Catalase epitopes vaccine design for Helicobacter pylori: A bioinformatics approach

Bioinformatics tools are helpful for epitopes prediction directly from the genomes of pathogens in order to design a vaccine. Epitopes are sub-sequences of proteins (8 to 10 mer peptides) which bind to MHC to interact with the T cell receptors and stimulate immune responses. Finding a suitable vaccine against Helicobacter pylori is necessary, because of high prevalence of the infection (25 to 90%). Moreover, this bacteria has been classified as a grade I carcinogen by WHO since 1994. Catalase, an important enzyme in the virulence of H. pylori, could be a suitable candidate for vaccine design because it is highly conserved, which is important for the survival of H. pylori; it is expressed in high level and it is exposed on the surface of the bacteria. In this study, we designed epitope-based vaccine for catalase specific regions of H. pylori by means of immunobioinformatic tools. H. pylori (26695) catalase has been compared with human catalase in order to select specific regions. Afterwards, epitopes of catalase were determined by propred software. Among predicted epitopes, three epitopes were selected including, MVNKDVKQTT, VLLQSTWFL and FHPFDVTKI. Three candidates out of 51catalase antigen epitopes had the highest score for reactivating with MHC II MHC in propred software. The candidate epitopes for vaccine design should be rather a composition of considering epitopes: MVNKDVKQTTKKVLLQSTWFLKKFHPFDVTKI. In this manner, 39 of 51 alleles of MHC class ІІ were involved and stimulated T-cell responses. We believe prediction of catalase epitopes by the immunoinformatics tools would be valuable for developing new immuoprophylatic strategy against H. pylori infection.Key words: Helicobacter pylori, catalase, epitopes

Water-induced modulation of Helicobacter pylori virulence properties

While the influence of water in Helicobacter pylori culturability and membrane integrity has been extensively studied, there are little data concerning the effect of this environment on virulence properties. Therefore, we studied the culturability of water-exposed H. pylori and determined whether there was any relation with the bacterium’s ability to adhere, produce functional components of pathogenicity and induce inflammation and alterations in apoptosis in an experimental model of human gastric epithelial cells. H. pylori partially retained the ability to adhere to epithelial cells even after complete loss of culturability. However, the microorganism is no longer effective in eliciting in vitro host cell inflammation and apoptosis, possibly due to the non-functionality of the cag type IV secretion system. These H. pylori-induced host cell responses, which are lost along with culturability, are known to increase epithelial cell turnover and, consequently, could have a deleterious effect on the initial H. pylori colonisation process. The fact that adhesion is maintained by H. pylori to the detriment of other factors involved in later infection stages appears to point to a modulation of the physiology of the pathogen after water exposure and might provide the microorganism with the necessary means to, at least transiently, colonise the human stomach.FCT (SFRH/BD/24579/2005) (to NMG

The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.Project GATOP - Genetic Algorithms for Team Orienteering Problem (Ref PTDC/EME-GIN/120761/2010), financed by national funds by FCT / MCTES, and co-funded by the European Social Development Fund (FEDER) through the COMPETE - Programa Operacional Fatores de Competitividade (POFC) Ref FCOMP-01-0124-FEDER-020609. This work has been par tially supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/201