MétaCan
Menu
Back to cohort
Record W3011104163 · doi:10.1186/s40709-020-0111-0

Metabolic engineering of Escherichia coli for the utilization of ethanol

2020· article· en· W3011104163 on OpenAlexfundno aff
Yujin Cao, Hui Mu, Jing Guo, Hui Liu, Rubing Zhang, Wei Liu, Mo Xian, Huizhou Liu

Bibliographic record

VenueJournal of Biological Research - Thessaloniki · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsnot available
FundersNational Institute of Standards and TechnologyPetroleum Technology Research CentreNational Natural Science Foundation of China
KeywordsEscherichia coliMetabolic engineeringEthanolChemistryFood scienceBiotechnologyBiochemistryMicrobiologyBiologyEnzyme

Abstract

fetched live from OpenAlex

Abstract Background The fuel ethanol industry has made tremendous progress in the last decades. Ethanol can be obtained by fermentation using a variety of biomass materials as the feedstocks. However, few studies have been conducted on ethanol utilization by microorganisms. The price of petroleum-derived ethanol, easily made by the hydrolysis of ethylene, is even lower than that of bioethanol. If ethanol can be metabolized by microorganisms to produce value-added chemicals, it will open a new door for the utilization of inexpensive ethanol resources. Results We constructed an engineered Escherichia coli strain which could utilize ethanol as the sole carbon source. The alcohol dehydrogenase and aldehyde dehydrogenase from Aspergillus nidulans was introduced into E. coli and the recombinant strain acquired the ability to grow on ethanol. Cell growth continued when ethanol was supplied after glucose starvation and 2.24 g L −1 of ethanol was further consumed during the shake-flasks fermentation process. Then ethanol was further used for the production of mevalonic acid by heterologously expressing its biosynthetic pathway. Deuterium-labeled ethanol-D6 as the feedstock confirmed that mevalonic acid was synthesized from ethanol. Conclusions This study demonstrated the possibility of using ethanol as the carbon source by engineered E. coli strains. It can serve as the basis for the construction of more robust strains in the future though the catabolic capacity of ethanol should be further improved.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.050
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.137
GPT teacher head0.356
Teacher spread0.220 · 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

Citations32
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biological Research - ThessalonikiSame topicMicrobial Metabolic Engineering and BioproductionFrench-language works237,207