Publications by authors named "Eli R Zunder"

17 Publications

  • Page 1 of 1

Identification of human immune cell subtypes most responsive to IL-1β-induced inflammatory signaling using mass cytometry.

Sci Signal 2021 03 9;14(673). Epub 2021 Mar 9.

Carter Immunology Center, University of Virginia, Charlottesville, VA 22908, USA.

IL-1β is a key mediator of the cytokine storm linked to high morbidity and mortality from COVID-19, and IL-1β blockade with anakinra and canakinumab during COVID-19 infection has entered clinical trials. Using mass cytometry of human peripheral blood mononuclear cells, we identified effector memory CD4 T cells and CD4CD8CD161 T cells, specifically those positive for the chemokine receptor CCR6, as the circulating immune subtypes with the greatest response to IL-1β. This response manifested as increased phosphorylation and, thus, activation of the proinflammatory transcription factor NF-κB and was also seen in other subsets, including CD11c myeloid dendritic cells, classical monocytes, two subsets of natural killer cells (CD16CD56CD161 and CD16CD56CD161), and lineage (Lin) cells expressing CD161 and CD25. IL-1β also induced a rapid but less robust increase in the phosphorylation of the kinase p38 as compared to that of NF-κB in most of these immune cell subsets. Prolonged IL-1β stimulation increased the phosphorylation of the transcription factor STAT3 and to a lesser extent that of STAT1 and STAT5 across various immune cell types. IL-1β-induced production of IL-6 likely led to the activation of STAT1 and STAT3 at later time points. Interindividual heterogeneity and inhibition of STAT activation by anakinra raise the possibility that assays measuring NF-κB phosphorylation in response to IL-1β in CCR6 T cell subtypes could identify those patients at higher risk of cytokine storm and most likely to benefit from IL-1β-neutralizing therapies.
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http://dx.doi.org/10.1126/scisignal.abc5763DOI Listing
March 2021

Stem Cell Pluripotency Genes Klf4 and Oct4 Regulate Complex SMC Phenotypic Changes Critical in Late-Stage Atherosclerotic Lesion Pathogenesis.

Circulation 2020 Nov 17;142(21):2045-2059. Epub 2020 Jul 17.

Robert M. Berne Cardiovascular Research Center (G.F.A., K.M.O, S.K., A.N., C.M.W., S.S., C.A.H., R.H., R.A.B., C.A.M., E.R.Z., G.K.O.), University of Virginia, Charlottesville.

Background: Rupture and erosion of advanced atherosclerotic lesions with a resultant myocardial infarction or stroke are the leading worldwide cause of death. However, we have a limited understanding of the identity, origin, and function of many cells that make up late-stage atherosclerotic lesions, as well as the mechanisms by which they control plaque stability.

Methods: We conducted a comprehensive single-cell RNA sequencing of advanced human carotid endarterectomy samples and compared these with single-cell RNA sequencing from murine microdissected advanced atherosclerotic lesions with smooth muscle cell (SMC) and endothelial lineage tracing to survey all plaque cell types and rigorously determine their origin. We further used chromatin immunoprecipitation sequencing (ChIP-seq), bulk RNA sequencing, and an innovative dual lineage tracing mouse to understand the mechanism by which SMC phenotypic transitions affect lesion pathogenesis.

Results: We provide evidence that SMC-specific Klf4- versus Oct4-knockout showed virtually opposite genomic signatures, and their putative target genes play an important role regulating SMC phenotypic changes. Single-cell RNA sequencing revealed remarkable similarity of transcriptomic clusters between mouse and human lesions and extensive plasticity of SMC- and endothelial cell-derived cells including 7 distinct clusters, most negative for traditional markers. In particular, SMC contributed to a Myh11, Lgals3 population with a chondrocyte-like gene signature that was markedly reduced with SMC- knockout. We observed that SMCs that activate Lgals3 compose up to two thirds of all SMC in lesions. However, initial activation of Lgals3 in these cells does not represent conversion to a terminally differentiated state, but rather represents transition of these cells to a unique stem cell marker gene-positive, extracellular matrix-remodeling, "pioneer" cell phenotype that is the first to invest within lesions and subsequently gives rise to at least 3 other SMC phenotypes within advanced lesions, including Klf4-dependent osteogenic phenotypes likely to contribute to plaque calcification and plaque destabilization.

Conclusions: Taken together, these results provide evidence that SMC-derived cells within advanced mouse and human atherosclerotic lesions exhibit far greater phenotypic plasticity than generally believed, with Klf4 regulating transition to multiple phenotypes including Lgals3 osteogenic cells likely to be detrimental for late-stage atherosclerosis plaque pathogenesis.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.120.046672DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7682794PMC
November 2020

FLOW-MAP: a graph-based, force-directed layout algorithm for trajectory mapping in single-cell time course datasets.

Nat Protoc 2020 02 13;15(2):398-420. Epub 2020 Jan 13.

Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.

High-dimensional single-cell technologies present new opportunities for biological discovery, but the complex nature of the resulting datasets makes it challenging to perform comprehensive analysis. One particular challenge is the analysis of single-cell time course datasets: how to identify unique cell populations and track how they change across time points. To facilitate this analysis, we developed FLOW-MAP, a graphical user interface (GUI)-based software tool that uses graph layout analysis with sequential time ordering to visualize cellular trajectories in high-dimensional single-cell datasets obtained from flow cytometry, mass cytometry or single-cell RNA sequencing (scRNAseq) experiments. Here we provide a detailed description of the FLOW-MAP algorithm and how to use the open-source R package FLOWMAPR via its GUI or with text-based commands. This approach can be applied to many dynamic processes, including in vitro stem cell differentiation, in vivo development, oncogenesis, the emergence of drug resistance and cell signaling dynamics. To demonstrate our approach, we perform a step-by-step analysis of a single-cell mass cytometry time course dataset from mouse embryonic stem cells differentiating into the three germ layers: endoderm, mesoderm and ectoderm. In addition, we demonstrate FLOW-MAP analysis of a previously published scRNAseq dataset. Using both synthetic and experimental datasets for comparison, we perform FLOW-MAP analysis side by side with other single-cell analysis methods, to illustrate when it is advantageous to use the FLOW-MAP approach. The protocol takes between 30 min and 1.5 h to complete.
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http://dx.doi.org/10.1038/s41596-019-0246-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7897424PMC
February 2020

levels in human hematopoietic progenitors are regulated by aging and dictate erythroid-myeloid balance.

Haematologica 2020 04 6;105(4):905-913. Epub 2019 Jun 6.

Department of Pathology, University of Virginia School of Medicine, Charlottesville, USA

Healthy bone marrow progenitors yield a co-ordinated balance of hematopoietic lineages. This balance shifts with aging toward enhanced granulopoiesis with diminished erythropoiesis and lymphopoiesis, changes which likely contribute to the development of bone marrow disorders in the elderly. In this study, RUNX3 was identified as a hematopoietic stem and progenitor cell factor whose levels decline with aging in humans and mice. This decline is exaggerated in hematopoietic stem and progenitor cells from subjects diagnosed with unexplained anemia of the elderly. Hematopoietic stem cells from elderly unexplained anemia patients had diminished erythroid but unaffected granulocytic colony forming potential. Knockdown studies revealed human hematopoietic stem and progenitor cells to be strongly influenced by RUNX3 levels, with modest deficiencies abrogating erythroid differentiation at multiple steps while retaining capacity for granulopoiesis. Transcriptome profiling indicated control by RUNX3 of key erythroid transcription factors, including and These findings thus implicate RUNX3 as a participant in hematopoietic stem and progenitor cell aging, and a key determinant of erythroid-myeloid lineage balance.
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http://dx.doi.org/10.3324/haematol.2018.208918DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7109730PMC
April 2020

Cutting Edge: Critical Roles for Microbiota-Mediated Regulation of the Immune System in a Prenatal Immune Activation Model of Autism.

J Immunol 2018 08 2;201(3):845-850. Epub 2018 Jul 2.

Center for Brain Immunology and Glia, Department of Neuroscience, School of Medicine, University of Virginia, Charlottesville, VA 22908;

Recent studies suggest that autism is often associated with dysregulated immune responses and altered microbiota composition. This has led to growing speculation about potential roles for hyperactive immune responses and the microbiome in autism. Yet how microbiome-immune cross-talk contributes to neurodevelopmental disorders currently remains poorly understood. In this study, we report critical roles for prenatal microbiota composition in the development of behavioral abnormalities in a murine maternal immune activation (MIA) model of autism that is driven by the viral mimetic polyinosinic-polycytidylic acid. We show that preconception microbiota transplantation can transfer susceptibility to MIA-associated neurodevelopmental disease and that this is associated with modulation of the maternal immune response. Furthermore, we find that ablation of IL-17a signaling provides protection against the development of neurodevelopmental abnormalities in MIA offspring. Our findings suggest that microbiota landscape can influence MIA-induced neurodevelopmental disease pathogenesis and that this occurs as a result of microflora-associated calibration of gestational IL-17a responses.
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http://dx.doi.org/10.4049/jimmunol.1701755DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057827PMC
August 2018

Atomic mass tag of bismuth-209 for increasing the immunoassay multiplexing capacity of mass cytometry.

Cytometry A 2017 12 4;91(12):1150-1163. Epub 2017 Dec 4.

Baxter Laboratory for Stem Cell Biology Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford California.

Mass cytometry (or CyTOF) is an atomic mass spectrometry-based single-cell immunoassay technology, which has provided an increasingly systematic and sophisticated view in basic biological and clinical studies. Using elemental reporters composed of stable heavy metal isotopes, more than 50 cellular parameters are measured simultaneously. However, this current multiplexing does not meet the theoretical capability of CyTOF instrumentation with 135 detectable channels, primarily due to the limitation of available chemistries for conjugating elemental mass tags to affinity reagents. To address this issue, we develop herein additional metallic mass tag based on bismuth-209 ( Bi) for efficient conjugation to monoclonal antibody. This enables the use of an addtional channel m/z = 209 of CyTOF for single-cell immunoassays. Bismuth has nearly the same charge-to-radius ratio as lanthanide elements; thus, bismuth(III) cations ( Bi ) could coordinate with DTPA chelators in the same geometry of O- and N-donor groups as that of lanthanide. In this report, the coordination chemistry of Bi with DTPA chelators and Maxpar® X8 polymers were investigated in details. Accordingly, the protocols of conjugating antibody with bismuth mass tag were provided. A method based on UV-Vis absorbance at 280 nm of Bi -labeling DTPA complexes was developed to evaluate the stoichiometric ratio of Bi cations to the conjugated antibody. Side-by-side single-cell analysis experiments with bismuth- and lanthanide-tagged antibodies were carried out to compare the analytical sensitivities. The measurement accuracy of bismuth-tagged antibody was validated within in vitro assay using primary human natural killer cells. Furthermore, bismuth-tagged antibodies were successfully employed in cell cycle measurements and high-dimensional phenotyping immunoassays. © 2017 International Society for Advancement of Cytometry.
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http://dx.doi.org/10.1002/cyto.a.23283DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5802970PMC
December 2017

AN UPDATED DEBARCODING TOOL FOR MASS CYTOMETRY WITH CELL TYPE-SPECIFIC AND CELL SAMPLE-SPECIFIC STRINGENCY ADJUSTMENT.

Pac Symp Biocomput 2017 ;22:588-598

Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22903, USA,

Pooled sample analysis by mass cytometry barcoding carries many advantages: reduced antibody consumption, increased sample throughput, removal of cell doublets, reduction of cross-contamination by sample carryover, and the elimination of tube-to-tube-variability in antibody staining. A single-cell debarcoding algorithm was previously developed to improve the accuracy and yield of sample deconvolution, but this method was limited to using fixed parameters for debarcoding stringency filtering, which could introduce cell-specific or sample-specific bias to cell yield in scenarios where barcode staining intensity and variance are not uniform across the pooled samples. To address this issue, we have updated the algorithm to output debarcoding parameters for every cell in the sample-assigned FCS files, which allows for visualization and analysis of these parameters via flow cytometry analysis software. This strategy can be used to detect cell type-specific and sample-specific effects on the underlying cell data that arise during the debarcoding process. An additional benefit to this strategy is the decoupling of barcode stringency filtering from the debarcoding and sample assignment process. This is accomplished by removing the stringency filters during sample assignment, and then filtering after the fact with 1- and 2-dimensional gating on the debarcoding parameters which are output with the FCS files. These data exploration strategies serve as an important quality check for barcoded mass cytometry datasets, and allow cell type and sample-specific stringency adjustment that can remove bias in cell yield introduced during the debarcoding process.
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http://dx.doi.org/10.1142/9789813207813_0054DOI Listing
March 2017

Highly multiplexed simultaneous detection of RNAs and proteins in single cells.

Nat Methods 2016 Mar 25;13(3):269-75. Epub 2016 Jan 25.

Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, California, USA.

To enable the detection of expression signatures specific to individual cells, we developed PLAYR (proximity ligation assay for RNA), a method for highly multiplexed transcript quantification by flow and mass cytometry that is compatible with standard antibody staining. When used with mass cytometry, PLAYR allowed for the simultaneous quantification of more than 40 different mRNAs and proteins. In primary cells, we quantified multiple transcripts, with the identity and functional state of each analyzed cell defined on the basis of the expression of a separate set of transcripts or proteins. By expanding high-throughput deep phenotyping of cells beyond protein epitopes to include RNA expression, PLAYR opens a new avenue for the characterization of cellular metabolism.
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http://dx.doi.org/10.1038/nmeth.3742DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4767631PMC
March 2016

IMMUNOLOGY. An interactive reference framework for modeling a dynamic immune system.

Science 2015 Jul;349(6244):1259425

Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA. Program in Immunology, Stanford University, Stanford, CA 94305, USA.

Immune cells function in an interacting hierarchy that coordinates the activities of various cell types according to genetic and environmental contexts. We developed graphical approaches to construct an extensible immune reference map from mass cytometry data of cells from different organs, incorporating landmark cell populations as flags on the map to compare cells from distinct samples. The maps recapitulated canonical cellular phenotypes and revealed reproducible, tissue-specific deviations. The approach revealed influences of genetic variation and circadian rhythms on immune system structure, enabled direct comparisons of murine and human blood cell phenotypes, and even enabled archival fluorescence-based flow cytometry data to be mapped onto the reference framework. This foundational reference map provides a working definition of systemic immune organization to which new data can be integrated to reveal deviations driven by genetics, environment, or pathology.
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http://dx.doi.org/10.1126/science.1259425DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537647PMC
July 2015

Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis.

Cell 2015 Jul 18;162(1):184-97. Epub 2015 Jun 18.

Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA. Electronic address:

Acute myeloid leukemia (AML) manifests as phenotypically and functionally diverse cells, often within the same patient. Intratumor phenotypic and functional heterogeneity have been linked primarily by physical sorting experiments, which assume that functionally distinct subpopulations can be prospectively isolated by surface phenotypes. This assumption has proven problematic, and we therefore developed a data-driven approach. Using mass cytometry, we profiled surface and intracellular signaling proteins simultaneously in millions of healthy and leukemic cells. We developed PhenoGraph, which algorithmically defines phenotypes in high-dimensional single-cell data. PhenoGraph revealed that the surface phenotypes of leukemic blasts do not necessarily reflect their intracellular state. Using hematopoietic progenitors, we defined a signaling-based measure of cellular phenotype, which led to isolation of a gene expression signature that was predictive of survival in independent cohorts. This study presents new methods for large-scale analysis of single-cell heterogeneity and demonstrates their utility, yielding insights into AML pathophysiology.
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http://dx.doi.org/10.1016/j.cell.2015.05.047DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4508757PMC
July 2015

Early reprogramming regulators identified by prospective isolation and mass cytometry.

Nature 2015 May 1;521(7552):352-6. Epub 2015 Apr 1.

1] Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California 94305, USA [2] Department of Pathology, Stanford University, Stanford, California 94305, USA.

In the context of most induced pluripotent stem (iPS) cell reprogramming methods, heterogeneous populations of non-productive and staggered productive intermediates arise at different reprogramming time points. Despite recent reports claiming substantially increased reprogramming efficiencies using genetically modified donor cells, prospectively isolating distinct reprogramming intermediates remains an important goal to decipher reprogramming mechanisms. Previous attempts to identify surface markers of intermediate cell populations were based on the assumption that, during reprogramming, cells progressively lose donor cell identity and gradually acquire iPS cell properties. Here we report that iPS cell and epithelial markers, such as SSEA1 and EpCAM, respectively, are not predictive of reprogramming during early phases. Instead, in a systematic functional surface marker screen, we find that early reprogramming-prone cells express a unique set of surface markers, including CD73, CD49d and CD200, that are absent in both fibroblasts and iPS cells. Single-cell mass cytometry and prospective isolation show that these distinct intermediates are transient and bridge the gap between donor cell silencing and pluripotency marker acquisition during the early, presumably stochastic, reprogramming phase. Expression profiling reveals early upregulation of the transcriptional regulators Nr0b1 and Etv5 in this reprogramming state, preceding activation of key pluripotency regulators such as Rex1 (also known as Zfp42), Dppa2, Nanog and Sox2. Both factors are required for the generation of the early intermediate state and fully reprogrammed iPS cells, and thus represent some of the earliest known regulators of iPS cell induction. Our study deconvolutes the first steps in a hierarchical series of events that lead to pluripotency acquisition.
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http://dx.doi.org/10.1038/nature14274DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4441548PMC
May 2015

A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry.

Cell Stem Cell 2015 Mar;16(3):323-37

Department of Microbiology and Immunology, Baxter Laboratory for Stem Cell Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. Electronic address:

To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4(high)Klf4(high) cells transitioned to a CD73(high)CD104(high)CD54(low) partially reprogrammed state. Ki67(low) cells from this intermediate population reverted to a MEF-like phenotype, but Ki67(high) cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like Nanog(high)Sox2(high)CD54(high) population and a mesendoderm-like Nanog(low)Sox2(low)Lin28(high)CD24(high)PDGFR-α(high) population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.
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http://dx.doi.org/10.1016/j.stem.2015.01.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4401090PMC
March 2015

Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm.

Nat Protoc 2015 Feb 22;10(2):316-33. Epub 2015 Jan 22.

Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, USA.

Mass-tag cell barcoding (MCB) labels individual cell samples with unique combinatorial barcodes, after which they are pooled for processing and measurement as a single multiplexed sample. The MCB method eliminates variability between samples in antibody staining and instrument sensitivity, reduces antibody consumption and shortens instrument measurement time. Here we present an optimized MCB protocol. The use of palladium-based labeling reagents expands the number of measurement channels available for mass cytometry and reduces interference with lanthanide-based antibody measurement. An error-detecting combinatorial barcoding scheme allows cell doublets to be identified and removed from the analysis. A debarcoding algorithm that is single cell-based rather than population-based improves the accuracy and efficiency of sample deconvolution. This debarcoding algorithm has been packaged into software that allows rapid and unbiased sample deconvolution. The MCB procedure takes 3-4 h, not including sample acquisition time of ∼1 h per million cells.
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http://dx.doi.org/10.1038/nprot.2015.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4347881PMC
February 2015

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

Cytometry A 2014 Dec 1;85(12):1011-9. Epub 2014 Oct 1.

Baxter Laboratory for Stem Cell Biology, Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California; Divisions of Hematology and Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, California.

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.
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http://dx.doi.org/10.1002/cyto.a.22573DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4361015PMC
December 2014

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

Nat Biotechnol 2012 Sep;30(9):858-67

Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, California, USA.

Mass cytometry facilitates high-dimensional, quantitative analysis of the effects of bioactive molecules on human samples at single-cell resolution, but instruments process only one sample at a time. Here we describe mass-tag cellular barcoding (MCB), which increases mass cytometry throughput by using n metal ion tags to multiplex up to 2n samples. We used seven tags to multiplex an entire 96-well plate, and applied MCB to characterize human peripheral blood mononuclear cell (PBMC) signaling dynamics and cell-to-cell communication, signaling variability between PBMCs from eight human donors, and the effects of 27 inhibitors on this system. For each inhibitor, we measured 14 phosphorylation sites in 14 PBMC types at 96 conditions, 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. High-content, high-throughput screening with MCB should be useful for drug discovery, preclinical testing and mechanistic investigation of human disease.
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http://dx.doi.org/10.1038/nbt.2317DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627543PMC
September 2012

Discovery of drug-resistant and drug-sensitizing mutations in the oncogenic PI3K isoform p110 alpha.

Cancer Cell 2008 Aug;14(2):180-92

Graduate Group in Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA.

p110 alpha (PIK3CA) is the most frequently mutated kinase in human cancer, and numerous drugs targeting this kinase are currently in preclinical development or early-stage clinical trials. Clinical resistance to protein kinase inhibitors frequently results from point mutations that block drug binding; similar mutations in p110 alpha are likely, but currently none have been reported. Using a S. cerevisiae screen against a structurally diverse panel of PI3K inhibitors, we have identified a potential hotspot for resistance mutations (I800), a drug-sensitizing mutation (L814C), and a surprising lack of resistance mutations at the "gatekeeper" residue. Our analysis further reveals that clinical resistance to these drugs may be attenuated by using multitargeted inhibitors that simultaneously inhibit additional PI3K pathway members.
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http://dx.doi.org/10.1016/j.ccr.2008.06.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2720137PMC
August 2008

A pharmacological map of the PI3-K family defines a role for p110alpha in insulin signaling.

Cell 2006 May 27;125(4):733-47. Epub 2006 Apr 27.

Department of Cellular and Molecular Pharmacology, Howard Hughes Medical Institute, University of California, San Francisco, CA 94143, USA.

Phosphoinositide 3-kinases (PI3-Ks) are an important emerging class of drug targets, but the unique roles of PI3-K isoforms remain poorly defined. We describe here an approach to pharmacologically interrogate the PI3-K family. A chemically diverse panel of PI3-K inhibitors was synthesized, and their target selectivity was biochemically enumerated, revealing cryptic homologies across targets and chemotypes. Crystal structures of three inhibitors bound to p110gamma identify a conformationally mobile region that is uniquely exploited by selective compounds. This chemical array was then used to define the PI3-K isoforms required for insulin signaling. We find that p110alpha is the primary insulin-responsive PI3-K in cultured cells, whereas p110beta is dispensable but sets a phenotypic threshold for p110alpha activity. Compounds targeting p110alpha block the acute effects of insulin treatment in vivo, whereas a p110beta inhibitor has no effect. These results illustrate systematic target validation using a matrix of inhibitors that span a protein family.
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http://dx.doi.org/10.1016/j.cell.2006.03.035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2946820PMC
May 2006