Screening for physical stability of a Pseudomonas amylase using self-interaction chromatography

A coarse-grained xDLVO model for colloidal protein-protein interactions

Colloidal protein-protein interactions (PPIs) of attractive and repulsive nature modulate the solubility of proteins, their aggregation, precipitation and crystallization. Such interactions are very important for many biotechnological processes, but are complex and hard to control, therefore, difficult to be understood in terms of measurements alone. In diluted protein solutions, PPIs can be estimated from the osmotic second virial coefficient, B22, which has been calculated using different methods and levels of theory. The most popular approach is based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory and its extended versions, i.e. xDLVO. Despite much efforts, these models are not fully quantitative and must be fitted to experiments, which limits their predictive value. Here, we report an extended xDLVO-CG model, which extends existing models by a coarse-grained representation of proteins and the inclusion of an additional ion-protein dispersion interaction term. We demonstrate for four proteins, i.e. lysozyme (LYZ), subtilisin (Subs), bovine serum albumin (BSA) and immunoglobulin (IgG1), that semi-quantitative agreement with experimental values without the need to fit to experimental B22 values. While most likely not the final step in the nearly hundred years of research in PPIs, xDLVO-CG is a step towards predictive PPIs calculations that are transferable to different proteins.

Low-volume solubility assessment during high-concentration protein formulation development

OBJECTIVE

Solubility is often one of the limiting factors for high-concentration protein formulation (HCF) development. Determination of protein solubility is challenging and requires high amount of material. Therefore, low-volume and predictive approaches are desired.

METHODS

This work presents a simple and material-saving approach using static light scattering to describe non-ideal solution behaviour of HCF. Non-ideality can be related to protein-protein interactions in solution. The type and strength of these interactions indicate maximum protein solubility at actual formulation compositions. Interactions of four therapeutic model proteins at multiple formulation compositions were investigated, and deduced solubility was compared to apparent solubility behaviour determined by ether turbidity or content measurements.

KEY FINDINGS

Protein-protein interactions and deduced solubilities matched actual solubility data for all tested formulations. Protein solubility was found to be lowest at pH values near the isoelectric point of each model protein. Buffer salts and ionic strength were also found to strongly influence protein solubility. In addition, sucrose and a combination of arginine and glycine enhanced protein solubility, whereas surfactants such as polysorbate 20 did not influence protein solubility.

CONCLUSIONS

The introduced screening procedure is a powerful tool during (early) protein formulation development. It meets several requirements of HCF development and enables reliable prediction of protein solubility based on determination of protein interactions. In addition, rare data about the influence of several common excipients on apparent solubility of therapeutic proteins were shown.

The second virial coefficient as a predictor of protein aggregation propensity: A self-interaction chromatography study

The second osmotic virial coefficients (b₂) of four proteins – lysozyme, recombinant human lactoferrin, concanavalin A and catalase were measured by self-interaction chromatography (SIC) in solutions of varying salt type, concentration and pH. Protein aggregate sizes based on the initial hydrodynamic radius of the protein solution species present were measured using dynamic light scattering, and the relationship between b₂ and protein aggregate size was studied. A linear correlation was established between b₂ values and protein aggregate hydrodynamic size for all proteins, and for almost all solution conditions. Aggregate sizes of <∼10 nm, indicative of non-aggregated protein systems, were consistently observed to have b₂ values >0. The observed b₂ trends as a function of solution conditions were very much protein dependent, with notable trends including the existence of attractive interactions (negative b₂ values) at low ionic strengths for catalase and concanavalin A, and the highly positive b₂ values observed for lactoferrin over a wide range of solution conditions, reflecting lactoferrin’s innately high stability. It is concluded that the quantification of protein–protein interactions using SIC based b₂ data is a potentially valuable screening tool for predicting protein aggregation propensity.

Applications of the second virial coefficient: protein crystallization and solubility

This article begins by highlighting some of the ground-based studies emanating from NASA's Microgravity Protein Crystal Growth (PCG) program. This is followed by a more detailed discussion of the history of and the progress made in one of the NASA-funded PCG investigations involving the use of measured second virial coefficients (B values) as a diagnostic indicator of solution conditions conducive to protein crystallization. A second application of measured B values involves the determination of solution conditions that improve or maximize the solubility of aqueous and membrane proteins. These two important applications have led to several technological improvements that simplify the experimental expertise required, enable the measurement of membrane proteins and improve the diagnostic capability and measurement throughput.

Monitoring of the bacterial and fungal biodiversity and dynamics during Massa Medicata Fermentata fermentation

The microbial community dynamics play an important role during Massa Medicata Fermentata (MMF) fermentation. In this study, bacterial and fungal communities were investigated based on the culture-dependent method and polymerase chain reaction-denaturing gradient gel electrophoresis analysis. Meanwhile the dynamic changes of digestive enzyme activities were also examined. Plating results showed that MMF fermentation comprised two stages: pre-fermentation stage (0–4 days) was dominated by bacterial community and post-fermentation stage (5–9 days) was dominated by fungal community. The amount of bacteria reached the highest copy number 1.2 × 10¹⁰ CFU/g at day 2, but the fungi counts reached 6.3 × 10⁵ CFU/g at day 9. A total of 170 isolates were closely related to genera Enterobacter, Klebsiella, Acinetobacter, Pseudomonas, Mucor, Saccharomyces, Rhodotorula, and Amylomyces. DGGE analysis showed a clear reduction of bacterial and fungal diversity during fermentation, and the dominant microbes belonged to genera Enterobacter, Pediococcus, Pseudomonas, Mucor, and Saccharomyces. Digestive enzyme assay showed filter paper activity; the activities of amylase, carboxymethyl cellulase, and lipase reached a peak at day 4; and the protease activity constantly increased until the end of the fermentation. In this study, we carried out a detailed and comprehensive analysis of microbial communities as well as four digestive enzymes' activities during MMF fermentation process. The monitoring of bacterial and fungal biodiversity and dynamics during MMF fermentation has significant potential for controlling the fermentation process.

The accurate measurement of second virial coefficients using self-interaction chromatography: experimental considerations

Measurement of B22, the second virial coefficient, is an important technique for describing the solution behaviour of proteins, especially as it relates to precipitation, aggregation and crystallisation phenomena. This paper describes the best practise for calculating B22 values from self-interaction chromatograms (SIC) for aqueous protein solutions. Detailed analysis of SIC peak shapes for lysozyme shows that non-Gaussian peaks are commonly encountered for SIC, with typical peak asymmetries of 10%. This asymmetry reflects a non-linear chromatographic retention process, in this case heterogeneity of the protein-protein interactions. Therefore, it is important to use the centre of mass calculations for determining accurate retention volumes and thus B22 values. Empirical peak maximum chromatogram analysis, often reported in the literature, can result in errors of up to 50% in B22 values. A methodology is reported here for determining both the mean and the variance in B22 from SIC experiments, includes a correction for normal longitudinal peak broadening. The variance in B22 due to chemical effects is quantified statistically and is a measure of the heterogeneity of protein-protein interactions in solution. In the case of lysozyme, a wide range of B22 values are measured which can vary significantly from the average B22 values.

Correlation of second virial coefficient with solubility for proteins in salt solutions

In this work, osmotic second virial coefficients (B(22)) were determined and correlated with the measured solubilities for the proteins, α-amylase, ovalbumin, and lysozyme. The B(22) values and solubilities were determined in similar solution conditions using two salts, sodium chloride and ammonium sulfate in an acidic pH range. An overall decrease in the solubility of the proteins (salting out) was observed at high concentrations of ammonium sulfate and sodium chloride solutions. However, for α-amylase, salting-in behavior was also observed in low concentration sodium chloride solutions. In ammonium sulfate solutions, the B(22) are small and close to zero below 2.4 M. As the ammonium sulfate concentrations were further increased, B(22) values decreased for all systems studied. The effect of sodium chloride on B(22) varies with concentration, solution pH, and the type of protein studied. Theoretical models show a reasonable fit to the experimental derived data of B(22) and solubility. B(22) is also directly proportional to the logarithm of the solubility values for individual proteins in salt solutions, so the log-linear empirical models developed in this work can also be used to rapidly predict solubility and B(22) values for given protein-salt systems.

Self-interaction chromatography of proteins on a microfluidic monolith

A novel miniaturized system has been developed for measuring protein-protein interactions in solution with high efficiency and speed, and minimal use of protein. A chromatographic monolith synthesized in a capillary is used in the method to make interaction measurements by self-interaction chromatography (SIC) in a manner that, compared to column methods, is more efficient as well as more readily practicable even if only small amounts of protein are available. The microfluidic monolith requires much less protein for both column synthesis and the chromatographic measurements than a conventional SIC system, and in addition offers improved mass transfer and hence higher chromatographic efficiency than for previous SIC miniaturization systems. Protein self-interactions for catalase as a model protein, quantified by measurement of second virial coefficients, B(22), were determined by SIC and follow trends that are consistent with previously reported values. Different column derivatization conditions were studied in order to optimize the chromatographic behavior of the microfluidic system for SIC measurements. Chromatographic sensitivity can be further increased by using different column synthesis conditions.

High throughput screening of protein formulation stability: practical considerations

The formulation of protein drugs is a difficult and time-consuming process, mainly due to the complexity of protein structure and the very specific physical and chemical properties involved. Understanding protein degradation pathways is essential for the success of a biopharmaceutical drug. The present review concerns the application of high throughput screening techniques in protein formulation development. A protein high throughput formulation (HTF) platform is based on the use of microplates. Basically, the HTF platform consists of two parts: (i) sample preparation and (ii) sample analysis. Sample preparation involves automated systems for dispensing the drug and the formulation ingredients in both liquid and powder form. The sample analysis involves specific methods developed for each protein to investigate physical and chemical properties of the formulations in microplates. Examples are presented of the use of protein intrinsic fluorescence for the analysis of protein aqueous properties (e.g., conformation and aggregation). Different techniques suitable for HTF analysis are discussed and some of the issues concerning implementation are presented with reference to the use of microplates.