Interpreting SARS-CoV-2 evolution

Panum (1847)

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

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 the pandemic.

But evolution of SARS-CoV-2 is not mutation-limited

RBD

fluorescent ACE2

yeast

fluorescent tag on RBD

Yeast display of spike receptor-binding domain (RBD) to measure ACE2 binding

Starr et al (2020)

cell sorting

Deep mutational scanning: selections on libraries of mutants, read out by sequencing

Experiments identified N501Y as a mutation that increases ACE2 binding

Starr et al (2020)

RBD

fluorescently labeled antibody

yeast

fluorescent tag on RBD

Yeast display to measure how all RBD mutations escape antibody binding

Greaney et al (2021)

Viral infection is more biologically relevant measure of mutation effects

However, there are legitimate biosafety concerns about mutagenizing 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, 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)

Dadonaite et al (2024)

Measured how spike mutations affect three molecular phenotypes

Dadonaite et al (2024)

Measured how spike mutations affect three molecular phenotypes

Estimating variant fitness (multinomial logistic regression)

With Trevor Bedford & Ben Murrell

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

Dadonaite et al (2024)

Combining phenotypes offers best predictions (mutations can affect multiple phenotypes)

Dadonaite et al (2024)

We can explain ~55% of the variance in growth of different clades, with largest fraction of variance uniquely explained by sera escape.

Initially, most people were exposed to early strain, imprinting antibody response (     )

First exposed to early strain in original vaccine

First infected by an early strain (pre-Omicron)

Imprinting to early strain shapes antibody response even after later exposures

But antibody response of infants is imprinted by more recent strains

Imprinted by recent strain

We measured which spike mutations erode neutralization by antibodies from people imprinted with different strains

Adults vaccinated with original strain followed by various exposures

Adult sera from Helen Chu's HAARVI study; infant sera from Mary Staat's IMPRINT cohort

6-12 month infants first infected by XBB*

Bloom lab

These slides: https://slides.com/jbloom/awaji-cov

Thanks

Fred Hutch Cancer Center

Trevor Bedford

University of Washington

Helen Chu and HAARVI cohort

Neil King

David Veesler

Cincinnati Children's Hospital

Mary Staat

David Haslam

Allie Burrell

Kate Crawford

William Hannon

Caelan Radford

Brendan Larsen