Project description:Primary human M1 and M2 macrophages were transfected with different human herpesvirus-derived viral miRNA and the impact on the cellular microRNAs was profiled using microarray. Viral miRNA-mediated impact was assessed on the host cellular microRNA profiles by miRNA microarray analysis. Five different viral miRNA representing 4 different human herpesviruses were overexpressed in M1 and M2 macrophages and the changes in cellular miRNA compared to control mimic were examined. Viral miRNA exhibit unique impact on M1 and M2 miRNA profiles.
Project description:Recent studies suggest the presence of both âclassically activatedâ M1 and âalternatively activatedâ M2 macrophages in human atherosclerotic tissue, yet due to the lack of validated markers the reported localization patterns of these macrophage phenotypes within plaques are ambiguous. In the present study, we searched for markers that indisputably can identify differentiated M1 and M2 macrophages independently of stimuli that affect the activation status of the two subpopulations. We used these validated markers to assess the presence of M1 and M2 macrophages in different zones of human carotid artery atherosclerotic plaques obtained from 12 patients. Using microarray and qPCR technology we show that the frequently used macrophage subpopulation markers MCP-1 and CD206 do not discriminate between M1 and M2 macrophages. However, we confirm the subtype specificity of the classical M2 marker CD163 and we report that the genes INHBA and DSP (both M1) and SEPP1 and MARCKS (both M2) are highly suitable for macrophage phenotyping. mRNA expression of the pan-macrophage marker CD68 in the shoulder zones of the plaques and in adjacent tissue segments correlated positively with mRNA expression levels of SEPP1, MARCKS and CD163 (r=0.86, 0.94 and 0.96, and r= 0.86, 0.98 and 0.69, respectively) but not with the expression of the M1 markers DSP and INHBA. In contrast, mRNA expression of CD68 in the core of the plaques correlated positively with expression of DSP and INHBA (r=0.73 and 0.49) but not with SEPP1, MARCKS and CD163. These findings suggest that M1 macrophages predominate in the core of human carotid atherosclerotic plaques while M2 macrophages prevail at the periphery of the plaque. Keywords: Expression profiling by array Monocytes from healthy volunteers were differentiated into M1 and M2 macrophages by incubation with granulocyte-macrophage colony-stimulating factor (GM-CSF) or macrophage colony-stimulating factor (M-CSF), respectively. After 5 days cells were exposed to oxidized LDL. Total RNA was isolated and subjected to gene expression profiling.
Project description:Macrophages have distinct characteristics depending on their microenvironment. We performed proteomic analysis between M1 and M2 macrophages and found that cellular metabolism is the key regulator of macrophage function. We used microarray to support proteomic data between M1 and M2 macrophages. M1 macrophages are obtained using cell sorting of CD45+MHCII+CD8a-F4/80+ population from C57BL/6J bone marrow cell derived heterogenous cells under GM-CSF conditioning for 7 days. M2 macrophages are differentiated with 20% L929 cell supernatant for 7 days and sorted from CD45+F4/80+CD11b+ population.
Project description:Classically (M1) and alternatively activated (M2) macrophages play distinct roles in various physiological and disease processes. Understanding the gene transcription programs that contribute to macrophage polarization along the M1/M2 spectrum may lead to new tools to detect and therapeutically manipulate macrophage phenotype. Here, we define the M1 and M2 macrophage signature through mRNA microarray. The M1 macrophage signature was defined by 629 up-regulated and 732 down-regulated genes while the M2 macrophage signature was formed by 388 up-regulated and 425 down-regulated genes. While a subset of probes was common to both M1 and M2 cells, others were exclusive to each macrophage subset. The common M1/M2 pathways were characterized by changes in various transcriptional regulators and signaling partners, including increases in Kruppel-like Factor (Klf) 4, but decreases in Klf2. To identify M1 and M2 biomarkers that help discriminate these populations, we selected genes that were increased during M1 or M2 differentiation but decreased in the opposite population. Among top novel M1-distinct genes, we identified CD38, G-protein coupled receptor 18 (Gpr18) and Formyl peptide receptor 2 (Fpr2). Among top M2 genes, we found early growth response protein 2 (Egr2) and Myc. We validated these genes by Real-Time PCR and developed a CD38/Egr2-based flow cytometry assay that discriminates between M1 and M2 macrophages. Overall, this work defines the M1 and M2 signature and identifies several novel M1 and M2 genes that may be used to distinguish and manipulate M1 and M2 macrophages. Total RNA was prepared from bone marrow-derived macrophages of wild-type mice (n=2-3 independent mice) treated in M0, M1 or M2 conditions (n=2-3 replicates per condition originating from different mice)
Project description:Macrophages have distinct characteristics depending on their microenvironment. We performed proteomic analysis between M1 and M2 macrophages and found that cellular metabolism is the key regulator of macrophage function. We used microarray to support proteomic data between M1 and M2 macrophages.
Project description:Classically (M1) and alternatively activated (M2) macrophages play distinct roles in various physiological and disease processes. Understanding the gene transcription programs that contribute to macrophage polarization along the M1/M2 spectrum may lead to new tools to detect and therapeutically manipulate macrophage phenotype. Here, we define the M1 and M2 macrophage signature through mRNA microarray. The M1 macrophage signature was defined by 629 up-regulated and 732 down-regulated genes while the M2 macrophage signature was formed by 388 up-regulated and 425 down-regulated genes. While a subset of probes was common to both M1 and M2 cells, others were exclusive to each macrophage subset. The common M1/M2 pathways were characterized by changes in various transcriptional regulators and signaling partners, including increases in Kruppel-like Factor (Klf) 4, but decreases in Klf2. To identify M1 and M2 biomarkers that help discriminate these populations, we selected genes that were increased during M1 or M2 differentiation but decreased in the opposite population. Among top novel M1-distinct genes, we identified CD38, G-protein coupled receptor 18 (Gpr18) and Formyl peptide receptor 2 (Fpr2). Among top M2 genes, we found early growth response protein 2 (Egr2) and Myc. We validated these genes by Real-Time PCR and developed a CD38/Egr2-based flow cytometry assay that discriminates between M1 and M2 macrophages. Overall, this work defines the M1 and M2 signature and identifies several novel M1 and M2 genes that may be used to distinguish and manipulate M1 and M2 macrophages.
Project description:Analysis of the effects of CNI-1493 treatment on M1 and M2 polarized macrophages. The purpose of this microarray is to identify genes that may be differentially expressed in M1 or M2 macrophages after treatment with CNI-1493. CNI-1493 is a known inhibitor of M1 macrophages but details of its molecular mechanism are unknown. The effect of CNI-1493 on M2 macrophages has yet to be explored, but we hypothesize that CNI-1493 treatment will attenuate pro-tumor properties of M2 macrophages. We demonstrate with this array that known macrophage markers are unchanged after treatment with CNI-1493, indicating that CNI-1493 does not change the macrophage phenotype on a transcriptional level. Additionally, no candidate genes to suggest how CNI-1493 may attenuate the pro-tumor effects of M2 macrophages are readily identifiable. Total RNA extracted from M1 or M2 macrophages after polarization with GM-CSF (25ng/ml) or M-CSF (25ng/ml) for 7 days, followed by addition of IFN-γ (20ng/ml) and LPS (100ng/ml) or IL-4 (40ng/ml) for 18 hours, respectively, from CD14+ human PBMCs, and treated with CNI-1493 (200nM)
Project description:Obesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response. We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment. We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam cell–like cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization. Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization. 15 samples; 2 genotypes and 2 time points
Project description:We report the application of RNA sequencing to determine the transcriptional response of primary bone marrow macorphages and murine macrophage Raw 264.7 cells in response to stimulation with LPS/IFNgamma(M1) or IL-4 (M2) stimulation conditions
Project description:Recent studies suggest the presence of both “classically activated” M1 and “alternatively activated” M2 macrophages in human atherosclerotic tissue, yet due to the lack of validated markers the reported localization patterns of these macrophage phenotypes within plaques are ambiguous. In the present study, we searched for markers that indisputably can identify differentiated M1 and M2 macrophages independently of stimuli that affect the activation status of the two subpopulations. We used these validated markers to assess the presence of M1 and M2 macrophages in different zones of human carotid artery atherosclerotic plaques obtained from 12 patients. Using microarray and qPCR technology we show that the frequently used macrophage subpopulation markers MCP-1 and CD206 do not discriminate between M1 and M2 macrophages. However, we confirm the subtype specificity of the classical M2 marker CD163 and we report that the genes INHBA and DSP (both M1) and SEPP1 and MARCKS (both M2) are highly suitable for macrophage phenotyping. mRNA expression of the pan-macrophage marker CD68 in the shoulder zones of the plaques and in adjacent tissue segments correlated positively with mRNA expression levels of SEPP1, MARCKS and CD163 (r=0.86, 0.94 and 0.96, and r= 0.86, 0.98 and 0.69, respectively) but not with the expression of the M1 markers DSP and INHBA. In contrast, mRNA expression of CD68 in the core of the plaques correlated positively with expression of DSP and INHBA (r=0.73 and 0.49) but not with SEPP1, MARCKS and CD163. These findings suggest that M1 macrophages predominate in the core of human carotid atherosclerotic plaques while M2 macrophages prevail at the periphery of the plaque. Keywords: Expression profiling by array