小鼠唾液腺巨细胞病毒感染的空间动力学和免疫控制。

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2024-08-16 eCollection Date: 2024-08-01 DOI:10.1371/journal.pcbi.1011940
Catherine M Byrne, Ana Citlali Márquez, Bing Cai, Daniel Coombs, Soren Gantt
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引用次数: 0

摘要

人类巨细胞病毒(HCMV)是最常见的先天性感染。目前有几种 HCMV 疫苗正在研发中,但还没有一种获得批准。了解巨细胞病毒复制和传播的动力学,有助于合理设计疫苗来预防这种感染。唾液腺(SG)是原发性感染后和病毒从潜伏期重新活化期间 CMV 持续复制的重要场所。因此,唾液腺免疫反应的强度可能会影响病毒在宿主体内和宿主之间的传播。为了研究免疫反应与 SG 中病毒复制以及病毒从 SG 传播到其他组织之间的关系,小鼠感染了低剂量的鼠 CMV(MCMV)。在SG内接种后,我们描述了SG、血液和脾脏中的病毒和免疫动态,并确定了器官特异性免疫保护相关性。利用这些数据,我们构建了 MCMV 感染的分区数学模型。模型与数据的拟合和分析表明了细胞免疫反应在不同器官中的重要性,并指出了建立和传播感染所必需的SG内感染阈值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial kinetics and immune control of murine cytomegalovirus infection in the salivary glands.

Human cytomegalovirus (HCMV) is the most common congenital infection. Several HCMV vaccines are in development, but none have yet been approved. An understanding of the kinetics of CMV replication and transmission may inform the rational design of vaccines to prevent this infection. The salivary glands (SG) are an important site of sustained CMV replication following primary infection and during viral reactivation from latency. As such, the strength of the immune response in the SG likely influences viral dissemination within and between hosts. To study the relationship between the immune response and viral replication in the SG, and viral dissemination from the SG to other tissues, mice were infected with low doses of murine CMV (MCMV). Following intra-SG inoculation, we characterized the viral and immunological dynamics in the SG, blood, and spleen, and identified organ-specific immune correlates of protection. Using these data, we constructed compartmental mathematical models of MCMV infection. Model fitting to data and analysis indicate the importance of cellular immune responses in different organs and point to a threshold of infection within the SG necessary for the establishment and spread of infection.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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