Flow Cytometry: An Overview

McKinnon, Katherine

doi:10.1002/cpim.40

Cited by 535 publications

(378 citation statements)

References 7 publications

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“…As Mtb is a strict human pathogen, there is also an advantage to study Mtb in humanized model systems. Flow cytometry is a powerful technology that offers the possibility to assess multiple phenotypic and functional characteristics of single cells in suspension 22 , something that could be fairly challenging with adherent cells such as macrophages that are also known to be autofluorescent 23 , 24 . In addition to chemical detachment…”

Section: Introductionmentioning

confidence: 99%

Polarization of M1 and M2 Human Monocyte-Derived Cells and Analysis with Flow Cytometry upon <em>Mycobacterium tuberculosis</em> Infection

Mily

Kalsum

Loreti

et al. 2020

JoVE

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Human macrophages are primary host cells of intracellular Mycobacterium tuberculosis (Mtb) infection and thus have a central role in immune control of tuberculosis (TB). We have established an experimental protocol to follow immune polarization of myeloid-derived cells into M1 (classically activated) or M2 (alternatively activated) macrophage-like cells through assessment with a 10-color flow cytometry panel that allows visualization and deep-characterization of green-fluorescent-protein (GFP)-labeled Mtb in diverse macrophages subsets. Monocytes obtained from healthy blood donors were polarized into M1 or M2 cells using differentiation with granulocyte macrophage-colony-stimulating factor (GM-CSF) or macrophage-colony stimulating factor (M-CSF) followed by polarization with IFN-γ and lipopolysaccharide (LPS) or IL-4, respectively. Fully polarized M1 and M2 cells were infected with Mtb-GFP for 4 hours before detached Mtb-infected macrophages were stained with flow cytometry at 4-or 24-hours post-infection. Sample acquisition was performed with flow cytometry and the data was analyzed using a flow cytometry analysis software. Manual gating as well as dimensionality reduction with Uniform Manifold Approximation and Projection (UMAP) and phenograph analysis was performed. This protocol resulted in effective M1/M2 polarization characterized by elevated levels of CD64, CD86, TLR2, HLA-DR and CCR7 on uninfected M1 cells, while uninfected M2 cells exhibited a strong upregulation of the M2 phenotype markers CD163, CD200R, CD206 and CD80. M1polarized cells typically contained fewer bacteria compared to M2-polarized cells. Several M1/M2 markers were downregulated after Mtb infection, which suggests that Mtb can modulate macrophage polarization. In addition, 24 different cell clusters of different sizes were found to be uniquely distributed among the M1 and M2 uninfected

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Section: Introductionmentioning

confidence: 99%

Polarization of M1 and M2 Human Monocyte-Derived Cells and Analysis with Flow Cytometry upon <em>Mycobacterium tuberculosis</em> Infection

Mily

Kalsum

Loreti

et al. 2020

JoVE

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“…For instance in the developing neocortex it was shown that dynamic waves of transcriptional programs drive neuronal differentiation and temporal patterning (Telley et al, 2019;Telley et al, 2016). Given that scRNA-Seq detects mRNA, flow cytometry represents a useful complementary approach that allows multiparametric analyses of large numbers of cells at single cell resolution, allowing the detection of proteins or DNA content (McKinnon, 2018). In addition, flow cytometry provides quantitative data at population level that is complementary to clonal analyses performed in the developing neocortex that provide quantitative information on clone size and composition (Beattie et al, 2020;Gao et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Population Dynamics and Neuronal Polyploidy in the Developing Neocortex

Jungas

Joseph

Fawal

et al. 2020

Preprint

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SUMMARYThe mammalian neocortex is composed of different subtypes of neurons which are generated during embryogenesis by sequential differentiation of neural progenitors. While molecular mechanisms that control neuronal production in the developing neocortex have been extensively studied, the dynamics and absolute numbers of the different progenitor and neuronal populations are still poorly characterized. Here we describe a medium throughput approach based on flow cytometry and well known identity markers of cortical subpopulations to collect quantitative data over the course of mouse neocortex development. We collected a complete dataset in a physiological developmental context on two progenitor and two neuron populations, including relative proportions and absolute numbers. Our study reveals unexpected numbers of progenitors. In addition, we discovered that a fraction of neurons in the developing mouse neocortex are polyploid.

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“…They are generally used to quantify DNA and to observe cells distribution during the cell cycle (Propidium Iodide, 7-Aminoactinomycin D or 7-AAD, DyeCycle Violet, 4 ,6-Diamidino-2-phenylindole or DAPI, Hoescht 33342), to estimate cell viability (PI, DAPI), to isolate chromosomes for sorting (Hoescht 33342, Chromomycin A3), to quantify apoptotic cell fractional DNA content (Acridine Orange or AO, 7-AAD), etc. [109,110] These dyes are frequently used for cell migration and tracking analysis due to their high retention. Nevertheless, DNA-binding dyes are not applicable for proliferation analysis because the content (and intensity) of the dye decreases after each cell cycle [111].…”

Section: Cell Tracking Dyesmentioning

confidence: 99%

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches

Voronin

Kozlova

Verkhovskii

et al. 2020

IJMS

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Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection of rare pathogenic objects in patient blood. These objects can be circulating tumor cells, very rare during the early stages of cancer development, various microorganisms and parasites in the blood during acute blood infections. All of these rare diagnostic objects can be detected and identified very rapidly to save a patient’s life. This review outlines the main techniques of visualization of rare objects in the blood flow, methods for extraction of such objects from the blood flow for further investigations and new approaches to identify the objects automatically with the modern deep learning methods.

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Flow Cytometry: An Overview

Cited by 535 publications

References 7 publications

Polarization of M1 and M2 Human Monocyte-Derived Cells and Analysis with Flow Cytometry upon <em>Mycobacterium tuberculosis</em> Infection

Polarization of M1 and M2 Human Monocyte-Derived Cells and Analysis with Flow Cytometry upon <em>Mycobacterium tuberculosis</em> Infection

Population Dynamics and Neuronal Polyploidy in the Developing Neocortex

Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches

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