A powerful directed-evolution tool for exploitation of chloroplast engineering biology

用于叶绿体工程生物学开发的强大定向进化工具

• 批准号: BB/Y008162/1
• 负责人: Saul Purton
• 金额: $ 136.3万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FY008162%2F1
• 关键词: powerful; directed; evolution; tool; exploitation

Photosynthetic organisms including plants and green algae offer significant potential for sustainable biotechnology in which sunlight is used to power the biosynthesis of industrial products using simple inputs of carbon dioxide, inorganic salts and water. Overlay on this the ability to genetically engineer the plant or algae using modern synthetic biology techniques, and these organisms offer the potential for making a myriad of novel bio-products for a wide range of commercial sectors including pharmaceuticals, nutraceuticals, cosmetics, textiles and food ingredients. Such applied synthetic biology is termed 'engineering biology', and requires reprogramming the cells of the organism with a suite of new genes to make bio-products. An attractive site for housing these genes within the cell is the chloroplast. This sub-cellular compartment contains a minimal chromosome (the 'plastome') harbouring only a hundred-or-so genes, and a simple expression system to decode these genes into enzymes and proteins. Re-design of the plastome using engineering design principles (i.e. standardisation, abstraction and predictable output for a given input) to house new genes is therefore relatively straightforward, and this technology has been developed for several plants and for the single cell alga, Chlamydomonas reinhardtii. However, an initial design is never optimal since numerous parameters need to be tuned to achieve the desired expression of the genes and the optimum design of the proteins encoded by those genes. Such optimisation can involve either multiple iterations where the knowledge gained from the first design informs changes incorporated in the next version of the design, and so-on. Such an approach can be lengthy and costly. Alternatively, millions of different design variants can be tested in parallel, but this requires the generation of millions of test organisms which can be impractical. In this project, we will build on the synthetic biology technology we have developed for the C. reinhardtii chloroplast and create a new and powerful optimisation tool. We will develop a system that allows us to introduce multiple random base changes (i.e. mutations) within the plastome in a controlled manner, and in a focused way so that we don't introduce unwanted mutations into the much larger nuclear genome. Our approach will involve creating a starting strain containing a highly error-prone version of the chloroplast DNA polymerase, which is the enzyme that replicated chloroplast genes. The activity of this polymerase will be tightly regulated, but when induced using a simple vitamin-regulated switch the design landscape of any gene(s) engineered into the plastome can be explored by simply growing the cells to produce millions of daughter cells, each carrying different DNA changes within the plastome. Selection or high-throughput screening of these cells would allow the rapid identification of those variants showing improvements in a desired outcome (higher level of product, more active or stable enzyme, etc.). As a first demonstration of the power of this approach, we will search for more efficient variants of key enzymes within the Calvin-Benson-Bassham cycle. This cyclical biochemical pathway is fundamental to the conversion of CO2 to organic carbon by photosynthesis, and it is known that improvements in the activity of several key enzymes (most notably the enzyme 'Rubisco') would markedly improve the growth of plants and algae. We will use our plastome mutator technology to search in vivo for such improved enzyme variants. This would not only provide new insights into how to improve photosynthetic performance in crop plants, but also produce faster growing C. reinhardtii strains for applications in green industrial biotechnology.

包括植物和绿藻在内的光合生物为可持续生物技术提供了巨大的潜力，其中利用简单的二氧化碳、无机盐和水的输入，利用阳光为工业产品的生物合成提供动力。在此基础上，利用现代合成生物学技术对植物或藻类进行基因工程改造的能力，这些生物体提供了为制药、营养保健品、化妆品、纺织品和食品等广泛商业领域制造无数新型生物产品的潜力原料。这种应用合成生物学被称为“工程生物学”，需要用一套新基因对生物体细胞进行重新编程来制造生物产品。细胞内容纳这些基因的一个有吸引力的位点是叶绿体。这个亚细胞区室包含一条最小的染色体（“质体”），仅包含一百个左右的基因，以及一个将这些基因解码为酶和蛋白质的简单表达系统。因此，使用工程设计原理（即给定输入的标准化、抽象化和可预测输出）重新设计质体来容纳新基因相对简单，并且该技术已针对多种植物和单细胞藻类莱茵衣藻开发。 。然而，初始设计永远不是最佳的，因为需要调整许多参数才能实现所需的基因表达以及这些基因编码的蛋白质的最佳设计。这种优化可以涉及多次迭代，其中从第一个设计获得的知识通知了设计的下一个版本中合并的更改，等等。这种方法可能是漫长且昂贵的。或者，可以并行测试数百万种不同的设计变体，但这需要生成数百万种测试生物体，这可能是不切实际的。在这个项目中，我们将基于我们为莱茵衣藻叶绿体开发的合成生物学技术，创建一种新的强大的优化工具。我们将开发一个系统，允许我们以受控的方式和集中的方式在质体中引入多个随机碱基变化（即突变），这样我们就不会在更大的核基因组中引入不需要的突变。我们的方法将涉及创建一个包含高度容易出错的叶绿体 DNA 聚合酶（复制叶绿体基因的酶）的起始菌株。这种聚合酶的活性将受到严格调节，但是当使用简单的维生素调节开关进行诱导时，可以通过简单地培养细胞以产生数百万个子细胞来探索工程化到质体中的任何基因的设计景观，每个子细胞都携带质体内不同的 DNA 变化。这些细胞的选择或高通量筛选将允许快速鉴定那些显示出期望结果改进的变体（更高水平的产物、更活性或更稳定的酶等）。作为这种方法威力的首次展示，我们将在卡尔文-本森-巴沙姆循环中寻找更有效的关键酶变体。这种循环生化途径是通过光合作用将二氧化碳转化为有机碳的基础，众所周知，提高几种关键酶（最著名的是酶“Rubisco”）的活性将显着改善植物和藻类的生长。我们将使用我们的质体突变技术在体内寻找这种改进的酶变体。这不仅可以为如何提高农作物的光合作用性能提供新的见解，而且还可以产生生长更快的莱茵衣藻菌株，用于绿色工业生物技术的应用。