Secretome Analysis for a New Strain of the Blackleg Fungus Plenodomus lingam Reveals Candidate Proteins for Effectors and Virulence Factors.

Autor: Bouqellah NA; Department of Biology, College of Science, Taibah University, P.O. Box 344, Al Madinah Al Munawwarah 42317-8599, Saudi Arabia., Elkady NA; Department of Microbiology, Faculty of Science, Ain Shams University, Cairo 11566, Egypt., Farag PF; Department of Microbiology, Faculty of Science, Ain Shams University, Cairo 11566, Egypt.
Jazyk: angličtina
Zdroj: Journal of fungi (Basel, Switzerland) [J Fungi (Basel)] 2023 Jul 11; Vol. 9 (7). Date of Electronic Publication: 2023 Jul 11.
DOI: 10.3390/jof9070740
Abstrakt: The fungal secretome is the main interface for interactions between the pathogen and its host. It includes the most important virulence factors and effector proteins. We integrated different bioinformatic approaches and used the newly drafted genome data of P. lingam isolate CAN1 (blackleg of rapeseed fungus) to predict the secretion of 217 proteins, including many cell-wall-degrading enzymes. All secretory proteins were identified; 85 were classified as CAZyme families and 25 were classified as protease families. Moreover, 49 putative effectors were predicted and identified, where 39 of them possessed at least one conserved domain. Some pectin-degrading enzymes were noticeable as a clustering group according to STRING web analysis. The secretome of P. lingam CAN1 was compared to the other two blackleg fungal species ( P. lingam JN3 and P. biglobosus CA1) secretomes and their CAZymes and effectors were identified. Orthologue analysis found that P. lingam CAN1 shared 14 CAZy effectors with other related species. The Pathogen-Host Interaction database (PHI base) classified the effector proteins in several categories where most proteins were assigned as reduced virulence and two of them termed as hypervirulence. Nowadays, in silico approaches can solve many ambiguous issues about the mechanism of pathogenicity between fungi and plant host with well-designed bioinformatics tools.
Databáze: MEDLINE
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