Instructors: John Martin, Mark Wilder, Travis Woods

This lab is designed to give the students a better appreciation of the inner workings of a flow cytometer, taking away some of the mysteries of what is hidden inside the cabinet.’

In this lab session you will assemble a small flow cytometer and use it to measure a sample of fluorescent microspheres. You will learn some of the important steps used in setting up a flow cytometer, some diagnostic clues that are useful for evaluating a flow cytometer’s performance and an appreciation for what is involved in constructing flow cytometers.
This compact flow cytometer is assembled using modular parts according to a detailed protocol. It includes the following components: laser, laser beam shutter, laser power attenuator, beam block, CCD camera and video monitor (used for viewing the laser beam – sample stream intersection region), flow chamber, fluorescence collection optics, fluorescence detector, electronics, oscilloscope and a computer.

Because you will be installing and aligning optical components along a laser beam line good laser safety practice will be discussed and stressed. By the end of the lab session, you will have assembled a working cytometer and will be analyzing the microsphere sample and optimizing the final adjustments to obtain the best CV. In recent years, CVs below 2% have been achieved.

Instructors: Mark Naivar and Jim Freyer

This laboratory will use flow cytometer simulators to learn key concepts of data acquisition, and also cover some basic data analysis. Regardless of whether you are going to gate or model your data to get your final result, and regardless of which instrument you are using, it is important to acquire flow data as accurately as possible. It is much better to collect your data properly up front, rather than try to “fix” poor data after the fact (many acquisition problems simply cannot be “fixed”).

Small teams of students will use flow cytometer simulators to explore critical factors that affect data acquisition (sample preparation, thresholding, PMT voltage, coincidence, aggregates, and sample throughput). Students will be able to reconfigure the cytometer simulator in ways that are impossible for real instruments in order to provide a more intuitive feel for how different conditions can affect data acquisition. We will also cover the basics of data visualization and gating, which are important for evaluating and adjusting acquisition parameters. Finally, the simulator will be used to explore some basic examples of compensation to give students a much better feel for when compensation is important, why it is needed, and how it improves the data that are collected. Because we will be using a simulator, no cells will be harmed, and no one will run out of sample! No lab coats, gloves or goggles required!

Instructors: Rui Gardner and Carolyn O’Connor

This practical laboratory session will focus on several areas of interest in cell sorting that apply to particle sorting in general. We will cover instrument setup based on the task at hand. In other words, how to realistically approach optimizing nozzle size, stream stability, deflection envelope, break off, drop rate and sample rate for any given experiment. The lab will try to provide the attendee with approaches for use in their own facility in problem solving a wide variety of sorting experiments, regardless of the cytometer they use, including suggestions on advising facility users on sample preparation.

Students will be grouped by prior cell sorting experience and the content will be tailored the the experience of each group.

Instructors: John Nolan

Modern flow cytometers are engineering marvels, capable of high throughput, quantitative, spectrally-resolved measurements of even low amounts of light from individual particles. Yet, a flow cytometer cannot measure a biological quantity unless it is appropriately calibrated and used with an optimized and validated assay. In this lab session we will review the principles of flow cytometer calibration, illustrate their application to several different instruments, and discuss the generation reporting of calibrated measurements for specific assays.

Instructors: Kathleen McGrath and Aja Reiger

Flow cytometry and microscopy are two powerhouse single cell analytical technologies. When combined, they can give unprecedented information about cell biology. In this lab, you will learn to how to analyze data that contain both types of information to answer biologically relevant questions. We will be utilizing an ImageStream flow cytometer (ISXMarkII) from Luminex (Amnis Corp). The bulk of the time, the class will doing independent hands-on tutorials of your choice that will teach fundamentals and advanced nuances in the combined gating of intensity level, shape, size, and texture to address a specific question in that data set. We will be available to assist and answer any questions, but the best way to learn this type of analysis is to do it! These tutorials range from those for training beginners to challenging experienced imaging flow cytometrists, with the central concepts of gating, masking, and combined morphometric/fluorescent feature selection that are core to any flow cytometric imaging analysis. We will include training data sets for the new machine learning module which makes combined features (like PCA or tSNE). Students will also run the ImageStream and look “under the hood” to see how it works. Finally, we will take some short breaks to discuss best practices for publishing imaging flow data, issues and value of compensation in imaging data, and how to encourage and train users in a core facility with this approach. The ultimate goal of the lab is to empower the participants to know if you can see a difference in cells, you can use imaging flow cytometry to quantitate it.

Instructor: Lauren Nettenstrom and Fred Preffer

Flow cytometry is a method for analyzing cells for multiple surface and intracellular proteins utilizing excitation lasers and monoclonal antibodies conjugated to unique fluorescent tags. Additionally, simultaneous light scatter measurements that impart cell size and complexity are coupled with this information to identify and describe individual leukocyte cell populations. There will be a concentrated discussion about the antibody/antigen reaction, antibody kinetics, antibody titration, conjugated versus unconjugated antibodies, the importance of choosing the correct monoclonal antibody clone as well as choosing the correct antibody/fluorochrome combination. We will go through the steps of successful panel design, perform an antibody titration, calculate the antibody’s signal-to-noise ratio, stain different combinations of reagents, determine both the optimal antibody clone and its preferred fluorochrome combination, and discuss the mechanics of staining, surface versus intracellular as well as all the reagents necessary to properly develop successful staining.

Instructors: Lola Martinez and Rachel Sheridan

This laboratory will use spectral flow cytometers from three different manufacturers (BD, Cytek and Sony) to learn key concepts to take into consideration when running and troubleshooting your spectral flow experiment.

Together, we will set up and acquire an 11-color immunophenotyping experiment on human PBMCs. We will cover gain or voltage optimization, threshold, area scaling factor, importance of reagent titration and the controls you need to succeed. We will also perform unmixing of our data and troubleshooting of controls – what is important to look at? Autofluorescence removal will be discussed and carried out in our samples.

A short survey will be sent before the course to assess students experience in spectral cytometry. We will work with a small group of students, and we will try to group them by their previous experience trying as much as possible to tailor the sessions to the experience and cytometer access of each group.

Instructors: Kathy Muirhead and Joe Tario

Flow cytometry is a powerful tool for monitoring three key aspects of adaptive immunity: antigen recognition, clonal expansion, and apoptotic cell death. In this lab we will focus on critical issues for:

• Identification of antigen-specific T cells using multimer labeling.
• Proliferation monitoring using dye dilution.
• Early apoptosis detection using probes for caspase activation, membrane integrity, and phosphatidylserine externalization.

Participants will be divided into small groups for hands-on experience with:

• Immunophenotpyic characterization of low-frequency multimer binding T cells.
• Staining optimization for proliferation analysis using protein-reactive or membrane intercalating dyes (CFSE, PKH26 and newer analogs of each).
• Probe selection for multicolor assays correlating antigen specificity with downstream outcomes (e.g., cell division, apoptosis).

Instructors: Paul Wallace, Vince Shankey, Kah Teong Soh

Lipopolysaccharide (LPS), a cell wall component found in most Gram-negative bacteria, activates signaling cascades in several different cell types, including some hematopoietic cells. Monocytes express surface Toll-like receptor-4 (TLR4), which binds LPS, and in conjunction with CD14, initiates a signaling cascade that results in the degradation of IkB (Inhibitor of NFKB) and release of NFKB (nuclear factor kappa B), with the latter localizing into the nucleus. There, NFKB binds to transcriptional initiation sites, resulting in the synthesis of new mRNA and translation into monokines and other proteins. Given the complexity of the response triggered by different cell populations, single cell flow cytometric analysis of signaling and downstream protein/cytokine expression patterns has greatly advanced our understanding of the immune system.

This lab will follow the kinetics of antigen binding, NFKB translocation, mRNA transcription, and protein expression. We will:

• Review the signal transduction pathways that regulate the acute inflammatory response via the NFKB transcription factor and methods to measure them.
• Discuss technical variations to simultaneously detect cell surface and intracellular targets.
• Present a simple approach to fixation and permeabilization which provide access to cytoplasmic and nuclear compartments.
• Discuss the technical aspects of simultaneously measuring intracellular mRNA and protein targets.
• Understand and appreciate the cytokine/monokine mRNA and protein kinetic profiles in activated lymphocytes and monocytes.
• In the hands-on wet lab portion, participates will stain and analyze control and activated lymphocytes for surface markers (CD45, CD3, CD4, and CD8), intracellular cytokines (IFNγ, IL-4, and IL-2), and viability.

Instructors: Joanne Lannigan, Vera Tang and Joshua Welsh

While implementing best practices is important in all cytometry, it is especially important when analyzing extracellular vesicles and other small particles because of their size. In this lab, you will learn how to optimize and quantify the sensitivity of your instrument for detecting small particles, determine whether you are detecting single particles or “coincidence”, utilize controls to interpret results, and calibrate your fluorescence and light scatter signals for downstream analysis and reporting in standard units.

Instructors: Dagna Sheerar and Kelly Lundsten

In this lab students will walk through the workflow of designing an optimized, rigorous, and reproducible flow cytometry panel. The tips and tricks shared in this lab will be applicable to all panels, small or large. With the goal of maximizing sensitivity for each marker detected in the assay, we’ll discuss power calculations to determine sample size, sample preparation, protocol development and optimization, annotation and record keeping, characteristics of available fluorochromes, characteristics of markers of interest, how to optimally pair markers with fluorochromes, proper controls, instrument characteristics, spillover spreading, assay standardization, and considerations for high dimensional data analysis. Students attending this lab should walk away with an understanding of proper considerations and a workflow for designing an optimal, rigorous, and reproducible flow cytometry assay.

Instructors: John Quinn & Chris Ciccolella

Recent advancements in cytometry allow us to measure an increasing number of features per cell, generating huge high-dimensional datasets. This creates challenges for data analysis. Traditional approaches based on subjective manual gating on biaxial plots are not sufficient. Computational techniques have been developed to analyze, visualize, and interpret these data. These techniques fall into seven primary categories: automated quality assessments, dimensionality reduction, automated cell and sample classification, normalization and batch effect removal, trajectory inference, differential statistics, and visualization.

This lab will introduce attendees to some of these techniques and approaches. We will discuss the pros and cons and practical aspects of different methods using a hands-on manner with a high-dimensional dataset. We will walk through a full high-dimensional workflow in both FlowJo™ version 10.9 and OMIQ, focusing our discussion on when an algorithm can expedite your analysis, how to use it, and what the differences are in similar algorithms, for example, tSNE and UMAP.  Our goal is to give you a good understanding of the mechanisms of a wide range of algorithms and the ability to use them in commercially available software.

Instructors: Suzie Alarcon and Si-Han Hai

This lab will provide an opportunity to learn techniques that are integral to several single cell genomics technologies. Students will receive guidance spanning the entire single cell workflow, including: generating quality single-cell suspensions; staining for cell surface proteins with both flow cytometry and NGS readouts (CITE-seq); cell-counting and morphological assessment; multiple methods for isolating single cells for multiomic interrogation, including cell partitioning using a microwell system and Gel Beads in Emulsion (GEMs); cDNA construction and quality control; and library prep. We will discuss common failure modes, and how to diagnose as well as mitigate them. We will also explore high-level bioinformatics analyses of single cell datasets.