DOCSLIB.ORG

Molecular Genetics of Residual Feed Intake and Mitochondrial Function in Cattle

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Molecular Genetics of Residual Feed Intake and Mitochondrial Function in Cattle MOLECULAR GENETICS OF RESIDUAL FEED INTAKE AND MITOCHONDRIAL FUNCTION IN CATTLE By Nadiatur Akmar Zulkifli A thesis submitted to the University of Adelaide in fulfilment of the requirement of the degree of Doctor of Philosophy The University of Adelaide School of Animal and Veterinary Sciences July 2016 TABLE OF CONTENTS Table of Contents ii Index of Figures vii Index of Tables ix Index of Appendices xii Abstract xiii Declaration xvi Acknowledgements xvii Dedication xix Chapter 1 : Literature Review 1 1.1 Introduction 2 1.2 Cattle 3 1.2.1 Jersey cattle 3 1.2.2 Limousin cattle 4 1.2.3 Jersey x Limousin cattle 6 1.2.4 Genetics of cattle 6 1.3 Residual feed intake 7 1.3.1 Residual feed intake as a genetic trait 10 1.3.2 Measurement of feed intake 11 1.3.2.1 Centralised testing facility 12 1.3.2.2 On-farm testing 12 1.3.3.3 Measurement on pasture 12 1.3.3 Genetic correlations for measures of body composition with residual feed intake 13 1.3.4 Quantitative trait loci in residual feed intake 14 1.4 Mechanisms affecting residual feed intake 17 1.4.1 Energy metabolism 17 1.4.2 Mitochondrial function 19 1.4.3 Cellular respiration process 21 ii 1.4.3.1 Glycolyis 21 1.4.3.2 Krebs cycle 24 1.4.3.3 Electron transport chain 26 1.4.3.3.1 Complex I 27 1.4.3.3.2 Complex II 28 1.4.3.3.3 Complex III 28 1.4.3.3.4 Complex IV 29 1.4.3.3.5 Complex V 29 1.4.3.4 Oxidative phosphorylation 31 1.4.3.5 Reactive oxygen species 32 1.4.4 Other known energy pathways affecting residual feed intake 34 1.4.4.1 Uncoupling proteins 34 1.4.4.2 Adenine monophosphate activated protein kinase (AMPK) 34 1.5 Relationship between mitochondrial function and residual feed intake in animals 35 1.5.1 Poultry 35 1.5.2 Pigs 36 1.5.3 Cattle 37 1.6 Summary 38 Chapter 2 : Materials and Methods 40 2.1 QTL mapping of residual feed intake in cattle 41 2.1.1 Cattle QTL mapping experimental design 41 2.1.2 Single Nucleotide Polymorphisms (SNP) experiments 43 2.1.2.1 Selection of candidate genes for SNP detection 43 2.1.2.2 Genomic DNA purification 43 2.1.2.3 DNA concentration 44 2.1.2.4 Primer design 44 2.1.2.5 Polymerase Chain Reaction (PCR) iii condition optimisation 44 2.1.2.6 Gel electrophoresis 46 2.1.2.7 PCR purification 46 2.1.2.8 DNA sequencing 47 2.2 Genotyping 49 2.2.1 High Resolution Melt (HRM) 49 2.2.2 Genotyping analysis 51 2.2.3 Pathway analysis 53 2.3 Mitochondrial enzyme experiments 53 2.3.1 Selection lines 53 2.3.2 Sample collection: Liver 54 2.3.3 Mitochondrial preparation from frozen liver samples 54 2.3.4 Bradford Assay 55 2.3.5 Oxidative phosphorylation enzyme complexes assays 55 2.3.5.1 Complex I Activity 55 2.3.5.2 Complex III Activity 56 2.3.5.3 Complex IV Activity 56 2.3.5.4 Protein carbonyl assay 56 2.3.5.5 Analysis for Biochemical Assay 57 Chapter 3 : Candidate Genes for RFI : Identification and DNA Variants 58 3.1 Introduction 59 3.2 Materials and Methods 60 3.2.1 DNA samples 60 3.2.2 Primer design 61 3.2.3 Polymerase Chain Reaction (PCR) 62 3.2.4 Sequencing 63 3.3 Results 63 3.3.1 Candidate Genes 63 3.3.1.1 Catalase 64 iv 3.3.1.2 Aldolase B 66 3.3.1.3 Adenylate Kinase 1 67 3.3.1.4 Superoxide Dismutase 1 68 3.3.1.5 Succinyl Co A Synthetase 69 3.3.1.6 Superoxide Dismutase 2 71 3.3.1.7 Ghrelin 71 3.3.1.8 NADH Dehydrogenase (Ubiquinone) I Beta Subcomplex, 5, 16kDa 72 3.3.1.9 NADH Dehydrogenase (Ubiquinone) I Alpha Subcomplex, 8, 19kDa 73 3.3.1.10 Hydroxyacyl-CoA Dehydrogenase-β Subunit 73 3.3.2 Sequencing variants 74 3.4 Discussion 80 3.5 Summary 83 Chapter 4 : Candidate Gene Associations 85 4.1 Introduction 86 4.2 Methods 88 4.2.1 Genotyping 88 4.2.1.1 High Resolution Melt (HRM) 89 4.2.1.2 Data analysis 90 4.3 Results 90 4.3.1 High Resolution Melt (HRM) 90 4.3.2 SNP association studies 96 4.3.3 Haplotype effects 105 4.4 Discussion 108 4.5 Summary 114 Chapter 5 : Candidate Gene Pathways and Epistatic Effects 116 5.1 Introduction 117 5.2 Methods 117 5.3 Results 118 v 5.3.1 Pathway analysis 118 5.3.2 Epistatic effects 122 5.3.2.1 Candidate gene epistatic interactions 122 5.3.2.2 Additional epistatic interactions on RFI and fat traits 130 5.4 Discussion 131 5.5 Summary 134 Chapter 6 : Mitochondrial enzyme assays 136 6.1 Introduction 137 6.2 Materials and Methods 139 6.2.1 Liver samples 140 6.2.2 Analysis for biochemical assays 141 6.3 Results 141 6.3.1 Bradford assay 141 6.3.2 Complex I enzyme assay 142 6.3.3 Complex III enzyme assay 144 6.3.4 Complex IV enzyme assay 146 6.3.5 Protein carbonyl assay 148 6.4 Discussion 150 6.5 Summary 155 Chapter 7 : General discussion 156 7.1 Introduction 157 7.2 Residual feed intake and mitochondrial function 160 7.3 Residual feed intake candidate genes 163 7.4 Residual feed intake and body composition 166 7.5 Conclusion 168 Appendices 169 References 195 vi INDEX OF FIGURES Figure 1.1 Relationship between feed intake and the expected weight gain 9 Figure 1.2 Contribution of biological mechanisms to variation in residual feed intake as determined from experiments on divergently selected cattle 19 Figure 1.3 Mitochondria structure 20 Figure 1.4 The reactions of glycolysis convert glucose to pyruvate 23 Figure 1.5 Reactions of the Krebs cycle 26 Figure 1.6 Electron transport chain 30 Figure 2.1 Davies cattle QTL mapping backcross design 42 Figure 3.1 Mechanism of oxidative cellular damage 65 Figure 3.2 Fructose utilisation in the liver showing its interrelationship with glucose and fatty acid metabolism 67 Figure 3.3 Regulation of energy homeostasis by the AMPK system 68 Figure 3.4 The disproportionation of superoxide is a two-step oxidation-reduction reaction that involves the cycling of the copper atom in SOD1 from Cu2+ to Cu+ and back to Cu+2 69 Figure 3.5 Krebs cycle and methylmalonate metabolism 70 Figure 4.1 Melt curve of SOD2SNP3, a transversion SNP with two genotypes, GC and GG 92 Figure 4.2 Melt profile analysis of SOD2SNP3, a transversion SNP with two genotypes, GC and GG 92 Figure 4.3 Melt curve of HADSNP7, a transversion SNP with three genotypes, AT, TT and AA 93 Figure 4.4 Melt profile analysis of HADSNP7, a transversion SNP with three genotypes, AT, TT and AA 93 Figure 4.5 Melt curve of HADSNP2, a transition SNP with three genotypes, AA, GG and AG 94 Figure 4.6 Melt profile analysis of HADSNP2, a transition SNP with three genotypes, AA, GG and AG 94 Figure 6.1 Standard curve at 595 nm for low RFI samples 142 vii Figure 6.2 Correlation between mid-parent RFI EBV and Complex I activity 144 Figure 6.3 Correlation between mid-parent RFI EBV and Complex III activity 146 Figure 6.4 Correlation between mid-parent RFI EBV and Complex IV activity 148 Figure 6.5 Correlation between mid-parent RFI EBV and ROS activity 149 viii INDEX OF TABLES Table 1.1 Heritability estimates for net feed efficiency in different species 11 Table 1.2 Genetic correlation for measures of body composition with residual feed intake 14 Table 1.3 NFE QTL identified in the Davies Jersey x Limousin herd 16 Table 2.1 PCR reagents concentration 45 Table 2.2 Sequencing reagents 47 Table 2.3 High resolution melt reagents concentration 50 Table 3.1 F1 mapping sires and their parents identification number 61 Table 3.2 Primer sets for neighbouring exons 62 Table 3.3 Primer sets for exon > 500bp 62 Table 3.4 Selected candidate genes and their function 64 Table 3.5 DNA variants identified in the candidate genes 75 Table 3.6 Summary of DNA variants found in candidate genes 78 Table 3.7 Synonymous and non-synonymous SNPs 78 Table 4.1 List of genotyped SNPs 89 Table 4.2 Summary data of the 14 genotyped SNPs 91 Table 4.3 Number of progeny with each genotype and allele frequencies 95 Table 4.4 Residual feed intake related traits 96 Table 4.5 Specific fat depot traits for association studies 97 Table 4.6 Traits affected by SNPs without and with MSTN F94L genotype in the model 98 Table 4.7 Number of SNPs affecting each trait with and without MSTN F94L genotype in the model 100 Table 4.8 Fat traits affected by SNPs without and with MSTN F94L genotype in the model 101 Table 4.9 Number of SNPs affecting fat depot trait with and without MSTN F94L genotype in the model 102 ix Table 4.10 SNP effects on daily feed intake (DFI) and residual feed intake (RFI) with and without MSTN F94L genotype in the model 103 Table 4.11 Additional SNPs analysed for effects on RFI with and without MSTN F94L genotype in the model 104 Table 4.12 Additional SNPs with significant effects on residual feed intake with and without MSTN F94L genotype in the model 105 Table 4.13 SNP interactions within genes without MSTN F94L genotype in the model 107 Table 4.14 SNP interactions within genes with MSTN F94L genotype in the model 107 Table 5.1 Protein state interactions 120 Table 5.2 Gene expression interactions 121 Table 5.3 Tests of significance for SNP interactions between candidate genes affecting RFI related traits 125 Table 5.4 Tests of significant for SNP interactions between candidate genes affecting specific fat depot traits 128 Table 5.5 SNP interactions between genes for RFI and DFI with and without the MSTN F94L genotype in the model 129 Table 5.6 Additional SNPs interactions with selected fat traits without MSTN F94L genotype in the model 130 Table 5.7 Additional SNPs interactions with selected fat traits with MSTN F94L genotype in the model 130 Table 6.1 Complex I enzyme activity of high and low residual feed intake animals 142 Table 6.2 Regression analysis for RFI related traits and Complex I enzyme activity with correlation and test of significant slope 143 Table 6.3 Complex III enzyme activity of high and low residual feed intake animals 144 Table 6.4 Regression analysis for RFI
Load more

Recommended publications
  • Remodeling Adipose Tissue Through in Silico Modulation of Fat Storage For
    Chénard et al. BMC Systems Biology (2017) 11:60 DOI 10.1186/s12918-017-0438-9 RESEARCHARTICLE Open Access Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes Thierry Chénard2, Frédéric Guénard3, Marie-Claude Vohl3,4, André Carpentier5, André Tchernof4,6 and Rafael J. Najmanovich1* Abstract Background: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. Results: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each
    [Show full text]
  • Multi-Targeted Mechanisms Underlying the Endothelial Protective Effects of the Diabetic-Safe Sweetener Erythritol
    Multi-Targeted Mechanisms Underlying the Endothelial Protective Effects of the Diabetic-Safe Sweetener Erythritol Danie¨lle M. P. H. J. Boesten1*., Alvin Berger2.¤, Peter de Cock3, Hua Dong4, Bruce D. Hammock4, Gertjan J. M. den Hartog1, Aalt Bast1 1 Department of Toxicology, Maastricht University, Maastricht, The Netherlands, 2 Global Food Research, Cargill, Wayzata, Minnesota, United States of America, 3 Cargill RandD Center Europe, Vilvoorde, Belgium, 4 Department of Entomology and UCD Comprehensive Cancer Center, University of California Davis, Davis, California, United States of America Abstract Diabetes is characterized by hyperglycemia and development of vascular pathology. Endothelial cell dysfunction is a starting point for pathogenesis of vascular complications in diabetes. We previously showed the polyol erythritol to be a hydroxyl radical scavenger preventing endothelial cell dysfunction onset in diabetic rats. To unravel mechanisms, other than scavenging of radicals, by which erythritol mediates this protective effect, we evaluated effects of erythritol in endothelial cells exposed to normal (7 mM) and high glucose (30 mM) or diabetic stressors (e.g. SIN-1) using targeted and transcriptomic approaches. This study demonstrates that erythritol (i.e. under non-diabetic conditions) has minimal effects on endothelial cells. However, under hyperglycemic conditions erythritol protected endothelial cells against cell death induced by diabetic stressors (i.e. high glucose and peroxynitrite). Also a number of harmful effects caused by high glucose, e.g. increased nitric oxide release, are reversed. Additionally, total transcriptome analysis indicated that biological processes which are differentially regulated due to high glucose are corrected by erythritol. We conclude that erythritol protects endothelial cells during high glucose conditions via effects on multiple targets.
    [Show full text]
  • Remodeling Adipose Tissue Through in Silico Modulation of Fat Storage For
    Chénard et al. BMC Systems Biology (2017) 11:60 DOI 10.1186/s12918-017-0438-9 RESEARCHARTICLE Open Access Remodeling adipose tissue through in silico modulation of fat storage for the prevention of type 2 diabetes Thierry Chénard2, Frédéric Guénard3, Marie-Claude Vohl3,4, André Carpentier5, André Tchernof4,6 and Rafael J. Najmanovich1* Abstract Background: Type 2 diabetes is one of the leading non-infectious diseases worldwide and closely relates to excess adipose tissue accumulation as seen in obesity. Specifically, hypertrophic expansion of adipose tissues is related to increased cardiometabolic risk leading to type 2 diabetes. Studying mechanisms underlying adipocyte hypertrophy could lead to the identification of potential targets for the treatment of these conditions. Results: We present iTC1390adip, a highly curated metabolic network of the human adipocyte presenting various improvements over the previously published iAdipocytes1809. iTC1390adip contains 1390 genes, 4519 reactions and 3664 metabolites. We validated the network obtaining 92.6% accuracy by comparing experimental gene essentiality in various cell lines to our predictions of biomass production. Using flux balance analysis under various test conditions, we predict the effect of gene deletion on both lipid droplet and biomass production, resulting in the identification of 27 genes that could reduce adipocyte hypertrophy. We also used expression data from visceral and subcutaneous adipose tissues to compare the effect of single gene deletions between adipocytes from each
    [Show full text]
  • Mitochondrial Hepatopathies Etiology and Genetics the Hepatocyte Mitochondrion Can Function Both As a Cause and As a Target of Liver Injury
    Mitochondrial Hepatopathies Etiology and Genetics The hepatocyte mitochondrion can function both as a cause and as a target of liver injury. Most mitochondrial hepatopathies involve defects in the mitochondrial respiratory chain enzyme complexes (Figure 1). Resultant dysfunction of mitochondria yields deficient oxidative phosphorylation (OXPHOS), increased generation of reactive oxygen species (ROS), accumulation of hepatocyte lipid, impairment of other metabolic pathways and activation of both apoptotic and necrotic pathways of cellular death. Figure 1: Since the mitochondria are under dual control of nuclear DNA and mitochondrial DNA (mtDNA), mutations in genes of both classes have been associated with inherited mitochondrial myopathies, encephalopathies, and hepatopathies. Autosomal nuclear gene defects affect a variety of mitochondrial processes such as protein assembly, mtDNA synthesis and replication (e.g., deoxyguanosine kinase [dGUOK]) and DNA polymerase gamma [POLG]), and transport of nucleotides or metals. MPV17 (function unknown) and RRM2B (encoding the cytosolic p53-inducible ribonucleotide reductase small subunit) are two genes recently identified as also causing mtDNA depletion syndrome and liver failure, as has TWINKLE, TRMU, and SUCLG1. Most children with mitochondrial hepatopathies have identified or presumed mutations in these nuclear genes, rather than mtDNA genes. A classification of primary mitochondrial hepatopathies involving energy metabolism is presented in Table 1. Drug interference with mtDNA replication is now recognized as a cause of acquired mtDNA depletion that can result in liver failure, lactic acidosis, and myopathy in human immunodeficiency virus infected patients and, previously, in hepatitis B virus patients treated with nucleoside reverse transcriptase inhibitors. Current estimates suggest a minimum prevalence of all mitochondrial diseases of 11.5 cases per 100,000 individuals, or 1 in 8500 of the general population.
    [Show full text]
  • A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family
    Rockefeller University Digital Commons @ RU Student Theses and Dissertations 2018 A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family Linda Molla Follow this and additional works at: https://digitalcommons.rockefeller.edu/ student_theses_and_dissertations Part of the Life Sciences Commons A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy by Linda Molla June 2018 © Copyright by Linda Molla 2018 A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY Linda Molla, Ph.D. The Rockefeller University 2018 APOBEC2 is a member of the AID/APOBEC cytidine deaminase family of proteins. Unlike most of AID/APOBEC, however, APOBEC2’s function remains elusive. Previous research has implicated APOBEC2 in diverse organisms and cellular processes such as muscle biology (in Mus musculus), regeneration (in Danio rerio), and development (in Xenopus laevis). APOBEC2 has also been implicated in cancer. However the enzymatic activity, substrate or physiological target(s) of APOBEC2 are unknown. For this thesis, I have combined Next Generation Sequencing (NGS) techniques with state-of-the-art molecular biology to determine the physiological targets of APOBEC2. Using a cell culture muscle differentiation system, and RNA sequencing (RNA-Seq) by polyA capture, I demonstrated that unlike the AID/APOBEC family member APOBEC1, APOBEC2 is not an RNA editor. Using the same system combined with enhanced Reduced Representation Bisulfite Sequencing (eRRBS) analyses I showed that, unlike the AID/APOBEC family member AID, APOBEC2 does not act as a 5-methyl-C deaminase.
    [Show full text]
  • Screen for Abnormal Mitochondrial Phenotypes in Mouse Embryonic Stem Cells Identifies a Model for Succinyl-Coa Ligase Deficiency and Mtdna Depletion Taraka R
    © 2014. Published by The Company of Biologists Ltd | Disease Models & Mechanisms (2014) 7, 271-280 doi:10.1242/dmm.013466 RESOURCE ARTICLE Screen for abnormal mitochondrial phenotypes in mouse embryonic stem cells identifies a model for succinyl-CoA ligase deficiency and mtDNA depletion Taraka R. Donti1,‡, Carmen Stromberger1,*,‡, Ming Ge1, Karen W. Eldin2, William J. Craigen1,3 and Brett H. Graham1,§ ABSTRACT prevalence of mitochondrial disorders might be as high as 1 in 5000, Mutations in subunits of succinyl-CoA synthetase/ligase (SCS), a making mitochondrial disease one of the more common genetic component of the citric acid cycle, are associated with mitochondrial causes of encephalomyopathies and multisystem disease (Schaefer et encephalomyopathy, elevation of methylmalonic acid (MMA), and al., 2004; Elliott et al., 2008; Schaefer et al., 2008). Despite important mitochondrial DNA (mtDNA) depletion. A FACS-based retroviral- insights into clinical, biochemical and molecular features of these mediated gene trap mutagenesis screen in mouse embryonic stem disorders, the underlying molecular pathogenesis remains poorly (ES) cells for abnormal mitochondrial phenotypes identified a gene understood and no clearly effective therapies exist. Mitochondria trap allele of Sucla2 (Sucla2SAβgeo), which was used to generate contain their own genome that consists of a multicopy, ~16.4-kilobase transgenic mice. Sucla2 encodes the ADP-specific β-subunit isoform circular chromosome. This mitochondrial DNA (mtDNA) encodes 13 of SCS. Sucla2SAβgeo homozygotes exhibited recessive lethality, with polypeptides that are subunits of various respiratory chain complexes most mutants dying late in gestation (e18.5). Mutant placenta and as well as 22 tRNAs and two rRNAs required for mitochondrial embryonic (e17.5) brain, heart and muscle showed varying degrees protein translation.
    [Show full text]
  • Dominant Mutations in Mtdna Maintenance Gene SSBP1 Cause Optic Atrophy and Foveopathy
    Dominant mutations in mtDNA maintenance gene SSBP1 cause optic atrophy and foveopathy Camille Piro-Mégy, … , Maria Sola, Cécile Delettre J Clin Invest. 2020;130(1):143-156. https://doi.org/10.1172/JCI128513. Research Article Genetics Ophthalmology Graphical abstract Find the latest version: https://jci.me/128513/pdf The Journal of Clinical Investigation RESEARCH ARTICLE Dominant mutations in mtDNA maintenance gene SSBP1 cause optic atrophy and foveopathy Camille Piro-Mégy,1 Emmanuelle Sarzi,1 Aleix Tarrés-Solé,2 Marie Péquignot,1 Fenna Hensen,3 Mélanie Quilès,1 Gaël Manes,1 Arka Chakraborty,2 Audrey Sénéchal,1 Béatrice Bocquet,1,4 Chantal Cazevieille,1 Agathe Roubertie,1,4 Agnès Müller,1,5 Majida Charif,6 David Goudenège,6 Guy Lenaers,6 Helmut Wilhelm,7 Ulrich Kellner,8 Nicole Weisschuh,9 Bernd Wissinger,9 Xavier Zanlonghi,10 Christian Hamel,1,4 Johannes N. Spelbrink,3 Maria Sola,2 and Cécile Delettre1 1Institute of Neurosciences of Montpellier, INSERM, University of Montpellier, Montpellier, France. 2Structural MitoLab, Department of Structural Biology, “Maria de Maeztu” Unit of Excellence, Molecular Biology Institute Barcelona (IBMB-CSIC), Barcelona, Spain. 3Radboud Center for Mitochondrial Medicine, Department of Paediatrics, Radboudumc, Nijmegen, Netherlands. 4CHU Montpellier, Centre of Reference for Genetic Sensory Diseases, Gui de Chauliac Hospital, Montpellier, France. 5Faculté de Pharmacie, Université de Montpellier, Montpellier, France. 6UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France. 7University Eye Hospital, Centre for Ophthalmology, University of Tübingen, Tübingen, Germany. 8Rare Retinal Disease Center, AugenZentrum Siegburg, MVZ Augenärztliches Diagnostik- und Therapiecentrum Siegburg GmbH, Siegburg, Germany. 9Institute for Ophthalmic Research, Centre for Ophthalmology, University of Tübingen, Tübingen, Germany.
    [Show full text]
  • SUCLG1 Gene Succinate-Coa Ligase Alpha Subunit
    SUCLG1 gene succinate-CoA ligase alpha subunit Normal Function The SUCLG1 gene provides instructions for making one part, the alpha subunit, of an enzyme called succinate-CoA ligase. Two slightly different versions of this enzyme are made with the alpha subunit: ADP-forming succinate-CoA ligase (A-SUCL) and GDP- forming succinate-CoA ligase (G-SUCL). A-SUCL is most active in tissues that require a large amount of energy, such as those of the brain and muscles. G-SUCL is most active in other tissues, particularly in the liver and kidneys. Both versions of succinate-CoA ligase play a critical role in mitochondria, which are structures inside cells that convert the energy from food into a form that cells can use. Within mitochondria, these enzymes are likely involved in a series of chemical reactions known as the citric acid cycle or Krebs cycle. These reactions allow cells to use oxygen and generate energy. Mitochondria each contain a small amount of DNA, known as mitochondrial DNA or mtDNA. Studies suggest that succinate-CoA ligase interacts with another enzyme, nucleoside diphosphate kinase, to produce and maintain the building blocks of mitochondrial DNA. Having an adequate amount of mitochondrial DNA is essential for normal energy production within cells. Health Conditions Related to Genetic Changes Succinate-CoA ligase deficiency At least two mutations in the SUCLG1 gene have been identified in people with succinate-CoA ligase deficiency. One mutation has been found to cause a very severe form of the condition known as fatal infantile lactic acidosis. Children with this condition usually live only a few days after birth.
    [Show full text]
  • REPORT Deficiency of the a Subunit of Succinate–Coenzyme a Ligase
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector REPORT Deficiency of the a Subunit of Succinate–Coenzyme A Ligase Causes Fatal Infantile Lactic Acidosis with Mitochondrial DNA Depletion Elsebet Ostergaard, Ernst Christensen, Elisabeth Kristensen, Bodil Mogensen, Morten Duno, Eric A. Shoubridge, and Flemming Wibrand Fatal infantile lactic acidosis is a severe metabolic disorder characterized by the onset of lactic acidosis within the 1st d of life and early death. We found a combined respiratory-chain enzyme deficiency associated with mitochondrial DNA (mtDNA) depletion in a small consanguineous family with this disorder. To identify the disease-causing gene, we per- formed single-nucleotide polymorphism homozygosity mapping and found homozygous regions on four chromosomes. DNA sequencing revealed a homozygous 2-bp deletion in SUCLG1, a gene that encodes the a subunit of the Krebs-cycle enzyme succinate–coenzyme A ligase (SUCL). The mtDNA depletion is likely explained by decreased mitochondrial nucleoside diphosphate kinase (NDPK) activity resulting from the inability of NDPK to form a complex with SUCL. The molecular basis of several disorders resulting from a line, and he had hepatomegaly and severe hypothermia. decrease in mtDNA copy number—the mtDNA-depletion He was hypotonic, and, in the 1st d of life, he became syndromes (MIM 251880)—has been elucidated over the severely acidotic, with a blood pH of 6.7. He had Cheyne- past decade. Mutations in six genes have now been re- Stokes respiration and received respiratory support. Find- ported to cause mtDNA depletion in humans: TP, which ings from an electroencephalogram were severely abnor- is associated with mitochondrial neurogastrointestinal mal, with focal and paroxystic activity, sharp waves, and 1 encephalopathy (MNGIE [MIM 603041]) ; TK2, which triphasic potentials bilaterally.
    [Show full text]
  • Two Transgenic Mouse Models for Β-Subunit Components of Succinate-Coa Ligase Yielding Pleiotropic Metabolic Alterations
    Two transgenic mouse models for -subunit components of succinate-CoA ligase yielding pleiotropic metabolic alterations Kacso, Gergely; Ravasz, Dora; Doczi, Judit; Németh, Beáta; Madgar, Ory; Saada, Ann; Ilin, Polina; Miller, Chaya; Ostergaard, Elsebet; Iordanov, Iordan; Adams, Daniel; Vargedo, Zsuzsanna; Araki, Masatake; Araki, Kimi; Nakahara, Mai; Ito, Haruka; Gál, Aniko; Molnár, Mária J; Nagy, Zsolt; Patocs, Attila; Adam-Vizi, Vera; Chinopoulos, Christos Published in: Biochemical Journal DOI: 10.1042/BCJ20160594 Publication date: 2016 Document version Publisher's PDF, also known as Version of record Document license: CC BY Citation for published version (APA): Kacso, G., Ravasz, D., Doczi, J., Németh, B., Madgar, O., Saada, A., Ilin, P., Miller, C., Ostergaard, E., Iordanov, I., Adams, D., Vargedo, Z., Araki, M., Araki, K., Nakahara, M., Ito, H., Gál, A., Molnár, M. J., Nagy, Z., ... Chinopoulos, C. (2016). Two transgenic mouse models for -subunit components of succinate-CoA ligase yielding pleiotropic metabolic alterations. Biochemical Journal, 473(20), 3463-3485. https://doi.org/10.1042/BCJ20160594 Download date: 26. Sep. 2021 Biochemical Journal (2016) 473 3463–3485 DOI: 10.1042/BCJ20160594 Research Article Two transgenic mouse models for β-subunit components of succinate-CoA ligase yielding pleiotropic metabolic alterations Gergely Kacso1,2, Dora Ravasz1,2, Judit Doczi1,2, Beáta Németh1,2, Ory Madgar1,2, Ann Saada3, Polina Ilin3, Chaya Miller3, Elsebet Ostergaard4, Iordan Iordanov1,5, Daniel Adams1,2, Zsuzsanna Vargedo1,2, Masatake
    [Show full text]
  • Syndromes Associated with Mitochondrial DNA Depletion
    Nogueira et al. Italian Journal of Pediatrics 2014, 40:34 http://www.ijponline.net/content/40/1/34 ITALIAN JOURNAL OF PEDIATRICS REVIEW Open Access Syndromes associated with mitochondrial DNA depletion Célia Nogueira1†, Ligia S Almeida1†, Claudia Nesti2, Ilaria Pezzini2, Arnaldo Videira3, Laura Vilarinho1,5* and Filippo M Santorelli2,4* Abstract Mitochondrial dysfunction accounts for a large group of inherited metabolic disorders most of which are due to a dysfunctional mitochondrial respiratory chain (MRC) and, consequently, deficient energy production. MRC function depends on the coordinated expression of both nuclear (nDNA) and mitochondrial (mtDNA) genomes. Thus, mitochondrial diseases can be caused by genetic defects in either the mitochondrial or the nuclear genome, or in the cross-talk between the two. This impaired cross-talk gives rise to so-called nuclear-mitochondrial intergenomic communication disorders, which result in loss or instability of the mitochondrial genome and, in turn, impaired maintenance of qualitative and quantitative mtDNA integrity. In children, most MRC disorders are associated with nuclear gene defects rather than alterations in the mtDNA itself. The mitochondrial DNA depletion syndromes (MDSs) are a clinically heterogeneous group of disorders with an autosomal recessive pattern of transmission that have onset in infancy or early childhood and are characterized by a reduced number of copies of mtDNA in affected tissues and organs. The MDSs can be divided into least four clinical presentations: hepatocerebral, myopathic, encephalomyopathic and neurogastrointestinal. The focus of this review is to offer an overview of these syndromes, listing the clinical phenotypes, together with their relative frequency, mutational spectrum, and possible insights for improving diagnostic strategies.
    [Show full text]
  • Table 1. Antibodies Used for Chromatin Immunoprecipitation (Chip)
    Table 1. Antibodies used for chromatin immunoprecipitation (ChIP) Protein Antibody Manufacturer References Western blot ChIP p65 sc-372 Santa Cruz (1, 2) (3-5) Biotechnology p50 sc-1190 Santa Cruz (6) (7) Biotechnology RelB sc-226 Santa Cruz (8) (5) Biotechnology c-Rel sc-71 Santa Cruz (8) (5, 9) Biotechnology p52 06-413 Upstate Biotechnology, (10) Lake Placid, NY E2F4 sc-1082 Santa Cruz (11) (12) Biotechnology Pol II 8WG16 (13) (14) The fact that the p65 dataset has no targets in unstimulated cells confirms the lack of background enrichment from the Dynal magnetic beads. The number of p50 targets in unstimulated cells is higher than for the other subunits. We were concerned that this might be due to the antibody used. Therefore, we tested another antibody raised against the N-terminus of the protein (sc-1191). In test experiments, 90% of enriched gene promoters were shared between the two p50 antibodies (data not shown). 1. Rodriguez, M. S., Thompson, J., Hay, R. T. & Dargemont, C. (1999) J. Biol. Chem. 274, 9108-9115. 2. Huang, T. T., Kudo, N., Yoshida, M. & Miyamoto, S. (2000) Proc. Natl. Acad. Sci. USA 97, 1014-1019. 3. Nissen, R. M. & Yamamoto, K. R. (2000) Genes Dev. 14, 2314-2329. 4. Martone, R., Euskirchen, G., Bertone, P., Hartman, S., Royce, T. E., Luscombe, N. M., Rinn, J. L., Nelson, F. K., Miller, P., Gerstein, M., et al. (2003) Proc. Natl. Acad. Sci. USA 100, 12247-12252. 5. Saccani, S., Pantano, S. & Natoli, G. (2003) Mol. Cell 11, 1563-1574. 6. Yamazaki, T. & Kurosaki, T.
    [Show full text]