ATAC-seq of purified immune cell populations
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE125164 | GEO | 2022/12/10
REPOSITORIES: GEO
Similar Datasets
Project description:These experiments were designed as a benchmark tool for deconvolution methods. 5 immune cell populations were sorted from 3 healthy donors' peripheral bloods. Peripheral Blood Mononuclear Cells (PBCMs) and PolymorphoNuclear Cells (PMN) were separated using gradient centrifugation. T cells (DAPI-/CD3+/CD14-/CD19-/CD56-), monocytes (DAPI-/CD3-/CD14+/CD19-/CD56-), B cells (DAPI-/CD3-/CD14-/CD19+/CD56-) and NK cells (DAPI-/CD3-/CD14-/CD19-/CD56+) were FACS-sorted from PBMCs and neutrophils (DAPI-/CD66b+/CD19-/CD3-/CD56-/CD14-) were sorted from PMNs. RNA was extracted from the purified cell population, as well as from the HCT116 colon cancer cell line. RNAs from pure populations were then mixed in various proportions. RNA from HCT116 cells and FACS-sorted T cells (DAPI-/CD3+/CD14-/CD19-/CD56-), monocytes (DAPI-/CD3-/CD14+/CD19-/CD56-), B cells (DAPI-/CD3-/CD14-/CD19+/CD56-), NK cells (DAPI-/CD3-/CD14-/CD19-/CD56+), and neutrophils (DAPI-/CD66b+/CD19-/CD3-/CD56-/CD14-) were mixed in various proportions.
2016-02-18 | E-GEOD-64385 | biostudies-arrayexpress
Project description:Bulk ATAC-Seq was performed on human cord-blood derived hematopoietis popuations using the following markers:
LT-HSC; CD34+CD38-CD45RA-CD90+CD49f+
ST-HSC; CD34+CD38-CD45RA-CD90-CD49f-
MLP; CD34+CD38-CD45RA+
CMP; CD34+CD38+ CD10-CD45RA-Flt3+CD71-
GMP; CD34+CD38+ CD10-CD45RA+ CD71-
MEP; CD34+CD38+ CD10-CD45RA-Flt3-CD71+
T cell; CD3+CD19-
B cell; CD19+CD3-
NK cell; CD56+CD3-CD19-CD14-
Granulocyte; CD14+CD15+CD3-CD19-
Monocyte; CD14+CD15-CD3-CD19-
DC; CD11c+CD45+
Erythroid cell; CD71+GPA+
| EGAS00001004742 | EGA
Project description:Monocytes and matching culture-derived nurse-like cells were compared using Illumina's EPIC/850k arrays Monocytes isolated using MACS and NLCs isolated using cytometry sorting as CD14+/CD19-
2022-07-12 | GSE206842 | GEO
Project description:Blood genomic profiling has been applied to disorders of the blood and various organ systems including brain to elucidate disease mechanisms and identify surrogate disease markers. Since most studies have not examined specific cell types, we performed a preliminary genomic survey of major blood cell types from normal individuals using microarrays. CD4+ T cells, CD8+ T cells, CD19+ B cells, CD56+ natural killer cells, and CD14+ monocytes were negatively selected using the RosetteSep antibody cocktail, while polymorphonuclear leukocytes were separated with density gradient media. Genes differentially expressed by each cell type were identified. To demonstrate the potential use of such cell subtype-specific genomic expression data, a number of the major genes previously reported to be regulated in ischemic stroke, migraine, and Tourette syndrome are shown to be associated with distinct cell populations in blood. These specific gene expression, cell-type-related profiles will need to be confirmed in larger data sets and could be used to study these and many other neurological diseases. This study includes data from major blood cell types from normal individuals. These cell types include CD4+ T cells, CD8+ T cells, CD19+ B cells, CD56+ natural killer cells, CD14+ monocytes and PMN (polymorphonuclear cells). The data were hybridized on 3 separate batches of gene chips.
2015-09-03 | E-GEOD-72642 | biostudies-arrayexpress
Project description:Natural Killer cells (NK), a major constituent of innate immune system, have the ability to kill the transformed and infected cells without prior sensitization; can be put to immunotherapeutic use against various malignancies. NK cells discriminate between normal cells and transformed cells via a balance of inhibitory and activating signals induced by interactions between NK cell receptors and target cell ligands. Present study investigates whether expansion of NK cells could augment their anti-myeloma (MM) activity. For NK cell expansion, peripheral blood mononuclear cells from healthy donors and myeloma patients were co-cultured with irradiated K562 cells transfected with 4-1BBL and membrane-bound IL15 (K562-mb15-41BBL). A genome-wide profiling approach was performed to identify gene expression signature in expanded NK (ENK) cells and non-expanded NK cells isolated from healthy donors and myeloma patients. A specific set of genes involved in proliferation, migration, adhesion, cytotoxicity, and activation were up regulated post expansion, also confirmed by flow cytometry. Exp-NK cells killed both allogeneic and autologous primary MM cells more avidly than non-exp-NK cells in vitro. Multiple receptors, particularly NKG2D, natural cytotoxicity receptors, and DNAM-1 contributed to target lysis, via a perforin mediated mechanism. In summary, vigorous expansion and high anti-MM activity both in vitro and in vivo provide the rationale for testing exp-NK cells in a clinical trial for high risk MM. Differential gene expression profile in expanded natural killer (ENK) cells and non-expanded natural killer (NK) cells from healthy donors and myeloma patients Eight healthy donor and eight myeloma patients were used in the study. Non-expanded natural killer (NK) cells were isolated from PBMCs of healthy donors and myeloma patients. Expanded natural killer (ENK) cells were generated from same set of samples as mentioned in expansion protocol. All ENK and NK cells were used for gene expression profiling.
2011-03-08 | E-GEOD-27838 | biostudies-arrayexpress
Project description:These experiments were designed as a benchmark tool for deconvolution methods. 5 immune cell populations were sorted from 3 healthy donors' peripheral bloods. Peripheral Blood Mononuclear Cells (PBCMs) and PolymorphoNuclear Cells (PMN) were separated using gradient centrifugation. T cells (DAPI-/CD3+/CD14-/CD19-/CD56-), monocytes (DAPI-/CD3-/CD14+/CD19-/CD56-), B cells (DAPI-/CD3-/CD14-/CD19+/CD56-) and NK cells (DAPI-/CD3-/CD14-/CD19-/CD56+) were FACS-sorted from PBMCs and neutrophils (DAPI-/CD66b+/CD19-/CD3-/CD56-/CD14-) were sorted from PMNs. RNA was extracted from the purified cell population, as well as from the HCT116 colon cancer cell line. RNAs from pure populations were then mixed in various proportions.
2016-02-18 | GSE64385 | GEO
Project description:Peripheral blood leukocytes are the most commonly used surrogates to study epigenome-induced risk and epigenomic response to disease related stress. We considered the hypothesis that the TET enzyme catalyzed hydroxymethylation of 5mC to 5hmC might vary among peripheral blood leukocytes and reflect their responsiveness to environment. Reduction in TET1 and/or TET2 activity leads to the over-proliferation of various leukocyte precursors in bone marrow and acute leukemia, yet, the role of 5mC hydroxymethylation in peripheral blood is less well studied. We developed simplified protocols to rapidly and reiteratively isolate mostly non-overlapping leukocyte populations from a single small sample of fresh or frozen whole blood. Among peripheral leukocyte types we found extreme variation in the levels of transcripts encoding proteins involved in cytosine methylation (DNMT1, 3A, 3B) and turnover by de-methylation (TET1, 2, 3) and DNA repair (GADD45a, b, g) and in the gene-region-specific levels of DNA 5hmC (CD4 T cells >> CD14 monocytes > CD16 neutrophils > CD19 B cells > CD56 NK cells > Siglec 8 eosinophils > CD8 T cells). Taken together our results suggest a hierarchy of responsiveness among classes of leukocytes with CD4+ and CD8+ T cells and CD14 monocytes being the most distinctly potentiated for a rapid methylome response to physiological stress and disease. TAB-seq data on 5-hydroxymehtylcytosine (Yu, M. et al. 2012. Cell 149, 1368-1380.) was collected from seven leukocyte types (CD4+ T cells, CD8+ T cells, CD14+ monocytes, CD16+ neutrophils, CD19+ B cells, CD56+ natural killer cells, and Siglec-8+ eosinophils) reiteratively isolated from peripheral blood collected from a healthy male.
2016-07-05 | E-GEOD-70519 | 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) 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:Tobacco smoking alters DNA methylation profiles of immune cells which may underpin some of the pathogenesis of smoking-associated diseases. However, approaches linking smoking-driven epigenetic effects in specific immune cell types with disease risk are limited. We isolated six leukocyte subtypes, CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, CD4+ T cells, CD8+ T cells, and CD56+ natural killer cells, from whole blood of healthy adult smokers and nonsmokers for epigenome-wide association study (EWAS).
2023-06-20 | GSE224807 | GEO
Project description:To investigate blood biomarkers of smokers and to provide molecular basis of B cell subtype shift from naïve to memory in smokers, total RNA from peripheral CD19+ B cells isolated from healthy adult smokers and nonsmokers was subjected to RNA-Seq and data were analyzed with covariates including age, race, sex, BMI, estimated CD4+T cell%, CD8+T cell%, natural killer (NK) cell%, monocyte%, granulocyte%, or naive B cell%.
2023-06-20 | GSE220113 | GEO