Safak Yilmaz, Xuhang Li, Shivani Nanda, Albertha J. M. Walhout University of Massachusetts Chan Medical School
A metabolic network is the system of biochemical reactions that take place in an organism. The structure of this network is dictated by the nutrients in the diet and the metabolic genes in the genome, which encode enzymes and transporters. Cells have different metabolic states that can be described as flux distributions over the metabolic network. The metabolic state of a cell is tightly regulated depending on cell type, life stage, and environmental conditions, including nutritional input and stress. Understanding the network structure, function, and regulation of metabolism is critical for preventing or curing metabolic diseases.
We study the transcriptional regulation of metabolism at systems level using the nematode Caenorhabditis elegans as a model organism. We developed a genome-scale metabolic network model of C. elegans, iCEL1314, based on 1314 annotated metabolic genes. We asked how much of metabolism is under transcriptional control. To answer this question, we analyzed metabolic gene expression during development, across tissues, and with different diets. We developed a novel computational pipeline called MERGE (Metabolic models Reconciled with Gene Expression) to integrate metabolic gene expression with iCEL1314, which resulted in numerous predictions about metabolic functions in different tissues.
Overall, our studies show that metabolism is greatly regulated by enzyme abundance, and that differential metabolic gene expression can be used to predict metabolic phenotypes when combined with the metabolic network context.
Support or Funding Information National Institutes of Health GM122502, DK115690 and DK068429
