KSP: “AILEEN” Artificial Intelligence guided Multi-Microbial Cultivation process

In the world of industrial biotechnology, a digital and automated revolution known as Bioprocess Industry 4.0 is on the horizon. This transformative wave has been building for three decades, fueled by remarkable advances in biotechnology. Genetic modifications have empowered bacteria to function as miniature production units, converting diverse feedstocks into sought-after products like vibrant colors, enticing perfumes, and potent antimicrobials. However, there's a hurdle to overcome. Most bacteria favor glucose over other sugars, limiting our ability to tap into new bioresources like sugar-rich seaweed. Previous attempts to broaden bacterial substrate preferences through extensive genetic alterations have failed due to genetic instability. To unlock this technology's potential, we face three key challenges: 1. Develop a microbial bioprocess that bypasses metabolic constraints, enabling cells to perform complex tasks with minimal genetic changes. 2. Create a sophisticated biosensor feedback system within co-cultures to monitor and control their intricate dynamics. 3. Devise effective co-culture control methods. Meet "AILEEN," our interdisciplinary team's groundbreaking creation. AILEEN is an AI-powered reinforcement learning algorithm that manages a consortium of bacterial strains in co-cultures. The cell factories will efficiently consume most of the sugars within complex substrates. Complementing AILEEN is a state-of-the-art biosensor system that swiftly provides feedback on co-culture composition and conditions. AILEEN continuously learns from its interactions with the co-culture, optimizing balance and conditions over time. The real-world implications are profound. We'll demonstrate how AILEEN, alongside co-culture technology, can fully harness the untapped potential of seaweed, yielding high-value products. This monumental transformation promises to reshape industrial biotechnology and drive innovation across enabling technologies.

Without doubt, the future of industrial biotechnology will incorporate digitalization, automation to improve bioprocess industry 4.0. Over the last 3 decades, biotechnology have made immense progress and genetic modifications have turned bacteria into micro production units that can convert feedstocks into products desired by modern society, e.g. colors, perfumes, antimicrobials. But most microbes prefer glucose over other sugars, which prevents bioprocesses to deploy new bioresources, e.g. seaweed, that contain sugar mix. Attempts to introduce large numbers of modifications in bacteria to extend their substrate spectra have so far failed due to genetic instability. To enable this technology we need to i) develop a microbial bioprocess that can bypass this metabolic burden so the cells can perform complex operations with minimal genetic modifications ii) develop biosensor feedback system in co-cultures and iii) develop control of the co-culture despite its complex dynamics. Our interdisciplinary team will establish the knowledge and approach to create "AILEEN", a novel A.I. reinforcement learning algorithm that supervises a palette of strains in co-cultures, each cell can stably and rapidly consume one type of sugar in complex substrates. A novel biosensor system will provide rapid feedback about the consortia composition and co-culture conditions back to AILEEN, which learns by interaction with the co-culture how to improve its balance and conditions. We will demonstrate how this radically new technology can fully utilize abundant, yet unexploited brown seaweed and produce high valuable products. AILEEN, with her accompanied co-culture technology holds the potential to transform industrial bioprocess forever, moving from traditional monocultures to effective co-cultures, enabling to valorize a range of alternative bioresources. This radical bioprocess transformation will be realised across the enabling technologies industrial Biotechnology.