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Khanal S, Liu Y, Bamidele AO, Wixom AQ, Washington AM, Jalan-Sakrikar N, Cooper SA, Vuckovic I, Zhang S, Zhong J, Johnson KL, Charlesworth MC, Kim I, Yeon Y, Yoon S, Noh YK, Meroueh C, Timbilla AA, Yaqoob U, Gao J, Kim Y, Lucien F, Huebert RC, Hay N, Simons M, Shah VH, Kostallari E. Glycolysis in hepatic stellate cells coordinates fibrogenic extracellular vesicle release spatially to amplify liver fibrosis. SCIENCE ADVANCES 2024; 10:eadn5228. [PMID: 38941469 PMCID: PMC11212729 DOI: 10.1126/sciadv.adn5228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 05/24/2024] [Indexed: 06/30/2024]
Abstract
Liver fibrosis is characterized by the activation of perivascular hepatic stellate cells (HSCs), the release of fibrogenic nanosized extracellular vesicles (EVs), and increased HSC glycolysis. Nevertheless, how glycolysis in HSCs coordinates fibrosis amplification through tissue zone-specific pathways remains elusive. Here, we demonstrate that HSC-specific genetic inhibition of glycolysis reduced liver fibrosis. Moreover, spatial transcriptomics revealed a fibrosis-mediated up-regulation of EV-related pathways in the liver pericentral zone, which was abrogated by glycolysis genetic inhibition. Mechanistically, glycolysis in HSCs up-regulated the expression of EV-related genes such as Ras-related protein Rab-31 (RAB31) by enhancing histone 3 lysine 9 acetylation on the promoter region, which increased EV release. Functionally, these glycolysis-dependent EVs increased fibrotic gene expression in recipient HSC. Furthermore, EVs derived from glycolysis-deficient mice abrogated liver fibrosis amplification in contrast to glycolysis-competent mouse EVs. In summary, glycolysis in HSCs amplifies liver fibrosis by promoting fibrogenic EV release in the hepatic pericentral zone, which represents a potential therapeutic target.
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Affiliation(s)
- Shalil Khanal
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
| | - Yuanhang Liu
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Alexander Q. Wixom
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Alexander M. Washington
- Biochemistry and Molecular Biology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Nidhi Jalan-Sakrikar
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
| | - Shawna A. Cooper
- Biochemistry and Molecular Biology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Ivan Vuckovic
- Metabolomics Core, Mayo Clinic, Rochester, MN 55905, USA
| | - Song Zhang
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Jun Zhong
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Iljung Kim
- Department of Computer Science, Hanyang University, Seoul 04763, Republic of South Korea
| | - Yubin Yeon
- Department of Computer Science, Hanyang University, Seoul 04763, Republic of South Korea
| | - Sangwoong Yoon
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul 02455, Republic of South Korea
| | - Yung-Kyun Noh
- Department of Computer Science, Hanyang University, Seoul 04763, Republic of South Korea
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul 02455, Republic of South Korea
| | - Chady Meroueh
- Department of Pathology, Division of Anatomic Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Abdul Aziz Timbilla
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Medical Biochemistry, Faculty of Medicine, Hradec Kralove, Charles University, Hradec Kralove, Czech Republic
| | - Usman Yaqoob
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
| | - Jinhang Gao
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
- Lab of Gastroenterology and Hepatology, State Key Laboratory of Biotherapy; Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China
| | - Yohan Kim
- Department of Urology, Mayo Clinic, Rochester, MN 55905, USA
| | - Fabrice Lucien
- Department of Urology, Mayo Clinic, Rochester, MN 55905, USA
| | - Robert C. Huebert
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
| | - Nissim Hay
- Department of Biochemistry and Molecular Genetics, College of Medicine, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Michael Simons
- Cardiovascular Research Center, Yale University, New Haven, CI 06510, USA
| | - Vijay H. Shah
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
| | - Enis Kostallari
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN 55905, USA
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Santos AA, Delgado TC, Marques V, Ramirez-Moncayo C, Alonso C, Vidal-Puig A, Hall Z, Martínez-Chantar ML, Rodrigues CM. Spatial metabolomics and its application in the liver. Hepatology 2024; 79:1158-1179. [PMID: 36811413 PMCID: PMC11020039 DOI: 10.1097/hep.0000000000000341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/05/2023] [Indexed: 02/24/2023]
Abstract
Hepatocytes work in highly structured, repetitive hepatic lobules. Blood flow across the radial axis of the lobule generates oxygen, nutrient, and hormone gradients, which result in zoned spatial variability and functional diversity. This large heterogeneity suggests that hepatocytes in different lobule zones may have distinct gene expression profiles, metabolic features, regenerative capacity, and susceptibility to damage. Here, we describe the principles of liver zonation, introduce metabolomic approaches to study the spatial heterogeneity of the liver, and highlight the possibility of exploring the spatial metabolic profile, leading to a deeper understanding of the tissue metabolic organization. Spatial metabolomics can also reveal intercellular heterogeneity and its contribution to liver disease. These approaches facilitate the global characterization of liver metabolic function with high spatial resolution along physiological and pathological time scales. This review summarizes the state of the art for spatially resolved metabolomic analysis and the challenges that hinder the achievement of metabolome coverage at the single-cell level. We also discuss several major contributions to the understanding of liver spatial metabolism and conclude with our opinion on the future developments and applications of these exciting new technologies.
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Affiliation(s)
- André A. Santos
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
| | - Teresa C. Delgado
- Liver Disease Lab, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance, Derio, Bizkaia, Spain
- Congenital Metabolic Disorders, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Vanda Marques
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
| | - Carmen Ramirez-Moncayo
- Institute of Clinical Sciences, Imperial College London, London, UK
- MRC London Institute of Medical Sciences, London, UK
| | | | - Antonio Vidal-Puig
- MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Centro Investigation Principe Felipe, Valencia, Spain
| | - Zoe Hall
- Division of Systems Medicine, Imperial College London, London, UK
| | - María Luz Martínez-Chantar
- Liver Disease Lab, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance, Derio, Bizkaia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Carlos III National Health Institute, Madrid, Spain
| | - Cecilia M.P. Rodrigues
- Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Lisbon, Portugal
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Proteomic analysis of hepatic effects of phenobarbital in mice with humanized liver. Arch Toxicol 2022; 96:2739-2754. [PMID: 35881160 PMCID: PMC9352639 DOI: 10.1007/s00204-022-03338-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/13/2022] [Indexed: 11/25/2022]
Abstract
Activation of the constitutive androstane receptor (CAR) may induce adaptive but also adverse effects in rodent liver, including the induction of drug-metabolizing enzymes, transient hepatocellular proliferation, and promotion of liver tumor growth. Human relevance of CAR-related adverse hepatic effects is controversially debated. Here, we used the chimeric FRG-KO mouse model with livers largely repopulated by human hepatocytes, in order to study human hepatocytes and their response to treatment with the model CAR activator phenobarbital (PB) in vivo. Mice received an intraperitoneal injection with 50 mg/kg body weight PB or saline, and were sacrificed after 72–144 h. Non-repopulated FRG-KO mice were used as additional control. Comprehensive proteomics datasets were generated by merging data obtained by targeted as well as non-targeted proteomics approaches. For the first time, a novel proteomics workflow was established to comparatively analyze the effects of PB on human and murine proteins within one sample. Analysis of merged proteome data sets and bioinformatics data mining revealed comparable responses in murine and human hepatocytes with respect to nuclear receptor activation and induction of xenobiotic metabolism. By contrast, activation of MYC, a key regulator of proliferation, was predicted only for mouse but not human hepatocytes. Analyses of 5-bromo-2′-deoxyuridine incorporation confirmed this finding. In summary, this study for the first time presents a comprehensive proteomic analysis of CAR-dependent effects in human and mouse hepatocytes from humanized FRG-KO mice. The data support the hypothesis that PB does induce adaptive metabolic responses, but not hepatocellular proliferation in human hepatocytes in vivo.
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