Structural insights into broadly neutralizing antibodies elicited by hybrid immunity against SARS-CoV-2
Bibliographic record
Abstract
Increasing spread by SARS-CoV-2 Omicron variants challenges existing vaccines and broadly reactive neutralizing antibodies (bNAbs) against COVID-19. Here we determine the diversity, potency, breadth and structural insights of bNAbs derived from memory B cells of BNT162b2-vaccinee after homogeneous Omicron BA.1 breakthrough infection. The infection activates diverse memory B cell clonotypes for generating potent class I/II and III bNAbs with new epitopes mapped to the receptor-binding domain (RBD). The top eight bNAbs neutralize wildtype and BA.1 potently but display divergent IgH/IgL sequences and neuralization profiles against other variants of concern (VOCs). Two of them (P2D9 and P3E6) belonging to class III NAbs display comparable potency against BA.4/BA.5, although structural analysis reveals distinct modes of action. P3E6 neutralizes all variants tested through a unique bivalent interaction with two RBDs. Our findings provide new insights into hybrid immunity on BNT162b2-induced diverse memory B cells in response to Omicron breakthrough infection for generating diverse bNAbs with distinct structural basis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".