MétaCan
Menu
Back to cohort
Record W2147806270 · doi:10.1002/bab.1423

Vector promoters used in <i>Klebsiella pneumoniae</i>

2015· article· en· W2147806270 on OpenAlexfundno aff
Xiao Jiang, Chengqian Zhu, Jie Lin, Jingkang Li, Shuilin Fu, Heng Gong

Bibliographic record

VenueBiotechnology and Applied Biochemistry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaPetroleum Technology Alliance Canada
KeywordsKlebsiella pneumoniaePromoterReporter genelac operonGene expressionGeneBiologyMicrobiologyEscherichia coliChemistryMolecular biologyGenetics

Abstract

fetched live from OpenAlex

Much effort has been devoted to the metabolic engineering of Klebsiella pneumoniae; however, our knowledge of the actual expression level of promoters used in K. pneumoniae is limited. In this study, the expression levels of three promoters were compared systematically by using the lacZ reporter gene with different carbon sources in K. pneumoniae. The results showed that, although promoters PT5 and Ptac designed for Escherichia coli were functional, PT5 appeared more efficient and the induction/repression ratio of Ptac was decreased extremely in K. pneumoniae. The basal level of Ptac for lacZ expression reached 396.5 U/mg, which was 9.5-fold higher compared with PT5 in LB medium, indicating Ptac can be used as an efficient "constitutive" promoter as well as an efficient induced promoter in K. pneumoniae. In different carbon sources medium, a newly constructed endogenous constitutive Pbud proved to be a stable and weak promoter. On the basis of our data, a set of Pbud and Ptac promoters could meet the broad range (about 1,000 orders of magnitude) of gene expression needed for engineered K. pneumoniae in glycerol-based medium.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.211
Teacher spread0.202 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueBiotechnology and Applied BiochemistrySame topicBacterial Genetics and BiotechnologyFrench-language works237,207