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 qSmax and acetate production qApmax; meanwhile, higher glucose concentrations had adverse effects on the biomass yield coefficient YXSem. Additional parameters compared to previous studies for the oxygen uptake rate and carbon dioxide production rate indicated differences in the specific oxygen uptake rate qOmax. 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.

Prediction and characterization of the stability enhancing effect of the Cherry-Tag™ in highly concentrated protein solutions by complex rheological measurements and MD simulations.

Solution stability attributes are one of the key parameters within the production and launching phase of new biopharmaceuticals. Instabilities of active biological compounds can reduce the yield of biopharmaceutical productions, and may induce undesired reactions in patients, such as immunogenic rejections. Protein solution stability thus needs to be engineered and monitored throughout production and storage. In contrast to the gold standard of long-term storage experiments applied in industry, novel experimental and in silico molecular dynamics tools for predicting protein solution stability can be applied within several minutes or hours. Here, a rheological approach in combination with molecular dynamics simulations are presented, for determining and predicting long-term phase behavior of highly concentrated protein solutions. A diversity of liquid phase conditions, including salt type, ionic strength, pH and protein concentration are tested in a Glutathione-S-Transferase (GST) case study, in combination with the enzyme with and without solubility-enhancing Cherry-Tag™. The rheological characterization of GST and Cherry-GST solutions enabled a fast and efficient prediction of protein instabilities without the need of long-term protein phase diagrams. Finally, the strong solubility enhancing properties of the Cherry-Tag™ were revealed by investigating protein surface properties in MD simulations. The tag highly altered the overall surface charge and hydrophobicity of GST, making it less accessible to alteration by the chemical surrounding.

Characterization of highly concentrated antibody solution - A toolbox for the description of protein long-term solution stability.

High protein titers are gaining importance in biopharmaceutical industry. A major challenge in the development of highly concentrated mAb solutions is their long-term stability and often incalculable viscosity. The complexity of the molecule itself, as well as the various molecular interactions, make it difficult to describe their solution behavior. To study the formulation stability, long- and short-range interactions and the formation of complex network structures have to be taken into account. For a better understanding of highly concentrated solutions, we combined established and novel analytical tools to characterize the effect of solution properties on the stability of highly concentrated mAb formulations. In this study, monoclonal antibody solutions in a concentration range of 50-200 mg/ml at pH 5-9 with and without glycine, PEG4000, and Na2SO4 were analyzed. To determine the monomer content, analytical size-exclusion chromatography runs were performed. ζ-potential measurements were conducted to analyze the electrophoretic properties in different solutions. The melting and aggregation temperatures were determined with the help of fluorescence and static light scattering measurements. Additionally, rheological measurements were conducted to study the solution viscosity and viscoelastic behavior of the mAb solutions. The so-determined analytical parameters were scored and merged in an analytical toolbox. The resulting scoring was then successfully correlated with long-term storage (40 d of incubation) experiments. Our results indicate that the sensitivity of complex rheological measurements, in combination with the applied techniques, allows reliable statements to be made with respect to the effect of solution properties, such as protein concentration, ionic strength, and pH shift, on the strength of protein-protein interaction and solution colloidal stability.

Concentration-dependent changes in apparent diffusion coefficients as indicator for colloidal stability of protein solutions.

The colloidal stability of a protein solution during downstream processing, formulation, and storage is a key issue for the biopharmaceutical production process. Thus, knowledge about colloidal solution characteristics, such as the tendency to form aggregates or high viscosity, at various processing conditions is of interest. This work correlates changes in the apparent diffusion coefficient as a parameter of protein interactions with observed protein aggregation and dynamic viscosity of the respective protein samples. For this purpose, the diffusion coefficient, the protein phase behavior, and the dynamic viscosity in various systems containing the model proteins α-lactalbumin, lysozyme, and glucose oxidase were studied. Each of these experiments revealed a wide range of variations in protein interactions depending on protein type, protein concentration, pH, and the NaCl concentration. All these variations showed to be mirrored by changes in the apparent diffusion coefficient in the respective samples. Whereas stable samples with relatively low viscosity showed an almost linear dependence, the deviation from the concentration-dependent linearity indicated both an increase in the sample viscosity and probability of protein aggregation. This deviation of the apparent diffusion coefficient from concentration-dependent linearity was independent of protein type and solution properties for this study. Thus, this single parameter shows the potential to act as a prognostic tool for colloidal stability of protein solutions.

Impact of polymer surface characteristics on the microrheological measurement quality of protein solutions - A tracer particle screening.

Microrheological measurements prove to be suitable to identify rheological parameters of biopharmaceutical solutions. These give information about the flow characteristics but also about the interactions and network structures in protein solutions. For the microrheological measurement tracer particles are required. Due to their specific surface characteristic not all are suitable for reliable measurement results in biopharmaceutical systems. In the present work a screening of melamine, PMMA, polystyrene and surface modified polystyrene as tracer particles were investigated at various protein solution conditions. The surface characteristics of the screened tracer particles were evaluated by zeta potential measurements. Furthermore each tracer particle was used to determine the dynamic viscosity of lysozyme solutions by microrheology and compared to a standard. The results indicate that the selection of the tracer particle had a strong impact on the quality of the microrheological measurement dependent on pH and additive type. Surface modified polystyrene was the only tracer particle that yielded good microrheological results for all tested conditions. The study indicated that the electrostatic surface charge of the tracer particle had a minor impact than its hydrophobicity. This characteristic was the crucial surface property that needs to be considered for the selection of a suitable tracer particle to achieve high measurement accuracy.

Squeeze flow rheometry as a novel tool for the characterization of highly concentrated protein solutions.

This study aims at defining rheological parameters for the characterization of highly concentrated protein solutions. As a basis for comparing rheological behavior with protein solution characteristics the protein phase behavior of Lysozyme from chicken egg white with concentrations up to 225 mg/mL, changing pH values and additive concentrations was studied in a microbatch scale format. The prepared phase diagrams, scored after 40 days (t40) give insights into the kind and kinetics of the phase transitions that occur. Oscillatory frequency sweep measurements of samples with exactly the same conditions were conducted immediately after preparation (t0). The protein solutions behave viscoelastic and show a characteristic curve shape of the storage modulus (G') and the loss modulus (G″). The graphs provide information about the cross-linking degree of the respective sample. The measured rheological parameters were sensitive concerning solution composition, protein concentration and solution inner structure. The rheological moduli G' and G″ and especially the ratio of these parameters over a frequency range from 100 to 40000 rad/sec give information about the aggregation tendency of the protein under tested conditions. We succeeded to correlate protein phase behavior with the defined rheological key parameter ωCO. This point represents the frequency value of the intersection point from G' and G″. In our study Lysozyme expressed a ωCO threshold value of 20000 rad/sec as a lower limit for stable protein solutions. The predictability of lysozyme aggregation tendency and crystallization by means of squeeze flow rheometry is shown.