Title: "Exploiting the syntegron technology platform for assembly and optimisation of complex genetic ensembles"
Funder: Biotechnology and Biological Sciences Research Council

Abstract: Previously we developed an innovative, versatile technology for enzymatically assembling and dynamically rearranging DNA modules. This "Syntegron" platform enables rapid assembly of multiple standardized DNA modules into large assemblies such as metabolic pathways and to exchange individual parts of assemblies (e.g., regulatory elements) to allow variation and optimization. We propose to build on these core technologies to develop a comprehensive experimental and computational toolkit enabling the rapid generation of important biomolecules: Objective 1: Develop Syntegron "parts" enabling the discovery and production of diverse, valuable biomolecules. An important source for drug leads has been plant natural products but many of these drugs are produced in miniscule amounts in their native hosts, making the drugs expensive and environmentally taxing to harvest. Organic chemistry methodologies have been widely used to synthesize pharmaceuticals but many natural pharmaceutically-relevant scaffolds cannot be achieved by these methods. An alternative is the use of enzymes to enable the production of drug candidates from inexpensive, green starting materials. The goal of this research is to synthesize a variety of natural product variants e.g. terpenes using the Syntegron technology platform constructed in the first phase of funding, and to manufacture these natural product variants for drug discovery applications. We will 1) Take advantage of the recently described phenomena of plant metabolic gene clusters to identify genes encoding enzymes involved in plant secondary metabolite pathways via the development of novel bioinformatic and data mining tools. 2) Use the Syntegron platform to assemble the synthetic metabolic pathways for natural products e.g. the triterpenes and enzymes that will decorate them with functional groups to synthesize a variety of natural product variants. 3) Develop new Syntegron host strains for metabolic engineering 4) Engineer in vivo biosensors for natural products and their variants and use these sensors in high throughput screens allowing dynamic optimization of metabolic pathways. Objective 2: Develop analytical tools, methods, and conceptual insights enabling the optimisation of diverse multigenic functions using Syntegron technology. Cell-free technology is useful for decoupling intracellular biochemical transformations from confounding experimental factors including cellular toxicity and mass transfer limitations. This has proven useful for quantitatively characterizing fundamental synthetic biology "parts". The relationship between cell-free parts characterization and performance in vivo remains unclear, and remains a fundamentally important scientific question. We propose to extend cell-free approaches to the high-throughput characterization of multi-genic assemblies constructed using the Syntegron platform, and to compare them with performance in vivo. The development of the Syntegron platform into a true technology for the synthetic biology community requires the development of novel computational modelling frameworks and quantitative tools for analysing and performing Syntegron-based directed evolution. We will therefore 1) develop a quantitative computational modelling framework describing Syntegron-based diversification and selection. 2) Optimise Syntegron-based directed evolution using in silico simulations paired with experiments. The ultimate test of the combined experimental and computational Syntegron platform will be to perform, analyse, and ultimately guide Syntegron-based directed evolution of a model metabolic pathway. We will initially pair in silico simulation with computational optimization to explore the influence of tuneable experimental parameters on the predicted chances of (a) generating sufficient genetic diversity to sample many potentially functional syntegron configurations, and (b) successfully selecting for variants that exhibit optimised biosynthesis.


Research activity codes: 1.3 CHEMICAL AND PHYSICAL SCIENCES
Health categories: GENERIC HEALTH RELEVANCE