Jesse Bloom PRO
Scientist studying evolution of proteins and viruses.
An antibody escape calculator for the SARS-CoV-2 receptor binding domain (RBD)
Jesse Bloom
Fred Hutch Cancer Center / HHMI
These slides at https://slides.com/jbloom/sars2-rbd-escape-calc
Human CoV spikes evolve to escape neutralizing antibodies
Human sera from 1985-1990 neutralizes contemporaneous CoV-229E spikes quite well, but as virus evolves into the "future", neutralization is eroded. There is substantial heterogeneity in the rate of erosion across sera from different human individuals.
Antibody selection concentrated in RBD
Sites of evolutionary change in spike of CoV-229E over last four decades
Sites of mutations in SARS-CoV-2 Omicron BQ.1.1 spike relative to Wuhan-Hu-1
Deep mutational scanning to map RBD mutations that escape antibody binding
RBD
fluorescently labeled antibody
yeast
fluorescent tag on RBD
Experiments combine flow cytometry and deep sequencing of a library of yeast expressing all RBD mutants
These measurements can be made on ~10,000 to ~100,000 mutants all at once
Escape map from one antibody (LY-CoV555, ie bamlanivimab)
484
452
490
This turned out be an unfortunate choice of an antibody for Eli Lilly to develop as drug, as mutations at sites 484 and 452 were prevalent by early to mid 2021
Infection / vaccination elicit polyclonal antibodies
How do mutations affect polyclonal antibodies? First, consider an equal mix of three monoclonal antibodies.
Interactive version of this mini example is at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/mini-example-escape-calc/
LY-CoV555 is escaped at both sites 484 and 490, so mutating either site has same overall effect
Average escape across all antibodies
Mutating site 484 or 490 eliminates neutralization by antibody LY-CoV555, as reflected in thick black line showing average
Interactive version of this mini example is at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/mini-example-escape-calc/
From Yunlong Cao, we have deep mutational scanning data on ~1000s antibodies that neutralize XBB
See here for summary of how successful escape calculator has been so far in pinpointing sites of evolution.
Sites of escape in XBB
Interactive escape calculator: https://jbloomlab.github.io/SARS2-RBD-escape-calc/
ACE2 affinity from: https://jbloomlab.github.io/SARS-CoV-2-RBD_DMS_Omicron/RBD-heatmaps/
Fitness effects from: https://jbloomlab.github.io/SARS2-mut-fitness/S.html
Interactive escape calculator: https://jbloomlab.github.io/SARS2-RBD-escape-calc/
Clear differences between one and two Omicron infections: eg, site 498 only major site of escape after two Omicron infections
We will probably see viral evolution at many of these sites of escape
See here for summary of how deep mutational scanning has predicted many of sites of antigenic evolution in the SARS-CoV-2 RBD over last few years
Escape calculator has been used 120,000 times by 18,000 users
Bloom lab
Tyler Starr (now at University of Utah)
Allie Greaney
Bernadeta Dadonaite
Peking University
Yunlong Cao
Fanchong Jian
These slides: https://slides.com/jbloom/sars2-rbd-escape-calc
Thanks
Use the escape calculator at https://jbloomlab.github.io/SARS2-RBD-escape-calc/
SARS2-RBD-escape-calc
By Jesse Bloom
SARS2-RBD-escape-calc
An antibody escape calculator for the SARS-CoV-2 receptor binding domain
