Getting everyone to agree on gene signatures for murine macrophage polarization in vitro

Abstract

Macrophages, key players in the innate immune system, showcase remarkable adaptability. Derived from monocytes, these phagocytic cells excel in engulfing and digesting pathogens and foreign substances as well as contributing to antigen presentation, initiating and regulating adaptive immunity. Macrophages are highly plastic, and the microenvironment can shaper their phenotype leading to numerous distinct polarized subsets, exemplified by the two ends of the spectrum: M1 (classical activation, inflammatory) and M2 (alternative activation, anti-inflammatory). RNA sequencing (RNA-Seq) has revolutionized molecular biology, offering a comprehensive view of transcriptomes. Unlike microarrays, RNA-Seq detects known and novel transcripts, alternative splicing, and rare transcripts, providing a deeper understanding of genome complexity. Despite the decreasing costs of RNA-Seq, data consolidation remains limited, hindering noise reduction and the identification of authentic signatures. Macrophages polarization is routinely ascertained by qPCR to evaluate those genes known to be characteristic of M1 or M2 skewing. Yet, the choice of these genes is literature- and experience-based, lacking therefore a systematic approach. This manuscript builds on the significant increase in deposited RNA-Seq datasets to determine an unbiased and robust murine M1 and M2 polarization profile. We now provide a consolidated list of global M1 differentially expressed genes (i.e. robustly modulated by IFN-γ, LPS, and LPS+ IFN-γ) as well as consolidated lists of genes modulated by each stimulus (IFN-γ, LPS, LPS+ IFN-γ, and IL-4).