Bioconversion of L-Tyrosine into p-Coumaric Acid by Tyrosine Ammonia-Lyase Heterologue of Rhodobacter sphaeroides Produced in Pseudomonas putida KT2440.

p-Coumaric acid (p-CA) is a valuable compound with applications in food additives, cosmetics, and pharmaceuticals. However, traditional production methods are often inefficient and unsustainable. This study focuses on enhancing p-CA production efficiency through the heterologous expression of tyrosine ammonia-lyase (TAL) from Rhodobacter sphaeroides in Pseudomonas putida KT2440. TAL catalyzes the conversion of L-tyrosine into p-CA and ammonia. We engineered P. putida KT2440 to express TAL in a fed-batch fermentation system. Our results demonstrate the following: (i) successful integration of the TAL gene into P. putida KT2440 and (ii) efficient bioconversion of L-tyrosine into p-CA (1381 mg/L) by implementing a pH shift from 7.0 to 8.5 during fed-batch fermentation. This approach highlights the viability of P. putida KT2440 as a host for TAL expression and the successful coupling of fermentation with the pH-shift-mediated bioconversion of L-tyrosine. Our findings underscore the potential of genetically modified P. putida for sustainable p-CA production and encourage further research to optimize bioconversion steps and fermentation conditions.

Investigation into struvite precipitation: A commonly encountered problem during fermentations on chemically defined media.

Chemically defined mineral media are widely used in bioprocesses, as these show less batch to batch variation compared with complex media. Nonetheless, the recommended media formulations often lead to the formation of precipitants at elevated pH values. These precipitates are insoluble and reduce the availability of macronutrients to the cells, which can result in limiting growth rates and lower productivity. They can also damage equipment by clogging pipes, hoses, and spargers in stirred tank fermenters. In this study, the observed precipitate was analyzed via X-ray fluorescence spectroscopy and identified as the magnesium ammonium phosphate salt struvite (MgNH4 PO4 × 6H2 O). The solubility of struvite crystals is known to be extremely low, causing the macronutrients magnesium, phosphate, and ammonium to be bound in the struvite crystals. Here, it was shown that struvite precipitates can be redissolved under common fermentation conditions. Furthermore, it was found that the struvite particle size distribution has a significant effect on the dissolution kinetics, which directly affects macronutrient availability. At a certain particle size, struvite crystals rapidly dissolved and provided unlimiting growth conditions. Therefore, struvite formation should be considered during media and bioprocess development, to ensure that the dissolution kinetics of struvite are faster than the growth kinetics.

Development of automated metabolite control using mid-infrared probe for bioprocesses and vaccine manufacturing.

Automation of metabolite control in fermenters is fundamental to develop vaccine manufacturing processes more quickly and robustly. We created an end-to-end process analytical technology and quality by design-focused process by replacing manual control of metabolites during the development of fed-batch bioprocesses with a system that is highly adaptable and automation-enabled. Mid-infrared spectroscopy with an attenuated total reflectance probe in-line, and simple linear regression using the Beer-Lambert Law, were developed to quantitate key metabolites (glucose and glutamate) from spectral data that measured complex media during fermentation. This data was digitally connected to a process information management system, to enable continuous control of feed pumps with proportional-integral-derivative controllers that maintained nutrient levels throughout fed-batch stirred-tank fermenter processes. Continuous metabolite data from mid-infrared spectra of cultures in stirred-tank reactors enabled feedback loops and control of the feed pumps in pharmaceutical development laboratories. This improved process control of nutrient levels by 20-fold and the drug substance yield by an order of magnitude. Furthermore, the method is adaptable to other systems and enables soft sensing, such as the consumption rate of metabolites. The ability to develop quantitative metabolite templates quickly and simply for changing bioprocesses was instrumental for project acceleration and heightened process control and automation. ONE-SENTENCE SUMMARY: Intelligent digital control systems using continuous in-line metabolite data enabled end-to-end automation of fed-batch processes in stirred-tank reactors.

Precision fermentation with mass spectrometry-based spent media analysis.

Optimization and monitoring of bioprocesses requires the measurement of several process parameters and quality attributes. Mass spectrometry (MS)-based techniques such as those coupled to gas chromatography (GCMS) and liquid Chromatography (LCMS) enable the simultaneous measurement of hundreds of metabolites with high sensitivity. When applied to spent media, such metabolome analysis can help determine the sequence of substrate uptake and metabolite secretion, consequently facilitating better design of initial media and feeding strategy. Furthermore, the analysis of metabolite diversity and abundance from spent media will aid the determination of metabolic phases of the culture and the identification of metabolites as surrogate markers for product titer and quality. This review covers the recent advances in metabolomics analysis applied to the development and monitoring of bioprocesses. In this regard, we recommend a stepwise workflow and guidelines that a bioprocesses engineer can adopt to develop and optimize a fermentation process using spent media analysis. Finally, we show examples of how the use of MS can revolutionize the design and monitoring of bioprocesses.

Nonlinear state estimation as tool for online monitoring and adaptive feed in high throughput cultivations.

Robotic facilities that can perform advanced cultivations (e.g., fed-batch or continuous) in high throughput have drastically increased the speed and reliability of the bioprocess development pipeline. Still, developing reliable analytical technologies, that can cope with the throughput of the cultivation system, has proven to be very challenging. On the one hand, the analytical accuracy suffers from the low sampling volumes, and on the other hand, the number of samples that must be treated rapidly is very large. These issues have been a major limitation for the implementation of feedback control methods in miniaturized bioreactor systems, where observations of the process states are typically obtained after the experiment has finished. In this work, we implement a Sigma-Point Kalman Filter in a high throughput platform with 24 parallel experiments at the mL-scale to demonstrate its viability and added value in high throughput experiments. The filter exploits the information generated by the ammonia-based pH control to enable the continuous estimation of the biomass concentration, a critical state to monitor the specific rates of production and consumption in the process. The objective in the selected case study is to ensure that the selected specific substrate consumption rate is tightly controlled throughout the complete Escherichia coli cultivations for recombinant production of an antibody fragment.

Towards a scalable bioprocess for rAAV production using a HeLa stable cell line.

The majority of recombinant adeno-associated viruses (rAAV) approved for clinical use or in clinical trials areproduced by transient transfection using the HEK293 cell line. However, this platform has several manufacturing bottlenecks at commercial scales namely, low product quality (full to empty capsid ratio <20% in most rAAV serotypes), lower productivities obtained after scale-up and the high cost of raw materials, in particular of Good Manufacturing Practice grade plasmid DNA required for transfection. The HeLa-based stable cell line rAAV production system provides a robust and scalable alternative to transient transfection systems. Nevertheless, the time required to generate the producer cell lines combined with the complexity of rAAV production and purification processes still pose several barriers to the use of this platform as a suitable alternative to the HEK293 transient transfection. In this work we streamlined the cell line development and bioprocessing for the HeLaS3-based production of rAAV. By exploring this optimized approach, producer cell lines were generated in 3-4 months, and presented rAAV2 volumetric production (bulk) > 3 × 1011 vg/mL and full to empty capsids ratio (>70%) at 2 L bioreactor scale. Moreover, the established downstream process, based on ion exchange and affinity-based chromatography, efficiently eliminated process related impurities, including the Adenovirus 5 helper virus required for production with a log reduction value of 9. Overall, we developed a time-efficient and robust rAAV bioprocess using a stable producer cell line achieving purified rAAV2 yields > 1 × 1011 vg/mL. This optimized platform may address manufacturing challenges for rAAV based medicines.

Biological control of melanin biosynthesis pathway on prolific and pleochromatic induction of Lasiodiplodia theobromae.

To obtain a kind of microbial pigment with high yield and variety coloration by regulating the pigment synthesis pathway in this experiment, Lasiodiplodia theobromae was used to induce pigment secretion by prolific inducing factors (tyrosinase, Cu2+, stilbene glycoside) and pleochromatic inducing factors (L-tyrosine, L-cysteine, tricyclazole). The results showed that through single factor and compound culture, the most reasonable inducing formula was 150 ku/L tyrosinase, while tricyclazole at 10 mg/L for 30 days had a maximum color difference of 42.92 NBS with a reddish-brown color in 10 days. The melanin content increased gradually with the extension of culture time, and the pleochromatic inducing group was up to 3.47 mg/mL, higher than that of the prolific inducing group. However, the poor solubility of purified melanin with a diameter of 100-200 nm was observed in conventional solvents. Through effective induction, it is expected that L. theobromae can secrete melanin stably and be widely used in printing, dyeing, electronics, and the chemical industry.

From frozen cell bank to product assay: high-throughput strain characterisation for autonomous Design-Build-Test-Learn cycles.

BACKGROUND: Modern genome editing enables rapid construction of genetic variants, which are further developed in Design-Build-Test-Learn cycles. To operate such cycles in high throughput, fully automated screening, including cultivation and analytics, is crucial in the Test phase. Here, we present the required steps to meet these demands, resulting in an automated microbioreactor platform that facilitates autonomous phenotyping from cryo culture to product assay. RESULTS: First, an automated deep freezer was integrated into the robotic platform to provide working cell banks at all times. A mobile cart allows flexible docking of the freezer to multiple platforms. Next, precultures were integrated within the microtiter plate for cultivation, resulting in highly reproducible main cultures as demonstrated for Corynebacterium glutamicum. To avoid manual exchange of microtiter plates after cultivation, two clean-in-place strategies were established and validated, resulting in restored sterile conditions within two hours. Combined with the previous steps, these changes enable a flexible start of experiments and greatly increase the walk-away time. CONCLUSIONS: Overall, this work demonstrates the capability of our microbioreactor platform to perform autonomous, consecutive cultivation and phenotyping experiments. As highlighted in a case study of cutinase-secreting strains of C. glutamicum, the new procedure allows for flexible experimentation without human interaction while maintaining high reproducibility in early-stage screening processes.

Workflow for shake flask and plate cultivations with fats for polyhydroxyalkanoate bioproduction.

Since natural resources for the bioproduction of commodity chemicals are scarce, waste animal fats (WAF) are an interesting alternative biogenic residual feedstock. They appear as by-product from meat production, but several challenges are related to their application: first, the high melting points (up to 60 °C); and second, the insolubility in the polar water phase of cultivations. This leads to film and clump formation in shake flasks and microwell plates, which inhibits microbial consumption. In this study, different flask and well designs were investigated to identify the most suitable experimental set-up and further to create an appropriate workflow to achieve the required reproducibility of growth and product synthesis. The dissolved oxygen concentration was measured in-line throughout experiments. It became obvious that the gas mass transfer differed strongly among the shake flask design variants in cultivations with the polyhydroxyalkanoate (PHA) accumulating organism Ralstonia eutropha. A high reproducibility was achieved for certain flask or well plate design variants together with tailored cultivation conditions. Best results were achieved with bottom baffled glass and bottom baffled single-use shake flasks with flat membranes, namely, >6 g L-1 of cell dry weight (CDW) with >80 wt% polyhydroxybutyrate (PHB) from 1 wt% WAF. Improved pre-emulsification conditions for round microwell plates resulted in a production of 14 g L-1 CDW with a PHA content of 70 wt% PHB from 3 wt% WAF. The proposed workflow allows the rapid examination of fat material as feedstock, in the microwell plate and shake flask scale, also beyond PHA production. KEY POINTS: • Evaluation of shake flask designs for cultivating with hydrophobic raw materials • Development of a workflow for microwell plate cultivations with hydrophobic raw materials • Production of polyhydroxyalkanoate in small scale experiments from waste animal fat.

Improved preculture management for Cupriavidus necator cultivations.

OBJECTIVES: Research on hydrogenases from Cupriavidus necator has been ongoing for more than two decades and still today the common methods for culture inoculation are used. These methods were never adapted to the requirements of modified bacterial strains, resulting in different physiological states of the bacteria in the precultures, which in turn lead prolonged and different lag-phases. RESULTS: In order to obtain uniform and always equally fit precultures for inoculation, we have established in this study an optimized protocol for precultures of the derivative of C. necator HF210 (C. necator HP80) which is used for homologous overexpression of the genes for the NAD+-reducing soluble hydrogenase (SH). We compared different media for preculture growth and determined the optimal time point for harvest. The protocol obtained in this study is based on two subsequent precultures, the first one in complex nutrient broth medium (NB) and a second one in fructose -nitrogen mineral salt medium (FN). CONCLUSION: Despite having two subsequent precultures our protocol reduces the preculture time to less than 30 h and provides reproducible precultures for cultivation of C. necator HP80.

Integrating metabolome dynamics and process data to guide cell line selection in biopharmaceutical process development.

The successful development of mammalian cell culture for the production of therapeutic antibodies is a resource-intensive and multistage process which requires the selection of high performing and stable cell lines at different scale-up stages. Accordingly, science-based approaches exploiting biological information, such as metabolomics, can support and accelerate the selection of promising cell lines to progress. In fact, the integration of dynamic biological information with process data can provide valuable insights on the cell physiological changes as a consequence of the cultivation process. This work studies the industrial development of monoclonal antibodies at micro-bioreactor scale (Ambr®15) and aims at accelerating the selection of the better performing cell lines. To that end, we apply a machine learning approach to integrate time-varying process and biological information (i.e., metabolomics), explicitly exploiting their dynamics. Strikingly, cell line performance during the cultivation can be predicted from early process timepoints by exploiting the gradual temporal evolution of metabolic phenotypes. Furthermore, product titer is estimated with good accuracy at late process timepoints, providing insights into its relationship with underlying metabolic mechanisms and enabling the identification of biomarkers to be further investigated. The biological insights obtained through the proposed machine learning approach provide data-driven metabolic understanding allowing early identification of high performing cell lines. Additionally, this analysis offers the opportunity to identify key metabolites which could be used as biomarkers for industrially relevant phenotypes and onward fit into our commercial manufacturing platforms.

High-throughput screening of optimal process conditions using model predictive control.

Modern biotechnological laboratories are equipped with advanced parallel mini-bioreactor facilities that can perform sophisticated cultivation strategies (e.g., fed-batch or continuous) and generate significant amounts of measurement data. These systems require not only optimal experimental designs that find the best conditions in very large design spaces, but also algorithms that manage to operate a large number of different cultivations in parallel within a well-defined and tightly constrained operating regime. Existing advanced process control algorithms have to be tailored to tackle the specific issues of such facilities such as: a very complex biological system, constant changes in the metabolic activity and phenotypes, shifts of pH and/or temperature, and metabolic switches, to name a few. In this study we implement a model predictive control (MPC) framework to demonstrate: (1) the challenges in terms of mathematical model structure, state, and parameter estimation, and optimization under highly nonlinear and stiff dynamics in biological systems, (2) the adaptations required to enable the application of MPC in high throughput bioprocess development, and (3) the added value of MPC implementations when operating parallel mini-bioreactors aiming to maximize the biomass concentration while coping with hard constrains on the dissolved oxygen tension profile.

Differential effects on natural killer cell production by membrane-bound cytokine stimulations.

Robust manufacturing production of natural killer (NK) cells has been challenging in allogeneic NK cell-based therapy. Here, we compared the impact of cytokines on NK cell expansion by developing recombinant K562 feeder cell lines expressing membrane-bound cytokines, mIL15, mIL21, and 41BBL, individually or in combination. We found that 41BBL played a dominant role in promoting up to 500,000-fold of NK cell expansion after a 21-day culture process without inducing exhaustion. However, 41BBL stimulation reduced the overall cytotoxic activity of NK cells when combined with mIL15 and/or mIL21. Additionally, long-term stimulation with mIL15 and/or mIL21, but not 41BBL, increased CD56 expression and the CD56bright population, which is unexpectedly correlated with NK cell cytotoxicity. By conducting single-cell sequencing, we identified distinct subpopulations of NK cells induced by different cytokines, including an adaptive-like CD56bright CD16- CD49a+ subset induced by mIL15. Through gene expression analysis, we found that different cytokines modulated signaling pathways and target genes involved in cell cycle, senescence, self-renewal, migration, and maturation in different ways. Together, our study demonstrates that cytokine signaling pathways play distinct roles in NK cell expansion and differentiation, which sheds light on NK cell process designs to improve productivity and product quality.

Control of parallelized bioreactors II: probabilistic quantification of carboxylic acid reductase activity for bioprocess optimization.

Autonomously operated parallelized mL-scale bioreactors are considered the key to reduce bioprocess development cost and time. However, their application is often limited to products with very simple analytics. In this study, we investigated enhanced protein expression conditions of a carboxyl reductase from Nocardia otitidiscaviarum in E. coli. Cells were produced with exponential feeding in a L-scale bioreactor. After the desired cell density for protein expression was reached, the cells were automatically transferred to 48 mL-scale bioreactors operated by a liquid handling station where protein expression studies were conducted. During protein expression, the feed rate and the inducer concentration was varied. At the end of the protein expression phase, the enzymatic activity was estimated by performing automated whole-cell biotransformations in a deep-well-plate. The results were analyzed with hierarchical Bayesian modelling methods to account for the biomass growth during the biotransformation, biomass interference on the subsequent product assay, and to predict absolute and specific enzyme activities at optimal expression conditions. Lower feed rates seemed to be beneficial for high specific and absolute activities. At the optimal investigated expression conditions an activity of [Formula: see text] was estimated with a [Formula: see text] credible interval of [Formula: see text]. This is about 40-fold higher than the highest published data for the enzyme under investigation. With the proposed setup, 192 protein expression conditions were studied during four experimental runs with minimal manual workload, showing the reliability and potential of automated and digitalized bioreactor systems.

Generation and Characterization of Stable Redox-Reporter Mammalian Cell Lines of Biotechnological Relevance.

Cellular functions such as DNA replication and protein translation are influenced by changes in the intracellular redox milieu. Exogenous (i.e., nutrients, deterioration of media components, xenobiotics) and endogenous factors (i.e., metabolism, growth) may alter the redox homeostasis of cells. Thus, monitoring redox changes in real time and in situ is deemed essential for optimizing the production of recombinant proteins. Recently, different redox-sensitive variants of green fluorescent proteins (e.g., rxYFP, roGFP2, and rxmRuby2) have been engineered and proved suitable to detect, in a non-invasive manner, perturbations in the pool of reduced and oxidized glutathione, the major low molecular mass thiol in mammals. In this study, we validate the use of cytosolic rxYFP on two cell lines widely used in biomanufacturing processes, namely, CHO-K1 cells expressing the human granulocyte macrophage colony-stimulating factor (hGM-CSF) and HEK-293. Flow cytometry was selected as the read-out technique for rxYFP signal given its high-throughput and statistical robustness. Growth kinetics and cellular metabolism (glucose consumption, lactate and ammonia production) of the redox reporter cells were comparable to those of the parental cell lines. The hGM-CSF production was not affected by the expression of the biosensor. The redox reporter cell lines showed a sensitive and reversible response to different redox stimuli (reducing and oxidant reagents). Under batch culture conditions, a significant and progressive oxidation of the biosensor occurred when CHO-K1-hGM-CSF cells entered the late-log phase. Medium replenishment restored, albeit partially, the intracellular redox homeostasis. Our study highlights the utility of genetically encoded redox biosensors to guide metabolic engineering or intervention strategies aimed at optimizing cell viability, growth, and productivity.

High-throughput screening for high-efficiency small-molecule biosynthesis.

Systems metabolic engineering faces the formidable task of rewiring microbial metabolism to cost-effectively generate high-value molecules from a variety of inexpensive feedstocks for many different applications. Because these cellular systems are still too complex to model accurately, vast collections of engineered organism variants must be systematically created and evaluated through an enormous trial-and-error process in order to identify a manufacturing-ready strain. The high-throughput screening of strains to optimize their scalable manufacturing potential requires execution of many carefully controlled, parallel, miniature fermentations, followed by high-precision analysis of the resulting complex mixtures. This review discusses strategies for the design of high-throughput, small-scale fermentation models to predict improved strain performance at large commercial scale. Established and promising approaches from industrial and academic groups are presented for both cell culture and analysis, with primary focus on microplate- and microfluidics-based screening systems.

Knowledge transfer across cell lines using hybrid Gaussian process models with entity embedding vectors.

To date, a large number of experiments are performed to develop a biochemical process. The generated data is used only once, to take decisions for development. Could we exploit data of already developed processes to make predictions for a novel process, we could significantly reduce the number of experiments needed. Processes for different products exhibit differences in behaviour, typically only a subset behave similar. Therefore, effective learning on multiple product spanning process data requires a sensible representation of the product identity. We propose to represent the product identity (a categorical feature) by embedding vectors that serve as input to a Gaussian process regression model. We demonstrate how the embedding vectors can be learned from process data and show that they capture an interpretable notion of product similarity. The improvement in performance is compared to traditional one-hot encoding on a simulated cross product learning task. All in all, the proposed method could render possible significant reductions in wet-lab experiments.

Bioprocess performance analysis of novel methanol-independent promoters for recombinant protein production with Pichia pastoris.

BACKGROUND: Pichia pastoris is a powerful and broadly used host for recombinant protein production (RPP), where past bioprocess performance has often been directed with the methanol regulated AOX1 promoter (PAOX1), and the constitutive GAP promoter (PGAP). Since promoters play a crucial role in an expression system and the bioprocess efficiency, innovative alternatives are constantly developed and implemented. Here, a thorough comparative kinetic characterization of two expression systems based on the commercial PDF and UPP promoters (PPDF, PUPP) was first conducted in chemostat cultures. Most promising conditions were subsequently tested in fed-batch cultivations. These new alternatives were compared with the classical strong promoter PGAP, using the Candida antarctica lipase B (CalB) as model protein for expression system performance. RESULTS: Both the PPDF and PUPP-based expression systems outperformed similar PGAP-based expression in chemostat cultivations, reaching ninefold higher specific production rates (qp). CALB transcription levels were drastically higher when employing the novel expression systems. This higher expression was also correlated with a marked upregulation of unfolded protein response (UPR) related genes, likely from an increased protein burden in the endoplasmic reticulum (ER). Based on the chemostat results obtained, best culture strategies for both PPDF and PUPP expression systems were also successfully implemented in 15 L fed-batch cultivations where qp and product to biomass yield (YP/X*) values were similar than those obtained in chemostat cultivations. CONCLUSIONS: As an outcome of the macrokinetic characterization presented, the novel PPDF and PUPP were observed to offer much higher efficiency for CalB production than the widely used PGAP-based methanol-free alternative. Thus, both systems arise as highly productive alternatives for P. pastoris-based RPP bioprocesses. Furthermore, the different expression regulation patterns observed indicate the level of gene expression can be adjusted, or tuned, which is interesting when using Pichia pastoris as a cell factory for different products of interest.

Development of redox potential-driven fermentation process for recombinant protein expression.

OBJECTIVES: A redox potential-driven fermentation, maintaining dissolved oxygen at a prescribed level while simultaneously monitoring the changes of fermentation redox potential, was developed to guide the cultivation progress of recombinant protein expression. RESULTS: A recombinant E. coli harboring prolinase-expressing plasmid (pKK-PepR2) was cultivated using the developed process. Two distinct ORP valleys were noticeable based on recorded profile. The first ORP valley is equivalent to the timing for the addition of inducing agent, and the second ORP valley serves to guide the timing for cell harvesting. The final prolinase activity is 0.172 µmol/mg/min as compared to that of 0.154 µmol/mg/min where the optical density was employed to guide the timing of inducer addition and an empirically determined length of the cultivation. CONCLUSION: The developed process can be further modified to become an automatic operation.

A scalable insect cell-based production process of the human recombinant BMX for in-vitro covalent ligand high-throughput screening.

Bone Marrow Tyrosine kinase in the chromosome X (BMX) is a TEC family kinase associated with numerous pathological pathways in cancer cells. Covalent inhibition of BMX activity holds promise as a therapeutic approach against cancer. To screen for potent and selective covalent BMX inhibitors, large quantities of highly pure BMX are normally required which is challenging with the currently available production and purification processes. Here, we developed a scalable production process for the human recombinant BMX (hrBMX) using the insect cell-baculovirus expression vector system. Comparable expression levels were obtained in small-scale shake flasks (13 mL) and in stirred-tank bioreactors (STB, 5 L). A two-step chromatographic-based process was implemented, reducing purification times by 75% when compared to traditional processes, while maintaining hrBMX stability. The final production yield was 24 mg of purified hrBMX per litter of cell culture, with a purity of > 99%. Product quality was assessed and confirmed through a series of biochemical and biophysical assays, including circular dichroism and dynamic light scattering. Overall, the platform herein developed was capable of generating 100 mg purified hrBMX from 5 L STB in just 34 days, thus having the potential to assist in-vitro covalent ligand high-throughput screening for BMX activity inhibition.