人类气道上皮（HAE）代表了SARS-CoV-2病毒感染的主要部位。由于包括不同的细胞群体，许多研究旨在解析决定疾病进展和严重程度的主要细胞类型和感染动力学。然而，细胞类型特异性的复制动力学以及呼吸上皮细胞组成对感染和病理学的贡献仍然不完全清楚。尽管包括HAE上的空气液界面（ALI）培养和肺器官体系在生理条件下观察感染动态的能力有了进展，但解析和量化个体过程和细胞对这些动态的贡献仍然具有挑战性。在这里，我们展示了如何结合实验数据和数学模型来推断和解决细胞类型特异性感染能力和组织构成对SARS-CoV-2感染动态的影响。我们采用逐步法，将关于HAE培养系统的各种实验数据整合起来，以了解组织分化和感染动力学，并开发了一种个体细胞模型，用于研究伪分层HAE内的感染和再生动态。此外，我们提出了一种基于图像数据的组织完整性量化方法，与相应的经皮电阻测量标准有关。我们的分析提供了对细胞类型特异性感染动力学进行定量评估的初步目标，并展示了组织构成和再生能力的变化如何影响疾病进展和病理学，例如吸烟者。此外，我们确定了仍需评估的关键测量指标，以改进对细胞类型特异性感染动力学和疾病进展的推断。我们的方法结合其他实验数据可以用于解析人类气道上皮培养系统中病毒感染和免疫的复杂动态。 版权所有：© 2023 Raach等人。这是一篇通过“知识共享许可协议”公开获取的文章，允许在任何媒体下无限制使用、分发和复制，前提是原作者和出处得到了适当的认可。

Human airway epithelium (HAE) represents the primary site of viral infection for SARS-CoV-2. Comprising different cell populations, a lot of research has been aimed at deciphering the major cell types and infection dynamics that determine disease progression and severity. However, the cell type-specific replication kinetics, as well as the contribution of cellular composition of the respiratory epithelium to infection and pathology are still not fully understood. Although experimental advances, including Air-liquid interface (ALI) cultures of reconstituted pseudostratified HAE, as well as lung organoid systems, allow the observation of infection dynamics under physiological conditions in unprecedented level of detail, disentangling and quantifying the contribution of individual processes and cells to these dynamics remains challenging. Here, we present how a combination of experimental data and mathematical modelling can be used to infer and address the influence of cell type specific infectivity and tissue composition on SARS-CoV-2 infection dynamics. Using a stepwise approach that integrates various experimental data on HAE culture systems with regard to tissue differentiation and infection dynamics, we develop an individual cell-based model that enables investigation of infection and regeneration dynamics within pseudostratified HAE. In addition, we present a novel method to quantify tissue integrity based on image data related to the standard measures of transepithelial electrical resistance measurements. Our analysis provides a first aim of quantitatively assessing cell type specific infection kinetics and shows how tissue composition and changes in regeneration capacity, as e.g. in smokers, can influence disease progression and pathology. Furthermore, we identified key measurements that still need to be assessed in order to improve inference of cell type specific infection kinetics and disease progression. Our approach provides a method that, in combination with additional experimental data, can be used to disentangle the complex dynamics of viral infection and immunity within human airway epithelial culture systems.Copyright: © 2023 Raach et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.