Subproteomic analysis of metal‐interacting proteins in human B cells
Why this work is in the frame
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Bibliographic record
Abstract
Metal-protein interactions are vitally important in all living organisms. Metalloproteins, including structural proteins and metabolic enzymes, participate in energy transfer and redox reactions or act as metallochaperones in metal trafficking. Among metal-associated diseases, T cell mediated allergy to nickel (Ni) represents the most common form of human contact hypersensitivity. With the aim to elucidate disease-underlying mechanisms such as Ni-specific T cell activation, we initiated a proteomic approach to identify Ni-interacting proteins in human B cells. As antigen presenting cells, B cells are capable of presenting MHC-associated Ni-epitopes to T cells, a prerequisite for hapten-specific T cell activation. Using metal-affinity enrichment, 2-DE and MS, 22 Ni-interacting proteins were identified. In addition to known Ni-binding molecules such as tubulin, actin or cullin-2, we unexpectedly discovered that at least nine of these 22 proteins belong to stress-inducible heat shock proteins or chaperonins. Enrichment was particularly effective for the hetero-oligomeric TRiC/CCT complex, which is involved in MHC class I processing. Blue Native/SDS electrophoresis analysis revealed that Ni-NTA-beads specifically retained the complete protein machinery, including the associated chaperonin substrate tubulin. The apparent Ni-affinity of heat shock proteins suggests a new function of these molecules in human Ni allergy, by linking innate and adaptive immune responses.
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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 | 0.000 | 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) | 0.000 | 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 it