A Comprehensive High-Efficiency Protocol for Isolation, Culture, Polarization, and Glycolytic Characterization of...

Macrophages are among the most important antigen-presenting cells. Many subsets of macrophages have been identified with unique metabolic signatures. Macrophages are commonly classified as M1-like (inflammatory) and M2-like (anti-inflammatory) subtypes. M1-like macrophages are pro-inflammatory macrophages that get activated by LPS and/or pro-inflammatory cytokines such as INF-γ, IL-12 & IL-2. M1-like polarized macrophages are involved in various diseases by mediating the host's defense to a variety of bacteria and viruses. That is very important to study LPS induced M1-like macrophages and their metabolic states in inflammatory diseases. M2-like macrophages are considered anti-inflammatory macrophages, activated by anti-inflammatory cytokines and stimulators. Under the pro-inflammatory state, macrophages show increased glycolysis in glycolytic function. The glycolytic function has been actively investigated in the context of glycolysis, glycolytic capacity, glycolytic reserve, compensatory glycolysis, or non-glycolytic acidification using extracellular flux (XF) analyzers. This paper demonstrates how to assess the glycolytic states in real-time with easy-to-follow steps when the bone marrow-derived macrophages (BMDMs) are respiring, consuming, and producing energy. Using specific inhibitors and activators of glycolysis in this protocol, we show how to obtain a systemic and complete view of glycolytic metabolic processes in the cells and provide more accurate and realistic results. To be able to measure multiple glycolytic phenotypes, we provide an easy, sensitive, DNA-based normalization method for polarization assessment of BMDMs. Culturing, activation/polarization and identification of the phenotype and metabolic state of the BMDMs are crucial techniques that can help to investigate many different types of diseases. In this paper, we polarized the naïve M0 macrophages to M1-like and M2-like macrophages with LPS and IL4, respectively, and measured a comprehensive set of glycolytic parameters in BMDMs in real-time and longitudinally over time, using extracellular flux analysis and glycolytic activators and inhibitors.