- Cell line development
- Bioprocess design
- Cell culture media
Current strategies for media and bioprocess optimization tend to rely primarily on empirical testing of changes in cellular proliferation and behavior in response to growth conditions. By combining these approaches with statistical methods for interpolating between the tested conditions, it is often possible to make reasonably accurate predictions of non-tested conditions that are most likely to be effective, even when components interact. This is the basis for strategies such as Design of Experiments (DOE). However, strategies relying on trial and error require a large number of experiments in order to achieve an effective formulation. Theoretically, it should be possible to predict the effects of culture conditions on cellular metabolism via a thorough understanding of the pathways involved, but our currently limited understanding of these pathways makes this challenging.
Techniques such as metabolic flux analysis should be used to build a more comprehensive understanding of the metabolic steps occurring in cell types relevant to cultivated meat and their relative rates under relevant conditions. Such data should then be used as a guide for optimization of culture media, culture conditions, and recycling strategies, as well as to guide strategies for engineering of cell lines. Quicker and cheaper methods such as metabolic profiling could also provide useful qualitative data to either inform culture strategies or to identify the compounds most worth focusing on for more in-depth analyses. Especially for more in-depth and expensive analyses, it would be better if these projects could be organized in such a way as to benefit multiple companies within the industry rather than performing the research in-house, since this would constitute a substantial duplication of effort and would not be an efficient use of the investor dollars available to the industry. Open access academic research is a good model in this situation. Another option would be for several companies to form a consortium in which each contributes a portion of the research funding and all benefit from the knowledge gained. Investors with multiple cultivated meat companies in their portfolio could play a role by encouraging this type of collaboration.
Understanding metabolic pathways in cell types relevant to cultivated meat and their interconnections will make optimization of media cheaper, faster, and more effective. For optimization of simple traits such as biomass production and maintenance of the desired cell state, existing techniques such as DOE are adequate, but improvements in efficiency are possible. Perhaps more importantly, metabolic profiles or flux models would give insights into the formation of flavor compounds or precursors, or other small molecules that impact the organoleptic properties of the final product. In addition, metabolic models could inform efforts at metabolic engineering, although the effectiveness of such strategies should be weighed carefully against potential regulatory or consumer acceptance concerns. It is conceivable that companies might undertake these efforts on their own, but for a single company the benefits might not outweigh the cost and time required. Either open access models or consortia between several companies would lead to more overall benefit for a given amount of research spending.
Metalytics offers metabolic flux analysis as a service and has indicated their interest in working with cultivated meat companies and researchers. | MetaFishNet is a metabolic model (not including fluxes) based on genomic data from several fish species. | Kim et al. (2010) reconstructed a chicken metabolic network, and Lohr et al. (2014) performed MFA in a chicken cell line. | Seo & Lewin (2009) and Kim et al. (2016) have reconstructed bovine metabolic networks
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