The diversity of transcriptional targets between four different coronavirus nsp1 proteins

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In a recent study posted to the bioRxiv* preprint server, researchers investigated variations in the host immune response-elicited by non-structural protein 1 (nsp1) of coronaviruses (CoVs). They examined four nsp1 proteins from β-CoVs, including SARS, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Middle East respiratory syndrome (MERS), and one α-CoV 229E.

Study: Nonstructural protein 1 (nsp1) widespread RNA decay phenotype varies among Coronaviruses. Image Credit: joshimerbin/Shutterstock


Studies have revealed that although the outcome for the host gene expression machinery and immune response may be the same, the mode of action of nsp1 of different CoVs is different.

Nevertheless, all nsp1 proteins disrupt host gene expression through messenger ribonucleic acid (mRNA) decay or binding the 40s ribosomal subunit for subsequent translational arrest. For instance, SARS-CoV-2 nsp1 suppresses signal transducer and activator of transcription (STAT) 1 and STAT2 phosphorylation in the host to strongly repress type I interferon (INF) expression compared to the nsp1 of SARS and MERS.

The extent and nature of nsp1-mediated mRNA decay and the effect of nsp1 from different CoVs on the host transcriptome remains poorly understood.

About the study

In the present study, researchers explored the transcriptional landscape of cells expressing different nsp1 proteins using RNA-sequencing (RNA-seq). They identified the similarities and dissimilarities in the functions of RNA regulatory proteins during CoV infections to understand how their expression led to different pathological conditions.

The team transfected HEK293T cells with plasmids expressing the four nsp1 proteins from 229E, SARS, SARS-CoV-2, and MERS to delineate their impact on the host transcriptome and map their interactome.

The team induced the nsp1 expression in the transduced cells by incubating them with doxycycline for 24 hours. Next, they harvested, lysed, and resolved these cells on sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE).

Likewise, the team transfected transduced cells with a green fluorescent protein (GFP) reporter for 24 hours, then induced nsp1 expression by incubating them with doxycycline. Finally, they monitored the GFP expression using fluorescent microscopy, and GFP-positive cells were also quantified.

The researchers used Venn diagrams to show the unique and shared genes identified by RNA-seq between each CoV nsp1 RNA-seq dataset. Similarly, volcano plots showed differentially expressed genes (DEGs) between the control and nsp1-induced cells.

Further, they hierarchically clustered RNA-seq data based on Fold Change to visualize the expression of nsp1 from MERS, 229E, SARS, and SARS-CoV-2 based on relatedness.

Lastly, the team deployed the SARS-CoV-2 and MERS nsp1 mutants to confirm whether they induced mRNA decay like their wild-type counterparts. Additionally, they identified interactors shared by the four nsp1 proteins.

Study findings

Regardless of the origin of nsp1 protein, close to 50% of transcripts identified by RNA-seq were downregulated upon nsp1 induction, suggesting that all the four nsp1 tested during the study profoundly impacted their host cells via regulating RNA stability.

Previous studies have suggested MERS nsp1 leads to mRNA decay by targeting transcripts independently of ribosome interactions. Surprisingly, several identified transcripts were non-coding RNAs (ncRNAs), raising the possibility that the role of nsp1 in mRNA decay may be more extensive or that it can target multiple decay pathways.

SARS and SARS-CoV-2-derived nsp1 proteins uniformly and extensively destabilized mRNA on the host transcriptome, whereas MERS and 229E nsp1 did not follow this pattern.

Further examing the MERS volcano plot revealed significant negative foldchanges in many genes, suggesting that MERS nsp1 only targeted nuclear-transcribed RNAs. The nsp1 protein of 229E showed little fold change in genes, suggesting that 229E preferentially targeted a subset of a transcript but mildly affected the rest of the transcriptome.

RNA-seq data also indicated that nsp1 largely contributed to host shutoff by binding to ribosomes resulting in translational arrest. Therefore 229E nsp1 caused less marked mRNA decay than its β-CoV counterparts.

Heat maps further validated these findings, with genes heavily downregulated by MERS nsp1 clustering in the lower half of the heatmap. As expected, the SARS-CoV-2 and MERS nsp1 mutants were unable to induce mRNA decay.

Hierarchical clustering revealed that not randomly, but nsp1 of even closely related CoVs targeted different gene clusters for RNA decay and shared only a few protein interactors.

Accordingly, 229E nsp1 had the highest number of unique interactors, and MERS nsp1 had the lowest. There are two plausible explanations for this finding. As 229E nsp1, like other α-coronavirus nsp1, is drastically smaller than those found in β-coronaviruses, it needed more interacting partners to achieve its primary functions during viral infection. It is also likely that 229E nsp1 possessed more disordered regions for facilitating protein-protein interactions.

The interactome of MERS nsp1 was uniquely different. Therefore, most interactors detected therein were associated with the mRNA catabolic process. Future studies should explore these interactions and assess whether any of these factors are essential for nsp1 activity.


The study highlighted that while nsp1 is a highly conserved protein with rather well-conserved functions across different CoVs, its effect on the host transcriptome is virus-specific.

In fact, the host target range and interactomes vary widely among different nsp1 proteins. The authors emphasized that future studies further explore these aspects for understanding how these differences impact CoV infections, which is crucial to inform antiviral drug development against CoVs.

*Important notice

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Source: News Medical

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