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Multi-omic characterization of antibody-producing CHO cell lines elucidates metabolic reprogramming and nutrient uptake bottlenecks
Metabolic Engineering ( IF 6.8 ) Pub Date : 2024-07-22 , DOI: 10.1016/j.ymben.2024.07.009 Saratram Gopalakrishnan 1 , William Johnson 2 , Miguel A Valderrama-Gomez 2 , Elcin Icten 2 , Jasmine Tat 3 , Fides Lay 2 , Jonathan Diep 2 , Natalia Gomez 2 , Jennitte Stevens 2 , Fabrice Schlegel 2 , Pablo Rolandi 2 , Cleo Kontoravdi 4 , Nathan E Lewis 5
Metabolic Engineering ( IF 6.8 ) Pub Date : 2024-07-22 , DOI: 10.1016/j.ymben.2024.07.009 Saratram Gopalakrishnan 1 , William Johnson 2 , Miguel A Valderrama-Gomez 2 , Elcin Icten 2 , Jasmine Tat 3 , Fides Lay 2 , Jonathan Diep 2 , Natalia Gomez 2 , Jennitte Stevens 2 , Fabrice Schlegel 2 , Pablo Rolandi 2 , Cleo Kontoravdi 4 , Nathan E Lewis 5
Affiliation
Characterizing the phenotypic diversity and metabolic capabilities of industrially relevant manufacturing cell lines is critical to bioprocess optimization and cell line development. Metabolic capabilities of production hosts limit nutrient and resource channeling into desired cellular processes and can have a profound impact on productivity. These limitations cannot be directly inferred from measured data such as spent media concentrations or transcriptomics. Here, we present an integrated multi-omic analysis pipeline combining exo-metabolomics, transcriptomics, and genome-scale metabolic network analysis and apply it to three antibody-producing Chinese Hamster Ovary cell lines to identify reprogramming features associated with high-producing clones and metabolic bottlenecks limiting product formation in an industrial bioprocess. Analysis of individual datatypes revealed a decreased nitrogenous byproduct secretion in high-producing clones and the topological changes in peripheral metabolic pathway expression associated with phase shifts. An integrated omics analysis in the context of the genome-scale metabolic model elucidated the differences in central metabolism and identified amino acid utilization bottlenecks limiting cell growth and antibody production that were not evident from exo-metabolomics or transcriptomics alone. Thus, we demonstrate the utility of a multi-omics characterization in providing an in-depth understanding of cellular metabolism, which is critical to efforts in cell engineering and bioprocess optimization.
更新日期：2024-07-22
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