Evidence map›Paper›PMID 33317614›Full record

ArticleBiotechnology for biofuels2020

Rewiring of glycerol metabolism in Escherichia coli for effective production of recombinant proteins.

Chung-Jen Chiang, Yi-Jing Ho, Mu-Chen Hu, Yun-Peng Chao

Abstract read
In one paragraph

Article in Biotechnology for biofuels, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Engineering ofMicroorganisms · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Evaluation of VariousJournal of microbiology and biotechnology · 2023
    Article
  9. Review
  10. Article
  11. Metabolically EngineeredFrontiers in bioengineering and biotechnology · 2022
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chung-Jen ChiangDepartment of Medical Laboratory Science and Biotechnology, China Medical University, No. 91, Hsueh-Shih Road, Taichung, 40402, Taiwan.
Yi-Jing HoDepartment of Chemical Engineering, Feng Chia University, 100 Wenhwa Road, Taichung, 40724, Taiwan.
Mu-Chen HuDepartment of Chemical Engineering, Feng Chia University, 100 Wenhwa Road, Taichung, 40724, Taiwan.
Yun-Peng ChaoDepartment of Chemical Engineering, Feng Chia University, 100 Wenhwa Road, Taichung, 40724, Taiwan. ypchao@fcu.edu.tw.ORCID http://orcid.org/0000-0001-7997-0752

Funding

Ministry of Science and Technology, Taiwan 108-2221-E-035-052-MY3
6 · The paper itself

Abstract

backgroundThe economic viability of a protein-production process relies highly on the production titer and the price of raw materials. Crude glycerol coming from the production of biodiesel is a renewable and cost-effective resource. However, glycerol is inefficiently utilized by Escherichia coli.

resultsThis issue was addressed by rewiring glycerol metabolism for redistribution of the metabolic flux. Key steps in central metabolism involving the glycerol dissimilation pathway, the pentose phosphate pathway, and the tricarboxylic acid cycle were pinpointed and manipulated to provide precursor metabolites and energy. As a result, the engineered E. coli strain displayed a 9- and 30-fold increase in utilization of crude glycerol and production of the target protein, respectively.

conclusionsThe result indicates that the present method of metabolic engineering is useful and straightforward for efficient adjustment of the flux distribution in glycerol metabolism. The practical application of this methodology in biorefinery and the related field would be acknowledged.

Indexed as

Crude glycerolMetabolic engineeringRecombinant protein

Identifiers

PMID33317614
PMCPMC7737366

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.