Single-cell technologies for monitoring immune systems.

The complex heterogeneity of cells, and their interconnectedness with each other, are major challenges to identifying clinically relevant measurements that reflect the state and capability of the immune system. Highly multiplexed, single-cell technologies may be critical for identifying correlates of disease or immunological interventions as well as for elucidating the underlying mechanisms of immunity. Here we review limitations of bulk measurements and explore advances in single-cell technologies that overcome these problems by expanding the depth and breadth of functional and phenotypic analysis in space and time. The geometric increases in complexity of data make formidable hurdles for exploring, analyzing and presenting results. We summarize recent approaches to making such computations tractable and discuss challenges for integrating heterogeneous data obtained using these single-cell technologies.

Single cell multiomic analysis of T cell exhaustion in vitro.

T-cell activation is a key step in the amplification of an immune response. Over the course of an immune response, cells may be chronically stimulated, with some proportion becoming exhausted; an enormous number of molecules are involved in this process. There remain a number of questions about the process, namely: (1) what degree of heterogeneity and plasticity do T-cells exhibit during stimulation? (2) how many unique cell states define chronic stimulation? and (3) what markers discriminate activated from exhausted cells? We addressed these questions by performing single-cell multiomic analysis to simultaneously measure expression of 38 proteins and 399 genes in human T cells expanded in vitro. This approach allowed us to study -with unprecedented depth-how T cells change over the course of chronic stimulation. Comprehensive immunophenotypic and transcriptomic analysis at day 0 enabled a refined characterization of T-cell maturational states and the identification of a donor-specific subset of terminally differentiated T-cells that would have been otherwise overlooked using canonical cell classification schema. As expected, activation downregulated naïve-cell markers and upregulated effector molecules, proliferation regulators, co-inhibitory and co-stimulatory receptors. Our deep kinetic analysis further revealed clusters of proteins and genes identifying unique states of activation, defined by markers temporarily expressed upon 3 days of stimulation (PD-1, CD69, LTA), markers constitutively expressed throughout chronic activation (CD25, GITR, LGALS1), and markers uniquely up-regulated upon 14 days of stimulation (CD39, ENTPD1, TNFDF10); expression of these markers could be associated with the emergence of short-lived cell types. Notably, different ratios of cells expressing activation or exhaustion markers were measured at each time point. These data reveal the high heterogeneity and plasticity of chronically stimulated T cells. Our study demonstrates the power of a single-cell multiomic approach to comprehensively characterize T-cells and to precisely monitor changes in differentiation, activation, and exhaustion signatures during cell stimulation.

A Cytometrist's Guide to Coordinating and Performing Effective COVID-19 Research.

Cytometry is playing a crucial role in addressing the COVID-19 pandemic. In this commentary-written by a variety of stakeholders in the cytometry, immunology, and infectious disease communities-we review cytometry's role in the COVID-19 response and discuss workflow issues critical to planning and executing effective research in this emerging field. We discuss sample procurement and processing, biosafety, technology options, data sharing, and the translation of research findings into clinical environments. © 2020 International Society for Advancement of Cytometry.

Simultaneous epitope and transcriptome measurement in single cells.

High-throughput single-cell RNA sequencing has transformed our understanding of complex cell populations, but it does not provide phenotypic information such as cell-surface protein levels. Here, we describe cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), a method in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout. CITE-seq is compatible with existing single-cell sequencing approaches and scales readily with throughput increases.

flowClean: Automated identification and removal of fluorescence anomalies in flow cytometry data.

Modern flow cytometry systems can be coupled to plate readers for high-throughput acquisition. These systems allow hundreds of samples to be analyzed in a single day. Quality control of the data remains challenging, however, and is further complicated when a large number of parameters is measured in an experiment. Our examination of 29,228 publicly available FCS files from laboratories worldwide indicates 13.7% have a fluorescence anomaly. In particular, fluorescence measurements for a sample over the collection time may not remain stable due to fluctuations in fluid dynamics; the impact of instabilities may differ between samples and among parameters. Therefore, we hypothesized that tracking cell populations (which represent a summary of all parameters) in centered log ratio space would provide a sensitive and consistent method of quality control. Here, we present flowClean, an algorithm to track subset frequency changes within a sample during acquisition, and flag time periods with fluorescence perturbations leading to the emergence of false populations. Aberrant time periods are reported as a new parameter and added to a revised data file, allowing users to easily review and exclude those events from further analysis. We apply this method to proof-of-concept datasets and also to a subset of data from a recent vaccine trial. The algorithm flags events that are suspicious by visual inspection, as well as those showing more subtle effects that might not be consistently flagged by investigators reviewing the data manually, and out-performs the current state-of-the-art. flowClean is available as an R package on Bioconductor, as a module on the free-to-use GenePattern web server, and as a plugin for FlowJo X. © 2016 International Society for Advancement of Cytometry.

A deep profiler's guide to cytometry.

In recent years, advances in technology have provided us with tools to quantify the expression of multiple genes in individual cells. The ability to measure simultaneously multiple genes in the same cell is necessary to resolve the great diversity of cell subsets, as well as to define their function in the host. Fluorescence-based flow cytometry is the benchmark for this; with it, we can quantify 18 proteins per cell, at >10 000 cells/s. Mass cytometry is a new technology that promises to extend these capabilities significantly. Immunophenotyping by mass spectrometry provides the ability to measure >36 proteins at a rate of 1000 cells/s. We review these cytometric technologies, capable of high-content, high-throughput single-cell assays.

Holoendemic malaria exposure is associated with altered Epstein-Barr virus-specific CD8(+) T-cell differentiation.

Coinfection with Plasmodium falciparum malaria and Epstein-Barr virus (EBV) is a major risk factor for endemic Burkitt lymphoma (eBL), still one of the most prevalent pediatric cancers in equatorial Africa. Although malaria infection has been associated with immunosuppression, the precise mechanisms that contribute to EBV-associated lymphomagenesis remain unclear. In this study, we used polychromatic flow cytometry to characterize CD8(+) T-cell subsets specific for EBV-derived lytic (BMFL1 and BRLF1) and latent (LMP1, LMP2, and EBNA3C) antigens in individuals with divergent malaria exposure. No malaria-associated differences in EBV-specific CD8(+) T-cell frequencies were observed. However, based on a multidimensional analysis of CD45RO, CD27, CCR7, CD127, CD57, and PD-1 expression, we found that individuals living in regions with intense and perennial (holoendemic) malaria transmission harbored more differentiated EBV-specific CD8(+) T-cell populations that contained fewer central memory cells than individuals living in regions with little or no (hypoendemic) malaria. This profile shift was most marked for EBV-specific CD8(+) T-cell populations that targeted latent antigens. Importantly, malaria exposure did not skew the phenotypic properties of either cytomegalovirus (CMV)-specific CD8(+) T cells or the global CD8(+) memory T-cell pool. These observations define a malaria-associated aberration localized to the EBV-specific CD8(+) T-cell compartment that illuminates the etiology of eBL.

Q and B values are critical measurements required for inter-instrument standardization and development of multicolor flow cytometry staining panels.

Much of the complexity of multicolor flow cytometry experiments lies within the development of antibody staining panels and the standardization of instruments. In this article, we propose a theoretical metric and describe how measurements of sensitivity and resolution can be used to predict the success of panels, and ensure that performance across instruments is standardized (i.e., inter-instrument standardization). Sensitivity can be determined by summing two major contributors of background, background originating from the instrument (optical noise and electronic noise) and background due to the experimental conditions (i.e., Raman scatter, and spillover spreading arising from other fluorochromes in the panel). The former we define as Bcal and the latter we define as Bsos . The combination of instrument and experiment background is defined as Btot . Importantly, the Btot will affect the degree of panel separation, therefore the greater the degree of Btot the lower the separation potential. In contrast, resolution is a measure of separation between populations. Resolution is directly proportional to the number of photoelectrons generated per molecule of excited fluorochrome and is known as the "Q" value. Q and Btot values can be used to define the performance of each detector on an instrument and together they can be used to calculate a separation index. Hence, detectors with known Q and Btot values can be used to evaluate panel success based on the detector specific separation index. However, the current technologies do not enable measurements of Q and Btot values for all parameters, but new technology to allow these measurements will likely be introduced in the near future. Nonetheless, Q and Btot measurements can aid in panel development, and reveal sources of instrument-to-instrument variation in panel performance. In addition, Q and B values can form the basis for a comprehensive and versatile quality assurance program.

Molecular cytometry for comprehensive immune profiling.

Molecular cytometry refers to a group of high-parameter technologies for single-cell analysis that share the following traits: (1) combined (multimodal) measurement of protein and transcripts, (2) medium throughput (10-100K cells), and (3) the use of oligonucleotide-tagged antibodies to detect protein expression. The platform can measure over 100 proteins and either hundreds of targeted genes or the whole transcriptome, on a cell-by-cell basis. It is currently one of the most powerful technologies available for immune monitoring. Here, we describe the technology platform (which includes CITE-Seq, REAP-Seq, and AbSeq), provide guidance for its optimization, and discuss advantages and limitations. Finally, we provide some vignettes from studies that demonstrate the application and potential insight that can be gained from molecular cytometry studies.

terraFlow, a high-parameter analysis tool, reveals T cell exhaustion and dysfunctional cytokine production in classical Hodgkin's lymphoma.

Immune cells express an incredible variety of proteins; by measuring combinations of these, cell types influencing disease can be precisely identified. We developed terraFlow, a platform that defines cell subsets exhaustively by combinatorial protein expression. Using high-parameter checkpoint-focused and function-focused panels, we studied classical Hodgkin's lymphoma (cHL), where systemic T cells have not been investigated in detail. terraFlow revealed immune perturbations in patients, including elevated activated, exhausted, and interleukin (IL)-17+ phenotypes, along with diminished early, interferon (IFN)γ+, and tumor necrosis factor (TNF)+ T cells before treatment; many perturbations remained after treatment. terraFlow identified more disease-associated differences than other tools, often with better predictive power, and included a non-gating approach, eliminating time-consuming and subjective manual thresholds. It also reports a method to identify the smallest set of markers distinguishing study groups. Our results provide mechanistic support for past reports of immune deficiency in cHL and demonstrate the value of terraFlow in immunotherapy and biomarker studies.

Early immunologic correlates of HIV protection can be identified from computational analysis of complex multivariate T-cell flow cytometry assays.

MOTIVATION: Polychromatic flow cytometry (PFC), has enormous power as a tool to dissect complex immune responses (such as those observed in HIV disease) at a single cell level. However, analysis tools are severely lacking. Although high-throughput systems allow rapid data collection from large cohorts, manual data analysis can take months. Moreover, identification of cell populations can be subjective and analysts rarely examine the entirety of the multidimensional dataset (focusing instead on a limited number of subsets, the biology of which has usually already been well-described). Thus, the value of PFC as a discovery tool is largely wasted. RESULTS: To address this problem, we developed a computational approach that automatically reveals all possible cell subsets. From tens of thousands of subsets, those that correlate strongly with clinical outcome are selected and grouped. Within each group, markers that have minimal relevance to the biological outcome are removed, thereby distilling the complex dataset into the simplest, most clinically relevant subsets. This allows complex information from PFC studies to be translated into clinical or resource-poor settings, where multiparametric analysis is less feasible. We demonstrate the utility of this approach in a large (n=466), retrospective, 14-parameter PFC study of early HIV infection, where we identify three T-cell subsets that strongly predict progression to AIDS (only one of which was identified by an initial manual analysis). AVAILABILITY: The 'flowType: Phenotyping Multivariate PFC Assays' package is available through Bioconductor. Additional documentation and examples are available at: www.terryfoxlab.ca/flowsite/flowType/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: rbrinkman@bccrc.ca.

Surface expression patterns of negative regulatory molecules identify determinants of virus-specific CD8+ T-cell exhaustion in HIV infection.

A highly complex network of coinhibitory and costimulatory receptors regulates the outcome of virus-specific CD8(+) T-cell responses. Here, we report on the expression patterns of multiple inhibitory receptors on HIV-specific, cytomegalovirus-specific, and bulk CD8(+) T-cell memory populations. In contrast to cytomegalovirus-specific CD8(+) T cells, the majority of HIV-specific CD8(+) T cells exhibited an immature phenotype and expressed Programmed Death-1, CD160 and 2B4 but not lymphocyte activation gene-3. Notably, before antiretroviral therapy, simultaneous expression of these negative regulators correlated strongly with both HIV load and impaired cytokine production. Suppression of HIV replication by antiretroviral therapy was associated with reduced surface expression of inhibitory molecules on HIV-specific CD8(+) T cells. Furthermore, in vitro manipulation of Programmed Death-1 and 2B4 inhibitory pathways increased the proliferative capacity of HIV-specific CD8(+) T cells. Thus, multiple coinhibitory receptors can affect the development of HIV-specific CD8(+) T-cell responses and, by extension, represent potential targets for new immune-based interventions in HIV-infected persons.

Cytometry: today's technology and tomorrow's horizons.

Flow cytometry has been the premier tool for single cell analysis since its invention in the 1960s. It has maintained this position through steady advances in technology and applications, becoming the main force behind interrogating the complexities of the immune system. Technology development was a three-pronged effort, including the hardware, reagents, and analysis algorithms to allow measurement of as many as 20 independent parameters on each cell, at tens of thousands of cells per second. In the coming years, cytometry technology will integrate with other techniques, such as transcriptomics, metabolomics, and so forth. Ongoing efforts are aimed at algorithms to analyse these aggregated datasaets over large numbers of samples. Here we review the development efforts heralding the next stage of flow cytometry.

Quantum dot semiconductor nanocrystals for immunophenotyping by polychromatic flow cytometry.

Immune responses arise from a wide variety of cells expressing unique combinations of multiple cell-surface proteins. Detailed characterization is hampered, however, by limitations in available probes and instrumentation. Here, we use the unique spectral properties of semiconductor nanocrystals (quantum dots) to extend the capabilities of polychromatic flow cytometry to resolve 17 fluorescence emissions. We show the need for this power by analyzing, in detail, the phenotype of multiple antigen-specific T-cell populations, revealing variations within complex phenotypic patterns that would otherwise remain obscure. For example, T cells specific for distinct epitopes from one pathogen, and even those specific for the same epitope, can have markedly different phenotypes. The technology we describe, encompassing the detection of eight quantum dots in conjunction with conventional fluorophores, should expand the horizons of flow cytometry, as well as our ability to characterize the intricacies of both adaptive and innate cellular immune responses.

Tumor infiltrating T cell states and checkpoint inhibitor expression in hepatic and pancreatic malignancies.

Hepato-pancreatico-biliary (HPB) malignancies are difficult-to-treat and continue to to have a high mortality and significant therapeutic resistance to standard therapies. Immune oncology (IO) therapies have demonstrated efficacy in several solid malignancies when combined with chemotherapy, whereas response rates in pancreatic ductal adenocarcinoma (PDA) are poor. While promising in hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), there remains an unmet need to fully leverage IO therapies to treat HPB tumors. We therefore defined T cell subsets in the tumor microenvironment of HPB patients utilizing a novel, multiparameter flow cytometry and bioinformatics analysis. Our findings quantify the T cell phenotypic states in relation to checkpoint receptor expression. We demonstrate the presence of CD103+ tissue resident memory T cells (TRM), CCR7+ central memory T cells, and CD57+ terminally differentiated effector cells across all HPB cancers, while the anti-tumor function was dampened by expression of multiple co-inhibitory checkpoint receptors. Terminally exhausted T cells lacking co-stimulatory receptors were more prevalent in PDA, whereas partially exhausted T cells expressing both co-inhibitory and co-stimulatory receptors were most prevalent in HCC, especially in early stage. HCC patients had significantly higher TRM with a phenotype that could confer restored activation in response to immune checkpoint therapies. Further, we found a lack of robust alteration in T cell activation state or checkpoint expression in response to chemotherapy in PDA patients. These results support that HCC patients might benefit most from combined checkpoint therapies, whereas efforts other than cytotoxic chemotherapy will likely be necessary to increase overall T cell activation in CCA and PDA for future clinical development.

Corrigendum: Tumor infiltrating T cell states and checkpoint inhibitor expression in hepatic and pancreatic malignancies.

[This corrects the article DOI: 10.3389/fimmu.2023.1067352.].