Abstract
Adipose tissue macrophages (ATMs) critically influence obesity-induced inflammation and metabolic dysfunction. Recent studies identified distinct ATM subsets characterized by markers such as CD11c, CD9, and Trem2, associated with pro-inflammatory and metabolically activated states. This protocol outlines a detailed, reproducible methodology for isolating, characterizing, and sorting these ATM subsets from murine epididymal white adipose tissue (eWAT) using multicolor flow cytometry. Key steps include stromal vascular fraction (SVF) isolation, immunophenotyping, sequential gating strategies, and fluorescence-activated cell sorting (FACS) for downstream gene expression analysis. The protocol was validated in diet-induced obese (DIO) mice treated with the IRE1 RNase inhibitor STF-083010, demonstrating its utility for studying ATMs in the context of obesity and metabolic disease. Key features • Detailed isolation and identification of multiple ATM subsets from eWAT. • Compatible with comprehensive flow cytometric analyses and fluorescence-activated cell sorting (FACS). • Facilitates downstream gene expression profiling from sorted ATM subsets. • Validated using a metabolic intervention (IRE1 RNase inhibitor STF-083010) in a mouse obesity model.