The shifting evolutionary landscape of SARS-CoV-2's receptor binding domain

 

Jesse Bloom

Fred Hutch Cancer Research Center / HHMI

 

Slides at https://slides.com/jbloom/shifting-rbd-landscape-niaid-save

 

@jbloom_lab

Tyler Starr

Allie Greaney

Disclosures

  • I am on the scientific advisory boards of Flagship Labs 77 and Oncorus
  • I consult for Moderna
  • I am an inventor on Fred Hutch licensed patents related to deep mutational scanning of viral proteins
  • My lab has unfunded research collaborations with Vir Biotechnology

Omicron has many mutations in its receptor binding domain (RBD)

Spheres show the 15 mutations in Omicron BA.1.

 

Epitopes are colored as class 1, class 2, class 3, or class 4.

How was Omicron RBD capable of tolerating so many mutations?

Very reasonable question, since Omicron RBD has many mutations in binding interface...

Most mutations in Omicron's RBD individually decrease ACE2 affinity

If mutations in Omicron's RBD acted together like they do individually, Omicron would have >100-fold reduction in ACE2 affinity.

log10 change dissociation (Kd) constant for individual mutations

Effects of mutations on binding to monomeric human ACE2 as measured in Starr et al (2022): interactive data here

log10 change dissociation (Kd) constant for individual mutations

But net effect of mutations ~0 in background of N501Y

Effects of mutations on binding to monomeric human ACE2 as measured in Starr et al (2022): interactive data here

Measurements in Wuhan-Hu-1

Measurements in a N501Y background

log10 change dissociation (Kd) constant for individual mutations

N501Y shifts effects of other mutations:

Q498R goes from 2-fold decrease to 40-fold increase in ACE2 affinity

G496S goes from 8-fold decrease to <2-fold effect on ACE2 affinity

Effects of mutations on binding to monomeric human ACE2 as measured in Starr et al (2022): interactive data here

Measurements in Wuhan-Hu-1

Measurements in a N501Y background

N501Y (but not K417N or E484K) shift the evolutionary space available to the RBD

Shifts in mutational effects on ACE2 binding as measured in Starr et al (2022): go here to explore interactively

Alpha and Beta (which both have N501Y) but not Delta or Eta have major shifts in mutational effects relative to Wuhan-Hu-1.

How: N501Y interacts with other mutations (eg, Q498R) to increase ACE2 affinity and buffer the cost of remaining mutations

Why was Omicron selected to have so many RBD mutations?

RBD is region under strongest selection in human CoV

Sites of evolutionary change in the spike of CoV-229E over the last four decades

Sites of evolutionary change in the spike of CoV-229E over the last four decades

Sites of mutations in SARS-CoV-2 Omicron (BA.1) spike relative to Wuhan-Hu-1

Most mutations in RBD for both SARS-CoV-2 and CoV-229E. Main difference is SARS-CoV-2 also fixing transmissibility-enhancing spike mutations that affect proteolytic processing and stabilize defects cause by furin-cleavage site

RBD is region under strongest selection in human CoV

RBD is under strong selection because it's what most neutralizing antibodies target

Effect depends to some extent on ACE2 expression in target cells.

We know which mutations escape antibodies from current vaccines

Plot from escape calculator described in Greaney et al (2021)

Delta only has modest mutations at antigenically important RBD sites

Plot from escape calculator described in Greaney et al (2021)

Omicron (BA.1) is extensively mutated at important RBD antigenic sites

Plot from escape calculator described in Greaney et al (2021)

Omicron (BA.2) shares most but not all key RBD antigenic mutations with BA.1

Plot from escape calculator described in Greaney et al (2021)

Why: Omicron was selected to have many RBD mutations to escape neutralizing antibodies

How & why combine: affinity-enhancing mutations buffer antibody escape

Mutations that enhance affinity without much antibody escape

Mutations that decrease affinity but strongly escape antibodies

What does all this mean for future antigenic evolution?

Plot from escape calculator described in Greaney et al (2021)

Omicron has already mutated many key RBD sites targeted by antibodies from current vaccines and early infections

Plot from escape calculator described in Greaney et al (2021)

Sites targeted by antibodies that still neutralize Omicron: candidates for future antigenic evolution

But increasingly, different people will have different antibodies due to having been exposed to different variants

Situation may become more like influenza where antigenic impact of new variants depends on a person's exposure history

Collaborators

Crowe lab (Vanderbilt)

Chu lab (Univ Wash)

Veesler lab (Univ Wash)

Matreyek lab (Case Western)

Gyorgy Snell, Davide Corti (Vir Biotechnology)

Tyler Starr

Allie Greaney

  • Rachel Eguia
  • Andrea Loes
  • Kate Crawford
  • Will Hannon
  • Bernadeta Dadonaite
  • Ariana Ghez-Farrell

Bloom lab (Fred Hutch)

Thanks

shifting-rbd-landscape-niaid-save

By Jesse Bloom

shifting-rbd-landscape-niaid-save

The shifting evolutionary landscape of the SARS-CoV-2 receptor-binding domain (for March-11-2022 NIAID SAVE retreat)

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