Chronic psoriatic skin inflammation leads to increased monocyte adhesion and aggregation
ABSTRACT: Psoriasis patients exhibit an increased risk of death by cardiovascular disease (CVD) and have elevated levels of circulating intermediate (CD14++CD16+) monocytes. This elevation could represent evidence of monocyte dysfunction in psoriasis patients at risk of CVD, as increases in circulating CD14++CD16+ monocytes are predictive of myocardial infarction and death. An elevation in the CD14++CD16+ cell population has been previously reported in patients with psoriatic disease, which has been confirmed in the cohort of our human psoriasis patients. CD16 expression was induced in CD14++CD16neg classical monocytes following plastic adhesion, which also elicited enhanced β2 but not β1 integrin surface expression, suggesting increased adhesive capacity. Indeed, we found that psoriasis patients have increased monocyte aggregation among circulating PBMCs which is recapitulated in the KC-Tie2 murine model of psoriasis. Visualization of human monocyte aggregates using imaging cytometry revealed that classical CD14++CD16neg monocytes are the predominant cell type participating in these aggregate pairs. Many of these pairs also included CD16+ monocytes, which could account for apparent elevations of intermediate monocytes. Additionally, intermediate monocytes and monocyte aggregates were the predominant cell type to adhere to TNF-α and IL-17A-stimulated dermal endothelium. Ingenuity Pathway Analysis (IPA) demonstrated that monocyte aggregates have a distinct transcriptional profile from singlet monocytes and monocytes following plastic adhesion, suggesting that circulating monocyte responses to aggregation are not fully accounted for by homotypic adhesion, and that further factors influence their functionality. qRT-PCR Gene Expression Profiling - 30 Samples Analyzed, 10 biological replicates, 10 Control Samples, 20 Test Samples
Project description:Human peripheral monocytes have been categorized into three subsets based on differential expression levels of CD14 and CD16. However, the factors that influence the distribution of monocyte subsets and the roles which each subset plays in autoimmunity are not well studied. To compare the gene expression profiling 1) on intermediate monocytes CD14++CD16+ monocytes between healthy donors and autoimmune uveitis patients and 2) among 3 monocyte subsets in health donors, here we purified circulating intermediate CD14++CD16+ monocytes from 5 patients with autoimmune uveitis (labeled as P1-5) and 4 healthy donors (labeled as HD1-4) by flow cytometry and isolated total RNA to proceed microarray assay. In addition, we also purified CD14+CD16++ (non-classical monocytes) and CD14++CD16- (classical monocytes) from 4 healthy donors to do microarray. We demonstrate that CD14++CD16+ monocytes from patients and healthy control donors share a similar gene expression profile. The CD14+CD16++ cells (non-classical monocytes) display the most distinctive gene expression profiling when compared to intermediate CD14++CD16+ monocytes and classical CD14++CD16- monocytes. Overall design: Pheripharal blood from 5 autoimmune uveitis patients and 4 healthy donors were collected. Immediately after collection, we purified circulating intermediate CD14++CD16+ monocytes from 5 patients with autoimmune uveitis ( Sample 13-17; titled as P intermediate 1-5) and 4 healthy donors (Sample 1, 4, 7, 10; titled as HD intermediate 1-4) by flow cytometry and isolated total RNA to proceed microarray assay. In addition, we also purified CD14+CD16++ (Sample 3, 6, 9, 12; titled HD non-classical 1-4) and CD14++CD16- (Sample 2, 5, 8, 11; titled HD classical 1-4) from 4 healthy donors to do microarray. Please note that data processing was performed in two groups;  HD intermediate, classical and non-classical samples (total 12 samples)  HD intermediate samples reanalyzed with P intermediate samples (total 9 samples).
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. Overall design: 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: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:Human monocytes are a heterogeneous cell population consisting of three subsets: classical CD14++CD16-, intermediate CD14++CD16+ and nonclassical CD14+CD16++ monocytes. Intermediate monocytes contribute to inflammation, and their circulating cell counts are increased in many chronic inflammatory diseases, even though the underlying pathways are poorly characterized. We tested in how far epigenetic mechanisms regulate human monocytes heterogeneity in chronic kidney disease, which is a proinflammatory condition of substantial epidemiological importance. By applying next-generation Methyl-Sequencing (Methyl-Seq) we characterized genome-wide DNA methylation within the three monocyte subsets and analyzed the impact of uremia on DNA methylation in differentiating monocytes. We found that each monocyte subset displays a unique phenotype with regards to DNA methylation. Genes with differentially methylated promoter regions in intermediate monocytes were linked to distinct immunological processes, which is in line with results from recent gene expression analyses. In vitro, uremia induced a dysregulation of DNA methylation in differentiating monocytes which affected several transcription factors important for monocyte differentiation (e.g. FLT3, HDAC1, MNT) and led to enhanced generation of intermediate monocytes. As a potential mediator, the uremic toxin and DNA methylation inhibitor S-Adenosylhomocysteine induced shifts in monocyte subsets in vitro, and associated with monocyte subset counts in vivo. In summary, our data support the concept of monocyte trichotomy and the distinct role of intermediate monocytes in human immunity. The shift in monocyte subsets which occurs in chronic kidney disease, a proinflammatory condition of substantial epidemiological impact, may be induced by the accumulation of specific uremic toxins that mediate epigenetic dysregulation. Overall design: Seven healthy donors were recruited for DNA methylation analysis of the three monocyte subsets; DNA methylation analysis of differentiating monocytes was performed in 5 independent experiments
Project description:The progression to AIDS is influenced by changes in the biology of heterogeneous monocyte subsets. Classical (CD14++CD16-), intermediate (CD14++CD16+), and nonclassical (CD14+CD16++) monocytes may represent progressive stages of monocyte maturation or disparate myeloid lineages with different turnover rates and function. To investigate the relationship between monocyte subsets and the response to SIV infection, we performed microarray analysis of monocyte subsets in rhesus macaques at three timepoints: prior to SIV infection, 26 days post-infection, and necropsy with AIDS. Genes with a 2-fold change between monocyte subsets (2023 genes) or infection timepoints (424 genes) were selected. We identify 172 genes differentially expressed among monocyte subsets in both uninfected and SIV-infected animals. Classical monocytes express genes associated with inflammatory responses and cell proliferation. Nonclassical monocytes express genes associated with activation, immune effector functions, and cell cycle inhibition. The classical and intermediate subsets are most similar at all timepoints, and transcriptional similarity between intermediate and nonclassical monocytes increases with AIDS. Cytosolic sensors of nucleic acids, restriction factors, and interferon-stimulated genes are induced in all three subsets with AIDS. We conclude that SIV infection alters the transcriptional relationship between monocyte subsets and that the innate immune response to SIV infection is conserved across monocyte subsets. Overall design: 30 total samples representing sorted CD14++CD16-, CD14++CD16+, and CD14+CD16++ peripheral blood monocytes from 4 rhesus macaques at three different stages of SIV infection (pre-infection, day 26 post-infection, and at necropsy with AIDS) are included.
Project description:Identification of micro-RNAs involved in regulating differential apoptosis and migration potential of human monocyte subsets Comparision between freshly isolated CD14++CD16- monocytes and CD14+CD16+ monocytes from healthy human blood
Project description:Rheumatoid arthritis (RA) accompanies infiltration and activation of monocytes in inflamed joints. In this study we investigated dominant alterations of RA monocytes in bone marrow (BM), blood and inflamed joints. CD14+ cells from BM and blood of RA and osteoarthritis (OA) patients were profiled with Affymetrix HG U133 Plus 2.0 Arrays. Detailed functional analysis was performed with reference transcriptomes of BM precursors, monocyte blood subsets, monocyte activation and mobilization. Cytometric profiling determined monocyte subsets of CD14++CD16-, CD14++CD16+ and CD14+CD16+ cells in BM, blood and synovial fluid (SF) and ELISAs quantified the release of activation markers into SF and serum. Investigation of genes differentially expressed between RA and OA monocytes by co-expression analysis with reference transcriptomes revealed gene patterns of early myeloid precursors in RA-BM and late myeloid precursors along with reduced terminal differentiation to CD14+CD16+ monocytes in RA blood. Patterns associated with TNF/LPS stimulation were weak and more pronounced in RA blood than BM. Cytometric phenotyping of cells in BM and blood disclosed differences related to monocyte subsets and confirmed the reduced frequency of terminally differentiated CD14+CD16+ monocytes in RA blood, as suggested by transcriptome data. Monocyte activation in SF was characterized by the predominance of CD14++CD16++CD163+HLA-DR+ cells and elevated concentrations of sCD14, sCD163 and S100P. Accelerated monocytopoiesis, BM egress and migration into inflamed joints characterise increased monocyte turnover in RA. Predominant activation in the joint suggests local and primary stimulants, which may promote also adaptive immune triggering through monocytes, thus indicating their importance for diagnostic and therapeutic strategies. Overall design: Expression profiles of human peripheral blood (PB) and bone marrow (BM) monocytes from patients with RA and OA. Monocytes from RA and OA patients with long-lasting disease that were undergoing hip-replacement surgery were collected and processed for analyses. Functional interpretation of differential expression of genes were analyzed with conventional tools like Gene Ontology, Ingenuity pathway analysis as well as with the reference transcriptomes that portrayed (1) cells of myeloid lineage in bone marrow (GSE42519), (2) monocyte subsets in blood (GSE18565), (3) monocytes activated in vitro by various inflammatory stimuli (GSE38351) and (4) leukocytes (including monocytes as well) mobilized from bone marrow into blood by G-CSF administration (GSE7400).
Project description:On the basis of the cell-surface molecule expression, CD16+ monocytes are likely comprised of distinct subpopulations of monocytes rather than a continuum of CD14+ monocytes with differing levels of cell activation. To better study this, we used gene array analysis that compared overall gene expression profiles of CD16+ subpopulations (CD14+CD16+ and CD16+) with that of CD14+CD16-. Gene expression in three FACS-sorted monocyte subsets was assessed by Affymetrix rhesus macaque oligonucleotide gene arrays that contain 52,024 probe sets covering 47,000 monkey genes. There were 29,361 probe sets that expressed in at least one subpopulation (raw array signal intensity > 32). Raw data were processed using robust multi-array average. To identify the most strongly, differentially expressed genes in each subpopulation, we only selected transcripts with consistently greater than four-fold difference (P < .05). In comparison to CD14+CD16- monocyte subset, a large number of genes (9098/29361, 30.9%) were differentially expressed in both CD14+CD16+ and CD16+ subsets: 1999 genes down-regulated; and 7099 genes up-regulated. Altogether, we observed large-scale gene expression differences between the CD14+CD16- subset and the two CD16+ subsets (CD14+CD16+ and CD16+), demonstrating transcriptional heterogeneity. The differential gene expression between CD16- and CD16+ monocytes underscore the fundamental differences between these cells. Comparisons between CD14+CD16+ and CD16+ were made to identify the genes that distinguish between these two CD16+ subpopulations. A relatively small number of genes were specifically associated with each subpopulation. Thirty-one genes were expressed strongly in CD14+CD16+ subset compared to CD16+ subset, and 94 genes were expressed strongly in CD16+ subset compared to CD14+CD16+ subset. A small set of genes that were expressed differentially between the two CD16+ subpopulations highlights similarity between the two cell types, but differentially expressed genes of function observed in each subset suggest different roles that these two subpopulations may play in vivo. Overall design: To identify differentially expressed genes in subpopulations of monkey monocytes, three monocyte subsets from two normal uninfected rhesus macaques were FACS sorted based on their CD14 and CD16 expression. RNA purification and labeling, hybridization, array scanning, and image quantification were performed according to the manufacturer’s instructions. Briefly, FACS-isolated monocytes were spun down and lysed in Trizol reagents (Invitrogen), and total RNA was prepared using PureLink Micro-to-Midi Total RNA Purification system (Invitrogen). Quality of RNA was determined by 2100 Bioanalyzer RNA LabChip (Agilent Technologies). One hundred ng of high-quality total RNA was subjected to Affymetrix 1-cycle or 2-cycle synthesis amplification, fluorescent labeling, and hybridization to Affymetrix Rhesus Genome Arrays. Expression data was obtained from two aligned replicates using an Affymetrix GSC3000 scanner and processed by GCOS software (Affymetrix). Partek Genomic Suite System was used for downstream analysis of GCOS processed data. Signals from all probe sets were normalized using Rhesus Array Normalization Controls.
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.
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. Overall design: 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.