Leigh Syndrome
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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. -
Neurodevelopmental Signatures of Narcotic and Neuropsychiatric Risk Factors in 3D Human-Derived Forebrain Organoids
Molecular Psychiatry www.nature.com/mp ARTICLE OPEN Neurodevelopmental signatures of narcotic and neuropsychiatric risk factors in 3D human-derived forebrain organoids 1 1 1 1 2 2 3 Michael Notaras , Aiman Lodhi , Estibaliz✉ Barrio-Alonso , Careen Foord , Tori Rodrick , Drew Jones , Haoyun Fang , David Greening 3,4 and Dilek Colak 1,5 © The Author(s) 2021 It is widely accepted that narcotic use during pregnancy and specific environmental factors (e.g., maternal immune activation and chronic stress) may increase risk of neuropsychiatric illness in offspring. However, little progress has been made in defining human- specific in utero neurodevelopmental pathology due to ethical and technical challenges associated with accessing human prenatal brain tissue. Here we utilized human induced pluripotent stem cells (hiPSCs) to generate reproducible organoids that recapitulate dorsal forebrain development including early corticogenesis. We systemically exposed organoid samples to chemically defined “enviromimetic” compounds to examine the developmental effects of various narcotic and neuropsychiatric-related risk factors within tissue of human origin. In tandem experiments conducted in parallel, we modeled exposure to opiates (μ-opioid agonist endomorphin), cannabinoids (WIN 55,212-2), alcohol (ethanol), smoking (nicotine), chronic stress (human cortisol), and maternal immune activation (human Interleukin-17a; IL17a). Human-derived dorsal forebrain organoids were consequently analyzed via an array of unbiased and high-throughput analytical approaches, including state-of-the-art TMT-16plex liquid chromatography/mass- spectrometry (LC/MS) proteomics, hybrid MS metabolomics, and flow cytometry panels to determine cell-cycle dynamics and rates of cell death. This pipeline subsequently revealed both common and unique proteome, reactome, and metabolome alterations as a consequence of enviromimetic modeling of narcotic use and neuropsychiatric-related risk factors in tissue of human origin. -
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. -
Ncomms8214.Pdf
ARTICLE Received 20 Feb 2015 | Accepted 17 Apr 2015 | Published 26 May 2015 DOI: 10.1038/ncomms8214 OPEN Comprehensive survey of condition-specific reproductive isolation reveals genetic incompatibility in yeast Jing Hou1, Anne Friedrich1, Jean-Sebastien Gounot1 & Joseph Schacherer1 Genetic variation within a species could cause negative epistasis leading to reduced hybrid fitness and post-zygotic reproductive isolation. Recent studies in yeasts revealed chromo- somal rearrangements as a major mechanism dampening intraspecific hybrid fertility on rich media. Here, by analysing a large number of Saccharomyces cerevisiae crosses on different culture conditions, we show environment-specific genetic incompatibility segregates readily within yeast and contributes to reproductive isolation. Over 24% (117 out of 481) of cases tested show potential epistasis, among which 6.7% (32 out of 481) are severe, with at least 20% of progeny loss on tested conditions. Based on the segregation patterns, we further characterize a two-locus Dobzhansky–Mu¨ller incompatibility case leading to offspring respiratory deficiency caused by nonsense mutation in a nuclear-encoding mitochondrial gene and tRNA suppressor. We provide evidence that this precise configuration could be adaptive in fluctuating environments, highlighting the role of ecological selection in the onset of genetic incompatibility and reproductive isolation in yeast. 1 Department of Genetics, Genomics and Microbiology, University of Strasbourg/CNRS, UMR7156, 28 rue Goethe, 67083 Strasbourg, France. Correspondence -
Alterations of Genetic Variants and Transcriptomic Features of Response to Tamoxifen in the Breast Cancer Cell Line
Alterations of Genetic Variants and Transcriptomic Features of Response to Tamoxifen in the Breast Cancer Cell Line Mahnaz Nezamivand-Chegini Shiraz University Hamed Kharrati-Koopaee Shiraz University https://orcid.org/0000-0003-2345-6919 seyed taghi Heydari ( [email protected] ) Shiraz University of Medical Sciences https://orcid.org/0000-0001-7711-1137 Hasan Giahi Shiraz University Ali Dehshahri Shiraz University of Medical Sciences Mehdi Dianatpour Shiraz University of Medical Sciences Kamran Bagheri Lankarani Shiraz University of Medical Sciences Research Keywords: Tamoxifen, breast cancer, genetic variants, RNA-seq. Posted Date: August 17th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-783422/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/33 Abstract Background Breast cancer is one of the most important causes of mortality in the world, and Tamoxifen therapy is known as a medication strategy for estrogen receptor-positive breast cancer. In current study, two hypotheses of Tamoxifen consumption in breast cancer cell line (MCF7) were investigated. First, the effect of Tamoxifen on genes expression prole at transcriptome level was evaluated between the control and treated samples. Second, due to the fact that Tamoxifen is known as a mutagenic factor, there may be an association between the alterations of genetic variants and Tamoxifen treatment, which can impact on the drug response. Methods In current study, the whole-transcriptome (RNA-seq) dataset of four investigations (19 samples) were derived from European Bioinformatics Institute (EBI). At transcriptome level, the effect of Tamoxifen was investigated on gene expression prole between control and treatment samples. -
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 -
FOXRED1 (D-4): Sc-377010
SANTA CRUZ BIOTECHNOLOGY, INC. FOXRED1 (D-4): sc-377010 BACKGROUND APPLICATIONS FOXRED1 (FAD-dependent oxidoreductase domain-containing protein 1), also FOXRED1 (D-4) is recommended for detection of FOXRED1 of human origin known as FP634, is a 486 amino acid single-pass membrane protein. Utilizing by Western Blotting (starting dilution 1:100, dilution range 1:100-1:1000), FAD as a cofactor, FOXRED1 may act as a chaperone protein essential for the immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml of cell function of mitochondrial complex I. Mutations to FOXRED1 may result in lysate)], immunofluorescence (starting dilution 1:50, dilution range 1:50- mitochondrial complex I deficiency (MT-C1D), which results in a wide range 1:500), immunohistochemistry (including paraffin-embedded sections) of clinical maladies from lethal neonatal disease to adult onset neurodegen- (starting dilution 1:50, dilution range 1:50-1:500) and solid phase ELISA erative disorders. Common phenotypes of MT-C1D include cardiomyopathy, (starting dilution 1:30, dilution range 1:30-1:3000). liver disease, Leigh syndrome, Leber hereditary optic neuropathy, and some Suitable for use as control antibody for FOXRED1 siRNA (h): sc-96988, forms of Parkinson disease. FOXRED1 exists as three alternatively spliced FOXRED1 shRNA Plasmid (h): sc-96988-SH and FOXRED1 shRNA (h) isoforms and is encoded by a gene mapping to human chromosome 11q24.2. Lentiviral Particles: sc-96988-V. With approximately 135 million base pairs and 1,400 genes, chromosome 11 makes up around 4% of human genomic DNA and is considered a gene and Molecular Weight of FOXRED1 isoform 1: 54 kDa. -
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. -
Supplementary Table S1. Correlation Between the Mutant P53-Interacting Partners and PTTG3P, PTTG1 and PTTG2, Based on Data from Starbase V3.0 Database
Supplementary Table S1. Correlation between the mutant p53-interacting partners and PTTG3P, PTTG1 and PTTG2, based on data from StarBase v3.0 database. PTTG3P PTTG1 PTTG2 Gene ID Coefficient-R p-value Coefficient-R p-value Coefficient-R p-value NF-YA ENSG00000001167 −0.077 8.59e-2 −0.210 2.09e-6 −0.122 6.23e-3 NF-YB ENSG00000120837 0.176 7.12e-5 0.227 2.82e-7 0.094 3.59e-2 NF-YC ENSG00000066136 0.124 5.45e-3 0.124 5.40e-3 0.051 2.51e-1 Sp1 ENSG00000185591 −0.014 7.50e-1 −0.201 5.82e-6 −0.072 1.07e-1 Ets-1 ENSG00000134954 −0.096 3.14e-2 −0.257 4.83e-9 0.034 4.46e-1 VDR ENSG00000111424 −0.091 4.10e-2 −0.216 1.03e-6 0.014 7.48e-1 SREBP-2 ENSG00000198911 −0.064 1.53e-1 −0.147 9.27e-4 −0.073 1.01e-1 TopBP1 ENSG00000163781 0.067 1.36e-1 0.051 2.57e-1 −0.020 6.57e-1 Pin1 ENSG00000127445 0.250 1.40e-8 0.571 9.56e-45 0.187 2.52e-5 MRE11 ENSG00000020922 0.063 1.56e-1 −0.007 8.81e-1 −0.024 5.93e-1 PML ENSG00000140464 0.072 1.05e-1 0.217 9.36e-7 0.166 1.85e-4 p63 ENSG00000073282 −0.120 7.04e-3 −0.283 1.08e-10 −0.198 7.71e-6 p73 ENSG00000078900 0.104 2.03e-2 0.258 4.67e-9 0.097 3.02e-2 Supplementary Table S2. -
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 -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Supplementary Data Table 1. Genes Upregulated in N-Myc-Overexpressing Mouse Mac1+/Gr1+ BM Cells
Supplementary Data Table 1. Genes upregulated in N-Myc-overexpressing mouse Mac1+/Gr1+ BM cells Probeset C-myc / N-myc / N-myc / C- Gene Title Representative 430v2 Vector Fold Vector Fold myc Fold Public ID Change Change Change 1435368_a_at 2.3 4.6 2.1 poly (ADP-ribose) polymerase family, member 1 BB767586 1455648_at 1.3 3.0 2.1 similar to reduced expression 2 /// similar to reduced expression 2 BG244780 1438973_x_at 2.5 9.8 4.0 gap junction membrane channel protein alpha 1 BB043407 1419915_at 2.0 3.0 2.1 DNA segment, Chr 10, ERATO Doi 438, expressed AW538011 1454842_a_at 1.6 4.0 2.3 UDP-GalNAc:betaGlcNAc beta 1,3-galactosaminyltransferase, AI853240 polypeptide 2 1436704_x_at 2.1 9.2 3.2 methylenetetrahydrofolate dehydrogenase (NADP+ dependent), AV215673 methenyltetrahydrofolate cyclohydrolase, formyltetrahydrofolate synthase 1423142_a_at 2.0 2.5 2.1 GTP binding protein 4 AI987834 1420043_s_at 2.5 5.7 2.8 THO complex 1 AW107924 1439444_x_at 1.5 4.3 2.5 transmembrane emp24-like trafficking protein 10 (yeast) /// similar to AV213456 transmembrane trafficking protein 1438610_a_at 1.9 4.9 2.3 Crystallin, zeta BB793369 1434291_a_at 2.5 4.3 2.8 small EDRK-rich factor 1 AA709993 1422716_a_at 2.8 6.5 2.6 acid phosphatase 1, soluble AW554436 1447895_x_at -1.3 2.3 2.6 PAN3 polyA specific ribonuclease subunit homolog (S. cerevisiae) AV368189 1434097_at 1.5 3.2 2.5 Transcribed locus BM218328 1420982_at 1.1 3.5 2.6 RNA-binding region (RNP1, RRM) containing 2 NM_133242 1433853_at 2.6 7.5 2.6 mindbomb homolog 1 (Drosophila) BG063791 1419824_a_at 1.6 4.0 2.1 RIKEN cDNA A230062G08 gene AI875121 1453797_at 7.5 14.9 2.1 phosphatase, orphan 2 AK010147 1440803_x_at 2.3 4.0 2.3 tachykinin receptor 3 BB498416 1455737_at -2.0 1.1 2.8 RIKEN cDNA C030002B11 gene AU040848 1450954_at -1.5 2.8 4.6 YME1-like 1 (S.