Evaluating spectral cytometry for immune profiling in viral disease

Increasing Signal Intensity of Fluorescent Oligo-Labeled Antibodies to Enable Combination Multiplexing

Full-spectrum flow cytometry has increased antibody-based multiplexing, yet further increases remain potentially impactful. We recently proposed how fluorescence multiplexing using spectral imaging and combinatorics (MuSIC) could do so using tandem dyes and an oligo-based antibody labeling method. In this work, we found that such labeled antibodies had significantly lower signal intensities than conventionally labeled antibodies in human cell experiments. To improve signal intensity, we tested moving the fluorophores from the original external (ext.) 5' or 3' end-labeled orientation to internal (int.) fluorophore modifications. Cell-free spectrophotometer measurements showed a ∼6-fold signal intensity increase of the new int. configuration compared to the previous ext. configuration. Time-resolved fluorescence and fluorescence correlation spectroscopy showed that the ∼3-fold brightness difference is due to static quenching most likely by the oligo or solution in the ext. configuration. Spectral flow cytometry experiments using peripheral blood mononuclear cells show int. MuSIC probe-labeled antibodies (i) retained increased signal intensity while having no significant difference in the estimated % of CD8+ lymphocytes and (ii) labeled with Atto488, Atto647, and Atto488/647 combinations can be demultiplexed in triple-stained samples. The antibody labeling approach is general and can be broadly applied to many biological and diagnostic applications where spectral detection is available.

Increasing Signal Intensity of Fluorescent Oligo-Labeled Antibodies to Enable Combination Multiplexing

Full-spectrum flow cytometry has increased antibody-based multiplexing, yet further increases remain potentially impactful. We recently proposed how fluorescence Multiplexing using Spectral Imaging and Combinatorics (MuSIC) could do so using tandem dyes and an oligo-based antibody labeling method. In this work, we found that such labeled antibodies had significantly lower signal intensity than conventionally-labeled antibodies in human cell experiments. To improve signal intensity, we tested moving the fluorophores from the original external (ext.) 5' or 3' end-labeled orientation to internal (int.) fluorophore modifications. Cell-free spectrophotometer measurements showed a ~6-fold signal intensity increase of the new int. configuration compared to the previous ext. configuration. Time-resolved fluorescence and fluorescence correlation spectroscopy showed that ~3-fold brightness difference is due to static quenching most likely by the oligo or solution in the ext. configuration. Spectral flow cytometry experiments using peripheral blood mononuclear cells show int. MuSIC probe-labeled antibodies (i) retained increased signal intensity while having no significant difference in the estimated % of CD8+ lymphocytes and (ii) labeled with Atto488, Atto647, and Atto488/647 combinations can be demultiplexed in triple-stained samples. The antibody labeling approach is general and can be broadly applied to many biological and diagnostic applications where spectral detection is available.

del Hierro A, H-Vázquez J, Cuesta-Sancho S, Bernardo D. State-of-the-art cytometry in the search of novel biomarkers in digestive cancers

Despite that colorectal and liver cancer are among the most prevalent tumours in the world, the identification of non-invasive biomarkers to aid on their diagnose and subsequent prognosis is a current unmet need that would diminish both their incidence and mortality rates. In this context, conventional flow cytometry has been widely used in the screening of biomarkers with clinical utility in other malignant processes like leukaemia or lymphoma. Therefore, in this review, we will focus on how advanced cytometry panels covering over 40 parameters can be applied on the study of the immune system from patients with colorectal and hepatocellular carcinoma and how that can be used on the search of novel biomarkers to aid or diagnose, prognosis, and even predict clinical response to different treatments. In addition, these multiparametric and unbiased approaches can also provide novel insights into the specific immunopathogenic mechanisms governing these malignant diseases, hence potentially unravelling novel targets to perform immunotherapy or identify novel mechanisms, rendering the development of novel treatments. As a consequence, computational cytometry approaches are an emerging methodology for the early detection and predicting therapies for gastrointestinal cancers.

Spectral flow cytometry: Fundamentals and future impact

Spectral flow cytometry has emerged as a significant player in the cytometry marketplace, with the potential for rapid growth. Despite a slow start, the technology has made significant strides in advancing various areas of single-cell analysis utilized by the scientific community. The integration of spectral cytometry into clinical laboratories and diagnostic processes is currently underway and is expected to garner a significant level of widespread acceptance in the near future. However, incorporating a new methodological approach into existing research programs can lead to misunderstandings or even misuse. This chapter offers an introductory yet comprehensive explanation of the scientific principles that form the foundation of spectral cytometry. Specifically, it delves into the unmixing processes that are utilized for data analysis. This overview is designed for those who are new to the field and seeking an informative guide to this exciting emerging technology.

Understanding Spondyloarthritis Pathogenesis: The Promise of Single-Cell Profiling

PURPOSE OF REVIEW

Single-cell profiling, either in suspension or within the tissue context, is a rapidly evolving field. The purpose of this review is to outline recent advancements and emerging trends with a specific focus on studies in spondyloarthritis.

RECENT FINDINGS

The introduction of sequencing-based approaches for the quantification of RNA, protein, or epigenetic modifications at single-cell resolution has provided a major boost to discovery-driven research. Fluorescent flow cytometry, mass cytometry, and image-based cytometry continue to evolve. Spatial transcriptomics and imaging mass cytometry have extended high-dimensional analysis to cells in tissues. Applications in spondyloarthritis include the indexing and functional characterization of cells, discovery of disease-associated cell states, and identification of signatures associated with therapeutic responses. Single-cell TCR-seq has provided evidence for clonal expansion of CD8+ T cells in spondyloarthritis. The use of single-cell profiling approaches in spondyloarthritis research is still in its early stages. Challenges include high cost and limited availability of diseased tissue samples. To harness the full potential of the rapidly expanding technical capabilities, large-scale collaborative efforts are imperative.

Immune cell phenotype and function patterns across the life course in individuals from rural Uganda

Background

To determine the pattern of immune cell subsets across the life span in rural sub-Saharan Africa (SSA), and to set a reference standard for cell subsets amongst Africans, we characterised the major immune cell subsets in peripheral blood including T cells, B cells, monocytes, NK cells, neutrophils and eosinophils, in individuals aged 3 to 89 years from Uganda.

Methods

Immune phenotypes were measured using both conventional flow cytometry in 72 individuals, and full spectrum flow cytometry in 80 individuals. Epstein-Barr virus (EBV) IFN-γ T cell responses were quantified in 332 individuals using an ELISpot assay. Full blood counts of all study participants were also obtained.

Results

The percentages of central memory (TCM) and senescent CD4+ and CD8+ T cell subsets, effector memory (TEM) CD8+ T cells and neutrophils increased with increasing age. On the other hand, the percentages of naïve T (TN) and B (BN) cells, atypical B cells (BA), total lymphocytes, eosinophils and basophils decreased with increasing age. There was no change in CD4+ or CD8+ T effector memory RA (TEMRA) cells, exhausted T cells, NK cells and monocytes with age. Higher eosinophil and basophil percentages were observed in males compared to females. T cell function as measured by IFN-γ responses to EBV increased with increasing age, peaking at 31-55 years.

Conclusion

The percentages of cell subsets differ between individuals from SSA compared to those elsewhere, perhaps reflecting a different antigenic milieu. These results serve as a reference for normal values in this population.

Spectral analysis and sorting of microbial organisms using a spectral sorter

This chapter discusses the problems related to the application of conventional flow cytometers to microbiology. To address some of those limitations, the concept of spectral flow cytometry is introduced and the advantages over conventional flow cytometry for bacterial sorting are presented. We demonstrate by using ThermoFisher's Bigfoot spectral sorter where the spectral signatures of different stains for staining bacteria are demonstrated with an example of performing unmixing on spectral datasets. In addition to the Bigfoot's spectral analysis, the special biosafety features of this instrument are discussed. Utilizing these biosafety features, the sorting and patterning at the single cell level is optimized using non-pathogenic bacteria. Finally, the chapter is concluded by presenting a novel, label free, non-destructive, and rapid phenotypic method called Elastic Light Scattering (ELS) technology for identification of the patterned bacterial cells based on their unique colony scatter patterns.

High-dimensional multi-pass flow cytometry via spectrally encoded cellular barcoding

Advances in immunology, immuno-oncology, drug discovery and vaccine development demand improvements in the capabilities of flow cytometry to allow it to measure more protein markers per cell at multiple timepoints. However, the size of panels of fluorophore markers is limited by overlaps in fluorescence-emission spectra, and flow cytometers typically perform cell measurements at one timepoint. Here we describe multi-pass high-dimensional flow cytometry, a method leveraging cellular barcoding via microparticles emitting near-infrared laser light to track and repeatedly measure each cell using more markers and fewer colours. By using live human peripheral blood mononuclear cells, we show that the method enables the time-resolved characterization of the same cells before and after stimulation, their analysis via a 10-marker panel with minimal compensation for spectral spillover and their deep immunophenotyping via a 32-marker panel, where the same cells are analysed in 3 back-to-back cycles with 10-13 markers per cycle, reducing overall spillover and simplifying marker-panel design. Cellular barcoding in flow cytometry extends the utility of the technique for high-dimensional multi-pass single-cell analyses.

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.

Spectral Flow Cytometry Analysis of Resident Tissue Macrophages

Spectral flow cytometry improves flow cytometry panels by resolving the full emission spectra of individual fluorophores, allowing greater flexibility to incorporate more fluorochromes when designing multicolor panels. Additionally, the spectral approach captures the autofluorescence of a sample or cell population (e.g., macrophages, which are highly autofluorescent) that can be considered during unmixing for improved downstream analyses. As the increased complexity of macrophage heterogeneity unravels in the scientific community, it is crucial to obtain high-dimensional data at the single-cell level to resolve these populations.

OMIP-097: High-parameter phenotyping of human platelets by spectral flow cytometry

Using spectral flow cytometry, we developed a 16-color panel for analysis of platelet phenotype and function in human whole blood. The panel contains markers of clinical relevance and follows an optimized protocol for the high-parameter phenotyping of (phosphatidylserine positive) procoagulant platelets. Inclusion of established markers, such as CD62P and PAC-1, allows the subsetting of classic (proinflammatory and proaggregatory) phenotypes, while addition of novel markers, such as TLR9, allows the resolution of platelets with nonclassic functions. Multiple inducible (C3b, CD63, CD107a, CD154, and TLT-1) and constitutive (CD29, CD31, CD32, CD36, CD42a, CD61, and GPVI) markers are also measurable, and we demonstrate the use of automatic gating for platelet analysis. The panel is widely applicable to research and clinical settings and can be readily modified, should users wish to tailor the panel to more specific needs.

OMIP-095: 40-Color spectral flow cytometry delineates all major leukocyte populations in murine lymphoid tissues

High-dimensional immunoprofiling is essential for studying host response to immunotherapy, infection, and disease in murine model systems. However, the difficulty of multiparameter panel design combined with a lack of existing murine tools has prevented the comprehensive study of all major leukocyte phenotypes in a single assay. Herein, we present a 40-color flow cytometry panel for deep immunophenotyping of murine lymphoid tissues, including the spleen, blood, Peyer's patches, inguinal lymph nodes, bone marrow, and thymus. This panel uses a robust set of surface markers capable of differentiating leukocyte subsets without the use of intracellular staining, thus allowing for the use of cells in downstream functional experiments or multiomic analyses. Our panel classifies T cells, B cells, natural killer cells, innate lymphoid cells, monocytes, macrophages, dendritic cells, basophils, neutrophils, eosinophils, progenitors, and their functional subsets by using a series of co-stimulatory, checkpoint, activation, migration, and maturation markers. This tool has a multitude of systems immunology applications ranging from serial monitoring of circulating blood signatures to complex endpoint analysis, especially in pre-clinical settings where treatments can modulate leukocyte abundance and/or function. Ultimately, this 40-color panel resolves a diverse array of immune cells on the axes of time, tissue, and treatment, filling the niche for a modern tool dedicated to murine immunophenotyping.

Immunophenotyping beyond the limits of time

Immunophenotyping is a powerful approach for deciphering responses of the immune system to drug screening and immunotherapy. In this issue of Cell Report Methods, Liechti et al. have advanced this approach by developing a pipeline, which allows high-throughput but still accurate single-cell immunophenotyping in time.

Design, optimisation and standardisation of a high-dimensional spectral flow cytometry workflow assessing T-cell immunophenotype in patients with melanoma

Objectives

Despite the success of immune checkpoint blockade, most metastatic melanoma patients fail to respond to therapy or experience severe toxicity. Assessment of biomarkers and immunophenotypes before or early into treatment will help to understand favourable responses and improve therapeutic outcomes.

Methods

We present a high-dimensional approach for blood T-cell profiling using three multi-parameter cytometry panels: (1) a TruCount panel for absolute cell counts, (2) a 27-colour spectral panel assessing T-cell markers and (3) a 20-colour spectral panel evaluating intracellular cytokine expression. Pre-treatment blood mononuclear cells from patients and healthy controls were cryopreserved before staining across 11 batches. Batch effects were tracked using a single-donor control and the suitability of normalisation was assessed. The data were analysed using manual gating and high-dimensional strategies.

Results

Batch-to-batch variation was minimal, as demonstrated by the dimensionality reduction of batch-control samples, and normalisation did not improve manual or high-dimensional analysis. Application of the workflow demonstrated the capacity of the panels and showed that patients had fewer lymphocytes than controls (P = 0.0027), due to lower naive CD4+ (P = 0.015) and CD8+ (P = 0.011) T cells and follicular helper T cells (P = 0.00076). Patients showed trends for higher proportions of Ki67 and IL-2-expressing cells within CD4+ and CD8+ memory subsets, and increased CD57 and EOMES expression within TCRγδ+ T cells.

Conclusion

Our optimised high-parameter spectral cytometry approach provided in-depth profiling of blood T cells and found differences in patient immunophenotype at baseline. The robustness of our workflow, as demonstrated by minimal batch effects, makes this approach highly suitable for the longitudinal evaluation of immunotherapy effects.

OMIP-086: Full spectrum flow cytometry for high-dimensional immunophenotyping of mouse innate lymphoid cells

This 25-parameter, 22-color full spectrum flow cytometry panel was designed and optimized for the comprehensive enumeration and functional characterization of innate lymphoid cell (ILC) subsets in mouse tissues. The panel presented here allows the discrimination of ILC progenitors (ILCP), ILC1, ILC2, NCR+ ILC3, NCR- ILC3, CCR6+ lymphoid tissue-inducer (LTi)-like ILC3 and mature natural killer (NK) cell populations. Further characterization of ILC and NK cell functional profiles in response to stimulation is provided by the inclusion of subset-specific cytokine markers, and proliferation markers. Development and optimization of this panel was performed on freshly isolated cells from adult BALB/c lungs and small intestine lamina propria, and ex vivo stimulation with phorbol 12-myrisate 13-acetate, ionomycin, and pro-ILC activating cytokines.

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.

Automating the High-Throughput Screening of Protein-Based Optical Indicators and Actuators

Over the last 25 years, protein engineers have developed an impressive collection of optical tools to interface with biological systems: indicators to eavesdrop on cellular activity and actuators to poke and prod native processes. To reach the performance level required for their downstream applications, protein-based tools are usually sculpted by iterative rounds of mutagenesis. In each round, libraries of variants are made and evaluated, and the most promising hits are then retrieved, sequenced, and further characterized. Early efforts to engineer protein-based optical tools were largely manual, suffering from low throughput, human error, and tedium. Here, we describe approaches to automating the screening of libraries generated as colonies on agar, multiwell plates, and pooled populations of single-cell variants. We also briefly discuss emerging approaches for screening, including cell-free systems and machine learning.

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.

Advanced immunophenotyping: A powerful tool for immune profiling, drug screening, and a personalized treatment approach

Various autoimmune diseases are characterized by distinct cell subset distributions and activation profiles of peripheral blood mononuclear cells (PBMCs). PBMCs can therefore serve as an ideal biomarker material, which is easily accessible and allows for screening of multiple cell types. A detailed understanding of the immune landscape is critical for the diagnosis of patients with autoimmune diseases, as well as for a personalized treatment approach. In our study, we investigate the potential of multi-parameter spectral flow cytometry for the identification of patients suffering from autoimmune diseases and its power as an evaluation tool for in vitro drug screening approaches (advanced immunophenotyping). We designed a combination of two 22-color immunophenotyping panels for profiling cell subset distribution and cell activation. Downstream bioinformatics analyses included percentages of individual cell populations and median fluorescent intensity of defined markers which were then visualized as heatmaps and in dimensionality reduction approaches. In vitro testing of epigenetic immunomodulatory drugs revealed an altered activation status upon treatment, which supports the use of spectral flow cytometry as a high-throughput drug screening tool. Advanced immunophenotyping might support the exploration of novel therapeutic drugs and contribute to future personalized treatment approaches in autoimmune diseases and beyond.

Development of Spectral Imaging Cytometry

Spectral flow cytometry is a new technology that enables measurements of fluorescent spectra and light scattering properties in diverse cellular populations with high precision. Modern instruments allow simultaneous determination of up to 40+ fluorescent dyes with heavily overlapping emission spectra, discrimination of autofluorescent signals in the stained specimens, and detailed analysis of diverse autofluorescence of different cells-from mammalian to chlorophyll-containing cells like cyanobacteria. In this paper, we review the history, compare modern conventional and spectral flow cytometers, and discuss several applications of spectral flow cytometry.

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.

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.

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.

SLAMF7 modulates B cells and adaptive immunity to regulate susceptibility to CNS autoimmunity

Background

Multiple sclerosis (MS) is a chronic, debilitating condition characterized by CNS autoimmunity stemming from a complex etiology involving both environmental and genetic factors. Our current understanding of MS points to dysregulation of the immune system as the pathogenic culprit, however, it remains unknown as to how the many genes associated with increased susceptibility to MS are involved. One such gene linked to MS susceptibility and known to regulate immune function is the self-ligand immune cell receptor SLAMF7.

Methods

We subjected WT and SLAMF7^−/− mice to multiple EAE models, compared disease severity, and comprehensively profiled the CNS immune landscape of these mice. We identified all SLAMF7-expressing CNS immune cells and compared the entire CNS immune niche between genotypes. We performed deep phenotyping and in vitro functional studies of B and T cells via spectral cytometry and BioPlex assays. Adoptive transfer studies involving the transfer of WT and SLAMF7^−/− B cells into B cell-deficient mice (μMT) were also performed. Finally, B–T cell co-culture studies were performed, and a comparative cell–cell interaction network derived from scRNA-seq data of SLAMF7⁺ vs. SLAMF7⁻ human CSF immune cells was constructed.

Results

We found SLAMF7^−/− mice to be more susceptible to EAE compared to WT mice and found SLAMF7 to be expressed on numerous CNS immune cell subsets. Absence of SLAMF7 did not grossly alter the CNS immune landscape, but allowed for altered immune cell subset infiltration during EAE in a model-dependent manner. Global lack of SLAMF7 expression increased myeloid cell activation states along with augmented T cell anti-MOG immunity. B cell profiling studies revealed increased activation states of specific plasma and B cell subsets in SLAMF7^−/− mice during EAE, and functional co-culture studies determined that SLAMF7^−/− B cells induce exaggerated T cell activation. Adoptive transfer studies revealed that the increased susceptibility of SLAMF7^−/− mice to EAE is partly B cell dependent and reconstruction of the human CSF SLAMF7-interactome found B cells to be critical to cell–cell communication between SLAMF7-expressing cells.

Conclusions

Our studies have identified novel roles for SLAMF7 in CNS immune regulation and B cell function, and illuminate underpinnings of the genetic association between SLAMF7 and MS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02594-9.

The evolution of spectral flow cytometry

This special issue of Cytometry marks the transition of spectral flow cytometry from an emerging technology into a transformative force that will shape the fields of cytometry and single-cell analysis for some time to come. Tracing its roots to the earliest years of flow cytometry, spectral flow cytometry has evolved from the domain of individual researchers pushing the limits of hardware, reagents, and software to the mainstream, where it is being harnessed and adapted to meet the analytical challenges presented by modern biomedical research. In particular, the current form of spectral flow technology has arisen to address the needs of multiparameter immunophenotyping of immune cells in basic and translational research, and much of the current instrumentation and software reflects the needs of those applications. Yet, the possibilities enabled by high-resolution analysis of the spectral properties of optical absorbance, scatter, and emission have only begun to be exploited. In this brief review, the author highlights the origins and early milestones of single-cell spectral analysis, assesses the current state of instrumentation and software, and speculates as to future directions of spectral flow cytometry technology and applications.

Detecting Förster resonance energy transfer in living cells by conventional and spectral flow cytometry

Assays based on Förster resonance energy transfer (FRET) can be used to study many processes in cell biology. Although this is most often done with microscopy for fluorescence detection, we report two ways to measure FRET in living cells by flow cytometry. Using a conventional flow cytometer and the "3-cube method" for intensity-based calculation of FRET efficiency, we measured the enzymatic activity of specific kinases in cells expressing a genetically-encoded reporter. For both AKT and protein kinase A, the method measured kinase activity in time-course, dose-response, and kinetic assays. Using the Cytek Aurora spectral flow cytometer, which applies linear unmixing to emission measured in multiple wavelength ranges, FRET from the same reporters was measured with greater single-cell precision, in real time and in the presence of other fluorophores. Results from gene-knockout studies suggested that spectral flow cytometry might enable the sorting of cells on the basis of FRET. The methods we present provide convenient and flexible options for using FRET with flow cytometry in studies of cell biology.

Differential Immune Checkpoint and Ig-like V-Type Receptor Profiles in COVID-19: Associations with Severity and Treatment

Identifying patients' immune system status has become critical to managing SARS-CoV-2 infection and avoiding the appearance of secondary infections during a hospital stay. Despite the high volume of research, robust severity and outcome markers are still lacking in COVID-19. We recruited 87 COVID-19 patients and analyzed, by unbiased automated software, 356 parameters at baseline emergency department admission including: high depth immune phenotyping and immune checkpoint expression by spectral flow cytometry, cytokines and other soluble molecules in plasma as well as routine clinical variables. We identified 69 baseline alterations in the expression of immune checkpoints, Ig-like V type receptors and other immune population markers associated with severity (O₂ requirement). Thirty-four changes in these markers/populations were associated with secondary infection appearance. In addition, through a longitudinal sample collection, we described the changes which take place in the immune system of COVID-19 patients during secondary infections and in response to corticosteroid treatment. Our study provides information about immune checkpoint molecules and other less-studied receptors with Ig-like V-type domains such as CD108, CD226, HVEM (CD270), B7H3 (CD276), B7H5 (VISTA) and GITR (CD357), defining these as novel interesting molecules in severe and corticosteroids-treated acute infections.

Using the Autofluorescence Finder on the Sony ID7000TM Spectral Cell Analyzer to Identify and Unmix Multiple Highly Autofluorescent Murine Lung Populations

Autofluorescence (AF) is a feature of all cell types, though some have more than others. In tissues with complex heterogeneous cellularity, AF is frequently a source of high background, masking faint fluorescent signals and reducing the available dynamic range of detectors for detecting fluorescence signals from markers of interest in a flow cytometry panel. Pulmonary flow cytometry presents unique challenges because lung cells are heterogeneous and contain varying amounts of high AF. The goal of this study was to demonstrate how a novel AF Finder tool on the Sony ID7000™ Spectral Cell Analyzer can be used to identify and screen multiple AF subsets in complex highly AF tissues like murine lungs. In lung single cell suspensions, the AF Finder tool identified four distinct AF spectra from six highly AF subsets. The subtraction of these distinct AF spectra resulted in a resolution increase by several log decades in several fluorescent channels. The major immune and lung tissue resident cells in a murine model of asthma were easily identified in a multi-color panel using AF subtraction. The findings demonstrate the practicality of the AF Finder tool, particularly when analyzing samples with multiple AF populations of varying intensities, in order to reduce fluorescence background and increase signal resolution in spectral flow cytometry.

Impact of Dietary Fiber on West Nile Virus Infection

Dietary fiber supports healthy gut bacteria and their production of short-chain fatty acids (SCFA), which promote anti-inflammatory cell development, in particular, regulatory T cells. It is thus beneficial in many diseases, including influenza infection. While disruption of the gut microbiota by antibiotic treatment aggravates West Nile Virus (WNV) disease, whether dietary fiber is beneficial is unknown. WNV is a widely-distributed neurotropic flavivirus that recruits inflammatory monocytes into the brain, causing life-threatening encephalitis. To investigate the impact of dietary fiber on WNV encephalitis, mice were fed on diets deficient or enriched with dietary fiber for two weeks prior to inoculation with WNV. To induce encephalitis, mice were inoculated intranasally with WNV and maintained on these diets. Despite increased fecal SCFA acetate and changes in gut microbiota composition, dietary fiber did not affect clinical scores, leukocyte infiltration into the brain, or survival. After the brain, highest virus loads were measured in the colon in neurons of the submucosal and myenteric plexuses. Associated with this, there was disrupted gut homeostasis, with shorter colon length and higher local inflammatory cytokine levels, which were not affected by dietary fiber. Thus, fiber supplementation is not effective in WNV encephalitis.

High-Dimensional Immunophenotyping with 37-Color Panel Using Full-Spectrum Cytometry

A comprehensive study of the cellular components of the immune system demands both deep and broad immunophenotyping of numerous cell subsets in an effective and practical way. Novel full-spectrum technology reveals the complete emission spectrum of each dye maximizing the amount of information that can be obtained on a single sample regarding conventional flow cytometry and provide an expanded knowledge of biological processes. In this chapter, we describe a 37-color protocol that allows to identify more than 45 different cell populations on whole blood samples of SARS-CoV-2-infected patients.

Absence of ERAP1 in B Cells Increases Susceptibility to Central Nervous System Autoimmunity, Alters B Cell Biology, and Mechanistically Explains Genetic Associations between ERAP1 and Multiple Sclerosis

Hundreds of genes have been linked to multiple sclerosis (MS); yet, the underlying mechanisms behind these associations have only been investigated in a fraction of cases. Endoplasmic reticulum aminopeptidase 1 (ERAP1) is an endoplasmic reticulum-localized aminopeptidase with important roles in trimming peptides destined for MHC class I and regulation of innate immune responses. As such, genetic polymorphisms in ERAP1 have been linked to multiple autoimmune diseases. In this study, we present, to our knowledge, the first mechanistic studies performed to uncover why polymorphisms in ERAP1 are associated with increased susceptibility to MS. Combining multiple mouse models of CNS autoimmunity with high-dimensional single-cell spectral cytometry, adoptive transfer studies, and integrative analysis of human single-cell RNA-sequencing datasets, we identify an intrinsic defect in B cells as being primarily responsible. Not only are mice lacking ERAP1 more susceptible to CNS autoimmunity, but adoptive transfer of B cells lacking ERAP1 into B cell-deficient mice recapitulates this susceptibility. We found B cells lacking ERAP1 display decreased proliferation in vivo and express higher levels of activation/costimulatory markers. Integrative analysis of single-cell RNA sequencing of B cells from 36 individuals revealed subset-conserved differences in gene expression and pathway activation in individuals harboring the MS-linked K528R ERAP1 single-nucleotide polymorphism. Finally, our studies also led us to create, to our knowledge, the first murine protein-level map of the CNS IL-10⁺ immune compartment at steady state and during neuroinflammation. These studies identify a role for ERAP1 in the modulation of B cells and highlight this as one reason why polymorphisms in this gene are linked to MS.

Considerations for user consultation in a flow cytometry shared resource laboratory

User consultation is an essential first step in assuring high-quality flow cytometric data. A central challenge to shared resource laboratory (SRL) staff is how to best guide new and current users to meet each projects' needs. One solution to this challenge is to follow a standard user consultation platform addressing all critical steps between the conception of the experiment and the actual acquisition of samples. Here we describe considerations to help an SRL understand the researcher's goals and how best the SRL staff can provide expert advice in a structured manner. User consultation has an educational nature, informing users about current best practices in cytometry that apply to their specific utilization. A consultation report also improves communication between the SRL, principal investigator, and lab members of the collaborating researcher. Development of best SRL practices is spearheaded by the ISAC SRL committee and this communication sets the foundation to initiate such report for user consultation. Implementation of best practices during user consultation will improve rigor and reproducibility in cytometry.

The Evolution of Single-Cell Analysis and Utility in Drug Development

This review provides a brief history of the advances of cellular analysis tools focusing on instrumentation, detection probes, and data analysis tools. The interplay of technological advancement and a deeper understanding of cellular biology are emphasized. The relevance of this topic to drug development is that the evaluation of cellular biomarkers has become a critical component of the development strategy for novel immune therapies, cell therapies, gene therapies, antiviral therapies, and vaccines. Moreover, recent technological advances in single-cell analysis are providing more robust cellular measurements and thus accelerating the advancement of novel therapies.

Graphical abstract

High-Dimensional Image Analysis using Histocytometry

Histocytometry is a technique for processing multiparameter microscopy images using computational approaches to identify and quantify cellular phenotypes. It allows for spatial analyses of cellular phenotypes in relation to each other and within defined spatial regions. The benefit of this technique over manual annotation and characterization of cells is a high degree of automation/throughput, significantly decreased user bias, and increased reproducibility. Recently, an increase in freely available software amenable to or deliberately designed for histocytometry has resulted in these complex analyses being available to a broader base of users who have amassed multi-component microscopic imaging data. This article provides an overview of a histocytometry pipeline, focusing on the strategic planning and software requirements to allow readers to perform cell segmentation, phenotyping, and spatial analyses to advance their research outputs. © 2021 Wiley Periodicals LLC.

Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease

Deep molecular profiling of biological tissues is an indicator of health and disease. We used imaging mass cytometry (IMC) to acquire spatially resolved 20-plex protein data in tissue sections from normal and chronic tonsillitis cases. We present SpatialViz, a suite of algorithms to explore spatial relationships in multiplexed tissue images by visualizing and quantifying single-cell granularity and anatomical complexity in diverse multiplexed tissue imaging data. Single-cell and spatial maps confirmed that CD68+ cells were correlated with the enhanced Granzyme B expression and CD3+ cells exhibited enrichment of CD4+ phenotype in chronic tonsillitis. SpatialViz revealed morphological distributions of cellular organizations in distinct anatomical areas, spatially resolved single-cell associations across anatomical categories, and distance maps between the markers. Spatial topographic maps showed the unique organization of different tissue layers. The spatial reference framework generated network-based comparisons of multiplex data from healthy and diseased tonsils. SpatialViz is broadly applicable to multiplexed tissue biology.

Integration, exploration, and analysis of high-dimensional single-cell cytometry data using Spectre

As the size and complexity of high-dimensional (HD) cytometry data continue to expand, comprehensive, scalable, and methodical computational analysis approaches are essential. Yet, contemporary clustering and dimensionality reduction tools alone are insufficient to analyze or reproduce analyses across large numbers of samples, batches, or experiments. Moreover, approaches that allow for the integration of data across batches or experiments are not well incorporated into computational toolkits to allow for streamlined workflows. Here we present Spectre, an R package that enables comprehensive end-to-end integration and analysis of HD cytometry data from different batches or experiments. Spectre streamlines the analytical stages of raw data pre-processing, batch alignment, data integration, clustering, dimensionality reduction, visualization, and population labelling, as well as quantitative and statistical analysis. Critically, the fundamental data structures used within Spectre, along with the implementation of machine learning classifiers, allow for the scalable analysis of very large HD datasets, generated by flow cytometry, mass cytometry, or spectral cytometry. Using open and flexible data structures, Spectre can also be used to analyze data generated by single-cell RNA sequencing or HD imaging technologies, such as Imaging Mass Cytometry. The simple, clear, and modular design of analysis workflows allow these tools to be used by bioinformaticians and laboratory scientists alike. Spectre is available as an R package or Docker container. R code is available on Github (https://github.com/immunedynamics/spectre).

Strategies for Immunomonitoring after Vaccination and during Infection

Immunomonitoring is the study of an individual's immune responses over the course of vaccination or infection. In the infectious context, exploring the innate and adaptive immune responses will help to investigate their contribution to viral control or toxicity. After vaccination, immunomonitoring of the correlate(s) and surrogate(s) of protection is a major asset for measuring vaccine immune efficacy. Conventional immunomonitoring methods include antibody-based technologies that are easy to use. However, promising sensitive high-throughput technologies allowed the emergence of holistic approaches. This raises the question of data integration methods and tools. These approaches allow us to increase our knowledge on immune mechanisms as well as the identification of key effectors of the immune response. However, the depiction of relevant findings requires a well-rounded consideration beforehand about the hypotheses, conception, organization and objectives of the immunomonitoring. Therefore, well-standardized and comprehensive studies fuel insight to design more efficient, rationale-based vaccines and therapeutics to fight against infectious diseases. Hence, we will illustrate this review with examples of the immunomonitoring approaches used during vaccination and the COVID-19 pandemic.

Full Spectrum Flow Cytometry as a Powerful Technology for Cancer Immunotherapy Research

The Nobel Prize-deserving concept of blocking inhibitory pathways in T cells, to unleash their anti-tumoral capacity, became one of the pillars of cancer treatment in the last decade and has resulted in durable clinical responses for multiple cancer types. Currently, two of the most important goals in cancer immunotherapy are to understand the mechanisms resulting in failure to checkpoint blockade and to identify predictive immunological biomarkers that correlate to treatment response, disease progression or adverse effects. The identification and validation of biomarkers for routine clinical use is not only critical to monitor disease or treatment progression, but also to personalize and develop new therapies. To achieve these goals, powerful research tools are needed. Flow cytometry stands as one of the most successful single-cell analytical tools used to characterize immune cell phenotypes to monitor solid tumors, hematological malignancies, minimal residual disease or metastatic progression. This technology has been fundamental in diagnosis, treatment and translational research in cancer clinical trials. Most recently, the need to evaluate simultaneously more features in each cell has pushed the field to implement more powerful adaptations beyond conventional flow cytometry, including Full Spectrum Flow Cytometry (FSFC). FSFC captures the full emission spectrum of fluorescent molecules using arrays of highly sensitive light detectors, and to date has enabled characterization of 40 parameters in a single sample. We will summarize the contributions of this technology to the advancement of research in immunotherapy studies and discuss best practices to obtain reliable, robust and reproducible FSFC results.

MRD Tailored Therapy in AML: What We Have Learned So Far

Acute myeloid leukemia (AML) is a heterogeneous clonal disease associated with a dismal survival, partly due to the frequent occurrence of relapse. Many patient- and leukemia-specific characteristics, such as age, cytogenetics, mutations, and measurable residual disease (MRD) after intensive chemotherapy, have shown to be valuable prognostic factors. MRD has become a rich field of research where many advances have been made regarding technical, biological, and clinical aspects, which will be the topic of this review. Since many laboratories involved in AML diagnostics have experience in immunophenotyping, multiparameter flow cytometry (MFC) based MRD is currently the most commonly used method. Although molecular, quantitative PCR based techniques may be more sensitive, their disadvantage is that they can only be applied in a subset of patients harboring the genetic aberration. Next-generation sequencing can assess and quantify mutations in many genes but currently does not offer highly sensitive MRD measurements on a routine basis. In order to provide reliable MRD results, MRD assay optimization and standardization is essential. Different techniques for MRD assessment are being evaluated, and combinations of the methods have shown promising results for improving its prognostic value. In this regard, the load of leukemic stem cells (LSC) has also been shown to add to the prognostic value of MFC-MRD. At this moment, MRD after intensive chemotherapy is most often used as a prognostic factor to help stratify patients, but also to select the most appropriate consolidation therapy. For example, to guide post-remission treatment for intermediate-risk patients where MRD positive patients receive allogeneic stem cell transplantation and MRD negative receive autologous stem cell transplantation. Other upcoming uses of MRD that are being investigated include: selecting the type of allogeneic stem cell transplantation therapy (donor, conditioning), monitoring after stem cell transplantation (to allow intervention), and determining drug efficacy for the use of a surrogate endpoint in clinical trials.

New cytometry tools for immune monitoring during cancer immunotherapy

The success of cancer immunotherapy (CIT) in the past decade has brought renewed excitement and the need to better understand how the human immune system functions during health and disease. Advances in single cell technologies have also inspired the creation of a Human Cell Atlas to identify and describe every cell in the human body with the intention of elucidating how to "fix" the ones that fail normal function. For example, treatment of cancer patients with immune checkpoint blockade (ICB) antibodies can reinvigorate their T cells and produce durable clinical benefit in a subset of patients, but a number of resistance mechanisms exist that prohibit full benefit to all treated patients. Early detection of biomarkers of response and mechanisms of resistance are needed to identify the patients who can benefit most from ICB. A noninvasive approach to predict treatment outcomes early after immunotherapies is a longitudinal analysis of peripheral blood immune cells using flow cytometry. Here we review some of the advances in our understanding of how ICB antibodies can re-invigorate tumor-specific T cells and also highlight the recent advances in high complexity flow cytometry, including spectral cytometers, that allow longitudinal sampling and deep immune phenotyping in clinical settings. We encourage the scientific community to utilize advanced cytometry platforms and analyses for immune monitoring in order to optimize CIT treatments for maximum clinical benefit.

Immovable Object Meets Unstoppable Force? Dialogue Between Resident and Peripheral Myeloid Cells in the Inflamed Brain

Inflammation of the brain parenchyma is characteristic of neurodegenerative, autoimmune, and neuroinflammatory diseases. During this process, microglia, which populate the embryonic brain and become a permanent sentinel myeloid population, are inexorably joined by peripherally derived monocytes, recruited by the central nervous system. These cells can quickly adopt a morphology and immunophenotype similar to microglia. Both microglia and monocytes have been implicated in inducing, enhancing, and/or maintaining immune-mediated pathology and thus disease progression in a number of neuropathologies. For many years, experimental and analytical systems have failed to differentiate resident microglia from peripherally derived myeloid cells accurately. This has impeded our understanding of their precise functions in, and contributions to, these diseases, and hampered the development of novel treatments that could target specific cell subsets. Over the past decade, microglia have been investigated more intensively in the context of neuroimmunological research, fostering the development of more precise experimental systems. In light of our rapidly growing understanding of these cells, we discuss the differential origins of microglia and peripherally derived myeloid cells in the inflamed brain, with an analysis of the problems resolving these cell types phenotypically and morphologically, and highlight recent developments enabling more precise identification.

Phenotyping of Adaptive Immune Responses in Inflammatory Diseases

Immunophenotyping on the molecular and cellular level is a central aspect for characterization of patients with inflammatory diseases, both to better understand disease etiopathogenesis and based on this to develop diagnostic and prognostic biomarkers which allow patient stratification and tailor-made treatment strategies. Technology-driven developments have considerably expanded the range of analysis tools. Especially the analysis of adaptive immune responses, often regarded as central though mostly poorly characterized disease drivers, is a major focus of personalized medicine. The identification of the disease-relevant antigens and characterization of corresponding antigen-specific lymphocytes in individual patients benefits significantly from recent developments in cytometry by sequencing and proteomics. The aim of this workshop was to identify the important developments for state-of-the-art immunophenotyping for clinical application and precision medicine. We focused here on recent key developments in analysis of antigen-specific lymphocytes, sequencing, and proteomics approaches, their relevance in precision medicine and the discussion of the major challenges and opportunities for the future.