RNA viruses are famous for two distinctive features: genomes composed entirely of RNA rather than DNA, and much higher mutation rates than other viruses. This combination allows RNA viruses to respond rapidly to changes in their environment, including host immunity, making them especially difficult viruses to combat. The best-known RNA viruses are influenza viruses, whose high mutation rates prevent vaccines from granting durable immunity and require new vaccines yearly to combat current strains. The RNA virus creating headlines at the moment is SARS-CoV-2, responsible for current pandemic conditions around the world. Thermo Fisher Scientific is a leader in producing the technologies and reagents needed to unravel the mystery of why RNA viruses behave this way, and recent studies are shedding light on these difficult, peculiar pathogens.
Fidelity Versus Speed: Why Mutation Rates Are High
RNA is, by and large, less stable than DNA, which is a large part of why complex organisms generally have DNA-based genomes. Even double-stranded RNA, as in many RNA viruses, is more fragile than its better-known counterpart. This fragility leads to a higher mutation rate on its own, but RNA viruses also have high replication rates that further increase the chance of errors in replication—that is, mutations—as thousands of copies are produced.1 Some RNA viruses even have specific genetic pathways that induce mutations under stress, such as deaminases that transform nucleic acids, to specifically cultivate genetic diversity when the virus’s current genetic makeup is not ideally suited to its environment.2 Fitzsimmons et al., for example, used Thermo Fisher Scientific tools and reagents to study polioviruses with qPCR (Power SYBR Green PCR Master Mix) and Sanger sequencing (Quanti PicoGreen dsDNA), revealing that polioviruses have this capacity.3
That said, current evidence suggests that a high baseline mutation rate in RNA viruses is more often an accident of a high replication rate rather than being consistently adaptive in its own right.3 Eckerle et al.used an Applied Biosystems 3730 ABI Sequencer to show that some RNA viruses (including coronaviruses) have enzymes devoted to slowing replication to increase fidelity, which reduces mutation rate, contrary to RNA viruses’ reputation for mutating at any opportunity.2 After all, most mutations are deleterious, even in viruses. Mutation rates can also be affected by host-virus interactions, with some viruses having higher mutation rates in some host species than others,4 and some treatment regimens lead to temporary spikes in viral mutation rates, including for SARS-CoV-2.5
Mutation Rates and SARS-CoV-2 Variants
To combat the pandemic, massive efforts have been underway to produce SARS-CoV-2 vaccines. Since most of the vaccines are made against the spike protein, understanding the effects of S-gene mutations on viral lifecycle and interaction with antibodies is critical for predicting the efficacy of candidate vaccines. For example, several highly transmissible strains (B.1.1.7, B.1.351, and B.1.28) have recently been identified.6, 7, 8 As described above, these variants likely arose due to the random mutation mutations arising from the viral polymerase, followed by positive selection in human hosts.
One critical question is whether vaccines developed against the reference “wild-type” strain would be effective against these derived strain lineages. In a study recently published by Xie et al., constructs carrying S-gene mutations found in these highly transmissible strains were tested against sera obtained from vaccinations from a “wild-type” strain.9 They found that S-gene mutations found in the highly transmissible strains were still effectively neutralized by the sera in research samples.
Groups are also trying to understand how mutations in the S-gene might influence the virus’s lifecycle and how this relates to vaccine efficacy. In two interesting studies, groups used selective pressure, directed by antibodies similar to vaccines, to characterize S-gene mutations. In the first study, Weisblum et al. constructed GFP-tagged SARS-CoV-2 strains.10 They grew these viral strains in the presence of neutralizing antibodies, selected mutants that were resistant to the antibodies, and sequenced the resistant strains using Sanger sequencing. They found these viruses had new mutations in the S-gene, but also demonstrated that they had the same growth kinetics as the starting strain. They therefore concluded that these new mutations bypassed interaction with the neutralizing antibodies but had little to no effect on binding to the ACE2 receptor.
The second study aimed to compare the growth characteristics that two different mutations, the “wild-type” and the dominant D614G mutant Spike gene mutation, confer on SARS-CoV-2 growth.10 Part of this study involved looking at the competitive fitness of the two strains by coinfecting cells with equal amounts of the two strains and determining the dominant genotype in the mixture at different time points. Since they were focused on a particular region of the S-gene, they used Sanger sequencing for the genotyping. They found that the D614G mutation conferred growth advantage relative to the wild-type virus, but that strain was still sensitive to antibodies generated against the wild-type virus. They concluded that this work demonstrates the importance of the D614G variant in spread of the virus, and may have implications for researching vaccine efficacy and interactions with antibodies.
The surveillance and characterization of newly arising strains is therefore critical for staying one step ahead of a moving viral target, especially when designing vaccines. Sanger sequencing is a critical component of that workflow, from verifying the sequence of mutations in artificial constructs, to focusing on new sequences in defined regions of the genome, to genotyping in mixed culture fitness experiments.
A great deal of the effort and expense of vaccine development research is finding target sites, whether on viral genomes or in their proteins, that provoke strong immune responses while also being stable enough that the resulting immunity can last for years. Data on mutation rates are critical to finding these targets, and Thermo Fisher Scientific’s abundance of high-quality sequencing and qPCR tools are available to make this research happen.
For research use only. Not for use in diagnostic procedures.
1. Sanjuán, R., and Domingo-Calap, P. (2016). Mechanisms of viral mutation. Cell. Mol. Life Sci. 73(23):4433–4448.
2. Eckerle, L.D., Becker, M.M., Halpin, R.A., et al. (2010). Infidelity of SARS-CoV Nsp14-Exonuclease Mutant Virus Replication Is Revealed by Complete Genome Sequencing. PLOS Pathog. 6(5):e1000896.
3. Fitzsimmons, W.J., Woods, R.J., McCrone, J.T., et al. (2018). A speed–fidelity trade-off determines the mutation rate and virulence of an RNA virus. PLOS Biol. 16(6):e2006459.
4. Combe, M., and Sanjuán, R. (2014). Variation in RNA Virus Mutation Rates across Host Cells. PLoS Pathog. 10(1).
5. Kemp, S.A., Collier, D.A., Datir, R., et al. (2020). Neutralising antibodies drive Spike mediated SARS-CoV-2 evasion. medRxiv:2020.12.05.20241927.
6. Wise, J. (2020). Covid-19: New coronavirus variant is identified in UK. BMJ 371:m4857.
7. Tegally, H., Wilkinson, E., Giovanetti, M., et al. (2020). Emergence and rapid spread of a new severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) lineage with multiple spike mutations in South Africa. medRxiv:2020.12.21.20248640.
8. Faria, N. (2021). Genomic characterisation of an emergent SARS-CoV-2 lineage in Manaus: preliminary findings – SARS-CoV-2 coronavirus / nCoV-2019 Genomic Epidemiology. January 12. https://virological.org/t/genomic-characterisation-of-an-emergent-sars-cov-2-lineage-in-manaus-preliminary-findings/586.
9. Xie, X., Liu, Y., Liu, J., et al. (2021). Neutralization of SARS-CoV-2 spike 69/70 deletion, E484K and N501Y variants by BNT162b2 vaccine-elicited sera. Nat. Med.:1–2.
10. Weisblum, Y., Schmidt, F., Zhang, F., et al. (2020). Escape from neutralizing antibodies by SARS-CoV-2 spike protein variants. eLife 9:e61312.