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The rapid prototyping and optimization of plasmid-based recombinant gene expression is one of the key steps in the development of bioengineered bacterial systems. Often, multiple genes or gene modules need to be coexpressed, and for this purpose compatible, inducible plasmid systems have been developed. However, inducible expression systems are not favored in industrial processes, due to their prohibitive cost, and consequently the conversion to constitutive expression systems is often desired. Here we present a set of constitutive-expression plasmids for this purpose, which were benchmarked using fluorescent reporter genes. To further facilitate the conversion between inducible and constitutive expression systems, we developed SelProm, a design tool that serves as a parts repository of plasmid expression strength and predicts portability rules between constitutive and inducible plasmids through model comparison and machine learning. The SelProm tool is freely available at http://selprom.synbiochem.co.uk .

The field of synthetic biology aims to make the design of biological systems predictable, shrinking the huge design space to practical numbers for testing. When designing microbial cell factories, most optimization efforts have focused on enzyme and strain selection/engineering, pathway regulation, and process development. In silico tools for the predictive design of bacterial ribosome binding sites (RBSs) and RBS libraries now allow translational tuning of biochemical pathways; however, methods for predicting optimal RBS combinations in multigene pathways are desirable. Here we present the implementation of machine learning algorithms to model the RBS sequence-phenotype relationship from representative subsets of large combinatorial RBS libraries allowing the accurate prediction of optimal high-producers. Applied to a recombinant monoterpenoid production pathway in Escherichia coli, our approach was able to boost production titers by over 60% when screening under 3% of a library. To facilitate library screening, a multiwell plate fermentation procedure was developed, allowing increased screening throughput with sufficient resolution to discriminate between high and low producers. High producers from one library did not translate during scale-up, but the reduced screening requirements allowed rapid rescreening at the larger scale. This methodology is potentially compatible with any biochemical pathway and provides a powerful tool toward predictive design of bacterial production chassis.

The microbial production of commodity, fine, and specialty chemicals is a driving force in biotechnology. An essential requirement is to introduce biosynthetic pathways to the target compound(s) into chassis organisms. First suitable enzymes must be selected and characterized, and then genetic pathways must be designed and assembled into suitable expression vectors. The design of these pathways is crucial for balancing the pathway for efficient in vivo activity. This can be achieved through optimization of the pathway regulation by altering transcription and translation rates. The possible permutations of a multigene pathway create a vast design space which is intractable to explore using traditional time-consuming and laborious pathway assembly methods. The advent of multifragment DNA assembly technologies has enabled simultaneous, multiplexed pathway construction allowing an increased capability to sample the design space. Furthermore, the implementation of laboratory automation allows error-reduced, high-throughput (HTP) construction of pathways. In this chapter, we present a workflow that combines automated in silico design of DNA parts followed by pathway assembly using the ligase cycling reaction on robotics platforms, to allow multiplexed assembly of plasmid-borne gene pathways with high efficiency. Details and considerations in designing DNA parts for expression bacterial chassis are discussed followed by laboratory protocols for HTP pathway assembly and screening using robotics platforms. This workflow is employed in the SYNBIOCHEM Synthetic Biology Research Center, providing the capability to assemble over 96 plasmids simultaneously, with over 40% of clones from each assembly harboring the correctly assembled plasmids. This workflow is easy to modify for use in other laboratories and will help to accelerate synthetic biology projects with diverse applications., (© 2018 Elsevier Inc. All rights reserved.)

Ligand-dependent control of gene expression is essential for gene functional analysis, target validation, protein production, and metabolic engineering. However, the expression tools currently available are difficult to transfer between species and exhibit limited mechanistic diversity. Here we demonstrate how the modular architecture of purine riboswitches can be exploited to develop orthogonal and chimeric switches that are transferable across diverse bacterial species, modulating either transcription or translation, to provide tunable activation or repression of target gene expression, in response to synthetic non-natural effector molecules. Our novel riboswitch-ligand pairings are shown to regulate physiologically important genes required for bacterial motility in Escherichia coli and cell morphology in Bacillus subtilis. These findings are relevant for future gene function studies and antimicrobial target validation, while providing new modular and orthogonal regulatory components for deployment in synthetic biology regimes.