TY - JOUR TI - Non-invasive classification of macrophage polarisation by 2P-FLIM and machine learning AU - Neto, Nuno GB AU - O'Rourke, Sinead A AU - Zhang, Mimi AU - Fitzgerald, Hannah K AU - Dunne, Aisling AU - Monaghan, Michael G A2 - Dustin, Michael L A2 - Walczak, Aleksandra M A2 - Dustin, Michael L A2 - Padilla-Parra, Sergi VL - 11 PY - 2022 DA - 2022/10/18 SP - e77373 C1 - eLife 2022;11:e77373 DO - 10.7554/eLife.77373 UR - https://doi.org/10.7554/eLife.77373 AB - In this study, we utilise fluorescence lifetime imaging of NAD(P)H-based cellular autofluorescence as a non-invasive modality to classify two contrasting states of human macrophages by proxy of their governing metabolic state. Macrophages derived from human blood-circulating monocytes were polarised using established protocols and metabolically challenged using small molecules to validate their responding metabolic actions in extracellular acidification and oxygen consumption. Large field-of-view images of individual polarised macrophages were obtained using fluorescence lifetime imaging microscopy (FLIM). These were challenged in real time with small-molecule perturbations of metabolism during imaging. We uncovered FLIM parameters that are pronounced under the action of carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP), which strongly stratifies the phenotype of polarised human macrophages; however, this performance is impacted by donor variability when analysing the data at a single-cell level. The stratification and parameters emanating from a full field-of-view and single-cell FLIM approach serve as the basis for machine learning models. Applying a random forests model, we identify three strongly governing FLIM parameters, achieving an area under the receiver operating characteristics curve (ROC-AUC) value of 0.944 and out-of-bag (OBB) error rate of 16.67% when classifying human macrophages in a full field-of-view image. To conclude, 2P-FLIM with the integration of machine learning models is showed to be a powerful technique for analysis of both human macrophage metabolism and polarisation at full FoV and single-cell level. KW - FLIM KW - multiphoton KW - macrophages KW - cellular metabolism KW - machine learning JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -