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    Home > Food News > Food Articles > Portable systems for rapid diagnosis of crop fungal diseases | BMC Biology

    Portable systems for rapid diagnosis of crop fungal diseases | BMC Biology

    • Last Update: 2021-03-16
    • Source: Internet
    • Author: User
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    Title: MARPLE, a point-of-care, strain-level disease diagnostics and surveillance tool for complex fungal pathogens
    Journal:
    Guru V. Radhakrishnan, Nicola M. Cook, . . . Diane G. O. Saunders
    Published: 2019/08/13
    DOI:
    WeChat Link:
    Plant Pests and Diseases Are Major Issues for Global Agriculture and Food Security. Early warning systems are critical to the preparation and fight against plant pests, and rapid diagnostic tools are essential. However, the current diagnosis of fungal diseases at strain levels is still lengthy and not straightforward. Dave Hodson and Diane Saunders discussed a recent study they published on
    that developed a mobile Real-Time Plant Disease (Mobile And Real-Time Plant DisEase, MARPLE) system. In a shared share, they explain how the system makes it possible to quickly diagnose fungal diseases based on field genes, especially wheat yellow rust, which is at strain level.Plant pests and diseases are a major threat to global food security and, if left unpelled, threaten to destroy entire crops. It is estimated that stopping the spread of fungal diseases in the top five food crops alone can feed more than 600 million people. Wheat is one of the world's top five crops, and it is under increasing threat, with wheat rust caused by fungal pathogens being one of the most worrying problems.
    , crops in less developed countries are most at risk of large-scale losses because of the lack of access to effective diagnostic tests and control measures. Just like treating human diseases, if you see obvious symptoms but are unsure of the cause, how can you take the right treatment? And that's where genome-based diagnosis and disease surveillance can play a role. In particular, for countries with fewer relevant resources, identifying precise strains of pathogens and ensuring that the most appropriate control measures are in place contribute to the more informed use of limited resources.in clinical laboratories, researchers often unlock the complete genetic code of human disease pathogens to aid in disease diagnosis. Since the launch of the first portable genome sequencer in 2015, the diagnosis and monitoring of this genomic level has now been carried out precisely at the site of an outbreak, no matter how uninhabitable the environment. This technological innovation revolutionized the speed of diagnosis, created real-time genomic information about the rate at which pathogen strains evolved, and helped map their transmission path.These initial studies focused on viral pathogens, but in fact, real-time genomic level diagnosis of fungal diseases is also critical and urgently needed. Unfortunately, using such diagnostic strategies for fungi is not easy. Fungal genomes are often tens of thousands of times longer than viruses and often cannot be isolated from host plants. We can't just sequence infected leaves that contain fungi and (quite a considerable) host plant genome, because it would be very expensive based on current technology. We need a different approach.we decided to use a method called targeted resequencing, which is often used to test specific human diseases. The focus of this approach is to analyze the genetic code of a small number of genes that can provide information about specific conditions. This targeted approach significantly reduces the amount of data generated per sample, thereby reducing the associated costs.
    a recent study published in
    , we focused on the wheat yellow rust fungal pathogen (Puccinia striiformis f.sp. tritici). We first identified genes that exhibit high variability in the DNA code between pathogen strains, and then used this small number of genes for targeted resequencing. This allows us to quickly identify specific strains in infected leaf samples. The new system, called Mobile And Real-time Plant DisEase, is also ideal for sudden disease events because it generates detailed data on yellow rust pathogen strains in the field within 48 hours of collecting samples.Ethiopia is the largest wheat producer in sub-Saharan Africa, but it is also the gateway to Africa for new wheat yellow rust pathogen strains and is therefore the highest priority country for implementing rapid diagnostic programmes. Wheat yellow rust continues to plague wheat production in Ethiopia and has led to a large-scale plant epidemic. For example, in 2010, 600,000 hectares of wheat were affected, with an estimated loss of more than $250 million, and new pathogen strains are at high risk of another pandemic.
    after such large-scale destruction, Ethiopia has developed an integrated early warning system for wheat rust to prevent future catastrophic losses. However, using the current common method, it is not possible to determine the exact line of pathogens in real time in farmers' fields. MARPLE is designed to fill this gap.
    in collaboration with the Ethiopian Agricultural Research Institute (EIAR), we have developed a mobile laboratory system that is housed in a separate box and does not require additional infrastructure or high levels of expertise to operate. In September 2018, we successfully commissioned the optimized MARPLE system in Ethiopia. As a testament to its robustness and mobility, we also operated the system directly in the trunk of a land cruiser in the field, demonstrating the feasibility of operating without continuous power supply or any additional laboratory equipment.Our partnership between John Innes Centre and CIMMYT also allows data generated directly from this approach to be used in early warning systems and control recommendation systems. The integration of the project currently makes Ethiopia a world leader in the diagnosis and prediction of wheat rust pathogens.the gene panels we developed for resequencing are also very flexible and can easily accommodate additional genes as needed. Currently, we are integrating genes that encode proteins that are considered conservative fungicide targets in fungal pathogens. This will allow for real-time mutation monitoring, thus reminding us of the ability to adjust the effectiveness of this yellow rust pathogen's fungicide. The MARPLE system provides a traceable picture of removable, genome-based, strain-level diagnostics and can be easily applied to other complex fungal pathogens that continue to threaten global food security.Effective disease management depends on timely and accurate diagnosis to guide control measures. The capacity to distinguish between individuals in a pathogen population with specific properties such as fungicide resistance, toxin production and virulence profiles is often essential to inform disease management approaches. The genomics revolution has led to technologies that can rapidly produce high-resolution genotypic information to define individual variants of a pathogen species. However, their application to complex fungal pathogens has remained limited due to the frequent inability to culture these pathogens in the absence of their host and their large genome sizes.Here, we describe the development of Mobile And Real-time PLant disEase (MARPLE) diagnostics, a portable, genomics-based, point-of-care approach specifically tailored to identify individual strains of complex fungal plant pathogens. We used targeted sequencing to overcome limitations associated with the size of fungal genomes and their often obligately biotrophic nature. Focusing on the wheat yellow rust pathogen, Puccinia striiformis f.sp. tritici (Pst), we demonstrate that our approach can be used to rapidly define individual strains, assign strains to distinct genetic lineages that have been shown to correlate tightly with their virulence profiles and monitor genes of importance.MARPLE diagnostics enables rapid identification of individual pathogen strains and has the potential to monitor those with specific properties such as fungicide resistance directly from field-collected infected plant tissue in situ. Generating results within 48 h of field sampling, this new strategy has far-reaching investments for tracking plant health
    (Source: Science.com)
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