Dynamic process conditions in bioprocess development

Model Transferability and Reduced Experimental Burden in Cell Culture Process Development Facilitated by Hybrid Modeling and Intensified Design of Experiments

Reliable process development is accompanied by intense experimental effort. The utilization of an intensified design of experiments (iDoE) (intra-experimental critical process parameter (CPP) shifts combined) with hybrid modeling potentially reduces process development burden. The iDoE can provide more process response information in less overall process time, whereas hybrid modeling serves as a commodity to describe this behavior the best way. Therefore, a combination of both approaches appears beneficial for faster design screening and is especially of interest at larger scales where the costs per experiment rise significantly. Ideally, profound process knowledge is gathered at a small scale and only complemented with few validation experiments on a larger scale, saving valuable resources. In this work, the transferability of hybrid modeling for Chinese hamster ovary cell bioprocess development along process scales was investigated. A two-dimensional DoE was fully characterized in shake flask duplicates (300 ml), containing three different levels for the cultivation temperature and the glucose concentration in the feed. Based on these data, a hybrid model was developed, and its performance was assessed by estimating the viable cell concentration and product titer in 15 L bioprocesses with the same DoE settings. To challenge the modeling approach, 15 L bioprocesses also comprised iDoE runs with intra-experimental CPP shifts, impacting specific cell rates such as growth, consumption, and formation. Subsequently, the applicability of the iDoE cultivations to estimate static cultivations was also investigated. The shaker-scale hybrid model proved suitable for application to a 15 L scale (1:50), estimating the viable cell concentration and the product titer with an NRMSE of 10.92% and 17.79%, respectively. Additionally, the iDoE hybrid model performed comparably, displaying NRMSE values of 13.75% and 21.13%. The low errors when transferring the models from shaker to reactor and between the DoE and the iDoE approach highlight the suitability of hybrid modeling for mammalian cell culture bioprocess development and the potential of iDoE to accelerate process characterization and to improve process understanding.

Monte Carlo-Based Error Propagation for a More Reliable Regression Analysis across Specific Rates in Bioprocesses

During process development, bioprocess data need to be converted into applicable knowledge. Therefore, it is crucial to evaluate the obtained data under the usage of transparent and reliable data reduction and correlation techniques. Within this contribution, we show a generic Monte Carlo error propagation and regression approach applied to two different, industrially relevant cultivation processes. Based on measurement uncertainties, errors for cell-specific growth, uptake, and production rates were determined across an evaluation chain, with interlinked inputs and outputs. These uncertainties were subsequently included in regression analysis to derive the covariance of the regression coefficients and the confidence bounds for prediction. The usefulness of the approach is shown within two case studies, based on the relations across biomass-specific rate control limits to guarantee high productivities in E. coli, and low lactate formation in a CHO cell fed-batch could be established. Besides the possibility to determine realistic errors on the evaluated process data, the presented approach helps to differentiate between reliable and unreliable correlations and prevents the wrong interpretations of relations based on uncertain data.

Insight into the pilot-scale fed-batch fermentation for production of Enterococcus faecium CW3801 using molasses-based medium

Enterococcus sp. has been used as starters in food fermentation due to their probiotic and antimicrobial properties in food biopreservation. The antimicrobial properties were mainly contributed by the bacteriocin called enterocin. Hence, the availability of a cost-effective pilot-scale cultivation conditions is a necessity for the production of probiotic bacteria. This study aims to investigate optimization of medium composition using sugarcane molasses as a carbon source using response surface methodology and the potential use of fed-batch cultivation for improvement of the cell viability of Enterococcus faecium CW3801 for the use as a probiotic starter culture. Two feeding strategies (ramp and constant) were applied in fed-batch cultivation for enhancement of the production of E. faecium in a 2-L stirred tank bioreactor using the optimized medium and scaled up to a 15-L bioreactor. Optimized fermentation medium which comprised of 10% (v/v) of molasses and 10 g/L of yeast extract at pH 7 yielded maximum cell viability of 29.4 × 10¹¹ CFU/mL with 3900 AU/mL of bacteriocin-like inhibitory substances (BLIS) activity. In the fed-batch, the cell viability (8.4 × 10¹³) and dry cell weight (6.34 g/L) reached the highest in optimized medium when the ramp (stepwise) feeding was applied. In scaling up to 15-L bioreactor, the growth of E. faecium was achieved at 2.3 × 10¹³ CFU/mL with the dry cell weight of 5.28 g/L under the same condition. The BLIS in 15-L bioreactor was 6% higher than the 2-L bioreactor. This study demonstrated that molasses and yeast extract are good feedstock for the growth of E. faecium. The E. faecium, a non-vancomycin resistant enterococcus (VRE) was successfully produced by a fed-batch cultivation approach and scaled up to a 15-L bioreactor using a ramp feeding strategy. Results from this study revealed that the fed-batch cultivation using molasses-based medium has industrial potential for the production of probiotics.

Dynamic response of Aspergillus niger to periodical glucose pulse stimuli in chemostat cultures

In industrial large-scale bioreactors, microorganisms encounter heterogeneous substrate concentration conditions, which can impact growth or product formation. Here we carried out an extended (12 h) experiment of repeated glucose pulsing with a 10-min period to simulate fluctuating glucose concentrations with Aspergillus niger producing glucoamylase, and investigated its dynamic response by rapid sampling and quantitative metabolomics. The 10-min period represents worst-case conditions, as in industrial bioreactors the average cycling duration is usually in the order of 1 min. We found that cell growth and the glucoamylase productivity were not significantly affected, despite striking metabolomic dynamics. Periodical dynamic responses were found across all central carbon metabolism pathways, with different time scales, and the frequently reported ATP paradox was confirmed for this A. niger strain under the dynamic conditions. A thermodynamics analysis revealed that several reactions of the central carbon metabolism remained in equilibrium even under periodical dynamic conditions. The dynamic response profiles of the intracellular metabolites did not change during the pulse exposure, showing no significant adaptation of the strain to the more than 60 perturbation cycles applied. The apparent high tolerance of the glucoamylase producing A. niger strain for extreme variations in the glucose availability presents valuable information for the design of robust industrial microbial hosts.

Potential of Integrating Model-Based Design of Experiments Approaches and Process Analytical Technologies for Bioprocess Scale-Down

Typically, bioprocesses on an industrial scale are dynamic systems with a certain degree of variability, system inhomogeneities, and even population heterogeneities. Therefore, the scaling of such processes from laboratory to industrial scale and vice versa is not a trivial task. Traditional scale-down methodologies consider several technical parameters, so that systems on the laboratory scale tend to qualitatively reflect large-scale effects, but not the dynamic situation in an industrial bioreactor over the entire process, from the perspective of a cell. Supported by the enormous increase in computing power, the latest scientific focus is on the application of dynamic models, in combination with computational fluid dynamics to quantitatively describe cell behavior. These models allow the description of possible cellular lifelines which in turn can be used to derive a regime analysis for scale-down experiments. However, the approaches described so far, which were for a very few process examples, are very labor- and time-intensive and cannot be validated easily. In parallel, alternatives have been developed based on the description of the industrial process with hybrid process models, which describe a process mechanistically as far as possible in order to determine the essential process parameters with their respective variances. On-line analytical methods allow the characterization of population heterogeneity directly in the process. This detailed information from the industrial process can be used in laboratory screening systems to select relevant conditions in which the cell and process related parameters reflect the situation in the industrial scale. In our opinion, these technologies, which are available in research for modeling biological systems, in combination with process analytical techniques are so far developed that they can be implemented in industrial routines for faster development of new processes and optimization of existing ones.

Continuous Cultivation as a Tool Toward the Rational Bioprocess Development With Pichia Pastoris Cell Factory

The methylotrophic yeast Pichia pastoris (Komagataella phaffii) is currently considered one of the most promising hosts for recombinant protein production (RPP) and metabolites due to the availability of several tools to efficiently regulate the recombinant expression, its ability to perform eukaryotic post-translational modifications and to secrete the product in the extracellular media. The challenge of improving the bioprocess efficiency can be faced from two main approaches: the strain engineering, which includes enhancements in the recombinant expression regulation as well as overcoming potential cell capacity bottlenecks; and the bioprocess engineering, focused on the development of rational-based efficient operational strategies. Understanding the effect of strain and operational improvements in bioprocess efficiency requires to attain a robust knowledge about the metabolic and physiological changes triggered into the cells. For this purpose, a number of studies have revealed chemostat cultures to provide a robust tool for accurate, reliable, and reproducible bioprocess characterization. It should involve the determination of key specific rates, productivities, and yields for different C and N sources, as well as optimizing media formulation and operating conditions. Furthermore, studies along the different levels of systems biology are usually performed also in chemostat cultures. Transcriptomic, proteomic and metabolic flux analysis, using different techniques like differential target gene expression, protein description and ¹³C-based metabolic flux analysis, are widely described as valued examples in the literature. In this scenario, the main advantage of a continuous operation relies on the quality of the homogeneous samples obtained under steady-state conditions, where both the metabolic and physiological status of the cells remain unaltered in an all-encompassing picture of the cell environment. This contribution aims to provide the state of the art of the different approaches that allow the design of rational strain and bioprocess engineering improvements in Pichia pastoris toward optimizing bioprocesses based on the results obtained in chemostat cultures. Interestingly, continuous cultivation is also currently emerging as an alternative operational mode in industrial biotechnology for implementing continuous process operations.

Performance of an acoustic settler versus a hollow fiber-based ATF technology for influenza virus production in perfusion

Process intensification and integration is crucial regarding an ever increasing pressure on manufacturing costs and capacities in biologics manufacturing. For virus production in perfusion mode, membrane-based alternating tangential flow filtration (ATF) and acoustic settler are the commonly described cell retention technologies. While acoustic settlers allow for continuous influenza virus harvesting, the use of commercially available membranes for ATF systems typically results in the accumulation of virus particles in the bioreactor vessel. Accordingly, with one single harvest at the end of a cultivation, this increases the risk of lowering the product quality. To assess which cell retention device would be most suitable for influenza A virus production, we compared various key performance figures using AGE1.CR.pIX cells at concentrations between 25 and 50 × 106 cells/mL at similar infection conditions using either an ATF system or an acoustic settler. Production yields, process-related impurities, and aggregation of viruses and other large molecules were evaluated. Taking into account the total number of virions from both the bioreactor and the harvest vessel, a 1.5-3.0-fold higher volumetric virus yield was obtained for the acoustic settler. In addition, fewer large-sized aggregates (virus particles and other molecules) were observed in the harvest taken directly from the bioreactor. In contrast, similar levels of process-related impurities (host cell dsDNA, total protein) were obtained in the harvest for both retention systems. Overall, a clear advantage was observed for continuous virus harvesting after the acoustic settler operation mode was optimized. This development may also allow direct integration of subsequent downstream processing steps. KEY POINTS: • High suspension cell density, immortalized avian cell line, influenza vaccine.

Escherichia coli metabolism under short-term repetitive substrate dynamics: adaptation and trade-offs

Background

Microbial metabolism is highly dependent on the environmental conditions. Especially, the substrate concentration, as well as oxygen availability, determine the metabolic rates. In large-scale bioreactors, microorganisms encounter dynamic conditions in substrate and oxygen availability (mixing limitations), which influence their metabolism and subsequently their physiology. Earlier, single substrate pulse experiments were not able to explain the observed physiological changes generated under large-scale industrial fermentation conditions.

Results

In this study we applied a repetitive feast–famine regime in an aerobic Escherichia coli culture in a time-scale of seconds. The regime was applied for several generations, allowing cells to adapt to the (repetitive) dynamic environment. The observed response was highly reproducible over the cycles, indicating that cells were indeed fully adapted to the regime. We observed an increase of the specific substrate and oxygen consumption (average) rates during the feast–famine regime, compared to a steady-state (chemostat) reference environment. The increased rates at same (average) growth rate led to a reduced biomass yield (30% lower). Interestingly, this drop was not followed by increased by-product formation, pointing to the existence of energy-spilling reactions. During the feast–famine cycle, the cells rapidly increased their uptake rate. Within 10 s after the beginning of the feeding, the substrate uptake rate was higher (4.68 μmol/g_CDW/s) than reported during batch growth (3.3 μmol/g_CDW/s). The high uptake led to an accumulation of several intracellular metabolites, during the feast phase, accounting for up to 34% of the carbon supplied. Although the metabolite concentrations changed rapidly, the cellular energy charge remained unaffected, suggesting well-controlled balance between ATP producing and ATP consuming reactions.

Conclusions

The adaptation of the physiology and metabolism of E. coli under substrate dynamics, representative for large-scale fermenters, revealed the existence of several cellular mechanisms coping with stress. Changes in the substrate uptake system, storage potential and energy-spilling processes resulted to be of great importance. These metabolic strategies consist a meaningful step to further tackle reduced microbial performance, observed under large-scale cultivations.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Implementing Process Analytical Technology for the Production of Recombinant Proteins in Escherichia coli Using an Advanced Controller Scheme

The performance of a bioreactor in meeting process goals is affected by the microorganism used, medium composition, and operating conditions. A typical bioreactor uses a supervisory control and data acquisition (SCADA) system for control, and a combination of software and hardware tools for real-time data analysis. However, when the process is disrupted by utility or instrumentation failure, typical process controllers may be unable to reinstate normal operating conditions before the cells in the reactor shift to unfavorable metabolic regimes. The objective of this study is to examine how the response of a controller affects process recovery when disruptive incidences occur under a process analytical technology (PAT) framework. The process used for this investigation is the production of lethal toxin-neutralizing factor (LTNF) by Escherichia coli (E. coli), which is controlled by a decoupled input-output-linearizing controller (DIOLC). The performance of the DIOLC is compared to a proportional integral derivative (PID) controller subjected to the same conditions. The disruptions are introduced manually and the effect of controller action on process recovery and LTNF synthesis is measured in terms of peak purity and concentration. It is observed that DIOLC performs better after reinstating operating conditions and results in a meaningful improvement in performance.

Methods for quantification of growth and productivity in anaerobic microbiology and biotechnology

Anaerobic microorganisms (anaerobes) possess a fascinating metabolic versatility. This characteristic makes anaerobes interesting candidates for physiological studies and utilizable as microbial cell factories. To investigate the physiological characteristics of an anaerobic microbial population, yield, productivity, specific growth rate, biomass production, substrate uptake, and product formation are regarded as essential variables. The determination of those variables in distinct cultivation systems may be achieved by using different techniques for sampling, measuring of growth, substrate uptake, and product formation kinetics. In this review, a comprehensive overview of methods is presented, and the applicability is discussed in the frame of anaerobic microbiology and biotechnology.

Recent Advances in Pichia pastoris as Host for Heterologous Expression System for Lipases: A Review

The production of heterologous lipases is one of the most promising strategies to increase the productivity of the bioprocesses and to reduce costs, with the final objective that more industrial lipase applications could be implemented.In this chapter, an overview of the new success in synthetic biology, with traditional molecular genetic techniques and bioprocess engineering in the last 5 years in the cell factory Pichia pastoris, the most promising host system for heterologous lipase production, is presented.The goals get on heterologous Candida antarctica, Rhizopus oryzae, and Candida rugosa lipases, three of the most common lipases used in biocatalysis, are showed. Finally, new cell factories producing heterologous lipases are presented.

Engineering microbial phenotypes through rewiring of genetic networks

The ability to program cellular behaviour is a major goal of synthetic biology, with applications in health, agriculture and chemicals production. Despite efforts to build 'orthogonal' systems, interactions between engineered genetic circuits and the endogenous regulatory network of a host cell can have a significant impact on desired functionality. We have developed a strategy to rewire the endogenous cellular regulatory network of yeast to enhance compatibility with synthetic protein and metabolite production. We found that introducing novel connections in the cellular regulatory network enabled us to increase the production of heterologous proteins and metabolites. This strategy is demonstrated in yeast strains that show significantly enhanced heterologous protein expression and higher titers of terpenoid production. Specifically, we found that the addition of transcriptional regulation between free radical induced signalling and nitrogen regulation provided robust improvement of protein production. Assessment of rewired networks revealed the importance of key topological features such as high betweenness centrality. The generation of rewired transcriptional networks, selection for specific phenotypes, and analysis of resulting library members is a powerful tool for engineering cellular behavior and may enable improved integration of heterologous protein and metabolite pathways.

Synthesis and analysis of separation networks for the recovery of intracellular chemicals generated from microbial-based conversions

BACKGROUND

Bioseparations can contribute to more than 70% in the total production cost of a bio-based chemical, and if the desired chemical is localized intracellularly, there can be additional challenges associated with its recovery. Based on the properties of the desired chemical and other components in the stream, there can be multiple feasible options for product recovery. These options are composed of several alternative technologies, performing similar tasks. The suitability of a technology for a particular chemical depends on (1) its performance parameters, such as separation efficiency; (2) cost or amount of added separating agent; (3) properties of the bioreactor effluent (e.g., biomass titer, product content); and (4) final product specifications. Our goal is to first synthesize alternative separation options and then analyze how technology selection affects the overall process economics. To achieve this, we propose an optimization-based framework that helps in identifying the critical technologies and parameters.

RESULTS

We study the separation networks for two representative classes of chemicals based on their properties. The separation network is divided into three stages: cell and product isolation (stage I), product concentration (II), and product purification and refining (III). Each stage exploits differences in specific product properties for achieving the desired product quality. The cost contribution analysis for the two cases (intracellular insoluble and intracellular soluble) reveals that stage I is the key cost contributor (>70% of the overall cost). Further analysis suggests that changes in input conditions and technology performance parameters lead to new designs primarily in stage I.

CONCLUSIONS

The proposed framework provides significant insights for technology selection and assists in making informed decisions regarding technologies that should be used in combination for a given set of stream/product properties and final output specifications. Additionally, the parametric sensitivity provides an opportunity to make crucial design and selection decisions in a comprehensive and rational manner. This will prove valuable in the selection of chemicals to be produced using bioconversions (bioproducts) as well as in creating better bioseparation flow sheets for detailed economic assessment and process implementation on the commercial scale.

Carbon dioxide consumption of the microalga Scenedesmus obtusiusculus under transient inlet CO2 concentration variations

The extensive microalgae diversity offers considerable versatility for a wide range of biotechnological applications in environmental and production processes. Microalgal cultivation is based on CO₂ fixation via photosynthesis and, consequently, it is necessary to evaluate, in a short time and reliable way, the effect of the CO₂ gas concentration on the consumption rate and establish the tolerance range of different strains and the amount of inorganic carbon that can be incorporated into biomass in order to establish the potential for industrial scale application. Dynamic experiments allow calculating the short-term microalgal photosynthetic activity of strains in photobioreactors. In this paper, the effect of step-changes in CO₂ concentration fed to a 20L bubble column photobioreactor on the CO₂ consumption rate of Scenedesmus obtusiusculus was evaluated at different operation times. The highest apparent CO₂ consumption rate (336μmolm^-2s^-1 and 5.6% of CO₂) was 6530mg_CO2g_b^-1d^-1 and it decreased to 222mg_CO2g_b^-1d^-1 when biomass concentration increased of 0.5 to 3.1g_bL^-1 and 5.6% of CO₂ was fed. For low CO₂ concentrations (<3.8%) the pH remained close to the optimal value (7.5 and 8). The CO₂ consumption rates show that S. obtusiusculus was not limited by CO₂ availability for concentrations above of 3.8%. The CO₂ mass balance showed that 90% of the C-CO₂ transferred was used for S. obtusiusculus growth.

Mechanistic platform knowledge of concomitant sugar uptake in Escherichia coli BL21(DE3) strains

When producing recombinant proteins, the use of Escherichia coli strain BL21(DE3) in combination with the T7-based pET-expression system is often the method of choice. In a recent study we introduced a mechanistic model describing the correlation of the specific glucose uptake rate (q_s,glu) and the corresponding maximum specific lactose uptake rate (q_s,lac,max) for a pET-based E. coli BL21(DE3) strain producing a single chain variable fragment (scFv). We showed the effect of q_s,lac,max on productivity and product location underlining its importance for recombinant protein production. In the present study we investigated the mechanistic q_s,glu/q_s,lac,max correlation for four pET-based E. coli BL21(DE3) strains producing different recombinant products and thereby proved the mechanistic model to be platform knowledge for E. coli BL21(DE3). However, we found that the model parameters strongly depended on the recombinant product. Driven by this observation we tested different dynamic bioprocess strategies to allow a faster investigation of this mechanistic correlation. In fact, we succeeded and propose an experimental strategy comprising only one batch cultivation, one fed-batch cultivation as well as one dynamic experiment, to reliably determine the mechanistic model for q_s,glu/q_s,lac,max and get trustworthy model parameters for pET-based E. coli BL21(DE3) strains which are the basis for bioprocess development.

Effects of glycerol supply and specific growth rate on methanol-free production of CALB by P. pastoris: functional characterisation of a novel promoter

As Pichia pastoris (syn. Komagataella sp.) yeast can secrete pure recombinant proteins at high rates, it is a desirable production system. The function of a novel synthetic variant of the AOX1 promoter was characterised comprehensively using a strain secreting Candida antarctica lipase B (CALB) as a model. A new time-saving approach was introduced to determine, in only one experiment, the hitherto unknown relationship between specific product formation rate (q_p) and specific growth rate (μ). Tight control of recombinant protein formation was possible in the absence of methanol, while using glycerol as a sole carbon/energy source. CALB was not synthesised during batch cultivation in excess glycerol (>10 g l⁻¹) and at a growth rate close to μ_max (0.15 h⁻¹). Between 0.017 and 0.115 h⁻¹ in glycerol-limited fedbatch cultures, basal levels of q_p > 0.4 mg g⁻¹ h⁻¹ CALB were reached, independent of the μ at which the culture grew. At μ > 0.04 h⁻¹, an elevated q_p occurred temporarily during the first 20 h after changing to fedbatch mode and decreased thereafter to basal. In order to accelerate the determination of the q_p(μ) relationship (kinetics of product formation), the entire μ range was covered in a single fedbatch experiment. By linearly increasing and decreasing glycerol addition rates, μ values were repeatedly shifted from 0.004 to 0.074 h⁻¹ and vice versa. Changes in q_p were related to changes in μ. A rough estimation of μ range suitable for production was possible in a single fedbatch, thus significantly reducing the experimental input over previous approaches comprising several experiments.

Using simple models to describe the kinetics of growth, glucose consumption, and monoclonal antibody formation in naive and infliximab producer CHO cells

Despite their practical and commercial relevance, there are few reports on the kinetics of growth and production of Chinese hamster ovary (CHO) cells-the most frequently used host for the industrial production of therapeutic proteins. We characterize the kinetics of cell growth, substrate consumption, and product formation in naive and monoclonal antibody (mAb) producing recombinant CHO cells. Culture experiments were performed in 125 mL shake flasks on commercial culture medium (CD Opti CHO™ Invitrogen, Carlsbad, CA, USA) diluted to different glucose concentrations (1.2-4.8 g/L). The time evolution of cell, glucose, lactic acid concentration and monoclonal antibody concentrations was monitored on a daily basis for mAb-producing cultures and their naive counterparts. The time series were differentiated to calculate the corresponding kinetic rates (rx = d[X]/dt; rs = d[S]/dt; rp = d[mAb]/dt). Results showed that these cell lines could be modeled by Monod-like kinetics if a threshold substrate concentration value of [S]t = 0.58 g/L (for recombinant cells) and [S]t = 0.96 g/L (for naïve cells), below which growth is not observed, was considered. A set of values for μmax, and Ks was determined for naive and recombinant cell cultures cultured at 33 and 37 °C. The yield coefficient (Yx/s) was observed to be a function of substrate concentration, with values in the range of 0.27-1.08 × 10(7) cell/mL and 0.72-2.79 × 10(6) cells/mL for naive and recombinant cultures, respectively. The kinetics of mAb production can be described by a Luedeking-Piret model (d[mAb]/dt = αd[X]/dt + β[X]) with values of α = 7.65 × 10(-7) µg/cell and β = 7.68 × 10(-8) µg/cell/h for cultures conducted in batch-agitated flasks and batch and instrumented bioreactors operated in batch and fed-batch mode.

The E. coli pET expression system revisited-mechanistic correlation between glucose and lactose uptake

Therapeutic monoclonal antibodies are mainly produced in mammalian cells to date. However, unglycosylated antibody fragments can also be produced in the bacterium Escherichia coli which brings several advantages, like growth on cheap media and high productivity. One of the most popular E. coli strains for recombinant protein production is E. coli BL21(DE3) which is usually used in combination with the pET expression system. However, it is well known that induction by isopropyl β-d-1-thiogalactopyranoside (IPTG) stresses the cells and can lead to the formation of insoluble inclusion bodies. In this study, we revisited the pET expression system for the production of a novel antibody single-chain variable fragment (scFv) with the goal of maximizing the amount of soluble product. Thus, we (1) investigated whether lactose favors the recombinant production of soluble scFv compared to IPTG, (2) investigated whether the formation of soluble product can be influenced by the specific glucose uptake rate (q_s,glu) during lactose induction, and (3) determined the mechanistic correlation between the specific lactose uptake rate (q_s,lac) and q_s,glu. We found that lactose induction gave a much greater amount of soluble scFv compared to IPTG, even when the growth rate was increased. Furthermore, we showed that the production of soluble protein could be tuned by varying q_s,glu during lactose induction. Finally, we established a simple model describing the mechanistic correlation between q_s,lac and q_s,glu allowing tailored feeding and prevention of sugar accumulation. We believe that this mechanistic model might serve as platform knowledge for E. coli.

Metabolic Control in Mammalian Fed-Batch Cell Cultures for Reduced Lactic Acid Accumulation and Improved Process Robustness

Biomass and cell-specific metabolic rates usually change dynamically over time, making the "feed according to need" strategy difficult to realize in a commercial fed-batch process. We here demonstrate a novel feeding strategy which is designed to hold a particular metabolic state in a fed-batch process by adaptive feeding in real time. The feed rate is calculated with a transferable biomass model based on capacitance, which changes the nutrient flow stoichiometrically in real time. A limited glucose environment was used to confine the cell in a particular metabolic state. In order to cope with uncertainty, two strategies were tested to change the adaptive feed rate and prevent starvation while in limitation: (i) inline pH and online glucose concentration measurement or (ii) inline pH alone, which was shown to be sufficient for the problem statement. In this contribution, we achieved metabolic control within a defined target range. The direct benefit was two-fold: the lactic acid profile was improved and pH could be kept stable. Multivariate Data Analysis (MVDA) has shown that pH influenced lactic acid production or consumption in historical data sets. We demonstrate that a low pH (around 6.8) is not required for our strategy, as glucose availability is already limiting the flux. On the contrary, we boosted glycolytic flux in glucose limitation by setting the pH to 7.4. This new approach led to a yield of lactic acid/glucose (Y L/G) around zero for the whole process time and high titers in our labs. We hypothesize that a higher carbon flux, resulting from a higher pH, may lead to more cells which produce more product. The relevance of this work aims at feeding mammalian cell cultures safely in limitation with a desired metabolic flux range. This resulted in extremely stable, low glucose levels, very robust pH profiles without acid/base interventions and a metabolic state in which lactic acid was consumed instead of being produced from day 1. With this contribution, we wish to extend the basic repertoire of available process control strategies, which will open up new avenues in automation technology and radically improve process robustness in both process development and manufacturing.

Advances in synthetic dynamic circuits design: using novel synthetic parts to engineer new generations of gene oscillations

As bioengineering applications expand, the need to design and implement circuits that exhibit dynamic properties increases. In particular, schemes that control precise patterns of gene expression as a function of time are essential for balancing multiple metabolic objectives in natural and synthetic systems. Given that modularity has been an important component of dynamic circuits, recent efforts to improve dynamic circuits have focused on replacing old parts for new components that increase the robustness, stability, and tunability. In this review, we show that incorporation of novel components such as regulatory noncoding RNAs (ncRNAs), promoter-transcription factor pairs, and metabolite sensors have allowed traditional dynamic circuits to obtain more robust functionality and improved dynamic properties.

A Critical Assessment of Microbiological Biogas to Biomethane Upgrading Systems

Microbiological biogas upgrading could become a promising technology for production of methane (CH(4)). This is, storage of irregular generated electricity results in a need to store electricity generated at peak times for use at non-peak times, which could be achieved in an intermediate step by electrolysis of water to molecular hydrogen (H(2)). Microbiological biogas upgrading can be performed by contacting carbon dioxide (CO(2)), H(2) and hydrogenotrophic methanogenic Archaea either in situ in an anaerobic digester, or ex situ in a separate bioreactor. In situ microbiological biogas upgrading is indicated to require thorough bioprocess development, because only low volumetric CH(4) production rates and low CH(4) fermentation offgas content have been achieved. Higher volumetric production rates are shown for the ex situ microbiological biogas upgrading compared to in situ microbiological biogas upgrading. However, the ex situ microbiological biogas upgrading currently suffers from H(2) gas liquid mass transfer limitation, which results in low volumetric CH(4) productivity compared to pure H(2)/CO(2) conversion to CH(4). If waste gas utilization from biological and industrial sources can be shown without reduction in volumetric CH(4) productivity, as well as if the aim of a single stage conversion to a CH(4) fermentation offgas content exceeding 95 vol% can be demonstrated, ex situ microbiological biogas upgrading with pure or enrichment cultures of methanogens could become a promising future technology for almost CO(2)-neutral biomethane production.

Quantitative comparison of dynamic physiological feeding profiles for recombinant protein production with Pichia pastoris

Pichia pastoris is widely used for the production of recombinant proteins in industrial biotechnology. In general, industrial production processes describe fed-batch processes based on the specific growth rate. Recently, we introduced the specific substrate uptake rate (q_s) as a novel parameter to design fed-batch strategies for P. pastoris. We showed that a dynamic feeding strategy where the feed was adjusted in steps to the maximum specific substrate uptake rate was superior to more traditional strategies in terms of specific productivity. In the present study, we compare three different dynamic feeding strategies based on q_s for a recombinant P. pastoris strain with respect to cell physiology, methanol accumulation, productivity and product quality. By comparing (A) a feeding profile at constant high q_s, (B) a periodically adjusted feeding profile for a stepwise q_s ramp, and (C) a feeding profile at linear increasing q_s, we evaluated potential effects of the mode of feeding. Although a dynamic feeding strategy with stepwise increases of q_s to q_{s max} resulted in the highest specific productivity, a feeding profile where the feeding rate was stepwise increased to a constant high q_s value was superior in terms of the amount of active enzyme produced and in the amount of accumulated methanol. Furthermore, this feeding strategy could be run automatically by integrating an online calculator tool, thus rendering manual interventions by the operator unnecessary.

A dynamic method for the investigation of induced state metabolic capacities as a function of temperature

Background

Science-based recombinant bioprocess designs as well as the design of statistical experimental plans for process optimization (Design of Experiments, DoE) demand information on physiological bioprocess boundaries, such as the onset of acetate production, adaptation times, mixed feed metabolic capabilities or induced state maximum metabolic rates as at the desired cultivation temperature. Dynamic methods provide experimental alternatives to determine this information in a fast and efficient way. Information on maximum metabolic capabilities as a function of temperature is needed in case a reduced cultivation temperature is desirable (e.g. to avoid inclusion body formation) and an appropriate feeding profile is to be designed.

Results

Here, we present a novel dynamic method for the determination of the specific growth rate as a function of temperature for induced recombinant bacterial bioprocesses. The method is based on the control of the residual substrate concentration at non-limiting conditions with dynamic changes in cultivation temperature. The presented method was automated in respect to information extraction and closed loop control by means of in-line Fourier Transformation Infrared Spectroscopy (FTIR) residual substrate measurements and on-line first principle rate-based soft-sensors. Maximum induced state metabolic capabilities as a function of temperature were successfully extracted for a recombinant E. coli C41 fed-batch bioprocess without the need for sampling in a time frame of 20 hours.

Conclusions

The presented method was concluded to allow the fast and automated extraction of maximum metabolic capabilities (specific growth rate) as a function of temperature. This complements the dynamic toolset necessary for science-based recombinant bacterial bioprocess design and DoE design.