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Record W2900548275 · doi:10.1111/mmi.14168

GcvB small RNA uses two distinct seed regions to regulate an extensive targetome

2018· article· en· W2900548275 on OpenAlexafffund
David Lalaouna, Alex Eyraud, Aurélie Devinck, Karine Prévost, Éric Massé

Bibliographic record

VenueMolecular Microbiology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsBiologyRNase PRNATransfer RNAMessenger RNASmall RNABase pairGeneticsCell biologyMolecular biologyGene

Abstract

fetched live from OpenAlex

GcvB small RNA is described as post-transcriptional regulator of 1-2% of all mRNAs in Escherichia coli and Salmonella Typhimurium. At least 24 GcvB:mRNA interactions have been validated in vivo, establishing the largest characterized sRNA targetome. By performing MS2-affinity purification coupled with RNA sequencing (MAPS) technology, we identified seven additional mRNAs negatively regulated by GcvB in E. coli. Contrary to the vast majority of previously known targets, which pair to the well-conserved GcvB R1 region, we validated four mRNAs targeted by GcvB R3 region. This indicates that base-pairing through R3 seed sequence seems relatively common. We also noticed unusual GcvB pairing sites in the coding sequence of two target mRNAs. One of these target mRNAs has a pairing site displaying a unique ACA motif, suggesting that GcvB could hijack a translational enhancer element. The second target mRNA is likely regulated via an active RNase E-mediated mRNA degradation mechanism. Remarkably, we confirmed the importance of the sRNA sponge SroC in the fine-tuning control of GcvB activity in function of growth conditions such as growth phase and nutrient availability.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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.

Opus teacher head0.013
GPT teacher head0.250
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2018
Admission routes2
Has abstractyes

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