The characterization of RNA-binding proteins and RNA metabolism-related proteins in fungal extracellular vesicles

Autor: Marianna Dallastella, Willian Klassen de Oliveira, Marcio L. Rodrigues, Samuel Goldenberg, Lysangela R. Alves
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Frontiers in Cellular and Infection Microbiology, Vol 13 (2023)
Druh dokumentu: article
ISSN: 2235-2988
DOI: 10.3389/fcimb.2023.1247329
Popis: RNA-binding proteins (RBPs) are essential for regulating RNA metabolism, stability, and translation within cells. Recent studies have shown that RBPs are not restricted to intracellular functions and can be found in extracellular vesicles (EVs) in different mammalian cells. EVs released by fungi contain a variety of proteins involved in RNA metabolism. These include RNA helicases, which play essential roles in RNA synthesis, folding, and degradation. Aminoacyl-tRNA synthetases, responsible for acetylating tRNA molecules, are also enriched in EVs, suggesting a possible link between these enzymes and tRNA fragments detected in EVs. Proteins with canonical RNA-binding domains interact with proteins and RNA, such as the RNA Recognition Motif (RRM), Zinc finger, and hnRNP K-homology (KH) domains. Polyadenylate-binding protein (PABP) plays a critical role in the regulation of gene expression by binding the poly(A) tail of messenger RNA (mRNA) and facilitating its translation, stability, and localization, making it a key factor in post-transcriptional control of gene expression. The presence of proteins related to the RNA life cycle in EVs from different fungal species suggests a conserved mechanism of EV cargo packing. Various models have been proposed for selecting RNA molecules for release into EVs. Still, the actual loading processes are unknown, and further molecular characterization of these proteins may provide insight into the mechanism of RNA sorting into EVs. This work reviews the current knowledge of RBPs and proteins related to RNA metabolism in EVs derived from distinct fungi species, and presents an analysis of proteomic datasets through GO term and orthology analysis, Our investigation identified orthologous proteins in fungal EVs on different fungal species.
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