Integrated Multiomics, Bioinformatics, and Computational Modeling Approaches to Central Metabolism in Organs.
Integrated Multiomics, Bioinformatics, and Computational Modeling Approaches to Central Metabolism in Organs.
复制标题
DOI：
10.1007/978-1-0716-1831-8_7
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
中科院分区：
文献类型：
--
作者：
由计算系统生物学方法主导的数据驱动研究，包括多组学数据集的生物信息学和数学建模，对于发现至关重要。在此，我们描述了应用于糖尿病心脏功能的多组学（代谢组学-通量组学）方法。所提出的方法具有普遍适用性，并且能够对葡萄糖和脂肪酸的中央分解代谢途径中的细胞质和线粒体区室的通量组或一组代谢通量进行量化。此外，我们首次提出了一种减少详细动力学维数的通用方法，以及稳态代谢网络的一般化学计量模型，以促进其优化并避免数值问题。代表性结果说明了可以从这种综合和定量方法中获得的强大的机制见解。
Data-driven research led by computational systems biology methods, encompassing bioinformatics of multi-omics datasets and mathematical modeling, are critical for discovery. Herein, we describe a multi-omics (metabolomics-fluxomics) approach as applied to heart function in diabetes. The methodology presented has general applicability and enables the quantification of the fluxome or set of metabolic fluxes from cytoplasmic and mitochondrial compartments in central catabolic pathways of glucose and fatty acids. Additionally, we present, for the first time, a general method to reduce the dimension of detailed kinetic, and in general stoichiometric models of metabolic networks at the steady state, to facilitate their optimization and avoid numerical problems. Representative results illustrate the powerful mechanistic insights that can be gained from this integrative and quantitative methodology.