A linear optimal feedback control for producing 1,3-propanediol via microbial fermentation

In this paper, we consider a multistage feedback control strategy for the production of 1,3-propanediol(1,3-PD) in microbial fermentation. The feedback control strategy is widely used in industry, and to the best of our knowledge, this is the first time it is applied to 1,3-PD. The feedback control law is assumed to be linear of the concentrations of biomass and glycerol, and the coefficients in the controller are continuous. A multistage feedback control law is obtained by using the control parameterization method on the coefficient functions. Then, the optimal control problem can be transformed into an optimal parameter selection problem. The time horizon is partitioned adaptively. The corresponding gradients are derived, and finally, our numerical results indicate that the strategy is flexible and efficient

Kinetic models in industrial biotechnology - Improving cell factory performance

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed

Design of experiments for microbiological models

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Continuous Biochemical Processing: Investigating Novel Strategies to Produce Sustainable Fuels and Pharmaceuticals

Biochemical processing methods have been targeted as one of the potential renewable strategies for producing commodities currently dominated by the petrochemical industry. To design biochemical systems with the ability to compete with petrochemical facilities, inroads are needed to transition from traditional batch methods to continuous methods. Recent advancements in the areas of process systems and biochemical engineering have provided the tools necessary to study and design these continuous biochemical systems to maximize productivity and substrate utilization while reducing capital and operating costs. The first goal of this thesis is to propose a novel strategy for the continuous biochemical production of pharmaceuticals. The structural complexity of most pharmaceutical compounds makes chemical synthesis a difficult option, facilitating the need for their biological production. To this end, a continuous, multi-feed bioreactor system composed of multiple independently controlled feeds for substrate(s) and media is proposed to freely manipulate the bioreactor dilution rate and substrate concentrations. The optimal feed flow rates are determined through the solution to an optimal control problem where the kinetic models describing the time-variant system states are used as constraints. This new bioreactor paradigm is exemplified through the batch and continuous cultivation of β-carotene, a representative product of the mevalonate pathway, using Saccharomyces cerevisiae strain mutant SM14. The second goal of this thesis is to design continuous, biochemical processes capable of economically producing alternative liquid fuels. The large-scale, continuous production of ethanol via consolidated bioprocessing (CBP) is examined. Optimal process topologies for the CBP technology selected from a superstructure considering multiple biomass feeds, chosen from those available across the United States, and multiple prospective pretreatment technologies. Similarly, the production of butanol via acetone-butanol-ethanol (ABE) fermentation is explored using process intensification to improve process productivity and profitability. To overcome the inhibitory nature of the butanol product, the multi-feed bioreactor paradigm developed for pharmaceutical production is utilized with in situ gas stripping to simultaneously provide dilution effects and selectively remove the volatile ABE components. Optimal control and process synthesis techniques are utilized to determine the benefits of gas stripping and design a butanol production process guaranteed to be profitable

Modelling of batch dextransucrase production

This study concerns an industrial enzyme-producing fermentation process. The bacterium Leuconostoc mesenteroides grows in a sucrose-containing medium to produce dextransucrase, an extracellular enzyme used to convert sucrose to dextran. This microbially produced biopolymer has unique properties of medicinal use. [Continues.

Bioprocess Monitoring and Control

Process monitoring and control are fundamental to all processes; this holds especially for bioprocesses, due to their complex nature. Usually, bioprocesses deal with living cells, which have their own regulatory systems. It helps to adjust the cell to its environmental condition. This must not be the optimal condition that the cell needs to produce whatever is desired. Therefore, a close monitoring of the cell and its environment is essential to provide optimal conditions for production. Without measurement, no information of the current process state is obtained. In this book, methods and techniques are provided for the monitoring and control of bioprocesses. From new developments for sensors, the application of spectroscopy and modelling approaches, the estimation and observer implementation for ethanol production and the development and scale-up of various bioprocesses and their closed loop control information are presented. The processes discussed here are very diverse. The major applications are cultivation processes, where microorganisms were grown, but also an incubation process of bird’s eggs, as well as an indoor climate control for humans, will be discussed. Altogether, in 12 chapters, nine original research papers and three reviews are presented

Structured monitoring of gas exchange in fermenters for control

Information from measurements made by on-line sensors are, directly or indirectly, critical to strategies for improved monitoring and control of industrial fermentations. Over the past 20 years, a large body of research has, with little success, attempted to expand the library of on-line measurements routinely used in industrial fermentation. Partly as a result, research efforts have increasingly been targeted at the development of models incorporating on-line data, that describe the dme-profiles of unmeasurable variables of importance to fermentation monitoring. Due to the complexity of most of these models, industrial applications have largely been limited to the simplest of empirical models, based around "derived variables" (that derive directly from one or more on-line measurements), most of them associated with gas exchange, examples being the carbon dioxide evolution rate (CER) and respiratory quotient (RQ). Improvements in the conditioning, analysis and application of gas exchange data would, therefore, be of considerable benefit in improved monitoring, modelling and control of fermentation. This project examines opportunities for such improvements. It was shown that the oxygen transfer rate (OTR) data contain a significant component of uncorrelated Gaussian noise arising from their calculation as a small difference between two large numbers. A chi-square filter was used to frt a linear model to a reduced data set containing only the most recent OTR data, in order to remove this noise. The benefits of applying such a filter were illustrated by the improvement in the quality of OTR data, and related derived variables (the mass transfer coefficient, KLO2a, and the respiratory quotient, RQ), during a Streptomyces clavuligerus fermentation. Theoretical work supported the view that carbon dioxide transfer can be treated as a purely liquid-film limited physical process, as for oxygen. Concerning the error involved in the (widely-used) assumption that the dissolved CO2 partial pressure is equal to the CO2 partial pressure in the exit gas, practical factors were shown to limit the maximum error possible. This error varies with KLO2a, and the aeration rate, being 20-30% in small fermentors, and less in large fermentors. The theoretical results were supported with experimental data from Escherichia coli fermentations. For fermentations run above pH 6.5, the high effective solubility of dissolved carbon dioxide can cause changes in the pH and CER to make unsteady-state terms in the CO2 mass balance important. An effect is to cause the "measured respiratory quotient" as apparent from gas analyses (called here the transfer quotient, or TQ) to differ from the real underlying respiratory quotient (RQ). A model to predict such effects agreed well with experimental results from fermentations of E. coli and S. clavuligerus. The control of pH by on-off additions of acid or base introduces regular fluctuations into the TQ that are not present in the underlying RQ. During exponential growth, the TQ is smaller than the RQ. The RQ can be estimated on-line from the TQ using the model developed. It was shown, both from theory and during an E. coli fermentation, that a simple ratio controller could control the partial pressure of dissolved CO2 to an approximately constant value