Proteome Characteristics of Liver Tissue from Patients with Parenteral
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
High-Throughput, Pooled Sequencing Identifies Mutations in NUBPL And
ARTICLES High-throughput, pooled sequencing identifies mutations in NUBPL and FOXRED1 in human complex I deficiency Sarah E Calvo1–3,10, Elena J Tucker4,5,10, Alison G Compton4,10, Denise M Kirby4, Gabriel Crawford3, Noel P Burtt3, Manuel Rivas1,3, Candace Guiducci3, Damien L Bruno4, Olga A Goldberger1,2, Michelle C Redman3, Esko Wiltshire6,7, Callum J Wilson8, David Altshuler1,3,9, Stacey B Gabriel3, Mark J Daly1,3, David R Thorburn4,5 & Vamsi K Mootha1–3 Discovering the molecular basis of mitochondrial respiratory chain disease is challenging given the large number of both mitochondrial and nuclear genes that are involved. We report a strategy of focused candidate gene prediction, high-throughput sequencing and experimental validation to uncover the molecular basis of mitochondrial complex I disorders. We created seven pools of DNA from a cohort of 103 cases and 42 healthy controls and then performed deep sequencing of 103 candidate genes to identify 151 rare variants that were predicted to affect protein function. We established genetic diagnoses in 13 of 60 previously unsolved cases using confirmatory experiments, including cDNA complementation to show that mutations in NUBPL and FOXRED1 can cause complex I deficiency. Our study illustrates how large-scale sequencing, coupled with functional prediction and experimental validation, can be used to identify causal mutations in individual cases. Complex I of the mitochondrial respiratory chain is a large ~1-MDa assembly factors are probably required, as suggested by the 20 factors macromolecular machine composed of 45 protein subunits encoded necessary for assembly of the smaller complex IV9 and by cohort by both the nuclear and mitochondrial (mtDNA) genomes. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Development of a Phage Display Library for Discovery of Antigenic Brucella Peptides Jeffrey Williams Iowa State University
Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations 2018 Development of a phage display library for discovery of antigenic Brucella peptides Jeffrey Williams Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/etd Part of the Microbiology Commons Recommended Citation Williams, Jeffrey, "Development of a phage display library for discovery of antigenic Brucella peptides" (2018). Graduate Theses and Dissertations. 16896. https://lib.dr.iastate.edu/etd/16896 This Thesis is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Development of a phage display library for discovery of antigenic Brucella peptides by Jeffrey Williams A thesis submitted to the graduate faculty in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Major: Microbiology Program of Study Committee: Bryan H. Bellaire, Major Professor Steven Olsen Steven Carlson The student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this thesis. The Graduate College will ensure this thesis is globally accessible and will not permit alterations after a degree is conferred. Iowa State University -
Proteomic and Metabolomic Analyses of Mitochondrial Complex I-Deficient
THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 287, NO. 24, pp. 20652–20663, June 8, 2012 © 2012 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A. Proteomic and Metabolomic Analyses of Mitochondrial Complex I-deficient Mouse Model Generated by Spontaneous B2 Short Interspersed Nuclear Element (SINE) Insertion into NADH Dehydrogenase (Ubiquinone) Fe-S Protein 4 (Ndufs4) Gene*□S Received for publication, November 25, 2011, and in revised form, April 5, 2012 Published, JBC Papers in Press, April 25, 2012, DOI 10.1074/jbc.M111.327601 Dillon W. Leong,a1 Jasper C. Komen,b1 Chelsee A. Hewitt,a Estelle Arnaud,c Matthew McKenzie,d Belinda Phipson,e Melanie Bahlo,e,f Adrienne Laskowski,b Sarah A. Kinkel,a,g,h Gayle M. Davey,g William R. Heath,g Anne K. Voss,a,h René P. Zahedi,i James J. Pitt,j Roman Chrast,c Albert Sickmann,i,k Michael T. Ryan,l Gordon K. Smyth,e,f,h b2 a,h,m,n3 David R. Thorburn, and Hamish S. Scott Downloaded from From the aMolecular Medicine Division, gImmunology Division, and eBioinformatics Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia, the bMurdoch Childrens Research Institute, Royal Children’s Hospital and Department of Paediatrics, University of Melbourne, Parkville, Victoria 3052, Australia, the cDépartement de Génétique Médicale, Université de Lausanne, 1005 Lausanne, Switzerland, the dCentre for Reproduction and Development, Monash Institute of Medical Research, Clayton, Victoria 3168, Australia, the hDepartment of Medical Biology -
Health Effects Support Document for Perfluorooctanoic Acid (PFOA)
United States Office of Water EPA 822-R-16-003 Environmental Protection Mail Code 4304T May 2016 Agency Health Effects Support Document for Perfluorooctanoic Acid (PFOA) Perfluorooctanoic Acid – May 2016 i Health Effects Support Document for Perfluorooctanoic Acid (PFOA) U.S. Environmental Protection Agency Office of Water (4304T) Health and Ecological Criteria Division Washington, DC 20460 EPA Document Number: 822-R-16-003 May 2016 Perfluorooctanoic Acid – May 2016 ii BACKGROUND The Safe Drinking Water Act (SDWA), as amended in 1996, requires the Administrator of the U.S. Environmental Protection Agency (EPA) to periodically publish a list of unregulated chemical contaminants known or anticipated to occur in public water systems and that may require regulation under SDWA. The SDWA also requires the Agency to make regulatory determinations on at least five contaminants on the Contaminant Candidate List (CCL) every 5 years. For each contaminant on the CCL, before EPA makes a regulatory determination, the Agency needs to obtain sufficient data to conduct analyses on the extent to which the contaminant occurs and the risk it poses to populations via drinking water. Ultimately, this information will assist the Agency in determining the most appropriate course of action in relation to the contaminant (e.g., developing a regulation to control it in drinking water, developing guidance, or deciding not to regulate it). The PFOA health assessment was initiated by the Office of Water, Office of Science and Technology in 2009. The draft Health Effects Support Document for Perfluoroctanoic Acid (PFOA) was completed in 2013 and released for public comment in February 2014. -
Oral Presentations
Journal of Inherited Metabolic Disease (2018) 41 (Suppl 1):S37–S219 https://doi.org/10.1007/s10545-018-0233-9 ABSTRACTS Oral Presentations PARALLEL SESSION 1A: Clycosylation and cardohydrate disorders O-002 Link between glycemia and hyperlipidemia in Glycogen Storage O-001 Disease type Ia Hoogerland J A1, Hijmans B S1, Peeks F1, Kooijman S3, 4, Bos T2, Fertility in classical galactosaemia, N-glycan, hormonal and inflam- Bleeker A1, Van Dijk T H2, Wolters H1, Havinga R1,PronkACM3, 4, matory gene expression interactions Rensen P C N3, 4,MithieuxG5, 6, Rajas F5, 6, Kuipers F1, 2,DerksTGJ1, Reijngoud D1,OosterveerMH1 Colhoun H O1,Rubio-GozalboME2,BoschAM3, Knerr I4,DawsonC5, Brady J J6,GalliganM8,StepienKM9, O'Flaherty R O7,MossC10, 1Dep Pediatrics, CLDM, Univ of Groningen, Groningen, Barker P11, Fitzgibbon M C6, Doran P8,TreacyEP1, 4, 9 Netherlands, 2Lab Med, CLDM, Univ of Groningen, Groningen, Netherlands, 3Dep of Med, Div of Endocrinology, LUMC, Leiden, 1Dept Paediatrics, Trinity College Dublin, Dublin, Ireland, 2Dept Paeds and Netherlands, 4Einthoven Lab Exp Vasc Med, LUMC, Leiden, Clin Genetics, UMC, Maastricht, Netherlands, 3Dept Paediatrics, AMC, Netherlands, 5Institut Nat Sante et Recherche Med, Lyon, Amsterdam, Netherlands, 4NCIMD, TSCUH, Dublin, Ireland, 5Dept France, 6Univ Lyon 1, Villeurbanne, France Endocrinology, NHS Foundation Trust, Birmingham, United Kingdom, 6Dept Clin Biochem, MMUH, Dublin, Ireland, 7NIBRT Glycoscience, Background: Glycogen Storage Disease type Ia (GSD Ia) is an NIBRT, Dublin, Ireland, 8UCDCRC,UCD,Dublin,Ireland,9NCIMD, inborn error of glucose metabolism characterized by fasting hypo- MMUH, Dublin, Ireland, 10Conway Institute, UCD, Dublin, Ireland, glycemia, hyperlipidemia and fatty liver disease. We have previ- 11CBAL, NHS Foundation, Cambridge, United Kingdom ously reported considerable heterogeneity in circulating triglycer- ide levels between individual GSD Ia patients, a phenomenon that Background: Classical Galactosaemia (CG) is caused by deficiency of is poorly understood. -
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. -
Characterization of the Scavenger Cell Proteome in Mouse and Rat Liver
Biol. Chem. 2021; 402(9): 1073–1085 Martha Paluschinski, Cheng Jun Jin, Natalia Qvartskhava, Boris Görg, Marianne Wammers, Judith Lang, Karl Lang, Gereon Poschmann, Kai Stühler and Dieter Häussinger* Characterization of the scavenger cell proteome in mouse and rat liver + https://doi.org/10.1515/hsz-2021-0123 The data suggest that the population of perivenous GS Received January 25, 2021; accepted July 4, 2021; scavenger cells is heterogeneous and not uniform as previ- published online July 30, 2021 ously suggested which may reflect a functional heterogeneity, possibly relevant for liver regeneration. Abstract: The structural-functional organization of ammonia and glutamine metabolism in the liver acinus involves highly Keywords: glutaminase; glutamine synthetase; liver specialized hepatocyte subpopulations like glutamine syn- zonation; proteomics; scavenger cells. thetase (GS) expressing perivenous hepatocytes (scavenger cells). However, this cell population has not yet been char- acterized extensively regarding expression of other genes and Introduction potential subpopulations. This was investigated in the present study by proteome profiling of periportal GS-negative and There is a sophisticated structural-functional organization in perivenous GS-expressing hepatocytes from mouse and rat. the liver acinus with regard to ammonium and glutamine Apart from established markers of GS+ hepatocytes such as metabolism (Frieg et al. 2021; Gebhardt and Mecke 1983; glutamate/aspartate transporter II (GLT1) or ammonium Häussinger 1983, 1990). Periportal hepatocytes express en- transporter Rh type B (RhBG), we identified novel scavenger zymes required for urea synthesis such as the rate-controlling cell-specific proteins like basal transcription factor 3 (BTF3) enzyme carbamoylphosphate synthetase 1 (CPS1) and liver- and heat-shock protein 25 (HSP25). -
Massive Parallel Sequencing As a New Diagnostic Approach For
Chaiyasap et al. BMC Medical Genetics (2017) 18:102 DOI 10.1186/s12881-017-0464-x RESEARCH ARTICLE Open Access Massive parallel sequencing as a new diagnostic approach for phenylketonuria and tetrahydrobiopterin-deficiency in Thailand Pongsathorn Chaiyasap1, Chupong Ittiwut1,2, Chalurmpon Srichomthong1,2, Apiruk Sangsin3, Kanya Suphapeetiporn1,2,4* and Vorasuk Shotelersuk1,2 Abstract Background: Hyperphenylalaninemia (HPA) can be classified into phenylketonuria (PKU) which is caused by mutations in the phenylalanine hydroxylase (PAH) gene, and BH4 deficiency caused by alterations in genes involved in tetrahydrobiopterin (BH4) biosynthesis pathway. Dietary restriction of phenylalanine is considered to be the main treatment of PKU to prevent irreversible intellectual disability. However, the same dietary intervention in BH4 deficiency patients is not as effective, as BH4 is also a cofactor in many neurotransmitter syntheses. Method: We utilized next generation sequencing (NGS) technique to investigate four unrelated Thai patients with hyperphenylalaninemia. Result: We successfully identified all eight mutant alleles in PKU or BH4-deficiency associated genes including three novel mutations, one in PAH and two in PTS, thus giving a definite diagnosis to these patients. Appropriate management can then be provided. Conclusion: This study identified three novel mutations in either the PAH or PTS gene and supported the use of NGS as an alternative molecular genetic approach for definite diagnosis of hyperphenylalaninemia, thus leading to proper management of these patients in Thailand. Keywords: Next generation sequencing, Exome, Hyperphenylalaninemia, Phenylketonuria, Tetrahydrobiopterin deficiency, Newborn screening Background 120 μmol/l (2 mg/dl), the individual is considered to be Phenylketonuria (PKU) is an autosomal recessive metabolic hyperphenylalaninemia (HPA) and needs further diagnosis disorder, characterized by progressive intellectual disability, [4]. -
Blueprint Genetics Hyperphenylalaninemia Panel
Hyperphenylalaninemia Panel Test code: ME2001 Is a 6 gene panel that includes assessment of non-coding variants. Is ideal for patients with a clinical suspicion of hyperphenylalaninaemias including hyperphenylalaninemia due to BH4 deficiency. The genes on this panel are included in the Comprehansive Metabolism Panel. About Hyperphenylalaninemia Hyperphenylalaninemias (HPA) are errors in metabolism resulting in characterics of elevated levels of phenylalanine amino acid in the blood. Phenylketonuria (PKU) results in hyperphenylalaninemia if left untreated. Elevated levels if phenylalanine will make a severe risk of intellectual disability for a child. Unborn babies with mutation in homozygous state are unaffected as mother’s circulation prevents buildup. After birth, phenylalanine-restricted diet prevents intellectual problems and the persons with homozygous mutated genotype have normal mental development. However, maternal PKU without metabolic control predisposes babies to severe mental retardation and heart defects. This is an example of a genetic disease of a baby based on mother’s genotype. Classical PKU is caused by mutations in PAH, but some 2% of all HPAs result from impaired synthesis or recycling of tetrahydrobiopterin (BH4). Causative mutations in these cases are in GCH1, PCBD1, PTS or QDPR genes. The worldwide prevalence of PKU is estimated at 1:10 000 births having, however, rather big variation in different populations. The prevalence of tetrahydrobiopterin is estimated at <1:500 000 newborns. However, in certain populations -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Generate Metabolic Map Poster
Authors: Pallavi Subhraveti Ron Caspi Peter Midford Peter D Karp An online version of this diagram is available at BioCyc.org. Biosynthetic pathways are positioned in the left of the cytoplasm, degradative pathways on the right, and reactions not assigned to any pathway are in the far right of the cytoplasm. Transporters and membrane proteins are shown on the membrane. Ingrid Keseler Periplasmic (where appropriate) and extracellular reactions and proteins may also be shown. Pathways are colored according to their cellular function. Gcf_001591825Cyc: Bacillus vietnamensis NBRC 101237 Cellular Overview Connections between pathways are omitted for legibility. Anamika Kothari sn-glycerol phosphate phosphate pro phosphate phosphate phosphate thiamine molybdate D-xylose D-ribose glutathione 3-phosphate D-mannitol L-cystine L-djenkolate lanthionine α,β-trehalose phosphate phosphate [+ 3 more] α,α-trehalose predicted predicted ABC ABC FliY ThiT XylF RbsB RS10935 UgpC TreP PutP RS10200 PstB PstB RS10385 RS03335 RS20030 RS19075 transporter transporter of molybdate of phosphate α,β-trehalose 6-phosphate L-cystine D-xylose D-ribose sn-glycerol D-mannitol phosphate phosphate thiamine glutathione α α phosphate phosphate phosphate phosphate L-djenkolate 3-phosphate , -trehalose 6-phosphate pro 1-phosphate lanthionine molybdate phosphate [+ 3 more] Metabolic Regulator Amino Acid Degradation Amine and Polyamine Biosynthesis Macromolecule Modification tRNA-uridine 2-thiolation Degradation ATP biosynthesis a mature peptidoglycan a nascent β an N-terminal-