Pseudovirus deep mutational to forecast SARS-CoV-2 evolution
Jesse Bloom
Fred Hutch Cancer Center / HHMI
These slides at https://slides.com/jbloom/sars2dms
Most viral vaccines induce neutralizing antibodies to the viral entry protein
All viruses have one or more entry proteins that bind receptor and then fuse with the cell membrane:
- SARS-CoV-2 spike
- influenza hemagglutinin
- HIV envelope protein
- Lassa virus glycoprotein
- Nipah virus G and F proteins
- RSV G and F proteins
Mutations to viral entry proteins affect antigenicity and transmissibility
For SARS-CoV-2 spike, we know following molecular phenotypes are important:
- Cell entry: if spike cannot mediate cell entry, virus will not be fit
- ACE2 binding: if spike does not bind ACE2 strongly enough, virus will not be fit
- Antibody escape: if spike is resistant to antibodies, virus will be more fit
Viruses constantly acquiring mutations that potentially affect these phenotypes
How can we rapidly and safely measure how mutations affect these phenotypes?
- General: can work for many viral entry proteins
- Comprehensive: measure mutations throughout spike, not just RBD
- High-throughput: can be applied new variants and antibodies
- Safe: we want to characterize mutations with making novel pathogenic viruses
- Applicable directly to sera, to capture heterogeneity due to imprinting
Lentiviral pseudotyping
- Many viruses have entry proteins amenable to lentiviral pseudotyping.
- However, traditional pseudotyping does not create genotype-phenotype link.
Two-step method to create genotype-phenotype linked spike-pseudotypes
Two-step method to create genotype-phenotype linked spike-pseudotypes
Sequencing measures relative amounts, so include neutralization standard
Example: RBD antibody LY-CoV1404
Validates very well
Example: S2 antibody CC67.105
days before present
fraction of USA sequences
Estimates of clade growth from multinomial logistic regression
Experimentally measured spike phenotypes correlate with SARS-CoV-2 clade growth
OLS regression combining spike phenotypes predicts clade growth quite well
We can measure how mutations affect key phenotypes that actually shape SARS-CoV-2 evolution
What could we hope to do next?
Develop a sustainable approach to keep generating these phenotypic data as the virus and population immunity evolve.
Share the data so they can be easily visualized and used by other scientists and variant trackers.
Partner with groups developing models to leverage these data for more sophisticated predictions and countermeasure development.
Overall, the last decade has seen tremendous advances in viral surveillance. What we need now is advances in interpreting the results of this surveillance.
Bloom lab
Bernadeta Dadonaite
Kate Crawford
Caelan Radford
University of Washington
David Veesler
Karolinska Institute
Ben Murrell
Penn
Raiees Andrabi
Scripps
Dennis Burton
Thanks
