Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.
College of Health Solutions, Arizona State University, Tempe, AZ 85287, USA.
Viruses. 2024 Jul 24;16(8):1188. doi: 10.3390/v16081188.
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 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.
SARS-CoV-2 大流行导致了在全球范围内扩大病毒基因组监测。然而，在许多资源有限的环境中，将新病毒变异序列信息转化为有意义的免疫学和结构见解的实验室限制（经济、基础设施和人员）仍然是一个挑战，这些见解对于开发广泛作用的对策（特别是针对新兴和重新出现的病毒）非常有价值。在这里，我们描述了一种工作流程，该流程结合了废水监测、高通量测序、系统发生学、免疫信息学和病毒衣壳结构建模，用于对废水中鉴定出的未培养小核糖核酸病毒序列进行基因型到血清型的特征描述。具体来说，我们分析了犬小核糖核酸病毒（CanPVs），它们是未培养的，尚未被归类为家族成员，会导致犬类全身感染。我们分析了 118 份存档（储存在-20°C）废水（WW）样本，这些样本代表了美国西南部约 700,000 人的人群，采集时间为 2019 年 10 月至 2020 年 3 月和 2020 年 10 月至 2021 年 3 月。这些样本通过每月分成 12 个两升的样本池进行汇总，然后使用 450nm 膜过滤器将其分为（滤渣和滤液），随后使用 10,000 Da MW 的离心过滤器浓缩至 2 mL（1000×）。对这 24 个浓缩物进行 RNA 提取、CanPV 完整衣壳单链 RT-PCR、Illumina 测序、系统发生学、免疫信息学和结构预测。我们在 58.3%（14/24）的样本中检测到 CanPVs，共生成了 13,824,046 个修剪过的 Illumina 读段和 27 个 CanPV 连续体。系统发育和成对同一性分析表明，存在八个属于四个簇的 CanPV 基因型（基因型内差异<14%），簇内差异<20%。相似性分析、免疫信息学以及病毒原聚体和衣壳结构预测表明，这四个簇可能是不同的血清型，预测的簇区分 B 细胞表位聚集在 5 重轴周围峡谷的北部和南部边缘。我们的方法通过结合系统发生学、免疫信息学和病毒衣壳结构预测，实现了对未培养小核糖核酸病毒序列的基因型到血清型的特征描述。这因此绕过了一个主要的实验室相关瓶颈，从而使资源有限的环境能够从废水来源的基因组数据直接获得有价值的免疫学见解，这些见解对于开发预防和其他缓解措施非常必要。
