Tunicamycin for COVID-19

Background: SARS-Co-V2 infection can induce ER stress-associated activation of unfolded protein response (UPR) in host cells, which may contribute to the pathogenesis of COVID-19. To understand the complex interplay between SARS-Co-V2 infection and UPR signaling, we examined the effects of acute pre-existing ER stress on SARS-Co-V2 infectivity. Methods: Huh-7 cells were treated with Tunicamycin (TUN) and Thapsigargin (THA) prior to SARS-CoV-2pp transduction (48 h p.i.) to induce ER stress. Pseudo-typed particles (SARS-CoV-2pp) entry into host cells was measured by Bright GloTM luciferase assay. Cell viability was assessed by cell titer Glo® luminescent assay. The mRNA and protein expression was evaluated by RT-qPCR and Western Blot. Results: TUN (5 µg/mL) and THA (1 µM) efficiently inhibited the entry of SARS-CoV-2pp into host cells without any cytotoxic effect. TUN and THA’s attenuation of virus entry was associated with differential modulation of ACE2 expression. Both TUN and THA significantly reduced the expression of stress-inducible ER chaperone GRP78/BiP in transduced cells. In contrast, the IRE1-XBP1s and PERK-eIF2α-ATF4-CHOP signaling pathways were downregulated with THA treatment, but not TUN in transduced cells. Insulin-mediated glucose uptake and phosphorylation of Ser307 IRS-1 and downstream p-AKT were enhanced with THA in transduced cells. Furthermore, TUN and THA differentially affected lipid metabolism and apoptotic signaling pathways. Conclusions: These findings suggest that short-term pre-existing ER stress prior to virus infection induces a specific UPR response in host cells capable of counteracting stress-inducible elements signaling, thereby depriving SARS-Co-V2 of essential components for entry and replication. Pharmacological manipulation of ER stress in host cells might provide new therapeutic strategies to alleviate SARS-CoV-2 infection.

Drug repurposing requires distinguishing established drug class targets from novel molecule-specific mechanisms and rapidly derisking their therapeutic potential in a time-critical manner, particularly in a pandemic scenario. In response to the challenge to rapidly identify treatment options for COVID-19, several studies reported that statins, as a drug class, reduce mortality in these patients. However, it is unknown if different statins exhibit consistent function or may have varying therapeutic benefit. A Bayesian network tool was used to predict drugs that shift the host transcriptomic response to SARS-CoV-2 infection towards a healthy state. Drugs were predicted using 14 RNA-sequencing datasets from 72 autopsy tissues and 465 COVID-19 patient samples or from cultured human cells and organoids infected with SARS-CoV-2. Top drug predictions included statins, which were then assessed using electronic medical records containing over 4,000 COVID-19 patients on statins to determine mortality risk in patients prescribed specific statins versus untreated matched controls. The same drugs were tested in Vero E6 cells infected with SARS-CoV-2 and human endothelial cells infected with a related OC43 coronavirus. Simvastatin was among the most highly predicted compounds (14/14 datasets) and five other statins, including atorvastatin, were predicted to be active in > 50% of analyses. Analysis of the clinical database revealed that reduced mortality risk was only observed in COVID-19 patients prescribed a subset of statins, including simvastatin and atorvastatin. In vitro testing of SARS-CoV-2 infected cells revealed simvastatin to be a potent direct inhibitor whereas most other statins were less effective. Simvastatin also inhibited OC43 infection and reduced cytokine production in endothelial cells. Statins may differ in their ability to sustain the lives of COVID-19 patients despite having a shared drug target and lipid-modifying mechanism of action. These findings highlight the value of target-agnostic drug prediction coupled with patient databases to identify and clinically evaluate non-obvious mechanisms and derisk and accelerate drug repurposing opportunities.