Bouqellah Nahla A, Elkady Nadia A, Farag Peter F
Department of Biology, College of Science, Taibah University, P.O. Box 344, Al Madinah Al Munawwarah 42317-8599, Saudi Arabia.
Department of Microbiology, Faculty of Science, Ain Shams University, Cairo 11566, Egypt.
J Fungi (Basel). 2023 Jul 11;9(7):740. doi: 10.3390/jof9070740.
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 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 CAN1 was compared to the other two blackleg fungal species ( JN3 and CA1) secretomes and their CAZymes and effectors were identified. Orthologue analysis found that 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.
真菌分泌组是病原体与其宿主之间相互作用的主要界面。它包括最重要的毒力因子和效应蛋白。我们整合了不同的生物信息学方法,并利用油菜黑胫病菌株CAN1的新绘制基因组数据预测了217种蛋白质的分泌情况,其中包括许多细胞壁降解酶。所有分泌蛋白均被鉴定出来;85种被归类为碳水化合物活性酶家族,25种被归类为蛋白酶家族。此外,预测并鉴定出49种假定效应蛋白,其中39种具有至少一个保守结构域。根据STRING网络分析,一些果胶降解酶作为一个聚类组很引人注目。将CAN1的分泌组与其他两种黑胫病菌(JN3和CA1)的分泌组进行了比较,并鉴定了它们的碳水化合物活性酶和效应蛋白。直系同源分析发现,CAN1与其他相关物种共有14种碳水化合物活性酶效应蛋白。病原体-宿主相互作用数据库(PHI base)将效应蛋白分为几类,其中大多数蛋白被归类为毒力降低,有两种被称为毒力增强。如今,通过精心设计的生物信息学工具,计算机方法可以解决许多关于真菌与植物宿主之间致病机制的模糊问题。