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

Abstract

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.

Cell culture media for recombinant protein expression in Chinese hamster ovary (CHO) cells: History, key components, and optimization strategies

“…Furthermore, the authors developed cell line specific models for CHO‐K1, CHO‐S, and CHO‐DG44 lineages by incorporating transcriptomic, metabolomic, and proteomic data for each cell line with the genome scale metabolic model . With the continued advancement of omics‐enabling molecular and analytical technologies, models such as these can be improved further through incorporation of glycomic, proteomic, and epigenomic data to model product quality and cell line stability as well as metabolic levers to control growth and productivity through media development for a given CHO cell line . Application of these types of advanced analyses to development of a CHO cell process can potentially enable highly specialized media development, tailored to a specific cell line based on its own unique “multiomic” profile.…”

“…While genomic and metabolomic approaches have already demonstrated utility in improving CHO cell culture processes, greater advances may be realized by integration of these techniques along with other "omics" analyses, including proteomics, glycomics, epigenomics, fluxomics, lipidomics, and transcriptomics, to build more complete mechanistic models. 209 A very large study with academic and industrial contributors from multiple countries has developed a genome-scale metabolic model of the CHO cell, and demonstrated its utility for optimizing growth and productivity, and for determining useful targets for genetic engineering to improve recombinant protein expression and secretion. 210 Furthermore, the authors developed cell line specific models for CHO-K1, CHO-S, and CHO-DG44 lineages by incorporating transcriptomic, metabolomic, and proteomic data for each cell line with the genome scale metabolic model.…”

CHOmics: a web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines

“…Conventionally, cell line and cell culture process development are mostly based on empirical knowledge and statistical designs, and investigation of product quality deviation to identify the root cause often requires tremendous resources and time. More recently, omics and systems biology approaches have shown the potential to facilitate identification of predictive markers and the molecular mechanisms associated with various bioprocess phenotypes [1][2][3]. There are different omics technologies, each focused on a different biological question.…”

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

“…prerequisite of targeted and fine-tuned genetic engineering is the availability of the genomic sequence of the host as well as the expression level of endogenous proteins and their function(Blattner et al, 1997;Jin et al, 2017;Kim, Rai, Zorraquino, & Tagkopoulos, 2016;Nandakumar et al, 2017;Rupp et al, 2018;Sturmberger et al, 2016). Therefore, the rapid improvements in next-generation sequencing (NGS) techniques(Goodwin, McPherson, & McCombie, 2016) and data generation via different omics approaches that span all cellular levels from genome, epigenome, transcriptome, proteome, and reactome, are the foundation for cell line editing to achieve optimal posttranslational modulation of biopharmaceuticals(Brunk et al, 2016;Feichtinger et al, 2016;Stolfa et al, 2018). Classical engineering strategies rely on the overexpression (OE) or disruption of individual enzymes and proteins in pathways that have been shown to mediate naturally occurring PTMs(Chen et al, 2010;Shcherbakova, Lanzov, Ogawa, & Filatov, 2000;Zhao & McAlister-Henn, 1996).…”