Vaccine Target Discovery

Computational designing of a novel subunit vaccine for human cytomegalovirus by employing the immunoinformatics framework

Human cytomegalovirus (HCMV) is a widespread virus that can cause serious and irreversible neurological damage in newborns and even death in children who do not have the access to much-needed medications. While some vaccines and drugs are found to be effective against HCMV, their extended use has given rise to dose-limiting toxicities and the development of drug-resistant mutants among patients. Despite half a century's worth of research, the lack of a licensed HCMV vaccine heightens the need to develop newer antiviral therapies and vaccine candidates with improved effectiveness and reduced side effects. In this study, the immunoinformatics approach was utilized to design a potential polyvalent epitope-based vaccine effective against the four virulent strains of HCMV. The vaccine was constructed using seven CD8+ cytotoxic T lymphocytes epitopes, nine CD4+ helper T lymphocyte epitopes, and twelve linear B-cell lymphocyte epitopes that were predicted to be antigenic, non-allergenic, non-toxic, fully conserved, and non-human homologous. Subsequently, molecular docking study, protein-protein interaction analysis, molecular dynamics simulation (including the root mean square fluctuation (RMSF) and root mean square deviation (RMSD)), and immune simulation study rendered promising results assuring the vaccine to be stable, safe, and effective. Finally, in silico cloning was conducted to develop an efficient mass production strategy of the vaccine. However, further in vitro and in vivo research studies on the proposed vaccine are required to confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Review: Unravelling the Role of DNA Sensing in Alum Adjuvant Activity

Public interest in vaccines is at an all-time high following the SARS-CoV-2 global pandemic. Currently, over 6 billion doses of various vaccines are administered globally each year. Most of these vaccines contain Aluminium-based adjuvants (alum), which have been known and used for almost 100 years to enhance vaccine immunogenicity. However, despite the historical use and importance of alum, we still do not have a complete understanding of how alum works to drive vaccine immunogenicity. In this article, we critically review studies investigating the mechanisms of action of alum adjuvants, highlighting some of the misconceptions and controversies within the area. Although we have emerged with a clearer understanding of how this ubiquitous adjuvant works, we have also highlighted some of the outstanding questions in the field. While these may seem mainly of academic interest, developing a more complete understanding of these mechanisms has the potential to rationally modify and improve the immune response generated by alum-adjuvanted vaccines.

An Alignment-Independent Approach for the Study of Viral Sequence Diversity at Any Given Rank of Taxonomy Lineage

The study of viral diversity is imperative in understanding sequence change and its implications for intervention strategies. The widely used alignment-dependent approaches to study viral diversity are limited in their utility as sequence dissimilarity increases, particularly when expanded to the genus or higher ranks of viral species lineage. Herein, we present an alignment-independent algorithm, implemented as a tool, UNIQmin, to determine the effective viral sequence diversity at any rank of the viral taxonomy lineage. This is done by performing an exhaustive search to generate the minimal set of sequences for a given viral non-redundant sequence dataset. The minimal set is comprised of the smallest possible number of unique sequences required to capture the diversity inherent in the complete set of overlapping k-mers encoded by all the unique sequences in the given dataset. Such dataset compression is possible through the removal of unique sequences, whose entire repertoire of overlapping k-mers can be represented by other sequences, thus rendering them redundant to the collective pool of sequence diversity. A significant reduction, namely ~44%, ~45%, and ~53%, was observed for all reported unique sequences of species Dengue virus, genus Flavivirus, and family Flaviviridae, respectively, while still capturing the entire repertoire of nonamer (9-mer) viral peptidome diversity present in the initial input dataset. The algorithm is scalable for big data as it was applied to ~2.2 million non-redundant sequences of all reported viruses. UNIQmin is open source and publicly available on GitHub. The concept of a minimal set is generic and, thus, potentially applicable to other pathogenic microorganisms of non-viral origin, such as bacteria.

Structural and immunological characterization of an epitope within the PAN motif of ectodomain I in Babesia bovis apical membrane antigen 1 for vaccine development

Background

Bovine babesiosis caused by Babesia bovis (B. bovis) has had a significant effect on the mobility and mortality rates of the cattle industry worldwide. Live-attenuated vaccines are currently being used in many endemic countries, but their wide use has been limited for a number of reasons. Although recombinant vaccines have been proposed as an alternative to live vaccines, such vaccines are not commercially available to date. Apical membrane antigen-1 (AMA-1) is one of the leading candidates in the development of a vaccine against diseases caused by apicomplexan parasite species. In Plasmodium falciparum (P. falciparum) AMA-1 (PfAMA-1), several antibodies against epitopes in the plasminogen, apple, and nematode (PAN) motif of PfAMA-1 domain I significantly inhibited parasite growth. Therefore, the purpose of this study was to predict an epitope from the PAN motif of domain I in the B. bovis AMA-1 (BbAMA-1) using a combination of linear and conformational B-cell epitope prediction software. The selected epitope was then bioinformatically analyzed, synthesized as a peptide (sBbAMA-1), and then used to immunize a rabbit. Subsequently, in vitro growth- and the invasion-inhibitory effects of the rabbit antiserum were immunologically characterized.

Results

Our results demonstrated that the predicted BbAMA-1 epitope was located on the surface-exposed α-helix of the PAN motif in domain I at the apex area between residues 181 and 230 with six polymorphic sites. Subsequently, sBbAMA-1 elicited antibodies capable of recognizing the native BbAMA-1 in immunoassays. Furthermore, anti-serum against sBbAMA-1 was immunologically evaluated for its growth- and invasion-inhibitory effects on B. bovis merozoites in vitro. Our results demonstrated that the rabbit anti-sBbAMA-1 serum at a dilution of 1:5 significantly inhibited (p < 0.05) the growth of B. bovis merozoites by approximately 50–70% on days 3 and 4 of cultivation, along with the invasion of merozoites by approximately 60% within 4 h of incubation when compared to the control groups.

Conclusion

Our results indicate that the epitope predicted from the PAN motif of BbAMA-1 domain I is neutralization-sensitive and may serve as a target antigen for vaccine development against bovine babesiosis caused by B. bovis.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.