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[P01-907]Strategic Optimization of Dual-Stage Cultivation and Feeding Processes in Bacillus spp. for Enhanced Production of Hair Loss Mitigation Materials

○WOOSHIK SHIN1, Jimin Hong2,1, Byeonghwa Lee3,1, Jaehoon Cho1 (1. KITECH(Korea Institute of Industrial Technology) (Korea), 2. Sun Moon University (Korea), 3. Korea University (Korea))
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Keywords:

Bacillus spp,Biocatalyst,Response surface methodology,Hair loss,Bio-materials

This study presents a comprehensive bioprocess engineering strategy to maximize the production of functional hair loss mitigation materials using Bacillus spp. As the demand for high-performance bioactive substances increases, establishing a scalable and efficient microbial production system has become essential. To address this, we implemented a dual-stage cultivation strategy designed to synergistically enhance both biomass accumulation and biocatalytic conversion efficiency. In the initial phase, we focused on maximizing cell growth through Response Surface Methodology (RSM). The optimized media composition resulted in an OD600 of 9.966, representing a 5.7-fold increase compared to conventional conditions. This optimization achieved a robust dry cell weight (DCW) of 2.3g/L within a short incubation period of 0.66 days, yielding a high productivity of 3.48 g/L/Day. By supplying a specialized feeding medium that prioritizes bioconversion over growth, we simultaneously achieved large-scale cell recovery and maximized the catalytic transformation of target substances. Crucially, this feeding step serves as a metabolic induction process, effectively upregulating the specific pathways required for secondary metabolite production. This integrated approach not only enhances industrial yield but also provides a platform for gene discovery, as the induction phase allows for the identification of key regulatory genes and enzymes involved in the conversion process. This research offers a robust technical foundation for the commercialization of Bacillus-derived functional materials by bridging efficient bioprocess design with molecular-level insights.

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