Picomolar zinc binding modulates formation of Bcl10-nucleating assemblies of the caspase recruitment domain (CARD) of CARD9
Bibliographic record
Abstract
The caspase recruitment domain–containing protein 9 (CARD9)–B-cell lymphoma/leukemia 10 (Bcl10) signaling axis is activated in myeloid cells during the innate immune response to a variety of diverse pathogens. This signaling pathway requires a critical caspase recruitment domain (CARD)–CARD interaction between CARD9 and Bcl10 that promotes downstream activation of factors, including NF-κB and the mitogen-activated protein kinase (MAPK) p38. Despite these insights, CARD9 remains structurally uncharacterized, and little mechanistic understanding of its regulation exists. We unexpectedly found here that the CARD in CARD9 binds to Zn 2+ with picomolar affinity—a concentration comparable with the levels of readily accessible Zn 2+ in the cytosol. NMR solution structures of the CARD9–CARD in the apo and Zn 2+ -bound states revealed that Zn 2+ has little effect on the ground-state structure of the CARD; yet the stability of the domain increased considerably upon Zn 2+ binding, with a concomitant reduction in conformational flexibility. Moreover, Zn 2+ binding inhibited polymerization of the CARD9–CARD into helical assemblies. Here, we also present a 20-Å resolution negative-stain EM (NS-EM) structure of these filamentous assemblies and show that they adopt a similar helical symmetry as reported previously for filaments of the Bcl10 CARD. Using both bulk assays and direct NS-EM visualization, we further show that the CARD9–CARD assemblies can directly template and thereby nucleate Bcl10 polymerization, a capacity considered critical to propagation of the CARD9–Bcl10 signaling cascade. Our findings indicate that CARD9 is a potential target of Zn 2+ -mediated signaling that affects Bcl10 polymerization in innate immune responses.
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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) | 0.003 | 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".