Hello, my name is James Lawrence from the Department of Biochemical Engineering at University College London. I'm going to be talking to you through this video on microbial fermentation processes and bioreactor design. We'll start by considering the different cells that we use in industrial biotechnology. We have a variety of cells, that vary in different degrees of complexity available to us from relatively simply prokaryotes, like E.coli on the left here up to complex mammalian cells like Chinese hamster ovary cells, also known as CHO cells, on the right. The simpler cells are easier to grow in large volumes, but are limited in terms of the size and complexity of products that they can produce. So it will be used to produce smaller molecules such as ethanol. More complex cells like CHO cells are more difficult to grow and also grow at a slower rate, that can be used to produce large and more complicated modules like monoclonal antibodies. We can use cells to produce a variety of molecules of varying size, complexity and value. From ethanol, for beverages or fuels, to enzymes, industrial metabolites, or therapeutic proteins. Sometimes the cells themselves might also be the product. The simpler molecules like ethanol can be produced in large amounts by individual cells, while larger and more complicated molecules such as enzymes or microbial metabolites can only be produced in smaller amounts by each cell. This is one reason why the cost of manufacture will increase with the complexity of product. We will look at this in a bit more detail in the last video of this series on process economics. The number of cells we grow per unit volume is also limited, therefore, more complex products require larger fermentation values per unit of products produced. The cells required to produce more complex products also increase in complexity themselves, becoming more difficult, and therefore more expensive to culture. Any cell culture we perform in industrial biotechnology will perform a similar pattern or will follow, sorry, a similar pattern as they grow. We can plot this as a growth curve. A plot of the log value of the number of cells against time. From the plot we can identify six distinct stages to the growth of cells in any culture. The first phase is the lag phase, which occurs as the cells are adapting themselves to the culture environment. In this phase, most of the cells' energy is devoted to preparing their metabolism to best suit the environment around them and so little growth occurs. Once the cells have adapted, they will begin to grow and will enter the acceleration phase, identified by rapid increase in the cell growth rate. The cell growth will become exponential, eventually, as each cell divides to produce two daughter cells, which in turn, will also divide to produce two more daughter cells, and so on. The cell population will, therefore, continue doubling in this way until a lack of available nutrients or oxygen or carbon dioxide begins to limit the rate of cell growth, causing the culture to enter the deceleration phase. The total growth rate will continue to decrease until it equilibrates with the rate of cell death with the total population being held constant at a level that can be sustained by the nutrients available in the culture. Finally when the available nutrients have been completely exhausted, the rate of cell death will overtake the rate of cell growth and the population number will decline. In industrial biotechnology, we are most interested in the exponential phase of cell growth, as we want to achieve the maximum number of cells in the shortest possible time. And the exponential phase is where the growth rate is highest. In the exponential phase, the growth rate is first order, i.e., the change in the cell number with time, dx by dt, is proportional to the cell population given by X. Written another way, we can say that dX by dt is equal to mu X, where mu represents the specific growth rate, which is the growth rate per cell. The value of mu will depend upon the nutrient availability, the temperature and pH, and the oxygen or carbon dioxide concentration. Where nutrients and gases are in excess, and the conditions are optimal for cell growth, the value of mu will be at its maximum. This is the fastest possible rate at which the cells can grow and it's the value that is inherent to each cell strain. Cells that grow on more than one type of nutrient will have several maximum specific growth rates, one for each nutrient. So, for example, yeast, which can grow on either glucose or dextrose will have a maximum specific growth rate for both glucose and dextrose, and the two will differ. The relationship between mu and the nutrient, which is also known as the substrate concentration can be characterized by the Monod equation. You might recognize a similar equation when you cover enzyme kinetics in the next video. The Monod equation is essentially the same as the Michaelis-Menten equation for enzyme reaction rates, and, essentially, the same process is occurring, but it's at a cellular rather than an enzymatic level. The Monod equation states that the specific growth rate will increase with substrate concentration up to a maximum specific growth rate which is inherent to the cells. Beyond this maximum specific growth rate, no further increase in growth rate will occur. We determine the mu max and Ks by experimentation, measuring specific growth rates of our variance substrate concentrations. By determining mu max, we can find out the maximum specific growth rate for all of our cells and the minimum concentration of substrate required to achieve this, thereby allowing us to optimize our cell culture and grow our cells at the fastest possible rate with the minimum possible nutrients. When growing cells on an industrial scale we can't start with a small 5mL cell stock and go straight into a production fermenter that is over 100L, as the lag phase would be too long, and we would waste time and energy waiting for the cells to enter exponential phase. Instead, it is crucial to employ a so-called train of fermenters of various scales. Gradually increasing the volume from 10 to 200mL, and then again to 10 to 100L. and then again to over 100L, Gradually increasing the volume and using the contents of each fermenter to inoculate the next larger fermenter. On smaller scales, we generally have less control in monitoring of the culture due to the technical complexity of the equipment required to do so. And developing this equipment to work at the smaller scale is the focus of a lot of research in biochemical engineering and industrial biotechnology, as being able to investigate conditions at a small scale would be useful, very useful, in fact, in order to save time and money in the development and optimization of biotech processes. There are three main types of reactor available to us to culture cells. Each of which is designed to ensure that all of the cells experience the same physical and chemical environment with good distribution in nutrients and gases. The stirred tank reactor uses an impeller or series of impellers driven by a motor, to achieve this by mixing the culture fluid. Airlift reactors use air passed into the center of the reactor to displace the fluid above, causing the fluid to mix and circulate around the reactor. Photobioreactors are a bit of a special case, as they are used for the culture of photosynthesising organisms such as algae. And so we are more concerned with the distribution of light rather than the distribution of nutrient and gases. These reactors typically take the form of long, clear tubes, and the culture fluid is driven through them by pumps. We can operate our reactors in one of three modes, Batch, Fed-Batch, or Continuous. In Batch mode we add a specific amount of nutrients to the reactor and let the cells grow, stopping the culture when the cell number reaches a maximum in the stationary phase. Fed-Batch cultures work in a similar way But we continue feeding in additional nutrients to allow cell growth to continue until we run out of space in the reactor. Continuous live cultures start off quite similarly to Fed-Batch modes but culture fluid is removed continuously, allowing further distribution of nutrients without hitting the space constraint in the reactor. In this mode the cell population and nutrient concentration will reach steady state, and so there's little change in the concentration of either, overall. We can do a material balance around each of these fermentation modes as we discussed in the previous video. And we'll have a look at the possible fermentation, enzyme material balances for Fed-Batch and Continuous mode of fermentation next. So if we think about the material balance around a Fed-Batch fermentation, we'll have an input of nutrients which leads to an accumulation of cells, and an accumulation of product within the fermenter as the cells grow. The accumulation is not going to be as limited as it would be in Batch mode, since, in Fed-Batch mode, we have further inputs of the nutrients, allowing further cell growth. However, the number of inputs is going to be limited by the reactor volume. As the culture continues, and the cell population grows, the rate of nutrient feeding will have to increase in order to maintain the cell growth rate. And this will continue until we hit the maximum volume for the reactor, at which point we can't feed anymore nutrients because we have run out of space. Continuous mode is a bit of a special case. So the culture is initially operated in a similar way to a Batch or a Fed-Batch mode fermentation to get the cell population into the exponential phase of growth. From this point on once the growth rate is controlled by the continuous feeding of further nutrients, and this is balanced by the continuous removal of culture fluids to keep the reactor at a constant volume, rather the contents of the reactor at a constant volume. As the cells are constantly removed from the reactor there won't be any accumulation of cells or of product once the culture reaches a steady state. And instead we will have a constant output of both the level of which is going to be determined by the nutrient feeding rate, and therefore the rate of overflow from the reactor.
