How To Use Flow Cytometry To Correctly Define T Cell Subsets And Their Functions

Flow Cytometry is a remarkably powerful tool for the study of T cells. It has been successfully used for many decades to accurately visualize and enumerate a variety of T cell subsets.

With a large sensitivity range for fluorescent probes, >95% sampling efficiency, and the ability to sort populations of interest for further study, fluorescent-based cytometry remains a tool of choice for T cell analysis.

Single cell visualization of T cells in a heterogeneous sample is clearest when the defined T cell populations are determined with ‘rock-solid’ gating and data analysis strategies.

For example, detection of the total CD4 and CD8 T cell compartments (via CD3+ CD4+ and CD3+ CD8+ cells, respectively) is straightforward; also, T cell populations that are clearly defined by surface antigen expression include antigen-specific (tetramer-binding) memory T cell clones and invariant Natural Killer T (iNKT) cells, a unique T cell subset discerned via binding to a CD1d-glycolipid loaded tetramer.

Such gating strategies, when paired with CD3 inclusion, doublet exclusion, and appropriate live/dead gating, allow clear, accurate visualization of your T cell population of interest and enumeration of frequency in your sample.

The Benefits And Caveats Of Advanced T Cell Antibody Panels

Flow panel sizes have expanded dramatically in the last 15+ years and continue to do so. An antibody panel with more than 10-colors is no longer uncommon, and with the adaptation of the more recent Brilliant dyes, 14+ colors are now very feasible on many instruments. With this increase in parameter detection per sample, the subsetting of T cells in the literature has exploded.

For example, when considering one aspect of T cell biology, the naïve to memory differentiation post-antigen exposure, the field has transcended from an era of two subsets (naïve and memory) into the era of Central Memory, Transitional Memory, Effector Memory, Terminally Differentiated Effector Memory, etc.

At first glance, these larger panels bring clarity to the T cell landscape. By revealing more of the complex marker distribution on individual cells, we gain a clearer picture of the heterogeneity of this facet of the immune cell compartment as a whole.

This, in turn, could allow better understanding of how the composite immune system functions in health and disease states (know your players, know the game) and also facilitate discovery of new therapeutic targets (á la anti-PD-1).

However, forcing square pegs into the round holes present in many linear differentiation models (with stages in the process noted via marker changes) can serve to further cloud the T cell field, potentially leading to misleading claims about the actual status of a T cell in a given sample or group of patients.

Some markers can change like the wind (it seems) and we must use caution to not underestimate the complex web of factors beyond mere ‘differentiation’ that impacts a T cell, causing it to express a given marker at a moment in time.

Why T Cell Function Should Guide Your T Cell Analysis

Figure_1_

When trolling these waters, it’s best to pair our T cell subset findings with functional profiling of the population of interest.

The winds of T cell differentiation ‘states’ or who is or is not a bona-fide Treg may change, but a functional profile will serve to anchor the biological relevance and potential role of your T cell population of interest on more solid ground.

This is where flow cytometry cell sorting is advantageous, for sorting and functionally profiling T cell subsets (via a series of elispots or multiplex supernatant analysis of ex vivo cultures, for example) allows highly sensitive, multi-analyte profiling with far fewer cells than would be required for intracellular cytokine staining.

And what is a cell whose face certainly looks naïve (CD45RA+, CCR7+) yet is secreting IFN-g and TNF-a (as such cells have been found in human samples)?

When in doubt, let a cell’s actions lead its definition, and step back from pigeonholing via previously defined label. For example, defining a population as bearing a “surface phenotype resembling a central memory T cell, while secreting Th1 cytokines” is a safe and accurate way to go (see above Figure).

Overall, flow cytometry is an ideal way to visualize T cells in a heterogeneous sample. The key is to define your T cell populations of interest with correct gating strategies and to back up your T cell subset findings with functional analysis of these subsets. A cell’s actions should guide its definition, not the other way around.

To learn more about analyzing T cell subsets and subset function by flow cytometry, and to get access to all of our advanced materials including 20 training videos, presentations, workbooks, and private group membership, get on the Flow Cytometry Mastery Class wait list.

Join Expert Cytometry's Mastery Class
Tim Bushnell, PhD
Tim Bushnell, PhD

Tim Bushnell holds a PhD in Biology from the Rensselaer Polytechnic Institute. He is a co-founder of—and didactic mind behind—ExCyte, the world’s leading flow cytometry training company, which organization boasts a veritable library of in-the-lab resources on sequencing, microscopy, and related topics in the life sciences.

Similar Articles

We Tested 5 Major Flow Cytometry SPADE Programs for Speed - Here Are The Results

We Tested 5 Major Flow Cytometry SPADE Programs for Speed - Here Are The Results

By: Tim Bushnell, PhD

In the flow cytometry community, SPADE (Spanning-tree Progression Analysis of Density-normalized Events) is a favored algorithm for dealing with highly multidimensional or otherwise complex datasets. Like tSNE, SPADE extracts information across events in your data unsupervised and presents the result in a unique visual format. Given the growing popularity of this kind of algorithm for dealing with complex datasets, we decided to test the SPADE algorithm in 5 software packages, including Cytobank, FCS Express, FlowJo, R, and the original, free software made available by the author of SPADE. Which was the fastest?

5 FlowJo Hacks To Boost The Quality Of Your Flow Cytometry Analysis

5 FlowJo Hacks To Boost The Quality Of Your Flow Cytometry Analysis

By: Tim Bushnell, PhD

FlowJo is a powerful tool for performing and analyzing flow cytometry experiments, if you know how to use it to the fullest. This includes understanding embedding and using keywords, the FlowJo compensation wizard, spillover spreading matrix, FlowJo and R, and creating tables in FlowJo. Extending your use of FJ using these hacks will help organize your data, improve analysis and make your exported data easier to understand and explain to others. Take a few moments and explore all you can do with FJ beyond just gating populations.

Statistical Challenges Of Rare Event Measurements In Flow Cytometry

Statistical Challenges Of Rare Event Measurements In Flow Cytometry

By: Tim Bushnell, PhD

It is necessary to sort through hundreds of thousands or millions of cells to find the few events of interest. With such low event numbers, we move away from the comfortable domain of the Gaussian distribution and move into the realm of Poisson statistics. There are 3 points to consider to build confidence in the data that the events being counted are truly events of interest and not random events that just happen to fall into the gates of interest.

How to Optimize Flow Cytometry Hardware For Rare Event Analysis

How to Optimize Flow Cytometry Hardware For Rare Event Analysis

By: Tim Bushnell, PhD

Preparing for rare event analysis requires an understanding of the power and limitation of the instrument to be used. From how fast to run the fluidics, to how the signal is processed to the number of gates that can be used in the sorting experiment, each factor impacts the outcome of the experiment.

How To Choose The Correct Antibody For Accurate Flow Cytometry Results

How To Choose The Correct Antibody For Accurate Flow Cytometry Results

By: Tim Bushnell, PhD

With the added emphasis on reproducibility, it is critical to look at every step where experiments can be improved. No single step makes an experiment more reproducible, rather it is a process, making changes at each stage that leads to reproducibility. Antibodies comprise a critical component that needs to be reviewed. As Bradbury et al. in a commentary in Nature pointed out, the global spending on antibodies is about $1.6 billion a year, and it is estimated about half of that money is spent on “bad” antibodies. This does not include the additional costs of wasted time and effort by…

How To Achieve Accurate Flow Cytometry Calcium Flux Measurements

How To Achieve Accurate Flow Cytometry Calcium Flux Measurements

By: Tim Bushnell, PhD

Dyes exist for the detection of everything from large nucleic acids to reactive oxygen species, and from lipid aggregates to small ions. Concentrations of physiologically important ions such as sodium, potassium, and calcium can be important indicators of health and disease. Calcium ions play an especially critical role in cellular signaling. As a signaling messenger, calcium is involved in everything from muscle contractions, to cell motility, to enzyme activity. Calcium experiments can be very informative, and with the advent of cheaper UV lasers, more and more researchers can use ratiometric measurements to evaluate the signaling processes in phenotypically defined populations.

How to Perform Doublet Discrimination In Flow Cytometry

How to Perform Doublet Discrimination In Flow Cytometry

By: Tim Bushnell, PhD

You are probably familiar with the term, “doublet discrimination” or “doublet exclusion”, and have likely included this flow cytometry measurement into at least some (if not all) of your gating strategies. Even though you may utilize this important gating strategy, you may not have had the chance to delve deeper to explore exactly what doublets are and why it’s critical to exclude them. This article aims to give you insight on the what, why, and how of doublet discrimination.

4 Considerations For Assessing Protein Phosphorylation Using Flow Cytometry

4 Considerations For Assessing Protein Phosphorylation Using Flow Cytometry

By: Tim Bushnell, PhD

For those working in the signaling field, having the ability to take a sample and phenotypically identify it, while knowing what is happening inside the cell to the target molecules of choice opens up a host of new opportunities. These assays are amenable to high throughput setup, meaning that biologically relevant outcomes in pre-clinical drug discovery can be measured directly. All told, with a little forethought, some careful planning and validation, and our helpful tips, phosphoflow assays are within your reach.

5 Essential Calculations For Accurate Flow Cytometry Results

5 Essential Calculations For Accurate Flow Cytometry Results

By: Tim Bushnell, PhD

Flow cytometry is a numbers game. There are percentages of a population, fluorescence intensity measurements, sample averages, data normalization, and more. Many of these common calculations are useful, but surrounded by misconceptions. This primer will help you decide which calculation to use, when to use it, and how to interpret the results.

Top Technical Training eBooks

Get the Advanced Microscopy eBook

Get the Advanced Microscopy eBook

Heather Brown-Harding, PhD

Learn the best practices and advanced techniques across the diverse fields of microscopy, including instrumentation, experimental setup, image analysis, figure preparation, and more.

Get The Free Modern Flow Cytometry eBook

Get The Free Modern Flow Cytometry eBook

Tim Bushnell, PhD

Learn the best practices of flow cytometry experimentation, data analysis, figure preparation, antibody panel design, instrumentation and more.

Get The Free 4-10 Compensation eBook

Get The Free 4-10 Compensation eBook

Tim Bushnell, PhD

Advanced 4-10 Color Compensation, Learn strategies for designing advanced antibody compensation panels and how to use your compensation matrix to analyze your experimental data.