Variants of Concern
Demystifying the coronavirus mutants
Alpha, Beta, Gamma, Delta, and Omicron: if we would have said these five letters five years back and asked you to connect them, your most probable response would’ve been, ‘it’s all Greek to me!’ But now, since the start of 2020, we’ve seen how alpha and beta swept the world and drove it into lockdown and how delta ravaged the population and led to a second lockdown and the deaths of many close to us. In this article, we explore how their names came to be, how research on the covid genome is carried out, and what the latest addition to this family, Omicron, holds for us.
Basics: How Viruses Mutate
The central concept behind virus mutation is their leanness: in Layman’s terms, viruses are the simplest living creatures you can imagine: all they’re made up of is a strand of DNA/RNA called the genome, which encodes the information about the virus, such as its size, shape, behavior, which cells it would infect and how often it would reproduce. It also contains a protein coat that protects the genome, called the capsid. A single unit of the virus is called a virion.
When a virion reproduces, there is a possibility that its genome is not a perfect copy of itself. In this case, whatever changes occur to the genome during reproduction are called mutations. Since the virus’s behavior is dependent on the genome, mutations can lead to significant alterations in the characteristics of the virus itself.
How do we track virus mutations?
To track the virus mutations, one needs to have detailed information about all the variants that a population in the particular region is affected. This is not as easy as it sounds. Genome sequencing is a tedious process and should be performed with great care and maximum precision possible. When we were hit by the pandemics in the years prior, it was impractical to conduct tests for all the people walking on the face of this earth, let alone perform genome sequencing of all their samples; hence sequencing individual samples for the entire population was utterly out of the question.
Fortunately, COVID doesn’t mutate as frequently as other viruses, such as influenza. If a mutation causes the virus to become more harmful (spread faster, have deadlier symptoms, etc.), it would be noticed more quickly. This implies that the deadliest variants would simply bubble up until they’re concerning, and then they would be tested and sequenced.
Another point regarding mutations is that mutations occur only when the virus reproduces. A simple yet efficient way to prevent the mutations would be to break the reproduction chain and prevent the virus from spreading. Conversely, this implies that the virus would mutate much more rapidly in case of an infection wave. With the overloaded infrastructure and the rapid increase in the number of mutations, sequencing virus mutations and capturing all the mutations would become grueling. This brings us to the next point: Do we need to sequence all the variants? Or could we rely on other nations with better infrastructure and/or lower infection rates to sequence the genomes and then collaboratively use the data.
The answer to the first question is conflicting: We would need to sequence as many samples as possible to understand the spread of various variants in the nation. However, the second suggestion provides much hope: genomes are merely sequences of characters, and unlike 100 years back when the Spanish flu hit, we possess the ability to transfer data almost instantaneously. Having information available about the strains of COVID would help research and prevention immensely.
Presently, there are three major systems for tracking COVID genomes: GISAID (Global Initiative on Sharing All Influenza Data), Pango, and NextStrain. In addition to containing millions of genome sequences, all these systems also include tools for naming, visualizing, and analyzing the data.
The centralization of the three systems has led to the establishment of nomenclature rules to make naming strains and/or their variations simple and more straightforward. It’s hard to come up with a nomenclature system, and it makes it harder for other researchers to learn a new nomenclature system.
NextStrian and GISAID use a Clade-based system, wherein there’s a hierarchical arrangement of the various genomes. One genome is either the parent or the child of another genome. On the other hand, Pango uses a Lineage-based system, wherein genomes are classified iteratively (e.g., A, then A.1, then A.1.1, and so on) and broken off if the hierarchy exceeds four steps (e.g., A.1.1.1 would become C.1). There are two main lineages, A and B (as of Rambaut’s original paper), and all others would be their derivatives. Quoting GISAID: “while Pango lineages provide more detailed outbreak cluster information, the other two nomenclatures offer a large-scale overall view of clade trends and all are in good overall agreement.”
The Pango Lineage System
The naming conventions followed above are quite a mouthful for anyone but epidemiologists. To simplify them, there are a few classifications that the WHO has made: firstly, variants are classified into variants of concern, variants of interest, and variants under monitoring. A variant of interest is a variant that changes a virus characteristic significantly: transmissibility, disease severity, immune escape, etc. A variant of interest also has the potential to cause a significant spread of the virus in multiple clusters. A variant of concern is a variant of interest that has the potential to become a global health hazard: causing new waves, significant transmission, and higher mortality rate. A variant under monitoring is simply a variant that could become a variant of interest in the near future. Therefore, a variant hierarchy is created based on the severity of infection caused by that variant.
With all the background so far, we finally come to the naming scheme that most of us would have seen in newspapers and online articles: the greek letter naming system. This is now fairly simple to understand: the WHO assigns a greek letter to every variant of concern and variant of interest. There are currently five variants of concern:
Ɑ,β,ɣ,δ and the latest, o (that’s an omicron, not an o). In addition, there are two variants of interest: λ and μ, and fifteen variants under monitoring. You might have encountered other variant names, such as ‘Delta Plus’ and ‘Alpha Killer’ (okay, we made that one up). These are merely variations of the four already established lineages.
Variants of interest and variants of concern need not be constant; if a variant of concern becomes less of a concern, then it may be shifted down in priority to become a variant of interest. If a variant of interest is no longer interesting, it may simply become a variant under monitoring. Also, variants under monitoring are not assigned greek letter names (unless they were previously variants of concern)
It’s interesting to note that the greek letter naming system was introduced in Late May 2021: this coincided with the second wave in India, and the δ and δ+ variants were primarily responsible for this wave (as shown by this lineage vs. time chart, courtesy the Vinod Scaria Lab), which is why they received so much media coverage at that point.
This helpful table, taken from CoVariants, shows the various lineages and the different naming conventions followed.
Note: The phylogeny graph has not been updated since June, hence the omicron variant is not visible there. We couldn’t find an updated version specific to India anywhere else.
The Way Forward
Similar to the nomenclature chapter we had at the start of our Organic chemistry studies, In this article, we’ve hardly scratched the surface of virology. The genome databases help epidemic prediction and drug development immensely, and without them, we wouldn’t have been able to develop vaccines and overcome the pandemic at the rate we did.
The information about omicron is mixed at the moment: while some pundits claim it’s for the better, due to the non-lethal nature and high transmissivity of the virus, others claim that current vaccines wouldn’t work and we would need booster shots to ensure immunity from this mutation.
To Conclude, Here’s a chart showing the proportion of the various variants vs. time in India. Correlating this with the timing of the waves would now present a broader perspective, one from the side of the virus rather than ours.
We all have witnessed the devastation of the second wave of covid and how the new variant omicron has already knocked on our doors. We all need to take all the essential measures to keep ourselves and our loved ones safe. Make sure you Stay Alert, Stay Safe!
Disclaimer: According to the authors, the information presented in this article is scientifically correct and has been taken from verified sources. Although we have done our best to make the article error-free, if you do find any errors, scientific or otherwise, please reach out to the authors at firstname.lastname@example.org.