A new coronavirus infection, COVID-19, has recently emerged, and has caused a global pandemic along with an international public health emergency. Currently, no licensed vaccines are available for COVID-19. The identification of immunodominant epitopes for both B- and T-cells that induce protective responses in the host is crucial for effective vaccine design. Computational prediction of potential epitopes might significantly reduce the time required to screen peptide libraries as part of emergent vaccine design. In our present study, we used an extensive immunoinformatics-based approach to predict conserved immunodominant epitopes from the proteome of SARS-CoV-2. Regions from SARS-CoV-2 protein sequences were defined as immunodominant, based on the following three criteria regarding B- and T-cell epitopes: (i) they were both mapped, (ii) they predicted protective antigens, and (iii) they were completely identical to experimentally validated epitopes of SARS-CoV. Further, structural and molecular docking analyses were performed in order to understand the binding interactions of the identified immunodominant epitopes with human major histocompatibility complexes (MHC). Our study provides a set of potential immunodominant epitopes that could enable the generation of both antibody- and cell-mediated immunity. This could contribute to developing peptide vaccine-based adaptive immunotherapy against SARS-CoV-2 infections and prevent future pandemic outbreaks.

Summary: Riboswitches are non-coding RNA located in the 5′ untranslated regions where they bind a target metabolite used to specify the riboswitch class and control the expression of associated genes. Accurate identification of riboswitches is the first step towards understanding their regulatory and functional roles in the cell. In this article, we describe a new web application named Riboswitch Scanner which provides an automated pipeline for pHMM-based detection of riboswitches in partial as well as complete genomic sequences rapidly, with high sensitivity and specificity. Availability and implementation: Riboswitch Scanner can be freely accessed on the web at http://service.iiserkol.ac.in/∼riboscan/. Contact:mukherjee.sumit89@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.

The recently emerged SARS-CoV-2 virus is responsible for the ongoing COVID-19 pandemic that has rapidly developed into a global public health threat. Patients severely affected with COVID-19 present distinct clinical features, including acute respiratory disorder, neutrophilia, cytokine storm, and sepsis. In addition, multiple pro-inflammatory cytokines are found in the plasma of such patients. Transcriptome sequencing of different specimens obtained from patients suffering from severe episodes of COVID-19 shows dynamics in terms of their immune responses. However, those host factors required for SARS-CoV-2 propagation and the underlying molecular mechanisms responsible for dysfunctional immune responses during COVID-19 infection remain elusive. In the present study, we analyzed the mRNA-long non-coding RNA (lncRNA) co-expression network derived from publicly available SARS-CoV-2-infected transcriptome data of human lung epithelial cell lines and bronchoalveolar lavage fluid (BALF) from COVID-19 patients. Through co-expression network analysis, we identified four differentially expressed lncRNAs strongly correlated with genes involved in various immune-related pathways crucial for cytokine signaling. Our findings suggest that the aberrant expression of these four lncRNAs can be associated with cytokine storms and anti-viral responses during severe SARS-CoV-2 infection of the lungs. Thus, the present study uncovers molecular interactions behind the cytokine storm activation potentially responsible for hyper-inflammatory responses in critical COVID-19 patients.

Many human genes are transcribed from both strands and produce sense-antisense gene pairs. Sense-antisense (SAS) chimeric transcripts are produced upon the coalescing of exons/introns from both sense and antisense transcripts of the same gene. SAS chimera was first reported in prostate cancer cells. Subsequently, numerous SAS chimeras have been reported in the ChiTaRS-2.1 database. However, the landscape of their expression in human cells and functional aspects are still unknown. We found that longer palindromic sequences are a unique feature of SAS chimeras. Structural analysis indicates that a long hairpin-like structure formed by many consecutive Watson-Crick base pairs appears because of these long palindromic sequences, which possibly play a similar role as double-stranded RNA (dsRNA), interfering with gene expression. RNA–RNA interaction analysis suggested that SAS chimeras could significantly interact with their parental mRNAs, indicating their potential regulatory features. Here, 267 SAS chimeras were mapped in RNA-seq data from 16 healthy human tissues, revealing their expression in normal cells. Evolutionary analysis suggested the positive selection favoring sense-antisense fusions that significantly impacted the evolution of their function and structure. Overall, our study provides detailed insight into the expression landscape of SAS chimeras in human cells and identifies potential regulatory features.

Riboswitches are metabolite or ion sensing cis-regulatory elements that regulate the expression of the associated genes involved in biosynthesis or transport of the corresponding metabolite. Among the nearly 40 different classes of riboswitches discovered in bacteria so far, only the TPP riboswitch has also been found in algae, plants, and in fungi where their presence has been experimentally validated in a few instances. We analyzed all the available complete fungal and related genomes and identified TPP riboswitch-based regulation systems in 138 fungi and 15 oomycetes. We find that TPP riboswitches are most abundant in Ascomycota and Basidiomycota where they regulate TPP biosynthesis and/or transporter genes. Many of these transporter genes were found to contain conserved domains consistent with nucleoside, urea and amino acid transporter gene families. The genomic location of TPP riboswitches when correlated with the intron structure of the regulated genes enabled prediction of the precise regulation mechanism employed by each riboswitch. Our comprehensive analysis of TPP riboswitches in fungi provides insights about the phylogenomic distribution, regulatory patterns and functioning mechanisms of TPP riboswitches across diverse fungal species and provides a useful resource that will enhance the understanding of RNA-based gene regulation in eukaryotes.