Identification of a NUAK1/2 Inhibitor as a Macrophage-Polarizing Compound by a Machine Learning-Based Phenotypic Cell Painting Screen.

Disease-associated macrophage states contribute to the pathogenesis of numerous inflammatory disorders. While small molecule-mediated macrophage repolarization represents a promising strategy to restore homeostasis, current approaches often rely on predefined molecular markers and may therefore overlook previously unrecognized modulators of macrophage plasticity. To address this limitation, we performed a phenotypic high-content cell painting screen in induced pluripotent stem cell-derived and blood monocyte-derived macrophages. Using our previously established machine learning-based cell painting analysis pipeline, we screened the annotated opnMe and JUMP-CP compound libraries and identified 26 compounds that induced M1- or M2-like polarization phenotypes. Among these hits, we identified WZ4003, an inhibitor of AMPK-related kinases NUAK1 and NUAK2, as novel macrophage-polarizing compound. Combining cell painting feature profiling with functional analyses, we revealed that the NUAK1/2 inhibitor WZ4003 induces a distinct macrophage state characterized by a rounded M1-like morphology, ferroptosis protection, mitochondrial reactive oxygen species increase, antioxidative adaptation, and phagocytosis and efferocytosis impairment. These findings link specific morphological signatures to functional macrophage states. Overall, this study provides a resource of macrophage-polarizing compounds and demonstrates the utility of machine learning-based cell painting for identifying novel modulators of macrophage polarization states.