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Tn<i>10</i>/IS<i>10</i> transposition is downregulated at the level of transposase expression by the RNA‐binding protein Hfq

2010· article· en· W1923825601 on OpenAlexafffund
Joseph A. Ross, Simon J. Wardle, David B. Haniford

Bibliographic record

VenueMolecular Microbiology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyTransposaseTransposition (logic)RNARNA silencingRNA interferenceGene expressionCell biologyMolecular biologyRNA-induced transcriptional silencingAntisense RNATranslation (biology)Sense (electronics)GeneMessenger RNATransposable elementGeneticsChemistry

Abstract

fetched live from OpenAlex

We show in this work that disruption of the hfq gene in Escherichia coli causes a large increase in IS10 transposition when IS10 is present on a multi-copy plasmid. Hfq is an RNA-binding protein that regulates the expression of a large number of genes at the post-transcriptional level by promoting the pairing of mRNAs with partially complementary short RNAs. As the translation of IS10 transposase mRNA (RNA-IN) is inhibited by an IS10-encoded anti-sense RNA (RNA-OUT), it seemed likely that Hfq would negatively regulate Tn10/IS10 transposition by promoting anti-sense inhibition of RNA-IN translation. Consistent with this, we show that Hfq promotes pairing of RNA-IN and RNA-OUT in vitro and downregulates RNA-IN expression in vivo. However, we also show that Hfq negatively regulates Tn10 transposition when no functional anti-sense RNA is produced. Taken together, the results suggest that Hfq acts at two distinct steps to inhibit Tn10/IS10 transposition. This is the first example of Hfq regulating a bacterial transposition reaction.

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 score0.142
Threshold uncertainty score0.868

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.209
Teacher spread0.201 · 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

Citations36
Published2010
Admission routes2
Has abstractyes

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