Back

Setdb2 Regulates Inflammatory Trigger-Induced Trained Immunity of Macrophages Through Two Different Epigenetic Mechanisms

Jaiswal, A.; Halasz, L.; Williams, D. L.; Osborne, T.

2025-03-19 immunology
10.1101/2025.03.18.644013 bioRxiv
Show abstract

"Trained immunity" of innate immune cells occurs through a sequential two-step process where an initial pathogenic or sterile inflammatory trigger is followed by an amplified response to a later un-related secondary pathogen challenge. The memory effect is mediated at least in part through epigenetic modifications of the chromatin landscape. Here, we investigated the role of the epigenetic modifier Setdb2 in microbial ({beta}-glucan) or sterile trigger (Western-diet-WD/oxidized-LDL-oxLDL)-induced trained immunity of macrophages. Using genetic mouse models and genomic analysis, we uncovered a critical role of Setdb2 in regulating proinflammatory and metabolic pathway reprogramming. We further show that Setdb2 regulates trained immunity through two different complementary mechanisms: one where it positively regulates glycolytic and inflammatory pathway genes via enhancer-promoter looping, and is independent of its enzymatic activity; while the second mechanism is associated with both increased promoter associated H3K9 methylation and repression of interferon response pathway genes. Interestingly, while both mechanisms occur in response to pathogenic training, only the chromatin-looping mechanism operates in response to the sterile inflammatory stimulus. These results reveal a previously unknown bifurcation in the downstream pathways that distinguishes between pathogenic and sterile inflammatory signaling responses associated with the innate immune memory response and may provide potential therapeutic opportunities to target cytokine vs. interferon pathways to limit complications of chronic inflammation.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.