New Insight Into Vitamin B6 Metabolism and Related Diseases
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Aspartate Aminotransferase (AST, GOT), Human Liver
BioVision 05/18 For research use only Aspartate Aminotransferase (AST, GOT), Human Liver CATALOG NO: P1299-100 1 units RELATED PRODUCTS: ALTERNATE NAMES: Aspartate Transaminase, Glutamate Oxaloacetate, AST, GOT, Aspartate Aminotransferase (AST) (Mouse) ELISA Kit (Cat. No. E4320) sGOT, AspAT, ASAT, serum glutamic oxaloacetic transaminase, AAT Aspartate Aminotransferase (AST) (Human) ELISA Kit (Cat. No. E4319) Aspartate Aminotransferase (AST) (Rat) ELISA Kit (Cat. No. E4321) SOURCE: Human Liver Aspartate Aminotransferase (AST or SGOT) Activity Colorimetric Assay Kit (Cat. PURITY: Purified No. K753) Anti-GOT2 Antibody (cat. No. A1273) MOL. WEIGHT: ~92 kDa Anti-GOT1 Antibody (Cat. No. A1272) FORM: Lyophilized GOT2, human recombinant (Cat. No. 7809) GOT1, human recombinant (Cat. No. 7808) STORAGE CONDITIONS: Store at -20°C. Avoid repeated freezing and thawing cycles. BIOLOGICAL ACTIVITY: ≥ 1 U/mg (Dimension® Clinical Chemistry System) UNIT DEFINITATION: One unit will catalyze the transamination of one micromole of L- aspartate to alpha-ketoglutarate forming L-glutamate and oxaloacetate per minute at 37°C and pH 7.8.Measured at 340 nm as one equimolar amount of NAD produced by a coupled reaction. RECONSTITUTION: > 1 mg/mL in tris buffered saline, 1% BSA, pH 8.0. AST/SGOT is found in many tissues throughout the body, including DESCRIPTION: the liver, heart, muscles, kidney, and brain. If any of these organs or tissues is affected by disease or injury, AST is released into the bloodstream. This means that AST isn't as specific an indicator of liver damage as ALT (also known as alanine aminotransferase, another type of enzyme found almost entirely in the liver). The ratio of AST and ALT levels are commonly used as biomarkers for liver health. -
Supplemental Figure 1. Vimentin
Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672 -
Molybdoproteomes and Evolution of Molybdenum Utilization
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Vadim Gladyshev Publications Biochemistry, Department of April 2008 Molybdoproteomes and evolution of molybdenum utilization Yan Zhang University of Nebraska-Lincoln, [email protected] Vadim N. Gladyshev University of Nebraska-Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/biochemgladyshev Part of the Biochemistry, Biophysics, and Structural Biology Commons Zhang, Yan and Gladyshev, Vadim N., "Molybdoproteomes and evolution of molybdenum utilization" (2008). Vadim Gladyshev Publications. 78. https://digitalcommons.unl.edu/biochemgladyshev/78 This Article is brought to you for free and open access by the Biochemistry, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Vadim Gladyshev Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Published in Journal of Molecular Biology (2008); doi: 10.1016/j.jmb.2008.03.051 Copyright © 2008 Elsevier. Used by permission. http://www.sciencedirect.com/science/journal/00222836 Submitted November 26, 2007; revised March 15, 2008; accepted March 25, 2008; published online as “Accepted Manuscript” April 1, 2008. Molybdoproteomes and evolution of molybdenum utilization Yan Zhang and Vadim N. Gladyshev* Department of Biochemistry, University of Nebraska–Lincoln, Lincoln, NE 685880664 *Corresponding author—tel 402 472-4948, fax 402 472-7842, email [email protected] Abstract The trace element molybdenum (Mo) is utilized in many life forms, where it is a key component of several enzymes involved in nitrogen, sulfur, and carbon metabolism. With the exception of nitrogenase, Mo is bound in proteins to a pterin, thus forming the molybdenum cofactor (Moco) at the catalytic sites of molybdoenzymes. -
Ornithine Aminotransferase, an Important Glutamate-Metabolizing Enzyme at the Crossroads of Multiple Metabolic Pathways
biology Review Ornithine Aminotransferase, an Important Glutamate-Metabolizing Enzyme at the Crossroads of Multiple Metabolic Pathways Antonin Ginguay 1,2, Luc Cynober 1,2,*, Emmanuel Curis 3,4,5,6 and Ioannis Nicolis 3,7 1 Clinical Chemistry, Cochin Hospital, GH HUPC, AP-HP, 75014 Paris, France; [email protected] 2 Laboratory of Biological Nutrition, EA 4466 PRETRAM, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France 3 Laboratoire de biomathématiques, plateau iB2, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France; [email protected] (E.C.); [email protected] (I.N.) 4 UMR 1144, INSERM, Université Paris Descartes, 75006 Paris, France 5 UMR 1144, Université Paris Descartes, 75006 Paris, France 6 Service de biostatistiques et d’informatique médicales, hôpital Saint-Louis, Assistance publique-hôpitaux de Paris, 75010 Paris, France 7 EA 4064 “Épidémiologie environnementale: Impact sanitaire des pollutions”, Faculté de Pharmacie, Université Paris Descartes, 75006 Paris, France * Correspondence: [email protected]; Tel.: +33-158-411-599 Academic Editors: Arthur J.L. Cooper and Thomas M. Jeitner Received: 26 October 2016; Accepted: 24 February 2017; Published: 6 March 2017 Abstract: Ornithine δ-aminotransferase (OAT, E.C. 2.6.1.13) catalyzes the transfer of the δ-amino group from ornithine (Orn) to α-ketoglutarate (aKG), yielding glutamate-5-semialdehyde and glutamate (Glu), and vice versa. In mammals, OAT is a mitochondrial enzyme, mainly located in the liver, intestine, brain, and kidney. In general, OAT serves to form glutamate from ornithine, with the notable exception of the intestine, where citrulline (Cit) or arginine (Arg) are end products. -
Multiomics Integration Elucidates Metabolic Modulators of Drug
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.07.425721; this version posted January 8, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Multiomics Integration Elucidates Metabolic Modulators of Drug Resistance in Lymphoma Choueiry, Fouad1*, Singh, Satishkumar2,3*, Sun, Xiaowei1, Zhang, Shiqi1, Sircar, Anuvrat2,3 ,Hart, Amber2, Alinari, Lapo2,3, Narendranath Epperla2,3, Baiocchi, Robert2,3, Zhu, Jiangjiang1,# and Sehgal, Lalit2,3# 1 Department of Human Sciences, The Ohio State University, Columbus, OH 43210; 2 Division of Hematology, Department of Internal Medicine, The Ohio State, 3 James Comprehensive Cancer Center, The Ohio State University Columbus, OH 43210. *Equal contribution, #Corresponding authors Abstract Background Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma (NHL). B-cell NHLs rely on Bruton’s tyrosine kinase (BTK) mediated B-cell receptor signaling for survival and disease progression. However, they are often resistant to BTK inhibitors or soon acquire resistance after drug exposure resulting in the drug tolerant form. The drug tolerant clones proliferate faster, have increased metabolic activity, and shift to oxidative phosphorylation; however, how this metabolic programming occurs in the drug resistant tumor is poorly understood. Methods In this study, we explored for the first time the metabolic regulators of ibrutinib-resistant activated B-cell (ABC) DLBCL using a ‘multi-omics’ analysis that integrated metabolomics (using high-resolution mass spectrometry) and transcriptomic (gene expression analysis). Overlay of the unbiased statistical analyses, genetic perturbation and pharmaceutical inhibition, were further used to identify the key players that contribute to the metabolic reprograming of the drug resistant clone. -
Page Numbers in Bold Indicate Main Discus- Sion of Topic. Page Numbers
168397_P489-520.qxd7.0:34 Index 6-2-04 26p 2010.4.5 10:03 AM Page 489 source of, 109, 109f pairing with thymine, 396f, 397, 398f in tricarboxylic acid cycle, 109–111, 109f Adenine arabinoside (vidarabine, araA), 409 Acetyl CoA-ACP acetyltransferase, 184 Adenine phosphoribosyltransferase (APRT), Index Acetyl CoA carboxylase, 183, 185f, 190 296, 296f in absorptive/fed state, 324 Adenosine deaminase (ADA), 299 allosteric activation of, 183–184, 184f deficiency of, 298, 300f, 301–302 allosteric inactivation of, 183, 184f gene therapy for, 485, 486f dephosphorylation of, 184 Adenosine diphosphate (ADP) in fasting, 330 in ATP synthesis, 73, 77–78, 78f Page numbers in bold indicate main discus- hormonal regulation of, 184, 184f isocitrate dehydrogenase activation by, sion of topic. Page numbers followed by f long-term regulation of, 184 112 denote figures. “See” cross-references direct phosphorylation of, 183–184 transport of, to inner mitochondrial short-term regulation of, 183–184, 184f membrane, 79 the reader to the synonymous term. “See Acetyl CoA carboxylase-2 (ACC2), 191 in tricarboxylic acid cycle regulation, 114, also” cross-references direct the reader to N4-Acetylcytosine, 292f 114f related topics. [Note: Positional and configura- N-Acetyl-D-glucosamine, 142 in urea cycle, 255–256 N-Acetylgalactosamine (GalNAc), 160, 168 ribosylation, 95 tional designations in chemical names (for N-Acetylglucosamindase deficiency, 164f Adenosine monophosphate (AMP; also called example, “3-“, “α”, “N-“, “D-“) are ignored in N-Acetylglucosamine (GlcNAc), -
Supplementary Materials
1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No. -
Review Article
REVIEW ARTICLE COLLAGEN METABOLISM COLLAGEN METABOLISM Types of Collagen 228 Structure of Collagen Molecules 230 Synthesis and Processing of Procollagen Polypeptides 232 Transcription and Translation 233 Posttranslational Modifications 233 Extracellular Processing of Procollagen and Collagen Fibrillogenesis 240 Functions of Collagen in Connective rissue 243 Collagen Degradation 245 Regulation of the Metabolism of Collagen 246 Heritable Diseases of Collagen 247 Recessive Dermatosparaxis 248 Recessive Forms of EDS 251 EDS VI 251 EDS VII 252 EDS V 252 Lysyl Oxidase Deficiency in the Mouse 253 X-Linked Cutis Laxa 253 Menke's Kinky Hair Syndrome 253 Homocystinuria 254 EDS IV 254 Dominant Forms of EDS 254 Dominant Collagen Packing Defect I 255 Dominant and Recessive Forms of Osteogenesis Imperfecta 258 Dominant and Recessive Forms of Cutis Laxa 258 The Marfan Syndrome 259 Acquired Diseases and Repair Processes Affecting Collagen 259 Acquired Changes in the Types of Collagen Synthesis 260 Acquired Changes in Amounts of Collagen Synthesized 263 Acquired Changes in Hydroxylation of Proline and Lysine 264 Acquired Changes in Collagen Cross-Links 265 Acquired Defects in Collagen Degradation 267 Conclusion 267 Bibliography 267 Collagen Metabolism A Comparison of Diseases of Collagen and Diseases Affecting Collagen Ronald R. Minor, VMD, PhD COLLAGEN CONSTITUTES approximately one third of the body's total protein, and changes in synthesis and/or degradation of colla- gen occur in nearly every disease process. There are also a number of newly described specific diseases of collagen in both man and domestic animals. Thus, an understanding of the synthesis, deposition, and turnover of collagen is important for the pathologist, the clinician, and the basic scientist alike. -
Glutamine Supports Pancreatic Cancer Growth Through a Kras- Regulated Metabolic Pathway
Glutamine supports pancreatic cancer growth through a Kras- regulated metabolic pathway The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Son, J., C. A. Lyssiotis, H. Ying, X. Wang, S. Hua, M. Ligorio, R. M. Perera, et al. 2013. “Glutamine supports pancreatic cancer growth through a Kras-regulated metabolic pathway.” Nature 496 (7443): 101-105. doi:10.1038/nature12040. http://dx.doi.org/10.1038/ nature12040. Published Version doi:10.1038/nature12040 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11878814 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA NIH Public Access Author Manuscript Nature. Author manuscript; available in PMC 2013 October 04. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Nature. 2013 April 4; 496(7443): 101–105. doi:10.1038/nature12040. Glutamine supports pancreatic cancer growth through a Kras- regulated metabolic pathway Jaekyoung Son1,#, Costas A. Lyssiotis2,3,11,#, Haoqiang Ying4, Xiaoxu Wang1, Sujun Hua4, Matteo Ligorio8, Rushika M. Perera5, Cristina R. Ferrone8, Edouard Mullarky2,3,11, Ng Shyh- Chang2,9, Ya’an Kang10, Jason B. Fleming10, Nabeel Bardeesy5, John M. Asara3,6, Marcia C. Haigis7, Ronald A. DePinho4, Lewis C. Cantley2,3,11,*, and Alec -
|I|||||IIIHIII US005541.108A United States Patent (19) 11 Patent Number: 5,541,108 Fujiwara Et Al
|I|||||IIIHIII US005541.108A United States Patent (19) 11 Patent Number: 5,541,108 Fujiwara et al. (45) Date of Patent: Jul. 30, 1996 54 GLUCONOBACTER OXYDANS STRAINS 5,082,785 l/1992. Manning et al. .................. 435/252.32 75 Inventors: Akiko Fujiwara, Kamakura; Teruhide FOREIGN PATENT DOCUMENTS Sugisawa; Masako Shinjoh, both of 994119 9/1963 United Kingdom................... 435/138 Yokohama; Yutaka Setoguchi; Tatsuo Hoshino, both of Kamakura, all of OTHER PUBLICATIONS Japan Stanbury et al. Principles of fermentation Technology, 1984, Pergamon Press. 73 Assignee: Hoffmann-La Roche Inc., Nutley, N.J. ATCC Catalogue of Bacteria, 1989, p. 106. Tsukada et al, Biotechnology and Bioengineering, vol 14, 21 Appl. No. 266,998 1972 pp. 799-810, John Wiley & Sons, Inc. Makover, et al., Biotechnology and Bioengineering XVII, 22 Filed: Jun. 28, 1994 pp. 1485-1514 (1975). Related U.S. Application Data Isono, et al. Agr. Biol. Chem, 35 No. 4 pp. 424–431 (1968). Okazaki, et al, Agr. Biol. Chem 32 No. 10 pp. 1250-1255 63 Continuation of Ser. No. 183,924, Jan. 18, 1994, abandoned, (1968). which is a continuation of Ser. No. 16,478, Feb. 10, 1993, Martin etal, Eur. S. Appl. Microbiology3, pp. 91-95 (1976). abandoned, which is a continuation of Ser. No. 517,972, Apr. Acta Microbologica Sinica 20 (3):246-251 (1980) (Abstract 30, 1990, abandoned, which is a continuation of Ser. No. only). 899,586, Aug. 25, 1986, abandoned. Acta Microbiologica Sinica 21 (2): 185-191- (1981) 30 Foreign Application Priority Data (Abstract only). Aug. 28, 1985 GB United Kingdom ................... 852359 Primary Examiner Irene Marx Jul. -
Amino Acid Disorders
471 Review Article on Inborn Errors of Metabolism Page 1 of 10 Amino acid disorders Ermal Aliu1, Shibani Kanungo2, Georgianne L. Arnold1 1Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; 2Western Michigan University Homer Stryker MD School of Medicine, Kalamazoo, MI, USA Contributions: (I) Conception and design: S Kanungo, GL Arnold; (II) Administrative support: S Kanungo; (III) Provision of study materials or patients: None; (IV) Collection and assembly of data: E Aliu, GL Arnold; (V) Data analysis and interpretation: None; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. Correspondence to: Georgianne L. Arnold, MD. UPMC Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Suite 1200, Pittsburgh, PA 15224, USA. Email: [email protected]. Abstract: Amino acids serve as key building blocks and as an energy source for cell repair, survival, regeneration and growth. Each amino acid has an amino group, a carboxylic acid, and a unique carbon structure. Human utilize 21 different amino acids; most of these can be synthesized endogenously, but 9 are “essential” in that they must be ingested in the diet. In addition to their role as building blocks of protein, amino acids are key energy source (ketogenic, glucogenic or both), are building blocks of Kreb’s (aka TCA) cycle intermediates and other metabolites, and recycled as needed. A metabolic defect in the metabolism of tyrosine (homogentisic acid oxidase deficiency) historically defined Archibald Garrod as key architect in linking biochemistry, genetics and medicine and creation of the term ‘Inborn Error of Metabolism’ (IEM). The key concept of a single gene defect leading to a single enzyme dysfunction, leading to “intoxication” with a precursor in the metabolic pathway was vital to linking genetics and metabolic disorders and developing screening and treatment approaches as described in other chapters in this issue. -
Supplementary Materials
Supplementary Materials COMPARATIVE ANALYSIS OF THE TRANSCRIPTOME, PROTEOME AND miRNA PROFILE OF KUPFFER CELLS AND MONOCYTES Andrey Elchaninov1,3*, Anastasiya Lokhonina1,3, Maria Nikitina2, Polina Vishnyakova1,3, Andrey Makarov1, Irina Arutyunyan1, Anastasiya Poltavets1, Evgeniya Kananykhina2, Sergey Kovalchuk4, Evgeny Karpulevich5,6, Galina Bolshakova2, Gennady Sukhikh1, Timur Fatkhudinov2,3 1 Laboratory of Regenerative Medicine, National Medical Research Center for Obstetrics, Gynecology and Perinatology Named after Academician V.I. Kulakov of Ministry of Healthcare of Russian Federation, Moscow, Russia 2 Laboratory of Growth and Development, Scientific Research Institute of Human Morphology, Moscow, Russia 3 Histology Department, Medical Institute, Peoples' Friendship University of Russia, Moscow, Russia 4 Laboratory of Bioinformatic methods for Combinatorial Chemistry and Biology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia 5 Information Systems Department, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia 6 Genome Engineering Laboratory, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia Figure S1. Flow cytometry analysis of unsorted blood sample. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S2. Flow cytometry analysis of unsorted liver stromal cells. Representative forward, side scattering and histogram are shown. The proportions of negative cells were determined in relation to the isotype controls. The percentages of positive cells are indicated. The blue curve corresponds to the isotype control. Figure S3. MiRNAs expression analysis in monocytes and Kupffer cells. Full-length of heatmaps are presented.