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Proteomics of SARS-CoV-2-infected host cells reveals therapy targets
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Abstract
A new coronavirus was recently discovered and named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infection with SARS-CoV-2 in humans causes coronavirus disease 2019 (COVID-19) and has been rapidly spreading around the globe 1,2. SARS-CoV-2 shows some similarities to other coronaviruses; however, treatment options and an understanding of how SARS-CoV-2 infects cells are lacking. Here we identify the host cell pathways that are modulated by SARS-CoV-2 and show that inhibition of these pathways prevents viral replication in human cells. We established a human cell-culture model for infection with a clinical isolate of SARS-CoV-2. Using this cell-culture system, we determined the infection profile of SARS-CoV-2 by translatome 3 and proteome proteomics at different times after infection. These analyses revealed that SARS-CoV-2 reshapes central cellular pathways such as translation, splicing, carbon metabolism, protein homeostasis (proteostasis) and nucleic acid metabolism. Small-molecule inhibitors that target these pathways prevented viral replication in cells. Our results reveal the cellular infection profile of SARS-CoV-2 and have enabled the identification of drugs that inhibit viral replication. We anticipate that our results will guide efforts to understand the molecular mechanisms that underlie the modulation of host cells after infection with SARS-CoV-2. Furthermore, our findings provide insights for the development of therapies for the treatment of COVID-19.
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“Clinical isolate infection models have been developed using Caco-2 cells154 with temporal proteome changes identified during infection using multiplexed MS by combining metabolic labelling with tandem mass tagging methods.”
From A high-stringency blueprint of the human proteome (2020) · cites this paper as [154]
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“Building on this knowledge of coronavirus infection, recent proteomics studies have focused on SARS-CoV-2, uncovering additional potential therapeutic targets154,155.”
From A high-stringency blueprint of the human proteome (2020) · cites this paper as [154]
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Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
Martínez González, M. (2020) · DSPACE System - Metalibrary (University of the Coast) · Cited by 18,463
Data Structures for Statistical Computing in Python
McKinney, W. (2010) · Proceedings of the Python in Science Conferences · doi:10.25080/majora-92bf1922-00a · Cited by 12,930
The NumPy Array: A Structure for Efficient Numerical Computation
van der Walt, S., Colbert, S. C., & Varoquaux, G. (2011) · Computing in Science & Engineering · doi:10.1109/mcse.2011.37 · Cited by 9,381
The Perseus computational platform for comprehensive analysis of (prote)omics data
Tyanova, S., Temu, T., Sinitcyn, P., Carlson, A., Hein, M. Y., Geiger, T., Mann, M., & Cox, J. (2016) · Nature Methods · doi:10.1038/nmeth.3901 · Cited by 8,803
Chan, J., Yuan, S.-F., Kok, K.-H., To, K., Chu, H., Yang, J., Xing, F., Liu, J.-L., Yip, C., Poon, R., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30154-9 · Cited by 8,450
A scaling normalization method for differential expression analysis of RNA-seq data
Robinson, M. D., & Oshlack, A. (2010) · Genome Biology · doi:10.1186/gb-2010-11-3-r25 · Cited by 7,876
Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR
Corman, V. M., Landt, O., Kaiser, M., Molenkamp, R., Meijer, A., Chu, D. K. W., Bleicker, T., Brünink, S., Schneider, J. A., Schmidt, M. L., et al. (2020) · Eurosurveillance · doi:10.2807/1560-7917.es.2020.25.3.2000045 · Cited by 7,266
Wang, M., Cao, R., Zhang, L., Yang, X., Liu, J., Xu, M., Shi, Z., Hú, Z., Zhong, W., & Xiao, G. (2020) · Cell Research · doi:10.1038/s41422-020-0282-0 · Cited by 6,994
Pérez-Riverol, Y., Csordas, A., Bai, J.-W., Bernal-Llinares, M., Hewapathirana, S., Kundu, D. J., Inuganti, A., Griss, J., Mayer, G., Eisenacher, M., et al. (2018) · Nucleic Acids Res. · doi:10.1093/nar/gky1106 · Cited by 6,216
Maere, S., Heymans, K., & Kuiper, M. T. R. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti551 · Cited by 4,163
Evidence for gastrointestinal infection of SARS-CoV-2
Xiao, F., Tang, M., Zheng, X., Liu, Y., Li, X., & Shan, H. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.02.055 · Cited by 2,836
Jin, Y., Cai, L., Cheng, Z., Cheng, H., Deng, T., Fan, Y., Fang, C., Huang, D., Huang, L., Huang, Q., et al. (2020) · Military Medical Research · doi:10.1186/s40779-020-0233-6 · Cited by 2,306
Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation
Merico, D., Isserlin, R., Stueker, O., Emili, A., & Bader, G. D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013984 · Cited by 2,235
Epidemiologic Features and Clinical Course of Patients Infected With SARS-CoV-2 in Singapore
Young, B. E., Ong, S. W. X., Kalimuddin, S., Low, J. G. H., Tan, S. Y., Loh, J., Ng, O. T., Marimuthu, K., Ang, L. W., Mak, T. M., et al. (2020) · JAMA · doi:10.1001/jama.2020.3204 · Cited by 2,090
Zhao, S., Lin, Q., Ran, J., Musa, S. S., Yang, G., Wang, W., Lou, Y., Gao, D., Yang, L., He, D., et al. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.01.050 · Cited by 1,852
Glycyrrhizin, an active component of liquorice roots, and replication of SARS-associated coronavirus
Cinátl, J., Morgenstern, B., Bauer, G., Chandra, P., Rabenau, H. F., & Hw, D. (2003) · The Lancet · doi:10.1016/s0140-6736(03)13615-x · Cited by 1,175
Evidence of SARS-CoV-2 Infection in Returning Travelers from Wuhan, China
Hoehl, S., Rabenau, H. F., Berger, A., Kortenbusch, M., Cinatl, J. J., Bojková, D., Behrens, P., Böddinghaus, B., Götsch, U., Naujoks, F., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2001899 · Cited by 578
Self-citationTreatment of SARS with human interferons
Cinátl, J., Morgenstern, B., Bauer, G., Chandra, P., Rabenau, H. F., & Doerr, H. W. (2003) · The Lancet · doi:10.1016/s0140-6736(03)13973-6 · Cited by 472
2019 novel coronavirus of pneumonia in Wuhan, China: emerging attack and management strategies
She, J., Jiang, J., Ye, L., Hu, L., Bai, C., & Song, Y. (2020) · Clinical and Translational Medicine · doi:10.1186/s40169-020-00271-z · Cited by 427
Narayanan, K., Huang, C., Lokugamage, K. G., Kamitani, W., Ikegami, T., Tseng, C.-T. K., & Makino, S. (2008) · Journal of Virology · doi:10.1128/jvi.02472-07 · Cited by 421
A two-pronged strategy to suppress host protein synthesis by SARS coronavirus Nsp1 protein
Kamitani, W., Huang, C., Narayanan, K., Lokugamage, K. G., & Makino, S. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1680 · Cited by 410
Recent discovery and development of inhibitors targeting coronaviruses
Pillaiyar, T., Meenakshisundaram, S., & Manickam, M. (2020) · Drug Discovery Today · doi:10.1016/j.drudis.2020.01.015 · Cited by 370
Plubell, D. L., Wilmarth, P. A., Zhao, Y., Fenton, A. M., Minnier, J., Reddy, A. P., Klimek, J. E., Yang, X., David, L. L., & Pamir, N. (2017) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m116.065524 · Cited by 338
Ectodomain shedding of angiotensin converting enzyme 2 in human airway epithelia
Jia, H. P., Look, D. C., Tan, P., Shi, L., Hickey, M. A., Gakhar, L., Chappell, M. C., Wohlford-Lenane, C., & McCray, P. B. (2009) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00071.2009 · Cited by 334
High-throughput screening and identification of potent broad-spectrum inhibitors of coronaviruses.
Shen, L., Niu, J., Wang, C., Huang, B., Wang, W., Zhu, N., Deng, Y., Wang, H., Ye, F., Cen, S., et al. (2019) · Journal of Virology · doi:10.1128/jvi.00023-19 · Cited by 319
Tang, B., Wang, X., Li, Q., Bragazzi, N. L., Tang, S., Xiao, Y., & Wu, J. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3525558 · Cited by 294
Pinkus, G. S., & SAID, J. W. (1977) · PubMed Central · Cited by 288
Yan, B., Chu, H., Yang, D., Sze, K. H., Lai, P.-M., Yuan, S., Shuai, H., Wang, Y., Kao, R. Y. T., Chan, J. F., et al. (2019) · Viruses · doi:10.3390/v11010073 · Cited by 267
Nucleoside analogues for the treatment of coronavirus infections
Pruijssers, A. J., & Denison, M. R. (2019) · Current Opinion in Virology · doi:10.1016/j.coviro.2019.04.002 · Cited by 196
Proteomics Analysis Unravels the Functional Repertoire of Coronavirus Nonstructural Protein 3
Neuman, B. W., Joseph, J. S., Saikatendu, K. S., Serrano, P., Chatterjee, A., Johnson, M. A., Liao, L., Klaus, J. P., Yates, J. R., Wüthrich, K., et al. (2008) · Journal of Virology · doi:10.1128/jvi.02631-07 · Cited by 192
A Mighty “Protein Extractor” of the Cell: Structure and Function of the p97/CDC48 ATPase
Ye, Y., Tang, W. K., Zhang, T., & Xia, D. (2017) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2017.00039 · Cited by 189
Whole-exome sequencing for finding de novo mutations in sporadic mental retardation
Robinson, P. (2010) · Genome Biology · doi:10.1186/gb-2010-11-12-144 · Cited by 180
Structural basis of splicing modulation by antitumor macrolide compounds
Cretu, C., Agrawal, A. A., Cook, A., Will, C. L., Fekkes, P., Smith, P. G., Lührmann, R., Larsen, N., Buonamici, S., & Pena, V. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.03.011 · Cited by 174
Functional Interaction Network Construction and Analysis for Disease Discovery
Wu, G., & Haw, R. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6783-4_11 · Cited by 155
Rhinovirus induces an anabolic reprogramming in host cell metabolism essential for viral replication
Gualdoni, G. A., Mayer, K. A., Kapsch, A., Kreuzberg, K., Puck, A., Kienzl, P., Oberndorfer, F., Frühwirth, K., Winkler, S., Blaas, D., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1800525115 · Cited by 154
Tippett, P. S., & Neet, K. (1982) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(18)33591-9 · Cited by 141
Marcelin, J. R., Wilson, J. W., & Razonable, R. R. (2014) · Transplant Infectious Disease · doi:10.1111/tid.12194 · Cited by 101
Klann, K., Tascher, G., & Münch, C. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.11.010 · Cited by 98
Self-citationEmmott, E., Munday, D., Bickerton, E., Britton, P., Rodgers, M. A., Whitehouse, A., Zhou, E.-M., & Hiscox, J. A. (2013) · Journal of Virology · doi:10.1128/jvi.00321-13 · Cited by 93
Ribavirin in the treatment of chronic hepatitis C
Martin, P. B., & Jensen, D. M. (2008) · Journal of Gastroenterology and Hepatology · doi:10.1111/j.1440-1746.2008.05398.x · Cited by 88
SAIJO, M., MORIKAWA, S., FUKUSHI, S., MIZUTANI, T., HASEGAWA, H., NAGATA, N., IWATA, N., & KURANE, I. (2005) · Antiviral Research · doi:10.1016/j.antiviral.2005.01.003 · Cited by 82
Wong, H. H., Kumar, P., Tay, F. P., Moreau, D., Liu, D. X., & Bard, F. (2015) · Journal of Virology · doi:10.1128/jvi.01360-15 · Cited by 75
Chen, J.-Y., Chen, W.-N., Poon, V. K., Zheng, B.-J., Lin, X., Wang, Y.-X., & Wen, Y. (2009) · Archives of Virology · doi:10.1007/s00705-009-0323-y · Cited by 57
Song, T., Fang, L., Wang, D., Zhang, R., Zeng, S., An, K., Chen, H., & Xiao, S. (2016) · Journal of Proteomics · doi:10.1016/j.jprot.2016.05.009 · Cited by 55
Jourdan, S. S., Osorio, F. A., & Hiscox, J. A. (2012) · PROTEOMICS · doi:10.1002/pmic.201100469 · Cited by 42
Wu, L. S., Rower, J. E., Burton, J. R., Anderson, P. L., Hammond, K. P., Baouchi‐Mokrane, F., Everson, G. T., Urban, T. J., D’Argenio, D. Z., & Kiser, J. J. (2015) · Antimicrobial Agents and Chemotherapy · doi:10.1128/aac.04618-14 · Cited by 33
Zhang, J., Hu, Y., Hau, R. K., Musharrafieh, R. G., Ma, C., Zhou, X., Chen, Y., & Wang, J. (2019) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2019.03.020 · Cited by 28
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Metadata
- Authors
- Bojkova, D., Klann, K., Koch, B., Widera, M., Krause, D., Ciesek, S., Cinatl, J., & Münch, C.
- Affiliations
- Goethe University Frankfurt (DE)
- University Hospital Frankfurt (DE)
- Corresponding author
- Cinatl, Jindrich
- Münch, Christian
- ORCID
- Venue
- Nature
- Published
- 2020-05-14
- Volume
- 583
- Issue
- 7816
- Pages
- 469-472
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7616921
- OpenAlex
- W3026002191
- Cited by
- 1,010
- References
- 53
- Citations by year
- 2026: 25 · 2025: 58 · 2024: 86 · 2023: 118 · 2022: 198 · 2021: 347 · 2020: 177
- FWCI
- 27.46
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- Research Square (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) (submittedVersion)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, cc-by)
- Funders
- Frankfurter Stiftung für krebskranke Kinder
- Hilfe für krebskranke Kinder Frankfurt
- European Commission
- Deutsche Forschungsgemeinschaft (ERC StG 803565, MU 4216/1-1, CRC 1177)
- Aventis Foundation
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- SARS-CoV-2, COVID-19 pandemic, viral replication, host-pathogen interaction, translation (biology), splicing, carbon metabolism, proteostasis, nucleic acid metabolism, small molecule inhibitors, antiviral drug targets, proteome, translatome
- MeSH terms
- Betacoronavirus, Proteostasis, COVID-19, SARS-CoV-2, COVID-19 Drug Treatment, Carbon, Drug Evaluation, Preclinical, Humans, Kinetics, Pneumonia, Viral, RNA Splicing, Time Factors, Protein Biosynthesis, Virus Replication, Coronavirus Infections, Caco-2 Cells, Proteome, Proteomics, Host-Pathogen Interactions, Pandemics, Molecular Targeted Therapy, In Vitro Techniques
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