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.

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.

From omics to Cellular mechanisms in mammalian cell factory development.

Mammalian cells have been used widely as biopharmaceutical cell factories due to their ability to make complex biotherapeutic proteins with human-compatible modifications. However, their application for some products has been hampered by low protein yields. Numerous studies have aimed to characterize cellular bottlenecks in the hope of boosting protein productivity, but the complexity of the underlying pathways and the diversity of the modifications have complicated cell engineering when relying solely on traditional methodologies. Incorporating omics-based and systems approaches into cell engineering can provide valuable insights into desirable phenotypes of cell factories. Here, we discuss cell engineering strategies for enhancing protein productivity in mammalian cell factories, particularly CHO and HEK293, and the opportunities and limitations of the genome-wide screening and multi-omics approaches for guiding cell engineering. Systems biology strategies will also be discussed to show how they refine our understanding of the cellular mechanisms which will aid in effective engineering strategies.

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.

Revealing Key Determinants of Clonal Variation in Transgene Expression in Recombinant CHO Cells Using Targeted Genome Editing.

Generation of recombinant Chinese hamster ovary (rCHO) cell lines is critical for the production of therapeutic proteins. However, the high degree of phenotypic heterogeneity among generated clones, referred to as clonal variation, makes the rCHO cell line development process inefficient and unpredictable. Here, we investigated the major genomic causes of clonal variation. We found the following: (1) consistent with previous studies, a strong variation in rCHO clones in response to hypothermia (33 vs 37 °C) after random transgene integration; (2) altered DNA sequence of randomly integrated cassettes, which occurred during the integration process, affecting the transgene expression level in response to hypothermia; (3) contrary to random integration, targeted integration of the same expression cassette, without any DNA alteration, into three identified integration sites showed the similar response of transgene expression in response to hypothermia, irrespective of integration site; (4) switching the promoter from CMV to EF1α eliminated the hypothermia response; and (5) deleting the enhancer part of the CMV promoter altered the hypothermia response. Thus, we have revealed the effects of integration methods and cassette design on transgene expression levels, implying that rCHO cell line generation can be standardized through detailed genomic understanding. Further elucidation of such understanding is likely to have a broad impact on diverse fields that use transgene integration, from gene therapy to generation of production cell lines.

A reference genome of the Chinese hamster based on a hybrid assembly strategy.

Accurate and complete genome sequences are essential in biotechnology to facilitate genome-based cell engineering efforts. The current genome assemblies for Cricetulus griseus, the Chinese hamster, are fragmented and replete with gap sequences and misassemblies, consistent with most short-read-based assemblies. Here, we completely resequenced C. griseus using single molecule real time sequencing and merged this with Illumina-based assemblies. This generated a more contiguous and complete genome assembly than either technology alone, reducing the number of scaffolds by >28-fold, with 90% of the sequence in the 122 longest scaffolds. Most genes are now found in single scaffolds, including up- and downstream regulatory elements, enabling improved study of noncoding regions. With >95% of the gap sequence filled, important Chinese hamster ovary cell mutations have been detected in draft assembly gaps. This new assembly will be an invaluable resource for continued basic and pharmaceutical research.

The emerging role of systems biology for engineering protein production in CHO cells.

To meet the ever-growing demand for effective, safe, and affordable protein therapeutics, decades of intense efforts have aimed to maximize the quantity and quality of recombinant proteins produced in CHO cells. Bioprocessing innovations and cell engineering efforts have improved product titer; however, uncharacterized cellular processes and gene regulatory mechanisms still hinder cell growth, specific productivity, and protein quality. Herein, we summarize recent advances in systems biology and data-driven approaches aiming to unravel how molecular pathways, cellular processes, and extrinsic factors (e.g. media supplementation) influence recombinant protein production. In particular, as the available omics data for CHO cells continue to grow, predictive models and screens will be increasingly used to unravel the biological drivers of protein production, which can be used with emerging genome editing technologies to rationally engineer cells to further control the quantity, quality and affordability of many biologic drugs.

Modulating carbohydrate-protein interactions through glycoengineering of monoclonal antibodies to impact cancer physiology.

Diverse glycans on proteins impact cell and organism physiology, along with drug activity. Since many protein-based biotherapeutics are glycosylated and these glycans have biological activity, there is a desire to engineer glycosylation for recombinant protein-based biotherapeutics. Engineered glycosylation can impact the recombinant protein efficacy and also influence many cell pathways by first changing glycan-protein interactions and consequently modulating disease physiologies. However, its complexity is enormous. Recent advances in glycoengineering now make it easier to modulate protein-glycan interactions. Here, we discuss how engineered glycans contribute to therapeutic monoclonal antibodies (mAbs) in the treatment of cancers, how these glycoengineered therapeutic mAbs affect the transformed phenotypes and downstream cell pathways. Furthermore, we suggest how systems biology can help in the next generation mAb glycoengineering process by aiding in data analysis and guiding engineering efforts to tailor mAb glycan and ultimately drug efficacy, safety and affordability.

Inhibition of Coenzyme Qs Accumulation in Engineered Escherichia coli by High Concentration of Farnesyl Diphosphate.

BACKGROUND: Coenzyme Q 10 (CoQ 10 ) is an isoprenoid component used widely in nutraceutical industries. Farnesyl diphosphate synthase (FPPS) is a responsible enzyme for biosynthesis of farnesyl diphosphate (FPP), a key precursor for CoQs production. This research involved investigating the effect of FPPS over-expression on CoQs production in engineered CoQ 10 -producing Escherichia coli (E. coli). METHODS: Two CoQ 10 -producing strains, as referred to E. coli Ba and E. coli Br, were transformed by the encoding gene for FPPS (ispA) under the control of either the trc or P BAD promoters. RESULTS: Over-expression of ispA under the control of P BAD promoter led to a relative increase in CoQ 10 production only in recombinant E. coli Br although induction by arabinose resulted in partial reduction of CoQ 10 production in both recombinant E. coli Ba and E. coli Br strains. Over-expression of ispA under the control of stronger trc promoter, however, led to a severe decrease in CoQ 10 production in both recombinant E. coli Ba and E. coli Br strains, as reflected by reductions from 629±40 to 30±13 and 564±28 to 80±14 µg/g Dried Cell Weight (DCW), respectively. The results showed high level of FPP reduces endogenous CoQ 8 production as well and that CoQs are produced in a complimentary manner, as the increase in production of one decreases the production of the other. CONCLUSION: The reduction in CoQ 10 production can be a result of Dds inhibition by high FPP concentration. Therefore, more effort is needed to verify the role of intermediate metabolite concentration and to optimize production of CoQ 10 .

Rational design of hyper-glycosylated interferon beta analogs: a computational strategy for glycoengineering.

Glycoengineering has been successfully used to improve the physicochemical and pharmaceutical properties of therapeutics. One aspect of glycoengineering is to introduce new N-linked glycosylation consensus sequences (Asn, X, Thr/Ser) into desirable positions in the peptide backbone by mutational insertion to generate proteins with increased sialic acid content. In the current work, human interferon beta (huIFN-ß) was used as a model to identify the potential positions for the addition of new N-glycosylation sites. A computational strategy was employed to predict the structural distortions and functional alterations that might be caused by the change in amino acid sequence. Accordingly, three-dimensional (3D) structures of the designed huIFN-ß analogs were generated by comparative modeling. Molecular dynamics (MD) simulation was carried out to assess the molecular stability and flexibility profile of the structures. Subsequently, for the purpose of glycoengineering huIFN-ß, analogs with 3D structures more similar to the wild-type huIFN-ß and exposed Asn residue in the new N-glycosylation site were identified. These modeling procedures indicated that the addition of the new N-glycosylation site in the loop regions had lower constraining effects on the tertiary structure of the protein. This computational strategy can be applied to avoid alterations in the 3D structure of proteins caused by changes in the amino acid sequences, when designing novel hyper-glycosylated therapeutics. This in turn reduces labor-intensive experimental analyses of each analog.