Bioinformatics analysis of rhinovirus capsid proteins VP1-4 sequences for cross-serotype vaccine development.

BACKGROUND: Rhinoviruses (RV) are associated with the development and exacerbations of asthma and chronic obstructive pulmonary disease. They've also been linked to more severe diseases like pneumonia, acute bronchiolitis, croup, and otitis media. Because of the hypervariable sequences in the same serotypes, no effective vaccine against rhinoviruses has been developed to date. With the availability of new full-length genome sequences for all RV-A and RV-B serotyped strains, this study used bioinformatics to find a suitable RV strain with the highest similarity matrices to the other strains. METHODS: The full genomic sequences of all known different RV-A and -B prototypes were downloaded from the National Centre for Biotechnology Information (NCBI) and divided into minor low-density lipoprotein receptor (LDLR) and major intercellular adhesion molecule groups (ICAM). The sequences were edited using Biological Sequence Alignment Editor, v 7.2.0 (BioEdit software) to study each capsid protein (VP1, VP2, VP3, and VP4) and analyzed using the EMBL-EBI ClustalW server and the more current Clustal Omega tool for the calculation of the identities and similarities. RESULTS: We analyzed and predicted immunogenic motifs from capsid proteins that are conserved across distinct RV serotypes using a bioinformatics technique. The amino acid sequences of VP3 were found to be the most varied, while VP4 was the most conserved protein among all RV-A and RV-B strains. Among all strains studied, RV-74 demonstrated the highest degree of homology to other strains and could be a potential genetic source for recombinant protein production. Nine highly conserved regions with a minimum length of 9-mers were identified, which could serve as potential immune targets against rhinoviruses. CONCLUSION: Therefore, bioinformatics analysis conducted in the current study has paved the way for the selection of immunogenic targets. Bioinformatically, the ideal strain's capsid protein is suggested to contain the most common RVs immunogenic sites.

A review of studies examining the association between genetic biomarkers (short tandem repeats and single-nucleotide polymorphisms) and risk of prostate cancer: the need for valid predictive biomarkers.

Prostate cancer (PCa) is a challenging polygenic disease because the genes that cause PCa remain largely elusive and are affected by several causal factors. Consequently, research continuously strives to identify a genetic marker which could be used as an indicator to predict the most vulnerable (i.e., predisposed) segments of the population to the disease or for the gene which may be directly responsible for PCa. To enhance the genetic etiology of PCa, this research sought to discover the key studies conducted in this field using data from the main journal publication search engines, as it was hoped that this could shed light on the main research findings from these studies, which in turn could assist in determining these genes or markers. From the research highlighted, the studies primarily used two kinds of markers: short tandem repeats or single-nucleotide polymorphisms. These markers were found to be quite prevalent in all the chromosomes within the research carried out. It also became apparent that the studies differed in both quantity and quality, as well as being conducted in a variety of societies. Links were also determined between the degree and strength of the relationship between these markers and the occurrence of the disease. From the studies identified, most recommended a larger and more diverse survey for the parameters which had not been studied before, as well as an increase in the size of the community (i.e., the population) being studied. This is an indication that work in this field is far from complete, and thus, current research remains committed toward finding genetic markers that can be used clinically for the diagnosis and screening of patients with PCa.