Twindemic Threats of Weeds Coinfected with Tomato Yellow Leaf Curl Virus and Tomato Spotted Wilt Virus as Viral Reservoirs in Tomato Greenhouses.

Tomato yellow leaf curl virus (TYLCV) and tomato spotted wilt virus (TSWV) are well-known examples of the begomovirus and orthotospovirus genera, respectively. These viruses cause significant economic damage to tomato crops worldwide. Weeds play an important role in the ongoing presence and spread of several plant viruses, such as TYLCV and TSWV, and are recognized as reservoirs for these infections. This work applies a comprehensive approach, encompassing field surveys and molecular techniques, to acquire an in-depth understanding of the interactions between viruses and their weed hosts. A total of 60 tomato samples exhibiting typical symptoms of TYLCV and TSWV were collected from a tomato greenhouse farm in Nonsan, South Korea. In addition, 130 samples of 16 different weed species in the immediate surroundings of the greenhouse were collected for viral detection. PCR and reverse transcription-PCR methodologies and specific primers for TYLCV and TSWV were used, which showed that 15 tomato samples were coinfected by both viruses. Interestingly, both viruses were also detected in perennial weeds, such as Rumex crispus, which highlights their function as viral reservoirs. Our study provides significant insights into the co-occurrence of TYLCV and TSWV in weed reservoirs, and their subsequent transmission under tomato greenhouse conditions. This project builds long-term strategies for integrated pest management to prevent and manage simultaneous virus outbreaks, known as twindemics, in agricultural systems.

Insights into the Differential Composition of Stem-Loop Structures of Nanoviruses and Their Impacts.

Multipartite viruses package their genomic segments independently and mainly infect plants; few of them target animals. Nanoviridae is a family of multipartite single-stranded DNA (ssDNA) plant viruses that individually encapsidate ssDNAs of ~1 kb and transmit them through aphids without replication in aphid vectors, thereby causing important diseases in host plants, mainly leguminous crops. All of these components constitute an open reading frame to perform a specific role in nanovirus infection. All segments contain conserved inverted repeat sequences, potentially forming a stem-loop structure and a conserved nonanucleotide, TAGTATTAC, within a common region. This study investigated the variations in the stem-loop structure of nanovirus segments and their impact using molecular dynamics (MD) simulations and wet lab approaches. Although the accuracy of MD simulations is limited by force field approximations and simulation time scale, explicit solvent MD simulations were successfully used to analyze the important aspects of the stem-loop structure. This study involves the mutants' design, based on the variations in the stem-loop region and construction of infectious clones, followed by their inoculation and expression analysis, based on nanosecond dynamics of the stem-loop structure. The original stem-loop structures showed more conformational stability than mutant stem-loop structures. The mutant structures were expected to alter the neck region of the stem-loop by adding and switching nucleotides. Changes in conformational stability are suggested expression variations of the stem-loop structures found in host plants with nanovirus infection. However, our results can be a starting point for further structural and functional analysis of nanovirus infection. IMPORTANCE Nanoviruses comprise multiple segments, each with a single open reading frame to perform a specific function and an intergenic region with a conserved stem-loop region. The genome expression of a nanovirus has been an intriguing area but is still poorly understood. We attempted to investigate the variations in the stem-loop structure of nanovirus segments and their impact on viral expression. Our results show that the stem-loop composition is essential in controlling the virus segments' expression level.

An Effective Integrated Machine Learning Framework for Identifying Severity of Tomato Yellow Leaf Curl Virus and Their Experimental Validation.

Tomato yellow leaf curl virus (TYLCV) dispersed across different countries, specifically to subtropical regions, associated with more severe symptoms. Since TYLCV was first isolated in 1931, it has been a menace to tomato industrial production worldwide over the past century. Three groups were newly isolated from TYLCV-resistant tomatoes in 2022; however, their functions are unknown. The development of machine learning (ML)-based models using characterized sequences and evaluating blind predictions is one of the major challenges in interdisciplinary research. The purpose of this study was to develop an integrated computational framework for the accurate identification of symptoms (mild or severe) based on TYLCV sequences (isolated in Korea). For the development of the framework, we first extracted 11 different feature encodings and hybrid features from the training data and then explored 8 different classifiers and developed their respective prediction models by using randomized 10-fold cross-validation. Subsequently, we carried out a systematic evaluation of these 96 developed models and selected the top 90 models, whose predicted class labels were combined and considered as reduced features. On the basis of these features, a multilayer perceptron was applied and developed the final prediction model (IML-TYLCVs). We conducted blind prediction on 3 groups using IML-TYLCVs, and the results indicated that 2 groups were severe and 1 group was mild. Furthermore, we confirmed the prediction with virus-challenging experiments of tomato plant phenotypes using infectious clones from 3 groups. Plant virologists and plant breeding professionals can access the user-friendly online IML-TYLCVs web server at https://balalab-skku.org/IML-TYLCVs, which can guide them in developing new protection strategies for newly emerging viruses.