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Pathogen-sugar interactions revealed by universal saturation transfer analysis

Authors: Buchanan, Charles; Gaunt, Ben; Harrison, Peter; Yang, Yun; Liu, Jiwei; Khan, Aziz; Giltrap, Andrew; +30 Authors

Pathogen-sugar interactions revealed by universal saturation transfer analysis

Abstract

Upgrades of 600 MHz and 950 MHz spectrometers were funded by the Wellcome Trust (Grant Ref: 095872/Z/10/Z) and the Engineering and Physical Sciences Research Council (Grant Ref: EP/R029849/1), respectively, and by the University of Oxford Institutional Strategic Support Fund, the John Fell Fund, and the Edward Penley Abraham Cephalosporin Fund. We thank the Wellcome Trust for support (20289/Z/16/Z and 100209/Z/12/Z). IB is an Investigator of the Wellcome Trust (106115/Z/14/Z). EM time was funded by a philanthropic gift to support COVID-19 research at the University of Oxford. The Chemistry theme at the Rosalind Franklin Institute is supported by the EPSRC (V011359/1 (P)). AMJJB and PIK acknowledge financial support from the European Union Horizon 2020 projects BioExcel (823830) and EOSC-Hub (777536) and the IMICARE project (101005077). This study is part of the GEN-COVID Multicenter Study (https://sites.google.com/dbm.unisi.it/gen-covid), the Italian multicenter study aimed at identifying the COVID-19 host genetic bases. Specimens were provided by the COVID-19 Biobank of Siena, which is part of the Genetic Biobank of Siena, member of BBMRI-IT, of Telethon Network of Genetic Biobanks (project No. GTB18001), of EuroBioBank, and of RDConnect. We thank the CINECA consortium for providing computational resources and the Network for Italian Genomes (NIG; http://www.nig.cineca.it) for its support. We thank private donors for the support provided to AR (Department of Medical Biotechnologies, University of Siena) for the COVID-19 host genetics research project (D.L n.18 of March 17, 2020). We also thank the COVID-19 Host Genetics Initiative (https://www.covid19hg.org/), MIUR project "Dipartimenti di Eccellenza 2018���2020" to the Department of Medical Biotechnologies University of Siena, Italy, and "Bando Ricerca COVID-19 Toscana'' project to Azienda Ospedaliero-Universitaria Senese. We thank Intesa San Paolo for the 2020 charity fund dedicated to the project N.B/2020/0119 "Identificazione delle basi genetiche determinanti la variabilit�� clinica della risposta a COVID-19 nella popolazione italiana and the Tuscany Region for funding within "Bando Ricerca COVID-19 Toscana'' project supporting research at the Azienda Ospedaliero-Universitaria Senese. The Italian Ministry of University and Research for funding within the "Bando FISR 2020" in COVID-19 fo the project "Editing dell'RNA contro il Sars-CoV-2: hackerare il virus per identificare bersagli molecolari e attenuare l'infezione - 33 HACKTHECOV) and the Istituto Buddista Italiano Soka Gakkai for funding the project "PATCOVID: Host genetics and pathogenetic mechanisms of COVID-19" (ID n. 2020-2016_RIC_3). We thank EU project H2020-SC1-FA-DTS-2018-2020, entitled "International consortium for integrative genomics prediction (INTERVENE)" - Grant Agreement No. 101016775. We would like to thank Professor Xi Chen at the University of California at Davis for providing the plasmid encoding Pd2,6ST; Professor John Mascola at the NIH for the plasmids encoding influenza A virus (IAV) NC99 (H1N1) haemagglutinin (HA) variants; Dr Piyada Supasa and Professor Gavin Screaton at the University of Oxford for templates for alpha and beta spike; Mikhail Kutuzov and Omer Dushek for useful discussions and assistance with SPR experiments; Dr Andrew Quigley and Nadisha Gamage (Wellcome Trust Membrane Protein Lab, Diamond Light Source (20289/Z16/Z)) for help with thermal stability assays; Professor Christina Redfield for assistance with high field Bruker instrumentation; Dr Lindsay Baker for insights into the structural models.

Supporting data for the "Pathogen-sugar interactions revealed by universal saturation transfer analysis" manuscript.

Keywords

NMR

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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