Location: Molecular Plant Pathology Laboratory
Project Number: 8042-22000-319-001-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 15, 2022
End Date: Sep 14, 2025
The goal of this agreement is to enhance research through collaborations that utilize sample collection followed by next-generation sequencing and bioinformatics technologies as tools for identification of citrus leprosis viruses/strains and their insect vectors in order to develop diagnostic methods for use in protecting US agriculture from the introduction of these diseases. Determination of host range of Brevipalpus transmitted viruses (BTVs) associated with Citrus leprosis disease complex in Colombia and identification of Brevipalpus sp. involved in the transmission. Sub-objectives: • Detection of CiLVs and its strains in citrus and novel host plants using RT-PCR, RT-qPCR and High Throughput Sequencing (HTS) technology. • Detection and identification of BTVs inside the Brevipalpus spp. using RT-PCR, RT-qPCR and HTS. • Application of artificial intelligence (AI) method for the detection of BTVs associated with citrus leprosis-like symptoms in Colombia.
Different species and strains of CiLV are present in diverse hosts and its vector Brevipalpus spp., in Colombia. Brevipalpus transmitted virus (BTV) suspected host samples will be collected from citrus-producing regions in Colombia, including the Atlantic coast (Magdalena state), north-east (Boyacá and Santander states), center (Cundinamarca and Tolima states), central coffee-growing region (Antioquia, Caldas, and Valle del Cauca states), south (Nariño state) and East plains (Casanare and Meta states). To establish the host ranges of cile- and dichorha-viruses, plants belonging to the multiple families showing any BTV like-symptoms will be collected and sent to the USDA-ARS-MPPL under APHIS-PPQ permit number P526P-21-04658 and will store in a freezer for future use. In addition, Brevipalpus mites from leprosis free and leprosis affected citrus groves will be imported for testing. Application of conventional and real-time RT-PCR will be applied to know Brevipalpus species are carrying any leprosis related cile- and dichorha-virus sequences. An optimized High-Throughput Sequencing (HTS)-Ribo-Zero protocol developed in our laboratory will be followed for the identification of novel hosts of CiLVs and the viruses present inside the Brevipalpus spp. An image database for citrus leprosis diseases has been created since 2012. Citrus leprosis infected leaf and fruit samples were collected from North, South and Central Americas (Panama, Costa Rica, Belize, Brazil, Colombia, Argentina, Mexico) and from Hawaii and South Africa. A machine learning approach with convolutional neural networks will be developed to detect and differentiate citrus leprosis disease-like symptoms associated with BTVs and Brevipalpus mite infection. The CiLVs positive sample received from Colombia will be confirmed by HTS. Same sample will be validated by submitting images to the model as unknowns and asking the model to estimate the probability of positive or negative for the presence of CiLVs. Similarly, after determining the Brevipalpus sp. Taxonomy associated with BTVs transmission, all the images will be captured and preserved for development of a machine learning method for flat mite species identification.