Integrated metabolic-transcriptomic network identifies immunometabolic modulations in human macrophages

Abstract

Summary: Macrophages exhibit diverse phenotypes and respond flexibly to environmental cues through metabolic remodeling. In this study, we present a comprehensive multi-omics dataset integrating intra- and extracellular metabolomes with transcriptomic data to investigate the metabolic impact on human macrophage function. Our analysis establishes a metabolite-gene correlation network that characterizes macrophage activation. We find that the concurrent inhibition of tryptophan catabolism by IDO1 and IL4I1 inhibitors suppresses the macrophage pro-inflammatory response, whereas single inhibition leads to pro-inflammatory activation. We find that a subset of anti-inflammatory macrophages activated by Fc receptor signaling promotes glycolysis, challenging the conventional concept of reduced glycolysis preference in anti-inflammatory macrophages. We demonstrate that cholesterol accumulation suppresses macrophage IFN-γ responses. Our integrated network enables the discovery of immunometabolic features, provides insights into macrophage functional metabolic reprogramming, and offers valuable resources for researchers exploring macrophage immunometabolic characteristics and potential therapeutic targets for immune-related disorders.

Keywords

• CP: Immunology
• CP: Metabolism