key: cord-0782731-ozspznxi authors: Kratzel, Annika; Kelly, Jenna N.; Brueggemann, Yannick; Portmann, Jasmine; V’kovski, Philip; Todt, Daniel; Ebert, Nadine; Steinmann, Eike; Dijkman, Ronald; Zimmer, Gert; Pfaender, Stephanie; Thiel, Volker title: A genome-wide CRISPR screen identifies interactors of the autophagy pathway as conserved coronavirus targets date: 2021-02-24 journal: bioRxiv DOI: 10.1101/2021.02.24.432634 sha: 99556bc378f46ec4a8e6abec5c99c55050fc2233 doc_id: 782731 cord_uid: ozspznxi Over the past 20 years, the emergence of three highly pathogenic coronaviruses (CoV) – SARS-CoV, MERS-CoV, and most recently SARS-CoV-2 – has shown that CoVs pose a serious risk to human health and highlighted the importance of developing effective therapies against them. Similar to other viruses, CoVs are dependent on host factors for their survival and replication. We hypothesized that evolutionarily distinct CoVs may exploit similar host factors and pathways to support their replication cycle. Here, we conducted two independent genome-wide CRISPR/Cas9 knockout screens to identify pan-CoV host factors required for the replication of both endemic and emerging CoVs, including the novel CoV SARS-CoV-2. Strikingly, we found that several autophagy-related genes, including the immunophilin FKBP8, TMEM41B, and MINAR1, were common host factors required for CoV replication. Importantly, inhibition of the immunophilin family with the compounds Tacrolimus, Cyclosporin A, and the non-immunosuppressive derivative Alisporivir, resulted in dose-dependent inhibition of CoV replication in primary human nasal epithelial cell cultures that resemble the natural site of virus replication. Overall, we identified host factors that are crucial for CoV replication and demonstrate that these factors constitute potential targets for therapeutic intervention by clinically approved drugs. To identify HDFs essential for CoV infection, we performed two independent genome-82 wide loss-of-function CRISPR screens with MERS-CoV, a highly pathogenic CoV, and 83 HCoV-229E, an endemic CoV that causes mild respiratory symptoms in humans. We sought 84 to uncover HDFs required for infection by a wide range of CoVs, including highly pathogenic 85 CoVs with pandemic potential. Our results revealed that a number of autophagy-related genes, 86 including FK506 binding protein 8 (FKBP8), transmembrane protein 41B (TMEM41B), 87 vacuole membrane protein 1 (VMP1), and Membrane Integral NOTCH2 Associated Receptor 88 1 (MINAR1), were among the top hits for both CoV screens, suggesting that host factors 89 involved in autophagy may also be required for CoV replication. Importantly, we found that 90 perturbation of FKBP8 and other members of the immunophilin family by clinically approved 91 and well-tolerated drugs, but not inhibition of late cellular autophagy, inhibited CoV infection 92 in a dose-dependent manner. Overall, the genes and pathways identified in our CoV screens 93 expand the current repertoire of essential HDFs required for CoV replication that can be 94 exploited to identify novel therapeutic targets for host-directed therapies against both existing 95 and future emerging CoVs. 96 97 98 99 Results 101 change (LFC) alpha median method. RRA analysis using the second-best LFC method 133 identified 989 significantly enriched genes in the MERS-CoV screen and 332 significantly 134 genes in the HCoV-229E screen. To prioritize genes and generate a more robust dataset, we 135 focused on genes identified as significantly enriched using both methods (RRA p-value < 0.05) 136 with a LFC of ≥ 2 (Figures S1C and S1D). In total, 944 genes from the MERS-CoV screen and 137 332 genes from the HCoV-229E screen met these criteria, including 19 genes that were 138 identified by both methods in both screens ( Figures 1B, 1D , and S1D). Top scoring genes from 139 both screens are shown in Figure 1E , including several virus-specific genes as well as the 19 140 aforementioned common genes. Coronaviruses encode a spike surface glycoprotein, which 141 enables specific binding to a host-cell receptor to mediate viral entry. Known host receptors 142 include dipeptidyl peptidase 4 (DPP4) for MERS-CoV, human aminopeptidase N (ANPEP) for 143 HCoV-229E, and angiotensin-converting enzyme 2 (ACE2) for SARS-CoV and SARS-CoV2 144 24,10,11,12 . Subsequent cleavage of the spike protein by cellular proteases, such as TMPRSS2, 145 cathepsin L, and/or furin enables membrane fusion followed by release of the viral genome 146 into the cellular cytoplasm for replication 13 . Importantly, in the MERS-CoV screen, the 147 DPP4/CD26 host cell receptor was identified as the top scoring gene, whereas in the HCoV-148 229E screen, the top scoring gene was ANPEP/CD13. Moreover, the known DPP4 149 transcription factor HNFA1 was ranked second in the MERS-CoV screen, demonstrating the 150 robustness of the screen. 151 To identify and compare host cell biological processes that may be required for CoV 152 replication, we next performed Gene Ontology (GO) enrichment analysis on each screen using 153 the enriched genes identified above. This analysis uncovered multiple biological processes 154 (BP) that were significantly enriched in both CoV screens, many of which clustered together 155 into 7 overarching biological themes ( Figure 2A ). Next, we calculated the semantic similarity 156 among the 636 unique GO terms (BP) that were identified as significantly enriched in one or 157 both screens (p-value < 0.05; Table 2 ). Hierarchical clustering was then used to group similar 158 GO terms together and a representative term for each group was selected based on scores 159 assigned to each term. The latter analysis led to the identification of 44 conserved 160 representative GO terms and 51 virus-specific representative GO terms ( Figure S2A ). 161 Representative GO terms found in both MERS-CoV and HCoV-229E screens included a 162 number of immune-related terms as well as terms related to the regulation of phosphorylation, 163 kinase activity, autophagy, and lipid transport. Several specific GO terms were also protein dephosphorylation, and regulation of the c-Jun N-terminal kinase (JNK) cascade 166 ( Figure S2B ). GO terms specific to our MERS-CoV screen included regulation of exit from 167 mitosis, protein glycosylation, and syncytium formation via plasma membrane fusion. In 168 contrast, GO terms specific to HCoV-229E included regulation of coagulation and nitric oxide 169 biosynthesis ( Figure S2A ). 170 To establish which pathways and/or processes may be particularly important for CoV 171 replication, we next focused on conserved representative GO terms that included one or more 172 of the 19 genes that were significantly enriched in both of our CoV screens ( Figures 1D and 173 1E ). The resulting 70 unique GO terms and their relationships to each other are the terms 174 illustrated in Figure 2A . The 7 prominent biological themes these 70 terms clustered into are 175 also shown and include autophagy, immunity, dephosphorylation, Golgi vesicle transport, 176 catabolic processes, homeostatic processes, and developmental processes. To examine each 177 biological cluster in more detail, we constructed cluster-specific heatmaps showing all enriched 178 genes from both CoV screens associated with that cluster ( Figure 2B ). Furthermore, for each 179 cluster we inspected the network of functionally related GO terms that comprise the cluster 180 ( Figure S3A- and HCoV-299E. Strikingly, SARS-CoV and SARS-CoV-2 also replicated to lower titers in 200 respective KO cell lines expressing the specific entry receptor ACE2, confirming a conserved 201 function in the CoV replication cycle for these three genes. (Figures 3C, 3D, and S4B ). Western 202 blot analysis confirmed stable knockout of both FKBP8 and TMEM41B ( Figure 3E ). 203 Moreover, CRISPR/Cas9 mediated genome editing in MINAR1, FKBP8, and TMEM41B KO 204 cell lines were confirmed via Sanger Sequencing ( Figure S4E ). To further validate the effect 205 of the CRISPR/Cas9-mediated KO of all the three host factors, we expressed CRISPR resistant 206 variants of these host factors and observed a rescue of virus titers for MERS-CoV, HCoV-207 229E, SARS-CoV, and SARS-CoV-2, thereby confirming the antiviral effect of TMEM41B, 208 FKBP8, and MINAR1 KO ( Figure 3F ). To investigate the step of the viral replication cycle for 209 which these factors are required, we employed a vesicular stomatitis virus (VSV) pseudo 210 particle system bearing spike proteins from one of several different CoVs and encoding GFP 211 as a reporter 28 . We found knockdown of TMEM41B, FKBP8, or MINAR1 did not alter VSV 212 pseudoparticle entry mediated by spike proteins from HCoV-229E, MERS-CoV, SARS-CoV, 213 or SARS-CoV-2 ( Figure 4A ). Collectively, these findings show that there is a conserved 214 requirement for the host factors TMEM41B, FKBP8, and MINAR1 during CoV replication, 215 but not during CoV entry. 216 Despite having distinct cellular functions, TMEM41B, FKBP8, and MINAR1 are all 217 involved in the cellular or mitochondrial autophagy pathways, albeit at different stages. As 218 autophagy was also identified as one of the main conserved biological clusters in our GO 219 analysis, we next chose to focus on these factors in the context of autophagy for further 220 analysis. To confirm the association of TMEM41B, FKBP8, and MINAR1 with cellular 221 autophagy, we induced autophagy in LC3-GFP transfected KO cells using Rapamycin and 222 subsequently infected these cells with HCoV-229E. Under normal physiological conditions, 223 the cytosolic protein LC3 translocates to autophagosomal membrane structures during early 224 autophagy 29 . We thus analyzed the ability of LC3-GFP to translocate to such vesicles in 225 TMEM41B, FKBP8, and MINAR1-KO cells infected with HCoV-229E and undergoing 226 autophagy as described previously 29 and analyzed our results using immunofluorescence HCoV-229E as a representative endemic virus, we identified multiple virus-specific and 275 conserved HDFs, including several that are required for the replication of the novel pandemic 276 CoV SARS-CoV-2. GO enrichment analysis revealed that the conserved HDFs were involved 277 in diverse biological processes that clustered into seven major categories. Interestingly, we 278 found that MERS-CoV and HCoV-229E seemed to exploit different components of the same 279 biological processes, as the majority of genes involved in each biological cluster were virus 280 specific, but the overall biological processes were similar. This may be due to evolutionary 281 differences between the viruses, as MERS-CoV is part of the betacoronavirus genus whereas 282 HCoV-229E is a member of alphacoronavirus genus. Furthermore, many commonly enriched 283 genes were involved in Golgi vesicle transport, or more specifically in vesicle coating and 284 budding from membranes, as well as regulation of endocytosis and exocytosis, which are 285 known to be associated with virus entry and exit 32 . Moreover, Golgi vesicle markers have been 286 found in close proximity to CoV replication compartments, suggesting another potential 287 function for genes in this cluster during CoV replication, e.g. membrane re-organization for 288 membranous replication compartments 33 . A second prominent category was the immune 289 system cluster, which may be associated with direct exploitation of immunological host 290 responses against CoVs and thus offer potential intervention strategies. These strategies may 291 also have antiviral efficacy and work to lower dysfunctional immune responses, which is a 292 known driver of disease progression and severe lung pathology 34 . Another major category containing enriched genes in both HCoV screens was dephosphorylation. Genes involved in 294 phosphorylation and kinase activities were strongly enriched in our screens, suggesting that 295 these processes are required for HCoV replication and that other CoVs also exploit the host's 296 phosphorylation machinery for their benefit. Importantly, recent work observed striking 297 changes in phosphorylation on host and viral proteins during SARS-CoV-2 infection, including 298 many changes related to dephosphorylation and altered kinase activity 35,36 . For example, the 299 JNK signaling cascade, but also the regulation of tau-protein kinase activity, were highly 300 enriched in our MERS-CoV screen. JNKs belong to the mitogen-activated protein kinase 301 (MAPK) family and SARS-CoV-2 infection was recently shown to promote p38 MAPK 302 signaling activity 35 . Of note, the FKBP8 gene clustered into the dephosphorylation category 303 and the MINAR1 gene was included in regulation of tau-protein kinase activity, suggesting 304 that these two genes may influence CoV replication via other biological processes in addition 305 to autophagy. Along this line, therapeutical intervention targeting AP2M1 (part of the clathrin-306 dependent endocytic pathway) phosphorylation using a kinase inhibitor resulted in reduced 307 SARS-CoV, MERS-CoV and SARS-CoV-2 infection, exemplifying the antiviral potential of 308 targeting specific phosphorylation sites during viral infection 37 . Finally, our analysis also found 309 that genes involved in catabolic and homeostatic processes were significantly enriched in both 310 CoV screens. Interestingly, a similar cluster linked to cholesterol metabolism was identified in 311 previous studies, including SARS-CoV-2, HCoV-229E, and HCoV-OC43 genome-wide 312 CRISPR/Cas9-mediated KO screens and SARS-CoV-2 interactome studies 21,38 and has been 313 linked to CoV entry and membrane fusion 39 . 314 For our downstream experimental analysis, we focused on the autophagy cluster. 315 Autophagy is a cellular stress response to e.g. starvation or infection by pathogens for the 316 recycling of proteins and cell organelles to maintain cellular homeostasis 40 . The processes 317 comprises a very wide-ranging family of trafficking pathways required for the transportation 318 of cytoplasmic material to the lysosome for destruction. The ER localized TMEM41B was 319 recently identified as a gene required for early autophagosome formation and lipid mobilization 320 in three independent genome-wide CRISPR knockout screens, which also observed that 321 in human patients. To address these limitations, we also tested these drugs on primary human 387 nasal epithelial cell cultures and found that both Alisporivir and Cyclosporin A potently inhibit 388 SARS-CoV-2 replication at concentrations known to be achievable and efficacious in patients. 389 destruction of lung tissue and subsequent triggering of a host immune response. Importantly, 393 in certain cases a dysregulated immune response is associated with severe lung pathology and 394 systemic pathogenesis 34 . The latter highlights the need for dual-acting antiviral drugs that also 395 target inflammation and/or cell death. Of interest, Alisporivir also blocks mitochondrial 396 cyclophilin-D, a key regulator of mitochondrial permeability transition pore (mPTP) opening, 397 which is a mechanism involved in triggering cell death. Hence, besides its antiviral properties, 398 it is possible that Alisporivir also reduces CoV-induced lung tissue damage 65 Dunnett's multiple comparison test, using Nev 2020 version 9.0. In F, statistical significance 479 was determined by two-tailed unpaired student t-test with Welch's correction. Statistical Further information and request for resources and reagents should be directed to and will be 594 fulfilled by Volker Thiel (Volker.thiel@vetuisse.unibe.ch). Unique reagents generated in this 595 study will be made available on request. 596 Unique reagents generated in this study will be made available on request. This applies to 598 pCaggs-MINAR1mut, pCaggs-FKBP8mut, with silent mutations in Cas9 binding PAM region, 599 as well as pCaggs-TMEM41Bmut. Payment/MTA may be required. Sequencing data from CRISPR/Cas9 knockout screens will be made available in a public 602 repository upon publication. 603 the 'compareCluster' function in clusterProfiler with the 'fun' option set to "enrichGO" and a 669 formula of "Entrez ~ Screen". To reduce GO term redundancy and identify a representative 670 GO term for groups of similar terms, the rrvgo package was used in R with the similarity 671 threshold set to 0.75. Finally, the plot in Figure 2A was created using the 'emapplot_cluster' 672 function in the enrichplot package with a filtered version of the compareCluster enrichment 673 result (filtered to include representative GO terms found in both CoV screens that contained 674 one or more of the 19 common significantly enriched genes). All heatmaps were generated 675 using the pheatmap package in R with clustering distance set to "Euclidean" and using the 676 complete linkage clustering method. Volcano plots and venn diagrams were created using the 677 EnhancedVolcano and VennDiagram packages, respectively. 678 ACE2 Expression, FKBP8, TMEM41B and MINAR1 KO in Huh7 Cells 680 pSCRPSY-Tag-RFP-ACE2 (kindly provided by John Schoggins) was used for lentivirus 681 production as described above and Huh7 cells were transduced and selected for using 0.5 ug/ml in CRISPR-KO screen were ordered as forward and reverse oligos for creation of stable knock-684 out cell lines. 685 HFNA1_FWD GTCGTCTCCCACCGAGACACGCACCTCCGTGACGGTTTCGAGACGTG ATP9B_FWD GTCGTCTCCCACCGAAGAGTTCAGACATACAAGTGTTTCGAGACGTG CDH7_FWD GTCGTCTCCCACCGGGTCCCGGACCAAGCGCAGCGTTTCGAGACGTG FAM110B_FWD GTCGTCTCCCACCGTCTCCACGTCCGCGTCCACTGTTTCGAGACGTG GUCY2C_FWD GTCGTCTCCCACCGGTGAAGGCCTCGACCTACTCGTTTCGAGACGTG KIAA1024_FWD GTCGTCTCCCACCGTGCACGGAATGCGGGCGACAGTTTCGAGACGTG MAP3K11_FWD GTCGTCTCCCACCGCTTCGACGAGCTGCGAGCCAGTTTCGAGACGTG OR9K2_FWD GTCGTCTCCCACCGCCATTATTATGACTGATCCTGTTTCGAGACGTG PCTP_FWD GTCGTCTCCCACCGGATCGAGAGTGACGGCAAGAGTTTCGAGACGTG C7orf50_FWD GTCGTCTCCCACCGGAGGGCCCAGCGCATCCGACGTTTCGAGACGTG DIO1_FWD GTCGTCTCCCACCGCTGCCTGCAGGCGATCCTGAGTTTCGAGACGTG ECI2_FWD GTCGTCTCCCACCGCCTTGTAACATGCCCAAACCGTTTCGAGACGTG ELFN2_FWD GTCGTCTCCCACCGGTGCCGTGCGTGCCGACTGCGTTTCGAGACGTG GLCCI1_FWD GTCGTCTCCCACCGAATAAGGCGAACCTCCTCTTGTTTCGAGACGTG HOXB6_FWD GTCGTCTCCCACCGAGACATTACCCCGCGCCCTAGTTTCGAGACGTG KAT7_FWD GTCGTCTCCCACCGGACAACTCACCATGTGCCGGGTTTCGAGACGTG NOM1_FWD GTCGTCTCCCACCGGGAGTTCGTGCACGCGACTTGTTTCGAGACGTG PIGR_FWD GTCGTCTCCCACCGGCAGGAAGGCTCGCCTATCCGTTTCGAGACGTG TIGD1_FWD GTCGTCTCCCACCGTATACTTACTCACTAAGCTGGTTTCGAGACGTG TMEM41B_FWD GTCGTCTCCCACCGTATACTTACTCACTAAGCTGGTTTCGAGACGTG ART1_FWD GTCGTCTCCCACCGGGGCCACCCCATGCTCATCGGTTTCGAGACGTG CD1C_FWD GTCGTCTCCCACCGTCGAGTAATCTTGACTTGCAGTTTCGAGACGTG FKBP8_FWD GTCGTCTCCCACCGCGTACATCTGCAGACGTCGCGTTTCGAGACGTG GIMAP4_FWD GTCGTCTCCCACCGGCGACAATGGCAGCCCAATAGTTTCGAGACGTG WNT5A_FWD GTCGTCTCCCACCGAGTATCAATTCCGACATCGAGTTTCGAGACGTG ZNF480_FWD GTCGTCTCCCACCGTCACTTACATCTGTCTGAACGTTTCGAGACGTG KRTAP13-4_FWD GTCGTCTCCCACCGAGAAATCCTGCTACCGCCCCGTTTCGAGACGTG HFNA1_REV CACGTCTCGAAACCGTCACGGAGGTGCGTGTCTCGGTGGGAGACGAC ATP9B_REV CACGTCTCGAAACACTTGTATGTCTGAACTCTTCGGTGGGAGACGAC CDH7_REV CACGTCTCGAAACGCTGCGCTTGGTCCGGGACCCGGTGGGAGACGAC FAM110B_REV CACGTCTCGAAACAGTGGACGCGGACGTGGAGACGGTGGGAGACGAC GUCY2C_REV CACGTCTCGAAACGAGTAGGTCGAGGCCTTCACCGGTGGGAGACGAC KIAA1024_REV CACGTCTCGAAACTGTCGCCCGCATTCCGTGCACGGTGGGAGACGAC MAP3K11_REV CACGTCTCGAAACTGGCTCGCAGCTCGTCGAAGCGGTGGGAGACGAC OR9K2_REV CACGTCTCGAAACAGGATCAGTCATAATAATGGCGGTGGGAGACGAC PCTP_REV CACGTCTCGAAACTCTTGCCGTCACTCTCGATCCGGTGGGAGACGAC C7orf50_REV CACGTCTCGAAACGTCGGATGCGCTGGGCCCTCCGGTGGGAGACGAC DIO1_REV CACGTCTCGAAACTCAGGATCGCCTGCAGGCAGCGGTGGGAGACGAC ECI2_REV CACGTCTCGAAACGGTTTGGGCATGTTACAAGGCGGTGGGAGACGAC ELFN2_REV CACGTCTCGAAACGCAGTCGGCACGCACGGCACCGGTGGGAGACGAC GLCCI1_REV CACGTCTCGAAACAAGAGGAGGTTCGCCTTATTCGGTGGGAGACGAC HOXB6_REV CACGTCTCGAAACTAGGGCGCGGGGTAATGTCTCGGTGGGAGACGAC KAT7_REV CACGTCTCGAAACCCGGCACATGGTGAGTTGTCCGGTGGGAGACGAC NOM1_REV CACGTCTCGAAACAAGTCGCGTGCACGAACTCCCGGTGGGAGACGAC PIGR_REV CACGTCTCGAAACGGATAGGCGAGCCTTCCTGCCGGTGGGAGACGAC TIGD1_REV CACGTCTCGAAACCAGCTTAGTGAGTAAGTATACGGTGGGAGACGAC TMEM41B_REV CACGTCTCGAAACCAGCTTAGTGAGTAAGTATACGGTGGGAGACGAC ART1_REV CACGTCTCGAAACCGATGAGCATGGGGTGGCCCCGGTGGGAGACGAC CD1C_REV CACGTCTCGAAACTGCAAGTCAAGATTACTCGACGGTGGGAGACGAC FKBP8_REV CACGTCTCGAAACGCGACGTCTGCAGATGTACGCGGTGGGAGACGAC GIMAP4_REV CACGTCTCGAAACTATTGGGCTGCCATTGTCGCCGGTGGGAGACGAC WNT5A_REV CACGTCTCGAAACTCGATGTCGGAATTGATACTCGGTGGGAGACGAC ZNF480_REV CACGTCTCGAAACGTTCAGACAGATGTAAGTGACGGTGGGAGACGAC KRTAP13-4_REV CACGTCTCGAAACGGGGCGGTAGCAGGATTTCTCGGTGGGAGACGAC 686 Oligonucleotides were denatured for 5 min at 99°C in TE buffer and then slowly adapted to 687 room temperature and assembled with pLentiCRISPRv2 vector using Golden Gate cloning. hrs cells were treated with 100 nM Rapamycin (Sigma Aldrich, S-015) or an equal volume of 791 DMSO for 6 hrs and GFP was analyzed using an EVOS FL Auto 2 Imaging System, using 10x 792 and processed as mentioned above. Alternatively, transfected cells were infected with HCoV-793 229E at a MOI 0.1 for 24 hrs and GFP expression was analyzed. Images were quantified for 794 autophagosome formation by manual counting using 5 images per condition and three 795 replicates in Fiji. Autophagosome formation was normalized to number of transfected cells. 796 For the CRISPR screens, positive enrichment scores, RRA p-values, log fold change (LFC), 799 and false discovery rates were calculated using the MAGeCK algorithm. In Figure S1B , the 800 mean normalized sgRNA counts for each biological replicate were used as input to calculate 801 pairwise correlation. The correlation matrix was generated using the 'cor' function in R with 802 the Pearson correlation method and visualized using pheatmap with the clustering performed 803 using correlation as distance metrics. 804 Significant difference in data was tested using Nev 2020, version 9.0 or GraphPad Prism 806 version 8.3.1 for Windows (GraphPad). Please refer to figure captions for details regarding the 807 statistical tests applied. P values < 0.05 were considered significant. 808 No additional resources have been created during this study. 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