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Open Access

Peer-reviewed

Research Article


A HUMAN CORONAVIRUS EVOLVES ANTIGENICALLY TO ESCAPE ANTIBODY IMMUNITY

 * Rachel T. Eguia,
   
   Roles Conceptualization, Investigation, Methodology, Writing – original draft
   
   Affiliation Basic Sciences and Computational Biology, Fred Hutchinson Cancer
   Research Center, Seattle, Washington, United States of America
   
   https://orcid.org/0000-0001-5772-1907
   
   ⨯
 * Katharine H. D. Crawford,
   
   Roles Conceptualization, Methodology, Software, Writing – review & editing
   
   Affiliations Basic Sciences and Computational Biology, Fred Hutchinson Cancer
   Research Center, Seattle, Washington, United States of America, Department of
   Genome Sciences, University of Washington, Seattle, Washington, United States
   of America, Medical Scientist Training Program, University of Washington,
   Seattle, Washington, United States of America
   
   https://orcid.org/0000-0002-6223-4019
   
   ⨯
 * Terry Stevens-Ayers,
   
   Roles Data curation, Resources, Writing – review & editing
   
   Affiliation Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer
   Research Center, Seattle, Washington, United States of America
   
   https://orcid.org/0000-0002-7546-8439
   
   ⨯
 * Laurel Kelnhofer-Millevolte,
   
   Roles Investigation
   
   Affiliation Medical Scientist Training Program, University of Washington,
   Seattle, Washington, United States of America
   
   https://orcid.org/0000-0002-1635-1222
   
   ⨯
 * Alexander L. Greninger,
   
   Roles Data curation, Resources, Writing – review & editing
   
   Affiliations Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer
   Research Center, Seattle, Washington, United States of America, Department of
   Laboratory Medicine and Pathology, University of Washington, Seattle,
   Washington, United States of America
   
   ⨯
 * Janet A. Englund,
   
   Roles Data curation, Resources, Writing – review & editing
   
   Affiliations Seattle Children’s Research Institute, Seattle, Washington,
   United States of America, Department of Pediatrics, University of Washington,
   Seattle, Washington, United States of America
   
   https://orcid.org/0000-0003-1134-4178
   
   ⨯
 * Michael J. Boeckh,
   
   Roles Data curation, Resources, Writing – review & editing
   
   Affiliation Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer
   Research Center, Seattle, Washington, United States of America
   
   https://orcid.org/0000-0003-1538-7984
   
   ⨯
 * Jesse D. Bloom
   
   Roles Conceptualization, Funding acquisition, Software, Supervision,
   Visualization, Writing – original draft, Writing – review & editing
   
   * E-mail: jbloom@fredhutch.org
   
   Affiliations Basic Sciences and Computational Biology, Fred Hutchinson Cancer
   Research Center, Seattle, Washington, United States of America, Department of
   Genome Sciences, University of Washington, Seattle, Washington, United States
   of America, Howard Hughes Medical Institute, Seattle, Washington, United
   States of America
   
   https://orcid.org/0000-0003-1267-3408
   
   ⨯


A HUMAN CORONAVIRUS EVOLVES ANTIGENICALLY TO ESCAPE ANTIBODY IMMUNITY

 * Rachel T. Eguia, 
 * Katharine H. D. Crawford, 
 * Terry Stevens-Ayers, 
 * Laurel Kelnhofer-Millevolte, 
 * Alexander L. Greninger, 
 * Janet A. Englund,  …
 * Michael J. Boeckh, 
 * Jesse D. Bloom

x
 * Published: April 8, 2021
 * https://doi.org/10.1371/journal.ppat.1009453
 * 


 * Article
 * Authors
 * Metrics
 * Comments
 * Media Coverage

 * Abstract
 * Author summary
 * Introduction
 * Results
 * Discussion
 * Methods
 * Supporting information
 * Acknowledgments
 * References

 * Reader Comments (0)
 * Figures




ABSTRACT

There is intense interest in antibody immunity to coronaviruses. However, it is
unknown if coronaviruses evolve to escape such immunity, and if so, how rapidly.
Here we address this question by characterizing the historical evolution of
human coronavirus 229E. We identify human sera from the 1980s and 1990s that
have neutralizing titers against contemporaneous 229E that are comparable to the
anti-SARS-CoV-2 titers induced by SARS-CoV-2 infection or vaccination. We test
these sera against 229E strains isolated after sera collection, and find that
neutralizing titers are lower against these “future” viruses. In some cases,
sera that neutralize contemporaneous 229E viral strains with titers >1:100 do
not detectably neutralize strains isolated 8–17 years later. The decreased
neutralization of “future” viruses is due to antigenic evolution of the viral
spike, especially in the receptor-binding domain. If these results extrapolate
to other coronaviruses, then it may be advisable to periodically update
SARS-CoV-2 vaccines.


AUTHOR SUMMARY

Hopes for controlling SARS-CoV-2 rely on vaccination or infection to confer
immunity that protects against subsequent infection. However, the “common-cold”
seasonal coronaviruses re-infect people every few years. It has been unclear if
these re-infections occur because immunity wanes rapidly, or because the virus
evolves to escape immunity elicited by prior infection. Here we investigate the
second hypothesis in the context of the common-cold coronavirus 229E. We test
how well antibodies in old human sera neutralize both contemporaneous old 229E
viruses, and more recent viruses that evolved after the sera was collected. We
find that as 229E evolves, its spike protein accumulates mutations that escape
neutralization by older human sera. The rate at which viral evolution degrades
immunity varies among individuals, but in some cases less than a decade of
evolution is sufficient to completely eliminate neutralization by human sera
that is potent against contemporaneous viruses. Many of the viral mutations
occur in the same regions of the spike (the RBD and NTD) that are changing in
emerging variants of SARS-CoV-2. Therefore, our results suggest that coronavirus
vaccines may need to be periodically updated to keep pace with viral evolution.


FIGURES

  

Citation: Eguia RT, Crawford KHD, Stevens-Ayers T, Kelnhofer-Millevolte L,
Greninger AL, Englund JA, et al. (2021) A human coronavirus evolves
antigenically to escape antibody immunity. PLoS Pathog 17(4): e1009453.
https://doi.org/10.1371/journal.ppat.1009453

Editor: Adam S. Lauring, University of Michigan, UNITED STATES

Received: March 1, 2021; Accepted: March 4, 2021; Published: April 8, 2021

Copyright: © 2021 Eguia et al. This is an open access article distributed under
the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.

Data Availability: All data are available on GitHub at
https://github.com/jbloomlab/CoV_229E_antigenic_drift.

Funding: This work was supported by the following grants from the National
Institute of Allergy and Infectious Disease of the National Institutes of Health
(https://www.niaid.nih.gov/): R01AI127893 (to JDB), R01AI141707 (to JDB),
F30AI149928 (to KDC). JDB is an Investigator of the Howard Hughes Medical
Institute (HHMI, https://www.hhmi.org/). The funders had no role in study
design, data collection and analysis, decision to publish, or preparation of the
manuscript.

Competing interests: I have read the journal’s policy and the authors of this
manuscript have the following competing interests: MJB has consulted for Moderna
and Vir Biotechnologies, and received research funding from Regeneron and Vir
Biotechnologies. JAE has consulted for Meissa Vaccines and Sanofi Pasteur, and
received research funding from Merck, GlaxoSmithKline, Pfizer, and AstraZeneca.
The other authors declare no competing interests.


INTRODUCTION

The SARS-CoV-2 pandemic has caused an urgent need to determine how well antibody
immunity protects against SARS-CoV-2 infection. The evidence so far is
promising. Neutralizing and anti-spike antibodies elicited by natural infection
correlate with reduced SARS-CoV-2 infection of humans [1,2], and vaccines that
elicit such antibodies protect humans with high efficacy [3]. These findings in
humans are corroborated by a multitude of animal studies showing that
neutralizing antibodies to the SARS-CoV-2 spike protect against infection and
disease [4–7].

However, humans are repeatedly re-infected with the “common-cold” coronaviruses
229E, OC43, HKU1, and NL63 [8–10]. For instance, serological studies suggest
that the typical person is infected with 229E every 2–3 years [8,10], although a
lower infection rate and no 229E re-infections were reported in a 4-year study
that identified infections by the criteria of a positive PCR test in the context
of respiratory illness [11]. In any case, the fact that common-cold coronavirus
re-infections occur at some appreciable rate has led to concerns that
coronavirus immunity is not “durable.” These concerns initially focused on the
possibility that the immune response itself is not durable [12]. This
possibility now seems less likely, as SARS-CoV-2 infection induces neutralizing
antibodies and memory B cells with dynamics similar to other respiratory viruses
[13–16].

But there is another mechanism by which viruses can re-infect even in the face
of long-lived and effective antibodies: antigenic evolution. For example,
infection with influenza virus elicits antibodies that generally protect humans
against that same viral strain for at least several decades [17,18].
Unfortunately, influenza virus undergoes rapid antigenic evolution to escape
these antibodies [19], meaning that although immunity to the original viral
strain lasts for decades, humans are susceptible to infection by its descendants
within about 5 years [17,20]. This continual antigenic evolution is the reason
that the influenza vaccine is periodically updated.

Strangely, the possibility of antigenic evolution by coronaviruses has received
only modest attention, perhaps because coronaviruses have lower mutation rates
than other RNA viruses [21,22]. However, mutation rate is just one factor that
shapes antigenic evolution; influenza and measles virus both have high mutation
rates, but only the former undergoes rapid antigenic evolution. Furthermore, the
assumption of minimal coronavirus antigenic evolution is not supported by the
limited evidence to date. In the 1980s, human-challenge studies found that
individuals infected with one strain of 229E were resistant to re-infection with
that same strain, but partially susceptible to a different strain [23].
Additional experimental studies suggest that sera or antibodies can
differentially recognize spike proteins from different 229E strains [24,25].
From a computational perspective, several studies have reported that the spikes
of 229E and OC43 evolve under positive selection [26–28], which is often a
signature of antigenic evolution.

Here we experimentally assess whether coronavirus 229E escapes neutralization by
human polyclonal sera by reconstructing the virus’s evolution over the last
several decades. We show that historical sera that potently neutralize virions
pseudotyped with contemporaneous 229E spikes often have little or no activity
against spikes from 229E strains isolated 8–17 years later. Conversely, modern
sera from adults generally neutralize spikes from a wide span of historical
viruses, whereas modern sera from children best neutralize spikes from recent
viruses that circulated during the children’s lifetimes. These patterns are
explained by antigenic evolution of the spike, especially within the
receptor-binding domain. If SARS-CoV-2 undergoes similarly rapid antigenic
evolution, then it may be advisable to periodically update vaccines to keep pace
with viral evolution.


RESULTS


PHYLOGENETIC ANALYSIS OF 229E SPIKES TO IDENTIFY HISTORICAL STRAINS FOR
EXPERIMENTAL STUDY

We focused our studies on the viral spike protein because it is the main target
of neutralizing antibodies [29], and because anti-spike antibodies are the
immune parameter best established to associate with protection against
coronavirus infection in humans [1–3,30,31].

Because SARS-CoV-2 has circulated in humans for just over a year, we needed to
choose another coronavirus with a more extensive evolutionary history. Of the
four human-endemic common-cold coronaviruses, the two alphacoronaviruses 229E
and NL63 are similar to SARS-CoV-2 in binding a protein receptor via the spike’s
receptor-binding domain (RBD, also known as S1-B) [6,32,33]. In contrast, the
two betacoronaviruses OC43 and HKU1 bind glycan receptors via the spike’s
N-terminal domain (NTD, also known as S1-A) [34]. Antibodies that block receptor
binding dominate the neutralizing activity of immunity elicited by SARS-CoV-2
infection [35–37], so we reasoned that even though SARS-CoV-2 is a
betacoronavirus, its antigenic evolution is more likely to be foreshadowed by
the two human alphacoronaviruses that also use their RBD to bind a protein
receptor. Of these two viruses, we chose 229E since it was first identified in
humans >50 years ago [38], whereas NL63 was only identified in 2003 [39].

We inferred a phylogenetic tree of 229E spikes from direct or low-passage human
isolates (Fig 1A), excluding older strains passaged extensively in the lab [38].
There are several important features of the tree. First, it is clock-like, with
sequence divergence proportional to virus isolation date (Figs 1A and S1).
Second, the tree is “ladder-like,” with short branches off a single trunk (Fig
1A). The ladder-like shape of the 229E phylogeny has been noted previously
[26,27,40], and is a signature of viruses such as influenza for which immune
pressure drives population turnover by selecting for antigenic variants [41–43].
Third, sequences group by date rather than country of isolation (in Fig 1A,
sequences from different countries but the same year are nearby). Phylogenies
that organize by date rather than geography indicate fast global transmission,
another signature of human influenza virus [44,45]. Finally, although there is
some intra-spike recombination, it is among closely related strains and does not
affect the broader topology of the tree (S2 Fig). For our study, the key
implication of the above observations is that date of virus isolation is a good
proxy for evolutionary position, since 229E evolves primarily along a single
trajectory through time.

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Fig 1. Spikes used in this study.



(A) Phylogenetic tree of 229E spikes, with tips colored by the country from
which the virus was isolated. The spikes used in the experiments are indicated
with black text and square shapes. The tree is a maximum-likelihood inference
with IQ-TREE [82] with a codon-substitution model and re-scaled with TreeTime
[84] to position tips by to date of isolation. S1 Fig shows a tree with branch
lengths proportional to divergence rather than time, and validates clock-like
evolution. S2 Fig shows recombination does not substantially affect the
phylogenetic placements of the spikes used in the experiments. (B) Protein
sequence divergence of the spikes used in the experiments, computed over just
the receptor-binding domain (RBD) or the full sequence. Divergence is the
Levenshtein distance between the amino-acid sequences divided by the number of
sites.



https://doi.org/10.1371/journal.ppat.1009453.g001

For our experiments, we chose five spikes from 229E viruses spaced at roughly
8-year intervals spanning 1984 to 2016 (Fig 1A). We synthesized genes encoding
all five spikes, truncating the last 19 residues of the cytoplasmic tail since
this improves titers of spike-pseudotyped viruses [13,46,47]. These five spikes
differ by up to 4% in amino-acid sequence over their entire lengths, but are
vastly more different in their RBDs, with 17% RBD divergence between 1984 and
2016 (Fig 1B). We generated lentiviral particles pseudotyped with each spike,
and found that all five supported high infectious titers in cells expressing
229E’s receptor aminopeptidase N [33] and the activating protease TMPRSS2 [48]
(S3 Fig). Any major antigenic evolution by 229E since the 1980s should be
captured by differences among these five spikes.


NEUTRALIZING TITERS OF HISTORICAL SERA DROP RAPIDLY AGAINST SPIKES FROM “FUTURE”
VIRUSES

To test if the 229E spikes had evolved to escape neutralization by human
immunity, we used historical sera collected from adults between 1985 and 1990.
The sera were all collected from apparently healthy individuals, and no
information of recent respiratory virus infections were available (see Methods
for details). Since the typical person is infected with 229E every 2–5 years
[8,10,11], many of these individuals were likely infected with 1984-like viruses
within a few years preceding sera collection. None of the individuals would have
been infected with any of the later viruses, since those viruses did not yet
exist at the time of sera collection.

Nearly all sera collected from 1985–1990 had at least some neutralizing activity
against viral particles pseudotyped with the 1984 spike (25 of 27 sera had
titers >1:10; S4 and S5 Figs). We focused further analysis on the roughly 30% of
sera (8 of 27) that had neutralizing titers against the 1984 spike of >1:90 (S5
Fig). Our reason for focusing on these sera is that their anti-229E neutralizing
titers are comparable to anti-SARS-CoV-2 sera neutralizing titers several months
after recovery from COVID-19 [13,16] or receipt of the Moderna mRNA-1273 vaccine
[49].

All sera that potently neutralized virions pseudotyped with the 1984 spike had
reduced titers against more recent spikes (Fig 2A). In some cases, the drop in
neutralization of more recent spikes was dramatic. For instance, serum collected
from a 28-year old in 1990 neutralized the 1984 spike at a titer of 1:125 but
did not neutralize the 1992 spike at our limit of detection of 1:10 (Fig 2A).
Similarly, serum collected from a 24-year old in 1987 neutralized the 1984 spike
at 1:120 but barely neutralized the 1992 spike and did not detectably neutralize
spikes more recent than 1992 (Fig 2A). Only 2 of 8 sera that potently
neutralized the 1984 spike detectably neutralized all subsequent spikes, and
only at greatly reduced titers against the most recent spikes.

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Fig 2. The neutralizing activity of human sera is lower against “future” viruses
than those that elicited the immunity.



(A) Sera collected between 1985 and 1990 was tested in neutralization assays
against spikes from viruses isolated between 1984 and 2016. Each plot facet is a
different serum, and black points show its neutralizing titer against viruses
from the indicated year. Blue shading indicates the portion of plotted timeframe
during which the individual could have been infected prior to serum collection.
The dotted gray horizontal line indicates the limit of detection (titer of
1:10). Plot titles give the year of serum collection, the individual’s age when
the serum was collected, and the serum ID. (B) Plots like those in (A) but for
sera collected between 1993 and 1995. (C) The fold change in neutralization
titer against viruses isolated 8–9 or 16–17 years in the “future” relative to
the virus isolated just before the serum was collected. Box plots show the
median and interquartile range, and each point is the fold change for a single
serum. For a few sera (triangles), the fold change is censored (as an upper
bound) because the titer against the future virus was below the limit of
detection.



https://doi.org/10.1371/journal.ppat.1009453.g002

To confirm that these results reflect antigenic evolution rather than some
unique neutralization susceptibility of the 1984 spike, we repeated similar
experiments using sera collected from 1992–1995 and initially screening for
neutralization of the 1992 spike. Again, nearly all sera (18 of 19) detectably
neutralized the 1992 spike, with about a quarter (5 of 19) having titers >1:90
(S4 and S5 Figs). These potent sera also neutralized the older 1984 spike with
high titers, but again generally had lower activity against spikes from viruses
isolated after the sera were collected (Fig 2B). Together, the results from the
two sera collection timeframes indicate that the 229E spike is evolving
antigenically, such that immunity elicited by infection with prior viruses is
often ineffective at neutralizing future viruses.

To quantify the rate of antigenic evolution, for all sera in Fig 2A and 2B we
computed the drop in neutralization titer against spikes from one and two
timepoints later relative to the contemporaneous spike. The median drop in titer
was 4-fold against viruses from 8–9 years in the future, and >6-fold for viruses
16–17 years in the future (Fig 2C). However, these medians mask substantial
serum-to-serum variation in neutralization of antigenically evolved future
viruses. Neutralization by some sera is eroded >10-fold by just 8–9 years of
viral evolution, whereas neutralization by a few sera is unaffected even by
16–17 years of evolution.


MODERN SERA NEUTRALIZE VIRUSES THAT CIRCULATED THROUGHOUT AN INDIVIDUAL’S
LIFETIME

The above results show that viral antigenic evolution erodes the capacity of
anti-229E immunity to neutralize the future descendants of the viruses that
elicited the immunity. We next addressed a related question: does serum immunity
durably retain the capacity to neutralize historical 229E strains that an
individual was exposed to many years ago?

To address this question, we used modern sera collected in 2020 from children
and adults. The adults were alive during circulation of all five 229E spikes in
our panel (i.e., they were born before 1984), but the children could only have
been exposed to the more recent spikes. We screened 31 modern sera against the
2016 spike, and found that 25 of 31 detectably neutralized at a threshold of
1:10 (S4 and S5 Figs). We again focused further analysis on the more potent sera
with titers >1:90 (7 of 31 sera, S5 Fig).

Modern adult sera that potently neutralized the 2016 spike also neutralized all
prior spikes dating back to 1984 (Fig 3). In contrast, the children’s sera
neutralized spikes from viruses that circulated during the children’s lifetimes
but often had reduced activity against spikes from before the children were born
(Fig 3). However, neutralization by children’s sera generally extends further
“back in time” to viruses that preceded birth than neutralization by adult sera
in Fig 2A and 2B extends “forward in time” to viruses that circulated after the
sera was collected. Similar time asymmetry in antigenic evolution has been
described for influenza virus [50,51]. Overall, the results in Fig 3 show that
neutralizing immunity can encompass the entire spectrum of spikes an individual
has been exposed to, consistent with the notion that reduced neutralization of
future viruses is due to antigenic evolution rather than a lack of durability in
immunity itself.

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Fig 3. Neutralizing titers of sera collected in 2020 are higher against
historical viruses that circulated during an individual’s lifetime than viruses
isolated before the individual was born.



As in Fig 2A and 2B, each plot facet is a different serum with the title giving
the individual’s age and black points indicating the titer against spikes from
viruses isolated in the indicated year. Blue shading represents the portion of
the plotted timeframe during which the individual was alive: for adults this is
the entire timeframe, but for children the left edge of the blue shading
indicates the birth year.



https://doi.org/10.1371/journal.ppat.1009453.g003


MUCH OF THE ANTIGENIC EVOLUTION IS DUE TO MUTATIONS IN THE SPIKE’S
RECEPTOR-BINDING DOMAIN (RBD)

We next sought to identify the region(s) within the 229E spike where mutations
drive antigenic drift. Coronavirus spikes consist of two subunits, S1 and S2,
and it is well known that S2 is relatively conserved whereas S1 is more rapidly
evolving [29,52]. The S1 subunit itself consists of several domains, and we were
inspired by several excellent papers by Rini and colleagues to pursue the
hypothesis that 229E’s antigenic drift might be driven by amino-acid
substitutions within the three loops in the S1 RBD that bind the cellular
receptor [25,53].

We first calculated the protein sequence variability at each residue across an
alignment of 229E spikes isolated between 1984 and 2019 (Fig 4A). As expected,
most sequence variability was in the S1 subunit, with particularly high
variability in the three receptor-binding loops within the RBD (Fig 4A).
However, there was also substantial variability within some portions of the
N-terminal domain (NTD) as well as other parts of the S1 subunit. The
variability of each site in spike is projected onto the protein structure in Fig
4B.

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Fig 4. Antigenic evolution is primarily due to changes in the spike’s receptor
binding domain (RBD).



(A) At top is a schematic of the 229E spike. Within the S1 subunit, the
schematic indicates the N-terminal domain (NTD, also known as S1-A) and the RBD
(also known as S1-B). The three loops in the RBD that bind the virus’s APN
receptor are indicated [53]. Below the schematic is a plot of sequence
variability across the alignment of 229E spikes in Fig 1A. Variability is
quantified as the effective number of amino acids at a site [86], with a value
of one indicating complete conservation and larger values indicating more
sequence variability. (B) Site entropy mapped on 229E spike structure (PDB 6U7H,
[53]). (C) Neutralizing titers of sera collected between 1985 and 1990 against
either the full spike of “future” viruses or chimeras consisting of the 1984
spike containing the RBD from “future” viruses. The plot format and the black
circles (full spike) are repeated from Fig 2A with the addition of the orange
triangles showing the titers against the chimeric spikes.



https://doi.org/10.1371/journal.ppat.1009453.g004

To experimentally test the extent that mutations in the RBD explained antigenic
evolution, we created chimeras consisting of the 1984 spike with the RBD
replaced by that of each of the four subsequent spikes. All these RBD-chimeric
spikes supported efficient entry by pseudotyped viral particles (S3 Fig). We
performed neutralization assays using the chimeric spikes against the sera from
1985–1990 that potently neutralized the 1984 spike (Fig 4C). For all sera with
neutralizing activity that was rapidly eroded by antigenic evolution, the drops
in titer against more recent spikes were paralleled by drops in titer against
the RBD-chimeric spikes (e.g., 26 and 24-year olds in Fig 4C). However, this
trend did not hold for some sera that were more resistant to antigenic
evolution: for instance, serum from the 29-year old did not neutralize the 2016
spike, but neutralized the chimera with the 2016 RBD (Fig 4C). Overall, these
results suggest that when the neutralizing activity of potent human sera is
rapidly eroded by viral evolution this is often due to mutations within the RBD,
but that antigenic evolution also occurs elsewhere in the spike. In this
respect, it is worth noting that while the neutralizing activity of SARS-CoV-2
immunity elicited by infection primarily targets the RBD [36,54], mutations to
the NTD also reduce neutralization by some antibodies and sera [55–62]—and some
regions of the NTD undergo significant sequence evolution in 229E (Fig 4A).


DISCUSSION

We have experimentally demonstrated that the spike of a human coronavirus
evolves antigenically with sufficient speed to escape neutralization by many
polyclonal human sera within one to two decades. This finding suggests that one
reason that humans are repeatedly re-infected with seasonal coronaviruses may be
that evolution of the viral spike erodes the immunity elicited by prior
infections.

How does the rate of antigenic evolution of 229E compare to that of influenza
virus? Remarkably, we could find no studies that measured how quickly influenza
evolution erodes neutralization by human sera. However, numerous studies examine
influenza antigenic evolution using hemagglutination-inhibition (HAI) assays
with sera from ferrets infected with single viral strains [63]. The rate at
which 229E escapes neutralization by human sera is several fold slower than the
rate at which influenza A/H3N2 escapes HAI by ferret sera, but comparable to the
rate of such escape by influenza B [19,64]. However, the sera of ferrets
infected by a single influenza virus strain tend to recognize fewer viral
strains than sera from humans who have been repeatedly infected with many
strains [65–67]. Therefore, ferret sera HAI may overestimate how quickly
influenza evolution erodes neutralization by actual human sera. For this reason,
further work is needed to enable head-to-head comparisons of antigenic evolution
across these viruses.

The rapid antigenic evolution of the 229E spike might seem puzzling given that
coronaviruses have a lower mutation rate than other RNA viruses [21,22]. But the
rate of phenotypic evolution is not equal to mutation rate; evolution also
depends on the effects of mutations and how selection acts on them. These other
factors explain why influenza undergoes rapid antigenic evolution while measles
does not, despite having a similar mutation rate. Specifically, mutations to
influenza hemagglutinin are often well tolerated [68], and single hemagglutinin
mutations can have huge effects on escaping polyclonal sera [69]. In contrast,
measles surface proteins are less tolerant of mutations [70], and the single
mutations that are tolerated never more than modestly affect measles
neutralization by polyclonal sera [71]. In these respects, coronaviruses
unfortunately seem more similar to influenza than measles. The neutralizing
antibody response to SARS-CoV-2 is often focused on just a small portion of
spike [36,61,72,73], and key receptor-binding loops are mutationally tolerant in
the spikes of both 229E [25,53] and SARS-CoV-2 [74]. Therefore, even though
mutations to coronaviruses occur at a lower rate, they are acted on by selection
in a fashion more similar to influenza than measles [27].

A striking aspect of our results is the extreme person-to-person variation in
how rapidly neutralizing immunity is eroded by the evolution of coronavirus
229E. Some sera that potently neutralize contemporaneous virus have no
detectable activity against viral strains isolated 8+ years later. But other
sera maintain neutralizing activity against strains isolated over two decades
later. This finding is reminiscent of how mutations to influenza virus can have
vastly different effects on neutralization by sera from different individuals
[69]. Identifying what factors determine how rapidly an individual’s coronavirus
immunity is eroded by viral mutations is an important area for future work, as
it would be desirable for SARS-CoV-2 vaccines to elicit immunity that is
relatively robust to viral evolution.

The biggest question is what our work implies about possible antigenic evolution
by SARS-CoV-2. While it is impossible to know if SARS-CoV-2 will evolve
similarly to 229E, it is ominous that mutations affecting neutralization by
polyclonal human sera are already present among SARS-CoV-2 lineages
[54,59,61,73,75–77] even though a large fraction of the human population is
still naive and so presumably exerting little immune pressure on the virus. But
two facts provide hope even in light of our observation that human coronaviruses
evolve to escape neutralizing immunity. First, the level of immunity required to
prevent severe COVID-19 may be low [3], perhaps because the slower course of
disease provides more time for a recall immune response than for “quicker”
viruses such as influenza. An optimistic interpretation is that disease might
often be mild even if viral antigenic evolution allows re-infections. Second,
many leading SARS-CoV-2 vaccines use new technologies such as mRNA-based
delivery [78] that should make it easy to update the vaccine if there is
antigenic evolution in spike. For this reason, we suggest that SARS-CoV-2
evolution should be monitored for antigenic mutations that might make it
advisable to periodically update vaccines.


METHODS


ETHICS STATEMENT

The human sera from the 1980s and 1990s from the Infectious Disease Sciences
Biospecimen Repository at the Vaccine and Infectious Disease Division (VIDD) of
the Fred Hutchinson Cancer Research Center were collected from prospective bone
marrow donors with approval from the Fred Hutch’s Human Subjects Institutional
Review Board. The modern children’s sera from 2020 are residual sera collected
at Seattle Children’s Hospital with approval from the Seattle Children’s
Hospital Human Subjects Institutional Review Board. All sera are fully
de-identified.


COMPUTER CODE

The computer code is on GitHub at
https://github.com/jbloomlab/CoV_229E_antigenic_drift. Relevant parts of this
GitHub repository are called out in the Methods below; in addition the
repository itself includes a README that aids in navigation.


PHYLOGENETIC ANALYSIS OF 229E SPIKES

To assemble a set of 229E spikes, we downloaded all accessions for “Human
coronavirus 229E (taxid:1137)” available from NCBI Virus as of July-13-2020.
These accessions are listed at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/data/NCBI_Virus_229E_accessions.csv.
The NCBI information for some sequence accessions (particularly older sequences)
were missing metadata that was available in publications describing the
sequences [24,26]. For these accessions, we manually extracted the relevant
metadata from the publications (see
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/data/extra_229E_accessions_metadata.yaml).
We also identified a few sequences that were clear outliers on the date-to-tip
regression in the analyses described below, and so are probably mis-annotations;
these accessions were excluded (see
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/data/accessions_to_include_exclude_annotate.yaml).

We parsed full-length human-isolate spikes encoding unique proteins from this
sequence set (see
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/results/get_parse_spikes.md),
used mafft [79] to align the protein sequences, and used a custom Python script
(https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/prot_to_codon_alignment.py)
to build a codon alignment from the protein alignment (S1 Data). We used GARD
[80,81] to screen for recombination (see tanglegram in S2 Fig and code at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/results/gard_tanglegram.md).

The phylogenetic tree topology was inferred using IQ-TREE [82] using a
codon-substitution model [83] with a transition-transversion ratio and F3X4
empirical codon frequencies. We then used TreeTime [84] to root the tree (S2
Fig) and also re-scale the branch lengths for the time tree in Fig 1A. The tree
images were rendered using ETE 3 [85].

To compute the variability at each site in spike (Fig 4A), we used the same
alignment as for the phylogenetic analysis. We then computed the amino-acid
variability at each site as the effective number of amino acids, which is the
exponential of the Shannon entropy [86]. The domains of spike were annotated
using the definitions in [53], which are provided at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/data/AAK32191_hand_annotated.gp.

The Shannon entropy for each site was mapped onto the structure of 229E spike
(pdb 6U7H) to produce Fig 4B. Pymol v 2.4.1 was used to visualize the structure.
There are 3 gaps in this structure, including one in the NTD that included 2
variable sites which we were unable to include in the visualization.


PLASMIDS ENCODING 229E SPIKES AND RBD CHIMERAS

The protein sequences of the spikes used in the experiments are in S2 Data. We
deleted the last 19 amino acids of the spike’s C-terminus (in the cytoplasmic
tail) as this modification has been reported [13,46,47] and validated in our
hands (S3 Fig) to improve titers of virions pseudotyped with spike. For the
1984, 1992, 2001, 2008, and 2016 spikes, the protein sequence matches the
Genbank sequences for these viral strains (Fig 1A and S1 Data) except for the
tail deletion. For the RBD chimeras, we annotated domains of spike as in [53];
see
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/data/AAK32191_hand_annotated.gp.
We then designed the RBD-chimera proteins by replacing the RBD of the 1984 spike
with the RBD of each of the 1992, 2001, 2008, and 2016 spikes.

We designed human-codon-optimized gene sequences encoding each of these spike
proteins using the tool provided by Integrated DNA Technologies, had the genes
synthesized commercially, and cloned them into a CMV-driven expression plasmid.
Genbank sequences of the resulting plasmids are at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/tree/master/exptl_data/plasmid_maps.
The names of the plasmids are listed below (note how the names include “delta19”
or “d19” to indicate the C-terminal deletion as well as the year for that viral
strain and whether it is a chimera; note also that we created a plasmid for the
2016 spike that did not have the C-terminal deletion for the experiments in S3
Fig that validated the benefits of the deletion):

 * HDM-229E-Spike-d19-1984
 * HDM-229E-Spike-d19-1992
 * HDM-229E-Spike-d19-2001
 * HDM-229E-Spike-d19-2008
 * HDM-229E-Spike-Seattle2016
 * HDM-229E-Spike-delta19-Seattle2016
 * HDM-229E-Spike-d19-1984-1992RBD
 * HDM-229E-Spike-d19-1984-2001RBD
 * HDM-229E-Spike-d19-1984-2008RBD
 * HDM-229E-Spike-d19-1984-2016RBD


GENERATION AND TITERING OF 229E SPIKE-PSEUDOTYPED LENTIVIRAL PARTICLES ENCODING
LUCIFERASE AND ZSGREEN

We generated spike-pseudotyped lentiviral particles using the same approach that
we have recently described for SARS-CoV-2 [13,87]. This approach involves
creating pseudotyped lentiviral particles by transfecting cells with a plasmid
expressing spike, a plasmid expressing a lentiviral backbone encoding luciferase
and ZsGreen, and plasmids expressing the other lentiviral proteins necessary for
virion formation [13,87]. The only modifications for this study are that we used
the plasmids expressing the 229E spike described above rather than plasmids
expressing the SARS-CoV-2 spike, and that after producing the pseudotyped
lentiviral particles we infected them into target cells engineered to be
infectable by the 229E spike.

Specifically, the 229E spike binds to human aminopeptidase N (APN) to initiate
viral entry [33]. Therefore, to make 293T cells infectable by 229E, we
transiently transfected them with an APN protein expression plasmid
(SinoBiological, NM_001150.2) prior to seeding the cells for infection. To
further promote lentiviral infection, we simultaneously transiently transfected
them with a plasmid encoding transmembrane serine protease 2 (TMPRSS2), which
facilitates 229E-spike mediated viral entry by cleaving and activating the spike
[48]. We used the TMPRSS2-expressing plasmid pHAGE2_EF1aInt_TMPRSS2_IRES_mCherry
[88].

For titering the spike-pseudotyped particles in these cells, we used the
following procedure. To mitigate any possible well-to-well differences in
transfection efficiency in a 96-well plate format, we first bulk transfected a
dish of 293T cells, followed by seeding the 96-well plates routinely used in
neutralization assays and viral titering. Specifically, an approximately 90%
confluent 10 cm dish of 293T cells was transfected with 8.5 μg APN-expressing
plasmid, 1 μg of TMPRSS2-expressing plasmid, and 0.5 μg of carrier DNA (Promega,
E4881) to achieve an 8.5:1 ratio of APN:TMPRSS2. We found that this ratio gave
sufficient TMPRSS2 expression, while maintaining low levels of cell toxicity.
Cells were transfected using the Bioland Scientific BioT transfection reagent
following the manufacturer’s protocol but incubating transfection complexes for
15 minutes at room temperature instead of the recommended 5 minutes as we have
anecdotally observed that this extended incubation increases transfection
efficiency. After 5–6 hours, transfection supernatant was removed and the APN
and TMPRSS2-transfected 293T cells were trypsinized (Fisher, MT25053CI). Cells
were then seeded in clear bottom, black-walled, poly-L-lysine coated 96-well
plates that were either professionally pre-coated (Greiner, 655936) or
hand-coated (Greiner, 655090) with poly-L-lysine solution (Millipore Sigma,
P4704) at 1.75x10e4 cells per well in 50 μL D10 growth media (DMEM with 10%
heat-inactivated FBS, 2 mM L-glutamine, 100 U/mL penicillin, and 100 μg/mL
streptomycin). Plates were incubated at 37°C with 5% CO2 for 20–24 hours, and
cells were infected with serial 2-fold serial dilutions of the pseudotyped
lentiviral particles. These viral dilutions were made in TC-treated “set-up”
96-well plates and then transferred to the pre-seeded 293T-ACE2-TMPRSS2 cells
from the previous day.

Approximately 50–52 hours later, we quantified infection by reading the
luminescence signal produced from the luciferase encoded in the lentiviral
backbone. Specifically, 100 μL of media in each well was removed—while being
sure to leave the cells undisturbed—leaving approximately 30 μL of media left
over. Then an equal volume of Bright-Glo reagent (Promega, E2610) was added to
the remaining 30 uL of media in each well and the solution was mixed up and down
to ensure complete cell lysis. In order to minimize the potential for premature
luciferase excitation, special care was taken to protect the assay plates from
light. Mainly, assay plate preparation was performed in a biosafety hood with
the lights off and plates were covered in tin foil after the addition of the
luciferase reagent. The luminescence was then measured on a TECAN Infinite M1000
Pro plate reader with no attenuation and a luminescence integration time of 1
second. S3 Fig shows the titers achieved for each 229E spike variant, and also
demonstrates the importance of the spike cytoplasmic tail deletion and the
expression of APN and TMPRSS2 for efficient viral infection. Note that for one
panel in S3 Fig, we instead determined the titer by using flow cytometry to
detect the fraction of cells expressing the ZsGreen also encoded in the
lentiviral backbone.


HUMAN SERA

All sera used in this study, along with relevant metadata (e.g., collection
date, patient age, and the measured neutralization titer against each assayed
virus) are listed in S3 Data, which is also available at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/exptl_data/results/all_neut_titers.csv.

Most of the historical human sera from the 1980s and 1990s are identified by the
prefix SD in S3 Data (e.g., SD85_1). These sera were obtained from the
Infectious Disease Sciences Biospecimen Repository at the Vaccine and Infectious
Disease Division (VIDD) of the Fred Hutchinson Cancer Research Center in
Seattle, WA, and were collected from prospective bone marrow donors with
approval from the Human Subjects Institutional Review Board. A few of the
historical sera are residual samples obtained from Bloodworks Northwest that
were collected from adults in Seattle; these sera are identified by the prefix
FH in S3 Data (e.g., FH007TR). A few of the sera were collected from subjects
with exact ages that were unknown, but were adults old enough to have been alive
in 1984 (the isolation year of the first spike in our panel). No information on
recent respiratory virus infections was available for any of the sera samples.

The modern children’s sera from 2020 are identified by the prefix POP_ in S3
Data (e.g., POP_0007), and are residual sera collected at Seattle Children’s
Hospital in Seattle, WA, in March of 2020 with approval from the Human Subjects
Institutional Review Board. Each of these serum samples is from a unique
individual who was confirmed to be seronegative for SARS-CoV-2 by an anti-RBD
ELISA [89].

The modern adult sera from 2020 are identified by the prefix AUSAB (e.g.,
AUSAB-01) in S3 Data, and are residual sera from University of Washington Lab
Medicine that were collected for testing for HBsAb (for which they tested
negative).

For a negative control, we used serum from a goat that had not been infected
with the 229E human coronavirus; namely WHO goat serum (FR-1377) procured from
the International Reagent Resource.

All sera were heat inactivated prior to use by incubation at 56°C for
approximately 30 minutes.


NEUTRALIZATION ASSAYS

The 293T cells used for our neutralization assays were transfected to express
APN and TMPRSS2 and seeded as for the viral titering described above. The
neutralization assays were set up at 20–24 hours after seeding of the cells into
96-well plates. First, the heat-inactivated serum samples were diluted 1:10 in
D10 growth media followed by 3-fold serial dilutions in TC-coated 96-well
“set-up” plates, ultimately giving seven total dilutions per sample. These
dilutions were done in duplicate for each serum sample. Each 229E
spike-pseudotyped lentivirus was then diluted to achieve luciferase readings of
approximately 200,000 RLUs per well (the exact dilution factor varied among
viruses due to differences in titers; see S3 Fig). An equal volume of virus was
then added to each well of the virus plus sera “set-up” plates, and these plates
were incubated for 1 hour at 37°C with 5% CO2, after which 100 uL of each virus
plus sera mixture were transferred to the 293T-APN-TMPRSS2 cell plate that had
been seeded the day prior. Plates were incubated at 37°C with 5% CO2 for
approximately 50–52 hours, and then the luciferase signal was read as described
above for viral titering.

Each neutralization plate contained a column of positive control wells
consisting of cells plus virus incubated with D10 media but no sera, and a
negative control consisting of virus but no cells (we also confirmed that using
a cells-only negative control gave similar results). The fraction infectivity
was computed at each serum dilution as the fraction of the signal for the
positive control (averaged across the two positive control wells for each row)
after subtracting the background reading for the negative control. We then fit
2-parameter Hill curves with baselines fixed to 1 and 0 using neutcurve
(https://jbloomlab.github.io/neutcurve/). Note that the serum concentration
reported in these curves is the concentration at which the virus was
pre-incubated with the sera for 1 hour. All of the neutralization curves are
plotted in S4 Fig. All of the IC50s are tabulated in S3 Data. See
https://github.com/jbloomlab/CoV_229E_antigenic_drift/tree/master/exptl_data for
raw and processed plate reader data and all of the computer code used for the
fitting. Note that all assays were done in duplicate, but some sera-virus pairs
have additional readings as we re-ran selected sera-virus pairs to confirm that
results remained consistent across different assay days. In all cases the
day-to-day consistency was good, and the reported values are the mean IC50s
across all assays.


SUPPORTING INFORMATION

The evolution of the 229E spike is clock-like, with the number of substitutions
per site proportional to time.

Showing 1/8: ppat.1009453.s001.tif

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S1 FIG. THE EVOLUTION OF THE 229E SPIKE IS CLOCK-LIKE, WITH THE NUMBER OF
SUBSTITUTIONS PER SITE PROPORTIONAL TO TIME.

(A) Phylogenetic tree exactly like that in Fig 1 but with branch lengths
proportional to divergence (not re-scaled based on tip isolation date). (B) A
plot produced by TreeTime showing the correlation between the distance of tip
nodes from the root and sampling date. The fact that all points fall on a line
indicates that the evolution is clock-like.

https://doi.org/10.1371/journal.ppat.1009453.s001

(TIF)


S2 FIG. ALTHOUGH THERE IS SOME EVIDENCE OF RECOMBINATION AMONG CLOSELY RELATED
229E SPIKES, THIS RECOMBINATION DOES NOT ALTER THE RELATIVE PHYLOGENETIC
RELATIONSHIPS AMONG THE SPIKES USED IN THE EXPERIMENTS.

Specifically, GARD was used to analyze the same set of 229E spike sequences used
in Fig 1 with a nucleotide substitution model and three gamma-distributed rate
classes. The best-fitting model had a single recombination breakpoint at
nucleotide 1089 that improved the AIC by 60 units. The trees for each partition
were then rooted and branch-re-scaled using TreeTime, and the resulting
tanglegram was rendered using dendextend. As can be seen above, the
recombination is all between closely related sequences and does not alter the
relative position of the 1984, 1992, 2001, 2008, and 2016 spikes used in the
experiments. See
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/results/gard_tanglegram.md
for details of the analysis steps described above.

https://doi.org/10.1371/journal.ppat.1009453.s002

(TIF)


S3 FIG. THE 229E SPIKES WITH A CYTOPLASMIC TAIL DELETION PSEUDOTYPE LENTIVIRAL
PARTICLES THAT EFFICIENTLY INFECT 293T CELLS EXPRESSING THE SPIKE’S RECEPTOR
AMINOPEPTIDASE N (APN) AND THE ACTIVATING PROTEASE TMPRSS2.

(A) Titer in transduction units per ml as determined using flow cytometry of
lentiviral particles pseudotyped with the full-length 2016 spike or that spike
with a deletion of the last 19 residues in spike (the end of the cytoplasmic
tail) on 293T cells transfected with a plasmid expressing APN. The dotted gray
line is the limit of detection, and the titers in the absence of spike were
below this line (undetectable). (B) Efficient entry by the pseudotyped virions
depends on expression of APN and to a lesser extent TMPRSS2. Virions pseudotyped
with the 2016 spike with the C-terminal deletion were infected into 293T cells
transfected with plasmids expressing one or both of APN and TMPRSS2, and titers
were determined by luciferase luminescence. Titers are normalized to one. (C)
All of the 229E spikes and chimeras used in this study mediated efficient viral
entry. Lentiviral particles were pseudotyped with the indicated spike (in all
cases with the C-terminal deletion) and titers were determined using luciferase
luminescence on 293T cells transfected with plasmids expressing APN and TMPRSS2.

https://doi.org/10.1371/journal.ppat.1009453.s003

(TIF)


S4 FIG. NEUTRALIZATION CURVES FOR ALL ASSAYS.

Each facet is a serum, with titles indicating the year the serum was collected.
Each point is the fraction infectivity at that serum concentration averaged
across at least two replicates (error bars are standard error), with colors
indicating the virus. The fits are 2-parameter Hill curves with baselines fixed
to 1 and 0, and were fit using neutcurve
(https://jbloomlab.github.io/neutcurve/). IC50s are in S3 Data. The curves are
also at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/exptl_data/results/all_neut_by_sera.pdf

https://doi.org/10.1371/journal.ppat.1009453.s004

(TIF)


S5 FIG. INITIAL SCREENING OF SERA TO IDENTIFY SAMPLES WITH NEUTRALIZING TITERS
OF AT LEAST 1:90 THAT WERE THEN USED FOR THE REST OF THE STUDIES DESCRIBED IN
THE PAPER.

Each sera was tested against the most-recent virus isolated prior to the serum
collection date: in other words, sera collected between 1985–1990 was tested
against the 1984 spike, sera collected between 1992–1995 was tested against the
1992 spike, and sera collected in 2020 was tested against the 2016 spike. Each
point shows the neutralizing titer for a different serum (see S4 Fig for full
neutralization curves). Sera above the cutoff of 1:90 (blue dashed line) was
then used for further studies against the full panel of viruses (e.g., Figs 2,
3, and 4). The numbers at the top of the plot indicate the number of sera above
the cutoff out of the total sera tested in each timeframe. The dotted horizontal
line at the bottom of the plot is the lower limit of detection of the
neutralization assay. Quantitative neutralization titers for each sera are in S3
Data.

https://doi.org/10.1371/journal.ppat.1009453.s005

(TIF)


S1 DATA. CODON-LEVEL ALIGNMENT OF THE 229E SPIKE SEQUENCES.

This FASTA alignment is at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/results/spikes_aligned_codon.fasta

https://doi.org/10.1371/journal.ppat.1009453.s006

(TXT)


S2 DATA. A ZIP OF GENPEPT FILES GIVING THE PROTEIN SEQUENCES OF THE SPIKES USED
IN THE EXPERIMENTS.

There are nine sequences: the five spikes from the 1984, 1992, 2001, 2008, and
2016 viruses (named by strain as shown in Fig 1A), and the four chimeras that
consist of the 1984 spike with the RBD of each of the other strains. Each
GenPept file annotates key domains in the spike. Note that the C-terminal 19
amino acids are deleted off each spike. These files are at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/tree/master/results/seqs_for_expts

https://doi.org/10.1371/journal.ppat.1009453.s007

(ZIP)


S3 DATA. A CSV FILE GIVING THE NEUTRALIZATION TITER, COLLECTION DATE, AND
SUBJECT AGE AT TIME OF COLLECTION DATE FOR EACH SERUM SAMPLE ANALYZED IN THIS
STUDY.

This file is at
https://github.com/jbloomlab/CoV_229E_antigenic_drift/blob/master/exptl_data/results/all_neut_titers.csv

https://doi.org/10.1371/journal.ppat.1009453.s008

(CSV)


ACKNOWLEDGMENTS

We thank David Veesler, Allison Greaney, Tyler Starr, Kathryn Kistler, and
Trevor Bedford for helpful comments. We also thank the Vaccine and Infectious
Diseases Division of the Fred Hutch for supporting the biorepository used for
the 1980s and 1990s sera.


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