TRANSFORM ‘Waste-to-Microbial Protein’

2024 – 2026

This project will develop new tools and knowledge on optimized, scalable, and sustainable fermentation-derived protein based on low-cost, food-grade carbon sourced from waste.

Production platform: Fermentation

Technology sector: Bioprocess design, Cell culture media, Computational modeling, Feedstocks

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Project aims

This program aims to leverage advancements in computational and mathematical modeling to develop new tools and knowledge for optimized, scalable, and sustainable fermentation-derived protein production. The focus is on utilizing low-cost, food-grade alternative carbon sourced from lignocellulosic polysaccharides and retailer soft-drink waste. Through a combination of experiments and modeling research, the project aims to map out global food-grade sustainable carbon sources from crop residues and contribute new insights into the growth of selected microbial strains in response to varying carbon sources. A software named

TRANSFORM will be developed to automate data processing, machine learning model selection, and optimization, enabling end-users to design and optimize fermentation-derived protein solutions with minimal user intervention. Collaboration with industry partners will be pursued to understand the feasibility and sustainability of protein fermentation using novel carbon sources and to identify industrial challenges.

Principal researchers

Sci24019 23 fm uk fc 1 688 guo headshot

Miao Guo

Senior Lecturer in Engineering, Department of Engineering

King’s College London, United Kingdom

With expertise in Life Sciences and Chemical Engineering, Miao Guo leads research to experimentally and computationally develop and optimize axenic/microbiome bioprocess to recover waste. Her research has led to 70 journal articles and received awards e.g. 2023 IChemE Senior Moulton Medal. Her lab develops open-source optimization methods and tools.

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