Dataset Information

Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications.

ABSTRACT: The highly infectious disease COVID-19 caused by the Betacoronavirus SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international COVID19-NMR consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in COVID19-NMR and the resources provided through the consortium are fully disclosed to accelerate access and exploitation. NMR investigations of the viral molecular components are designated to provide the essential basis for further work, including macromolecular interaction studies and high-throughput drug screening. Here, we present the extensive catalog of a holistic SARS-CoV-2 protein preparation approach based on the consortium's collective efforts. We provide protocols for the large-scale production of more than 80% of all SARS-CoV-2 proteins or essential parts of them. Several of the proteins were produced in more than one laboratory, demonstrating the high interoperability between NMR groups worldwide. For the majority of proteins, we can produce isotope-labeled samples of HSQC-grade. Together with several NMR chemical shift assignments made publicly available on covid19-nmr.com, we here provide highly valuable resources for the production of SARS-CoV-2 proteins in isotope-labeled form.

SUBMITTER: Altincekic N

PROVIDER: S-EPMC8141814 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications.

Altincekic Nadide N Korn Sophie Marianne SM Qureshi Nusrat Shahin NS Dujardin Marie M Ninot-Pedrosa Martí M Abele Rupert R Abi Saad Marie Jose MJ Alfano Caterina C Almeida Fabio C L FCL Alshamleh Islam I de Amorim Gisele Cardoso GC Anderson Thomas K TK Anobom Cristiane D CD Anorma Chelsea C Bains Jasleen Kaur JK Bax Adriaan A Blackledge Martin M Blechar Julius J Böckmann Anja A Brigandat Louis L Bula Anna A Bütikofer Matthias M Camacho-Zarco Aldo R AR Carlomagno Teresa T Caruso Icaro Putinhon IP Ceylan Betül B Chaikuad Apirat A Chu Feixia F Cole Laura L Crosby Marquise G MG de Jesus Vanessa V Dhamotharan Karthikeyan K Felli Isabella C IC Ferner Jan J Fleischmann Yanick Y Fogeron Marie-Laure ML Fourkiotis Nikolaos K NK Fuks Christin C Fürtig Boris B Gallo Angelo A Gande Santosh L SL Gerez Juan Atilio JA Ghosh Dhiman D Gomes-Neto Francisco F Gorbatyuk Oksana O Guseva Serafima S Hacker Carolin C Häfner Sabine S Hao Bing B Hargittay Bruno B Henzler-Wildman K K Hoch Jeffrey C JC Hohmann Katharina F KF Hutchison Marie T MT Jaudzems Kristaps K Jović Katarina K Kaderli Janina J Kalniņš Gints G Kaņepe Iveta I Kirchdoerfer Robert N RN Kirkpatrick John J Knapp Stefan S Krishnathas Robin R Kutz Felicitas F Zur Lage Susanne S Lambertz Roderick R Lang Andras A Laurents Douglas D Lecoq Lauriane L Linhard Verena V Löhr Frank F Malki Anas A Bessa Luiza Mamigonian LM Martin Rachel W RW Matzel Tobias T Maurin Damien D McNutt Seth W SW Mebus-Antunes Nathane Cunha NC Meier Beat H BH Meiser Nathalie N Mompeán Miguel M Monaca Elisa E Montserret Roland R Mariño Perez Laura L Moser Celine C Muhle-Goll Claudia C Neves-Martins Thais Cristtina TC Ni Xiamonin X Norton-Baker Brenna B Pierattelli Roberta R Pontoriero Letizia L Pustovalova Yulia Y Ohlenschläger Oliver O Orts Julien J Da Poian Andrea T AT Pyper Dennis J DJ Richter Christian C Riek Roland R Rienstra Chad M CM Robertson Angus A Pinheiro Anderson S AS Sabbatella Raffaele R Salvi Nicola N Saxena Krishna K Schulte Linda L Schiavina Marco M Schwalbe Harald H Silber Mara M Almeida Marcius da Silva MDS Sprague-Piercy Marc A MA Spyroulias Georgios A GA Sreeramulu Sridhar S Tants Jan-Niklas JN Tārs Kaspars K Torres Felix F Töws Sabrina S Treviño Miguel Á MÁ Trucks Sven S Tsika Aikaterini C AC Varga Krisztina K Wang Ying Y Weber Marco E ME Weigand Julia E JE Wiedemann Christoph C Wirmer-Bartoschek Julia J Wirtz Martin Maria Alexandra MA Zehnder Johannes J Hengesbach Martin M Schlundt Andreas A

Frontiers in molecular biosciences 20210510

The highly infectious disease COVID-19 caused by the <i>Betacoronavirus</i> SARS-CoV-2 poses a severe threat to humanity and demands the redirection of scientific efforts and criteria to organized research projects. The international <i>COVID19-NMR</i> consortium seeks to provide such new approaches by gathering scientific expertise worldwide. In particular, making available viral proteins and RNAs will pave the way to understanding the SARS-CoV-2 molecular components in detail. The research in ...[more]

PMID: 34041264

Similar Datasets

Project description:BackgroundThe success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology.ResultsHere, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/).ConclusionsTranslating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

Dataset Information

Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications.

Publications

Large-Scale Recombinant Production of the SARS-CoV-2 Proteome for High-Throughput and Structural Biology Applications.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets