Function and Crystal Structure of the Dimeric P-Loop Atpase CFD1 Coordinating an Exposed [4Fe-4S] Cluster for Transfer to Apoproteins
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Supplementary Data
Supplementary Data for Quantitative Changes in the Mitochondrial Proteome from Subjects with Mild Cognitive Impairment, Early Stage and Late Stage Alzheimer’s disease Table 1 - 112 unique, non-redundant proteins identified and quantified in at least two of the three analytical replicates for all three disease stages. Table 2 - MCI mitochondrial samples, Protein Summary Table 3 - MCI mitochondrial samples, Experiment 1 Table 4 - MCI mitochondrial samples, Experiment 2 Table 5 - MCI mitochondrial samples, Experiment 3 Table 6 - EAD Mitochondrial Study, Protein Summary Table 7 - EAD Mitochondrial Study, Experiment 1 Table 8 - EAD Mitochondrial Study, Experiment 2 Table 9 - EAD Mitochondrial Study, Experiment 3 Table 10 - LAD Mitochondrial Study, Protein Summary Table 11 - LAD Mitochondrial Study, Experiment 1 Table 12 - LAD Mitochondrial Study, Experiment 2 Table 13 - LAD Mitochondrial Study, Experiment 3 Supplemental Table 1. 112 unique, non-redundant proteins identified and quantified in at least two of the three analytical replicates for all three disease stages. Description Data MCI EAD LAD AATM_HUMAN (P00505) Aspartate aminotransferase, mitochondrial precursor (EC Mean 1.43 1.70 1.31 2.6.1.1) (Transaminase A) (Glutamate oxaloacetate transaminase 2) [MASS=47475] SEM 0.07 0.09 0.09 Count 3.00 3.00 3.00 ACON_HUMAN (Q99798) Aconitate hydratase, mitochondrial precursor (EC 4.2.1.3) Mean 1.24 1.61 1.19 (Citrate hydro-lyase) (Aconitase) [MASS=85425] SEM 0.05 0.17 0.18 Count 3.00 2.00 3.00 ACPM_HUMAN (O14561) Acyl carrier protein, mitochondrial -
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. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Noelia Díaz Blanco
Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr. -
Genotype Frequency Distributions of 28 SNP Markers in Two Commercial
Li et al. BMC Genetics (2020) 21:12 https://doi.org/10.1186/s12863-020-0815-z RESEARCH ARTICLE Open Access Genotype frequency distributions of 28 SNP markers in two commercial lines and five Chinese native chicken populations Jing-Jing Li1, Long Zhang2, Peng Ren1, Ye Wang1, Ling-Qian Yin1, Jin-Shan Ran1, Xian-Xian Zhang1 and Yi-Ping Liu1* Abstract Background: Modern breeding in the poultry industry mainly aims to produce high-performance poultry lines and breeds in two main directions of productivity, meat and eggs. To understand more about the productive potential of lowly selected Chinese native chicken populations, we selected 14 representative SNP markers strongly associated with growth traits or carcass traits and 14 SNP markers strongly associated with egg laying traits through previous reports. By using the MassArray technology, we detected the genotype frequency distributions of these 28 SNP markers in seven populations including four lowly selected as well as one moderately selected Sichuan native chicken populations, one commercial broiler line and one commercial layer line. Results: Based on the genotype frequency distributions of these 28 SNP markers in 5 native chicken populations and 2 commercial lines, the results suggested that these Chinese indigenous chicken populations have a relatively close relationship with the commercial broiler line but a marked distinction from the commercial layer line. Two native chicken breeds, Shimian Caoke Chicken and Daheng Broilers, share similar genetic structure with the broiler line. Conclusions: Our observations may help us to better select and breed superior domestic chickens and provide new clues for further study of breeding programs in local chicken populations. -
Human Leucine-Rich Repeat Proteins: a Genome-Wide Bioinformatic Categorization and Functional Analysis in Innate Immunity
Human leucine-rich repeat proteins: a genome-wide bioinformatic categorization and functional analysis in innate immunity Aylwin C. Y. Nga,b,1, Jason M. Eisenberga,b,1, Robert J. W. Heatha, Alan Huetta, Cory M. Robinsonc, Gerard J. Nauc, and Ramnik J. Xaviera,b,2 aCenter for Computational and Integrative Biology, and Gastrointestinal Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114; bThe Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA 02142; and cMicrobiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261 Edited by Jeffrey I. Gordon, Washington University School of Medicine, St. Louis, MO, and approved June 11, 2010 (received for review February 17, 2010) In innate immune sensing, the detection of pathogen-associated proteins have been implicated in human diseases to date, notably molecular patterns by recognition receptors typically involve polymorphisms in NOD2 in Crohn disease (8, 9), CIITA in leucine-rich repeats (LRRs). We provide a categorization of 375 rheumatoid arthritis and multiple sclerosis (10), and TLR5 in human LRR-containing proteins, almost half of which lack other Legionnaire disease (11). identifiable functional domains. We clustered human LRR proteins Most LRR domains consist of a chain of between 2 and 45 by first assigning LRRs to LRR classes and then grouping the proteins LRRs (12). Each repeat in turn is typically 20 to 30 residues long based on these class assignments, revealing several of the resulting and can be divided into a highly conserved segment (HCS) fol- protein groups containing a large number of proteins with certain lowed by a variable segment (VS). -
Transdifferentiation of Human Mesenchymal Stem Cells
Transdifferentiation of Human Mesenchymal Stem Cells Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Julius-Maximilians-Universität Würzburg vorgelegt von Tatjana Schilling aus San Miguel de Tucuman, Argentinien Würzburg, 2007 Eingereicht am: Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Martin J. Müller Gutachter: PD Dr. Norbert Schütze Gutachter: Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am: Hiermit erkläre ich ehrenwörtlich, dass ich die vorliegende Dissertation selbstständig angefertigt und keine anderen als die von mir angegebenen Hilfsmittel und Quellen verwendet habe. Des Weiteren erkläre ich, dass diese Arbeit weder in gleicher noch in ähnlicher Form in einem Prüfungsverfahren vorgelegen hat und ich noch keinen Promotionsversuch unternommen habe. Gerbrunn, 4. Mai 2007 Tatjana Schilling Table of contents i Table of contents 1 Summary ........................................................................................................................ 1 1.1 Summary.................................................................................................................... 1 1.2 Zusammenfassung..................................................................................................... 2 2 Introduction.................................................................................................................... 4 2.1 Osteoporosis and the fatty degeneration of the bone marrow..................................... 4 2.2 Adipose and bone -
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DISSERTATION submitted to the Combined Faculties for the Natural Sciences and for Mathematics of the Ruperto-Carola University of Heidelberg, Germany for the degree of Doctor of Natural Sciences presented by M.Sc. Daniela Casarrubea born in Palermo (Italy) Oral examination: 1st February 2013 A NEW MOUSE MODEL WITH GAIN OF IRON REGULATORY PROTEIN 1 FUNCTION Referees: 1. Dr. Darren Gilmour 2. Prof. Dr. Klaus Unsicker SUMMARY SUMMARY Disorders of iron metabolism account for some of the most common human diseases, such as anemias and hemochromatosis. To maintain physiological iron balance, homeostatic mechanisms are normally in place both at the systemic and the cellular level. Cellular iron homeostasis is secured by Iron Regulatory Proteins (IRP) −1 and −2 through their binding to cis- regulatory iron-responsive elements (IRE) in target mRNAs encoding proteins with key functions in iron metabolism. In turn, the IRE−binding activity of the two IRPs is feedback regulated by the cellular labile iron pool. Mouse models with IRP deficiency have contributed valuable insights into the in vivo roles of the IRP/IRE system as well as mammalian iron biology. However, the physiological consequences of gain of IRP function have so far remained unexplored. To investigate the importance of adequate IRP expression in vivo, we have generated a mouse model allowing conditional gain of IRP function using Cre/Lox technology. This new line expresses a flag-tagged IRP1 mutant (IRP1*), which escapes iron-mediated regulation, being constitutively active in its IRE binding form. Systemic expression of the IRP1* transgene from the Rosa26 locus yields viable animals with gain of IRE-binding activity in all organs that were analyzed. -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts. -
Cytosolic Iron-Sulfur Protein Assembly 1 (CIAO1) Downstream Activation
ogy iol : Op r B e a n l A u c c c e l e s Qi et al., Mol Biol 2012, 1:2 o s M Molecular Biology: Open Access DOI: 10.4172/2168-9547.1000105 ISSN: 2168-9547 Research Article Open Access Cytosolic Iron-Sulfur Protein Assembly 1 (CIAO1) Downstream Activation of Phospholipase A2 and Hormone-Mediated Signaling-Induced Cell Death Network in Human Hepatocellular Carcinoma (HCC) by Systems- Theoretical Analysis Lianxiu Qi1, Lin Wang1*, Minghu Jiang2, Juxiang Huang1 and Hong Lin1 1Biomedical Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China 2Lab of Computational Linguistics, School of Humanities and Social Sciences, Tsinghua University, Beijing, 100084, China Abstract We constructed the significant high expression (fold change ≥ 2) cytosolic iron-sulfur protein assembly 1 (CIAO1) downstream activation of phospholipase A2 and hormone-mediated signaling-induced cell death network in human Hepato Cellular Carcinoma (HCC), compared with low expression no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) in GEO data set, by using integration of gene regulatory activated and inhibited network inference method. Our result showed that CIAO1 downstream activation of phospholipase A2 and hormone-mediated signaling-induced cell death upstream network had no result, and downstream CIAO1-activated PLA2G1B, NUP62 in HCC. By integrative analysis of biological processes simultaneous occurrence between the different CIAO1 activated downstream cell death gene ontology (GO) network of HCC -
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245 E L Woodward et al. Genetic changes in anaplastic 24:5 209–220 Research thyroid cancer Genomic complexity and targeted genes in anaplastic thyroid cancer cell lines Eleanor L Woodward1, Andrea Biloglav1, Naveen Ravi1, Minjun Yang1, Lars Ekblad2, Johan Wennerberg3 and Kajsa Paulsson1 1Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden Correspondence 2Division of Oncology and Pathology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden should be addressed 3Division of Otorhinolaryngology/Head and Neck Surgery, Clinical Sciences, Lund University and Skåne to K Paulsson University Hospital, Lund, Sweden Email [email protected] Abstract Anaplastic thyroid cancer (ATC) is a highly malignant disease with a very short median Key Words survival time. Few studies have addressed the underlying somatic mutations, and the f thyroid genomic landscape of ATC thus remains largely unknown. In the present study, we f molecular genetics have ascertained copy number aberrations, gene fusions, gene expression patterns, f gene expression and mutations in early-passage cells from ten newly established ATC cell lines using single nucleotide polymorphism (SNP) array analysis, RNA sequencing and whole exome sequencing. The ATC cell line genomes were highly complex and displayed signs of replicative stress and genomic instability, including massive aneuploidy and frequent Endocrine-Related Cancer Endocrine-Related breakpoints in the centromeric regions and in fragile sites. Loss of heterozygosity involving whole chromosomes was common, but there were no signs of previous near- haploidisation events or chromothripsis. A total of 21 fusion genes were detected, including six predicted in-frame fusions; none were recurrent.