Project description:scRNAseq of monocytes from in vitro Trained immunity experiments stimulated by β-glucan (BG), uric acid (UA), muramyl dipeptide (MDP), oxidized low-density lipoprotein (oxLDL), or RPMI-Control, and respective samples restimulated with Lipopolysaccharide (LPS).
Project description:To identify the differences between human umbilical cord blood and peripheral blood monocytes, we performed unsupervised bioinformatic analyses by microarrays.
Project description:To evaluate gene expression in human peripheral blood derived monocytes over the course of an LPS stimulation time-series. Keywords: time course
Project description:Purpose: We characterized genome-wide DNA methylation profiles (methylome) in purified peripheral blood monocytes (PBMs) from 18 healthy postmenopausal Caucasian females aged 50-56 years. Methods: DNA methylome of Human Peripheral Blood Monocytes were generated by methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq), using Illumina GAIIx. The sequence reads that passed quality filters were analyzed using MEDIPS package. Targeted methylation validation analysis was performed by using MassARRAY EpiTYPER assays. Genome-wide gene expression profiles have been obtained for 7 of the 18 subjects by using Affymetrix 1.0 Human Exon ST arrays following the manufacturer's recommended protocols. Results: Using MeDIP-seq,a total of approximately 283 million reads were uniquely aligned to human genome (Build NCBI37, HG19), resulting in average ~16 million uniquely aligned high quality reads per sample. Distinct patterns were revealed at different genomic features. For instance, promoters were commonly (~58%) found to be unmethylated; whereas protein coding regions were largely (~84%) methylated. We found that approximately 24% CpG islands (CGIs) were highly methylated in PBMs. Further characterization of CGIs with respect to their relative locations to RefSeq genes revealed that the highly methylated CGIs were largely enriched (~89%) in CGIs located in gene bodies and intergenic regions. By integration of the methylome data with genome-wide PBM gene expression data, we found negative correlation between promoter methylation levels and gene transcription levels when comparing groups of genes with different expression levels, and this relationship was consistently observed across promoters with high to low CpG densities. Furthermore, we observed a modest but significant excess (permutation p<0.0001) of genes showing negative correlation between inter-individual promoter methylation and transcription levels, particularly for genes associated with CpG-rich promoters. Across the 18 individual PBM methylomes, we also identified genomic regions that were constitutively highly methylated in PBMs as well as regions showing large inter-individual variability. Conclusions: This study represents a comprehensive analysis of the PBM methylome and our data provides a valuable resource for future epigenomic and multi-omic studies exploring biological and disease-related regulatory mechanisms in PBMs. DNA methylome of human peripheral blood monocytes were generated by MeDIP-seq, using Illumina GAIIx.
Project description:CD14+ monocytes were separated from human peripheral blood and exposed to IL-4 for 12 or 72 hours then subjected to microarray analysis We used Affymetrix miRNA1.0 microarray to obtain global miRNA expression data of human monocytes, unstimulated and IL-4-stimulated differentiating macrophages.
Project description:Chromatin immunoprecipitation in combination with a genome-wide analysis via high-throughput sequencing is the state of the art method to gain genome-wide representation of histone modification or transcription factor binding profiles. However, chromatin immunoprecipitation analysis in the context of human experimental samples is limited, especially in the case of blood cells. The typically extremely low yields of precipitated DNA are usually not compatible with library amplification for next generation sequencing. We developed a highly reproducible protocol to present a guideline from the first step of isolating monocytes from a blood sample to analyse the distribution of histone modifications in a genome-wide manner. ChIP-seq histone modifications in CD14++ CD16- monocytes from human blood samples
