Molecular fate-mapping of serum antibodies reveals the effects of antigenic imprinting on repeated immunization
Bibliographic record
Abstract
The ability of serum antibody to protect against pathogens arises from the interplay of antigen-specific B cell clones of different affinities and fine specificities. These cellular dynamics are ultimately responsible for serum-level phenomena such as antibody imprinting or "Original Antigenic Sin" (OAS), a proposed propensity of the immune system to rely repeatedly on the first cohort of B cells that responded to a stimulus upon exposure to related antigens. Imprinting/OAS is thought to pose a barrier to vaccination against rapidly evolving viruses such as influenza and SARS-CoV-2. Precise measurement of the extent to which imprinting/OAS inhibits the recruitment of new B cell clones by boosting is challenging because cellular and temporal origins cannot readily be assigned to antibodies in circulation. Thus, the extent to which imprinting/OAS impacts the induction of new responses in various settings remains unclear. To address this, we developed a "molecular fate-mapping" approach in which serum antibodies derived from specific cohorts of B cells can be differentially detected. We show that, upon sequential homologous boosting, the serum antibody response strongly favors reuse of the first cohort of B cell clones over the recruitment of new, naÏve-derived B cells. This "primary addiction" decreases as a function of antigenic distance, allowing secondary immunization with divergent influenza virus or SARS-CoV-2 glycoproteins to overcome imprinting/OAS by targeting novel epitopes absent from the priming variant. Our findings have implications for the understanding of imprinting/OAS, and for the design and testing of vaccines aimed at eliciting antibodies to evolving antigens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".