Department of Chemical and Process Engineering, Faculty of Engineering, University of Moratuwa, Moratuwa, Sri Lanka.
Department of Mechanical Engineering, Faculty of Engineering, University of Moratuwa, Moratuwa, Sri Lanka.
Crit Rev Biotechnol. 2024 Sep;44(6):996-1017. doi: 10.1080/07388551.2023.2237183. Epub 2023 Aug 16.
Natural astaxanthin is synthesized by diverse organisms including: bacteria, fungi, microalgae, and plants involving complex cellular processes, which depend on numerous interrelated parameters. Nonetheless, existing knowledge regarding astaxanthin biosynthesis and the conditions influencing astaxanthin accumulation is fairly limited. Thus, manipulation of the growth conditions to achieve desired biomass and astaxanthin yields can be a complicated process requiring cost-intensive and time-consuming experiment-based research. As a potential solution, modeling and simulation of biological systems have recently emerged, allowing researchers to predict/estimate astaxanthin production dynamics in selected organisms. Moreover, mathematical modeling techniques would enable further optimization of astaxanthin synthesis in a shorter period of time, ultimately contributing to a notable reduction in production costs. Thus, the present review comprehensively discusses existing mathematical modeling techniques which simulate the bioaccumulation of astaxanthin in diverse organisms. Associated challenges, solutions, and future perspectives are critically analyzed and presented.
天然虾青素是由多种生物体合成的，包括细菌、真菌、微藻和植物，涉及复杂的细胞过程，这些过程依赖于许多相互关联的参数。然而，关于虾青素生物合成和影响虾青素积累的条件的现有知识相当有限。因此，操纵生长条件以达到所需的生物量和虾青素产量可能是一个复杂的过程，需要成本密集型和耗时的基于实验的研究。作为一种潜在的解决方案，生物系统的建模和模拟最近已经出现，使研究人员能够预测/估计选定生物体中虾青素的生产动态。此外，数学建模技术将能够在更短的时间内进一步优化虾青素的合成，最终有助于显著降低生产成本。因此，本综述全面讨论了现有的模拟不同生物体中虾青素生物积累的数学建模技术。对相关挑战、解决方案和未来展望进行了批判性分析和阐述。
