Comparison of Antibody Repertoires Produced by HIV-1 Infection, Other Chronic and Acute Infections, and Systemic Autoimmune Disease
Bibliographic record
Abstract
BACKGROUND: Antibodies (Abs) produced during HIV-1 infection rarely neutralize a broad range of viral isolates; only eight broadly-neutralizing (bNt) monoclonal (M)Abs have been isolated. Yet, to be effective, an HIV-1 vaccine may have to elicit the essential features of these MAbs. The V genes of all of these bNt MAbs are highly somatically mutated, and the V(H) genes of five of them encode a long (≥ 20 aa) third complementarity-determining region (CDR-H3). This led us to question whether long CDR-H3s and high levels of somatic mutation (SM) are a preferred feature of anti-HIV bNt MAbs, or if other adaptive immune responses elicit them in general. METHODOLOGY AND PRINCIPAL FINDINGS: We assembled a V(H)-gene sequence database from over 700 human MAbs of known antigen specificity isolated from chronic (viral) infections (ChI), acute (bacterial and viral) infections (AcI), and systemic autoimmune diseases (SAD), and compared their CDR-H3 length, number of SMs and germline V(H)-gene usage. We found that anti-HIV Abs, regardless of their neutralization breadth, tended to have long CDR-H3s and high numbers of SMs. However, these features were also common among Abs associated with other chronic viral infections. In contrast, Abs from acute viral infections (but not bacterial infections) tended to have relatively short CDR-H3s and a low number of SMs, whereas SAD Abs were generally intermediate in CDR-H3 length and number of SMs. Analysis of V(H) gene usage showed that ChI Abs also tended to favor distal germline V(H)-genes (particularly V(H)1-69), especially in Abs bearing long CDR-H3s. CONCLUSIONS AND SIGNIFICANCE: The striking difference between the Abs produced during chronic vs. acute viral infection suggests that Abs bearing long CDR-H3s, high levels of SM and V(H)1-69 gene usage may be preferentially selected during persistent infection.
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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 | 0.001 | 0.001 |
| 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".