A mine is a terrible thing to waste: high content, single cell technologies for comprehensive immune analysis

A monodispersed metal-complexing peptide-based polymer for mass cytometry enabling spectral applications

We report the synthesis of a novel class of metal-complexing peptide-based polymers, which we name HyperMAPs (Hyper-loaded MetAl-complexed Polymers). The controlled solid-phase synthesis of HyperMAPs' scaffold peptide provides our polymer with a well-defined molecular structure that allows for an accurate on-design assembly of a wide variety of metals. The peptide-scaffold features a handle for direct conjugation to antibodies or any other biomolecules by means of a thiol-maleimide-click or aldehyde-oxime reaction, a fluorogenic moiety for biomolecule conjugation tracking, and a well-defined number of functional groups for direct incorporation of metal-chelator complexes. Since metal-chelator complexes are prepared in a separate reaction prior to incorporation to the peptide scaffold, polymers can be designed to contain specific ratios of metal isotopes, providing each polymer with a unique CyTOF spectral fingerprint. We demonstrate the complexing of 21 different metals using two different chelators and provide evidence of the application of HyperMAPs on a 13 parameter CyTOF panel and compare its performance to monoisotopic metal-conjugated antibodies.

OMIP-94: Twenty-four-color (thirty-marker) panel for deep immunophenotyping of immune cells in human peripheral blood

This newly established 24-color (30-marker) panel focuses on the characterization of the main human immune cell subtypes and was optimized for the analysis of human whole blood using a full spectrum flow cytometer. The panel covers all main leukocyte populations: neutrophils, eosinophils and basophils, monocytes (with additional subsets), dendritic cells, innate lymphoid cells and lymphocytes. As for lymphocytes, this panel includes CD4+ T helper, Treg cells, and CD8+ cytotoxic T cells. Further T cells subsets are included with special focus on invariant T cells: γδ T cells (including δ2TCR variant), invariant NKT cells and MAIT (mucosal-associated invariant T cells) cells. Additionally, total B cells (including Bregs and plasmocytes), NK cells, and NKT cells are included. For the overall check of activation status of the analyzed immune cells we used HLA-DR, CD38, CD57, CD69, PD-1, and CD94. In addition, we used CD62L, CD45RA, CD27, and CD39 to describe the differentiation status of these cells. The panel was designed to maximize the information that can be obtained from surface markers in order to avoid the need for fixation and permeabilization steps. The presented multimarker panel offers the possibility to discover new immune cell subtypes which in patients and in cohort studies may lead to the identification of altered immune phenotypes and might give a link to immune system based or to certain other diseases. This panel was developed for a full spectrum flow cytometer equipped with a minimum of three lasers. We developed this panel using healthy human fresh blood, however it was also successfully used for staining of isolated human peripheral blood mononuclear cells (PBMC).

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.

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.

Application of single-cell transcriptomics to kinetoplastid research

Kinetoplastid parasites are responsible for both human and animal diseases across the globe where they have a great impact on health and economic well-being. Many species and life cycle stages are difficult to study due to limitations in isolation and culture, as well as to their existence as heterogeneous populations in hosts and vectors. Single-cell transcriptomics (scRNA-seq) has the capacity to overcome many of these difficulties, and can be leveraged to disentangle heterogeneous populations, highlight genes crucial for propagation through the life cycle, and enable detailed analysis of host–parasite interactions. Here, we provide a review of studies that have applied scRNA-seq to protozoan parasites so far. In addition, we provide an overview of sample preparation and technology choice considerations when planning scRNA-seq experiments, as well as challenges faced when analysing the large amounts of data generated. Finally, we highlight areas of kinetoplastid research that could benefit from scRNA-seq technologies.

A novel evaluation method for Ki-67 immunostaining in paraffin-embedded tissues

The Ki-67 labeling index is traditionally used to investigate tumor aggressiveness. However, no diagnostic or prognostic value has been associated to the heterogeneous pattern of nuclear positivity. The aims of this study were to develop a classification for the patterns of Ki-67-positive nuclei; to search scientific evidence for the Ki-67 expression and location throughout the cell cycle; and to develop a protocol to apply the classification of patterns of Ki-67-positive nuclei in squamous epithelium with different proliferative activities. Based on empirical observation of paraffin sections submitted to immunohistochemistry for the determination of Ki-67 labeling index and literature review about Ki-67 expression, we created a classification of the patterns of nuclear positivity (NP1, NP2, NP3, NP4, and mitosis). A semi-automatic protocol was developed to identify and quantify the Ki-67 immunostaining patterns in target tissues. Two observers evaluated 7000 nuclei twice to test the intraobserver reliability, and six evaluated 1000 nuclei to the interobserver evaluation. The results showed that the immunohistochemical patterns of Ki-67 are similar in the tumoral and non-tumoral epithelium and were classified without difficulty. There was a high intraobserver reliability (Spearman correlation coefficient > 0.9) and moderate interobserver agreement (k = 0.523). Statistical analysis showed that non-malignant epithelial specimens presented a higher number of NP1 (geographic tongue = 83.8 ± 21.8; no lesion = 107.6 ± 52.7; and mild dysplasia = 86.6 ± 25.8) when compared to carcinoma in Situ (46.8 ± 34.8) and invasive carcinoma (72.6 ± 37.9). The statistical evaluation showed significant difference (p < 0.05). Thus, we propose a new way to evaluate Ki-67, where the pattern of its expression may be associated with the dynamics of the cell cycle. Future proof of this association will validate the use of the classification for its possible impact on cancer prognosis and guidance on personalized therapy.

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.

Double emulsion flow cytometry with high-throughput single droplet isolation and nucleic acid recovery

Droplet microfluidics has made large impacts in diverse areas such as enzyme evolution, chemical product screening, polymer engineering, and single-cell analysis. However, while droplet reactions have become increasingly sophisticated, phenotyping droplets by a fluorescent signal and sorting them to isolate individual variants-of-interest at high-throughput remains challenging. Here, we present sdDE-FACS (s[combining low line]ingle d[combining low line]roplet D[combining low line]ouble E[combining low line]mulsion-FACS), a new method that uses a standard flow cytometer to phenotype, select, and isolate individual double emulsion droplets of interest. Using a 130 μm nozzle at high sort frequency (12-14 kHz), we demonstrate detection of droplet fluorescence signals with a dynamic range spanning 5 orders of magnitude and robust post-sort recovery of intact double emulsion (DE) droplets using 2 commercially-available FACS instruments. We report the first demonstration of single double emulsion droplet isolation with post-sort recovery efficiencies >70%, equivalent to the capabilities of single-cell FACS. Finally, we establish complete downstream recovery of nucleic acids from single, sorted double emulsion droplets via qPCR with little to no cross-contamination. sdDE-FACS marries the full power of droplet microfluidics with flow cytometry to enable a variety of new droplet assays, including rare variant isolation and multiparameter single-cell analysis.

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

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

OMIP-060: 30-Parameter Flow Cytometry Panel to Assess T Cell Effector Functions and Regulatory T Cells

We developed this comprehensive 28-color flow cytometry panel with the aim to measure a variety of T cell effector functions in combination with T cell differentiation markers (CCR7, CD27, CD28, CD45RO, CD95) in γδ T cells and CD4⁺ and CD8⁺ αβ T cells (Table 1). The effector functions measured in this panel include activation and co-stimulatory molecules (CD69, CD137, and CD154), cytokines (IL-2, IL-13, IL-17A, IL-21, IL-22, TNF, and IFNγ), the chemokine IL-8, cytotoxic molecules (perforin and granzyme B), and the degranulation marker CD107a. In addition, Ki67 enables the identification and analysis of recently activated T cells. To characterize regulatory T cells (T_regs ), we included CD25, CD39, and the canonical T_regs transcription factor FoxP3. We developed and optimized this panel for cryopreserved human peripheral blood mononuclear cells (PBMC) and stimulation with phorbol 12-myristate 13-acetate (PMA) and ionomycin. However, we successfully tested other types of stimulation such as staphylococcus enterotoxin B (SEB) or a mix of immunodominant peptides (CEF peptide pool) from cytomegalovirus (CMV), Epstein-Barr virus (EBV) and influenza. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.

High-Parameter Single-Cell Analysis

Thousands of transcripts and proteins confer function and discriminate cell types in the body. Using high-parameter technologies, we can now measure many of these markers at once, and multiple platforms are now capable of analysis on a cell-by-cell basis. Three high-parameter single-cell technologies have particular potential for discovering new biomarkers, revealing disease mechanisms, and increasing our fundamental understanding of cell biology. We review these three platforms (high-parameter flow cytometry, mass cytometry, and a new class of technologies called integrated molecular cytometry platforms) in this article. We describe the underlying hardware and instrumentation, the reagents involved, and the limitations and advantages of each platform. We also highlight the emerging field of high-parameter single-cell data analysis, providing an accessible overview of the data analysis process and choice of tools.

Immunophenotyping of Tissue Samples Using Multicolor Flow Cytometry

Flow cytometry enables the measurement of single cells in a flowing system. Heterogeneous mixtures of cells or particles can be analyzed with respect to their morphology, surface and intracellular protein expression, DNA content, and cellular physiology at high speed and purity. A series of key technical developments and improvements in flow cytometry hardware, software, and dye chemistry made it possible to measure more than 20 parameters simultaneously. Here, we provide a stepwise protocol for the preparation of single cell suspension samples from different murine lymphoid or tumor tissues and a detailed description of a 17-color polychromatic flow cytometry analysis of tumor-infiltrating leukocytes.

CytoBinning: Immunological insights from multi-dimensional data

New cytometric techniques continue to push the boundaries of multi-parameter quantitative data acquisition at the single-cell level particularly in immunology and medicine. Sophisticated analysis methods for such ever higher dimensional datasets are rapidly emerging, with advanced data representations and dimensional reduction approaches. However, these are not yet standardized and clinical scientists and cell biologists are not yet experienced in their interpretation. More fundamentally their range of statistical validity is not yet fully established. We therefore propose a new method for the automated and unbiased analysis of high-dimensional single cell datasets that is simple and robust, with the goal of reducing this complex information into a familiar 2D scatter plot representation that is of immediate utility to a range of biomedical and clinical settings. Using publicly available flow cytometry and mass cytometry datasets we demonstrate that this method (termed CytoBinning), recapitulates the results of traditional manual cytometric analyses and leads to new and testable hypotheses.

Methods for Measuring T-Cell Memory to Vaccination: From Mouse to Man

The development of effective vaccines continues to be a key goal for public health bodies, governments, funding bodies and pharmaceutical companies. With new vaccines such as Shingrix targeting Shingles and Bexsero for Meningitis B, licensed in recent years, today's population can be protected from more infectious diseases than ever before. Despite this, we are yet to license vaccines for some of the deadliest endemic diseases affecting children, such as malaria. In addition, the threat of epidemics caused by emerging pathogens is very real as exemplified by the 2014⁻2016 Ebola outbreak. Most licensed vaccines provide efficacy through humoral immunity and correlates of protection often quantify neutralising antibody titre. The role of T-cells in vaccine efficacy is less well understood and more complex to quantify. Defining T-cell responses which afford protection also remains a challenge, although more sophisticated assays for assessing cell-mediated immunity with the potential for higher throughput and scalability are now available and warrant review. Here we discuss the benefits of multiparameter cytokine analysis and omics approaches compared with flow cytometric and ELISpot assays. We also review technical challenges unique to clinical trial studies, including assay validation across laboratories and availability of sample type. Measuring T-cell immunogenicity alongside humoral responses provides information on the breadth of immune responses induced by vaccination. Accurately enumerating and phenotyping T-cell immunogenicity to vaccination is key for the determination of immune correlates of protection. However, identifying such T-cell parameters remains challenging without a clear understanding of the immunological mechanisms by which a T-cell-mediated response induces protection.

Blood-based analyses of cancer: Circulating myeloid-derived suppressor cells - is a new era coming?

Progress in cancer treatment made by the beginning of the 21st century has shifted the paradigm from one-size-fits-all to tailor-made treatment. The popular vision, to study solid tumors through the relatively noninvasive sampling of blood, is one of the most thrilling and rapidly advancing fields in global cancer diagnostics. From this perspective, immune-cell analysis in cancer could play a pivotal role in oncology practice. This approach is driven both by rapid technological developments, including the analysis of circulating myeloid-derived suppressor cells (cMDSCs), and by the increasing application of (immune) therapies, the success or failure of which may depend on effective and timely measurements of relevant biomarkers. Although the implementation of these powerful noninvasive diagnostic capabilities in guiding precision cancer treatment is poised to change the ways in which we select and monitor cancer therapy, challenges remain. Here, we discuss the challenges associated with the analysis and clinical aspects of cMDSCs and assess whether the problems in implementing tumor-evolution monitoring as a global tool in personalized oncology can be overcome.

Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry

The advent of mass cytometry increased the number of parameters measured at the single-cell level while decreasing the extent of crosstalk between channels relative to dye-based flow cytometry. Although reduced, spillover still exists in mass cytometry data, and minimizing its effect requires considerable expert knowledge and substantial experimental effort. Here, we describe a novel bead-based compensation workflow and R-based software that estimates and corrects for interference between channels. We performed an in-depth characterization of the spillover properties in mass cytometry, including limitations defined by the linear range of the mass cytometer and the reproducibility of the spillover over time and across machines. We demonstrated the utility of our method in suspension and imaging mass cytometry. To conclude, our approach greatly simplifies the development of new antibody panels, increases flexibility for antibody-metal pairing, opens the way to using less pure isotopes, and improves overall data quality, thereby reducing the risk of reporting cell phenotype artifacts.

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Signal spillover can impact quality of mass cytometry data

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Spillover can be corrected by compensation throughout the linear range of the CyTOF

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Compensation enables signal correction and data structure preservation

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CATALYST is a new R package and a web tool to estimate and correct for spillover

Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is ("Isolate-Inactivate-Inject") Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview

Vaccines are public health interventions aimed at preventing infections-related mortality, morbidity, and disability. While vaccines have been successfully designed for those infectious diseases preventable by preexisting neutralizing specific antibodies, for other communicable diseases, additional immunological mechanisms should be elicited to achieve a full protection. “New vaccines” are particularly urgent in the nowadays society, in which economic growth, globalization, and immigration are leading to the emergence/reemergence of old and new infectious agents at the animal–human interface. Conventional vaccinology (the so-called “vaccinology 1.0”) was officially born in 1796 thanks to the contribution of Edward Jenner. Entering the twenty-first century, vaccinology has shifted from a classical discipline in which serendipity and the Pasteurian principle of the three Is (isolate, inactivate, and inject) played a major role to a science, characterized by a rational design and plan (“vaccinology 3.0”). This shift has been possible thanks to Big Data, characterized by different dimensions, such as high volume, velocity, and variety of data. Big Data sources include new cutting-edge, high-throughput technologies, electronic registries, social media, and social networks, among others. The current mini-review aims at exploring the potential roles as well as pitfalls and challenges of Big Data in shaping the future vaccinology, moving toward a tailored and personalized vaccine design and administration.

High-Dimensional Fluorescence Cytometry

The immune system consists of a complex network of cells, all expressing a wide range of surface and/or intracellular proteins. Using flow cytometry, these cells can be analyzed by labeling with fluorophore-conjugated antibodies. The recent expansion of fluorescence flow cytometry technology, in conjunction with the ever-expanding understanding of the complexity of the immune system, has led to the generation of larger high-dimensional fluorescence flow cytometry panels. However, as panel size and complexity increases, so too does the difficulty involved in constructing high-quality panels, in addition to the challenges of analyzing such high-dimensional datasets. As such, this unit seeks to review the key principles involved in building high-dimensional panels, as well as to guide users through the process of building and analyzing quality panels. Here, cytometer configuration, fluorophore brightness, spreading error, antigen density, choosing the best conjugates, titration, optimization, and data analysis will all be addressed. © 2017 by John Wiley & Sons, Inc.

Application and utility of mass cytometry in vaccine development

Mass cytometry enables highly multiplexed profiling of cellular immune responses in limited-volume samples, advancing prospects of a new era of systems immunology. The capabilities of mass cytometry offer expanded potential for deciphering immune responses to infectious diseases and to vaccines. Several studies have used mass cytometry to profile protective immune responses, both postinfection and postvaccination, although no vaccine-development program has yet systematically employed the technology from the outset to inform both candidate design and clinical evaluation. In this article, we review published mass cytometry studies relevant to vaccine development, briefly compare immune profiling by mass cytometry to other systems-level technologies, and discuss some general considerations for deploying mass cytometry in the context of vaccine development.-Reeves, P. M., Sluder, A. E., Raju Paul, S., Scholzen, A., Kashiwagi, S., Poznansky, M. C. Application and utility of mass cytometry in vaccine development.

Targeted reconstruction of T cell receptor sequence from single cell RNA-seq links CDR3 length to T cell differentiation state

The T cell compartment must contain diversity in both T cell receptor (TCR) repertoire and cell state to provide effective immunity against pathogens. However, it remains unclear how differences in the TCR contribute to heterogeneity in T cell state. Single cell RNA-sequencing (scRNA-seq) can allow simultaneous measurement of TCR sequence and global transcriptional profile from single cells. However, current methods for TCR inference from scRNA-seq are limited in their sensitivity and require long sequencing reads, thus increasing the cost and decreasing the number of cells that can be feasibly analyzed. Here we present TRAPeS, a publicly available tool that can efficiently extract TCR sequence information from short-read scRNA-seq libraries. We apply it to investigate heterogeneity in the CD8⁺ T cell response in humans and mice, and show that it is accurate and more sensitive than existing approaches. Coupling TRAPeS with transcriptome analysis of CD8⁺ T cells specific for a single epitope from Yellow Fever Virus (YFV), we show that the recently described ‘naive-like’ memory population have significantly longer CDR3 regions and greater divergence from germline sequence than do effector-memory phenotype cells. This suggests that TCR usage is associated with the differentiation state of the CD8⁺ T cell response to YFV.

Blue intensity matters for cell cycle profiling in fluorescence DAPI-stained images

In the past decades, there has been an amazing progress in the understanding of the molecular mechanisms of the cell cycle. This has been possible largely due to a better conceptualization of the cycle itself, but also as a consequence of technological advances. Herein, we propose a new fluorescence image-based framework targeted at the identification and segmentation of stained nuclei with the purpose to determine DNA content in distinct cell cycle stages. The method is based on discriminative features, such as total intensity and area, retrieved from in situ stained nuclei by fluorescence microscopy, allowing the determination of the cell cycle phase of both single and sub-population of cells. The analysis framework was built on a modified k-means clustering strategy and refined with a Gaussian mixture model classifier, which enabled the definition of highly accurate classification clusters corresponding to G1, S and G2 phases. Using the information retrieved from area and fluorescence total intensity, the modified k-means (k=3) cluster imaging framework classified 64.7% of the imaged nuclei, as being at G1 phase, 12.0% at G2 phase and 23.2% at S phase. Performance of the imaging framework was ascertained with normal murine mammary gland cells constitutively expressing the Fucci2 technology, exhibiting an overall sensitivity of 94.0%. Further, the results indicate that the imaging framework has a robust capacity to both identify a given DAPI-stained nucleus to its correct cell cycle phase, as well as to determine, with very high probability, true negatives. Importantly, this novel imaging approach is a non-disruptive method that allows an integrative and simultaneous quantitative analysis of molecular and morphological parameters, thus awarding the possibility of cell cycle profiling in cytological and histological samples.

A Perspective on the Role of Computational Models in Immunology

This is an exciting time for immunology because the future promises to be replete with exciting new discoveries that can be translated to improve health and treat disease in novel ways. Immunologists are attempting to answer increasingly complex questions concerning phenomena that range from the genetic, molecular, and cellular scales to that of organs, whole animals or humans, and populations of humans and pathogens. An important goal is to understand how the many different components involved interact with each other within and across these scales for immune responses to emerge, and how aberrant regulation of these processes causes disease. To aid this quest, large amounts of data can be collected using high-throughput instrumentation. The nonlinear, cooperative, and stochastic character of the interactions between components of the immune system as well as the overwhelming amounts of data can make it difficult to intuit patterns in the data or a mechanistic understanding of the phenomena being studied. Computational models are increasingly important in confronting and overcoming these challenges. I first describe an iterative paradigm of research that integrates laboratory experiments, clinical data, computational inference, and mechanistic computational models. I then illustrate this paradigm with a few examples from the recent literature that make vivid the power of bringing together diverse types of computational models with experimental and clinical studies to fruitfully interrogate the immune system.

Human immune system variation

The human immune system is highly variable between individuals but relatively stable over time within a given person. Recent conceptual and technological advances have enabled systems immunology analyses, which reveal the composition of immune cells and proteins in populations of healthy individuals. The range of variation and some specific influences that shape an individual's immune system is now becoming clearer. Human immune systems vary as a consequence of heritable and non-heritable influences, but symbiotic and pathogenic microbes and other non-heritable influences explain most of this variation. Understanding when and how such influences shape the human immune system is key for defining metrics of immunological health and understanding the risk of immune-mediated and infectious diseases.

Standardization and quality control for high-dimensional mass cytometry studies of human samples

Mass cytometry (CyTOF), a mass spectrometry-based single cell phenotyping technology, allows utilization of over 35 antibodies in a single sample and is a promising tool for translational human immunology studies. Although several analysis tools are available to interpret the complex data sets generated, a robust method for standardization and quality control within and across studies is needed. Here we report an efficient and easily adaptable method to monitor quality of individual samples in human immunology studies and to facilitate reproducible data analysis. Samples to be assessed are spiked with a defined amount of reference peripheral blood mononuclear cells from a healthy donor, derived from a single large blood draw. The presence of known standardized numbers and phenotypic profiles of these reference cells greatly facilitates sample analysis by allowing for: 1) quality control for consistent staining of each antibody in the panel, 2) identification of potential batch effects, and 3) implementation of a robust gating strategy. We demonstrate the utility of this method using peripheral blood and bronchoalveolar lavage samples from HIV⁺ patients by characterizing their CD8⁺ T-cell phenotypes and cytokine expression, respectively. Our results indicate that this method allows quality control of experimental conditions and results in highly reproducible population frequencies through a robust gating strategy. © 2016 International Society for Advancement of Cytometry.

Advancing haematopoietic stem and progenitor cell biology through single-cell profiling

Haematopoietic stem and progenitor cells (HSPCs) sit at the top of the haematopoietic hierarchy, and their fate choices need to be carefully controlled to ensure balanced production of all mature blood cell types. As cell fate decisions are made at the level of the individual cells, recent technological advances in measuring gene and protein expression in increasingly large numbers of single cells have been rapidly adopted to study both normal and pathological HSPC function. In this review we emphasise the importance of combining the correct computational models with single-cell experimental techniques, and illustrate how such integrated approaches have been used to resolve heterogeneities in populations, reconstruct lineage differentiation, identify regulatory relationships and link molecular profiling to cellular function.

Analysis of cell-mediated immune responses in support of dengue vaccine development efforts

Dengue vaccine development has made significant strides, but a better understanding of how vaccine-induced immune responses correlate with vaccine efficacy can greatly accelerate development, testing, and deployment as well as ameliorate potential risks and safety concerns. Advances in basic immunology knowledge and techniques have already improved our understanding of cell-mediated immunity of natural dengue virus infection and vaccination. We conclude that the evidence base is adequate to argue for inclusion of assessments of cell-mediated immunity as part of clinical trials of dengue vaccines, although further research to identify useful correlates of protective immunity is needed.

Detecting Antigen-Specific T Cell Responses: From Bulk Populations to Single Cells

A new generation of sensitive T cell-based assays facilitates the direct quantitation and characterization of antigen-specific T cell responses. Single-cell analyses have focused on measuring the quality and breadth of a response. Accumulating data from these studies demonstrate that there is considerable, previously-unrecognized, heterogeneity. Standard assays, such as the ICS, are often insufficient for characterization of rare subsets of cells. Enhanced flow cytometry with imaging capabilities enables the determination of cell morphology, as well as the spatial localization of the protein molecules within a single cell. Advances in both microfluidics and digital PCR have improved the efficiency of single-cell sorting and allowed multiplexed gene detection at the single-cell level. Delving further into the transcriptome of single-cells using RNA-seq is likely to reveal the fine-specificity of cellular events such as alternative splicing (i.e., splice variants) and allele-specific expression, and will also define the roles of new genes. Finally, detailed analysis of clonally related antigen-specific T cells using single-cell TCR RNA-seq will provide information on pathways of differentiation of memory T cells. With these state of the art technologies the transcriptomics and genomics of Ag-specific T cells can be more definitively elucidated.