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叙利亚仓鼠中新冠病毒的生物数学模型。

A biomathematical model of SARS-CoV-2 in Syrian hamsters.

作者信息

Schirm Sibylle, Nouailles Geraldine, Kirsten Holger, Trimpert Jakob, Wyler Emanuel, Teixeira Alves Luiz Gustavo, Landthaler Markus, Ahnert Peter, Suttorp Norbert, Witzenrath Martin, Scholz Markus

机构信息

Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, 04107, Leipzig, Germany.

Department of Infectious Diseases and Respiratory Medicine and Critical Care, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 10117, Berlin, Germany.

出版信息

Sci Rep. 2024 Dec 18;14(1):30541. doi: 10.1038/s41598-024-80498-9.

Abstract

When infected with SARS-CoV-2, Syrian hamsters (Mesocricetus auratus) develop moderate disease severity presenting key features of human COVID-19. We here develop a biomathematical model of the disease course by translating known biological mechanisms of virus-host interactions and immune responses into ordinary differential equations. We explicitly describe the dynamics of virus population, affected alveolar epithelial cells, and involved relevant immune cells comprising for example CD4+ T cells, CD8+ T cells, macrophages, natural killer cells and B cells. We also describe the humoral response dynamics of neutralising antibodies and major regulatory cytokines including CCL8 and CXCL10. The model is developed and parametrized based on experimental data collected at days 2, 3, 5, and 14 post infection. Pulmonary cell composition and their transcriptional profiles were obtained by lung single-cell RNA (scRNA) sequencing analysis. Parametrization of the model resulted in a good agreement of model and data. The model can be used to predict, for example, the time course of the virus population, immune cell dynamics, antibody production and regeneration of alveolar cells for different therapy scenarios or after multiple-infection events. We aim to translate this model to the human situation in the future.

摘要

感染严重急性呼吸综合征冠状病毒2(SARS-CoV-2)时,叙利亚仓鼠(金仓鼠)会出现中度疾病严重程度,呈现出人类2019冠状病毒病(COVID-19)的关键特征。我们在此通过将病毒-宿主相互作用和免疫反应的已知生物学机制转化为常微分方程,建立了该疾病病程的生物数学模型。我们明确描述了病毒种群、受影响的肺泡上皮细胞以及包括例如CD4+T细胞、CD8+T细胞、巨噬细胞、自然杀伤细胞和B细胞在内的相关免疫细胞的动态变化。我们还描述了中和抗体以及包括CCL8和CXCL10在内的主要调节细胞因子的体液反应动态。该模型是根据感染后第2、3、5和14天收集的实验数据开发并进行参数化的。通过肺单细胞RNA(scRNA)测序分析获得了肺细胞组成及其转录谱。模型的参数化使得模型与数据达成了良好的一致性。该模型可用于预测,例如,不同治疗方案或多次感染事件后病毒种群的时间进程、免疫细胞动态、抗体产生以及肺泡细胞的再生情况。我们的目标是在未来将该模型转化应用于人类情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2d8/11655638/1a28c4743b60/41598_2024_80498_Fig1_HTML.jpg

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