Institute of Virology, University of Zurich, Zurich, Switzerland.
Molecular and Integrative Biosciences Research Programme, University of Helsinki, Helsinki, Finland.
Nat Commun. 2023 Jul 27;14(1):4515. doi: 10.1038/s41467-023-40148-6.
Prediction, prevention and treatment of virus infections require understanding of cell-to-cell variability that leads to heterogenous disease outcomes, but the source of this heterogeneity has yet to be clarified. To study the multimodal response of single human cells to herpes simplex virus type 1 (HSV-1) infection, we mapped high-dimensional viral and cellular state spaces throughout the infection using multiplexed imaging and quantitative single-cell measurements of viral and cellular mRNAs and proteins. Here we show that the high-dimensional cellular state scape can predict heterogenous infections, and cells move through the cellular state landscape according to infection progression. Spatial information reveals that infection changes the cellular state of both infected cells and of their neighbors. The multiplexed imaging of HSV-1-induced cellular modifications links infection progression to changes in signaling responses, transcriptional activity, and processing bodies. Our data show that multiplexed quantification of responses at the single-cell level, across thousands of cells helps predict infections and identify new targets for antivirals.
预测、预防和治疗病毒感染需要了解导致异质疾病结果的细胞间变异性，但这种异质性的来源尚未阐明。为了研究单纯疱疹病毒 1（HSV-1）感染对单个人类细胞的多模态反应，我们使用多重成像和病毒及细胞 mRNA 和蛋白质的定量单细胞测量，绘制了整个感染过程中的高维病毒和细胞状态空间。在这里，我们表明高维细胞状态景观可以预测异质感染，并且细胞根据感染进展在细胞状态景观中移动。空间信息表明，感染改变了受感染细胞及其相邻细胞的细胞状态。对 HSV-1 诱导的细胞修饰的多重成像将感染进展与信号转导反应、转录活性和处理体的变化联系起来。我们的数据表明，在单细胞水平上对反应进行多重定量，对数千个细胞进行分析有助于预测感染并确定抗病毒药物的新靶点。
