Tryptophan Production Maximization in a Fed-Batch Bioreactor with Modified E. coli Cells, by Optimizing Its Operating Policy Based on an Extended Structured Cell Kinetic Model

Hybrid kinetic models, linking structured cell metabolic processes to the dynamics of macroscopic variables of the bioreactor, are more and more used in engineering evaluations to derive more precise predictions of the process dynamics under variable operating conditions. Depending on the cell model complexity, such a math tool can be used to evaluate the metabolic fluxes in relation to the bioreactor operating conditions, thus suggesting ways to genetically modify the microorganism for certain purposes. Even if development of such an extended dynamic model requires more experimental and computational efforts, its use is advantageous. The approached probative example refers to a model simulating the dynamics of nanoscale variables from several pathways of the central carbon metabolism (CCM) of E. coli cells, linked to the macroscopic state variables of a fed-batch bioreactor (FBR) used for the tryptophan (TRP) production. The used E. coli strain was modified to replace the PTS system for glucose (GLC) uptake with a more efficient one. The study presents multiple elements of novelty: (i) the experimentally validated modular model itself, and (ii) its efficiency in computationally deriving an optimal operation policy of the FBR.

Effect of Nickel as Stress Factor on Phenol Biodegradation by Stenotrophomonas maltophilia KB2

This study focuses on the phenol biodegradation kinetics by Stenotrophomonas maltophilia KB2 in a nickel-contaminated medium. Initial tests proved that a nickel concentration of 33.3 mg·L−1 caused a cessation of bacterial growth. The experiments were conducted in a batch bioreactor in several series: without nickel, at constant nickel concentration and at varying metal concentrations (1.67–13.33 g·m−3). For a constant Ni2+ concentration (1.67 or 3.33 g·m−3), a comparable bacterial growth rate was obtained regardless of the initial phenol concentration (50–300 g·m−3). The dependence µ = f (S0) at constant Ni2+ concentration was very well described by the Monod equations. The created varying nickel concentrations experimental database was used to estimate the parameters of selected mathematical models, and the analysis included different methods of determining metal inhibition constant KIM. Each model showed a very good fit with the experimental data (R2 values were higher than 0.9). The best agreement (R2 = 0.995) was achieved using a modified Andrews equation, which considers the metal influence and substrate inhibition. Therefore, kinetic equation parameters were estimated: µmax = 1.584 h−1, KS = 185.367 g·m−3, KIS = 106.137 g·m−3, KIM = 1.249 g·m−3 and n = 1.0706.

Influence of B. subtilis 3NA mutations in spo0A and abrB on surfactin production in B. subtilis 168

Background Bacillus subtilis is a well-established host for a variety of bioproduction processes, with much interest focused on the production of biosurfactants such as the cyclic lipopeptide surfactin. Surfactin production is tightly intertwined with quorum sensing and regulatory cell differentiation processes. As previous studies have shown, a non-sporulating B. subtilis strain 3NA encoding a functional sfp locus but mutations in the spo0A and abrB loci, called JABs32, exhibits noticeably increased surfactin production capabilities. In this work, the impacts of introducing JABs32 mutations in the genes spo0A, abrB and abh from 3NA into strain KM1016, a surfactin-forming derivative of B. subtilis 168, was investigated. This study aims to show these mutations are responsible for the surfactin producing performance of strain JABs32 in fed-batch bioreactor cultivations. Results Single and double mutant strains of B. subtilis KM1016 were constructed encoding gene deletions of spo0A, abrB and homologous abh. Furthermore, an elongated abrB version, called abrB*, as described for JABs32 was integrated. Single and combinatory mutant strains were analysed in respect of growth behaviour, native PsrfA promoter expression and surfactin production. Deletion of spo0A led to increased growth rates with lowered surfactin titers, while deletion or elongation of abrB resulted in lowered growth rates and high surfactin yields, compared to KM1016. The double mutant strains B. subtilis KM1036 and KM1020 encoding Δspo0A abrB* and Δspo0A ΔabrB were compared to reference strain JABs32, with KM1036 exhibiting similar production parameters and impeded cell growth and surfactin production for KM1020. Bioreactor fed-batch cultivations comparing a Δspo0A abrB* mutant of KM1016, KM681, with JABs32 showed a decrease of 32% in surfactin concentration. Conclusions The genetic differences of B. subtilis KM1016 and JABs32 give rise to new and improved fermentation methods through high cell density processes. Deletion of the spo0A locus was shown to be the reason for higher biomass concentrations. Only in combination with an elongation of abrB was this strain able to reach high surfactin titers of 18.27 g L−1 in fed-batch cultivations. This work shows, that a B. subtilis strain can be turned into a high cell density surfactin production strain by introduction of two mutations.

An Improved Robust Adaptive Controller for a Fed-Batch Bioreactor with Input Saturation and Unknown Varying Control Gain via Dead-Zone Quadratic Forms

In this work, a new adaptive controller is designed for substrate control of a fed-batch bioreactor in the presence of input saturation and unknown varying control gain with unknown upper and lower bounds. The output measurement noise and the unknown varying nature of reaction rate and biomass concentration and water volume are also handled. The design is based on dead zone quadratic forms. The designed controller ensures the convergence of the modified tracking error and the boundedness of the updated parameters. As the first distinctive feature, a new robust adaptive auxiliary system is proposed in order to tackle input saturation and control gain uncertainty. As the second distinctive feature, the modified tracking error converges to a compact region whose bound is user-defined, in contrast to related studies where the convergence region depends on upper bounds of either external disturbances, system states, model parameters or terms and model parameter values. Simulations confirm the properties of the closed loop behavior.

Dynamic Modeling of the Impact of Temperature Changes on CO2 Production during Milk Fermentation in Batch Bioreactors

Knowledge of the mathematical models of the fermentation processes is indispensable for their simulation and optimization and for the design and synthesis of the applicable control systems. The paper focuses on determining a dynamic mathematical model of the milk fermentation process taking place in a batch bioreactor. Models in the literature describe milk fermentation in batch bioreactors as an autonomous system. They do not enable the analysis of the effect of temperature changes on the metabolism during fermentation. In the presented extensive multidisciplinary study, we have developed a new mathematical model that considers the impact of temperature changes on the dynamics of the CO2 produced during fermentation in the batch bioreactor. Based on laboratory tests and theoretical analysis, the appropriate structure of the temperature-considered dynamic model was first determined. Next, the model parameters of the fermentation process in the laboratory bioreactor were identified by means of particle swarm optimization. Finally, the experiments with the laboratory batch bioreactor were compared with the simulations to verify the derived mathematical model. The developed model proved to be very suitable for simulations, and, above all, it enables the design and synthesis of a control system for batch bioreactors.

Adaptive Control of CO2 Production during Milk Fermentation in a Batch Bioreactor

The basic characteristic of batch bioreactors is their inability to inflow or outflow the substances during the fermentation process. This follows in the simple construction and maintenance, which is the significant advantage of batch bioreactors. Unfortunately, this characteristic also results in the inability of the current industrial and laboratory batch bioreactors to control fermentation production during the process duration. In some recent studies, it was shown that changing the temperature could influence the execution of the fermentation process. The presented paper shows that this phenomenon could be used to develop the closed-loop control system for the fermentation production control in batch bioreactors. First, based on theoretical work, experiments, and numerical methods, the appropriate structure of the mathematical model was determined and parameters were identified. Next, the closed-loop control system structure for batch bioreactor was proposed, and the linear and adaptive control system based on this structure and the derived and identified model were developed. Both modeling and adaptive control system design are new and represent original contributions. As expected, due to the non-linearity of the controlled plant, the adaptive control represents a more successful approach. The simulation and experimental results were used to confirm the applicability of the proposed solution.

The functional expression in yeast of two unusual acidic peroxygenases from Candolleomyces aberdarensis by adopting evolved secretion mutations

Fungal unspecific peroxygenases (UPOs) are emergent biocatalysts that perform highly selective C-H oxyfunctionalizations of organic compounds, yet their heterologous production at high levels is required for their practical use in synthetic chemistry. Here, we achieved functional expression in yeast of two new unusual acidic peroxygenases from Candolleomyces ( Psathyrella ) aberdarensis ( Pab UPO) and their production at large scale in bioreactor. Our strategy was based on adopting secretion mutations from Agrocybe aegerita UPO mutant −PaDa-I variant− designed by directed evolution for functional expression in yeast, which belongs to the same phylogenetic family as Pab UPOs –long-type UPOs− and that shares 65% sequence identity. After replacing the native signal peptides by the evolved leader sequence from PaDa-I, we constructed and screened site-directed recombination mutant libraries yielding two recombinant Pab UPOs with expression levels of 5.4 and 14.1 mg/L in S. cerevisiae . These variants were subsequently transferred to P. pastoris for overproduction in fed-batch bioreactor, boosting expression levels up to 290 mg/L with the highest volumetric activity achieved to date for a recombinant peroxygenase (60,000 U/L, with veratryl alcohol as substrate). With a broad pH activity profile, ranging from 2.0 to 9.0, these highly secreted, active and stable peroxygenases are promising tools for future engineering endeavors, as well as for their direct application in different industrial and environmental settings. IMPORTANCE In this work, we incorporated several secretion mutations from an evolved fungal peroxygenase to enhance the production of active and stable forms of two unusual acidic peroxygenases. The tandem-yeast expression system based on S. cerevisiae for directed evolution and P. pastoris for overproduction in a ∼300 mg/L scale, is a versatile tool to generate UPO variants. By employing this approach, we foresee that acidic UPO variants will be more readily engineered in the near future and adapted to practical enzyme cascade reactions that can be performed over a broad pH range to oxyfunctionalize a variety of organic compounds.