WSJ: There's scientific evidence of the Wuhan lab-leak theory -- in the COVID-19 virus itself

AP Photo/Ng Han Guan

Was Brett Giroir correct after all? Perhaps even more so than he knew. According to two scientists writing at the Wall Street Journal yesterday, the COVID-19 virus bears a clear fingerprint of genetic manipulation characteristic of gain-of-function research. In fact, Steven Quay and Richard Muller argue, that fingerprint has been evident from the first full translation of the COVID-19 genome.

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Note well that this is argument, not necessarily evidence, however:

In the case of the gain-of-function supercharge, other sequences could have been spliced into this same site. Instead of a CGG-CGG (known as “double CGG”) that tells the protein factory to make two arginine amino acids in a row, you’ll obtain equal lethality by splicing any one of 35 of the other two-word combinations for double arginine. If the insertion takes place naturally, say through recombination, then one of those 35 other sequences is far more likely to appear; CGG is rarely used in the class of coronaviruses that can recombine with CoV-2.

In fact, in the entire class of coronaviruses that includes CoV-2, the CGG-CGG combination has never been found naturally. That means the common method of viruses picking up new skills, called recombination, cannot operate here. A virus simply cannot pick up a sequence from another virus if that sequence isn’t present in any other virus.

Although the double CGG is suppressed naturally, the opposite is true in laboratory work. The insertion sequence of choice is the double CGG. That’s because it is readily available and convenient, and scientists have a great deal of experience inserting it. An additional advantage of the double CGG sequence compared with the other 35 possible choices: It creates a useful beacon that permits the scientists to track the insertion in the laboratory.

Now the damning fact. It was this exact sequence that appears in CoV-2. Proponents of zoonotic origin must explain why the novel coronavirus, when it mutated or recombined, happened to pick its least favorite combination, the double CGG. Why did it replicate the choice the lab’s gain-of-function researchers would have made?

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Keep a skeptical mind here for now, just as with claims that the lab-leak theory has been “debunked.” This is not a peer-reviewed study, but an opinion piece by two scientists. Neither of them appear to be epidemiologists, according to the WSJ’s bio; one is a founder of a therapeutics company, and the other a physics professor at Berkeley, as well as a “former senior scientist at Lawrence Berkeley National Laboratory.” Certainly both would have enough skill to recognize genomes and parse sequences, but it’s not at all clear that they have the requisite expertise for full context of that data.

Besides, this is more of a circumstantial argument than a full smoking gun. The response to this could be simply that this was the first known coronavirus to develop the double CGG sequence naturally. Alternatively, one could argue that the double-CGG sequence might be found in nature, but in viruses that we haven’t yet sequenced. That seems a bit less likely, given how virulent the double-CGG sequence apparently is to humans, but it’s still possible. And if the pair doesn’t have broad expertise in this field (although they might) then this might not be as “damning” as it appears.

The same may apply to their bolstering argument:

There is additional scientific evidence that points to CoV-2’s gain-of-function origin. The most compelling is the dramatic differences in the genetic diversity of CoV-2, compared with the coronaviruses responsible for SARS and MERS.

Both of those were confirmed to have a natural origin; the viruses evolved rapidly as they spread through the human population, until the most contagious forms dominated. Covid-19 didn’t work that way. It appeared in humans already adapted into an extremely contagious version. No serious viral “improvement” took place until a minor variation occurred many months later in England.

Such early optimization is unprecedented, and it suggests a long period of adaptation that predated its public spread. Science knows of only one way that could be achieved: simulated natural evolution, growing the virus on human cells until the optimum is achieved. That is precisely what is done in gain-of-function research.

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It’s certainly an interesting argument. If their description of the genome is accurate, it would explain why Giroir was so skeptical of zoonotic transfer as an origin for COVID-19. It could also explain why researcher Kristian Andersen raised the possibility of a lab leak in Wuhan early in the pandemic. However, if this was truly a “damning” smoking gun, why did Andersen become skeptical of that explanation later?

As for the “evolution” point, that also cuts both ways. Allahpundit pointed out in the Giroir post that the point of gain-of-function research is to emulate natural evolution to predict and protect against zoonotic transfer of potentially dangerous viruses. It’s essentially a time-warp for one potential path of evolution. Again, this second argument looks like circumstantial evidence of an engineered virus (if accurate), but it might also have been evolved in nature.

And one last question: if this was such an obvious smoking gun, why hasn’t it come to light before now? The genome has been widely circulated among epidemiologists since February 2020, around the world. If this was that significant as evidence of lab manipulation, it’s certainly odd that no one has pointed it out until now.

Perhaps this sequence issue could explain why Giroir and Redfield suspect a lab leak, or at the very least remain skeptical of zoonotic transfer as an explanation. To get to the bottom of this argument, however, we would need to see a real peer-reviewed study by people with the expertise necessary to get it done right. Op-eds are useful for raising questions and demanding real answers, but shouldn’t be taken as scientifically conclusive, let alone “damning.”

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David Strom 10:30 AM | November 15, 2024
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