MétaCan
Menu
Back to cohort
Record W2732562267 · doi:10.1080/09168451.2017.1345612

<i>Escherichia coli yjjPB</i> genes encode a succinate transporter important for succinate production

2017· article· en· W2732562267 on OpenAlexfundno aff
Keita Fukui, Kei Nanatani, Yoshihiko Hara, Suguru Yamakami, Daiki Yahagi, Akito Chinen, Mitsunori Tokura, Keietsu Abe

Bibliographic record

VenueBioscience Biotechnology and Biochemistry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsnot available
FundersKeio UniversityPetroleum Technology Alliance Canada
KeywordsEscherichia coliCorynebacterium glutamicumComplementationGeneSuccinate dehydrogenaseBiologySuccinic acidBiochemistryCitric acid cycleMicrobiologyChemistryMitochondrionMetabolismPhenotype

Abstract

fetched live from OpenAlex

Under anaerobic conditions, Escherichia coli produces succinate from glucose via the reductive tricarboxylic acid cycle. To date, however, no genes encoding succinate exporters have been established in E. coli. Therefore, we attempted to identify genes encoding succinate exporters by screening an E. coli MG1655 genome library. We identified the yjjPB genes as candidates encoding a succinate transporter, which enhanced succinate production in Pantoea ananatis under aerobic conditions. A complementation assay conducted in Corynebacterium glutamicum strain AJ110655ΔsucE1 demonstrated that both YjjP and YjjB are required for the restoration of succinate production. Furthermore, deletion of yjjPB decreased succinate production in E. coli by 70% under anaerobic conditions. Taken together, these results suggest that YjjPB constitutes a succinate transporter in E. coli and that the products of both genes are required for succinate export.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBioscience Biotechnology and BiochemistrySame topicMicrobial Metabolic Engineering and BioproductionFrench-language works237,207