scholarly journals Insights From Single Cell RNA Sequencing Into the Immunology of Type 1 Diabetes- Cell Phenotypes and Antigen Specificity

2021 ◽  
Vol 12 ◽  
Author(s):  
Stephanie J. Hanna ◽  
Danijela Tatovic ◽  
Terri C. Thayer ◽  
Colin M. Dayan
Keyword(s):  
Type 1 Diabetes ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Insulin Binding ◽  
Antigen Specificity ◽  
Autoantibody Production ◽  
Individual Level ◽  
V Genes

In the past few years, huge advances have been made in techniques to analyse cells at an individual level using RNA sequencing, and many of these have precipitated exciting discoveries in the immunology of type 1 diabetes (T1D). This review will cover the first papers to use scRNAseq to characterise human lymphocyte phenotypes in T1D in the peripheral blood, pancreatic lymph nodes and islets. These have revealed specific genes such as IL-32 that are differentially expressed in islet –specific T cells in T1D. scRNAseq has also revealed wider gene expression patterns that are involved in T1D and can predict its development even predating autoantibody production. Single cell sequencing of TCRs has revealed V genes and CDR3 motifs that are commonly used to target islet autoantigens, although truly public TCRs remain elusive. Little is known about BCR repertoires in T1D, but scRNAseq approaches have revealed that insulin binding BCRs commonly use specific J genes, share motifs between donors and frequently demonstrate poly-reactivity. This review will also summarise new developments in scRNAseq technology, the insights they have given into other diseases and how they could be leveraged to advance research in the type 1 diabetes field to identify novel biomarkers and targets for immunotherapy.

scholarly journals Single-Cell RNA Sequencing Reveals Expanded Clones of Islet Antigen-Reactive CD4+ T Cells in Peripheral Blood of Subjects with Type 1 Diabetes

2017 ◽  
Vol 199 (1) ◽  
pp. 323-335 ◽  
Author(s):  
Karen Cerosaletti ◽  
Fariba Barahmand-pour-Whitman ◽  
Junbao Yang ◽  
Hannah A. DeBerg ◽  
Matthew J. Dufort ◽  
...  
Keyword(s):  
T Cells ◽  
Type 1 Diabetes ◽  
Single Cell ◽  
Rna Sequencing ◽  
Peripheral Blood ◽  
Cd4 T Cells ◽  
Single Cell Rna Sequencing ◽  
Islet Antigen

scholarly journals Cryopreservation of microglia enables single-cell RNA sequencing with minimal effects on disease-related gene expression patterns

iScience ◽  
2021 ◽  
Vol 24 (4) ◽  
pp. 102357
Author(s):  
Brenda Morsey ◽  
Meng Niu ◽  
Shetty Ravi Dyavar ◽  
Courtney V. Fletcher ◽  
Benjamin G. Lamberty ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Related Gene ◽  
Single Cell Rna Sequencing ◽  
Disease Related Gene

scholarly journals Higher Ultraviolet Radiation During Early Life Reduces Risk of Childhood Type 1 Diabetes in Boys

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Kate Miller
Keyword(s):  
Type 1 Diabetes ◽  
Ultraviolet Radiation ◽  
Western Australia ◽  
Early Life ◽  
Population Based ◽  
First Year ◽  
Third Trimester ◽  
Individual Level ◽  
First Year Of Life

IntroductionThere is increasing evidence that environmental exposures may be important in the pathogenesis of type 1 diabetes (T1D). Ultraviolet radiation (UVR) is of interest in relation to the development of T1D because of its immunoregulatory actions. Ecological studies testing the correlation between levels of UVR and T1D have shown a significant inverse relationship for both incidence and prevalence. Objectives and Approach We used large linked datasets to test ambient UVR during early life against T1D risk at the individual level. We conducted a nested case-control study using linked data from state-wide administrative datasets and NASA satellites. Cases (n=1819) were all children born in Western Australia from 1980-2014 with a diagnosis of T1D on the population-based Western Australian Children’s Diabetes Database between 0-16 years of age. Controls (n=27 259) were randomly selected from all live births in Western Australia and matched to cases on sex and date of birth. Daily UVR data from NASA satellites, that were date-and location-specific for each individual, were used to estimate total UVR dose for each trimester of pregnancy and the first year of life. ResultsConditional logistic regression showed that T1D risk was 44% lower in boys of mothers with UVR levels in the highest quartile (compared to the lowest quartile) during their third trimester of pregnancy (p=0.04). Higher UVR in the first year of life was also associated with a significantly lower risk of T1D in later childhood among boys. Among girls, there was no evidence of an association between total UVR dose and T1D risk. ConclusionHigher UVR in the third trimester and first year of life appears to interact with sex-specific factors to lower T1D risk among boys (but not girls) in Western Australia.

scholarly journals Single-Cell RNA Sequencing Unveils Unique Transcriptomic Signatures of Organ-Specific Endothelial Cells

Circulation ◽  
2020 ◽  
Vol 142 (19) ◽  
pp. 1848-1862 ◽  
Author(s):  
David T. Paik ◽  
Lei Tian ◽  
Ian M. Williams ◽  
Siyeon Rhee ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Receptor Expression ◽  
Transcriptional Networks ◽  
Sequencing Data ◽  
Tissue Specific ◽  
Functional Relationships ◽  
Single Cell Rna Sequencing

Background: Endothelial cells (ECs) display considerable functional heterogeneity depending on the vessel and tissue in which they are located. Whereas these functional differences are presumably imprinted in the transcriptome, the pathways and networks that sustain EC heterogeneity have not been fully delineated. Methods: To investigate the transcriptomic basis of EC specificity, we analyzed single-cell RNA sequencing data from tissue-specific mouse ECs generated by the Tabula Muris consortium. We used a number of bioinformatics tools to uncover markers and sources of EC heterogeneity from single-cell RNA sequencing data. Results: We found a strong correlation between tissue-specific EC transcriptomic measurements generated by either single-cell RNA sequencing or bulk RNA sequencing, thus validating the approach. Using a graph-based clustering algorithm, we found that certain tissue-specific ECs cluster strongly by tissue (eg, liver, brain), whereas others (ie, adipose, heart) have considerable transcriptomic overlap with ECs from other tissues. We identified novel markers of tissue-specific ECs and signaling pathways that may be involved in maintaining their identity. Sex was a considerable source of heterogeneity in the endothelial transcriptome and we discovered Lars2 to be a gene that is highly enriched in ECs from male mice. We found that markers of heart and lung ECs in mice were conserved in human fetal heart and lung ECs. We identified potential angiocrine interactions between tissue-specific ECs and other cell types by analyzing ligand and receptor expression patterns. Conclusions: We used single-cell RNA sequencing data generated by the Tabula Muris consortium to uncover transcriptional networks that maintain tissue-specific EC identity and to identify novel angiocrine and functional relationships between tissue-specific ECs.

scholarly journals PRIME: a probabilistic imputation method to reduce dropout effects in single-cell RNA sequencing

2020 ◽  
Vol 36 (13) ◽  
pp. 4021-4029
Author(s):  
Hyundoo Jeong ◽  
Zhandong Liu
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Imputation Method ◽  
Supplementary Information ◽  
Single Cell Sequencing ◽  
Depth Analysis ◽  
Single Cell Rna Sequencing

Abstract Summary Single-cell RNA sequencing technology provides a novel means to analyze the transcriptomic profiles of individual cells. The technique is vulnerable, however, to a type of noise called dropout effects, which lead to zero-inflated distributions in the transcriptome profile and reduce the reliability of the results. Single-cell RNA sequencing data, therefore, need to be carefully processed before in-depth analysis. Here, we describe a novel imputation method that reduces dropout effects in single-cell sequencing. We construct a cell correspondence network and adjust gene expression estimates based on transcriptome profiles for the local subnetwork of cells of the same type. We comprehensively evaluated this method, called PRIME (PRobabilistic IMputation to reduce dropout effects in Expression profiles of single-cell sequencing), on synthetic and eight real single-cell sequencing datasets and verified that it improves the quality of visualization and accuracy of clustering analysis and can discover gene expression patterns hidden by noise. Availability and implementation The source code for the proposed method is freely available at https://github.com/hyundoo/PRIME. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Heterogeneity of T Cells in Atherosclerosis Defined by Single-Cell RNA-Sequencing and Cytometry by Time of Flight

2020 ◽  
Author(s):  
Holger Winkels ◽  
Dennis Wolf
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
T Regulatory Cells ◽  
Foam Cell ◽  
Regulatory Cells ◽  
T Helper ◽  
Antigen Specificity ◽  
Single Cell Rna Sequencing

The infiltration and accumulation of pro- and anti-inflammatory leukocytes within the intimal layer of the arterial wall is a hallmark of developing and progressing atherosclerosis. While traditionally perceived as macrophage- and foam cell-dominated disease, it is now established that atherosclerosis is a partial autoimmune disease that involves the recognition of peptides from ApoB (apolipoprotein B), the core protein of LDL (low-density lipoprotein) cholesterol particles, by CD4 + T-helper cells and autoantibodies against LDL and ApoB. Autoimmunity in the atherosclerotic plaque has long been understood as a pathogenic T-helper type-1 driven response with proinflammatory cytokine secretion. Recent developments in high-parametric cell immunophenotyping by mass cytometry, single-cell RNA-sequencing, and in tools exploring antigen-specificity have established the existence of several unforeseen layers of T cell diversity with mixed T H 1 and T regulatory cells transcriptional programs and unpredicted fates. These findings suggest that pathogenic ApoB-reactive T cells evolve from atheroprotective and immunosuppressive CD4 + T regulatory cells that lose their protective properties over time. Here, we discuss T cell heterogeneity in atherosclerosis with a focus on plasticity, antigen-specificity, exhaustion, maturation, tissue residency, and its potential use in clinical prediction.

scholarly journals Erratum: Corrigendum: Analysis of self-antigen specificity of islet-infiltrating T cells from human donors with type 1 diabetes

2017 ◽  
Vol 23 (8) ◽  
pp. 1004-1004 ◽  
Author(s):  
Jenny Aurielle B Babon ◽  
Megan E DeNicola ◽  
David M Blodgett ◽  
Inne Crèvecoeur ◽  
Thomas S Buttrick ◽  
...  
Keyword(s):  
T Cells ◽  
Type 1 Diabetes ◽  
Antigen Specificity ◽  
Self Antigen
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