Suzuki Yoshiyuki, Doan Yen Hai, Kimura Hirokazu, Shinomiya Hiroto, Shirabe Komei, Katayama Kazuhiko
Graduate School of Natural Sciences, Nagoya City University, Nagoya, Japan.
Department of Virology II, National Institute of Infectious Diseases, Musashimurayama, Japan.
Front Microbiol. 2019 Feb 5;10:116. doi: 10.3389/fmicb.2019.00116. eCollection 2019.
The norovirus forecasting system (NOROCAST) has been developed for predicting directions of changes in genotype proportions between human norovirus (HuNoV) seasons in Japan through modeling herd immunity to structural protein 1 (VP1). Here 404 nearly complete genomic sequences of HuNoV were analyzed to examine whether the performance of NOROCAST could be improved by modeling herd immunity to VP2 and non-structural proteins (NS) in addition to VP1. It was found that the applicability of NOROCAST may be extended by compensating for unavailable sequence data and observed genotype proportions of 0 in each season. Incorporation of herd immunity to VP2 and NS did not appear to improve the performance of NOROCAST, suggesting that VP1 may be a suitable target of vaccines.
已开发出诺如病毒预测系统（NOROCAST），用于通过对结构蛋白1（VP1）的群体免疫进行建模，预测日本人类诺如病毒（HuNoV）不同流行季之间基因型比例的变化趋势。本文分析了404条近乎完整的HuNoV基因组序列，以研究除VP1外，通过对VP2和非结构蛋白（NS）的群体免疫进行建模，是否能提高NOROCAST的性能。研究发现，通过补充缺失的序列数据以及各流行季中观察到的基因型比例为0的情况，NOROCAST的适用性可能会得到扩展。纳入对VP2和NS的群体免疫似乎并未提高NOROCAST的性能，这表明VP1可能是疫苗的合适靶点。
