Increasing evidence indicates the involvement of B cells in the pathogenesis of multiple sclerosis (MS), but their precise roles are unclear. In this Review, we provide an overview of the development and physiological functions of B cells and the main mechanisms through which B cells are thought to contribute to CNS autoimmunity. In MS, abnormalities of B cell function include pro-inflammatory cytokine production, defective B cell regulatory function and the formation of tertiary lymphoid-like structures in the CNS, which are the likely source of abnormal immunoglobulin production detectable in the cerebrospinal fluid. We also consider the hypothesis that Epstein-Barr virus (EBV) is involved in the B cell overactivation that leads to inflammatory injury to the CNS in MS. We also review the immunological effects - with a focus on the effects on B cell subsets - of several successful therapeutic approaches in MS, including agents that selectively deplete B cells (rituximab, ocrelizumab and ofatumumab), agents that less specifically deplete lymphocytes (alemtuzumab and cladribine) and autologous haematopoietic stem cell transplantation, in which the immune system is unselectively ablated and reconstituted. We consider the insights that these effects on B cell populations provide and their potential to further our understanding and targeting of B cells in MS.

B cells in multiple sclerosis - from targeted depletion to immune reconstitution therapies.

Mass cytometry enables the measurement of up to 50 features on single cell. This has catalyzed a shift toward multidimensional data analysis methods, rather than the manual gating strategies as traditionally for in flow cytometry data. This shift means that data scientists are involved in the analysis process to an increasing degree. As the data is analyzed in a more unbiased fashion, where noisy or uninformative observations are not easily excluded, a deeper knowledge of the origin, noise, and modalities of the data is therefore needed to embark on useful data analysis. In this primer, we introduce the idiosyncrasies of mass cytometry data with a focus on the technical properties of how data generated with the CyTOF® system, and the characteristics of protein expression in the cells of the hematopoietic continuum, specifically targeted toward data scientists. We also provide a comprehensive online repository of scripts, tutorials, and example data. © 2018 International Society for Advancement of Cytometry.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1002/cyto.a.23621

The anatomy of single cell mass cytometry data

Multiple myeloma (MM) is characterized by the uncontrolled proliferation of plasma cells. Despite recent treatment advances, it is still incurable as disease progression is not fully understood. To investigate MM and its immune environment, we apply single cell RNA and linked-read whole genome sequencing to profile 29 longitudinal samples at different disease stages from 14 patients. Here, we collect 17,267 plasma cells and 57,719 immune cells, discovering patient-specific plasma cell profiles and immune cell expression changes. Patients with the same genetic alterations tend to have both plasma cells and immune cells clustered together. By integrating bulk genomics and single cell mapping, we track plasma cell subpopulations across disease stages and find three patterns: stability (from precancer to diagnosis), and gain or loss (from diagnosis to relapse). In multiple patients, we detect "B cell-featured" plasma cell subpopulations that cluster closely with B cells, implicating their cell of origin. We validate AP-1 complex differential expression (JUN and FOS) in plasma cell subpopulations using CyTOF-based protein assays, and integrated analysis of single-cell RNA and CyTOF data reveals AP-1 downstream targets (IL6 and IL1B) potentially leading to inflammation regulation. Our work represents a longitudinal investigation for tumor and microenvironment during MM progression and paves the way for expanding treatment options.

/pdf/co-evolution-of-tumor-and-immune-cells-during-progression-of-rkzx449fyl.pdf

Co-evolution of tumor and immune cells during progression of multiple myeloma

Objective To assess functional changes in lymphocyte repertoire and subsequent clinical implications during delayed-release dimethyl fumarate (DMF) treatment in patients with multiple sclerosis. Methods Using peripheral blood from several clinical trials of DMF, immune cell subsets were quantified using flow cytometry. For some patients, lymphocyte counts were assessed after DMF discontinuation. Incidence of adverse events, including serious and opportunistic infections, was assessed. Results In DMF-treated patients, absolute lymphocyte counts (ALCs) demonstrated a pattern of decline followed by stabilization, which also was reflected in the global reduction in numbers of circulating functional lymphocyte subsets. The relative frequencies of circulating memory T- and B-cell populations declined and naive cells increased. No increased incidence of serious infection or malignancy was observed for patients treated with DMF, even when stratified by ALC or T-cell subset frequencies. For patients who discontinued DMF due to lymphopenia, ALCs increased after DMF discontinuation; recovery time varied by ALC level at discontinuation. T-cell subsets closely correlated with ALCs in both longitudinal and cross-sectional analyses. Conclusions DMF shifted the immunophenotype of circulating lymphocyte subsets. ALCs were closely correlated with CD4 + and CD8 + T-cell counts, indicating that lymphocyte subset monitoring is not required for safety vigilance. No increased risk of serious infection was observed in patients with low T-cell subset counts. Monitoring ALC remains the most effective way of identifying patients at risk of subsequently developing prolonged moderate to severe lymphopenia, a risk factor for progressive multifocal leukoencephalopathy in DMF-treated patients. Trial registration numbers EUDRA CT 2015-001973-42, NCT00168701, NCT00420212, NCT00451451, and NCT00835770.

https://n.neurology.org/content/neurology/92/15/e1724.full.pdf

Effect of dimethyl fumarate on lymphocytes in RRMS: Implications for clinical practice.

Comprehensive analysis of single-cell metabolites is critical since differences in cellular chemical compositions give rise to specialized biological functions. Herein, we propose a label-free mass cytometry by coupling flow cytometry to ESI-MS (named CyESI-MS) for high-coverage and high-throughput detection of cellular metabolites. Cells in suspension were isolated, online extracted by sheath fluid, and lysed during gas-assisted electrospray, followed by real-time MS analysis. Hundreds of metabolites, including nucleotides, amino acids, peptides, carbohydrates, fatty acyls, glycerolipids, glycerophospholipids, and sphingolipids, were detected and identified from one single cell. Discrimination of four types of cancer cell lines and even three subtypes of breast cancer cells was readily achieved using their distinct metabolic profiles. Furthermore, we screened out 102 characteristic ions from 615 detected peak signals for distinguishing breast cancer cell subtypes and identified 40 characteristic molecules which exhibited significant differences among these subtypes and would be potential metabolic markers for clinical diagnosis. CyESI-MS is expected to be a new-generation mass cytometry for studying cell heterogeneity on the metabolic level.

Label-free Mass Cytometry for Unveiling Cellular Metabolic Heterogeneity.

Multiple sclerosis is an inflammatory T cell-mediated autoimmune disease. In a Phase II clinical trial, high-dose immunosuppressive therapy combined with autologous CD34+ haematopoietic stem cell transplant resulted in 69·2% of subjects remaining disease-free without evidence of relapse, loss of neurological function or new magnetic resonance imaging (MRI) lesions to year 5 post-treatment. A combination of CyTOF mass cytometry and multi-parameter flow cytometry was used to explore the reconstitution kinetics of immune cell subsets in the periphery post-haematopoietic cell transplant (HSCT) and the impact of treatment on the phenotype of circulating T cells in this study population. Repopulation of immune cell subsets progressed similarly for all patients studied 2 years post-therapy, regardless of clinical outcome. At month 2, monocytes and natural killer (NK) cells were proportionally more abundant, while CD4 T cells and B cells were reduced, relative to baseline. In contrast to the changes observed at earlier time-points in the T cell compartment, B cells were proportionally more abundant and expansion in the proportion of naive B cells was observed 1 and 2 years post-therapy. Within the T cell compartment, the proportion of effector memory and late effector subsets of CD4 and CD8 T cells was increased, together with transient increases in proportions of CD45RA-regulatory T cells (Tregs ) and T helper type 1 (Th1 cells) and a decrease in Th17·1 cells. While none of the treatment effects studied correlated with clinical outcome, patients who remained healthy throughout the 5-year study had significantly higher absolute numbers of memory CD4 and CD8 T cells in the periphery prior to stem cell transplantation.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/cei.12985

Reconstitution of immune cell populations in multiple sclerosis patients after autologous stem cell transplantation.

T Cells specific for a single antigen tend to be rare, even after expansion of memory cells. They are commonly detected by in vitro stimulation with peptides or protein, followed by staining for intracellular cytokines. In this protocol, we use CyTOF® mass cytometry to collect single-cell data on a large number of cytokines/chemokines, as well as cell-surface proteins that characterize T cells and other immune cells. We also include a method for magnetic bead enrichment of antigen-stimulated T cells, based on their expression of CD154 and CD69. Coupling magnetic enrichment with highly multi-parameter mass cytometry, this method enables the ability to dissect the frequency, phenotype, and function of antigen-specific T cells in greater detail than previously possible. Rare cell subsets can be examined, while minimizing run times on the CyTOF.

Mass Cytometry Assays for Antigen-Specific T Cells Using CyTOF.

In this protocol, we use a CyTOF™ mass cytometry to collect single-cell data on a large number of cytokines/chemokines as well as cell-surface proteins that characterize T cells and other immune cells. The current selected mass window in AW 103-203 includes the lanthanides used for most antibody labeling, along with iridium and rhodium for DNA intercalators. The output data are in the format as .txt and .fcs files, which is compatible with many analysis programs. This protocol could be adapted to include tetramers into the staining panel, but we have not optimized for that purpose. The principal steps of intracellular cytokine staining are as follows: First, cells are activated for a few hours using either a specific peptide or a non-specific activation cocktail. An inhibitor of protein transport (e.g. Brefeldin A) is added to retain the cytokines within the cell. Next, EDTA is added to remove adherent cells from the activation vessel. After washing, antibodies to cell surface markers are added to the cells. The cells are then fixed in paraformaldehyde and permeabilized. We use a gentle detergent, saponin, as the permealization buffer because it is less destructive to surface and intracellular epitopes compared to harsh detergents or methanol. After permeabilization, the metal-conjugated anti-cytokine antibodies are added into the cell suspension. The stained cells are then sequentially introduced into the mass cytometry for signal intensity analysis.

Intracellular Cytokine Staining on PBMCs Using CyTOFTM Mass Cytometry

The antiviral response to influenza virus is complex and multifaceted, involving many immune cell subsets. There is an urgent need to understand the role of CD4+ T cells, which orchestrate an effective antiviral response, to improve vaccine design strategies. In this study, we analyzed PBMCs from human participants immunized with influenza vaccine, using high-dimensional single-cell proteomic immune profiling by mass cytometry. Data were analyzed using a novel clustering algorithm, denoised ragged pruning, to define possible influenza virus-specific clusters of CD4+ T cells. Denoised ragged pruning identified six clusters of cells. Among these, one cluster (Cluster 3) was found to increase in abundance following stimulation with influenza virus peptide ex vivo. A separate cluster (Cluster 4) was found to expand in abundance between days 0 and 7 postvaccination, indicating that it is vaccine responsive. We examined the expression profiles of all six clusters to characterize their lineage, functionality, and possible role in the response to influenza vaccine. Clusters 3 and 4 consisted of effector memory cells, with high CD154 expression. Cluster 3 expressed cytokines like IL-2, IFN-γ, and TNF-α, whereas Cluster 4 expressed IL-17. Interestingly, some participants had low abundance of Clusters 3 and 4, whereas others had higher abundance of one of these clusters compared with the other. Taken together, we present an approach for identifying novel influenza virus-reactive CD4+ T cell subsets, a method that could help advance understanding of the immune response to influenza, predict responsiveness to vaccines, and aid in better vaccine design.

https://www.immunohorizons.org/content/immunohorizon/4/12/774.full.pdf

Mass Cytometry Defines Virus-Specific CD4+ T Cells in Influenza Vaccination.

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Papers

Reconstitution of immune cell populations in multiple sclerosis patients after autologous stem cell transplantation.

Mass Cytometry Assays for Antigen-Specific T Cells Using CyTOF.

Intracellular Cytokine Staining on PBMCs Using CyTOFTM Mass Cytometry

Mass Cytometry Defines Virus-Specific CD4+ T Cells in Influenza Vaccination.