TDRD3, a novel Tudor domain-containing protein, localizes to cytoplasmic stress granules
Bibliographic record
Abstract
Our previous work has demonstrated that the Tudor domain of the 'survival of motor neuron' protein and the Tudor domain-containing protein 3 (TDRD3) are highly similar and that they both have the ability to interact with arginine-methylated polypeptides. TDRD3 has been identified among genes whose overexpression has a strong predictive value for poor prognosis of estrogen receptor-negative breast cancers, although its precise function remains unknown. TDRD3 is a modular protein, and in addition to its Tudor domain, it harbors a putative nucleic acid recognition motif and a ubiquitin-associated domain. We report here that TDRD3 localizes predominantly to the cytoplasm, where it co-sediments with the fragile X mental retardation protein on actively translating polyribosomes. We also demonstrate that TDRD3 accumulates into stress granules (SGs) in response to various cellular stresses. Strikingly, the Tudor domain of TDRD3 was found to be both required and sufficient for its recruitment to SGs, and the methyl-binding surface in the Tudor domain is important for this process. Pull down experiments identified five novel TDRD3 interacting partners, most of which are potentially methylated RNA-binding proteins. Our findings revealed that two of these proteins, SERPINE1 mRNA-binding protein 1 and DEAD/H box-3 (a gene often deleted in Sertoli-cell-only syndrome), are also novel constituents of cytoplasmic SGs. Taken together, we report the first characterization of TDRD3 and its functional interaction with at least two proteins implicated in human genetic diseases and present evidence supporting a role for arginine methylation in the regulation of SG dynamics.
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) | 0.001 | 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".