Single-cell RNA-seq reveals cellular heterogeneity of activated pDCs stimulated by R848
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ABSTRACT:
PROVIDER: PRJNA736062 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14760775.fastq.gz | Fastqsanger.gz |
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Project description:Purpose: PDCs will differentiated into different subclusters upon single stimulation. The goals of this study are to identify the heterogeneity of activated pDCs stimulated by R848. Methods: Human primary plasmacytoid dendritic cells were stimulated with R848 for 16 hours. Then, after FACS sorting, about 12000 pDCs were counted and the viability was confirmed to be >90%. Single-cell suspensions were loaded on a 10x Genomics Chromium single-cell 3’ v2 chip to prepare the libraries according to the manufacturer’s protocol. The library quality was checked by Agilent 2100 Bioanalyzer and Qubit fluorometric quantitation. Samples were sequenced on an Illumina NovaSeq 6000 with a sequencing depth of at least 50000 reads per cell. The raw fastq data were processed with CellRanger (v2.1.1) by using GRCh38 annotation (v1.2.0) (Zheng, G.X., et al.Nat Commun 2017;8,14049.). Output from CellRanger was loaded into R and used Seurat (v3.1.1) for further analysis (Stuart, T., et al. Cell 2019;177,1888-1902 e1821.). Cells with fewer than 1000 or more than 4500 expressed genes, and a high percentage of mitochondrial genes (>5%) were removed. We also used cell selection as Peter Karchenko-the Pagoda way to define outliers. Among them, 6010 cells passed the filtering. After normalizing and scaling, we used ‘Find Variable Features’ to identify 1000 highly variable genes. Then we used 992 highly variable genes (removing mitochondrial and ribosomal genes) for PCA. Upon ‘Elbow plot’, we selected the first 20 PC for clustering and UMAP visualization with default parameters. For clustering, we selected resolution parameter=0.2 which produced 4 clusters. To obtain cluster-specific gene signatures, we identified differential expression analysis of each cluster with default parameters. IFN scores based on IFN gene sets were calculated for each cell as the average of scaled expression of these genes and corrected by subtracting the average of a large set of similar genes, as proposed by Tirosh et al (Tirosh, I., et al. Science 2016;352,189-196.). Results: 4 subcluster of pDCs were obtained.Group 0 express chemokines, group 1 express Gzmb, group 2 express type I interferons, and group 3 express Id2 and IL-23A.
2021-06-09 | GSE176392 | GEO
Project description:To identify chromatic alterations in BMDMs stimulated by R848, we performed ATAC-sequencing. We identified regions of chromatin that were altered in BMDMs stimulated with R848(2 Hours) or not.
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Project description:Two well-characterized blood dendritic cell populations, conventional (cDC) and plasmacytoid (pDC), exhibit multiple phenotypic, migratory and functional differences that suggest specialized and may be complementary and coordinated functions. To study this possible coordination, cDCs and pDCs from healthy blood donors were sorted and cDCs were stimulated either with LPS or R848 whereas pDCs were CFSE-labelled and maintained in IL3. Then, CFSE labelled-pDCs and stimulated-cDCs were mixed and co-cultured. Following this "conditioning", CFSE-pDCs were sorted again and further analyzed. Conditioned pDCs showed moderate phenotypic maturation and acquired allostimulatory capacity. Microarray and RT-PCR analyses showed the induction of different genes including chemokines and proinflammatory cytokines that were dependent on the stimulation received from the "conditioner" cDC. Additionally, the differential pattern of conditioning was confirmed by protein secretion analyses with the production of specific chemokines and cytokines by conditioned pDCs. Importantly, conditioning of pDCs by activated cDCs required cell-cell contact.
2011-01-20 | E-MEXP-2555 | biostudies-arrayexpress
Project description:Apilimod is a reported TLR pathway antagonist in clinical trial. To understand the mode of action of apilimod, we applied global microarray analysis to explore the effect of apilimod on gene expression of RAW cell in the absence of presence of R848 (TLR7 ligand). RAW cells were stimulated with R848 in the absence or presence of apilimod (1μM). mRNAs were extracted at 0h, 1h,3h, 7h, and 22h for affymetrix analysis. The inactive analog of apilimod (API09) was included as a control.
2014-02-18 | E-GEOD-22124 | biostudies-arrayexpress
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2024-08-10 | GSE210395 | GEO
Project description:Systemic sclerosis (SSc) is an uncommon disease characterized by elevated autoantibody production, vasculopathy and fibrosis of the skin and internal organs. pDCs are the core cell type to produce type I IFN and contributes to the ISG signature and SSc progression. Using single-cell RNA sequencing, we profiled 32529 pDCs enriched and T cell depleted peripheral blood mononuclear cells (PBMCs) from 4 patients with SSc and 4 matched controls. Increased CD16+ monocytes and decreased cDCs are the major changes in the cell composition between SSc and heathy controls. Increased expression of interferon-stimulated genes (ISGs) and apoptotic genes distinguished cells from patients with SSc from healthy control cells. The high ISG expression signature (ISGhi) derived from a small number of transcriptionally defined subpopulations within major cell types, including monocytes, natural killer cells, conventional and plasmacytoid dendritic cells, B cells. Profiling of 10976 pDCs revealed a newly identified PTGDS+ population and a clear increased ISG hi clusters in SSc pDCs. Profiling of 13317 Monocytes revealed increased CD16+ Monocytes and a clear increased ISG hi clusters in SSc monocytes. We then compared the TLRs-IFN response of the pDCs from SSc and Healthy control. RNASeq revealed SSc pDCs enables an unexpected TLR8-IFN signaling to increase the IFN signature. This study lays the groundwork for resolving the origin of the SSc transcriptional signatures and the disease heterogeneity towards precision medicine applications.
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Project description:Purpose: Genome-wide identification of genes binding by KAT8, we performed Cleavage Under Targets and Tagmentation (CUT&Tag) analysis of wild-type BMDMs. Methods: Mouse BMDMs were generated from bone marrow cells in RPMI-1640 medium with recombinant mouse M-CSF (20ng/ml). BMDMs were stained to confirm the surface expression of CD11b and F4/80. Cells with purity >97.5% were used for subsequent experiments. WT BMDMs were stimulated with R848 (100ng/ml) for 2 hours or not. Results: We carried out the CUT&Tag assay using antibodies against KAT8, and found the global binding prefernece of KAT8 in activated macrophages.
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Project description:Purpose: Genome-wide identification of genes with H4K16ac, we performed Cleavage Under Targets and Tagmentation (CUT&Tag) analysis of wild-type (WT)and KAT8-deficient BMDMs. Methods: Mouse BMDMs were generated from bone marrow cells in RPMI-1640 medium with recombinant mouse M-CSF (20ng/ml). BMDMs were stained to confirm the surface expression of CD11b and F4/80. Cells with purity >97.5% were used for subsequent experiments. BMDMs were stimulated with R848 (100ng/ml) for 2 hours. Results: We carried out a CUT&Tag assay using antibodies against H4K16ac（CST）, and found the global influence of H4K16ac in regulating genes of transcription regulatory regions of key genes for psoriasis.
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Project description:H4K16ac Cut&Tag profiling of Bone Marrow Derived macrophage stimulated with R848
| PRJNA1095979 | ENA
Project description:ATAC-seq to profile the chromatin accessibility of BMDMs stimulated with R848
| PRJNA1095977 | ENA