通过系统发育推断预测潜在的 PRRSV-2 变异出现

N. Pamornchainavakul, M. Kikuti, I. Paploski, Cesar A. Corzo, K. VanderWaal
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摘要

猪繁殖与呼吸综合征(PRRS)是一种严重的猪病,每年给美国猪肉业造成超过 5 亿美元的巨大损失。不同基因的 PRRSV-2 病毒的共循环和出现阻碍了 PRRS 的控制,尤其是疫苗的开发。与季节性流感和 SARS-CoV-2 等其他病毒感染类似,用于识别潜在新出现病毒变种的预测工具可能有助于预防性缓解疾病。然而,尽管有大量相关数据,但尚未对 PRRSV-2 进行过此类预测。在本研究中,我们分析了十年来的病毒 ORF5 序列(n = 20,700)和相应的元数据,以确定基于系统发育的短期(12 个月)和长期(24 个月)变异体出现的早期指标。我们的分析重点是 PRRSV-2 1 号系,它是这一时期美国境内的主要病毒系。我们评估了作为变异体出现的关键成功指标的种群扩张、空间分布和遗传多样性。我们的研究结果表明,成功变种的最佳特征是在广泛地理扩散的同时进行种群扩张,但遗传多样性有限。条件逻辑回归显示,地方分支指数是预测种群扩张的唯一信息指标(平衡准确度(BA)= 0.75),而祖先分支长度与未来遗传多样性密切相关(BA = 0.79)。预测空间散布依赖于分支长度和假定抗原差异(BA = 0.67),但它们之间的因果关系仍不清楚。虽然预测模型有效地捕捉到了大多数新出现的变异(灵敏度 = 0.58-0.81),但它们的阳性预测值(PPV = 0.09-0.16)相对较低。PRRSV-2预测的第一步是未来更精确地预防PRRS战略的关键一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Potential PRRSV-2 Variant Emergence through Phylogenetic Inference
Porcine reproductive and respiratory syndrome (PRRS) is a significant pig disease causing substantial annual losses exceeding half a billion dollars to the United States pork industry. The cocirculation and emergence of genetically distinct PRRSV-2 viruses hinder PRRS control, especially vaccine development. Similar to other viral infections like seasonal flu and SARS-CoV-2, predictive tools for identifying potential emerging viral variants may prospectively aid in preemptive disease mitigation. However, such predictions have not been made for PRRSV-2, despite the abundance of relevant data. In this study, we analyzed a decade’s worth of virus ORF5 sequences (n = 20,700) and corresponding metadata to identify phylogenetic-based early indicators for short-term (12 months) and long-term (24 months) variant emergence. Our analysis focuses on PRRSV-2 Lineage 1, which was the predominant lineage within the U.S. during this period. We evaluated population expansion, spatial distribution, and genetic diversity as key success metrics for variant emergence. Our findings indicate that successful variants were best characterized as those that underwent population expansion alongside widespread geographical spread but had limited genetic diversification. Conditional logistic regression revealed the local branching index as the sole informative indicator for predicting population expansion (balanced accuracy (BA) = 0.75), while ancestral branch length was strongly linked to future genetic diversity (BA = 0.79). Predicting spatial dispersion relied on the branch length and putative antigenic difference (BA = 0.67), but their causal relationships remain unclear. Although the predictive models effectively captured most emerging variants (sensitivity = 0.58–0.81), they exhibited relatively low positive predictive value (PPV = 0.09–0.16). This initial step in PRRSV-2 prediction is a crucial step for more precise prevention strategies against PRRS in the future.
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