Driving towards digital biomanufacturing by CHO genome-scale models

Seo-Young Park; Dong-Hyuk Choi; Jinsung Song; Meiyappan Lakshmanan; Anne Richelle; Seongkyu Yoon; Cleo Kontoravdi; Nathan E Lewis; Dong-Yup Lee

doi:10.1016/j.tibtech.2024.03.001

Driving towards digital biomanufacturing by CHO genome-scale models

Trends Biotechnol. 2024 Mar 27:S0167-7799(24)00065-9. doi: 10.1016/j.tibtech.2024.03.001. Online ahead of print.

Authors

Seo-Young Park¹, Dong-Hyuk Choi¹, Jinsung Song¹, Meiyappan Lakshmanan², Anne Richelle³, Seongkyu Yoon⁴, Cleo Kontoravdi⁵, Nathan E Lewis⁶, Dong-Yup Lee⁷

Affiliations

¹ School of Chemical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do 16419, Republic of Korea.
² Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, and Centre for Integrative Biology and Systems Medicine (IBSE), Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India.
³ Sartorius Corporate Research, Avenue Ariane 5, 1200 Brussels, Belgium.
⁴ Department of Chemical Engineering, University of Massachusetts Lowell, Lowell, MA 01850, USA.
⁵ Department of Chemical Engineering and Chemical Technology, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
⁶ Departments of Pediatrics and Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.
⁷ School of Chemical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do 16419, Republic of Korea. Electronic address: dongyuplee@skku.edu.

PMID: 38548556
DOI: 10.1016/j.tibtech.2024.03.001

Abstract

Genome-scale metabolic models (GEMs) of Chinese hamster ovary (CHO) cells are valuable for gaining mechanistic understanding of mammalian cell metabolism and cultures. We provide a comprehensive overview of past and present developments of CHO-GEMs and in silico methods within the flux balance analysis (FBA) framework, focusing on their practical utility in rational cell line development and bioprocess improvements. There are many opportunities for further augmenting the model coverage and establishing integrative models that account for different cellular processes and data for future applications. With supportive collaborative efforts by the research community, we envisage that CHO-GEMs will be crucial for the increasingly digitized and dynamically controlled bioprocessing pipelines, especially because they can be successfully deployed in conjunction with artificial intelligence (AI) and systems engineering algorithms.

Keywords: Chinese hamster ovary cells; bioprocess digital twins; digital biomanufacturing; flux balance analysis; genome-scale metabolic models; recombinant therapeutic proteins.

Publication types

Review