Panum, 1846

The Faroe Islands

Panum was describing immune memory, which provides lifelong protection from measles.

What was reason for thinking coronavirus immunity would not be affected by viral mutations?

Coronaviruses have lower mutation rate than other RNA viruses

Coronaviruses are only RNA viruses with proofreading activity in their polymerase, and so have ~5- to 10-fold lower mutation rate than influenza virus

But rate is still high enough that evolution is not mutation-limited

The average single-nucleotide mutation to SARS-CoV-2 had occurred >10,000 independent times in human-transmitted SARS-CoV-2 by third year of pandemic.

Add some plot here

Evolution is not just mutation: also involves selection on phenotypic effects of mutations

We first asked: what is net effect of mutations to a coronavirus over decades of evolution in humans?

CoV-229E causes common colds and has been circulating in humans for a long time.

Typical person is infected every ~3 to 5 years.

We first asked: what is net effect of mutations to a coronavirus over decades of evolution in humans?

Evolution of CoV-229E spike

We experimentally generated CoV-229E spikes at ~8 year intervals so we could study them in the lab:

- 1984

- 1992

- 2001

- 2008

- 2016

Eguia et al

Eguia et al

Ideally vaccines would elicit evolution-resistant neutralizing antibodies (like those made by person at right) rather than evolution-sensitive antibodies (like those made by person at left)

Evolution erodes neutralization by sera from different people at different rates

We now know SARS-CoV-2 evolves to erode neutralizing antibodies, just like CoV-229E

Original vaccine induced hight neutralizing antibody titers against early viral strains

Lasrado et al (2023)

Main regions where neutralizing antibodies bind

Molecular basis of this antigenic evolution?

Lasrado et al (2023); Greaney et al (2021)

Lasrado et al (2023); Greaney et al (2021)

Molecular basis of this antigenic evolution?Mutations where antibodies bind

Sites of mutations in recent (BA.2.86) SARS-CoV-2 strain relative to early 2020 strain

So overall, some human RNA viruses evolve to escape immunity, others don't

Rate of viral antigenic evolution

Measles

Mumps

Influenza

SARS-CoV-2

All viruses have entry proteins, which are critical determinants of host range and immunity

target cell membrane

SARS-CoV-2 virion

Example: SARS-CoV-2's entry protein spike first binds ACE2 on target cells

spike protein

Image adapted from here

ACE2

After binding receptor, spike then fuses the viral and cell membranes to enable viral entry

viral membrane

cell membrane

spike

spike conformational change

Image adapted from here

ACE2

Antibodies to spike can block viral entry, such as by preventing receptor binding or fusion

antibody

Image adapted from here

Deep mutational scanning involves pooled selections on libraries of protein mutants, read out by deep sequencing

Initially we used yeast display of receptor binding domain (RBD) of SARS-CoV-2 spike

cell sorting

RBD

fluorescent ACE2

yeast

fluorescent tag on RBD

Yeast display allows us to separate RBD mutants by how strongly they bind ACE2

Starr et al (2020)

In 2020, we identified N501Y as affinity-enhancing mutation; by 2021 it was widespread in SARS-CoV-2

Starr et al (2020)

RBD

fluorescently labeled antibody

yeast

fluorescent tag on RBD

We also used yeast display to measure how all RBD mutations affect antibody binding

Greaney et al (2021)

But we wanted more relevant experiments: yeast display only measures binding

cell sorting

Viral infection is more biologically relevant measure of mutation effects

However, we are cognizant of biosafety concerns of mutating actual virus

actual SARS-CoV-2 virion: pathogen capable of spread in humans

pseudotyped lentiviral particle: not a pathogen, cannot spread in humans

actual SARS-CoV-2 virion: pathogen capable of spread in humans

pseudotyped lentiviral particle: not a pathogen, cannot spread in humans

Therefore we use pseudoviruses rather than actual replicative SARS-CoV-2

Pseudoviruses are modified viruses that can only undergo single round of infection

Crawford et al (2020)

Crawford et al (2020)

We need to link phenotype (spike mutant) and genotype (sequence encoded by virus)

To link genotype to phenotype link, we encode spike in viral genome with barcode

Dadonaite et al (2023)

We then create genotype-phenotype linked libraries by two-step process

Dadonaite et al (2023)

Result is library of spike mutant pseudoviruses with identifying barcodes

• Captures full cell-entry function of spike
• Each mutant identified by short barcode
• Pseudoviruses safe at biosafety-level 2
• Broadly applicable to viral entry proteins

Dadonaite et al (2023)

Measured how spike mutations to XBB.1.5 spike affect three molecular phenotypes

Dadonaite et al (2024)

Measured how spike mutations to XBB.1.5 spike affect three molecular phenotypes

Dadonaite et al (2024)

Deep mutational scanning correlates well with traditional neutralization assays

Dadonaite et al (2024)

Fitness from multinomial logistic regression

With Trevor Bedford & Ben Murrell

Deep mutational scanning measurements correlate with SARS-CoV-2 variant growth

Dadonaite et al (2024)

Combining phenotypes offers best predictions (because mutations can involve tradeoffs)

Dadonaite et al (2024)

Dadonaite et al (2024)

Can partially predict evolution in real-world from experiments!

• SARS-CoV-2 spike
• influenza hemagglutinin (HA)
• HIV envelope protein
• Lassa virus glycoprotein
• Nipah virus RBP and F proteins
• RSV G and F proteins
• Rabies G protein
• Chikungunya virus E proteins

All enveloped viruses have entry proteins

• SARS-CoV-2 spike
• influenza hemagglutinin (HA)
• HIV envelope protein
• Lassa virus glycoprotein
• Nipah virus RBP and F proteins
• RSV G and F proteins
• Rabies G protein
• Chikungunya virus E proteins

All enveloped viruses have entry proteins

Pseudovirus of clade 2.3.4.4b H5 HA

Dadonaite et al, bioRxiv (2024)

HA molecular phenotypes relevant to pandemic risk

Dadonaite et al, bioRxiv (2024)

HA molecular phenotypes relevant to pandemic risk

Dadonaite et al, bioRxiv (2024)

HA molecular phenotypes relevant to pandemic risk

Dadonaite et al, bioRxiv (2024)

HA molecular phenotypes relevant to pandemic risk

Dadonaite et al, bioRxiv (2024)

HA molecular phenotypes relevant to pandemic risk

Dadonaite et al, bioRxiv (2024)

These data can inform surveillance of H5 influenza viruses spreading in animals

We prospectively identified A160T as strongly reducing neutralization by sera elicited by candidate vaccine strains

(L122Q, P162Q, T199I)

Dadonaite et al, bioRxiv (2024)

A160T in recent human case in Missouri

Bloom lab

Bernadeta Dadonaite

Kate Crawford

Caelan Radford

Tyler Starr

Allie Greaney

Rachel Eguia

William Hannon

Jenny Ahn

Fred Hutch Cancer Center

Trevor Bedford

John Huddleston

University of Washington

Helen Chu and HAARVI cohort

Neil King

David Veesler

Slides: https://slides.com/jbloom/scripps-circuits-to-systems-2024

Thanks

Pirbright Institute

Thomas Peacock

University of Pennsylvania

Scott Hensley

Louise Moncla

Jordan Ort

St Jude Children's Hospital

Richard Webby