T box RNA decodes both the information content and geometry of tRNA to affect gene expression
Bibliographic record
Abstract
The T box leader sequence is an RNA element that controls gene expression by binding directly to a specific tRNA and sensing its aminoacylation state. This interaction controls expression of amino acid-related genes in a negative feedback loop. The T box RNA structure is highly conserved, but its tRNA binding mechanism is only partially understood. Known sequence elements are the specifier sequence, which recognizes the tRNA anticodon, and the antiterminator bulge, which base pairs with the tRNA acceptor end. Here, we reveal the crucial function of the highly conserved stem I distal region in tRNA recognition and report its 2.65-Å crystal structure. The apex of this region contains an intricately woven loop-loop interaction between two conserved motifs, the Adenine-guanine (AG) bulge and the distal loop. This loop-loop structure presents a base triple on its surface that is optimally positioned for base-stacking interactions. Mutagenesis, cross-linking, and small-angle X-ray scattering data demonstrate that the apical base triple serves as a binding platform to dock the tRNA D- and T-loops. Strikingly, the binding platform strongly resembles the D- and T-loop binding elements from RNase P and the ribosome exit site, suggesting that this loop-loop structure may represent a widespread tRNA recognition platform. We propose a two-checkpoint molecular ruler model for tRNA decoding in which the information content of tRNA is first examined through specifier sequence-anticodon interaction, and the length of the tRNA anticodon arm is then measured by the distal loop-loop platform. When both conditions are met, tRNA is secured, and its aminoacylation state is sensed.
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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".