Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids

Jones, J. Andrew; Vernacchio, Victoria R.; Sinkoe, Andrew; Collins, Shannon M.; Ibrahim, Mohammad H.A.; Lachance, Daniel M.; Hahn, Juergen; Koffas, Mattheos

doi:10.1016/j.ymben.2016.01.006

Cited by 223 publications

(169 citation statements)

References 36 publications

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“…The first example is E. coli-E. coli coculture for the production of flavan-3-ols. [168] The authors split the whole pathway into two parts: the upstream part covering the production of flavanones from p-coumaric acid or caffeic acid and the downstream part leading to the final product. Through elaborate optimization of the fermentation processes, they were able to improve the titer of afzelechin by 970-fold compared with the monoculture process.…”

Section: Coculture Strategiesmentioning

confidence: 99%

Metabolic Engineering of Microorganisms for the Production of Natural Compounds

Park

Yang

et al. 2017

Adv. Biosys.

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Natural products have been attracting much interest around the world for their diverse applications, especially in drug and food industries. Plants have been a major source of many different natural products. However, plants are affected by weather and environmental conditions and their successful extraction is rather limited. Chemical synthesis is inefficient due to the complexity of their chemical structures involving enantioselectivity and regioselectivity. For these reasons, an alternative means of overproducing valuable natural products using microorganisms has emerged. In recent years, various metabolic engineering strategies have been developed for the production of natural products by microorganisms. Here, the strategies taken to produce natural products are reviewed. For convenience, natural products are classified into four main categories: terpenoids, phenylpropanoids, polyketides, and alkaloids. For each product category, the strategies for establishing and rewiring the metabolic network for heterologous natural product biosynthesis, systems approaches undertaken to optimize production hosts, and the strategies for fermentation optimization are reviewed. Taken together, metabolic engineering has enabled microorganisms to serve as a prominent platform for natural compounds production. This article examines both the conventional and novel strategies of metabolic engineering, providing general strategies for complex natural compound production through the development of robust microbial‐cell factories.

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Section: Coculture Strategiesmentioning

confidence: 99%

Metabolic Engineering of Microorganisms for the Production of Natural Compounds

Park

Yang

et al. 2017

Adv. Biosys.

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“…However, there is increasing evidence that such processes could run more efficiently if a community of microbial species is used (Logan and Rabaey 2012;Jones et al 2016;Wen et al 2016). There are multiple reasons including an increased production efficiency of the system due to lessening of metabolic burden for individual cells.…”

Section: For a Community Of Microbesmentioning

confidence: 99%

“…The developed algorithms are currently being used for developing consortia of polyphenol-producing Gram-positive bacteria. This task was inspired by the work of Jones and colleagues, who were able to achieve an overall 970-fold improvement in titers for flavan-3-ols production from phenylpropanoic acids by using a co-culture of two E. coli strains with further optimization of cultivation conditions, as compared to previous studies that used monocoltures for this purpose (Jones et al 2016). …”

Section: For a Community Of Microbesmentioning

confidence: 99%

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

et al. 2017

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BACterial Hosts for production of Bioactive phenolics from bERRY fruits (BacHBerry) was a 3-year project funded by the Seventh Framework Programme (FP7) of the European Union that ran between November 2013 and October 2016. The overall aim of the project was to establish a sustainable and economically-feasible strategy for the production This article is written by the BacHBerry consortium (www. bachberry.eu) and represents the collective effort of all participating institutions. The authors are therefore listed in alphabetical order.Electronic supplementary material The online version of this article

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“…Optimal experimental design has been utilized for decades in a variety of settings in which it is of interest to maximize efficiency of resource use and obtain a significant amount of information from experiments with acceptable cost [8][9][10][11][12][13][14][15][16]. Recently, as biological modeling and systems biology have emerged as an important area in biomedical research, optimal experimental design applied to biological experimental systems has become more popular [17][18][19][20][21][22][23][24][25][26][27][28]; additionally, optimal experimental design has been recognized as a valuable tool in optimal control for several decades [29].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, as biological modeling and systems biology have emerged as an important area in biomedical research, optimal experimental design applied to biological experimental systems has become more popular [17][18][19][20][21][22][23][24][25][26][27][28]; additionally, optimal experimental design has been recognized as a valuable tool in optimal control for several decades [29]. For example, Jones et al [13] maximized production of an exogenous commodity chemical in metabolically engineered E. coli using an empirical modeling method similar to those used in [15,16] to maximize the efficacy of drug delivery. Weber [26] utilized optimal experimental design to maximize model prediction accuracy for a model of vesicle transport via the trans-Golgi network.…”

Section: Introductionmentioning

confidence: 99%

Optimal Experimental Design for Parameter Estimation of an IL-6 Signaling Model

Sinkoe

Hahn

2017

Processes

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IL-6 signaling plays an important role in inflammatory processes in the body. While a number of models for IL-6 signaling are available, the parameters associated with these models vary from case to case as they are non-trivial to determine. In this study, optimal experimental design is utilized to reduce the parameter uncertainty of an IL-6 signaling model consisting of ordinary differential equations, thereby increasing the accuracy of the estimated parameter values and, potentially, the model itself. The D-optimality criterion, operating on the Fisher information matrix and, separately, on a sensitivity matrix computed from the Morris method, was used as the objective function for the optimal experimental design problem. Optimal input functions for model parameter estimation were identified by solving the optimal experimental design problem, and the resulting input functions were shown to significantly decrease parameter uncertainty in simulated experiments. Interestingly, the determined optimal input functions took on the shape of PRBS signals even though there were no restrictions on their nature. Future work should corroborate these findings by applying the determined optimal experimental design on a real experiment.

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Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids

Cited by 223 publications

References 36 publications

Metabolic Engineering of Microorganisms for the Production of Natural Compounds

Metabolic Engineering of Microorganisms for the Production of Natural Compounds

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

Optimal Experimental Design for Parameter Estimation of an IL-6 Signaling Model

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