Showing papers by "Garry P. Nolan published in 2014"

Multiplexed ion beam imaging of human breast tumors

Abstract: Immunohistochemistry (IHC) is a tool for visualizing protein expression that is employed as part of the diagnostic workup for the majority of solid tissue malignancies. Existing IHC methods use antibodies tagged with fluorophores or enzyme reporters that generate colored pigments. Because these reporters exhibit spectral and spatial overlap when used simultaneously, multiplexed IHC is not routinely used in clinical settings. We have developed a method that uses secondary ion mass spectrometry to image antibodies tagged with isotopically pure elemental metal reporters. Multiplexed ion beam imaging (MIBI) is capable of analyzing up to 100 targets simultaneously over a five-log dynamic range. Here, we used MIBI to analyze formalin-fixed, paraffin-embedded human breast tumor tissue sections stained with ten labels simultaneously. The resulting data suggest that MIBI can provide new insights into disease pathogenesis that will be valuable for basic research, drug discovery and clinical diagnostics.

Automated identification of stratifying signatures in cellular subpopulations

Abstract: Elucidation and examination of cellular subpopulations that display condition-specific behavior can play a critical contributory role in understanding disease mechanism, as well as provide a focal point for development of diagnostic criteria linking such a mechanism to clinical prognosis. Despite recent advancements in single-cell measurement technologies, the identification of relevant cell subsets through manual efforts remains standard practice. As new technologies such as mass cytometry increase the parameterization of single-cell measurements, the scalability and subjectivity inherent in manual analyses slows both analysis and progress. We therefore developed Citrus (cluster identification, characterization, and regression), a data-driven approach for the identification of stratifying subpopulations in multidimensional cytometry datasets. The methodology of Citrus is demonstrated through the identification of known and unexpected pathway responses in a dataset of stimulated peripheral blood mononuclear cells measured by mass cytometry. Additionally, the performance of Citrus is compared with that of existing methods through the analysis of several publicly available datasets. As the complexity of flow cytometry datasets continues to increase, methods such as Citrus will be needed to aid investigators in the performance of unbiased—and potentially more thorough—correlation-based mining and inspection of cell subsets nested within high-dimensional datasets.

Clinical recovery from surgery correlates with single-cell immune signatures.

Abstract: Delayed recovery from surgery causes personal suffering and substantial societal and economic costs. Whether immune mechanisms determine recovery after surgical trauma remains ill-defined. Single-cell mass cytometry was applied to serial whole-blood samples from 32 patients undergoing hip replacement to comprehensively characterize the phenotypic and functional immune response to surgical trauma. The simultaneous analysis of 14,000 phosphorylation events in precisely phenotyped immune cell subsets revealed uniform signaling responses among patients, demarcating a surgical immune signature. When regressed against clinical parameters of surgical recovery, including functional impairment and pain, strong correlations were found with STAT3 (signal transducer and activator of transcription), CREB (adenosine 3′,5′-monophosphate response element–binding protein), and NF-κB (nuclear factor κB) signaling responses in subsets of CD14 + monocytes ( R = 0.7 to 0.8, false discovery rate

Conditional density-based analysis of T cell signaling in single-cell data

Abstract: Cellular circuits sense the environment, process signals, and compute decisions using networks of interacting proteins. To model such a system, the abundance of each activated protein species can be described as a stochastic function of the abundance of other proteins. High-dimensional single-cell technologies, such as mass cytometry, offer an opportunity to characterize signaling circuit-wide. However, the challenge of developing and applying computational approaches to interpret such complex data remains. Here, we developed computational methods, based on established statistical concepts, to characterize signaling network relationships by quantifying the strengths of network edges and deriving signaling response functions. In comparing signaling between naive and antigen-exposed CD4(+) T lymphocytes, we find that although these two cell subtypes had similarly wired networks, naive cells transmitted more information along a key signaling cascade than did antigen-exposed cells. We validated our characterization on mice lacking the extracellular-regulated mitogen-activated protein kinase (MAPK) ERK2, which showed stronger influence of pERK on pS6 (phosphorylated-ribosomal protein S6), in naive cells as compared with antigen-exposed cells, as predicted. We demonstrate that by using cell-to-cell variation inherent in single-cell data, we can derive response functions underlying molecular circuits and drive the understanding of how cells process signals.

Transient partial permeabilization with saponin enables cellular barcoding prior to surface marker staining.

Abstract: Fluorescent cellular barcoding and mass-tag cellular barcoding are cytometric methods that enable high sample throughput, minimize inter-sample variation, and reduce reagent consumption. Previously employed barcoding protocols require that barcoding be performed after surface marker staining, complicating combining the technique with measurement of alcohol-sensitive surface epitopes. This report describes a method of barcoding fixed cells after a transient partial permeabilization with 0.02% saponin that results in efficient and consistent barcode staining with fluorescent or mass-tagged reagents while preserving surface marker staining. This approach simplifies barcoding protocols and allows direct comparison of surface marker staining of multiple samples without concern for variations in the antibody cocktail volume, antigen-antibody ratio, or machine sensitivity. Using this protocol, cellular barcoding can be used to reliably detect subtle differences in surface marker expression.

Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.

Abstract: In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template – used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.

Single-cell mass cytometry of TCR signaling: Amplification of small initial differences results in low ERK activation in NOD mice

Abstract: Signaling from the T-cell receptor (TCR) conditions T-cell differentiation and activation, requiring exquisite sensitivity and discrimination Using mass cytometry, a high-dimensional technique that can probe multiple signaling nodes at the single-cell level, we interrogate TCR signaling dynamics in control C57BL/6 and autoimmunity-prone nonobese diabetic (NOD) mice, which show ineffective ERK activation after TCR triggering By quantitating signals at multiple steps along the signaling cascade and parsing the phosphorylation level of each node as a function of its predecessors, we show that a small impairment in initial pCD3ζ activation resonates farther down the signaling cascade and results in larger defects in activation of the ERK1/2–S6 and IκBα modules This nonlinear property of TCR signaling networks, which magnifies small initial differences during signal propagation, also applies in cells from B6 mice activated at different levels of intensity Impairment in pCD3ζ and pSLP76 is not a feedback consequence of a primary deficiency in ERK activation because no proximal signaling defect was observed in Erk2 KO T cells These defects, which were manifest at all stages of T-cell differentiation from early thymic pre-T cells to memory T cells, may condition the imbalanced immunoregulation and tolerance in NOD T cells More generally, this amplification of small initial differences in signal intensity may explain how T cells discriminate between closely related ligands and adopt strongly delineated cell fates

Multiplexed imaging of tissues using mass tags and secondary ion mass spectrometry

Abstract: A method of generating a high resolution two-dimensional image of a sample comprising cells and extracellular structures is provided. In certain embodiments, the method comprises: labeling a sample with at least one mass tag, thereby producing a labeled sample; scanning the sample with a secondary ion mass spectrometer (SIMS) ion beam to generate a data set that comprises spatially-addressable measurements of the abundance of the mass tag across an area of the sample; and outputting the data set. In many embodiments, the data set contains the identity and abundance of the mass tag. A system for performing the method is also provided.

Antigen-Dependent Integration of Opposing Proximal TCR-Signaling Cascades Determines the Functional Fate of T Lymphocytes

Abstract: T cell anergy is a key tolerance mechanism to mitigate unwanted T cell activation against self by rendering lymphocytes functionally inactive following Ag encounter. Ag plays an important role in anergy induction where high supraoptimal doses lead to the unresponsive phenotype. How T cells "measure" Ag dose and how this determines functional output to a given antigenic dose remain unclear. Using multiparametric phospho-flow and mass cytometry, we measured the intracellular phosphorylation-dependent signaling events at a single-cell resolution and studied the phosphorylation levels of key proximal human TCR activation- and inhibition-signaling molecules. We show that the intracellular balance and signal integration between these opposing signaling cascades serve as the molecular switch gauging Ag dose. An Ag density of 100 peptide-MHC complexes/cell was found to be the transition point between dominant activation and inhibition cascades, whereas higher Ag doses induced an anergic functional state. Finally, the neutralization of key inhibitory molecules reversed T cell unresponsiveness and enabled maximal T cell functions, even in the presence of very high Ag doses. This mechanism permits T cells to make integrated "measurements" of Ag dose that determine subsequent functional outcomes.

Mass Cytometry to Decipher the Mechanism of Nongenetic Drug Resistance in Cancer

Abstract: Nongenetic resistance has recently been described as a major impediment to effective cancer therapy. Nongenetic resistance is challenging to study since it occurs nonuniformly, even in cell lines, and can involve the interplay of multiple survival pathways. Until recently, no technology allowed measurement of large-scale alterations in survival pathways with single-cell resolution. Mass cytometry, a flow-based technique in which the activation of up to 50 proteins can be measured simultaneously in single-cell, now provides the ability to examine nongenetic resistance on the functional level on a cell-by-cell basis. The application of mass cytometry, in combination with new bioinformatic techniques, will allow fundamental questions on nongenetic resistance to be addressed: Is resistance caused by selection of cells with a pre-existing survival phenotype or induction of a survival program? Which survival pathways are necessary for nongenetic resistance and how do they interact? Currently, mass cytometry is being used to investigate the mechanism of nongenetic resistance to TRAIL-induced apoptosis. The approaches being developed to understand resistance to TRAIL will likely be applied to elucidate the mechanisms of nongenetic resistance broadly and in the clinic.

High-Dimensional Single Cell Analysis

Abstract: Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a ‘‘single-cell systems biology’’ view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell–cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy. J. M. Irish (&) D. B. Doxie Vanderbilt University, Nashville, TN, USA e-mail: jonathan.irish@vanderbilt.edu Current Topics in Microbiology and Immunology (2014) 377: 1–21 1 DOI: 10.1007/82_2014_367 Springer-Verlag Berlin Heidelberg 2014 Published Online: 27 March 2014

Metal-Based Covalent Viability Reagent for Single Cell Analysis

Abstract: The present invention provides a robust viability stain for methods utilizing elemental analysis. A population of cells is contacted with an effective dose of a non-chelated biomacromolecule-reactive metal derivative, which selectively crosses the plasma membrane of non-viable cells, and which covalently modifies a biological macromolecule within the cell, for a period of time sufficient to permit entry into non-viable cells. The population of cells is then washed free of unbound viability reagent; and the presence of the metal within the cells is detected, wherein non-viable cells are selectively labeled with the viability reagent.

High-dimensional single cell analysis : mass cytometry, multi-parametric flow cytometry and bioinformatic techniques

Abstract: High Dimensional Single Cell Cancer Biology.- Studying the Human Immunome: The Complexity of Comprehensive Leukocyte Immunophenotyping.- High-dimensional Analysis of Human CD8+ T Cell Phenotype, Function and Antigen-Specificity.- Mass Cytometry to Decipher the Mechanism of Non-genetic Drug Resistance in Cancer.- A Practical Guide to Multiplexed Mass Cytometry.- Analysis of Protein Interactions in situ by Proximity Ligation Assays.- Cytobank: Providing an Analytics Platform for Community Cytometry Data Analysis and Collaboration.- Computational Analysis of High-Dimensional Flow Cytometric Data for Diagnosis and Discovery.- Shooting Movies of Signaling Network Dynamics with Multiparametric Cytometry.- Hyperspectral Cytometry.