CyTOF/CODEX mini-course
Garry Nolan: Overview and Introduction
Peter Krutzik (Nolan): Phospho-Specific Flow Cytometry: The Basics
In this talk we will go through the basics of phospho-specific flow cytometry, or phospho flow. Phospho flow enables the analysis of intracellular signaling cascades at the single cell level. Testing of different fixation and permeabilization conditions lead to the identification of formaldehyde fixation followed by methanol permeabilization as the optimal method for detection of phospho-epitopes, particularly the STAT family of transcription factors. Phospho flow is quantitative, comparing well with data from Western blotting, and can be used to follow dose response as well as time course experiments. The data can be visualized in several different ways, from one-dimensional histograms, to two-dimensional contour plots, to massive heatmaps of disease profiling experiments. Due to the multiparameter nature of flow cytometry, phospho flow is particularly well-suited to analysis of complex primary cell populations, as will be discussed in further talks and briefly presented here.
https://www.youtube.com/watch?v=ZhgBBtR97vc
Sean Bendall (Nolan): Mass Cytometry: Guilt-free, 35-plus Parameter, Single Cell Analysis for Proteomic Dissection of Immune Function
Classical four-color fluorescence flow cytometry helped define the major cell subsets of the immune system that we understand today (i.e. T-cells, B-cells, macrophages). Machines with eight or more colors brought characterization of rare immune subsets and stem cells. With intracellular staining, higher parameter measurements lead to examination of regulatory signaling networks and patient stratification with clinical outcomes. However, this progression has now been stymied by the limit of fluorescence parameters measurable, realistically capped at 12-15 due to boundaries in instrumentation and spectral overlap considerations in fluorophore-based tagging methods. Now, a novel combination of elemental mass spectrometry with single cell analysis (mass cytometry) offers examination of 30-50 parameters (theoretically up to 100) without fluorescent agents or interference from spectral overlap. Instead, it utilizes non-biological, elemental isotopes as reporters. By exploiting the resolution, sensitivity, and dynamic range of elemental mass spectrometry, on a time-scale that allows the measurement of 1000 individual cells per second, this device offers a much-simplified alternative for ultra-high content cytometric analysis. At Stanford, using the world’s first commercial version of this instrument (CyTOF), we have applied simple modifications to protocols already established in our lab for quantization of cellular signaling events in immunological subtypes. Already measuring 20+ intracellular antigens (phosphorylations) in conjunction with 10+ cell surface markers we detail the approaches we are taking towards an unprecedented profile of cytokine/immune responses of all major cell types in human blood and bone marrow. We will present these studies and demonstrate the detailed systems-level view of immune function they reveal.
https://www.youtube.com/watch?v=DYCbzugUGBU
Matt Spitzer (Nolan): Tools of the Trade: Reagent Development and Antibody Conjugation
A brief overview of CyTOF antibody chelation chemistry will be covered. A summary of the antibody conjugation protocol will be provided as well as information regarding intercalating reagents, viability stains and barcode reagents. I will also address relevant troubleshooting and optimization topics including titrations, antibody purification and approaches for circumventing conjugation for problematic antibody clones.
https://www.youtube.com/watch?v=V9EgJ6Xa8ik
Nikesh Kotecha (Nolan): Cytobank - Manage, Analyze and Share Flow Cytometry Data from Anywhere
Phospho flow cytometry generates a unique challenge in data analysis, as it requires quantitative measurements to be made on multi-dimensional data. Therefore, we have written a software package called Cytobank, that enables: 1) secure storage of annotated flow cytometry data, 2) sharing of data between users and collaborators, eliminating the need for FTP servers or shared drives, 3) annotation and tagging of data and individual experiments, 4) compensation 5) calculation of custom statistics such as fold change over unstimulated, 6) heat map generation, 7) pivoting of data to visualize many different parameters rapidly and easily, and 8) histogram overlays. We will present the background and development of Cytobank, as well as show a live demo of the software.
https://www.youtube.com/watch?v=qXkQHvA2ZRw
Holden Maecker (Director, Human Immune Monitoring Center, ITI): Introduction to the Human Immune Monitoring Center
https://www.youtube.com/watch?v=zphhhVOm7Os
The Human Immune Monitoring Center (HIMC) is a service center created by the Institute for Immunity, Transplantation, and Infection, in the Stanford School of Medicine. Its purpose is to provide full-service, comprehensive, and standardized immune monitoring assays on multiple technology platforms. Standardized CyTOF/flow cytometry, Luminex, gene expression, and nanoimmunoassay services are currently offered, and new technologies are being explored. The HIMC also supports an online database that can be mined for metrics of immunological health and disease.
Greg Behbehani MD, PhD (Nolan): Cell cycle analysis using mass cytometry
This presentation will discuss the basic methods for analyzing the cell cycle by mass cytometry. The current methodology relies on Incorporation of 5- iodo-2-deoxyuridine (IdU) to label S-phase cells, and cyclins A and B1 to separate G1 from G2 cells. G0 cells can be identified using an antibody against retinoblastoma protein phosphorylated at serines 807 and 811, and M phase cells are detected through the use of an antibody directed against histone H3 phosphorylated at serine 28. These methods yield equivalent results to traditional fluorescence methods in both cultured cell lines and stimulated normal T cells. This analysis can be combined with large panels of surface or functional markers to measure the cell cycle across multiple sub-populations of cells within complex samples.
https://www.youtube.com/watch?v=lqpzoJM33tg
Harris Fienberg (Nolan): Mass Cytometry as a Tool to Unravel Apoptotic Signaling
Apoptosis has proved to be a difficult to study process due to its massive complexity and asynchronous execution. Mass cytometry represents a useful tool to resolve the inscrutability of the apoptotic cascade. We have developed reagents to examine apoptosis both in cell lines and in primary tissue and bioinformatic approaches to unravel the signaling cascade leading to apoptosis.
https://www.youtube.com/watch?v=A4woGhba0uU
Peter Krutzik (Nolan): Fluorescent Cell Barcoding (FCB) Enables High Throughput Flow Cytometry
https://www.youtube.com/watch?v=U8pXhKWPCRU
We recently developed a technique which we call Fluorescent Cell Barcoding (FCB) that dramatically improves the throughput of flow cytometry experiments and enables larger disease profiling and drug screening. In FCB, each sample is labeled with a unique signature of fluorescence by combining different intensities and types of fluorophores. The samples can then be combined into one sample for staining with the antibody cocktail. In this way, all samples are exposed to the same cocktail, dramatically reducing staining variability as a source of uncertainty in experiments. After staining, the samples are run on the flow cytometer, and upon software analysis are separated, or deconvoluted, back to the original samples. FCB is an enabling platform that reduces antibody consumption 10-100 fold, and decreases acquisition time on the cytometer 5-10 fold. The FCB method can be applied to both cell lines and primary cell populations, and is routinely used in our laboratory for both systems.
Eli Zunder (Nolan): Kinase Inhibitor Profiling With Mass-Tag Cell Barcoding
https://www.youtube.com/watch?v=V4MEJm3SWCQ
Mass cytometry enables quantitative, high-content analysis at the single cell level with more measured parameters than traditional fluorescence-based flow cytometry. Here I describe a method termed mass-tag cellular barcoding (MCB) that significantly increases sample throughput by multiplexing masstag encoded samples while enabling comprehensive signaling network analysis. 96-well format MCB was used to characterize the signaling dynamics of human peripheral blood mononuclear cells (PBMCs) and to define the impact of 24 commonly used small molecule kinase inhibitors on this system. For each small molecule, 14 phosphorylation states were measured per cell in 14 PBMC types under 96 conditions, resulting in 18,816 quantified phosphorylation levels from a single multiplexed sample
Erin Simonds (Nolan): High-dimensional cytometry data analysis using SPADE
https://www.youtube.com/watch?v=Tlx2B5AhWNE
A discussion of the SPADE algorithm for visualizing high-dimensional data, with an overview of the theory and several real-world examples using fluorescence and mass cytometry datasets.
Evan Newell (Davis): Recent advancements in pMHC-tetramer staining for phenotypic profiling antigen-specific T cells. The direct detection of antigen-specific T cells using fluorescently tagged pMHC-tetramers is widely used in basic and clinical immunology, allowing the unperturbed assessment of T cell phenotypes by concurrent staining with surface and/or intracellular markers. However, several technical limitations remain, including: the number of specificities that can be detected in a sample, the number of phenotypic markers that can be simultaneously assessed on the antigen-specific cells, and the incompatibility with phospho-flow technology. Several recent advancements made by our group and others are overcoming each of these limitations and will be described. In particular, the usefulness of pMHC-tetramer in combination with CyTOF will be demonstrated.
https://www.youtube.com/watch?v=Q0Ip_PuM_Jk
Holden Maecker (Director, Human Immune Monitoring Center, ITI): Nanofluidic qPCR Arrays for Single-Cell Gene Expression
The Fluidigm BioMark platform allows for the construction of qPCR arrays using a microfluidic “dynamic array”, creating combinatorial reactions of samples and reaction mixtures with minimal input material and minimal pipetting. The platform is particularly suited for assessing single-cell gene expression, and data from a study of single CMV epitope-specific T cells will be presented.
https://www.youtube.com/watch?v=473uU-NqhhE
Yael Rosenberg-Hasson (Immunoassay Manager, Human Immune Monitoring Center, ITI): Multiplexed Immunoassays for Human Cytokine Detection
Multiple platforms for multiplexed immunoassays exist, of which Luminex is the most widely used. These assays use microspheres with separate fluorescent reporting of both bead address and analyte binding. They can provide picogram per milliliter sensitivity and multiplexing of 50 or more analytes in a single well, requiring <50 microliters of serum, plasma, or other fluid. Issues of matrix effects, concentration calculation, etc. will be discussed. Comparison data with an electrochemiluminescence platform (MesoScale Discovery) will also be presented.
https://www.youtube.com/watch?v=RTykvvstsWQ
Prajna Bannerjee (NanoPro Specialist, Human Immune Monitoring Center, ITI): Nanoimmunoassays For Phosphoprotein Analysis
The NanoPro platform enables detailed characterization of proteins from limited biological samples. Current methods of protein detection are insensitive to subtleties in post-translational modification and often require large samples size. NanoPro technology allows quantification of various protein and other small molecule isoforms using capillary electrophoresis. We have used NanoPro to analyze proteins in as little as 500 primary cells and have embraced the system to assist in evaluating clinical therapeutics. Thus, NanoPro may be a promising novel technology for new diagnostic and biomarker studies.
https://www.youtube.com/watch?v=augAjgnn3aY
Robert Tibshirani (Professor, Statistics): Cell Subset Deconvolution of Gene Expression Data
Blood contains many different cell-types, each with its own functional attributes and molecular signature. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity and great difficulty in identifying the cellular source of any perturbations in any assay in which whole tissue measurements are performed in aggregate. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive. With a focus on gene expression analysis, I will present a statistical methodology which estimates in a virtual manner the gene expression data for each cell-type at a group level, and uses these to identify differentially expressed genes at a cell-type specific level between groups. The methodology is widely applicable and can be extended to other data modalities.
https://www.youtube.com/watch?v=T-Hkr2dfxLA
Evan Newell (Postdoctoral Fellow, Microbiology and Immunology): Comparison of Analysis Techniqus for High- Dimensional Flow Cytometry Data
Traditional flow cytometry analysis is done by sequential gating of 2-parameter dot plots. This approach becomes inefficient and limiting with highly multiparameter data sets, such as those generated by CyTOF. Here, several alternative approaches for more objective and comprehensive analysis of such data will be presented. These include heat maps, principle components, and SPADE.
https://www.youtube.com/watch?v=3cDFxbnEUVw
Brian Kidd (Postdoctoral Fellow, ITI): Quality Control, Trending Analyses, and Normalization for Large Data Sets
Quantitative approaches for analyzing the complex data generated from high throughput studies will be discussed. The emphasis will be on data quality control checks, trending analyses of longitudinal data, and normalization routines to account for batch and other effects.
https://www.youtube.com/watch?v=b9P3uuzwgMQ
Professor, Microbiology & Immunology - Baxter Laboratory
Member, Bio-X Member, Child Health Research Institute Member, Stanford Cancer Institute Full bio