Immune Tolerance Negatively Regulates B Cells in Knock-In Mice Expressing Broadly Neutralizing HIV Antibody 4E10
Bibliographic record
Abstract
A major goal of HIV research is to develop vaccines reproducibly eliciting broadly neutralizing Abs (bNAbs); however, this has proved to be challenging. One suggested explanation for this difficulty is that epitopes seen by bNAbs mimic self, leading to immune tolerance. We generated knock-in mice expressing bNAb 4E10, which recognizes the membrane proximal external region of gp41. Unlike b12 knock-in mice, described in the companion article (Ota et al. 2013. J. Immunol. 191: 3179-3185), 4E10HL mice were found to undergo profound negative selection of B cells, indicating that 4E10 is, to a physiologically significant extent, autoreactive. Negative selection occurred by various mechanisms, including receptor editing, clonal deletion, and receptor downregulation. Despite significant deletion, small amounts of IgM and IgG anti-gp41 were found in the sera of 4E10HL mice. On a Rag1⁻/⁻ background, 4E10HL mice had virtually no serum Ig of any kind. These results are consistent with a model in which B cells with 4E10 specificity are counterselected, raising the question of how 4E10 was generated in the patient from whom it was isolated. This represents the second example of a membrane proximal external region-directed bNAb that is apparently autoreactive in a physiological setting. The relative conservation in HIV of the 4E10 epitope might reflect the fact that it is under less intense immunological selection as a result of B cell self-tolerance. The safety and desirability of targeting this epitope by a vaccine is discussed in light of the newly described bNAb 10E8.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".