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Kesharwani D, Brown AC. Navigating the Adipocyte Precursor Niche: Cell-Cell Interactions, Regulatory Mechanisms and Implications for Adipose Tissue Homeostasis. JOURNAL OF CELLULAR SIGNALING 2024; 5:65-86. [PMID: 38826152 PMCID: PMC11141760 DOI: 10.33696/signaling.5.114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Support for stem cell self-renewal and differentiation hinges upon the intricate microenvironment termed the stem cell 'niche'. Within the adipose tissue stem cell niche, diverse cell types, such as endothelial cells, immune cells, mural cells, and adipocytes, intricately regulate the function of adipocyte precursors. These interactions, whether direct or indirect, play a pivotal role in governing the balance between self-renewal and differentiation of adipocyte precursors into adipocytes. The mechanisms orchestrating the maintenance and coordination of this niche are still in the early stages of comprehension, despite their crucial role in regulating adipose tissue homeostasis. The complexity of understanding adipocyte precursor renewal and differentiation is amplified due to the challenges posed by the absence of suitable surface receptors for identification, limitations in creating optimal ex vivo culture conditions for expansion and constraints in conducting in vivo studies. This review delves into the current landscape of knowledge surrounding adipocyte precursors within the adipose stem cell niche. We will review the identification of adipocyte precursors, the cell-cell interactions they engage in, the factors influencing their renewal and commitment toward adipocytes and the transformations they undergo during instances of obesity.
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Affiliation(s)
- Devesh Kesharwani
- Center for Molecular Medicine, MaineHealth Institute for Research, 81 Research Drive, Scarborough, ME 04074, USA
| | - Aaron C. Brown
- Center for Molecular Medicine, MaineHealth Institute for Research, 81 Research Drive, Scarborough, ME 04074, USA
- School of Biomedical Sciences and Engineering, The University of Maine, Orono, Maine 04469, USA
- Tufts University School of Medicine, 145 Harrison Ave, Boston, MA 02111, USA
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Madsen S, Nelson ME, Deshpande V, Humphrey SJ, Cooke KC, Howell A, Diaz-Vegas A, Burchfield JG, Stöckli J, James DE. Deep Proteome Profiling of White Adipose Tissue Reveals Marked Conservation and Distinct Features Between Different Anatomical Depots. Mol Cell Proteomics 2023; 22:100508. [PMID: 36787876 PMCID: PMC10014311 DOI: 10.1016/j.mcpro.2023.100508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 01/26/2023] [Accepted: 02/08/2023] [Indexed: 02/16/2023] Open
Abstract
White adipose tissue is deposited mainly as subcutaneous adipose tissue (SAT), often associated with metabolic protection, and abdominal/visceral adipose tissue, which contributes to metabolic disease. To investigate the molecular underpinnings of these differences, we conducted comprehensive proteomics profiling of whole tissue and isolated adipocytes from these two depots across two diets from C57Bl/6J mice. The adipocyte proteomes from lean mice were highly conserved between depots, with the major depot-specific differences encoded by just 3% of the proteome. Adipocytes from SAT (SAdi) were enriched in pathways related to mitochondrial complex I and beiging, whereas visceral adipocytes (VAdi) were enriched in structural proteins and positive regulators of mTOR presumably to promote nutrient storage and cellular expansion. This indicates that SAdi are geared toward higher catabolic activity, while VAdi are more suited for lipid storage. By comparing adipocytes from mice fed chow or Western diet (WD), we define a core adaptive proteomics signature consisting of increased extracellular matrix proteins and decreased fatty acid metabolism and mitochondrial Coenzyme Q biosynthesis. Relative to SAdi, VAdi displayed greater changes with WD including a pronounced decrease in mitochondrial proteins concomitant with upregulation of apoptotic signaling and decreased mitophagy, indicating pervasive mitochondrial stress. Furthermore, WD caused a reduction in lipid handling and glucose uptake pathways particularly in VAdi, consistent with adipocyte de-differentiation. By overlaying the proteomics changes with diet in whole adipose tissue and isolated adipocytes, we uncovered concordance between adipocytes and tissue only in the visceral adipose tissue, indicating a unique tissue-specific adaptation to sustained WD in SAT. Finally, an in-depth comparison of isolated adipocytes and 3T3-L1 proteomes revealed a high degree of overlap, supporting the utility of the 3T3-L1 adipocyte model. These deep proteomes provide an invaluable resource highlighting differences between white adipose depots that may fine-tune their unique functions and adaptation to an obesogenic environment.
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Affiliation(s)
- Søren Madsen
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Marin E Nelson
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Vinita Deshpande
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Sean J Humphrey
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Kristen C Cooke
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Anna Howell
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Alexis Diaz-Vegas
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - James G Burchfield
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - Jacqueline Stöckli
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia
| | - David E James
- School of Life and Environmental Sciences, University of Sydney, Camperdown, New South Wales, Australia; Charles Perkins Centre, University of Sydney, Camperdown, New South Wales, Australia; Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia.
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Zeng J, Li J, Liu S, Yang Z, Zhong Y, Chen X, Li G, Li J. Lipidome disturbances in preadipocyte differentiation associated with bisphenol A and replacement bisphenol S exposure. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 753:141949. [PMID: 32891999 DOI: 10.1016/j.scitotenv.2020.141949] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 08/22/2020] [Accepted: 08/22/2020] [Indexed: 06/11/2023]
Abstract
Bisphenol S (BPS) is the major substitute for the production of bisphenol A (BPA)-free products and detected in both food and environment. Although the relationship between BPA exposure and increased risk of obesity and diabetes has been noted, the potential influence of BPS is not fully understood. Herein, a non-targeted lipidomic study was performed to explore BPA/BPS exposure actions using the 3T3-L1 preadipocyte differentiation model, and revealed the comprehensive lipidome disturbance induced by either BPA or BPS exposure at different doses of 0.01, 1 and 100 μM. BPA was more potent than BPS in disturbance of lipid metabolism. A considerable similarity of BPS exposure to BPA was discovered. The key lipid remodeling in response to exposure was found to involve the cardiolipins, phosphatidylglycerols and fatty acids metabolic pathways, providing novel clues of potential mechanism in which both BPA and BPS exposure could be associated with increased risk of insulin resistance. Our study supplies the perspective into the lipidome response to environmental stress induced by BPA/BPS, and shows that BPA-free products are not necessarily safer. Substitution of BPA by its structural analog BPS should be therefore performed with caution.
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Affiliation(s)
- Jun Zeng
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China; Xiamen Key Laboratory of Marine Functional Food, Xiamen 361021, China.
| | - Junli Li
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China
| | - Sishangyu Liu
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China
| | - Zhiqiang Yang
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China
| | - Yue Zhong
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China
| | - Xiaomei Chen
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China
| | - Guiling Li
- College of Food and Biological Engineering, Jimei University, Xiamen 361021, China; Xiamen Key Laboratory of Marine Functional Food, Xiamen 361021, China
| | - Jia Li
- Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China.
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Yu P, Li J, Deng SP, Zhang F, Grozdanov PN, Chin EWM, Martin SD, Vergnes L, Islam MS, Sun D, LaSalle JM, McGee SL, Goh E, MacDonald CC, Jin P. Integrated analysis of a compendium of RNA-Seq datasets for splicing factors. Sci Data 2020; 7:178. [PMID: 32546682 PMCID: PMC7297722 DOI: 10.1038/s41597-020-0514-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 03/13/2020] [Indexed: 02/05/2023] Open
Abstract
A vast amount of public RNA-sequencing datasets have been generated and used widely to study transcriptome mechanisms. These data offer precious opportunity for advancing biological research in transcriptome studies such as alternative splicing. We report the first large-scale integrated analysis of RNA-Seq data of splicing factors for systematically identifying key factors in diseases and biological processes. We analyzed 1,321 RNA-Seq libraries of various mouse tissues and cell lines, comprising more than 6.6 TB sequences from 75 independent studies that experimentally manipulated 56 splicing factors. Using these data, RNA splicing signatures and gene expression signatures were computed, and signature comparison analysis identified a list of key splicing factors in Rett syndrome and cold-induced thermogenesis. We show that cold-induced RNA-binding proteins rescue the neurite outgrowth defects in Rett syndrome using neuronal morphology analysis, and we also reveal that SRSF1 and PTBP1 are required for energy expenditure in adipocytes using metabolic flux analysis. Our study provides an integrated analysis for identifying key factors in diseases and biological processes and highlights the importance of public data resources for identifying hypotheses for experimental testing.
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Affiliation(s)
- Peng Yu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
- Medical Big Data Center, Sichuan University, Chengdu, China.
| | - Jin Li
- Center for Epigenetics & Disease Prevention, Institute of Biosciences and Technology, College of Medicine, Texas A&M University, Houston, TX, 77030, USA
| | - Su-Ping Deng
- School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009, China
| | - Feiran Zhang
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Petar N Grozdanov
- Department of Cell Biology & Biochemistry, Texas Tech University Health Sciences Center, Lubbock, Texas, 79430, USA
| | - Eunice W M Chin
- Neuroscience Academic Clinical Programme, Duke-NUS Medical School, NA, Singapore
| | - Sheree D Martin
- Metabolic Reprogramming Laboratory, Metabolic Research Unit, School of Medicine and Centre for Molecular and Medical Research, Deakin University, Geelong, Victoria, Australia
| | - Laurent Vergnes
- Department of Human Genetics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, USA
| | - M Saharul Islam
- Department of Medical Microbiology and Immunology, Genome Center, and MIND Institute, University of California Davis, Davis, CA, USA
| | - Deqiang Sun
- Center for Epigenetics & Disease Prevention, Institute of Biosciences and Technology, College of Medicine, Texas A&M University, Houston, TX, 77030, USA
| | - Janine M LaSalle
- Department of Medical Microbiology and Immunology, Genome Center, and MIND Institute, University of California Davis, Davis, CA, USA
| | - Sean L McGee
- Metabolic Reprogramming Laboratory, Metabolic Research Unit, School of Medicine and Centre for Molecular and Medical Research, Deakin University, Geelong, Victoria, Australia
| | - Eyleen Goh
- Neuroscience Academic Clinical Programme, Duke-NUS Medical School, NA, Singapore
| | - Clinton C MacDonald
- Department of Cell Biology & Biochemistry, Texas Tech University Health Sciences Center, Lubbock, Texas, 79430, USA
| | - Peng Jin
- Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
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