mstdn.science is one of the many independent Mastodon servers you can use to participate in the fediverse.

Administered by:

Server stats:

0
active users

Bloom Lab

I wanted to summarize what is known about the new XBB.1.5 variant of SARS-CoV-2, which is starting to generate a lot of interest.

(There are no new scientific results in this thread, it simply aggregates previously reported results for those not following topic closely.)

Reason people are discussing XBB.1.5 is because it's so transmissible. Below are estimates of current Rt (measure of transmissibility) of different variants in US from @trvrb's group.

XBB.1.5 is more transmissible than other variants like BQ.1.1 that until recently dominated in US.

High transmissibility means XBB.1.5 is becoming responsible for larger fraction of COVID-19 cases.

This continues a pattern of strain replacement we've seen over last few years of SARS-CoV-2 evolution (see below).

Eg, there will always be new variants spreading, and right now it's XBB.1.5.

Whether increase in relative fraction of cases due to XBB.1.5 will also lead to surge in absolute cases is still not certain.

But sometimes new variants drive increase in total cases, and in general human coronaviruses (and other respiratory viruses) surge in winter.

A scientifically interesting aspect of XBB.1.5 is we pretty much understand what mutation made it so transmissible, the mechanism by which the mutation acts, and why it took so long for the mutation to emerge.

XBB.1.5 is a descendant of XBB.1, which descends from XBB, which evolved through recombination between two descendants of the earlier Omicron BA.2 variant.

The parental XBB and XBB.1 variants were already notable because they were fairly transmissible and had lots of antibody escape, as shown by @yunlong_cao et al & others (nature.com/articles/s41586-022).

However, XBB and XBB.1 were not as transmissible as XBB.1.5.

One of the sites that is mutated in the parental XBB/XBB.1 variants is 486 in the RBD.

486 has been a major site of antibody escape going back to the earliest variants (see image below from our antibody-escape calculator jbloomlab.github.io/SARS2_RBD_).

But while some antibody escape sites such as 484 were fixing mutations in major variants by late 2020, it took longer for major variants to emerge w mutations at site 486: eg, BA.4/5 w F486V in spring 2022, & then XBB w F486S later in 2022.

It’s easy to understand why it took longer for variants to emerge at site 486: mutations at 486 reduce ACE2 affinity, so benefit they provide in antibody escape comes at cost to receptor binding.

See our deep mutational scanning: science.org/doi/10.1126/scienc

So variants like XBB/XBB.1 fixed mutation (F486S) that was beneficial for antibody escape but detrimental to ACE2 affinity. In other words, they made an evolutionary tradeoff.

But as Ryan Hisner noticed months ago, our deep mutational scanning shows one mutation at site 486 is not so bad for ACE2 affinity, especially in background of BA.2, F486P: twitter.com/LongDesertTrain/st

TwitterRyan Hisner on Twitter“So of the 19 possible amino acid mutations at F486, P is #1 for ACE2 binding (well ahead of all others), #5 for RBD expression (very close to the top and #1 among all six observed F486 mutations), and appears to be #2 for evading antibodies. 13/16”

The difference between XBB.1.5 and its immediate parent XBB.1 is that it has traded the more costly F486S mutation for F486P. Therefore, XBB.1.5 isn’t expected to have more antibody escape than XBB.1 (which already had mutated F486), but it should have greater ACE2 affinity.

And as @yunlong_cao nicely describes, this is exactly what is directly measured: twitter.com/yunlong_cao/status

TwitterYunlong Richard Cao on Twitter“The superior growth advantage of XBB.1.5 has been well-documented by many colleagues @JPWeiland @LongDesertTrain @EricTopol. Here I'll add some experimental data: 1) XBB.1.5 is equally immune evasive as XBB.1, but 2) XBB.1.5 has a much higher hACE2 binding affinity. 1/”

So it’s greater ACE2 affinity (and perhaps RBD stability) that is giving XBB.1.5 its boost in transmissibility.

@jbloom_lab @trvrb May I use this graph in an Intro Bio course? If so, should I credit your lab? Thank you for this thread - it was very helpful (and interesting!).

Oops!An unexpected error occurred.