SARS-CoV-2

Omicron, delta, E484K. What do they mean?

alanmc — Tue, 30 Nov 2021 20:28:09 +0000

Omicron, delta, E484K. What do they mean? alanmc Tue, 11/30/2021 - 12:28 More Blog Posts November 30, 2021

Understanding the alphabet soup of Coronavirus SARS-CoV-2 genome. B.1.1.7, Delta, E484K… What do the numbers (and letters) mean?

News reports on Covid and the virus responsible for the infection, SARS-CoV-2, is on the news with plenty of science-speak numbers and acronyms. But because these acronyms are usually not part of the ‘news’ being covered in the story, exactly what those codes mean is rarely explained. For example, former FDA Commissioner Scott Gottlieb recently tweeted:

“UK reported its biggest one-day Covid case increase in 3 months just as the new delta variant AY.4 with the S:Y145H mutation in the spike reaches 8% of UK sequenced cases. We need urgent research to figure out if this delta plus is more transmissible, has partial immune evasion?

Delta, AY.4, S:Y145H from Gottlieb’s tweet are all opaque to most readers, (we presume they know UK refers to United Kingdom…), and clearly, the urgency of this tweet demanded attention be focused on the spread and virulence of the then-new worrisome strain (“Delta Plus”) rather than a mundane explanation of the acronyms. The delta plus strain includes the K417N mutation, which may increase the virus strain’s ability to reinfect survivors of earlier Covid strain infections.

and

“…a delta sublineage newly designated as AY.4.2 is noted to be expanding in England… This sublineage is currently increasing in frequency. It includes spike mutations A222V and Y145H." (https://www.cnbc.com/2021/10/20/uk-doctors-call-for-return-of-covid-restrictions-new-mutation-watched.html)

SARS-CoV-2 genome

The genome of the coronavirus responsible for Covid, technically called SAS-CoV-2, is a ring of RNA almost 30,000 bases long. The bases are like a long string of letters spelling words, but in this case, RNA uses only 4 letters (A,U,C, and G) and the words spelled out by the exact sequence of letters in structural genes are instructions for the infected human cell to make specific kinds of proteins. In the structural gene "coding" portion of the genome, each three RNA bases, called a triplet, is like a word calling for a specific amino acid. For example, if the RNA triplet base sequence is AUG, that calls for the amino acid methionine, which is added to the growing chain of amino acids that eventually becomes a functional protein.

The SARS-CoV-2 genome spells out about two dozen different proteins, many of which are important in the infection process or the severity of the resulting illness.

One example is the “spike” protein, which sticks out of the virus particle like points on a crown (and hence the name ‘coronavirus’). The spike protein is responsible for the virus docking with their target human cells, especially the ACE-2 cells) to start the infection process. The Spike protein is also the target for current mRNA based vaccines.

Mutations are permanent changes to the base sequence of letters in the genome, whether the genome is RNA (like coronavirus and many other viruses) or DNA (like other viruses, and all other living things, including humans). Mutations happen in all living things and can be induced by certain chemicals, environmental conditions, or just spontaneously. Mutations can affect a single base, or several bases, or even very long stretches of bases, and can involve deletion of the base(s), or changing a base from one letter to another, or duplication of the base(s), or inversion, insertion of additional bases, or virtually anything that can go wrong with the genome.

Many known mutations in SARS-CoV-2 are single base changes, called point mutations. Because the viral genome is short compared to other living things, the mutation of a large number of bases will likely render the virus weak or incompetent, effectively killing it off as a pathogen. Any quickly growing population (not just viruses) will tend to generate more mutations, and the bigger the population, the more mutations will accumulate. At least some of these mutations will likely make the pathogen even more virulent.

While this mutation stuff is fascinating for molecular geneticists like me, most people just want to know how they relate to Covid. Well here it is— each mutation has the potential to increase infectivity, or severity of illness, or evade antibodies, so scientific management of Covid requires knowing each one precisely, which requires providing names. Each new variant or strain carries one or more mutations in the genome. The naming convention started haphazardly, based on the lab which initially identified and characterized each mutation, or the geographic source where the strain was first identified. As identification and documentation of variants increased this practice became unwieldy and prone to ambiguity and misinterpretation, so WHO (World Health Organization) took over to standardize the naming procedure, using Greek letters.

Under WHO, the identity of the first group of “variants of concern” (i.e., those strains with potentially increased pathogenicity, either in infectivity or increased severity of illness potential) went from B.1.1.7 to Alpha, B1.351 to Beta, P.1 to Gamma and B.1.617.2 to Delta, the first four letters of the Greek alphabet. Omicron (also known as B.1.1.529 under the old nomenclature system) is the 5^th “Variant of Concern” and undoubtedly will go well beyond.

Each Greek letter refers to a known variant strain with identified mutations in the genome. Each variant of concern has multiple mutations in their RNA sequence, and specifically in sequences providing the recipes for Spike and other structural proteins involved in pathogenicity. That is, mutations in the gene for the spike protein can lead to a strain with spike proteins better able to dock with human target cells (and thus increase infectivity) or spike proteins less susceptible to mRNA vaccine antibodies that recognize specific parts of the spike protein. Omicron, for example, has over 30 mutations in the spike protein gene alone. Note, however, that the absolute number of mutations does not correlate with altered pathogenicity. A single mutation at a particular location on the gene converting one specific amino acid might have more impact than 50 mutations scattered elsewhere. Omicron carries several mutations, including base substitutions resulting in amino acid substitutions, base deletions, base insertions, and more. Some of these are especially worrisome because they are known to influence pathogenicity.

Scientists need a means to identify those specific mutations within the Greek letter strain designation. The exact amino acid sequence of a given protein is determined by the exact base sequence of the respective gene. If a mutation in the gene's RNA sequence changes, say, converting a G to an A, the resulting protein might have a crucial amino acid change. So, for example. E484K refers to the Spike protein’s 484th amino acid in the protein chain. The amino acid glutamine (abbreviated ‘E’) at that exact location in the ancestral strain is replaced by the amino acid Lysine (abbr. ‘K’). This apparently small difference of one amino acid in the spike protein can have grave consequences, as this mutation seems to help the virus evade immune responses, including the protective effect of vaccines. Importantly, this E484K mutation is found in Beta, Gamma and Delta. Each mutation causing a change in the amino acid sequence of proteins involved in pathogenicity must be carefully scrutinized in each new strain as they arise. The best defense against new, potentially pathogenic mutations is to limit the population of viral particles. That is best achieved by vaccinations, masking and social distancing.

Gene map of common SARS-CoV-2 Variants, with Spike protein gene magnified. Detail from https://www.news-medical.net/news/20211122/Interferon-beta-versus-the-SARS-CoV-2-Delta-variant.aspx

More info:

https://www.newsweek.com/delta-ay-variant-ay4-2-urgent-research-scott-gottlieb-fda-which-us-states-uk-1639842

https://www.ncbi.nlm.nih.gov/gene/43740568

https://www.nytimes.com/interactive/2021/health/coronavirus-variant-tracker.html

https://www.newsweek.com/delta-ay-variant-ay4-2-urgent-research-scott-gottlieb-fda-which-us-states-uk-1639842

https://www.cdc.gov/coronavirus/2019-ncov/variants/delta-variant.html?s_cid=11512:covid%20delta:sem.ga:p:RG:GM:gen:PTN:FY21

https://www.sfchronicle.com/health/article/What-we-know-about-AY-4-2-a-delta-subvariant-16544024.php

https://pubmed.ncbi.nlm.nih.gov/33532796/ (E484K mutation)

https://en.wikipedia.org/wiki/Variants_of_SARS-CoV-2

https://www.bmj.com/content/372/bmj.n359 (E484K variant impact on immune response)

https://www.sciencealert.com/how-concerned-should-you-be-about-ay-4-2-delta-subvariant-an-expert-explains (AY-4-2 variant)

https://www.science.org/doi/10.1126/science.abl9463?fbclid=IwAR3CQnDova5tnhXqkK1BmJJXrfjmHnL4NlC4Q8ckV_T2bF52ECRKIifs8j0

https://www.news-medical.net/news/20211122/Interferon-beta-versus-the-SARS-CoV-2-Delta-variant.aspx (Figure 2)

https://covariants.org/variants/21K.Omicron

Covid-19: Sound policy on social distancing demands sound science

alanmc — Tue, 21 Apr 2020 23:24:16 +0000

Covid-19: Sound policy on social distancing demands sound science alanmc Tue, 04/21/2020 - 16:24 More Blog Posts April 21, 2020

Effective policies to fight Covid-19 require policymakers abide by the advice offered by qualified scientists using valid scientific data. Georgia Governor Brian Kemp, for example, put Georgians at risk by ignoring experts advising that the virus could spread by those infected but not showing symptoms of Covid-191. The price for Governor Kemp’s ignorance was paid by innocent Georgians.

Scientists worldwide are working intensively and extensively to collect the scientific data and evidence to inform policymakers (at least those willing to listen) drafting policies to mitigate the damage from SARS-CoV-2, the virus responsible for Covid-19. Among the crucial questions:

Can people infected but not showing symptoms shed viable virus to infect others?

This was the question Governor Kemp failed on. Unlike most other questions, the answer to this one is a fairly straightforward ‘Yes’ or ‘No’. And the correct answer, Yes, was evident early on.

What is the lag period between infection and appearance of usual symptoms (fever, cough, breathing difficulties)?

The lag period sets the range for establishing mitigation strategies. If we don’t know this duration, we can’t calculate appropriate quarantine or self isolation periods after contact with a known carrier. If we calculate too short, and release an asymptomatic patient too early, he or she can go out to unknowingly inoculate others. Similarly, if we relax controls too soon, asymptomatic people can inadvertently initiate a resurgence, or “second wave” of the contagion. Knowing that it takes only one infected patient released too early to start a new wave makes the answer to this question crucial to controlling the plague. How many waves or resurgences are we as a society willing to tolerate?

How many others, on average, will an infected person infect?

This is the famous “R0” (“R-nought’) question, used to estimate how contagious the pathogen is. If the value is high, it means rapid spread and distribution. Seasonal influenza has an R0 of 2 to 3, meaning a person with the 'flu will pass it on to two or three others, on average. Measles is over 12. The estimate for SARS-CoV-2 is about 5.7, so a Covid-19 victim will infect, on average, five or six other people, each of which will also go on to infect five or six others.

How far can viral particles travel from an infected person to successfully infect another person?

Scientific analysis is needed to calculate this distance to inform effective social distancing. The current recommendation, based on estimates, in the USA is six feet, in Europe and elsewhere it is a bit larger, two meters. Is this distance sufficient to minimize contagion? Or is it unnecessarily distant? More data are required to gain confidence in the recommendation.

Getting reliable answers to these latter questions has been difficult for several reasons, not least of which is the rapid spread of the plague, overwhelming epidemiologists (specialty scientists who study the onset and spread of contagions) as well as physicians, nurses and other medical professionals dealing with a sudden tsunami of sick people. Trying to identify “Patient Zero”-- the first victim -- in a given location has been complicated by the sheer numbers of patients, their various prior and subsequent contacts, and the uncertainty of the lag period between infection and appearance of symptoms.

Now, a new study2 (although not fully peer reviewed) sheds some light and data to help answer these questions. Dr Lu et al. tracked down the "Patient Zero" in an initial outbreak to a family having lunch at a restaurant in Guangzhou, China.

Briefly, on January 23 a family showing no symptoms departed Wuhan (the origin of the pandemic) just before a lockdown closed that city, and traveled to Guangzhou, a city previously devoid of Covid-19. Five apparently healthy members of the family went to lunch at a local restaurant next day and sat at a round table (Table “A”) between two other tables set about three feet apart (see Figure). On the left, a family of three occupied Table B, spending 53 minutes adjacent to the family from Wuhan at Table A. On the right, a family occupying Table C stayed for 73 minutes adjacent to the Wuhan family’s table. Later that same day, January 24, one of the diners from Wuhan sitting at Table A ("Patient Zero", A1) started coughing and developed a fever. Subsequently, nine others lunching at Tables A, B and C also contracted Covid-19. The five victims at Tables B and C had no other opportunity to contract the virus other than via the Wuhan family they shared the lunch restaurant with on January 24, providing a scientifically solid “anchor” for the time and place of inoculation. It also confirmed that an asymptomatic carrier can indeed infect others.

The time and place anchor provides a basis for calculating the lag period between infection and onset of symptoms. The five showed symptoms beginning January 27, 31 (Table C), and (Table B) February 1, 5 and 5 (although it’s possible these latter two were later infected by their Tablemate who showed symptoms February 1st). Thus, the lag period was 3 days, 6 days, 7 days and (possibly) 11 days. These data support the current policy foundations of 2 to 14 days for onset of symptoms as a reasonable quarantine period after possible infection.

Less reliable is the R0 calculation, as we don’t know how many others were infected by the initial case. But it was at least three (and possibly five) victims from Tables B and C at that one lunchtime encounter alone. In addition, four others at Table A later contracted Covid-19, but we cannot be sure when or from whom they were inoculated, so they cannot be included in the R0 calculation.

The fourth question, travel distance of viral inoculum, is confounded here because an air conditioner over Table C constantly blew air over all of the tables and so mixed the air. Nevertheless, all victims of the lunchtime distribution were sitting at the same or adjacent table as the initial victim. Of the 83 others in the restaurant that lunchtime, no other diners or workers, including those at nearby but not adjacent tables, contracted Covid-19. Clearly, some victims, particularly those at Table C, were further than six feet away-- possibly as much as 12 feet, although exact measurements were not recorded.

Questions arise from this study. How did Patient A1 infect the others if she wasn’t coughing? If the pathogen was solely in her breath, how did her virulent breath infect those at Table C when the air conditioner was blowing air away from Table C? What were the differences in severity of the disease among these victims? How long were they ill? Are they all recovered now?

This small study helps us understand the dynamics of SARS-CoV-19 spread and Covid-19 onset. As data from additional such studies accumulate, scientists will continue to refine, modify and re-set recommendations for public policy with increasing confidence.

But in the meantime, considering the fact that asymptomatic carriers can infect others, the long lag time of up to 14 days between infection and appearance of symptoms, and the high R0, it remains irresponsible for policymakers to relax social distancing rules until at least 14 days have passed since the last case resolves. No matter what the ‘official’ policy may be, I will maintain rigorous social distancing and stay at home for a full 14 days after the last confirmed case in my community. All it takes is one asymptomatic carrier to rekindle a second wave insurgence of Covid-19 and we're all back to square one.

The Guangzhou restaurant layout, showing the three tables involved at lunchtime on January 24th, with the seating arrangement of the victims, along with the dates they became symptomatic. The air conditioner airflow, from over Table C, is also depicted.

Citations and Links

1. https://www.nbcnews.com/politics/politics-news/georgia-gov-brian-kemp-admits-he-just-learned-asymptomatic-people-n1174976

2. Lu J, Gu J, Li K, Xu C, Su W, Lai Z, et al. COVID-19 outbreak associated with air conditioning in restaurant, Guangzhou, China, 2020. Emerg Infect Dis. 2020 Jul [date cited]. https://doi.org/10.3201/eid2607.200764