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Proteomics of SARS-CoV-2-infected host cells reveals therapy targets
Open accessPublished version of a preprint
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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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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