Biofuel metabolic engineering with biosensors

Morgan, Stacy-Anne; Nadler, Dana C.; Yokoo, Rayka; Savage, David F.

doi:10.1016/j.cbpa.2016.09.020

Cited by 23 publications

(12 citation statements)

References 72 publications

(88 reference statements)

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“…Biosensors/Biocontrollers Biosensors, such as RNA aptamers or proteins which bind to small molecules and elicit a transcriptional or allosteric response, are key synthetic biology tools and have been comprehensively reviewed [75][76][77]. As noted in earlier sections, applications of biosensors range from reporting metabolic states or heterogeneity in cellular response to being coupled to regulation, enabling a dynamic response to stresses.…”

Section: Growth-decoupled Productionmentioning

confidence: 99%

Engineering Robust Production Microbes for Large-Scale Cultivation

Wehrs

Tanjore

Eng

et al. 2019

Trends in Microbiology

180

118

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Systems biology and synthetic biology are increasingly used to examine and modulate complex biological systems. As such, many issues arising during scaling-up microbial production processes can be addressed using these approaches. We review differences between laboratory-scale cultures and larger-scale processes to provide a perspective on those strain characteristics that are especially important during scaling. Systems biology has been used to examine a range of microbial systems for their response in bioreactors to fluctuations in nutrients, dissolved gases, and other stresses. Synthetic biology has been used both to assess and modulate strain response, and to engineer strains to improve production. We discuss these approaches and tools in the context of their use in engineering robust microbes for applications in largescale production. Challenges during Industrial Scale-up Highlights Strain engineering in the laboratory often does not consider process requirements in larger-scale bioreactors. Systems and synthetic biology can be applied to design microbial strains that allow reliable and robust production on a large scale. Commercial microbial platforms should be selected and developed based on their relevance to final process goals.

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Section: Growth-decoupled Productionmentioning

confidence: 99%

Engineering Robust Production Microbes for Large-Scale Cultivation

Wehrs

Tanjore

Eng

et al. 2019

Trends in Microbiology

180

118

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“…The past decade has witnessed a blooming and rapid development of synthetic biology [ 4 , 5 ]. New technologies in this field provide effective ways to both understand and deal with these challenges [ 6 – 8 ], such as the improvement of the production of some pharmaceutically important molecules and biofuels [ 9 – 12 ] and the development of functional genetic circuits [ 13 – 16 ]. Recently, researchers have developed a riboswitch-based method and generated a series of pH-sensing genetic devices for resisting acidic conditions [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Intelligent microbial cell factory with genetic pH shooting (GPS) for cell self-responsive base/acid regulation

Gao

Peng

et al. 2020

Microb Cell Fact

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Background In industrial fermentation, pH fluctuation resulted from microbial metabolism influences the strain performance and the final production. The common way to control pH is adding acid or alkali after probe detection, which is not a fine-tuned method and often leads to increased costs and complex downstream processing. Here, we constructed an intelligent pH-sensing and controlling genetic circuits called “Genetic pH Shooting (GPS)” to realize microbial self-regulation of pH. Results In order to achieve the self-regulation of pH, GPS circuits consisting of pH-sensing promoters and acid-/alkali-producing genes were designed and constructed. Designed pH-sensing promoters in the GPS can respond to high or low pHs and generate acidic or alkaline substances, achieving endogenously self-responsive pH adjustments. Base shooting circuit (BSC) and acid shooting circuit (ASC) were constructed and enabled better cell growth under alkaline or acidic conditions, respectively. Furthermore, the genetic circuits including GPS, BSC and ASC were applied to lycopene production with a higher yield without an artificial pH regulation compared with the control under pH values ranging from 5.0 to 9.0. In scale-up fermentations, the lycopene titer in the engineered strain harboring GPS was increased by 137.3% and ammonia usage decreased by 35.6%. Conclusions The pH self-regulation achieved through the GPS circuits is helpful to construct intelligent microbial cell factories and reduce the production costs, which would be much useful in industrial applications.

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“…Several strategies can be taken to build such sensors. The ideal sensors consist of a regulator that directly binds to a known signal, such as the metabolite, and then strongly regulates the activity of a promoter (Tang & Cirino, 2011;Zhang et al, 2012;Rogers et al, 2015;Albanesi & de Mendoza, 2016;Libis et al, 2016;Morgan et al, 2016;Rogers & Church, 2016). When a sensor for a specific metabolite is unavailable, native promoters that respond to a given stimulus have also been co-opted as sensors (Dahl et al, 2013;Yuan & Ching, 2015).…”

Section: Introductionmentioning

confidence: 99%

Dynamic control of endogenous metabolism with combinatorial logic circuits

Moser

Borujeni

Ghodasara

et al. 2018

Molecular Systems Biology

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Controlling gene expression during a bioprocess enables real‐time metabolic control, coordinated cellular responses, and staging order‐of‐operations. Achieving this with small molecule inducers is impractical at scale and dynamic circuits are difficult to design. Here, we show that the same set of sensors can be integrated by different combinatorial logic circuits to vary when genes are turned on and off during growth. Three Escherichia coli sensors that respond to the consumption of feedstock (glucose), dissolved oxygen, and by‐product accumulation (acetate) are constructed and optimized. By integrating these sensors, logic circuits implement temporal control over an 18‐h period. The circuit outputs are used to regulate endogenous enzymes at the transcriptional and post‐translational level using CRISPRi and targeted proteolysis, respectively. As a demonstration, two circuits are designed to control acetate production by matching their dynamics to when endogenous genes are expressed (pta or poxB) and respond by turning off the corresponding gene. This work demonstrates how simple circuits can be implemented to enable customizable dynamic gene regulation.

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Biofuel metabolic engineering with biosensors

Cited by 23 publications

References 72 publications

Engineering Robust Production Microbes for Large-Scale Cultivation

Engineering Robust Production Microbes for Large-Scale Cultivation

Intelligent microbial cell factory with genetic pH shooting (GPS) for cell self-responsive base/acid regulation

Dynamic control of endogenous metabolism with combinatorial logic circuits

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