iPhyDSDB: Phytoplasma disease and symptom database

Authors: Wei, Wei; Shao, Jonathan; Zhao, Yan; Inaba, Junichi; IVANAUSKAS, ALGIRDAS - Nature Research Centre; Bottner, Kristi; Costanzo, Stefano; Kim, Bo Min; Flowers, Kailin; Escobar, Jazmin

Submitted to: Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/21/2024
Publication Date: 8/24/2024
Citation: Wei, W., Shao, J.Y., Zhao, Y., Inaba, J., Ivanauskas, A., Bottner-Parker, K.D., Costanzo, S., Kim, B., Flowers, K., Escobar, J.I. 2024. iPhyDSDB: Phytoplasma disease and symptom database. Biology. 13(9):657. https://doi.org/10.3390/biology13090657.
DOI: https://doi.org/10.3390/biology13090657

Interpretive Summary: Phytoplasmas are intracellular bacteria that infect numerous plant species, severely impacting crop yields and quality and causing significant economic losses. Early and rapid diagnosis is crucial to prevent disease spread, particularly through early symptom recognition by farmers and growers. To aid in this effort, ARS scientists in Beltsville, Maryland, retrieved nearly 35,000 phytoplasma sequences from the NCBI nucleotide database and identified almost 950 plant species associated with phytoplasma infections. Recognizing the importance of visual diagnosis, symptomatic images of these plants were manually curated to create the Phytoplasma Disease and Symptom Database (iPhyDSDB). A web-based interface was further designed to serve as a valuable resource for the agricultural community. iPhyDSDB features a collection of high-quality symptomatic images, each linked to its original source and accompanied by detailed descriptions of typical phytoplasma symptoms. Users can efficiently query the database by plant host and symptom type, making it easier to compare, identify, and diagnose phytoplasma-related diseases. This comprehensive resource not only facilitates early detection and accurate diagnosis but also enhances the overall understanding of phytoplasma infections. By providing a centralized repository of disease symptom information, the iPhyDSDB supports farmers and growers in making decisions about disease management practices. Researchers and educators also benefit from the extensive data available, which can be used to advance scientific studies and educational programs.

Technical Abstract: Phytoplasmas are small, intracellular bacteria that infect a vast range of plant species, causing significant economic losses and impacting agriculture and farmers’ livelihoods. Early and rapid diagnosis of phytoplasma infections is crucial for preventing the spread of these diseases, particularly through early symptom recognition in the field by farmers and growers. A symptom database for phytoplasma infections can assist in recognizing the symptoms and enhance early detection and management. In this study, nearly 35,000 phytoplasma sequence entries were retrieved from the NCBI nucleotide database using the keyword “phytoplasma,” and information on phytoplasma disease-associated plant hosts and symptoms was gathered. Nearly 950 plant species were identified to be associated with phytoplasma infection. Subsequently, the symptomatic images of these known susceptible plant species were manually curated, and the Phytoplasma Disease Symptom Database (iPhyDSDB) was established and implemented on a web-based interface using MySQL Server and a PHP program. One of the key features of iPhyDSDB is the collection of symptomatic images representing various phytoplasma-infected plant species. In addition, the image address links were also stored within the database, allowing users to easily access the original source of the collected images and detailed disease information. Furthermore, images and descriptive definitions of typical symptoms induced by phytoplasmas were also included in iPhyDSDB. The newly developed database and web interface, equipped with advanced search functionality, will help farmers, growers, researchers, and educators to efficiently query the database based on specific categories such as plant host and symptom type. This resource will aid the users in comparing, identifying, and diagnosing phytoplasma-related diseases, enhancing understanding and management of these infections.