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Aug 16 12 tweets 5 min read Twitter logo Read on Twitter
I wanted to provide assessment of spike amino-acid mutations in new highly mutated 2nd generation BA.2 SARS-CoV-2 variant

This is analysis for those (like me) scientifically interested in SARS2 evolution

(Anyone else is completely within reason to ignore this variant right now)
Full analysis of the mutations is in these slides:

Analysis is based mostly on deep mutational scanning experiments

TLDR: lots of antigenic change, and some interesting RBD mutations (addition of N-linked glycan & deletion in receptor-binding motif)slides.com/jbloom/new_2nd…
First, to emphasize, only THREE sequences of variant identified so far. There is not currently evidence of wide transmission.

As this thread outlines, people who study SARS2 evolution may want to pay attention to features of this variant. Everyone else can ignore if they wish. Image
As has been noted already, this variant has lots of amino-acid mutations in spike: 33 relative to its putative ancestor BA.2. It is also very different from XBB.1.5.

This makes it an evolutionary jump comparable in size to that which originally gave rise to Omicron. Image
Below is list of spike amino-acid mutations relative to BA.2, w my annotations of likely effects based on experimental data from @bdadonaite @tylernstarr @yunlong_cao @Dr_MattMcCallum @veeslerlab

One thing that is obvious is that many of these mutations cause antibody escape. Image
I’m going to call out three mutations that I think are especially interesting.

K356T creates a N-linked glycosylation site (at N354) in the RBD, with the resulting glycan likely to completely mask that antibody epitope. Image
There is deletion of V483 in RBD’s receptor-binding motif

Unpublished data from @tylernstarr & @bdadonaite (linked in slides) indicate delV483 will moderately reduce ACE2 affinity & antibody recognition, but effect will be no bigger than some point mutations we’ve seen. Image
There is P1143L at beginning of S2 stem helix

In our spike deep mutational scanning (), we found mutating P1143 improves infection by pseudotypes.

We speculated just cell-culture phenomenon, but here is mutation in virus that transmitted at least a bit.cell.com/cell/fulltext/…
To assess overall antigenic of mutations, we can use antibody-escape calculator () informed by data from @yunlong_cao

New variant has at least as much antigenic change relative to BA.2 as does XBB.1.5. https://t.co/z9ma98lY6Njbloomlab.github.io/SARS2-RBD-esca…
Image
In fact, antigenic advantage of new variant over XBB is likely larger than indicated above, as many people have recently had XBB-specific antibodies boosted by infection. New variant differs from XBB at many key antigenic sites (see details)slides.com/jbloom/new_2nd…
Of course, to spread widely, antigenic advantage would need to be combined w inherent transmissibility close to best XBB variants

With only three sequences so far, there isn’t currently evidence that is case

But important to monitor if more sequences of new variant appear
Thanks to:

Labs that sequenced variant:

Variant trackers who spotted sequences: @shay_fleishon, @LongDesertTrain, et al

Scientists doing deep mutational scanning on SARS2 spike mutations: @tylernstarr, @bdadonaite, @yunlong_cao, et alepicov.org/epi3/epi_set/2…

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More from @jbloom_lab

Aug 3
In new study, we develop rigorous method to jointly analyze deep mutational scanning of different protein homologs or conditions

We use it to identify mutations w effects on spike-mediated viral entry that differ by >1,000-fold among #SARSCoV2 strains.

biorxiv.org/content/10.110…
As background, common question in evolution is if some mutations have different effects in different homologs or conditions

Eg, our lab has measured how most mutations to Delta, BA.1 & BA.2 spike affect viral entry. Which mutations have different effects in these viral variants?
If deep mutational scanning experiments were perfect, we’d just compare the measured effects of each mutation in the different spikes to see if they were non-identical.

But in practice, experiments have noise: so how do we tell true biological differences from noise?
Read 12 tweets
Jul 27
This paper from Linfa Wang’s group to which @tylernstarr & I contributed illustrates interesting points about

1⃣ Importance of imprinting for antibody specificity to SARS-like CoV

2⃣ How it may be easier to broadly neutralize animal sarbecoviruses than human #SARSCoV2 variants
Briefly, the study (which was led by Wan Ni Chia @CheeWahTan2 @LokShee @linfa_wang), isolated antibodies from person who had been infected by SARS-CoV-1 in ~2003, then received Pfizer SARS-CoV-2 vaccine in 2021.
So unlike most people in the world, whose first immunological exposure to a SARS-related CoV was to an early SARS-CoV-2 strain via either infection or vaccination in 2020 or 2021, this person’s immune system had been “imprinted” by SARS-CoV-1 prior to their COVID vaccine.
Read 15 tweets
Jun 5
I wanted to post notes on potentially beneficial non-spike mutations in #SARSCoV2 variants XBB.1.16 & XBB.1.9.1, two of fastest growing variants.

These are from estimates of effects of mutations to all SARS-CoV-2 proteins from @richardneher & myself
Both XBB.1.16 & XBB.1.9.1 have I5T mutation in ORF9b innate-immune antagonist accessory protein. XBB.1.16 also has N55S in this protein.

According to our estimates (jbloomlab.github.io/SARS2-mut-fitn…), I5T in ORF9b is beneficial while N55S is roughly neutral Image
XBB.1.9.1 has the T35I mutation in nsp9 (equivalent to T4175I in ORF1a).

According to our estimates (jbloomlab.github.io/SARS2-mut-fitn…), T35I in nsp9 is beneficial. Image
Read 6 tweets
May 16
I’ve created new SARS-CoV-2 antibody escape calculator () with latest data from @yunlong_cao

TLDR: look at image below for likely future sites of antigenic evolution in XBB spike.

For details, read full thread below. https://t.co/yB43xtDIuLjbloomlab.github.io/SARS2-RBD-esca…
Image
Escape calculator uses deep mutational scanning to quantify antibody escape caused by mutations.

Update is based on large new dataset recently posted by @yunlong_cao et al:

Dataset is first to include antibodies induced by multiple Omicron infections.
This addition is important, because as @yunlong_cao describes in his thread, two Omicron infections is sufficient to partially break imprinting in their cohort & induce new antibodies.

So sites of escape differ depending on number of Omicron exposures (see image below). Image
Read 21 tweets
Apr 27
In new study, I have analyzed correlation between SARS-CoV-2 & animal genetic material in full set of environmental samples from Huanan Seafood Market.
biorxiv.org/content/10.110…

Analysis clarifies what sequencing these samples can & cannot tell us about early outbreak at market.
Background:

China first reported coronavirus cases associated w market & no human transmission. But then we learned was human transmission & some early cases not from market.

Thus began still unanswered questions of role of market, nicely summarized here science.org/content/articl…
In 2022, Chinese CDC released pre-print describing sampling market beginning Jan-1-2020: researchsquare.com/article/rs-137…

They collected 457 animal & 923 environmental samples. They stated all animal samples tested negative, but 73 environmental samples positive.
Read 40 tweets
Apr 13
I wanted to flag this study by Lihong Liu, David Ho, et al that identifies new class of #SARSCoV2 antibodies that neutralize all major variants from early strains (eg, D614G) to current strains (eg, XBB.1.5): biorxiv.org/content/10.110…
These antibodies, 12-16 and 12-19, bind to an epitope at the interface of the NTD and SD-1 domain.

They block ACE2 binding, but not by directly binding the RBD.

Instead, they lock the RBD in the down conformation, as schematized below. Image
Most NTD antibodies (eg, those directed to supersite) act by Fc steric hindrance.

But new antibodies in this paper (12-16 & 12-19) are equally potent neutralizers as IgG or F(ab')2 molecules that lack Fc, whereas NTD supersite antibodies like 4-18 are less potent without Fc. Image
Read 4 tweets

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