1
|
Xu K, Nnyamah C, Pandya N, Sweis N, Corona-Avila I, Priyadarshini M, Wicksteed B, Layden BT. β cell acetate production and release are negligible. Islets 2024; 16:2339558. [PMID: 38607959 PMCID: PMC11018053 DOI: 10.1080/19382014.2024.2339558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 04/02/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND Studies suggest that short chain fatty acids (SCFAs), which are primarily produced from fermentation of fiber, regulate insulin secretion through free fatty acid receptors 2 and 3 (FFA2 and FFA3). As these are G-protein coupled receptors (GPCRs), they have potential therapeutic value as targets for treating type 2 diabetes (T2D). The exact mechanism by which these receptors regulate insulin secretion and other aspects of pancreatic β cell function is unclear. It has been reported that glucose-dependent release of acetate from pancreatic β cells negatively regulates glucose stimulated insulin secretion. While these data raise the possibility of acetate's potential autocrine action on these receptors, these findings have not been independently confirmed, and multiple concerns exist with this observation, particularly the lack of specificity and precision of the acetate detection methodology used. METHODS Using Min6 cells and mouse islets, we assessed acetate and pyruvate production and secretion in response to different glucose concentrations, via liquid chromatography mass spectrometry. RESULTS Using Min6 cells and mouse islets, we showed that both intracellular pyruvate and acetate increased with high glucose conditions; however, intracellular acetate level increased only slightly and exclusively in Min6 cells but not in the islets. Further, extracellular acetate levels were not affected by the concentration of glucose in the incubation medium of either Min6 cells or islets. CONCLUSIONS Our findings do not substantiate the glucose-dependent release of acetate from pancreatic β cells, and therefore, invalidate the possibility of an autocrine inhibitory effect on glucose stimulated insulin secretion.
Collapse
Affiliation(s)
- Kai Xu
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Chioma Nnyamah
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Nupur Pandya
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Nadia Sweis
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Irene Corona-Avila
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Medha Priyadarshini
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Barton Wicksteed
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
| | - Brian T. Layden
- Division of Endocrinology, Diabetes and Metabolism, University of Illinois at Chicago, Chicago, IL, USA
- Jesse Brown VA Medical Center, Chicago, IL, USA
| |
Collapse
|
2
|
Wang J, Wen S, Chen M, Xie J, Lou X, Zhao H, Chen Y, Zhao M, Shi G. Regulation of endocrine cell alternative splicing revealed by single-cell RNA sequencing in type 2 diabetes pathogenesis. Commun Biol 2024; 7:778. [PMID: 38937540 PMCID: PMC11211498 DOI: 10.1038/s42003-024-06475-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 06/19/2024] [Indexed: 06/29/2024] Open
Abstract
The prevalent RNA alternative splicing (AS) contributes to molecular diversity, which has been demonstrated in cellular function regulation and disease pathogenesis. However, the contribution of AS in pancreatic islets during diabetes progression remains unclear. Here, we reanalyze the full-length single-cell RNA sequencing data from the deposited database to investigate AS regulation across human pancreatic endocrine cell types in non-diabetic (ND) and type 2 diabetic (T2D) individuals. Our analysis demonstrates the significant association between transcriptomic AS profiles and cell-type-specificity, which could be applied to distinguish the clustering of major endocrine cell types. Moreover, AS profiles are enabled to clearly define the mature subset of β-cells in healthy controls, which is completely lost in T2D. Further analysis reveals that RNA-binding proteins (RBPs), heterogeneous nuclear ribonucleoproteins (hnRNPs) and FXR1 family proteins are predicted to induce the functional impairment of β-cells through regulating AS profiles. Finally, trajectory analysis of endocrine cells suggests the β-cell identity shift through dedifferentiation and transdifferentiation of β-cells during the progression of T2D. Together, our study provides a mechanism for regulating β-cell functions and suggests the significant contribution of AS program during diabetes pathogenesis.
Collapse
Affiliation(s)
- Jin Wang
- Department of Endocrinology & Metabolism, Medical Center for Comprehensive Weight Control, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
| | - Shiyi Wen
- Department of Endocrinology & Metabolism, Medical Center for Comprehensive Weight Control, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Minqi Chen
- Key Laboratory of Stem Cells and Tissue Engineering, Zhongshan School of Medicine, Sun Yat-sen University, Ministry of Education, Guangzhou, Guangdong, China
| | - Jiayi Xie
- Key Laboratory of Stem Cells and Tissue Engineering, Zhongshan School of Medicine, Sun Yat-sen University, Ministry of Education, Guangzhou, Guangdong, China
| | - Xinhua Lou
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Haihan Zhao
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yanming Chen
- Department of Endocrinology & Metabolism, Medical Center for Comprehensive Weight Control, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Meng Zhao
- Key Laboratory of Stem Cells and Tissue Engineering, Zhongshan School of Medicine, Sun Yat-sen University, Ministry of Education, Guangzhou, Guangdong, China.
| | - Guojun Shi
- Department of Endocrinology & Metabolism, Medical Center for Comprehensive Weight Control, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
- Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
- State Key Laboratory of Oncology in Southern China, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
| |
Collapse
|
3
|
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, Consortium HDAS, 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] [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 Ca 2+ -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.
Collapse
|
4
|
Unger Avila P, Padvitski T, Leote AC, Chen H, Saez-Rodriguez J, Kann M, Beyer A. Gene regulatory networks in disease and ageing. Nat Rev Nephrol 2024:10.1038/s41581-024-00849-7. [PMID: 38867109 DOI: 10.1038/s41581-024-00849-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/15/2024] [Indexed: 06/14/2024]
Abstract
The precise control of gene expression is required for the maintenance of cellular homeostasis and proper cellular function, and the declining control of gene expression with age is considered a major contributor to age-associated changes in cellular physiology and disease. The coordination of gene expression can be represented through models of the molecular interactions that govern gene expression levels, so-called gene regulatory networks. Gene regulatory networks can represent interactions that occur through signal transduction, those that involve regulatory transcription factors, or statistical models of gene-gene relationships based on the premise that certain sets of genes tend to be coexpressed across a range of conditions and cell types. Advances in experimental and computational technologies have enabled the inference of these networks on an unprecedented scale and at unprecedented precision. Here, we delineate different types of gene regulatory networks and their cell-biological interpretation. We describe methods for inferring such networks from large-scale, multi-omics datasets and present applications that have aided our understanding of cellular ageing and disease mechanisms.
Collapse
Affiliation(s)
- Paula Unger Avila
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Tsimafei Padvitski
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Ana Carolina Leote
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - He Chen
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Department II of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Julio Saez-Rodriguez
- Faculty of Medicine and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg University, Heidelberg, Germany
| | - Martin Kann
- Department II of Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Andreas Beyer
- Cluster of Excellence on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Cologne, Germany.
- Center for Molecular Medicine Cologne, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
- Institute for Genetics, Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany.
| |
Collapse
|
5
|
Hua H, Wang Y, Wang X, Wang S, Zhou Y, Liu Y, Liang Z, Ren H, Lu S, Wu S, Jiang Y, Pu Y, Zheng X, Tang C, Shen Z, Li C, Du Y, Deng H. Remodeling ceramide homeostasis promotes functional maturation of human pluripotent stem cell-derived β cells. Cell Stem Cell 2024; 31:850-865.e10. [PMID: 38697109 DOI: 10.1016/j.stem.2024.04.010] [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: 09/10/2023] [Revised: 03/21/2024] [Accepted: 04/12/2024] [Indexed: 05/04/2024]
Abstract
Human pluripotent stem cell-derived β cells (hPSC-β cells) show the potential to restore euglycemia. However, the immature functionality of hPSC-β cells has limited their efficacy in application. Here, by deciphering the continuous maturation process of hPSC-β cells post transplantation via single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), we show that functional maturation of hPSC-β cells is an orderly multistep process during which cells sequentially undergo metabolic adaption, removal of negative regulators of cell function, and establishment of a more specialized transcriptome and epigenome. Importantly, remodeling lipid metabolism, especially downregulating the metabolic activity of ceramides, the central hub of sphingolipid metabolism, is critical for β cell maturation. Limiting intracellular accumulation of ceramides in hPSC-β cells remarkably enhanced their function, as indicated by improvements in insulin processing and glucose-stimulated insulin secretion. In summary, our findings provide insights into the maturation of human pancreatic β cells and highlight the importance of ceramide homeostasis in function acquisition.
Collapse
Affiliation(s)
- Huijuan Hua
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yaqi Wang
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China
| | | | - Shusen Wang
- Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Yunlu Zhou
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yinan Liu
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Zhen Liang
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Huixia Ren
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Sufang Lu
- Hangzhou Reprogenix Bioscience, Hangzhou, China
| | | | - Yong Jiang
- Hangzhou Reprogenix Bioscience, Hangzhou, China
| | - Yue Pu
- Hangzhou Reprogenix Bioscience, Hangzhou, China
| | - Xiang Zheng
- Hangzhou Repugene Technology, Hangzhou, China
| | - Chao Tang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Zhongyang Shen
- Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Cheng Li
- School of Life Sciences, Center for Bioinformatics, Center for Statistical Science, Peking University, Beijing, China.
| | - Yuanyuan Du
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
| | - Hongkui Deng
- MOE Engineering Research Center of Regenerative Medicine, School of Basic Medical Sciences, State Key Laboratory of Natural and Biomimetic Drugs, Peking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and Differentiation, College of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; Changping Laboratory, Beijing, China.
| |
Collapse
|
6
|
Li T, Li S, Ma K, Kong J. Application potential of senolytics in clinical treatment. Biogerontology 2024; 25:379-398. [PMID: 38109001 DOI: 10.1007/s10522-023-10084-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/13/2023] [Indexed: 12/19/2023]
Abstract
Of the factors studied in individual ageing, the accumulation of senescent cells has been considered as an essential cause of organ degeneration to eventually initiate age-related diseases. Cellular senescence is attributed to the accumulation of damage for an inducement in the activation of cell cycle inhibitory pathways, resulting the cell permanently withdraw from the cell proliferation cycle. Further, senescent cells will activate the inflammatory factor secretion pathway to promote the development of various age-related diseases. Senolytics, a small molecule compound, can delay disease development and extend mammalian lifespan. The evidence from multiple trials shows that the targeted killing of senescent cells has a significant clinical application for the treatment of age-related diseases. In addition, senolytics are also significant for the development of ageing research in solid organ transplantation, which can fully develop the potential of elderly organs and reduce the age gap between demand and supply. We conclude that the main characteristics of cellular senescence, the anti-ageing drug senolytics in the treatment of chronic diseases and organ transplantation, and the latest clinical progress of related researches in order to provide a theoretical basis for the prevention and treatment of ageing and related diseases.
Collapse
Affiliation(s)
- Tiantian Li
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, People's Republic of China
| | - Shiyuan Li
- West China School of Pharmacy, Sichuan University, Chengdu, 610207, Sichuan, People's Republic of China
| | - Kefeng Ma
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, People's Republic of China.
| | - Jinming Kong
- School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu, People's Republic of China.
| |
Collapse
|
7
|
Mathisen AF, Legøy TA, Larsen U, Unger L, Abadpour S, Paulo JA, Scholz H, Ghila L, Chera S. The age-dependent regulation of pancreatic islet landscape is fueled by a HNF1a-immune signaling loop. Mech Ageing Dev 2024; 220:111951. [PMID: 38825059 DOI: 10.1016/j.mad.2024.111951] [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: 01/09/2024] [Revised: 04/30/2024] [Accepted: 05/21/2024] [Indexed: 06/04/2024]
Abstract
Animal longevity is a function of global vital organ functionality and, consequently, a complex polygenic trait. Yet, monogenic regulators controlling overall or organ-specific ageing exist, owing their conservation to their function in growth and development. Here, by using pathway analysis combined with wet-biology methods on several dynamic timelines, we identified Hnf1a as a novel master regulator of the maturation and ageing in the adult pancreatic islet during the first year of life. Conditional transgenic mice bearing suboptimal levels of this transcription factor in the pancreatic islets displayed age-dependent changes, with a profile echoing precocious maturation. Additionally, the comparative pathway analysis revealed a link between Hnf1a age-dependent regulation and immune signaling, which was confirmed in the ageing timeline of an overly immunodeficient mouse model. Last, the global proteome analysis of human islets spanning three decades of life largely backed the age-specific regulation observed in mice. Collectively, our results suggest a novel role of Hnf1a as a monogenic regulator of the maturation and ageing process in the pancreatic islet via a direct or indirect regulatory loop with immune signaling.
Collapse
Affiliation(s)
- Andreas Frøslev Mathisen
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Thomas Aga Legøy
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ulrik Larsen
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Lucas Unger
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Shadab Abadpour
- Hybrid Technology Hub-Centre of Excellence, Faculty of Medicine, University of Oslo, Norway; Institute for Surgical Research, Department of Transplant Medicine, Oslo University Hospital, Oslo, Norway
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Hanne Scholz
- Hybrid Technology Hub-Centre of Excellence, Faculty of Medicine, University of Oslo, Norway; Institute for Surgical Research, Department of Transplant Medicine, Oslo University Hospital, Oslo, Norway
| | - Luiza Ghila
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Simona Chera
- Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, University of Bergen, Bergen, Norway.
| |
Collapse
|
8
|
Chu LX, Wang WJ, Gu XP, Wu P, Gao C, Zhang Q, Wu J, Jiang DW, Huang JQ, Ying XW, Shen JM, Jiang Y, Luo LH, Xu JP, Ying YB, Chen HM, Fang A, Feng ZY, An SH, Li XK, Wang ZG. Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine. Mil Med Res 2024; 11:31. [PMID: 38797843 PMCID: PMC11129507 DOI: 10.1186/s40779-024-00537-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 05/07/2024] [Indexed: 05/29/2024] Open
Abstract
Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.
Collapse
Affiliation(s)
- Liu-Xi Chu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Wen-Jia Wang
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Xin-Pei Gu
- School of Pharmaceutical Sciences, Guangdong Provincial Key Laboratory of New Drug Screening, Southern Medical University, Guangzhou, 510515, China
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China
| | - Ping Wu
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Chen Gao
- State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Quan Zhang
- Integrative Muscle Biology Laboratory, Division of Regenerative and Rehabilitative Sciences, University of Tennessee Health Science Center, Memphis, TN, 38163, United States
| | - Jia Wu
- Key Laboratory for Laboratory Medicine, Ministry of Education, Zhejiang Provincial Key Laboratory of Medical Genetics, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Da-Wei Jiang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jun-Qing Huang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China
| | - Xin-Wang Ying
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Jia-Men Shen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi Jiang
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Li-Hua Luo
- School and Hospital of Stomatology, Wenzhou Medical University, Wenzhou, 324025, Zhejiang, China
| | - Jun-Peng Xu
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Yi-Bo Ying
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Hao-Man Chen
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Ao Fang
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China
| | - Zun-Yong Feng
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Departments of Diagnostic Radiology, Surgery, Chemical and Biomolecular Engineering, and Biomedical Engineering, Yong Loo Lin School of Medicine and College of Design and Engineering, National University of Singapore, Singapore, 119074, Singapore.
- Clinical Imaging Research Centre, Centre for Translational Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117599, Singapore.
- Nanomedicine Translational Research Program, NUS Center for Nanomedicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117597, Singapore.
- Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research (A*STAR), Singapore, 138673, Singapore.
| | - Shu-Hong An
- Department of Human Anatomy, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China.
| | - Xiao-Kun Li
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
| | - Zhou-Guang Wang
- Affiliated Cixi Hospital, Wenzhou Medical University, Ningbo, 315300, Zhejiang, China.
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- National Key Laboratory of Macromolecular Drug Development and Manufacturing, School of Pharmaceutical Science, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui Hospital of Zhejiang University, Lishui, 323000, Zhejiang, China.
| |
Collapse
|
9
|
Guo Q, Yuan M, Zhang L, Deng M. scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement. Brief Bioinform 2024; 25:bbae305. [PMID: 38935069 PMCID: PMC11209730 DOI: 10.1093/bib/bbae305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/22/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
MOTIVATION In the past decade, single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal method for transcriptomic profiling in biomedical research. Precise cell-type identification is crucial for subsequent analysis of single-cell data. And the integration and refinement of annotated data are essential for building comprehensive databases. However, prevailing annotation techniques often overlook the hierarchical organization of cell types, resulting in inconsistent annotations. Meanwhile, most existing integration approaches fail to integrate datasets with different annotation depths and none of them can enhance the labels of outdated data with lower annotation resolutions using more intricately annotated datasets or novel biological findings. RESULTS Here, we introduce scPLAN, a hierarchical computational framework designed for scRNA-seq data analysis. scPLAN excels in annotating unlabeled scRNA-seq data using a reference dataset structured along a hierarchical cell-type tree. It identifies potential novel cell types in a systematic, layer-by-layer manner. Additionally, scPLAN effectively integrates annotated scRNA-seq datasets with varying levels of annotation depth, ensuring consistent refinement of cell-type labels across datasets with lower resolutions. Through extensive annotation and novel cell detection experiments, scPLAN has demonstrated its efficacy. Two case studies have been conducted to showcase how scPLAN integrates datasets with diverse cell-type label resolutions and refine their cell-type labels. AVAILABILITY https://github.com/michaelGuo1204/scPLAN.
Collapse
Affiliation(s)
- Qirui Guo
- Center for Quantitative Biology, Peking University, Yiheyuan Road, 100871, Beijing, China
| | - Musu Yuan
- Center for Quantitative Biology, Peking University, Yiheyuan Road, 100871, Beijing, China
| | - Lei Zhang
- Center for Quantitative Biology, Peking University, Yiheyuan Road, 100871, Beijing, China
- Beijing International Center for Mathematical Research, Peking University, Yiheyuan Road, 100871, Beijing, China
- Center for Machine Learning Research, Peking University, Yiheyuan Road, 100871, Beijing, China
| | - Minghua Deng
- Center for Quantitative Biology, Peking University, Yiheyuan Road, 100871, Beijing, China
- School of Mathematical Sciences, Peking University, Yiheyuan Road, 100871, Beijing, China
- Center for Statistical Science, Peking University, Yiheyuan Road, 100871, Beijing, China
| |
Collapse
|
10
|
Vendramini-Costa DB, Francescone R, Franco-Barraza J, Luong T, Graves M, de Aquino AM, Steele N, Gardiner JC, Dos Santos SAA, Ogier C, Malloy E, Borghaei L, Martinez E, Zhigarev DI, Tan Y, Lee H, Zhou Y, Cai KQ, Klein-Szanto AJ, Wang H, Andrake M, Dunbrack RL, Campbell K, Cukierman E. Netrin G1 Ligand is a new stromal immunomodulator that promotes pancreatic cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.15.594354. [PMID: 38798370 PMCID: PMC11118300 DOI: 10.1101/2024.05.15.594354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Understanding pancreatic cancer biology is fundamental for identifying new targets and for developing more effective therapies. In particular, the contribution of the stromal microenvironment to pancreatic cancer tumorigenesis requires further exploration. Here, we report the stromal roles of the synaptic protein Netrin G1 Ligand (NGL-1) in pancreatic cancer, uncovering its pro-tumor functions in cancer-associated fibroblasts and in immune cells. We observed that the stromal expression of NGL-1 inversely correlated with patients' overall survival. Moreover, germline knockout (KO) mice for NGL-1 presented decreased tumor burden, with a microenvironment that is less supportive of tumor growth. Of note, tumors from NGL-1 KO mice produced less immunosuppressive cytokines and displayed an increased percentage of CD8 + T cells than those from control mice, while preserving the physical structure of the tumor microenvironment. These effects were shown to be mediated by NGL-1 in both immune cells and in the local stroma, in a TGF-β-dependent manner. While myeloid cells lacking NGL-1 decreased the production of immunosuppressive cytokines, NGL-1 KO T cells showed increased proliferation rates and overall polyfunctionality compared to control T cells. CAFs lacking NGL-1 were less immunosuppressive than controls, with overall decreased production of pro-tumor cytokines and compromised ability to inhibit CD8 + T cells activation. Mechanistically, these CAFs downregulated components of the TGF-β pathway, AP-1 and NFAT transcription factor families, resulting in a less tumor-supportive phenotype. Finally, targeting NGL-1 genetically or using a functionally antagonistic small peptide phenocopied the effects of chemotherapy, while modulating the immunosuppressive tumor microenvironment (TME), rather than eliminating it. We propose NGL-1 as a new local stroma and immunomodulatory molecule, with pro-tumor roles in pancreatic cancer. Statement of Significance Here we uncovered the pro-tumor roles of the synaptic protein NGL-1 in the tumor microenvironment of pancreatic cancer, defining a new target that simultaneously modulates tumor cell, fibroblast, and immune cell functions. This study reports a new pathway where NGL-1 controls TGF-β, AP-1 transcription factor members and NFAT1, modulating the immunosuppressive microenvironment in pancreatic cancer. Our findings highlight NGL-1 as a new stromal immunomodulator in pancreatic cancer.
Collapse
|
11
|
Kedlian VR, Wang Y, Liu T, Chen X, Bolt L, Tudor C, Shen Z, Fasouli ES, Prigmore E, Kleshchevnikov V, Pett JP, Li T, Lawrence JEG, Perera S, Prete M, Huang N, Guo Q, Zeng X, Yang L, Polański K, Chipampe NJ, Dabrowska M, Li X, Bayraktar OA, Patel M, Kumasaka N, Mahbubani KT, Xiang AP, Meyer KB, Saeb-Parsy K, Teichmann SA, Zhang H. Human skeletal muscle aging atlas. NATURE AGING 2024; 4:727-744. [PMID: 38622407 PMCID: PMC11108788 DOI: 10.1038/s43587-024-00613-3] [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: 11/20/2023] [Accepted: 03/19/2024] [Indexed: 04/17/2024]
Abstract
Skeletal muscle aging is a key contributor to age-related frailty and sarcopenia with substantial implications for global health. Here we profiled 90,902 single cells and 92,259 single nuclei from 17 donors to map the aging process in the adult human intercostal muscle, identifying cellular changes in each muscle compartment. We found that distinct subsets of muscle stem cells exhibit decreased ribosome biogenesis genes and increased CCL2 expression, causing different aging phenotypes. Our atlas also highlights an expansion of nuclei associated with the neuromuscular junction, which may reflect re-innervation, and outlines how the loss of fast-twitch myofibers is mitigated through regeneration and upregulation of fast-type markers in slow-twitch myofibers with age. Furthermore, we document the function of aging muscle microenvironment in immune cell attraction. Overall, we present a comprehensive human skeletal muscle aging resource ( https://www.muscleageingcellatlas.org/ ) together with an in-house mouse muscle atlas to study common features of muscle aging across species.
Collapse
Affiliation(s)
- Veronika R Kedlian
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Tianliang Liu
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xiaoping Chen
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Liam Bolt
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Catherine Tudor
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Zhuojian Shen
- Department of Thoracic Surgery, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China
| | - Eirini S Fasouli
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Elena Prigmore
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | | | - Jan Patrick Pett
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Tong Li
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - John E G Lawrence
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Shani Perera
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Martin Prete
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Ni Huang
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Qin Guo
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xinrui Zeng
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Lu Yang
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Krzysztof Polański
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Nana-Jane Chipampe
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Monika Dabrowska
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Xiaobo Li
- Core Facilities for Medical Science, Sun Yat-sen University, Guangzhou, China
| | - Omer Ali Bayraktar
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Minal Patel
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Natsuhiko Kumasaka
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Krishnaa T Mahbubani
- Department of Surgery, University of Cambridge, Cambridge, UK
- Collaborative Biorepository for Translational Medicine (CBTM), NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - Andy Peng Xiang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Kerstin B Meyer
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Kourosh Saeb-Parsy
- Department of Surgery, University of Cambridge, Cambridge, UK.
- Collaborative Biorepository for Translational Medicine (CBTM), NIHR Cambridge Biomedical Research Centre, Cambridge, UK.
| | - Sarah A Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
- Cavendish Laboratory, University of Cambridge, Cambridge, UK.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
| |
Collapse
|
12
|
Xie G, Toledo MP, Hu X, Yong HJ, Sanchez PS, Liu C, Naji A, Irianto J, Wang YJ. NKX2-2 based nuclei sorting on frozen human archival pancreas enables the enrichment of islet endocrine populations for single-nucleus RNA sequencing. BMC Genomics 2024; 25:427. [PMID: 38689254 PMCID: PMC11059690 DOI: 10.1186/s12864-024-10335-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 04/22/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Current approaches to profile the single-cell transcriptomics of human pancreatic endocrine cells almost exclusively rely on freshly isolated islets. However, human islets are limited in availability. Furthermore, the extensive processing steps during islet isolation and subsequent single cell dissolution might alter gene expressions. In this work, we report the development of a single-nucleus RNA sequencing (snRNA-seq) approach with targeted islet cell enrichment for endocrine-population focused transcriptomic profiling using frozen archival pancreatic tissues without islet isolation. RESULTS We cross-compared five nuclei isolation protocols and selected the citric acid method as the best strategy to isolate nuclei with high RNA integrity and low cytoplasmic contamination from frozen archival human pancreata. We innovated fluorescence-activated nuclei sorting based on the positive signal of NKX2-2 antibody to enrich nuclei of the endocrine population from the entire nuclei pool of the pancreas. Our sample preparation procedure generated high-quality single-nucleus gene-expression libraries while preserving the endocrine population diversity. In comparison with single-cell RNA sequencing (scRNA-seq) library generated with live cells from freshly isolated human islets, the snRNA-seq library displayed comparable endocrine cellular composition and cell type signature gene expression. However, between these two types of libraries, differential enrichments of transcripts belonging to different functional classes could be observed. CONCLUSIONS Our work fills a technological gap and helps to unleash frozen archival pancreatic tissues for molecular profiling targeting the endocrine population. This study opens doors to retrospective mappings of endocrine cell dynamics in pancreatic tissues of complex histopathology. We expect that our protocol is applicable to enrich nuclei for transcriptomics studies from various populations in different types of frozen archival tissues.
Collapse
Affiliation(s)
- Gengqiang Xie
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Maria Pilar Toledo
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Xue Hu
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Hyo Jeong Yong
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Pamela Sandoval Sanchez
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Chengyang Liu
- Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Naji
- Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Jerome Irianto
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA
| | - Yue J Wang
- Department of Biomedical Sciences, College of Medicine, Florida State University, 1115 West Call Street, Tallahassee, FL, 32306, USA.
| |
Collapse
|
13
|
Cuozzo F, Viloria K, Shilleh AH, Nasteska D, Frazer-Morris C, Tong J, Jiao Z, Boufersaoui A, Marzullo B, Rosoff DB, Smith HR, Bonner C, Kerr-Conte J, Pattou F, Nano R, Piemonti L, Johnson PRV, Spiers R, Roberts J, Lavery GG, Clark A, Ceresa CDL, Ray DW, Hodson L, Davies AP, Rutter GA, Oshima M, Scharfmann R, Merrins MJ, Akerman I, Tennant DA, Ludwig C, Hodson DJ. LDHB contributes to the regulation of lactate levels and basal insulin secretion in human pancreatic β cells. Cell Rep 2024; 43:114047. [PMID: 38607916 PMCID: PMC11164428 DOI: 10.1016/j.celrep.2024.114047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 02/19/2024] [Accepted: 03/19/2024] [Indexed: 04/14/2024] Open
Abstract
Using 13C6 glucose labeling coupled to gas chromatography-mass spectrometry and 2D 1H-13C heteronuclear single quantum coherence NMR spectroscopy, we have obtained a comparative high-resolution map of glucose fate underpinning β cell function. In both mouse and human islets, the contribution of glucose to the tricarboxylic acid (TCA) cycle is similar. Pyruvate fueling of the TCA cycle is primarily mediated by the activity of pyruvate dehydrogenase, with lower flux through pyruvate carboxylase. While the conversion of pyruvate to lactate by lactate dehydrogenase (LDH) can be detected in islets of both species, lactate accumulation is 6-fold higher in human islets. Human islets express LDH, with low-moderate LDHA expression and β cell-specific LDHB expression. LDHB inhibition amplifies LDHA-dependent lactate generation in mouse and human β cells and increases basal insulin release. Lastly, cis-instrument Mendelian randomization shows that low LDHB expression levels correlate with elevated fasting insulin in humans. Thus, LDHB limits lactate generation in β cells to maintain appropriate insulin release.
Collapse
Affiliation(s)
- Federica Cuozzo
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Katrina Viloria
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Ali H Shilleh
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Daniela Nasteska
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Charlotte Frazer-Morris
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jason Tong
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Zicong Jiao
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Geneplus-Beijing, Changping District, Beijing 102206, China
| | - Adam Boufersaoui
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Bryan Marzullo
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Daniel B Rosoff
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Oxford Kavli Centre for Nanoscience Discovery, University of Oxford, Oxford, UK
| | - Hannah R Smith
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Caroline Bonner
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000 Lille, France
| | - Julie Kerr-Conte
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000 Lille, France
| | - Francois Pattou
- University of Lille, Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Lille (CHU Lille), Institute Pasteur Lille, U1190 -European Genomic Institute for Diabetes (EGID), F59000 Lille, France
| | - Rita Nano
- San Raffaele Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Lorenzo Piemonti
- San Raffaele Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Paul R V Johnson
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Rebecca Spiers
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Jennie Roberts
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Gareth G Lavery
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Centre for Systems Health and Integrated Metabolic Research (SHiMR), Department of Biosciences, School of Science and Technology, Nottingham Trent University, Nottingham, UK
| | - Anne Clark
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Carlo D L Ceresa
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - David W Ray
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK; Oxford Kavli Centre for Nanoscience Discovery, University of Oxford, Oxford, UK
| | - Leanne Hodson
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Amy P Davies
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Guy A Rutter
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK; CHUM Research Centre and Faculty of Medicine, University of Montreal, Montreal, QC, Canada; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Masaya Oshima
- Université Paris Cité, Institut Cochin, INSERM U1016, CNRS UMR 8104, 75014 Paris, France
| | - Raphaël Scharfmann
- Université Paris Cité, Institut Cochin, INSERM U1016, CNRS UMR 8104, 75014 Paris, France
| | - Matthew J Merrins
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, WI 53705, USA; William S. Middleton Memorial Veterans Hospital, Madison, WI 53705, USA
| | - Ildem Akerman
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK
| | - Daniel A Tennant
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK.
| | - Christian Ludwig
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK.
| | - David J Hodson
- Institute of Metabolism and Systems Research (IMSR) and Centre of Membrane Proteins and Receptors (COMPARE), University of Birmingham, Birmingham, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), NIHR Oxford Biomedical Research Centre, Churchill Hospital, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
| |
Collapse
|
14
|
Pina C. Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230052. [PMID: 38432321 PMCID: PMC10909511 DOI: 10.1098/rstb.2023.0052] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 12/04/2023] [Indexed: 03/05/2024] Open
Abstract
Transcriptional noise is proposed to participate in cell fate changes, but contributions to mammalian cell differentiation systems, including cancer, remain associative. Cancer evolution is driven by genetic variability, with modulatory or contributory participation of epigenetic variants. Accumulation of epigenetic variants enhances transcriptional noise, which can facilitate cancer cell fate transitions. Acute myeloid leukaemia (AML) is an aggressive cancer with strong epigenetic dependencies, characterized by blocked differentiation. It constitutes an attractive model to probe links between transcriptional noise and malignant cell fate regulation. Gcn5/KAT2A is a classical epigenetic transcriptional noise regulator. Its loss increases transcriptional noise and modifies cell fates in stem and AML cells. By reviewing the analysis of KAT2A-depleted pre-leukaemia and leukaemia models, I discuss that the net result of transcriptional noise is diversification of cell fates secondary to alternative transcriptional programmes. Cellular diversification can enable or hinder AML progression, respectively, by differentiation of cell types responsive to mutations, or by maladaptation of leukaemia stem cells. KAT2A-dependent noise-responsive genes participate in ribosome biogenesis and KAT2A loss destabilizes translational activity. I discuss putative contributions of perturbed translation to AML biology, and propose KAT2A loss as a model for mechanistic integration of transcriptional and translational control of noise and fate decisions. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
Collapse
Affiliation(s)
- Cristina Pina
- College of Health, Medicine and Life Sciences, Brunel University London, Kingston Lane, Uxbridge, London, UB8 3PH, United Kingdom
- CenGEM – Centre for Genome Engineering and Maintenance, Brunel University London, Kingston Lane, Uxbridge, London, UB8 3PH, United Kingdom
| |
Collapse
|
15
|
Jia H, Chang Y, Chen Y, Chen X, Zhang H, Hua X, Xu M, Sheng Y, Zhang N, Cui H, Han L, Zhang J, Fu X, Song J. A single-cell atlas of lung homeostasis reveals dynamic changes during development and aging. Commun Biol 2024; 7:427. [PMID: 38589700 PMCID: PMC11001898 DOI: 10.1038/s42003-024-06111-x] [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: 08/08/2023] [Accepted: 03/26/2024] [Indexed: 04/10/2024] Open
Abstract
Aging is a global challenge, marked in the lungs by function decline and structural disorders, which affects the health of the elderly population. To explore anti-aging strategies, we develop a dynamic atlas covering 45 cell types in human lungs, spanning from embryonic development to aging. We aim to apply the discoveries of lung's development to address aging-related issues. We observe that both epithelial and immune cells undergo a process of acquisition and loss of essential function as they transition from development to aging. During aging, we identify cellular phenotypic alternations that result in reduced pulmonary compliance and compromised immune homeostasis. Furthermore, we find a distinctive expression pattern of the ferritin light chain (FTL) gene, which increases during development but decreases in various types of lung cells during the aging process.
Collapse
Affiliation(s)
- Hao Jia
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuan Chang
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yulin Chen
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of Traditional Chinese and Western Medicine, Gansu University of Chinese Medicine, Lanzhou, China
| | - Xiao Chen
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hang Zhang
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiumeng Hua
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mengda Xu
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yixuan Sheng
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ningning Zhang
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hao Cui
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lei Han
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Department of General Surgery, Yanan Hospital, Kunming Medical University, Kunming, China
| | - Jian Zhang
- Thoracic Surgery Department, the third affiliated hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.
| | - Xiaodong Fu
- Department of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
| | - Jiangping Song
- Beijing Key Laboratory of Preclinical Research and Evaluation for Cardiovascular Implant Materials, Animal Experimental Centre, National Centre for Cardiovascular Disease, Department of Cardiac Surgery, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| |
Collapse
|
16
|
Yin K, Büttner M, Deligiannis IK, Strzelecki M, Zhang L, Talavera-López C, Theis F, Odom DT, Martinez-Jimenez CP. Polyploidisation pleiotropically buffers ageing in hepatocytes. J Hepatol 2024:S0168-8278(24)00227-7. [PMID: 38583492 DOI: 10.1016/j.jhep.2024.03.043] [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: 05/05/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/09/2024]
Abstract
BACKGROUND & AIMS Polyploidy in hepatocytes has been proposed as a genetic mechanism to buffer against transcriptional dysregulation. Here, we aim to demonstrate the role of polyploidy in modulating gene regulatory networks in hepatocytes during ageing. METHODS We performed single-nucleus RNA sequencing in hepatocyte nuclei of different ploidy levels isolated from young and old wild-type mice. Changes in the gene expression and regulatory network were compared to three independent strains that were haploinsufficient for HNF4A, CEBPA or CTCF, representing non-deleterious perturbations. Phenotypic characteristics of the liver section were additionally evaluated histologically, whereas the genomic allele composition of hepatocytes was analysed by BaseScope. RESULTS We observed that ageing in wild-type mice results in nuclei polyploidy and a marked increase in steatosis. Haploinsufficiency of liver-specific master regulators (HFN4A or CEBPA) results in the enrichment of hepatocytes with tetraploid nuclei at a young age, affecting the genomic regulatory network, and dramatically suppressing ageing-related steatosis tissue wide. Notably, these phenotypes are not the result of subtle disruption to liver-specific transcriptional networks, since haploinsufficiency in the CTCF insulator protein resulted in the same phenotype. Further quantification of genotypes of tetraploid hepatocytes in young and old HFN4A-haploinsufficient mice revealed that during ageing, tetraploid hepatocytes lead to the selection of wild-type alleles, restoring non-deleterious genetic perturbations. CONCLUSIONS Our results suggest a model whereby polyploidisation leads to fundamentally different cell states. Polyploid conversion enables pleiotropic buffering against age-related decline via non-random allelic segregation to restore a wild-type genome. IMPACT AND IMPLICATIONS The functional role of hepatocyte polyploidisation during ageing is poorly understood. Using single-nucleus RNA sequencing and BaseScope approaches, we have studied ploidy dynamics during ageing in murine livers with non-deleterious genetic perturbations. We have identified that hepatocytes present different cellular states and the ability to buffer ageing-associated dysfunctions. Tetraploid nuclei exhibit robust transcriptional networks and are better adapted to genomically overcome perturbations. Novel therapeutic interventions aimed at attenuating age-related changes in tissue function could be exploited by manipulation of ploidy dynamics during chronic liver conditions.
Collapse
Affiliation(s)
- Kelvin Yin
- Helmholtz Pioneer Campus (HPC), Helmholtz Munich, Neuherberg, Germany
| | - Maren Büttner
- Institute of Computational Biology, Computational Health Department, Helmholtz Munich, Neuherberg, Germany
| | | | | | - Liwei Zhang
- Helmholtz Pioneer Campus (HPC), Helmholtz Munich, Neuherberg, Germany
| | - Carlos Talavera-López
- Division of Infectious Diseases and Tropical Medicine, Ludwig-Maximilian-Universität Klinikum, Germany
| | - Fabian Theis
- Institute of Computational Biology, Computational Health Department, Helmholtz Munich, Neuherberg, Germany; Technical University of Munich, Department of Mathematics, 85748 Garching. Munich, Germany; German Cancer Research Centre, Heidelberg, Germany.
| | - Duncan T Odom
- German Cancer Research Center, Division of Regulatory Genomics and Cancer Evolution (B270), Heidelberg, Germany; Cancer Research UK Cambridge Institute, University of Cambridge, CB20RE, United Kingdom.
| | - Celia P Martinez-Jimenez
- Helmholtz Pioneer Campus (HPC), Helmholtz Munich, Neuherberg, Germany; TUM School of Medicine, Technical University of Munich, Munich, Germany; Institute of Biotechnology and Biomedicine (BIOTECMED), Department of Biochemistry and Molecular Biology, University of Valencia, Burjassot, Spain.
| |
Collapse
|
17
|
Wang HT, Xiao FH, Gao ZL, Guo LY, Yang LQ, Li GH, Kong QP. Methylation entropy landscape of Chinese long-lived individuals reveals lower epigenetic noise related to human healthy aging. Aging Cell 2024:e14163. [PMID: 38566438 DOI: 10.1111/acel.14163] [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: 12/15/2023] [Revised: 03/12/2024] [Accepted: 03/15/2024] [Indexed: 04/04/2024] Open
Abstract
The transition from ordered to noisy is a significant epigenetic signature of aging and age-related disease. As a paradigm of healthy human aging and longevity, long-lived individuals (LLI, >90 years old) may possess characteristic strategies in coping with the disordered epigenetic regulation. In this study, we constructed high-resolution blood epigenetic noise landscapes for this cohort by a methylation entropy (ME) method using whole genome bisulfite sequencing (WGBS). Although a universal increase in global ME occurred with chronological age in general control samples, this trend was suppressed in LLIs. Importantly, we identified 38,923 genomic regions with LLI-specific lower ME (LLI-specific lower entropy regions, for short, LLI-specific LERs). These regions were overrepresented in promoters, which likely function in transcriptional noise suppression. Genes associated with LLI-specific LERs have a considerable impact on SNP-based heritability of some aging-related disorders (e.g., asthma and stroke). Furthermore, neutrophil was identified as the primary cell type sustaining LLI-specific LERs. Our results highlight the stability of epigenetic order in promoters of genes involved with aging and age-related disorders within LLI epigenomes. This unique epigenetic feature reveals a previously unknown role of epigenetic order maintenance in specific genomic regions of LLIs, which helps open a new avenue on the epigenetic regulation mechanism in human healthy aging and longevity.
Collapse
Affiliation(s)
- Hao-Tian Wang
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Fu-Hui Xiao
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zong-Liang Gao
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Li-Yun Guo
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Li-Qin Yang
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Gong-Hua Li
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Qing-Peng Kong
- Key Laboratory of Genetic Evolution & Animal Models (Chinese Academy of Sciences), Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| |
Collapse
|
18
|
Chatsirisupachai K, de Magalhães JP. Somatic mutations in human ageing: New insights from DNA sequencing and inherited mutations. Ageing Res Rev 2024; 96:102268. [PMID: 38490496 DOI: 10.1016/j.arr.2024.102268] [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: 08/23/2023] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 03/17/2024]
Abstract
The accumulation of somatic mutations is a driver of cancer and has long been associated with ageing. Due to limitations in quantifying mutation burden with age in non-cancerous tissues, the impact of somatic mutations in other ageing phenotypes is unclear. Recent advances in DNA sequencing technologies have allowed the large-scale quantification of somatic mutations in ageing tissues. These studies have revealed a gradual accumulation of mutations in normal tissues with age as well as a substantial clonal expansion driven mostly by cancer-related mutations. Nevertheless, it is difficult to envision how the burden and stochastic nature of age-related somatic mutations identified so far can explain most ageing phenotypes that develop gradually. Studies across species have also found that longer-lived species have lower somatic mutation rates, though these could be due to selective pressures acting on other phenotypes such as perhaps cancer. Recent studies in patients with higher somatic mutation burden and no signs of accelerated ageing further question the role of somatic mutations in ageing. Overall, with a few exceptions like cancer, recent DNA sequencing studies and inherited mutations do not support the idea that somatic mutations accumulating with age drive ageing phenotypes, and the phenotypic role, if any, of somatic mutations in ageing remains unclear.
Collapse
Affiliation(s)
- Kasit Chatsirisupachai
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK; European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - João Pedro de Magalhães
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK; Institute of Inflammation and Ageing, University of Birmingham, Queen Elizabeth Hospital, Mindelsohn Way, Birmingham, UK.
| |
Collapse
|
19
|
Huang W, O'Hara SE, Xie C, Liu N, Rayner CK, Nicholas LM, Wu T. Effects of a bitter substance, denatonium benzoate, on pancreatic hormone secretion. Am J Physiol Endocrinol Metab 2024; 326:E537-E544. [PMID: 38477876 DOI: 10.1152/ajpendo.00046.2024] [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: 01/24/2024] [Revised: 03/06/2024] [Accepted: 03/06/2024] [Indexed: 03/14/2024]
Abstract
There is increasing evidence linking bitter taste receptor (BTR) signaling to gut hormone secretion and glucose homeostasis. However, its effect on islet hormone secretion has been poorly characterized. This study investigated the effect of the bitter substance, denatonium benzoate (DB), on hormone secretion from mouse pancreatic islets and INS-1 832/13 cells. DB (0.5-1 mM) augmented insulin secretion at both 2.8 mM and 16.7 mM glucose. This effect was no longer present at 5 mM DB likely due to the greater levels of cellular apoptosis. DB-stimulated insulin secretion involved closure of the KATP channel, activation of T2R signaling in beta-cells, and intraislet glucagon-like peptide-1 (GLP-1) release. DB also enhanced glucagon and somatostatin secretion, but the underlying mechanism was less clear. Together, this study demonstrates that the bitter substance, DB, is a strong potentiator of islet hormone secretion independent of glucose. This observation highlights the potential for widespread off-target effects associated with the clinical use of bitter-tasting substances.NEW & NOTEWORTHY We show that the bitter substance, denatonium benzoate (DB), stimulates insulin, glucagon, somatostatin, and GLP-1 secretion from pancreatic islets, independent of glucose, and that DB augments insulin release via the KATP channel, bitter taste receptor signaling, and intraislet GLP-1 secretion. Exposure to a high dose of DB (5 mM) induces cellular apoptosis in pancreatic islets. Therefore, clinical use of bitter substances to improve glucose homeostasis may have unintended negative impacts beyond the gut.
Collapse
Affiliation(s)
- Weikun Huang
- Centre for Research Excellence in Translating Nutritional Sciences to Good Health, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
- Institute for Photonics and Advanced Sensing, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Stephanie E O'Hara
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- Adelaide Centre for Epigenetics, School of Biomedicine, The University of Adelaide, Adelaide, South Australia, Australia
| | - Cong Xie
- Centre for Research Excellence in Translating Nutritional Sciences to Good Health, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
| | - Ning Liu
- Bioinformatics Division, The Walter and Eliza Hall Institute, Melbourne, Victoria, Australia
| | - Christopher K Rayner
- Centre for Research Excellence in Translating Nutritional Sciences to Good Health, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
| | - Lisa M Nicholas
- Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia
- Adelaide Centre for Epigenetics, School of Biomedicine, The University of Adelaide, Adelaide, South Australia, Australia
| | - Tongzhi Wu
- Centre for Research Excellence in Translating Nutritional Sciences to Good Health, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
| |
Collapse
|
20
|
Ren P, Zhang J, Vijg J. Somatic mutations in aging and disease. GeroScience 2024:10.1007/s11357-024-01113-3. [PMID: 38488948 DOI: 10.1007/s11357-024-01113-3] [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: 10/11/2023] [Accepted: 02/27/2024] [Indexed: 03/17/2024] Open
Abstract
Time always leaves its mark, and our genome is no exception. Mutations in the genome of somatic cells were first hypothesized to be the cause of aging in the 1950s, shortly after the molecular structure of DNA had been described. Somatic mutation theories of aging are based on the fact that mutations in DNA as the ultimate template for all cellular functions are irreversible. However, it took until the 1990s to develop the methods to test if DNA mutations accumulate with age in different organs and tissues and estimate the severity of the problem. By now, numerous studies have documented the accumulation of somatic mutations with age in normal cells and tissues of mice, humans, and other animals, showing clock-like mutational signatures that provide information on the underlying causes of the mutations. In this review, we will first briefly discuss the recent advances in next-generation sequencing that now allow quantitative analysis of somatic mutations. Second, we will provide evidence that the mutation rate differs between cell types, with a focus on differences between germline and somatic mutation rate. Third, we will discuss somatic mutational signatures as measures of aging, environmental exposure, and activities of DNA repair processes. Fourth, we will explain the concept of clonally amplified somatic mutations, with a focus on clonal hematopoiesis. Fifth, we will briefly discuss somatic mutations in the transcriptome and in our other genome, i.e., the genome of mitochondria. We will end with a brief discussion of a possible causal contribution of somatic mutations to the aging process.
Collapse
Affiliation(s)
- Peijun Ren
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Jie Zhang
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jan Vijg
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
| |
Collapse
|
21
|
Peng M, Lin B, Zhang J, Zhou Y, Lin B. scFSNN: a feature selection method based on neural network for single-cell RNA-seq data. BMC Genomics 2024; 25:264. [PMID: 38459442 PMCID: PMC10924397 DOI: 10.1186/s12864-024-10160-1] [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: 07/26/2023] [Accepted: 02/25/2024] [Indexed: 03/10/2024] Open
Abstract
While single-cell RNA sequencing (scRNA-seq) allows researchers to analyze gene expression in individual cells, its unique characteristics like over-dispersion, zero-inflation, high gene-gene correlation, and large data volume with many features pose challenges for most existing feature selection methods. In this paper, we present a feature selection method based on neural network (scFSNN) to solve classification problem for the scRNA-seq data. scFSNN is an embedded method that can automatically select features (genes) during model training, control the false discovery rate of selected features and adaptively determine the number of features to be eliminated. Extensive simulation and real data studies demonstrate its excellent feature selection ability and predictive performance.
Collapse
Affiliation(s)
- Minjiao Peng
- School of Mathematical Sciences, Shenzhen University, Nanshan, Shenzhen, 518060, Guangdong, China
- School of Mathematics and Statistics and KLAS, Northeast Normal University, Renmin Street, Changchun, 130000, Jilin, China
| | - Baoqin Lin
- Experimental Center, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510405, China
| | - Jun Zhang
- School of Mathematical Sciences, Shenzhen University, Nanshan, Shenzhen, 518060, Guangdong, China
| | - Yan Zhou
- School of Mathematical Sciences, Shenzhen University, Nanshan, Shenzhen, 518060, Guangdong, China
| | - Bingqing Lin
- School of Mathematical Sciences, Shenzhen University, Nanshan, Shenzhen, 518060, Guangdong, China.
| |
Collapse
|
22
|
Oropeza D, Herrera PL. Glucagon-producing α-cell transcriptional identity and reprogramming towards insulin production. Trends Cell Biol 2024; 34:180-197. [PMID: 37626005 DOI: 10.1016/j.tcb.2023.07.004] [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: 04/27/2023] [Revised: 07/07/2023] [Accepted: 07/11/2023] [Indexed: 08/27/2023]
Abstract
β-Cell replacement by in situ reprogramming of non-β-cells is a promising diabetes therapy. Following the observation that near-total β-cell ablation in adult mice triggers the reprogramming of pancreatic α-, δ-, and γ-cells into insulin (INS)-producing cells, recent studies are delving deep into the mechanisms controlling adult α-cell identity. Systematic analyses of the α-cell transcriptome and epigenome have started to pinpoint features that could be crucial for maintaining α-cell identity. Using different transgenic and chemical approaches, significant advances have been made in reprogramming α-cells in vivo into INS-secreting cells in mice. The recent reprogramming of human α-cells in vitro is an important step forward that must now be complemented with a comprehensive molecular dissection of the mechanisms controlling α-cell identity.
Collapse
Affiliation(s)
- Daniel Oropeza
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Pedro Luis Herrera
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| |
Collapse
|
23
|
Wang Q, Wang X, Liu B, Ma S, Zhang F, Sun S, Jing Y, Fan Y, Ding Y, Xiong M, Li J, Zhai Q, Zheng Y, Liu C, Xu G, Yang J, Wang S, Ye J, Izpisua Belmonte JC, Qu J, Liu GH, Zhang W. Aging induces region-specific dysregulation of hormone synthesis in the primate adrenal gland. NATURE AGING 2024; 4:396-413. [PMID: 38503993 DOI: 10.1038/s43587-024-00588-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 02/05/2024] [Indexed: 03/21/2024]
Abstract
Adrenal glands, vital for steroid secretion and the regulation of metabolism, stress responses and immune activation, experience age-related decline, impacting systemic health. However, the regulatory mechanisms underlying adrenal aging remain largely uninvestigated. Here we established a single-nucleus transcriptomic atlas of both young and aged primate suprarenal glands, identifying lipid metabolism and steroidogenic pathways as core processes impacted by aging. We found dysregulation in centripetal adrenocortical differentiation in aged adrenal tissues and cells in the zona reticularis region, responsible for producing dehydroepiandrosterone sulfate (DHEA-S), were highly susceptible to aging, reflected by senescence, exhaustion and disturbed hormone production. Remarkably, LDLR was downregulated in all cell types of the outer cortex, and its targeted inactivation in human adrenal cells compromised cholesterol uptake and secretion of dehydroepiandrosterone sulfate, as observed in aged primate adrenal glands. Our study provides crucial insights into endocrine physiology, holding therapeutic promise for addressing aging-related adrenal insufficiency and delaying systemic aging.
Collapse
Affiliation(s)
- Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xuebao Wang
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
| | - Beibei Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Shuai Ma
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Feng Zhang
- Division of Endocrinology, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China
| | - Shuhui Sun
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Yaobin Jing
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- International Center for Aging and Cancer, Hainan Medical University, Haikou, China
| | - Yanling Fan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Muzhao Xiong
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qiaocheng Zhai
- Division of Endocrinology, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China
| | - Yandong Zheng
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
| | - Chengyu Liu
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China
| | - Gang Xu
- Liver Transplant Center, Organ Transplant Center, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Liver Transplantation, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital of Sichuan University, Chengdu, China
| | - Jiayin Yang
- Liver Transplant Center, Organ Transplant Center, West China Hospital of Sichuan University, Chengdu, China
- Laboratory of Liver Transplantation, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital of Sichuan University, Chengdu, China
| | - Si Wang
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China
- The Fifth People's Hospital of Chongqing, Chongqing, China
- Aging Biomarker Consortium, Beijing, China
| | - Jinlin Ye
- The Joint Innovation Center for Engineering in Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou, China
| | | | - Jing Qu
- University of Chinese Academy of Sciences, Beijing, China.
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
- Aging Biomarker Consortium, Beijing, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, China.
- Key Laboratory of Organ Regeneration and Reconstruction, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, China.
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China.
- Aging Biomarker Consortium, Beijing, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, China.
- Aging Biomarker Consortium, Beijing, China.
| |
Collapse
|
24
|
Xu Y, Zhang W, Zheng X, Cai X. Combining Global-Constrained Concept Factorization and a Regularized Gaussian Graphical Model for Clustering Single-Cell RNA-seq Data. Interdiscip Sci 2024; 16:1-15. [PMID: 37815679 DOI: 10.1007/s12539-023-00587-7] [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: 02/06/2023] [Revised: 09/14/2023] [Accepted: 09/17/2023] [Indexed: 10/11/2023]
Abstract
Single-cell RNA sequencing technology is one of the most cost-effective ways to uncover transcriptomic heterogeneity. With the rapid rise of this technology, enormous amounts of scRNA-seq data have been produced. Due to the high dimensionality, noise, sparsity and missing features of the available scRNA-seq data, accurately clustering the scRNA-seq data for downstream analysis is a significant challenge. Many computational methods have been designed to address this issue; nevertheless, the efficacy of the available methods is still inadequate. In addition, most similarity-based methods require a number of clusters as input, which is difficult to achieve in real applications. In this study, we developed a novel computational method for clustering scRNA-seq data by considering both global and local information, named GCFG. This method characterizes the global properties of data by applying concept factorization, and the regularized Gaussian graphical model is utilized to evaluate the local embedding relationship of data. To learn the cell-cell similarity matrix, we integrated the two components, and an iterative optimization algorithm was developed. The categorization of single cells is obtained by applying Louvain, a modularity-based community discovery algorithm, to the similarity matrix. The behavior of the GCFG approach is assessed on 14 real scRNA-seq datasets in terms of ACC and ARI, and comparison results with 17 other competitive methods suggest that GCFG is effective and robust.
Collapse
Affiliation(s)
- Yaxin Xu
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China
| | - Wei Zhang
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China.
| | - Xiaoying Zheng
- Operations Research and Planning Department, Naval University of Engineering, Wuhan, 430033, China
| | - Xianxian Cai
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China
| |
Collapse
|
25
|
Nishikawa T, Lee M, Amau M. New generative methods for single-cell transcriptome data in bulk RNA sequence deconvolution. Sci Rep 2024; 14:4156. [PMID: 38378978 PMCID: PMC10879528 DOI: 10.1038/s41598-024-54798-z] [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: 09/08/2023] [Accepted: 02/16/2024] [Indexed: 02/22/2024] Open
Abstract
Numerous methods for bulk RNA sequence deconvolution have been developed to identify cellular targets of diseases by understanding the composition of cell types in disease-related tissues. However, issues of heterogeneity in gene expression between subjects and the shortage of reference single-cell RNA sequence data remain to achieve accurate bulk deconvolution. In our study, we investigated whether a new data generative method named sc-CMGAN and benchmarking generative methods (Copula, CTGAN and TVAE) could solve these issues and improve the bulk deconvolutions. We also evaluated the robustness of sc-CMGAN using three deconvolution methods and four public datasets. In almost all conditions, the generative methods contributed to improved deconvolution. Notably, sc-CMGAN outperformed the benchmarking methods and demonstrated higher robustness. This study is the first to examine the impact of data augmentation on bulk deconvolution. The new generative method, sc-CMGAN, is expected to become one of the powerful tools for the preprocessing of bulk deconvolution.
Collapse
Affiliation(s)
- Toui Nishikawa
- Faculty of Medicine, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan.
| | - Masatoshi Lee
- Faculty of Medicine, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan
| | | |
Collapse
|
26
|
Cai X, Zhang W, Zheng X, Xu Y, Li Y. scEM: A New Ensemble Framework for Predicting Cell Type Composition Based on scRNA-Seq Data. Interdiscip Sci 2024:10.1007/s12539-023-00601-y. [PMID: 38368575 DOI: 10.1007/s12539-023-00601-y] [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: 06/12/2023] [Revised: 12/22/2023] [Accepted: 12/24/2023] [Indexed: 02/19/2024]
Abstract
With the advent of single-cell RNA sequencing (scRNA-seq) technology, many scRNA-seq data have become available, providing an unprecedented opportunity to explore cellular composition and heterogeneity. Recently, many computational algorithms for predicting cell type composition have been developed, and these methods are typically evaluated on different datasets and performance metrics using diverse techniques. Consequently, the lack of comprehensive and standardized comparative analysis makes it difficult to gain a clear understanding of the strengths and weaknesses of these methods. To address this gap, we reviewed 20 cutting-edge unsupervised cell type identification methods and evaluated these methods comprehensively using 24 real scRNA-seq datasets of varying scales. In addition, we proposed a new ensemble cell-type identification method, named scEM, which learns the consensus similarity matrix by applying the entropy weight method to the four representative methods are selected. The Louvain algorithm is adopted to obtain the final classification of individual cells based on the consensus matrix. Extensive evaluation and comparison with 11 other similarity-based methods under real scRNA-seq datasets demonstrate that the newly developed ensemble algorithm scEM is effective in predicting cellular type composition.
Collapse
Affiliation(s)
- Xianxian Cai
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China
| | - Wei Zhang
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China.
| | - Xiaoying Zheng
- Operations research and planning department, Naval University of Engineering, Wuhan, 430033, China
| | - Yaxin Xu
- School of Sciences, East China Jiaotong University, Nanchang, 330013, China
| | - Yuanyuan Li
- School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan, China
| |
Collapse
|
27
|
Omidsalar AA, McCullough CG, Xu L, Boedijono S, Gerke D, Webb MG, Manojlovic Z, Sequeira A, Lew MF, Santorelli M, Serrano GE, Beach TG, Limon A, Vawter MP, Hjelm BE. Common mitochondrial deletions in RNA-Seq: evaluation of bulk, single-cell, and spatial transcriptomic datasets. Commun Biol 2024; 7:200. [PMID: 38368460 PMCID: PMC10874445 DOI: 10.1038/s42003-024-05877-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 01/31/2024] [Indexed: 02/19/2024] Open
Abstract
Common mitochondrial DNA (mtDNA) deletions are large structural variants in the mitochondrial genome that accumulate in metabolically active tissues with age and have been investigated in various diseases. We applied the Splice-Break2 pipeline (designed for high-throughput quantification of mtDNA deletions) to human RNA-Seq datasets and describe the methodological considerations for evaluating common deletions in bulk, single-cell, and spatial transcriptomics datasets. A robust evaluation of 1570 samples from 14 RNA-Seq studies showed: (i) the abundance of some common deletions detected in PCR-amplified mtDNA correlates with levels observed in RNA-Seq data; (ii) RNA-Seq library preparation method has a strong effect on deletion detection; (iii) deletions had a significant, positive correlation with age in brain and muscle; (iv) deletions were enriched in cortical grey matter, specifically in layers 3 and 5; and (v) brain regions with dopaminergic neurons (i.e., substantia nigra, ventral tegmental area, and caudate nucleus) had remarkable enrichment of common mtDNA deletions.
Collapse
Affiliation(s)
- Audrey A Omidsalar
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Carmel G McCullough
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Lili Xu
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Stanley Boedijono
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Daniel Gerke
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Michelle G Webb
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Zarko Manojlovic
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Adolfo Sequeira
- Department of Psychiatry and Human Behavior, University of California - Irvine (UCI) School of Medicine, Irvine, CA, USA
| | - Mark F Lew
- Department of Neurology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Marco Santorelli
- Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Geidy E Serrano
- Banner Sun Health Research Institute (BSHRI), Sun City, AZ, USA
| | - Thomas G Beach
- Banner Sun Health Research Institute (BSHRI), Sun City, AZ, USA
| | - Agenor Limon
- Mitchell Center for Neurodegenerative Diseases, Department of Neurology, School of Medicine, University of Texas Medical Branch, Galveston, TX, USA
| | - Marquis P Vawter
- Department of Psychiatry and Human Behavior, University of California - Irvine (UCI) School of Medicine, Irvine, CA, USA
| | - Brooke E Hjelm
- Department of Translational Genomics, Keck School of Medicine of USC, Los Angeles, CA, USA.
| |
Collapse
|
28
|
Winkler I, Tolkachov A, Lammers F, Lacour P, Daugelaite K, Schneider N, Koch ML, Panten J, Grünschläger F, Poth T, Ávila BMD, Schneider A, Haas S, Odom DT, Gonçalves Â. The cycling and aging mouse female reproductive tract at single-cell resolution. Cell 2024; 187:981-998.e25. [PMID: 38325365 DOI: 10.1016/j.cell.2024.01.021] [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: 07/25/2022] [Revised: 04/21/2023] [Accepted: 01/12/2024] [Indexed: 02/09/2024]
Abstract
The female reproductive tract (FRT) undergoes extensive remodeling during reproductive cycling. This recurrent remodeling and how it shapes organ-specific aging remains poorly explored. Using single-cell and spatial transcriptomics, we systematically characterized morphological and gene expression changes occurring in ovary, oviduct, uterus, cervix, and vagina at each phase of the mouse estrous cycle, during decidualization, and into aging. These analyses reveal that fibroblasts play central-and highly organ-specific-roles in FRT remodeling by orchestrating extracellular matrix (ECM) reorganization and inflammation. Our results suggest a model wherein recurrent FRT remodeling over reproductive lifespan drives the gradual, age-related development of fibrosis and chronic inflammation. This hypothesis was directly tested using chemical ablation of cycling, which reduced fibrotic accumulation during aging. Our atlas provides extensive detail into how estrus, pregnancy, and aging shape the organs of the female reproductive tract and reveals the unexpected cost of the recurrent remodeling required for reproduction.
Collapse
Affiliation(s)
- Ivana Winkler
- German Cancer Research Center (DKFZ), Division of Somatic Evolution and Early Detection, 69120 Heidelberg, Germany
| | - Alexander Tolkachov
- German Cancer Research Center (DKFZ), Division of Regulatory Genomics and Cancer Evolution, 69120 Heidelberg, Germany
| | - Fritjof Lammers
- German Cancer Research Center (DKFZ), Division of Regulatory Genomics and Cancer Evolution, 69120 Heidelberg, Germany
| | - Perrine Lacour
- German Cancer Research Center (DKFZ), Division of Somatic Evolution and Early Detection, 69120 Heidelberg, Germany; Heidelberg University, Faculty of Biosciences, 69117 Heidelberg, Germany
| | - Klaudija Daugelaite
- German Cancer Research Center (DKFZ), Division of Regulatory Genomics and Cancer Evolution, 69120 Heidelberg, Germany; Heidelberg University, Faculty of Biosciences, 69117 Heidelberg, Germany
| | - Nina Schneider
- German Cancer Research Center (DKFZ), Division of Somatic Evolution and Early Detection, 69120 Heidelberg, Germany
| | - Marie-Luise Koch
- German Cancer Research Center (DKFZ), Division of Regulatory Genomics and Cancer Evolution, 69120 Heidelberg, Germany
| | - Jasper Panten
- German Cancer Research Center (DKFZ), Division of Regulatory Genomics and Cancer Evolution, 69120 Heidelberg, Germany; Heidelberg University, Faculty of Biosciences, 69117 Heidelberg, Germany; German Cancer Research Center (DKFZ), Division of Computational Genomics and Systems Genetics, 69120 Heidelberg, Germany
| | - Florian Grünschläger
- Heidelberg University, Faculty of Biosciences, 69117 Heidelberg, Germany; German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Division of Stem Cells and Cancer, 69120 Heidelberg, Germany; Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany
| | - Tanja Poth
- CMCP - Center for Model System and Comparative Pathology, Institute of Pathology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | | | - Augusto Schneider
- Universidade Federal de Pelotas, Faculdade de Nutrição, 96010-610 Pelotas, RS, Brazil
| | - Simon Haas
- German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Division of Stem Cells and Cancer, 69120 Heidelberg, Germany; Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), 69120 Heidelberg, Germany; Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany; Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany; German Cancer Consortium (DKTK), 69120 Heidelberg, Germany; Charité - Universitätsmedizin Berlin, Department of Hematology, Oncology and Cancer Immunology, 10115 Berlin, Germany
| | - Duncan T Odom
- German Cancer Research Center (DKFZ), Division of Regulatory Genomics and Cancer Evolution, 69120 Heidelberg, Germany; Cancer Research UK - Cambridge Institute, University of Cambridge, Cambridge, UK.
| | - Ângela Gonçalves
- German Cancer Research Center (DKFZ), Division of Somatic Evolution and Early Detection, 69120 Heidelberg, Germany.
| |
Collapse
|
29
|
Rampazzo Morelli N, Pipella J, Thompson PJ. Establishing evidence for immune surveillance of β-cell senescence. Trends Endocrinol Metab 2024:S1043-2760(24)00017-1. [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] [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.
Collapse
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.
| |
Collapse
|
30
|
Yin P, Chen M, Rao M, Lin Y, Zhang M, Xu R, Hu X, Chen R, Chai W, Huang X, Yu H, Yao Y, Zhao Y, Li Y, Zhang L, Tang P. Deciphering Immune Landscape Remodeling Unravels the Underlying Mechanism for Synchronized Muscle and Bone Aging. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2304084. [PMID: 38088531 PMCID: PMC10837389 DOI: 10.1002/advs.202304084] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/30/2023] [Indexed: 02/04/2024]
Abstract
Evidence from numerous studies has revealed the synchronous progression of aging in bone and muscle; however, little is known about the underlying mechanisms. To this end, human muscles and bones are harvested and the aging-associated transcriptional dynamics of two tissues in parallel using single-cell RNA sequencing are surveyed. A subset of lipid-associated macrophages (triggering receptor expressed on myeloid cells 2, TREM2+ Macs) is identified in both aged muscle and bone. Genes responsible for muscle dystrophy and bone loss, such as secreted phosphoprotein 1 (SPP1), are also highly expressed in TREM2+ Macs, suggesting its conserved role in aging-related features. A common transition toward pro-inflammatory phenotypes in aged CD4+ T cells across tissues is also observed, activated by the nuclear factor kappa B subunit 1 (NFKB1). CD4+ T cells in aged muscle experience Th1-like differentiation, whereas, in bone, a skewing toward Th17 cells is observed. Furthermore, these results highlight that degenerated myocytes produce BAG6-containing exosomes that can communicate with Th17 cells in the bone through its receptor natural cytotoxicity triggering receptor 3 (NCR3). This communication upregulates CD6 expression in Th17 cells, which then interact with TREM2+ Macs through CD6-ALCAM signaling, ultimately stimulating the transcription of SPP1 in TREM2+ Macs. The negative correlation between serum exosomal BCL2-associated athanogene 6 (BAG6) levels and bone mineral density further supports its role in mediating muscle and bone synchronization with aging.
Collapse
Affiliation(s)
- Pengbin Yin
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Ming Chen
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Man Rao
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
- Analytical Biosciences LimitedBeijing100191China
| | - Yuan Lin
- The Department of Orthopedic SurgerySecond Affiliated Hospital of Harbin Medical UniversityHarbin150086China
| | - Mingming Zhang
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Ren Xu
- State Key Laboratory of Cellular Stress BiologySchool of MedicineFaculty of Medicine and Life SciencesXiamen UniversityXiamen361102China
| | - Xueda Hu
- Analytical Biosciences LimitedBeijing100191China
| | - Ruijing Chen
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Wei Chai
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Xiang Huang
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Haikuan Yu
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Yao Yao
- Center for Healthy Aging and Development StudiesNational School of DevelopmentPeking UniversityBeijing100871China
| | - Yali Zhao
- Central LaboratoryHainan Hospital of Chinese People's Liberation Army General HospitalSanya572013China
| | - Yi Li
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Licheng Zhang
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| | - Peifu Tang
- Senior Department of OrthopedicsThe Fourth Medical Center of PLA General HospitalBeijing100048China
- National Clinical Research Center for OrthopedicsSports Medicine & RehabilitationBeijing100048China
| |
Collapse
|
31
|
Pang Z, Cravatt BF, Ye L. Deciphering Drug Targets and Actions with Single-Cell and Spatial Resolution. Annu Rev Pharmacol Toxicol 2024; 64:507-526. [PMID: 37722721 DOI: 10.1146/annurev-pharmtox-033123-123610] [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] [Indexed: 09/20/2023]
Abstract
Recent advances in chemical, molecular, and genetic approaches have provided us with an unprecedented capacity to identify drug-target interactions across the whole proteome and genome. Meanwhile, rapid developments of single-cell and spatial omics technologies are revolutionizing our understanding of the molecular architecture of biological systems. However, a significant gap remains in how we align our understanding of drug actions, traditionally based on molecular affinities, with the in vivo cellular and spatial tissue heterogeneity revealed by these newer techniques. Here, we review state-of-the-art methods for profiling drug-target interactions and emerging multiomics tools to delineate the tissue heterogeneity at single-cell resolution. Highlighting the recent technical advances enabling high-resolution, multiplexable in situ small-molecule drug imaging (clearing-assisted tissue click chemistry, or CATCH), we foresee the integration of single-cell and spatial omics platforms, data, and concepts into the future framework of defining and understanding in vivo drug-target interactions and mechanisms of actions.
Collapse
Affiliation(s)
- Zhengyuan Pang
- Department of Neuroscience, The Scripps Research Institute, La Jolla, California, USA;
| | - Benjamin F Cravatt
- Department of Chemistry, The Scripps Research Institute, La Jolla, California, USA;
| | - Li Ye
- Department of Neuroscience, The Scripps Research Institute, La Jolla, California, USA;
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California, USA
| |
Collapse
|
32
|
Wan H, Yuan M, Fu Y, Deng M. Continually adapting pre-trained language model to universal annotation of single-cell RNA-seq data. Brief Bioinform 2024; 25:bbae047. [PMID: 38388681 PMCID: PMC10883808 DOI: 10.1093/bib/bbae047] [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: 10/04/2023] [Revised: 12/29/2023] [Accepted: 01/18/2024] [Indexed: 02/24/2024] Open
Abstract
MOTIVATION Cell-type annotation of single-cell RNA-sequencing (scRNA-seq) data is a hallmark of biomedical research and clinical application. Current annotation tools usually assume the simultaneous acquisition of well-annotated data, but without the ability to expand knowledge from new data. Yet, such tools are inconsistent with the continuous emergence of scRNA-seq data, calling for a continuous cell-type annotation model. In addition, by their powerful ability of information integration and model interpretability, transformer-based pre-trained language models have led to breakthroughs in single-cell biology research. Therefore, the systematic combining of continual learning and pre-trained language models for cell-type annotation tasks is inevitable. RESULTS We herein propose a universal cell-type annotation tool, called CANAL, that continuously fine-tunes a pre-trained language model trained on a large amount of unlabeled scRNA-seq data, as new well-labeled data emerges. CANAL essentially alleviates the dilemma of catastrophic forgetting, both in terms of model inputs and outputs. For model inputs, we introduce an experience replay schema that repeatedly reviews previous vital examples in current training stages. This is achieved through a dynamic example bank with a fixed buffer size. The example bank is class-balanced and proficient in retaining cell-type-specific information, particularly facilitating the consolidation of patterns associated with rare cell types. For model outputs, we utilize representation knowledge distillation to regularize the divergence between previous and current models, resulting in the preservation of knowledge learned from past training stages. Moreover, our universal annotation framework considers the inclusion of new cell types throughout the fine-tuning and testing stages. We can continuously expand the cell-type annotation library by absorbing new cell types from newly arrived, well-annotated training datasets, as well as automatically identify novel cells in unlabeled datasets. Comprehensive experiments with data streams under various biological scenarios demonstrate the versatility and high model interpretability of CANAL. AVAILABILITY An implementation of CANAL is available from https://github.com/aster-ww/CANAL-torch. CONTACT dengmh@pku.edu.cn. SUPPLEMENTARY INFORMATION Supplementary data are available at Journal Name online.
Collapse
Affiliation(s)
- Hui Wan
- School of Mathematical Sciences, Peking University, Beijing, China, 100871
| | - Musu Yuan
- Center for Quantitative Biology, Peking University, Beijing, China, 100871
| | - Yiwei Fu
- School of Mathematical Sciences, Peking University, Beijing, China, 100871
| | - Minghua Deng
- School of Mathematical Sciences, Peking University, Beijing, China, 100871
- Center for Quantitative Biology, Peking University, Beijing, China, 100871
- Center for Statistical Science, Peking university, Beijing, China, 100871
| |
Collapse
|
33
|
Sturgill D, Wang L, Arda HE. PancrESS - a meta-analysis resource for understanding cell-type specific expression in the human pancreas. BMC Genomics 2024; 25:76. [PMID: 38238687 PMCID: PMC10797729 DOI: 10.1186/s12864-024-09964-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND The human pancreas is composed of specialized cell types producing hormones and enzymes critical to human health. These specialized functions are the result of cell type-specific transcriptional programs which manifest in cell-specific gene expression. Understanding these programs is essential to developing therapies for pancreatic disorders. Transcription in the human pancreas has been widely studied by single-cell RNA technologies, however the diversity of protocols and analysis methods hinders their interpretability in the aggregate. RESULTS In this work, we perform a meta-analysis of pancreatic single-cell RNA sequencing data. We present a database for reference transcriptome abundances and cell-type specificity metrics. This database facilitates the identification and definition of marker genes within the pancreas. Additionally, we introduce a versatile tool which is freely available as an R package, and should permit integration into existing workflows. Our tool accepts count data files generated by widely-used single-cell gene expression platforms in their original format, eliminating an additional pre-formatting step. Although we designed it to calculate expression specificity of pancreas cell types, our tool is agnostic to the biological source of count data, extending its applicability to other biological systems. CONCLUSIONS Our findings enhance the current understanding of expression specificity within the pancreas, surpassing previous work in terms of scope and detail. Furthermore, our database and tool enable researchers to perform similar calculations in diverse biological systems, expanding the applicability of marker gene identification and facilitating comparative analyses.
Collapse
Affiliation(s)
- David Sturgill
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA
| | - Li Wang
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA
| | - H Efsun Arda
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD, 20892, USA.
| |
Collapse
|
34
|
Chandra V, Li L, Le Roux O, Zhang Y, Howell RM, Rupani DN, Baydogan S, Miller HD, Riquelme E, Petrosino J, Kim MP, Bhat KPL, White JR, Kolls JK, Pylayeva-Gupta Y, McAllister F. Gut epithelial Interleukin-17 receptor A signaling can modulate distant tumors growth through microbial regulation. Cancer Cell 2024; 42:85-100.e6. [PMID: 38157865 DOI: 10.1016/j.ccell.2023.12.006] [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: 06/30/2022] [Revised: 04/05/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
Microbes influence cancer initiation, progression and therapy responsiveness. IL-17 signaling contributes to gut barrier immunity by regulating microbes but also drives tumor growth. A knowledge gap remains regarding the influence of enteric IL-17-IL-17RA signaling and their microbial regulation on the behavior of distant tumors. We demonstrate that gut dysbiosis induced by systemic or gut epithelial deletion of IL-17RA induces growth of pancreatic and brain tumors due to excessive development of Th17, primary source of IL-17 in human and mouse pancreatic ductal adenocarcinoma, as well as B cells that circulate to distant tumors. Microbial dependent IL-17 signaling increases DUOX2 signaling in tumor cells. Inefficacy of pharmacological inhibition of IL-17RA is overcome with targeted microbial ablation that blocks the compensatory loop. These findings demonstrate the complexities of IL-17-IL-17RA signaling in different compartments and the relevance for accounting for its homeostatic host defense function during cancer therapy.
Collapse
Affiliation(s)
- Vidhi Chandra
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Le Li
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Olivereen Le Roux
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yu Zhang
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rian M Howell
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Dhwani N Rupani
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Seyda Baydogan
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Haiyan D Miller
- Department of Pediatrics and Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Erick Riquelme
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Respiratory Diseases, Faculty of Medicine, Pontifical Catholic University of Chile, Santiago, Chile
| | - Joseph Petrosino
- Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Michael P Kim
- Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Krishna P L Bhat
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Jay K Kolls
- Department of Pediatrics and Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Yuliya Pylayeva-Gupta
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, School of Medicine, Chapel Hill, NC, USA
| | - Florencia McAllister
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Gastrointestinal Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Immunology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| |
Collapse
|
35
|
Shah MA, Faheem HI, Hamid A, Yousaf R, Haris M, Saleem U, Shah GM, Alhasani RH, Althobaiti NA, Alsharif I, Silva AS. The entrancing role of dietary polyphenols against the most frequent aging-associated diseases. Med Res Rev 2024; 44:235-274. [PMID: 37486109 DOI: 10.1002/med.21985] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 01/27/2023] [Accepted: 07/06/2023] [Indexed: 07/25/2023]
Abstract
Aging, a fundamental physiological process influenced by innumerable biological and genetic pathways, is an important driving factor for several aging-associated disorders like diabetes mellitus, osteoporosis, cancer, and neurodegenerative diseases including Alzheimer's and Parkinson's diseases. In the modern era, the several mechanisms associated with aging have been deeply studied. Treatment and therapeutics for age-related diseases have also made considerable advances; however, for the effective and long-lasting treatment, nutritional therapy particularly including dietary polyphenols from the natural origin are endorsed. These dietary polyphenols (e.g., apigenin, baicalin, curcumin, epigallocatechin gallate, kaempferol, quercetin, resveratrol, and theaflavin), and many other phytochemicals target certain molecular, genetic mechanisms. The most common pathways of age-associated diseases are mitogen-activated protein kinase, reactive oxygen species production, nuclear factor kappa light chain enhancer of activated B cells signaling pathways, metal chelation, c-Jun N-terminal kinase, and inflammation. Polyphenols slow down the course of aging and help in combatting age-linked disorders. This exemplified in the form of clinical trials on specific dietary polyphenols in various aging-associated diseases. With this context in mind, this review reveals the new insights to slow down the aging process, and consequently reduce some classic diseases associated with age such as aforementioned, and targeting age-associated diseases by the activities of dietary polyphenols of natural origin.
Collapse
Affiliation(s)
| | - Hafiza Ishmal Faheem
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, Pakistan
| | - Ayesha Hamid
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, Pakistan
| | - Rimsha Yousaf
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, Pakistan
| | - Muhammad Haris
- Faculty of Pharmaceutical Sciences, Universiteit Gent, Ghent, Belgium
| | - Uzma Saleem
- Department of Pharmacology, Faculty of Pharmaceutical Sciences, Government College University, Faisalabad, Pakistan
| | - Ghulam Mujtaba Shah
- Department of Botany, Faculty of Health and Biological Sciences, Hazara University, Mansehra, Pakistan
| | - Reem H Alhasani
- Department of Biology, Faculty of Applied Science, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Norah A Althobaiti
- Department of Biology, College of Science and Humanities, Shaqra University, Al-Quwaiiyah, Saudi Arabia
| | - Ifat Alsharif
- Department of Biology, Jamoum University College, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Ana Sanches Silva
- National Institute for Agrarian and Veterinary Research (INIAV), I.P., Rua dos Lágidos, Lugar da Madalena, Vairão, Vila do Conde, Portugal
- University of Coimbra, Faculty of Pharmacy, Polo III, Azinhaga de St Comba, Coimbra, Portugal
- Centre for Animal Science Studies (CECA), ICETA, University of Porto, Porto, Portugal
| |
Collapse
|
36
|
Paz-Barba M, Muñoz Garcia A, de Winter TJJ, de Graaf N, van Agen M, van der Sar E, Lambregtse F, Daleman L, van der Slik A, Zaldumbide A, de Koning EJP, Carlotti F. Apolipoprotein L genes are novel mediators of inflammation in beta cells. Diabetologia 2024; 67:124-136. [PMID: 37924378 PMCID: PMC10709252 DOI: 10.1007/s00125-023-06033-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 08/22/2023] [Indexed: 11/06/2023]
Abstract
AIMS/HYPOTHESIS Inflammation induces beta cell dysfunction and demise but underlying molecular mechanisms remain unclear. The apolipoprotein L (APOL) family of genes has been associated with innate immunity and apoptosis in non-pancreatic cell types, but also with metabolic syndrome and type 2 diabetes mellitus. Here, we hypothesised that APOL genes play a role in inflammation-induced beta cell damage. METHODS We used single-cell transcriptomics datasets of primary human pancreatic islet cells to study the expression of APOL genes upon specific stress conditions. Validation of the findings was carried out in EndoC-βH1 cells and primary human islets. Finally, we performed loss- and gain-of-function experiments to investigate the role of APOL genes in beta cells. RESULTS APOL genes are expressed in primary human beta cells and APOL1, 2 and 6 are strongly upregulated upon inflammation via the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway. APOL1 overexpression increases endoplasmic reticulum stress while APOL1 knockdown prevents cytokine-induced beta cell death and interferon-associated response. Furthermore, we found that APOL genes are upregulated in beta cells from donors with type 2 diabetes compared with donors without diabetes mellitus. CONCLUSIONS/INTERPRETATION APOLs are novel regulators of islet inflammation and may contribute to beta cell damage during the development of diabetes. DATA AVAILABILITY scRNAseq data generated by our laboratory and used in this study are available in the Gene Expression Omnibus (GEO; www.ncbi.nlm.nih.gov/geo/ ), accession number GSE218316.
Collapse
Affiliation(s)
- Miriam Paz-Barba
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Amadeo Muñoz Garcia
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Twan J J de Winter
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Natascha de Graaf
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Maarten van Agen
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Elisa van der Sar
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Ferdy Lambregtse
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Lizanne Daleman
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Arno van der Slik
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Arnaud Zaldumbide
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Eelco J P de Koning
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands
| | - Françoise Carlotti
- Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands.
| |
Collapse
|
37
|
Zhang T, Jia H, Song T, Lv L, Gulhan DC, Wang H, Guo W, Xi R, Guo H, Shen N. De novo identification of expressed cancer somatic mutations from single-cell RNA sequencing data. Genome Med 2023; 15:115. [PMID: 38111063 PMCID: PMC10726641 DOI: 10.1186/s13073-023-01269-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 12/04/2023] [Indexed: 12/20/2023] Open
Abstract
Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is challenging but highly valuable. We propose RESA - Recurrently Expressed SNV Analysis, a computational framework to identify expressed somatic mutations from scRNA-seq data. RESA achieves an average precision of 0.77 on three in silico spike-in datasets. In extensive benchmarking against existing methods using 19 datasets, RESA consistently outperforms them. Furthermore, we applied RESA to analyze intratumor mutational heterogeneity in a melanoma drug resistance dataset. By enabling high precision detection of expressed somatic mutations, RESA substantially enhances the reliability of mutational analysis in scRNA-seq. RESA is available at https://github.com/ShenLab-Genomics/RESA .
Collapse
Affiliation(s)
- Tianyun Zhang
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Hanying Jia
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- Kidney Disease Center, the First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 311121, China
| | - Tairan Song
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Lin Lv
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
| | - Doga C Gulhan
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Haishuai Wang
- College of Computer Science, Zhejiang University, Hangzhou, 311121, Zhejiang, China
| | - Wei Guo
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Jiaxing, 314400, China
| | - Ruibin Xi
- School of Mathematical Sciences and Center for Statistical Science, Peking University, 5 Yiheyuan Road, Beijing, 100871, China
| | - Hongshan Guo
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China
- Bone Marrow Transplantation Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
| | - Ning Shen
- Department of Hepatobiliary and Pancreatic Surgery of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 311121, China.
| |
Collapse
|
38
|
Yang M, Harrison BR, Promislow DEL. Cellular age explains variation in age-related cell-to-cell transcriptome variability. Genome Res 2023; 33:gr.278144.123. [PMID: 37973195 PMCID: PMC10760448 DOI: 10.1101/gr.278144.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 10/12/2023] [Indexed: 11/19/2023]
Abstract
Organs and tissues age at different rates within a single individual. Such asynchrony in aging has been widely observed at multiple levels, from functional hallmarks, such as anatomical structures and physiological processes, to molecular endophenotypes, such as the transcriptome and metabolome. However, we lack a conceptual framework to understand why some components age faster than others. Just as demographic models explain why aging evolves, here we test the hypothesis that demographic differences among cell types, determined by cell-specific differences in turnover rate, can explain why the transcriptome shows signs of aging in some cell types but not others. Through analysis of mouse single-cell transcriptome data across diverse tissues and ages, we find that cellular age explains a large proportion of the variation in the age-related increase in transcriptome variance. We further show that long-lived cells are characterized by relatively high expression of genes associated with proteostasis and that the transcriptome of long-lived cells shows greater evolutionary constraint than short-lived cells. In contrast, in short-lived cell types, the transcriptome is enriched for genes associated with DNA repair. Based on these observations, we develop a novel heuristic model that explains how and why aging rates differ among cell types.
Collapse
Affiliation(s)
- Ming Yang
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Benjamin R Harrison
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington 98195, USA
| | - Daniel E L Promislow
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, Washington 98195, USA;
- Department of Biology, University of Washington, Seattle, Washington 98195, USA
| |
Collapse
|
39
|
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.
Collapse
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.
| |
Collapse
|
40
|
Zane F, Bouzid H, Sosa Marmol S, Brazane M, Besse S, Molina JL, Cansell C, Aprahamian F, Durand S, Ayache J, Antoniewski C, Todd N, Carré C, Rera M. Smurfness-based two-phase model of ageing helps deconvolve the ageing transcriptional signature. Aging Cell 2023; 22:e13946. [PMID: 37822253 PMCID: PMC10652310 DOI: 10.1111/acel.13946] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 07/17/2023] [Accepted: 07/18/2023] [Indexed: 10/13/2023] Open
Abstract
Ageing is characterised at the molecular level by six transcriptional 'hallmarks of ageing', that are commonly described as progressively affected as time passes. By contrast, the 'Smurf' assay separates high-and-constant-mortality risk individuals from healthy, zero-mortality risk individuals, based on increased intestinal permeability. Performing whole body total RNA sequencing, we found that Smurfness distinguishes transcriptional changes associated with chronological age from those associated with biological age. We show that transcriptional heterogeneity increases with chronological age in non-Smurf individuals preceding the other five hallmarks of ageing that are specifically associated with the Smurf state. Using this approach, we also devise targeted pro-longevity genetic interventions delaying entry in the Smurf state. We anticipate that increased attention to the evolutionary conserved Smurf phenotype will bring about significant advances in our understanding of the mechanisms of ageing.
Collapse
Affiliation(s)
- Flaminia Zane
- Université Paris Cité, INSERM UMR U1284ParisFrance
- Institut de Biologie Paris Seine, Sorbonne UniversitéParisFrance
| | - Hayet Bouzid
- Université Paris Cité, INSERM UMR U1284ParisFrance
- Institut de Biologie Paris Seine, Sorbonne UniversitéParisFrance
| | | | - Mira Brazane
- Institut de Biologie Paris Seine, Sorbonne UniversitéParisFrance
| | | | | | - Céline Cansell
- Université Paris‐Saclay, AgroParisTech, INRAE, UMR PNCAPalaiseauFrance
| | - Fanny Aprahamian
- Metabolomics and Cell Biology Platforms, UMS AMMICaInstitut Gustave RoussyVillejuifFrance
- Centre de Recherche des Cordeliers, Equipe Labellisée par la Ligue Contre le CancerUniversité de Paris, Sorbonne Université, INSERM U1138, Institut Universitaire de FranceParisFrance
| | - Sylvère Durand
- Metabolomics and Cell Biology Platforms, UMS AMMICaInstitut Gustave RoussyVillejuifFrance
- Centre de Recherche des Cordeliers, Equipe Labellisée par la Ligue Contre le CancerUniversité de Paris, Sorbonne Université, INSERM U1138, Institut Universitaire de FranceParisFrance
| | - Jessica Ayache
- Institut Jacques Monod, CNRS UMR 7592, Université Paris CitéParisFrance
| | | | - Nicolas Todd
- Eco‐Anthropologie (EA), Muséum National d'Histoire Naturelle, CNRSUniversité de Paris, Musée de l'HommeParisFrance
| | - Clément Carré
- Institut de Biologie Paris Seine, Sorbonne UniversitéParisFrance
| | - Michael Rera
- Université Paris Cité, INSERM UMR U1284ParisFrance
| |
Collapse
|
41
|
Yousefzadeh MJ, Huerta Guevara AP, Postmus AC, Flores RR, Sano T, Jurdzinski A, Angelini L, McGowan SJ, O’Kelly RD, Wade EA, Gonzalez-Espada LV, Henessy-Wack D, Howard S, Rozgaja TA, Trussoni CE, LaRusso NF, Eggen BJ, Jonker JW, Robbins PD, Niedernhofer LJ, Kruit JK. Failure to repair endogenous DNA damage in β-cells causes adult-onset diabetes in mice. AGING BIOLOGY 2023; 1:20230015. [PMID: 38124711 PMCID: PMC10732477 DOI: 10.59368/agingbio.20230015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Age is the greatest risk factor for the development of type 2 diabetes mellitus (T2DM). Age-related decline in organ function is attributed to the accumulation of stochastic damage, including damage to the nuclear genome. Islets of T2DM patients display increased levels of DNA damage. However, whether this is a cause or consequence of the disease has not been elucidated. Here, we asked if spontaneous, endogenous DNA damage in β-cells can drive β-cell dysfunction and diabetes, via deletion of Ercc1, a key DNA repair gene, in β-cells. Mice harboring Ercc1-deficient β-cells developed adult-onset diabetes as demonstrated by increased random and fasted blood glucose levels, impaired glucose tolerance, and reduced insulin secretion. The inability to repair endogenous DNA damage led to an increase in oxidative DNA damage and apoptosis in β-cells and a significant loss of β-cell mass. Using electron microscopy, we identified β-cells in clear distress that showed an increased cell size, enlarged nuclear size, reduced number of mature insulin granules, and decreased number of mitochondria. Some β-cells were more affected than others consistent with the stochastic nature of spontaneous DNA damage. Ercc1-deficiency in β-cells also resulted in loss of β-cell function as glucose-stimulated insulin secretion and mitochondrial function were impaired in islets isolated from mice harboring Ercc1-deficient β-cells. These data reveal that unrepaired endogenous DNA damage is sufficient to drive β-cell dysfunction and provide a mechanism by which age increases the risk of T2DM.
Collapse
Affiliation(s)
- Matthew J. Yousefzadeh
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Ana P. Huerta Guevara
- Department of Pediatrics, Section Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Andrea C. Postmus
- Department of Pediatrics, Section Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Rafael R. Flores
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Tokio Sano
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
| | - Angelika Jurdzinski
- Department of Pediatrics, Section Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Luise Angelini
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Sara J. McGowan
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Ryan D. O’Kelly
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Erin A. Wade
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
| | - Lisa V. Gonzalez-Espada
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
| | - Danielle Henessy-Wack
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
| | - Shannon Howard
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
| | - Tania A. Rozgaja
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
| | - Christy E. Trussoni
- Division of Gastroenterology and Center for Cell Signaling in Gastroenterology, Mayo Clinic, Rochester, MN 55905, USA
| | - Nicholas F. LaRusso
- Division of Gastroenterology and Center for Cell Signaling in Gastroenterology, Mayo Clinic, Rochester, MN 55905, USA
| | - Bart J.L. Eggen
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Johan W. Jonker
- Department of Pediatrics, Section Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Paul D. Robbins
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Laura J. Niedernhofer
- Department of Molecular Medicine and the Center on Aging, The Scripps Research Institute, 130 Scripps Way #3B3, Jupiter FL, 33458, USA
- Department of Biochemistry, Molecular Biology and Biophysics and Institute on the Biology of Aging and Metabolism, University of Minnesota, 6-155 Jackson Hall, 321 Church St., Minneapolis, MN 55455, USA
| | - Janine K. Kruit
- Department of Pediatrics, Section Molecular Metabolism and Nutrition, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| |
Collapse
|
42
|
Zheng H, Vijg J, Fard AT, Mar JC. Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging. Genome Biol 2023; 24:238. [PMID: 37864221 PMCID: PMC10588274 DOI: 10.1186/s13059-023-03036-2] [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: 11/27/2022] [Accepted: 08/11/2023] [Indexed: 10/22/2023] Open
Abstract
BACKGROUND Single-cell RNA-sequencing (scRNA-seq) technologies enable the capture of gene expression heterogeneity and consequently facilitate the study of cell-to-cell variability at the cell type level. Although different methods have been proposed to quantify cell-to-cell variability, it is unclear what the optimal statistical approach is, especially in light of challenging data structures that are unique to scRNA-seq data like zero inflation. RESULTS We systematically evaluate the performance of 14 different variability metrics that are commonly applied to transcriptomic data for measuring cell-to-cell variability. Leveraging simulations and real datasets, we benchmark the metric performance based on data-specific features, sparsity and sequencing platform, biological properties, and the ability to recapitulate true levels of biological variability based on known gene sets. Next, we use scran, the metric with the strongest all-round performance, to investigate changes in cell-to-cell variability that occur during B cell differentiation and the aging processes. The analysis of primary cell types from hematopoietic stem cells (HSCs) and B lymphopoiesis reveals unique gene signatures with consistent patterns of variable and stable expression profiles during B cell differentiation which highlights the significance of these methods. Identifying differentially variable genes between young and old cells elucidates the regulatory changes that may be overlooked by solely focusing on mean expression changes and we investigate this in the context of regulatory networks. CONCLUSIONS We highlight the importance of capturing cell-to-cell gene expression variability in a complex biological process like differentiation and aging and emphasize the value of these findings at the level of individual cell types.
Collapse
Affiliation(s)
- Huiwen Zheng
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, Australia
| | - Jan Vijg
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
- Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Atefeh Taherian Fard
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, Australia.
| | - Jessica Cara Mar
- Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, Australia.
| |
Collapse
|
43
|
Sanchez-Quant E, Richter ML, Colomé-Tatché M, Martinez-Jimenez CP. Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge. Genome Biol 2023; 24:234. [PMID: 37848949 PMCID: PMC10583437 DOI: 10.1186/s13059-023-03075-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/26/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND Xenobiotics are primarily metabolized by hepatocytes in the liver, and primary human hepatocytes are the gold standard model for the assessment of drug efficacy, safety, and toxicity in the early phases of drug development. Recent advances in single-cell genomics demonstrate liver zonation and ploidy as main drivers of cellular heterogeneity. However, little is known about the impact of hepatocyte specialization on liver function upon metabolic challenge, including hepatic metabolism, detoxification, and protein synthesis. RESULTS Here, we investigate the metabolic capacity of individual human hepatocytes in vitro. We assess how chronic accumulation of lipids enhances cellular heterogeneity and impairs the metabolisms of drugs. Using a phenotyping five-probe cocktail, we identify four functional subgroups of hepatocytes responding differently to drug challenge and fatty acid accumulation. These four subgroups display differential gene expression profiles upon cocktail treatment and xenobiotic metabolism-related specialization. Notably, intracellular fat accumulation leads to increased transcriptional variability and diminishes the drug-related metabolic capacity of hepatocytes. CONCLUSIONS Our results demonstrate that, upon a metabolic challenge such as exposure to drugs or intracellular fat accumulation, hepatocyte subgroups display different and heterogeneous transcriptional responses.
Collapse
Affiliation(s)
- Eva Sanchez-Quant
- Helmholtz Pioneer Campus (HPC), Helmholtz Zentrum München, 85764, Neuherberg, Germany
| | - Maria Lucia Richter
- Helmholtz Pioneer Campus (HPC), Helmholtz Zentrum München, 85764, Neuherberg, Germany
| | - Maria Colomé-Tatché
- Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Germany.
- TUM School of Life Sciences Weihenstephan, Technical University of Munich (TUM), 85354, Freising, Germany.
- Biomedical Center (BMC), Physiological Chemistry, Faculty of Medicine, Ludwig Maximilian University of Munich (LMU), 82152, Munich, Germany.
| | - Celia Pilar Martinez-Jimenez
- Helmholtz Pioneer Campus (HPC), Helmholtz Zentrum München, 85764, Neuherberg, Germany.
- TUM School of Medicine, Technical University of Munich, Munich (TUM), 80333, Munich, Germany.
| |
Collapse
|
44
|
Hirano M, Yamada Y. Reprogramming of pancreatic islet cells for regeneration and rejuvenation. Curr Opin Genet Dev 2023; 82:102099. [PMID: 37611379 DOI: 10.1016/j.gde.2023.102099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 07/13/2023] [Accepted: 07/19/2023] [Indexed: 08/25/2023]
Abstract
The pancreatic β cell, which produces insulin, is a terminally differentiated cell type that divides rarely. Consequently, the regenerative ability of β cells is limited and irreversible diabetes occurs after severe loss of β-cell function. In view of such poor regenerative capacity, considerable research efforts have been made to promote the expansion of functional insulin-producing cells as a regenerative therapy for diabetes. Here, we discuss recent findings regarding the robust expansion of functional mature islet cells both in vivo and ex vivo through MYCL-mediated reprogramming. We also describe the potential prospects for the application of reprogramming technologies to regenerative therapy and rejuvenation of islet cells.
Collapse
Affiliation(s)
- Michitada Hirano
- Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
| | - Yasuhiro Yamada
- Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
| |
Collapse
|
45
|
Shi Q, Chen X, Zhang Z. Decoding Human Biology and Disease Using Single-cell Omics Technologies. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:926-949. [PMID: 37739168 PMCID: PMC10928380 DOI: 10.1016/j.gpb.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/22/2023] [Accepted: 06/08/2023] [Indexed: 09/24/2023]
Abstract
Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.
Collapse
Affiliation(s)
- Qiang Shi
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Xueyan Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Changping Laboratory, Beijing 102206, China.
| |
Collapse
|
46
|
Omrani O, Krepelova A, Rasa SMM, Sirvinskas D, Lu J, Annunziata F, Garside G, Bajwa S, Reinhardt S, Adam L, Käppel S, Ducano N, Donna D, Ori A, Oliviero S, Rudolph KL, Neri F. IFNγ-Stat1 axis drives aging-associated loss of intestinal tissue homeostasis and regeneration. Nat Commun 2023; 14:6109. [PMID: 37777550 PMCID: PMC10542816 DOI: 10.1038/s41467-023-41683-y] [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: 10/28/2021] [Accepted: 09/14/2023] [Indexed: 10/02/2023] Open
Abstract
The influence of aging on intestinal stem cells and their niche can explain underlying causes for perturbation in their function observed during aging. Molecular mechanisms for such a decrease in the functionality of intestinal stem cells during aging remain largely undetermined. Using transcriptome-wide approaches, our study demonstrates that aging intestinal stem cells strongly upregulate antigen presenting pathway genes and over-express secretory lineage marker genes resulting in lineage skewed differentiation into the secretory lineage and strong upregulation of MHC class II antigens in the aged intestinal epithelium. Mechanistically, we identified an increase in proinflammatory cells in the lamina propria as the main source of elevated interferon gamma (IFNγ) in the aged intestine, that leads to the induction of Stat1 activity in intestinal stem cells thus priming the aberrant differentiation and elevated antigen presentation in epithelial cells. Of note, systemic inhibition of IFNγ-signaling completely reverses these aging phenotypes and reinstalls regenerative capacity of the aged intestinal epithelium.
Collapse
Affiliation(s)
- Omid Omrani
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Anna Krepelova
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
- Department of Life Sciences and Systems Biology, University of Turin, Torino, Italy
- Molecular Biotechnology Center, University of Turin, Torino, Italy
| | | | - Dovydas Sirvinskas
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Jing Lu
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | | | - George Garside
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Seerat Bajwa
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Susanne Reinhardt
- Dresden-concept Genome Center, c/o Center for Regenerative Therapies Dresden (CRTD), Dresden, Germany
| | - Lisa Adam
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Sandra Käppel
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Nadia Ducano
- Department of Life Sciences and Systems Biology, University of Turin, Torino, Italy
- Molecular Biotechnology Center, University of Turin, Torino, Italy
| | - Daniela Donna
- Department of Life Sciences and Systems Biology, University of Turin, Torino, Italy
- Molecular Biotechnology Center, University of Turin, Torino, Italy
| | - Alessandro Ori
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
| | - Salvatore Oliviero
- Department of Life Sciences and Systems Biology, University of Turin, Torino, Italy
- Molecular Biotechnology Center, University of Turin, Torino, Italy
| | | | - Francesco Neri
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany.
- Department of Life Sciences and Systems Biology, University of Turin, Torino, Italy.
- Molecular Biotechnology Center, University of Turin, Torino, Italy.
| |
Collapse
|
47
|
Jin Y, Wei C, Huang X, Zhang D, Zhang L, Li X. Bioinformatics Analysis and Experimental Verification of Exercise for Aging Mice in Different Brain Regions Based on Transcriptome Sequencing. Life (Basel) 2023; 13:1988. [PMID: 37895370 PMCID: PMC10608440 DOI: 10.3390/life13101988] [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: 08/17/2023] [Revised: 09/20/2023] [Accepted: 09/27/2023] [Indexed: 10/29/2023] Open
Abstract
PURPOSE Physical exercise mitigates the effects of aging and cognitive decline. However, the precise neurobiological mechanisms underlying this phenomenon remain unclear. The primary aim of this study was to investigate the protective effect of exercise on age-related memory deficits in the prefrontal cortex (PFC) and hippocampus using bioinformatic analysis and biochemical verification. METHODS Young and aging mice were subjected to natural feeding or treadmill exercise (12 m/min, 8 weeks). Cognitive function was accessed using the Barnes maze and novel object recognition. Bioinformatic analysis was performed to identify co-expressed genes in different groups and brain regions. The selected genes and pathways were validated using RT-qPCR. RESULTS Regular exercise significantly ameliorated age-related cognitive deficits. Four up-regulated targets (Ifi27l2a, Irf7, Oas1b, Ifit1) and one down-regulation (Septin2) were reversed by exercise, demonstrating the underlying mechanisms of cognitive functions induced by aging with exercise in the hippocampus and PFC. The Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses indicated that the NOD-like receptor signaling pathway was inhibited in the neuroinflammation effects of exercise in aging mice in both brain regions. CONCLUSION Exercise enhances age-related learning and memory deficits. This beneficial effect may be attributed to the changes in five up/down-regulated genes and the NOD-like receptor signaling pathway in both the hippocampus and PFC. These findings establish the modulation of neuroinflammation as a pivotal molecular mechanism supporting exercise intervention in the brain aging process.
Collapse
Affiliation(s)
- Yu Jin
- School of Sport Medicine and Health, Chengdu Sport University, Chengdu 610041, China; (Y.J.); (C.W.); (X.H.); (D.Z.)
| | - Changling Wei
- School of Sport Medicine and Health, Chengdu Sport University, Chengdu 610041, China; (Y.J.); (C.W.); (X.H.); (D.Z.)
| | - Xiaohan Huang
- School of Sport Medicine and Health, Chengdu Sport University, Chengdu 610041, China; (Y.J.); (C.W.); (X.H.); (D.Z.)
| | - Deman Zhang
- School of Sport Medicine and Health, Chengdu Sport University, Chengdu 610041, China; (Y.J.); (C.W.); (X.H.); (D.Z.)
| | - Li Zhang
- Joint International Research Laboratory of CNS Regeneration, Guangdong-Hong Kong-Macau Institute of CNS Regeneration, Jinan University, Guangzhou 510632, China;
| | - Xue Li
- School of Sport Medicine and Health, Chengdu Sport University, Chengdu 610041, China; (Y.J.); (C.W.); (X.H.); (D.Z.)
| |
Collapse
|
48
|
Fiannaca A, La Rosa M, La Paglia L, Gaglio S, Urso A. GOWDL: gene ontology-driven wide and deep learning model for cell typing of scRNA-seq data. Brief Bioinform 2023; 24:bbad332. [PMID: 37756593 PMCID: PMC10530315 DOI: 10.1093/bib/bbad332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/17/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023] Open
Abstract
Single-cell RNA-sequencing (scRNA-seq) allows for obtaining genomic and transcriptomic profiles of individual cells. That data make it possible to characterize tissues at the cell level. In this context, one of the main analyses exploiting scRNA-seq data is identifying the cell types within tissue to estimate the quantitative composition of cell populations. Due to the massive amount of available scRNA-seq data, automatic classification approaches for cell typing, based on the most recent deep learning technology, are needed. Here, we present the gene ontology-driven wide and deep learning (GOWDL) model for classifying cell types in several tissues. GOWDL implements a hybrid architecture that considers the functional annotations found in Gene Ontology and the marker genes typical of specific cell types. We performed cross-validation and independent external testing, comparing our algorithm with 12 other state-of-the-art predictors. Classification scores demonstrated that GOWDL reached the best results over five different tissues, except for recall, where we got about 92% versus 97% of the best tool. Finally, we presented a case study on classifying immune cell populations in breast cancer using a hierarchical approach based on GOWDL.
Collapse
Affiliation(s)
- Antonino Fiannaca
- ICAR-CNR, National Research Council of Italy, Via Ugo La Malfa 153, 90146, Palermo, Italy
| | - Massimo La Rosa
- ICAR-CNR, National Research Council of Italy, Via Ugo La Malfa 153, 90146, Palermo, Italy
| | - Laura La Paglia
- ICAR-CNR, National Research Council of Italy, Via Ugo La Malfa 153, 90146, Palermo, Italy
| | - Salvatore Gaglio
- ICAR-CNR, National Research Council of Italy, Via Ugo La Malfa 153, 90146, Palermo, Italy
- Dipartimento di Ingegneria, Università degli studi di Palermo, Viale Delle Scienze, ed. 6, 90128, Palermo, Italy
| | - Alfonso Urso
- ICAR-CNR, National Research Council of Italy, Via Ugo La Malfa 153, 90146, Palermo, Italy
| |
Collapse
|
49
|
dos Santos C, Shrestha S, Cottam M, Perkins G, Lev-Ram V, Roy B, Acree C, Kim KY, Deerinck T, Cutler M, Dean D, Cartailler JP, MacDonald PE, Hetzer M, Ellisman M, Drigo RAE. Caloric restriction promotes beta cell longevity and delays aging and senescence by enhancing cell identity and homeostasis mechanisms. RESEARCH SQUARE 2023:rs.3.rs-3311459. [PMID: 37790446 PMCID: PMC10543285 DOI: 10.21203/rs.3.rs-3311459/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Caloric restriction (CR) extends organismal lifespan and health span by improving glucose homeostasis mechanisms. How CR affects organellar structure and function of pancreatic beta cells over the lifetime of the animal remains unknown. Here, we used single nucleus transcriptomics to show that CR increases the expression of genes for beta cell identity, protein processing, and organelle homeostasis. Gene regulatory network analysis link this transcriptional phenotype to transcription factors involved in beta cell identity (Mafa) and homeostasis (Atf6). Imaging metabolomics further demonstrates that CR beta cells are more energetically competent. In fact, high-resolution light and electron microscopy indicates that CR reduces beta cell mitophagy and increases mitochondria mass, increasing mitochondrial ATP generation. Finally, we show that long-term CR delays the onset of beta cell aging and senescence to promote longevity by reducing beta cell turnover. Therefore, CR could be a feasible approach to preserve compromised beta cells during aging and diabetes.
Collapse
Affiliation(s)
- Cristiane dos Santos
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| | - Shristi Shrestha
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| | - Matthew Cottam
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| | - Guy Perkins
- National Center for Imaging and Microscopy Research, University of California San Diego, La Jolla, CA USA
| | - Varda Lev-Ram
- University of California San Diego, Department of Pharmacology, School of Medicine. La Jolla, CA USA
| | - Birbickram Roy
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Canada
| | - Christopher Acree
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| | - Keun-Young Kim
- National Center for Imaging and Microscopy Research, University of California San Diego, La Jolla, CA USA
| | - Thomas Deerinck
- National Center for Imaging and Microscopy Research, University of California San Diego, La Jolla, CA USA
| | - Melanie Cutler
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| | - Danielle Dean
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| | | | - Patrick E. MacDonald
- Department of Pharmacology and Alberta Diabetes Institute, University of Alberta, Edmonton, Canada
| | - Martin Hetzer
- Institute of Science and Technology Austria (ISTA), Vienna, Austria
| | - Mark Ellisman
- National Center for Imaging and Microscopy Research, University of California San Diego, La Jolla, CA USA
| | - Rafael Arrojo e Drigo
- Vanderbilt University, Department of Molecular Physiology and Biophysics, Nashville, TN USA
| |
Collapse
|
50
|
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: 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: 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.
Collapse
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.
| |
Collapse
|