Mechanistic Constraints on the Acquisition of Variation by Alphaviruses

该项目要求：RNA病毒的基因组结构是否对病毒获取变异产生了机械约束？这些约束是否可以以一种有助于设计元测序应用程序的数据处理和分析算法的方式来定义？它解决了BBSRC的主题“开发新的工作方式”：战略优先事项“数据驱动的生物学”;调查生物系统或过程中表型性状和变异之间的联系。RNA病毒的RNA聚合酶是容易出错的，以比其宿主的校对DNA聚合酶高得多的速率引入突变。RNA病毒基因组的自然复制是自然选择和人工选择都可能作用的遗传变异的有力来源。一些值得注意的新出现的疾病是由RNA病毒引起的。它们的出现部分归因于其快速进化的能力，但几乎没有定量数据说明是什么限制了这种能力。一些RNA病毒的高毒性也引起了对故意滥用的关注。因此，需要对病毒进化有更深入的了解，以帮助预测和了解出现事件，以及快速可靠地检测和区分自然和合成生物。对RNA病毒的研究表明，密码子的使用可以沿着多顺反子RNA的长度变化，并且这与共翻译修饰的位点相关。这可能是一种自适应机制，以减缓在沿着多顺反子的点处的翻译速率，以促进共翻译修饰，并且可能代表对可变性的约束。此外，一些研究将病毒RNA二级结构与免疫应答诱导联系起来，这可能导致基于基因组结构的选择。除此之外，目前尚不清楚RNA病毒变异的获得受到哪些限制，除了与非沉默突变相关的限制。DNA测序现在允许对包括多个分类群的复杂生物环境进行元测序，并通过数据处理算法识别不同的基因组。元测序的数据处理挑战可以通过算法来简化，以便在组装过程中对潜在的基因组进行排名，优先考虑那些更有可能是真实的的基因组。它们也可以通过算法进行简化，以在主要的自然环境中快速识别合成基因组。该项目将研究合成危害组2甲病毒基因组向最佳序列进化的能力，可能通过一个比初始修饰形式更不理想的中间体。它将比较野生型和计算优化的序列，以及杂交序列的稳定性和突变方向。该项目将产生关于RNA病毒的可变性和影响变异的因素的定量数据，为今后优化筛选元序列数据的算法提供数据，以快速可靠地识别合成生物体;并快速识别和分类以前未知的生物体，以及复杂生物混合物中的新出现或潜在病原体。研究结果将应用于进化生物学、环境监测、流行病学、法医学以及医学和兽医诊断。该项目将Pirbright在重组甲病毒方面的专业知识与萨里大学对人畜共患RNA病毒遗传和表型变异的兴趣以及Dstl对甲病毒准种动力学的兴趣相结合。该项目将扩大TPI在甲病毒细胞和分子生物学方面的产品组合;它将为UoS的人畜共患病病毒分析提供信息;并扩大Dstl的产品组合，其中包括生物威胁病毒的CL 2替代物，有助于了解RNA病毒的总体种群动态。它将开始评估来自自然和合成来源的威胁性质的潜在限制。

This project asks: Does the genome structure of RNA viruses place mechanistic constraints on acquisition of variation by the virus; and can these be defined in a way that aids the design of data handling and analysis algorithms for metasequencing applications? It addresses the BBSRC Theme 'Exploiting New Ways of Working': Strategic Priority 'Data Driven Biology'; Investigating links between phenotypic traits and variation in biological systems or processes. RNA polymerases of RNA viruses are error prone, introducing mutations at much higher rates than the proof-reading DNA polymerases of their hosts. The natural replication of RNA virus genomes is a potent source of genetic variation upon which both natural and artificial selection may act. Several notable emerging diseases are caused by RNA viruses. Their emergence has been attributed partly to the ability to evolve rapidly, but there is little quantitative data on what may constrain this. The high virulence of some RNA viruses has also led to concerns regarding intentional misuse. Consequently a greater understanding of viral evolution is required to help predict and understand emergence events, as well as to detect and distinguish natural and synthetic organisms rapidly and reliably. Studies of RNA viruses have demonstrated that codon usage can vary along the length of a polycistronic RNA, and this correlates with sites of co-translational modification. This may be an adaptive mechanism to slow the rate of translation at points along the polycistron to facilitate co-translational modification, and may represent a constraint on variability. Furthermore, some studies have connected virus RNA secondary structure with immune response induction, which may result in selection on the basis of genome structure. Beyond this, it is not clear what constraints on the acquisition of variation in RNA viruses apply, except those associated with non-silent mutations. DNA sequencing now allows metasequencing of complex biological milieux comprising multiple taxa, and identification of distinct genomes through data handling algorithms. The data handling challenges of metasequencing could be streamlined by algorithms to rank potential genomes during assembly, giving priority to those with a greater likelihood of being real. They could also be streamlined by algorithms to rapidly identify synthetic genomes in predominantly natural milieux. The project will examine the ability of a synthetic Hazard Group 2 alphavirus genome to evolve towards an optimal sequence, potentially passing through an intermediate that is less optimal than the initial modified form. It will compare wildtype and computationally optimized sequences; and the stability and direction-of-mutation of hybrid sequences. The project will produce quantitative data on the mutability of RNA viruses and factors which militate against variation, providing data for the future optimization of algorithms for sifting metasequence data to rapidly and reliably identify synthetic organisms; and for rapid identification and classification of previously unknown organisms, and emergent or potential pathogens in complex biological mixtures. The results will have applications in evolutionary biology, environmentalmonitoring, epidemiology, forensic science, and medical and veterinary diagnostics. The project combines Pirbright's expertise with recombinant alphaviruses with University Of Surrey's interest in genetic and phenotypic variation in zoonotic RNA viruses, and Dstl's interest in the dynamics of alphavirus quasispecies. The project will expand TPI's portfolio on the cell and molecular biology of alphaviruses; it will inform UoS' analyses of zoonotic viruses; and expand Dstl's portfolio with CL2 surrogates for biothreat viruses that help to understand the population dynamics of RNA viruses generally. It will begin to assess potential limits on the nature of threat from both nature of threat from both natural & synthetic sources.