Model-driven multi-omic data analysis elucidates metabolic immunomodulators of macrophage activation

ABSTRACT: We used genome-scale modeling and multi-omics (transcriptomics, proteomics, and metabolomics) analysis to assess metabolic features that are critical for macrophage activation. We constructed a genome-scale metabolic network for the RAW 264.7 cell line to determine metabolic modulators of activation. Metabolites well-known to be associated with immunoactivation (glucose and arginine) and immunosuppression (tryptophan and vitamin D3) were among the most critical effectors. Intracellular metabolic mechanisms were assessed, identifying a suppressive role for de-novo nucleotide synthesis. Finally, underlying metabolic mechanisms of macrophage activation are identified by analyzing multi-omic data obtained from LPS-stimulated RAW cells in the context of our flux-based predictions. Two condition

ORGANISM(S): Mus musculus

SUBMITTER: Bryan Frank 

PROVIDER: E-GEOD-39785 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress