New (not yet peer-reviewed) work by Katie Kistler and @huddlej in the lab assessing adaptive evolution in SARS-CoV-2 across the viral genome. 1/12
biorxiv.org/content/10.110…
We measure adaptive evolution by correlating mutations in different regions of the genome with growth of clade frequency. For this, we use a viral phylogeny of ~10k genomes sampled equitably through space and time across the pandemic (nextstrain.org/groups/blab/nc…). 2/12
If mutations to a region result in fitter viruses, clades bearing these mutations should expand more rapidly. We find that the S1 domain of spike accumulates protein-coding (nonsynonymous) changes rapidly and that clades with more S1 mutations tend to grow in frequency. 3/12
As a control we looked at non-protein coding (synonymous) mutations in S1 and nonsynonymous mutations in the RdRp polymerase. In both cases we fail to observe a significant correlation with clade growth. 4/12
Across the genome, we see the highest correlation in the S1 domain of spike, but find weaker (though statistically significant) evidence of adaptive evolution in Nsp6 and ORF7a. 5/12
Focusing on S1, we calculate a common metric called dN/dS that compares nonsynonymous mutations to synonymous mutations. We find that dN/dS in S1 increases through time during the pandemic with the most recent timepoint showing dN/dS of ~2.1. 6/12
This is a fast pace of adaptive evolution and it's rare to observe such a strong signal. HA1 in influenza H3N2 as the canonical example of an adaptively evolving viral protein shows dN/dS of ~0.4, or about 5 times lower than what's currently being observed in SARS-CoV-2. 7/12
Further observations show that nonsynonymous mutations in S1 cluster along the phylogeny quantifying the anecdotal observation that variant viruses often have multiple mutations occurring all together. 8/12
We also observe convergent evolution in individual mutations and identify a subset that occur repeatedly in parallel and when occurring are associated with clade growth. This highlights spike mutations 95I, 452R and 484K as well as a 3 amino acid deletion in Nsp6. 9/12
Most of this rapid pace of evolution is likely due to adaptation to a new host, but in general, this suggests to me that the S1 domain of spike in SARS-CoV-2 is a readily evolvable domain. 10/12
Circulating mutations like 484K partially escape from antibody responses and although I'd anticipate the pace of evolution to slow as the virus becomes endemic in the human population, I would also expect relatively rapid antigenic drift, just given this data. 11/12
We'll of course have to wait to see what unfolds, but I would, at this point, suspect an influenza H3N2-like process of antigenic drift and necessarily frequent vaccine updates in the upcoming years. 12/12

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More from @trvrb

7 Sep
It looks like we're about at the peak of the Delta SARS-CoV-2 wave in the US (figure based on @CDCGov data). A thread on current circulation patterns and the impact of Delta. 1/14
This inflection point in case loads at the country-level is due to decline in some states (such as FL and LA) and growth in others (such as OH and WV). Figure shows cases per 100k population on a log axis to emphasis state-level growth and decline. 2/14
Using previously described method to split cases by variant frequency (), we see a striking pattern in which most states have a moderate spring wave comprised of a mix of Alpha and other variants, but show a large Delta wave in the summer. 3/14
Read 17 tweets
31 Aug
I'm not an immunologist, but I've been trying to read into the literature on waning immunity to SARS-CoV-2 and to understand the recent NIH, CDC, FDA booster recommendation (hhs.gov/about/news/202…). I'll share some takeaways here. 1/14
Previous studies in other viruses found that the potency and the concentration of circulating antibodies in an individual is often predictive of their protection to infection or illness after exposure. 2/14
This potency + concentration is commonly quantified as the titer required to neutralize 50% of viral plaques in a lab assay. These assays are run by diluting sera from an individual and seeing what dilution causes loss of neutralization. 3/14
Read 14 tweets
30 Jun
How big of a wave of #COVID19 do we expect in the US from the Delta variant? Here I describe a simple approach to this question and attempt a rough back-of-the-envelop estimate. 1/16
First off, epidemic size is determined by two primary factors:
1. Efficiency of onward transmission from an index case, commonly quantified as R0
2. Size of susceptible pool
2/16
Given a specified R0, we can calculate final epidemic size in a simple SIR model with the following equation where Z is final epidemic size. For initial R0 of 1.1, an epidemic is expected to infect 18% of the susceptible population. 3/16
Read 18 tweets
24 Jun
Jesse Bloom's preprint has, of course, caused quite a stir. I wanted to try to explain a bit about the "rooting issue" discussed in the manuscript and also provide some hopefully clarifying phylogenetic trees. 1/15
For this post, I've made a @nextstrain "build" targeted at SARS-CoV-2 genomes from Dec 2019 through Jan 2020, totaling 549 viruses. All code is here: github.com/blab/ncov-earl… and should be reproducible using a download of @GISAID data. 2/15
There is genetic diversity within these very early samples with much of it arising from a split in early transmission chains into lineage A and lineage B viruses (lineage B as in B.1.1.7). Lineage A and lineage B viruses are separated by mutations at sites 8782 and 28144. 3/15
Read 15 tweets
22 Jun
An update on genomic surveillance in the US and spread of the Delta variant (PANGO lineage B.1.617.2, Nextstrain clade 21A). At this point, 95% of viruses circulating in the US are "variant" viruses that have been designated as "Variant of Concern" or "Variant of Interest". 1/12 Image
This update mirrors how I was looking at the rise of P.1 across the US in May. 2/12
Here, we can look at frequencies of different variant lineages through time and across states where it's clear that variant viruses and in particular B.1.617.2 viruses are continuing to increase in frequency. 3/12 Image
Read 12 tweets
2 Jun
With the publication of the Science letter, the Overton window for discussion of "lab leak" hypothesis has shifted dramatically. We now have mainstream scientific opinions that largely range between "lab leak can be dismissed" and "both zoonosis and lab leak are viable". 1/8
I am in the both are plausible camp. The data (as it exists) is consistent with zoonosis, but it's also consistent with lab leak. Parsing the relative probabilities of the two depends on multiple lines of evidence and is necessarily assumption ridden. 2/8
However, I think that there is a philosophical divide among scientists in how to assess hypotheses that perhaps explains some of the gap in opinion. Ie, is zoonosis the "null" hypothesis that we need significant evidence to reject or are we comparing two competing hypotheses? 3/8
Read 8 tweets

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