-based diagnostic assays using MiProbe™, a platform used for developing pathogen-specific e-probes. Validated e-probes are made available to diagnosticians through MiDetect™. Here we describe the e-probe development, curation and validation process of MiFi® using grapevine pathogens as a model system. MiFi® can be used with any pathosystem and HTS platform after e-probes have been validated

Communications Ecosystem to Support the Assay Validation Community: A Concept

The ability to minimize negative economic, environmental, or productivity impacts to plant systems caused by recurrent and emerging pathogens and pests depends on the early detection and accurate identification of those pests and pathogens. New pest and pathogen populations and genotypes are being detected and reported monthly in peer-reviewed journals across the globe. Accurate and timely identification of pests and pathogens is dependent on the capability and capacity of the diagnostic laboratory. Among the important attributes for a diagnostic laboratory are the technologies and methods used and the number and types of samples that the laboratory can process. Because pathogen or pest identification informs response, accurate identification is also dependent on the reliability of the assay employed and the correct interpretation of assay results. Confidence in the test results generated, and ultimately in the identification rendered, is dependent on the design and rigor of the validation process for the assay(s) used. Well-designed and -executed validation requires access to an array of resources including positive controls, reference strains to build inclusivity and exclusivity panels, reference nucleic acid sequence databases, and fully vetted standard operating procedures. A communications ecosystem to facilitate the sharing of such resources, as well as to provide access to taxon and technology expertise, will greatly accelerate the development, validation, and reliability of trusted diagnostic tests to support plant biosecurity specifically and plant health in general. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license

Microbe Finder (MiFi^®): Implementation of an Interactive Pathogen Detection Tool in Metagenomic Sequence Data

Agricultural high throughput diagnostics need to be fast, accurate and have multiplexing capacity. Metagenomic sequencing is being widely evaluated for plant and animal diagnostics. Bioinformatic analysis of metagenomic sequence data has been a bottleneck for diagnostic analysis due to the size of the data files. Most available tools for analyzing high-throughput sequencing (HTS) data require that the user have computer coding skills and access to high-performance computing. To overcome constraints to most sequencing-based diagnostic pipelines today, we have developed Microbe Finder (MiFi®). MiFi® is a web application for quick detection and identification of known pathogen species/strains in raw, unassembled HTS metagenomic data. HTS-based diagnostic tools developed through MiFi® must pass rigorous validation, which is outlined in this manuscript. MiFi® allows researchers to collaborate in the development and validation of HTS-based diagnostic assays using MiProbe™, a platform used for developing pathogen-specific e-probes. Validated e-probes are made available to diagnosticians through MiDetect™. Here we describe the e-probe development, curation and validation process of MiFi® using grapevine pathogens as a model system. MiFi® can be used with any pathosystem and HTS platform after e-probes have been validated

TASPERT: Target-Specific Reverse Transcript Pools to Improve HTS Plant Virus Diagnostics

High-throughput sequencing (HTS) is becoming the new norm of diagnostics in plant quarantine settings. HTS can be used to detect, in theory, all pathogens present in any given sample. The technique’s success depends on various factors, including methods for sample management/preparation and suitable bioinformatic analysis. The Limit of Detection (LoD) of HTS for plant diagnostic tests can be higher than that of PCR, increasing the risk of false negatives in the case of low titer of the target pathogen. Several solutions have been suggested, particularly for RNA viruses, including rRNA depletion of the host, dsRNA, and siRNA extractions, which increase the relative pathogen titer in a metagenomic sample. However, these solutions are costly and time-consuming. Here we present a faster and cost-effective alternative method with lower HTS-LoD similar to or lower than PCR. The technique is called TArget-SPecific Reverse Transcript (TASPERT) pool. It relies on pathogen-specific reverse primers, targeting all RNA viruses of interest, pooled and used in double-stranded cDNA synthesis. These reverse primers enrich the sample for only pathogens of interest. Evidence on how TASPERT is significantly superior to oligodT, random 6-mer, and 20-mer in generating metagenomic libraries containing the pathogen of interest is presented in this proof of concept

The Need and a Vision for a Diagnostic Assay Validation Network

Plant biosecurity depends heavily on early detection of biological pest and disease threats and accurate diagnosis of causal agents. The information from these activities is disseminated and communicated with decision makers to promote effective mitigation. In the United States, most land-grant university, state, and private diagnostic and expert pest identifier labs are successfully networked via the U.S. Department of Agriculture Animal Plant Health Inspection Service, Plant Protection and Quarantine (USDA APHIS PPQ; https://www.aphis.usda.gov/), the National Plant Diagnostic Network (NPDN; https://www.npdn.org), and the National Clean Plant Network (NCPN; https://www.nationalcleanplantnetwork.org/). These organizations provide access to training, shared protocols, and standardized communications. For example, the NPDN has secure communications tools that network leadership built into its IT infrastructure and deploys a formal communications process and protocol for regulatory and high-risk samples. Additionally, the diagnostic networks adopt protocols from regulatory organizations such as the USDA-APHIS, European and Mediterranean Plant Protection Organization (EPPO), North American Plant Protection Organization (NAPPO), and other international and national plant protection organizations (NPPOs). However, plant health diagnosticians also need access to validated protocols for endemic and nonregulated organisms. Although there is strong networking of diagnostic laboratories, plant disease diagnostic assay development and validation are siloed, representing a critical gap in our biosecurity infrastructure, especially for new or emerging pathogens. Most assays are developed in independent research labs and then chosen independently by the end-use laboratory. Assay developers, those who provide reference materials, labs that can provide ring testing for validation, and assay end users could be connected and integrated for more streamlined operations. Terminology and validation protocols need to be standardized within the United States and harmonized with our trade partners to ensure understanding. The ideal would be availability of standard, taxon-specific validation protocols, essential reference materials, and appropriate control materials for use to quickly develop and deploy assays in emergencies, as well as for day-to-day testing. This perspective article provides a summary of principles of assay validation, fitness-for-purpose concepts, and the need for continuous evaluation of assay performances. We describe the existing capacity and resources needed to efficiently develop, validate, and use diagnostic tests, as well as the inefficiencies and resource shortfalls currently faced. We propose development of a Diagnostic Assay Validation Network (DAVN) system to coordinate resources at the national level and harmonize with our partners at the international level. Here, we outline a project to set up the DAVN with the objectives of standardizing terminology and statistics and facilitating location of reference materials used in diagnostic assay development and validation via a portal of tools designed by and for the plant disease research and extension community. Although many of the concepts are also relevant to insects and other pests, the focus of this article is primarily plant pathogens. [Graphic: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license

Inferring the presence of aflatoxin-producing Aspergillus flavus strains using RNA sequencing and electronic probes as a transcriptomic screening tool.

E-probe Diagnostic for Nucleic acid Analysis (EDNA) is a bioinformatic tool originally developed to detect plant pathogens in metagenomic databases. However, enhancements made to EDNA increased its capacity to conduct hypothesis directed detection of specific gene targets present in transcriptomic databases. To target specific pathogenicity factors used by the pathogen to infect its host or other targets of interest, e-probes need to be developed for transcripts related to that function. In this study, EDNA transcriptomics (EDNAtran) was developed to detect the expression of genes related to aflatoxin production at the transcriptomic level. E-probes were designed from genes up-regulated during A. flavus aflatoxin production. EDNAtran detected gene transcripts related to aflatoxin production in a transcriptomic database from corn, where aflatoxin was produced. The results were significantly different from e-probes being used in the transcriptomic database where aflatoxin was not produced (atoxigenic AF36 strain and toxigenic AF70 in Potato Dextrose Broth)