Cole‐Cole modeling of real‐time capacitance data for estimation of cell physiological properties in recombinant Escherichia coli cultivation

• Published in: Biotechnology and bioengineering 2022-03, Vol.119 (3), p.922-935
• Main Authors: Swaminathan, Nivedhitha, Priyanka, Priyanka, Rathore, Anurag S., Sivaprakasam, Senthilkumar, Subbiah, Senthilmurugan
• Format: Article
• Language: English
• Subjects: Capacitance; cell physiology; Cell viability; Cole‐Cole modeling; Cultivation; Diameters; dielectric spectroscopy; Dry cells; E coli; Escherichia coli; Estimation; Evolutionary algorithms; Flow cytometry; genetic algorithm; Genetic algorithms; Physiology; process analytical technology; Spectroscopy; Spectrum analysis
• ISSN: 0006-3592; 1097-0290
• DOI: 10.1002/bit.28028

Real‐time estimation of physiological properties of the cell during recombinant protein production would ensure enhanced process monitoring. In this study, we explored the application of dielectric spectroscopy to track the fed‐batch phase of recombinant Escherichia coli cultivation for estimating the physiological properties, namely, cell diameter and viable cell concentration (VCC). The scanning capacitance data from the dielectric spectroscopy were pre‐processed using moving average. Later, it was modeled through a nonlinear theoretical Cole‐Cole model and further solved using a global evolutionary genetic algorithm (GA). The parameters obtained from the GA were further applied for the estimation of the aforementioned physiological properties. The offline cell diameter and cell viability data were obtained from particle size analyzer and flow cytometry measurements to validate the Cole‐Cole model. The offline VCC was calculated from the cell viability % from flow cytometry data and dry cell weight concentration. The Cole‐Cole model predicted the cell diameter and VCC with an error of 1.03% and 7.72%, respectively. The proposed approach can enable the operator to take real‐time process decisions to achieve desired productivity and product quality. A robust system for real‐time estimation of physiological properties of biomass using dielectric spectroscopy (DS) is proposed. The authors applied scanning DS to measure real‐time capacitance measurements and estimated the Cole‐Cole model parameters by using a hybrid optimization technique for a recombinant E. coli system. Further, obtained physiological properties were validated using the traditional offline analytical methods. The proposed approach would be useful for predicting harvest time and developing capacitance‐based control strategies leading to enhanced process monitoring and improved product quality.