Effects of transmission-blocking vaccines simultaneously targeting pre- and post-fertilization antigens in the rodent malaria parasite Plasmodium yoelii

Transmission-Blocking Strategies Against Malaria Parasites During Their Mosquito Stages

Malaria is still the most widespread parasitic disease and causes the most infections globally. Owing to improvements in sanitary conditions and various intervention measures, including the use of antimalarial drugs, the malaria epidemic in many regions of the world has improved significantly in the past 10 years. However, people living in certain underdeveloped areas are still under threat. Even in some well-controlled areas, the decline in malaria infection rates has stagnated or the rates have rebounded because of the emergence and spread of drug-resistant malaria parasites. Thus, new malaria control methods must be developed. As the spread of the Plasmodium parasite is dependent on the part of its life cycle that occurs in mosquitoes, to eliminate the possibility of malaria infections, transmission-blocking strategies against the mosquito stage should be the first choice. In fact, after the gametocyte enters the mosquito body, it undergoes a series of transformation processes over a short period, thus providing numerous potential blocking targets. Many research groups have carried out studies based on targeting the blocking of transmission during the mosquito phase and have achieved excellent results. Meanwhile, the direct killing of mosquitoes could also significantly reduce the probability of malaria infections. Microorganisms that display complex interactions with Plasmodium, such as Wolbachia and gut flora, have shown observable transmission-blocking potential. These could be used as a biological control strategy and play an important part in blocking the transmission of malaria.

A comprehensive analysis of amino-peptidase N1 protein (APN) from Anopheles culicifacies for epitope design using Immuno-informatics models

Analysis of the Amino-peptidase N (APN) protein from Anopheles culicifacies as a vector based Transmission Blocking Vaccines (TBV) target has been considered for malaria vaccine development. Short peptides as potential epitopes for B cells and cytotoxic T cells and/or helper T cells were identified using prediction models provided by NetCTL and IEDB servers. Antigenicity determination, allergenicity, immunogenicity, epitope conservancy analysis, atomic interaction with HLA allele specific structure models and population coverage were investigated in this study. The analysis of the target protein helped to identify conserved regions as potential epitopes of APN in various Anopheles species. The T cell epitopes like peptides were further analyzed by using molecular docking to check interactions against the allele specific HLA models. Thus, we report the predicted B cell (VDERYRL) and T cell (RRYLATTQF for HLA class I and LKATFTVSI for HLA class II) epitopes like peptides from APN protein of Anopheles culicifacies (Diptera: Culicidae) for further consideration as vaccine candidates subsequent to in vitro and in vivo analysis.

A probabilistic model of pre-erythrocytic malaria vaccine combination in mice

Malaria remains one the world’s most deadly infectious diseases, with almost half a million deaths and over 150 million clinical cases each year. An effective vaccine would contribute enormously to malaria control and will almost certainly be required for eventual eradication of the disease. However, the leading malaria vaccine candidate, RTS,S, shows only 30–50% efficacy under field conditions, making it less cost-effective than long-lasting insecticide treated bed nets. Other subunit malaria vaccine candidates, including TRAP-based vaccines, show no better protective efficacy. This has led to increased interest in combining subunit malaria vaccines as a means of enhancing protective efficacy. Mathematical models of the effect of combining such vaccines on protective efficacy can help inform optimal vaccine strategies and decision-making at all stages of the clinical process. So far, however, no such model has been developed for pre-clinical murine studies, the stage at which all candidate antigens and combinations begin evaluation. To address this gap, this paper develops a mathematical model of vaccine combination adapted to murine malaria studies. The model is based on simple probabilistic assumptions which put the model on a firmer theoretical footing than previous clinical models, which rather than deriving a relationship between immune responses and protective efficacy posit the relationship to be either exponential or Hill curves. Data from pre-clinical murine malaria studies are used to derive values for unknowns in the model which in turn allows simulations of vaccine combination efficacy and suggests optimal strategies to pursue. Finally, the ability of the model to shed light on fundamental biological variables of murine malaria such as the blood stage growth rate and sporozoite infectivity is explored.