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Enhancement and rescue of target capture in Tn<i>10</i> transposition by site‐specific modifications in target DNA

2004· article· en· W1920299835 on OpenAlexafffund
Patrick Pribil, Simon J. Wardle, David B. Haniford

Bibliographic record

VenueMolecular Microbiology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsTn10TransposaseBiologyDNATransposable elementTransposition (logic)GeneticsBiophysicsComputational biologyCell biologyGeneMutantComputer science

Abstract

fetched live from OpenAlex

The bacterial transposon Tn10 inserts preferentially into specific target sequences. This insertion specificity appears to be linked to the ability of target sites to adopt symmetrically positioned DNA bends after binding the transposition machinery. Target DNA bending is thought to permit the transposase protein to make additional contacts with the target DNA, thereby stabilizing the target complex so that the joining of transposon and target DNA sequences can occur efficiently. In the current work, we have asked whether the introduction of a discontinuity in a target DNA strand, a modification that is expected to make it easier for a DNA molecule to bend, can enhance or rescue target capture under otherwise suboptimal reaction conditions. We show that either a nick or a missing phosphate specifically at the site of reaction chemistry increases the ability of various target DNAs to form the target capture complex. The result suggests that the bends in the target DNA are highly localized and include the scissile phosphates. This raises the possibility that strand transfer is mechanistically linked to target capture. We have also identified specific residues in the target DNA and in transposase that appear to play an important role in target DNA bending.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.004
GPT teacher head0.195
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2004
Admission routes2
Has abstractyes

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