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Record W4400572285 · doi:10.1016/j.microb.2024.100125

Deletion of HindIIR and HindIIIR improves DNA transfer via electroporation to Haemophilus influenzae Rd

2024· article· en· W4400572285 on OpenAlexaff
Samir Hamadache, Yu Kang Huang, Adam Shedeed, Aqil Syed, Bogumil J. Karas

Bibliographic record

VenueThe Microbe · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsWestern University
Fundersnot available
KeywordsElectroporationHaemophilus influenzaePlasmidBiologyTransformation (genetics)MicrobiologyDNAGeneticsComputational biologyAntibioticsGene

Abstract

fetched live from OpenAlex

Haemophilus influenzae is a bacterial species of interest for its medical relevance and utility as a model system. Despite its role in several landmark molecular and synthetic biology studies, H. influenzae remains underexplored as a potential chassis organism. The limited availability of reliable and convenient transformation methods and genetic tools for H. influenzae are obstacles to this end. However, a strain of H. influenzae Rd KW20 lacking the type II restriction endonucleases Hin dII and Hin dIII has previously been developed. Here, we show that this strain is more readily transformable by electroporation than wild-type Rd KW20. We also developed a series of multi-host plasmids carrying antibiotic selection and fluorescent visual markers based on the pSU20 vector. The availability of H. influenzae Δ Hin dII/III, paired with the electroporation method and plasmids presented here, will promote the exploration of H. influenzae as a host organism for synthetic biology applications. • Deletion of HindII and HindIII in H. influenzae Rd KW20 improves transformation efficiency via electroporation. • Developed pSU20-based plasmids with antibiotic and fluorescent markers, compatible with various bacterial hosts. • Method was developed for preparing electrocompetent H. influenzae cells and transforming them via electroporation.

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 score0.026
Threshold uncertainty score0.317

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 head0.222
Teacher spread0.216 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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