Scaling up E. coli from the lab to industrial conditions: Lessons learned to engineer robust processes and production hosts

For commercialization, strain and bioprocess developments need to be successfully transferred from the lab to industrial scale. Often, this step crucially decides about economic feasibility and survival of the approach. Accordingly, profound understanding of impact factors that hamper the successful scale-up is key, either to create novel microbial production platforms with enhanced robustness or to improve bioreactor design targeting minimized impact on cellular performance. Using an experimental scale-up simulator consisting of a stirred tank reactor (STR) and a plug flow reactor (PFR) Escherichia coli was exposed to typical large-scale mixing conditions in continuous experiments. Installing mixing times of about 110 seconds and simulating fluctuating availability of carbon and nitrogen sources, short-term responses revealed the repeated on/off switching of about 600 genes (Löffler et al.,Metab Eng 2016; Simen et al. Microbial Biotechnol 2017). Dynamics of gene expression and protein formation were modelled using an agent-based approach and simulating large-scale conditions (Nieß et al. Frontiers Microbiol., 2017). ATP balancing of gene expression and protein formation showed that maintenance demands increased by ~50%. Thereof, strategies for genome reduction were deduced. Large-scale simulation revealed the dominating role of the alarmone ppGpp which triggers the on/off-switching of the stringent response. Accordingly, a novel chassis was engineered such that intracellular ppGpp levels were no more affected thereby disconnecting the extracellular stimulus from the intracellular response, even under nitrogen or carbon limitation. Experimental studies outline the energetic advantages of stringent response deficient production hosts. Additionally, changes were implemented in central metabolism finally yielding E. coli HGT (high glucose throughput, Michalowski et al., Metab Eng 2017). The patent-filed strain offers about 10 fold risen glucose uptake rates (relative to maintenance demands under glucose limitation) under resting conditions which is beneficial for large-scale production processes

Transferring bubble breakage models tailored for Euler-Euler approaches to Euler-Lagrange simulations

Most bubble breakage models have been developed for multiphase simulations using Euler-Euler (EE) approaches. Commonly, they are linked with population balance models (PBM) and are validated by making use of Reynolds-averaged Navier-Stokes (RANS) turbulence models. The latter, however, may be replaced by alternate approaches such as Large Eddy simulations (LES) that play a pivotal role in current developments based on lattice Boltzmann (LBM) technologies. Consequently, this study investigates the possibility of transferring promising bubble breakage models from the EE framework into Euler-Lagrange (EL) settings aiming to perform LES. Using our own model, it was possible to reproduce similar bubble size distributions (BSDs) for EL and EE simulations. Therefore, the critical Weber (Wecrit) number served as a threshold value for the occurrence of bubble breakage events. Wecrit depended on the bubble daughter size distribution (DSD) and a set minimum time between two consecutive bubble breakage events. The commercial frameworks Ansys Fluent and M-Star were applied for EE and EL simulations, respectively. The latter enabled the implementation of LES, i.e., the use of a turbulence model with non-time averaged entities. By properly choosing Wecrit, it was possible to successfully transfer two commonly applied bubble breakage models from EE to EL. Based on the mechanism of bubble breakage, Wecrit values of 7 and 11 were determined, respectively. Optimum Wecrit were identified as fitting the shape of DSDs, as this turned out to be a key criterion for reaching optimum prediction quality. Optimum Wecrit values hold true for commonly applied operational conditions in aerated bioreactors, considering water as the matrix

CO2 - intrinsic product, essential substrate and regulatory trigger of microbial and mammalian production processes

Carbon dioxide formation mirrors the final carbon oxidation steps of aerobic metabolism in microbial and mammalian cells. As a consequence CO2/HCO3- dissociation equilibria arise in fermenters by the growing culture. Anaplerotic reactions make use of the abundant CO2/HCO3- levels for refueling citric acid cycle demands and for enabling oxaloacetate derived products. At the same time CO2 is released manifold in metabolic reactions via decarboxylation activity. The levels of extracellular CO2/HCO3- depend on cellular activities and physical constraints such like hydrostatic pressures, aeration and the efficiency of mixing in large-scale bioreactors. Besides, local CO2/HCO3- levels might also act as metabolic inhibitors or transcriptional effectors triggering regulatory events inside the cells. This review gives an overview about fundamental physicochemical properties of CO2/HCO3- in microbial and mammalian cultures effecting cellular physiology, production processes, metabolic activity and transcriptional regulation

Compartment-specific metabolome analysis reveals the tight link between IgG1 formation and necessarily high mitochondrial shuttle activities in Chinese Hamster Ovary cells

Chinese hamster ovary (CHO) cells are the dominating host for the production of pharmaceutical proteins, in particular monoclonal antibodies (mABs). Although production titers improved more than 100 fold during the last 2 decades, similar enhancements of cell specific productivities are less pronounced. They demand for detailed subcellular studies to identify promising metabolic engineering targets. In this context, our study focused on compartment specific metabolome analysis to measure metabolic patterns in the cytosol and in the mitochondrion during cell cultivation. Thereof, in vivo shuttle activities were calculated and correlated with cell specific IgG1 formation rates. The compartment-specific metabolome and labelling analysis (13C) distinguishes between cytosol and mitochondrion. Metabolomics and instationary 13C metabolic flux analysis build on preliminary own studies of 13C analytics (Teleki et al., Anal Biochem 2015; Teleki et al. Metab Eng 2017) and compartment-specific metabolomics (Matuszczyk et al., Biotechnol J 2015; Pfitzenmaier et al., Biotechnol J 2016). Further development and optimization has been performed finally reaching the current status that allows monitoring compartment-specific flux distributions and shuttle activities during the course of cell cultivation. Studying multiple periods of an IgG1 production process the crucial role of the mitochondrion not only as a provider of ATP but also as an essential part of metabolism was unraveled. 13C flux analysis disclosed the time-variant activities of the mitochondrial shuttles that are tightly linked to mitochondrial and cytosolic metabolism. Clear evidence was found that mAB production strongly depends on sufficient NADPH supply provided by cytosolic malic enzyme activity and malate export from the mitochondrio

Data‐driven in silico prediction of regulation heterogeneity and ATP demands of Escherichia coli in large‐scale bioreactors

Escherichia coli exposed to industrial‐scale heterogeneous mixing conditions respond to external stress by initiating short‐term metabolic and long‐term strategic transcriptional programs. In native habitats, long‐term strategies allow survival in severe stress but are of limited use in large bioreactors, where microenvironmental conditions may change right after said programs are started. Related on/off switching of genes causes additional ATP burden that may reduce the cellular capacity for producing the desired product. Here, we present an agent‐based data‐driven model linked to computational fluid dynamics, finally allowing to predict additional ATP needs of Escherichia coli K12 W3110 exposed to realistic large‐scale bioreactor conditions. The complex model describes transcriptional up‐ and downregulation dynamics of about 600 genes starting from subminute range covering 28 h. The data‐based approach was extracted from comprehensive scale‐down experiments. Simulating mixing and mass transfer conditions in a 54 m3 stirred bioreactor, 120,000 E. coli cells were tracked while fluctuating between different zones of glucose availability. It was found that cellular ATP demands rise between 30% and 45% of growth decoupled maintenance needs, which may limit the production of ATP‐intensive product formation accordingly. Furthermore, spatial analysis of individual cell transcriptional patterns reveal very heterogeneous gene amplifications with hot spots of 50%-80% messenger RNA upregulation in the upper region of the bioreactor. The phenomenon reflects the time‐delayed regulatory response of the cells that propagate through the stirred tank. After 4.2 h, cells adapt to environmental changes but still have to bear an additional 6% ATP demand.Projekt DEA

Optimizing mass transfer in multiphase fermentation : the role of drag models and physical conditions

Detailed knowledge of the flow characteristics, bubble movement, and mass transfer is a prerequisite for the proper design of multiphase bioreactors. Often, mechanistic spatiotemporal models and computational fluid dynamics, which intrinsically require computationally demanding analysis of local interfacial forces, are applied. Typically, such approaches use volumetric mass-transfer coefficient (kLa) models, which have demonstrated their predictive power in water systems. However, are the related results transferrable to multiphase fermentations with different physicochemical properties? This is crucial for the proper design of biotechnological processes. Accordingly, this study investigated a given set of mass transfer data to characterize the fermentation conditions. To prevent time-consuming simulations, computational efforts were reduced using a force balance stationary 0-dimension model. Therefore, a competing set of drag models covering different mechanistic assumptions could be evaluated. The simplified approach of disregarding fluid movement provided reliable results and outlined the need to identify the liquid diffusion coefficients in fermentation media. To predict the rising bubble velocities uB, the models considering the Morton number (Mo) showed superiority. The mass transfer coefficient kL was best described using the well-known Higbie approach. Taken together, the gas hold-up, specific surface area, and integral mass transfer could be accurately predicted

Methylthioadenosine (MTA) boosts cell‐specific productivities of Chinese hamster ovary cultures : dosage effects on proliferation, cell cycle and gene expression

A major goal for process and cell engineering in the biopharmaceutical industry is enhancing production through increasing volumetric and cellspecific productivities (CSP). Here, we present 50-deoxy-50-(methylthio)adenosine (MTA), the degradation product of S-(50-adenosyl)-L-methionine (SAM), as a highly attractive native additive which can boost CSP by 79% when added to exponentially growing cells at a concentration of 250-300 lM. Notably, cell viability and cell size remain higher than in non-treated cultures. In addition, cell cycle arrests first in S-, then in G2-phase before levelling out compared to non-treated cultivations. Intensive differential gene analysis reveals that expression of genes for cytoskeleton mediated proteins and vesicle transport is amplified by treatment. Furthermore, the interaction of MTA with cell proliferation additionally stimulated recombinant protein formation. The results may serve as a promising starting point for further developments in process and cell engineering to boost productivity.Bundesministerium für Bildung und ForschungProjekt DEA

Revisiting basics of kLa dependency on aeration in bubble columns : a is surprisingly stable

A comprehensive experimental characterization of a small‐scale bubble column bioreactor (60 mL) is presented. Bubble size distribution (BSD), gas holdup, and kLa were determined for different types of liquids, relevant fermentation conditions and superficial gas velocities uG. The specific interfacial area a and liquid mass transfer coefficient kL have been identified independent of each other to unravel their individual impact on kLa. Results show that increasing uG leads to larger bubbles and higher gas holdup. As both parameters influence a in opposite ways, no increase of a with uG is found. Furthermore, kL increases with increasing bubble size outlining that improved oxygen transfer is not the result of higher a but of risen kL instead. The results build the foundation for further simulative investigations.Projekt DEA

Getting the right clones in an automated manner : an alternative to sophisticated colony-picking robotics

In recent years, the design-build-test-learn (DBTL) cycle has become a key concept in strain engineering. Modern biofoundries enable automated DBTL cycling using robotic devices. However, both highly automated facilities and semi-automated facilities encounter bottlenecks in clone selection and screening. While fully automated biofoundries can take advantage of expensive commercially available colony pickers, semi-automated facilities have to fall back on affordable alternatives. Therefore, our clone selection method is particularly well-suited for academic settings, requiring only the basic infrastructure of a biofoundry. The automated liquid clone selection (ALCS) method represents a straightforward approach for clone selection. Similar to sophisticated colony-picking robots, the ALCS approach aims to achieve high selectivity. Investigating the time analogue of five generations, the model-based set-up reached a selectivity of 98 ± 0.2% for correctly transformed cells. Moreover, the method is robust to variations in cell numbers at the start of ALCS. Beside Escherichia coli , promising chassis organisms, such as Pseudomonas putida and Corynebacterium glutamicum , were successfully applied. In all cases, ALCS enables the immediate use of the selected strains in follow-up applications. In essence, our ALCS approach provides a ‘low-tech’ method to be implemented in biofoundry settings without requiring additional devices.German Research Foundation (DFG

CRISPRi enables fast growth followed by stable aerobic pyruvate formation in Escherichia coli without auxotrophy

CRISPR interference (CRISPRi) was applied to enable the aerobic production of pyruvate in Escherichia coli MG1655 under glucose excess conditions by targeting the promoter regions of aceE or pdhR. Knockdown strains were cultivated in aerobic shaking flasks and the influence of inducer concentration and different sgRNA binding sites on the production of pyruvate was measured. Targeting the promoter regions of aceE or pdhR triggered pyruvate production during the exponential phase and reduced expression of aceE. In lab‐scale bioreactor fermentations, an aceE silenced strain successfully produced pyruvate under fully aerobic conditions during the exponential phase, but loss of productivity occurred during a subsequent nitrogen‐limited phase. Targeting the promoter region of pdhR enabled pyruvate production during the growth phase of cultivations, and a continued low‐level accumulation during the nitrogen‐limited production phase. Combinatorial targeting of the promoter regions of both aceE and pdhR in E. coli MG1655 pdCas9 psgRNA_aceE_234_pdhR_329 resulted in the stable aerobic production of pyruvate with non‐growing cells at YP/S  =  0.36 ± 0.029 gPyruvate/gGlucose in lab‐scale bioreactors throughout an extended nitrogen‐limited production phase