key: cord-0776431-irmh86pk
authors: Chen, Xi; Saccon, Elisa; Appelberg, K. Sofia; Mikaeloff, Flora; Rodriguez, Jimmy Esneider; Vinhas, Beatriz Sá; Frisan, Teresa; Végvári, Ákos; Mirazimi, Ali; Neogi, Ujjwal; Gupta, Soham
title: Type-I interferon signatures in SARS-CoV-2 infected Huh7 cells
date: 2021-02-04
journal: bioRxiv
DOI: 10.1101/2021.02.04.429738
sha: ac3906b3e98981ed79f7bb75ef5c7219f315ca6e
doc_id: 776431
cord_uid: irmh86pk

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes Coronavirus disease 2019 (COVID-19) has caused a global health emergency. A key feature of COVID-19 is dysregulated interferon-response. Type-I interferon (IFN-I) is one of the earliest antiviral innate immune responses following viral infection and plays a significant role in the pathogenesis of SARS-CoV-2. In this study, using a proteomics-based approach, we identified that SARS-CoV-2 infection induces delayed and dysregulated IFN-I signaling in Huh7 cells. We demonstrate that SARS-CoV-2 is able to inhibit RIG-I mediated IFN-β production. Our results also confirm the recent findings that IFN-I pretreatment is able to reduce susceptibility of Huh7 cells to SARS-CoV-2, but not post-treatment. Moreover, senescent Huh7 cells, in spite of showing accentuated IFN-I response were more susceptible to SARS-CoV-2 infection, and the virus effectively inhibited IFIT1 in these cells. Finally, proteomic comparison between SARS-CoV-2, SARS-CoV and MERS-CoV revealed a distinct differential regulatory signature of interferon-related proteins emphasizing that therapeutic strategies based on observations in SARS-CoV and MERS-CoV should be used with caution. Our findings provide a better understanding of SARS-CoV-2 regulation of cellular interferon response and a perspective on its use as a treatment. Investigation of different interferon stimulated genes and their role in inhibition of SARS-CoV-2 pathogenesis may direct novel antiviral strategies.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in the end of 2019, caused a major ongoing pandemic with more than a million deaths worldwide by the end of 2020 1 . SARS-CoV-2 belongs to the genus betacoronavirus, which also includes SARS-CoV and MERS-CoV, two viruses that caused outbreaks in 2002 and 2012, respectively 2 .

These viruses have the capability of infecting both upper and lower respiratory tract with potential to cause severe and fatal respiratory syndrome in humans 3 . While SARS-CoV-2 presented a lower case-fatality than SARS-CoV and MERS-CoV, they shared similar clinical features 2,4 . The severe form of the disease is often associated with a dysregulated type-I interferon (IFN-I) response leading to the pathogenesis 5 , which is attributed to the immunomodulatory proteins encoded by the coronaviruses.

Type-I interferon response that majorly constitutes IFNα and IFNβ is produced by almost every cell and is one of the first lines of defense against viruses 6 . The early activation of IFN responses against coronaviruses is initiated by recognition of viral products by the host pattern recognition receptors like Toll-like receptors (TLRs) and RIG-I like receptors (RLRs). RLRs can recognize the viral RNA that promotes their oligomerization and subsequent activation of a signaling cascade leading to production of IFNα and IFNβ 7 . Through autocrine and paracrine signaling the secreted IFN can bind to IFN-α/β receptors (IFNARs) that activates the Janus kinase 1 (JAK1) and Tyrosine kinase 2 (Tyk2) leading to phosphorylation of signal transducer and activator of transcription proteins, STAT1 and STAT2. Activated STAT1 and STAT2 form the interferon-stimulated gene factor 3 (ISGF3) complex in association with IRF9, translocate to the nucleus with the help of nuclear transporter proteins, bind to IFN-stimulated response elements and trigger transcription of several interferon stimulated genes (ISGs) with antiviral properties 8 . Coronaviruses also have evolved mechanisms to evade the host's antiviral immune response. Several proteins in SARS-CoV (nsp1, PLpro, nsp7, nsp15, ORF3b, M, ORF6 and N) 9 , in MERS-CoV (M, ORF4a, ORF4b, PLpro and ORF5) 3, 9 and in SARS-CoV-2 (ORF6, PLpro, nsp6, nsp13, nsp1, ORF3a, ORF7a/b and M) 10, 11 have been shown to be strong IFN-antagonist.

Most of the current treatment options for SARS-CoV-2 have been guided by knowledge on SARS-CoV and MERS-CoV infection. Based on which therapeutic interventions with type-I IFN treatment and remdesivir have been employed for SARS-CoV-2 [12] [13] [14] . However, the dynamics of the IFN response in mouse models of SARS-CoV and MERS-CoV was observed to vary 15, 16 as well as the sensitivity to IFN-treatment in vitro 17 . Moreover, the transcriptome analysis comparing in vitro host cell response to SARS-CoV-2, SARS-CoV and MERS-CoV have shown distinct virus specific patters 18 . Thus, a deeper understanding of the SARS-CoV-2 mediated regulation of IFN response is necessary to develop rationale and novel therapeutic approaches for SARS-CoV-2

In this study, we characterized the SARS-CoV-2 mediated dysregulation of IFN-signaling in Huh7 infected cells using quantitative proteomics. We show a delayed activation of IFNsignaling with the ability of the virus to evade RIG-I mediated IFN-signaling during early infection. In line with recent studies susceptibility of Huh7 cells to SARS-CoV-2 decreased upon IFN-pretreatment, but not post-treatment. We also determined the IFN-signaling response pattern of SARS-CoV and MERS-CoV infection in Huh7 cells using proteomics and show a distinction compared to SARS-CoV-2. Together, the results provide a perspective of immune regulation by coronaviruses.

Interferons (IFNs) play a critical role in exerting an early antiviral response to inhibit viral replication and spread. To understand how the IFN responses are modulated following SARS-CoV-2 infection, we re-used the proteomics and transcriptomics data set from our earlier study 19 . We first analyzed the quantitative proteomics data on Huh7 cells that were either mock infected or infected with SARS-CoV-2 at multiplicity of infection (MOI) of 1, over a period of 24 and 48 hours post infection (hpi). Genes associated with the interferon response, including the interferon alpha/beta signaling (Pathway: R-HSA-909733), interferon gamma signaling (Pathway: R-HSA-877300) and antiviral mechanism by IFN-stimulated genes (ISGs, Pathway: R-HSA-1169410) were extracted from the data. For mock infected we considered the data for two replicates as one of the replicated was a major outlier as shown in the PCA plot (Supplementary Figure 1) . No major changes were observed in the interferon signaling genes at 24hpi and significant modulation was only observed at 48hpi after infection as represented in the heatmap ( Figure 1A ). Of the 94 proteins studied, a number of proteins showed significant reduction in abundance (n=20), while a major cluster of proteins showed an increase (n=26) (LIMMA, FDR < 0.05). The log2 foldchange of the significantly regulated genes are represented as volcano plot in Figure 1B . The protein-protein interaction network of the significantly changed genes showed two definite clusters (cluster-1 and cluster-2). Cluster-1 involved proteins associated with the RIG-I (DDX58) and type-1 interferon signaling cascade, while cluster-2 mostly involved proteins associated with transporters belonging to the components of nucleoporin complex and karyopherin family ( Figure 1C ).

We also looked into the IFN-signaling genes in the transcriptomics dataset and observed no major changes in the differential expression of the transcripts related to this pathway except for EIF4A2, STAT2, TRIM10 (upregulated) and FLNA, JAK1, GBP2, MT2A, TRIM26 (down regulated) 48 h after infection (Figure 2A ). Of the genes corresponding to the proteins that were altered in the pathway ( Figure 2B ) only EIF4A2, STAT2, JAK1, GBP2 and FLNA showed transcript levels correlating with protein expression ( Figure 2C ). Of note, we had previously observed major changes in the global transcriptome to occur only after 72 h of infection 19, 20 .

In our global transcriptomics and proteomics data we observed a delayed activation of RIG-I and dysregulation of type-I IFN response associated proteins including ISGs. RIG-I, a key cytosolic receptor that can detect SARS-CoV-2 RNA is responsible for activation of IFN-β through a signaling cascade that can further lead to activation of antiviral ISGs ( Figure 3A ). We next studied the effect of SARS-CoV-2 in induction of IFN-β. We did not observe any significant changes in the levels of IFN-β specific mRNAs in SARS-CoV-2 infected Huh7 cells both at 24hpi and 48hpi ( Figure 3B ). Even though not significant, we observed an increase in IFN-β mRNA at 48hpi with an infective dose of MOI 0.1 ( Figure 3B ). This effect was concomitant with a marginal suppression of RIG-I and MDA-5 protein expression at 24 hpi and an observable increase in at 48 hpi detected in western blots probed with specific antibodies ( Figure 3C and 3D). The Western blot data was in line with our proteomics data.

SARS-CoV-2 infection was shown to induce high level of IFN-β in Calu-3 cells and Caco2 cells at 24hpi 21, 22 . However, we did not observe any IFN-β induction or RIG-I activation at 24hpi, suggesting that SARS-CoV-2 is able to inhibit IFN-β activation in Huh7 cells. To determine this Huh7 cells were either mock infected or infected with SARS-CoV-2 at MOI 0.1, followed by either treatment with RIG-I agonist acitretin or transfected with poly I:C for 24h to induce transcription of IFN-β. Treatment with acitretin or poly I:C post-infection did not inhibit production of the virus as measured by qPCR targeting the E-gene in the cell culture supernatant ( Figure 3E and 3G). SARS-CoV-2 was able to efficiently inhibit the IFN-β production in the RIG-I activated cells ( Figure 3F and 3H).

IFN-β produced by a cell binds to IFN-α/β membrane receptors (IFNAR), activating the JAK-STAT signaling cascade, which leads to expression of several ISGs with antiviral properties ( Figure 4A ). Similar to our transcriptomics data, qPCR analysis to detect IFIT1, RIG-I (DDX58) and MX2 in SARS-CoV-2 infected Huh7 cells did not show any significant changes in RNA expression of these genes compared to uninfected cells ( Figure 4B ). Though, in our proteomics data we observed several ISGs to be stimulated among which ISG15 showed an increase in protein level 48hpi. ISG15 can conjugate itself to host proteins to regulate diverse cellular functions as well as viral proteins to alter their mechanisms ( Figure 4A ) 23 . In the unconjugated form ISG15 can behave as a cytokine with ability to inhibit viral replication 24 . We examined the mRNA levels of ISG15 in SARS-CoV-2 infected Huh7 cells after 24h and 48h. We did not observe any significant change in ISG15 at transcript level ( Figure 4C ). However, at protein level it was interesting to note that there was an observable decrease in the conjugated ISG15 at 24hpi and a marked increase in host-cell ISGylation at 48hpi ( Figure 4D and 4E) in a dose dependent manner, suggesting the virus can modulate cellular ISGylation to alter the cellular environment. It was not surprising to observe a decreased ISGylation during early infection as SARS-CoV-2 encodes papain-like protease (PLpro) that is a potent de-ISGylase 11 .

SARS-CoV-2 was observed to change the levels of different ISGs in Huh7 cells ( Figure 1A , 1B and 1C). ISGs can also be stimulated in experimental models by external treatment with IFNs. In order to evaluate the susceptibility of SARS-CoV-2 to type-I IFN (IFN-I), we either presensitized cells (16h) with IFN-α (5000u/mL) and IFN-β (100u/mL) or treated the cells with the same concentrations of IFNs starting 1hpi and continued for 24h. Huh7 cells were infected with SARS-CoV-2 at MOI 0.1 and at 24hpi the supernatant was collected to determine the virus production in presence or absence of different IFN-I treatment conditions. As shown in Figure   4F , IFN-pre-sensitization lead to a significant reduction in SARS-CoV-2 production in the supernatant as compared to levels in supernatant from untreated cells at 24hpi.. However, IFN-I treatment after infection did not suppress virus production ( Figure 4H ). This observation suggests firstly that the presence of high level of IFN-response can suppress the incoming virus and secondly that the virus has also developed measures to counteract these responses when it has already established an infection. Then, we further looked into the effect of IFN-I treatment and infection in transcriptional activation of few of the ISGs that were modulated by SARS-CoV-2 infection. For this we selected MX2, IFIT1 and ISG15. While SARS-CoV-2 suppressed MX2 mRNA in untreated cells, MX2 did not show any activation following IFN-treatment (data not shown). Both ISG15 and IFIT1 were significantly induced following IFN-I treatment, however SARS-CoV-2 did not cause any significant alterations to the mRNA levels ( Figure 4G and Figure 4I respectively).

Elderly people has been suggested to be more susceptible to SARS-CoV-2 infection 25 and cellular senescence is postulated as factor for increased infection. Cellular senescence has been observed to play different role in either promoting infection for some viruses or inhibiting infection for others. To this end we aimed to examine the susceptibility of senescent Huh7 cells to SARS-CoV-2 and associated IFN-I response. To induce cellular senescence Huh7 cells were treated with 0.5 μM of etoposide for 6 days followed by 2 days without any treatment and then infected with SARS-CoV-2 for 1h and cells and supernatants were harvested 24hpi. Etoposide treatment resulted in massive cell death and surviving cells were large in size. Cellular senescence was determined by detecting p21 mRNA levels ( Figure 5B , top-panel leftmost).

SARS-CoV-2 infectivity was determined by measuring the viral E-gene in the supernatant.

Senescent Huh7 cells showed a significant increase in virus production in senescent Huh7 cells compared to the etoposide untreated control cells ( Figure 5A ). We next investigated the IFNresponse in senescence-induced and non-induced cells by detecting mRNA transcripts of IFN-β and ISG's such as ISG15, IFIT1, MX2 and RIG-I. Cellular senescence induced an increase in the IFN-response with significant increase in the levels of IFN-β and other ISG's tested ( Figure 5B ).

Among the genes tested SARS-CoV-2 failed to significantly alter the levels of any except for IFIT1, where a significant decrease in the mRNA levels were noted upon infection ( Figure 

To explore the differences in pathogenicity of SARS-CoV-2 in comparison with its predecessor human pathogenic coronaviruses; SARS-CoV and MERS-CoV, we measured the global proteomic changes by infection in the same cell line and at the same infective dose. MERS-CoV-2 was observed to be highly cytopathic and by 48hpi all the cells were dead restricting our analysis to 24hpi, while SARS-CoV showed a slower cytopathogenicity and infected cells were collected both at 24hpi and 48hpi. Quantitative proteomics was performed utilizing a TMTlabeling strategy of mock infected and virus-infected cells in triplicate as previously described by us 19 . The PCA plots are shown in supplementary Figure S3 We next examined the pathways that were enriched in common proteins with differential abundance in SARS-CoV, MERS-CoV and SARS-CoV-2 infected cells compared to mock using ClusterProfiler. We observed that several pathways in relation to infectious diseases, rRNA processing and mRNA translation were significantly regulated by all the three viruses (Supplementary Figure S5 ). For the current paper we focused our analysis to regulation of IFNresponse. In the IFN-signaling pathways, we looked at proteins that were differentially regulated by any of the three viruses and they are represented as a heatmap in Figure Figure S7 . Cumulatively, this data shows distinct pattern of regulation of type-I IFN response in these three viruses.

The impact of the viral infection is most often dictated by the host innate immune responses and the ability of the virus to regulate these antiviral responses. Type-I interferon (IFN-I) response is one of the earliest antiviral innate immune responses following virus infection. In the present study using a proteomics-based approach, we show that SARS-CoV-2 infection induces a dysregulated IFN-I signaling in a delayed manner in Huh7 cells. Furthermore, comparison between SARS-CoV-2, SARS-CoV and MERS-CoV revealed a differential regulatory signature of interferon-related proteins.

In case of RNA viruses IFN-I response is usually initiated by recognition of the viral RNA by pattern recognition receptors (PRRs) like RIG-I and MDA-5 7,26 . Activation of RIG-I and MDA-5 leads to signaling cascades that are tightly controlled by post-translational modifications like ubiquitination, ISGylation and phosphorylation. The Phosphorylation of IRF3 a downstream effector of this cascade and a transcription factor leads to its dimerization and entry into the nucleus where it binds to IFN-β gene regulatory elements leading to production and release of IFN-β 27 . The released IFN-β can further bind to interferon-α/β receptors (IFNARs) in bystander cells and initiate JAK-STAT signaling cascade, where STAT1 and STAT2 are phosphorylated and forms either a homo-dimer or hetero-dimer, which drives transcription of several interferon stimulatory genes (ISGs) upon translocation to the nucleus and 28 . In our proteomics data we observed several components of this signaling pathway to be dysregulated and the proteomic changes are delayed by 48hrs after infection in Huh7 cells (Figure 1 ). In concordance with the delay in induction of ISGs, we have observed that SARS-CoV-2 can inhibit IFN-β production ( Figure 3F and 3H). However, it needs to be noted that while SARS-CoV-2 induced several ISGs, many of them like MX2, GBP2, IFI30, IFI35 etc. were suppressed. Most interestingly even though several ISGs were induced, JAK1 levels were suppressed, which can make the infected cells resistant towards IFN-treatment at later stages 29 . Other than the ISG's several nuclear transporter complexes were also differentially modulated.

Like any other pathogenic virus, SARS-CoV-2 has developed mechanisms to suppress IFNresponse. For example, by SARS-CoV-2 proteins interacting with various components of the host innate immune responses 30 . ORF6, nsp6, nsp13, nsp1 and M proteins has been shown to inhibit IFN-I signaling pathway at different levels 10, 22, 31 . On the other hand, several SARS-CoV-2 proteins like nsp2 and S proteins were found to stimulate IFN response 22 . Thus, SARS-CoV-2 has the ability to modulate the IFN signaling in both positive and negative ways. This is represented in our findings of both increased expression and suppression of many ISGs in the infected Huh7. Not only ISGs, but also the expression of several nuclear pore complexes (involved in STAT translocation to the nucleus and subsequent ISRE-dependent gene activation) was altered in our infection model. Among the nuclear transporters Nup98 is the most studied with respect to SARS-CoV-2 infection as the ORF-6 protein interacts with it and blocks the translocation of STAT-1 to the nucleus to inhibit ISGs 31 . However, we did not observe any change in Nup98 expression levels. Interestingly we detected another family of nuclear transporter KPNA1, KPNA2 and KPNA4 to be significantly decreased at the later time point of infection (Figure 1 ). KPNA1 forms a complex with pSTAT1 and aids in its translocation to the nucleus 32 and thus serves a major purpose in transcription of ISGs. Reduced expression of KPNA's could result in insufficient nuclear translocation of p-STATs and thus suppress expression of many of the ISGs. Several viruses, like foot-and-mouth disease virus (FMDV), can degrade KPNA1 to block ISGs by their 3C-like protease activity 33 that is also encoded in ORF1a of coronaviruses and was detected in proteomics 19 . SARS-CoV-2 also encodes another protease, papain-like protease (PLpro) that has de-ubiquitinase and de-ISGylase activity. PLpro can hydrolyze ubiquitin and ISG15 conjugation and has been implicated in SARS-CoV-2 immune evasion strategies. PLpro was also reported to be a stronger de-ISGylase than a de-ubiquitinase compared to SARS-CoV and MERS-CoV PLpro 11 . Based on our observation of a dosedependent decrease in conjugated-ISG15 levels at 24hpi and thereafter increase at later stages (48h) of infection, it is tempting to speculate that PLpro may play a significant role in early infection, that requires further validation.

IFN-I pathway is of significance in SARS-CoV-2 pathogenesis because IFN-I has been considered as a major treatment choice 34, 35 . Furthermore, in severe COVID-19 patients and Ferret models in spite of a cytokine storm and induction of ISGs, a very low-level of circulating IFN-I was noted [36] [37] [38] . This was particularly interesting since in our infection model we did not observe any significant transcriptional activation of IFN-β in qPCR, despite observing changes in the levels of proteins related to RIG-I signaling and ISGs (Figure 1) . A recurrent observation was the absence of correlation between transcript levels and protein levels, as both in qPCR and in transcriptomics data we did not observe any significant changes in ISG15, IFIT1, MX2, DDX58 mRNAs between the mock infected and SARS-CoV-2 infected after 48h (Figure 2 and In our Huh7 senescent cell model even though there was a significant increase in IFN-response compared to healthy cells, the virus production was significantly increased ( Figure 5 ), suggesting that the virus is able to escape the antiviral response in senescent cells. In particular among the ISGs tested we observed a significant suppression of IFIT1. However, this effect may be celltype dependent. For instance, Caco2 cells showed more resistance to etoposide with a very lowlevel induction of senescence as represented by p21. However, we observed an inhibition of viral replication with visible upregulation of IFIT1. This indicates, IFIT1 to be an important antiviralfactor that needs further attention. Also, the differences observed among the two cell lines underscores the drawback of studying a single cell line (Huh7 in this case) as it may not be reflective of other cell populations where there could be differential regulation of IFN-response.

SARS-CoV-2 shows a higher level of susceptibility to IFN-treatment in comparison to SARS-CoV 17 and its sensitivity to IFN-I pretreatment is shared by MERS-CoV 10, 17, 44, 45 . In the Huh7 infection model, we have observed the MERS-CoV to be highly cytopathic, a delayed cytopathic effect in SARS-CoV and no cytopathic effect with SARS-CoV-2 infection at the same infective dose. This points towards a differential regulation of immune-signaling pathways by these viruses. Using proteomics, we attempted to delineate the immunological features of the cells during infection with these three viruses. We were restricted with our analysis of MERS-CoV to 24hpi and we observed a large number of proteins expression to be significantly altered when compared to the mock. While in case of SARS-CoV and SARS-CoV-2 the major changes were observed at 48hpi. While we observed a variety of cellular processes to be commonly regulated by these viruses (Supplementary Fig S5) , we focused our analysis to IFN-I signaling. 

The human hepatocyte-derived cellular carcinoma Huh7 cell line was obtained from Marburg Virology Lab, Germany and Caco2 was obtained from CLS cell line services, GmbH, Germany (#300137). The cell lines were maintained in Dulbecco's modified Eagle medium (DMEM, ThermoFisher, USA) supplemented with 10% fetal bovine serum (FBS, ThermoFisher, USA) and 20 units/mL penicillin combined with 20 μg/mL streptomycin (Sigma, USA). Cells were cultured in 5% CO 2 at 37°C.

The SARS-CoV-2 virus was isolated from a nasopharyngeal sample of a patient in Sweden and the isolated virus was confirmed as SARS-CoV-2 by sequencing (Genbank accession number MT093571) and titrated as described elsewhere 19 .

Huh7 cells were seeded in 24-well plates (6x10 4 

heat-inactivated FBS; and after 24 h the cells were treated with poly I:C (10 µg/mL), acitretin (25 µM), IFN-β (100 IU) and IFN-α (5000 IU) in DMEM supplemented with 5% heatinactivated FBS for 16 h before infection. Then, pre-treated and non-treated cells were either cultured in DMEM with 5% FBS (uninfected control) or infected with SARS-CoV-2 at a multiplicity of infection (MOI) of 0.1 added in a total volume of 0.5 mL. After one hour of incubation (37°C, 5% CO 2 ) the inoculum was removed, and medium only was added to pretreated and uninfected cells, while medium with the compounds dilutions was added for cell treatment post-infection.

Huh7 cells were seeded in 6-well plates in DMEM supplemented with 10% heat-inactivated guidelines.

Proteomics workflow was performed similarly as we described previously 19 . Briefly, proteins were extracted with SDS-based buffer, digestion was performed on S-Trap micro columns (Protifi, Huntington, NY) and resulting peptides were labeled with isobaric TMTpro™ reagents. Interferon-regulated genes and proteins from differential abundance analysis were extracted and represented as volcano plot using ggplot2. Significant proteins (proteomics data, LIMMA, FDR < 0.05) were represented as a network with Cytoscape ver 3.6.1. For each node, fold changes were added to the network template file. Protein-protein interactions were retrieved from STRING Db (v5.0) (https://string-db.org/). Interactions were filtered on confidence score with minimum interaction of 0,700. Only interactions from databases and experiences were conserved. Genes associated with type I interferon identified in proteomics data were represented as dot plots using ggplot2.

Huh7 cells infected were collected at 24 and 48hpi for SARS-CoV and 24hpi for MERS-CoV.

Mock infected cells were collected at similar time points. Proteomics raw data was first filtered for empty rows and quantile normalized with R package NormalizerDE. Histogram was used to display the distribution of data and assess that the distribution follows a normal law. Principal E) The intensity of specific bands was quantified by ImageJ and fold change was calculated relative to the uninfected cells (mock). The mean ± SEM of three experiments is shown.

To determine the effect of Type I interferon on SARS-Cov-2 infection, Huh7 cells were treated with 5000 u/mL IFN-α, 100 u/mL IFN-β 16h prior or 24 h after infection. The cells were infected with SARS-CoV-2 at a MOI of 0.1, the mean ± SEM is shown. Unpaired t test was used to determine p-values (* p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001)

F) The virus production in the cell culture supernatant in type I interferon pre-sensitized cells.

The mean ± SD of three independent experiments is shown. 

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The authors would like to acknowledge the support from the Proteomics Biomedicum, 

The authors declare no competing interests.

The raw mass spectrometric data was deposited to the ProteomeXhanger Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD023450. All the bioinformatic analysis codes are available in github at https://github.com/neogilab/COVID_IFN. Additional datasets generated for this study are available on request to the corresponding author.