Coronavirus seems to mutate much slower than seasonal flu
That could be good news for a vaccine.
When you hear the term "evolutionary tree," you may think of Charles Darwin and the study of the relationships between different species over the span of millions of years.
While the concept of an "evolutionary tree" originated in Darwin's "On the Origin of Species," one can apply this concept to anything that evolves, including viruses. Scientists can study the evolution of SARS-CoV-2 to learn more about how the genes of the virus function. It is also useful to make inferences about the spread of the virus around the world, and what type of vaccine may be most effective.
I am a bioinformatician who studies the relationships between epidemics and viral evolution, and I am among the many researchers now studying the evolution of SARS-CoV-2 because it can help researchers and public health officials track the spread of the virus over time. What we are finding is that the SARS-CoV-2 virus appears to be mutating more slowly than the seasonal flu which may allow scientists to develop a vaccine.
How do sequences evolve?
Viruses evolve by mutating. That is, there are changes in their genetic code over time. The way it happens is a little like that game of telephone. Amy is the first player, and her word is "CAT." She whispers her word to Ben, who accidentally hears "MAT." Ben whispers his word to Carlos, who hears "MAD." As the game of telephone goes on, the word will transform further and further away from its original form.
We can think of a biological genetic material as a sequence of letters, and over time, sequences mutate: The letters of the sequence can change. Scientists have developed various models of sequence evolution to help them study how mutations occur over time.
Much like our game of telephone, the genome sequence of the SARS-CoV-2 virus changes over time: Mutations occur randomly, and any changes that occur in a given virus will be inherited by all copies of the next generation. Then, much as we could try to decode how "CAT" became "MAD," scientists can use models on genetic evolution to try to determine the most likely evolutionary history of the virus.
How can we apply this to viruses like COVID-19?
—Coronavirus in the US: Map & cases
—What are the symptoms of COVID-19?
—How deadly is the new coronavirus?
—How long does coronavirus last on surfaces?
—Is there a cure for COVID-19?
—How does COVID-19 compare with seasonal flu?
—How does the coronavirus spread?
DNA sequencing is the process of experimentally finding the sequence of nucleotides (A, C, G and T) — the chemical building blocks of genes — of a piece of DNA. DNA sequencing is largely used to study human diseases and genetics, but in recent years, sequencing has become a routine part of viral point of care, and as sequencing becomes cheaper and cheaper, viral sequencing will become even more frequent as time progresses.
RNA is a molecule similar to DNA, and it is essentially a temporary copy of a short segment of DNA. Specifically, in the central dogma of biology, DNA is transcribed into RNA. SARS-CoV-2 is an RNA virus, meaning our DNA sequencing technologies cannot directly decode its sequence. However, scientists can first reverse transcribe the RNA of the virus into complementary DNA (or cDNA), which can then be sequenced.
Given a collection of viral genome sequences, we can use our models of sequence evolution to predict the virus's history, and we can use this to answer questions like, "How fast do mutations occur?" or "Where in the genome do mutations occur?" Knowing which genes are mutating frequently can be useful in drug design.
Tracking how viruses have changed in a location can also answer questions like, "How many separate outbreaks exist in my community?" This type of information can help public health officials contain the spread of the virus.
For COVID-19, there has been a global initiative to share viral genomes with all scientists. Given a collection of sequences with sample dates, scientists can infer the evolutionary history of the samples in real-time and use the information to infer the history of transmissions.
One such initiative is Nextstrain, an open-source project that provides users real-time reports of the spread of seasonal influenza, Ebola and many other infectious diseases. Most recently, they have been spearheading the evolutionary tracking of COVID-19 by providing a real-time analysis as well as a situation report meant to be readable by the general public. Further, they enable the global population to benefit from their efforts by translating the situation report to many other languages.
As the amount of available information grows, scientists need faster tools to be able to crunch the numbers. My lab at UC San Diego, in collaboration with the System Energy Efficiency (SEE) Lab led by Professor Tajana Šimunić Rosing, is working to create new algorithms, software tools and computer hardware to make the real-time analysis of the COVID-19 epidemic more feasible.
What have we learned about the epidemic?
Based on current data, it seems as though SARS-CoV-2 mutates much more slowly than the seasonal flu. Specifically, SARS-CoV-2 seems to have a mutation rate of less than 25 mutations per year, whereas the seasonal flu has a mutation rate of almost 50 mutations per year.
Given that the SARS-CoV-2 genome is almost twice as large as the seasonal flu genome, it seems as though the seasonal flu mutates roughly four times as fast as SARS-CoV-2. The fact that the seasonal flu mutates so quickly is precisely why it is able to evade our vaccines, so the significantly slower mutation rate of SARS-CoV-2 gives us hope for the potential development of effective long-lasting vaccines against the virus.
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This article was originally published at The Conversation. The publication contributed the article to Live Science's Expert Voices: Op-Ed & Insights.
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Niema Moshiri is an assistant teaching professor in the Computer Science & Engineering Department at the University of California, San Diego (UCSD). He works on computational biology, with a research focus on viral phylogenetics and epidemiology. He holds a PhD in bioinformatics and systems biology from UCSD and a B.S. in bioengineering from the same institution. He is also affiliated with the Pandemic Response to Emerging Pathogens, Antimicrobial Resistance and Equity (PREPARE) Institute.
By Ben Turner
The mutation rate of seasonal flu is extrapolated from seven to eight years of data while Covid-19's mutation rate is extrapolated from five months of data - (to article's author) is it fair to speculate on the efficacy of a vaccine based on this amount of data?
Selenium deficiency causes inflammatory response in the presence of increased levels of LPS. China is very low in selenium. Sars-Cov-2 appears to be an opportunistic viral infection increasing levels of LPS endotoxin based on concentration of organisms in direct proportion to selenium levels.
Iodine/ selenium is ancient method for destroying biofilms against poisonous reactive oxygen species (ROS) combating oxidative stress able to disrupt biofilm
While you may have some interesting comments and certainly knowledgeable about infectious disease, I would like to present a couple of counter arguments:
1) I looked up photos of electron microscope images of fungus and influenza-like viruses. They appear very similar them. What I'm saying is that you are correct in saying it looks similar, but it would look similar even if it was just the virus.
2) The histoplasmosis comment that it happens in the middle of the US where COVID-19 doesn't appear to be doing as much damage seems inaccurate. Louisiana and Chicago are both in these histoplasmosis endemic areas. Also, overall, the maps of outbreaks of COVID-19 appear to coincide with population maps, so per capita things seem to be progressing equally everywhere in an exponential fashion, which would not indicate a bacterial infection, unless it was a new one we were not aware of. This is actually more like extremely strong evidence against your theory. I have the benefit of foresight as you posted your theory 10 days ago, but just saying.
3) I do not understand the statement about animal to human transcription in a way that seems meaningful to a lay person. Viruses and other infectious diseases are transmitted between human and animal hosts all the time, even through eating meat that isn't well-cooked. Not sure what you're saying, here.
4) Some more evidence against you is your theory about a volcano launching these spores in the air. How much guano would have to be in that cave to disseminate to the entire world. Not to be mean, but that is a pretty laughable theory. With that properly dismissed, we are left with the notion that an extremely large portion of the population eats food from wet markets, or that transmission from mammal to mammal has occurred on a massive scale in a short amount of time. Which is a remote possibility, but not consistent with your argument.
I have been totally frustrated at the use of graphs and charts rather than ignoring the human element. It is more important to use therapy than to develop a vaccine. I don't know what your experience is with Histoplasmosis, but I had systemic histoplasmosis and it was a mixed culture along with bacteria. It was an airborne dust from the tunneling of old chicken houses and it was an airborne dust from the spreading of the litter on fields. It was carried on clothes, etc and transported from one place to another. Hence, the virus could have come from a cave if the scientists believed it was from a bat and the wet markets were an issue and China was in denial about the problem. Wet markets sell bats and many of them come from caves.
Along with many others across the US, I had this covid19 in the summer of 2018 and it was very very serious. This is the second wave because there was no way of identifying the illness that was being experienced in different
areas of the United States in the summer when flu season was over.
So in theory, the virus does mix with or use gram negative bacteria as a medium for budding and the budding is just like budding yeast. Nobody really understand a virus only that is is not considered a living thing because it does not reproduce. But when you look at yeast, it only reproduces when it has a substrate to grow on and then it buds and the buds resemble the virus.
Imagine a petri dish for identification of bacteria. One bacteria swarms over the entire plate. A virus comes along who is attracted to the bacteria and the virus hooks on to the cell membrane and forces his way in. The virus uses the cell to reproduce and out comes a virus - a bud of the cell. The more bacteria that are present, the greater the reproduction of viral buds. The concentration of bacteria, as with dental biofilm, that forms tartar on the teeth is like the petri dish and that makes one person more contagious than the other. The bacterial cell performs like a budding yeast. Common - virus plus a biofilm
You may have looked at maps but did not live in the middle of the horrible contagion that was going on and finally ended by the environmental protection agency in the tunneling of old chicken houses. Imagine the concentration of pathogenic organisms. This is what I think happened with China----
This problem started in China with the pigletts in 2016-2017, not far from the viral lab in China. They probably took the virus to the lab to work on it and it went into a bat and then into a human. It had already started in 2017 and by 2018, it was already the first surge of the virus. I have no doubt that the WHO covered this up - probably a deal they cut with China.
I do not know what China uses as lab animals - in America, we use mice because they have a similar genetic profile. I don't know just how the bat is involved whether the bat gave the disease to the pigs but the virus did come from that lab and I think it was released before 2019. Scientists know very little about viruses. They are unpredictable and controlling a viral contagion with graphs and charts is ridiculous. It may work for bacteria or a fungus like Histoplasmosis, but viral diseases are poorly understood even after years and years of research. Look at China - they are perfect proof.
Your post is very interesting and you seem to have a lot of applicable knowledge. I can understand the frustration of knowing facets of this pandemic others are unaware of. But, I think people are looking at the graphs to understand when it might be safe for them to resume their normal lives so they don't endanger their elderly and immune-compromised relatives. So, the reality is we are in a Catch-22 situation, where the more people trying therapies with infected patients, the more people exposing the people in their life to it. Imagine being a researcher trying out therapies, trying to save thousands of lives, only to infect your mother or father and cause their premature death. That's quite a risk.
The very article here points out searching for a vaccine for COVID-19 is more promising than a vaccine for the flu, because the low mutation rate. I'm not sure why you would be frustrated that this is a possibility for ending the pandemic.