Similar Datasets
Project description:Single-cell transcriptome analysis reveals phenotypically diverse islet-infiltrating T cell subsets in type 1 diabetes
| PRJNA516423 | ENA
Project description:Clonal expansions occur in the persistent HIV reservoir as shown by the duplication of proviral integration sites. However, the source of the proliferation of HIV-infected cells remains unclear. Here, we analyze the TCR repertoire of single HIV-infected cells harboring translation-competent proviruses in longitudinal samples from eight individuals on antiretroviral therapy (ART). When compared to uninfected cells, the TCR repertoire of reservoir cells is heavily biased: expanded clonotypes are present in all individuals, account for the majority of reservoir cells and are often maintained over time on ART. Infected T cell clones are detected at low frequencies in the long-lived central memory compartment and overrepresented in the most differentiated memory subsets. Our results indicate that clonal expansions highly contribute to the persistence of the HIV reservoir and suggest that reservoir cells displaying a differentiated phenotype are the progeny of infected central memory cells undergoing antigen-driven clonal expansion during ART.
| S-EPMC7427996 | biostudies-literature
Project description:Type 1 diabetes, the immune mediated form of diabetes, represents a prototypical organ specific autoimmune disease in that insulin producing pancreatic islets are specifically targeted by T cells. The disease is now predictable in humans with the measurement of type 1 diabetes associated autoantibodies (islet autoantibodies) in the peripheral blood which are directed against insulin and beta cell proteins. With an increasing incidence of disease, especially in young children, large well-controlled clinical prevention trials using antigen specific immunotherapy have been completed but with limited clinical benefit. To improve outcomes, it is critical to understand the antigen and T cell receptor repertoires of those cells that infiltrate the target organ, pancreatic islets, in human type 1 diabetes. With international networks to identify organ donors with type 1 diabetes, improved immunosequencing platforms, and the ability to reconstitute T cell receptors of interest into immortalized cell lines allows antigen discovery efforts for rare tissue specific T cells. Here we review the disease pathogenesis of type 1 diabetes with a focus on human islet infiltrating T cell antigen discovery efforts, which provides necessary knowledge to define biomarkers of disease activity and improve antigen specific immunotherapy approaches for disease prevention.
| S-EPMC6418007 | biostudies-literature
Project description:To better understand cellular communication driving diverse behaviors, we need to uncover the molecular mechanisms of within-cell-type functional heterogeneity. While single-cell RNA sequencing (scRNAseq) has advanced our understanding of cell heterogeneity, linking individual cell phenotypes to transcriptomic data remains challenging. Here, we used a phenotypic cell sorting technique to ask whether phenotypically supervised scRNAseq analysis (pheno-scRNAseq) can provide more insight into heterogeneous cell behaviors than unsupervised scRNAseq. Using a simple 3D in vitro breast cancer (BRCA) model, we conducted pheno-scRNAseq on invasive and non-invasive cells and compared the results to phenotype-agnostic scRNAseq analysis. Pheno-scRNAseq identified unique and more selective differentially expressed genes than unsupervised scRNAseq analysis. Functional studies validated the utility of pheno-scRNAseq in understanding within-cell-type functional heterogeneity and revealed that migration phenotypes were coordinated with specific metabolic, proliferation, stress, and immune phenotypes. This approach lends new insight into the molecular systems underlying BRCA cell phenotypic heterogeneity.
| S-EPMC7808958 | biostudies-literature
Project description:Manual gating of bivariate plots remains the most frequently used data analysis method in flow cytometry. However, gating is operator-dependent and cumbersome, particularly with the increasing complexity of modern multicolor immunophenotyping data. A method that can remove operator bias, enable systematic and thorough analysis of complex high-dimensional data, correlate temporal changes in different subsets and lead to biomarker discovery is needed. Here we apply such a method, called cytometric fingerprinting (CF), to data obtained on peripheral blood B cells from an adult patient with type-1 diabetes who underwent pancreatic islet transplantation. We establish that CF can be used to analyze longitudinal trends in immunophenotypic data, and show that results from CF are comparable to those obtained with traditional gating methods. Both methods reveal the appearance of transitional B cells and subsequent accumulation of more mature B cells following immunosuppression and transplantation. This pattern is consistent with a temporally ordered process of B cell auto-reconstitution. We also show the comparative efficiency of fingerprinting in recognizing relative changes in B cell subsets with respect to time, its ability to couple the data with statistical methods (agglomerative clustering) and its potential to define novel subsets.
| S-EPMC3010186 | biostudies-literature
Project description: Not available
| S-EPMC11233144 | biostudies-literature
Project description:Blood glucose levels are tightly controlled by the coordinated action of at least four cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 (T2D) diabetes. Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet (dys)function, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single-cell transcriptomes for 638 cells from nondiabetic (ND) and T2D human islet samples. Analyses of ND single-cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single-cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell-type-specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis.
| S-EPMC5287227 | biostudies-literature
Project description:Separation of B cells has been historically important in discovering their functional relevance, particularly in relation to infection, immune disorders and vaccination. Traditional use of phenotypic markers often poses problems in distinguishing heterogeneous populations such as the Double Negative (DN, CD19+CD27-IgD-) cells. B cells represent a small subset of PBMCs; this represents challenges to use bottom-up approaches such as single-cell transcriptomics in defining B cell subpopulations. In this study we therefore used the 10X single-cell RNAseq platform on B cell populations already defined by FACS sorting (Transitional, CD19+CD27-IgD+CD10+; Naïve, CD19+CD27-IgD+CD10-; Classical Memory, CD19+CD27+IgD-; IgM Memory, CD19+CD27+IgD+; and DN). These data match known phenotypes to transcriptionally defined B cell subpopulations, and provide a reference atlas for researchers interested in better defining B cell subsets in their data.
2021-03-19 | E-MTAB-9544 | biostudies-arrayexpress
Project description:Blood glucose levels are tightly controlled by the coordinated action of at least five cell types constituting pancreatic islets. Changes in the proportion and/or function of these cells are associated with genetic and molecular pathophysiology of monogenic, type 1, and type 2 diabetes (T2D). Cellular heterogeneity impedes precise understanding of the molecular components of each islet cell type that govern islet dysfunction, particularly the less abundant delta and gamma/pancreatic polypeptide (PP) cells. Here, we report single cell transcriptomes for 617 islet cells after profiling ~1000 cells from non-diabetic (ND) and T2D human organ donors. Analyses of non-diabetic single cell transcriptomes identified distinct alpha, beta, delta, and PP/gamma cell-type signatures. Genes linked to rare and common forms of islet dysfunction and diabetes were expressed in the delta and PP/gamma cell types. Moreover, this study revealed that delta cells specifically express receptors that receive and coordinate systemic cues from the leptin, ghrelin, and dopamine signaling pathways implicating them as integrators of central and peripheral metabolic signals into the pancreatic islet. Finally, single cell transcriptome profiling revealed genes differentially regulated between T2D and ND alpha, beta, and delta cells that were undetectable in paired whole islet analyses. This study thus identifies fundamental cell type-specific features of pancreatic islet (dys)function and provides a critical resource for comprehensive understanding of islet biology and diabetes pathogenesis. Grant ID: Award No. W81XWH-16-1-0130 Grant title: Peer Reviewed Medical Research Program Funding Source: Assistant Secretary of Defense for Health Affairs Affiliation: Jackson Laboratory for Genomic Medicine, Farmington, CT Name: Michael Stitzel
2016-11-09 | GSE86469 | GEO
Project description:Pancreatic islet cells are critical for maintaining normal blood glucose levels and their malfunction underlies diabetes development and progression. We used single-cell RNA sequencing to determine the transcriptomes of 1,492 human pancreatic α-, β-, δ- and PP cells from non-diabetic and type 2 diabetes organ donors. We identified cell type specific genes and pathways as well as 245 genes with disturbed expression in type 2 diabetes. Importantly, 92% of the genes have not previously been associated with islet cell function or growth. Comparison of gene profiles in mouse and human α- and β-cells revealed species-specific expression. All data are available for online browsing and download and will hopefully serve as a resource for the islet research community.
2016-08-31 | GSE81608 | GEO