基于基因组条形码的肠道病毒分子分型及致病谱预警平台的建立

It is common reported that intestinal virus (EV) caused large outbreaks and fulminant epidemic in recent years, Polio outbreak in xinjiang, outbreaks of hand-foot-and-mouth disease in Mainland China and Hong Kong , as well as the infection of EV71, has become a serious public health problem. EV has 106 subtypes, which causes complex types of diseases. A subtype can often cause several diseases or symptoms and the same subtype of virus causes different clinical manifestations, so that the typing identification becomes the key link of a pointed prevention of EV. The traditional serological typing has been a long haul, the high variability of EV makes it lack of accuracy and uniformity to typing EV by single region sequences analysis. It is urgent to establish a new mode of molecular subtyping which based on the whole genome information mining and the virus-host protein mutual regulative network molecule. Our project aim to impart a molecular typing to EV through the visualization of genome bar code and the European matrix analysis of bar code, to analyze the interactional network map of different types of EV protein with their host protein and the differences between the disease spectrums of different EV types, to achieve the functional enrichment of EV in the same superfamily and establish a new molecular typing of EV and a relative disease spectrum of comment system platform and a EV warning platform eventually. It is a new technology which the past biology research and computer operations are unable to realize, and this technology will promote this field in China be in line with international practice.

近年肠道病毒（EV）引起大规模爆发与流行常有报道, 新疆爆发脊髓灰质炎，内地与香港爆发手足口病及EV71感染，已成严重的公共卫生问题。EV型别多达106种，引起的疾病类型复杂,不同EV引起相同症状，同一病毒引起不同临床表现，使EV的分型鉴定成为针对性防治的关键环节。传统的血清学分型费事费力，EV的高变异使得应用单一区域序列进行分子分型缺乏准确及统一性，亟待建立一种基于全基因组信息挖掘及病毒-宿主蛋白相互调控网络分子分型的新模式。项目通过基因组条形码可视化及条形码欧式矩阵分析，对EV进行分子分型，分析不同型别EV蛋白与宿主蛋白间的相互作用网络图谱及不同型别EV疾病谱的差异，实现对同一超家族蛋白的EV进行功能富集，最终建立基于Web网页查询及实时更新的EV分子分型及相关疾病谱注释系统平台及EV预警平台。这是已往生物学研究及计算机运算都无法实现的新技术，必将促进我国该领域与国际研究接轨。

项目组整合传统的分子生物学及新型的计算生物技术，建立了微生物基因组条形码可视化平台。然后计算不同病毒基因组的条形码特征向量间的欧式距离，籍此距离对肠道病毒进行鉴定并对肠道病毒建立系统发育树。结果表明：不同的病毒具有不同的基因组条形码图像，其中的异常区域可能为水平转移的基因片段。基因组条形码距离能完全将各种病毒进行分类，并且对肠道病毒的各亚型也能起到很好的分型效果。建立的系统发育树与基于VP1使用传统序列比对方法建立的系统发育树具有94%的相似度，但是对于某些柯萨奇A组的某些型别的病毒，基于基因组条形码技术的分类结果更符合病毒临床表现，说明此方法可能反映出传统基于单基因序列比对无法表现的信息。通过粪便、咽拭子或疤疹液标本分离长春地区各医院及疾病控中心的可疑肠道病临床样本，将此类全部数据编辑整理后上传至我们构建的肠道病毒信息数据库。通过基因组条形码欧式距离的分析及BEAST贝叶斯进化分析软件，来推导肠道病毒各亚型变异与引发大规模爆发的时间相互关系的预警模型。