Genetic substructure and host-specific natural selection trend across vaccine-candidate ORF-2 capsid protein of hepatitis-E virus.

Hepatitis E virus is a primary cause of acute hepatitis worldwide. The present study attempts to assess the genetic variability and evolutionary divergence among HEV genotypes. A vaccine promising capsid-protein coding ORF-2 gene sequences of HEV was evaluated using phylogenetics, model-based population genetic methods and principal component analysis. The analyses unveiled nine distinct clusters as subpopulations for six HEV genotypes. HEV-3 genotype samples stratified into four different subgroups, while HEV-4 stratified into three additional subclusters. Rabbit-infectious HEV-3ra samples constitute a distinct cluster. Pairwise analysis identified marked genetic distinction of HEV-4c and HEV-4i subgenotypes compared to other genotypes. Numerous admixed, inter and intragenotype recombinant strains were detected. The MEME method identified several ORF-2 codon sites under positive selection. Some selection signatures lead to amino acid substitutions within ORF-2, resulting in altered physicochemical features. Moreover, a pattern of host-specific adaptive signatures was identified among HEV genotypes. The analyses conclusively depict that recombination and episodic positive selection events have shaped the observed genetic diversity among different HEV genotypes. The significant genetic diversity and stratification of HEV-3 and HEV-4 genotypes into subgroups, as identified in the current study, are noteworthy and may have implications for the efficacy of anti-HEV vaccines.

Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling.

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.

Population genetic analyses unveiled genetic stratification and differential natural selection signatures across the G-gene of viral hemorrhagic septicemia virus.

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.

Genomic stratification and differential natural selection signatures among human norovirus genogroup II isolates.

Noroviruses (NoVs), which are members of the family Caliciviridae, are the most common cause of gastroenteritis in humans. Ten NoV genogroups have been reported so far. Of these, genogroup II (GII) is the most prevalent, and it causes serious infections worldwide. The complete genome sequences of NoV GII isolates from different geographical regions 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 tools were used for phylogenetic analysis. Genome-wide natural selection analysis was performed using maximum-likelihood-based methods. The demographic features of NoV GII genome sequences were assessed using the BEAST package. All of the NoV GII sequences initially clustered into two main subpopulations at significant K = 2, where the genotype GII.4 samples clearly split from the rest of the genotypes. This indicates a marked genetic distinction between norovirus GII.4 and non-GII.4 samples. Phylogenetic analysis showed the presence of five distinct subclades for genotype GII.2 and seven subclades for GII.4 samples. Several isolates with admixed ancestry were identified that constituted distinct subclusters in the phylogenetic tree. No continental-specific genetic distinctions were observed among the NoV GII samples. Significant genomic signatures of both positive and negative natural selection were identified across the NoV GII genes. A differential pattern of positive selection signals was inferred between the GII.4 and non-GII.4 genotypes. The demographic analysis revealed an increase in the effective population size of NoV GII during 2009-2010, followed by a rapid fall in 2015.