Ran into what looks to me like the first very good candidate for deer-to-human transmission. Below is the Usher tree containing it. It's the one on the right.
Before going into this seq's details, a brief description of the characteristics of deer sequences I've seen. 1/20
The branches leading to deer sequences are quite long. They also tend to be of variants that disappeared from circulation in humans many months ago.
The Alpha deer tree below is pretty typical. Note the most closely related human sequences are from ~6-7 months prior. 2/20
The Gamma tree below is the most extensive deer-seq tree. These are long branches. I doubt if there are *any* human Gamma sequences with over 75 mutations from wild-type, for example. Here there are several. But it's not just the number of mutations that distinguish these. 3/20
The types of nucleotide (nt) mutations in deer sequences are unlike any human seqs. Deer sequences overwhelmingly consist of C->T mutations. This is also the most common mutation in humans, making up ~42% of mutations. See @jbloom_lab chart below. 4/20
But deer sequences are in another league entirely. It’s common to see C->T make >75% of nt mutations in them. I made Usher trees for all deer seqs, opened the first 6 trees, & selected 1 seq from each w/many mutations (less dropout) & no obvious errors or recombination. 5/20
Counting only the mutations that took place within the deer part of the tree, I did an amateur analysis of the types of nt mutations, as well as the amino acid (AA) substitutions in 6 deer seq. Non-synonymous nt mutations are ones that change the AA. Results below. 6/20
Combined stats for 6 deer seqs 👇
5 things stand out: 1) Very large # of mutations 2) Extremely high C->T content (79.4%) 3) Deer *really* like the synonymous C7303T 4) Very low % of non-synonymous mutations (44.8%) 5) Few spike mutations, almost none in RBD 7/20
How does the BF.11 deer-to-human candidate compare in terms of number & type of mutations? It's very similar to deer seqs—more similar than any human seq I've ever seen.
Very low non-synonymous %, very high C->T content, few spike mutations, zero in RBD—and C7303T! 8/20
It's also, like most deer sequences, from a variant that ceased circulating in humans many months ago.
Why the big deal about C7303T? This is a rare mutation in humans—in just 0.07% of sequences. But it’s in about 50% of deer sequences. 9/20
What about other private nt mutations in this seq? I ran all deer seq through Nextclade to extract their private mutations—ones not shared with other sequences in the tree—and compared them to their overall prevalence in human sequences. To be clear..... 10/20
...the comparison is *not* apples to apples. An equal % in each means a mutation is likely *far* more common in deer than in human seqs.
What we'd really like is the # of times a mutation has independently emerged in humans & in deer. But I don't know how to do that. 11/20
Overall, the similarity of this sequence to past deer sequences is amazing to me. There's been much talk about reverse zoonosis, but this is the first sequence I've seen that really has the look of it. Nothing else comes close. 12/20
What is the risk of deer-to-human transmission of SARS-CoV-2? It's not zero, but I think it's far less worrisome than, e.g., the risk of a molnupiravir-creation hitting a mutational jackpot & spreading. See @sergeilkp & @DarrenM98230782 on this topic. 13/20
These deer sequences have almost no antigenically important spike mutations. None that I've seen would have the slightest chance of circulating in humans. The molnupiravir sequences, on the other hand, often have many spike mutations & at least appear to be quite fit. 14/20
Of course we only have a small sample of deer sequences—almost none Omicron—so there could be more sinister SARS-CoV-2 variants lurking out there.
Finally, how do we know this sequences is not a MOV sequence? 15/20
I assumed when I first saw it that it was a MOV creation. Branches like this—with 59 private mutations—are almost always MOV creations. Rarely, they're very old variants from a chronic infection—virological demons of the ancient world, which this is decidedly not. 16/20
But a cursory examination of the mutations makes it clear this sequence is not MOV-related. First, the most distinctive MOV mutation, G->A, is less common than usual here. There are also more transversion mutations that we typically see in a MOV sequence. 17/20
Finally, MOV preferentially causes mutations in certain nt contexts. For example, G w/an upstream T & downstream C—TGC—is a favored context, but AGA is a very unfavorable context. Similarly, some contexts favor MOV-driven C->T mutations, while others don’t. 18/20
The preternaturally talented @theosanderson created a tool to examine the nucleotide contexts of mutations & assess the likelihood they were caused by MOV. It’s not uncommon to see probabilities of 0.99 or greater in MOV seqs. Probability for this sequence = 0.001 19/20
Last, I want to give a shout out to the @nextstrain team for creating Nextclade, which features heavily in all SARS-CoV-2 work I do. I am in great debt to @ivan_aksamentov, @CorneliusRoemer, @richardneher, & whoever else created & maintains this brilliant tool.
20/20
Addendum: Thanks to @midnucas for suggesting I include the paper below. I had not read this paper, but they document 3 sequences that clearly involved human-deer-human transmission. A1/4
When looking at the Usher tree for one of the human-deer-human sequences the authors identified, I came across 2 nearby sequences that to me seem likely examples of deer-to-human transmission.
It's amazing to me that this kind of transmission happens at all. A2/4
One of these clusters has an odd feature: it also involves 3 lion sequences from a zoo in North Carolina. How did a variant originating in wild white-tailed deer manage to infect lions in a zoo? I can't imagine many people—or any deer—have close contact with lions. A3/4
But @PeacockFlu suggested that perhaps these lions were fed deer (leftovers from hunters' takes?) & were infected that way. That's the only thing that makes sense to me.
Does anyone know if this is common practice at zoos in North Carolina (or elsewhere)? A4/4
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Molnupiravir-created mutants still show up intermittently, mostly in Australia and Japan. A remarkable one popped up today: A KP.3.1.1 with 94 private mutations. 1/6
The closest related sequences are from the same region and from about 1 month earlier, suggesting these 94 consensus mutations were acquired in about one month, and possibly a shorter period of time. 2/6
It has the classic MOV signature of an extremely high percentage of transversions, primarily C->T and (especially) G->A.
93/94 mutations are transitions
27/94 are C->T
38/94 are G->A
More detailed discussion of this in 2022 thread below.
There aren't many convergent mutations in ORF1b in chronic-infection sequences. But many of the ones that do show up repeatedly are also highlighted in this study looking at NSP12 mutations that developed in immunocompromised pts treated with remdesivir. 1/4
I've spent hundreds of hours compiling a list of >3500 likely chronic-infection sequences & have created an imperfect, approximate measure for how overrepresented a mutation is in chronic sequences compared to circulating sequences (as measured by independent acquisitions). 2/4
Of the top 10 ORF1b chronic-infection-specific mutations on this list (occurring ≥5 times), five appeared in the remdesivir-treated patients in this study: Q435K, C455Y, V783I, M785I, & C790Y.
V783I was in 2 study patients & is also the most common of these in chronics. 3/4
It seems more certain than ever: getting Covid is bad for your brain.
This study, which found cognitive effects at 1 year post Covid to be equivalent to brain aging from age 50 to 70, looked only at hospitalized patients. But as Dr. Topol says.... 1/7
...another recent study—a controlled experimental one involving young (18-30), healthy volunteers—found significant negative cognitive effects from mild illness 1 year after the challenge trial.
Mild illness. Healthy 18-30-year-olds. 1 yr later. 2/7
And that study almost certainly underestimates the cognitive effects of 1 mild case of Covid. As @Mike_Honey_ pointed out, during the following year, which encompassed the Delta, BA.1, BA.2, & BA.5 waves, many in both groups were undoubtedly infected. 3/7
I’ve mostly pooh-poohed the rise of XEC for 2 reasons:
#1. Its spike is almost identical to the dominant KP.3.1.1
#2. I don’t think its advantage over KP.3.1.1 is large enough to make a significant real-world impact.
But one aspect of XEC is noteworthy: The demise of N*.
1/20
I’ve talked a lot about nucleocapsid before, mostly in this 120-tweet thread that was too long for anyone to want to read. Nucleocapsid is by far the most abundant SARS-CoV-2 protein. Nothing else comes close. It is very, very important. 2/20
An essential aspect of N is its phosphorylation. Phosphorylation involves the attachment of a highly negatively charged phosphate to (usually) an S or T amino acid. We even know how it happens in the SARS-CoV-2 N. It’s pretty neat. 3/20
Update on XEC: the weekly growth advantage of XEC relative to KP.3.1.1 has withered to approximately zero in Germany, the country XEC has been in longest and which has by far the highest proportion of XEC sequences. 1/13
The country of origin is generally the best place to compare a new variant to others. But globally, most seqs have been collected outside Germany (World: ~225, Germany: ~60), & these deserve some weight.
And globally, it looks like an XEC massacre. 2/13
But global growth figures are often misleading. There have been virtually no XEC detected in Asia or Australia, for example. Apart from Germany, only Denmark, the Netherlands, the UK, & Canada have >20 seqs and >0.3% prevalence in the past 2 months. So let's look at these. 3/13
Lots of talk about the XEC variant lately. It's a fast variant, but I want to emphasize two things.
First, I don't think XEC is much faster than the dominant KP.3.1.1. Germany is the only country w/enough seqs for a reliable growth estimate & it's pretty modest & uncertain. 1/6
A variant w/such a small growth advantage (assuming it's accurate) takes months to grow to dominance. And such modest advantages do not result in any noticeable change in case levels, so I don't expect XEC to have any real impact. By the time it would become dominant... 2/6
...it's almost certain that some other, more dramatic evolutionary event will have taken place, whether that be another chronic-infection-derived saltation variant or simply further stepwise spike mutations on top of current variants. 3/6