scholarly journals Gene Signatures of NEUROGENIN3+ Endocrine Progenitor Cells in the Human Pancreas

2021 ◽  
Vol 12 ◽  
Author(s):  
Hyo Jeong Yong ◽  
Gengqiang Xie ◽  
Chengyang Liu ◽  
Wei Wang ◽  
Ali Naji ◽  
...  
Keyword(s):  
Single Cell ◽  
Network Inference ◽  
Current Knowledge ◽  
Pancreatic Tissue ◽  
Integrated Analysis ◽  
Human Pancreas ◽  
Rna Seq ◽  
Endocrine Differentiation ◽  
Pancreatic Cells ◽  
Homeobox Protein

NEUROGENIN3+ (NEUROG3+) cells are considered to be pancreatic endocrine progenitors. Our current knowledge on the molecular program of NEUROG3+ cells in humans is largely extrapolated from studies in mice. We hypothesized that single-cell RNA-seq enables in-depth exploration of the rare NEUROG3+ cells directly in humans. We aligned four large single-cell RNA-seq datasets from postnatal human pancreas. Our integrated analysis revealed 10 NEUROG3+ epithelial cells from a total of 11,174 pancreatic cells. Noticeably, human NEUROG3+ cells clustered with mature pancreatic cells and epsilon cells displayed the highest frequency of NEUROG3 positivity. We confirmed the co-expression of NEUROG3 with endocrine markers and the high percentage of NEUROG3+ cells among epsilon cells at the protein level based on immunostaining on pancreatic tissue sections. We further identified unique genetic signatures of the NEUROG3+ cells. Regulatory network inference revealed novel transcription factors including Prospero homeobox protein 1 (PROX1) may act jointly with NEUROG3. As NEUROG3 plays a central role in endocrine differentiation, knowledge gained from our study will accelerate the development of beta cell regeneration therapies to treat diabetes.

scholarly journals SAT-298 Integrative Single-Cell Transcriptomic and Epigenomic Landscape of Mouse Anterior Pituitary Cell Types

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Frederique Murielle Ruf-Zamojski ◽  
Michel A Zamojski ◽  
German Nudelman ◽  
Yongchao Ge ◽  
Natalia Mendelev ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Line ◽  
Anterior Pituitary ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Pituitary Cell ◽  
Integrated Analysis ◽  
Pituitary Cells ◽  
Rna Seq ◽  
Cell Type

Abstract The pituitary gland is a critical regulator of the neuroendocrine system. To further our understanding of the classification, cellular heterogeneity, and regulatory landscape of pituitary cell types, we performed and computationally integrated single cell (SC)/single nucleus (SN) resolution experiments capturing RNA expression, chromatin accessibility, and DNA methylation state from mouse dissociated whole pituitaries. Both SC and SN transcriptome analysis and promoter accessibility identified the five classical hormone-producing cell types (somatotropes, gonadotropes (GT), lactotropes, thyrotropes, and corticotropes). GT cells distinctively expressed transcripts for Cga, Fshb, Lhb, Nr5a1, and Gnrhr in SC RNA-seq and SN RNA-seq. This was matched in SN ATAC-seq with GTs specifically showing open chromatin at the promoter regions for the same genes. Similarly, the other classically defined anterior pituitary cells displayed transcript expression and chromatin accessibility patterns characteristic of their own cell type. This integrated analysis identified additional cell-types, such as a stem cell cluster expressing transcripts for Sox2, Sox9, Mia, and Rbpms, and a broadly accessible chromatin state. In addition, we performed bulk ATAC-seq in the LβT2b gonadotrope-like cell line. While the FSHB promoter region was closed in the cell line, we identified a region upstream of Fshb that became accessible by the synergistic actions of GnRH and activin A, and that corresponded to a conserved region identified by a polycystic ovary syndrome (PCOS) single nucleotide polymorphism (SNP). Although this locus appears closed in deep sequencing bulk ATAC-seq of dissociated mouse pituitary cells, SN ATAC-seq of the same preparation showed that this site was specifically open in mouse GT, but closed in 14 other pituitary cell type clusters. This discrepancy highlighted the detection limit of a bulk ATAC-seq experiment in a subpopulation, as GT represented ~5% of this dissociated anterior pituitary sample. These results identified this locus as a candidate for explaining the dual dependence of Fshb expression on GnRH and activin/TGFβ signaling, and potential new evidence for upstream regulation of Fshb. The pituitary epigenetic landscape provides a resource for improved cell type identification and for the investigation of the regulatory mechanisms driving cell-to-cell heterogeneity. Additional authors not listed due to abstract submission restrictions: N. Seenarine, M. Amper, N. Jain (ISMMS).

scholarly journals Mercury in Pancreatic Cells of People with and without Pancreatic Cancer

2020 ◽  
Vol 17 (23) ◽  
pp. 8990
Author(s):  
Roger Pamphlett ◽  
Andrew J. Colebatch ◽  
Philip A. Doble ◽  
David P. Bishop
Keyword(s):  
Pancreatic Cancer ◽  
Toxic Metals ◽  
Inductively Coupled Plasma ◽  
Islet Cells ◽  
Inorganic Mercury ◽  
Pancreatic Tissue ◽  
Human Pancreas ◽  
Inductively Coupled ◽  
Pancreatic Cells ◽  
Cadmium Lead

Toxic metals have been implicated in the pathogenesis of pancreatic cancer. Human exposure to mercury is widespread, but it is not known how often mercury is present in the human pancreas and which cells might contain mercury. We therefore aimed to determine, in people with and without pancreatic cancer, the distribution and prevalence of mercury in pancreatic cells. Paraffin-embedded sections of normal pancreatic tissue were obtained from pancreatectomy samples of 45 people who had pancreatic adenocarcinoma, and from autopsy samples of 38 people without pancreatic cancer. Mercury was identified using two methods of elemental bio-imaging: (1) With autometallography, inorganic mercury was seen in islet cells in 14 of 30 males (47%) with pancreatic cancer compared to two of 17 males (12%) without pancreatic cancer (p = 0.024), and in 10 of 15 females (67%) with pancreatic cancer compared to four of 21 females (19%) without pancreatic cancer (p = 0.006). Autometallographic mercury was present in acinar cells in 24% and in periductal cells in 11% of people with pancreatic cancer, but not in those without pancreatic cancer. (2) Laser ablation-inductively coupled plasma-mass spectrometry confirmed the presence of mercury in islets that stained with autometallography and detected cadmium, lead, chromium, iron, nickel and aluminium in some samples. In conclusion, the genotoxic metal mercury is found in normal pancreatic cells in more people with, than without, pancreatic cancer. These findings support the hypothesis that toxic metals such as mercury contribute to the pathogenesis of pancreatic cancer.

scholarly journals SCell: integrated analysis of single-cell RNA-seq data

2016 ◽  
Vol 32 (14) ◽  
pp. 2219-2220 ◽  
Author(s):  
Aaron Diaz ◽  
Siyuan J. Liu ◽  
Carmen Sandoval ◽  
Alex Pollen ◽  
Tom J. Nowakowski ◽  
...  
Keyword(s):  
Single Cell ◽  
Integrated Analysis ◽  
Rna Seq

scholarly journals SCODE: an efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

2017 ◽  
Vol 33 (15) ◽  
pp. 2314-2321 ◽  
Author(s):  
Hirotaka Matsumoto ◽  
Hisanori Kiryu ◽  
Chikara Furusawa ◽  
Minoru S H Ko ◽  
Shigeru B H Ko ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Network ◽  
Network Inference ◽  
Inference Algorithm ◽  
Rna Seq

scholarly journals Integrated analyses of the single-cell ATAC-seq and RNA-seq reveal the epigenetic landscape of human ovarian aging

2021 ◽  
Author(s):  
Yunzhao Xu ◽  
Jinling Chen ◽  
Shuting Gu ◽  
Yuanlin Liu ◽  
Huihua Ni ◽  
...  
Keyword(s):  
Single Cell ◽  
Molecular Mechanisms ◽  
Integrated Analysis ◽  
Age Difference ◽  
Rna Seq ◽  
Epigenetic Landscape ◽  
Operating Characteristics ◽  
Ovarian Aging ◽  
Age Related ◽  
Oocyte Aging

Studying the molecular mechanisms of ovarian aging is crucial for understanding the age-related fertility issues in females. Recently, a single-cell transcriptomic roadmap of ovarian aging based on non-human primates revealed the molecular signatures of the oocytes at different developmental stages. Herein, we present the first epigenetic landscape of human ovarian aging, through an integrated analysis of the single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) and single-cell RNA-seq. We depicted the transcriptional profiles and chromatin accessibility of the ovarian tissues isolated from old (n=4) and young (n=2) donors. The unsupervised clustering of data revealed seven distinct cell populations in the ovarian tissues and six subtypes of oocytes, which could be distinguished by age difference. Further analysis of the scATAC-seq data from the young and old oocytes revealed that the interaction between the Notch signaling pathway and AP-1 family transcription factors may crucially determine oocyte aging. Finally, a machine-learning algorithm was applied to calculate the optimal model based on the single-cell dataset for predicting oocyte aging, which exhibited excellent accuracy with a cross-validated area under the receiver operating characteristics score of 0.99. In summary, this study provides a comprehensive understanding of human ovarian aging at both the transcriptomic and epigenetic levels, based on an integrated analysis of large-scale single-cell datasets. We believe our results will shed light on the discovery of potential therapeutic targets or diagnostic markers for age-related ovarian disorders.

scholarly journals Single-cell analysis identifies a key role forHhipin murine coronal suture development

2021 ◽  
Author(s):  
Greg Holmes ◽  
Ana S. Gonzalez-Reiche ◽  
Madrikha Saturne ◽  
Xianxiao Zhou ◽  
Ana C. Borges ◽  
...  
Keyword(s):  
Single Cell ◽  
Hedgehog Signaling ◽  
Bone Growth ◽  
Single Cell Analysis ◽  
Abnormal Development ◽  
Integrated Analysis ◽  
Coronal Suture ◽  
Rna Seq ◽  
Osteogenic Cells ◽  
Insight Into

AbstractCraniofacial development depends on proper formation and maintenance of sutures between adjacent bones of the skull. In sutures, bone growth occurs at the edge of each bone, and suture mesenchyme maintains the separation between them. We performed single-cell RNA-seq analyses of the embryonic, murine coronal suture. Analyzing replicate libraries at E16.5 and E18.5, we identified 14 cell populations. Seven populations at E16.5 and nine at E18.5 comprised the suture mesenchyme, osteogenic cells, and associated populations. Through an integrated analysis with bulk RNA-seq data, we found a distinct coronal suture mesenchyme population compared to other neurocranial sutures, marked by expression ofHhip, an inhibitor of hedgehog signaling. We found that at E18.5,Hhip-/-coronal osteogenic fronts are closely apposed and suture mesenchyme is depleted, demonstrating thatHhipis required for coronal suture development. Our transcriptomic approach provides a rich resource for insight into normal and abnormal development.

scholarly journals Integrated analyses of the single-cell ATAC-seq and RNA-seq reveal the epigenetic landscape of human ovarian aging

2022 ◽  
Author(s):  
Yunzhao Xu ◽  
Jinling Chen ◽  
Shuting Gu ◽  
Yuanlin Liu ◽  
Huihua Ni ◽  
...  
Keyword(s):  
Single Cell ◽  
Molecular Mechanisms ◽  
Integrated Analysis ◽  
Age Difference ◽  
Rna Seq ◽  
Epigenetic Landscape ◽  
Operating Characteristics ◽  
Ovarian Aging ◽  
Age Related ◽  
Oocyte Aging

Abstract Studying the molecular mechanisms of ovarian aging is crucial for understanding the age-related fertility issues in females. Recently, a single-cell transcriptomic roadmap of ovarian aging based on non-human primates revealed the molecular signatures of the oocytes at different developmental stages. Herein, we present the first epigenetic landscape of human ovarian aging, through an integrated analysis of the single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) and single-cell RNA-seq. We depicted the transcriptional profiles and chromatin accessibility of the ovarian tissues isolated from old (n=4) and young (n=2) donors. The unsupervised clustering of data revealed seven distinct cell populations in the ovarian tissues and six subtypes of oocytes, which could be distinguished by age difference. Further analysis of the scATAC-seq data from the young and old oocytes revealed that the interaction between the Notch signaling pathway and AP-1 family transcription factors may crucially determine oocyte aging. Finally, a machine-learning algorithm was applied to calculate the optimal model based on the single-cell dataset for predicting oocyte aging, which exhibited excellent accuracy with a cross-validated area under the receiver operating characteristics score of 0.99. In summary, this study provides a comprehensive understanding of human ovarian aging at both the transcriptomic and epigenetic levels, based on an integrated analysis of large-scale single-cell datasets. We believe our results will shed light on the discovery of potential therapeutic targets or diagnostic markers for age-related ovarian disorders.

scholarly journals High dimensional analyses of cells dissociated from cryopreserved synovial tissue

2018 ◽  
Author(s):  
Laura T. Donlin ◽  
Deepak A. Rao ◽  
Kevin Wei ◽  
Kamil Slowikowski ◽  
Mandy J. McGeachy ◽  
...  
Keyword(s):  
T Cell ◽  
Single Cell ◽  
Rna Sequencing ◽  
Synovial Tissue ◽  
High Dimensional ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Mass Cytometry ◽  
Viable Cells ◽  
Cellular Phenotypes

AbstractBackgroundDetailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership (AMP) RA/SLE network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples.MethodsMultiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10%-DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T cell, B cell, and macrophage suspensions for bulk population RNA-seq and plate-based single cell CEL-Seq2 RNA-seq.ResultsUpon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ∼30 arthroplasty and ∼20 biopsy samples yielded a consensus digestion protocol using 100µg/mL of Liberase TL™ enzyme. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished: 1) diverse fibroblast phenotypes, 2) distinct populations of memory B cells and antibody-secreting cells, and 3) multiple CD4+ and CD8+ T cell activation states. Bulk RNA sequencing of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified.ConclusionWe have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

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