2020
DOI: 10.1021/acs.iecr.9b05847
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Linking Engineered Gene Circuit Kinetic Modeling to Cellulose Biosynthesis Prediction in Escherichia coli: Toward Bioprocessing of Microbial Cell Factories

Abstract: Microbial cell factories synthesize value-added products; their bioprocessing with the aid of synthetic and system biology represents a green and sustainable alternative to the traditional chemical industry. Currently, bioprocess performance prediction of microbial cell factories is limited. Herein, we present a rational modeling approach linking the designed engineered gene circuit to bioprocess kinetics, whereby the engineered gene circuit model informs the formulation of product biosynthesis and is coupled … Show more

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Cited by 4 publications
(6 citation statements)
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References 60 publications
(130 reference statements)
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“…In addition, the cellulose production was increased by heterologous expression of bcsA and B genes from Gluconacetobacter xylinus in E. coli Nissle 1917 without affecting its crystallization index (Sajadi et al, 2019 ). Recently, engineered gene circuit kinetic modeling was designed and applied in cellulose biosynthesis prediction in E. coli , providing important data support for the development of cell factories for bacterial cellulose synthesis (Buldum et al, 2020 ). Based on the cellulose-producing E. coli 1094 strain as a model, the structure–function relationships between core and accessory Bcs subunits were analyzed, which showed that regulatory Bcs components contribute to secretion by affecting both the initial assembly and subsequent stability of the system and provide additional inputs for function regulation by the activating second messenger c-di-GMP (Krasteva et al, 2017 ).…”
Section: Natural Bacterial Cellulose Produced By Microorganismsmentioning
confidence: 99%
“…In addition, the cellulose production was increased by heterologous expression of bcsA and B genes from Gluconacetobacter xylinus in E. coli Nissle 1917 without affecting its crystallization index (Sajadi et al, 2019 ). Recently, engineered gene circuit kinetic modeling was designed and applied in cellulose biosynthesis prediction in E. coli , providing important data support for the development of cell factories for bacterial cellulose synthesis (Buldum et al, 2020 ). Based on the cellulose-producing E. coli 1094 strain as a model, the structure–function relationships between core and accessory Bcs subunits were analyzed, which showed that regulatory Bcs components contribute to secretion by affecting both the initial assembly and subsequent stability of the system and provide additional inputs for function regulation by the activating second messenger c-di-GMP (Krasteva et al, 2017 ).…”
Section: Natural Bacterial Cellulose Produced By Microorganismsmentioning
confidence: 99%
“…Specifically, if the translation efficiencies of Cmcax, CcpAx, BcsC, BcsD, and cellulose synthase were modified, the cellulose biosynthesis would be significantly affected. Furthermore, an increase in plasmid instability would affect glucose degradation and biomass growth patterns and, subsequently, cellulose biosynthesis because of its coupling to microbial growth [77].…”
Section: Synthetic Circuit Modelingmentioning
confidence: 99%
“…One of the enzymes of the metabolic pathway is considered the most important for substrate degradation and another for biomass growth and product formation [130]. Hence, the gene regulatory network model can be connected to the microbial growth kinetics model, where instead of having the substrate as the limiting factor, the limiting factor will be the gene responsible for the growth, biodegradation and product formation, respectively.…”
Section: Proposed Conceptmentioning
confidence: 99%
“…The genetic circuit was designed and optimized to produce cellulose. The framework could predict cellulose production through the hybrid gene regulatory network-microbial growth kinetic model [130]. This framework can, therefore, be applied to different natural or engineered biosystems to predict bioprocess kinetics through the targeted gene regulatory network, thus enhancing bioprocess scaling-up.…”
Section: Proposed Conceptmentioning
confidence: 99%