Consistent development of bioprocesses from microliter cultures to the industrial scale

Digitalization concepts in academic bioprocess development

Digitalization with integrated devices, digital and physical assistants, automation, and simulation is setting a new direction for laboratory work. Even with complex research workflows, high staff turnover, and a limited budget some laboratories have already shown that digitalization is indeed possible. However, academic bioprocess laboratories often struggle to follow the trend of digitalization. Due to their diverse research circumstances, high variety of team composition, goals, and limitations the concepts are substantially different. Here, we will provide an overview on different aspects of digitalization and describe how academic laboratories successfully digitalized their working environment. The key aspect is the collaboration and communication between IT-experts and scientific staff. The developed digital infrastructure is only useful if it supports the laboratory worker and does not complicate their work. Thereby, laboratory researchers have to collaborate closely with IT-experts in order for a well-developed and maintainable digitalization concept that fits their individual needs and level of complexity. This review may serve as a starting point or a collection of ideas for the transformation toward a digitalized laboratory.

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.

Model-Based Characterization of E. coli Strains with Impaired Glucose Uptake

The bacterium Escherichia coli is a widely used organism in biotechnology. For high space-time yields, glucose-limited fed-batch technology is the industry standard; this is because an overflow metabolism of acetate occurs at high glucose concentrations. As an interesting alternative, various strains with limited glucose uptake have been developed. However, these have not yet been characterized under process conditions. To demonstrate the efficiency of our previously developed high-throughput robotic platform, in the present work, we characterized three different exemplary E. coli knockout (KO) strains with limited glucose uptake capacities at three different scales (microtiter plates, 10 mL bioreactor system and 100 mL bioreactor system) under excess glucose conditions with different initial glucose concentrations. The extensive measurements of growth behavior, substrate consumption, respiration, and overflow metabolism were then used to determine the appropriate growth parameters using a mechanistic mathematical model, which allowed for a comprehensive comparative analysis of the strains. The analysis was performed coherently with these different reactor configurations and the results could be successfully transferred from one platform to another. Single and double KO mutants showed reduced specific rates for substrate uptake q_Smax and acetate production q_Apmax; meanwhile, higher glucose concentrations had adverse effects on the biomass yield coefficient Y_XSem. Additional parameters compared to previous studies for the oxygen uptake rate and carbon dioxide production rate indicated differences in the specific oxygen uptake rate q_Omax. This study is an example of how automated robotic equipment, together with mathematical model-based approaches, can be successfully used to characterize strains and obtain comprehensive information more quickly, with a trade-off between throughput and analytical capacity.

Black glucose-releasing silicon elastomer rings for fed-batch operation allow measurement of the oxygen transfer rate from the top and optical signals from the bottom for each well of a microtiter plate

BACKGROUND

In industrial microbial biotechnology, fed-batch processes are frequently used to avoid undesirable biological phenomena, such as substrate inhibition or overflow metabolism. For targeted process development, fed-batch options for small scale and high throughput are needed. One commercially available fed-batch fermentation system is the FeedPlate^®, a microtiter plate (MTP) with a polymer-based controlled release system. Despite standardisation and easy incorporation into existing MTP handling systems, FeedPlates^® cannot be used with online monitoring systems that measure optically through the transparent bottom of the plate. One such system that is broadly used in biotechnological laboratories, is the commercial BioLector. To allow for BioLector measurements, while applying the polymer-based feeding technology, positioning of polymer rings instead of polymer disks at the bottom of the well has been proposed. This strategy has a drawback: measurement requires an adjustment of the software settings of the BioLector device. This adjustment modifies the measuring position relative to the wells, so that the light path is no longer blocked by the polymer ring, but, traverses through the inner hole of the ring. This study aimed at overcoming that obstacle and allowing for measurement of fed-batch cultivations using a commercial BioLector without adjustment of the relative measurement position within each well.

RESULTS

Different polymer ring heights, colours and positions in the wells were investigated for their influence on maximum oxygen transfer capacity, mixing time and scattered light measurement. Several configurations of black polymer rings were identified that allow measurement in an unmodified, commercial BioLector, comparable to wells without rings. Fed-batch experiments with black polymer rings with two model organisms, E. coli and H. polymorpha, were conducted. The identified ring configurations allowed for successful cultivations, measuring the oxygen transfer rate and dissolved oxygen tension, pH, scattered light and fluorescence. Using the obtained online data, glucose release rates of 0.36 to 0.44 mg/h could be determined. They are comparable to formerly published data of the polymer matrix.

CONCLUSION

The final ring configurations allow for measurements of microbial fed-batch cultivations using a commercial BioLector without requiring adjustments of the instrumental measurement setup. Different ring configurations achieve similar glucose release rates. Measurements from above and below the plate are possible and comparable to measurements of wells without polymer rings. This technology enables the generation of a comprehensive process understanding and target-oriented process development for industrial fed-batch processes.

Explore or exploit? A model-based screening strategy for PETase secretion by Corynebacterium glutamicum

Extracellular production of target proteins simplifies downstream processing due to obsolete cell disruption. However, optimal combinations of a heterologous protein, suitable signal peptide, and secretion host can currently not be predicted, resulting in large strain libraries that need to be tested. On the experimental side, this challenge can be tackled by miniaturization, parallelization, and automation, which provide high-throughput screening data. These data need to be condensed into a candidate ranking for decision-making to focus bioprocess development on the most promising candidates. We screened for Bacillus subtilis signal peptides mediating Sec secretion of two polyethylene terephthalate degrading enzymes (PETases), leaf-branch compost cutinase (LCC) and polyester hydrolase mutants, by Corynebacterium glutamicum. We developed a fully automated screening process and constructed an accompanying Bayesian statistical modeling framework, which we applied in screenings for highest activity in 4-nitrophenyl palmitate degradation. In contrast to classical evaluation methods, batch effects and biological errors are taken into account and their uncertainty is quantified. Within only two rounds of screening, the most suitable signal peptide was identified for each PETase. Results from LCC secretion in microliter-scale cultivation were shown to be scalable to laboratory-scale bioreactors. This work demonstrates an experiment-modeling loop that can accelerate early-stage screening in a way that experimental capacities are focused to the most promising strain candidates. Combined with high-throughput cloning, this paves the way for using large strain libraries of several hundreds of strains in a Design-Build-Test-Learn approach.

Optimization and Scale-Up of Fermentation Processes Driven by Models

In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.

Promoting Sustainability through Next-Generation Biologics Drug Development

The fourth industrial revolution in 2011 aimed to transform the traditional manufacturing processes. As part of this revolution, disruptive innovations in drug development and data science approaches have the potential to optimize CMC (chemistry, manufacture, and control). The real-time simulation of processes using “digital twins” can maximize efficiency while improving sustainability. As part of this review, we investigate how the World Health Organization’s 17 sustainability goals can apply toward next-generation drug development. We analyze the state-of-the-art laboratory leadership, inclusive personnel recruiting, the latest therapy approaches, and intelligent process automation. We also outline how modern data science techniques and machine tools for CMC help to shorten drug development time, reduce failure rates, and minimize resource usage. Finally, we systematically analyze and compare existing approaches to our experiences with the high-throughput laboratory KIWI-biolab at the TU Berlin. We describe a sustainable business model that accelerates scientific innovations and supports global action toward a sustainable future.

Automated Bioprocess Feedback Operation in a High-Throughput Facility via the Integration of a Mobile Robotic Lab Assistant

The development of biotechnological processes is challenging due to the diversity of process parameters. For efficient upstream development, parallel cultivation systems have proven to reduce costs and associated timelines successfully while offering excellent process control. However, the degree of automation of such small-scale systems is comparatively low, and necessary sample analysis requires manual steps. Although the subsequent analysis can be performed in a high-throughput manner, the integration of analytical devices remains challenging, especially when cultivation and analysis laboratories are spatially separated. Mobile robots offer a potential solution, but their implementation in research laboratories is not widely adopted. Our approach demonstrates the integration of a small-scale cultivation system into a liquid handling station for an automated cultivation and sample procedure. The samples are transported via a mobile robotic lab assistant and subsequently analyzed by a high-throughput analyzer. The process data are stored in a centralized database. The mobile robotic workflow guarantees a flexible solution for device integration and facilitates automation. Restrictions regarding spatial separation of devices are circumvented, enabling a modular platform throughout different laboratories. The presented cultivation platform is evaluated on the basis of industrially relevant E. coli BW25113 high cell density fed-batch cultivation. The necessary magnesium addition for reaching high cell densities in mineral salt medium is automated via a feedback operation loop between the analysis station located in the adjacent room and the cultivation system. The modular design demonstrates new opportunities for advanced control options and the suitability of the platform for accelerating bioprocess development. This study lays the foundation for a fully integrated facility, where the physical connection of laboratory equipment is achieved through the successful use of a mobile robotic lab assistant, and different cultivation scales can be coupled through the common data infrastructure.

Growth and eGFP Production of CHO-K1 Suspension Cells Cultivated From Single Cell to Laboratory Scale

Scaling down bioproduction processes has become a major driving force for more accelerated and efficient process development over the last decades. Especially expensive and time-consuming processes like the production of biopharmaceuticals with mammalian cell lines benefit clearly from miniaturization, due to higher parallelization and increased insights while at the same time decreasing experimental time and costs. Lately, novel microfluidic methods have been developed, especially microfluidic single-cell cultivation (MSCC) devices have been proved to be valuable to miniaturize the cultivation of mammalian cells. So far, growth characteristics of microfluidic cultivated cell lines were not systematically compared to larger cultivation scales; however, validation of a miniaturization tool against initial cultivation scales is mandatory to prove its applicability for bioprocess development. Here, we systematically investigate growth, morphology, and eGFP production of CHO-K1 cells in different cultivation scales ranging from a microfluidic chip (230 nl) to a shake flask (125 ml) and laboratory-scale stirred tank bioreactor (2.0 L). Our study shows a high comparability regarding specific growth rates, cellular diameters, and eGFP production, which proves the feasibility of MSCC as a miniaturized cultivation tool for mammalian cell culture. In addition, we demonstrate that MSCC provides insights into cellular heterogeneity and single-cell dynamics concerning growth and production behavior which, when occurring in bioproduction processes, might severely affect process robustness.

Screening for optimal protease producing Bacillus licheniformis strains with polymer-based controlled-release fed-batch microtiter plates

Background

Substrate-limited fed-batch conditions have the favorable effect of preventing overflow metabolism, catabolite repression, oxygen limitation or inhibition caused by elevated substrate or osmotic concentrations. Due to these favorable effects, fed-batch mode is predominantly used in industrial production processes. In contrast, screening processes are usually performed in microtiter plates operated in batch mode. This leads to a different physiological state of the production organism in early screening and can misguide the selection of potential production strains. To close the gap between screening and production conditions, new techniques to enable fed-batch mode in microtiter plates have been described. One of these systems is the ready-to-use and disposable polymer-based controlled-release fed-batch microtiter plate (fed-batch MTP). In this work, the fed-batch MTP was applied to establish a glucose-limited fed-batch screening procedure for industrially relevant protease producing Bacillus licheniformis strains.

Results

To achieve equal initial growth conditions for different clones with the fed-batch MTP, a two-step batch preculture procedure was developed. Based on this preculture procedure, the standard deviation of the protease activity of glucose-limited fed-batch main culture cultivations in the fed-batch MTP was ± 10%. The determination of the number of replicates revealed that a minimum of 6 parallel cultivations were necessary to identify clones with a statistically significant increased or decreased protease activity. The developed glucose-limited fed-batch screening procedure was applied to 13 industrially-relevant clones from two B. licheniformis strain lineages. It was found that 12 out of 13 clones (92%) were classified similarly as in a lab-scale fed-batch fermenter process operated under glucose-limited conditions. When the microtiter plate screening process was performed in batch mode, only 5 out of 13 clones (38%) were classified similarly as in the lab-scale fed-batch fermenter process.

Conclusion

The glucose-limited fed-batch screening process outperformed the usual batch screening process in terms of the predictability of the clone performance under glucose-limited fed-batch fermenter conditions. These results highlight that the implementation of glucose-limited fed-batch conditions already in microtiter plate scale is crucial to increase the precision of identifying improved protease producing B. licheniformis strains. Hence, the fed-batch MTP represents an efficient high-throughput screening tool that aims at closing the gap between screening and production conditions.

Model-based workflow for scale-up of process strategies developed in miniaturized bioreactor systems

Miniaturized bioreactor (MBR) systems are routinely used in the development of mammalian cell culture processes. However, scale-up of process strategies obtained in MBR- to larger scale is challenging due to mainly non-holistic scale-up approaches. In this study, a model-based workflow is introduced to quantify differences in the process dynamics between bioreactor scales and thus enable a more knowledge-driven scale-up. The workflow is applied to two case studies with antibody-producing Chinese hamster ovary cell lines. With the workflow, model parameter distributions are estimated first under consideration of experimental variability for different scales. Second, the obtained individual model parameter distributions are tested for statistical differences. In case of significant differences, model parametric distributions are transferred between the scales. In case study I, a fed-batch process in a microtiter plate (4 ml working volume) and lab-scale bioreactor (3750 ml working volume) was mathematically modeled and evaluated. No significant differences were identified for model parameter distributions reflecting process dynamics. Therefore, the microtiter plate can be applied as scale-down tool for the lab-scale bioreactor. In case study II, a fed-batch process in a 24-Deep-Well-Plate (2 ml working volume) and shake flask (40 ml working volume) with two feed media was investigated. Model parameter distributions showed significant differences. Thus, process strategies were mathematically transferred, and model predictions were simulated for a new shake flask culture setup and confirmed in validation experiments. Overall, the workflow enables a knowledge-driven evaluation of scale-up for a more efficient bioprocess design and optimization.

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.

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

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

Screening of a genome-reduced Corynebacterium glutamicum strain library for improved heterologous cutinase secretion

The construction of microbial platform organisms by means of genome reduction is an ongoing topic in biotechnology. In this study, we investigated whether the deletion of single or multiple gene clusters has a positive effect on the secretion of cutinase from Fusarium solani pisi in the industrial workhorse Corynebacterium glutamicum. A total of 22 genome-reduced strain variants were compared applying two Sec signal peptides from Bacillus subtilis. High-throughput phenotyping using robotics-integrated microbioreactor technology with automated harvesting revealed distinct cutinase secretion performance for a specific combination of signal peptide and genomic deletions. The biomass-specific cutinase yield for strain GRS41_51_NprE was increased by ~ 200%, although the growth rate was reduced by ~ 60%. Importantly, the causative deletions of genomic clusters cg2801-cg2828 and rrnC-cg3298 could not have been inferred a priori. Strikingly, bioreactor fed-batch cultivations at controlled growth rates resulted in a complete reversal of the screening results, with the cutinase yield for strain GRS41_51_NprE dropping by ~ 25% compared to the reference strain. Thus, the choice of bioprocess conditions may turn a 'high-performance' strain from batch screening into a 'low-performance' strain in fed-batch cultivation. In conclusion, future studies are needed in order to understand metabolic adaptations of C. glutamicum to both genomic deletions and different bioprocess conditions.

Monitoring Parallel Robotic Cultivations with Online Multivariate Analysis

In conditional microbial screening, a limited number of candidate strains are tested at different conditions searching for the optimal operation strategy in production (e.g., temperature and pH shifts, media composition as well as feeding and induction strategies). To achieve this, cultivation volumes of >10 mL and advanced control schemes are required to allow appropriate sampling and analyses. Operations become even more complex when the analytical methods are integrated into the robot facility. Among other multivariate data analysis methods, principal component analysis (PCA) techniques have especially gained popularity in high throughput screening. However, an important issue specific to high throughput bioprocess development is the lack of so-called golden batches that could be used as a basis for multivariate analysis. In this study, we establish and present a program to monitor dynamic parallel cultivations in a high throughput facility. PCA was used for process monitoring and automated fault detection of 24 parallel running experiments using recombinant E. coli cells expressing three different fluorescence proteins as the model organism. This approach allowed for capturing events like stirrer failures and blockage of the aeration system and provided a good signal to noise ratio. The developed application can be easily integrated in existing data- and device-infrastructures, allowing automated and remote monitoring of parallel bioreactor systems.

Robust microorganisms for biofuel and chemical production from municipal solid waste

Background

Worldwide 3.4 billion tonnes of municipal solid waste (MSW) will be produced annually by 2050, however, current approaches to MSW management predominantly involve unsustainable practices like landfilling and incineration. The organic fraction of MSW (OMSW) typically comprises ~ 50% lignocellulose-rich material but is underexplored as a biomanufacturing feedstock due to its highly inconsistent and heterogeneous composition. This study sought to overcome the limitations associated with studying MSW-derived feedstocks by using OMSW produced from a realistic and reproducible MSW mixture on a commercial autoclave system. The resulting OMSW fibre was enzymatically hydrolysed and used to screen diverse microorganisms of biotechnological interest to identify robust species capable of fermenting this complex feedstock.

Results

The autoclave pre-treated OMSW fibre contained a polysaccharide fraction comprising 38% cellulose and 4% hemicellulose. Enzymatic hydrolysate of OMSW fibre was high in d-glucose (5.5% w/v) and d-xylose (1.8%w/v) but deficient in nitrogen and phosphate. Although relatively low levels of levulinic acid (30 mM) and vanillin (2 mM) were detected and furfural and 5-hydroxymethylfurfural were absent, the hydrolysate contained an abundance of potentially toxic metals (0.6% w/v). Hydrolysate supplemented with 1% yeast extract to alleviate nutrient limitation was used in a substrate-oriented shake-flask screen with eight biotechnologically useful microorganisms (Clostridium saccharoperbutylacetonicum, Escherichia coli, Geobacillus thermoglucosidasius, Pseudomonas putida, Rhodococcus opacus, Saccharomyces cerevisiae, Schizosaccharomyces pombe and Zymomonas mobilis). Each species’ growth and productivity were characterised and three species were identified that robustly and efficiently fermented OMSW fibre hydrolysate without significant substrate inhibition: Z. mobilis, S. cerevisiae and R. opacus, respectively produced product to 69%, 70% and 72% of the maximum theoretical fermentation yield and could theoretically produce 136 kg and 139 kg of ethanol and 91 kg of triacylglycerol (TAG) per tonne of OMSW.

Conclusions

Developing an integrated biorefinery around MSW has the potential to significantly alleviate the environmental burden of current waste management practices. Substrate-oriented screening of a representative and reproducible OMSW-derived fibre identified microorganisms intrinsically suited to growth on OMSW hydrolysates. These species are promising candidates for developing an MSW biorefining platform and provide a foundation for future studies aiming to valorise this underexplored feedstock.

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.

Establishing a Fed-Batch Process for Protease Expression with Bacillus licheniformis in Polymer-Based Controlled-Release Microtiter Plates

Introducing fed-batch mode in early stages of development projects is crucial for establishing comparable conditions to industrial fed-batch fermentation processes. Therefore, cost efficient and easy to use small-scale fed-batch systems that can be integrated into existing laboratory equipment and workflows are required. Recently, a novel polymer-based controlled-release fed-batch microtiter plate is described. In this work, the polymer-based controlled-release fed-batch microtiter plate is used to investigate fed-batch cultivations of a protease producing Bacillus licheniformis culture. Therefore, the oxygen transfer rate (OTR) is online-monitored within each well of the polymer-based controlled-release fed-batch microtiter plate using a µRAMOS device. Cultivations in five individual polymer-based controlled-release fed-batch microtiter plates of two production lots show good reproducibility with a mean coefficient of variation of 9.2%. Decreasing initial biomass concentrations prolongs batch phase while simultaneously postponing the fed-batch phase. The initial liquid filling volume affects the volumetric release rate, which is directly translated in different OTR levels of the fed-batch phase. An increasing initial osmotic pressure within the mineral medium decreases both glucose release and protease yield. With the volumetric glucose release rate as scale-up criterion, microtiter plate- and shake flask-based fed-batch cultivations are highly comparable. On basis of the small-scale fed-batch cultivations, a mechanistic model is established and validated. Model-based simulations coincide well with the experimentally acquired data.

Integrated Robotic Mini Bioreactor Platform for Automated, Parallel Microbial Cultivation With Online Data Handling and Process Control

During process development, the experimental search space is defined by the number of experiments that can be performed in specific time frames but also by its sophistication (e.g., inputs, sensors, sampling frequency, analytics). High-throughput liquid-handling stations can perform a large number of automated experiments in parallel. Nevertheless, the experimental data sets that are obtained are not always relevant for development of industrial bioprocesses, leading to a high rate of failure during scale-up. We present an automated mini bioreactor platform that enables parallel cultivations in the milliliter scale with online monitoring and control, well-controlled conditions, and advanced feeding strategies similar to industrial processes. The combination of two liquid handlers allows both automated mini bioreactor operation and at-line analysis in parallel. A central database enables end-to-end data exchange and fully integrated device and process control. A model-based operation algorithm allows for the accurate performance of complex cultivations for scale-down studies and strain characterization via optimal experimental redesign, significantly increasing the reliability and transferability of data throughout process development. The platform meets the tradeoff between experimental throughput and process control and monitoring comparable to laboratory-scale bioreactors.

Monte Carlo Simulations for the Analysis of Non-linear Parameter Confidence Intervals in Optimal Experimental Design

Especially in biomanufacturing, methods to design optimal experiments are a valuable technique to fully exploit the potential of the emerging technical possibilities that are driving experimental miniaturization and parallelization. The general objective is to reduce the experimental effort while maximizing the information content of an experiment, speeding up knowledge gain in R&D. The approach of model-based design of experiments (known as MBDoE) utilizes the information of an underlying mathematical model describing the system of interest. A common method to predict the accuracy of the parameter estimates uses the Fisher information matrix to approximate the 90% confidence intervals of the estimates. However, for highly non-linear models, this method might lead to wrong conclusions. In such cases, Monte Carlo sampling gives a more accurate insight into the parameter's estimate probability distribution and should be exploited to assess the reliability of the approximations made through the Fisher information matrix. We first introduce the model-based optimal experimental design for parameter estimation including parameter identification and validation by means of a simple non-linear Michaelis-Menten kinetic and show why Monte Carlo simulations give a more accurate depiction of the parameter uncertainty. Secondly, we propose a very robust and simple method to find optimal experimental designs using Monte Carlo simulations. Although computational expensive, the method is easy to implement and parallelize. This article focuses on practical examples of bioprocess engineering but is generally applicable in other fields.

Polymer-based controlled-release fed-batch microtiter plate - diminishing the gap between early process development and production conditions

BACKGROUND

Fed-batch conditions are advantageous for industrial cultivations as they avoid unfavorable phenomena appearing in batch cultivations. Those are for example the formation of overflow metabolites, catabolite repression, oxygen limitation or inhibition due to elevated osmotic concentrations. For both, the early bioprocess development and the optimization of existing bioprocesses, small-scale reaction vessels are applied to ensure high throughput, low costs and prompt results. However, most conventional small-scale procedures work in batch operation mode, which stands in contrast to fed-batch conditions in large-scale bioprocesses. Extensive expenditure for installations and operation accompany almost all cultivation systems in the market allowing fed-batch conditions in small-scale. An alternative, more cost efficient enzymatic glucose release system is strongly influenced by environmental conditions. To overcome these issues, this study investigates a polymer-based fed-batch system for controlled substrate release in microtiter plates.

RESULTS

Immobilizing a solid silicone matrix with embedded glucose crystals at the bottom of each well of a microtiter plate is a suitable technique for implementing fed-batch conditions in microtiter plates. The results showed that the glucose release rate depends on the osmotic concentration, the pH and the temperature of the medium. Moreover, the applied nitrogen source proved to influence the glucose release rate. A new developed mathematical tool predicts the glucose release for various media conditions. The two model organisms E. coli and H. polymorpha were cultivated in the fed-batch microtiter plate to investigate the general applicability for microbial systems. Online monitoring of the oxygen transfer rate and offline analysis of substrate, product, biomass and pH confirmed that fed-batch conditions are comparable to large-scale cultivations. Furthermore, due to fed-batch conditions in microtiter plates, product formation could be enhanced by the factor 245 compared to batch cultivations.

CONCLUSIONS

The polymer-based fed-batch microtiter plate represents a sophisticated and cost efficient system to mimic typical industrial fed-batch conditions in small-scale. Thus, a more reliable strain screening and early process development can be performed. A systematical scale-down with low expenditure of work, time and money is possible.

An Industrial Perspective on Scale-Down Challenges Using Miniaturized Bioreactors

Miniaturized stirred bioreactors (MSBRs) are gaining popularity as a cost-effective approach to scale-down experimentation. However, realizing conditions that reflect the large-scale process accurately can be challenging. This article highlights common challenges of using MSBRs for scale-down. The fundamental difference between oxygen mass transfer coefficient (k_La) and oxygen transfer rate scaling is addressed and the difficulty of achieving turbulent flow and industrially relevant tip speeds is described. More practical challenges of using MSBR systems for scale-down are also discussed, including the risk of vortex formation, changed volume dynamics, and wall growth. By highlighting these challenges, the article aims to create more awareness of these difficulties and to contribute to improved design of scale-down experiments.

Accelerated Bioprocess Development of Endopolygalacturonase-Production with Saccharomyces cerevisiae Using Multivariate Prediction in a 48 Mini-Bioreactor Automated Platform

Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations are a promising alternative to accelerate and optimize bioprocess development allowing for sophisticated cultivation experiments in high throughput. These include fed-batch and continuous cultivations with multiple options of process control and sample analysis which deliver valuable screening tools for industrial production. However, the model-based methods needed to operate these robotic facilities efficiently considering the complexity of biological processes are missing. We present an automated experiment facility that integrates online data handling, visualization and treatment using multivariate analysis approaches to design and operate dynamical experimental campaigns in up to 48 mini-bioreactors (8⁻12 mL) in parallel. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed, running and comparing 16 experimental conditions in triplicate. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable to different strains and cultivation strategies, and suitable for automatized process development reducing the experimental times and costs.

Rocking Aspergillus: morphology-controlled cultivation of Aspergillus niger in a wave-mixed bioreactor for the production of secondary metabolites

Background

Filamentous fungi including Aspergillus niger are cell factories for the production of organic acids, proteins and bioactive compounds. Traditionally, stirred-tank reactors (STRs) are used to cultivate them under highly reproducible conditions ensuring optimum oxygen uptake and high growth rates. However, agitation via mechanical stirring causes high shear forces, thus affecting fungal physiology and macromorphologies. Two-dimensional rocking-motion wave-mixed bioreactor cultivations could offer a viable alternative to fungal cultivations in STRs, as comparable gas mass transfer is generally achievable while deploying lower friction and shear forces. The aim of this study was thus to investigate for the first time the consequences of wave-mixed cultivations on the growth, macromorphology and product formation of A. niger.

Results

We investigated the impact of hydrodynamic conditions on A. niger cultivated at a 5 L scale in a disposable two-dimensional rocking motion bioreactor (CELL-tainer^®) and a BioFlo STR (New Brunswick^®), respectively. Two different A. niger strains were analysed, which produce heterologously the commercial drug enniatin B. Both strains expressed the esyn1 gene that encodes a non-ribosomal peptide synthetase ESYN under control of the inducible Tet-on system, but differed in their dependence on feeding with the precursors d-2-hydroxyvaleric acid and l-valine. Cultivations of A. niger in the CELL-tainer resulted in the formation of large pellets, which were heterogeneous in size (diameter 300–800 μm) and not observed during STR cultivations. When talcum microparticles were added, it was possible to obtain a reduced pellet size and to control pellet heterogeneity (diameter 50–150 μm). No foam formation was observed under wave-mixed cultivation conditions, which made the addition of antifoam agents needless. Overall, enniatin B titres of about 1.5–2.3 g L⁻¹ were achieved in the CELL-tainer^® system, which is about 30–50% of the titres achieved under STR conditions.

Conclusions

This is the first report studying the potential use of single-use wave-mixed reactor systems for the cultivation of A. niger. Although final enniatin yields are not competitive yet with titres achieved under STR conditions, wave-mixed cultivations open up new avenues for the cultivation of shear-sensitive mutant strains as well as high cell-density cultivations.

Automated Cell Treatment for Competence and Transformation of Escherichia coli in a High-Throughput Quasi-Turbidostat Using Microtiter Plates

Metabolic engineering and genome editing strategies often lead to large strain libraries of a bacterial host. Nevertheless, the generation of competent cells is the basis for transformation and subsequent screening of these strains. While preparation of competent cells is a standard procedure in flask cultivations, parallelization becomes a challenging task when working with larger libraries and liquid handling stations as transformation efficiency depends on a distinct physiological state of the cells. We present a robust method for the preparation of competent cells and their transformation. The strength of the method is that all cells on the plate can be maintained at a high growth rate until all cultures have reached a defined cell density regardless of growth rate and lag phase variabilities. This allows sufficient transformation in automated high throughput facilities and solves important scheduling issues in wet-lab library screenings. We address the problem of different growth rates, lag phases, and initial cell densities inspired by the characteristics of continuous cultures. The method functions on a fully automated liquid handling platform including all steps from the inoculation of the liquid cultures to plating and incubation on agar plates. The key advantage of the developed method is that it enables cell harvest in 96 well plates at a predefined time by keeping fast growing cells in the exponential phase as in turbidostat cultivations. This is done by a periodic monitoring of cell growth and a controlled dilution specific for each well. With the described methodology, we were able to transform different strains in parallel. The transformants produced can be picked and used in further automated screening experiments. This method offers the possibility to transform any combination of strain- and plasmid library in an automated high-throughput system, overcoming an important bottleneck in the high-throughput screening and the overall chain of bioprocess development.

Streptomyces clavuligerus shows a strong association between TCA cycle intermediate accumulation and clavulanic acid biosynthesis

Clavulanic acid (CA) is produced by Streptomyces clavuligerus (S. clavuligerus) as a secondary metabolite. Knowledge about the carbon flux distribution along the various routes that supply CA precursors would certainly provide insights about metabolic performance. In order to evaluate metabolic patterns and the possible accumulation of tricarboxylic acid (TCA) cycle intermediates during CA biosynthesis, batch and subsequent continuous cultures with steadily declining feed rates were performed with glycerol as the main substrate. The data were used to in silico explore the metabolic capabilities and the accumulation of metabolic intermediates in S. clavuligerus. While clavulanic acid accumulated at glycerol excess, it steadily decreased at declining dilution rates; CA synthesis stopped when glycerol became the limiting substrate. A strong association of succinate, oxaloacetate, malate, and acetate accumulation with CA production in S. clavuligerus was observed, and flux balance analysis (FBA) was used to describe the carbon flux distribution in the network. This combined experimental and numerical approach also identified bottlenecks during the synthesis of CA in a batch and subsequent continuous cultivation and demonstrated the importance of this type of methodologies for a more advanced understanding of metabolism; this potentially derives valuable insights for future successful metabolic engineering studies in S. clavuligerus.

Microbioreactor Systems for Accelerated Bioprocess Development

In recent years, microbioreactor (MBR) systems have evolved towards versatile bioprocess engineering tools. They provide a unique solution to combine higher experimental throughput with extensive bioprocess monitoring and control, which is indispensable to develop economically and ecologically competitive bioproduction processes. MBR systems are based either on down-scaled stirred tank reactors or on advanced shaken microtiter plate cultivation devices. Importantly, MBR systems make use of optical measurements for non-invasive, online monitoring of important process variables like biomass concentration, dissolved oxygen, pH, and fluorescence. The application range of MBR systems can be further increased by integration into liquid handling robots, enabling automatization and, thus standardization, of various handling and operation procedures. Finally, the tight integration of quantitative strain phenotyping with bioprocess development under industrially relevant conditions greatly increases the probability of finding the right combination of producer strain and bioprocess control strategy. This review will discuss the current state of the art in the field of MBR systems and we can readily conclude that their importance for industrial biotechnology will further increase in the near future.

Detection of growth rate-dependent product formation in miniaturized parallel fed-batch cultivations

Saccharomyces cerevisiae is a popular expression system for recombinant proteins. In most cases, production processes are performed as carbon-limited fed-batch cultures to avoid aerobic ethanol formation. Especially for constitutive expression systems, the specific product formation rate depends on the specific growth rate. The development of optimal feeding strategies strongly depends on laboratory-scale cultivations, which are time and resource consuming, especially when continuous experiments are carried out. It is therefore beneficial for accelerated process development to look at alternatives. In this study, S. cerevisiae AH22 secreting a heterologous endo-polygalacturonase (EPG) was characterized in microwell plates with an enzyme-based fed-batch medium. Through variation of the glucose release rate, different growth profiles were established and the impact on EPG secretion was analyzed. Product formation rates of 200-400 U (gx h)-1 were determined. As a reference, bioreactor experiments using the change-stat cultivation technique were performed. The growth-dependent product formation was analyzed over dilution rates of D = 0.01-0.35 with smooth change of D at a rate of 0.003 h-2. EPG production was found to be comparable with a qp of 400 U (gx h)-1 at D = 0.27 h-1. The presented results indicate that parallel miniaturized fed-batch cultures can be applied to determine product formation profiles of putative production strains. With further automation and parallelization of the concept, strain characterization can be performed in shorter time.

Customized microscale approach for optimizing two-phase bio-oxidations of alkanes with high reproducibility

Background

Numerous challenges remain to achieve industrially competitive space–time yields for bio-oxidations. The ability to rapidly screen bioconversion reactions for characterization and optimization is of major importance in bioprocess development and biocatalyst selection; studies at conventional lab scale are time consuming and labor intensive with low experimental throughput. The direct ω-oxyfunctionalization of aliphatic alkanes in a regio- and chemoselective manner is efficiently catalyzed by monooxygenases such as the AlkBGT enzyme complex from Pseudomonas putida under mild conditions. However, the adoption of microscale tools for these highly volatile substrates has been hindered by excessive evaporation and material incompatibility.

Results

This study developed and validated a robust high-throughput microwell platform for whole-cell two-liquid phase bio-oxidations of highly volatile n-alkanes. Using microwell plates machined from polytetrafluoroethylene and a sealing clamp, highly reproducible results were achieved with no significant variability such as edge effects determined. A design of experiment approach using a response surface methodology was adopted to systematically characterize the system and identify non-limiting conditions for a whole cell bioconversion of dodecane. Using resting E. coli cells to control cell concentration and reducing the fill volume it is possible to operate in non-limiting conditions with respect to oxygen and glucose whilst achieving relevant total product yields (combining 1-dodecanol, dodecanal and dodecanoic acid) of up to 1.5 mmol g_DCW⁻¹.

Conclusions

Overall, the developed microwell plate greatly improves experimental throughput, accelerating the screening procedures specifically for biocatalytic processes in non-conventional media. Its simplicity, robustness and standardization ensure high reliability of results.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-017-0788-4) contains supplementary material, which is available to authorized users.

High throughput automated microbial bioreactor system used for clone selection and rapid scale-down process optimization

High throughput automated fermentation systems have become a useful tool in early bioprocess development. In this study, we investigated a 24 x 15 mL single use microbioreactor system, ambr 15f, designed for microbial culture. We compared the fed‐batch growth and production capabilities of this system for two Escherichia coli strains, BL21 (DE3) and MC4100, and two industrially relevant molecules, hGH and scFv. In addition, different carbon sources were tested using bolus, linear or exponential feeding strategies, showing the capacity of the ambr 15f system to handle automated feeding. We used power per unit volume (P/V) as a scale criterion to compare the ambr 15f with 1 L stirred bioreactors which were previously scaled‐up to 20 L with a different biological system, thus showing a potential 1,300 fold scale comparability in terms of both growth and product yield. By exposing the cells grown in the ambr 15f system to a level of shear expected in an industrial centrifuge, we determined that the cells are as robust as those from a bench scale bioreactor. These results provide evidence that the ambr 15f system is an efficient high throughput microbial system that can be used for strain and molecule selection as well as rapid scale‐up. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 34:58–68, 2018

Valorization of Proteins from Co- and By-Products from the Fish and Meat Industry

Large volumes of protein-rich residual raw materials, such as heads, bones, carcasses, blood, skin, viscera, hooves and feathers, are created as a result of processing of animals from fisheries, aquaculture, livestock and poultry sectors. These residuals contain proteins and other essential nutrients with potentially bioactive properties, eligible for recycling and upgrading for higher-value products, e.g. for human, pet food and feed purposes. Here, we aim to cover all the important aspects of achieving optimal utilization of proteins in such residual raw materials, identifying those eligible for human consumption as co-products and for feed applications as by-products. Strict legislation regulates the utilization of various animal-based co- and by-products, representing a major hurdle if not addressed properly. Thorough understanding and optimization of all parts of the production chain, including conservation and processing, are important prerequisites for successful upgrading and industrial implementation of such products. This review includes industrially applied technologies such as freezing/cooling, acid preservation, salting, rendering and protein hydrolysis. In this regard, it is important to achieve stable production and quality through all the steps in the manufacturing chain, preferably supported by at- or online quality control points in the actual processing step. If aiming for the human market, knowledge of consumer trends and awareness are important for production and successful introduction of new products and ingredients.

Industrial biomanufacturing: The future of chemical production

The current model for industrial chemical manufacturing employs large-scale megafacilities that benefit from economies of unit scale. However, this strategy faces environmental, geographical, political, and economic challenges associated with energy and manufacturing demands. We review how exploiting biological processes for manufacturing (i.e., industrial biomanufacturing) addresses these concerns while also supporting and benefiting from economies of unit number. Key to this approach is the inherent small scale and capital efficiency of bioprocesses and the ability of engineered biocatalysts to produce designer products at high carbon and energy efficiency with adjustable output, at high selectivity, and under mild process conditions. The biological conversion of single-carbon compounds represents a test bed to establish this paradigm, enabling rapid, mobile, and widespread deployment, access to remote and distributed resources, and adaptation to new and changing markets.