key: cord-341502-jlzufa28
authors: Lee, Sungyul; Lee, Young-suk; Choi, Yeon; Son, Ahyeon; Park, Youngran; Lee, Kyung-Min; Kim, Jeesoo; Kim, Jong-Seo; Kim, V. Narry
title: The SARS-CoV-2 RNA interactome
date: 2020-11-02
journal: bioRxiv
DOI: 10.1101/2020.11.02.364497
sha: 
doc_id: 341502
cord_uid: jlzufa28

SARS-CoV-2 is an RNA virus whose success as a pathogen relies on its ability to repurpose host RNA-binding proteins (RBPs) to form its own RNA interactome. Here, we developed and applied a robust ribonucleoprotein capture protocol to uncover the SARS-CoV-2 RNA interactome. We report 109 host factors that directly bind to SARS-CoV-2 RNAs including general antiviral factors such as ZC3HAV1, TRIM25, and PARP12. Applying RNP capture on another coronavirus HCoV-OC43 revealed evolutionarily conserved interactions between viral RNAs and host proteins. Network and transcriptome analyses delineated antiviral RBPs stimulated by JAK-STAT signaling and proviral RBPs responsible for hijacking multiple steps of the mRNA life cycle. By knockdown experiments, we further found that these viral-RNA-interacting RBPs act against or in favor of SARS-CoV-2. Overall, this study provides a comprehensive list of RBPs regulating coronaviral replication and opens new avenues for therapeutic interventions.

subgenomic RNAs (sgRNAs) (Kim et al., 2020a) . All canonical viral (+) RNAs share the common 5′ end sequence called the leader sequence and the 3′ end sequences. The sgRNAs are generated via discontinuous transcription which leads to the fusion between the 5′ leader sequence and the "body" parts containing the downstream open reading frames (Sola et al., 2015) that encode structural proteins (S, E, M, and N) and accessory proteins (3a, 3c, 6, 7a, 7b, 8 , and 9b) (Kim et al., 2020a) .

To accomplish this, coronaviruses employ unique strategies to evade, modulate, and utilize the host machinery (Fung and Liu, 2019) . For example, the gRNA molecules must be kept in an intricate balance between translation, transcription, and encapsulation by recruiting the right host RNA-binding proteins (RBPs) and forming specific ribonucleoprotein (RNP) complexes. As host cells counteract by launching RBPs such as RIG-I, MDA5, and Toll-like receptors (TLRs) to recognize and eliminate viral RNAs, the virus needs to evade the immune system using its components to win the arms race between virus and host. How such stealthy devices are genetically coded in this compact RNA genome is yet to be explored (Snijder et al., 2016) . Thus, the identification of the RBPs that bind to viral transcripts (or the SARS-CoV-2 RNA interactome)

is key to uncovering the molecular rewiring of viral gene regulation and the activation of antiviral defense systems.

Biochemical techniques for studying RNA-protein interactions have been developed (Ramanathan et al., 2019) with the advancement in protein-centric methods such as CLIP-seq (crosslinking immunoprecipitation followed by sequencing) . In CLIP-seq experiments, RNP complexes are crosslinked by UV irradiation within cells to identify direct RNA-protein interactions. The protein of interest is immunoprecipitated to identify the associated RNAs (Lee and Ule, 2018; Van Nostrand et al., 2020) . More recently, RNA-centric methods have also been developed to profile the mRNA interactome and RNP complexes (Roth and Diederichs, 2015) . After UV irradiation, the RNA of interest is purified with oligonucleotide probes and the crosslinked proteins are identified by mass spectrometry. For example, RAP-MS exhibits compelling evidence of highly confident profiling of proteins that bind to a specific RNA owing to a combination of long hybridization probes and harsh denaturing condition (Engreitz et al., 2013; McHugh et al., 2015) .

In this study, we developed a robust RNP capture protocol to define the repertoire of viral and host proteins that associate with the transcripts of coronaviruses, namely SARS-CoV-2 and HCoV-OC43. Network and transcriptome analyses combined with knockdown experiments revealed host factors that link the viral RNAs to mRNA regulators and putative antiviral factors.

To identify the viral and host proteins that directly interact with the genomic and subgenomic RNAs of SARS-CoV-2, we modified the RNA antisense purification coupled with mass spectrometry (RAP-MS) (McHugh and Guttman, 2018) protocol which was developed to profile the interacting proteins of a particular RNA species ( Figure 1A) . Briefly, cells were first detached from culture vessels and then irradiated with 254 nm UV to induce RNA-protein crosslink while preserving RNA integrity. Crosslinked cells were treated with DNase and lysed with an optimized buffer condition to homogenize and denature the proteins in high concentration.

Massive pools of biotinylated antisense 90-nt probes were used to capture the denatured RNP complexes in a sequence-specific manner. After stringent washing and detergent removal, the RNP complexes were released and digested by serial benzonase and on-bead trypsin treatment.

These modifications to the RAP-MS protocol enabled robust and sensitive identification of proteins directly bound to the RNA target of interest (see Methods for detailed explanation).

We designed two separate pools of densely overlapping 90-nt antisense probes to achieve an unbiased perspective of the SARS-CoV-2 RNA interactome ( Figure 1B and Table S1 ). The SARS-CoV-2 transcriptome consists of (1) a genomic RNA (gRNA) encoding 16 nonstructural proteins (nsps) and (2) multiple subgenomic RNAs (sgRNAs) that encode structural and accessory proteins (Sola et al., 2015) . The sgRNAs are more abundant than the gRNA (Kim et al., 2020a) . The first pool ("Probe I") consists of 707 oligos tiles every 30 nucleotides across the ORF1ab region (266:21553, NC_045512.2) and thus hybridizes specifically with the gRNA molecules ( Figure 1B) . The second pool of 275 oligos ("Probe II") covers the remaining region (21563:29872, NC_045512.2) which is shared by both the gRNA and sgRNAs.

To first check whether our method specifically captures the viral RNP complexes, we compared the resulting purification from Vero cells infected with SARS-CoV-2 (BetaCoV/Korea/KCDC03/2020) at MOI 0.1 for 24 hours (Kim et al., 2020b ) by either Probe I or Probe II. As negative controls, we pulled-down without probes ("no probe" control) or with the control probes (for either 18S or 28S rRNA). Protein composition of each RNP sample was distinct as shown by silver staining and western blotting ( Figure S1A ) with prominent SARS-CoV-2 N protein associated with Probes I and II, as expected. Enrichment of SARS-CoV-2 RNAs were confirmed by RT-qPCR ( Figure S1B ), suggesting that our protocol purfies specific RNP complexes. Note that SARS-CoV-2 gRNA was not enriched in the Probe II experiment, hinting at the excess amount of sgRNAs over gRNA in our culture condition.

We conducted Label-free quantification (LFQ) by liquid chromatography with tandem mass spectrometry (LC-MS/MS) and identified 429 host proteins and 9 viral proteins in total ( Figure   1C ). As highly abundant proteins may nonspecifically co-precipitate during the RNP capture experiment, we statistically modelled this protein background as a multinomial distribution and assessed the probability (i.e. p-value) of the quantity of the identified protein in the RNP capture (e.g. Probe I) experiment over the protein background of the control (e.g. no-probe) experiment (see Methods for details). This unweighted spectral count analysis resulted in 199 and 220 proteins that are overrepresented in the Probe I and Probe II sample, respectively (FDR < 10%, Table S2 ). Protein domain enrichment analysis revealed that these proteins indeed harbor RNAbinding domains such as RNA recognition motif (RRM) domain and K Homology (KH) domain ( Figure S1C ). Of note, unlike the cellular mRNA interactome (Castello et al., 2012; Gerstberger et al., 2014) , the RNA-binding repertoire of SARS-CoV-2 RNAs showed a depletion of DEAD/DEAH box helicase domains and an enrichment of KH domain.

As for viral proteins, the N protein was the most strongly enriched one, as expected ( Figure 1D ).

The nsp1 protein was also statistically enriched in both Probe I and Probe II experiments.

Nsp12, S, M, and nsp9 were detected more with Probe I than with Probe II. Coronavirus nsp9 is a single-strand RNA binding protein (Egloff et al., 2004; Sutton et al., 2004) essential for viral replication (Miknis et al., 2009) . Nsp1 is one of the major virulence factors that suppresses host translation by binding to the 40S ribosomal subunit (Thoms et al., 2020) . While nsp1 is mostly studied in the context of host gene expression (Narayanan et al., 2008) , our result hints at the direct role of nsp1 on the transcripts of SARS-CoV-2.

To delineate the host proteins that are enriched in the SARS-CoV-2 RNP complex, we employed an additional negative control experiment with uninfected cells ( Figure 1E ). In effect, this control provides a conservative background of host proteins as shown by silver staining ( Figure S1D ). Distributions of peptide length were consistent across technical replicates ( Figure   S1E ), demonstrating the robustness of the"on-bead" digestion step. Spectral count analysis against the "uninfected probe control" resulted in 74 and 72 proteins that are enriched in the infected samples with Probe I and Probe II, respectively (FDR < 5%, Figure 1F -H). In combination, we define these 109 proteins as the "SARS-CoV-2 RNA interactome." 37 host proteins such as CSDE1 (Unr), EIF4H, FUBP3, G3BP2, PABPC1, ZC3HAV1 were enriched in both the Probe I and Probe II RNP capture experiments on infected cells ( Figure 1F ), thus identifying a robust set of the "core SARS-CoV-2 RNA interactome." Gene ontology (GO) term enrichment analysis revealed that these host factors are involved in RNA stability control, mRNA function, and viral process ( Figure S1F ).

To investigate the evolutionary conservation of the RNA-protein interactions in coronaviruses, we conducted RNP capture on HCoV-OC43 that belongs to the lineage A of genus betacoronavirus. HCoV-OC43 shows 54.2% nucleotide homology to SARS-CoV-2 which belongs to lineage B. We profiled the HCoV-OC43 RNP complexes at multiple time points: 12, Figure S2D ), indicating the specificity of the coprecipitated RBPs.

Fourteen viral proteins were detected within the HCoV-OC43 RNP complexes ( Figure 2B , Figure S2E ). Specifically, LFQ intensities for viral structural proteins N, M, and S increased over time more evidently in the gRNA-hybridizing Probe I experiment ( Figure 2B ). HCoV-OC43 2a, an accessory protein unique to betacoronavirus lineage A, was also detected and increased over time, indicating that this protein of unknown function may act as an RBP. The RdRP nsp12 and the papain-like protease nsp3 also increased along with the other nsps identified in this experiment. Only a marginal amount of the HCoV-OC43 nsp1 was detected ( Figure S2E ), implying the functional divergence of nsp1 in betacoronavirus lineages A and B.

Next, we compared the host factors that form the viral RNA interactome of HCoV-OC43 and SARS-CoV-2. All 107 proteins from the SARS-CoV-2 interactome were also detected in the HCoV-OC43 interactome throughout multiple infection timepoints, except for RBMS1 and DDX3Y ( Figure 2C ), indicating that many of the same host proteins interact with RNAs of both HCoV-OC43 and SARS-CoV-2. To determine the core host factors that are conserved in the coronavirus RNA interactomes, we applied our spectral count analysis on the HCoV-OC43 experiment of 36 hpi ( Figure S2A ) and conducted statistical analysis in comparison to the noprobe control ( Figure 2D , FDR < 10%) and the uninfected-probe control ( Figure 2E , FDR < 5%).

We identified 67 and 70 host proteins for the HCoV-OC43 Probe I and Probe II experiments, respectively (Table S5) . 38 proteins were statistically enriched in both probe sets. GO term enrichment analysis revealed that these 38 host proteins are involved in transcriptional regulation, RNA processing, and RNA stability control ( Figure S2F 

To understand the regulatory significance of the SARS-CoV-2 RNA interactome, we compiled a list of "neighboring" proteins that are known to physically interact with the factors identified in our study (see Methods for details). In particular, we generated a physical interaction network centered (or seeded) by the core SARS-CoV-2 interactome ( Figure S3A ). Network analysis revealed several network hubs (e.g. NPM1 and PABPC1) and two highly connected network modules: the ribosomal subunits and the EIF3 complex. GO term enrichment analysis resulted in translation-related biological processes ( Figure S3B ), most likely due to the overrepresentation of ribosomal proteins and subunits of the EIF3 complex, which reflects the active translational status of viral mRNPs.

To achieve a more indepth functional perspective of the RNA interactome, we reconstructed the physical interaction network with the SARS-CoV-2 RNA interactome but excluding ribosomal proteins and EIF3 proteins ( Figure 3A ). This analysis identified additional hub proteins such as TRIM25, SQSTM1, and KHDRBS1. GO term enrichment analysis revealed multiple steps of the mRNA life cycle such as mRNA splicing, mRNA export, mRNA stability, and stress granule assembly ( Figure 3B ), suggesting these mRNA regulators are co-opted to assist the viral life cycle. Interestingly, we also found GO terms related to viral processes and innate immune response. In terms of intracellular localization, the SARS-CoV-2 RNA interactome is enriched by proteins localized in the paraspeckle and cytoplasmic RNP granule (e.g. stress granule) compared to the cellular mRNA interactome ( Figure 3C ) (Baltz et al., 2012; Castello et al., 2012) .

These observations suggest the regulatory mechanisms of viral RNAs distinct from that of host mRNAs, which involve activation of host antiviral machinery and sequestration of viral RNAs. 

To measure the impact of these host proteins on coronavirus RNAs, we conducted knockdown experiments and infected Calu-3 cells with SARS-CoV-2 ( Figure 5A and 5B). Calu-3 cells are human lung epithelial cells and often used as a model system for coronavirus infection (Sims et al., 2008) . Strategically, we selected a subset of the SARS-CoV-2 RNA interactome that covers a broad range of functional modules that we identified above: JAK-STAT signaling, mRNA transport, mRNA stability, and translation. Knockdown of host factors that are stimulated by SARS-CoV-2 infection or INFß treatment, namely PARP12, TRIM25, ZC3HAV1, CELF1, and SHFL, led to increased viral RNAs ( Figure 5C ). The result suggests that these RBPs which directly recognize the viral RNAs are induced by the interferon and JAK-STAT signaling pathway to suppress coronaviruses. ZC3HAV1 (ZAP/PARP13) is an ISG and known to restrict the replication of many RNA viruses such as HIV-1 (Retroviridae), sindbis virus (Togaviridae), and Ebola (Filoviridae) (Goodier et al., 2015) . ZC3HAV1 was previously reported to recognize CpG and recruits decay factors to degrade HIV RNAs (Takata et al., 2017) . ZC3HAV1 acts as a cofactor for TRIM25, an E3 ubiquitin ligase that promotes antiviral signaling mainly through RIG-I (Choudhury et al., 2020; Gack et al., 2007) . Our knockdown results indicate that both ZC3HAV1 and TRIM25 may act as antiviral factors against SARS-CoV-2 ( Figure 5C ). SARS-CoV N protein was previously shown to interact with the SPRY domain of TRIM25, interfering with the activation of RIG-I (Hu et al., 1 2017). Further investigation is needed to understand how ZC3HAV1 and TRIM25 recognize and suppress SARS-CoV-2 transcripts and if SARS-COV-2 N protein counteracts TRIM25.

PARP12, a cytoplasmic mono-ADP-ribosylation (MARylation) enzyme, is also known to have broad antiviral activity against RNA viruses such as Venezuelan equine encephalitis virus (Togaviridae), vesicular stomatitis virus (Rhabdoviridae), Rift Valley fever virus (Phenuiviridae), encephalomyocarditis virus (Picornaviridae), and Zika virus (Flaviviridae) by multiple mechanisms including blocking cellular RNA translation (Atasheva et al., 2014; Welsby et al., 2014) or triggering proteasome-mediated destabilization of viral proteins (Li et al., 2018) . ADP ribosyltransferases are evolutionarily ancient tools used for host-pathogen interactions (Fehr et al., 2020) . Of note, coronavirus nsp3 carries a conserved macrodomain that can remove ADPribose to reverse the activity of PARP enzymes (Fehr et al., 2015) . Knockdown of PARP12 and PARP14 was shown to increase the replication of the macrodomain-deficient mouse hepatitis virus (MHV) which belongs to the lineage A of genus betacoronavirus (Grunewald et al., 2019) which is consistent with our knockdown results ( Figure 5C ). Based on our RNA interactome data, we hypothesize that the RNA-binding activity of PARP12 and its role in viral RNA recognition may explain the underlying molecular mechanism of its antiviral activity against SARS-CoV-2 transcripts.

Other interferon-stimulated RBPs may also be involved in host defense against SARS-CoV-2. CELF1 (CUGBP1 Elav-like protein family 1) mediates alternative splicing and controls mRNA stability and translation (Konieczny et al., 2014) . CELF1 is required for IFN -mediated suppression of simian immunodeficiency virus (Retroviridae) (Dudaronek et al., 2007) , but its involvement in other viral infections is unknown. SHFL (Shiftless/RyDEN) was induced prominently upon viral infection and interferon treatment, and suppressed by JAK inhibitor (Figure 4) . SHFL suppresses the translation of diverse RNA viruses, including dengue virus (Flaviviridae) and HIV (Retroviridae) (Balinsky et al., 2017; Suzuki et al., 2016; Wang et al., 2019) . Under our experimental condition, upregulation of viral RNA was only modest in CELF1and SHFL-depleted cells, but further examination is needed as the knockdown efficiency of ISGs were low in infected cells ( Figure S4B ), likely because virus-induced interferon response compromised gene silencing.

Apart from the above RBPs, we identified multiple host factors that have not been previously described in the context of viral infection. In particular, LARP1 depletion resulted in a substantial upregulation of viral RNAs ( Figure 5C ), suggesting that LARP1 may have an antiviral function. LARP1 stabilizes 5′ TOP mRNAs encoding ribosomal proteins and translation factors, which contain the 5′ terminal oligopyrimidine (5′ TOP) motif in the 5′ UTR (Philippe et al., 2018) .

LARP1 also represses the translation of 5′ TOP mRNAs in response to metabolic stress in an mTORC1-dependent manner (Hong et al., 2017; Lahr et al., 2017) . While much is unknown regarding the role of LARP1 during viral infection, a recent proteomics study showed that SARS-CoV-2 N protein binds to LARP1 (Gordon et al., 2020) . Based on our RNP capture and knockdown results, it is conceivable that LARP1 may interfere with viral translation directly via viral RNA interaction. The role of N protein in the context of LARP1-dependent viral suppression warrants further investigation. Of note, we cannot exclude the possibility that LARP1 indirectly regulates SARS-CoV-2 RNAs via the control of 5′ TOP mRNAs encoding translation machinery.

In fact, the SARS-CoV-2 RNA interactome includes specific components of the 40S and 60S ribosomal subunits and translational initiation factors ( Figure 1F -H). Knockdown experiments indicated that ribosomal proteins (RPS9 and RPS3) and translation initiation factor EIF4H may have antiviral activities ( Figure 5C ). EIF4H along with EIF4B is a cofactor for RNA helicase EIF4A (Rogers et al., 2001 ) whose depletion results in RNA granule formation (Tauber et al., 2020) . EIF4H and EIF4B were both identified as the core SARS-CoV-2 RNA interactome ( Figure 1F ). EIF4H also interacts with SARS-CoV-2 nsp9 (Gordon et al., 2020) , so it will be interesting to investigate the functional consequence of the EIF4H-nsp9 interaction. Together, our observations implicate that SARS-CoV-2 infection may be closely intertwined with the regulation of ribosome biogenesis, metabolic rewiring, and global translational control.

Other translation factors EIF3A, EIF3D, and CSDE1 exhibited proviral effects ( Figure 5C ).

EIF3A is the RNA-binding component of the mammalian EIF3 complex and evolutionarily conserved along with EIF3B and EIF3C (Masutani et al., 2007) . EIF3D is known to interact with mRNA cap and is required for specialized translation initiation . CSDE1 (Unr) is required for IRES-dependent translation in human rhinovirus (Picornaviridae) and poliovirus (Picornaviridae) (Anderson et al., 2007; Boussadia et al., 2003) . In all, our finding suggests that SARS-CoV-2 may recruit EIF3D and CSDE1 to respectively regulate cap-dependent and IRESdependent translation initiation (Lee et al., 2017) of SARS-CoV-2 gRNA and sgRNAs.

Lastly, the coronaviral RNA interactomes are enriched with RBPs with KH domains ( Figure S1D and Figure S2B ) unlike the mRNA interactome. Depletion of FUBP3 (MARTA2) and HDLBP (Vigilin) increased the viral RNA levels ( Figure 5C ), hinting at a potential antiviral role of proteins containing KH domains. HDLBP is a conserved protein that contains 14 KH domains and has been implicated in viral translation of dengue virus (Ooi et al., 2019) . FUBP3 was enriched in all four RNP capture experiments (i.e. SARS-CoV-2 Probe I/II and OC43 Probe I/II) ( Figure 2D ).

FUBP3 is a nuclear protein with 4 KH domains and binds to the 3′ UTR of cellular mRNAs regulating mRNA localization (Blichenberg et al., 1999; Mukherjee et al., 2019) . Its connection to the life cycle of coronavirus is unknown to our knowledge.

Our current study reveals a broad-spectrum of antiviral factors such as TRIM25, ZC3HAV1, PARP12, and SHFL and also many RBPs whose Along with proteins regulating RNAs, it would also be interesting to consider the possibility of 'riboregulation' (Hentze et al., 2018) in which RNA controls its interacting proteins. Dengue virus, for example, uses its subgenomic RNA called sfRNA to sequester TRIM25 (Chapman et al., 2014) . The sgRNA/gRNA ratio is a critical determinant of epidemic potential of dengue virus (Manokaran et al., 2015) . Notably, coronaviruses including SARS-CoV-2 produces substantial amounts of noncanonical sgRNAs that may serve as noncoding decoys to interact with host RBPs to modulate host immune responses (Kim et al., 2020a) . genome-wide CRISPR screen , and off-label drug screening have all provided invaluable insights of the underlying biology of this novel human coronavirus. 

The authors declare no competing interests. 

Calu-3 cells 24 hours after infection at 0.05 MOI. Data are represented as mean ± s.e.m.

(n = 3 independent experiments). 18S rRNA was used for normalization.

By scanning the genomic RNAs of SARS-CoV-2 (NCBI RefSeq accession NC_045512.2) and

HCoV-OC43 (GenBank accession AY391777.1) from head to tail, partially overlapping 90 nt tiles were enumerated. These tiles were designed to have 30 nt spacing, so adjacent tiles share a subsequence of 60 nt. To avoid ambiguous targeting, tiles were aligned to the human transcriptome (version of Oct 14, 2019) using bowtie 2 (Langmead and Salzberg, 2012) and multi-mapped sequences were discarded. To prepare biotinylated antisense oligonucleotides (ASOs) in bulk, the sequence elements for in vitro transcription (IVT), reverse transcription (RT) and PCR were added to the 90 nt tiles. The T7 promoter (5′-TAA TAC GAC TCA CTA TAG GG-3′) and a pad for RT priming (5′-TGG AAT TCT CGG GTG CCA AGG-3′) were added to the head and tail of each tile, respectively. We grouped ASOs into two sets for each viral genome: Table S2 .

ASO templates were amplified using KAPA HiFi HotStart ReadyMix (Roche) and PCR primers for an ASO pool. PCR products were purified by QIAquick PCR purification kit (QIAGEN). RNA intermediates were then transcribed using 5X MEGAscript T7 transcription kit (Invitrogen), and DNA templates were degraded by TURBO DNase (Invitrogen). To clean up enzymes and other reagents, 1.8× reaction volume of AMPure XP (Beckman) was applied and polyethylene glycol was added to be final 20%. The size selection was carried out according to the manufacturer's protocol. Biotinylated ASOs were synthesized by RevertAid Reverse Transcriptase (Thermo Scientific) and 5′ biotin-TEG primer. RNA intermediates were hydrolyzed at 0.1 M NaOH and neutralized with acetic acid. Finally, ASO purification was performed in the same manner as IVT RNA selection. The primer sequences used for PCR and reverse transcription are listed in Table S6 .

The Uniprot reference proteome sets for human (UP000005640, canonical, SwissProt) and

African green monkey (Chlorocebus sabaeus; UP000029965, canonical, SwissProt and TrEMBL) were used to identify host proteins in each mass spectrometry experiment (version 03/21/2020) (UniProt Consortium, 2019). The reference proteome set for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was manually curated largely based on the NCBI Reference Sequence (NC_045512.2) and related literature of other accessory proteins (e.g. ORF3b, ORF9b and ORF9c). The reference proteome set for the Human coronavirus OC43 (HCoV-OC43) was compiled based on the Uniprot Swiss-Prot proteins for HCoV-OC43

(taxonomy:31631) except for HCoV-OC43 Protein I which was separated into Protein Ia and Protein Ib (or N2) (Vijgen et al., 2005) .

Virus experiments were carried out in accordance with the biosafety guideline by the Korea 

For total RNA purification from virus-infected cells, 1 mL TRIzol LS (Invitorgen) were added to media-removed cell monolayers per single well of 12 well plates followed by on-column DNA digestion and purification (Zymo Research). For RNA purification from RNP capture sample, bead-captured RNAs were digested with 100 ng Proteinase K (PCR grade, Roche) and incubated at 37˚C for 1 hour, followed by RNA isolation by TRIzol LS with GlycoBlue (Invitrogen). 1~5 µg RNA were reverse-transcribed using RevertAid transcriptase (Thermo Scientific) and random hexamer. qPCR was performed with primer pairs listed in Table S6 and

PowerSYBR Green (Applied Biosystems) and analyzed with QuantStudio 5 (Thermo Scientific).

Virus infected cells were detached from culture vessels by trypsin and cell pellets were resuspended with ice-cold PBS. 12 mL cell suspensions were dispersed in 150 mm dishes to irradiate 254 nm UV for 2.5 J/cm 2 using BIO-LINK BLX-254 for SARS-CoV-2 or 0.8 J/cm 2 using Spectrolinker XL-1500 for HCoV-OC43. UV-crosslinked cells were pelleted by centrifugation was used for both the peptide and protein level. The match-between-runs option was enabled with default parameters in the identification step. Finally, LFQ was performed for those with a minimum ratio count of 1.

To identify host and viral proteins that interact with the particular RNA species of interest (e.g.

sgRNA or gRNA), we utilized the results from the "bead only" and "probe only" samples as technical backgrounds. Specifically, the "bead only" (or no-probe) experiment in infected cells was used to account for non-specific interactors and biotin-containing carboxylases (e.g. PCCA,

ACACA, and ACACB) and determine the set of host and viral proteins that in a broad sense bind to the RNA, which we call Probe I/II "binding" proteins. The probe experiment in uninfected cells (i.e. "probe only") was then used as the technical background against target RNAindependent interactors and determine the set of host proteins that are enriched for the target RNA, which we call Probe I/II "enriched" proteins.

To accomplish this, we considered the protein spectra count data as a multinomial distribution and applied a statistical test for spectra count enrichment. Specifically, let N p be the number of identified spectra counts for protein group p from the case experiment (e.g. Probe I experiment in infected cells), and M p be the respective count number from the control experiment (e.g. noprobe experiment in infected cells 

We conducted enrichment analyses of Gene Ontology (GO) terms (Gene Ontology Consortium, 2001 ) by means of summarizing the function of tens of host proteins identified in the RNP capture experiment. In general, Fisher's exact test is used to estimate the statistical significance of the association (i.e. contingency) between a particular GO term and the gene set of interest.

To improve the explanatory power of this analysis, we used the weight01 algorithm (Alexa et al., 2006) from the topGO R package which accounts for the GO graph structure and reduces local dependencies between GO terms. Detailed information of the Gene Ontology was from the GO.db R package (version 3.8.2), and GO gene annotations were from the org.Hs.eg.db R package (version 3.8.2).

We integrated protein-protein interaction data from the BioGRID database (Release 3.5.187) (Stark et al., 2006) and retrieved other proteins that do not necessarily bind to the SARS-CoV-2 RNA but form either transient or stable physical interactions with the host proteins identified from the RNP capture experiments. In detail, we considered only human protein-protein interactions that were (1) found from at least two different types of experiments and (2) reported by at least three publication records which resulted in a total of 65,625 interactions covering 12,143 human proteins. Physical interactions between SARS-CoV-2 proteins and human proteins were by affinity capture and mass spectrometry in SARS-CoV-2 protein expressing cells (Gordon et al., 2020) . The network R package and the ggnet2 function of the GGally R package was used for graph visualization.

Pfam database (version 33.1) (El-Gebali et al., 2019) was used for protein domain enrichment analysis. Taxon 9606 (human) and Taxon 60711 (green monkey) protein domain annotations were used to analyze RNP capture results of HCoV-OC43 and SARS-CoV-2, respectively. Onesided Fisher's exact test was applied to estimate the statistical enrichment of a particular protein domain for the specific gene set (e.g. SARS-CoV-2 Probe I binding proteins). We utilized the set of all proteins identified in the RNP capture experiments and all protein domains annotated to those proteins as the statistical background of the enrichment analysis.

To investigate the subcellular localizations of the SARS-CoV-2 interactome, we leveraged the protein subcellular localization information from the Human cell map database v1 (Go et al., 2019) . Information from the SAFE algorithm was used primarily but then supplemented by information from the NMF algorithm in case of "no prediction" or "-" localizations.. Localization terms of the NMF algorithm were matched to terms of the SAFE algorithm in general, but few were mapped to the higher term of the SAFE algorithm. For example, the "cell junction" term of the NMF algorithm was merged to the "cell junction, plasma membrane" term of the SAFE algorithm.

Zhou, P., Yang, X. Relative viral RNA level Amplicon nsp12 N Figure 5 

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LARP1 functions as a molecular switch for mTORC1-mediated translation of an essential class of mRNAs

The Severe Acute Respiratory Syndrome Coronavirus Nucleocapsid Inhibits Type I Interferon Production by Interfering with TRIM25-Mediated RIG-I Ubiquitination

Dynamic rewiring of the human interactome by interferon signaling

The Architecture of SARS-CoV-2 Transcriptome

Identification of Coronavirus Isolated from a Patient in Korea with COVID-19

MBNL proteins and their target RNAs, interaction and splicing regulation

La-related protein 1 (LARP1) binds the mRNA cap

The Molecular Biology of Coronaviruses

Comparative analysis of RNA genomes of mouse hepatitis viruses

Structure of the full SARS-CoV-2 RNA genome in infected cells

Fast gapped-read alignment with Bowtie 2

Advances in CLIP Technologies for Studies of Protein-RNA Interactions

eIF3d is an mRNA capbinding protein that is required for specialized translation initiation

Regulation Mechanisms of Viral IRES-Driven Translation

PARP12 suppresses Zika virus infection through PARP-dependent degradation of NS1 and NS3 viral proteins

Dengue subgenomic RNA binds TRIM25 to inhibit interferon expression for epidemiological fitness

Reconstitution reveals the functional core of mammalian eIF3

RAP-MS: A Method to Identify Proteins that Interact Directly with a Specific RNA Molecule in Cells

The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3

Chromosomes. A comprehensive Xist interactome reveals cohesin repulsion and an RNA-directed chromosome conformation

β -Actin mRNA interactome mapping by proximity biotinylation

Severe acute respiratory syndrome coronavirus nsp1 suppresses host gene expression, including that of type I interferon, in infected cells

An RNA-centric dissection of host complexes controlling flavivirus infection

Coronavirus as a possible cause of severe acute respiratory syndrome

Coronaviruses post-SARS: update on replication and pathogenesis

La-related protein 1 (LARP1) repression of TOP mRNA translation is mediated through its cap-binding domain and controlled by an adjacent regulatory region

Methods to study RNA-protein interactions

Modulation of the helicase activity of eIF4A by eIF4B, eIF4H, and eIF4F

Molecular biology: Rap and chirp about X inactivation

Interplay between SARS-CoV-2 and the type I interferon response

Fundamental properties of the mammalian innate immune system revealed by multispecies comparison of type I interferon responses

SARS-CoV replication and pathogenesis in an in vitro model of the human conducting airway epithelium

The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing

Continuous and Discontinuous RNA Synthesis in Coronaviruses

BioGRID: a general repository for interaction datasets

A SARS-CoV-2 BioID-based virus-host membrane protein interactome and virus peptide compendium: new proteomics resources for COVID-19 research

The nsp9 replicase protein of SARS-coronavirus, structure and functional insights

Characterization of RyDEN (C19orf66) as an Interferon-Stimulated Cellular Inhibitor against Dengue Virus Replication

CG dinucleotide suppression enables antiviral defence targeting non-self RNA

Modulation of RNA Condensation by the DEAD-Box Protein eIF4A

Structural basis for translational shutdown and immune evasion by the Nsp1 protein of SARS-CoV-2

The Future of Cross-Linking and Immunoprecipitation (CLIP)

UniProt: a worldwide hub of protein knowledge

A large-scale binding and functional map of human RNA-binding proteins

Complete genomic sequence of human coronavirus OC43: molecular clock analysis suggests a relatively recent zoonotic coronavirus transmission event

Regulation of HIV-1 Gag-Pol Expression by Shiftless, an Inhibitor of Programmed -1 Ribosomal Frameshifting

Genome-wide CRISPR screen reveals host genes that regulate SARS-CoV-2 infection

PARP12, an interferon-stimulated gene involved in the control of protein translation and inflammation

Discovery of seven novel Mammalian and avian coronaviruses in the genus deltacoronavirus supports bat coronaviruses as the gene source of alphacoronavirus and betacoronavirus and avian coronaviruses as the gene source of gammacoronavirus and deltacoronavirus