Re-infection with SARS-CoV-2 is associated with increased antibody breadth and potency against diverse sarbecovirus strains
Bibliographic record
Abstract
ABSTRACT The ease with which emerging SARS-CoV-2 variants escape neutralizing antibodies limits protection afforded by a prior exposure, be it infection or vaccination. While rare, broadly neutralizing antibodies with activity towards diverse sarbecoviruses have been detected in convalescent serum. Motivated by findings that plasma responses show increased neutralization breadth and potency with continued antigen exposure, we isolated monoclonal antibodies (mAbs) after a SARS-CoV-2 re-infection and compared them to those isolated one year prior, after the first breakthrough infection. Among clonal lineage members identified at both time points, mAbs from the later time point showed improved neutralization potency and breadth. One mAb isolated after re-infection, C68.490, targets a conserved region in the receptor binding domain core and shows remarkable activity not only against SARS-CoV-2 variants, but also diverse sarbecoviruses from more distant clades present in animal reservoirs. These findings suggest that a focus on individuals with diverse and repeated antigen exposure could lead to identification of antibodies with therapeutic utility not just towards current and future SARS-CoV-2 variants, but also distant sarbecoviruses in the event of a future spillover.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".