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Model-Based Design of Biochemical Microreactors

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, February 2016
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Title
Model-Based Design of Biochemical Microreactors
Published in
Frontiers in Bioengineering and Biotechnology, February 2016
DOI 10.3389/fbioe.2016.00013
Pubmed ID
Authors

Tobias Elbinger, Markus Gahn, Maria Neuss-Radu, Falk M. Hante, Lars M. Voll, Günter Leugering, Peter Knabner

Abstract

Mathematical modeling of biochemical pathways is an important resource in Synthetic Biology, as the predictive power of simulating synthetic pathways represents an important step in the design of synthetic metabolons. In this paper, we are concerned with the mathematical modeling, simulation, and optimization of metabolic processes in biochemical microreactors able to carry out enzymatic reactions and to exchange metabolites with their surrounding medium. The results of the reported modeling approach are incorporated in the design of the first microreactor prototypes that are under construction. These microreactors consist of compartments separated by membranes carrying specific transporters for the input of substrates and export of products. Inside the compartments of the reactor multienzyme complexes assembled on nano-beads by peptide adapters are used to carry out metabolic reactions. The spatially resolved mathematical model describing the ongoing processes consists of a system of diffusion equations together with boundary and initial conditions. The boundary conditions model the exchange of metabolites with the neighboring compartments and the reactions at the surface of the nano-beads carrying the multienzyme complexes. Efficient and accurate approaches for numerical simulation of the mathematical model and for optimal design of the microreactor are developed. As a proof-of-concept scenario, a synthetic pathway for the conversion of sucrose to glucose-6-phosphate (G6P) was chosen. In this context, the mathematical model is employed to compute the spatio-temporal distributions of the metabolite concentrations, as well as application relevant quantities like the outflow rate of G6P. These computations are performed for different scenarios, where the number of beads as well as their loading capacity are varied. The computed metabolite distributions show spatial patterns, which differ for different experimental arrangements. Furthermore, the total output of G6P increases for scenarios where microcompartimentation of enzymes occurs. These results show that spatially resolved models are needed in the description of the conversion processes. Finally, the enzyme stoichiometry on the nano-beads is determined, which maximizes the production of glucose-6-phosphate.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 29%
Student > Ph. D. Student 4 19%
Student > Bachelor 2 10%
Student > Master 2 10%
Professor 1 5%
Other 1 5%
Unknown 5 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 24%
Chemical Engineering 2 10%
Agricultural and Biological Sciences 2 10%
Chemistry 2 10%
Computer Science 1 5%
Other 3 14%
Unknown 6 29%
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 26 February 2016.
All research outputs
#17,787,961
of 22,849,304 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,896
of 6,577 outputs
Outputs of similar age
#275,544
of 403,162 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#26
of 45 outputs
Altmetric has tracked 22,849,304 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,577 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 48th percentile – i.e., 48% 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 403,162 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.