Metabolic characterisation of THP-1 macrophage polarisation using LC–MS-based metabolite profiling

Abstract

Introduction Macrophages constitute a heterogeneous population of functionally distinct cells involved in several physiological and pathological processes. They display remarkable plasticity by changing their phenotype and function in response to environmental cues representing a spectrum of different functional phenotypes. The so-called M1 and M2 macrophages are often considered as representative of pro-and anti-inflammatory ends of such spectrum. Metabolomics approach is a powerful tool providing important chemical information about the cellular phenotype of living systems, and the changes in their metabolic pathways in response to various perturbations. Objectives This study aimed to characterise M1 and M2 phenotypes in THP-1 macrophages in order to identify characteristic metabolites of each polarisation state. Methods Herein, untargeted liquid chromatography (LC)-mass spectrometry (MS)-based metabolite profiling was applied to characterise the metabolic profile of M1-like and M2-like THP-1 macrophages. Results The results showed that M1 and M2 macrophages have distinct metabolic profiles. Sphingolipid and pyrimidine metabolism was significantly changed in M1 macrophages whereas arginine, proline, alanine, aspartate and glutamate metabolism was significantly altered in M2 macrophages. Conclusion This study represents successful application of LC-MS metabolomics approach to characterise M1 and M2 macrophages providing functional readouts that show unique metabolic signature for each phenotype. These data could contribute to a better understanding of M1 and M2 functional properties and could pave the way for developing new therapeutics targeting different immune diseases.

The Janus-like role of proline metabolism in cancer

“…M2 cells influence multiple features of tumor development, including cell survival, proliferation, stemness, and invasiveness along with angiogenesis and immune evasion 167 . M2 polarized macrophages display an intense rewiring of NEAA metabolism, including arginine-glutamine-proline metabolism 165 . As previously discussed, the mitochondrial chaperon Lon interacts with PYCR1 in cancer cells to increase intracellular ROS production and activate a p38-NF-kB signaling axis 125 .…”

“…However, proline metabolism can also influence non-tumor cells within the stroma. Indeed, the transcription factor c-Myc triggers expression of PYCR1 and ALDH18A1 in activated T lymphocytes, and there is evidence that proline metabolism contributes to the reprogramming of tumor-infiltrating macrophages 125 , 165 , 166 . Two major molecular subtypes of macrophages populate the TME; M1 macrophages are very effective antigen-presenting cells and support anti-tumor immune response, whereas the alternative M2 phenotype exhibits anti-inflammatory and pro-tumorigenic activity.…”

Macrophage Plasticity in Reproduction and Environmental Influences on Their Function

“…Thus in M1 macrophages, aerobic glycolysis is recognized as a crucial metabolic event with inhibition of glycolysis affecting pro-inflammatory functions such as phagocytosis and cytokine release ( 27 , 28 ). A high proportion of glycolysis-derived carbon is shunted into the pentose phosphate pathway to produce biosynthetic precursors required for nucleotide synthesis (pentose sugars and ribose-5-phosphate), and nicotinamide adenine dinucleotide phosphate (NADPH) which is required for reductive biosynthesis reactions and as a substrate for NADPH oxidase (NOX2) to generate ROS as part of their anti-microbial response ( 29 , 30 ).…”

Metabolic characterisation ofMagnetospirillum gryphiswaldenseMSR-1 using LC-MS-based metabolite profiling

“…Metabolomics using liquid chromatography-mass spectrometry (LC-MS) has the potential to provide an insight into cell metabolism and metabolic pathways. 16,17 For instance, LC-MS was successfully used to monitor the intracellular metabolites of Clostridium autoethanogenum during gas fermentation, which enabled the optimisation of biofuel production using computational modelling. 18 In addition, the growth medium analysis of bacterial cells using LC-MS provides comprehensive metabolic information which enables the study of the microenvironmental changes caused by the microbial activities under different culture conditions.…”