1
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Chen C, Li Y, Wei W, Lu Y, Zou B, Zhang L, Shan J, Zhu Y, Wang S, Wu H, Su H, Zhou G. A precise microdissection strategy enabled spatial heterogeneity analysis on the targeted region of formalin-fixed paraffin-embedded tissues. Talanta 2024; 278:126501. [PMID: 38963978 DOI: 10.1016/j.talanta.2024.126501] [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: 04/01/2024] [Revised: 06/26/2024] [Accepted: 06/30/2024] [Indexed: 07/06/2024]
Abstract
In recent years, the development of spatial transcriptomic technologies has enabled us to gain an in-depth understanding of the spatial heterogeneity of gene expression in biological tissues. However, a simple and efficient tool is required to analyze multiple spatial targets, such as mRNAs, miRNAs, or genetic mutations, at high resolution in formalin-fixed paraffin-embedded (FFPE) tissue sections. In this study, we developed hydrogel pathological sectioning coupled with the previously reported Sampling Junior instrument (HPSJ) to assess the spatial heterogeneity of multiple targets in FFPE sections at a scale of 180 μm. The HPSJ platform was used to demonstrate the spatial heterogeneity of 9 ferroptosis-related genes (TFRC, NCOA4, FTH1, ACSL4, LPCAT3, ALOX12, SLC7A11, GLS2, and GPX4) and 2 miRNAs (miR-185-5p and miR522) in FFPE tissue samples from patients with triple-negative breast cancer (TNBC). The results validated the significant heterogeneity of ferroptosis-related mRNAs and miRNAs. In addition, HPSJ confirmed the spatial heterogeneity of the L858R mutation in 7 operation-sourced and 4 needle-biopsy-sourced FFPE samples from patients with lung adenocarcinoma (LUAD). The successful detection of clinical FFPE samples indicates that HPSJ is a precise, high-throughput, cost-effective, and universal platform for analyzing spatial heterogeneity, which is beneficial for elucidating the mechanisms underlying drug resistance and guiding the prescription of mutant-targeted drugs in patients with tumors.
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Affiliation(s)
- Chen Chen
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China; Department of Pharmacy, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210018, China
| | - Ying Li
- Department of Pathology Center of Diagnostic of Pathology, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210018, China
| | - Wei Wei
- Department of Pharmacy, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210018, China
| | - Yin Lu
- Department of Pharmacy, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210018, China
| | - Bingjie Zou
- Key Laboratory of Drug Quality Control and Pharmacovigilance of Ministry of Education, School of Pharmacy, China Pharmaceutical University, Nanjing, 210009, China
| | - Likun Zhang
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China
| | - Jingwen Shan
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China
| | - Yue Zhu
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China
| | - Shanshan Wang
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China
| | - Haiping Wu
- Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
| | - Hua Su
- Department of Pharmacy, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210018, China.
| | - Guohua Zhou
- School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China; Department of Clinical Pharmacy, State Key Laboratory of Analytical Chemistry for Life Science and Jiangsu Key Laboratory of Molecular Medicine, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, China.
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2
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Tang X, Zhang Y, Zhang H, Zhang N, Dai Z, Cheng Q, Li Y. Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases. Clin Rev Allergy Immunol 2024:10.1007/s12016-024-09001-6. [PMID: 39186216 DOI: 10.1007/s12016-024-09001-6] [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] [Accepted: 07/20/2024] [Indexed: 08/27/2024]
Abstract
Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.
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Affiliation(s)
- Xuening Tang
- Department of Pediatrics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Yudi Zhang
- Department of Pediatrics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China
| | - Hao Zhang
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, 400010, China
| | - Nan Zhang
- College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
| | - Yongzhen Li
- Department of Pediatrics, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
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3
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Sarkar S, Zheng X, Clair GC, Kwon YM, You Y, Swensen AC, Webb-Robertson BJM, Nakayasu ES, Qian WJ, Metz TO. Exploring new frontiers in type 1 diabetes through advanced mass-spectrometry-based molecular measurements. Trends Mol Med 2024:S1471-4914(24)00195-3. [PMID: 39152082 DOI: 10.1016/j.molmed.2024.07.009] [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: 05/23/2024] [Revised: 07/17/2024] [Accepted: 07/22/2024] [Indexed: 08/19/2024]
Abstract
Type 1 diabetes (T1D) is a devastating autoimmune disease for which advanced mass spectrometry (MS) methods are increasingly used to identify new biomarkers and better understand underlying mechanisms. For example, integration of MS analysis and machine learning has identified multimolecular biomarker panels. In mechanistic studies, MS has contributed to the discovery of neoepitopes, and pathways involved in disease development and identifying therapeutic targets. However, challenges remain in understanding the role of tissue microenvironments, spatial heterogeneity, and environmental factors in disease pathogenesis. Recent advancements in MS, such as ultra-fast ion-mobility separations, and single-cell and spatial omics, can play a central role in addressing these challenges. Here, we review recent advancements in MS-based molecular measurements and their role in understanding T1D.
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Affiliation(s)
- Soumyadeep Sarkar
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Xueyun Zheng
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Geremy C Clair
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Yu Mi Kwon
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Youngki You
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Adam C Swensen
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | | | - Ernesto S Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, 99352, USA.
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4
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Jeong Y, Ronen J, Kopp W, Lutsik P, Akalin A. scMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data. BMC Bioinformatics 2024; 25:257. [PMID: 39107690 PMCID: PMC11304929 DOI: 10.1186/s12859-024-05880-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 07/23/2024] [Indexed: 08/10/2024] Open
Abstract
The recent advances in high-throughput single-cell sequencing have created an urgent demand for computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are required to avoid biases towards a specific modality and overcome sparsity. Batch effects obfuscating biological signals must also be taken into account. Here, we introduce a new single-cell multiomics integration model, Single-cell Multiomics Autoencoder Integration (scMaui) based on variational product-of-experts autoencoders and adversarial learning. scMaui calculates a joint representation of multiple marginal distributions based on a product-of-experts approach which is especially effective for missing values in the modalities. Furthermore, it overcomes limitations seen in previous VAE-based integration methods with regard to batch effect correction and restricted applicable assays. It handles multiple batch effects independently accepting both discrete and continuous values, as well as provides varied reconstruction loss functions to cover all possible assays and preprocessing pipelines. We demonstrate that scMaui achieves superior performance in many tasks compared to other methods. Further downstream analyses also demonstrate its potential in identifying relations between assays and discovering hidden subpopulations.
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Affiliation(s)
- Yunhee Jeong
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, Germany
- Faculty of Mathematics and Informatics, Heidelberg University, Im Neuenheimer Feld 205, Heidelberg, Germany
| | - Jonathan Ronen
- Bioinformatics and Omics Data Science Platform, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
- Inceptive Nucleics, Inc., Palo Alto, CA, USA
| | - Wolfgang Kopp
- Bioinformatics and Omics Data Science Platform, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
- Roche Diagnostics GmbH, Penzberg, Germany
| | - Pavlo Lutsik
- Division of Cancer Epigenomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, Heidelberg, Germany.
- Department of Oncology, Catholic University (KU) Leuven, Leuven, Belgium.
| | - Altuna Akalin
- Bioinformatics and Omics Data Science Platform, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany.
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5
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Robertson CC, Elgamal RM, Henry-Kanarek BA, Arvan P, Chen S, Dhawan S, Eizirik DL, Kaddis JS, Vahedi G, Parker SCJ, Gaulton KJ, Soleimanpour SA. Untangling the genetics of beta cell dysfunction and death in type 1 diabetes. Mol Metab 2024; 86:101973. [PMID: 38914291 PMCID: PMC11283044 DOI: 10.1016/j.molmet.2024.101973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise. SCOPE OF REVIEW Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D. MAJOR CONCLUSIONS We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.
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Affiliation(s)
- Catherine C Robertson
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Ruth M Elgamal
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Belle A Henry-Kanarek
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Peter Arvan
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA; Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA
| | - Decio L Eizirik
- ULB Center for Diabetes Research, Université Libre de Bruxelles, Brussels, Belgium
| | - John S Kaddis
- Department of Diabetes and Cancer Discovery Science, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Golnaz Vahedi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Kyle J Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
| | - Scott A Soleimanpour
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA.
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6
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Li M, Su Y, Gao Y, Tian W. ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions. Brief Bioinform 2024; 25:bbae422. [PMID: 39177263 PMCID: PMC11342246 DOI: 10.1093/bib/bbae422] [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: 04/02/2024] [Revised: 07/16/2024] [Accepted: 08/12/2024] [Indexed: 08/24/2024] Open
Abstract
In this study, we introduce Robust estimation of Cell type proportions by Integrating single-reference-based DEconvolutions (ReCIDE), an innovative framework for robust estimation of cell type proportions by integrating single-reference-based deconvolutions. ReCIDE outperforms existing approaches in benchmark and real datasets, particularly excelling in estimating rare cell type proportions. Through exploratory analysis on public bulk data of triple-negative breast cancer (TNBC) patients using ReCIDE, we demonstrate a significant correlation between the prognosis of TNBC patients and the proportions of both T cell and perivascular-like cell subtypes. Built upon this discovery, we develop a prognostic assessment model for TNBC patients. Our contribution presents a novel framework for enhancing deconvolution accuracy, showcasing its effectiveness in medical research.
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Affiliation(s)
- Minghan Li
- State Key Laboratory of Genetic Engineering, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Yangpu District, Shanghai 200438, China
| | - Yuqing Su
- State Key Laboratory of Genetic Engineering, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Yangpu District, Shanghai 200438, China
| | - Yanbo Gao
- Shanghai SPH Jiaolian Pharmaceutical Technology Company, Limited, Buliding 4, 998 Ha Lei Road, Pudong District, Shanghai 201203, China
| | - Weidong Tian
- State Key Laboratory of Genetic Engineering, Department of Computational Biology, School of Life Sciences, Fudan University, 2005 Songhu Road, Yangpu District, Shanghai 200438, China
- Children’s Hospital of Fudan University, 399 Wanyuan Road, Minhang District, Shanghai 201102, China
- Children’s Hospital of Shandong University, 23976 Jingshi Road, Huaiyin District, Jinan, Shandong 250022, China
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7
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Pu C, Wang Y, Li Y, Wang Y, Li L, Xiang H, Sun Q, Yong Y, Yang H, Jiang K. Nano-enzyme functionalized hydrogels promote diabetic wound healing through immune microenvironment modulation. Biomater Sci 2024; 12:3851-3865. [PMID: 38899957 DOI: 10.1039/d4bm00348a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Non-healing diabetic wounds often culminate in amputation and mortality. The main pathophysiological features in diabetic wounds involve the accumulation of M1-type macrophages and excessive oxidative stress. In this study, we engineered a nano-enzyme functionalized hydrogel by incorporating a magnesium ion-doped molybdenum-based polymetallic oxide (Mg-POM), a novel bioactive nano-enzyme, into a GelMA hydrogel, to obtain the GelMA@Mg-POM system to enhance diabetic wound healing. GelMA@Mg-POM was crosslinked using UV light, yielding a hydrogel with a uniformly porous three-dimensional mesh structure. In vitro experiments showed that GelMA@Mg-POM extraction significantly enhanced human umbilical vein endothelial cell (HUVEC) migration, scavenged ROS, improved the inflammatory microenvironment, induced macrophage reprogramming towards M2, and promoted HUVEC regeneration of CD31 and fibroblast regeneration of type I collagen. In in vivo experiments, diabetic rat wounds treated with GelMA@Mg-POM displayed enhanced granulation tissue genesis and collagen production, as evidenced by HE and Masson staining. Immunohistochemistry demonstrated the ability of GelMA@Mg-POM to mitigate macrophage-associated inflammatory responses and promote angiogenesis. Overall, these findings suggest that GelMA@Mg-POM holds significant promise as a biomaterial for treating diabetic wounds.
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Affiliation(s)
- Chaoyu Pu
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Yong Wang
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Yuling Li
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Yi Wang
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Linfeng Li
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Honglin Xiang
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Qiyuan Sun
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Yuan Yong
- School of Chemistry and Environment, Southwest Minzu University, Chengdu 610041, PR China
| | - Hanfeng Yang
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
| | - Ke Jiang
- Department of Orthopedics, Laboratory of Biological Tissue Engineering and Digital Medicine, Nanomedicine Innovation Research and Development Transformation Institute, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, PR China.
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8
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Song Z, Li S, Shang Z, Lv W, Cheng X, Meng X, Chen R, Zhang S, Zhang R. Integrating multi-omics data to analyze the potential pathogenic mechanism of CTSH gene involved in type 1 diabetes in the exocrine pancreas. Brief Funct Genomics 2024; 23:406-417. [PMID: 38050341 DOI: 10.1093/bfgp/elad052] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/19/2023] [Accepted: 11/09/2023] [Indexed: 12/06/2023] Open
Abstract
Type 1 diabetes (T1D) is an autoimmune disease caused by the destruction of insulin-producing pancreatic islet beta cells. Despite significant advancements, the precise pathogenesis of the disease remains unknown. This work integrated data from expression quantitative trait locus (eQTL) studies with Genome wide association study (GWAS) summary data of T1D and single-cell transcriptome data to investigate the potential pathogenic mechanisms of the CTSH gene involved in T1D in exocrine pancreas. Using the summary data-based Mendelian randomization (SMR) approach, we obtained four potential causative genes associated with T1D: BTN3A2, PGAP3, SMARCE1 and CTSH. To further investigate these genes'roles in T1D development, we validated them using a scRNA-seq dataset from pancreatic tissues of both T1D patients and healthy controls. The analysis showed a significantly high expression of the CTSH gene in T1D acinar cells, whereas the other three genes showed no significant changes in the scRNA-seq data. Moreover, single-cell WGCNA analysis revealed the strongest positive correlation between the module containing CTSH and T1D. In addition, we found cellular ligand-receptor interactions between the acinar cells and different cell types, especially ductal cells. Finally, based on functional enrichment analysis, we hypothesized that the CTSH gene in the exocrine pancreas enhances the antiviral response, leading to the overexpression of pro-inflammatory cytokines and the development of an inflammatory microenvironment. This process promotes β cells injury and ultimately the development of T1D. Our findings offer insights into the underlying pathogenic mechanisms of T1D.
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Affiliation(s)
- Zerun Song
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Shuai Li
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Zhenwei Shang
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Wenhua Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Xiangshu Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Xin Meng
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Rui Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Shuhao Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
| | - Ruijie Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin City, Heilongjiang Province, China
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9
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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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10
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Rampazzo Morelli N, Pipella J, Thompson PJ. Establishing evidence for immune surveillance of β-cell senescence. Trends Endocrinol Metab 2024; 35:576-585. [PMID: 38307810 DOI: 10.1016/j.tem.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 02/04/2024]
Abstract
Cellular senescence is a programmed state of cell cycle arrest that involves a complex immunogenic secretome, eliciting immune surveillance and senescent cell clearance. Recent work has shown that a subpopulation of pancreatic β-cells becomes senescent in the context of diabetes; however, it is not known whether these cells are normally subject to immune surveillance. In this opinion article, we advance the hypothesis that immune surveillance of β-cells undergoing a senescence stress response normally limits their accumulation during aging and that the breakdown of these mechanisms is a driver of senescent β-cell accumulation in diabetes. Elucidation and therapeutic activation of immune surveillance mechanisms in the pancreas holds promise for the improvement of approaches to target stressed senescent β-cells in the treatment of diabetes.
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Affiliation(s)
- Nayara Rampazzo Morelli
- Diabetes Research Envisioned and Accomplished in Manitoba (DREAM) Theme, Children's Hospital Research Institute of Manitoba, Winnipeg, MB R3E 3P4, Canada; Department of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Jasmine Pipella
- Diabetes Research Envisioned and Accomplished in Manitoba (DREAM) Theme, Children's Hospital Research Institute of Manitoba, Winnipeg, MB R3E 3P4, Canada; Department of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Peter J Thompson
- Diabetes Research Envisioned and Accomplished in Manitoba (DREAM) Theme, Children's Hospital Research Institute of Manitoba, Winnipeg, MB R3E 3P4, Canada; Department of Physiology and Pathophysiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
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11
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Ewald JD, Lu Y, Ellis CE, Worton J, Kolic J, Sasaki S, Zhang D, dos Santos T, Spigelman AF, Bautista A, Dai XQ, Lyon JG, Smith NP, Wong JM, Rajesh V, Sun H, Sharp SA, Rogalski JC, Moravcova R, Cen HH, Manning Fox JE, Atlas E, Bruin JE, Mulvihill EE, Verchere CB, Foster LJ, Gloyn AL, Johnson JD, Pepper AR, Lynn FC, Xia J, MacDonald PE. HumanIslets: An integrated platform for human islet data access and analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.19.599613. [PMID: 38948734 PMCID: PMC11212983 DOI: 10.1101/2024.06.19.599613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.
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Affiliation(s)
- Jessica D. Ewald
- Institute of Parasitology, McGill University, Montreal, QC
- Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yao Lu
- Institute of Parasitology, McGill University, Montreal, QC
| | - Cara E. Ellis
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Jessica Worton
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Surgery, University of Alberta, Edmonton, AB
| | - Jelena Kolic
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Shugo Sasaki
- Diabetes Research Group, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Surgery, School of Biomedical Engineering, University of British Columbia, Vancouver, BC
| | - Dahai Zhang
- Diabetes Research Group, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Surgery, School of Biomedical Engineering, University of British Columbia, Vancouver, BC
| | - Theodore dos Santos
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Aliya F. Spigelman
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Austin Bautista
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
| | - Xiao-Qing Dai
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - James G. Lyon
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
| | - Nancy P. Smith
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | - Jordan M. Wong
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Surgery, University of Alberta, Edmonton, AB
| | - Varsha Rajesh
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - Han Sun
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - Seth A. Sharp
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - Jason C. Rogalski
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Renata Moravcova
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Haoning H Cen
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Jocelyn E. Manning Fox
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
| | | | - Ella Atlas
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON
| | - Jennifer E. Bruin
- Department of Biology & Institute of Biochemistry, Carleton University, Ottawa, ON
| | - Erin E. Mulvihill
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, ON
- University of Ottawa Heart Institute, Ottawa, ON
| | - C. Bruce Verchere
- Department of Surgery, BC Children’s Hospital Research Institute and University of British Columbia, Vancouver, BC
- Department of Pathology and Laboratory Medicine, BC Children’s Hospital Research Institute and University of British Columbia, Vancouver, BC
- Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, BC
| | - Leonard J. Foster
- Department of Biochemistry & Molecular Biology, Michael Smith Laboratories, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Anna L. Gloyn
- Department of Pediatrics, Division of Endocrinology, Stanford School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA
| | - James D. Johnson
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC
| | - Andrew R. Pepper
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Surgery, University of Alberta, Edmonton, AB
| | - Francis C. Lynn
- Diabetes Research Group, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Surgery, School of Biomedical Engineering, University of British Columbia, Vancouver, BC
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, QC
| | - Patrick E. MacDonald
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB
- Department of Pharmacology, University of Alberta, Edmonton, AB
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12
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Fernández Á, Casamitjana J, Holguín-Horcajo A, Coolens K, Mularoni L, Guo L, Hartwig O, Düking T, Vidal N, Strickland LN, Pasquali L, Bailey-Lundberg JM, Rooman I, Wang YJ, Rovira M. A Single-Cell Atlas of the Murine Pancreatic Ductal Tree Identifies Novel Cell Populations With Potential Implications in Pancreas Regeneration and Exocrine Pathogenesis. Gastroenterology 2024:S0016-5085(24)05063-7. [PMID: 38908487 DOI: 10.1053/j.gastro.2024.06.008] [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: 08/24/2023] [Revised: 06/04/2024] [Accepted: 06/07/2024] [Indexed: 06/24/2024]
Abstract
BACKGROUND & AIMS Pancreatic ducts form an intricate network of tubules that secrete bicarbonate and drive acinar secretions into the duodenum. This network is formed by centroacinar cells, terminal, intercalated, intracalated ducts, and the main pancreatic duct. Ductal heterogeneity at the single-cell level has been poorly characterized; therefore, our understanding of the role of ductal cells in pancreas regeneration and exocrine pathogenesis has been hampered by the limited knowledge and unexplained diversity within the ductal network. METHODS We used single cell RNA sequencing to comprehensively characterize mouse ductal heterogeneity at single-cell resolution of the entire ductal epithelium from centroacinar cells to the main duct. Moreover, we used organoid cultures, injury models, and pancreatic tumor samples to interrogate the role of novel ductal populations in pancreas regeneration and exocrine pathogenesis. RESULTS We have identified the coexistence of 15 ductal populations within the healthy pancreas and characterized their organoid formation capacity and endocrine differentiation potential. Cluster isolation and subsequent culturing let us identify ductal cell populations with high organoid formation capacity and endocrine and exocrine differentiation potential in vitro, including a Wnt-responsive population, a ciliated population, and Flrt3+ cells. Moreover, we have characterized the location of these novel ductal populations in healthy pancreas, chronic pancreatitis, and tumor samples. The expression of Wnt-responsive, interferon-responsive, and epithelial-to-mesenchymal transition population markers increases in chronic pancreatitis and tumor samples. CONCLUSIONS In light of our discovery of previously unidentified ductal populations, we unmask potential roles of specific ductal populations in pancreas regeneration and exocrine pathogenesis. Thus, novel lineage-tracing models are needed to investigate ductal-specific populations in vivo.
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Affiliation(s)
- Ángel Fernández
- Department of Physiological Science, School of Medicine, Universitat de Barcelona, L'Hospitalet de Llobregat, Spain; Pancreas Regeneration: Pancreatic Progenitors and Their Niche Group, Regenerative Medicine Program, Instituto de Investigación Biomédica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain; Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Spain; Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Joan Casamitjana
- Department of Physiological Science, School of Medicine, Universitat de Barcelona, L'Hospitalet de Llobregat, Spain; Pancreas Regeneration: Pancreatic Progenitors and Their Niche Group, Regenerative Medicine Program, Instituto de Investigación Biomédica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain; Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Spain
| | - Adrián Holguín-Horcajo
- Department of Physiological Science, School of Medicine, Universitat de Barcelona, L'Hospitalet de Llobregat, Spain; Pancreas Regeneration: Pancreatic Progenitors and Their Niche Group, Regenerative Medicine Program, Instituto de Investigación Biomédica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain; Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Spain
| | - Katarina Coolens
- Vrije Universiteit Brussel, Translational Oncology Research Center, Laboratory for Medical and Molecular Oncology, Brussels, Belgium
| | - Loris Mularoni
- Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Spain
| | - Li Guo
- Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, Florida
| | - Olga Hartwig
- Miltenyi Biotec B.V. & Co KG, Bergisch Gladbach, Germany
| | - Tim Düking
- Miltenyi Biotec B.V. & Co KG, Bergisch Gladbach, Germany
| | - Noemi Vidal
- Pathology Department, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Lincoln N Strickland
- Department of Anesthesiology, Critical Care and Pain Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Lorenzo Pasquali
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Jennifer M Bailey-Lundberg
- Department of Anesthesiology, Critical Care and Pain Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, Texas
| | - Ilse Rooman
- Vrije Universiteit Brussel, Translational Oncology Research Center, Laboratory for Medical and Molecular Oncology, Brussels, Belgium
| | - Yue J Wang
- Department of Biomedical Sciences, College of Medicine, Florida State University, Tallahassee, Florida
| | - Meritxell Rovira
- Department of Physiological Science, School of Medicine, Universitat de Barcelona, L'Hospitalet de Llobregat, Spain; Pancreas Regeneration: Pancreatic Progenitors and Their Niche Group, Regenerative Medicine Program, Instituto de Investigación Biomédica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain; Program for Advancing the Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos III, Barcelona, Spain.
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13
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Azzarello F, Carli F, De Lorenzi V, Tesi M, Marchetti P, Beltram F, Raimondi F, Cardarelli F. Machine-learning-guided recognition of α and β cells from label-free infrared micrographs of living human islets of Langerhans. Sci Rep 2024; 14:14235. [PMID: 38902357 PMCID: PMC11190282 DOI: 10.1038/s41598-024-65161-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024] Open
Abstract
Human islets of Langerhans are composed mostly of glucagon-secreting α cells and insulin-secreting β cells closely intermingled one another. Current methods for identifying α and β cells involve either fixing islets and using immunostaining or disaggregating islets and employing flow cytometry for classifying α and β cells based on their size and autofluorescence. Neither approach, however, allows investigating the dynamic behavior of α and β cells in a living and intact islet. To tackle this issue, we present a machine-learning-based strategy for identification α and β cells in label-free infrared micrographs of living human islets without immunostaining. Intrinsic autofluorescence is stimulated by infrared light and collected both in intensity and lifetime in the visible range, dominated by NAD(P)H and lipofuscin signals. Descriptive parameters are derived from micrographs for ~ 103 cells. These parameters are used as input for a boosted decision-tree model (XGBoost) pre-trained with immunofluorescence-derived cell-type information. The model displays an optimized-metrics performance of 0.86 (i.e. area under a ROC curve), with an associated precision of 0.94 for the recognition of β cells and 0.75 for α cells. This tool promises to enable longitudinal studies on the dynamic behavior of individual cell types at single-cell resolution within the intact tissue.
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Affiliation(s)
| | - Francesco Carli
- Laboratorio di Biologia Bio@SNS, Scuola Normale Superiore, Pisa, Italy
| | | | - Marta Tesi
- Department of Clinical and Experimental Medicine, Islet Cell Laboratory, University of Pisa, Pisa, Italy
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, Islet Cell Laboratory, University of Pisa, Pisa, Italy
| | - Fabio Beltram
- NEST Laboratory, Scuola Normale Superiore, Pisa, Italy
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14
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Barlow GL, Schürch CM, Bhate SS, Phillips D, Young A, Dong S, Martinez HA, Kaber G, Nagy N, Ramachandran S, Meng J, Korpos E, Bluestone JA, Nolan GP, Bollyky PL. The Extra-Islet Pancreas Supports Autoimmunity in Human Type 1 Diabetes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.03.15.23287145. [PMID: 36993739 PMCID: PMC10055577 DOI: 10.1101/2023.03.15.23287145] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
In autoimmune Type 1 diabetes (T1D), immune cells infiltrate and destroy the islets of Langerhans - islands of endocrine tissue dispersed throughout the pancreas. However, the contribution of cellular programs outside islets to insulitis is unclear. Here, using CO-Detection by indEXing (CODEX) tissue imaging and cadaveric pancreas samples, we simultaneously examine islet and extra-islet inflammation in human T1D. We identify four sub-states of inflamed islets characterized by the activation profiles of CD8 + T cells enriched in islets relative to the surrounding tissue. We further find that the extra-islet space of lobules with extensive islet-infiltration differs from the extra-islet space of less infiltrated areas within the same tissue section. Finally, we identify lymphoid structures away from islets enriched in CD45RA + T cells - a population also enriched in one of the inflamed islet sub-states. Together, these data help define the coordination between islets and the extra-islet pancreas in the pathogenesis of human T1D.
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15
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Patil AR, Schug J, Liu C, Lahori D, Descamps HC, Naji A, Kaestner KH, Faryabi RB, Vahedi G. Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets. Cell Rep Med 2024; 5:101535. [PMID: 38677282 PMCID: PMC11148720 DOI: 10.1016/j.xcrm.2024.101535] [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: 08/09/2023] [Revised: 01/22/2024] [Accepted: 04/07/2024] [Indexed: 04/29/2024]
Abstract
Type 1 diabetes (T1D) is a chronic condition in which beta cells are destroyed by immune cells. Despite progress in immunotherapies that could delay T1D onset, early detection of autoimmunity remains challenging. Here, we evaluate the utility of machine learning for early prediction of T1D using single-cell analysis of islets. Using gradient-boosting algorithms, we model changes in gene expression of single cells from pancreatic tissues in T1D and non-diabetic organ donors. We assess if mathematical modeling could predict the likelihood of T1D development in non-diabetic autoantibody-positive donors. While most autoantibody-positive donors are predicted to be non-diabetic, select donors with unique gene signatures are classified as T1D. Our strategy also reveals a shared gene signature in distinct T1D-associated models across cell types, suggesting a common effect of the disease on transcriptional outputs of these cells. Our study establishes a precedent for using machine learning in early detection of T1D.
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Affiliation(s)
- Abhijeet R Patil
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Jonathan Schug
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Chengyang Liu
- Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Deeksha Lahori
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Hélène C Descamps
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Ali Naji
- Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Klaus H Kaestner
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Robert B Faryabi
- Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Golnaz Vahedi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
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16
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Luan J, Truong C, Vuchkovska A, Guo W, Good J, Liu B, Gang A, Infarinato N, Stewart K, Polak L, Pasolli HA, Andretta E, Rudensky AY, Fuchs E, Miao Y. CD80 on skin stem cells promotes local expansion of regulatory T cells upon injury to orchestrate repair within an inflammatory environment. Immunity 2024; 57:1071-1086.e7. [PMID: 38677291 PMCID: PMC11265648 DOI: 10.1016/j.immuni.2024.04.003] [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: 12/12/2022] [Revised: 03/21/2024] [Accepted: 04/05/2024] [Indexed: 04/29/2024]
Abstract
Following tissue damage, epithelial stem cells (SCs) are mobilized to enter the wound, where they confront harsh inflammatory environments that can impede their ability to repair the injury. Here, we investigated the mechanisms that protect skin SCs within this inflammatory environment. Characterization of gene expression profiles of hair follicle SCs (HFSCs) that migrated into the wound site revealed activation of an immune-modulatory program, including expression of CD80, major histocompatibility complex class II (MHCII), and CXC motif chemokine ligand 5 (CXCL5). Deletion of CD80 in HFSCs impaired re-epithelialization, reduced accumulation of peripherally generated Treg (pTreg) cells, and increased infiltration of neutrophils in wounded skin. Importantly, similar wound healing defects were also observed in mice lacking pTreg cells. Our findings suggest that upon skin injury, HFSCs establish a temporary protective network by promoting local expansion of Treg cells, thereby enabling re-epithelialization while still kindling inflammation outside this niche until the barrier is restored.
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Affiliation(s)
- Jingyun Luan
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA
| | - Cynthia Truong
- Howard Hughes Medical Institute, Robin Chemers Neustein Laboratory of Mammalian Development and Cell Biology, The Rockefeller University, New York, NY 10065, USA
| | - Aleksandra Vuchkovska
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA
| | - Weijie Guo
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA
| | - Jennifer Good
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA
| | - Bijun Liu
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA
| | - Audrey Gang
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA
| | - Nicole Infarinato
- Howard Hughes Medical Institute, Robin Chemers Neustein Laboratory of Mammalian Development and Cell Biology, The Rockefeller University, New York, NY 10065, USA
| | - Katherine Stewart
- Howard Hughes Medical Institute, Robin Chemers Neustein Laboratory of Mammalian Development and Cell Biology, The Rockefeller University, New York, NY 10065, USA
| | - Lisa Polak
- Howard Hughes Medical Institute, Robin Chemers Neustein Laboratory of Mammalian Development and Cell Biology, The Rockefeller University, New York, NY 10065, USA
| | - Hilda Amalia Pasolli
- Electron Microscopy Resource Center, The Rockefeller University, New York, NY 10065, USA
| | - Emma Andretta
- Howard Hughes Medical Institute, Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Alexander Y Rudensky
- Howard Hughes Medical Institute, Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Elaine Fuchs
- Howard Hughes Medical Institute, Robin Chemers Neustein Laboratory of Mammalian Development and Cell Biology, The Rockefeller University, New York, NY 10065, USA.
| | - Yuxuan Miao
- Ben May Department of Cancer Research, The University of Chicago, Chicago, IL 60615, USA.
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17
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Yang K, Zhang Y, Ding J, Li Z, Zhang H, Zou F. Autoimmune CD8+ T cells in type 1 diabetes: from single-cell RNA sequencing to T-cell receptor redirection. Front Endocrinol (Lausanne) 2024; 15:1377322. [PMID: 38800484 PMCID: PMC11116783 DOI: 10.3389/fendo.2024.1377322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 04/18/2024] [Indexed: 05/29/2024] Open
Abstract
Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cell destruction and mediated primarily by autoreactive CD8+ T cells. It has been shown that only a small number of stem cell-like β cell-specific CD8+ T cells are needed to convert normal mice into T1D mice; thus, it is likely that T1D can be cured or significantly improved by modulating or altering self-reactive CD8+ T cells. However, stem cell-type, effector and exhausted CD8+ T cells play intricate and important roles in T1D. The highly diverse T-cell receptors (TCRs) also make precise and stable targeted therapy more difficult. Therefore, this review will investigate the mechanisms of autoimmune CD8+ T cells and TCRs in T1D, as well as the related single-cell RNA sequencing (ScRNA-Seq), CRISPR/Cas9, chimeric antigen receptor T-cell (CAR-T) and T-cell receptor-gene engineered T cells (TCR-T), for a detailed and clear overview. This review highlights that targeting CD8+ T cells and their TCRs may be a potential strategy for predicting or treating T1D.
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Affiliation(s)
- Kangping Yang
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yihan Zhang
- The Second Clinical Medicine School, Nanchang University, Nanchang, China
| | - Jiatong Ding
- The Second Clinical Medicine School, Nanchang University, Nanchang, China
| | - Zelin Li
- The First Clinical Medicine School, Nanchang University, Nanchang, China
| | - Hejin Zhang
- The Second Clinical Medicine School, Nanchang University, Nanchang, China
| | - Fang Zou
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, China
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18
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Yang H, Luo J, Liu X, Luo Y, Lai X, Zou F. Unveiling cell subpopulations in T1D mouse islets using single-cell RNA sequencing. Am J Physiol Endocrinol Metab 2024; 326:E723-E734. [PMID: 38506753 DOI: 10.1152/ajpendo.00323.2023] [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: 09/29/2023] [Revised: 03/05/2024] [Accepted: 03/15/2024] [Indexed: 03/21/2024]
Abstract
Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of beta cells by immune cells. The interactions among cells within the islets may be closely linked to the pathogenesis of T1D. In this study, we used single-cell RNA sequencing (scRNA-Seq) to analyze the cellular heterogeneity within the islets of a T1D mouse model. We established a T1D mouse model induced by streptozotocin and identified cell subpopulations using scRNA-Seq technology. Our results revealed 11 major cell types in the pancreatic islets of T1D mice, with heterogeneity observed in the alpha and beta cell subgroups, which may play a crucial role in the progression of T1D. Flow cytometry further confirmed a mature alpha and beta cell reduction in T1D mice. Overall, our scRNA-Seq analysis provided insights into the cellular heterogeneity of T1D islet tissue and highlighted the potential importance of alpha and beta cells in developing T1D.NEW & NOTEWORTHY In this study, we created a comprehensive single-cell atlas of pancreatic islets in a T1D mouse model using scRNA-Seq and identified 11 major cell types in the islets, highlighting the role of alpha and beta cells in T1D. This study revealed a significant reduction in the maturity alpha and beta cells in T1D mice through flow cytometry. It also demonstrated the heterogeneity of alpha and beta cells, potentially crucial for T1D progression. Overall, our scRNA-Seq analysis provided new insights for understanding and treating T1D by studying cell subtype changes and functions.
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Affiliation(s)
- Huan Yang
- Department of Endocrinology, Jiujiang University Affiliated Hospital, Jiujiang, People's Republic of China
| | - Junming Luo
- Department of Respiratory Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China
| | - Xuyang Liu
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China
| | - Yue Luo
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China
| | - Xiaoyang Lai
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China
| | - Fang Zou
- Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Nanchang University, Nanchang, People's Republic of China
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19
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Muñoz García A, Juksar J, Groen N, Zaldumbide A, de Koning E, Carlotti F. Single-cell transcriptomics reveals a role for pancreatic duct cells as potential mediators of inflammation in diabetes mellitus. Front Immunol 2024; 15:1381319. [PMID: 38742118 PMCID: PMC11089191 DOI: 10.3389/fimmu.2024.1381319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Accepted: 03/25/2024] [Indexed: 05/16/2024] Open
Abstract
Introduction Inflammation of the pancreas contributes to the development of diabetes mellitus. Although it is well-accepted that local inflammation leads to a progressive loss of functional beta cell mass that eventually causes the onset of the disease, the development of islet inflammation remains unclear. Methods Here, we used single-cell RNA sequencing to explore the cell type-specific molecular response of primary human pancreatic cells exposed to an inflammatory environment. Results We identified a duct subpopulation presenting a unique proinflammatory signature among all pancreatic cell types. Discussion Overall, the findings of this study point towards a role for duct cells in the propagation of islet inflammation, and in immune cell recruitment and activation, which are key steps in the pathophysiology of diabetes mellitus.
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Affiliation(s)
- Amadeo Muñoz García
- Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Juri Juksar
- Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Nathalie Groen
- Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Arnaud Zaldumbide
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, Netherlands
| | - Eelco de Koning
- Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
| | - Françoise Carlotti
- Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands
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20
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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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21
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Melchiorre CK, Lynes MD, Bhandari S, Su SC, Potts CM, Thees AV, Norris CE, Liaw L, Tseng YH, Lynes MA. Extracellular metallothionein as a therapeutic target in the early progression of type 1 diabetes. Cell Stress Chaperones 2024; 29:312-325. [PMID: 38490439 PMCID: PMC10990868 DOI: 10.1016/j.cstres.2024.03.005] [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: 01/26/2024] [Revised: 02/23/2024] [Accepted: 03/11/2024] [Indexed: 03/17/2024] Open
Abstract
Type 1 diabetes (T1D) is characterized by lymphocyte infiltration into the pancreatic islets of Langerhans, leading to the destruction of insulin-producing beta cells and uncontrolled hyperglycemia. In the nonobese diabetic (NOD) murine model of T1D, the onset of this infiltration starts several weeks before glucose dysregulation and overt diabetes. Recruitment of immune cells to the islets is mediated by several chemotactic cytokines, including CXCL10, while other cytokines, including SDF-1α, can confer protective effects. Global gene expression studies of the pancreas from prediabetic NOD mice and single-cell sequence analysis of human islets from prediabetic, autoantibody-positive patients showed an increased expression of metallothionein (MT), a small molecular weight, cysteine-rich metal-binding stress response protein. We have shown that beta cells can release MT into the extracellular environment, which can subsequently enhance the chemotactic response of Th1 cells to CXCL10 and interfere with the chemotactic response of Th2 cells to SDF-1α. These effects can be blocked in vitro with a monoclonal anti-MT antibody, clone UC1MT. When administered to NOD mice before the onset of diabetes, UC1MT significantly reduces the development of T1D. Manipulation of extracellular MT may be an important approach to preserving beta cell function and preventing the development of T1D.
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Affiliation(s)
- Clare K Melchiorre
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Matthew D Lynes
- Center for Molecular Medicine, MaineHealth Institute for Research, Scarborough, ME, USA
| | - Sadikshya Bhandari
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Sheng-Chiang Su
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA; Division of Endocrinology and Metabolism, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Christian M Potts
- Center for Molecular Medicine, MaineHealth Institute for Research, Scarborough, ME, USA
| | - Amy V Thees
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Carol E Norris
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Lucy Liaw
- Center for Molecular Medicine, MaineHealth Institute for Research, Scarborough, ME, USA
| | - Yu-Hua Tseng
- Section on Integrative Physiology and Metabolism, Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - Michael A Lynes
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA.
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22
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Ye F, Wang J, Li J, Mei Y, Guo G. Mapping Cell Atlases at the Single-Cell Level. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2305449. [PMID: 38145338 PMCID: PMC10885669 DOI: 10.1002/advs.202305449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 12/01/2023] [Indexed: 12/26/2023]
Abstract
Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.
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Affiliation(s)
- Fang Ye
- Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative MedicineZhejiang University School of MedicineHangzhouZhejiang310000China
- Liangzhu LaboratoryZhejiang UniversityHangzhouZhejiang311121China
| | - Jingjing Wang
- Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative MedicineZhejiang University School of MedicineHangzhouZhejiang310000China
- Liangzhu LaboratoryZhejiang UniversityHangzhouZhejiang311121China
| | - Jiaqi Li
- Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative MedicineZhejiang University School of MedicineHangzhouZhejiang310000China
| | - Yuqing Mei
- Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative MedicineZhejiang University School of MedicineHangzhouZhejiang310000China
| | - Guoji Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital, and Center for Stem Cell and Regenerative MedicineZhejiang University School of MedicineHangzhouZhejiang310000China
- Liangzhu LaboratoryZhejiang UniversityHangzhouZhejiang311121China
- Zhejiang Provincial Key Lab for Tissue Engineering and Regenerative MedicineDr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative MedicineHangzhouZhejiang310058China
- Institute of HematologyZhejiang UniversityHangzhouZhejiang310000China
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23
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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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24
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Sleiman PM, Qu HQ, Connolly JJ, Mentch F, Pereira A, Lotufo PA, Tollman S, Choudhury A, Ramsay M, Kato N, Ozaki K, Mitsumori R, Jeon JP, Hong CH, Son SJ, Roh HW, Lee DG, Mukadam N, Foote IF, Marshall CR, Butterworth A, Prins BP, Glessner JT, Hakonarson H. Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study. Alzheimers Dement 2023; 19:5765-5772. [PMID: 37450379 PMCID: PMC10854406 DOI: 10.1002/alz.13378] [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: 01/12/2023] [Revised: 04/26/2023] [Accepted: 05/05/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.
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Affiliation(s)
- Patrick M. Sleiman
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Hui-Qi Qu
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - John J Connolly
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Frank Mentch
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Alexandre Pereira
- Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Centro de Pesquisas Clínicas e Epidemiológicas, Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Paulo A Lotufo
- Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Centro de Pesquisas Clínicas e Epidemiológicas, Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil
| | - Stephen Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ananyo Choudhury
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Michele Ramsay
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Norihiro Kato
- National Center for Global Health and Medicine, Tokyo, 1628655, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology (NCGG), Obu City, Aichi Prefecture, Japan
| | - Risa Mitsumori
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology (NCGG), Obu City, Aichi Prefecture, Japan
| | - Jae-Pil Jeon
- Korea Biobank Project, Korea National Institute of Health, Osong, Korea
| | - Chang Hyung Hong
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Sang Joon Son
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Hyun Woong Roh
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
| | - Dong-gi Lee
- Department of Psychiatry, Ajou University School of Medicine, Suwon, Korea
- Department of Biostatistics, Epidemiology and Informatics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Naaheed Mukadam
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, UK
| | - Isabelle F Foote
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, UK
- Genes & Health, Blizard Institute, Queen Mary University of London, UK
| | - Charles R Marshall
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, UK
- Genes & Health, Blizard Institute, Queen Mary University of London, UK
| | - Adam Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Bram P Prins
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Joseph T Glessner
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Hakon Hakonarson
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Division of Pulmonary Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
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25
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Sarkar S, Syed F, Webb-Robertson BJ, Melchior JT, Chang G, Gritsenko M, Wang YT, Tsai CF, Liu J, Yi X, Cui Y, Eizirik DL, Metz TO, Rewers M, Evans-Molina C, Mirmira RG, Nakayasu ES. Protection of β cells against pro-inflammatory cytokine stress by the GDF15-ERBB2 signaling. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.27.23298904. [PMID: 38076918 PMCID: PMC10705646 DOI: 10.1101/2023.11.27.23298904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
Aim/hypothesis Growth/differentiation factor 15 (GDF15) is a therapeutic target for a variety of metabolic diseases, including type 1 diabetes (T1D). However, the nausea caused by GDF15 is a challenging point for therapeutic development. In addition, it is unknown why the endogenous GDF15 fails to protect from T1D development. Here, we investigate the GDF15 signaling in pancreatic islets towards opening possibilities for therapeutic targeting in β cells and to understand why this protection fails to occur naturally. Methods GDF15 signaling in islets was determined by proximity-ligation assay, untargeted proteomics, pathway analysis, and treatment of cells with specific inhibitors. To determine if GDF15 levels would increase prior to disease onset, plasma levels of GDF15 were measured in a longitudinal prospective study of children during T1D development (n=132 cases vs. n=40 controls) and in children with islet autoimmunity but normoglycemia (n=47 cases vs. n=40 controls) using targeted mass spectrometry. We also investigated the regulation of GDF15 production in islets by fluorescence microscopy and western blot analysis. Results The proximity-ligation assay identified ERBB2 as the GDF15 receptor in islets, which was confirmed using its specific antagonist, tucatinib. The untargeted proteomics analysis and caspase assay showed that ERBB2 activation by GDF15 reduces β cell apoptosis by downregulating caspase 8. In plasma, GDF15 levels were higher (p=0.0024) during T1D development compared to controls, but not in islet autoimmunity with normoglycemia. However, in the pancreatic islets GDF15 was depleted via sequestration of its mRNA into stress granules, resulting in translation halting. Conclusions/interpretation GDF15 protects against T1D via ERBB2-mediated decrease of caspase 8 expression in pancreatic islets. Circulating levels of GDF15 increases pre-T1D onset, which is insufficient to promote protection due to its localized depletion in the islets. These findings open opportunities for targeting GDF15 downstream signaling for pancreatic β cell protection in T1D and help to explain the lack of natural protection by the endogenous protein.
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26
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Doke M, Álvarez-Cubela S, Klein D, Altilio I, Schulz J, Mateus Gonçalves L, Almaça J, Fraker CA, Pugliese A, Ricordi C, Qadir MMF, Pastori RL, Domínguez-Bendala J. Dynamic scRNA-seq of live human pancreatic slices reveals functional endocrine cell neogenesis through an intermediate ducto-acinar stage. Cell Metab 2023; 35:1944-1960.e7. [PMID: 37898119 DOI: 10.1016/j.cmet.2023.10.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 08/23/2023] [Accepted: 10/03/2023] [Indexed: 10/30/2023]
Abstract
Human pancreatic plasticity is implied from multiple single-cell RNA sequencing (scRNA-seq) studies. However, these have been invariably based on static datasets from which fate trajectories can only be inferred using pseudotemporal estimations. Furthermore, the analysis of isolated islets has resulted in a drastic underrepresentation of other cell types, hindering our ability to interrogate exocrine-endocrine interactions. The long-term culture of human pancreatic slices (HPSs) has presented the field with an opportunity to dynamically track tissue plasticity at the single-cell level. Combining datasets from same-donor HPSs at different time points, with or without a known regenerative stimulus (BMP signaling), led to integrated single-cell datasets storing true temporal or treatment-dependent information. This integration revealed population shifts consistent with ductal progenitor activation, blurring of ductal/acinar boundaries, formation of ducto-acinar-endocrine differentiation axes, and detection of transitional insulin-producing cells. This study provides the first longitudinal scRNA-seq analysis of whole human pancreatic tissue, confirming its plasticity in a dynamic fashion.
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Affiliation(s)
- Mayur Doke
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Silvia Álvarez-Cubela
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Dagmar Klein
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Isabella Altilio
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Joseph Schulz
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Luciana Mateus Gonçalves
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Joana Almaça
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Christopher A Fraker
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Alberto Pugliese
- Arthur Riggs Diabetes & Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Camillo Ricordi
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Mirza M F Qadir
- Tulane University School of Medicine, New Orleans, LA 70112, USA
| | - Ricardo L Pastori
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
| | - Juan Domínguez-Bendala
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA.
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Kondegowda NG, Filipowska J, Do JS, Leon-Rivera N, Li R, Hampton R, Ogyaadu S, Levister C, Penninger JM, Reijonen H, Levy CJ, Vasavada RC. RANKL/RANK is required for cytokine-induced beta cell death; osteoprotegerin, a RANKL inhibitor, reverses rodent type 1 diabetes. SCIENCE ADVANCES 2023; 9:eadf5238. [PMID: 37910614 PMCID: PMC10619938 DOI: 10.1126/sciadv.adf5238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 09/29/2023] [Indexed: 11/03/2023]
Abstract
Treatment for type 1 diabetes (T1D) requires stimulation of functional β cell regeneration and survival under stress. Previously, we showed that inhibition of the RANKL/RANK [receptor activator of nuclear factor kappa Β (NF-κB) ligand] pathway, by osteoprotegerin and the anti-osteoporotic drug denosumab, induces rodent and human β cell proliferation. We demonstrate that the RANK pathway mediates cytokine-induced rodent and human β cell death through RANK-TRAF6 interaction and induction of NF-κB activation. Osteoprotegerin and denosumab protected β cells against this cytotoxicity. In human immune cells, osteoprotegerin and denosumab reduce proinflammatory cytokines in activated T-cells by inhibiting RANKL-induced activation of monocytes. In vivo, osteoprotegerin reversed recent-onset T1D in nonobese diabetic/Ltj mice, reduced insulitis, improved glucose homeostasis, and increased plasma insulin, β cell proliferation, and mass in these mice. Serum from T1D subjects induced human β cell death and dysfunction, but not α cell death. Osteoprotegerin and denosumab reduced T1D serum-induced β cell cytotoxicity and dysfunction. Inhibiting RANKL/RANK could have therapeutic potential.
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Affiliation(s)
- Nagesha Guthalu Kondegowda
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Joanna Filipowska
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jeong-su Do
- Department of Immunology and Theranostics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Nancy Leon-Rivera
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Rosemary Li
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Rollie Hampton
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Selassie Ogyaadu
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Division of Endocrinology and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Camilla Levister
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Division of Endocrinology and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Josef M. Penninger
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna 1030, Austria
- Department of Medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver, Canada
| | - Helena Reijonen
- Department of Immunology and Theranostics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
| | - Carol J. Levy
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Division of Endocrinology and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Rupangi C. Vasavada
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA 91010, USA
- Diabetes, Obesity, and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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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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Thomaidou S, Munoz Garcia A, de Lange S, Gan J, van der Slik AR, Hoeben RC, Roep BO, Carlotti F, Zaldumbide A. IFNɣ but not IFNα increases recognition of insulin defective ribosomal product-derived antigen to amplify islet autoimmunity. Diabetologia 2023; 66:2075-2086. [PMID: 37581620 PMCID: PMC10542729 DOI: 10.1007/s00125-023-05991-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 06/26/2023] [Indexed: 08/16/2023]
Abstract
AIMS/HYPOTHESIS The inflammatory milieu characteristic of insulitis affects translation fidelity and generates defective ribosomal products (DRiPs) that participate in autoimmune beta cell destruction in type 1 diabetes. Here, we studied the role of early innate cytokines (IFNα) and late immune adaptive events (IFNɣ) in insulin DRiP-derived peptide presentation to diabetogenic CD8+ T cells. METHODS Single-cell transcriptomics of human pancreatic islets was used to study the composition of the (immuno)proteasome. Specific inhibition of the immunoproteasome catalytic subunits was achieved using siRNA, and antigenic peptide presentation at the cell surface of the human beta cell line EndoC-βH1 was monitored using peptide-specific CD8 T cells. RESULTS We found that IFNγ induces the expression of the PSMB10 transcript encoding the β2i catalytic subunit of the immunoproteasome in endocrine beta cells, revealing a critical role in insulin DRiP-derived peptide presentation to T cells. Moreover, we showed that PSMB10 is upregulated in a beta cell subset that is preferentially destroyed in the pancreases of individuals with type 1 diabetes. CONCLUSIONS/INTERPRETATION Our data highlight the role of the degradation machinery in beta cell immunogenicity and emphasise the need for evaluation of targeted immunoproteasome inhibitors to limit beta cell destruction in type 1 diabetes. DATA AVAILABILITY The single-cell RNA-seq dataset is available from the Gene Expression Omnibus (GEO) using the accession number GSE218316 ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE218316 ).
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Affiliation(s)
- Sofia Thomaidou
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Amadeo Munoz Garcia
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Sabine de Lange
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jin Gan
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Arno R van der Slik
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Rob C Hoeben
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Bart O Roep
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Françoise Carlotti
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Arnaud Zaldumbide
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
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30
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Hou X, Chen Y, Zhou B, Tang W, Ding Z, Chen L, Wu Y, Yang H, Du C, Yang D, Ma G, Cao H. Talin-1 inhibits Smurf1-mediated Stat3 degradation to modulate β-cell proliferation and mass in mice. Cell Death Dis 2023; 14:709. [PMID: 37903776 PMCID: PMC10616178 DOI: 10.1038/s41419-023-06235-8] [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: 07/08/2023] [Revised: 10/09/2023] [Accepted: 10/19/2023] [Indexed: 11/01/2023]
Abstract
Insufficient pancreatic β-cell mass and reduced insulin expression are key events in the pathogenesis of diabetes mellitus (DM). Here we demonstrate the high expression of Talin-1 in β-cells and that deficiency of Talin-1 reduces β-cell proliferation, which leads to reduced β-cell mass and insulin expression, thus causing glucose intolerance without affecting peripheral insulin sensitivity in mice. High-fat diet fed exerbates these phenotypes. Mechanistically, Talin-1 interacts with the E3 ligase smad ubiquitination regulatory factor 1 (Smurf1), which prohibits ubiquitination of the signal transducer and activator of transcription 3 (Stat3) mediated by Smurf1, and ablation of Talin-1 enhances Smurf1-mediated ubiquitination of Stat3, leading to decreased β-cell proliferation and mass. Furthermore, haploinsufficiency of Talin-1 and Stat3 genes, but not that of either gene, in β-cell in mice significantly impairs glucose tolerance and insulin expression, indicating that both factors indeed function in the same genetic pathway. Finally, inducible deletion Talin-1 in β-cell causes glucose intolerance in adult mice. Collectively, our findings reveal that Talin-1 functions as a crucial regulator of β-cell mass, and highlight its potential as a therapeutic target for DM patients.
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Affiliation(s)
- Xiaoting Hou
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yangshan Chen
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Bo Zhou
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Wanze Tang
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
- The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Zhen Ding
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Litong Chen
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yun Wu
- Department of Oral and Maxillofacial Surgery, Stomatological Center, Peking University Shenzhen Hospital; Guangdong Provincial High-level Clinical Key Specialty; Guangdong Province Engineering Research Center of Oral Disease Diagnosis and Treatment; The Institute of Stomatology, Peking University Shenzhen Hospital, Shenzhen Peking University; The Hong Kong University of Science and Technology Medical Center, Guangdong, China
| | - Hongyu Yang
- Department of Oral and Maxillofacial Surgery, Stomatological Center, Peking University Shenzhen Hospital; Guangdong Provincial High-level Clinical Key Specialty; Guangdong Province Engineering Research Center of Oral Disease Diagnosis and Treatment; The Institute of Stomatology, Peking University Shenzhen Hospital, Shenzhen Peking University; The Hong Kong University of Science and Technology Medical Center, Guangdong, China
| | - Changzheng Du
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Dazhi Yang
- The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Guixing Ma
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Huiling Cao
- Department of Biochemistry, School of Medicine, Southern University of Science and Technology, Key University Laboratory of Metabolism and Health of Guangdong, Guangdong Provincial Key Laboratory of Cell Microenvironment and Disease Research, Southern University of Science and Technology, Shenzhen, 518055, China.
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31
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Zhao Z, D’Oliveira Albanus R, Taylor H, Tang X, Han Y, Orchard P, Varshney A, Zhang T, Manickam N, Erdos M, Narisu N, Taylor L, Saavedra X, Zhong A, Li B, Zhou T, Naji A, Liu C, Collins F, Parker SCJ, Chen S. An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals. RESEARCH SQUARE 2023:rs.3.rs-3343318. [PMID: 37886586 PMCID: PMC10602166 DOI: 10.21203/rs.3.rs-3343318/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.
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Affiliation(s)
- Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | | | - Henry Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xuming Tang
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Yuling Han
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Tuo Zhang
- Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mike Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaxia Saavedra
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Aaron Zhong
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Bo Li
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Ting Zhou
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Francis Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Stephen CJ Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
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32
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Zhang Z, Mathew D, Lim T, Mason K, Martinez CM, Huang S, Wherry EJ, Susztak K, Minn AJ, Ma Z, Zhang NR. Signal recovery in single cell batch integration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.05.539614. [PMID: 37215021 PMCID: PMC10197537 DOI: 10.1101/2023.05.05.539614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Data integration to align cells across batches has become a cornerstone of single cell data analysis, critically affecting downstream results. Yet, how much biological signal is erased during integration? Currently, there are no guidelines for when the biological differences between samples are separable from batch effects, and thus, data integration usually involve a lot of guesswork: Cells across batches should be aligned to be "appropriately" mixed, while preserving "main cell type clusters". We show evidence that current paradigms for single cell data integration are unnecessarily aggressive, removing biologically meaningful variation. To remedy this, we present a novel statistical model and computationally scalable algorithm, CellANOVA, to recover biological signal that is lost during single cell data integration. CellANOVA utilizes a "pool-of-controls" design concept, applicable across diverse settings, to separate unwanted variation from biological variation of interest. When applied with existing integration methods, CellANOVA allows the recovery of subtle biological signals and corrects, to a large extent, the data distortion introduced by integration. Further, CellANOVA explicitly estimates cell- and gene-specific batch effect terms which can be used to identify the cell types and pathways exhibiting the largest batch variations, providing clarity as to which biological signals can be recovered. These concepts are illustrated on studies of diverse designs, where the biological signals that are recovered by CellANOVA are shown to be validated by orthogonal assays. In particular, we show that CellANOVA is effective in the challenging case of single-cell and single-nuclei data integration, where the recovered biological signals are replicated in an independent study.
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Affiliation(s)
- Zhaojun Zhang
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, PA, United States
| | - Divij Mathew
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Tristan Lim
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Kaishu Mason
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, PA, United States
| | - Clara Morral Martinez
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Mark Foundation Center for Immunotherapy, Immune Signaling, and Radiation, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Sijia Huang
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - E John Wherry
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Mark Foundation Center for Immunotherapy, Immune Signaling, and Radiation, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Katalin Susztak
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, PA, United States
- Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, PA, United States
- Department of Genetics, University of Pennsylvania, PA, United States
| | - Andy J Minn
- Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, PA, United States
- Mark Foundation Center for Immunotherapy, Immune Signaling, and Radiation, Perelman School of Medicine, University of Pennsylvania, PA, United States
| | - Zongming Ma
- Department of Statistics and Data Science, Yale University, CT, United States
| | - Nancy R Zhang
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, PA, United States
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33
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Zhao Y, Wang D, Qian T, Zhang J, Li Z, Gong Q, Ren X, Zhao Y. Biomimetic Nanozyme-Decorated Hydrogels with H 2O 2-Activated Oxygenation for Modulating Immune Microenvironment in Diabetic Wound. ACS NANO 2023; 17:16854-16869. [PMID: 37622922 DOI: 10.1021/acsnano.3c03761] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
Diabetic foot ulcers (DFUs) remain a devastating threat to human health. While hydrogels are promising systems for DFU-based wound management, their effectiveness is often hindered by the immune response and hostile wound microenvironment associated with the uncontrollable accumulation of reactive oxygen species and hypoxia. Here, we develop a therapeutic wound dressing using a biomimetic hydrogel system with the decoration of catalase-mimic nanozyme, namely, MnCoO@PDA/CPH. The hydrogel can be designed to match the mechanical and electrical cues of skins simultaneously with H2O2-activated oxygenation ability. As a proof of concept, DFU-based rat models are created to validate the therapeutic efficacy of the MnCoO@PDA/CPH hydrogel in vivo. The results indicate that the developed hydrogel can promote DFU healing and improve the quality of the healed wound as featured by alleviated proinflammatory, increased re-epithelialization, highly ordered collagen deposition, and functional blood vessel growth.
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Affiliation(s)
- Yue Zhao
- International Joint Research Center for Molecular Science, College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, China
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore
| | - Dongdong Wang
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore
| | - Tianwei Qian
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200025, China
| | - Junmin Zhang
- International Joint Research Center for Molecular Science, College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, China
| | - Zuhao Li
- Department of Orthopaedics, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China
| | - Qiaoyun Gong
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai Engineering Center for Visual Science and Photomedicine, Shanghai 200025, China
| | - Xiangzhong Ren
- International Joint Research Center for Molecular Science, College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen 518060, China
| | - Yanli Zhao
- School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore
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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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35
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Cantley J, Eizirik DL, Latres E, Dayan CM. Islet cells in human type 1 diabetes: from recent advances to novel therapies - a symposium-based roadmap for future research. J Endocrinol 2023; 259:e230082. [PMID: 37493471 PMCID: PMC10502961 DOI: 10.1530/joe-23-0082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/25/2023] [Indexed: 07/27/2023]
Abstract
There is a growing understanding that the early phases of type 1 diabetes (T1D) are characterised by a deleterious dialogue between the pancreatic beta cells and the immune system. This, combined with the urgent need to better translate this growing knowledge into novel therapies, provided the background for the JDRF-DiabetesUK-INNODIA-nPOD symposium entitled 'Islet cells in human T1D: from recent advances to novel therapies', which took place in Stockholm, Sweden, in September 2022. We provide in this article an overview of the main themes addressed in the symposium, pointing to both promising conclusions and key unmet needs that remain to be addressed in order to achieve better approaches to prevent or reverse T1D.
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Affiliation(s)
- J Cantley
- School of Medicine, University of Dundee, Dundee, United Kingdom of Great Britain and Northern Ireland
| | - D L Eizirik
- ULB Center for Diabetes Research, Université Libre de Bruxelles Faculté de Médecine, Bruxelles, Belgium
| | - E Latres
- JDRF International, New York, NY, USA
| | - C M Dayan
- Cardiff University School of Medicine, Cardiff, United Kingdom of Great Britain and Northern Ireland
| | - the JDRF-DiabetesUK-INNODIA-nPOD Stockholm Symposium 2022
- School of Medicine, University of Dundee, Dundee, United Kingdom of Great Britain and Northern Ireland
- ULB Center for Diabetes Research, Université Libre de Bruxelles Faculté de Médecine, Bruxelles, Belgium
- JDRF International, New York, NY, USA
- Cardiff University School of Medicine, Cardiff, United Kingdom of Great Britain and Northern Ireland
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36
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Vanheer L, Fantuzzi F, To SK, Schiavo A, Van Haele M, Ostyn T, Haesen T, Yi X, Janiszewski A, Chappell J, Rihoux A, Sawatani T, Roskams T, Pattou F, Kerr-Conte J, Cnop M, Pasque V. Inferring regulators of cell identity in the human adult pancreas. NAR Genom Bioinform 2023; 5:lqad068. [PMID: 37435358 PMCID: PMC10331937 DOI: 10.1093/nargab/lqad068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 06/17/2023] [Accepted: 06/28/2023] [Indexed: 07/13/2023] Open
Abstract
Cellular identity during development is under the control of transcription factors that form gene regulatory networks. However, the transcription factors and gene regulatory networks underlying cellular identity in the human adult pancreas remain largely unexplored. Here, we integrate multiple single-cell RNA-sequencing datasets of the human adult pancreas, totaling 7393 cells, and comprehensively reconstruct gene regulatory networks. We show that a network of 142 transcription factors forms distinct regulatory modules that characterize pancreatic cell types. We present evidence that our approach identifies regulators of cell identity and cell states in the human adult pancreas. We predict that HEYL, BHLHE41 and JUND are active in acinar, beta and alpha cells, respectively, and show that these proteins are present in the human adult pancreas as well as in human induced pluripotent stem cell (hiPSC)-derived islet cells. Using single-cell transcriptomics, we found that JUND represses beta cell genes in hiPSC-alpha cells. BHLHE41 depletion induced apoptosis in primary pancreatic islets. The comprehensive gene regulatory network atlas can be explored interactively online. We anticipate our analysis to be the starting point for a more sophisticated dissection of how transcription factors regulate cell identity and cell states in the human adult pancreas.
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Affiliation(s)
| | | | - San Kit To
- Department of Development and Regeneration; KU Leuven - University of Leuven; Single-cell Omics Institute and Leuven Stem Cell Institute, Herestraat 49, B-3000 Leuven, Belgium
| | - Andrea Schiavo
- ULB Center for Diabetes Research; Université Libre de Bruxelles; Route de Lennik 808, B-1070 Brussels, Belgium
| | - Matthias Van Haele
- Department of Imaging and Pathology; Translational Cell and Tissue Research, KU Leuven and University Hospitals Leuven; Herestraat 49, B-3000 Leuven, Belgium
| | - Tessa Ostyn
- Department of Imaging and Pathology; Translational Cell and Tissue Research, KU Leuven and University Hospitals Leuven; Herestraat 49, B-3000 Leuven, Belgium
| | - Tine Haesen
- Department of Development and Regeneration; KU Leuven - University of Leuven; Single-cell Omics Institute and Leuven Stem Cell Institute, Herestraat 49, B-3000 Leuven, Belgium
| | - Xiaoyan Yi
- ULB Center for Diabetes Research; Université Libre de Bruxelles; Route de Lennik 808, B-1070 Brussels, Belgium
| | - Adrian Janiszewski
- Department of Development and Regeneration; KU Leuven - University of Leuven; Single-cell Omics Institute and Leuven Stem Cell Institute, Herestraat 49, B-3000 Leuven, Belgium
| | - Joel Chappell
- Department of Development and Regeneration; KU Leuven - University of Leuven; Single-cell Omics Institute and Leuven Stem Cell Institute, Herestraat 49, B-3000 Leuven, Belgium
| | - Adrien Rihoux
- Department of Development and Regeneration; KU Leuven - University of Leuven; Single-cell Omics Institute and Leuven Stem Cell Institute, Herestraat 49, B-3000 Leuven, Belgium
| | - Toshiaki Sawatani
- ULB Center for Diabetes Research; Université Libre de Bruxelles; Route de Lennik 808, B-1070 Brussels, Belgium
| | - Tania Roskams
- Department of Imaging and Pathology; Translational Cell and Tissue Research, KU Leuven and University Hospitals Leuven; Herestraat 49, B-3000 Leuven, Belgium
| | - Francois Pattou
- University of Lille, Inserm, CHU Lille, Institute Pasteur Lille, U1190-EGID, F-59000 Lille, France
- European Genomic Institute for Diabetes, F-59000 Lille, France
- University of Lille, F-59000 Lille, France
| | - Julie Kerr-Conte
- University of Lille, Inserm, CHU Lille, Institute Pasteur Lille, U1190-EGID, F-59000 Lille, France
- European Genomic Institute for Diabetes, F-59000 Lille, France
- University of Lille, F-59000 Lille, France
| | - Miriam Cnop
- Correspondence may also be addressed to Miriam Cnop. Tel: +32 2 555 6305; Fax: +32 2 555 6239;
| | - Vincent Pasque
- To whom correspondence should be addressed. Tel: +32 16 376283; Fax: +32 16 330827;
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Sun F, Yang CL, Wang FX, Rong SJ, Luo JH, Lu WY, Yue TT, Wang CY, Liu SW. Pancreatic draining lymph nodes (PLNs) serve as a pathogenic hub contributing to the development of type 1 diabetes. Cell Biosci 2023; 13:156. [PMID: 37641145 PMCID: PMC10464122 DOI: 10.1186/s13578-023-01110-7] [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: 03/08/2023] [Accepted: 08/21/2023] [Indexed: 08/31/2023] Open
Abstract
Type 1 diabetes (T1D) is a chronic, progressive autoinflammatory disorder resulting from the breakdown of self-tolerance and unrestrained β cell-reactive immune response. Activation of immune cells is initiated in islet and amplified in lymphoid tissues, especially those pancreatic draining lymph nodes (PLNs). The knowledge of PLNs as the hub of aberrant immune response is continuously being replenished and renewed. Here we provide a PLN-centered view of T1D pathogenesis and emphasize that PLNs integrate signal inputs from the pancreas, gut, viral infection or peripheral circulation, undergo immune remodeling within the local microenvironment and export effector cell components into pancreas to affect T1D progression. In accordance, we suggest that T1D intervention can be implemented by three major ways: cutting off the signal inputs into PLNs (reduce inflammatory β cell damage, enhance gut integrity and control pathogenic viral infections), modulating the immune activation status of PLNs and blocking the outputs of PLNs towards pancreatic islets. Given the dynamic and complex nature of T1D etiology, the corresponding intervention strategy is thus required to be comprehensive to ensure optimal therapeutic efficacy.
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Affiliation(s)
- Fei Sun
- Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chun-Liang Yang
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Fa-Xi Wang
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shan-Jie Rong
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia-Hui Luo
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wan-Ying Lu
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tian-Tian Yue
- Devision of Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Cong-Yi Wang
- Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
- NHC Key Laboratory of Respiratory Diseases, Department of Respiratory and Critical Care Medicine, The Center for Biomedical Research, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Shi-Wei Liu
- Shanxi Bethune Hospital, Shanxi Academy of Medical Science, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
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38
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Van Emmenis L. Golnaz Vahedi: My environment enables me to achieve impossible goals. J Exp Med 2023; 220:e20231182. [PMID: 37477639 PMCID: PMC10360022 DOI: 10.1084/jem.20231182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023] Open
Abstract
Golnaz Vahedi is an associate professor of genetics at the Perelman School of Medicine, University of Pennsylvania. Golnaz runs a multidisciplinary lab that uses cutting-edge computational and experimental approaches to understand the molecular mechanisms by which genomic information in immune cells is interpreted in normal development and during immune-mediated diseases. We talked about her diverse scientific background, the benefits of integrating molecular biology and immunology, and the importance of staying positive in academia.
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39
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Jiang H, Zheng S, Qian Y, Zhou Y, Dai H, Liang Y, He Y, Gao R, Lv H, Zhang J, Xia Z, Bian W, Yang T, Fu Q. Restored UBE2C expression in islets promotes β-cell regeneration in mice by ubiquitinating PER1. Cell Mol Life Sci 2023; 80:226. [PMID: 37486389 PMCID: PMC11072275 DOI: 10.1007/s00018-023-04868-8] [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: 01/16/2023] [Revised: 07/08/2023] [Accepted: 07/10/2023] [Indexed: 07/25/2023]
Abstract
Insulin deficiency may be due to the reduced proliferation capacity of islet β-cell, contributing to the onset of diabetes. It is therefore imperative to investigate the mechanism of the β-cell regeneration in the islets. NKX6.1, one of the critical β-cell transcription factors, is a pivotal element in β-cell proliferation. The ubiquitin-binding enzyme 2C (UBE2C) was previously reported as one of the downstream molecules of NKX6.1 though the exact function and mechanism of UBE2C in β-cell remain to be elucidated. Here, we determined a subpopulation of islet β-cells highly expressing UBE2C, which proliferate actively. We also discovered that β-cell compensatory proliferation was induced by UBE2C via the cell cycle renewal pathway in weaning and high-fat diet (HFD)-fed mice. Moreover, the reduction of β-cell proliferation led to insulin deficiency in βUbe2cKO mice and, therefore, developed type 2 diabetes. UBE2C was found to regulate PER1 degradation through the ubiquitin-proteasome pathway via its association with a ubiquitin ligase, CUL1. PER1 inhibition rescues UBE2C knockout-induced β-cell growth inhibition both in vivo and in vitro. Notably, overexpression of UBE2C via lentiviral transduction in pancreatic islets was able to relaunch β-cell proliferation in STZ-induced diabetic mice and therefore partially alleviated hyperglycaemia and glucose intolerance. This study indicates that UBE2C positively regulates β-cell proliferation by promoting ubiquitination and degradation of the biological clock suppressor PER1. The beneficial effect of UBE2C on islet β-cell regeneration suggests a promising application in treating diabetic patients with β-cell deficiency.
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Affiliation(s)
- Hemin Jiang
- 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
| | - Yu Qian
- 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
| | - Hao Dai
- 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
| | - 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
| | - Hui Lv
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Zhang
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhiqing Xia
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Wenxuan Bian
- 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.
| | - Qi Fu
- Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Xie B, Gao D, Zhou B, Chen S, Wang L. New discoveries in the field of metabolism by applying single-cell and spatial omics. J Pharm Anal 2023; 13:711-725. [PMID: 37577385 PMCID: PMC10422156 DOI: 10.1016/j.jpha.2023.06.002] [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: 10/30/2022] [Revised: 05/29/2023] [Accepted: 06/02/2023] [Indexed: 08/15/2023] Open
Abstract
Single-cell multi-Omics (SCM-Omics) and spatial multi-Omics (SM-Omics) technologies provide state-of-the-art methods for exploring the composition and function of cell types in tissues/organs. Since its emergence in 2009, single-cell RNA sequencing (scRNA-seq) has yielded many groundbreaking new discoveries. The combination of this method with the emergence and development of SM-Omics techniques has been a pioneering strategy in neuroscience, developmental biology, and cancer research, especially for assessing tumor heterogeneity and T-cell infiltration. In recent years, the application of these methods in the study of metabolic diseases has also increased. The emerging SCM-Omics and SM-Omics approaches allow the molecular and spatial analysis of cells to explore regulatory states and determine cell fate, and thus provide promising tools for unraveling heterogeneous metabolic processes and making them amenable to intervention. Here, we review the evolution of SCM-Omics and SM-Omics technologies, and describe the progress in the application of SCM-Omics and SM-Omics in metabolism-related diseases, including obesity, diabetes, nonalcoholic fatty liver disease (NAFLD) and cardiovascular disease (CVD). We also conclude that the application of SCM-Omics and SM-Omics approaches can help resolve the molecular mechanisms underlying the pathogenesis of metabolic diseases in the body and facilitate therapeutic measures for metabolism-related diseases. This review concludes with an overview of the current status of this emerging field and the outlook for its future.
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Affiliation(s)
- Baocai Xie
- Department of Critical Care Medicine, Shenzhen Institute of Translational Medicine, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, Guangdong, 518060, China
- Department of Respiratory Diseases, The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450014, China
| | - Dengfeng Gao
- State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, 100193, China
| | - Biqiang Zhou
- Department of Geriatric & Spinal Pain Multi-Department Treatment, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen, Guangdong, 518035, China
| | - Shi Chen
- Department of Critical Care Medicine, Shenzhen Institute of Translational Medicine, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, Guangdong, 518060, China
- Department of Gastroenterology, Ministry of Education Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Zhongnan Hospital of Wuhan University, School of Pharmaceutical Sciences, Wuhan University, Wuhan, 430071, China
| | - Lianrong Wang
- Department of Respiratory Diseases, The Research and Application Center of Precision Medicine, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450014, China
- Department of Gastroenterology, Ministry of Education Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Zhongnan Hospital of Wuhan University, School of Pharmaceutical Sciences, Wuhan University, Wuhan, 430071, China
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Eizirik DL, Szymczak F, Mallone R. Why does the immune system destroy pancreatic β-cells but not α-cells in type 1 diabetes? Nat Rev Endocrinol 2023; 19:425-434. [PMID: 37072614 DOI: 10.1038/s41574-023-00826-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/06/2023] [Indexed: 04/20/2023]
Abstract
A perplexing feature of type 1 diabetes (T1D) is that the immune system destroys pancreatic β-cells but not neighbouring α-cells, even though both β-cells and α-cells are dysfunctional. Dysfunction, however, progresses to death only for β-cells. Recent findings indicate important differences between these two cell types. First, expression of BCL2L1, a key antiapoptotic gene, is higher in α-cells than in β-cells. Second, endoplasmic reticulum (ER) stress-related genes are differentially expressed, with higher expression levels of pro-apoptotic CHOP in β-cells than in α-cells and higher expression levels of HSPA5 (which encodes the protective chaperone BiP) in α-cells than in β-cells. Third, expression of viral recognition and innate immune response genes is higher in α-cells than in β-cells, contributing to the enhanced resistance of α-cells to coxsackievirus infection. Fourth, expression of the immune-inhibitory HLA-E molecule is higher in α-cells than in β-cells. Of note, α-cells are less immunogenic than β-cells, and the CD8+ T cells invading the islets in T1D are reactive to pre-proinsulin but not to glucagon. We suggest that this finding is a result of the enhanced capacity of the α-cell to endure viral infections and ER stress, which enables them to better survive early stressors that can cause cell death and consequently amplify antigen presentation to the immune system. Moreover, the processing of the pre-proglucagon precursor in enteroendocrine cells might favour immune tolerance towards this potential self-antigen compared to pre-proinsulin.
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Affiliation(s)
- Decio L Eizirik
- Université Libre de Bruxelles (ULB) Center for Diabetes Research and Welbio, Medical Faculty, Brussels, Belgium.
| | - Florian Szymczak
- Université Libre de Bruxelles (ULB) Center for Diabetes Research and Welbio, Medical Faculty, Brussels, Belgium
| | - Roberto Mallone
- Université Paris Cité, Institut Cochin, CNRS, INSERM, Paris, France
- Assistance Publique Hôpitaux de Paris, Service de Diabétologie et Immunologie Clinique, Cochin Hospital, Paris, France
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Cephas AT, Hwang WL, Maitra A, Parnas O, DelGiorno KE. It is better to light a candle than to curse the darkness: single-cell transcriptomics sheds new light on pancreas biology and disease. Gut 2023; 72:1211-1219. [PMID: 36997301 PMCID: PMC10988578 DOI: 10.1136/gutjnl-2022-329313] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/19/2023] [Indexed: 04/01/2023]
Abstract
Recent advances in single-cell RNA sequencing and bioinformatics have drastically increased our ability to interrogate the cellular composition of traditionally difficult to study organs, such as the pancreas. With the advent of these technologies and approaches, the field has grown, in just a few years, from profiling pancreas disease states to identifying molecular mechanisms of therapy resistance in pancreatic ductal adenocarcinoma, a particularly deadly cancer. Single-cell transcriptomics and related spatial approaches have identified previously undescribed epithelial and stromal cell types and states, how these populations change with disease progression, and potential mechanisms of action which will serve as the basis for designing new therapeutic strategies. Here, we review the recent literature on how single-cell transcriptomic approaches have changed our understanding of pancreas biology and disease progression.
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Affiliation(s)
- Amelia T Cephas
- Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
| | - William L Hwang
- Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Eli and Edythe L Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
| | - Anirban Maitra
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Sheikh Ahmed Pancreatic Cancer Research Center, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Oren Parnas
- Lautenberg Center for Immunology and Cancer Research, IMRIC, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Kathleen E DelGiorno
- Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Digestive Disease Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Patil AR, Schug J, Naji A, Kaestner KH, Faryabi RB, Vahedi G. Single-cell expression profiling of islets generated by the Human Pancreas Analysis Program. Nat Metab 2023; 5:713-715. [PMID: 37188822 PMCID: PMC10731597 DOI: 10.1038/s42255-023-00806-x] [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: 05/17/2023]
Affiliation(s)
- Abhijeet R Patil
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jonathan Schug
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ali Naji
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Klaus H Kaestner
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Robert B Faryabi
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Golnaz Vahedi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute for Immunology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
- Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
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Wang Y, Gao Y, Li X, Tian G, Lü J. Single-cell infrared phenomics identifies cell heterogeneity of individual pancreatic islets in mouse model. Anal Chim Acta 2023; 1258:341185. [PMID: 37087295 DOI: 10.1016/j.aca.2023.341185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 03/27/2023] [Accepted: 04/05/2023] [Indexed: 04/08/2023]
Abstract
Identifying the islet heterogeneity (cell types and the proportion of each subpopulation) and their relevance to function and disease will lead to fundamental information for the prevention and therapies of diabetes. Here, we introduce a single-cell phenotypic essay on the heterogeneity within individual pancreatic islets by using the combination of synchrotron infrared microspectroscopy and quantitative calculation. In a mouse model, the cellular heterogeneities at both the whole pancreas and single intact islet level were identified. The variation of biochemical phenotypes successfully subdivided islet cells into five main groups and quantitatively determined their proportion. These findings not only demonstrate single-cell infrared phenomics as a value complementary technique and strategy for the description of cellular heterogeneity within the pancreatic islets but also provide a quick, label-free optical platform for investigating phenotypic heterogeneity at the small-organelle level with single cell resolution.
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Basu L, Bhagat V, Ching MEA, Di Giandomenico A, Dostie S, Greenberg D, Greenberg M, Hahm J, Hilton NZ, Lamb K, Jentz EM, Larsen M, Locatelli CAA, Maloney M, MacGibbon C, Mersali F, Mulchandani CM, Najam A, Singh I, Weisz T, Wong J, Senior PA, Estall JL, Mulvihill EE, Screaton RA. Recent Developments in Islet Biology: A Review With Patient Perspectives. Can J Diabetes 2023; 47:207-221. [PMID: 36481263 PMCID: PMC9640377 DOI: 10.1016/j.jcjd.2022.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/24/2022] [Accepted: 11/02/2022] [Indexed: 11/09/2022]
Abstract
Navigating the coronavirus disease-2019 (COVID-19, now COVID) pandemic has required resilience and creativity worldwide. Despite early challenges to productivity, more than 2,000 peer-reviewed articles on islet biology were published in 2021. Herein, we highlight noteworthy advances in islet research between January 2021 and April 2022, focussing on 5 areas. First, we discuss new insights into the role of glucokinase, mitogen-activated protein kinase-kinase/extracellular signal-regulated kinase and mitochondrial function on insulin secretion from the pancreatic β cell, provided by new genetically modified mouse models and live imaging. We then discuss a new connection between lipid handling and improved insulin secretion in the context of glucotoxicity, focussing on fatty acid-binding protein 4 and fetuin-A. Advances in high-throughput "omic" analysis evolved to where one can generate more finely tuned genetic and molecular profiles within broad classifications of type 1 diabetes and type 2 diabetes. Next, we highlight breakthroughs in diabetes treatment using stem cell-derived β cells and innovative strategies to improve islet survival posttransplantation. Last, we update our understanding of the impact of severe acute respiratory syndrome-coronavirus-2 infection on pancreatic islet function and discuss current evidence regarding proposed links between COVID and new-onset diabetes. We address these breakthroughs in 2 settings: one for a scientific audience and the other for the public, particularly those living with or affected by diabetes. Bridging biomedical research in diabetes to the community living with or affected by diabetes, our partners living with type 1 diabetes or type 2 diabetes also provide their perspectives on these latest advances in islet biology.
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Affiliation(s)
- Lahari Basu
- Department of Biology and Institute of Biochemistry, Carleton University, Ottawa, Ontario, Canada
| | - Vriti Bhagat
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada; BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Ma Enrica Angela Ching
- Department of Biology and Institute of Biochemistry, Carleton University, Ottawa, Ontario, Canada
| | | | - Sylvie Dostie
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Dana Greenberg
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Marley Greenberg
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Jiwon Hahm
- Department of Physiology and Pharmacology, Western University, London, Ontario, Canada
| | - N Zoe Hilton
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Krista Lamb
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Emelien M Jentz
- School of Pharmacy, University of Waterloo, Kitchener, Ontario, Canada
| | - Matt Larsen
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Cassandra A A Locatelli
- University of Ottawa Heart Institute, Energy Substrate Laboratory, Ottawa, Ontario, Canada; Department of Biochemistry, Immunology and Microbiology, University of Ottawa, Ottawa, Ontario, Canada
| | - MaryAnn Maloney
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | | | - Farida Mersali
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | | | - Adhiyat Najam
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Ishnoor Singh
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Tom Weisz
- Diabetes Action Canada, Toronto General Hospital, Toronto, Ontario, Canada
| | - Jordan Wong
- Alberta Diabetes Institute and Department of Pharmacology, Li Ka Shing Centre for Health Research Innovation, University of Alberta, Edmonton, Alberta, Canada; Alberta Diabetes Institute and Department of Surgery, University of Alberta, Edmonton, Alberta, Canada
| | - Peter A Senior
- Alberta Diabetes Institute and Department of Medicine, Edmonton, Alberta, Canada
| | - Jennifer L Estall
- Faculté de Médecine, Université de Montréal, Montréal, Québec, Canada; Institut de recherches cliniques de Montréal, Center for Cardiometabolic Health, Montréal, Québec, Canada
| | - Erin E Mulvihill
- University of Ottawa Heart Institute, Energy Substrate Laboratory, Ottawa, Ontario, Canada; Department of Biochemistry, Immunology and Microbiology, University of Ottawa, Ottawa, Ontario, Canada
| | - Robert A Screaton
- Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada; Sunnybrook Research Institute, Toronto, Ontario, Canada.
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Jung S, Lee JS. Single-Cell Genomics for Investigating Pathogenesis of Inflammatory Diseases. Mol Cells 2023; 46:120-129. [PMID: 36859476 PMCID: PMC9982059 DOI: 10.14348/molcells.2023.0002] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 03/03/2023] Open
Abstract
Recent technical advances have enabled unbiased transcriptomic and epigenetic analysis of each cell, known as "single-cell analysis". Single-cell analysis has a variety of technical approaches to investigate the state of each cell, including mRNA levels (transcriptome), the immune repertoire (immune repertoire analysis), cell surface proteins (surface proteome analysis), chromatin accessibility (epigenome), and accordance with genome variants (eQTLs; expression quantitative trait loci). As an effective tool for investigating robust immune responses in coronavirus disease 2019 (COVID-19), many researchers performed single-cell analysis to capture the diverse, unbiased immune cell activation and differentiation. Despite challenges elucidating the complicated immune microenvironments of chronic inflammatory diseases using existing experimental methods, it is now possible to capture the simultaneous immune features of different cell types across inflamed tissues using various single-cell tools. In this review, we introduce patient-based and experimental mouse model research utilizing single-cell analyses in the field of chronic inflammatory diseases, as well as multi-organ atlas targeting immune cells.
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Affiliation(s)
- Seyoung Jung
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Jeong Seok Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
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47
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Zhang S, Chen S, Zhu R. Electroporation-Assisted Surface-Enhanced Raman Detection for Long-Term, Label-Free, and Noninvasive Molecular Profiling of Live Single Cells. ACS Sens 2023; 8:555-564. [PMID: 36399395 DOI: 10.1021/acssensors.2c01582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Molecule characterization of live single cells is greatly important in disease diagnoses and personalized treatments. Conventional molecule detection methods, such as mass spectrography, gene sequencing, or immunofluorescence, are usually destructive or labeled and unable to monitor the dynamic change of live cellular molecules. Herein, we propose an electroporation-assisted surface-enhanced Raman scattering (EP-SERS) method using a microchip to implement label-free, noninvasive, and continuous detections of the molecules of live single cells. The microchip containing microelectrodes with nanostructured EP-SERS probes has a multifunction of cell positioning, electroporation, and SERS detection. The EP-SERS method capably detects both the intracellular and extracellular molecules of live single cells without losing cell viability so as to enable long-term monitoring of the molecular pathological process in situ. We detect the molecules of single cells for two breast cancer cell lines with different malignancies (MCF-7 and MDA-MB-231), one liver cancer cell line (Huh-7), and one normal cell line (293T) using the EP-SERS method and classify these cell types to achieve high accuracies of 91.4-98.3% using their SERS spectra. Furthermore, 24 h continuous monitoring of the heterogeneous molecular responses of different cancer cell lines under doxorubicin treatment is successfully implemented using the EP-SERS method. This work provides a long-term, label-free, and biocompatible approach to simultaneously detect intracellular and extracellular molecules of live single cells on a chip, which would facilitate research and applications of cancer diagnoses and personalized treatments.
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Affiliation(s)
- Shengsen Zhang
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing100084, China
| | - Shengjie Chen
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing100084, China
| | - Rong Zhu
- State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua University, Beijing100084, China
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48
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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. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.03.526994. [PMID: 36778506 PMCID: PMC9915747 DOI: 10.1101/2023.02.03.526994] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Pancreatic islets are comprised of multiple endocrine cell types that produce hormones required for glucose homeostasis, and islet dysfunction is a major factor in the development of type 1 and type 2 diabetes (T1D, T2D). Numerous studies have generated gene expression profiles in individual islet cell types using single cell assays. However, there is no canonical reference of gene expression in islet cell types in both health and disease that is also easily accessible for researchers to access, query, and use in bioinformatics pipelines. Here we present an integrated reference map of islet cell type-specific gene expression from 192,203 cells derived from single cell RNA-seq assays of 65 non-diabetic, T1D autoantibody positive (Aab+), T1D, and T2D donors from the Human Pancreas Analysis Program. We identified 10 endocrine and non-endocrine cell types as well as sub-populations of several cell types, and defined sets of marker genes for each cell type and sub-population. We tested for differential expression within each cell type in T1D Aab+, T1D, and T2D states, and identified 1,701 genes with significant changes in expression in any cell type. Most changes were observed in beta cells in T1D, and, by comparison, there were almost no genes with changes in T1D Aab+. To facilitate user interaction with this reference, we provide the data using several single cell visualization and reference mapping tools as well as open-access analytical pipelines used to create this reference. The results will serve as a valuable resource to investigators studying islet biology and diabetes.
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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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49
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Embracing lipidomics at single-cell resolution: Promises and pitfalls. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2023.116973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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50
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Peng G, Mosleh E, Yuhas A, Katada K, Cherry C, Golson ML. FOXM1 acts sexually dimorphically to regulate functional β-cell mass. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.12.523673. [PMID: 36711451 PMCID: PMC9882186 DOI: 10.1101/2023.01.12.523673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
The transcription factor FOXM1 regulates β-cell proliferation and insulin secretion. Our previous work demonstrates that expressing an activated form of FOXM1 (FOXM1*) in β cells increases β-cell proliferation and mass in aged male mice. Additionally, FOXM1* enhances β-cell function even in young mice, in which no β-cell mass elevation occurs. Here, we demonstrate that FOXM1 acts in a sexually dimorphic manner in the β cell. Expression of FOXM1* in female mouse β cells does not affect β-cell proliferation or glucose tolerance. Transduction of male but not female human islets with FOXM1* enhances insulin secretion in response to elevated glucose. Estrogen contributes to diabetes susceptibility differences between males and females, and the estrogen receptor (ER)α is the primary mediator of β-cell estrogen signaling. We show that FOXM1* can rescue impaired glucose tolerance in female mice with a pancreas-wide ERα deletion. Further, FOXM1 and ERα binding sites overlap with each other and with other β-cell-enriched transcription factors, including ISL1, PAX6, MAF, and GATA. These data indicate that FOMX1 and ERα cooperate to regulate β-cell function and suggest a general mechanism contributing to the lower incidence of diabetes observed in women.
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