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Grobecker P, Sakoparnig T, van Nimwegen E. Identifying cell states in single-cell RNA-seq data at statistically maximal resolution. PLoS Comput Biol 2024; 20:e1012224. [PMID: 38995959 DOI: 10.1371/journal.pcbi.1012224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 06/04/2024] [Indexed: 07/14/2024] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has become a popular experimental method to study variation of gene expression within a population of cells. However, obtaining an accurate picture of the diversity of distinct gene expression states that are present in a given dataset is highly challenging because the sparsity of the scRNA-seq data and its inhomogeneous measurement noise properties. Although a vast number of different methods is applied in the literature for clustering cells into subsets with 'similar' expression profiles, these methods generally lack rigorously specified objectives, involve multiple complex layers of normalization, filtering, feature selection, dimensionality-reduction, employ ad hoc measures of distance or similarity between cells, often ignore the known measurement noise properties of scRNA-seq measurements, and include a large number of tunable parameters. Consequently, it is virtually impossible to assign concrete biophysical meaning to the clusterings that result from these methods. Here we address the following problem: Given raw unique molecule identifier (UMI) counts of an scRNA-seq dataset, partition the cells into subsets such that the gene expression states of the cells in each subset are statistically indistinguishable, and each subset corresponds to a distinct gene expression state. That is, we aim to partition cells so as to maximally reduce the complexity of the dataset without removing any of its meaningful structure. We show that, given the known measurement noise structure of scRNA-seq data, this problem is mathematically well-defined and derive its unique solution from first principles. We have implemented this solution in a tool called Cellstates which operates directly on the raw data and automatically determines the optimal partition and cluster number, with zero tunable parameters. We show that, on synthetic datasets, Cellstates almost perfectly recovers optimal partitions. On real data, Cellstates robustly identifies subtle substructure within groups of cells that are traditionally annotated as a common cell type. Moreover, we show that the diversity of gene expression states that Cellstates identifies systematically depends on the tissue of origin and not on technical features of the experiments such as the total number of cells and total UMI count per cell. In addition to the Cellstates tool we also provide a small toolbox of software to place the identified cellstates into a hierarchical tree of higher-order clusters, to identify the most important differentially expressed genes at each branch of this hierarchy, and to visualize these results.
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Affiliation(s)
- Pascal Grobecker
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Thomas Sakoparnig
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Erik van Nimwegen
- Biozentrum, University of Basel and Swiss Institute of Bioinformatics, Basel, Switzerland
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2
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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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3
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Huang D, Jiao X, Huang S, Liu J, Si H, Qi D, Pei X, Lu D, Wang Y, Li Z. Analysis of the heterogeneity and complexity of murine extraorbital lacrimal gland via single-cell RNA sequencing. Ocul Surf 2024; 34:60-95. [PMID: 38945476 DOI: 10.1016/j.jtos.2024.06.005] [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: 08/26/2022] [Revised: 06/22/2024] [Accepted: 06/26/2024] [Indexed: 07/02/2024]
Abstract
PURPOSE The lacrimal gland is essential for maintaining ocular surface health and avoiding external damage by secreting an aqueous layer of the tear film. However, a healthy lacrimal gland's inventory of cell types and heterogeneity remains understudied. METHODS Here, 10X Genome-based single-cell RNA sequencing was used to generate an unbiased classification of cellular diversity in the extraorbital lacrimal gland (ELG) of C57BL/6J mice. From 43,850 high-quality cells, we produced an atlas of cell heterogeneity and defined cell types using classic marker genes. The possible functions of these cells were analyzed through bioinformatics analysis. Additionally, the CellChat was employed for a preliminary analysis of the cell-cell communication network in the ELG. RESULTS Over 37 subclasses of cells were identified, including seven types of glandular epithelial cells, three types of fibroblasts, ten types of myeloid-derived immune cells, at least eleven types of lymphoid-derived immune cells, and five types of vascular-associated cell subsets. The cell-cell communication network analysis revealed that fibroblasts and immune cells play a pivotal role in the dense intercellular communication network within the mouse ELG. CONCLUSIONS This study provides a comprehensive transcriptome atlas and related database of the mouse ELG.
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Affiliation(s)
- Duliurui Huang
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China
| | - Xinwei Jiao
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Shenzhen Huang
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Jiangman Liu
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China
| | - Hongli Si
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China
| | - Di Qi
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Xiaoting Pei
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Dingli Lu
- Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China
| | - Yimian Wang
- Division of Medicine, Faculty of Medical Sciences, University College London, Gower Street, London, WC1E 6BT, UK
| | - Zhijie Li
- Department of Ophthalmology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, China; Henan Eye Institute, Henan Eye Hospital and Henan Key Laboratory of Ophthalmology and Visual Science, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, 450000, China.
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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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Dobson JR, Jacobson DA. Disrupted Endoplasmic Reticulum Ca 2+ Handling: A Harβinger of β-Cell Failure. BIOLOGY 2024; 13:379. [PMID: 38927260 PMCID: PMC11200644 DOI: 10.3390/biology13060379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/17/2024] [Accepted: 05/17/2024] [Indexed: 06/28/2024]
Abstract
The β-cell workload increases in the setting of insulin resistance and reduced β-cell mass, which occurs in type 2 and type 1 diabetes, respectively. The prolonged elevation of insulin production and secretion during the pathogenesis of diabetes results in β-cell ER stress. The depletion of β-cell Ca2+ER during ER stress activates the unfolded protein response, leading to β-cell dysfunction. Ca2+ER is involved in many pathways that are critical to β-cell function, such as protein processing, tuning organelle and cytosolic Ca2+ handling, and modulating lipid homeostasis. Mutations that promote β-cell ER stress and deplete Ca2+ER stores are associated with or cause diabetes (e.g., mutations in ryanodine receptors and insulin). Thus, improving β-cell Ca2+ER handling and reducing ER stress under diabetogenic conditions could preserve β-cell function and delay or prevent the onset of diabetes. This review focuses on how mechanisms that control β-cell Ca2+ER are perturbed during the pathogenesis of diabetes and contribute to β-cell failure.
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Affiliation(s)
| | - David A. Jacobson
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA;
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Mbara KC, Fotsing MC, Ndinteh DT, Mbeb CN, Nwagwu CS, Khan R, Mokhetho KC, Baijnath H, Nlooto M, Mokhele S, Leonard CM, Tembu VJ, Tarirai C. Endoplasmic reticulum stress in pancreatic β-cell dysfunction: The potential therapeutic role of dietary flavonoids. CURRENT RESEARCH IN PHARMACOLOGY AND DRUG DISCOVERY 2024; 6:100184. [PMID: 38846008 PMCID: PMC11153890 DOI: 10.1016/j.crphar.2024.100184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/09/2024] Open
Abstract
Diabetes mellitus (DM) is a global health burden that is characterized by the loss or dysfunction of pancreatic β-cells. In pancreatic β-cells, endoplasmic reticulum (ER) stress is a fact of life that contributes to β-cell loss or dysfunction. Despite recent advances in research, the existing treatment approaches such as lifestyle modification and use of conventional therapeutics could not prevent the loss or dysfunction of pancreatic β-cells to abrogate the disease progression. Therefore, targeting ER stress and the consequent unfolded protein response (UPR) in pancreatic β-cells may be a potential therapeutic strategy for diabetes treatment. Dietary phytochemicals have therapeutic applications in human health owing to their broad spectrum of biochemical and pharmacological activities. Flavonoids, which are commonly obtained from fruits and vegetables worldwide, have shown promising prospects in alleviating ER stress. Dietary flavonoids including quercetin, kaempferol, myricetin, isorhamnetin, fisetin, icariin, apigenin, apigetrin, vitexin, baicalein, baicalin, nobiletin hesperidin, naringenin, epigallocatechin 3-O-gallate hesperidin (EGCG), tectorigenin, liquiritigenin, and acacetin have shown inhibitory effects on ER stress in pancreatic β-cells. Dietary flavonoids modulate ER stress signaling components, chaperone proteins, transcription factors, oxidative stress, autophagy, apoptosis, and inflammatory responses to exert their pharmacological effects on pancreatic β-cells ER stress. This review focuses on the role of dietary flavonoids as potential therapeutic adjuvants in preserving pancreatic β-cells from ER stress. Highlights of the underlying mechanisms of action are also presented as well as possible strategies for clinical translation in the management of DM.
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Affiliation(s)
- Kingsley C. Mbara
- Nanomedicines Manufacturing, Biopharmaceutics and Diagnostics Research Laboratory, Department of Pharmaceutical Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
| | - Marthe C.D. Fotsing
- Drug Discovery and Smart Molecules Research Laboratory, Centre for Natural Products Research (CNPR), Department of Chemical Sciences, University of Johannesburg, Doornfontein, Johannesburg, 2028, South Africa
| | - Derek T. Ndinteh
- Drug Discovery and Smart Molecules Research Laboratory, Centre for Natural Products Research (CNPR), Department of Chemical Sciences, University of Johannesburg, Doornfontein, Johannesburg, 2028, South Africa
| | - Claudine N. Mbeb
- Nanomedicines Manufacturing, Biopharmaceutics and Diagnostics Research Laboratory, Department of Pharmaceutical Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
| | - Chinekwu S. Nwagwu
- Drug Delivery and Nanomedicines Research Laboratory, Department of Pharmaceutics, University of Nigeria, Nsukka, Enugu State, Nigeria
| | - Rene Khan
- Discipline of Medical Biochemistry, School of Laboratory Medicine and Medical Science, University of KwaZulu-Natal, Durban, South Africa
| | - Kopang C. Mokhetho
- Nanomedicines Manufacturing, Biopharmaceutics and Diagnostics Research Laboratory, Department of Pharmaceutical Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
| | - Himansu Baijnath
- Ward Herbarium, School of Life Sciences, University of KwaZulu-Natal, Durban, 4000, KwaZulu-Natal, South Africa
| | - Manimbulu Nlooto
- Department of Pharmaceutical Sciences, Healthcare Sciences, University of Limpopo, South Africa
| | - Shoeshoe Mokhele
- Department of Pharmaceutical Sciences, School of Pharmacy, Sefako Makgatho Health Sciences University, Pretoria, 0208, South Africa
| | - Carmen M. Leonard
- Nanomedicines Manufacturing, Biopharmaceutics and Diagnostics Research Laboratory, Department of Pharmaceutical Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
| | - Vuyelwa J. Tembu
- Natural Products Chemistry Research Laboratory, Department of Chemistry, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
| | - Clemence Tarirai
- Nanomedicines Manufacturing, Biopharmaceutics and Diagnostics Research Laboratory, Department of Pharmaceutical Sciences, Tshwane University of Technology, Private Bag X680, Pretoria, 0001, South Africa
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Xie G, Toledo MP, Hu X, Yong HJ, Sanchez PS, Liu C, Naji A, Irianto J, Wang YJ. NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing. BMC Genomics 2024; 25:427. [PMID: 38689254 PMCID: PMC11059690 DOI: 10.1186/s12864-024-10335-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: 01/03/2024] [Accepted: 04/22/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation. RESULTS We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed. CONCLUSIONS Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.
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Affiliation(s)
- Gengqiang Xie
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Maria Pilar Toledo
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Xue Hu
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Hyo Jeong Yong
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Pamela Sandoval Sanchez
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Chengyang Liu
- Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Naji
- Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Jerome Irianto
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Yue J Wang
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA.
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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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9
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Cuozzo F, Viloria K, Shilleh AH, Nasteska D, Frazer-Morris C, Tong J, Jiao Z, Boufersaoui A, Marzullo B, Rosoff DB, Smith HR, Bonner C, Kerr-Conte J, Pattou F, Nano R, Piemonti L, Johnson PRV, Spiers R, Roberts J, Lavery GG, Clark A, Ceresa CDL, Ray DW, Hodson L, Davies AP, Rutter GA, Oshima M, Scharfmann R, Merrins MJ, Akerman I, Tennant DA, Ludwig C, Hodson DJ. LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic β cells. Cell Rep 2024; 43:114047. [PMID: 38607916 PMCID: PMC11164428 DOI: 10.1016/j.celrep.2024.114047] [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: 03/16/2023] [Revised: 02/19/2024] [Accepted: 03/19/2024] [Indexed: 04/14/2024] Open
Abstract
Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.
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Affiliation(s)
- Federica Cuozzo
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Katrina Viloria
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Ali H Shilleh
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Daniela Nasteska
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Charlotte Frazer-Morris
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jason Tong
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Zicong Jiao
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Geneplus-Beijing, Changping District, Beijing 102206, China
| | - Adam Boufersaoui
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Bryan Marzullo
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Daniel B Rosoff
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Oxford Kavli Centre for Nanoscience Discovery, University of Oxford, Oxford, UK
| | - Hannah R Smith
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Caroline Bonner
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000 Lille, France
| | - Julie Kerr-Conte
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000 Lille, France
| | - Francois Pattou
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000 Lille, France
| | - Rita Nano
- San Raffaele Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Lorenzo Piemonti
- San Raffaele Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Paul R V Johnson
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Rebecca Spiers
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Jennie Roberts
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Gareth G Lavery
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Centre for Systems Health and Integrated Metabolic Research (SHiMR), Department of Biosciences, School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Anne Clark
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Carlo D L Ceresa
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - David W Ray
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Oxford Kavli Centre for Nanoscience Discovery, University of Oxford, Oxford, UK
| | - Leanne Hodson
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Amy P Davies
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Guy A Rutter
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK; CHUM Research Centre and Faculty of Medicine, University of Montreal, Montreal, QC, Canada; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Masaya Oshima
- Université Paris Cité, Institut Cochin, INSERM U1016, CNRS UMR 8104, 75014 Paris, France
| | - Raphaël Scharfmann
- Université Paris Cité, Institut Cochin, INSERM U1016, CNRS UMR 8104, 75014 Paris, France
| | - Matthew J Merrins
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, WI 53705, USA; William S. Middleton Memorial Veterans Hospital, Madison, WI 53705, USA
| | - Ildem Akerman
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Daniel A Tennant
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK.
| | - Christian Ludwig
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK.
| | - David J Hodson
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
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10
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Bourgeois S, Coenen S, Degroote L, Willems L, Van Mulders A, Pierreux J, Heremans Y, De Leu N, Staels W. Harnessing beta cell regeneration biology for diabetes therapy. Trends Endocrinol Metab 2024:S1043-2760(24)00082-1. [PMID: 38644094 DOI: 10.1016/j.tem.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Revised: 03/21/2024] [Accepted: 03/21/2024] [Indexed: 04/23/2024]
Abstract
The pandemic scale of diabetes mellitus is alarming, its complications remain devastating, and current treatments still pose a major burden on those affected and on the healthcare system as a whole. As the disease emanates from the destruction or dysfunction of insulin-producing pancreatic β-cells, a real cure requires their restoration and protection. An attractive strategy is to regenerate β-cells directly within the pancreas; however, while several approaches for β-cell regeneration have been proposed in the past, clinical translation has proven challenging. This review scrutinizes recent findings in β-cell regeneration and discusses their potential clinical implementation. Hereby, we aim to delineate a path for innovative, targeted therapies to help shift from 'caring for' to 'curing' diabetes.
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Affiliation(s)
- Stephanie Bourgeois
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Sophie Coenen
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Laure Degroote
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Lien Willems
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Annelore Van Mulders
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Julie Pierreux
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Yves Heremans
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium
| | - Nico De Leu
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium; Endocrinology, Universiteit Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium; Endocrinology, ASZ Aalst, 9300 Aalst, Belgium.
| | - Willem Staels
- Genetics, Reproduction, and Development (GRAD), Beta Cell Neogenesis (BENE) Research Unit, Vrije Universiteit Brussel (VUB), 1090 Brussels, Belgium; Pediatric Endocrinology, Department of Pediatrics, KidZ Health Castle, Universiteit Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium.
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11
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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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12
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Manandhar B, Pandzic E, Deshpande N, Chen SY, Wasinger VC, Kockx M, Glaros EN, Ong KL, Thomas SR, Wilkins MR, Whan RM, Cochran BJ, Rye KA. ApoA-I Protects Pancreatic β-Cells From Cholesterol-Induced Mitochondrial Damage and Restores Their Ability to Secrete Insulin. Arterioscler Thromb Vasc Biol 2024; 44:e20-e38. [PMID: 38095105 DOI: 10.1161/atvbaha.123.319378] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Accepted: 11/13/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND High cholesterol levels in pancreatic β-cells cause oxidative stress and decrease insulin secretion. β-cells can internalize apo (apolipoprotein) A-I, which increases insulin secretion. This study asks whether internalization of apoA-I improves β-cell insulin secretion by reducing oxidative stress. METHODS Ins-1E cells were cholesterol-loaded by incubation with cholesterol-methyl-β-cyclodextrin. Insulin secretion in the presence of 2.8 or 25 mmol/L glucose was quantified by radioimmunoassay. Internalization of fluorescently labeled apoA-I by β-cells was monitored by flow cytometry. The effects of apoA-I internalization on β-cell gene expression were evaluated by RNA sequencing. ApoA-I-binding partners on the β-cell surface were identified by mass spectrometry. Mitochondrial oxidative stress was quantified in β-cells and isolated islets with MitoSOX and confocal microscopy. RESULTS An F1-ATPase β-subunit on the β-cell surface was identified as the main apoA-I-binding partner. β-cell internalization of apoA-I was time-, concentration-, temperature-, cholesterol-, and F1-ATPase β-subunit-dependent. β-cells with internalized apoA-I (apoA-I+ cells) had higher cholesterol and cell surface F1-ATPase β-subunit levels than β-cells without internalized apoA-I (apoA-I- cells). The internalized apoA-I colocalized with mitochondria and was associated with reduced oxidative stress and increased insulin secretion. The IF1 (ATPase inhibitory factor 1) attenuated apoA-I internalization and increased oxidative stress in Ins-1E β-cells and isolated mouse islets. Differentially expressed genes in apoA-I+ and apoA-I- Ins-1E cells were related to protein synthesis, the unfolded protein response, insulin secretion, and mitochondrial function. CONCLUSIONS These results establish that β-cells are functionally heterogeneous, and apoA-I restores insulin secretion in β-cells with elevated cholesterol levels by improving mitochondrial redox balance.
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Affiliation(s)
- Bikash Manandhar
- School of Biomedical Sciences, Faculty of Medicine (B.M., E.N.G., K.L.O., S.R.T., B.J.C., K.-A.R.), UNSW, Sydney, Australia
| | - Elvis Pandzic
- Katharina Gaus Light Microscopy Facility, Mark Wainwright Analytical Centre (E.P., R.M.W.), UNSW, Sydney, Australia
| | - Nandan Deshpande
- School of Biotechnology and Biomolecular Sciences (N.D., S.-Y.C., M.R.W.), UNSW, Sydney, Australia
| | - Sing-Young Chen
- School of Biotechnology and Biomolecular Sciences (N.D., S.-Y.C., M.R.W.), UNSW, Sydney, Australia
| | - Valerie C Wasinger
- Bioanalytical Mass Spectrometry Facility, Mark Wainwright Analytical Centre (V.C.W.), UNSW, Sydney, Australia
| | - Maaike Kockx
- ANZAC Research Institute, Concord, Sydney, Australia (M.K.)
| | - Elias N Glaros
- School of Biomedical Sciences, Faculty of Medicine (B.M., E.N.G., K.L.O., S.R.T., B.J.C., K.-A.R.), UNSW, Sydney, Australia
| | - Kwok Leung Ong
- School of Biomedical Sciences, Faculty of Medicine (B.M., E.N.G., K.L.O., S.R.T., B.J.C., K.-A.R.), UNSW, Sydney, Australia
| | - Shane R Thomas
- School of Biomedical Sciences, Faculty of Medicine (B.M., E.N.G., K.L.O., S.R.T., B.J.C., K.-A.R.), UNSW, Sydney, Australia
| | - Marc R Wilkins
- School of Biotechnology and Biomolecular Sciences (N.D., S.-Y.C., M.R.W.), UNSW, Sydney, Australia
| | - Renee M Whan
- Katharina Gaus Light Microscopy Facility, Mark Wainwright Analytical Centre (E.P., R.M.W.), UNSW, Sydney, Australia
| | - Blake J Cochran
- School of Biomedical Sciences, Faculty of Medicine (B.M., E.N.G., K.L.O., S.R.T., B.J.C., K.-A.R.), UNSW, Sydney, Australia
| | - Kerry-Anne Rye
- School of Biomedical Sciences, Faculty of Medicine (B.M., E.N.G., K.L.O., S.R.T., B.J.C., K.-A.R.), UNSW, Sydney, Australia
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13
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Weidemann BJ, Marcheva B, Kobayashi M, Omura C, Newman MV, Kobayashi Y, Waldeck NJ, Perelis M, Lantier L, McGuinness OP, Ramsey KM, Stein RW, Bass J. Repression of latent NF-κB enhancers by PDX1 regulates β cell functional heterogeneity. Cell Metab 2024; 36:90-102.e7. [PMID: 38171340 PMCID: PMC10793877 DOI: 10.1016/j.cmet.2023.11.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 07/17/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024]
Abstract
Interactions between lineage-determining and activity-dependent transcription factors determine single-cell identity and function within multicellular tissues through incompletely known mechanisms. By assembling a single-cell atlas of chromatin state within human islets, we identified β cell subtypes governed by either high or low activity of the lineage-determining factor pancreatic duodenal homeobox-1 (PDX1). β cells with reduced PDX1 activity displayed increased chromatin accessibility at latent nuclear factor κB (NF-κB) enhancers. Pdx1 hypomorphic mice exhibited de-repression of NF-κB and impaired glucose tolerance at night. Three-dimensional analyses in tandem with chromatin immunoprecipitation (ChIP) sequencing revealed that PDX1 silences NF-κB at circadian and inflammatory enhancers through long-range chromatin contacts involving SIN3A. Conversely, Bmal1 ablation in β cells disrupted genome-wide PDX1 and NF-κB DNA binding. Finally, antagonizing the interleukin (IL)-1β receptor, an NF-κB target, improved insulin secretion in Pdx1 hypomorphic islets. Our studies reveal functional subtypes of single β cells defined by a gradient in PDX1 activity and identify NF-κB as a target for insulinotropic therapy.
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Affiliation(s)
- Benjamin J Weidemann
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Biliana Marcheva
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Mikoto Kobayashi
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Chiaki Omura
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Marsha V Newman
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Yumiko Kobayashi
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Nathan J Waldeck
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Mark Perelis
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Ionis Pharmaceuticals, Carlsbad, CA 92010, USA
| | - Louise Lantier
- Vanderbilt-NIH Mouse Metabolic Phenotyping Center, Nashville, TN 37232, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Owen P McGuinness
- Vanderbilt-NIH Mouse Metabolic Phenotyping Center, Nashville, TN 37232, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Kathryn Moynihan Ramsey
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Roland W Stein
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Joseph Bass
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
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14
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Katz LS, Brill G, Wang P, Lambertini L, Zhang P, Haldeman JM, Liu H, Newgard CB, Stewart AF, Garcia-Ocaña A, Scott DK. Transcriptional activation of the Myc gene by glucose in β-cells requires a ChREBP-dependent 3-D chromatin interaction between the Myc and Pvt1 genes. Mol Metab 2024; 79:101848. [PMID: 38042369 PMCID: PMC10714240 DOI: 10.1016/j.molmet.2023.101848] [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: 06/30/2023] [Revised: 11/14/2023] [Accepted: 11/28/2023] [Indexed: 12/04/2023] Open
Abstract
OBJECTIVE All forms of diabetes result from insufficient functional β-cell mass. Thus, achieving the therapeutic goal of expanding β-cell mass requires a better mechanistic understanding of how β-cells proliferate. Glucose is a natural β-cell mitogen that mediates its effects in part through the glucose-responsive transcription factor, carbohydrate response element binding protein (ChREBP) and the anabolic transcription factor, MYC. However, mechanistic details by which glucose activates Myc at the transcriptional level are poorly understood. METHODS Here, siRNA was used to test the role of ChREBP in the glucose response of MYC, ChIP and ChIPseq to identify potential regulatory binding sites, chromatin conformation capture to identify DNA/DNA interactions, and an adenovirus was constructed to expresses x-dCas9 and an sgRNA that specifically disrupts the recruitment of ChREBP to a specific targeted ChoRE. RESULTS We found that ChREBP is essential for glucose-mediated transcriptional induction of Myc, and for increases in Myc mRNA and protein abundance. Further, ChIPseq revealed that the carbohydrate response element (ChoRE) nearest to the Myc transcriptional start site (TSS) is immediately upstream of the gene encoding the lncRNA, Pvt1, 60,000 bp downstream of the Myc gene. Chromatin Conformation Capture (3C) confirmed a glucose-dependent interaction between these two sites. Transduction with an adenovirus expressing x-dCas9 and an sgRNA specifically targeting the highly conserved Pvt1 ChoRE, attenuates ChREBP recruitment, decreases Myc-Pvt1 DNA/DNA interaction, and decreases expression of the Pvt1 and Myc genes in response to glucose. Importantly, isolated and dispersed rat islet cells transduced with the ChoRE-disrupting adenovirus also display specific decreases in ChREBP-dependent, glucose-mediated expression of Pvt1 and Myc, as well as decreased glucose-stimulated β-cell proliferation. CONCLUSIONS The mitogenic glucose response of Myc is mediated via glucose-dependent recruitment of ChREBP to the promoter of the Pvt1 gene and subsequent DNA looping with the Myc promoter.
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Affiliation(s)
- Liora S Katz
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA
| | - Gabriel Brill
- Pharmacologic Sciences Department, Stony Brook University, Stony Brook, NY, USA(5)
| | - Peng Wang
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA
| | - Luca Lambertini
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA
| | - Pili Zhang
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA
| | | | - Hongtao Liu
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA
| | | | - Andrew F Stewart
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA
| | - Adolfo Garcia-Ocaña
- Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, 1500 E Duarte Rd, Duarte, CA 91010, USA
| | - Donald K Scott
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1152, New York, NY 10029, USA.
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15
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Møller AF, Madsen JGS. JOINTLY: interpretable joint clustering of single-cell transcriptomes. Nat Commun 2023; 14:8473. [PMID: 38123569 PMCID: PMC10733431 DOI: 10.1038/s41467-023-44279-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023] Open
Abstract
Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) is increasingly being used to characterise the transcriptomic state of cell types at homeostasis, during development and in disease. However, this is a challenging task, as biological effects can be masked by technical variation. Here, we present JOINTLY, an algorithm enabling joint clustering of sxRNA-seq datasets across batches. JOINTLY performs on par or better than state-of-the-art batch integration methods in clustering tasks and outperforms other intrinsically interpretable methods. We demonstrate that JOINTLY is robust against over-correction while retaining subtle cell state differences between biological conditions and highlight how the interpretation of JOINTLY can be used to annotate cell types and identify active signalling programs across cell types and pseudo-time. Finally, we use JOINTLY to construct a reference atlas of white adipose tissue (WATLAS), an expandable and comprehensive community resource, in which we describe four adipocyte subpopulations and map compositional changes in obesity and between depots.
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Affiliation(s)
- Andreas Fønss Møller
- Institute of Biochemistry and Molecular Biology, University of Southern, Odense, Denmark
- Sino-Danish College (SDC), University of Chinese Academy of Sciences, Beijing, China
| | - Jesper Grud Skat Madsen
- Institute of Biochemistry and Molecular Biology, University of Southern, Odense, Denmark.
- Institute of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.
- Center for Functional Genomics and Tissue Plasticity (ATLAS), Odense M, 5230, Denmark.
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
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16
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Thomas P, Gallagher MT, Da Silva Xavier G. Beta cell lipotoxicity in the development of type 2 diabetes: the need for species-specific understanding. Front Endocrinol (Lausanne) 2023; 14:1275835. [PMID: 38144558 PMCID: PMC10739424 DOI: 10.3389/fendo.2023.1275835] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 11/13/2023] [Indexed: 12/26/2023] Open
Abstract
The propensity to develop type 2 diabetes (T2D) is known to have both environmental and hereditary components. In those with a genetic predisposition to T2D, it is widely believed that elevated concentrations of circulatory long-chain fatty acids (LC-FFA) significantly contribute towards the demise of insulin-producing pancreatic β-cells - the fundamental feature of the development of T2D. Over 25 years of research support that LC-FFA are deleterious to β-cells, through a process termed lipotoxicity. However, the work underpinning the theory of β-cell lipotoxicity is mostly based on rodent studies. Doubts have been raised as to whether lipotoxicity also occurs in humans. In this review, we examine the evidence, both in vivo and in vitro, for the pathogenic effects of LC-FFA on β-cell viability and function in humans, highlighting key species differences. In this way, we aim to uncover the role of lipotoxicity in the human pathogenesis of T2D and motivate the need for species-specific understanding.
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Affiliation(s)
- Patricia Thomas
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, Birmingham Medical School, University of Birmingham, Birmingham, United Kingdom
| | - Meurig T. Gallagher
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, Birmingham Medical School, University of Birmingham, Birmingham, United Kingdom
| | - Gabriela Da Silva Xavier
- Institute for Metabolism and Systems Research, Birmingham Medical School, University of Birmingham, Birmingham, United Kingdom
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17
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Kavaliauskaite G, Madsen JS. Automatic quality control of single-cell and single-nucleus RNA-seq using valiDrops. NAR Genom Bioinform 2023; 5:lqad101. [PMID: 38025048 PMCID: PMC10657416 DOI: 10.1093/nargab/lqad101] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 10/05/2023] [Accepted: 11/01/2023] [Indexed: 12/01/2023] Open
Abstract
Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) measures gene expression in individual cells or nuclei enabling comprehensive characterization of cell types and states. However, isolation of cells or nuclei for sxRNA-seq releases contaminating RNA, which can distort biological signals, through, for example, cell damage and transcript leakage. Thus, identifying barcodes containing high-quality cells or nuclei is a critical analytical step in the processing of sxRNA-seq data. Here, we present valiDrops, an automated method to identify high-quality barcodes and flag dead cells. In valiDrops, barcodes are initially filtered using data-adaptive thresholding on community-standard quality metrics, and subsequently, valiDrops uses a novel clustering-based approach to identify barcodes with distinct biological signals. We benchmark valiDrops and show that biological signals from cell types and states are more distinct, easier to separate and more consistent after filtering by valiDrops compared to existing tools. Finally, we show that valiDrops can predict and flag dead cells with high accuracy. This novel classifier can further improve data quality or be used to identify dead cells to interrogate the biology of cell death. Thus, valiDrops is an effective and easy-to-use method to improve data quality and biological interpretation. Our method is openly available as an R package at www.github.com/madsen-lab/valiDrops.
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Affiliation(s)
- Gabija Kavaliauskaite
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense M 5230, Denmark
- Center for Functional Genomics and Tissue Plasticity (ATLAS), Odense M 5230, Denmark
| | - Jesper Grud Skat Madsen
- Center for Functional Genomics and Tissue Plasticity (ATLAS), Odense M 5230, Denmark
- Department of Mathematics and Computer Science, University of Southern Denmark, Odense M 5230, Denmark
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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18
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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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19
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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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20
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Shah A, Huck I, Duncan K, Gansemer ER, Liu K, Adajar RC, Apte U, Stamnes MA, Rutkowski DT. Interference with the HNF4-dependent gene regulatory network diminishes endoplasmic reticulum stress in hepatocytes. Hepatol Commun 2023; 7:e0278. [PMID: 37820274 PMCID: PMC10578741 DOI: 10.1097/hc9.0000000000000278] [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: 02/21/2023] [Accepted: 08/08/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND In all eukaryotic cell types, the unfolded protein response (UPR) upregulates factors that promote protein folding and misfolded protein clearance to help alleviate endoplasmic reticulum (ER) stress. Yet, ER stress in the liver is uniquely accompanied by the suppression of metabolic genes, the coordination and purpose of which are largely unknown. METHODS Here, we combined in silico machine learning, in vivo liver-specific deletion of the master regulator of hepatocyte differentiation HNF4α, and in vitro manipulation of hepatocyte differentiation state to determine how the UPR regulates hepatocyte identity and toward what end. RESULTS Machine learning identified a cluster of correlated genes that were profoundly suppressed by persistent ER stress in the liver. These genes, which encode diverse functions including metabolism, coagulation, drug detoxification, and bile synthesis, are likely targets of the master regulator of hepatocyte differentiation HNF4α. The response of these genes to ER stress was phenocopied by liver-specific deletion of HNF4α. Strikingly, while deletion of HNF4α exacerbated liver injury in response to an ER stress challenge, it also diminished UPR activation and partially preserved ER ultrastructure, suggesting attenuated ER stress. Conversely, pharmacological maintenance of hepatocyte identity in vitro enhanced sensitivity to stress. CONCLUSIONS Together, our findings suggest that the UPR regulates hepatocyte identity through HNF4α to protect ER homeostasis even at the expense of liver function.
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Affiliation(s)
- Anit Shah
- Department of Anatomy and Cell Biology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Ian Huck
- Department of Pharmacology, Toxicology, and Therapeutics, Kansas University Medical Center, Kansas City, Kansas, USA
| | - Kaylia Duncan
- Department of Anatomy and Cell Biology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Erica R. Gansemer
- Department of Anatomy and Cell Biology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Kaihua Liu
- Department of Anatomy and Cell Biology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Reed C. Adajar
- Department of Anatomy and Cell Biology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Udayan Apte
- Department of Pharmacology, Toxicology, and Therapeutics, Kansas University Medical Center, Kansas City, Kansas, USA
| | - Mark A. Stamnes
- Department of Molecular Physiology and Biophysics, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - D. Thomas Rutkowski
- Department of Anatomy and Cell Biology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
- Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
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21
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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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22
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Son J, Accili D. Reversing pancreatic β-cell dedifferentiation in the treatment of type 2 diabetes. Exp Mol Med 2023; 55:1652-1658. [PMID: 37524865 PMCID: PMC10474037 DOI: 10.1038/s12276-023-01043-8] [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] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 03/29/2023] [Accepted: 04/24/2023] [Indexed: 08/02/2023] Open
Abstract
The maintenance of glucose homeostasis is fundamental for survival and health. Diabetes develops when glucose homeostasis fails. Type 2 diabetes (T2D) is characterized by insulin resistance and pancreatic β-cell failure. The failure of β-cells to compensate for insulin resistance results in hyperglycemia, which in turn drives altered lipid metabolism and β-cell failure. Thus, insulin secretion by pancreatic β-cells is a primary component of glucose homeostasis. Impaired β-cell function and reduced β-cell mass are found in diabetes. Both features stem from a failure to maintain β-cell identity, which causes β-cells to dedifferentiate into nonfunctional endocrine progenitor-like cells or to trans-differentiate into other endocrine cell types. In this regard, one of the key issues in achieving disease modification is how to reestablish β-cell identity. In this review, we focus on the causes and implications of β-cell failure, as well as its potential reversibility as a T2D treatment.
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Affiliation(s)
- Jinsook Son
- Department of Medicine and Naomi Berrie Diabetes Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA.
| | - Domenico Accili
- Department of Medicine and Naomi Berrie Diabetes Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
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23
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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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24
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Theodoris CV, Xiao L, Chopra A, Chaffin MD, Al Sayed ZR, Hill MC, Mantineo H, Brydon EM, Zeng Z, Liu XS, Ellinor PT. Transfer learning enables predictions in network biology. Nature 2023; 618:616-624. [PMID: 37258680 PMCID: PMC10949956 DOI: 10.1038/s41586-023-06139-9] [Citation(s) in RCA: 78] [Impact Index Per Article: 78.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 04/27/2023] [Indexed: 06/02/2023]
Abstract
Mapping gene networks requires large amounts of transcriptomic data to learn the connections between genes, which impedes discoveries in settings with limited data, including rare diseases and diseases affecting clinically inaccessible tissues. Recently, transfer learning has revolutionized fields such as natural language understanding1,2 and computer vision3 by leveraging deep learning models pretrained on large-scale general datasets that can then be fine-tuned towards a vast array of downstream tasks with limited task-specific data. Here, we developed a context-aware, attention-based deep learning model, Geneformer, pretrained on a large-scale corpus of about 30 million single-cell transcriptomes to enable context-specific predictions in settings with limited data in network biology. During pretraining, Geneformer gained a fundamental understanding of network dynamics, encoding network hierarchy in the attention weights of the model in a completely self-supervised manner. Fine-tuning towards a diverse panel of downstream tasks relevant to chromatin and network dynamics using limited task-specific data demonstrated that Geneformer consistently boosted predictive accuracy. Applied to disease modelling with limited patient data, Geneformer identified candidate therapeutic targets for cardiomyopathy. Overall, Geneformer represents a pretrained deep learning model from which fine-tuning towards a broad range of downstream applications can be pursued to accelerate discovery of key network regulators and candidate therapeutic targets.
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Affiliation(s)
- Christina V Theodoris
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA.
- Harvard Medical School Genetics Training Program, Boston, USA.
| | - Ling Xiao
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Anant Chopra
- Precision Cardiology Laboratory, Bayer US LLC, Cambridge, MA, USA
| | - Mark D Chaffin
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zeina R Al Sayed
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matthew C Hill
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Helene Mantineo
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | - Zexian Zeng
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - X Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Patrick T Ellinor
- Cardiovascular Disease Initiative and Precision Cardiology Laboratory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
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25
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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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26
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Varghese SS, Dhawan S. Senescence: a double-edged sword in beta-cell health and failure? Front Endocrinol (Lausanne) 2023; 14:1196460. [PMID: 37229454 PMCID: PMC10203573 DOI: 10.3389/fendo.2023.1196460] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 04/19/2023] [Indexed: 05/27/2023] Open
Abstract
Cellular senescence is a complex process marked by permanent cell-cycle arrest in response to a variety of stressors, and acts as a safeguard against the proliferation of damaged cells. Senescence is not only a key process underlying aging and development of many diseases, but has also been shown to play a vital role in embryogenesis as well as tissue regeneration and repair. In context of the pancreatic beta-cells, that are essential for maintaining glucose homeostasis, replicative senescence is responsible for the age-related decline in regenerative capacity. Stress induced premature senescence is also a key early event underlying beta-cell failure in both type 1 and type 2 diabetes. Targeting senescence has therefore emerged as a promising therapeutic avenue for diabetes. However, the molecular mechanisms that mediate the induction of beta-cell senescence in response to various stressors remain unclear. Nor do we know if senescence plays any role during beta-cell growth and development. In this perspective, we discuss the significance of senescence in beta-cell homeostasis and pathology and highlight emerging directions in this area that warrant our attention.
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Affiliation(s)
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, United States
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27
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Zhu H, Wang G, Nguyen-Ngoc KV, Kim D, Miller M, Goss G, Kovsky J, Harrington AR, Saunders DC, Hopkirk AL, Melton R, Powers AC, Preissl S, Spagnoli FM, Gaulton KJ, Sander M. Understanding cell fate acquisition in stem-cell-derived pancreatic islets using single-cell multiome-inferred regulomes. Dev Cell 2023; 58:727-743.e11. [PMID: 37040771 PMCID: PMC10175223 DOI: 10.1016/j.devcel.2023.03.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 01/06/2023] [Accepted: 03/14/2023] [Indexed: 04/13/2023]
Abstract
Pancreatic islet cells derived from human pluripotent stem cells hold great promise for modeling and treating diabetes. Differences between stem-cell-derived and primary islets remain, but molecular insights to inform improvements are limited. Here, we acquire single-cell transcriptomes and accessible chromatin profiles during in vitro islet differentiation and pancreas from childhood and adult donors for comparison. We delineate major cell types, define their regulomes, and describe spatiotemporal gene regulatory relationships between transcription factors. CDX2 emerged as a regulator of enterochromaffin-like cells, which we show resemble a transient, previously unrecognized, serotonin-producing pre-β cell population in fetal pancreas, arguing against a proposed non-pancreatic origin. Furthermore, we observe insufficient activation of signal-dependent transcriptional programs during in vitro β cell maturation and identify sex hormones as drivers of β cell proliferation in childhood. Altogether, our analysis provides a comprehensive understanding of cell fate acquisition in stem-cell-derived islets and a framework for manipulating cell identities and maturity.
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Affiliation(s)
- Han Zhu
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Gaowei Wang
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Kim-Vy Nguyen-Ngoc
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Dongsu Kim
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Michael Miller
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Georgina Goss
- Centre for Gene Therapy and Regenerative Medicine, King's College London, London SE1 9RT, UK
| | - Jenna Kovsky
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Austin R Harrington
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Diane C Saunders
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232-0475, USA
| | - Alexander L Hopkirk
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232-0475, USA
| | - Rebecca Melton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, USA; Pediatric Diabetes Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Alvin C Powers
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232-0475, USA; Department of Molecular Physiology & Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232-0615, USA; VA Tennessee Valley Healthcare System, Nashville, TN 37212-2637, USA
| | - Sebastian Preissl
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Francesca M Spagnoli
- Centre for Gene Therapy and Regenerative Medicine, King's College London, London SE1 9RT, UK
| | - Kyle J Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093-0653, 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 92093-0653, 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.
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28
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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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29
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Aguayo-Mazzucato C, Stitzel ML. "FunDNAmethyl" Mechanism for Developmental Restriction of a β-Cell Subpopulation. Diabetes 2023; 72:557-559. [PMID: 37146281 PMCID: PMC10130483 DOI: 10.2337/dbi23-0001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Affiliation(s)
- Cristina Aguayo-Mazzucato
- Section on Islet Cell and Regenerative Biology, Joslin Diabetes Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Michael L. Stitzel
- The Jackson Laboratory for Genomic Medicine, Farmington, CT
- Department of Genetics and Genome Sciences, Institute for Systems Genomics, UConn Health, Farmington, CT
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30
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Huang X, Gu W, Zhang J, Lan Y, Colarusso JL, Li S, Pertl C, Lu J, Kim H, Zhu J, Breault DT, Sévigny J, Zhou Q. Stomach-derived human insulin-secreting organoids restore glucose homeostasis. Nat Cell Biol 2023; 25:778-786. [PMID: 37106062 DOI: 10.1038/s41556-023-01130-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 03/15/2023] [Indexed: 04/29/2023]
Abstract
Gut stem cells are accessible by biopsy and propagate robustly in culture, offering an invaluable resource for autologous cell therapies. Insulin-producing cells can be induced in mouse gut, but it has not been possible to generate abundant and durable insulin-secreting cells from human gut tissues to evaluate their potential as a cell therapy for diabetes. Here we describe a protocol to differentiate cultured human gastric stem cells into pancreatic islet-like organoids containing gastric insulin-secreting (GINS) cells that resemble β-cells in molecular hallmarks and function. Sequential activation of the inducing factors NGN3 and PDX1-MAFA led human gastric stem cells onto a distinctive differentiation path, including a SOX4High endocrine and GalaninHigh GINS precursor, before adopting β-cell identity, at efficiencies close to 70%. GINS organoids acquired glucose-stimulated insulin secretion in 10 days and restored glucose homeostasis for over 100 days in diabetic mice after transplantation, providing proof of concept for a promising approach to treat diabetes.
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Affiliation(s)
- Xiaofeng Huang
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Wei Gu
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jiaoyue Zhang
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Ying Lan
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jonathan L Colarusso
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Sanlan Li
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Christoph Pertl
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jiaqi Lu
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Hyunkee Kim
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jian Zhu
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Endocrinology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - David T Breault
- Division of Endocrinology, Boston Children's Hospital and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Jean Sévigny
- Département de Microbiologie-Infectiologie et d'Immunologie, Faculté de Médecine, Université Laval, Quebec City, Quebec, Canada
- Centre de recherche du CHU de Québec-Université Laval, Quebec City, Quebec, Canada
| | - Qiao Zhou
- Division of Regenerative Medicine and Hartman Institute for Therapeutic Organ Regeneration, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
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31
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Chung JY, Ma Y, Zhang D, Bickerton HH, Stokes E, Patel SB, Tse HM, Feduska J, Welner RS, Banerjee RR. Pancreatic islet cell type-specific transcriptomic changes during pregnancy and postpartum. iScience 2023; 26:106439. [PMID: 37020962 PMCID: PMC10068570 DOI: 10.1016/j.isci.2023.106439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/11/2023] [Accepted: 03/14/2023] [Indexed: 03/19/2023] Open
Abstract
Pancreatic β-cell mass expands during pregnancy and regresses in the postpartum period in conjunction with dynamic metabolic demands on maternal glucose homeostasis. To understand transcriptional changes driving these adaptations in β-cells and other islet cell types, we performed single-cell RNA sequencing on islets from virgin, late gestation, and early postpartum mice. We identified transcriptional signatures unique to gestation and the postpartum in β-cells, including induction of the AP-1 transcription factor subunits and other genes involved in the immediate-early response (IEGs). In addition, we found pregnancy and postpartum-induced changes differed within each endocrine cell type, and in endothelial cells and antigen-presenting cells within islets. Together, our data reveal insights into cell type-specific transcriptional changes responsible for adaptations by islet cells to pregnancy and their resolution postpartum.
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Affiliation(s)
- Jin-Yong Chung
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA
| | - Yongjie Ma
- Department of Pharmacology, the University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Dingguo Zhang
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, The University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Hayden H. Bickerton
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, The University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Eric Stokes
- Department of Pharmacology, University of Colorado Denver/Anschutz, Aurora, CO 80045, USA
| | - Sweta B. Patel
- Division of Hematology and Oncology, Department of Medicine, The University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Hubert M. Tse
- Department of Microbiology, the University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Joseph Feduska
- Department of Microbiology, the University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Rob S. Welner
- Division of Hematology and Oncology, Department of Medicine, The University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Ronadip R. Banerjee
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA
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Koppes EA, Johnson MA, Moresco JJ, Luppi P, Lewis DW, Stolz DB, Diedrich JK, Yates JR, Wek RC, Watkins SC, Gollin SM, Park HJ, Drain P, Nicholls RD. Insulin secretion deficits in a Prader-Willi syndrome β-cell model are associated with a concerted downregulation of multiple endoplasmic reticulum chaperones. PLoS Genet 2023; 19:e1010710. [PMID: 37068109 PMCID: PMC10138222 DOI: 10.1371/journal.pgen.1010710] [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: 06/18/2022] [Revised: 04/27/2023] [Accepted: 03/21/2023] [Indexed: 04/18/2023] Open
Abstract
Prader-Willi syndrome (PWS) is a multisystem disorder with neurobehavioral, metabolic, and hormonal phenotypes, caused by loss of expression of a paternally-expressed imprinted gene cluster. Prior evidence from a PWS mouse model identified abnormal pancreatic islet development with retention of aged insulin and deficient insulin secretion. To determine the collective roles of PWS genes in β-cell biology, we used genome-editing to generate isogenic, clonal INS-1 insulinoma lines having 3.16 Mb deletions of the silent, maternal- (control) and active, paternal-allele (PWS). PWS β-cells demonstrated a significant cell autonomous reduction in basal and glucose-stimulated insulin secretion. Further, proteomic analyses revealed reduced levels of cellular and secreted hormones, including all insulin peptides and amylin, concomitant with reduction of at least ten endoplasmic reticulum (ER) chaperones, including GRP78 and GRP94. Critically, differentially expressed genes identified by whole transcriptome studies included reductions in levels of mRNAs encoding these secreted peptides and the group of ER chaperones. In contrast to the dosage compensation previously seen for ER chaperones in Grp78 or Grp94 gene knockouts or knockdown, compensation is precluded by the stress-independent deficiency of ER chaperones in PWS β-cells. Consistent with reduced ER chaperones levels, PWS INS-1 β-cells are more sensitive to ER stress, leading to earlier activation of all three arms of the unfolded protein response. Combined, the findings suggest that a chronic shortage of ER chaperones in PWS β-cells leads to a deficiency of protein folding and/or delay in ER transit of insulin and other cargo. In summary, our results illuminate the pathophysiological basis of pancreatic β-cell hormone deficits in PWS, with evolutionary implications for the multigenic PWS-domain, and indicate that PWS-imprinted genes coordinate concerted regulation of ER chaperone biosynthesis and β-cell secretory pathway function.
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Affiliation(s)
- Erik A Koppes
- Division of Genetic and Genomic Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Marie A Johnson
- Division of Genetic and Genomic Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - James J Moresco
- Department of Molecular Medicine and Neurobiology, The Scripps Research Institute, La Jolla, California, United States of America
| | - Patrizia Luppi
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Dale W Lewis
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, United States of America
| | - Donna B Stolz
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Jolene K Diedrich
- Department of Molecular Medicine and Neurobiology, The Scripps Research Institute, La Jolla, California, United States of America
| | - John R Yates
- Department of Molecular Medicine and Neurobiology, The Scripps Research Institute, La Jolla, California, United States of America
| | - Ronald C Wek
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana, United States of America
| | - Simon C Watkins
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Susanne M Gollin
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, United States of America
| | - Hyun Jung Park
- Department of Human Genetics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, United States of America
| | - Peter Drain
- Department of Cell Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Robert D Nicholls
- Division of Genetic and Genomic Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
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Rubio-Navarro A, Gómez-Banoy N, Stoll L, Dündar F, Mawla AM, Ma L, Cortada E, Zumbo P, Li A, Reiterer M, Montoya-Oviedo N, Homan EA, Imai N, Gilani A, Liu C, Naji A, Yang B, Chong ACN, Cohen DE, Chen S, Cao J, Pitt GS, Huising MO, Betel D, Lo JC. A beta cell subset with enhanced insulin secretion and glucose metabolism is reduced in type 2 diabetes. Nat Cell Biol 2023; 25:565-578. [PMID: 36928765 PMCID: PMC10449536 DOI: 10.1038/s41556-023-01103-1] [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: 05/11/2022] [Accepted: 02/02/2023] [Indexed: 03/18/2023]
Abstract
The pancreatic islets are composed of discrete hormone-producing cells that orchestrate systemic glucose homeostasis. Here we identify subsets of beta cells using a single-cell transcriptomic approach. One subset of beta cells marked by high CD63 expression is enriched for the expression of mitochondrial metabolism genes and exhibits higher mitochondrial respiration compared with CD63lo beta cells. Human and murine pseudo-islets derived from CD63hi beta cells demonstrate enhanced glucose-stimulated insulin secretion compared with pseudo-islets from CD63lo beta cells. We show that CD63hi beta cells are diminished in mouse models of and in humans with type 2 diabetes. Finally, transplantation of pseudo-islets generated from CD63hi but not CD63lo beta cells into diabetic mice restores glucose homeostasis. These findings suggest that loss of a specific subset of beta cells may lead to diabetes. Strategies to reconstitute or maintain CD63hi beta cells may represent a potential anti-diabetic therapy.
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Affiliation(s)
- Alfonso Rubio-Navarro
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Excellence Research Unit "Modeling Nature" (MNat), CTS-963-Center of Biomedical Research (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), University Hospitals of Granada-University of Granada, Granada, Spain
| | - Nicolás Gómez-Banoy
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Lisa Stoll
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Friederike Dündar
- Department of Physiology and Biophysics, Applied Bioinformatics Core, Weill Cornell Medicine, New York, NY, USA
| | - Alex M Mawla
- Department of Neurobiology, Physiology and Behavior, College of Biological Sciences, University of California, Davis, CA, USA
| | - Lunkun Ma
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Eric Cortada
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Paul Zumbo
- Department of Physiology and Biophysics, Applied Bioinformatics Core, Weill Cornell Medicine, New York, NY, USA
| | - Ang Li
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Moritz Reiterer
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Nathalia Montoya-Oviedo
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Lipids and Diabetes Laboratory, Department of Physiological Sciences, Faculty of Medicine, National University of Colombia, Bogotá, Colombia
| | - Edwin A Homan
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Norihiro Imai
- Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Gastroenterology and Hepatology, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Ankit Gilani
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Boris Yang
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | | | - David E Cohen
- Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA
| | - Jingli Cao
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Geoffrey S Pitt
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Mark O Huising
- Department of Neurobiology, Physiology and Behavior, College of Biological Sciences, University of California, Davis, CA, USA
- Department of Physiology and Membrane Biology, School of Medicine, University of California Davis, Davis, CA, USA
| | - Doron Betel
- Department of Physiology and Biophysics, Applied Bioinformatics Core, Weill Cornell Medicine, New York, NY, USA
- Institute for Computational Biomedicine, Division of Hematology and Medical Oncology, Applied Bioinformatics Core, Weill Cornell Medicine, New York, NY, USA
| | - James C Lo
- Weill Center for Metabolic Health, Cardiovascular Research Institute, Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
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Fu Q, Jiang H, Qian Y, Lv H, Dai H, Zhou Y, Chen Y, He Y, Gao R, Zheng S, Liang Y, Li S, Xu X, Xu K, Yang T. Single-cell RNA sequencing combined with single-cell proteomics identifies the metabolic adaptation of islet cell subpopulations to high-fat diet in mice. Diabetologia 2023; 66:724-740. [PMID: 36538064 PMCID: PMC9765371 DOI: 10.1007/s00125-022-05849-5] [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: 06/05/2022] [Accepted: 10/13/2022] [Indexed: 12/24/2022]
Abstract
AIMS/HYPOTHESIS Islets have complex heterogeneity and subpopulations. Cell surface markers representing alpha, beta and delta cell subpopulations are urgently needed for investigations to explore the compositional changes of each subpopulation in obesity progress and diabetes onset, and the adaptation mechanism of islet metabolism induced by a high-fat diet (HFD). METHODS Single-cell RNA sequencing (scRNA-seq) was applied to identify alpha, beta and delta cell subpopulation markers in an HFD-induced mouse model of glucose intolerance. Flow cytometry and immunostaining were used to sort and assess the proportion of each subpopulation. Single-cell proteomics was performed on sorted cells, and the functional status of each alpha, beta and delta cell subpopulation in glucose intolerance was deeply elucidated based on protein expression. RESULTS A total of 33,999 cells were analysed by scRNA-seq and clustered into eight populations, including alpha, beta and delta cells. For alpha cells, scRNA-seq revealed that the Ace2low subpopulation had downregulated expression of genes related to alpha cell function and upregulated expression of genes associated with beta cell characteristics in comparison with the Ace2high subpopulation. The impaired function and increased fragility of ACE2low alpha cells exposure to HFD was further suggested by single-cell proteomics. As for beta cells, the CD81high subpopulation may indicate an immature signature of beta cells compared with the CD81low subpopulation, which had robust function. We also found differential expression of Slc2a2 in delta cells and a potentially stronger cellular function and metabolism in GLUT2low delta cells than GLUT2high delta cells. Moreover, an increased proportion of ACE2low alpha cells and CD81low beta cells, with a constant proportion of GLUT2low delta cells, were observed in HFD-induced glucose intolerance. CONCLUSIONS/INTERPRETATION We identified ACE2, CD81 and GLUT2 as surface markers to distinguish, respectively, alpha, beta and delta cell subpopulations with heterogeneous maturation and function. The changes in the proportion and functional status of islet endocrine subpopulations reflect the metabolic adaptation of islets to high-fat stress, which weakened the function of alpha cells and enhanced the function of beta and delta cells to bring about glycaemic homeostasis. Our findings provide a fundamental resource for exploring the mechanisms maintaining each islet endocrine subpopulation's fate and function in health and disease. DATA AVAILABILITY The scRNA-seq analysis datasets from the current study are available in the Gene Expression Omnibus (GEO) repository under the accession number GSE203376.
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Affiliation(s)
- Qi Fu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hemin Jiang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yu Qian
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hui Lv
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hao Dai
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yuncai Zhou
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yang Chen
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yunqiang He
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Rui Gao
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shuai Zheng
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yucheng Liang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Siqi Li
- BGI-Shenzhen, Shenzhen, China
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, Wuhan, China
| | - Xinyu Xu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kuanfeng Xu
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
| | - Tao Yang
- Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Miranda MA, Macias-Velasco JF, Schmidt H, Lawson HA. Integrated transcriptomics contrasts fatty acid metabolism with hypoxia response in β-cell subpopulations associated with glycemic control. BMC Genomics 2023; 24:156. [PMID: 36978008 PMCID: PMC10052828 DOI: 10.1186/s12864-023-09232-5] [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: 05/24/2022] [Accepted: 03/07/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND Understanding how heterogeneous β-cell function impacts diabetes is imperative for therapy development. Standard single-cell RNA sequencing analysis illuminates some factors driving heterogeneity, but new strategies are required to enhance information capture. RESULTS We integrate pancreatic islet single-cell and bulk RNA sequencing data to identify β-cell subpopulations based on gene expression and characterize genetic networks associated with β-cell function in obese SM/J mice. We identify β-cell subpopulations associated with basal insulin secretion, hypoxia response, cell polarity, and stress response. Network analysis associates fatty acid metabolism and basal insulin secretion with hyperglycemic-obesity, while expression of Pdyn and hypoxia response is associated with normoglycemic-obesity. CONCLUSIONS By integrating single-cell and bulk islet transcriptomes, our study explores β-cell heterogeneity and identifies novel subpopulations and genetic pathways associated with β-cell function in obesity.
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Affiliation(s)
- Mario A Miranda
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave, Campus Box 8232, Saint Louis, MO, 63110, USA
| | - Juan F Macias-Velasco
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave, Campus Box 8232, Saint Louis, MO, 63110, USA
| | - Heather Schmidt
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave, Campus Box 8232, Saint Louis, MO, 63110, USA
| | - Heather A Lawson
- Department of Genetics, Washington University School of Medicine, 660 South Euclid Ave, Campus Box 8232, Saint Louis, MO, 63110, USA.
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Cell Replacement Therapy for Type 1 Diabetes Patients: Potential Mechanisms Leading to Stem-Cell-Derived Pancreatic β-Cell Loss upon Transplant. Cells 2023; 12:cells12050698. [PMID: 36899834 PMCID: PMC10000642 DOI: 10.3390/cells12050698] [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: 11/16/2022] [Revised: 02/09/2023] [Accepted: 02/20/2023] [Indexed: 02/25/2023] Open
Abstract
Cell replacement therapy using stem-cell-derived insulin-producing β-like cells (sBCs) has been proposed as a practical cure for patients with type one diabetes (T1D). sBCs can correct diabetes in preclinical animal models, demonstrating the promise of this stem cell-based approach. However, in vivo studies have demonstrated that most sBCs, similarly to cadaveric human islets, are lost upon transplantation due to ischemia and other unknown mechanisms. Hence, there is a critical knowledge gap in the current field concerning the fate of sBCs upon engraftment. Here we review, discuss effects, and propose additional potential mechanisms that could contribute toward β-cell loss in vivo. We summarize and highlight some of the literature on phenotypic loss in β-cells under both steady, stressed, and diseased diabetic conditions. Specifically, we focus on β-cell death, dedifferentiation into progenitors, trans-differentiation into other hormone-expressing cells, and/or interconversion into less functional β-cell subtypes as potential mechanisms. While current cell replacement therapy efforts employing sBCs carry great promise as an abundant cell source, addressing the somewhat neglected aspect of β-cell loss in vivo will further accelerate sBC transplantation as a promising therapeutic modality that could significantly enhance the life quality of T1D patients.
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Brownrigg GP, Xia YH, Chu CMJ, Wang S, Chao C, Zhang JA, Skovsø S, Panzhinskiy E, Hu X, Johnson JD, Rideout EJ. Sex differences in islet stress responses support female β cell resilience. Mol Metab 2023; 69:101678. [PMID: 36690328 PMCID: PMC9971554 DOI: 10.1016/j.molmet.2023.101678] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 01/07/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023] Open
Abstract
OBJECTIVE Pancreatic β cells play a key role in maintaining glucose homeostasis; dysfunction of this critical cell type causes type 2 diabetes (T2D). Emerging evidence points to sex differences in β cells, but few studies have examined male-female differences in β cell stress responses and resilience across multiple contexts, including diabetes. Here, we address the need for high-quality information on sex differences in β cell and islet gene expression and function using both human and rodent samples. METHODS In humans, we compared β cell gene expression and insulin secretion in donors with T2D to non-diabetic donors in both males and females. In mice, we generated a well-powered islet RNAseq dataset from 20-week-old male and female siblings with similar insulin sensitivity. Our unbiased gene expression analysis pointed to a sex difference in the endoplasmic reticulum (ER) stress response. Based on this analysis, we hypothesized female islets would be more resilient to ER stress than male islets. To test this, we subjected islets isolated from age-matched male and female mice to thapsigargin treatment and monitored protein synthesis, cell death, and β cell insulin production and secretion. Transcriptomic and proteomic analyses were used to characterize sex differences in islet responses to ER stress. RESULTS Our single-cell analysis of human β cells revealed sex-specific changes to gene expression and function in T2D, correlating with more robust insulin secretion in human islets isolated from female donors with T2D compared to male donors with T2D. In mice, RNA sequencing revealed differential enrichment of unfolded protein response pathway-associated genes, where female islets showed higher expression of genes linked with protein synthesis, folding, and processing. This differential expression was physiologically significant, as islets isolated from female mice were more resilient to ER stress induction with thapsigargin. Specifically, female islets showed a greater ability to maintain glucose-stimulated insulin production and secretion during ER stress compared with males. CONCLUSIONS Our data demonstrate sex differences in β cell gene expression in both humans and mice, and that female β cells show a greater ability to maintain glucose-stimulated insulin secretion across multiple physiological and pathological contexts.
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Affiliation(s)
- George P Brownrigg
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Yi Han Xia
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Chieh Min Jamie Chu
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Su Wang
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Charlotte Chao
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Jiashuo Aaron Zhang
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Søs Skovsø
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Evgeniy Panzhinskiy
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - Xiaoke Hu
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada
| | - James D Johnson
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada.
| | - Elizabeth J Rideout
- Department of Cellular and Physiological Sciences, Life Sciences Institute, The University of British Columbia, 2350 Health Sciences Mall, Vancouver, BC, V6T 1Z3, Canada.
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Lin H, Ye Z, Xu R, Li XE, Sun B. The transcription factor JUN is a major regulator of quiescent pancreatic stellate cell maintenance. Gene X 2023; 851:147000. [DOI: 10.1016/j.gene.2022.147000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/01/2022] [Accepted: 10/18/2022] [Indexed: 11/27/2022] Open
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Pancreatic Islet Cells Response to IFNγ Relies on Their Spatial Location within an Islet. Cells 2022; 12:cells12010113. [PMID: 36611907 PMCID: PMC9818682 DOI: 10.3390/cells12010113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 12/19/2022] [Accepted: 12/23/2022] [Indexed: 12/30/2022] Open
Abstract
Type 1 diabetes (T1D) is an auto-immune disease characterized by the progressive destruction of insulin-producing pancreatic beta cells. While beta cells are the target of the immune attack, the other islet endocrine cells, namely the alpha and delta cells, can also be affected by the inflammatory milieu. Here, using a flow cytometry-based strategy, we compared the impact of IFNγ, one of the main cytokines involved in T1D, on the three endocrine cell subsets isolated from C57BL/6 mouse islets. RNA-seq analyses revealed that alpha and delta cells exposed in vitro to IFNγ display a transcriptomic profile very similar to that of beta cells, with an increased expression of inflammation key genes such as MHC class I molecules, the CXCL10 chemokine and the programmed death-ligand 1 (PD-L1), three hallmarks of IFNγ signaling. Interestingly, at low IFNγ concentration, we observed two beta cell populations (responders and non-responders) based on PD-L1 protein expression. Our data indicate that this differential sensitivity relies on the location of the cells within the islet rather than on the existence of two different beta cells subsets. The same findings were corroborated by the in vivo analysis of pancreatic islets from the non-obese diabetic mouse model of T1D, showing more intense PD-L1 staining on endocrine cells close to immune infiltrate. Collectively, our work demonstrates that alpha and delta cells are as sensitive as beta cells to IFNγ, and suggests a gradual diffusion of the cytokine into an islet. These observations provide novel insights into the in situ inflammatory processes occurring in T1D progression.
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Subramanian A, Alperovich M, Yang Y, Li B. Biology-inspired data-driven quality control for scientific discovery in single-cell transcriptomics. Genome Biol 2022; 23:267. [PMID: 36575523 PMCID: PMC9793662 DOI: 10.1186/s13059-022-02820-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/23/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Quality control (QC) of cells, a critical first step in single-cell RNA sequencing data analysis, has largely relied on arbitrarily fixed data-agnostic thresholds applied to QC metrics such as gene complexity and fraction of reads mapping to mitochondrial genes. The few existing data-driven approaches perform QC at the level of samples or studies without accounting for biological variation. RESULTS We first demonstrate that QC metrics vary with both tissue and cell types across technologies, study conditions, and species. We then propose data-driven QC (ddqc), an unsupervised adaptive QC framework to perform flexible and data-driven QC at the level of cell types while retaining critical biological insights and improved power for downstream analysis. ddqc applies an adaptive threshold based on the median absolute deviation on four QC metrics (gene and UMI complexity, fraction of reads mapping to mitochondrial and ribosomal genes). ddqc retains over a third more cells when compared to conventional data-agnostic QC filters. Finally, we show that ddqc recovers biologically meaningful trends in gradation of gene complexity among cell types that can help answer questions of biological interest such as which cell types express the least and most number of transcripts overall, and ribosomal transcripts specifically. CONCLUSIONS ddqc retains cell types such as metabolically active parenchymal cells and specialized cells such as neutrophils which are often lost by conventional QC. Taken together, our work proposes a revised paradigm to quality filtering best practices-iterative QC, providing a data-driven QC framework compatible with observed biological diversity.
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Affiliation(s)
- Ayshwarya Subramanian
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.38142.3c000000041936754XBrigham and Womens’s Hospital, Harvard Medical School, Boston, USA
| | - Mikhail Alperovich
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786MIT PRIMES, Massachusetts Institute of Technology, Cambridge, MA USA ,Lexington High School, Lexington, MA USA ,grid.422478.f0000 0000 9142 997XPresent Address: Wake Technical Community College, Raleigh, USA
| | - Yiming Yang
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114 USA ,grid.418158.10000 0004 0534 4718Present Address: Department of Cellular and Tissue Genomics, Genentech Inc., South San Francisco, CA USA
| | - Bo Li
- grid.66859.340000 0004 0546 1623Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA USA ,grid.32224.350000 0004 0386 9924Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114 USA ,grid.418158.10000 0004 0534 4718Present Address: Department of Cellular and Tissue Genomics, Genentech Inc., South San Francisco, CA USA ,grid.38142.3c000000041936754XDepartment of Medicine, Harvard Medical School, Boston, MA 02115 USA
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Chu CMJ, Modi H, Ellis C, Krentz NAJ, Skovsø S, Zhao YB, Cen H, Noursadeghi N, Panzhinskiy E, Hu X, Dionne DA, Xia YH, Xuan S, Huising MO, Kieffer TJ, Lynn FC, Johnson JD. Dynamic Ins2 Gene Activity Defines β-Cell Maturity States. Diabetes 2022; 71:2612-2631. [PMID: 36170671 DOI: 10.2337/db21-1065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 09/20/2022] [Indexed: 01/11/2023]
Abstract
Transcriptional and functional cellular specialization has been described for insulin-secreting β-cells of the endocrine pancreas. However, it is not clear whether β-cell heterogeneity is stable or reflects dynamic cellular states. We investigated the temporal kinetics of endogenous insulin gene activity using live cell imaging, with complementary experiments using FACS and single-cell RNA sequencing, in β-cells from Ins2GFP knockin mice. In vivo staining and FACS analysis of islets from Ins2GFP mice confirmed that at a given moment, ∼25% of β-cells exhibited significantly higher activity at the evolutionarily conserved insulin gene, Ins2. Live cell imaging over days captured Ins2 gene activity dynamics in single β-cells. Autocorrelation analysis revealed a subset of oscillating cells, with mean oscillation periods of 17 h. Increased glucose concentrations stimulated more cells to oscillate and resulted in higher average Ins2 gene activity per cell. Single-cell RNA sequencing showed that Ins2(GFP)HIGH β-cells were enriched for markers of β-cell maturity. Ins2(GFP)HIGH β-cells were also significantly less viable at all glucose concentrations and in the context of endoplasmic reticulum stress. Collectively, our results demonstrate that the heterogeneity of insulin production, observed in mouse and human β-cells, can be accounted for by dynamic states of insulin gene activity.
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Affiliation(s)
- Chieh Min Jamie Chu
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Honey Modi
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Cara Ellis
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Nicole A J Krentz
- BC Children's Hospital Research Institute, Department of Surgery, University of British Columbia, Vancouver, Canada
| | - Søs Skovsø
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Yiwei Bernie Zhao
- Biomedical Research Centre, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Haoning Cen
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Nilou Noursadeghi
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Evgeniy Panzhinskiy
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Xiaoke Hu
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Derek A Dionne
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Yi Han Xia
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Shouhong Xuan
- Division of Hematology/Oncology, Department of Medicine, Columbia University Medical Center, New York, NY
| | - Mark O Huising
- Department of Neurobiology, Physiology and Behavior, University of California, Davis, Davis, CA
- Department of Physiology and Membrane Biology, University of California, Davis, Davis, CA
| | - Timothy J Kieffer
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
| | - Francis C Lynn
- BC Children's Hospital Research Institute, Department of Surgery, University of British Columbia, Vancouver, Canada
| | - James D Johnson
- Diabetes Focus Team, Life Sciences Institute, Departments of Cellular and Physiological Sciences and Surgery, University of British Columbia, Vancouver, Canada
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Non-coding variants disrupting a tissue-specific regulatory element in HK1 cause congenital hyperinsulinism. Nat Genet 2022; 54:1615-1620. [PMID: 36333503 PMCID: PMC7614032 DOI: 10.1038/s41588-022-01204-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 09/16/2022] [Indexed: 11/06/2022]
Abstract
Gene expression is tightly regulated, with many genes exhibiting cell-specific silencing when their protein product would disrupt normal cellular function1. This silencing is largely controlled by non-coding elements, and their disruption might cause human disease2. We performed gene-agnostic screening of the non-coding regions to discover new molecular causes of congenital hyperinsulinism. This identified 14 non-coding de novo variants affecting a 42-bp conserved region encompassed by a regulatory element in intron 2 of the hexokinase 1 gene (HK1). HK1 is widely expressed across all tissues except in the liver and pancreatic beta cells and is thus termed a 'disallowed gene' in these specific tissues. We demonstrated that the variants result in a loss of repression of HK1 in pancreatic beta cells, thereby causing insulin secretion and congenital hyperinsulinism. Using epigenomic data accessed from public repositories, we demonstrated that these variants reside within a regulatory region that we determine to be critical for cell-specific silencing. Importantly, this has revealed a disease mechanism for non-coding variants that cause inappropriate expression of a disallowed gene.
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Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space. Nat Commun 2022; 13:6118. [PMID: 36253379 PMCID: PMC9574176 DOI: 10.1038/s41467-022-33758-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 09/30/2022] [Indexed: 12/24/2022] Open
Abstract
Computational tools for integrative analyses of diverse single-cell experiments are facing formidable new challenges including dramatic increases in data scale, sample heterogeneity, and the need to informatively cross-reference new data with foundational datasets. Here, we present SCALEX, a deep-learning method that integrates single-cell data by projecting cells into a batch-invariant, common cell-embedding space in a truly online manner (i.e., without retraining the model). SCALEX substantially outperforms online iNMF and other state-of-the-art non-online integration methods on benchmark single-cell datasets of diverse modalities, (e.g., single-cell RNA sequencing, scRNA-seq, single-cell assay for transposase-accessible chromatin use sequencing, scATAC-seq), especially for datasets with partial overlaps, accurately aligning similar cell populations while retaining true biological differences. We showcase SCALEX's advantages by constructing continuously expandable single-cell atlases for human, mouse, and COVID-19 patients, each assembled from diverse data sources and growing with every new data. The online data integration capacity and superior performance makes SCALEX particularly appropriate for large-scale single-cell applications to build upon previous scientific insights.
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44
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Yong HJ, Toledo MP, Nowakowski RS, Wang YJ. Sex Differences in the Molecular Programs of Pancreatic Cells Contribute to the Differential Risks of Type 2 Diabetes. Endocrinology 2022; 163:bqac156. [PMID: 36130190 PMCID: PMC10409906 DOI: 10.1210/endocr/bqac156] [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: 07/26/2022] [Indexed: 11/19/2022]
Abstract
Epidemiology studies demonstrate that women are at a significantly lower risk of developing type 2 diabetes (T2D) compared to men. However, the molecular basis of this risk difference is not well understood. In this study, we examined the sex differences in the genetic programs of pancreatic endocrine cells. We combined pancreas perifusion data and single-cell genomic data from our laboratory and from publicly available data sets to investigate multiple axes of the sex differences in the human pancreas at the single-cell type and single-cell level. We systematically compared female and male islet secretion function, gene expression program, and regulatory principles of pancreatic endocrine cells. The perifusion data indicate that female endocrine cells have a higher secretion capacity than male endocrine cells. Single-cell RNA-sequencing analysis suggests that endocrine cells in male controls have molecular signatures that resemble T2D. In addition, we identified genomic elements associated with genome-wide association study T2D loci to have differential accessibility between female and male delta cells. These genomic elements may play a sex-specific causal role in the pathogenesis of T2D. We provide molecular mechanisms that explain the differential risk of T2D between women and men. Knowledge gained from our study will accelerate the development of diagnostics and therapeutics in sex-aware precision medicine for diabetes.
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Affiliation(s)
- Hyo Jeong Yong
- Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, Florida 32306, USA
| | - Maria Pilar Toledo
- Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, Florida 32306, USA
| | - Richard S Nowakowski
- Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, Florida 32306, USA
| | - Yue J Wang
- Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, Florida 32306, USA
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Shrestha S, Erikson G, Lyon J, Spigelman AF, Bautista A, Manning Fox JE, dos Santos C, Shokhirev M, Cartailler JP, Hetzer MW, MacDonald PE, Arrojo e Drigo R. Aging compromises human islet beta cell function and identity by decreasing transcription factor activity and inducing ER stress. SCIENCE ADVANCES 2022; 8:eabo3932. [PMID: 36197983 PMCID: PMC9534504 DOI: 10.1126/sciadv.abo3932] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 08/17/2022] [Indexed: 05/02/2023]
Abstract
Pancreatic islet beta cells are essential for maintaining glucose homeostasis. To understand the impact of aging on beta cells, we performed meta-analysis of single-cell RNA sequencing datasets, transcription factor (TF) regulon analysis, high-resolution confocal microscopy, and measured insulin secretion from nondiabetic donors spanning most of the human life span. This revealed the range of molecular and functional changes that occur during beta cell aging, including the transcriptional deregulation that associates with cellular immaturity and reorganization of beta cell TF networks, increased gene transcription rates, and reduced glucose-stimulated insulin release. These alterations associate with activation of endoplasmic reticulum (ER) stress and autophagy pathways. We propose that a chronic state of ER stress undermines old beta cell structure function to increase the risk of beta cell failure and type 2 diabetes onset as humans age.
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Affiliation(s)
- Shristi Shrestha
- Creative Data Solutions, Vanderbilt Center for Stem Cell Biology, Nashville, TN 37232, USA
| | - Galina Erikson
- Integrative Genomics and Bioinformatics Core, Salk Institute of Biological Studies, La Jolla, CA 92037, USA
| | - James Lyon
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta T6G2E1, Canada
| | - Aliya F. Spigelman
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta T6G2E1, Canada
| | - Austin Bautista
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta T6G2E1, Canada
| | - Jocelyn E. Manning Fox
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta T6G2E1, Canada
| | - Cristiane dos Santos
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
| | - Maxim Shokhirev
- Integrative Genomics and Bioinformatics Core, Salk Institute of Biological Studies, La Jolla, CA 92037, USA
| | | | - Martin W. Hetzer
- Molecular and Cell Biology Laboratory, Salk Institute of Biological Studies, La Jolla, CA 92037, USA
| | - Patrick E. MacDonald
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Alberta T6G2E1, Canada
| | - Rafael Arrojo e Drigo
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232, USA
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46
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Rohli KE, Boyer CK, Bearrows SC, Moyer MR, Elison WS, Bauchle CJ, Blom SE, Zhang J, Wang Y, Stephens SB. ER Redox Homeostasis Regulates Proinsulin Trafficking and Insulin Granule Formation in the Pancreatic Islet β-Cell. FUNCTION 2022; 3:zqac051. [PMID: 36325514 PMCID: PMC9614934 DOI: 10.1093/function/zqac051] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/11/2022] [Accepted: 09/21/2022] [Indexed: 01/07/2023] Open
Abstract
Defects in the pancreatic β-cell's secretion system are well-described in type 2 diabetes (T2D) and include impaired proinsulin processing and a deficit in mature insulin-containing secretory granules; however, the cellular mechanisms underlying these defects remain poorly understood. To address this, we used an in situ fluorescent pulse-chase strategy to study proinsulin trafficking. We show that insulin granule formation and the appearance of nascent granules at the plasma membrane are decreased in rodent and cell culture models of prediabetes and hyperglycemia. Moreover, we link the defect in insulin granule formation to an early trafficking delay in endoplasmic reticulum (ER) export of proinsulin, which is independent of overt ER stress. Using a ratiometric redox sensor, we show that the ER becomes hyperoxidized in β-cells from a dietary model of rodent prediabetes and that addition of reducing equivalents restores ER export of proinsulin and insulin granule formation and partially restores β-cell function. Together, these data identify a critical role for the regulation of ER redox homeostasis in proinsulin trafficking and suggest that alterations in ER redox poise directly contribute to the decline in insulin granule production in T2D. This model highlights a critical link between alterations in ER redox and ER function with defects in proinsulin trafficking in T2D. Hyperoxidation of the ER lumen, shown as hydrogen peroxide, impairs proinsulin folding and disulfide bond formation that prevents efficient exit of proinsulin from the ER to the Golgi. This trafficking defect limits available proinsulin for the formation of insulin secretory granules during the development of T2D.
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Affiliation(s)
- Kristen E Rohli
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, Division of Endocrinology and Metabolism, University of Iowa, Iowa City, IA 52242, USA
| | - Cierra K Boyer
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Department of Pharmacology, University of Iowa, Iowa City, IA 52242, USA
| | - Shelby C Bearrows
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, Division of Endocrinology and Metabolism, University of Iowa, Iowa City, IA 52242, USA
| | - Marshall R Moyer
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, Division of Endocrinology and Metabolism, University of Iowa, Iowa City, IA 52242, USA
| | - Weston S Elison
- Department of Nutrition, Dietetics, and Food Science, Brigham Young University, Provo, UT 84602, USA
| | - Casey J Bauchle
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, Division of Endocrinology and Metabolism, University of Iowa, Iowa City, IA 52242, USA
| | - Sandra E Blom
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, Division of Endocrinology and Metabolism, University of Iowa, Iowa City, IA 52242, USA
| | - Jianchao Zhang
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48103, USA
| | - Yanzhuang Wang
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI 48103, USA
- Department of Neurology, School of Medicine, University of Michigan, Ann Arbor, MI 48103, USA
| | - Samuel B Stephens
- Fraternal Order of Eagles Diabetes Research Center, University of Iowa, Iowa City, IA 52242, USA
- Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa City, IA 52242, USA
- Department of Internal Medicine, Division of Endocrinology and Metabolism, University of Iowa, Iowa City, IA 52242, USA
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47
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Yu L, Li L, Liu J, Sun H, Li X, Xiao H, Alfred MO, Wang M, Wu X, Gao Y, Luo C. Recombinant Reg3α Prevents Islet β-Cell Apoptosis and Promotes β-Cell Regeneration. Int J Mol Sci 2022; 23:ijms231810584. [PMID: 36142497 PMCID: PMC9504149 DOI: 10.3390/ijms231810584] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 09/05/2022] [Accepted: 09/09/2022] [Indexed: 11/16/2022] Open
Abstract
Progressive loss and dysfunction of islet β-cells has not yet been solved in the treatment of diabetes. Regenerating protein (Reg) has been identified as a trophic factor which is demonstrated to be associated with pancreatic tissue regeneration. We previously produced recombinant Reg3α protein (rReg3α) and proved that it protects against acute pancreatitis in mice. Whether rReg3α protects islet β-cells in diabetes has been elusive. In the present study, rReg3α stimulated MIN6 cell proliferation and resisted STZ-caused cell death. The protective effect of rReg3α was also found in mouse primary islets. In BALB/c mice, rReg3α administration largely alleviated STZ-induced diabetes by the preservation of β-cell mass. The protective mechanism could be attributed to Akt/Bcl-2/-xL activation and GRP78 upregulation. Scattered insulin-expressing cells and clusters with small size, low insulin density, and exocrine distribution were observed and considered to be neogenic. In isolated acinar cells with wheat germ agglutinin (WGA) labeling, rReg3α treatment generated insulin-producing cells through Stat3/Ngn3 signaling, but these cells were not fully functional in response to glucose stimulation. Our results demonstrated that rReg3α resists STZ-induced β-cell death and promotes β-cell regeneration. rReg3α could serve as a potential drug for β-cell maintenance in anti-diabetic treatment.
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Affiliation(s)
- Luting Yu
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 210037, China
| | - Liang Li
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
| | - Junli Liu
- MeDiC Program, The Research Institute of McGill University Health Centre, Division of Endocrinology and Metabolism, Department of Medicine, McGill University, Montreal, QC H3A 0G4, Canada
| | - Hao Sun
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
| | - Xiang Li
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
| | - Hanyu Xiao
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
| | - Martin Omondi Alfred
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
- Institute of Primate Research, End of Karen Road, Karen, Nairobi P.O. Box 24481-00502, Kenya
| | - Min Wang
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
- State Key Laboratory of Nature Medicines, China Pharmaceutical University, Nanjing 210009, China
| | - Xuri Wu
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
- State Key Laboratory of Nature Medicines, China Pharmaceutical University, Nanjing 210009, China
| | - Yan Gao
- Institute of Suzhou Biobank, Suzhou Center for Disease Prevention and Control, Suzhou 215007, China
- Suzhou Institute of Advanced Study in Public Health, Gusu School, Nanjing Medical University, Suzhou 210029, China
- Correspondence: (Y.G.); (C.L.); Tel.: +86-0512-6826-2385 (Y.G.); +86-138-1388-3828 (C.L.)
| | - Chen Luo
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 210009, China
- State Key Laboratory of Nature Medicines, China Pharmaceutical University, Nanjing 210009, China
- Correspondence: (Y.G.); (C.L.); Tel.: +86-0512-6826-2385 (Y.G.); +86-138-1388-3828 (C.L.)
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48
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Tritschler S, Thomas M, Böttcher A, Ludwig B, Schmid J, Schubert U, Kemter E, Wolf E, Lickert H, Theis FJ. A transcriptional cross species map of pancreatic islet cells. Mol Metab 2022; 66:101595. [PMID: 36113773 PMCID: PMC9526148 DOI: 10.1016/j.molmet.2022.101595] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 08/20/2022] [Accepted: 09/03/2022] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE Pancreatic islets of Langerhans secrete hormones to regulate systemic glucose levels. Emerging evidence suggests that islet cells are functionally heterogeneous to allow a fine-tuned and efficient endocrine response to physiological changes. A precise description of the molecular basis of this heterogeneity, in particular linking animal models to human islets, is an important step towards identifying the factors critical for endocrine cell function in physiological and pathophysiological conditions. METHODS In this study, we used single-cell RNA sequencing to profile more than 50'000 endocrine cells isolated from healthy human, pig and mouse pancreatic islets and characterize transcriptional heterogeneity and evolutionary conservation of those cells across the three species. We systematically delineated endocrine cell types and α- and β-cell heterogeneity through prior knowledge- and data-driven gene sets shared across species, which altogether capture common and differential cellular properties, transcriptional dynamics and putative driving factors of state transitions. RESULTS We showed that global endocrine expression profiles correlate, and that critical identity and functional markers are shared between species, while only approximately 20% of cell type enriched expression is conserved. We resolved distinct human α- and β-cell states that form continuous transcriptional landscapes. These states differentially activate maturation and hormone secretion programs, which are related to regulatory hormone receptor expression, signaling pathways and different types of cellular stress responses. Finally, we mapped mouse and pig cells to the human reference and observed that the spectrum of human α- and β-cell heterogeneity and aspects of such functional gene expression are better recapitulated in the pig than mouse data. CONCLUSIONS Here, we provide a high-resolution transcriptional map of healthy human islet cells and their murine and porcine counterparts, which is easily queryable via an online interface. This comprehensive resource informs future efforts that focus on pancreatic endocrine function, failure and regeneration, and enables to assess molecular conservation in islet biology across species for translational purposes.
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Affiliation(s)
- Sophie Tritschler
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Technical University of Munich, School of Life Sciences Weihenstephan, 85354 Freising, Germany
| | - Moritz Thomas
- Technical University of Munich, School of Life Sciences Weihenstephan, 85354 Freising, Germany; Institute of AI for Health, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Anika Böttcher
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Barbara Ludwig
- Department of Medicine III, University Hospital Carl Gustav Carus, Technical University of Dresden, 01307 Dresden, Germany; Paul Langerhans Institute Dresden of Helmholtz Zentrum München, University Hospital Carl Gustav Carus, Technical University of Dresden, 01307 Dresden, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
| | - Janine Schmid
- Department of Medicine III, University Hospital Carl Gustav Carus, Technical University of Dresden, 01307 Dresden, Germany
| | - Undine Schubert
- Department of Medicine III, University Hospital Carl Gustav Carus, Technical University of Dresden, 01307 Dresden, Germany
| | - Elisabeth Kemter
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany; Chair for Molecular Animal Breeding and Biotechnology, Gene Center, LMU Munich, 81377 Munich, Germany; Center for Innovative Medical Models (CiMM), Department of Veterinary Sciences, LMU Munich, 85764 Oberschleißheim, Germany
| | - Eckhard Wolf
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany; Chair for Molecular Animal Breeding and Biotechnology, Gene Center, LMU Munich, 81377 Munich, Germany; Center for Innovative Medical Models (CiMM), Department of Veterinary Sciences, LMU Munich, 85764 Oberschleißheim, Germany
| | - Heiko Lickert
- Institute of Diabetes and Regeneration Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Stem Cell Research, Helmholtz Zentrum München, 85764 Neuherberg, Germany; German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany; Technical University of Munich, Medical Faculty, 81675 Munich, Germany.
| | - Fabian J Theis
- Institute of Computational Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany; Technical University of Munich, Department of Mathematics, 85748 Garching b. Munich, Germany.
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Abstract
Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area.
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Affiliation(s)
| | - Nils Wierup
- Lund University Diabetes Centre, Malmö, Sweden.
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50
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Yang X, Raum JC, Kim J, Yu R, Yang J, Rice G, Li C, Won KJ, Stanescu DE, Stoffers DA. A PDX1 cistrome and single-cell transcriptome resource of the developing pancreas. Development 2022; 149:dev200432. [PMID: 35708349 PMCID: PMC9340549 DOI: 10.1242/dev.200432] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/31/2022] [Indexed: 09/09/2023]
Abstract
Pancreatic and duodenal homeobox 1 (PDX1) is crucial for pancreas organogenesis, yet the dynamic changes in PDX1 binding in human or mouse developing pancreas have not been examined. To address this knowledge gap, we performed PDX1 ChIP-seq and single-cell RNA-seq using fetal human pancreata. We integrated our datasets with published datasets and revealed the dynamics of PDX1 binding and potential cell lineage-specific PDX1-bound genes in the pancreas from fetal to adult stages. We identified a core set of developmentally conserved PDX1-bound genes that reveal the broad multifaceted role of PDX1 in pancreas development. Despite the well-known dramatic changes in PDX1 function and expression, we found that PDX1-bound genes are largely conserved from embryonic to adult stages. This points towards a dual role of PDX1 in regulating the expression of its targets at different ages, dependent on other functionally congruent or directly interacting partners. We also showed that PDX1 binding is largely conserved in mouse pancreas. Together, our study reveals PDX1 targets in the developing pancreas in vivo and provides an essential resource for future studies on pancreas development.
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Affiliation(s)
- Xiaodun Yang
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jeffrey C. Raum
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Junil Kim
- School of Systems Biomedical Science, Soongsil University, 369 Sangdo-Ro, Dongjak-Gu, Seoul 06978, Republic of Korea
| | - Reynold Yu
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Juxiang Yang
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Gabriella Rice
- Department of Cell and Developmental Biology, Institute for Regenerative Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Changhong Li
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kyoung-Jae Won
- Biotech Research & Innovation Centre, University of Copenhagen, Copenhagen 2200, Denmark
| | - Diana E. Stanescu
- Division of Endocrinology and Diabetes, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Doris A. Stoffers
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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