Brief Report: Elastin Microfibril Interface 1 and Integrin-Linked Protein Kinase Are Novel Markers of Islet Regenerative Function in Human Multipotent Mesenchymal Stromal Cells

Multipotent mesenchymal stromal cell (MSC) transplantation is proposed as a novel therapy for treating diabetes by promoting the regeneration of damaged islets. The clinical promise of such treatments may be hampered by a high degree of donor-related variability in MSC function and a lack of standards for comparing potency. Here, we set out to identify markers of cultured human MSCs directly associated with islet regenerative function. Stromal cultures from nine separate bone marrow donors were demonstrated to have differing capacities to reduce hyperglycemia in the NOD/SCID streptozotocin-induced diabetic model. Regenerative (R) and non-regenerative (NR) MSC cultures were directly compared using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics. A total of 1,410 proteins were quantified resulting in the identification of 612 upregulated proteins and 275 downregulated proteins by ± 1.2-fold in R-MSC cultures. Elastin microfibril interface 1 (EMILIN-1), integrin-linked protein kinase (ILK), and hepatoma-derived growth factor (HDGF) were differentially expressed in R-MSCs, and Ingenuity Pathway Analyses revealed each candidate as known regulators of integrin signaling. Western blot validation of EMILIN-1, ILK, and HDGF not only showed significantly higher abundance levels in R-MSCs, as compared with NR-MSCs, but also correlated with passage-induced loss of islet-regenerative potential. Generalized estimating equation modeling was applied to examine the association between each marker and blood glucose reduction. Both EMILIN-1 and ILK were significantly associated with blood glucose lowering function in vivo. Our study is the first to identify EMILIN-1 and ILK as prospective markers of islet regenerative function in human MSCs. Stem Cells 2016;34:2249–2255

The hydrophobic region of the Leishmania peroxin 14 : requirements for association with a glycosome mimetic membrane

This work was funded by operating grants from the Canadian Institutes of Health Research (CIHR) and a Natural Sciences Engineering Research Council of Canada (NSERC) Discovery grant [Fonds de recherche du Québec — Nature et technologies (FRQNT) Regroupement Stratégique grant to the Centre for Host-Parasite Interactions (A.J.)]. N.C. was supported by a doctoral research scholarship from FRQNT. E.B. was supported by a Banting postdoctoral fellowship from CIHR. This work was also supported in part by Wellcome Trust grants [086658 and 093228] to T.K.S. C.S. recognizes the financial support from the Natural Sciences and Engineering Research Council of Canada and a Canada Foundation for Innovation grant [16299].Protein import into the Leishmania glycosome requires docking of the cargo-loaded peroxin 5 (PEX5) receptor to the peroxin 14 (PEX14) bound to the glycosome surface. To examine the LdPEX14-membrane interaction, we purified L. donovani promastigote glycosomes and determined the phospholipid and fatty acid composition. These membranes contained predominately phosphatidylethanolamine, phosphatidylcholine, and phosphatidylglycerol (PG) modified primarily with C18 and C22 unsaturated fatty acid. Using large unilamellar vesicles (LUVs) with a lipid composition mimicking the glycosomal membrane in combination with sucrose density centrifugation and fluorescence-activated cell sorting technique, we established that the LdPEX14 membrane-binding activity was dependent on a predicted transmembrane helix found within residues 149-179. Monolayer experiments showed that the incorporation of PG and phospholipids with unsaturated fatty acids, which increase membrane fluidity and favor a liquid expanded phase, facilitated the penetration of LdPEX14 into biological membranes. Moreover, we demonstrated that the binding of LdPEX5 receptor or LdPEX5-PTS1 receptor-cargo complex was contingent on the presence of LdPEX14 at the surface of LUVs.PostprintPeer reviewe

Passerine Birds Breeding under Chronic Noise Experience Reduced Fitness

Background Fitness in birds has been shown to be negatively associated with anthropogenic noise, but the underlying mechanisms remain obscure. It is however crucial to understand the mechanisms of how urban noise impinges on fitness to obtain a better understanding of the role of chronic noise in urban ecology. Here, we examine three hypotheses on how noise might reduce reproductive output in passerine birds: (H1) by impairing mate choice, (H2) by reducing territory quality and (H3) by impeding chick development. Methodology/Principal Findings We used long-term data from an island population of house sparrows, Passer domesticus, in which we can precisely estimate fitness. We found that nests in an area affected by the noise from large generators produced fewer young, of lower body mass, and fewer recruits, even when we corrected statistically for parental genetic quality using a cross-fostering set-up, supporting H3. Also, individual females provided their young with food less often when they bred in the noisy area compared to breeding attempts by the same females elsewhere. Furthermore, we show that females reacted flexibly to increased noise levels by adjusting their provisioning rate in the short term, which suggests that noise may be a causal factor that reduces reproductive output. We rejected H1 and H2 because nestbox occupancy, parental body mass, age and reproductive investment did not differ significantly between noisy and quiet areas. Conclusions/Significance Our results suggest a previously undescribed mechanism to explain how environmental noise can reduce fitness in passerine birds: by acoustically masking parent–offspring communication. More importantly, using a cross-fostering set-up, our results demonstrate that birds breeding in a noisy environment experience significant fitness costs. Chronic noise is omnipresent around human habitation and may produces similar fitness consequences in a wide range of urban bird species

Unveiling Integrated Functional Pathways Leading to Enhanced Respiratory Disease Associated With Inactivated Respiratory Syncytial Viral Vaccine

Respiratory syncytial virus (RSV) infection is a severe threat to young children and the elderly. Despite decades of research, no vaccine has been approved. Notably, instead of affording protection, a formalin-inactivated RSV vaccine induced severe respiratory disease including deaths in vaccinated children in a 1960s clinical trial; however, recent studies indicate that other forms of experimental vaccines can also induce pulmonary pathology in pre-clinical studies. These findings suggest that multiple factors/pathways could be involved in the development of enhanced respiratory diseases. Clearly, a better understanding of the mechanisms underlying such adverse reactions is critically important for the development of safe and efficacious vaccines against RSV infection, given the exponential growth of RSV vaccine clinical trials in recent years. By employing an integrated systems biology approach in a pre-clinical cotton rat model, we unraveled a complex network of pulmonary canonical pathways leading to disease development in vaccinated animals upon subsequent RSV infections. Cytokines including IL-1, IL-6 GRO/IL-8, and IL-17 in conjunction with mobilized pulmonary inflammatory cells could play important roles in disease development, which involved a wide range of host responses including exacerbated pulmonary inflammation, oxidative stress, hyperreactivity, and homeostatic imbalance between coagulation and fibrinolysis. Moreover, the observed elevated levels of MyD88 implicate the involvement of this critical signal transduction module as the central node of the inflammatory pathways leading to exacerbated pulmonary pathology. Finally, the immunopathological consequences of inactivated vaccine immunization and subsequent RSV exposure were further substantiated by histological analyses of these key proteins along with inflammatory cytokines, while hypercoagulation was supported by increased pulmonary fibrinogen/fibrin accompanied by reduced levels of plasma D-dimers. Enhanced respiratory disease associated with inactivated RSV vaccine involves a complex network of host responses, resulting in significant pulmonary lesions and clinical manifestations such as tachypnea and airway obstruction. The mechanistic insight into the convergence of different signal pathways and identification of biomarkers could help facilitate the development of safe and effective RSV vaccine and formulation of new targeted interventions

NIST Interlaboratory Study on Glycosylation Analysis of Monoclonal Antibodies: Comparison of Results from Diverse Analytical Methods

Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submit- Avenue, Silver Spring, Maryland 20993; 22Glycoscience Research Laboratory, Genos, Borongajska cesta 83h, 10 000 Zagreb, Croatia; 23Faculty of Pharmacy and Biochemistry, University of Zagreb, A. Kovacˇ ic´ a 1, 10 000 Zagreb, Croatia; 24Department of Chemistry, Georgia State University, 100 Piedmont Avenue, Atlanta, Georgia 30303; 25glyXera GmbH, Brenneckestrasse 20 * ZENIT / 39120 Magdeburg, Germany; 26Health Products and Foods Branch, Health Canada, AL 2201E, 251 Sir Frederick Banting Driveway, Ottawa, Ontario, K1A 0K9 Canada; 27Graduate School of Advanced Sciences of Matter, Hiroshima University, 1-3-1 Kagamiyama Higashi-Hiroshima 739–8530 Japan; 28ImmunoGen, 830 Winter Street, Waltham, Massachusetts 02451; 29Department of Medical Physiology, Jagiellonian University Medical College, ul. Michalowskiego 12, 31–126 Krakow, Poland; 30Department of Pathology, Johns Hopkins University, 400 N. Broadway Street Baltimore, Maryland 21287; 31Mass Spec Core Facility, KBI Biopharma, 1101 Hamlin Road Durham, North Carolina 27704; 32Division of Mass Spectrometry, Korea Basic Science Institute, 162 YeonGuDanji-Ro, Ochang-eup, Cheongwon-gu, Cheongju Chungbuk, 363–883 Korea (South); 33Advanced Therapy Products Research Division, Korea National Institute of Food and Drug Safety, 187 Osongsaengmyeong 2-ro Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do, 363–700, Korea (South); 34Center for Proteomics and Metabolomics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; 35Ludger Limited, Culham Science Centre, Abingdon, Oxfordshire, OX14 3EB, United Kingdom; 36Biomolecular Discovery and Design Research Centre and ARC Centre of Excellence for Nanoscale BioPhotonics (CNBP), Macquarie University, North Ryde, Australia; 37Proteomics, Central European Institute for Technology, Masaryk University, Kamenice 5, A26, 625 00 BRNO, Czech Republic; 38Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, 39106 Magdeburg, Germany; 39Department of Biomolecular Sciences, Max Planck Institute of Colloids and Interfaces, 14424 Potsdam, Germany; 40AstraZeneca, Granta Park, Cambridgeshire, CB21 6GH United Kingdom; 41Merck, 2015 Galloping Hill Rd, Kenilworth, New Jersey 07033; 42Analytical R&D, MilliporeSigma, 2909 Laclede Ave. St. Louis, Missouri 63103; 43MS Bioworks, LLC, 3950 Varsity Drive Ann Arbor, Michigan 48108; 44MSD, Molenstraat 110, 5342 CC Oss, The Netherlands; 45Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, 5–1 Higashiyama, Myodaiji, Okazaki 444–8787 Japan; 46Graduate School of Pharmaceutical Sciences, Nagoya City University, 3–1 Tanabe-dori, Mizuhoku, Nagoya 467–8603 Japan; 47Medical & Biological Laboratories Co., Ltd, 2-22-8 Chikusa, Chikusa-ku, Nagoya 464–0858 Japan; 48National Institute for Biological Standards and Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire EN6 3QG United Kingdom; 49Division of Biological Chemistry & Biologicals, National Institute of Health Sciences, 1-18-1 Kamiyoga, Setagaya-ku, Tokyo 158–8501 Japan; 50New England Biolabs, Inc., 240 County Road, Ipswich, Massachusetts 01938; 51New York University, 100 Washington Square East New York City, New York 10003; 52Target Discovery Institute, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, OX3 7FZ, United Kingdom; 53GlycoScience Group, The National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Blackrock, Co. Dublin, Ireland; 54Department of Chemistry, North Carolina State University, 2620 Yarborough Drive Raleigh, North Carolina 27695; 55Pantheon, 201 College Road East Princeton, New Jersey 08540; 56Pfizer Inc., 1 Burtt Road Andover, Massachusetts 01810; 57Proteodynamics, ZI La Varenne 20–22 rue Henri et Gilberte Goudier 63200 RIOM, France; 58ProZyme, Inc., 3832 Bay Center Place Hayward, California 94545; 59Koichi Tanaka Mass Spectrometry Research Laboratory, Shimadzu Corporation, 1 Nishinokyo Kuwabara-cho Nakagyo-ku, Kyoto, 604 8511 Japan; 60Children’s GMP LLC, St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, Tennessee 38105; 61Sumitomo Bakelite Co., Ltd., 1–5 Muromati 1-Chome, Nishiku, Kobe, 651–2241 Japan; 62Synthon Biopharmaceuticals, Microweg 22 P.O. Box 7071, 6503 GN Nijmegen, The Netherlands; 63Takeda Pharmaceuticals International Co., 40 Landsdowne Street Cambridge, Massachusetts 02139; 64Department of Chemistry and Biochemistry, Texas Tech University, 2500 Broadway, Lubbock, Texas 79409; 65Thermo Fisher Scientific, 1214 Oakmead Parkway Sunnyvale, California 94085; 66United States Pharmacopeia India Pvt. Ltd. IKP Knowledge Park, Genome Valley, Shamirpet, Turkapally Village, Medchal District, Hyderabad 500 101 Telangana, India; 67Alberta Glycomics Centre, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 68Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2 Canada; 69Department of Chemistry, University of California, One Shields Ave, Davis, California 95616; 70Horva´ th Csaba Memorial Laboratory for Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Egyetem ter 1, Hungary; 71Translational Glycomics Research Group, Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Egyetem ut 10, Hungary; 72Delaware Biotechnology Institute, University of Delaware, 15 Innovation Way Newark, Delaware 19711; 73Proteomics Core Facility, University of Gothenburg, Medicinaregatan 1G SE 41390 Gothenburg, Sweden; 74Department of Medical Biochemistry and Cell Biology, University of Gothenburg, Institute of Biomedicine, Sahlgrenska Academy, Medicinaregatan 9A, Box 440, 405 30, Gothenburg, Sweden; 75Department of Clinical Chemistry and Transfusion Medicine, Sahlgrenska Academy at the University of Gothenburg, Bruna Straket 16, 41345 Gothenburg, Sweden; 76Department of Chemistry, University of Hamburg, Martin Luther King Pl. 6 20146 Hamburg, Germany; 77Department of Chemistry, University of Manitoba, 144 Dysart Road, Winnipeg, Manitoba, Canada R3T 2N2; 78Laboratory of Mass Spectrometry of Interactions and Systems, University of Strasbourg, UMR Unistra-CNRS 7140, France; 79Natural and Medical Sciences Institute, University of Tu¨ bingen, Markwiesenstrae 55, 72770 Reutlingen, Germany; 80Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands; 81Division of Bioanalytical Chemistry, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, de Boelelaan 1085, 1081 HV Amsterdam, The Netherlands; 82Department of Chemistry, Waters Corporation, 34 Maple Street Milford, Massachusetts 01757; 83Zoetis, 333 Portage St. Kalamazoo, Michigan 49007 Author’s Choice—Final version open access under the terms of the Creative Commons CC-BY license. Received July 24, 2019, and in revised form, August 26, 2019 Published, MCP Papers in Press, October 7, 2019, DOI 10.1074/mcp.RA119.001677 ER: NISTmAb Glycosylation Interlaboratory Study 12 Molecular & Cellular Proteomics 19.1 Downloaded from https://www.mcponline.org by guest on January 20, 2020 ted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide communityderived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods. Molecular & Cellular Proteomics 19: 11–30, 2020. DOI: 10.1074/mcp.RA119.001677.L

Data generated from three quantitative mass spectral methods for the analysis of trivalent influenza vaccine antigens are compared

Herein we present the data necessary for generation of alternative means to produce equimolar mixtures of peptides (“Design and Expression of a QconCAT Protein to Validate Hi3 Protein Quantification of Influenza Vaccine Antigens” (D.G.S. Smith, G. Gingras, Y. Aubin, T.D. Cyr, 2016) [1]), such as QConCAT (“Trends in QconCATs for targeted proteomics” (J. Chen, I.V. Turko, 2014) [2] , “Natural flanking sequences for peptides included in a quantification concatamer internal standard” (C.S. Cheung, K.W. Anderson, M. Wang, I.V. Turko, 2015) [3]) and SpikeTides versus the label free Hi3 approach. The experimental design and the interpretation of results are discussed in the original article [1]

Re-Assessing Red Blood Cell Storage

Numerous reports have surfaced over the past decade centering on the potential for complications when transfusing “new” versus “old” stored red blood cells (RBCs). The transfusion of whole blood and packed RBCs has been a standard medical treatment since Landsteiner in 1900 developed red cell ABO typing, leading to compatible transfusions from donor to recipient. Nearly fifteen million units of whole blood are donated in the United States each year by approximately eight million volunteer blood donors. These donor units are transfused to about four million recipients. Unfortunately, despite the great need and the generous contributions of volunteers, blood is always in short supply; and therefore, the need for donated blood continues. On any given day, approximately 35,000 units of blood are needed to treat surgical patients, accident victims, and patients who are anemic from leukemia, cancer, or other diseases.</p