Multi-objective Bayesian algorithm automatically discovers low-cost high-growth serum-free media for cellular agriculture application.

In this work, we applied a multi-information source modeling technique to solve a multi-objective Bayesian optimization problem involving the simultaneous minimization of cost and maximization of growth for serum-free C2C12 cells using a hyper-volume improvement acquisition function. In sequential batches of custom media experiments designed using our Bayesian criteria, collected using multiple assays targeting different cellular growth dynamics, the algorithm learned to identify the trade-off relationship between long-term growth and cost. We were able to identify several media with >100% more growth of C2C12 cells than the control, as well as a medium with 23% more growth at only 62.5% of the cost of the control. These algorithmically generated media also maintained growth far past the study period, indicating the modeling approach approximates the cell growth well from an extremely limited data set.

Techno-economic modeling and assessment of cultivated meat: Impact of production bioreactor scale.

Increases in global meat demands cannot be sustainably met with current methods of livestock farming, which has a substantial impact on greenhouse gas emissions, land use, water consumption, and farm animal welfare. Cultivated meat is a rapidly advancing technology that produces meat products by proliferating and differentiating animal stem cells in large bioreactors, avoiding conventional live-animal farming. While many companies are working in this area, there is a lack of existing infrastructure and experience at commercial scale, resulting in many technical bottlenecks such as scale-up of cell culture and media availability and costs. In this study, we evaluate theoretical cultivated beef production facilities with the goal of envisioning an industry with multiple facilities to produce in total 100,000,000 kg of cultured beef per year or ~0.14% of the annual global beef production. Using the computer-aided process design software, SuperPro Designer®, facilities are modeled to create a comprehensive analysis to highlight improvements that can lower the cost of such a production system and allow cultivated meat products to be competitive. Three facility scenarios are presented with different sized production reactors; ~42,000 L stirred tank bioreactor (STR) with a base case cost of goods sold (COGS) of $35/kg, ~211,000 L STR with a COGS of $25/kg, and ~262,000 L airlift reactor (ALR) with a COGS of $17/kg. This study outlines how advances in scaled up bioreactors, alternative bioreactor designs, and decreased media costs are necessary for commercialization of cultured meat products.

Considerations for the development of cost-effective cell culture media for cultivated meat production.

Innovation in cultivated meat development has been rapidly accelerating in recent years because it holds the potential to help attenuate issues facing production of dietary protein for a growing world population. There are technical obstacles still hindering large-scale commercialization of cultivated meat, of which many are related to the media that are used to culture the muscle, fat, and connective tissue cells. While animal cell culture media has been used and refined for roughly a century, it has not been specifically designed with the requirements of cultivated meat in mind. Perhaps the most common industrial use of animal cell culture is currently the production of therapeutic monoclonal antibodies, which sell for orders of magnitude more than meat. Successful production of cultivated meat requires media that is food grade with minimal cost, can regulate large-scale cell proliferation and differentiation, has acceptable sensory qualities, and is animal ingredient-free. Much insight into strategies for achieving media formulations with these qualities can be obtained from knowledge of conventional culture media applications and from the metabolic pathways involved in myogenesis and protein synthesis. In addition, application of principles used to optimize media for large-scale microbial fermentation processes producing lower value commodity chemicals and food ingredients can also be instructive. As such, the present review shall provide an overview of the current understanding of cell culture media as it relates to cultivated meat.

Identification of critical batch operating parameters in fed-batch recombinant E. coli fermentations using decision tree analysis.

To develop a useful fermentation process model, it is first necessary to identify which batch operating parameters are critical in determining the process outcome. To identify critical processing inputs in large databases, we have explored the use of Decision Tree Analysis with the decision metrics of Gain (i.e., Shannon Entropy changes), Gain Ratio, and a multiple hypergeometric distribution. The usefulness of this approach lies in its ability to treat "categorical" variables, which are typical of archived fermentation databases, as well as "continuous" variables. In this work, we demonstrate the use of Decision Tree Analysis for the problem of optimizing recombinant green fluorescent protein production in E. coli. A database of 85 fermentations was generated to examine the effect of 15 process input parameters on final biomass yield, maximum recombinant protein concentration, and productivity. The use of Decision Tree Analysis led to a considerable reduction in the fermentation database through the identification of the significant as well as insignificant inputs. However, different decision metrics selected different inputs and different numbers of inputs to classify the data for each output.