key: cord-0854979-qfdp4ov9
authors: Shaban, Mohammed Samer; Müller, Christin; Mayr-Buro, Christin; Weiser, Hendrik; Albert, Benadict Vincent; Weber, Axel; Linne, Uwe; Hain, Torsten; Babayev, Ilya; Karl, Nadja; Hofmann, Nina; Becker, Stephan; Herold, Susanne; Schmitz, M. Lienhard; Ziebuhr, John; Kracht, Michael
title: Inhibiting coronavirus replication in cultured cells by chemical ER stress
date: 2020-08-26
journal: bioRxiv
DOI: 10.1101/2020.08.26.266304
sha: 6a40289e5b47e467c0352057a6643d1a5df4192a
doc_id: 854979
cord_uid: qfdp4ov9

Coronaviruses (CoVs) are important human pathogens for which no specific treatment is available. Here, we provide evidence that pharmacological reprogramming of ER stress pathways can be exploited to suppress CoV replication. We found that the ER stress inducer thapsigargin efficiently inhibits coronavirus (HCoV-229E, MERS-CoV, SARS-CoV-2) replication in different cell types, (partially) restores the virus-induced translational shut-down, and counteracts the CoV-mediated downregulation of IRE1α and the ER chaperone BiP. Proteome-wide data sets revealed specific pathways, protein networks and components that likely mediate the thapsigargin-induced antiviral state, including HERPUD1, an essential factor of ER quality control, and ER-associated protein degradation complexes. The data show that thapsigargin hits a central mechanism required for CoV replication, suggesting that thapsigargin (or derivatives thereof) may be developed into broad-spectrum anti-CoV drugs. One Sentence Summary / Running title Suppression of coronavirus replication through thapsigargin-regulated ER stress, ERQC / ERAD and metabolic pathways

The ER is critically involved in surveying the quality and fidelity of membrane and secreted protein 40 synthesis, as well as the folding, assembly, transport and degradation of these proteins (Wang &  41 Kaufman, 2016). The accumulation of unfolded or misfolded proteins in the ER lumen leads to ER 42 stress and UPR activation, thereby slowing down protein synthesis and increasing the folding capacity 43 of the ER (Karagoz et al, 2019) . As a result, cellular protein homeostasis can be restored and the cell 44

survives. If this compensatory mechanism fails, ER stress pathways can also switch function and will 45 eventually induce oxidative stress and cell death (Hetz & Papa, 2018; Wang & Kaufman, 2016). 46 47

The system relies on three ER membrane-inserted sensors, including the protein kinase R (PKR)-like 48 ER kinase (PERK), inositol-requiring protein 1α (IRE1α) and cyclic AMP-dependent transcription 49 factor 6α (ATF6α). PERK and IRE1α are Ser/Thr kinases whose conserved N termini are oriented 50 towards the ER lumen (Wu et al, 2014) . In non-stressed cells, the highly abundant major ER 51 chaperone and ER stress sensor binding-immunoglobulin protein BiP (also called 78 kDa glucose-52 regulated protein, GPR78; heat shock protein family A member 5, HSPA5) binds to PERK and IRE1α, 53

which keeps these two proteins in an inactive monomeric state ( The activation of ER stress by infectious agents has been widely observed. However, with few 68 exceptions, it remains to be studied how this response is shaped in a microbe-specific manner and 69 whether or not these responses are beneficial or detrimental to the host (Grootjans et al, 2016). 70

Moreover, there is a lack of knowledge on CoV-mediated (de)regulation of ER stress components at 71 the protein level. The latter is important because CoVs, in common with many RNA viruses, are 72 known to cause a global shutdown of host protein synthesis (Hilton et al, 1986). 73 74

Here, we report that CoV infection activates UPR signaling and induces ER stress components at the 75 mRNA level but suppresses them at the protein level. Strikingly, the well-known chemical activator of 76 the UPR, thapsigargin, exerts a profound antiviral effect in the lower nanomolar range on three 77 different CoVs in different cell types. A detailed proteomics analysis reveals multiple thapsigargin-78 regulated pathways and a network of proteins that are suppressed by CoV but (re)activated by 79 chemically stressed infected cells. These results reveal new insight into central factors required for 80

CoV replication and open new avenues for targeted CoV antivirals. 81 82

Results

To investigate how CoVs modulate ER stress components at the mRNA compared to the protein level, 84

we determined the expression levels of 166 components of the ER stress pathway KEGG 04141 85 "protein processing in endoplasmic reticulum" in human HuH7 liver cells, a commonly used cellular 86 model for CoV replication, in response to infections with HCoV-229E and MERS-CoV, respectively. 87

For untreated HuH7 cells, we obtained mRNA (by RNA-seq) and protein (by LC-MS/MS) expression 88 data for 119 components which revealed a positive correlation between mRNA and protein 89 abundancies (Fig.1A, upper graph) . However, in cell lysates obtained at 24 h post infection (p.i.), this 90 effect was largely lost (Fig. 1A , middle and lower graph). Pearson correlation matrix confirmed a 91 progressive loss of correlation between mRNA levels and protein levels for this pathway over a time 92 course from 3 h to 24 h p.i. (Fig. 1B) . Thus, out of 37 (for HCoV-229E) or 56 (for MERS-CoV) ER 93 stress factors that were found to be regulated at the mRNA level, only a few remained (down)regulated 94 at the protein level at late time points (Fig. 1C, Fig. S1 ). 95

To determine the functional consequences of this opposing regulation at the mRNA and protein levels 96

in CoV-infected cells, we focused on HCoV-229E and assessed key regulatory features of the ER  97 stress pathway as shown in Fig. 2A . As a reference, we included samples from cells exposed to 98 thapsigargin, a compound that has been widely used to study prototypically activated ER stress 99 mechanistically (Bertolotti et al., 2000; Oslowski & Urano, 2011) . This setup included experiments, in 100 which thapsigargin and virus were added simultaneously to the cell culture medium (followed by a 101 further incubation for 24 h) or thapsigargin was added to the cells at 8 h p.i. for 16 h (Fig. 2B) .

The presence of thapsigargin in the growth medium resulted in a major drop in viral titers by more 104 than 150-fold (from 9.18*10 6 to 5.7*10 4 pfu / ml) which was paralleled by reduced amounts of viral 105 RNA isolated from thapsigargin-treated, HCoV-229E-infected infected cells at 24 h p.i. (Fig. 2C) .

Immunofluorescence analysis of HCoV-229E-infected cells treated with thapsigargin confirmed the 107 impaired formation of functional viral replication/transcription complexes (RTCs) as shown by the 108 reduced levels of both double-stranded RNA (an intermediate of viral RNA replication) and 109 nonstructural protein (nsp) 8 (an essential part of the viral RTC) (Fig. 2D) .

A strong suppression of viral replication was also demonstrated by the reduced protein levels observed 112 for the nucleocapsid (N) protein (a major coronavirus structural protein) as well as nonstructural 113

proteins (nsp) 8 and 12, both of which representing essential components of the viral replication 114 complex (Snijder et al, 2016) (Fig. 2E, F) . In all cases, the antiviral effect of thapsigargin remained 115 readily detectable when the compound was added at 8 h p.i, suggesting that it does not prevent viral 116 entry but rather suppresses intracellular pathways required for efficient RNA replication and/or 117 particle formation and release or activates unknown antiviral effector systems (Fig. 2C-F) . 118 119

Next, we investigated ER stress signaling under these conditions. Both virus and thapsigargin were 120 confirmed to activate the PERK branch of ER stress (Fig. 2E, F) , as shown by the retarded mobility of 121 PERK in SDS gels (indicating multisite phosphorylation) and by phosphorylation of the PERK 122 substrate eIF2α at Ser51 (Fig. 2E, F) . Unlike thapsigargin treatment, HCoV-229E infection led to a 123 weak but significant decrease of PERK (mean 71±15 %) and eIF2α (mean 67±13 %) levels compared 124 to the controls. Infection also caused an approximately twofold (mean 42±22 %) reduction in BiP 125 expression (Fig. 2E, F) . In contrast, long-term thapsigargin treatment (for 16 h or 24 h) caused a 3-4-126 fold increase in BiP expression, also in HCoV-229E-infected cells, thus reversing the suppression by 127 viral infection (Fig. 2E, F) . Similarly, thapsigargin treatment for 16 h or 24 h caused a 1.5-2-fold 128 increase in IRE1α expression (but not phosphorylation), again also in infected cells (Fig. 2E, F) . In 129 this set of experiments, ATF3 proved to be the only protein that was induced by virus alone (Fig. 2E,  130 F), while the expression levels of ATF4 remained largely unchanged (Fig. 2E, F) . 131 132

These data show that both CoV infection and chemicals like thapsigargin activate ER stress through 133 the same proximal PERK pathway, although they affect downstream cellular outcomes differentially. 134

The restoration of BiP and IRE1α levels by long-term thapsigargin treatment further suggests that the 135

CoV-induced block of inducible host factors is not irreversible and can be reprogrammed by a 136 (presumably protective) thapsigargin-mediated response. Our comparative analyses of viral replication 137 and host response lead us to conclude that chemically and virus-induced forms of ER stress, although 138 proceeding through the same core PERK pathway, do not simply potentiate each other but rather 139

(somewhat counterintuitively) counteract each other. 140 141

To explore a potential pharmacological exploitation of this effect, we assessed the cytotoxicity of the 142 combined thapsigargin treatment and virus infection, because both conditions are known to promote 143 cell death. 144

At 24 h p.i., cell viability of HCoV-229E-infected HuH7 cells was only marginally reduced (mean 145 90.02±12.32 %) (Fig. 2G, upper graph) . After 24 h of incubation, thapsigargin decreased cell 146 viability in a dose-dependent manner with a CC50 of 10.7 µM in line with previous reports (Fig. 2G,  147 middle graph, Fig. 2H ) (Sehgal et al, 2017; Tombal et al, 2000) . The combination of thapsigargin 148

and HCoV-229E infection did not cause additional cytotoxicity as shown by a nearly identical CC50 of 149 9.7 µM (lower graph, Fig. 2G, Fig. 2H ). At 1 µM thapsigargin, i.e., a concentration shown to 150

completely abolish viral protein translation and replication (see above), the cell viability of cells 151

infected with HCoV-229E and treated with thapsigargin was 76.6±7.9 %, suggesting that thapsigargin 152 exerts its antiviral effects at concentrations well below its cytotoxic concentrations (Fig. 2G, H) .

To further characterize the metabolic state of the cells under the conditions used in these experiments, 155

we investigated protein de novo synthesis. Newly produced proteins were quantified by in vivo 156 puromycinylation tagging of nascent protein chains followed by immunoblotting using anti-puromycin 157

antibodies. HCoV-229E was found to shut down protein biosynthesis by 90.3±5.4% while 1 h of 158 thapsigargin treatment led to a shutdown by 94.3±4.3% (Fig. 2I) . However, in infected cells, the 159 simultaneous or delayed addition of thapsigargin restored (or rescued) protein biosynthesis to 160 approximately 50 % of the level observed in untreated cells (Fig. 2I) . These data demonstrate that, 161

although both viral infection and thapsigargin treatment (individually) induce ER stress and cause a 162 translational shut-down, their combination shows no additive harmful effects to the cells. On the 163 contrary, their combination appears to have opposing effects that result in a partial restoration of the 164 cellular metabolic capacity while retaining a profound antiviral effect. 165 166 We next assessed if these effects were cell-type or virus-specific. In line with the results described To characterize the underlying molecular mechanisms responsible for the observed antiviral effects of 177 thapsigargin, we focused on two highly pathogenic coronaviruses, MERS-CoV and SARS-CoV, for 178 which, to our knowledge, no side-by-side comparison of proteomic changes has been reported to date. 179

The large-scale proteomic study included (i) untreated cells and cells that were (ii) infected with 180 MERS-CoV, (iii) SARS-CoV-2, (iv) treated with thapsigargin, (v and vi) infected with one of these 181 viruses in the presence of thapsigargin. We used label-free quantification of six replicates per sample 182

to determine the expression levels of > 5000 proteins from total cell extracts. 183 184

In a systematic approach, we identified differentially expressed proteins (DEPs) based on pairwise 185

comparisons of proteins obtained from untreated cells, virus-infected cells or thapsigargin-treated cells 186 using a p value of -log10 ≥ 1.3 as cut-off. As visualized by Volcano plot representations, MERS-CoV 187 infection suppressed 413 (at 12 h p.i.) and 1171 proteins (at 24 h p.i.), respectively, and increased the 188 levels of 150 proteins (at 12 h p.i.) and 508 proteins (at 24 h p.i.), respectively (Fig. 4A, B) , while 189 SARS-CoV-2 suppressed the expression of 232 proteins at 12 h p.i. and 141 proteins at 24 h p.i. and 190 increased the expression of 184 proteins at 12 h p.i. and 56 proteins at 24 h p.i. (Fig. 4C, D) . We then devised a bioinformatics strategy to identify patterns of co-regulated or unique pathways and 205

link deregulated protein sets identified in these data to specific (known) biological functions. As 206

shown schematically in up-/or downregulated DEPs we found that many of the most highly enriched categories are related to 218 RNA, DNA, metabolic functions and localization (Fig. S5A) . We then combined the 400 pathway 219 categories and searched this list for identical or unique GO terms in response to MERS-CoV, SARS-220

CoV-2 or thapsigargin. By filtering 227 pathways (out of 400) with enrichment p values ≤ -log10 3 we 221

found 27 pathway categories shared by both viruses and by thapsigargin, which are mostly related to 222 RNA, folding, stress and localization (Fig. 4F, Fig. S5B ). 61 pathway categories unique to 223 thapsigargin almost exclusively represented metabolic and biosynthetic pathways as shown for the top 224 20 overrepresented pathways containing up-or downregulated DEPs, suggesting that thapsigargin on 225 its own, unlike CoV infection, initiates a broad metabolic response (Fig. 4F, Fig. S5B ).

This raised the question of whether the thapsigargin effects were retained in infected cells or, 228

alternatively, drug-sensitive pathway patterns were reprogrammed (or masked) by the virus infection. 229

To address this point, we pooled all pathways enriched under virus+thapsigargin conditions and 230 compared them to virus infection or thapsigargin alone. 53% (132 out 248) pathway terms were shared 231 by these three conditions reflecting multiple stress-related, catabolic and RNA regulatory processes 232 (Fig. 4G, H) . 21 pathway terms were unique to the virus+thapsigargin situation. They primarily 233 mapped to specific splicing, signaling (TORC, RHOA, ARF3) and transport/localization pathways 234 (Fig. 4G, H) . The 34 categories shared by virus+thapsigargin and thapsigargin conditions but were not 235 detectable in cells infected with virus (only) recapitulate the thapsigargin-regulated metabolic 236 pathways (pyruvate, aldehyde, carbohydrate, amino/nucleotide sugar, amino acid and glutamine 237 metabolism, TCA cycle, ERAD pathway, N-linked glycosylation) (Fig. 4G, H) . For several of these 238 pathways (e.g. ERAD, heat stress, carbohydrate metabolism), some DEPs were induced while others 239

were repressed, indicating remodeling of pathway functions at the protein level (Fig. 4G, H) . The 53 240 pathway terms that were absent in the virus+thapsigargin group of terms (groups 27, 9, 17 of the Venn 241 diagram shown in Fig. 4G ) represent a distinct set of terms, mostly related to nucleotide and DNA-242 related processes, such as DNA repair, DNA unwinding, chromatin silencing (Fig. 4G, H) . In 243 summary, the functional analysis of DEPs at the level of differentially enriched pathway categories 244

shows that the antiviral effects of thapsigargin strongly correlate with the activation / suppression of a 245 range of metabolic programs. 246 247

The enriched pathway terms provided important overarching information on shared and unique 248 biological processes but not necessarily encompassed identical sets of DEPs as exemplified by the ten 249 pathways shown in Fig. 4I . We therefore refined our analysis to the individual component level to 250

identify proteins with similar regulation between both viruses across both cell types. The proteomes of 251

HuH7 and Vero E6 cells overlap by 57 % (Fig. 5A) . In this group, only 43 identical proteins were 252 found to be deregulated by both MERS-CoV and SARS-CoV-2 (Fig. 5B, it becomes apparent that the majority of proteins are regulated in the same direction by thapsigargin 256 alone; demonstrating that thapsigargin largely overrides any virus-induced modulation of host 257 processes (Fig. 5C ). 258 259

In the absence of thapsigargin, the virus infection generally has little or opposite effects on the levels 260

of the 108 proteins, as exemplified by the suppression seen for BiP (HSPA5) or HERPUD1 (Fig. 5C,  261 highlighted in green). The 108 induced factors map to pathways involving COPI-mediated 262 anterograde transport, ER stress, organelle organization and apoptosis (Fig. 5D) . Across their pathway 263

annotations, 59 out of the 108 proteins were reported to strongly interact, thus probably being involved 264 in protein:protein networks that coordinate activities of the enriched pathways (Fig. 5E, left graph) . 265 Likewise, the 61 repressed proteins map to specific (though different) pathways, such as fatty acid 266

degradation or viral life cycle (Fig. 5D) . 26 components can be allocated to a few small protein 267 interaction networks (Fig. 5E, right graph) . 268 269

We then validated mass spectrometry data by immunoblotting, confirming the induction of HERPUD1 270 in thapsigargin-treated cells infected individually with each of the three CoVs (Fig. 5F , G). We also 271 confirmed an additional hit belonging to the enriched pathways GO:0006520 (cellular amino acid 272 metabolic process) and GO:0034976 (response to endoplasmic reticulum stress, as shown in Fig.   273 4G, H), cystathionine-γ-lyase (CTH), a regulator of glutathione homeostasis and cell survival (Lee et 274 al, 2014), as a further independent example for the fidelity and robustness of the proteomics data (Fig.  275 5F, G). 276 277

The highly inducible HERPUD1 protein has an essential scaffolding function for the organization of searching our proteomics data for further ERAD factors we were able to retrieve a total of 34 (for 284 MERS-CoV) and 20 (for SARS-CoV-2) proteins of the canonical ERQC and ERAD pathways for 285 which a differential expression was observed in virus-infected cells treated with thapsigargin (Fig.  286  5H) . Mapping of these data on the KEGG 04141 pathway suggests that thapsigargin enhances or 287 restores these mechanisms at key nodes of ERQC and ERAD in coronavirus-infected cells (Fig. S6) . 288 289 We also intersected the 108+59 proteins jointly regulated by thapsigargin in MERS-CoV and SARS-290

CoV-2 infected cells with data from a recent genome-wide sgRNA screen that reported new ERAD 291 factors required for protein degradation (Leto et al, 2019) . This analysis identified 31 additional 292

thapsigargin-regulated factors that may further support antiviral ERAD, including UBA6 and ZNF622, 293

which were recently described either as negative regulators of DNA virus infections or of autophagy, 294 the latter process playing diverse roles during CoV infection (Fig. 5I) In conclusion, these data show that thapsigargin forces the (re)expression of a dedicated network of 298 proteins with roles in ER stress, ERQC, ERAD, and a range of metabolic pathways. Collectively, these 299 changes at the protein level confer an "antiviral state" and profoundly suppress CoV replication as 300 summarized schematically in Fig. 5J .

Discussion 303

In this study, we report a potent inhibitory effect of the chemical thapsigargin on the replication of 304 three human CoVs in three different cell types. Clearly, the mechanistic basis for these effects remains to be identified in additional studies. The 353

proteomic data show that thapsigargin affects multiple pathways beyond the core ER stress response. 354

They also indicate that it will not be trivial to identify the essential targets that mediate thapsigargin's 355 antiviral effects. Our data provide a rich resource for further drug target analysis, also in conjunction 356

with the few deep protein sequencing studies available for SARS-CoV-2 (but not MERS-CoV) 357

( In the absence of effective therapeutic and prophylactic strategies (antivirals and vaccines) to combat 362 coronaviruses, and in view of the current SARS-CoV-2 pandemic, we report these observations to 363

invite other laboratories to embark on a broader investigation of this potential therapeutic avenue. 364

Given that thapsigargin concentrations in the lower nanomolar range were shown to abolish CoV 365 replication in cultured cells, even when added later in infection (8 h translational shut-down and are secreted in a cell-type specific manner (Fig. S7) . Some of these 380 cytokines may contribute to the cytokine storm observed in some COVID-19 patients (Mehta et al, 381 2020). While thapsigargin had no effect on IL-8, IL-6, CXCL2 and CCL20 in cell culture (Fig. S7) , a 382 single bolus of the compound was shown to efficiently reduce the translation of pro-inflammatory 383 cytokines in preclinical models of sepsis (Wei et al, 2019) . Thus, an additional benefit of thapsigargin 384 treatment may arise from dampening overshooting tissue inflammation in COVID-19 patients. In 385 summary, the study provides several lines of evidence that thapsigargin hits a central mechanism of 386

CoV replication, which may be exploited to develop novel therapeutic strategies. This compound or 387 derivatives with improved specificity, pharmacokinetics and safety profiles may also turn out to be 388 valuable to mitigate the consequences of potential future CoV epidemics more effectively. Infection. Sci 

Pepstatin 874 A, PMSF and microcystin were dissolved in ethanol and leupeptin in water. Other reagents were from 875 Sigma-Aldrich or Thermo Fisher Scientific

anti PERK (Abcam, #ab65142), anti BiP (Cell Signaling, 879 #3177), anti eIF2α (Cell Signaling #9722), anti P(S51)-eIF2α (Cell Signaling #9721), anti P

anti IRE1α

#sc-188), anti HERPUD1 antibody (Abnova, 882 #H00009709-A01), anti CTH antibody (Cruz, #sc-374249), anti HCoV-229E N protein ((Ingenasa, 883 Batch 250609), mouse anti HCoV-229E nsp12 (gift from Carsten Grötzinger), rabbit anti HCoV-229E 884 nsp8 (Ziebuhr & Siddell, 1999), anti MERS-CoV N protein (Sinobiological, #100213-RP02), rabbit 885 anti SARS-CoV N protein cross-reacting with SARS-CoV-2 N protein (gift from Friedemann Weber), 886 anti SARS-CoV-2 N protein (Rockland, #200-401-A50), anti puromycin

The following secondary antibodies were used: Dako P0447; polyclonal goat anti-mouse 889 immunoglobulins/HRP, Dako P0448; polyclonal goat anti-rabbit immunoglobulins/HRP, Cy3-coupled 890 anti rabbit (rb) IgG (dk, Merck Millipore, #AP182C), Dylight 488-coupled anti mouse (ms) IgG (dk, Immunoblotting was performed essentially as described (Hoffmann et al

After blocking with 5% 923 dried milk in Tris-HCl-buffered saline/0.05% Tween (TBST) for 1 h, membranes were incubated for 924 12-24 h with primary antibodies, washed in TBST and incubated for 1-2 h with the peroxidase-925 coupled secondary antibody. Proteins were detected by using enhanced chemiluminescence (ECL) 926 systems from Millipore or GE Healthcare

mRNA expression analysis by RT-qPCR 930 0.5 -1 µg of total RNA was prepared by column purification (MachereyNagel) and transcribed into 931 cDNA using Moloney murine leukemia virus reverse transcriptase

#EP0441) in a total volume of 10 or 20 µl. 1 or 2 µl of this reaction 933 mixture was used to amplify cDNAs using

Fisher Scientific) for GUSB (81 bp, Hs99999908_m1), IL6 (95 bp

IL8 (101 bp, Hs0017 4103_m1), CXCL2 (68 bp, Hs00236966_m1), and CCL20 (81 936 bp, Hs00171125_m1), as well as TaqMan Fast Universal PCR Master Mix (Applied Biosystems/ 937

All PCRs 942 were performed in duplicate on an ABI 7500 real-time PCR instrument. The cycle threshold value (ct) 943 for each individual PCR product was calculated by the instrument's software, and the ct values 944 obtained for inflammatory/target mRNAs were normalized by subtracting the ct values obtained for 945 GUSB. The resulting Δct values were also used to calculate relative changes of mRNA expression as 946 ratio (R) of mRNA expression of treated

After 2x 952 washing, cells were fixed with 4% paraformaldehyde in PBS (Santa Cruz, #281692) for 5 min, washed 953 3x 10 min with Hank's BSS (PAN, #P04-32505), blocked with 10% normal donkey serum (Jackson 954 ImmunoResearch, #017-000-121) for 20 min and incubated with primary and secondary antibodies 955 diluted in Hank's BSS containing 0.005% saponin (Sigma-Aldrich, #S4521-10G) for 2 h at room 956 temperature. Following 3 washing steps with Hank's BSS containing 0.005% saponin

In brief, 1.2 x 10 4 HuH7 or 1 x 10 4 MRC-5 968 cells were seeded in 96-well plates for 24 hours and thereafter treated with DMSO, thapsigargin, virus 969 alone or virus plus thapsigargin for 24 hours as indicated in the figure legends. Then, the medium was 970 replaced by 100 µl complete cell culture medium including 20 µl CellTiter 96® AQueous one solution 971 reagent according to the manufacturer's recommendations. Cells were further incubated for 0.5 -1 972 hour at 33° C. Then, absorbance values were measured at 490 nm

After 24 h, 200 µl MTT mix (DMEM supplemented with 10% FCS 976 containing 250µg/ml tetrazolium bromide, Sigma) was added to each well. Next, cells were incubated 977 for 90-120 min at 37°C and fixed using 3.7% PFA in PBS. The tetrazolium crystals were dissolved by 978 adding 200 µl/well isopropanol and the absorbance at 490 nm was measured using an ELISA reader 979 (BioTek)

ELISA 984 Sandwich ELISAs from R&D Systems (DuoSet ELISA for human IL-8 (DY208)

The cell culture supernatants were harvested, centrifuged at 15,000 × g at 4°C for 15 s 988 and stored at -80°C. 100 µl of the supernatants were either used undiluted or were diluted in cell 989 culture medium as follows

or mock infection) using two biological replicates resulting in 32 RNA-seq data sets. 998 RNA was sequenced (with rRNA depletion) using Illumina reagents and an Illumina HiSeq 4000 999 instrument (single read, 150 bases)

Cysteines were alkylated with Iodoacetamide and 8 M urea buffer was exchanged 1015 to 50 mM ammonium-bicarbonate buffer with a pH of 8.0. Samples were digested within the filter 1016 devices by the addition of sequencing grade modified trypsin (Serva) and incubation at 37 °C over-1017 night. Thereafter, the filter-units were transferred to fresh tubes. Peptides were eluted by the addition 1018 of 50 µL 0.5 M NaCl solution and centrifugation (14.000 x g for 10 min)

Finally, peptides were dissolved in 25 µl water with 5% acetonitrile and 0.1% 1022 formic acid. The mass spectrometric analysis of the samples was performed using a timsTOF Pro mass 1023 spectrometer (Bruker Daltonic). A nanoElute HPLC system

Sample loading was performed at a constant pressure 1027 of 800 bar. Separation of the tryptic peptides was achieved at 50°C column temperature with the 1028 following gradient of water/0.1% formic acid (solvent A) and acetonitrile/0.1% formic acid (solvent 1029 B) at a flow rate of 400 nL/min: Linear increase from 2%B to 17%B within 60 minutes, followed by a 1030 linear gradient to 25%B within 30 minutes and linear increase to 37% solvent B in additional 10 1031 minutes. Finally B was increased to 95% within 10 minutes and hold for additional 10 minutes. The 1032 built-in "DDA PASEF-standard_1.1sec_cycletime" method developed by Bruker Daltonics was used 1033 for mass spectrometric measurement. Data analysis was performed using MaxQuant with the 1034 Andromeda search engine and Uniprot databases were used for annotating and assigning protein 1035 identifiers

The normalized expression values assigned 1041 to uninfected HuH7 cells were derived from a total of 59 mock samples representing multiple 1042 technical repeats of two biological samples generated at each of the 3 h, 6 h, 12 h, 24 h time points in 1043 order to generate a common reference sample for the mean protein expression found in uninfected / 1044 untreated HuH7 cells. This mean reference was used to calculate all ratio values. From the entire data 1045 set, only protein intensity values for 166 uniprot IDs assigned to KEGG 04141 were extracted, 1046 quantile normalized and further analyzed using the software tools described below. 1047 For the data shown in Fig. 4 and 5, raw data from 96 LC-MS/MS runs (representing two independent 1048 experiments and three technical replicates per sample) were mapped to Homo sapiens

All data sets were processed by 1052 MaxQuant version 1.6.10.43 (raw data submission was done with version 1.6.17.0) (Tyanova et al., 1053 2016a) including the match between runs option enabled resulting in the identification of

IDs 1056 assigned to contaminants and reverse sequences were omitted. For calculation of ratio values between 1057 conditions, the 2 x 6 replicates from each condition were assigned to one analysis group. 1058 Differentially expressed proteins were identified from log2 transformed normalized protein intensity 1059 values by Volcano plot analysis using Perseus functions. All subsequent filtering steps and heatmap 1060 representations were performed in Excel 2016 as described in the figure legends

Pearson correlations) were 1070 calculated using SigmaPlot 11

 Thirty minutes  902 prior to harvest, the medium was supplemented with 3 µM puromycin (InvivoGen, #ant-pr-1). Then, 903 cells were lysed as described above. After immunoblotting (see below), membranes were stained with 904Coomassie brilliant blue and then hybridized with an anti puromycin antibody (Kerafast, #EQ0001) to 905 detect puromycinylated polypetides. 906Total cell lysates of MERS-CoV-and SARS-CoV-2-infected cells used for immunoblotting or mass 907 spectrometry were prepared as follows. Cells were scraped in ice-cold PBS and pelleted at 500 x g for 908 5 min at 4°. Cell pellets were washed in ice-cold PBS and stored in liquid N2 (or lysed and processed 909 immediately). After thawing, cell pellets (corresponding to ≈ 300.000 cells seeded in 60 mm dishes at 910 the start of the experiment) were resuspended in 90 µl of ice-cold Ca 2+ / Mg 2+ -free PBS and 911 transferred to fresh tubes. After addition of 10 µl of 10% SDS, samples were heated at 100 °C for 10 912 min and centrifuged at 600 x g for 1 minute at room temperature. Supernatants were transferred to a 913 fresh tube and heated again at 100°C for 10 minutes and centrifuged at 600 x g for 1 minute at room 914 temperature. Protein concentrations were determined with the detergent compatible Bradford assay kit 915 (Pierce™, #23246) using a 150-fold dilution. Aliquots corresponding to 20-25 µg protein (per lane) 916were mixed with 4 x SDS sample buffer (ROTI ® Load, Roth, #K929) and stored at -20 °C prior to 917 SDS-PAGE, or loaded immediately. Cell lysates were subjected to SDS-PAGE on 8-10% gels. The 918PageRuler™ prestained protein ladder (Thermo Scientific, #26616) was used as Mr marker. 919