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Fisher C, Johnson K, Moore M, Sadrati A, Janecek JL, Graham ML, Klein AH. Loss of ATP-Sensitive Potassium Channel Expression and Function in the Nervous System Decreases Opioid Sensitivity in a High-Fat Diet-Fed Mouse Model of Diet-Induced Obesity. Diabetes 2024; 73:1244-1254. [PMID: 38776417 PMCID: PMC11262047 DOI: 10.2337/db23-1030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 05/20/2024] [Indexed: 05/25/2024]
Abstract
During diabetes progression, β-cell dysfunction due to loss of potassium channels sensitive to ATP, known as KATP channels, occurs, contributing to hyperglycemia. The aim of this study was to investigate if KATP channel expression or activity in the nervous system was altered in a high-fat diet (HFD)-fed mouse model of diet-induced obesity. Expression of two KATP channel subunits, Kcnj11 (Kir6.2) and Abcc8 (SUR1), were decreased in the peripheral and central nervous system of mice fed HFD, which was significantly correlated with mechanical paw-withdrawal thresholds. HFD mice had decreased antinociception to systemic morphine compared with control diet (CON) mice, which was expected because KATP channels are downstream targets of opioid receptors. Mechanical hypersensitivity in HFD mice was exacerbated after systemic treatment with glyburide or nateglinide, KATP channel antagonists clinically used to control blood glucose levels. Upregulation of SUR1 and Kir6.2, through an adenovirus delivered intrathecally, increased morphine antinociception in HFD mice. These data present a potential link between KATP channel function and neuropathy during early stages of diabetes. There is a need for increased knowledge of how diabetes affects structural and molecular changes in the nervous system, including ion channels, to lead to the progression of chronic pain and sensory issues. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Cole Fisher
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN
| | - Kayla Johnson
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN
| | - Madelyn Moore
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN
| | - Amir Sadrati
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN
| | - Jody L. Janecek
- Department of Surgery, University of Minnesota, St. Paul, MN
| | | | - Amanda H. Klein
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN
- Department of Pharmacology and Toxicology, University at Buffalo, Buffalo, NY
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2
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Tang Z, Wang S, Li X, Hu C, Zhai Q, Wang J, Ye Q, Liu J, Zhang G, Guo Y, Su F, Liu H, Guan L, Jiang C, Chen J, Li M, Ren F, Zhang Y, Huang M, Li L, Zhang H, Hou G, Jin X, Chen F, Zhu H, Li L, Zeng J, Xiao H, Zhou A, Feng L, Gao Y, Liu G. Longitudinal integrative cell-free DNA analysis in gestational diabetes mellitus. Cell Rep Med 2024:101660. [PMID: 39059385 DOI: 10.1016/j.xcrm.2024.101660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 05/13/2024] [Accepted: 07/03/2024] [Indexed: 07/28/2024]
Abstract
Gestational diabetes mellitus (GDM) presents varied manifestations throughout pregnancy and poses a complex clinical challenge. High-depth cell-free DNA (cfDNA) sequencing analysis holds promise in advancing our understanding of GDM pathogenesis and prediction. In 299 women with GDM and 299 matched healthy pregnant women, distinct cfDNA fragment characteristics associated with GDM are identified throughout pregnancy. Integrating cfDNA profiles with lipidomic and single-cell transcriptomic data elucidates functional changes linked to altered lipid metabolism processes in GDM. Transcription start site (TSS) scores in 50 feature genes are used as the cfDNA signature to distinguish GDM cases from controls effectively. Notably, differential coverage of the islet acinar marker gene PRSS1 emerges as a valuable biomarker for GDM. A specialized neural network model is developed, predicting GDM occurrence and validated across two independent cohorts. This research underscores the high-depth cfDNA early prediction and characterization of GDM, offering insights into its molecular underpinnings and potential clinical applications.
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Affiliation(s)
- Zhuangyuan Tang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; BGI Research, Shenzhen 518083, China
| | - Shuo Wang
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Xi Li
- BGI Research, Shenzhen 518083, China; BGI Research, Wuhan 430074, China
| | | | | | - Jing Wang
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Qingshi Ye
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; BGI Research, Shenzhen 518083, China
| | - Jinnan Liu
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | | | - Yuanyuan Guo
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | | | - Huikun Liu
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Lingyao Guan
- China National GeneBank, BGI, Shenzhen 518083, China
| | - Chang Jiang
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Jiayu Chen
- China National GeneBank, BGI, Shenzhen 518083, China
| | - Min Li
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Fangyi Ren
- China National GeneBank, BGI, Shenzhen 518083, China
| | - Yu Zhang
- Tianjin Women and Children's Health Center, Tianjin 300070, China
| | - Minjuan Huang
- China National GeneBank, BGI, Shenzhen 518083, China
| | - Lingguo Li
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; BGI Research, Shenzhen 518083, China
| | | | | | - Xin Jin
- Tianjin Women and Children's Health Center, Tianjin 300070, China; The Innovation Centre of Ministry of Education for Development and Diseases, School of Medicine, South China University of Technology, Guangzhou 510006, China
| | | | | | - Linxuan Li
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China; BGI Research, Shenzhen 518083, China
| | - Jingyu Zeng
- BGI Research, Shenzhen 518083, China; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Han Xiao
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Aifen Zhou
- Institute of Maternal and Child Health, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Obstetrics, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lingyan Feng
- Tianjin Women and Children's Health Center, Tianjin 300070, China.
| | - Ya Gao
- BGI Research, Shenzhen 518083, China; Shenzhen Engineering Laboratory for Birth Defects Screening, Shenzhen, China.
| | - Gongshu Liu
- Tianjin Women and Children's Health Center, Tianjin 300070, China.
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3
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Grenko CM, Taylor HJ, Bonnycastle LL, Xue D, Lee BN, Weiss Z, Yan T, Swift AJ, Mansell EC, Lee A, Robertson CC, Narisu N, Erdos MR, Chen S, Collins FS, Taylor DL. Single-cell transcriptomic profiling of human pancreatic islets reveals genes responsive to glucose exposure over 24 h. Diabetologia 2024:10.1007/s00125-024-06214-4. [PMID: 38967666 DOI: 10.1007/s00125-024-06214-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 05/08/2024] [Indexed: 07/06/2024]
Abstract
AIMS/HYPOTHESIS Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes. METHODS We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-βH1 cells, followed by a glucose-stimulated insulin secretion assay. RESULTS In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA1c, random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three (ERO1B, HNRNPA2B1 and RHOBTB3) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-βH1 cells. CONCLUSIONS/INTERPRETATION The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production. DATA AVAILABILITY The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository ( https://zenodo.org/ ) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse .
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Affiliation(s)
- Caleb M Grenko
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, USA
| | - Henry J Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
- Heart and Lung Research Institute, University of Cambridge, Cambridge, UK.
| | - Lori L Bonnycastle
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dongxiang Xue
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA
- Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA
| | - Brian N Lee
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Zoe Weiss
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Tingfen Yan
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Amy J Swift
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Erin C Mansell
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Angela Lee
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Catherine C Robertson
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael R Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA
- Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA
| | - Francis S Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
| | - D Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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4
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Maestas MM, Ishahak M, Augsornworawat P, Veronese-Paniagua DA, Maxwell KG, Velazco-Cruz L, Marquez E, Sun J, Shunkarova M, Gale SE, Urano F, Millman JR. Identification of unique cell type responses in pancreatic islets to stress. Nat Commun 2024; 15:5567. [PMID: 38956087 PMCID: PMC11220140 DOI: 10.1038/s41467-024-49724-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 06/14/2024] [Indexed: 07/04/2024] Open
Abstract
Diabetes involves the death or dysfunction of pancreatic β-cells. Analysis of bulk sequencing from human samples and studies using in vitro and in vivo models suggest that endoplasmic reticulum and inflammatory signaling play an important role in diabetes progression. To better characterize cell type-specific stress response, we perform multiplexed single-cell RNA sequencing to define the transcriptional signature of primary human islet cells exposed to endoplasmic reticulum and inflammatory stress. Through comprehensive pair-wise analysis of stress responses across pancreatic endocrine and exocrine cell types, we define changes in gene expression for each cell type under different diabetes-associated stressors. We find that β-, α-, and ductal cells have the greatest transcriptional response. We utilize stem cell-derived islets to study islet health through the candidate gene CIB1, which was upregulated under stress in primary human islets. Our findings provide insights into cell type-specific responses to diabetes-associated stress and establish a resource to identify targets for diabetes therapeutics.
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Affiliation(s)
- Marlie M Maestas
- Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University School of Medicine, MSC 8127-057-08, 660 South Euclid Avenue, St. Louis, MO, 63110, USA
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Matthew Ishahak
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Punn Augsornworawat
- Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, 10700, Thailand
| | - Daniel A Veronese-Paniagua
- Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University School of Medicine, MSC 8127-057-08, 660 South Euclid Avenue, St. Louis, MO, 63110, USA
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Kristina G Maxwell
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, USA
| | - Leonardo Velazco-Cruz
- Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University School of Medicine, MSC 8127-057-08, 660 South Euclid Avenue, St. Louis, MO, 63110, USA
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Erica Marquez
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, USA
| | - Jiameng Sun
- Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University School of Medicine, MSC 8127-057-08, 660 South Euclid Avenue, St. Louis, MO, 63110, USA
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Mira Shunkarova
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Sarah E Gale
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
| | - Fumihiko Urano
- Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University School of Medicine, MSC 8127-057-08, 660 South Euclid Avenue, St. Louis, MO, 63110, USA
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, USA
| | - Jeffrey R Millman
- Roy and Diana Vagelos Division of Biology and Biomedical Sciences, Washington University School of Medicine, MSC 8127-057-08, 660 South Euclid Avenue, St. Louis, MO, 63110, USA.
- Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, MSC 8127-057-08, St. Louis, USA.
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, USA.
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5
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Delgadillo-Silva LF, Tasöz E, Singh SP, Chawla P, Georgiadou E, Gompf A, Rutter GA, Ninov N. Optogenetic β cell interrogation in vivo reveals a functional hierarchy directing the Ca 2+ response to glucose supported by vitamin B6. SCIENCE ADVANCES 2024; 10:eado4513. [PMID: 38924394 PMCID: PMC11204215 DOI: 10.1126/sciadv.ado4513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/20/2024] [Indexed: 06/28/2024]
Abstract
Coordination of cellular activity through Ca2+ enables β cells to secrete precise quantities of insulin. To explore how the Ca2+ response is orchestrated in space and time, we implement optogenetic systems to probe the role of individual β cells in the glucose response. By targeted β cell activation/inactivation in zebrafish, we reveal a hierarchy of cells, each with a different level of influence over islet-wide Ca2+ dynamics. First-responder β cells lie at the top of the hierarchy, essential for initiating the first-phase Ca2+ response. Silencing first responders impairs the Ca2+ response to glucose. Conversely, selective activation of first responders demonstrates their increased capability to raise pan-islet Ca2+ levels compared to followers. By photolabeling and transcriptionally profiling β cells that differ in their thresholds to a glucose-stimulated Ca2+ response, we highlight vitamin B6 production as a signature pathway of first responders. We further define an evolutionarily conserved requirement for vitamin B6 in enabling the Ca2+ response to glucose in mammalian systems.
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Affiliation(s)
- Luis Fernando Delgadillo-Silva
- Centre for Regenerative Therapies TU Dresden, Dresden 01307, Germany
- Paul Langerhans Institute Dresden of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus of TU Dresden, German Center for Diabetes Research (DZD e.V.), Dresden 01307, Germany
- Cardiometabolic Axis, CR-CHUM, and University of Montreal, Montreal, QC, Canada; 1IRIBHM, Université Libre de Bruxelles (ULB), 1070 Brussels, Belgium
| | - Emirhan Tasöz
- Centre for Regenerative Therapies TU Dresden, Dresden 01307, Germany
- Paul Langerhans Institute Dresden of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus of TU Dresden, German Center for Diabetes Research (DZD e.V.), Dresden 01307, Germany
| | | | - Prateek Chawla
- Centre for Regenerative Therapies TU Dresden, Dresden 01307, Germany
| | - Eleni Georgiadou
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Faculty of Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London W12 ONN, UK
| | - Anne Gompf
- Centre for Regenerative Therapies TU Dresden, Dresden 01307, Germany
| | - Guy A. Rutter
- Cardiometabolic Axis, CR-CHUM, and University of Montreal, Montreal, QC, Canada; 1IRIBHM, Université Libre de Bruxelles (ULB), 1070 Brussels, Belgium
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Faculty of Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital, London W12 ONN, UK
- Lee Kong Chian School of Medicine, Nanyang Technological College, Singapore, Singapore
| | - Nikolay Ninov
- Centre for Regenerative Therapies TU Dresden, Dresden 01307, Germany
- Paul Langerhans Institute Dresden of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus of TU Dresden, German Center for Diabetes Research (DZD e.V.), Dresden 01307, Germany
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6
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Ewald JD, Lu Y, Ellis CE, Worton J, Kolic J, Sasaki S, Zhang D, Dos Santos T, Spigelman AF, Bautista A, Dai XQ, Lyon JG, Smith NP, Wong JM, Rajesh V, Sun H, Sharp SA, Rogalski JC, Moravcova R, Cen HH, Manning Fox JE, Atlas E, Bruin JE, Mulvihill EE, Verchere CB, Foster LJ, Gloyn AL, Johnson JD, Pepper AR, Lynn FC, Xia J, MacDonald PE. HumanIslets: An integrated platform for human islet data access and analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.19.599613. [PMID: 38948734 PMCID: PMC11212983 DOI: 10.1101/2024.06.19.599613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.
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Affiliation(s)
- Jessica D Ewald
- Institute of Parasitology, McGill University, Montreal, QC
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yao Lu
- Institute of Parasitology, McGill University, Montreal, QC
| | - Cara E Ellis
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Jessica Worton
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Surgery, University of Alberta, Edmonton, AB
| | - Jelena Kolic
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Shugo Sasaki
- Diabetes Research Group, BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Surgery, School of Biomedical Engineering, University of British Columbia, Vancouver, BC
| | - Dahai Zhang
- Diabetes Research Group, BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Surgery, School of Biomedical Engineering, University of British Columbia, Vancouver, BC
| | - Theodore Dos Santos
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Aliya F Spigelman
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Austin Bautista
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
| | - Xiao-Qing Dai
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - James G Lyon
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
| | - Nancy P Smith
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Jordan M Wong
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Surgery, University of Alberta, Edmonton, AB
| | - Varsha Rajesh
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - Han Sun
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - Seth A Sharp
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - Jason C Rogalski
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Renata Moravcova
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Haoning H Cen
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Jocelyn E Manning Fox
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Ella Atlas
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON
| | - Jennifer E Bruin
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, ON
| | - Erin E Mulvihill
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, ON
- University of Ottawa Heart Institute, Ottawa, ON
| | - C Bruce Verchere
- Department of Surgery, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, BC
- Department of Pathology and Laboratory Medicine, BC Children's Hospital Research Institute and University of British Columbia, Vancouver, BC
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC
| | - Leonard J Foster
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Anna L Gloyn
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - James D Johnson
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Andrew R Pepper
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Surgery, University of Alberta, Edmonton, AB
| | - Francis C Lynn
- Diabetes Research Group, BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Surgery, School of Biomedical Engineering, University of British Columbia, Vancouver, BC
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, QC
| | - Patrick E MacDonald
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
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7
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Beyer ASL, Kaemmerer D, Sänger J, Lupp A. Expression of FAM159B in Humans, Rats, and Mice: A Cross-species Examination. J Histochem Cytochem 2024:221554241262368. [PMID: 38907656 DOI: 10.1369/00221554241262368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2024] Open
Abstract
Little is known about the adaptor protein FAM159B. To determine whether FAM159B expression findings in rats or mice can be extrapolated to humans, we compared FAM159B expression in healthy tissue samples from all three species using immunohistochemistry. Despite variations in expression intensity, similar FAM159B expression patterns were observed in most organs across species. The most prominent species difference was noted in pancreatic islets; while FAM159B expression was limited to single cells on the outer edges in mice and rats, it was detectable across entire islets in humans. Double-labeling immunohistochemistry revealed partial overlap of FAM159B expression with that of insulin, glucagon, and somatostatin in human islets. By contrast, FAM159B showed complete colocalization with only somatostatin in rats and mice. An additional analysis of FAM159B expression in lean and obese Zucker rats revealed larger islet areas due to increased β-cell mass in obese rats, which was accompanied by a smaller percentage of FAM159B-positive δ-cells per islet area. Beyond the known differences in islet architecture across species, our results point to larger dissimilarities in blood glucose regulation between rodents and humans than generally assumed. Moreover, findings regarding FAM159B expression (and function) cannot be directly transferred between rodents and humans.
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Affiliation(s)
| | - Daniel Kaemmerer
- Department of General and Visceral Surgery, Zentralklinik Bad Berka, Bad Berka, Germany
| | - Jörg Sänger
- Laboratory of Pathology and Cytology Bad Berka, Bad Berka, Germany
| | - Amelie Lupp
- Institute of Pharmacology and Toxicology, Jena University Hospital, Jena, Germany
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8
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Yu V, Yong F, Marta A, Khadayate S, Osakwe A, Bhattacharya S, Varghese SS, Chabosseau P, Tabibi SM, Chen K, Georgiadou E, Parveen N, Suleiman M, Stamoulis Z, Marselli L, De Luca C, Tesi M, Ostinelli G, Delgadillo-Silva L, Wu X, Hatanaka Y, Montoya A, Elliott J, Patel B, Demchenko N, Whilding C, Hajkova P, Shliaha P, Kramer H, Ali Y, Marchetti P, Sladek R, Dhawan S, Withers DJ, Rutter GA, Millership SJ. Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity. Diabetologia 2024; 67:1079-1094. [PMID: 38512414 PMCID: PMC11058053 DOI: 10.1007/s00125-024-06123-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 01/09/2024] [Indexed: 03/23/2024]
Abstract
AIMS/HYPOTHESIS Beta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly connected 'hub' cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility, which we explore here by focusing on the imprinted gene Nnat (encoding neuronatin [NNAT]), which is required for normal insulin synthesis and secretion. METHODS Single-cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing enhanced GFP under the control of the Nnat enhancer/promoter regions were generated for FACS of beta cells and downstream analysis of CpG methylation by bisulphite sequencing and RNA-seq, respectively. Animals deleted for the de novo methyltransferase DNA methyltransferase 3 alpha (DNMT3A) from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 AM and Cal-590 AM. Insulin secretion was measured using homogeneous time-resolved fluorescence imaging. RESULTS Nnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic datasets demonstrated the early establishment of Nnat-positive and -negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a subpopulation specialised for insulin production, and were diminished in db/db mice. 'Hub' cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialisation. CONCLUSIONS/INTERPRETATION These findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes. DATA AVAILABILITY The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD048465.
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Affiliation(s)
- Vanessa Yu
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Fiona Yong
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore
| | - Angellica Marta
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | | | - Adrien Osakwe
- Quantitative Life Sciences Program, McGill University, Montréal, QC, Canada
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Sneha S Varghese
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA
| | - Pauline Chabosseau
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Sayed M Tabibi
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Keran Chen
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
- Biomedical Research Centre, School of Biological Sciences, University of East Anglia, Norwich, UK
| | - Eleni Georgiadou
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Nazia Parveen
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA
| | - Mara Suleiman
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Zoe Stamoulis
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
- Medical Sciences Division, University of Oxford, Oxford, UK
| | - Lorella Marselli
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Carmela De Luca
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Marta Tesi
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Giada Ostinelli
- CHUM Research Center and Faculty of Medicine, University of Montréal, Montréal, QC, Canada
| | - Luis Delgadillo-Silva
- CHUM Research Center and Faculty of Medicine, University of Montréal, Montréal, QC, Canada
| | - Xiwei Wu
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Yuki Hatanaka
- MRC Laboratory of Medical Sciences, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | | | | | | | - Nikita Demchenko
- MRC Laboratory of Medical Sciences, London, UK
- Imaging Resource Facility, Research Operations, St George's, University of London, London, UK
| | | | - Petra Hajkova
- MRC Laboratory of Medical Sciences, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | | | | | - Yusuf Ali
- Nutrition, Metabolism and Health Programme & Centre for Microbiome Medicine, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Republic of Singapore
- Singapore Eye Research Institute (SERI), Singapore General Hospital, Singapore, Republic of Singapore
- Clinical Research Unit, Khoo Teck Puat Hospital, National Healthcare Group, Singapore, Republic of Singapore
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy
| | - Robert Sladek
- Quantitative Life Sciences Program, McGill University, Montréal, QC, Canada
- Departments of Medicine and Human Genetics, McGill University, Montréal, QC, Canada
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA
| | - Dominic J Withers
- MRC Laboratory of Medical Sciences, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Guy A Rutter
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore.
- CHUM Research Center and Faculty of Medicine, University of Montréal, Montréal, QC, Canada.
| | - Steven J Millership
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
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9
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Di Piazza E, Todi L, Di Giuseppe G, Soldovieri L, Ciccarelli G, Brunetti M, Quero G, Alfieri S, Tondolo V, Pontecorvi A, Gasbarrini A, Nista EC, Giaccari A, Pani G, Mezza T. Advancing Diabetes Research: A Novel Islet Isolation Method from Living Donors. Int J Mol Sci 2024; 25:5936. [PMID: 38892122 PMCID: PMC11172646 DOI: 10.3390/ijms25115936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 05/23/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open
Abstract
Pancreatic islet isolation is critical for type 2 diabetes research. Although -omics approaches have shed light on islet molecular profiles, inconsistencies persist; on the other hand, functional studies are essential, but they require reliable and standardized isolation methods. Here, we propose a simplified protocol applied to very small-sized samples collected from partially pancreatectomized living donors. Islet isolation was performed by digesting tissue specimens collected during surgery within a collagenase P solution, followed by a Lympholyte density gradient separation; finally, functional assays and staining with dithizone were carried out. Isolated pancreatic islets exhibited functional responses to glucose and arginine stimulation mirroring donors' metabolic profiles, with insulin secretion significantly decreasing in diabetic islets compared to non-diabetic islets; conversely, proinsulin secretion showed an increasing trend from non-diabetic to diabetic islets. This novel islet isolation method from living patients undergoing partial pancreatectomy offers a valuable opportunity for targeted study of islet physiology, with the primary advantage of being time-effective and successfully preserving islet viability and functionality. It enables the generation of islet preparations that closely reflect donors' clinical profiles, simplifying the isolation process and eliminating the need for a Ricordi chamber. Thus, this method holds promises for advancing our understanding of diabetes and for new personalized pharmacological approaches.
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Affiliation(s)
- Eleonora Di Piazza
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
| | - Laura Todi
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
| | - Gianfranco Di Giuseppe
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Laura Soldovieri
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Gea Ciccarelli
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Michela Brunetti
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Giuseppe Quero
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
- Digestive Surgery Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Digestive Surgery Unit, Ospedale Isola Tiberina—Gemelli Isola, 00186 Roma, Italy
| | - Sergio Alfieri
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
- Digestive Surgery Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Digestive Surgery Unit, Ospedale Isola Tiberina—Gemelli Isola, 00186 Roma, Italy
| | - Vincenzo Tondolo
- Digestive Surgery Unit, Ospedale Isola Tiberina—Gemelli Isola, 00186 Roma, Italy
| | - Alfredo Pontecorvi
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Antonio Gasbarrini
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
- Pancreas Unit, CEMAD Centro Malattie dell’Apparato Digerente, Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
| | - Enrico Celestino Nista
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
- Pancreas Unit, CEMAD Centro Malattie dell’Apparato Digerente, Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
| | - Andrea Giaccari
- Endocrinology and Diabetology Unit, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Giovambattista Pani
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
| | - Teresa Mezza
- Department of Medicine and Translational Surgery, General Pathology Section, Università Cattolica del Sacro Cuore, 00168 Roma, Italy
- Pancreas Unit, CEMAD Centro Malattie dell’Apparato Digerente, Medicina Interna e Gastroenterologia, Fondazione Policlinico Universitario Gemelli IRCCS, 00168 Roma, Italy
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10
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Zhao Y, Ansarullah, Kumar P, Mahoney JM, He H, Baker C, George J, Li S. Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595431. [PMID: 38826370 PMCID: PMC11142180 DOI: 10.1101/2024.05.22.595431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic β-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting β-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to β-cell dysfunction, we investigated single-cell gene expression changes in β-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.
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Affiliation(s)
- Yue Zhao
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Ansarullah
- Center for Biometric Analysis, The Jackson Laboratory, Bar Harbor, ME, USA
| | - Parveen Kumar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - Hao He
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Candice Baker
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Joshy George
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Sheng Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA
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11
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Yang K, Zhang Y, Ding J, Li Z, Zhang H, Zou F. Autoimmune CD8+ T cells in type 1 diabetes: from single-cell RNA sequencing to T-cell receptor redirection. Front Endocrinol (Lausanne) 2024; 15:1377322. [PMID: 38800484 PMCID: PMC11116783 DOI: 10.3389/fendo.2024.1377322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 04/18/2024] [Indexed: 05/29/2024] Open
Abstract
Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cell destruction and mediated primarily by autoreactive CD8+ T cells. It has been shown that only a small number of stem cell-like β cell-specific CD8+ T cells are needed to convert normal mice into T1D mice; thus, it is likely that T1D can be cured or significantly improved by modulating or altering self-reactive CD8+ T cells. However, stem cell-type, effector and exhausted CD8+ T cells play intricate and important roles in T1D. The highly diverse T-cell receptors (TCRs) also make precise and stable targeted therapy more difficult. Therefore, this review will investigate the mechanisms of autoimmune CD8+ T cells and TCRs in T1D, as well as the related single-cell RNA sequencing (ScRNA-Seq), CRISPR/Cas9, chimeric antigen receptor T-cell (CAR-T) and T-cell receptor-gene engineered T cells (TCR-T), for a detailed and clear overview. This review highlights that targeting CD8+ T cells and their TCRs may be a potential strategy for predicting or treating T1D.
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Affiliation(s)
- Kangping Yang
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yihan Zhang
- The Second Clinical Medicine School, Nanchang University, Nanchang, China
| | - Jiatong Ding
- The Second Clinical Medicine School, Nanchang University, Nanchang, China
| | - Zelin Li
- The First Clinical Medicine School, Nanchang University, Nanchang, China
| | - Hejin Zhang
- The Second Clinical Medicine School, Nanchang University, Nanchang, China
| | - Fang Zou
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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12
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Dahiya S, Saleh M, Rodriguez UA, Rajasundaram D, R Arbujas J, Hajihassani A, Yang K, Sehrawat A, Kalsi R, Yoshida S, Prasadan K, Lickert H, Hu J, Piganelli JD, Gittes GK, Esni F. Acinar to β-like cell conversion through inhibition of focal adhesion kinase. Nat Commun 2024; 15:3740. [PMID: 38702347 PMCID: PMC11068907 DOI: 10.1038/s41467-024-47972-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 04/15/2024] [Indexed: 05/06/2024] Open
Abstract
Insufficient functional β-cell mass causes diabetes; however, an effective cell replacement therapy for curing diabetes is currently not available. Reprogramming of acinar cells toward functional insulin-producing cells would offer an abundant and autologous source of insulin-producing cells. Our lineage tracing studies along with transcriptomic characterization demonstrate that treatment of adult mice with a small molecule that specifically inhibits kinase activity of focal adhesion kinase results in trans-differentiation of a subset of peri-islet acinar cells into insulin producing β-like cells. The acinar-derived insulin-producing cells infiltrate the pre-existing endocrine islets, partially restore β-cell mass, and significantly improve glucose homeostasis in diabetic mice. These findings provide evidence that inhibition of the kinase activity of focal adhesion kinase can convert acinar cells into insulin-producing cells and could offer a promising strategy for treating diabetes.
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Affiliation(s)
- Shakti Dahiya
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
| | - Mohamed Saleh
- Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Uylissa A Rodriguez
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Dhivyaa Rajasundaram
- Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Jorge R Arbujas
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Arian Hajihassani
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Kaiyuan Yang
- Institute of Diabetes and Regeneration Research, Helmholtz Munich, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Anuradha Sehrawat
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Ranjeet Kalsi
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Shiho Yoshida
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Krishna Prasadan
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Munich, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- School of Medicine, Technical University of Munich, Munich, Germany
| | - Jing Hu
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jon D Piganelli
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - George K Gittes
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Farzad Esni
- Department of Surgery, Division of Pediatric General and Thoracic Surgery, Children's Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
- School of Medicine, Technical University of Munich, Munich, Germany.
- Department of Developmental Biology, University of Pittsburgh, Pittsburgh, PA, USA.
- UPMC Hillman Cancer Center, Pittsburgh, PA, USA.
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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13
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Chong ACN, Vandana JJ, Jeng G, Li G, Meng Z, Duan X, Zhang T, Qiu Y, Duran-Struuck R, Coker K, Wang W, Li Y, Min Z, Zuo X, de Silva N, Chen Z, Naji A, Hao M, Liu C, Chen S. Checkpoint kinase 2 controls insulin secretion and glucose homeostasis. Nat Chem Biol 2024; 20:566-576. [PMID: 37945898 PMCID: PMC11062908 DOI: 10.1038/s41589-023-01466-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 10/03/2023] [Indexed: 11/12/2023]
Abstract
After the discovery of insulin, a century ago, extensive work has been done to unravel the molecular network regulating insulin secretion. Here we performed a chemical screen and identified AZD7762, a compound that potentiates glucose-stimulated insulin secretion (GSIS) of a human β cell line, healthy and type 2 diabetic (T2D) human islets and primary cynomolgus macaque islets. In vivo studies in diabetic mouse models and cynomolgus macaques demonstrated that AZD7762 enhances GSIS and improves glucose tolerance. Furthermore, genetic manipulation confirmed that ablation of CHEK2 in human β cells results in increased insulin secretion. Consistently, high-fat-diet-fed Chk2-/- mice show elevated insulin secretion and improved glucose clearance. Finally, untargeted metabolic profiling demonstrated the key role of the CHEK2-PP2A-PLK1-G6PD-PPP pathway in insulin secretion. This study successfully identifies a previously unknown insulin secretion regulating pathway that is conserved across rodents, cynomolgus macaques and human β cells in both healthy and T2D conditions.
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Affiliation(s)
- Angie Chi Nok Chong
- Department of Surgery, Weill Cornell Medicine, New York City, NY, USA
- Center for Genomic Health, Weill Cornell Medicine, New York City, NY, USA
| | - J Jeya Vandana
- Department of Surgery, Weill Cornell Medicine, New York City, NY, USA
- Center for Genomic Health, Weill Cornell Medicine, New York City, NY, USA
- Tri-Institutional PhD Program in Chemical Biology, New York City, NY, USA
| | - Ginnie Jeng
- Department of Urology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ge Li
- Department of Medicine, Weill Cornell Medicine, New York City, NY, USA
- Department of Biological Sciences, Bronx Community College, City University of New York, Bronx, NY, USA
| | - Zihe Meng
- Department of Surgery, Weill Cornell Medicine, New York City, NY, USA
- Center for Genomic Health, Weill Cornell Medicine, New York City, NY, USA
| | - Xiaohua Duan
- Department of Surgery, Weill Cornell Medicine, New York City, NY, USA
- Center for Genomic Health, Weill Cornell Medicine, New York City, NY, USA
| | - Tuo Zhang
- Department of Microbiology and Immunology, Weill Cornell Medicine, New York City, NY, USA
| | - Yunping Qiu
- Department of Medicine, Fleischer Institute for Diabetes and Metabolism, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Raimon Duran-Struuck
- Department of Pathobiology, University of Pennsylvania School of Veterinary Medicine, Philadelphia, PA, USA
| | - Kimberly Coker
- Department of Pathobiology, University of Pennsylvania School of Veterinary Medicine, Philadelphia, PA, USA
| | - Wei Wang
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Yanjing Li
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Zaw Min
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Xi Zuo
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Neranjan de Silva
- Department of Surgery, Weill Cornell Medicine, New York City, NY, USA
| | - Zhengming Chen
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, NY, USA
| | - Ali Naji
- Department of Pathobiology, University of Pennsylvania School of Veterinary Medicine, Philadelphia, PA, USA
| | - Mingming Hao
- Department of Biochemistry, Weill Cornell Medicine, New York City, NY, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York City, NY, USA.
- Center for Genomic Health, Weill Cornell Medicine, New York City, NY, USA.
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14
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Leenders F, de Koning EJP, Carlotti F. Pancreatic β-Cell Identity Change through the Lens of Single-Cell Omics Research. Int J Mol Sci 2024; 25:4720. [PMID: 38731945 PMCID: PMC11083883 DOI: 10.3390/ijms25094720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/12/2024] [Accepted: 04/17/2024] [Indexed: 05/13/2024] Open
Abstract
The main hallmark in the development of both type 1 and type 2 diabetes is a decline in functional β-cell mass. This decline is predominantly attributed to β-cell death, although recent findings suggest that the loss of β-cell identity may also contribute to β-cell dysfunction. This phenomenon is characterized by a reduced expression of key markers associated with β-cell identity. This review delves into the insights gained from single-cell omics research specifically focused on β-cell identity. It highlights how single-cell omics based studies have uncovered an unexpected level of heterogeneity among β-cells and have facilitated the identification of distinct β-cell subpopulations through the discovery of cell surface markers, transcriptional regulators, the upregulation of stress-related genes, and alterations in chromatin activity. Furthermore, specific subsets of β-cells have been identified in diabetes, such as displaying an immature, dedifferentiated gene signature, expressing significantly lower insulin mRNA levels, and expressing increased β-cell precursor markers. Additionally, single-cell omics has increased insight into the detrimental effects of diabetes-associated conditions, including endoplasmic reticulum stress, oxidative stress, and inflammation, on β-cell identity. Lastly, this review outlines the factors that may influence the identification of β-cell subpopulations when designing and performing a single-cell omics experiment.
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Affiliation(s)
| | | | - Françoise Carlotti
- Department of Internal Medicine, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (F.L.); (E.J.P.d.K.)
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15
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Hill TG, Hill DJ. The Importance of Intra-Islet Communication in the Function and Plasticity of the Islets of Langerhans during Health and Diabetes. Int J Mol Sci 2024; 25:4070. [PMID: 38612880 PMCID: PMC11012451 DOI: 10.3390/ijms25074070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 03/27/2024] [Accepted: 03/27/2024] [Indexed: 04/14/2024] Open
Abstract
Islets of Langerhans are anatomically dispersed within the pancreas and exhibit regulatory coordination between islets in response to nutritional and inflammatory stimuli. However, within individual islets, there is also multi-faceted coordination of function between individual beta-cells, and between beta-cells and other endocrine and vascular cell types. This is mediated partly through circulatory feedback of the major secreted hormones, insulin and glucagon, but also by autocrine and paracrine actions within the islet by a range of other secreted products, including somatostatin, urocortin 3, serotonin, glucagon-like peptide-1, acetylcholine, and ghrelin. Their availability can be modulated within the islet by pericyte-mediated regulation of microvascular blood flow. Within the islet, both endocrine progenitor cells and the ability of endocrine cells to trans-differentiate between phenotypes can alter endocrine cell mass to adapt to changed metabolic circumstances, regulated by the within-islet trophic environment. Optimal islet function is precariously balanced due to the high metabolic rate required by beta-cells to synthesize and secrete insulin, and they are susceptible to oxidative and endoplasmic reticular stress in the face of high metabolic demand. Resulting changes in paracrine dynamics within the islets can contribute to the emergence of Types 1, 2 and gestational diabetes.
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Affiliation(s)
- Thomas G. Hill
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
| | - David J. Hill
- Lawson Health Research Institute, St. Joseph’s Health Care, London, ON N6A 4V2, Canada;
- Departments of Medicine, Physiology and Pharmacology, Western University, London, ON N6A 3K7, Canada
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16
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Marmarelis MG, Littman R, Battaglin F, Niedzwiecki D, Venook A, Ambite JL, Galstyan A, Lenz HJ, Ver Steeg G. q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics. Commun Biol 2024; 7:400. [PMID: 38565955 PMCID: PMC11255321 DOI: 10.1038/s42003-024-06104-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 03/25/2024] [Indexed: 04/04/2024] Open
Abstract
Unlocking the full dimensionality of single-cell RNA sequencing data (scRNAseq) is the next frontier to a richer, fuller understanding of cell biology. We introduce q-diffusion, a framework for capturing the coexpression structure of an entire library of genes, improving on state-of-the-art analysis tools. The method is demonstrated via three case studies. In the first, q-diffusion helps gain statistical significance for differential effects on patient outcomes when analyzing the CALGB/SWOG 80405 randomized phase III clinical trial, suggesting precision guidance for the treatment of metastatic colorectal cancer. Secondly, q-diffusion is benchmarked against existing scRNAseq classification methods using an in vitro PBMC dataset, in which the proposed method discriminates IFN-γ stimulation more accurately. The same case study demonstrates improvements in unsupervised cell clustering with the recent Tabula Sapiens human atlas. Finally, a local distributional segmentation approach for spatial scRNAseq, driven by q-diffusion, yields interpretable structures of human cortical tissue.
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Affiliation(s)
- Myrl G Marmarelis
- Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Marina del Rey, CA, 90292, USA.
| | - Russell Littman
- University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Francesca Battaglin
- Keck School of Medicine, University of Southern California, 1975 Zonal Ave., Los Angeles, CA, 90033, USA
| | | | - Alan Venook
- University of California San Francisco, San Francisco, CA, 94143, USA
| | - Jose-Luis Ambite
- Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Marina del Rey, CA, 90292, USA
| | - Aram Galstyan
- Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Marina del Rey, CA, 90292, USA
| | - Heinz-Josef Lenz
- Keck School of Medicine, University of Southern California, 1975 Zonal Ave., Los Angeles, CA, 90033, USA
| | - Greg Ver Steeg
- Information Sciences Institute, University of Southern California, 4676 Admiralty Way, Marina del Rey, CA, 90292, USA
- University of California Riverside, Riverside, CA, 92521, USA
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17
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Fang X, Zhang Y, Miao R, Zhang Y, Yin R, Guan H, Huang X, Tian J. Single-cell sequencing: A promising approach for uncovering the characteristic of pancreatic islet cells in type 2 diabetes. Biomed Pharmacother 2024; 173:116292. [PMID: 38394848 DOI: 10.1016/j.biopha.2024.116292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 02/03/2024] [Accepted: 02/17/2024] [Indexed: 02/25/2024] Open
Abstract
Single-cell sequencing is a novel and rapidly advancing high-throughput technique that can be used to investigating genomics, transcriptomics, and epigenetics at a single-cell level. Currently, single-cell sequencing can not only be used to draw the pancreatic islet cells map and uncover the characteristics of cellular heterogeneity in type 2 diabetes, but can also be used to label and purify functional beta cells in pancreatic stem cells, improving stem cells and islet organoids therapies. In addition, this technology helps to analyze islet cell dedifferentiation and can be applied to the treatment of type 2 diabetes. In this review, we summarize the development and process of single-cell sequencing, describe the potential applications of single-cell sequencing in the field of type 2 diabetes, and discuss the prospects and limitations of single-cell sequencing to provide a new direction for exploring the pathogenesis of type 2 diabetes and finding therapeutic targets.
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Affiliation(s)
- Xinyi Fang
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China; Graduate College, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yanjiao Zhang
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Runyu Miao
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China; Graduate College, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yuxin Zhang
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Ruiyang Yin
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Huifang Guan
- College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Jilin 130117, China
| | - Xinyue Huang
- First Clinical Medical College, Changzhi Medical College, Shanxi 046013, China
| | - Jiaxing Tian
- Institute of Metabolic Diseases, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
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18
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Gu G, Brown M, Agan V, Nevills S, Hu R, Simmons A, Xu Y, Yang Y, Yagan M, Najam S, Dadi P, Sampson L, Magnuson M, Jacobson D, Lau K, Hodges E. Endocrine islet β-cell subtypes with differential function are derived from biochemically distinct embryonic endocrine islet progenitors that are regulated by maternal nutrients. RESEARCH SQUARE 2024:rs.3.rs-3946483. [PMID: 38496675 PMCID: PMC10942487 DOI: 10.21203/rs.3.rs-3946483/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Endocrine islet b cells comprise heterogenous cell subsets. Yet when/how these subsets are produced and how stable they are remain unknown. Addressing these questions is important for preventing/curing diabetes, because lower numbers of b cells with better secretory function is a high risk of this disease. Using combinatorial cell lineage tracing, scRNA-seq, and DNA methylation analysis, we show here that embryonic islet progenitors with distinct gene expression and DNA methylation produce b-cell subtypes of different function and viability in adult mice. The subtype with better function is enriched for genes involved in vesicular production/trafficking, stress response, and Ca2+-secretion coupling, which further correspond to differential DNA methylation in putative enhancers of these genes. Maternal overnutrition, a major diabetes risk factor, reduces the proportion of endocrine progenitors of the b-cell subtype with better-function via deregulating DNA methyl transferase 3a. Intriguingly, the gene signature that defines mouse b-cell subtypes can reliably divide human cells into two sub-populations while the proportion of b cells with better-function is reduced in diabetic donors. The implication of these results is that modulating DNA methylation in islet progenitors using maternal food supplements can be explored to improve b-cell function in the prevention and therapy of diabetes.
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Affiliation(s)
| | | | | | | | | | | | | | - Yilin Yang
- Vanderbilty University School of Medicine
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19
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Coykendall VM, Qian MF, Tellez K, Bautista A, Bevacqua RJ, Gu X, Hang Y, Neukam M, Zhao W, Chang C, MacDonald PE, Kim SK. RFX6 Maintains Gene Expression and Function of Adult Human Islet α-Cells. Diabetes 2024; 73:448-460. [PMID: 38064570 PMCID: PMC10882151 DOI: 10.2337/db23-0483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/21/2023] [Indexed: 02/22/2024]
Abstract
Mutations in the gene encoding the transcription factor regulatory factor X-box binding 6 (RFX6) are associated with human diabetes. Within pancreatic islets, RFX6 expression is most abundant in islet α-cells, and α-cell RFX6 expression is altered in diabetes. However, the roles of RFX6 in regulating gene expression, glucagon output, and other crucial human adult α-cell functions are not yet understood. We developed a method for selective genetic targeting of human α-cells and assessed RFX6-dependent α-cell function. RFX6 suppression with RNA interference led to impaired α-cell exocytosis and dysregulated glucagon secretion in vitro and in vivo. By contrast, these phenotypes were not observed with RFX6 suppression across all islet cells. Transcriptomics in α-cells revealed RFX6-dependent expression of genes governing nutrient sensing, hormone processing, and secretion, with some of these exclusively expressed in human α-cells. Mapping of RFX6 DNA-binding sites in primary human islet cells identified a subset of direct RFX6 target genes. Together, these data unveil RFX6-dependent genetic targets and mechanisms crucial for regulating adult human α-cell function. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Vy M.N. Coykendall
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Mollie F. Qian
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Krissie Tellez
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Austin Bautista
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Romina J. Bevacqua
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Xueying Gu
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Yan Hang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA
| | - Martin Neukam
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Weichen Zhao
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Charles Chang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
| | - Patrick E. MacDonald
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Seung K. Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
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20
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Farrim MI, Gomes A, Milenkovic D, Menezes R. Gene expression analysis reveals diabetes-related gene signatures. Hum Genomics 2024; 18:16. [PMID: 38326874 PMCID: PMC10851551 DOI: 10.1186/s40246-024-00582-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 02/01/2024] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction. METHODS A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network. RESULTS Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets. CONCLUSIONS This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.
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Affiliation(s)
- M I Farrim
- CBIOS, Universidade Lusófona's Research Center for Biosciences & Health Technologies, Universidade Lusófona, Lisbon, Portugal
- Universidad de Alcalá, Escuela de Doctorado, Madrid, Spain
| | - A Gomes
- CBIOS, Universidade Lusófona's Research Center for Biosciences & Health Technologies, Universidade Lusófona, Lisbon, Portugal
| | - D Milenkovic
- Department of Nutrition, University of California Davis, Davis, USA
| | - R Menezes
- CBIOS, Universidade Lusófona's Research Center for Biosciences & Health Technologies, Universidade Lusófona, Lisbon, Portugal.
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21
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Camunas-Soler J. Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca 2+ imaging and electrophysiology. Biophys Rev 2024; 16:89-107. [PMID: 38495444 PMCID: PMC10937895 DOI: 10.1007/s12551-023-01174-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 11/29/2023] [Indexed: 03/19/2024] Open
Abstract
I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.
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Affiliation(s)
- Joan Camunas-Soler
- Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, University of Gothenburg, 405 30 Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, Sahlgrenska Academy, University of Gothenburg, 405 30 Gothenburg, Sweden
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22
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Roy G, Syed R, Lazaro O, Robertson S, McCabe SD, Rodriguez D, Mawla AM, Johnson TS, Kalwat MA. Identification of type 2 diabetes- and obesity-associated human β-cells using deep transfer learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.18.576260. [PMID: 38328172 PMCID: PMC10849510 DOI: 10.1101/2024.01.18.576260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Diabetes affects >10% of adults worldwide and is caused by impaired production or response to insulin, resulting in chronic hyperglycemia. Pancreatic islet β-cells are the sole source of endogenous insulin and our understanding of β-cell dysfunction and death in type 2 diabetes (T2D) is incomplete. Single-cell RNA-seq data supports heterogeneity as an important factor in β-cell function and survival. However, it is difficult to identify which β-cell phenotypes are critical for T2D etiology and progression. Our goal was to prioritize specific disease-related β-cell subpopulations to better understand T2D pathogenesis and identify relevant genes for targeted therapeutics. To address this, we applied a deep transfer learning tool, DEGAS, which maps disease associations onto single-cell RNA-seq data from bulk expression data. Independent runs of DEGAS using T2D or obesity status identified distinct β-cell subpopulations. A singular cluster of T2D-associated β-cells was identified; however, β-cells with high obese-DEGAS scores contained two subpopulations derived largely from either non-diabetic or T2D donors. The obesity-associated non-diabetic cells were enriched for translation and unfolded protein response genes compared to T2D cells. We selected DLK1 for validation by immunostaining in human pancreas sections from healthy and T2D donors. DLK1 was heterogeneously expressed among β-cells and appeared depleted from T2D islets. In conclusion, DEGAS has the potential to advance our holistic understanding of the β-cell transcriptomic phenotypes, including features that distinguish β-cells in obese non-diabetic or lean T2D states. Future work will expand this approach to additional human islet omics datasets to reveal the complex multicellular interactions driving T2D.
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23
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Sturgill D, Wang L, Arda HE. PancrESS - a meta-analysis resource for understanding cell-type specific expression in the human pancreas. BMC Genomics 2024; 25:76. [PMID: 38238687 PMCID: PMC10797729 DOI: 10.1186/s12864-024-09964-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND The human pancreas is composed of specialized cell types producing hormones and enzymes critical to human health. These specialized functions are the result of cell type-specific transcriptional programs which manifest in cell-specific gene expression. Understanding these programs is essential to developing therapies for pancreatic disorders. Transcription in the human pancreas has been widely studied by single-cell RNA technologies, however the diversity of protocols and analysis methods hinders their interpretability in the aggregate. RESULTS In this work, we perform a meta-analysis of pancreatic single-cell RNA sequencing data. We present a database for reference transcriptome abundances and cell-type specificity metrics. This database facilitates the identification and definition of marker genes within the pancreas. Additionally, we introduce a versatile tool which is freely available as an R package, and should permit integration into existing workflows. Our tool accepts count data files generated by widely-used single-cell gene expression platforms in their original format, eliminating an additional pre-formatting step. Although we designed it to calculate expression specificity of pancreas cell types, our tool is agnostic to the biological source of count data, extending its applicability to other biological systems. CONCLUSIONS Our findings enhance the current understanding of expression specificity within the pancreas, surpassing previous work in terms of scope and detail. Furthermore, our database and tool enable researchers to perform similar calculations in diverse biological systems, expanding the applicability of marker gene identification and facilitating comparative analyses.
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Affiliation(s)
- David Sturgill
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA
| | - Li Wang
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA
| | - H Efsun Arda
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.
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24
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Shao M, Zhang W, Li Y, Tang L, Hao ZZ, Liu S. Patch-seq: Advances and Biological Applications. Cell Mol Neurobiol 2023; 44:8. [PMID: 38123823 DOI: 10.1007/s10571-023-01436-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/24/2023] [Indexed: 12/23/2023]
Abstract
Multimodal analysis of gene-expression patterns, electrophysiological properties, and morphological phenotypes at the single-cell/single-nucleus level has been arduous because of the diversity and complexity of neurons. The emergence of Patch-sequencing (Patch-seq) directly links transcriptomics, morphology, and electrophysiology, taking neuroscience research to a multimodal era. In this review, we summarized the development of Patch-seq and recent applications in the cortex, hippocampus, and other nervous systems. Through generating multimodal cell type atlases, targeting specific cell populations, and correlating transcriptomic data with phenotypic information, Patch-seq has provided new insight into outstanding questions in neuroscience. We highlight the challenges and opportunities of Patch-seq in neuroscience and hope to shed new light on future neuroscience research.
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Affiliation(s)
- Mingting Shao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Wei Zhang
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Ye Li
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Lei Tang
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Zhao-Zhe Hao
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China
| | - Sheng Liu
- State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou, 510060, China.
- Guangdong Province Key Laboratory of Brain Function and Disease, Guangzhou, 510080, China.
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25
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Walker JT, Saunders DC, Rai V, Chen HH, Orchard P, Dai C, Pettway YD, Hopkirk AL, Reihsmann CV, Tao Y, Fan S, Shrestha S, Varshney A, Petty LE, Wright JJ, Ventresca C, Agarwala S, Aramandla R, Poffenberger G, Jenkins R, Mei S, Hart NJ, Phillips S, Kang H, Greiner DL, Shultz LD, Bottino R, Liu J, Below JE, Parker SCJ, Powers AC, Brissova M. Genetic risk converges on regulatory networks mediating early type 2 diabetes. Nature 2023; 624:621-629. [PMID: 38049589 DOI: 10.1038/s41586-023-06693-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 09/28/2023] [Indexed: 12/06/2023]
Abstract
Type 2 diabetes mellitus (T2D), a major cause of worldwide morbidity and mortality, is characterized by dysfunction of insulin-producing pancreatic islet β cells1,2. T2D genome-wide association studies (GWAS) have identified hundreds of signals in non-coding and β cell regulatory genomic regions, but deciphering their biological mechanisms remains challenging3-5. Here, to identify early disease-driving events, we performed traditional and multiplexed pancreatic tissue imaging, sorted-islet cell transcriptomics and islet functional analysis of early-stage T2D and control donors. By integrating diverse modalities, we show that early-stage T2D is characterized by β cell-intrinsic defects that can be proportioned into gene regulatory modules with enrichment in signals of genetic risk. After identifying the β cell hub gene and transcription factor RFX6 within one such module, we demonstrated multiple layers of genetic risk that converge on an RFX6-mediated network to reduce insulin secretion by β cells. RFX6 perturbation in primary human islet cells alters β cell chromatin architecture at regions enriched for T2D GWAS signals, and population-scale genetic analyses causally link genetically predicted reduced RFX6 expression with increased T2D risk. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs and individuals, and thus we anticipate that this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits using GWAS data.
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Affiliation(s)
- John T Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Diane C Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Hung-Hsin Chen
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chunhua Dai
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yasminye D Pettway
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alexander L Hopkirk
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Conrad V Reihsmann
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yicheng Tao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Simin Fan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Shristi Shrestha
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Lauren E Petty
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan J Wright
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christa Ventresca
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Samir Agarwala
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Radhika Aramandla
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Greg Poffenberger
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Regina Jenkins
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shaojun Mei
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nathaniel J Hart
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sharon Phillips
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dale L Greiner
- Department of Molecular Medicine, Diabetes Center of Excellence, University of Massachusetts Medical School, Worcester, MA, USA
| | | | - Rita Bottino
- Imagine Pharma, Devon, PA, USA
- Institute of Cellular Therapeutics, Allegheny-Singer Research Institute, Allegheny Health Network, Pittsburgh, PA, USA
| | - Jie Liu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA.
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Alvin C Powers
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN, USA.
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- VA Tennessee Valley Healthcare System, Nashville, TN, USA.
| | - Marcela Brissova
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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Yu V, Yong F, Marta A, Khadayate S, Osakwe A, Bhattacharya S, Varghese SS, Chabosseau P, Tabibi SM, Chen K, Georgiadou E, Parveen N, Suleiman M, Stamoulis Z, Marselli L, De Luca C, Tesi M, Ostinelli G, Delgadillo-Silva L, Wu X, Hatanaka Y, Montoya A, Elliott J, Patel B, Demchenko N, Whilding C, Hajkova P, Shliaha P, Kramer H, Ali Y, Marchetti P, Sladek R, Dhawan S, Withers DJ, Rutter GA, Millership SJ. Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.04.527050. [PMID: 38076935 PMCID: PMC10705251 DOI: 10.1101/2023.02.04.527050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Aims/hypothesis Beta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly-connected 'hub' cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility which we explore here by focussing on the imprinted gene neuronatin (Nnat), which is required for normal insulin synthesis and secretion. Methods Single cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing eGFP under the control of the Nnat enhancer/promoter regions were generated for fluorescence-activated cell (FAC) sorting of beta cells and downstream analysis of CpG methylation by bisulphite and RNA sequencing, respectively. Animals deleted for the de novo methyltransferase, DNMT3A from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 and Cal-590. Insulin secretion was measured using Homogeneous Time Resolved Fluorescence Imaging. Results Nnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic data sets demonstrated the early establishment of Nnat-positive and negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a sub-population specialised for insulin production, reminiscent of recently-described "βHI" cells and were diminished in db/db mice. 'Hub' cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialization. Conclusions/interpretation These findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may thus contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes.
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Affiliation(s)
- Vanessa Yu
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Fiona Yong
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, 637553, Singapore
| | - Angellica Marta
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Sanjay Khadayate
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Adrien Osakwe
- Departments of Medicine, Human Genetics and Quantitative Life Sciences, McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada
| | - Supriyo Bhattacharya
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Sneha S. Varghese
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Pauline Chabosseau
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Sayed M. Tabibi
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Keran Chen
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Eleni Georgiadou
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Nazia Parveen
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Mara Suleiman
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa 56126, Italy
| | - Zoe Stamoulis
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Lorella Marselli
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa 56126, Italy
| | - Carmela De Luca
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa 56126, Italy
| | - Marta Tesi
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa 56126, Italy
| | - Giada Ostinelli
- CHUM Research Center and Faculty of Medicine, University of Montréal, 900 Rue St Denis, Montréal, H2X OA9, QC, Canada
| | - Luis Delgadillo-Silva
- CHUM Research Center and Faculty of Medicine, University of Montréal, 900 Rue St Denis, Montréal, H2X OA9, QC, Canada
| | - Xiwei Wu
- Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Yuki Hatanaka
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Alex Montoya
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - James Elliott
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Bhavik Patel
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Nikita Demchenko
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Chad Whilding
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Petra Hajkova
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Pavel Shliaha
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Holger Kramer
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
| | - Yusuf Ali
- Nutrition, Metabolism and Health Programme & Centre for Microbiome Medicine, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, 308232
- Singapore Eye Research Institute (SERI), Singapore General Hospital, Singapore, 168751
- Clinical Research Unit, Khoo Teck Puat Hospital, National Healthcare Group, Singapore, 768828
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa 56126, Italy
| | - Robert Sladek
- Departments of Medicine, Human Genetics and Quantitative Life Sciences, McGill University and Genome Quebec Innovation Centre, Montreal, QC, Canada
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, 1500 E Duarte Road, Duarte, CA 91010, USA
| | - Dominic J. Withers
- MRC Laboratory of Medical Sciences, Du Cane Road, London, W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
| | - Guy A. Rutter
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, 637553, Singapore
- CHUM Research Center and Faculty of Medicine, University of Montréal, 900 Rue St Denis, Montréal, H2X OA9, QC, Canada
| | - Steven J. Millership
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Du Cane Road, London, W12 0NN, UK
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Blankenship HE, Carter KA, Cassidy NT, Markiewicz AN, Thellmann MI, Sharpe AL, Freeman WM, Beckstead MJ. VTA dopamine neurons are hyperexcitable in 3xTg-AD mice due to casein kinase 2-dependent SK channel dysfunction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.16.567486. [PMID: 38014232 PMCID: PMC10680865 DOI: 10.1101/2023.11.16.567486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Alzheimer's disease (AD) patients exhibit neuropsychiatric symptoms that extend beyond classical cognitive deficits, suggesting involvement of subcortical areas. Here, we investigated the role of midbrain dopamine (DA) neurons in AD using the amyloid + tau-driven 3xTg-AD mouse model. We found deficits in reward-based operant learning in AD mice, suggesting possible VTA DA neuron dysregulation. Physiological assessment revealed hyperexcitability and disrupted firing in DA neurons caused by reduced activity of small-conductance calcium-activated potassium (SK) channels. RNA sequencing from contents of single patch-clamped DA neurons (Patch-seq) identified up-regulation of the SK channel modulator casein kinase 2 (CK2). Pharmacological inhibition of CK2 restored SK channel activity and normal firing patterns in 3xTg-AD mice. These findings shed light on a complex interplay between neuropsychiatric symptoms and subcortical circuits in AD, paving the way for novel treatment strategies.
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Doke M, Álvarez-Cubela S, Klein D, Altilio I, Schulz J, Mateus Gonçalves L, Almaça J, Fraker CA, Pugliese A, Ricordi C, Qadir MMF, Pastori RL, Domínguez-Bendala J. Dynamic scRNA-seq of live human pancreatic slices reveals functional endocrine cell neogenesis through an intermediate ducto-acinar stage. Cell Metab 2023; 35:1944-1960.e7. [PMID: 37898119 DOI: 10.1016/j.cmet.2023.10.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 08/23/2023] [Accepted: 10/03/2023] [Indexed: 10/30/2023]
Abstract
Human pancreatic plasticity is implied from multiple single-cell RNA sequencing (scRNA-seq) studies. However, these have been invariably based on static datasets from which fate trajectories can only be inferred using pseudotemporal estimations. Furthermore, the analysis of isolated islets has resulted in a drastic underrepresentation of other cell types, hindering our ability to interrogate exocrine-endocrine interactions. The long-term culture of human pancreatic slices (HPSs) has presented the field with an opportunity to dynamically track tissue plasticity at the single-cell level. Combining datasets from same-donor HPSs at different time points, with or without a known regenerative stimulus (BMP signaling), led to integrated single-cell datasets storing true temporal or treatment-dependent information. This integration revealed population shifts consistent with ductal progenitor activation, blurring of ductal/acinar boundaries, formation of ducto-acinar-endocrine differentiation axes, and detection of transitional insulin-producing cells. This study provides the first longitudinal scRNA-seq analysis of whole human pancreatic tissue, confirming its plasticity in a dynamic fashion.
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Affiliation(s)
- Mayur Doke
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Silvia Álvarez-Cubela
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Dagmar Klein
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Isabella Altilio
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Joseph Schulz
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Luciana Mateus Gonçalves
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Joana Almaça
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Christopher A Fraker
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Alberto Pugliese
- Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Camillo Ricordi
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Mirza M F Qadir
- Tulane University School of Medicine, New Orleans, LA 70112, USA
| | - Ricardo L Pastori
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
| | - Juan Domínguez-Bendala
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
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29
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Maglov J, Feng MY, Lin D, Barkhouse K, Alexander A, Grbic M, Zhurov V, Grbic V, Tudzarova S. A link between energy metabolism and plant host adaptation states in the two-spotted spider mite, Tetranychus urticae (Koch). Sci Rep 2023; 13:19343. [PMID: 37935795 PMCID: PMC10630510 DOI: 10.1038/s41598-023-46589-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 11/02/2023] [Indexed: 11/09/2023] Open
Abstract
Energy metabolism is a highly conserved process that balances generation of cellular energy and maintenance of redox homeostasis. It consists of five interconnected pathways: glycolysis, tricarboxylic acid cycle, pentose phosphate, trans-sulfuration, and NAD+ biosynthesis pathways. Environmental stress rewires cellular energy metabolism. Type-2 diabetes is a well-studied energy metabolism rewiring state in human pancreatic β-cells where glucose metabolism is uncoupled from insulin secretion. The two-spotted spider mite, Tetranychus urticae (Koch), exhibits a remarkable ability to adapt to environmental stress. Upon transfer to unfavourable plant hosts, mites experience extreme xenobiotic stress that dramatically affects their survivorship and fecundity. However, within 25 generations, mites adapt to the xenobiotic stress and restore their fitness. Mites' ability to withstand long-term xenobiotic stress raises a question of their energy metabolism states during host adaptation. Here, we compared the transcriptional responses of five energy metabolism pathways between host-adapted and non-adapted mites while using responses in human pancreatic islet donors to model these pathways under stress. We found that non-adapted mites and human pancreatic β-cells responded in a similar manner to host plant transfer and diabetogenic stress respectively, where redox homeostasis maintenance was favoured over energy generation. Remarkably, we found that upon host-adaptation, mite energy metabolic states were restored to normal. These findings suggest that genes involved in energy metabolism can serve as molecular markers for mite host-adaptation.
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Affiliation(s)
- Jorden Maglov
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada
| | - Min Yi Feng
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada
| | - Dorothy Lin
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada
| | - Kennedy Barkhouse
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada
| | - Anton Alexander
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada
| | - Miodrag Grbic
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada
| | - Vladimir Zhurov
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada.
| | - Vojislava Grbic
- Department of Biology, The University of Western Ontario, London, N6A 5B7, Canada.
| | - Slavica Tudzarova
- Larry L. Hillblom Islet Research Center, University of California, Los Angeles, CA, 90095, USA.
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30
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Elgamal RM, Kudtarkar P, Melton RL, Mummey HM, Benaglio P, Okino ML, Gaulton KJ. An Integrated Map of Cell Type-Specific Gene Expression in Pancreatic Islets. Diabetes 2023; 72:1719-1728. [PMID: 37582230 PMCID: PMC10588282 DOI: 10.2337/db23-0130] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 08/03/2023] [Indexed: 08/17/2023]
Abstract
Pancreatic islets consist of multiple cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in type 1 and type 2 diabetes. Numerous studies have assessed transcription across individual cell types using single-cell assays; however, there is no canonical reference of gene expression in islet cell types that is also easily accessible for researchers to query and use in bioinformatics pipelines. Here we present an integrated map of islet cell type-specific gene expression from 192,203 cells from single-cell RNA sequencing of 65 donors without diabetes, donors who were type 1 diabetes autoantibody positive, donors with type 1 diabetes, and donors with type 2 diabetes from the Human Pancreas Analysis Program. We identified 10 distinct cell types, annotated subpopulations of several cell types, and defined cell type-specific marker genes. We tested differential expression within each cell type across disease states and identified 1,701 genes with significant changes in expression, with most changes observed in β-cells from donors with type 1 diabetes. To facilitate user interaction, we provide several single-cell visualization and reference mapping tools, as well as the open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology. ARTICLE HIGHLIGHTS
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Affiliation(s)
- Ruth M. Elgamal
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Parul Kudtarkar
- Department of Pediatrics, University of California, San Diego, La Jolla, CA
| | - Rebecca L. Melton
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Hannah M. Mummey
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA
| | - Paola Benaglio
- Department of Pediatrics, University of California, San Diego, La Jolla, CA
| | - Mei-Lin Okino
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Kyle J. Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA
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31
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Li J, Yang J, Hong T. Delineating the transcriptional atlas for impaired insulin secretion: A window into type 2 diabetes pathophysiology. J Diabetes Investig 2023; 14:1231-1233. [PMID: 37494274 PMCID: PMC10583644 DOI: 10.1111/jdi.14060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/04/2023] [Accepted: 07/10/2023] [Indexed: 07/28/2023] Open
Affiliation(s)
- Jian Li
- Department of Endocrinology and MetabolismPeking University Third HospitalBeijingChina
| | - Jin Yang
- Department of Endocrinology and MetabolismPeking University Third HospitalBeijingChina
- Clinical Stem Cell Research CenterPeking University Third HospitalBeijingChina
| | - Tianpei Hong
- Department of Endocrinology and MetabolismPeking University Third HospitalBeijingChina
- Clinical Stem Cell Research CenterPeking University Third HospitalBeijingChina
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Lee JH, Ryu H, Lee H, Yu HR, Gao Y, Lee KM, Kim YJ, Lee J. Endoplasmic reticulum stress in pancreatic β cells induces incretin desensitization and β-cell dysfunction via ATF4-mediated PDE4D expression. Am J Physiol Endocrinol Metab 2023; 325:E448-E465. [PMID: 37729023 DOI: 10.1152/ajpendo.00156.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/18/2023] [Accepted: 09/05/2023] [Indexed: 09/22/2023]
Abstract
Pancreatic β-cell dysfunction and eventual loss are key steps in the progression of type 2 diabetes (T2D). Endoplasmic reticulum (ER) stress responses, especially those mediated by the protein kinase RNA-like ER kinase and activating transcription factor 4 (PERK-ATF4) pathway, have been implicated in promoting these β-cell pathologies. However, the exact molecular events surrounding the role of the PERK-ATF4 pathway in β-cell dysfunction remain unknown. Here, we report our discovery that ATF4 promotes the expression of PDE4D, which disrupts β-cell function via a downregulation of cAMP signaling. We found that β-cell-specific transgenic expression of ATF4 led to early β-cell dysfunction and loss, a phenotype that resembles accelerated T2D. Expression of ATF4, rather than C/EBP homologous protein (CHOP), promoted PDE4D expression, reduced cAMP signaling, and attenuated responses to incretins and elevated glucose. Furthermore, we found that β-cells of leptin receptor-deficient diabetic (db/db) mice had elevated nuclear localization of ATF4 and PDE4D expression, accompanied by impaired β-cell function. Accordingly, pharmacological inhibition of the ATF4 pathway attenuated PDE4D expression in the islets and promoted incretin-simulated glucose tolerance and insulin secretion in db/db mice. Finally, we found that inhibiting PDE4 activity with selective pharmacological inhibitors improved β-cell function in both db/db mice and β-cell-specific ATF4 transgenic mice. In summary, our results indicate that ER stress causes β-cell failure via ATF4-mediated PDE4D production, suggesting the ATF4-PDE4D pathway could be a therapeutic target for protecting β-cell function during the progression of T2D.NEW & NOTEWORTHY Endoplasmic reticulum stress has been implied to cause multiple β-cell pathologies during the progression of type 2 diabetes (T2D). However, the precise molecular events underlying this remain unknown. Here, we discovered that elevated ATF4 activity, which was seen in T2D β cells, attenuated β-cell proliferation and impaired insulin secretion via PDE4D-mediated downregulation of cAMP signaling. Additionally, we demonstrated that pharmacological inhibition of the ATF4 pathway or PDE4D activity alleviated β-cell dysfunction, suggesting its therapeutic usefulness against T2D.
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Affiliation(s)
- Ji-Hye Lee
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
- New Biology Research Center, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Hanguk Ryu
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Hyejin Lee
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Hye Ram Yu
- Well Aging Research Center, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Yurong Gao
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Kyeong-Min Lee
- Division of Biotechnology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Young-Joon Kim
- Department of Life Sciences, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
| | - Jaemin Lee
- Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
- New Biology Research Center, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
- Well Aging Research Center, Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
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Zhao Z, D’Oliveira Albanus R, Taylor H, Tang X, Han Y, Orchard P, Varshney A, Zhang T, Manickam N, Erdos M, Narisu N, Taylor L, Saavedra X, Zhong A, Li B, Zhou T, Naji A, Liu C, Collins F, Parker SCJ, Chen S. An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals. RESEARCH SQUARE 2023:rs.3.rs-3343318. [PMID: 37886586 PMCID: PMC10602166 DOI: 10.21203/rs.3.rs-3343318/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.
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Affiliation(s)
- Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | | | - Henry Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xuming Tang
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Yuling Han
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Tuo Zhang
- Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mike Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaxia Saavedra
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Aaron Zhong
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Bo Li
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Ting Zhou
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Francis Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Stephen CJ Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
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Riahi Y, Kogot-Levin A, Kadosh L, Agranovich B, Malka A, Assa M, Piran R, Avrahami D, Glaser B, Gottlieb E, Jackson F, Cerasi E, Bernal-Mizrachi E, Helman A, Leibowitz G. Hyperglucagonaemia in diabetes: altered amino acid metabolism triggers mTORC1 activation, which drives glucagon production. Diabetologia 2023; 66:1925-1942. [PMID: 37480416 DOI: 10.1007/s00125-023-05967-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/07/2023] [Indexed: 07/24/2023]
Abstract
AIM/HYPOTHESIS Hyperglycaemia is associated with alpha cell dysfunction, leading to dysregulated glucagon secretion in type 1 and type 2 diabetes; however, the mechanisms involved are still elusive. The nutrient sensor mammalian target of rapamycin complex 1 (mTORC1) plays a major role in the maintenance of alpha cell mass and function. We studied the regulation of alpha cell mTORC1 by nutrients and its role in the development of hyperglucagonaemia in diabetes. METHODS Alpha cell mTORC1 activity was assessed by immunostaining for phosphorylation of its downstream target, the ribosomal protein S6, and glucagon, followed by confocal microscopy on pancreatic sections and flow cytometry on dispersed human and mouse islets and the alpha cell line, αTC1-6. Metabolomics and metabolic flux were studied by 13C glucose labelling in 2.8 or 16.7 mmol/l glucose followed by LC-MS analysis. To study the role of mTORC1 in mediating hyperglucagonaemia in diabetes, we generated an inducible alpha cell-specific Rptor knockout in the Akita mouse model of diabetes and tested the effects on glucose tolerance by IPGTT and on glucagon secretion. RESULTS mTORC1 activity was increased in alpha cells from diabetic Akita mice in parallel to the development of hyperglycaemia and hyperglucagonaemia (two- to eightfold increase). Acute exposure of mouse and human islets to amino acids stimulated alpha cell mTORC1 (3.5-fold increase), whereas high glucose concentrations inhibited mTORC1 (1.4-fold decrease). The mTORC1 response to glucose was abolished in human and mouse diabetic alpha cells following prolonged islet exposure to high glucose levels, resulting in sustained activation of mTORC1, along with increased glucagon secretion. Metabolomics and metabolic flux analysis showed that exposure to high glucose levels enhanced glycolysis, glucose oxidation and the synthesis of glucose-derived amino acids. In addition, chronic exposure to high glucose levels increased the expression of Slc7a2 and Slc38a4, which encode amino acid transporters, as well as the levels of branched-chain amino acids and methionine cycle metabolites (~1.3-fold increase for both). Finally, conditional Rptor knockout in alpha cells from adult diabetic mice inhibited mTORC1, thereby inhibiting glucagon secretion (~sixfold decrease) and improving diabetes, despite persistent insulin deficiency. CONCLUSIONS/INTERPRETATION Alpha cell exposure to hyperglycaemia enhances amino acid synthesis and transport, resulting in sustained activation of mTORC1, thereby increasing glucagon secretion. mTORC1 therefore plays a major role in mediating alpha cell dysfunction in diabetes. DATA AVAILABILITY All sequencing data are available from the Gene Expression Omnibus (GEO) repository (accession no. GSE154126; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE154126 ).
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Affiliation(s)
- Yael Riahi
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviram Kogot-Levin
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Liat Kadosh
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Bella Agranovich
- Laboratory for Metabolism in Health and Disease, Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Assaf Malka
- The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Michael Assa
- The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Ron Piran
- The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Dana Avrahami
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Developmental Biology and Cancer Research, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Benjamin Glaser
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eyal Gottlieb
- Laboratory for Metabolism in Health and Disease, Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
- Department of Cancer Biology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fields Jackson
- Department of Biochemistry, Food Science and Nutrition, Robert H. Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel
| | - Erol Cerasi
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Ernesto Bernal-Mizrachi
- Department of Internal Medicine, Division of Endocrinology, Diabetes and Metabolism, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Aharon Helman
- Department of Biochemistry, Food Science and Nutrition, Robert H. Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot, Israel.
| | - Gil Leibowitz
- Diabetes Unit, Department of Endocrinology and Metabolism, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
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Mathisen AF, Abadpour S, Legøy TA, Paulo JA, Ghila L, Scholz H, Chera S. Global proteomics reveals insulin abundance as a marker of human islet homeostasis alterations. Acta Physiol (Oxf) 2023; 239:e14037. [PMID: 37621186 PMCID: PMC10592125 DOI: 10.1111/apha.14037] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 08/07/2023] [Accepted: 08/10/2023] [Indexed: 08/26/2023]
Abstract
AIM The variation in quality between the human islet samples represents a major problem for research, especially when used as control material. The assays assessing the quality of human islets used in research are non-standardized and limited, with many important parameters not being consistently assessed. High-throughput studies aimed at characterizing the diversity and segregation markers among apparently functionally healthy islet preps are thus a requirement. Here, we designed a pilot study to comprehensively identify the diversity of global proteome signatures and the deviation from normal homeostasis in randomly selected human-isolated islet samples. METHODS By using Tandem Mass Tag 16-plex proteomics, we focused on the recurrently observed disparity in the detected insulin abundance between the samples, used it as a segregating parameter, and analyzed the correlated changes in the proteome signature and homeostasis by pathway analysis. RESULTS In this pilot study, we showed that insulin protein abundance is a predictor of human islet homeostasis and quality. This parameter is independent of other quality predictors within their acceptable range, thus being able to further stratify islets samples of apparent good quality. Human islets with low amounts of insulin displayed changes in their metabolic and signaling profile, especially in regard to energy homeostasis and cell identity maintenance. We further showed that xenotransplantation into diabetic hosts is not expected to improve the pre-transplantation signature, as it has a negative effect on energy balance, antioxidant activity, and islet cell identity. CONCLUSIONS Insulin protein abundance predicts significant changes in human islet homeostasis among random samples of apparently good quality.
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Affiliation(s)
- Andreas F. Mathisen
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Shadab Abadpour
- Hybrid Technology Hub-Centre of Excellence, Faculty of Medicine, University of Oslo, Norway
- Institute for Surgical Research and Department of Transplant Medicine, Oslo University Hospital, Oslo, Norway
| | - Thomas Aga Legøy
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Joao A. Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Luiza Ghila
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Hanne Scholz
- Hybrid Technology Hub-Centre of Excellence, Faculty of Medicine, University of Oslo, Norway
- Institute for Surgical Research and Department of Transplant Medicine, Oslo University Hospital, Oslo, Norway
| | - Simona Chera
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
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Jæger KH, Tveito A. The simplified Kirchhoff network model (SKNM): a cell-based reaction-diffusion model of excitable tissue. Sci Rep 2023; 13:16434. [PMID: 37777588 PMCID: PMC10542379 DOI: 10.1038/s41598-023-43444-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 09/24/2023] [Indexed: 10/02/2023] Open
Abstract
Cell-based models of excitable tissues offer the advantage of cell-level precision, which cannot be achieved using traditional homogenized electrophysiological models. However, this enhanced accuracy comes at the cost of increased computational demands, necessitating the development of efficient cell-based models. The widely-accepted bidomain model serves as the standard in computational cardiac electrophysiology, and under certain anisotropy ratio conditions, it is well known that it can be reduced to the simpler monodomain model. Recently, the Kirchhoff Network Model (KNM) was developed as a cell-based counterpart to the bidomain model. In this paper, we aim to demonstrate that KNM can be simplified using the same steps employed to derive the monodomain model from the bidomain model. We present the cell-based Simplified Kirchhoff Network Model (SKNM), which produces results closely aligned with those of KNM while requiring significantly less computational resources.
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37
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Lin D, Yu J, Lin L, Ou Q, Quan H. MRPS6 modulates glucose-stimulated insulin secretion in mouse islet cells through mitochondrial unfolded protein response. Sci Rep 2023; 13:16173. [PMID: 37758822 PMCID: PMC10533529 DOI: 10.1038/s41598-023-43438-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 09/24/2023] [Indexed: 09/29/2023] Open
Abstract
Lack of efficient insulin secretion from the pancreas can lead to impaired glucose tolerance (IGT), prediabetes, and diabetes. We have previously identified two IGT-associated single nucleotide polymorphisms (SNPs) rs62212118 and rs13052524 located at two overlapping genes: MRPS6 and SLC5A3. In this study, we show that MRPS6 but not SLC5A3 regulates glucose-stimulated insulin secretion (GSIS) in primary human β-cell and a mouse pancreatic insulinoma β-cell line. Data mining and biochemical studies reveal that MRPS6 is positively regulated by the mitochondrial unfolded protein response (UPRmt), but feedback inhibits UPRmt. Disruption of such feedback by MRPS6 knockdown causes UPRmt hyperactivation in high glucose conditions, hence elevated ROS levels, increased apoptosis, and impaired GSIS. Conversely, MRPS6 overexpression reduces UPRmt, mitigates high glucose-induced ROS levels and apoptosis, and enhances GSIS in an ATF5-dependent manner. Consistently, UPRmt up-regulation or down-regulation by modulating ATF5 expression is sufficient to decrease or increase GSIS. The negative role of UPRmt in GSIS is further supported by analysis of public transcriptomic data from murine islets. In all, our studies identify MRPS6 and UPRmt as novel modulators of GSIS and apoptosis in β-cells, contributing to our understanding of the molecular and cellular mechanisms of IGT, prediabetes, and diabetes.
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Affiliation(s)
- Danhong Lin
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19 Xiuhua Road, Haikou, 570311, Hainan, China
| | - Jingwen Yu
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19 Xiuhua Road, Haikou, 570311, Hainan, China
| | - Leweihua Lin
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19 Xiuhua Road, Haikou, 570311, Hainan, China
| | - Qianying Ou
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19 Xiuhua Road, Haikou, 570311, Hainan, China
| | - Huibiao Quan
- Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, No.19 Xiuhua Road, Haikou, 570311, Hainan, China.
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Bohuslavova R, Fabriciova V, Smolik O, Lebrón-Mora L, Abaffy P, Benesova S, Zucha D, Valihrach L, Berkova Z, Saudek F, Pavlinkova G. NEUROD1 reinforces endocrine cell fate acquisition in pancreatic development. Nat Commun 2023; 14:5554. [PMID: 37689751 PMCID: PMC10492842 DOI: 10.1038/s41467-023-41306-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 08/30/2023] [Indexed: 09/11/2023] Open
Abstract
NEUROD1 is a transcription factor that helps maintain a mature phenotype of pancreatic β cells. Disruption of Neurod1 during pancreatic development causes severe neonatal diabetes; however, the exact role of NEUROD1 in the differentiation programs of endocrine cells is unknown. Here, we report a crucial role of the NEUROD1 regulatory network in endocrine lineage commitment and differentiation. Mechanistically, transcriptome and chromatin landscape analyses demonstrate that Neurod1 inactivation triggers a downregulation of endocrine differentiation transcription factors and upregulation of non-endocrine genes within the Neurod1-deficient endocrine cell population, disturbing endocrine identity acquisition. Neurod1 deficiency altered the H3K27me3 histone modification pattern in promoter regions of differentially expressed genes, which resulted in gene regulatory network changes in the differentiation pathway of endocrine cells, compromising endocrine cell potential, differentiation, and functional properties.
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Affiliation(s)
- Romana Bohuslavova
- Laboratory of Molecular Pathogenetics, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Valeria Fabriciova
- Laboratory of Molecular Pathogenetics, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Ondrej Smolik
- Laboratory of Molecular Pathogenetics, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Laura Lebrón-Mora
- Laboratory of Molecular Pathogenetics, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Pavel Abaffy
- Laboratory of Gene Expression, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Sarka Benesova
- Laboratory of Gene Expression, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Daniel Zucha
- Laboratory of Gene Expression, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Lukas Valihrach
- Laboratory of Gene Expression, Institute of Biotechnology CAS, 25250, Vestec, Czechia
| | - Zuzana Berkova
- Diabetes Centre, Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, 14021, Prague, Czechia
| | - Frantisek Saudek
- Diabetes Centre, Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, 14021, Prague, Czechia
| | - Gabriela Pavlinkova
- Laboratory of Molecular Pathogenetics, Institute of Biotechnology CAS, 25250, Vestec, Czechia.
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Fisher C, Johnson K, Moore M, Sadrati A, Janecek JL, Graham ML, Klein AH. Loss of ATP-sensitive channel expression and function decreases opioid sensitivity in a mouse model of type 2 diabetes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.06.556526. [PMID: 37732180 PMCID: PMC10508758 DOI: 10.1101/2023.09.06.556526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
During diabetes, β-cell dysfunction due to loss of potassium channels sensitive to ATP, known as KATP channels occurs progressively over time contributing to hyperglycemia. KATP channels are additionally present in the central and peripheral nervous systems and are downstream targets of opioid receptor signaling. The aim of this study is to investigate if KATP channel expression or activity in the nervous system changes in diabetic mice and if morphine antinociception changes in mice fed a high fat diet (HFD) for 16 weeks compared to controls. Mechanical thresholds were also monitored before and after administration of glyburide or nateglinide, KATP channel antagonists, for four weeks. HFD mice have decreased antinociception to systemic morphine, which is exacerbated after systemic treatment with glyburide or nateglinide. HFD mice also have lower rotarod scores, decreased mobility in an open field test, and lower burrowing behavior compared to their control diet counterparts, which is unaffected by KATP channel antagonist delivery. Expression of KATP channel subunits, Kcnj11 (Kir6.2) and Abcc8 (SUR1), were decreased in the peripheral and central nervous system in HFD mice, which is significantly correlated with baseline paw withdrawal thresholds. Upregulation of SUR1 through an adenovirus delivered intrathecally increased morphine antinociception in HFD mice, whereas Kir6.2 upregulation improved morphine antinociception only marginally. Perspective: This article presents the potential link between KATP channel function and neuropathy during diabetes. There is a need for increased knowledge in how diabetes affects structural and molecular changes in the nervous system to lead to the progression of chronic pain and sensory issues.
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Affiliation(s)
- Cole Fisher
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN, USA
| | - Kayla Johnson
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN, USA
| | - Madelyn Moore
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN, USA
| | - Amir Sadrati
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN, USA
| | - Jody L. Janecek
- Department of Surgery, University of Minnesota, St. Paul, MN, USA
| | | | - Amanda H. Klein
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota, Duluth, MN, USA
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Weng C, Gu A, Zhang S, Lu L, Ke L, Gao P, Liu X, Wang Y, Hu P, Plummer D, MacDonald E, Zhang S, Xi J, Lai S, Leskov K, Yuan K, Jin F, Li Y. Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A. Nat Commun 2023; 14:5400. [PMID: 37669939 PMCID: PMC10480445 DOI: 10.1038/s41467-023-41228-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023] Open
Abstract
Broad heterogeneity in pancreatic β-cell function and morphology has been widely reported. However, determining which components of this cellular heterogeneity serve a diabetes-relevant function remains challenging. Here, we integrate single-cell transcriptome, single-nuclei chromatin accessibility, and cell-type specific 3D genome profiles from human islets and identify Type II Diabetes (T2D)-associated β-cell heterogeneity at both transcriptomic and epigenomic levels. We develop a computational method to explicitly dissect the intra-donor and inter-donor heterogeneity between single β-cells, which reflect distinct mechanisms of T2D pathogenesis. Integrative transcriptomic and epigenomic analysis identifies HNF1A as a principal driver of intra-donor heterogeneity between β-cells from the same donors; HNF1A expression is also reduced in β-cells from T2D donors. Interestingly, HNF1A activity in single β-cells is significantly associated with lower Na+ currents and we nominate a HNF1A target, FXYD2, as the primary mitigator. Our study demonstrates the value of investigating disease-associated single-cell heterogeneity and provides new insights into the pathogenesis of T2D.
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Affiliation(s)
- Chen Weng
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Anniya Gu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- Medical Scientist Training Program (MSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Shanshan Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Luxin Ke
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Peidong Gao
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Yuntong Wang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Peinan Hu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Dylan Plummer
- Department of Computer and Data Sciences, School of Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Elise MacDonald
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Saixian Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Jiajia Xi
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Sisi Lai
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Konstantin Leskov
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Kyle Yuan
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- Department of Biochemistry, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Department of Computer and Data Sciences, School of Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
| | - Yan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
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Hrovatin K, Bastidas-Ponce A, Bakhti M, Zappia L, Büttner M, Salinno C, Sterr M, Böttcher A, Migliorini A, Lickert H, Theis FJ. Delineating mouse β-cell identity during lifetime and in diabetes with a single cell atlas. Nat Metab 2023; 5:1615-1637. [PMID: 37697055 PMCID: PMC10513934 DOI: 10.1038/s42255-023-00876-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 07/26/2023] [Indexed: 09/13/2023]
Abstract
Although multiple pancreatic islet single-cell RNA-sequencing (scRNA-seq) datasets have been generated, a consensus on pancreatic cell states in development, homeostasis and diabetes as well as the value of preclinical animal models is missing. Here, we present an scRNA-seq cross-condition mouse islet atlas (MIA), a curated resource for interactive exploration and computational querying. We integrate over 300,000 cells from nine scRNA-seq datasets consisting of 56 samples, varying in age, sex and diabetes models, including an autoimmune type 1 diabetes model (NOD), a glucotoxicity/lipotoxicity type 2 diabetes model (db/db) and a chemical streptozotocin β-cell ablation model. The β-cell landscape of MIA reveals new cell states during disease progression and cross-publication differences between previously suggested marker genes. We show that β-cells in the streptozotocin model transcriptionally correlate with those in human type 2 diabetes and mouse db/db models, but are less similar to human type 1 diabetes and mouse NOD β-cells. We also report pathways that are shared between β-cells in immature, aged and diabetes models. MIA enables a comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation and demise.
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Affiliation(s)
- Karin Hrovatin
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | - Aimée Bastidas-Ponce
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Medical Faculty, Technical University of Munich, Munich, Germany
| | - Mostafa Bakhti
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Luke Zappia
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Maren Büttner
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
- Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Bonn, Germany
| | - Ciro Salinno
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Medical Faculty, Technical University of Munich, Munich, Germany
| | - Michael Sterr
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Anika Böttcher
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Adriana Migliorini
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- McEwen Stem Cell Institute, University Health Network (UHN), Toronto, Ontario, Canada
| | - Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Neuherberg, Germany.
- Medical Faculty, Technical University of Munich, Munich, Germany.
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
- Department of Mathematics, Technical University of Munich, Garching, Germany.
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42
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Cantley J, Eizirik DL, Latres E, Dayan CM. Islet cells in human type 1 diabetes: from recent advances to novel therapies - a symposium-based roadmap for future research. J Endocrinol 2023; 259:e230082. [PMID: 37493471 PMCID: PMC10502961 DOI: 10.1530/joe-23-0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/25/2023] [Indexed: 07/27/2023]
Abstract
There is a growing understanding that the early phases of type 1 diabetes (T1D) are characterised by a deleterious dialogue between the pancreatic beta cells and the immune system. This, combined with the urgent need to better translate this growing knowledge into novel therapies, provided the background for the JDRF-DiabetesUK-INNODIA-nPOD symposium entitled 'Islet cells in human T1D: from recent advances to novel therapies', which took place in Stockholm, Sweden, in September 2022. We provide in this article an overview of the main themes addressed in the symposium, pointing to both promising conclusions and key unmet needs that remain to be addressed in order to achieve better approaches to prevent or reverse T1D.
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Affiliation(s)
- J Cantley
- School of Medicine, University of Dundee, Dundee, United Kingdom of Great Britain and Northern Ireland
| | - D L Eizirik
- ULB Center for Diabetes Research, Université Libre de Bruxelles Faculté de Médecine, Bruxelles, Belgium
| | - E Latres
- JDRF International, New York, NY, USA
| | - C M Dayan
- Cardiff University School of Medicine, Cardiff, United Kingdom of Great Britain and Northern Ireland
| | - the JDRF-DiabetesUK-INNODIA-nPOD Stockholm Symposium 2022
- School of Medicine, University of Dundee, Dundee, United Kingdom of Great Britain and Northern Ireland
- ULB Center for Diabetes Research, Université Libre de Bruxelles Faculté de Médecine, Bruxelles, Belgium
- JDRF International, New York, NY, USA
- Cardiff University School of Medicine, Cardiff, United Kingdom of Great Britain and Northern Ireland
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43
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Cha J, Aguayo-Mazzucato C, Thompson PJ. Pancreatic β-cell senescence in diabetes: mechanisms, markers and therapies. Front Endocrinol (Lausanne) 2023; 14:1212716. [PMID: 37720527 PMCID: PMC10501801 DOI: 10.3389/fendo.2023.1212716] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 08/15/2023] [Indexed: 09/19/2023] Open
Abstract
Cellular senescence is a response to a wide variety of stressors, including DNA damage, oncogene activation and physiologic aging, and pathologically accelerated senescence contributes to human disease, including diabetes mellitus. Indeed, recent work in this field has demonstrated a role for pancreatic β-cell senescence in the pathogenesis of Type 1 Diabetes, Type 2 Diabetes and monogenic diabetes. Small molecule or genetic targeting of senescent β-cells has shown promise as a novel therapeutic approach for preventing and treating diabetes. Despite these advances, major questions remain around the molecular mechanisms driving senescence in the β-cell, identification of molecular markers that distinguish senescent from non-senescent β-cell subpopulations, and translation of proof-of-concept therapies into novel treatments for diabetes in humans. Here, we summarize the current state of the field of β-cell senescence, highlighting insights from mouse models as well as studies on human islets and β-cells. We identify markers that have been used to detect β-cell senescence to unify future research efforts in this field. We discuss emerging concepts of the natural history of senescence in β-cells, heterogeneity of senescent β-cells subpopulations, role of sex differences in senescent responses, and the consequences of senescence on integrated islet function and microenvironment. As a young and developing field, there remain many open research questions which need to be addressed to move senescence-targeted approaches towards clinical investigation.
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Affiliation(s)
- Jeeyeon Cha
- Division of Diabetes, Endocrinology and Metabolism, Vanderbilt University Medical Center, Nashville, TN, United States
| | | | - Peter J. Thompson
- Diabetes Research Envisioned and Accomplished in Manitoba Theme, Children’s Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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44
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Brooks EP, Sussel L. Not the second fiddle: α cell development, identity, and function in health and diabetes. J Endocrinol 2023; 258:e220297. [PMID: 37171828 PMCID: PMC10524258 DOI: 10.1530/joe-22-0297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 05/12/2023] [Indexed: 05/13/2023]
Abstract
Historic and emerging studies provide evidence for the deterioration of pancreatic α cell function and identity in diabetes mellitus. Increased access to human tissue and the availability of more sophisticated molecular technologies have identified key insights into how α cell function and identity are preserved in healthy conditions and how they become dysfunctional in response to stress. These studies have revealed evidence of impaired glucagon secretion, shifts in α cell electrophysiology, changes in α cell mass, dysregulation of α cell transcription, and α-to-β cell conversion prior to and during diabetes. In this review, we outline the current state of research on α cell identity in health and disease. Evidence in model organisms and humans suggests that in addition to β cell dysfunction, diabetes is associated with a fundamental dysregulation of α cell identity. Importantly, epigenetic studies have revealed that α cells retain more poised and open chromatin at key cell-specific and diabetes-dysregulated genes, supporting the model that the inherent epigenetic plasticity of α cells makes them susceptible to the transcriptional changes that potentiate the loss of identity and function seen in diabetes. Thus, additional research into the maintenance of α cell identity and function is critical to fully understanding diabetes. Furthermore, these studies suggest α cells could represent an alternative source of new β cells for diabetes treatment.
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Affiliation(s)
- Elliott P Brooks
- Barbara Davis Center for Diabetes, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado, USA
| | - Lori Sussel
- Barbara Davis Center for Diabetes, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado, USA
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45
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Park SY, Ter-Saakyan S, Faraci G, Lee HY. Immune cell identifier and classifier (ImmunIC) for single cell transcriptomic readouts. Sci Rep 2023; 13:12093. [PMID: 37495649 PMCID: PMC10372073 DOI: 10.1038/s41598-023-39282-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 07/22/2023] [Indexed: 07/28/2023] Open
Abstract
Single cell RNA sequencing has a central role in immune profiling, identifying specific immune cells as disease markers and suggesting therapeutic target genes of immune cells. Immune cell-type annotation from single cell transcriptomics is in high demand for dissecting complex immune signatures from multicellular blood and organ samples. However, accurate cell type assignment from single-cell RNA sequencing data alone is complicated by a high level of gene expression heterogeneity. Many computational methods have been developed to respond to this challenge, but immune cell annotation accuracy is not highly desirable. We present ImmunIC, a simple and robust tool for immune cell identification and classification by combining marker genes with a machine learning method. With over two million immune cells and half-million non-immune cells from 66 single cell RNA sequencing studies, ImmunIC shows 98% accuracy in the identification of immune cells. ImmunIC outperforms existing immune cell classifiers, categorizing into ten immune cell types with 92% accuracy. We determine peripheral blood mononuclear cell compositions of severe COVID-19 cases and healthy controls using previously published single cell transcriptomic data, permitting the identification of immune cell-type specific differential pathways. Our publicly available tool can maximize the utility of single cell RNA profiling by functioning as a stand-alone bioinformatic cell sorter, advancing cell-type specific immune profiling for the discovery of disease-specific immune signatures and therapeutic targets.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Sonia Ter-Saakyan
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Gina Faraci
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, USA.
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46
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Eizirik DL, Szymczak F, Mallone R. Why does the immune system destroy pancreatic β-cells but not α-cells in type 1 diabetes? Nat Rev Endocrinol 2023; 19:425-434. [PMID: 37072614 DOI: 10.1038/s41574-023-00826-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 04/20/2023]
Abstract
A perplexing feature of type 1 diabetes (T1D) is that the immune system destroys pancreatic β-cells but not neighbouring α-cells, even though both β-cells and α-cells are dysfunctional. Dysfunction, however, progresses to death only for β-cells. Recent findings indicate important differences between these two cell types. First, expression of BCL2L1, a key antiapoptotic gene, is higher in α-cells than in β-cells. Second, endoplasmic reticulum (ER) stress-related genes are differentially expressed, with higher expression levels of pro-apoptotic CHOP in β-cells than in α-cells and higher expression levels of HSPA5 (which encodes the protective chaperone BiP) in α-cells than in β-cells. Third, expression of viral recognition and innate immune response genes is higher in α-cells than in β-cells, contributing to the enhanced resistance of α-cells to coxsackievirus infection. Fourth, expression of the immune-inhibitory HLA-E molecule is higher in α-cells than in β-cells. Of note, α-cells are less immunogenic than β-cells, and the CD8+ T cells invading the islets in T1D are reactive to pre-proinsulin but not to glucagon. We suggest that this finding is a result of the enhanced capacity of the α-cell to endure viral infections and ER stress, which enables them to better survive early stressors that can cause cell death and consequently amplify antigen presentation to the immune system. Moreover, the processing of the pre-proglucagon precursor in enteroendocrine cells might favour immune tolerance towards this potential self-antigen compared to pre-proinsulin.
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Affiliation(s)
- Decio L Eizirik
- Université Libre de Bruxelles (ULB) Center for Diabetes Research and Welbio, Medical Faculty, Brussels, Belgium.
| | - Florian Szymczak
- Université Libre de Bruxelles (ULB) Center for Diabetes Research and Welbio, Medical Faculty, Brussels, Belgium
| | - Roberto Mallone
- Université Paris Cité, Institut Cochin, CNRS, INSERM, Paris, France
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, Paris, France
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47
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Pettway YD, Saunders DC, Brissova M. The human α cell in health and disease. J Endocrinol 2023; 258:e220298. [PMID: 37114672 PMCID: PMC10428003 DOI: 10.1530/joe-22-0298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 04/27/2023] [Indexed: 04/29/2023]
Abstract
In commemoration of 100 years since the discovery of glucagon, we review current knowledge about the human α cell. Alpha cells make up 30-40% of human islet endocrine cells and play a major role in regulating whole-body glucose homeostasis, largely through the direct actions of their main secretory product - glucagon - on peripheral organs. Additionally, glucagon and other secretory products of α cells, namely acetylcholine, glutamate, and glucagon-like peptide-1, have been shown to play an indirect role in the modulation of glucose homeostasis through autocrine and paracrine interactions within the islet. Studies of glucagon's role as a counterregulatory hormone have revealed additional important functions of the α cell, including the regulation of multiple aspects of energy metabolism outside that of glucose. At the molecular level, human α cells are defined by the expression of conserved islet-enriched transcription factors and various enriched signature genes, many of which have currently unknown cellular functions. Despite these common threads, notable heterogeneity exists amongst human α cell gene expression and function. Even greater differences are noted at the inter-species level, underscoring the importance of further study of α cell physiology in the human context. Finally, studies on α cell morphology and function in type 1 and type 2 diabetes, as well as other forms of metabolic stress, reveal a key contribution of α cell dysfunction to dysregulated glucose homeostasis in disease pathogenesis, making targeting the α cell an important focus for improving treatment.
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Affiliation(s)
- Yasminye D. Pettway
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, 37232, USA
| | - Diane C. Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, 37232, USA
| | - Marcela Brissova
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, 37232, USA
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48
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Wang G, Chiou J, Zeng C, Miller M, Matta I, Han JY, Kadakia N, Okino ML, Beebe E, Mallick M, Camunas-Soler J, Dos Santos T, Dai XQ, Ellis C, Hang Y, Kim SK, MacDonald PE, Kandeel FR, Preissl S, Gaulton KJ, Sander M. Integrating genetics with single-cell multiomic measurements across disease states identifies mechanisms of beta cell dysfunction in type 2 diabetes. Nat Genet 2023; 55:984-994. [PMID: 37231096 PMCID: PMC10550816 DOI: 10.1038/s41588-023-01397-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 04/12/2023] [Indexed: 05/27/2023]
Abstract
Dysfunctional pancreatic islet beta cells are a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of the underlying mechanisms, including gene dysregulation, is lacking. Here we integrate information from measurements of chromatin accessibility, gene expression and function in single beta cells with genetic association data to nominate disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 nondiabetic, pre-T2D and T2D donors, we identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift during T2D progression. Subtype-defining accessible chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both beta cell subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is probably induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for characterizing mechanisms of complex diseases.
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Affiliation(s)
- Gaowei Wang
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Joshua Chiou
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
- Biomedical Graduate Studies Program, University of California San Diego, La Jolla, CA, USA
| | - Chun Zeng
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Ileana Matta
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Jee Yun Han
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Nikita Kadakia
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Mei-Lin Okino
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Elisha Beebe
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | - Medhavi Mallick
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA
| | | | - Theodore Dos Santos
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
- Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Xiao-Qing Dai
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
- Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Cara Ellis
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
- Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Yan Hang
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Medicine and of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Seung K Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
- Departments of Medicine and of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Patrick E MacDonald
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
- Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Fouad R Kandeel
- Department of Clinical Diabetes, Endocrinology & Metabolism, City of Hope, Duarte, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA.
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| | - Kyle J Gaulton
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
| | - Maike Sander
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
- Pediatric Diabetes Research Center, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.
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49
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Dror E, Fagnocchi L, Wegert V, Apostle S, Grimaldi B, Gruber T, Panzeri I, Heyne S, Höffler KD, Kreiner V, Ching R, Tsai-Hsiu Lu T, Semwal A, Johnson B, Senapati P, Lempradl A, Schones D, Imhof A, Shen H, Pospisilik JA. Epigenetic dosage identifies two major and functionally distinct β cell subtypes. Cell Metab 2023; 35:821-836.e7. [PMID: 36948185 PMCID: PMC10160009 DOI: 10.1016/j.cmet.2023.03.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 01/17/2023] [Accepted: 03/08/2023] [Indexed: 03/24/2023]
Abstract
The mechanisms that specify and stabilize cell subtypes remain poorly understood. Here, we identify two major subtypes of pancreatic β cells based on histone mark heterogeneity (βHI and βLO). βHI cells exhibit ∼4-fold higher levels of H3K27me3, distinct chromatin organization and compaction, and a specific transcriptional pattern. βHI and βLO cells also differ in size, morphology, cytosolic and nuclear ultrastructure, epigenomes, cell surface marker expression, and function, and can be FACS separated into CD24+ and CD24- fractions. Functionally, βHI cells have increased mitochondrial mass, activity, and insulin secretion in vivo and ex vivo. Partial loss of function indicates that H3K27me3 dosage regulates βHI/βLO ratio in vivo, suggesting that control of β cell subtype identity and ratio is at least partially uncoupled. Both subtypes are conserved in humans, with βHI cells enriched in humans with type 2 diabetes. Thus, epigenetic dosage is a novel regulator of cell subtype specification and identifies two functionally distinct β cell subtypes.
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Affiliation(s)
- Erez Dror
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany.
| | - Luca Fagnocchi
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Vanessa Wegert
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany; Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Stefanos Apostle
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Brooke Grimaldi
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Tim Gruber
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ilaria Panzeri
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany; Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Steffen Heyne
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany
| | - Kira Daniela Höffler
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany
| | - Victor Kreiner
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany
| | - Reagan Ching
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany
| | - Tess Tsai-Hsiu Lu
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany
| | - Ayush Semwal
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Ben Johnson
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Parijat Senapati
- Department of Diabetes Complications and Metabolism, Diabetes and Metabolism Research Institute, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Adelheid Lempradl
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany; Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Dustin Schones
- Department of Diabetes Complications and Metabolism, Diabetes and Metabolism Research Institute, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Axel Imhof
- Biomedical Center Munich, Ludwig Maximilian University of Munich, 82152 Planegg-Martinsried, Germany
| | - Hui Shen
- Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - John Andrew Pospisilik
- Department of Epigenetics, Max Planck Institute of Immunobiology and Epigenetics, Freiburg 79108, Germany; Department of Epigenetics, Van Andel Institute, Grand Rapids, MI 49503, USA.
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50
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Kang RB, Li Y, Rosselot C, Zhang T, Siddiq M, Rajbhandari P, Stewart AF, Scott DK, Garcia-Ocana A, Lu G. Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles. Genome Med 2023; 15:30. [PMID: 37127706 PMCID: PMC10150516 DOI: 10.1186/s13073-023-01179-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 04/12/2023] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND Single-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts. METHODS We obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library. RESULTS First, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo. CONCLUSIONS In summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.
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Affiliation(s)
- Randy B Kang
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Present address: Department of Molecular and Cellular Endocrinology, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA
| | - Yansui Li
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Carolina Rosselot
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Tuo Zhang
- Genomics Resources Core Facility, Weill Cornell Medicine, New York, NY, 10065, USA
| | - Mustafa Siddiq
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Prashant Rajbhandari
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Andrew F Stewart
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pharmacological Sciences and Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Donald K Scott
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Pharmacological Sciences and Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Adolfo Garcia-Ocana
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Present address: Department of Molecular and Cellular Endocrinology, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
- Department of Pharmacological Sciences and Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Geming Lu
- Diabetes, Obesity and Metabolism Institute, and Division of Endocrinology, Diabetes and Bone Diseases, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Present address: Department of Molecular and Cellular Endocrinology, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, 1500 East Duarte Road, Duarte, CA, 91010, USA.
- Department of Pharmacological Sciences and Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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