Harnessing Statistical Designs for Sustainable Optimization of Fermentation Media for Hyaluronic Acid Production
Research Poster Engineering 2025 Graduate ExhibitionPresentation by Nasim Espah Borujeni
Exhibition Number 100
Abstract
Hyaluronic acid (HA) is an essential bio-product recognized for its extensive applications in healthcare, regenerative medicine, and cosmetics due to its distinctive viscoelastic and biocompatible characteristics. In 2023, the global HA market was appraised at USD 10.04 billion, with projections estimating it will escalate to USD 16.8 billion by 2030. Consequently, enhancing microbial production through optimizing fermentation processes is vital for achieving cost-effective and sustainable industrial applications. This research utilizes a systematic statistical methodology to fine-tune the fermentation medium for optimal HA yield. Initially, the Plackett-Burman design was employed to screen eight medium components—yeast extract, casein, peptone, beef extract, MgSO4·7H2O, K2HPO4, KH2PO4, and (NH4)2SO4—across 12 fermentation trials. The results revealed that yeast extract, MgSO4·7H2O, and KH2PO4 were the most significant factors affecting HA production. Following this, the optimization of carbon sources determined that sucrose outperformed glucose and lactose as the preferred carbon source. Furthermore, the Response Surface Methodology was applied to optimize the concentrations of the most significant fermentation medium components identified through the Plackett-Burman design. Therefore, various concentrations of yeast extract (10.00–30.00 g/L), MgSO4·7H2O (0.2–2.00 g/L), and KH2PO4 (1.00–4.00 g/L) were tested over 15 fermentation runs. The optimized medium has been determined as 27.79 g/L of yeast extract, 1.11 g/L of MgSO4·7H2O, and 4.00 g/L of KH2PO4, which resulted in an increased HA to 330 mg/L. In conclusion, this research demonstrated the synergy between statistical modeling and fermentation engineering as a potent approach for optimizing HA production, ensuring improved productivity, scalability, and economic viability for industrial applications.
Importance
Hyaluronic acid (HA) is recognized as a significant biopolymer with diverse applications across the pharmaceutical, food, and cosmetic industries, attributable to its remarkable biocompatibility and hydration capabilities. Originally, HA was isolated from animal tissues; however, this process raised ethical dilemmas, contamination risks, and yielded low quantities. As a sustainable alternative, microbial fermentation emerged, offering higher purity, sustainability, and scalability. Nevertheless, optimizing fermentation media, which is essential for microbial proliferation and HA biosynthesis, continues to address significant challenges. This investigation employs statistical design methodologies to optimize the composition of fermentation media, thereby maximizing HA production and minimizing resource wastage. By integrating statistical optimization, the efficiency of the process, along with its sustainability and economic viability, is augmented, thereby facilitating advancements in biotechnological production.