Modeling nonlinear stochastic kinetic system and stochastic optimal control of microbial bioconversion process in batch culture

In this paper, we analyze a stochastic model representing batch fermentation in the process of glycerol bio-dissimilation to 1,3-propanediol by klebsiella pneumoniae. The stochasticity in the model is introduced by parameter perturbation which is a standard technique in stochastic population modelling. Thus, based on the nonlinear deterministic dynamical system of glycerol bioconversion to 1,3-propanediol in batch culture, we present the stochastic version of the batch fermentation process driven by a five-dimensional Brownian motion and Lipschitz coefficients, which is suitable for the factual fermentation. Subsequently, we study the existence and uniqueness of solutions for the stochastic system as well as the boundedness and Markov property of solutions. Moveover a stochastic optimal control model is constructed and the sufficient and necessary conditions for optimality are proved via dynamic programming principle. Finally we present computer simulation for the stochastic system by using Stochastic Euler–Maruyama scheme. Compared with the results from the deterministic system, numerical results reveal the peculiar role of stochasticity in the dynamical responses of the batch culture

Optimal parameter selection for nonlinear multistage systems with time-delays

In this paper, we consider a novel dynamic optimization problem for nonlinear multistage systems with time-delays. Such systems evolve over multiple stages, with the dynamics in each stage depending on both the current state of the system and the state at delayed times. The optimization problem involves choosing the values of the time-delays, as well as the values of additional parameters that influence the system dynamics, to minimize a given cost functional. We first show that the partial derivatives of the system state with respect to the time-delays and system parameters can be computed by solving a set of auxiliary dynamic systems in conjunction with the governing multistage system. On this basis, a gradient-based optimization algorithm is proposed to determine the optimal values of the delays and system parameters. Finally, two example problems, one of which involves parameter identification for a realistic fed-batch fermentation process, are solved to demonstrate the algorithm’s effectiveness

Multi-objective optimization of nonlinear switched time-delay systems in fed-batch process

© 2016 Elsevier Inc.Maximization of productivity and minimization of consumption are two top priorities for biotechnological industry. In this paper, we model a fed-batch process as a nonlinear switched time-delay system. Taking the productivity of target product and the consumption rate of substrate as the objective functions, we present a multi-objective optimization problem involving the nonlinear switched time-delay system and subject to continuous state inequality constraints. To solve the multi-objective optimization problem, we first convert the problem into a sequence of single-objective optimization problems by using convex weighted sum and normal boundary intersection methods. A gradient-based single-objective solver incorporating constraint transcription technique is then developed to solve these single-objective optimization problems. Finally, a numerical example is provided to verify the effectiveness of the numerical solution approach. Numerical results show that the normal boundary intersection method in conjunction with the developed single-objective solver is more favourable than the convex weighted sum method

Modelling and parameter identification for a two-stage fractional dynamical system in microbial batch process

In this paper, we consider mathematical modelling and parameter identification problem in bioconversion of glycerol to 1,3-propanediol by Klebsiella pneumoniae. In view of the dynamic behavior with memory and heredity and experimental results in batch culture, a two-stage fractional dynamical system with unknown fractional orders and unknown kinetic parameters is proposed to describe the fermentation process. For this system, some important properties of the solution are discussed. Then, taking the weighted least-squares error between the computational values and the experimental data as the performance index, a parameter identification model subject to continuous state inequality constraints is presented. An exact penalty method is introduced to transform the parameter identification problem into the one only with box constraints. On this basis, we develop a parallel Particle Swarm Optimization algorithm to find the optimal fractional orders and kinetic parameters. Finally, numerical results show that the model can reasonably describe the batch fermentation process, as well as the effectiveness of the developed algorithm. Keywords: fractional dynamical system, parameter identification, parallel optimization

High-level fed-batch fermentative expression of an engineered Staphylococcal protein A based ligand in E. coli: purification and characterization

The major platform for high level recombinant protein production is based on genetically modified microorganisms like Escherichia coli (E. coli) due to its short dividing time, ability to use inexpensive substrates and additionally, its genetics is comparatively simple, well characterized and can be manipulated easily. Here, we investigated the possibilities of finding the best media for high cell density fermentation, by analyzing different media samples, focusing on improving fermentation techniques and recombinant protein production. Initial fermentation of E. coli BL21 DE3:pAV01 in baffled flasks showed that high cell density was achieved when using complex media, Luria–Bertani (LB) and Terrific medium broth (TB) (10 and 14 g/L wet weight, respectively), as compared to mineral media M9, modified minimal medium (MMM) and Riesenberg mineral medium (RM) (7, 8 and 7 g/L, respectively). However, in fed-batch fermentation processes when using MMM after 25 h cultivation, it was possible to yield an optical density (OD600) of 139 corresponding to 172 g/L of wet biomass was produced in a 30 L TV Techfors-S Infors HT fermenter, with a computer controlled nutrient supply (glucose as a carbon source) delivery system, indicating nearly 1.5 times that obtained from TB. Upon purification, a total of 1.65 mg/g of protein per gram cell biomass was obtained and the purified AviPure showed affinity for immunoglobulin. High cell density fed batch fermentation was achieved by selecting the best media and growth conditions, by utilizing a number of fermentation parameters like media, fermentation conditions, chemical concentrations, pO2 level, stirrer speed, pH level and feed media addition. It is possible to reach cell densities higher than shake flasks and stirred tank reactors with the improved oxygen transfer rate and feed.Fil: Kangwa, Martin. Jacobs University; AlemaniaFil: Yelemane, Vikas. Jacobs University; AlemaniaFil: Polat, Ayse Nur. Jacobs University; AlemaniaFil: Gorrepati, Kanaka Durga Devi. Jacobs University; AlemaniaFil: Grasselli, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; ArgentinaFil: Fernández Lahore, Marcelo. Jacobs University; Alemani

Optimization of a fed-batch bioreactor for 1,3-propanediol production using hybrid nonlinear optimal control

A nonlinear hybrid system was proposed to describe the fed-batch bioconversion of glycerol to 1,3-propanediol with substrate open loop inputs and pH logic control in previous work [47]. The current work concerns the optimal control of this fed-batch process. We slightly modify the hybrid system to provide a more convenient mathematical description for the optimal control of the fed-batch culture. Taking the feeding instants and the terminal time as decision variables, we formulate an optimal control model with the productivity of 1,3-propanediol as the performance index. Inequality path constraints involved in the optimal control problem are transformed into a group of end-point constraints by introducing an auxiliary hybrid system. The original optimal control problem is associated with a family of approximation problems. The gradients of the cost functional and the end-point constraint functions are derived from the parametric sensitivity system. On this basis, we construct a gradient-based algorithm to solve the approximation problems. Numerical results show that the productivity of 1,3-propanediol can be increased considerably by employing our optimal control policy

Evaluation of microbial systems for bioremediation of petroleum refinery effluents in Nigeria

The potential of various organisms to catabolize and metabolize organic compounds has been recognized as potentially effective means of disposing of hazardous wastes. Phenolic compounds has long been recognized as one of the most recalcitrant and persistent substance in petroleum refinery effluents. This is a cause of some concern because of the high toxicity and of this compound. Bioremediation of phenolic compounds has been recognized as a potential solution for the disposal of phenolic compounds due to its scale ability, cost effectiveness and simplicity. The two species of Pseudomonas, P. aeruginosa and P. fluorescence were studied for their bioremediation potential on Refinery effluent with respect to phenol biodegradation in a batch reactor. Phenol was degraded completely by the two species. While P. aeruginosa completely mineralize phenol at the 60th hour of cultivation, only 75% (23 mg/l) of phenol was degraded by P. fluorescence; complete degradation was achieved at the 84th hour of fermentation. There was highly positive correlation between phenol biodegradation and the microbial growth. (r = +0.994 and r = +0.980 at

Simulation and optimization of dynamic flux balance analysis models using an interior point method reformulation

This work presents a novel, differentiable, way of solving dynamic Flux Balance Analysis (dFBA) problems by embedding flux balance analysis of metabolic network models within lumped bulk kinetics for biochemical processes. The proposed methodology utilizes transformation of the bounds of the embedded linear programming problem of flux balance analysis via a logarithmic barrier (interior point) approach. By exploiting the first-order optimality conditions of the interior-point problem, and with further transformations, the approach results in a system of implicit ordinary differential equations. Results from four case studies, show that the CPU and wall-times obtained using the proposed method are competitive with existing state-of-the-art approaches for solving dFBA simulations, for problem sizes up to genome-scale. The differentiability of the proposed approach allows, using existing commercial packages, its application to the optimal control of dFBA problems at a genome-scale size, thus outperforming existing formulations as shown by two dynamic optimization case studies.• R. Conejeros would like to thank CONICYT’s research grant FONDECYT 1151295 for funding this research. • F. Scott gratefully acknowledges financial support from CONICYT (Proyectos REDES ETAPA INICIAL, Convocatoria 2017, REDI170254)

Flavour formation in continuous fermentations

Fundação para a Ciência e a Tecnologia (FCT

Very high gravity bioethanol revisited: main challenges and advances

Over the last decades, the constant growth of the world-wide industry has been leading to more and more concerns with its direct impact on greenhouse gas (GHG) emissions. Resulting from that, rising efforts have been dedicated to a global transition from an oil-based industry to cleaner biotechnological processes. A specific example refers to the production of bioethanol to substitute the traditional transportation fuels. Bioethanol has been produced for decades now, mainly from energy crops, but more recently, also from lignocellulosic materials. Aiming to improve process economics, the fermentation of very high gravity (VHG) mediums has for long received considerable attention. Nowadays, with the growth of multi-waste valorization frameworks, VHG fermentation could be crucial for bioeconomy development. However, numerous obstacles remain. This work initially presents the main aspects of a VHG process, giving then special emphasis to some of the most important factors that traditionally affect the fermentation organism, such as nutrients depletion, osmotic stress, and ethanol toxicity. Afterwards, some factors that could possibly enable critical improvements in the future on VHG technologies are discussed. Special attention was given to the potential of the development of new fermentation organisms, nutritionally complete culture media, but also on alternative process conditions and configurations.This work has been carried out at the Biomass and Bioenergy Research Infrastructure (BBRI)- LISBOA-01-0145-FEDER-022059, supported by Operational Programme for Competitive ness and Internationalization (PORTUGAL2020), by Lisbon Portugal Regional Operational Pro gramme (Lisboa 2020) and by North Portugal Regional Operational Program (Norte 2020) under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) and has been supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 and through Project EcoTech (POCI-01-0145- FEDER-032206/ FAPESP 2018/07522-6) funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. The authors also acknowledge the financial support of Research Support Foundation of the state of Minas Gerais-FAPEMIG, National Counsel of Technological and Scientific Development-CNPq and Coordination for the Improvement of Higher Education Personnel-CAPES (Finance Code 001).info:eu-repo/semantics/publishedVersio