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Super resolution microscopy and deep learning identify Zika virus reorganization of the endoplasmic reticulum

  • Rory K.M. Long
  • , Kathleen P. Moriarty
  • , Ben Cardoen
  • , Guang Gao
  • , A. Wayne Vogl
  • , François Jean*
  • , Ghassan Hamarneh*
  • , Ivan R. Nabi*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number20937
JournalScientific Reports
Volume10
Issue number1
DOIs
Publication statusPublished - Dec 2020

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus subject areas

  • General

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