Dielectric Spectroscopy and Optical Density Measurement for the Online Monitoring and Control of Recombinant Protein Production in Stably Transformed Drosophila melanogaster S2 Cells

Real-Time Auto Controlling of Viable Cell Density in Perfusion Cultivation Aided by In-Line Dielectric Spectroscopy With Segmented Adaptive PLS Model

Serving as a dedicated process analytical technology (PAT) tool for biomass monitoring and control, the capacitance probe, or dielectric spectroscopy, is showing great potential in robust pharmaceutical manufacturing, especially with the growing interest in integrated continuous bioprocessing. Despite its potential, challenges still exist in terms of its accuracy and applicability, particularly when it is used to monitor cells during stationary and decline phases. In this study, data pre-processing methods were first evaluated through cross-validation, where the first-order derivative emerged as the most effective method to diminish variability in prediction accuracy across different training datasets. Subsequently, a segmented adaptive partial least squares (SA-PLS) model was developed, and its accuracy and universality were demonstrated through several validation studies using different clones and culture processes. Furthermore, a real-time viable cell density (VCD) auto-control system in perfusion culture was established, where the VCD was maintained around the target with notable precision and robustness. This model enhanced the monitoring capabilities of capacitance-based PAT tools throughout the cultivation, expanded their application in cell-specific automatic control strategies, and contributed vitally to the advancement of continuous manufacturing paradigms.

Precise regulating the specific oxygen consumption rate to strengthen the CoQ10 biosynthesis by Rhodobater sphaeroides

Coenzyme Q10 (CoQ10) is the most consumed dietary supplement and mainly biosynthesized by aerobic fermentation of Rhodobacter sphaeroides (R. sphaeroides). Oxygen supply was identified as a bottleneck for improving CoQ10 yield in R. sphaeroides. In this study, a precise regulation strategy based on dielectric spectroscopy (DS) was applied to further improve CoQ10 biosynthesis by R. sphaeroide. First, a quantitative response model among viable cells, cell morphology, and oxygen uptake rate (OUR) was established. DS could be used to detect viable R. sphaeroides cells, and the relationship among cell morphology, CoQ10 biosynthesis, and OUR was found to be significant. Based on this model, the online specific oxygen consumption rate (QO2) control strategy was successfully applied to the CoQ10 fermentation process. QO2 controlled at 0.07 ± 0.01 × 10- 7mmol/cell/h was most favorable for CoQ10 biosynthesis, resulting in a 28.3% increase in CoQ10 production. Based on the multi-parameters analysis and online QO2 control, a precise online nutrient feeding strategy was established using conductivity detected by DS. CoQ10 production was improved by 35%, reaching 3384 mg/L in 50 L bioreactors. This online control strategy would be effectively applied for improving industrial CoQ10 production, and the precise fermentation control strategy could also be applied to other fermentation process.

Large-Scale Expansion of Human Liver Stem Cells Using Two Different Bioreactor Systems

The assessment of human liver stem cells (HLSCs) as cell therapeutics requires scalable, controlled expansion processes. We first focused on defining appropriate process parameters for HLSC expansion such as seeding density, use of antibiotics, optimal cell age and critical metabolite concentrations in conventional 2D culture systems. For scale-up, we transferred HLSC expansion to multi-plate and stirred-tank bioreactor systems to determine their limitations. A seeding density of 4000 cells cm-2 was needed for efficient expansion. Although growth was not significantly affected by antibiotics, the concentrations of lactate and ammonia were important. A maximum expansion capacity of at least 20 cumulative population doublings (cPDs) was observed, confirming HLSC growth, identity and functionality. For the expansion of HLSCs in the multi-plate bioreactor system Xpansion (XPN), the oxygen supply strategy was optimized due to a low kLa of 0.076 h-1. The XPN bioreactor yielded a final mean cell density of 94 ± 8 × 103 cells cm-2, more than double that of the standard process in T-flasks. However, in the larger XPN50 device, HLSC density reached only 28 ± 0.9 × 103 cells cm-2, while the glucose consumption rate increased 8-fold. In a fully-controlled 2 L stirred-tank bioreactor (STR), HLSCs expanded at a comparable rate to the T-flask and XPN50 processes in a homogeneous microenvironment using advanced process analytical technology. Ultimately, the scale-up of HLSCs was successful using two different bioreactor systems, resulting in sufficient numbers of viable, functional and undifferentiated HLSCs for therapeutic applications.

Multivariate data analysis on multisensor measurement for inline process monitoring of adenovirus production in HEK293 cells

In the era of Biopharma 4.0, process digitalization fundamentally requires accurate and timely monitoring of critical process parameters (CPPs) and quality attributes. Bioreactor systems are equipped with a variety of sensors to ensure process robustness and product quality. However, during the biphasic production of viral vectors or replication-competent viruses for gene and cell therapies and vaccination, current monitoring techniques relying on a single working sensor can be affected by the physiological state change of the cells due to infection/transduction/transfection step required to initiate production. To address this limitation, a multisensor (MS) monitoring system, which includes dual-wavelength fluorescence spectroscopy, dielectric signals, and a set of CPPs, such as oxygen uptake rate and pH control outputs, was employed to monitor the upstream process of adenovirus production in HEK293 cells in bioreactor. This system successfully identified characteristic responses to infection by comparing variations in these signals, and the correlation between signals and target critical variables was analyzed mechanistically and statistically. The predictive performance of several target CPPs using different multivariate data analysis (MVDA) methods on data from a single sensor/source or fused from multiple sensors were compared. An MS regression model can accurately predict viable cell density with a relative root mean squared error (rRMSE) as low as 8.3% regardless of the changes occurring over the infection phase. This is a significant improvement over the 12% rRMSE achieved with models based on a single source. The MS models also provide the best predictions for glucose, glutamine, lactate, and ammonium. These results demonstrate the potential of using MVDA on MS systems as a real-time monitoring approach for biphasic bioproduction processes. Yet, models based solely on the multiplicity and timing of infection outperformed both single-sensor and MS models, emphasizing the need for a deeper mechanistic understanding in virus production prediction.

Unveiling the potential of specific growth rate control in fed-batch fermentation: bridging the gap between product quantity and quality

During the epoch of sustainable development, leveraging cellular systems for production of diverse chemicals via fermentation has garnered attention. Industrial fermentation, extending beyond strain efficiency and optimal conditions, necessitates a profound understanding of microorganism growth characteristics. Specific growth rate (SGR) is designated as a key variable due to its influence on cellular physiology, product synthesis rates and end-product quality. Despite its significance, the lack of real-time measurements and robust control systems hampers SGR control strategy implementation. The narrative in this contribution delves into the challenges associated with the SGR control and presents perspectives on various control strategies, integration of soft-sensors for real-time measurement and control of SGR. The discussion highlights practical and simple SGR control schemes, suggesting their seamless integration into industrial fermenters. Recommendations provided aim to propose new algorithms accommodating mechanistic and data-driven modelling for enhanced progress in industrial fermentation in the context of sustainable bioprocessing.

A Bioreactor-Based Yellow Fever Virus-like Particle Production Process with Integrated Process Analytical Technology Based on Transient Transfection

Yellow Fever (YF) is a severe disease that, while preventable through vaccination, lacks rapid intervention options for those already infected. There is an urgent need for passive immunization techniques using YF-virus-like particles (YF-VLPs). To address this, we successfully established a bioreactor-based production process for YF-VLPs, leveraging transient transfection and integrating Process Analytical Technology. A cornerstone of this approach was the optimization of plasmid DNA (pDNA) production to a yield of 11 mg/L using design of experiments. Glucose, NaCl, yeast extract, and a phosphate buffer showed significant influence on specific pDNA yield. The preliminary work for VLP-production in bioreactor showed adjustments to the HEK cell density, the polyplex formation duration, and medium exchanges effectively elevated transfection efficiencies. The additive Pluronic F-68 was neutral in its effects, and anti-clumping agents (ACA) adversely affected the transfection process. Finally, we established the stirred-tank bioreactor process with integrated dielectric spectroscopy, which gave real-time insight in relevant process steps, e.g., cell growth, polyplex uptake, and harvest time. We confirmed the presence and integrity of YF-VLP via Western blot, imaging flow cytometry measurement, and transmission electron microscopy. The YF-VLP production process can serve as a platform to produce VLPs as passive immunizing agents against other neglected tropical diseases.

Capacitance spectroscopy enables real-time monitoring of early cell death in mammalian cell culture

BACKGROUND/AIMS

Previous work developed a quantitative model using capacitance spectroscopy in an at-line setup to predict the dying cell percentage measured from a flow cytometer. This work aimed to transfer the at-line model to monitor lab-scale bioreactors in real-time, waiving the need for frequent sampling and enabling precise controls.

METHODS AND RESULTS

Due to the difference between the at-line and in-line capacitance probes, direct application of the at-line model resulted in poor accuracy and high prediction bias. A new model with a variable range and offering similar spectral shape across all probes was first constructed, improving prediction accuracy. Moreover, the global calibration method included the variance of different probes and scales in the model, reducing prediction bias. External parameter orthogonalization, a preprocessing method, also mitigated the interference from feeding, which further improved model performance. The root-mean-square error of prediction of the final model was 6.56% (8.42% of the prediction range) with an R² of 92.4%.

CONCLUSION

The culture evolution trajectory predicted by the in-line model captured the cell death and alarmed cell death onset earlier than the trypan blue exclusion test. Additionally, the incorporation of at-line spectra following orthogonal design into the calibration set was shown to generate calibration models that are more robust than the calibration models constructed using the in-line spectra only. This is advantageous, as at-line spectral collection is easier, faster, and more material-sparing than in-line spectra collection.

Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review

The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.

Process intensification for the continuous production of an antimicrobial peptide in stably-transformed Sf-9 insect cells

The antibiotic resistance crisis has prompted research into alternative candidates such as antimicrobial peptides (AMPs). However, the demand for such molecules can only be met by continuous production processes, which achieve high product yields and offer compatibility with the Quality-by-Design initiative by implementing process analytical technologies such as turbidimetry and dielectric spectroscopy. We developed batch and perfusion processes at the 2-L scale for the production of BR033, a cecropin-like AMP from Lucilia sericata, in stably-transformed polyclonal Sf-9 cells. This is the first time that BR033 has been expressed as a recombinant peptide. Process analytical technology facilitated the online monitoring and control of cell growth, viability and concentration. The perfusion process increased productivity by ~ 180% compared to the batch process and achieved a viable cell concentration of 1.1 × 10⁷ cells/mL. Acoustic separation enabled the consistent retention of 98.5–100% of the cells, viability was > 90.5%. The recombinant AMP was recovered from the culture broth by immobilized metal affinity chromatography and gel filtration and was able to inhibit the growth of Escherichia coli K12. These results demonstrate a successful, integrated approach for the development and intensification of a process from cloning to activity testing for the production of new biopharmaceutical candidates.

Two-methods approach to follow up biomass by impedance spectroscopy: Bacillus thuringiensis fermentations as a study model

Impedance spectroscopy is used for the characterization of electrochemical systems as well as for the monitoring of bioprocesses. However, the data obtained using this technique allow multiple interpretations, depending on the methodology implemented. Hence, it is necessary to establish a robust methodology to reliably follow-up biomass in fermentations. In the present work, two methodological approaches, mainly used for the characterization of electrochemical systems, were employed to characterize and determine a frequency that allows the monitoring of biomass in Bacillus thuringiensis fermentations by impedance spectroscopy. The first approach, based on a conventional analysis, revealed a single distribution with a characteristic frequency of around 2 kHz. In contrast, the second approach, based on the distribution of relaxation times, gave three distributions (A, B, and C). The C distribution, found near 9 kHz, was more related to the microbial biomass than the distribution at 2 kHz using the equivalent circuits. The time course of the B. thuringiensis fermentation was followed; bacilli, spores, glucose, and acid and base consumption for pH were determined out of line; and capacitance at 9 kHz was monitored. The correlation between the time course data and the capacitance profile indicated that the monitoring of B. thuringiensis at 9 kHz mainly corresponds to extracellular activity and, in a second instance, to the cellular concentration. These results show that it is necessary to establish a robust and reliable methodology to monitor fermentation processes by impedance spectroscopy, and the distribution of relaxation times was more appropriate. KEY POINTS: • Application of impedance spectroscopy for bioprocess monitoring • Low-frequency monitoring of biomass in fermentations • Analysis of impedance data by two methodological approaches.

On-line monitoring of industrial interest Bacillus fermentations, using impedance spectroscopy

Impedance spectroscopy is a technique used to characterize electrochemical systems, increasing its applicability as well to monitor cell cultures. During their growth, Bacillus species have different phases which involve the production and consumption of different metabolites, culminating in the cell differentiation process that allows the generation of bacterial spores. In order to use impedance spectroscopy as a tool to monitor industrial interest Bacillus cultures, we conducted batch fermentations of Bacillus species such as B. subtilis, B. amyloliquefaciens, and B. licheniformis coupled with this technique. Each fermentation was characterized by the scanning of 50 frequencies between 0.5 and 5 MHz every 30 min. Pearson's correlation between impedance and phase angle profiles (obtained from each frequency scanned) with the kinetic profiles of each strain allowed the selection of fixed frequencies of 0.5, 1.143, and 1.878 MHz to follow-up of the fermentations of B. subtilis, B. amyloliquefaciens and B. licheniformis, respectively. Dielectric profiles of impedance, phase angle, reactance, and resistance obtained at the fixed frequency showed consistent changes with exponential, transition, and spore release phases.

Cole-Cole modeling of real-time capacitance data for estimation of cell physiological properties in recombinant Escherichia coli cultivation

Real-time estimation of physiological properties of the cell during recombinant protein production would ensure enhanced process monitoring. In this study, we explored the application of dielectric spectroscopy to track the fed-batch phase of recombinant Escherichia coli cultivation for estimating the physiological properties, viz. cell diameter and viable cell concentration (VCC). The scanning capacitance data from the dielectric spectroscopy were pre-processed using moving average (MA). Later, it was modelled through a nonlinear theoretical Cole-Cole model and further solved using a global evolutionary genetic algorithm (GA). The parameters obtained from the GA were further applied for the estimation of the aforementioned physiological properties. The offline cell diameter and cell viability data were obtained from particle size analyzer and flow cytometry measurements to validate the Cole-Cole model. The offline VCC was calculated from the cell viability % from flow cytometry data and dry cell weight concentration (DCW). The Cole-Cole model predicted the cell diameter and VCC with an error of 1.03% and 7.72%, respectively. The proposed approach can enable the operator to take real-time process decisions in order to achieve desired productivity and product quality. This article is protected by copyright. All rights reserved.

Rapid At-line Early Cell Death Quantification using Capacitance Spectroscopy

Cell death is one of the failure modes of mammalian cell culture. Apoptosis is a regulated cell death process mainly observed in cell culture. Timely detection of apoptosis onset allows opportunities for preventive controls that ensure high productivity and consistent product quality. Capacitance spectroscopy captures the apoptosis-related cellular properties changes and thus quantifies the percentage of dying cells. This work demonstrated a quantification model that measures the percentage of apoptotic cells using a capacitance spectrometer in an at-line setup. When predicting the independent test set collected from bench-scale bioreactors, the root-mean-squared error of prediction (RMSEP) was 8.8% (equivalent to 9.9% of the prediction range). The predicted culture evolution trajectory aligned with measured values from the flow cytometer. Furthermore, this method alarms cell death onset earlier than the traditional viability test, i.e., trypan blue exclusion test. Comparing to flow cytometry (the traditional early cell death detection method), this method is rapid, simple, and less labor-intensive. Additionally, this at-line setup can be easily transferred between scales (e.g., lab-scale for development to manufacturing-scale), which benefits process transfers between facilities, scale-up, and other process transitions. This article is protected by copyright. All rights reserved.

Recombinant Antibody Engineering Enables Reversible Binding for Continuous Protein Biosensing

Engineering antibodies to improve target specificity, reduce detection limits, or introduce novel functionality is an important research area for biosensor development. While various affinity biosensors have been developed to generate an output signal upon varying analyte concentrations, reversible and continuous protein monitoring in complex biological samples remains challenging. Herein, we explore the concept of directed evolution to modulate dissociation kinetics of a high affinity anti-epidermal growth factor receptor (EGFR) single-chain variable antibody fragment (scFv) to enable continuous protein sensing in a label-free binding assay. A mutant scFv library was generated from the wild type (WT) fragment via targeted permutation of four residues in the antibody-antigen-binding interface. A single round of phage display biopanning complemented with high-throughput screening methods then permitted isolation of a specific binder with fast reaction kinetics. We were able to obtain ∼30 times faster dissociation rates when compared to the WT without appreciably affecting overall affinity and specificity by targeting a single paratope that is known to contribute to the binding interaction. Suitability of a resulting mutant fragment to sense varying antigen concentrations in continuous mode was demonstrated in a modified label-free binding assay, achieving low nanomolar detection limits (K_D = 8.39 nM). We also confirmed these results using an independent detection mechanism developed previously by our group, incorporating a polarity-dependent fluorescent dye into the scFv and reading out EGFR binding based on fluorescence wavelength shifts. In future, this generic approach could be employed to generate improved or novel binders for proteins of interest, ready for deployment in a broad range of assay platforms.

Application of In-Situ and Soft-Sensors for Estimation of Recombinant P. pastoris GS115 Biomass Concentration: A Case Analysis of HBcAg (Mut+) and HBsAg (MutS) Production Processes under Varying Conditions

Microbial biomass concentration is a key bioprocess parameter, estimated using various labor, operator and process cross-sensitive techniques, analyzed in a broad context and therefore the subject of correct interpretation. In this paper, the authors present the results of P. pastoris cell density estimation based on off-line (optical density, wet/dry cell weight concentration), in-situ (turbidity, permittivity), and soft-sensor (off-gas O₂/CO₂, alkali consumption) techniques. Cultivations were performed in a 5 L oxygen-enriched stirred tank bioreactor. The experimental plan determined varying aeration rates/levels, glycerol or methanol substrates, residual methanol levels, and temperature. In total, results from 13 up to 150 g (dry cell weight)/L cultivation runs were analyzed. Linear and exponential correlation models were identified for the turbidity sensor signal and dry cell weight concentration (DCW). Evaluated linear correlation between permittivity and DCW in the glycerol consumption phase (<60 g/L) and medium (for Mut⁺ strain) to significant (for Mut^S strain) linearity decline for methanol consumption phase. DCW and permittivity-based biomass estimates used for soft-sensor parameters identification. Dataset consisting from 4 Mut⁺ strain cultivation experiments used for estimation quality (expressed in NRMSE) comparison for turbidity-based (8%), permittivity-based (11%), O₂ uptake-based (10%), CO₂ production-based (13%), and alkali consumption-based (8%) biomass estimates. Additionally, the authors present a novel solution (algorithm) for uncommon in-situ turbidity and permittivity sensor signal shift (caused by the intensive stirrer rate change and antifoam agent addition) on-line identification and minimization. The sensor signal filtering method leads to about 5-fold and 2-fold minimized biomass estimate drifts for turbidity- and permittivity-based biomass estimates, respectively.

Novel external-loop-airlift milliliter scale bioreactors for cell growth studies: Low cost design, CFD analysis and experimental characterization

Many researchers have limited access to fully equipped laboratory-scale batch bioreactors and chemostats due to their relatively high cost. This becomes particularly prohibitive when multiple replicas of the same experiment are required, but not enough bioreactors are available to operate simultaneously. Additionally, experiments using shaken flasks are common but show significant limitations in terms of maintaining homogeneous conditions in liquid cultures or installing instrumentation for monitoring. Here, we proposed to tackle this significant hurdle by providing a route to make available the manufacture of low-cost, milliliter-scale bioreactors. This approach seems plausible for enabling proof-of-concept experiments before moving to a larger scale without significant investments. The conceptually designed systems were based on external-loop bioreactors due to their flexibility, simplicity, and ease of assembling and testing. Designs were initially evaluated in silico with the aid of COMSOL Multiphysics. The successfully evaluated systems were then constructed via additive manufacturing and assembled for hydrodynamics testing via tracer methods. This was enabled by a newly home-made optical absorbance sensor (OAS) for in-line and real-time measurements. Both the in silico and experimental results indicated close to ideal mixing conditions and low shear stress. Cell growth curves were prepared by culturing Escherichia coli and following its cell density in real-time. Our cell growth rate and maximum cell density were similar to those previously obtained in closely related systems. Therefore, the proposed bioreactors are an affordable alternative for batch and continuous cell growth studies rapidly and inexpensively.

Bioreactor-Based Antigen Production Process Using the Baculovirus Expression Vector System

Several vaccines are already produced using the baculovirus expression vector system (BEVS). This chapter describes methods for generating recombinant baculoviral DNA (also called bacmid) for cultivating Spodoptera frugiperda Sf-9 cells and producing a baculovirus stock from the recombinant bacmid and for producing a protein-based vaccine with the BEVS in a stirred tank reactor.

Turbidimetry and Dielectric Spectroscopy as Process Analytical Technologies for Mammalian and Insect Cell Cultures

The production of biopharmaceuticals in cell culture involves stringent controls to ensure product safety and quality. To meet these requirements, quality by design principles must be applied during the development of cell culture processes so that quality is built into the product by understanding the manufacturing process. One key aspect is process analytical technology, in which comprehensive online monitoring is used to identify and control critical process parameters that affect critical quality attributes such as the product titer and purity. The application of industry-ready technologies such as turbidimetry and dielectric spectroscopy provides a deeper understanding of biological processes within the bioreactor and allows the physiological status of the cells to be monitored on a continuous basis. This in turn enables selective and targeted process controls to respond in an appropriate manner to process disturbances. This chapter outlines the principles of online dielectric spectroscopy and turbidimetry for the measurement of optical density as applied to mammalian and insect cells cultivated in stirred-tank bioreactors either in suspension or as adherent cells on microcarriers.

Monitoring online biomass with a capacitance sensor during scale-up of industrially relevant CHO cell culture fed-batch processes in single-use bioreactors

In 2004, the FDA published a guideline to implement process analytical technologies (PAT) in biopharmaceutical processes for process monitoring to gain process understanding and for the control of important process parameters. Viable cell concentration (VCC) is one of the most important key performance indicator (KPI) during mammalian cell cultivation processes. Commonly, this is measured offline. In this work, we demonstrated the comparability and scalability of linear regression models derived from online capacitance measurements. The linear regressions were used to predict the VCC and other familiar offline biomass indicators, like the viable cell volume (VCV) and the wet cell weight (WCW), in two different industrially relevant CHO cell culture processes (Process A and Process B). Therefore, different single-use bioreactor scales (50–2000 L) were used to prove feasibility and scalability of the in-line sensor integration. Coefficient of determinations of 0.79 for Process A and 0.99 for Process B for the WCW were achieved. The VCV was described with high coefficients of determination of 0.96 (Process A) and 0.98 (Process B), respectively. In agreement with other work from the literature, the VCC was only described within the exponential growth phase, but resulting in excellent coefficients of determination of 0.99 (Process A) and 0.96 (Process B), respectively. Monitoring these KPIs online using linear regression models appeared to be scale-independent, enabled deeper process understanding (e.g. here demonstrated in monitoring, the feeding profile) and showed the potential of this method for process control.

Process Intensification for an Insect Antimicrobial Peptide Elastin-Like Polypeptide Fusion Produced in Redox-Engineered Escherichia coli

Peptides and proteins containing disulfide bonds can be produced in Escherichia coli by targeting the oxidizing periplasm, co-expressing isomerases or chaperons, refolding from inclusion bodies, or by using redox-engineered E. coli strains. Thus far, protein expression in glutathione reductase and thioredoxin reductase deficient (Δgor ΔtrxB) E. coli strains has required a complex medium. However, a chemically defined medium suitable for large-scale production would be preferable for industrial applications. Recently, we developed a minimal medium supplemented with iron (M9i) for high-density cultivation using E. coli Rosetta gami B(DE3)pLysS cells. Here we show that M9i is suitable for the production of insect metalloproteinase inhibitor (IMPI), which contains five disulfide bonds, in the same E. coli strain. We demonstrated the scalability of the new fed-batch process by combining the scale-up criteria of constant dissolved oxygen (DO) and matching volumetric power inputs (P/V) at the borders of the stirrer cascade. Process intensification was achieved by investigating production feed rates and different induction times. We improved product titers by ~200-fold compared to the standard process in complex medium while maintaining the activity of the IMPI protein. Our results show for the first time that it is possible to produce active proteins containing multiple disulfide bonds in a Δgor ΔtrxB E. coli strain using M9i medium. The success of scale-up and process intensification shows that the industrial production of complex recombinant proteins in such strains using chemically defined M9i minimal medium is feasible.

Downstream processing of Cry4AaCter-induced inclusion bodies containing insect-derived antimicrobial peptides produced in Escherichia coli

The Cry4AaCter tag is a pull-down tag which promotes the formation of inclusion bodies (IBs) that can be resolubilized in an alkaline buffer. Here, we used the Cry4AaCter tag to create a platform for the production of antimicrobial peptides (AMPs) in Escherichia coli featuring a uniform resolubilization process independent of the peptide fused to the pull-down tag. The Cry4AaCter tag conserves the bioactivity of fusion proteins and thus allows the purification of simple AMPs and more complex AMPs stabilized by disulfide bonds. We developed a downstream process (DSP) for the purification of IBs containing the mutated Galleria mellonella insect metalloprotease inhibitor IMPI(I38V), which has a globular structure stabilized by five disulfide bonds. IMPI(I38V) is a potent inhibitor of the M4 metalloproteases used as virulence factors by several human pathogens. We used a single crossflow filtration for the washing and resolubilization of the Cry4AaCter-induced IBs and obtained bioactive IMPI(I38V) after tag removal. We achieved a 68-fold higher protein yield using our IB system compared to an alternative DSP approach in which a GST-fusion strategy was used to produce soluble IMPI(I38V). The Cry4AaCter-based process was transferable to gloverin (another G. mellonella AMP) and the visible marker green fluorescent protein, which accumulated in fluorescent IBs, confirming it is a broadly applicable strategy for the recovery of functional proteins.

Single-cell cloning enables the selection of more productive Drosophila melanogaster S2 cells for recombinant protein expression

The generation of monoclonal cell lines is an important early process development step for recombinant protein production. Although single-cell cloning is an established method in mammalian cell lines, straightforward protocols are not yet available for insect cells. We describe a new method for the generation of monoclonal insect cells without using fetal bovine serum and/or feeder cells pretreated by irradiation or exposure to mitomycin. Highly productive clones of Drosophila melanogaster S2 cells were prepared in a two-step procedure, comprising the establishment of a polyclonal population and subsequent single cell isolation by limiting dilution. Necessary growth factors were provided by co-cultivation of single transformants with untransfected feeder cells, which were later removed by antibiotic selection. Enhanced expression of EGFP and two target peptides was confirmed by flow cytometry and dot/western blotting. Highly productive clones were stable, showed a uniform expression profile and typically a sixfold to tenfold increase in cell-specific productivity.