Recombinant Protein Production Processes Research Articles

Understanding exopolysaccharide byproduct formation in Komagataella phaffii fermentation processes for recombinant protein production

BackgroundKomagataella phaffii (Pichia pastoris) has emerged as a common and robust biotechnological platform organism, to produce recombinant proteins and other bioproducts of commercial interest. Key advantage of K. phaffii is the secretion of recombinant proteins, coupled with a low host protein secretion. This facilitates downstream processing, resulting in high purity of the target protein. However, a significant but often overlooked aspect is the presence of an unknown polysaccharide impurity in the supernatant. Surprisingly, this impurity has received limited attention in the literature, and its presence and quantification are rarely addressed.ResultsThis study aims to quantify this exopolysaccharide in high cell density recombinant protein production processes and identify its origin. In stirred tank fed-batch fermentations with a maximal cell dry weight of 155 g/L, the polysaccharide concentration in the supernatant can reach up to 8.7 g/L. This level is similar to the achievable target protein concentration. Importantly, the results demonstrate that exopolysaccharide production is independent of the substrate and the protein production process itself. Instead, it is directly correlated with biomass formation and proportional to cell dry weight. Cell lysis can confidently be ruled out as the source of this exopolysaccharide in the culture medium. Furthermore, the polysaccharide secretion can be linked to a mutation in the HOC1 gene, featured by all derivatives of strain NRRL Y-11430, leading to a characteristic thinner cell wall.ConclusionsThis research sheds light on a previously disregarded aspect of K. phaffii fermentations, emphasizing the importance of monitoring and addressing the exopolysaccharide impurity in biotechnological applications, independent of the recombinant protein produced.

Cheese-whey permeate improves the fitness of Escherichia coli cells during recombinant protein production

BackgroundEscherichia coli cells are the most frequently used hosts in recombinant protein production processes and mainly require molecules such as IPTG or pure lactose as inducers of heterologous expression. A possible way to reduce the production costs is to replace traditional inducers with waste materials such as cheese whey permeate (CWP). CWP is a secondary by-product generated from the production of the valuable whey proteins, which are obtained from ultrafiltration of cheese whey, a main by-product of the dairy industry, which is rich in lactose.ResultsThe effects of CWP collected from an Italian plant were compared with those of traditional inducers on the production of two model proteins (i.e., green fluorescent protein and the toxic Q55 variant of ataxin-3), in E. coli BL21 (DE3) cells. It was found that the high lactose content of CWP (165 g/L) and the antioxidant properties of its micronutrients (vitamins, cofactors and osmolytes) sustain production yields similar to those obtained with traditional inducers, accompanied by the improvement of cell fitness.ConclusionsCWP has proven to be an effective and low-cost alternative inducer to produce recombinant proteins. Its use thus combines the advantage of exploiting a waste product with that of reducing the production costs of recombinant proteins.

PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in Escherichia coli

Optimization of the fermentation process for recombinant protein production (RPP) is often resource-intensive. Machine learning (ML) approaches are helpful in minimizing the experimentations and find vast applications in RPP. However, these ML-based tools primarily focus on features with respect to amino-acid-sequence, ruling out the influence of fermentation process conditions. The present study combines the features derived from fermentation process conditions with that from amino acid-sequence to construct an ML-based model that predicts the maximal protein yields and the corresponding fermentation conditions for the expression of target recombinant protein in the Escherichia coli periplasm. Two sets of XGBoost classifiers were employed in the first stage to classify the expression levels of the target protein as high (>50 mg/L), medium (between 0.5 and 50 mg/L), or low (<0.5 mg/L). The second-stage framework consisted of three regression models involving support vector machines and random forest to predict the expression yields corresponding to each expression-level-class. Independent tests showed that the predictor achieved an overall average accuracy of 75% and a Pearson coefficient correlation of 0.91 for the correctly classified instances. Therefore, our model offers a reliable substitution of numerous trial-and-error experiments to identify the optimal fermentation conditions and yield for RPP. It is also implemented as an open-access webserver, PERISCOPE-Opt (http://periscope-opt.erc.monash.edu).

Generic model based control of different specific rates in recombinant E. coli Fed-batch processes

In addition to often reported control of the specific growth rate we show in this contribution a novel method to control the biomass specific substrate uptake as well as the protein production rate during the production phase of microbial fed-batch cultures. The control laws base on a calibrated process model including experimental data sets with different constant glycerol feed rates. The model includes changing growth and production behaviour in function of the induced metabolic stress. Based on the method of non-linear feedback linearization, the control laws were derived from the model, using the glycerol feed rate as the manipulable variable. Considering comparable setpoints at three different levels the effectiveness of the controller as well as their potential to improve the production phase was assessed by simulations. The direct control of product formation rates enables to ensure constant production performance and therefore to reach highest product levels in short time. As a drawback, the controller needs high feed adaption towards the end to counteract the advancing decay of the attainable production rates. This, to a lesser extend, also applies for the growth rate. A constant substrate uptake rate resulted in a valuable alternative to a uncontrolled, constant feed rate during the production phase of recombinant protein production processes.

Construction of Fluorescent Immunosensor Quenchbody to Detect His-Tagged Recombinant Proteins Produced in Bioprocess.

With the widespread application of recombinant DNA technology, many useful substances are produced by bioprocesses. For the monitoring of the recombinant protein production process, most of the existing technologies are those for the culture environment (pH, O2, etc.). However, the production status of the target protein can only be known after the subsequent separation and purification process. To speed up the monitoring of the production process and screening of the higher-yield target protein variants, here we developed an antibody-based His-tag sensor Quenchbody (Q-body), which can quickly detect the C-terminally His-tagged recombinant protein produced in the culture medium. Compared with single-chain Fv-based Q-body having one dye, the Fab-based Q-body having two dyes showed a higher response. In addition, not only was fluorescence response improved but also detection sensitivity by the mutations of tyrosine to tryptophan in the heavy chain CDR region. Moreover, the effect of the mutations on antigen-binding was successfully validated by molecular docking simulation by CDOCKER. Finally, the constructed Q-body was successfully applied to monitor the amount of anti-SARS CoV-2 nanobody secreted into the Brevibacillus culture media.

Semicontinuous system for the production of recombinant mCherry protein in Chlamydomonas reinhardtii.

Biotechnology advances have allowed bacteria, yeasts, plants, mammalian and insect cells to function as heterologous protein expression systems. Recently, microalgae have gained attention as an innovative platform for recombinant protein production, due to low culture media cost, compared to traditional systems, as well as the fact that microalgae such as Chlamydomonas reinhardtii are considered safe (GRAS) by the Food and Drug Administration (FDA). Previous studies showed that recombinant protein production in traditional platforms by semicontinuous process increased biomass and bio product productivity, when compared to batch process. As there is a lack of studies on semicontinuous process for recombinant protein production in microalgae, the production of recombinant mCherry fluorescent protein was evaluated by semicontinuous cultivation of Chlamydomonas reinhardtii in bubble column photobioreactor. This semicontinuous cultivation process was evaluated in the following conditions: 20%, 40%, and 60% culture portion withdrawal. The highest culture withdrawal percentage (60%) provided the best results, as an up to 161% increase in mCherry productivity (454.5 RFU h-1 - Relative Fluorescence Unit h-1 ), in comparison to batch cultivation (174.0 RFU h-1 ) of the same strain. All cultivations were carried out for 13 days, at pH 7, temperature 25°C and, by semicontinuous process, two culture withdrawals were taken during the cultivations. Throughout the production cycles, it was possible to obtain biomass concentration up to 1.36 g L-1 .

Repetitive Fed-Batch: A Promising Process Mode for Biomanufacturing With E. coli.

Recombinant protein production with Escherichia coli is usually carried out in fed-batch mode in industry. As set-up and cleaning of equipment are time- and cost-intensive, it would be economically and environmentally favorable to reduce the number of these procedures. Switching from fed-batch to continuous biomanufacturing with microbials is not yet applied as these cultivations still suffer from time-dependent variations in productivity. Repetitive fed-batch process technology facilitates critical equipment usage, reduces the environmental fingerprint and potentially increases the overall space-time yield. Surprisingly, studies on repetitive fed-batch processes for recombinant protein production can be found for yeasts only. Knowledge on repetitive fed-batch cultivation technology for recombinant protein production in E. coli is not available until now. In this study, a mixed feed approach, enabling repetitive fed-batch technology for recombinant protein production in E. coli, was developed. Effects of the cultivation mode on the space-time yield for a single-cycle fed-batch, a two-cycle repetitive fed-batch, a three-cycle repetitive fed batch and a chemostat cultivation were investigated. For that purpose, we used two different E. coli strains, expressing a model protein in the cytoplasm or in the periplasm, respectively. Our results demonstrate that a repetitive fed-batch for E. coli leads to a higher space-time yield compared to a single-cycle fed-batch and can potentially outperform continuous biomanufacturing. For the first time, we were able to show that repetitive fed-batch technology is highly suitable for recombinant protein production in E. coli using our mixed feeding approach, as it potentially (i) improves product throughput by using critical equipment to its full capacity and (ii) allows implementation of a more economic process by reducing cleaning and set-up times.

Recombinant Protein-Based Nanoparticles: Elucidating their Inflammatory Effects In Vivo and their Potential as a New Therapeutic Format.

Bacterial inclusion bodies (IBs) are protein-based nanoparticles of a few hundred nanometers formed during recombinant protein production processes in different bacterial hosts. IBs contain active protein in a mechanically stable nanostructured format that has been broadly characterized, showing promising potential in different fields such as tissue engineering, protein replacement therapies, cancer, and biotechnology. For immunomodulatory purposes, however, the interference of the format immunogenic properties—intrinsic to IBs—with the specific effects of the therapeutic protein is still an uncovered gap. For that, active and inactive forms of the catalytic domain of a matrix metalloproteinase-9 (MMP-9 and mutMMP-9, respectively) have been produced as IBs and compared with the soluble form for dermal inflammatory effects in mmp9 knock-out mice. After protein injections in air-pouches in the mouse model, MMP-9 IBs induce local neutrophil recruitment and increase pro-inflammatory chemokine levels, lasting for at least two days, whereas the effects triggered by the soluble MMP-9 format fade out after 3 h. Interestingly, the IB intrinsic effects (mutMMP-9 IBs) do not last more than 24 h. Therefore, it may be concluded that IBs could be used for the delivery of therapeutic proteins, such as immunomodulating proteins while preserving their stability in the specific tissue and without triggering important unspecific inflammatory responses due to the protein format.

The Biological Potential Hidden in Inclusion Bodies.

Inclusion bodies (IBs) are protein nanoclusters obtained during recombinant protein production processes, and several studies have demonstrated their potential as biomaterials for therapeutic protein delivery. Nevertheless, IBs have been, so far, exclusively sifted by their biological activity in vitro to be considered in further protein-based treatments in vivo. Matrix metalloproteinase-9 (MMP-9) protein, which has an important role facilitating the migration of immune cells, was used as model protein. The MMP-9 IBs were compared with their soluble counterpart and with MMP-9 encapsulated in polymeric-based micelles (PM) through ionic and covalent binding. The soluble MMP-9 and the MMP-9-ionic PM showed the highest activity values in vitro. IBs showed the lowest activity values in vitro, but the specific activity evolution in 50% bovine serum at room temperature proved that they were the most stable format. The data obtained with the use of an air-pouch mouse model showed that MMP-9 IBs presented the highest in vivo activity compared to the soluble MMP-9, which was associated only to a low and a transitory peak of activity. These results demonstrated that the in vivo performance is the addition of many parameters that did not always correlate with the in vitro behavior of the protein of interest, becoming especially relevant at evaluating the potential of IBs as a protein-based nanomaterial for therapeutic purposes.

Bioreactor-Scale Strategies for the Production of Recombinant Protein in the Yeast Yarrowia lipolytica.

Recombinant protein production represents a multibillion-dollar market. Therefore, it constitutes an important research field both in academia and industry. The use of yeast as a cell factory presents several advantages such as ease of genetic manipulation, growth at high cell density, and the possibility of post-translational modifications. Yarrowia lipolytica is considered as one of the most attractive hosts due to its ability to metabolize raw substrate, to express genes at a high level, and to secrete protein in large amounts. In recent years, several reviews have been dedicated to genetic tools developed for this purpose. Though the construction of efficient cell factories for recombinant protein synthesis is important, the development of an efficient process for recombinant protein production in a bioreactor constitutes an equally vital aspect. Indeed, a sports car cannot drive fast on a gravel road. The aim of this review is to provide a comprehensive snapshot of process tools to consider for recombinant protein production in bioreactor using Y. lipolytica as a cell factory, in order to facilitate the decision-making for future strain and process engineering.

Dual Data-Independent Acquisition Approach Combining Global HCP Profiling and Absolute Quantification of Key Impurities during Bioprocess Development.

Host cell proteins (HCP) are a major class of impurities derived from recombinant protein production processes. While HCP are usually monitored by ELISA, mass spectrometry (MS)-based approaches are emerging as promising orthogonal methods. Here, we developed an original method relying on data-independent acquisition (DIA) coupling global HCP amount estimation (Top 3) and absolute quantification with isotope dilution (ID). The method named Top 3-ID-DIA was benchmarked against ELISA and a gold-standard selected reaction monitoring assay (ID-SRM). Various samples generated at different steps and conditions of the purification process, including different culture durations, harvest procedures, and purification protocols were used to compare the methods. Overall, HCP were quantified over 5 orders of magnitude and down to the sub-ppm level. The Top 3-ID-DIA strategy proved to be equivalent to the gold-standard ID-SRM in terms of sensitivity (1-10 ppm), accuracy, and precision. Moreover, 81% of the Top 3 estimations were accurate within a factor of 2 when compared to ID-SRM. Thus, our approach aggregates global HCP profiling for comprehensive process understanding with absolute quantification of key HCP within a single analysis and provides an improved support for bioprocess development and product purity assessment.

Integrating metabolic modeling and population heterogeneity analysis into optimizing recombinant protein production by Komagataella (Pichia) pastoris.

The methylotrophic yeast Komagataella (Pichia) pastoris has become one of the most utilized cell factories for the production of recombinant proteins over the last three decades. This success story is linked to its specific physiological traits, i.e., the ability to grow at high cell density in inexpensive culture medium and to secrete proteins at high yield. Exploiting methanol metabolism is at the core of most P. pastoris-based processes but comes with its own challenges. Co-feeding cultures with glycerol/sorbitol and methanol is a promising approach, which can benefit from improved understanding and prediction of metabolic response. The development of profitable processes relies on the construction and selection of efficient producing strains from less efficient ones but also depends on the ability to master the bioreactor process itself. More specifically, how a bioreactor processes could be monitored and controlled to obtain high yield of production. In this review, new perspectives are detailed regarding a multi-faceted approach to recombinant protein production processes by P. pastoris; including gaining improved understanding of the metabolic pathways involved, accounting for variations in transcriptional and translational efficiency at the single cell level and efficient monitoring and control of methanol levels at the bioreactor level.

Expression Optimization of Anti-CD22 scFv-Apoptin Fusion Protein Using Experimental Design Methodology

Background:Design of experiments is a rapid and cost-effective approach for optimization of recombinant protein production process. In our previous study, we generated a potent dual-acting fusion protein, anti-CD22 scFv-apoptin, to target B-cell malignant cell lines. In the present investigation, we report the effect of different variables on the expression levels of this fusion protein.Methods:Four variables (cell optical density at induction, IPTG concentration, induction temperature, and induction time) were tested using experimental design.Results:Our findings demonstrated that among the examined variables, only the induction time had a significant positive effect on the protein expression yield.Conclusion:Experimental design was successfully applied in this study. The optimized condition obtained in the current study can be applied in future commercial production of this novel fusion protein.

Hybrid Approach to State Estimation for Bioprocess Control.

An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF) is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the less established relationship between the state variables and the measurement quantities, is formulated in a data driven way. The latter is formulated by means of a support vector regression (SVR) model. The UKF is applied to a recombinant therapeutic protein production process using Escherichia coli bacteria. Additionally, the state vector was extended by the specific biomass growth rate µ in order to allow for the estimation of this key variable which is crucial for the implementation of innovative control algorithms in recombinant therapeutic protein production processes. The state estimates depict a sufficiently low noise level which goes perfectly with different advanced bioprocess control applications.

Effects of antibiotic concentration and nutrient medium composition on Escherichia coli biofilm formation and green fluorescent protein expression.

Recombinant protein production processes have to maximise yield while minimising cost, which involves balancing plasmid maintenance with cell growth and protein expression. The aim of this study was to analyse the influence of two factors on heterologous protein production in Escherichia coli biofilm cells-the concentration of antibiotic used to maintain the selective pressure and the nutrient medium composition. Escherichia coli JM109(DE3) cells transformed with plasmid pFM23 for enhanced green fluorescent protein (eGFP) expression and containing a kanamycin resistance gene were used. They were exposed to 20 or 30 μgmL-1 kanamycin during biofilm growth in two different culture media, a diluted medium (DM) or the lysogeny broth (LB). The higher antibiotic concentration increased the specific eGFP production in planktonic cells, whereas no increase was detected in biofilm cells. Biofilm formation was increased in DM when compared to LB. Nevertheless, bacteria grown in LB had higher eGFP production than those grown in DM in both planktonic and sessile states (20-fold and 2-fold, respectively). Therefore, among the conditions tested, LB supplemented with 20 μgmL-1 kanamycin was the most advantageous medium to obtain the highest specific eGFP production in biofilm cells.

Artificial Intelligence vs. Statistical Modeling and Optimization of Continuous Bead Milling Process for Bacterial Cell Lysis.

For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery. RSM predicted an optimum of feed rate of 310.73 mL/h, bead loading of 79.9% (v/v), cell loading OD600 nm of 74, and run time of 29.9 min with a recovery of ~3.2 g/L. ANN-GA predicted a maximum COD recovery of ~3.5 g/L at an optimum feed rate (mL/h): 258.08, bead loading (%, v/v): 80%, cell loading (OD600 nm): 73.99, and run time of 32 min. An overall 3.7-fold increase in productivity is obtained when compared to a batch process. Optimization and comparison of statistical vs. artificial intelligence techniques in continuous bead milling process has been attempted for the very first time in our study. We were able to successfully represent the complex non-linear multivariable dependence of enzyme recovery on bead milling parameters. The quadratic second order response functions are not flexible enough to represent such complex non-linear dependence. ANN being a summation function of multiple layers are capable to represent complex non-linear dependence of variables in this case; enzyme recovery as a function of bead milling parameters. Since GA can even optimize discontinuous functions present study cites a perfect example of using machine learning (ANN) in combination with evolutionary optimization (GA) for representing undefined biological functions which is the case for common industrial processes involving biological moieties.

Bioprocess development workflow: Transferable physiological knowledge instead of technological correlations.

Microbial bioprocesses need to be designed to be transferable from lab scale to production scale as well as between setups. Although substantial effort is invested to control technological parameters, usually the only true constant parameter is the actual producer of the product: the cell. Hence, instead of solely controlling technological process parameters, the focus should be increasingly laid on physiological parameters. This contribution aims at illustrating a workflow of data life cycle management with special focus on physiology. Information processing condenses the data into physiological variables, while information mining condenses the variables further into physiological descriptors. This basis facilitates data analysis for a physiological explanation for observed phenomena in productivity. Targeting transferability, we demonstrate this workflow using an industrially relevant Escherichia coli process for recombinant protein production and substantiate the following three points: (1) The postinduction phase is independent in terms of productivity and physiology from the preinduction variables specific growth rate and biomass at induction. (2) The specific substrate uptake rate during induction phase was found to significantly impact the maximum specific product titer. (3) The time point of maximum specific titer can be predicted by an easy accessible physiological variable: while the maximum specific titers were reached at different time points (19.8±7.6 h), those maxima were reached all within a very narrow window of cumulatively consumed substrate dSn (3.1±0.3 g/g). Concluding, this contribution provides a workflow on how to gain a physiological view on the process and illustrates potential benefits. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:261-270, 2017.

Advances in Molecular Cloning

"Molecular cloning" meaning creation of recombinant DNA molecules has impelled advancement throughout life sciences. DNA manipulation has become easy due to powerful tools showing exponential growth in applications and sophistication of recombinant DNA technology. Cloning genes has become simple what led to an explosion in the understanding of gene function by seamlessly stitching together multiple DNA fragments or by the use of swappable gene cassettes, maximizing swiftness and litheness. A novel archetype might materialize in the near future with synthetic biology techniques that will facilitate quicker assembly and iteration of DNA clones, accelerating the progress of gene therapy vectors, recombinant protein production processes and new vaccines by in vitro chemical synthesis of any in silico-specified DNA construct. The advent of innovative cloning techniques has opened the door to more refined applications such as identification and mapping of epigenetic modifications and high-throughput assembly of combinatorial libraries. In this review, we will examine the major breakthroughs in cloning techniques and their applications in various areas of biological research that have evolved mainly due to easy construction of novel expression systems.

Efficient high-throughput biological process characterization: Definitive screening design with the ambr250 bioreactor system.

The burgeoning pipeline for new biologic drugs has increased the need for high-throughput process characterization to efficiently use process development resources. Breakthroughs in highly automated and parallelized upstream process development have led to technologies such as the 250-mL automated mini bioreactor (ambr250™) system. Furthermore, developments in modern design of experiments (DoE) have promoted the use of definitive screening design (DSD) as an efficient method to combine factor screening and characterization. Here we utilize the 24-bioreactor ambr250™ system with 10-factor DSD to demonstrate a systematic experimental workflow to efficiently characterize an Escherichia coli (E. coli) fermentation process for recombinant protein production. The generated process model is further validated by laboratory-scale experiments and shows how the strategy is useful for quality by design (QbD) approaches to control strategies for late-stage characterization.

Operator training simulation for integrating cultivation and homogenisation in protein production

Operating training simulators (OTS) are virtual simulation tools used for training of process operators in industry in performing procedures and running processes. Based on structured mathematical models of the unit operations of a bioprocess an OTS can train a process operator by visualising changing conditions during the process, allow testing operator actions, testing controller settings, experience unexpected technical problems and getting practice in using prescribed standard procedures for a plant.This work shows the design of an OTS where two sequential steps of a recombinant protein production process, a fed-batch cultivation and a high-pressure homogenisation, are integrated. The OTS was evaluated on a user test group and showed that the OTS promoted and developed their understanding of the process, their capability to identify parameters influencing process efficiency and the skills of operating it.