PITA, a pre-bilaterian p75NTR, is the evolutionary ancestor of TNF receptors
Bibliographic record
Abstract
Abstract Tumor necrosis factor receptors (TNFRs) regulate a diverse array of biological functions, including adaptive immunity, neurodevelopment, and many others. Although TNFRs are expressed in all metazoan phyla, a coherent model of the molecular origins of mammalian TNFRs—and how they relate to TNFRs in other phyla—has remained elusive. To address this, we executed a large-scale, systematic Basic Local Alignment Search Tool (BLAST)-based approach to trace the evolutionary ancestry of all 29 human TNFRs. We discovered that all human TNFRs are descendants of a single pre-bilaterian TNFR with strong sequence similarity to the p75 neurotrophin receptor (p75NTR), which we designate as PITA for ‘ p75NTR is the TNFR Ancestor ’. A distinct subset of human TNFRs—including EDAR, XEDAR and TROY—share a unique history as descendants of EDAR-XEDAR-TROY (EXT), which diverged from PITA in a bilaterian ancestor. Most PITA descendants possess a death domain (DD) within their intracellular domain (ICD) but EXTs do not. PITA descendants are expressed in all bilaterian phyla and Cnidaria, but not in non-planulozoan ParaHoxozoa, suggesting that PITA originated in an ancestral planulozoan. Drosophila melanogaster TNFRs (Wengen (Wgn) and Grindelwald (Grnd)) were identified as divergent PITA descendants, providing the first evolutionary link between this model TNFR system and the mammalian TNFR superfamily. This study reveals PITA as the ancestor to human and Drosophila TNFR systems and describes an evolutionary model that will facilitate deciphering TNF-TNFR functions in health and disease.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".