RESUMEN
Combinations of direct-acting antivirals are needed to minimize drug-resistance mutations and stably suppress replication of RNA viruses. Currently, there are limited therapeutic options against the Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) and testing of a number of drug regimens has led to conflicting results. Here we show that cobicistat, which is an-FDA approved drug-booster that blocks the activity of the drug metabolizing proteins Cytochrome P450-3As (CYP3As) and P-glycoprotein (P-gp), inhibits SARS-CoV-2 replication. Cell-to-cell membrane fusion assays indicated that the antiviral effect of cobicistat is exerted through inhibition of spike protein-mediated membrane fusion. In line with this, incubation with low micromolar concentrations of cobicistat decreased viral replication in three different cell lines including cells of lung and gut origin. When cobicistat was used in combination with the putative CYP3A target and nucleoside analog remdesivir, a synergistic effect on the inhibition of viral replication was observed in cell lines and in a primary human colon organoid. The cobicistat/remdesivir combination was able to potently abate viral replication to levels comparable to mock-infected cells leading to an almost complete rescue of infected cell viability. These data highlight cobicistat as a therapeutic candidate for treating SARS-CoV-2 infection and as a potential building block of combination therapies for COVID-19.
RESUMEN
Emergence of the novel pathogenic coronavirus SARS-CoV-2 and its rapid pandemic spread presents numerous questions and challenges that demand immediate attention. Among these is the urgent need for a better understanding of humoral immune response against the virus as a basis for developing public health strategies to control viral spread. For this, sensitive, specific and quantitative serological assays are required. Here we describe the development of a semi-quantitative high-content microscopy-based assay for detection of three major classes (IgG, IgA and IgM) of SARS-CoV-2 specific antibodies in human samples. The possibility to detect antibodies against the entire viral proteome together with a robust semi-automated image analysis workflow resulted in specific, sensitive and unbiased assay which complements the portfolio of SARS-CoV-2 serological assays. The procedure described here has been used for clinical studies and provides a general framework for the application of quantitative high-throughput microscopy to rapidly develop serological assays for emerging virus infections.
RESUMEN
The global outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing coronavirus disease 2019 (COVID-19) reached over two million confirmed cases worldwide, and numbers are still growing at a fast rate. The majority of new infections are now being reported outside of China, where the outbreak officially originated in December 2019 in Wuhan. Despite the wide outbreak of the infection, a remarkable asymmetry is observed in the number of cases and in the distribution of the severity of the COVID-19 symptoms in patients with respect to the countries/regions. In the early stages of a new pathogen outbreak, it is critical to understand the dynamics of the infection transmission, in order to follow contagion over time and project the epidemiological situation in the near future. While it is possible to reason that observed variation in the number and severity of cases stem from the initial number of infected individuals, the difference in the testing policies and social aspects of community transmissions, the factors that could explain high discrepancy in areas with a similar level of healthcare still remain unknown. Here we introduce a binary classifier based on an artificial neural network that can help in explaining those differences and that can be used to support the design of containment policies. We propose that air pollutants, and specifically particulate matter (PM) 2.5 and ozone, are oppositely related with the SARS-CoV-2 infection frequency and could serve as surrogate markers to complement the infection outbreak anticipation.