Global insights into the Chinese hamster and CHO cell transcriptomes

Multi-cell-line learning for the data-driven construction of mechanistic metabolic models

Mammalian cells are commonly used as hosts in cell culture for biologics production in the pharmaceutical industry. Structured mechanistic models of metabolism have been used to capture complex cellular mechanisms that contribute to varying metabolic shifts in different cell lines. However, little research has focused on the impact of temporal changes in enzyme abundance and activity on the modeling of cell metabolism. In this work, we present a framework for constructing mechanistic models of metabolism that integrate growth-signaling control of enzyme activity and transcript dynamics. The proposed approach is applied to build models for three Chinese hamster ovary (CHO) cell lines using fed-batch culture data and time-series transcript profiles. Leveraging information from the transcriptome data, we develop a parameter estimation approach based on multi-cell-line (MCL) learning, which combines data sets from different cell lines and trains the individual cell-line models jointly to improve model accuracy. The computational results demonstrate the important role of growth signaling and transcript variability in metabolic models as well as the virtue of the MCL approach for constructing cell-line models with a limited amount of data. The resulting models exhibit a high level of accuracy in predicting distinct metabolic behaviors in the different cell lines; these models can potentially be used to accelerate the process and cell-line development for the biomanufacturing of new protein therapeutics.

The microRNomes of Chinese hamster ovary (CHO) cells and their extracellular vesicles, and how they respond to osmotic and ammonia stress

A new area of focus in Chinese hamster ovary (CHO) biotechnology is the role of small (exosomes) and large (microvesicles or microparticles) extracellular vesicles (EVs). CHO cells in culture exchange large quantities of proteins and RNA through these EVs, yet the content and role of these EVs remain elusive. MicroRNAs (miRs or miRNA) are central to adaptive responses to stress and more broadly to changes in culture conditions. Given that EVs are highly enriched in miRs, and that EVs release large quantities of miRs both in vivo and in vitro, EVs and their miR content likely play an important role in adaptive responses. Here we report the miRNA landscape of CHO cells and their EVs under normal culture conditions and under ammonia and osmotic stress. We show that both cells and EVs are highly enriched in five miRs (among over 600 miRs) that make up about half of their total miR content, and that these highly enriched miRs differ significantly between normal and stress culture conditions. Notable is the high enrichment in miR-92a and miR-23a under normal culture conditions, in contrast to the high enrichment in let-7 family miRs (let-7c, let-7b, and let-7a) under both stress conditions. The latter suggests a preserved stress-responsive function of the let-7 miR family, one of the most highly preserved miR families across species, where among other functions, let-7 miRs regulate core oncogenes, which, depending on the biological context, may tip the balance between cell cycle arrest and apoptosis. While the expected-based on their profound enrichment-important role of these highly enriched miRs remains to be dissected, our data and analysis constitute an important resource for exploring the role of miRs in cell adaptation as well as for synthetic applications.

LncRNA analysis of mAb producing CHO clones reveals marker and engineering potential

Long non-coding RNAs (lncRNAs) are a potential new cell line engineering tool for improvement of yield and stability of CHO cells. In this study, we performed RNA sequencing of mAb producer CHO clones to study the lncRNA and protein coding transcriptome in relation to productivity. First, a robust linear model was used to identify genes correlating to productivity. To unravel specific patterns in expression of these genes, we employed weighted gene coexpression analysis (WGCNA) to find coexpressed modules, looking both for lncRNAs and coding genes. There was little overlap in the genes associated with productivity between the two products studied, possibly due to the difference in absolute range of productivity between the two mAbs. Therefore, we focused on the product with higher productivity and stronger candidate lncRNAs. To evaluate their potential as engineering targets, these candidate lncRNAs were transiently overexpressed or deleted by stable CRISPR Cas9 knock out both in a high and a low productivity subclone. We found that the thus achieved expression level of the identified lncRNAs, as confirmed by qPCR, does correlate well to productivity, so that they represent good markers that may be used for early clone selection. Additionally, we found that the deletion of one tested lncRNA region decreased viable cell density (VCD), prolonged culture time and increased cell size, final titer and specific productivity per cell. These results demonstrate the feasibility and usefulness of engineering lncRNA expression in production cell lines.

A pooled CRISPR/AsCpf1 screen using paired gRNAs to induce genomic deletions in Chinese hamster ovary cells

• Development of a small-scale CRISPR/AsCpf1 screen in CHO.

• Usage of paired gRNAs enables full deletion of coding or noncoding genomic regions.

• Growth perturbing paired gRNAs identified.

• Key points for considerations in future screens identified.

Chinese hamster ovary (CHO) cells are the most widely used host for the expression of therapeutic proteins. Recently, significant progress has been made due to advances in genome sequence and annotation quality to unravel the black box CHO. Nevertheless, in many cases the link between genotype and phenotype in the context of suspension cultivated production cell lines is still not fully understood. While frameshift approaches targeting coding genes are frequently used, the non-coding regions of the genome have received less attention with respect to such functional annotation. Importantly, for non-coding regions frameshift knock-out strategies are not feasible. In this study, we developed a CRISPR-mediated screening approach that performs full deletions of genomic regions to enable the functional study of both the translated and untranslated genome.

An in silico pipeline for the computational high-throughput design of paired guide RNAs (pgRNAs) directing CRISPR/AsCpf1 was established and used to generate a library tackling process-related genes and long non-coding RNAs. Next generation sequencing analysis of the plasmid library revealed a sufficient, but highly variable pgRNA composition. Recombinase-mediated cassette exchange was applied for pgRNA library integration rather than viral transduction to ensure single copy representation of pgRNAs per cell. After transient AsCpf1 expression, cells were cultivated over two sequential batches to identify pgRNAs which massively affected growth and survival. By comparing pgRNA abundance, depleted candidates were identified and individually validated to verify their effect.

Epigenomic features revealed by ATAC-seq impact transgene expression in CHO cells

Different regions of a mammalian genome have different accessibilities to transcriptional machinery. The integration site of a transgene affects how actively it is transcribed. Highly accessible genomic regions called super-enhancers have been recently described as strong regulatory elements that shape cell identity. Super-enhancers have been identified in Chinese hamster ovary (CHO) cells using the Assay for Transposase-Accessible Chromatin Sequencing (ATAC-seq). Genes near super-enhancer regions had high transcript levels and were enriched for oncogenic signaling and proliferation functions, consistent with an immortalized phenotype. Inaccessible regions in the genome with low ATAC signal also had low transcriptional activity. Genes in inaccessible regions were enriched for remote tissue functions such as taste, smell, and neuronal activation. A lentiviral reporter integration assay showed integration into super-enhancer regions conferred higher reporter expression than insertion into inaccessible regions. Targeted integration of an IgG vector into the Plec super-enhancer region yielded clones that expressed the immunoglobulin light chain gene mostly in the top 20% of all transcripts with the majority in the top 5%. The results suggest the epigenomic landscape of CHO cells can guide the selection of integration sites in the development of cell lines for therapeutic protein production.

Incorporating RNA-Seq transcriptomics into glycosylation-integrating metabolic network modelling kinetics: Multiomic Chinese hamster ovary (CHO) cell bioreactors

In this work, the kinetic model based on the previously developed metabolic and glycan reaction networks of the ovarian cells of the Chinese hamster ovary (CHO) cell line was improved by the inclusion of transcriptomic data that took into account the values of the RPKM gene (Reads per Kilobase of Exon per Million Reads Mapped). The transcriptomic (RNASeq) data were obtained together with metabolic and glycan data from the literature, and the concentrations with RPKM values were collected at several points in time from two fed-batch processes. First, the fluxes were determined by regression analysis of the metabolic data, then these fluxes were corrected by using the fold change in gene expression as a measure of enzyme concentrations. Next, the corrected fluxes in the kinetic model were used to calculate the concentration profiles of the metabolites, and literature data were used to evaluate the predicted results of the model. Compared to other studies where the concentration profiles of CHO cell metabolites were described using a kinetic model without consideration of RNA-Seq data to correct the fluxes, this model is unique. The additional integration of transcriptomic data led to better predictions of metabolic concentrations in the fed-batch process, which is a significant improvement of the modelling technique used.

Directed evolution approach to enhance efficiency and speed of outgrowth during single cell subcloning of Chinese Hamster Ovary cells

Chinese Hamster Ovary (CHO) cells are the working horse of the pharmaceutical industry. To obtain high producing cell clones and to satisfy regulatory requirements single cell cloning is a necessary step in cell line development. However, it is also a tedious, labor intensive and expensive process. Here we show an easy way to enhance subclonability using subcloning by single cell sorting itself as the selection pressure, resulting in improved subcloning performance of three different host cell lines. These improvements in subclonability also lead to an enhanced cellular growth behavior during standard batch culture. RNA-seq was performed to shed light on the underlying mechanisms, showing that there is little overlap in differentially expressed genes or associated pathways between the cell lines, each finding their individual strategy for optimization. However, in all three cell lines pathways associated with the extracellular matrix were found to be enriched, indicating that cells struggle predominantly with their microenvironment and possibly lack of cell-to-cell contact. The observed small overlap may hint that there are multiple ways for a cell line to achieve a certain phenotype due to numerous genetic and subsequently metabolic redundancies.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

Mammalian Systems Biotechnology Reveals Global Cellular Adaptations in a Recombinant CHO Cell Line

Effective development of host cells for therapeutic protein production is hampered by the poor characterization of cellular transfection. Here, we employed a multi-omics-based systems biotechnology approach to elucidate the genotypic and phenotypic differences between a wild-type and recombinant antibody-producing Chinese hamster ovary (CHO) cell line. At the genomic level, we observed extensive rearrangements in specific targeted loci linked to transgene integration sites. Transcriptional re-wiring of DNA damage repair and cellular metabolism in the antibody producer, via changes in gene copy numbers, was also detected. Subsequent integration of transcriptomic data with a genome-scale metabolic model showed a substantial increase in energy metabolism in the antibody producer. Metabolomics, lipidomics, and glycomics analyses revealed an elevation in long-chain lipid species, potentially associated with protein transport and secretion requirements, and a surprising stability of N-glycosylation profiles between both cell lines. Overall, the proposed knowledge-based systems biotechnology framework can further accelerate mammalian cell-line engineering in a targeted manner.

Combating viral contaminants in CHO cells by engineering innate immunity

Viral contamination in biopharmaceutical manufacturing can lead to shortages in the supply of critical therapeutics. To facilitate the protection of bioprocesses, we explored the basis for the susceptibility of CHO cells to RNA virus infection. Upon infection with certain ssRNA and dsRNA viruses, CHO cells fail to generate a significant interferon (IFN) response. Nonetheless, the downstream machinery for generating IFN responses and its antiviral activity is intact in these cells: treatment of cells with exogenously-added type I IFN or poly I:C prior to infection limited the cytopathic effect from Vesicular stomatitis virus (VSV), Encephalomyocarditis virus (EMCV), and Reovirus-3 virus (Reo-3) in a STAT1-dependent manner. To harness the intrinsic antiviral mechanism, we used RNA-Seq to identify two upstream repressors of STAT1: Gfi1 and Trim24. By knocking out these genes, the engineered CHO cells exhibited activation of cellular immune responses and increased resistance to the RNA viruses tested. Thus, omics-guided engineering of mammalian cell culture can be deployed to increase safety in biotherapeutic protein production among many other biomedical applications.

A Comparative Transcriptomics Workflow for Analyzing Microarray Data From CHO Cell Cultures

Microarray-based comparative transcriptomics analysis is a powerful tool to understand therapeutic protein producing mammalian cell lines at the gene expression level. However, an integrated analysis workflow specifically designed for end-to-end analysis of microarray data for CHO cells, the most prevalent host for commercial recombinant protein production, is lacking. To address this gap, an automated data analysis workflow in R that leverages public domain analysis modules is developed to analyze microarray based gene expression data. In addition to testing the global transcriptome differences of CHO cells at different conditions, the workflow identifies differentially expressed genes and pathways with intuitive visualizations as the outputs. The utility of this automated workflow is demonstrated by comparing the transcriptomic profiles of recombinant protein expressing CHO cells with and without a temperature shift. Statistically significant differential expression at the gene, pathway, and global transcriptome levels are identified and visualized. An automated workflow like the one developed in this study will enable rapid translation of CHO culture microarray data into biologically relevant information for mechanism-driven cell line optimization and bioprocess development.

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.

CHO-Omics Review: The Impact of Current and Emerging Technologies on Chinese Hamster Ovary Based Bioproduction

CHO cells are the most prevalent platform for modern bio-therapeutic production. Currently, there are several CHO cell lines used in bioproduction with distinct characteristics and unique genotypes and phenotypes. These differences limit advances in productivity and quality that can be achieved by the most common approaches to bioprocess optimization and cell line engineering. Incorporating omics-based approaches into current bioproduction processes will complement traditional methodologies to maximize gains from CHO engineering and bioprocess improvements. In order to highlight the utility of omics technologies in CHO bioproduction, the authors discuss current applications as well as limitations of genomics, transcriptomics, proteomics, metabolomics, lipidomics, fluxomics, glycomics, and multi-omics approaches and the potential they hold for the future of bioproduction. Multiple omics approaches are currently being used to improve CHO bioprocesses; however, the application of these technologies is still limited. As more CHO-omic datasets become available and integrated into systems models, the authors expect significant gains in product yield and quality. While individual omics technologies provide incremental improvements in bioproduction, the authors will likely see the most significant gains by applying multi-omics and systems biology approaches to individual CHO cell lines.

Amino acid misincorporation in recombinant proteins

Proteins provide the molecular basis for cellular structure, catalytic activity, signal transduction, and molecular transport in biological systems. Recombinant protein expression is widely used to prepare and manufacture novel proteins that serve as the foundation of many biopharmaceutical products. However, protein translation bioprocesses are inherently prone to low-level errors. These sequence variants caused by amino acid misincorporation have been observed in both native and recombinant proteins. Protein sequence variants impact product quality, and their presence can be exacerbated through cellular stress, overexpression, and nutrient starvation. Therefore, the cell line selection process, which is used in the biopharmaceutical industry, is not only directed towards maximizing productivity, but also focuses on selecting clones which yield low sequence variant levels, thereby proactively avoiding potentially inauspicious patient safety and efficacy outcomes. Here, we summarize a number of hallmark studies aimed at understanding the mechanisms of amino acid misincorporation, as well as exacerbating factors, and mitigation strategies. We also describe key advances in analytical technologies in the identification and quantification of sequence variants, and some practical considerations when using LC-MS/MS for detecting sequence variants.

Evaluation of two public genome references for chinese hamster ovary cells in the context of rna-seq based gene expression analysis

RNA-Seq is a powerful transcriptomics tool for mammalian cell culture process development. Successful RNA-Seq data analysis requires a high quality reference for read mapping and gene expression quantification. Currently, there are two public genome references for Chinese hamster ovary (CHO) cells, the predominant mammalian cell line in the biopharmaceutical industry. In this study, we compared these two references by analyzing 60 RNA-Seq samples from a variety of CHO cell culture conditions. Among the 20,891 common genes in both references, we observed that 31.5% have more than 7.1% quantification differences, implying gene definition differences in the two references. We propose a framework to quantify this difference using two metrics, Consistency and Stringency, which account for the average quantification difference between the two references over all samples, and the sample-specific effect on the quantification result, respectively. These two metrics can be used to identify potential genes for future gene model improvement and to understand the reliability of differentially expressed genes identified by RNA-Seq data analysis. Before a more comprehensive genome reference for CHO cells emerges, the strategy proposed in this study can enable more robust transcriptome analysis from CHO cell RNA-Seq data. Biotechnol. Bioeng. 2017;114: 1603-1613. © 2017 Wiley Periodicals, Inc.

Regulation of miR-29b-1/a transcription and identification of target mRNAs in CHO-K1 cells

miR-29b and miR-29a transcript levels were reported to increase in exponentially growing CHO-K1 cells. Here, we examine the regulation of miR-29b-1/a in CHO-K1 cells. We observed that 4-hydroxytamoxifen (4-OHT) increased pri-miR-29b-1 and pri-miR-29a transcription in CHO-K1 cells by activating endogenous estrogen receptor α (ERα). DICER, an established, bona fide target of miR-29b-1/a, was shown to be regulated by 4-OHT in CHO-K1 cells. We showed that miR-29b-1 and miR-29a serve a repressive role in cell proliferation, migration, invasion, and colony formation in CHO-K1 cells. To identify other targets of miR-29b-1 and miR-29a, RNA sequencing was performed by transfecting cells with anti-miR-29a, which inhibits both miR-29a and miR-29b-1, pre-miR-29b-1, and/or pre-miR-29a. In silico network analysis in MetaCore™ identified common and unique putative gene targets of miR-29b-1 and miR-29a. Pathway analysis of identified putative miR-29 targets were related to cell adhesion, cytoskeletal remodeling, and development. Further inquiry revealed regulation of pathways mediating responses to growth factor stimulus and cell cycle regulation.

Unveiling gene trait relationship by cross-platform meta-analysis on Chinese hamster ovary cell transcriptome

In the past few years, transcriptome analysis has been increasingly employed to better understand the physiology of Chinese hamster ovary (CHO) cells at a global level. As more transcriptome data accumulated, meta-analysis on data sets collected from various sources can potentially provide better insights on common properties of those cells. Here, we performed meta-analysis on transcriptome data of different CHO cell lines obtained using NimbleGen or Affymetrix microarray platforms. Hierarchical clustering, non-negative matrix factorization (NMF) analysis, and principal component analysis (PCA) accordantly showed the samples were clustered into two groups: one consists of adherent cells in serum-containing medium, and the other suspension cells in serum-free medium. Genes that were differentially expressed between the two clusters were enriched in a few functional classes by Database for Annotation, Visualization, and Integrated Discovery (DAVID) of which many were common with the enriched gene sets identified by Gene Set Enrichment Analysis (GSEA), including extracellular matrix (ECM) receptor interaction, cell adhesion molecules (CAMs), and lipid related metabolism pathways. Despite the heterogeneous sources of the cell samples, the adherent and suspension growth characteristics and serum-supplementation appear to be a dominant feature in the transcriptome. The results demonstrated that meta-analysis of transcriptome could uncover features in combined data sets that individual data set might not reveal. As transcriptome data sets accumulate over time, meta-analysis will become even more revealing. Biotechnol. Bioeng. 2017;114: 1583-1592. © 2017 Wiley Periodicals, Inc.

Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion

Recombinant protein production coopts the host cell machinery to provide high protein yields of industrial enzymes or biotherapeutics. However, since protein translation is energetically expensive and tightly controlled, it is unclear if highly expressed recombinant genes are translated as efficiently as host genes. Furthermore, it is unclear how the high expression impacts global translation. Here, we present the first genome-wide view of protein translation in an IgG-producing CHO cell line, measured with ribosome profiling. Through this we found that our recombinant mRNAs were translated as efficiently as the host cell transcriptome, and sequestered up to 15% of the total ribosome occupancy. During cell culture, changes in recombinant mRNA translation were consistent with changes in transcription, demonstrating that transcript levels influence specific productivity. Using this information, we identified the unnecessary resistance marker NeoR to be a highly transcribed and translated gene. Through siRNA knock-down of NeoR, we improved the production- and growth capacity of the host cell. Thus, ribosomal profiling provides valuable insights into translation in CHO cells and can guide efforts to enhance protein production.

Effect of Temperature Downshift on the Transcriptomic Responses of Chinese Hamster Ovary Cells Using Recombinant Human Tissue Plasminogen Activator Production Culture

Recombinant proteins are widely used as biopharmaceuticals, but their production by mammalian cell culture is expensive. Hence, improvement of bioprocess productivity is greatly needed. A temperature downshift (TDS) from 37°C to 28–34°C is an effective strategy to expand the productive life period of cells and increase their productivity (q_p). Here, TDS in Chinese hamster ovary (CHO) cell cultures, initially grown at 37°C and switched to 30°C during the exponential growth phase, resulted in a 1.6-fold increase in the q_p of recombinant human tissue plasminogen activator (rh-tPA). The transcriptomic response using next-generation sequencing (NGS) was assessed to characterize the cellular behavior associated with TDS. A total of 416 (q > 0.8) and 3,472 (q > 0.9) differentially expressed transcripts, with more than a 1.6-fold change at 24 and 48 h post TDS, respectively, were observed in cultures with TDS compared to those at constant 37°C. In agreement with the extended cell survival resulting from TDS, transcripts related to cell growth arrest that controlled cell proliferation without the activation of the DNA damage response, were differentially expressed. Most upregulated genes were related to energy metabolism in mitochondria, mitochondrial biogenesis, central metabolism, and avoidance of apoptotic cell death. The gene coding for rh-tPA was not differentially expressed, but fluctuations were detected in the transcripts encoding proteins involved in the secretory machinery, particularly in glycosylation. Through NGS the dynamic processes caused by TDS were assessed in this biological system.

Precision control of recombinant gene transcription for CHO cell synthetic biology

The next generation of mammalian cell factories for biopharmaceutical production will be genetically engineered to possess both generic and product-specific manufacturing capabilities that may not exist naturally. Introduction of entirely new combinations of synthetic functions (e.g. novel metabolic or stress-response pathways), and retro-engineering of existing functional cell modules will drive disruptive change in cellular manufacturing performance. However, before we can apply the core concepts underpinning synthetic biology (design, build, test) to CHO cell engineering we must first develop practical and robust enabling technologies. Fundamentally, we will require the ability to precisely control the relative stoichiometry of numerous functional components we simultaneously introduce into the host cell factory. In this review we discuss how this can be achieved by design of engineered promoters that enable concerted control of recombinant gene transcription. We describe the specific mechanisms of transcriptional regulation that affect promoter function during bioproduction processes, and detail the highly-specific promoter design criteria that are required in the context of CHO cell engineering. The relative applicability of diverse promoter development strategies are discussed, including re-engineering of natural sequences, design of synthetic transcription factor-based systems, and construction of synthetic promoters. This review highlights the potential of promoter engineering to achieve precision transcriptional control for CHO cell synthetic biology.

Transcriptome sequencing and development of an expression microarray platform for liver infection in adenovirus type 5-infected Syrian golden hamsters

The Syrian golden hamster is an attractive animal for research on infectious diseases and other diseases. We report here the sequencing, assembly, and annotation of the Syrian hamster transcriptome. We include transcripts from ten pooled tissues from a naïve hamster and one stimulated with lipopolysaccharide. Our data set identified 42,707 non-redundant transcripts, representing 34,191 unique genes. Based on the transcriptome data, we generated a custom microarray and used this new platform to investigate the transcriptional response in the Syrian hamster liver following intravenous adenovirus type 5 (Ad5) infection. We found that Ad5 infection caused a massive change in regulation of liver transcripts, with robust up-regulation of genes involved in the antiviral response, indicating that the innate immune response functions in the host defense against Ad5 infection of the liver. The data and novel platforms developed in this study will facilitate further development of this important animal model.

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Syrian hamster transcriptome; 42,707 transcripts representing 34,191 unique genes

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Syrian hamster custom expression microarray platform

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Ad5 intravenous infection of the Syrian hamster liver

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Ad5 upregulation of hamster liver genes involved in innate antiviral response.

A Panel of Recombinant Mucins Carrying a Repertoire of Sialylated O-Glycans Based on Different Core Chains for Studies of Glycan Binding Proteins

Sialylated glycans serve as key elements of receptors for many viruses, bacteria, and bacterial toxins. The microbial recognition and their binding specificity can be affected by the linkage of the terminal sugar residue, types of underlying sugar chains, and the nature of the entire glycoconjugate. Owing to the pathobiological significance of sialylated glycans, we have engineered Chinese hamster ovary (CHO) cells to secrete mucin-type immunoglobulin-fused proteins carrying terminal α2,3- or α2,6-linked sialic acid on defined O-glycan core saccharide chains. Besides stably expressing P-selectin glycoprotein ligand-1/mouse immunoglobulin G2b cDNA (PSGL-1/mIgG2b), CHO cells were stably transfected with plasmids encoding glycosyltransferases to synthesize core 2 (GCNT1), core 3 (B3GNT6), core 4 (GCNT1 and B3GNT6), or extended core 1 (B3GNT3) chains with or without the type 1 chain-encoding enzyme B3GALT5 and ST6GAL1. Western blot and liquid chromatography-mass spectrometry analysis confirmed the presence of core 1, 2, 3, 4, and extended core 1 chains carrying either type 1 (Galb3GlcNAc) or type 2 (Galb4GlcNAc) outer chains with or without α2,6-linked sialic acids. This panel of recombinant mucins carrying a repertoire of sialylated O-glycans will be important tools in studies aiming at determining the fine O-glycan binding specificity of sialic acid-specific microbial adhesins and mammalian lectins.

An evaluation of public genomic references for mapping RNA-Seq data from Chinese hamster ovary cells

While RNA-Seq is increasingly used as the method of choice for transcriptome analysis of mammalian cell culture processes, no universal genomic reference for mapping RNA-Seq reads from CHO cells has been reported. In previous publications, de novo transcriptomes assembled using these RNA-Seq reads were subsequently used for mapping. Potential caveats with this approach include the incomplete coverage and the non-universal nature of the de novo assemblies, leading to challenges in comparing results across studies. In order to facilitate future RNA-Seq studies in CHO cells, we performed a comprehensive evaluation of four public genomic references for CHO cells hosted by the NCBI Reference Sequence Database (RefSeq), including two annotated genomes released in 2012 and 2014 and their accompanying transcriptomes. Each genome showed significantly higher mapped rates compared to its accompanying transcriptome. Furthermore, higher mapped rates in deep intra-genic regions, especially within exons, were observed for the more recent genome release (2014) compared to the older one (2012), indicating that the 2014 genome was the preeminent reference among the four. Sequential addition of human and mouse genomes increased the total mapped rate to 87.3 and 89.7%, respectively, from 73.5% using the 2014 Chinese hamster genome alone. Thus, the sequential combination of the 2014 RefSeq Chinese hamster genome, the Ensembl human genome (h38), and the Ensembl mouse genome (m38) was suggested as the most effective strategy for mapping RNA-Seq data from CHO cells.

Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling

Eukaryotic cell lines, including Chinese hamster ovary cells, yeast, and insect cells, are invaluable hosts for the production of many recombinant proteins. With the advent of genomic resources, one can now leverage genome-scale computational modeling of cellular pathways to rationally engineer eukaryotic host cells. Genome-scale models of metabolism include all known biochemical reactions occurring in a specific cell. By describing these mathematically and using tools such as flux balance analysis, the models can simulate cell physiology and provide targets for cell engineering that could lead to enhanced cell viability, titer, and productivity. Here we review examples in which metabolic models in eukaryotic cell cultures have been used to rationally select targets for genetic modification, improve cellular metabolic capabilities, design media supplementation, and interpret high-throughput omics data. As more comprehensive models of metabolism and other cellular processes are developed for eukaryotic cell culture, these will enable further exciting developments in cell line engineering, thus accelerating recombinant protein production and biotechnology in the years to come.