ReviewJournal of industrial microbiology & biotechnology2011
Metabolically engineered Escherichia coli for biotechnological production of four-carbon 1,4-dicarboxylic acids.
Review in Journal of industrial microbiology & biotechnology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
Who cites it
8 citing papers in PubMed.
- Proteomics Reveal the Effect of Exogenous Electrons on ElectroactiveFrontiers in microbiology · 2022Article
- High yield production of four-carbon dicarboxylic acids by metabolically engineered Escherichia coli.Journal of industrial microbiology & biotechnology · 2018Article
- Metabolic engineering of carbon and redox flow in the production of small organic acids.Journal of industrial microbiology & biotechnology · 2015Review
- Engineering microorganisms based on molecular evolutionary analysis: a succinate production case study.Evolutionary applications · 2014Article
- Succinate Overproduction: A Case Study of Computational Strain Design Using a Comprehensive Escherichia coli Kinetic Model.Frontiers in bioengineering and biotechnology · 2014Article
- Engineered Bacillus subtilis 168 produces L-malate by heterologous biosynthesis pathway construction and lactate dehydrogenase deletion.World journal of microbiology & biotechnology · 2013Article
- Fermentative succinate production: an emerging technology to replace the traditional petrochemical processes.BioMed research international · 2013Review
- Improved succinate production by metabolic engineering.BioMed research international · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Confronted with inescapable exhaustion of the earth's fossil energy resources, the bio-based process to produce industrial chemicals is receiving significant interest. Biotechnological production of four-carbon 1,4-dicarboxylic acids (C4 diacids) from renewable plant biomass is a promising and attractive alternative to conventional chemistry routes. Although the C4 diacids pathway is well characterized and microorganisms able to convert biomass to these acids have been isolated and described, much still has to be done to make this process economically feasible. Metabolically engineered Escherichia coli has been developed as a biocatalyst to provide new processes for the biosynthesis of many valuable chemicals. However, E. coli does not naturally produce C4 diacids in large quantities. Rational strain development by metabolic engineering based on efficient genetic tools and detailed knowledge of metabolic pathways are crucial to successful production of these compounds. This review summarizes recent efforts and experiences devoted to metabolic engineering of the industrial model bacteria E. coli that led to efficient recombinant biocatalysts for the production of C4 diacids, including succinate, fumarate, malate, oxaloacetate, and aspartate, as well as the key limitations and challenges. Continued advancements in metabolic engineering will help to improve the titers, yields, and productivities of the C4 diacids discussed here.
Indexed as
Identifiers
21113642What OpenQuestion holds
Registered trials
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.