Proteomic Analysis of the Increased Proteins in Peroxiredoxin 0
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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. -
Figure S1. DMD Module Network. the Network Is Formed by 260 Genes from Disgenet and 1101 Interactions from STRING. Red Nodes Are the Five Seed Candidate Genes
Figure S1. DMD module network. The network is formed by 260 genes from DisGeNET and 1101 interactions from STRING. Red nodes are the five seed candidate genes. Figure S2. DMD module network is more connected than a random module of the same size. It is shown the distribution of the largest connected component of 10.000 random modules of the same size of the DMD module network. The green line (x=260) represents the DMD largest connected component, obtaining a z-score=8.9. Figure S3. Shared genes between BMD and DMD signature. A) A meta-analysis of three microarray datasets (GSE3307, GSE13608 and GSE109178) was performed for the identification of differentially expressed genes (DEGs) in BMD muscle biopsies as compared to normal muscle biopsies. Briefly, the GSE13608 dataset included 6 samples of skeletal muscle biopsy from healthy people and 5 samples from BMD patients. Biopsies were taken from either biceps brachii, triceps brachii or deltoid. The GSE3307 dataset included 17 samples of skeletal muscle biopsy from healthy people and 10 samples from BMD patients. The GSE109178 dataset included 14 samples of controls and 11 samples from BMD patients. For both GSE3307 and GSE10917 datasets, biopsies were taken at the time of diagnosis and from the vastus lateralis. For the meta-analysis of GSE13608, GSE3307 and GSE109178, a random effects model of effect size measure was used to integrate gene expression patterns from the two datasets. Genes with an adjusted p value (FDR) < 0.05 and an │effect size│>2 were identified as DEGs and selected for further analysis. A significant number of DEGs (p<0.001) were in common with the DMD signature genes (blue nodes), as determined by a hypergeometric test assessing the significance of the overlap between the BMD DEGs and the number of DMD signature genes B) MCODE analysis of the overlapping genes between BMD DEGs and DMD signature genes. -
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. -
PROTEOMIC ANALYSIS of HUMAN URINARY EXOSOMES. Patricia
ABSTRACT Title of Document: PROTEOMIC ANALYSIS OF HUMAN URINARY EXOSOMES. Patricia Amalia Gonzales Mancilla, Ph.D., 2009 Directed By: Associate Professor Nam Sun Wang, Department of Chemical and Biomolecular Engineering Exosomes originate as the internal vesicles of multivesicular bodies (MVBs) in cells. These small vesicles (40-100 nm) have been shown to be secreted by most cell types throughout the body. In the kidney, urinary exosomes are released to the urine by fusion of the outer membrane of the MVBs with the apical plasma membrane of renal tubular epithelia. Exosomes contain apical membrane and cytosolic proteins and can be isolated using differential centrifugation. The analysis of urinary exosomes provides a non- invasive means of acquiring information about the physiological or pathophysiological state of renal cells. The overall objective of this research was to develop methods and knowledge infrastructure for urinary proteomics. We proposed to conduct a proteomic analysis of human urinary exosomes. The first objective was to profile the proteome of human urinary exosomes using liquid chromatography-tandem spectrometry (LC- MS/MS) and specialized software for identification of peptide sequences from fragmentation spectra. We unambiguously identified 1132 proteins. In addition, the phosphoproteome of human urinary exosomes was profiled using the neutral loss scanning acquisition mode of LC-MS/MS. The phosphoproteomic profiling identified 19 phosphorylation sites corresponding to 14 phosphoproteins. The second objective was to analyze urinary exosomes samples isolated from patients with genetic mutations. Polyclonal antibodies were generated to recognize epitopes on the gene products of these genetic mutations, NKCC2 and MRP4. The potential usefulness of urinary exosome analysis was demonstrated using the well-defined renal tubulopathy, Bartter syndrome type I and using the single nucleotide polymorphism in the ABCC4 gene. -
Uncovering Ubiquitin and Ubiquitin-Like Signaling Networks Alfred C
REVIEW pubs.acs.org/CR Uncovering Ubiquitin and Ubiquitin-like Signaling Networks Alfred C. O. Vertegaal* Department of Molecular Cell Biology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, The Netherlands CONTENTS 8. Crosstalk between Post-Translational Modifications 7934 1. Introduction 7923 8.1. Crosstalk between Phosphorylation and 1.1. Ubiquitin and Ubiquitin-like Proteins 7924 Ubiquitylation 7934 1.2. Quantitative Proteomics 7924 8.2. Phosphorylation-Dependent SUMOylation 7935 8.3. Competition between Different Lysine 1.3. Setting the Scenery: Mass Spectrometry Modifications 7935 Based Investigation of Phosphorylation 8.4. Crosstalk between SUMOylation and the and Acetylation 7925 UbiquitinÀProteasome System 7935 2. Ubiquitin and Ubiquitin-like Protein Purification 9. Conclusions and Future Perspectives 7935 Approaches 7925 Author Information 7935 2.1. Epitope-Tagged Ubiquitin and Ubiquitin-like Biography 7935 Proteins 7925 Acknowledgment 7936 2.2. Traps Based on Ubiquitin- and Ubiquitin-like References 7936 Binding Domains 7926 2.3. Antibody-Based Purification of Ubiquitin and Ubiquitin-like Proteins 7926 1. INTRODUCTION 2.4. Challenges and Pitfalls 7926 Proteomes are significantly more complex than genomes 2.5. Summary 7926 and transcriptomes due to protein processing and extensive 3. Ubiquitin Proteomics 7927 post-translational modification (PTM) of proteins. Hundreds ff fi 3.1. Proteomic Studies Employing Tagged of di erent modi cations exist. Release 66 of the RESID database1 (http://www.ebi.ac.uk/RESID/) contains 559 dif- Ubiquitin 7927 ferent modifications, including small chemical modifications 3.2. Ubiquitin Binding Domains 7927 such as phosphorylation, acetylation, and methylation and mod- 3.3. Anti-Ubiquitin Antibodies 7927 ification by small proteins, including ubiquitin and ubiquitin- 3.4. -
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. -
Product Information
Product information Monoclonal anti-human UBE2L6 antibody (clone K1H3) Mouse IgG2b, Cat. No. IBAUB0907 Immunogen: Recombinant human UBE2L6 (1-152aa) purified from E. coli NCBI Accession No.: NP_004214 Isotype: Mouse IgG2b heavy chain and light chain Clone: Anti-human UBE2L6 mAb, clone K1H3, is derived from hybridization of mouse F0 myeloma cells with spleen cells from BALB/c mice immunized with a recombinant human UBE2L6 protein. Description: Ubiquitin-conjugating enzyme E2L6 (UBE2L6), also known as UbcH8, is a member of the E2 ubiquitin-conjugating enzyme family. The modification of proteins with ubiquitin is an important cellular mechanism for targeting abnormal or short-lived proteins for degradation. Ubiquitination of a protein substrate requires the concerted action of 3 classes of enzymes: E1 ubiquitin-activating enzymes, E2 ubiquitin- conjugating enzymes, and E3 ubiquitin protein ligases. The E2 ubiquitin-conjugating enzyme is highly similar in primary structure to the enzyme encoded by UBE2L3 gene. Concentration: 1mg/ml Form: Liquid. In Phosphate-Buffered Saline (pH 7.4) with 0.02% Sodium Azide, 10% Glycerol. Storage: Can be stored at +4°C. For long term storage, aliquot and store at -20°C. Avoid repeated freezing and thawing cycles. Usage: The antibody has been tested by ELISA, Western blot analysis, Flow cytometry and ICC/IF immunohistochemistry to assure specificity and reactivity. Since application varies, however, each investigation should be titrated by the reagent to obtain optimal results. Application: ELISA, WB, IHC, Flow cytometry, ICC/IF For research use only. This product is not intended or approved for human, diagnostics or veterinary use. Manufactured for: Immuno-Biological Laboratories, Inc. -
Supplementary Table 1. Pain and PTSS Associated Genes (N = 604
Supplementary Table 1. Pain and PTSS associated genes (n = 604) compiled from three established pain gene databases (PainNetworks,[61] Algynomics,[52] and PainGenes[42]) and one PTSS gene database (PTSDgene[88]). These genes were used in in silico analyses aimed at identifying miRNA that are predicted to preferentially target this list genes vs. a random set of genes (of the same length). ABCC4 ACE2 ACHE ACPP ACSL1 ADAM11 ADAMTS5 ADCY5 ADCYAP1 ADCYAP1R1 ADM ADORA2A ADORA2B ADRA1A ADRA1B ADRA1D ADRA2A ADRA2C ADRB1 ADRB2 ADRB3 ADRBK1 ADRBK2 AGTR2 ALOX12 ANO1 ANO3 APOE APP AQP1 AQP4 ARL5B ARRB1 ARRB2 ASIC1 ASIC2 ATF1 ATF3 ATF6B ATP1A1 ATP1B3 ATP2B1 ATP6V1A ATP6V1B2 ATP6V1G2 AVPR1A AVPR2 BACE1 BAMBI BDKRB2 BDNF BHLHE22 BTG2 CA8 CACNA1A CACNA1B CACNA1C CACNA1E CACNA1G CACNA1H CACNA2D1 CACNA2D2 CACNA2D3 CACNB3 CACNG2 CALB1 CALCRL CALM2 CAMK2A CAMK2B CAMK4 CAT CCK CCKAR CCKBR CCL2 CCL3 CCL4 CCR1 CCR7 CD274 CD38 CD4 CD40 CDH11 CDK5 CDK5R1 CDKN1A CHRM1 CHRM2 CHRM3 CHRM5 CHRNA5 CHRNA7 CHRNB2 CHRNB4 CHUK CLCN6 CLOCK CNGA3 CNR1 COL11A2 COL9A1 COMT COQ10A CPN1 CPS1 CREB1 CRH CRHBP CRHR1 CRHR2 CRIP2 CRYAA CSF2 CSF2RB CSK CSMD1 CSNK1A1 CSNK1E CTSB CTSS CX3CL1 CXCL5 CXCR3 CXCR4 CYBB CYP19A1 CYP2D6 CYP3A4 DAB1 DAO DBH DBI DICER1 DISC1 DLG2 DLG4 DPCR1 DPP4 DRD1 DRD2 DRD3 DRD4 DRGX DTNBP1 DUSP6 ECE2 EDN1 EDNRA EDNRB EFNB1 EFNB2 EGF EGFR EGR1 EGR3 ENPP2 EPB41L2 EPHB1 EPHB2 EPHB3 EPHB4 EPHB6 EPHX2 ERBB2 ERBB4 EREG ESR1 ESR2 ETV1 EZR F2R F2RL1 F2RL2 FAAH FAM19A4 FGF2 FKBP5 FLOT1 FMR1 FOS FOSB FOSL2 FOXN1 FRMPD4 FSTL1 FYN GABARAPL1 GABBR1 GABBR2 GABRA2 GABRA4 -
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 -
Ykt6 Membrane-To-Cytosol Cycling Regulates Exosomal Wnt Secretion
bioRxiv preprint doi: https://doi.org/10.1101/485565; this version posted December 3, 2018. 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. Ykt6 membrane-to-cytosol cycling regulates exosomal Wnt secretion Karen Linnemannstöns1,2, Pradhipa Karuna1,2, Leonie Witte1,2, Jeanette Kittel1,2, Adi Danieli1,2, Denise Müller1,2, Lena Nitsch1,2, Mona Honemann-Capito1,2, Ferdinand Grawe3,4, Andreas Wodarz3,4 and Julia Christina Gross1,2* Affiliations: 1Hematology and Oncology, University Medical Center Goettingen, Goettingen, Germany. 2Developmental Biochemistry, University Medical Center Goettingen, Goettingen, Germany. 3Molecular Cell Biology, Institute I for Anatomy, University of Cologne Medical School, Cologne, Germany 4Cluster of Excellence-Cellular Stress Response in Aging-Associated Diseases (CECAD), Cologne, Germany *Correspondence: Dr. Julia Christina Gross, Hematology and Oncology/Developmental Biochemistry, University Medical Center Goettingen, Justus-von-Liebig Weg 11, 37077 Goettingen Germany Abstract Protein trafficking in the secretory pathway, for example the secretion of Wnt proteins, requires tight regulation. These ligands activate Wnt signaling pathways and are crucially involved in development and disease. Wnt is transported to the plasma membrane by its cargo receptor Evi, where Wnt/Evi complexes are endocytosed and sorted onto exosomes for long-range secretion. However, the trafficking steps within the endosomal compartment are not fully understood. The promiscuous SNARE Ykt6 folds into an auto-inhibiting conformation in the cytosol, but a portion associates with membranes by its farnesylated and palmitoylated C-terminus. Here, we demonstrate that membrane detachment of Ykt6 is essential for exosomal Wnt secretion. -
Targeting the Ubiquitin System in Glioblastoma', Frontiers in Oncology
Citation for published version: Licchesi, J 2020, 'Targeting the Ubiquitin System in Glioblastoma', Frontiers in Oncology. https://doi.org/10.3389/fonc.2020.574011 DOI: 10.3389/fonc.2020.574011 Publication date: 2020 Document Version Publisher's PDF, also known as Version of record Link to publication University of Bath Alternative formats If you require this document in an alternative format, please contact: [email protected] General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 24. Sep. 2021 REVIEW published: 25 November 2020 doi: 10.3389/fonc.2020.574011 Targeting the Ubiquitin System in Glioblastoma Nico Scholz 1, Kathreena M. Kurian 2, Florian A. Siebzehnrubl 3 and Julien D. F. Licchesi 1* 1 Department of Biology & Biochemistry, University of Bath, Bath, United Kingdom, 2 Brain Tumour Research Group, Institute of Clinical Neurosciences, University of Bristol, Bristol, United Kingdom, 3 Cardiff University School of Biosciences, European Cancer Stem Cell Research Institute, Cardiff, United Kingdom Glioblastoma is the most common primary brain tumor in adults with poor overall outcome and 5-year survival of less than 5%. Treatment has not changed much in the last decade or so, with surgical resection and radio/chemotherapy being the main options. -
Figure S1. HAEC ROS Production and ML090 NOX5-Inhibition
Figure S1. HAEC ROS production and ML090 NOX5-inhibition. (a) Extracellular H2O2 production in HAEC treated with ML090 at different concentrations and 24 h after being infected with GFP and NOX5-β adenoviruses (MOI 100). **p< 0.01, and ****p< 0.0001 vs control NOX5-β-infected cells (ML090, 0 nM). Results expressed as mean ± SEM. Fold increase vs GFP-infected cells with 0 nM of ML090. n= 6. (b) NOX5-β overexpression and DHE oxidation in HAEC. Representative images from three experiments are shown. Intracellular superoxide anion production of HAEC 24 h after infection with GFP and NOX5-β adenoviruses at different MOIs treated or not with ML090 (10 nM). MOI: Multiplicity of infection. Figure S2. Ontology analysis of HAEC infected with NOX5-β. Ontology analysis shows that the response to unfolded protein is the most relevant. Figure S3. UPR mRNA expression in heart of infarcted transgenic mice. n= 12-13. Results expressed as mean ± SEM. Table S1: Altered gene expression due to NOX5-β expression at 12 h (bold, highlighted in yellow). N12hvsG12h N18hvsG18h N24hvsG24h GeneName GeneDescription TranscriptID logFC p-value logFC p-value logFC p-value family with sequence similarity NM_052966 1.45 1.20E-17 2.44 3.27E-19 2.96 6.24E-21 FAM129A 129. member A DnaJ (Hsp40) homolog. NM_001130182 2.19 9.83E-20 2.94 2.90E-19 3.01 1.68E-19 DNAJA4 subfamily A. member 4 phorbol-12-myristate-13-acetate- NM_021127 0.93 1.84E-12 2.41 1.32E-17 2.69 1.43E-18 PMAIP1 induced protein 1 E2F7 E2F transcription factor 7 NM_203394 0.71 8.35E-11 2.20 2.21E-17 2.48 1.84E-18 DnaJ (Hsp40) homolog.