1
Multilevel proteomics reveals host perturbations by SARS-CoV-2 and
SARS-CoV
Alexey Stukalov
1
*, Virginie Girault
1
*, Vincent Grass
1
*, Ozge Karayel
2
*, Valter Bergant
1
*,
Christian Urban
1
*, Darya A. Haas
1
*, Yiqi Huang
1
*, Lila Oubraham
1
, Anqi Wang
1
, M. Sabri
Hamad
1
, Antonio Piras
1
, Fynn M. Hansen
2
, Maria C. Tanzer
2
, Igor Paron
2
, Luca Zinzula
3
,
Thomas Enghleitner
4
, Maria Reinecke
5, 6
, Teresa M. Lavacca
1
, Rosina Ehmann
7, 8
, Roman
Wölfel
7, 8
, Jörg Jores
9
, Bernhard Kuster
5, 6
, Ulrike Protzer
1, 8
, Roland Rad
4
, John Ziebuhr
10
,
Volker Thiel
11
, Pietro Scaturro
1,12
, Matthias Mann
2
and Andreas Pichlmair
1, 8, §
1
Technical University of Munich, School of Medicine, Institute of Virology, 81675 Munich,
Germany,
2
Department of Proteomics and Signal transduction, Max-Planck Institute of
Biochemistry, Martinsried/Munich, 82152, Germany,
3
Department of Molecular Structural
Biology, Max-Planck Institute of Biochemistry, Martinsried/Munich, 82152, Germany,
4
Institute of Molecular Oncology and Functional Genomics and Department of Medicine II,
School of Medicine, Technical University of Munich, 81675 Munich, Germany,
5
Chair of
Proteomics and Bioanalytics, Technical University of Munich, 85354 Freising, Germany,
6
German Cancer Consortium (DKTK), Munich partner site and German Cancer Research
Center, (DKFZ) Heidelberg, Germany,
7
Bundeswehr Institute of Microbiology, 80937
Munich, Germany,
8
German Center for Infection Research (DZIF), Munich partner site,
Germany,
9
Institute of Veterinary Bacteriology, Department of Infectious Diseases and
Pathobiology, University of Bern, Bern, Switzerland,
10
Justus Liebig University Giessen,
Institute of Medical Virology, 35392 Giessen, Germany,
11
Institute of Virology and
Immunology (IVI), Bern, Switzerland & Department of Infectious Diseases and
Pathobiology, University of Bern, Bern, Switzerland,
12
Systems 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
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2
Summary:
The 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 individual omics studies have extended our knowledge of COVID-19
pathophysiology
1–10
. Integration of such datasets to obtain a holistic view of virus-host
interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the
heterogeneity of the experimental systems. We therefore conducted a concurrent multi-
omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we
profiled the interactome of both viruses, as well as their influence on transcriptome,
proteome, ubiquitinome and phosphoproteome in a lung-derived human cell line.
Projecting these data onto the global network of cellular interactions revealed crosstalk
between the perturbations taking place upon SARS-CoV-2 and SARS-CoV infections
at different layers and identified unique and common molecular mechanisms of these
closely related coronaviruses. The TGF-
β
pathway, known for its involvement in tissue
fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy by SARS-
CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org
)
highlights many hotspots that can be targeted by existing drugs and it can guide
rational design of virus- and host-directed therapies, which we exemplify by identifying
kinase and MMPs inhibitors with potent antiviral effects against SARS-CoV-2.
Main text:
Comparative SARS-CoV-2 and SARS-CoV virus-host interactome and effectome
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
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viral proteins (Figure 1a; Extended data Fig. 1a; Supplementary Table 1). Affinity
purification followed by mass spectrometry (AP-MS) analysis and statistical modelling of
the quantitative data identified 1
801 interactions between 1
086 cellular proteins and 24
SARS-CoV-2 and 27 SARS-CoV bait proteins (Figure 1b; Extended data Fig. 1b;
Supplementary Table 2), significantly expanding the currently reported interactions of
SARS-CoV-2 and SARS-CoV (Supplementary Table 10)
1–11
. 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 that SARS-CoV-2 targets a number of key innate immunity regulators
(ORF7b–MAVS, –UNC93B1), stress response components (N–HSPA1A) and DNA damage
response mediators (ORF7a–ATM, –ATR) (Figure 1b; Extended data Fig. 1c-e).
Additionally, SARS-CoV-2 proteins interact with molecular complexes involved in
intracellular trafficking (e.g. ER Golgi trafficking) and transport (e.g. Solute carriers, Ion
transport by ATPases) as well as cellular metabolism (e.g. Mitochondrial respiratory chain,
Glycolysis) (Figure 1b, Extended data Table 1, Supplementary Table 2). Comparing the AP-
MS data of homologous SARS-CoV-2 and SARS-CoV proteins identified differences in the
enrichment of individual host targets, highlighting potential virus-specific interactions
(Figure 1b (edge color); Figure 1c; Extended data Fig. 1f, 2a-b; Supplementary Table 2). For
instance, we recapitulated the known interaction between SARS-CoV NSP2 and prohibitins
(PHB, PHB2)
12
but this was not conserved in SARS-CoV-2 NSP2, suggesting that the two
viruses differ in their ability to modulate mitochondrial function and homeostasis through
NSP2 (Extended data Fig. 2a). The exclusive interaction of SARS-CoV-2 ORF8 with the
TGFB1-LTBP1 complex is another interaction potentially explaining the differences in
pathogenicity of the two viruses (Extended data Fig. 1f, 2b). Notably, disbalanced TGF-
β
signaling has been linked to lung fibrosis and oedema, a common complication of severe
pulmonary diseases including COVID-19
13–16
.
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(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
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To map the virus-host interactions to the functions of viral proteins, we have conducted an
unprecedented study of total proteomes of A549 cells expressing 54 individual viral
proteins, the “effectome” (Figure 1a; Supplementary Table 3). This dataset provides clear
links between protein expression changes and virus-host interactions, as exemplified by
ORF9b, which leads to a dysregulation of mitochondrial functions and binds to TOMM70, a
known regulator of mitophagy
2,17
(Figure 1b; Supplementary Tables 2, 3). Global pathway
enrichment analysis of the effectome dataset confirmed such mitochondrial dysregulation by
ORF9b of both viruses
2,18
(Extended data Fig. 2c; Supplementary Table 3) and further
highlighted virus-specific effects, as exemplified by the exclusive upregulation of proteins
involved in cholesterol metabolism (CYP51A1, DHCR7, IDI1, SQLE) by SARS-CoV-2
NSP6. Intriguingly, cholesterol metabolism was recently shown to be implicated in SARS-
CoV-2 replication and suggested as a promising target for drug development
19–21
. Beside
perturbations at the pathway level, viral proteins specifically modulated single host proteins,
possibly explaining more distinct molecular mechanisms involved in viral protein function.
Focusing on the 180 most affected host proteins, we identified RCOR3, a putative
transcriptional corepressor, as strongly upregulated by NSP4 of both viruses (Extended data
Fig. 2d, 3a). Remarkably, the apolipoprotein B (APOB) was substantially regulated by
ORF3 and NSP1 of SARS-CoV-2, suggesting its importance for SARS-CoV-2 biology
(Extended data Fig. 3b).
Multi-omics profiling of SARS-CoV-2 and SARS-CoV infection
While interactome and effectome provide in-depth information on the activity of individual
viral proteins, we wished to directly study their concerted activities in the context of viral
infection. To this end, we infected ACE2-expressing A549 cells (Extended data Fig. 4a, b)
with SARS-CoV-2 and SARS-CoV, and profiled the impact of viral infection on mRNA
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expression, protein abundance, ubiquitination and phosphorylation in a time-resolved
manner (Figure 2 a-b).
In line with previous reports
9,22
, both SARS-CoV-2 and SARS-CoV share the ability to
down-regulate type-I interferon response and activate a pro-inflammatory signature at
transcriptome and proteome levels (Figure 2a-c, Extended data Fig. 4c-f, i, Supplementary
Table 4, 8, Supplementary discussion 1). However, SARS-CoV elicited a more pronounced
activation of the NFkB pathway, correlating with its higher replication rate and potentially
explaining the reduced severity of pulmonary disease in case of SARS-CoV-2
23
(Supplementary Tables 4, 5). In contrast, SARS-CoV-2 infection led to higher expression of
FN1 and SERPINE1, which may be linked to the specific recruitment of TGFB factors
(Figure 1b) and supporting regulation of TGF-
β
signaling by SARS-CoV-2.
To better understand the mechanisms underlying perturbation of cellular signaling, we
performed comparative ubiquitination and phosphorylation profiling of SARS-CoV-2 and
SARS-CoV infection. This analysis identified 1
108 of 16
541 detected ubiquitination
sites to be differentially regulated by SARS-CoV-2 or SARS-CoV infection (Figure 2a, b, d,
Extended data Fig. 5a; Supplementary Table 6). More than half of the significant sites were
regulated in a similar manner by both viruses. These included sites on SLC35 and SUMO
family proteins, indicating possible regulation of sialic acid transport and the process of
SUMO-regulation itself. SARS-CoV-2 specifically increased ubiquitination on autophagy-
related factors (MAP1LC3A, GABARAP, VPS33A, VAMP8) as well as particular sites on
EGFR (e.g. K739, K754, K970). Sometimes the two viruses targeted distinct sites on the
same cellular protein, as exemplified by HSP90 family members (HSP90AA1-K84, -K191
and -K539) (Figure 2d). Notably, a number of proteins (e.g. ALCAM, ALDH3B1,
CTNNA1, EDF1 and SLC12A2) exhibited concomitant ubiquitination and a decrease at the
protein level after infection, pointing to ubiquitination-mediated protein degradation (Figure
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(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
The copyright holder for this preprintthis version posted March 15, 2021. ; https://doi.org/10.1101/2020.06.17.156455doi: bioRxiv preprint