Unheeded SARS-CoV-2 proteins? A deep look into negative-sense RNA.

SARS-CoV-2 is a novel positive-sense single-stranded RNA virus from the Coronaviridae family (genus Betacoronavirus), which has been established as causing the COVID-19 pandemic. The genome of SARS-CoV-2 is one of the largest among known RNA viruses, comprising of at least 26 known protein-coding loci. Studies thus far have outlined the coding capacity of the positive-sense strand of the SARS-CoV-2 genome, which can be used directly for protein translation. However, it has been recently shown that transcribed negative-sense viral RNA intermediates that arise during viral genome replication from positive-sense viruses can also code for proteins. No studies have yet explored the potential for negative-sense SARS-CoV-2 RNA intermediates to contain protein-coding loci. Thus, using sequence and structure-based bioinformatics methodologies, we have investigated the presence and validity of putative negative-sense ORFs (nsORFs) in the SARS-CoV-2 genome. Nine nsORFs were discovered to contain strong eukaryotic translation initiation signals and high codon adaptability scores, and several of the nsORFs were predicted to interact with RNA-binding proteins. Evolutionary conservation analyses indicated that some of the nsORFs are deeply conserved among related coronaviruses. Three-dimensional protein modeling revealed the presence of higher order folding among all putative SARS-CoV-2 nsORFs, and subsequent structural mimicry analyses suggest similarity of the nsORFs to DNA/RNA-binding proteins and proteins involved in immune signaling pathways. Altogether, these results suggest the potential existence of still undescribed SARS-CoV-2 proteins, which may play an important role in the viral lifecycle and COVID-19 pathogenesis

The implication of glycans on the ACE2: SARS-CoV-2 spike interaction

Since its emergence in 2019 the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) continues to a profoundly impact and threaten human health. For the development of novel prophylactic and therapeutic measures a detailed understanding of the virus-host interaction and features that modulate the interaction is of utmost importance. Attachment of the SARS-CoV-2 virus to human host cells predominantly relies on the specific interaction of the viral spike (S) surface glycoprotein with the receptor angiotensin-converting enzyme 2 (ACE-2). Glycans within or surrounding the binding interface have been demonstrated to play an important role in the ACE2:S interaction. The quality of this interaction is multifaceted and affected by several parameters, such as the speed, the number, the strength and duration of bond formation. As mutations within the coding sequences of the interaction partners may affect their binding capacity, they should be thoroughly studied. In this respect, viral evolution and the effect of mutations within the S-protein have received much attention, while human ACE2 polymorphisms naturally occurring throughout the population have so far been largely ignored. Of note, natural ACE2 polymorphisms and viral spike mutants that result in the loss of glycans within the binding interface should receive our particular attention. Please click Download on the upper right corner to see the full abstract

The M, E, and N structural proteins of the severe acute respiratory syndrome coronavirus are required for efficient assembly, trafficking, and release of virus-like particles

Copyright @ 2008 American Society for Microbiology.The production of virus-like particles (VLPs) constitutes a relevant and safe model to study molecular determinants of virion egress. The minimal requirement for the assembly of VLPs for the coronavirus responsible for severe acute respiratory syndrome in humans (SARS-CoV) is still controversial. Recent studies have shown that SARS-CoV VLP formation depends on either M and E proteins or M and N proteins. Here we show that both E and N proteins must be coexpressed with M protein for the efficient production and release of VLPs by transfected Vero E6 cells. This suggests that the mechanism of SARS-CoV assembly differs from that of other studied coronaviruses, which only require M and E proteins for VLP formation. When coexpressed, the native envelope trimeric S glycoprotein is incorporated onto VLPs. Interestingly, when a fluorescent protein tag is added to the C-terminal end of N or S protein, but not M protein, the chimeric viral proteins can be assembled within VLPs and allow visualization of VLP production and trafficking in living cells by state-of-the-art imaging technologies. Fluorescent VLPs will be used further to investigate the role of cellular machineries during SARS-CoV egress.The University of Hong Kong and the French Ministry of Health

Evaluation of the humoral and mucosal immune response of a multiepitope vaccine against COVID-19 in pigs

IntroductionThis study evaluated the immune response to a multiepitope recombinant chimeric protein (CHIVAX) containing B- and T-cell epitopes of the SARS-CoV-2 spike’s receptor binding domain (RBD) in a translational porcine model for pre-clinical studies.MethodsWe generated a multiepitope recombinant protein engineered to include six coding conserved epitopes from the RBD domain of the SARS-CoV-2 S protein. Pigs were divided into groups and immunized with different doses of the protein, with serum samples collected over time to determine antibody responses by indirect ELISA and antibody titration. Peptide recognition was also analyzed by Western blotting. A surrogate neutralization assay with recombinant ACE2 and RBDs was performed. Intranasal doses of the immunogen were also prepared and tested on Vietnamese minipigs.ResultsWhen the immunogen was administered subcutaneously, it induced specific IgG antibodies in pigs, and higher doses correlated with higher antibody levels. Antibodies from immunized pigs recognized individual peptides in the multiepitope vaccine and inhibited RBD-ACE2 binding for five variants of concern (VOC). Comparative antigen delivery methods showed that both, subcutaneous and combined subcutaneous/intranasal approaches, induced specific IgG and IgA antibodies, with the subcutaneous approach having superior neutralizing activity. CHIVAX elicited systemic immunity, evidenced by specific IgG antibodies in the serum, and local mucosal immunity, indicated by IgA antibodies in saliva, nasal, and bronchoalveolar lavage secretions. Importantly, these antibodies demonstrated neutralizing activity against SARS-CoV-2 in vitro.DiscussionThe elicited antibodies recognized individual epitopes on the chimeric protein and demonstrated the capacity to block RBD-ACE2 binding of the ancestral SARS-CoV-2 strain and four VOCs. The findings provide proof of concept for using multiepitope recombinant antigens and a combined immunization protocol to induce a neutralizing immune response against SARS-CoV-2 in the pig translational model for preclinical studies

Novel SARS-CoV-2 encoded small RNAs in the passage to humans

The Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) has recently emerged as the responsible for the pandemic outbreak of the coronavirus disease (COVID-19). This virus is closely related to coronaviruses infecting bats and Malayan pangolins, species suspected to be an intermediate host in the passage to humans. Several genomic mutations affecting viral proteins have been identified, contributing to the understanding of the recent animal-to-human transmission. However, the capacity of SARS-CoV-2 to encode functional putative microRNAs (miRNAs) remains largely unexplored. We have used deep learning to discover 12 candidate stem-loop structures hidden in the viral protein-coding genome. Among the precursors, the expression of eight mature miRNAs-like sequences was confirmed in small RNA-seq data from SARS-CoV-2 infected human cells. Predicted miRNAs are likely to target a subset of human genes of which 109 are transcriptionally deregulated upon infection. Remarkably, 28 of those genes potentially targeted by SARS-CoV-2 miRNAs are down-regulated in infected human cells. Interestingly, most of them have been related to respiratory diseases and viral infection, including several afflictions previously associated with SARS-CoV-1 and SARS-CoV-2. The comparison of SARS-CoV-2 pre-miRNA sequences with those from bat and pangolin coronaviruses suggests that single nucleotide mutations could have helped its progenitors jumping inter-species boundaries, allowing the gain of novel mature miRNAs targeting human mRNAs. Our results suggest that the recent acquisition of novel miRNAs-like sequences in the SARS-CoV-2 genome may have contributed to modulate the transcriptional reprogramming of the new host upon infection.Fil: Merino, Gabriela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina. European Molecular Biology Laboratory. European Bioinformatics Institute; Reino UnidoFil: Raad, Jonathan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Bugnon, Leandro Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Yones, Cristian Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Kamenetzky, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Claus, Juan Daniel. Universidad Nacional del Litoral; ArgentinaFil: Ariel, Federico Damian. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Stegmayer, Georgina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentin

MicroRNA Interaction Networks

La tesi di Giorgio Bertolazzi è incentrata sullo sviluppo di nuovi algoritmi per la predizione dei legami miRNA-mRNA. In particolare, un algoritmo di machine-learning viene proposto per l'upgrade del web tool ComiR; la versione originale di ComiR considerava soltanto i siti di legame dei miRNA collocati nella regione 3'UTR dell'RNA messaggero. La nuova versione di ComiR include nella ricerca dei legami la regione codificante dell'RNA messaggero.Bertolazzi’s thesis focuses on developing and applying computational methods to predict microRNA binding sites located on messenger RNA molecules. MicroRNAs (miRNAs) regulate gene expression by binding target messenger RNA molecules (mRNAs). Therefore, the prediction of miRNA binding is important to investigate cellular processes. Moreover, alterations in miRNA activity have been associated with many human diseases, such as cancer. The thesis explores miRNA binding behavior and highlights fundamental information for miRNA target prediction. In particular, a machine learning approach is used to upgrade an existing target prediction algorithm named ComiR; the original version of ComiR considers miRNA binding sites located on mRNA 3’UTR region. The novel algorithm significantly improves the ComiR prediction capacity by including miRNA binding sites located on mRNA coding regions

It isn't over ‘till it’s over: A continuing concern of the SARS-CoV-2 variants, and miRNAs targeting the S protein as a probable absolute cure

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak which still continues to affect the general population, has mutated day by day and new variants have emerged. More than 40 variants, usually caused by mutations in the spike (S) protein, have been recorded. Observation of S protein mutations in the development of t herapeutic agents will increase success rates. As we identify the three-dimensional (3D) conformation of viruses, it is more and more possible to work on models for understanding molecular interactions. Development of agents for arrays and 3D sequencing of proteins paves the way for potential therapeutic studies against variants. MicroRNAs (miRNAs) seemingly act as a potentially important group of biomolecules in combating uncontrolled cytokine release. Besides antiviral response, miRNAs promise to be  powerful therapeutic agents against infections. Studies have shown that miRNAs are able to inhibit the genome directly by miRNA-based treatments as they are sprecific to the SARS-CoV-2 genome. In order to expose this potential, in silico studies before continuing with lab studies are helpful. In our bioinformatics analysis, we proposed to compare the S protein similarities of Delta and Omicron, two of the most common variants, and to detect miRNAs targeting the S protein. The S proteins and coding sequences were compared between the two variants, and differences were determined. Within our analysis, 105 and 109 miRNAs for the Delta and Omicron variants, respectively, were detected. We believe that our study will be a potential guide for deciding on the miRNAs that may most likely have an effect on the management of the infection caused by both variants