An integrated natural remanent magnetization acquisition model for the Matuyama-Brunhes reversal recorded by the Chinese loess

Geomagnetic polarity reversal boundaries are key isochronous chronological controls for the long Chinese loess sequences, and further facilitate paleoclimatic correlation between Chinese loess and marine sediments. However, owing to complexity of postdepositional remanent magnetization (pDRM) acquisition processes related to variable dust sedimentary environments on the Chinese Loess Plateau (CLP), there is a long-standing dispute concerning the downward shift of the pDRM recorded in Chinese loess. In this study, after careful stratigraphic correlation of representative climatic tie points and the Matuyama-Brunhes boundaries (MBB) in the Xifeng, Luochuan, and Mangshan loess sections with different pedogenic environments, the downward shift of the pDRM is semiquantitatively estimated and the acquisition model for the loess natural remanent magnetization (NRM) is discussed. The measured MB transition zone has been affected by the surficial mixing layer (SML) and remagnetization. Paleoprecipitation is suggested to be the dominant factor controlling the pDRM acquisition processes. Rainfall-controlled leaching would restrict the efficiency of the characterized remanent magnetization carriers aligning along the ancient geomagnetic field. We conclude that the MBB in the central CLP with moderate paleoprecipitation could be considered as an isochronous chronological control after moderate upward adjustment. A convincing case can then be made to correlate L8/S8 to MIS 18/1

Helicobacter suis binding to carbohydrates on human and porcine gastric mucins and glycolipids occurs via two modes

Helicobacter suis colonizes the stomach of most pigs and is the most prevalent non-Helicobacter pylori Helicobacter species found in the human stomach. In the human host, H. suis contributes to the development of chronic gastritis, peptic ulcer disease and MALT lymphoma, whereas in pigs it is associated with gastritis, decreased growth and ulcers. Here, we demonstrate that the level of H. pylori and H. suis binding to human and pig gastric mucins varies between individuals with species dependent specificity. The binding optimum of H. pylori is at neutral pH whereas that of H. suis has an acidic pH optimum, and the mucins that H. pylori bind to are different than those that H. suis bind to. Mass spectrometric analysis of mucin O-glycans from the porcine mucin showed that individual variation in binding is reflected by a difference in glycosylation; of 109 oligosaccharide structures identified, only 14 were present in all examined samples. H. suis binding to mucins correlated with glycans containing sulfate, sialic acid and terminal galactose. Among the glycolipids present in pig stomach, binding to lactotetraosylceramide (Gal beta 3GlcNAc beta 3Gal beta 4Glc beta 1Cer) was identified, and adhesion to Gal beta 3GlcNAc beta 3Gal beta 4Glc at both acidic and neutral pH was confirmed using other glycoconjugates. Together with that H. suis bound to DNA (used as a proxy for acidic charge), we conclude that H. suis has two binding modes: one to glycans terminating with Gal beta 3GlcNAc, and one to negatively charged structures. Identification of the glycan structures H. suis interacts with can contribute to development of therapeutic strategies alternative to antibiotics

Sulfated glycan recognition by carbohydrate sulfatases of the human gut microbiota

International audienceSulfated glycans are ubiquitous nutrient sources for microbial communities that have co-evolved with eukaryotic hosts. Bacteria metabolise sulfated glycans by deploying carbohydrate sulfatases that remove sulfate esters. Despite the biological importance of sulfatases, the mechanisms underlying their ability to recognise their glycan substrate remain poorly understood. Here, we utilise structural biology to determine how sulfatases from the human gut microbiota recognise sulfated glycans. We reveal 7 new carbohydrate sulfatase structures span four S1 sulfatase subfamilies. Structures of S1_16 and S1_46 represent the first structures of these subfamilies. Structures of S1_11 and S1_15 demonstrate how non-conserved regions of the protein drive specificity towards related but distinct glycan targets. Collectively, these data reveal that Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: https://www.springernature.com/gp/open-research/policies/accepted-manuscript-term

Correlation of IDH1 Mutation with Clinicopathologic Factors and Prognosis in Primary Glioblastoma: A Report of 118 Patients from China

It has been reported that IDH1 (IDH1R132) mutation was a frequent genomic alteration in grade II and grade III glial tumors but rare in primary glioblastoma (pGBM). To elucidate the frequency of IDH1 mutation and its clinical significance in Chinese patients with pGBM, one hundred eighteen pGBMs were assessed by pyro-sequencing for IDH1 mutation status, and the results were correlated with clinical characteristics and molecular pathological factors. IDH1 mutations were detected in 19/118 pGBM cases (16.1%). Younger age, methylated MGMT promoter, high expression of mutant P53 protein, low expression of Ki-67 or EGFR protein were significantly correlated with IDH1 mutation status. Most notably, we identified pGBM cases with IDH1 mutation were mainly involved in the frontal lobe when compared with those with wild-type IDH1. In addition, Kaplan-Meier survival analysis revealed a highly significant association between IDH1 mutation and a better clinical outcome (p = 0.026 for progression-free survival; p = 0.029 for overall survival). However, in our further multivariable regression analysis, the independent prognostic effect of IDH1 mutation is limited when considering age, preoperative KPS score, extent of resection, TMZ chemotherapy, and Ki-67 protein expression levels, which might narrow its prognostic power in Chinese population in the future

A single sulfatase is required to access colonic mucin by a gut bacterium

International audienceHumans have co-evolved with a dense community of microbial symbionts that inhabit the lower intestine. In the colon, secreted mucus creates a barrier that separates these microorganisms from the intestinal epithelium1. Some gut bacteria are able to utilize mucin glycoproteins, the main mucus component, as a nutrient source. However, it remains unclear which bacterial enzymes initiate degradation of the complex O-glycans found in mucins. In the distal colon, these glycans are heavily sulfated, but specific sulfatases that are active on colonic mucins have not been identified. Here we show that sulfatases are essential to the utilization of distal colonic mucin O-glycans by the human gut symbiont Bacteroides thetaiotaomicron. We characterized the activity of 12 different sulfatases produced by this species, showing that they are collectively active on all known sulfate linkages in O-glycans. Crystal structures of three enzymes provide mechanistic insight into the molecular basis of substrate specificity. Unexpectedly, we found that a single sulfatase is essential for utilization of sulfated O-glycans in vitro and also has a major role in vivo. Our results provide insight into the mechanisms of mucin degradation by a prominent group of gut bacteria, an important process for both normal microbial gut colonization2 and diseases such as inflammatory bowel diseas

Comparative genome structure, secondary metabolite, and effector coding capacity across Cochliobolus pathogens.

The genomes of five Cochliobolus heterostrophus strains, two Cochliobolus sativus strains, three additional Cochliobolus species (Cochliobolus victoriae, Cochliobolus carbonum, Cochliobolus miyabeanus), and closely related Setosphaeria turcica were sequenced at the Joint Genome Institute (JGI). The datasets were used to identify SNPs between strains and species, unique genomic regions, core secondary metabolism genes, and small secreted protein (SSP) candidate effector encoding genes with a view towards pinpointing structural elements and gene content associated with specificity of these closely related fungi to different cereal hosts. Whole-genome alignment shows that three to five percent of each genome differs between strains of the same species, while a quarter of each genome differs between species. On average, SNP counts among field isolates of the same C. heterostrophus species are more than 25× higher than those between inbred lines and 50× lower than SNPs between Cochliobolus species. The suites of nonribosomal peptide synthetase (NRPS), polyketide synthase (PKS), and SSP-encoding genes are astoundingly diverse among species but remarkably conserved among isolates of the same species, whether inbred or field strains, except for defining examples that map to unique genomic regions. Functional analysis of several strain-unique PKSs and NRPSs reveal a strong correlation with a role in virulence

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