Panel Optimization for High-Dimensional Immunophenotyping Assays Using Full-Spectrum Flow Cytometry

Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization

Flow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2-3 months) and aged (18-19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+ and CD4+ T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.

Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by photo-excitatory molecular content, which can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and, even within one cell type, heterogeneity of autofluorescence spectra can be present, for example, as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of photo detectors across a range of wavelengths, creating an unique signature for that fluorochrome. This signature is then used to identify, or unmix, that fluorochrome's unique spectrum from a multicolor sample containing different fluorescent molecules. Importantly, this means that this technology can also be used to identify intrinsic autofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has a singular, relatively homogeneous and bright autofluorescence spectrum. To analyze samples with heterogeneous autofluorescence spectral profiles, we setup an unbiased workflow to more quickly identify differing autofluorescence spectra present in a sample to include as "autofluorescence signatures" during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering of unstained cells. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. Independent of the intensity of the autofluorescence and immunophenotyping of cell subsets, this unbiased method allows for the identification of most of the distinct autofluorescence spectra present in a sample, leading to less confounding autofluorescence spillover and spread into extrinsic phenotyping markers. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells, and in vitro cultures of (primary) cells.

Immune cells at the feto-maternal interface: Comprehensive characterization and insights into term labor

Immune cells at the feto-maternal interface play an important role in pregnancy; starting at implantation, maintenance of pregnancy, and parturition. The role of decidual immune cells in induction of labor still needs to be understood. Published reports on this topic show heterogeneity in methods of cell isolation, assay, analysis and cellular characterization making it difficult to collate available information in order to understand the contribution of immune cells at term leading to parturition. In the present study, available literature was reviewed to study the differences in immune cells between the decidua basalis and decidua parietalis, as well as between immune cells in term and preterm labor. Additionally, immune cells at the decidua parietalis were isolated from term not in labor (TNL) or term in labor (TL) samples and characterized via flow cytometry using a comprehensive, high-dimensional antibody panel. This allowed a full view of immune cell differences without combining multiple studies, which must include variation in isolation and analysis methods, for more conclusive data. The ratio of cells found in decidua parietalis in this study generally matched those reported in the literature, although we report a lower percentage of natural killer (NK) cells at term. We report that CD4 expression on CD8- NK cells decreased in term labor compared to not in labor samples, suggesting that natural killer cells may be migrating to other sites during labor. Also, we report a decrease in CD38 expression on CD8+ CD57+ T cells in labor, indicative of cytotoxic T cell senescence. Our study provides a comprehensive status of immune cells at the decidua-chorion interface at term.

OMIP-102: 50-color phenotyping of the human immune system with in-depth assessment of T cells and dendritic cells

We report the development of an optimized 50-color spectral flow cytometry panel designed for the in-depth analysis of the immune system in human blood and tissues, with the goal of maximizing the amount of information that can be collected using currently available flow cytometry platforms. We established and tested this panel using peripheral blood mononuclear cells (PBMCs), but included CD45 to enable its future use for the analysis of human tissue samples. The panel contains lineage markers for all major immune cell subsets, and an extensive set of phenotyping markers focused on the activation and differentiation status of the T cell and dendritic cell (DC) compartment. We outline the biological insight that can be gained from the simultaneous measurement of such a large number of proteins and propose that this approach provides a unique opportunity for the comprehensive exploration of the immune status in human samples with a limited number of cells. Of note, we tested the panel to be compatible with cell sorting for further downstream applications. Furthermore, to facilitate the wide-spread implementation of such a panel across different cohorts and samples, we established a trimmed-down 45-color version which can be used with different spectral cytometry platforms. Finally, to generate this panel, we utilized not only existing panel design guidelines, but also developed new metrics to systematically identify the optimal combination of 50 fluorochromes and evaluate fluorochrome-specific resolution in the context of a 50-color unmixing matrix.

Fluorochrome-dependent specific changes in spectral profiles using different compensation beads or primary cells in full spectrum cytometry

Full spectrum flow cytometry is a powerful tool for immune monitoring on a single-cell level and with currently available machines, panels of 40 or more markers per sample are possible. However, with an increased panel size, spectral unmixing issues arise, and appropriate single stain reference controls are required for accurate experimental results and to avoid unmixing errors. In contrast to conventional flow cytometry, full spectrum flow cytometry takes into account even minor differences in spectral signatures and requires the full spectrum of each fluorochrome to be identical in the reference control and the fully stained sample to ensure accurate and reliable results. In general, using the cells of interest is considered optimal, but certain markers may not be expressed at sufficient levels to generate a reliable positive control. In this case, compensation beads show some significant advantages as they bind a consistent amount of antibody independent of its specificity. In this study, we evaluated two types of manufactured compensation beads for use as reference controls for 30 of the most commonly used and commercially available fluorochromes in full spectrum cytometry and compared them to human and murine primary leukocytes. While most fluorochromes show the same spectral profile on beads and cells, we demonstrate that specific fluorochromes show a significantly different spectral profile depending on which type of compensation beads is used, and some fluorochromes should be used on cells exclusively. Here, we provide a list of important considerations when selecting optimal reference controls for full spectrum flow cytometry.

Within- and between-subject biological variation estimates for the enumeration of lymphocyte deep immunophenotyping and monocyte subsets

OBJECTIVES

This study aimed to deliver biological variation (BV) estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping (memory T/B cells, regulatory T cells, etc.) and classical, intermediate, and nonclassical monocyte subsets based on the full spectrum flow cytometry (FS-FCM) and a Biological Variation Data Critical Appraisal Checklist (BIVAC) design.

METHODS

Samples were collected biweekly from 60 healthy Chinese adults over 10 consecutive two-week periods. Each sample was measured in duplicate within a single run for lymphocyte deep immunophenotyping and monocyte subset determination using FS-FCM, including the percentage (%) and absolute count (cells/μL). After trend adjustment, a Bayesian model was applied to deliver the within-subject BV (CVI) and between-subject BV (CVG) estimates with 95 % credibility intervals.

RESULTS

Enumeration (% and cells/μL) for 25 types of lymphocyte deep immunophenotyping and three types of monocyte subset percentages showed considerable variability in terms of CVI and CVG. CVI ranged from 4.23 to 47.47 %. Additionally, CVG ranged between 10.32 and 101.30 %, except for CD4+ effector memory T cells re-expressing CD45RA. No significant differences were found between males and females for CVI and CVG estimates. Nevertheless, the CVGs of PD-1+ T cells (%) may be higher in females than males. Based on the desired analytical performance specification, the maximum allowable imprecision immune parameter was the CD8+PD-1+ T cell (cells/μL), with 23.7 %.

CONCLUSIONS

This is the first study delivering BV estimates for 25 types of lymphocyte subpopulations subjected to deep immunophenotyping, along with classical, intermediate, and nonclassical monocyte subsets, using FS-FCM and adhering to the BIVAC design.

FLAER as a standalone reagent for paroxysmal nocturnal hemoglobinuria: Do we need to reconsider the guidelines for testing?

INTRODUCTION

Flow cytometry-based paroxysmal nocturnal hemoglobinuria (PNH) testing involves utilization of monoclonal antibodies against GPI-linked proteins and FLAER. The ability of FLAER to bind to a wide variety of GPI-linked structures and to be utilized across different leukocyte subsets is remarkable. We hypothesize that FLAER as a standalone reagent may be equally effective for detecting PNH clones. The present study intends to compare the results of a FLAER alone-based strategy to the recommended FLAER+GPI-linked protein-based approach for applicability in clinical settings.

METHODS

EDTA-anticoagulated blood samples from patients for PNH workup were tested for PNH by multiparametric flow cytometry. A conventional panel comprising gating markers (CD45 for WBC, CD15 for granulocytes, and CD64 for monocytes) and a combination of FLAER and GPI-linked markers, such as CD24 and CD14, henceforth referred to as the "routine panel," was employed. Second, a "FLAER-only panel" comprising the gating markers and FLAER alone (excluding the GPI-linked markers CD24 and CD14) was set up. The samples were processed using the lyse-wash-stain-wash technique, and events were acquired on BC Navios Ex flow cytometer (Beckman Coulter, Inc., USA) and analyzed on Kaluza Software 2.1. The presence of a PNH clone was reported at a value of ≥0.01%.

RESULTS

A total of 209 patients were tested. Both panels found a PNH clone in 20.1% of patients (n = 42/209) with a 100% concordance rate. The PNH clone range for granulocytes was 0.01%-89.68%, and for monocyte was 0.04%-96.09% in the routine panel. The range in the FLAER-only panel for granulocytes was 0.01%-89.61%, and for monocytes, it was 0.01%-96.05%. Pearson correlation statistics revealed a significant correlation between the size of the PNH clone of granulocytes and monocytes among the two panels tested (granulocytes r = 0.9999, p < 0.0001, 95% CI = 0.9999 to 1.000; monocytes r = 0.9974, p < 0.0001, 95% CI = 0.9966-0.9980).

CONCLUSION

Based on our results, FLAER as a standalone marker is specific and sensitive for identifying PNH clones in granulocytes and monocytes, even for high-sensitivity PNH assay. The proposed "FLAER-only panel" panel is efficient and cost-effective for highly sensitive PNH testing in two different cell lineages, especially in resource-limited clinical settings.

Immunophenotyping challenging tissue types using high-dimensional full spectrum flow cytometry

Technological advancements in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system, have led to the development of large flow cytometry panels, reaching up to 40 markers at the single-cell level. Full spectrum flow cytometry, that measures the full emission range of all the fluorophores present in the panel instead of only the emission peaks is now routinely used in many laboratories internationally, and the demand for this technology is rapidly increasing. With the capacity to use larger and more complex staining panels, optimized protocols are required for the best panel design, panel validation and high-dimensional data analysis outcomes. In addition, for ex vivo experiments, tissue preparation methods for single-cell analysis should also be optimized to ensure that samples are of the highest quality and are truly representative of tissues in situ. Here we provide optimized step-by-step protocols for full spectrum flow cytometry panel design, tissue digestion and panel optimization to facilitate the analysis of challenging tissue types.

A 19-color single-tube full spectrum flow cytometry assay for the detection of measurable residual disease in acute myeloid leukemia

Multiparameter flow cytometry (MFC) has emerged as a standard method for quantifying measurable residual disease (MRD) in acute myeloid leukemia. However, the limited number of available channels on conventional flow cytometers requires the division of a diagnostic sample into several tubes, restricting the number of cells and the complexity of immunophenotypes that can be analyzed. Full spectrum flow cytometers overcome this limitation by enabling the simultaneous use of up to 40 fluorescent markers. Here, we used this approach to develop a good laboratory practice-conform single-tube 19-color MRD detection assay that complies with recommendations of the European LeukemiaNet Flow-MRD Working Party. We based our assay on clinically-validated antibody clones and evaluated its performance on an IVD-certified full spectrum flow cytometer. We measured MRD and normal bone marrow samples and compared the MRD data to a widely used reference MRD-MFC panel generating highly concordant results. Using our newly developed single-tube panel, we established reference values in healthy bone marrow for 28 consensus leukemia-associated immunophenotypes and introduced a semi-automated dimensionality-reduction, clustering and cell type identification approach that aids the unbiased detection of aberrant cells. In summary, we provide a comprehensive full spectrum MRD-MFC workflow with the potential for rapid implementation for routine diagnostics due to reduced cell requirements and ease of data analysis with increased reproducibility in comparison to conventional FlowMRD routines.

High-Dimensional Methods of Single-Cell Microglial Profiling to Enhance Understanding of Neuropathological Disease

Microglia are the innate myeloid cells of the central nervous system (CNS) parenchyma, functionally implicated in almost every defined neuroinflammatory and neurodegenerative disorder. Current understanding of disease pathogenesis for many neuropathologies is limited and/or lacks reliable diagnostic markers, vaccines, and treatments. With the increasing aging of society and rise in neurogenerative diseases, improving our understanding of their pathogenesis is essential. Analysis of microglia from murine disease models provides an investigative tool to unravel disease processes. In many neuropathologies, bone-marrow-derived monocytes are recruited to the CNS, adopting a phenotype similar to that of microglia. This significantly confounds the accurate identification of cell-type-specific functions and downstream therapeutic targeting. The increased capacity to analyze more phenotypic markers using spectral-cytometry-based technologies allows improved separation of microglia from monocyte-derived cells. Full-spectrum profiling enables enhanced marker resolution, time-efficient analysis of >40 fluorescence parameters, and extraction of cellular autofluorescence parameters. Coupling this system with additional cytometric technologies, including cell sorting and high-parameter imaging, can improve the understanding of microglial phenotypes in disease. To this end, we provide detailed, step-by-step protocols for the analysis of murine brain tissue by high-parameter ex vivo cytometric analysis using the Aurora spectral cytometer (Cytek), including best practices for unmixing and autofluorescence extraction, cell sorting for single-cell RNA analysis, and imaging mass cytometry. Together, this provides a toolkit for researchers to comprehensively investigate microglial disease processes at protein, RNA, and spatial levels for the identification of therapeutic targets in neuropathology. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Processing the mouse brain into a single-cell suspension for microglia isolation Basic Protocol 2: Staining single-cell mouse brain suspensions for microglial phenotyping by spectral cytometry Basic Protocol 3: Flow cytometric sorting of mouse microglia for ex vivo analysis Basic Protocol 4: Processing the mouse brain for imaging mass cytometry for spatial microglia analysis.

Review of flow cytometry as a tool for cell and gene therapy

Quality control testing and analytics are critical for the development and manufacture of cell and gene therapies, and flow cytometry is a key quality control and analytical assay that is used extensively. However, the technical scope of characterization assays and safety assays must keep apace as the breadth of cell therapy products continues to expand beyond hematopoietic stem cell products into producing novel adoptive immune therapies and gene therapy products.  Flow cytometry services are uniquely positioned to support the evolving needs of cell therapy facilities, as access to flow cytometers, new antibody clones and improved fluorochrome reagents becomes more egalitarian. This report will outline the features, logistics, limitations and the current state of flow cytometry within the context of cellular therapy.

Panel Design and Optimization for Full Spectrum Flow Cytometry

Technological advancements in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system have led to the development of large flow cytometry panels, reaching up to 40 markers at the single-cell level. Full spectrum flow cytometry, which measures the full emission range of all the fluorophores present in the panel instead of only the emission peaks, is now routinely used in laboratories around the world, and the demand for this technology is rapidly increasing. With the ability to use larger and more complex staining panels, optimized protocols are vital for achieving the best panel design, panel optimization, and high-dimensional data analysis outcomes. In addition, a better understanding of how to fully characterize the autofluorescence of the sample, coupled with an intelligent panel design approach, allows improved marker resolution on highly autofluorescent tissues or cells. Here, we provide optimized step-by-step protocols for full spectrum flow cytometry, covering panel design and optimization, autofluorescence evaluation and strategy selection, and methods for performing longitudinal studies.

Flow cytometry analysis of protein expression using antibody-derived tags followed by CITE-Seq

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) is a single-cell phenotyping method that uses antibody-derived tags (ADTs) to quantitatively detect cell surface protein expression and generate transcriptomic data at the single-cell level. Despite the increased popularity of this technique to study cellular heterogeneity and dynamics, detailed methods on how to choose ADT markers and ensuring reagent performance in biological relevant systems prior to sequencing is not available. Here we describe a novel and easy-to-use multiplex flow proxy assay in which multiple protein markers can be measured simultaneously using a combination of ADT reagents and dye-oligo conjugates by flow cytometry. Using dye-oligo conjugates with sequences complementary to the ADT reagents, we can achieve specific binding and evaluate protein marker expression in a multiplex way. This quality control assay is useful for guiding ADT marker choice and confirming protein expression prior to sequencing. Importantly, the labeled cells can be directly isolated based on the specific fluorescence from dye-oligo conjugates using a flow cytometry cell sorter and processed for downstream single-cell multiomics. Using this streamlined workflow, we sorted natural killer cells and T cells efficiently using only ADT and dye-oligo reagents, avoiding the possibility of decreased marker resolution from co-staining cells with ADT and fluorescent antibodies. This novel workflow provides a viable option for improving ADT marker choice and cell sorting efficiency, allowing subsequent CITE-Seq.

Quantitative flow cytometry enables end-to-end optimization of cross-platform extracellular vesicle studies

Flow cytometry (FCM) is a common method for characterizing extracellular particles (EPs), including viruses and extracellular vesicles (EVs). Frameworks such as MIFlowCyt-EV exist to provide reporting guidelines for metadata, controls, and data reporting. However, tools to optimize FCM for EP analysis in a systematic and quantitative way are lacking. Here, we demonstrate a cohesive set of methods and software tools that optimize FCM settings and facilitate cross-platform comparisons for EP studies. We introduce an automated small-particle optimization (SPOT) pipeline to optimize FCM fluorescence and light scatter detector settings for EP analysis and leverage quantitative FCM (qFCM) as a tool to further enable FCM optimization of fluorophore panel selection, laser power, pulse statistics, and window extensions. Finally, we demonstrate the value of qFCM to facilitate standardized cross-platform comparisons, irrespective of instrument configuration, settings, and sensitivity, in a cross-platform standardization study utilizing a commercially available EV reference material.

50-color phenotyping of the human immune system with in-depth assessment of T cells and dendritic cells

We report the development of an optimized 50-color spectral flow cytometry panel designed for the in-depth analysis of the immune system in human blood and tissues, with the goal of maximizing the amount of information that can be collected using currently available flow cytometry platforms. We established and tested this panel using peripheral blood mononuclear cells (PBMCs), but included CD45 to enable its use for the analysis of human tissue samples. The panel contains lineage markers for all major immune cell subsets, and an extensive set of phenotyping markers focused on the activation and differentiation status of the T cell and dendritic cell (DC) compartment. We outline the biological insight that can be gained from the simultaneous measurement of such a large number of proteins and propose that this approach provides a unique opportunity for the comprehensive exploration of the immune status in tissue biopsies and other human samples with a limited number of cells. Of note, we tested the panel to be compatible with cell sorting for further downstream applications. Furthermore, to facilitate the wide-spread implementation of such a panel across different cohorts and samples, we established a trimmed-down 45-color version which can be used with different spectral cytometry platforms. Finally, to generate this panel, we utilized not only existing panel design guidelines, but also developed new metrics to systematically identify the optimal combination of 50 fluorochromes and evaluate fluorochrome-specific resolution in the context of a 50-color unmixing matrix.

Side-by-Side Comparison of Compensation Beads Used in Polychromatic Flow Cytometry

Compensation or unmixing is essential in analyzing multiparameter flow cytometry data. Errors in data correction, either by compensation or unmixing, can completely change the outcome or mislead the researchers. Owing to limited cell numbers, researchers often use synthetic beads to generate the required single stains for the necessary calculation. In this study, the capacity of synthetic beads to influence data correction is evaluated. Corrected data for human peripheral blood cells were generated using cell-based compensation from the same cells or bead-based compensation to identify differences between the methods. These data suggest that correction with beads on full-spectrum and conventional cytometers does not always follow the basic flow compensation/unmixing expectations and alters the data. Overall, the best approach for bead-based correction for an experiment is to evaluate which beads and fluorochromes are most accurately compensated/unmixed.

Multicompartmental analysis of the murine pulmonary immune response by spectral flow cytometry

Studies of pulmonary inflammation require unique considerations due to the complex structure and composition of the lungs. The lungs have multiple compartments and diverse immune cell populations, with inherently high autofluorescence, and are involved in the host response to pulmonary pathogens. We describe a protocol that accounts for these factors through a novel combination of methodologies-in vivo compartmental analysis and spectral flow cytometry with a broad panel of antibodies. In vivo compartmental analysis enables the precise localization of immune cells within the marginated vasculature, lung interstitium, nonlavageable airways, and lavageable airways of the lungs, as well as the pulmonary lymph nodes. Spectral flow cytometry with a broad panel of antibodies supports an unbiased exploratory approach to investigating diverse immune cell populations during pulmonary inflammation. Most importantly, spectral flow uses cellular autofluorescence to aid in the resolution and identification of immune cell populations. This methodology enables the acquisition of high-quality data compatible with informed gating and dimensionality reduction algorithms. In addition, our protocol emphasizes considerations for compartmentalization of the inflammatory response, spectral flow panel design, and autofluorescence spectra analysis. These methodologies are critical for increasing the rigor of pulmonary research. We apply this protocol for the precise characterization and localization of leukocytes in the pulmonary host response to influenza A virus in C57BL/6J mice. In particular, we demonstrate that this protocol improves the quantification and localization of alveolar macrophages within the airways. The methodology is modifiable and expandable to allow for further characterization of leukocyte populations of special interest.NEW & NOTEWORTHY We describe a novel combination of methodologies that incorporates dual in vivo compartmental analysis using intravascular and intratracheal CD45 labeling, a broad panel of antibodies for identifying lymphoid and nonlymphoid cells, and spectral flow cytometry that uses cellular autofluorescence to aid in resolving and identifying immune cell populations. This methodology allows precise localization of immune cells in the lavageable airways, nonlavageable airways, interstitial lung tissue, and marginated in the lung vasculature.

Detection of radiation-induced senescence by the Debacq-Chainiaux protocol: Improvements and upgrade in the detection of positive events

Senescent cells are blocked in the cell cycle but remain metabolically active. These cells, once engaged in the senescence process, fail to initiate DNA replication. Due to the shortening of telomeres, replicative senescence can be triggered by a DNA damage response. Moreover, cells can also be induced to senesce by DNA damage in response to elevated reactive oxygen species (ROS), activation of oncogenes, cell-cell fusion or after ionizing radiation. There are multiple experimental ways to detect senescent cells directly or indirectly. Senescence-associated cellular traits (SA β-Gal activity, increase in cell volume and lysosome content, appearance of γ-H2AX foci, increase of ROS and oxidative damage adducts, etc.) can be identified by numerous methods of detection (flow cytometry, confocal imaging, in situ staining, etc.). Here, we improved an existing flow cytometry protocol and further developed a new one specifically tailored to ionizing radiation-induced endothelial senescence. Thus, we have upgraded the Debacq-Chainiaux protocol and added improvements in this protocol (i) to better detect positive events (ii) to offer a compatibility to simultaneously analyze various intracellular molecules including phosphorylated signaling proteins and cytokines, whether related or not to senescence processes.

A 16-color full spectrum flow cytometric analysis for comprehensive evaluation of T-cell reconstitution in SIV-infected rhesus macaques

T-cell reconstitution is central in human immunodeficiency virus (HIV) infection/disease progression. Simian immunodeficiency virus (SIV)-infected rhesus macaques (Macaca mulatta) have been the most widely used animal model for HIV research so far. An effective flow cytometry panel is crucial for monitoring the T cell reconstitution in SIV infection progression. We developed this sixteen-color flow cytometry-based panel for a T cell subsets analysis by manual gating and, once successfully gated, to characterize T cells function in-depth in rhesus macaques. This panel included markers to characterize CD4+ T cells and CD8+ T cells, T regulatory cells (Tregs), and T cell differentiation status (CD45RA and CCR7). Additionally, we included antibodies that measure T cell activation and proliferation molecules (CD69, HLA-DR, CD38 and Ki67), antibodies that examine the expressions of key PD-1 pathway molecule (PD-1), SIV potential target (CD32) and the primary SIV co-receptor CCR5 (CD195). High-dimensional single cell analysis was also performed to identify CD3+ T cells immunophenotypes of SIV-infected rhesus macaques. We designed this panel to evaluate the responses of different T cell subsets to SIV in whole blood from SIV-infected rhesus macaques.

Ensuring Full Spectrum Flow Cytometry Data Quality for High-Dimensional Data Analysis

Full spectrum flow cytometry (FSFC) allows for the analysis of more than 40 parameters at the single-cell level. Compared to the practice of manual gating, high-dimensional data analysis can be used to fully explore single-cell datasets and reduce analysis time. As panel size and complexity increases so too does the detail and time required to prepare and validate the quality of the resulting data for use in downstream high-dimensional data analyses. To ensure data analysis algorithms can be used efficiently and to avoid artifacts, some important steps should be considered. These include data cleaning (such as eliminating variable signal change over time, removing cell doublets, and antibody aggregates), proper unmixing of full spectrum data, ensuring correct scale transformation, and correcting for batch effects. We have developed a methodical step-by-step protocol to prepare full spectrum high-dimensional data for use with high-dimensional data analyses, with a focus on visualizing the impact of each step of data preparation using dimensionality reduction algorithms. Application of our workflow will aid FSFC users in their efforts to apply quality control methods to their datasets for use in high-dimensional analysis, and help them to obtain valid and reproducible results. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Data cleaning Basic Protocol 2: Validating the quality of unmixing Basic Protocol 3: Data scaling Basic Protocol 4: Batch-to-batch normalization.

Platelet Phenotyping by Full Spectrum Flow Cytometry

Platelets play key roles in hemostasis, immunity, and inflammation, and tests of platelet phenotype and function are useful in studies of disease biology and pathology. Full spectrum flow cytometry offers distinct advantages over standard tests and enables the sensitive and simultaneous detection of many biomarkers. A typical assay provides a wealth of information on platelet biology and allows the assessment of in vivo activation and in vitro reactivity, as well as the discovery of novel phenotypes. Here, we describe the analysis of platelets by full spectrum flow cytometry and discuss a range of controls and methods for interpreting results. © 2023 Wiley Periodicals LLC. Basic Protocol: Platelet phenotyping by full spectrum flow cytometry Support Protocol 1: Spectral unmixing Support Protocol 2: Data preprocessing.

Analyzing the Tumor-Immune Microenvironment by Flow Cytometry

Flow cytometry is an essential tool for studying the tumor-immune microenvironment. It allows us to quickly quantify and identify multiple cell types in a heterogeneous sample. This chapter provides an overview of the flow cytometry instrumentation and a discussion of the appropriate considerations and steps in building a reproducible flow cytometry staining panel. We present an updated lymphoid tissue and solid tumor-infiltrating leucocyte flow cytometry staining protocol and an example of flow cytometry data analysis.

Cross-platform immunophenotyping of human peripheral blood mononuclear cells with four high-dimensional flow cytometry panels

Immunophenotyping using high dimensional flow cytometry is a central component of human immune system multi-omic studies. We present four high parameter flow cytometry panels for deep immunophenotyping of human peripheral blood mononuclear cells (PBMC). This set of four 25+ color panels include 64 cell surface markers to resolve broad immune compartment populations, as well as activation and memory of specific T, B, natural killer (NK), and myeloid lineages. Common lineage bridging markers are integrated into each panel to allow for inter-panel quality control through major lineage frequency verification. These panels were developed using a five laser BD Symphony A5 conventional cytometer and successfully transferred to a five laser Cytek Aurora spectral cytometer capable of acquiring the panels. Nine representative PBMC samples were stained with the four phenotyping panels and acquired on both instruments to evaluate population frequency and visual staining patterns for gating between the systems. Both instruments produced comparable high quality flow cytometry data and supported our decision to acquire samples on the spectral cytometer moving forward. This modular set of panels and instrument performance metrics provide guidelines for designing flow cytometry experiments suitable for longitudinal or cross-sectional immune profiling.

A roadmap for translational cancer glycoimmunology at single cell resolution

Cancer cells can evade immune responses by exploiting inhibitory immune checkpoints. Immune checkpoint inhibitor (ICI) therapies based on anti-CTLA-4 and anti-PD-1/PD-L1 antibodies have been extensively explored over the recent years to unleash otherwise compromised anti-cancer immune responses. However, it is also well established that immune suppression is a multifactorial process involving an intricate crosstalk between cancer cells and the immune systems. The cancer glycome is emerging as a relevant source of immune checkpoints governing immunosuppressive behaviour in immune cells, paving an avenue for novel immunotherapeutic options. This review addresses the current state-of-the-art concerning the role played by glycans controlling innate and adaptive immune responses, while shedding light on available experimental models for glycoimmunology. We also emphasize the tremendous progress observed in the development of humanized models for immunology, the paramount contribution of advances in high-throughput single-cell analysis in this context, and the importance of including predictive machine learning algorithms in translational research. This may constitute an important roadmap for glycoimmunology, supporting careful adoption of models foreseeing clinical translation of fundamental glycobiology knowledge towards next generation immunotherapies.

Human Embryonic Stem Cells as a Model for Hematopoietic Stem Cell Differentiation and Viral Infection

Pluripotent human embryonic stem cell (hESC) lines are a valuable in vitro tool to differentiate specific cell lineages, including cells from all three germ layers, i.e., neuronal cells, myocytes, and hematopoietic cells, including progenitors (described here), lymphoid cells, and myeloid cells. However, dramatically different cell subtypes and functional properties of specific cells can arise depending on the differentiation technique used. We previously optimized hematopoietic stem cell differentiation from two different NIH-approved hESC lines to generate CD34+ hematopoietic progenitor cells (HPCs). Infection of these HPCs with a common herpesvirus (human cytomegalovirus) results in maintenance of viral latency, capability of viral reactivation, recapitulation of viral mutant phenotypes, and virus-induced myelosuppression of hematopoietic differentiation. However, different HPC subpopulations support different viral latency and reactivation phenotypes, and different hESC-to-HPC differentiation methods alter the ratio of stem cell subsets. In addition, differences in differentiation methods are dependent on both protocol/reagents and user techniques. Here, we report a simplified and optimized method to generate large numbers of CD34+ HPCs with consistent phenotypes and demonstrate a comparison of several common methods that can be used to control the ratio of available HPC subpopulations. A key aspect of this approach is that we achieve consistency in differentiation across users in different laboratories and, importantly, among newly trained individuals. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Maintenance of human embryonic stem cells (hESCs) Basic Protocol 2: Differentiation of hESCs to hematopoietic progenitor cells (HPCs) Basic Protocol 3: Downstream functional differentiation of hESC-derived HPCs to mature lineages Support Protocol 1: Freezing and testing frozen batches of hESCs Support Protocol 2: Counting hESCs Support Protocol 3: Phenotyping by flow cytometry.

iCoreDrop: A robust immune monitoring spectral cytometry assay with six open channels for biomarker flexibility

Recent advances in spectral cytometry have extended our ability to monitor immune cell subsets and activation status while simultaneously improving rare population detection. However, technical challenges in reference control selection and autofluorescence extraction serve as barriers to broad application of spectral flow cytometry. Furthermore, the complexity of spectral cytometry panel development limits the adaptation of established assays. Here, we describe the development of a spectral immunophenotyping assay with robust drop-in capability to enable biomarker interrogation flexibility. The immune monitoring core (iCore), which can be used in part or total, captures broad and granular immune subsets across T cells, B cells, NK cells, monocytes, dendritic cells, and granulocytes in peripheral whole blood. Additional user-selected biomarkers can be dropped in (Drop) using channels BV421, Alexa Fluor 488, PE, PE-Cy7, APC, and APC-Cy7. A comprehensive assessment of reagent and panel performance was conducted, including reference control comparison and optimal autofluorescence (AF) extraction on the 5-laser Cytek Aurora system for healthy donor blood. Assay precision and stability analyses revealed robust intra-assay precision, with 95% of 83 distinct population gates having <20% CV. In the presence of additional drop-in markers in two different settings, a T cell module and a myeloid/B cell module, the drop-in channels themselves achieved <20% CV across 12 out of 13 additionally queried population gates. Overall, establishment of optimal unmixing practices will enable widespread adoption of spectral cytometry assays.

Do more with Less: Improving High Parameter Cytometry Through Overnight Staining

Recent advances in flow cytometry have allowed high-dimensional characterization of biological phenomena, enabling breakthroughs in a multitude of fields. Despite the appreciation of the unique properties of antigens and fluorophores in high-parameter panel design, staining conditions are often standardized for short surface stains, regardless of antibody affinity or antigen accessibility. Here, we demonstrate how increasing antibody incubation times can lead to substantial improvements in sensitivity, maintaining specificity, and reducing background, while also significantly reducing the costs of high-parameter cytometry panels. Furthermore, overnight staining reduces the influence of interexperimental variability, assisting accurate pooling over experiments over extended time courses. We provide guidance on how to optimize staining conditions for diverse antigens, including how different fixation strategies can affect epitope accessibility. Overnight staining can thus substantially improve the resolution, repeatability, and cost-effectiveness of high-parameter cytometry. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Full spectrum flow cytometry and mass cytometry: A 32-marker panel comparison

High-dimensional single-cell data has become an important tool in unraveling the complexity of the immune system and its involvement in homeostasis and a large array of pathologies. As technological tools are developed, researchers are adopting them to answer increasingly complex biological questions. Up until recently, mass cytometry (MC) has been the main technology employed in cytometric assays requiring more than 29 markers. Recently, however, with the introduction of full spectrum flow cytometry (FSFC), it has become possible to break the fluorescence barrier and go beyond 29 fluorescent parameters. In this study, in collaboration with the Stanford Human Immune Monitoring Center (HIMC), we compared five patient samples using an established immune panel developed by the HIMC using their MC platform. Using split samples and the same antibody panel, we were able to demonstrate highly comparable results between the two technologies using multiple data analysis approaches. We report here a direct comparison of two technology platforms (MC and FSFC) using a 32-marker flow cytometric immune monitoring panel that can identify all the previously described and anticipated immune subpopulations defined by this panel.

A comparison of spectral unmixing to conventional compensation for the calculation of fluorochrome abundances from flow cytometric data

Traditionally, flow cytometers acquired data using the same number of detectors as fluorochromes being measured in the experiment. More recently, spectral flow cytometers utilize a larger number of detectors than fluorochromes. This seemingly small difference opens the door to a wide variety of mathematical tools for the calculation of the true fluorochrome abundances from the raw detector values as compared with traditional compensation. This review will provide a brief overview of the mathematics and theory underlying traditional compensation and unmixing focusing on the differences between them and the additional information provided by unmixing approaches.

Unlocking autofluorescence in the era of full spectrum analysis: Implications for immunophenotype discovery projects

Understanding the complex elements affecting signal resolution in cytometry is key for quality experimental design and data. In this study, we incorporate autofluorescence as a contributing factor to our understanding of resolution in cytometry and corroborate its impact in fluorescence signal detection through mathematical predictions supported by empirical evidence. Our findings illustrate the critical importance of autofluorescence extraction via full spectrum unmixing in unmasking dim signals and delineating the expression and subset distribution of low abundance markers in discovery projects. We apply our findings to the precise definition of the tissue and cellular distribution of a weakly expressed fluorescent protein that reports on a low-abundance immunological gene. Exploiting the full spectrum coverage enabled by Aurora 5L, we describe a novel approach to the isolation of pure cell subset-specific autofluorescence profiles based on high dimensionality reduction algorithms. This method can also be used to unveil differences in the autofluorescent fingerprints of tissues in homeostasis and after immunological challenges.

Using Full-Spectrum Flow Cytometry to Phenotype Memory T and NKT Cell Subsets with Optimized Tissue-Specific Preparation Protocols

Full-spectrum flow cytometry is now routinely used in many laboratories internationally, and the demand for this technology is rapidly increasing. With capacity to use larger and more complex staining panels, standardized protocols are required for optimal panel design and analysis. Importantly, for ex vivo analysis, tissue preparation methods also need to be optimized to ensure samples are truly representative of tissues in situ. This is particularly relevant given the recent interest in adaptive immune cells that form residency in specific organs. Here we provide optimized protocols for tissue processing and phenotyping of memory T cells and natural killer T (NKT) cell subsets from liver, lung, spleen, and lymph node using full-spectrum flow cytometry. We provide a 21-color antibody panel for identification of different memory subsets, including tissue-resident memory T (T_RM ) cells, which are increasingly regarded as important effectors in adaptive immunity. We show that processing procedures can affect outcomes, with liver T_RM cells particularly sensitive to heat, such that accurate evaluation requires fast processing at defined temperatures. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Processing mouse liver for flow cytometric analysis of memory T and NKT cell subsets Basic Protocol 2: Processing mouse spleen for flow cytometric analysis of memory T and NKT cell subsets Basic Protocol 3: Processing mouse lungs for flow cytometric analysis of memory T and NKT cell subsets Basic Protocol 4: Processing mouse lymph nodes for flow cytometric analysis of memory T and NKT cell subsets Basic Protocol 5: Staining and flow cytometric analysis of samples for memory T and NKT cell subsets Support Protocol: Obtaining cell counts from flow cytometry data.

Intratumoural administration of an NKT cell agonist with CpG promotes NKT cell infiltration associated with an enhanced antitumour response and abscopal effect

Intratumoural administration of unmethylated cytosine-phosphate-guanine motifs (CpG) to stimulate toll-like receptor (TLR)-9 has been shown to induce tumour regression in preclinical studies and some efficacy in the clinic. Because activated natural killer T (NKT) cells can cooperate with pattern-recognition via TLRs to improve adaptive immune responses, we assessed the impact of combining a repeated dosing regimen of intratumoural CpG with a single intratumoural dose of the NKT cell agonist α-galactosylceramide (α-GalCer). The combination was superior to CpG alone at inducing regression of established tumours in several murine tumour models, primarily mediated by CD8⁺ T cells. An antitumour effect on distant untreated tumours (abscopal effect) was reliant on sustained activity of NKT cells and was associated with infiltration of KLRG1⁺ NKT cells in tumours and draining lymph nodes at both injected and untreated distant sites. Cytometric analysis pointed to increased exposure to type I interferon (IFN) affecting many immune cell types in the tumour and lymphoid organs. Accordingly, antitumour activity was lost in animals in which dendritic cells (DCs) were incapable of signaling through the type I IFN receptor. Studies in conditional ablation models showed that conventional type 1 DCs and plasmacytoid DCs were required for the response. In tumour models where the combined treatment was less effective, the addition of tumour-antigen derived peptide, preferably conjugated to α-GalCer, significantly enhanced the antitumour response. The combination of TLR ligation, NKT cell agonism, and peptide delivery could therefore be adapted to induce responses to both known and unknown antigens.

Staggered starts in the race to T cell activation

How T lymphocytes tune their responses to different strengths of stimulation is a fundamental question in immunology. Recent work using new optogenetic, single-cell genomic, and live-imaging approaches has revealed that stimulation strength controls the rate of individual cell responses within a population. Moreover, these responses have been found to use shared molecular programs, regardless of stimulation strength. However, additional data indicate that stimulation duration or cytokine feedback can impact later gene expression phenotypes of activated cells. In-depth molecular studies have suggested mechanisms by which stimulation strength might modulate the probability of T cell activation. This emerging model allows activating T cells to achieve a wide range of population responses through probabilistic control within individual cells.