Live Flow Cytometry Analysis of c-di-GMP Levels in Single Cell Populations

BackgroundMucosal-associated invariant T (MAIT) cells are considered to participate of the host immune response against acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection; however, single-cell transcriptomic profiling of MAIT cells in patients with COVID-19 remains unexplored.MethodsWe performed single-cell RNA sequencing analyses on peripheral MAIT cells from 13 patients with COVID-19 and 5 healthy donors. The transcriptional profiles of MAIT cells, together with assembled T-cell receptor sequences, were analyzed. Flow cytometry analysis was also performed to investigate the properties of MAIT cells.ResultsWe identified that differentially expressed genes (DEGs) of MAIT cells were involved in myeloid leukocyte activation and lymphocyte activation in patients with COVID-19. In addition, in MAIT cells from severe cases, more DEGs were enriched in adaptive cellular and humoral immune responses compared with those in moderate cases. Further analysis indicated that the increase of cell cytotoxicity (killing), chemotaxis, and apoptosis levels in MAIT cells were consistent with disease severity and displayed the highest levels in patients with severe disease. Interestingly, flow cytometry analysis showed that the frequencies of pyroptotic MAIT cells, but not the frequencies of apoptotic MAIT cells, were increased significantly in patients with COVID-19, suggesting pyroptosis is one of leading causes of MAIT cell deaths during SARS-CoV-2 infection. Importantly, there were more clonal expansions of MAIT cells in severe cases than in moderate cases.ConclusionsThe results of the present study suggest that MAIT cells are likely to be involved in the host immune response against SARS-CoV-2 infection. Simultaneously, the transcriptomic data from MAIT cells provides a deeper understanding of the immune pathogenesis of the disease.

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Flow cytometry analysis of dual red blood cell populations after bone marrow transplantation

British Journal of Haematology ◽

10.1111/j.1365-2141.1995.tb08410.x ◽

2008 ◽

Vol 89 (4) ◽

pp. 741-747 ◽

Cited By ~ 15

Author(s):

D. Blanchard ◽

V. Bruneau ◽

F. Germond-Arnoult ◽

D. Bernard ◽

A. Gourbil ◽

...

Keyword(s):

Bone Marrow ◽

Flow Cytometry ◽

Bone Marrow Transplantation ◽

Blood Cell ◽

Red Blood Cell ◽

Marrow Transplantation ◽

Cell Populations ◽

Flow Cytometry Analysis

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Discovering Myeloid Cell Heterogeneity in Mandibular Bone – Cell by Cell Analysis

Frontiers in Physiology ◽

10.3389/fphys.2021.731549 ◽

2021 ◽

Vol 12 ◽

Author(s):

Kyu Hwan Kwack ◽

Natalie A. Lamb ◽

Jonathan E. Bard ◽

Elliot D. Kramer ◽

Lixia Zhang ◽

...

Keyword(s):

Bone Marrow ◽

Flow Cytometry ◽

Single Cell ◽

Rna Sequencing ◽

Myeloid Cell ◽

Cell Populations ◽

Cell Heterogeneity ◽

Mandibular Bone ◽

Single Cell Rna Sequencing ◽

Myeloid Progenitors

The myeloid-derived bone marrow progenitor populations from different anatomical locations are known to have diverse osteoclastogenesis potential. Specifically, myeloid progenitors from the tibia and femur have increased osteoclast differentiation potential compared to myeloid progenitors from the alveolar process. In this study, we explored the differences in the myeloid lineage progenitor cell populations in alveolar (mandibular) bone versus long (femur) bone using flow cytometry and high-throughput single cell RNA sequencing (scRNA-seq) to provide a comprehensive transcriptional landscape. Results indicate that mandibular bone marrow-derived cells exhibit consistent deficits in myeloid differentiation, including significantly fewer myeloid-derived suppressor cell (MDSC)-like populations (CD11b+Ly6C+, CD11b+Ly6G+), as well as macrophages (CD11b+F4/80+). Although significantly fewer in number, MDSCs from mandibular bone exhibited increased immunosuppressive activity compared to MDSCs isolated from long bone. Using flow cytometry panels specific for bone marrow progenitors, analysis of hematopoietic stem cells showed no defects in mandibular bone marrow in LSK (Lin–Sca1+cKit+) cell and LK (Lin–Sca1–cKit+) cell populations. While there was no significant difference in granulocyte progenitors, the granulocyte-monocyte progenitors and monocyte progenitor population were significantly decreased in the mandibular bone marrow. T-lymphocyte subsets were not significantly different between mandibular and femoral bone, except for CD4+CD25+Foxp3+ regulatory T lymphocytes, which were significantly increased in the mandible. In addition, B lymphocytes were significantly increased in mandible. Single cell RNA sequencing from mandible and femur BM revealed distinct differences in transcriptomic profiles in myeloid populations establishing previously unappreciated aspects of mandibular bone marrow populations. These analyses reveal site-specific differences in the myeloid progenitor cellular composition and transcriptional programs providing a deeper appreciation of the complex differences in myeloid cell heterogeneity from different anatomical bone marrow sites.

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Single-cell variability in growing Saccharomyces cerevisiae cell populations measured with automated flow cytometry

Journal of Biotechnology ◽

10.1016/j.jbiotec.2004.01.003 ◽

2004 ◽

Vol 109 (3) ◽

pp. 239-254 ◽

Cited By ~ 29

Author(s):

James Kacmar ◽

Abdelqader Zamamiri ◽

Ross Carlson ◽

Nicholas R Abu-Absi ◽

Friedrich Srienc

Keyword(s):

Saccharomyces Cerevisiae ◽

Flow Cytometry ◽

Single Cell ◽

Cell Populations

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Single-cell RNA-seq analysis of human CSF microglia and myeloid cells in neuroinflammation

Neurology Neuroimmunology & Neuroinflammation ◽

10.1212/nxi.0000000000000732 ◽

2020 ◽

Vol 7 (4) ◽

pp. e732 ◽

Cited By ~ 6

Author(s):

Ekaterina Esaulova ◽

Claudia Cantoni ◽

Irina Shchukina ◽

Konstantin Zaitsev ◽

Robert C. Bucelli ◽

...

Keyword(s):

Gene Expression ◽

Flow Cytometry ◽

High Resolution ◽

Single Cell ◽

Gene Expression Analysis ◽

Myeloid Cell ◽

Cell Populations ◽

Cell Gene Expression ◽

Cell Gene ◽

Resolution Single

ObjectiveTo identify and characterize myeloid cell populations within the CSF of patients with MS and anti-myelin oligodendrocyte glycoprotein (MOG) disorder by high-resolution single-cell gene expression analysis.MethodsSingle-cell RNA sequencing (scRNA-seq) was used to profile individual cells of CSF and blood from 2 subjects with relapsing-remitting MS (RRMS) and one with anti-MOG disorder. Publicly available scRNA-seq data from the blood and CSF of 2 subjects with HIV were also analyzed. An informatics pipeline was used to cluster cell populations by transcriptomic profiling. Based on gene expression by CSF myeloid cells, a flow cytometry panel was devised to examine myeloid cell populations from the CSF of 11 additional subjects, including individuals with RRMS, anti-MOG disorder, and control subjects without inflammatory demyelination.ResultsCommon myeloid populations were identified within the CSF of subjects with RRMS, anti-MOG disorder, and HIV. These included monocytes, conventional and plasmacytoid dendritic cells, and cells with a transcriptomic signature matching microglia. Microglia could be discriminated from other myeloid cell populations in the CSF by flow cytometry.ConclusionsHigh-resolution single-cell gene expression analysis clearly distinguishes distinct myeloid cell types present within the CSF of subjects with neuroinflammation. A population of microglia exists within the human CSF, which is detectable by surface protein expression. The function of these cells during immunity and disease requires further investigation.

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Gene expression markers of Tumor Infiltrating Leukocytes

10.1101/068940 ◽

2016 ◽

Cited By ~ 5

Author(s):

Patrick Danaher ◽

Sarah Warren ◽

Lucas Dennis ◽

Leonard D’Amico ◽

Andrew White ◽

...

Keyword(s):

Gene Expression ◽

Flow Cytometry ◽

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Expression Patterns ◽

Cell Populations ◽

Marker Genes ◽

Cell Type ◽

Single Cell Type

AbstractBackgroundAssays of the abundance of immune cell populations in the tumor microenvironment promise to inform immune oncology research and the choice of immunotherapy for individual patients. We propose to measure the intratumoral abundance of various immune cells populations with gene expression. In contrast to IHC and flow cytometry, gene expression assays yield high information content from a clinically practical workflow. Previous studies of gene expression in purified immune cells have reported hundreds of genes showing enrichment in a single cell type, but the utility of these genes in tumor samples is unknown. We describe a novel statistical method for using co-expression patterns in large tumor gene expression datasets to validate previously reported candidate cell type marker genes, and we use this method to winnow previously published gene lists down to a subset of high confidence marker genes.MethodsWe use co-expression patterns in 9986 samples from The Cancer Genome Atlas (TCGA) to validate previously reported cell type marker genes. We compare immune cell scores derived from these genes to measurements from flow cytometry and immunohistochemistry. We characterize the reproducibility of our cell scores in replicate runs of RNA extracted from FFPE tumor tissue.ResultsWe identify a list of 60 marker genes whose expression levels quantify 14 immune cell populations. Cell type scores calculated from these genes are concordant with flow cytometry and IHC readings, show high reproducibility in replicate RNA samples from FFPE tissue, and reveal an intricate picture of the immune infiltrate in TCGA. Most genes previously reported to be enriched in a single cell type have co-expression patterns inconsistent with cell type specificity.ConclusionsDue to their concise gene set, computational simplicity and utility in tumor samples, these cell type gene signatures may be useful in future discovery research and clinical trials to understand how tumors and therapeutic intervention shape the immune response.

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Flow cytometry analysis of epithelial cell populations from touch samples using the BD Influx flow cytometry platform

F1000Research ◽

10.12688/f1000research.8338.1 ◽

2016 ◽

Vol 5 ◽

pp. 390 ◽

Cited By ~ 1

Author(s):

Ye Jin Kwon ◽

Cristina E. Stanciu ◽

M. Katherine Philpott ◽

Christopher J. Ehrhardt

Keyword(s):

Flow Cytometry ◽

Optical Properties ◽

Epithelial Cell ◽

Genetic Analysis ◽

Epidermal Cell ◽

Cell Populations ◽

Single Source ◽

Flow Cytometry Analysis ◽

Physical Separation ◽

Genetic Profiles

‘Touch’ or trace cell mixtures submitted as evidence are a significant problem for forensic laboratories as they can render resulting genetic profiles difficult or even impossible to interpret. Optical signatures that distinguish epidermal cell populations from different contributors could facilitate the physical separation of mixture components prior to genetic analysis, and potentially the downstream production of single source profiles and/or simplified mixtures. For this dataset, optical properties including forwards scatter (FSC), side scatter (SSC), and fluorescence emissions in the Allophycocyanin (APC) channel were measured in epithelial cell populations from touch samples collected from several different contributors on multiple days to assess inter- and intra-contributor variability.

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