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One of the features of our approach is its ability to distinguish between antibodies targeting overlapping epitopes in a substantially different ways: There is a significant difference in the correlation coefficients for antibodies targeting a similar epitope versus the correlation coefficients for antibodies targeting different epitopes on the same site of vulnerability. Similarly, there is a significant difference for similar epitopes versus different sites of vulnerability; however, there is no significant difference for different epitopes on the same site of vulnerability versus different sites of vulnerability (fig. S1).
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To resolve the discrepancy between epitope mapping and neutralization-based predictions, we determined the cocrystal structure of VRC06 in complex with the gp120 core and compared it with the structure of the VRC01-like antibody VRC03: The antibody variable-domain root mean square deviation upon alignment of the respective VRC06- and VRC03-bound gp120 cores was 1.45 Å, confirming the similarity in the modes of gp120 recognition by these two antibodies (Fig. 2B and table S3). Although VRC03 and VRC06 exhibit extraordinary similarity in their mode of recognition of gp120 when compared with VRC01, unlike VRC01, antibodies VRC03 and VRC06 contain a long insertion in the heavy-chain framework 3 region that falls in the vicinity of the gp120 bridging sheet. In the crystallized complexes of these antibodies and monomeric gp120 core (which lacks the full V1/V2 region), the insertions do not make substantial contact with gp120. On the functional trimer spike, however, these insertions likely make additional contacts with the antigen, extending the antibody epitopes as compared with VRC01. The result is that VRC03 and VRC06 cluster in the periphery of the VRC01 cluster.
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The division into monoclonal antibody clusters was based on the clustering results from the larger 34-strain panel (Fig. 2A), whereas serum delineation was performed on an available 21-strain panel (because of serum volume constraints, we used a 21-strain subset of the main panel). Although antibody clustering is sensitive to the size of the viral panel (appendix S1), predictions with smaller panels (such as the 21-strain panel used in the serum analysis) could nonetheless be sufficient (fig. S3); delineation of component-antibody specificities for the CAP256 sera was based on a smaller 13-strain panel (41).
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A signal for PGT128-like antibodies in donor 45 was also observed. However, only part of the neutralization activity of the donor 45 serum could be attributed to VRC01-like antibodies (fig. S11), which indicated that other antibody specificities may also exist in that serum. It is thus not surprising to observe other neutralization signals in the predictions.
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For example, standard serum mapping for glycan-V3 antibodies uses N332 mutants and, thus, may not be as sensitive for some antibodies in the PGT128-like group that are more affected by glycan-301 (table S4).
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The neutralization-based delineation showed relatively strong signals (>0.2) for 2G12- or b12-like antibodies with many of the sera, and potential VRC01-, PG9-, PGT128-, and 10E8-like specificities were predicted for specific subsets of the sera. In the case of 2G12-like activity, many serum samples were also found to be positive by experimental mapping assays, which indicated that this epitope might be a more frequent target compared with other major epitopes, although not necessarily by antibodies having the specific domain-exchanged nature of 2G12 (Fig. 3D). A clear threshold for the presence or absence of a particular specificity in a given serum was not apparent: A level of 0.35 positively identified 10E8-like antibodies in donor N152, but sporadic signals of up to ∼0.3 were observed in longitudinal samples (Fig. 3B).
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