Leveraging a comprehensive unbiased RNAseq database to characterize human monocyte-derived macrophage gene expression profiles within commonly employed in vitro polarization methods

Abstract

Abstract Macrophages are pivotal innate immune cells which exhibit high phenotypic plasticity and can exist in different polarization states dependent on exposure to external stimuli. Numerous methods have been employed to simulate macrophage polarization states to test their function in vitro. However, limited research has explored whether these polarization methods yield comparable populations beyond key gene, cytokine, and cell surface marker expression. Here, we employ an unbiased comprehensive analysis using data organized through the all RNA-seq and ChIP-seq sample and signature search (ARCHS4) database, which compiles all RNAseq data deposited into the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In silico analyses were carried out demonstrating that commonly employed macrophage polarization methods generate distinct gene expression profiles in macrophage subsets that remained poorly described until now. Our analyses confirm existing knowledge on broad macrophage polarization, while expanding nuanced differences between M2a and M2c subsets, suggesting non-interchangeable stimuli for M2a polarization. Furthermore, we characterize divergent gene expression patterns in M1 macrophages following standard polarization protocols, indicating significant subset distinctions. Consequently, equivalence cannot be assumed among polarization regimens for in vitro macrophage studies, particularly in simulating diverse pathogen responses.