A deep profiler's guide to cytometry

Bendall, Sean C.; Nolan, Garry P.; Roederer, Mario; Chattopadhyay, Pratip K.

doi:10.1016/j.it.2012.02.010

Cited by 602 publications

(640 citation statements)

References 63 publications

(83 reference statements)

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“…Up to 15 distinct signaling events can be assayed simultaneously in live cells. Interference between fluorescent probes is an inherent issue with flow cytometry, becoming more acute with an increasing number of assayed parameters in any one experiment (for review see Bendall et al 2012 39 ). Nonspecific antibody interactions within the cell can also be problematic.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

Antibody-based detection of protein phosphorylation status to track the efficacy of novel therapies using nanogram protein quantities from stem cells and cell lines

et al. 2014

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This protocol describes a highly reproducible antibody-based method providing protein level and phosphorylation status information from nanogram quantities of protein cell lysate. Nanocapillary isoelectric focusing (cIEF) combines with UV activated linking chemistry to detect changes in phosphorylation status. We describe how to detect changes in response to tyrosine kinase inhibitors (TKIs) in the phosphorylation status of the adapter protein CrkL a major substrate of the oncogenic tyrosine kinase BCR/ABL in chronic myeloid leukaemia (CML), using highly enriched CML stem cells and mature cell populations in vitro. This protocol provides a 2.5pg/nL limit of protein detection (<0.2% of a stem cell sample containing <10 4 cells). Additional assays are described for pTyr207-CrkL and PTPRC/CD45, developed using this protocol and applied to CML patient samples. This method is high throughput and can act as a screen for in vitro cancer stem cell response to drugs and novel agents. SummaryThis protocol uses a highly sensitive and reproducible antibody-based capillary isoelectric focusing approach to establish protein phosphorylation status from nanogram quantities of protein cell lysate from cell line or primary stem cell material. Is-protocol-to

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Section: Comparison With Other Methodsmentioning

confidence: 99%

Antibody-based detection of protein phosphorylation status to track the efficacy of novel therapies using nanogram protein quantities from stem cells and cell lines

et al. 2014

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“…In contrast, mass cytometry allows up to 42 parameters to be quantified on individual cells using metal-chelated probes without any significant signal overlap, thus resolving cellular phenotypes at an unprecedented level of detail (4). Using this technology, Newell et al recently showed a continuous distribution of human CD8 + T-cell phenotypes and a previously unexpected level of functional diversity among these cells (5).…”

mentioning

confidence: 99%

Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)

Shekhar

Brodin

Davis

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

211

216

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Mass cytometry enables an unprecedented number of parameters to be measured in individual cells at a high throughput, but the large dimensionality of the resulting data severely limits approaches relying on manual "gating." Clustering cells based on phenotypic similarity comes at a loss of single-cell resolution and often the number of subpopulations is unknown a priori. Here we describe ACCENSE, a tool that combines nonlinear dimensionality reduction with density-based partitioning, and displays multivariate cellular phenotypes on a 2D plot. We apply ACCENSE to 35-parameter mass cytometry data from CD8 + T cells derived from specific pathogen-free and germ-free mice, and stratify cells into phenotypic subpopulations. Our results show significant heterogeneity within the known CD8 + T-cell subpopulations, and of particular note is that we find a large novel subpopulation in both specific pathogen-free and germ-free mice that has not been described previously. This subpopulation possesses a phenotypic signature that is distinct from conventional naive and memory subpopulations when analyzed by ACCENSE, but is not distinguishable on a biaxial plot of standard markers. We are able to automatically identify cellular subpopulations based on all proteins analyzed, thus aiding the full utilization of powerful new single-cell technologies such as mass cytometry.immunophenotyping | machine learning | class discovery | CyTOF | FACS

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“…Quando acoplada à espectrometria de massas, esse número pode passar de 36. 37 Em geral, citômetros de fluxo descartam as amostras após a análise, ainda que alguns possam utilizar a técnica de separação de células cuja fluorescência foi previamente ativada (Fuorescence-Activated Cell Sorting, FACS) permitindo a coleta e análise de informações sobre subpopulações, separadamente. Nesse caso, as células das subpopulações podem ser cultivadas isoladamente, ampliando o leque de análises possíveis.…”

Section: Citometria De Fluxounclassified

Como estudar interações entre nanopartículas e sistemas biológicos

et al. 2016

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Recebido em 02/05/2016; aceito em 15/06/2016; publicado na web em 16/08/2016 STUDYING THE INTERACTIONS BETWEEN NANOPARTICLES AND BIOLOGICAL SYSTEMS. Although in recent years there has been an increasing amount of literature on nanotechnology and their clinical applications, it is still scarce a deep understanding of the interactions at the molecular levels between nanoparticles and cells. Studies demonstrating the underlying mechanisms of nanoparticles endocytosis, intracellular trafficking, and cellular processing are imperative to understand better how cells interact with those materials and their possible undesired effects, e.g. nanotoxicity. The rising awareness concerning nanoparticles applications and its interactions with the cellular environment is part of the new research field called Nanotoxicology. The cumulative knowledge in nanotoxicology will allow us to foresee toxic effects, establish regulations and limits for nanoparticles applications. In this work, we discuss the theoretical concepts about studying endocytosis and intracellular trafficking of nanoparticles. The nanoparticles-cell interactions are a multi-step process, which can be divided into nanoparticles' internalization, intracellular processing and triggering effects of nanomaterials on eukaryotic cells. Finally, we discuss the main techniques used to study this process: flow cytometry, use of endocytosis inhibitors and confocal microscopy.Keywords: endocytosis; intracellular trafficking; nanoparticles, nanotoxicology; nano-cell interactions. INTRODUÇÃONanotecnologia é um dos ramos mais promissores de tecnologia, sobre o qual se deposita grandes expectativas. 1 Somente em 2015, foram publicados cerca de 9400 artigos relacionados ao termo "Nanotechnology" no banco de dados Science Direct; além disso, diversos produtos têm sido testados e comercializados, por exemplo, protetores solares, cosméticos, produtos biomédicos, biosensores e sistemas para transporte e entrega de fármacos. 2 Entretanto, há uma crescente preocupação com a segurança e possíveis efeitos nocivos de nanomateriais que vêm sendo desenvolvidos, 3 pois dados e regulamentações internacionais referentes à segurança e uso desses materiais ainda são escassos, ainda estão em debate ou em fase de implementação. 4 Uma nova área da ciência destinada ao estudo de efeitos adversos de nanomateriais foi recentemente criada, a Nanotoxicologia. 5 O conhecimento acumulado nessa área tem como objetivo prever efeitos tóxicos e auxiliar nas regulamentações e diretrizes para aplicação da nanotecnologia 6 e uso de produtos a ela relacionados. A Figura 1 mostra o crescimento do número de artigos científicos que contêm o termo "nanotoxicology" e estão no banco de dados do National Center for Biotechnology Information (NCBI), subdivisão do National Institute of Health (NIH/USA).Apesar do número de artigos em nanotoxicologia ser crescente, esta é uma área ainda muito recente (com menos de uma década), e ainda não é possível determinar exatamente quais impactos os sistemas naturais e artificiais co...

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A deep profiler's guide to cytometry

Cited by 602 publications

References 63 publications

Antibody-based detection of protein phosphorylation status to track the efficacy of novel therapies using nanogram protein quantities from stem cells and cell lines

Antibody-based detection of protein phosphorylation status to track the efficacy of novel therapies using nanogram protein quantities from stem cells and cell lines

Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE)

Como estudar interações entre nanopartículas e sistemas biológicos

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