A Rapid Method for Refolding Cell Surface Receptors and Ligands

A multi-epitope chimeric protein elicited a strong antibody response and partial protection against Edwardsiella ictaluri in Nile tilapia

Edwardsiella ictaluri infects several fish species and protection of the all the susceptible fish hosts from the pathogen using a monovalent vaccine is impossible because the species is composed of host-based genotypes that are genetic, serological and antigenic heterogenous. Here, immunoinformatic approach was employed to design a cross-immunogenic chimeric EiCh protein containing multi-epitopes. The chimeric EiCh protein is composed of 11 B-cell epitopes and 7 major histocompatibility complex class II epitopes identified from E. ictaluri immunogenic proteins previously reported. The 49.32 kDa recombinant EiCh protein was expressed in vitro in Escherichia coli BL-21 (DE3) after which inclusion bodies were successfully solubilized and refolded. Ab initio protein modelling revealed secondary and tertiary structures. Secondary structure was confirmed by circular dichroism spectroscopy. Antigenicity of the chimeric EiCh protein was exhibited by strong reactivity with serum from striped catfish and Nile tilapia experimentally infected with E. ictaluri. Furthermore, immunogenicity of the chimeric EiCh protein was investigated in vivo in Nile tilapia juveniles and it was found that the protein could strongly induce production of specific antibodies conferring agglutination activity and partially protected Nile tilapia juveniles with a relative survival percentage (RPS) of 42%. This study explored immunoinformatics as reverse vaccinology approach in vaccine design for aquaculture to manage E. ictaluri infections.

An Engineered Multimodular Enzybiotic against Methicillin-Resistant Staphylococcus aureus

Development of multidrug antibiotic resistance in bacteria is a predicament encountered worldwide. Researchers are in a constant hunt to develop effective antimicrobial agents to counter these dreadful pathogenic bacteria. Here we describe a chimerically engineered multimodular enzybiotic to treat a clinical isolate of methicillin-resistant Staphylococcus aureus (S. aureus). The cell wall binding domain of phage ϕ11 endolysin was replaced with a truncated and more potent cell wall binding domain from a completely unrelated protein from a different phage. The engineered enzybiotic showed strong activity against clinically relevant methicillin-resistant Staphylococcus aureus. In spite of a multimodular peptidoglycan cleaving catalytic domain, the engineered enzybiotic could not exhibit its activity against a veterinary isolate of S. aureus. Our studies point out that novel antimicrobial proteins can be genetically engineered. Moreover, the cell wall binding domain of the engineered protein is indispensable for a strong binding and stability of the proteins.

Computational predictive approaches for interaction and structure of aptamers

Aptamers are short single-strand sequences that can bind to their specific targets with high affinity and specificity. Usually, aptamers are selected experimentally via systematic evolution of ligands by exponential enrichment (SELEX), an evolutionary process that consists of multiple cycles of selection and amplification. The SELEX process is expensive, time-consuming, and its success rates are relatively low. To overcome these difficulties, in recent years, several computational techniques have been developed in aptamer sciences that bring together different disciplines and branches of technologies. In this paper, a complementary review on computational predictive approaches of the aptamer has been organized. Generally, the computational prediction approaches of aptamer have been proposed to carry out in two main categories: interaction-based prediction and structure-based predictions. Furthermore, the available software packages and toolkits in this scope were reviewed. The aim of describing computational methods and tools in aptamer science is that aptamer scientists might take advantage of these computational techniques to develop more accurate and more sensitive aptamers.