Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor,Industrial & Engineering Chemistry Research

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Improved Prediction of Phosphorus Dynamics in Biotechnological Processes by Considering Precipitation and Polyphosphate Formation: A Case Study on Antibiotic Production with Streptomyces coelicolor
Industrial & Engineering Chemistry Research ( IF 3.8 ) Pub Date : 2018-04-26 , DOI: 10.1021/acs.iecr.7b05249
Patrick Bürger ₁ , Xavier Flores-Alsina ₂ , Harvey Arellano-Garcia ₃ , Krist V. Gernaey ₂

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The multiplicity of physicochemical and biological processes, where phosphorus is involved, makes their accurate prediction using current mathematical models in biotechnology quite a challenge. In this work, an antibiotic production model of Streptomyces coelicolor is chosen as a representative case study in which major difficulties arise in explaining the measured phosphate dynamics among some minor additional issues. Thus, the utilization of an advanced speciation model and a multiple mineral precipitation framework is proposed to improve phosphorus predictions. Furthermore, a kinetic approach describing intracellular polyphosphate accumulation and consumption has been developed and implemented. A heuristic re-estimation of selected parameters is carried out to improve overall model performance. The improved process model predicts phosphate dynamics (root mean squared error_≤52h: −90%; relative average deviation_≤52h: −96%) very accurately in comparison to the original implementation, where biomass growth/decay was the only phosphorus source-sink. In addition, parameter re-estimation achieved an improved description of the available measurements for biomass, total ammonia, dissolved oxygen, and actinorhodin concentrations. This work contributes to the existing process knowledge of biotechnological systems in general and especially to antibiotic production with S. coelicolor, while emphasizing the (unavoidable) need of considering both physico-chemical and biological processes to accurately describe phosphorus dynamics.

中文翻译：

考虑到沉淀和多磷酸盐的形成，改善了生物工艺过程中磷动力学的预测：以链霉菌链霉菌抗生素生产为例

涉及磷的多种物理化学和生物过程使得使用当前生物技术中的数学模型进行准确的预测成为一个挑战。在这项工作中，天蓝色链霉菌的抗生素生产模型选择了具有代表性的案例研究，其中在解释一些次要的其他问题中，在解释测得的磷酸盐动力学方面存在重大困难。因此，提出了利用先进的形态学模型和多种矿物沉淀框架来改善磷的预测。此外，已经开发并实施了描述细胞内多磷酸盐积累和消耗的动力学方法。对所选参数进行启发式重新估计，以提高整体模型的性能。改进的过程模型可预测磷酸盐动力学（均方根误差_≤52h：-90％；相对平均偏差_≤52h：-96％），与原始实施方案相比非常准确，在原始实施方案中，生物量的增长/衰减是唯一的磷源汇。此外，参数重新估算对生物量，总氨，溶解氧和放线菌ho蛋白浓度的可用测量值进行了改进的描述。这项工作为一般生物技术系统的现有工艺知识做出了贡献，特别是对天蓝色链霉菌的抗生素生产做出了贡献，同时强调了（不可避免的）需要同时考虑物理化学和生物过程以准确描述磷动力学的需求。

更新日期：2018-07-14

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