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Cryptic pathogen-sugar interactions revealed by universal saturation transfer analysis

Charles J. Buchanan, Ben Gaunt, Peter J. Harrison, Yun Yang, Jiwei Liu, Aziz Khan, Andrew M. Giltrap, Audrey Le Bas, Philip N. Ward, Kapil Gupta, Maud Dumoux, Sergio Daga, Nicola Picchiotti, Margherita Baldassarri, Elisa Benetti, Chiara Fallerini, Francesca Fava, Annarita Giliberti, Panagiotis I. Koukos, Abirami Lakshminarayanan, Xiaochao Xue, Georgios Papadakis, Lachlan P. Deimel, Virgínia Casablancas-Antràs, Timothy D.W. Claridge, Alexandre M.J.J. Bonvin, Quentin J. Sattentau, Simone Furini, Marco Gori, Jiandong Huo, Raymond J. Owens, Christiane Schaffitzel, Imre Berger, Alessandra Renieri, GEN-COVID Multicenter Study, James H. Naismith, Andrew Baldwin, Benjamin G. Davis
doi: https://doi.org/10.1101/2021.04.14.439284
Charles J. Buchanan
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Ben Gaunt
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
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Peter J. Harrison
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
12Diamond Light Source, Harwell Science & Innovation Campus, Oxfordshire, UK
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Yun Yang
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
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Jiwei Liu
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
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Aziz Khan
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Andrew M. Giltrap
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Audrey Le Bas
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
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Philip N. Ward
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
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Kapil Gupta
13Max Planck Bristol Centre for Minimal Biology, University of Bristol, UK
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Maud Dumoux
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
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Sergio Daga
5Medical Genetics, University of Siena, Siena, Italy
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Nicola Picchiotti
8Department of Information Engineering and Mathematics, University of Siena, Italy
9Department of Mathematics, University of Pavia, Pavia, Italy
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Margherita Baldassarri
5Medical Genetics, University of Siena, Siena, Italy
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Elisa Benetti
7Department of Medical Biotechnologies, University of Siena, Siena, Italy
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Chiara Fallerini
5Medical Genetics, University of Siena, Siena, Italy
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Francesca Fava
5Medical Genetics, University of Siena, Siena, Italy
6Azienda Ospedaliera Universitaria Senese, Siena, Italy
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Annarita Giliberti
5Medical Genetics, University of Siena, Siena, Italy
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Panagiotis I. Koukos
11Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Netherlands
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Abirami Lakshminarayanan
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Xiaochao Xue
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
4Sir William Dunn School of Pathology, South Parks Road, Oxford, UK
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Georgios Papadakis
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Lachlan P. Deimel
4Sir William Dunn School of Pathology, South Parks Road, Oxford, UK
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Virgínia Casablancas-Antràs
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Timothy D.W. Claridge
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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Alexandre M.J.J. Bonvin
11Bijvoet Centre for Biomolecular Research, Faculty of Science, Utrecht University, Netherlands
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Quentin J. Sattentau
4Sir William Dunn School of Pathology, South Parks Road, Oxford, UK
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Simone Furini
7Department of Medical Biotechnologies, University of Siena, Siena, Italy
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Marco Gori
8Department of Information Engineering and Mathematics, University of Siena, Italy
10Maasai, I3S CNRS, Université Côte d’Azur, France
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Jiandong Huo
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
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Raymond J. Owens
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
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Christiane Schaffitzel
13Max Planck Bristol Centre for Minimal Biology, University of Bristol, UK
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Imre Berger
13Max Planck Bristol Centre for Minimal Biology, University of Bristol, UK
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Alessandra Renieri
5Medical Genetics, University of Siena, Siena, Italy
6Azienda Ospedaliera Universitaria Senese, Siena, Italy
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James H. Naismith
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
3Division of Structural Biology, University of Oxford, The Wellcome Centre for Human Genetics, Headington, Oxford, OX3 7BN, UK
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  • For correspondence: naismith@strubi.ox.ac.uk andrew.baldwin@chem.ox.ac.uk ben.davis@chem.ox.ac.uk
Andrew Baldwin
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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  • For correspondence: naismith@strubi.ox.ac.uk andrew.baldwin@chem.ox.ac.uk ben.davis@chem.ox.ac.uk
Benjamin G. Davis
1The Rosalind Franklin Institute, Harwell Science & Innovation Campus, OX11 0FA, UK
2Department of Chemistry, University of Oxford, Oxford, OX1 3TA
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  • For correspondence: naismith@strubi.ox.ac.uk andrew.baldwin@chem.ox.ac.uk ben.davis@chem.ox.ac.uk
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Abstract

Many host pathogen interactions such as human viruses (including non-SARS-coronaviruses) rely on attachment to host cell-surface glycans. There are conflicting reports about whether the Spike protein of SARS-CoV-2 binds to sialic acid commonly found on host cell-surface N-linked glycans. In the absence of a biochemical assay, the ability to analyze the binding of glycans to heavily- modified proteins and resolve this issue is limited. Classical Saturation Transfer Difference (STD) NMR can be confounded by overlapping sugar resonances that compound with known experimental constraints. Here we present ‘universal saturation transfer analysis’ (uSTA), an NMR method that builds on existing approaches to provide a general and automated workflow for studying protein-ligand interactions. uSTA reveals that B-origin-lineage-SARS-CoV-2 spike trimer binds sialoside sugars in an ‘end on’ manner and modelling guided by uSTA localises binding to the spike N-terminal domain (NTD). The sialylated-polylactosamine motif is found on tetraantennary human N-linked-glycoproteins in deeper lung and may have played a role in zoonosis. Provocatively, sialic acid binding is abolished by mutations in some subsequent SARS- CoV-2 variants-of-concern. A very high resolution cryo-EM structure confirms the NTD location and ‘end on’ mode; it rationalises the effect of NTD mutations and the structure-activity relationship of sialic acid analogues. uSTA is demonstrated to be a robust, rapid and quantitative tool for analysis of binding, even in the most demanding systems.

Extended Abstract The surface proteins found on both pathogens and host cells mediate entry (and exit) and influence disease progression and transmission. Both types can bear host-generated post- translational modifications such as glycosylation that are essential for function but can confound biophysical methods used for dissecting key interactions. Several human viruses (including non- SARS-coronaviruses) attach to host cell-surface N-linked glycans that include forms of sialic acid (sialosides). There remains, however, conflicting evidence as to if or how SARS-associated coronaviruses might use such a mechanism. Here, we demonstrate quantitative extension of ‘saturation transfer’ protein NMR methods to a complete mathematical model of the magnetization transfer caused by interactions between protein and ligand. The method couples objective resonance-identification via a deconvolution algorithm with Bloch-McConnell analysis to enable a structural, kinetic and thermodynamic analysis of ligand binding beyond previously-perceived limits of exchange rates, concentration or system. Using an automated and openly available workflow this ‘universal saturation transfer’ analysis (uSTA) can be readily-applied in a range of even heavily-modified systems in a general manner to now obtain quantitative binding interaction parameters (KD, kEx). uSTA proved critical in mapping direct interactions between natural sialoside sugar ligands and relevant virus-surface attachment glycoproteins – SARS-CoV-2-spike and influenza-H1N1-haemagglutinin variants – by quantitating ligand signal in spectral regions otherwise occluded by resonances from mobile protein glycans (that also include sialosides). In B- origin-lineage-SARS-CoV-2 spike trimer ‘end on’-binding to sialoside sugars was revealed contrasting with ‘extended surface’-binding for heparin sugar ligands; uSTA-derived constraints used in structural modelling suggested sialoside-glycan binding sites in a beta-sheet-rich region of spike N-terminal domain (NTD). Consistent with this, uSTA-glycan binding was minimally- perturbed by antibodies that neutralize the ACE2-binding domain (RBD) but strongly disrupted in spike from the B1.1.7/alpha and B1.351/beta variants-of-concern, which possess hotspot mutations in the NTD. Sialoside binding in B-origin-lineage-NTD was unequivocally pinpointed by cryo-EM to a site that is created from residues that are notably deleted in variants (e.g. H69,V70,Y145 in alpha). An analysis of beneficial genetic variances in cohorts of patients from early 2020 suggests a model in which this site in the NTD of B-origin-lineage-SARS-CoV-2 (but not in alpha/beta-variants) may have exploited a specific sialylated-polylactosamine motif found on tetraantennary human N-linked-glycoproteins in deeper lung. Together these confirm a novel binding mode mediated by the unusual NTD of SARS-CoV-2 and suggest how it may drive virulence and/or zoonosis via modulation of glycan attachment. Since cell-surface glycans are widely relevant to biology and pathology, uSTA can now provide ready, quantitative, widespread analysis of complex, host-derived and post-translationally modified proteins with putative ligands relevant to disease even in previously confounding complex systems.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • ↵ψ These authors contributed equally.

  • Additional pertinent results now added to the manuscript.

  • https://ora.ox.ac.uk/objects/uuid:121699de-68d5-4b6f-b77e-cee85895da6c

  • https://doi.org/10.5281/zenodo.4271288

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Cryptic pathogen-sugar interactions revealed by universal saturation transfer analysis
Charles J. Buchanan, Ben Gaunt, Peter J. Harrison, Yun Yang, Jiwei Liu, Aziz Khan, Andrew M. Giltrap, Audrey Le Bas, Philip N. Ward, Kapil Gupta, Maud Dumoux, Sergio Daga, Nicola Picchiotti, Margherita Baldassarri, Elisa Benetti, Chiara Fallerini, Francesca Fava, Annarita Giliberti, Panagiotis I. Koukos, Abirami Lakshminarayanan, Xiaochao Xue, Georgios Papadakis, Lachlan P. Deimel, Virgínia Casablancas-Antràs, Timothy D.W. Claridge, Alexandre M.J.J. Bonvin, Quentin J. Sattentau, Simone Furini, Marco Gori, Jiandong Huo, Raymond J. Owens, Christiane Schaffitzel, Imre Berger, Alessandra Renieri, GEN-COVID Multicenter Study, James H. Naismith, Andrew Baldwin, Benjamin G. Davis
bioRxiv 2021.04.14.439284; doi: https://doi.org/10.1101/2021.04.14.439284
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Cryptic pathogen-sugar interactions revealed by universal saturation transfer analysis
Charles J. Buchanan, Ben Gaunt, Peter J. Harrison, Yun Yang, Jiwei Liu, Aziz Khan, Andrew M. Giltrap, Audrey Le Bas, Philip N. Ward, Kapil Gupta, Maud Dumoux, Sergio Daga, Nicola Picchiotti, Margherita Baldassarri, Elisa Benetti, Chiara Fallerini, Francesca Fava, Annarita Giliberti, Panagiotis I. Koukos, Abirami Lakshminarayanan, Xiaochao Xue, Georgios Papadakis, Lachlan P. Deimel, Virgínia Casablancas-Antràs, Timothy D.W. Claridge, Alexandre M.J.J. Bonvin, Quentin J. Sattentau, Simone Furini, Marco Gori, Jiandong Huo, Raymond J. Owens, Christiane Schaffitzel, Imre Berger, Alessandra Renieri, GEN-COVID Multicenter Study, James H. Naismith, Andrew Baldwin, Benjamin G. Davis
bioRxiv 2021.04.14.439284; doi: https://doi.org/10.1101/2021.04.14.439284

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