The Role of Overexpressed Apolipoprotein AV in Insulin-Resistant Hepatocytes

Total Page:16

File Type:pdf, Size:1020Kb

The Role of Overexpressed Apolipoprotein AV in Insulin-Resistant Hepatocytes Hindawi BioMed Research International Volume 2020, Article ID 3268505, 13 pages https://doi.org/10.1155/2020/3268505 Research Article The Role of Overexpressed Apolipoprotein AV in Insulin-Resistant Hepatocytes Wang Zhao,1 Yaqiong Liu,1 Xiaobo Liao,2 and Shuiping Zhao 1 1Department of Cardiovascular Medicine, e Second Xiangya Hospital, Central South University, No. 139 Middle Renmin Road, Changsha, Hunan 410011, China 2Department of Cardiovascular Surgery, e Second Xiangya Hospital, Central South University, No. 139 Middle Renmin Road, Changsha, Hunan 410011, China Correspondence should be addressed to Shuiping Zhao; [email protected] Received 31 January 2019; Revised 16 July 2019; Accepted 16 August 2019; Published 21 April 2020 Academic Editor: Kui Li Copyright © 2020 Wang Zhao et al. *is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In this paper, we sought to explore the relationship between apolipoprotein AV (APOAV) overexpression and insulin resistance in hepatocytes. *e insulin-resistant HepG2 cell model was constructed, and then, APOAV-overexpressed HepG2 cells (B-M) were induced by infecting with a recombinant adenovirus vector. Microarray data were developed from B-M samples compared with negative controls (A-con), and the microarray data were analyzed by bioinformatic methods. APOAV-overexpression induced 313 upregulated genes and 563 downregulated ones in B-M sample. *e differentially expressed genes (DEGs) were significantly classified in fat digestion and absorption pathway. Protein-protein interaction network was constructed, and AGTR1 (angiotensin II receptor type 1) and P2RY2 (purinergic receptor P2Y, G-protein coupled 2) were found to be the significant nodes closely related with G-protein related signaling. Additionally, overexpression of APOAV could change the expression of Glut4 and release the insulin resistance of hepatic cells. *us, APOAV overexpression may prevent the insulin resistance in liver cells by mediating the genes such as AGTR1 and P2RY2. 1. Introduction lipid metabolism [6, 7]. APOAV is mainly expressed in liver and closely associated with high-density lipoprotein [8]. Insulin resistance has become an increasingly common Moreover, APOAV is also found to participate in the metabolic syndrome in people around the word. *e main metabolism of triglycerides by stimulating hydrolysis of understanding of the mechanism for insulin resistance is the triglycerides, reducing the lipoprotein production rate, and glycometabolism disorder in liver [1]. Insulin resistance facilitating clearance of triglyceride-rich lipoprotein [9]. A results in excessive glucose consumption in liver, which previous study suggests that APOAV is downregulated in contributes to the development of hyperglycemia [2]. In insulin-treated mice and the expression of APOAV a con- addition, hyperglycemia is frequently associated with met- tributor for hypertriglyceridemia [10]. *e decreased ex- abolic syndromes such as hypertension, coronary heart pression APOAV is involved in insulin resistance-related disease, and diabetes [3, 4]. Type 2 diabetes (T2D) is a hypertriglyceridemia [6]. APOAV seems to be closely related common metabolic disorder that characterizes high blood with insulin resistance in diabetics, but whether the over- sugar, insulin deficiency, and insulin resistance. T2D (non- expression of APOAV could prevent insulin resistance needs insulin-dependent) is the risk for cardiovascular disease that to be further determined. is the main cause for death of diabetes patients [5]. Microarray technology has been widely used to generate Recently, apolipoprotein AV (APOAV), also served as the gene expression data on a genomic scale [11]. In this the APOA5, has been found to be a novel apolipoprotein and paper, we performed the microarray analysis for the human to play a key role in the processes of insulin resistance and hepatoma (HepG2) cells to discover the differentially 2 BioMed Research International expressed genes (DEGs) induced by APOAV overexpression. then transferred to a polyvinylidene difluoride (PVDF) HepG2 cells, which are characterized by the common membrane. After blocked with 5% skimmed milk for 1 h, the physiological function in glucose metabolism with normal membrane was incubated with primary antibodies hepatic cells [12], were used in this study. *erefore, in the (APOAV5, 1 :1000; beta actin, 1 :1000) at 4°C overnight. present study, we sought to explore the potential mechanism Following washing with TBST for 3 times, the membrane of relationship between APOAV expression and insulin was incubated with secondary antibody (antirabbit IgG- resistance in hepatocytes. HRP, 1 : 5000; antimouse IgG-HRP, 1 : 5000) for 2 h at room temperature. Finally, the proteins were visualized using the 2. Materials and Methods ECL chemiluminescence reagent. 2.1. Insulin-Resistant HepG2 Cell Model Construction. 2.3. Recombinant Plasmid Vector with APOAV. *e APOAV HepG2 cell lines (Cell Culture Center of Peking Union gene was amplified by PCR with the primers, such as 5′-ACA ° Medical Science, Beijing, China) were cultured at 37 C in CGGATCCATGGCAAGCATGGCTGCCGT-3′ (forward) Dulbecco’s modified eagle medium (DMEM) supplemented and 5′-ACACGAATTCTCAGGGGTCCCCCAGATG-3′ with 10% (v/v) FBS (fetal bovine serum) and 100 IU peni- (reverse). After the plasmid pHBAd-MCMV-GFP was cillin/streptomycin/amphotericin in a humidified 5% CO2 digested with BamH1 and EcoR1, the recombinant plasmid atmosphere. When entering the logarithmic phase, the cells vector was constructed by connecting with APOAV at 4°C were washed by PBS, and then digested with trypsin enzyme. overnight. *e positive recombinant clone was named as After the cells turned round, cell suspension was put into pHBAd-MCMV-APOAV-GFP. *e expressions of APOAV 15 ml centrifuge tube and centrifuged at 1000 rpm for 3 min 3 and GFP were regulated by cytomegalovirus (CMV) and inoculated in 96-well plates at the density of 5 ×10 cells/ promoter. cm2. In order obtain the insulin-resistant HepG2 cell model, the cells were treated with insulin at a series of concentration 2.4. Insulin-Resistant HepG2 Cells Infection by Recombinant gradients. *e insulin-resistant HepG2 cell model was in- Adenovirus. HEK293 was the common cell for packing the duced as described previously [13]. Briefly, HepG2 cells were recombinant adenoviruses because of its E1 genes. To subjected to 24h-culture of 5 ×10−5, 5 ×10−6, 5 ×10−7, and generate recombinant adenovirus vectors with APOAV 5 ×10−8 mol/L bovine insulin, followed by incubating in expression, the pHBAd-MCMV-APOAV-GFP and adeno- 10−9 mol/L insulin for 24 h. And to determine whether the virus skeleton plasmid vector of pHBAd-BHG were coin- insulin model was successfully constructed, glucose uptake fected into HEK293 cells with the lipofectamine 2000 kit rate and liver glycogen synthesis were measured. For glucose following the manufacturer’s instruction. After 6 h trans- uptake rate measurement, the supernatant was absorbed into formation, the recombinant adenoviruses were harvested. a 15 mL centrifuge tube at 1500 rpm/6 min, and transferred *en, the insulin-resistant HepG2 cells were cultured and to a 1.5 ml EP tube. After the supernatant was diluted 6 times infected with the recombinant adenovirus vector for 48 h. with distilled water, and the glucose uptake rate was de- *e successful infection by recombinant adenovirus was termined by the urine glucose assay kit-oxidase assay determined, when the expression of GFP was observed by according to the manufacturer’s instructions. Glucose up- fluorescence microscopy. take rate � (preinduced glucose concentration-postinduced glucose concentration)/preinduced glucose concentration. 2.5. RNA Isolation. Total RNA of insulin-resistant HepG2 For glycogen synthesis measurement, (1) the cells were cells with APOAV overexpression (B-M) and negative digested with trypsin, centrifuged (3000 g, 5 min) and controls (A-con) was isolated using TRIzol reagent (Invi- weighed; (2) hydrolysis: sample weight (mg): lye volume trogen, Carlsbad, CA) according to the manufacturer’s (μL) � 1 : 3, boiled in boiling water for 20 min; (3) liver protocol. *e expected quality of RNA was determined by glycogen detection solution (1%); (4) the standard glucose measuring the absorbance ratios (A260/A280) between 1.8 solution: the standard glucose solution was prepared into 25, and 2.0 under the spectrophotometer. 12.5, 6.25, 3.125, and 1.5625 g/ml with distilled water; (5) OD620 nm value of each tube was measured; and (6) standard curve was drawn for calculating the liver glycogen 2.6. Microarray Analysis. *e RNA library was constructed concentration. by using the NEBNext ultra directional RNA library prep kit for illumina (New England Biolabs, Ipswich, MA, USA) following the manufacturer’s instruction. After the library 2.2. Western Blot Analysis. To determine the native APOAV quality was assessed by Aglient 2100 Bioanalyzer (Agilent expression in the induced model cells and insulin-resistant Technologies, Palo Alto, CA), the next-generation se- HepG2 cells infected by recombinant adenovirus, western quencing was performed based on the Illumina HiSeq4000 blot analysis was performed. Briefly, the cells were lysed in a platform (Illumina Inc., San Diego, CA). Read counts were radioimmunoprecipitation assay (RIPA) buffer supple- normalized by TMM (trimmed mean of M values) in the mented with for
Recommended publications
  • Supporting Online Material
    1 2 3 4 5 6 7 Supplementary Information for 8 9 Fractalkine-induced microglial vasoregulation occurs within the retina and is altered early in diabetic 10 retinopathy 11 12 *Samuel A. Mills, *Andrew I. Jobling, *Michael A. Dixon, Bang V. Bui, Kirstan A. Vessey, Joanna A. Phipps, 13 Ursula Greferath, Gene Venables, Vickie H.Y. Wong, Connie H.Y. Wong, Zheng He, Flora Hui, James C. 14 Young, Josh Tonc, Elena Ivanova, Botir T. Sagdullaev, Erica L. Fletcher 15 * Joint first authors 16 17 Corresponding author: 18 Prof. Erica L. Fletcher. Department of Anatomy & Neuroscience. The University of Melbourne, Grattan St, 19 Parkville 3010, Victoria, Australia. 20 Email: [email protected] ; Tel: +61-3-8344-3218; Fax: +61-3-9347-5219 21 22 This PDF file includes: 23 24 Supplementary text 25 Figures S1 to S10 26 Tables S1 to S7 27 Legends for Movies S1 to S2 28 SI References 29 30 Other supplementary materials for this manuscript include the following: 31 32 Movies S1 to S2 33 34 35 36 1 1 Supplementary Information Text 2 Materials and Methods 3 Microglial process movement on retinal vessels 4 Dark agouti rats were anaesthetized, injected intraperitoneally with rhodamine B (Sigma-Aldrich) to label blood 5 vessels and retinal explants established as described in the main text. Retinal microglia were labelled with Iba-1 6 and imaging performed on an inverted confocal microscope (Leica SP5). Baseline images were taken for 10 7 minutes, followed by the addition of PBS (10 minutes) and then either fractalkine or fractalkine + candesartan 8 (10 minutes) using concentrations outlined in the main text.
    [Show full text]
  • Angiopoietin 4 (ANGPT4) (NM 015985) Human Untagged Clone Product Data
    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC304373 Angiopoietin 4 (ANGPT4) (NM_015985) Human Untagged Clone Product data: Product Type: Expression Plasmids Product Name: Angiopoietin 4 (ANGPT4) (NM_015985) Human Untagged Clone Tag: Tag Free Symbol: ANGPT4 Synonyms: ANG3; ANG4 Vector: pCMV6-XL5 E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: None This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 3 Angiopoietin 4 (ANGPT4) (NM_015985) Human Untagged Clone – SC304373 Fully Sequenced ORF: >OriGene sequence for NM_015985 edited CAGGCAAGCCTGGCCACTGTTGGCTGCAGCAGGACATCCCAGGCACAGCCCCTAGGGCTC TGAGCAGACATCCCTCGCCATTGACACATCTTCAGATGCTCTCCCAGCTAGCCATGCTGC AGGGCAGCCTCCTCCTTGTGGTTGCCACCATGTCTGTGGCTCAACAGACAAGGCAGGAGG CGGATAGGGGCTGCGAGACACTTGTAGTCCAGCACGGCCACTGTAGCTACACCTTCTTGC TGCCCAAGTCTGAGCCCTGCCCTCCGGGGCCTGAGGTCTCCAGGGACTCCAACACCCTCC AGAGAGAATCACTGGCCAACCCACTGCACCTGGGGAAGTTGCCCACCCAGCAGGTGAAAC AGCTGGAGCAGGCACTGCAGAACAACACGCAGTGGCTGAAGAAGCTAGAGAGGGCCATCA AGACGATCTTGAGGTCGAAGCTGGAGCAGGTCCAGCAGCAAATGGCCCAGAATCAGACGG CCCCCATGCTAGAGCTGGGCACCAGCCTCCTGAACCAGACCACTGCCCAGATCCGCAAGC TGACCGACATGGAGGCTCAGCTCCTGAACCAGACATCAAGAATGGATGCCCAGATGCCAG AGACCTTTCTGTCCACCAACAAGCTGGAGAACCAGCTGCTGCTACAGAGGCAGAAGCTCC AGCAGCTTCAGGGCCAAAACAGCGCGCTCGAGAAGCGGTTGCAGGCCCTGGAGACCAAGC
    [Show full text]
  • Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients with Stable Coronary Heart Disease
    Supplementary Online Content Ganz P, Heidecker B, Hveem K, et al. Development and validation of a protein-based risk score for cardiovascular outcomes among patients with stable coronary heart disease. JAMA. doi: 10.1001/jama.2016.5951 eTable 1. List of 1130 Proteins Measured by Somalogic’s Modified Aptamer-Based Proteomic Assay eTable 2. Coefficients for Weibull Recalibration Model Applied to 9-Protein Model eFigure 1. Median Protein Levels in Derivation and Validation Cohort eTable 3. Coefficients for the Recalibration Model Applied to Refit Framingham eFigure 2. Calibration Plots for the Refit Framingham Model eTable 4. List of 200 Proteins Associated With the Risk of MI, Stroke, Heart Failure, and Death eFigure 3. Hazard Ratios of Lasso Selected Proteins for Primary End Point of MI, Stroke, Heart Failure, and Death eFigure 4. 9-Protein Prognostic Model Hazard Ratios Adjusted for Framingham Variables eFigure 5. 9-Protein Risk Scores by Event Type This supplementary material has been provided by the authors to give readers additional information about their work. Downloaded From: https://jamanetwork.com/ on 10/02/2021 Supplemental Material Table of Contents 1 Study Design and Data Processing ......................................................................................................... 3 2 Table of 1130 Proteins Measured .......................................................................................................... 4 3 Variable Selection and Statistical Modeling ........................................................................................
    [Show full text]
  • Genetic Heterogeneity, Therapeutic Hurdle Confronting Sorafenib and Immune Checkpoint Inhibitors in Hepatocellular Carcinoma
    cancers Review Genetic Heterogeneity, Therapeutic Hurdle Confronting Sorafenib and Immune Checkpoint Inhibitors in Hepatocellular Carcinoma Sara M. Atwa 1,2, Margarete Odenthal 3 and Hend M. El Tayebi 2,* 1 Pharmaceutical Biology Department, German University in Cairo, Cairo 11865, Egypt; [email protected] 2 Molecular Pharmacology Research Group, Department of Pharmacology and Toxicology, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo 11835, Egypt 3 Institute for Pathology, University Hospital Cologne, 50924 Cologne, Germany; [email protected] * Correspondence: [email protected] Simple Summary: Hepatocellular carcinoma (HCC) represents a worldwide health challenge, rank- ing globally as the third most common cause of cancer-related mortality. Current advancements in the HCC therapeutic armamentarium succeeded in challenging HCC conventional therapy. Systemic therapies including tyrosine kinase inhibitors and immune checkpoint inhibitors (ICIs) come at the forefront of novel HCC therapeutic modalities. However, emerging drug resistance remains an obstacle during HCC therapy. According to the ongoing genomic analysis of HCC, a complex mutational landscape lies behind HCC pathogenesis and hence, affects the response of the tumor to the applied therapy. This review aims at categorizing and summarizing the different resistance Citation: Atwa, S.M.; Odenthal, M.; mechanisms confronting tyrosine kinase inhibitors, represented by sorafenib, as well as ICIs, during M. El Tayebi, H. Genetic HCC therapy. In addition, giving an insight into how genomic heterogeneity can influence the Heterogeneity, Therapeutic Hurdle response of HCC to the aforementioned therapies. Confronting Sorafenib and Immune Checkpoint Inhibitors in Abstract: Despite the latest advances in hepatocellular carcinoma (HCC) screening and treatment Hepatocellular Carcinoma.
    [Show full text]
  • Molecular Analysis of Insulin Action Using High Throughput Genetic Screens
    Molecular analysis of insulin action using high throughput genetic screens Poh Sim Khoo Thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Garvan Institute of Medical Research University of New South Wales 31st March 2011 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name: Khoo First name: Poh Sim Other name/s: Abbreviation for degree as given in the University calendar: PhD School: St Vincent's Cllinical School Faculty:Medicine Title: Molecular analysis of insulin action using high throughput genetic screens Abstract 350 words maximum: (PLEASE TYPE) The insulin-stimulated uptake of glucose by muscle and adipose is vital for the maintenance of glucose homeostasis in the body. This uptake primarily occurs through the action of the insulin-regulatable glucose transporter GLUT4, which is rapidly translocated to the plasma membrane in response to the insulin signal. However, in the insulin resistant state, insulin is unable to effect a normal biological response in its target tissues, characterized by decreased glucose uptake as a result of defects in insulin signaling and attenuated GLUT4 translocation. Elucidating the molecular causes underlying insulin resistance is important for the development of therapeutics for this disease. Identifying the components involved in the propagation or regulation of insulin signaling is an important step in understanding insulin resistance. To date, the upstream components of the signaling pathway are well established, demonstrating the importance of the insulin receptor, IRS proteins and PI3K/Akt signaling axis in this process. As a result much work has focused on defects at the point of IRS in the development of insulin resistance.
    [Show full text]
  • And CD45+ Stromal Populations in Extra-Skeletal Tumors With
    RESEARCH ARTICLE Osterix-Cre marks distinct subsets of CD45- and CD45+ stromal populations in extra-skeletal tumors with pro- tumorigenic characteristics Biancamaria Ricci1, Eric Tycksen2, Hamza Celik3, Jad I Belle3, Francesca Fontana3, Roberto Civitelli4, Roberta Faccio1,5* 1Department of Orthopedics, Washington University School of Medicine, St. Louis, United States; 2Genome Technology Access Center, Department of Genetics, Washington University School of Medicine, St. Louis, United States; 3Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, United States; 4Department of Medicine, Division of Bone and Mineral Diseases, Washington University School of Medicine, St. Louis, United States; 5Shriners Children Hospital, St. Louis, United States Abstract Cancer-associated fibroblasts (CAFs) are a heterogeneous population of mesenchymal cells supporting tumor progression, whose origin remains to be fully elucidated. Osterix (Osx) is a marker of osteogenic differentiation, expressed in skeletal progenitor stem cells and bone-forming osteoblasts. We report Osx expression in CAFs and by using Osx-cre;TdTomato reporter mice we confirm the presence and pro-tumorigenic function of TdTOSX+ cells in extra-skeletal tumors. Surprisingly, only a minority of TdTOSX+ cells expresses fibroblast and osteogenic markers. The majority of TdTOSX+ cells express the hematopoietic marker CD45, have a genetic and phenotypic profile resembling that of tumor infiltrating myeloid and lymphoid populations, but with higher expression of lymphocytic immune suppressive genes. We find Osx transcript and Osx protein expression early during hematopoiesis, in subsets of hematopoietic stem cells and multipotent *For correspondence: progenitor populations. Our results indicate that Osx marks distinct tumor promoting CD45- and [email protected] CD45+ populations and challenge the dogma that Osx is expressed exclusively in cells of Competing interests: The mesenchymal origin.
    [Show full text]
  • Human Angiopoietin 4 / ANG4 / ANGPT4 Protein (His Tag)
    Human Angiopoietin 4 / ANG4 / ANGPT4 Protein (His Tag) Catalog Number: 10293-H07H General Information SDS-PAGE: Gene Name Synonym: AGP4; ANG-3; ANG4 Protein Construction: A DNA sequence encoding the human ANGPT4 (NP_068769.2) (Met282- Ile503) was expressed, with an N-terminal polyhistidine tag. Source: Human Expression Host: HEK293 Cells QC Testing Purity: > 80 % as determined by SDS-PAGE Endotoxin: < 1.0 EU per μg of the protein as determined by the LAL method Stability: Samples are stable for up to twelve months from date of receipt at -70 ℃ References Predicted N terminal: His 1.Grosios K, et al. (1999) Assignment of ANGPT4, ANGPT1, and ANGPT2 Molecular Mass: encoding angiopoietins 4, 1 and 2 to human chromosome bands 20p13, 8q22.3?q23 and 8p23.1, respectively, by in situ hybridization and radiation The recombinant human ANGPT4 comprises 242 amino acids and has a hybrid mapping. Cytogenet. Cell Genet. 84 (1-2): 118-20. 2.Yamakawa M, predicted molecular mass of 27.6 kDa. The apparent molecular mass of et al. (2004) Expression of angiopoietins in renal epithelial and clear cell the protein is approximately 38 kDa in SDS-PAGE under reducing carcinoma cells: regulation by hypoxia and participation in angiogenesis. conditions due to glycosylation. Am J Physiol Renal Physiol. 287 (4): 649-57. 3.Oliner J, et al. (2004) Formulation: Suppression of angiogenesis and tumor growth by selective inhibition of angiopoietin-2. Cancer Cell. 6 (5): 507-16. Lyophilized from sterile PBS, pH 7.4 Normally 5 % - 8 % trehalose, mannitol and 0.01% Tween80 are added as protectants before lyophilization.
    [Show full text]
  • Linkage to 20P13 Including the ANGPT4 Gene in Families With
    Journal of Human Genetics (2010) 55, 649–655 & 2010 The Japan Society of Human Genetics All rights reserved 1434-5161/10 $32.00 www.nature.com/jhg ORIGINAL ARTICLE Linkageto20p13includingtheANGPT4 gene in families with mixed Alzheimer’s disease and vascular dementia Anna Sille´n1, Jesper Brohede1, Lena Lilius1, Charlotte Forsell1, Jorge Andrade2,5, Jacob Odeberg2, Hayao Ebise3, Bengt Winblad1 and Caroline Graff1,4 This study aimed at identifying novel susceptibility genes for a mixed phenotype of Alzheimer’s disease and vascular dementia. Results from a genome scan showed strongest linkage to 20p13 in 18 families, and subsequent fine mapping was performed with both microsatellites and single-nucleotide polymorphisms in 18 selected candidate transcripts in an extended sample set of 30 families. The multipoint linkage peak was located at marker rs2144151 in the ANGPT4 gene, which is a strong candidate gene for vascular disease because of its involvement in angiogenesis. Although the significance of the linkage decreased, we find this result intriguing, considering that we included additional families, and thus the reduced linkage signal may be caused by genetic heterogeneity. Journal of Human Genetics (2010) 55, 649–655; doi:10.1038/jhg.2010.79; published online 1 July 2010 Keywords: Alzheimer’s disease; ANGPT4; association study; candidate genes; familial dementia; linkage analysis; SNP INTRODUCTION Previous genome-wide family-based linkage analyses have identified Alzheimer’s disease (AD; MIM104300) is the major cause of dementia several loci linked to AD9–19 and confirmed linkage by several in the elderly. Its main neuropathological signs are extracellular groups has been reported to chromosome (chr.) 9p, 9q, 10q, 12p depositions of amyloid b-protein and intracellular neurofibrillary and 19q.20–24 Extensive follow-up and fine mapping studies have been tangles composed of hyperphosphorylated tau.
    [Show full text]
  • Prolyl Hydroxylase Domain Inhibitor Protects Against Metabolic Disorders and Associated Kidney Disease in Obese Type 2 Diabetic Mice
    BASIC RESEARCH www.jasn.org Prolyl Hydroxylase Domain Inhibitor Protects against Metabolic Disorders and Associated Kidney Disease in Obese Type 2 Diabetic Mice Mai Sugahara,1 Shinji Tanaka ,1 Tetsuhiro Tanaka,1 Hisako Saito,1 Yu Ishimoto,1 Takeshi Wakashima,2 Masatoshi Ueda,2 Kenji Fukui,2 Akira Shimizu,3 Reiko Inagi,4 Toshimasa Yamauchi,5 Takashi Kadowaki,5 and Masaomi Nangaku1 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background Prolyl hydroxylase domain (PHD) inhibitors, which stimulate erythropoietin production through the activation of hypoxia-inducible factor (HIF), are novel therapeutic agents used for treating renal anemia. Several PHD inhibitors, including enarodustat, are currently undergoing phase 2 or phase 3 clinical trials. Because HIF regulates a broad spectrum of genes, PHD inhibitors are expected to have other effects in addition to erythropoiesis, such as protection against metabolic disorders. However, whether such beneficial effects would extend to metabolic disorder–related kidney disease is largely unknown. Methods We administered enarodustat or vehicle without enarodustat in feed to diabetic black and tan brachyury (BTBR) ob/ob mice from 4 to 22 weeks of age. To elucidate molecular changes induced by enarodustat, we performed transcriptome analysis of isolated glomeruli and in vitro experiments using murine mesangial cells. Results Compared with BTBR ob/ob mice that received only vehicle, BTBR ob/ob mice treated with enarodustat displayed lower body weight, reduced blood glucose levels with improved insulin sensitivity, lower total cholesterol levels, higher adiponectin levels, and less adipose tissue, as well as a tendency for lower macrophage infiltration.
    [Show full text]
  • Peripheral Nerve Single-Cell Analysis Identifies Mesenchymal Ligands That Promote Axonal Growth
    Research Article: New Research Development Peripheral Nerve Single-Cell Analysis Identifies Mesenchymal Ligands that Promote Axonal Growth Jeremy S. Toma,1 Konstantina Karamboulas,1,ª Matthew J. Carr,1,2,ª Adelaida Kolaj,1,3 Scott A. Yuzwa,1 Neemat Mahmud,1,3 Mekayla A. Storer,1 David R. Kaplan,1,2,4 and Freda D. Miller1,2,3,4 https://doi.org/10.1523/ENEURO.0066-20.2020 1Program in Neurosciences and Mental Health, Hospital for Sick Children, 555 University Avenue, Toronto, Ontario M5G 1X8, Canada, 2Institute of Medical Sciences University of Toronto, Toronto, Ontario M5G 1A8, Canada, 3Department of Physiology, University of Toronto, Toronto, Ontario M5G 1A8, Canada, and 4Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada Abstract Peripheral nerves provide a supportive growth environment for developing and regenerating axons and are es- sential for maintenance and repair of many non-neural tissues. This capacity has largely been ascribed to paracrine factors secreted by nerve-resident Schwann cells. Here, we used single-cell transcriptional profiling to identify ligands made by different injured rodent nerve cell types and have combined this with cell-surface mass spectrometry to computationally model potential paracrine interactions with peripheral neurons. These analyses show that peripheral nerves make many ligands predicted to act on peripheral and CNS neurons, in- cluding known and previously uncharacterized ligands. While Schwann cells are an important ligand source within injured nerves, more than half of the predicted ligands are made by nerve-resident mesenchymal cells, including the endoneurial cells most closely associated with peripheral axons. At least three of these mesen- chymal ligands, ANGPT1, CCL11, and VEGFC, promote growth when locally applied on sympathetic axons.
    [Show full text]
  • Differentially Expressed Genes in Aneurysm Tissue Compared With
    On-line Table: Differentially expressed genes in aneurysm tissue compared with those in control tissue Fold False Discovery Direction of Gene Entrez Gene Name Function Change P Value Rate (q Value) Expression AADAC Arylacetamide deacetylase Positive regulation of triglyceride 4.46 1.33E-05 2.60E-04 Up-regulated catabolic process ABCA6 ATP-binding cassette, subfamily A (ABC1), Integral component of membrane 3.79 9.15E-14 8.88E-12 Up-regulated member 6 ABCC3 ATP-binding cassette, subfamily C (CFTR/MRP), ATPase activity, coupled to 6.63 1.21E-10 7.33E-09 Up-regulated member 3 transmembrane movement of substances ABI3 ABI family, member 3 Peptidyl-tyrosine phosphorylation 6.47 2.47E-05 4.56E-04 Up-regulated ACKR1 Atypical chemokine receptor 1 (Duffy blood G-protein–coupled receptor signaling 3.80 7.95E-10 4.18E-08 Up-regulated group) pathway ACKR2 Atypical chemokine receptor 2 G-protein–coupled receptor signaling 0.42 3.29E-04 4.41E-03 Down-regulated pathway ACSM1 Acyl-CoA synthetase medium-chain family Energy derivation by oxidation of 9.87 1.70E-08 6.52E-07 Up-regulated member 1 organic compounds ACTC1 Actin, ␣, cardiac muscle 1 Negative regulation of apoptotic 0.30 7.96E-06 1.65E-04 Down-regulated process ACTG2 Actin, ␥2, smooth muscle, enteric Blood microparticle 0.29 1.61E-16 2.36E-14 Down-regulated ADAM33 ADAM domain 33 Integral component of membrane 0.23 9.74E-09 3.95E-07 Down-regulated ADAM8 ADAM domain 8 Positive regulation of tumor necrosis 4.69 2.93E-04 4.01E-03 Up-regulated factor (ligand) superfamily member 11 production ADAMTS18
    [Show full text]
  • SUPPLEMENTARY APPENDIX Exome Sequencing Reveals Heterogeneous Clonal Dynamics in Donor Cell Myeloid Neoplasms After Stem Cell Transplantation
    SUPPLEMENTARY APPENDIX Exome sequencing reveals heterogeneous clonal dynamics in donor cell myeloid neoplasms after stem cell transplantation Julia Suárez-González, 1,2 Juan Carlos Triviño, 3 Guiomar Bautista, 4 José Antonio García-Marco, 4 Ángela Figuera, 5 Antonio Balas, 6 José Luis Vicario, 6 Francisco José Ortuño, 7 Raúl Teruel, 7 José María Álamo, 8 Diego Carbonell, 2,9 Cristina Andrés-Zayas, 1,2 Nieves Dorado, 2,9 Gabriela Rodríguez-Macías, 9 Mi Kwon, 2,9 José Luis Díez-Martín, 2,9,10 Carolina Martínez-Laperche 2,9* and Ismael Buño 1,2,9,11* on behalf of the Spanish Group for Hematopoietic Transplantation (GETH) 1Genomics Unit, Gregorio Marañón General University Hospital, Gregorio Marañón Health Research Institute (IiSGM), Madrid; 2Gregorio Marañón Health Research Institute (IiSGM), Madrid; 3Sistemas Genómicos, Valencia; 4Department of Hematology, Puerta de Hierro General University Hospital, Madrid; 5Department of Hematology, La Princesa University Hospital, Madrid; 6Department of Histocompatibility, Madrid Blood Centre, Madrid; 7Department of Hematology and Medical Oncology Unit, IMIB-Arrixaca, Morales Meseguer General University Hospital, Murcia; 8Centro Inmunológico de Alicante - CIALAB, Alicante; 9Department of Hematology, Gregorio Marañón General University Hospital, Madrid; 10 Department of Medicine, School of Medicine, Com - plutense University of Madrid, Madrid and 11 Department of Cell Biology, School of Medicine, Complutense University of Madrid, Madrid, Spain *CM-L and IB contributed equally as co-senior authors. Correspondence:
    [Show full text]