Dynamic metabolic modeling for a MAB bioprocess

Production of monoclonal antibodies (MAb) for diagnostic or therapeutic applications has become an important task in the pharmaceutical industry. The efficiency of high-density reactor systems can be potentially increased by model-based design and control strategies. Therefore, a reliable kinetic model for cell metabolism is required. A systematic procedure based on metabolic modeling is used to model nutrient uptake and key product formation in a MAb bioprocess during both the growth and post-growth phases. The approach combines the key advantages of stoichiometric and kinetic models into a complete metabolic network while integrating the regulation and control of cellular activity. This modeling procedure can be easily applied to any cell line during both the cell growth and post-growth phases. Quadratic programming (QP) has been identified as a suitable method to solve the underdetermined constrained problem related to model parameter identification. The approach is illustrated for the case of murine hybridoma cells cultivated in stirred spinners.     

Enzyme technology and bioprocess engineering

The impact of directed evolution and site-specific mutagenesis on the industrial utility of enzymatic catalysis through the modification of enzyme structure and function is clearly an important area of research in bioprocess engineering. High-throughput screening for novel or improved enzyme activities, both by more efficiently exploring nature's diversity and by creating new diversity in the test tube, allows new bioprocesses to be developed. Similarly, innovations in enzyme technology that address novel ways to apply enzymes in bioprocesses also have an impact on bioprocess engineering. Several recent developments have been made in this latter aspect of bioprocess engineering.     

Web-based education in bioprocess engineering

The combination of web technology, knowledge of bioprocess engineering, and theories on learning and instruction might yield innovative learning material for bioprocess engineering. In this article, an overview of the characteristics of web-based learning material is given, as well as guidelines for the design of learning material from theories of learning and instruction and from the bioprocess engineering domain. A diverse body of learning material is presented, which illustrates the application of these guidelines; this material has been developed during the past six years for different courses, mostly at undergraduate level, and it illustrates how web-based learning material can enable various different approaches to learning objectives that might improve overall learning. Such learning material has been used for several years in education, it has been evaluated with positive results, and is now part of the regular learning material for bioprocess engineering at Wageningen University.     

Improved E. coli erythromycin A production through the application of metabolic and bioprocess engineering

In this report, small-scale culture and bioreactor experiments were used to compare and improve the heterologous production of the antibiotic erythromycin A across a series of engineered prototype Escherichia coli strains. The original strain, termed BAP1(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4, pGro7), was designed to allow full erythromycin A biosynthesis from the exogenous addition of propionate. This strain was then compared against two alternatives hypothesized to increase final product titer. Strain TB3(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4, pGro7) is a derivative of BAP1 designed to increase biosynthetic pathway carbon flow as a result of a ygfH deletion; whereas, strain TB3(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4-2, pGro7) provided an extra copy of a key deoxysugar glycosyltransferase gene. Production was compared across the three strains with TB3(pBPJW130, pBPJW144, pHZT1, pHZT2, pHZT4, pGro7) showing significant improvement in erythronolide B (EB), 3-mycarosylerythronolide B (MEB), and erythromycin A titers. This strain was further tested in the context of batch bioreactor production experiments with time-course titers leveling at 4 mg/L, representing an approximately sevenfold increase in final erythromycin A titer.     

Metabolic and bioprocess engineering of the yeast Candida famata for FAD production

Flavins in the form of flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD) play an important role in metabolism as cofactors for oxidoreductases and other enzymes. Flavin nucleotides have applications in the food industry and medicine; FAD supplements have been efficiently used for treatment of some inheritable diseases. FAD is produced biotechnologically; however, this compound is much more expensive than riboflavin. Flavinogenic yeast Candida famata synthesizes FAD from FMN and ATP in the reaction catalyzed by FAD synthetase, a product of the FAD1 gene. Expression of FAD1 from the strong constitutive promoter TEF1 resulted in 7- to 15-fold increase in FAD synthetase activity, FAD overproduction, and secretion to the culture medium. The effectiveness of FAD production under different growth conditions by one of these recombinant strains, C. famata T-FD-FM 27, was evaluated. First, the two-level Plackett–Burman design was performed to screen medium components that significantly influence FAD production. Second, central composite design was adopted to investigate the optimum value of the selected factors for achieving maximum FAD yield. FAD production varied most significantly in response to concentrations of adenine, KH₂PO₄, glycine, and (NH₄)₂SO₄. Implementation of these optimization strategies resulted in 65-fold increase in FAD production when compared to the non-optimized control conditions. Recombinant strain that has been cultivated for 40 h under optimized conditions achieved a FAD accumulation of 451 mg/l. So, for the first time yeast strains overproducing FAD were obtained, and the growth media composition for maximum production of this nucleotide was designed.     

Marine bioprocess engineering: the missing link to commercialization

Success of US biotechnology has been and continues to be dependent on new discoveries and their timely transformation into useful products through bioprocess engineering and a systems approach. Bioprocess engineering is an essential element of ‘generic applied’ or ‘precompetitive’ research. For marine biotechnology, like biopharmaceutical biotechnology, bioprocess engineering represents the key. The many hundreds of tantalizing bioactive compounds discovered and isolated from varied marine organisms over the past decades have led to only minimal commercialization due to the limited availability of the compounds in question. To address international competitiveness and the revitalization of key US industries, the National Science Foundation launched the Engineering Research Centers Program in the mid 1980s. The essential feature of this program is a partnership among academia, industry and the government to develop next-generation technology through cutting-edge research, relevant education and innovative technology transfer. MarBEC (Marine Bioproducts Engineering Center) is a recently established multi-disciplinary engineering-science cooperative effort of the University of Hawaii and the University of California at Berkeley. Additional partners include three federal laboratories—Argonne National Laboratory, the Edgewood Research, Development and Engineering Center and the Eastern Regional Research Center of the US Department of Agriculture—and the Bishop Museum. MarBEC's research program consists of four major thrusts: Production Systems; Marine Bioproducts and Bioresources; Separation and Conversion; and Bioproduct Formulation.     

Constraints-based genome-scale metabolic simulation for systems metabolic engineering

Random mutagenesis and selection approaches used traditionally for the development of industrial strains have largely been complemented by metabolic engineering, which allows purposeful modification of metabolic and cellular characteristics by using recombinant DNA and other molecular biological techniques. As systems biology advances as a new paradigm of research thanks to the development of genome-scale computational tools and high-throughput experimental technologies including omics, systems metabolic engineering allowing modification of metabolic, regulatory and signaling networks of the cell at the systems-level is becoming possible. In silico genome-scale metabolic model and its simulation play increasingly important role in providing systematic strategies for metabolic engineering. The in silico genome-scale metabolic model is developed using genomic annotation, metabolic reactions, literature information, and experimental data. The advent of in silico genome-scale metabolic model brought about the development of various algorithms to simulate the metabolic status of the cell as a whole. In this paper, we review the algorithms developed for the system-wide simulation and perturbation of cellular metabolism, discuss the characteristics of these algorithms, and suggest future research direction.     

Inducible product gene expression technology tailored to bioprocess engineering

Bioprocess engineering has developed as a discipline to design optimal culture conditions and bioreactor operation protocols for production cell lines engineered for constitutive expression of desired protein pharmaceuticals. With the advent of heterologous gene regulation systems it has become possible to fine-tune expression of difficult-to-produce protein pharmaceuticals to optimal levels and to conditionally engineer cell metabolism for the best production performance. However, most of the small-molecules used to trigger expression of product or metabolic engineering product genes are incompatible with downstream processing regulations or process economics. Recent progress in product gene control design has resulted in the development of bioprocess-compatible regulation systems, which are responsive to physical parameters such as temperature or physiologic trigger molecules that are either an inherent part of host cell metabolism or intrinsic components of licensed protein-free cell culture media, such as redox status, vitamin H and gaseous acetaldehyde. While all of these systems have been shown to fine-tune product gene expression independent of the host cell metabolism some of them can be plugged into metabolic networks to capture critical physiologic parameters and convert them into an optimal production response. Assembly of individual product gene control modalities into synthetic networks has recently enabled construction of autonomously regulated time-delay or cell density-sensitive gene circuits, which trigger population-wide induction of product gene expression at a predefined time or culture density. We provide a comprehensive overview on the latest developments in the design of bioprocess-compatible product gene control systems.     

Computational tools for metabolic engineering

A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area.     

Stem cell bioprocess engineering towards cGMP production and clinical applications

Stem cells, including mesenchymal stem cells and pluripotent stem cells, are becoming an indispensable tool for various biomedical applications including drug discovery, disease modeling, and tissue engineering. Bioprocess engineering, targeting large scale production, provides a platform to generate a controlled microenvironment that could potentially recreate the stem cell niche to promote stem cell proliferation or lineage-specific differentiation. This survey aims at defining the characteristics of stem cell populations currently in use and the present-day limits in their applications for therapeutic purposes. Furthermore, a bioprocess engineering strategy based on bioreactors and 3-D cultures is discussed in order to achieve the improved stem cell yield, function, and safety required for production under current good manufacturing practices.     

Metabolic and bioprocess engineering for production of selenized yeast with increased content of seleno-methylselenocysteine

Specific Se-metabolites have been recognized to be the main elements responsible for beneficial effects of Se-enriched diet, and Se-methylselenocysteine (SeMCys) is thought to be among the most effective ones. Here we show that an engineered Saccharomyces cerevisiae strain, expressing a codon optimized heterologous selenocysteine methyltransferase and endowed with high intracellular levels of S-adenosyl-methionine, was able to accumulate SeMCys at levels higher than commercial selenized yeasts. A fine tuned carbon- and sulfate-limited fed-batch bioprocess was crucial to achieve good yields of biomass and SeMCys. Through the coupling of metabolic and bioprocess engineering we achieved a ～24-fold increase in SeMCys, compared to certified reference material of selenized yeast. In addition, we investigated the interplay between sulfur and selenium metabolism and the possibility that redox imbalance occurred along with intracellular accumulation of Se. Collectively, our data show how the combination of metabolic and bioprocess engineering can be used for the production of selenized yeast enriched with beneficial Se-metabolites.     

Applications of metabolic modeling to drive bioprocess development for the production of value-added chemicals

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput ‘omics’ data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.     

Multi-fold enhancement in vitamin E (alpha-tocopherol) production via integration of bioprocess optimisation and metabolic engineering in cell suspension of sunflower

Journal of Plant Biochemistry and Biotechnology - Alpha-tocopherol, a highly active form of the antioxidant vitamin E in humans, effectively scavenges free radicals and protects the cell membranes....     

Rapid sampling devices for metabolic engineering applications

A number of rapid sampling devices for metabolic engineering applications have been developed over the last years with the purpose of the estimation of in vivo metabolic concentrations and dynamics. This review outlines the designs and characteristics as well as the developments and changes in diverse approaches over the years. Primary performance parameters for these constructions are sampling time and rate and, for an accurate representation of the in vivo condition in cells, the reproducibility of results and easy handling throughout the sampling operation.     

Potential for metabolic engineering of resveratrol biosynthesis

Resveratrol, an interesting plant phenolic compound, is found in red wine but is not widely distributed in other common food sources. Health benefits of resveratrol include prevention of cardiovascular diseases and cancers, and--as discovered more recently--promotion of longevity in several animal systems. The pathway and enzymes for resveratrol biosynthesis are well characterized. Furthermore, metabolic engineering of this compound has been achieved in plants, microbes and animals. This review attempts to summarize current understanding of resveratrol pathway-engineering in various systems, to outline the challenges in commercial applications and to identify future opportunities for resveratrol bioengineering.     

Spatial organization of enzymes for metabolic engineering

As synthetic pathways built from exogenous enzymes become more complicated, the probability of encountering undesired interactions with host organisms increases, thereby lowering product titer. An emerging strategy to combat this problem is to spatially organize pathway enzymes into multi-protein complexes, where high local concentrations of enzymes and metabolites may enhance flux and limit problematic interactions with the cellular milieu. Co-localizing enzymes using synthetic scaffolds has improved titers for multiple pathways. While lacking physical diffusion barriers, scaffolded systems could concentrate intermediates locally through a mechanism analogous to naturally occurring microdomains. A more direct strategy for compartmentalizing pathway components would be to encapsulate them within protein shells. Several classes of shells have been loaded with exogenous proteins and expressed successfully in industrial hosts. A critical challenge for achieving ideal pathway compartmentalization with protein shells will likely be evolving pores to selectively limit intermediate diffusion. Eventually, these tools should enhance our ability to rationally design metabolic pathways.