Optimal Fed Batch Experiment Design for Estimation of Monod Kinetics of Azospirillum brasilense: From Theory to Practice

Cappuyns, Astrid; Bernaerts, Kristel; Smets, Ilse; Ona, Ositadinma; Prinsen, Els; Vanderleyden, Jos; Impe, Jan Van

doi:10.1021/bp070046x

Cited by 12 publications

(11 citation statements)

References 11 publications

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“…Estimating parameters to describe Monod growth and substrate utilization kinetics from experimental data is problematic due to the potential colinearity of max and K s (41). Other investigators have demonstrated that optimal experimental conditions can be established to limit the colinearity of max and K s , thus rendering those parameters identifiable (42,43). Optimal conditions are based on ratios between the initial cell and substrate concentrations and the magnitude of max and K s .…”

Section: Low-concentration Incubation Experimentsmentioning

confidence: 99%

Kinetics and Yields of Pesticide Biodegradation at Low Substrate Concentrations and under Conditions Restricting Assimilable Organic Carbon

Helbling

Hammes

Egli

et al. 2014

Appl Environ Microbiol

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The fundamentals of growth-linked biodegradation occurring at low substrate concentrations are poorly understood. Substrate utilization kinetics and microbial growth yields are two critically important process parameters that can be influenced by low substrate concentrations. Standard biodegradation tests aimed at measuring these parameters generally ignore the ubiquitous occurrence of assimilable organic carbon (AOC) in experimental systems which can be present at concentrations exceeding the concentration of the target substrate. The occurrence of AOC effectively makes biodegradation assays conducted at low substrate concentrations mixed-substrate assays, which can have profound effects on observed substrate utilization kinetics and microbial growth yields. In this work, we introduce a novel methodology for investigating biodegradation at low concentrations by restricting AOC in our experiments. We modified an existing method designed to measure trace concentrations of AOC in water samples and applied it to systems in which pure bacterial strains were growing on pesticide substrates between 0.01 and 50 mg liter ؊1 . We simultaneously measured substrate concentrations by means of high-performance liquid chromatography with UV detection (HPLC-UV) or mass spectrometry (MS) and cell densities by means of flow cytometry. Our data demonstrate that substrate utilization kinetic parameters estimated from high-concentration experiments can be used to predict substrate utilization at low concentrations under AOC-restricted conditions. Further, restricting AOC in our experiments enabled accurate and direct measurement of microbial growth yields at environmentally relevant concentrations for the first time. These are critical measurements for evaluating the degradation potential of natural or engineered remediation systems. Our work provides novel insights into the kinetics of biodegradation processes and growth yields at low substrate concentrations.

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Section: Low-concentration Incubation Experimentsmentioning

confidence: 99%

Kinetics and Yields of Pesticide Biodegradation at Low Substrate Concentrations and under Conditions Restricting Assimilable Organic Carbon

Helbling

Hammes

Egli

et al. 2014

Appl Environ Microbiol

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“…The closer these initial values approach the true values, the better the obtained OED will be. OED is, therefore, an iterative procedure (Box and Lucas, 1959;Cappuyns et al, 2007;Franceschini and Macchietto, 2008d;Walter and Pronzato, 1990). OED can also be employed for designing parallel experiments (Galvanin et al, 2007).…”

Section: Optimal Experimental Design and Measurement Techniquesmentioning

confidence: 99%

“…Later on, this concept was further improved and investigated in detail (Asprey and Macchietto, 2000;Fedorov, 1975a, 1975b;Burke et al, 1997;Draper and Hunter, 1966;Hill, 1978;Kremling et al, 2004;Walter and Pronzato, 1990). In all cases OED requires interactions between modeler and experimenter since a compromise between maximum information content and practical feasibility has to be achieved (Cappuyns et al, 2007).…”

Section: Optimal Experimental Design and Measurement Techniquesmentioning

confidence: 99%

Model-based experimental analysis of enzyme kinetics in aqueous–organic biphasic systems

Zavrel

Schmidt

Michalik

et al. 2007

Journal of Biotechnology

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“…10,30 The difficulties were either no single solution or insufficient accuracy. [31][32][33] To address the nonlinear features of kinetics in cell culture, neural networks were used to simulate the kinetic model. 8,9 Although neural networks were able to simulate time profiles of variables in cell culture, they were unable to estimate parameters in a physiological sense.…”

Section: Introductionmentioning

confidence: 99%

Modeling kinetics of a large‐scale fed‐batch CHO cell culture by Markov chain Monte Carlo method

Xing

Bishop

Leister

et al. 2009

Biotechnology Progress

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Markov chain Monte Carlo (MCMC) method was applied to model kinetics of a fed-batch Chinese hamster ovary cell culture process in 5,000-L bioreactors. The kinetic model consists of six differential equations, which describe dynamics of viable cell density and concentrations of glucose, glutamine, ammonia, lactate, and the antibody fusion protein B1 (B1). The kinetic model has 18 parameters, six of which were calculated from the cell culture data, whereas the other 12 were estimated from a training data set that comprised of seven cell culture runs using a MCMC method. The model was confirmed in two validation data sets that represented a perturbation of the cell culture condition. The agreement between the predicted and measured values of both validation data sets may indicate high reliability of the model estimates. The kinetic model uniquely incorporated the ammonia removal and the exponential function of B1 protein concentration. The model indicated that ammonia and lactate play critical roles in cell growth and that low concentrations of glucose (0.17 mM) and glutamine (0.09 mM) in the cell culture medium may help reduce ammonia and lactate production. The model demonstrated that 83% of the glucose consumed was used for cell maintenance during the late phase of the cell cultures, whereas the maintenance coefficient for glutamine was negligible. Finally, the kinetic model suggests that it is critical for B1 production to sustain a high number of viable cells. The MCMC methodology may be a useful tool for modeling kinetics of a fed-batch mammalian cell culture process.

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Optimal Fed Batch Experiment Design for Estimation of Monod Kinetics of Azospirillum brasilense: From Theory to Practice

Cited by 12 publications

References 11 publications

Kinetics and Yields of Pesticide Biodegradation at Low Substrate Concentrations and under Conditions Restricting Assimilable Organic Carbon

Kinetics and Yields of Pesticide Biodegradation at Low Substrate Concentrations and under Conditions Restricting Assimilable Organic Carbon

Model-based experimental analysis of enzyme kinetics in aqueous–organic biphasic systems

Modeling kinetics of a large‐scale fed‐batch CHO cell culture by Markov chain Monte Carlo method

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