Exploring the Potential Application of Short Non-Coding RNA-Based Genetic Circuits in Chinese Hamster Ovary Cells

The majority of cell engineering for recombinant protein production to date has relied on traditional genetic engineering strategies, such as gene overexpression and gene knock-outs, to substantially improve the production capabilities of Chinese Hamster Ovary (CHO) cells. However, further improvements in cellular productivity or control over product quality is likely to require more sophisticated rational approaches to coordinate and balance cellular pathways. For these strategies to be implemented, novel molecular tools need to be developed to facilitate more refined control of gene expression. Multiple gene control strategies are developed over the last decades in the field of synthetic biology, including DNA and RNA-based systems, which allows tight and timely control over gene expression. microRNAs has received a lot of attention over the last decade in the CHO field and are used to engineer and improve CHO cells. In this review we focus on microRNA-based gene control systems and discuss their potential use as tools rather than targets in order to gain better control over gene expression.

Improvements in protein production in mammalian cells from targeted metabolic engineering

Bioprocess optimization has yielded powerful clones for biotherapeutic production. However, new genomic technologies allow more targeted approaches to cell line development. Here we review efforts to enhance protein production in mammalian cells through metabolic engineering. Most efforts aimed to reduce toxic byproducts accumulation to enhance protein productivity. However, recent work highlights the possibility of regulating other desirable traits (e.g., apoptosis and glycosylation) by targeting central metabolism since these processes are interconnected. Therefore, as we further detail the pathways underlying cell growth and protein production and deploy diverse algorithms for their analysis, opportunities will arise to move beyond simple cell line designs and facilitate cell engineering strategies with complex combinations of genes that together underlie a phenotype of interest.

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.

Recon 2.2: from reconstruction to model of human metabolism

INTRODUCTION

The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.

OBJECTIVES

We report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.

METHODS

Recon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.

RESULTS

Recon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.

CONCLUSION

Through these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001).

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.

CRISPR/Cas9-mediated genome engineering of CHO cell factories: Application and perspectives

Chinese hamster ovary (CHO) cells are the most widely used production host for therapeutic proteins. With the recent emergence of CHO genome sequences, CHO cell line engineering has taken on a new aspect through targeted genome editing. The bacterial clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system enables rapid, easy and efficient engineering of mammalian genomes. It has a wide range of applications from modification of individual genes to genome-wide screening or regulation of genes. Facile genome editing using CRISPR/Cas9 empowers researchers in the CHO community to elucidate the mechanistic basis behind high level production of proteins and product quality attributes of interest. In this review, we describe the basis of CRISPR/Cas9-mediated genome editing and its application for development of next generation CHO cell factories while highlighting both future perspectives and challenges. As one of the main drivers for the CHO systems biology era, genome engineering with CRISPR/Cas9 will pave the way for rational design of CHO cell factories.

Deep sequencing reveals different compositions of mRNA transcribed from the F8 gene in a panel of FVIII-producing CHO cell lines

Coagulation factor VIII (FVIII) is one of the most complex biopharmaceuticals due to the large size, poor protein stability and extensive post-translational modifications. As a consequence, efficient production of FVIII in mammalian cells poses a major challenge, with typical yields two to three orders of magnitude lower than for antibodies. In the present study we investigated CHO DXB11 cells transfected with a plasmid encoding human coagulation factor VIII. Single cell clones were isolated from the pool of transfectants and a panel of 14 clones representing a dynamic range of FVIII productivities was selected for RNA sequencing analysis. The analysis showed distinct differences in F8 RNA composition between the clones. The exogenous F8-dhfr transcript was found to make up the most abundant transcript in the present clones. No correlation was seen between F8 mRNA levels and the measured FVIII productivity. It was found that three MTX resistant, nonproducing clones had different truncations of the F8 transcripts. We find that by using deep sequencing, in contrast to microarray technology, for determining the transcriptome from CHO transfectants, we are able to accurately deduce the mature mRNA composition of the transgene and identify significant truncations that would probably otherwise have remained undetected.