The SARS-CoV-2 RNA–protein interactome in infected human cells

Characterizing the interactions that SARS-CoV-2 viral RNAs make with host cell proteins during infection can improve our understanding of viral RNA functions and the host innate immune response. Using RNA antisense purification and mass spectrometry, we identified up to 104 human proteins that directly and specifically bind to SARS-CoV-2 RNAs in infected human cells. We integrated the SARS-CoV-2 RNA interactome with changes in proteome abundance induced by viral infection and linked interactome proteins to cellular pathways relevant to SARS-CoV-2 infections. We demonstrated by genetic perturbation that cellular nucleic acid-binding protein (CNBP) and La-related protein 1 (LARP1), two of the most strongly enriched viral RNA binders, restrict SARS-CoV-2 replication in infected cells and provide a global map of their direct RNA contact sites. Pharmacological inhibition of three other RNA interactome members, PPIA, ATP1A1, and the ARP2/3 complex, reduced viral replication in two human cell lines. The identification of host dependency factors and defence strategies as presented in this work will improve the design of targeted therapeutics against SARS-CoV-2.

replication 20,21 . SARS-CoV-2 preferentially infects cells in the respiratory tract, but infection of multiple organs, including the liver, has been reported 22 .
To test if our pool of antisense capture probes was suitable for the purification of SARS-CoV-2 RNAs from infected Huh7 cells, we performed RAP-MS 24 h after infection when viral replication levels were high 21 . We implemented a covalent protein capture step after the release of SARS-CoV-2 RNA-bound proteins, which enabled us to identify RNA sequences crosslinked to purified proteins ( Fig. 1a and Methods). Protein-crosslinked RNA fragments mapped to the entire length of the viral genome with near-complete sequence coverage, indicating that interactions across all viral RNA regions were captured (Extended Data Fig. 1a). Sequencing reads originating from SARS-CoV-2 RNA made up 93 and 92% of all mapped reads in 2 highly correlated replicate experiments (r = 0.994; Extended Data Fig. 1b,c).
On average, approximately 90% of all crosslinked RNA fragments originated from the SARS-CoV-2 genome in SARS-CoV-2 RNA purifications, while more than 99% of crosslinked RNA fragments from RMRP purifications mapped to the human genome (Extended Data Fig. 1d). Western blot analysis confirmed the specific capture of SARS-CoV-2 nucleocapsid protein only in SARS-CoV-2-purified samples (Extended Data Fig. 1e). The RMRP component POP1 was detected only in RMRP purifications. Together, these experiments verify the high specificity of our approach for capturing the desired RNAs and the proteins that directly bind to them.
An atlas of SARS-CoV-2 RNA-protein interactions in human cells. Next, we subjected proteins purified with RMRP and SARS-CoV-2 RNAs to tandem mass tag (TMT) labelling and relative quantification by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In two replicate experiments, we identified 699 proteins, of which 583 were detected with 2 or more unique peptides (Supplementary Table 1 and Methods). As shown in Fig. 1b, we found five known RMRP components among the ten most significantly enriched proteins in RMRP purifications.
Next, we analysed proteins enriched in SARS-CoV-2 RNA purifications and found 15 SARS-CoV-2 proteins, 6 of which were among the 20 most significantly enriched proteins (Fig. 1b,c). In addition to 5 viral proteins translated from distinct open reading frames (ORFs), 10 of the 16 non-structural proteins (NSPs), which are derived from a precursor polyprotein 24 , were detected by RAP-MS.
As expected, the SARS-CoV-2 nucleocapsid protein, which binds the viral RNA, was one of the two most significantly enriched viral proteins, followed by several known viral RNA binders, such as the endoribonuclease NSP15 (ref. 25 ), the RNA-dependent RNA polymerase (RdRP) NSP12 (ref. 26 ), the methyltransferase NSP16 (ref. 27 ), the RNA-binding protein NSP9 (ref. 28 ), the capping factor NSP10 (ref. 27 ), the primase NSP8 (ref. 26 ), the 5′-UTR binder NSP1 (ref. 29 ) and the multifunctional protein NSP3 (ref. 30 ). Remarkably, NSP3 and the most strongly enriched protein in our data, NSP6, were required for the formation of double-membrane vesicles 31 and both proteins are candidate constituents of a molecular pore complex involved in the export of RNA from coronavirus double-membrane vesicles 32 . We also found ORF3a, which binds the 5′-end of the SARS-CoV-1 genome 33 , as well as ORF9b and the S and M proteins among strongly enriched candidates. While M is known to interact with the nucleocapsid protein, a model for genomic RNA packaging further suggests a possible RNA-binding function for M 34 . An RNA-binding activity of S was not previously reported. While S covers the surface of the viral envelope, it has a transmembrane domain and an intracellular tail 35 , making it conceivable that S may indeed contact viral RNA.
Discovery of 104 human proteins that bind SARS-CoV-2 RNA. We next focused on the human proteins enriched in SARS-CoV-2 RNA purifications. We identified 276 proteins with a positive log 2 fold change. Of these, 57 were significantly enriched (adjusted P < 0.05, two-tailed t-test), which we subsequently defined as the set of core SARS-CoV-2 RNA interacting proteins (Fig. 1c). Additionally, we also defined an expanded SARS-CoV-2 RNA interactome using a relaxed false discovery rate (FDR) of less than 20% (Fig. 1c).
The expanded SARS-CoV-2 RNA interactome encompassed 104 human proteins and included 13 SARS-CoV-2-encoded proteins. The vast majority of the human RNA interactome proteins (100 proteins, 96%) have been identified previously in system-wide studies aimed at capturing proteins that crosslink to RNA 36 (Supplementary  Table 2). Comparing this expanded SARS-CoV-2 RNA interactome with the poly(A)-RNA interactome in Huh7 cells 37 , revealed high overlap between both datasets (69 proteins, 66%) (Fig. 2a). Next, we compared our direct SARS-CoV-2 RNA interactome with proteins that directly or indirectly associate with the RNA genomes of Dengue and Zika viruses in Huh7.5 cells 38 . Sixty-six proteins (63%) of the expanded SARS-CoV-2 RNA interactome also associated with the Dengue and Zika virus RNAs, while 38 proteins (36.5%) were unique SARS-CoV-2 RNA binders (Fig. 2a). Since coronaviruses form replication/transcription complexes (RTCs), we also compared the expanded SARS-CoV-2 RNA interactome to the protein content of murine coronavirus RTCs 39 and found 64 shared proteins (Supplementary Table 2).
Finally, only 10 of the 332 human proteins that bound recombinant SARS-CoV-2 proteins in uninfected cells 10 also bound directly to viral RNA in infected cells (Supplementary Table 2). These results highlight the importance of discriminating between protein-protein and RNA-protein interactions when dissecting the biology of SARS-CoV-2.

Biological functions of SARS-CoV-2 RNA-binding proteins.
To analyse the biological functions of SARS-CoV-2 RNA binders, we performed a hypergeometric gene ontology (GO) enrichment analysis on the expanded SARS-CoV-2 RNA interactome. We observed strong enrichment for GO terms linked to translational initiation (GO:0006413), nonsense-mediated decay (GO:0000184), signal-recognition particle-dependent cotranslational protein targeting to the membrane (GO:0006614) and viral transcription (GO:0019083) (Fig. 2b and Supplementary Table 3). Consistent with the enrichment of these GO terms, the importance of subgenomic mRNA translation at the endoplasmic reticulum membrane is well established for coronaviruses 40 . Further, nonsense-mediated mRNA decay was recently described as an antiviral mechanism targeting coronavirus RNAs 41 .
In agreement with the crucial role of mRNA translation, the expanded SARS-CoV-2 RNA interactome included 19 ribosomal proteins and 12 translation factors. Among the translation factors, the eukaryotic translation initiation factor 4F (EIF4F) components EIF4G1 and EIF4B are regulated by mammalian target of rapamycin (mTOR) signalling 42,43 . EIF4B is important for recruiting the 40S subunit to mRNA and both the phosphatidylinositol-3-kinase (PI3K)/mTOR and mitogen-activated protein kinase (MAPK) pathways target EIF4B to control its activity 43 . Inhibition of PI3K/Akt/ mTOR signalling has been demonstrated to suppress SARS-CoV-2 replication in Caco2 cells 8 .
To examine the connectivity of the identified SARS-CoV-2 RNA-binding proteins and their relationship to virus-associated biological processes systematically, we constructed a protein-protein association network using our expanded RNA interactome ( Fig. 2c and Supplementary Table 4). We observed a striking enrichment for physical interactions when comparing the total connectivity among RNA interactome proteins to the connectivity of equally sized networks sampled from expressed proteins (Extended Data Fig. 2 and Methods; permutation test P < 2.2 × 10 −16 ). In addition to ribosomal proteins and translation factors, many virus-associated RNA-binding proteins are prominently represented in this network (Fig. 2c). Since RNA-binding proteins can be regulated by phosphorylation, we intersected our expanded SARS-CoV-2 RNA interactome with a recent phosphoproteomic dissection of SARS-CoV-2-infected cells 7 , highlighting 30 proteins that might be dynamically phosphorylated in response to SARS-CoV-2 infection (Fig. 2d).
Identification of activated host response pathways. To gain deeper insight into host response pathways activated upon SARS-CoV-2 infection, we globally measured protein abundance changes in infected cells. We performed triplicate MS experiments on SARS-CoV-2-infected and uninfected Huh7 cells and identified 10,956 proteins with 2 or more unique peptides (Fig. 3a  and Supplementary Table 5). Among the detected proteins, 4,578 proteins were regulated (adjusted P < 0.05, two-tailed t-test) after 24 h of SARS-CoV-2 infection, which is consistent with widespread proteome regulation and agrees well with previously published data (Extended Data Fig. 3a) 8,9 . As expected, proteome samples clustered according to their infection status in a principal component analysis (Extended Data Fig. 3b). Among differentially expressed proteins, we detected 13 viral proteins and 56 proteins from our expanded SARS-CoV-2 RNA interactome (Fig. 3a).
We next performed gene set enrichment analysis (GSEA) using our proteome abundance measurements. Among the most  significantly enriched hallmark gene sets were 'TGF-β signalling' , 'TNF-α signalling via NF-κB' , 'interferon (IFN)-γ response' and 'IL-6 JAK STAT3 signalling' (Fig. 3b and Extended Data Fig. 3c), which is consistent with the induction of broad pro-inflammatory and antiviral responses in infected cells. Further, we observed significant enrichment of the gene sets 'GO regulation of MAPK cascade' , 'GO positive regulation of MAPK activity' and 'GO response to type I interferon' (Supplementary Table 6). Recent evidence indicates that these pathways are indeed highly relevant in the context of SARS-CoV-2 infections 5,7,8 . Inhibition of growth factor signalling through the MAPK pathway, which responds to and controls the production of pro-inflammatory cytokines, including TNFα and IL-6, was shown to modulate SARS-CoV-2 replication 7,8 . In agreement with recent transcriptome studies 5,6 , our proteome data suggest activation of interferon signalling upon SARS-CoV-2 infection. Among interferon-related genes, we observed significant upregulation of several major components of IFN signalling pathways, including STAT1 and IRF9, which together with STAT2 make up the interferon stimulated gene factor 3 (ISGF3) complex, their upstream components TYK2 and JAK1, as well as their downstream targets IFIT1, IFIT3, IFITM3, OAS2 and ISG15 (Fig. 3a). Other strongly upregulated IFN-related genes include BST2, SP110, UBE2L6, ADAR and TGIF1 (Supplementary Table 5). Notably, many SARS-CoV-2 RNA interactome members are linked to the IFN response. These include the strongly enriched PUM1 (ref. 45 ), YBX1 (ref. 46 57 ), DDX1 (ref. 58 ), PCBP2 (ref. 59 ), HNRNPA2B1 (ref. 60 ) and YWHAZ 61 . In conclusion, our proteome analysis verifies the induction of an appropriate host response in SARS-CoV-2-infected Huh7 cells and further supports an important role for IFN and MAPK signalling in SARS-CoV-2 infection.
Interplay between SARS-CoV-2 RNA binders and host cell proteins. As an RNA-based obligate intracellular parasite, SARS-CoV-2 must effectively interface with the host cell and rewire RNA metabolism and RNA-associated regulatory processes. In addition to controlling the RNA life cycle 62 , host RNA-binding proteins are an integral part of regulatory circuits that participate in host defence mechanisms 63,64 . To examine the interplay and connectivity between direct SARS-CoV-2 RNA binders and the host cell proteome, we used curated protein-protein interaction data to build a network that visualizes interactions between SARS-CoV-2 RNA binders and regulated host proteins (  Table 7). We considered the connectivity among all differentially expressed host proteins and those that were detected in our core RNA interactome. Interactome proteins had a greater than twofold enrichment for network connections (mean 108) when compared to proteins not detected by RAP-MS (mean 45), indicating a significant enrichment in connectivity (Wilcoxon test, P = 8.92 × 10 −08 ). To further contextualize this network, we overlaid biological processes that were enriched among regulated protein communities that associate with SARS-CoV-2 RNA binders ( Fig. 3c and Supplementary Table 8). This analysis highlighted several cellular pathways and processes emerging as highly relevant in the context of SARS-CoV-2 infections, including myeloid-mediated immunity 65 , receptor signalling 8 , protein phosphorylation 7,8 , vesicle transport 8,10 , protein folding 6,7 and translational regulation 8,66 .
Taken together, our network analysis connects RNA interactome proteins to emerging SARS-CoV-2 biology and provides a map of putative regulatory hubs in SARS-CoV-2 infections.

Genetic screens identify functional SARS-CoV-2 RNA binders.
To functionally stratify our direct RNA binders, we intersected the SARS-CoV-2 RNA interactome with a recent genome-wide CRISPR perturbation screen designed to identify host factors that affect cell survival after SARS-CoV-2 infection 67 . Out of 104 human proteins in our expanded RNA interactome, we obtained CRISPR z-scores for 94 proteins 67 ; depletion of 11 of these proteins had a statistically significant effect on SARS-CoV-2-induced cell death (Fig. 4a). Strikingly, cellular nucleic acid-binding protein (CNBP), the human protein most significantly enriched in RAP-MS, also had the most significant effect on virus-induced cell death among all SARS-CoV-2 RNA interactome members (Fig. 4a). In addition to the 11 aforementioned proteins, the direct SARS-CoV-2 RNA binders cold shock domain-containing protein E1 (CSDE1) 68 , polyadenylate-binding protein 1 (PABPC1) (refs. 11,68 ) and Ras-related protein Rab-7a (RAB7A) 11 were also identified as host factors with functional relevance in SARS-CoV-2 infections by genetic screening approaches.
CNBP functions as an antiviral regulator. CNBP is required to activate the innate immune response and has been linked to regulating the expression of pro-inflammatory cytokines in response to foreign nucleic acid sensing 69,70 . Notably, CNBP-deficient animals were highly susceptible to infections with different pathogens 69,70 . These findings are consistent with CNBP-depleted cells being sensitized to virus-induced cell death, which suggests that CNBP may act as an antiviral regulator. To corroborate the functional importance of CNBP in SARS-CoV-2 infections, we generated polyclonal Huh7 CNBP knockout cell lines using CRISPR-Cas9 (Fig. 4b). We infected CNBP knockout cells with SARS-CoV-2 and noted significantly elevated levels of intracellular viral RNA compared to matched Huh7 control cells (Fig. 4b). Thus, CNBP is indeed a functionally important SARS-CoV-2 RNA interactor.
To confirm the direct physical engagement of SARS-CoV-2 RNAs by CNBP, we performed enhanced crosslinking and immunoprecipitation (eCLIP) in SARS-CoV-2-infected Huh7 cells and quantified the enrichment of CNBP peaks relative to size-matched input libraries 71 . First, we analysed CNBP binding to the human transcriptome. Consistent with earlier reports 72 , CNBP bound to protein-coding transcripts and displayed a preference for binding within the coding sequence (CDS) of mRNAs (Fig. 4c,d). A large number of transcripts bound by CNBP in SARS-CoV-2-infected cells were previously reported as CNBP targets (approximately 46%; Supplementary Table 9). We next analysed CNBP binding to SARS-CoV-2 RNA and observed several strongly enriched binding sites in the viral genome (Fig. 4e). These data provide strong evidence for a direct interaction between CNBP and SARS-CoV-2 RNAs in infected cells and validate that RAP-MS indeed identifies direct RNA binders. Further, the finding that CNBP preferentially associates with the CDS of mature mRNAs lends credibility to its previously proposed role as a translational regulator 72 in addition to its function in regulating pro-inflammatory cytokines.

LARP1 binds genomic and subgenomic SARS-CoV-2 RNAs.
Other than CNBP, two members of the La-related protein (LARP) family, namely LARP1 and LARP4, were strongly enriched in SARS-CoV-2 RNA purifications. While LARP1 did not quite meet our significance cut-off, both LARP1 and LARP4 were among the 15 host proteins with the strongest enrichment based on overall effect size, indicating that LARP1 is very likely a SARS-CoV-2 RNA binder. Additionally, LARP1 was detected among protein-protein interactors of the nucleocapsid protein in uninfected cells 10 .
Given that LARP1 is a major downstream target of mammalian target of rapamycin complex 1 (mTORC1) (refs. 73,74 ) and inhibition of PI3K/Akt/mTOR was recently shown to inhibit SARS-CoV-2 replication in Caco2 cells 8 , we sought to characterize the LARP1-SARS-CoV-2 axis in greater detail. We performed eCLIP 71 to map direct physical interactions between LARP1 and its RNA targets. LARP1 predominantly bound protein-coding transcripts and we observed most of the enriched peaks in the CDS, followed by 5′-UTR and 3′-UTR sequences (Fig. 5a). Previous work suggested that LARP1 binds the 7-methylguanosine triphosphate (m 7 Gppp) moiety of the cap and the adjacent 5′-terminal oligopyrimidine (5′TOP) motif of mRNAs to regulate their translation 75 . Consistent with this finding, our eCLIP data revealed a strong enrichment of 5′-proximal nucleotides in 5′-UTR sequences and we recovered an oligopyrimidine motif reminiscent of TOP-like sequences in approximately 30% of all bound 5′-UTRs (Fig. 5b,c). Out of 112 mRNAs that are regulated by LARP1 downstream of mTOR 76 , we observed LARP1 binding to 84 mRNAs (75%; Supplementary Table 10). In line with the known regulatory functions of LARP1 (ref. 76 ), LARP1 target transcripts were most strongly enriched for GO terms linked to translational regulation (Supplementary  Table 11). Together, these data demonstrate that our eCLIP experiments recovered known regulatory interactions of LARP1.
Having confirmed the quality of our eCLIP experiment on host RNAs, we next characterized LARP1 binding to SARS-CoV-2 RNAs and found several regions of enrichment that coincided with oligopyrimidine sequences (Fig. 5d). Notably, we observed LARP1 binding to the first 70 nucleotides at the 5′-end of the SARS-CoV-2 genome, which corresponds to the viral 5′-leader sequence 77 and contains a TOP-like motif instance (Fig. 5d). Binding to the 5′-leader, which is present in all viral subgenomic mRNAs, suggests a direct association of LARP1 with subgenomic mRNAs.

LARP1 represses SARS-CoV-2 replication.
To determine the impact of LARP1 depletion on SARS-CoV-2 replication, we generated four clonal LARP1 knockout cell lines using CRISPR-Cas9 in HEK293 cells (Extended Data Fig. 4a). We infected cells with SARS-CoV-2 and measured intracellular viral RNA levels and the production of infectious virus. Compared to wild-type (WT) cells, LARP1 knockout cells displayed approximately fivefold higher levels of intracellular viral RNA and a similar increase in the production of infectious virus (Fig. 5e). Conversely, transient overexpression of LARP1 fused to green fluorescent protein (GFP) in WT cells led to a significant reduction of viral RNA and infectious virus when compared to GFP expression alone ( Fig. 5f and Extended Data Fig.  4b). Next, we complemented LARP1 knockout cells with transiently expressed LARP1-GFP proteins (Fig. 5g, Extended Data Fig. 4c).
In all knockout cell lines, we observed a clear reduction in intracellular viral RNA that approached WT levels when compared to cells transfected with GFP alone. These experiments established that LARP1 functions as a repressor of SARS-CoV-2 replication in infected human cells.
RyDEN suppresses ribosomal frameshifting during SARS-CoV-2 RNA translation. LARP1 interacts with PABPC1 and both LARP1 and PABPC1 have been proposed to reside in the same ribonucleoprotein complex with RyDEN 54 , all of which were enriched in RAP-MS experiments. In addition to being an IFN-induced protein, RyDEN suppresses Dengue virus production in infected cells 54 and inhibits programmed -1 ribosomal frameshifting (-1FS) in human immunodeficiency virus type 1 (HIV-1) infections 55 .
In coronaviruses, production of RdRP requires translation of the ORF1b gene, which is controlled by -1FS. For SARS-CoV-2, it is presently unknown if the efficiency of -1FS is important for the viral life cycle 78 . To dissect if RyDEN can modulate the frequency of -1FS in SARS-CoV-2, we generated a dual-colour fluorescence reporter system to quantify frameshifting efficiency in response to RyDEN induction, as seen upon SARS-CoV-2 infection (Extended Data Fig.  4d and Methods). Using a reporter containing the HIV-1 frameshift element as a positive control, we confirmed that overexpression of RyDEN fused to enhanced cyan fluorescent protein (eCFP) suppressed -1FS when compared to eCFP expression alone (Fig. 5h). Importantly, overexpression of RyDEN also led to a significant reduction of -1FS during translation of the SARS-CoV-2 frameshift element (Fig. 5h). Together, our results show that RyDEN is induced upon SARS-CoV-2 infection, associates with the SARS-CoV-2 RNA in infected cells and modulates the efficiency of SARS-CoV-2 -1FS.
Pharmacological inhibition of interactome proteins restricts viral replication. Next, we tested if targeting the SARS-CoV-2 RNA interactome and its associated pathways with known inhibitors is effective in restricting viral replication. We selected four inhibitors that target components of our expanded RNA interactome: PPIA; ARP2; ATP1A1; and DDX3X. While DDX3X is a DEAD-box RNA helicase and canonical RNA-binding protein, PPIA, ARP2 and ATP1A1 are non-classical RNA binders that are nonetheless robustly detected among RNA-binding proteins in Huh7 cells 36,37,79 . In addition to Huh7 cells, we evaluated all inhibitors in Calu3 cells, a human lung epithelial cell line that is naturally susceptible to SARS-CoV-2 infection.
We observed a dose-dependent inhibition of intracellular viral RNA expression accompanied by a reduction in the production of infectious virus for the PPIA inhibitor cyclosporin A (Extended Data Fig. 5a,b), the ARP2/3 complex inhibitor CK-548 and the ATP1A1 inhibitor ouabain (Fig. 6a,b). The observed effect was highly consistent between Calu3 and Huh7 cells (Fig. 6a,b). While CK-548 treatment reduced cell viability at the highest concentration in Huh7 cells, we did not observe such effects at identical concentrations in Calu3 cells. All other efficacious inhibitors had no apparent effect on cell viability (Extended Data Fig. 5c,d). Unlike the three aforementioned compounds, inhibition of DDX3X only led to a moderate reduction of intracellular viral RNA and infectious virus in Calu3 cells at the highest concentration (Fig. 6a,b).
Beyond inhibiting direct RNA binders, we also targeted mTORC1, the upstream regulatory complex that controls LARP1 activity. Consistent with LARP1 restricting SARS-CoV-2 replication, we observed that inhibiting mTORC1/2 resulted in reduced viral replication in Huh7 and Calu3 cells (Fig. 6a,b). These findings agree well with previous results showing that mTORC1 phosphorylates LARP1, which leads to a translational de-repression of LARP1 target mRNAs 76 . Indeed, recent phosphoproteomic surveys demonstrate that LARP1 undergoes dynamic phosphorylation in response to SARS-CoV-2 infection 7,8 .
Inhibition of another upstream regulator, TANK-binding kinase 1, which interacts with the SARS-CoV-2 RNA binders DDX3X 52 and ANXA1 (ref. 57 ), increased the levels of viral RNA and infectious virus in A549-ACE2 cells, but did not show a consistent effect in Huh7 or Calu3 cells (Extended Data Fig. 5a,b). Together, our experiments demonstrate that RNA interactome proteins represent viable targets for inhibiting SARS-CoV-2 replication. The SARS-CoV-2 RNA interactome provides valuable starting points for future mechanistic studies and may help developing new antiviral approaches for COVID-19.

Discussion
Decoding how the RNA genomes of pathogenic RNA viruses interface with the host cell proteome has been a long-standing challenge. In this study, we provide detailed molecular insights into the identity of host factors and cellular machinery that directly and specifically bind SARS-CoV-2 RNAs during infection of human cells. We integrate CRISPR perturbation data and perform genetic and pharmacological validation experiments that together suggest functional roles for 18 RNA interactome proteins in SARS-CoV-2 infections. Quantification relative to 18S rRNA and GFP-transfected WT cells is shown. P values were determined using an unpaired two-tailed t-test. e-g, All values are the mean ± s.d. (n = 3 independent infections) h, Quantification of ribosomal frameshifting efficiency using a dual-fluorescence translation reporter (Extended Data Fig. 4d) in HEK293 cells is shown. Data were normalized to cells transfected with eCFP (n = 6 independent transfections, except for control RNA n = 4). Values are the mean ± s.d. ****P < 0.0001, ***P < 0.001, **P < 0.01, *P < 0.05; NS, not significant; FSE, frameshift element.
Beyond identifying proteins that bind SARS-CoV-2 RNAs, we globally mapped where CNBP and LARP1 contact viral and human RNA and report binding preferences that are consistent with previously described regulatory functions of both proteins. While we show that CNBP acts as an antiviral factor, it remains to be determined if its role as a regulator of mRNA translation or its effect on cytokine expression is critical for this function. We provide strong genetic evidence for a functional role of LARP1 in restricting SARS-CoV-2 replication. Remarkably, the SARS-CoV-2 5′-leader contains a TOP-like sequence motif that is bound by LARP1 in infected cells. While the TOP-like sequence is still several nucleotides away from the 5′-end of the SARS-CoV-2 leader, it is tempting to speculate that binding of LARP1 would negatively influence translation of SARS-CoV-2 RNAs similar to LARP1-mediated translational repression of host-encoded 5′TOP mRNAs. In addition to genetic perturbation, we inhibited SARS-CoV-2 RNA binders pharmacologically. Notably, all host proteins and complexes that are effectively targeted by these inhibitors have previously been linked to viral diseases: (1) PPIA is involved in protein folding and has a well-documented impact on the replication of viruses 80,81 . Its direct interaction with SARS-CoV-2 RNA expands these previously described functions. While the PPIA inhibitor cyclosporin A has immunosuppressive properties, the non-immunosuppressive cyclosporin A analogue alisporivir may offer greater translational potential 82 ; (2) a role for the RNA-binding metabolic enzyme ATP1A1 37 in coronavirus and respiratory syncytial virus infections has been reported previously 83,84 . ATP1A1 had a significant effect on virus-induced cell death in a SARS-CoV-2 CRISPR perturbation screen 67 . Hence, both genetic and pharmacological evidence point to ATP1A1 as an important SARS-CoV-2 host factor; (3) ARP2 is part of the actin-related protein 2/3 complex and contributes to regulating cell shape and motility, which can affect intracellular pathogens 82 . ARP2 has been identified as a respiratory syncytial virus host factor and is involved in filopodia formation 85 . Recent work demonstrated that SARS-CoV-2 infection induced a dramatic increase in filopodia and viral particles localized to these actin-rich protrusions 7 .
Our work highlights opportunities for targeting proteins or pathways linked to the SARS-CoV-2 RNA interactome to interfere with viral infection. We believe that our approach provides a general roadmap for dissecting the biology of RNA viruses and the interactions between hosts and pathogens at the molecular level.
Generation of LARP1 knockout cell lines using CRISPR-Cas9. To generate the LARP1 CRISPR knockout cells, we used the pX335-U6-chimeric-BB-CBh-hSpCas 9n(D10A) nickase (a generous gift from F. Zhang) together with GTTGGGT GGCAGTTTACGGGT and GCCACCCAAGAAGGACATGA as guide sequences. HEK293 cells were transfected with TransIT-X2 (Mirus Bio) and selected with 2 µg ml −1 of puromycin in DMEM for 48 h and with 1 µg ml −1 for another 48 h. We picked single colonies and screened for LARP1 deletion by western blotting.
Generation of CNBP knockout cell lines using CRISPR-Cas9. A total of 2.5 × 10 5 Huh7 cells per well were seeded in a 6-well plate and transfected the next day with 2.5 µg of a commercially available CNBP CRISPR-Cas9 knockout plasmid (catalogue no. sc-404090; Santa Cruz Biotechnology) using 2 µl of Lipofectamine 2000 (Thermo Fisher Scientific) per 1 µg of DNA. A plasmid containing a puromycin resistance gene was cotransfected as the selection marker. Control cells were transfected only with the puromycin resistance plasmid. Successfully transfected cells were selected with puromycin (5 µg ml −1 ) starting at 24 h post-transfection for 2 d. CNBP expression in polyclonal cell populations was analysed by western blot.
Virus production. We used previously described patient-derived SARS-CoV-2 isolates 86,87 propagated on Vero cells. To make high-titre viral stocks, we used TMPRSS2-Vero E6 cells, which were infected at a multiplicity of infection (MOI) of 0.005 plaque-forming units (p.f.u.) per cell for virus propagation. After 1 h of incubation at 37 °C, the inoculum was removed, cells were washed with PBS and OptiMEM (Gibco) containing 1% FCS was added. At 48 h post-infection, the cell culture supernatant was cleared by centrifugation (500g for 5 min) and aliquoted. Viral titres were determined by plaque assay on TMPRSS2-Vero E6 cells and by crystal violet staining.

Virus infections.
In general, the virus inoculum was prepared in DMEM containing 5% FCS and 100 U ml −1 of streptomycin and 100 mg ml −1 of penicillin. Cells were washed with PBS and incubated with the inoculum for 1 h at 37 °C. The inoculum was removed and fresh DMEM supplemented with 5% FCS; 100 U ml −1 of streptomycin and 100 mg ml −1 of penicillin were added to the cells.

RAP-MS.
RAP-MS was carried out as described previously 15 with the following modifications: to capture endogenous SARS-CoV-2 RNAs, we designed and synthesized 5′ biotinylated 90-mer DNA oligonucleotides (Integrated DNA Technologies) antisense to the complementary target RNA sequence. We used 67 probes such that one probe binding site occurred roughly every 400 bases in the approximately 30-kilobase (kb) SARS-CoV-2 genome and excluded regions that matched to human transcripts or genomic regions as described previously 88,89 .
For the SARS-CoV-2 RNA and RMRP antisense purifications, we grew ten 10-cm tissue culture plates of Huh7 cells per replicate. We prepared two replicates for SARS-CoV-2 RNA and RMRP purifications and included two non-crosslinked control samples that were used for RMRP purifications. SARS-CoV-2 infection was carried out with a previously described isolate 87 at an MOI of 10 for 24 h. Cells were washed once with PBS and then crosslinked on ice using 0.8 J cm −2 of 254 nm UV light in a GS Gene Linker (Bio-Rad Laboratories). Cells were then lysed on the tissue culture plate by adding 1 ml of RAP lysis buffer (10 mM of Tris pH 7.5, 500 mM of LiCl, 0.5% dodecyl maltoside, 0.2% SDS, 0.1% sodium deoxycholate, EDTA-free protease inhibitor cocktail (Thermo Fisher Scientific) and murine RNase inhibitor (New England Biolabs)). Lysates were then collected and flash-frozen in liquid nitrogen for storage at −80 °C. All subsequent steps were carried out as described previously 15 .

RAP-MS protein digestion and TMT labelling.
RAP-captured proteins were resuspended in 40 μl of 8 M of urea in 50 mM of Tris-HCl, followed by reduction with 4 mM of dithiothreitol (DTT) for 30 min at room temperature and alkylation with 10 mM of iodoacetamide for 45 min at room temperature in the dark. All six samples were then digested with 0.1 μg of Lys-C for 2 h, followed by a reduction of the urea concentration to <2 M and continued digestion with 0.5 μg of trypsin overnight. Reactions were quenched with formic acid at a final concentration of 5% and then desalted by reverse-phase C18 stage tips as described previously 90 and dried down. Peptides were then resuspended in 50 μl of 50 mM of HEPES buffer and isobarically labelled using 400 μg of TMT 6-plex (TMT6) isobaric labelling reagent (Thermo Fisher Scientific). The labelling reactions were then quenched with 4 μl of 5% hydroxylamine; samples were mixed together and dried. The sample was fractionated by SCX stage tip strategy using three pH cuts at 5.15, 8.25 and 10.3 as described previously 90 .

Proteome analyses of SARS-CoV-2-infected cells.
For the proteome measurements, we expanded the Huh7 cells to two 10-cm tissue culture plates per replicate. Cells were infected with a previously described SARS-CoV-2 isolate 87 at an MOI of 10 and incubated for 24 h before being collected. Three process replicates of infected and non-infected cell line samples were generated. Cells were lysed in 8 M of urea, 75 mM of NaCl, 50 mM of Tris pH 8.0, 1 mM of EDTA, 2 µg ml −1 aprotinin, 10 μg ml −1 of leupeptin, 1 mM of phenylmethylsulfonyl fluoride, 10 mM of NaF, phosphatase inhibitor cocktail 2 (PIC2) (Sigma-Aldrich), PIC3 (Sigma-Aldrich) and 10 mM of sodium butyrate. Benzonase was added to digest nucleic acids and DNA was sheared using a probe sonicator (10% amplitude, 0.7 s on, 2.3 s off, 6 min 15 s total). Cell debris was removed by centrifugation and lysates were flash-frozen for storage. All samples were prepared for MS analysis using an optimized workflow as described previously 91 . Briefly, lysed samples were reduced, alkylated and digested by LysC for 2 h, followed by overnight digestion with trypsin. Digestions were quenched with formic acid and all peptide samples were desalted using reverse-phase C18 Sep-Pak cartridges. Samples were then quantified using the Pierce bicinchoninic acid protein assay and measured into 500-μg aliquots for isobaric labelling. Peptides were isobarically labelled with TMT6 following the reduced TMT protocol 92 . After confirming 98% or greater label incorporation, samples were mixed together and desalted. The resulting sample was then fractionated by offline high pH reversed-phase chromatography and concatenated into 24 fractions for analysis using online LC-MS/MS 91 .  93 ) and 23 new unannotated SARS-CoV-2 ORFs whose translation is supported by ribosome profiling 94 , yielding a total of 42,337 proteins. Among the 28 annotated SARS-CoV-2 proteins, we opted to omit the full-length ORF1ab to simplify peptide-to-protein assignment, and instead represented ORF1a and ORF1ab as the mature 16 individual NSPs that resulted from proteolytic processing of the 1a and 1ab polyprotein. Finally, we added to the database the UniProt entry for ORF9b. We further added the D614G variant of the SARS-CoV-2 spike protein that is commonly observed in European and American virus isolates. Spectrum Mill search parameters included: instrument setting of ESI-QEXACTIVE-HCD-v4-35-20; parent and fragment mass tolerance of 20 parts per million; trypsin allow P enzyme setting; and up to 4 missed cleavages. Carbamidomethylation and TMT labelling at lysine (with and without labelling at the N terminus) were set as fixed modifications, while variable modifications included acetylation of protein N termini, oxidized methionine, deamidation of asparagine and pyroglutamic acid at the peptide N-terminal glutamine. Peptide spectrum match score thresholding was optimized to achieve a target-decoy FDR of 1.2% for the validation of spectra. Peptide-level auto-validation was followed by protein polishing with an FDR of 0% at the protein level and a minimum score of 13. The Spectrum Mill generated proteome-level export from the RAP-MS and proteome datasets, which were filtered for human proteins identified by two or more distinct peptides, SARS-CoV-2 proteins and unannotated virus ORFs, were used for further statistical analyses. Five of the SARS-CoV-2 NSPs (NSP6, NSP15, NSP16, NSP9 and NSP1) identified by a single, highly scoring distinct peptide were kept in the dataset. Keratins were excluded from the RAP-MS data. Protein quantification was achieved by taking the ratio of TMT reporter ion for each sample/channel over the median of all six channels. A moderated two-sample t-test was applied to compare SARS-CoV-2 RNA and RMRP samples after mean normalization and SARS-CoV-2-infected and non-infected samples after median-median absolute deviation (MAD) normalization of RAP-MS and proteome datasets, respectively. A Benjamini-Hochberg-corrected P value threshold of 0.05 was used to assess significantly regulated proteins in each of the datasets.

LC-MS/MS analysis (RAP-MS and proteome
Covalent protein capture and sequencing of crosslinked RNA. To capture RNA sequences covalently crosslinked to proteins purified with RAP-MS, we carried out RAP as described above. After our pilot RAP-MS experiment (Extended Data Fig. 1a,b), SARS-CoV-2-bound proteins were eluted from streptavidin beads by heat fragmentation of RNA (3 min at 91 °C in 100 mM of HEPES pH 7.5, 5 mM of MgCl 2 , 100 mM of KCl, 0.02% Triton X-100). For subsequent RAP-MS experiments, we replaced heat fragmentation with ribonuclease (RNase) H digestion, using 7.5 μl of RNase H (New England Biolabs), 2 μl of TURBO DNase (Thermo Fisher Scientific) in 55.5 μl of RNase H buffer (100 mM of HEPES pH 7.5, 75 mM of NaCl, 3 mM of MgCl 2 , 0.125% N-lauroylsarcosine (NLS), 0.025% sodium deoxycholate, 2.5 mM of tris(2-carboxyethyl)phosphine (TCEP)) and incubating for 30 min at 37 °C. Following the elution of proteins, supernatants were transferred into new tubes and beads were washed once with RNase H buffer. Wash fractions were pooled with eluates and stored on ice. The next steps were described previously in similar form by Quinodoz et al. 95 . We separated 100 μl of NHS magnetic beads (Thermo Fischer Scientific) on a magnet and discarded the supernatant. We then washed them with 1 ml of 1 mM of ice-cold HCl, followed by a quick rinse in 1 ml of ice-cold PBS. After removing the PBS, we immediately added the stored eluates to the prepared beads. Binding was carried out overnight at 4 °C on a rotating wheel. The next day, we quenched the NHS beads by adding 1 ml of 0.5 M Tris pH 8.0 and incubating for 1 h at 4 °C. We then washed the beads 4 times in 1 ml of modified RLT buffer (RLT buffer supplied by QIAGEN with added 10 mM of Tris pH 7.5, 1 mM of EDTA, 1 mM of EGTA, 0.2% NLS, 0.1% Triton X-100 and 0.1% NP-40). Next, we washed the beads twice more in 1 ml of 1× PBS, 5 mM of EDTA, 5 mM of EGTA, 5 mM of DTT, 0.2% Triton X-100, 0.2% NP-40, 0.2% sodium deoxycholate and incubated each washing step for 5 min at 55 °C. These heated washing steps were followed by two additional washes in the same buffer at room temperature. Subsequently, beads were rinsed on the magnet in 1× FastAP buffer (10 mM of Tris pH 7.5, 5 mM of MgCl 2 , 100 mM of KCl, 0.02% Triton X-100). Next, end repair was carried out by resuspending the beads in 50 μl After proteinase K digestion, we separated beads on a magnet, transferred the supernatant into a new tube and extracted RNA using phenol-chloroform extraction. All subsequent manipulation steps were carried out as described in the eCLIP library preparation protocol 71 , starting with the reverse transcription of recovered RNA fragments. eCLIP. For the eCLIP experiments, we grew approximately 24 × 10 6 Huh7 cells and infected them with SARS-CoV-2 at an MOI of 5 PFU per cell; 24 h after infection, culture medium was removed, cells were briefly rinsed with PBS and subjected to UV irradiation with a total dose of 0.8 J cm −2 . Cells were scraped in PBS using a flexible rubber scraper, pelleted at 200g for 5 min and lysed by adding 2× CLIP lysis buffer (100 mM of Tris-HCl pH 7.4, 300 mM of NaCl, 2 mM of EDTA, 2% (v/v) NP40, 1% sodium deoxycholate, 0.5 mM of DTT). After a 30-min incubation at room temperature, lysates were stored at −80 °C.
Frozen lysates were combined with an equal amount of nuclease-free water to adjust the lysis buffer to a 1× concentration. Subsequent steps were performed as described in the eCLIP protocol 71 with the following modifications. Immunoprecipitates were washed twice in 1 ml of CLIP lysis buffer, twice in immunoprecipitation wash buffer (50 mM of Tris-HCl pH 7.4, 300 mM of NaCl, 1 mM of EDTA, 1% (v/v) NP40, 0.5% sodium deoxycholate, 0.25 mM of DTT), followed by two washes in 50 mM of Tris-HCl pH 7.4, 1 mM of EDTA and 0.5% (v/v) NP40. All other steps were carried out as described in the eCLIP method 71 . We used the following antibodies for the immunoprecipitation reactions: CNBP antibody (catalogue no. 67109-1-Ig; Proteintech) and LARP1 (catalogue no. A302-087A; Bethyl Laboratories).

Infection of Huh7 CNBP knockout cells.
A total of 1 × 10 5 cells were seeded per well of a 24-well plate. The next day, cells were infected with SARS-CoV-2 at an MOI of 0.5 PFU per cell as described above. At the indicated time points post-infection, supernatants were collected for plaque assay analyses and cells were lysed for RT-qPCR analyses.
Infection of HEK293 LARP1 knockout cells. A total of 1.5 × 10 5 cells were seeded per well of a poly-L-lysine-coated 24-well plate. For the rescue experiments, cells were transfected the next day with 500 ng per well LARP1-GFP overexpression plasmid or pEGFP-C1 as the control using 3 µl of TransIT-X2 transfection reagent per 1 µg of DNA. At 24 h post-transfection, cells were infected with SARS-CoV-2 at an MOI of 0.5 PFU per cell as described above. At the indicated time points post-infection, supernatants were collected for the plaque assay analyses and cells were lysed for the RT-qPCR analyses.
RNA extraction and RT-qPCR. Cells were lysed in 300 µl of TRIzol per well and RNA was extracted using the Direct-zol RNA Microprep Kit (Zymo Research). RNA was reverse-transcribed into complementary DNA using the AffinityScript Multiple Temperature Reverse Transcriptase system (Agilent Technologies) according to the manufacturer's instructions. Viral RNA was quantified by qPCR using the PowerUp SYBR Green Master Mix (Thermo Fisher Scientific) and primers specific to the SARS-CoV-2 RdRP gene (forward: GTGARATGGTCATGTGTGGCGG, reverse: CARATGTTAAASACA CTATTAGCATA) and 18S ribosomal RNA (forward: ATGGCCGTTCTTAGTTG GTG, reverse: GAACGCCACTTGTCCCTCTA). We calculated the differences in RNA expression using the ΔΔ CT I method versus 18S. To achieve power to detect small effects in gene expression, we performed four technical qPCR replicates from the same cDNA and took the median value for further analysis.
Plaque assay. TMPRSS2-Vero E6 cells were infected with 10-fold serial dilutions of the virus-containing sample in DMEM with 1% FCS. After a 1-h incubation, the inoculum was removed and cells were overlayed with 0.6% (w/v) methylcellulose (Carl Roth) in MEM (Gibco) supplemented with 25 mM of HEPES, 0.44% NaHCO 3 , 2 mM of GlutaMAX (Gibco), 100 U ml −1 of streptomycin, 100 mg ml −1 of penicillin and 5% FCS. At 4 d post-infection, cells were fixed and stained by adding 2× staining solution (0.23% crystal violet, 8% formaldehyde, 10% ethanol) directly to the medium for 2 h. Cells were washed with H 2 0 and plaques were counted to determine viral titres.
Cell viability assay. For the cell viability assays, cells were seeded in 96-well plates (2 × 10 4 cells per well for Huh7 and A549-ACE2 cells, 6 × 10 4 cells per well for Calu3 cells) and treated with inhibitors as described for the infection assays. After 24 h (Calu3 cells) or 48 h (Huh7 and A549-ACE2 cells) of treatment, cell viability was assessed using the CellTiter-Glo reagent (Promega Corporation) according to the manufacturer's instructions.
Quantification of ribosomal frameshifting. HEK293 cells were transiently transfected with either the control or frameshifting construct of our dual-colour enhanced GFP (eGFP)-mCherry translation reporter outlined in Extended Data Fig. 4d. Briefly, cells transfected with this reporter express a single fluorescent protein (eGFP) when the 0 reading frame is translated (Extended Data Fig. 4d). Expression of a second fluorescent protein (mCherry) downstream of eGFP is dependent on -1FS, which prevents translation of an inframe stop codon. Thus, the ratio between mCherry and eGFP directly correlates to -1FS efficiency. As a normalization control, we used a construct lacking a stop codon in the 0 reading frame, leading to the expression of eGFP and mCherry in equal ratios.
RyDEN was expressed as fusion protein with eCFP. In the control experiments, a plasmid only carrying eCFP was used. Using flow cytometry (Novocyte Quanteon), eCFP + cells were analysed for the ratio between mCherry and eGFP, providing a direct readout of ribosomal frameshifting efficiency. Accordingly, frameshifting efficiency was calculated using the ratio of mCherry to eGFP observed with the frameshifting reporter construct relative to the mCherry/eGFP ratio observed with the control construct (Extended Data Fig. 4d).

Computational analyses. Protein-protein interaction network.
To establish protein-protein interactions for the proteins identified from the MS experiments, we utilized STRING v.11 (ref. 96 ). For all network and interaction inferences, we used the 'combined score' from STRING, which utilizes both physical and functional interactions. Specifically, for the RAP-MS network (Fig. 2), we seeded all proteins detected with an adjusted P < 0.2 and positive log fold change from the moderated t-test between SARS-CoV-2 RNA and RMRP purifications. The edges between interacting proteins were included for those above a combined interaction score of 550. To generate the combined RAP-MS and proteome MS network, we seeded nodes where the adjusted P < 0.05 for either of the assays. Edges between RAP-MS and proteome MS nodes were included for combined interaction scores exceeding 700.
Gene set and pathway enrichment analysis. First, we performed a hypergeometric GO enrichment analysis for the expanded SARS-CoV-2 RNA interactome proteins using the DAVID tool (v.6.8, https://david.ncifcrf.gov/tools.jsp) and applying default settings (Fig. 2b) (Fig. 3b). Genes were ranked based on the product of the log 2 fold change and the log 10 moderated t-test P value between SARS-CoV-2 and mock treatments. To establish enriched terms for communities within the interactome network (Fig. 3c), we considered all regulated genes in the proteome measurements interacting with a specific direct binder and computed enrichments using the C5 biological processes gene sets. eCLIP and RNA sequencing analysis. Paired-end sequencing reads from (1) eCLIP experiments or (2) sequencing of crosslinked RNA fragments after RAP-MS, were trimmed using a custom Python script that simultaneously identified the unique molecular identifier associated with each read. These trimmed reads were then aligned to the SARS-CoV-2 reference genome (NC_045512.2 contig) using the Burrows-Wheeler Aligner (v.0.7.17) 99 . Next, we removed PCR duplicates using the unique molecular identifier-aware deduplication functionality in Picard's MarkDuplicates (v.2.22.0). Finally, enriched regions of protein binding were identified using model-based analysis of ChIP-seq 2 (MACS2 v.2.2.7) 100 to model the fold change between per-million fragment normalized counts (signal per million mapped reads) of the treated and control samples. Visualizations of the region were rendered from the PCR-deduplicated .bam files using the Integrative Genomics Viewer. CLIP peak annotations and overlaps were determined using custom functions and the GenomicRanges package (v.1.40.0) 101 . Meta-gene enrichment plots were computed using deepTools (v.3.4.3) 102 . To establish the binding motif of the LARP1 CLIP peaks, we performed a de novo motif enrichment using MEME (v.5.2). 103 via a strand-aware sequence enrichment for peaks that overlapped a single 5′-UTR in our hg38 reference.
Reporting Summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability
The original mass spectra for all experiments and the protein sequence databases used for the searches have been deposited with the MassIVE repository (https:// massive.ucsd.edu) and can be accessed at ftp://massive.ucsd.edu/MSV000085734/. The high-throughput sequencing data have been deposited with the Gene Expression Omnibus under the accession no. GSE154430. Source data are provided with this paper.

Code availability
The computer code for the custom analyses is publicly available at https:// munschauerlab.github.io/SCoV2-proteome-atlas/.      . Expression of LARP1 was evaluated relative to Tubulin. b, Western blot of HEK293 cells transiently overexpressing (OE) GFP or LARP1-GFP proteins at 48 h post transfection. Arrows indicate endogenous LARP1 proteins and GFP-tagged LARP1. c, Western blot of four different HEK293 LARP1 knockout cell lines transiently transfected with plasmids encoding GFP or LARP1-GFP proteins at 48 h post transfection. Experiments were repeated at least two times. d, Schematic of dual-fluorescence translation reporter to quantify ribosomal frameshifting efficiency. The depicted control construct contains enhanced GFP (eGFP) and mCherry in an in-frame orientation, leading to the production of both fluorescent proteins separated by a self-cleaving 2A peptide when the 0 reading frame is translated. In the frameshift construct depicted below, eGFP and mCherry are separated by an in-frame stop codon, preventing the production of mCherry when the 0 reading frame is translated. −1FS leads to the production of eGFP and mCherry and the ratio between both fluorescent proteins is a direct measure of frameshifting efficacy. −1FS: -1 ribosomal frameshifting. Last updated by author(s): Nov 27, 2020 Reporting Summary Nature Research wishes to improve the reproducibility of the work that we publish. This form provides structure for consistency and transparency in reporting. For further information on Nature Research policies, see our Editorial Policies and the Editorial Policy Checklist.

Statistics
For all statistical analyses, confirm that the following items are present in the figure legend, table legend, main text, or Methods section.
n/a Confirmed The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Computer code for custom analyses is publicly available at: https://munschauerlab.github.io/SCoV2-proteome-atlas/.
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

Data
Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability The original mass spectra for all experiments, and the protein sequence databases used for searches have been deposited in the public proteomics repository MassIVE (https://massive.ucsd.edu) and are accessible at ftp://massive.ucsd.edu/MSV000085734/.