预测PCV13后的肺炎球菌演变,使用侵袭性疾病数据,并通过反向侵袭性权重增强
Xueting Qiu1, Lesley McGee2, Laura L Hammitt3
1Center for Communicable Disease Dynamics, Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.
medRxiv : the preprint server for health sciences
|January 3, 2024
概括
预测疫苗接种后的Streptococcus pneumoniae进化是关键. 这项研究使用了加权的侵入性数据,准确地建模了疫苗接种后肺炎球菌载体群体动态.
科学领域:
- 微生物学 微生物学
- 进化生物学 进化生物学
- 基因组学就是基因组学.
背景情况:
- 肺炎球菌合疫苗 (PCV) 已经改变了Streptococcus pneumoniae种群,导致血清型替代.
- 了解肺炎球菌疫苗接种后的演变对于疫苗设计和公共卫生战略至关重要.
研究的目的:
- 评估负频率依赖选择 (NFDS) 模型在解释PCV13引入后肺炎球菌载体种群演变中的有效性.
- 调整入侵性疾病数据,以使用逆入侵性权重计算,在运输群体中近似估计菌株比例.
主要方法:
- 来自侵入性肺炎球菌分离物 (1998-2018) 的基因组数据使用生物信息管道进行了分析,用于组装,注释和泛基因组分析来定义菌株.
- 采用了NFDS模型,对侵入性数据进行加权,以通过调整血清型特定的反向侵入性来估计载体群体动态.
- 使用调整后的侵入性疾病数据分析了疫苗接种前和后的辅助基因频率和菌株比例 (PCV7,PCV13).
主要成果:
- 反向-侵入性权重显著改善了不同时间段的侵入性和载体数据之间的辅助基因频率的相关性.
- 在应用权重方法后,调整后的R平方值用于预测运输群体中应变比例从0.176增加到0.544.
- 使用权重侵入性数据的NFDS模型成功预测了PCV13后肺炎球菌菌株在运输群体中的比例.
结论:
- 开发的权重系统有效地调整了侵入性疾病监测数据,以更好地代表Streptococcus pneumoniae载体种群.
- 该NFDS模型准确地预测了PCV13.3后预测的运输群体中的菌株比例.
- 这种方法增强了易于获得的基因组数据的实用性,从侵入性疾病监测到公共卫生洞察力.
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