Impact of aeration strategy on CHO cell performance during antibody production

Stirred tank bioreactors using suspension adapted mammalian cells are typically used for the production of complex therapeutic proteins. The hydrodynamic conditions experienced by cells within this environment have been shown to directly impact growth, productivity, and product quality and therefore an improved understanding of the cellular response is critical. Here we investigate the sub‐lethal effects of different aeration strategies on Chinese hamster ovary cells during monoclonal antibody production. Two gas delivery systems were employed to study the presence and absence of the air–liquid interface: bubbled direct gas sparging and a non‐bubbled diffusive silicone membrane system. Additionally, the effect of higher gas flow rate in the sparged bioreactor was examined. Both aeration systems were run using chemically defined media with and without the shear protectant Pluronic F‐68 (PF‐68). Cells were unable to grow with direct gas sparging without PF‐68; however, when a silicone membrane aeration system was implemented growth was comparable to the sparged bioreactor with PF‐68, indicating the necessity of shear protectants in the presence of bubbles. The cultures exposed to increased hydrodynamic stress were shown by flow cytometry to have decreased F‐actin intensity within the cytoskeleton and enter apoptosis earlier. This indicates that these conditions elicit a sub‐lethal physiological change in cells that would not be detected by the at‐line assays which are normally implemented during cell culture. These physiological changes only result in a difference in continuous centrifugation performance under high flow rate conditions. Product quality was more strongly affected by culture age than the hydrodynamic conditions tested. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2013.     

Enhancing operational stability and exhibition of enzyme activity by removing water in the immobilized lipase‐catalyzed production of erythorbyl laurate

Erythorbyl laurate was continuously synthesized by esterification in a packed‐bed enzyme reactor with immobilized lipase from Candida antarctica. Response surface methodology based on a five‐level three‐factor central composite design was adopted to optimize conditions for the enzymatic esterification. The reaction variables, such as reaction temperature (10–70°C), substrate molar ratio ([lauric acid]/[erythorbic acid], 5–15), and residence time (8–40 min) were evaluated and their optimum conditions were found to be 56.2°C, 14.3, and 24.2 min, respectively. Under the optimum conditions, the molar conversion yield was 83.4%, which was not significantly different (P < 0.05) from the value predicted (84.4%). Especially, continuous water removal by adsorption on an ion‐exchange resin in a packed‐bed enzyme reactor improved operational stability, resulting in prolongation of half‐life (2.02 times longer compared to the control without water‐removal system). Furthermore, in the case of batch‐type reactor, it exhibited significant increase in initial velocity of molar conversion from 1.58% to 2.04%/min. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:882–889, 2013     

Three‐dimensional neural differentiation of embryonic stem cells with ACM induction in microfibrous matrices in bioreactors

The clinical use of pluripotent stem cell (PSC)‐derived neural cells requires an efficient differentiation process for mass production in a bioreactor. Toward this goal, neural differentiation of murine embryonic stem cells (ESCs) in three‐dimensional (3D) polyethylene terephthalate microfibrous matrices was investigated in this study. To streamline the process and provide a platform for process integration, the neural differentiation of ESCs was induced with astrocyte‐conditioned medium without the formation of embryoid bodies, starting from undifferentiated ESC aggregates expanded in a suspension bioreactor. The 3D neural differentiation was able to generate a complex neural network in the matrices. When compared to 2D differentiation, 3D differentiation in microfibrous matrices resulted in a higher percentage of nestin‐positive cells (68% vs. 54%) and upregulated gene expressions of nestin, Nurr1, and tyrosine hydroxylase. High purity of neural differentiation in 3D microfibrous matrix was also demonstrated in a spinner bioreactor with 74% nestin + cells. This study demonstrated the feasibility of a scalable process based on 3D differentiation in microfibrous matrices for the production of ESC‐derived neural cells. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:1013–1022, 2013     

A dynamic metabolic flux balance based model of fed‐batch fermentation of bordetella pertussis

A mathematical model based on a dynamic metabolic flux balance (DMFB) is developed for a process of fed‐batch fermentation of Bordetella pertussis. The model is based on the maximization of growth rate at each time interval subject to stoichiometric constraints. The model is calibrated and verified with experimental data obtained in two different bioreactor experimental systems. It was found that the model calibration was mostly sensitive to the consumption or production rates of tyrosine and, for high supplementation rates, to the consumption rate of glutamate. Following this calibration the model correctly predicts biomass and by‐products concentrations for different supplementation rates. Comparisons of model predictions to oxygen uptake and carbon emission rates measurements indicate that the TCA cycle is fully functional. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 520–531, 2013     

Continuous rhamnolipid production using denitrifying Pseudomonas aeruginosa cells in hollow‐fiber bioreactor

Rhamnolipids are high‐value effective biosurfactants produced by Pseudomonas aeruginosa. Large‐scale production of rhamnolipids is still challenging especially under free‐cell aerobic conditions in which the highly foaming nature of the culture broth reduces the productivity of the process. Immobilized systems relying on oxygen as electron acceptor have been previously investigated but oxygen transfer limitation presents difficulties for continuous rhamnolipid production. A coupled system using immobilized cells and nitrate instead of oxygen as electron acceptor taking advantage of the ability of P. aeruginosa to perform nitrate respiration was evaluated. This denitrification‐based immobilized approach based on a hollow‐fiber setup eliminated the transfer limitation problems and was found suitable for continuous rhamnolipid production in a period longer than 1,500 h. It completely eliminated the foaming difficulties related to aerobic systems with a comparable specific productivity of 0.017 g/(g dry cells)‐h and allowed easy recovery of rhamnolipids from the cell‐free medium. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 346–351, 2013     

Dissecting the energy metabolism in Mycoplasma pneumoniae through genome‐scale metabolic modeling

Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint‐based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time‐dependent changes, albeit using a static model. By performing an in silico knock‐out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.     

Systematic identification of proteins that elicit drug side effects

Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large‐scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug–target relations to identify overrepresented protein–side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.     

Promoters maintain their relative activity levels under different growth conditions

Most genes change expression levels across conditions, but it is unclear which of these changes represents specific regulation and what determines their quantitative degree. Here, we accurately measured activities of ～900 S. cerevisiae and ～1800 E. coli promoters using fluorescent reporters. We show that in both organisms 60–90% of promoters change their expression between conditions by a constant global scaling factor that depends only on the conditions and not on the promoter's identity. Quantifying such global effects allows precise characterization of specific regulation—promoters deviating from the global scale line. These are organized into few functionally related groups that also adhere to scale lines and preserve their relative activities across conditions. Thus, only several scaling factors suffice to accurately describe genome‐wide expression profiles across conditions. We present a parameter‐free passive resource allocation model that quantitatively accounts for the global scaling factors. It suggests that many changes in expression across conditions result from global effects and not specific regulation, and provides means for quantitative interpretation of expression profiles.