A combinatorial assembly strategy to optimise biosynthetic pathway performance in yeast - a synthetic biology

优化酵母生物合成途径性能的组合组装策略 - 合成生物学

• 批准号: 1790816
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1790816
• 关键词: combinatorial; assembly; strategy; optimise; biosynthetic

Microbial biosynthetic pathways are an important source of high value products, including industrial precursors, agrochemicals, drugs, food additives, biofuels and biopharmaceuticals, and can also be applied in situ for bioremediation, biofiltration, biomass production and other processes. However, a considerable amount of time and effort generally have to be invested in 'pathway development' in order to optimise productivity. Since the productivity of any given biosynthetic pathway is influenced by genetic factors, host physiology, metabolic dynamics and rate control characteristics, the optimization of biosynthetic pathways by traditional means can be a hit-and-miss process that wastes time and resources. Here, we focus on Saccharomyces cerevisiae, which is a GRAS (generally regarded as safe) organism with a proven biotechnological pedigree, but our strategy could equally be applied to other microbes. The strategy that we will follow in this project has only very recently become feasible by virtue of rapid progress in experimental and theoretical methods in the fields of synthetic and systems biology and also due to the rapidly decreasing cost of DNA synthesis. For example, we can now explore very large numbers of biosynthetic pathway variants in parallel utilizing computational design algorithms, robotics, DNA synthesis and rapid multi-component DNA assembly technologies. Now that these new opportunities are available to us, we can use them to bypass the traditional trial-and-error approach to pathway development. Demonstration of cost-effective production of the target molecule (EtOH) through construction and optimisation of the model (cellulose-degrading enzyme) pathway will represent a commercial opportunity in the biofuel field for Ingenza. In addition, more efficient feedstock conversion into valuable chemical(s) could result in mid- to long-term environmental benefits.

微生物生物合成途径是高价值产品的重要来源，包括工业前体、农用化学品、药物、食品添加剂、生物燃料和生物制药，并且还可以原位应用于生物修复、生物过滤、生物质生产和其他过程。然而，为了优化生产力，通常必须在“路径开发”上投入大量的时间和精力。由于任何给定生物合成途径的生产力都受到遗传因素、宿主生理学、代谢动力学和速率控制特征的影响，因此通过传统方法优化生物合成途径可能是一个时好时坏的过程，浪费时间和资源。在这里，我们专注于酿酒酵母，这是一种GRAS（通常被认为是安全的）生物，具有经过验证的生物技术谱系，但我们的策略同样可以应用于其他微生物。我们将在这个项目中遵循的策略只是最近才变得可行，这是由于合成和系统生物学领域的实验和理论方法的快速进展，也是由于DNA合成成本的迅速下降。例如，我们现在可以利用计算设计算法、机器人技术、DNA合成和快速多组分DNA组装技术并行探索大量生物合成途径变体。既然这些新的机会已经提供给我们，我们可以利用它们来绕过传统的试错法来开发途径。通过构建和优化模型（纤维素降解酶）途径，证明目标分子（EtOH）的成本效益生产将代表Ingenza在生物燃料领域的商业机会。此外，更有效地将原料转化为有价值的化学品可带来中长期环境效益。