In silico analysis of genomic landscape of SARS-CoV-2 and its variant of concerns (Delta and Omicron) reveals changes in the coding potential of miRNAs and their target genes.

COVID-19 related morbidities and mortalities are still continued due to the emergence of new variants of SARS-CoV-2. In the last few years, viral miRNAs have been the centre of study to understand the disease pathophysiology. In this work, we aimed to predict the change in coding potential of the viral miRNAs in SARS-CoV-2's VOCs, Delta and Omicron compared to the Reference (Wuhan origin) strain using bioinformatics tools. After ab-intio based screening by the Vmir tool and validation, we retrieved 22, 6, and 6 pre-miRNAs for Reference, Delta, and Omicron. Most of the predicted unique pre-miRNAs of Delta and Omicron were found to be encoded from the terminal and origin of the genomic sequence, respectively. Mature miRNAs identified by MatureBayes from the unique pre-miRNAs were used for target identification using miRDB. A total of 1786, 216, and 143 high-confidence target genes were captured for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. The GO and KEGG pathways terms analysis revealed the involvement of Delta miRNAs targeted genes in the pathways such as Human cytomegalovirus infection, Breast cancer, Apoptosis, Neurotrophin signaling, and Axon guidance whereas the Sphingolipid signaling pathway was found for the Omicron. Furthermore, we focussed our analysis on target genes that were validated through GEO's (Gene Expression Omnibus) DEGs (Differentially Expressed Genes) dataset, in which FGL2, TNSF12, OGN, GDF11, and BMP11 target genes were found to be down-regulated by Reference miRNAs and YAE1 and RSU1 by Delta. Few genes were also observed to be validated among in up-regulated gene set of the GEO dataset, in which MMP14, TNFRSF21, SGMS1, and TMEM192 were related to Reference whereas ZEB2 was detected in all three strains. This study thus provides an in-silico based analysis that deciphered the unique pre-miRNAs in Delta and Omicron compared to Reference. However, the findings need future wet lab studies for validation.

In silico functional and structural characterization revealed virulent proteins of Francisella tularensis strain SCHU4.

Francisella tularensis is a pathogenic, aerobic gram-negative coccobacillus bacterium. It is the causative agent of tularemia, a rare infectious disease that can attack skin, lungs, eyes, and lymph nodes. The genome of F. tularensis has been sequenced, and ~16% of the proteome is still uncharacterized. Characterizations of these proteins are essential to find new drug targets for better therapeutics. In silico characterization of proteins has become an extremely important approach to determine the functionality of proteins as experimental functional elucidation is unable to keep pace with the current growth of the sequence database. Initially, we have annotated 577 Hypothetical Proteins (HPs) of F. tularensis strain SCHU4 with seven bioinformatics tools which characterized them based on the family, domain and motif. Out of 577 HPs, 119 HPs were annotated by five or more tools and are further screened to predict their virulence properties, subcellular localization, transmembrane helices as well as physicochemical parameters. VirulentPred predicted 66 HPs out of 119 as virulent. These virulent proteins were annotated to find the interacting partner using STRING, and proteins with high confidence interaction scores were used to predict their 3D structures using Phyre2. The three virulent proteins Q5NH99 (phosphoserine phosphatase), Q5NG42 (Cystathionine beta-synthase) and Q5NG83 (Rrf2-type helix turn helix domain) were predicted to involve in modulation of cytoskeletal and innate immunity of host, H2S (hydrogen sulfide) based antibiotic tolerance and nitrite and iron metabolism of bacteria. The above predicted virulent proteins can serve as novel drug targets in the era of antibiotic resistance.

Deciphering the functional role of hypothetical proteins from Chloroflexus aurantiacs J-10-f1 using bioinformatics approach.

Chloroflexus aurantiacus J-10-f1 is an anoxygenic, photosynthetic, facultative autotrophic gram negative bacterium found from hot spring at a temperature range of 50-60°C. It can sustain itself in dark only if oxygen is available thereby exhibiting a dark orange color, however display a dark green color when grown in sunlight. Genome of the organism contains total of 3853 proteins out of which 785 (~20%) proteins are uncharacterised or hypothetical proteins (HPs). Therefore in this work we have characterized the 785 hypothetical proteins of Chloroflexus aurantiacus J-10-f1 using bioinformatics tools and databases. HPs annotated by more than five domain prediction tools were filtered and named high confidence-hypothetical proteins (HC-HPs). These HC-HPs were further annotated by calculating their physiochemical properties, homologous, subcellular locations, signal peptides and transmembrane regions. We found most of the HC-HPs were involved in photosynthesis, carbohydrate metabolism, biofuel production and cellulose synthesis processes. Furthermore, few of these HC-HPs could provide resistance to bacteria at high temperature due to their thermophilic nature. Hence these HC-HPs have the potential to be used in industrial as well as in biomedical needs. To conclude, the bioinformatics approach used in this study provides an insight to better understand the nature and role of Chloroflexus aurantiacus J-10-f1 hypothetical proteins.

Genome-wide computational prediction of miRNAs in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) revealed target genes involved in pulmonary vasculature and antiviral innate immunity.

The current outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China threatened humankind worldwide. The coronaviruses contains the largest RNA genome among all other known RNA viruses, therefore the disease etiology can be understood by analyzing the genome sequence of SARS-CoV-2. In this study, we used an ab-intio based computational tool VMir to scan the complete genome of SARS-CoV-2 to predict pre-miRNAs. The potential pre-miRNAs were identified by ViralMir and mature miRNAs were recognized by Mature Bayes. Additionally, predicted mature miRNAs were analysed against human genome by miRDB server to retrieve target genes. Besides that we also retrieved GO (Gene Ontology) terms for pathways, functions and cellular components. We predicted 26 mature miRNAs from genome of SARS-CoV-2 that targets human genes involved in pathways like EGF receptor signaling, apoptosis signaling, VEGF signaling, FGF receptor signaling. Gene enrichment tool analysis and substantial literature evidences suggests role of genes like BMPR2 and p53 in pulmonary vasculature and antiviral innate immunity respectively. Our findings may help research community to understand virus pathogenesis.

Computational prediction of miRNAs in Nipah virus genome reveals possible interaction with human genes involved in encephalitis.

Current re-emergence of Nipah virus (NiV) in India caused 11 deaths so far and many patients were kept in quarantine. A thorough study of previous outbreaks occurred in Malaysia, Bangladesh and India represents cases with high rate of fatality due to acute encephalitis. Our work involves genome analysis of NiV for prediction of miRNAs and their targeted genes in human in order to understand encephalitis origin. Ab-intio program-VMir was used for initial screening of genome, obtained nine pre-miRNAs was analyzed by ViralMir to check for any pseudo pre-miRNAs. Eighteen functional mature miRNAs were extracted from pre-miRNAs by using Mature-Bayes tool, which targets 669 genes in human genome as retrieved by miRDB. Gene ontology terms by PANTHER provide important pathways in which target genes were involved like Axon guidance, T cell activation, and nicotinic acetylcholine receptor signaling. Significant outcome was obtained after NCBI Gene and OMIM database mining and literature search for predicted target genes. TLR3, TJP1, NOTCH2, FHL1, and GRIA3 target genes obtained showed their involvement in host defense, blood brain barrier, neurogenesis, mental retardation and encephalitis. To conclude, we predicted significant genes in human that can be inhibited by miRNAs of NiV and results in etiology of encephalitis.