High-Throughput, Pooled Sequencing Identifies Mutations in NUBPL And
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Molecular Mechanism of ACAD9 in Mitochondrial Respiratory Complex 1 Assembly
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.07.425795; this version posted January 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Molecular mechanism of ACAD9 in mitochondrial respiratory complex 1 assembly Chuanwu Xia1, Baoying Lou1, Zhuji Fu1, Al-Walid Mohsen2, Jerry Vockley2, and Jung-Ja P. Kim1 1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, Wisconsin, 53226, USA 2Department of Pediatrics, University of Pittsburgh School of Medicine, University of Pittsburgh, Children’s Hospital of Pittsburgh of UPMC, Pittsburgh, PA 15224, USA Abstract ACAD9 belongs to the acyl-CoA dehydrogenase family, which catalyzes the α-β dehydrogenation of fatty acyl-CoA thioesters. Thus, it is involved in fatty acid β-oxidation (FAO). However, it is now known that the primary function of ACAD9 is as an essential chaperone for mitochondrial respiratory complex 1 assembly. ACAD9 interacts with ECSIT and NDUFAF1, forming the mitochondrial complex 1 assembly (MCIA) complex. Although the role of MCIA in the complex 1 assembly pathway is well studied, little is known about the molecular mechanism of the interactions among these three assembly factors. Our current studies reveal that when ECSIT interacts with ACAD9, the flavoenzyme loses the FAD cofactor and consequently loses its FAO activity, demonstrating that the two roles of ACAD9 are not compatible. ACAD9 binds to the carboxy-terminal half (C-ECSIT), and NDUFAF1 binds to the amino-terminal half of ECSIT. Although the binary complex of ACAD9 with ECSIT or with C-ECSIT is unstable and aggregates easily, the ternary complex of ACAD9-ECSIT-NDUFAF1 (i.e., the MCIA complex) is soluble and extremely stable. -
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. -
Differential Expression Profile Prioritization of Positional Candidate Glaucoma Genes the GLC1C Locus
LABORATORY SCIENCES Differential Expression Profile Prioritization of Positional Candidate Glaucoma Genes The GLC1C Locus Frank W. Rozsa, PhD; Kathleen M. Scott, BS; Hemant Pawar, PhD; John R. Samples, MD; Mary K. Wirtz, PhD; Julia E. Richards, PhD Objectives: To develop and apply a model for priori- est because of moderate expression and changes in tization of candidate glaucoma genes. expression. Transcription factor ZBTB38 emerges as an interesting candidate gene because of the overall expres- Methods: This Affymetrix GeneChip (Affymetrix, Santa sion level, differential expression, and function. Clara, Calif) study of gene expression in primary cul- ture human trabecular meshwork cells uses a positional Conclusions: Only1geneintheGLC1C interval fits our differential expression profile model for prioritization of model for differential expression under multiple glau- candidate genes within the GLC1C genetic inclusion in- coma risk conditions. The use of multiple prioritization terval. models resulted in filtering 7 candidate genes of higher interest out of the 41 known genes in the region. Results: Sixteen genes were expressed under all condi- tions within the GLC1C interval. TMEM22 was the only Clinical Relevance: This study identified a small sub- gene within the interval with differential expression in set of genes that are most likely to harbor mutations that the same direction under both conditions tested. Two cause glaucoma linked to GLC1C. genes, ATP1B3 and COPB2, are of interest in the con- text of a protein-misfolding model for candidate selec- tion. SLC25A36, PCCB, and FNDC6 are of lesser inter- Arch Ophthalmol. 2007;125:117-127 IGH PREVALENCE AND PO- identification of additional GLC1C fami- tential for severe out- lies7,18-20 who provide optimal samples for come combine to make screening candidate genes for muta- adult-onset primary tions.7,18,20 The existence of 2 distinct open-angle glaucoma GLC1C haplotypes suggests that muta- (POAG) a significant public health prob- tions will not be limited to rare descen- H1 lem. -
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. -
Assembly Factors for the Membrane Arm of Human Complex I
Assembly factors for the membrane arm of human complex I Byron Andrews, Joe Carroll, Shujing Ding, Ian M. Fearnley, and John E. Walker1 Medical Research Council Mitochondrial Biology Unit, Cambridge CB2 0XY, United Kingdom Contributed by John E. Walker, October 14, 2013 (sent for review September 12, 2013) Mitochondrial respiratory complex I is a product of both the nuclear subunits in a fungal enzyme from Yarrowia lipolytica seem to be and mitochondrial genomes. The integration of seven subunits distributed similarly (12, 13). encoded in mitochondrial DNA into the inner membrane, their asso- The assembly of mitochondrial complex I involves building the ciation with 14 nuclear-encoded membrane subunits, the construc- 44 subunits emanating from two genomes into the two domains of tion of the extrinsic arm from 23 additional nuclear-encoded the complex. The enzyme is put together from preassembled sub- proteins, iron–sulfur clusters, and flavin mononucleotide cofactor complexes, and their subunit compositions have been characterized require the participation of assembly factors. Some are intrinsic to partially (14, 15). Extrinsic assembly factors of unknown function the complex, whereas others participate transiently. The suppres- become associated with subcomplexes that accumulate when as- sion of the expression of the NDUFA11 subunit of complex I dis- sembly and the activity of complex I are impaired by pathogenic rupted the assembly of the complex, and subcomplexes with mutations. Some assembly factor mutations also impair its activ- masses of 550 and 815 kDa accumulated. Eight of the known ex- ity (16). Other pathogenic mutations are found in all of the core trinsic assembly factors plus a hydrophobic protein, C3orf1, were subunits, and in 10 supernumerary subunits (NDUFA1, NDUFA2, associated with the subcomplexes. -
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. -
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 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. -
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 -
WO 2018/067991 Al 12 April 2018 (12.04.2018) W !P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2018/067991 Al 12 April 2018 (12.04.2018) W !P O PCT (51) International Patent Classification: achusetts 021 15 (US). THE BROAD INSTITUTE, A61K 51/10 (2006.01) G01N 33/574 (2006.01) INC. [US/US]; 415 Main Street, Cambridge, Massachu C07K 14/705 (2006.01) A61K 47/68 (2017.01) setts 02142 (US). MASSACHUSETTS INSTITUTE OF G01N 33/53 (2006.01) TECHNOLOGY [US/US]; 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (US). (21) International Application Number: PCT/US2017/055625 (72) Inventors; and (71) Applicants: KUCHROO, Vijay K. [IN/US]; 30 Fairhaven (22) International Filing Date: Road, Newton, Massachusetts 02149 (US). ANDERSON, 06 October 2017 (06.10.2017) Ana Carrizosa [US/US]; 110 Cypress Street, Brookline, (25) Filing Language: English Massachusetts 02445 (US). MADI, Asaf [US/US]; c/o The Brigham and Women's Hospital, Inc., 75 Francis (26) Publication Language: English Street, Boston, Massachusetts 021 15 (US). CHIHARA, (30) Priority Data: Norio [US/US]; c/o The Brigham and Women's Hospital, 62/405,835 07 October 2016 (07.10.2016) US Inc., 75 Francis Street, Boston, Massachusetts 021 15 (US). REGEV, Aviv [US/US]; 15a Ellsworth Ave, Cambridge, (71) Applicants: THE BRIGHAM AND WOMEN'S HOSPI¬ Massachusetts 02139 (US). SINGER, Meromit [US/US]; TAL, INC. [US/US]; 75 Francis Street, Boston, Mass c/o The Broad Institute, Inc., 415 Main Street, Cambridge, (54) Title: MODULATION OF NOVEL IMMUNE CHECKPOINT TARGETS CD4 FIG.