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Driving towards digital biomanufacturing by CHO genome-scale models
Seo-Young Park1, Dong-Hyuk Choi1, Jinsung Song1
1School of Chemical Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do 16419, Republic of Korea.
Trends in Biotechnology
|March 28, 2024
Summary
Genome-scale metabolic models (GEMs) for Chinese hamster ovary (CHO) cells offer insights into cell metabolism and bioprocessing. Future integrated models, combined with AI, will advance biomanufacturing.
Area of Science:
- Biotechnology
- Metabolic Engineering
- Systems Biology
Background:
- Chinese hamster ovary (CHO) cells are critical for biopharmaceutical production.
- Genome-scale metabolic models (GEMs) provide a framework for understanding cellular metabolism.
Purpose of the Study:
- To provide a comprehensive overview of CHO cell GEMs and their applications.
- To highlight opportunities for improving and integrating CHO cell models.
- To discuss the role of CHO GEMs in advancing bioprocessing.
Main Methods:
- Review of existing literature on CHO GEMs.
- Analysis of flux balance analysis (FBA) methods.
- Discussion of in silico approaches for bioprocess optimization.
Main Results:
- CHO GEMs have evolved significantly, offering mechanistic insights into CHO cell metabolism.
- Current models facilitate rational cell line development and bioprocess improvements.
- Integration of diverse cellular processes and data can further enhance model utility.
Conclusions:
- CHO GEMs are essential tools for understanding and optimizing mammalian cell culture.
- Future developments should focus on integrative models and community collaboration.
- CHO GEMs, coupled with AI and systems engineering, will be vital for future bioprocessing pipelines.
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