Optimization of the Inorganic Salts in Coenzyme Q<sub>10</sub> Fermentation Medium of <i>Rhodobacter sphaeroides</i> Based on Uniform Design and Artificial Neural Network and Genetic Algorithm

Optimization of the Inorganic Salts in Coenzyme Q<sub>10</sub> Fermentation Medium of <i>Rhodobacter sphaeroides</i> Based on Uniform Design and Artificial Neural Network and Genetic Algorithm

Coenzyme Q<sub>10</sub> (CoQ<sub>10</sub>) has attracted widespread attention in recent years due to its momentous physiological functions. Microbial fermentation is the major method in CoQ<sub>10</sub> industrial production, and <i>Rhodobacter sphaeroides&l...

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Bibliographic Details
Main Authors: Yi Zheng, Yujun Xiao, Shuling Tang, Junpeng Li, Yingzi Wu, Yong Zhou
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Fermentation
Subjects:
CoQ<sub>10</sub>
fermentation medium
inorganic salts
UD
ANN-GA
<i>Rhodobacter sphaeroides</i>
Online Access:https://www.mdpi.com/2311-5637/11/7/383
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Summary:Coenzyme Q<sub>10</sub> (CoQ<sub>10</sub>) has attracted widespread attention in recent years due to its momentous physiological functions. Microbial fermentation is the major method in CoQ<sub>10</sub> industrial production, and <i>Rhodobacter sphaeroides</i> is the main strain for the production of CoQ<sub>10</sub> by fermentation. Optimization of the culture medium is a popular solution to improve the metabolite production. Culture medium is the material basis for microbial growth and product synthesis, of which inorganic salts are a key ingredient. Uniform design (UD), artificial neural network (ANN), and genetic algorithm (GA) are the main research methods. Through uniform design (UD) and artificial neural network/genetic algorithm (ANN-GA) progressive optimization, an optimal formulation of the inorganic salts in fermentation medium was obtained (g·L<sup>−1</sup>): MgSO<sub>4</sub> 12, NaCl 2.5, FeSO<sub>4</sub> 1.6, KH<sub>2</sub>PO<sub>4</sub> 0.8, MnSO<sub>4</sub> 0.1, CaCl<sub>2</sub> 0.1. Ultimately, the fermentation yield of CoQ<sub>10</sub> could reach 255.36 mg·L<sup>−1</sup>. ANN-GA exhibited a superior prediction capability compared to UD. Compared to UD, the optimization results of ANN-GA had a smaller relative error (ANN-GA 1.23%; UD 3.01%) and a higher increase rate in the fermentation level of CoQ<sub>10</sub> (ANN-GA 4.1%; UD 2.04%). <i>R. sphaeroides</i> had a high demand for Mg<sup>2+</sup>.
ISSN:2311-5637

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