bioRxivMolecular BiologyPreprint
Niclosamide targets macrophages to rescue the disrupted peritoneal homeostasis in endometriosis
Liang ZhaoiD, Mingxin ShiiD, Sarayut WinuthayanoniD, James A. MacLeaniD, Kanako HayashiiD
Abstract
Due to the vital roles of macrophages in the pathogenesis of endometriosis, targeting macrophages could be a new therapeutic direction. Here, we investigated the efficacy of niclosamide for the resolution of perturbed microenvironment caused by dysregulated macrophages in a mouse model of endometriosis. Single-cell transcriptomic analysis revealed the heterogeneity of macrophage subpopulations including three newly identified intermediate subtypes with sharing characteristics of traditional "small" or "large" peritoneal macrophages (SPMs and LPMs) in the peritoneal cavity. Endometriosis-like lesions (ELL) enhanced the differentiation of recruited macrophages, promoted the replenishment of resident LPMs, and increased ablation of embryo-derived LPMs, which were stepwise suppressed by niclosamide. In addition, niclosamide reversed intercellular communications between macrophages and B cells which were disrupted by ELL. Therefore, niclosamide rescued the perturbed microenvironment in endometriosis through its fine regulations on the dynamic progression of macrophages and could be a new promising therapy for endometriosis. SummaryNiclosamide tunes the dynamic progression of peritoneal macrophages and their intercellular communications with B cells to rescue the disrupted microenvironment in the peritoneal cavity in a mouse model of endometriosis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/487220v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@e6700eorg.highwire.dtl.DTLVardef@c6c557org.highwire.dtl.DTLVardef@1c60b92org.highwire.dtl.DTLVardef@121bce6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic AbstractC_FLOATNO C_FIG
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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