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The Expression of the Human Apolipoprotein Genes and Their Regulation by Ppars
CORE Metadata, citation and similar papers at core.ac.uk Provided by UEF Electronic Publications The expression of the human apolipoprotein genes and their regulation by PPARs Juuso Uski M.Sc. Thesis Biochemistry Department of Biosciences University of Kuopio June 2008 Abstract The expression of the human apolipoprotein genes and their regulation by PPARs. UNIVERSITY OF KUOPIO, the Faculty of Natural and Environmental Sciences, Curriculum of Biochemistry USKI Juuso Oskari Thesis for Master of Science degree Supervisors Prof. Carsten Carlberg, Ph.D. Merja Heinäniemi, Ph.D. June 2008 Keywords: nuclear receptors; peroxisome proliferator-activated receptor; PPAR response element; apolipoprotein; lipid metabolism; high density lipoprotein; low density lipoprotein. Lipids are any fat-soluble, naturally-occurring molecules and one of their main biological functions is energy storage. Lipoproteins carry hydrophobic lipids in the water and salt-based blood environment for processing and energy supply in liver and other organs. In this study, the genomic area around the apolipoprotein genes was scanned in silico for PPAR response elements (PPREs) using the in vitro data-based computer program. Several new putative REs were found in surroundings of multiple lipoprotein genes. The responsiveness of those apolipoprotein genes to the PPAR ligands GW501516, rosiglitazone and GW7647 in the HepG2, HEK293 and THP-1 cell lines were tested with real-time PCR. The APOA1, APOA2, APOB, APOD, APOE, APOF, APOL1, APOL3, APOL5 and APOL6 genes were found to be regulated by PPARs in direct or secondary manners. Those results provide new insights in the understanding of lipid metabolism and so many lifestyle diseases like atherosclerosis, type 2 diabetes, heart disease and stroke. -
The Role of High Density Lipoprotein Compositional and Functional Heterogeneity in Metabolic Disease
The role of high density lipoprotein compositional and functional heterogeneity in metabolic disease By Scott M. Gordon B.S. State University of New York College at Brockport October, 2012 A Dissertation Presented to the Faculty of The University of Cincinnati College of Medicine in partial fulfillment of the requirements for the Degree of Doctor of Philosophy from the Pathobiology and Molecular Medicine graduate program W. Sean Davidson Ph.D. (Chair) David Askew Ph.D. Professor and Thesis Chair Professor Department of Pathology Department of Pathology University of Cincinnati University of Cincinnati Francis McCormack M.D. Gangani Silva Ph.D. Professor Assistant Professor Department of Pathology Department of Pathology University of Cincinnati University of Cincinnati Jason Lu Ph.D. Assistant Professor Division of Bioinformatics Cincinnati Children’s Hospital i Abstract High density lipoproteins (HDL) are complexes of phospholipid, cholesterol and protein that circulate in the blood. Epidemiological studies have demonstrated a strong inverse correlation between plasma levels of HDL associated cholesterol (HDL-C) and the incidence of cardiovascular disease (CVD). Clinically, HDL-C is often measured and used in combination with low density lipoprotein cholesterol (LDL-C) to assess overall cardiovascular health. HDL have been shown to possess a wide variety of functional attributes which likely contribute to this protection including anti-inflammatory and anti- oxidative properties and the ability to remove excess cholesterol from peripheral tissues and deliver it to the liver for excretion, a process known as reverse cholesterol transport. This functional diversity might be explained by the complexity of HDL composition. Recent studies have taken advantage of advances in mass spectrometry technologies to characterize the proteome of total HDL finding that over 50 different proteins can associate with these particles. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Identification and Prioritization Genes
Original Article 2015, Vol: 3, Issue: 1, Pages: 18-23 Bioinformatics useful tool in study of genes associated with diseases Research in Molecular Medicine DOI: 10.7508/rmm.2015.01.004 Identifying and prioritizing genes related to Familial hypercholesterolemia QTLs using gene ontology and protein interaction networks Ali Kazemi-Pour 1, Bahram Goliaei 2*, Hamid Pezeshk 3, Behjat Kalantari khandani 4 1 PhD student of Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. 2 Professor of Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. 3 Professor of statistics, Science College, University of Tehran, Tehran, Iran. 4 Assistant Professor of Internal Medicine, Kerman University of Medical Sciences, Kerman, Iran. Received: 17 Aug 2014 Abstract Revised : 4 Sep 2014 Background: Gene identification represents the first step to a better understanding of the physiological role of the underlying protein and disease Accepted: 10 Sep 2014 pathways, which in turn serves as a starting point for developing therapeutic interventions. Familial hypercholesterolemia is a hereditary metabolic disorder Corresponding Authors: Bahram Goliaei characterized by high low-density lipoprotein cholesterol levels. Institute of Biochemistry and Hypercholesterolemia is a quantitative trait that is controlled by interactions Biophysics, University of Tehran, among several quantitative trait loci. Many biological data is presented in the Tehran, Iran. context of biological networks and evaluation of biological networks is considered Phone: +98-2161113356 E-mail: [email protected] as the essential key to understanding complex biological systems. Materials and Methods: In this research, we used combination of information about quantitative trait loci of hypercholesterolemia with information of gene ontology and protein–protein interaction network for identification of genes associated with hypercholesterolemia. -
Identification of Key Genes Affecting Porcine Fat Deposition Based on Co
Xing et al. Journal of Animal Science and Biotechnology (2021) 12:100 https://doi.org/10.1186/s40104-021-00616-9 RESEARCH Open Access Identification of key genes affecting porcine fat deposition based on co- expression network analysis of weighted genes Kai Xing1†, Huatao Liu2†, Fengxia Zhang2, Yibing Liu2, Yong Shi2, Xiangdong Ding2* and Chuduan Wang2* Abstract Background: Fat deposition is an important economic consideration in pig production. The amount of fat deposition in pigs seriously affects production efficiency, quality, and reproductive performance, while also affecting consumers’ choice of pork. Weighted gene co-expression network analysis (WGCNA) is effective in pig genetic studies. Therefore, this study aimed to identify modules that co-express genes associated with fat deposition in pigs (Songliao black and Landrace breeds) with extreme levels of backfat (high and low) and to identify the core genes in each of these modules. Results: We used RNA sequences generated in different pig tissues to construct a gene expression matrix consisting of 12,862 genes from 36 samples. Eleven co-expression modules were identified using WGCNA and the number of genes in these modules ranged from 39 to 3,363. Four co-expression modules were significantly correlated with backfat thickness. A total of 16 genes (RAD9A, IGF2R, SCAP, TCAP, SMYD1, PFKM, DGAT1, GPS2, IGF1, MAPK8, FABP, FABP5, LEPR, UCP3, APOF, and FASN) were associated with fat deposition. Conclusions: RAD9A, TCAP, SMYD1, PFKM, GPS2, and APOF were the key genes in the four modules based on the degree of gene connectivity. Combining these results with those from differential gene analysis, SMYD1 and PFKM were proposed as strong candidate genes for body size traits. -
Biostatistics Mining Associated Method Identifies AKR1B10
www.nature.com/scientificreports OPEN Biostatistics mining associated method identifes AKR1B10 enhancing hepatocellular Received: 26 February 2018 Accepted: 25 June 2018 carcinoma cell growth and Published: xx xx xxxx degenerated by miR-383-5p Junqing Wang 1,2,3, Yunyun Zhou4, Xiaochun Fei5, Xuehua Chen2,3 & Yongjun Chen1 Previous studies have reported that the aberrantly expressed AKR1B10 is associated with many cancer development, however the functional roles of AKR1B10 and its regulatory mechanisms in hepatocellular carcinoma (HCC) have been limited studied. In this project, we identifed AKR1B10 functional as an oncogene in HCC through tumor/normal human tissue comparison from both GEO microarray and TCGA RNAseq dataset. Further experimental validations from three HCC cell lines (SMMC-7721, HePG2 and HeP3B) also suggested the ontogenetic functions of AKR1B10 in HCC tumor growth. By knocking down AKR1B10 through shRNA in HCC HeP3B cells, we showed it signifcantly induced cell cycle arrest and inhibited cell growth. Interestingly, integrative analysis of TCGA RNAseq data and miRNA-seq data predicted that miR-383-5p, a novel post-transcriptional tumor suppressor, is negatively associated with AKR1B10 expression. To further investigate the role of miR-383-5p in regulating AKR1B10 in HCC, we performed Dual-luciferase reporter assay experiments. Results showed that miR-383-5p is an upstream modulator targeting AKR1B10 in the post-transcriptional stage. Thus, we report AKR1B10 modulated regulated by miR-383-5p, promotes HCC tumor progress, and could be potentially a therapeutic target for precision medicine in HCC. World widely, hepatocellular carcinoma (HCC) presents a high incidence rate among human malignancies, rank- ing a ffh of morbidity and second of malignancy-related mortality1,2. -
TAC3 Gene Products Regulate Brain and Digestive System Gene Expression in the Spotted Sea Bass (Lateolabrax Maculatus)
ORIGINAL RESEARCH published: 14 August 2019 doi: 10.3389/fendo.2019.00556 TAC3 Gene Products Regulate Brain and Digestive System Gene Expression in the Spotted Sea Bass (Lateolabrax maculatus) Zhanxiong Zhang, Haishen Wen, Yun Li, Qing Li, Wenjuan Li, Yangyang Zhou, Lingyu Wang, Yang Liu, Likang Lyu and Xin Qi* Key Laboratory of Mariculture, Ministry of Education, Ocean University of China, Qingdao, China Neurokinin B (NKB) is a member of the tachykinin (tac) family that plays important roles in mammalian growth by modulating prolactin (PRL) synthesis and secretion and causing contraction of the stomach and intestine. However, its potential role in regulating growth of teleosts is less clear. We aimed to explore the role that NKB plays in regulating fish growth using the spotted sea bass (Lateolabrax maculatus) as a model. In the present study, two tac3 and two tacr3 genes were identified in the spotted sea bass. Sequence analysis showed that two tac3 transcripts, tac3a and tac3b, encode four NKBs: NKBa-13, NKBa-10, NKBb-13, and NKBb-10. Expression analysis in different Edited by: tissues showed that both genes are highly expressed in the brain, stomach and intestine Vance L. Trudeau, University of Ottawa, Canada of the spotted sea bass. In situ hybridization indicated that the tac3a and tac3b mRNAs Reviewed by: are both localized in several brain regions, such as the telencephalon and hypothalamus, Berta Levavi-Sivan, and that tacr3a and tacr3b are localized in the intestinal villus and gastric gland. To Hebrew University of Jerusalem, Israel Satoshi Ogawa, investigate the potential role of NKBs in regulating growth, in vitro experiments were Monash University Malaysia, Malaysia performed to detect the effect of NKBs on growth-related gene expression in the brain *Correspondence: and brain-gut peptide (BGP)-related genes in the stomach and intestine. -
Potential Role in Controlling Fish Reproduction
Neurokinin Bs and neurokinin B receptors in zebrafish- potential role in controlling fish reproduction Jakob Birana, Ori Palevitcha, Shifra Ben-Dorb, and Berta Levavi-Sivana,1 aDepartment of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, Rehovot 76100, Israel; and bDepartment of Biological Services, Weizmann Institute of Science, Rehovot 76100, Israel Edited by John E. Halver, University of Washington, Seattle, WA, and approved April 27, 2012 (received for review December 2, 2011) The endocrine regulation of vertebrate reproduction is achieved by zebrafish (Danio rerio) as a model, was to examine the in- the coordinated actions of several peptide neurohormones, tachy- volvement of NKB in fish reproduction. kinin among them. To study the evolutionary conservation and NKB is a member of the tachykinin (TK) family of peptides. physiological functions of neurokinin B (NKB), we identified tachy- TKs are characterized by a common carboxyl-terminal amino acid kinin (tac) and tac receptor (NKBR) genes from many fish species, sequence of FXGLM-NH2 (where X is a hydrophobic residue), and cloned two cDNA forms from zebrafish. Phylogenetic analysis and include substance P, neurokinin A (NKA) and NKB, as well γ showed that piscine Tac3s and mammalian neurokinin genes arise as neuropeptide K, neuropeptide- , and hemokinin-1 (7). NKB is from one lineage. High identity was found among different fish the only TK synthesized from the preprotachykinin-B gene (8), species in the region encoding the NKB; all shared the common C- which is currently designated as TAC3 in mammals, except for terminal sequence. Although the piscine Tac3 gene encodes for two rodents, where it was named Tac2. -
WO 2014/205555 Al 31 December 2014 (31.12.2014) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2014/205555 Al 31 December 2014 (31.12.2014) P O P C T (51) International Patent Classification: British Columbia V5Y 2G1 (CA). WATAHIKI, Akira; A61K 31/713 (2006.01) G01N 33/48 (2006.01) 15-5 Takakura-cho, Nishinomiya, 62-0872 (JP). LIU, Hui A61K 31/7088 (2006.01) G01N 33/50 (2006.01) Hsuan; 207 - 5770 Oak Street, Vancouver, British A61P 35/00 (2006.01) CI2N 15/113 (2010.01) Columbia V6M 4M5 (CA). PAROLIA, Abhijit; 505 C12Q 1/68 (2006.01) Mumfordganj, 2 11002 Allahabad U.P. (IN). (21) International Application Number: (74) Agents: SECHLEY, Konrad et al; Gowling Lafleur PCT/CA2014/000538 Henderson LLP, 2300, 550 Burrard Street, Vancouver, British Columbia V6C 2B5 (CA). (22) International Filing Date: 27 June 2014 (27.06.2014) (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, (25) Filing Language: English AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, (26) Publication Language: English BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, (30) Priority Data: HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KN, KP, KR, 61/841,225 28 June 2013 (28.06.2013) US KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, (71) Applicant: BRITISH COLUMBIA CANCER AGENCY MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, BRANCH [CA/CA]; 675 West 10th Avenue, Vancouver, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, British Columbia V5Z 1L3 (CA). -
1 Gene Networks and Pathways for Plasma Lipid Traits Via Multi-Tissue
bioRxiv preprint doi: https://doi.org/10.1101/2020.02.28.970368; this version posted December 21, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Gene Networks and Pathways for Plasma Lipid Traits via Multi-tissue Multi-omics Systems Analysis Montgomery Blencowe+a, b, In Sook Ahn+a, Zara Saleema, Helen Luka, Ingrid Celya, Ville-Petteri Mäkinena, c, Yuqi Zhaoa*, Xia Yang a, b, d* a Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA b Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA c South Australian Health and Medical Research Institute, Adelaide, Australia dInterdepartmental Program of Bioinformatics, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA + co-first author * Correspondence should be addressed to: Xia Yang, Ph.D. Department of Integrative Biology and Physiology University of California Los Angeles Los Angeles, CA 90095 Phone: 310-206-1812 Email: [email protected] Yuqi Zhao, Ph.D. Department of Integrative Biology and Physiology University of California Los Angeles Los Angeles, CA 90095 Phone: 310-206-1812 Email: [email protected] Running Title: Systems Regulation of Plasma Lipids 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.02.28.970368; this version posted December 21, 2020. -
APOF Antibody (Center) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap10107c
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 APOF Antibody (Center) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP10107c Specification APOF Antibody (Center) - Product Information Application WB, IHC-P,E Primary Accession Q13790 Other Accession NP_001629.1 Reactivity Human Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 35399 Antigen Region 111-138 APOF Antibody (Center) - Additional Information Gene ID 319 Other Names Apolipoprotein F, Apo-F, Lipid transfer Anti-APOF Antibody (Center) at 1:1000 inhibitor protein, LTIP, APOF dilution + human liver lysate Lysates/proteins at 20 µg per lane. Secondary Goat Target/Specificity Anti-Rabbit IgG, (H+L), Peroxidase This APOF antibody is generated from conjugated at 1/10000 dilution. Predicted rabbits immunized with a KLH conjugated band size : 35 kDa Blocking/Dilution buffer: synthetic peptide between 111-138 amino 5% NFDM/TBST. acids from the Central region of human APOF. Dilution WB~~1:1000 IHC-P~~1:10~50 Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is purified through a protein A column, followed by peptide affinity purification. Storage Maintain refrigerated at 2-8°C for up to 2 weeks. For long term storage store at -20°C in small aliquots to prevent freeze-thaw cycles. APOF antibody (Center) (Cat. #AP10107c) Precautions immunohistochemistry analysis in formalin APOF Antibody (Center) is for research use fixed and paraffin embedded human only and not for use in diagnostic or hepatocarcinoma followed by peroxidase Page 1/2 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 therapeutic procedures. -
Molecular Characterization of Selectively Vulnerable Neurons in Alzheimer’S Disease
RESOURCE https://doi.org/10.1038/s41593-020-00764-7 Molecular characterization of selectively vulnerable neurons in Alzheimer’s disease Kun Leng1,2,3,4,13, Emmy Li1,2,3,13, Rana Eser 5, Antonia Piergies5, Rene Sit2, Michelle Tan2, Norma Neff 2, Song Hua Li5, Roberta Diehl Rodriguez6, Claudia Kimie Suemoto7,8, Renata Elaine Paraizo Leite7, Alexander J. Ehrenberg 5, Carlos A. Pasqualucci7, William W. Seeley5,9, Salvatore Spina5, Helmut Heinsen7,10, Lea T. Grinberg 5,7,11 ✉ and Martin Kampmann 1,2,12 ✉ Alzheimer’s disease (AD) is characterized by the selective vulnerability of specific neuronal populations, the molecular sig- natures of which are largely unknown. To identify and characterize selectively vulnerable neuronal populations, we used single-nucleus RNA sequencing to profile the caudal entorhinal cortex and the superior frontal gyrus—brain regions where neurofibrillary inclusions and neuronal loss occur early and late in AD, respectively—from postmortem brains spanning the progression of AD-type tau neurofibrillary pathology. We identified RORB as a marker of selectively vulnerable excitatory neu- rons in the entorhinal cortex and subsequently validated their depletion and selective susceptibility to neurofibrillary inclusions during disease progression using quantitative neuropathological methods. We also discovered an astrocyte subpopulation, likely representing reactive astrocytes, characterized by decreased expression of genes involved in homeostatic functions. Our characterization of selectively vulnerable neurons in AD paves the way for future mechanistic studies of selective vulnerability and potential therapeutic strategies for enhancing neuronal resilience. elective vulnerability is a fundamental feature of neurodegen- Here, we performed snRNA-seq on postmortem brain tissue erative diseases, in which different neuronal populations show from a cohort of individuals spanning the progression of AD-type a gradient of susceptibility to degeneration.