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

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，在这种生物技术中，利用阳光为工业产品的生物合成提供动力，只需输入二氧化碳、无机盐和水。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，这些生物为制药、保健品、化妆品、纺织品和食品配料等广泛的商业领域提供了制造无数新型生物产品的潜力。这种应用合成生物学被称为“工程生物学”，它需要用一套新基因对生物体的细胞进行重新编程，以制造生物产品。在细胞内安置这些基因的一个有吸引力的位置是叶绿体。这个亚细胞区室包含一个最小的染色体（“质体”），仅容纳100个左右的基因，以及一个简单的表达系统，将这些基因解码为酶和蛋白质。因此，利用工程设计原则（即标准化、抽象化和给定输入的可预测输出）重新设计质体以容纳新基因相对简单，这项技术已用于几种植物和单细胞藻类莱茵衣藻。然而，最初的设计从来都不是最佳的，因为需要调整许多参数来实现所需的基因表达和由这些基因编码的蛋白质的最佳设计。这种优化可以包括多次迭代，其中从第一次设计中获得的知识通知了下一个设计版本中包含的更改，等等。这种方法可能耗时且代价高昂。或者，可以同时测试数百万种不同的设计变体，但这需要产生数百万种测试生物体，这可能是不切实际的。在这个项目中，我们将建立在我们为莱茵哈特氏菌叶绿体开发的合成生物学技术的基础上，创造一个新的强大的优化工具。我们将开发一种系统，使我们能够以可控的方式在质体体内引入多个随机碱基变化（即突变），并且以一种集中的方式，这样我们就不会将不必要的突变引入更大的核基因组。我们的方法将包括创造一种起始菌株，它含有一种高度容易出错的叶绿体DNA聚合酶，这种酶可以复制叶绿体基因。这种聚合酶的活性将受到严格的调控，但当使用一种简单的维生素调节开关诱导时，通过简单地培养细胞来产生数百万个子细胞，每个子细胞在质体体内携带不同的DNA变化，就可以探索任何基因工程进入质体体的设计景观。这些细胞的选择或高通量筛选将允许快速识别那些变异，显示出期望结果的改进（更高水平的产品，更活跃或更稳定的酶等）。作为这种方法力量的第一次演示，我们将在卡尔文-本森-巴萨姆循环中寻找更有效的关键酶变体。这种循环的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，几种关键酶（最明显的是“Rubisco”酶）活性的改善将显著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。这不仅将为如何提高作物的光合性能提供新的见解，而且还将为绿色工业生物技术的应用提供生长更快的莱茵哈蒂梭菌菌株。

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.