During the ongoing coronavirus disease 2019 (COVID-19) pandemic, a common concern has been whether widely used anti-inflammatory medications affect the risk of infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, or disease severity. Used ubiquitously for the relief of pain and inflammation, nonsteroidal anti-inflammatory drugs (NSAIDs) have been one such target of concern, with the health minister of France and the medical director of the National Health Service of England recommending the use of acetaminophen over NSAIDs for treating COVID-19 symptoms (1
NSAIDs function by inhibiting the cyclooxygenase (COX) isoforms COX-1 and COX-2. COX-1 is constitutively expressed in most cells, while COX-2 expression is induced by inflammatory stimuli (3
). COX-1 and COX-2 metabolize arachidonic acid into prostaglandin H2
, which can then be converted to several different bioactive prostaglandins (PGs), including PGD2
, and PGI2
). PGs signal through specific receptors to perform diverse roles, such as regulating immune responses and gastrointestinal barrier integrity (3
). Several potential hypotheses have linked NSAID use and COVID-19 pathogenesis. First, it has been suggested that NSAID use may upregulate angiotensin-converting enzyme 2 (ACE2), the cell entry receptor for SARS-CoV-2, and increase the risk of infection (4
). Second, NSAIDs may directly affect SARS-CoV-2 replication, since COX signaling has been shown to regulate replication of other viruses, including mouse coronavirus (6
). Third, given their anti-inflammatory properties, NSAIDs may impair the immune response to SARS-CoV-2 and delay disease resolution or, alternatively, dampen the cytokine storm associated with severe disease (1
). Therefore, given the widespread use of NSAIDs, evaluation of the interaction between NSAIDs and SARS-CoV-2 is warranted.
NSAIDs may modulate multiple stages of the SARS-CoV-2 life cycle. As described above, one potential mechanism is that NSAIDs could lead to ACE2 upregulation and thus increase susceptibility to SARS-CoV-2. Ibuprofen treatment of diabetic rats was found to increase ACE2 expression in the heart (7
). In addition, inhibition of the PGE2
receptor EP4 in human and mouse intestinal organoids increases ACE2 expression (8
), suggesting that NSAID inhibition of COX/PGE2
signaling could similarly lead to ACE2 upregulation. NSAIDs could also affect a later stage of the SARS-CoV-2 life cycle. For porcine sapovirus, feline calicivirus, murine norovirus, and mouse coronavirus, COX inhibition impairs viral replication (6
). COX inhibition was found to impair mouse coronavirus infection at a postbinding step early in the replication cycle, potentially entry or initial genome replication (6
). Furthermore, SARS-CoV, the closest relative of SARS-CoV-2 among human coronaviruses and cause of the 2002-2003 epidemic (11
), stimulates COX-2 expression via its spike and nucleocapsid proteins (12
), indicating the potential relevance of this pathway for SARS-CoV-2.
NSAIDs could also regulate the immune response to SARS-CoV-2 in multiple ways that ameliorate or exacerbate COVID-19. While mounting an immune response is necessary for clearing SARS-CoV-2 infection and establishing immunological memory to combat reinfection, it has also been appreciated that hyperinflammatory responses underlie the pathology of severe COVID-19 (14
). Studies using immunomodulatory agents to treat COVID-19 suggest that immunostimulation is helpful early in the disease course, whereas immunosuppression may be more beneficial later (14
). For example, dexamethasone treatment decreases mortality in COVID-19 patients on respiratory support but is potentially harmful for those with milder disease, suggesting that late-stage disease is mediated by hyperinflammation and therefore benefits from immunosuppression (15
). Disease severity and mortality in COVID-19 patients is associated with elevated levels of proinflammatory cytokines, including interleukin-1β (IL-1β), IL-6, interferon gamma (IFN-γ), and tumor necrosis factor alpha (TNF-α), as well as chemokines such as CCL2, CCL4, CXCL9, and CXCL10 (16
). Since PGs can regulate and amplify the production of these cytokines (18
), NSAIDs could potentially mitigate the hyperinflammatory pathology of COVID-19. However, PGs can also be immunosuppressive in certain contexts, such that NSAIDs may instead promote immune responses. For instance, PGD2
have been shown to impair both innate and adaptive immunity to influenza A virus, with PGD2
having a similar impact on SARS-CoV (20
). In addition, PGD2
signaling prevents excessive inflammasome activation during murine coronavirus-induced encephalitis (22
). Therefore, reducing PGD2
levels with NSAID treatment could improve the induction of antiviral immunity and yet also promote hyperinflammatory responses. Conversely, NSAID treatment could have detrimental effects on resolution of infection by inhibiting production of PGI2
, which is antiviral in respiratory syncytial virus infection (23
). Furthermore, NSAIDs may inhibit antibody production to SARS-CoV-2, which has been observed for other viruses, but the effect of this on disease severity is unclear as antibodies can be protective or pathogenic (24
). Altogether, given the complex and sometimes conflicting roles of PGs, it is difficult to predict the overall effect of NSAIDs on the immune response to SARS-CoV-2 and, ultimately, disease outcome.
We therefore systematically assessed the effect of NSAIDs on SARS-CoV-2 infection and the immune response to SARS-CoV-2. We found that SARS-CoV-2 infection induced COX-2 expression in human cells and mice. However, suppression of COX-2 by two commonly used NSAIDs, ibuprofen and meloxicam, had no effect on ACE2 expression, viral entry, or viral replication. In a mouse model of SARS-CoV-2 infection, NSAID treatment impaired the production of proinflammatory cytokines and neutralizing antibodies but did not affect weight loss, viral burden, or activation of innate and adaptive immune cells in the lung. These results indicate that NSAID use in humans may affect COVID-19 pathogenesis by mitigating the inflammatory response and the production of protective antibodies rather than by directly influencing viral replication.
Given the concerns about NSAID use in patients with COVID-19, we studied whether NSAIDs affect SARS-CoV-2 infection and the immune response to the virus. We found that SARS-CoV-2 infection induced PTGS2 upregulation in diverse systems, including Calu-3 and A549 lung cancer cell lines, primary HBEC air-liquid interface cultures, and the lungs of K18-hACE2 mice. Inhibition of COX-2 with the commonly used NSAIDs ibuprofen and meloxicam did not affect ACE2 expression in multiple cell and tissue types in vitro or in vivo, nor did it affect SARS-CoV-2 entry or replication. In K18-hACE2 mice infected with SARS-CoV-2, NSAID treatment impaired the production of neutralizing antibodies and proinflammatory cytokines but did not influence weight loss, viral burden, or activation state of innate and adaptive immune cells in the lung. Our findings therefore rule out a direct effect of NSAIDs on SARS-CoV-2 infection but indicate that NSAIDs could modulate COVID-19 severity by dampening production of neutralizing antibodies and inflammatory cytokines.
An important question arising from our findings is how SARS-CoV-2 infection induces COX-2 expression. One possibility is that the pattern recognition receptor retinoic acid inducible gene-I (RIG-I), which can recognize double-stranded RNA generated during viral genome replication and transcription (46
), may drive this response. Indeed, COX-2 induction by influenza A virus is RIG-I-dependent (47
), and we showed here that Huh7.5 cells, which are defective in RIG-I signaling (48
), do not upregulate PTGS2
in response to SARS-CoV-2. Alternatively, SARS-CoV-2 proteins may mediate the induction of COX-2 through their complex effects on host cells. In the case of SARS-CoV, transfection of plasmids encoding either the spike or the nucleocapsid genes is sufficient to stimulate COX-2 expression (12
). SARS-CoV spike protein induces COX-2 expression through both calcium-dependent PKCα/ERK/NF-κB and calcium-independent PI3K/PKCε/JNK/CREB pathways (13
), while the nucleocapsid protein directly binds to the COX-2 promoter to regulate its expression (12
). Any of these potential mechanisms are consistent with our HBEC scRNA-seq results demonstrating that SARS-CoV-2 increases PTGS2
expression in a cell-intrinsic manner.
One of the effects of NSAID treatment on the immune response to SARS-CoV-2 was impairment of early, neutralizing spike-specific antibodies. These early humoral responses are mediated by short-lived plasmablasts, and their requirement for T cell help is unclear (49
). NSAID treatment could therefore act by inhibiting activation (T cell-dependent or T cell-independent), proliferation, differentiation, or antibody-secreting capacity of spike-specific B cells and plasmablasts. B cells have been found to upregulate COX-2 expression following activation with T cell-dependent and T cell-independent stimuli (50
), and treatment of purified B cell cultures with NSAIDs reduces IgM and IgG production (52
). COX-2 inhibition reduces expression of BLIMP-1 and XBP-1 (53
), which are essential transcription factors for plasmablast differentiation, providing a potential mechanism by which NSAIDs impair antibody production. In addition, in mice infected with vaccinia virus, antiviral antibody production is impaired by chronic but not acute COX-2 inhibition (24
), indicating that the duration of NSAID treatment may regulate the impact on antibody production. Given that K18-hACE2 mice succumb to lethal SARS-CoV-2 disease within 7 days (36
), we could not assess the effect of NSAID treatment on long-term antibody production. This could be explored in nonlethal models of SARS-CoV-2 infection, as well as in the setting of vaccination.
Understanding the effect of NSAID treatment on cytokine production is also critical, as cytokines may be protective early in COVID-19 but potentially pathological at later stages, thus informing the timing of immunomodulatory drugs like NSAIDs. We observed that NSAID treatment decreased the production of a subset of cytokines that were induced by infection, including IL-6, CCL2, GM-CSF, CXCL10, IL-2, and TNF-α. This is consistent with prior reports of COX-2 inhibitors decreasing the production of these cytokines in various inflammatory settings (55–59
). Mechanistically, NSAIDs may reduce production of these cytokines through inhibition of the PGE2
/NF-κB positive-feedback loop, in which NF-κB and COX-2 can reciprocally activate their respective signaling pathways and amplify inflammatory responses (18
However, it is less clear whether this dampened cytokine response is beneficial, detrimental, or neutral in the setting of COVID-19 given the many roles that cytokines can play in controlling infection or driving immunopathology. GM-CSF is a myelopoietic growth factor, as well as proinflammatory cytokine, with pathogenic GM-CSF-producing Th1 cells being reported in patients with severe COVID-19 (61
). Reduction of GM-CSF production by meloxicam could therefore indicate a beneficial effect of NSAIDs on restraining hyperinflammatory responses. IL-2, IFN-γ, TNF-α can be coproduced by polyfunctional T cells, which play important roles in the control of viral infections, and yet these cytokines can also promote lethal cytokine shock and tissue damage (62–64
). In addition, while IL-6 is correlated with disease severity in COVID-19, clinical trials blocking IL-6 signaling have not shown clear evidence of benefit for patients (65
). While we observed decreased cytokine responses with NSAID treatment in K18-hACE2 mice, these changes did not translate into differences in weight loss or viral burden, suggesting that these features of the disease may involve other cytokines or pathology at other sites (e.g., the brain) not affected by NSAID treatment (36
). The timing, duration, and dosing of NSAID treatment may also matter for COVID-19 pathogenesis, potentially with early treatment impacting the initiation of antiviral immune responses and later treatment suppressing immune-driven pathology (14
). In the present study, we treated K18-hACE2 mice continuously throughout the course of infection, but it would be interesting to explore in future work whether limiting NSAID treatment to particular phases of disease has differential effects on pathogenesis.
Here, we demonstrated that SARS-CoV-2 infection induces COX-2 expression in cell lines, primary airway epithelial cells, and mice. Inhibition of COX-2 by NSAIDs did not affect viral entry or replication in vitro
or in vivo
. However, NSAID treatment impaired the production of proinflammatory cytokines and neutralizing antibodies in response to SARS-CoV-2 infection in mice. NSAIDs could therefore have complex effects on the host response to SARS-CoV-2. While studies thus far have not observed worse clinical outcomes in COVID-19 patients taking NSAIDs (66–71
), evaluation of the breadth, potency, and durability of the humoral immune response is warranted in patients on NSAIDs in response to both natural infection and vaccination.
MATERIALS AND METHODS
Calu-3 and Huh7.5 were from ATCC. Calu-3 cells were cultured in Eagle minimum essential medium with 10% heat-inactivated fetal bovine serum (FBS), 1% GlutaMAX (Gibco), and 1% penicillin/streptomycin. Huh7.5 cells were cultured in Dulbecco modified Eagle medium (DMEM) with 10% heat-inactivated FBS and 1% penicillin/streptomycin. All cell lines tested negative for Mycoplasma spp.
Generation of SARS-CoV-2 stocks.
As previously described (42
), SARS-CoV-2 P1 stock was generated by inoculating Huh7.5 cells with SARS-CoV-2 isolate USA-WA1/2020 (BEI Resources, NR-52281) at a multiplicity of infection (MOI) of 0.01 for 3 days. The P1 stock was then used to inoculate Vero-E6 cells, and after 3 days, the supernatant was harvested and clarified by centrifugation (450 × g
for 5 min), filtered through a 0.45-μm filter, and stored in aliquots at –80°C. Virus titer was determined by plaque assay using Vero-E6 cells (42
To generate icSARS-CoV-2-mNG stocks (45
), lyophilized icSARS-CoV-2-mNG was reconstituted in 0.5 ml of deionized water. Then, 50 μl of virus was diluted in 5 ml of medium and added to 107
Vero-E6 cells. After 3 days, the supernatant was harvested and clarified by centrifugation (450 × g
for 5 min), filtered through a 0.45-μm filter, and stored in aliquots at –80°C.
All work with SARS-CoV-2 or icSARS-CoV-2-mNG was performed in a biosafety level 3 facility with approval from the office of Environmental Health and Safety and the Institutional Animal Care and Use Committee at Yale University.
Preparation of NSAIDs.
Ibuprofen (I4883) and meloxicam (M3935) were purchased from Sigma-Aldrich. For cell culture experiments, ibuprofen and meloxicam were solubilized in DMSO at a stock concentration of 10 mM and then diluted in medium to make working solutions. For mouse experiments, stock solutions of ibuprofen (300 mg/ml) and meloxicam (10 mg/ml) were prepared in DMSO and then diluted 100-fold in phosphate-buffered saline (PBS) to make working solutions. To determine the maximum nontoxic dose of NSAIDs to use for cell culture experiments, cells were treated with different concentrations of ibuprofen or meloxicam for 48 h, and cell viability was measured by a CellTiter-Glo luminescent cell viability assay (Promega) according to the manufacturer’s instructions.
C57BL/6J and K18-hACE2 [B6.Cg-Tg(K18-ACE2)2Prlmn/J (29
)] were purchased from Jackson Laboratory. Mice were bred in-house using mating trios to enable utilization of littermates for experiments. Mice of both sexes between 6 and 8 weeks old were used for this study. C57BL/6J and K18-hACE2 mice were anesthetized using 30% (vol/vol) isoflurane diluted in propylene glycol (30% isoflurane) and administered 30 mg/kg ibuprofen, 1 mg/kg meloxicam, or an equivalent amount of DMSO intraperitoneally in a volume of 10 ml/kg daily for 4 or 7 days as indicated in the figure legends. K18-hACE2 mice were anesthetized using 30% isoflurane and administered 1.2 × 106
PFU or 103
PFU of SARS-CoV-2 intranasally as indicated in the figure legends. Mice were monitored daily for weight and survival. Animal use and care was approved in agreement with the Yale Animal Resource Center and Institutional Animal Care and Use Committee (no. 2018-20198) according to the standards set by the Animal Welfare Act.
Analysis of RNA-seq data.
We utilized RNA-seq data from recent published studies to assess the impact of SARS-CoV-2 infection on PTGS2
expression. From GSE147507
), we reanalyzed the raw count data from Calu-3 and A549-ACE2 cells, comparing SARS-CoV-2 infection to matched mock-treated controls. We performed differential expression analysis using the Wald test from DESeq2 (72
), using a Benjamini-Hochberg adjusted P
< 0.05 as the cutoff for statistical significance. For visualization of PTGS2
expression, the DESeq2-normalized counts were exported and plotted in GraphPad Prism. Statistical significance was assessed using a Student two-tailed, unpaired t
For analysis of HBEC air-liquid interface cultures infected with SARS-CoV-2, we utilized a previously generated catalog of differentially expressed genes that our group recently described in a preprint study (28
). The differential expression table is publicly available (https://github.com/vandijklab/HBEC_SARS-CoV-2_scRNA-seq
). Here, we specifically investigated PTGS2
expression in ciliated cells, comparing infected cells to bystander cells (cells aggregated across the 1, 2, and 3 dpi time points). The cutoff for statistical significance was set at adjusted P
< 0.05, and the results were visualized as a volcano plot in R.
), we reanalyzed the raw count data from the lungs of K18-hACE2 mice infected with SARS-CoV-2, performing pairwise comparisons of mice at 2 dpi, 4 dpi, and 7 to 0 dpi controls (prior to infection). For visualization of Ptgs2
expression, the DESeq2-normalized counts were exported and plotted in GraphPad Prism. Statistical significance was assessed using a Student two-tailed, unpaired t
Levels of PGE2 in cell culture supernatants were measured using the Prostaglandin E2 enzyme-linked immunosorbent assay (ELISA) kit (Cayman Chemical) according to the manufacturer’s instructions. Absorbance was measured at 410 nm on a microplate reader (Molecular Devices), and PGE2 concentrations were calculated using a standard curve.
Cells or tissues were lysed in TRIzol (Life Technologies), and total RNA was extracted using the Direct-zol RNA Miniprep Plus kit (Zymo Research) according to the manufacturer’s instructions. cDNA synthesis was performed using random hexamers and ImProm-II reverse transcriptase (Promega). qPCR was performed with Power SYBR Green (Thermo Fisher) and run on the QuantStudio3 (Applied Biosystems). Target mRNA levels were normalized to those of ACTB or Actb. The qPCR primer sequences were as follows: ACTB (human), GAGCACAGAGCCTCGCCTTT (forward) and ATCATCATCCATGGTGAGCTGG (reverse); PTGS2 (human), AGAAAACTGCTCAACACCGGAA (forward) and GCACTGTGTTTGGAGTGGGT (reverse); ACE2 (human), GGGATCAGAGATCGGAAGAAGAAAA (forward) and AAGGAGGTCTGAACATCATCAGTG (reverse); Actb (mouse), ACTGTCGAGTCGCGTCCA (forward) and ATCCATGGCGAACTGGTGG (reverse); Ptgs2 (mouse), CTCCCATGGGTGTGAAGGGAAA (forward) and TGGGGGTCAGGGATGAACTC (reverse); and Ace2 (mouse), ACCTTCGCAGAGATCAAGCC (forward) and CCAGTGGGGCTGATGTAGGA (reverse).
VSV-based pseudotyped viruses were produced as previously described (41
). Vector pCAGGS containing the SARS-related coronavirus 2, Wuhan-Hu-1 Spike glycoprotein gene, NR-52310, was produced under HHSN272201400008C and obtained through BEI Resources, NIAID, NIH. 293T cells were transfected with the pCAGGS vector expressing the SARS-CoV-2 spike glycoprotein and then incubated with replication-deficient VSV expressing Renilla
luciferase for 1 h at 37°C (41
). The virus inoculum was then removed, and the cells were washed with PBS before adding media with anti-VSV-G clone I4 to neutralize residual inoculum. No antibody was added to cells expressing VSV-G. Supernatant containing pseudoviruses was collected 24 h postinoculation, clarified by centrifugation, and stored in aliquots at –80°C.
Pseudovirus entry and neutralization assays.
We plated 3 × 104 Calu-3 or 1 × 104 Huh7.5 cells in a 100-μl volume in each well of a 96-well plate. The following day, the medium was replaced with 50 μM ibuprofen, 50 μM meloxicam, or an equivalent amount of DMSO. One day later, 10 μl of SARS-CoV-2 spike protein-pseudotyped (SARS2-VSVpp) or VSV glycoprotein-typed virus was added. The luciferase activity was measured at 24 hpi using the Renilla luciferase assay system (Promega). Each well of cells was lysed with 50 μl of lysis buffer, and 15 μl of cell lysate was then mixed with 15 μl of luciferase assay reagent. The luminescence was measured on a microplate reader (BioTek Synergy).
For neutralization assays, 2 × 104
Huh7.5 cells were plated in a 100-μl volume in each well of a 96-well plate. The following day, serial dilutions of serum were incubated with SARS2-VSVpp pseudovirus for 1 h at 37°C. The growth medium was then aspirated from the cells and replaced with 50 μl of the serum/virus mixture. Luciferase activity was measured at 24 hpi as detailed above. Half-maximal inhibitory concentrations (IC50
s) were calculated as previously described (73
We plated 6.5 × 103 Calu-3 or 2.5 × 103 Huh7.5 cells in 20 μl of phenol red-free medium containing 50 μM ibuprofen, 50 μM meloxicam, or an equivalent amount of DMSO in each well of a black-walled, clear-bottom 384-well plate. The following day, icSARS-CoV-2-mNG was added at an MOI of 1 in a 5-μl volume. The frequency of infected cells was measured by mNeonGreen expression at 1, 2, and 3 dpi by high content imaging (BioTek Cytation 5) configured with brightfield and GFP cubes. The total cell numbers were quantified by Gen5 software for brightfield images. Object analysis was used to determine the number of mNeonGreen-positive cells. The percentage of infection was calculated as the ratio of the number of mNeonGreen-positive cells to the total number of cells in brightfield.
Measurement of lung viral burden and cytokines.
Lungs were perfused with 3 ml of sterile PBS. The left lobe was collected and homogenized in 1 ml of DMEM supplemented with 2% heat-inactivated FBS and 1% antibiotic-antimycotic. The viral burden was measured in lung homogenates by plaque assay on Vero-E6 cells as previously described (42
). To measure cytokines, lung homogenates were incubated with a final concentration of 1% Triton X-100 for 1 h at room temperature to inactivate SARS-CoV-2. Cytokine analysis was performed by Eve Technologies using their Mouse Cytokine Array/Chemokine Array 31-Plex (MD31) platform.
Flow cytometry analysis of lung immune cells.
Lungs were perfused with 3 ml of sterile PBS. The right inferior lobe was collected and digested with 0.5 mg/ml collagenase IV (Sigma-Aldrich) and 100 U/ml DNase I (Sigma-Aldrich) in complete RPMI for 45 min at 37°C. Single-cell suspensions of digested lung tissue were preincubated with Fc block (clone 2.4G2) for 5 min at room temperature before staining. The cells were stained with the following antibodies or viability dyes for 30 min at 4°C: PE anti-CD64 (clone X54-5/7.1), PE/Cy7 anti-Ly6C (clone HK1.4), PerCP/Cy5.5 anti-CD45.2 (clone 104), APC anti-CD86 (clone GL1), AF700 anti-CD19 (clone 6D5), DAPI (4′,6′-diamidino-2-phenylindole; Thermo Fisher), BV510 anti-I-A/I-E (clone M5/114.15.2), BV605 anti-CD11c (clone N418), Live/Dead Fixable Green (Thermo Fisher), PE anti-TCRγ/δ (clone GL3), PE/Cy7 anti-CD69 (clone H1.2F3), PerCP/Cy5.5 anti-CD8 (clone 53.6-7), APC anti-CD45.2 (clone 104), APC/Cy7 anti-TCRβ (clone H57-597), AF700 anti-CD4 (clone RM4-5), PB anti-Ly6G (clone 1A8), BV510 anti-NK1.1 (clone PK136), and BV605 anti-CD44 (clone IM7). After being washed, the cells were fixed with 4% paraformaldehyde for 30 min at room temperature to inactivate SARS-CoV-2. Samples were acquired on a CytoFLEX S (Beckman Coulter) and analyzed using FlowJo software (BD).
Serum was incubated with a final concentration of 0.5% Triton X-100 and 0.5 mg/ml RNase A to inactivate any potential SARS-CoV-2. SARS-CoV-2 stabilized spike glycoprotein (BEI Resources, NR-53524) was coated at a concentration of 2 μg/ml in carbonate buffer on 96-well MaxiSorp plates (Thermo Fisher) overnight at 4°C. Plates were blocked with 1% BSA in PBS for 1 h at room temperature. Serum samples were serially diluted in 1% BSA in PBS and incubated in plates for 2 h at room temperature. Antibody isotypes were detected with anti-mouse IgM-HRP or anti-mouse IgG Fc-HRP (Southern Biotech) by incubation for 1 h at room temperature. The plates were developed with TMB stabilized chromogen (Thermo Fisher), stopped with 3 N hydrochloric acid, and read at 450 nm on a microplate reader.
Data analysis was performed using GraphPad Prism 8 unless otherwise indicated. Data were analyzed using Welch’s two-tailed, unpaired t test; Student two-tailed, unpaired t test; two-tailed Mann-Whitney test; or two-way ANOVA, as indicated. P < 0.05 was considered statistically significant.
All previously published data are available as described above. Cytokine data generated in this study are available in Table S1 in the supplemental material.
We acknowledge Benhur Lee, Pei-Yong Shi, the World Reference Center for Emerging Viruses and Arboviruses (WRCEVA), Paulina Pawlica, Joan Steitz, Michael Diamond, Adam Bailey, Emma Winkler, and BEI Resources for providing critical reagents and expertise. We thank all members of the Wilen and Eisenbarth labs for helpful discussions. We thank Yale Environmental Health and Safety for providing necessary training and support for SARS-CoV-2 research.
This study was supported by NIH Medical Scientist Training Program Training Grant T32GM007205 (J.S.C., R.D.C.), NIH/NHLBI F30HL149151 (J.S.C.), NIH/NCI F30CA250249 (R.D.C.), NIH/NIAID K08 AI128043 (C.B.W.), a Burroughs Wellcome Fund Career Award for Medical Scientists (C.B.W.), the Mathers Charitable Foundation (C.B.W.), the Ludwig Family Foundation (C.B.W.), and an Emergent Ventures Fast Grant (C.B.W.).
Jennifer S. Chen: Conceptualization, Formal Analysis, Investigation, Validation, Visualization, Writing – Original Draft; Mia Madel Alfajaro: Methodology, Investigation; Jin Wei: Methodology, Investigation; Ryan D. Chow: Formal Analysis, Visualization; Renata B. Filler: Investigation; Stephanie C. Eisenbarth: Supervision; Craig B. Wilen: Conceptualization, Formal Analysis, Funding Acquisition, Resources, Supervision, Writing – Original Draft. All authors reviewed and edited the manuscript.
Yale University (C.B.W.) has a patent pending related to this work entitled “Compounds and Compositions for Treating, Ameliorating, and/or Preventing SARS-CoV-2 Infection and/or Complications Thereof.” Yale University has committed to rapidly executable nonexclusive royalty-free licenses to intellectual property rights for the purpose of making and distributing products to prevent, diagnose, and treat COVID-19 infection during the pandemic and for a short period thereafter.