Characterisation of the E. coli HMS174 and BLR host cell proteome to guide purification process development

Mass-spectrometry-based proteomics is increasingly employed to monitor purification processes or to detect critical host cell proteins in the final drug substance. This approach is inherently unbiased and can be used to identify individual host cell proteins without prior knowledge. In process development for the purification of new biopharmaceuticals, such as protein subunit vaccines, a broader knowledge of the host cell proteome could promote a more rational process design. Proteomics can establish qualitative and quantitative information on the complete host cell proteome before purification (i.e., protein abundances and physicochemical properties). Such information allows for a more rational design of the purification strategy and accelerates purification process development. In this study, we present an extensive proteomic characterisation of two E. coli host cell strains widely employed in academia and industry to produce therapeutic proteins, BLR and HMS174. The established database contains the observed abundance of each identified protein, information relating to their hydrophobicity, the isoelectric point, molecular weight, and toxicity. These physicochemical properties were plotted on proteome property maps to showcase the selection of suitable purification strategies. Furthermore, sequence alignment allowed integration of subunit information and occurrences of post-translational modifications from the well-studied E. coli K12 strain.

Isotherm model discrimination for multimodal chromatography using mechanistic models derived from high-throughput batch isotherm data

In this work, we have examined an array of isotherm formalisms and characterized them based on their relative complexities and predictive abilities with multimodal chromatography. The set of isotherm models studied were all based on the stoichiometric displacement framework, with considerations for electrostatic interactions, hydrophobic interactions, and thermodynamic activities. Isotherm parameters for each model were first determined through twenty repeated fits to a set of mAb - Capto MMC batch isotherm data spanning a range of loading, ionic strength, and pH as well as a set of mAb - Capto Adhere batch data at constant pH. The batch isotherm data were used in two ways-spanning the full range of loading or consisting of only the high concentration data points. Predictive ability was defined through the model's capacity to capture prominent changes in salt gradient elution behavior with respect to pH for Capto MMC or unique elution patterns and yield losses with respect to gradient slope for Capto Adhere. In both cases, model performance was quantified using a scoring metric based on agreement in peak characteristics for column predictions and accuracy of fit for the batch data. These scores were evaluated for all twenty isotherm fits and their corresponding column predictions, thereby producing a statistical distribution of model performances. Model complexity (number of isotherm parameters) was then considered through use of the Akaike information criterion (AIC) calculated from the score distributions. While model performance for Capto MMC benefitted substantially from removal of low protein concentration data, this was not the case for Capto Adhere; this difference was likely due to the qualitatively different shapes of the isotherms between the two resins. Surprisingly, the top-performing (high accuracy with minimal number of parameters) isotherm model was the same for both resins. The extended steric mass action (SMA) isotherm (containing both protein-salt and protein-protein activity terms) accurately captured both the pH-dependent elution behavior for Capto MMC as well as loss in protein recovery with increasing gradient slope for Capto Adhere. In addition, this isotherm model achieved the highest median score in both resin systems, despite it lacking any explicit hydrophobic stoichiometric terms. The more complex isotherm models, which explicitly accounted for both electrostatic and hydrophobic interaction stoichiometries, were ill-suited for Capto MMC and had lower AIC model likelihoods for Capto Adhere due to their increased complexity. Interestingly, the ability of the extended SMA isotherm to predict the Capto Adhere results was largely due to the protein-salt activity coefficient, as determined via isotherm parameter sensitivity analyses. Further, parametric studies on this parameter demonstrated that it had a major impact on both binding affinity and elution behavior, therein fully capturing the impact of hydrophobic interactions. In summary, we were able to determine the isotherm formalisms most capable of consistently predicting a wide range of column behavior for both a multimodal cation-exchange and multimodal anion-exchange resin with high accuracy, while containing a minimized set of model parameters.

Protein association on multimodal chromatography media

The phenomenon of protein-protein association on multimodal chromatography resins was described for two different case study examples. The adsorption pattern of single-component solutions of calcium-rich alpha-lactalbumin (aLaCa) and calcium-depleted alpha-lactalbumin (aLa) and their mixtures with bovine serum albumin was determined on a multimodal anion-exchange chromatography medium. In single-component solutions, both aLaCa and aLa exhibited identical adsorption behavior at low resin loadings, whereas at high loadings the adsorption strength of aLa markedly exceeded that of alaCa. In binary mixtures, the adsorption of BSA enhanced at high concentrations of aLa or aLaCa in the adsorbed phase. The unusual adsorption patterns observed were attributed to the tendency of the proteins for molecular association in the adsorbed phase in single and binary solutions. The phenomena was examined for different pH of the solution: pH 6, 7, 8, and different solvent environments: phosphate buffer (PB), bis tris buffer (BT), 100 mM NaCl in BT and bis tris propane buffer (BTP). The strongest effect was observed for PB and for 100 mM NaCl in BT. Its occurrence was also evidenced for other case study example, i.e., adsorption of single-component solutions and binary mixtures of a monoclonal antibody (mAb) and lysozyme (LYZ) on a multimodal cation-exchange chromatography medium. The enhancement of adsorption of mAb was observed at high concentrations of LYZ in the adsorbed phase. To quantify the underlying effects, a mechanistic model was used, which accounted for both protein association and exclusion resulting from attractive and repulsive protein-protein iterations in the adsorbed phase.

The use of predictive models to develop chromatography-based purification processes

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Direct and indirect effects of IFN-α2b in malignancy treatment: not only an archer but also an arrow

Interferon-α2b (IFN-α2b) is a highly active cytokine that belongs to the interferon-α (IFN-α) family. IFN-α2b has beneficial antiviral, antitumour, antiparasitic and immunomodulatory activities. Direct and indirect antiproliferative effects of IFN-α2b have been found to occur via multiple pathways, mainly the JAK-STAT pathway, in certain cancers. This article reviews mechanistic studies and clinical trials on IFN-α2b. Potential regulators of the function of IFN-α2b were also reviewed, which could be utilized to relieve the poor response to IFN-α2b. IFN-α2b can function not only by enhancing the systematic immune response but also by directly killing tumour cells. Different parts of JAK-STAT pathway activated by IFN-α2b, such as interferon alpha and beta receptors (IFNARs), Janus kinases (JAKs) and IFN‐stimulated gene factor 3 (ISGF3), might serve as potential target for enhancing the pharmacological action of IFN-α2b. Despite some issues that remain to be solved, based on current evidence, IFN-α2b can inhibit disease progression and improve the survival of patients with certain types of malignant tumours. More efforts should be made to address potential adverse effects and complications.

Steric accessibility of the N-terminus improves the titer and quality of recombinant proteins secreted from Komagataella phaffii

BACKGROUND

Komagataella phaffii is a commonly used alternative host for manufacturing therapeutic proteins, in part because of its ability to secrete recombinant proteins into the extracellular space. Incorrect processing of secreted proteins by cells can, however, cause non-functional product-related variants, which are expensive to remove in purification and lower overall process yields. The secretion signal peptide, attached to the N-terminus of the recombinant protein, is a major determinant of the quality of the protein sequence and yield. In K. phaffii, the signal peptide from the Saccharomyces cerevisiae alpha mating factor often yields the highest secreted titer of recombinant proteins, but the quality of secreted protein can vary highly.

RESULTS

We determined that an aggregated product-related variant of the SARS-CoV-2 receptor binding domain is caused by N-terminal extension from incomplete cleavage of the signal peptide. We eliminated this variant and improved secreted protein titer up to 76% by extension of the N-terminus with a short, functional peptide moiety or with the EAEA residues from the native signal peptide. We then applied this strategy to three other recombinant subunit vaccine antigens and observed consistent elimination of the same aggregated product-related variant. Finally, we demonstrated that this benefit in quality and secreted titer can be achieved with addition of a single amino acid to the N-terminus of the recombinant protein.

CONCLUSIONS

Our observations suggest that steric hindrance of proteases in the Golgi that cleave the signal peptide can cause unwanted N-terminal extension and related product variants. We demonstrated that this phenomenon occurs for multiple recombinant proteins, and can be addressed by minimal modification of the N-terminus to improve steric accessibility. This strategy may enable consistent secretion of a broad range of recombinant proteins with the highly productive alpha mating factor secretion signal peptide.

A framework for calculating orthogonal selectivities in multimodal systems directly from cell culture fluid

This paper presents a straightforward approach for measuring and quantifying orthogonality directly in complex cell culture fluids (CCFs) without the requirement for tracking the retention behaviors of large sets of proteins. Null-producing CCFs were fractionated using linear salt gradients at constant pH on a set of multimodal resins. Fractions were then analyzed by ultraperformance-reversed phase liquid chromatography and the resulting chromatograms provided host cell protein (HCP) "fingerprints." Using these fingerprints, an inner product vector-based approach was employed to quantify the degree of orthogonality between pairs of resins and operating conditions for these large HCP protein sets. To compare resin orthogonality behavior in different expression systems, the Chinese hamster ovary and Pichia pastoris null-producing CCFs were examined. Orthogonality in multimodal systems was found to strongly depend on the expression system and the HCPs being screened. We also identified several unexpected pairs of multimodal resins within the same family that exhibited significant orthogonality. Furthermore, "self-orthogonality" was evaluated between resins operated at different pHs, and important operating regimes were identified for maximizing orthogonal selectivities. The framework developed in this paper for calculating orthogonality without the need for labor-intensive HCP tracking has important implications for efficient process development and resin/operating condition selection for both monoclonal antibody (mAb) polishing steps and non-mAb processes. In addition, this study provides a tool to unlock the untapped potential of multimodal resins by aiding in their rational selection and incorporation. Finally, the orthogonality framework here can facilitate the development of sets of next-generation multimodal resins specifically designed to provide highly orthogonal and efficient separations tailored for different expression systems.

Systematic workflow for studying domain contributions of bispecific antibodies to selectivity in multimodal chromatography

In this article, a systematic workflow was formulated and implemented to understand selectivity differences and preferred binding patches for bispecific monoclonal antibodies (mAbs) and their parental mAbs on three multimodal cation exchange resin systems. This workflow incorporates chromatographic screening of the parent mAbs and their fragments at various pH followed by surface property mapping and protein footprinting using covalent labeling followed by liquid chromatography-mass spectrometry analysis. The chromatography screens on multimodal resins with the intact mAbs indicated enhanced selectivity as compared to single-mode interaction systems. While the bispecific antibody (bsAb) eluted between the two parental mAbs on most of the resins, the retention of the bispecific transitioned from co-eluting with one parental mAb to the other parental mAb on Capto MMC. To investigate the contribution of different domains, mAb fragments were evaluated and the results indicated that the interactions were likely dominated by the Fab domain at higher pH. Protein surface property maps were then employed to hypothesize the potential preferred binding patches in the solvent-exposed regions of the parental Fabs. Finally, protein footprinting was carried out with the parental mAbs and the bsAb in the bound and unbound states at pH 7.5 to identify the preferred binding patches. Results with the intact mAb analysis supported the hypothesis that interactions with the resins were primarily driven by the residues in the Fab fragments and not the Fc. Furthermore, peptide mapping data indicated that the light chain may be playing a more important role in the higher binding of Parent A as compared with Parent B in these resin systems. Finally, results with the bsAb indicated that both halves of the molecule contributed to binding with the resins, albeit with subtle differences as compared to the parental mAbs. The workflow presented in this paper lays the foundation to systematically study the chromatographic selectivity of large multidomain molecules which can provide insights into improved biomanufacturability and expedited downstream bioprocess development.

Evaluation of guanidine-based multimodal anion exchangers for protein selectivity and orthogonality

In this paper, we examined the chromatographic behavior of a new class of guanidine-based multimodal anion exchange resins. The selectivities and protein recoveries on these resins were first evaluated using linear gradient chromatography with a model acidic protein library at pH 5, 6 and 7. While a single-guanidine based resin exhibited significant recovery issues at high ligand density, a bis-guanidine based resin showed high recoveries of all but two of the proteins evaluated in the study. In addition, the bis-guanidine resin showed a more pH dependent selectivity pattern as compared to the low density single-guanidine resin. The salt elution range for the low density single-guanidine and bis-guanidine resins was also observed to vary from 0.250 to 0.621 M and 0.162 to 0.828 M NaCl, respectively. A QSAR model was then developed to predict the elution behavior of these proteins on the guanidine prototypes at multiple pH with overall training and test scores of 0.88 and 0.85, respectively. In addition, molecular dynamics simulations were performed with these ligands immobilized on a self-assembled monolayer (SAM) to characterize their conformational preferences and to gain insight into the molecular basis of their chromatographic behavior. Finally, a recently developed framework was employed to evaluate the separability of the bis-guanidine resin as well as its orthogonality to the multimodal cation exchanger, Nuvia cPrime. This evaluation was carried out using a second model protein library which included both acidic and basic proteins. The results of this analysis indicated that the bis-guanidine prototype exhibited both higher pair separability (0.73) and pair enhancement (0.42) as compared to the less hydrophobic commercial Nuvia aPrime 4A with pair separability and enhancement factors of 0.57 and 0.22, respectively. The enhanced selectivity and orthogonality of this new multimodal anion exchange ligand may offer potential opportunities for bioprocessing applications.

Rapid optimization of processes for the integrated purification of biopharmaceuticals

Straight‐through chromatography, wherein the eluate from one column passes directly onto another column without adjustment, is one strategy to integrate and intensify manufacturing processes for biologics. Development and optimization of such straight‐through chromatographic processes is a challenge, however. Conventional high‐throughput screening methods optimize each chromatographic step independently, with limited consideration for the connectivity of steps. Here, we demonstrate a method for the development and optimization of fully integrated, multi‐column processes for straight‐through purification. Selection of resins was performed using an in silico tool for the prediction of processes for straight‐through purification based on a one‐time characterization of host‐cell proteins combined with the chromatographic behavior of the product. A two‐step optimization was then conducted to determine the buffer conditions that maximized yield while minimizing process‐ and product‐related impurities. This optimization of buffer conditions included a series of range‐finding experiments on each individual column, similar to conventional screening, followed by the development of a statistical model for the fully integrated, multi‐column process using design of experiments. We used this methodology to develop and optimize integrated purification processes for a single‐domain antibody and a cytokine, obtaining yields of 88% and 86%, respectively, with process‐ and product‐related variants reduced to phase‐appropriate levels for nonclinical material.

Molecular engineering improves antigen quality and enables integrated manufacturing of a trivalent subunit vaccine candidate for rotavirus

BACKGROUND

Vaccines comprising recombinant subunit proteins are well-suited to low-cost and high-volume production for global use. The design of manufacturing processes to produce subunit vaccines depends, however, on the inherent biophysical traits presented by an individual antigen of interest. New candidate antigens typically require developing custom processes for each one and may require unique steps to ensure sufficient yields without product-related variants.

RESULTS

We describe a holistic approach for the molecular design of recombinant protein antigens-considering both their manufacturability and antigenicity-informed by bioinformatic analyses such as RNA-seq, ribosome profiling, and sequence-based prediction tools. We demonstrate this approach by engineering the product sequences of a trivalent non-replicating rotavirus vaccine (NRRV) candidate to improve titers and mitigate product variants caused by N-terminal truncation, hypermannosylation, and aggregation. The three engineered NRRV antigens retained their original antigenicity and immunogenicity, while their improved manufacturability enabled concomitant production and purification of all three serotypes in a single, end-to-end perfusion-based process using the biotechnical yeast Komagataella phaffii.

CONCLUSIONS

This study demonstrates that molecular engineering of subunit antigens using advanced genomic methods can facilitate their manufacturing in continuous production. Such capabilities have potential to lower the cost and volumetric requirements in manufacturing vaccines based on recombinant protein subunits.

Development of a platform process for the production and purification of single-domain antibodies

Single‐domain antibodies (sdAbs) offer the affinity and therapeutic value of conventional antibodies, with increased stability and solubility. Unlike conventional antibodies, however, sdAbs do not benefit from a platform manufacturing process. While successful production of a variety of sdAbs has been shown in numerous hosts, purification methods are often molecule specific or require affinity tags, which generally cannot be used in clinical manufacturing due to regulatory concerns. Here, we have developed a broadly applicable production and purification process for sdAbs in Komagataella phaffii (Pichia pastoris) and demonstrated the production of eight different sdAbs at a quality appropriate for nonclinical studies. We developed a two‐step, integrated purification process without the use of affinity resins and showed that modification of a single process parameter, pH of the bridging buffer, was required for the successful purification of a variety of sdAbs. Further, we determined that this parameter can be predicted based only on the biophysical characteristics of the target molecule. Using these methods, we produced nonclinical quality sdAbs as few as 5 weeks after identifying the product sequence. Nonclinical studies of three different sdAbs showed that molecules produced using our platform process conferred protection against viral shedding of rotavirus or H1N1 influenza and were equivalent to similar molecules produced in Escherichia coli and purified using affinity tags.