Single-cell RNA-sequencing of CD14+ monocyte differentiation with M-CSF stimulus
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ABSTRACT:
PROVIDER: PRJNA520990 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8530150_1.fastq.gz | Fastqsanger.gz | |||
| SRR8530150_2.fastq.gz | Fastqsanger.gz | |||
| SRR8530151_1.fastq.gz | Fastqsanger.gz | |||
| SRR8530151_2.fastq.gz | Fastqsanger.gz | |||
| SRR8530152_1.fastq.gz | Fastqsanger.gz |
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Project description:We obtained single-cell RNA-sequencing (scRNA-seq) profiles of CD14+ monocytes isolated from human peripheral blood at 0, 3 and 6 days after M-CSF stimulation (to differentiate the cells into macrophages) across multiple donors. Integration of single-cell RNA sequencing (scRNA-seq) data from multiple experiments, laboratories, and technologies can uncover biological insights, but current methods for scRNA-seq data integration are limited by a requirement for datasets to derive from functionally similar cells. We use a novel algorithm, Scanorama, to identify and merge the shared cell types among all pairs of datasets and to accurately integrate heterogeneous scRNA-seq datasets. Scanorama is sensitive to subtle temporal changes within the same cell lineage, successfully integrating functionally similar cells across time series data of CD14+ monocytes at different stages of differentiation into macrophages. Scanorama is not only able to differentiate between completely disparate cell types but is also sensitive to subtler transcriptional changes within a cell type due to processes like stimulation.
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Project description:Identification of genes differentially expressed between human CD14+CD16- and CD16+ monocyte-derived macrophages generated in the presence of either GM-CSF (termed GM14 and GM16, respectively) or M-CSF (termed M14 and M16, respectively) Human peripheral CD14+CD16- and CD16+ blood monocytes from three independent healthy donors (D1, D2 and D3) were isolated by positive selection from peripheral blood mononuclear cells (PBMC) using magnetic separation systems (MACS, Miltenyi Biotec). Briefly, PBMC were first incubated with MACS anti-CD56 antibody conjugated to paramagnetic microbeads in order to eliminate the NK (CD16+) cell fraction. NK-depleted PBMC were further incubated with MACS anti-CD16 antibody to isolate CD16+ monocytes. CD56-CD16- PBMC were finally incubated with MACS anti-CD14 antibody to obtain the CD14+CD16- monocyte fraction. Monocytes were cultured for 7 days in medium containing either GM-CSF or M-CSF. Total RNA from each condition was extracted using the RNeasy kit (Qiagen) and hybridized to an Agilent Human Whole Genome (4x44) Oligo Microarray. All experimental procedures were performed following manufacturer instructions.
2015-04-21 | E-GEOD-68061 | biostudies-arrayexpress
Project description:Identification of genes differentially expressed between human CD14+CD16- and CD16+ monocyte-derived macrophages generated in the presence of either GM-CSF (termed GM14 and GM16, respectively) or M-CSF (termed M14 and M16, respectively)
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Project description:Comparison of the transcriptome of CD14+ human monocytes and CD14+ human monocyte-derived macrophages generated in the presence of M-CSF (M-MØ) or GM-CSF (GM-MØ).
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Project description:Identification of genes differentially expressed between human monocyte-macrophages generated in the presence of either GM-CSF (termed M1) or M-CSF (termed M2) Human peripheral blood monocytes from three independent healthy donors (#1, #2 and #3) were isolated by anti-CD14-labeled magnetic microbeads. CD14+ monocytes were cultured for 7 days in RPMI 10% FCS containing either GM-CSF or M-CSF. Total RNA from each condition was extracted and purified using the RNeasy kit (Qiagen). Labelled RNA was used as hybridization probes on human Codelink Whole genome Bioarray. All experimental procedures were performed following manufacturer instructions. Microarrays were scanned with a GenePix 4000B (Axon Instruments) scanner. Scanned images and raw data were processed using the Codelink Expression Software.
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Project description:Stroma provides tissues with structural integrity and organization, but its capacity to shape myeloid cells is poorly understood. Here we quantify stromal response to inflammation in pediatric inflammatory bowel disease (IBD) and reveal subset-specific inflammatory responses across colon segments and intestinal layers. Using data from a murine dynamic gut injury model and human ex vivo transcriptomic/protein/spatial analysis, we found that PDGFRA+CD142-/low fibroblasts and monocytes/macrophages co-localize in the intestine. Primary human fibroblast-monocyte co-cultures showed that intestinal PDGFRA+CD142-/low fibroblasts foster monocyte transition to CCR2+CD206+ macrophages through granulocyte-macrophage colony-stimulating factor (GM-CSF). Monocyte-derived CCR2+CD206+ cells from co-cultures had a phenotype similar to intestinal CCR2+CD206+ macrophages from newly diagnosed pediatric IBD patients, with higher levels of PD-L1 and lower levels of GM-CSF receptor. The study depicts subset-specific changes in stromal response to inflammation and demonstrates the stromal potential to guide intestinal macrophage differentiation.
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Project description:Monocytes are a heterogeneous cell population with subset-specific functions and phenotypes. The differential expression of CD14 and CD16 distinguishes classical CD14++CD16-, intermediate CD14++CD16+ and non-classical CD14+CD16++ monocytes. However, CD14++CD16+ monocytes remain the most poorly characterized subset so far. Therefore we analyzed the transcriptomes of the three monocyte subsets using SuperSAGE in combination with high-throughput sequencing. Analysis of 5,487,603 tags revealed unique identifiers of CD14++CD16+ monocytes, delineating these cells from the two other monocyte subsets. CD14++CD16+ monocytes were linked to antigen processing and presentation (e.g. CD74, HLA-DR, IFI30, CTSB), to inflammation and monocyte activation (e.g. TGFB1, AIF1, PTPN6), and to angiogenesis (e.g. TIE2, CD105). Therefore we provide genetic evidence for a distinct role of CD14++CD16+ monocytes in human immunity. Human monocyte subsets (CD14++CD16-, CD14++CD16+, CD14+CD16++) were isolated from 12 healthy volunteers based on MACS technology. Total RNA from monocyte subsets was isolated and same aliquots from each donor and monocyte subset were matched for SuperSAGE. Three SuperSAGE libraries (CD14++CD16-, CD14++CD16+ and CD14+CD16++) were generated.
2011-07-24 | E-GEOD-30811 | biostudies-arrayexpress
Project description:The new official nomenclature subdivides human monocytes into three subsets, classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+). Here, we comprehensively define relationships and unique characteristics of the three human monocyte subsets using microarray and flow cytometry analysis. Our analysis revealed that the intermediate and nonclassical monocyte subsets were most closely related. For the intermediate subset, majority of genes and surface markers were expressed at an intermediary level between the classical and nonclassical subset. There features therefore indicate a close and direct lineage relationship between the intermediate and nonclassical subset. From gene expression profiles, we define unique characteristics for each monocyte subset. Classical monocytes were functionally versatile, due to the expression of a wide range of sensing receptors and several members of the AP-1 transcription factor family. The intermediate subset was distinguished by high expression of MHC class II associated genes. The nonclassical subset were most highly differentiated and defined by genes involved in cytoskeleton rearrangement that explains their highly motile patrolling behavior in vivo. Additionally, we identify unique surface markers, CLEC4D, IL-13RA1 for classical, GFRA2, CLEC10A for intermediate and GPR44 for nonclassical. Our study hence defines the fundamental features of monocyte subsets necessary for future research on monocyte heterogeneity. Three human monocyte subsets, the CD14++CD16- classical, the CD14++CD16+ intermediate and CD14+CD16+ nonclassical subsets were purified using fluorescence activated cell sorting from peripheral blood mononuclear cells. RNA was processed from the three monocyte subsets from 4 individual donors in duplicates, giving a total of 24 samples.
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