Table 2. List of 113 Potential Blastocystis Mitochondrial Proteins and Proteins Associated with Mitochondria with Their EST Accession Numbers
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Progressive Encephalopathy and Central Hypoventilation Related to Homozygosity of NDUFV1 Nuclear Gene, a Rare Mitochondrial Disease
Avens Publishing Group Inviting Innovations Open Access Case Report J Pediatr Child Care August 2019 Volume:5, Issue:1 © All rights are reserved by AL-Buali MJ, et al. AvensJournal Publishing of Group Inviting Innovations Progressive Encephalopathy Pediatrics & and Central Hypoventilation Child Care AL-Buali MJ*, Al Ramadhan S, Al Buali H, Al-Faraj J and Related to Homozygosity of Al Mohanna M Pediatric Department , Maternity Children Hospital , Saudi Arabia *Address for Correspondence: NDUFV1 Nuclear Gene, a Rare Al-buali MJ, Pediatric Consultant and Consultant of Medical Genetics, Deputy Chairman of Medical Genetic Unite, Pediatrics Department , Maternity Children Hospital, Al-hassa, Hofuf city, Mitochondrial Disease Saudi Arabia; E-mail: [email protected] Submission: 15 July 2019 Accepted: 5 August 2019 Keywords: Progressive encephalopathy; Central hypoventilation; Published: 9 August 2019 Nuclear mitochondrial disease; NDUFV1 gene Copyright: © 2019 AL-Buali MJ, et al. This is an open access article distributed under the Creative Commons Attribution License, which Abstract permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Mitochondrial diseases are a group of disorders caused by dysfunctional organelles that generate energy for our body. Mitochondria small double-membrane organelles found in of the most common groups of genetic diseases with a minimum every cell of the human body except red blood cells. Mitochondrial diseases are sometimes caused by mutations in the mitochondrial DNA prevalence of greater than 1 in 5000 in adults. Mitochondrial diseases that affect mitochondrial function. Other mitochondrial diseases are can be present at birth but can be manifested also at any age [2]. -
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. -
Dual Role of the Mitochondrial Protein Frataxin in Astrocytic Tumors
Laboratory Investigation (2011) 91, 1766–1776 & 2011 USCAP, Inc All rights reserved 0023-6837/11 $32.00 Dual role of the mitochondrial protein frataxin in astrocytic tumors Elmar Kirches1, Nadine Andrae1, Aline Hoefer2, Barbara Kehler1,3, Kim Zarse4, Martin Leverkus3, Gerburg Keilhoff5, Peter Schonfeld5, Thomas Schneider6, Annette Wilisch-Neumann1 and Christian Mawrin1 The mitochondrial protein frataxin (FXN) is known to be involved in mitochondrial iron homeostasis and iron–sulfur cluster biogenesis. It is discussed to modulate function of the electron transport chain and production of reactive oxygen species (ROS). FXN loss in neurons and heart muscle cells causes an autosomal-dominant mitochondrial disorder, Friedreich’s ataxia. Recently, tumor induction after targeted FXN deletion in liver and reversal of the tumorigenic phenotype of colonic carcinoma cells following FXN overexpression were described in the literature, suggesting a tumor suppressor function. We hypothesized that a partial reversal of the malignant phenotype of glioma cells should occur after FXN transfection, if the mitochondrial protein has tumor suppressor functions in these brain tumors. In astrocytic brain tumors and tumor cell lines, we observed reduced FXN levels compared with non-neoplastic astrocytes. Mitochondrial content (citrate synthase activity) was not significantly altered in U87MG glioblastoma cells stably overexpressing FXN (U87-FXN). Surprisingly, U87-FXN cells exhibited increased cytoplasmic ROS levels, although mitochondrial ROS release was attenuated by FXN, as expected. Higher cytoplasmic ROS levels corresponded to reduced activities of glutathione peroxidase and catalase, and lower glutathione content. The defect of antioxidative capacity resulted in increased susceptibility of U87-FXN cells against oxidative stress induced by H2O2 or buthionine sulfoximine. -
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. -
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. -
Low Abundance of the Matrix Arm of Complex I in Mitochondria Predicts Longevity in Mice
ARTICLE Received 24 Jan 2014 | Accepted 9 Apr 2014 | Published 12 May 2014 DOI: 10.1038/ncomms4837 OPEN Low abundance of the matrix arm of complex I in mitochondria predicts longevity in mice Satomi Miwa1, Howsun Jow2, Karen Baty3, Amy Johnson1, Rafal Czapiewski1, Gabriele Saretzki1, Achim Treumann3 & Thomas von Zglinicki1 Mitochondrial function is an important determinant of the ageing process; however, the mitochondrial properties that enable longevity are not well understood. Here we show that optimal assembly of mitochondrial complex I predicts longevity in mice. Using an unbiased high-coverage high-confidence approach, we demonstrate that electron transport chain proteins, especially the matrix arm subunits of complex I, are decreased in young long-living mice, which is associated with improved complex I assembly, higher complex I-linked state 3 oxygen consumption rates and decreased superoxide production, whereas the opposite is seen in old mice. Disruption of complex I assembly reduces oxidative metabolism with concomitant increase in mitochondrial superoxide production. This is rescued by knockdown of the mitochondrial chaperone, prohibitin. Disrupted complex I assembly causes premature senescence in primary cells. We propose that lower abundance of free catalytic complex I components supports complex I assembly, efficacy of substrate utilization and minimal ROS production, enabling enhanced longevity. 1 Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne NE4 5PL, UK. 2 Centre for Integrated Systems Biology of Ageing and Nutrition, Newcastle University, Newcastle upon Tyne NE4 5PL, UK. 3 Newcastle University Protein and Proteome Analysis, Devonshire Building, Devonshire Terrace, Newcastle upon Tyne NE1 7RU, UK. Correspondence and requests for materials should be addressed to T.v.Z. -
NICU Gene List Generator.Xlsx
Neonatal Crisis Sequencing Panel Gene List Genes: A2ML1 - B3GLCT A2ML1 ADAMTS9 ALG1 ARHGEF15 AAAS ADAMTSL2 ALG11 ARHGEF9 AARS1 ADAR ALG12 ARID1A AARS2 ADARB1 ALG13 ARID1B ABAT ADCY6 ALG14 ARID2 ABCA12 ADD3 ALG2 ARL13B ABCA3 ADGRG1 ALG3 ARL6 ABCA4 ADGRV1 ALG6 ARMC9 ABCB11 ADK ALG8 ARPC1B ABCB4 ADNP ALG9 ARSA ABCC6 ADPRS ALK ARSL ABCC8 ADSL ALMS1 ARX ABCC9 AEBP1 ALOX12B ASAH1 ABCD1 AFF3 ALOXE3 ASCC1 ABCD3 AFF4 ALPK3 ASH1L ABCD4 AFG3L2 ALPL ASL ABHD5 AGA ALS2 ASNS ACAD8 AGK ALX3 ASPA ACAD9 AGL ALX4 ASPM ACADM AGPS AMELX ASS1 ACADS AGRN AMER1 ASXL1 ACADSB AGT AMH ASXL3 ACADVL AGTPBP1 AMHR2 ATAD1 ACAN AGTR1 AMN ATL1 ACAT1 AGXT AMPD2 ATM ACE AHCY AMT ATP1A1 ACO2 AHDC1 ANK1 ATP1A2 ACOX1 AHI1 ANK2 ATP1A3 ACP5 AIFM1 ANKH ATP2A1 ACSF3 AIMP1 ANKLE2 ATP5F1A ACTA1 AIMP2 ANKRD11 ATP5F1D ACTA2 AIRE ANKRD26 ATP5F1E ACTB AKAP9 ANTXR2 ATP6V0A2 ACTC1 AKR1D1 AP1S2 ATP6V1B1 ACTG1 AKT2 AP2S1 ATP7A ACTG2 AKT3 AP3B1 ATP8A2 ACTL6B ALAS2 AP3B2 ATP8B1 ACTN1 ALB AP4B1 ATPAF2 ACTN2 ALDH18A1 AP4M1 ATR ACTN4 ALDH1A3 AP4S1 ATRX ACVR1 ALDH3A2 APC AUH ACVRL1 ALDH4A1 APTX AVPR2 ACY1 ALDH5A1 AR B3GALNT2 ADA ALDH6A1 ARFGEF2 B3GALT6 ADAMTS13 ALDH7A1 ARG1 B3GAT3 ADAMTS2 ALDOB ARHGAP31 B3GLCT Updated: 03/15/2021; v.3.6 1 Neonatal Crisis Sequencing Panel Gene List Genes: B4GALT1 - COL11A2 B4GALT1 C1QBP CD3G CHKB B4GALT7 C3 CD40LG CHMP1A B4GAT1 CA2 CD59 CHRNA1 B9D1 CA5A CD70 CHRNB1 B9D2 CACNA1A CD96 CHRND BAAT CACNA1C CDAN1 CHRNE BBIP1 CACNA1D CDC42 CHRNG BBS1 CACNA1E CDH1 CHST14 BBS10 CACNA1F CDH2 CHST3 BBS12 CACNA1G CDK10 CHUK BBS2 CACNA2D2 CDK13 CILK1 BBS4 CACNB2 CDK5RAP2 -
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. -
The Pathogenetic Role of Β-Cell Mitochondria in Type 2 Diabetes
236 3 Journal of M Fex et al. Mitochondria in β-cells 236:3 R145–R159 Endocrinology REVIEW The pathogenetic role of β-cell mitochondria in type 2 diabetes Malin Fex1, Lisa M Nicholas1, Neelanjan Vishnu1, Anya Medina1, Vladimir V Sharoyko1, David G Nicholls1, Peter Spégel1,2 and Hindrik Mulder1 1Department of Clinical Sciences in Malmö, Unit of Molecular Metabolism, Lund University Diabetes Centre, Clinical Research Center, Malmö University Hospital, Lund University, Malmö, Sweden 2Department of Chemistry, Center for Analysis and Synthesis, Lund University, Sweden Correspondence should be addressed to H Mulder: [email protected] Abstract Mitochondrial metabolism is a major determinant of insulin secretion from pancreatic Key Words β-cells. Type 2 diabetes evolves when β-cells fail to release appropriate amounts f TCA cycle of insulin in response to glucose. This results in hyperglycemia and metabolic f coupling signal dysregulation. Evidence has recently been mounting that mitochondrial dysfunction f oxidative phosphorylation plays an important role in these processes. Monogenic dysfunction of mitochondria is a f mitochondrial transcription rare condition but causes a type 2 diabetes-like syndrome owing to β-cell failure. Here, f genetic variation we describe novel advances in research on mitochondrial dysfunction in the β-cell in type 2 diabetes, with a focus on human studies. Relevant studies in animal and cell models of the disease are described. Transcriptional and translational regulation in mitochondria are particularly emphasized. The role of metabolic enzymes and pathways and their impact on β-cell function in type 2 diabetes pathophysiology are discussed. The role of genetic variation in mitochondrial function leading to type 2 diabetes is highlighted. -
Role of Tafazzin in Hematopoiesis and Leukemogenesis
Role of Tafazzin in Hematopoiesis and Leukemogenesis by Ayesh Seneviratne A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Institute of Medical Science University of Toronto © Copyright by Ayesh Seneviratne 2020 Role of Tafazzin in Hematopoiesis and Leukemogenesis Ayesh Seneviratne Doctor of Philosophy Institute of Medical Science University of Toronto 2020 Abstract Tafazzin (TAZ) is a mitochondrial transacylase that remodels the mitochondrial cardiolipin into its mature form. Through a CRISPR screen, we identified TAZ as necessary for the growth and viability of acute myeloid leukemia (AML) cells. Genetic inhibition of TAZ reduced stemness and increased differentiation of AML cells both in vitro and in vivo. In contrast, knockdown of TAZ did not impair normal hematopoiesis under basal conditions. Mechanistically, inhibition of TAZ decreased levels of cardiolipin but also altered global levels of intracellular phospholipids, including phosphatidylserine, which controlled AML stemness and differentiation by modulating toll-like receptor (TLR) signaling (Seneviratne et al., 2019). ii Acknowledgments Firstly, I would like to thank Dr. Aaron Schimmer for his guidance and support during my PhD studies. I really enjoyed our early morning meetings where he provided much needed perspective to navigate the road blocks of my project, whilst continuing to push me. It was a privilege to be mentored by such an excellent clinician scientist. I hope to continue to build on the skills I learned in Dr. Schimmer’s lab as I progress on my path to become a clinician scientist. Working in the Schimmer lab was a wonderful learning environment. I would like to especially thank Dr. -
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 -
Src Inhibitors Modulate Frataxin Protein Levels
Human Molecular Genetics, 2015, Vol. 24, No. 15 4296–4305 doi: 10.1093/hmg/ddv162 Advance Access Publication Date: 6 May 2015 Original Article ORIGINAL ARTICLE Src inhibitors modulate frataxin protein levels Downloaded from https://academic.oup.com/hmg/article/24/15/4296/2453025 by guest on 28 September 2021 Fabio Cherubini1, Dario Serio1, Ilaria Guccini1, Silvia Fortuni1,2, Gaetano Arcuri1, Ivano Condò1, Alessandra Rufini1,2, Shadman Moiz1, Serena Camerini3, Marco Crescenzi3, Roberto Testi1,2 and Florence Malisan1,* 1Laboratory of Signal Transduction, Department of Biomedicine and Prevention, University of Rome ‘Tor Vergata’, Via Montpellier 1, 00133 Rome, Italy, 2Fratagene Therapeutics Ltd, 22 Northumberland Rd, Dublin, Ireland and 3Department of Cell Biology and Neurosciences, Italian National Institute of Health, Viale Regina Elena, 299, 00161 Rome, Italy *To whom correspondence should be addressed at: Laboratory of Signal Transduction, Department of Biomedicine and Prevention, University of Rome ‘Tor Vergata’, Via Montpellier 1, 00133 Rome, Italy. Tel: +39 0672596501; Fax: +39 0672596505; Email: [email protected] Abstract Defective expression of frataxin is responsible for the inherited, progressive degenerative disease Friedreich’s Ataxia (FRDA). There is currently no effective approved treatment for FRDA and patients die prematurely. Defective frataxin expression causes critical metabolic changes, including redox imbalance and ATP deficiency. As these alterations are known to regulate the tyrosine kinase Src, we investigated whether Src might in turn affect frataxin expression. We found that frataxin can be phosphorylated by Src. Phosphorylation occurs primarily on Y118 and promotes frataxin ubiquitination, a signal for degradation. Accordingly, Src inhibitors induce accumulation of frataxin but are ineffective on a non-phosphorylatable frataxin- Y118F mutant.