GSE202333
Chemokines form nanoparticles with DNA and can superinduce TLR-driven immune inflammation
Chemokines are chemotactic cytokines that control the migratory patterns and positioning of immune cells. Many chemokines have been associated with systemic autoimmune diseases that have chronic IFN signature. We now describe that a series of chemokines, including CXCL4, CXCL10, CXCL12 and CCL5, can superinduce type I IFN (IFN-I) by TLR9-activated plasmacytoid DCs (pDCs), independently of their respective known chemokine receptors. Mechanistically, we show that chemokines such as CXCL4 mediate transcriptional and epigenetic changes in pDCs, mostly targeted to the IFN-I pathways. We also describe that chemokines physically interact with DNA to form nanoparticles which promote clathrin-mediated cellular uptake and delivery of DNA in the early endosomes of pDCs. Using two mouse models of skin inflammation, we observed the presence of CXCL4 associated with DNA in vivo. These data thus reveal a non-canonical role for chemokines to modulate TLR signaling, and extend our understanding on the mechanism associated with the chronic expression of IFN-I by pDCs in autoimmune diseases. Overall design: One hundred thousand purified pDCs were cultured in 96 U-bottom well plate with medium, CXCL4 (10µg/ml), CpG (0.25µM) alone or with CXCL4 (10µg/ml) for 6h. Total RNA was isolated using RNeasy Plus Mini kit. SMART-Seq v3 Ultra Low Input RNA Kit (Clontech) followed by Nextera library preparation were used to prepare Illumina-compatible sequencing libraries. Quality of all RNA were evaluated with BioAnalyser 2100 (Agilent). Single-end reads were obtained on an Illumina HiSeq 2500 in the Weill Cornell Epigenomics Core Facility at the depth of 21-37 million fragments per sample. Sequencing quality was measured with fastp (Chen et al., 2018). Reads were then mapped reads in genes counted against the human genome (hg38) with STAR aligner and Gencode v21(Dobin et al., 2013; Frankish et al., 2019). Differential gene expression analysis was performed in R(Team, 2020) using the edgeR package (Robinson et al., 2010).