Valine feeding reduces ammonia production through rearrangement of metabolic fluxes in central carbon metabolism of CHO cells.

Ammonia is a toxic byproduct of CHO cell metabolism, which inhibits cell growth, reduces cell viability, alters glycosylation, and decreases recombinant protein productivity. In an attempt to minimize the ammonium accumulation in cell culture media, different amino acids were added individually to the culture medium before the production phase to alleviate the negative effects of ammonium on cell culture performance. Among all the amino acids examined in this study, valine showed the most positive impact on CHO cell culture performance. When the cultured CHO cells were fed with 5 mM valine, EPO titer was increased by 25% compared to the control medium, and ammonium and lactate production were decreased by 23 and 26%, respectively, relative to the control culture. Moreover, the sialic acid content of the EPO protein in valine-fed culture was higher than in the control culture, most likely because of the lower ammonium concentration. Flux balance analysis (FBA) results demonstrated that the citric acid cycle was enriched by valine feeding. The measurement of TCA cycle activity supported this finding. The analysis revealed that there might be a link between promoting tricarboxylic acid (TCA) cycle metabolism in valine-fed culture and reduction in lactate and ammonia accumulation. Furthermore, in valine-fed culture, FBA outcomes showed that alanine was excreted into the medium as the primary mechanism for reducing ammonium concentration. It was predicted that the elevated TCA cycle metabolism was concurrent with an increment in recombinant protein production. Taken together, our data demonstrate that valine addition could be an effective strategy for mitigating the negative impacts of ammonium and enhancing glycoprotein production in both quality and quantity. KEY POINTS: • Valine feeding can mitigate the negative impacts of ammonia on CHO cell growth. • Valine addition assists the ammonia removal mechanism by enriching the TCA cycle. • Ammonia is removed from the media through alanine excretion in valine-fed culture.

Synergisms of machine learning and constraint-based modeling of metabolism for analysis and optimization of fermentation parameters.

Recent noteworthy advances in developing high-performing microbial and mammalian strains have enabled the sustainable production of bio-economically valuable substances such as bio-compounds, biofuels, and biopharmaceuticals. However, to obtain an industrially viable mass-production scheme, much time and effort are required. The robust and rational design of fermentation processes requires analysis and optimization of different extracellular conditions and medium components, which have a massive effect on growth and productivity. In this regard, knowledge- and data-driven modeling methods have received much attention. Constraint-based modeling (CBM) is a knowledge-driven mathematical approach that has been widely used in fermentation analysis and optimization due to its ability to predict the cellular phenotype from genotype through high-throughput means. On the other hand, machine learning (ML) is a data-driven statistical method that identifies the data patterns within sophisticated biological systems and processes, where there is inadequate knowledge to represent underlying mechanisms. Furthermore, ML models are becoming a viable complement to constraint-based models in a reciprocal manner when one is used as a pre-step of another. As a result, a more predictable model is produced. This review highlights the applications of CBM and ML independently and the combination of these two approaches for analyzing and optimizing fermentation parameters.

An integrated modular framework for modeling the effect of ammonium on the sialylation process of monoclonal antibodies produced by CHO cells.

BACKGROUND: Monoclonal antibodies (mABs) have emerged as one of the most important therapeutic recombinant proteins in the pharmaceutical industry. Their immunogenicity and therapeutic efficacy are influenced by post-translational modifications, specifically the glycosylation process. Bioprocess conditions can influence the intracellular process of glycosylation. Among all the process conditions that have been recognized to affect the mAB glycoforms, the detailed mechanism underlying how ammonium could perturb glycosylation remains to be fully understood. It was shown that ammonium induces heterogeneity in protein glycosylation by altering the sialic acid content of glycoproteins. Hence, understanding this mechanism would aid pharmaceutical manufacturers to ensure consistent protein glycosylation. METHODS: Three different mechanisms have been proposed to explain how ammonium influences the sialylation process. In the first, the inhibition of CMP-sialic acid transporter, which transports CMP-sialic acid (sialylation substrate) into the Golgi, by an increase in UDP-GlcNAc content that is brought about by the augmented incorporation of ammonium into glucosamine formation. In the second, ammonia diffuses into the Golgi and raises its pH, thereby decreasing the sialyltransferase enzyme activity. In the third, the reduction of sialyltransferase enzyme expression level in the presence of ammonium. We employed these mechanisms in a novel integrated modular platform to link dynamic alteration in mAB sialylation process with extracellular ammonium concentration to elucidate how ammonium alters the sialic acid content of glycoproteins. RESULTS: Our results show that the sialylation reaction rate is insensitive to the first mechanism. At low ammonium concentration, the second mechanism is the controlling mechanism in mAB sialylation and by increasing the ammonium level (< 8 mM) the third mechanism becomes the controlling mechanism. At higher ammonium concentrations (> 8 mM) the second mechanism becomes predominant again. CONCLUSION: The presented model in this study provides a connection between extracellular ammonium and the monoclonal antibody sialylation process. This computational tool could help scientists to develop and formulate cell culture media. The model illustrated here can assist the researchers to select culture media that ensure consistent mAB sialylation.

Systems biology approach in the formulation of chemically defined media for recombinant protein overproduction.

The cell culture medium is an intricate mixture of components which has a tremendous effect on cell growth and recombinant protein production. Regular cell culture medium includes various components, and the decision about which component should be included in the formulation and its optimum amount is an underlying issue in biotechnology industries. Applying conventional techniques to design an optimal medium for the production of a recombinant protein requires meticulous and immense research. Moreover, since the medium formulation for the production of one protein could not be the best choice for another protein, hence, the most suitable media should be determined for each recombinant cell line. Accordingly, medium formulation becomes a laborious, time-consuming, and costly process in biomanufacturing of recombinant protein, and finding alternative strategies for medium development seems to be crucial. In silico modeling is an attractive concept to be adapted for medium formulation due to its high potential to supersede laboratory examinations. By emerging the high-throughput datasets, scientists can disclose the knowledge about the effect of medium components on cell growth and metabolism, and via applying this information through systems biology approach, medium formulation optimization could be accomplished in silico with no need of significant amount of experimentation. This review demonstrates some of the applications of systems biology as a powerful tool for medium development and illustrates the effect of medium optimization with system-level analysis on the production of recombinant proteins in different host cells.

Bimodal electricity generation and aromatic compounds removal from purified terephthalic acid plant wastewater in a microbial fuel cell.

Wastewater of purified terephthalic acid (PTA) from a petrochemical plant was examined in a membrane-less single chamber microbial fuel cell for the first time. Time course of voltage during the cell operation cycle had two steady phases, which refers to the fact that metabolism of microorganisms was shifted from highly to less biodegradable carbon sources. The produced power density was 31.8 mW m(-2) (normalized per cathode area) and the calculated coulombic efficiency was 2.05 % for a COD removal of 74 % during 21 days. The total removal rate of different pollutants in the PTA wastewater was observed in the following order: (acetic acid) > (benzoic acid) > (phthalic acid) > (terephthalic acid) > (p-toluic acid). The cyclic voltammetry results revealed that the electron transfer mechanism was dominated by mediators which were produced by bacteria.

Simultaneous decolorization and bioelectricity generation in a dual chamber microbial fuel cell using electropolymerized-enzymatic cathode.

Effect of cathodic enzymatic decolorization of reactive blue 221 (RB221) on the performance of a dual-chamber microbial fuel cell (MFC) was investigated. Immobilized laccase on the surface of a modified graphite electrode was used in the cathode compartment in order to decolorize the azo dye and enhance the oxygen reduction reaction. First, methylene blue which is an electroactive polymer was electropolymerized on the surface of a graphite bar to prepare the modified electrode. Utilization of the modified electrode with no enzyme in the MFC increased the power density up to 57% due to the reduction of internal resistance from 1000 to 750 Ω. Using the electropolymerized-enzymatic cathode resulted in 65% improvement of the power density and a decolorization efficiency of 74%. Laccase could act as a biocatalyst for oxygen reduction reaction along with catalyzing RB221 decolorization. Treatment of RB221 with immobilized laccase reduced its toxicity up to 5.2%. Degradation products of RB221 were identified using GC-MS, and the decomposition pathway was proposed. A discussion was also provided as to the mechanism of dye decolorization on the enhancement of the MFC performance.

Amperometric sulfide detection using Coprinus cinereus peroxidase immobilized on screen printed electrode in an enzyme inhibition based biosensor.

In the present work, an amperometric inhibition biosensor for the determination of sulfide has been fabricated by immobilizing Coprinus cinereus peroxidase (CIP) on the surface of screen printed electrode (SPE). Chitosan/acrylamide was applied for immobilization of peroxidase on the working electrode. The amperometric measurement was performed at an applied potential of -150 mV versus Ag/AgCl with a scan rate of 100 mV in the presence of hydroquinone as electron mediator and 0.1M phosphate buffer solution of pH 6.5. The variables influencing the performance of sensor including the amount of substrate, mediator concentration and electrolyte pH were optimized. The determination of sulfide can be achieved in a linear range of 1.09-16.3 µM with a detection limit of 0.3 µM. Developed sensor showed quicker response to sulfide compared to the previous developed sulfide biosensors. Common anions and cations in environmental water did not interfere with sulfide detection by the developed biosensor. Cyanide interference on the enzyme inhibition caused 43.25% error in the calibration assay which is less than the amounts reported by previous studies. Because of high sensitivity and the low-cost of SPE, this inhibition biosensor can be successfully used for analysis of environmental water samples.