Targeting of plasmodesmal proteins requires unconventional signals

• Autores: Robles Luna, Gabriel; Li, Jiefu; Wang, Xu; Liao, Li; Jung-Youn Lee
• Año de publicación: 2023
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Plasmodesmata; Targeting signal; virus movement; Machine learning
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Effective cellular signaling relies on precise spatial localization and dynamic interactions among proteins in specific subcellular compartments or niches, such as cell-to-cell contact sites and junctions. In plants, endogenous and pathogenic proteins gained the ability to target plasmodesmata, membrane-lined cytoplasmic connections, through evolution to regulate or exploit cellular signaling across cell wall boundaries. For example, the receptor-like membrane protein PLASMODESMATA-LOCATED PROTEIN 5 (PDLP5), a potent regulator of plasmodesmal permeability, generates feed-forward or feed-back signals important for plant immunity and root development. However, the molecular features that determine the plasmodesmal association of PDLP5 or other proteins remain largely unknown, and no protein motifs have been identified as plasmodesmal targeting signals. Here, we developed an approach combining custom-built machine-learning algorithms and targeted mutagenesis to examine PDLP5 in Arabidopsis thaliana and Nicotiana benthamiana. We report that PDLP5 and its closely related proteins carry unconventional targeting signals consisting of short stretches of amino acids. PDLP5 contains two divergent, tandemly arranged signals, either of which is sufficient for localization and biological function in regulating viral movement through plasmodesmata. Notably, plasmodesmal targeting signals exhibit little sequence conservation but are located similarly proximal to the membrane. These features appear to be a common theme in plasmodesmal targeting.
Fil: Robles Luna, Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Biotecnología y Biología Molecular. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Biotecnología y Biología Molecular; Argentina
Fil: Li, Jiefu. University of Delaware; Estados Unidos
Fil: Wang, Xu. University of Delaware; Estados Unidos
Fil: Liao, Li. University of Delaware; Estados Unidos
Fil: Jung-Youn Lee. University of Delaware; Estados Unidos