病毒-病毒共感染期间的相互作用如何塑造感染动力学
Lubna Pinky1, Joseph R DeAguero2, Christopher H Remien3
1Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
Viruses
|June 28, 2023
概括
病毒共感染可以通过复杂的相互作用加剧或减少疾病的严重程度. 数学建模显示,病毒特异性细胞清除率显著影响共感染的结果,如流感A病毒与RSV或SARS-CoV-2.
科学领域:
- 病毒学和数学生物学数学生物学
- 呼吸道病毒感染 呼吸道病毒感染
- 病毒与病毒之间的相互作用
背景情况:
- 呼吸道病毒感染是全球主要的健康问题,并发感染很常见.
- 病毒共感染对疾病严重性的影响是可变的,从降低到增加的致病性.
- 在病毒共感染中这些不同结果的背后的机制尚未完全理解.
研究的目的:
- 调查病毒共感染中导致不同疾病结果的机制.
- 使用数学建模预测病毒-病毒相互作用的潜在动态.
- 探索不同的感染顺序,时间和病毒配对如何影响疾病严重程度.
主要方法:
- 数学模型与感染呼吸道同胞病毒 (RSV) 和甲型流感病毒 (IAV) 的子的病毒载荷数据相匹配.
- 模型模拟探索了未经检查的共感染场景,包括不同的感染顺序和病毒配对 (例如,IAV与犀利病毒 (RV) 或SARS-CoV-2 (CoV2)).
- 人类病毒载量数据和单一和并发感染的小鼠体重减轻数据被用来解释模型结果.
主要成果:
- 在RSV-IAV共感染中,IAV减少了RSV的产生,RSV减缓了IAV感染细胞的清除.
- 在小鼠中,与IAV和RV或Cov2的同时感染显示出严重程度的增加,可能是由于IAV感染细胞清除速度较慢.
- 当IAV跟随RV时,改善的结果与IAV降低RV感染细胞清除率相关.
结论:
- 病毒共感染的数学建模提供了关于病毒-病毒相互作用如何调节疾病严重性的见解.
- 病毒特异性感染细胞清除率是共感染结果的关键决定因素.
- 该研究产生了可测试的假设,用于实验评估病毒共感染动态.
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