Life Sciences Institute, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
Department of Cellular and Physiological Sciences, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
Sci Rep. 2020 Dec 1;10(1):20937. doi: 10.1038/s41598-020-77170-3.
The endoplasmic reticulum (ER) is a complex subcellular organelle composed of diverse structures such as tubules, sheets and tubular matrices. Flaviviruses such as Zika virus (ZIKV) induce reorganization of ER membranes to facilitate viral replication. Here, using 3D super resolution microscopy, ZIKV infection is shown to induce the formation of dense tubular matrices associated with viral replication in the central ER. Viral non-structural proteins NS4B and NS2B associate with replication complexes within the ZIKV-induced tubular matrix and exhibit distinct ER distributions outside this central ER region. Deep neural networks trained to distinguish ZIKV-infected versus mock-infected cells successfully identified ZIKV-induced central ER tubular matrices as a determinant of viral infection. Super resolution microscopy and deep learning are therefore able to identify and localize morphological features of the ER and allow for better understanding of how ER morphology changes due to viral infection.
内质网（ER）是一种复杂的亚细胞细胞器，由各种结构组成，如小管、薄片和管状基质。寨卡病毒（ZIKV）等黄病毒诱导内质网膜的重排，以促进病毒复制。在这里，使用 3D 超分辨率显微镜，显示寨卡病毒感染诱导致密管状基质的形成，该基质与中央内质网中的病毒复制相关。病毒非结构蛋白 NS4B 和 NS2B 与寨卡病毒诱导的管状基质内的复制复合物结合，并在该中央内质网区域之外表现出不同的内质网分布。经过训练以区分寨卡病毒感染细胞与模拟感染细胞的深度神经网络成功地将寨卡病毒诱导的中央内质网管状基质识别为病毒感染的决定因素。超分辨率显微镜和深度学习因此能够识别和定位内质网的形态特征，并更好地了解内质网形态如何因病毒感染而发生变化。
