A new approach for finding smooth optimal feeding profiles in fed-batch fermentations

Identification of optimal flow rate for culture media, cell density, and oxygen toward maximization of virus production in a fed-batch baculovirus-insect cell system

In recent times, it has been realized that novel vaccines are required to combat emerging disease outbreaks, and faster optimization is required to respond to global vaccine demands. Although, fed-batch operations offer better productivity, experiment-based optimization of a new fed-batch process remains expensive and time-consuming. In this context, we propose a novel computational framework that can be used for process optimization and control of a fed-batch baculovirus-insect cell system. Since the baculovirus expression vector system (BEVS) is known to be widely used platforms for recombinant protein/vaccine production, we chose this system to demonstrate the identification of optimal profile. Toward this, first, we constructed a mathematical model that captures the time course of cell and virus growth in a baculovirus-insect cell system. Second, the proposed model was used for numerical analysis to determine the optimal operating profiles of control variables such as culture media, cell density, and oxygen based on a multiobjective optimal control formulation. Third, a detailed comparison between batch and fed-batch culture was perfromed along with a comparison between various alternatives of fed-batch operation. Finally, we demonstrate that a model-based quantification of controlled feed addition in fed-batch culture is capable of providing better productivity as compared to a batch culture. The proposed framework can be utilized for the estimation of optimal operating regions of different control variables to achieve maximum infected cell density and virus yield while minimizing the substrate/media, uninfected cell, and oxygen consumption.

Challenges and opportunities for engineered Escherichia coli as a pivotal chassis toward versatile tyrosine-derived chemicals production

Growing concerns over limited fossil resources and associated environmental problems are motivating the development of sustainable processes for the production of high-volume fuels and high-value-added compounds. The shikimate pathway, an imperative pathway in most microorganisms, is branched with tyrosine as the rate-limiting step precursor of valuable aromatic substances. Such occurrence suggests the shikimate pathway as a promising route in developing microbial cell factories with multiple applications in the nutraceutical, pharmaceutical, and chemical industries. Therefore, an increasing number of studies have focused on this pathway to enable the biotechnological manufacture of pivotal and versatile aromatic products. With advances in genome databases and synthetic biology tools, genetically programmed Escherichia coli strains are gaining immense interest in the sustainable synthesis of chemicals. Engineered E. coli is expected to be the next bio-successor of fossil fuels and plants in commercial aromatics synthesis. This review summarizes successful and applicable genetic and metabolic engineering strategies to generate new chassis and engineer the iterative pathway of the tyrosine route in E. coli, thus addressing the opportunities and current challenges toward the realization of sustainable tyrosine-derived aromatics.

Production of L (+) Lactic Acid by Lactobacillus casei Ke11: Fed Batch Fermentation Strategies

Lactic acid and its derivatives are widely used in pharmaceutical, leather, textile and food industries. However, until now there have been few systematic reports on fed-batch fermentation for efficient production and high concentration of l-lactic acid by lactic acid bacteria. This study describes the obtainment of L (+) lactic acid from sucrose using the Lactobacillus casei Ke11 strain through different feeding strategies using an accessible pH neutralizer such as CaCO3. The exponential feeding strategy can increase lactic acid production and productivity (175.84 g/L and 3.74 g/L/h, respectively) with a 95% yield, avoiding inhibition by high initial substrate concentration and, combined with the selected agent controller, avoids the cellular stress that could be caused by the high osmotic pressure of the culture media. The purification of the acid using charcoal and celite, followed by the use of a cation exchange column proved to be highly efficient, allowing a high yield of lactic acid, high removal of sugars and proteins. The described process shows great potential for the production of lactic acid, as well as the simple, efficient and low-cost purification method. This way, this work is useful to the large-scale fermentation of L. casei Ke11 for production of l-lactic acid.

State estimation and nonlinear tracking control simulation approach. Application to a bioethanol production system

Tracking control of specific variables is key to achieve a proper fermentation. This paper analyzes a fed-batch bioethanol production process. For this system, a controller design based on linear algebra is proposed. Moreover, to achieve a reliable control, on-line monitoring of certain variables is needed. In this sense, for unmeasurable variables, state estimators based on Gaussian processes are designed. Cell, ethanol and glycerol concentrations are predicted with only substrates measurement. Simulation results when the controller and estimators are coupled, are shown. Furthermore, the algorithms were tested with parametric uncertainties and disturbances in the control action, and are compared, in all cases, with neural networks estimators (previous work). Bayesian estimators show a performance improvement, which is reflected in a decrease of the total error. Proposed techniques give reliable monitoring and control tools, with a low computational and economic cost, and less mathematical complexity than neural network estimators.

Establishing a Robust Manufacturing Platform for Recombinant Veterinary Vaccines: An Adenovirus-Vector Vaccine to Control Newcastle Disease Virus Infections of Poultry in Sub-Saharan Africa

Developing vaccine technology platforms to respond to pandemic threats or zoonotic diseases is a worldwide high priority. The risk of infectious diseases transmitted from wildlife and domestic animals to humans makes veterinary vaccination and animal health monitoring highly relevant for the deployment of public health global policies in the context of “one world, one health” principles. Sub-Saharan Africa is frequently impacted by outbreaks of poultry diseases such as avian influenza and Newcastle Disease (ND). Here, an adenovirus-vectored vaccine technology platform is proposed for rapid adaptation to ND or other avian viral threats in the region. Ethiopian isolates of the Newcastle Disease virus (NDV) were subjected to sequence and phylogenetic analyses, enabling the construction of antigenically matched vaccine candidates expressing the fusion (F) and hemagglutinin-neuraminidase (HN) proteins. A cost-effective vaccine production process was developed using HEK293 cells in suspension and serum-free medium. Productive infection in bioreactors (1–3 L) at 2 × 10⁶ cells/mL resulted in consistent infectious adenoviral vector titers of approximately 5–6 × 10⁸ TCID₅₀/mL (approximately 10¹¹VP/mL) in the harvest lysates. Groups of chickens were twice immunized with 1 × 10¹⁰ TCID₅₀ of the vectors, and full protection against a lethal NDV challenge was provided by the vector expressing the F antigen. These results consolidate the basis for a streamlined and scalable-vectored vaccine manufacturing process for deployment in low- and medium-income countries.

Application of process system engineering tools to the fed-batch production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) from a vinasses-molasses Mixture

Fed-batch production of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) copolymer using vinasses-molasses mixture is carried out in this work by implementing different process systems engineering tools. Two fed-batch strategies are tested experimentally at 5 L scale, considering only offline information: (1) offline optimizing control and (2) exponential feeding. Application of these strategies showed that different feeding profiles result in different dynamic behaviour, influencing both, yield and biopolymer properties. As offline-based feeding strategies do not consider information of the culture status, they cannot deal with uncertainties. Therefore, a closed loop control strategy was implemented, which uses biomass and substrate information predicted online by soft-sensors. Results demonstrated the technical feasibility to produce biopolymer using a 75/25%vol. vinasses-molasses mixture. Successful implementation of the soft-sensor-based control strategy was evidenced at pilot plant scale, where sugar concentration was kept almost constant for 14 h, while obtaining the desired copolymer. Thus, proposed control strategy could be of interest at industrial-scale.

Production optimization for concentration and volume-limited fed-batch reactors in biochemical processes

Since a very slight violation of constraint could cause process safety and product quality problems in biochemical processes, an adaptive approach of fed-batch reactor production optimization that can strictly satisfy constraints over the entire operating time is presented. In this approach, an improved smooth function is proposed such that the inequality constraints can be transformed into smooth constraints. Based on this, only an auxiliary state is needed to monitor violations in the augmented performance index. Combined with control variable parameterization (CVP), the dynamic optimization is executed and constraint violations are examined by calculating the sensitivities of states to ensure that the inequality constraints are satisfied everywhere inside the time interval. Three biochemical production optimization problems, including the manufacturing of ethanol, penicillin and protein, are tested as illustrations. Meanwhile, comparisons with pure penalty CVP method, famous dynamic optimization toolbox DOTcvp and literature results are carried out. Research results show that the proposed method achieves better performances in terms of optimization accuracy and computation cost.