Structural basis for autoantibody recognition of phosphatidylserine-[beta]2-glycoprotein I and apoptotic cells
Bibliographic record
Abstract
The work described in this dissertation was undertaken to explore the nature of the autoantibody response in two antibody-mediated autoimmune diseases, systemic lupus erythematosus (SLE) and the antiphospholipid syndrome (APS). Mutant versions of a murine anti-DNA and anti-phospholipid autoantibody, 3H9, were constructed and expressed as recombinant single chain Fv (scFv) in Escherichia coli. Purified scFv were tested for binding to phosphatidylserine and to phosphatidylserine as a complex with [beta]2-glycoprotein I ([beta]2GPI) in ELISA, revealing that the 3H9 heavy (H) chain V gene encodes specificity for these antigens. Moreover, it was determined that higher affinity for phosphatidylserine-[beta]2GPI could be achieved by the introduction of arginine residues into the CDR1, CDR2, and FWR3 of the 3H9 H chain at positions previously shown to be important for DNA binding. Flow cytometric analysis of structurally diverse variants of 3H9 established that the autoantibodies preferentially recognize Jurkat cells in advancing stages of apoptosis as defined by positive binding of annexin V and staining with propidium idodide. Confocal fluorescence microscopy revealed that the scFv initially bind to the cell surface at positions that overlap with the binding of annexin V and that the binding of the scFv and annexin V begin to segregate as the cell undergoes blebbing. The segregation of binding was found to culminate in the exclusive localization of the scFv to surface blebs on the apoptotic cells, with annexin V bound to regions between adjacent blebs. The results of these experiments suggest that, in SLE, B cells that express Ig receptors reactive against phosphatidylserine bind to apoptotic blebs and may have implications for the processing of nuclear antigens and the regulation of immune tolerance to self.
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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 | 0.000 |
| 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".