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Record W2109515448 · doi:10.1534/genetics.107.082040

Metabolic Changes Associated With Adaptive Diversification in <i>Escherichia coli</i>

2008· article· en· W2109515448 on OpenAlexaff
Mickaël Le Gac, Michelle D. Brazas, Melanie Bertrand, Jabus Tyerman, Christine C. Spencer, Robert E. W. Hancock, Michael Doebeli

Bibliographic record

VenueGenetics · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEvolution and Genetic Dynamics
Canadian institutionsBritish Columbia Institute of TechnologyUniversity of British Columbia
FundersJames S. McDonnell Foundation
KeywordsBiologyEscherichia coliOperonGeneGeneticsAdaptation (eye)Biochemistry

Abstract

fetched live from OpenAlex

During a 1000-generation evolution experiment, two types of morphologically and kinetically distinct bacteria repeatedly diverged from a common ancestor in a fully sympatric seasonal environment containing glucose and acetate. To investigate the metabolic modifications associated with this adaptive diversification, we compared transcription profiles of the two derived types and the common ancestor. Both derived types share a suite of common metabolic changes that may represent adaptation to the environment preceding the diversification event. These include improved translation efficiency, glucose uptake capacity via the mal/lamB genes, upregulation of various transporters during stationary phase, and likely the disruption of the rbs operon. The diversification event is associated with the overexpression of genes involved in the TCA cycle, glyoxylate shunt, acetate consumption, and anaerobic respiration in one type and in acetate excretion in the other. These results reveal that competition for both carbon and oxygen have likely played an important role in the adaptation of Escherichia coli during this adaptive diversification event, where one derived type mainly consumes glucose at a fast rate when oxygen is not limiting, and the other derived type consumes glucose and acetate at a slower rate, even when oxygen is limiting.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score0.513

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 head0.016
GPT teacher head0.217
Teacher spread0.200 · 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 designObservational
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

Citations41
Published2008
Admission routes1
Has abstractyes

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