Konopacki Maciej, Augustyniak Adrian, Grygorcewicz Bartłomiej, Dołęgowska Barbara, Kordas Marian, Rakoczy Rafał
Department of Chemical and Process Engineering, Faculty of Chemical Technology and Engineering, West Pomeranian University of Technology in Szczecin, Piastów Avenue 42, 71-065 Szczecin, Poland.
Department of Laboratory Medicine, Chair of Microbiology, Immunology and Laboratory Medicine, Pomeranian Medical University in Szczecin, Powstańców Wielkopolskich Avenue 72, 70-111 Szczecin, Poland.
Microorganisms. 2020 Oct 31;8(11):1706. doi: 10.3390/microorganisms8111706.
The cultivation of bacteria sets a ground for studying biological processes in many scientific disciplines. The development of the bacterial population is commonly described with three factors that can be used to evaluate culture conditions. However, selecting only one of them for the optimization protocol is rather problematic and may lead to unintended errors. Therefore, we proposed a novel mathematical approach to obtain a single factor that could be used as the objective function to evaluate the whole growth dynamic and support the optimization of the biomass production process. The sigmoidal-shape curve, which is the commonly used function to plot the amount of biomass versus time, was the base for the mathematical analysis. The key process parameters, such as maximal specific growth rate and lag-phase duration were established with the use of mathematical coefficients of the model curve and combined to create the single growth parameter. Moreover, this parameter was used for the exemplary optimization of the cultivation conditions of that was cultured to be further used in the production of lytic bacteriophages. The proposed growth parameter was successfully validated and used to calculate the optimal process temperature of the selected bacterial strain. The obtained results indicated that the proposed mathematical approach could be effortlessly adapted for a precise evaluation of growth curves.
细菌培养为许多科学学科研究生物过程奠定了基础。细菌群体的发展通常用三个可用于评估培养条件的因素来描述。然而，在优化方案中仅选择其中一个因素存在相当大的问题，可能会导致意外错误。因此，我们提出了一种新颖的数学方法，以获得一个单一因素，该因素可作为目标函数来评估整个生长动态，并支持生物量生产过程的优化。S形曲线是绘制生物量与时间关系的常用函数，是数学分析的基础。通过使用模型曲线的数学系数确定了关键过程参数，如最大比生长速率和延迟期持续时间，并将它们组合以创建单一生长参数。此外，该参数用于对培养条件进行示例优化，该培养物用于进一步生产裂解性噬菌体。所提出的生长参数得到了成功验证，并用于计算所选细菌菌株的最佳工艺温度。所得结果表明，所提出的数学方法可以轻松地适用于精确评估生长曲线。
