Integrating Multi-Omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulatory, and Metabolic Pathways.

Alteration of the status of the metabolic enzymes could be a probable way to regulate metabolic reprogramming, which is a critical cellular adaptation mechanism especially for cancer cells. Coordination among biological pathways, such as gene-regulatory, signaling, and metabolic pathways is crucial for regulating metabolic adaptation. Also, incorporation of resident microbial metabolic potential in human body can influence the interplay between the microbiome and the systemic or tissue metabolic environments. Systemic framework for model-based integration of multi-omics data can ultimately improve our understanding of metabolic reprogramming at holistic level. However, the interconnectivity and novel meta-pathway regulatory mechanisms are relatively lesser explored and understood. Hence, we propose a computational protocol that utilizes multi-omics data to identify probable cross-pathway regulatory and protein-protein interaction (PPI) links connecting signaling proteins or transcription factors or miRNAs to metabolic enzymes and their metabolites using network analysis and mathematical modeling. These cross-pathway links were shown to play important roles in metabolic reprogramming in cancer scenarios.