Escherichia coli proteins uL29 and ACP stabilize the Tn7-encoded TnsD and its DNA binding
Bibliographic record
Abstract
Tn7 mobile genetic elements are known for their sophisticated target-site selection mechanisms and, in some cases, programmability. Recognition of target sites is mediated by designated transposon-encoded proteins and modulated by host factor proteins. In the case of the CRISPR-associated Tn7 elements from the type V-K, the ribosomal protein uS15 is an integral component of recruitment complex that promotes R-loop completion. Previous biochemical work also revealed that the ribosomal protein uL29 and the acyl carrier protein (ACP) influence Tn7 transposition frequency in vitro. However, how uL29 and ACP regulate the formation of the Tn7 targeting complex remains unclear. The prototypical Tn7 element encodes a heteromeric transposase (TnsA, TnsB), a AAA + adaptor (TnsC), and two target-site selection proteins (TnsD and TnsE). TnsD targets a highly conserved site at the end of the glmS gene (attTn7). However, poor protein stability has precluded the molecular characterization of how TnsD recognizes its target site. Here, we show that ACP and uL29 interact with the C-terminal region of TnsD through reciprocal electrostatic interactions, in turn, mitigating its tendency to aggregate. Additionally, we identify the uL29 and ACP residues that mediate the interaction with TnsD and stimulate DNA binding. These results unveil unique features of the TnsD-mediated target-site selection complex.
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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 | 0.001 |
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".