No abstract

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5′, 3′ UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

Introduction: Viral hemorrhagic septicemia virus (VHSV) is the most lethal pathogen in aquaculture, infecting more than 140 fish species in marine, estuarine, and freshwater environments. Viral hemorrhagic septicemia virus is an enveloped RNA virus that belongs to the family Rhabdoviridae and the genus Novirhabdovirus. The current study is designed to infer the worldwide Viral hemorrhagic septicemia virus isolates’ genetic diversity and evolutionary dynamics based on G-gene sequences.Methods: The complete G-gene sequences of viral hemorrhagic septicemia virus were retrieved from the public repositories with known timing and geography details. Pairwise statistical analysis was performed using Arlequin. The Bayesian model-based approach implemented in STRUCTURE software was used to investigate the population genetic structure, and the phylogenetic tree was constructed using MEGA X and IQ-TREE. The natural selection analysis was assessed using different statistical approaches, including IFEL, MEME, and SLAC.Results and Discussion: The global Viral hemorrhagic septicemia virus samples are stratified into five genetically distinct subpopulations. The STRUCTURE analysis unveiled spatial clustering of genotype Ia into two distinct clusters at K = 3. However, at K = 5, the genotype Ia samples, deposited from Denmark, showed temporal distribution into two groups. The analyses unveiled that the genotype Ia samples stratified into subpopulations possibly based on spatiotemporal distribution. Several viral hemorrhagic septicemia virus samples are characterized as genetically admixed or recombinant. In addition, differential or subpopulation cluster-specific natural selection signatures were identified across the G-gene codon sites among the viral hemorrhagic septicemia virus isolates. Evidence of low recombination events elucidates that genetic mutations and positive selection events have possibly driven the observed genetic stratification of viral hemorrhagic septicemia virus samples.

The Norovirus (NoV) from the family Caliciviridae is the most common cause of gastroenteritis diseases in human. There are ten NoV genogroups are reported so far. Among these, the genogroup II (GII) is commonly prevalent and causes serious infection worldwide. The complete genome sequences of NoV GII isolates from different continental origin were retrieved from the public database. The model-based clustering approach implemented in the STRUCTURE resource was employed for assessment of genetic composition. The Mega-X and IQ tree were tools used for phylogenetic analyses. Genome-wide natural selection analyses were pursued via the maximum likelihood based methods. The demography features of NoV GII genome sequences were assessed using the BEAST package. All the NoV GII sequences initially clustered into two main subpopulations at significant K=2. The genotype GII.4 samples clearly split from the rest of all the genotypes. This indicate marked genetic distinction between norovirus GII.4 and non-GII.4 samples. The phylogenetic analyses depicted five distinct sub-clades for genotype GII.2 and seven sub-clades for GII.4 samples, speculate about the emergence of new lineages from these genotypes. Several isolates with admixed ancestry were identified, that constituted distinct sub-clusters. No continental-specific genetic distinction was observed among the NoV GII isolates. Significant genomic signatures of both positive and negative natural selection were identified across the NoV GII genes. Differential pattern of positive selection signal inferred between the GII.4 and non-GII.4 genotypes. The demographic analyses unveiled a rise in effective population size of NoV GII during 2009-2010, followed by a rapid fall in 2015.