Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding

Abstract

The receptor binding domain (RBD) of the SARS-CoV-2 spike glycoprotein mediates viral attachment to ACE2 receptor, and is a major determinant of host range and a dominant target of neutralizing antibodies. Here we experimentally measure how all amino-acid mutations to the RBD affect expression of folded protein and its affinity for ACE2. Most mutations are deleterious for RBD expression and ACE2 binding, and we identify constrained regions on the RBD's surface that may be desirable targets for vaccines and antibody-based therapeutics. But a substantial number of mutations are well tolerated or even enhance ACE2 binding, including at ACE2 interface residues that vary across SARS-related coronaviruses. However, we find no evidence that these ACE2-affinity enhancing mutations have been selected in current SARS-CoV-2 pandemic isolates. We present an interactive visualization and open analysis pipeline to facilitate use of our dataset for vaccine design and functional annotation of mutations observed during viral surveillance.

Figure 1.. Yeast display of RBDs from SARS-CoV-2 and related sarbecoviruses.

(A) Maximum likelihood phylogenetic tree of sarbecovirus RBDs. RBDs included in the present study are in bold text colored by RBD clade. Node labels indicate bootstrap support. (B) RBD yeast surface display enables fluorescent detection of RBD surface expression and ACE2 binding. (C) Yeast displaying the indicated RBD were incubated with varying concentrations of human ACE2, and binding was measured via flow cytometry. Binding constants are reported as K_D,app from the illustrated titration curve fits. (D) Comparison of yeast display binding with previous measurements of the capacity of viral particles to enter ACE2-expressing cells. Relative binding is Δlog10(K_D,app) measured in the current study; relative cellular entry is infection of ACE2-expressing cells by VSV pseudotyped with spike containing the indicated RBD, reported by Letko et al. (Letko et al., 2020) in arbitrary luciferase units relative to SARS-CoV-1 RBD; n.d. indicates not determined by Letko et al.

Figure 2.. Deep mutational scanning of the SARS-CoV-2 RBD.

(A, B) FACS approach for deep mutational scans for expression (A) and binding (B). Cells were sorted into four bins from low to high expression or binding signal, with separate sorts for each ACE2 concentration. The frequency of each library variant in each bin was determined by Illumina sequencing of the barcodes of cells collected in that bin, enabling reconstruction of per-variant expression and binding phenotypes. Bin boundaries were drawn based on distributions of expression or binding for unmutated SARS-CoV-2 controls (blue), and gray shows the distribution of library variants for library replicate 1 in these bins. See also Figure S2. (C, D) Distribution of library variant phenotypes for expression (C) and binding (D), with variants classified by the types of mutations they contain. Internal control RBD homologs are indicated with vertical lines giving the measured expression or binding phenotype, colored by clade as in Figure 1A. Stop-codon-containing variants were purged by an RBD+ pre-sort prior to ACE2 binding deep mutational scanning measurements, and so are not sampled in (D). (E, F) Correlation in single-mutant effects on expression (E) and binding (F), as determined from independent mutant library replicates. See also Figure S3.

Figure 3.. Sequence-to-phenotype maps of the SARS-CoV-2 RBD.

(A, B) Heatmaps illustrating how all single mutations affect RBD expression (A) and ACE2 binding affinity (B). Interactive versions of these heatmaps are at https://jbloomlab.github.io/SARS-CoV-2-RBD_DMS and in Supplemental File 2. Squares are colored by mutational effect according to scale bars on the left, with red indicating deleterious mutations. The SARS-CoV-2 amino acid is indicated with an ‘x’, and when the SARS-CoV-1 amino acid is different it is indicated with an ‘o’. The top overlay uses black boxes to indicate residues that contact ACE2 in the SARS-CoV-2 (PDB 6M0J) or SARS-CoV-1 (PDB 2AJF) crystal structures. The purple overlay represents the relative solvent accessibility (RSA) of a residue in the ACE2-bound SARS-CoV-2 crystal structure. See also Figure S4.

Figure 4.. Validation of mutation effects measured in deep mutational scanning.

(A) Titration curves for select mutations that were re-cloned and validated in isogenic cultures. (B, C) Correlation in binding (B) and expression (C) effects of mutations between deep mutational scanning and isogenic validation experiments, including mutants shown in (A) and Figure 8C. (D) Comparisons of dissociation constants measured for mammalian-expressed purified RBD binding to monomeric human ACE2 (see Figure S5) and yeast displayed RBD binding to natively dimeric ACE2 from our deep mutational scan. (E) Effects of mutations on transduction of ACE2-expressing cells by lentiviral particles pseudotyped with SARS-CoV-2 spike carrying the indicated mutation. Mutants are colored by their effects on ACE2 binding as measured in the deep mutational scanning using the same color scale as in Figure 3B (increased affinity in blue, reduced affinity in red). Titers that fell below the limit of detection (dashed horizontal line) are plotted on the x-axis.

Figure 5.. Mutation effects in the context of the RBD structure.

(A, B) Mutational constraint mapped to the SARS-CoV-2 RBD structure. A sphere at each site’s Cɑ is colored according to the mean effect of amino-acid mutations at the site with respect to expression (A) or binding (B), with red indicating more constraint. RBD structural features and the ACE2 K31 and K353 interaction hotspot residues are labeled. Yellow sticks indicate disulfide bridges. Interactive structure-based visualizations of these data are at https://jbloomlab.github.io/SARSCoV-2-RBD_DMS/structures/ (C) Relationship between mutational constraint on binding and expression. The structural view shows in cyan the sites that are under strong mutational constraint with respect to ACE2 binding but are tolerant of mutations with respect to expression. (D) Relationship between mutational constraint on binding and residue solvent accessibility (RSA). Black dots indicate RSA in the full ACE2-bound RBD structure, and when sites have large changes in RSA in the unbound structure, then their RSA in that structure is also shown in orange. (E) Mutation effects on binding at disulfide cysteine residues. Heatmaps as in Figure 3B. RBD sites are grouped by disulfide pair, and labeled according to location in the core-RBD or RBM sub-domains. (F) Mutation effects on expression at N-linked glycosylation sites (NLGS). RBD sites are grouped by NLGS motif (NxS/T, where x is any amino acid except proline). Boxed amino acids indicate those that encode a NLGS motif. NLGS motifs are labeled according to whether they are present in both the SARS-CoV-2 and SARS-CoV-1 RBD (N331 and N343 glycans), or in SARS-CoV-1 only (N370 glycan). See also Figure S6.

Figure 6.. Mutation effects at ACE2 contact sites and implications for sarbecovirus evolution.

(A) Heatmap as in Figure 3B, subsetted on sites that directly contact ACE2 in the SARS-CoV-2 or SARS-CoV-1 RBD structures, plus interface site 494 which is discussed as a key site of adaptation in the SARS-CoV-1 literature. (B) RBD sites Q493, Q498, and N501, which have many affinity-enhancing mutations, participate in polar contact networks involving the ACE2 interaction hotspot residues K31 and K353. (C) Variation at ACE2 contact sites in other sarbecovirus RBDs. The circles show the effects of the individual mutations that differentiate that virus’s ACE2 interface from SARS-CoV-2, while the x shows the mean effect of all mutations at that site. The sum of individual mutation effects at interface residues is shown, compared to the actual RBD binding relative to unmutated SARS-CoV-2.

Figure 7.. Mutational constraint of antibody epitopes.

(A) Mutational constraint on surface residues comprising antibody epitopes. For each of 8 RBD-directed antibodies, black outlines indicate the epitope structural footprint, with surfaces colored by mutational constraint (red indicates more constrained). The direct ACE2 interface is shown in the upper-left, for reference. Names of antibodies capable of neutralizing SARS-CoV-2 are boxed. (Others neutralize SARS-CoV-1 but have not been demonstrated to neutralize SARS-CoV-2.) Constraint is illustrated as mutational effects on binding for RBM-directed antibodies (blue, top), and expression for core-RBD-directed antibodies (orange, bottom). The N343 glycan, which is present in the S309 epitope and is constrained with respect to expression, is shown only on this surface for clarity. (B) Average mutational constraint for binding and expression within each epitope. Points are colored according to the RBM versus core-RBD designation in (A). (C) Identification of a patch of mutational constraint surrounding RBD residue E465 which has not yet been targeted by any described antibodies. Surface is colored according to mutational effects on expression, as in (A, bottom). Residues in this constrained E465 patch are listed.

Figure 8.. Phenotypic impacts of current genetic variation in the SARS-CoV-2 RBD.

(A) Distribution of effects on ACE2 binding of mutations observed among circulating SARS-CoV-2 isolates. The distribution of mutation effects is shown for all amino-acid mutations accessible via single-nucleotide mutation from the SARS-CoV-2 Wuhan-Hu-1 gene sequence, compared to the distributions for subsets of mutations that are observed in sequenced SARS-CoV-2 isolates deposited in GISAID at increasing observation count thresholds. n, number of mutations in each subset. (B) Summary of most frequent mutations among GISAID sequences, reporting our deep mutational scanning measured effect on binding and expression, the number of GISAID sequences containing the mutation, and the number of geographic regions from which a mutation has been reported. (C, D) Validation of the mutational effects on binding (C) and expression (D) for 4 of the 5 most frequent circulating RBD variants. S477N rose to high frequency after we began our validation experiments, and so was not included. Error bars in (D) are standard error from 11 samples.