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The frequency and nature of RNA errors in both SARS-CoV-2 and its vaccine

A recent article posted to the Research Square* preprint server demonstrated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutants and vaccine variability stem from ribonucleic acid polymerase (RNAP) inaccuracy. 

Study: RNA polymerase inaccuracy underlies SARS-CoV-2variants and vaccine heterogeneity. Image Credit: gagalaguna/Shutterstock


Since the beginning of the CoV disease 2019 (COVID-19) pandemic, the world has seen the emergence of novel SARS-CoV-2 variants of concern (VOC) and viral lineages that can evade vaccine protection. COVID-19 messenger RNA (mRNA) vaccines centered on the SARS-CoV-2 spike (S) protein have been commonly used to avert COVID-19 and induce a protective immune response towards VOCs following multiple doses.

COVID-19 mRNA vaccines for their synthesis and SARS-CoV-2 for replication require RNAP. Nevertheless, these enzymes are intrinsically fault-prone than their deoxyribonucleic acid (DNA) equivalents and could introduce SARS-CoV-2 mutants to the RNA3. 

To date, no empirical research has directly evaluated the frequency of SARS-CoV-2 RNA-dependent RNAP (RdRp) defects during replication, a critical parameter for modeling viral evolution. Likewise, the frequency and nature of RNA variants produced during vaccine production are unclear. The distribution and extent of mistakes generated by the RNAPs participating in each phase are crucial to understanding SARS-CoV-2 evolution and vaccination efficacy. Current approaches are not adequately sensitive and specific to detect de novo RNA mutants in low-input samples such as virus isolates.

About the study

In the present work, utilizing a targeted, accurate RNA consensus sequencing (tARC-seq) approach, the scientists establish the nature and frequency of RNA faults in both SARS-CoV-2 and its vaccination. tARC-seq integrates the core characteristics of ARC-seq and the hybrid capture technique for target enhancement to allow deep variant probing of low input SARS-CoV-2 samples. The researchers offer a targeted sequencing approach for finding RNA mutants in low abundance samples and infrequent transcripts.

The team initially validated tARC-seq in Escherichia coli (E. coli). They next examined SARS-CoV-2 RNA extracted from infected Vero cells using tARC-seq. To determine whether RNA variants were distributed randomly throughout the SARS-CoV-2 genome, frequencies were determined by position. 

Since SARS-CoV-2 has developed into multiple separate lineages, each with its own set of mutations and VOCs, the investigators analyzed if the frequency of RNA variants differed across viral lineages. They applied tARC-seq to the SARS-CoV-2 Alpha and Delta variants. 

Further, the team examined the frequency and spectrum of RNA variants in the Pfizer vaccination since vaccine mRNA was plentiful and susceptible to sequencing using bulk RNA consensus sequencing, i.e., ARC-seq. A sequence of T7 in vitro transcription (IVT) reactions was carried out simultaneously over a variety of temperatures on two distinct templates: 1) the native S gene from the SARS-CoV-2 WT strain and 2) the codon-optimized S structure from the COVID-19 Pfizer vaccine.


Overall, the authors discovered that the SARS-CoV-2 RdRp creates one mistake for every 10,000 nucleotides, greater than prior estimates by sequencing three SARS-CoV-2 isolates. While this frequency was higher than other forecasts, it was equivalent to earlier findings in poliovirus, which uses an RdRp for replication but does not have a proofreading function. The team also found that RNA mutants were not dispersed randomly throughout the genome, albeit were linked to specific genomic characteristics and genes, like S protein.

The mistake frequency estimates were based previously on the discovery of a proofreading 3′-to-5′ exoribonuclease (ExoN, non-structural protein 14 (nsp14)) separate from the SARS-CoV-2 RdRp. The same proofreading process has been linked to template switching, which the researchers found error-prone. 

Large deletions, insertions, and intricate mutations were detected using tARC-seq, which could be simulated using non-programmed RdRp template flipping. Many substantial genetic alterations identified in the evolution of multiple SARS-CoV-2 lineages globally, including the Omicron variant, can be explained by RdRp’s template-switching function. Subsequent sequencing of the COVID-19 Pfizer-BioNTech vaccine showed an RNA variant frequency of about one in 5,000, implying that majority of the vaccine transcripts generated in vitro by T7 phage RNAP contain a variant.

On the whole, these findings highlight the exceptional genetic variety of the SARS-CoV-2 populations and the diverse trait of an mRNA vaccine fueled by RNAP inefficiency. 


To summarize, the study findings show that the RdRp of SARS-CoV-2 was promiscuous due to nucleotide misincorporation and faulty template flipping, both of which were regulated by the same exonuclease. ExoN could be a crucial protein in viral evolution tuning. These findings demonstrate the fundamental biology that drove viral variety and evolution on such a large scale in the SARS-CoV-2 pandemic.

It is yet uncertain what role vaccination heterogenicity plays in the immunological response. The data from the Pfizer BioNTech SARS-CoV-2 vaccine analysis utilizing ARC-seq could explain why mRNA vaccines against COVID-19 provide broader immunity against new strains after boosting. 

tARC-seq variant spectra, when combined with functional investigations and pandemic datasets, can help models anticipate how SARS-CoV-2 will evolve. Ultimately, the current findings add to a growing corpus of medicine and public health studies that promotes mRNA-based therapeutic technology. As mRNA therapeutics gain traction, these findings may aid future COVID-19 vaccine development and research design.

*Important notice

Research Square 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.

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