单核细胞
巨噬细胞
鉴定(生物学)
计算生物学
细胞生物学
细胞
化学
生物
免疫学
生物化学
植物
体外
作者
Johanna B. Brüggenthies,Jakob Dittmer,Eva M. Garrido-Martín,Igor Zingman,Ibrahim Tabet,Helga Bronner,Sarah Groetzner,Julia Sauer,Mozhgan Dehghan Harati,Rebekka Scharnowski,J.M.T. de Bakker,Katharina Riegger,Caroline Heinzelmann,Birgit Ast,Robert Ries,Sophie Fillon,Anna Bachmayr-Heyda,Kerstin Kitt,Marc A. Grundl,Ralf Heilker,Lina Humbeck,Michael Schuler,Bernd Weigle
标识
DOI:10.3390/ijms252212330
摘要
Macrophage polarization critically contributes to a multitude of human pathologies. Hence, modulating macrophage polarization is a promising approach with enormous therapeutic potential. Macrophages are characterized by a remarkable functional and phenotypic plasticity, with pro-inflammatory (M1) and anti-inflammatory (M2) states at the extremes of a multidimensional polarization spectrum. Cell morphology is a major indicator for macrophage activation, describing M1(-like) (rounded) and M2(-like) (elongated) states by different cell shapes. Here, we introduced cell painting of macrophages to better reflect their multifaceted plasticity and associated phenotypes beyond the rigid dichotomous M1/M2 classification. Using high-content imaging, we established deep learning- and feature-based cell painting image analysis tools to elucidate cellular fingerprints that inform about subtle phenotypes of human blood monocyte-derived and iPSC-derived macrophages that are characterized as screening surrogate. Moreover, we show that cell painting feature profiling is suitable for identifying inter-donor variance to describe the relevance of the morphology feature ‘cell roundness’ and dissect distinct macrophage polarization signatures after stimulation with known biological or small-molecule modulators of macrophage (re-)polarization. Our novel established AI-fueled cell painting analysis tools provide a resource for high-content-based drug screening and candidate profiling, which set the stage for identifying novel modulators for macrophage (re-)polarization in health and disease.
科研通智能强力驱动
Strongly Powered by AbleSci AI