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Published on: December 4, 2021
Metabolite coupling analysis and metabolite-flux coupling analysis of genome-scale metabolic models
1Department of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, WI, United States.
Background:
Genome-scale metabolic models (GEMs) provide detailed representations of metabolic networks. Flux Coupling Analysis (FCA) is widely used for analyzing dependencies between reaction fluxes in GEMs.
Results:
We introduce Metabolite Coupling Analysis (MCA) and Metabolite-flux Coupling Analysis (MetFCA), two methods that extend FCA concepts from reactions to metabolites and metabolite-reaction pairs, enabling the identification of condition-specific modules for omics (e.g., transcriptomics, proteomics, and metabolomics) data analysis.
Conclusion:
MCA and MetFCA, together with FCA, provide a unified framework for generating condition-specific modules in GEMs. These modules exhibit clearer biological functions than those generated by statistical, data-driven approaches. A case study demonstrates the use of gene modules to analyze transcriptomics data in the influenza-infected Calu-3 cell line.
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