Reconstruction of context-specific genome-scale metabolic models using multi-omics data to study metabolic rewiring

Abstract Metabolic rewiring or reprogramming is the alteration of metabolism in living organisms, leading to disordered states aberrant from homeostasis. As large amounts of omics data become available, complex mechanisms leading to or driven by metabolic rewiring of cells can be better understood using reconstructed context-specific genome-scale metabolic models (GEMs). Here we review recent advances in reconstructing context-specific GEMs for studying metabolic rewiring of human cells or tissues, from generic GEMs and omics databases to multi-omics data integration methods. Also, we review recent studies that utilize context-specific GEMs to obtain insights such as identifying key regulators or therapeutic targets. Analyses of recent trends indicate the importance of integrating context-specific GEMs with multi-scale networks for understanding metabolic diseases and advancing precision medicine.