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.

Cheng Y, Newell EW. | Adv Immunol. 131, 101 (2016)

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.

J. Immunol 2016 | Cheng et al

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.

Sumatoh et al | Cytometry Part A 2016

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.

Wong MT, et al. | Cell Reports 2015

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.

Becher B, et al. | Nat Immunol. 2014