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Modeling and simulation of the redox regulation of the metabolism in Escherichia coli at different oxygen concentrations

Overview of attention for article published in Biotechnology for Biofuels and Bioproducts, July 2017
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Title
Modeling and simulation of the redox regulation of the metabolism in Escherichia coli at different oxygen concentrations
Published in
Biotechnology for Biofuels and Bioproducts, July 2017
DOI 10.1186/s13068-017-0867-0
Pubmed ID
Authors

Yu Matsuoka, Hiroyuki Kurata

Abstract

Microbial production of biofuels and biochemicals from renewable feedstocks has received considerable recent attention from environmental protection and energy production perspectives. Many biofuels and biochemicals are produced by fermentation under oxygen-limited conditions following initiation of aerobic cultivation to enhance the cell growth rate. Thus, it is of significant interest to investigate the effect of dissolved oxygen concentration on redox regulation in Escherichia coli, a particularly popular cellular factory due to its high growth rate and well-characterized physiology. For this, the systems biology approach such as modeling is powerful for the analysis of the metabolism and for the design of microbial cellular factories. Here, we developed a kinetic model that describes the dynamics of fermentation by taking into account transcription factors such as ArcA/B and Fnr, respiratory chain reactions and fermentative pathways, and catabolite regulation. The hallmark of the kinetic model is its ability to predict the dynamics of metabolism at different dissolved oxygen levels and facilitate the rational design of cultivation methods. The kinetic model was verified based on the experimental data for a wild-type E. coli strain. The model reasonably predicted the metabolic characteristics and molecular mechanisms of fnr and arcA gene-knockout mutants. Moreover, an aerobic-microaerobic dual-phase cultivation method for lactate production in a pfl-knockout mutant exhibited promising yield and productivity. It is quite important to understand metabolic regulation mechanisms from both scientific and engineering points of view. In particular, redox regulation in response to oxygen limitation is critically important in the practical production of biofuel and biochemical compounds. The developed model can thus be used as a platform for designing microbial factories to produce a variety of biofuels and biochemicals.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 22%
Student > Bachelor 9 13%
Student > Master 9 13%
Researcher 8 12%
Other 4 6%
Other 8 12%
Unknown 14 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 27%
Agricultural and Biological Sciences 14 21%
Engineering 9 13%
Chemical Engineering 3 4%
Computer Science 3 4%
Other 4 6%
Unknown 16 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2017.
All research outputs
#15,173,117
of 25,382,440 outputs
Outputs from Biotechnology for Biofuels and Bioproducts
#790
of 1,578 outputs
Outputs of similar age
#169,520
of 324,716 outputs
Outputs of similar age from Biotechnology for Biofuels and Bioproducts
#26
of 50 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,578 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 324,716 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.