Enzyme-aware model maps microbial trade-offs for cleaner biohydrogen production

A research team has developed an enzyme-constrained genome-scale metabolic model for the bacterium Ethanoligenens harbinense YUAN-3, which explains why hydrogen-producing microbes struggle to grow fast and generate hydrogen efficiently at the same time. The model, published in Environmental Science and Ecotechnology, predicts growth rates and hydrogen yields more accurately than conventional approaches by accounting for limited enzyme resources. It shows that rapid growth diverts enzyme capacity toward precursor synthesis, reducing hydrogen output, while the stationary phase allows higher hydrogen yields. The model identified amino acid biosynthesis and specific gene targets, such as deletion of phosphoglycerate kinase, as promising routes for improving fermentative biohydrogen production. This approach offers a practical path for engineering hydrogen-producing microbes beyond trial-and-error optimization, supporting cleaner hydrogen production from organic waste. As biological hydrogen production moves toward industrial use, enzyme-constrained modeling could become a key tool for linking microbial metabolism with low-carbon energy systems.