Structural basis for DNA targeting by the Tn7 transposon
Bibliographic record
Abstract
Abstract Tn7 transposable elements are unique for their highly specific, and sometimes programmable, target-site selection mechanisms and precise insertions. All the elements in the Tn7-family utilize a AAA+ adaptor (TnsC) to coordinates target-site selection with transposase activation and prevent insertions at sites already containing a Tn7 element. Due to its multiple functions, TnsC is considered the linchpin in the Tn7 element. Here we present the high-resolution cryo-EM structure of TnsC bound to DNA using a gain-of-function variant of the protein and a DNA substrate that together recapitulate the recruitment to a specific DNA target site. We find that TnsC forms an asymmetric ring on target DNA that segregates target-site selection and transposase recruitment to opposite faces of the ring. Unlike most AAA+ ATPases, TnsC uses a DNA distortion to find the target site but does not remodel DNA to activate transposition. By recognizing pre-distorted substrates, TnsC creates a built-in regulatory mechanism where ATP-hydrolysis abolishes ring formation proximal to an existing element. This work unveils how Tn7 and Tn7-like elements determine the strict spacing between the target and integration sites.
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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) | 0.002 | 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".