Search tips
Search criteria

Results 1-25 (37)

Clipboard (0)

Select a Filter Below

Year of Publication
more »
Document Types
1.  A platinum-based covalent viability reagent for single cell mass cytometry 
In fluorescence-based flow cytometry, cellular viability is determined with membrane-impermeable fluorescent reagents that specifically enter and label plasma membrane-compromised non-viable cells. A recent technological advance in flow cytometry uses antibodies conjugated to elemental metal isotopes, rather than to fluorophores, to allow signal detection by atomic mass spectrometry. Unhampered by the limitations of overlapping emission fluorescence, mass cytometry increases the number of parameters that can be measured in single cells. However, mass cytometry is unable to take advantage of current fluorescent viability dyes. An alternative methodology was therefore developed here in which the platinum-containing chemotherapy drug cisplatin was used to label cells for mass cytometry determinations of live/dead ratios. In a one-minute incubation step, cisplatin preferentially labeled non-viable cells, from both adherent and suspension cultures, resulting in a platinum signal quantifiable by mass cytometry. This protocol was compatible with established sample processing steps for cytometry. Furthermore, the live/dead ratios were comparable between mass and fluorescence based cytometry. Importantly, although cisplatin is a known DNA-damaging agent, a one-minute “pulse” of cisplatin did not induce observable DNA damage or apoptotic responses even within 6 hours post-exposure. Cisplatin can therefore be used as a viability reagent for a wide range of mass cytometry protocols.
PMCID: PMC3808967  PMID: 22577098
Mass cytometry; cisplatin; viability reagent
2.  Tyramide signal amplification for analysis of kinase activity by intracellular flow cytometry 
Intracellular flow cytometry permits quantitation of diverse molecular targets at the single-cell level. However, limitations in detection sensitivity inherently restrict the method, sometimes resulting in the inability to measure proteins of very low abundance or to differentiate cells expressing subtly different protein concentrations. To improve these measurements, an enzymatic amplification approach called tyramide signal amplification (TSA) was optimized for assessment of intracellular kinase cascades. First, Pacific Blue, Pacific Orange, and Alexa Fluor 488 tyramide reporters were shown to exhibit low non-specific binding in permeabilized cells. Next, the effects of antibody concentration, tyramide concentration, and reaction time on assay resolution were characterized. Use of optimized TSA resulted in a 10-fold or greater improvement in measurement resolution of endogenous Erk and Stat cell signaling pathways relative to standard, non-amplified detection. TSA also enhanced assay sensitivity and, in conjunction with fluorescent cell barcoding, improved assay performance according to a metric used to evaluate high-throughput drug screens. TSA was used to profile Stat1 phosphorylation in primary immune system cells, which revealed heterogeneity in various populations, including CD4+ FoxP3+ regulatory T cells. We anticipate the approach will be broadly applicable to intracellular flow cytometry assays with low signal-to-noise ratios.
PMCID: PMC3036012  PMID: 20824632
flow cytometry; intracellular flow cytometry; phospho flow; tyramide signal amplification; catalyzed reporter deposition; enzymatic amplification staining; cell signaling; signal transduction; cell-based assay; background
3.  WebFlow: A Software Package for High-Throughput Analysis of Flow Cytometry Data 
Flow cytometry has emerged as a powerful tool for quantitative, single-cell analysis of both surface markers and intracellular antigens, including phosphoproteins and kinase signaling cascades, with the flexibility to process hundreds of samples in multiwell plate format. Quantitative flow cytometric analysis is being applied in many areas of biology, from the study of immunology in animal models or human patients to high-content drug screening of pharmacologically active compounds. However, these experiments generate thousands of data points per sample, each with multiple measured parameters, leading to data management and analysis challenges. We developed WebFlow (, a web server-based software package to manage, analyze, and visualize data from flow cytometry experiments. WebFlow is accessible via standard web browsers and does not require users to install software on their personal computers. The software enables plate-based annotation of large data sets, which provides the basis for exploratory data analysis tools and rapid visualization of multiple different parameters. These tools include custom user-defined statistics to normalize data to other wells or other channels, as well as interactive, user-selectable heat maps for viewing the underlying single-cell data. The web-based approach of WebFlow allows for sharing of data with collaborators or the general public. WebFlow provides a novel platform for quantitative analysis of flow cytometric data from high-throughput drug screening or disease profiling experiments.
PMCID: PMC2956679  PMID: 19187010
4.  Snapin, Positive Regulator of Stimulation- Induced Ca2+ Release through RyR, Is Necessary for HIV-1 Replication in T Cells 
PLoS ONE  2013;8(10):e75297.
To identify critical host factors necessary for human immunodeficiency virus 1 (HIV-1) replication, large libraries of short-peptide-aptamers were expressed retrovirally. The target of one inhibitor peptide, Pep80, identified in this screen was determined to be Snapin, a protein associated with the soluble N-ethyl maleimide sensitive factor adaptor protein receptor (SNARE) complex that is critical for calcium-dependent exocytosis during neurotransmission. Pep80 inhibited Ca2+ release from intracellular stores and blocked downstream signaling by direct interruption of the association between Snapin and an intracellular calcium release channel, the ryanodine receptor (RyR). NFAT signaling was preferentially abolished by Pep80. Expression of Snapin overcame Pep80-mediated inhibition of Ca2+/NFAT signaling and HIV-1 replication. Furthermore, Snapin induced HIV-1 replication in primary CD4+ T cells. Thus, through its interaction with RyR, Snapin is a critical regulator of Ca2+ signaling and T cell activation. Use of the genetically selected intracellular aptamer inhibitors allowed us to define unique mechanisms important to HIV-1 replication and T cell biology.
PMCID: PMC3794929  PMID: 24130701
5.  CytoSPADE: high-performance analysis and visualization of high-dimensional cytometry data 
Bioinformatics  2012;28(18):2400-2401.
Motivation: Recent advances in flow cytometry enable simultaneous single-cell measurement of 30+ surface and intracellular proteins. CytoSPADE is a high-performance implementation of an interface for the Spanning-tree Progression Analysis of Density-normalized Events algorithm for tree-based analysis and visualization of this high-dimensional cytometry data.
Availability: Source code and binaries are freely available at and via Bioconductor version 2.10 onwards for Linux, OSX and Windows. CytoSPADE is implemented in R, C++ and Java.
Supplementary Information: Additional documentation available at
PMCID: PMC3436846  PMID: 22782546
6.  Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators 
Nature biotechnology  2012;30(9):858-867.
The ability to comprehensively explore the impact of bio-active molecules on human samples at the single-cell level can provide great insight for biomedical research. Mass cytometry enables quantitative single-cell analysis with deep dimensionality, but currently lacks high-throughput capability. Here we report a method termed mass-tag cellular barcoding (MCB) that increases mass cytometry throughput by sample multiplexing. 96-well format MCB was used to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics, cell-to-cell communication, the signaling variability between 8 donors, and to define the impact of 27 inhibitors on this system. For each compound, 14 phosphorylation sites were measured in 14 PBMC types, resulting in 18,816 quantified phosphorylation levels from each multiplexed sample. This high-dimensional systems-level inquiry allowed analysis across cell-type and signaling space, reclassified inhibitors, and revealed off-target effects. MCB enables high-content, high-throughput screening, with potential applications for drug discovery, pre-clinical testing, and mechanistic investigation of human disease.
PMCID: PMC3627543  PMID: 22902532
7.  Cytometry by Time-of-Flight Shows Combinatorial Cytokine Expression and Virus-Specific Cell Niches within a Continuum of CD8+ T Cell Phenotypes 
Immunity  2012;36(1):142-152.
Cytotoxic CD8+ T lymphocytes directly kill infected or aberrant cells and secrete proinflammatory cytokines. By using metal-labeled probes and mass spectrometric analysis (cytometry by time-of-flight, or CyTOF) of human CD8+ T cells, we analyzed the expression of many more proteins than previously possible with fluorescent labels, including surface markers, cytokines, and antigen specificity with modified peptide-MHC tetramers. With 3-dimensional principal component analysis (3D-PCA) to display phenotypic diversity, we observed a relatively uniform pattern of variation in all subjects tested, highlighting the interrelatedness of previously described subsets and the continuous nature of CD8+ T cell differentiation. These data also showed much greater complexity in the CD8+ T cell compartment than previously appreciated, including a nearly combinatorial pattern of cytokine expression, with distinct niches occupied by virus-specific cells. This large degree of functional diversity even between cells with the same specificity gives CD8+ T cells a remarkable degree of flexibility in responding to pathogens.
PMCID: PMC3752833  PMID: 22265676
8.  A Deep Profiler’s Guide to Cytometry 
Trends in Immunology  2012;33(7):323-332.
In recent years, advances in technology have provided us with tools to quantify the expression of multiple genes in individual cells. The ability to simultaneously measure multiple genes on the same cell is necessary to resolve the incredible diversity of cell subsets, as well as to define their function in the host. Fluorescence-based flow cytometry is the benchmark for this; with it, we can quantify 18 proteins per cell, at >10,000 cells per second. “Mass cytometry” is a new technology that promises to significantly extend these capabilities. Immunophenotyping by mass spectrometry provides the ability to measure more than three dozen proteins at a rate of 1,000 cells per second. We review these cytometric technologies, capable of high-content, high-throughput single-cell assays.
PMCID: PMC3383392  PMID: 22476049
Fluorescence; Inductively Coupled Plasma Mass Spectrometry; Single Cell Analysis; Immunophenotyping; Data Analysis
9.  Single Cell Mass Cytometry Adapted to Measurements of the Cell Cycle1 
Mass cytometry is a recently introduced technology that utilizes transition element isotope-tagged antibodies for protein detection on a single-cell basis. By circumventing the limitations of emission spectral overlap associated with fluorochromes utilized in traditional flow cytometry, mass cytometry currently allows measurement of up to 40 parameters per cell. Recently a comprehensive mass cytometry analysis was described for the hematopoietic differentiation program in human bone marrow from a healthy donor. The present study describes approaches to delineate cell cycle stages utilizing iododeoxyuridine (IdU) to mark cells in S phase, simultaneously with antibodies against cyclin B1, cyclin A, and phosphorylated histone H3 (S28) that characterize the other cell cycle phases. Protocols were developed in which an antibody against phosphorylated retinoblastoma protein (Rb) at serines 807 and 811 was used to separate cells in G0 and G1 phases of the cell cycle. This mass cytometry method yielded cell cycle distributions of both normal and cancer cell populations that were equivalent to those obtained by traditional fluorescence cytometry techniques. We applied this to map the cell cycle phases of cells spanning the hematopoietic hierarchy in healthy human bone marrow as a prelude to later studies with cancers and other disorders of this lineage.
PMCID: PMC3667754  PMID: 22693166
Mass Cytometry; Cell Cycle; Flow Cytometry; Retinoblastoma; iododeoxyuridine; hematopoiesis
10.  Decoupling of Tumor-Initiating Activity from Stable Immunophenotype In HoxA9-Meis1 Driven AML 
Cell Stem Cell  2012;10(2):210-217.
Increasing evidence suggests tumors are maintained by cancer stem cells; however, their nature remains controversial. In a HoxA9-Meis1 (H9M) model of acute myeloid leukemia (AML), we found that tumor-initiating activity existed in three, immunophenotypically distinct compartments, corresponding to disparate lineages on the normal hematopoietic hierarchy—stem/progenitor cells (Lin−kit+), and committed progenitors of the myeloid (Gr1+kit+) and lymphoid lineages (Lym+kit+). These distinct tumor-initiating cells (TIC) clonally recapitulated the immunophenotypic spectrum of the original tumor in vivo (including cells with a less-differentiated immunophenotype) and shared signaling networks, such that in vivo pharmacologic targeting of conserved TIC survival pathways (DNA methyltransferase and MEK phosphorylation) significantly increased survival. Collectively, H9M AML is organized as an atypical hierarchy that defies the strict lineage marker boundaries and unidirectional differentiation of normal hematopoiesis. Moreover, this suggests that in certain malignancies tumor-initiation activity (or “cancer-stemness”) can represent a cellular state that exists independently of distinct immunophenotypic definition.
PMCID: PMC3273989  PMID: 22305570
11.  COP9 Signalosome Component JAB1/CSN5 Is Necessary for T Cell Signaling through LFA-1 and HIV-1 Replication 
PLoS ONE  2012;7(7):e41725.
To determine critical host factors involved in HIV-1 replication, a dominant effector genetics approach was developed to reveal signaling pathways on which HIV-1 depends for replication. A large library of short peptide aptamers was expressed via retroviral delivery in T cells. Peptides that interfered with T cell activation-dependent processes that might support HIV-1 replication were identified. One of the selected peptides altered signaling, lead to a difference in T cell activation status, and inhibited HIV-1 replication. The target of the peptide was JAB1/CSN5, a component of the signalosome complex. JAB1 expression overcame the inhibition of HIV-1 replication in the presence of peptide and also promoted HIV-1 replication in activated primary CD4+ T cells. This peptide blocked physiological release of JAB1 from the accessory T cell surface protein LFA-1, downstream AP-1 dependent events, NFAT activation, and HIV-1 replication. Thus, genetic selection for intracellular aptamer inhibitors of host cell processes proximal to signals at the immunological synapse of T cells can define unique mechanisms important to HIV-1 replication.
PMCID: PMC3404009  PMID: 22911848
12.  Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE 
Nature biotechnology  2011;29(10):886-891.
Multiparametric single-cell analysis is critical for understanding cellular heterogeneity. Despite recent technological advances in single-cell measurements, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system under investigation. To objectively uncover cellular heterogeneity from single-cell measurements, we present a novel computational approach, Spanning-tree Progression Analysis of Density-normalized Events (SPADE). We applied SPADE to cytometry data of mouse and human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. In addition, SPADE produced a map of intracellular signal activation across the landscape of human hematopoietic development. SPADE revealed a functionally distinct cell population, natural killer (NK) cells, without using any NK-specific parameters. SPADE is a versatile method that facilitates the analysis of cellular heterogeneity, the identification of cell types, and comparison of functional markers in response to perturbations.
PMCID: PMC3196363  PMID: 21964415
13.  Structural linkage between ligand discrimination and receptor activation by type I interferons 
Cell  2011;146(4):621-632.
Type I Interferons (IFNs) are important cytokines for innate immunity against viruses and cancer. Sixteen human IFN variants signal through the same cell surface receptors, IFNAR1 and IFNAR2, yet they can evoke markedly different physiological effects. The crystal structures of two human type I IFN ternary signaling complexes containing IFNα2 and IFNω reveal recognition modes and heterotrimeric architectures that are unique amongst the cytokine receptor superfamily, but conserved between different type I IFNs. Receptor-ligand cross-reactivity is enabled by conserved receptor-ligand "anchor-points" interspersed amongst ligand-specific interactions that ‘tune’ the relative IFN binding affinities, in an apparent extracellular ‘ligand proofreading’ mechanism that modulates biological activity. Functional differences between IFNs are linked to their respective receptor recognition chemistries, in concert with a ligand-induced conformational change in IFNAR1, that collectively control signal initiation and complex stability, ultimately regulating differential STAT phosphorylation profiles, receptor internalization rates, and downstream gene expression patterns.
PMCID: PMC3166218  PMID: 21854986
14.  Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum 
Science (New York, N.y.)  2011;332(6030):687-696.
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.
PMCID: PMC3273988  PMID: 21551058
15.  Fluorescent Cell Barcoding for Multiplex Flow Cytometry 
Fluorescent Cell Barcoding (FCB) enables high throughput, i.e. high content flow cytometry by multiplexing samples prior to staining and acquisition on the cytometer. Individual cell samples are barcoded, or labeled, with unique signatures of fluorescent dyes so that they can be mixed together, stained, and analyzed as a single sample. By mixing samples prior to staining, antibody consumption is typically reduced 10 to 100-fold. In addition, data robustness is increased through the combination of control and treated samples, which minimizes pipetting error, staining variation, and the need for normalization. Finally, speed of acquisition is enhanced, enabling large profiling experiments to be run with standard cytometer hardware. In this unit, we outline the steps necessary to apply the FCB method to cell lines as well as primary peripheral blood samples. Important technical considerations such as choice of barcoding dyes, concentrations, labeling buffers, compensation, and software analysis are discussed.
PMCID: PMC3036011  PMID: 21207359
flow cytometry; multiplex; barcode; fluorescence; dye; high throughput
16.  Mammalian target of rapamycin controls dendritic cell development downstream of Flt3 ligand signaling 
Immunity  2010;33(4):597-606.
Dendritic cells (DCs) comprise distinct functional subsets including CD8− and CD8+ classical DCs (cDCs) and interferon-secreting plasmacytoid DCs (pDCs). The cytokine Flt3 ligand (Flt3L) controls the development of DCs, and is particularly important for the pDC, CD8+ cDC and their CD103+ tissue counterparts. We report that mammalian target of rapamycin (mTOR) inhibitor rapamycin impaired Flt3L-driven DC development in vitro, with the pDCs and CD8+-like cDCs most profoundly affected. Conversely, deletion of the phosphoinositide 3-kinase (PI3K)-mTOR negative regulator Pten facilitated Flt3L-driven DC development in culture. DC-specific Pten targeting in vivo caused the expansion of CD8+ and CD103+ cDC numbers, which was reversible by rapamycin. The increased CD8+ cDC numbers caused by Pten deletion correlated with increased susceptibility to the intracellular pathogen Listeria. Thus, PI3K-mTOR signaling downstream of Flt3L controls DC development, and its restriction by Pten ensures optimal DC pool size and subset composition.
PMCID: PMC2966531  PMID: 20933441
17.  A regression model approach to enable cell morphology correction in high-throughput flow cytometry 
Large variations in cell size and shape can undermine traditional gating methods for analyzing flow cytometry data. Correcting for these effects enables analysis of high-throughput data sets, including >5000 yeast samples with diverse cell morphologies.
The regression model approach corrects for the effects of cell morphology on fluorescence, as well as an extremely small and restrictive gate, but without removing any of the cells.In contrast to traditional gating, this approach enables the quantitative analysis of high-throughput flow cytometry experiments, since the regression model can compare between biological samples that show no or little overlap in terms of the morphology of the cells.The analysis of a high-throughput yeast flow cytometry data set consisting of >5000 biological samples identified key proteins that affect the time and intensity of the bifurcation event that happens after the carbon source transition from glucose to fatty acids. Here, some yeast cells undergo major structural changes, while others do not.
Flow cytometry is a widely used technique that enables the measurement of different optical properties of individual cells within large populations of cells in a fast and automated manner. For example, by targeting cell-specific markers with fluorescent probes, flow cytometry is used to identify (and isolate) cell types within complex mixtures of cells. In addition, fluorescence reporters can be used in conjunction with flow cytometry to measure protein, RNA or DNA concentration within single cells of a population.
One of the biggest advantages of this technique is that it provides information of how each cell behaves instead of just measuring the population average. This can be essential when analyzing complex samples that consist of diverse cell types or when measuring cellular responses to stimuli. For example, there is an important difference between a 50% expression increase of all cells in a population after stimulation and a 100% increase in only half of the cells, while the other half remains unresponsive. Another important advantage of flow cytometry is automation, which enables high-throughput studies with thousands of samples and conditions. However, current methods are confounded by populations of cells that are non-uniform in terms of size and granularity. Such variability affects the emitted fluorescence of the cell and adds undesired variability when estimating population fluorescence. This effect also frustrates a sensible comparison between conditions, where not only fluorescence but also cell size and granularity may be affected.
Traditionally, this problem has been addressed by using ‘gates' that restrict the analysis to cells with similar morphological properties (i.e. cell size and cell granularity). Because cells inside the gate are morphologically similar to one another, they will show a smaller variability in their response within the population. Moreover, applying the same gate in all samples assures that observed differences between these samples are not due to differential cell morphologies.
Gating, however, comes with costs. First, since only a subgroup of cells is selected, the final number of cells analyzed can be significantly reduced. This means that in order to have sufficient statistical power, more cells have to be acquired, which, if even possible in the first place, increases the time and cost of the experiment. Second, finding a good gate for all samples and conditions can be challenging if not impossible, especially in cases where cellular morphology changes dramatically between conditions. Finally, gating is a very user-dependent process, where both the size and shape of the gate are determined by the researcher and will affect the outcome, introducing subjectivity in the analysis that complicates reproducibility.
In this paper, we present an alternative method to gating that addresses the issues stated above. The method is based on a regression model containing linear and non-linear terms that estimates and corrects for the effect of cell size and granularity on the observed fluorescence of each cell in a sample. The corrected fluorescence thus becomes ‘free' of the morphological effects.
Because the model uses all cells in the sample, it assures that the corrected fluorescence is an accurate representation of the sample. In addition, the regression model can predict the expected fluorescence of a sample in areas where there are no cells. This makes it possible to compare between samples that have little overlap with good confidence. Furthermore, because the regression model is automated, it is fully reproducible between labs and conditions. Finally, it allows for a rapid analysis of big data sets containing thousands of samples.
To probe the validity of the model, we performed several experiments. We show how the regression model is able to remove the morphological-associated variability as well as an extremely small and restrictive gate, but without the caveat of removing cells. We test the method in different organisms (yeast and human) and applications (protein level detection, separation of mixed subpopulations). We then apply this method to unveil new biological insights in the mechanistic processes involved in transcriptional noise.
Gene transcription is a process subjected to the randomness intrinsic to any molecular event. Although such randomness may seem to be undesirable for the cell, since it prevents consistent behavior, there are situations where some degree of randomness is beneficial (e.g. bet hedging). For this reason, each gene is tuned to exhibit different levels of randomness or noise depending on its functions. For core and essential genes, the cell has developed mechanisms to lower the level of noise, while for genes involved in the response to stress, the variability is greater.
This gene transcription tuning can be determined at many levels, from the architecture of the transcriptional network, to epigenetic regulation. In our study, we analyze the latter using the response of yeast to the presence of fatty acid in the environment. Fatty acid can be used as energy by yeast, but it requires major structural changes and commitments. We have observed that at the population level, there is a bifurcation event whereby some cells undergo these changes and others do not. We have analyzed this bifurcation event in mutants for all the non-essential epigenetic regulators in yeast and identified key proteins that affect the time and intensity of this bifurcation. Even though fatty acid triggers major morphological changes in the cell, the regression model still makes it possible to analyze the over 5000 flow cytometry samples in this data set in an automated manner, whereas a traditional gating approach would be impossible.
Cells exposed to stimuli exhibit a wide range of responses ensuring phenotypic variability across the population. Such single cell behavior is often examined by flow cytometry; however, gating procedures typically employed to select a small subpopulation of cells with similar morphological characteristics make it difficult, even impossible, to quantitatively compare cells across a large variety of experimental conditions because these conditions can lead to profound morphological variations. To overcome these limitations, we developed a regression approach to correct for variability in fluorescence intensity due to differences in cell size and granularity without discarding any of the cells, which gating ipso facto does. This approach enables quantitative studies of cellular heterogeneity and transcriptional noise in high-throughput experiments involving thousands of samples. We used this approach to analyze a library of yeast knockout strains and reveal genes required for the population to establish a bimodal response to oleic acid induction. We identify a group of epigenetic regulators and nucleoporins that, by maintaining an ‘unresponsive population,' may provide the population with the advantage of diversified bet hedging.
PMCID: PMC3202802  PMID: 21952134
flow cytometry; high-throughput experiments; statistical regression model; transcriptional noise
Cell host & microbe  2010;8(2):174-185.
Although vaccinia virus infection results in induction of a robust immunizing response, many closely related poxviruses such as variola (smallpox) and ectromelia (mousepox) are highly pathogenic in their natural hosts. We developed a strategy to map the activation of key signaling networks in vivo and applied this approach to define and compare the earliest signaling events elicited by poxvirus infections in mice. Vaccinia induced rapid TLR2-dependent responses leading to IL-6 production, which then initiated STAT3 signaling in dendritic cells and T cells. In contrast, ectromelia did not induce TLR2 activation and profound mouse strain-dependent responses were observed. In resistant C57BL/6 mice, the STAT1 and STAT3 pathways were rapidly activated, whereas in susceptible BALB/c mice, IL-6-dependent STAT3 activation did not occur. These results indicate that vaccination with vaccinia is dependent on rapid TLR2 and IL-6 driven responses and link the earliest immune signaling events to the outcome of infection.
PMCID: PMC2940993  PMID: 20709294
19.  Computational solutions to large-scale data management and analysis 
Nature reviews. Genetics  2010;11(9):647-657.
Today we can generate hundreds of gigabases of DNA and RNA sequencing data in a week for less than US$5,000. The astonishing rate of data generation by these low-cost, high-throughput technologies in genomics is being matched by that of other technologies, such as real-time imaging and mass spectrometry-based flow cytometry. Success in the life sciences will depend on our ability to properly interpret the large-scale, high-dimensional data sets that are generated by these technologies, which in turn requires us to adopt advances in informatics. Here we discuss how we can master the different types of computational environments that exist — such as cloud and heterogeneous computing — to successfully tackle our big data problems.
PMCID: PMC3124937  PMID: 20717155
20.  Characterization of Patient Specific Signaling via Augmentation of Bayesian Networks with Disease and Patient State Nodes 
Characterization of patient-specific disease features at a molecular level is an important emerging field. Patients may be characterized by differences in the level and activity of relevant biomolecules in diseased cells. When high throughput, high dimensional data is available, it becomes possible to characterize differences not only in the level of the biomolecules, but also in the molecular interactions among them. We propose here a novel approach to characterize patient specific signaling, which augments high throughput single cell data with state nodes corresponding to patient and disease states, and learns a Bayesian network based on this data. Features distinguishing individual patients emerge as downstream nodes in the network. We illustrate this approach with a six phospho-protein, 30,000 cell-per-patient dataset characterizing three comparably diagnosed follicular lymphoma, and show that our approach elucidates signaling differences among them.
PMCID: PMC3124088  PMID: 19963681
21.  Phosphoproteomic Analysis Reveals Interconnected System-Wide Responses to Perturbations of Kinases and Phosphatases in Yeast 
Science signaling  2010;3(153):rs4.
The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules, and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery, and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.
PMCID: PMC3072779  PMID: 21177495
22.  Distinct Patterns of DNA Damage Response and Apoptosis Correlate with Jak/Stat and PI3Kinase Response Profiles in Human Acute Myelogenous Leukemia 
PLoS ONE  2010;5(8):e12405.
Single cell network profiling (SCNP) utilizing flow cytometry measures alterations in intracellular signaling responses. Here SCNP was used to characterize Acute Myeloid Leukemia (AML) disease subtypes based on survival, DNA damage response and apoptosis pathways.
Methodology and Principal Findings
Thirty four diagnostic non-M3 AML samples from patients with known clinical outcome were treated with a panel of myeloid growth factors and cytokines, as well as with apoptosis-inducing agents. Analysis of induced Jak/Stat and PI3K pathway responses in blasts from individual patient samples identified subgroups with distinct signaling profiles that were not seen in the absence of a modulator. In vitro exposure of patient samples to etoposide, a DNA damaging agent, revealed three distinct “DNA damage response (DDR)/apoptosis” profiles: 1) AML blasts with a defective DDR and failure to undergo apoptosis; 2) AML blasts with proficient DDR and failure to undergo apoptosis; 3) AML blasts with proficiency in both DDR and apoptosis pathways. Notably, AML samples from clinical responders fell within the “DDR/apoptosis” proficient profile and, as well, had low PI3K and Jak/Stat signaling responses. In contrast, samples from clinical non responders had variable signaling profiles often with in vitro apoptotic failure and elevated PI3K pathway activity. Individual patient samples often harbored multiple, distinct, leukemia-associated cell populations identifiable by their surface marker expression, functional performance of signaling pathway in the face of cytokine or growth factor stimulation, as well as their response to apoptosis-inducing agents.
Conclusions and Significance
Characterizing and tracking changes in intracellular pathway profiles in cell subpopulations both at baseline and under therapeutic pressure will likely have important clinical applications, potentially informing the selection of beneficial targeted agents, used either alone or in combination with chemotherapy.
PMCID: PMC2928279  PMID: 20811632
An early reaction of CD4+ T lymphocytes to antigen is the production of cytokines, notably IL-2. In order to detect cytokine dependent responses, naive antigen-specific T cells were stimulated in vivo and the presence of phosphorylated STAT5 molecules was used to identify the cell populations responding to IL-2. Within hours of T-cell priming, IL-2-dependent STAT5 phosphorylation occurred primarily in Foxp3+ regulatory T cells. In contrast, the antigen-specific T cells received STAT5 signals only after repeated antigen exposure or memory differentiation. Regulatory T cells receiving IL-2 signals proliferated and developed enhanced suppressive activity. These results indicate that one of the earliest events in a T cell response is the activation of endogenous regulatory cells, potentially to prevent autoimmunity.
PMCID: PMC2753472  PMID: 19542444
T-cells; cytokines; cell activation; tolerance/suppression
24.  Learning Signaling Network Structures with Sparsely Distributed Data 
Journal of Computational Biology  2009;16(2):201-212.
Flow cytometric measurement of signaling protein abundances has proved particularly useful for elucidation of signaling pathway structure. The single cell nature of the data ensures a very large dataset size, providing a statistically robust dataset for structure learning. Moreover, the approach is easily scaled to many conditions in high throughput. However, the technology suffers from a dimensionality constraint: at the cutting edge, only about 12 protein species can be measured per cell, far from sufficient for most signaling pathways. Because the structure learning algorithm (in practice) requires that all variables be measured together simultaneously, this restricts structure learning to the number of variables that constitute the flow cytometer's upper dimensionality limit. To address this problem, we present here an algorithm that enables structure learning for sparsely distributed data, allowing structure learning beyond the measurement technology's upper dimensionality limit for simultaneously measurable variables. The algorithm assesses pairwise (or n-wise) dependencies, constructs “Markov neighborhoods” for each variable based on these dependencies, measures each variable in the context of its neighborhood, and performs structure learning using a constrained search.
PMCID: PMC3198894  PMID: 19193145
Bayesian networks; flow cytometry; graphical models; proteomics; signaling pathways
25.  Electron Microscopy Localization and Characterization of Functionalized Composite Organic-Inorganic SERS Nanoparticles on Leukemia Cells 
Ultramicroscopy  2008;109(1):111-121.
We demonstrate the use of electron microscopy as a powerful characterization tool to identify and locate antibody-conjugated composite organic-inorganic (COINs) surface enhanced Raman scattering (SERS) nanoparticles on cells. U937 leukemia cells labeled with antibody CD54-conjugated COINs were characterized in their native, hydrated state using wet Scanning Electron Microscopy (SEM) and in their dehydrated state using high-resolution SEM. In both cases, the backscattered electron detector (BSE) was used to detect and identify the silver constituents in COINs due to its high sensitivity to atomic number variations within a specimen. The imaging and analytical capabilities in the SEM were further complemented by higher resolution Transmission Electron Microscope (TEM) images and Scanning Auger Electron Spectroscopy (AES) data to give reliable and high-resolution information about nanoparticles and their binding to cell surface antigens.
PMCID: PMC2650478  PMID: 18995965
SERS Nanoparticles on Cells; Scanning Electron Microscopy; Transmission Electron Microscopy; Scanning Auger Electron Spectroscopy

Results 1-25 (37)