The Raging Evolutionary War Between Humans and Covid-19

The race is on On. Vaccines against the virus that causes Covid-19 are piercing shoulders around the world, the tip of the subcutaneous spear of a year-long scientific triumph. But that protein virus, like all things that infect humans and make them sick, jukes and evades.

Virology vs Epidemiology. Vaccinology vs Evolution. Mutation versus mutation, transmission versus infection, virus versus vaccine. Get started! Your! Engines! The past (horrible, tragic, not-good, really bad) year may have seemed like a straightforward fight between scientists and a virus to find new drugs and vaccines. But this wasn’t just a stand-up fight; it was also an insect hunt – a subtle push-pull over a dozen different vectors. Viruses aren’t exactly living, but they still follow the same rules as any living thing on Earth: adapt or die. Understanding those more occult forces – how viruses evolve within us, their hosts, and how they change the way they move from one person to another – will define the next phase of the pandemic.

It’s easy to panic about new variants of the SARS-CoV-2 virus, with their science fiction nomenclature. There is B.1.1.7, which seems to be an expert in infecting new people. And you have B.1.351 and P.1 – maybe not better at host-to-host transmission, but better at evading an immune response (a natural one, or the kind that elicits a vaccine). Some of the immune-escaping ones share the same single mutation, even if only distantly related. That, as the saying goes, is life. “The way the virus evolves, the fundamentals of evolution are the same. What’s different is that it’s happening on a very, very large scale. There are just so many people who are infected, and each person has a lot of viruses in them. So there are many opportunities for the virus to make mutations and try new things, ”said Adam Lauring, a virologist at the University of Michigan who studies viral evolution. “Every now and then one of them rises. It is a rare occurrence, but if the virus has so many possibilities to play this out, it will happen more and more often. In other words, this is an epidemiological game as well as an evolutionary biology.

So while it may seem like these variants have some sort of evil purpose – make people sicker, kill all people! – that’s not what’s going on. Viruses don’t want anything; they are just verbs. Infect, reproduce, infect. A virus that kills too efficiently does not become a virus for very long, as dead hosts cannot walk around and breathe on uninfected but sensitive suckers. So one hypothesis says that these successful mutations are usually changes in the way the virus infects. That is, they improve the way the virus gets into a human, or gets into a human cell, or reproduces in that cell (because the more virus a person makes, the more they shed, and the more likely it is to another person).

That’s probably why all of these similar variants seem to be popping up all at once and quickly. Viruses are just little blobs of proteins wrapped around large molecules of code, genetic material. In SARS-CoV-2, that material is RNA. And some viruses make mutations appear more often than others.

Viruses evolve because they reproduce – in fact, that’s pretty much their whole thing – and mistakes creep into that genetic material. Over the generations, those random or “stochastic” errors sometimes make the virus do its thing better; sometimes they make it worse. That is, the conditions of a virus’s life, or kind of life, play out against random changes in the code that underlies its genes. (SARS-CoV-2 appears to mutate at about the same rate as other RNA viruses, even though, like other coronaviruses in its family, it has a built-in error correction mechanism. It needs it because the genome is so large, relatively speaking. – three times the genome in HIV, the virus that causes AIDS, for example. “Without proofreading, it would likely cause too many mutations per virus replication event to remain viable,” said Katrina Lythgoe, an evolutionary epidemiologist at the Big Data Institute. Oxford University. That kind of genomic suicide is called crossing the ‘threshold of catastrophe in error’.

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