Nature as blueprint: Global phenotype engineering of CHO production cells based on a multi-omics comparison with plasma cells.

Especially for the production of artificial, difficult to express molecules a further development of the CHO production cell line is required to keep pace with the continuously increasing demands. However, the identification of novel targets for cell line engineering to improve CHO cells is a time and cost intensive process. Since plasma cells are evolutionary optimized for a high antibody expression in mammals, we performed a comprehensive multi-omics comparison between CHO and plasma cells to exploit optimized cellular production traits. Comparing the transcriptome, proteome, miRNome, surfaceome and secretome of both cell lines identified key differences including 392 potential overexpression targets for CHO cell engineering categorized in 15 functional classes like transcription factors, protein processing or secretory pathway. In addition, 3 protein classes including 209 potential knock-down/out targets for CHO engineering were determined likely to affect aggregation or proteolysis. For production phenotype engineering, several of these novel targets were successfully applied to transient and transposase mediated overexpression or knock-down strategies to efficiently improve productivity of CHO cells. Thus, substantial improvement of CHO productivity was achieved by taking nature as a blueprint for cell line engineering.

Inferring secretory and metabolic pathway activity from omic data with secCellFie.

Understanding protein secretion has considerable importance in biotechnology and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer properties of protein secretion from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can help predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.

Multi-lipase gene knockdown in Chinese hamster ovary cells using artificial microRNAs to reduce host cell protein mediated polysorbate degradation.

A large number of companies observe polysorbate (PS) degradation and associated (sub-)visible particle formation in biological drug formulations, which compromise the stability of the drug product, ultimately posing a risk toward delivering innovative medicines to patients. The main culprits of PS degradation are hydrolytic host cell proteins (HCPs) originating from the production cell lines, which are mostly Chinese hamster ovary (CHO) cell derived. Here, a small portion of particularly difficult-to-remove HCPs-mainly lipases-cause hydrolytic cleavage of PS resulting in the accumulation of free fatty acid aggregates/particles. One possible mitigation strategy is the removal of such critical HCPs in the production cell line. Multigene regulation can be achieved via microRNAs (miRNAs) thereby serving as a smart tool to reduce the expression of different target genes using a single miRNA. To enable a tailored gene regulation of multiple specific target lipases self-designed and non-naturally occurring artificial miRNAs (amiRNA) can be designed. Based on micro-conserved regions in the mRNA sequence of two sets of target HCPs, we provide a proof-of-concept for a simultaneous multi-lipase knockdown in CHO cells using single amiRNAs. By this, we were not only able to reduce PS degradation but laid the foundation to expand this tool to other areas of cell line phenotype engineering.

Tailoring polishing steps for effective removal of polysorbate-degrading host cell proteins in antibody purification.

Ensuring the quality and safety of biopharmaceutical products requires the effective separation of monoclonal antibodies (mAbs) from host cell proteins (HCPs). A major challenge in this field is the enzymatic hydrolysis of polysorbates (PS) in drug products. This study addresses this issue by investigating the removal of polysorbate-degrading HCPs during the polishing steps of downstream purification, an area where knowledge about individual HCP behavior is still limited. We investigated the separation of different mAb formats from four individual polysorbate degrading hydrolases (CES1F, CES2C, LPLA2, and PAF-AH) using cation exchange (CEX) and mixed-mode chromatography (MMC) polishing steps. Our research identified a key challenge: The similar elution behavior of mAbs and HCPs during chromatographic separation. To investigate this phenomenon, we performed high-throughput binding screenings for recombinant polysorbate degrading hydrolases and representative mAb candidates on CEX and MMC chromatography resins. We then employed a three-step strategy that also served as a scale-up process, optimizing separation conditions and leading to the successful removal of specific HCPs while maintaining high mAb recovery rates (>96%). This strategy involved the use of surface response models and miniature columns for screening, followed by validation on larger columns using a chromatography system. Our results highlight the critical role of the inherent properties of mAbs for successful separation from HCPs. These results underscore the need to tailor the purification process to leverage the slight differences in binding behavior and elution profiles between mAbs and specific HCPs. This approach lays the foundation for developing more effective strategies for overcoming the challenge of enzymatic polysorbate degradation, paving the way for improved quality and safety in biopharmaceutical products.

In situ detection of protein interactions for recombinant therapeutic enzymes.

Despite their therapeutic potential, many protein drugs remain inaccessible to patients since they are difficult to secrete. Each recombinant protein has unique physicochemical properties and requires different machinery for proper folding, assembly, and posttranslational modifications (PTMs). Here we aimed to identify the machinery supporting recombinant protein secretion by measuring the protein-protein interaction (PPI) networks of four different recombinant proteins (SERPINA1, SERPINC1, SERPING1, and SeAP) with various PTMs and structural motifs using the proximity-dependent biotin identification (BioID) method. We identified PPIs associated with specific features of the secreted proteins using a Bayesian statistical model and found proteins involved in protein folding, disulfide bond formation, and N-glycosylation were positively correlated with the corresponding features of the four model proteins. Among others, oxidative folding enzymes showed the strongest association with disulfide bond formation, supporting their critical roles in proper folding and maintaining the ER stability. Knockdown of disulfide-isomerase PDIA4, a measured interactor with significance for SERPINC1 but not SERPINA1, led to the decreased secretion of SERPINC1, which relies on its extensive disulfide bonds, compared to SERPINA1, which has no disulfide bonds. Proximity-dependent labeling successfully identified the transient interactions supporting synthesis of secreted recombinant proteins and refined our understanding of key molecular mechanisms of the secretory pathway during recombinant protein production.

In pursuit of a minimal CHO genome: Establishment of large-scale genome deletions.

Chinese hamster ovary (CHO) cells are the most commonly used mammalian cell line for the production of complex therapeutic glycoproteins. As CHO cells have evolved as part of a multicellular organism, they harbor many cellular functions irrelevant for their application as production hosts in industrial bioprocesses. Consequently, CHO cells have been the target for numerous genetic engineering efforts in the past, but a tailored host cell chassis holistically optimized for its specific task in a bioreactor is still missing. While the concept of genome reduction has already been successfully applied to bacterial production cells, attempts to create higher eukaryotic production hosts exhibiting reduced genomes have not been reported yet. Here, we present the establishment and application of a large-scale genome deletion strategy for targeted excision of large genomic regions in CHO cells. We demonstrate the feasibility of genome reduction in CHO cells using optimized CRISPR/Cas9 based experimental protocols targeting large non-essential genomic regions with high efficiency. Achieved genome deletions of non-essential genetic regions did not introduce negative effects on bioprocess relevant parameters, although we conducted the largest reported genomic excision of 864 kilobase pairs in CHO cells so far. The concept presented serves as a directive to accelerate the development of a significantly genome-reduced CHO host cell chassis paving the way for a next generation of CHO cell factories.

Illuminating a biologics development challenge: systematic characterization of CHO cell-derived hydrolases identified in monoclonal antibody formulations.

Monoclonal antibodies (mAb) and other biological drugs are affected by enzymatic polysorbate (PS) degradation that reduces product stability and jeopardizes the supply of innovative medicines. PS represents a critical surfactant stabilizing the active pharmaceutical ingredients, which are produced by recombinant Chinese hamster ovary (CHO) cell lines. While the list of potential PS-degrading CHO host cell proteins (HCPs) has grown over the years, tangible data on industrially relevant HCPs are still scarce. By means of a highly sensitive liquid chromatography-tandem mass spectrometry method, we investigated seven different mAb products, resulting in the identification of 12 potentially PS-degrading hydrolases, including the strongly PS-degrading lipoprotein lipase (LPL). Using an LPL knockout CHO host cell line, we were able to stably overexpress and purify the remaining candidate hydrolases through orthogonal affinity chromatography methods, enabling their detailed functional characterization. Applying a PS degradation assay, we found nine mostly secreted, PS-active hydrolases with varying hydrolytic activity. All active hydrolases showed a serine-histidine-aspartate/glutamate catalytical triad. Further, we subjected the active hydrolases to pH-screenings and revealed a diverse range of activity optima, which can facilitate the identification of residual hydrolases during bioprocess development. Ultimately, we compiled our dataset in a risk matrix identifying PAF-AH, LIPA, PPT1, and LPLA2 as highly critical hydrolases based on their cellular expression, detection in purified antibodies, active secretion, and PS degradation activity. With this work, we pave the way toward a comprehensive functional characterization of PS-degrading hydrolases and provide a basis for a future reduction of PS degradation in biopharmaceutical drug products.

Inferring secretory and metabolic pathway activity from omic data with secCellFie.

Understanding protein secretion has considerable importance in the biotechnology industry and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer protein secretion capabilities from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can be used to predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells.

Transduction Enhancers Enable Efficient Human Adenovirus Type 5-Mediated Gene Transfer into Human Multipotent Mesenchymal Stromal Cells.

Human multipotent mesenchymal stromal cells (hMSCs) are currently developed as cell therapeutics for different applications, including regenerative medicine, immune modulation, and cancer treatment. The biological properties of hMSCs can be further modulated by genetic engineering. Viral vectors based on human adenovirus type 5 (HAdV-5) belong to the most frequently used vector types for genetic modification of human cells in vitro and in vivo. However, due to a lack of the primary attachment receptor coxsackievirus and adenovirus receptor (CAR) in hMSCs, HAdV-5 vectors are currently not suitable for transduction of this cell type without capsid modification. Here we present several transduction enhancers that strongly enhance HAdV-5-mediated gene transfer into both bone marrow- and adipose tissue-derived hMSCs. Polybrene, poly-l-lysine, human lactoferrin, human blood coagulation factor X, spermine, and spermidine enabled high eGFP expression levels in hMSCs. Importantly, hMSCs treated with enhancers were not affected in their migration behavior, which is a key requisite for many therapeutic applications. Exemplary, strongly increased expression of tumor necrosis factor (TNF)-stimulated gene 6 (TSG-6) (a secreted model therapeutic protein) was achieved by enhancer-facilitated HAdV-5 transduction. Thus, enhancer-mediated HAdV-5 vector transduction is a valuable method for the engineering of hMSCs, which can be further exploited for the development of innovative hMSC therapeutics.