MANY MINDEDUniversity of Sheffield Uses AI and Evolutionary Principles to Develop Scalable Sustainable Proteins
University of Sheffield researchers are applying Darwinian evolution principles with AI to rapidly develop precision-fermented proteins. The team, led by Prof Tuck Seng Wong (chair of biomanufacturing and deputy co-director of UK’s National Alternative Protein Innovation Centre), has identified nearly 800 plant-based proteins with emulsifier properties using AI and statistical physics. Their work focuses on microbial strains for dairy proteins and animal fats through selective pressure in automated fermenters, while also exploring Rubisco protein extraction from crop waste—a recent advancement with decades of technical hurdles. The research partners with Unilever, Mars, and startup FibreFolks, and benefits from £38 million in 2024 funding for the UK’s National Alternative Protein Innovation Centre.
This approach aims to create scalable, low-carbon protein sources that avoid livestock and carbon-intensive agriculture. By targeting the nutrition paradox, it seeks equitable access to nutritious food globally. However, the work remains in development: no cost or environmental impact metrics are quantified, and Rubisco extraction’s scalability is unproven despite its potential. The 60% plant-derived calorie figure referenced in the research applies only to rice, maize, and wheat globally, not current extraction volumes.
If scaled, this method could reduce protein production costs and environmental strain while expanding sustainable food access. For now, it represents a promising technical pathway but requires overcoming significant development hurdles before impacting real-world food systems. The next phase will test whether these microbial strains can reliably produce proteins at scale without compromising nutritional quality or ecological impact.
Source: Green Queen