An in silico pipeline approach uncovers a potentially intricate network involving spike SARS-CoV-2 RNA, RNA vaccines, host RNA-binding proteins (RBPs), and host miRNAs at the cellular level.

BACKGROUND: In the last 2 years, we have been fighting against SARS-CoV-2 viral infection, which continues to claim victims all over the world. The entire scientific community has been mobilized in an attempt to stop and eradicate the infection. A well-known feature of RNA viruses is their high mutational rate, particularly in specific gene regions. The SARS-CoV-2 S protein is also affected by these changes, allowing viruses to adapt and spread more easily. The vaccines developed using mRNA coding protein S undoubtedly contributed to the "fight" against the COVID-19 pandemic even though the presence of new variants in the spike protein could result in protein conformational changes, which could affect vaccine immunogenicity and thus vaccine effectiveness. RESULTS: The study presents the findings of an in silico analysis using various bioinformatics tools finding conserved sequences inside SARS-CoV-2 S protein (encoding mRNA) same as in the vaccine RNA sequences that could be targeted by specific host RNA-binding proteins (RBPs). According to the results an interesting scenario emerges involving host RBPs competition and subtraction. The presence of viral RNA in cytoplasm could be a new tool in the virus's armory, allowing it to improve its chances of survival by altering cell gene expression and thus interfering with host cell processes. In silico analysis was used also to evaluate the presence of similar human miRNA sequences within RBPs motifs that can modulate human RNA expression. Increased cytoplasmic availability of exogenous RNA fragments derived from RNA physiological degradation could potentially mimic the effect of host human miRNAs within the cell, causing modulation of the host cell network. CONCLUSIONS: Our in silico analysis could aid in shedding light on the potential effects of exogenous RNA (i.e. viruses and vaccines), thereby improving our understanding of the cellular interactions between virus and host biomolecules. Finally, using the computational approach, it is possible to obtain a safety assessment of RNA-based vaccines as well as indications for use in specific clinical conditions.

SARS-CoV-2 in Urine May Predict a Severe Evolution of COVID-19.

We hypothesized that the spread of SARS-CoV-2 in urine during a severe COVID-19 infection may be the expression of the worsening disease evolution. Therefore, the aim of this study was to verify if the COVID-19 disease severity is related to the viral presence in urine samples. We evaluated the clinical evolution in acute COVID-19 patients admitted in the sub-intensive care and intensive care units between 28 of December 2020 and 15th of February 2021 and being positive for SARS-CoV-2 RNA in the respiratory tract, including repeated endotracheal aspirates (ETA), sputum, nasopharyngeal swabs (NPS) and urine. We found that those subjects with SARS-COV-2 in the urine at admittance (8 out of 60 eligible patients) had a more severe disease than those with negative SARS-CoV-2 in urine. Further, they showed an increase in fibrinogen and (C-reactive Protein) CRP serum levels, requiring mechanic ventilation. Of those with positive SARS-CoV-2 in the urine, 50% died. According to our preliminary results, it seems that the presence of SARS-CoV-2 in the urine characterizes patients with a more severe disease and is also related to a higher death rate.

In Silico Analysis of Possible Interaction between Host Genomic Transcription Factors (TFs) and Zika Virus (ZikaSPH2015) Strain with Combinatorial Gene Regulation; Virus Versus Host-The Game Reloaded.

In silico analysis is a promising approach for understanding biological events in complex diseases. Herein we report on the innovative computational workflow allowed to highlight new direct interactions between human transcription factors (TFs) and an entire genome of virus ZikaSPH2015 strain in order to identify the occurrence of specific motifs on a genomic Zika Virus sequence that is able to bind and, therefore, sequester host's TFs. The analysis pipeline was performed using different bioinformatics tools available online (free of charge). According to obtained results of this in silico analysis, it is possible to hypothesize that these TFs binding motifs might be able to explain the complex and heterogeneous phenotype presentation in Zika-virus-affected fetuses/newborns, as well as the less severe condition in adults. Moreover, the proposed in silico protocol identified thirty-three different TFs identical to the distribution of TFBSs (Transcription Factor Binding Sites) on ZikaSPH2015 strain, potentially able to influence genes and pathways with biological functions confirming that this approach could find potential answers on disease pathogenesis.

A SARS-CoV-2 host infection model network based on genomic human Transcription Factors (TFs) depletion.

In December 2019 a new beta-coronavirus was isolated and characterized by sequencing samples from pneumonia patients in Wuhan, Hubei Province, China. Coronaviruses are positive-sense RNA viruses widely distributed among different animal species and humans in which they cause respiratory, enteric, liver and neurological symptomatology. Six species of coronavirus have been described (HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1) that cause cold-like symptoms in immunocompetent or immunocompromised subjects and two strains of sometimes fatal zoonotic origin that cause severe acute respiratory syndrome (SARS-CoV and MERS-CoV). The SARS-CoV-2 strain is the emerging seventh member of the coronavirus family, which is actually determining a global emergency. In silico analysis is a promising approach for understanding biological events in complex diseases and due to serious worldwide emergency and serious threat to global health, it is extremely important to use bioinformatics methods able to study an emerging pathogen like SARS-CoV-2. Herein, we report on in silico comparative analysis between complete genome of SARS-CoV, MERS-CoV, HCoV-OC43 and SARS-CoV-2 strains, to identify the occurrence of specific conserved motifs on viral genomic sequences which should be able to bind and therefore induce a subtraction of host's Transcription Factors (TFs) which lead to a depletion, an effect comparable to haploinsufficiency (a genetic dominant condition in which a single copy of wild-type allele at a locus, in heterozygous combination with a variant allele, is insufficient to produce the correct quantity of transcript and, therefore, of protein, for a correct standard phenotypic expression). In this competitive scenario, virus versus host, the proposed in silico protocol identified the TFs same as the distribution of TFBSs (Transcription Factor Binding Sites) on analyzed viral strains, potentially able to influence genes and pathways with biological functions confirming that this approach could brings useful insights regarding SARS-CoV-2. According to our results obtained by this in silico approach it is possible to hypothesize that TF-binding motifs could be of help in the explanation of the complex and heterogeneous clinical presentation in SARS-CoV-2 and subsequently predict possible interactions regarding metabolic pathways, and drug or target relationships.