The microbial production of fine chemicals provides a promising biosustainable manufacturing solution that has led to the successful production of a growing catalog of natural products and high-value chemicals. However, development at industrial levels has been hindered by the large resource investments required. Here we present an integrated Design–Build-Test–Learn (DBTL) pipeline for the discovery and optimization of biosynthetic pathways, which is designed to be compound agnostic and automated throughout. We initially applied the pipeline for the production of the flavonoid (2S)-pinocembrin in Escherichia coli, to demonstrate rapid iterative DBTL cycling with automation at every stage. In this case, application of two DBTL cycles successfully established a production pathway improved by 500-fold, with competitive titers up to 88 mg L−1. The further application of the pipeline to optimize an alkaloids pathway demonstrates how it could facilitate the rapid optimization of microbial strains for production of any chemical compound of interest.

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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.

S‐adenosyl‐l‐methionine (SAM)‐dependent methyltransferases (MTs) catalyse the methylation of a vast array of small metabolites and biomacromolecules. Recently, rare carboxymethylation pathways have been discovered, including carboxymethyltransferase enzymes that utilise a carboxy‐SAM (cxSAM) cofactor generated from SAM by a cxSAM synthase (CmoA). We show how MT enzymes can utilise cxSAM to catalyse carboxymethylation of tetrahydroisoquinoline (THIQ) and catechol substrates. Site‐directed mutagenesis was used to create orthogonal MTs possessing improved catalytic activity and selectivity for cxSAM, with subsequent coupling to CmoA resulting in more efficient and selective carboxymethylation. An enzymatic approach was also developed to generate a previously undescribed co‐factor, carboxy‐S‐adenosyl‐l‐ethionine (cxSAE), thereby enabling the stereoselective transfer of a chiral 1‐carboxyethyl group to the substrate.

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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 .

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Glucose is a key intermediate in cellulose photoreforming for H 2 production. This work presents a mechanistic investigation of glucose photoreforming over TiO 2 and Pt/m-TiO 2 catalysts. Analysis of the intermediates formed in the process confirmed the α-scission mechanism of glucose oxidation forming arabinose (C n-1 sugar) and formic acid in the initial oxidation step. The selectivity to sugar products and formic acid differed over Pt/ TiO 2 and TiO 2 , with Pt/TiO 2 showing the lower selectivity to formic acid due to enhanced adsorption/conversion of formic acid over Pt/TiO 2 . In situ ATR-IR spectroscopy of glucose photoreforming showed the presence of molecular formic acid and formate on the surface of both catalysts at low glucose conversions, suggesting that formic acid oxidation could dominate surface reactions in glucose photoreforming. Further in situ ATR-IR of formic acid photoreforming showed Pt-TiO 2 interfacial sites to be key for formic acid oxidation as TiO 2 was unable to convert adsorbed formic acid/formate. Isotopic studies of the photoreforming of formic acid in D 2 O (with different concentrations) showed that the source of the protons (to form H 2 at Pt sites) was determined by the relative surface coverage of adsorbed water and formic acid.