Many commercial microbial fermentation processes utilize a fed-batch approach, where a main medium is inoculated with the microbe, and after a period of time is fed with additional nutrients over the course of the bioprocess. This is due to a number of factors. First, the amount of nutrients required to produce the amount of biomass and product generated during many bioprocesses is simply not feasible to add into a batch medium due to chemical solubility constraints. Second, many microbes are subject to overflow metabolism, whereby excess substrate in the medium results in production of overflow metabolites. This can divert flux away from the product, complicate downstream operations and, at worst, have toxic effects on the strain.
Each microbe’s physiology is different, and genetically distinct strains of a single species may have different growth rates, nutrient uptake rates and pathway fluxes. Moreover, environmental conditions in the fermentor, such as inoculum density, media composition and temperature setpoints may also impact growth and production kinetics. Thus, optimal feed rates in order to maximize pathway flux and minimize overflow metabolites change not only with different strains, but also with changing bioprocesses. As, during development, the bioprocess and the genetics of the strain are being optimized in parallel, the consummate feed rates for a strain or process are also changing. Therefore, in order to realize the full potential of each strain in evolving processes, it is imperative to have accompanying optimization of feed rates.
There are a number of different strategies that can be used to control the feed rates in a fed-batch bioprocess; the type adopted will depend on the available capabilities and specific microbe and process.
Each fed-batch fermentation usually begins with a batch medium, which contains the initial nutrients required for microbial growth. Once the carbon in the batch medium is depleted, the fermentation will shift to the fed-batch phase, where a carbon source and additional nutrients are provided via an external feed. This transition can be a timed change, where the feed is initiated at a predetermined time within the fermentation. However, this strategy will result in suboptimal feeding if the strain growth or metabolism differs from the strain used to design the timing of feed initiation. Transitions to the fed-batch portion of the fermentation can also be initiated using physiological signals from the microbe. There are several hallmarks of carbon depletion source that can be leveraged as physiological triggers to initiate feeding. These include an increase in dissolved oxygen, decrease in OUR or increase in pH. Programming feeds to initiate upon these quantifiable signals ensures feeding initiation is timed correctly for each strain.
Fixed feed regimes are those that are predefined in advance of the fermentation. Feeds can be simple, fixed at the same rate for the entirety of the fed-batch portion of the fermentation or with discrete steps up and down in rate over time. Feeds can also increase in a linear or exponential fashion, or incorporate various combinations of different rate architectures throughout the fermentation.
Manual feedback control allows for maintaining the concentration of a substrate within a predetermined range using offline measurements. Fermentation operators take samples at regular intervals, measure the concentration of a media component offline, and make adjustments to the feed rate to maintain the substrate broth concentration within the defined bounds accordingly.
Dynamic feed regimes, similar to feed triggers, leverage physiological signals by microbes in response to their environment. Microbes have been characterized to have measurable physiological responses to substrate in their environment. Signals that can be leveraged in these dynamic feed schemes include dissolved oxygen (%DO), oxygen uptake rates (OUR), pH, or respiratory quotient (RQ). Feeds can be pre-programmed to cycle on and off in response to these signals or adjust feed rates up and down to maintain a setpoint. Some commonly used organisms, such as Saccharomyces cerevisiae or Escherichia coli, have overflow metabolism profiles that are amenable to more complex feed probing strategies. Here, feed rates are probed down and/or up in order to assess for the likelihood of overflow metabolism and to adjust rates accordingly.
While some fermentations only use a single nutrient feed, many processes incorporate multiple different feeds into the process. This can be for a variety of reasons. The product of interest may incorporate various elements or precursors into the structure of the product that can be fed and controlled separately from the main carbon source. Alternatively, the carbon source can be mixed, or changed during the fermentation in order to provide maximal flux into the product pathway.
Feed strategies can significantly impact the performance of a microbe. Without an optimized feed strategy, microbes may not perform to their full potential and lead to potentially incorrect assessments of strain or process performance. This is further compounded by the fact that microbes are often being optimized at the same time as the process, which equates to multiple ways in which a fixed feed regime can quickly become obsolete. While dynamic feed schemes can alleviate many of these challenges, a strategy should be selected carefully based on the physiology of the organism, and in some cases, the product being produced.
Even with a dynamic feed scheme, there can be some challenges. As mentioned above, selecting a scheme well suited to the physiology of the microbe is important. In addition, when using quantifiable signals as a trigger, it is important to build in safety mechanisms to avoid false signals. For example, DO trends can be noisy at the beginning of a fermentation, and a feed could easily be triggered based on signal noise. Here, safety measures such as timed pauses on feed initiation can be built in, or incorporating the most reliable signal for the dynamic process. Moreover, development of dynamic feed strategies takes time as factors such as signal magnitude may need to be optimized empirically for each microbe and process. Building in time to develop a robust dynamic feed scheme may be challenging when competing with other activities and constrained bioreactor capacity.
The best practices around feed strategies can begin with an assessment of the microbe being used for the process and the best feeding strategy for that microbe. Developing a feed strategy with a knowledge of the physiology of the microbe can help ensure that optimal process performance is achieved with the selected strategy.
When developing a feeding strategy, it is also best practice to optimize setpoints empirically when developing a process. For example, if developing a pH stat, an understanding of the threshold required to trigger feeding rapidly after substrate exhaustion without false triggers due to noise can result in a finely tuned feed. If using a fixed feed regime, testing the impact of over and underfeeding on strain performance can aid in determining the suitability of the method.
Culture’s cloud bioreactors have a number of hardware and software features that enable precision control of fermentations.
Culture offers a variety of feed control schemes. These include standard pre-defined timed feed regimes with fixed, linear and exponential feed rates. Feeds can be programmed with automated feed triggers to initiate feeds upon completion of carbon in the main batch phase. Culture also offers a variety of dynamic feeds including pH-stat, DO-stat, and various pulse feed strategies. As each reactor is outfitted with continuous off-gas measurements, a number of dynamic methods based on these measurements are also available, including OUR-stat, CER-stat and RQ-stat. Methods can be developed on demand.
Each of Culture’s bioreactors has available up to 5 separate feeds. Each of these feeds is delivered via a peristaltic pump with individual scale feedback control. This results in precise weight based delivery of feeds so that the amount of feed delivered over the course of the fermentation is as intended. The capacity to deliver up to 5 feeds means that schemes with auxiliary feeds can be supported.
When developing a feed scheme, some factors may need to be optimized empirically. These include the magnitude of signals used to trigger feeds and trials of the impact of over and underfeeding. Culture’s capacity enables methods to be developed and fine-tuned with a number of different variables.