bioRxiv preprint doi: https://doi.org/10.1101/2020.06.17.156455; this version posted June 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Multi-level proteomics reveals host-perturbation strategies of SARS-CoV-2 and SARS-CoV Alexey Stukalov1*, Virginie Girault1*, Vincent Grass1*, Valter Bergant1*, Ozge Karayel2*, Christian Urban1*, Darya A. Haas1*, Yiqi Huang1, Lila Oubraham1, Anqi Wang1, Sabri M. Hamad1, Antonio Piras1, Maria Tanzer2, Fynn M. Hansen2, Thomas Enghleitner3, Maria Reinecke4, 5, Teresa M. Lavacca1, Rosina Ehmann6, 7, Roman Wölfel6, 7, Jörg Jores8, Bernhard Kuster4, 5, Ulrike Protzer1, 7, Roland Rad3, John Ziebuhr9, Volker Thiel10, Pietro Scaturro1,11, Matthias Mann2 and Andreas Pichlmair1, 7, § 1Technical University of Munich, School of Medicine, Institute of Virology, 81675 Munich, Germany, 2Department of Proteomics and Signal transduction, Max-Planck Institute of Biochemistry, Martinsried/Munich, 82152, Germany, 3Institute of Molecular Oncology and Functional Genomics and Department of Medicine II, School of Medicine, Technical University of Munich, 81675 Munich, Germany, 4Chair of Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany, 5German Cancer Consortium (DKTK), Munich partner site and German Cancer Research Center, (DKFZ) Heidelberg, Germany, 6Bundeswehr Institute of Microbiology, 80937 Munich, Germany, 7German Center for Infection Research (DZIF), Munich partner site, Germany, 8Institute of Veterinary Bacteriology, Department of Infectious Diseases and Pathobiology, University of Bern, Bern, Switzerland, 9Justus Liebig University Giessen, Institute of Medical Virology, 35392 Giessen, Germany, 10Institute of Virology and Immunology (IVI), Bern, Switzerland & Department of Infectious Diseases and Pathobiology, University of Bern, Bern, Switzerland, 11Systems Arbovirology, Heinrich Pette Institute, Leibniz Institute for Experimental Virology, Hamburg, Germany. * these authors contributed equally §Corresponding author: Andreas Pichlmair, PhD, DVM Technical University Munich, Faculty of Medicine Institute of Virology - Viral Immunopathology Schneckenburger Str. 8 D-81675 Munich, Germany bioRxiv preprint doi: https://doi.org/10.1101/2020.06.17.156455; this version posted June 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Abstract: The sudden global emergence of SARS-CoV-2 urgently requires an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several omics studies have extended our knowledge of COVID-19 pathophysiology, including some focused on proteomic aspects1–3. To understand how SARS-CoV-2 and related coronaviruses manipulate the host we here characterized interactome, proteome and signaling processes in a systems-wide manner. This identified connections between the corresponding cellular events, revealed functional effects of the individual viral proteins and put these findings into the context of host signaling pathways. We investigated the closely related SARS-CoV-2 and SARS-CoV viruses as well as the influence of SARS-CoV-2 on transcriptome, proteome, ubiquitinome and phosphoproteome of a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed relationships between the perturbations taking place upon SARS-CoV-2 infection at different layers and identified unique and common molecular mechanisms of SARS coronaviruses. The results highlight the functionality of individual proteins as well as vulnerability hotspots of SARS-CoV-2, which we targeted with clinically approved drugs. We exemplify this by identification of kinase inhibitors as well as MMPase inhibitors with significant antiviral effects against SARS-CoV-2. Main text: To identify interactions of SARS-CoV-2 and SARS-CoV with cellular proteins, we transduced A549 lung carcinoma cells with lentiviruses expressing individual HA-tagged viral proteins (Figure 1a; Extended data Fig. 1a; Supplementary Table 1). Affinity purification followed by mass spectrometry analysis (AP-MS) and statistical modelling of the MS1-level quantitative data allowed identification of 1484 interactions between 1086 cellular proteins and 24 SARS-CoV-2 and 27 SARS-CoV bait proteins (Figure 1b; Extended data Fig. 1b; Supplementary Table 2). The resulting virus-host interaction network revealed a wide range of cellular activities intercepted by SARS-CoV-2 and SARS-CoV (Figure 1b; Extended data Table 1; Supplementary Table 2). In particular, we discovered bioRxiv preprint doi: https://doi.org/10.1101/2020.06.17.156455; this version posted June 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. that SARS-CoV-2 targets a number of key cellular regulators involved in innate immunity (ORF7b- MAVS, -UNC93B1), stress response components (N-HSPA1A) and DNA damage response mediators (ORF7a-ATM, -ATR) (Figure 1b; Extended data Fig. 1c - e). Overall, SARS-CoV-2 interacts with specific protein complexes contributing to a range of biological processes (Supplementary Table 2). To evaluate the consequences of these interactions on cellular proteostasis, we proceeded with the total proteome analysis of A549 cells expressing the 54 individual viral proteins (Figure 1a, d; Supplementary Table 3). The analysis of the proteome changes induced by each viral protein and consideration of the interactions of this respective protein provided direct insights into their functions. For instance, we confirmed that ORF9b of SARS-CoV-2 leads to a dysregulation of mitochondrial functions (Figure 1d; Supplementary Table 3), as was previously reported for SARS-CoV4, correlating with the binding of ORF9b of both viruses to TOMM70 (Figure 1b; Supplementary Table 2)1, a known regulator of mitophagy5, which was not yet known for SARS-CoV ORF9b. Importantly, this approach identified novel SARS-CoV-2 activities, such as the regulation of proteins involved in cholesterol metabolism by NSP6 (Figure 1d; Supplementary Table 3). Despite the high similarity of SARS-CoV-2 and SARS-CoV6, these datasets allow to discriminate the commonalities and differences of both viruses, which may in part explain the characteristics in pathogenicity and transmission capabilities. By comparing the AP-MS data of homologous SARS-CoV-2 and SARS-CoV proteins, we identified significant differences in the enrichment of individual host targets, highlighting potential virus-specific interactions (Figure 1b (edge color); Figure 1c; Extended data Fig. 1f - h; Supplementary Table 2). For instance, we could recapitulate the known interaction between SARS- CoV NSP2 and prohibitins (PHB, PHB2)7, whereas their enrichment was not observed for NSP2 of SARS-CoV-2 (Extended data Fig. 1g). Alternatively, we found that ORF8 of SARS-CoV-2, but not its SARS-CoV homolog, binds specifically to the TGFB1-LTBP1 complex (Extended data Fig. 1f, h). To obtain information on the concerted activity of the viral proteins during infection, we infected ACE2-expressing A549 cells (Extended data Fig. 2a-b) with SARS-CoV-2, and profiled the impact of viral infection on mRNA transcription, protein abundance, ubiquitination and phosphorylation in a time-resolved manner (Figure 2a – e; Supplementary Tables 4 - 7; Methods). In line with previous reports8,9, we did not observe major upregulation of type-I interferons and related genes at the mRNA bioRxiv preprint doi: https://doi.org/10.1101/2020.06.17.156455; this version posted June 17, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. level (e.g. IFNB, IFIT3, MX1; Extended data Fig. 2c – d; Supplementary Table 4), suggesting active viral inhibition of this system. In contrast, SARS-CoV-2 upregulated NF-κB and stress responses, as inferred from the induction of IL6, CXCL2 and JUNs and transcription factor enrichment analysis (Extended data Fig. 2c – e; Supplementary Tables 4, 8; Methods). At the proteome level, we found 1053 regulated proteins (Figure 2a - b). Most notably, SARS-CoV-2 infection failed to induce an interferon response pattern indicative for an appropriate cellular antiviral response in this dataset (Extended data Fig. 2f; Supplementary Table 5). We complemented these data with global MS analysis of protein ubiquitination, which revealed 884 sites that were differentially regulated after SARS-CoV-2 infection (Figure 2a and c, Extended data Fig. 2f; Supplementary Table 6). A number of proteins displayed both differential abundance and dynamic ubiquitination patterns in an infection- dependent manner (e.g. mediators of caveolar-mediated endocytosis signaling) (Figure 2c; Extended data Fig. 2f; Supplementary Tables 5, 6, 8). Notably, EFNB1, POLR2B, TYMS and DHFR showed concomitant ubiquitination and a decrease at the protein level (Figure 2c; Extended data Fig. 2f; Supplementary Tables 5, 6).