key: cord-0810738-o68mentl authors: Hekman, Ryan M.; Hume, Adam J.; Goel, Raghuveera K.; Abo, Kristine M.; Huang, Jessie; Blum, Benjamin C.; Werder, Rhiannon B.; Suder, Ellen L.; Paul, Indranil; Phanse, Sadhna; Youssef, Ahmed; Alysandratos, Konstantinos D.; Padhorny, Dzmitry; Ojha, Sandeep; Mora-Martin, Alexandra; Kretov, Dmitry; Ash, Peter; Verma, Mamta; Zhao, Jian; Patten, J. J.; Villacorta-Martin, Carlos; Bolzan, Dante; Perea-Resa, Carlos; Bullitt, Esther; Hinds, Anne; Braunschweig, Ulrich; Farhangmehr, Shaghayegh; Tilston-Lunel, Andrew; Varelas, Xaralabos; Kwan, Julian H.; McComb, Mark; Basu, Avik; Saeed, Mohsan; Perissi, Valentina; Burks, Eric J.; Layne, Matthew D.; Connor, John H.; Davey, Robert; Cheng, Ji-Xin; Wolozin, Benjamin L.; Blencowe, Benjamin J.; Wuchty, Stefan; Lyons, Shawn M.; Kozakov, Dima; Cifuentes, Daniel; Blower, Michael; Kotton, Darrell N.; Wilson, Andrew A.; Mühlberger, Elke; Emili, Andrew title: Actionable Cytopathogenic Host Responses of Human Alveolar Type 2 Cells to SARS-CoV-2 date: 2020-11-19 journal: Mol Cell DOI: 10.1016/j.molcel.2020.11.028 sha: ea2e167aa15ae1e5f6430ed60b0bb75714ad8107 doc_id: 810738 cord_uid: o68mentl Human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative pathogen of the COVID-19 pandemic, exerts a massive health and socioeconomic crisis. The virus infects alveolar epithelial type 2 cells (AT2s), leading to lung injury and impaired gas exchange, but the mechanisms driving infection and pathology are unclear. We performed a quantitative phosphoproteomic survey of induced pluripotent stem cell-derived AT2s (iAT2s) infected with SARS-CoV-2 at air-liquid interface (ALI). Time course analysis revealed rapid remodeling of diverse host systems, including signaling, RNA processing, translation, metabolism, nuclear integrity, protein trafficking, and cytoskeletal-microtubule organization, leading to cell cycle arrest, genotoxic stress, and innate immunity. Comparison to analogous data from transformed cell lines revealed respiratory-specific processes hijacked by SARS-CoV-2, highlighting potential novel therapeutic avenues which were validated by a high hit rate in a targeted small molecule screen in our iAT2 ALI system. We identified phosphosites on viral membrane (M) and nucleocapsid (N) by 24 hpi (Table S1) . To verify this, we performed in vitro kinase assays with purified N, CK2, and GSK3B (see STAR*Methods) and analyzed the products via MS, confirming N phosphorylation by GSK3B on three sites (S176, S180, T391) (Table S1), two of which (S176, S180) match the expected S-R-rich consensus, suggesting a role for GSK3B in SARS-CoV-2 replication. We also confirmed CK2 phosphorylates N on S23 and S410. We generated simulation-based 3D structures to visualize phosphorylation of N by CSNKA2. Our model shows that S79 maps to the interface of the RNA binding domain in the Nterminal region of N proposed to tetramerize (Figure 3C) , suggesting a role in multimerization. Since both SARS-CoV and SARS-CoV-2 N have been shown to undergo liquid-liquid phase separation (LLPS) to facilitate viral assembly (Perdikari et al., 2020), with RNA sequestering influenced by N phosphorylation (Chang et al., 2013), we explored whether phosphorylation of J o u r n a l P r e -p r o o f SARS-CoV-2 N by GSK3B or CK2 modulated LLPS using an in vitro phase separation assay (STAR*Methods). Phosphorylation by CK2 elicited a strong increase in droplet formation at concentrations of N < 1 µM. In contrast, phosphorylation by GSK3B greatly reduced LLPS by N, increasing the concentration at which LLPS occurs by 20-fold (400 nM to 10 µM) ( Figure S4) . These data suggest that SARS-CoV-2 N phosphorylation by host kinases modulates phase separation, impacting RNA assembly and packaging. Intermediate pathways associated with clusters 3 and 4 ( Figure 3D ; Table S2 ) centered on RNA processing (e.g. splicing, 3'-end processing), cell proliferation/survival (e.g. apoptosis), and protein synthesis (e.g. mTOR signaling), indicating remodeling of host post-transcriptional programs by 6 hpi, coincident with viral replication. J o u r n a l P r e -p r o o f A motif-based assessment identified host kinases potentially mediating differential phosphorylation in the SARS-CoV-2 replication cycle. Kinases with activities predicted (FDR <0.05) to be highly responsive to infection included CSNK1E, CDK2, and EEF2K in the immediate (1 hpi) response to viral entry and activation of RPS6KA3, CDK1/2, and MAPK14 by 3-6 hpi ( Figure 3F ). While elevated CDK1/2 activity is characteristic of actively proliferating cells In late infection (24 hpi), we predicted significant activation of CAMK2G, RPS6KB2, CSNK1E, PNCK, and to a lesser extent mTOR (p<0.06) ( Figure S2 ; Table S1), and downregulation of CDK2/5, MAP2K1, AURKA, ROCK2, ERBB2, and SRC (Table S1) . Collectively, these kinases are essential signaling hubs controlling host cell growth, proliferation, and metabolism. We identified conserved phosphosites, such as in kinase activation loops, that directly reflect catalytic status or other well-characterized functions missed by enrichment criteria. Specifically, we found RPS6KB1 (S441/T444/S447), CAMK2D (T287), PAK2 (PAK2 T197/209), and CDK1 (hypophosphorylation of inhibitory T14/Y15) as potentially hyperactivated in infected iAT2s ( Figure 3H ; Table S1 ). Notably, CAMK2D interacts with SARS-CoV Nsp3 (Ma-Lauer et al., 2016) and is implicated in deregulation of innate antiviral immunity. Conversely, epidermal growth factor receptor (EGFR) was hypophosphorylated on S991/T993, which is linked to receptor internalization and downregulation ( Figure 3H ). To investigate the impact of phosphorylation, we modelled PPIs in the vicinity of differential phosphosites. The most frequently occurring interactions are dominated by kinase associations (e.g. GSK3, MAPL, CK1) mediating phosphorylation of a motif (e.g. DDX21-CK1 association, wherein CK1 phosphorylates DDX21 on Ser171) ( Figure 3I) . A diverse set of motifdomain associations were also predicted to be regulated by virus-induced changes in phosphorylation ( Figure 3J ). These include 14-3-3 domains that bind to specific phosphoserine/threonine-containing motifs on proteins involved in nuclear transport. Since our phospho/proteomic data indicated SARS-CoV-2-induced disruption of RPSK6B1 (Table S1) , reflecting increased catalytic activity, which we confirmed by immunoblotting ( Figure 4A) . Additionally, we observed hyperphosphorylation of CAMK2D at T287 (Figure 3F) , implicated in apoptotic signaling (Toko et al., 2010), coincident with hyperphosphorylation and upregulated kinase activity of PAK2 (Figure 3H ), another apoptotic target (Chan et al., 1999) . In turn, EGFR was hyperphosphorylated on S991 ( We likewise observed hyperphosphorylation of S44/S101/S102/S105 of HMGA2 3-6 hpi S44 is a known target of CDK1, which regulates its DNA binding activity (Schwanbeck et al., 2000) . Phosphorylation of C-terminal HMGA2 sites (S101/S102/S105) may also alter DNA binding to regulate host gene expression (Sgarra et al., 2009). J o u r n a l P r e -p r o o f We detected increased MAPK1 and SRPK1 activity and CLK1 levels 3-6 hpi (Table S1) To assess the impact on host splicing, we screened RNA-seq data sets of control and SARS-CoV-2-infected iAT2 samples (STAR*Methods) for alternative splicing events triggered by SR phosphorylation (Figure 4D ). Large effects were observed on exon cassette (EC) inclusion 24 hpi ( Figure 4D /E), with ~200 exons displaying decreasing inclusion or intron retention (IR) ( Figure 4F ; Table S2 ), potentially impacting diverse host functions. We performed RT-PCR to directly evaluate processing of FERMT3, CCNL1, DOCK4, RBM5, FMR1, NPR2, and CLK1 transcripts displaying IR defects, and observed differential splicing of retained introns in infected cells ( Figure 4G ). Besides reduced IR in CLK1, increased inclusion of EC 4 of CLK1 was observed, a stress signal that activates CLK1 (Ninomiya et al., 2011). These data are consistent with the SR hyperphosphorylation we detected in infected iAT2s (Table S1) . Collectively, these results imply that SARS-CoV-2 primes viral replication via altered RNA processing, which disrupts AT2 gene expression. J o u r n a l P r e -p r o o f While viral replication occurs in the cytoplasm, the observed RNA splicing defects imply that host nuclear functions are impacted by SARS-CoV-2 infection. Consistent with this, we detected extensive phosphorylation of lamins (LMNA/B1/B2) suggestive of nuclear lamina disruption (de Castro et al., 2018), which was confirmed by transmission electron microscopy ( Figure 4G ). While the nuclear envelope of the mock-infected cells was intact, we observed considerable changes in SARS-CoV-2-infected iAT2s 24 hpi, in which nuclear envelopes appeared distended, while the quantity of ER in close proximity was greatly increased and studded with ribosomes. We also observed increased phosphorylation of major centrosomal proteins, such as CEP170 (S135/S138) at 6 hpi and CEP131 (S414/S416/S417) at 24 hpi ( Table S1 ).The phosphorylation of these proteins, the fact that their phosphorylation by Polo-like kinases PLK1/4 is tightly controlled during mitosis (Denu et al., 2019), and the lack of other markers of mitosis point to aberrant regulation and suggest SARS-CoV-2 remodels the centrosomemicrotubule system. To test this, we analyzed the intracellular distribution of the centrosomal marker γ-tubulin by IFA. While a distinct single centrosomal focus was observed in mockinfected cells, SARS-CoV-2-infected iAT2s exhibited dispersed cytoplasmic γ-tubulin foci ( Figure 4H) , suggestive of centrosome fragmentation that would disrupt mitotic programs. Additionally, consistent with the elevated expression of CEP152 detected at 3-6 hpi (Table S1) To explore alveolar pathways and processes altered by SARS-CoV-2 infection, we performed enrichment analyses on our differential protein and phosphoprotein profiles. We merged significant results (FDR <0.1; Table S2 ) into higher-level modules based on shared components Figure S5 ). These map to TNF production (HSPB1, MIF), cellular RNA polymerase regulation (ITGA3, PRKDC, SUB1, AKR1B1), and response to dsRNA (MAVS, CAV1), suggesting that cellular context dominates the host response. One example unique to iAT2s is Claudin-18a, a marker of alveolar epithelial cells, which decreased significantly 3-6 hpi (Table S1) After merging all phospho/proteomic enrichments prior to matching (Table S2) , only 71 pathways were altered across all four studies ( Figure 5B) . These included disrupted cell cycle, nucleic acid metabolism, and immune signaling ( Figure 5C ). Strikingly, A549 cells showed predominant downregulation, whereas Vero E6 showed upregulation of these components. Dozens of pathways were preferentially impacted in infected iAT2s ( Figure 5A ), including dysregulation of tight junction organization and lipid metabolism, providing a contextual viral signature in distal lung epithelial cells. To explore the therapeutic potential of our data, we examined the network of differential host phospho/proteins to identify potential points of vulnerability. In particular, we solved a Steiner tree problem (STAR*Methods), connecting the largest number of differential features (leaves) to upstream regulators (connectors) (Figure 6A ). We then inferred druggable linchpins Random sampling showed linchpins were significantly (P <0.0001, Fisher's) more actionable ( Figure 6C) . Strikingly, these network hubs were enriched for interaction partners of SARS-CoV-2 effector proteins (Gordon et al., 2020) ( Figure 6D) , and for highly connected viral targets ( Figure 6E ), reinforcing their relevance to viral replication. As a corollary, we ranked iAT2 linchpins based on frequency of links to host proteins ( Figure 6F) . Intriguingly, most of these nodes were non-differential in other infected cell lines such as Caco-2. We leveraged our data-driven targets to select small molecule inhibitors to test for anti-SARS-CoV-2 activity in iAT2s. We selected compounds from ~7,000 approved drugs and leads in Intriguingly, other inhibitors which failed to inhibit SARS-CoV-2 replication in Vero E6 cells were potent in iAT2s (Table S2) . Four (levofloxacin, FRAX486, losmapimod, AZ20) exhibiting <10% reduction in Vero E6 displayed more than a log reduction in iAT2s ( Figure 6G /H). Levofloxacin, a quinolone antibiotic used to treat pneumonia, inhibits topoisomerase TOP2A. FRAX486, a PAK2 inhibitor, was recently reported to inhibit SARS-CoV-2 in human Huh7.5 cells, but not in Calu-3 adenocarcinoma cells (Dittmar et al., 2020). Losmapimod, a MAP kinase inhibitor not previously identified as a SARS-CoV-2 antiviral, is currently in a Phase 3 clinical trial as an anti-inflammatory therapeutic (Grimes and Grimes, 2020). Finally, AZ20, a selective ATR inhibitor, highlights a novel target for SARS-CoV-2 inhibition directly relevant to human pulmonary cells. To gain insight into the molecular mechanisms underlying cell-type/species-specific differences in drug activity, we structurally modeled the compounds bound to active sites of their respective targets in Vero E6 cells (Chlorocebus sabaeus) and iAT2s (Homo sapiens). In line with our results that KN-93 efficiently blocked SARS-CoV-2 replication in both cell lines, we did not observe any structural differences in the predicted KN-93 binding pockets of human and C. sabaeus CAMK2A ( Figure 6I ). In contrast, we identified amino acid differences in the predicted levofloxacin binding site of TOP2A (490 isoleucine in human substituted for methionine in the C. sabaeus protein). Since methionine is bulkier than isoleucine, steric differences could account for species-specific differences in compound activity. While we did not find major structural differences in the MAPK14 pocket for losmapimod, differences around the pocket might cause an allosteric hindrance to compound engagement ( Figure S6 ). J o u r n a l P r e -p r o o f SARS-CoV-2 infection disrupts molecular processes required for normal lung homeostasis leading to impaired pulmonary function. Elucidating which cellular pathways the virus hijacks in a native alveolar context is paramount for understanding pathogenesis and devising treatments. To this end, we combined human primary-like AT2 cells with phospho/proteomic time course analysis that demonstrate diverse host responses to infection of alveolar epithelial cells. Our approach mapped iAT2 responses during early infection, before viral particle formation, and later stages characterized by dominant viral replication. Our data suggest a dynamic disease signature that evolves as the virus disrupts host programs and rewires modules (Figure 7) . Our study is an advance over recent work (Bouhaddou et We also noted hyperphosphorylation of MST kinase and upregulation of LATS1 and MOB1A by 24 hpi, implicating Hippo pathway signaling (Figure 7) . Several lines of evidence point to growth arrest and apoptosis in infected iAT2s. First, we found hyperphosphorylation of EGFR at S991 (Figure 3F) , a site linked to internalization. Second, we observed a DNA damage response in infected iAT2s, characterized by increased ATR kinase by 6 hpi, hypoactive cell cycle kinases, and direct phosphoproteomic evidence of activated pro-apoptotic kinase CAMK2D, suggesting that SARS-CoV-2 disrupts multiple signaling modules to cause AT2 growth arrest and apoptosis, potentially contributing to pulmonary necrosis (Carsana et al., 2020) . Exploring the mechanism by which SARS-CoV-2 promotes centrosomal abnormalities and the impact of PLK-inhibition in attenuating this process is warranted. We leveraged our dataset to discover drug targets by identifying viral signaling linchpins. In addition to tubercidin, which targets SARS-CoV-2 replicase, we identified 5 drugs inhibiting viral replication by >90% in iAT2s, of which 4 showed no or weak efficacy (<10% inhibition) in Vero E6 cells (Figure 6G ,I). Since we performed our screen, a Phase 3 clinical trial for treatment of COVID-19 was initiated with losmapimod, a MAP kinase inhibitor and potent antiviral in iAT2s that did not show antiviral activity in Vero E6 ( Figure S6 ). Structural modeling suggested a potential molecular mechanism underlying the species specificity, highlighting the need for disease-relevant models. Potentially potent inhibitors of viral replication may be overlooked if antiviral screens continue to be performed in physiologically irrelevant cell lines. Our use of a simplified, single cell type system (iAT2s) does not capture the functional heterogeneity of the distal lung. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Andrew Emili (aemili@bu.edu). Reagents or materials used in this work may be requested from the Lead Contact by signing a completed material transfer agreement. Pluripotent stem cell lines described in this study are available from the CReM repository at the Boston University School of Medicine. More information regarding these lines can be found at http://www.bu.edu/dbin/stemcells/. The mass spectrometry proteomics data (including the files for viewing the annotated spectra) SARS-CoV-2 infections of iAT2s were performed as previously described (Huang et al., 2020). Briefly, iAT2s plated in ALI culture for 7-21 days were infected with SARS-CoV-2 at the indicated MOIs or mock-infected by adding 100 µl inoculum to the apical chamber. Inoculum For immunofluorescence staining, iAT2s cultured on Transwell inserts were fixed in 10% formalin for 30 minutes to 12 hours and stained, mounted, and imaged as previously described Grace Bio-labs), cover-slipped then inverted (allowing forming droplets to settle by gravity onto coverslips) and incubated at 24°C for 2 hours. Droplets in imaging spacers were imaged at 63x on a Zeiss AxioObserver A1 microscope using differential interference contrast (DIC). Bioinformatic analysis was performed using R: A language and environment for Statistical Briefly, the iAT2s were lysed and the virus inactivated by re-suspending the cell pellets in 100 µL of urea lysis buffer (9 M urea, 20 mM HEPES pH 8.0) followed by heating to 100°C for 10 minutes. Twenty five micrograms of protein lysate was run on a 12% SDS-PAGE Stain-Free gel (Bio-Rad). Stain-free gels were imaged using a ChemiDoc (BioRad) to ensure equal loading before transferring to Nitrocellulose using Turbo TransBlot. Membranes were blocked in 5% milk, 0.02% sodium azide in TBST at room temperature for 1 hour. Primary antibodies were incubated overnight at 4°C while rocking in 5% normal horse serum in TBS. Blots were washed 3 times in TBST at room temperature. Secondary antibodies (Immun-Star HRP, BioRad) were incubated with membranes for 1 hour at room temperature in 5% normal horse serum in TBS before washing 3 times in TBST. Chemiluminescent detection was performed using Pierce PicoPlus ECL detection reagent and imaged using BioRad ChemiDoc. Alternative splicing was analyzed using vast-tools v2. In a directed weighted molecular interaction network, we considered a set of 'prized genes' (e.g. differentially expressed or phosphorylated genes) with a non-zero score in a network of weighted molecular interactions. To solve the Steiner Forest problem we prune away proteins and interactions until a forest of trees remains that simultaneously maximizes the sum of the gene prizes and the sum of the edge weights, creating a forest of trees that connects as many prized host proteins that are connected through as few non-prized nodes as possible. The prizes on a protein reflect its importance, indicating its chance to be selected in the optimal forest. As a consequence, all leafs (i.e. terminal nodes) in the optimal forest are prized proteins. Edge weights take values between 0 and 1, indicating that edges with higher weights are more likely to be selected in the optimal forest. More formally, given a weighted graph G(V, E) with node set V, edge set E, a function p(v) that assigns a prize to each node v ∈ V, a function w(e) that assigns a weight to each edge e ∈ E, we seek to find a forest F( VF , EF ) that minimizes the objective function w(e), suggesting that edges with low cost c(e) = 1 -w(e) are more likely to be selected in the optimal forest. Given a directed edge e = (x, y), where the node x is the tail or the source of the interaction and node y is the head, we defined that the weighting function is the reciprocal of the outdegree of x as ( ) = !"# $% . Consequently, edges that involve tail genes with high outdegree will be more likely to be removed during the Steiner forest optimization. Such a step allowed us to more effectively penalize hub nodes, indicating higher confidence that edges selected in the optimal forest are more specific to a viral response instead. As for a set of priced genes, we considered genes that were significantly differentially expressed or phosphorylated in each time step after infection if their corresponding FDR < 0.05. To generate four networks that show how interactions evolve in a cohesive manner, we assigned uniform prizes to host proteins that were differentially expressed or phosphorylated Proteomic data and phosphoproteomic data used for analysis, Kinase enrichment analysis based on phosphoproteomic data and RNA-seq data used for analysis. Prot_1-3-6 Hour: Proteomics abundance data and protein annotation at 1, 3, and 6 hours. Normalized data extracted from MaxQuant proteinGroups.txt file, with feature annotation, and differential analysis statistics. Phospho_1-3-6 Hour: Phosphoproteomic abundance data and protein annotation at 1, 3, and 6 hours. Normalized data extracted from MaxQuant PhosphoSites file, with feature annotation, and differential analysis statistics. Proteomics _24 Hour: Proteomics abundance data and protein annotation at 24 hours. Normalized data extracted from MaxQuant proteinGroups.txt file, with feature annotation, and differential analysis statistics. Phospho_24 Hour: Phosphoproteomic abundance data and protein annotation at 24 hours. Phosphoproteomic abundance data and protein annotation at 1, 3, and 6 hours. Normalized data extracted from the MaxQuant PhosphoSites file, with feature annotation and differential statistics. In vitro kinase assay: Phosphoproteomic data corresponding to in vitro kinase assays performed using GSK3 and CNSK2 as kinases and SARS-CoV-2 Nucleoprotein (N) as substrate. Phosphosites on N, upon incubation with either kinase are annotated. Drug Table: Based on our prediction of drug targets in Fig. 5 in the main paper, we annotated confirmed 22 genes as successful targets with their corresponding drugs. We also added drugs that targeted the underlying genes but proved ineffective in hampering SARS-CoV-2. Candidate Drugs: Candidate drugs that target differential proteins across timepoints in our dataset. 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Sci Rep Concerted regulation of nuclear and cytoplasmic activities of SR proteins by AKT Proteomics of SARS-CoV-2-infected host cells reveals therapy targets Identification of broadspectrum antiviral compounds and assessment of the druggability of their target for efficacy against respiratory syncytial virus (RSV) The Global Phosphorylation Landscape of SARS-CoV-2 Infection Pulmonary post-mortem findings in a series of COVID-19 cases from northern Italy: a two-centre descriptive study Kinase-substrate enrichment analysis provides insights into the heterogeneity of signaling pathway activation in leukemia cells PAK2 is cleaved and activated during hyperosmotic shock-induced apoptosis via a caspase-dependent mechanism: evidence for the involvement of oxidative stress We thank team members for expert support. We acknowledge the following sources of funding:KMA (NIH F30HL147426); RBW (CJ Martin Fellowship from the Australian NHMRC). KDA (IM Rosenzweig Award, Pulmonary Fibrosis Foundation); BW (NIH AG056318, AG064932,