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Record W4388214118 · doi:10.26508/lsa.202302045

CRISPR/Cas9 bioluminescence-based assay for monitoring CFTR trafficking to the plasma membrane

2023· article· en· W4388214118 on OpenAlexafffund
Martin Ondra, L. Lenart, Amanda Centorame, Daciana Catalina Dumut, Alexander He, Syeda Sadaf Zehra Zaidi, John W. Hanrahan, Juan Bautista De Sanctis, Danuta Radzioch, Marián Hajdúch

Bibliographic record

VenueLife Science Alliance · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersInstitut de recherche, Centre universitaire de santé McGillUniversity of North Carolina at Chapel HillCanadian Institutes of Health ResearchMcGill University Health CentreMinistère du Développement Économique, de l’Innovation et de l’ExportationCystic Fibrosis Foundation Therapeutics
KeywordsCRISPRCas9Genome editingLuciferaseMolecular biologyBioluminescenceBiologyHEK 293 cellsTransfectionChemistryCell biologyGeneGeneticsBiochemistry

Abstract

fetched live from OpenAlex

CFTR is a membrane protein that functions as an ion channel. Mutations that disrupt its biosynthesis, trafficking or function cause cystic fibrosis (CF). Here, we present a novel in vitro model system prepared using CRISPR/Cas9 genome editing with endogenously expressed WT-CFTR tagged with a HiBiT peptide. To enable the detection of CFTR in the plasma membrane of live cells, we inserted the HiBiT tag in the fourth extracellular loop of WT-CFTR. The 11-amino acid HiBiT tag binds with high affinity to a large inactive subunit (LgBiT), generating a reporter luciferase with bright luminescence. Nine homozygous clones with the HiBiT knock-in were identified from the 182 screened clones; two were genetically and functionally validated. In summary, this work describes the preparation and validation of a novel reporter cell line with the potential to be used as an ultimate building block for developing unique cellular CF models by CRISPR-mediated insertion of CF-causing mutations.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.051
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.334
Teacher spread0.309 · 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
Published2023
Admission routes2
Has abstractyes

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