Soluble αβ-tubulins reversibly sequester TTC5 to regulate tubulin mRNA decay
Bibliographic record
Abstract
Summary Microtubules, built from heterodimers of α- and β-tubulins, control cell shape, mediate intracellular transport and power cell division. The concentration of αβ-tubulins is tightly controlled through a post-transcriptional mechanism involving selective and regulated degradation of tubulin-encoding mRNAs. Degradation is initiated by TTC5, which recognizes tubulin-synthesizing ribosomes and recruits downstream effectors to trigger mRNA deadenylation. Here, we have investigated how cells regulate TTC5 activity. Biochemical and structural proteomic approaches reveal that under normal conditions, soluble αβ-tubulins bind to and sequester TTC5, preventing it from engaging nascent tubulins at translating ribosomes. We identify the flexible C-terminal tail of TTC5 as a molecular switch, toggling between soluble αβ-tubulin-bound and nascent tubulin-bound states. Loss of sequestration by soluble αβ-tubulins constitutively activates TTC5, leading to diminished tubulin mRNA levels and compromised microtubule-dependent chromosome segregation during cell division. Our findings provide a paradigm for how cells regulate the activity of a specificity factor to adapt posttranscriptional regulation of gene expression to cellular needs.
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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) | 0.001 | 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".