Hi I'm Dr. Andrew Currin. I work at the University of Manchester in the Center for Synthetic Biology. And I work in the builds team and looking at directed evolution and engineering of different enzymes and pathways for synthetic biology. And my short talk is on engineering and controlling pathways in synthetic biology. In this video we will look at controlling and engineering pathways in synthetic biology. And just so that we are clear where this fits into the overall synthetic biology scheme of design, build and test. This sits very much in the build area of pathway and compartment assembly, as you can see highlighted in the middle of the diagram there. So this will be covered in more detail elsewhere in the course. But just to put this video in context, it's important to know that in nature, many organisms produce secondary metabolites that are useful to us, things like drugs, flavors, etcetera. And what we want to do is to be able to produce these metabolites ourselves in different host organisms. So that we can make them in sufficient quantity for use in things like medicines and food. So we've already explained the concept that we can design the pathways that we want to make. And then build them for production in any host organism we require. This section explores the issues of inserting this pathway into a new host, and the means by which we can optimize this system to make production of our target molecule as efficient as possible. And this optimization is a crucial part of the overall process. Because the enzymes that are selected for the pathway often originate from different organisms themselves. And the way in which they will work together in the new pathway is unknown. As is the way that the host cell will react to this new pathway. For instance, the metabolites produced may be toxic. Drawn here is a simplified diagram of a pathway that we may wish to express in a chassis, under the control of a promoter and terminator sequence. This is very much simplified for the purpose of this short talk. And if you read further you will know that extra regulatory elements like ribosome binding sites are also important. As I said earlier, these are often heterologous enzymes from a variety of organisms, and evolution has optimized these parts in their respective natural host. However, this doesn't mean that each of these enzymes will work perfectly when exposed to a new pathway and host. Therefore, the initial design of any pathway isn't likely to be optimal. Even if a pathway can successfully produce our compound of interest, the system is likely to require substantial optimization to improve its yield. And this yield is often referred to as milligrams or grams per liter of culture. So by means of an example, a paper from Jake Aisling's lab assembled the genes identified in green into a pathway and expressed them in yeast. And through optimization, they were able to produce 25 grams per liter, which is a high yield of the compound artemisinic acid and a precursor to Artemisinin, which is a drug used to treat malaria. So it's important to understand that there are several levels of complexity that occur when expressing pathways within a chassis. The pathway itself might not be optimal. And when expressed in the context of a host cell its own metabolic pathways, there may be problems with pathway fluxes, toxicity, etc. So this section focuses on experimental ways to optimize these pathways, aside from the modeling that can be done at the outset. So experimentally, optimization can be done through a variety of methods. Including engineering of pathway expression levels, controlling when the pathways are expressed, which is temporal expression, and controlling where they are synthesized and localized within the cell, which is spatial expression. So, firstly, altering gene expression allows for transcriptional and translational control of all parts of the pathway. So there are a variety of strategies you can adopt. Here we outline one example, which is altering the order of genes in which they are encoded in the pathway. The order of genes has a large effect on the overall product yield. At the start, we don't know which combination will give the best yield. So we often shuffle these sequences into different orders creating what we call a library. And then test these different combinations to find which is the best version and gives you the best yield. So an example of this from publications is from Chris Voigt's lab, where they altered the sequence of a pathway generating libraries that were then screened for their abilities to fix nitrogen. Here the top hit, number 1, was found to have a higher activity in growth, which is the OD 600 compared to the other top hits from the screen. So next we discuss temporal expression of a pathway. So if you constitutively express all the genes of a pathway simultaneously in a host cell, this can often not lead to high product yields. This might be because of the high energy demands it takes for protein expression. And this can conflict with a cell's need for their own pathways and growth. And some intermediates can also be toxic and build up within the cell. And all these things impede the cell growth and survival. Therefore changing the timing (or temporal control) of expression for different parts of a pathway can be used to control metabolic flux, and direct cellular resources towards producing the required enzyme at the right time. This can be done in a variety of different ways, as shown here. For example, allosteric control, so control using things like riboswitches and metabolite sensors, can allow for very precise control of when a protein is expressed, and the use of feedback loops can produce self-regulating circuits, providing a just in time expression control mechanism. And on a larger scale, whole cell populations can be regulated to produce a synchronized expression pathway. So our third strategy for controlling pathways is spatial expression, which is controlling exactly where parts of a pathway are expressed. The pathways expressed, when they are expressed in the cell cytoplasm are not necessarily an efficient means for high pathway production. So you may have sub optimal yields. Therefore concentration of a pathway's enzymes to a local environment, and therefore its intermediates, can increase a product titre. For example, toxic products that may impede the host cell can be sequestered away into a separate compartment. And this improves both production of the pathway and also the survival of the host cell. And some strategies that you can adopt are physically linking enzymes within a scaffold, localizing pathways in a cell. For instance, using bacterial microcompartments or peroxisomes, and creating microbial communities. And here, we show a microbial consortia where adjacent cultures are separated by a semipermeable membrane, through which key metabolites can pass through but not the cells. So a good working example of localizing proteins to a compartment has been done by Professor Warren. They use bacterial microcompartments, or BMCs, and they can successfully target different proteins and pathways into these. And a good visual example shown here is where they can target GFP and mCherry, which are different green and red fluorescent proteins, directly into these BMCs. So these are localized within a small compartment of the cell. So just to summarize, efficient production of a new pathway in a new host cell is often not optimal from the outset of the experiment. Therefore we employ considerable optimization to improve the product yield. And this can include engineering the pathway expression levels, which is constitutive expression. Controlling when the parts of the pathway are expressed, temporal control. And controlling where they are synthesised and localised within the cell, spatial control. And through precise control of the way pathways are expressed we can create biological systems capable of producing useful chemicals at good yield, making it a viable process for industry.
