Using deep mutational scanning to identify possible next steps in SARS-CoV-2 antigenic evolution

 

Jesse Bloom

These slides: https://slides.com/jbloom/escape-calc

Data shown here from:

Allie Greaney, Tyler Starr, Jesse Bloom (Fred Hutch)

Sunney Xie, Richard Cao, Fanchong Jian, et al (Peking University)

Background: deep mutational scanning antibody-escape calculator

Deep mutational scanning maps how all mutations to SARS-CoV-2 receptor-binding domain (RBD) affect 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

For an interactive version of this escape map, see:

https://jbloomlab.github.io/SARS-CoV-2-RBD_MAP_LY-CoV555/

Escape map from one antibody (LY-CoV555, ie bamlanivimab). Peaks indicate sites where mutations escape binding.

484

452

490

Infection / vaccination elicit polyclonal antibodies 

How do mutations affect polyclonal antibodies? First, consider an equal mix of three monoclonal antibodies.

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

Antibody-escape calculator extends this principle to deep mutational scanning data for ~1,500 different human antibodies

Escape calculator is described in Greaney et al (2022), and is available at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/

36 antibodies mapped by Tyler Starr & Allie Greaney in Bloom lab, from early SARS-CoV-2 strains

Antibody-escape calculator extends this principle to deep mutational scanning data for ~1,500 different human antibodies

Escape calculator is described in Greaney et al (2022), and is available at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/

36 antibodies mapped by Tyler Starr & Allie Greaney in Bloom lab, from early SARS-CoV-2 strains

1,522 (!) antibodies mapped by Sunney Xie, Richard Cao, Fanchong Jian, et al at Peking University. From early strains, BA.1, & patients with prior SARS-CoV-1 infection. See here.

What does escape calculator using these data tell us about evolution that has already happened?

Antibodies elicited by early SARS-CoV-2 that neutralize Wuhan-Hu-1 heavily focus on sites like 484, 417, 446

417

446

484

417

446

484

490 not mutated, but antibodies that bind there are escaped by mutation at 484 which is in same epitope.

Note Omicron has additional escape not modeled here due to mutations that put RBD more in down conformation and cause N343 glycan displacement: Cao et al (2022), Gobeil et al (2022), and explanation here.

Omicron BA.1 is mutated at many of these sites, which is why it is neutralized substantially less well by current vaccines

Omicron BA.2 has some different RBD mutations than BA.1, but similar overall escape from antibodies from early SARS-CoV-2

Note Omicron has additional escape not modeled here due to mutations that put RBD more in down conformation and cause N343 glycan displacement: Cao et al (2022), Gobeil et al (2022), and explanation here.

Can identify mutations that mediate further escape. In Dec 2021 we predicted 486 as likely site of future evolution--in April 2022, mutation F486V was identified in Omicron BA.4 and BA.5.

486 is largest site of escape for antibodies not already escaped by mutations in BA.2

What are likely next steps in antigenic evolution of SARS-CoV-2?

Sites of escape from antibodies elicited by early (pre-Omicron) infection/vaccination that still neutralize Omicron BA.2

346

356

444-446

452

450

462

468

486

499

mutated in BA.4/BA.5 or BA.2.12.1

Sites of escape are somewhat different for antibodies from people who had an Omicron BA.1 breakthrough infection 

346-348

444-446

452

486

468

mutated in BA.4/BA.5 or BA.2.12.1

356

490

The differences in antibody-escape mutations between people who have / have-not had BA.1 breakthrough infections is consistent with prior studies on other viruses showing that serum antibodies from people with different exposure histories have different viral escape mutations.

Averaging across early SARS-CoV-2 & BA.1 breakthrough exposures, sites of escape in BA.2. Watch these sites!

346-348

444-446

452

486

468

mutated in BA.4/BA.5 or BA.2.12.1

356

Explore yourself with online escape calculator: select antibodies by eliciting virus or strains they neutralize, click sites to mutate

https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/