bioRxivImmunology
Endotoxin Tolerance Induced by Different TLR Ligands
Abstract
Endotoxin tolerance is a long-recognised property of macrophages that leads to an altered response to repeated or chronic exposure to Toll-like receptor (TLR) ligands. The physiological role of tolerance is to limit the potential damage to host tissue that may otherwise result from prolonged production of pro-inflammatory cytokines. Endotoxin tolerance is induced by all TLRs tested to date, however, tolerance induced by the TLR4 ligand lipopolysaccharide (LPS) is by far the best studied. LPS tolerance involves a global transcriptional shift from a pro-inflammatory response toward one characterised by the expression of anti-inflammatory and pro-resolution factors. Although largely reversible, LPS-tolerance leads to a hybrid macrophage activation state that is pro-inflammatory in nature but possesses distinct regulatory anti-inflammatory features. Remarkably, a comparative transcriptomic analysis of tolerance induced by different TLR ligands has not previously been reported. Here we describe the transcriptomic profiles of mouse macrophages tolerised with ligands for TLR2, TLR3, TLR4 and TLR 9. While we identified TLR-specific transcriptional profiles in macrophages tolerised with each ligand, tolerance induced by TLR4 was the most comprehensive state, such that each gene tolerised by any of the TLRs tested was also found to be tolerised by TLR4. Pro-inflammatory cytokines are not universally supressed in all tolerant cells but distinct patterns of cytokine expression distinguished TLR-specific tolerance. Analysis of gene regulatory regions revealed specific DNA sequence motifs associated with distinct states of TLR tolerance, implicating previously identified as well as novel transcriptional regulators of tolerance in macrophages. These data provide a basis for the future exploitation of TLR-specific tolerant states to achieve therapeutic re-programming of the innate immune response.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
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