Identification of Interleukin1β as an Amplifier of Interferon alpha-induced Antiviral Responses

IFN-γ-mediated control of SARS-CoV-2 infection through nitric oxide

Introduction

The COVID-19 pandemic has highlighted the need to identify mechanisms of antiviral host defense against SARS-CoV-2. One such mediator is interferon-g (IFN-γ), which, when administered to infected patients, is reported to result in viral clearance and resolution of pulmonary symptoms. IFN-γ treatment of a human lung epithelial cell line triggered an antiviral activity against SARS-CoV-2, yet the mechanism for this antiviral response was not identified.

Methods

Given that IFN-γ has been shown to trigger antiviral activity via the generation of nitric oxide (NO), we investigated whether IFN-γ induction of antiviral activity against SARS-CoV-2 infection is dependent upon the generation of NO in human pulmonary epithelial cells. We treated the simian epithelial cell line Vero E6 and human pulmonary epithelial cell lines, including A549-ACE2, and Calu-3, with IFN-γ and observed the resulting induction of NO and its effects on SARS-CoV-2 replication. Pharmacological inhibition of inducible nitric oxide synthase (iNOS) was employed to assess the dependency on NO production. Additionally, the study examined the effect of interleukin-1b (IL-1β) on the IFN-g-induced NO production and its antiviral efficacy.

Results

Treatment of Vero E6 cells with IFN-γ resulted in a dose-responsive induction of NO and an inhibitory effect on SARS-CoV-2 replication. This antiviral activity was blocked by pharmacologic inhibition of iNOS. IFN-γ also triggered a NO-mediated antiviral activity in SARS-CoV-2 infected human lung epithelial cell lines A549-ACE2 and Calu-3. IL-1β enhanced IFN-γ induction of NO, but it had little effect on antiviral activity.

Discussion

Given that IFN-g has been shown to be produced by CD8+ T cells in the early response to SARS-CoV-2, our findings in human lung epithelial cell lines, of an IFN-γ-triggered, NO-dependent, links the adaptive immune response to an innate antiviral pathway in host defense against SARS-CoV-2. These results underscore the importance of IFN-γ and NO in the antiviral response and provide insights into potential therapeutic strategies for COVID-19.

Deciphering signal transduction networks in the liver by mechanistic mathematical modelling

In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.

IL1β Promotes TMPRSS2 Expression and SARS-CoV-2 Cell Entry Through the p38 MAPK-GATA2 Axis

After the outburst of the SARS-CoV-2 pandemic, a worldwide research effort has led to the uncovering of many aspects of the COVID-19, among which we can count the outstanding role played by inflammatory cytokine milieu in the disease progression. Despite that, molecular mechanisms that regulate SARS-CoV-2 pathogenesis are still almost unidentified. In this study, we investigated whether the pro-inflammatory milieu of the host affects the susceptibility of SARS-CoV-2 infection by modulating ACE2 and TMPRSS2 expression. Our results indicated that the host inflammatory milieu favors SARS-CoV-2 infection by directly increasing TMPRSS2 expression. We unveiled the molecular mechanism that regulates this process and that can be therapeutically advantageously targeted.

Decoding the dynamics of multilayered stochastic antiviral IFN-I responses

Type I Interferon (IFN-I) responses were first recognized for their role in antiviral immunity, but it is now widely appreciated that IFN-Is have many immunomodulatory functions, influencing antitumor responses, autoimmune manifestations, and antimicrobial defenses. Given these pivotal roles, it may be surprising that multilayered stochastic events create highly heterogeneous, but tightly regulated, all-or-nothing cellular decisions. Recently, mathematical models have provided crucial insights into the stochastic nature of antiviral IFN-I responses, which we critically evaluate in this review. In this context, we emphasize the need for innovative single-cell technologies combined with mathematical models to further reveal, understand, and predict the complexity of the IFN-I system in physiological and pathological conditions that may be relevant to a plethora of diseases.

Comparative transcriptome analysis reveals key epigenetic targets in SARS-CoV-2 infection

COVID-19 is an infection caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2), which has caused a global outbreak. Current research efforts are focused on the understanding of the molecular mechanisms involved in SARS-CoV-2 infection in order to propose drug-based therapeutic options. Transcriptional changes due to epigenetic regulation are key host cell responses to viral infection and have been studied in SARS-CoV and MERS-CoV; however, such changes are not fully described for SARS-CoV-2. In this study, we analyzed multiple transcriptomes obtained from cell lines infected with MERS-CoV, SARS-CoV, and SARS-CoV-2, and from COVID-19 patient-derived samples. Using integrative analyses of gene co-expression networks and de-novo pathway enrichment, we characterize different gene modules and protein pathways enriched with Transcription Factors or Epifactors relevant for SARS-CoV-2 infection. We identified EP300, MOV10, RELA, and TRIM25 as top candidates, and more than 60 additional proteins involved in the epigenetic response during viral infection that has therapeutic potential. Our results show that targeting the epigenetic machinery could be a feasible alternative to treat COVID-19.