Genome‐scale metabolic models applied for human health and biopharmaceutical engineering

Author:

Li Feiran1,Chen Yu2,Gustafsson Johan3,Wang Hao3,Wang Yi45,Zhang Chong45,Xing Xinhui1456

Affiliation:

1. Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China

2. Key Laboratory of Quantitative Synthetic Biology Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen China

3. Department of Biology and Biological Engineering Chalmers University of Technology Gothenburg Sweden

4. Key Laboratory for Industrial Biocatalysis Ministry of Education, Institute of Biochemical Engineering, Department of Chemical Engineering Tsinghua University Beijing China

5. Center for Synthetic and Systems Biology Tsinghua University Beijing China

6. Institute of Biomedical Health Technology and Engineering Shenzhen Bay Laboratory Shenzhen China

Abstract

AbstractOver the last 15 years, genome‐scale metabolic models (GEMs) have been reconstructed for human and model animals, such as mouse and rat, to systematically understand metabolism, simulate multicellular or multi‐tissue interplay, understand human diseases, and guide cell factory design for biopharmaceutical protein production. Here, we describe how metabolic networks can be represented using stoichiometric matrices and well‐defined constraints for flux simulation. Then, we review the history of GEM development for quantitative understanding of Homo sapiens and other relevant animals, together with their applications. We describe how model develops from H. sapiens to other animals and from generic purpose to precise context‐specific simulation. The progress of GEMs for animals greatly expand our systematic understanding of metabolism in human and related animals. We discuss the difficulties and present perspectives on the GEM development and the quest to integrate more biological processes and omics data for future research and translation. We truly hope that this review can inspire new models developed for other mammalian organisms and generate new algorithms for integrating big data to conduct more in‐depth analysis to further make progress on human health and biopharmaceutical engineering.

Publisher

Wiley

Subject

Applied Mathematics,Computer Science Applications,Biochemistry, Genetics and Molecular Biology (miscellaneous),Modeling and Simulation

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