基因组尺度代谢模型应用于人类健康和生物制药工程

IF 0.6 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Quantitative Biology Pub Date : 2023-11-13 DOI:10.1002/qub2.21
Feiran Li, Yu Chen, Johan Gustafsson, Hao Wang, Yi Wang, Chong Zhang, Xinhui Xing
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引用次数: 0

摘要

在过去的15年里,基因组尺度的代谢模型(GEMs)已经被用于人类和模型动物,如小鼠和大鼠,以系统地了解代谢,模拟多细胞或多组织的相互作用,了解人类疾病,并指导生物制药蛋白生产的细胞工厂设计。在这里,我们描述了如何使用化学计量矩阵和通量模拟的明确约束来表示代谢网络。然后,我们回顾了GEM的发展历史,以定量了解智人和其他相关动物,以及它们的应用。我们描述了模型是如何从H。从智人到其他动物,从通用目的到精确的情境特定模拟。动物GEMs的进展极大地扩展了我们对人类及相关动物代谢的系统认识。我们讨论了GEM发展的困难和目前的观点,并寻求整合更多的生物过程和组学数据,以供未来的研究和翻译。我们真诚地希望这篇综述能够启发其他哺乳动物生物的新模型,并产生新的算法来整合大数据进行更深入的分析,从而进一步在人类健康和生物制药工程方面取得进展。
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Genome‐scale metabolic models applied for human health and biopharmaceutical engineering
Abstract Over 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.
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来源期刊
Quantitative Biology
Quantitative Biology MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
5.00
自引率
3.20%
发文量
264
期刊介绍: Quantitative Biology is an interdisciplinary journal that focuses on original research that uses quantitative approaches and technologies to analyze and integrate biological systems, construct and model engineered life systems, and gain a deeper understanding of the life sciences. It aims to provide a platform for not only the analysis but also the integration and construction of biological systems. It is a quarterly journal seeking to provide an inter- and multi-disciplinary forum for a broad blend of peer-reviewed academic papers in order to promote rapid communication and exchange between scientists in the East and the West. The content of Quantitative Biology will mainly focus on the two broad and related areas: ·bioinformatics and computational biology, which focuses on dealing with information technologies and computational methodologies that can efficiently and accurately manipulate –omics data and transform molecular information into biological knowledge. ·systems and synthetic biology, which focuses on complex interactions in biological systems and the emergent functional properties, and on the design and construction of new biological functions and systems. Its goal is to reflect the significant advances made in quantitatively investigating and modeling both natural and engineered life systems at the molecular and higher levels. The journal particularly encourages original papers that link novel theory with cutting-edge experiments, especially in the newly emerging and multi-disciplinary areas of research. The journal also welcomes high-quality reviews and perspective articles.
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