Epi-SEQ - Molecular epidemiology of epizootic diseases using next generation sequencing technology

下一代测序(NGS)技术提供了前所未有的阶跃变化，增加了可以从样本生成的序列数据量。NGS技术可以确定完整的病毒基因组，其分辨率允许量化样本内的RNA准物种变异，并可以节省大量样本或更大DNA病毒基因组的测序。该项目的重点是威胁欧洲畜牧业的重要流行性病毒疾病，其目的是利用NGS产生可在疫情期间实时使用的改进工具。这项工作将由来自比利时、德国、意大利、瑞典和英国的多学科科学家团队承担，他们在分子病毒学、生物信息学、数学建模和进化生物学方面具有专业知识。RNA病毒进化迅速，迅速适应不同的环境压力，逃避宿主免疫防御，改变其致病性和宿主范围，并逃避诊断测试。目前的方法限制了我们研究这些病毒典型的复杂基因组混合物(准种)的进化动力学的分辨率。代表口蹄疫病毒(FMDV)、禽流感病毒(AIV)、新城疫病毒(NDV)和猪瘟病毒(CSFV)等病原体流行的存档样本收集将用于监测疾病现场暴发期间的演变。在实地收集的时空数据将与这些遗传数据相结合，以产生可用于重建病毒流行期间传播树的稳健模型。此外，在强大的选择压力下，将使用FMDV(ss+RNA基因组)和AIV(ss片段RNA基因组)进行体外实验。对由此产生的NGS数据进行建模将提供一个框架，以描述在这些现场暴发期间测量到的更大范围的演变模式。将通过研究具有大基因组的DNA病毒(ASFV和痘病毒)将遗传数据与病毒表型联系起来。尽管这些病毒的基因组相对稳定，但它们的大小给使用传统桑格方法进行测序带来了挑战。具体的一揽子工作将侧重于技术方案的改进和传播，以及生物信息学和建模工具的数据分析和传播。该项目的见解将导致：a)关于病毒进化和(亚)种群的新信息；b)不同基因组组织(正义RNA、节段RNA、节段RNA)之间的比较进化数据；c)基于对适当序列基序的改进识别，改进诊断分析；d)分子流行病学的强大工具；e)增强优化疫苗毒株构成并与新出现的病毒变种匹配的能力；f)更有效地控制流行和地方性传染病的工具。

Next-generation sequencing (NGS) techniques offer an unprecedented step-change increase in the amount of sequence data that can be generated from a sample. NGS technologies can determine complete viral genomes with a resolution allowing the quantification of RNA quasispecies variation within samples and can economize the sequencing of large numbers of samples or larger DNA virus genomes. Focusing on important epizootic viral diseases that threaten livestock industries in Europe, the aim of this project is to exploit NGS to generate improved tools that can be used in real-time during epidemics. This work will be undertaken by a multidisciplinary team of scientists from Belgium, Germany, Italy, Sweden, and the United Kingdom with expertise in molecular virology, bioinformatics, mathematical modeling, and evolutionary biology. RNA viruses evolve rapidly and quickly adapt to different environmental pressures escaping host immune defenses, altering their pathogenicity and host range, and evading diagnostic tests. Current methodologies limit the resolution at which we can study the evolutionary dynamics of the complex genomic mixtures (quasispecies) that are typical for these viruses. Archived sample collections representing epizootic outbreaks of pathogens such as foot-and-mouth disease virus (FMDV), avian influenza virus (AIV), Newcastle Disease Virus (NDV) and classical swine fever virus (CSFV) will be used to monitor the evolution during field outbreaks of disease. Spatiotemporal data collected in the field will be integrated with this genetic data to produce robust models that can be used to reconstruct transmission trees during viral epidemics. Furthermore, in vitro experiments will be performed using FMDV (ss+RNA genome) and AIV (ss segmented-RNA genome) under strong selection pressures. Modeling of the resulting NGS data will provide a framework to describe the wider scale evolutionary patterns that are measured during these field outbreaks. Linking genetic data to viral phenotype will be undertaken by studying DNA viruses with large genomes (ASFV and poxviruses). Although the viruses have relatively stable genomes, their large size poses challenges for sequencing using traditional Sanger approaches. Specific work packages will focus on the improvement and dissemination of technical protocols and on data analysis and dissemination of bioinformatics and modeling tools. Insights from this project will result in: a) Novel information on viral evolution and (sub)populations; b) comparative evolutionary data between viruses with different genome organisation (+ vs. - sense RNA, segmented RNA, c) Improved diagnostic assays, based on an improved recognition of suitable sequence motifs; d) Powerful tools for molecular epidemiology; e) Enhanced capacity to optimize the strain composition of vaccines, and match to emerging virus variants; f) More effective tools to control epidemic and endemic infectious diseases.