Project description:In this study gene expression of human blood classical monocytes (CD14++CD16-), CD16 positive monocytes (consisting of non-classical CD14+16++ and intermediate CD14++CD16+ monocytes) and CD1c+ CD19- dendritic cells from healthy subjects were investigated. Keywords: expression profiling by array
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.
Project description:Serum-free Fibrocytes, Serum-containing Fibrocytes, CD14++CD16- Monocytes, CD14++CD16+ Monocytes, CD14+CD16++ Monocytes, Macrophages were all generated from up to 3 biological replicates from each of 3 separate donors. RNA was extracted (Ambion RNAqueous), labelled with cy3, mixed with cy5 labelled human reference (Stratagene), and hybridised to slides printed with Human AROS v4.0 oligonucleotides (Operon). Slides were scanned using a Perkin Elmer GX plus, and the data then normalised with GEPAS v4.0 and collated. Final data analysis was carried out using TMEV 4.0. SAM was performed using a 0.1% FDR. PCA were plotted from this list, and interrogation carried out using DAVID to determine pathway enrichment.
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.
Project description:The aim of our work was to evaluate what happens to the two most polar subpopulations of peripheral blood monocytes in women diagnosed preeclampsia in comparison with physiological pregnancy. We used microarrays for comparison of CD14+ and CD16+ monocytes from patients with preeclampsia and women with physiological pregnancy
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.
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.
Project description:Transcriptomic profiling of peripheral immune cells can provide a wealth of information. Classical CD14++ CD16- monocytes were isolated from the peripheral blood of healthy volunteers and patients with pancreatic ductal adenocarcinoma and profiled for differential gene expression using Affymetrix human Genechips 2.1 U133.
Project description:Bone marrow monocytes are primarily committed to osteoclast formation. It is, however, unknown whether potential primary alterations are specifically present in bone marrow monocytes from patients with multiple myeloma, smoldering myeloma or monoclonal gammopathy of undetermined significance. We analyzed the immunophenotypic and transcriptional profiles of bone marrow CD14+ monocytes in a cohort of patients with different types of monoclonal gammopathies to identify alterations involved in myeloma-enhanced osteoclastogenesis. The number of bone marrow CD14+CD16+ cells was higher in patients with active myeloma than in those with smoldering myeloma or monoclonal gammopathy of undetermined significance. Interestingly, sorted bone marrow CD14+CD16+ cells from myeloma patients were more pro-osteoclastogenic than CD14+CD16-cells in cultures ex vivo Moreover, transcriptional analysis demonstrated that bone marrow CD14+ cells from patients with multiple myeloma (but neither monoclonal gammopathy of undetermined significance nor smoldering myeloma) significantly upregulated genes involved in osteoclast formation, including IL21RIL21R mRNA over-expression by bone marrow CD14+ cells was independent of the presence of interleukin-21. Consistently, interleukin-21 production by T cells as well as levels of interleukin-21 in the bone marrow were not significantly different among monoclonal gammopathies. Thereafter, we showed that IL21R over-expression in CD14+ cells increased osteoclast formation. Consistently, interleukin-21 receptor signaling inhibition by Janex 1 suppressed osteoclast differentiation from bone marrow CD14+ cells of myeloma patients. Our results indicate that bone marrow monocytes from multiple myeloma patients show distinct features compared to those from patients with indolent monoclonal gammopathies, supporting the role of IL21R over-expression by bone marrow CD14+ cells in enhanced osteoclast formation.
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.