Genetically-encoded biosensors for monitoring cellular stress in bioprocessing

Polizzi, Karen M.; Kontoravdi, Cleo

doi:10.1016/j.copbio.2014.07.011

Cited by 44 publications

(45 citation statements)

References 42 publications

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“…In the field of bioprocess regulation, external feedback using appropriate biosensors and inducers has already been proposed as a means to improve productivity, robustness and batch-to-batch reproducibility14. Light would be an ideal inducer for gene-expression control of these systems, as it can provide targeted, non-toxic and bidirectional regulation, which more-expensive chemical inducers cannot achieve.…”

Section: Discussionmentioning

confidence: 99%

“…Automatic feedback control of cell populations has been implemented111213 with promising results using microfluidics. However, while microfluidic approaches are well-suited for high-throughput analysis of single-cell behaviour as well as biomedical diagnostics, promising biotechnological applications of optogenetics, such as control of metabolic activity in microbial production strains1415, require the use of large-volume liquid cell cultures.…”

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confidence: 99%

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Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth

et al. 2016

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Dynamic control of gene expression can have far-reaching implications for biotechnological applications and biological discovery. Thanks to the advantages of light, optogenetics has emerged as an ideal technology for this task. Current state-of-the-art methods for optical expression control fail to combine precision with repeatability and cannot withstand changing operating culture conditions. Here, we present a novel fully automatic experimental platform for the robust and precise long-term optogenetic regulation of protein production in liquid Escherichia coli cultures. Using a computer-controlled light-responsive two-component system, we accurately track prescribed dynamic green fluorescent protein expression profiles through the application of feedback control, and show that the system adapts to global perturbations such as nutrient and temperature changes. We demonstrate the efficacy and potential utility of our approach by placing a key metabolic enzyme under optogenetic control, thus enabling dynamic regulation of the culture growth rate with potential applications in bacterial physiology studies and biotechnology.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth

et al. 2016

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“…These reporter outputs may also help coordinate complementary manipulations of the culture environment itself (mixing, nutrient addition, timing of harvest) to further improve production (Polizzi and Kontoravdi, 2015). Second, biosensors can be engineered to couple the sensing of a desirable product or intermediate metabolite with a fitness advantage for the cell by expressing a gene necessary for survival under selective conditions (Dietrich et al, 2013;Raman et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Applications and advances of metabolite biosensors for metabolic engineering

Liu

Evans

Zhang

2015

Metabolic Engineering

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138

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Quantification and regulation of pathway metabolites is crucial for optimization of microbial production bioprocesses. Genetically encoded biosensors provide the means to couple metabolite sensing to several outputs invaluable for metabolic engineering. These include semi-quantification of metabolite concentrations to screen or select strains with desirable metabolite characteristics, and construction of dynamic metabolite-regulated pathways to enhance production. Taking inspiration from naturally occurring systems, biosensor functions are based on highly diverse mechanisms including metabolite responsive transcription factors, two component systems, cellular stress responses, regulatory RNAs, and protein activities. We review recent developments in biosensors in each of these mechanistic classes, with considerations towards how these sensors are engineered, how new sensing mechanisms have led to improved function, and the advantages and disadvantages of each of these sensing mechanisms in relevant applications. We particularly highlight recent examples directly using biosensors to improve microbial production, and the great potential for biosensors to further inform metabolic engineering practices.

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“…Genetically-encoded biosensors, for instance are pieces of DNA that contain the instructions for a biosensor circuit [70]. They have the ability to monitor cellular stresses online and maintain control of cells in large bioreactors, resulting in a gain in productivity whilst ensuring robustness and reproducibility in the overall bioprocess [70].…”

Section: Bioprocessing and Controlmentioning

confidence: 99%