Biochemistry-informed design selects potent siRNAs against SARS-CoV-2

RNA interference (RNAi) offers an efficient way to repress genes of interest, and it is widely used in research settings. Clinical applications emerged more recently, with 5 approved siRNAs (the RNA guides of the RNAi effector complex) against human diseases. The development of siRNAs against the SARS-CoV-2 virus could therefore provide the basis of novel Covid-19 treatments, while being easily adaptable to future variants or to other, unrelated viruses. Because the biochemistry of RNAi is very precisely described, it is now possible to design siRNAs with high predicted activity and specificity using only computational tools. While previous siRNA design algorithms tended to rely on simplistic strategies (raising fully complementary siRNAs against targets of interest), our approach uses the most up-to-date mechanistic description of RNAi to allow mismatches at tolerable positions and to force them at beneficial positions, while optimizing siRNA duplex asymmetry. Our pipeline proposes 8 siRNAs against SARS-CoV-2, and ex vivo assessment confirms the high antiviral activity of 6 out of 8 siRNAs, also achieving excellent variant coverage (with several 3-siRNA combinations recognizing each correctly-sequenced variant as of September 2022). Our approach is easily generalizable to other viruses as long as a variant genome database is available. With siRNA delivery procedures being currently improved, RNAi could therefore become an efficient and versatile antiviral therapeutic strategy.

Optimized production and fluorescent labelling of SARS-CoV-2 Virus-Like-Particles to study virus assembly and entry.

SARS-CoV-2 is an RNA enveloped virus responsible for the COVID-19 pandemia that conducted in 6 million deaths worldwide so far. SARS-CoV-2 particles are mainly composed of the 4 main structural proteins M, N, E and S to form 100nm diameter viral particles. Based on productive assays, we propose an optimal transfected plasmid ratio mimicking the virus RNA ratio allowing SARS-CoV-2 Virus-Like Particle (VLPs) formation composed of the viral structural proteins M, N, E and S. Furthermore, monochrome, dual-color fluorescent or photoconvertible VLPs were produced. Thanks to live fluorescence and super-resolution microscopy, we quantified VLPs size and concentration. It shows a diameter of 110 and 140 nm respectively for MNE-VLPs and MNES-VLPs with a minimum concentration of 10e12 VLP/ml. SARS-CoV-2 VLPs could tolerate the integration of fluorescent N and M tagged proteins without impairing particle assembly. In this condition, we were able to establish incorporation of the mature Spike in fluorescent VLPs. The Spike functionality was then shown by monitoring fluorescent MNES-VLPs docking and endocytosis in human pulmonary cells expressing the receptor hACE2. This work provides new insights on the use of non-fluorescent and fluorescent VLPs to study and visualize the SARS-CoV-2 viral life cycle in a safe environment (BSL-2 instead of BSL-3). Moreover, optimized SARS-CoV-2 VLP production can be further adapted to vaccine design strategies.

Reorganization of F-actin nanostructures is required for the late phases of SARS-CoV-2 replication in pulmonary cells.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is worldwide the main cause of the COVID-19 pandemic. After infection of human pulmonary cells, intracellular viral replication take place in different cellular compartments resulting in the destruction of the host cells and causing severe respiratory diseases. Although cellular trafficking of SARS-CoV-2 have been explored, little is known about the role of the cytoskeleton during viral replication in pulmonary cells. Here we show that SARS-CoV-2 infection induces dramatic changes of F-actin nanostructures overtime. Ring-like actin nanostructures are surrounding viral intracellular organelles, suggesting a functional interplay between F-actin and viral M clusters during particle assembly. Filopodia-like structures loaded with viruses to neighbour cells suggest these structures as mechanism for cell-to-cell virus transmission. Strikingly, gene expression profile analysis and PKN inhibitor treatments of infected pulmonary cells reveal a major role of alpha-actinins superfamily proteins in SARS-CoV-2 replication. Overall, our results highlight cell actors required for SARS-CoV2 replication that are promises for antiviral targets. TeaserImpairing regulation of actin filaments inhibits SARS-CoV-2 particle production in human pulmonary cells.

Low selectivity index of ivermectin and macrocyclic lactones on SARS-CoV2 replication in vitro argues against their therapeutic use for COVID-19.

There are very limited antiviral therapeutic options for coronavirus infections, therefore global drug re-purposing efforts are paramount to identify available compounds that could provide clinical benefits to patients with COVID-19. Ivermectin was first approved for human use as an endectocide in the 1980s. It remains one of the most important global health medicines in history and has recently been shown to exert in vitro activity against SARS-CoV-2. However, the macrocyclic lactone family of compounds has not previously been evaluated for activity against SARS-CoV-2. The present study aims at comparing their anti-viral activity in relevant pulmonary cell lines in vitro. Here, in vitro antiviral activity of the avermectins (ivermectin and selamectin) and milbemycins (moxidectin and milbemycin oxime) were assessed against a clinical isolate from a CHU Montpellier patient infected with SARS-CoV-2 in 2020. Ivermectin demonstrated anti-SARS-CoV-2 activity in vitro in human pulmonary cells in comparison to VeroE6 (with EC50 of 1-3 M). Similarly, the other macrocyclic lactones moxidectin, milbemycin oxime and selamectin reduced SARS-CoV-2 replication in vitro (with EC50 of 2-5 M). Immunofluorescence assays with ivermectin and moxidectin showed a reduction in the number of infected and polynuclear cells suggesting a drug action on viral cell fusion. However, cellular toxicity of the avermectins and milbemycins during infection showed a very low selectivity index <10 for all compounds. In conclusion, none of these agents appears suitable for human use for its anti-SARS-CoV-2 activity per se, due to low selectivity index. This is discussed in regards to recent clinical COVID studies on ivermectin.

Direct visualization of native infectious SARS-CoV-2 ant its inactivation forms using high resolution Atomic Force Microscopy

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for COVID19, a new emerging pandemic affecting humans. Here, single viruses were analyze by atomic force microscopy (AFM) operating directly in a level 3 biosafety (BSL3) facility, which appeared as a fast and powerful method to assess infectious virus morphology in its native conformation, or upon inactivation treatments, at the nanoscale level and in 3D. High resolution AFM reveals structurally intact infectious and inactivated SARS-CoV-2 upon low concentration of formaldehyde treatment. This protocol allows the preparation of intact inactivated SARS-CoV-2 particles for safe use of samples out of level 3 laboratory, as revealed by combining AFM and plaque assays, to accelerate researches against the COVID-19 pandemic. Overall, we illustrate how adapted BSL3-atomic force microscopy is a remarkable toolbox for rapid and direct virus identification and characterization.

Virus detection and identification in minutes using single-particle imaging and deep learning

The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in less than five minutes and does not require any lysis, purification or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses. Additionally, we were able to differentiate closely related strains of influenza, as well as SARS-CoV-2 variants. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic and genomic sequencing methods, and has the potential for significant impact.