Biomedical subjects

Velushka Swart

Publications and source records attributed to Velushka Swart.

2 recordsLinked to original sources

PubMed2025

Small RNAs derived from avocado sunblotch viroid and their association with bleaching symptoms: implications for pathogenesis in avocado sunblotch disease.

Avocado sunblotch viroid (ASBVd) is a structured RNA molecule responsible for sunblotch disease of avocado, characterised by distinct chloroses of fruit, leaves, and stems. Despite its impact on avocado, the mechanism by which ASBVd elicits sunblotch symptoms remains unknown. Previous studies on other avsunviroids have shown that viroid-derived small RNAs (vd-sRNAs) with specific sequence mutations can trigger leaf chlorosis via RNA silencing of host genes. Building on this knowledge, we aimed to shed light on the molecular basis of ASBVd pathogenesis by analysing ASBVd sequence variants and ASBVd-sRNAs from bleached and asymptomatic leaf tissues of sunblotch-affected avocado trees. Sequencing of ASBVd clones revealed that variants carrying the pathogenic determinant for bleaching were present in both green and yellow leaf tissues. Next-generation sequencing (NGS) identified ASBVd-sRNAs that varied in abundance between symptomatic and asymptomatic leaf tissues, correlating with viroid titre. We discovered 64 vd-sRNAs spanning the pathogenic region of the ASBVd genome, which were almost exclusively found in yellow tissues. The ASBVd-sRNAs containing the bleaching-associated mutation were predicted to target numerous avocado transcripts for degradation, with 25 of these transcripts significantly downregulated in bleached tissues. Notably, one of these genes, encoding a chloroplastic protein, demonstrated strong evidence of ASBVd-sRNA-guided RNA silencing, presenting a promising candidate for future research into the molecular trigger for ASBVd-induced bleaching symptoms. This study is the first to investigate ASBVd-sRNAs in bleached leaves using NGS. Our findings support the role of RNA silencing in sunblotch symptom development and reveal a unique silencing trigger compared to other avsunviroids.

Persea↗

PubMed2025

In silico prediction method for plant Nucleotide-binding leucine-rich repeat- and pathogen effector interactions.

Plant Nucleotide-binding leucine-rich repeat (NLR) proteins play a crucial role in effector recognition and activation of Effector triggered immunity following pathogen infection. Genome sequencing advancements have led to the identification of a myriad of NLRs in numerous agriculturally important plant species. However, deciphering which NLRs recognize specific pathogen effectors remains challenging. Predicting NLR-effector interactions in silico will provide a more targeted approach for experimental validation, critical for elucidating function, and advancing our understanding of NLR-triggered immunity. In this study, NLR-effector protein complex structures were predicted using AlphaFold2-Multimer for all experimentally validated NLR-effector interactions reported in literature. Binding affinities- and energies were predicted using 97 machine learning models from Area-Affinity. We show that AlphaFold2-Multimer predicted structures have acceptable accuracy and can be used to investigate NLR-effector interactions in silico. Binding affinities for 58 NLR-effector complexes ranged between -8.5 and -10.6 log(K), and binding energies between -11.8 and -14.4 kcal/mol-1, depending on the Area-Affinity model used. For 2427 "forced" NLR-effector complexes, these estimates showed larger variability, enabling identification of novel NLR-effector interactions with 99% accuracy using an Ensemble machine learning model. The narrow range of binding energies- and affinities for "true" interactions suggest a specific change in Gibbs free energy, and thus conformational change, is required for NLR activation. This is the first study to provide a method for predicting NLR-effector interactions, applicable to all pathosystems. Finally, the NLR-Effector Interaction Classification (NEIC) resource can streamline research efforts by identifying NLRs important for plant-pathogen resistance, advancing our understanding of plant immunity.

Plant Proteins↗