Optimization of Chemical Defined Medium for Lactobacillus brevis Based on Artificial Intelligence

ABSTRACT Lactobacillus brevis ( L. brevis ) is a bacterium known for its lactic acid production and probiotic properties. However, the limited research on industrial fermentation of L. brevis and its low productivity pose challenges. This work aimed to develop a cost‐effective synthetic medium as an alternative to a complex medium for its large‐scale production. We first investigated the nutrient requirements of L. brevis in terms of amino acids, vitamins, and nucleotides using the single nutrient omission method. Artificial intelligence algorithms combined with the Growth Profiler 960 (GP960) were then employed to optimize the concentration in the synthetic medium. The results indicate that L. brevis has diverse nutritional demands, including 18 essential amino acids (excluding aspartic acid and glutamine) and specific vitamins (pantothenic acid, nicotinic acid, vitamin B6, riboflavin) and nucleotides. Furthermore, the developed synthetic medium supported equivalent growth of L. brevis to that of the complex medium. The specific growth rate of L. brevis in synthetic medium could reach 0.297 h −1 . The cost of synthetic medium was 57.52% lower than that of fermentation medium. These results provide a solid foundation for further research on industrial fermentation of L. brevis . Summary Determine the requirements of Lactobacillus brevis growth for various types of amino acids, vitamins, and nucleotides. A combination of artificial intelligence algorithms and Growth Profiler 960 (GP960) equipment is used to optimize the medium at high throughput. No restrictions are placed on the factors and levels of medium optimization. Compared to complex medium, the components of the synthetic medium for Lactobacillus brevis are clearer and less expensive.