Absolute quantitation of individual SARS-CoV-2 RNA molecules provides a new paradigm for infection dynamics and variant differences

Jeffrey Y. Lee, Peter A.C. Wing, Dalia S. Gala, Marko Noerenberg, Aino I. Järvelin, Joshua Titlow, Xiaodong Zhuang, Natasha Palmalux, Louisa Iselin, Mary Kay Thompson, Richard M. Parton, Maria Prange-Barczynska, Alan Wainman, Francisco J. Salguero, Tammie Bishop, Daniel Agranoff, William James, Alfredo Castello*, Jane A. McKeating, Ilan Davis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Despite an unprecedented global research effort on SARS-CoV-2, early replication events remain poorly understood. Given the clinical importance of emergent viral variants with increased transmission, there is an urgent need to understand the early stages of viral replication and transcription. We used single-molecule fluorescence in situ hybridisation (smFISH) to quantify positive sense RNA genomes with 95% detection efficiency, while simultaneously visualising negative sense genomes, subgenomic RNAs, and viral proteins. Our absolute quantification of viral RNAs and replication factories revealed that SARS-CoV-2 genomic RNA is long-lived after entry, suggesting that it avoids degradation by cellular nucleases. Moreover, we observed that SARS-CoV-2 replication is highly variable between cells, with only a small cell population displaying high burden of viral RNA. Unexpectedly, the B.1.1.7 variant, first identified in the UK, exhibits significantly slower replication kinetics than the Victoria strain, suggesting a novel mechanism contributing to its higher transmissibility with important clinical implications.

Original languageEnglish
Article numbere74153
JournaleLife
Volume11
DOIs
Publication statusPublished - 20 Jan 2022

Bibliographical note

Funding Information: We are grateful to Danail Stoychev and Maria Kiourlappou for the advice on Python programming and high-performance computing. We are very grateful to Olympus UK and Europe for their generous loan of an Olympus IXplore SpinSR spinning disk system for the imaging work in this project and to Matthew Freeman and Jordan Raff for enabling us to install the microscope in the Dunn School of Pathology specifically for this SARS-CoV-2 work. We thank Michael Knight, Maeva Dupont, Lisa Chauveau, and Javier Gilbert Jaramillo for their provision of resources and assistance in Category III containment labs. We thank Micron Advanced Imaging Unit (https://micronoxford.com) for provision of advanced microscopy facilities and technical advice. ID: The Davis laboratory is funded by a Wellcome Investigator Award 209412/Z/17/Z and Wellcome Strategic Awards (Micron Oxford) 091911/B/10/Z and 107457/Z/15/Z. JAM: The McKeating laboratory is funded by a Wellcome Investigator Award 200838/Z/16/Z, UK Medical Research Council (MRC) project grant MR/R022011/1, and the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Science (CIFMS), China (grant number: 2018-I2M-2–002). AC is supported by an MRC Career Development Award (MR/L019434/1), MRC grants (MR/R021562/1, MC_UU_12014/10, and MC_UU_12014/12), and John Fell funds, University of Oxford. FJS is funded by the UK Health Security Agency (UK-HSA). James & Lillian Martin Centre is generously supported by the James Martin 21st Century Foundation. MKT is funded by a Leverhulme Grant to ID. AW and RMP are supported by Wellcome Strategic Award 107457/Z/15/Z. WJ, MP-B and TB are funded by the COVID-19 Research Response Fund, University of Oxford. JYL and DSG are funded by the Medial Sciences Graduate Studentship, University of Oxford.

Open Access: This article is distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Publisher Copyright: © Lee et al.

Citation: Lee, Jeffrey Y., et al. "Absolute quantitation of individual SARS-CoV-2 RNA molecules provides a new paradigm for infection dynamics and variant differences." Elife 11 (2022): e74153.

DOI: https://doi.org/10.7554/eLife.74153

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