SARS-CoV-2大流行导致全球病毒基因组监测的规模扩大。然而,潮湿实验室的限制(经济,基础设施,和人员)在许多资源有限的环境中,将新病毒变体序列信息翻译为有意义的免疫学和结构见解,这些见解对于开发具有广泛作用的对策(特别是对于新兴和重新出现的病毒)仍然是一个挑战。这里,我们描述了一个结合废水监测的工作流程,高通量测序,系统发育学,免疫信息学,和病毒衣壳结构建模,用于对废水中鉴定的未培养的小核糖核酸病毒序列进行基因型到血清型表征。具体来说,我们分析了犬小核糖核酸病毒(CanPV),它们是引起犬科全身性感染的未培养且尚未分配的Picornaviridae家族成员。我们分析了2019年10月至2020年3月以及2020年10月至2021年3月期间美国西南部约70万人的118个存档(储存在-20°C)废水(WW)样本。按月将样品汇集成12个两升体积,使用450nm膜过滤器分配(过滤捕获的固体[FTSs]和滤液),随后使用10,000DaMW截止离心过滤器浓缩至2mL(1000X)。对24种浓缩物进行RNA提取,CanPV完整衣壳单重叠群RT-PCR,Illumina测序,系统发育学,免疫信息学,和结构预测。我们在58.3%(14/24)的样品中检测到CanPV,产生了13,824,046个修剪的Illumina读数和27个CanPV重叠群。系统发育和配对同一性分析显示,8个CanPV基因型(基因型差异<14%)属于四个集群,内部发散<20%。相似性分析,免疫信息学,病毒原粒和衣壳结构预测表明,这四个簇可能是不同的血清学类型,预测的簇区分性B细胞表位聚集在围绕5倍对称轴的峡谷的北部和南部边缘。我们的方法允许通过耦合系统发育来对未培养的小核糖核酸病毒序列进行基因型到血清型表征,免疫信息学,和病毒衣壳结构预测。因此,这绕过了一个主要的潮湿实验室相关瓶颈,从而使资源有限的环境从废水来源的基因组数据跃升为制定预防和其他缓解措施所需的有价值的免疫学见解。
The SARS-CoV-2 pandemic resulted in a scale-up of viral genomic surveillance globally. However, the wet lab constraints (economic, infrastructural, and personnel) of translating novel virus variant sequence information to meaningful immunological and structural insights that are valuable for the development of broadly acting countermeasures (especially for emerging and re-emerging viruses) remain a challenge in many resource-limited settings. Here, we describe a workflow that couples wastewater surveillance, high-throughput sequencing, phylogenetics, immuno-informatics, and virus
capsid structure modeling for the genotype-to-serotype characterization of uncultivated picornavirus sequences identified in wastewater. Specifically, we analyzed canine picornaviruses (CanPVs), which are uncultivated and yet-to-be-assigned members of the family Picornaviridae that cause systemic infections in canines. We analyzed 118 archived (stored at -20 °C) wastewater (WW) samples representing a population of ~700,000 persons in southwest USA between October 2019 to March 2020 and October 2020 to March 2021. Samples were pooled into 12 two-liter volumes by month, partitioned (into filter-trapped solids [FTSs] and filtrates) using 450 nm membrane filters, and subsequently concentrated to 2 mL (1000×) using 10,000 Da MW cutoff centrifugal filters. The 24 concentrates were subjected to RNA extraction, CanPV complete
capsid single-contig RT-PCR, Illumina sequencing, phylogenetics, immuno-informatics, and structure prediction. We detected CanPVs in 58.3% (14/24) of the samples generated 13,824,046 trimmed Illumina reads and 27 CanPV contigs. Phylogenetic and pairwise identity analyses showed eight CanPV genotypes (intragenotype divergence <14%) belonging to four clusters, with intracluster divergence of <20%. Similarity analysis, immuno-informatics, and virus protomer and
capsid structure prediction suggested that the four clusters were likely distinct serological types, with predicted cluster-distinguishing B-cell epitopes clustered in the northern and southern rims of the canyon surrounding the 5-fold axis of symmetry. Our approach allows forgenotype-to-serotype characterization of uncultivated picornavirus sequences by coupling phylogenetics, immuno-informatics, and virus
capsid structure prediction. This consequently bypasses a major wet lab-associated bottleneck, thereby allowing resource-limited settings to leapfrog from wastewater-sourced genomic data to valuable immunological insights necessary for the development of prophylaxis and other mitigation measures.