The molecular basis of T cell receptor recognition of citrullinated tenascin-C presented by HLA-DR4
Bibliographic record
Abstract
CD4 + T cell autoreactivity against citrullinated (cit) self-epitopes presented by HLA-DRB1 is associated with rheumatoid arthritis (RA) pathogenesis. We understand the molecular bases of T cell receptor (TCR) recognition of cit-fibrinogen, cit-vimentin, and cit-α-enolase epitopes, and the role of citrulline in shaping TCR repertoire usage. Nevertheless, how TCRs recognise other cit-epitopes, including tenascin-C (TNC) and how alternative citrullination positions may modulate the T cell recognition remains unclear. Here, we examined TNC 1014,1016cit peptide, which contains citrullination at position P-1 and P2, to study the underlying TCR-HLA-DRB1*04:01- TNC 1014,1016cit molecular interactions. Crystal structure of HLA-DRB1*04:01 TNC1014,1016cit at 2.4 Å resolution revealed a conserved peptide binding register to the established HLA-DRB1*04:01-peptide structures, where both citrullines protruded upwards. Next, we determined the crystal structure of a RA patient-derived TRAV35 + /TRBV10-2 + (PB) TCR in complex with HLA-DRB1*04:01 TNC1014,1016cit at 3.2 Å resolution. The CDR3α loop ( 109 VGNTN 113 ) of PB TCR formed a secondary helical conformation at the N-terminus of the peptide binding cleft, allowing extensive interactions between the P-1 and P2 citrullines of TNC 1014,1016cit peptide. Surface plasmon resonance, tetramer staining, and CD69 activation assays revealed that the PB TCR did not cross-react to other RA autoantigens, and the P-1-Cit, P2-Cit, and P5-Tyr of TNC 1014,1016cit are the key determinants underlining the strict specificity of the PB TCR. Collectively, we provide molecular insight of citrullination in modulating TCR recognition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".