全基因组预测樟疫霉的候选效应分子

Prediction for candidate effector proteins from Phytophthora cinnamomi genome

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。

Phytophthora cinnamomi can devastate the important food crops and lauraceae plants,and cause serious harm in many countries. To study the pathogenesis and prevention methods of Ph. cinnamomi,based on the typical character of the pathogen effector,candidate effector proteins were predicted from 328 457 proteins in Ph. cinnamomi using the prediction programs including Signal P,Prot Comp,TMHMM,big-PI Fungal Predictor and Target P. The results showed that 3 439 secreted proteins were found with the 50-300 aa in length of amino acids,and the number of cysteine-rich and the length of the signal peptide were analyzed. The results showed that there were many redundant proteins in 3 439 secreted proteins,the proportion was up to 50%,and containing 1 to 10 cysteine,and the signal peptide length was 17 to 26. Further,based on the conserved motif RXLR in the effector of oomycetes,160 candidate effector proteins were identified from 1 549 secreted proteins with a unique amino acid sequence. Above bioinformatics analysis method could effectively achieve the candidate effector proteins in Ph. cinnamomi,which provided an important theoretical basis to further clarify the function of effectors.