Mammalian systems biotechnology: An integrative framework for combining in silico modeling and multi-Omics datasets in different CHO parental cell lines

摘要

The increasing availability of multi-omics data from Chinese hamster ovary (CHO) cell cultures entails both opportunity and challenges toward next generation cell culture engineering. Herein, we present a comprehensive and integrative framework to systematically combine trancriptome, proteome, metabolome and glycome datasets in conjunction with a genome-scale metabolic model of CHO cells. We then apply the framework to compare and contrast the metabolic characteristics of the three commonly used parental cell lines (CHO-K1, CHO-DUKXB11 and CHO-DG44) so that "global" attributes of the parental hosts (e.g. growth related characteristics, glycosylation patterns, etc.) could be highlighted (Figure 1).