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

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.

Chloroplasts contain a minimal genetic system that lends itself well to engineering biology and applications within the green biotechnology sector. In principle, the minimal genetic system of the chloroplast can be reprogrammed using either 'bottom-up' or 'top-down' approaches to create designed versions of its tiny genome (i.e. the plastome), thereby creating light-driven cell factories that synthesise novel bio-products within the chloroplast using CO2 and inorganic salts as simple inputs. However, an engineering biology design is rarely optimally achieved in a single step. Rather it may require multiple iterative cycles of 'Design-Build-Test-Learn' (DBTL) where designs are modelled in silico, tested in vivo and the output data used to guide a design improvement. Alternatively, a 'one-cycle' forward-genetics approach can be taken in which very large DNA libraries of design variants are tested in parallel through the generation of huge numbers of transformant lines, and these are screened for the best output. Both approaches have their drawbacks and limitations when applied to non-model systems, and a more effective approach would be to use just a single transformant line to explore in vivo the myriad of design possibilities. But such a mutagenesis approach needs to be focussed on a subset of genes and not the whole genome. In this project, we aim to develop a system based on the inducible expression of a highly error-prone DNA polymerase within the chloroplast of the alga Chlamydomonas reinhardtii. The power of this approach will be demonstrated by using it in combination with high-throughput screening/ selection methods to discover more efficient variants of Rubisco and other rate-limiting enzymes of the Calvin cycle. Such technology would have wide applications in chloroplast engineering biology: from optimising production of recombinant products to discovering novel approaches to improving carbon-fixation rates, both in this algal platform and in crop plants.