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为了更好地研究樟疫霉的致病机制及防治方法,笔者基于病原菌效应分子具有的典型特征,利用Signal P、Prot Comp、TMHMM、big-PI Fungal Predictor和Target P等生物信息学预测程序对樟疫霉中328 457条蛋白质序列进行候选效应分子找寻,发现该菌含有3 439个小分子分泌蛋白,同时,对上述蛋白进行冗余性、半胱氨酸数量以及信号肽长度等性质进行分析。结果表明:上述分泌蛋白中存在较多的冗余性蛋白,所占比例为50%以上,并以含有1~10个半胱氨酸、17~26个氨基酸信号肽的分泌蛋白居多。另外,利用卵菌中效应分子所具有的保守基序RXLR,对拥有唯一氨基酸序列的1 549个分泌蛋白进行基序找寻,明确樟疫霉中存在160个候选效应分子。通过上述生物信息学分析方法可实现樟疫霉候选效应分子的预测。
In order to better study the pathogenesis and control methods of P. jasminoides, we used the bioinformatics prediction programs SignalP, Prot Comp, TMHMM, big-PI Fungal Predictor and Target P based on the typical characteristics of pathogen effector molecules Candida camphora 328457 protein sequence candidate effect molecules to find and found that the bacteria contains 3 439 small molecule secreted protein, at the same time, the above protein redundancy, cysteine number and signal peptide length and other properties were analyzed . The results showed that there were more redundant proteins in the above secreted proteins, accounting for more than 50% of the total secreted proteins, and most of the secreted proteins were from 1 to 10 cysteines and 17 to 26 amino acids. In addition, based on the conserved motif RXLR of effector molecules in Oomycetes, motifs of 1 549 secreted proteins with unique amino acid sequences were searched for motifs, and 160 candidate effectors were identified. The prediction of Candida albicans candidate effector molecules can be achieved by the above bioinformatics analysis method.