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Record W2117199038 · doi:10.1139/w03-072

Fitness cost of the green fluorescent protein in gastrointestinal bacteria

2003· article· en· W2117199038 on OpenAlexvenueno aff
Camilla U. Rang, James E. Galen, James B. Kaper, Lin Chao

Bibliographic record

VenueCanadian Journal of Microbiology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsnot available
FundersUniversity of California, San DiegoVetenskapsrådet
KeywordsGreen fluorescent proteinBiologyBacteriaEscherichia coliShigellaReporter geneMicrobiologyVibrio choleraeShigella flexneriSalmonellaExpression vectorGene expressionGeneticsGeneRecombinant DNA

Abstract

fetched live from OpenAlex

There are surprisingly few studies that have successfully used the green fluorescent protein (GFP) as a quantitative reporter in selection experiments screening for inducible bacterial promoters. One explanation is that GFP expression may confer a fitness cost for bacteria. To test this possibility, we monitored the doubling time in enteric bacteria expressing GFP. Four bacterial species, Escherichia coli, enterohaemorrhagic E. coli, Shigella flexneri, Salmonella typhi, and Vibrio cholerae, were examined. The level of GFP expression was varied by using a salt-inducible promoter. After accounting for the increase in doubling time resulting from elevated osmolarity, the doubling time of all bacteria was found to increase proportionally with GFP expression, and some strains were more affected than others. Cultures of the bacteria most affected by GFP exhibited a proportion of elongated cells, which suggests that GFP production could interfere with cell division in these strains. The results in this study show that GFP is costly to bacteria and suggest that overly active promoters should be difficult to obtain from a genomic promoter library. They also suggest that the chances of succeeding in using GFP as a reporter in selection experiments are increased by growing the bacteria for the fewest number of generations and by subduing the expression of GFP whenever possible, such as by using a low copy vector to clone the library.

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 score0.141
Threshold uncertainty score0.979

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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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

Citations64
Published2003
Admission routes1
Has abstractyes

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