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Application of combinatorial optimization strategies in synthetic biology.

ABSTRACT: In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

SUBMITTER: Naseri G

PROVIDER: S-EPMC7229011 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Application of combinatorial optimization strategies in synthetic biology.

Naseri Gita G Koffas Mattheos A G MAG

Nature communications 20200515 1

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level ...[more]

PMID: 32415065

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Project description:Protein engineering by combinatorial site-directed mutagenesis evaluates a portion of the sequence space near a target protein, seeking variants with improved properties (e.g., stability, activity, immunogenicity). In order to improve the hit-rate of beneficial variants in such mutagenesis libraries, we develop methods to select optimal positions and corresponding sets of the mutations that will be used, in all combinations, in constructing a library for experimental evaluation. Our approach, OCoM (Optimization of Combinatorial Mutagenesis), encompasses both degenerate oligonucleotides and specified point mutations, and can be directed accordingly by requirements of experimental cost and library size. It evaluates the quality of the resulting library by one- and two-body sequence potentials, averaged over the variants. To ensure that it is not simply recapitulating extant sequences, it balances the quality of a library with an explicit evaluation of the novelty of its members. We show that, despite dealing with a combinatorial set of variants, in our approach the resulting library optimization problem is actually isomorphic to single-variant optimization. By the same token, this means that the two-body sequence potential results in an NP-hard optimization problem. We present an efficient dynamic programming algorithm for the one-body case and a practically-efficient integer programming approach for the general two-body case. We demonstrate the effectiveness of our approach in designing libraries for three different case study proteins targeted by previous combinatorial libraries--a green fluorescent protein, a cytochrome P450, and a beta lactamase. We found that OCoM worked quite efficiently in practice, requiring only 1 hour even for the massive design problem of selecting 18 mutations to generate 10? variants of a 443-residue P450. We demonstrate the general ability of OCoM in enabling the protein engineer to explore and evaluate trade-offs between quality and novelty as well as library construction technique, and identify optimal libraries for experimental evaluation.

Project description:BackgroundMicrobes are extensively engineered to produce compounds of biotechnological or pharmaceutical interest. However, functional integration of synthetic pathways into the respective host cell metabolism and optimization of heterologous gene expression for achieving high product titers is still a challenging task. In this manuscript, we describe the optimization of a tetracistronic operon for the microbial production of the plant-derived phenylpropanoid p-coumaryl alcohol in Escherichia coli.ResultsBasis for the construction of a p-coumaryl alcohol producing strain was the development of Operon-PLICing as method for the rapid combinatorial assembly of synthetic operons. This method is based on the chemical cleavage reaction of phosphorothioate bonds in an iodine/ethanol solution to generate complementary, single-stranded overhangs and subsequent hybridization of multiple DNA-fragments. Furthermore, during the assembly of these DNA-fragments, Operon-PLICing offers the opportunity for balancing gene expression of all pathway genes on the level of translation for maximizing product titers by varying the spacing between the Shine-Dalgarno sequence and START codon. With Operon-PLICing, 81 different clones, each one carrying a different p-coumaryl alcohol operon, were individually constructed and screened for p-coumaryl alcohol formation within a few days. The absolute product titer of the best five variants ranged from 48 to 52 mg/L p-coumaryl alcohol without any further optimization of growth and production conditions.ConclusionsOperon-PLICing is sequence-independent and thus does not require any specific recognition or target sequences for enzymatic activities since all hybridization sites can be arbitrarily selected. In fact, after PCR-amplification, no endonucleases or ligases, frequently used in other methods, are needed. The modularity, simplicity and robustness of Operon-PLICing would be perfectly suited for an automation of cloning in the microtiter plate format.

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Application of combinatorial optimization strategies in synthetic biology.

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Application of combinatorial optimization strategies in synthetic biology.

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