Publications
Multiplex peptide-MHC tetramer staining using mass cytometry for deep analysis of the influenza-specific T-cell response in mice
Antigen-specific T cells play a crucial role for the host protective immunity against viruses and other diseases. The use of mass cytometry together with a combinatorial multiplex tetramer staining has successfully been applied for probing and characterization of multiple antigen-specific CD8+ T cells in human blood samples. The present study shows that this approach can also be used to rapidly assess the magnitude of influenza-specific CD8+ T cell epitope dominance across lymph nodes and lungs in a murine model of a highly pathological influenza infection. Moreover, we show feasibility of extending this approach to include concurrent identification of virus-specific CD4+ T cells. By using a double coding approach, we probed for five influenza-specific MHCI-peptide complexes as well as one influenza-specific MHCII-peptide complex in the presence of irrelevant control peptides and show that this approach is capable of tracking antigen-specific T cells across individual lymph nodes and lungs. The simultaneous staining with 26 surface maker molecules further facilitated an in-depth characterization of T cells reacting with influenza epitopes and revealed tissue specific phenotypic differences between CD4+ T cells targeting the same pathogenic epitope. In conclusion, this approach provides the possibility for a rapid and comprehensive analysis of antigen-specific CD8+ and CD4+ T cells in different disease settings that might be advantageous for subsequent vaccine formulation strategies.
Human Innate Lymphoid Cell Subsets Possess Tissue-Type Based Heterogeneity in Phenotype and Frequency
Animal models have highlighted the importance of innate lymphoid cells (ILCs) in multiple immune responses. However, technical limitations have hampered adequate characterization of ILCs in humans. Here, we used mass cytometry including a broad range of surface markers and transcription factors to accurately identify and profile ILCs across healthy and inflamed tissue types. High dimensional analysis allowed for clear phenotypic delineation of ILC2 and ILC3 subsets. We were not able to detect ILC1 cells in any of the tissues assessed, however, we identified intra-epithelial (ie)ILC1-like cells that represent a broader category of NK cells in mucosal and non-mucosal pathological tissues. In addition, we have revealed the expression of phenotypic molecules that have not been previously described for ILCs. Our analysis shows that human ILCs are highly heterogeneous cell types between individuals and tissues. It also provides a global, comprehensive, and detailed description of ILC heterogeneity in humans across patients and tissues.
Checkpoint blockade immunotherapy reshapes the high-dimensional phenotypic heterogeneity of murine intratumoural neoantigen-specific CD8+ T cells
The analysis of neoantigen-specific CD8+ T cells in tumour-bearing individuals is challenging due to the small pool of tumour antigen-specific T cells. Here we show that mass cytometry with multiplex combinatorial tetramer staining can identify and characterize neoantigen-specific CD8+ T cells in mice bearing T3 methylcholanthrene-induced sarcomas that are susceptible to checkpoint blockade immunotherapy. Among 81 candidate antigens tested, we identify T cells restricted to two known neoantigens simultaneously in tumours, spleens and lymph nodes in tumour-bearing mice. High-dimensional phenotypic profiling reveals that antigen-specific, tumour-infiltrating T cells are highly heterogeneous. We further show that neoantigen-specific T cells display a different phenotypic profile in mice treated with anti-CTLA-4 or anti-PD-1 immunotherapy, whereas their peripheral counterparts are not affected by the treatments. Our results provide insights into the nature of neoantigen-specific T cells and the effects of checkpoint blockade immunotherapy.
A High-Dimensional Atlas of Human T Cell Diversity Reveals Tissue-Specific Trafficking and Cytokine Signatures.
Depending on the tissue microenvironment, T cells can differentiate into highly diverse subsets expressing unique trafficking receptors and cytokines. Studies of human lymphocytes have primarily focused on a limited number of parameters in blood, representing an incomplete view of the human immune system. Here, we have utilized mass cytometry to simultaneously analyze T cell trafficking and functional markers across eight different human tissues, including blood, lymphoid, and non-lymphoid tissues. These data have revealed that combinatorial expression of trafficking receptors and cytokines better defines tissue specificity. Notably, we identified numerous T helper cell subsets with overlapping cytokine expression, but only specific cytokine combinations are secreted regardless of tissue type. This indicates that T cell lineages defined in mouse models cannot be clearly distinguished in humans. Overall, our data uncover a plethora of tissue immune signatures and provide a systemic map of how T cell phenotypes are altered throughout the human body.
Mass cytometry: blessed with the curse of dimensionality
Immunologists are being compelled to develop new high-dimensional perspectives of cellular heterogeneity and to determine which applications best exploit the power of mass cytometry and associated multiplex approaches.
Deep Profiling Human T Cell Heterogeneity by Mass Cytometry.
Advances of mass cytometry and high-dimensional single-cell data analysis have brought cellular immunological research into a new generation. By coupling these two powerful technology platforms, immunologists now have more tools to resolve the tremendous diversity of immune cell subsets, and their heterogeneous functionality. Since the first introduction of mass cytometry, many reports have been published using this novel technology to study a range of cell types. At the outset, studies of human hematopoietic stem cell and peripheral CD8(+) T cells using mass cytometry have shad the light of future experimental approach in interrogating immune cell phenotypic and functional diversity. Here, we briefly revisit the past and present understanding of T cell heterogeneity, and the technologies that facilitate this knowledge. In addition, we review the current progress of mass cytometry and high-dimensional cytometric analysis, including the methodology, panel design, experimental procedure, and choice of computational algorithms with a special focus on their utility in exploration of human T cell immunology.
Categorical Analysis of Human T Cell Heterogeneity with One-Dimensional Soli-Expression by Nonlinear Stochastic Embedding.
Rapid progress in single-cell analysis methods allow for exploration of cellular diversity at unprecedented depth and throughput. Visualizing and understanding these large, high-dimensional datasets poses a major analytical challenge. Mass cytometry allows for simultaneous measurement of >40 different proteins, permitting in-depth analysis of multiple aspects of cellular diversity. In this article, we present one-dimensional soli-expression by nonlinear stochastic embedding (One-SENSE), a dimensionality reduction method based on the t-distributed stochastic neighbor embedding (t-SNE) algorithm, for categorical analysis of mass cytometry data. With One-SENSE, measured parameters are grouped into predefined categories, and cells are projected onto a space composed of one dimension for each category. In contrast with higher-dimensional t-SNE, each dimension (plot axis) in One-SENSE has biological meaning that can be easily annotated with binned heat plots. We applied One-SENSE to probe relationships between categories of human T cell phenotypes and observed previously unappreciated cellular populations within an orchestrated view of immune cell diversity. The presentation of high-dimensional cytometric data using One-SENSE showed a significant improvement in distinguished T cell diversity compared with the original t-SNE algorithm and could be useful for any high-dimensional dataset.
Optimization of Mass Cytometry Sample Cryopreservation After Staining
The advent of mass cytometry has facilitated highly multi‐parametric single‐cell analysis allowing for the deep assessment of cellular diversity. While the data and analytical power of this approach are well described, associated technical and experimental hurdles remain. Issues like equipment breakdown and sampling of large‐scale batches, which may require multiple days of data acquisition, are minor but critical obstacles that prompt a technical solution, especially when dealing with precious samples. An ability to cryopreserve mass cytometry samples that have already been stained would alleviate numerous technical limitations we face with currently used sample‐handling approaches. Here, we evaluated two protocols for freezing of already‐stained and fixed cellular samples and compared them with standard sample refrigeration in staining buffer. A comprehensive human T cell staining phenotypic and functional profiling panel was used and the signal intensity and reliability of each marker was assessed over a 4‐week period. In general, cellular viability, DNA Ir‐Intercalator and barcode staining were minimally affected by freezing compared to refrigeration, and the signal intensities for cell surface markers and receptors were not compromised. Intracellular cytokine staining did show some decreases in signal intensity after freezing, with the decreases more prominent in a methanol‐based protocol compared to a protocol involving the use of 10% DMSO in FBS. We conclude that freezing already‐stained samples suspended in 10% DMSO in FBS is practical and efficient way to preserve already‐stained samples when needed. © 2016 International Society for Advancement of Cytometry.
Mapping the Diversity of Follicular Helper T Cells in Human Blood and Tonsils Using High-Dimensional Mass Cytometry Analysis.
Single-cell analysis technologies such as mass cytometry allow for measurements of cellular heterogeneity with unprecedented dimensionality. Here, we applied dimensionality reduction and automated clustering methods on human T helper (T(H)) cells derived from peripheral blood and tonsils, which showed differential cell composition and extensive T(H) cell heterogeneity. Notably, this analysis revealed numerous subtypes of follicular helper T (T(FH)) cells that followed a continuum spanning both blood and tonsils. Furthermore, we identified tonsillar CXCR5(lo)PD-1(lo)CCR7(lo) T(FH) cells expressing interferon-γ (IFN-γ), interleukin-17 (IL-17), or Foxp3, indicating that T(FH) cells exhibit diverse functional capacities within extrafollicular stages. Regression analysis demonstrated that CXCR5(lo)PD-1(-) and CXCR5(lo)PD-1(lo) cells accumulate during childhood in secondary lymphoid organs, supporting previous findings that these subsets represent memory T(FH) cells. This study provides an in-depth comparison of human blood and tonsillar T(FH) cells and outlines a general approach for subset discovery and hypothesizing of cellular progressions.
High-dimensional analysis of the murine myeloid cell system.
Advances in cell-fate mapping have revealed the complexity in phenotype, ontogeny and tissue distribution of the mammalian myeloid system. To capture this phenotypic diversity, we developed a 38-antibody panel for mass cytometry and used dimensionality reduction with machine learning-aided cluster analysis to build a composite of murine (mouse) myeloid cells in the steady state across lymphoid and nonlymphoid tissues. In addition to identifying all previously described myeloid populations, higher-order analysis allowed objective delineation of otherwise ambiguous subsets, including monocyte-macrophage intermediates and an array of granulocyte variants. Using mice that cannot sense granulocyte macrophage-colony stimulating factor GM-CSF (Csf2rb(-/-)), which have discrete alterations in myeloid development, we confirmed differences in barrier tissue dendritic cells, lung macrophages and eosinophils. The methodology further identified variations in the monocyte and innate lymphoid cell compartment that were unexpected, which confirmed that this approach is a powerful tool for unambiguous and unbiased characterization of the myeloid system.