Autofluorescence imaging of endogenous metabolic cofactors in response to cytokine stimulation of classically activated macrophages.

利用细胞因子刺激经典激活的巨噬细胞,观察内源性代谢辅因子的自发荧光成像

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作者:Bess Shelby N, Igoe Matthew J, Denison Abby C, Muldoon Timothy J
BACKGROUND: Macrophages are one of the most prevalent subsets of immune cells within the tumor microenvironment and perform a range of functions depending on the cytokines and chemokines released by surrounding cells and tissues. Recent research has revealed that macrophages can exhibit a spectrum of phenotypes, making them highly plastic due to their ability to alter their physiology in response to environmental cues. Recent advances in examining heterogeneous macrophage populations include optical metabolic imaging, such as fluorescence lifetime imaging (FLIM), and multiphoton microscopy. However, the method of detection for these systems is reliant upon the coenzymes NAD(P)H and FAD, which can be affected by factors other than cytoplasmic metabolic changes. In this study, we seek to validate these optical measures of metabolism by comparing optical results to more standard methods of evaluating cellular metabolism, such as extracellular flux assays and the presence of metabolic intermediates. METHODS: Here, we used autofluorescence imaging of endogenous metabolic co-factors via multiphoton microscopy and FLIM in conjunction with oxygen consumption rate and extracellular acidification rate through Seahorse extracellular flux assays to detect changes in cellular metabolism in quiescent and classically activated macrophages in response to cytokine stimulation. RESULTS: Based on our Seahorse XFP flux analysis, M0 and M1 macrophages exhibit comparable trends in oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Autofluorescence imaging of M0 and M1 macrophages was not only able to show acute changes in the optical redox ratio from pre-differentiation (0 hours) to 72 hours post-cytokine differentiation (M0: 0.320 to 0.258 and M1: 0.316 to 0.386), mean NADH lifetime (M0: 1.272 ns to 1.379 ns and M1: 1.265 ns to 1.206 ns), and A1/A2 ratio (M0: 3.452 to ~ 4 and M1: 3.537 to 4.529) but could also detect heterogeneity within each macrophage population. CONCLUSIONS: Overall, the findings of this study suggest that autofluorescence metabolic imaging could be a reliable technique for longitudinal tracking of immune cell metabolism during activation post-cytokine stimulation.

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