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Record W3023230312 · doi:10.1111/jam.14690

Controlled expression of lysis gene E by a mutant of the promoter pL of the thermo‐inducible λcI857‐pL system

2020· article· en· W3023230312 on OpenAlexfundno aff
L.-X. Fu, Jiansen Gong, Bo Gao, Dejun Ji, Xiangan Han, L. B. Zeng

Bibliographic record

VenueJournal of Applied Microbiology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
FundersMinistry of Agriculture - Saskatchewan
KeywordsLytic cycleLysisMutantMutagenesisEscherichia coliBiologyMolecular biologyPlasmidGeneMutationLambda phageMicrobiologyChemistryBiochemistryGeneticsBacteriophage

Abstract

fetched live from OpenAlex

AIMS: To identify a lambda promoter pL mutant that could extend the thermal stability of the thermo-inducible λcI857-pR/pL system and to evaluate the effects of the modified system for the controlled expression of lysis gene E during the production of bacterial ghosts (BGs). METHODS AND RESULTS: The promoter pL mutant was identified by random mutagenesis and site-directed mutagenesis. The results showed that a T → 35C mutation in the pL promoter was responsible for the phenotype alteration. Under the same induction conditions, the lysis rates of the modified lytic system on Escherichia coli and Salmonella enteritidis were significantly lower than that of the control, while the lysis rates of Escherichia coli with the thermo-inducible lytic system were significantly higher than that of S. enteritidis with the corresponding plasmid (P < 0·05). CONCLUSIONS: Increasing the heat stability of the thermo-inducible lytic systems decreased lysis efficiency during the production of BGs. There exist differences in the lysis efficiency of thermo-inducible lytic systems between different bacterial strains. SIGNIFICANCE AND IMPACT OF THE STUDY: These findings enrich current knowledge about modifications to thermo-inducible systems and provide a reference for the application of these modified systems for the production of BGs and controlled gene expression in bacteria.

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 score0.002
Threshold uncertainty score0.129

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.169
Teacher spread0.160 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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