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Macrophages are ubiquitously distributed throughout the various tissues of the body and perform many functions including the orchestration of inflammatory responses against pathogens by classically activated M1 macrophages and the regulation of wound healing and tissue remodeling by anti-inflammatory, alternatively activated M2 macrophages. The responsibility for these pleiotropic functions lies in the expression of a myriad of surface receptors unique to given subsets of macrophages. Much of what we know about the function of human macrophage subsets has been gleaned by studying in vitro generated macrophages matured in the presence of GM-CSF or M-CSF and polarized with different cytokines. Oftentimes, culture conditions, such as the type of serum used, the duration of the culture, and the use of polarizing cytokines, vary between studies making direct comparisons difficult. Sample preparation and processing (e.g., Ficoll

Natural killer (NK) lymphocytes exhibit potent responses against transformed and pathogen-infected cells. NK cells can act rapidly as they monitor the bloodstream and tissues for tumorigenic and infected cells that lack “self” markers of MHC class I. Upon recognition of a foreign invader or tumor cell, NK cells release cytotoxic proteins such as interferon-gamma and granzyme B. Because of their ability to recognize stressed cells lacking “self” markers, human NK cells have shown promise as therapeutics in clinical trials to reduce disease burden in patients with therapy-resistant or advanced-stage blood cancers. With more than one hundred NK cell- and induced NK cell-based clinical trials ongoing for blood cancers and refractory solid tumors, there is an ever-increasing need for NK cell therapies to treat cancer and immune diseases. We sought to develop novel, clinically relevant, and robust methods for human NK cell expansion. In addition, to simplify the processing of cells for characterization, we developed a flow cytometry based killing assay to monitor NK activity. Therefore, within the same experiment, we can analyze NK cell phenotype profiles with specific antibody panels while also assessing NK cell killing activity. Using optimized serum- and xeno-free conditions with minimal cell manipulations, we have expanded highly purified NK cells up to 500-fold in 14 days from human peripheral blood mononuclear cells (PBMCs) using optimized cytokines and Cloudz CD2/NKp46 microspheres. To characterize the resulting NK cell population, we used a unique antibody panel to phenotype the NK cells by flow cytometry. Within the same experiment, NK killing assays against K562 cells can be performed using a flow cytometry-based killing assay, which has the advantage of using one instrument for all analyses, shortened processing times, and reproducibility. Using this workflow, we can identify different culture conditions that adversely affect NK activity. Together, this data presents a comprehensive and clinically relevant workflow for the expansion of highly purified NK cells and assessing their killing potential. Furthermore, this workflow can be used for screening the activity of chimeric antigen receptor (CAR) expressing immune cells against specific cancer antigens. Citation Format: Jody Bonnevier, Christine Goetz, Li Peng, Jamie Van Etten, Bora Faulkner, Christopher Hammerbeck, Ariel Miller, Gabriella Perell, Christopher Johnson, Joseph Lomakin, David Hermanson, Kevin Flynn. Assessment of natural killer (NK) cell activity for immunotherapy using a novel flow cytometry-based killing assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB141.

Macrophages are key mediators of tissue homeostasis and inflammation and do so by virtue of differential expression of secreted and cell surface proteins. Cytokines such as IFNγ or IL-4 and IL-13 are known to generate classical proinflammatory M1 and alternatively activated M2 macrophages, respectively, but it is less clear how cell density, cell-cell contact and corticosteroids work together to affect macrophage function. Corticosteroids such as cortisol are known to downregulate the inflammatory signaling but they can also alter the expression of cell surface proteins, such as CD163, on steady-state macrophages. Here we examined the effect of monocyte seeding density and cortisol on the expression of cell surface proteins on human macrophages. The expression of the macrophage markers CD16, CD163, CD204 and VSIG4 were found to correlate with monocyte seeding density such that at low seeding densities, monocyte-derived macrophages were found to express minimal amounts of CD16, CD163, CD204 and VSIG4 while at high seeding densities, expression of these markers was restored. When cultured in the presence of cortisol, macrophages seeded at low densities were found to upregulate expression of these markers, but not CD204, to levels comparable to macrophages seeded at high densities grown in the presence of MCSF. Additionally, in the presence of cortisol, macrophages expressed higher levels of GPBAR1 which has also been shown to reduce classical proinflammatory macrophage activation in colitis models. This data suggests that corticosteroids may regulate macrophage function by modulating the expression of cell surface proteins such as GPBAR1 and not just interfering with morer conventional inflammatory cell signaling pathways..

Natural killer (NK) cells play a key role in the elimination of microbial pathogens and cancer cells. NK cells rapidly respond to stressed cells that are infected or bear tumorigenic mutations that reduce “self” markers of MHC class 1 and/or display increased presentation of activating ligands. These signals prompt NK cells to form an immunological synapse with an infected or tumor cell and discharge lytic granules containing cytotoxic proteins such as IFNγ, perforin and granzyme B leading to target cell destruction. Because of their natural ability to recognize and kill cancer cells, a plethora of preclinical studies and clinical trials have shown that NK cell therapies offer a potentially powerful weapon to fight both advanced-stage blood cancers and solid tumors. Given the great potential of NK cell therapies, we developed clinically relevant serum- and xeno-free methods for human NK cell expansion. Using optimized media and cytokines, either with anti-NKp46 coated tissue culture dishes or Cloudz™ CD2/NKp46 microspheres we have greatly expanded highly purified NK cells from human peripheral blood mononuclear cells (PBMCs) that are capable of potent cytolytic activity, as indicated with a novel flow cytometry-based NK cytotoxicity assay. Using this NK expansion methodology, we performed high-throughput screening methods to identify novel agents that enhance NK cell killing activity as assessed by IFNγ and Granzyme B quantikine ELISA assays which were then confirmed with NK cytotoxicity assays. The methods established here provide a novel workflow for generating highly purified NK cells that are applicable to clinical translation. Furthermore, the agents identified in this work provide insight for augmenting NK killing potential.

Multicolor flow cytometry requires thorough knowledge not only of your proteins of interest, but also of the corresponding fluorochromes that will be used in your panel. Not all fluorochromes are bright, some are prone to photobleaching, and others are sensitive to fixation and permeabilization. In addition, some proteins are high-density such as lineage markers, whereas others are low-density such as markers associated with differentiation. Multicolor flow cytometry will require compensation, thereby dimming some of your proteins of interest due to corrections in spectral overlap. Use of panel builders and spectrum viewers is instrumental in building panels that will perform optimally. In this chapter, we will review the various fluorochromes available for purchase, highlighting their pros and cons. We will also go over how to use spectrum viewers to estimate the degree of spectral overlap between fluorochromes, and how to optimally pair high- and low-density proteins with certain fluorochromes.

Now that you are familiar with the various types of flow cytometers, we will go over how the most common type of flow cytometer, fluidic-based flow cytometers, works. In this chapter, we will touch on the physics of flow cytometry and how photons of light from fluorochromes are translated into meaningful flow cytometry data plots. We will discuss the nature of the excitation lasers and how they are related to the nature of fluorochromes emitting light. The concepts behind Jablonski diagrams and Stokes Shift will be highlighted in this chapter. The rest of the book will focus on the use of fluidic-based flow cytometers. We will cover the three main components of the flow cytometer including the fluidics, optics, and electronics.

The goal of flow cytometry is to quantitate protein expression on cells or classify cells based on the expression of a particular protein. This technique is widespread as it is used in both basic developmental biology labs and the clinic. In either case, the cells need to be processed into a single-cell suspension for evaluating surface and intracellular gene expression. Here, we will discuss the various staining buffers that are used in flow cytometry. In addition, we have outlined detailed protocols for carrying out both surface and intracellular staining in human and rodent tissues such as whole blood and PBMCs. Specifically, for surface staining we outline the various protocols for detection of basic surface markers, chemokine receptors, biotinylated antibodies, and LAMP proteins in natural killer (NK) cells. For intracellular staining, we outline each of the protocols for the various Fixation and Permeabilization buffers systems commonly used including Formaldehyde/Saponin, the FoxP3/Transcription buffer set, and Formaldehyde/Methanol. Finally, in each section, we discuss the various protocols for staining directly conjugated versus unconjugated antibodies.

Flow cytometry, or the analysis of cells in a fluid phase, is a powerful single-cell analysis technique used in nearly every aspect of cell biology research and clinical patient cell analysis. The development of flow cytometry began with the desire to analyze and categorize cells according to their size and phenotype. There are three essential components needed for flow cytometry: instrumentation, highly specific monoclonal antibodies, and fluorescent molecules for the labeling and tagging of desired targets. Consequentially, the three components are closely interwoven and have been co-developed and evolved over many decades. This chapter will cover some of the key events in the history of flow cytometry as a basis for understanding the capabilities of this technique.

Now that you have a basic understanding of the principles of flow cytometry, we will delve into how powerful this technique is for detecting multiparameter surface marker expression on cells. Accurate and clean looking data is always the goal, and we’ll show how to achieve this using dead cell exclusion and Fc block. We’ll demonstrate the importance of titrating your antibodies and using the correct cell number when staining your cells. We’ll discuss how to optimize and detect cell proliferation using various reagents available on the market. We’ll illustrate the importance of temperature when detecting chemokine receptor expression and how to detect LAMP proteins using a killing assay. We’ll end with topics focusing on cellular function such as cell activation, detecting phosphorylated proteins, transcription factor expression, and secreted cytokine upregulation using Intracellular staining.

The language of flow cytometry inadvertently gives the impression that this technique is difficult. However, it is not; there is just a lot of jargon to learn like in any other field. In this chapter, we will define basic terminology that will enable end users to understand concepts important for experimental setup and how to interpret flow cytometry data. In particular, we will discuss FSC and SSC in detail with emphasis on gating strategies and how dead cell exclusion can be used to clean up your data. We will also outline how to interpret flow data on commonly used data plots including histograms, dot plots, and density plots. We will describe the differences between biexponential versus logarithmic scaling. We will define what CS&T is, why it is necessary, and how to apply all these concepts in basic experimental setup. Finally, we will conclude with the fundamental principles of compensation.

Flow cytometry requires robust, sensitive, and specific monoclonal antibodies conjugated to bright, stable fluorochromes. In this chapter, we’ll discuss the development process to generate antibodies specifically geared for use in flow cytometry. We will delve into how this technique is used for detecting multiparameter surface marker expression on cells by outlining how to use unconjugated antibodies in flow. We will finish by describing the various controls that can be used for evaluating protein expression including isotype controls, lineage controls, activation controls, and fluorescence minus one.

When fluorochromes are excited by a laser, they emit photons of light at a range of wavelengths in what is known as that fluorochromes emission spectrum. A portion of this emission spectrum is detected or is “seen” by the flow cytometer. However, when the emission spectrums of multiple fluorochromes overlap, fluorescence spillover can occur. This may negatively impact flow cytometry data, resulting in false positives. Compensation must be performed to eliminate spectral overlap between closely related fluorochromes; otherwise, cells may appear to express surface markers that they do not actually express.

Mesenchymal stem cells (MSCs) are multipotent adult stem cells found in a variety of tissues, including bone marrow, adipose, and umbilical cord. Although MSCs have the ability to differentiate into a variety of cell types useful for regenerative medicine, their ability to modulate the immune system has been at the forefront in the clinic. The mechanisms by which MSCs affect the immune system are not fully understood. This makes it difficult to design specific quality control measures for MSCs used for cell therapy as well as to understand what parameters are the most critical for their immunomodulatory abilities. This specific testing is important to determine batch-to-batch variability and to better forecast patient-to-patient efficacy. In this study, we demonstrate a workflow to investigate the effects of MSCs on immune cell subset populations. Human MSCs were co-cultured with human T cell subtypes (Th1, Th2, Th17, and Treg) that have been differentiated utilizing CellXVivo™ Differentiation Kits. Co-culture supernates are then analyzed via Proteome Profiler™ Antibody Arrays to screen for changes in cytokine levels, relative to MSCs cultured in the absence of T-cells. Analytes discovered to change in the screening arrays are then quantitated using Luminex® Assays. We hypothesize that these tools and techniques will allow for a better understanding of the mechanisms contributing to MSC immunomodulation and provide methods for routine quality control testing of MSC populations prior to clinical use.

Macrophages are ubiquitously distributed throughout the various tissues of the body and perform many functions. These include inflammatory responses against pathogens by classically activated M1 macrophages and the regulation of wound healing and tissue remodeling by anti-inflammatory alternatively activated M2 macrophages. The responsibility for these pleiotropic functions lies in the expression of a myriad of surface receptors unique to a given subset. Much of what we know about the function of human macrophage subsets has been gleaned by studying in vitro generated macrophages, matured in the presence of GM-CSF or M-CSF, and polarized with different cytokines. Oftentimes, culture conditions (such as the type of serum used, the duration of the culture and the use of polarizing cytokines) vary between studies making direct comparisons difficult. Furthermore, overlap in surface marker expression can make it difficult to distinguish between the different macrophage subsets. We directly compared the expression of fifty different surface markers on M1 and M2a macrophages cultured in the presence of fetal bovine serum, human AB serum or serum free media and found that the type or presence of serum used affected the expression of several markers such as CD200R1 and CD32. Moreover, we compared the expression of these surface markers on polarized and unpolarized macrophages and determined that polarization was critical to the expression of several of these markers, such as CD38 and SLAM F7. The results of these studies should significantly expand our knowledge of the phenotypic differences between human M1 and M2a macrophages as well as demonstrate the importance of culture conditions in generating these phenotypes.