Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

Bodenmiller, Bernd; Zunder, Eli R.; Finck, Rachel; Chen, Tiffany J.; Savig, Erica S.; Bruggner, Robert V.; Simonds, Erin F.; Bendall, Sean C.; Sachs, Karen; Krutzik, Peter O.; Nolan, Garry P.

doi:10.1038/nbt.2317

Cited by 519 publications

(575 citation statements)

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“…This approach uses FACS to simultaneously measure dozens of antibody labeled proteins on the surface of individual cells, permitting interrogation of the protein milieu expressed on the plasma membrane (Bendall et al, 2011;Bodenmiller et al, 2012;Doerr, 2011). Adaptation of this method to cell preparations from postmortem brain may be challenging, as important elements found in the CNS (such as dendrites and axons) are difficult to preserve when processing or dissociating brain tissue.…”

Section: Fluorescence Activated Cell Sorting (Facs) and Single-cell Mmentioning

confidence: 99%

Postmortem Brain: An Underutilized Substrate for Studying Severe Mental Illness

McCullumsmith

Hammond

Shan

et al. 2013

Neuropsychopharmacol

107

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We propose that postmortem tissue is an underutilized substrate that may be used to translate genetic and/or preclinical studies, particularly for neuropsychiatric illnesses with complex etiologies. Postmortem brain tissues from subjects with schizophrenia have been extensively studied, and thus serve as a useful vehicle for illustrating the challenges associated with this biological substrate. Schizophrenia is likely caused by a combination of genetic risk and environmental factors that combine to create a disease phenotype that is typically not apparent until late adolescence. The complexity of this illness creates challenges for hypothesis testing aimed at understanding the pathophysiology of the illness, as postmortem brain tissues collected from individuals with schizophrenia reflect neuroplastic changes from a lifetime of severe mental illness, as well as treatment with antipsychotic medications. While there are significant challenges with studying postmortem brain, such as the postmortem interval, it confers a translational element that is difficult to recapitulate in animal models. On the other hand, data derived from animal models typically provide specific mechanistic and behavioral measures that cannot be generated using human subjects. Convergence of these two approaches has led to important insights for understanding molecular deficits and their causes in this illness. In this review, we discuss the problem of schizophrenia, review the common challenges related to postmortem studies, discuss the application of biochemical approaches to this substrate, and present examples of postmortem schizophrenia studies that illustrate the role of the postmortem approach for generating important new leads for understanding the pathophysiology of severe mental illness.

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Section: Fluorescence Activated Cell Sorting (Facs) and Single-cell Mmentioning

confidence: 99%

Postmortem Brain: An Underutilized Substrate for Studying Severe Mental Illness

McCullumsmith

Hammond

Shan

et al. 2013

Neuropsychopharmacol

107

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“…1A). SPADE is a clustering method developed to analyze and visualize highdimensional cytometry data (27,57,(59)(60)(61)(62)(63)(64). It includes an initial density-based down-sampling step performed to preserve cells of rare phenotypes, and it organizes cells into hierarchies of related phenotypes.…”

Section: Multiparametric Spade Clustering To Group B Cells Based On Pmentioning

confidence: 99%

Identification of Vaccine-Altered Circulating B Cell Phenotypes Using Mass Cytometry and a Two-Step Clustering Analysis

Pejoski¹,

Tchitchek²,

Pozo³

et al. 2016

The Journal of Immunology

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Broadening our understanding of the abundance and phenotype of B cell subsets that are induced or perturbed by exogenous Ags will improve the vaccine evaluation process. Mass cytometry (CyTOF) is being used to increase the number of markers that can be investigated in single cells, and therefore characterize cell phenotype at an unprecedented level. We designed a panel of CyTOF Abs to compare the B cell response in cynomolgus macaques at baseline, and 8 and 28 d after the second homologous immunization with modified vaccinia virus Ankara. The spanning-tree progression analysis of density-normalized events (SPADE) algorithm was used to identify clusters of CD20+ B cells. Our data revealed the phenotypic complexity and diversity of circulating B cells at steady-state and significant vaccine-induced changes in the proportions of some B cell clusters. All SPADE clusters, including those altered quantitatively by vaccination, were characterized phenotypically and compared using double hierarchical clustering. Vaccine-altered clusters composed of previously described subsets including CD27hiCD21lo activated memory and CD27+CD21+ resting memory B cells, and subphenotypes with novel patterns of marker coexpression. The expansion, followed by the contraction, of a single memory B cell SPADE cluster was positively correlated with serum anti-vaccine Ab titers. Similar results were generated by a different algorithm, automatic classification of cellular expression by nonlinear stochastic embedding. In conclusion, we present an in-depth characterization of B cell subphenotypes and proportions, before and after vaccination, using a two-step clustering analysis of CyTOF data, which is suitable for longitudinal studies and B cell subsets and biomarkers discovery.

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“…In contrast, the output of SPADE are small clusters of cells arranged in branches in a dendrogram, which has proven to be useful for the visualization of differences in the expression level of functional markers between different sample groups (e.g. phospho-epitopes, not used in this example) [29]. Additionally, these two methods provide a more unbiased way to analyze and compare this high-dimensional cytometry dataset, as in contrast to manual analysis they are not dependent on previous knowledge.…”

Section: End Of Gating -A Practical Examplementioning

confidence: 99%

“…As a consequence, several runs of SPADE will result in differently organized trees, which should be kept in mind when applying SPADE. While the organization of the tree at each individual run might appear distinct, the identified populations have been found to be comparable across several runs.SPADE has been used in several publications [25,[28][29][30], mostly to give an instant overview of different immune populations and their expression of surface markers or intracellular signaling molecules. SPADE is available as a Bioconductor package (CytoSPADE), which can be used through a standard command line interface or through an interactive graphical user interface available as a plugin for the Cytospace Network Visualization Platform (www.cytospace.org).…”

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confidence: 99%

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

et al. 2015

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Ever since its invention half a century ago, flow cytometry has been a major tool for single-cell analysis, fueling advances in our understanding of a variety of complex cellular systems, in particular the immune system. The last decade has witnessed significant technical improvements in available cytometry platforms, such that more than 20 parameters can be analyzed on a single-cell level by fluorescence-based flow cytometry. The advent of mass cytometry has pushed this limit up to, currently, 50 parameters. However, traditional analysis approaches for the resulting high-dimensional datasets, such as gating on bivariate dot plots, have proven to be inefficient. Although a variety of novel computational analysis approaches to interpret these datasets are already available, they have not yet made it into the mainstream and remain largely unknown to many immunologists. Therefore, this review aims at providing a practical overview of novel analysis techniques for high-dimensional cytometry data including SPADE, t-SNE, Wanderlust, Citrus, and PhenoGraph, and how these applications can be used advantageously not only for the most complex datasets, but also for standard 14-parameter cytometry datasets. Keywords: Citrus CyTOF Data analysis Flow cytometry Mass cytometry PSM PhenoGraph SPADE t-SNE WanderlustYear 2015 marked the 50-year anniversary of the publication of the first cell sorter, a device that was able to separate cells in suspension based on their difference in volume [1], as well as the first cytometry-based cell analyzer [2]. Shortly after that, the first sorter that could discriminate cells based on fluorescence was developed [3,4], and this seminal work marked the advent of flow cytometry as a widely used, single-cell analysis technique driving the identification of all major immune cell subsets known today [3,5] (for an overview, see Fig. 1, top). These days, many laboratories are equipped with flow cytometers capable of detecting 10-20 parameters [6], revealing an ever-increasing diversity within established cellular subsets, such as CD4 + T-helper cells or professional APCs. Quite recently, an alternative cytometry-based technique has been developed that relies on antibodies labeled with heavyCorrespondence: Prof. Burkhard Becher e-mail: becher@immunology.uzh.ch metal isotopes instead of fluorophores, detecting the resulting signals using a time-of-flight detector as is done in atomic mass spectrometers [7][8][9]. This method has been termed "mass cytometry" and became commercially known as the "CyTOF" (cytometry by time-of-flight), allowing the theoretical detection of more than 100 parameters per cell.While both fluorescence-based flow cytometry as well as mass cytometry provide a technological platform to interrogate the immune system at a previously unprecedented level (for a comparison of the two techniques see [10]), scientific progress depends on our ability to analyze and comprehend the resulting data in a meaningful way. Historically, flow cytometric data were-and still is-analyzed using a se...

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Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators

Cited by 519 publications

References 50 publications

Postmortem Brain: An Underutilized Substrate for Studying Severe Mental Illness

Postmortem Brain: An Underutilized Substrate for Studying Severe Mental Illness

Identification of Vaccine-Altered Circulating B Cell Phenotypes Using Mass Cytometry and a Two-Step Clustering Analysis

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

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