The prediction of a pathogenesis-related secretome of Puccinia helianthi through high-throughput transcriptome analysis.
The prediction of a pathogenesis-related secretome of Puccinia helianthi through high-throughput transcriptome analysis.
复制标题
通过高通量转录组分析预测向日葵柄锈病发病机制相关的分泌组
DOI：
10.1186/s12859-017-1577-0
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发表时间：
2017-03-11
影响因子：
3
通讯作者：
Niu X
中科院分区：
文献类型：
--
作者：
Jing L;Guo D;Hu W;Niu X
背景：许多植物病原分泌蛋白是诱导子或致病因子，在寄主-病原互作过程中发挥重要作用。生物信息学方法使大规模预测和分析向日葵柄锈菌转录组分泌蛋白成为可能。结果：共鉴定出908个ORF（占总蛋白的2.6%）为含信号肽的分泌蛋白，其中908个ORF（占总蛋白的2.6%）为含信号肽的分泌蛋白。大多数蛋白质的长度范围为51至300个氨基酸（aa），而信号肽的长度为18至20个aa。信号肽酶I（SpI）切割位点被发现在463这些推定的分泌信号肽。55个蛋白质含有信号肽酶II（SpII）的脂蛋白信号肽识别位点。在908个分泌蛋白中，581个（63.8%）具有与信号识别和转导、代谢、运输和催化有关的功能。此外，143个推定的分泌蛋白质被归类为27个功能组的基础上基因本体论的术语，其中包括14组的生物过程中，7个细胞成分，和6个分子功能。分泌蛋白的基因本体分析揭示了水解酶活性的富集。82（9.0%）分泌蛋白的通路协会成立。同时还鉴定了大豆疫霉效应子特异性的细胞壁降解酶和3个同源蛋白，它们可能参与了向日葵锈病病原菌的致病性。结论：本研究为鉴定诱导子和致病因子提供了新的途径。908胞外分泌蛋白的最终鉴定和表征将促进我们对向日葵和锈病病原体之间相互作用的分子机制的理解，并将提高我们干预疾病状态的能力。
Background:Many plant pathogen secretory proteins are known to be elicitors or pathogenic factors,which play an important role in the host-pathogen interaction process. Bioinformatics approaches make possible the large scale prediction and analysis of secretory proteins from the Puccinia helianthi transcriptome. The internet-based software SignalP v4.1, TargetP v1.01, Big-PI predictor, TMHMM v2.0 and ProtComp v9.0 were utilized to predict the signal peptides and the signal peptide-dependent secreted proteins among the 35,286 ORFs of the P. helianthi transcriptome.Results:908 ORFs (accounting for 2.6% of the total proteins) were identified as putative secretory proteins containing signal peptides. The length of the majority of proteins ranged from 51 to 300 amino acids (aa), while the signal peptides were from 18 to 20 aa long. Signal peptidase I (SpI) cleavage sites were found in 463 of these putative secretory signal peptides. 55 proteins contained the lipoprotein signal peptide recognition site of signal peptidase II (SpII). Out of 908 secretory proteins, 581 (63.8%) have functions related to signal recognition and transduction, metabolism, transport and catabolism. Additionally, 143 putative secretory proteins were categorized into 27 functional groups based on Gene Ontology terms, including 14 groups in biological process, seven in cellular component, and six in molecular function. Gene ontology analysis of the secretory proteins revealed an enrichment of hydrolase activity. Pathway associations were established for 82 (9.0%) secretory proteins. A number of cell wall degrading enzymes and three homologous proteins specific to Phytophthora sojae effectors were also identified, which may be involved in the pathogenicity of the sunflower rust pathogen.Conclusions:This investigation proposes a new approach for identifying elicitors and pathogenic factors. The eventual identification and characterization of 908 extracellularly secreted proteins will advance our understanding of the molecular mechanisms of interactions between sunflower and rust pathogen and will enhance our ability to intervene in disease states.