Identification of SARS-CoV-2 packaging signals via bacteria-based inhibition assay

Nattaporn  Sripairoj; Chairat  Tunghirun; Sarin  Chimnaronk

Authors

Nattaporn Sripairoj Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom 73170, Thailand
Chairat Tunghirun Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom 73170, Thailand
Sarin Chimnaronk Institute of Molecular Biosciences, Mahidol University, Nakhon Pathom 73170, Thailand

Keywords:

bacteria-based assay, coronavirus, nucleocapsid protein, packaging signal, SARS-CoV-2

Abstract

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has damaged global public health. The nucleocapsid (N) protein of SARS-CoV-2 is the major viral RNA-binding protein that recognizes and binds to a specific sequence in the viral RNA genome, designated as a packaging signal (PS), and initiates viral genome packaging. However, the molecular details of the packaging mechanism and consensus on the PS sequence in the SARS-CoV-2 genome remain elusive. This study aims at development of a bacteria-based inhibition assay for measuring the interaction of N protein with viral RNA fragments in order to identify PS from SARS-CoV-2 genome. We initially conducted an unbiased bioinformatic analysis based on the conserved regions in both RNA sequence and secondary structure, and made predictions for three highly plausible packaging signal candidates (PSCs), referred to as PSC1, PSC2, and PSC3, within nucleotides 20,080 to 21,171 in the SARS-CoV-2 genome. These PSC cDNAs were fused with the downstream luciferase gene and introduced, along with the N protein expression plasmid, into the Lemo21 (DE3) Escherichia coli system. We carried out extensive optimization of the bacteria-based inhibition system and assessed the N–PS interaction through the translational suppression of luciferase expression. The results showed over 70% inhibition of luciferase expression for PSC1 and PSC2 with both N proteins from SARS-CoV-1 and SARS-CoV-2, supporting our bioinformatic prediction. Our results provide a useful tool for further elucidating of the mechanism of viral genome packaging and for studying other RNA–protein interactions.

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