scholarly journals Generic Model Control Applied to E. coli BL21(DE3) Fed-Batch Cultures

Processes ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 772 ◽  
Author(s):  
Merouane Abadli ◽  
Laurent Dewasme ◽  
Sihem Tebbani ◽  
Didier Dumur ◽  
Alain Vande Wouwer
Keyword(s):  
Mechanistic Model ◽  
Biomass Concentration ◽  
Generic Model ◽  
Control Law ◽  
Overflow Metabolism ◽  
Fed Batch ◽  
Batch Cultures ◽  
E Coli ◽  
Model Control ◽  
Generic Model Control

This work proposes a Generic Model Control (GMC) strategy to regulate biomass growth in fed-batch cultures of Escherichia coli BL21(DE3). The control law is established using a previously validated mechanistic model based on the overflow metabolism paradigm. A model reduction is carried out to prevent the controller from relying on kinetics, which may be uncertain. In order to limit the controller to the use of a single measurement, i.e., biomass concentration which is readily available, a Kalman filter is designed to reconstruct the nonmeasurable information from the outlet gas and the remaining stoichiometry. Several numerical simulations are presented to assess the controller robustness with respect to model uncertainty. Experimental validation of the proposed GMC strategy is achieved with a lab-scale bioreactor.

scholarly journals Generic estimator of biomass concentration for Escherichia coli and Saccharomyces cerevisiae fed-batch cultures based on cumulative oxygen consumption rate

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Renaldas Urniezius ◽  
Arnas Survyla ◽  
Dziugas Paulauskas ◽  
Vladas Algirdas Bumelis ◽  
Vytautas Galvanauskas
Keyword(s):  
Escherichia Coli ◽  
Saccharomyces Cerevisiae ◽  
Exponential Growth ◽  
Biomass Concentration ◽  
Estimation Procedure ◽  
Exponential Growth Phase ◽  
Fed Batch ◽  
Batch Cultures ◽  
E Coli ◽  
Substrate Feeding

Abstract Background The focus of this study is online estimation of biomass concentration in fed-batch cultures. It describes a bioengineering software solution, which is explored for Escherichia coli and Saccharomyces cerevisiae fed-batch cultures. The experimental investigation of both cultures presents experimental validation results since the start of the bioprocess, i.e. since the injection of inoculant solution into bioreactor. In total, four strains were analyzed, and 21 experiments were performed under varying bioprocess conditions, out of which 7 experiments were carried out with dosed substrate feeding. Development of the microorganisms’ culture invariant generic estimator of biomass concentration was the main goal of this research. Results The results show that stoichiometric parameters provide acceptable knowledge on the state of biomass concentrations during the whole cultivation process, including the exponential growth phase of both E. coli and S. cerevisiae cultures. The cell culture stoichiometric parameters are estimated by a procedure based on the Luedeking/Piret-model and maximization of entropy. The main input signal of the approach is cumulative oxygen uptake rate at fed-batch cultivation processes. The developed noninvasive biomass estimation procedure was intentionally made to not depend on the selection of corresponding bioprocess/bioreactor parameters. Conclusions The precision errors, since the bioprocess start, when inoculant was injected to a bioreactor, confirmed that the approach is relevant for online biomass state estimation. This included the lag and exponential growth phases for both E. coli and S. cerevisiae. The suggested estimation procedure is identical for both cultures. This approach improves the precision achieved by other authors without compromising the simplicity of the implementation. Moreover, the suggested approach is a candidate method to be the microorganisms’ culture invariant approach. It does not depend on any numeric initial optimization conditions, it does not require any of bioreactor parameters. No numeric stability issues of convergence occurred during multiple performance tests. All this makes this approach a potential candidate for industrial tasks with adaptive feeding control or automatic inoculations when substrate feeding profile and bioreactor parameters are not provided.

scholarly journals High Kanamycin Concentration as Another Stress Factor Additional to Temperature to Increase pDNA Production in E. coli DH5α Batch and Fed-Batch Cultures

2019 ◽  
Vol 7 (12) ◽  
pp. 711
Author(s):  
Fernando Grijalva-Hernández ◽  
Jesús Vega-Estrada ◽  
Montserrat Escobar-Rosales ◽  
Jaime Ortega-López ◽  
Ricardo Aguilar-López ◽  
...  
Keyword(s):  
Morphological Changes ◽  
Growth Conditions ◽  
Medium Composition ◽  
High Cell Density Culture ◽  
Overflow Metabolism ◽  
Fed Batch ◽  
Batch Cultures ◽  
E Coli ◽  
Metabolic Burden ◽  
Kanamycin Concentration

Plasmid DNA (pDNA) vaccines require high supercoiled-pDNA doses (milligrams) to achieve an adequate immune response. Therefore, processes development to obtain high pDNA yields and productivity is crucial. pDNA production is affected by several factors including culture type, medium composition, and growth conditions. We evaluated the effect of kanamycin concentration and temperature on pDNA production, overflow metabolism (organic acids) and metabolic burden (neomycin phosphotransferase II) in batch and fed-batch cultures of Escherichia coli DH5α-pVAX1-NH36. Results indicated that high kanamycin concentration increases the volumetric productivity, volumetric and specific yields of pDNA when batch cultures were carried out at 42 °C, and overflow metabolism reduced but metabolic burden increased. Micrographs taken with a scanning electron microscope (SEM) were analyzed, showing important morphological changes. The high kanamycin concentration (300 mg/L) was evaluated in high cell density culture (50 gDCW/L), which was reached using a fed-batch culture with temperature increase by controlling heating and growth rates. The pDNA volumetric yield and productivity were 759 mg/L and 31.19 mg/L/h, respectively, two-fold greater than the control with a kanamycin concentration of 50 mg/L. A stress-based process simultaneously caused by temperature and high kanamycin concentration can be successfully applied to increase pDNA production.

Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor

2007 ◽  
Vol 2 (1) ◽  
Author(s):  
Emmanuel E Ekpo ◽  
Iqbal M Mujtaba
Keyword(s):  
Performance Analysis ◽  
Batch Reactor ◽  
Monomer Conversion ◽  
Average Chain Length ◽  
Generic Model ◽  
Batch Reactors ◽  
Dynamic Optimisation ◽  
Model Control ◽  
Simple Kinetic Model ◽  
Generic Model Control

The performance analysis of three advanced non linear controllers is the main focus of this paper. All three controllers are applied for the control of a batch polymerisation reactor which is defined by a very simple kinetic model for the polymerisation of styrene. This simple set of equations describing the polymerisation process is first solved using the sequential strategy i.e. Control Vector Parameterisation (CVP) technique within gPROMS to find optimal initial initiator concentrations and the reactor temperature trajectory necessary to yield desired polymer molecular properties (defined here as fixed values of monomer conversion and number average chain length) in minimum time. The sequential solution strategy has had limited application in solving optimisation problems for polymerisation in batch reactors, most researchers instead employing the Pontryagin's Maximum Principle (PMP) to solve optimal control problems involving these systems.The temperature trajectory obtained from the dynamic optimisation is used as the setpoint to be tracked by the three controllers: Dual Mode control with PID, which is representative of industrial practice, Generic Model Control (GMC) with Neural Networks as online heat release estimator, and Direct Inverse Control (DIC). Published work on the last two controllers as applied to the control of a batch polymerisation reactor is absent from the literature.When the performances of the different controllers are evaluated, it is seen that the GMC-NN controller performs better than the other two for the system under consideration.

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