McGarrity Sarah, Karvelsson Sigurður T, Sigurjónsson Ólafur E, Rolfsson Óttar
School of Science and Engineering, Reykjavik University, Reykjavik, Iceland.
Center for Systems Biology, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
Methods Mol Biol. 2020;2088:223-269. doi: 10.1007/978-1-0716-0159-4_11.
Metabolic network flux analysis uses genome-scale metabolic reconstructions to integrate transcriptomics, proteomics, and/or metabolomics data to allow for comprehensive interpretation of genotype to metabolic phenotype relationships. The compilation of many Constraint-based model analysis methods into one MATLAB package, the COBRAtoolbox, has opened the possibility of using these methods to the many biologists with some knowledge of the commonly used statistical program, MATLAB. Here we outline the steps required to take a published genome-scale metabolic reconstruction and interrogate its consistency and biological feasibility. Subsequently, we demonstrate how mRNA expression data and metabolomics data, relating to one or more cell types or biological contexts, can be applied to constrain and generate metabolic models descriptive of metabolic flux phenotypes. Finally, we describe the comparison of the resulting models and model outputs with the aim of identifying metabolic biomarkers and changes in cellular metabolism.
代谢网络通量分析利用基因组规模的代谢重建来整合转录组学、蛋白质组学和/或代谢组学数据，以便全面解读基因型与代谢表型之间的关系。将许多基于约束的模型分析方法整合到一个MATLAB软件包COBRAtoolbox中，这使得有一定常用统计程序MATLAB知识的众多生物学家能够使用这些方法。在这里，我们概述了获取已发表的基因组规模代谢重建并探究其一致性和生物学可行性所需的步骤。随后，我们展示了如何将与一种或多种细胞类型或生物学背景相关的mRNA表达数据和代谢组学数据应用于约束和生成描述代谢通量表型的代谢模型。最后，我们描述了对所得模型和模型输出进行比较，目的是识别代谢生物标志物和细胞代谢变化。
