Arcturus: The Coronavirus Variant That Is Taking Over the World

The Coronavirus variant strikes back: How it is forcing the world to mask up again.

Milton Simba Kambarami
Microbial Instincts

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Photo by Tai's Captures on Unsplash

This article consists of two main sections and a recap section: the first section provides a review of the existing literature on the Arcturus variant, and the second section presents the results of my own analysis and some insights on this coronavirus sub-variant, which has been scarcely studied in the scientific community.

Section 1: Introduction

The COVID-19 pandemic has been driven by various variants of the SARS-CoV-2 virus, but since the end of 2021, the omicron variant has been the dominant strain causing havoc globally.

However, not all omicron variants have the same natural fitness, which determines their evolutionary success.

One of the most recent and concerning omicron sub-variants is Arcturus, also known as omicron XBB.1.16. It emerged in January 2023 and was named after the brightest star in the northern celestial hemisphere, reflecting its rapid spread and high transmissibility.

According to WHO, Arcturus is the most infectious omicron variant yet and has been classified as a variant of interest. Arcturus is a descendant of another omicron sub-variant called Kraken (omicron XBB.1.5), which was the predominant strain globally until April 2023.

Arcturus has a higher estimated growth advantage in human populations than its parent sub-lineages and has increased 13-fold in India in less than a month. It has also caused a surge in COVID-19 hospitalizations in India and other countries according to the source.

So far, there is no evidence that Arcturus can evade vaccines or antibodies from prior infections, and its clinical outcomes and severity are not different from other omicron sub-lineages.

However, its high infectivity poses a serious threat to public health and requires close monitoring and preventive measures.

Viral evolution: lessons from immunodeficiency viruses

I have observed a trend in the evolution of viruses, based on my extensive studies on them.

Viruses that have recently adapted to a new host (juvenile viruses) tend to be more virulent and lethal, as they maximize their reproductive success. This may be because they face less competition and more susceptible hosts.

However, as the viral populations evolve over time, they tend to become less virulent and more benign, as they reach a balance with their host. This is because excessive virulence can reduce the availability of hosts and increase the risk of extinction.

This trend can be illustrated by the case of simian immunodeficiency virus (SIV), which crossed the species barrier and caused human immunodeficiency virus (HIV) in humans.

In the 1980s, HIV was highly fatal and caused many deaths. Although this was partly due to the lack of effective treatments and prevention strategies, it was also due to the high virulence of the juvenile virus.

Over time, HIV has become less lethal and more manageable, not only because of the advances in medical research, but also because of the adaptation of the virus to its human host.

This is supported by the fact that the human immune system does not develop lasting immunity against HIV, unlike SARS-CoV-2. Moreover, some simians that carry SIV do not show symptoms, as they have co-evolved with the virus for a long time.

However, this trend may not apply to all organisms or all viruses, as many factors influence the evolution of virulence. Viruses also have different rates of mutation and recombination, which affect their genetic diversity and adaptation potential.

Viral evolution similar to human development

Viral evolution can also be compared to human development. To make this comparison meaningful, I am not referring to a single virus growing up, but to generations of viruses as if they are an individual organism.

From December 2019 to the end of 2020, SARS-CoV-2 accumulated a number of mutations compared to the changes in its genomic structure in 2021. We could liken this to a pubescent stage, where the virus underwent rapid and diverse changes trying to adapt to its new environment.

By November 2021, there had been several SARS-CoV-2 variants that competed for dominance, some being more prevalent in certain regions than others, such as alpha, beta and delta.

However, from November 2021 until now, there has been one SARS-CoV-2 variant that has remained dominant, omicron, resembling a stable young adult. This is the phase that the SARS-CoV-2 virus is in right now.

Young adults may occasionally revert to pubescent behaviours when triggered by some stimuli, which is analogous to the emergence of new sub-variants with minor mutations.

However, these do not significantly alter the genetic structure of the virus.

Section 2: Bioinformatics Analyses

As a bioinformatics scientist, I wanted to understand the mutations and the statistics behind the growth advantage of Arcturus.

I used a method I developed and documented in this article to analyze the sequences from GISAID, in which I had to hide some of the contents per their terms and conditions. These studies are based on the SARS-CoV-2 S protein.

I found some interesting and unexpected results from the data from India only.

Peaks show sites on the spike protein which are showing strong positive selection / adaptive selection (Image by Author)

Bayes Factor is a tool that helps us estimate the likelihood of a hypothesis being true. For example, we can use it to identify the sites that show strong positive selection in Arcturus.

The graph above shows some remarkable peaks, indicating a high probability of positive selection. Normally, the highest peak I see is around 50, but for Arcturus, one peak reached above 1200.

The table below lists the sites that had strong positive or negative results.

I usually consider sites with probabilities above 0.9 for both positive ‘Prob[alpha < beta]’ and negative selection ‘Prob[alpha < beta]’, but for Arcturus, I raised the threshold to 0.99 for positive selection because there were too many sites to choose from.

This narrowed down the list to four outstanding mutations: Y505H, D142G, T547I and K417N. However, K417N turned out to be a false positive when I checked the sequence alignment again.

Table showing sites with strong negative and positive selection (Image by Author)

Biochemistry of positively selected mutations

I used my biochemistry background to study how amino acid changes affect their interactions based on their different physicochemical properties.

Amino acids are similar in most parts except for the R-groups, which determine their characteristics.

The other parts are involved in forming peptide bonds, which link amino acids into larger molecules called proteins.

Negative selection mutations or as some call them purification mutations are mutations necessitating the stability of the protein, so we won’t discuss a lot about them.

1. Y505H

Image showing the difference in the amino acid R groups of Tyrosine and Histidine (Image by Author)

This mutation occurs on the receptor-binding domain of the spike protein, where tyrosine is replaced by histidine.

I chose to discuss this mutation first because it showed a remarkable peak above 1200.

Some studies have documented this mutation and labelled it as deleterious to the fitness of the viruses that carry it.

However, in the Arcturus, it is the most positively selected mutation. This means the mutation has an adaptive effect rather than a harmful one.

As shown in the diagram above, the amino acid substitution of tyrosine (Tyr) by histidine (His) involves replacing a phenolic group with an imidazole ring.

The phenolic group exhibits weak acidity, whereas the imidazole ring exhibits strong basicity. Consequently, Tyr can be partially or fully deprotonated, while His is fully protonated.

This charge reversal mutation, which is positively selected in the Arcturus sub-variant, implies an increased binding affinity between the spike protein and the hACE2 receptor, possibly mediated by a stronger electrostatic interaction from a fully charged group rather than a weak dipole-dipole interaction from a polar group.

A higher binding affinity confers a higher fitness advantage to the virus carrying this mutation.

2. T547I

Image showing the difference in the amino acid R groups of Threonine and Isoleucine (Image by Author)

The amino acid substitution of threonine (Thr) by isoleucine (Ile) involves replacing a polar hydroxyl group with a non-polar methyl group.

The interaction between residue 547 and the hACE2 receptor is enhanced by the elimination of polarity, possibly due to hydrophobic effects.

According to this source, the T547I mutation is one of the 37 mutations in the spike protein of the SARS-CoV-2 Omicron variant.

It resides in the N-terminal domain (NTD) of the spike protein, which mediates host cell attachment and immune evasion. The T547I mutation may alter the stability and conformation of the NTD and decrease its antigenicity.

However, the precise impact of this mutation on viral fitness, transmissibility and pathogenicity remains uncertain and warrants further investigation.

3. D142G

Image showing the difference in the amino acid R groups of Aspartic acid and Glycine (Image by Author)

This mutation is not surprising as it is one of the most common tricks that the coronavirus uses.

As you can see in the picture above, aspartic acid has a shape that changes when it is in water. It loses a tiny particle called a proton and becomes negatively charged.

Glycine is the simplest building block of proteins and has only a hydrogen atom as its side group. It is much smaller than aspartic acid. So this mutation causes two changes:

1. a change in charge

2. a change in size.

The spike protein has a spot crucial for the immune system to recognize the virus. This spot is made of many parts, including site 142.

The mutation changes this site from aspartic acid to glycine and then back to aspartic acid. This makes it harder for the immune system to detect and attack the virus, leading to more virus particles in the body.

Section 3: Demographics of COVID-19 Infection

1. Age group

Age vs population bar graphs, comparing Arcturus (top) and delta variant (bottom) — Image by Author

The next objective of the analysis was to examine if there was any significant difference in the age distribution of the Arcturus cases.

The results of the analysis are presented in the first graph above. The data are inconclusive but can provide a rough estimate of the situation.

Overall, no specific age group was identified as more vulnerable to Arcturus infection.

However, a comparison with a similar variant may be informative. The SARS-CoV-2 Delta variant caused a COVID-19 wave around the same time in 2021 and was predominant in India, like Arcturus.

The second bar graph shows the statistics of age versus the number of COVID-19-positive patients from the Delta variant.

It appears that Arcturus is infecting more children under 10 years old than the Delta variant, but as mentioned earlier, the infection is spread evenly across all age groups.

2. Gender

Number of individuals per gender infected by Arcturus virus (Image by Author)

The graph above shows that Arcturus is affecting more men than women. I wonder if this is because more men are getting tested for Covid-19 at their workplaces.

This is just my guess and it may be influenced by my background from a different part of the world where more men work outside the home than women.

I tried to find proof of men being more likely to test positive for Covid-19 than women, but I did not find any convincing.

Significance Testing for Gender Distribution

To understand the significance of the difference in males and females who tested positive, I then did a hypothesis testing which is a way of using math to see if the difference seen in the data is real or just due to chance.

I started by making two guesses:

  • The first guess is that there is no difference between how many women and how many men got COVID-19. This is called the null hypothesis.
  • The second guess is that there is a difference between how many women and how many men got COVID-19. This is called the alternative hypothesis.

I then chose a number that tells me how sure I want to be about my answer.

This number is called the alpha level. A common choice in Biology is 0.05, which is to say I want to be 95% sure about my answer. But it can vary depending on your situation. For this analysis, I used 0.05 as the alpha level.

The p-value obtained was much smaller than the alpha level, meaning the first guess is wrong and that there is a difference between how many women and how many men got COVID-19.

Some possible causes for this difference are:

  • There may be biological factors that make women or men more or less susceptible to Arcturus variant.
  • There may be social factors that make women or men more or less exposed to Arcturus variant.
  • There may be measurement errors or biases in how the tests were conducted or reported.

Section 4: Recap…

In this article, I have provided a comprehensive overview of Arcturus, a new subvariant of omicron that emerged in India and has been spreading rapidly around the world, especially in April.

I have explained what Arcturus is, how it differs from other variants, and what it means for the pandemic.

I have also used my expertise in bioinformatics and biochemistry to explain the mutations that make Arcturus more adaptable and infectious.

Finally, I have looked at the data on who is getting infected by Arcturus and what factors may influence its transmission and severity.

Arcturus is a highly contagious and potentially dangerous subvariant of COVID-19 that threatens global health and requires more research and surveillance to understand its characteristics and implications.

If you read up to this end, I believe you have learnt something new from Arcturus. Til’ we meet again.

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