MétaCan
Menu
Back to cohort
Record W2111170958 · doi:10.1128/jb.02205-14

Development, Antibiotic Production, and Ribosome Assembly in Streptomyces venezuelae Are Impacted by RNase J and RNase III Deletion

2014· article· en· W2111170958 on OpenAlexaff
Stephanie E. Jones, Vivian Leong, Joaquín Ortega, Marie A. Elliot

Bibliographic record

VenueJournal of Bacteriology · 2014
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyRNase PRibosomeAntibioticsStreptomycesGeneticsRNase MRPRibonuclease IIIMicrobiologyRNABacteriaGeneRNA interference

Abstract

fetched live from OpenAlex

RNA metabolism is a critical but frequently overlooked control element affecting virtually every cellular process in bacteria. RNA processing and degradation is mediated by a suite of ribonucleases having distinct cleavage and substrate specificity. Here, we probe the role of two ribonucleases (RNase III and RNase J) in the emerging model system Streptomyces venezuelae. We show that each enzyme makes a unique contribution to the growth and development of S. venezuelae and further affects the secondary metabolism and antibiotic production of this bacterium. We demonstrate a connection between the action of these ribonucleases and translation, with both enzymes being required for the formation of functional ribosomes. RNase III mutants in particular fail to properly process 23S rRNA, form fewer 70S ribosomes, and show reduced translational processivity. The loss of either RNase III or RNase J additionally led to the appearance of a new ribosomal species (the 100S ribosome dimer) during exponential growth and dramatically sensitized these mutants to a range of antibiotics.

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 score0.004
Threshold uncertainty score0.007

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)0.0010.000

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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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

Citations26
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of BacteriologySame topicMicrobial Natural Products and BiosynthesisFrench-language works237,207