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Leishmaniases are neglected diseases caused by infection with Leishmania parasites and there are currently no prophylactic vaccines. In this study, we designed in silico a synthetic recombinant vaccine against visceral leishmaniasis (VL) called ChimeraT, which contains specific T-cell epitopes from Leishmania Prohibitin, Eukaryotic Initiation Factor 5a and the hypothetical LiHyp1 and LiHyp2 proteins. Subcutaneous delivery of ChimeraT plus saponin stimulated a Th1 cell-mediated immune response and protected mice against L. infantum infection, significantly reducing the parasite load in distinct organs. ChimeraT/saponin vaccine stimulated significantly higher levels of IFN-γ, IL-12, and GM-CSF cytokines by both murine CD4 + and CD8 + T cells, with correspondingly low levels of IL-4 and IL-10. Induced antibodies were predominantly IgG2a isotype and homologous antigen-stimulated spleen cells produced significant nitrite as a proxy for nitric oxide. ChimeraT also induced lymphoproliferative responses in peripheral blood mononuclear cells from VL patients after treatment and healthy subjects, as well as higher IFN-γ and lower IL-10 secretion into cell supernatants. Thus, ChimeraT associated with a Th1 adjuvant could be considered as a potential vaccine candidate to protect against human disease.

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Background: Leishmaniases are neglected diseases caused by infection with Leishmania parasites and there are no human vaccines in use routinely. The purpose of this study was to examine the immunogenicity of ChimeraT, a novel synthetic recombinant vaccine against visceral leishmaniasis (VL), incorporated into a human-compatible liposome formulation. Methods: BALB/c mice were immunized subcutaneously with ChimeraT/liposome vaccine, ChimeraT/saponin adjuvant, or ChimeraT/saline and immune responses examined in vitro and in vivo. Results: Immunization with the ChimeraT/liposome formulation induced a polarized Th1-type response and significant protection against L. infantum infection. ChimeraT/liposome vaccine stimulated significantly high levels of interferon (IFN)-γ, interleukin (IL)-12, and granulocyte macrophage-colony stimulating factor (GM-CSF) cytokines by both CD4 and CD8 T-cells, with correspondingly lower levels of IL-4 and IL-10 cytokines. Induced antibodies were predominantly IgG2a isotype, and homologous antigen-stimulated spleen cells produced significant nitrite as a proxy for nitric oxide (NO). Furthermore, we examined a small number of treated VL patients and found higher levels of circulating anti-ChimeraT protein IgG2 antibodies, compared to IgG1 levels. Conclusions: Overall, the liposomal formulation of ChimeraT induced a protective Th1-type immune response and thus could be considered in future studies as a vaccine candidate against human VL.

Epitope identification is essential for developing effective antibodies that can detect and neutralize bioactive proteins. Computational prediction is a valuable and time-saving alternative for experimental identification. Current computational methods for epitope prediction are underused and undervalued due to their high false positive rate. In this work, we targeted common properties of linear B-cell epitopes identified in an individual protein class (metalloendopeptidases) and introduced an alternative method to reduce the false positive rate and increase accuracy, proposing to restrict predictive models to a single specific protein class. For this purpose, curated epitope sequences from metalloendopeptidases were transformed into frame-shifted Kmers (3 to 15 amino acid residues long). These Kmers were decomposed into a matrix of biochemical attributes and used to train a decision tree classifier. The resulting prediction model showed a lower false positive rate and greater area under the curve when compared to state-of-the-art methods. Our predictions were used for synthesizing peptides mimicking the predicted epitopes for immunization of mice. A predicted linear epitope that was previously undetected by an experimental immunoassay was able to induce neutralizing-antibody production in mice. Therefore, we present an improved prediction alternative and show that computationally identified epitopes can go undetected during experimental mapping.

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