Multi-scale modelling, simulation, control and optimisation for sustainable SCP production

Securing access to healthy and affordable food for the fast-growing global population is one of the largest challenges of the future. Addressing this challenge requires innovative solutions that can sustainably increase food production while minimizing environmental impact. One such solution is the utilization of protein from bacteria (SCPs) produced by bacteria like Methyloccus Capsulatus. These SCPs, that can be derived from cow farts, present a promising alternative to traditional protein sources, which are often resource-intensive and environmentally damaging. By leveraging the digestion in Methyloccus Capsulatus, we can convert methane gases into SCPs, contributing to a circular economy and promoting food security.

In this project, we will study metabolic cell networks, growth models, and machine learning. These models will be designed to accurately simulate the process of SCP production, which is a complex biological process involving the conversion of simple substrates into proteins. However, a significant challenge lies in the integration of mathematical models with data from biological experiments. Mechanistic models, which are based on known biochemical reactions, the highways within the cell, provide a detailed understanding of can be computationally intensive and difficult to parameterize. On the other hand, the biological data provides a comprehensive snapshot of the bacteria but can be noisy and complex.

The outcome of this project is a multi-scale mechanistic model of the metabolism in Methyloccus Capsulatus within a simulated chemical tank, enabling relevant conclusions to be drawn for industrial-scale operations from laboratory bench data. Our research has the potential to enhance sustainable protein production, contribute to global food security, and reduce greenhouse gas emissions.