SYNBIOCHEM-a SynBio foundry for the biosynthesis and sustainable production of fine and speciality chemicals

Getting the Right Clones in an Automated Manner: An Alternative to Sophisticated Colony-Picking Robotics

In recent years, the design-build-test-learn (DBTL) cycle has become a key concept in strain engineering. Modern biofoundries enable automated DBTL cycling using robotic devices. However, both highly automated facilities and semi-automated facilities encounter bottlenecks in clone selection and screening. While fully automated biofoundries can take advantage of expensive commercially available colony pickers, semi-automated facilities have to fall back on affordable alternatives. Therefore, our clone selection method is particularly well-suited for academic settings, requiring only the basic infrastructure of a biofoundry. The automated liquid clone selection (ALCS) method represents a straightforward approach for clone selection. Similar to sophisticated colony-picking robots, the ALCS approach aims to achieve high selectivity. Investigating the time analogue of five generations, the model-based set-up reached a selectivity of 98 ± 0.2% for correctly transformed cells. Moreover, the method is robust to variations in cell numbers at the start of ALCS. Beside Escherichia coli, promising chassis organisms, such as Pseudomonas putida and Corynebacterium glutamicum, were successfully applied. In all cases, ALCS enables the immediate use of the selected strains in follow-up applications. In essence, our ALCS approach provides a 'low-tech' method to be implemented in biofoundry settings without requiring additional devices.

Consolidated Bioprocessing: Synthetic Biology Routes to Fuels and Fine Chemicals

The long road from emerging biotechnologies to commercial “green” biosynthetic routes for chemical production relies in part on efficient microbial use of sustainable and renewable waste biomass feedstocks. One solution is to apply the consolidated bioprocessing approach, whereby microorganisms convert lignocellulose waste into advanced fuels and other chemicals. As lignocellulose is a highly complex network of polymers, enzymatic degradation or “saccharification” requires a range of cellulolytic enzymes acting synergistically to release the abundant sugars contained within. Complications arise from the need for extracellular localisation of cellulolytic enzymes, whether they be free or cell-associated. This review highlights the current progress in the consolidated bioprocessing approach, whereby microbial chassis are engineered to grow on lignocellulose as sole carbon sources whilst generating commercially useful chemicals. Future perspectives in the emerging biofoundry approach with bacterial hosts are discussed, where solutions to existing bottlenecks could potentially be overcome though the application of high throughput and iterative Design-Build-Test-Learn methodologies. These rapid automated pathway building infrastructures could be adapted for addressing the challenges of increasing cellulolytic capabilities of microorganisms to commercially viable levels.

Enzyme Discovery: Enzyme Selection and Pathway Design

In this protocol, we describe in silico design methods that can assist in the engineering of production pathways that are based on enzymatic transformations. The described protocols are the basis for automated processes to be integrated into an iterative Design-Build-Test-Learn cycle in synthetic biology for chemical production. Selecting the right enzyme sequence for a desired biocatalytic activity from the extensive catalogue of sequences available in databases is challenging and can dramatically influence the success of bioproducing chemical compounds. A method for enzyme selection is presented that helps identifying candidate enzyme sequences through a scoring approach that considers not only sequence homology but also reaction similarity. Selecting a viable biochemical pathway for compound production requires screening large sets of reactions in a process involving combinatorial complexity. A method for pathway design using retrosynthesis is presented. The protocol allows the discovery of alternative chemical pathways leading to the final product by using reaction rules of selectable degree of specificity. The protocols can be reversed through clustering discovery and product identification processes. The integration of these protocols into a general pipeline provides a toolbox for enhanced automated synthetic biology design and metabolic engineering.

Evolutionary algorithms and synthetic biology for directed evolution: commentary on "on the mapping of genotype to phenotype in evolutionary algorithms" by Peter A. Whigham, Grant Dick, and James Maclaurin

I rehearse two issues around the commentary of Whigham and colleagues. (1) There really are many more reasons than those given as to why natural evolution cannot reasonably find or select the 'optimal' individual. (2) A series of experimental molecular biology programmes, known generically as directed evolution, can use operators and selection schemes that natural evolution cannot. When developed further using the methods of synthetic biology, there are no operators or schemes for in silico evolution that cannot be applied precisely to directed evolution. The issues raised apply only to natural evolution but not to directed evolution.

SYNBIOCHEM Synthetic Biology Research Centre, Manchester - A UK foundry for fine and speciality chemicals production

The UK Synthetic Biology Research Centre, SYNBIOCHEM, hosted by the Manchester Institute of Biotechnology at the University of Manchester is delivering innovative technology platforms to facilitate the predictable engineering of microbial bio-factories for fine and speciality chemicals production. We provide an overview of our foundry activities that are being applied to grand challenge projects to deliver innovation in bio-based chemicals production for industrial biotechnology.

Mapping the patent landscape of synthetic biology for fine chemical production pathways

A goal of synthetic biology bio‐foundries is to innovate through an iterative design/build/test/learn pipeline. In assessing the value of new chemical production routes, the intellectual property (IP) novelty of the pathway is important. Exploratory studies can be carried using knowledge of the patent/IP landscape for synthetic biology and metabolic engineering. In this paper, we perform an assessment of pathways as potential targets for chemical production across the full catalogue of reachable chemicals in the extended metabolic space of chassis organisms, as computed by the retrosynthesis‐based algorithm RetroPath. Our database for reactions processed by sequences in heterologous pathways was screened against the PatSeq database, a comprehensive collection of more than 150M sequences present in patent grants and applications. We also examine related patent families using Derwent Innovations. This large‐scale computational study provides useful insights into the IP landscape of synthetic biology for fine and specialty chemicals production.