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      Development of an autonomous and bifunctional quorum-sensing circuit for metabolic flux control in engineered Escherichia coli

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          Abstract

          Metabolic engineering seeks to reprogram microbial cells to efficiently and sustainably produce value-added compounds. Since chemical production can be at odds with the cell’s natural objectives, strategies have been developed to balance conflicting goals. For example, dynamic regulation modulates gene expression to favor biomass and metabolite accumulation at low cell densities before diverting key metabolic fluxes toward product formation. To trigger changes in gene expression in a pathway-independent manner without the need for exogenous inducers, researchers have coupled gene expression to quorum-sensing (QS) circuits, which regulate transcription based on cell density. While effective, studies thus far have been limited to one control point. More challenging pathways may require layered dynamic regulation strategies, motivating the development of a generalizable tool for regulating multiple sets of genes. We have developed a QS-based regulation tool that combines components of the lux and esa QS systems to simultaneously and dynamically up- and down-regulate expression of 2 sets of genes. Characterization of the circuit revealed that varying the expression level of 2 QS components leads to predictable changes in switching dynamics and that using components from 2 QS systems allows for independent tuning capability. We applied the regulation tool to successfully address challenges in both the naringenin and salicylic acid synthesis pathways. Through these case studies, we confirmed the benefit of having multiple control points, predictable tuning capabilities, and independently tunable regulation modules.

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          Most cited references22

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          Engineering dynamic pathway regulation using stress-response promoters.

          Heterologous pathways used in metabolic engineering may produce intermediates toxic to the cell. Dynamic control of pathway enzymes could prevent the accumulation of these metabolites, but such a strategy requires sensors, which are largely unknown, that can detect and respond to the metabolite. Here we applied whole-genome transcript arrays to identify promoters that respond to the accumulation of toxic intermediates, and then used these promoters to control accumulation of the intermediate and improve the final titers of a desired product. We apply this approach to regulate farnesyl pyrophosphate (FPP) production in the isoprenoid biosynthetic pathway in Escherichia coli. This strategy improved production of amorphadiene, the final product, by twofold over that from inducible or constitutive promoters, eliminated the need for expensive inducers, reduced acetate accumulation and improved growth. We extended this approach to another toxic intermediate to demonstrate the broad utility of identifying novel sensor-regulator systems for dynamic regulation.
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            Improving lycopene production in Escherichia coli by engineering metabolic control.

            Metabolic engineering has achieved encouraging success in producing foreign metabolites in a variety of hosts. However, common strategies for engineering metabolic pathways focus on amplifying the desired enzymes and deregulating cellular controls. As a result, uncontrolled or deregulated metabolic pathways lead to metabolic imbalance and suboptimal productivity. Here we have demonstrated the second stage of metabolic engineering effort by designing and engineering a regulatory circuit to control gene expression in response to intracellular metabolic states. Specifically, we recruited and altered one of the global regulatory systems in Escherichia coli, the Ntr regulon, to control the engineered lycopene biosynthesis pathway. The artificially engineered regulon, stimulated by excess glycolytic flux through sensing of an intracellular metabolite, acetyl phosphate, controls the expression of two key enzymes in lycopene synthesis in response to flux dynamics. This intracellular control loop significantly enhanced lycopene production while reducing the negative impact caused by metabolic imbalance. Although we demonstrated this strategy for metabolite production, it can be extended into other fields where gene expression must be closely controlled by intracellular physiology, such as gene therapy.
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              Metabolic engineering of flavonoids in plants and microorganisms.

              Over 9,000 flavonoid compounds have been found in various plants, comprising one of the largest families of natural products. Flavonoids are an essential factor in plant interactions with the environment, often serving as the first line of defense against UV irradiation and pathogen attacks. Flavonoids are also major nutritional compounds in foods and beverages, with demonstrated health benefits. Some flavonoids are potent antioxidants, and specific flavonoid compounds are beneficial in many physiological and pharmacological processes. Therefore, engineering of flavonoid biosynthesis in plants or in microorganisms has significant scientific and economical importance. Construction of biosynthetic pathways in heterologous systems offers promising results for large-scale flavonoid production by fermentation or bioconversion. Genomics and metabolomics now offer unprecedented tools for detailed understanding of the engineered transgenic organism and for developing novel technologies to further increase flavonoid production yields. We summarize some of the recent metabolic engineering strategies in plants and microorganisms, with a focus on applications of metabolic flux analysis. We are confident that these engineering approaches will lead to successful industrial flavonoid production in the near future.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                December 03 2019
                : 201911144
                Article
                10.1073/pnas.1911144116
                6926038
                31796590
                b846559b-ab03-418f-a46d-4018e65c3003
                © 2019

                Free to read

                https://www.pnas.org/site/aboutpnas/licenses.xhtml

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