The contributions of individual galactosyltransferases to protein specific N-glycan processing in Chinese Hamster Ovary cells

Identification of drug responsible glycogene signature in liver carcinoma from meta-analysis using RNA-seq data

Glycans have attracted much attention in cancer therapeutic strategies, and cell surface proteins and lipids with glycans are known to be altered during the carcinogenic process. However, our understanding of how the glycogenes profile responds to drug stimulation remains incomplete. In this study, we search public databases for Sequence Read Archive data on drug-treated liver cancer cells, with the aim to comprehensively analyze the drug responses of glycogenes via bioinformatic meta-analysis. The study comprised 86 datasets, encompassing eight distinct liver cancer cell lines and 13 different drugs. Differentially expressed genes were quantified, and 399 glycogenes were identified. The glycogenes signature was then analyzed using bioinformatics methodologies. In the Protein-protein interaction network analysis, we identified drug-responsive glycogenes such as Beta-1,4-Galactosyltransferase 1, GDP-Mannose 4,6-Dehydratase, UDP-Glucose Ceramide Glucosyltransferase, and Solute Carrier Family 2 Member 4 as key glycan biomarkers. In the enrichment analysis using the pathway list of glycogenes, the results also demonstrated that drug stimulation resulted in alterations to glycopathway-related genes involved in several processes, namely O-Mannosylation, POMGNT2 Type, Capping, Heparan Sulfate Sulfation, and Glucuronidation pathways. These genes and pathways commonly exhibit variable expression across multiple liver cancer cells in response to the same drug, making them potential targets for new cancer therapies. In addition to their primary roles, drugs may also participate in the regulation of glycans. The insights from this study could pave the way for the development of liver cancer therapies that target the regulation of gene profiles involved in the biosynthesis of glycans.

Developing microRNAs as engineering tools to modulate monoclonal antibody galactosylation

N-linked glycosylation is one of the most important post-translational modifications of monoclonal antibodies (mAbs) and is considered to be a critical quality attribute (CQA), as the glycan composition often has immunomodulatory effects. Since terminal galactose residues of mAbs can affect antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytolysis (CDC) activation, serum half-life, and antiviral activity it has to be monitored, controlled and modulated to ensure therapeutic effects. The ability of small noncoding microRNAs (miRNAs) to modulate glycosylation in Chinese hamster ovary (CHO) production cells was recently reported establishing miRNAs as engineering tools for modulation of protein glycosylation. In this study, we report the characterization and validation of miRNAs as engineering tools for increased (mmu-miR-452-5p, mmu-miR-193b-3p) or decreased (mmu-miR-7646-5p, mmu-miR-7243-3p, mmu-miR-1668, mmu-let-7c-1-3p, mmu-miR-7665-3p, mmu-miR-6403) degree of galactosylation. Furthermore, the biological mode of action regulating gene expression of the galactosylation pathway was characterized as well as their influence on bioprocess-related parameters. Most important, stable plasmid-based overexpression of these miRNAs represents a versatile tool for engineering N-linked galactosylation to achieve favorable phenotypes in cell lines for biopharmaceutical production.

Decreased B4GALT1 promotes hepatocellular carcinoma cell invasiveness by regulating the laminin-integrin pathway

Beta1,4-galactosyltransferases (B4GALTs) play a crucial role in several diseases, including cancer. B4GALT1 is highly expressed in the liver, and patients with mutations in B4GALT1 exhibit hepatopathy. However, the role of B4GALT1 in liver cancer remains unclear. Here, we found that B4GALT1 was significantly downregulated in hepatocellular carcinoma (HCC) tissue compared with the adjacent liver tissue, and low B4GALT1 expression was associated with vascular invasion and poor overall survival in patients with HCC. Additionally, silencing or loss of B4GALT1 enhanced HCC cell migration and invasion in vitro and promoted lung metastasis of HCC in NOD/SCID mice. Moreover, B4GALT1 knockdown or knockout increased cell adhesion to laminin, whereas B4GALT1 overexpression decreased the adhesion. Through a mass spectrometry-based approach and Griffonia simplicifolia lectin II (GSL-II) pull-down assays, we identified integrins α6 and β1 as the main protein substrates of B4GALT1 and their N-glycans were modified by B4GALT1. Further, the increased cell migration and invasion induced by B4GALT1 knockdown or knockout were significantly reversed using a blocking antibody against integrin α6 or integrin β1. These results suggest that B4GALT1 downregulation alters N-glycosylation and enhances the laminin-binding activity of integrin α6 and integrin β1 to promote invasiveness of HCC cells. Our findings provide novel insights into the role of B4GALT1 in HCC metastasis and highlight targeting the laminin-integrin axis as a potential therapeutic strategy for HCC with low B4GALT1 expression.

Enhancing the Heterologous Expression of a Thermophilic Endoglucanase and Its Cost-Effective Production in Pichia pastoris Using Multiple Strategies

Although Pichia pastoris was successfully used for heterologous gene expression for more than twenty years, many factors influencing protein expression remain unclear. Here, we optimized the expression of a thermophilic endoglucanase from Thermothielavioides terrestris (TtCel45A) for cost-effective production in Pichia pastoris. To achieve this, we established a multifactorial regulation strategy that involved selecting a genome-editing system, utilizing neutral loci, incorporating multiple copies of the heterologous expression cassette, and optimizing high-density fermentation for the co-production of single-cell protein (SCP). Notably, even though all neutral sites were used, there was still a slight difference in the enzymatic activity of heterologously expressed TtCel45A. Interestingly, the optimal gene copy number for the chromosomal expression of TtCel45A was found to be three, indicating limitations in translational capacity, post-translational processing, and secretion, ultimately impacting protein yields in P. pastoris. We suggest that multiple parameters might influence a kinetic competition between protein elongation and mRNA degradation. During high-density fermentation, the highest protein concentration and endoglucanase activity of TtCel45A with three copies reached 15.8 g/L and 9640 IU/mL, respectively. At the same time, the remaining SCP of P. pastoris exhibited a crude protein and amino acid content of up to 59.32% and 46.98%, respectively. These findings suggested that SCP from P. pastoris holds great promise as a sustainable and cost-effective alternative for meeting the global protein demand, while also enabling the production of thermophilic TtCel45A in a single industrial process.

Nanopore Cas9-targeted sequencing enables accurate and simultaneous identification of transgene integration sites, their structure and epigenetic status in recombinant Chinese hamster ovary cells

The integration of a transgene expression construct into the host genome is the initial step for the generation of recombinant cell lines used for biopharmaceutical production. The stability and level of recombinant gene expression in Chinese hamster ovary (CHO) can be correlated to the copy number, its integration site as well as the epigenetic context of the transgene vector. Also, undesired integration events, such as concatemers, truncated, and inverted vector repeats, are impacting the stability of recombinant cell lines. Thus, to characterize cell clones and to isolate the most promising candidates, it is crucial to obtain information on the site of integration, the structure of integrated sequence and the epigenetic status. Current sequencing techniques allow to gather this information separately but do not offer a comprehensive and simultaneous resolution. In this study, we present a fast and robust nanopore Cas9-targeted sequencing (nCats) pipeline to identify integration sites, the composition of the integrated sequence as well as its DNA methylation status in CHO cells that can be obtained simultaneously from the same sequencing run. A Cas9-enrichment step during library preparation enables targeted and directional nanopore sequencing with up to 724× median on-target coverage and up to 153 kb long reads. The data generated by nCats provides sensitive, detailed, and correct information on the transgene integration sites and the expression vector structure, which could only be partly produced by traditional Targeted Locus Amplification-seq data. Moreover, with nCats the DNA methylation status can be analyzed from the same raw data without prior DNA amplification.

Glutamine synthetase (GS) knockout (KO) using CRISPR/Cpf1 diversely enhances selection efficiency of CHO cells expressing therapeutic antibodies

The glutamine synthetase (GS)-based Chinese hamster ovary (CHO) selection system is an attractive approach to efficiently identify suitable clones in the cell line generation process for biologics manufacture, for which GS-knockout (GS-KO) CHO cell lines are commonly used. Since genome analysis indicated that there are two GS genes in CHO cells, deleting only 1 GS gene could potentially result in the activation of other GS genes, consequently reducing the selection efficiency. Therefore, in this study, both GS genes identified on chromosome 5 (GS5) and 1 (GS1) of CHO-S and CHO-K1, were deleted using CRISPR/Cpf1. Both single and double GS-KO CHO-S and K1 showed robust glutamine-dependent growth. Next, the engineered CHO cells were tested for their efficiency of selection of stable producers of two therapeutic antibodies. Analysis of pool cultures and subclones after a single round of 25 µM methionine sulfoxinime (MSX) selection indicated that for CHO-K1 the double GS5,1-KO was more efficient as in the case of a single GS5-KO the GS1 gene was upregulated. In CHO-S, on the other hand, with an autologously lower level of expression of both variants of GS, a single GS5-KO was more robust and already enabled selection of high producers. In conclusion, CRISPR/Cpf1 can be efficiently used to knock out GS genes from CHO cells. The study also indicates that for the generation of host cell lines for efficient selection, the initial characterisation of expression levels of the target gene as well as the identification of potential escape mechanisms is important.

miR-27b targets MAIP1 to mediate lipid accumulation in cultured human and mouse hepatic cells

Non-alcoholic liver disease (NAFLD) is a condition caused by excessive fat accumulation in the liver and developed via multiple pathways. miR-27b has been suggested to play crucial roles in the development of NAFLD, assuming via targeting genes involved in lipid catabolism and anabolism. However, other pathways regulated by miR-27b are largely unknown. Here we show that lipid accumulation was induced in miR-27b-transfected human and mouse hepatic cells and that knockdowns of three miR-27b-target genes, β-1,4-galactosyltransferase 3 (B4GALT3), matrix AAA peptidase interacting protein 1 (MAIP1) and PH domain and leucine rich repeat protein phosphatase 2 (PHLPP2), induced lipid accumulation. We also show that B4GALT3 and MAIP1 were direct targets of miR-27b and overexpression of MAIP1 ameliorated miR-27b-induced lipid accumulation. In addition, we show that hepatic Maip1 expression declined in mice fed a high-fat diet, suggesting the involvement of decreased Maip1 expression in the condition of fatty liver. Overall, we identified MAIP1/miR-27b axis as a mediator of hepatic lipid accumulation, a potential therapeutic target for NAFLD.

CRISPR-interceded CHO cell line development approaches

For industrial production of recombinant protein biopharmaceuticals, Chinese hamster ovary (CHO) cells represent the most widely adopted host cell system, owing to their capacity to produce high-quality biologics with human-like posttranslational modifications. As opposed to random integration, targeted genome editing in genomic safe harbor sites has offered CHO cell line engineering a new perspective, ensuring production consistency in long-term culture and high biotherapeutic expression levels. Corresponding the remarkable advancements in knowledge of CRISPR-Cas systems, the use of CRISPR-Cas technology along with the donor design strategies has been pushed into increasing novel scenarios in cell line engineering, allowing scientists to modify mammalian genomes such as CHO cell line quickly, readily, and efficiently. Depending on the strategies and production requirements, the gene of interest can also be incorporated at single or multiple loci. This review will give a gist of all the most fundamental recent advancements in CHO cell line development, such as different cell line engineering approaches along with donor design strategies for targeted integration of the desired construct into genomic hot spots, which could ultimately lead to the fast-track product development process with consistent, improved product yield and quality.

CHOGlycoNET: Comprehensive glycosylation reaction network for CHO cells

Chinese hamster ovary (CHO) cells are extensively used for the production of glycoprotein therapeutics proteins, for which N-linked glycans are a critical quality attribute due to their influence on activity and immunogenicity. Manipulation of protein glycosylation is commonly achieved through cell or process engineering, which are often guided by mathematical models. However, each study considers a unique glycosylation reaction network that is tailored around the cell line and product at hand. Herein, we use 200 glycan datasets for both recombinantly produced and native proteins from different CHO cell lines to reconstruct a comprehensive reaction network, CHOGlycoNET, based on the individual minimal reaction networks describing each dataset. CHOGlycoNET is used to investigate the distribution of mannosidase and glycosyltransferase enzymes in the Golgi apparatus and identify key network reactions using machine learning and dimensionality reduction techniques. CHOGlycoNET can be used for accelerating glycomodel development and predicting the effect of glycoengineering strategies. Finally, CHOGlycoNET is wrapped in a SBML file to be used as a standalone model or in combination with CHO cell genome scale models.

Deep learning explains the biology of branched glycans from single-cell sequencing data

Glycosylation is ubiquitous and often dysregulated in disease. However, the regulation and functional significance of various types of glycosylation at cellular levels is hard to unravel experimentally. Multi-omics, single-cell measurements such as SUGAR-seq, which quantifies transcriptomes and cell surface glycans, facilitate addressing this issue. Using SUGAR-seq data, we pioneered a deep learning model to predict the glycan phenotypes of cells (mouse T lymphocytes) from transcripts, with the example of predicting β1,6GlcNAc-branching across T cell subtypes (test set F1 score: 0.9351). Model interpretation via SHAP (SHapley Additive exPlanations) identified highly predictive genes, in part known to impact (i) branched glycan levels and (ii) the biology of branched glycans. These genes included physiologically relevant low-abundance genes that were not captured by conventional differential expression analysis. Our work shows that interpretable deep learning models are promising for uncovering novel functions and regulatory mechanisms of glycans from integrated transcriptomic and glycomic datasets.

Atractylenolide-1 targets SPHK1 and B4GALT2 to regulate intestinal metabolism and flora composition to improve inflammation in mice with colitis

BACKGROUND

Atractylenolide-1, an active component of Atractylodes Lancea, which is widely used to improve the gastrointestinal function. However, the efficacy and mechanism remain unclear in treating ulcerative colitis (UC).

PURPOSE

This study aimed to investigate the efficacy and the underlying mechanism of atractylenolide-1in UC.

METHODS

A dextran sulfate sodium (DSS)-induced UC mouse model was used to investigate the efficacy of atractylenolide-1. 16S DNA sequencing, GC-MS technique and transcriptome sequencing were used to detect the composition of mouse intestinal flora, the changes of metabolites and gene expression in mouse intestine. Compound-reaction-enzyme-gene network was used to find drug targets. Recombinant plasmid overexpression was used to verify drug targets in DSS mouse models.

RESULTS

The results showed that Atractylenolide-1 could significantly improve weight loss, diarrhea, blood in the stool, shortening of the colon, the loss of colonic goblet cells, reduction in mucoprotein MUC2, and tight junction proteins (zo-1, occludin) in mice with colitis. It reduced the inflammatory factors TNF-α, IL-6, IL-1β as well. The 16S sequencing showed that Atractylenolide-1 regulated the diversity and abundance of the intestinal flora in mice with colitis, and the analysis of flora enrichment indicated that the regulation of intestinal flora by atractylenolide-1 may be related to the regulation of metabolism. Correlation analysis of metabolomics and transcriptome showed that two genes SPHK1 and B4GALT2 related to the metabolism of fructose and galactose were regulated by atractylenolide-1. Further verification showed that atractylenolide-1 significantly inhibited the aberrance of SPHK1 and B4GALT2 in the colon with colitis. Meanwhile, it inhibited the activation of the PI3K-AKT pathway. SPHK1 and B4GALT2 overexpressing reversed the therapeutic effect of atractylenolide-1 in mice with colitis.

CONCLUSION

Atractylenolide-1 is a potential drug for the treatment of colitis by suppressing inflammation via the SPHK1/PI3K/AKT axis and by targeting SPHK1 and B4GAT2 to regulate fructose/galactose-related metabolism, thereby regulating the composition of the intestinal flora.

How to train your cell - Towards controlling phenotypes by harnessing the epigenome of Chinese hamster ovary production cell lines

Recent advances in omics technologies and the broad availability of big datasets have revolutionized our understanding of Chinese hamster ovary cells in their role as the most prevalent host for production of complex biopharmaceuticals. In consequence, our perception of this "workhorse of the biopharmaceutical industry" has successively shifted from that of a nicely working, but unknown recombinant protein producing black box to a biological system governed by multiple complex regulatory layers that might possibly be harnessed and manipulated at will. Despite the tremendous progress that has been made to characterize CHO cells on various omics levels, our understanding is still far from complete. The well-known inherent genetic plasticity of any immortalized and rapidly dividing cell line also characterizes CHO cells and can lead to problematic instability of recombinant protein production. While the high mutational frequency has been a focus of CHO cell research for decades, the impact of epigenetics and its role in differential gene expression has only recently been addressed. In this review we provide an overview about the current understanding of epigenetic regulation in CHO cells and discuss its significance for shaping the cell's phenotype. We also look into current state-of-the-art technology that can be applied to harness and manipulate the epigenetic network so as to nudge CHO cells towards a specific phenotype. Here, we revise current strategies on site-directed integration and random as well as targeted epigenome modifications. Finally, we address open questions that need to be investigated to exploit the full repertoire of fine-tuned control of multiplexed gene expression using epigenetic and systems biology tools.

Multiplexed engineering glycosyltransferase genes in CHO cells via targeted integration for producing antibodies with diverse complex-type N-glycans

Therapeutic antibodies are decorated with complex-type N-glycans that significantly affect their biodistribution and bioactivity. The N-glycan structures on antibodies are incompletely processed in wild-type CHO cells due to their limited glycosylation capacity. To improve N-glycan processing, glycosyltransferase genes have been traditionally overexpressed in CHO cells to engineer the cellular N-glycosylation pathway by using random integration, which is often associated with large clonal variations in gene expression levels. In order to minimize the clonal variations, we used recombinase-mediated-cassette-exchange (RMCE) technology to overexpress a panel of 42 human glycosyltransferase genes to screen their impact on antibody N-linked glycosylation. The bottlenecks in the N-glycosylation pathway were identified and then released by overexpressing single or multiple critical genes. Overexpressing B4GalT1 gene alone in the CHO cells produced antibodies with more than 80% galactosylated bi-antennary N-glycans. Combinatorial overexpression of B4GalT1 and ST6Gal1 produced antibodies containing more than 70% sialylated bi-antennary N-glycans. In addition, antibodies with various tri-antennary N-glycans were obtained for the first time by overexpressing MGAT5 alone or in combination with B4GalT1 and ST6Gal1. The various N-glycan structures and the method for producing them in this work provide opportunities to study the glycan structure-and-function and develop novel recombinant antibodies for addressing different therapeutic applications.

Glycoengineering Chinese hamster ovary cells: a short history

Biotherapeutic glycoproteins have revolutionised the field of pharmaceuticals, with new discoveries and continuous improvements underpinning the rapid growth of this industry. N-glycosylation is a critical quality attribute of biotherapeutic glycoproteins that influences the efficacy, half-life and immunogenicity of these drugs. This review will focus on the advances and future directions of remodelling N-glycosylation in Chinese hamster ovary (CHO) cells, which are the workhorse of recombinant biotherapeutic production, with particular emphasis on antibody products, using strategies such as cell line and protein backbone engineering.

Genetic glycoengineering in mammalian cells

Advances in nuclease-based gene-editing technologies have enabled precise, stable, and systematic genetic engineering of glycosylation capacities in mammalian cells, opening up a plethora of opportunities for studying the glycome and exploiting glycans in biomedicine. Glycoengineering using chemical, enzymatic, and genetic approaches has a long history, and precise gene editing provides a nearly unlimited playground for stable engineering of glycosylation in mammalian cells to explore and dissect the glycome and its many biological functions. Genetic engineering of glycosylation in cells also brings studies of the glycome to the single cell level and opens up wider use and integration of data in traditional omics workflows in cell biology. The last few years have seen new applications of glycoengineering in mammalian cells with perspectives for wider use in basic and applied glycosciences, and these have already led to discoveries of functions of glycans and improved designs of glycoprotein therapeutics. Here, we review the current state of the art of genetic glycoengineering in mammalian cells and highlight emerging opportunities.

Expression of β-1,4-galactosyltransferases during Aging in Caenorhabditis elegans

BACKGROUND

Altered plasma activity of β-1,4-galac-tosyl-transferases (B4GALTs) is a novel candidate biomarker of human aging. B4GALT1 is assumed to be largely responsible for this activity increase, but how it modulates the aging process is unclear at present.

OBJECTIVES

To determine how expression of B4GALT1 and other B4GALT enzymes changes during aging of an experimentally tractable model organism, Caenorhabditis elegans.

METHODS

Targeted analysis of mRNA levels of all 3 C. elegans B4GALT family members was performed by qPCR in wild-type and in long-lived daf-2 (insulin/IGF1-like receptor)-deficient or germline-deficient animals.

RESULTS

bre-4 (B4GALT1/2/3/4) is the only B4GALT whose expression increases during aging in wild-type worms. In addition, bre-4 levels also rise during aging in long-lived daf-2-deficient worms, but not in animals that are long-lived due to the lack of germline stem cells. On the other hand, expression of sqv-3 (B4GALT7) and of W02B12.11 (B4GALT5/6) appears decreased or constant, respectively, in all backgrounds during aging.

CONCLUSIONS

The age-dependent bre-4 mRNA increase in C. elegans parallels the age-dependent B4GALT activity increase in humans and is consistent with C. elegans being a suitable experimental organism to define potentially conserved roles of B4GALT1 during aging.

N-glycosylation of the human β1,4-galactosyltransferase 4 is crucial for its activity and Golgi localization

β1,4-galactosyltransferase 4 (B4GalT4) is one of seven B4GalTs that belong to CAZy glycosyltransferase family 7 and transfer galactose to growing sugar moieties of proteins, glycolipids, glycosaminoglycans as well as single sugar for lactose synthesis. Herein, we identify two asparagine-linked glycosylation sites in B4GalT4. We found that mutation of one site (Asn220) had greater impact on enzymatic activity while another (Asn335) on Golgi localization and presence of N-glycans at both sites is required for production of stable and enzymatically active protein and its secretion. Additionally, we confirm B4GalT4 involvement in synthesis of keratan sulfate (KS) by generating A375 B4GalT4 knock-out cell lines that show drastic decrease in the amount of KS proteoglycans and no significant structural changes in N- and O-glycans. We show that KS decrease in A375 cells deficient in B4GalT4 activity can be rescued by overproduction of either partially or fully glycosylated B4GalT4 but not with N-glycan-depleted B4GalT4 version.

Harnessing the potential of artificial neural networks for predicting protein glycosylation

Kinetic models offer incomparable insight on cellular mechanisms controlling protein glycosylation. However, their ability to reproduce site-specific glycoform distributions depends on accurate estimation of a large number of protein-specific kinetic parameters and prior knowledge of enzyme and transport protein levels in the Golgi membrane. Herein we propose an artificial neural network (ANN) for protein glycosylation and apply this to four recombinant glycoproteins produced in Chinese hamster ovary (CHO) cells, two monoclonal antibodies and two fusion proteins. We demonstrate that the ANN model accurately predicts site-specific glycoform distributions of up to eighteen glycan species with an average absolute error of 1.1%, correctly reproducing the effect of metabolic perturbations as part of a hybrid, kinetic/ANN, glycosylation model (HyGlycoM), as well as the impact of manganese supplementation and glycosyltransferase knock out experiments as a stand-alone machine learning algorithm. These results showcase the potential of machine learning and hybrid approaches for rapidly developing performance-driven models of protein glycosylation.

Transfection of glycoprotein encoding mRNA for swift evaluation of N-glycan engineering strategies

N‐glycosylation is defined as a key quality attribute for the majority of complex biological therapeutics. Despite many N‐glycan engineering efforts, the demand to generate desired N‐glycan profiles that may vary for different proteins in a reproducible manner is still difficult to fulfill in many cases. Stable production of homogenous structures with a more demanding level of processing, for instance high degrees of branching and terminal sialylation, is particularly challenging. Among many other influential factors, the level of productivity can steer N‐glycosylation towards less mature N‐glycan structures. Recently, we introduced an mRNA transfection system capable of elucidating bottlenecks in the secretory pathway by stepwise increase of intracellular model protein mRNA load. Here, this system was applied to evaluate engineering strategies for enhanced N‐glycan processing. The tool proves to indeed be valuable for a quick assessment of engineering approaches on the cellular N‐glycosylation capacity at high productivity. The gene editing approaches tested include overexpression of key Golgi‐resident glycosyltransferases, partially coupled with multiple gene deletions. Changes in galactosylation, sialylation, and branching potential as well as N‐acetyllactosamine formation were evaluated.

A Markov model of glycosylation elucidates isozyme specificity and glycosyltransferase interactions for glycoengineering

Glycosylated biopharmaceuticals are important in the global pharmaceutical market. Despite the importance of their glycan structures, our limited knowledge of the glycosylation machinery still hinders controllability of this critical quality attribute. To facilitate discovery of glycosyltransferase specificity and predict glycoengineering efforts, here we extend the approach to model N-linked protein glycosylation as a Markov process. Our model leverages putative glycosyltransferase (GT) specificity to define the biosynthetic pathways for all measured glycans, and the Markov chain modelling is used to learn glycosyltransferase isoform activities and predict glycosylation following glycosyltransferase knock-in/knockout. We apply our methodology to four different glycoengineered therapeutics (i.e., Rituximab, erythropoietin, Enbrel, and alpha-1 antitrypsin) produced in CHO cells. Our model accurately predicted N-linked glycosylation following glycoengineering and further quantified the impact of glycosyltransferase mutations on reactions catalyzed by other glycosyltransferases. By applying these learned GT-GT interaction rules identified from single glycosyltransferase mutants, our model further predicts the outcome of multi-gene glycosyltransferase mutations on the diverse biotherapeutics. Thus, this modeling approach enables rational glycoengineering and the elucidation of relationships between glycosyltransferases, thereby facilitating biopharmaceutical research and aiding the broader study of glycosylation to elucidate the genetic basis of complex changes in glycosylation.

Model-Driven Engineering of N-Linked Glycosylation in Chinese Hamster Ovary Cells

Chinese hamster ovary (CHO) cells are used for industrial production of protein-based therapeutics (i.e., "biologics"). Here we describe a method for combining systems-level kinetic models with a synthetic biology platform for multigene overexpression to rationally perturb N-linked glycosylation. Specifically, we sought to increase galactose incorporation on a secreted Immunoglobulin G (IgG) protein. We rationally design, build, and test a total of 23 transgenic cell pools that express single or three-gene glycoengineering cassettes comprising a total of 100 kilobases of engineered DNA sequence. Through iterative engineering and model refinement, we rationally increase the fraction of bigalactosylated glycans five-fold from 11.9% to 61.9% and simultaneously decrease the glycan heterogeneity on the secreted IgG. Our approach allows for rapid hypothesis testing and identification of synergistic behavior from genetic perturbations by bridging systems and synthetic biology.

mRNA Transfection into CHO-Cells Reveals Production Bottlenecks

Obtaining highly productive Chinese hamster ovary (CHO)-cell clones for the production of therapeutic proteins relies on multiple time-consuming selection steps. Several CHO-cell strains with high degrees of genomic and epigenetic variation are available. Each harbor potential advantages and disadvantages for any given product, particularly those considered difficult to express. A simple test system to quickly assess compatibility of cell line and product may therefore prove useful. Transient plasmid transfection falls short of the specific productivities of stable producer cells, making it unsuitable for the elucidation of high specific productivity bottlenecks. The aim of the study is to reach specific productivities approaching those of industrial production cell lines by transfection of in vitro transcribed mRNA. The system is characterized with respect to transfection efficacy (by quantitative PCR) and protein production (by flow cytometry and biolayer interferometry). Fluorescence of intracellular eGFP saturates at higher amounts of mRNA per cell, while the amount of secreted and intracellular EPO-Fc remain linearly correlated to the amount of mRNA taken up. Nevertheless, MS shows a severe reduction in N-glycosylation quality. This method allows for rapid elucidation of bottlenecks that would otherwise remain undetected until later during cell line development, giving insight into suitable strategies for preemptive targeted metabolic engineering and host cell line optimization.

Genetic engineering approaches to improve posttranslational modification of biopharmaceuticals in different production platforms

The number of approved biopharmaceuticals, where product quality attributes remain of major importance, is increasing steadily. Within the available variety of expression hosts, the production of biopharmaceuticals faces diverse limitations with respect to posttranslational modifications (PTM), while different biopharmaceuticals demand different forms and specifications of PTMs for proper functionality. With the growing toolbox of genetic engineering technologies, it is now possible to address general as well as host- or biopharmaceutical-specific product quality obstacles. In this review, we present diverse expression systems derived from mammalians, bacteria, yeast, plants, and insects as well as available genetic engineering tools. We focus on genes for knockout/knockdown and overexpression for meaningful approaches to improve biopharmaceutical PTMs and discuss their applicability as well as future trends in the field.