key: cord-0729065-wqy9ywze
authors: Mac Kain, Alice; Maarifi, Ghizlane; Aicher, Sophie-Marie; Arhel, Nathalie; Baidaliuk, Artem; Munier, Sandie; Donati, Flora; Vallet, Thomas; Tran, Quang Dinh; Hardy, Alexandra; Chazal, Maxime; Porrot, Françoise; OhAinle, Molly; Carlson-Stevermer, Jared; Oki, Jennifer; Holden, Kevin; Simon-Lorière, Etienne; Bruel, Timothée; Schwartz, Olivier; van der Werf, Sylvie; Jouvenet, Nolwenn; Nisole, Sébastien; Vignuzzi, Marco; Roesch, Ferdinand
title: Identification of DAXX As A Restriction Factor Of SARS-CoV-2 Through A CRISPR/Cas9 Screen
date: 2021-11-24
journal: bioRxiv
DOI: 10.1101/2021.05.06.442916
sha: 30e0813472f7205fc8417cf6f559487acc7d9aad
doc_id: 729065
cord_uid: wqy9ywze

Interferon restricts SARS-CoV-2 replication in cell culture, but only a handful of Interferon Stimulated Genes with antiviral activity against SARS-CoV-2 have been identified. Here, we describe a functional CRISPR/Cas9 screen aiming at identifying SARS-CoV-2 restriction factors. We identified DAXX, a scaffold protein residing in PML nuclear bodies known to limit the replication of DNA viruses and retroviruses, as a potent inhibitor of SARS-CoV-2 and SARS-CoV replication in human cells. Basal expression of DAXX was sufficient to limit the replication of SARS-CoV-2, and DAXX over-expression further restricted infection. In contrast with most of its previously described antiviral activities, DAXX-mediated restriction of SARS-CoV-2 was independent of the SUMOylation pathway. SARS-CoV-2 infection triggered the re-localization of DAXX to cytoplasmic sites and promoted its degradation. Mechanistically, this process was mediated by the viral papain-like protease (PLpro) and the proteasome. Together, these results demonstrate that DAXX restricts SARS-CoV-2, which in turn has evolved a mechanism to counteract its action.

of infection, DAXX re-localizes to sites of viral replication in the cytoplasm, likely targeting viral 54 transcription. We show that the SARS-CoV-2 papain-like protease (PLpro) induces the proteasomal 55 degradation of DAXX, demonstrating that SARS-CoV-2 developed a mechanism to evade, at least 56 partially, the restriction imposed by DAXX.

Results.

A restriction factor-focused CRISPR/Cas9 screen identifies genes potentially involved in 61 SARS-CoV-2 inhibition. To identify restriction factors limiting SARS-CoV-2 replication, we generated 62 a pool of A549-ACE2 cells knocked-out (KO) for 1905 potential ISGs, using the sgRNA library we 63 previously developed to screen HIV-1 restriction factors (34). This library includes more ISGs than 64 most published libraries, as the inclusion criteria was less stringent (fold-change in gene expression in 65 THP1 cells, primary CD4+ T cells or PBMCs ³ 2). Therefore, some genes present in the library may 66 not be ISGs per se in A549 cells. Transduced cells were selected by puromycin treatment, treated with 67 IFNa and infected with SARS-CoV-2. Infected cells were immuno-labelled with a spike (S)-specific 68 antibody and analyzed by flow cytometry. As expected (11, 12) , IFNa inhibited infection by 7-fold (Fig. 69 S1). Infected cells were sorted based on S expression (Fig. 1a) , and DNA was extracted from infected representing antiviral and proviral factors, respectively (Fig. 1b) . Although our screen was not 74 designed to explicitly study proviral factors, we did successfully identify the well-described SARS-CoV-75 2 co-factor cathepsin L (CTSL) (36), validating our approach. USP18, a negative regulator of the IFN 76 signaling pathway (37), and ISG15, which favors Hepatitis C Virus replication (38), were also identified 77 as proviral ISGs. Core IFN pathway genes such as the IFN receptor (IFNAR1), STAT1, and STAT2, 78 were detected as antiviral factors, further validating our screening strategy. LY6E, a previously 79 described inhibitor of SARS-CoV-2 entry (15, 16) , was also a significant hit. Moreover, our screen 80 identified APOL6, IFI6, DAXX and HERC5, genes that are known to encode proteins with antiviral 81 activity against other viruses (39-42), but had not previously been studied in the context of SARS-

CoV-2 infection. For all these genes except APOL6, individual sgRNAs were consistently enriched (for 83 antiviral factors) or depleted (for proviral factors) in the sorted population of infected cells, while non-84 targeting sgRNAs were not (Fig. 1c) .

LY6E and DAXX display antiviral activity against SARS-CoV-2. To validate the ability of the 87 identified hits to modulate SARS-CoV-2 replication in human cells, we generated pools of A549-ACE2 88 knocked-out (KO) cells for different genes of interest by electroporating a mix of 3 sgRNA/Cas9 89 ribonucleoprotein (RNP) complexes per gene target. Levels of gene editing were above 80% in all of 90 the A549-ACE2 KO cell lines, as assessed by sequencing of the edited loci ( Table 1) . As controls, we 91 used cells KO for IFNAR1, for the proviral factor CTSL or for the antiviral factor LY6E, as well as cells 92 electroporated with non-targeting (NTC) sgRNAs/Cas9 RNPs. These different cell lines were then 93 treated with IFNa and infected with SARS-CoV-2. Viral replication was assessed by measuring the 94 levels of viral RNA in the supernatant of infected cells using RT-qPCR (Fig. 2a) . In parallel, we titrated 95 the levels of infectious viral particles released into the supernatant of infected cells (Fig. 2b) . As 

In IFNa-treated cells, DAXX and LY6E KO led to a modest, but significant rescue of viral 105 replication, which was particularly visible when measuring the levels of infectious virus by plaque 106 assay titration (Fig. 2b) , while the antiviral effect of IFNa treatment was completely abrogated in 107 IFNAR1 KO cells, as expected (Fig. 2c) . However, IFNa still had robust antiviral effect on SARS-CoV-108 2 replication in both DAXX KO and LY6E KO cells (Fig. 2c) . While DAXX and LY6E contribute to the 109 IFN-mediated restriction, this suggests that there are likely other ISGs contributing to this effect. DAXX 110 is sometimes referred to as an ISG, and was originally included in our ISG library, although its 111 expression is only weakly induced by IFN in some human cell types (32, 44) . Consistent with this, we 112 found little to no increase in DAXX expression in IFNa-treated A549-ACE2 cells (Fig. S3) . In addition,

we tested the antiviral effect of DAXX on several SARS-CoV-2 variants that have been suggested to 114 be partially resistant to the antiviral effect of IFN in A549-ACE2 cells (45). Our results confirmed that 115 Lineage B. 1.1.7. (Alpha) and Lineage P1 (Gamma) SARS-CoV-2 variants were indeed less sensitive 116 to IFN (Fig. 2d) . DAXX, however, restricted all variants to a similar level than the original Lineage B 117 strain of SARS-CoV-2 (Fig. 2d) , suggesting that while some variants may have evolved towards IFN-118 resistance, they are still efficiently restricted by DAXX. To determine whether DAXX is specific to 119 SARS-CoV-2 or also inhibits other RNA viruses, including coronaviruses, we infected A549-ACE2 WT 120 and DAXX KO cells with SARS-CoV, MERS-CoV, and 2 RNA viruses belonging to unrelated viral 121 families: Yellow Fever Virus (YFV) and Measles Virus (MeV), which are positive and negative strand 122 RNA viruses, respectively. Our results show that DAXX restricts SARS-CoV, but has no effect on the 123 replication of YFV, MeV or MERS-CoV ( Fig. 2e-f ). Thus, our data suggests that DAXX restriction may 124 exhibit some level of specificity.

DAXX targets SARS-CoV-2 transcription. Next, we investigated whether DAXX targets early steps 127 of the SARS-CoV-2 viral life cycle such as viral entry or transcription. The intracellular levels of two 128 viral transcripts were assessed at different time post-infection in A549-ACE2 WT or DAXX KO cells 129 ( Fig. 3) . At early time points (from 2h to 6h p.i.), the levels of viral RNA were similar in WT and DAXX 130 KO cells, suggesting that comparable amounts of SARS-CoV-2 virions were entering cells. The levels 131 of viral transcripts significantly increased starting at 8h p.i., representing the initiation of viral 132 transcription. The levels of the 5' UTR viral transcript (Fig. 3a) were 6.4-fold higher at 8h; 4.1-fold 133 higher at 10h; and 8-fold higher at 24h post-infection in DAXX KO cells compared to WT cells. The 134 levels of RdRp transcripts were less affected by the absence of DAXX than 5'UTR transcripts (Fig. 3b) 135 with levels of viral transcripts 1.7-fold and 3.5-fold higher in DAXX KO cells compared to WT cells at 136 10h and 24h pos-infection, respectively. These results suggest that DAXX acts early during the SARS-

CoV-2 replication cycle, likely targeting the step of viral transcription.

DAXX restriction is SUMO-independent. DAXX is a small scaffold protein that acts by recruiting 140 other SUMOylated proteins in nuclear bodies through its C-terminal SUMO-Interacting Motif (SIM) 141 domain (46). The recruitment of these factors is required for the effect of DAXX on various cellular 142 processes such as transcription and apoptosis, and on its antiviral activities (32, (47) (48) (49) . DAXX can 143 also be SUMOylated itself (50), which may be important for some of its functions. To investigate the 144 role of SUMOylation in DAXX-mediated SARS-CoV-2 restriction, we used overexpression assays to 145 compare the antiviral activity of DAXX WT with two previously described DAXX mutants (51). First, we 146 used a version of DAXX in which 15 lysine residues have been mutated to arginine (DAXX 15KR),

which is unable to be SUMOylated; and second, a truncated version of DAXX that is missing its C- 

We examined the effect of DAXX WT overexpression on the replication of SARS-CoV-2-153 mNeonGreen (52) by microscopy. DAXX overexpression starkly reduced the number of infected cells 154 ( Fig. 4a-b) , revealing that DAXX-mediated restriction is not specific to A549-ACE2 cells. Using double 155 staining for HA-tagged DAXX and SARS-CoV-2, we found that most of the DAXX-transfected cells 156 were negative for infection, and conversely, that most of the infected cells did not express transfected In order to quantify the antiviral effect of overexpressed DAXX WT and mutants, we assessed the 159 number of cells positive for the S protein (among transfected cells) by flow cytometry and the 160 abundance of viral transcripts by qRT-PCR. Western blot (Fig. S4a ) and flow cytometry (Fig. S4b) 

analyses showed that DAXX WT and mutants were expressed at similar levels, with a transfection 162 efficiency of around 40 to 50% for all three constructs. DAXX WT, 15KR and ∆SIM all efficiently 163 restricted SARS-CoV-2 replication. Indeed, at 24 hours p.i., the proportion of infected cells (among 164 HA-positive cells) was reduced by 2 to 3-fold as compared to control transfected cells for all 3 165 constructs (Fig. 4d) . This effect was less pronounced but still significant at 48 hours p.i. (Fig. 4e) .

Moreover, DAXX overexpression led to a significant reduction of the levels of two different viral 186   6a ). In contrast, SARS-CoV-2 infection had no effect on DAXX mRNA levels (Fig. S6) . Importantly, the 187 decrease in DAXX protein levels is likely not attributed to a global host cell shut down, as the levels of 

These inhibitors had minimal effects on cell viability at the selected concentrations ( Fig. S7 ).

Strikingly, GRL0617 treatment partially restored DAXX expression (Fig. 6b) , especially at the highest 197 concentration. Similarly, MG132 also prevented DAXX degradation in SARS-CoV-2 infected cells. In 198 contrast, Masitinib treatment had no effect on DAXX levels. These results suggest that PLpro, but not 199 3CL, targets DAXX for proteasomal degradation. Consistently, GRL0617 treatment also restored 200 DAXX subcellular localization to nuclear bodies (Fig. 6c) . As expected, GRL0617 treatment also 201 inhibited the production of SARS-CoV-2 proteins such as spike (Fig. 6b) , and may thus have an 202 indirect effect on DAXX by inhibiting SARS-CoV-2 replication itself. However, the fact that Masitinib 203 also inhibits spike production but does not restore DAXX expression suggested that DAXX 204 degradation is not an unspecific consequence of viral replication but rather a specific activity of PLpro.

To investigate the potential direct contribution of PLpro to DAXX degradation, we assessed the impact 206 of overexpressing individual SARS-CoV-2 proteins in 293T-ACE2 cells on DAXX levels. We included 207 in the analysis mCherry-tagged SARS-CoV-2 Non-structural proteins (Nsp) (58), which are not 208 expressed from a lentiviral vector that may be targeted by DAXX antiviral activity (33). This included 209 Nsp3 (which encodes PLro), Nsp4, Nsp6, Nsp7, Nsp10, Nsp13 and Nsp14. All proteins were 210 expressed at similar levels ( Fig. S8a) . Only the overexpression of Nsp3 led to DAXX degradation ( Fig.  6d ). This effect was dose-dependent ( Fig. 6e and Fig. S8b) , and was abrogated when cells were 212 treated with GRL0617 ( Fig. 6f) . Taken together, these results strongly indicate that PLpro directly 213 induces the proteasomal degradation of DAXX.

Discussion.

Comparison with other screens. The whole-genome CRISPR/Cas9 screens conducted to date on 218 SARS-CoV-2 infected cells mostly identified host factors necessary for viral replication (24-29) and 219 did not focus on antiviral genes, as did our screen. Three overexpression screens, however, identified 220 ISGs with antiviral activity against SARS- 22, 21) . In the first one, Pfaender et al. screened (Table S5 -6), we did identify hits in common with this screen, 236 including IFI6 and OAS2 (that were also identified by Pfaender et al.) . Of note, DAXX was absent from 237 the ISG libraries used by these overexpression screens, which explains why it was not previously 

DAXX is a restriction factor for SARS-CoV-2. We identify DAXX as a potent antiviral factor 246 restricting the replication of SARS-CoV-2, acting independently of IFN and likely targeting an early 247 step of the viral life cycle such as transcription (Fig. 3) . DAXX fulfills all of the criteria defining a bona 248 fide SARS-CoV-2 restriction factor: knocking-out endogenous DAXX leads to enhanced viral 249 replication (Fig. 2) , while over-expression of DAXX restricts infection (Fig. 4) . DAXX co-localizes with 250 viral dsRNAs (Fig. 5) and SARS-CoV-2 antagonizes DAXX to some extent, as evidenced by the 251 proteasomal degradation of DAXX induced by PLpro (Fig. 6) . Although DAXX expression is not 252 upregulated by IFNa in A549 cells (Fig. S3) , basal levels of expression are sufficient for its antiviral 253 activity, as has been shown for other potent restriction factors. Publicly available single-cell RNAseq 254 analyses (Fig. S2) indicated that DAXX is expressed in cell types targeted by the virus in vivo, such as 255 lung epithelial cells and macrophages. Interestingly, DAXX exhibited some degree of specificity in its 256 antiviral activity, as unrelated viruses such as YFV and MeV, as well as the closely related MERS-CoV 257 were not sensitive to its action, in contrast to SARS-CoV and SARS-CoV-2 (Fig. 2) . Future work will 258 determine which viral determinants are responsible for this specific antiviral activity of DAXX.

Mechanism of DAXX-mediated restriction. DAXX is mostly known for its antiviral activity against 261 DNA viruses replicating in the nucleus, such as adenovirus 5 (AdV5) (60) and human papillomavirus 262 (HPV) (61). Most of these viruses antagonize PML and/or DAXX, which interacts with PML in nuclear 263 bodies (30). We show here that DAXX is also able to restrict SARS-CoV-2, a positive sense RNA virus that replicates in the cytoplasm. Recent studies have shown that DAXX inhibits the reverse 265 transcription of HIV-1 in the cytoplasm (32,33). Within hours of infection, DAXX subcellular localization 266 was altered, with DAXX accumulating in the cytoplasm and colocalizing with incoming HIV-1 capsids 267 (33). Here, we observed a similar phenomenon, with a rapid re-localization of DAXX from the nucleus 268 to cytoplasmic viral replication sites (Fig. 5) , where it likely exerts its antiviral effect. Early events in the 269 replication cycle of both HIV-1 and SARS-CoV-2, such as viral fusion or virus-induced stress, may 270 thus trigger DAXX re-localization to the cytoplasm. DAXX seems to inhibit SARS-CoV-2 by a distinct 271 mechanism: whereas the recruitment of interaction partners through the SIM-domain is required for 272 the effect of DAXX on HIV-1 reverse transcription (32), it was not the case in the context of SARS-

CoV-2 restriction. This result was unexpected, since DAXX has no enzymatic activity and rather acts 274 as a scaffold protein recruiting SUMOylated partners through its SIM domain (51). Some DAXX 275 functions, such as interaction with the chromatin remodeler ATRX (30) or its recently described role as 276 a chaperone protein (62) are, however, SIM-independent. Future work should determine which DAXX 277 domains and residues are required for its antiviral activity.

Antagonism of DAXX by SARS-CoV-2. Our results suggest that SARS-CoV-2 developed a 280 mechanism to antagonize DAXX restriction, with PLpro inducing its degradation to the proteasome 281 ( Fig. 6) . his antagonism, however, is only partial, since knocking-out DAXX still enhances SARS-CoV-282 2 replication (Fig. 2) . Another possibility is that DAXX, by acting early in the viral life cycle (i.e. as soon 283 as 8 hours p.i., Fig. 3 ) may exert its antiviral effect before PLpro is able to complete its degradation.

Proteins expressed by other viruses are also able to degrade DAXX: for instance, the AdV5 viral factor 285 E1B-55K targets DAXX for proteasomal degradation (60), and FDMV PLpro cleaves DAXX (56). We 286 showed in Fig. 2 that SARS-CoV, but not MERS-CoV, is sensitive to DAXX. Thus, it will be interesting 287 to test whether PLpro from these different coronaviruses differ in their ability to degrade DAXX, and 

harvesting at 3 dpi) using DMEM supplemented with 2% FBS and 1 μg/mL TPCK-trypsin (Sigma-Aldrich #1426-321 100MG). SARS-CoV and MERS-CoV viral stocks were generated by infecting VeroE6 cells (MOI 0.0001) using 322 DMEM supplemented with 5% FCS and harvesting at 3 dpi or 6 dpi, respectively. The Yellow Fever Virus (YFV)

Asibi strain was provided by the Biological Resource Center of the Institut Pasteur. The Measles Schwarz strain 324 expressing GFP (MeV-GFP) was described previously (70). Both viral stocks were produced on Vero NK cells.

The Human Interferon-Stimulated Gene CRISPR Knockout Library was a gift from Michael Emerman and is 326 available on Addgene (Pooled Library #125753). The plentiCRISPRv.2 backbone was ordered through Addgene 327 (Plasmid #52961). pMD2.G and psPAX2 were gifts from Didier Trono (Addgene #12259; #12260). pcDNA3.1 328 was purchased from Invitrogen. Plasmids constructs expressing WT and mutant HA-tagged DAXX constructs Table S1 . PCR1 products were purified using QIAquick PCR Purification kit (Qiagen #28104). PCR2 products were purified using Agencourt AMPure XP Beads (Beckman

Coulter Life Sciences #A63880). DNA concentration was determined using Qubit dsDNA HS Assay Kit (Thermo

Fisher #Q32854) and adjusted to 2 nM prior to sequencing. NGS was performed using the NextSeq 500/550 380 High Output Kit v2.5 75 cycles (Illumina #20024906).

Screen analysis. Reads were demultiplexed using bcl2fastq Conversion Software v2.20 (Illumina) and 383 fastx_toolkit v0.0.13. Sequencing adapters were removed using cutadapt v1.9.1 (66). The reference library was 384 built using bowtie2 v2.2.9 (67). Read mapping was performed with bowtie2 allowing 1 seed mismatch in --local 385 mode and samtools v1.9 (68). Mapping analysis and gene selection were performed using MAGeCK v0.5.6, 386 normalizing the data with default parameters. sgRNA and gene enrichment analyses are available in Table S5 -387 S6, respectively and full MAGeCK output at https://github.com/Simon-LoriereLab/crispr_isg_sarscov2.

Generation of multi-guide gene knockout cells. 3 sgRNAs per gene were designed (Table S2) Table   434 S4. Cycling conditions were the following: 10 min at 55°C, 1 min at 95°C and 40 cycles of 95°C for 10s and 60°C 435 for 1 min. Results are expressed as genome copies/mL as the standard curve was performed by diluting a 436 commercially available synthetic RNA with a known concentration (EURM-019, JRC). For SARS-CoV and 437 MERS-CoV, qRT-PCR were performed using FAM-labelled probes (Eurogentech) and the Superscript III 438 Platinum One-Step qRT-PCR System (Thermo Fisher Scientific, #11732020). The cycling conditions were the 439 following: 20 min at 55°C, 3 min at 95°C and 50 cycles of 95°C for 15 s and 58°C for 30 s. The primers used are 440 described in Table S4 . Standard curves were performed using serial dilutions of RNA extracted from and SARS-

CoV and MERS-CoV viral culture supernatants of known infectious titer. For plaque assay titration, VeroE6 cells 442 were seeded in 24-well plates (10 5 cells per well) and infected with serial dilutions of infectious supernatant 443 diluted in DMEM during 1h at 37°C. After infection, 0.1% agarose semi-solid overlays were added. At 72h post-444 infection, cells were fixed with Formalin 4% (Sigma #HT501128-4L) and plaques were visualized using crystal 445 violet coloration. Time-course experiments were performed the same way except that supernatants and cellular 446 monolayers were harvested at 0h, 2h, 4h, 6h, 8h, 10h and 24h post-infection.

Overexpression assay. 2x10 5 293T-ACE2 cells were seeded in a 24-well plate 18h before experiment. Cells Table S4 .

Microscopy Immunolabeling and Imaging. 293T-ACE2 cells were cultured and infected with SARS-CoV-2 as 

Supernatants were harvested at 72h p.i. The mean of three independent experiments, with infections 531 carried out in triplicate, is shown. a: For the titration of RNA levels, supernatants were heat inactivated 532 prior to quantification by qRT-PCR. Genome copies/mL were calculated by performing serial dilutions 533 of a synthetic RNA with a known concentration. Statistics: 2-way ANOVA using Dunnett's test, * = p-534 value < 0.05, ** = p-value < 0.01, *** = p-value < 0.001, **** = p-value < 0.0001. b: For the titration of 535 infectious virus levels by plaque assay, supernatants were serially diluted and used to infect VeroE6 536 cells. Plaques formed after 3 days of infection were quantified using crystal violet coloration. Statistics:

Dunnett's test on a linear model, * p-value < 0.05, ** p-value < 0.01, *** p-value < 0.001. c: For each 538 of the indicated KO, the data shown in a. is represented as fold change in log10 titers (i.e. the triplicate 539 log10 titers of the non-treated condition divided by the mean of the triplicate log10 titers IFNa-treated 540 condition, n=3). Statistics: 2-way ANOVA using Sidak's test, ns = p-value > 0.05, **** = p-value < 

CNRS (UMR 3569), the Labex IBEID

is supported by 612 a grant of the French Ministry of Higher Education

Posadas for helpful comments on the 615 manuscript. Illustrative figures in this manuscript were created with BioRender

Contributions. F.R. designed the research project. F.R. and M.V. secured the funding for the study

generated and 620 validated KO cell lines. T.B. performed the single-cell RNAseq data analysis. S.M. and F.D. performed 621 the SARS-CoV and MERS-CoV experiments. A.B. and E.S.L. performed the bio-informatic analyses of 622 the CRISPR/Cas9 screen

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Acknowledgements. We thank the Cytometry Platform, Center for Technological Resources and 609 Research, Institut Pasteur, for cell sorting experiments. This work was funded by the Institut Pasteur

Correspondence and requests for materials should be addressed to either M.V., N.J., S.N. or F.R.

Data availability: Raw NGS data was deposited to the NCBI GEO portal and is accessible with the 631 number GSE173418.