SARS-CoV-2 infection mediates differential expression of human endogenous retroviruses and long interspersed nuclear elements.

SARS-CoV-2 promotes an imbalanced host response that underlies the development and severity of COVID-19. Infections with viruses are known to modulate transposable elements (TEs), which can exert downstream effects by modulating host gene expression, innate immune sensing, or activities encoded by their protein products. We investigated the impact of SARS-CoV-2 infection on TE expression using RNA-Seq data from cell lines and from primary patient samples. Using a bioinformatics tool, Telescope, we showed that SARS-CoV-2 infection led to upregulation or downregulation of TE transcripts, a subset of which differed from cells infected with SARS, Middle East respiratory syndrome coronavirus (MERS-CoV or MERS), influenza A virus (IAV), respiratory syncytial virus (RSV), and human parainfluenza virus type 3 (HPIV3). Differential expression of key retroelements specifically identified distinct virus families, such as Coronaviridae, with unique retroelement expression subdividing viral species. Analysis of ChIP-Seq data showed that TEs differentially expressed in SARS-CoV-2 infection were enriched for binding sites for transcription factors involved in immune responses and for pioneer transcription factors. In samples from patients with COVID-19, there was significant TE overexpression in bronchoalveolar lavage fluid and downregulation in PBMCs. Thus, although the host gene transcriptome is altered by infection with SARS-CoV-2, the retrotranscriptome may contain the most distinctive features of the cellular response to SARS-CoV-2 infection.

Identifying FDA-approved drugs with multimodal properties against COVID-19 using a data-driven approach and a lung organoid model of SARS-CoV-2 entry.

BACKGROUND: Vaccination programs have been launched worldwide to halt the spread of COVID-19. However, the identification of existing, safe compounds with combined treatment and prophylactic properties would be beneficial to individuals who are waiting to be vaccinated, particularly in less economically developed countries, where vaccine availability may be initially limited. METHODS: We used a data-driven approach, combining results from the screening of a large transcriptomic database (L1000) and molecular docking analyses, with in vitro tests using a lung organoid model of SARS-CoV-2 entry, to identify drugs with putative multimodal properties against COVID-19. RESULTS: Out of thousands of FDA-approved drugs considered, we observed that atorvastatin was the most promising candidate, as its effects negatively correlated with the transcriptional changes associated with infection. Atorvastatin was further predicted to bind to SARS-CoV-2's main protease and RNA-dependent RNA polymerase, and was shown to inhibit viral entry in our lung organoid model. CONCLUSIONS: Small clinical studies reported that general statin use, and specifically, atorvastatin use, are associated with protective effects against COVID-19. Our study corroborrates these findings and supports the investigation of atorvastatin in larger clinical studies. Ultimately, our framework demonstrates one promising way to fast-track the identification of compounds for COVID-19, which could similarly be applied when tackling future pandemics.

Genetic risk for severe COVID-19 correlates with lower inflammatory marker levels in a SARS-CoV-2-negative cohort.

OBJECTIVES: It remains unknown how inflammatory marker levels differ amongst individuals susceptible to coronavirus disease 2019 (COVID-19), prior to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the onset of the cytokine storm. We used genetic risk scores to model how susceptibility to severe COVID-19 correlates with baseline levels of 35 inflammatory markers, by testing their impact in a SARS-CoV-2-negative population cohort. Because of the established effects of age and body mass index on severe COVID-19 risk, we further considered how these variables interacted with genetic risk to affect inflammatory marker levels. METHODS: We accessed data on 406 SARS-CoV-2-negative individuals as part of a UK population study. Multiplex electrochemiluminescence methods were applied to blood serum, and 35 inflammatory markers were assayed. Corresponding genotype data, alongside results from a large genome-wide association study of severe COVID-19, allowed us to construct genetic risk scores and to test their impact on inflammatory protein levels. RESULTS: Our results revealed that a higher genetic risk for severe COVID-19 was associated with lower blood levels of interferon gamma (IFN-γ), vascular endothelial growth factor D (VEGF-D) and tumor necrosis factor alpha (TNF-α). Inflammatory profiles of those with high genetic risk increasingly diverge from the norm in association with age and obesity. CONCLUSION: Our results support the theory that individuals at risk of severe COVID-19 have a deficient innate immunity marked by reduced levels of inflammatory markers at baseline, including IFN-γ, VEGF-D and TNF-α. We hypothesise that a secondary overactive adaptive immune response may subsequently explain the high levels of cytokines observed in SARS-CoV-2-positive COVID-19 patients.

Antiretroviral drug activity and potential for pre-exposure prophylaxis against COVID-19 and HIV infection.

COVID-19 is the disease caused by SARS-CoV-2 which has led to 2,643,000 deaths worldwide, a number which is rapidly increasing. Urgent studies to identify new antiviral drugs, repurpose existing drugs, or identify drugs that can target the overactive immune response are ongoing. Antiretroviral drugs (ARVs) have been tested in past human coronavirus infections, and also against SARS-CoV-2, but a trial of lopinavir and ritonavir failed to show any clinical benefit in COVID-19. However, there is limited data as to the course of COVID-19 in people living with HIV, with some studies showing a decreased mortality for those taking certain ARV regimens. We hypothesized that ARVs other than lopinavir and ritonavir might be responsible for some protection against the progression of COVID-19. Here, we used chemoinformatic analyses to predict which ARVs would bind and potentially inhibit the SARS-CoV-2 main protease (Mpro) or RNA-dependent-RNA-polymerase (RdRp) enzymes in silico. The drugs predicted to bind the SARS-CoV-2 Mpro included the protease inhibitors atazanavir and indinavir. The ARVs predicted to bind the catalytic site of the RdRp included Nucleoside Reverse Transcriptase Inhibitors, abacavir, emtricitabine, zidovudine, and tenofovir. Existing or new combinations of antiretroviral drugs could potentially prevent or ameliorate the course of COVID-19 if shown to inhibit SARS-CoV-2 in vitro and in clinical trials. Further studies are needed to establish the activity of ARVs for treatment or prevention of SARS-CoV-2 infection .Communicated by Ramaswamy H. Sarma.