Isolation of monoclonal antibodies from anti-synthetase syndrome patients and affinity maturation by recombination of independent somatic variants
Bibliographic record
Abstract
The autoimmune disease known as Jo-1 positive anti-synthetase syndrome (ASS) is characterized by circulating antibody titers to histidyl-tRNA synthetase (HARS), which may play a role in modulating the non-canonical functions of HARS. Monoclonal antibodies to HARS were isolated by single-cell screening and sequencing from three Jo-1 positive ASS patients and shown to be of high affinity, covering diverse epitope space. The immune response was further characterized by repertoire sequencing from the most productive of the donor samples. In line with previous studies of autoimmune repertoires, these antibodies tended to have long complementarity-determining region H3 sequences with more positive-charged residues than average. Clones of interest were clustered into groups with related sequences, allowing us to observe different somatic mutations in related clones. We postulated that these had found alternate structural solutions for high affinity binding, but that mutations might be transferable between clones to further enhance binding affinity. Transfer of somatic mutations between antibodies within the same clonal group was able to enhance binding affinity in a number of cases, including beneficial transfer of a mutation from a lower affinity clone into one of higher affinity. Affinity enhancement was seen with mutation transfer both between related single-cell clones, and directly from related repertoire sequences. To our knowledge, this is the first demonstration of somatic hypermutation transfer from repertoire sequences to further mature in vivo derived antibodies, and represents an additional tool to aid in affinity maturation for the development of antibodies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".