New Evidence for the Lab Origin of Covid-19 By Brian Simpson
A paper, not yet peer-reviewed, has appeared putting the biological case for a synthetic origin of Covid-19, meaning it was made in a lab. The researchers do not investigate who did it, but we know that! I found an article giving an overview of the argument, and even that was complex, and I was a science teacher; but we do have STEM students drop by the blog, so I think they would require a bit more proof than what say, Farmer Bob would be happy with. In a nutshell for readers who will now move on, the Covid-19 virus has the hallmarks of a lab made virus, having various parts just as if it was produced by genetic engineering, and quite unlike what is found in nature, as to get those structures involves doing activities to the sites which is not likely to occur naturally. The details are complex, but for our purposes we can say that the molecular structure of the virus indicates that it was made, like say finding a brick wall, made of bricks, and concluding that someone made it. In this case I think other evidence points to it coming straight out of the Wuhan lab, a “gift” from the CCP, the first shot, or is it jab, in World War III.
https://alexwasburne.substack.com/p/a-synthetic-origin-of-sars-cov-2
“Drs. Valentin Bruttel, Tony VanDongen and I recently released a pre-print providing evidence of a synthetic origin of SARS-CoV-2.
This article is my attempt at a lay summary of what we found, its limitations, and what we can and cannot conclude from our work. I’ll cover the bioengineering methods used to make “infectious clones”, the genomic fingerprints of this tech, what we found in SARS-CoV-2, how we could be wrong, and what to do next.
First and foremost, I want to say: our use of the word “synthetic” derives from “synthesis”. There are methods to synthesize viruses in the lab, and we study those methods. In talking with friends & family, I learned that “synthetic” can have a more nefarious connotation, so I want to clarify that we find no evidence of anything nefarious. We find no evidence of SARS-CoV-2 being a bioweapon (on the contrary, this looks like an accident) or any gain of function work. We find evidence suggesting SARS-CoV-2 may have been synthesized in the lab with known methods, probably for normal pre-COVID research purposes.
Idiot’s Guide to Infectious Clones
"Like “synthetic”, “infectious clone” also has a nefarious sound to it, but I want to dispel that right away. Infectious clones are simply clones of a virus that can go on to infect cells. Infectious clones can be very bad at infecting, and still be infectious clones. If you’ve seen or read the hit anime Naruto, Naruto clones himself and sometimes his clones are duds. Same with infectious clones, “kage bunshin no jutsu” of modern virology - some may be duds, others dangerous.
SARS-CoV-2 is a large, RNA virus with over 30,000 base pairs (A’s, T’s, G’s and C’s) in its genome. RNA is unstable and difficult to work with, so make a clone of SARS-CoV-2 that we can easily modify (e.g. to study the function of one virus’ Spike protein in another virus’ backbone as done recently in Boston) we need a DNA copy. In order to build a 30,000 base pair (or 30kb) DNA copy, we need to assemble this copy from a set of smaller pieces or segments of the viral genome.
There are many ways to cut and paste a viral genome to assemble that 30kb DNA copy. One very common method is to use a special scissors called a “type IIS endonuclease” or “type IIS restriction enzyme”. These enzymatic scissors cut the virus at very specific sequences, such as CGTCTC, the “recognition site” for the restriction enzyme BsmBI. These enzymes don’t just cut the DNA straight across, though, they slice the DNA such that the two pieces cut apart have 3-4 nucleotide “sticky ends” that can be used to assemble the virus. The sticky ends help us glue the virus back together - if all of our sticky ends are unique, then by the magic of A’s pairing with T’s and G’s pairing with C’s we can re-assemble the virus in exactly the same order we cut it. These enzymes allow us to work with DNA segments of the virus, mutate them, swap a spike gene from one virus with the spike gene of another, and glue it all back together again like a chimeric Mr. Potato Head with the arms of GI Joe.
Making chimeric Mr. Potato Head viruses helps us study things like whether GI Joe arms provide any clear benefit for an important task in the virus life cycle like lifting weights or binding human ACE2 receptors. Researchers in Boston took the Spike gene of Omicron and put it into the backbone of an ancestral SARS-CoV-2 strain: to test the function of the Omicron spike gene for binding ACE2, immune evasion, etc. Chimeras help us study “genotype-to-phenotype” (G2P) relationships. Virologists study G2P in order to learn things like whether some viruses are more likely to cause a pandemic than others.
Researchers cut and paste viruses to create chimeric infectious clones, and these cool type IIS enzymes let them cut and paste viruses without leaving duct-tape or massive Frankenstein-esque stitches all over the viral genome. However, while assembling viruses via type IIS DNA assembly doesn’t leave a scar, we found it does leave a very subtle but identifiable fingerprint.
Viruses in the wild don’t have cutting sites exactly where researchers want them. To accomplish research goals more easily, researchers often add + remove cutting sites from the wild (“wild type”) virus. When adding and removing cutting sites, researchers like to have more regularly-spaced cutting sites with all unique sticky ends and with a region of interest (e.g. the Spike gene’s receptor-binding domain) docked entirely within one segment.
For example, researchers studying bat coronaviruses pre-COVID found a weird coronavirus, WIV1, and wanted to study one of its genes, ORFX. The figure below shows the viral genome (A), and the cutting/pasting sites for a particular enzyme BglI (B). In (B), the researchers used two existing sites (no arrows), removed one site (white arrow), and added 4 more sites (black arrows). When adding or removing cutting sites, researchers made sure every mutation was “silent” or didn’t alter the amino acid produced by the resulting RNA sequence. The new cutting sites produced the fragments in (C), with the 3 nucleotide sticky ends shown (e.g. fragment A has sticky end TAA on the right that can easily find the ATT on the left side of fragment B). The researchers then assemble all of these segments inside a big circular DNA (“bacterial artificial chromosome", this unique one being named pBAC-CMV-rWIV1) with all the right bells and whistles to help them express that DNA, make the full-length viral RNA genome, and insert that genome inside a cell to make their infectious clone.
That’s how we make infectious clones of RNA viruses. Find a virus, decide which region you want to study, look at the viral genome for cutting sites, add/remove cutting sites to suit your research purposes and satisfy the bioengineering constraints of this DNA assembly procedure, order the DNA segments online (or make them yourself by reverse-transcribing the viral RNA into cDNA), and prepare the bench. Order your restriction enzymes, cut up the fragments, assemble them either into a full-length cDNA copy of the virus or in a BAC clone, transcribe the DNA into full-length RNA, electrocute cells to make holes in their cell membrane, and insert the viral RNA. The cells will express the RNA.
Viola: an infectious clone is born, an immaculate conception of modern biotechnology.
Genomic Fingerprints of Infectious Clones
While the cutting/pasting of DNA chunks is seamless, the adding/removing of restriction sites can leave a trace. In wild viruses, these cutting/pasting sites are randomly distributed because there's no evolutionary pressure for the virus to be thusly cut and pasted in nature. In infectious clones, however, the humans behind the screen tend to modify restriction sites in a regular way. For any given restriction enzyme or set of enzymes, the set of all cutting sites is called the “restriction map”, and looking at these restriction maps helps us see the fingerprint of infectious clones.
Below are two published examples of infectious clones: a MERS coronavirus (A) and the WIV1 coronavirus shown above (B). We can compare restriction maps across viruses by plotting dots for every cutting site as a function of where those dots are located on the genome. When researchers made one of these “reverse genetic systems” for MERS, they removed pre-existing cutting sites and added a bunch of regularly-spaced sites. The same thing happened with WIV1: they kept some sites, but removed others and the resulting map had rather regularly-spaced sites. The wild type viruses have randomly spaced cutting sites, the synthetic viruses have more regularly spaced sites. One way to measure “regular-spacing” of sites is to look at the length of the longest fragment. In subpanel (C) below, boxplots show the length of the longest fragment as a function of the number of fragments in a wide range of 70 coronaviruses digested by over 200 enzymes and 1,000 enzyme pairs - when researchers created infectious clones pre-COVID, they made regularly-spaced sites, turning viruses well-within the boxplots to viruses that are well below the boxplots. Unusually short longest-fragment-lengths from digestion with type IIS enzymes is a fingerprint of an infectious clone. We show only two examples below for clarity and illustrative purposes, but to show that this is a common fingerprint and not specific to these two, we ran a meta-analysis to find 10 examples of infectious clone CoVs made by type IIS assembly from 2000-2019.
There are other requirements for infectious clones as well. Researchers tended to use 5-8 fragments for coronaviruses (5-7 fragments was proposed as the ideal range for an “efficient reverse genetic system” for coronaviruses). All sticky ends must be unique. All mutations used to modify sites from close relatives are silent.
Additional evidence isn’t necessary but is important to consider when evaluating whether or not a genome is an infectious clone. If such anomalous restriction maps are unlikely to evolve from close relatives, then that adds weight to a synthetic origin. If the restriction maps contain key sites docked entirely within a segment, especially sites also thought to be modified, that too adds weight to a synthetic origin.
Recap: researchers make infectious clones by cutting/pasting chunks of DNA. They do this by modifying cutting/pasting sites from wild type coronaviruses, and researchers will tend to make cutting/pasting sites more regularly-spaced than expected by chance. We can measure regular-spacing by looking at the length of the longest fragment, and we can further test (and reject!) our hypothesis of synthetic origin by seeing if other required criteria are met: sticky ends are good for faithful assembly, and all mutations modifying these cut/paste sites are silent. We can get some more understanding and debate the fingerprints we find by assessing how likely this weird map is to evolve by chance, whether it docks a key site of interest entirely within a segment, and more.
A Synthetic Fingerprint on SARS-CoV-2
To study this question on SARS-CoV-2, we could look at all type IIS cutting sites, but doing that would dredge the data by making multiple comparisons of SARS-CoV-2 versus the wild type distribution. Multiple comparisons may cause us to lose power to detect a subtle signal. To avoid this, we justified focusing on a very common type IIS enzyme pair: BsaI and BsmBI. The full (and technical) details of this justification are given in the manuscript, but essentially Valentin and Tony approached this problem like the bioengineers they are. They asked: what would a bioengineer do?
The WIV1 example above used the enzyme BglI, which was by far the most common enzyme used for cutting & pasting coronavirus infectious clones pre-COVID. However, when we start looking at coronaviruses like SARS-CoV-2, the restriction maps of BglI are sparse - there’s only one site and its inconveniently located near the beginning of the genome. If researchers were interested in studying chimeric viruses of SARS CoVs in this larger clade, they would want more conserved cutting sites as those will ensure they can cut & paste arms and legs from different viruses.
After BglI, two of the most popular type IIS enzymes on the market are BsaI and BsmBI. First, BsaI/BsmBI leave 4 nucleotide sticky-ends instead of 3nt, allowing for more faithful assembly. Second, BsaI and BsmBI restriction maps are highly conserved across coronaviruses, and provide a rich range of cutting & pasting sites among close relatives of SARS-CoV-2 that would make it easier to build chimeric viruses across a larger range of CoVs. The figure below shows a bunch of CoVs on an evolutionary tree and the BsaI/BsmBI restriction maps. The BsaI/BsmBI sites of SARS-CoV-2 are indicated with vertical lines for easy comparison across the whole range of CoVs. Tony and Valentin reasoned: if they were engineering chimeric CoVs in this group of coronaviruses, they’d switch to BsaI/BsmBI for more faithful assembly of a wide phylogenetic range of coronavirus chimeras.
The SARS-CoV-2 BsaI/BsmBI map has 5 sites creating 6 fragments that are rather regularly-spaced. The receptor binding domain of the Spike protein is entirely within the 5th fragment.
When we plot the maximum fragment length of SARS-CoV-2 relative to the wild type distribution and the 10 engineered CoVs we found in the literature, the SARS-CoV-2 BsaI/BsmBI maximum fragment length is well below the expectation from the wild type distribution and right within the narrow range of fragment number we find in engineered CoVs (B). One way to compare these viruses across fragment-number is to measure how many standard deviations below the mean they are for their observed number of fragments. These ‘z-scores’ help us compare all viruses in the 5-8 fragment range by ranking their z-scores. (C) SARS-CoV-2 has a higher z-score in the top 1% of all wild type coronavirus and 3 of the known engineered coronaviruses. When we restrict the wild type distribution to only type IIS enzymes that could be used for this assembly and yielding the idealized 5-7 fragments, SARS-CoV-2 has the highest z-score of 1,491 digestions.
So, we estimate there’s a 1% chance of seeing as great or greater z-score from all enzymes, and less than 0.07% chance of seeing as great or greater z-score from a type IIS digestion yielding 5-7 fragments. The BsaI/BsmBI restriction map of SARS-CoV-2 is an outlier among wild coronaviruses. It falls squarely within the range of what we expect from infectious clones.
As seen from the 1%—>0.07% drop in how big an outlier SARS-CoV-2 is, the wild type distribution above is sensitive to which enzymes we use, and perhaps also sensitive to which coronaviruses we use. We can’t rest on this wild type outlier analysis alone. We needed to test all the criteria.
It turns out, the sticky ends produced by BsaI/BsmBI digestion of SARS-CoV-2 are all unique, non-palindromic, and all contain at least one A or T - all criteria either required or recommended for in vitro genome assembly.
It also turns out, the mutations separating SARS-CoV-2 BsaI/BsmBI sites from those of its close relatives are all silent. About 84% of mutations between SARS-CoV-2 and its two closest relatives (BANAL-20-52 and RaTG13) are silent. There are 14 distinct mutations separating SARS-CoV-2 BsaI/BsmBI sites, and all of them are silent. There’s a ~9% chance that 14 randomly drawn mutations are all silent.
But that’s not all: we also looked at the concentration of silent mutations per-nucleotide in BsaI/BsmBI sites. If we just looked at WIV1 or the MERS-CoV examples above, we’d find a small number of mutations significantly concentrated within the modified type IIS sites. Compared to the rest of the genomes, we found a significantly higher rate of silent mutations within BsaI/BsmBI sites. Between BANAL52 and SARS-CoV-2, there is a 5x higher rate of silent mutations within BsaI/BsmBi recognition sites than the rest of the genome (P=0.004). Between RaTG13 and SARS-CoV-2, there’s a whopping 8x higher rate of silent mutations with 1/100 million odds of seeing as high or higher concentration of silent mutations within the BsaI/BsmBI restriction sites.
Recap: BsaI/BsmBI are particularly useful restriction enzymes to use if you wanted to study a bunch of chimeric coronaviruses like the close relatives of SARS-CoV-2. The SARS-CoV-2 BsaI/BsmBI cutting sites look regularly-spaced (ish). The maximum fragment length is in the bottom percentile of all CoVs digestions in the idealized fragment-number range, the bottom 0.07% for all type IIS digestions within the idealized range, and the number of fragments is also in the idealized range. The SARS-CoV-2 BsaI/BsmBI restriction map looks a lot more like known pre-COVID infectious clones than a wild coronaviruses. All sticky ends are unique & meet other nice criteria for good assembly. All mutations separating these sites from close relatives are silent, and there’s a significantly higher rate per nucleotide of silent mutations within BsaI/BsmBI recognition sites than the rest of the viral genome.
The odds of meeting any one of these criteria vary, from 1%-0.07% of having such a small maximum fragment length to 1/250 to 1/100 million odds of having such high concentration of silent mutations within BsaI/BsmBI recognition sites. The odds of meeting every single one of these criteria are even smaller. Much smaller.
As a result of this analysis, we theorize that SARS-CoV-2 was assembled in a lab via common methods used to assemble infectious clones pre-COVID.
What this doesn’t mean & what we don’t know
A synthetic origin of SARS-CoV-2 doesn’t mean there was malicious intent. In fact, the location of BsaI/BsmBI site appear almost chimeric: some are shared with close relatives and others are shared with distant relatives, making us hypothesize that perhaps researchers just wanted to make chimeric viruses within this clade of relatively unstudied CoVs. Again, this is a common research project, much like that conducted at Boston University recently, and it is often done with noble intentions of learning about genotype-to-phenotype relationships and even preemptively designing vaccines against viruses that are most-likely to cause a pandemic. That would be tragically ironic if proven true.
We don’t identify who constructed the virus. Many people in the world could do this, although the origin of this outbreak in Wuhan does narrow the range of suspects considerably. The technology used to make infectious clones is relatively cheap, especially compared to making an atom bomb. Even if our theory is rejected by later tests, the ease of these experiments should scare the shit out of all of us enough to start talking about global biosafety. In addition to, I don’t know, regulating which sequences you can purchase online, we may also want to require some identifiability of chimeric experiments. As silencers for guns are illegal, we may be wise to require all chimeric viral research have clearly identifiable sequences that help us identify right away who did it and what was done, as such information may be relevant for preventing a lab accident from turning into a full-blown pandemic.
We also don’t find any information on gain of function research, except for our hypothesis that this can be used to make chimeras and, as the uproar over the Boston University experiment is showing us, making chimeras is itself a form of gain-of-function research. Chimeras are not found in nature, and a novel chimera made in vitro could have novel functions that make it more infectious, more lethal, or immunoevasive. On the spectrum of gain-of-function research, making chimeras of wild viruses is (depending on the wild viruses) one of the less risky experiments, but clearly there are still risks. We should talk about those risks and manage them.
I want to reiterate: we don’t know ‘whodunit’. I have been very vocal on the topic of COVID origins, and it’s essential to separate this research paper from my public proclamations. As a citizen, I’m upset by the lack of transparency from the people studying coronaviruses, proposing to make chimeras and insert Furin cleavage sites inside the receptor binding domain - such transparency would have put lab leak questions to rest, provided the virus did not leak from a lab. As a citizen-scientist, I’m also shocked by unusual, declining standards of evidence in the peer-reviewed literature on SARS-CoV-2 origins, especially things like leading researchers being “80:20 lab leak” one day and then proclaiming “lab leak is a conspiracy theory” days later - the changing standards of evidence and massive changes in the stated beliefs of researchers was unusual and I stand by my questions about what evidence, exactly, changed their minds.
As a scientist and human being, this work was conducted because I and others noticed the lack of transparency, the unusual literature, and the sudden right-turns towards calling lab origin hypotheses conspiracy theories. I wrote a paper highlighting the statistical and methodological reasons why I am unconvinced by the literature claiming “dispositive” evidence of a wet market origin. Science is a fierce, unyielding, yet honorable pursuit of truth, and it is conducted by humans. Yet, when I wear my scientist-hat I hold myself to a higher standard of evidence and professionalism than when I wear my human-citizen hat. As a human-citizen, I advocated for transparency and shared my honest perspectives on the literature because I believe the public needs transparency and honesty from scientist.
As a scientist conducting this research, I did my best to ensure our methods were reproducible, our statistics conservative, and our presentation honest. We discovered SARS-CoV-2 was unusual, knew the massive stakes of our finding, and set out to disprove our hypothesis by looking closer at sticky ends, silent mutations, and analyses of the evolution of CoVs. Any one of these tests could’ve rejected our hypothesis and the world would never have seen this paper. We sought peer-reviews from world experts at every leading institution we could connect with, and we asked them to shake down our results. The pre-print is not exactly “not peer-reviewed”, as it is the product of rolling feedback from world experts and we did our best to incorporate all of their feedback, test all of their proposed tests, and include all of the limitations they identified in our manuscript.
As a scientist, I want to be explicitly clear: while we find strong evidence of synthetic origin, we present no evidence of intentional release, specific labs or specific people. We don’t know who knew what or whodunit, we only know that the BsaI/BsmBI restriction map of SARS-CoV-2 looks a heck of a lot like the restriction map of an infectious clone and such a weird restriction map is very unlikely to be found in nature or evolve naturally from the close relatives of SARS-CoV-2. Yet, like all science, there remains the possibility that we could be wrong and we will remain open to that possibility.
How we could be wrong
We used BsaI and BsmBI maximum fragment lengths as our test statistic because these enzymes are good and the maximum fragment length relates to some bioengineering constraints (we justify those further in the MS). However, others may find that there are better fingerprints of synthetic restriction maps and using another statistic may change just how anomalous the SARS-CoV-2 BsaI/BsmBI restriction map is. It won’t change the unique sticky ends or the concentration of exclusively silent mutations, but it would change how SARS-CoV-2 compares to wild type viruses.
We don’t account for phylogenetic dependence of CoVs. Consider a ridiculous scenario of one collecting 1,000 copies of SARS-CoV-1, digested them, and then saying SARS-CoV-2 is a 1/1000 event compared to these wild type digestions. That estimate isn’t justified by that analysis, because those wild type genomes are all the same. The evolution of CoVs from a common ancestor makes CoV genomes not the same, but similar, and we do encourage a robustness check that accounts for the phylogenetic similarities of CoVs. We didn’t really know how to do that, though, at least not right away. I’m familiar with ways to account for phylogenetic dependence, and somewhat an expert on that topic, but how to do it for this particular problem of determining a quantile of a single virus under a wild type distribution wasn’t clear. I’d honestly love to hear how to do this, and would gladly incorporate that into our paper.
When we analyzed mutations, we used a very simple model of mutation that assumes uniform rates across the viral genome. This model is clearly wrong, however it’s not clear which way a more accurate model would affect the results nor what exactly would be the most agreeable way to do this. To put it simply: not all sites mutate at the same rates. What if the sites within BsaI/BsmBI recognition sequences mutate at a higher rate than others? Alternatively, what if sites within BsaI/BsmBI sequences are under strong selection possibly due to strong codon biases of that site? The realistic non-uniform rate of mutations across coronaviral genomes is important, it is more realistic than our uniform-rate assumption, and it can affect our results. We didn’t run analyses with non-uniform rates, however, because we are not experts in this topic, and we felt this was best left to future research.
Scientists publish papers not because the paper is the end of science, but because it is a unit of research that is valuable to share with others so that others can use this brick of knowledge and either build with it… or find its weakness and break it down. We remain open to both possibilities, that our work may lead others to e.g. search communications and lab notebooks for “BsaI” to find (or not find!) evidence that these enzymes were used to modify a bat CoV genome. Others may probe our stated limitations and find that more robust analyses lower the odds that SARS-CoV-2 is synthetic… or they may find that more robust analyses multiplicatively raise the odds that SARS-CoV-2 is synthetic.
We wrote our entire analysis in R and shared our code with the world. I tried SO hard to check every single line of code and make our pipeline clear & easy to reproduce. However, despite nearly giving myself stomach ulcers checking every line and stressing about these findings, it’s possible someone finds a mistake in our work. We don’t share this work happily - this is the saddest paper I’ve ever written. We’ve shared our code precisely for that reason: we want you to see exactly what we’ve done, and if we’ve done something wrong we are open to hearing it. We sincerely care about the truth. We tested our hypothesis as well as we could until it hardened to a brick of knowledge we felt the world needed to hear, and we give this brick to you all to build a pyramid or knowledge or perhaps find fault and turn our brick back to dust.
As a scientist, with my scientist hat on, we’ve tried to be clear about the limitations and I’m excited to hear what others contribute, especially if they prove us wrong. I believe SARS-CoV-2 likely arose from a lab based on clear flaws of existing literature claiming zoonotic origin, the strength of the evidence we’ve provided, and additional geographic, genomic, and circumstantial evidence discussed elsewhere. I could be wrong. I’m not judge/jury/executioner, I’m just a scientist. My civic duty is to see something, say something, and my job as a scientist is to pay particular attention to topics in which I may be able to see something non-scientists cannot.
We found strong evidence of synthetic origin of SARS-CoV-2.”
https://www.biorxiv.org/content/10.1101/2022.10.18.512756v1
“Abstract
To prevent future pandemics, it is important that we understand whether SARS-CoV-2 spilled over directly from animals to people, or indirectly in a laboratory accident. The genome of SARS-COV-2 contains a peculiar pattern of unique restriction endonuclease recognition sites allowing efficient dis- and re-assembly of the viral genome characteristic of synthetic viruses. Here, we report the likelihood of observing such a pattern in coronaviruses with no history of bioengineering. We find that SARS-CoV-2 is an anomaly, more likely a product of synthetic genome assembly than natural evolution. The restriction map of SARS-CoV-2 is consistent with many previously reported synthetic coronavirus genomes, meets all the criteria required for an efficient reverse genetic system, differs from closest relatives by a significantly higher rate of synonymous mutations in these synthetic-looking recognitions sites, and has a synthetic fingerprint unlikely to have evolved from its close relatives. We report a high likelihood that SARS-CoV-2 may have originated as an infectious clone assembled in vitro.
Lay Summary To construct synthetic variants of natural coronaviruses in the lab, researchers often use a method called in vitro genome assembly. This method utilizes special enzymes called restriction enzymes to generate DNA building blocks that then can be “stitched” together in the correct order of the viral genome. To make a virus in the lab, researchers usually engineer the viral genome to add and remove stitching sites, called restriction sites. The ways researchers modify these sites can serve as fingerprints of in vitro genome assembly.
We found that SARS-CoV has the restriction site fingerprint that is typical for synthetic viruses. The synthetic fingerprint of SARS-CoV-2 is anomalous in wild coronaviruses, and common in lab-assembled viruses. The type of mutations (synonymous or silent mutations) that differentiate the restriction sites in SARS-CoV-2 are characteristic of engineering, and the concentration of these silent mutations in the restriction sites is extremely unlikely to have arisen by random evolution. Both the restriction site fingerprint and the pattern of mutations generating them are extremely unlikely in wild coronaviruses and nearly universal in synthetic viruses. Our findings strongly suggest a synthetic origin of SARS-CoV2.”
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