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Currently, industrial production processes of probiotics, including bifidobacteria, are typically optimized based on empirical design approaches. During fermentation, Bifidobacterium bacteria are typically cultured in a nutrient-rich medium, which provides them with the necessary nutrients to grow and reproduce. The fermentation process may involve various conditions such as temperature, pH, and oxygen levels, which are carefully controlled to optimize the growth and activity of the bacteria. There are several commercial Bifidobacterium species that are commonly used in the production of probiotic products and dietary supplements.

Bifidobacterium bifidum Fermentation

B. bifidum is found in the human gut and has been associated with various health benefits, including improved digestion and immune function.

Bifidobacterium lactis Fermentation

B. lactis is found in the human gut and has been shown to improve gut health, boost the immune system, and reduce inflammation.

Bifidobacterium longum Fermentation

B. longum has been shown to improve gut health, reduce inflammation, and boost the immune system. It is also commonly used in the production of infant formula to promote healthy gut development in infants.

Bifidobacterium animalis Fermentation

B. animalis is used in the production of dairy products, such as yogurt and cheese, and has been shown to improve gut health and boost the immune system.

Bifidobacterium breve Fermentation

B. breve has been shown to improve gut health and may help reduce the symptoms of irritable bowel syndrome (IBS).

It is desirable to adopt more rational, knowledge-driven approaches for identifying the essential nutritional requirements and advancing industrial-scale production. The reconstruction of high-quality strain-specific genome-scale metabolic networks is a powerful approach in microbial systems biology, since it leverages the value of the exponentially growing genomics data. Converting a network reconstruction into a genome-scale metabolic models (GEM) enables the quantitative and qualitative analysis of the reconstructed metabolic network using constraint-based methods. Model-generated insights can be used to guide the formulation of a chemically defined medium (CDM) that supports the growth of Bifidobacterium strains in the same manner as complex medium. The models would be finally quantitatively validated in the newly developed medium in lab-scale batch fermentations.