Molecular Basis of Angiogenesis and Neuroprotection by Angiogenin By
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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 -
An Interactomics Overview of the Human and Bovine Milk Proteome Over Lactation Lina Zhang1, Aalt D
Zhang et al. Proteome Science (2017) 15:1 DOI 10.1186/s12953-016-0110-0 RESEARCH Open Access An interactomics overview of the human and bovine milk proteome over lactation Lina Zhang1, Aalt D. J. van Dijk2,3,4 and Kasper Hettinga1* Abstract Background: Milk is the most important food for growth and development of the neonate, because of its nutrient composition and presence of many bioactive proteins. Differences between human and bovine milk in low abundant proteins have not been extensively studied. To better understand the differences between human and bovine milk, the qualitative and quantitative differences in the milk proteome as well as their changes over lactation were compared using both label-free and labelled proteomics techniques. These datasets were analysed and compared, to better understand the role of milk proteins in development of the newborn. Methods: Human and bovine milk samples were prepared by using filter-aided sample preparation (FASP) combined with dimethyl labelling and analysed by nano LC LTQ-Orbitrap XL mass spectrometry. Results: The human and bovine milk proteome show similarities with regard to the distribution over biological functions, especially the dominant presence of enzymes, transport and immune-related proteins. At a quantitative level, the human and bovine milk proteome differed not only between species but also over lactation within species. Dominant enzymes that differed between species were those assisting in nutrient digestion, with bile salt- activated lipase being abundant in human milk and pancreatic ribonuclease being abundant in bovine milk. As lactation advances, immune-related proteins decreased slower in human milk compared to bovine milk. -
1 Metabolic Dysfunction Is Restricted to the Sciatic Nerve in Experimental
Page 1 of 255 Diabetes Metabolic dysfunction is restricted to the sciatic nerve in experimental diabetic neuropathy Oliver J. Freeman1,2, Richard D. Unwin2,3, Andrew W. Dowsey2,3, Paul Begley2,3, Sumia Ali1, Katherine A. Hollywood2,3, Nitin Rustogi2,3, Rasmus S. Petersen1, Warwick B. Dunn2,3†, Garth J.S. Cooper2,3,4,5* & Natalie J. Gardiner1* 1 Faculty of Life Sciences, University of Manchester, UK 2 Centre for Advanced Discovery and Experimental Therapeutics (CADET), Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UK 3 Centre for Endocrinology and Diabetes, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, UK 4 School of Biological Sciences, University of Auckland, New Zealand 5 Department of Pharmacology, Medical Sciences Division, University of Oxford, UK † Present address: School of Biosciences, University of Birmingham, UK *Joint corresponding authors: Natalie J. Gardiner and Garth J.S. Cooper Email: [email protected]; [email protected] Address: University of Manchester, AV Hill Building, Oxford Road, Manchester, M13 9PT, United Kingdom Telephone: +44 161 275 5768; +44 161 701 0240 Word count: 4,490 Number of tables: 1, Number of figures: 6 Running title: Metabolic dysfunction in diabetic neuropathy 1 Diabetes Publish Ahead of Print, published online October 15, 2015 Diabetes Page 2 of 255 Abstract High glucose levels in the peripheral nervous system (PNS) have been implicated in the pathogenesis of diabetic neuropathy (DN). However our understanding of the molecular mechanisms which cause the marked distal pathology is incomplete. Here we performed a comprehensive, system-wide analysis of the PNS of a rodent model of DN. -
Deamidation of Human Proteins
Deamidation of human proteins N. E. Robinson*† and A. B. Robinson‡ *Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA 91125; and ‡Oregon Institute of Science and Medicine, Cave Junction, OR 97523 Communicated by Frederick Seitz, The Rockefeller University, New York, NY, August 31, 2001 (received for review May 8, 2001) Deamidation of asparaginyl and glutaminyl residues causes time- 3D structure is known (23). This method is more than 95% dependent changes in charge and conformation of peptides and reliable in predicting relative deamidation rates of Asn residues proteins. Quantitative and experimentally verified predictive cal- within a single protein and is also useful for the prediction of culations of the deamidation rates of 1,371 asparaginyl residues in absolute deamidation rates. a representative collection of 126 human proteins have been It is, therefore, now possible to compute the expected deami- performed. These rates suggest that deamidation is a biologically dation rate of any protein for which the primary and 3D relevant phenomenon in a remarkably large percentage of human structures are known, except for very long-lived proteins. These proteins. proteins require measurement of the 400 Gln pentapeptide rates. in vivo deamidation ͉ asparaginyl residues Materials and Methods Calculation Method. The Brookhaven Protein Data Bank (PDB) eamidation of asparaginyl (Asn) and glutaminyl (Gln) was searched to select 126 human proteins of general biochem- Dresidues to produce aspartyl (Asp) and glutamyl (Glu) ical interest and of known 3D structure without bias toward any residues causes structurally and biologically important alter- known data about their deamidation, except for 13 proteins (as ations in peptide and protein structures. -
(12) Patent Application Publication (10) Pub. No.: US 2003/0082511 A1 Brown Et Al
US 20030082511A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2003/0082511 A1 Brown et al. (43) Pub. Date: May 1, 2003 (54) IDENTIFICATION OF MODULATORY Publication Classification MOLECULES USING INDUCIBLE PROMOTERS (51) Int. Cl." ............................... C12O 1/00; C12O 1/68 (52) U.S. Cl. ..................................................... 435/4; 435/6 (76) Inventors: Steven J. Brown, San Diego, CA (US); Damien J. Dunnington, San Diego, CA (US); Imran Clark, San Diego, CA (57) ABSTRACT (US) Correspondence Address: Methods for identifying an ion channel modulator, a target David B. Waller & Associates membrane receptor modulator molecule, and other modula 5677 Oberlin Drive tory molecules are disclosed, as well as cells and vectors for Suit 214 use in those methods. A polynucleotide encoding target is San Diego, CA 92121 (US) provided in a cell under control of an inducible promoter, and candidate modulatory molecules are contacted with the (21) Appl. No.: 09/965,201 cell after induction of the promoter to ascertain whether a change in a measurable physiological parameter occurs as a (22) Filed: Sep. 25, 2001 result of the candidate modulatory molecule. Patent Application Publication May 1, 2003 Sheet 1 of 8 US 2003/0082511 A1 KCNC1 cDNA F.G. 1 Patent Application Publication May 1, 2003 Sheet 2 of 8 US 2003/0082511 A1 49 - -9 G C EH H EH N t R M h so as se W M M MP N FIG.2 Patent Application Publication May 1, 2003 Sheet 3 of 8 US 2003/0082511 A1 FG. 3 Patent Application Publication May 1, 2003 Sheet 4 of 8 US 2003/0082511 A1 KCNC1 ITREXCHO KC 150 mM KC 2000000 so 100 mM induced Uninduced Steady state O 100 200 300 400 500 600 700 Time (seconds) FIG. -
MALE Protein Name Accession Number Molecular Weight CP1 CP2 H1 H2 PDAC1 PDAC2 CP Mean H Mean PDAC Mean T-Test PDAC Vs. H T-Test
MALE t-test t-test Accession Molecular H PDAC PDAC vs. PDAC vs. Protein Name Number Weight CP1 CP2 H1 H2 PDAC1 PDAC2 CP Mean Mean Mean H CP PDAC/H PDAC/CP - 22 kDa protein IPI00219910 22 kDa 7 5 4 8 1 0 6 6 1 0.1126 0.0456 0.1 0.1 - Cold agglutinin FS-1 L-chain (Fragment) IPI00827773 12 kDa 32 39 34 26 53 57 36 30 55 0.0309 0.0388 1.8 1.5 - HRV Fab 027-VL (Fragment) IPI00827643 12 kDa 4 6 0 0 0 0 5 0 0 - 0.0574 - 0.0 - REV25-2 (Fragment) IPI00816794 15 kDa 8 12 5 7 8 9 10 6 8 0.2225 0.3844 1.3 0.8 A1BG Alpha-1B-glycoprotein precursor IPI00022895 54 kDa 115 109 106 112 111 100 112 109 105 0.6497 0.4138 1.0 0.9 A2M Alpha-2-macroglobulin precursor IPI00478003 163 kDa 62 63 86 72 14 18 63 79 16 0.0120 0.0019 0.2 0.3 ABCB1 Multidrug resistance protein 1 IPI00027481 141 kDa 41 46 23 26 52 64 43 25 58 0.0355 0.1660 2.4 1.3 ABHD14B Isoform 1 of Abhydrolase domain-containing proteinIPI00063827 14B 22 kDa 19 15 19 17 15 9 17 18 12 0.2502 0.3306 0.7 0.7 ABP1 Isoform 1 of Amiloride-sensitive amine oxidase [copper-containing]IPI00020982 precursor85 kDa 1 5 8 8 0 0 3 8 0 0.0001 0.2445 0.0 0.0 ACAN aggrecan isoform 2 precursor IPI00027377 250 kDa 38 30 17 28 34 24 34 22 29 0.4877 0.5109 1.3 0.8 ACE Isoform Somatic-1 of Angiotensin-converting enzyme, somaticIPI00437751 isoform precursor150 kDa 48 34 67 56 28 38 41 61 33 0.0600 0.4301 0.5 0.8 ACE2 Isoform 1 of Angiotensin-converting enzyme 2 precursorIPI00465187 92 kDa 11 16 20 30 4 5 13 25 5 0.0557 0.0847 0.2 0.4 ACO1 Cytoplasmic aconitate hydratase IPI00008485 98 kDa 2 2 0 0 0 0 2 0 0 - 0.0081 - 0.0 -
Nucleic Acid Nanostructures–DNA and RNA Nanoparticles Lekhana S, Kanishka B, Sneha Thakur*
REVIEW ARTICLE Nucleic Acid Nanostructures–DNA and RNA Nanoparticles Lekhana S, Kanishka B, Sneha Thakur* Department of Pharmacy, Bojjam Narsimhulu Pharmacy College for Women, Saidabad, Hyderabad-500059, Telangana, India Received: 20th March, 2020; Revised: 19th April, 2020; Accepted: 21st May, 2020; Available Online: 25th June, 2020 ABSTRACT Nanotechnology is the field of science that encompasses the production of nanoparticles at nanoatomic scale. The nanoparticles size governs wide range of therapeutic properties. The nanostructures when formulated using deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) materials can result in enhanced hydrophobic properties, shelf life, and also may enhance targeted drug delivery. Structured or dynamic DNA nanostructures involve basic nucleotide pairing with protein backbone. The DNA nanostructures produced by bottom to top approach are currently being applied in medicine, cancer, ophthalmic drug delivery, and also for diagnosis and treatment. They involve complimentary DNA base pairing (AT/GC) for strong interaction resulting in formulation of structures with 10 to 50 mm size. RNA nanostructures are multifunctional manipulative structures synthesized using a bottom-up approach, which results in modulated physiochemical properties and enhanced stability. RNA nanoparticles are currently exploited in the field of cancer. Both DNA and RNA nanostructures are 2D/3D multidimensional models, which are novel structures in the field of nanoscience. DNA/RNA nanostructures can be identified by the Killer Killiani test, quantitative estimation, and also spectroscopic methods like UV, SDS-Page, XRD, SEM, and DLS techniques can be applied. The wide range of applications of these DNA/RNA nanostructures are currently considered as an area of interest in field of therapeutics by most of the researchers. -
Assembly of Phi29 Prna Nanoparticles for Gene Or Drug
Assembly of Phi29 pRNA Nanoparticles for Gene or Drug Delivery and for Application in Nanotechnology and Nanomedicine A dissertation submitted to The Division of Research and Advanced Studies, University of Cincinnati In partial fulfillment of the requirements for the degree of Doctor of Philosophy In the Biomedical Engineering Program School of Energy, Environmental, Biological and Medical Engineering College of Engineering and Applied Science 2012 by Yi Shu M.S. Chinese Center for Disease Control and Prevention (CCDC), China, 2007 B.S. Lanzhou University, China, 2004 Committee Chair: Jing-Hui Lee, Ph.D Co-chair: Peixuan Guo, Ph.D ABSTRACT RNA nanotechnology is to extract defined RNA structure motifs and tertiary interactions, apply them as the building blocks to self-assemble nano-scaled scaffolds with rational designs, and incorporate functional molecules such as siRNA, ribozyme, aptamer and therapeutical compounds to form functionalized RNA nanoparticles. Bacteriophage phi29 packaging RNA (pRNA) has two defined domains: the 5’/3’-end helical domain and the interlocking loop region which is located at the central part of the pRNA sequence. pRNA dimer is formed by hand-in-hand interaction via 4-bp interlocking base pairing. The dimeric pRNA nanoparticle has been shown to be an efficient vector for the specific delivery of small interfering RNA (siRNA) into specific cancer or viral infected cells. However, there are several problems hindering the therapeutic applications of pRNA nanoparticles. In this thesis, I will try to address: 1) The problem of large-scale synthesis of longer RNA molecules. Industrial scale production of RNA by chemical synthesis is limited to ~ 80nt. -
The Interplay Between the RNA Decay and Translation Machinery in Eukaryotes
Downloaded from http://cshperspectives.cshlp.org/ on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press The Interplay between the RNA Decay and Translation Machinery in Eukaryotes Adam M. Heck1,2 and Jeffrey Wilusz1,2 1Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado 80525 2Program in Cell & Molecular Biology, Colorado State University, Fort Collins, Colorado 80525 Correspondence: [email protected] RNA decay plays a major role in regulating gene expression and is tightly networked with other aspects of gene expression to effectively coordinate post-transcriptional regulation. The goal of this work is to provide an overview of the major factors and pathways of general messenger RNA (mRNA) decay in eukaryotic cells, and then discuss the effective interplay of this cytoplasmic process with the protein synthesis machinery. Given the transcript-specific and fluid nature of mRNA stability in response to changing cellular conditions, understanding the fundamental networking between RNA decay and translation will provide a foundation for a complete mechanistic understanding of this important aspect of cell biology. NA degradation plays a major role in regu- gene expression is needed to further elucidate Rlating both the quantity and quality of gene the depth of regulation that occurs in cells. expression in the cell. The abundance of an RNA The goal of this work is to provide an up-to- transcript is a reflection of both its rate of syn- date overview of the factors and mechanisms thesis and degradation. There are numerous ex- of general mRNA decay and then focus on the amples in the literature regarding the regulation interplay of this process with the translational of gene expression associated with major cellular machinery. -
Molecular Cloning of Four Novel Murine Ribonuclease Genes: Unusual Expansion Within the Ribonuclease a Gene Family Dean Batten+, Kimberly D
1997 Oxford University Press Nucleic Acids Research, 1997, Vol. 25, No. 21 4235–4239 Molecular cloning of four novel murine ribonuclease genes: unusual expansion within the Ribonuclease A gene family Dean Batten+, Kimberly D. Dyer, Joseph B. Domachowske§ and Helene F. Rosenberg* The Laboratory of Host Defenses, Building 10, Room 11N104, National Institute of Allergy and Infectious Diseases, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA Received August 4, 1997; Revised and Accepted September 17, 1997 DDBJ/EMBL/GenBank accession numbers: U72031, U72032, AF017258–AF017261 ABSTRACT numerous somatic tissues in addition to pancreas (5). RNases 2 and 3, eosinophil-derived neurotoxin (EDN) and eosinophil cationic We have characterized four novel murine ribonuclease protein (ECP), respectively, have been characterized primarily with genes that, together with the murine eosinophil- respect to eosinophil function (6,7), although expression of EDN associated ribonucleases 1 and 2, form a distinct and [also known as RNase Us (8) or human liver ribonuclease (9)] is unusual cluster within the RNase A gene superfamily. also widespread (5). Angiogenin (RNase 5), a structurally atypical Three of these genes (mR-3, mR-4, mR-5) include member of this family, was originally identified as an agent complete open reading frames, encoding ribo- promoting blood vessel growth and development (10,11). RNase 4 nucleases with eight cysteines and appropriately (12,13) and RNase k6 (14) are also members of the RNase A spaced histidines (His11 and His124) and lysine (Lys35) superfamily, although their functions are currently obscure. that are characteristic of this enlarging protein family; Recently, Larson and colleagues (15) described cDNAs encoding the fourth sequence encodes a non-functional pseudo- two highly homologous murine ribonucleases, the murine eosino- gene (mR-6P). -
Protein Symbol Protein Name Rank Metric Score 4F2 4F2 Cell-Surface
Supplementary Table 2 Supplementary Table 2. Ranked list of proteins present in anti-Sema4D treated macrophage conditioned media obtained in the GSEA analysis of the proteomic data. Proteins are listed according to their rank metric score, which is the score used to position the gene in the ranked list of genes of the GSEA. Values are obtained from comparing Sema4D treated RAW conditioned media versus REST, which includes untreated, IgG treated and anti-Sema4D added RAW conditioned media. GSEA analysis was performed under standard conditions in November 2015. Protein Rank metric symbol Protein name score 4F2 4F2 cell-surface antigen heavy chain 2.5000 PLOD3 Procollagen-lysine,2-oxoglutarate 5-dioxygenase 3 1.4815 ELOB Transcription elongation factor B polypeptide 2 1.4350 ARPC5 Actin-related protein 2/3 complex subunit 5 1.2603 OSTF1 teoclast-stimulating factor 1 1.2500 RL5 60S ribomal protein L5 1.2135 SYK Lysine--tRNA ligase 1.2135 RL10A 60S ribomal protein L10a 1.2135 TXNL1 Thioredoxin-like protein 1 1.1716 LIS1 Platelet-activating factor acetylhydrolase IB subunit alpha 1.1067 A4 Amyloid beta A4 protein 1.0911 H2B1M Histone H2B type 1-M 1.0514 UB2V2 Ubiquitin-conjugating enzyme E2 variant 2 1.0381 PDCD5 Programmed cell death protein 5 1.0373 UCHL3 Ubiquitin carboxyl-terminal hydrolase isozyme L3 1.0061 PLEC Plectin 1.0061 ITPA Inine triphphate pyrophphatase 0.9524 IF5A1 Eukaryotic translation initiation factor 5A-1 0.9314 ARP2 Actin-related protein 2 0.8618 HNRPL Heterogeneous nuclear ribonucleoprotein L 0.8576 DNJA3 DnaJ homolog subfamily -
BIOINF-2006-1117 Revision 3
Bioinformatics Advance Access published January 31, 2007 S.K.L NG and S.K MISHRA large internal loops or bulges especially large asymmetric ones from the hairpins that obviates the use of comparative genomics infor- (Ambros et al., 2003). Apparently, mere application of simple align- mation. The SVM classifier model trained with the experimental do- ment queries and positive-selection rules is likely to overlook novel main knowledge and binary-labeled feature vectors, recovered 71% of families lacking clear homologues to published mature miRNAs. the positive pre-miRs with a remarkably low false-positive rate of ~3%. Advanced comparative approaches like MiRscan (Lim et al., 2003b; It also predicted ~50 to 100 novel pre-miRs for several species; ~30% Lim et al., 2003a), MIRcheck (Jones-Rhoades and Bartel 2004), miR- of these were previously experimentally validated. The validation rate Finder (Bonnet et al., 2004a), miRseeker (Lai et al., 2003), findMiRNA among the predicted cases that were conserved in ≥1 other species was (Adai et al., 2005), PalGrade (Bentwich et al., 2005), and MiRAlign higher at ~60%; many had not been detected by comparative genomics (Wang et al., 2005) have systematically exploit the greater availability approaches. The 3SVM (Xue et al., 2005) improved the performances of sequenced genomes for eliminating the over-represented false- to ~90.00% for human and up to 90.00% in other species. Albeit its positives. Cross-species sequence conservation based on computation- methodological simplicity, promising performances, and independence ally intensive multiple genome alignments is a powerful approach for of comparative genomics information, 3SVM was largely limited to genome-wide screening of phylogentically well conserved pre-miRs classifying RNA sequences that fold into secondary structures without between closely related species.