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English: Synthetic biology tools are used to establish combinatorial optimization methods. The generated library is profiled using barcoding tools and biosensors allow to screen top producers within the library (gray area). Nature is a vital source of identified nutrients and pharmaceuticals. Metabolic engineering applies synthetic biology tools to produce compounds of the characterized biosynthetic pathway in a desired host (blue area). The production of certain compounds can be optimized using combinatorial optimization strategies. The data obtained from combinatorial library and its pre-characterized modules are computationally integrated to establish mathematical models to support the early design steps for chosen host on the basis of genome-scale metabolic modelling. The computational data suggest which synthetic pathways are the most promising in a given target organism and which host pathway genes need to be upregulated or be silenced based on knowledge of how different cellular subsystems work together. The best producers in combinatorial libraries can provide detailed information to feed into models that aim to uncover principles of how synthetic circuits behave in host systems. Blue arrows, regulators. Orange squares, CDSs. Brown “T”, terminators.[1]
Date
Source https://doi.org/10.1038/s41467-020-16175-y
Author Gita Naseri & Mattheos A. G. Koffas

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Computational design and evaluation of DNA circuits to achieve optimal performance

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15 May 2020

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current22:02, 17 May 2020Thumbnail for version as of 22:02, 17 May 2020512 × 484 (471 KB)Rob HurtUploaded a work by Gita Naseri & Mattheos A. G. Koffas from https://doi.org/10.1038/s41467-020-16175-y with UploadWizard

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