Literature DB >> 23656232

Genetic circuit performance under conditions relevant for industrial bioreactors.

Felix Moser1, Nicolette J Broers, Sybe Hartmans, Alvin Tamsir, Richard Kerkman, Johannes A Roubos, Roel Bovenberg, Christopher A Voigt.   

Abstract

Synthetic genetic programs promise to enable novel applications in industrial processes. For such applications, the genetic circuits that compose programs will require fidelity in varying and complex environments. In this work, we report the performance of two synthetic circuits in Escherichia coli under industrially relevant conditions, including the selection of media, strain, and growth rate. We test and compare two transcriptional circuits: an AND and a NOR gate. In E. coli DH10B, the AND gate is inactive in minimal media; activity can be rescued by supplementing the media and transferring the gate into the industrial strain E. coli DS68637 where normal function is observed in minimal media. In contrast, the NOR gate is robust to media composition and functions similarly in both strains. The AND gate is evaluated at three stages of early scale-up: 100 mL shake flask experiments, a 1 mL MTP microreactor, and a 10 L bioreactor. A reference plasmid that constitutively produces a GFP reporter is used to make comparisons of circuit performance across conditions. The AND gate function is quantitatively different at each scale. The output deteriorates late in fermentation after the shift from exponential to constant feed rates, which induces rapid resource depletion and changes in growth rate. In addition, one of the output states of the AND gate failed in the bioreactor, effectively making it only responsive to a single input. Finally, cells carrying the AND gate show considerably less accumulation of biomass. Overall, these results highlight challenges and suggest modified strategies for developing and characterizing genetic circuits that function reliably during fermentation.

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Year:  2012        PMID: 23656232      PMCID: PMC3904225          DOI: 10.1021/sb3000832

Source DB:  PubMed          Journal:  ACS Synth Biol        ISSN: 2161-5063            Impact factor:   5.110


  50 in total

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4.  Model-driven engineering of RNA devices to quantitatively program gene expression.

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  33 in total

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3.  Functional optimization of gene clusters by combinatorial design and assembly.

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5.  Engineering RGB color vision into Escherichia coli.

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6.  Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER.

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Review 9.  Synthetic biology to access and expand nature's chemical diversity.

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Review 10.  Digital and analog gene circuits for biotechnology.

Authors:  Nathaniel Roquet; Timothy K Lu
Journal:  Biotechnol J       Date:  2014-02-20       Impact factor: 4.677

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