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Record W2989392176 · doi:10.1007/s10529-019-02749-4

Identification and characterization of sequence signatures in the Bacillus subtilis promoter Pylb for tuning promoter strength

2019· article· en· W2989392176 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiotechnology Letters · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsBiotechnology Research Institute
FundersNational Natural Science Foundation of China
KeywordsPromoterGeneBiologyBacillus subtilisMolecular biologyMutantConsensus sequenceNucleic acid sequenceGeneticsGene expressionPeptide sequenceBacteria

Abstract

fetched live from OpenAlex

OBJECTIVE: promoter and identify the elements that affect the promoter activity. RESULT: promoter were divided into six segments, and six random-scanning mutant promoter libraries fused to an enhanced green fluorescent protein EGFP were made and analyzed by flow cytometry. Our results showed that the four nucleotides flanking the - 35 box could mostly influence the promoter activity, and this influence was related to the GC content. The promoters mutated in these regions were successfully used for expressing the gene ophc2 encoding organophosphorus hydrolase (OPHC2) and the gene katA encoding catalase (KatA). CONCLUSION: promoter that could tune the promoter strength, providing further information for the potential application of this promoter. Meanwhile, the sequence signatures have the potential to be used for tuning gene expression in enzyme production, metabolic engineering, and synthetic biology.

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.

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 score0.006
Threshold uncertainty score0.252

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.208
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