scholarly journals Multiomics single-cell analysis of human pancreatic islets reveals novel cellular states in health and type 1 diabetes

2021 ◽  
Author(s):  
Maria Fasolino ◽  
Gregory W. Schwartz ◽  
Maria L. Golson ◽  
Yue J. Wang ◽  
Ashleigh Morgan ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Single Cell ◽  
Pancreatic Islets ◽  
Mhc Class Ii ◽  
Single Cell Analysis ◽  
Cell Types ◽  
Human Pancreas ◽  
Analytical Strategy ◽  
Ductal Cells

AbstractType 1 diabetes (T1D) is an autoimmune disease of only partially defined etiology in which immune cells destroy insulin-producing beta cells. Using single-cell transcriptomics and an advanced analytical strategy to assess pancreatic islets of T1D, autoantibody-positive, and non-diabetic organ donors, we identified both canonical cell types and rare insulin-expressing cells with a hybrid mixture of endocrine and exocrine gene signatures within all donors. We further found elevated expression of MHC Class II pathway genes in exocrine ductal cells of T1D donors, which we confirmed through CyTOF, in situ imaging mass cytometry, and immunofluorescence analysis. Taken together, our multimodal analyses identify novel cell types and processes that may contribute to T1D immunopathogenesis and provide new cellular and molecular insights into human pancreas function.

scholarly journals Single-Cell Analysis of CD4 T Cells in Type 1 Diabetes: From Mouse to Man, How to Perform Mechanistic Studies

Diabetes ◽  
2019 ◽  
Vol 68 (10) ◽  
pp. 1886-1891 ◽  
Author(s):  
Siddhartha Sharma ◽  
Jeremy Pettus ◽  
Michael Gottschalk ◽  
Brian Abe ◽  
Peter Gottlieb ◽  
...  
Keyword(s):  
T Cells ◽  
Type 1 Diabetes ◽  
Single Cell ◽  
Cd4 T Cells ◽  
Single Cell Analysis ◽  
Cell Analysis ◽  
Mechanistic Studies

scholarly journals Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

2020 ◽  
Author(s):  
Yuming Cao ◽  
Zhiru Guo ◽  
Pranitha Vangala ◽  
Elisa Donnard ◽  
Ping Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Mhc Class Ii ◽  
Cultured Cells ◽  
Single Cell Analysis ◽  
Influenza Infection ◽  
Cell Types ◽  
Human Infection ◽  
Specific Cell ◽  
Natural Setting ◽  
Healthy Human

AbstractInfluenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection.

scholarly journals Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk

2021 ◽  
Author(s):  
Joshua Chiou ◽  
Ryan J Geusz ◽  
Mei-Lin Okino ◽  
Jee Yun Han ◽  
Michael Miller ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Complex Disease ◽  
Cell Types ◽  
Causal Variant ◽  
Cell Type ◽  
Ductal Cells ◽  
Risk Variants ◽  
Cell Type Specific

ABSTRACTTranslating genome-wide association studies (GWAS) of complex disease into mechanistic insight requires a comprehensive understanding of risk variant effects on disease-relevant cell types. To uncover cell type-specific mechanisms of type 1 diabetes (T1D) risk, we combined genetic association mapping and single cell epigenomics. We performed the largest to-date GWAS of T1D in 489,679 samples imputed into 59.2M variants, which identified 74 novel association signals including several large-effect rare variants. Fine-mapping of 141 total signals substantially improved resolution of causal variant credible sets, which primarily mapped to non-coding sequence. To annotate cell type-specific regulatory mechanisms of T1D risk variants, we mapped 448,142 candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cell types using snATAC-seq of 131,554 nuclei. T1D risk variants were enriched in cCREs active in CD4+ T cells as well as several additional cell types including pancreatic exocrine acinar and ductal cells. High-probability T1D risk variants at multiple signals mapped to exocrine-specific cCREs including novel loci near CEL, GP2 and CFTR. At the CFTR locus, the likely causal variant rs7795896 mapped in a ductal-specific distal cCRE which regulated CFTR and the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in T1D pathogenesis and highlight the power of combining large-scale GWAS and single cell epigenomics to provide insight into the cellular origins of complex disease.

scholarly journals Development of a Bioartificial Vascular Pancreas

2021 ◽  
Vol 12 ◽  
pp. 204173142110277
Author(s):  
Edward X Han ◽  
Juan Wang ◽  
Mehmet Kural ◽  
Bo Jiang ◽  
Katherine L Leiby ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Pancreatic Islets ◽  
Vascular Graft ◽  
Term Treatment ◽  
Diffusion Limitations ◽  
Human Scale ◽  
Arterial Blood ◽  
Long Term Treatment

Transplantation of pancreatic islets has been shown to be effective, in some patients, for the long-term treatment of type 1 diabetes. However, transplantation of islets into either the portal vein or the subcutaneous space can be limited by insufficient oxygen transfer, leading to islet loss. Furthermore, oxygen diffusion limitations can be magnified when islet numbers are increased dramatically, as in translating from rodent studies to human-scale treatments. To address these limitations, an islet transplantation approach using an acellular vascular graft as a vascular scaffold has been developed, termed the BioVascular Pancreas (BVP). To create the BVP, islets are seeded as an outer coating on the surface of an acellular vascular graft, using fibrin as a hydrogel carrier. The BVP can then be anastomosed as an arterial (or arteriovenous) graft, which allows fully oxygenated arterial blood with a pO2 of roughly 100 mmHg to flow through the graft lumen and thereby supply oxygen to the islets. In silico simulations and in vitro bioreactor experiments show that the BVP design provides adequate survivability for islets and helps avoid islet hypoxia. When implanted as end-to-end abdominal aorta grafts in nude rats, BVPs were able to restore near-normoglycemia durably for 90 days and developed robust microvascular infiltration from the host. Furthermore, pilot implantations in pigs were performed, which demonstrated the scalability of the technology. Given the potential benefits provided by the BVP, this tissue design may eventually serve as a solution for transplantation of pancreatic islets to treat or cure type 1 diabetes.

scholarly journals Single-cell analysis of human adipose tissue identifies depot- and disease-specific cell types

2019 ◽  
Vol 2 (1) ◽  
pp. 97-109 ◽  
Author(s):  
Jinchu Vijay ◽  
Marie-Frédérique Gauthier ◽  
Rebecca L. Biswell ◽  
Daniel A. Louiselle ◽  
Jeffrey J. Johnston ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Single Cell ◽  
Single Cell Analysis ◽  
Human Adipose Tissue ◽  
Cell Types ◽  
Specific Cell ◽  
Cell Analysis ◽  
Disease Specific

Immunotherapy: Building a bridge to a cure for type 1 diabetes

Science ◽  
2021 ◽  
Vol 373 (6554) ◽  
pp. 510-516
Author(s):  
Jeffrey A. Bluestone ◽  
Jane H. Buckner ◽  
Kevan C. Herold
Keyword(s):  
Type 1 Diabetes ◽  
Immune Cell ◽  
Cell Types ◽  
Underlying Disease ◽  
Β Cells ◽  
Current State ◽  
Islet Inflammation ◽  
Genetic And Environmental Factors ◽  
Key Events

Type 1 diabetes (T1D) is an autoimmune disease in which T cells attack and destroy the insulin-producing β cells in the pancreatic islets. Genetic and environmental factors increase T1D risk by compromising immune homeostasis. Although the discovery and use of insulin have transformed T1D treatment, insulin therapy does not change the underlying disease or fully prevent complications. Over the past two decades, research has identified multiple immune cell types and soluble factors that destroy insulin-producing β cells. These insights into disease pathogenesis have enabled the development of therapies to prevent and modify T1D. In this review, we highlight the key events that initiate and sustain pancreatic islet inflammation in T1D, the current state of the immunological therapies, and their advantages for the treatment of T1D.

scholarly journals Modeling Type 1 Diabetes Using Pluripotent Stem Cell Technology

2021 ◽  
Vol 12 ◽  
Author(s):  
Kriti Joshi ◽  
Fergus Cameron ◽  
Swasti Tiwari ◽  
Stuart I. Mannering ◽  
Andrew G. Elefanty ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Stem Cell ◽  
Genetic Variants ◽  
Genetic Background ◽  
Pluripotent Stem Cell ◽  
Cell Types ◽  
Polygenic Inheritance

Induced pluripotent stem cell (iPSC) technology is increasingly being used to create in vitro models of monogenic human disorders. This is possible because, by and large, the phenotypic consequences of such genetic variants are often confined to a specific and known cell type, and the genetic variants themselves can be clearly identified and controlled for using a standardized genetic background. In contrast, complex conditions such as autoimmune Type 1 diabetes (T1D) have a polygenic inheritance and are subject to diverse environmental influences. Moreover, the potential cell types thought to contribute to disease progression are many and varied. Furthermore, as HLA matching is critical for cell-cell interactions in disease pathogenesis, any model that seeks to test the involvement of particular cell types must take this restriction into account. As such, creation of an in vitro model of T1D will require a system that is cognizant of genetic background and enables the interaction of cells representing multiple lineages to be examined in the context of the relevant environmental disease triggers. In addition, as many of the lineages critical to the development of T1D cannot be easily generated from iPSCs, such models will likely require combinations of cell types derived from in vitro and in vivo sources. In this review we imagine what an ideal in vitro model of T1D might look like and discuss how the required elements could be feasibly assembled using existing technologies. We also examine recent advances towards this goal and discuss potential uses of this technology in contributing to our understanding of the mechanisms underlying this autoimmune condition.

scholarly journals Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hongyu Zhao ◽  
Yu Teng ◽  
Wende Hao ◽  
Jie Li ◽  
Zhefeng Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Single Cell ◽  
Cancer Progression ◽  
Cox Regression ◽  
Single Cell Analysis ◽  
Cell Types ◽  
In Vitro Assays ◽  
Migration And Invasion ◽  
Dominant Type

Abstract Background Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications. Methods We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan–Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression. Results We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion. Conclusions Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.

scholarly journals Single-cell analysis reveals cellular heterogeneity and molecular determinants of hypothalamic leptin-receptor cells

2020 ◽  
Author(s):  
N. Kakava-Georgiadou ◽  
J.F. Severens ◽  
A.M. Jørgensen ◽  
K.M. Garner ◽  
M.C.M Luijendijk ◽  
...  
Keyword(s):  
Single Cell ◽  
Leptin Receptor ◽  
Single Cell Analysis ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Molecular Signature ◽  
Neuronal Populations ◽  
Hypothalamic Nuclei ◽  
Satiety Hormone ◽  
Multiple Cell

AbstractHypothalamic nuclei which regulate homeostatic functions express leptin receptor (LepR), the primary target of the satiety hormone leptin. Single-cell RNA sequencing (scRNA-seq) has facilitated the discovery of a variety of hypothalamic cell types. However, low abundance of LepR transcripts prevented further characterization of LepR cells. Therefore, we perform scRNA-seq on isolated LepR cells and identify eight neuronal clusters, including three uncharacterized Trh-expressing populations as well as 17 non-neuronal populations including tanycytes, oligodendrocytes and endothelial cells. Food restriction had a major impact on Agrp neurons and changed the expression of obesity-associated genes. Multiple cell clusters were enriched for GWAS signals of obesity. We further explored changes in the gene regulatory landscape of LepR cell types. We thus reveal the molecular signature of distinct populations with diverse neurochemical profiles, which will aid efforts to illuminate the multi-functional nature of leptin’s action in the hypothalamus.

scholarly journals Substance Use Affects Type 1 Diabetes Pancreas Pathology: Implications for Future Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Brittany S. Bruggeman ◽  
Martha Campbell-Thompson ◽  
Stephanie L. Filipp ◽  
Matthew J. Gurka ◽  
Mark A. Atkinson ◽  
...  
Keyword(s):  
Acute Pancreatitis ◽  
Substance Use ◽  
Type 1 Diabetes ◽  
Chronic Pancreatitis ◽  
Fatty Infiltration ◽  
Organ Donors ◽  
Human Pancreas ◽  
Islet Amyloid ◽  
Control Organ

Access to human pancreas samples from organ donors has greatly advanced our understanding of type 1 diabetes pathogenesis; however, previous studies have shown that donors have a high rate of substance use, and its impact on pancreatic histopathology in this disease is not well described. One-hundred-thirty-one type 1 diabetes and 111 control organ donor pancreata from persons 12-89 years of age (mean 29.8 ± 15.5 years) within the Network for Pancreatic Organ donors with Diabetes (nPOD) were examined for insulin positivity, insulitis, amyloid staining, acute and chronic pancreatitis, and chronic exocrine changes (acinar atrophy, fibrosis, fatty infiltration, or periductal fibrosis); findings were compared by history of substance use. A secondary analysis compared exocrine pancreatic histopathologic findings in type 1 diabetes versus control organ donors regardless of substance use history. We observed a high but congruent rate of substance use in type 1 diabetes and control organ donors (66.4% and 64% respectively). Among donors with type 1 diabetes (but not controls), islet amyloid (OR 9.96 [1.22, 81.29]) and acute pancreatitis (OR 3.2 [1.06, 9.63]) were more common in alcohol users while chronic exocrine changes (OR 8.86 [1.13, 69.31]) were more common in cocaine users. Substance use impacted the pancreata of donors with type 1 diabetes more than controls. Overall, despite similar rates of substance use, acute pancreatitis (15.3% versus 4.5%, p=0.0061), chronic pancreatitis (29.8% versus 9.9%, p=0.0001), and chronic exocrine changes (73.3% versus 36.9%, p&lt;0.0001) were more common in type 1 diabetes donors than controls. Alcohol and/or cocaine use in type 1 diabetes organ donors increases exocrine pancreas pathology and islet amyloid deposition but does not affect insulitis or insulin positivity. Exocrine pathology in type 1 diabetes donors is common, and further study of the pathophysiology of these changes is needed.

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