Novel full-spectral flow cytometry with multiple spectrally-adjacent fluorescent proteins and fluorochromes and visualization of in vivo cellular movement

Computational Hyperspectral Microflow Cytometry

Miniaturized flow cytometry has significant potential for portable applications, such as cell-based diagnostics and the monitoring of therapeutic cell manufacturing, however, the performance of current techniques is often limited by the inability to resolve spectrally-overlapping fluorescence labels. Here, the study presents a computational hyperspectral microflow cytometer (CHC) that enables accurate discrimination of spectrally-overlapping fluorophores labeling single cells. CHC employs a dispersive optical element and an optimization algorithm to detect the full fluorescence emission spectrum from flowing cells, with a high spectral resolution of ≈3 nm in the range from 450 to 650 nm. CHC also includes a dedicated microfluidic device that ensures in-focus imaging through viscoelastic sheathless focusing, thereby enhancing the accuracy and reliability of microflow cytometry analysis. The potential of CHC for analyzing T lymphocyte subpopulations and monitoring changes in cell composition during T cell expansion is demonstrated. Overall, CHC represents a major breakthrough in microflow cytometry and can facilitate its use for immune cell monitoring.

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.

Beyond 40 fluorescent probes for deep phenotyping of blood mononuclear cells, using spectral technology

The analytical capability of flow cytometry is crucial for differentiating the growing number of cell subsets found in human blood. This is important for accurate immunophenotyping of patients with few cells and a large number of parameters to monitor. Here, we present a 43-parameter panel to analyze peripheral blood mononuclear cells from healthy individuals using 41 fluorescence-labelled monoclonal antibodies, an autofluorescent channel, and a viability dye. We demonstrate minimal population distortions that lead to optimized population identification and reproducible results. We have applied an advanced approach in panel design, in selection of sample acquisition parameters and in data analysis. Appropriate autofluorescence identification and integration in the unmixing matrix, allowed for resolution of unspecific signals and increased dimensionality. Addition of one laser without assigned fluorochrome resulted in decreased fluorescence spill over and improved discrimination of cell subsets. It also increased the staining index when autofluorescence was integrated in the matrix. We conclude that spectral flow cytometry is a highly valuable tool for high-end immunophenotyping, and that fine-tuning of major experimental steps is key for taking advantage of its full capacity.

Comparative assessment of cytometry by time-of-flight and full spectral flow cytometry based on a 33-color antibody panel

Mass cytometry and full spectrum flow cytometry have recently emerged as new promising single cell proteomic analysis tools that can be exploited to decipher the extensive diversity of immune cell repertoires and their implication in human diseases. In this study, we evaluated the performance of mass cytometry against full spectrum flow cytometry using an identical 33-color antibody panel on four healthy individuals. Our data revealed an overall high concordance in the quantification of major immune cell populations between the two platforms using a semi-automated clustering approach. We further showed a strong correlation of cluster assignment when comparing manual and automated clustering. Both comparisons revealed minor disagreements in the quantification and assignment of rare cell subpopulations. Our study showed that both single cell proteomic technologies generate highly overlapping results and substantiate that the choice of technology is not a primary factor for successful biological assessment of cell profiles but must be considered in a broader design framework of clinical studies.

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.

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.

Guidelines for establishing a cytometry laboratory

The purpose of this document is to provide guidance for establishing and maintaining growth and development of flow cytometry shared resource laboratories. While the best practices offered in this manuscript are not intended to be universal or exhaustive, they do outline key goals that should be prioritized to achieve operational excellence and meet the needs of the scientific community. Additionally, this document provides information on available technologies and software relevant to shared resource laboratories. This manuscript builds on the work of Barsky et al. 2016 published in Cytometry Part A and incorporates recent advancements in cytometric technology. A flow cytometer is a specialized piece of technology that require special care and consideration in its housing and operations. As with any scientific equipment, a thorough evaluation of the location, space requirements, auxiliary resources, and support is crucial for successful operation. This comprehensive resource has been written by past and present members of the International Society for Advancement of Cytometry (ISAC) Shared Resource Laboratory (SRL) Emerging Leaders Program https://isac-net.org/general/custom.asp?page=SRL-Emerging-Leaders with extensive expertise in managing flow cytometry SRLs from around the world in different settings including academia and industry. It is intended to assist in establishing a new flow cytometry SRL, re-purposing an existing space into such a facility, or adding a flow cytometer to an individual lab in academia or industry. This resource reviews the available cytometry technologies, the operational requirements, and best practices in SRL staffing and management.

Standardized high-dimensional spectral cytometry protocol and panels for whole blood immune phenotyping in clinical and translational studies

Flow cytometry is the method of choice for immunophenotyping in the context of clinical, translational, and systems immunology studies. Among the latter, the Milieu Intérieur (MI) project aims at defining the boundaries of a healthy immune response to identify determinants of immune response variation. MI used immunophenotyping of a 1000 healthy donor cohort by flow cytometry as a principal outcome for immune variance at steady state. New generation spectral cytometers now enable high-dimensional immune cell characterization from small sample volumes. Therefore, for the MI 10-year follow up study, we have developed two high-dimensional spectral flow cytometry panels for deep characterization of innate and adaptive whole blood immune cells (35 and 34 fluorescent markers, respectively). We have standardized the protocol for sample handling, staining, acquisition, and data analysis. This approach enables the reproducible quantification of over 182 immune cell phenotypes at a single site. We have applied the protocol to discern minor differences between healthy and patient samples and validated its value for application in immunomonitoring studies. Our protocol is currently used for characterization of the impact of age and environmental factors on peripheral blood immune phenotypes of >400 donors from the initial MI cohort.

Multiparameter Flow Cytometry Monitoring of T Cell Responses

Multiparameter flow cytometry is a common tool for assessing responses of T, B, and other cells to pathogens or vaccines. Such responses are likely to be important for predicting the efficacy of an HIV vaccine, despite the elusive findings in HIV vaccine trials to date. Fortunately, flow cytometry has evolved to be capable of readily measuring 30-40 parameters, providing the ability to dissect detailed phenotypes and functions that may be correlated with disease protection. Nevertheless, technical hurdles remain, and standardization of assays is still largely lacking. Here an optimized protocol for antigen-specific T cell monitoring is presented, with specific variations for particular markers. It covers the analysis of multiple cytokines, cell surface proteins, and other functional markers such as CD107, CD154, CD137, etc. References are given to published panels of 8-28 colors.

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.

Opportunities in optical and electrical single-cell technologies to study microbial ecosystems

New techniques are revolutionizing single-cell research, allowing us to study microbes at unprecedented scales and in unparalleled depth. This review highlights the state-of-the-art technologies in single-cell analysis in microbial ecology applications, with particular attention to both optical tools, i.e., specialized use of flow cytometry and Raman spectroscopy and emerging electrical techniques. The objectives of this review include showcasing the diversity of single-cell optical approaches for studying microbiological phenomena, highlighting successful applications in understanding microbial systems, discussing emerging techniques, and encouraging the combination of established and novel approaches to address research questions. The review aims to answer key questions such as how single-cell approaches have advanced our understanding of individual and interacting cells, how they have been used to study uncultured microbes, which new analysis tools will become widespread, and how they contribute to our knowledge of ecological interactions.

Development of Spectral Nano-Flow Cytometry for High-Throughput Multiparameter Analysis of Individual Biological Nanoparticles

Correlated analysis of multiple biochemical parameters at the single-particle level and in a high-throughput manner is essential for insights into the diversity and functions of biological nanoparticles (BNPs), such as bacteria and subcellular organelles. To meet this challenge, we developed a highly sensitive spectral nano-flow cytometer (S-nFCM) by integrating a spectral recording module to a laboratory-built nFCM that is 4-6 orders of magnitude more sensitive in side scattering detection and 1-2 orders of magnitude more sensitive in fluorescence detection than conventional flow cytometers. An electron-multiplying charge-coupled device (EMCCD) was used to acquire the full fluorescence spectra of single BNPs upon holographic grating dispersion. Up to 10,000 spectra can be collected in 1 min with 2.1 nm resolution. The precision, linearity, and sensitivity were examined. Complete discernment of single influenza viruses against the background signal, discrimination of different strains of marine cyanobacteria in a mixed sample based on their spectral properties of natural fluorescence, classification of bacterial categories exhibiting different patterns of antigen expression, and multiparameter analysis of single mitochondria for drug discovery were successfully demonstrated.

Prism Design for Spectral Flow Cytometry

Flow cytometers are instruments used for the rapid quantitative analysis of cell suspension. Traditional flow cytometry uses multi-channel filters to detect fluorescence, whereas full-spectrum fluorescence based on dispersion detection is a more effective and accurate method. The application of various dispersion schemes in flow cytometry spectroscopy has been studied. From the perspective of modern detectors and demand for the miniaturization of flow cytometry, prism dispersion exhibits higher and more uniform light energy utilization, meaning that it is a more suitable dispersion method for small flow cytometers, such as microfluidic flow cytometers. Prism dispersion designs include the size, number, and placement of prisms. By deducing the formula of the final position of light passing through the prism and combining it with the formula of transmittance, the design criteria of the top angle and the incident angle of the prism in pursuit of the optimum transmittance and dispersion index can be obtained. Considering the case of multiple prisms, under the premise of pursuing a smaller size, the optimal design criteria for dispersion system composed of multiple prisms can be obtained. The design of prism dispersion fluorescence detection was demonstrated with a microfluidic flow cytometer, and the effectiveness of the design results was verified by microsphere experiments and practical biological experiments. This design criterion developed in this study is generally applicable to spectral flow cytometers.

Using Virtual Filtering Approach to Discriminate Microalgae by Spectral Flow Cytometer

Fluorescence methods are widely used for the study of marine and freshwater phytoplankton communities. However, the identification of different microalgae populations by the analysis of autofluorescence signals remains a challenge. Addressing the issue, we developed a novel approach using the flexibility of spectral flow cytometry analysis (SFC) and generating a matrix of virtual filters (VF) which allowed thorough examination of autofluorescence spectra. Using this matrix, different spectral emission regions of algae species were analyzed, and five major algal taxa were discriminated. These results were further applied for tracing particular microalgae taxa in the complex mixtures of laboratory and environmental algal populations. An integrated analysis of single algal events combined with unique spectral emission fingerprints and light scattering parameters of microalgae can be used to differentiate major microalgal taxa. We propose a protocol for the quantitative assessment of heterogenous phytoplankton communities at the single-cell level and monitoring of phytoplankton bloom detection using a virtual filtering approach on a spectral flow cytometer (SFC-VF).

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.

In Vivo Tracking of Dendritic Cell Migration

Dendritic cells (DCs) in peripheral tissue serve as a sentinel to invasion and maintain tolerance. They ingest and carry antigens to the draining lymph nodes and present antigens to antigen-specific T cells to initiate acquired immune responses. Thus, understanding DC migration from peripheral tissues and function is critical for understanding DCs' roles in immune homeostasis. Here, we introduced the KikGR in vivo photolabeling system, an ideal tool for monitoring precise cellular movements and related functions in vivo under physiological conditions and during various immune responses that occur in pathologic condition. Using a mouse line expressing photoconvertible fluorescent protein KikGR, we can label DCs in peripheral tissues by changing the color of KikGR from green to red after exposure to violet light and accurately track DC migration from each peripheral tissue to its respective draining lymph nodes.

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.

Autofluorescence-based high-throughput isolation of nonbleaching Cyanidioschyzon merolae strains under nitrogen-depletion

Photosynthetic organisms maintain optimum levels of photosynthetic pigments in response to environmental changes to adapt to the conditions. The identification of cyanobacteria strains that alleviate bleaching has revealed genes that regulate levels of phycobilisome, the main light-harvesting complex. In contrast, the mechanisms of pigment degradation in algae remain unclear, as no nonbleaching strains have previously been isolated. To address this issue, this study attempted to isolate nonbleaching strains of the unicellular red alga Cyanidioschyzon merolae after exposure to nitrogen (N)-depletion based on autofluorescence information. After four weeks under N-depletion, 13 cells from 500,000 cells with almost identical pre- and post-depletion chlorophyll a (Chl a) and/or phycocyanin autofluorescence intensities were identified. These nonbleaching candidate strains were sorted via a cell sorter, isolated on solid medium, and their post-N-depletion Chl a and phycocyanin levels were analyzed. Chl a levels of these nonbleaching candidate strains were lower at 1-4 weeks of N-depletion similar to the control strains, however, their phycocyanin levels were unchanged. Thus, we successfully isolated nonbleaching C. merolae strains in which phycocyanin was not degraded under N-depletion, via autofluorescence spectroscopy and cell sorting. This versatile method will help to elucidate the mechanisms regulating pigments in microalgae.

Demands and technical developments of clinical flow cytometry with emphasis in quantitative, spectral, and imaging capabilities

As the gold-standard method for single-cell analysis, flow cytometry enables high-throughput and multiple-parameter characterization of individual biological cells. This review highlights the demands for clinical flow cytometry in laboratory hematology (e.g., diagnoses of minimal residual disease and various types of leukemia), summarizes state-of-the-art clinical flow cytometers (e.g., FACSLyricTM by Becton Dickinson, DxFLEX by Beckman Coulter), then considers innovative technical improvements in flow cytometry (including quantitative, spectral, and imaging approaches) to address the limitations of clinical flow cytometry in hematology diagnosis. Finally, driven by these clinical demands, future developments in clinical flow cytometry are suggested.

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.

Identification of fetal liver stroma in spectral cytometry using the parameter autofluorescence

The fetal liver (FL) is the main hematopoietic organ during embryonic development. The FL is also the unique anatomical site where hematopoietic stem cells expand before colonizing the bone marrow, where they ensure life-long blood cell production and become mostly resting. The identification of the different cell types that comprise the hematopoietic stroma in the FL is essential to understand the signals required for the expansion and differentiation of the hematopoietic stem cells. We used a panel of monoclonal antibodies to identify FL stromal cells in a 5-laser equipped spectral flow cytometry (FCM) analyzer. The "Autofluorescence Finder" of SONY ID7000 software identified two distinct autofluorescence emission spectra. Using autofluorescence as a fluorescence parameter we could assign the two autofluorescent signals to three distinct cell types and identified surface markers that characterize these populations. We found that one autofluorescent population corresponds to hepatoblast-like cells and cholangiocytes whereas the other expresses mesenchymal transcripts and was identified as stellate cells. Importantly, after birth, autofluorescence becomes the unique identifying property of hepatoblast-like cells because mature cholangiocytes are no longer autofluorescent. These results show that autofluorescence used as a parameter in spectral FCM is a useful tool to identify new cell subsets that are difficult to analyze in conventional FCM.

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.

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.

Novel PE and APC tandems: Additional near-infrared fluorochromes for use in spectral flow cytometry

Recent advances in flow cytometry instrumentation and fluorochrome chemistries have greatly increased fluorescent conjugated antibody combinations that can be used reliably and easily in routine experiments. The Cytek Aurora flow cytometer was first released with three excitation lasers (405, 488, and 640 nm) and incorporated the latest Avalanche Photodiode (APD) technology, demonstrating significant improvement in sensitivity for fluorescent emission signals longer than 800 nm. However, there are limited commercially available fluorochromes capable of excitation with peak emission signals beyond 800 nm. To address this gap, we engineered six new fluorochromes: PE-750, PE-800, PE-830 for the 488 nm laser and APC-750, APC-800, APC-830 for the 640 nm laser. Utilizing the principal of fluorescence resonance energy transfer (FRET), these novel structures were created by covalently linking a protein donor dye with an organic small molecule acceptor dye. Additionally, each of these fluorochrome conjugates were shown to be compatible with fixation/permeabilization buffer reagents, and demonstrated acceptable brightness and stability when conjugated to antigen-specific monoclonal antibodies. These six novel fluorochrome reagents can increase the numbers of fluorochromes that can be used on a spectral flow cytometer.

Mapping Cell Phenomics with Multiparametric Flow Cytometry Assays

Phenomics explores the complex interactions among genes, epigenetics, symbiotic microorganisms, diet, and environmental exposure based on the physical, chemical, and biological characteristics of individuals and groups. Increasingly efficient and comprehensive phenotyping techniques have been integrated into modern phenomics-related research. Multicolor flow cytometry technology provides more measurement parameters than conventional flow cytometry. Based on detailed descriptions of cell phenotypes, rare cell populations and cell subsets can be distinguished, new cell phenotypes can be discovered, and cell apoptosis characteristics can be detected, which will expand the potential of cell phenomics research. Based on the enhancements in multicolor flow cytometry hardware, software, reagents, and method design, the present review summarizes the recent advances and applications of multicolor flow cytometry in cell phenomics, illuminating the potential of applying phenomics in future studies.

CyTOF® for the Masses

Mass cytometry has revolutionized immunophenotyping, particularly in exploratory settings where simultaneous breadth and depth of characterization of immune populations is needed with limited samples such as in preclinical and clinical tumor immunotherapy. Mass cytometry is also a powerful tool for single-cell immunological assays, especially for complex and simultaneous characterization of diverse intratumoral immune subsets or immunotherapeutic cell populations. Through the elimination of spectral overlap seen in optical flow cytometry by replacement of fluorescent labels with metal isotopes, mass cytometry allows, on average, robust analysis of 60 individual parameters simultaneously. This is, however, associated with significantly increased complexity in the design, execution, and interpretation of mass cytometry experiments. To address the key pitfalls associated with the fragmentation, complexity, and analysis of data in mass cytometry for immunologists who are novices to these techniques, we have developed a comprehensive resource guide. Included in this review are experiment and panel design, antibody conjugations, sample staining, sample acquisition, and data pre-processing and analysis. Where feasible multiple resources for the same process are compared, allowing researchers experienced in flow cytometry but with minimal mass cytometry expertise to develop a data-driven and streamlined project workflow. It is our hope that this manuscript will prove a useful resource for both beginning and advanced users of mass cytometry.

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.

Fate-mapping mice: new tools and technology for immune discovery

The fate-mapping mouse has become an essential tool in the immunologist's toolbox. Although traditionally used by developmental biologists to trace the origins of cells, immunologists are turning to fate-mapping to better understand the development and function of immune cells. Thus, an expansion in the variety of fate-mapping mouse models has occurred to answer fundamental questions about the immune system. These models are also being combined with new genetic tools to study cancer, infection, and autoimmunity. In this review, we summarize different types of fate-mapping mice and describe emerging technologies that might allow immunologists to leverage this valuable tool and expand our functional knowledge of the immune system.

An effective spectral unmixing algorithm for flow cytometry based on GA and least squares

Spectral unmixing algorithm is one of the key technologies for spectral flow cytometer in biology, chemistry and medicine. The proposed algorithm can separate the overlapping spectra automatically without the premeasured single stained or un-stained samples as the basic pure spectra. Genetic algorithm is adopted to search the optimal positions and peak sharps of the basic spectra derived from the unknown components, and then the concentration of each component can be estimated simultaneously by least squares method. Compared with conventional methods, the proposed algorithm has a wider application scope, such as the multi-stained samples with unknown components or the samples with auto-fluorescence. In the simulation, the convergence rate, accuracy and stability of the proposed algorithm are evaluated under the conditions of completely and partly unknown components. In the experiment, the flow spectra of cyanobacteria are processed, and the results demonstrate the feasibility and effectiveness of the proposed algorithm.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers.

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

Analyzing high-dimensional cytometry data using FlowSOM

The dimensionality of cytometry data has strongly increased in the last decade, and in many situations the traditional manual downstream analysis becomes insufficient. The field is therefore slowly moving toward more automated approaches, and in this paper we describe the protocol for analyzing high-dimensional cytometry data using FlowSOM, a clustering and visualization algorithm based on a self-organizing map. FlowSOM is used to distinguish cell populations from cytometry data in an unsupervised way and can help to gain deeper insights in fields such as immunology and oncology. Since the original FlowSOM publication (2015), we have validated the tool on a wide variety of datasets, and to write this protocol, we made use of this experience to improve the user-friendliness of the package (e.g., comprehensive functions replacing commonly required scripts). Where the original paper focused mainly on the algorithm description, this protocol offers user guidelines on how to implement the procedure, detailed parameter descriptions and troubleshooting recommendations. The protocol provides clearly annotated R code, and is therefore relevant for all scientists interested in computational high-dimensional analyses without requiring a strong bioinformatics background. We demonstrate the complete workflow, starting from data preparation (such as compensation, transformation and quality control), including detailed discussion of the different FlowSOM parameters and visualization options, and concluding with how the results can be further used to answer biological questions, such as statistical comparison between groups of interest. An average FlowSOM analysis takes 1-3 h to complete, though quality issues can increase this time considerably.

Cutting Edge: Recruitment, Retention, and Migration Underpin Functional Phenotypic Heterogeneity of Regulatory T Cells in Tumors

Tumor-infiltrating regulatory T cells (Tregs) have been extensively studied as therapeutic targets. However, not all infiltrating T cells exert their functions equally, presumably because of their heterogeneity and substantial turnover in tissues. In this study, we hypothesized that intertissue migration underlies the functional heterogeneity of Tregs. To test this, we applied in vivo photolabeling to examine single-cell diversity of immunosuppressive molecules in mouse Tregs migrating to, remaining in, and emigrating from MC38 tumors. Neuropilin-1 (Nrp1) expression was inversely correlated with that of six other molecules associated with Treg function. Unsupervised clustering analyses revealed that clusters containing Tregs that were retained in tumors expressed high levels of the six functional molecules but not of Nrp1. However, these clusters represented only half of the Tregs migrating to the tumor, suggesting evolving heterogeneity of tumor-infiltrating Tregs. Thus, we propose progressive pathways of Treg activation and migration between tumors and draining lymph nodes.

Panel Design and Optimization for High-Dimensional Immunophenotyping Assays Using Spectral Flow Cytometry

Technological advances in fluorescence flow cytometry and an ever-expanding understanding of the complexity of the immune system have led to the development of large (20+ parameters) flow cytometry panels. However, as panel complexity and size increase, so does the difficulty involved in designing a high-quality panel, accessing the instrumentation capable of accommodating large numbers of parameters, and analyzing such high-dimensional data. A recent advancement is spectral flow cytometry, which in contrast to conventional flow cytometry distinguishes the full emission spectrum of each fluorophore across all lasers, rather than identifying only the peak of emission. Fluorophores with a similar emission maximum but distinct off-peak signatures can therefore be accommodated within the same flow cytometry panel, allowing greater flexibility in terms of panel design and fluorophore detection. Here, we highlight the specific characteristics of spectral flow cytometry and aim to guide users through the process of building, designing, and optimizing high-dimensional spectral flow cytometry panels using a comprehensive step-by-step protocol. Special considerations are also given for using highly overlapping dyes, and a logical selection process for optimal marker-fluorophore assignment is provided. © 2020 by John Wiley & Sons, Inc.

Predictive Markers of Immunogenicity and Efficacy for Human Vaccines

Vaccines represent one of the major advances of modern medicine. Despite the many successes of vaccination, continuous efforts to design new vaccines are needed to fight "old" pandemics, such as tuberculosis and malaria, as well as emerging pathogens, such as Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Vaccination aims at reaching sterilizing immunity, however assessing vaccine efficacy is still challenging and underscores the need for a better understanding of immune protective responses. Identifying reliable predictive markers of immunogenicity can help to select and develop promising vaccine candidates during early preclinical studies and can lead to improved, personalized, vaccination strategies. A systems biology approach is increasingly being adopted to address these major challenges using multiple high-dimensional technologies combined with in silico models. Although the goal is to develop predictive models of vaccine efficacy in humans, applying this approach to animal models empowers basic and translational vaccine research. In this review, we provide an overview of vaccine immune signatures in preclinical models, as well as in target human populations. We also discuss high-throughput technologies used to probe vaccine-induced responses, along with data analysis and computational methodologies applied to the predictive modeling of vaccine efficacy.

AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data

Compensating in flow cytometry is an unavoidable challenge in the data analysis of fluorescence-based flow cytometry. Even the advent of spectral cytometry cannot circumvent the spillover problem, with spectral unmixing an intrinsic part of such systems. The calculation of spillover coefficients from single-color controls has remained essentially unchanged since its inception, and is increasingly limited in its ability to deal with high-parameter flow cytometry. Here, we present AutoSpill, an alternative method for calculating spillover coefficients. The approach combines automated gating of cells, calculation of an initial spillover matrix based on robust linear regression, and iterative refinement to reduce error. Moreover, autofluorescence can be compensated out, by processing it as an endogenous dye in an unstained control. AutoSpill uses single-color controls and is compatible with common flow cytometry software. AutoSpill allows simpler and more robust workflows, while reducing the magnitude of compensation errors in high-parameter flow cytometry.

Tracking the fate and migration of cells in live animals with cell-cycle indicators and photoconvertible proteins

Cell migration and cell proliferation are the basic principles that make up a living organism, and both biologically and medically. In order to understand living organism and biological phenomena, it is essential to track the migration, proliferation, and fate of cells in living cells and animals and to clarify the properties and molecular expression of cells. Recent developments in novel fluorescent proteins have made it possible to observe cell migration and proliferation as the cell cycle at the single-cell level in living individuals and tissues. Here, we introduce cell cycle visualization of living cells and animals by Fucci (Fluorescent Ubiquitination-based Cell Cycle Indicator) system and in situ cell labeling of cells and tracking cell migration by photoactivatable and photoconvertible proteins. In addition, we will present our established methods as an example of combines above tools with single-cell molecular expression analysis to reveal the fate of migrating cells at single cell level.

SIMON: Open-Source Knowledge Discovery Platform

Data analysis and knowledge discovery has become more and more important in biology and medicine with the increasing complexity of biological datasets, but the necessarily sophisticated programming skills and in-depth understanding of algorithms needed pose barriers to most biologists and clinicians to perform such research. We have developed a modular open-source software, SIMON, to facilitate the application of 180+ state-of-the-art machine-learning algorithms to high-dimensional biomedical data. With an easy-to-use graphical user interface, standardized pipelines, and automated approach for machine learning and other statistical analysis methods, SIMON helps to identify optimal algorithms and provides a resource that empowers non-technical and technical researchers to identify crucial patterns in biomedical data.

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.

Diffractive Beam Shaper for Multiwavelength Lasers for Flow Cytometry

Illumination spot in a flow cytometer is a crucial factor determining the measurement accuracy and stability. The traditional mechanism is to precisely calibrate multiple optical components to convert circular Gaussian beams into elliptical Gaussian beams, making it difficult to shape multiwavelength lasers simultaneously. A diffractive beam shaper for multicolor lasers with high simplicity, only containing one diffractive optical element and one focusing lens is created in this work. It can produce rectangular spots, of which the number, the sizes, and the positions are accurately determined by the incident wavelengths. Demonstrated in the customized microflow cytometer, the coefficient of variations (CV) of the optical signals by the beam shaper are 3.6-6.5%, comparable to those derived from the commercial instrument with 3.3-6.3% CVs. Benefiting from the narrow rectangular spots and the flexibility of diffractively shaped lasers, the measurement of bead sizes with 4-15 μm diameters and the real-time detection of flow velocity from 0.79 to 9.50 m/s with the CV of <5% are achieved. © 2020 International Society for Advancement of Cytometry.

OMIP-069: Forty-Color Full Spectrum Flow Cytometry Panel for Deep Immunophenotyping of Major Cell Subsets in Human Peripheral Blood

This 40-color flow cytometry-based panel was developed for in-depth immunophenotyping of the major cell subsets present in human peripheral blood. Sample availability can often be limited, especially in cases of clinical trial material, when multiple types of testing are required from a single sample or timepoint. Maximizing the amount of information that can be obtained from a single sample not only provides more in-depth characterization of the immune system but also serves to address the issue of limited sample availability. The panel presented here identifies CD4 T cells, CD8 T cells, regulatory T cells, γδ T cells, NKT-like cells, B cells, NK cells, monocytes and dendritic cells. For each specific cell type, the panel includes markers for further characterization by including a selection of activation and differentiation markers, as well as chemokine receptors. Moreover, the combination of multiple markers in one tube might lead to the discovery of new immune phenotypes and their relevance in certain diseases. Of note, this panel was designed to include only surface markers to avoid the need for fixation and permeabilization steps. The panel can be used for studies aimed at characterizing the immune response in the context of infectious or autoimmune diseases, monitoring cancer patients on immuno- or chemotherapy, and discovery of unique and targetable biomarkers. Different from all previously published OMIPs, this panel was developed using a full spectrum flow cytometer, a technology that has allowed the effective use of 40 fluorescent markers in a single panel. The panel was developed using cryopreserved human peripheral blood mononuclear cells (PBMC) from healthy adults (Table 1). Although we have not tested the panel on fresh PBMCs or whole blood, it is anticipated that the panel could be used in those sample preparations without further optimization. @ 2020 Cytek Biosciences, Inc. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry.

Evaluating spectral cytometry for immune profiling in viral disease

In conventional fluorescence cytometry, each fluorophore present in a panel is measured in a target detector, through the use of wide band-pass optical filters. In contrast, spectral cytometry uses a large number of detectors with narrow band-pass filters to measure a fluorophore's signal across the spectrum, creating a more detailed fluorescent signature for each fluorophore. The spectral approach shows promise in adding flexibility to panel design and improving the measurement of fluorescent signal. However, few comparisons between conventional and spectral systems have been reported to date. We therefore sought to compare a modern conventional cytometry system with a modern spectral system, and to assess the quality of resulting datasets from the point of view of a flow cytometry user. Signal intensity, spread, and resolution were compared between the systems. Subsequently, the different methods of separating fluorophore signals were compared, where compensation mathematically separates multiple overlapping fluorophores and unmixing relies on creating a detailed fluorescent signature across the spectrum to separate the fluorophores. Within the spectral data set, signal spread and resolution were comparable between compensation and unmixing. However, for some highly overlapping fluorophores, unmixing resolved the two fluorescence signals where compensation did not. Finally, data from mid- to large-size panels were acquired and were found to have comparable resolution for many fluorophores on both instruments, but reduced levels of spreading error on our spectral system improved signal resolution for a number of fluorophores, compared with our conventional system. Furthermore, autofluorescence extraction on the spectral system allowed for greater population resolution in highly autofluorescent samples. Overall, the implementation of a spectral cytometry approach resulted in data that are comparable to that generated on conventional systems, with a number of potential advantages afforded by the larger number of detectors, and the integration of the spectral unmixing approach. © 2020 International Society for Advancement of Cytometry.

Dynamic Changes in the Phenotype of Dendritic Cells in the Uterus and Uterine Draining Lymph Nodes After Coitus

Dendritic cells (DCs) are essential for successful embryo implantation. However, the properties of uterine DCs (uDCs) during the implantation period are not well characterized. In this study, we investigated the dynamic changes in the uDC phenotypes during the period between coitus and implantation. In virgin mice, we evaluated the expressions of CD103 and XCR1, this is the first report to demonstrate uDCs expressing CD103 in XCR1⁺cDC1s and XCR1⁺cDC2s. On day 0.5 post coitus (pc), the number of uterine CD11c⁺CD103^–MHC classII^highCD86^high–mature DCs rapidly increased and then decreased to non-pregnancy levels on days 1.5 and 2.5 pc. On day 3.5 pc just before implantation, the number of CD11c⁺CD103⁺MHC class II^dimCD86^dim–immature DCs increased in the uterus. The increase in mature uDCs on day 1.5 pc was observed in both allogeneic- and syngeneic mating, suggesting that sexual intercourse, or semen, play a role in this process. Meanwhile, the increase in immature uDCs on day 3.5 pc was only observed in allogeneic mating, suggesting that allo-antigens in the semen contribute to this process. Next, to understand the turnover and migration of uDCs, we monitored DC movement in the uterus and uterine draining lymph nodes (dLNs) using photoconvertible protein Kikume Green Red (KikGR) mice. On day 0.5 pc, uDCs were composed of equal numbers of remaining DCs and migratory DCs. However, on day 3.5 pc, uDCs were primarily composed of migratory DCs, suggesting that most of the uDCs migrate from the periphery just before implantation. Finally, we studied the expression of PD-L2—which induces immunoregulation—on DCs. On day 3.5 pc, PD-L2 was expressed on CD103⁺-mature and CD103^–-mature DCs in the uterus. However, PD-L2 expression on CD103^–-immature DCs and CD103⁺-immature DCs was very low. Furthermore, both remaining and migratory DCs in the uterus and uterus-derived-DCs in the dLNs on day 3.5 pc highly expressed PD-L2 on their surface. Therefore, our study findings provide a better understanding of the dynamic changes occurring in uterine DCs and dLNs in preparation for implantation following allogeneic- and syngeneic mating.

Circulation of gut-preactivated naïve CD8+ T cells enhances antitumor immunity in B cell-defective mice

The gut microbiome has garnered attention as an effective target to boost immunity and improve cancer immunotherapy. We found that B cell-defective (BCD) mice, such as µ-membrane targeted deletion (µMT) and activation-induced cytidine deaminase (AID) knockouts (KOs), have elevated antitumor immunity under specific pathogen-free but not germ-free conditions. Microbial dysbiosis in these BCD mice enriched the type I IFN (IFN) signature in mucosal CD8⁺ T cells, resulting in up-regulation of the type I IFN-inducible protein stem cell antigen-1 (Sca-1). Among CD8⁺ T cells, naïve cells predominantly circulate from the gut to the periphery, and those that had migrated from the mesenteric lymph nodes (mLNs) to the periphery had significantly higher expression of Sca-1. The gut-educated Sca-1⁺ naïve subset is endowed with enhanced mitochondrial activity and antitumor effector potential. The heterogeneity and functional versatility of the systemic naïve CD8⁺ T cell compartment was revealed by single-cell analysis and functional assays of CD8⁺ T cell subpopulations. These results indicate one of the potential mechanisms through which microbial dysbiosis regulates antitumor immunity.

Genomic Cytometry and New Modalities for Deep Single-Cell Interrogation

In the past few years, the rapid development of single-cell analysis techniques has allowed for increasingly in-depth analysis of DNA, RNA, protein, and epigenetic states, at the level of the individual cell. This unprecedented characterization ability has been enabled through the combination of cytometry, microfluidics, genomics, and informatics. Although traditionally discrete, when properly integrated, these fields create the synergistic field of Genomic Cytometry. In this review, we look at the individual methods that together gave rise to the broad field of Genomic Cytometry. We further outline the basic concepts that drive the field and provide a framework to understand this increasingly complex, technology-intensive space. Thus, we introduce Genomic Cytometry as an emerging field and propose that synergistic rationalization of disparate modalities of cytometry, microfluidics, genomics, and informatics under one banner will enable massive leaps forward in the understanding of complex biology. © 2020 International Society for Advancement of Cytometry.