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Mass-tag cell barcoding has increased the throughput, multiplexing, and robustness of multiple cytometry approaches. Previously, we adapted mass cytometry for cells to analyze synaptosome preparations (mass synaptometry or SynTOF), extending mass cytometry to these smaller, anuclear particles. To improve throughput and individual event resolution, we report here the application of palladium-based barcoding in human synaptosomes. Up to 20 individual samples, each with a unique combinatorial barcode, were pooled for labeling with an antibody cocktail. Our synaptosome protocol used six palladium-based barcoding reagents, and in combination with sequential gating increased the identification of presynaptic events approximately 4-fold. These same parameters also efficiently resolved two other anuclear particles: human red blood cells (RBCs) and platelets. The addition of palladium-based mass-tag barcoding to our approach improves mass cytometry of synaptic particles.

Alzheimer’s disease (AD) differentially and specifically affects brain regions and neuronal cell types in a predictable pattern. Damage to the brain appears to spread and worsens with time, taking over more regions and activating multiple stressors that can converge to promote vulnerability of certain cell types. At the same time, other cell types and brain regions remain intact in the face of this onslaught of neuropathology. Although neuropathologic descriptions of AD have been extensively expanded and mapped over the last several decades, our understanding of the mechanisms underlying how certain regions and cell populations are specifically vulnerable or resistant has lagged behind. In this review, we detail what is known about the selectivity of local initiation of AD pathology in the hippocampus, its proposed spread via synaptic connections, and the diversity of clinical phenotypes and brain atrophy patterns that may arise from different fibrillar strains of pathologic proteins or genetic predispositions. We summarize accumulated and emerging knowledge of the cellular and molecular basis for neuroanatomic selectivity, consider potential disease-relevant differences between vulnerable and resistant neuronal cell types and isolate molecular markers to identify them.

Peripheral immune responses of Alzheimer’s disease patients are uniquely different from those of healthy and disease controls., Peripheral blood mononuclear cells (PBMCs) may provide insight into the pathogenesis of Alzheimer’s disease (AD) or Parkinson’s disease (PD). We investigated PBMC samples from 132 well-characterized research participants using seven canonical immune stimulants, mass cytometric identification of 35 PBMC subsets, and single-cell quantification of 15 intracellular signaling markers, followed by machine learning model development to increase predictive power. From these, three main intracellular signaling pathways were identified specifically in PBMC subsets from people with AD versus controls: reduced activation of PLCγ2 across many cell types and stimulations and selectively variable activation of STAT1 and STAT5, depending on stimulant and cell type. Our findings functionally buttress the now multiply-validated observation that a rare coding variant in PLCG2 is associated with a decreased risk of AD. Together, these data suggest enhanced PLCγ2 activity as a potential new therapeutic target for AD with a readily accessible pharmacodynamic biomarker.

SummaryCellular metabolism regulates immune cell activation, differentiation and effector functions to the extent that its perturbation can augment immune responses. However, the analytical technologies available to study cellular metabolism lack single-cell resolution, obscuring metabolic heterogeneity and its connection to immune phenotype and function. To that end, we utilized high-dimensional, antibody-based technologies to simultaneously quantify the single-cell metabolic regulome in combination with phenotypic identity. Mass cytometry (CyTOF)-based application of this approach to early human T cell activation enabled the comprehensive reconstruction of the coordinated metabolic remodeling of naïve CD8+T cells and aligned with conventional bulk assays for glycolysis and oxidative phosphorylation. Extending this analysis to a variety of tissue-resident immune cells revealed tissue-restricted metabolic states of human cytotoxic T cells, including metabolically repressed subsets that expressed CD39 and PD1 and that were enriched in colorectal carcinoma versus healthy adjacent tissue. Finally, combining this approach with multiplexed ion beam imaging by time-of-flight (MIBI-TOF) demonstrated the existence of spatially enriched metabolic neighborhoods, independent of cell identity and additionally revealed exclusion of metabolically repressed cytotoxic T cell states from the tumor-immune boundary in human colorectal carcinoma. Overall, we provide an approach that permits the robust approximation of metabolic states in individual cells along with multimodal analysis of cell identity and functional characteristics that can be applied to human clinical samples to study cellular metabolism how it may be perturbed to affect immunological outcomes.

Cytokine dysregulation is a central driver of chronic inflammatory diseases such as multiple sclerosis (MS). Here, we sought to determine the characteristic cellular and cytokine polarization profile in patients with relapsing-remitting multiple sclerosis (RRMS) by high-dimensional single-cell mass cytometry (CyTOF). Using a combination of neural network-based representation learning algorithms, we identified an expanded T helper cell subset in patients with MS, characterized by the expression of granulocyte-macrophage colony-stimulating factor and the C-X-C chemokine receptor type 4. This cellular signature, which includes expression of very late antigen 4 in peripheral blood, was also enriched in the central nervous system of patients with relapsing-remitting multiple sclerosis. In independent validation cohorts, we confirmed that this cell population is increased in patients with MS compared with other inflammatory and non-inflammatory conditions. Lastly, we also found the population to be reduced under effective disease-modifying therapy, suggesting that the identified T cell profile represents a specific therapeutic target in MS.

The central nervous system (CNS) is under close surveillance by immune cells, which mediate tissue homeostasis, protection, and repair. Conversely, in neuroinflammation, dysregulated leukocyte invasion into the CNS leads to immunopathology and neurological disability. To invade the brain parenchyma, autoimmune encephalitogenic T helper (TH) cells must encounter their cognate antigens (Ags) presented via local Ag-presenting cells (APCs). The precise identity of the APC that samples, processes, and presents CNS-derived Ags to autoaggressive T cells is unknown. Here, we used a combination of high-dimensional single-cell mapping and conditional MHC class II ablation across all CNS APCs to systematically interrogate each population for its ability to reactivate encephalitogenic TH cells in vivo. We found a population of conventional dendritic cells, but not border-associated macrophages or microglia, to be essential for licensing T cells to initiate neuroinflammation.

Individual reports suggest that the central nervous system (CNS) contains multiple immune cell types with diverse roles in tissue homeostasis, immune defense, and neurological diseases. It has been challenging to map leukocytes across the entire brain, and in particular in pathology, where phenotypic changes and influx of blood-derived cells prevent a clear distinction between reactive leukocyte populations. Here, we applied high-dimensional single-cell mass and fluorescence cytometry, in parallel with genetic fate mapping systems, to identify, locate, and characterize multiple distinct immune populations within the mammalian CNS. Using this approach, we revealed that microglia, several subsets of border-associated macrophages and dendritic cells coexist in the CNS at steady state and exhibit disease-specific transformations in the immune microenvironment during aging and in models of Alzheimer's disease and multiple sclerosis. Together, these data and the described framework provide a resource for the study of disease mechanisms, potential biomarkers, and therapeutic targets in CNS disease.

Autoimmune diseases like multiple sclerosis (MS) develop from the activation and complex interactions of a wide network of immune cells, which penetrate the central nervous system (CNS) and cause tissue damage and neurological deficits. Experimental autoimmune encephalomyelitis (EAE) is a model used to study various aspects of MS, including the infiltration of autoaggressive T cells and pathogenic, inflammatory myeloid cells into the CNS. Various signature landscapes of immune cell infiltrates have proven useful in shedding light on the causes of specific EAE symptoms in transgenic mice. However, single cell analysis of these infiltrates has thus far been limited in conventional fluorescent flow cytometry methods by 14-16 parameter staining panels. With the advent of mass cytometry and metal-tagged antibodies, a staining panel of 35-45 parameters is now possible. With the aid of dimensionality reducing and clustering algorithms to visualize and analyze this high dimensional data, this allows for a more comprehensive picture of the different cell populations in an inflamed CNS, at a single cell resolution level. Here, we describe the induction of active EAE in C56BL/6 mice and, in particular, the staining of microglia and CNS invading immune cells for mass cytometry with subsequent data visualization and analysis.