Computational modelling of genome-scale metabolic networks and its application to CHO cell cultures

作者：Rejc Ziva; Magdevska Lidija; Trselic Tilen; Osolin Timotej; Vodopivec Rok; Mraz Jakob; Pavliha Eva; Zimic Nikolaj; Cvitanovic Tanja; Rozman Damjana; Moskon Miha^*; Mraz Miha

来源：Computers in Biology and Medicine, 2017, 88: 150-160.

DOI：10.1016/j.compbiomed.2017.07.005

• Metabolic networks
• Genome-scale metabolic models
• Chinese hamster ovary cells
• Flux balance analysis
• Modelling and analysis

Genome-scale metabolic models (GEMs) have become increasingly important in recent years. Currently, GEMs are the most accurate in silico representation of the genotype-phenotype link. They allow us to study complex networks from the systems perspective. Their application may drastically reduce the amount of experimental and clinical work, improve diagnostic tools and increase our understanding of complex biological phenomena. GEMs have also demonstrated high potential for the optimisation of bio-based production of recombinant proteins. Herein, we review the basic concepts, methods, resources and software tools used for the reconstruction and application of GEMs. We overview the evolution of the modelling efforts devoted to the metabolism of Chinese Hamster Ovary (CHO) cells. We present a case study on CHO cell metabolism under different amino acid depletions. This leads us to the identification of the most influential as well as essential amino acids in selected CHO cell lines.

• 出版日期2017-9-1