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Record W2154192760 · doi:10.1002/bit.20428

Transient gene expression in HEK293 cells: Peptone addition posttransfection improves recombinant protein synthesis

2005· article· en· W2154192760 on OpenAlexaff
Phuong Lan Pham, Sylvie Perret, Brian Cass, Éric Le Carpentier, G. J. St-Laurent, Louis Bisson, Amine Kamen, Yves Durocher

Bibliographic record

VenueBiotechnology and Bioengineering · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsNational Research Council CanadaBiotechnology Research Institute
Fundersnot available
KeywordsGreen fluorescent proteinBiochemistryValineAmino acidRecombinant DNAProtein biosynthesisTransfectionLeucineAsparagineChemistryGene expressionCaseinGlycineMolecular biologyGeneBiology

Abstract

fetched live from OpenAlex

Gene expression by large-scale transfection of mammalian cells is becoming an established technology for the fast production of milligram and even gram amounts of recombinant proteins (r-proteins). However, efforts are still needed to optimize production parameters in order to maximize volumetric productivities while maintaining product quality. In this study, transfection efficiency and volumetric productivity following transient gene expression in HEK293 cells were evaluated using green fluorescent protein (GFP) and human placental secreted alkaline phosphatase (SEAP) as reporter genes. We show that a single pulse of peptones (protein hydrolysates) to the cultures performed in a low serum (1%, v/v) and in serum-free medium results in a significant increase in volumetric protein productivity. Sixteen peptones from different sources were tested and almost all of them showed a positive effect on r-protein production. This effect, however, is time- and concentration-dependent. By using Tryptone N1 (a casein peptone, TN1) to feed the cultures at 24 h posttransfection (hpt), a 2-fold increase in volumetric SEAP productivity was obtained 5 days posttransfection. This effect was shown to be equal to that obtained when the culture was fed with a supplementary 4% (v/v) of serum. The positive effect of TN1 on protein production was also demonstrated with Tie2 protein ectodomain produced in serum-free medium. HPLC analysis of amino acids consumption/production during control batch and TN1 pulse culture showed some major differences in amino acid metabolism when using TN1 pulse. Asparagine, glycine, histidine, threonine, leucine, and valine show accumulation in the medium over the cultivation period instead of being consumed as observed in unfed sample (except for asparagine, which remained unchanged). Isoleucine, tyrosine, methionine, and phenylalanine all remained unchanged or slightly fluctuated in TN1-fed culture after the feeding pulse, while they were all steadily consumed in the control run. The relative abundance of SEAP's mRNA suggests that the improvement in protein yield results both from an increase of the translational activity and transcription efficiency. Further understanding of mechanisms by which amino acids/peptides regulate transcriptional and translational machinery in mammalian cells should facilitate the design of new strategies for the improvement of r-protein production by large-scale transfection.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations115
Published2005
Admission routes1
Has abstractyes

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