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Open AccessJournal ArticleDOI

Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum

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TLDR
Single-cell “mass cytometry” analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.
Abstract
Flow cytometry is an essential tool for dissecting the functional complexity of hematopoiesis. We used single-cell "mass cytometry" to examine healthy human bone marrow, measuring 34 parameters simultaneously in single cells (binding of 31 antibodies, viability, DNA content, and relative cell size). The signaling behavior of cell subsets spanning a defined hematopoietic hierarchy was monitored with 18 simultaneous markers of functional signaling states perturbed by a set of ex vivo stimuli and inhibitors. The data set allowed for an algorithmically driven assembly of related cell types defined by surface antigen expression, providing a superimposable map of cell signaling responses in combination with drug inhibition. Visualized in this manner, the analysis revealed previously unappreciated instances of both precise signaling responses that were bounded within conventionally defined cell subsets and more continuous phosphorylation responses that crossed cell population boundaries in unexpected manners yet tracked closely with cellular phenotype. Collectively, such single-cell analyses provide system-wide views of immune signaling in healthy human hematopoiesis, against which drug action and disease can be compared for mechanistic studies and pharmacologic intervention.

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Citations
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Journal ArticleDOI

A Continuous Molecular Roadmap to iPSC Reprogramming through Progression Analysis of Single-Cell Mass Cytometry

TL;DR: Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems, which varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry.
Journal ArticleDOI

The end of gating? An introduction to automated analysis of high dimensional cytometry data

TL;DR: A practical overview of novel analysis techniques for high‐dimensional cytometry data including SPADE, t‐SNE, Wanderlust, Citrus, and PhenoGraph are provided and how these applications can be used advantageously not only for the most complex datasets, but also for standard 14‐parameter cytometry datasets.
Journal ArticleDOI

Single-cell mass cytometry for analysis of immune system functional states

TL;DR: This review will cover the basics of mass cytometry as well as outline assays developed for the platform that enhance the immunologist's analytical arsenal.
Journal ArticleDOI

Imaging Mass Cytometry

TL;DR: Imaging Mass Cytometry is an expansion of mass cytometry, but rather than analyzing single cells in suspension, it uses laser ablation to generate plumes of particles that are carried to the mass cytometer by a stream of inert gas.
References
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疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

宁北芳, +1 more
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
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The green fluorescent protein

TL;DR: In just three years, the green fluorescent protein from the jellyfish Aequorea victoria has vaulted from obscurity to become one of the most widely studied and exploited proteins in biochemistry and cell biology.
Journal ArticleDOI

A quantitative analysis of kinase inhibitor selectivity.

TL;DR: This work presents interaction maps for 38 kinase inhibitors across a panel of 317 kinases representing >50% of the predicted human protein kinome and introduces the concept of a selectivity score as a general tool to quantify and differentiate the observed interaction patterns.
Book

Practical Flow Cytometry

TL;DR: Using Flow Cytometers: Applications, Extensions, and Alternatives as mentioned in this paper is an excellent overview of the history of the field of Flow Sorting, its applications, extensions, and alternatives.
Journal ArticleDOI

Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data

TL;DR: Reconstruction of network models from physiologically relevant primary single cells might be applied to understanding native-state tissue signaling biology, complex drug actions, and dysfunctional signaling in diseased cells.
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