Persistence of Japanese Encephalitis Virus Is Associated with Abnormal Expression of the Nonstructural Protein NS1 in Host Cells

AbstractPersistent infection with Japanese encephalitis virus (JEV) was established in murine neuroblastoma N18 cells, and the persistency has been maintained in cell culture for over 6 months. From the persistently infected cells, a clone named C2-2 was selected and expanded to form a stable cell line. The vast majority of C2-2 cells showed viral protein staining by immunofluorescence and continuously produced low levels of virus (103to 104PFU/ml) without marked cytopathic effects or cyclic variations. In addition to the wild-type viral proteins, truncated forms of the viral nonstructural protein 1 (NS1) as well as its derivative NS1′ were produced in C2-2 cells. Both truncated NS1 and NS1′ contain deletions at their N-termini; however, the analyses by RT–PCR and direct sequencing of the viral RNA failed to detect any truncations or mutations within the NS1 region, suggesting that NS1 truncation was a result of a unique posttranslational proteolytic cleavage of NS1 in the persistently infected cells. Similar but not identical truncation of NS1 was also observed in two other persistently infected cell lines established in Vero and DBT (murine astrocytoma) cells. However, viruses released from C2-2 cells did not produce truncated NS1 upon infection of N18 cells, suggesting that NS1 truncations were the result of virus–cell interaction in persistently infected cells. These data indicate a strong association between abnormal NS1 expression and JEV persistency. A probable involvement of dysfunctional NS1 in the establishment and/or maintenance of JEV persistency in tissue culture is discussed

Dengue Virus Targets the Adaptor Protein MITA to Subvert Host Innate Immunity

Dengue is one of the most important arboviral diseases caused by infection of four serotypes of dengue virus (DEN). We found that activation of interferon regulatory factor 3 (IRF3) triggered by viral infection and by foreign DNA and RNA stimulation was blocked by DEN-encoded NS2B3 through a protease-dependent mechanism. The key adaptor protein in type I interferon pathway, human mediator of IRF3 activation (MITA) but not the murine homologue MPYS, was cleaved in cells infected with DEN-1 or DEN-2 and with expression of the enzymatically active protease NS2B3. The cleavage site of MITA was mapped to LRR↓96G and the function of MITA was suppressed by dengue protease. DEN replication was reduced with overexpression of MPYS but not with MITA, while DEN replication was enhanced by MPYS knockdown, indicating an antiviral role of MITA/MPYS against DEN infection. The involvement of MITA in DEN-triggered innate immune response was evidenced by reduction of IRF3 activation and IFN induction in cells with MITA knockdown upon DEN-2 infection. NS2B3 physically interacted with MITA, and the interaction and cleavage of MITA could be further enhanced by poly(dA:dT) stimulation. Thus, we identified MITA as a novel host target of DEN protease and provide the molecular mechanism of how DEN subverts the host innate immunity

Non-nosocomial healthcare-associated infective endocarditis in Taiwan: an underrecognized disease with poor outcome

<p>Abstract</p> <p>Background</p> <p>Non-nosocomial healthcare-associated infective endocarditis (NNHCA-IE) is a new category of IE of increasing importance. This study described the clinical and microbiological characteristics and outcome of NNHCA-IE in Taiwan.</p> <p>Methods</p> <p>A retrospective study was conducted of all patients with IE admitted to the Kaohsiung Veterans General Hospital in Kaohsiung, Taiwan over a five-year period from July 2004 to July 2009. The clinical and microbiological features of NNHCA-IE were compared to those of community-acquired and nosocomial IE. Predictors for in-hospital death were determined.</p> <p>Results</p> <p>Two-hundred episodes of confirmed IE occurred during the study period. These included 148 (74%) community-acquired, 30 (15%) non-nosocomial healthcare-associated, and 22 (11%) nosocomial healthcare-associated IE. <it>Staphylococcus aureus </it>was the most frequent pathogen. Patients with NNHCA-IE compared to community-acquired IE, were older (median age, 67 vs. 44, years, <it>p </it>< 0.001), had more MRSA (43.3% vs. 9.5%, <it>p </it>< 0.001), more comorbidity conditions (median Charlson comorbidity index [interquartile range], 4[2-6] vs. 0[0-1], <it>p </it>< 0.001), a higher in-hospital mortality (50.0% vs. 17.6%, <it>p </it>< 0.001) and were less frequently recognized by clinicians on admission (16.7% vs. 47.7%, <it>p </it>= 0.002). The overall in-hospital mortality rate for all patients with IE was 25%. Shock was the strongest risk factor for in-hospital death (odds ratio 7.8, 95% confidence interval 2.4-25.2, <it>p </it>< 0.001).</p> <p>Conclusions</p> <p>NNHCA-IE is underrecognized and carries a high mortality rate. Early recognition is crucial to provide optimal management and improve outcome.</p

The cytotoxic T cell proteome and its shaping by the kinase mTOR

High-resolution mass spectrometry maps the cytotoxic T lymphocyte (CTL) proteome and the impact of mammalian target of rapamycin complex 1 (mTORC1) on CTLs. The CTL proteome was dominated by metabolic regulators and granzymes and mTORC1 selectively repressed and promoted expression of subset of CTL proteins (~10%). These included key CTL effector molecules, signaling proteins and a subset of metabolic enzymes. Proteomic data highlighted the potential for mTORC1 negative control of phosphatidylinositol (3,4,5)-trisphosphate (PtdIns(3,4,5)P(3)) production in CTL. mTORC1 was shown to repress PtdIns(3,4,5)P(3) production and to determine the mTORC2 requirement for activation of the kinase Akt. Unbiased proteomic analysis thus provides a comprehensive understanding of CTL identity and mTORC1 control of CTL function

Spatiotemporal DNA methylome dynamics of the developing mouse fetus

Cytosine DNA methylation is essential for mammalian development but understanding of its spatiotemporal distribution in the developing embryo remains limited. Here, as part of the mouse Encyclopedia of DNA Elements (ENCODE) project, we profiled 168 methylomes from 12 mouse tissues or organs at 9 developmental stages from embryogenesis to adulthood. We identified 1,808,810 genomic regions that showed variations in CG methylation by comparing the methylomes of different tissues or organs from different developmental stages. These DNA elements predominantly lose CG methylation during fetal development, whereas the trend is reversed after birth. During late stages of fetal development, non-CG methylation accumulated within the bodies of key developmental transcription factor genes, coinciding with their transcriptional repression. Integration of genome-wide DNA methylation, histone modification and chromatin accessibility data enabled us to predict 461,141 putative developmental tissue-specific enhancers, the human orthologues of which were enriched for disease-associated genetic variants. These spatiotemporal epigenome maps provide a resource for studies of gene regulation during tissue or organ progression, and a starting point for investigating regulatory elements that are involved in human developmental disorders

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Genome organization and chromatin analysis identify transcriptional downregulation of insulin-like growth factor signaling as a hallmark of aging in developing B cells.

BACKGROUND: Aging is characterized by loss of function of the adaptive immune system, but the underlying causes are poorly understood. To assess the molecular effects of aging on B cell development, we profiled gene expression and chromatin features genome-wide, including histone modifications and chromosome conformation, in bone marrow pro-B and pre-B cells from young and aged mice. RESULTS: Our analysis reveals that the expression levels of most genes are generally preserved in B cell precursors isolated from aged compared with young mice. Nonetheless, age-specific expression changes are observed at numerous genes, including microRNA encoding genes. Importantly, these changes are underpinned by multi-layered alterations in chromatin structure, including chromatin accessibility, histone modifications, long-range promoter interactions, and nuclear compartmentalization. Previous work has shown that differentiation is linked to changes in promoter-regulatory element interactions. We find that aging in B cell precursors is accompanied by rewiring of such interactions. We identify transcriptional downregulation of components of the insulin-like growth factor signaling pathway, in particular downregulation of Irs1 and upregulation of Let-7 microRNA expression, as a signature of the aged phenotype. These changes in expression are associated with specific alterations in H3K27me3 occupancy, suggesting that Polycomb-mediated repression plays a role in precursor B cell aging. CONCLUSIONS: Changes in chromatin and 3D genome organization play an important role in shaping the altered gene expression profile of aged precursor B cells. Components of the insulin-like growth factor signaling pathways are key targets of epigenetic regulation in aging in bone marrow B cell precursors

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