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Record W2111556389 · doi:10.1002/bit.22407

Auditioning of CHO host cell lines using the artificial chromosome expression (ACE) technology

2009· article· en· W2111556389 on OpenAlex
Malcolm L. Kennard, Danika L. Goosney, Diane Monteith, S.M. Roe, David Fischer, John E. Mott

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 and Bioengineering · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsCentre for Drug Research and DevelopmentCanadian Institutes of Health Research
Fundersnot available
KeywordsChinese hamster ovary cellTransfectionCell cultureBiologyGeneMonoclonal antibodyGene expressionMolecular biologyCellCell biologyGeneticsComputational biologyAntibody

Abstract

fetched live from OpenAlex

In order to maximize recombinant protein expression in mammalian cells many factors need to be considered such as transfection method, vector construction, screening techniques and culture conditions. In addition, the host cell line can have a profound effect on the protein expression. However, auditioning or directly comparing host cell lines for optimal protein expression may be difficult since most transfection methods are based on random integration of the gene of interest into the host cell genome. Thus it is not possible to determine whether differences in expression between various host cell lines are due to the phenotype of the host cell itself or genetic factors such as gene copy number or gene location. To improve cell line generation, the ACE System was developed based on pre-engineered artificial chromosomes with multiple recombination acceptor sites. This system allows for targeted transfection and has been effectively used to rapidly generate stable CHO cell lines expressing high levels of monoclonal antibody. A key feature of the ACE System is the ability to isolate and purify ACEs containing the gene(s) of interest and transfect the same ACEs into different host cell lines. This feature allows the direct auditioning of host cells since the host cells have been transfected with ACEs that contain the same number of gene copies in the same genetic environment. To investigate this audition feature, three CHO host cell lines (CHOK1SV, CHO-S and DG44) were transfected with the same ACE containing gene copies of a human monoclonal IgG1 antibody. Clonal cell lines were generated allowing a direct comparison of antibody expression and stability between the CHO host cells. Results showed that the CHOK1SV host cell line expressed antibody at levels of more than two to five times that for DG44 and CHO-S host cell lines, respectively. To confirm that the ACE itself was not responsible for the low antibody expression seen in the CHO-S based clones, the ACE was isolated and purified from these cells and transfected back into fresh CHOK1SV cells. The resulting expression of the antibody from the ACE newly transfected into CHOK1SV increased fivefold compared to its expression in CHO-S and confirmed that the differences in expression between the different CHO host cells was due to the cell phenotype rather than differences in gene copy number and/or location. These results demonstrate the utility of the ACE System in providing a rapid and direct technique for auditioning host cell lines for optimal recombinant protein expression.

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 score0.009
Threshold uncertainty score0.479

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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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