Publication | Closed Access
ePathBrick: A Synthetic Biology Platform for Engineering Metabolic Pathways in <i>E. coli</i>
255
Citations
51
References
2012
Year
EngineeringMolecular BiologySynthetic CircuitMetabolic NetworksBiological ComputingEngineering Metabolic PathwaysBiochemical EngineeringSynthetic Biology PlatformMetabolic EngineeringMetabolic Pathway AnalysisChemical BiotechnologyCell FactoriesMolecular BiotechnologyBiochemistryBiomolecular EngineeringMetabolic PathwaysNatural SciencesBiotechnologySynthetic BiologyPathway Engineering
Cell factories for biofuel and pharmaceutical production have driven the development of modular synthetic biology tools for pathway engineering. The study presents BioBrick‑compatible vectors designed for metabolic engineering. The ePathBrick vectors feature four strategically placed restriction sites that enable fine‑tuning of gene expression and modular assembly of pathway components, allowing combinatorial generation of pathway variants in three configurations. The authors assembled a seven‑gene (~9 kb) pathway on a single vector and demonstrate that ePathBrick facilitates rapid design and optimization of metabolic pathways in *E.
Harnessing cell factories for producing biofuel and pharmaceutical molecules has stimulated efforts to develop novel synthetic biology tools customized for modular pathway engineering and optimization. Here we report the development of a set of vectors compatible with BioBrick standards and its application in metabolic engineering. The engineered ePathBrick vectors comprise four compatible restriction enzyme sites allocated on strategic positions so that different regulatory control signals can be reused and manipulation of expression cassette can be streamlined. Specifically, these vectors allow for fine-tuning gene expression by integrating multiple transcriptional activation or repression signals into the operator region. At the same time, ePathBrick vectors support the modular assembly of pathway components and combinatorial generation of pathway diversities with three distinct configurations. We also demonstrated the functionality of a seven-gene pathway (~9 Kb) assembled on one single ePathBrick vector. The ePathBrick vectors presented here provide a versatile platform for rapid design and optimization of metabolic pathways in E. coli.
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