↓ Skip to main content

Modeling the Contribution of Allosteric Regulation for Flux Control in the Central Carbon Metabolism of E. coli

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, October 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
35 Dimensions

Readers on

mendeley
85 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Modeling the Contribution of Allosteric Regulation for Flux Control in the Central Carbon Metabolism of E. coli
Published in
Frontiers in Bioengineering and Biotechnology, October 2015
DOI 10.3389/fbioe.2015.00154
Pubmed ID
Authors

Daniel Machado, Markus J. Herrgård, Isabel Rocha

Abstract

Modeling cellular metabolism is fundamental for many biotechnological applications, including drug discovery and rational cell factory design. Central carbon metabolism (CCM) is particularly important as it provides the energy and precursors for other biological processes. However, the complex regulation of CCM pathways has still not been fully unraveled and recent studies have shown that CCM is mostly regulated at post-transcriptional levels. In order to better understand the role of allosteric regulation in controlling the metabolic phenotype, we expand the reconstruction of CCM in Escherichia coli with allosteric interactions obtained from relevant databases. This model is used to integrate multi-omics datasets and analyze the coordinated changes in enzyme, metabolite, and flux levels between multiple experimental conditions. We observe cases where allosteric interactions have a major contribution to the metabolic flux changes. Inspired by these results, we develop a constraint-based method (arFBA) for simulation of metabolic flux distributions that accounts for allosteric interactions. This method can be used for systematic prediction of potential allosteric regulation under the given experimental conditions based on experimental data. We show that arFBA allows predicting coordinated flux changes that would not be predicted without considering allosteric regulation. The results reveal the importance of key regulatory metabolites, such as fructose-1,6-bisphosphate, in controlling the metabolic flux. Accounting for allosteric interactions in metabolic reconstructions reveals a hidden topology in metabolic networks, improving our understanding of cellular metabolism and fostering the development of novel simulation methods that account for this type of regulation.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 1%
Denmark 1 1%
Unknown 83 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 22%
Researcher 17 20%
Student > Bachelor 10 12%
Student > Master 9 11%
Professor 4 5%
Other 5 6%
Unknown 21 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 28%
Agricultural and Biological Sciences 23 27%
Chemical Engineering 4 5%
Engineering 3 4%
Computer Science 3 4%
Other 8 9%
Unknown 20 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 October 2015.
All research outputs
#18,428,159
of 22,829,683 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#3,396
of 6,561 outputs
Outputs of similar age
#200,101
of 278,190 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#43
of 68 outputs
Altmetric has tracked 22,829,683 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,561 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 30th percentile – i.e., 30% 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 278,190 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.